A111D3 D7DbDb

NAFL INST OF STANDARDS & TECH R.I.C.

A1 11 03070606

Sympos/Ultrasonic tissue c QC100 .U57 N0.525, 1979 C.2 NBS-PUB-C 19

CO Q NBS SPECIAL PUBLICATION 525

U.S. DEPARTMENT OF COMMERCE/National Bureau of Standards

National Bureau of Standards

Library, E-01 Admin. B!dg.

OCT 1 1981

ISICGS

Ultrasonic

Tissue Characterization II
NATIONAL BUREAU OF STANDARDS

The National Bureau of Standards' was established by an act of Congress March 3, 1901. The

Bureau's overall goal is to strengthen and advance the Nation's science and technology and

facilitate their effective application for public benefit. To this end, the Bureau conducts

research and provides: (1) a basis for the Nation's physical measurement system, (2) scientific and technological services for industry and government, (3) a technical basis for equity in trade, and (4) technical services to promote public safety. The Bureau's technical work is performed by the National Measurement Laboratory, the National Engineering Laboratory,

and the Institute for Computer Sciences and Technology.

THE NATIONAL MEASURE\iENT LABORATORY provides the national system of

physical and chemical and materials measurement; cooidinates the system with measurement

systems of other nations and furnishes essential services leading to accurate and uniform

physical and chemical measurement throughout the Nation's scientific community, industry,

and commerce; conducts materials research leading to improved methods of measurement,

standards, and data on the properties of materials needed by industry, commerce, educational

institutions, and Government; provides advisory and research services to other Government

Agencies; develops, produces, and distributes Standard Reference Materials; and provides

calibration services. The Laboratory consists of the following centers:

Absolute Physical Quantities^ — Radiation Research — Thermodynamics and

Molecular Science — Analytical Chemistry — Materials Science. THE NATIONAL ENGINEERING LABORATORY provides technology and technical

services to users in the public and private sectors to address national needs and to solve national problems in the public interest; conducts research in engineering and applied science

in support of objectives in these efforts; builds and maintains competence in the necessary

disciplines required to carry out this research and technical service; develops engineering data and measurement capabilities; provides engineering measurement traceability services; develops test methods and proposes engineering standards and code changes; develops and

proposes new engineering practices; and develops and improves mechanisms to transfer

results of its research to the utlimate user. The Laboratory consists of the following centers:

Applied Mathematics — Electronics and Electrical Engineering^ — Mechanical

Engineering and Process Technology' — Building Technology — Fire Research —

Consumer Product Technology — Field Methods.

THE INSTITUTE FOR COMPUTER SCIENCES AND TECHNOLOGY conducts

research and provides scientific and technical services to aid Federal Agencies in the selection, acquisition, application, and use of computer technology to improve effectiveness and

economy in Government operations in accordance with Public Law 89-306 (40 U.S.C. 759), relevant Executive Orders, and other directives; carries out this mission by managing the Federal Information Processing Standards Program, developing Federal ADP standards

guidelines, and managing Federal participation in ADP voluntary standardization activities; provides scientific and technological advisory services and assistance to Federal Agencies; and

provides the technical foundation for computer-related policies of the Federal Government.

The Institute consists of the following divisions:

Systems and Software — Computer Systems Engineering — Information Technology.

'Headquarters and Laboratories at Gaithersburg, Maryland, unless otherwise noted; mailing address Washington, D.C. 20234. ^Some divisions within the center are located at Boulder, Colorado, 80303.

The National Bureau of Standards was ceorganized, effective Aprii 9, 1978.
Ultrasonic Tissue Characterization li

1 - . A collection of reviewed papers based on talks presented at the *Q O OC)

Second International Symposium on Ultrasonic Tissue Characterization -

^ held at the National Bureau of Standards, Gaithersburg, Maryland U - 1 June 13-15, 1977

^ ^

Edited by , .

Melvin Linzer

National Measurement Laboratory

National Bureau of Standards

Washington, DC 20234

Cosponsors of Symposium on Ultrasonic Tissue Characterization:

National Bureau of Standards

(National Measurement Laboratory)

National Science Foundation

(Research Applied to National Needs, RANN)

National Institutes of Health

(Diagnostic Radiology Department, Clinical Center)

U.S. DEPARTMENT OF COMMERCE, Juanita M. Kreos, Secretary

Jordan J. Baruch, Assistant Secretary for Science and Teclinology

NATIONAL BUREAU OF STANDARDS, Ernest Ambler, Director

Issued April 1 979
Library of Congress Catalog Card Number: 79-600026

National Bureau of Standards Special Publication 525

Nat. Bur, Stand. (U.S.), Spec. Publ. 525, 339 pages (Apr. 1979) CODEN: XNBSAV

U.S. GOVERNMENT PRINTING OFFICE

WASHINGTON: 1979

For sale by the Superintendent of Documents, U.S. Government Printing Office, Washington, D.C. 20402 Stock No. 003-003-02058-3 Price $5.50

(Add 25 percent additional for other than U.S. mailing)


FOREWORD

The Second International Symposium on Ultrasonic Tissue Characterization

set the stage for establishing this series of meetings as the world's leading

forums for the dissemination of the most recent and advanced research in the field. Undoubtedly, the Symposium contributed significantly to the contemporary

improvement in medical diagnosis. This improvement has resulted from the application to instrumentation design of the results of measurements of the interactions of ultrasound with tissue and from the deeper understanding of the physical principles underlying these interactions.

The interdicipl inary approach of engineers, physical scientists, physicians,

and mathematicians made the Symposium a unique and fertile occasion. This

collection of reviewed papers which describes the research results presented at the meeting makes it possible for the benefits of this work to be shared by the whole community of those dedicated to the advancement of biomedical ultrasonics

and its application to health care.

The National Bureau of Standards is pleased to be responsible for this

publication and to have joined the National Science Foundation and the National

Institutes of Health as cosponsors of the Symposium.

John D. Hoffman

Director

National Measurement Laboratory

National Bureau of Standards

V
PREFACE

This volume forms a comparison with Ultrasonic Tissue Characterization , NBS Special

Publication 453 (1976). It contains extended versions of 43 of the 54 papers presented at the Second International Symposium on Ultrasonic Tissue Characterization which was held at the National Bureau of Standards on June 13-15, 1977. In a departure from the normal practice for conference proceedings, these papers were critically reviewed by experts in the field.

In the pages preceding the scientific papers, an overview of the. meeting is presented.

The first article in this chapter is a resume of the proceedings of the entire Symposium and

it serves to put the presentations and discussions into perspective. This is folowed by a report summarizing the Panel Discussion on Breast Cancer, which was one of the highlights of the meeting, and finally, by the introductory talk given by Dr. A. J. Eggers, Jr., who at the time of the meeting was Assistant Director for Research Application, National Science

Foundation. The scientific papers presented at the meeting are grouped into chapters

devoted to: attenuation and velocity I: mechanisms; attenuation and velocity II: methodology and measurements; scattering and attenuation; scattering; tumor Doppler signatures;

propagation through bone and skull; image reconstruction; signal processing and pattern

recognition; and tissue viability and tissue phantoms. A survey of velocity and attenuation

data in mammalian tissue is included in an appendix.

The success of the Symposium was due to the dedicated efforts of many individuals.

Acknowledgment is given to the members of the Program committee (F. Dunn, A. C. Kak,

J. F. Greenleaf, J. G. Miller, R. C. Waag and P. N. T. Wells) and to the other individuals

who served as reviewers for this volume. Special appreciation is due to Peter Wells for

his contributions as cochai rperson of the Panel Discussion on Breast Cancer and for his valuable collaboration in preparing the summaries of the Symposium and of the Panel Discussion. The efforts of Ronald B. Johnson and Sara Torrence and their conference staffs

in the organization and management of the Symposium are gratefully acknowledged. Special thanks is given to Rosemary S. Maddock who has provided the coordination and the editorial

assistance in the many phases of the preparation of this volume.

Melvin Linzer

Editor and Symposium Chairperson

vi
ABSTRACT

The Second International Symposium on Ultrasonic Imaging and Tissue Characterization was held at the National Bureau of Standards on June 13-15, 1977. The meeting was cosponsored by the National Bureau of Standards, the National Science

Foundation, and the National Institutes of Health. This volume contains extended

and reviewed papers based on 43 of the 54 talks presented at the Symposium. Topics

covered include techniques for measurement of ultrasonic tissue parameters, the dependence of tissue properties on physical and biological variables (e.g., ultra- sonic frequency, temperature), mechanisms of ultrasonic tissue interactions, propa- gation through bone and skull, tumor Doppler signatures, computerized tomography,

signal processing and pattern recognition, and tissue phantoms. A survey of velocity

and attenuation data in mammalian tissue is included in an appendix.

Key words: Absorption; attenuation; computerized tomography; Doppler;

impedance; medical diagnosis; microscopy; pattern recognition;

scattering; signal processing; tissue characterization; tissue

parameters; ultrasound; velocity.

In order to describe experiments adequately, it has been necessary to identify commercial

materials and equipment in this book. In no case does such identification imply recommendation

or endorsement by the National Bureau of Standards, nor does it imply that the material or equipment is necessarily the best available for the purpose.

vi i
/J
CONTENTS

Page

Chapter 1. OVERVIEW

Report on the Symposium 3

Report on Panel Discussion: Ultrasonic Diagnosis of Breast Cancer 11

Introductory Address 15

Chapter 2. ATTENUATION AND VELOCITY I: MECHANISMS

Elements of Tissue Characterization. Part I. Ultrasonic Propagation J

Properties 19 Johnston, R. L., Goss, S. A., Maynard, V., Brady, J. K.

Frizzell, L. A., O'Brien, W. D., Jr., and Dunn, F.

Absorption of Sound in Tissues ^

. . 29 Carstensen, E. L.

Mechanisms of Ultrasonic Attenuation in Soft Tissue 37 O'Donnell , M. and Miller, J. G.

Chapter 3. ATTENUATION AND VELOCITY II: METHODOLOGY AND MEASUREMENTS

Elements of Tissue Characterization. Part II. Ultrasonic Propagation Parameter Measurements 43 Goss, S. A., Johnston, R. L., Maynard, V., Nider, L., Frizzell, L. A., O'Brien, W. D., Jr., and Dunn, F.

A Device for Measuring Ultrasonic Propagation Velocity in Tissue . . . . . 53 Sollish, B. D.

Measurement of the Temperature Dependence of the Velocity of Ultra- \y sound in Soft Tissues 57 Bowen , T., Connor, W. G., Nasoni , R. L., Pifer, A. E., and Sholes, R. R.

Ultrasonic Attenuation in Normal and Ischemic Myocardium 63 O'Donnell, M., Mimbs, J. W., Sobel, B. E., and Miller, J. G.

Acoustic Microscopic Analysis of Myocardium 73 Yuhas, D. E. and Kessler, L. W.

Acoustic Properties of Normal and Abnormal Human Brain 81 Kremkau, F. W., McGraw, C. P., and Barnes, R. W.

Frequency Dependent Attenuation of Malignant Breast Tumors Studied

by the Fast Fourier Transform Technique 85 Fry, E. K., Sanghvi , N. T., Fry, F. J., and Gallager, H. S.

Correlation of Ultrasonic Attenuation with Connective Tissue Content

in Breast Cancers 93 Kobayashi , T.

The Attenuation of Selected Soft Tissue as a Function of Frequency 101 Le Croissette, D. H., Heyser, R. C, Gammell, P. M., Roseboro, J. A., and Wilson, R. L.

Chapter 4. SCATTERING AND ATTENUATION

Clinical Spectrum Analysis Techniques for Tissue Characterization Ill Lizzi, F. L. and Elbaum, M. E.

ix
Tissue Characterization In Vivo by Differential Attenuation

Measurements 121 L^vi, S. and Keuwez, J.

Statistical Estimation of the Acoustic Attenuation Coefficient

Slope for Liver Tissue from Reflected Ultrasonic Signals 125 Kuc, R., Schwartz, M., Finby, N., and Dain, F.

Chapter 5. SCATTERING

An Ultrasonic Tissue Signature for the Lung Surface 135 Rhyne, T. L.

Angle Scan and Frequency-Swept Ultrasonic Scattering Characterization of Tissue 143 Waag, R. C, Lee, P. P. K., Lerner, R. M., Hunter, L. P., Gramiak, R., and Schenk, E. A.

Quantitative Measurements of Scattering of Ultrasound by Heart

and Liver 153 Reid, J. M. and Shung, K. K.

Dependence of Ultrasound Backscatter from Human Liver Tissue on Frequency and Protein/Lipid Composition 157 Freese, M. and Lyons, E. A.

Ultrasound Backscattering from Blood: Hematocrit and Erythrocyte

Aggregation Dependence 165 Hanss, M. and Boynard, M.

Chapter 6. TUMOR DOPPLER SIGNATURES

Tumour Detection by Ultrasonic Doppler Blood-Flow Signals 173 Wells, P. N. T., Halliwell, M., Mountford, R. A., Skidmore, R., Webb, A. J'., and Woodcock, J. P.

Chapter 7. PROPAGATION THROUGH BONE AND SKULL

A Theory Relating Sonic Velocity to Mineral Content in Bone 179 Lees, S. and Davidson, C. L.

Ultrasonic Properties and Microtexture of Human Cortical Bone 189 Yoon, H. S. , and Katz, J. L.

Attenuation and Dispersion of Ultrasound in Cancellous Bone 197 Barger, J. E.

Transkull Transmission of Axisymmetric Focused Ultrasonic Beams

in the 0.5 to 1 MHz Frequency Range: Implications for Brain Tissue

Visualization, Interrogation, and Therapy 203

Fry, F. J.

Some Advances in Acoustic Imaging Through Skull 209 Smith, S. W., Phillips, D. J., von Ramm, 0. T. , and Thurstone, F. L.

Chapter 8. IMAGE RECONSTRUCTION

Characterization of In Vivo Breast Tissue by Ultrasonic

Time-of-Fl ight Computed Tomography 221 Glover, G. H.

Variation of Acoustic Speed with Temperature in Various Excised Human Tissues Studied by Ultrasound Computerized Tomography 227 Rajagopalan, B., Greenleaf, J. F., Thomas, P. J., Johnson, S. A., and Bahn, R. C.

X
High Spatial Resolution Ultrasonic Measurement Techniques for Characterization of Static and Moving Tissues 235 Johnson, S. A., Greenleaf, J. F., Rajagopalan, B., Bahn, R. C,

Baxter, B. and Christensen, D.

Mapping True Ultrasonic Backscatter and Attenuation Distribution

in Tissue - A Digital Reconstruction Approach 247 Duck, F. A. and Hill, C. R.

Chapter 9. SIGNAL PROCESSING AND PATTERN RECOGNITION

A Comprehensive Ultrasonic Tissue Analysis System 255 Linzer, M., Parks, S. I., Norton, S. J., Higgins, F. P., Dietz, D. R., Shideler, R. W., Shawker, T. H., and Doppman, J. L.

Theoretical Analysis of Instantaneous Power Spectra as Applied

to Spectra-Color Ultrasonography 261 Jennings, W. D., Holasek, E., and Purnell, E. W.

Identification of Tissue Parameters by Digital Processing of Real-Time Ultrasonic Clinical Cardiac Data 267 Joynt, L., Boyle, D., Rakowski, H., Popp, R., and Beaver, W.

Dynamic Autocorrelation Analysis of A-Scans Iji Vivo 275 Gore, J. C, Leeman, S., Metreweli, C, Plessner, N. J., and Willson, K.

Computer Spectral Analysis of Ultrasonic A Mode Echoes 281 Robinson, D. E.

Cepstral Signal Processing for Tissue Signature Analysis 287 Fraser, J., Kino, G. S., and Birnholz, J.

Recognition of Patterns in Ultrasonic Sectional Pictures of the Prostate for Tumor Diagnosis 297

von Seelen, W., Gaca, A., Lock, E., Scheiding, W., and Wessels, G.

Recent Developments in Obtaining Histopathological Information from Ultrasound Tissue Signatures 303 Preston, K., Jr., Czerwinski, M. J., Skolnik, M. L., and

Leb, D. E.

Chapter 10. TISSUE VIABILITY AND TISSUE PHANTOMS

Damage and Death in Tissues and Associated Changes in Their

Mechanical Properties 317 Weiss, L.

A Human Abdominal Tissue Phantom 323 Edmonds, P. D., Reyes, Z., Parkinson, D. B., Filly, R. A.,

and Busey, H.

Tissue Simulators for Diagnostic Ultrasound 327 Eggleton, R. C. and Whitcomb, J. A.

Tissue Equivalent Test Objects for Comparison of Ultrasound

Transmission Tomography by Reconstruction with Pulse Echo Ultrasound Imaging 337 Carson, P. L., Shabason, L., Dick, D. E., and dayman, W.

Appendi X

Data of the Velocity and Attenuation of Ultrasound in Mammal ian Ti ssues - A Survey 343 Parry, R. J. and Chivers, R. C.

xi
I
Chapter 1

OVERVIEW

1

REPORT ON THE SYMPOSIUM

The Second International Symposium on Ultra-

', onic Tissue Characterization had six principal

objectives

•to review the progress which had been made

J in the past two years since the first

'

. Symposium

• to provide a forum for the exchange of ideas

among researchers, manufacturers, and

cl inicians

•to identify clinical problems which might be solved by ultrasonic tissue characterization

I •to identify research opportunities

j •to promote the transfer of new technological

' advances in medical ultrasound to commercial

appl ication

' •to explore the potential for using ultrasonic

tissue characterization as a mass screening

! technique for breast cancer.

The Symposium, which extended over three days,

fas cosponsored by the National Bureau of Stanllards (NBS), the National Science Foundation (NSF),

'.nd the National Institutes of Health (NIH). The introductory Session opened with a welcoming

iddress by Dr. E. Ambler, Director of NBS. He

'!poke of the rapid growth in the application of

jiltrasonic diagnosis. The U.S. market was estimated to be $64M in 1977, increasing at 31 percent

i^er year. Ultrasonic diagnosis was apparently

;afe. Quantitative methods were being developed,

Accelerated by the work of the Tissue Signature

'roject supported by NSF. One of the most exciting

liossibilities was that ultrasound might be useful

iin mass screening for breast cancer. The interest

ijind involvement of NBS in these medical applica-

'|;ions was increasing. Dr. A. J. Eggers, Jr.,

'Assistant Director for Research Applications, NSF,

Emphasized the importance of interagency collaboraipion. He pointed out the dramatic decline in the

jcost of microelectronic systems; forecasts indicajced that tasks requiring microelectronics presently

:bosting $1M would cost ( 1 977 money) $100K in five

j/ears, and only $10K in ten years. He predicted

jthe imminent end of the "visible" computer age,

'jinticipating the development of displays with

J'ntegrated microelectronics for operator interaction. He referred to the 1973 findings of the kudy group sponsored by NSF, and to the resulting

initiation of Experiment No. 5, which was designed

io test the acceleration of technology transfer to industry through the vehicle of diagnostic ultra50und. This had been followed by the preparation

py the Alliance for Engineering in Medicine and

Siology (AEMB), with NSF support, of a five-

/ear research and development agendum; 23 research

categories had been identified. Finally, in addition to many project grants, NSF was supporting

the Tissue Signature Project of the Carnegie-Mellon

Institute of Research. Dr. Eggers was followed by

Dr. M. B. Lipsett, Director, Clinical Center, NIH.

Dr. Lipsett outlined the NIH program of support for diagnostic ultrasonic research, presently running

at about $5M per year. The National Cancer Insti- tute (NCI) was funding projects concerned with

breast pathology imaging and with endoscopy. The National Heart and Lung Institute (NHLI) was involved with real-time imaging and with Doppler

studies of blood flow. The National Institute of General Medical Sciences (NI6MS) was supporting

research in imaging systems and the biological effects of ultrasound. The Clinical Center was developing a real-time scanner, and was collaborating with NBS in the construction of a comprehensive

tissue analysis system. Dr. Lipsett stated that

NBS expected to continue to be concerned with the advancing horizon of ultrasonic diagnostics.

The Symposium Chairperson, Dr. M. Linzer (NBS,

Gai thersburg , Maryland) discussed the present

knowledge of the ultrasonic properties of tissues.

He reviewed the advantages of ultrasonic diagnosis,

particularly in comparison with x-ray imaging. He demonstrated these by state-of-the-art illustrations of ultrasonic data obtained in several leading

laboratories -- Ultrasonics Institute, Sydney,

Australia, Duke University, Durham, North Carolina,

and Horizons Research Laboratories, Fort Lauderdale,

Florida. Comparably impressive results were beginning to be obtainable with commercial instruments.

Dr. Linzer went on to discuss basic data necessary

for further development of ultrasonic diagnostics

and he spoke of new methods of display. He then recalled the First International Symposium on Ultrasonic Tissue Characterization which had been held two years previously at NBS in Gai thersburg

That meeting had been attended by more than 200 people and the proceedings were recorded in NBS Special Publication 453. As a result of the meeting, NSF had supported the Ultrasonic Tissue

Signature Working Group and the Advisory Council

of Users. Data on tissue parameters were being

updated, and libraries of algorithms and scans were to be collected. In the present Symposium,

there were to be more than 50 papers, both from within the United States and by 15 speakers from

nine countries outside the United States. It was evident that measurements were more difficult to make in the clinic than in the laboratory. Dr. Linzer outlined the conference program which was designed to focus sharply on measurement of tissue

characteristics. He emphasized that other considerations were also vital for clinical success, and that consequently the program for the Third Symposium, which would be held in June 1978, would have

an expanded scope and would include imaging and Doppler techniques.

The first scientific session. Velocity and Attenuation I: Mechanisms , began with R. L. Johnston,

S. A. Goss, V. Maynard, J. K. Brady, L. A. Frizzell,

W. D. O'Brien, Jr., and F. Dunn (University of Illinois, Urbana, Illinois) reviewing ultrasonic

3
propagation properties. Different materials were considered in order of increasing complexity. In water, attenuation was proportional to the square

of the frequency, although the absolute value of attenuation was rather greater than that which

would be expected to be due to viscosity. Solutions of amino acids had similar properties to those of water; while those of polypeptides

exhibited greater absorption probably due to such interactions as helix-coil rearrangements and proton transfers. Proteins were made up of large

molecules, with relaxational absorption. Tissues

had characteristic attenuation dependency on temperature and frequency. In general, both increasing attenuation and velocity seemed to be associated with decreasing water content and with increasing protein and collagen content. Bone

and lung exhibited more complicated relationships.

For non-gas-containing soft tissues, however,

tissues with similar physiological functions had similar attenuation, and this property might be used to characterize tissues. In discussion, the authors stated that the strong frequency dependence

of velocity in lung might be due to changing ultrasonic pathways, and they agreed that the role of collagen deserved further study. E. A. Carstensen

(University of Rochester, Rochester, New York) then reviewed the absorption of ultrasound in tissue.

He considered first the relatively small contribution to total absorption due to the cellular structural components of tissue. The linear frequency

dependence of absorption suggested a spectrum of relaxation processes. The temperature coefficient

of attenuation had been measured for few tissues,

and data on dispersion were sparse. Experimental

results, however, were consistent with the theory.

Mechanisms of ultrasonic attenuation in soft tissue were further discussed by M. O'Donnell and J. G. Miller (Washington University, St. Louis, Missouri).

They presented a theoretical analysis of losses due

to cellular motion, and showed that in the limit for small scatterers there was a linear frequency

dependence of attenuation. They concluded that

losses due to microscopic inhomogeneities accounted

for a substantial fraction of the total observed

attenuation in soft tissues. The authors were questioned about the effects of concentration,

which they said they had taken into account, and about the existence of dispersion, which they

believed to be due to relaxation.

Session 2, Scattering and Attenuation , dealt with techniques for estimating attenuation from measurements of scattering. F. L. Lizzi and M. Elbaum (Riverside Research Institute, New York, New York) described clinical spectrum analysis

techniques for tissue characterization. They had measured the echo amplitude decrement from within

a narrow gated sample tracked increasingly deeply

into homogeneous tissue layers. Moreover, spectral analysis revealed characteristic periodicities for different histologies. Within the eye

and orbit, retina, hemorrhage, fat, melanoma and glioma could be distinguished. Using a model embodying scattering (from a fixed interface) and attenuation, S. Levi and J. Keuwez (Hopital

Uni versitaire Brugmann, Brussels, Belgium) re- ported an attempt to characterize tissues in vivo

by differential attenuation measurements on the basis of observations made at two frequencies

(2 and 4 MHz). Results obtained in vivo with

leiomyoma and cyst were encouraging^ RT Kuc and

M. Schwartz (Columbia University, New York, New

York) and N. Finby and F. Dain (St. Luke's Hospital

Center, New York, New York), in a joint paper on statistical estimation of the acoustic attenuation

coefficient slope for liver tissue from reflected

ultrasonic signals, discussed the separation of fixed and refrigerated liver tissue on the basis

of spectral differences in the backscattered signals.

The liver was treated as a random linear filter.

This Session was closely related to Session 3, Scattering . The surface of the lung was considered

by T. L. Rhyne (Massachusetts Institute of Tech- nology, Cambridge, Massachusetts) to have an ultrasonic tissue signature which could be represented

by a stochastic model. Dr. Rhyne took special care to measure the characteristics of the ultrasonic transmitter, transducer, and receiver which

he used. Recent developments in research into angle-scan and frequency-swept ultrasonic scattering characterization of tissue were reported by

R. C. Waag, P. P. K. Lee, R. M. Lerner, L. P. Hunter, R. Gramiak, and E. A. Schenk (University

of Rochester, Rochester, New York). Using an experimental arrangement giving a true analog of Bragg scattering, they demonstrated distinctive

correlations for normal, cirrhotic, and fatty

liver. Measurements of tissue in vitro were

related to models and measurements of known suspensions. Some of the difficulties of measuring

scattering had been solved by F. E. Barber (Harvard

Medical School, Boston, Massachusetts), who described ultrasonic microprobe methods for tissue

characterization. Dr. Barber's microprobe operated

at 10 MHz, and had an almost Gaussian focus with

a diameter of about 0.2 mm. Where large inter- faces existed, they dominated the scattering. The relationships between interface dimensions and scattering directivity were elegantly demonstrated

by reference to a micrograph of the experimental

tissue. J. M. Reid and K. K. Shung (Providence

Medical Center and Institute of Applied Physiology

and Medicine, Seattle, Washington) presented quan- titative measurements of scattering by heart and

liver. They had plotted the scattering cross- sections of 12-20 cm' samples of tissue for many

orientations, and they discussed these in relation

to scattering equations for isotropic, plane, and lossy scatterers. In particular, they considered

the effects of attenuation, both within the sample

and in the region between the transducer and the sample. The dependence of ultrasound backscatter

from human liver tissue on frequency and protein/

lipid composition was discussed by M. Freese and

E. A. Lyons (Radionics Limited, Montreal, Quebec,

Canada). They had used a system with a bandwidth

equal to 25 percent of the center frequency, and found that a frequency of 2.25 MHz gave the best separation between normal and fatty liver. Significant correlations of the backscatter with protein content were observed in normal liver and with both protein and lipid content in abnormal fatty liver.

Final lyjn this Session, M. Hanss and M. Boynard,

(Faculte de Medecine et de Biologie, Bobigny,

France) reported data on ultrasound backscattering

from blood and its hematocrit and erythrocyte

aggregation dependence. They stated that fluctuations in backscattered amptitude were increased in frequency with higher sedimentation rates during

the sedimentation process, and explained this by

a theory involving the existence of rouleaux in Kigh sedimentation rate blood, and the occupancy

4
of potential scattering sites. They suggested

that eventually a noninvasive ultrasonic measurement might supersede the contemporary pathology

test.

Session 4, Tumor Doppler Signatures , consisted of two papers describing measurements of blood flow changes due to malignancy. P. N. T. Wells, M. Halliwell, R. A. Montford, R. Skidmore,

A. J. Webb, and J. P. Woodcock, (Bristol General

Hospital and Bristol Royal Infirmary, Bristol,

United Kingdom) explained the hypothesis that an

in situ carcinoma only becomes a rapidly proliferating tumor after initiation of vascularization.

They showed that asymmetrical arterial blood flow patterns might be found with two breasts, one containing a malignant tumor. This was confirmed

in the following paper on Doppler echography by

G. Dale, Ch. M. Gros, M. Gautherie, and B. Gairard

(Senolgie-Hospices Civils, Strasbourg, France). These authors had used a pulsed 8 MHz Doppler

system to study arterial flow patterns, and they

explained the complementary nature of thermography

in imaging venous flow. Returning to the paper by Wells and his colleagues, these authors had gone

on to describe the discovery with an 8 MHz continuous wave system of abnormal flow signals, appar- ently associated with malignant tumor neovascularization, arising from within the breast lesions themselves. Such signals are not found in normal breasts, or associated with benign tumors. They

reported that they had also detected similarly

augmented blood flow signals, using a 2 MHz pulsed

Doppler instrument, from within a malignant pan- creatic tumor. In discussion, it was explained

that the breast tumor signals were sometimes

strongest at the edge of the lesion, perhaps because of necrosis at the center.

Three papers reporting studies of cardiac

muscle were presented in Session 5, Attenuation

and Velocity II: Myocardium . T. D. Franklin, Jr.,

N. T. Sanghvi , F. J. Fry, K. M. Egenes, and A. E. Weyman (Indiana School of Medicine and Indianapolis

Center for Advanced Research, Indianapolis, Indiana)

described ultrasonic tissue characterization studies

of ischemic and infarcted myocardium. The impetus

for this research came from the non-specificity

of conventional echocardiography in evaluating

infarction. Their preliminary results showed that attenuation fell immediately after infarct. A more extensive study by J. G. Miller, M. O'Donnell,

J. W. Mimbs, and B. E. Sobel (Washington University,

St. Louis, Missouri) of ultrasonic attenuation in normal and ischemic myocardium, involved measurements made with a cadmium sulfide phase-insensitive receiving transducer. The range of attenuation variation in normal myocardium was about 12 to 15 percent, and attenuation fell by about 20 percent when the temperature of the sample was increased from 20° to 37 °C. The slope of a least-squares line fitted to the attenuation

coefficient versus frequency data served as a con- venient ultrasonic index. In dogs with experimentally-induced ischemia, this slope was less than the normal value if sacrifice was within

about 1 day after occlusion, but with later

killing it became greater. This may reflect an increase in collagen content in necrotic scar

tissue. Acoustic microscopic analysis of myocardium by D. E. Yuhas and L. W. Kessler (Sonoscan

Inc., Bensenville, Illinois) had yielded 100 MHz

data on attenuation and velocity in formalinfixed tissue. In kidney, it had previously been shown that the effect on attenuation of formalin

fixing may not be significant. In normal myocardium, the attenuation was about 3.5 to 5.7 dB cm"^ MHz-^. Moreover, the detailed demonstration at high frequency of structures which were of wave- length-order dimensions at low megahertz

frequencies was directly relevant to the study

of scattering in conventional echography.

The second day of the Symposium began with

Session 6, Image Reconstruction . G. H. Glover

(General Electric Co., Milwaukee, Wisconsin)

discussed in vivo measurement of ultrasonic refractive index distributions in human breasts by time- of-f light tomography. His laboratory instrument

was a 5 MHz transmission computerized tomograph.

The patient lay prone on a canvas sling with one of her breasts immersed in water at 32° to 36 °C. Nine minutes were required to scan a slice of 5 mm thickness. Reconstructed two-dimensional images

revealed cysts and fibroadenomas (having velocities

around 2 percent higher than water) and malignant

tumors (having velocities about 4 to 5.5 percent

lower). Young normals (age range 24 to 29 years)

had quite wide velocity variations, but they

might not need to be scanned in a mass screening

program. Histograms of pixel velocity distributions, and cumulative pixel velocity plots, might

provide accurate separation of normals from patients with breasts made asymmetrical by the presence of malignancy. Dr. Glover stated that he was developing a fan beam detector array with 127 elements, designed to reduce the examination time

to 10 seconds per breast. Questions were raised

by the audience concerning path straightness (Dr. Glover had ray plots), resolution (which was 1 ns, although 10 ns would have been adequate), point

spread function (MTF - 1 mm), and accessibility

(slices could be within 20 mm of the chest wall

in the experimental system). Using a synthetic

"fan beam," R. Bal asubramani an , J. F. Greenleaf,

P. J. Thomas, and S. A. Johnson (Mayo Clinic,

Rochester, Minnesota) reported measurements of temperature coefficients of ultrasonic speed in various human tissue. Apart from that of fat, the temperature coefficients of liver, kidney, and other tissues were all about 2 m s"^K"^. The possibility that tumors might be identifiable

because of their elevated temperatures was mentioned during the discussion, but the authors had not investigated velocity changes with temperature

in tumor tissue. Results obtained with computed

tomographic reconstruction of attenuation images

had previously been disappointing, but new approaches were suggested by A. C. Kak and K. A. Dines (Purdue University, West Lafayette, Indiana)

in their paper on signal processing for the measurement of attenuation of soft tissue. They

pointed out that reflection contributed a loss of about 4 percent at each major interface, making

algebraic reconstruction techniques unsatisfactory.

Other frequency and time domain methods, such as polynomial fitting, frequency averaging and energy analysis, might prove to be good candidates

for attenuation measurements. For example, a reconstruction of a section through a dog's

heart by the energy method demonstrated immunity

to reflection artifacts. In discussion, members

of the audience emphasized the importance of clinical practicability. S. A. Johnson, J. F.

5
Greenleaf, and B. Rajagopalan (Mayo Clinic,

Rochester, Minnesota) and R. C. Bahn and B. Baxter (University of Utah, Salt Lake City, Utah),

in a joint paper on the future role of high

spatial resolution ultrasonic measurement tech- niques for characterization of static and moving

tissue, discussed the determination by computerized tomography of three-dimensional fluid flow

and temperature. They proposed the use of seismological approaches for high-resolution

imaging. Another new method, possibly leading

to mapping true ultrasonic backscatter and attenuation distributions in tissue -- a digital

reconstruction approach -- was suggested by F. A. Duck and C. R. Hill (Institute of Cancer Research,

Sutton, United Kingdom). By assuming that attenuation and scattering were constant and iso- tropic within each volume element of the object,

they showed that the corresponding pixel values in the image could be calculated by algebraic recon- struction techniques (ART) in about six iterations.

Discussion revealed that isotropic assumptions

might not be satisfied in clinical practice.

Sessions 7 and 8, Signal Processing and Pattern Recognition I and II , contained a total of twelve

papers. Region-of-interest analysis methods were

used in feature extraction techniques designed to improve recognition of patterns in ultrasonic

pictures of the prostate for tumor diagnosis, by

W. V. Seelen (Johannes Gutenberg Universitat,

Mainz), E. G. Lock and G. Wessels (Deutsche Klinik

fiir Diagnostik, Wiesbaden), U. Scheiding (Battelle

Institut, Frankfurt), and A. Gaca (Deutsche Klinik

fiir Diagnostik, Wiesbaden, Federal Republic of Germany). J. C. Birnholz (Harvard University,

Boston, Massachusetts) then reviewed the elements

of visual pattern recognition in ultrasonography.

He showed some remarkably excellent grey-scale

pictures. The influence of signal processing, and particularly of the detection method, on the quality

of echograms was discussed by I. Beretsky, D. Arnold,

and J. Cason (Searle Ultrasound Research and Ad- vanced Development, Spring Valley, New York), in their paper on impulse detection in pulse echo ultrasound -- recent in vitro experiments with a human aorta. This was followed by a theoretical

analysis of instantaneous power spectra as applied

to spectra-color ultrasonography, by W. D. Jennings,

E. Holasek, and E. W. Purnell (Case Western Reserve

University, Cleveland, Ohio). The method was based on the separate display in the primary colors

on the same image of three frequency bands constituting the echo signals. Session 7 ended with a paper by C. K. Kuni (University of Colorado

Medical Center, Denver, Colorado) on tissue identification by spectral analysis of scattered ultrasound. Dr. Kuni discussed some of the problems of obtaining and interpreting backscattered spectra.

The following Session 8 began with a description of a comprehensive ultrasonic tissue analysis

system by M. Linzer, S. I. Parks, R. W. Shideler,

S. J. Norton, F. P. Higgins, and D. R. Dietz

(National Bureau of Standards, Washington, D.C.)

and J. L. Doppman and T. H. Shawker (National

Institutes of Health, Bethesda, Maryland). Dr. Linzer described a dynamically-focused system

using an expanding-aperture annular array with an approximately constant F-number, and an rf sub- system capable of operating with impulses, gated

continuous wave, and chirp pulses. Chirp operation

with 8:1 compression had been achieved. An ultrafast signal averager was developed for im- provement of the signal-to-noise ratio of A-scans.

This instrument had a sampling rate of 50 MHz and

a 4-bit analog-to-digital converter, and had potential applications in the examination of obese patients, the use of higher frequencies, and the

use of inefficient transducers. Next, an instru- ment called the "SonoChromascope" was described.

Interfaced to a commercial two-dimensional B- scanner, this device formed a versatile digital

real-time acquisition, signal processing, and display system. The 250 kbyte memory allowed

operation in normalized averaging, maximum,

minimum, and parameter comparison modes. Gray-scale,

color, and window displays, as well as digital

readout of area and average echo amplitude in regions-of-interest were possible. Finally,

Dr. Linzer stated that other methods, including CT scanning, were being investigated at NBS. There

was discussion about the rather low digitization

accuracy of commercial transient recorders which

do not contain sample-and-hold circuits. The subject of spectrum analysis was again considered

in the following paper by L. Joynt, D. Boyle, H. Rakowski, and W. Beaver (Stanford University,

Stanford, California), on the identification of tissue parameters by digital processing of realtime ultrasonic clinical data. Data obtained with

a real-time phased array sector scanner from selected regions within the myocardium in various

clinical conditions were subjected to spectral

analysis. Although there was substantial overlap

between groups, spectra from patients with myocardial infarcts had much less fluctuation in their

means and variances as a function of time. J. C. Gore and S. Leeman (Royal Postgraduate Medical

School, London, United Kingdom) presented two short

papers. The first, on the theoretical evaluation

of backscatter of ultrasonic pulses from human tissue and its implications for tissue characterization, dealt with the effects of the characteristics of pulser, transducer, and receiver. The second paper, on autocorrelation analysis of A- scans in vivo and the possible clinical application

of temporal changes in echo characteristics,

revealed similarities between the echoes from different specimens of the same types of tissue,

while different types of tissue had dissimilar

autocorrelation functions. With the goal of implementing computer spectral analysis of ultrasonic

A-mode echoes, D. E. Robinson (Ultrasonics Institute,

Sydney, Australia) had developed an on-line data acquisition system based on a clinical scanner,

10 MHz sample rate transient recorder, and Inter- data 85 computer. Special consideration had been given by K. Preston, Jr. (Carnegie-Mellon University, Pittsburgh, Pennsylvania) and M. L. Skolnik

(University of Pittsburgh, Pittsburgh, Pennsylvania)

to the application of pattern recognition techniques

to the separation of ultrasonic echoes from different types of tissue. Digitized A-scans had been converted to sound patterns as a preliminary to testing the feasibility of using the ear to dis- tinguish the sound patterns from different types

of tissue. The A-scans had been analyzed in terms

of skew, kurtosis, and other statistical parameters.

Initial results had been obtained from normal and neoplastic kidney. In order to determine the correlation function of echoes from a region-ofinterest identified on a two-dimensional B-scan,

J. Eraser and G. S. Kino (Stanford University,

6
Stanford, California) and J. Birnholz (Harvard

Medical School, Boston, Massachusetts) reported

the use of cepstrum processing for tissue analysis.

The transducer response appeared mainly centered

at the cepstrum origin, and it was gated out so that the inverted cepstrum allowed the well-deconvoluted autocorrelation response of the tissue

alone to be observed. Finally in this lengthy

pair of sessions, R. D. Lepper, R. Reuter, and

H. G. Trier (Universitat Bonn, Bonn, Federal Republic of Germany) pointed out the advantage of asychronous writing and reading on a storage tube

in time-stretching ophthalmic A-scans in order to improve the precision of digitization.

Session 9 was a Panel Discussion on Ul tra- sonic Diagnosis of Breast Cancer . The cochairperson, P. N. T. Wells (Bristol General Hospital,

Bristol, United Kingdom) in his introductory remarks pointed out that mortality from breast cancer had not improved over the last 20 years. He explained

that in the Western World, breast cancer, which had many different pathological types, killed 1 in 50 women, was the main cause of death in females in the age range 40 to 44, and in the U.S. had an annual economic cost of $200M. Existing diagnostic

methods were inadequate for mass screening. Interest

in ultrasonic techniques hinged around the possibility that earlier detection by screening might

improve prognosis. Cochai rperson W. Pomerance

(National Institutes of Health, Bethesda, Maryland),

defined screening as the application of known methods to an asymptomatic population to detect

early cancer. He considered that a successful method for breast screening would need to detect

tumors of less than 5 mm diameter, and that it should be free from hazard and have at least a 90 percent success rate. Encouraging results with

high-resolution scanning led L. Weiss (Roswell Park Memorial Institute, Buffalo, New York) to suggest that ultrasound might be capable of detecting lesions of 2 mm diameter. This would be an important although numerically modest improvement

over the present ability to detect 5 mm lesions by manual palpation. He explained that it had been estimated that screening the whole adult female population with an effective ultrasonic method, if one should be developed, would have cost $620M per year in 1971, and he felt that it would therefore

be necessary to restrict screening to women known

to be at risk, or over 50 years old. J. L. Doppman (National Institutes of Health, Bethesda,

Maryland) described the role of mammography, and stated that the x-ray exposure was presently less than 0.01 Gy. Mammography could ensure that the lesion was removed by the surgeon. Five years of experience of ultrasonic visualization of the breast in Japan were reviewed by T. Kobayashi

(National Cancer Center Hospital, Tokyo, Japan).

Ultrasonic screening was being made available by means of mobile units. G. Dale (Senologie-Hospices

Civils, Strasbourg, France) described the complementary use of ultrasonic scanning, both pulseecho and Doppler, together with thermography and mammography, to decrease the overall error rate. The results of research into high resolution pulseecho imaging of the breast, and the problems of analyzing the scans, were presented by G. Baum

(Albert Einstein College of Medicine, New York, New York). Elizabeth K. Fry (Indiana University

School of Medicine and Indiana University Hospital,

Indianapolis, Indiana) described a versatile ultrasonic breast scanning research instrument. She presented some scans, and discussed their interpretation, emphasized the importance of shadows, and

the different patterns obtained with different

transducers and frequencies. Cautious optimism

was expressed by D. E. Robinson (Ultrasonics

Institute, Sydney, Australia). He demonstrated

some excellent scans, obtained with a 4 MHz focused beam in a water bath scanner, and spoke

of eight features for which the scans required to be examined in reaching a diagnosis. J. F. Greenleaf (Mayo Clinic, Rochester, Minnesota)

described the role of ultrasonic computed tomography in obtaining data on tissue properties and

in correcting two-dimensional B-scans. G. H. Glover (General Electric Company, Milwaukee,

Wisconsin) had previously talked about his work

on ultrasonic computed tomography in a paper pre- sented during Session 6. As time was short. Dr. Glover did not add to the information which he had already given concerning the increase in velocity

associated with malignancy in breast tissue. For

the same reason. Dr. Wells did not elaborate on the potential of neovascularization blood flow Doppler detection, as he had mentioned this in Session 4. M. Linzer (National Bureau of Standards,

Washington, D.C.) emphasized the vast quantity of data which would be obtained in scanning only one patient, and of the refinements in methodology

which would be necessary to make ultrasonic breast screening feasible. Members of the Panel and the audience then began an open discussion, and several points were made. The demonstration of microcalcification in ultrasonic scans was possible if sufficiently extensive. Ultrasonic scanning was beneficial in young women with "lumpy" breasts. Mammography did not contribute further when ultra- sound had already detected a lesion. Present

commercial equipment was unsuitable for starting a mass screening program. Mammography would in principle never be an acceptable mass screening

method, as it would always involve exposure to some radiation. Dr. Wells closed the discussion

with a short summary. Mass screening of selected

groups of the female population would be worthwhile if a suitable technique could be developed.

Such a technique might well be based on ultrasound

but it would need to be accurate and economical.

The present lines of research were promising; more resources should be devoted to solving the fundamental and technological problems, so that earlier clinical application would be possible.

Propagation Through Bone and Skull was the subject of Session 10, which opened the final day

of the Symposium. A theory relating sonic velocity

to mineral content in bone was presented by S. Lees (Forsyth Dental Center, Boston, Massachusetts).

Bone had a higher velocity than that predicted on the basis of its longitudinal elastic modulus.

Dr. Lees suggested that this was due to the bone consisting of mineral hydroxyapati te crystallites

embedded in a matrix of collagen, behaving in the same way as a plastic filled with powdered mineral.

H. S. Yoon and J. L. Katz (Rensselaer Polytechnic

Institute, Troy, New York) considered the ultrasonic properties and microtexture of human cortical

bone, and showed that bone could be treated as an elastic dielectric. The attenuation of ultrasound

in cancellous bone was the subject of a paper by

J. E. Barger (Bolt Beranek and Newman, Cambridge,

Massachusetts). He distinguished between phase

7
and group velocities, and showed that scattering

in the dipole made an important contribution to losses at frequencies in the range 0.5 to 2 MHz. The results of measurements of transmission through

skull were presented, in a discussion of the acoustic characteristics of the skull, by D. N. White (Queens University, Kingston, Ontario,

Canada). Dr. White explained that propagating

ultrasonic energy appeared to be distributed

between the bony and the soft tissue elements of cancellous bone resulting in substantial

attenuation, although it was transmitted with

relatively low loss through ivory bone. Inhomo- geneities led to marked distortion of megahertz

frequency beams transmitted through the skull. Because of this difficulty, F. J. Fry (Indianapolis Center for Advanced Research, Indianapolis, Indiana)

had investigated the transkull transmission of axi- symmetric focused ultrasonic beams in the 0.5 to

1 MHz frequency range, and its implications for brain tissue visualization, interrogation, and therapy. Beams at the relatively low frequency of

0.5 MHz were not greatly distorted in travelling

through skull, and there seemed to be quite good

correlation between transkull ultrasonic two- dimensional brain scans and x-ray computed tomo- graphs. The potential for therapy resulting from

the relatively low attenuation in the skull was demonstrated by a lesion induced in lucite by a beam of ultrasound which had passed through part

of a cadaver skull. The feasibility of visualizing

the brain was further demonstrated by some advances

in acoustic imaging through the skull which were reported in a joint paper by S. W. Smith (Bureau

of Radiological Health, Rockville, Maryland), D. J. Phillips (University of Washington, Seattle, Washington), and 0. T. von Ramm and F. L. Thurstone

(Duke University, Durham, North Carolina). Remarkable real-time pictures, showing brain structures

and pulsating arteries, had been made with a phased-array sector scanner. Treating the skull

as a random acoustic lens, optimal results were theoretically obtained at a frequency of about

1 MHz and an aperture width of about 35 to 40 mm. The ultrasonic images were well correlated with

pictures from a brain atlas. The possibility was pointed out that phase correction for the effect

of the skull could be obtained element-by-element

across the array, if a suitable intracranial source

of uniform wavefronts could be devised.

The following Sessions 11 and 12, Attenuation

and Velocity III and IV had ten papers. S. A. Goss,

R. L. Johnston, V. Maynard, L. Nider, L. A. Frizzell,

W. D. O'Brien, Jr., and F. Dunn (University of Illinois, Urbana, Illinois) reviewed ultrasonic

propagation parameter measurements. They discussed

the advantages, disadvantages, and accuracies of resonant cavities, interferometers, and thermo- couple probes, and techniques based on velocity

difference measurement, pulse superposition, radiation pressure, and time-of-f 1 ight measurement.

The temperature dependence of the velocity of sound

in soft tissues, a parameter of great importance in hyperthermia therapy for control of cancer, was reported by T. Bowen, W. G. Connor, R. L. Nasoni,

A. E. Pifer, and R. R. Sholes (University of Arizona, Tucson, Arizona). With the exception of

fat, vegetable oil, and water, which had negative

temperature coefficients of velocity, all the other

tissues investigated -- spleen, muscle, liver, and kidney -- had positive temperature coefficients

over the range 36° to 44 °C. A simple but effective device for measuring ultrasonic propagation

velocity in tissue, both in vitro and, with

suitable anatomy, in vivo , was described by B. D. Sollish (Weismann Institute of Science, Rehovat,

Israel). The following three papers were con- cerned with ultrasonic studies of the breast. T. Kobayashi (National Cancer Center Hospital, Tokyo,

Japan) spoke about the correlation of attenuation

in breast cancers with connective tissue content.

He showed that stronger shadowing, associated

with greater attenuation, was correlated with

higher connective tissue content. Thus, strong

shadows were produced by scirrhous carcinoma

(rich in connective tissue), average shadows by

papillary carcinoma, and weak shadows by medullary

carcinoma (poor in connective tissue). The comments of the audience substantiated the conclusion that increasing attenuation was correlated

with increase in collagen, as in operative scars

and older breasts. Next, G. Dale, Ch. M. Gros,

M. Gautherie, and B. Gairard (Senologie-Hospices

Civils, Strasbourg, France) carefully reviewed

diagnostic image features, in their paper on echo- graphic syndromes of breast cancer. This was followed by a mul ti -di sci pi ine approach to the detection of breast cancer by ultrasonic techniques,

with intercomparison of signal-processed ultra- sound transmission data, ultrasound pulse-echo

information, and whole breast pathology, by E. K. Fry, N. T. Sanghvi , and F. J. Fry (Indiana University School of Medicine and Indianapolis Center for Advanced Research, Indianapolis, Indiana) and H. S. Gallager (University of Texas, Houston, Texas).

Experiments with an excised, formalin-fixed breast revealed non-uniform attenuation particularly in and near the nipple. The audience asked about the contributions of reflections (which were felt not

to be large), the possibility of the existence of bubbles and the effect of formalin, and, for in vivo measurements , the effects of lactation and

the taking of the contraceptive pill. F. W. Kremkau,

C. P. McGraw, and R. W. Barnes (Bowman Gray School

of Medicine, Winston-Salem, North Carolina) reported

the results of some careful measurements of the acoustic properties of human brain. The infant

brain had about 60 percent lower attenuation than

the adult. In adult brain, fixing with formalin

increased velocity by about 30 percent. Fixed

brain had a dispersion of about 1.6 m s'^MHz"^, and fresh brain about 2 m s"^MHz-i. The temperature

coefficient of attenuation was negative, and attenuation was 1.4 times greater in white matter

than in gray. Tissue characterization using

acoustic transmission and scattering parameters was further discussed in a joint paper by M. P. Kadaba,

W. P. Cockerill, and P. K. Bhagat (University of Kentucky, Lexington, Kentucky), and R. W. Ware (Veterans Administration Hospital, Lexington,

Kentucky). In tissues such as kidney, liver, and cardiac muscle, over the frequency range to 1 to

10 MHz, attenuation increased from about 2 to 16 dB cm-^, and velocity, from 1520 to 1580 m s"' ( i.e. , by about 4 percent). In another joint paper, D. H. Le Croissette, R. C. Heyser, P. M. Gammell, and

J. A. Roseboro (California Institute of Technology,

Pasadena, California), and R. L. Wilson (University

of Southern California, Los Angeles, California)

reported values of the attenuation of selected

tissue as a function of frequency. Using time-delay

spectrometry, involving the measurement of the frequency difference between the received signal

8
and a transmitted frequency-modulated wavetrain,

they studied attenuation over the range 1 to 8 MHz

in liver, pancreas, muscle, and fat. In liver, for example, attenuation decreased after death but increased as a result of fixing. Apparently

similar tissues often had very different attenuations. Finally in Session 12, D. Hughes, L. A. Geddes, and V. Newhouse (Purdue University, West Lafayette, Indiana) discussed the velocity and attenuation of ultrasound in blood at 37 °C. These

data were required in order to estimate Young's

modulus of the aortic wall. Besides presenting

accurate values, Hughes reported that attenuation increased with packed cell volume (up to at least 60 percent packing), and velocity had a minimum value with a packed cell volume of about

10 percent.

The final session. Session 13, Tissue Viability

and Tissue Phantoms , began with a paper by L. Weiss

(Roswell Park Memorial Institute, Buffalo, New York)

on tissue signatures -- a matter of life and death.

Dr. Weiss discussed the changes which took place in

1n vitro tissues, and the precautions which needed

to be taken to minimize consequential changes in tissue signature interactions. For example, poor oxygenation might result in death within 5 minutes.

Even in life, many tumors had dead or dying cells,

and these differences probably affect ultrasonic

imaging. Mechanically-induced cell separation measurements were related to degenerative changes

in tissue, and might possibly be used to standardize

interactions with ultrasound. The remaining three papers in this Session were concerned with tissue

equivalent materials for ultrasonic imaging. In a joint paper, P. Edmonds, Z. Reye, and D. Parkinson

(Stanford Research Institute, Menlo Park, California), R. Filly (University of California Medical

Center, San Francisco, California), and H. Busey

(Picker Corporation, Northford, Connecticut)

described a human tissue phantom for testing con- ventional ultrasonic scanners. After experimenting

with several rubber and plastic materials, it was found that gelatin-water gels, loaded with

glass microspheres or cellulose fillers as scatterers, gave satisfactory results. Questions

from the audience were answered by statements that

the gel had an acceptable dependence of attenuation on frequency, and that the plastic materials

had attenuations which were too high to permit

the addition of scatterers. R. C. Eggleton (Indiana

University School of Medicine and Indianapolis

Center for Advanced Research, Indianapolis, Indiana)

mentioned the application of tissue simulators for ultrasonic diagnosis, in teaching and training,

evaluation of scanner performance, and as models

for basic research. He presented results obtained

with a plastisol, and showed the effects of adding

scatterers. A joint paper by P. L. Carson, L. Shabason, and D. E. Dick (University of Colorado

Medical Center, Denver, Colorado) and W. dayman

(Alderson Research Laboratories, Inc., Denver,

Colorado) on tissue equivalent test objects for comparison of ultrasound transmission tomography

by reconstruction and pulse echo imaging, also discussed special plastic materials. Although

these materials did have rather high attenuation

(about 2 dB cm-iMHz"-), scatterers could be added

and phantoms satisfactory for testing systems

could be constructed. Finally, Dr. Carson showed

an ultrasonic CT scan of an in^ vi vo breast indicating an attenuation coefficient of about 15 dB cm"^

at 3.5 MHz. •

In summary, the Second International Symposium

on Ultrasonic Tissue Characterization brought the subject into focus and perspective. The 286 par- ticipants, including many of the leaders in the field, spent three days exchanging ideas and learning from each other. Mass screening for breast cancer in particular was identified as one

of several clinical problems which might be solved

by ultrasonic tissue characterization. Research

opportunities were evident in the development of fundamental theories, the acquisition of data on velocity, attenuation and scattering, and in clinical validation. Image reconstruction, signal

processing, pattern recognition, and Doppler blood flow signals, emerged as fruitful areas for investigation. New technological advances, for example,

in tissue phantom materials, were identified as already being ready for transfer to commercial

application.

M. Linzer

P. N. T. Wells

July, 1977

9

REPORT ON PANEL DISCUSSION

ULTRASONIC DIAGNOSIS OF BREAST CANCER

PANEL

Cochairpersons

William Pomerance

Diagnosis Branch Division of Cancer Biology and Diagnosis

National Institutes of Health

Bethesda, Maryland

P. N. T. Wells Department of Medical Physics

Bristol General Hospital

Bristol, United Kingdom

Panel Members

Gilbert Baum Albert Einstein College of Medicine

Bronx, New York

John L. Doppman

Department of Diagnostic Radiology

Clinical Center

National Institutes of Health

Bethesda, Maryland

G. H. Glover

General Electric Company

Medical Systems Division

Milwaukee, Wisconsin

Toshiji Kobayashi

Department of Internal Medicine

National Cancer Center Hospital

Tokyo, Japan

D. E. Robinson

Ultrasonics Institute

Sydney, Australia

G. J. Dale Senologie-Hospices Civils

Strasbourg, France

Elizabeth K. Fry

Indiana University School of Medicine and Indiana University Hospital

Indianapolis, Indiana

J. F. Greenleaf

Mayo Clinic

Rochester, Minnesota

Melvin Linzer

National Measurement Laboratory

National Bureau of Standards

Washington, D.C.

Leonard Weiss

Roswell Park Memorial Institute

Buffalo, New York

In his introductory remarks, P. N. T. Wells

pointed out that the overall mortality from breast cancer was the main cause of death in Western women

between the ages of 40 and 44 years, and the annual economic cost of the disease in the U.S. was around

$200M. Consequently, it was timely to review the contribution which ultrasonic diagnostics might

make to the solution of the breast cancer problem. There were many different malignant tumors of the breast — scirrhous, mammary duct, papillary,

medullary, colloid, lobular, intracystic, apocrine

and adenoid cystic carcinoma, Paget' s disease,

lymphoma, and sarcoma. The earlier that breast

cancer was treated, the better was the prognosis.

A patient treated with in situ carcinoma was cured.

If the tumor was localized, the five-year survival

was 85 percent; but this fell to 53 percent if there was lymph node involvement. A patient with

distant metastases was incurable, although the survival time varied from patient to patient.

Interest in screening hinged around the possibility that earlier detection might improve prognosis.

Unfortunately, thermography was unsatisfactory as

a screening method for breast cancer: in one

series, for example, only 25 percent of those who developed cancer within 18 months were detected,

and the false positive rata was approaching 15 percent. When combined with clinical examination, in another trial, only about 20 percent of cancers in women under 50 years of age would not have been detected without mammography. Moreover, mammography, whilst having a negligible risk as far aS the individual patient was concerned, would itself

induce by radiation a large number of cancers if every member of a large population were to be exposed to it.

William Pomerance said that it had to be admitted that contemporary methods of treating

advanced breast cancer were ineffective, and that progress might depend on earlier detection. He defined screening as the application of known methods to an asymptomatic population to detect

early cancer. He considered that an acceptable

method for breast cancer screening would need to detect tumors of less than 5 mm diameter, and

that it should be free from hazard and have at least a 90 percent success rate. The assessment

of the value of breast cancer screening would take

a long time, since the mortality of patients sur- viving treatment only coincided with that of the

normal population after about 17 years. He thought

that screening might have its biggest impact in detecting slowly growing asymptomatic tumors.

11
The fact that screening for cancer of the uterine cervix had resulted in a reduction in mortality led Leonard Weiss to hope that breast

cancer screening might also be effective. Moreover,

he was encouraged by results which he had obtained

using a high-resolution ultrasonic scanner, that

it might soon become possible to detect lesions

of less than 2 mm diameter, although it might be difficult to distinguish histologically between

different types of lesion. The detection of 2 mm

diameter lesions would be an important but numerically modest advance from the present ability to detect 5 mm lesions by manual palpation; an improve- ment of 10 percent in effectively treated patients

might result. Weiss stressed the importance of growth rate in determining prognosis. He then referred to a study of the feasibility of breast

cancer screening, which had been carried out in 1971. If the 38 million women in the U.S. who might have benefited from screening were to have

been given this advantage, it had been estimated

that the annual cost then would have been around

$620M. He felt that it would therefore be necessary

to restrict screening to women known to be at risk,

or over 50 years old.

The role of mammography was discussed by J . L. Doppman. He showed some typical mammograms, and explained that the method was best for visualizing

microcalcif ication. Three-dimensional display was

needed. A great advantage of mammography was that

it could be used by the surgeon to ensure that he removed the entire lesion. Recent developments had resulted in a reduction in the x-ray exposure, which presently was generally less than 0.01 Gy

(1 rad).

Next, experience with pulse-echo ultrasonic

methods was reviewed. Toshiji Kobayashi had worked

for five years in Japan on the ultrasonic visualization of the breast. For Japanese women, scanning

through a flexible membrane at the bottom of a water-bath was satisfactory. Kobayashi described

the distinctive echographic features of lesions

of differing histologies, and he emphasized the importance of retrotumorous shadowing in deducing

information about the attenuation by the lesion. Such was the confidence which was felt in the method in Japan that specially equipped minibuses

were being used in mass screening trials. In the breast cancer clinic, both pulse-echo and Doppler investigations were complementary to thermography and mammography, according to G. J. Dale. He discussed the ultrasonic scans of two typical patients, and concluded that in breast

cancer diagnosis the false positive rate was 0.6 percent; the false negative rate was 11 percent,

but this fell to 5 percent when combined with

clinical examination. Using pulsed Doppler, he had traced breast arteries of greater than 1 to

2 mm in diameter, and he explained that Doppler

information related more to function than to structure. He had not studied the capillary

system of malignant tumors by the Doppler method. Gilbert Baum described the interpretation of breast echograms. Not only was textural analysis

of breast tissue patterns difficult because of their wide variations, but also the skin of different individuals seemed often to transmit

ultrasound differently. He felt that it was necessary to scan through water, particularly because

lesions might otherwise be displaced by the pressure

of the ultrasonic probe. Coupling through a water

bath also allowed a large aperture transducer to be used, and the scanning motion could be automatic.

Apart from the need to develop instrumentation

capable of yielding reproducible results, the main

problem was not to obtain the scans, but to find

the time to analyze them. Furthermore, it was sub- jectively apparent that image degradation occurred

when digitized either to fewer than 360 x 360 pixels, or to less than 32 gray levels. Sixty

scans were obtained for each patient, and to reduce

the analysis time he had tried color-coding, and

the superimposition of seven serial scans on a three-dimensional optical hologram. Even with such techniques, it was obvious that screening could

only be offered to selected groups of patients.

Elizabeth K. Fry had constructed a versatile

scanner for research into breast disease. This

was important, because the modification of instru- ments primarily designed for the examination of other structures was unsatisfactory. The patient

lay prone, her breasts immersed in water. A variety of transducers, operating at different

frequencies, had been used to make many scans, producing a great range of patterns for analytical

study. Cautious optimism was expressed by D. E. Robinson because of his experience with a waterimmersion breast scanner using a 4 MHz transducer,

with an aperture of 40 mm diameter and a focal length of 100 mm. Both simple and compound scans

had been made with this instrument. The ultrasonic breast scan pattern depended on the age of the patient. Cysts could easily be demonstrated,

and so could some parts of the ductal system.

Robinson mentioned eight features, such as the degree of shadowing, for which scans of solid

lesions required to be examined in reaching a diagnosis. It was easier to see skin dimpling

associated with malignancy in immersed breasts,

because of the extra support provided by the water.

The possible role of ultrasonic computed

tomography in obtaining data on tissue properties

was emphasized by J. F. Greenleaf. In any particular breast, it should be possible to measure the attenuation and velocity in the constituent image

pixels, and these data could be used to correct

conventional two-dimensional pulse-echo scans.

G. H. Glover had previously talked about his work

on ultrasonic computed tomography in a paper presented during Session 6. As time was short. Glover did not add to the information which he had already given concerning the increase in velocity

associated with malignancy in breast tissue. For

the same reason. Wells did not elaborate on the potential of neovascularization blood flow Doppler

detection, as he had mentioned this in the paper which he had already presented in Session 4.

Melvin Linzer emphasized that computed

reflection and transmission tomography coupled

with ray tracing and frequency-dependent time-gaincompensation techniques would be needed to make

ultrasonic breast screening feasible. Because

of the complexity of these calculations and the vast quantities of data which would be obtained

in scanning only one patient, ultrafast processers

with large memory are required. He felt that the potential advantages of ultrasonic investigation,

and especially the possibility of safe serial surveys, justified the expenditure of substantial resources on research.

12
Members of the Panel and the audience then began an open discussion. M. L. Skolnik asked whether it was possible to demonstrate microcalcification on ultrasonic scans, and Dale replied

that this was so if the calcification was sufficiently extensive. Fry pointed out that the echo- graphy was very helpful in monitoring young women with "lumpy" breasts, because a suggestion of the development of malignancy could be discovered

early on; Robinson agreed with this. Pomerance

asked Fry whether she felt that mammography had anything to contribute where a lesion had been detected by ultrasound, and although she thought

that this might occasionally be the case, Weiss

did not. C. R. Hill returned to the value of echography in managing patients with benign lesions,

but he felt that the method was not helpful if the lesions were very small. Greenleaf stressed the importance of data obtained from time-of-f 1 ight

computed tomography. Fry considered that past progress more than justified continued efforts to develop an ultrasonic breast screening method; but there was general agreement with Baum when he said that the presently available commercial equipment

ought not to be used in a trial of ultrasonic

breast cancer screening as this would inevitably

bring the method into disrepute. F. E. Barber

enquired about the potential of low-dose mammography, and Doppman replied that the accuracies of such techniques had not been assessed; he thought

that it would be better to wait for a viable ultrasonic method, than to extend the use of mammography.

According to Pomerance, even if the x-ray exposure

were to be reduced to 2 mGy, mammography would be unacceptable for mass screening. A member of the audience asked whether it was the tumor which was demonstrated by echography, or the reaction of the surrounding tissue. Robinson replied that both features might be seen; for example, besides the echoes from the tumor, there might be skin thickening and shadowing. In this connection. Fry

mentioned the change in the collagen content of

the entire breast, which might be due to a malignant tumor. Wells closed the discussion with a short summary.

He said that it seemed to have been established that mass screening of selected groups of the female population for breast cancer ~ those specially at risk, and those more than 50 years

old -- would be worthwhile, if a suitable technique

could be developed. Such a technique might well

be based on ultrasound but it would not necessarily

be a simple pulse-echo method. It would need to

be accurate and economic. The present lines of research were promising; more resources should be devoted to solving the fundamental and technological problems, so that earlier clinical application

would be possible.

P. N. T. Wells

July, 1977

13

INTRODUCTORY ADDRESS

THE RELATIONSHIP OF TISSUE SIGNATURE RESEARCH TO IMPROVED HEALTH CARE

Alfred J. Eggers , Jr.

Assistant Director for Research Applications

National Science Foundation

Washington, DC 20550

It is a pleasure to be here today before such

a distinguished audience. It has been only two years since the first conference devoted to ultrasonic tissue characterization. Much has been accomplished in those two years. Even more will

be done in the future. You should be proud to be part of such a vigorous research effort, and I know you share my pleasure at the prospects for

the improved medical devices that should derive

from the efforts of all of you.

It is because of these prospects that the applications side of the National Science Foundation is so interested in your efforts. In addition, there is the revolution in microelectronics

which has provided an order of magnitude reduction

in cost and improved performance every five years

for well over 25 years. Our technologists confidently expect another decade of the same. What

does this mean? Suppose a highly sophisticated

piece of equipment using the current tissue signature technology would cost $1,000,000 on the market today. I'm told that this is a reasonable

ball park estimate. Five years from now the cost could plummet to $1 00,000--sti 1 1 a bit rich for the average physician. But in another five, we

find that $100,000 may drop to $1 0,000--much

closer to what can be afforded.

Reflect for a moment on what the implications

of these changes could be. We may be approaching

the end of the "visible" computer because microelectronics can make a computer so small and inexpensive that it will disappear behind the imaging screen. One question is how will we exploit this capability? This is why efforts such

as this conference are so important. It is one

crucial step in preparing wisely for the future.

Of course, we must be aware that extrapolation is sometimes a hazardous experience. There

is no assurance that wanting or expecting a major

cost--performance breakthrough will make that change happen. Still, we would all be derelict in discharging our responsibilities if we were not ready. After all, the sums being devoted to research are not trivial, but they are really a low cost insurance payment if the predicted gains

from electronics are realized. The real waste

would be to have all this great technology available and not be ready to apply it for improved

health care. You might be interested in the back- ground for the Research Applied to National Needs

(RANN) participation with the National Bureau of

Standards and the National Institutes of Health in support of this conference. Early in the history

of the applications directorate, we set up a series of experiments to investigate ways of accelerating the use of technology. One is of particular interest to you. The first step was to set up a study group in 1973 which evaluated the state of development of medical ultrasonic diagnostic instruments. This survey team found that

exi sti ng technology could be marshalled into improved systems. Our group of RSD incentives

experiments, therefore, included an Experiment No.

5 to encourage the industrial community to create

these new systems. As in most experiments, we have learned and did not do everything to per- fection. Overall, however, it was a useful investigation. Today there is new equipment on the market and clinical ultrasound is rapidly

becoming an important part of diagnostic services.

That same report of 1973 also had another

major finding. To make a major step forward

beyond the experiment five objectives would take

far more research across a broad front of activity. Later, we had the Alliance for Engineering

in Medicine and Biology suggest in their report

entitled, "A Five Year Research and Development

Agendum for Ultrasonic Imaging Diagnostic Instru- mentation," that a complete system look across 23 research categories was needed. In broad terms,

the report pointed out the need to balance the

total program and consider it as a system of interrelated parts. Funds for research on bio- hazard were described as needed. Still, it is silly to not avail oneself of the opportunity to acquire information at lower powers which are intuitively less risky. Both types of efforts

were recommended. Included in this list was research on tissue characteri zati on--the subject

of this conference.

A direct outgrowth of the last tissue signature conference was a recognition that ultrasound

tissue signature research was not yet a coherent

body of knowledge. The RANN program provided

grant funds to establish and disseminate a pre- liminary data base for ultrasound tissue charac- terization research. I understand that a news- letter is being published and that several of you

in this conference will meet on June 16 to con- tinue the task of systematically collating re- search results. I also understand that the first

meeting will take the place of an advisory com- mittee under the leadership of Dr. McKinney, past

15
president of the AIUM and professor of neurology

at the Bowman Gray Medical School . Both of these

groups are part of a major effort whose objective

is clear. We want improved patient care. Moving

from the present to the future is difficult, and we must be sure that all opinions are brought to focus on this objective.

Now, let me point out that we have three

basic objectives in the RANN program. These are

to:

Increase the effective use of science and technology in dealing with national

probl ems

Shorten the lead time between basic

scientific discoveries and relevant

practical applications; and provide early warning of potential national

problems and initiative assessments and research useful in avoiding or solving

such problems.

It is clear that your research efforts sat- isfy these criteria. You will note that we em- phasize national needs. I believe that each country shares our concerns about improved health

care. It is a pleasure to join with all of you from many nations to present, hear, and discuss common research interests in this area. I wish

you all the best in your efforts today, tomorrow,

and in the future to use science and technology

more effectively to make this world a healthier

place in which to live and thrive.

16
CHAPTER 2

ATTENUATION AND VELOCITY I: MECHANISMS

17

Reprinted from Ultrasonic Tissue Characterization II, M. Linzer, ed., National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C., 1979).

ELEMENTS OF TISSUE CHARACTERIZATION

Part I. Ultrasonic Propagation Properties

R. L. Johnston, S. A. Goss, V. Maynard, J. K. Brady,

L. A. Frizzell, W. D. O'Brien, Jr., and F. Dunn

Bioacoustics Research Laboratory

University of Illinois

Urbana, Illinois 61801, U.S.A.

Tissues can be characterized ultrasonical ly by their attenuation, absorption, and velocity, all of which correlate well with the presence of the major tissue com- ponents of water, and protein, particularly, collagen. This correlation is examined

in solutions of biologically important molecules and in a number of tissues and organs. It is shown that tissues can be grouped according to similar ultrasonic

propagation properties, physiological functions, and concentration of elementary

constituents. The role of collagen in determining ultrasonic properties of normal

and pathological tissues is discussed.

Key words: Absorption; amino acids; attenuation; frequency; mammalian tissues;

polypeptides; proteins; tissue characterization; ultrasonics; velocity.

1. Introduction

The ultrasonic propagation properties of bio- logical materials include the behavior of those measurable acoustic parameters, as functions of

the state and acoustic variables, which characterize the fate of acoustic signals propagating

within the biological environment. The ultra- sonic attenuation includes not only the absorption of the ultrasonic signal, which is degraded

to heat, but also losses due to other mechanisms

by which energy is extracted from the propagating

wave or is redirected by virtue of the inhomogeneous nature of the media. The ultrasonic velocity and the characteristic acoustic impedance,

which can be determined with the addition of density information, embody within them both the inertial and restoring parameters of the particular materials. Thus, knowledge of the ultrasonic

velocity and loss terms may provide a basis for developing tissue signatures for various biological materials.

The paper will deal with the ultrasonic propagation properties of tissues beginning with the elemental constituents. As water, soft tissues,

and organs have very much the same densities and compressibilities, it is instructive to begin a review with properties of aqueous media.

2. Biological Molecules in Solution

A. Water

The measured ultrasonic absorption in water is proportional to the square of the frequency, over

the range 10"^ to 10"^ MHz, with the frequency-free

absorption coefficient, a/f^, having a constant

value of 15.7 x iQ-i^ s2/cm at 37 °C. The magnitude of this absorption is greater than one would

expect from consideration of the so-called classical absorption due to viscosity and thermal conductivity. This absorption in excess of the classical value has been attributed by Hall [1]^

to a structural relaxation mechanism involving a transition between two possible quasi-crystalline

states for water. More recent experimental re- sults [2] are consistent with the hypothesis that water undergoes a structural relaxation characterized by a time constant of lO'^^ seconds, and supports the idea that water is a mixture of two

or more states and that the relaxation processes consist of the independent jumping of molecules

from one state to another.

The velocity of sound propagation in pure water

exhibits a maximum at 75 °C due to the existence

of a minimum in the product of density and adiabatic compressibility at that temperature [3]. Similar behavior is exhibited by dilute aqueous

solutions, although the temperature of maximum

velocity may be decreased since the solutes modify

the structural arrangements of water. The velocity in water has been measured most precisely by

McSkimin [4], Greenspan and Tschiegg [5], and DelGrosso and Mader [6].

B. Amino Acids

Since it has been observed that proteins play a dominant role in the absorption properties of tis-

' Figures in brackets indicate literature

references at the end of this paper.

19
sues, aqueous solutions of amino acids and polypeptides require attention, for completeness.

When dissolved in water without additional ionic

constituents to influence the state of charge of

the amino acid, the solution exhibits a magnitude

of the frequency-free absorption parameter, a/f^,

which varies little with frequency in the megahertz range, and differs only slightly from that

of the solvent, water [7-12]. Amino acids in aqueous solution at neutral pH may be considered

according to their action of structure making or structure breaking in the solvent. Herein, the amino acids are present as doubly charged molecules

(zwitterions ) and are susceptible to dissociation

and recombination reactions upon a change of their

environment. Hydrogen-bonding sites are located

on both the amino and carboxyl groups, while the side chain may be acidic, nonpolar, or basic. Thus, the potential for breaking or making structure, in the vicinity of the solute molecules are considerable. Hammes and Pace [7] suggested that

the predominate ultrasonic absorption mechanism in aqueous solutions of glycine, diglycine, and tri- glycine is that which involves solute-solvent

(water) interaction. When the pH of an amino acid aqueous solution is within the range of 2 to 4 or

11 to 13, the relaxational behavior can be described by a single relaxation frequency. A number of amino acids have been investigated as a function

of pH, viz . , glycine [9,13-16], serine and threonine [8], glutamic acid, aspartic acid and alanine

[14], and arginine and lysine [10,15]. Absorption

maxima have been observed within the pH ranges

2 to 4, and 11 to 13, with such peaks being de- scribed quantitatively by assuming that the protontransfer reaction dominates the absorption.

C. Polypeptides

When the amino acids are formed into polypeptide chains, the absorption increases dramatically,

and the mechanisms believed to be responsible for

the absorption in tissues may begin to appear. In general, aqueous solutions of polypeptides at neutral pH exhibit an ultrasonic absorption behavior greatly increased over those of amino acids in solution or of water, and with a somewhat lesser

than the square-of-frequency dependence. The absorption in aqueous polypeptide solutions may

involve any or all of the following four possible

mechanisms, vi

z

. , proton transfer, helix-coil

transition, solvation, and relaxation of the shear

viscosity. Major interest has tended to be focused

on the proton-transfer reactions [17-20] and helix-coil transitions [21-24].

D. Proteins

Continuing with increasing complexity of the biological media, the polypeptides may be con- sidered to be arranged in a particular, -ubiquitous way to form the globular proteinaceous state. Hemoglobin and serum albumin solutions have re- ceived considerable attention, partly because of

the availabilities of the materials. Special con- sideration is given to other macromolecul ar species

such as nucleic acids and polysaccharides.

When biological macromolecules , such as the globular protein hemoglobin are in aqueous solution,

a certain amount of the solvent becomes an inherent

part of the molecule since the polymer possesses

ionic and polar groups which associate with water

molecules. In addition, proteins contain a number

of nonpolar side chains such that, within the vicinity of the macromolecules, some water structuring occurs. Thus, it is possible that the structure of liquid water, the hydration layer,

increases in the neighborhood of the biological

macromolecule. It is considered, therefore, that

as an acoustic wave propagates through an aqueous solution of biopolymers, it perturbs the hydration

layer manifesting absorption of energy by a structural relaxation process. The role of molecular

conformation of the biopolymer has also been con- sidered as the origin of the observed ultrasonic

absorption. Figure 1 shows the excess frequencyfree absorption per unit concentration for several biomacromolecules and supports the view that struc- turing contributes to the ultrasonic absorption

spectra [25]. Both dextran [26], a carbohydrate,

and polyethylene glycol [27], a synthetic polymer,

assume random coil configurations in aqueous solution and exhibit absorption magnitudes similar to that of gelatin. Hemoglobin has a quaternary

structure, bovine serum albumin and ovalbumin have tertiary structure, polyglutamic acid [28], a syn- thetic polyamino acid, has secondary structure,

and the double helix, DNA, has a rigid rod con- formation [29]. However, hemoglobin in 5 molar

aqueous guanidine hydrochloride solution exists

as a random coil [30] and yet exhibits ultrasonic

absorption spectra similar to that of hemoglobin

in aqueous solutions [31]. The importance of molecular spatial arrangement is thus an unsettled

question, though the polypeptide structure appears

to be of considerable significance.

1

1 1

1 1 ' 1 1 1 1 M 1. ^DNA-SS 10 °c : ^BSA- OX,IO°C / \ x>0^\ / ^ > / voO^

/ vO-

- Hb-0X,IO°C ^ .OM -ox,io°c

f DNA-CT,I0°C^"^ ^ ^PGA pH 5.8 ,25°C -_

^^ DEXTRAN, 20°C -

- PEG, 20.7 "C^ /Hb,25°C

PEG, 4.2°C

ll,1 1 1^ t 1 1 1 1 1 1 I I l^l I 1 1 1 1 1 I 10 100 1000

frequency ( MHz

)

Fig. 1. Excess frequency-free ultrasonic absorption per unit concentration [25].

Within figure 1, bovine serum albumin and hemo- globin have a molecular weight of 68,000 while

that of ovalbumin is 46,000. e-lactoglobin [32] (not on graph) with a molecular weight of 35,000,

would fall in the range determined by hemoglobin,

bovine serum albumin, and ovalbumin, while lyso- zyme [32] (not on graph) with a molecular weight

of 14,600, would appear between hemoglobin at

25 °C and dextran. Two random coil polymers, dextran and polyethylene glycol, have been studied

as a function of molecular weight. For dextran solutions, the frequency-free absorption per unit concentration increases with increasing molecular

weight to a molecular weight of about 10,000,

which corresponds to approximately 100 monomer

units, beyond which it is independent of molecular

20
weight [33]. Aqueous polyethylene glycol solu- tions show similar absorption behavior in that be- yond a molecular weight of about 4500, which also corresponds to a chain length of about 100 monomer

units, the absorption is independent of molecular

weight [27]. Thus, ultrasonic absorption depends

to some degree upon molecular weight. Possibly

beyond about 100 monomer units, the macromolecule

assumes random coil characteristics.

It is uncertain whether the absorption mechanism(s) responsible for energy loss in biological

polymer solutions (usually of concentrations less than 10 percent by weight) are the same as those responsible for the absorption properties of tissue [34]. Kremkau and Carstensen [11] have sug- gested that more highly concentrated macromolecular

solutions, promoting solute-solute ( intermolecul ar

interactions, may better approximate the tissue

environment, and from the point of view of biological effects, may be the most important level at which the ultrasound interacts. In the case of dilute solutions, where the absorption is con- sidered to vary linearly with polymer concentration, the mechanism of absorption is attributed to processes involving the interaction between the solvent (usually water) and the solute. In other

than dilute solutions, the absorption is found to increase nonlinearly, and it has been suggested

that this phenomenon is due to intermol ecul ar in- teraction processes [34-36]. It has recently been

shown [37], from absorption measurements of bovine serum albumin, to concentrations of 40 g/100 ml, over the frequency range 3.4 to 15 MHz, and at

20 °C, that the absorption dependence upon con- centration does not possess a linear region.

Here, the excess ultrasonic absorption can be de- scribed adequately by a concentration dependence

to the 1.2 power. It thus appears essential to consider intermolecular interaction over the en- tire range.

3. Tissues

The nearly linear frequency dependence of at- tenuation in liver, kidney, brain, muscle, fat, and other parenchyma, are considered in the ap- proximate frequency range of 100 kHz to 100 MHz,

and the recent findings with regard to the tem- perature dependence are discussed. Several tissues and organs, such as bone, lung, refractive

media of the eye, and collagenous tissues, are singled out for special detailed consideration.

It is shown that classification of tissues according to certain ultrasonic propagation properties

can be carried out with regard to water and collagen content, and with regard to certain teleological considerations. Pulmonary tissue is an exception here.

A. Frequency Dependence

The dependence of the ultrasonic absorption co- efficient upon the acoustic frequency has been studied by numerous investigators. Goldman and Hueter [38] prepared an early compilation of ultra- sonic velocity and absorption data in mammalian

soft tissues. Therein it is seen that the velocity, excluding lung, is very nearly that of dilute

salt solutions and varies only slightly among

those tissues. Fatty tissues are exceptions in having a velocity about 10 percent less than the others. Figure 2, taken from their paper, is a graphical representation of the acoustic amplitude

absorption coefficient per wavelength for several mammalian tissues in the frequency range of ap- proximately 200 kHz to 10 MHz. As they attempted

to include all measurements available at that time,

by numerous investigators employing different ex- perimental techniques, the scatter of the data exhibited by the bands, or broad shaded regions is thus not wholly surprising since many neglect to give either complete specifications of their ex- perimental procedure or a description of the state

of the specimen used. For example, it is not possible, in many cases, to determine from the literature the temperatures employed by the investigators

reporting the data. It is, however, possible to discern several relatively simple relationships.

For example, the absorption per cycle, a/f, is generally constant over the frequency range considered. For fat, a/f increases slightly in the frequency range from 1 to 10 MHz. The experimental results for striated muscle and liver appear to exhibit a minimum in the neighborhood of 2 MHz. Kessler [39] has shown that for kidney the linear

dependence of the attenuation on frequency exists

to about 100 MHz, after which a square law (or

greater) dependence exists. Fry [40] has con- sidered a viscous mechanism for the absorption of ultrasound in tissue, in which it is shown that

the viscous forces acting between a suitably chosen

distribution of suspended particles (or structural elements) and a suspending liquid can account for

the experimentally observed linear relationship be21
tween acoustic absorption coefficient and ultrasonic frequency. The frequency band over which

linearity obtains (in the model) is determined by the limits of the distribution Of values for the parameters chosen to describe the structural elements. Below the linear range the theory predicts

a quadratic dependence, in agreement with ex- periment.

Figure 3 is another way of presenting the data which may be suggestive for determination of mechanisms of absorption [41]. Here, the logarithm of the absorption coefficient is plotted as

a function of the logarithm of the ultrasonic fre- quency, and the slopes of the resulting curves are examined (the slope is the exponent of frequency

upon which the magnitude of the absorption coefficient depends). Figure 3 shows data for several materials of increasing biological complexity,

exhibiting correspondingly increasing complexity

in absorptive behavior. The urea solution exhibits

a slope of 2, indicative of classical viscous

absorption for which a/f^ is a constant. Homogenized milk, a suspension of fat particles and hydrated casein complexes, exhibits a slope of nearly unity from approximately 1 to 40 MHz. Be- havior of this type cannot be explained in terms

of simple viscosity or scattering theories. The curves of the absorption coefficients of egg al- bumin, brain tissue, liver, and striated muscle

(not shown in fig. 3) exhibit slopes between 1 and

2 in the neighborhood of 1 MHz and approach a slope

of 2 at higher frequencies. Hueter [41] has sug- gested that this type of frequency dependence can

be described for specific muscle preparations by

a double relaxation process in which the bulk

(volume) viscosity of the tissue possesses a relax- ation frequency near 40 kHz, and the shear viscosity

possesses a relaxation near 400 kHz. Although it is conceded that this is an oversimplification of a complicated process, it will be shown below that the temperature dependence of the acoustic absorption

coefficient lends support to this view.

m 1.0 -o 8 S 6 I I § 3 ct 2

0.1

0.02

1 1 1 1 1 1 1

1

whole liver, -^

1 hour \

fresh brain —

1

1 1 1 1 y 1

// / / / /

/ // /

1 //^XT\\\Y. /

/ '//

' / /

/ / -

/

^

^_

liver homog

1 hour /

/// —y-—

/A / // /

/''^ ^egg white /

lOm.urea^ /

1 / 1 1 1 1 1 1

1 1 1

0.1 1.0 10 *50

frequency in (MHz)

Fig. 3. Acoustic amplitude absorption coefficient

versus frequency for materials of different biological complexity [41].

B. Temperature Dependence

Details of the absorption coefficient as a function of temperature and frequency have re- cently become available. Figure 4 shows observations on mammalian central nervous system, the only tissue for which such data are available.

0.8

O.G

eo

0.2

0.26 MHz

0.5 MHz

0.7 MHz

"^'^^ 4.2 MHz

Fig. 4. Frequency and temperature dependence of ultrasonic absorption in mammalian central nervous tissue [43].

The curves for 0.26, 0.5, 0.7, and 1 MHz rep- resent in vivo measurements in the spinal cords

of neonatal mice (essential poi ki 1 otherms

)

[42-44] and those for 4.2 MHz are in vitro measurements in brains of adult cats (homeotherms) [45]. The relatively complex behavior of the frequency-free absorption coefficient with

frequency and temperature suggests a family of curves whose maxima decrease in magnitude, and oc- cur at ever higher temperatures, as frequency in- creases, supporting the suggestion mentioned

above. It is not known whether other soft tissues exhibit similar behavior but Kishimoto [46] has observed a positive temperature coefficient

for the absorption coefficient of bone in the frequency range 1.4 to 4.5 MHz. These data il- lustrate the necessity for complete specification

of the state of specimens when reporting experimental results.

C. Absorption and Velocity in Bone

Bone is a tissue possessing acoustic propagation properties greatly different from those of

the soft tissues discussed previously. An early

study of specially prepared skull bone, in the frequency range 0.6 to 3.5 MHz (25 to 35 °C),

yielded a quadratic dependence of the absorption

coefficient upon frequency with a transition to a linear dependence beyond about 2 MHz [47]. An average value found for the acoustic amplitude

22
absorption coefficient per unit path length in skull bone, in the neighborhood of 1 MHz, was of

the order of 1 cm"^, approximately an order of magnitude greater than that of soft tissues of the same temperature. However, recent observations

have called these values into question, and Adler

and Cook [48] have obtained absorption measurements of 1.5 cm"^ and 2.2 cm"^ in freshly frozen

dog tibia at room temperature at, respectively,

3 and 5 MHz. Reports of measurements of the longitudinal speed of sound in bone are largely in agreement that it is approximately twice that of

soft tissues [46,48-50]. Anisotropy of elastic

properties and variations in density of bone present special problems for measurement and for interpretation of results [48-50].

D. Refractive Media of the Eye

Begui [51] has studied the acoustic properties

of the refractive media of the eye in vitro . He determined the ultrasonic absorption coefficient

of the aqueous and vitreous humors at 30 MHz and that of the lens at 3 MHz. The specimens were ob- tained from excised fresh calf eyes. At 30 MHz

and 27.5 °C, the aqueous and vitreous humors both exhibit an acoustic amplitude absorption coefficient of 0.35 cm"^. Since this is approximately

50 percent greater than the absorption coefficient

of dilute salt solutions, it suggests that the ab- sorption coefficients of the humoral media of the calf eye possess a viscous-type dependence upon frequency; that is, the absorption coefficient

probably increases as the square of the frequency.

The lens of the calf eye exhibits a value of 0.7

cm"-' for the acoustic amplitude absorption coef- ficient at 3 MHz and 28 °C. Since the lens con- tains a relatively high concentration of protein,

it is reasonable to assume, in the absence of further information, that the frequency dependence

of the absorption coefficient of the lens re- sembles that of other soft tissue for which the absorption appears to be dominated by the protein

content, i.e ., it is probable that the absorption

coefficient per unit path length of the lens varies approximately with the first power of the frequency. Some investigators currently using

ultrasonic methods for diagnosing disorders of

the human eye feel that the lens absorption value

given by Begui is larger than that for the human

lens in vivo . The possible discrepancy may result because of species differences. Indeed, Begui

observed that the viscosity of the intraocular

fluid of calf eyes is greater than the values normally stated for the fluid media of human eyes. Further, the specimens used by Begui were first

stored (at temperatures in the neighborhood of

0 to 5 °C) and were used for measurement purposes

within a time interval of 10 days. Begui obtained

for the speed of sound in refractive media of the

eye 1497 m/s for the aqueous humor, 1516 for the vitreous humor, and 1616 for the lens.

E. Pulmonary Tissue

Two earlier studies [52,53] showed that ultrasonic attenuation in freshly excised dog lung was unusually high, that the speed of sound was con- siderably less than that of water, and that both

of these quantities had a strong dependence on pulmonary inflation and acoustic frequency. It was also shown that a pathological condition involving an accumulation of liquid-like matter

within the pulmonary architecture, had the effect

of appreciably reducing both the attenuation and

the velocity. Two recent studies have provided

details of the frequency and inflation dependencies.

Dunn [54] has shown that for excised dog lung of inflation to a fraction of residual air, such that

the specimen density is 0.4 g/cm^, the attenuation

increases exponentially from 4 cm"^ at 1 MHz to

12 cm~i at 5 MHz. In this same frequency range,

the speed of sound increased linearly from 0.66 x 10^ cm/s to 1.2 X 10^ cm/s. These findings are in general agreement with those of Bauld and Schwan

[55] who also showed that, for fixed inflated

specimens, the energy reflected at the lung-liquid

interface ever increases the gaseous inflation

allowing for lesser amounts of energy to enter

the lung.

4. Role of Collagen

Collagen is the most abundant single protein in the human body and the most common protein in the animal kingdom. It is closely associated in con- nective tissue of vertebrates and comprises be- tween one-quarter and one-third of the total protein in the human body, being about six percent of the total body weight [56]. However, more

than the prevalence of collage in the body, there

is some evidence to suggest that its contribution

to the elastic properties of most soft tissues,

together with other structural proteins, determines acoustic contrast during echographic visualization [57,58]. This hypothesis is based on the fact that the static or low- frequency elastic

modulus of collagenous fibers is at least 1000 times greater than those of soft tissues. Since

the ultrasonic velocity is proportional to the square root of the elastic modulus, collagenous

tissues are thought to introduce a greater im- pedance mismatch than would be the case for a soft tissue interface, thereby increasing the acoustic

reflectivity. The increased deposition of collagen

and the concomitant increase in attenuation seen

in many pathological conditions is a basis for ultrasonic differential diagnosis.

Table 1 contains ultrasonic attenutati on , ve- locity, water content, total protein content, and collagen content for various tissues [59]. It is apparent that the greater the collagen content,

the greater the attenuation. Dependence of at- tenuation and velocity upon water content are also apparent. These data allow empirical relations

to be formed for more quantitative assessment of the role of collagen content of tissues upon their

ultrasonic propagation properties. For example,

figure 5 represents a summary of table I of the ultrasonic attenuation at 1 MHz as a function of

the wet weight percentage of collagen for ten tissues. Using linear regression by the method of

least squares, a reasonable fit to the data is provided by the relation

A = 0.17 C°-3, (1)

where A is the ultrasonic attenuation in cm"^ and

C is the wet weight percentage of collagen. The best fit parameter, the coefficient of determination, r^, yields a value of 0.71 (unity represents

a perfect fit). Equation 1 is represented on figure 5 by the solid straight line. Logarithmic,

exponential, and linear functions were also analyz23
Table 1. Ultrasonic attenuation and velocity for tissues of various

water, protein and collagen content. Tissue Attenuation at Velocity Water Protein Collagen

1 MHz (cm-i) (m/s) (%) (%) (%)

Water (20 °C) 0.0003 1483 100 Amniotic fluid 0.0008 1510 97 0.27 Agueous humor 0 10 - 0.017 QQ u . UU J - 1 Vitreous humor 0 10 - 0.017 1 D 1 0 QQyy - QQyy y U . - U . £13 0.014 - 0.06;

r c r Lor 0.0012 1 A QQ 1 0 1 D QQyy (J, UJ

PI a sma 0.01 1 0/ 1 y u

- QRy D7

Tes ti

s

0.019 (absorption)

Q/l trace

Blood 0.02 1571 74 - 83 Milk 0.04 1485 87 3 - 4 Fat 0 04 - 0.09 1410 - 1479 10 - 19 5 - 7 yes

Spl een 0.06 1520 - 1591 76 - 80 17 - 18 0.5 -1.2

Liver 0 07 0.13 1 550 - 1607 68 - 78 20 - 21 0.1 -1.3

Kidney 0 09 - 0.13 1558 - 1568 76-83 15 - 17 0.5 - 1.5 Brain 0 09 - 0.13 1510 - 1565 75 - 79 10 10 0.04 - 0.3

Spinal cord 0 09 - 0.12 64 - 80 Striated muscle

against grain

with grain

0

0

18 - 0.25

08 - 0.12 0.16

1 DDO - 1592 -

1 576 -

1 cnQ 1 oUi 1603

1587

66 - 80 on 91 0.7 - 1.2

Heart 0 25 - 0.38 1572 77 - 78 17 0.4 - 1.6 Tongue

against grain

with grain

0.58

0.28

1 ETC 1 0/0 1585

62 - 68 14 - 17

Lens 0 10 - 0.20 1616 63 - 69 30 - 36 Articular capsule 0.38 Integument 0.40 1498 60 - 72 7 - 30 Cartilage 0.58 1665 23 - 34 70 49 - 63 10 - 20 Tendon

against grain

with grain

0.54

0.58 1750

63 35 32

0.01

tissue collagen (percentage) Fig. 5. Attenuation at 1 MHz as a function of the percentage of tissue

collagen for 10 tissue types [59].

24
ed but yielded worse fits than equation 1. Similarly, to a first approximation, the ultrasonic

velocity was examined as a function of collagen content for 8 tissues, excluding integument, and yielded the expression

C = -1700 + 230 In v, (2)

where v is the ultrasonic velocity in meters/second

and r^ = 0.91. Again, first approximations for wet weight percentage of total protein, P, yielded

A = 0.004 pi-26, r2 = 0.77, (3)

for 16 biological materials excluding integument.

Thus to a first approximation there appear to be mathematical relationships which can be developed

to relate the amount of tissue constituents to the ultrasonic propagation properties. There are some tissues, such as fat and integument, which may

have to be treated separately but, otherwise, this approach suggests that such relationships may aid

in developing ultrasonic tissue signatures which

can be incorporated into clinical instrumentation.

5. Concluding Remarks

What emerges from all this is summarized in table 2, following Dussik and Dunn [50,61], which

is an attempt to characterize tissues according

to their ultrasonic propagation properties and biological function. It is seen that tissues can

be grouped according to apparent teleology fashion

with relatively narrow ranges of attenuation

values within each group. The attenuation approximately doubles from group to group in the direction of increasing attenuation, and the speed of sound increases in the same direction. Further,

proceeding from group to group in the same direction, tissues of ever-decreasing water content and ever-increasing structural protein content become

included. Thus, it is seen that ultrasonic at- tenuation and velocity may be invoked to characterize tissues according to functional, structural,

and teleological criteria. Possibly detailed mea- surements will allow assignment of resolvably

unique values to each tissue structure, including

usefully differentiable values for pathological

states. Should this be the case, ultrasonic

attenuation and impedance values, as functions

of state and acoustic parameters, media, etc .

,

should specify uniquely tissues for diagnostic

purposes

Acknowledgment

The authors acknowledge gratefully the partial

support for portions of the activities described

herein by grants from the National Institutes of Health.

Table 2. Average attenuation of tissues by categories.

Tissue

attenuation

categories

Attenuation

at 1 MHz

(cm-i) Ti ssue Assumed

teleology

General trends

1. Very low

2. Low

3. Medium

4. High

5. Very high

0.03

0.01

0.06-0.07

0.08-0.11

0.11 0.08-0.16

0.23

0.3

0.4

0.5

0.6

1 or more

> 4

serum

blood

adipose tissue

nervous tissue

1 i ver muscle

heart kidney

integument

tendon

carti lage

bone (mineralized)

pulmonary tissue

ion , metabol ic , etc .

transport convection

energy and (water)

storage

physiological

function

parenchymal

tissue

structural integration

stromal tissues

skeletal framework

gaseous exchange

Increas- Increasing ing struc- speed

tural of protein sound content

Increasing H2O content

References

[1] Hall, L., The origin of ultrasonic absorption in water, Phys. Rev . 73, 775 (1948).

[2] Davis, C. and Jarzynsky, J., Liquid Water- Acoustic Properties: Absorption and Re- laxation, Chapter 12 in The Physics and Physical Chemistry of Water , Vol . I of Water:

A Comprehensive Treatise , F. Franks, ed.,

(Plenum Press, New York, 1972).

[3] Willard, G. W. , Temperature coefficient of

ultrasonic velocity in solutions, J. Acoust . Soc. Am . 19, 235 (1947).

[4] McSkimin, H. J., Velocity of sound in distilled water for the temperature range 20 °C - 75 °C, J. Acoust. Soc. Am . 37, 325 (1965).

[5] Greenspan, M. and Tschiegg, C. E., Speed of

sound in water by a direct method, J. Res . Natl. Bur. Std . 59 249-254 (1957).

[6] DelGrosso, V. A. and Mader, C. W. , Speed of

sound in pure water, J. Acoust. Soc. Am . 52 ,

25
1442-1446 (1972).

[7] Hammes, G. G. and Pace, C. N., Ultrasonic

absorption measurements in aqueous solutions

of glycine, diglycine, and triglycine,

J. Phys. Chem . 72, 2227 (1968).

[8] White, R. D., Slutsky, L. J., and Pattison,

S., Kinetics of the proton transfer reactions of serine and theronine, J. Phys . Chem . 25, 161 (1971).

[9] Hussey, M. and Edmonds, P. D., Ultrasonic

examination of proton-transfer reactions in aqueous solutions of glycine, J. Acoust . Soc. Am . 49, 1309 (1971).

[10] Hussey, M. and Edmonds, P. D., Ultrasonic

examination of proton-transfer reactions at

the a-amino and side-chain groups of arginine

and lysine in aqueous solution, J. Acoust . Soc. Am . 49, 1907 (1971).

[11] Kremkau, F. W. and Carstensen, E. L.

,

Macromolecular Interaction in Sound Absorption, in Interaction of Ultrasound and Biological Tissues--Workshop Proceedings , J. M. Reid and M. R. Sikov, eds., DHEW Publication (FDA) 73-8008 BRH/DBE 73-1,

p. 37 (U.S. Government Printing Office,

Washington, D.C. 1972).

[12] Kremkau, F. W., Macromolecular Interaction

in the Absorption of Ultrasound in Biological Material, Ph.D. Thesis, University of Rochester (1972).

[13] Maass, G., Ph.D. Thesis, University of Gottingen (1962).

[14] Applegate, K. , Slutsky, L. J., and Parker,

R. C, Kinetics of proton-transfer reactions

of amino acids and simple polypeptides,

J. Am. Chem. Soc. 90, 6909 (1968).

[15] Hussey, M. , Proton Transfer at Side Chain

Groups: A Mechanism for the Absorption of Ultrasound in Protein Solutions, Ph.D. Thesis, University of Pennsylvania (1970).

[16] Hussey, M. , Proton Transfer Processes: One of the Modes of Interaction of Ultrasound

with Proteins and DNA, in Interaction of Ultrasound and Biological Tissues , J. M. Reid and M. R. Sikov, eds., DHEW Publication

(FDA), 73-8008 BRH/DBE 73-1, p. 31 (U.S. Government Printing Office, Washington, D.C. 1972).

[17] Zana, R. and Tondre, C, Ultrasonic studies

of proton transfers in solutions of poly-

(lysine) and poly(ornithine) . Implications

for the kinetics of the helix-cord transition of polypeptides and for the ultrasonic

absorption of proteins, J. Phys. Chem . 76 1737 (1972).

[18] Lang, J., Tondre, C, and Zana, R. , Effect

of urea and other organic substances on the ultrasonic absorption of protein solutions,

J. Phys. Chem . 75, 374 (1971).

[19] Zana, R. and Lang, J., Effect of pH on the ultrasonic absorption of aqueous solutions

of proteins, J. Phys. Chem . 74, 2734 (1970).

[20] Applegate, K. , Slutsky, L. J., and Parker,

R. C, Kinetics of proton-transfer reactions

of amino acids and simple polypeptides, J^. Am. Chem. Soc . 90, 6909 (1968).

[21] Doty, P., Wada, A., Yang, J. T., and Blout,

E. R. , Polypeptides: VIII, molecular con- figurations of poly-L-glutamic acid in water-dioxane solution, J. Polymer Sci . 23, 851 (1957).

[22] Barksdale, A. D. and Stuehr, J. E., The kinetics of the helix-coil transition in aqueous poly-L-glutamic acid, J. Am. Chem . Soc . 94, 3334 (1972).

[23] Schwarz, G., On the kinetics of helix-coil

transition of polypeptides in solution,

J. Mol. Biol . n_, 64 (1965).

[24] Wada, Y., Sasabe, H., and Tomono, M.

,

Viscoelastic relaxations in solutions of poly-(glutamic acid) and gelatin at ultra- sonic frequencies, Biopolymers 5, 887 (1967).

[25] Dunn, F., Acoustic Properties of Biological

Materials, in Fundamental and Applied

Aspects of Nonionizing Radiation , S. M. Michaelson and M. W. Miller, eds., p. 21 (Plenum Publishing Corporation, New York,

1975).

[26] Hawley, A. S., Kessler, L. W., and Dunn, F. , Ultrasonic absorption in aqueous solutions

of high-molecular-weight polysaccharides,

J. Acoust. Soc. Am . 38, 521 (1965).

[27] Kessler, L. W., O'Brien, W. D., Jr., and Dunn, F., Ultrasonic absorption in aqueous solutions of polyethylene glycol, J. Phys . Chem . 74, 4096 (1970).

[28] Burke, J. J., Hammes, G. G., and Lewis,

T. B., Ultrasonic attenuation measurements

in poly-L-glutamic acid solutions, J. Phys . Chem. 42, 3520 (1965).

[29] O'Brien, W. D. , Christman, C. L., and Dunn,

F., Ultrasonic investigation of aqueous solutions of deoxyribose nucleic acid,

J. Acoust. Soc. Am . 52, 1251-1255 (1972).

[30] Kawahara, K. , Kirscher, A. G., and Tanford,

C, Dissociation of human co-hemoglobin by urea, guanidine hydrochloride and other

reagent. Biochemistry 4, 1203 (1965).

[31] O'Brien, W. D., Jr. and Dunn, F. , Ultrasonic

examination of the hemoglobin dissociation

process in aqueous solutions of guanidine

hydrochloride, J. Acoust. Soc. Am . 50 , 1213-

1215 (1971).

[32] Lang, J., Tondre, G., and Zana, R., Effects

of urea and other organic substances on the ultrasonic absorption of protein solutions,

J. Phys. Chem . 75, 374 (1971).

26
[33] Hawley, S. A. and Dunn, F., Ultrasonic ab- sorption in aqueous solutions of dextran,

J. Chem. Phys . 50^, 3523 (1969).

[34] O'Brien, W. D. , Jr. and Dunn, F., Ultrasonic Absorption by Biomacromolecules

in Interaction of Ultrasound and Biological

Tissues--Worl<shop Proceedings , J. M. Re id and M. R. Sikov, eds., p. 13, DHEW Publication (FDA) 73-8008 BRH/DBE 73-1 (U.S. Government Printing Office, Washington, D.C. 1972).

[35] Kessler, L. W. and Dunn, F., Ultrasonic

investigation of the conformal changes of bovine serum albumin in aqueous solution,

J. Phys. Chem . 73, 4256 (1969).

[36] O'Brien, W. D., Jr. and Dunn, F., Ultrasonic

absorption mechanisms in aqueous solutions

of bovine hemoglobin, J. Phys. Chem . 76 , 528 (1972).

[37] Goss, S. A. and Dunn, F., Concentration De- pendence of Ultrasonic Absorption in Aqueous

Solutions of Bovine Serum Albumin, in IEEE Ultrasonics Symposium Proceedings , p. 65 (1974).

[38] Goldman, D. E. and Hueter, T. F., Tablar

data of the velocity and absorption of highfrequency sound in mammalian tissues, J_. Acoust. Soc. Am . 28, 35 (1956); 29, 655 (1957).

[39] Kessler, L. W., VHF ultrasonic attenuation

in mammalian tissue, J. Acoust. Soc. Am . 53 1759 (1973).

[40] Fry, W. J., Mechanism of acoustic absorption

in tissue, J. Acoust. Soc. Am . 24, 412-415

(1952).

[41] Hueter, T. F., Viscoelastic Losses in Tissues

in the Ultrasonic Range, WADC Technical Re- port 57-706 (1958).

[42] Dunn, F., Temperature and amplitude dependence of acoustic absorption in tissue, J_. Acoust. Soc. Am . 34, 1545 (1962).

[43] Dunn, F. and Brady, J. K., Pogloshchenie

ul ' trazvyeka v biologicheski kh sredakh,

Biofizika 18, 1063 (1973). Translation,

Ultrasonic absorption in biological materials.

Biophysics 18, 1128 (1974).

[44] Dunn, F. and Brady, J. K. , Temperature and Frequency Dependence of Ultrasonic Absorption in Tissue, in Proceedings 8th International Congress on Acoustics , Vol. I, p. 366c (Goldcrest Press, Trowbridge, Wilts.,

1974).

[45] Robinson, T. C. and Lele, P. P., An analysis

of lesion development in the brain and in plastics high intensity focused ultrasound

at low megahertz frequencies, J. Acoust . Soc. Am . 51, 133 (1972).

[46] Kishimoto, T. , Ultrasonic absorption in bones, Acustica 8, 179 (1958).

[47] Hueter, T. F., Messung der Ultraschal labsorption in menschlichen Schadel knochen und ihre Abhangigkeit von der Frequenz, Naturwissenschaften 39, 21 (1952).

[48] Adler, L. and Cook, K. V., Ultrasonic para- meters of freshly frozen dog tibia, J. Acoust. Soc. Am . 58, 1107-1108 (1975T.

[49] Thiesmann, H. and Pfander, F. , Uber die

Durchlassigkeit des Knochens fiir Ultraschall,

Strahlentherapie 80. 607 (1949).

[50] Lang, S. B., Ultrasonic Method for Measuring

Elastic Coefficients of Bone and Results on Fresh and Dried Bovine Bones, IEEE Trans . Biomed. Eng . BME-17 , 101 (1970T^

[51] Begui, Z. E., Acoustic properties of the re- fractive media of the eye, J. Acoust. Soc. Am^ 26 , 365 (1954).

[52] Dunn, F. and Fry, W. J., Ultrasonic absorption and reflection by lung tissue, Phys . Med. Biol . 5, 401 (1961).

[53] Reid, J. M., Ultrasonic Diagnostic Methods

in Cardiology, Ph.D. Thesis, University

of Pennsylvania, 1965.

[54] Dunn, F., Attenuation and speed of sound in lung, J. Acoust. Soc. Am . 56, 1638 (1974).

[55] Bauld, T. J. and Schwan, H. P., Attenuation

and reflection of ultrasound in canine lung

tissue, J. Acoust. Soc. Am . 56^, 1630 (1974).

[56] White, A., Handler, P., and Smith E. L., Principles of Biochemistry (McGraw Hill Book

Co., New York, 1968).

[57] Fields, S. and Dunn, F., Correlation of echographic vi sual izabi 1 i ty of tissue with

biological composition and physiological

state, J. Acoust. Soc. Am . 54, 809-812 (1973).

[58] Kessler, L. W., Fields, S. I., and Dunn, F., Acoustic microscopy of mammalian kidney,

J. Clinical Ultrasound 2, 317-320 (1974).

[59] O'Brien, W. D. , The Role of Collagen in Determining Ultrasonic Propagation Properties in Tissue, in Acoustical Holography , L. W. Kessler, ed.. Vol. 7 (Plenum Press,

New York, 1977).

[60] Dussik, K. T. , Kyriazidov, M. , Fritch, D. J., and Srear, R. S., Measurement of articular

tissues with ultrasound, Amer. J. Phys. Med . 37, 160-165 (1958).

[61] Dunn, F., Ultrasonic Attenuation, Absorption,

and Velocity in Tissues and Organs, in Ul tra- sonic Tissue Characterization , M. Linzer,

ed. , National Bureau of Standards Special

Publication 453, pp. 21-28 (U.S. Government

Printing Office, Washington, D.C. 1976).

27

Reprinted from Ultrasonic Tissue Characterization II, M. Linzer, ed.. National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C., 1979).

ABSORPTION OF SOUND IN TISSUES

Edwin L. Carstensen

Department of Electrical Engineering

University of Rochester

Rochester, New York 14627, U.S.A.

In spite of extensive applications of ultrasound in diagnosis, therapy and even surgery, there are still many problems to be solved in the basic physics of sound propagation in tissues. Absorption of longitudinal ultrasonic waves occurs primarily

at the macromolecular level. There is evidence to indicate that this absorption can

be profoundly modified by macromolecular interaction. The specific structural or chemical relaxation mechanisms responsible for the absorption are unknown. Microscopic

inhomogeneities may lead to certain forms of relative motion viscous losses or thermal absorption. Macroscopic inhomogeneities in tissue affect sound propagation and can

lead to artifacts in certain methods of measurement of tissue absorption. Shear waves

are not important in the soft tissues of the body.

Key words: Absorption of ultrasound; macromolecular relaxation; relaxation phenomenon;

ultrasonic tissue absorption.

Although acoustic absorption phenomena play

an important role in every medical application

of ultrasound, we still have only a rudimentary

understanding of the responsible physical mechanisms forty years after the first work in this

field [1]^. This review of basic concepts at- tempts to outline what we know about these processes and to identify problems to be solved.

1. Absorption Data

Information on absorption of sound in tissues,

as it is available to us today, is outlined in figure 1. (A more complete summary of absorption data is included in the paper by Johnston

et al . [2].) Data for packed red cells are in- cluded iDecause we can think of this preparation

as a kind of simple model tissue and because it has been studied over a wide range of frequencies.

The absorption of sound in fatty tissue is significantly lower than the other soft tissues.

Bone is much lossier than other tissues of the

body. Water makes a negligible contribution to

the absorption of tissues at low frequencies.

Only a few measurements have been carried out above 10 MHz. We can guess that values of (aA) for soft tissues will follow the pattern set by

hemoglobin [3] and approach but remain significantly above that of water at frequencies of

the order of 1000 MHz. From acoustic microscopy

it is clear that sharp differences in absorption

among components of cells exist at frequencies

above 1000 MHz [4]. The range of values which have been reported

for a given tissue type is large. This results

^Figures in brackets indicate literature

references at the end of this paper.

in part from normal biological variability. In addition, there is a potential for error in measurement with i nhomogeneous tissue samples.

10"

2 5 2 5 2 5 2 5 0.1 1.0 10 100 1000 FREQUENCY (MHz)

Fig. 1. Absorption of sound in biological materials. Solid lines are estimates of mean absorption coefficients from many investigators. The range of reported values is large particularly for bone. The high

frequency extrapolation (dashed line) for concentrated red cells is based on measurements of hemoglobin solutions [3]. Ex Exprapolation of the data for soft tissues

(dashed line) to 100 MHz is based on meas- urements of kidney at 100 and 200 MHz

[35].

29
For example, we found that in measuring sample

attenuation with a phase sensitive receiver the apparent absorption for muscle could be as much

as four times its true value [5]. It is interesting that the radiation force method used by

Pohlman [1] in the first tissue absorption

studies is still perhaps the most reliable technique available. Acoustoel ectric receivers

show great promise for this kind of investigation [6]

.

Almost all of the absorption studies have

used excised tissue samples. Very few in vivo

tissue absorption measurements have been made;

but those few are in rough agreement with

values for excised tissue. It was reported that freshly excised liver had a much higher absorption than aged tissue samples at frequencies

near 1 MHz [7,8]. We have recently attempted

to duplicate these observations without success

[9]. Other aging studies have shown very little

change in absorption of tissues with time after excision [10]. From the information available,

it appears reasonable to assume that the data

in figure 1 are valid for living tissues, but we should realize that this is an assumption

which has not been thoroughly tested.

It is a surprising admission that after forty years of study we do not know the temperature

dependence of the absorption coefficient for all of the tissues of the body. The absorption co- efficients for blood [11], brain [12], and myocardial muscle [10] decrease slightly with tem- perature in the range 0 to 40 °C. One study

reports a positive temperature coefficient for bone between 0 to 60 °C [13], As discussed

below, mouse spinal cord is reported to have a complex temperature dependence [14].

This discussion, of course, concerns longitudinal ultrasonic waves in tissue. The propagation constants for shear waves in tissues are not known in detail. However, recent rough measurements indicate that transverse waves will not be generated in any of the soft tissues of the body

with any current medical application of ultrasound [9,15].

2. Macromol ecul ar Absorption

The primary absorption of ultrasound in tissue

appears to take place at the macromol ecular level. This was demonstrated directly by Pauly and Schwan

through a comparison in the absorption of sound

in liver tissue and a subcellular homogenate of the tissue [16]. The near identity of the two values suggests that tissue structure had little

influence on the absorption process.

A simpler biological system yields more de- tailed information. The absorption coefficients

for packed red cells and for a solution of hemo- globin at the same concentration in which it is found in the erythrocyte {'^ 30 g/100 ml) are es- sentially identical. This is shown as the upper curves in figure 2. Now, if a 26 percent suspension of red cells in physiological saline is pre- pared, the volumes of cells are the same as in the packed preparation. Thus, the local concentration and environment of the hemoglobin in the

cell remains the same, and hence the contribution

to the absorption from the hemoglobin should be

in direct proportion to amount of protein present

as shown by the dashed line in the figure 2 [17].

Saline contributes little to the absorption

30

2i

FREQUENCY (MHz)

Fig. 2. Absorption of sound in a suspension of bovine erythrocyte in physiological saline

[17,18]. Dashed curve is the macromolecular contribution to the absorption of the suspension (26% cells).

especially at low frequencies. Actual absorption measurements on such a suspension show that

the contributions of the hemoglobin solution in the cell accounts for most, but not all, of the observed loss. The excess absorption which

arises from the i nhomogeneous property of the medium will be discussed later. Since none of the smaller molecules or ions in the red cell makes a significant contribution to the absorption, it appears that the primary loss comes from the presence of the protein itself. Even the amino acid building blocks of hemo- globin have much smaller specific absorptions

( i.e ., absorption per gram solute) than the in- tact protein as shown in figure 3. In fact, the absorption of a 10 percent solution of amino

acids in the proportions found in hemoglobin is barely distinguishable from water itself, where1 0

—\ 1 1

1

1 1 11 1

1 2 5 2 5 2 5 105 107 108 109

f (Hz)

Fig. 3. Absorption of sound in a 10 percent

hemoglobin solution at 25 °C [18]. Treat- ment with the enzyme pronase fragmented

the protein yielding components with

molecular weight less than 10,000 and re- sulting in a decreased absorption. A prep- aration of amino acids in concentrations

equivalent to that in the hemoglobin solu- tion give absorption values which are hardly different than water alone.
as the absorption of a 10 percent solution of hemoglobin is ten times that of water at 10 MHz

[18]. A pronase-treated hemoglobin solution

yielding subunits with molecular weight less than 10,000 showed a somewhat smaller specific absorption than that of the intact protein. A more

subtle dissection of hemoglobin using quanidine

hydrochloride produced specific absorptions which

were both larger and smaller than that of intact

hemoglobin as the fractionation proceeded [19].

The "whole much greater than the sum of its parts" is not limited to hemoglobin or, for that matter, to proteins. Figure 4 shows a very similar relationship among polysaccharides. The

absorption for dextran is much greater than for simple sugars. It is interesting that the spe- cific absorption of dextran and Ficoll molecules

of the same molecular weight are roughly equal. Dextran is a long chain polymer whereas Ficoll

is globular. As a result, the macroscopic viscosity of equivalent concentrations of the two molecules is dramatically different. This is just one of many observations that virtually

eliminate classical viscous processes from con- sideration in tissue absorption.

^ 10-1

CM4-U

o

^ 2

9 MHz

sucrose

5 2 103

5 2

10"* 105 Molecular weight

Fig. 4. Specific absorption of polysaccharides

vs_. molecular weight [18]. Data for dextran are taken from reference [36].

Another polysaccharide, Ficoll, which

is nearly spherical and thus has a much

lower intrinsic viscosity than dextran,

has approximately the same specific

absorption as dextran.

A number of proteins, nucleic acids and polysaccharides have now been studied [2]. The spe- cific absorption values for the macromolecules

are uniformly greater than those associated with

the small molecules and ions which make up tissue.

3. Macromolecular Interaction

The increase in specific absorption with molecular complexity does not appear to stop at the macromolecular level. Association among macromolecules in some cases results in increased

values for the absorption per molecule. This is

a vague loosely defined concept and is not based

on any specific, postulated mechanism. However, there are a number of observations which seem to fit this generic heading. The specific absorption of hemoglobin increases dramatically with

1Q2-

5-

" "^insulin Ficoll

o-dextran [36]

2-

lOi5-

10°-

• - hemoglobin solution

- erythrocyte suspension i.

30 MHz

10 —I20 30 40 50 60 70

g Hb/100 cm3

Fig. 5. Absorption of hemoglobin as a function of concentration at 25 °C [18]. For frequencies greater than 10 MHz the absorption

coefficients of suspensions of red cells

are determined almost entirely by the hemoglobin which they contain [11].

concentration as shown in figure 5 [18]. At a concentration of 60 grams hemoglobin per 100 ml solution, where the mean spacing of molecules is very nearly equal to the molecular diameter, the absorption per molecule is five times greater

than its value in a dilute solution. Whether

by introducing a new mechanism or modifying an existing process, the interaction between macro- molecules as the concentration increases causes

a marked increase in the specific absorption.

There are many other clear examples where macromolecular interaction is associated with in- creased absorption. The hemoglobin in rat erythrocytes, when stored in sodium citrate at

4 °C for several days, becomes paracrystal 1 ine

(fig. 6) [20]. The specific absorption of para- crystalline cells is at least twice that of normal rat erythrocytes [ 18] . Treatment of red cells with acrolein cross links the hemoglobin

and leads to specific absorption values which

are four times greater than the values for normal erythrocytes as shown in figure 7 [21]. Other examples may be found in figure 8. It is interesting that the sediment from homogenized liver

has a specific absorption three times greater

than the "supernatant" from that preparation

[16]. Presumably the supernatant is a dilute

solution of macromolecules; whereas the sedi- ment consists of highly organized subcellular

particles

.

Perhaps these observations are no more than a series of coincidences. However, the information available today suggests that the trend to- ward increasing absorption with increasing interaction extends beyond the macromolecular level

to interactions among macromolecules.

31
acrolein-fixed erythrocytes hypertonic L

erythrocytes J

• paracrystalllne ^

rat erythrocytes Jerythrocyte '1 ghost membranej

yeast

normal rat "erythrocytes

dilute albumin normal bovine"L

erythrocytes J

-dilute hemoglobin

ficoll pronase treated Hb

amino acids

5.0 muscle tissue

liver nuclei

3.0

liver tissue

liver sediment

2,0

1-0

0.5

liver homogenate

DNA, RNA

liver 'supernatant'

dextran (MW > 30.000)

0.3

0.2

gelatin

amino acids

Fig. 6. Electron micrographic comparison of normal and paracrystal 1 ine rat erythrocytes.

103-

asp

5-

rdB/cm]

Lg/cm^J

2-

102-

IQi 102

f (MHz)

Fig. 7. Specific absorption for normal (o) and fixed {o,x,/\) bovine erythrocytes in aqueous suspension at 25 °C. Acrolein concentrations in the original fixing solutions were 0.3, 1.0 and 2 g/100 cm^. Cells were washed free of excess acrolein before meas- urement [21].

Fig. 8. Comparison of specific absorptions of biological materials using dilute hemo- globin as a reference. All data are for

10 MHz at 25 °C [18].

4. Relaxation Absorption

When stress-strain relationships for a medium

depend upon shifts in chemical or structural equilibria, it is possible that a sound wave propagated

in the medium will experience relaxation absorption.

Specifically, the absorption per wavelength is [22,23].

1 +

(1)

where t is the relaxation time of the internal sys- tem and c, cs, Cco are the phase velocity, and the

low and high frequency limits of the velocity re- spectively. As implied by the equation, the magnitudes of the absorption and the dispersion in the velocity are related. The relation has been tested quantitatively for hemoglobin [11]. The results are consistent with the hypothesis that a relaxation mechanism is responsible for the absorption

[24]. The first velocity dispersion measurements

reported for tissues support the hypothesis that relaxation absorption is involved in these materials as well as in macromol ecular solutions.

2To a very rough approximation we can write [11] aA * (f/c)(Ac/Af ). Kremkau [12] reports for brain values of aA * 0.015, in agreement with

figure 1, and velocity dispersion of around

1 m/s/MHz near 1 MHz.

32
Frequency (MHz)

Fig. 9. Relaxation absorption. Log (aX) vs^ log

frequency is plotted for three temperatues

under assumptions discussed in the text.

In this example, the activation energy is 20 kcal/mol. The value for (aX)niax fot" the illustration is arbitrary. With this model, the (aX) curves simply shift to the right, with log coq proportional to the in- crement in temperature.

The frequency dependence of (aX) given by eq.

(1) is shown in figure 9. For certain simple re- actions which may be perturbed by the sound wave,

we may write [25]

^

= . A e-E/f^T (2)

where E is the activation energy of the dominant

rate process in the internal system, T the absolute temperature, A and R are constants. If a reference temperature Tq is chosen so that

T = To + AT, we can write

log wo * constant + -—^ • (3)

The general behavior predicted by figure 9 is seen

in a variety of simple systems i.e. the curves

of log (aX) vs

log f shift to the right in increments proportional to the change in temperature. This is illustrated with MnSO^ solutions

in figure 10 [26]. The temperature coefficient

of the absorption is negative if observations

are carried out somewhat below the relaxation

frequencies, while it is positive at high fre- quencies. Figure 11 shows the temperature de- pendence of (aX) for relaxation absorption with

activation energies of 20 and 50 cal/mol. As an example, data for lecithin vesicles at 1 MHz are

shown [27]. Few biological materials can be characterized

by a single relaxation process. Rather, in most

cases there appear to be broad distributions of relaxation frequencies, in the case of hemo- globin, for example, extending from below 0.1 MHz to beyond 100 MHz (fig. 1). From our first

order model, we would anticipate that increasing

temperature would simply shift the curve of log

(aX) vs_. log f to higher frequencies. Where the

slope of this curve is slightly positive this

leads to small negative temperature coefficients

0.0

0.21 I I \ \ I \ I 0.2 0.4 0.6 1.0 2.0 4.0 6.0 10.0 Frequency (MHz)

Fig. 10. Absorption of sound in 0.5 molar MnSOi, solutions in water. Dashed curves represent the contribution of the low frequency relaxation to the absorption

[26].

10-2i

Temperature (°C)

Fig. 11. Relaxation absorption. Log (aX) vs_. temperature is plotted for activation

energies of 20 and 50 kcal/mol. As an example, data (o) for lecithin vessicles

[27] are shown.

for the absorption. Brain [12], blood [11], and heart muscle [10] (fig. 12) appear to have this

characteristic. The absorption per wavelength

in bone, as reported by Kishimoto [13] decreases

with frequency (fig. 13). As anticipated, this

leads to a positive temperature coefficient for

the absorption. In all of these materials, the activation energies are of the order of a few thousand kilocalories per mole.

33
The 1n v1vo data for mouse spinal cord [14] are unique among the limited sample of tissues

for which temperature dependence of absorption

has been studied (fig. 14). In contrast with

other tissues which appear to have many relaxation frequencies, mouse spinal cord at 2 °C shows a frequency dependence of (aA) which is too strong to be explained even by a single re- laxation frequency. In addition, the shape of

the log (aX) vs. log f curve changes with temperature. Because of these unusual properties, mouse

spinal cord appears to be a particular candidate

for further study. Since temperature studies

may provide general information about the properties of internal relaxing systems and in a sense

extend the range of frequencies observed, it would be desirable to have this information for

a broad range of tissues.

1.0

Fig. 12.

2 5 Frequency (MHz) 10.0

Absorption of sound by myocardium [10]. The data illustrate the pairing of a positive slope in log (aX) vs^. log fre- quency with a negative temperature coef- ficient for the absorption.

10-1

2-

10-

^s ingle

^v^relaxation time

1.0-

0.14 ^ , 12 1 5 10 Frequency (MHz)

Fig. 13. Absorption of sound by bone [13]. In this case the slope in log (aX) vs^. log

frequency is negative and the teniperature

coefficient of the absorption is positive

Frequency (MHz)

Fig. 14. Absorption of sound by mouse spinal cord

[14]. It appears the observations at

2 °C cannot be explained by relaxation

mechanisms.

Identification of the specific chemical or structural reactions which are responsible for relaxation absorption in tissues remains the pristine challenge of this field of study. Al- though some effort has been given to this problem, we must admit almost complete ignorance of

the nature of tissue relaxation mechanisms at a meaningful, basic level.

5. Microscopically Inhomogeneous Materials

Although the absorption of sound in blood oc- curs primarily at the macromolecular level, a significant, measurable, contribution at fre- quencies below 10 MHz arises from the presence of intact red cells in suspension (fig. 2). Scat- tering, viscous relative motion, and thermal absorption have been considered as possible mech- anisms for this excess loss [17,28-34]. Classical scattering is ruled out on qualitative and quantitative grounds. Relative motion absorption

occurs when, because of density differences be- tween suspended particle and suspending medium.

34
there is relative motion between the two phases

with a consequent viscous loss. A comparison of observed, excess, non-protein absorption for sus- pensions of red cells in physiological saline

with that predicted by theory for relative motion absorption is shown in figure 15 [17].

0.4 0.7 .0 2 4 Frequency (MHzI

20

Fig. 15. Comparison of non-hemoglobin absorption

in suspensions of red cells in saline

with that predicted by relative motion

absorption (solid curves). Points are

taken from the data in figure 2 and reference [17].

Thermal absorption arises when thermal expansion

coefficients and specific heats of particles and the suspending medium differ significantly thus leading to irreversible heat flow between the two phases. If extreme assumptions are made for the thermal properties of blood cells, the predicted

thermal asborption is almost as large as that predicted for viscous relative motion [33].

Definitive experiments to compare contributions

from the two mechanisms have not been attempted.

Present evidence, however, points to relative

motion as the dominant process. The suggestion

that relative motion may be important in the solid tissues [31,34] remains to be tested.

Acknowledgments

The author wishes to acknowledge the contribution of Dr. Robert Weed for the use of the electron micrograph of a paracrystal 1 i ne red cell. This review and much of the research reported

has been supported in part by U.S.P.H.S. Grant

GM09933.

References

[1] Pohlman, R., Ueber die Absorption des Ultraschalls im menschlichen Gewebe und ihre Abhaengi gkei t von der Frequenz,

Physik. Z . 40, 159-161 (1939).

[2] Johnston, R. L., Goss, S. A., Maynard , V., Brady, J. K. , Frizzell, L. A., O'Brien,

W. D., Jr., and Dunn, F., Elements of Tissue

Characterization. Part I. Ultrasonic Propagation Properties (this publication, p. 19).

[3] Edmonds, P. D., Bauld, T. J., Ill, Dyro,

J. F. , and Hussey, M., Ultrasonic absorption of hemoglobin solutions, Biochim. et Biophys. Acta 200 , 174-177 (1969y

[4] Lemons, R. A. and Quate, C. F., Acoustic

microscopy: biomedical applications.

Science 188, 905-911 (1975).

[5] Marcus, P. W. and Carstensen, E. L., Problems with absorption measurements of inhomogeneous solids, J. Acoust. Soc . Am . 58, 1134-1335 (1975).

[6] Busse, L. J., Miller, J. G., Yuhas, D. E. , Mimbs, J. W., Weiss, A. N., and Sobel , B. E., Phase Cancellation Effects: A Source of Attenuation Artifact Eliminated

by a CdS Acoustoelectric Receiver in Ultrasound in Medicine, 0. White, ed. Vol. 3, pp. 1519-1535 (Plenum Press, New York,

1977).

[7] Hueter, T. F., Visco-Elastic Losses in Tissues in the Ultrasonic Range, Wright Air

Development Center. Wright-Patterson AFB,

Ohio, Tech. Rept. No. 57-706, ASTIA Doc. No. AD142171 (August, 1968).

[8] Carstensen, E. L., The Mechanism of the Absorption of Ultrasound in Biological Materials, IRE Trans, on Med. Electronics . MET., 158-162 (1960).

[9] Frizzell, L. A. and Carstensen, E. L., Ultrasonic Heating of Tissues, University

of Rochester, Department of Electrical

Engineering Technical Report GM09933-20

(November, 1975).

[1^0] O'Donnell, M., Mimbs, J. W. , Sobel, B. E. , \ and Miller, J. G., Ultrasonic attenuation

of myocardial tissue: dependence on time after excision and on temperature, J^. Acoust. Soc. Am . (in press).

[11] Carstensen, E. L. and Schwan, H. P., Acoustic properties of hemoglobin solutions,

J. Acoust. Soc. Am . 31, 205-311 (1959).

[12] Kremkau, F. W., McGraw, C. P., and Barnes,

R. W. , Acoustic Properties of Normal and Abnormal Human Brain (this publication, p. 81)

[13] Kishimoto, T., Ultrasonic absorption in , bones, Acustica 8, 179-180 (1959).

[14] Dunn, F. and Brady, J. K., Ultrasonic ab- sorption in biological media, Biofizika

18, 1063-1066 (1973); Biophysics 18, 1128- 1132 (1974).

[15] Frizzell, L. A. and Carstensen, E. L., Shear properties of mammalian tissues at low megahertz frequencies, J. Acoust. Soc . Am. 60_, 1409-1411 (1976).

[16] Pauly, H. and Schwan, H. P., Mechanism of absorption of ultrasound in liver tissue,

J. Acoust. Soc. Am. 50, 692-699 (1971).

35
[17] Carstensen, E. L. and Schwan, H. P., Absorption of sound arising from the pres- ence of intact cells in blood, J. Acoust . Soc. Am . 31, 185-189 (1959).

[18] Kremkau, F. W. and Carstensen, E. L., Macromolecular Interaction in Sound Absorption, Proc. of Workshop on Interaction of Ultrasound and Biological Tissues, Battelle

Seattle Research Center, Food and Drug

Administration, U.S. Dept. of Health Education and Welfare, Rockville, Maryland

(1972), pp. 37-42.

[19] O'Brien, W. D. and Dunn, F., Ultrasonic

examination of the hemoglobin dissociation

process in aqueous solutions of guanidine

hydrochloride, J. Acoust. Soc. Am . 50 , 1213-1215 (1971'r

[20] Ponder, E. , The paracrystall i ne state of the rat red cell, J. Gen. Physiol . 29 , 89-102 (1945).

[21] Kremkau, F. W. and Carstensen, E. L., Macromolecular interaction in the absorption of ultrasound in fixed erythrocytes,

J. Acoust. Soc. Am . 53, 1448-1451 (1973).

[22] Kremkau, F. W. and Carstensen, E. L., Macromolecular Interaction in the Absorption of Ultrasound in Biological Material,

University of Rochester, Department of Electrical Engineering Tech. Report, No. GM09933-18 (April, 1972).

[23] Markham, J. J., Beyer, R. T., and Lindsay,

R. B., Absorption of sound in fluids.

Rev, of Mod. Phys . 22, 353-411 (1951).

[24] Eigen, M. and deMaeyer, L., Relaxation

Methods, in Technique o f Organic Chemistry , A. Weissberger, ed. , Vol . 8, Part II, pp. 895-1054 (Wiley, New York, 1963).

[25] Stuehr, J. and Yeager, E., The Propagation

of Ultrasonic Waves in Electrolytic Solu- tions, in Physical Acoustics , W. P. Mason,

ed.. Vol. 2, Part A, pp. 351-462 (Academic

Press, New York, 1965).

[26] Carstensen, E. L., Relaxation processes

in aqueous solution of MnSO^ and CoSO^,

J. Acoust. Soc. Am . 26, 862-864 (1954).

[27] Eggers, F. and Funck, T., Ultrasonic re- laxation spectroscopy in liquids, Natur- wissenschaften 63, 280-285 (1976).

[28] Epstein, P. S. , On the Absorption of Sound Waves in Suspensions and Emulsions, Theo- dore von Karman Anniversary Volume, California Institute of Technology, Pasadena,

California, 1941.

[29] Epstein, P. S. and Carhart, R. R. , The absorption of sound in suspensions and emulsions. I. Water fog in air, J. Acoust . Soc. Am. 25, 553-565 (1953)

[30] Urick, R. J., The absorption of sound in suspensions of irregular particles, J_. Acoust. Soc. Am . 20, 283-289 (1948).

[31] Fry, W. J., Mechanism of acoustic absorption in tissue, J. Acoust. Soc. Am . 24 , 412-415 (1952).

[32] Allegra, J. B. and Hawley, S. A., Attenuation of sound in suspensions and emulsions:

theory and experiments, J. Acoust. Soc . Am. 51, 1545-1564 (1972).

[33] Ahuja, A. J., Acoustical properties of blood: a look at the basic assumptions,

Med. Phys . 1, 311 (1974).

[34] O'Donnell, M. and Miller, J. G., Mechanisms of Ultrasonic Attenuation in Soft Tissue (this publication, p. 37).

[35] Kessler, L. W. , VHF ultrasonic attenuation

in mammalian tissue, J. Acoust. Soc. Am . 53, 1759-1760 (1973).

[36] Hawley, S. A. and Dunn, F., Ultrasonic

Absorption in Aqueous Solutions of Dextran,

J. Chem. Phys . 50, 3523-3526 (1969).

36
Reprinted from Ultrasonic Tissue Characterization II, M. Linzer, ed., National Bureau

of Standards, Spec. Publ . 525 (U.S. Government Printing Office, Washington, D.C., 1979).

MECHANISMS OF ULTRASONIC ATTENUATION IN SOFT TISSUE

M. O'Donnell and J. G. Miller

Laboratory for Ultrasonics

Department of Physics

Washington University

St. Louis, Missouri 63130, U.S.A.

Ultrasonic loss mechanisms which arise from the microscopically i nhomogeneous nature

of soft tissue are investigated over the frequency range 1 to 10 MHz. Contributions to the ultrasonic attenuation due to viscous relative motion losses and thermal losses are shown to exhibit an approximately linear dependence on frequency. Numerical

estimates of the attenuation arising from these mechanisms are compared with the re- sults of experiments for a representative substance in each of three attenuation categories: low (blood), medium (heart), and high (skin). Inhomogeneity losses can account

for 60 percent of the attenuation observed in heart and skin, and thus may contribute

a non- negl igi bl e fraction to the attenuation observed in most soft tissue.

Key words: Inhomogenei ties ; inhomogenity thermal losses; mechanisms; viscous relative

motion

.

In efforts to account for the ultrasonic at- tenuation exhibited by soft tissue, two types

of mechanisms have been considered: (1) structural or chemical relaxation of the macro- molecular constituents [1-3]^, and (2) processes arising from the i nhomogeneous nature of tissue, including scattering, viscous relative

motion, and thermal losses [1,3-8]. In this paper we estimate the fraction of the total at- tenuation observed in the 1 to 10 MHz frequency

range which is attributable to processes arising

solely from the microscopically i nhomogeneous

nature of soft tissue, as opposed to that fraction presumed to arise from macromol ecu! ar re- laxation processes.

We consider a model in which a longitudinal

ultrasonic wave propagates through tissue which

is viewed as a suspension of scatterers in a liquid medium (cytoplasm). For the sake of simplicity all scatterers are considered to be spherical in shape. At an interface between

the medium and a scatterer, longitudinal, viscous, and thermal waves may be excited in the suspending medium due to the discontinuity of acoustic and thermal properties at the surface

1 of the scatterer. Energy that is coupled into

!] these waves is lost from the incident ultrai sonic beam and thus contributes to the total

1 attenuation that is observed.

For scatterers small compared to the wave-

[j length of the incident wave the reradiated

1, longitudinal wave corresponds to Rayleigh

j scattering. The effect contributes a term to the attenuation coefficient that varies as the fourth power of frequency and the third

^Figures in brackets indicate literature

references at the end of this paper.

power of the scatterer radius for a fixed

volume concentration of scatterers. The magnitude of Rayleigh scattering depends upon

the square of the difference in adiabatic

compressibilities of the scatterer and the suspending medium and upon the square of the difference in densities. The numerical value

of the contribution due to Rayleigh scattering is several orders of magnitude lower than

the observed attenuation coefficient of soft tissue in the frequency range 1 to 10 MHz [1,2].

Details of the scattering process for scat- terers of dimensions which are not small compared to the ultrasonic wavelength are less well understood. (Specular reflections from objects

much larger in size than the ultrasonic wavelength are explicitly excluded here.) The

general features of the scattering problem in- dicate that the magnitude of scattering events depends primarily on the square of the differences in densities and compressibilities of the scatterer and the suspending medium. In soft tissue, scatterers of dimensions comparable to ultrasonic wavelengths in the 1 to 10 MHz range

( i.e ., scatterers of sizes ranging from 0.05

mm to 1 mm) exhibit densities and compressibilities yery close to those of the suspending

medium. Thus losses arising from these scattering events are expected to represent small contributions to the attenuation coefficient.

Such scattering events, however, may be of central importance in scattering and reflection ( i.e ., 180° backscattering) experiments.

Viscous drag losses arise from the generation of a highly damped viscous wave in the suspending medium. The scatterers attempt to mirror the motion of the suspending medium to

all extent determined by a function which depends upon the relative densities of the scat37
terers and the medium, the ultrasonic fre- quency, and the viscosity of the medium [4,7].

For fixed frequency, viscosity, and volume

concentration of scatterers, the contribution

of viscous drag losses to the attenuation co- efficient is predicted to rise, reach a maximum, and subsequently fall as a function of scatterer size. A similar rise, plateau, and

fall is predicted if viscous relative motion

losses are plotted as a function of frequency

for fixed scatterer size. Contributions to the attenuation of ultrasound in tissue by viscous

relative motion losses were considered by Fry

[6], Carstensen and Schwan [1], and Kremkau,

Carstensen, and Aldridge [3]. An additional contribution to the ultrasonic

attenuation arises from the generation of a highly damped thermal wave at the surface of a scatterer. (Strictly speaking, the viscous drag

and thermal effects are coupled, but the strength

of this coupling is sufficiently small that it can be ignored [4].) The magnitude of the losses associated with the generation of the thermal wave depends upon frequency and upon the relative

heat capacities, coefficients of thermal expansion, and thermal conductivities of the scat- terers and suspending medium. At low frequencies

the system is in an isothermal limit in which

energy is reversibly exchanged between the carrier medium and a scatterer, which closely follow

each other in temperature ("isothermal"), so that relatively little loss of energy occurs. At high

frequencies the system is in an adiabatic limit

in which temperature changes in the suspending

medium occur so rapidly that they cannot be com- municated to a scatterer. Thus little heat transfer occurs ("adiabatic") and relatively

little energy is dissipated. Maximum energy is dissipated in the intermediate range of fre- quencies where the thermal response of the scat- terers to the incident compressi onal ultrasonic

wave lags sufficiently behind that of the sus- pending medium that substantial energy is dissipated. Thermal losses in i nhomogeneous media

have been considered by Epstein and Carhart [4],

Allegra and Hawley [7], Kremkau, Carstensen, and Aldridge [3], and Ahuja [8].

In order to estimate the contribution to the observed attenuation arising from viscous and thermal effects, it is necessary to identify the relevant scatterers in biological specimens. In principle, all inhomogeneities contribute to the observed attenuation at any frequency. The

physical arguments presented above, however,

suggest that for a fixed range of frequencies

only scatterers exhibiting specific physical

properties that define the relatively narrow

ranges over which either viscous or thermal losses are near maximum need be considered.

Numerical computations discussed below indicate

that for the range of scatterer dimensions

which results in significant viscous relative

motion losses or thermal losses, contributions

to the attenuation coefficient exhibit an ap- proximately linear dependence on frequency,

i.e ., log (attenuation) versus log (frequency)

exhibits a slope of 0.8 to 1.2 over the fre- quency range 1 to 10 MHz. Therefore, the slope

of the attenuation versus frequency curve over

the range of 1 to 10 MHz (hereafter referred to as the slope of the attenuation) can serve as a useful index of ultrasonic properties. This

conclusion, arrived at from theoretical con- siderations, is consistent with the results of experiments, which indicate an approximately

linear dependence on frequency for the ultrasonic attenuation coefficient of soft tissue. The slope of the attenuation represents a de- sirable index since in transmission experiments

it is less susceptible to errors associated

with impedance discontinuities and may be less susceptible to errors resulting from phase

cancellation effects than is the apparent at- tenuation coefficient.

LO

U.8 / \ THERMAL ATTENUATION

'e / \ Con^ = 17% b

0.6

/ \ Pscatt = 1 4lg/cm3

Its

of 0.4 c

0.2

SLOPE 0.0 1 1 .

1

0.01 01 I 10 100 SCATTERER DIAMETER ( /xm )

Fig. 1. Slope of the attenuation versus frequency

curve over the range 1 to 10 MHz arising

from thermal losses plotted as a function

of scatterer diameter.

In figure 1 the contribution to the slope of the attenuation arising from thermal losses is plotted as a function of scatterer size. The

physical properties of the scatterers and the suspending medium used in calculating the re- sults shown in figure 1 appear in table 1 which

is discussed below. As illustrated in figure 1, contributions from thermal losses are largest when the thermal wavelength Xi of the suspending

medium approximately equals 2 ir times the radius

of the scatterer. (A^ is on the order of 0.4 to

1.3 m in the frequency range 1 to 10 MHz.)

The slope of the attenuation which results from the coupling of energy into a viscous wave

is plotted as a function of scatterer size in figure 2. As illustrated, viscous relative motion losses are largest when the viscous wavelength Ay of the suspending medium approximately equals 2 ir times the radius of the scatterers.

(Ay is the order of 1.8 to 5.5 vim in the 1 to

10 MHz frequency range.

)

Our calculations indicate that viscous rela- tive motion losses dominate thermal losses in the 1 to 10 MHz frequency range for a wide

range of scatterer properties consistent with

the microscopic anatomy of soft tissue. We thus focus on viscous relative motion losses in an attempt to identify specific physical properties that must be exhibited by the relevant

scatterers. The numerical magnitude of the viscous relative motion term is approximately

proportional to (p'/p - 1)^, where p' is the density of the scatterer and p is the density

of the suspending medium. Therefore, significant contributions to the observed attenuation

result only from those scatterers which (1) ex- hibit sizes that maximize viscous relative mo38
75

X 60

45

30

/~\ VISCOUS ATTENUATION

/ \ Con^, = 17%

/ \ '^suspending = 2.5cp

/ \ medium

-

-

/ \ ^scQtt = I.41g/cm3

\ -

'

- , 1 1 111 1 1 0.01 0.1 I 10 SCATTERER DIAMETER (/xm)

100

Fig. 2. Slope of the attenuation (1 to 10 MHz)

arising from viscous relative motion

losses plotted as a function of scatterer

diameter.

tion losses, (2) have densities significantly

different from that of the suspending medium,

and (3) are present in sufficient concentrations. Aggregates of structural protein such

as fibrils of collagen or muscle myofibrils ap- pear to be the principal constituents of soft tissue which possess these properties. (Dunn and his colleagues have identified collagen as

a significant determinant of the ultrasonic

properties of soft tissue, in part because of

its large compressional modulus and ubiquity

[9,10].)

Limiting our attenuation to scatterers ex- hibiting the requisite physical properties, we estimate the contribution to the observed at- tenuation arising from microscopic inhomogeneities. Specific numerical values for the properties of the scatterers and the suspending medium which were used in our calculations

are presented in table 1. An attempt has been made to estimate the contribution to the ex- perimentally observed attenuation arising only

from viscous and thermal effects for a repre- sentative substance in each of three attenuation categories: low (blood), medium (heart).

and high (skin). Results of these calculations

are summarized in table 2. Losses associated

with viscous relative motion are seen to dominate thermal losses in the 1 to 10 MHz range,

a feature which appears to be preserved over a wide range of scatterer properties.

The quantitative results presented in table

2 indicate that losses arising solely from microscopic inhomogeneities appear to account

for a significant fraction ('v 60 percent) of the total observed attenuation of heart and

skin. These results suggest that i nhomogeneity

losses may contribute a non-negligible fraction

to the attenuation of most soft tissue. Al- though the exact magnitude of these losses is certain to be altered by the use of more realistic assumptions (e^. , non-spherical scat- terers and improved estimates of the values of physical properties specified in table 1), the

general conclusions of this study would not be altered if the illustrative numerical results presented in table 2 were in error by 30 percent.

Table 2. Slope of attentuation coeff icient-vs-frequency

(cm-iMHz-i

Tissue Viscous Thermal Theoretical Experimental Percent

value^ value accounted forC

Blood

(40% Hct) Heart 0.042 Skin 0.101

0.003 0.000

0.001

0.001

0.003

0.043

0.102

0.03ld 10

0.0726 60 0.17of 60

Numerical results presented to 3 significant digits for

j^i 1 1 ustrati ve purposes only. ^Sum of contributions from columns 2 and 3. Percent of experimentally observed values (column 5) accounted

for by sum of contributions (column 4) arising from losses due

.to microscopic inhomogeneities. Carstensen, E. L., Li, K. , and Schwan, H. P., J. Acoust. Soc . Am. 25, 286-289 (1953). ^O'Donnel, H., Mimbs, J. W. , Sobel , B. E., and Miller J. G., Ultrasonic Attenuation in Normal and Ischemic Myocardium

^(this conference).

Dussik, K. T., Kyriazidov, M., Fritch, 0. J., and Sear, R. S.,

Am. J. Rhys. Med . 37, 160 (1958).

Table 1. Acoustic and thermal properties of tissue scatterers (T = 20 'C).

Tissue Scatterers Size range^ Density Vol ume Thermal Coefficient Speci f ic concentration conductivity of thermal heat expansion

% of total 10-5

(pm) (g/cm3) vol ume cal/s-cm-^C 10-" deg-i cal /g-°C

Blood Red cells 4.6 - 5. 6b 1 .09b 40b 1.1b 1.2c 0.8b

(40% Hct) Heart Muscl 1 .32^

e

1,0 - 2.0^ 18d 0.4c 1 .2C 0.4c myof i bri 1

s

Skin Ccl lagen 0.7 - 1.56 1 .4lf 259 0.4c 1 .2= 0.4c

f ibri 1

s

1 Suspendi .03b ng^ 1 .5b 1.41 1 .Ob —medium

.Uniform distribution of scatterers with diameters expressed in micrometers.

°Ahuja, A. S., Med. Phj^. 1, 311-316 (1974). ^Estimated

.

Bailey, Kenneth, Proteins , H. Neurath and Kenneth Bailey, eds., Chapt. 4 (Academic Press, New York, 1954).

.pGross, Jerome, Scientific American , 120-130 (May 1961). Pomeroy, C. D. and Milton, R. J., J. Soc. Leather Trades Chem . 35, 360 (1951). ^Chupvil , .M. , Physiology of Connective Tissue (Butterworth, London, 1967). .Viscosity (1 to 10 MHz) estimated to be 2.5 centipoise.

Epstein, P. S. and Carhart, R. C, J. Acoust. Soc. Am . 25, 553 ( 1953).

39
Acknowl edgment

This work was supported in part by grants

HL19537, HL17646, and HL07081 from the National

Institutes of Health. Pranoat Suntharothok-Priesmeyer was respon- sible for production of the text and illustrations.

References

[1] Carstensen, E. L. and Schwan, H. P., Absorption of sound arising from the presence of intact cells in blood, J_. Acoust. Soc. Am . 31_, 185 (1959).

[2] Pauly, H. and Schwan, H. P., Mechanism of absorption of ultrasound in liver tissue,

J. Acoust. Soc. Am . 50, 692 (1971).

[3] Kremkau, F. W. , Carstensen, E. L., and Aldridge, W. G., Macromolecular interactions in the absorption of ultrasound

in fixed erythrocytes, J. Acoust. Soc . Am. 53, 1448 (1973).

[4] Epstein, P. S. and Carhart, R. C, The absorption of sound in suspensions and emulsions. I. Water fog in air, J_. Acoust. Soc. Am . 25., 553 (1953).

[5] Urick, R. J., The absorption of sound in suspensions of irregular particles, J_. Acoust. Soc. Am . 20, 283 (1948).

[6] Fry, W. J., Mechanism of acoustic absorption in tissue, J. Acoust. Soc. Am . 24 412 (1952).

[7] Allegra, J. R. and Hawley, S. A., Attenuation of sound in suspensions and emulsions

theory and experiments, J. Acoust. Soc. Am

51, 1545 (1972).

[8] Ahuja, A. J., Acoustical properties of blood: a look at the basic assumptions,

Med. Phys . U 311 (1974).

[9] Fields, S. and Dunn, F., Correlation of echographic visualization of tissue with

biological composition and physiological

state, J. Acoust. Soc. Am . 54, 809 (1973).

[10] O'Brien, W. D. Jr., The Role of Collagen

in Determining Ultrasonic Propagation

Properties in Tissue, in Acoustical Holo- graphy , L. W. Kessler, ed. , Vol . 7 (Plenum

Press, New York, 1976).
CHAPTER 3

ATTENUATION AND VELOCITY II:

METHODOLOGY AND MEASUREMENTS

41

Reprinted from Ultrasonic Tissue Characterization II, M. Linzer , ed. , National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C., 1979).

ELEMENTS OF TISSUE CHARACTERIZATION

Part II. Ultrasonic Propagation Parameter Measurements

S. A. Goss, R. L. Johnston, V. Maynard, L. Nider,

L. A. Frizzell, W. D. O'Brien, Jr., and F. Dunn

Bioacoustics Research Laboratory

University of Illinois

Urbana, Illinois 61801, U.S.A.

Methods employed at the Bioacoustics Research Laboratory of the University of

Illinois for the determination of ultrasonic propagation properties of biological

media are described, with attention devoted to attenuation, absorption and velocity measurements of both longitudinal and shear ultrasonic waves. These include

systems specifically for the ultrasonic characterization of soft tissues and for solutions of biologically significant macromolecules. Each method is presented

in terms of theory, limitations, applicability, and possible sources of error. Important new techniques from other laboratories are also discussed.

Key words: Ultrasonic absorption; ultrasonic attenuation; ultrasonic instrumentation; ultrasonic measurements; ultrasonic spectroscopy; ultrasonic

tissue characterization; ultrasonic tissue parameters; ultrasonic

tissue signature; ultrasonic velocity.

1. Introduction

A number of measuring techniques have been developed, or are otherwise employed, at the Bioacoustics Research Laboratory of the University of Illinois in the research efforts as- sociated with the propagation characteristics of ultrasound in biological tissue, and toward a basic understanding of the mechanism(s) re- sponsible for the acoustic properties exhibited

by those tissues. These include specialized

systems for biological liquids and for soft tissues which are capable of measuring attenuation, absorption, and velocity of longitudinal

ultrasonic waves as functions of frequency, tem- perature and, where appropriate, pH and ambient

pressure. In addition, a system is presently

being developed to measure the shear acoustical

properties of biological materials as a function

of frequency and temperature. These techniques,

thirteen in all, are described in this paper in terms of parameters measured, theory, application, precision/accuracy, frequency, and temperature range, so that each technique may be as- sessed separately.

2. Attenuation and Velocity Measurements in Soft Tissue

Attenuation of longitudinal waves in soft tissue specimens are determined using the radiation

force, pulse transmission, and standing wave

techniques. Velocity measurements in soft tissues can be made by observing the time of flight

of an acoustic pulse through a known path length

of a tissue sample, and by acoustic interferometry.

A. Attenuation: Radiation Force Method

The phenomenon of radiation force provides a primary method for the measurement of the second order quantities of intensity and power [l-4]i.

Radiation force is a direct result of energy

transport by the sound wave, and is equal to the time rate of change of momentum of the wave. Thus a continuous wave incident on a reflecting

or absorbing object will produce a time independent force on that object equal to, and in the direction of, the time rate of change of momentum. Consequently, a sensitive balance can

be employed to measure the radiation force exerted by an ultrasonic beam incident on a suspended

target. It then follows that force, measured as

a change in tension of the suspending wire, on a perfectly absorbing target intercepting a vertically directed sound beam is

where F is the measured change in tension of the suspending wire, P is the time average power in- tercepted by the target, and c is the velocity

of propagation. Thus, in water, 1 milliwatt of incident power will exert a force equivalent to a weight of 67 pg, which is measured as an apparent

target weight change. Similarly, a perfectly

reflecting target intercepting a vertically

directed sound beam will produce a measurable

change in suspension tension, given as

Figures in brackets indicate literature

references at the end of this paper.

43
F=2Pcos29

c

where e is the angle between the beam axis and the

normal to the target surface. Consequently in water, when the target is inclined 45° to the vertical, the sensitivity of the balance is again 67 pg/mW of intercepted power. Thus, a phase insensitive, frequency independent technique for power and intensity attenuation measurements becomes available

by interposing a tissue sample between the sound source and the sound intercepting target, by deter- mining that power lost or redirected with the tissue

sample in place compared with measured power with

the tissue absent [2,5,6]. Care must be taken to insure that the system's sensitivity is actually that

that predicted for such idealized cases. The attenuation present in the liquid media (water or physiological saline) will inevitably cause acoustic

streaming which will lead to systematic errors in the power estimation. The streaming effect can be minimized by positioning an acoustically transparent

barrier of, for example, stretched polyethylene,

directly in front of the target.

A second possible source of error is due to the inherent insensitivity of the measurement system

to horizontal forces. For maximum accuracy, the main lobe of the sound beam should be directed

precisely vertically. Because the beam may contain components of momentum in the plane perpen- dicular to the main lobe, the radiation force balance method does not respond to all the energy

emitted by the source. As the temperature of the target increases due to the fact that energy is being deposited in it, thermal expansion of the target can introduce an error by virtue of in- creasing its buoyancy and resulting in an apparent

target weight change. The ultimate accuracy of

the radiation force balance method is limited by

noise associated with mechanical vibrations and atmospheric perturbations, which can be reduced by proper design considerations. However, in the presence of pressure gradients, the target is acted on by forces proportional to the target

volume, making a small target advantageous.

B. Attenuation: Pulse Transmission Method

The pulse transmission technique is applicable

to measurements of sound pressure attenuation in various types of biological specimens [7,8]. The instrumentation consists of a transmitting ultrasonic transducer immersed in a bath (usually

physiological saline) which serves as the acoustic

coupling medium and aligned axially with either a reflecting surface or a receiving transducer. The associated electronic instrumentation provides an RF pulse to the transmitting crystal and also triggers the sweep of an oscilloscope a variable, but selected, length of time after the initiation of

the transmitting pulse. An oscilloscope serves

to display the amplified received signal. Measurement of sound attenuation can be performed as follows. First, with no sample in the ultrasonic

path, the gain of the receiving amplifier is ad- justed to give a signal display of a predetermined

amplitude. Then, with the specimen in place, the gain of the system is adjusted, either by increasing the receiving amplifier gain or by removing

electrical attenuation in the signal path, to com- pensate for the loss of acoustic energy in the sample to bring the display trace to the same

preselected amplitude. The attenuation measurement is repeated for other samples of the same material, but of varying thicknesses. The measured attenuation values are then plotted versus

sample thickness, and the slope of the resulting

straight line yields the attenuation per unit

length of the specimen.

C. Velocity: Pulse Transit Time Method

Velocity measurements in tissue can be made simply by measuring the time of flight of an acoustic pulse over a known path length of the specimen [9,10]. Differential techniques should

be used to minimize uncertainties in path length

and t^'me delay measurements, such as the uncertainty of the actual location of the active face of

the transducer. If commercial transducers are employed, additional allowances must be made for the quarter-wave impedance matching layer on their

surface. Errors may be encountered in time of flight measurements of the acoustic signal in in- homogeneous media, such as tissues. Since a short duration acoustic pulse contains a broad spectrum

of components, the frequency dependent effects of velocity dispersion, attenuation, and multiple

phase shifts at tissue interfaces, can distort

and delay the signal [11]. Techniques which

rely on the detection of the leading edge of the received acoustic pulse for timing are prone to the greatest inaccuracies under such distortions.

D. Velocity: Acoustic Interferometric

Method

Nearly an order of magnitude improvement in ac- curacy can be realized by the use of acoustic in- terferometric techniques employing CW excitation

[12,13]. By sandwiching the tissue sample between transmitting and receiving transducers, or between

a transducer and a reflecting target, a standing

wave is created in the tissue sample. It has been shown that tissue may be distorted in this manner

up to 25 percent without affecting the measured

velocity [12]. By monitoring the maxima and minima of the received acoustic signal as the path

length is changed, the standing wave pattern and

the wavelength of sound in the tissue can be measured. This information combined with the fre- quency employed for the measurement yields the velocity of sound in the sample. Alternatively,

the path length may be held fixed and the frequency of excitation changed. The change in frequency necessary to move from one mode in the standingwave pattern to the next is directly proportional

to velocity. The accuracy of such interferometric

techniques, under tight temperature control, can reach about 0.1 percent.

E. Attenuation and Velocity: Standing

Wave Method

While the measuring techniques described above

may be applied to the measurement of the ultrasonic absorption and velocity of most biological

tissues, some specimens require specialized

techniques

.

Lung, by virtue of its extraordinarily high

attenuation, presents some problems in determination of its ultrasonic propagation properties.

The following method has been developed and yields

results in agreement with other similar ones [8].

44
Briefly, the lung is suspended in the sound field between the sound source and an absorption chamber,

to eliminate standing waves beyond the lung. The transient thermoelectric probe [14] provides a convenient acoustic detector to investigate (A) the acoustic field between the specimen and the source, to determine the axial standing wave pattern, and (B) the acoustic field between the specimen and the absorption chamber, to determine the wave amplitude transmitted beyond the lung specimen 15 (see fig. 1). Probing the field in A yields the fraction of incident energy reflected

at the lung-saline interface. Assuming that in- finitesimal wave acoustics prevails and that the attenuation in the lung is sufficiently great that multiple reflections within the specimen need not

be considered, the speed of sound in the lung can

be obtained from

!pv)i ung (pv)saline SWR (3)

where the p's are the known densities and SWR is the observed standing wave ratio (between the source and specimen) and is greater than unity. The attenuation coefficient per unit path length is determined

from a knowledge of the energy reflected at the two lung-saline interfaces, the thickness of the sample,

and the acoustic intensity detected by the probe in

B in accordance with the relation

Ine -2al (4)

where Iq and Ij are, respectively, the acoustic in- tensities at the lung-saline interface nearest to and farthest from the source, 1 is the thickness

of the sample, and a is the attenuation coefficient.

3. Absorption Measurements

in Soft Tissue

The transient thermoelectric method is well suited for determining acoustic absorption in

small volumes of highly absorbing liquid or tissue ir[ vivo as well as i_n vitro , and may be the only method, applicable to tissues, that measures directly absorption rather than attenuation. As such it is invaluable in determining

the portion of attenuation due to absorption visa-vis that portion due to scattering effects

L16,17]. The method requires that a thermocouple

junction of small diameter relative to the wavelength be implanted in the sample. The thermo- couple and surrounding sample are then exposed to

a plane traveling wave ultrasonic field having a temporally rectangular envelope of known intensity.

The typical thermoelectric emf response to a 1 second ultrasonic pulse has an initial fast rise

which results from conversion of acoustic energy

into heat by the viscous forces acting between

the thermocouple wire and the sample. This portion of the response approaches equilibrium very quickly with a magnitude that depends mainly upon

the thermocouple wire radius, the viscous properties of the sample medium, the sound intensity,

and the frequency. The fast rise is followed by

a relatively linear rise (in the absence of

thermal conduction processes) that is a result of absorption of the ultrasound in the surrounding

medium. From a determination of the slope of the

1 inear portion of the thermoelectric emf response

as a function of time, the absorption coefficient

can be calculated using the following relation,

p'-p CnK

21 /dT\

^dt/n

(5)

where a is the absorption coefficient (cm"i), p is the density (g/cm^), Cp is the specific heat at constant pressure (cal/°C g), K is the mechanical

equivalent of heat (4.18 J/cal), I is the acoustic

intensity (W/cm^), and (dT/dt)o is the initial

time rate of change of temperature due to absorption in the medium (°C/s). Effects limiting the

i

pC — rubber diaphragm

position of probe

for determination

of absorbed energy \

position of probe

for determination

of reflected energy

(A)

castor oil absorption

chamber

coupl ing

medium

position of excised

lung capsule

sound

tank

Fig. 1, Schematic diagram of the experimental arrangement for attenuation and velocity measurements in lung using the standing wave method [15].

45
accuracy of the method include any changes of the thermal properties of the tissue and/or the absorption itself with temperature. Provided the tem- perature rise during measurement is on the order

of one degree or less these effects will be minimal. Dunn [18] has indicated that the total uncertainty in the determination of (dT/dt)n is of

the order of 5 to 10 percent. In application of the transient thermoelectric method the initial value

of a is determined by using the ultrasonic in- tensity that would be present at the site of the junction were the sample absent. The measured

depth of the thermocouple and the initial value of

a are then used to calculate intensity at the site of the junction by correcting for absorption using

an iterative method [18] until the value of o con- verges (note that if the value of a and/or the depth of the thermocouple are too large, the value

of a will not converge).

This technique has been used at frequencies as low as 0.26 MHz [19] and as high as 7 MHz [20] in tissues, but modifications have been used to 2 GHz

in fluid media [21]. The lower frequency limit is determined by the value of the absorption, since

too low an a yields too low a temperature rise to

be detected accurately without having to increase

the exposing intensity to unacceptable levels. Also, at low frequencies and absorptions the initial viscous heating portion of the transient

thermal emf may become a major portion of the signal, making the subtraction process a relatively

erroneous one. At higher frequencies the limitations on accuracy of the method, as described for tissues, are imposed by (1) availability of broad

plane wave ultrasonic fields, (2) the size of the thermocouple relative to the wavelength so that

the field is affected by scattering from the wire

and thermal conduction along it, and ultimately

by (3) nonconvergence in the iterative method of depth correction due to high absorption. The lat- ter two limiting effects have not yet been troublesome in the region of application. The method has been found to be very useful and easily applied to most tissues over the frequency range from 0.5 to 4.0 MHz.

4. Absorption and Velocity Measurement

in Biological Liquids

The primary mechanism(s) for the absorption of sound in biological material seems to occur at the macromolecul ar level. Carstensen, Li, and Schwan [22] discovered that the acoustical properties of blood are determined largely by the protein content, and that the absorption coefficient is directly proportional to the protein

concentration, whether in solution or within the

cell. Pauly and Schwan [23] have demonstrated

that nearly two-thirds of the ultrasonic absorption of beef liver lies at the macromolecular

level, with the remaining one-third due to structural features of the tissue. Since the primary

mechanism for the absorption of sound in tissue

seems to occur at the macromolecular level, it has been instructive to investigate the acoustic

properties of simpler systems of macromolecules,

such as solutions of biopolymers, with the hope that such studies may provide details applicable

to the more complex systems.

Three measurement systems have been used at the Bioacoustics Research Laboratory to study acoustic

absorption and velocity of solutions and suspensions of biomacromolecules as functions of molecular characteristics, pH, temperature, concentration, and frequency to aid in the elucidation of

the mechanisms of interaction between ultrasound

and biological tissues.

A. Absorption: High Frequency Method

(5 MHz to 200 MHz)

The high frequency system applies pulsed ultra- sound to solutions for the purpose of measuring

absorption and velocity [24-26]. Two advantages

of pulsed ultrasound are that heating effects and standing waves are virtually eliminated. Heating

is proportional to the mean power. Using a 10 ps pulse at a repetition frequency of 300 pps results

in a signal which is present for only 0.3 percent

of the time. Thus the average intensity is much

less than the peak intensity, and produces a negligible temperature rise. Since the signal is on for such a small fraction of the time, standing

waves are not produced. The basic technique was

first described by Pellam and Gait in 1946 [27]. Two transducers, arranged coaxial ly face each other at opposite ends of a cylindrical tank. The receiving transducer has its position fixed while

the sending transducer moves toward or away from

it at a constant speed. Assuming the relation

governing the process is

p(x) = p(o) e" (6)

where p(x) is the wave pressure amplitude at the distance x from the transmitting transducer, p(o)

is the pressure amplitude at x = o ( i.e ., at the face of the transmitting transducer), and a is the absorption coefficient, the natural logarithm of the ultrasonic pressure amplitude is proportional

to the signal path length. The proportionality

constant, i.e ., the absorption coefficient, can

be found by monitoring the pressure as a function

of intertransducer distance. A block diagram of

the system is shown in figure 2. A pulsed rf signal is amplified, passed through a variable

FREQUENCY SYNTHESIZER

PULSE DOUBLE- BALANCED

MIXER GENERATOR

WIDE BAND AMPLIFIER

HATCHING

NETWORK

TRANSMITTING

TRANSDUCER

RECEIVING TRANSDUCER T

PREAMPLIFIER

SPECTRUM ANALYZER

OPERATIONAL

AMPLIFIER

PULSE HEIGHT

DETECTOR

CHART RECORDER 1

ISOLATION AMPLIFIER

DIGITAL VOLTMETER

DIGITAL COMPUTER

Fig. 2. Block diagram of instrumentation used for high frequency (5 to 200 MHz) ultrasonic

absorption measurements in biological

liquids.

46
attenuator, and impedance-matched to the sending

transducer. Both transducers are air backed,

gold-on-nickel plated X-cut quartz with a fundamental resonant frequency of, for example, 3 MHz,

and operated at their odd harmonics. The wave

passes through the liquid, where it is attenuated,

and impinges upon the receiving transducer. Some

of the ultrasound is then reconverted into an electric signal, while the remainder is reflected

back through the liquid. A pulse height monitor

continually detects the voltage peak of the primary signal (which is linearly proportional

to p(x)) as the transducers are moved toward, or away from each other, and converts it to its natural logarithmic value. An on-line computer

samples the output of the pulse height detector

(a dc voltage proportional to the pulse height)

via a digital voltmeter, calculates the attenuation coefficient, and corrects for diffraction

effects by the method of Del Grosso [28] yielding

the true absorption coefficient. Solute absorption is obtained by subtracting results of a sol- vent measurement from a solution measurement. Approximately one liter of sample is required for

this technique, with measurement error in absorption of about 5 percent over the approximate

frequency range 3 to 200 MHz. Greater errors occur in low absorbing liquids at low frequencies

and are mainly due to relatively large diffraction

effects.

B. Velocity: High Frequency Method

The acoustic velocity can be determined in the

high frequency system to within 0.1 percent by

measuring the period of the wave in the liquid.

This is accomplished by superimposing a reference

signal on the received signal, which results in

an interference pattern. If the acoustic path

length is changed at a constant rate, Vp, the period of this pattern is T = (x/Vp) where X is the acoustic wavelength. Since X - c/f, where f is the excitation frequency, the acoustic velocity

positioning rod

is given as c = TfVp. The period T is measured

using a time interval counter to determine the time required for the interference signal to go through a greater number (100) of maxima.

C. Absorption: Low Frequency Method

(0.3 MHz to 20 MHz)

In the frequency range of 0.3 to 20 MHz, a pulse technique developed by Schwan and Carstensen [29] is employed in order to avoid having to make unreasonable corrections for effects of diffraction phenomena. A sending and a receiving

transducer face each other; the former is in the reference liquid and the latter in the test liquid

(see fig. 3). An acoustic window separates the two liquids. The distance between the transducers remains constant while the entire trans- ducer ensemble is moved horizontally at a constant

speed from a position such that the acoustic path

is primarily in the test liquid to a position such that it is primarily in the reference liquid. The reference liquid is chosen to be dispersionless

and acoustically well characterized with a sound velocity as near to that of the unknown as pos- sible. Water is an appropriate choice for dilute aqueous solutions. Since the path length is constant, diffraction effects, due to the in- equality of the velocities in the two liquids,

are corrected by a computer using the method of

Del Grosso [28]. Liquid volumes of 1 to 4 liters

are used in each chamber, depending upon frequency.

As with the high frequency system, measurement

error ranges from 2 to 10 percent. The pressure amplitude in the receiving transducer is given by

-aw(d-

(7)

where p^ is the pressure amplitude at the sending

transducer, and the other symbols are described

by figure 3. This equation can be rewritten as

1 n p„ = In Pt o, d + w

(8)

transducer acoustic window

X

transducer

Figure 3. Schematic diagram of apparatus used for ultrasonic absorption and velocity measurements

at low frequencies (0.3 MHz to 20 MHz) in biological liquids [24].

47
and can be obtained graphically from the slope

since is known.

As the acoustic window (polyethylene) reflects

a negligible, but constant amount of the acoustic

energy, it will affect the results only by changing the intercept, i.e ., the slope is not affected. Signal processing to obtain the desired

absorption coefficient closely resembles that

used in the high frequency system, described

above [14,24].

nally developed by Eggers [31], which employs two X-cut quartz disks, with a fundamental frequency

of the order of 2 MHz, separated by a lucite ring,

and forming a cylindrical cavity in which the specimen solution is placed. One transducer

serves as a transmitter, and the other a receiver. When the transmitting transducer is excited with a sinusoidal voltage, standing waves in the specimen

solution result at particular frequencies that obey the resonance equation

D. Velocity: Low Frequency Method

Velocity of the acoustic wave can be determined

with the low frequency system to 0.01 percent

[30] by superimposing the received and reference

signals in the same fashion as was done for the high frequency system. If the velocities in the test and reference liquids are different, moving

the transducer assembly will change the acoustic

path length. By observing the interference pattern on the oscilloscope, one can position the transducers such that a maximum occurs. If this

is position 1 in figure 3, the number n, of acoustic wave lengths between the transducers is given by

n=^^ + ^ (9)

If the transducers are moved a distance. Ax, such that the interference pattern undergoes an integral number, m, of 2t\ phase shifts, the above ex- pression becomes

d - X + Ax , x

n ± m

= + - Ax (10)

where the positive sign applies when the velocity

in the test liquid is larger than that of the re- ference liquid, as is usually the case. Eliminating n between these equations, expressing wavelengths in terms of velocity and frequency, and a rearranging of terms yields

Pq^qCntan PcCs^s

r-tan

1 [cotanj 2 f. (12)

where pq and c„ are the density and speed of ' sound in the quartz transducers, and Pg and c^ are the corresponding quantities in the solution.

The fundamental frequency of the transducer is fg, and of the liquid-filled cavity, f^. At the resonant frequencies fp, the receiving trans- ducer registers pronounced voltage peaks, whose

frequency separation depends on the sound velo- city of the specimen solution, and the half- power (3 dB) bandwidth Af of which is related to the attenuation per wavelength, aX. Eggers

[31,32] has shown that the velocity of sound Vf

in an unknown medium may be related to the velocity of sound in some reference medium v,, by the expression

v_

D 1 + 2(DfZf - D^Ir)

^q^q

(13)

where If and Z„ are respectively, the acoustic

impedance of tne unknown and reference medium,

and and Dp are the respective separations in frequency units between adjacent resonances for

the liquid and reference media, and f^ and I„ respectively, are the frequency of the quartz and

its acoustic impedance. Equation 13 may be ap- proximated by a simpler expression (with a dif- ference of only a few parts per thousand) as

Cv = (11) fAx

Note that some other procedure must be performed

to determine the correct sign.

E. Absorption and Velocity Measurements

in Small Liquid Volumes: Resonant Cavity Method

The various methods for determining the acoustic

propagation properties of liquids discussed thus far were devised with little consideration for the volume of material necessary for measurement. The minimum volume required in the high frequency

system is 500 ml, with greater volumes generally

required at lower frequencies to avoid effects due

to diffraction phenomena. The necessity for having

such large volumes available becomes a serious

problem when biological macromolecules are to be treated in solutions (usually in concentrations of

10 percent by weight), since only a few can be examined within the bounds of reasonable economics.

It is possible to reduce the specimen volume to less than 50 ml using a resonance technique or^'^i-

&Cf 6f, (14)

where SCf is the velocity difference between the unknown and reference media, Sf^ is the difference

between corresponding resonances, and Cf is the velocity of the reference medium at a frequency

fp. In general, velocity measurements are more difficult to perform than absorption measurements

due to temperature drift and other instabilities

of the unit. The attenuation of the specimen

solution may be calculated from the examination

of the quality factor Q of the liquid filled

cavity, defined as the frequency fp divided by the

3 dB bandwidth, Afp, of the resonance. This quali

ty factor is a function of the mechanical clamping

and the attenuation per wavelength aX of the ultra sonic energy and is expressed as.

Q

= Afn oX

(15)

The measured Q, however, includes losses associated with attenuation in the solvent, as well as

^

those arising from diffraction, wall effects, im- perfect reflections at the quartz surface, etc .

,

48
in addition to the desired excess attenuation due

to the solute. Assuming all of these energy losses

are additive [32], the measured quality factor Q is given by

%eas ^solute ^extra

where Qsolute is the quality factor due to sound absorption in the solute, and Qextra includes sol- vent and other cell losses previously discussed.

The excess solute absorption can be obtained by means of a reference measurement in the same cell at the same frequencies with the reference liquid,

having equal or very similar sound velocity to in- sure the same sound field pattern for both mea- surements. The excess absorption per wavelength

in the specimen solution is then obtained from

-lexcess \ ^n /

where Af^ and Af^ are the corresponding 3 dB bandwidtns of the n^h resonant peak in the sample

and reference liquid, respectively. The application of an overpressure (usually about 10 psi) causes a slight concavity of the transducers,

which reduces diffraction and boundary effects,

and thereby reduces the minimum frequency of measurement [33]. This technique has been used

in our laboratory over the frequency range from

0.5 to 10 MHz.

5. Absorption and Velocity Measurements

of Shear Waves in Biological Specimens

A system based on a pulse superposition tech- nique allows measurement of the shear acoustical

properties of biological materials of interest

[34]. The technique involves phase-amplitude

balance to measure the magnitude and phase angle

of the reflection coefficient of a shear wave

impinging on a quartz-sample interface, and using

the known impedance of the quartz, the complex

shear specific impedance of the sample being in- vestigated is obtained [35]. From the shear im- pedance and density, it is possible to calculate

the dynamic shear stiffness pi, dynamic shear viscosity \i2' shear velocity cs, and shear absorption coefficient ag as shown in the following

relationships:

impedance and Xs is the imaginary part of the specific shear acoustic impedance. This method

has been used to measure the shear acoustic prop- erties of tissues and other biological specimens

[36-38]. An improved system utilizing a gated

carrier as opposed to a pulsed oscillator approach

and an improved ultrasonic unit of beveled AT quartz is being developed that will be useful over the frequency range from 2 to greater than

20 MHz and for temperatures from 10 to 40 °C. These and additional improvements should provide

accuracies for the real and imaginary parts of the specific acoustic impedance v/ithin ± 100 mech-ohm/cm^

at 10 MHz, allowing more accurate measurement of im- pedance close to that for water.

6. Concluding Remarks

The measuring techniques for ultrasonic absorption, attenuation and velocity in biological specimens discussed above have been only those utilized

at the Bioacoustics Research Laboratory. There

are, however, techniques employed elsewhere which

may provide the same information in a more efficient manner. For example, the above discussed

methods provide information at discrete frequencies and loci, or, for spatial averages. Spec- trum analysis methods [39-41] have been promoted

to permit measurements over a somewhat broadened

frequency range. The measurement of the spatial

distribution of ultrasonic properties such as at- tenuation or velocity within a specimen may be possible using the algebraic reconstruction from two-dimensional acoustic projections [42,43], al- though only velocity reconstruction has been con- sidered practical so far. Recent studies have also considered improvements regarding possible error in established

methods of ultrasonic parameter measurements.

Artifacts in acoustic attenuation due to phase

cancellation effects have been described by Marcus and Carstensen [6], who compared a piezoelectric receiver (phase-sensitive) with a radiation-force receiver (phase-insensitive), and also by Busse et al . [44], comparing the piezoelectric receiver with an acousto-electric re- ceiver. Both studies found that measurements

using piezoelectric (phase-preserving) receivers

yielded higher apparent attenuation values than those obtained using phase-insensitive receivers.

Phase cancellation artifacts are thought to be the source of this error.

Pi = M_Lis (18)

P The authors acknowledge gratefully the partial

support for portions of the activities described

Y herein by grants from the National Institutes of

V2 = (19) Health.

2 Acknowledgment

up

Rc +

pojX

References

s '^s (20) [1] Rooney, J. A., Determination of acoustic

pR power outputs in the microwatt-milliwatt

range. Ultrasound Med. Biol . 1, 13-16 (1973). ^— ^^^^ [2] O'Brien, W. D. , Jr., Ultrasonic Dosimetry,

in Ultrasound: Its Application in Medicine

where p is the density, u is the angular frequency,

Rj is the real part of the specific shear acoustic

and Biology , F. J. Fry, ed. , Chap.

(Elsevier, Amsterdam, in press]

49
[3] Kossoff, G., Balance technique for the measurement of very low ultrasonic power

outputs, J. Acoust. Soc. Am . 38^, 880-881

(1965).

[4] Hill, C. R. , Calibration of ultrasonic beams

for biomedical applications, Phys. Med . Biol . 15, 241-248 (1970).

[5] Pohlman, R. , Uber die Absorption des Ultraschalls im menschlichen Gewebe und ihre Abhangigkeit von der Frequenz, Physik Z . 40 , 159- 161 (1939).

[6] Marcus, P. W. and Carstensen, E. L., Problems with absorption measurements of in- homogeneous solids, J. Acoust. Soc. Am . 58

,

1334-1335 (1975).

[7] Dussik, K. T., Fritch, D. J., Kyriazidou, M. , and Sear, R. S., Measurements of articular

tissue with ultrasound, J. Phys. Med . 37 , 160- 165 (1958).

[8] Bauld, T. J. and Schwan, H. P., Attenuation

and reflection of ultrasound in canine lung

tissue, J. Acoust. Soc. Am . 56 , 1630-1637

(1974).

[9] Wladimiroff, J. W., Craft, I. L., and Talbert,

D. G. , In vitro measurement of sound velocity

in human fetal brain, Ul trasound Med. Biol . I, 377-382 (1975).

[10] Buschmann, W. , Voss, M., and Kemmerling, S.

,

Acoustic properties of normal human orbit

tissues, Ophtal. Res . I, 354-364 (1970).

[11] Lange, J. N., Group velocity dispersion due

to pulse reflection from a frequency dependent boundary impedance, J. Acoust. Soc. Am . 40, 998-1001 (1966).

[12] Goldman, D. E. and Richards, J. R., Measurement of high frequency sound velocity in mammalian soft tissues, J. Acoust. Soc. Am . 26^, 981-983 (1954).

[13] Hueter, T. F. , Viscoelastic Losses in Tissues in the Ultrasonic Range, Wright Air

Development Center Technical Report 57-706

(1958).

[14] Fry, W. J. and Dunn, F. , Ultrasound:

Analysis and Experimental Methods in Biological Research, in Physical Techniques

in Biological Re search , W. L. Nastuk, ed..

Vol. IV, Chap. 6, pp. 261-394 (Academic

Press, New York, 1962).

[15] Dunn, F. and Fry, W. J., Ultrasonic absorption and reflection by lung tissue, Phys . Med. Biol . 5^, 401-410 (1961).

[16] Fry, W. J. and Fry, R. B. , Determination

of absolute sound levels and acoustic ab- sorption coefficients by thermocouple

probes--theory , J. Acoust. Soc. Am. 26, 294-310 (1954). ^

[17] Fry, W. J. and Fry, R. B., Determination

of absolute sound levels and acoustic absorption coefficients by thermocouple

probes--experiment, J. Acoust. Soc. Am . 26, 311-317 (1954).

[18] Dunn, F., Temperature and amplitude dependence of acoustic absorption in tissue, J_. Acoust. Soc. Am . 34, 1545-1547 (1962).

[19] Dunn, F. and Brady, J. K., Temperature and Frequency Dependence of Ultrasonic Absorption in Tissue, in Proceedings 8th Inter- national Congress on Acoustics , Vol. 1, p. 366c (Goldcrest Press, Trowbridge

,

Wilts., 1974).

[20] Brady, J. K., Goss, S. A., Johnston, R. L., O'Brien, W. D., Jr., and Dunn, F., Ultra- sonic propagation properties of mammalian

testes, J. Acoust. Soc. Am . 60_, 1407-1409

(1976).

[21] Dunn, F. and Breyer, J. E., Generation and detection of ultra-high-frequency sound in liquids, J. Acoust. Soc. Am . 34, 775-778

(1962).

[22] Carstensen, E. L., Li, K. , and Schwan, H. P., Determination of the acoustic properties of blood and its components, J. Acoust. Soc . Am. 25, 286-289 (1953).

[23] Pauly, H. and Schwan, H. P., Mechanism of absorption of ultrasound in liver tissue,

J. Acoust. Soc. Am . 50, 692-699 (1971).

[24] O'Brien, W. D. , Jr., The Absorption of Ultrasound in Aqueous Solutions of Biological Polymers, Ph.D. Thesis, University of Illinois, Urbana, Illinois (1970).

[25] Goss, S. A., The Concentration Dependence

of the Ultrasonic Absorption in Aqueous

Solutions of Bovine Serum Albumin, M.S. Thesis, University of Illinois, Urbana,

Illinois (1974).

[26] Kessler, L. W., Hawley, S. A., and Dunn, F.

,

Semi-automatic determination of ultrasonic

velocity and absorption in liquids,

Acustica 24, 105-107 (1971).

[27] Pellam, J. R. and Gait, J. K., Ultrasonic

propagation in liquids: I. Application of pulse technique to velocity and absorption measurements at 15 megacycles, J. Chem . Phys . 14' 608-614 (1946).

[28] Del Grosso, V.A., Systematic Errors in Ultrasonic Propagation Parameter Measurements

Part I--Effect of Free-Field Diffraction,

U.S. Naval Research Laboratory Report 6026

(1964).

[29] Schwan, H. D. and Carstensen, E. L., Ultrasonics aids diathermy experiments. Elec- tronics 25, 216-220 (1952).

[30] Carstensen, E. L., Measurement of dispersion

of velocity of sound in liquids, J. Acoust . Soc. Am . 26, 858-861 (1954).

[31] Eggers, F., Eine Resonatormethode zur Be50
stimmung von Schal 1 --Geschwindigkei t und Dampfung an gen'ngen Fliissigkeitsmengen,

Acustica 19. 323-329 (1968).

[32] Eggers, F. and Funck, Th., Ultrasonic mea- surements with milliliter liquid samples in the 0.5-100 MHz range, Rev. Sci. Instrum . 44, 969-977 (1973).

[33] Eggers, F., Funck, Th., and Richman, K. H., High Q ultrasonic liquid resonators with concave transducers. Rev. Sci. Instrum . 47 , 361-367 (1976).

[34] Frizzell, L. A., Carstensen, E. L., and

Dyro, J. F. , Shear properties of mammalian

tissues at low megahertz frequencies, J^. Acoust. Soc. Am . 60, 1409-1411 (1976).

[35] Moore, R. S. and McSkimin, H. J., Dynamic

Shear Properties of Solvents and Polystyrene

Solutions from 20 to 300 MHz, in Physical

Acoustics , W. P. Mason and R. N. Thurston,

eds.. Vol. VI, Chap. 4, pp. 167-242 (Academic

Press, Inc., New York, 1970).

[36] Dyro, J. F., Ultrasonic Study of Material Related to Atherosclerotic Plaque--Dynamic

Viscoelastic Properties of Cholestoric

Esters, Ph.D. Thesis, University of Penn- sylvania, Philadelphia, Pennsylvania (1972).

[37] Dyro, J. F. and Edmonds, P. D., Ultrasonic

absorption and dispersion in cholesteryl

esters, Mol. Cryst. Liq. Cryst . 25, 175-193

(1974).

[38] Frizzell, L. A., Ultrasonic Heating of Tissues, Ph.D. Thesis, University of Rochester,

New York (1975).

[39]- Chivers, R. C. and Hill, C. R., Ultrasonic

attenuation in human tissue. Ultrasound Med . Biol . 2, 25-29 (1975).

[40] Lizzi, F., Katz, L., St. Louis, L., and Coleman, D. J., Applications of Spectral

Analysis in Medical Ultrasonography, Ultrasonics 14, 77-80 (1976).

[41] Le Croissette, D. H. and Heyser, R. C,

Attenuation and Velocity Measurements in Tissue Using Time Delay Spectrometry, in Ultrasonic Tissue Characterization , M. Linzer, ed.. National Bureau of Standards

Spec. Publ. 453, pp. 81-95 (U.S. Government

Printing Office, Washington, D.C., 1976).

[42] Greenleaf, J. F., Johnson, S. A., Lee, S. L. Herman, G. T., and Wood, E. H., Algebraic

Reconstruction of Spatial Distributions of Acoustic Absorption Within Tissue From Their

Two-Dimensional Acoustic Projections, in Acoustical Holography , P. S. Green, ed..

Vol . 5, pp. 591-603 (Plenum Press, New York,

1974).

[43] Greenleaf, J. P., Johnson, S. A., Samayoa,

W. F., and Duck, F. A., Algebraic Reconstruc

tion of Spatial Distributions of Acoustic

Velocities in Tissue From Their Time of Flight Profiles, in Acoustical Holography , N. Booth, ed.. Vol. 6, pp. 71-90 (Plenum

Press, New York, 1975).

[44] Busse, L. J., Miller, J. G., Yuhas, D. E., Mimbs, J. W., Weiss, A. N., and Sobel, B. E. Phase Cancellation Effects: A Source of At- tenuation Artifact Eliminated by a CdS Acoustoelectric Receiver, in Ultrasound in Medicine , D. White, Ed., Vol. 3, pp. 1519-

1535 (Plenum Press, New York, 1977).

51

Reprinted from Ultrasonic Tissue Characterization II, M. Linzer, ed., National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C., 1979).

A DEVICE FOR MEASURING ULTRASONIC PROPAGATION VELOCITY IN TISSUE

Bruce D. Sollish

Harry De Jur Diagnostic Instrumentation Laboratory

Department of Electronics

Weizmann Institute of Science

Rehovot, Israel

This paper discusses a device capable of measuring propagation velocity in tissue,

both excised and in vivo . The device produces a 4-digit decimal readout of propagation

velocity in the specimen relative to that in water. As presently constituted the de- vice is capable of 1 velocity measurement per second, with one additional second re- quired for printout of the result. The theory of the device is described, and experimental results are presented for solids and soft tissues.

Key words: Propagation velocity; reflection technique; solids; tissue; ultrasound.

1. Introduction

Ultrasonic propagation velocity has been measured in a variety of soft tissues. In a review

article, Wells [iy has compiled some of the more significant velocity data published in the literature. It would appear that accurate measurement

of velocity could help in characterizing soft tissues. Kossoff et al . [2], for example, have measured ultrasonic velocity in the human female breast and have concluded that the results as to characteristics of tissue type correlate reasonably well with the findings of mammography.

One problem in velocity measurement is the need for determining thickness of the tissue

along the path of propagation. Thickness can be measured directly or by the method of equivalent

water path given by Kossoff [2,3] for transmission and reflection velocity measurement techniques. For each new propagation path through

the tissue, another thickness measurement must

be made. The process of measuring velocity in

a variety of paths through the tissue could

therefore be quite time consuming.

In order to eliminate the need to determine

tissue thickness along the propagation path, a new pulse-echo method for measuring ultrasound

velocity has been developed. This technique

utilizes a reflecting surface at a fixed dis- tance from the transducer. The overall propagation path consists of a suitable medium, such

as water, and the tissue sample.

Since only the overall distance between the transducer and reflector need be constant, the thickness of the tissue need not be measured.

The technique can therefore be readily applied

in velocity measurements in different samples or through different paths in the same sample.

^Figures in brackets indicate literature

references at the end of this paper.

without repeated thickness calculations. Indeed,

the velocity data can be used to compute thickness in the specimen along the propagation path,

which can be compared with the thickness as measured directly, for checking the accuracy of the measurement.

A prototype of a device incorporating this reflection technique has been built, for mea- surements of propagation velocity in solids and

in tissue. The following sections describe in more detail the reflection technique, the prototype device implementing the technique, and re- sults of velocity measurements in solids and in tissue.

2. Description of the Technique

The method used for measuring propagation

velocity is illustrated in figure 1. A flat reference reflecting surface is positioned at a convenient fixed distance from the ultrasonic

transducer. Both are immersed in a suitable

propagating medium such as distilled water. An A-mode pulse-echo device displays an echo due to the reflecting surface. This echo is a reference

echo for the remainder of the velocity measurement.

The tissue specimen is next interposed between

the transducer and the reflector as shown in the figure. The A-scope is adjusted to display the echoes corresponding to the following interfaces:

the anterior boundary of the specimen, the pos- terior boundary of the specimen, and the re- flector surface as returned through the specimen.

The reflector echo is shifted in time from its reference position if the velocity in the specimen is different from that in the medium.

As shown in the figure, there are in general

two configurations for velocity measurement. In the first configuration, the specimen is positioned somewhere in between the transducer and

the reflector. In this case four echoes of in53
transducer water

reference reflector

initial pulse

transducer

reference echo

initio! pulse

transducer

reference reflector

onginol reference echo

displaced reference echo

target reference reflector n-t, J

Tllbreference echo

initial pulse anterior posterior / displaced

target target / reference echo echo / echo

Fig. 1. Reference reflector technique for velocity measurements

.

a) initial calibration

b) target interposed between transducer

and reference reflector

c) target in contact with reference

ref 1 ector

.

terest are produced. In the second configuration,

the specimen is positioned so that its posterior

boundary is coincident with the reflector. In this case, there are only three echoes to consider. The second configuration is readily

adapted for use in velocity measurements made via

a water bag, in which case the specimen and the reflector lie outside the water bag. For either configuration, velocity in the sample is calculated as follows. Denote the dis- tance between the transducer and reflector by L, the thickness of the specimen by i, the velocity

in the medium by Vq, and the velocity in the specimen by V. Let the time between the anterior

and posterior echoes from the specimen be T^, and

let the time displacement of the reflector echo

due to interposition of the specimen be T2. Then

the following equations apply for Tj and T2:

Ti = 2e/V

- 2L

Vo

T, = ^ [20:

L Vn

21"

V

= 2? iIVo

(1)

(2)

From these equations, the ratio of propagation

velocity in the specimen to that in the medium is

V/Vo = 1 + T2/T1 (3)

We note that To is positive if the reflector echo

is displaced toward the transducer when the specimen is in position, and negative if the reflector

is displaced away from the transducer.

The thickness of the specimen along the path

of propagation can be calculated from the above

equations, as

where

5./f.o = V/Vr

VoTi

2

(4)

. (5)

We note that Sq is the thickness of the specimen

measured by the A-scope calibrated for velocity

in the medium.

The significance of eqs. (1) through (5) is that the ratio of T2 to T^ is independent of the thickness i of the specimen. Accurate measurement of times Tj and T2 will give an accurate measurement of velocity in the specimen relative

to velocity in the medium. Even if the specimen

is repositioned or if a different specimen is examined, Tj and T2 will both change accordingly,

as long as the transducer to reflector distance

remains unchanged. Thus, the technique enables

rapid velocity measurements in a variety of tis- sues, as long as the reference echo is returned

through the specimen.

3. Description of the Device

A block diagram of a device utilizing the re- ference reflector technique for measuring ultra- sound velocity is shown in figure 2. An A-scope

and an oscilloscope are required. In addition,

a printer may be added for hard copy output of velocity data.

sync out \

a-scope

tinning circuitry program

circuitry

data

acquisition

circuitry

calculator

circuitry

digital display

transducer auxiliary display

oscilloscope

Fig. 2. Block diagram of velocity measurement

device and associated equipment.

Operation of the system is as follows. Before

the specimen is immersed in water, the A-scope is adjusted to display the echo due to the reference

reflector. The A-mode ("video") signal is fed to the data acquisition circuit, passing through a

54
time-gated threshold detector and a pulse shaper.

The processed echo from the reflector is displayed on the oscilloscope, together with a pulse

whose position on the display is variable. The user presets the time delay of the variable pulse,

so that the pulse overlaps the reference echo, as seen on the oscilloscope and confirmed by a frontpanel LED indicator. This procedure, which

stores in the data acquisition circuitry the prop- agation time from the transducer to the reflector,

is performed only once before the specimen is in- serted. At any time, calibration may be checked

by removing the specimen, and noting if the overlap condition is resumed. Following storage of the reference echo, the specimen is interposed between the transducer and

the reflector. The data acquisition circuit, by

adjustment of the time-gated threshold detector,

eliminates internal echoes from within the sample.

The present velocity device implements the con- figuration of figure Ic. Therefore only two echoes remain after processing: the anterior

echo of the specimen and the echo at the inter- face between the specimen and reflector.

The data acquisition circuit now contains

three pulses: the two echoes processed from the tissue specimen and the preset pulse supplied by the user as described earlier. Two gates are de- rived from these pulses. The first gate is opened by the anterior pulse and closed by the specimen-reflector boundary echo. The second

gate is opened by the specimen-reflector boundary

echo and closed by the preset pulse or opened by the preset pulse and closed by the specimenboundary echo, depending on which signal arrives

first. In the latter case, a flag is sent out

to the calculator circuit to perform a subtraction instead of an addition, as discussed later. Each gate enables one of two 4-digit BCD counters clocked at a rate of 15 MHz. By the end

of the second gate, two data words have been loaded into the counters. These two 4-digit

words, corresponding to Tj and T2 in eq. (3),

provide all the information required for calculating velocity in the specimen (relative to water). The maximum count of 9999 corresponds

to a round-trip travel time through 500 mm of water.

A 10-step hard-wired program sequentially con- trols the operation of a 4-function calculator

chip. These steps include clearing the calculater, entering the values Ti and T?, performing

the arithmetic operations of eq. (3), and dis- playing the result to 4 significant digits via

a front-panel LED display. In the event of a flag generated by the data acquisition circuitry,

the program treats T2/T1 as a negative number.

If desired, the results of each measurement are printed by an IBM output writer, 10 measurements

to a line. The timing> circuitry maintains synchronization

among all elements of the velocity measuring system. When the user presses the start button after checking on the oscilloscope that the correct echoes are present, the timing circuit in- sures that only a single set of data words enters

the calculator until calculation and printout of

the results are complete. Using a free-running

start signal, a new velocity value is calculated

and printed every two seconds.

4. Experimental Results

A. Measurements of Velocity in Solids

Before conducting measurements of ultrasound

velocity in tissues, it was necessary to check the accuracy of the reference reflector velocity tech- nique and its implementation in the device de- scribed in the previous section. For this purpose three objects were chosen: a 4-mm thick slab of polyvinylchloride (PVC), a 6-mm thick

slab of perspex, and a 10-mm thick combination of

the two materials. The ultrasonic frequency was

5 MHz. Fifty velocity measurements were made for each object. Results of measurements of velocity in the three test objects are given in table 1. Absolute

values of velocity are found by multiplying the respective relative values by the ultrasound

velocity in water, 1498 m/s. The standard deviations vary from about 0.3 to 0.5 percent of the measured values.

Table 1. Velocity measurements of selected solids.

Polyvinylchloride (PVC ) Relative velocity data {- 10"') 486 1486 1479 1472 1486 1479 1479 1486 1486 1486 486 1486 1500 1500 1486 1486 1479 1479 1486 1479

486 1486 1500 1486 1486 1500 1486 1486 1486 1500

486 1500 1486 1486 1486 1486 1472 1479 1500 1479

500 1486 1486 1486 1486 1472 1472 1486 1486 1486 Average relative velocity: 1.4860 Average absolute velocity: 2226.0 m/s Standard deviation; 11.2 m/s Perspex Relative velocity data 10- 1822 1811 1811 1811 1811 1811 1811 1822 1822 1811 1811 1820 1811 1811 1822 1811 1811 1820 1811 1811

1811 1820 1820 1800 1811 1822 1811 1811 1808 1800

1822 1811 1811 1800 1820 1811 1811 1811 1822 1820

1811 1811 1820 1820 1811 1811 1831 1811 1820 1811 Average relative velocity: 1.8138 Average absolute velocity: 2717.1 m/s Standard deviation: 9.4 m/s PVC-perspex combination

Relative velocity data (« 10"

3) 1670 1664 1664 1668 1674 1668 1674 1668 1668 1664

1664 1658 1664 1668 1664 1664 1670 1670 1674 1664

1658 1664 1664 1664 1664 1664 1664 1674 1658 1664 1658 1664 1674 1674 1670 1674 1668 1664 1664 1664

1668 1668 1668 1664 1674 1658 1674 1658 1668 1668 Average relative velocity: 1.6664 Average absolute velocity: 2496.3 m/s Standard deviation; 7.2 m/s

To check the accuracy of the results obtained

for each, object, the thickness given by eqs. (4) and (5) was compared to the thickness measured by

a caliper. Propagation times were respectively

3.60 ps, 4.42 us, and 8.02 us in the PVC, perspex,

and PVC-perspex combination. The corresponding

thicknesses calculated from the data and eqs. (4) and (5) are 4.003 mm, 6.005 mm, and 10.01 mm, respectively, which are within 0.1 percent of the measured values.

55
B. Measurements of Velocity in Soft Tissues

In order to demonstrate measurement of velocity

in soft tissue, a sample of fat in vitro and two human forearms in vivo were examined. As previously, the insonifying frequency was 5 MHz and 50 individual velocity measurements were taken for each target. Results of the measurements are given in table 2.

Table 2. Velocity measurements of soluble soft tissues.

Fat (bovine ) Relative velocity data (> 10"') 0987 0987 0987 0987 0987 0987 0987 0987 0991 0991

0991 0991 0991 0987 0987 0991 0987 0987 0987 0991 0987 0987 0987 0991 0987 0991 0991 0991 0987 0987

0991 0987 0991 0987 0991 0991 0987 0991 0983 0991 0991 0987 0987 0987 0991 0987 0987 0987 0987 0987 Average relative velocity: 0.9884 Average absolute velocity; 1480.7 m/s Standard deviation: 3.1 m/s Forearm (subject A ) Relative velocity data (» 10"^) 1057 1058 1058 1058 1057 1057 1058 1057 1057 1056

1056 1057 1057 1057 1057 1057 1058 1057 1058 1058

1057 1057 1057 1057 1056 1057 1057 1057 1057 1057

1056 1057 1056 1056 1057 1057 1057 1057 1057 1057

1057 1058 1057 1059 1057 1057 1057 1057 1056 1056 Average relative velocity: 1.0570 Average absolute velocity: 1583.4 m/s Standard deviation: 1.0 m/s Forearm (subject B ) Relative velocity data ( 10"') 1056 1056 1055 1055 1056 1056 1055 1056 1055 1055

1056 1055 1055 1056 1056 1055 1056 1056 1056 1055

1055 1056 1055 1055 1056 1055 1054 1053 1054 1053 1053 1053 1053 1054 1054 1055 1054 1054 1054 1053

1054 1054 1054 1053 1054 1053 1053 1054 1053 1053 Average relative velocity: 1.0546 Average absolute velocity: 1579.8 m/s Standard deviation: 1.7 m/s

that velocity measurements accurate to within

0.2 percent can be achieved with the device.

An improved model is now under construction.

It will incorporate microprocessor-based circuitry for increasing the number of measurements at

a single location to 500 per second. This will increase the precision of the measured velocity

as well as eliminate problems of motion during

measurement. The new device should enable scanning a structure such as the breast with the object of studying local variations in propagation velocity.

Acknowledgments

The author wishes to express his gratitude to the Harry de Jur Foundation and the Rose Teitelbaum Cancer Research Foundation for their partial support of this research. The author would

also like to thank Professor E.H. Frei, and Y. Dreier, I. Gonen, E. Grinwald, A. Kuprak, J. Leibovitz, and M. Moshitzky of the Weizmann

Institute for their roles in the project.

References

[1] Wells, P. N. T., Absorption and dispersion

of ultrasound in biological tissue. Ultra- sound in Med, and Biol . U 369-376 (1975).

[2] Kossoff, G., Fry, E. K. , and Jellins, J., Average velocity of ultrasound in the human female breast, J. Acoust. Soc. Am . 53 , 1730-1736 (1973T:

[3] Kossoff, G., Reflection Techniques for Mea- surement of attenuation and velocity, in Ultrasonic Tissue Characterization , M. Linzer,

ed., National Bureau of Standards Spec. Publ.

453, pp. 135-139 (U.S. Government Printing

Office, Washington, D.C., 1976).

The specimen of bovine fat was refrigerated

for several days and then warmed to room temperature before insoni fi cation . The velocity of

1481 m/s is approximately 1 percent higher than

the velocity for cow fat given by Goldman and Hueter [4], but well within the limits for mam- malian fat in general. The standard deviation

in the present measurement is about 0.2 percent.

The next measurements were made in the forearms of two male subjects, the same age (27). Care was taken to investigate the same portion

of forearm of each subject. The average velocities in the two subjects, 1583 m/s and 1580 m/s,

respectively, lie within the range given by Goldman and Hueter for human limbs. The standard

deviations are of the order of 0.1 percent of the measured velocities. More data would be required

to determine if the difference in velocity be- tween the two subjects is statistically significant.

[4] Goldman, D. E., and Hueter, T. F., Tabular

data on the velocity and absorption of high

frequency sound in mammalian tissues, J^. Acoust. Soc. Am . 28, 35-78 (1956).

5. Conclusion

A device for measuring ultrasonic propagation

velocity in tissue using a reference reflector

has been described. On the basis of experimental

results in solids and soft tissue, it appears

56
Reprinted from Ultrasonic Tissue Characterization II, M. Linzer, ed. , National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C., 1979).

MEASUREMENT OF THE TEMPERATURE DEPENDENCE OF THE VELOCITY

OF ULTRASOUND IN SOFT TISSUES

T. Bowen, W. G. Connor, R. L. Nasoni , A. E. Pifer, and R. R. Sholes

Departments of Physics and Radiology

University of Arizona

Tucson, Arizona 85724, U.S.A.

The velocity of 5 MHz ultrasound is being measured in tissue samples in order

to evaluate the feasibility of non-invasive monitoring of temperature distributions

produced during hyperthermia treatments. By employing a pul sed-ul trasound technique in which the time of the first zero-crossing of the received signal is re- corded, the velocity measurements are insensitive to reflections and to changes of attenuation. Results in the 35 to 45 °C range for fresh canine tissues, such as kidney, liver, and muscle, indicate that the rate of velocity change with temperature is correlated with the magnitude of the ultrasonic velocity, but the relationship appears to be altogether different for tissue fat. The results give encourage- ment to carry out the more extensive measurements, particularly in vivo , which would

be needed to determine feasibility of an ultrasonic temperature monitoring system.

Key words: Non-invasive temperature monitoring; soft tissue; temperature dependence;

ultrasound velocity; zero crossing detection.

1. Introduction

There has been increasing interest recently

in hyperthermia as a promising modality for control of some types of malignancies [1-3]^. In such treatments the tissue temperature must be raised from the usual body temperature of 37 °C

to approximately 43 °C for a period of one-half

to one hour. If the temperature is accidentally

a few degrees higher, all cells will be killed;

if a few degrees lower, the effect of the treat- ment will be negligible. A non-invasive tem- perature monitoring system is needed for this

application. In addition, such a system might

find other diagnostic applications where thermal anomalies are caused by changes in the circulatory system or in metabolic processes.

An ultrasonic temperature monitoring system

might be devised for soft tissue if some ultrasonic characteristic varies in a known way with

temperature. The most promising parameters ap- pear to be ultrasonic velocity and attenuation.

Earlier work on transmission-type tomographic

image reconstruction systems [4] indicated that

velocity data gives much more reproducible results. However, the task of utilizing velocity

changes to measure temperature is not an easy

one. At 37 °C the velocity of sound in water

changes 1.8 m/s per °C or about 0.12 percent

per °C. It is clear when one examines results

for the velocity of ultrasound in any particuiFigures in brackets indicate literature

references at the end of this paper.

lar tissue type that the variation from one sample to another is much larger than the variation over a 10 °C temperature range; con- sequently, one cannot hope to measure tem- perature ultrasonically. However, it still might be possible to measure temperature

'" hanges ultrasonically, making use of the fact

it the initial reference temperature, 37 °C,

is known to be quite uniform and corrections

for regional differences are also known. Suppose it is desired to monitor a temperature change from body temperature (37 °C) to

a treatment temperature in the neighborhood

of 43 °C within ± 10 percent for each tissue

type in the region of interest. It is the purpose of this work to discuss the first

experimental step toward answering whether or

not this property of soft tissue can be pre- dicted with such accuracy.

2. Experimental Arrangement

The experimental arrangement for the in vitro measurement of ultrasonic velocity in 1 to 10 cm

thick tissue samples as a function of temperature is shown schematically in figure 1. The

pulse generator provides a pulse which shock

excites the 12.7 mm diameter 5 MHz ultrasound

transmitter immersed in the water temperature

bath. This pulse also starts the digital timer.

The oscilloscope serves only to visually monitor the system; its trace is initiated by a trigger pulse from the pulse generator whose

timing can be delayed or advanced relative to the main pulse so as to observe any part of

57
Digital VOM

(Keithley 168)

Plastic Sample Bag

Thermistora

Acoustic

Transmitter

r:

Acoustic

Receiver

' Heater/

Circulator (Haake E52)

Thermometer

Tissue Sample Temperature Bath Tank

Pulse Generator (HP 2I4A)

Pulse Trigger Out Out

Oscilloscope

(Tektronix R(vl45A)

Ext Vertical Trigger Input

(a) Large Signal

Fig. 1. Block diagram of the experimental

arrangement for in vitro measurements of ultrasound velocity as a function of temperature.

the signal at the receiver. The output of the

12.7 mm diameter ultrasound receiver, which is also immersed in the temperature bath, is connected both to the vertical oscilloscope input

for observation of its amplitude and to a zero- crossing discriminator whose output stops the digital timer. The digital timer measures to the nearest 0.01 ms the transit time plus a fixed time related to the delays in the system

not connected with the sound propagation. The fixed delays are found by an extrapolation to zero separation of a series of measurements

of transit time in water as a function of separation within the errors of measurement.

This agrees with the results of others who have found that, although the pressure distribution

in the near field is very complicated, the average pressure sensed by a detector whose

dimensions are large compared to a wavelength be- haves like a plane wave [5]. Adjustment of the width of the shock excitation pulse from the pulse generator can provide a signal at the re- ceiver in which only one or two cycles have large

ampl i tude

.

The zero-crossing discriminator is an essential component to define a time reference in a received signal burst. Its operation is illus- trated in figure 2. By initiating discriminator

action at the occurrence of the first zero crossing, the timing becomes independent of re- ceived signal amplitude. This is important when

studying the temperature dependence of sound velocity as the attenuation (hence, the received

receiver

signal time

first zero crossing

(b) Small Signal

recei ver

signal

time

first zero crossing

Fig. 2. The first zero-crossing is shown

for a large signal (a) and a small signal (b) to illustrate that its position in time remains unaffeced

by changes of amplitude.

signal amplitude) also varies with temperature.

A pulsed ultrasound system with the timing ref- erenced to the first zero crossing not only is very stable in operation [6], but also is com- paratively immune to the effects caused by

multiple reflections, as these only disturb a later part of the received signal. The frequency dependence of ultrasonic velocity and attenuation in tissue affects the shape

of the received signal, which could introduce

timing shifts. The change of velocity with fre- quency, or dispersion, causes the pressure pulse

to propagate with a group velocity differing

slightly from the phase velocity of a continuous wave. Tissue dispersion is typically 0.1

to 1.0 m/s per MHz [7], which at 5 MHz shifts

the group velocity 0.5 to 5 m/s above the phase

velocity. For sample thicknesses on the order

of 2 cm the first zero crossing is still propa- gating with a velocity nearly equal to the group velocity, and only the leading edge of the first one-half cycle is distorted because the pulse is moving faster than its constituent fre- quency components [8]. A small velocity shift

of this magnitude would have little effect upon the observed rate of change with temperature.

The increasing attenuation at higher fre- quencies in tissue changes the signal waveform

with changing depth. However, the shape of the received waveform was not observed to change

significantly over the 35 to 45 °C range of temperatures at fixed depth.

For path lengths on the order of 2 cm the transit time jitter is less than 0.001 \is . The

0.01 \iS least count of the digital timer pres- ently limits the timing precision, but this can

be greatly improved with the same time digitization by adding an event counter and digital

logic so that the transit time is automatically

accumulated for, say, 1000 transmitted pulses.

However, this improvement will come about only

if the time reference oscillator is not synchronized with the start of the transit time measurement.

58
For samples more than a few centimeters

thick, which may often be encountered for i

vivo measurements , the optimum ultrasound fre- quency may be somewhat less than the 5 MHz ini- tially employed. If V(t) is the received

transducer voltage as a function of time near

the first zero crossing and if the voltage er- ror in detecting the true zero point is given,

it is desired to maximize dV/dt at the zero crossing. This would be proportional in the near field to f exp (-gaf), where a is the spacing between transducers and gf is the ultrasonic amplitude attenuation coefficient

for the tissue being examined. This function

is maximum when gaf = 1, or f = (ga)- . For example, 6 ^ 0.01 ps-mm"! is typical for many

soft tissues, so if a = 100 mm, f = 1 MHz. This result can be easily generalized for cases where the voltage error or noise is frequency

dependent.

In a typical data-taking run, the temperature of the bath is increased at a rate of 0.4

°C/miri. The rate must be reasonably high so that changes do not take place in the tissue

which are a function only of time. However,

the higher the rate of change of temperature,

the greater the lag of temperature at the center of the sample. In order to correct the

data for this temperature lag, a thermistor is inserted at the center of the sample to monitor

the temperature difference with respect to the

bath. It can be shown from the solution of the one-dimensional heat-diffusion equation when

the temperature at the surfaces is a linear

function of time that the average temperature

along the ultrasound path at time t, Q(t), is approximately given by:

^(t) =i«bath

^

Wmistor '

"^^'^ %ath thermistor ^^^^^^^ ^he temperatures at time t of the ,bath (and sample

surfaces) and center thermistor, respectively.

TEMPERATURE (°C)

Fig. 3. The speed of ultrasound as a function of temperature for water. The points represent data obtained in this work. The

solid curve represents the results of J. R. Lovett, J. Acoust. Soc. Amer . 45 , 1051 (1969).

For samples more than a few centimeters thick

and for in vivo measurement, other methods of heating the sample may be necessary to avoid

large temperature inhomogeneities. This may

often necessitate synchronized alternate pulsing of the heat source and the ultrasound

transmission to avoid spurious electrical

pickup.

Data obtained with the system outlined above

for water is illustrated in figure 3. Note the excellent agreement when the rate of variation

with temperature is compared with results ob- tained by others [ 9]

3. Results

Freshly excised samples of canine skeletal muscle, liver, kidney, spleen, brain, and fat were measured within one hour after sacrifice

of the animal. Each run began at approximately 35 °C. When approximately 45 °C was reached

the temperature was held constant for at least

30 minutes to verify that the observed changes were attributable to the changes of temperature and not to tissue degeneration. Some data were taken where the temperature was held con- stant at other values between 35 and 45 °C; no runs gave evidence of ultrasound velocity

changes due to tissue degeneration for samples

within the first hour after sacrifice. At later times (> 60 minutes after sacrifice),

velocity changes (occasionally dramatic de- creases) at constant temperature were ob- served with muscle samples. Each data run was least-square fitted to a polynomial in tem- perature containing linear and quadratic terms.

Table 1. Ultrasound velocity at 37 °C and rate

of change of ultrasound velocity with

temperature, dv/de, at 37, 40, 43 °C for fresh canine tissue samples, water,

and corn oi 1

Sound velocity (dv/do) [ (m/s )/°C]

Tissue at 37 °C type (m/s 37 °C 40 °C 4; °

Skeletal muscle 1589 1 1

23 1 03 0. 82 Skeletal muscle 1603 3 1

13 0 92 0. 71 Skeletal muscle 1588 8 1

16 0 95 0. 78 Skeletal muscle 1591 6 1

08 0 87 0 65 Liver 1591 7 0. 93 0 78 0 62 Liver 1594 8 1 13 0 96 0 80 Liver 1604 0 0 99 0 72 0 46 Kidney 1570 2 1 35 1 16 0 98 Kidney 1566 5 1 29 1 11 0 93 Kidney 1571 1 1 29 1 11 0 94

Bra i n 1563 2 0 67 0 62 0 26 (white matter)

Spl een 1601 3 1 31 1 07 0 84 Water 1522 5 1 84 1 66 1 48 Stomach fat 1411 9 -2 89 -2 85 -2 86 (fresh)

Stomach fat 1412 9 -3 43 -2 86 -2 91 .(refrig. 5 h) Corn oil 1420 0 -2 75 -2 58

59
1600

1550

skeletal

•muscl

e

'1 i ver

• ••kidney

• brain

•water

1400

1350

stomach

fat

37 39 41 43 TEMPERATURE (°C)

45

Fig. Typical data showing the dependence

of ultrasound velocity on temperature for fresh canine skeletal muscle,

liver, kidney, brain (white matter),

and stomach fat, as well as for water.

The results are listed in table 1 along with

the results for water and corn oil for comparison. Typical curves of ultrasound velocity

versus temperature are shown in figure 4. In every case, the variation of ultrasound velocity with temperature, dv/de', is less than the corresponding value for water, actually re- versing sign for fat. For tissues other than

fat at a specified temperature, a negative

correlation between the magnitude of the ultrasound velocity, v, and dv/de is apparent. This

is shown in figure 5, where dv/de at 37 °C is plotted against v at 37 °C for each sample (except brain and fat) and for water. Except for

one data point for liver and the single point

for spleen in figure 5, there appears to be a close connection between dv/de and v for water

and soft tissues having high water content.

4. Conclusions

The results of this study are encouraging in two respects: (1) Changes of ultrasound velocity in soft tissues with temperature can be simply, yet accurately, measured with readily available digital electronic circuitry. (2) The rate

of change of ultrasound velocity in soft tissues

with high water content in this study fell within ± 10 percent of a prediction based only upon

1.9

1 .8

1.7 o

3. 1.6 1 1.5

1.4-

3 1.3

1.2

1.1

1.0

0.91520

Fig. 5.

water A kidney

o liver

• muscle

X spleen

A

A A

O

J I 1540 1560 1580

v (m/s)

1600

The rate of change of ultrasound

velocity with temperature, dv/de,

at 37 °C is plotted as a function

of the corresponding ultrasound

velocity, v, at 37 °C for each fresh canine tissue sample and for water.

the magnitude of the velocity itself for 9 out of

12 samples. However, it is already apparent that

the relative fat content of various tissues may

be an important parameter. Before any conclusions can be reached concerning the feasibility

of non-invasive ultrasonic temperature monitoring, further measurements, especially in vivo , must more precisely ascertain the predictability

of ultrasonic velocity temperature dependence in soft tissues.

References

[1] Gerner, E. W., Connor, W. G., Boone, M. L. M., Doss, J. D. , Mayer, E. G., and Miller,

R. C, Radiology 116 , 433 (1975).

[2] Miller, R. C, Connor, W. G., Heusinkveld,

R. S., and Boone, M. L. M., Prospects for Hyperthermia in Human Cancer Therapy, Part

I: Hyperthermic Effects in Man and Spon- taneous Animal Tumors (to be published).

[3] Pettigrew, R. T., Gait, J. M. , Ludgate,

CM., Horn, D. B., and Smith, A. N.,

Br. J. Surg . 61, 727 (1974).

[4] Greenleaf, J. F. and Johnson, S. A., Algebraic Reconstruction of Spatial Distributions of Acoustic Velocity and At- tenuation in Tissue from Time-of-Fl ight and Amplitude Profiles, in Ultrasonic Tis - sue Characterization , M. Linzer, ed.. National Bureau of Standards Spec. Publ. 453, pp. 109-119 (U.S. Government Printing

Office, Washington, D.C., 1976).

60
Rschevkin, S. N., The Theory of Sound , pp. 440-444 (Macmillan, New York, 1963).

Lees, S., Gerhard, F. B. Jr., and Oppenheim, F. G., Ultrasonics 11, 269 (1973).

Carstensen, E. L. and Schwan, H. P., J_. Acoust. Soc. Amer . 3i, 305 (1959); Carstensten, E. L., Absorption of Sound in Tissue

(this publication, p. 29).

[8] Icsevgi , A. and Lamb, W. E. Jr., Phys . Rev . 185, 517 (1969). Section IV of this paper

gives an elegant and clear explanation of the behavior of the pulse velocity when the group velocity exceeds the phase velocity.

[9] Lovett, J. R., J. Acoust. Soc. Amer . 45,

1051 (1969).

61

Reprinted from Ultrasonic Tissue Characterization II, M. Linzer, ed.. National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C., 1979).

ULTRASONIC ATTENUATION IN NORMAL AND ISCHEMIC MYOCARDIUM

M. O'Donnell, J. W. Mimbs, B. E. Sobel , and J. G. Miller

Washington University

St. Louis, Missouri 63130, U.S.A.

The ultrasonic attenuation coefficient of dog myocardium was measured in vitro over the frequency range 2 to 10 MHz. Changes in the attenuation of normal myocardium

were measured as a function of time after excision at fixed temperatures. Results of measurements made on tissue maintained at 35 °C revealed progressive changes in the attenuation as a function of time, presumably indicative of tissue degradation. Re- sults of measurements at 19.5 °C, however, showed no significant changes in attenuation

up to 4 hours following excision. The temperature dependence of the attenuation was measured over the range 20 ^C to 37 °C, yielding the result that the attenuation

coefficient at 37 °C is about 20 percent lower than that at 20 °C. The attenuation co- efficient was measured in vitro at 20 °C in hearts from dogs previously subjected to coronary occlusion and sacrificed at intervals ranging from 15 minutes to 3 days fol- lowing occlusion. Results of these measurements indicate a modest decrease in the attenuation of ischemic tissue measured at 15 minutes, 1 hour, 6 hours and 24 hours,

and an increase in attenuation of ischemic regions studied 3 days following occlusion.

Key words: Ischemic injury; myocardial infarction; ultrasonic attenuation.

1. Introduction

Previous reports from our laboratory presented

the ultrasonic attenuation in normal myocardium

and in myocardium subjected to ischemic injury

from dogs sacrificed 4 to 11 weeks after coronary

artery occlusion. In this report, we present the results of a new series of attenuation measurements on dog left ventricle. Results from this series of measurements are analyzed to: (1) contrast attenuation in normal and ischemic zones

of tissue from animals sacrificed 15 minutes,

1 hour, 6 hours, 24 hours, and 3 days following

coronary occlusion, (2) examine changes in the ultrasonic attenuation of tissue in vitro at fixed

temperatures as a function of time after excision,

and (3) examine the temperature dependence of the ultrasonic attenuation of tissue in vitro .

2. Methods

A. Ultrasonic analysis

TRANSMITTER SPECIMEN RECEIVER

DRIVER TIMING UNIT

SPECTRUM

ANALYZER

GATE

SAMPLE a HOLD

ADC

ADC

DIGITAL PROCESSING STORAGE

Fig. 1. Block diagram of the ultrasonic

instrumentation used in this study.

The instrumentation employed for ultrasonic

analysis is depicted in figure 1. The transmitting transducer and driver yielded an ultrasonic

pulse with frequency components of sufficient

amplitude to permit operation over a range of

2 to 10 MHz. Details of transducer design are discussed subsequently. Under control of a timing unit, broadband ultrasonic pulses were gated

into a slowly sweeping analogue spectrum analyzer.

Output pulses from the spectrum analyzer, comprising the logarithm of the Fourier transform of the received ultrasonic pulses, were converted by a sample-and-hold unit into a slowly varying (dc)

signal. As the spectrum analyzer was slowly

swept through frequency, the output of the sampleand-hold and a voltage corresponding to the fre- quency being analyzed by the spectrum analyzer were

transmitted to two analogue-to-digital converters

(ADC's). The digital outputs from the ADC's were

recorded on magnetic tape for subsequent analysis.

The procedure used for the quantitative measurement of the attenuation following transmission of ultrasound through tissue has been described in detail in previous reports [1,2]^ and is similar

to a substitution technique developed by Schwan

^Figures in brackets indicate literature

references at the end of this paper.

53
and Carstensen [3]. If reflections at salinetissue interfaces can be neglected (and in the absence of artifacts arising from phase cancellation effects), the ultrasonic attenuation coefficient of tissue of thickness Az is given by

[Va(v) - Vb(v)] , . at = ; ^

' ^ AZ log^oe

where the term [V/\(v) - Vb(v)] represents the signal loss, which is obtained by subtracting the logarithmic output of the spectrum analyzer in the presence of tissue [Vd(v)] from that recorded

in the absence of tissue IVa(v)]. The signal loss (expressed in decibels) is calibrated by comparison

with an electronic attenuation standard.

Figure 2 illustrates the use of the method to determine the attenuation coefficient of a test object, a flat polyethylene plate of Az = 0.5 cm. The left panel of figure 2 exhibits a plot of Va(v) with no specimen present (upper curve) and

a plot of Vb(v) with the polyethylene specimen

present (lower curve). The result of subtraction

of the two curves in the left panel of figure 2 is displayed as the attenuation-frequency plot in the right panel, with data points calculated according

to eq. (1). For cases in which reflections from

saline-specimen interfaces cannot be neglected,

the slope of the attenuation coefficient versus frequency curve displayed in figure 2 remains a valid ultrasonic index, although the attenuation

coefficient may not. (The ultrasonic pulse

length used in these studies was less than 0.05 cm

in a polyethylene plate of Az = 0.5 cm. Thus standing wave effects could not occur.)

A possible source of artifact in the apparent

attenuation coefficient as determined from eq.

(1) arises from phase cancellation effects [1,2]. Phase cancellation effects may occur if inhomogeneities in the tissue distort the ultrasonic

field presented to a spatially extended piezoelectric receiving transducer. These wavefront

distortions may result from transmission of ultra- sound through tissue with variations in surface

characteristics, internal structural characteristics, or both. When the wavefronts incident upon

a piezoelectric receiver are distorted, the

generated electrical signal is degraded because

of the phase sensitive nature of the receiver.

Phase cancellation effects can induce artifacts

into attenuation data which might be interpreted

incorrectly as reflecting only the absorption and scattering properties of a specimen [1,2,4].

An intensity sensitive ultrasonic receiving

transducer which is inherently insensitive to phase cancellation effects is under continuing

development in our laboratory [1,2]. This trans- ducer makes use of the acoustoelectric effect in single crystal cadmium sulfide to convert the in- tensity of an incident ultrasonic wave into an electronic current in the semiconducting crystal.

An illustration of phase cancellation effects is presented in figure 3, which contrasts the per- formance of a piezoelectric and an acoustoelectric

transducer of equal diameters (1.3 cm). The upper

panel of figure 3 illustrates the apparent attenuation coefficient as a function of frequency for four adjacent sites of dog left ventricle measured with the piezoelectric receiver. Marked

variability is observed in data obtained from four morphologically similar regions. The lower panel

depicts the results of measurements on the identical four sites; however, the intensity sensitive

acoustoelectric receiver was used. The data of

the lower panel exhibit more uniform consistency,

presumably reflecting the reduction or elimination

of artifacts due to phase cancellation.

The present configuration of the acousto- electric receiver is cumbersome and would not permit the rapid collection of data that was re- quired in experiments on ischemic tissue (see

below). All data reported here were obtained

using identical focused piezoelectric transducers

(1.3 cm diameter, 5 cm focal distance) for trans- mitter and receiver. By positioning the specimen

of interest so that it lay entirely within the depth of field of the focused transducers, phase

cancellation artifacts were minimized. A com- parison of the performance of the focused trans- ducers and the acoustoelectric receiver is shown

in figure 4. In this figure the apparent at- tenuation coefficient versus frequency plots ob- tained from analysis of the identical four ad- jacent sites of left ventricle are presented.

The upper panel presents data obtained with the

Fig. 2. The left panel is a plot of Va(v) obtained without a specimen and Vb(v) obtained

with a specimen (a polyethylene plate of Az = 0.5 cm in this case). The right

panel depicts the attenuation versus frequency plot determined using eq. (1) and

the data shown in the left panel.

64
0.8

0.6

0.4

0.2-

0.0

1.0

0.8 -

0.6 -

0.6

0.4

Piezoelectric receiver

Acoustoel ectric receiver

O.OL

4 6 FREQUENCY (MHz)

Fig. 3. Planar piezoelectric transmitter. The upper panel depicts the apparent attenuation coefficient as a function of fre- quency for four contiguous sites of dog

left ventricle measured with a 1.3 cm diameter planar piezoelectric receiver.

The lower panel depicts the results of measurements on the identical four sites

using a 1.3 cm diameter intensity sensitive acoustoel ectric receiver.

0.8r

0.6

0.4

0.2

0.0

0.8

0.6

0.4

0.2

Focused piezoelectric

receiver

0.0

Acoustoelectric receiver

4 6 FREQUENCY (MHz)

Fig. 4. Focused piezoelectric transmitter. The upper panel illustrates the apparent at- tenuation coefficient as a function of frequency for four contiguous sites of dog

left ventricle measured using a 1.3 cm di- ameter focused (5 cm focal distance) piezoelectric receiver. The lower panel de- picts the results of measurements on the identical four sites, using a 1.3 cm diameter acoustoelectric receiver.

focused piezoelectric receiver and the lower

panel presents data obtained with the acoustoelectric receiver. A focused piezoelectric trans- mitter was used to obtain the results shown in both panels of figure 4. The focused piezoelectric transducer arrangement (fig. 4) is seen

to offer significant improvement over the planar

piezoelectric transducer arrangement of figure 3. Data reproducibility and consistency remain,

however, more satisfactory with the use of the acoustoelectric receiver.

In an attempt to quantitate the extent to which phase-cancellation effects resulted in de- gradation of attenuation-frequency data, a statistical index was developed. Because phase

cancellation effects in attenuation-frequency

data may manifest themselves as erratic (nonmonotonic) frequency dependences (in contrast with

the expected monotonic variation of attenuation

with frequency), one method of segregating the data is on the basis of a statistical test of the goodness of a fit to a monotonic curve. Using a

65
three parameter fit to the measured signal loss date [(V/\-Vb) of eq. (1)], a root mean square deviation (RMSD) was calculated. The RMSD was defined by

RMSD = (v, - "0'' jV [ym(-^') - yc(v)]

j dv (2)

where v is the ultrasonic frequency, - v-^) de- fining the frequency interval of the measurements.

y^{v) is the measured signal loss at frequency v, and y(-(v) is the calculated signal, loss, deter- mined by a least squares three parameter fit to the data, ihe units of RMSD are the same as those

of y(v), in this case decibels (dB). The value of RMSD was used to quantitate the degree of non- monotonicity and thus to estimate in a relative

fashion the contribution of phase cancellation effects. Large values of RMSD would be expected

whenever substantial phase cancellation contributions influenced the apparent attenuation.

The application of this approach is demonstrated in figure 5, which illustrates our progress in systematically reducing artifacts due to phase

cancellation. The calculated RMSD for each at- tenuation-frequency curve obtained with several transducer combinations is shown. Data obtained

in 20 measurements with a 1.3 cm diameter planar

piezoelectric receiver are shown in panel A and

in 44 measurements using a 0.2 cm diameter planar

piezoelectric receiver in panel B. In both cases

the transmitter was a 1.3 cm diameter planar

piezoelectric transducer. The reduced RMSD's of

1 3cm diameter A

1 piezoelectric receiver N= 20

/

\ 0 2 cm diameter n piezoelectric receiver

1 N -- 44

1

1 Focused piezoeleclric r-

, receiver and tionsmitter

1 N = 42

1 1.3cm diameter

' acoustoelertf ic receiver D

1 N : 33

1 ill 1 1 1 1 1 1 00 05 10 15 20 2.5 30 35 4 0 45

ROOT MEAN SQUARE DEVIATION (dB)

Fig. 5. Histogram showing the range of cal- culated root mean square deviations

(RMSD's) of attenuation-frequency

curves determined with four different transducer configurations.

panel B as compared with panel A presumably re- flect a decrease in the phase cancellation artifacts achieved by reducing the area over which

the ultrasonic field was integrated. Panel C exhibits the results of measurements on 42 sites made with a focused transducer pair and demonstrates substantial improvement over the arrangements of panels A and B. (It should be noted,

however, that substantial artifacts due to phase

cancellation occur in the presence of intervening

tissue located outside of the focal zone. Thus,

for future applications in vivo , the use of a focused transducer does not appear to be a satisfactory method for minimizing artifacts due to phase cancellation.) The results of the measurements on 33 sites using the acoustoelectric re- ceiver are presented in panel D of figure 5. The very small RMSD's obtained with the intensity

sensitive acoustoelectric receiver reflect the inherent freedom from phase cancellation artifacts, making a transducer of this design potentially suitable for future in vivo applications.

B. Tissue preparation and independent

indices of pathology

All measurements were carried out in vitro on myocardial tissue obtained from adult, mongrel,

15 to 30 kg dogs. In studies of ischemic injury,

each dog was intubated after anesthesia with

sodium pentobarbital (25 mg/kg, intravenously),

placed on a Harvard respirator, ventilated with

room air, and subjected to a left thoracotomy via

the fifth interspace. The pericardium was in- cised, and the left anterior descending coronary artery dissected free immediately distal to the first ventricular branch and ligated. The pericardium was left open. For dogs studied at 6 hours, 24 hours, and 3 days following occlusion,

the chest was closed conventionally, with intrapleural suction maintained for at least one hour

via a chest tube.

At the time of sacrifice, each animal was again

anesthetized with sodium pentobarbital (50 mg/kg,

intravenously). The heart was rapidly excised

and placed in a 0.9 percent NaCl solution. To prepare the tissue for ultrasonic analysis an in- cision was made at the root of the aorta, con- tinued interiorly along the left ventricular sur- face of the interventricular septum to the apex,

and extended posteriorly and superiorly, terminating at the base of the heart. This permitted

prompt excision of a segment of the left ventricular anterior and apical wall. This segment com- prised the area of infarction and surrounding

area of normal myocardium in all animals subjected to coronary ligation. (We note that this seg- ment was measured unaltered, i.e ., no additional

preparation such as further slicing to achieve

flat or parallel surfaces was undertaken.) Except

as noted, ultrasonic analysis was initiated within

5 minutes following the death of the animal, and completed within 45 minutes.

Tissue from animals sacrificed at 24 hours and

72 hours following coronary occlusion was analyzed

biochemically for creatine kinase (CK) content,

an established index of tissue pathology. One centimeter diameter biopsies corresponding to re- gions of ultrasonic analysis were obtained im- mediately following ultrasonic measurement. To facilitate comparison of data from different ani- mals, regional CK activity was expressed as the percentage of depletion compared to activity in normal myocardium from the same animal. Sites

with CK depletion of greater than 40 percent were

classified as ischemic and those with CK depletion

less than 20 percent were classified as normal.

For dogs sacrificed from 15 minutes to 6 hours following occlusion, colloidal carbon black was

66
injected into the left atrium fifteen seconds prior to killing the animal for the purpose of differentiating regions of ischemic and normal myocardium. Regions of ischemia did not change

color after injection, while non-ischemic regions

rapidly were stained black. Visual inspection of

the tissue after excision was used to differentiate normal from ischemic tissue. Analysis of

60 sites from 4 control dogs indicated that the presence of dye did not alter the ultrasonic measurements of normal myocardium.

3. Results

Prior to addressing questions related to ischemic injury, it is necessary to determine ex- perimentally the range of variability introduced

into the results of ultrasonic attenuation mea- surements in vitro by variables such as: (1) the time interval that elapses between the sacrifice

of the dog and the ultrasonic measurement, (2) the temperature of the tissue during ultrasonic

measurement, and (3) the specific region of the

left ventricle that is analyzed.

A. Time interval between sacrifice

and measurement

In an effort to estimate the extent to which

tissue degradation compromises the results of in vitro measurements, the ultrasonic attenuation

coefficient of dog myocardium was measured at

Time after

exci sii

15 min

2 h

4 h

15 min

2 h

4 h

B. Temperature dependence of the attenuation

To relate the results obtained at 20 °C to what might be expected if the measurements were

carried out at 37 °C, an additional series of experiments was designed to elucidate the tem- perature dependence of the attenuation in a manner relatively independent of effects arising from tissue degradation. Results from the previous series of experiments (table 1) suggested the possibility that tissue might be temporarily stored at approximately 20 °C without undergoing significant degradation be- tween measurements made at elevated temperatures.

Using this approach, four freshly excised hearts were used for a measurement of the attenuation at 20.5 °C, 25 °C, 30 °C, and 37 °C. Each segment

of left ventricle was placed in a 20.5 °C bath

and analyzed ul trasoni cally immediately after

constant temperature as a function of time fol- lowing excision. All experiments were performed

in a 0.9 percent NaCl bath with temperature re- gulated to ± 0.2 °C by means of a controller and

reci rcul ator.

In table 1 data are displayed as a function of

time following excision for experiments performed

at two temperatures: (1) 19.5 °C (analysis of 27 regions from 3 hearts) and (2) 35 °C (analysis of

27 regions of 3 additional hearts). The ultra- sonic attenuation coefficient as a fraction of frequency was approximately independent of time

up to 4 hours following excision for tissue maintained at 19.5 °C. When the temperature was maintained at 35 °C, however, a definite change

with time was observed. For measurements at

35 °C, the value of the slope of a least squares

line fit to the attenuation versus frequency data changed from (0.061 ± 0.003) cm-iMHz-i (mean ± standard error (S.E.)) at 15 minutes following

sacrifice to (0.071 + 0.003) cm-iMHz-i at 4 hours following sacrifice. It thus appears that

no statistically significant changes in attenuation occur for periods up to several hours fol- lowing excision for tissue maintained at approximately 20 °C, although small {'^ 15 percent) but significant changes occur over that time interval

for tissue maintained at 35 °C. These results

motivated the choice of 20 °C as the temperature

at which the extensive series of measurements on ischemic and normal myocardial tissue in vitro

reported below were carried out.

excision. After analysis at this temperature,

the tissue sample and holder were removed from

the measurement bath and placed in a storage bath which was maintained at 19.5 °C. The measurement

bath was heated to 25 °C and regulated to maintain

this temperature to ± 0.2 °C. Upon stabilization

of the temperature at 25 °C, the sample and holder were reinserted into the original bath and al- lowed to equilibrate, whereupon the ultrasonic

attenuation was measured. The same procedure was repeated for measurements at 30 °C and 37 °C,

with the entire process lasting about 80 minutes.

To check the validity of this method for identifying the true temperature dependence, the attenuation obtained at 37 °C using the above procedure

was compared to the attenuation measured at 37 °C for 3 additional freshly excised hearts at 27 sites. The slope of the attenuation for these measurements made at 37 °C within minutes of exTable 1. Ultrasonic attenuation of normal myocardium as a function of time after excision.

Number Number Temp. Attenuation coefficient (cm"') (mean + SE) Slope of a vs^ of of frequency

sites dogs O

C 2 MHz 4 MHz 6 MHz 8 MHz 10 MHz ( cm ' MHz -1)

27 3 19 .5 0. 10 ± 0 02 0. 19 ± 0 02 0 34 ± 0 02 0 38 ± 0.03 0 65 ± 0 03 0 072 ± 0 002

27 3 19 .5 0 10 ± 0 02 0. 20 ± 0 02 0 36 ± 0 02 0 50 ± 0.03 0 70 z 0 03 0 075 ± 0 002

27 3 19 .5 0 10 ± 0 02 0 20 ± 0 02 0 35 ± 0 02 0 49 ± 0.03 0 69 ± 0 03 0 .075 ± 0 002

27 3 35 0 09 + 0 02 0 17 ± 0 03 0 30 ± 0 03 0 43 + 0.03 0 56 ± 0 04 0 .061 ± 0 003

27 3 35 0 09 ± 0 02 0 19 ± 0 03 0 34 ± 0 03 0 47 ± 0.03 0 61 ± 0 04 0 .068 ± 0 003

27 3 35 0 11 ± 0 02 0 22 ± 0 .03 0 37 ± 0 03 0 52 ± 0.03 0 64 ± 0 04 0 .071 ± 0 003

67
Table 2. Ultrasonic attenuation of normal myocardium as a function of temperature.

Number Number Temp. Attenuation coefficient (cm"^) (mean ± SE) Slope of a vs of

ites of dogs 2 MHz 4 MHz 6 MHz 8 MHz 10 MHz frequency

(cm-' MHz-i)

36 4 20.5 0 10 ± 0 02 0 19 ± 0 02 0 34 ± 0 03 0 48 + 0 03 0 64 ± 0 03 0.071 + 0.002

36 4 lb U 10 ± 0 02 0 19 + 0 02 0 33 ± 0 03 0 45 ± 0 03 0 61 ± 0 03 0.058 ± 0.UU2

36 4 30 0 10 ± 0 02 0 17 ± 0 02 0 31 ± 0 03 0 43 ± 0 03 0 58 ± 0 03 0.054 ± 0.002

36 4 37 0 11 ± 0 02 0 19 ± 0 02 0 31 ± 0 03 0 41 ± 0 03 0 56 ± 0 03 0.058 ± 0.002

cision was (0.060 ± 0.002) cm"i MNz"! in good

agreement with the value 0.058 ± 0.002 cm-^ MMz"! measured at 37 °C for the 36 sites of tissue

stored at 19.5 °C between measurements. This re- sult suggests that the procedure is methodologically sound. Results of this series of experiments on 36 regions from 4 hearts designed to determine the temperature dependence of the attenuation coefficient are presented in table 2. The slope of a least squares line fit to the attenuationfrequency data decreases approximately linearly

with increasing temperature over the range

20.5 °C to 37 °C, with the value at 37 °C being

about 20 percent less than that at 20.5 °C.

C. Regional variations in attenuation

In order to identify possible variations in the attenuation coefficient as a function of the re- gion of the left ventricle that was analyzed, 102 sites from 4 dogs not subjected to coronary ligation were studied and the results segregated into

4 groups based on the region investigated. Data from these experiments are presented in table 3. Values of the attenuation coefficient for regions

in the mid-posterior and apical aspects of the left ventricle were essentially identical. Some- what higher values were exhibited by regions in the papillary muscles and generally lower values were exhibited by regions near the base of the heart. These results are summarized in figure 6, utilizing the slope of a least squares line fit

to the attenuation coefficient versus frequency

plots for comparative purposes.

Based on the results of this study of regional

variability of the ultrasonic attenuation coefficient of normal myocardium, subsequent studies were conducted primarily on sites from midposterior and apex, avoiding sites from the papillary muscles and the base. With this approach, the value of the slope of the attenuation

for normal left ventricle, as determined from measurements at 245 discrete sites from 36 dogs, was (0.072 ± 0.001) cm"! MHz'i (mean ± S.E.).

0.08

iS 0.06

0.04

LUo 0.02

posterior

aspect

=21

papi 1 lary

muscl es

7^

// '//

/' / / f.

N=38 N=21 N=21 apex mid- base posterior

Fig. 6. Regional variation of the slope of the attenuation (2 to 10 MHz) in normal myocardium.

Number Number Temp Descrip- of of tion sites dogs °C

Table 3. Regional variation of ultrasonic attenuation in normal myocardium.

Attenuation coefficient (cm"M (mean ± SE)

2 MHz 4 MHz 5 MHz 8 MHz 10 MHz

Slope of g vs frequency

(cm'i MHz-i)

20 0.11 ± 0.02 0.20 ± 0.02 0.34 ± 0.02 0.45 ± 0.03 0.62 + 0.03 0.064 ± 0.002

20 0.10 ± 0.02 0.19 ± 0.02 0.34 ± 0.02 0.48 ± 0.03 0.64 ± 0.03 0.070 ± 0.002

Base

Mid- posterior

Apex

21

21

39

Papillary 21 muscles

20 0.10 ± 0.02 0.19 ± 0.02 0.35 ± 0.02 0.49 ± 0.03 0.65 ± 0.03 0.071 ± 0.002

20 0.13 + 0.02 0.26 ± 0.02 0.41 ± 0.02 0.55 ± 0.03 0.76 ± 0.03 0.079 ± 0.002

68
D. Effects of ischemic injury

To investigate changes in physical properties of tissue resulting from ischemic injury, ultrasonic measurements were carried out on freshly excised

hearts previously subjected to coronary occlusion

for intervals of 15 minutes, 1 hour, 6 hours, 24 hours, and 3 days. Results of these measurements

are summarized in table 4. The attenuation measured at 15 minutes, 1 hour, 6 hours, and 24 hours following coronary occlusion is lower than that ex- hibited by normal myocardium, while that at 3 days

following occlusion is higher than that of normal. The attenuation values reported in table 4 rep- resent averages of the values obtained for all sites analyzed. Results illustrated in figures 4 and 5 suggest that artifacts arising from phase

cancellation effects may occur in data obtained

using the focused transmitter-focused receiver con- figuration. To eliminate measurements exhibiting

probable phase cancellation effects from further consideration, an index based on RMDS (eq. 2) was

used to segregate the data. Attenuation coefficient versus frequency curves exhibing RMSD's greater than 0.25 dB were deleted from further con- sideration. The value 0.25 dB was selected for

segregating the data because it represents an RMSD

two times the maximum RMSD exhibited by data ob- tained using the phase cancellation insensitive

acoustoel ectric receiver. The results of segregating the data in this way are illustrated in table 5. The average values of the slope of the attenuation versus frequency curves are presented

for two groupTl {^) data including sites exhibiting phase cancellation effects, and (2) data ex- cluding sites exhibiting phase cancellation effects.

A comparison of the number of sites contributing

to the average slope in each group indicates that a modest but significant number of attenuation versus frequency curves were compromised by phase cancellation effects.

The results of experiments on normal and ischemic myocardium are summarized in figure 7. The average slope of the attenuation (last column of table 5) is shown at 15 minutes, 1 hour, 6 hours,

24 hours, and 3 days following coronary occlusion.

The slope of the attenuation of ischemic myocardium

is significantly lower than that of normal myocardium for times ranging from 15 minutes through 24 hours following coronary occlusion and is significantly larger at 3 days following occlusion.

Descrip- of tion sites

Table 4. Ultrasonic attenuation of normal and ischemic myocardium

Number Number Temp. Attenuation coefficient (cm'^) (rtiean ± SE)

C of

dogs 2 MHz 4 MHz 6 MHz 8 MHz 10 MHz

Slope of g vs frequency

(cm-' MHz-')

Normal Time after

occl usion

245 36 20 0.10 ± 0.02 0.19 ± 0.02 0.33 ± 0.02 0.48 ± 0.03 0.65 ± 0.03 0.072 ± 0.001

15 min 56 5 20 0 10 0 02 0 17 + 0 02 0 32 + 0 02 0 43 + 0 03 0 57 + 0 03 0 063 + 0 003

1 h 64 8 20 0 09 + 0 02 0 17 0 02 0 32 4- 0 02 0 43 + 0 03 0 57 + 0 03 0 063 + 0 003

6 h 59 5 20 0 08 0 02 0 15 + 0 02 0 30 + 0 02 0 44 0 03 0 57 + 0 03 0 066 + 0 002

24 h 29 11 20 0 08 0 02 0 16 + 0 02 0 29 + 0 02 0 43 0 03 0 59 + 0 03 0 067 + 0 002

3 d 31 7 20 0 11 + 0 02 0 20 + 0 02 0 38 + 0 02 0 52 0 03 0 69 + 0 03 0 079 + 0 002

Table 5. Slope of the ultrasonic attenuation of normal and ischemic myocardium.

Including sites Excluding sites exhibiting phase exhibiting phase

Description cancellation effects cancellation effects

Time after Numoer Temperature Character Number Slope Number Slope coronary occlusion of dogs °C of sites of sites (cm"' MHz"M of sites (cm"^ MHz'M

15 min 5 20 normal 58 0 073 ± 0 003 45 0 072 + 0 003

15 min 5 20 ischemic 56 0 063 + 0 003 49 0 062 + 0 002

1 h 8 20 normal 69 0 072 + 0 003 52 0 071 0 003

1 h 8 20 i schemic 64 0 063 + 0 003 57 0 062 + 0 003

6 h 5 20 normal 59 0 072 + 0 002 51 0 072 + 0 002

6 h 5 20 ischemic 59 0 066 + 0 002 49 0 064 + 0 002

24 h 11 20 normal 29 0 073 + 0 002 24 0 068 + 0 002

24 h 11 20 ischemic 29 0 067 + 0 002 27 0 060 + 0 002

3 d 7 20 normal 30 0 072 + 0 002 25 0 072 + 0 001

3 d 7 20 i schemic 31 0 079 + 0 002 28 0 082 0 002

£9
I 0 08 MX

.0 07

So 06 o

005

Fig. 7.

0.09 i

NORMAL ISCHEMIC

N=24 27

I5min Ih 6h 24 h TIME AFTER OCCLUSION

25 28

3d

Slope of the ultrasonic attenuation

(2 to 10 MHz) for normal and ischemic

myocardial tissue determined at specified

intervals following coronary occlusion.

tenuation might be expected to accompany edema,

which is a recognized correlate of recent ischemic injury. If the small decrease in at- tenuation of ischemic tissue is corroborated by measurements ir[ vivo , the use of an index based

on the ultrasonic attenuation to characterize the state of myocardium might be approached. Efforts

to use an index based on attenuation to characterize the state of myocardial tissue might

utilize each heart as its own control thus abro- gating data variability due to regional myocardial

variations as documented in table 3. An increase in attenuation over that of normal myocardium is observed in tissue subjected to ischemic injury and measured three days following coronary occlusion. Previous reports from this laboratory documented substantial increases in at- tenuation in tissue studied 4 to 11 weeks after coronary occlusion [2,9]. This increase in at- tenuation, evident at three days following occlusion and reaching substantial magnitude weeks

after occlusion, appears to be related to the on- set of scar formation, reflecting the increase in the collagen content of necrotic tissue.

4. Discussion

Emphasis in the present studies was placed on systematic measurements making use of carefully

defined control experiments. Either creatine

kinase depletion or reduced uptake of colloidal

carbon was used as an independent index for documenting myocardial ischemia. Care was taken

to eliminate artifacts due to ultrasonic phase

cancellation effects, a potentially significant

source of variability in attenuation coefficient

measurements. Methods suitable for conducting

meaningful experiments on excised tissue were de- veloped and validated. Results of the study

addressing the problem of tissue degradation fol- lowing excision led to the choice of ^ 20 °C rather than 37 °C for the present series of in- vestigations. The possibility of significant

changes in the ultrasonic properties of tissue

measured in vitro as a function of time following excision was considered by Hueter [5], and more recently by Frizell and Carstensen [6], and

by Bamber et al . [7]. Previous studies examined

changes for time intervals substantially larger

(tens of hours) than the present experiments,

which had the more limited goal of defining the range of validity of attenuation measurements on freshly excised tissue.

The temperature dependence of the attenuation

of normal myocardium was measured over the range

^. 20 °C to 37 °C using a technique designed to minimize artifacts arising from tissue degradation. Results of these measurements suggest that

the data obtained at 37 °C might be expected to differ by only about 20 percent from that ob- tained at 20 °C. However, these limited measurements on normal myocardium do not adequately ad- dress the possibility of differences in the tem- perature dependence of the attenuation exhibited

by ischemic as opposed to normal tissue. Results of this study indicate a small de- crease in the attenuation in the early stages of

a myocardial infarct (up to 24 hours following

coronary occlusion). Although mechanisms re- sponsible for the attenuation of soft tissue are inadequately understood [8], a decrease in atAcknowl edgments

Lawrence J. Busse carried out the investigations of phase cancellation effects described in the text and presented in figures 3, 4, and 5. Pranoat Suntharothok-Priesmeyer was responsible

for production of the text and illustrations.

This work was supported in part by grants

HL19537, HL17646, and HL07081 from the National

Institutes of Health.

References

[1] Busse, L. J., Miller, J. G., Yuhas, D. E., Mimbs, J. W., Weiss, A. N., and Sobel , B. E., Phase Cancellation Effects: A Source of Attenuation Artifacts Eliminated by a CdS Acoustoelectric Receiver, in Ul trasound

in Medicine , D. White, ed., vol. 3, pp. 1519-1535 (Plenum Press, New York, 1977).

[2] Miller, J. G., Yuhas, D. E., Mimbs, J. W.

,

Dierker, S. B., Busse, L. J., Laterra, J. J., Weiss, A. N., and Sobel, B. E., Ultrasonic

Tissue Characterization: Correlation Between

Biochemical and Ultrasonic Indices of Myocardial Injury, in Proceedings 1976 IEEE Ultrasonics Symposium 79, 33-43 (Cat. No. CM 1120-43U, IEEE, New York, 1976).

[3] Schwan, H. P. and Carstensen, E. L., Ultrasonics aids in diathermy experiments.

Electronics, 216-220 (July 1952).

[4] Marcus, P. N. and Carstensen, E. L., Problem

with absorption methods of inhomogeneous

solids, J. Acoust. Soc. Am. 58_, 1334-1335

(1975).

[5] Hueter, T.A., WADC Tech. Rept. 57-706 (1958).

[6] Frizell, L. A., Ultrasonic Heating of Tissue,

Ph.D. Thesis, University of Rochester (1976)

(unpublished).

70
[7] Bamber, J. C, Fry, M. J., Hill, C. R. , and

, Dunn, F., Ultrasonic attenuation and back- scattering by mammalian organs as a function

of time after excision, Ultrasound in Medicine and Biology 3, 15-20 TT977T-

[8] See the references listed in O'Donnell, M. and Miller, J. G. , Mechanisms of Ultrasonic

Attenuation in Soft Tissue (this publication,

p. 37).

[9] Yuhas, D. E. , Mimbs, J. W., Miller, J. G., Weiss, A. N., and Sobel , B. E., Changes in Ultrasonic Attenuation Indicative of Regional

Myocardial Infarction, in Ultrasound in Medicine , D. W. White, ed., vol. 3, 1883-

1894 (Plenum Press, New York, 1977).

71

Reprinted from Ultrasonic Tissue Characterization II, M. Linzer, ed., National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C., 1979).

ACOUSTIC MICROSCOPIC ANALYSIS OF MYOCARDIUM

Donald E. Yuhas and Lawrence W. Kessler

Sonoscan Inc. 720 Foster Avenue Bensenville, niinois 60106, U.S.A.

Acoustic microscopy can be employed to measure variations in the ultrasonic attenuation and velocity over spatial dimension of tens of micrometers. Knowledge of the in- teractions at this fine-structure level provides a more complete understanding of the response of tissues at diagnostic frequencies. In this article we investigate the ultrasonic characteristics of formalin-fixed infarcted and normal myocardium at the microscopic level. The elastic microstructure of normal tissues is found to be uniform over

spatial dimensions of hundreds of micrometers. The attenuation coefficient a, at

100 MHz, ranges from 37 to 68 cm"^ while the velocity varies less than ± 20 m/s.

Acoustic anisotropy, attributed to muscle fiber orientation, is found to be a primary

source of attenuation variability. The elastic microstructure in the zones of infarction is very distinct from that in normal zones. With infarction, variations in the attenuation ranging from 38 to 100 cm"i occur over dimensions of hundreds of micrometers. Accompanying this variability in attenuation is a wide distribution of velocity.

The most highly attenuating regions in the infarcted tissue show localized increases in the velocity of more than 75 m/s. Such large variations in sonic velocity are sufficient

in magnitude to be an important source of phase cancellation in low frequency attenuation measurements. Additionally, the 100 MHz data indicate that the frequency dependence of the attenuation coefficient observed in the 1 to 10 MHz range for infarcted and normal myocardium may not hold in the 10 to 100 MHz frequency interval.

Key words: Acoustic microscopy; anisotropy; attenuation; elastic microstructure;

infarct; interferogram; phase cancellation; myocardium; velocity.

1. Introduction

The complete ultrasonic characterization of tissue can be divided into two distinct levels

of interaction: 1) structures greater than the wavelength of diagnostic ultrasound and 2) structures that are finer. The larger structures

give rise to specular reflections which are used

to define the outlines of tissues and organs

seen in conventional B-scan echograms. The finer structures give rise to characteristic

scattering properties of tissue and are also responsible for intrinsic attenuation and velocity. It is this sensitivity to fine structure,

that makes the diagnostic frequency ultrasonic

parameters so important in determining tissue

pathologies.

As an aid to understanding the low frequency

scattering, attenuation, and velocity data,

direct visualization of the finer structures is desirable. Conventional microscopy (optical and electron) can be used to delineate various structural components, but these methods do not provide

the required information regarding the ultrasonic

properties of the tissue.

On the other hand, the elastic microstructural

information obtained through acoustic microscopy

is directly applicable to the lower frequency (1 to 10 MHz) characteristics. Acoustic microscopy

provides a means for visualizing directly the

elastic architecture as well as for measuring

variations in the ultrasonic attenuation and velocity properties over areas tens of micrometers in diameter. By using this technique,

valuable insight can be gained into mechanisms

responsible for the attenuation of sound as well

as factors which influence tissue characterization measurements at lower frequencies.

This preliminary study consists of a series of acoustic microscope observations of myocardial

tissue. Previous reports have shown that quantitative changes in ultrasonic attenuation over the frequency range 2 to 10 MHz are associated with

regional myocardial infarction [1-4]^. The ultra- sonic attenuation in normal tissue was found to exhibit a linear frequency dependence, while in- farcted tissue exhibits a significant quadratic

dependence. As a clue to elucidating the nature

of the change in attenuation at lower frequencies,

acoustic microscopy was used to investigate the elastic microstructure of normal and infarcted

myocardi urn.

2. Methods

Acoustic micrographs were obtained with a com- mercially available 100 MHz scanning laser acoustic

^Figures in brackets indicate literature

references at the end of this paper.

73
microscope, SONOMICROSrOPE 100. A brief description of the technique is presented here for com- pleteness. For a more detailed description, the reader may refer to the listed references [5-9].

Figure 1 illustrates the instrumentation used

to produce 100 MHz acoustic micrographs. A sample

is placed on a glass stage between an insonifying

transducer and receiver. The transmitting trans- ducer is a piezoelectric element which is bonded

to a glass substrate, and the receiver is a scan- ning focused laser beam. The acoustic energy is coupled to the specimen through the glass sub- strate without need for an acoustically lossy water bath. The specimen is moistened with liquid

to ensure good acoustic coupling. The sound is transmitted through the sample at an angle of 10° with respect to the normal. In order to provide

a specularly reflecting surface for the scanning

laser beam receiver, the specimen is covered with

a partially silvered coverslip. The coverslip al- lows a small amount of light to penetrate to the sample and render an optical view simultaneously

with the acoustic.

laser beam scanners

imaging optics

demodulator and photodetector

mirrored cover'sl in i g_ spec \men

acoustic

signal processor

acoustic frequency generator T

stage

photodetector

ultrasonic transducer

optical

signal processor

Acoustic Image

Display

Fig. 1. Schematic diagram of the acoustic microscope used in this study. The instrument

employs a scanning laser beam technique

for detecting the amplitude and phase of acoustic energy transmitted through the sample. Acoustic and optical images are produced simultaneously and are presented

on separate monitors.

The acoustic energy transmitted through the specimen imparts a slight oscillatory mechanical

perturbation to the coverslip surface. The amplitude of these perturbations, which vary at the acoustic frequency, is inversely proportional to the localized ultrasonic attenuation properties in the underlying sample. By sensing the perturbations and displaying the signal on a TV monitor,

an acoustic image is formed. Images are obtained

in real time and displayed at a magnification of

about 70 X. The bright regions seen on the acoustic micrographs correspond to areas of high

transmission through the sample, whereas the darker areas correspond to regions of higher ultrasonic attenuation.

Quantitative attenuation measurements of the tissue observed in the microscope can be made any- where within the field of view by an optical technique described previously [10]. With the sample

in place, an acoustic image is obtained. Areas of interest are noted and readings of the image brightness are obtained with a light meter. Once the image brightness is recorded the sample is removed

and replaced by an equivalent thickness of coupling

medium. For this work formalin (10 percent formal- dehyde) was used. Electrical attenuation is then inserted into the electro-acoustic signal path to restore the image brightness to its previous level. Although the acoustic field is quite uniform,

care was taken to ensure that the same region of sound field was measured for the cases with and without the sample in place. Using this technique,

attenuation can be measured over an area as small

as 5 X 10"^ cm2. The sensitivity of the photo cell used in these studies permitted discrimination of sound levels to within ± 1 dB, which introduced a

3 to 8 percent uncertainty in the measured at- tenuation coefficient. Because the acoustic image of the specimen is observed during the course of

the measurement procedure, it is possible to select

regions of low contrast structural details, thereby assuring the attenuation values obtained were

free from artifacts arising from vessels or fluid

filled cavities.

In addition to recording the transmissivity of specimens, the scanning laser acoustic microscope

is equipped with an acoustic interferogram mode of operation. Acoustic interferograms display the localized distribution of transit times through

the sample. For specimens of uniform thickness

these transit time variations are directly related

to localized variations in sonic velocity. Inter- ferograms can be conceptualized with reference to figure 2. In this schematic, an ultrasonic plane wave is incident on the sample at an angle with

respect to the normal. The intersection of the wavefronts with the plane below the specimen re- sults in a series of fringes (indicated by the dots) which run in and out of the plane of the

page. Using phase sensitive detection, the positions of these equiphase lines are displayed on

elastic plane of inclusion / observation

Fig. 2. Model for conceptualizing acoustic inter- ferograms. As a plane wave propagates

through a sample, regions of velocity

variations cause refraction. The resulting wavefronts are displaced as they ar- rive at the sample surface as shown by the dots. The lateral position of the wavefronts (fringes) are a function of the change in velocity and can be calculated

from the formulas given in the text.

74
the image monitor. Figure 3 is a micrograph of an interferogram recorded with no specimen on the

stage. In this case the interferogram lines (fringes) are straight and parallel. Going from

left to right, each successive interference fringe

represents an increase in transit time through the glass stage of exactly one period of oscillation

(10 nanoseconds at 100 MHz).

Fig. 3. Interferogram obtained eith no sample on the microscope stage showing equally

spaced, parallel, interference fringes.

This is the same type of interferogram

that would be obtained on a sample that exhibited no regional changes in sonic

veloci ty.

Figure 2 also illustrates the effect of elastic

inhomogeneity on the position of the interferogram

fringes. As the wave enters the sample it refracts according to Snell's law. In the areas of the sample with uniform propagation velocity (white

areas) the separation of successive fringes after

propagating through the specimen is the same as that measured with no sample. When structures

with variations in propagation velocity are present,

illustrated by the hatched area, the separation of successive fringes in the vicinity of the elastic

inclusion changes. The magnitude of the fringe

shift, N, is directly related to the propagation

velocities of the two components by the following

relations [11]:

M

= (cot ei - cot 62) (1)

where N is the dimensionless magnitude of the

lateral fringe shift normalized by the unperturbed

fringe spacing: Xi is the wavelength of sound in region 1 of the specimen; At is the specimen

thickness; and ei and 62 are the propagation angles

in regions 1 and 2 respectively.

The relationship between the propagation angles

and the sonic velocity is given by Snell's law:

sin 9i _ sin 62 ^2)

Ci C2

where Cj and C2 are the respective propagation

velocities.

Using eqs. (1) and (2) and knowing the magnitude of the sonic velocity of one component in the field of view, the sonic velocities of all other

areas can be determined. The primary factor de- termining the sensitivity of the technique for measuring variations in velocity is the sample

thickness. For the sample thicknesses used in this study, a displacement of a fringe by 1/10 of

the unperturbed fringe spacing ( i.e ., N = 0.1)

corresponds to a velocity change of 5 m/s.

3. Myocardial Samples

The specimens used in this study^ were taken from regions of formalin-fixed canine myocardium.

Sections .05 ± .005 cm in thickness were made in several different myocardial regions extending

from the apex to the base of the heart. The plane

of dissection was oriented approximately at an angle of 45° with respect to the long axis of the heart and each section extended from epicardial to endocardial surface. Samples were taken from regions of infarcted and non-infarcted tissues

with the regions of infarction lying nearer to the apex of the heart. Analysis was carried out on section taken from a single heart which had been formalin fixed for more than a year and was originally excised 4 weeks after coronary occlusion.

4. Results

Figure 4 presents an acoustic micrograph (a) and interferogram (b) obtained on a myocardial

section taken from a non-infarcted region. Brightness variations in this micrograph (fig. 4a) gen- erally range from light to dark grey. A band of lighter material approximately 1 mm wide can be seen running almost vertically through the central portion of the micrograph. On either side of this acoustically transmissive region are darker areas oriented both perpendicular and parallel to the

band. Except for the dark structure (indicated by

the arrow), which is attributed to a vessel, the change in brightness between the various regions

is relatively subdued and gradual. The interfero- gram of this region (fig. 4b) shows a uniform

sonic velocity distribution. Only the area in- dicated by the arrow exhibits an abrupt disruption

of the interferogram lines showing a slight in- crease of sonic velocity of 20 m/s. Throughout

most of the sample the lateral shifts in the interferogram lines going from the top to the bottom of

the micrograph over the entire field are less than

.4 fringes indicating velocity changes of less

than ± 10 m/s in the vertical direction.

Figure 5 illustrates an interesting effect,

that of acoustic anisotropy in myocardial tissue. These micrographs were obtained on the same sample

shown in figure 4; however, the sample has been rotated 90° in the plane of the stage. Recall that the angle of insonif ication is approximately

10° from the specimen normal. Thus, while the major component of the propagation vector K is perpendicular to the sample, a small off-axis com- ponent leads to some dramatic changes in image contrast on rotation. The amplitude micrograph

shown in figure 5a reveals two distinct regions.

The upper half of the micrograph shows acoustic

morphology similar to that observed in the previous micrographs. The lower half of the micro-

^Samples provided courtesy of Washington

University, Division of Cardiology, St. Louis, Missouri.

75
(a)

Fig. 4. Acoustic amplitude micrographs (a) and interferogram (b) of normal myocardium.

The field of view in each micrograph is 2.3 by 3.0 mm and the sample thickness is 500 micrometers. In the amplitude micrograph the light areas are regions of low attenuation. The interferograms are ar- ranged so that a lateral shift to the right

corresponds to a region of increased velo- city and a shift to the left, lower velocity. A shift of one fringe corresponds

to a velocity change of 50 m/s. Typical

variations in this sample are + 10 m/s.

Fig. 5. Acoustic amplitude micrograph (a) and interferogram (b) of the same region de- picted in figure 4 after sample rotation

(counter-clockwise) by 90°. The dramatic

changes in these images compared to figure

4 are due to the tissue being anisotropic

acoustical ly. The top portion of the interferogram shows velocity variations of ± 5 m/s, while

variations of 40 m/s are seen in the lower portion of the micrograph.

graph is significantly different, showing bands of acoustically light and dark material running horizontally across the field of view. The change of acoustic contrast is abrupt across these boundaries and their morphology suggests that they arise from muscle fiber orientation. In this micrograph

the off-axis component of the propagation vector

k is parallel to the acoustic striations seen in the micrograph, i.e . with the grain, whereas in the previous figure it is perpendicular or across

the grain.

It should be emphasized here that the portion

of the sample comprising the lower half of this field of view (fig. 5a) is the same area as that imaged in the left half of figure 4a. Some of

the most highly attenuating areas seen in figure

5a become the least attenuating areas as the sample is rotated in the sound field. The acoustic

interferogram of the same region is shown in figure

5b. Again, the spatial distribution character of

sonic velocity in the upper portion of the micrograph is similar to that seen in figure 4b. The sonic velocity in this region is 1580 m/s with

typical variations less than ± 5 m/s. In the darker regions the interferogram lines become quite jagged, indicative of sharply localized

changes in sonic velocity. Typical shifts here

are on the order of 0.8 normalized fringes, cor- responding to an increase in velocity of 40 m/s.

Figures 6a and 6b show a comparison between interferograms obtained on normal and infarcted

tissue. The interferogram obtained on the normal

76
(b)

Fig. 6. Interferograms comparing normal and in- farcted tissue, (a) Interferogram of

normal tissue shows uniform attenuation

and velocity. Velocity variations are typically ± 5 m/s. (b) Interferogram of infarcted tissue. Both attenuation and sonic velocity are highly variable.

Typically, the highly attenuating areas show increased sonic velocity, for example,

the region indicated by the arrow has a velocity of 75 m/s higher than the sur- rounding tissue.

specimen (fig. 6a) shows similar characteristics

as discussed previously, i.e . uniform attenuation

and velocity over the field of view. In contrast,

the most distinctive feature of the infarcted tissue (fig. 6b) is its overall microelastic in- homogeneity. There are small regions of this micrograph which show uniform velocity profiles

and attenuation characteristics (similar to normal tissue), however, there also exists a number of highly attenuating (darker) areas. These dark

areas show increases in sonic velocity of more

than 75 m/s compared to that seen in the neighboring tissue. The complex interference fringe pattern indicates that, in the infarcted zones, there

is considerable variation in the sonic velocity

on a microscopic scale.

On several sections, ultrasonic attenuation

measurements were made at 100 MHz. The results

Table 1. Summary of 100 MHz attenuation

measurements.

Section Attenuation Number of range (cm-i) measurements

A non-infarct 48 l B non-farct^ 43b 2

B non-infarctc 41-68 2

C non-infarct 37-61 2

D infarct 38 - 100 5

E infarct 27-70 5

Off-axis component of sound is perpendicular

^to grain.

Off-axis component of sound is parallel to ^grain.

Typical value.

are presented in table 1. Sections A through C were obtained from normal regions while sections

D and E were obtained from zones of infarction.

Each attenuation measurement was made on a small region of tissue (1 x 10~'*cm2) gp^^ general,

several different areas on each section were measured. The range of attenuation measured in a section is given in column 2 of the table. The variations tabulated here represent structural variations in the tissue as opposed to uncertainties in the measurement technique (which are on the order of ± 10 percent). The number of mea- surements made on each section was governed primarily by the image contrast as seen on the TV monitor. Areas that looked distinct on the monitors were subsequently measured. Thus, sections

with uniform attenuation properties were subjected

to fewer measurements than sections displaying a variety of brightness levels. The attenuation values obtained in the 3 sec- tions of normal tissue range from 37 to 68 cm"^ . For section B, two entries are presented in the table corresponding to the two different orientations of the section in the sound field. The first entry, Bi, represents measurements made on section B in the orientation depicted in figure

4a, while the second entry, B,,, presents measurements made in the orientation depicted in figure

5a. The attenuation measured in the B orientation

show relatively minor variations from the typical value of 43 cm--'. In contrast, measurements on the same section in the B,, orientation yield values ranging from 41 to 68 cm-^. Perhaps the most

striking feasure of the acoustic anisotropy is the observation that the same area that yields an attenuation coefficient of 45 cm-^ in orientation

Bi gives a value of 68 cm-^ in the B,, orientation.

Thus, variations in attenuation which are attributed solely to anisotropic propagation are of the same magnitude as variations observed in different

sections

.

The attenuation measured in the zones of in- farction serve to quantify the visual impression

given by the acoustic micrographs. Infarcted

zones show inhomogeneous attenuation properties

with variations ranging between 27 and 100 cm"^ for the two sections analyzed. The highly attenuating zones with attenuation coefficients in ex- cess of 70 cm"^, are morphologically distinct from

any features present in the non-infarcted regions.

77
5. Discussion

This study presents some acoustic microstructure characteristics of myocardial tissue at a frequency of 100 MHz. The features revealed in the acoustic micrographs as well as the quantitative attenuation and velocity data can lead to important conclusions with regard to the complete

ultrasonic characterization of tissues.

First of all, 100 MHz acoustic micrographs can

be used to distinguish between and recognize in- farcted and normal tissue. The most distinctive

feature of the infarcted zone is the high degree

of localized variations in attenuation and velocity. Such acoustic contrast could result from fibrous scar tissue distributed in a matrix of normal myocardium. The highly attenuating, high

sonic velocity regions can be attributed to areas

of substantial scar. This identification is con- sistent with lower frequency measurements on tis- sues rich in collagen [12].

Secondly, significant acoustic anisotropy,

arising from muscle fiber orientation, has been observed at 100 MHz. One of the sections analyzed

(sample B) showed a large orientational dependence,

and this may have been due to the particular geom- etry of the fibers. With a small component of the propagation vector K along the fiber an increase

in attenuation was observed. This is in the same direction as the attenuation anisotropy previously

observed in striated muscle at lower frequencies

[13]. The magnitude of change in attenuation is rather substantial, 45 to 68 cm"^, indicating that structural aspects and tissue architecture play an important role in determining overall attenuation.

The orientation effect favors scattering type loss mechani sm. Thirdly, the large velocity variations measured

in the infarcted tissue may have important con- sequences for low frequency attenuation measurements. Phase cancellation losses have been im- plicated as a primary source of artifact in at- tenuation measurement made using piezoelectric

receivers [14,15]. Although small diameter

(~ .2 cm) receiving transducers or confocal pairs

of transducers can be used to minimize phase can- cellation loss, they do not completely eliminate

it. Phase cancellation occurs when inhomogenei ties

in the tissue distort the ultrasonic phase fronts presented to a spatially extended piezoelectric

receiving transducer. The i nterferogram, figure

6b, displays the high degree of wavefront distortion which actually occurs in infarcted myocardium.

Quantitatively, the distortion is greater than 1.5 fringes or 540° in phase over a distance which is smaller than the diameter of the small receiving

transducer (.2 cm) measurement reported at lower frequency [2-4].

Lastly, it is interesting to compare the attenu- ation measurements made at 100 MHz with those ob- tained at lower frequencies. Figure 7 is a plot

of the attenuation coefficient divided by frequency

(a/f) vs f. The data in the frequency range 2 to

10 MHz were reported previously and are average attenuation values obtained on fresh myocardium

excised 4 to 5 weeks after vascular occlusion [4]. On the other hand, the 100 MHz data, taken from

table 1, represent the range of attenuation values

in the infarcted and non-infarcted zones. Analysis of figure 7 indicates that for normal tissue, in the frequency interval 2 to 10 MHz, a/f

has a relatively constant value of .07 cm'^ MHz"i.

non-i nfarct

J ] I I \ L_

2 5 10 20 50 100 Frequency (MHz)

Fig. 7. Comparison of 100 MHz attenuation data with that obtained at lower frequencies

for infarcted and non-infarcted myocardium.

Low frequency data are taken from the work

of Miller et al . [4] while the 100 MHz

data are from table 1.

The 100 MHz values reported here are substantially

higher (.37 to .68 cm'^ MHz'M- For the infarcted

tissue, the 2 to 10 MHz a/f values increase with

frequency. Linear extrapolation of these data would predict a value of 1.9 cm~^ MHz"^ at 100 MHz. However, the most highly attenuating regions ob- served in the infarcted zones at 100 MHz have a/f values of 1.0 cm"i MHz"^, a value significantly

lower than that predicted. Thus, the a/f versus

f dependence for normal and infarcted tissue pre- dicted in the range 1 to 10 MHz may no longer hold

in the interval 10 to 100 MHz. The following limitations to this conclusion

should be pointed out. First of all, the referred

to low frequency data were obtained on freshly ex- cised tissue, while this 100 MHz investigation

used formalin fixed tissues. Although data ob- tained on other tissues, e.g . , kidney, indicate

that the effect of formalin on the overall attenuation values at 100 MHz may not be significant

[10], this has not yet been verified for the myocardium. The second point concerns orientation

effects. The lower frequency measurements were

made by transmitting sound through the myocardial

wall roughly perpendicular to the epicardial surface, while the 100 MHz measurements were done in

a plane perpendicular to this. Results presented

in this study indicate the presence of an orientational effect on the acoustic properties.

Although more comprehensive work needs to be done to quantify the extent to which orientation

and fixing influence the acoustic properties, the results of this study show that high frequency

acoustic microscopy can play an important role

in the understanding and characterization of tis- sues at diagnostic frequencies.

Acknowledgment

The stimulating discussions with W. D. O'Brien,

University of Illinois are gratefully acknowledged.

References

[1] Lele, P. P. and Namery, J., A computer-based

ultrasonic system for detection and mapping

78
of myocardial infarcts, in Proc. San Diego [9] Biomed. Symp . U, 121 (19721:

[2] Yuhas, D. E., Mimbs, J. W. , Miller, J. G., Weiss, A. N., and Sobel , B. E., Changes in Ultrasonic Attenuation Indicative of Regional [10]

Myocardial Infarc'-'on, In Ultrasound in Medicine , D. White, ed.. Vol . 3 (Plenurfi' Press

,

New York, 1977).

[11]

[3] Mimbs, J. W., Yuhas, D. E., Miller, J. G., Weiss, A. N., and Sobel, B. E., Detection of myocardial infarction in vitro based on altered attenuation of ultrasound. Circulation

Research (in press).

[4] Miller, J. G., Yuhas, D. E., Mimbs, J. W., [12]

Dierken, S. B., Busse, L. J., Weiss, A. N., and Sobel, B. E., Ultrasonic Tissue Characterization: Correlation between Biochemical

and Ultrasonic Indices of Myocardial Injury,

in Proc. of IEEE Ultrasonic Symposium , J. deKlerk and B. McAvoy, eds.. Cat. No. 76 [13]

Ch. 1120-4SU, p. 33 (Annapolis, 1976).

[5] Korpel , A., Kessler, L. W., and Palermo,

P. R., An acoustic microscope operating

at 100 MHz, Nature 232, 110 (1971).

[6] Kessler, L. W. , Korpel, A., and Palermo,

P. R. , Simultaneous acoustic and optical

microscopy of biological specimens.

Nature 239, 111 (1972). [14]

[7] Kessler, L. W. , Palermo, P. R. , and Korpel,

A., Practical High Resolution Acoustic

Microscopy, in Acoustical Holography , G. [15]

Wade, ed. , Vol. 4, p. 51 (Plenum Press,

New York, 1972).

[8] Kessler, L. W., Palermo, P. R., and Korpel,

A., Recent Developments with the Scanning

Laser Acoustic Microscope, in Acoustical

Holography , P. S. Green, ed.. Vol. 5, p. 15 (Plenum Press , New York, 1974).

Kessler, L. W., The Sonosmicroscope , in Proc . of IEEE Ultrasonic Symposium , J. deKlerk,

ed., p. 735, Cat. No. 74-CH0-896-1 SU (IEEE, New York, 1974).

Kessler, L. W. , VHP ultrasonic attenuation

in mammalian tissue, J. Acoust. See. Am . 53 1759 (1973).

Kessler, L. W., Tissue Characterization by Means of Acoustic Microscopy, in U ltrasonic

Tissue Characterization , M. Linzer, ed..

Spec. Publ . 453, p. 261 (U.S. Government

Printing Office, Washington, D.C., 1976).

O'Brien, W. D., Jr., The Role of Collagen in Determining Ultrasonic Propagation Properties in Tissue, in Acoustical Holography , L. W. Kessler, ed. , Vol. 7 (Plenum Press,

New York, 1977).

Dussik, K. T. and Fritch, D. J., Determination of Sound Attenuation and Sound Velocity

in the Structures Constituting the Joints

and of the Ultrasonic Field Distribution

within the Joints on Living Tissues and Anatomical Preparations, both in Normal and Pathological Condition, Progress Report , Project A454 , Public Health Service, April

(1955), September (1956).

Marcus, P. N. and Carstensen, E. L., Problems

with absorption methods of inhomogeneous

solids, J. Acoust. Soc. Am . 58, 1334 (1975).

Busse, L. J., Miller, J. G., Yuhas, D. E., Mimbs, J. W., Weiss, A. N., and Sobel, B. E., Phase Cancellation Effects: A Source of At- tenuation Artifact Eliminated by a CdS Acoustoelectric Receiver, in Ultrasound in Medicine , D. White, ed.. Vol. 3, pp. 1519- 1535"TPTenum Press, New York, 1977).

79
i 5
Reprinted from Ultrasonic Tissue Characterization II, M. Linzer, ed. , National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C., 1979).

ACOUSTIC PROPERTIES OF NORMAL AND ABNORMAL HUMAN BRAIN

F. W. Kremkau, C. P. McGraw, and R. W. Barnes

Bowman Gray School of Medicine

Winston-Salem, North Carolina 27103, U.S.A.

Attenuation and propagation speed at 1, 3, and 5 MHz and specific acoustic im- pedance at 2 MHz were measured j_n vitro in 10 tissue samples from 8 abnormal human brains. The results were compared to values resulting from a study of 5 normal human brains reported elsewhere. Conclusions from literature review are that attenuation is lower in gliobastoma than in normal brain and attenuation, propagation speed

and impedance are higher in meningioma than in normal brain. Conclusions from the data of the present study are that subarachnoid hemorrhage appears acoustically

normal; infarcts have normal attenuation but increased speed; clots, intracerebral

hemorrhage, and metastases have increased attenuation and speed; hydrocephalic brain

has very low attenuation and low speed. In general, it appears that abnormal conditions produce increases in all three acoustic properties studied.

Key words: Attenuation; brain tumor; clot; hemorrhage; hydrocephalus; impedance;

infarct; speed; ultrasonic.

1. Introduction

As part of a study of acoustic properties of

normal and abnormal tissues, attenuation and propagation speed at 1, 3, and 5 MHz and specific

acoustic impedance (hereafter called impedance)

at 2 MHz were measured in vitro in 10 tissue

samples from 8 abnormal human brains. Results from our study of 23 tissue samples

from 5 normal human brains are reported elsewhere [l]i. The important observations were:

(a) attenuation measured with piezoelectric

transducers resulted in higher values

(0 to 50 percent) than those obtained

using radiation force method;

(b) attenuation (using transducer method)

was 0.9 dB/cm at 1 MHz and was a function

of f^"-' over the range 1 to 5 MHz;

(c) propagation speeds at 1 MHz were 1546 and 1539 m/s for fresh and fixed tissues,

respecti vely

;

(d) speed dispersion was 2 ms"^ MHz-^ and

1.6 ms"i MHz-i for fresh and fixed tissues,

respectively;

(e) white matter had attenuation 1.4 times that for gray;

(f) attenuation of adult brain was 2.7 times that for infant;

(g) one day aging reduced attenuation up to

20 percent;

(h) attenuation depended upon temperature to the power -0.1 and -0.5 at 1 and 5 MHz, respecti vely

;

(i) propagation speed as a function of tem- perature exhibited a minimum at approximately 15 °C.

^Figures in brackets indicate literature

references at the end of this paper.

The differences between white and gray matter and between infant and adult attenuation can be ex- plained on the basis of tissue water content.

The minimum in propagation speed with respect to temperature may indicate a sensitivity to the crystal -1 iquid crystal phase transition for mem- brane phospholipid bilayers. There are several reports in the literature

regarding the acoustic properties of normal and abnormal human brain tissue. A review of the data for normal brain may be found in our earlier

report [1]. In addition, reported values for im- pedance are 1.59 x 10^ MKS rayl (kg/m^s) for "brain" [2], 1.60 for cerebellum [2], 1.51 for cerebrum [3], and 1.52 for white matter [4]. An early paper by Wild and Reid [5] showed differences in received echo patterns for normal brain and several malignant and benign tumors. More recently Fishman. Heyser, and Le Croissette

[6] reported high attenuation in tumor regions of human brain sections using qualitative transmission images. A summary of the data for abnormal

brain is given in table 1. Only tumors are cited

as no other abnormality was found in the literature. Table 2 shows an attempt to simplify this summary and draw some conclusions from it. It lists reports of greater (+), equal (==), or lesser

(-) values for attenuation, speed, or impedance

as compared to the same authors' values for normal brain tissue. Citing only those situations where

at least two reports are in agreement, the following are concluded:

(a) attenuation is lower in glioblastoma than

in normal brain;

(b) attenuation is higher in meningioma than

in normal brain;

(c) propagation speed and impedance are higher in meningioma than in normal brain.

81
Table 1. Attenuation, propagation speed, and impedance

for several brain tumors--l iterature summary.

Tissue Frequency Attenuation Speed Impedance Reference

(MHz) (dB/cm) (m/s) {^0'' MKS rayl

)

2

7

2

78

9

9

7

2

79

7 10

1112

13

29

9

2

7

39910

12

13

14

3 12

2

7 10

4

7

7

7

3

2

apormalin fixed sampl es

.

2. Materials and Methods

Normal and abnormal human brain tissue samples were obtained at autopsy. Measurements were made

at 37 °C after at least 24 hours of fixation in

10 percent formalin. Except during measurement,

tissues were stored at 4 °C. Tissue samples were

cut to fill the sample holder - a Teflon® ring with

inner diameter 33 mm, outer diameter 45 mm, and (sample) length 15 mm. Saran® membranes were stretched over both sides of the chamber to pro- vide flat tissue surfaces and acoustic windows.

The sample holder fit into a guide in a temperature controlled water bath which provided con- sistent placement (within 1 mm in each coordinate)

relative to source and receiver transducers. The transducers were one inch diameter Val pey-Fi sher polished 1 MHz X-cut quartz. The source trans- ducer was driven by an Arenberg PG-650C pulsed

oscillator. Bursts were typically 20 cycles long and reasonably characterized by a single (fundamental) frequency. The receiver transducer was connected to the input of a 7A18 amplifier in a Tektronix 7904 oscilloscope with a 7B92 dual time

base. Amplitude of received burst, with and without tissue sample between transducers, was measured and attenuation coefficient, calculated

from the following relation:

Table 2. Attenuation, propagation speed, and impedance are higher

than (+), equal to (=), or lower than (-) that for normal tissue as measured by the same authors. There is a con- sensus that glioblastoma has lower attenuation and that meningioma has higher attenuation, speed, and impedance.

Tumor Attenuation Speed Impedance Reference

acoustic neurinoma + + 2

7 arachnoidal sarcoma 2 astrocytoma

+ +

7

8 craniopharyngioma + 7 ependymoma

+

+ + 27 glioblastoma

+

710

111213

g 1 i oma 2 medul loblastoma + 7 meningioma

+

+

+

+

+

+

+

+

+

2

73 10

12

1 3 14 metastatic adenocarcinoma

- + + 3 12 metastatic carcinoma

+

+ + 2

7 10

4 oligodendroglioma 7 pineal oma 7 pituitary adenoma 7 retinoblastoma + 3 spongioblastoma 2

m = ^ 20 log^o

Ai

"

where m and ni,^ are attenuation coefficients in dB/cm of tissue sample and water, respectively,

m^ is window loss in dB, d is sample thickness in cm, Aq is received amplitude with sample not present (water path), and Aj is received amplitude

with sample present. Amplitudes were measured

with precision ± 2 percent or better and accuracy

(based on Tektronix specification) within 2 percent. Measurements were taken at 1, 3, and 5 MHz. Corrections for m^ and m^ are normally less than 1 percent except m^, at 3 and 5 MHz (typically 2 and 7 percent, respectively). The value for

m^- is obtained by measuring the received amplitude change when a water filled chamber is in- serted between the transducers. Additional re- flection loss resulting from impedance discontinuity between water and tissue is not significant.Propagation speed was calculated using the arrival time change occurring when the sample was inserted between source and receiver transducers,

c = d/(t2 - t ) where c is propagation speed in the tissue sample^in m/s, d is sample thickness in meters, tj is propagation time in seconds in d path

length of water, and t is arrival time change in seconds when sample is introduced into sound path.

Arrival time changes are typically 200 to 400 ns read to a precision of + 10 ns and accuracy (based

on Tektronix specification) within 5 percent. Measurements were taken at 1, 3, and 5 MHz.

acoustic

neurinoma

arachnoidal

sarcoma astrocytoma

craniopharyngioma

ependymoma

gl ioblastoma

6-8

gl ioma

medulloblastoma

men i ng ioma 4

5

2

2

5

1

15 metastatic adenocarcinoma 1 metastatic 4 carcinoma 5

5

5 oligodendroglioma 5 pineal oma 5 pituitary adenoma 5 retinoblastoma

spongioblastoma 4

9-12

9

6-9

3.3a 20a0.5

0.5

8-11

10-13

6.3a 0.9-1.2

0.6-1.2

35

0.3

8-10

4.3a

7

9

7

1522-1547 1

1530

1660

1545

1517a

1537-1545 1

1501

1525-1547 1 1529 1500

1540-1550 1

1640 1546-1569

1524a

1590

1535

1600

1532

57-1 .62

1.58

1.71

1 .64a

60-1 .62

1 .54

.57-1 .61

1 .56

1 .54

61-1 .64

1 .72

1 .57a

1.68

1 .60

1 .52

1 .67 1.59

82
Acoustic impedance was measured using the method of Gregg and Palagallo [4]. A Parametrics

Pulser/Receiver 5050PR was used with a Hoffrel 310A

2.0 MHz, 13 mm diameter diagnostic transducer. Display was produced on the Tektronix 7904 oscilloscope.

3. Results

The results of seven abnormal conditions are given in table 3. With respect to attenuation

and propagation speed, the following observations

are made:

(a) subarachnoid hemorrhages appear normal acoustically;

(b) infarcts have normal attenuation but increased speed;

(c) clots, intracerebral hemorrhage, and metastases have increased attenuation

and speed;

(d) hydrocephalic brain has very low at- tenuation and low propagation speed.

Impedance values do not correlate well with tissue type or with propagation speed values.

Table 3. Acourtic properties for seven abnormal conditions

in human brain.

Tissue Attenuation

(dB/cm) Speed(m/s) Impedance

(10'' MK5 rayl )

1 MHz 3 MHz 5 MHz 1 MHz 2 MHz

normals 0.9 2.8 5.2 1539 1 .43 metastatic lung carcinoma

1.5 5.6 11.0 1568 1 .56

ventricular

clotb

2.3 9.6 12.2 1575 1 .55

subarachnoid

hemorrhage^

0.9 3.2 5.6 1535 1 .73

intracerebral hemorrhage1.9 8.2 12.8 1553 1 .78

hemorrhagic infarct with necrosis

0.9 3.0 5.7 1552 1.72

Island of Kiel infarct0.9 3.2 6.6 1556 1 .46

hydrocephalus 0.2 0.8 1.3 1516 2.13

^See reference [1]. Impedance value was obtained by measurement

on one normal brain of the five studied with respect to attenuj^ation and propagation speed. Mean of three samples. Mean of two samples.

4. Discussion

In general, it appears that abnormal conditions produce increases in all three acoustic

properties studied. The measured metastatic

carcinoma values agree reasonably well with

those of others [4,7] (see table 1). The low attenuation for hydrocephalus is similar to that reported for infant brain where high water

content was suggested as an explanation [1]. The low propagation speed for hydrocephalus was

not observed in the normal infant. Our results

show normal attenuation for infarcts (1 to 5 MHz). Mi 1 ler et al . [15] observed an increase

in attenuation for dog heart after infarct but

this was evidenced only at frequencies above

5 MHz. Lele and Namery [16] reported increased

attenuation above 2 MHz for infarcted dog heart compared to normal. They also observed reduced

impedance for infarct which was not observed in our study of brain.

Few of these abnormal tissues have been studied by more than one group. Much more data

will be required before confident generalizations can be agreed upon.

Acknowledgments

The authors are grateful for technical assistance from Ms. S. Gaskey.

This work was supported in part by NINCDS Contract NOl-NS-4-2304.

References

[1] Kremkau, F. W., McGraw, C. P., and Barnes,

R. W. , Ultrasonic attenuation and preparation

speed in normal human brain, submitted for publication, J. Acoust. Soc. Am .

[2] Schiefer, W. , Kazner, E. , and Kunze, S.

Clinical Echo-Encephalography , pp. 67-68 (Springer-Verlag, New York, 1968 )

[3] Ishikawa, S., Yukishita, K. , and Ito, K.

Ultrasonic attenuation in brain (7th report),

Jap. Med. Ultrasonics 3, 33 (1965), quoted

in reference 7.

[4] Gregg, E. C. and Palagallo, G. L., Acoustic

impedance of tissue. Investigative Radiol . 4, 357-363 (1969).

[5] Wild, J. J. and Reid, J. M. , The effects of biological tissues on 15-mc pulsed ultrasound, J. Acoust. Soc. Am . 25^, 270-280 (1953).

[6] Fishman, L. S. , Heyser, R. C, and Le Croissette, D. H., Ultrasonic transmission measurements in human brain sections.

Radiology 112 , 211-213 (1974).

[7] Ishikawa, S., Yukishita, K. , Sato, K. , Ito,

K. , and Wagai, T. , Ultrasonic attenuation in brain tissue (the 7th report), Jap. Med . Ultrasonics 3, 48 (1965).

[8] Uematsu, S. and Walker, A. E., A Manual of Echoencephalography , p. 40 (Williams and Wilkins, Baltimore, 1971).

[9] Van Venrooij, G. E. P. M., Measurement of ultrasound velocity in tissue. Ultrasonics

9, 240-242 (1971).

[10] Tanaka, K. , Yukishita, K. , Ito, K. , Ehara,

K. , and Watanabe, H. , Ultrasonic diagnosis

of brain tumors, Proc. Intl. Symp. on Echo- Encephalography , (1967), pp. 38-44, quoted

in Erikson, K. R. , Fry, J. J., and Jones,

J. P., Ultrasound in medicine - a review,

IEEE Trans. Sonics Ultrasonics SU-21 , 144-

170 (1974).

[11] Le Croissette, D. H. and Heyser, R. D.

Attenuation and Velocity Measurements in Tissue Using Time Delay Spectrometry, in Ultrasonic tissue Characterization , M. Linzer, ed.. National Bureau of Standards

Spec. Publ . 453, pp. 81-95 (U.S. Government

Printing Office, Washington, D.C., 1976).

83
[12] Oka, M. and Yosioko, K. , Ultrasonic absorption of human brain tissue. Paper #1302

presented at World Congress of Ultrasound

in Medicine, San Francisco (1976).

[13] Nakaima, N., Study of the ultrasonic at- tenuation of brains bearing tumors, J^. Wakayama Med. Soc . 27, 69-106 (1976).

[14] Kikuchi, Y., Tanaka, K. , and Wagai, T.

,

Early cancer diagnosis through ultrasonics,

J. Acoust. Soc. Am . 29, 824-833 (1957).

[15] Miller, J. G., Yuhas, D. E., Mimbs, J. W., Dierker, S. B., Busse, L. J., Laterra,

J. J., Weiss, A. N., and Sobel , B. E., Ultrasonic tissue characterization: cor- relation between biochemical and ultra- sonic indices of myocardial injury, IEEE Ultrasonics Symposium Proceedings (1976 ) IEEE Catalogue No. 76 CH 1120-5SU, pp. 33-43.

[16] Lele, P. P. and Namery, J., A Computer-Based

Ultrasonic System for the Detection and Mapping of Myocardial Infarcts, in Proceedings San Diego Biomedical Symposium , pp. 121-132, San Diego Biomedical Symposium,

San Diego, California, 1974.

84
Reprinted from Ultrasonic Tissue Characterization II, M. Linzer, ed., National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C., 1979).

FREQUENCY DEPENDENT ATTENUATION OF MALIGNANT BREAST TUMORS

STUDIED BY THE FAST FOURIER TRANSFORM TECHNIQUE

E. Kelly Fry, N. T. Sanghvi, and F. J. Fry

Indiana University School of Medicine and Indianapolis Center for Advanced Research

Indianapolis, Indiana 46202, U.S.A.

and

H. S. Gallager

The University of Texas System/Cancer Center

Houston, Texas 77025, U.S.A.

The work discussed in this paper comprises one aspect of an experimental design

concerned with the use of multi-discipline examination methods to provide detailed

information on the interaction of normal and malignant breast tissues with a high

frequency sound field. The complete experimental design included x-ray and needle

biopsy examination of the breast of a patient prior to mastectomy, followed by: x-ray examination of the excised breast (the malignant tumor remained intact in the excised

breast); ultrasound visualization and FFT studies of the formalin-fixed, excised

breast specimen; x-ray examination of 0.5 cm thick, whole breast sections of the tissue; and, finally, sectioning and histological staining of the primary mal ignant tumor region and other tissue areas of interest. Emphasis is given in this preliminary report to a study of attenuation of the sound beam as a function of frequency

for specific tissue paths ( i.e ., from skin to back surface of the excised breast),

which included (1) the malignant tumor, (2) the nipple and (3) the areola.

For the tissue path which included the malignant tumor, the FFT studies indicate

that the attenuation for the full range of frequencies studied (1.1 to 4.4 MHz) was greater than that of any other area of the breast. A significant result of the in- vestigations reported in this paper is the determination that this analytical tech- nique is feasible and can yield data on malignant and normal regions of breast tissue which correlate with the ultrasound visualization imaging information and with

the tissue structure information as revealed by histological examination.

Key words: Attenuation of areola; attenuation of breast tissue; attenuation of malignant tumors; breast cancer detection; breast carcinoma; breast

examination techniques; FFT techniques for breast; histology of breast tumors; signal processing for tissue; x-ray examination of breast.

1. Introduction

At the present time, ultrasound visualization

techniques, if used in conjunction with other

clinical examination methods, can improve the

level of success in the differential diagnosis

of breast pathologies [1]^. However, the theoretical capability of ultrasound for providing a successful method of early detection of breast

cancer is not presently realized, in part because

of the lack of sufficient clinical studies with

this method and, in addition, because of the need for more basic experimental studies on the interaction of ultrasound and breast tissue. There

is, in fact, a serious need for relatively so-

^Figures in brackets indicate literature

references at the end of this paper.

phisticated investigations concerned with (1) the complex structure of normal breast in terms

of its interaction with sound fields and (2) the variability in structural features of malignant

tumors (including those in the same pathology

classification) insofar as this variability is significant to medical diagnostic data obtained

by ultrasound examination of such tumors. The experimental work discussed in this paper comprises one aspect of an overall approach of using multi-discipline examination methods, namely, x-rays, ultrasound visualization, signal

processing of ultrasound transmission data ( i.e ., Fast Fourier Transform (FFT) techniques) and histological techniques to provide detailed in- formation on the structural features of breast tissue and their interaction with a high frequency

sound field. In the initial experimental stages,

85
procedures such as the FFT are best performed on an excised breast. A special preparation, namely,

an excised, formalin-fixed breast with a known in- tact malignant tumor, was used in the investigations discussed in this paper. Detailed examination of such breasts, by both standard and ex- perimental breast cancer detection methods, and

the correlation of the results with tissue structure information provided by histological in- vestigations, can yield data that is pertinent

to early breast cancer detection [2-8]. The

rationale, validity and value of studying such

fixed, whole specimens by ultrasound visualization

techniques have been discussed in detail by Kelly

Fry and Gallager in a previous publication [8]. Additionally, Calderon et al . have published re- sults of an investigation on the ultrasound at- tenuation values of formalin-fixed breast tumors

[9].

In capsule form, the overall experimental de- sign called for collection of data first by x-ray examination of the breast of the patient prior to surgery, followed by: x-ray examination of the excised breast; detailed ultrasound visualization

and FFT studies of the formalin-fixed excised

breast specimen; whole breast sectioning of the tissue in blocks of approximately 0.5 cm in thickness; x-ray examination of each of these cross sections and, finally, sectioning and histological

staining of the primary malignant tumor region and other tissue areas of interest. The FFT studies were considered in the nature of a feasibility study and it is in that regard they are reported in this paper. Emphasis

is given in this preliminary report to a study of attenuation of the sound beam both in the region

of the malignant tumor and in other areas of the breast tissue (such as nipple and areola) as a function of frequency. As used in this paper,

the term "attenuation" designates all losses in sound pressure amplitude or intensity as the acoustic beam traverses the tissue, including

those due to specular reflection, scattering, re- fraction, absorption and diffraction.

Both the location (as revealed by x-ray examination of the whole, excised breast) and the malignant character of the primary mass (as revealed by

needle biopsy) were known at the time of the ultrasound visualization and FFT studies. At the time

of this writing, the histological classification

of the primary malignant tumor has been determined

and detailed histological studies are underway.

The precise correlations between information re- vealed by histology, ultrasound visualization and FFT techniques will be the subject of a later

paper.

2. Experimental Methods

The tissue specinen used in the subject study

was an excised, formalin-fixed, left breast of a female subject who was 49 years of age at the time of the mastectomy. Since the diagnosis of breast carcinoma had been made by x-ray and needle biopsy

prior to surgery, the mastectomy was carried out without a surgical biopsy so that the excised

breast contained the previously detected malignant

mass in an essentially undisturbed state. After

excision, the breast was made to assume its ap- proximate normal contour by pinning it to a layer

of paraffin, was x-rayed and then formalin-fixed.

The fixation process consisted of covering the

pinned breast with 10 percent formalin solution,

completely draining this solution and adding a fresh formalin solution every other day for a total period of two weeks. After the completion

of this process, the breast was maintained in formalin solution except for periods of ultrasonic

examination.

The instrumentation used for pulse-echo examination of the excised breast was a linear scan, B- mode visualization system which included a variety

of types of transducers. Only two of these trans- ducers were used as transmitters in the FFT studies, namely, 1.1 MHz and 4.4 MHz center fre- quency units. Most of the FFT studies were carried out with the 4.4 MHz unit and the results ob- tained with this transducer will be discussed in this paper. This transducer has a diameter of

1.9 cm, a 7.5 cm focal length, a midband frequency

response of 4.4 MHz, a band width of 3 MHz jutt

above noise, and 1 MHz at the 3 dB point.

During the visualization scanning procedures,

the breast and examining transducers were com- pletely immersed in mammalian Ringer's solution

at room temperature (23 °C) so that there was direct fluid coupling of the ultrasound to the tissue. Both transverse (medial-to-lateral) and longitudinal (superior-to-inferior) scans were

taken at distance intervals of 1 to 2 mm. In order to relate data recorded on the echograms to specific areas of the tissue, an anatomical land- mark on the tissue (such as the center of the nipple or the center of a prominent skin discoloration over the area of abnormality) was selected

and a highly reflective and attenuating acoustic

target placed on this landmark. With the focus

of the transducer set on the target center, the echogram of the breast tissue showed a distinct,

easily identified front surface reflection and an attenuation shadow of the target. Since the linear coordinates (X and Y) were recorded for each echogram, subsequent scans of the tissue with

the target removed could be directly related to the chosen anatomical landmark. These surface landmarks were subsequently used in the FFT ex- periments for identification of desired sound transmission tissue paths.

For the ultrasound attenuation studies in the transmission mode, the previously described axi- symmetric focused transducer was used as a trans- mitter, and a 4 mm diameter, 10 MHz frequency,

PZT cera:mic sandwi ch-type piezoelectric probe was

used as a receiver. A Panametrics Model 5050R

unit pulse-excited the transmitter, and a series

unit step attenuator was used to attenuate the ultrasonic received signals prior to their entrance into an amplifier receiver. The breast

preparation was mounted on a three-motion co- ordinate system in a temperature controlled mam- malian Ringer's bath (average temperature 23 °C) and positioned between the sending and receiving

transducers, with the anterior aspect of the tissue facing the sending transducer (fig. 1). With

this arrangement, any area of the tissue could be easily examined and the tissue could be moved in

1 mm steps in the three-axis coordinate system.

In order to record the system's reference waveform, transmitter and receiver transducers were

placed facing each other and adjusted in position

to receive the optimum plane wave acoustic signals.

A linearity test of the system was performed by

setting the attenuator unit at different values

and comparing the corresponding outputs of the FFT

86
Fig. 1. Experimental arrangement of examining

transducer (left), excised breast (side

view) and receiving transducer.

spectrum. The system was found to be accurate to

± 1 dB in the useable frequency band, for any particular transmitting transducer. The received

ultrasonic waveforms were digitized at a sampling

rate of 10 or 20 nanoseconds using an eight bit

Biomation Model 8100 digitizer and then transferred to a PDP-11/45 computer. Generally, four waveforms were digitized for each tissue region

of interest ( i.e ., nipple, areola, etc.), stored

on a computer disc, and later processed using a 1024 point FFT. In order to obtain attenuation

and phase-angle versus frequency plots, they were deconvolved with the original system's reference

waveform. The waveforms were transformed into the frequency domain and the absolute amplitude for each waveform was compared with the amplitude of

the reference waveform for the relative attenuation

measurement. To obtain the phase angle for each

waveform, the phase was compared with the reference waveform and subsequently linearized for each frequency. For optimum frequency resolution, ap- propriate sampling intervals were selected on the Biomation digitizer. The output was presented in

a graphical form in three different formats; namely, normalized pressure amplitude, attenuation and phase-angle spectra. The phase-angle data is pre- sented in a separate paper [10]. The tissue was sampled at various selected re- gions by moving the specimen across the ultrasound beam on the three-axis system. The regions

of interest chosen for this study were specific

tissue paths ( i.e ., f"om skin to back surface of

the specimen) which included 1) the malignant

tumor, 2) the nipple and 3) the areola. In that regard, eighteen separate transmission mode studies

were made in the tumor path, nine in the areola

path and eight in the nipple path. In addition,

the upper inner aspect of the breast was chosen as representative of normal, middle-aged, mamnary

adipose tissue and test ultrasound transmissions

were made in that region.

Following completion of the FFT studies, the tissue was longitudinally sliced to produce whole

breast sections from 5 to 8 mm in thickness. Each

of these cross sections was x-rayed and the radiographs studied to determine which specific regions

of the breast would be further examined by means

of histological techniques. Tissue cubes 2 x 2.5

cm in overall dimensions were excised from the selected regions of interest and prepared for histological study. The primary malignant mass

was included in one of these cubes of tissue.

3. Results

The ongoing histological studies indicate that

the primary malignant mass was an invasive carcinoma of duct cell origin with an intermediate de- gree of differentiation. The mass was multinodular, fairly v/ell circumscribed but not encapsulated, with a dense fibrotic center and a peripheral shell (3 to 4 mm thickness) of neoplastic

cells. The fibrotic tissue, representing the major tumor mass, was highly collagenous but the cellular shell had a minimum deposit of collagen.

Included in the illustrations shown in this paper are duplications of the recorded system

reference waveform (normalized pressure amplitude versus frequency) for sound wave transmission

through Ringer's solution, compared to the waveforms recorded for sound transmission through

breast tissue immersed in Ringer's solution. Such pressure amplitude graphical displays are presented in order to demonstrate the characteristics of

the reference waveform and the dynamic range limi- tations of the system.

Before discussing the results obtained for the tissue path that included the malignant tumor, it

is of interest to consider the attenuation values obtained for the areola and nipple tissue path re- gions of the breast which, on the basis of the x-ray examination, can be assumed normal. In calculating precise attenuation values, on the basis of the recorded, normalized pressure amplitude values, the tissue path length was taken as the distance between the anterior surface of the skin overlying the nipple or areola and the posterior surface of the breast specimen (as determined

by the previously obtained ultrasound visualization images of the breast specimen). Therefore,

it is emphasized here that the attenuation values

shown in figures 3 and 4 are not specifically for areola or nipple, but are for the tissue path that includes these structures.

Figure 2 presents recorded pressure amplitude

waveforms for four sound transits through the nipple at entrance points separated by 2 mm of surface tissue. These waveforms show the maximum

variability in pressure amplitude (differences in pressure amplitude for waveforms A, B, C, D) found

for the nipple region. The attenuation frequency

spectrum plot for the nipple path shown in figure

3 is based on the pressure amplitude waveforms

shown in figure 2 and the tissue path length (sur- face of nipple to back surface of the specimen)

traversed by the sound wave. Figure 4 is the attenuation frequency spectrum

for the areola region of the breast. As in the

case of the nipple, this data is also based on differences in pressure amplitude response curves

(three sound transits through the areola region at entrance points separated laterally by 1 mm of surface tissue) and the tissue path length (areola

skin to back surface of the specimen). All other

sound transmissions in the areola path gave re- sults within the range of values shown in figure

4. The tissue region of greatest attenuation, as shown in figure 4, was located closer to the nipple

in comparison to the other two sound transit regions.

87
12345678JL_ 1

Frequency Megahertz

Fig. 2. Computer recorded display of: (a) ref- erence waveform for ultrasound trans- mission through Ringer's solution only;

(b) waveforms A, B, C, D for ultrasound

transmission through four separate re- gions of the "nipple tissue path" of an excised, formalin-fixed breast immersed

in Ringer's solution.

9r

8 -

1 -

1 I

I I I I 1 2 3 4 5 6 Frequency MHz

Fig. 3. Attenuation frequency spectrum

for "nipple tissue path" based

on waveforms shown in figure 2.

I I I I

I I

1 2 3 4 5 6

Frequency MHz

Fig. 4. Attenuation frequency spectrum

for "areola tissue path" based

on three sound transmissions

through separate regions of the

areol a

.

Frequency Megahertz

Fig. 5. Computer recorded display of: (a) ref- erence waveform for transmission through

Ringer's solution only; (b) three waveforms for ultrasound transmission in separate regions of the "tumor tissue path" of an excised, formalin-fixed breast im- mersed in Ringer's solution.

88
The wavefonn recordings shown in figure 5 re- sulted from three sound transits in the tumor tissue path, with each of the test points separated

by 1 mm of tumor tissue in terms of skin surface

distance. In contrast to results obtained in all other tested regions of the breast, the recorded

waveform data show a total lack of recorded pressure amplitude response in the higher frequency

regions. This result indicates that there is at least 40 dB of amplitude loss, for the tissue path

from skin to back surface, in the frequency re- gions above approximately 2 MHz. At the lower end

of the frequency spectrum, pressure amplitude re- sponse was recorded but, as shown later in this paper, the level of these pressure amplitudes in- dicates a greater attenuation for the tumor tissue

path than for that of the nipple tissue path. For the main body of the primary malignant

tumor, the overlying tissue is approximately

1.5 cm in depth (from skin to anterior border

of overt mass); the tumor has a diameter of

1.5 cm in depth and the tissue below the tumor

is approximately 2 cm in depth. X-ray examination of the excised breast indicated the tissues surrounding the tumor were primarily fatty in nature. Consequently, if the attenuation

for the 3.5 cm of tissue surrounding the tumor

is considered to be that of normal breast adipose tissue and, further, if the attenuation

value for such tissue is assumed comparable to that found in the present studies for tissue

paths (skin to back of tissue) through other

fatty regions of the breast, namely, 2.5 dB/cm

at 2.0 MHz, then the tissues surrounding the tumor account for 8.8 dB of the attenuation. It should

be noted that the 2.5 dB/cm value for breast adipose tissue is in general agreement with that found by Calderon et al . [9], namely 2.3 dB/cm at 2.25 MHz for formalin-fixed, excised, normal breast tissue. Deducting the 8.8 dB from the 40

dB maximum dynamic range response of the system

and taking into account the 1.5 cm tumor path, it

is found that the attenuation for the malignant

tumor itself is 21 dB/cm at a frequency of 2 MHz. Since this value is in general agreement with that

of Calderon et a1 . who found an attenuation of

20 dB/cm at 2.25 MHz for formalin-fixed, excised,

malignant breast tumors, it is expected that the

40 dB dynamic range limitation, which represents

a factor of 100 in pressure amplitude and 10,000

in intensity, is close to an adequate dynamic

range response. Carrying out the same type of calculation, using

the pressure amplitude data shown in figure 5 for

the lower frequencies, gives an attenuation value

for the malignant mass of 8 dB/cm at a frequency

of 1.5 MHz. This is calculated on the basis of

3.5 cm of normal fatty breast tissue, with an at- tenuation value of 2.0 dB/cm at 1.5 MHz (as found

for other normal fatty regions of this breast

specimen) and a 1.5 cm depth of tumor mass. Of the total of 18 separate runs through the tumor tissue path, with the exception of two sound transits in a particular region of this path, all recorded results indicated that for frequencies

above 2 MHz there apparently was total attenuation

of the sound wave ( i.e ., within the 40 dB recording level capability of the system). The exceptional cases showed 1) a pressure amplitude waveform that was highly, but not completely, attenuated by the tumor path and thus was within the 40 dB maximum dynamic range of the system and 2) for a

sound transit in an area just 2 mm laterally distant from that of number one above, a pressure amplitude waveform which had precisely the same frequency spectrum, pressure amplitude response

as that found for normal fatty regions of the breast. On the basis of this result, it was assumed, prior to the histological examination, that

the tumor included a border region of less density

(conjectured to be a mixture of normal and neo- plastic tissue) than the central mass and an ad- jacent region of distinct adipose tissue. Based

on pressure amplitude data and the known tissue

path, an attenuation value of 13 dB/cm at a fre- quency of 2 MHz was calculated for this border

area of neoplastic tissue.

The histological studies, to date, clearly show

adipose tissue immediately adjacent to and sur- rounding the malignant mass, thus accounting for

the characteristics of the wavefonn which duplicated those of the fatty regions of the breast. The

3 to 4 mm thick neoplastic shell located adjacent

to the adipose tissue and surrounding the fibrotic center of the tumor presumably accounted for the

13 dB/cm attenuation value.

4. Discussion

At the present time, in clinical studies con- cerned with the use of pulse-echo methods for breast examination, differential diagnosis is primarily based on the characteristics of the wall of the tumor, the presence and nature of the echoes from the internal structure of the tumor and the existence or absence of a shadowing phenomenon re- sulting from the attenuation of acoustic energy

by a malignant mass. In evaluating each of these parameters, considerable emphasis and reliance is placed on the so-called "attenuation shadow" which,

when present, is generally considered to be indicative of the presence of a malignant mass. However, precise knowledge regarding attenuation

characteristics of normal, benign and malignant

breast tissue is extremely limited. This is a serious deficit since its consequence may be misdiagnosis of the benign or malignant nature of a breast tumor. Considerable care should be used in interpreting attenuation shadows produced by pulse-echo

examination of breast, with specific regard to the question of whether normal or benign tissues can produce significant shadowing effects. In that regard, Kobayashi has found that fat necrosis re- sults in an attenuation shadowing comparable to that produced by a malignant mass, as judged by

pulse-echo visualization [11]. Calderon et al .

'

studies at a frequency of 2.25 MHz of formal in- fixed excised breast tissue gave values of 20 dB/

cm for malignant masses, 9 dB/cm for benign masses

and approximately 2.3 dB/cm for normal breast tis- sue surrounding the tumors [9]. Although there

is a significant difference between attenuation

values for benign and malignant tumors as found by these investigators, it must be realized that in the clinical pulse-echo methods, differential diagnosis is made on the basis of a comparison between

the image pattern of the overt mass and that of the surrounding normal tissue. Therefore, the Calderon et al . data indicate that for pulse-echo

techniques in which the sound beam makes two passes through the breast, common sized benign tumors

(2 cm and above) with an attenuation of 9 dB/cm

could result in shadowing in relation to surround89
ing normal tissue with an attenuation value of

2.3 dB/cm. Additionally, the first author of this paper recently found, in the case of several clinical patients, each with an overt, benign mass within the breast (identified by x-ray examination

and confirmed by surgical biopsy), that the echograms obtained using standard pulse-echo methods

at frequencies of 4.4 MHz to 5.0 MHz displayed

distinct shadows in the region of the mass. The significance of this result, insofar as the present paper is concerned, is the recognition of the need for quantitative attenuation data on multiple

types of benign and malignant breast tumors, as opposed to simple visual inspection of shadow

phenomena of such masses and consider. -^ion of whether signal processing techniques may orovide

some of the needed data [12]. The FFT studies discussed in this paper, for the tissue path which included the malignant tumor, showed that the attenuation for the full range of frequencies studied (1.1 to 4.4 MHz) was greater

for this tissue path than for that of any other

area of the breast. Further, these findings were

consistent with those found in the visualization

echograms, that is to say, even at a frequency of

1.1 MHz, this specific tumor could be recognized

by "pale shadowing," while at the higher frequencies the attenuation shadow was more opaque and formed a distinctive border in relation to ad- jacent tissue. From the viewpoint of possible in vivo breast

examinations by FFT methods, it is of interest

that in the present study the dual structural com- ponents of the tumor (as shown by the two attenuation values) and the adipose tissue surrounding

the tumor were recognized prior to any histological investigations. Further, the finding that

the tc' ^1 malignant mass was attenuating but the greater attenuation was in the region of fibrosis

agrees with earlier studies [8] relating attenuation (as judged by nonquantitati ve pulse-echo

methods) of breast tumors with specific tumor tissues (as revealed by detailed histological

studies). The highly collagenous nature of the primary malignant mass combined with its high at- tenuation values and the minimum collagen content

of the surrounding cellular shell is of interest

in regard to the relative importance of elastic

properties versus physical structural make-up for

sound reflection and transmission through overt

tissue masses [13]. The ongoing histological

studies and the preliminary phase-angle data may

provide some information on this aspect [10].

There are many factors, both tissue and instrumentation related, associated with the attenuation

in the nipple path region as determined by the FFT ultrasound transmission studies discussed in this

paper. Included in the tissue aspects are the non- uniform structure of the skin surface and the vari- able tissue components within the nipple and in the regions deep to the nipple. Although the above factors may be significant, information

which is relevant to present pulse-echo clinical

techniques can be derived from the preliminary

FFT data without complete analysis of such parameters. In that regard, for example, the results

shown in figure 3 are important in relation to detection of an overt breast mass located in the region directly posterior to the nipple. If pulseecho techniques are applied to scan directly over

the nipple region, there may be a lack of success

in detecting such masses (particularly at frequencies of the order of 5 MHz) because of their loca- tion in the attenuating path of the nipple. For

the purposes oftumor detection, therefore, the tissues deep to the nipple should be viewed by

scanning from the side regions of the breast and

by using lower frequencies. These two approaches

to visualizing structures deep to the nipple were successfully applied by the present authors in the case of the excised breast discussed in this paper,

and breasts studied in vivo . To accomplish the overall aim of the studies

carried out in this preliminary investigation,

that is, to correlate x-ray, visualization, FFT analysis and histological findings, requires ex- tensive and time-consuming investigations. However, if some of the significant parameters that

are relevant to differential diagnosis of breast

tumors by ultrasonic techniques are to be determined by methods other than the necessai^'iy slow

process of interpreting ultrasound clinical data,

such detailed investigations are necessary. A significant result of the investigation reported

in this paper is the determination that this com- puter based, signal processing technique is feasible and can yield data on malignant and normal regions of breast tissue. It also appears evident

from these experiments that similar investigations

could be carried out on freshly excised whole

breast tissue. If such investigations are suc- cessful, then this technique could be considered

for application to breast patient examination.

Success in that regard could lead directly to de- velopment of an ultrasound breast examination

technique which might eventually limit the need

for surgical biopsy to a small number of exceptional cases.

Acknowledgments

Grateful acknowledgment is made to the assistance of George W. Ga ler, ultrasound technologist,

in all aspects of the above studies.

This research was supported by the Grace M. and Ralph W. Showalter Residua»"y Trust, and by the Indianapolis Center for Advanced Research, Inc.

References

[1] Kobayashi, T., Review: Ultrasonic Diagnosis

of Breast Cancer, in Ultrasound in Medicine

and Biology , Vol. 1 (1975), pp. 383-391.

[2] Gallager, H. S. and Martin, J. E., The Pathology of Early Breast Cancer, in

'

~

east Cancer : Early and Late , The Univers: f Texas,

M. D. Anderson Hospital, pp. 3/-50 (Year Book

Medical Publishers, Inc., Chicago, 1968).

[3] Gallager, H. S. and Martin, J. M., The study

of mammary carcinoma by mammography and whole

organ sectioning. Cancer 23 (4), 855-873

(1969).

[4] Fry, E. Kelly, Franklin, T. D., Jr., and Gallager, H. S., Ultrasound Visualization of Excised Breast Tissue: An Experimental Approach to the Problem of Precise Identification of Structure from Echogram Data, Acoustical Society of America meeting, Washington,

D.C., April (1971).

[5] Fry, E. Kelly, Gallager, H. S., and Franklin,

90
T. D. , Jr. , In Vivo and In Vitro Studies of Application o7 Ultrasonir~Visualization Tech- niques for Detection of Breast Cancer, in Proc, IEEE Ultrasonics Symposium , Miami,

Florida, December (1971). ~

[6] Martin, J. E. and Gallager, H. S., Reflections on Benign Disease: A RadiographicHistologic Correlation, in Early Breast Cancer Detection and Treatment , H. S. Gallager, ed. , pp. 177-181 (John Wiley and Sons, New York, 1976).

[7] Fry, E. Kelly, The Use of Ultrasound Methods

to Detect Changes in Breast Tissue Which Pre- cede the Formation of a Malignant Tumor, in Acoustical Holography , L. W. Kessler, ed.,

pp. 1-20, Vol. 7 (Plenum Publishing Corp., New York, 1977).

[8] Fry, E. Kelly and Gallager, H. S., A Research

Approach to Visualization of Breast Tumors by

Ultrasound Methods, in Ultrasound: Its Application in Medicine and Biology , F. J. Fry,

ed. (Elsevier Scientific Publishing Co.

,

Amsterdam, 1978).

[9] Calderon, C, Vilkomerson, D., Mezrich, R., Etzold, K. F., Kingsley, B., and Haskin, M.

,

Differences in the attenuation of ultrasound

by normal, benign and malignant breast tissue, J. Clin. Ultrasound 4 (4), 249-254

(19761:

[10] Fry, E. Kelly, Sanghvi , N. T., Fry, F. J., Gardner, G. W., and Gallager, H. S., Deter- mination of Alterations of Phase Angle of Ultrasound Transmitted Through a Malignant

Breast Tumor: A Preliminary Investigation,

in Ultrasound in Medicine , D. White, ed..

Vol. 4 (Plenum Publ ishing Corp., New York,

1978).

[11] Kobayashi, T., Takatani, 0., Hattori, N., and Kimura, K., Study of sensitivity-graded

ultrasonotomography of breast tumor (preliminary report), Med. Ultrasonics 10 (1), 38-40 (1972).

[12] Lizzi, F., Katz, L., St. Louis, L., and Jackson-Coleman, D., Applications of spectral

analysis in medical ultrasonography. Ultrasonics 14 (2), 77-80, March (1976).

[13] Fields, S. and Dunn, F., Correlation of echographic visual izabil ity of tissue with

biological composition and physiological

state, J. Acoust. Soc. Amer . 54 (3), 809- 812 (1973T:

91

Reprinted from Ultrasonic Tissue Characterization II, M. Linzer, ed., National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C., 1979).

CORRELATION OF ULTRASONIC ATTENUATION WITH CONNECTIVE TISSUE

CONTENT IN BREAST CANCERS

Toshiji Kobayashi

Division of Clinical Electrophysiology

Department of Internal Medicine

National Cancer Center Hospital

5-1-1, Tsukiji, Chuo-ku, Tokyo-104, Japan

In recent years, ultrasonic techniques have been applied to the diagnosis of breast

cancer. Various characteristics suggestive of tumor pathology have been determined.

In this paper, some of these signs, such as the acoustic middle shadow and the com- plete disappearance of the distal limit of the tumor mass echo, are correlated with

the connective tissue content of various breast cancers. Because of the high acoustic

impedance of connective tissue relative to the other tissues, tumors rich in connective tissue are believed more strongly to attenuate the ultrasonic waves and thus to cause shadows in the tissues beyond them.

Key words: Attenuation; breast cancer; cancer; connective tissue; differential

diagnosis; medullary carcinoma; papillary carcinoma; scirrhous

carcinoma; shadowing; ultrasound.

1. Introduction

Because of its noninvasive nature, diagnostic

ultrasound is a good clinical tool for the fine visualization of soft tissue pathologies. This

technique has been applied in the past several years to the differential diagnosis of breast

tumors with high diagnostic accuracies. Echo- graphic criteria for differentiating malignant

and benign lesions have been reported by several investigators [1-8]^.

Echographic patterns of shadowing beyond tumors (retromammary shadowing) provide reliable and ac- curate diagnostic information for the diagnosis of breast cancer. In this paper, various malignant

signs, such as the acoustic middle shadow sign and

the complete disappearance of the distal limit of

the tumor mass echo, are shown to be correlated

with the connective tissue content within the breast cancer. Because of the high acoustic im- pedance of connective tissue relative to the other

tissue, tumors rich in connective tissue are be- lieved more strongly to attenuate the ultrasonic

waves and thus to cause shadows in the tissues be- yond them.

2. Method and Results

During the past five years, 1617 cases of palpable breast tumors were examined echographi cal ly and all cases with breast cancer were verified by

mastectomy. This material forms the basis of this retrospective study. The method of examination is

^Figures in brackets indicate literature

references at the end of this paper.

shown in figure 1. The criteria for the differential diagnosis of breast tumors can be divided in- to three major categories comprising (1) the boundary echoes and shape, (2) internal echoes, and

(3) shadowing, as illustrated in figure 2.

Fig. 1. Method of scanning the breast. The 5 MHz probe is moved automatically along the arc of a circle, and ultrasonic coupling to the patient is through the water in the flexible

plastic bag.

93
BOUNDARY ECHO & SHAPE

usual ly regular and smooth, round, oval or hetnioval

INTERNAL ECHO RETROMAMMARY SHADOWING

uniform- si zed,

homogeneous or echo-free (anechoicl

irregular and jagged

bizarre, crab-like or polymorphous

non-uniform-sized

,

heterogeneous or polymerous

tadpole-tail sign

lateral shadow sign

accentuation of posterior echo

acoustic middle shadow

(posterior shadowing)

attenuation of posterior echo

Fig. 2. Diagram illustrating echogram appearances for differential diagnosis

of benign and malignant tumors.

The first two categories, that is, the boundary

echoes and shape, and internal echoes, result from

echo patterns mainly confined to the tumor mass it- self or its vicinity. The third category, shadowing, is a result of various attenuation mechanisms

such as multiple reflections, changes in beam velocity, and scattering due to the impedance discontinuities within the tumor.

The boundary echoes provide important diagnostic

information, producing outlines which are usually

irregular in the case of breast cancers, and regular in the case of benign lesions, such as cysts

and fibroadenomas. A cancerous tumor is uneven with a jagged edge, sometimes triangular, rectangular or irregular in shape, whereas a benign tumor

is usually round, oval or hemioval. Moreover, the internal echo pattern in a malignant tumor is usually irregular both in size and distribution, in contrast with the either homogeneous or anechoic

internal echo pattern of a benign lesion. Other differential diagnostic criteria result

from echo patterns due to multiple reflections from

the tumor mass, modifying the shadowing. It is this phenomenon which is the principal subject of

this paper. The tadpole-tail sign arises from the

low energy loss in the beam as it passes normally

through the distal wall of a cyst leaving sufficient energy to cause multiple reflections or "ringing" between the distal cyst wall and the chest

wall. The difference in the velocities in tissue

and cyst may play an important role in causing this

pattern. This sign is usually not seen in the majority of malignant lesions except in some cases

of medullary carcinoma. The lateral shadow sign is believed to be formed by the almost total reflection of the ultrasonic beam at the lateral wall of cystic lesions as, for example, with benign tumors

[6]; an explanation of the formation of this sign

has recently been published [9]. A characteristic of malignant lesions designated

as "acoustic middle shadow sign" is sometimes ob- served. This phenomenon is believed to be caused

by the high attenuation of the ultrasonic energy by

malignant tumor tissue, due to large acoustic im- pedance discontinuities within such tissue.

The reliability of these various signs for the differential diagnosis of various histological types

of breast cancer is seen in table 1. Diagnostic

accuracy is greatest in scirrhous carcinoma and lowest in medullary carcinoma.

Echographic characteristics suggestive of malignant lesions, such as the acoustic middle shadow

sign and the complete disappearance of the distal

limit of the tumor mass echo, have been correlated

with the connective tissue content of tumor masses

for various histological types of breast cancer.

The grading of the connective tissue content was di- vided into three categories based on the observation

of many microscopic field specimens. These categories were expressed as follows: 1) the connective

tissue over 75 percent (rich), 2) 25 to 75 percent

(moderate) and 3) less than 25 percent (poor). The specimens were stained by hemtoxylin and eosin and are shown magnified by approximately 100. The results of the analysis are shown in tables

1, 2, 3 and 4. The acoustic middle shadow sign as well as the complete disappearance of the distal

limit of the tumor mass echo, were most frequently

seen in the cases with abundant connective tissue,

whereas the tadpole-tail sign and the lateral shadow sign were often seen in cases with little

connective tissue content, mainly in medullary

carcinoma. These analyses were carried out on 12 cases of various breast cancers (4 scirrhous car- cinomas, 5 papillary carcinomas and 3 medullary

carcinomas).

94
Table 1. Reliability of various criteria for the differential diagnosis

of breast cancer (53 cases).

4-> O

ro -r- s- -c

ra

01 S- Q- O

Q- E

=C 3

Type of carcinoma Medullary Papi 1 1 ary Sci rrhous

Diagnostic accuracy rate 20/24 (83°/,) 13/15 (87%) 14/14 (100%)

nant Complete disappearance of

distal limit of tumor echo 17/24 (70%) 12/15 (80%) 11/14 f -t no/ \ (78%)

Irregular boundary echo 23/24 (95%) 14/15 (93%) 11/14 (78%)

ID s: Acoustic middle shadow sign 18/24 (75%) 11/15 (73%) 14/14 (100%)

c

Bilateral disappearance of distal limit of tumor echo 4/24 (17%) 1/15 (0.6%) 0/14 (0%)

(U Tadpole-tail sign 4/24 (17%) 2/15 (1.3%) 0/14 (0%)

CO Lateral shadow sign 4/24 (1.3%) 2/15 (1.3%) 0/14 (0%)

Table 2. Connective tissue content of 12 cases of carcinoma. Rich = over 75 percent;

moderate = 25 to 75 percent; poor = less than 25 percent. High consistency is indicated by (+++), intermediate consistency by (++), and low consistency by (+).

Connective tissue content Nonconnecti ve tissue content

1) Scirrhous carcinoma (Tl) (+++)

2) Sci rrhous carcinoma (Tl) (+++)

3) Scirrhous carcinoma (T2) (+++)

4) Scirrhous carcinoma (T2)

5) Papi 1 1 ary carcinoma (Tl)

6) Papillary carcinoma (Tl)

7) Papi 1 1 ary carcinoma (T2)

8) Papi 1 lary carcinoma (T2) (+++)

9) Papi 1 1 ary carcinoma (T2) (+++)

10) Medul lary carcinoma (Tl) (+) 11) Medul lary carcinoma (T2) (+)

12) Medullary carcinoma (T2) (+)

rich moderate

(++)

(++)

(++)

(++)

poor

(+++)

(+++)

(+++)

rich moderate

(++)

(++)

(++)

(++)

poor

(+)

(+)

(+)

(+)

(+)

Table 3. Correlation between appearance of various echo signs and connective tissue contents in

12 cases of carcinoma, classified according to echo signs. Signs indicated by circled

letters in the table have the higher reliabilities. A = acoustic middle shadow sign;

C = complete disappearance of distal limit of tumor mass echo; N= no change of shadow

or intermediate pattern; T = tadpole-tail sign; L = lateral shadow sign.

Connective tissue content

rich moderate poor

1) Scirrhous care i noma (Tl) (A) N T L A C N T L A C N T L 2) Scirrhous carcinoma (Tl) @ N T L A C N T L A C N T L 3) Scirrhous carcinoma (T2) C N T L A (0 N T L A C N T L 4) Sci rrhous carcinoma (T2) A c N T L A c N 'X) CD A C N T L

5) Papillary carcinoma (Tl) A c N T L A c N (T) A C N T L 6) Papi 1 lary carcinoma (Tl) A c N T L A c N (T) ® A C N T L 7) Papi 1 lary carcinoma (T2) A c N T L A c IN) T L A C N T L 8) Papil lary carcinoma (T2) (A) © N T L A c N T L A C N T L 9) Papil lary carcinoma (T2) CA) © N T L A c N T L A C N T L

10) Medullary carcinoma (Tl) A c N T L A c N T L A C N 8(T) 11) Medul 1 ary carcinoma (T2) A c N T L A c N T L A C N 0 12) Medullary carcinoma (T2) A c N T L A c (N) T L A C N T L

95
Table 4. Correlation between appearance of various echo signs and connective tissue contents in 12 cases of carcinoma, classified according to carcinoma type.

(S) = scirrhous carcinoma; (P) = papillary carcinoma; (M) = medullary

carcinoma.

Connective tissue content Nonconnecti ve tissue content

rich moderate poor rich moderate poor

Acoustic middle shadow sign (S)

(P)

(S) (S)

(P)

(S)

(P)

(S) (S)

(P) Complete disappearance of distal limit of tumor mass echo

(S)

(P)

(S) (P) (S) (S) (S)

(P)

(S) (P)

Tadpole-tail sign (P) (P) (M) (M) (M) (M) (P) (P) Lateral shadow sign (P) (P) (M) (M) (M) (M) (P) (P) No shadow or intermediate

pattern (P) (M) (P) (M)

3. Demonstration of Typical Echograms

and Tissue Characteristics

Tables 3 and 4 show the correlations between

the amount of connective tissue and the various

echo patterns described in the following para- graphs .

A. Scirrhous Carcinoma (Tl and T2)

A series of echograms recorded by the sensitivitygraded method [6] show typical patterns of shadowing (acoustic middle shadow sign) suggestive of T2 malignancy (fig. 3). The distal limit of the tumor mass echo gradually fades as the attenuation increases, as may be

Fig. 3. Echograms of breast with T2 scirrhous

carcinoma (acoustic middle shadow sign)

recorded at a range of sensitivities, to- gether with corresponding histological

section magnified approximately 100 times.

seen on the echograms taken at -15 to -20 dB at- tenuation, and finally completely disappears. The microscopic picture shows the tissue type content

to be predominantly connective in cellular structure. The echogram in figure 4 is a typical pattern of early scirrhous carcinoma (Tl), showing the acoustic middle shadow underneath the tumor mass

echo. Histologically, the connective tissue com- ponent is predominant.

Fig. 4. Echogram of breast with Tl scirrhous

carcinoma (acoustic middle shadow sign),

together with corresponding histological

section magnified approximately 100 times.

96
Fig. 5. Echogram of breast suggesting Tl scirrhous

carcinoma (acoustic middle shadow sign),

together with confirmatory corresponding

histological section magnified approximately 100 times.

The echogram in figure 5 shows another typical

acoustic middle shadow pattern suggestive of Tl malignancy. The microscopic picture also shows

rich connective tissue. These results suggest that rich connective tissue content may play an important role in producing the acoustic middle shadow sign and in the complete

disappearance of the distal limit of the tumor mass

echo in clinical echograms of scirrhous carcinoma.

B. Papillary Carcinoma (Tl)

The echogram of early papillary carcinoma shows

a typical attenuation of the shadowing, so that the acoustic middle shadow sign is not clear. Moreover, the typical benign signs such as tadpole-tail

sign and the lateral shadow sign do not appear either (fig. 6. )

The histological picture shows connective tissue

and nonconnecti ve tissue approximately evenly dis- tributed. Therefore, this pattern of papillary

carcinoma may lie in between those of scirrhous

carcinoma and medullary carcinoma (see C below)

with respect to the connective tissue content.

This kind of evenly-distributed connective and non- connective tissue produces an equivocal echographic

pattern which makes it difficult correctly to diagnose early papillary carcinomas.

C. Medullary Carcinoma (T2)

This echogram shows a rather homogeneous inFig. 6. Echogram of breast with papillary carcinoma (note absence of acoustic middle

shadow and tadpole-tail signs), together

with corresponding histological section

magnified approximately 100 times.

ternal echo, mimicking a benign cyst, and an atypical tadpole-tail shorter than that of tadpole-tail

usually seen in the case of benign tumors (fig. 7). Consequently correct diagnosis is rather difficult.

The histological picture shows rich non-connective

tissue content, and especially abundant and uni- formly distributed tumor cells. This kind of homogeneous and even distribution of tumor cells should produce little sonic reflection from within

the tumor mass, thus mimicking the pattern of benign cysts.

4. Discussion

In the past several years, researchers have hypothesized that the ultrasonic characteristics

of malignant breast tumors could be attributed to the increased attenuation of ultrasonic energy by

the cancerous tissue with greater internal acoustic

impedance discontinuities, and hence increased

scattering losses, as compared with those with

normal breast tissue and benign breast tissues.

In direct measurements of the attenuation of ultrasound within 18 samples of various normal,

benign and malignant breast tissues, significant

differences have been found [10]. At 2.25 MHz, malignant tissue had the highest attenuation (1.2 dB per wavelength), whilst benign tissues had a median value of 0.6 dB per wavelength. These re- sults support the hypothesis.

From a histological standpoint, the percentage

of connective tissue (consisting of fibroblasts

97
Fig. 7. Echogram of breast with T2 medullary

carcinoma (the tadpole-tail sign is shorter than that generally seen with

benign tumors), together with corresponding histological section magnified ap- proximately 100 times.

and fibrous tissue) has been suggested to be one of the principal factors responsible for ultrasonic

attenuation in neoplastic tissue [11].

In an analysis [12] of 53 cases of breast cancer

for the incidence of the appearance of various echo- graphic characteristics such as the acoustic middle

shadow sign, the complete disappearance of the distal limit of the tumor mass echo was suggestive

of malignancy, and the tadpole-tail sign and the lateral shadow sign was suggestive of a benign con- dition. Diagnostic accuracy rates were 100 percent, 87 percent and 83 percent in scirrhous carcinoma, papillary carcinoma and medullary carcinoma

respectively, as may be seen in table 1. It is in- teresting to note that the tadpole-tail sign and the lateral shadow sign appeared most rarely, and

the disappearance of the distal limit of the tumor

echo was most frequent, in medullary carcinomas.

Generally these signs suggest benign lesions, and this may account for the fact that the lowest diagnostic accuracy is obtained with medullary carcinomas . The connective tissue content seems to be gener- ally rich in scirrhous carcinoma and poor in medullary carcinoma. The tumor cellular component

usually predominates Within the nonconnecti ve tis- sue of medullary carcinoma and this tissue structure may be responsible for the bioacoustical homo- geneity observed within the tumor mass. This homo- geneity in medullary carcinoma may produce less attenuation of ultrasonic energy, resulting in shadowing suggestive of benign tumors, such as the tadpole-tail sign and the lateral shadow sign. In the present investigation, these echographic charac- teristics appear regardless of the tumor size and

the location of the tumor mass within the breast. Medullary carcinoma has lower attenuation than other types of carcinoma [10]; its measured value

at 2.25 MHz falls in a range comparable to that of benign tumor tissue, whereas the attenuation is highest in scirrhous carcinomas followed by papillary carcinomas. It is interesting to note that

the discrimination on the basis of attenuation was very clear between normal breast tissue, benign

tumors, and malignant tumors, except for the case

of medullary carcinoma. This finding is in agree- ment with the hypothesized echographic origin of

the medullary carcinomas even at the frequency of

5 MHz used in the present analysis.

As to the other factors contributing to the echographic characteristics of tumors, especially

irregular and nonsmooth boundary echoes of various

carcinomas, the incident rate of its irregularity

is 95 percent for medullary carcinoma, 93 percent

for papillary carcinoma and 78 percent for scirrhous

carcinoma. This kind of irregularity may be closely related with infiltrative pattern of cancerous

cells, and the reflection coefficient at the tumor

interface as well as other factors.

It should be emphasized that the correlation of clinical echographic signs with the histological

characteristics of the tumors does not imply that

in any given case, a particular sign is indicative

of any histological type. Because of inadequacies

of the clinical equipment used in this study, these correlations should only be considered qualitative.

The principal conclusion is that the amount of con- nective tissue within the tumor mass may play an important role in the formation of the acoustic

middle shadow sign and the complete disappearance

of the distal limit of the tumor mass echo, and that it is probably due to the increased ultrasonic

attenuation caused by the high acoustic impedance

of the connective tissue.

References

[1] Baum, G., Ultrasonic Examination of the Breast, in Fundamentals of Medical Ultra- sonography , G. Baum, ed., pp. 380-402

(Putnam' s Sons, New iork, 1975).

[2] Cole-Beuglet, C. and Beique, R. A., Con- tinuous ultrasound B-scanning of palpable

breast masses. Radiology 117, 123-128 (1975).

[3] Fujii, T. , Izuo, M., Kishi, S., Yokomori , T., and Fujimori, M., The results and the evaluation of ultrasonic diagnosis of breast disease, J. Jap. Soc. Cancer Therap . 8^, 253-

[4] Hirose, M. and Furuki, R. , Ultrasonic diagnosis of breast disease, Proc. 17th Meeting

Jap. Soc. Ultrasonics Med . 17, 37-38 (1971)

[5] Jellins, J., Kossoff, G., Reeve, T. S., and Barraclough, B. H., Ultrasonic grey scale visualization of breast disease. Ultrasound

Med. & Biol . I, 393-404 (1975).
Kobayashi , T. , Takatani, 0., Hattori , N., and Kimura, K. , Differential diagnosis of breast tumors: The sensitivity graded method

of ul trasonotomography and clinical evaluation of its diagnostic accuracy. Cancer 33 , 940-951 (1974).

Pluygers, E., Diagnostic ultrasonore, par echographie A et B, des affections Mammaires,

J. Beige. Radiol . 58, 15-29 (1975).

Wagai, T., Tsutsumi , M. , and Takeuchi, H.

,

Diagnostic Ultrasound in Breast Diseases, in Present and Future of Diagnostic Ultrasound,

I. Donald and S. Levi, eds., pp. 148-161

Okujima, M., Refraction of ultrasonic beam incident near circumference of spherical

medium, Proc. Jap. Soc. Ultrasonics Med . 29 , 231-232 (1976).

[10] Calderon, C. , Vilkomerson, D., Mezrich, R.

,

Etzold, K. E., Kingsley, B., and Haskin, M., Differences in the attenuation of ultrasound

by normal, benign and malignant breast tissue,

J. Clin. Ultrasound 4, 249-254 (1976).

[11] Field, S. and Dunn, F., Correlation of echographic visualization of tissue with biological composition and physiological state,

J. Acoust. Soc. Am . 54, 809-812 (1973).

[12] Kobayashi, T. , Takatani, 0., Hattori, N. , and Kimura, K. , Clinical investigation for

the differential diagnosis of breast tumor

by means of the sensitivity graded method

of ul trasonotomography (fourth report) - Analytical re-appraisal of diagnostic

criteria in echographie and mammographic

findings, Proc. 24th Meeting Jap. Soc . Ultrasonics Med . 24, 147-148 (1973).

99

Reprinted from Ultrasonic Tissue Characterization II, M. Linzer, ed., National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C., 1979).

THE ATTENUATION OF SELECTED SOFT TISSUE AS A FUNCTION OF FREQUENCY

D. H. Le Croissette, R. C. Heyser, P. M. Gammell , and J. A. Roseboro

Jet Propulsion Laboratory

California Institute of Technology

Pasadena, California 91103, U.S.A.

and

R. L. Wilsoni

School of Medicine

University of Southern California

Los Angeles, California 95033, U.S.A.

Measurements of attenuation versus frequency have been made on pancreas, kidney,

fat and liver specimens of hog tissue. Hogs were of the "Berkshire" variety and the tissue obtained from a slaughterhouse. The measurements were taken under controlled

conditions of temperature and formalin fixing to determine the effects of aging and fixing on the tissue. A swept-frequency transmission system was used operating over the range of about 1.5 to 9.5 MHz. The curves show the changes occurring in fresh tissue as a result of several days of aging at refrigerator temperatures (5 °C) and

the effects of fixing the tissue in formalin immediately post-mortem or after several days of 5 °C storage. All measurements were made at 37 °C.

Key words: Attenuation; tissue properties; transmission; ultrasound.

1. Introduction

The recent interest in characterizing soft tissue by ultrasound is based upon measurements made

as early as 1952 [2]^ and later observations by

scientific investigators attempting to lay the groundwork for a new technique of ultrasonic diagnosis. The work reported here is the start of a systematic attempt to measure the attenuation of soft tissue as a function of frequency. This

topic was chosen because of the belief, substantiated by initial measurements [2], that there is

I a variation in the attenuation of ultrasound

through tissue as a function of frequency that can

be correlated with the pathological state of the

tissue. The measurements reported here were made

j on excised tissue obtained from hogs. This paper

I reports data obtained from fresh, aged and fixed

specimens.

In a typical pulse-echo ultrasound imaging

system, the frequency variation of attenuation

cannot usually be identified. Furthermore, the

ii increase in attenuation of normal tissue as a

j function of frequency tends to mask the high

1 frequency behavior of tissue when a measurement

is made over a long path length, i.e ., far from

the transducer. These two factors have made the identification of pathological tissue by its

^Current address: Harbor General Hospital,

Torrance, California 90509. ^Figures in brackets indicate literature

references at the end of this paper.

frequency-dependent characteristic unlikely and

so this phenomenon plays little part in the sub- jective pattern recognition techniques used in contemporary diagnostic ultrasonography. It is believed, however, that if an identification

mechanism based on frequency-dependent phenomenon

can be found, suitable instrumentation will be devised for tissue identification. Measurements on tissues of known pathologies

can greatly increase the knowledge of tissue

characterization needed to develop such instrumentation. Specimens obtained from cadavers

are especially useful since the individual organ

can be studied. Most autopsy material, however,

is not available until after a one or two-day

delay. Furthermore, the general availability of pathological tissue is greatly enhanced if a study is not constrained to specimens a few hours

old. This study is therefore to determine the acoustic attenuation characteristics of several organs as a function of time after death and after fixing in formalin solution.

2. Methodology

There are two major methods for examining the ultrasonic propagation behavior of tissue as a function of frequency. The most popular method

[3-5] uses the frequency spectrum that is emitted

by a heavily damped transducer operated in a pulse mode. This method is capable of giving

useable data at frequencies several times the natural resonant frequency of the crystal with

adequate signal-to-noise ratios. By contrast.

101
the technique used in this work does not pulse

the transducer but sweeps the operating frequency

over a wide band. This technique [6], known as Time Delay Spectrometry (TDS), reduces the ef- fects of multipath propagation and reverberation

by using a swept frequency transmitter and re- ceiver so that the frequency acts as a "time

tag" to the signal. The sweep of the receiver

is delayed from that of the transmitter so it will only respond to the signals with the proper

time delay. This discriminates against signals

with different arrival times, especially those

due to reverberation and multipath propagation.

The data were taken with a standard swept-type

spectrum analyzer-tracking generator which has been modified by offsetting the tracking generator

by a constant frequency. A Panoramic SPA-3 spec- trum analyzer and Panoramic G6 tracking generator

were used. This tracking generator can be adjusted to compensate for the time of transit of the ultrasound through the sample. A sweep rate of

100 MHz'S"-' and 3 dB intermediate frequency band- width of 600 Hz were used. If the sweep frequency

versus time of the spectrum analyzer is linear,

this constant frequency offset will exactly com- pensate for a constant time delay of the ultra- sound through the specimen. The time delay will

be constant across the frequency sweep if both

the specimen and the medium in which it is im- mersed are nondispersi ve. Dispersion of the me- dium and the sample will not affect the measurements by more than 1 dB, provided the average velocity of the sample and medium does not change

by more than 1 percent. Linearity requirements

on the sweep of the spectrum analyzer are ex- treme, however. The measurements were made over the frequency

range 1.5 to 9.4 MHz. Two Aerotech Alpha trans- ducers were used. The 10 MHz, 0.63 cm diameter

(0.25 inches) transducers were selected so that

the resonant frequency was just above the range

of interest. This frequency was chosen so that

the transducer sensitivity increased with fre- quency over the band. This compensates for the increase in tissue attenuation with frequency to give a more nearly constant signal-to-noise ratio

over the selected frequency spectrum. The specimen was located midway between the transducers,

which were 12 cm apart.

3. Specimen Handl ing

Specimens of tissue from hogs were studied no more than four hours after slaughter. The tissue

type and the time sequence of the measurements

are shown in figure 1. All specimens were heat sealed in a plastic bag containing either 0.9 percent saline or formaldehyde diluted 10:1 with water (i.e., approximately 4 percent). The liver

specimens were sliced to approximately 15 mm

thickness; the kidney and pancreas specimens were

studied intact. The backfat specimen was left in the form of a slab as it was stripped from the carcass. The thickness of all of the specimens

was calipered at the locations studied. Fat is normally removed one day after slaughter which accounts for the one-day delay shown in figure

Kb).

Figures 2 through 9 show the measured attenuation versus frequency for the hog tissue at

37 °C. Four or five locations on each specimen were studied. Obvious ducts, vessels, and taperDAYS POST MORTEM

SPEC. NO. 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 1 10 1 11 1 12 1

1 1 1

. —I 1 .—L- I 1 I 1 1 1 1 I

PANCREAS ^

KIDNEY

r.

I 205 9 O 1 1 1 1 1 0 1 , . , .1 , , i, lot 1 1 ;Sl

1 2062 1 1 1 1 1 O ) lit 1 1 t

.^-^

1 2061 1 1 O 1 1 1 t 1 ) 1 1 ) 1

1 2060 ' . l i 1 t .

. . , .V-,', ,. . ^. .V-. J^. -\-, ,V A ^K\^\\\^

1 2047 O 1 1 O 1 1 1 0 1, . f :\X7. } t

] 2064 o 1 1 o 1 1 1 0 f 1 lot I t t ..^

1 2048 1 1 O 1 } t 1 1 J 1 I 1 i .. aN

1 2049 i A 1 t t i t lot 1 1 t §1

1 2063

1 1 1 1 1 t t t O t t 1 1 NX\1

1 2065 11 1 1 |o| 1 oi,,, t,„J„^,,t

(a)

h^AX'xv^NXKx^'^l FIXED (:':-:^::v:-:';-:';''->v:'J FROZEN

1

1 5 °C Q DATA

DAYS POST MORTEM

SPEC. NO. 0|l|2|3l4l5|6|7|8|9llO|n|l2|

FAT -

1 2055 lot 1 o 1 1 1 oi-i?*:' 1 lot 1 1

1 2057

1 1 1 1 1 1 o'iixi' t 1 1 1 1

1 2056 1 1 1 c ! 1 1 ! t ! 1 1 1 1

1 4.:<i;.<.t.,.J,.-4.,,i<v.J,, J A 1

LI m

1 2050 1 o 1 lo! 1 1 o^<^:V^^^^^^^^,;^t*^^^^^^^^^^ ,1

1 206 7 o 1 1 o 1 1 Id 1 t o 1 1 1 1 ,';5l

1 2052 1 1 1 1

1 o 1 1 1 1 1 1 i

I 20511 1 o'l r ! 1 1 i t 1 1 1'^^

1 2Q66 1 \t

' 1 r t 1 1 i c 1 1 i 15^

1 2053 1 1 1 1 1 ! 1 1 o 1 1 i, , t_:^

1 2054 1 t t 1 1 f 1 1 o 1 i !

1 2068

1 1 i 1 1 i

1 O i 1 1 1 t OS)

(b)

Fig . 1.

t" J FIXED [ : 1 FROZEN

1 1 5 °C O DATA

Specimen history: (a) pancreas and kidney, (b) fat and liver.

ed edges were avoided. In the case of the kidney, measurements were not made in the central portion,

which contains the large vessels and the renal pelvis. All of the kidney measurements were made

in the region of the pyramids, and so include

both cortical and medullary matter. The loca- tions studied on any given specimen can be identified by the shape of the symbol used on figures

2 through 5. That is, the circle, square, or triangle represents the same visible location on the specimen when studied on the day of slaughter,

five days later, and after fixing. Care was taken to avoid multipath effects by visual in- spection of the area of the specimen and by

observing the spectrum analyzer for obvious signs

of multipath interference. Since no fine structure was observed in the attenuation versus fre- quency curves, the data are reported at 0.5 MHz

i nterval s

.

Each specimen was measured at four or five

points. This is a compromise between sampling

enough locations to insure that the measurements are representative and reducing experi- ment time to a minimum. Since tissue is known

to deteriorate rapidly at 37 °C, it is important that the experiment time be kept as short

as possible. Stray air bubbles that initially

clung to the specimen were gently brushed away.

No gas evolution was subsequently observed

vi sual ly.

102
2 4 6 Frequency, MHz

10

25r

20-

5

15-

10-

4 6 Frequency, MHz

10

25r

20-

15-

10-

25

20

15

53u lOh

M1 Oh -

20-

I— 0,

2 4 6 8 Frequency, MHz

(d)

A A

o

O V

a <s O

Fig. 2. Attenuation versus frequency for hog pancreas: (a) 6 hours post-mortem (fresh) , (c) 5 hours post-mortem (fixed), (d) 5

4 6 8 Frequency, MHz post-mortem (fresh), (b) 5 days

days post-mortem (fixed).

10

These measured values of tissue attenuation

exhibit considerable variability. At this

stage in the experiments it was considered that little was to be gained by applying statistical

analysis on the four or five readings taken al- though it is recognized that a mean and variance will be meaningful on readings from a

) higher number of points. Accordingly, the

; averaged or summarized data are presented in

I the form of band diagrams in figures 6 through

J 9. These bands were selected to follow the data

with no more than 10 percent of the points falli ing outside of the band.

4. Data Acquisition

The response of the system was recorded with

attenuations of 0, 5, 10, 15, 20, 25, and 30 dB

switched into the system. The response with the specimen between the transducers was then recorded on the same polaroid film. Since the sweep

of the spectrum analyzer only covers a 5.5 MHz range in the present equipment, it was necessary

to take the data in two parts. As a check,

readings taken from both spectra are reported in the range of overlap, which is 4.5 to 5.5 MHz.

If only one reading is reported at a given loca103
OL- 0, 4 6 Frequency, MHz

2 4 6 Frequency, MHz

25

20

S 15

10

25

20

15

10

OL

2 4 6 Frequency, MHz

10

Frequency, MHz

Fig. 3. Attenuation versus frequency for hog kidney: (a) 3 hours post-mortem (fresh),

post-mortem (fresh) , (c) 4 hours post-mortem (fixed), (d) 5 days post-mortem (f

(b) 5 days

i xed )

.

tion on the specimen then the readings from the upper and from the lower spectra agree within

0.5 dB. Since the calibration spectra are ob- tained for 5 dB increments, interpolation to the nearest 1 dB is reliable. For smoothness in plotting the data, the graphs are plotted to the nearest 0.5 dB, although no significance should

be attached to changes of less than 1 dB. The accuracy of the data is believed to be generally

± 1 dB, with rare deviations of ± 2 dB. Meas- urements using standard, non-biological samples

show a system repeatability error of + 0.5 dB.

5. Measurements

Figure 2 shows the plot of attenuation versus frequency for hog pancreas under four conditions;

(a) six hours post-mortem (fresh), (b) five days

post-mortem (fresh), (c) fixed five hours postmortem, and (d) fixed five days post-mortem.

Storage of the fresh tissue at 5 °C results in a decreased attenuation particularly at the higher

frequencies. These data do not seem conclusive,

however, since figure 2(b) shows a bimodal distribution of readings. The organ lacks rigidity

and so accurate placement and replacement of the

104
25r

20-

15-

10-

25r25|-

20-

15-

15-

."10-

- o -

10-

o) 5

OL- OL

2 4 6 Frequency, MHz

4 6 Frequency, MHz

8

V o

A i o

r\ o O g 8

°

O

25

20-

15

10

2 4 6 Frequency, MHz

10

OL- 0, 2 4 6 Frequency, MHz

10

Fig. 4. Attenuation versus frequency for hog backfat: (a) 1 day post-mortem (fresh), (b) 6 days

post-mortem (fresh) , (c) 1 day post-mortem (fixed, (d) 6 days post-mortem (fixed).

transducers on these specimens is very difficult.

In addition, the pancreas contains lobules of glandular tissue on the order of 1 cm, interspersed with fat. It is therefore considered

that the wide spread in data can be accounted for

by the lack of rigidity and the inhomogeneity of the specimen. Figure 6 shows the bands of attenuation versus frequency for the fresh specimens

under two conditions; six hours and five days

post-mortem.

The measurements on fresh and fixed kidneys

are shown in figure 3 and the corresponding bands

of attenuation are given in figure 7. For the

fresh specimens, storage of the tissue at 5 °C for five days has resulted in a decrease in at- tenuation, especially at the higher frequencies. Measurements taken 48 hours post-mortem (not re- ported here) lie between the two values. This

decrease is just sufficient to separate the band curves. The attenuation of fixed tissue is above that of the tissue just post-mortem.

Figures 4 and 8 made on hog fat show that there

is little effect of aging on the attenuation char- acteristics. Little significance can be placed on the differences at low frequencies shown in figure

8 since the attenuation is only of the order of

105
25 25

15-

sio-

(a)

4 6 Frequency, MHz

20

15

10

10

15

10

(b)

X

^ a

C)

2 4 Frequency,6 MHz

10

251-

20

15

10

OLFrequency, MHz

4 6 Frequency, MHz

Fig. 5. Attenuation versus frequency for hog liver: (a) 5 hours post-mortem (fresh), (b) 5 days

post-mortem (fresh) , (c) 5 hours post-mortem (fixed), (d) 5 days post-mortem (fixed).

the uncertainties in the measurements. Fixing the specimens gives a slightly higher attenuation.

There is considerable difference between this fat

and typical fat found in human studies so that

these data should be applied with caution. Hog fat is white and of a uniform texture whereas

human fat is yellow and has a lobular structure

with connective tissue interspersed.

Figures 5 and 9 show the data for hog liver. Here the storage of a fresh specimen results in

a lower attenuation over a five-day period. The

fixed specimens show increased attenuation. The

data bands are fairly narrow probably because of

the homogeneity of the tissue at the resolution

level studied. These tissue specimens were stored at 5 °C and heated to the measurement temperature of 37 °C over about a one-hour period. Following this procedure, each specimen was returned to the re- frigerator for storage until the next measurement

was made or until the specimen was fixed. For comparison, some specimens were held undisturbed

at 5 °C until a single measurement was taken. No significant difference in attenuation could be seen between the two groups.

106
T

6 h post-mortem

5 d post-mortem

4 6 Frequency, MHz

10

Attenuation versus frequency data bands

for hog pancreas: 6 hours and 5 days

post-mortem (fresh).

5

3 h post-mortem

iyZ\ 5 d post-mortem

4 6 Frequency, MHz

10

Fig. 7, Attenuation versus frequency data bands

for hog kidney: 3 hours and 5 days

post-mortem (fresh).

T

Frequency, MHz

8. Attenuation versus frequency data bands

for hog backfat: 1 day and 6 days

post-mortem (fresh).

T

5 h post-mortem

5 d post-mortem

Frequency, MHz

Fig. 9. Attenuation versus frequency data bands

for hog liver: 5 hours and 5 days

post-mortem (fresh).

107
6. Discussion

The accuracy of these measurements relies

upon the internal sweep linearity of the spectrum

analyzer to provide a constant time delay across

the frequency band matching the constant transit

time of the sound energy through the specimen.

Slight non-linearities in the sweep were observed

to give an error as high as 1 dB in the measured

attenuation. Some indication of this error may

be seen in the region between 4.5 and 5.5 MHz.

In practice, two sets of data were taken; the lower half extended from 1.5 to 5.5 MHz and the upper part from 4.5 to 9.5 MHz. Small errors in the overlapping region are indicated by two values being plotted with the same symbol. In many

cases identical values were obtained or the er- ror was small. Since these measurements were

taken, a new system has been built in which the sweeps of the transmitter and receiver are ob- tained from digitally programmed phase-coherent

synthesizers. This will insure that the system

is aligned over the entire frequency range of 1 to 10 MHz and will materially improve the quality

of the data

.

Acknowledgment

This paper presents the results of one phase

of research conducted at the Jet Propulsion

Laboratory, California Institute of Technology

for the National Science Foundation, by agree- ment with the National Aeronautics and Space

Administration.

References

[2] Le Croissette, D. H. and Heyser, R. C,

Attenuation and Velocity Measurements in Tissue Using Time Delay Spectrometry, in Ultrasonic Tissue Characterization , M.Linzer,

ed.. National Bureau of Standards Spec. Publ. 453, pp. 167-196 (U.S. Government Printing

Office, Washington, D.C., 1976).

[3] Lele, P. P., Mansfield, A. B., Murphy, A. I., Namery, J., and Senapati , N., Tissue Characterization by Ultrasonic Frequency-Dependent

Attentuation and Scattering, in Ul trasoni

c

Tissue Characterization , M. Linzer, ed.. National Bureau of Standards Spec. Publ. 453,

pp. 167-196 (U. S. Government Printing

Office, Washington, D.C., 1976).

[4] Lizzi, F. L. and Laviola, M. A., Tissue

signature characterization using frequency

domain analysis. Ultrasonics Symposium

Proceedings (IEEE), pp. 714-719, 1976.

[5] Miller, J. G., Yuhas, D. E., Mimbs, J. W.

,

Dierker, S. B., Buse, L. J., Laterra, J. J., Weiss, A. N. , and Sobel , B. E., Ultrasonic

tissue characterization: correlation be- tween biochemical and ultrasonic indices of myocardial injury. Ultrasonics Symposium

Proceedings (IEEE), pp. 33-43, 1976.

[6] Heyser, R. C. and Le Croissette, D. H.,

A new ultrasonic imaging system using Time

Delay Spectrometry, Ultrasound in Med, and

Biol . 1, 119-131 (1974).

[1] Wild, J. J. and Reid, J. M., Further pilot

echographic studies on the histologic structure of tumor of the living and intact human

breast. Am. J. Pathol . 28, 831-861 (1952).

108
CHAPTER 4

SCATTERING AND ATTENUATION

109

Reprinted from Ultrasonic Tissue Characterization II, M. Linzer, ed.. National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C., 1979).

CLINICAL SPECTRUM ANALYSIS TECHNIQUES FOR TISSUE CHARACTERIZATION

Frederic L. Lizzi and Marek E. Elbaum

Riverside Research Institute

80 West End Avenue

New York, New York 10023, U.S.A.

A spectrum analysis system is being used in a clinical measurement program to ex- amine the reflectance characteristics of intraocular structures. The on-line system

computes power spectra descriptive of echoes returned from well-defined tissue seg- ments chosen by the examiner. Clinical data are digitized for subsequent post- processing and cataloguing. This paper presents an overview of the theoretical

analysis used to formulate system design and to guide data interpretation. The analysis accounts for stochastic tissue architectures and treats the specific il- lumination conditions employed in the system. The paper also discusses system parameters as related to observable tissue characteristics and presents typical test

data and clinical spectra for several pathologic conditions.

Keywords: Clinical ultrasound; ocular tumor; power spectra; Rayleigh scattering;

ultrasonic spectrum analysis.

1. Introduction

Within the past few years, a variety of ad- vanced techniques have been employed to measure

the ultrasonic properties of soft-tissue structures [l-3]i. This paper describes a clinical

spectrum analysis technique [4] which has been used to measure the frequency-domain charac- teristics of ultrasonic backscatter from tissues

of the eye and orbit. The technique employs a clinical, on-line system together with computer

post-processing and data cataloguing. Following

laboratory verification, an extensive series of clinical measurements has been carried out. The

in vivo spectral data base is now being evaluated in terms of potential diagnostic signifi- cance and is also being employed in analytic modelling of tissue reflectance.

The spectrum analysis techniques have been de- signed to accommodate the stochastic nature of clinically relevant tissue structures, such as ocular tumors and vitreous hemorrhages. These

structures exhibit randomness in terms of the size,

orientation, and/or spatial position of their con- stituent internal scattering centers. Single re- flectance measurements made on such stochastic

entities exhibit a significant degree of statistical fluctuation which can preclude the reliable

identification of pertinent tissue characteristics.

Accordingly, the spectrum analysis techniques de- scribed below incorporate on-line ensemble averaging: the resulting power spectra determinations

constitute statistically stable descriptors of tissue properties. In addition, compensatory procedures are employed to account for extraneous spectral weighting introduced by the transfer functions

^Figures in brackets indicate literature

references at the end of this paper.

of transducers and electronic subsystems.

The spectral techniques can ultimately be em- ployed clinically to examine organs other than the

eye. However, their in vivo application is now practicable in ocular examinations since the media

of the eye do not present additional constraints

found in other organs. If transmission through

the ocular lens is avoided [5], acoustic attenuation and refraction do not present significant

obstacles in viewing intra-ocular structures at center frequencies higher than 10 MHz. The large

bandwidths that can be realized at these high fre- quencies permit spectral sensitivity to morphological features whose scale sizes are significantly less than 0.5 mm. In addition, the narrow beam- widths ( e.g . , 0.3 mm) available at these center

frequencies provide precise spatial definition of tissue segments to be analyzed and permit meaningful ensemble averaging, even within small tissue

vol umes

.

To date well over 200 clinically derived spectra

of normal and abnormal structures have been ac- quired, processed, and catalogued in diseaseindexed digital files. Previous publications have discussed the operation of the spectrum analysis

system and presented clinical findings [6,7].

This paper first outlines the analytic framework

which has guided system design, clinical operation,

and data interpretation. It then describes system

operation emphasizing the relations between system

performance parameters and observable tissue characteristics. Lastly, it presents representative test

results for comparison with clinical data obtained

for several ocular pathologies.

2. Outline of Analytic Framework

The clinical deployment of the spectrum analysis

techniques employed in the present system has been

111
guided by an analysis which accounts for both the stochastic nature of tissue architectures and the geometry and temporal spectrum of the ultrasonic

illumination beam. This analysis is presented in outline form to facilitate discussions in following sections. (A more comprehensive treatment will

be presented elsewhere [8].) The analysis is discussed, first, in terms of

its general formulation which accounts for the use of focused illumination conditions. Second, tissue architectures which are statistically stationary are discussed. Lastly, attention is given to tissues which can be modelled as randomly distributed Rayleigh scatterers.

A. Basic Formulation

The geometry involved in the analysis is shown

in figure 1. A focused transducer emits a short,

broadband ultrasonic pressure pulse. Radio fre- quency echo signals received from scatterers within

a range-gated segment (0-L) are subjected to spec- trum analysis. The range gate is positioned within

the focal volume of the transducer and its time

duration is chosen to be much larger than the duration of echoes from a single scatterer. The trans- mission characteristics of all intervening structures are assumed to be statistically homogeneous

and to result in negligible attenuation.

X

Gated Segment

Fig. 1. Geometry for spectrum analysis

measurements.

widths ( e.g . , 0.3 degree) and small fractional

range segments, L/R, that are of interest, the beam pattern over the gated segment can be expressed as a function of cross-sectional arguments

only: i.e ., F(re) = F(y,z). Also, the range, r, can be replaced by R + x. Thus, eq. (1) can be rewritten as

„-jwR/c , p'(co) = (jcoA/c)P(co)^ e J"''/''F(y,z) . (2)

2ttR

The backscatter from the gated tissue volume is characterized in terms of a scattering function,

S(a); x,y,z). This function relates the amplitude

of the incident pressure at a point (x,y,z) within

the volume of interest to the strength of the back- scattered spherical wave originating at that point. The backscattered wave is sensed by the transducer

which responds to the spatial average of the pressure distribution generated over its surface. The spatially averaged pressure received from each scattering element is proportional to F2(y,z) and

can be readily calculated by using the coordinate

system employed by O'Neil [9]. The total received pressure is then obtained by integration over the gated volume, v,^

p,^(co) = B(a,)yS(a3; x,y,z)F2(y,z)e-j2'^^/^dxdydz (3a)

^m

where B(u)) is

^-j2coR/c

B(aj) = (jwA/c)P(oj)^ (3b)

(2TrR)2

and the sub-index m indicates the m'-'' measurement.

As a first approximation for many tissues of interest, S(u); x,y,z) characterizes weak scattering of identical, randomly distributed, isotropic

scattering elements. Under these conditions it

is convenient to factor the scattering function

as follows

The received signals are analyzed in the fre- quency domain. The classic results obtained by

O'Neil [9] are applicable for the weakly focused

transducers used in this program. These results

show that, at a point Q in the focal zone, the in- cident wave is essentially planar and its pressure amplitude is given by

p-jkr

p' (oj) = jkA P{m)- F(r,e)

2TTr (1)

where k = u/c is the wave number; u and c are radian temporal frequency and propagation velocity,

respectively; P(a)) is the pressure amplitude at the transducer surface with area A. The function

F(r,e) describes the beam pattern at a constant

range from the transducer and is equal to 2Ji(k a sin e)/(k a sin e) where Ji(6) represents

a Bessel function of the first kind and first

order with argument g. It is useful to simplify this expression at the outset. By virtue of the narrow angular beamS(w; x,y,z) = H(a))N(x,y,z) (4)

Here H(aj) defines the reflectance characteristic

of a single scattering element while N(x,y,z)

describes their effective spatial concentration.

With eqs. (3) and (4), the total received pressure in the m^'^ measurement can be written as a Fourier transformation, with respect to axial range,

of the product of the gating function G(x) and a function characterizing the weighted concentration

of tissue elements; i.e.

p^(w) = B(a))H(w)J

G(x)|" 'N(x,y,z; (5)

F2(y,z)dydz e-j2(^x/c^^

The function G(x) describes the length of the range

gate and the range-weighting function ( e.g . , Ham112
ming) applied in the measurement. Denoting the Fourier Integral by Qfji(co), eq. (5) can be rewritten

as

p (w) = B(a))H(a))Q^((.

'^m m

(6)

It is important to notice the stochastic nature

of Qm(a)) resulting from the stochastic nature of

the tissue concentration function, N(x,y,z). Qualitatively, for equal, but non-overlapping tissue

volumes, Pm(u) can vary randomly from measurement

to measurement, as different tissue realizations

are illuminated with the ultrasonic beam. This

stochastic process can be meaningfully characterized in terms of the power spectrum, p, computed

by forming an ensemble average of the modulussquare of Pni(a)) -, i e .

,

<N(x,y,z)N(xi,yi,Zi)> = R.,(Ax,Ay,Az) (9)

where Ax = x-xj. Ay = y-yi, az = z-zi. For this case, substitution into eqs. (5) through (7) can

be carried out with considerable simplification.

The expected value of p, taken in the sense of an average over the ensemble of tissue realizations

becomes

<P> (10)

|B(aj)|: |H(w)|2y J J

Rg(Ax) Rp(Ay,Az)

P = 1 E |P (f^) M ' ^m

m=l

(7a)

(7b) m=l

In the present technique, the ensemble average

is computed from a series of observations of

|Pi,i(oj)[2 taken along adjacent, non-overlapping

beam headings within the examined tissue. The re- sulting function p then constitutes an estimate of

the "true" power spectrum, <p>. (The symbol <•> refers to ensemble averaging over all realizations

of the structure of interest.)

The statistical fluctuations associated with

estimates of <p> are of significant practical im- portance. For tissues characterized by a Gaussian-distributed concentration function and

a correlation volume much smaller than the sampling

volume, Vpi, Pni(a)) has a Gaussian distribution and

|Pni(u)p obeys Chi-square statistics. (Tissues

which possess many independent scattering centers

within Vm obey these statistics as well by virtue

of the law of large numbers.)

It follows from the properties of the Chi-square

distribution that independent measurements of

|P[ii(a))|2 exhibit significant variability; in fact,

at any value of u, the standard deviation, a, of

such measurements is equal to their mean value,

<p>. The relative fluctuations which persist after averaging M independent realizations of |Pu,(a))|2 can be assessed from the ratio

<P> ± o <P>

= 1 ± M" 18)

In spectral measurements, this degree of fluctuation is evidenced at each value of u producing a statistical "ripple" of the above magnitude about

the mean spectral shape. This result has been employed to select a value of M that is suitable

for clinical measurements as discussed below.

B. Statistically Stationary Architectures

If the concentration function, N(x,y,z), is a weakly stationary process, then its autocorrelation function can be expressed as

R^(Ax,Ay,Az) x ^-^^^^^/^ d(Ax)d(Ay)d(Az)

where Rq and Rp are the autocorrelation functions

of the gate function, G, and directivity function,

F^, respectively.

For a limiting case that is of practical in- terest here, the correlation volume defined by the system-related functions Rq and Rp is much larger

than that of the tissue function Rn. Equation

(10) can then be approximated as

<P> ^ |B(a))|2 |H(w)|2 Rg(0) Rp(0,0) T(a3) (11)

where T(aj) depends only on the tissue structure

and is given by

T(w) ^ J ff

Rf^(Ax,Ay,Az) d(Ay)d(Az (12)

^-j2a.Ax/c

C. Spatial Distribution

of Rayleigh Scat<-erers

The above discussions are applicable directly

to tissues which can be modelled as a set of ran- domly distributed, discrete Rayleigh scatterers:

i.e ., scatterers whose sizes are much smaller than the illumination wavelengths. We next treat the case where the number of Rayleigh scatterers within a unit volume is a Poisson process; i.e.,

K N(x,y,z) ^ 6(x-x.) 6(y-y.) 6(z-z.:

i = l

(13)

where 6 is the Dirac delta function and (xi,yi,z-j) are the random coordinates of the ith scatterer

which are uniformly distributed over the inspected

tissue volume. K is the number of scatterers per

unit volume and obeys Poisson statistics with para- meter <K>. It follows [10] that R^, the autocor- relation function of N, is

= <K> 6(Ax) 6(Ay) 6(Az) + <K>2 (14)

113
Using eq. (14) for in eq. (10), one obtains

<P> = |B(a))|2 |H(to)|2 <K>Rg(0)Rp(0,0) + (15)

<K>2 |G(a)) |2 / / Rj-(Ay,Az) d(Ay)d(Az)

where G(u)) is the Fourier transform of Rg(ax). The first term in eq. (15), proportional to the expected number of scatterers, is identified with non-coherent scattering. The second

term, proportional to the square of the ex- pected number of scatterers, is identified

with coherent scattering. The relative con- tributions of both components to the total mea- surement varies with frequency. The non- coherent spectral component is distributed over

the frequency domain, whereas the coherent com- ponent primarily contributes at zero frequency

providing that the power spectrum |G(u))|2 can

be adequately approximated as a Dirac delta function at the frequency origin.

In practice, non-coherent spectra predominate

in clinical observations. This occurs because

spectral observations are carried out at high

frequencies and a time-weighting function is used

to suppress the sidelobes of |G(a))|2. These sidelobes fall-off at a rate which is more rapid than

the a)"2 characteristic associated with a rectangular gating function.

Equation (15) can be used to address the topic

of spectral normalization. The non-coherent term

is proportional to |H(a3)|2 which for Rayleigh scatterers has an aj'+ dependence. However, other

system-related terms are also frequency-dependent.

To account for these factors, spectral data are normalized using calibration spectra obtained from

a flat, water-glass interface viewed at normal in- cidence and located at R + L/2. It can be shown

that this normalization removes the system-related

frequency dependence in the non-coherent component

of eq. (15) and that the normalized spectrum is indeed proportional to u'*. Experimental results verifying this conclusion are presented in a sub- sequent section.

These results and those of preceding sections

are applicable to a variety of tissue structures.

However, all tissues of interest do not fall within simple categories and further analysis is war- ranted to treat more complex tissue structures

and to investigate the most appropriate approaches

to data normalization. Such analyses are being

conducted as the clinical data base is expanded

and histologic preparations become available.

3. Spectrum Analysis System

The spectrum analysis techniques described above

have been implemented with an on-line clinical system. The system is integrated with a highresolution A- and B-scan instrument which is em- ployed routinely in ophthalmic examinations (fig.

2). The operation of the system is described

elsewhere [6] and is only briefly summarized here. The tissue segment to be analyzed is selected by

observing A- and B-scan displays in which the position of the moveable, system range gate is superimposed. These displays are also monitored to in- sure that the beam does not traverse the absorptive ocular lens and that the tissue segment to be analyzed lies within the transducer's focal zone. After the range gate has been placed over the desired tissue segment, processing is initiated.

First, the gated rf echo complex is multiplied by

a time-weighting function to suppress spectral side

lobes which would prevent accurate measurements of steeply rising or falling spectra. Then, the gated signals are applied to a scanning electronic

spectrum analyzer which computes the desired spec- trum comprised of 50 spectral elements occupying

adjacent 300-KHz frequency bands. An ensemble of these spectra are computed along

13 adjacent, non-overlapping beam headings and entered into an on-line averager. The spectral

ensemble is obtained by executing a slow sector

scan during which an optical encoder initiates a spectrum analysis computation each time the transELECTRONIC PULSER

T/R TIME-WEIGHTED SCANNING SPECTRUM

RANGE GATE —a» SPECTRUM SWITCH UNIT ANALYZER AVERAGER

SECTOR SCAN

ANALYSIS REGION

(1.5 X 4 0 mm )

A/B -SCAN

MONI TORS

STRI P CHART

RECORDER

Fig. 2. Configuration of spectrum analysis system.

114
ducer heading is incremented by one angular beam- width (0.3 degrees at 10 MHz). (In practice, 100 partly redundant spectra are averaged to improve

electronic signal-to-noise ratios.) Averaged

spectra are presented on a strip chart recorder

which also displays frequency and amplitude calibration signals for use in subsequent processing.

After each examination session, calibration

spectra are recorded from an optically flat glass

plate situated at each of the ranges used in tissue measurements. The calibration spectra and tissue spectra are subsequently digitized and entered into a computer for spectral normalization,

smoothing, regression analysis, and data cataloguing.Table 1 lists the salient system parameters

which influence the detail with which tissue char- acteristics such as |H([jj)|2 and T(aj) can be examined. As discussed below, the frequency coverage,

spectral resolution, and number of non-overlapping

beam positions are of central importance in tissue

studies.

Table 1. Nominal system parameters.

Frequency coverage 5 to 13 MHz

Spectral resolution

Gating function

Spectrum analyzer

Gated range segment

Lateral scan dimension

Beam width (10 MHz)

0.6 MHz

0.3 MHz

1. 5 mm

4 mm

0. 3 mm

Number of distinct beam positions 13

Dynamic range 30 to 35

The frequency coverage achievable in spectral measurements has been found to approximate the 20-dB system bandwidth as defined by glass plate

spectra. This coverage is nominally 5 to 13 MHz

for a broadband transducer with a 10 MHz resonant

frequency. Beyond this range, limited signal-tonoise ratios are encountered and spectral normalization can become inaccurate. The available fre- quency coverage determines the spectral characteristics of tissue elements with specific scale

sizes. Within the above frequency range, Rayleigh

scattering is encountered for spherical elements

whose diameters are less than 35 ym. As discussed

below, membranes, or periodic features, with axial dimensions larger than 100 pm will produce periodic spectra with at least one spectral cycle displayed over the achievable 8 MHz coverage. In ad- dition, tissue septa whose thicknesses are less

than 30 ym will exhibit monotonical ly rising

spectra.

Spectral resolution is determined by the 2-us

gate duration and the weighting function. These

variables have been chosen to achieve a 0.6 MHz resolution while the spectrum analyzer employs a 0.3 MHz filter bandwidth. The short gate duration

corresponds to a 1.5 mm tissue depth permitting

analysis within small ocular tumors and avoiding

significant signal weighting due to attenuation

within the gated echo complex.

The number of independent spectra which are ensemble averaged is an important factor in assessing the residual statistical fluctuation with

estimations of mean spectral shape and amplitude.

Usually, 13 spectra from non-overlapping beam positions are used to form the ensemble average.

For the conditions described with reference to eq.

(8), a statistical spectral "ripple" of approximately ± 1 dB is expected. While spectral fluc- tuations are often confined within this range, there are situations where significantly larger ex- cursions occur suggesting that the analyzed tissues exhibit relatively large correlation volumes. (Further analyses of these parameters in terms

of the accuracies of spectral slope and attenuation

estimations have been presented in a previous

publ ication [7] .

4. Representative Results

Before clinical deployment, the performance of

the spectrum analysis system and the applicability

of the theoretical approach was verified on a number of test targets. One type of test target was

a thin plastic membrane immersed in distilled water

and viewed at normal incidence. For this target,

N(x,y,z) is proportional to 6(x-Xq) - 6(x-Xq-D)

where D represents thickness and x^ locates the proximal membrane surface. From eq. (5) and (7), the calculated power spectrum, is proportional to sin (2TTfD/c) so that spectral minima will occur

at frequencies separated by an interval equal to c/2D. The observed spectrum, shown in figure 3, exhibits a scalloped shape in agreement with this result. The measured frequency interval between successive spectral minima is 3.6 MHz which cor- responds to a calculated thickness of 360 pm. This value is within 5 percent of the measured

membrane thickness.

Spectral data were also obtained for dilute

solutions of plastic microspheres with 25 ym diameters. These dilute solutions insure that single scattering from points is approximated over

the spectral measurement band. Moreover, it is reasonable to assume that their spatial distribution forms a Poisson process since the random position of each scatterer should be independent and uniformly distributed within the analyzed volume. Accordingly, measured spectra should be described

by eq. (15).

Figure 4 shows normalized spectra measured for

two microsphere concentrations. The spectral curves agree very closely with the u"* dependence

expected from the normalized, non-coherent spectral

component in eq. (15). In addition, a fourfold

change in microsphere concentration was found to produce a proportional 6-dB change in spectral

amplitude. This amplitude change is consistent

with non-coherent scattering, in which received

spectral power is proportional to the mean number

of scattering particles.

Clinical measurements have been carried out on

a wide variety of normal and diseased structures

in the eye and orbit. In vivo data on more than

200 cases have been acquired and digitally cata- logued as part of an on-going research effort. The following paragraphs review some of the observed

spectral features which relate directly to cases treated in the preceding discussions of analytic

and experimental results.

115
-20

-24

^ -28

u -32 Q

3

-36

-40

-44

-48

-5 2

-

Af = 3.6 MH z D = 360

J L J I I L J I L

5 10 FREQUENCY (MHz)

Fig. 3. Spectrum of echoes from plastic membrane.

Oi-

- - 5

-10

-20

MICROSPHERE SPECTRA

25 ^im DIAMETER

FULL CONCENTRATION

1.7 X 10^/cm

RAYLEIGH RESPONSE (f^*) ONE-QUARTER CONCENTRATION

0 43 X 10^ /cm^

0.42l_ J L

Fig. 4.

7 8 9 10 1 1 12 13 14 15 16 17 18 FREQUENCY (MHz)

Spectra obtained for two concentrations

of dilute microsphere suspensions.

Detached retinas, observed prior to the develop- ment of gross degenerative processes, constitute

thin membranes bounded, anteriorly, by vitreous

humor and, posteriorly, by fluid exudate. Spectra

obtained from these structures display a marked

scalloped appearance similar to that seen for the plastic membrane (fig. 3). This fact is demonstrated in figure 5 which shows clinical spectra

in decibels relative to a glass ^'late (dBr) ob- tained from three different cases of retinal de- tachments. Retinal thickness can be computed from

the frequency repetition interval of these spectra.

Using a nominal propagation velocity of 1.5 mm/ps

for the retina, the computed values in the illus116
Fig. 6. Clinical spectra obtained for vitreous hemorrahages (9 cases). Spectral amplitudes

have been off-set by indicated values.

117
trated cases are on the order of 190 ym and are consistent with expected retinal dimensions.

Vitreous hemorrhages have been studied exten- sively with the spectrum analysis system. In their

unorganized state, these hemorrhages contain ran- domly placed aggregations of hemorrhagic debris

dispersed in sections of the vitreous humor. Un- organized hemorrhages consistently produce spectra

whose amplitudes increase markedly with increasing

frequency as shown in figure 6. The rate of in- crease can sometimes be as rapid as the f"* charac- teristic associated with Rayleigh scattering:

this fact indicates scattering from a uniform

distribution of elements that are smaller than

35 ym. Spectral amplitudes are typically -70 dBr

near 5 MHz: these very low levels can often be exceeded by returns from isolated specular reflectors or, in the extreme, by the system noise level. At higher frequencies, the spectral amplitudes

produced by hemorrhagic debris are significantly

larger and exceed these background levels. Occasionally, other spectral shapes have been observed within an examined vitreous hemorrhage.

They indicate a possible high-density packing or organization of the hemorrhagic debris. The presence of membranes has also been found to af- fect the observed spectral shape. For example,

figure 7 shows the scalloped spectra received from

a range-gated volume which contained both hemor- rhagic debris and a thickened intravitreal

membrane.

5. Conclusion

The analysis outlined in the preceding sections

has proven extremely useful in designing the spec- trum analysis system and in selecting system para- meters, such as gate dimensions, for clinical ap- plication. It has also formed a constructive

framework for interpreting in vivo data, especially for detached retinas, vitreous hemorrhages, and intra-vitreal dispersions of cholesterol aggregations. The analysis is being extended to accommodate

more complex tissue architectures. This effort

is proceeding using clinically measured spectra

and subsequent histologic preparations when available. Of particular interest are intra-ocular

tumors such as malignant melanomas and metastatic

carcinomas.

Other topics under investigation include the use of spectral data to estimate tissue attenuation characteristics. Presently, attenuation

estimates are formed from ratios of power spectra

measured at sequential range sites separated by

aR. If the examined tissue architecture satisfies

certain conditions ( e.g . , statistical homogeneity),

then such ratios describe the attenuation ex- perienced within AR. Spectral data indicate that

this approach is appropriate for some tissues

( e.g . , orbital fat) but is not applicable to other

tissues ( e.g . , heterogeneous tumors). In these latter cases, spectral ratios might serve as a useful index of statistical homogeneity.

As the clinical data base is expanded, these investigations can proceed toward the ultimate

goal of applying spectrum analysis techniques to supplement conventional A- and B-scan ultrasonography.

Acknowledgments

The authors wish to acknowledge the collaboration of D. Jackson Coleman and Louise Franzen in the clinical aspects of this work. They also wish

to thank Angel Rosado for his assistance in data processi ng. Portions of this work were supported by Public

Health Service Grants EY-0I212-04 and EY-01218-04

from the National Eye Institute.

-44 -

m

u -52

Q

K -56

^

-60

<

-64

-68

^-72

CO -76 PATIENT 3943

10

FREQUENCY (MHz)

15

Fig. 7. Clinical spectrum obtained for a vitreous hemorrhage and associated intravitreal membrane.

118
References

[1] Waag, R. , Lerner, R. , and Gramiak, R.

,

Swept-Frequency Ultrasonic Determination of Tissue Macrostructure , in Ultrasonic Tissue

Characterization , M. Linzer, ed. National Bureau of Standards Spec. Publ . 453, pp. 213-230 (U.S. Government Printing Office,

Washington, D.C. , 1976). •

[2] Lele, P. and Namery, J., A Computer-Based

Ultrasonic System for the Detection and Mapping of Myocardial Infarcts, in Proceedings of the San Diego Biomedical Symp . 13 , 121-132 (1974).

[3] Sigelmann, R. and Reid, J., Analysis and measurement of ultrasound backscattering

from an ensemble of scatterers excited by

sine-wave bursts, J. Acoust. Soc. Am . 5^, 1351-1355 (1973).

[4] Lizzi, F. L., St. Louis, L. , and Coleman,

D. J., Applications of spectral analysis in medical ultrasonography. U ltrasonics 14 (2), 77-80 (1976).

[5] Lizzi, F. , Burt, W. , and Coleman, D. J., Effects of ocular structures on the propagation of ultrasound in the eye. Arch. Ophthalmol . 84, 635-640 (1970).

[6] Lizzi, F., Laviola, M. , and Coleman, D. J., Ultrasonic Tissue Characterization Using

Spectrum Analysis, in Proceedings of SPIE/SPSE

Conference on Application of Optical In - strumentation in Medicine V , Society of Photo-Optical Instrumentation Engineers,

Palos Verdes Estates, California, pp. 322- 328 (1976).

[7] Lizzi, F. , Laviola, M., and Coleman, D. J., Tissue Signature Characterization Utilizing

Frequency Domain Analysis, in Proceedings of

IEEE Ultrasonics Symposium 1976 , Institute

of Electrical and Electronics Engineers, Inc., New York, pp. 714-719 (1976).

[8] Lizzi, F. and Elbaum, M. , Ultrasonic Spectrum

Analysis Techniques in Medical Ultrasound,

Riverside Research Institute Technical Re- port, Riverside Research Institute, New York,

N.Y. (in preparation).

[9] O'Neil, H., The theory of focussing radiators,

J. Acoust. Soc. Am . 21_, 516-526 (1949).

[10] Pratt, W. Laser Communications Systems , pp. 255-262 (John Wiley and Sons, New York,

1969).

119

Reprinted from Ultrasonic Tissue Characterization II, M. Linzer, ed. , National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C., 1979).

TISSUE CHARACTERIZATION IN VIVO BY DIFFERENTIAL ATTENUATION MEASUREMENTS

Salavatore Levi and Jose Keuwez

Ultrasound Lab and F.R.E.S.E.R.H. , Hopital Brugmann

Universite Libre de Bruxelles, Brussels, Belgium

A practical ultrasound method has been applied for the differentiation in vivo

of pelvic tumors. This method has the advantage of being applicable during usual ultrasonic examination and does not require information about the tissues involved,

nor the surrounding tissues.

The method is based upon the fact that the ultrasonic attenuation increases with

frequency; the comparison of the echoes from the posterior and anterior boundaries

of the tumor leads to a coefficient of differential attenuation. This coefficient

has been determined in examinations of 95 gynecological patients; the organs and tumors explored were normal uteri, leiomyomas and ovarian cysts. The values of the coefficient of differential attenuation obtained for these three categories of tissue are sufficiently separated, which enables us to make a differentiation.

Key words: Characterization; differential attenuation; tumor; ultrasound.

1. Introduction

Ultrasound has been shown to be effective in the diagnosis of tumors and is generally capable

of differentiating between solid and liquid components. The current acoustic methods, which

have been applied for a number of years, give de- pendable results in 93 percent of the leiomyoma

cases and in 84 percent of the cases involving

ovarian cysts [1 ]^

Ultrasonic imaging has reached a high level of accuracy, especially with the application of "grey-scale" techniques. However, other aspects

of diagnostic ultrasound have not yet reached

their full potential. More precise information

on the viscoelastic properties of tissues, espe- cially those of tumors, should be the next step

in research on diagnostic methods. Quantitative studies should produce more meaningful numerical data regarding the various types

of tumors investigated. Such data will be rep- resentative of the acoustical properties of the tissues and complete the subjective data produced

by imaging. One of the most important of these properties

is the attenuation of sound. The loss in acoustic

intensity in travelling through the biological

tissues is caused mainly by absorption and scattering. These causes may be grouped under the

term "attenuation". It is difficult to assess the individual contribution of these mechanisms (absorption, scattering, ...) and it is therefore

quite preferable to confine oneself to examining

attenuation as a whole.

The importance of the various mechanisms is de- pendent on the wave frequency; therefore the at-

^Figures in brackets indicate literature

references at the end of this paper.

tenuation is a function of frequency. The attenuation is a characteristic of a tissue, but generally it is quite impossible to measure it in vivo

without invasive techniques. We chose the deter- mination of the variation of the attenuation with

frequency as a basis for the differentiation of tissues [2-4]. A similar concept has been pro- posed by Kossoff [5,6], but no results have been published. For a good understanding, we envisioned a model similar to that published by Hill [7].

2. Model and Analysis

The following analysis is approximate and does not take into account various mechanisms

which could be important. The objective of this

analysis is to give an idea of the relation be- tween the ultrasonic properties of tissues under

investigation and the coefficient of differential

attenuation which will be defined below. Generally any mass^ consists of several layers

of tissue which have their own properties; for example, the uterine fibroma in which a layer of

normal muscle surrounds pathological tissues. The model (fig. 1) has been constructed in order

to represent the different layers of the region under investigation and of the mass. Each layer

is characterized by an acoustic absorption coefficient, and each interface by a back-scattering

cross-section (a), (o is used here to take account

of all the mechanisms which contribute to the loss of energy at this interface.)

These layers are separated into two sets; p layers between the transducer and the mass, the mass being constituted of r - p = n layers. In each layer, one of the important mechanisms in

2ln this paper, the term "mass" will include

the normal uterus, leiomyoma, and cyst.

121
MASS

ai

V 1

p layers n layers

Fig. 1. Model of the different layers of the region under investigation.

which acoustic energy is degraded as heat by in- ternal friction of viscosity is the absorption.

This loss of acoustic energy follows the relation

given by the equation:

A = Aq exp(-ax) (1)

where a is the amplitude absorption coefficient,

Aq and A are, respectively, the wave amplitude at some reference point and the amplitude at a fur- ther distance, x, from that reference point.

Let us consider a sound wave propagating from

the source S to the point R (fig. 1). The amplitude of that wave at R is given by

A(R,v) = Ao(v) o(R,v) exp(-ai(v)<Si) (2)

. . . exp(-ap(v)6p)

where v is the wave frequency, a-j and s-j are, re- spectively, the amplitude absorption coefficient

and the thickness of the layer i; a{\>) is a factor

which describes the decrease of amplitude at the several interfaces. The amplitude, SA, of the reflected wave coming from R on to the transducer

is related as follows:

SA(R,v) = AqIv) a(R,v) exp(-2 ^ cx^^i) (3)

i = l

If (vi,v2) are two different frequencies, let us consider the ratio of the amplitudes SA(R,vi) and SA(R,V2); according to eq. (3), this ratio is given

by the following equation:

SA(P,Vi) Ao(vi) o(R,vi)

In = In + In SA(R,V2) Ao{v2) a(R,V2)

r

- 2 ^ (ai(vi)-ai(v2))

i = l

Similarly, (see fig. 1)

SA(P,Vi) Ao(vi) o(P,Vi)

In = In + In SA(P,V2) Ao(V2) ct(P,v2)

2 (ai (vi )-aT (v2)

)

i=l

(4)

(5)

Now we introduce J as the difference of eqs. (4) and (5).

SA(R,vi) SA(P,Vi)

J = In In SA(P,V2)

a(R,V2)

J = In In a(P,Vi) o(P,V2)

2 J2 (ai (vi (V2) )6i i=p+l

(6)

(7)

Equation (6) can be written in the following form:

(n(vi) - n(v2)) - (a(vi) - a(v2))

2d

= Af) - Aa where

a^6] = ad (d = thickness of the mass) (10) i=p+l

In

t(R,n a(P,v] 2dn(v) (IT)

Examining eq. (8), we see that J/2d depends only

on the ultrasonic properties of the layers com- prised between P and R; J/2d is a characteristic

of the mass and tells us about the variation of attenuation with frequency.

Let us remark that, for the calculation of

the value of J, we only need the knowledge of four amplitudes, and no information is required

about the tissues involved nor the surrounding

tissues.

3. Materials and Methods

We have defined eq. (6)

J = In SA(R,Vi)

SA(R,V2;

In SA(P,Vi;

SA(P,V2;

(12)

which is the basic equation for characterization

based upon differential attenuation. For the cal- culation of J it is necessary to measure the amplitudes of the waves reflected by the anterior

and posterior boundaries of the mass. This mea- surement must be performed at two frequencies

(vi and V2). Theoretically, it is possible to undertake these measurements with a single pulse

[6], however, we have chosen to adapt eq. (10) by

considering that these amplitudes are for waves generated by two relatively narrow band (9.5 MHz)

transducers

.

These amplitudes have been measured with the ultrasonic equipment "Kretz Combison I" [2-4]. For each amplitude measurement, all the settings

were identical except that of the master gain.

This last one was adequately adjusted to obtain an amplitude of given level on the A-Scope for the echo of interest (I). The corresponding reading

122
L(I,v) (in dB) was used in the following equation

based on eq. (12)

Table 1. Statistical analysis.

2d L(R,Vi) - L(R,V2) - (L(P,Vi) - L(P,V2)) (13)

where d = dimension of the mass. We call y the coefficient of differential attenuation. This at- tenuation coefficient has been determined in examiing 95 gynecological patients. The masses under in- vestigation were the normal uterus, leiomyoma and

cyst. The nominal frequencies were 2 MHz and 4 MHz.

4. Results -

At present, twelve cases have been labeled as normal uterus, and 34 other cases have been classified as leiomyoma or cyst after surgery. We plotted the values of the differential attenuation

coefficient, y, versus the dimension, d, of the mass (fig. 2). The plot shows that y is not in- fluenced by d and that the y belonging to the three categories of tissues (normal uterus, leiomyoma and cyst) are quite characteristic. Some cysts have shown an abnormally high differential

attenuation for masses with liquid content; we also obtained negative values for some cysts, however,

this peculiarity has been reported and explained

[8]. The values of y for the normal uterus are higher than those obtained for the leiomyoma, which

is in agreement with the ultrasonic properties of these tissues and with previous results [4]. The results of the statistical analysis are shown

in table 1.

y (dB/cm)

1-8.

1.6.

1.4.

1.2.

1.0.

0.8.

0.6.

0.4.

0.2.

0.0

-0.2

+ normal uterus

0 leiomyoma

X cyst

O OOCP

d (cm)

12 15

Fig. 2. Plot of the values of the differential

attenuation coefficient, y, versus the dimension, d, of the mass.

Organ No. Mean y(db/cm)

S.D.

Normal uterus Leiomyoma

Cyst

1222

10

1.39 0.57

0.13

0.27

0.22 0.20

The absolute values are not interesting by them- selves because y is also depending on the instrumentation.

5. Comments and Discussion

If in vitro it is possible to imagine trans- mission methods, it is more difficult in vivo

where generally only reflections methods are ap- plicable. Unfortunately, it is not enough to know

the amplitude of the reflected signals to tell something about the tissues involved. It is also necessary to know the properties and the orientation of the interfaces which have partially re- flected the sound waves.

When working in vitro , the samples can generally be chosen, cut and positioned as desired. In

vi vo , many constraints have to be taken into ac- count. Theoretically our method avoids some of them; for instance no information concerning the surrounding tissues is required. However, difficulties due to the orientation of the interfaces

remain. Sometimes it was difficult to obtain a posterior echo because of the orientation of the tumor with respect to the abdominal wall. The orientation is also affected by the cardiorespiratory movements. Besides the difficulties

of measurement, one should be aware that the re- fraction properties are frequency dependent. This could cause important differences in amplitude

when using two frequencies vj and V2 at oblique

incidence. The dispersion of our results can in part be explained by this last discussion as well

as by considering effects due to the beam geometry.

We characterized our transducers [4]; however

this characterization was made in a nonattenuating

medium (water). In our experiments the sound was propagating into an inhomogeneous and attenuating

medium (for instance the abdominal wall) which

could strongly influence the beam geometry.

Therefore it is illusory to pursue this discussion

based on our transducer characterization. How- ever one must be aware that the beam geometry can dominate the results. That is probably the reason

we did not obtain coherent results when working

with other transducers. This method, as it is ap- plied, considerably extends the duration of the examination, which is generally performed with a full bladder. Under these circumstances it is difficult for the patient to lie still. Technical improvements are necessary.

6. Conclusion

The characterization of tissues based upon the variation of attenuation with frequency seems to be suitable and helpful in cases where scans alone

do not permit an accurate diagnosis. However, we would like to emphasize that it was not always

possible to determine the coefficient of differential attenuation, for several reasons developed

123
in the previous paragraph. The results reported

in this paper are those obtained for frequencies

of 4 and 2 MHz; however, we also determined this coefficient for frequencies of 2 and 1 MHz. The results obtained in this last case were incoherent

and the overlap between the three categories of tumors investigated was important. The various inconveniences described above

should be resolved by a better choice of trans- ducers and the way of determining the various

amplitudes required for the computation of the coefficient of differential attenuation.

Acknowledgments

We wish to thank Professor R. C. Eggleton

(Indianapolis Center for Advanced Research,

Indianapolis, Indiana) for helpful suggestions

in preparing this paper, and Mrs. J. Drake

for her secretarial assistance.

References

[1] Levi, S. and Delval, R., Value of ultrasonic

diagnosis of gynecological tumors in 370 surgical cases. Acta Qbstet Gynecol Scand 55 261-266 (1976).

[2]

[3]

in Abstracts of the 2nd World Congress on

Ul trasonics in Medicine, p. 81 (Junge und Sohn, Muchen, 1975).

[4] Levi, S. and Keuwez, J., An Attempt to Find

a Differential Attenuation Coefficient for Ultrasonic Diagnosis of Pelvic Tumors in Vivo , in Ultrasound in Medicine , Vol. 3B,

p. 1989 (Plenum Press, New York, 1977).

[5] Kossoff, G., Display techniques in ultrasound

pulse echo investigations; a review, J. Clin . Ultrasound 2, 61 (1974).

[6] Kossoff, G., Reflection Techniques for Meas- urements of Attenuation and Velocity, in Ultrasonic Tissue Characterization , M. Linzer,

ed., National Bureau of Standards Spec. Publ

.

453, pp. 135-139 (U.S. Government Printing

Office, Washington, D.C., 1976).

[7] Hill, C. R., Echoes from Human Tissues, in Ultrasonics International '75 Conference

Proceedings , 24-26 March 1975, Imperial

College, London, pp. 20-22 (Guildford IPC Science and Technology Press Ltd., London,

1975).

Levi, S., Essai d'analyse quantitative des [8] echogrammes de tumeurs pelviennes; Journees

d^Etudes sur les Ultrasons Appliques a la Medicine, Nancy (1974), Resume des Communications, p. 40.

Levi, S., An Attempt to Differentiate Pelvic Tumors in Vivo by Attenuation Measurements,

LeCroissette, D. H. and Heyser, R. C,

Attenuation and Velocity Measurements in Tissue Using Time Delay Spectrometry, in Ultrasonic Tissue Characterization , M. Linzer,

ed., National Bureau of Standards Spec. Publ. 453, pp. 81-95 (U.S. Government Printing

Office, Washington, D.C., 1976).

124
Reprinted from Ultrasonic Tissue Characterization II, M. Linzer, ed.. National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C. , 1979).

STATISTICAL ESTIMATION OF THE ACOUSTIC ATTENUATION COEFFICIENT SLOPE

FOR LIVER TISSUE FROM REFLECTED ULTRASONIC SIGNALS

Roman Kuc,^ Mischa Schwartz, ^ Nathaniel Finby,^ and Frank Dain^

^Department of Electrical Engineering and Computer Science

Columbia University

New York, New York 10027, U.S.A.

^Department of Radiology

St. Luke's Hospital Center New York, New York 10027, U.S.A.

The acoustic attenuation coefficient measured in dB/cm is known to increase linearly with frequency for liver tissue. The slope of this linear function, denoted by b, has been shown by other investigators to be an indicator of tissue state. 6 is usually measured from the change in the log spectrum experienced by an acoustic pulse when

it is transmitted through the tissue. This paper presents research in estimating 6 from the reflected signals which are currently used in the clinical environment to generate diagnostic images. The reflected signals from internal tissue structures

(in liver - the vascular and biliary systems) are distorted by the irregular reflector shapes. By modeling the roughness of the typical acoustic reflector, the distribution of the received spectra can be derived and the 95 percent confidence limits

for the measured B can be calculated. The confidence limits are presented in terms

of the tissue size and average reflector density. Experimental results using the reflected signals from in v itro refrigerated and formalin-fixed liver sections are presented.

Key words: Computer processing; estimation theory; liver attenuation; spectral

analysis; statistical modeling; ultrasonic tissue characterization.

1. Introduction

As an acoustic pulse propagates through liver

tissue it experiences a frequency dependent attenuation. Pauly and Schwan [l]i observed that the acoustic attenuation was a linear function of fre- quency and postulated that this behavior was primarily the result of macromolecular relaxation pro- cesses. Lele Gt_ aj_. [2] confirmed the linear fre- quency dependence of the acoustic attenuation and

in addition experimentally demonstrated that the slope of the linear dependence increased for necrotized tissue. Lele's experiments were performed by

transmitting an acoustic pulse of known shape

through a thin liver section and observing the change in the log power spectrum as the pulse propagated through the tissue. In this paper we discuss

our work in estimating the slope of the linear fre- quency dependent attenuation, which we denote by the coefficient B, from the reflected acoustic

signals, typical of those currently used in the clinical environment to generate the acoustic

images. The reflections observed from liver tissue are caused primarily by the vascular and biliary sys-

^Figures in brackets indicate literature

references at the end of this paper.

tems that permeate the liver volume. Because the typical reflector encountered within the liver is neither plane nor normally incident to the inci- dent pulse, the log spectra of the reflected signals are distorted. In this paper we account for

the distortion caused by the irregularly shaped

reflector by modeling the reflector as a random

linear filter having an impulse response which is

a sample function from a zero mean, white Gaussian

process. From this assumed model we can derive

the distribution of the observed sample spectrum.

Using this distribution we can calculate confidence

intervals for the resulting estimates of e. Finally, we predict the sensitivity of the estimator on the tissue thickness, L, by assuming that the liver

tissue has a reflector density y reflectors per cm. Experimental results using in vitro refrigerated

and fixed liver tissue specimens will be compared

to the analytically predicted performance.

2. Acoustic Attenuation of Liver Tissue

We first describe the experimental procedure

that we use to measure g from transmitted pulses.

This is used to verify the reflection measurements.

The power spectrum of the incident pulse, denoted

by Sx(f) in figure 1, is found by reflecting the pulse from a plane, normally incident reflector

125
LIVER d

Power Spectrum

dB

The average values of 6 that we obtained for in vitro refrigerated and fixed liver specimens are shown in figure 1. These values agree with those

found by other researchers [1,2]. The transmission technique works well when thin, parallel cut sections of tissue are used. When large hetero- geneous tissue specimens, or tissue specimens

which have irregular shapes are used, the propagating pulse becomes distorted producing artifacts

in the measurements [3,4].

We will extend this technique of measuring 6 to signals reflected from tissue structures by sub- tracting the log spectra of signals from two re- flectors within the tissue. But because of the distortion to the spectra caused by the irregular

reflectors the observed spectral difference will

be a distorted linear function. The coefficient 6 will be estimated by fitting a straight line to the spectral difference and dividing by the round-trip

distance between the reflector locations. In order

to find a suitable estimation technique and the confidence intervals for the resulting estimate we

will derive the distribution of the distortion to the log spectrum in the next section.

3. Reflector Model

FIXED LIVER

(e = 1.20 dB/cm-MHz) REFRIGERATED LIVER

(e = 0.63 dB/cm-MHz)

f (MHz)

Fig. 1. Transmission experimental configuration

results. An acoustic pulse propagates

through liver sample having thickness d,

is reflected by plane, normally incident

reflector and propagates through sample

a second time. The liver acts like a low pass filter, attenuating the high fre- quencies in the power spectrum. The dif- ference between the power spectra is found

to be linear with a slope which is an in- dicator of tissue state. The parameter 6 is the observed slope divided of twice the tissue thickness.

with no tissue in the acoustic path. The power spectrum of the pulse transmitted through the tissue of thickness d back to the transducer is de- noted by SY(f). The effect of the tissue acoustic

attenuation can be found by taking the log spectral

difference (in dB) of the two spectra. For a line- arly frequency dependent acoustic attenuation ibhis will be equal to

10 logS„(f) - logs (f) = 2 3df (1)

The value of B, in units of dB/cm-MHz, for a given

tissue can be measured by dividing the observed

slope of the log spectral difference by the acoustic path length through the tissue. For reflected

signals the acoustic path length is equal to twice

the tissue thickness.

We propose to model the irregular reflector as

a random linear filter with an impulse response, denoted by r(n) for n = 1, 2, KTj, which is sample function from a zero mean, white Gaussian

process. The probability density function (p) of

r(n) is then given by

p(r(n)) =

1 expr2(n]

(2)

For a white Gaussian process, the values of r(n) and r(m) for sampling times n m are independent.

This appears to be a reasonable assumption in this work, considering the irregularity of the reflecting vascular structures [5]. This is verified by the experimental results to be described later.

If Sx(f) is the power spectrum of the acoustic

pulse incident to the reflector having the impulse response r(n), then the power spectrum of the re- flected signal, SR(f), can be written as

SR(f) = |R(f)|2Sx(f) (3)

where |R(f)|2 is the power transfer function of the reflector [6]. We will estimate 6 from the log spectral difference. The logarithm (in units of dB) of eq. (3) is equal to

10 logSj^(f) = 10 logS^(f) + 10 log |R(f)|2

= 10 logS^(f) + n(f)

(4)

(5)

The last equation indicates that the effect of

an irregular reflector is an additive distortion to the log spectrum of the incident pulse at the re- flector location. Furthermore, since the reflector

impulse response is assumed to be zero mean, white

Gaussian, it can be shown [6] that the random

variables

iR{fi)r (6)

126
are mutually independent and have an exponential

distribution (the chi-square distribution with two degrees of freedom), at frequencies f^ which are separated by the fundamental frequency, F = l/KIg.

Since we are seeking the distribution of the distortion in the log spectral domain (in dB) we

set

n. = 10 logC. = 10 log |R(f.: (7)

Using the relation for the pdf of a transformed

random variable [7,8] the pdf of the distortion to the log spectrum n-,- is found to be equal to

p(n ) = _

^ 4.34 a^T

exp

r s

"i 4.34

n .

"

1 .4.34

a2T

r s

(8)

for '1 This distribution is shown in figure 2a. If we let h = In a^Ts, then a^Tj = e^ can then be written

P(n^.) 4.34

exp

n

1 4.34

- h 4.34

This last result shows that the effect

Eq. (8)

(9)

the vari- ance of the reflector impulse response Oy on the distribution of the log spectral distortion is only

a shift by an amount h. We shall now describe the technique we have de- veloped to partition the total reflected signal from a liver tissue into segments which are used for calculating the sample spectra of the returns

from the irregular reflectors.

4. Processing of Reflected Data

An acoustic pulse having an arbitrary power spectrum Sx(f) propagates into a tissue medium

and reflections due to changes in tissue acoustic

impedance are detected by the transducer. A typical reflected signal denoted by y(n), is shown in figure 3. The envelope of y(n) is calculated by

rectifying the sample values and low pass filtering with a digital nonrecursive filter. The envelope is observed to contain a series of N maxima

which have random amplitudes and occurrence times.

We assume that the occurrence of a maximum, or

peak, in the reflected signal envelope indicates

the presence of an irregular reflector. This is the same assumption used in the equipment producing sonograms in the clinical environment. The

time series is divided into N nonoverl appi ng data segments corresponding to the signals returned

from the individual reflectors.

The shape of the reflected signal envelope sug- gests a way of segmenting the reflected data. For

our reflected signal analysis the data was segmented about the peaks in the envelope using the locations of the adjacent minima to delimit the segment. Each segment is then assumed to represent

the return from an irregular reflector, with the position of the envelope peak in the total re- flected signal defined as the reflector location

within the tissue. This procedure produces a set

noi se

P(4>i) 4.34

I exp

'I'i exp 8.68

N^N(0,ai)

For the emitted

reflected signal

(b)

Fig. 2. Reflection experimental configuration and procedure. An acoustic pulse is emitted

and the reflection from the liver tissue

parenchyma are detected,

signal shown, a typical

contains a series of peaks which have ran- dom amplitudes and occurrence times. These

are most evident in the envelope. The received signal is divided into segments

delimited by the envelope mimma. The power spectra are calculated and e is estimated from the spectral differences

using least squares.

of nonoverlapping data segments which are assumed

to be statistically independent.

The data segment corresponding to the k^h re- flector will be denoted by yk(n), n = 1,2, . . . jM^Ts- The sample power spectrum, denoted by S|^(f), is calculated from y|<(n) by using the squares of the cosine and sine transforms given by

T l/'Vs

.(f) = — 11 E y(n)cos2TTfn

k > \n=l

(10)

X] y(n)sin 2iTfn n=l

127
Because of the symmetry of the power spectrum it suffices to consider the positive frequencies only.

In a manner similar to the transmission experi- ment we will calculate the differences between the sample spectra to estimate the value for b. For N segments there are N/2 independent spectral differences as shown in figure 3. From each observed

spectral difference we will estimate a value for 6, denoted by 6k foi" the kth spectral difference.

The estimate for 6 using the entire reflected signal will be taken as the average of these individual estimates. A technique for pairing the seg- ments to minimize the estimator variance will be

discussed later. The power spectrum of the incident pulse has significant energy only in a band of frequencies,

from fL (for lower) to fy ( for upper). It is in this usable range that the log power spectral dif- ference given in eq. (1) will be approximately

linear. Outside this range noise effects cause random deviations. The set of frequencies f^ separated by the fundamental frequency spacing

are confined to be within this usable range, i.e..

(11)

LIVER

Emitted signal

Reflected

signal

Envelope

Segments

Set of

log spectral

di fferences

(b)

Fig. 3. Probability density functions. With the rough boundaries modeled as linear filters

with random zero-mean Gaussian impulse responses, the values of the power spec- trum at the harmonic frequencies are independent and distributed as the function shown in (a). The values of the power spectral difference at the harmonic

frequencies are also independent and dis- tributed as the function shown in (b).

In the analysis we shall assume that there are m frequencies within the usable range, with fj de- fined as the smallest.

5. Distribution of the Log

Spectral Difference

Now let us consider the log spectral difference

between the returns from two irregular reflectors,

i and j (a<j), separated by a distance d^j. If the corresponding power spectra of the reflected signal are denoted by S|^(f) and Sj(f), then their log spectral difference in dB at the harmonic frequencies

is equal to

z. = 10 logS^(f.) - 10 logSj.(f.)

= 10 logs (f ) - 10 logSy (f.

+ n^(fi) - n (f.; (12)

for i = 1 , 2, . . . , m

where ^X^ (f), k = n, j, is the power spectrum of

the propagating pulse at the k^h reflector. For a tissue with a linearly increasing attenuation with

frequency, the difference between the propagating

pulse log spectra is the same as the transmission

experiment results given in eq. (1). In our case,

it is equal to

10 logS„ (f.)

for i = 1 , 2

,

10 logS^ (f^) (13)

If the difference of the spectral distortions at

the harmonic frequencies is defined as

^i = "£(^) n.(f.) = n. „ - n. .

f (MHz) then eq. (12) can be written as

z. = 23d^jf . . s.

for i = 1 , 2,

(14)

(15)

In words, this last result states that the log

spectral difference between two reflected signals

at the harmonic frequencies is a distorted linear

function of frequency with a slope equal to the value of 6, the coefficient to be estimated, and

the round-trip distance between the reflectors.

128
The distortion enters as an additive noise term. Since e-j is the difference of random variables

which are independent and identically distributed

(iid) at the harmonic frequencies, ei is also iid and the variances are equal at the harmonic fre- quencies. Therefore, we can2drop the i subscript

a^d denote the variance by a^. We can show that

oe is independent of the individual reflector variances and is equal to 62 (dB)^ [7]. Therefore, the distortions to the straight line calculated by

using the log spectra from any two reflectors will have the same variance as the reflectors are spaced

farther apart (larger d^j) the slope of the log

spectral difference will increase. But since the statistical roughness is assumed to be constant for

all reflectors, the distortions should remain the

same. We shall use this fact later in how we pair

segments to calculate the spectral difference.

Since the attenuation coefficient g affects only

the slope in eq. (15), the mean value of the distortion e-j can be eliminated by translating the

axes. This can be ac^compl i shed by destining new variables Z-j = z-j - z and F.j = f-j - f where

and

i = l

(16a)

(16b)

The statistical model with zero mean distortion

and centered frequency axis can be written as

N' differences from which to estimate 6, where

N' 2 N/2. The statistical model using the entire

reflected signal can be written

Z., = 23d, F, +

^•k (20)

for ik

1, 2,

1, 2,

. , m

. , N' <

where Zj|^ is the observed value of the k^h log

spectral difference (after the mean value is sub- tracted) at frequency F-j using signals from re- flectors spaced d)^ apart.

6. Derivation of Maximum Likelihood

Estimator for 6

The results of the previous section indicated

that the additive distortions to the log spectral

difference are closely approximated by independent

and identically distributed Gaussian random vari- ables with mean zero and variance a^. Under these conditions the maximum likelihood

estimate of g, denoted by BmL' is found to be equal to

N'

k=l k^k

^ML N'

k=l

(21)

where

for i = 1 , 2, m.

(17)

The pdf of the additive noise term with zero mean can be shown [7] to be equal to

1

1 4.34

*i + e

(18)

1 i=l

^ (22)

2d

i = l

is the maximum likelihood estimate of g using only

the information in the kth spectral difference.

It can be shown that this estimator is efficient,

i.e ., it has the smallest variance of any unbiased

estimator [7]. The variance of the resulting

estimator can be shown to be equal to

We plot p(4>-j) in figure 2b. For comparison we also s^ow the Gaussian pdf having mean 0 and variance Oj. = 62, in dashed lines. Because of their

similarity, we will approximate ifi-j by a Gaussian

random variable having mean 0 and variance a^, i.e .. i.e..

Var hi] =

k=l

mz

i = l

(23)

For notational convenience let us define S as

1 ^"^l

P(<f'-i) = — e

^

^ V2tt a

e

(19)

S =

i = l

(24)

The statistical model given by eq. (17) de- scribes the log spectral difference between 2 re- flectors separated by distance di^. The entire

reflected signal contains H segments from which we

can calculate N/2 independent log spectral differences. We will show later that depending on how

the segments are paired it may be desirable to use

The estimator variance given in eq. be written as

(21) can then

Var hi] - N' 4r d2

k=l

'

(25)

129
We want to minimize the estimator variance by

properly selecting the segments used in calculating

the spectral difference. If adjacent peaks are chosen, all the du's will be small and the variance

will be large. Physically, this occurs because the acoustic attenuation doesn't affect the signal

significantly for small tissue distances while the irregular boundary effects are large. If we take segments far apart so that the effect of acoustic

attenuation is more apparent, the number of spectral differences N' becomes smaller. We will find

the optimum separation by considering a simple

tissue model

.

For heuristic purposes let us consider a statistically homogeneous tissue L cm long and having a reflector density equal to y reflectors per cm. The average spacing between reflectors is 1/p and

the average number of peaks in the reflected signal

is N = yL. If the segments to be used in calculating the log spectral difference are chosen such that the distances between them are constant and

equal to d^ = n/y, N/2 5 n f N-1, the number of in- dependent differences that can be formed is equal

to N' = N-n. The minimum variance can be shown to occur for n = 2N/3. Then from eq. (25) we find the minimum variance to be

Var

16

27 ^

(26)

The ED denotes equal d^istance separations between

reflectors. To relate this to tissue size we sub- stitute N = yL to get

VarFLj . L EDJmin

27

(27)

Recalling that yL = N we can write eq. (27) as

Varje^J . = L EDJmin — N.| 2 27 ^ (28)

This shows that in addition to decreasing as 1/N, the variance also decreases as l/L^. This demonstrates quantitatively the intuitive result that

for larger tissues, the acoustic attenuation be- comes increasingly discernible relative to the boundary distortion.

^

7. Confidence Intervals for the Estimator

In the previous section we derived the variance of the ED estimator as a function of tissue

size and reflector density. For Gaussian random

variables, the 95 percent confidence interval is defined as an interval 1.96 times the square root

of the variance about the estimate of the parameter. From eq. (27) the confidence interval

width is given by

\ „1/2l3/2

(29)

with Cj = /27/1 6 S. For a given reflector density

y the confidence intervals will indicate the tissue size required for a desired estimator resolution.

We will now present some experimental results

using refrigerated and formalin-fixed liver tis- sue specimens.

8. Experimental Results

A 2.0 MHz transducer was used to obtain data from in vitro refrigerated and fixed liver specimens. The thickness of the refrigerated liver was

6.7 cm. After 1 month of formalin-fixation the tissue size was 7.5 cm. From transmission tests

the average values of 6 were observed to be equal

to 0.63 dB/cm-MHz for refrigerated liver and 1.20 dB/cm-MHz for formalin-fixed liver. These values agree favorably with those observed for refrigerated liver by Pauly and Schwan [1] and for formalinfixed liver by Lele [2]. The usable bandwidth was determined from the transmission experiments to be 1.2 to 2.4 MHz. The envelope of the reflected

signal was calculated by using a 15 point lowpass

filter with a Gaussian shape truncated at ± 3 a. This particular filter was chosen because its im- pulse response matched the envelope of the incident

pulse. With this filter the average density of peaks, y, in the reflected signal envelope was observed to be equal to 7. The data were partitioned into non-overlapping segments delimited by the locations of the envelope minima. The same power spectrum was calculated for each segment by

using eq. (10). The coefficient s was estimated

from the difference of spectra separated by a dis- tance approximately equal to 2L/3, where L is the

total size of the tissue.

In the above analysis we were concerned with

the estimator performance as a function of tissue

size. In order to verify the predicted perfor- mance of the confidence intervals with respect to tissue size, small tissue sizes were simulated by

taking the equivalent amount of data from the total signal reflected from the liver, starting at the beginning of the record. The results then indi- cate the experimental performance of the estimator

as the tissue size is increased. The confidence

intervals, instead of being taken about the estimated value, for purposes of comparing the results

of different runs, are taken about the average

values of B observed from the transmission ex- periments.

With the 15 point filter the average segment

size was 18 samples at Tj = 0.1 ys, producing a fundamental frequency equal to 0.6 MHz. Two in- dependent values per spectrum, located at 1.5 (Fi = -.3) and 2.1 (F2 = +.3) MHz were used. From eq.

(24) the resulting value for S is 345. For y = 7 the variance given by eq. (Z7) is equal to

Var K] - (30)

From eq. (29) the resulting 95 percent confidence

intervals are given by

CI 18 18

(31)

The ED estimates as a function of tissue size for 4 independent (nonoverlapping) runs, denoted

130
by Rl through R4, through refrigerated liver are shown in figure 4. The 95 percent conficence in- tervals are indicated. From the figure it is noted

that the confidence intervals are a reasonable pre- diction of the estimator performance: wider variations and extreme values are found at the smaller

tissue sizes with the variations decreasing as the tissue size increases. The confidence intervals

are rather wide indicating that large tissue sizes

are required to determine e accurately with this technique.

The estimates for 6 independent runs, Fl to F6,

through fixed liver are shown in figure 5. The confidence intervals are centered about the average

value of 6 observed for fixed liver. Again the confidence intervals reasonably predict the observed performance.

The averages of the independent runs for refrig- erated and fixed livers are shown in figure 6. The confidence intervals have been reduced to account

for the averages of independent values (by 1/2 for refrigerated liver, by 1//6 for fixed liver). Here

again the confidence intervals are consistent with

the observed results. Even for the averaged esti- mates the reduced confidence intervals are still

B (dB/cm-MHz) 2.8t \

REFRIGERATED LIVER ESTIMATES

e (dB/cm-MHz) FIXED LIVER ESTIMATES

-1.2

Fig. 4. B estimates for refrigerated liver. The theoretically derived 95 percent confidence

intervals are shown in dashed lines as a function of liver size. The curves are centered about the value observed from transmission results. The larger the liver

the more data is produced and the better

the resulting estimate. Experimental re- sults from four runs Rl to R4 are shown. Smaller liver sizes were simulated by taking equivalent sections of data from the

total reflected signal.

estimates for formalin-fixed liver. The confidence intervals are shown in dashed

lines as a function of liver size. The curves are centered about the value ob- served from transmission results. Experimental results are shown for six runs

Fl to F6. overlapped at 8 cm. Even though the experimental

results shown here differ noticeably for refrigerated and fixed liver, the fixed liver estimates

are close to the upper confidence interval predicted for refrigerated liver.

9. Conclusion

The first order model of the irregular reflector

presented in this paper offers a reasonable de- scription of the actual results obtained from re- frigerated and fixed liver samples. The resulting

confidence intervals, however, are wide and overlap

significantly indicating that a large amount of data is required for a reasonable estimator resolution. The spread in the estimates predicted by the confidence intervals are due to the wide variations

possible in the reflected signal power spectrum

caused by the white Gaussian impulse response model

of the irregular reflector. To decrease the con- fidence intervals, and hopefully the resulting ex- perimental estimates, a more accurate model of the typical reflector is required. In the reflector

model assumed here we have ignored possible de- terministic reflections and have assumed the re- flector effects to be completely random. We plan

to study an improved model, combining both de- terministic and random effects, for which better

estimation techniques can be derived to produce

more accurate estimates from smaller tissue samples.

131
(dB/cm-MHz)

2.4

2.0

1.6

1.2

0.4

\ \

\ \ Averaged Estimates

>v\ \

\\

V 0 Refrigerated \ liver

\^ * Formal in-fixed

tv. \^ liver

\\ ^^~^^^95%-F

FORMAl IN-FIXED \,^%-R"

_REFRIGERA1ED

1—1

1 1 1 1

1 2 ^3

-

^

f—{ \—1^ \ 1 \—

1

/4 / 5 6 7 (cm

/ /

/ /

//

1/

// // -1.2

Fig. 6. Comparison averaged B estimates for refrigerated and fixed livers. The respective

confidence intervals are indicated about

the values observed in transmission experiments. The averages of the 4 refrigerated

liver runs and 6 formalin-fixed liver runs indicate a separation in their values.

Acknowledgment

This research was made possible by the loan of the fast analog-to-digital converter and paper tape

unit by the Picker Corporation.

References

[1] Pauly, H. and Schwan, H. P., Mechanism of absorption of ultrasound in liver tissue,

J. Acoust. Soc. Am . 50, 792-99 (1971).

[2] Lele, P. D., Mansfield, A. B., Murphy, A. I., Namery, J., and Senepati , N. , Tissue Charac- terization by Ultrasonic Frequency-dependent

Attenuation and Scattering, in Ultrasonic

Tissue Characterization , M. Linzer, ed.,

pp. 167-96, National Bureau of Standards Spec. Publ. 453 (U.S. Government Printing Office,

Washington, D.C., 1976).

[3] Miller, J. G. , Yuhas, D. E., Mimbs, J. W., Dierker, S. B., Busse, L. J., Laterra, J. J., Weiss, A. N., and Sobel , B. E. , Ultrasonic

Tissue Characterization, 1976 IEEE Ultrasonics

Symposium Proc . , 76 CH 1120-5SU, 33-43 (1976).

[4] Kuc, R. , Schwartz, M. , and Von Micsky, L., Parametric Estimation of the Acoustic At- tenuation Coefficient Slope for Soft Tissue,

1976 IEEE Ultrasonics Symposium Proc . , 76 CH 1120-5SU, 44-47 (1976).

[5] Elias, H. and Sherrick, J. S., Morphology of the Liver (Academic Press, New York, 1969).

[6] Jenkins, G. N. and Watts, D. G., Spectral

Analysis and Its Applications (Holden-Day,

San Franci sco, 1968)

.

[7] Kuc, R., Statistical Estimation of the Acoustic Attenuation Slope for Liver Tissue, Ph.D. Dissertation, Columbia University (1977).

[8] Schwartz, M. , Information Transmission, Modulation, and Noise (McGraw-Hill, New York,

1970).

[9] E. Parzen, Modern Probability Theory and Its Applications (Wiley, New York, 1967).

132
CHAPTER 5

SCATTERING

133

Reprinted from Ultrasonic Tissue Characterization II, M. Linzer, ed.. National Bureau

of Standards, Spec. Publ . 525 (U.S. Government Printing Office, Washington, D.C., 1979)

AN ULTRASONIC TISSUE SIGNATURE FOR THE LUNG SURFACE

Theodore L. Rhynei

Massachusetts Institute of Technology

and Massachusetts General Hospital

Cambridge, Massachusetts 02139, U.S.A.

The normal lung surface is modeled as a statistically rough surface composed of

the air-containing alveolar sacs at the periphery. The ultrasonic reflection (scatter) from the rough surface is analyzed as a random process and a frequency signature, which

depends upon alveolar sac radii statistics, is predicted for the reflectance. Pulseecho ultrasonic instrumentation for the measurement of the absolute reflectance from

the lung surface is presented. Lung reflectance data confirming the lung surface fre- quency signature is presented for humans. Applications of the model are discussed to the detection of pulmonary embolism, atelectasis, pulmonary edema, and chronic lung

disease.

Keywords: Detection of lung disease; frequency signature; statistical scattering;

tissue signature; ultrasonic scattering; ultrasound.

1. Introduction

Ultrasonic characterization of tissue rep- resents a considerable challenge to the re- searcher in that he must exploit essentially

"second order" phenomena while current clinical

techniques have already exploited the "first

order" phenomena. The "second order" phenomena

(dispersion, reflection, scattering, movement,

etc . ) are often measurable only after suitable

instrumentation has been developed. The re- searcher is especially challenged to select from

an infinity of possible instrumentation approaches and plausible phenomena in order to arrive at

a clinically useful diagnostic technique. The work reported here is the development of a tissue

characterization for the normal lung surface using

an analytical approach. The approach is quite

possibly as significant as the results since it offers a path through the complex decisions in- volving instrumentation design, study of phenomena,

and definition of the useful measurement.

The analytical approach used here is summarized

in the four interactive steps outlined below. The interplay of each step can be followed as the

normal lung model is developed.

1) Calibration of the transmitter-receiver

circuitry and transduction process to either an absolute or traceable standard for measurement of tissue acoustic properties that are independent of

the instrumentation.

2) Design of the transmitted acoustic signal

waveform to accentuate the desired tissue phenomena.

3) Development and validation of analytical

models for the tissue target which characterize

^Current Address: Bolt, Beranek and Newman, Inc.,

50 Moulton Street, Cambridge, MA 02138.

the measurable acoustic phenomena of tissue in the normal and diseased states.

4) Development of signal processing operations

performed by the instrumentation to detect and quantify echo parameters that characterize the normal and diseased states of the tissue.

2. Normal Lung

The lung is a very large organ whose surface

lies within a few centimeters of the skin over most of the chest. As shown in figure la, a trans- ducer coupled to the skin may direct ultrasonic

waves through the soft tissues of the intercostal space that lies between adjacent ribs. If a sufficiently small transducer is utilized, the lung

surface can be examined with no interference from

nearby ribs.

A normal lung has a gross density that is ap- proximately one third that of water. Thus, the

lung is approximately two thirds air and one third

soft tissue. At the periphery the schematic of

the magnified lung surface in figure lb indicates

the relationship of the air-containing alveolar

sacs to the soft tissues that surround the sacs. The alveolar sac is the end-respiratory airway and

is divided up into the familiar alveolar chambers.

The marked difference in acoustic impedance be- tween the air and the surrounding soft tissue

causes nearly perfect reflection at the air to soft tissue boundary. For our purposes we postulate an "ultrasonic" lung surface which is a roughened

planar surface composed of the outer walls of the multitude of peripheral alveolar sacs that lie just

inside the pleural membrane.

The physical lung surface (as opposed to the "ultrasonic" surface) is a pleural membrane which

forms a unique bearing with a second pleural mem- brane that is attached to the inside of the chest

135
Lung Surface (Pleura)

Skin and Soft Tissue

(a )

Pleural Surface

Alveolar Sac

(Diameter «275;i.m)

(b)

Fig. 1. Schematic representation of the chest

and lung surface; (a) cross section of the chest wall; (b) enlarged cross sec- tion of the lung surface.

wall. During respiration the lung moves laterally within the chest on this pleura-fluid-pleura

bearing. Since the bearing is composed of soft tissue and is only a few tens of a micrometer

thick, it does not contribute a significant echo

in comparison to the "ultrasonic" lung surface. Furthermore, the lateral motion of the lung per- mits the lung surface to be scanned during respiration by a transducer held stationary with respect

to the chest wal 1

.

The geometry of the lung examination is provided in figure 2. A radiating and receiving transTransducer Aperture Rough Surface of

Infinite Extent

Fig. 2. Geometry for the examination of the lung surface by a transducer with a circular

aperture.

ducer located at the skin is represented by a circular disk which is the aperture of the transducer. The radiating and receiving disk observes the lung

surface through the soft tissue of the intercostal

space, which is a uniformly lossy media. The

"ultrasonic" lung surface is a rough surface normal

to the disk and of infinite extent. The rough sur- face may move laterally with no change in range, thus presenting new portions of its surface to the

area directly underlying the disk.

3. Calibrated Instrumentation

and Signal and Design

Wave propagation between the radiating (and re- ceiving) aperture and lung surface forms a central issue in the calibrated measurement of echoes re- flected from the lung surface. If we further

simplify the situation represented in figure 2 to

a lossless media and a flat perfectly reflective

plane, we have a classic radiation (or diffraction)

problem. By virtue of the finite size of the radiating and receiving disk plus the wave speed

of the media, waves launched by the disk produce

filtered echoes as they reflect from the plane and return to the disk. The radiation (or diffraction)

filter response is given in Appendix A as developed

in the literature [1]^. If the response is graphed

as in figure 3 for a representative situation, we see that the radiation filter is a high pass filter. The nearly flat response of the radiation filter

depends on the selection of aperture size, fre- quency, and range so that the surface lies within

the near-field of the transducer. This is the case for the lung surface measurements. Sub- sequently, the radiation filter will be used both

for calibration and adjustment of lung surface

data.

cr -5 - .

-6 1——^ ^ 1 1 1

I I I I 0 I 23456789 10 Frequency MHz

Fig. 3. Frequency response of the radiation

filter between a radiating disk of radius 0.0125 inch and a flat perfectly

reflecting plane 1.5 cm distant.

The pulse echo instrumentation is diagrammed in the network of figure 4. It consists of a trans- mitter, a receiver, and a transducer, each linear- '< ly coupled to a common transmission system. The transmitting waveform excites the system. The waveform V^(t) propagates through the transmission

line to the transducer. The transducer couples

the electrical domain to the acoustic radiation

field. Energy launched by the radiating disk of figure 2 is represented as energy consumed in the radiation resistance. Conversely, echoed waves striking the disk are represented by the wave '

^Figures in brackets indicate literature

references at the end of this paper.

136
Radiation Impedance

+ Wave

Potential

Transducer

Loss

Lossless

Lossless Matching Transducer Network

I Transmission Line Transformer of Impedance Rg

Receiver

Outputs

Fig. 4. Schematic of pulse-echo ultrasonic instrumentation.

potential Vg(t). The radiated waveform is Vt(t)

as filtered by the transmission line and the transducer. The received waveform Vf-(t) is the wave potential Vg(t) as filtered once again by the transducer and transmission line.

If the transmitter (plus receiver) matches the impedance of the transmission line, then the filtration of the transmission line consists of simple

time delays of the transmitted and received signals. Also, the impedance presented to the transducer is Rq in series with V-t-(t). Thus, matching

effectively removes the transmission line from the network of figure 4. The net effect of the in- strumentation is the filtration of transmitted and received signals by the transducer.

In order to measure transducer response and the magnitude of echoes from a target, it becomes im- portant to define a measure of absolute signal

loss. This is done by energy conservation of the energy in the transmitted wave V^(t), a portion of which ultimately returns as the received echo

Vp(t). Loss is defined here as the ratio of the exchangeable power of the transmitter to the re- ceived power in eq. (1). This is more conveniently expressed as the gain (always less than unity)

or transfer gain in eq. (2) which can be expressed

in decibel or magnitude notation.

(V2)/(4R ) V. Loss (dB) = 10 logio — 20 logiQ— (1) (Vp/(R ) 2V

2V gain = —^ , (2)

Since the transmitted acoustic waveform is de- termined by V|.(t), we are free to choose it so as to accentuate some property of the target. Here,

the magnitude of the lung surface echo is the im- portant property. Furthermore, the returned lung echo will be corrected by the radiation filter

and transducer filter magnitudes. Therefore, we select a transmitted waveform which is a carrier

burst of sufficient duration to allow the transducer and the radiation process to reach their

steady-state or Fourier responses. The transmitted pulse waveform is completely described by the magnitude, frequency, and duration of the sinusoidal carrier. Conversely, the carrier

burst must be sufficiently short in time to allow

range discrimination of the lung echo from other

echoes. The values for and utilized in loss calculations are the instantaneous values of the envelopes of carrier waves.

The transducer frequency response is experimentally determined as an absolute quantity using

the selected signals, the definition of loss, the radiation filter correction (fig. 3), and an ex- perimental geometry as in figure 2 (with a flat perfectly reflective planar test target) [2]. It

is interesting to note that absolute dosimetry may

be determined as the power dissipated in the radiation resistance of figure 4 [2,3]. The transducer

of figure 4 provides a transformer and a lossless matching network in addition to the transducing

plate and associated radiation and dissipation

loads. Modeling of the transducing disk is ex- tensively discussed elsewhere [2,3] where it is shown that a simple model for transducer gain

exists at half-wave resonance. Also, it is shown that optimum loop sensitivity results from adjustment of the transformer for impedance matching of transmitter to transducer impedances. The adoption of a transmission system impedance plus

specification of transducer transfer function

could form the basis of standardization for pulse echo instrumentation.

4. Scattering Model for the Lung Surface

Returning to the measurement of the reflection

from the lung surface depicted in figure 2, we are motivated by the microscopic structure to model

the lung as a randomly rough surface. The essential difference between the flat surface of figure

3 and a rough surface is that the rough surface

has a finite thickness or scattering depth and is said to be range-spread. Mathematically, this is described in eq. (3) as an integration over all range of some range-spread function m(') with the impulse response of the radiation coupling

f(',-,-)^ which is the time domain pair to eq. (A-1).

00 r(t) = f

f(r,a,t) m(r) dr (3)

For a "thinly rough" surface we may expand the function f(r,a,t) about some fixed range (rp),

make a change of variables for fixed wave speed c, and thus turn the equation into the time convolution in eq. (4).

137
r(t) J

f(r^,a,t-T) c_ m(CT)

2 2 dx (4)

Equation (4) is highly significant in that the re- ceived signal r(t) is the result of a linear filtra- tion in cascade with the radiation filter of eq. (A-1). The frequency equivalent of eq. (4) is simply a product of transfer functions in eq. (5),

where G(f) is the transfer function associated

with m( •

)

•

R(f) = F(r,a,f) G(f) (5)

The filter G(f) and its transform pair he m(%CT) represent the filtration of a randomly

rough surface and, therefore, are themselves random. In a sense the precise G(f) depends upon the particular ensemble of scattering elements

that lie in the field pattern of the transducing

disk of figure 2. The value of the Fourier function G(f) is the magnitude (and phase) of the re- flection due to a long carrier burst. By allowing the transducer, radiation filter, and reflection filter to reach steady-state as discussed

above, one may make direct measurement of the magnitude of G(f). The measured value will vary

as different ensembles of scattering elements

sweep in front of the transducer. The charac- terization of the lung surface lies in relating

the statistical properties of the lung surface to the probability density function (and its mean and variance) for the random variable |G(f)|.

A randomly rough surface representing the normal

lung consists of a planar array of the alveolar

sac wall segments shown in figure 1(b). Between adjacent alveolar sac chambers cusp-like regions

are formed which contain soft tissue which readily

support wave propagation. The depth of these

cusps constitutes the thickness or scattering

depth of the "ultrasonic" lung surface. The lung

surface is characterized as having a mean scattering depth (wq) and standard deviation of scattering depth [o^). Figure 1(b) indicates that the scattering depth Wq is approximately equal to the mean radius of the peripheral alveolar sacs. If the wavelength of the ultrasound is very much

greater than Wq one expects the surface to reflect

as though it were flat. Conversely, at some critical wavelength related to the mean scattering

depth Wq one would expect destructive interference.

The degree of the destructive interference would

of course depend upon the regularity of the scat- tering surface with greater destructive interference occurring for smaller a^. Using the above model for the lung surface plus several additional assumptions the probability

density function plus its mean and standard deviation for |G(f)| are predicted in Appendix B. The density function is a Ricean function whose shape

depends upon Wq, a^, and the frequency f. The most significar[t measurable properties of |G(f)| are the mean (Z) and standard deviation (a^) given

in figure 5 as functions of frequency. At lower frequencies the curves approach those of a perfect

reflector (OdB). Conversely, there is a destructive interference minimum at a frequency where

one-half a wavelength equals the mean scattering

depth Wq. Figure 5(a) demonstrates the dependence

of the dip frequency on Wq. In figure 5(b) we note that the depth of the dip increases for greater regularity in the scattering depth (smaller c^)

.

?-5

^-10

o

tr1-20

o^-25

qI -30

1 1 1 1 1 \ 1 1 r

Mean Z

leO^nn

Standard Deviation o-.

J_4 5 Frequency MHz

(a)

4 5 Frequency MHz

(b)

Fig. 5. Families of curves for the mean Z and standard deviation of the predicted

echo amplitude, dB versus frequency, (a) curves for two values of scattering

depth Wq and fixed a^; (b) curves for

two values of a^^ and fixed Wq.

5. Experimental Results

Experimental measurement of the lung surface

reflection can be made to confirm the above model. Measured values are corrected for radiation,

transducer, transmitted voltage, and bulk tissue

effects as in eq. (6). The resulting experimental

value (Y) is ,(l/20)2rf0.897 IQ-^

2V 10'

r |F(r,a,f)| |T(f)P

(6)

is a measure of the absolute reflectivity |G(f)| of

the lung surface at the frequency f. In the equation Vr and Vt are envelopes of sinusoids as dis- cussed earlier. The function |T(f)|2 is the measured transducer loop transfer function and F(r,a,f) is the radiation transfer function for range r and frequency f. Correction is made for bulk tissue loss using an attenuation constant of 0.897 dB/cm.

By averaging over many values of Y at a single

frequency for successive pulse echo transmissions

with the lung surface scanning before the_transducer, we arrive at the mean reflectance Y for

138
m -5 o- 10 -

=£-15-

-20

g-25

-30

Mean Y

Standard Deviation a„

4 5 6-

Frequency MHz

Fig. 6. Experimental data for the mean and standard deviation of lung reflection Y for a normal human volunteer.

that frequency. Similarly, one may compute the standard deviation (a^) for Y over the data for

a single frequency, when multiple frequencies

are examined and the data reduced for Y and oy, the experimental data in figure 6 is arrived at. Note that the destructive dip is present near

5.2 MHz and the curve rises toward 0 dB at lower frequencies. A more extensive discussion shows

close correlation between the predicted probability density function of Appendix B and ex- perimental histograms [2,31. These data confirm

the analytical model of tissue thus completing

step 3 in the approach to tissue characterization.

6. Applications

The final element in the approach to tissue

characterization is to define the signal processing functions of figure 4 to perform some clinically useful application. Two areas of application are suggested for the normal lung tissue sig- nature developed here, they are: a) detection of

acute infiltrative disease and b) detection of chronic pulmonary disease. The normal lung surface strongly reflects the ultrasound due primarily to the presence of air

at the periphery. Several diseases, including

pneumonia, edema, atelectasis, and pulmonary em- bolism, which acutely alter the air content at the periphery should be detectable as a departure from

the normal model. Preliminary clinical evidence

suggests that reductions in lung reflectivity from

10 dB to 30 dB are associated with these acute dis- eases [2,3]. An optimal method of detecting the reduction in reflection has been suggested [2,3]

utilizing the predicted probability density function to determine a sufficient statistic which is the root mean square reflection. An ultrasonic

instrument embodying this technique is shown in figure 7. The performance of this detection

scheme can be evaluated in terms of probability

for false positive and false negative with the testing threshold (T) set to optimize performance.

The chronically abnormal lung can be postulated

to produce reflection functions differing from

those of figures 5 and 6 due to rearrangement of tissue structures at the periphery of the lung.

Diseases such as emphysema and pleural diseases

are of clinical intere^st. Figure 8 demonstrates

the reflection data (Y,ay) for a subject with severe chronic pulmonary disease. The destructive

interference dip has been suppressed presumably by the higher variance in the scattering depth (a^) of the diseased structures at the periphery. In- deed, if a greater value of a^j is used in the model

of figure 5(b) the dip becomes obliterated. A sug- gested application to chronic disease is to fit

predicted curves to experimental data and take the resulting scattering parameters Wq and as in- dices of the lung surface [2,3]. The above applications depend upon detecting

departures from the normal model. Further develop- ment of this tissue characterization approach sug- gests developing detailed models (step 3) for the diseased states so that further clinical applications can be defined (step 4).

Transducer

Lung Surface

Transnnitter

•lF(r,a,f)l Vt lT(f)|2-

.7;

Meter

Light if Less Than

Threshold

RMS Envelope

Comparator

2 ll/2

Sample Lung Echo

T Threshold

Fig. 7. Ultrasonic instrument for detecting acute lung disease using

a sufficient statistic for testing against a threshold.

139
CD"°-5

;-io

-15

^-25 -

-30

"I 1 1 1 1 1 r

Mean Y

2^-20- -_ -

Standard Deviation

,

J I 1 L_ J L 4 5 6

Frequency MHz

Fig. 8. Experimental data for the mean and standard deviation of lung reflection Y for a subject with severe chronic pulmo- nary disease.

Appendix A Radiation Filter Response

The radiation filter response reported in the literature [1] and tabulated [2] is given in eq. (A-1) for the definitions in eqs. (A-2). It is an exact solution to the radiation coupling between

two coaxial disks spaced at distance 2r apart.

F(r,a,f) = [cos(2Trft3) + j sin(2TTft3 )] (A-1

c^- t3ti,

;.2

"tu + t,

Lt, + ti

jQ(2^ft3) + jJi(2TTft3

rtu + t, + — tf

In the equations c is the wave speed, f is the frequency, a is the disl< radius, and r is the range between disl< and plane. The functions Jq, are Bessel functions of the first l<ind.

Appendix B Detailed Scattering Function

for the Lung Surface

This appendix is a summary of a more detailed

development of the scattering function for the

lung given elsewhere [2,3]. The range spread

function m(r) is considered to be the incremental

reflectance of the rough surface due to surface elements between r and r+dr in range. In order to simplify the development the following assumptions

are made:

1) Reflection is a first order scattering

process involving no shadowing of reflective ele- ments nor multiple reflection among elements.

2) The dimensions of roughness elements are

small compared to the diameter of the transducer.

3) The soft tissue to air interfaces perfectly reflect with no other loss mechanism.

4) The disl< is normal to the surface.

5) The scattering depth is thin compared to variations in the radiation transfer function.

6) The incremental reflectance from an in- dividual scattering element is of constant amplitude over the depth of the element.

7) The scattering elements are statistically

independent.

8) The lung surface approaches a flat perfectly reflective plane as the frequency approaches

zero.The transfer function for an individual scat- tering element of depth Wjv, is given in eq. (B-1). The overall transfer function is a sum over a large number of individual scattering elements in eq. (B-2).

L(f ,wni) j^TTf

-j2TTf2wni

1 - e (B-1

1 . + tu + tl t. + t;

J^(27Tft3;

Jl (27Tftc

+ higher terms

tl = 2r/c

[432 + 4r2

27Tft.

+ jJl(2TTft:

(A-2a)

(A-2b)

F(f) = h E L(f,wm)

M=l (B-2)

Invoking the central limit theorem G(f) becomes a Gaussian random variable with independent real and imaginary parts with means R^, Qq and variance a^. When the value of k in eq. (B-1) is adjusted to normalize the magnitude as in assumption 8, the essential values for Rp, Qq and are arrived at

in eqs. (B-3) and (8-4).

4w2(2Trf)2

1 + e

-4aw2(2Trf )2 r2

t3 = h{t2 - tl)

= h[t2 + tl)

(A-2c)

(A-2d)

. .^ -2aw2(2Trf)2 (2wo2uf) ^2—^

2 cos e (B-3)

140
8w2(2TTf)2

-4aw2(2Trf )-

If we are concerned only with the magnitude Z of G(f) the probability density function becomes

Ricean as in eq. (B-5). The mean and a variance

of the magnitude are given in eqs. (B-6) and (B-7)

respectively. The functions lo(') and lii-) are modified Bessel functions.

References

^"4) [1] Rhyne, T. L., Radiation coupling of a disk

to a plane and back or a disk to a disk: An exact solution, J. Acoust. Soc. Am . 61 , 318- 324 (1977).

-(Z2 + R2 + Q2)

.(Z) = ^ e 2a2 Z(R2 + Q2)

0 0

[2] Rhyne, T. L. , Acoustic Instrumentation and Characterization of Lung Tissue (Forest

Grove, Oregon, 1977).

[3] Rhyne, T. L. , Sonar Characterization of Tissue as Applied to the Lung, Sc. D. Thesis,

Department of Electrical Engineering and Com- puter Science, Massachusetts Institute of Technology, Cambridge, Massachusetts (1976).

Z > 0 (B-5)

-(R^ + Q^)

Z = e 4a2 a^Tt

' R2 + Q2\ R2 + Q2

1 + _o ^1 i_ 0 ^0

2t2 4t2

R2 + Q2 /r2 + q2

2t2 4t2

(B-6)

j2 =

z Z2 -7)

The mean squared lung surface reflectance in eq. (B-8) expresses the energy scattered at a given frequency. This function is essentially

the scattering function discussed in radar.

|G(f)| 2 = ,2 = R2 . Q2 . 2a2 (B-E

Acknowledgments

This paper is essentially a summary of work re- ported in the three references cited. It was felt

that it would be useful to the reader to report

the essential results here in summary form and to refer the interested reader to the more extensive

discussions and numerous literature citations to

be found in the basic papers.

The work summarized here and in the basic papers was supported by the Ambrose Monell Foundation and the G. Linger Vetlesen Foundation.

141

Reprinted from Ultrasonic Tissue Characterization II, M. Linzer, ed., National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C., 1979).

ANGLE SCAN AND FREQUENCY-SWEPT ULTRASONIC SCATTERING CHARACTERIZATION OF TISSUE

R. C. Waag, P. P. K. Lee, R. M. Lerner, L. P. Hunter, R. Gramiak, and E. A. Schenk

Departments of Electrical Engineering, Radiology, and Pathology

University of Rochester

Rochester, New York 14627, U.S.A.

Ultrasonic wave interference has been applied to characterize tissue by measuring

scattered wave intensity as a function of frequency and angle. A theory of acoustic

wave propagation and scattering in an inhomogeneous medium has been employed to show

that received ultrasound may be expressed in terms of medium refractive index variations via a Fourier transform. Using a computer-based system, measurements were made

on model targets and post-mortem liver specimens. Model studies demonstrate that regular scatterer spacing can be inferred from measured diffraction data by Fourier

inversion and that scattering differences can be observed from random media consisting of particles of different average sizes. Scattering from liver indicates there

is significantly more energy scattered at small angles than is backscattered. Cor- relation of ultrasound scattering with structure observed through a microscope has been obtained by computing the diffraction pattern of the two-dimensional optical

transmittance images acquired through a microscope-TV chain attached to the computer.

Average particle sizes of the model random media determined by Fourier analysis that exhibited diffraction rings of the digitized cross-sections yielded scattering predictions which were in agreement with measured acoustic data.

Key words: Angular scattering; characterization of tissue; optical correlation;

scattering; swept-f requency diffraction.

1. Introduction

Although ultrasound has been widely accepted

as a valuable diagnostic tool in medical imaging,

its use in quantitative characterization of tissue is just beginning to emerge. Among methods

which employ amplitude, phase, frequency, and at- tenuation of ultrasound signals, diffractionbased techniques offer the potential of characterizing acoustic scattering element distribution on a scale corresponding to the wavelength

within a finite volume probed by the ultrasound

beam [l-6]i. Success of wave interference methods

in x-ray studies of materials as well as in atmospheric probing by radar motivates the development

of the methodology for acoustic studies of tissue.

However, realization of practical tissue characterization systems based on diffraction require

more detailed understanding of the acoustic scattering process, including development of useful models and knowledge of practical measurement

limitations.

In this paper, our ultrasonic scattering studies

of model targets and preliminary results from liver

tissue are described. A model is developed to show

the fundamental relationship between scattered

acoustic waves and tissue structure. The measurements demonstrate feasibility of the method and identify problems. The results indicate the prom-

^Figures in brackets indicate literature

references at the end of this paper.

ise of the concept but point out the need for ad- ditional data to characterize tissue. Our research combining angle scanning and fre- quency sweeping is intended to provide a foundation for characterization of tissue by its ultra- sonic scattering properties.

2. Theoretical Basis

A. Acoustic Scattering Model

The model we use relates the scattered intensity to the acoustic structure of the tissue and in- dicates that different levels of organization may

be studied with ultrasound by appropriate choice

of frequency and geometry. The resulting acoustic

characterization can then be compared to microscopic determinations of structure to establish

tissue pathology. The theory is analogous to that

used in x-ray diffraction of amorphous materials

and allows the structure of the medium to be in- ferred from measurements of the scattered acoustic

wave.The tissue is modeled as an inhomogeneous medium

in which the acoustic properties exhibit variations

from point to point. Since wave propagation is af- fected by the local environment, wavefronts are dis- torted and scattered. The derivation has followed

the basic approach used in modeling wave propagation and scattering for acoustic studies of the lower atmosphere [7].

143
The analysis begins with consideration of a plane wave propagating through a lossless unbounded

medium which has small variations in refractive

index. Small values of absorption do not change

the basic relationships [6]. Assuming a monochromatic incident plane wave, weak single scattering, and a receiver in the far- field, the resulting scattered wave velocity potential 't'llrjk) is given by

(t.i(r,k) = A k2 e^^^ r k-r'

2-nr ni(r' )dV' (1) V

in which

Aq = incident plane wave amplitude

k = incident wave number

K = scattering wave vector

ni(r') = variations of acoustic refractive index

V = scattering volume

r = distance from the scattering volume center to the reception point

Thus, the velocity potential at a receiving point r is equal to the product of a frequency-dependent

factor and the three-dimensional spatial Fourier

transform of the acoustic refractive index variations. The theory also relates the mean square value

of velocity potential to the correlation function

of the acoustic refractive index variations in a random medium if the variations are stationary in space. The relation is

:|4>i(r,k)|:

A2k'*V'

0 "1 (p)dV' (2)

where

(p) = <ni(r' )ni(r' + p)>

where < > denotes ensemble averaging. This shows

that the average intensity of the scattered wave

is proportional to the three-dimensional spatial

Fourier transform of the correlation function of the acoustic refractive index variations.

The expression for the mean square velocity

potential allows determination of the correlation

function of the acoustic refractive index variations in the medium by inversion of the transform

relating tbe measured average scattered intensity

as a function of scattering vector [8]. Alternatively, a specific form for the correlation function can be employed to evaluate the average scattered intensity for comparison with experimental

data. The latter approach has been used to evaluate scattering from a cloud of scatterers assuming

a correlation function with a Gaussian shape modified to remove the dc spectral component [9]. Neglecting density variations, the resultant ex- pression for the scattered intensity per unit in- cident intensity is

(3)

k2a2sin2|)e -2k2a^ .2^

V = scattering angle

NV = mean number of scatterers in sample volume

a = mean radius of the particles

= mean value of compressibility variations

between scatterers and medium

The result predicts that smaller particles scatter more energy off-axis than large particles for a fixed incident frequency.

B. Optical Correlation

Optical data for comparison to ultrasound angle

scattering data can be obtained by computing the diffraction pattern of a sample region with variable transmission representing spatial distribution of scattering inhomogeneities. In the far- field of a plane through the region, the diffracted

optical field is given in terms of the two-dimensional Fourier transform of the transmission pat- tern [10].

Ae

-i kr J ^^l >^ " - dr' (4)

where

A

k

T(r')

constant

2i r

\ r transmittance of aperture S

The intensity of I(r) of the pattern is then

I(r) = *(r)**(r)

The dimensions over which diffraction occurs are determined by the wavelength or, equivalently, the sampling interval of the optical transmittance and

can be readily chosen in analysis to yield a scale comparable to that in ultrasound diffraction.

Averaging the two-dimensional diffraction intensity

patterns of any collection of typical cross-sections

in the region results in a statistical characterization of diffraction by a random medium. For an isotropic random medium with local order,

the predicted average diffracted intensity takes

the form of concentric rings [ill. The spacing of

the rings gives nearest neighbor distance while the width of the rings is a measure of the spread in scatterer size and the number of visible rings in- dicates ranges of local order. Optical diffraction

also allows quantitative determinations of parameters describing known optical morphology for com- parison with similar parameters derived ultrasonically when there is no order since the width or general shape of the power spectra can be used in these cases.

3. Experimental Methods

A. Acoustic Scattering

Initial studies employed frequency sweeping

with fixed transducer-target orientation. The scattering experiments were performed in a waterfilled tank containing a fixture on which trans- ducer holders were mounted. The holders could be angled to align the ultrasonic beams and could be slid along the fixture as well.

144
The electronic instrumentation used for this

investigation consisted of a transmitter capable

of frequency sweeping, a range-gated receiver and

a recorder. Bursts of ultrasound were gated from

a variable frequency master oscillator to a power amplifier which drives a wideband 9.5 mm diameter

transducer with a 5 MHz center frequency. The frequency of the master oscillator was slowly

swept over a range of 2 to 8 MHz by a linear ramp function that produced negligible carrier frequency variation over any single pulse. The scattered ultrasound pressure was detected

by a receiving transducer matched to that used for transmission and the amplified RF signal was energy-detected to give a video signal proportional to the incident wave peak intensity which was

then recorded. Arrays of cylinders were studied to provide in- formation about the influence of geometric align- ment and beam uniformity. The scatterer positions

for array measurements were established by five

sets of uniformly spaced grooves two centimeters

in length. A rubber sheet was used to shield the holder exposing only one set of wires for acoustic measurements. The center of the array was nominally set at the intersection of the transducer beams for each study with the array elements lying along

the bisector of the angle formed by the beams. The energy detector output was bandpass filtered to produce a signal that was displayed as a function of frequency on the face of an oscilloscope for photographic recording. The analog curves were sampled at 0.115 MHz intervals and quantized into integers in the range 0 to 255 for cal- culation of Fourier transforms. Ultrasound scattering as a function of angle

was measured in a water tank using an acoustic

diffractometer [12] that provided precise control

of transducer position relative to the scattering

volume. The scattering medium was contained in a cylindrical column 28 mm in diameter by a .0254 mm thick cellulose tubing that minimized reflected

energy loss at the perimeter of the sample. Trans- mitting and receiving transducers containing 4.76

mm radius ceramic disks as active elements were

rotated in equal increments but opposite directions

about the axis of the cylindrical sample. Trans- mitter and receiver distances from the axis of rotation were each equal to 13.6 cm. This scanning

procedure maintains a constant scattering vector direction while changing the scattering angle, v, and hence the scattering vector magnitude. The centers of transducer rotation were maintained to within ± 0.3 mm during the angle scan. The electronics were the same as in the sweptfrequency measurements. The receiver electronics

were also the same as used in the previous studies

except that a log amplifier was added to accommodate both the small off-axis scattering and the

large direct transmission signals. The energy de- tected output was sampled by the computer and re- corded in digital form along with appropriate positional information for statistical analysis and display.

A typical scattering experiment consisted of sixteen angle scans taken at 2.5 mm increments

along the axis of the cylindrical sample. In each

angle scan, data was collected at 163 equally

spaced increments of 2° from a scattering angle of -153° to 165°. The transmitted tone burst was

10 MS long while the receiver gate was 6 ys long

and centered in the scattering volume.

Fresh samples of pig liver and human liver

samples obtained at autopsy have also been studied

ul trasonical ly by angle scanning and varying fre- quency. Cylindrical plugs were taken from peripheral regions near the capsule to minimize the inclusion of large vessels. Transmit pulse length

and receiver gates were set as in the random medium model studies to minimize inclusion of specular

reflectors from the surface.

B. Optical Data

Optical data was acquired under computer control by sampling a TV image obtained through a transmission microscope. Drops of the particle

suspensions were spread over a microscope slide

and typical areas digitized. Five different

images from a smear of each particle suspension were obtained for analysis. The individual images

consisted of 8-bit samples representing light in- tensity transmission over a field of 1.7 mm spanned by 384 x 384 matrix elements.

The cylindrical liver specimens were fixed in formalin and standard sectioning and staining

procedures used to evaluate histomorphologic changes in the sections that were studied ultrasonically. Each stained section was digitized into a 256 x 256 matrix covering a field of 4.5 mm. In the optical studies of liver tissue, a Van Gieson

connective tissue stain was employed to bring out structures believed to cause ultrasonic scattering

and the computed average power spectra were used

to characterize the architecture for comparison

with ultrasound angle scan data. The digital representations of the optical

images obtained through the microscope-TV system

were enhanced to improve the contrast between the particle boundaries and the background. This was accomplished by forming histograms of original

image amplitudes and using these histograms to de- velop mappings that spread the original light in- tensity transmission values over wider ranges. The far-field diffraction pattern of each optical

image was obtained by a two-dimensional Fourier

transformation implemented using an integer FFT algorithm. The log magnitude of the resultant

spectra was calculated to facilitate display of a wide range of spatial frequency amplitudes. Averages of the log magnitude spectra from the five

sample functions of the same particle size distribution were computed. The spherical symmetry of

this spectral estimate was used to produce additional smoothing by averaging spatial frequency

amplitudes determined along radii spaced 1° apart. The results were used to find average nearest neighbor distances.

4. Results

Data was collected by frequency scanning 10 mil monofilament nylon cylinders in arrays with spacings of 0.72 and 1.52 mm at a range of 11.0 cm and a Fourier transform was applied to infer the spacings (fig. 1). The influence of transmitter

range on measurements of diffraction by an array spacing of 1.52 mm was observed for ranges of 4.5

and 11.5 cm (fig. 2). The distances (0.78 and 1.55 mm) indicated by the peaks on the transformed

data in each of the measurements are within 4 percent of the actual values. The envelope of the data collected at 4.5 cm is different from the far- field measurements, but did not invalidate calcula145
Fig. 1. Swept- Frequency Diffraction by Arrays. Measured values of scat- tered energy as a function of frequency are shown (left) on a linear scale with their corresponding Fourier transforms (right) also on a linear scale for array spacings of 1.52 mm (top) and 0.76 mm (bottom) at a transmitter range of 11.0 cm. The ultra- sonically determined spacings were 1.55 mm and 0.78 mm respectively.

Fig. 2. Swept-Frequency Diffraction as a Function of Range. Measured

curves of energy as a function of frequency are displayed (left)

on a linear scale with corresponding Fourier transforms (right) also on a linear scale for transmitter ranges of 4.5 cm (top) and 11.5 cm (bottom) for an array spacing of 1.52 tom. The ultrasonically determined spacings were 1.48 mm at the far range and

1.55 mm at the near range.

146
Fig. 3. Frequency-Dependent Angular Scattering by a Random Medium Model. Measurements of average intensity are shown (left) on a logarithmic scale along with calculated scattering (right) on the same scale for a frequency of 3.8 MHz (top) and 6.0 MHz (bottom). The measured data obtained from a suspension of particles demonstrates

more forward scattering as frequency increases and compares well with computations of scattering from a cloud in which the average

particle radius is 128 pm.

tions of spacings by Fourier inversion of the data. Angle scans were carried out on three suspensions

of different average size Sephadex2 particles. Mea- surements of scattered ultrasound signal as a function of angle were averaged for each distribution

of particle size. The averaged angle scan data is an estimate of the spectral power in wave number

or reciprocal space of the variations in acoustic

index of refraction.

Averages of ten angle scans for each of three particle size distributions were obtained. The transmitted main beam was subtracted from the average data and the resulting angular scattering data smoothed to remove artificial fluctuations arising

from averaging only a finite number of sample functions. The final result was compared with calcula-

^Trademark of Pharmacia Fine Chemicals.

tions of scattered intensity using eq. (3) to de- termine average scattered intensity as a function

of angle at two frequencies for the coarse grade

of particles which had the largest average size

(fig. 3). The averages for two other particle

distributions show how off-axis scattering increases as average particle size decreases (fig. 4). Enhanced optical transmittance images of five

sample functions and the corresponding average log

magnitude spectra were obtained from smears of three particle grades (fig. 5). A smoothed spatial

frequency amplitude distribution was found by aver- aging the amplitudes along radii from which the nearest neighbor distances may be determined

(table 1). Pilot studies of acoustic scattering from human

and pig liver tissue by angle scanning have been carried out (fig. 6). The data shows that there

147
Fig. 4. Size-Dependent Angular Scattering by a Random Medium Model. The polar plots and corresponding Cartesian displays show average in- tensity on a linear scale at 5.9 MHz for distributions of scatterers with an average particle radius of 93 ym (top) and with an average radius of 84 m (bottom). The increase in omnidirectional

scattering for smaller scatterers is evident in both plots and also demonstrated by the mean scattering angle defined by arrows crossing standard deviation bars below the Cartesian plots.

Table 1. Nearest neighbor spacing determined

by Fourier transform analysis of optical transmi ttance.

Particle Mean spacing Spread of distribution (pm) spacings (+la)

(ym)

G50M 93.3 63.2 - 177.6

G50F 84.3 57.3 - 159.4

is significantly more scattered energy at small angles than in the backscattered mode. Scattering

In the forward direction becomes greater as the frequency increases. Optical data obtained from

these specimens shows the well-defined regular

lobular structure of pig liver and the irregular

structure of a post-necrotic cirrhotic human liver

(fig. 7). The power spectra and their corresponding average radial distributions show the same trend of increased omnidirectional scattering from

pig liver that the acoustic data demonstrate.

5. Discussion

The measured scattering from arrays of nylon

cylinders yields element spacings that correspond

well to actual values and shows the influence of near-field variations of transducer beams on the

determination of scatterer spacing. The number of peaks in the transformed data indicates diffraction

by integer multiples of the basic spacing and are a measure of the number of scatterers in the beam or the effective width of the common scattering volume

which contains more array elements as the spacing

decreases. Diffraction-based measurements of array element

spacing as a function of range from the transmitter

show peaks that do not vary in position when the scatterers are in the near-field of the transducers. These measurements also support the utility of a model that employs the far-field assumption

for inferring structure even when the far-field as- sumption is not strictly satisfied.

Acoustic scattering from Sephadex was measured

using a wavelength that ranged from 2 to 30 times the particle diameters and corresponds to a transition region between point scattering and diffraction by individual spheres. This relationship of wavelength and particle size was chosen for its potential similarity to situations of interest in medical ultrasound. Differences in scattering due to par- ticle size are still demonstrated by the analysis

of both the acoustic and optical data. The acoustic

data from the Sephadex experiments agrees with the predictions of the expression describing scattering

from a cloud of particles.

For the coarse grade of particles, the computed

results agree well with the experimental data. The mean value size parameter of 128 ym is well

148
Fig. 5. Optical Image Analysis of Random Media Model. In (a) particles

with an average size of 84 pm (left) and 93 ym are shown with

the central field enhanced by amplitude mapping. The power spectra (b) obtained by averaging showed diffraction rings with

an average radial distribution of energy (c) that is inversely

proportional to scatterer size and consistent with the acoustic scattering results.

within the range of the manufacturer's specifications on sizes and is also confirmed by the optical

determinations. Both experimental data and calculations show that the scattering becomes greater in the forward direction as frequency increases. Polar

plots of average acoustic intensity as a function

of scattering angle also show that a distribution

of small particles scatters relatively more energy

at larger angles than does a distribution of large

particles. These results are in agreement with theoretical

predictions about scattering off-axis as a function

of particle size, and support the swept-frequency

studies in which small particles scattered more

energy at high frequency than did large particles

reported earlier [4]. The experiments are comparable because the Sephadex suspensions are isotropic

so that angle scanning produces the same result as frequency scanning. The acoustic scattering data was collected under conditions that reasonably approximate the plane

wave, point receiver, and weak scattering assumptions employed in the theoretical development. The

170 microseconds between transmit and receive gates

correspond to transducer distances of 12.6 cm from

the center of the scattering volume. This distance

normalized by the ratio, the square of transducer

radius to the wavelength, is 10.9 and is well within the far-field resulting in a plane wave incident

on the scattering volume. The distance also results

149
Fig. 6. Comparison of Average Angular Scattered Intensity From Normal Pig

Liver and Cirrhotic Human Liver. Specimens studied at 3 MHz (upper

panels) show that the normal pig liver scatters more omnidirectionally

than cirrhotic human liver and that, as the frequency is increased to

6 MHz, the forward scattering component increases in both cases. This

is consistent with scattering from collagen which is arranged in a smaller, more uniform matrix in the pig liver than in the cirrhotic

human liver.

in a maximum phase variation of 16.4° across the face of the receiving transducer for a wave originating from a point at the center of the scattering

volume and thus a point receiver approximation is justified. . The logarithmic compression of the received

ultrasound signal near 0° scattering angle, needed

to allow simultaneous demonstration of scattering

signals at other angles, indicates that the assumption of weak, single scattering or the Born ap- proximation is valid. The polar plots do not demonstrate symmetric

scattering about each side of the 0° scattering

angle beam as anticipated from the isotropy as- sumption. A reason for this is that a slightly

different scattering volume was sampled on each

side of 0° due to error in concentricity of the transducer arms. Optical characterization of a distribution of spheres shows a ring which agrees with theory.

The good agreement between theory and final ring structures obtained by processing only five samples

supports the notion that the particle distribution

used for a random medium model is isotropic. Since

the particles are closely packed, the spacings ob- served by light transmittance analysis are equal

to particle size. Parameters for the particle distributions derived from averages of radial lines in the two- dimensional log spectra are in excellent agree- ment with the values supplied by the manufacturer

as well as being in qualitative agreement with

analysis of acoustic scattering data. The angle scan data from pig and human liver

specimens demonstrate differences as a result of

the different architecture of the tissues. The

pig liver scatters more omnidirectionally than the human liver. At lower frequencies, the pig liver

also shows a lobe structure indicative of local order in the lobular arrangement, while the human liver scattering, which is predominantly in the forward direction, results from larger, more ir- regular spacings. The increase in forward scat- tering at high frequencies as in the Sephadex ex^

150
Fig. 7. Optical Image Analysis of Liver. In (a), normal pig liver (left) and cirrhotic human liver have been stained to show connective tissue as dark bands. The power spectra (b) obtained by averaging show that the

pig liver produces a broader distribution of scattering than the human

liver. The relatively isotropic patterns have been reduced to a one- dimensional form (c) by averaging radial lines at 1° increments to produce

data comparable to ultrasound angular scattering when viewed as a Cartesian plot. The optical analysis demonstrates the same increased spread

in scattering from pig liver that the acoustic patterns contain.

151
periments indicates that important scattering may

take place from elements in the size range included in the Sephadex studies. The data also implies

that backscattered energy, while easier to monitor

in practical situations, represents only a small amount of tissue structure information. It re- mains to determine whether observed peaks in the scattering pattern are due to many randomly spaced scatterers in the tissue or a few large single

scattering objects.

Further investigation is also required to determine the specific structural changes observed

acoustically, correlate these results with histopathology, and establish the reproducibility of

the results from these initial studies of liver

specimens

.

6. Conclusion

Experimental observation of acoustic diffraction

by arrays using swept-frequency ultrasound have agreed well with theoretical predictions. The ex- periments indicate that near-field beam nonuniformities need not invalidate inference of scatterer

spacing from a model employing a far-field approximation. However, more results are needed to bound limitations imposed on measurement of scattering

by acoustic diffraction as a result of beam non- uniformities and misalignments.

The ultrasound angle scan data from Sephadex

shows size-dependent scattering and agrees with

theoretical predictions as well as with optical

analysis. The Fourier analysis of optical data accurately confirms the particle size distribution

information provided by the vendor and demonstrates a way optical images can be quantitatively

analyzed to provide a reference for comparison with

ultrasound data. The results obtained indicate the potential for remote probing with ultrasound to characterize a random medium from its scattering

and the use of digitally processed optical data

to confirm the results. Preliminary data from swept-frequency and angle

scan experiments with pig and diseased human liver

tissue shows the importance of scattering at small angles and also that this technique may lead to a useful diagnostic tool. However, additional data

is needed to characterize tissue and thus point

the way to optimum parameters for clinical deter- minations of tissue structure from diffraction ef- fects with ultrasound.

Acknowledgments

We wish to acknowledge important assistance in the conduct of this work by Edward E. Eyler, C. Robert Hoffman III, and Jeffrey Astheimer who de- veloped computer programs, and Frank H. Slaymaker

and Peter H. Helmers who designed major parts of

the mechanical and electronic hardware used in these studies.

This work was supported by the National Science

Foundation under grant #APR75-14890 and the National Heart and Lung Institute under grant #HL15016.

[2] Chivers, R. C, Hill, R. R. , and Nicholas, D,, Frequency Dependence of Ultrasonic Backscattering Cross-Section: an Indicator of Tissue

Structure Characteristics, in Proc. of the 2nd World Congress on Ultrasonics in Medicine , Rotterdam, The Netherlands, 4-8 June, 1973,

M. deVlieger, D. N. White, and V. R. McCready,

eds., pp. 300-303 (Excerpta Medica, Amsterdam,

1974).

[3] Heyser, R. C. and LeCroissette, D. H., A new ultrasonic imaging system using time delay

spectrometry. Ultrasound in Medicine and Bi - ology 1, (2), 119 (March 1974). ~

[4] Waag, R. C. and Lerner, R. M. , Tissue Macro- Structure Determination with Swept-Frequency

Ultrasound, in Proc. of 1973 Ultrasonics

Symposium , Monterey, Calif., IEEE Cat. No. 73 CHO 807-8 SU 63-66, 5-7 November, 1973.

[5] Namery, J. and Lele, P. P., Ultrasonic Detection of Myocardial Infarction in Dog, in Proc. of 1972 Ultrasonics Symposium , Boston,

Mass., IEEE Cat. No. 72 CHO 708-8 SU: 491-

494, 4-7 October, 1972.

[6] Waag, R. C, Lerner, R. M. , and Gramiak, R.

,

Swept-Frequency Ultrasonic Determination of Tissue Macrostructure, in Ultrasonic Tissue

Characterization , M. Linzer, ed.. National Bureau of Standards Spec. Publ. 453, pp. 213- 228 (U.S. Government Printing Office, Washington, D.C., 1976).

[7] Tatars kii, V. I., Wave Propagation in a Tur- bulent Medium (McGraw-Hill Book Company, New

York, 1961).

[8] Lee, P. P. K., Waag, R. C, and Hunter, L. P., Swept-frequency diffraction of ultrasound by

cylinders and arrays, J. Acoust. Soc. Am . 63

(2), 600-606 (1978).

[9] Morse, P. M. and Ingard, K. U., Theoretical

Acoustics , Chapter 8, p. 439 (McGraw-Hill

,

Inc. , New York, 1968).

[10] Goodman, J. W., Introduction to Fourier Optics (McGraw-Hill Book Company, New York,

1968).

[11] Azaroff, L. V. et al., X-Ray Diffraction

(McGraw-Hill Book Company, New York, 1974).

[12] Slaymaker, F. H., Ultrssonic diffraction ap- paratus users manual, (Preliminary) Progress

Report on Tissue Characterization with Ultrasound (NSF Project No. APR 75-14890), Appendix I, Dept. of Electrical Engineering,

College of Engineering and Applied Science,

Rochester, New York, June 1976. NTIS #PB267397/AS.

References

[1] Baum, G., Quantized Ultrasonography, in Recent Advances in Diagnostic Ultrasound , E. Rand,

ed. (Charles C. Thomas, Publisher, Springfield, 111., 1971).

152
Reprinted from Ultrasonic Tissue Characterization II, M. Linzer, ed . , National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C., 1979).

QUANTITATIVE MEASUREMENTS OF SCATTERING OF ULTRASOUND BY HEART AND LIVER

J. M. Reid and K. K. Shung

Institute of Applied Physiology and Medicine

and Providence Medical Center Seattle, Washington 98122, U.S.A.

Quantitative backscattering measurements have been made using the substitution method

used to measure the scattering properties of blood previously. We have obtained pre- liminary experimental values Tor the backscattering coefficients of liver and myocardium,

fully corrected for equipment and transducer parameters as well as attenuation of the scattering tissue. Results show that scattering for both liver and myocardium is an increasing function of frequency up to 10 MHz. This increase indicates that the tissue

elements responsible for the scattering must be less than 30 micrometers in diameter.

The level of scattering from liver tissue indicates that if it is isotropic scattering

the scattering loss is lange enough to account for about 28 percent of the total at- tenuation reported at 10 MHz frequency.

Keywords: Absorption; attenuation; heart; liver; scattering; scattering cross-section.

1. Introduction

The recent interest in characterizing biological tissues through noninvasive ultrasonic means

has resulted in investigations and reports on values of velocity, attenuation, impedance, and scattering and echo strength. The first three

quantities are nearly always measured in a quantitative sense, the last two are usually measured

in a relative sense. The last two quantities are sometimes spoken of interchangeably as if they were

the same thing. However, echo strength is the re- sult of the operation of a number of factors:

1) the absolute scattering strength of the tissues;

2) the absorption of the tissues (including the tissue that is doing the scattering); and 3) many equipment parameters.

Although it may appear to be expeditious to do characterization on the basis of echo amplitudes

produced by existing equipment, we believe it preferable to obtain the data under conditions

which allow the absolute scattering coefficients

to be calculated independent of tissue absorption

and equipment parameters. Knowledge of absolute

scattering parameters is useful for the identification of mechanisms and the prediction of possible

applications in medicine. An even more exciting

use, however, is in the design of new equipment

utilizing new approaches to tissue characterization which can generally only be done if the data obtained are independent of the taking equipment.

Quantitative backscattering measurements can be made using a substitution method which has already

been used to measure the scattering properties of

blood [l-4]i. We have used this method to obtain

preliminary experimental values for the scattering

properties of liver and myocardium. Further more extensive studies on human tissues will be con- ducted. Animal tissues were used for coneenience

in adapting the system to solid tissues. Results have been presented by Nicholas [5] on backscattering coefficients per solid angle for

liver, spleen and brain. No details are given on the formalism used to derive the backscattering

coefficient. Nicholas' values for liver are about

an order of magnitude greater than our values, and

at the higher frequencies would predict a scattering loss which equals the entire observed attenuation. Since this a relatively new field, we be- lieve it essential to give as many details of the measurement and data reduction process as possible

and, in this article, will present our complete

procedure.

2. Method

The backscattering coefficient defined as power

scattered per unit solid angle in the backward

direction by a unit volume of scatterers was cal- culated by comparing the RMS value of the backscattered wave to that of a known reflected wave. The coefficient can be defined to be independent of the measuring system and the attenuation characteristics of the tissue [1,2]. Measurements were performed in a large water

^Figures in brackets indicate literature

references at the end of this paper.

153
tank which was filled with normal saline solution.

The temperature of the saline was kept at 18 °C +

1 °C. The samples were fixed on a sample holder about 15 cm away from the transducer. Excised

calf liver and heart were obtained immediately

after the sacrifice of the animal and stored in normal saline solution at a temperature of 4 to

6 °C. Measurements were carried out within three

days.

Five liver specimens and five heart specimens were used with each cut into sample regions which were examined so that only those samples free of gross connective tissue or blood vessel interface were used for the measurements to better define

the bulk properties of each tissue type. The samples were 2 cm x 2 cm squares with a thickness

of 3 to 5 cm. The liver samples were examined in

a number of randomly chosen orientations so that

30 to 45 experimental values were calculated for each point on the results. In the measurements of myocardium samples, the direction of the sound beam was always perpendicular to the muscle fibers.

Ultrasonic transducers (Panametrics ) with resonant frequencies at 3, 5 and 10 MHz and a diameter of 0.635 cm were used. Electronic equipment

consisted of a gated burst generator, pulse echo receiver, and a controllable receiver gating circuit [2,3]. All time measurements were made on an oscilloscope and the output gated echo measured by

a true RMS voltmeter. A calibrated attenuator, im- pedance matched to the receiver input circuit, was adjusted to obtain the same reference reading on the voltmeter for the reflected wave and the scat- tered wave. The backscattering coefficient was calculated

from the attenuator readings, equipment and equations expressing the received available power from targets located on the axis in the far field of a round piston transducer [1]. The received available power in the wave reflected from a plane in- terface can be written

where nd = backscattering coefficient per unit

solid angle, per cm^

S = cross-sectional area of the sound beam,

cm2

o = attenuation coefficient of the scattering tissue

c = velocity of sound in the scattering

tissue

R = range to surface of scattering tissue

ti = time from first surface echo to opening of receiver gate

ta = time from first surface echo to closing

of receiver gate

Equation (2) neglects the front surface reflection

of the sample since the cut specimens we employed

did not include surface covering membranes, the usual source of such reflections. The terms in brackets are correction factors to account for

the total attenuation losses of the scattering

material. These losses include absorption of the sound in the scattering tissue between its sur- face and the region from which scattered echoes

are gated into our receiver and measuring circuit,

absorption of sound during the transmitted pulse

and interaction factors which depend on the absorption of the wave during the duration of the re- ceiver gate and the transmitted pulse. The scat- tering coefficient can be found by dividing eq.

(2) by eq. (1) and solving for the coefficient.

The resulting equation is:

E^A^xe .4amR

0 R2Tp4x2

k2 (1)

where = received available electrical power (RMS)

Pq = transmitter electrical power (RMS)

E = transducer efficiency (a function of frequency)

A = transducer area

R = range from transducer to interface

Tp = pulse repetition period

T = transmitted pulse length

X = wavelength

am = pressure attenuation coefficient for propagation medium

k = amplitude reflection coefficient between propagating medium and reflector

In a similar manner, the available power in a wave scattered from a distribution of lossy scatterers,

Pg, can be written [2]:

E2A2S2e .4amR

P 8R'*TDX2a2c

0 P

(2)

nd(e

-2act aCT _aCTK

- e )

2k2R2a2cT

(3)

P s(e-2°'cti _ g-2act2)(gaCT _ g-acx.

The ratio of P^ to Pp is obtained from the change of the input attenuator settings necessary

to make the RMS readings of the pulse from the flat reflector equal the reading of the gated,

scattered waves. Theoretically, this ratio should

be expressed in terms of the open circuit trans- ducer voltages due to the scattered and the re- flected waves. When the attenuator is connected

we read instead a loaded or closed circuit voltage.

Since we use the same transducer and receiver im- pedance for the two waves, the loaded voltage is less than the open circuit voltage by a complex

frequency-dependent factor which depends on the im- pedances in the circuit. This factor is the same

for the scattered wave as for the reflected wave,

however, and hence divides out when the ratio is taken. Therefore, the ratio is the same for the open-circuit as for the loaded condition. The other factors in eq. (3) can be obtained by direct measurement of apparatus dimensions, oscilloscope

time settings and separate measurements of attenuation and velocity within the scattering tissue.

In this investigation, these tissue properties were taken from the published literature [6-8]. The time lapse between the receiver gate and the tissue - saline surface (tj is in the order of 10

to 20 \im. Attenuation losses in this layer as well

as losses in the sample volume are corrected for

by use of eq. (3). The amplitude reflection coef- ficient between the saline and tissue surface was

less than 0.1 and assumed negligible.

Figure 1 is the data collection sheet filled

out by the experimenter at the time of measurement

for one specimen at one frequency. The section of

the sheet before the calibration run consists of equipment parameters. The calibration run allows

154
Date * MARCH, 1977

Data Collection Sheet for the Scattering Experiment

Sign_

Specimen: CALF MYOCARDIUM Wave Frequency: 10 MH2 Temperature of Water Bath: 18 "C Gate Width: 10 us T^: 1( Transducer Position: 34 cm

Sample Position: 52.7 cm

Beam Width: 0.27 cm Calibration Run: Reflector Position

Pulse Repetition Rate; 1 kHz Pulse Width: 4 vs

Reflector Positi

Beam Cross -Sect ion : 0.057 cm^

Attenuator Readi

58

Reference on RMS Meter: 0.003 V, -8 dB RCDistance between Transducer and Sample) = 15.4

a [Attenuation Coefficient for Sample) = .1 c(Velocity of Propagation) = 1.58DATA

1 11.5 2 10 3 11 4 9,5 89 9 8 10 10 11 9.5

IS 11 REDUCED DATA

1 0.017 2 0.023 3 0.015 4 o.Oll

8 0.01 9 0.008 10 0.012 H 0.011 1

15 0.015 Average

5 10.5

12 15

cm -31.19

0.29 Nepers/cm 1,68 -20.59 cm/second -29.19

14 15

SCATTERING COEFFICIENT

0.014 6 0.03 7 0.06

0.038 13 0.06 14 0.038

Fig. 1. Sample data collection sheet. For each specimen at each frequency the data shown were recorded by the experimenter.

us to check for R"2 echo dependence, eq. (1), as proof of far-field conditions, and relates the at- tenuator reading at the surface of the sample to the attenuator reading at a reference position within the tank. Readings from the reference position

are used to monitor system gain. The next four

lines retain data which apply to this particular

experiment. The distance, R, shown was calculated

from the position of transducer and sample carriers

shown at the top of the page and the use of corrections for the distance between the active surfaces

of transducer and sample and the holder position.

Attenuation coefficients and velocity of propagation (inadvertently recorded as cm/second rather

than meters/second used in calculation) were ob- tained from the literature. The numbers shown at the right side of the figure were notes made during

calculation in which various factors in eq. (3) were expressed in terms of dB. Under data we list

the attenuator readings necessary to keep the RMS meter at its reference reading. The result of final calculation of scattering

coefficient, nd, is shown at the bottom of the

page.

3. Results and Discussion

The experimentally determined values of scattering coefficient are plotted in figures 2 and 3.

0.03

0.02

0.01

0.005 -

0.001

^ 0.0005

0.0001

For Myocardium

O Normal • Fixed

till

1 2 3 4 5 6 Frequency (MHz] 10

Fig. 2. Measured backscattering coefficient for

the myocardium as a function of frequency.

Experimental points are the average of

30 to 45 separate measurements on five or

six samples. Bars indicate the standard

deviation vs_. frequency slopes for Rayleigh,

fourth power scattering and for third power

scattering.

One point using tissue fixed with 10 percent for- malin is included for comparison. The data show that liver is a much stronger scatterer than heart tissue at the lower MHz frequencies. Also, the

fixed tissue has a stronger scattering than the normal tissue in each case. The backscattering

from both myocardium and liver increases with fre- quency. Figure 2 shows reference lines drawn through arbitrary points to give the attenuation

slope for both fourth power (Rayleigh) and third power scattering. At the higher frequencies, the heart tissue appears to be approaching approximate

fourth power dependence and the liver tissue less than a third power dependence. It must be recog- nized that the program is still in its early stages

since only a few data points have been taken and positive conclusions, particularly with respect to frequency dependence, are not warranted. Scattering does appear to increase with frequency, however.Since the scattering at 10 MHz is still increasing with frequency (fig. 2), it appears that the

155
0.03

0.02

0.01

01

S 0.005

0.001

For Liver

A Normal Fixed

1

1 2 3 4 5 Frequency (MHz)

Fig. 3, Backscattering coefficient for liver tis- sue as a function of frequency. structure responsible for producing the scattering must be smaller than the wavelength. For a spherical particle it is known that the circumference

must be less than one wavelength, indicating that

the diameter of such tissue elements in liver is less than 30 microns. From these data, it is possible to estimate the contribution to attenuation caused by scattering

alone. In cases where the angular dependence is known the total scattering loss, as, can be found from

4tt

|i ,o)da)

fluence the total attenuation. Since the scattering contribution is a strong function of frequency,

we might expect that at a sufficiently high fre- quency the attenuation of some tissues or tumors might increase at a rate greater than the first

power dependence found by previous investigators

working at lower frequencies. If verified, such behavior could have great importance for tissue

characterization, whether it be done using scattered waves or measurements of attenuation.

References

[1] Reid, J. M. , The Scattering of Ultrasound

by Tissues, in Ultrasonic Tissue Characterization , M. Linzer, ed.. National Bureau

of Standards Spec. Publ. 453, pp. 29-47

(U.S. Government Printing Office, Washington, D.C., 1976).

[2] Sigelmann, R. A. and Reid, J. M., The analysis and measurement of ultrasound backscattering from an ensemble of scatterers excited by sine wave bursts, J. Acoust. Soc. Am . 35^, 1351 (1973).

[3] Shung, K. K., Sigelmann, R. A., and Reid,

J. M. , The scattering of ultrasound by blood,

IEEE Trans, on Biomedical Engineering , BME-23 , 6, 460 (1976).

[4] Shung, K. K., Sigelmann, R. A., and Reid,

J. M. , The Scattering of Ultrasound by Red

8 10 Blood Cells, In Ultrasonic Tissue Characterization , M. Linzer, ed.. National Bureau of Standards Spec. Publ. 453, pp. 207-212 (U.S. Government Printing Office, Washington, D.C.,

1976).

[5] Nicholas, D., The Application of Acoustic

Scattering Parameters to the Characterization

of Human Soft Tissues, in 1976, IEEE Ultrasonic Symposium Proc , pp. 64-69 (1976), No. 76CH 1120-5SU.

[6] Wells, P. N. T., Physical Principles of Ultrasonic Diagnosis (Academic Press, London and New York, 1969]".

[7] Pauly, H. and Schwan, H. P., Mechanism of ab- sorption of ultrasound In liver, J. Acoust . Soc. Am . 50, 192 (1971).

I I I I

(4)

where

Dd

I0

the solid angle

differential scattering coefficient

the Incident direction of the wave

the direction of observation

As a first approximation, let us assume that the scattering from liver is isotropic, then.

4Trn 180

At 10 MHz frequency the attenuation coefficient for liver due to scattering alone is then 0.3 neper/cm.

This loss is about 28 percent of the total attenuation found in the literature [7j~.

This investigation has obtained experimental

evidence that the scattering from within functionally homogenous tissue may be strong enough to in-

[8] Yuhas, D. E., Mimbs, J. W. , Miller, J. G., Weiss, A. N., and Sobel , B. E., Changes in Ultrasonic Attenuation Indicative of Regional

Myocardial Infarction, in Ultrasonics in Medicine , D. White, ed., Vol. 3 (Plenum Press, New York, 1976).

[9] Gramiak, R. , Hunter, L. P., Lee, P. P. K.

,

Lerner, P. H., Schenk, E. , and Waag, K. C,

Diffraction Characterization of Tissue Using

Ultrasound, in 1976, IEEE Ultrasonics Symposium Proc . , pp. 60-63 (1976), No. 76CH 1120-5SU.

^It has to be noted this figure obtained was based

on a very rough assumption. In reality, the scattering from liver is not isotropic as indicated

by the experimental results of Gramiak et_ aj_. [9]. Our measurements do average n over many directions,

so we feel the conclusions are warranted.

156
Reprinted from Ultrasonic Tissue Characterization II, M. Linzer, ed. , National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C., 1979).

DEPENDENCE OF ULTRASOUND BACKSCATTER FROM HUMAN LIVER TISSUE

ON FREQUENCY AND PROTEIN/LIPID COMPOSITION

M. Freese

Radionics Ltd. Montreal, Quebec, Canada

E. A. Lyons

Winnipeg Health Sciences Center Winnipeg, Manitoba, Canada

The dependence of ultrasonic volume backscatter on frequency, lipid and protein content in normal and fatty human (post-mortem) liver tissue was investigated with a view

towards the possible development of a noninvasive quantitative diagnostic test for fatty liver. Mean values of the backscatter coefficient, its range and frequency de- pendence were determined for normal liver in the 1 to 5 MHz range and for fatty liver

at frequencies of 2.25 and 3.56 MHz. The results indicate that frequencies below about

2 MHz should be avoided for quantitative measurements of the backscatter in liver. Although the measurements revealed considerable variation in the backscatter levels of normal liver, the backscatter levels in moderately and severely fatty liver were significantly greater than the normal range. Simple linear correlation of the backscatter

magnitude with the lipid content for 21 samples (10 normal, 8 fatty, 1 cirrhotic, 2 other abnormal) yielded a value of 0.94, significant at the 1 percent level.

Key words: Backscatter frequency dependence; cirrhosis; composition-dependent

scattering; fatty liver; stochastic scattering; tissue characterization;

ultrasound attenuation; ultrasound diagnosis; ultrasonic tissue

scattering.

1. Introduction

Quantitative data on the dependence of ultrasound scattering on the physical structure and composition of tissue is needed to understand the underlying scattering processes, to aid the de- velopment of optimum diagnostic scattering

methods and to serve as a reference in clinical

applications. From the standpoint of these ob- jectives, specifically, the possible development

of a noninvasive diagnostic test for fatty liver

[1]^, this paper describes the results of a series of quantitative measurements of ultrasonic

volume backscatter in the 1 to 5 MHz range for

normal and fatty post-mortem human liver as a function of frequency and protein-1 ipid content.

The results suggest that a noninvasive quantitative test for fatty liver based on the magnitude

of the backscatter is feasible if the in vivo mea- surement problems can be overcome.

2. Methodology

The pulse echo technique and the calibration

procedure employed for the backscatter measurements

^Figures in brackets indicate literature

references at the end of this paper.

have been described in detail elsewhere [2]. Es- sentially, the received backscatter from the tissue

is range gated, passed through either a square-law

or linear envelope detector and integrated; time

varied gain is employed to compensate for sample

attenuation. The measurements are referenced to stainless steel ball bearing targets of known crosssection.

A. Backscatter Parameters

The parameters used to describe the backscattering are the average backscatter coefficient <n> and the average "envelope" backscatter coefficient

<r>, the brackets denoting ensemble averaging. For monochromatic (CW) frequencies, <fi> is identical to the average backscatter cross-section per unit

volume, while for pulses, the difference between

<fi> and the corresponding CW value is dependent on the absorption coef f icient--path length--pulse

bandwidth product and the scatterer frequency

responses [2,3]. (The maximum estimated error due

to the finite pulse bandwidth was approximately

0.1 dB in these measurements.) The envelope back- scatter coefficient <r> is proportional to the average magnitude of the backscatter signal but is normalized to be consistent with the statistical

relation <fi> = <v'^>.

157
B. Signal Processing

Stochastic signal process theoretical results were employed to determine appropriate thresholds

for refining of the raw data. Scattering by the larger blood vessels in the liver poses a problem

because its contribution tends to be largely extraneous to the scattering process of interest. To reduce this interference, the raw data were refined

by rejecting individual measurements with values of

the coefficient of variation y > 0.81, the coefficientjOf variation being defined as y

= {<r'^> - <r>2)^/<r>. The presence of isolated large specular echoes tends to increase the expectation value

of Y (= 0.52 for a random process described by a Rayleigh distribution [4]). Ordinarily, the probability of Y exceeding 0.81 is about 7 percent. The A-scan time averaging employed reduced this probability to 5 percent at 1.1 MHz decreasing to 0.5 percent at 3.56 MHz. To further improve the averaging and avoid the

long delay path required for far-field measurements, the measurements were performed in the near fields of the transducers. The measured values were then converted to equivalent far-field values

using the experimental results obtained by Freese

[5]; the same transducers were used in the present

measurements^. The near- to far-field conversion

factors ranged from + 1.4 and + 1.1 dB at 1.1 MHz

to - 1.1 dB at 4.88 MHz. Time varied gain based on running mean absorption estimates were employed during the measurements with appropriate corrections based on the measured absorptions being applied at the completion

of the experiments [6].

C. Measurements

The ultrasonic measurements on the liver samples

were conducted with two exceptions within one to three days post-mortem. The samples were removed

from the cadaver prior to any postmortem infusion

procedures, and were cut from the anterior portion

of the liver extending below the ribs, with the backplane of the sample sliced roughly parallel to the external liver surface. With the samples im- mersed in physiological saline held at 20 °C and

the ultrasonic beam incident perpendicularly on the external liver surface, the backscatter was measured at two depths extending from 0.6 cm to 1.8 cm, and from 1.2 cm to 2.4 cm below the surface, re- spectively. Four separate measurements were made

at each depth. The total insonified volume averaged about 10 cm^ per sample (5 cm^ per sample in the case of the 1.1 MHz measurements).

The absorptions were measured by means of a sub- stitution technique. To the extent possible, all of the measurements were carried out under doubleblind conditions.

D. Diagnostics and Biochemical Assays

Subsequent to the ultrasonic measurements, the samples (nineteen male, six female) were classified

2The conversion factors (as a function of trans- ducer distance) were determined from scattering measurements on model media containing random scatterers whose dimensions were comparable to tissue cells. Corresponding data obtained for whitefish muscle tissue were generally found to be within 0.5 dB of the model media values.

on the basis of clinical and autopsy data as either

normal or abnormal. The abnormal group (eight male,

four female) was then further categorized according to the lipid content--fatty (seven male, two female) or nonfatty. One normal and one fatty

sample were rejected because of technical problems.

The lipid, protein, and moisture contents of the samples were determined by B. Guy Hunt Laboratories

(Winnipeg) using standard chemical analytical

methods

.

3. Results and Discussion

The average lipid content and physical data for

the normal samples (table 1) are in good agreement

with generally accepted values [7]; however, the protein content appears to be about 20 percent low. Detailed data on the abnormal samples is given in table 2.

Table 1. Composition and physical characteristics

of normal liver samples.

Factor Mean Standard

deviation

Total lipid {%)^ 4.8 1.1 Protein {% nitrogen x 6.25) 14.6 2.1 Moisture {%) 77.5 2.8

Liver weight (g) 1680 280

Age of deceased (y) 55 26 Weight of deceased (kg) 67 9

^Eleven male, one female, ranging in age from

,15 to 93 years. Estimated accurace of liqid analytical deter- mination ± (0.1 {% lipid) + ]%).

A. Normal and Fatty Liver Tissue

Ultrasound Attenuation

The attenuation was measured in eight of the normal samples, and yielded a mean value of 0.64 dB/cm/MHz for the frequency normalized absorption

coefficient, a/f. Possibly reflecting a lower protein content, this value is about 10 percent

lower than the mean value quoted by Wells [8] for

the 3 to 5 MHz range. The average attenuation for

the normal samples at the 2.25, 3.56 and 4.88 MHz frequencies were 1.5, 2.3 and 3.2 dB/cm, respectively.

In the case of the fatty livers, the absorptions

were determined for all but the 7.7 percent lipid

sample (table 2). Excluding the 45.6 percent lipid

sample, which exhibited anomalously high absorption,

the average value of a/f for the fatty livers was 0.86 dB/cm/MHz or about one third greater than for the normal livers. The two extremely fatty samples (table 2) were

rather interesting for, although similar in ap- pearance, they had markedly different absorptions.

The 35.5 percent lipid sample measured 2.74 dB/cm

at 3.56 MHz (six replicates) which is only slightly more than in normal liver, while the 45.6 per- cent lipid sample measured a remarkable 14 dB/cm

(three replicates). The reason for this anomalously high absorption is not certain but it seems to point to the possible presence of gas bubbles in the latter sample, despite the fact that the liver

sample was obtained one day post-mortem. Also, un158
Table 2. Composition and clinical data for the abnormal samples.

Group Total Protein Moisture Clinical information Autopsy results

lipid sex age height weight history Liver Liver

% % % y m kg weight, g appearance

Fatty 7.7 9.0

11.4

14.7

14.9

19.1

35.5 45.6

16.0

14.0

11.4a

13.2

13.2 11.9

10.6 8.4

72.2

71.1

74.3

64.1

71.2

70.1

52.5 44.4

M —

M 26

M —

M 45

M 54

F 69

M 60

M 50

1.63

1.70

1.65

1.80

1.63

1.82

1.68

5269

64

59

66

84

117

alcohol ism

(blood alcohol

150 mg)

alcohol ism

(blood alcohol

16 mg)

alcohol ism

1630

1690

1940

1900 pale yellowish

alcoholic hepatitis, mod. fat

infilt.

1600 pale

3450

5600

yell ow yellow, fatty

Nonfatty 3.6 18.1

3.7 15.2 3.8 16.8

79.8

79.6

78

M 64

9176

1.74

1.56

1.51

82 cirrhosis 1730

40 diabetes (diet) 1220

37 — 730

yellow, firm

nodul ar

adv. cirrhosis

smal 1

Estimate.

like the 35.5 percent lipid sample, the 45.6 per- cent sample was buoyant in the 0.1 N saline solution.

B. Normal Liver Backscatter Coefficient,

Range and Frequency Dependence

The backscatter coefficients and corresponding

envelope backscatter coefficients for the normal samples are plotted as a function of frequency in figure 1(a) and (b). (A number of single data points are also included.) The ranges of the back- scatter coefficients at each of the measurement

frequencies are extremely broad. For example, at 2.25 mHz, <^> varies from 0.17 to 2.9 mm2/cm3—

range of over 12 dB. With the exception of a single low value at 4.88 MHz, which may have been

the result of a faulty measurement, the largest

range is exhibited by the 1.1 MHz values. It is tempting to attribute this primarily to firstorder diffraction effects [9,10] and to the greater statistical fluctuation at this frequency, but

a more careful analysis of the measurements does

not seem to support this view. While large fluc- tuations in the individual measurement values were

observed in many of the samples, when the measurements were repeated on the same sample using slightly different aspect angles and insonified sites,

the mean values seldom differed by more than 1 or

2 dB. Furthermore, if we take into account the dimensions of the blood vessels in terms of wavelength, the decrease of the highest <fi> values be- tween 1.09 and 2.25 MHz is consistent with oblique

incidence scattering by cylinders of corresponding

radii in the transition region from Rayleigh to geometrical scattering ( i.e ., the vessels will tend to scatter specularly with increasing frequency). Since the larger blood vessels tend to radiate towards the liver surface, the oblique

aspect angles would be more probable in our measurements resulting in an effective decrease in the backscatter at the higher frequencies. In contrast

to the vessel orientations, the orientations of the liver lobule "fascia" appear essentially random

over the extent of the insonified volumes. This

would lead one to expect the ensemble averaged

backscatter to be independent of aspect angle. In attempting to answer the question concerning the relative contributions of the liver lobules, blood vessels and other liver structures to the overall scattering process [11], our results would seem to indicate that scattering by the larger vessel in- homogeneities, if present in the insonified volume,

will tend to dominate the backscatter below about

1.5 MHz. The average frequency dependence of <fi> over the 2.25 to 3.56 MHz range is given by f0-8(fig. 1(a)),

decreasing to about f° in the 1.09 to 2.25 MHz in- terval, and increasing to f^-^ between 3.56 and 4.88 MHz (if we exclude the 4.88 MHz value for the borderline sample). While there are too few values

to provide more than a rough estimate of the fre- quency dependence in the latter two intervals,

these values are in good agreement with those ob- tained by Nicholas [12] using spectral analysis.

The relatively low frequency dependence observed

illustrates the effect that the presence of even a relatively small number of "geometric! region" scatterers can have on the composite frequency de- pendence. For this reason the frequency dependence

of diffuse volume backscatter may not be as aseful

a parameter for some tissue diagnostic applications

as, the magnitude, the angular dependence or the absorption.

159
10

2J3 3D 5D

Frequency (MHz)

(a)

70 2.0 3JD

Frequency (MHz)

(b)

50 7.0

Fig. 1. (a) Backscatter coefficients as a function of frequency for samples of normal liver tissue. The logarithmic mean values of <n> for the 2.25 and 3.56 MHz

data are indicated by connecting heavy barred lines. The dashed lines correspond to ± 6 dB about the logarithmic means and bound essentially all of the measured values in this frequency range. The sample with the lowest back- scatter coefficients suggests a borderline sample. Its moisture content of

81 percent was second highest of the normal samples,

(b) Corresponding envel ope backscatter coefficients.

Similar comments apply to the envelope backscatter coefficient shovm in figure 1(b) although the frequency dependence is only half as great (or less

if the scattering process is inhomogeneous) . The principal advantages of using <r> are that it sim- plifies the electronics requirements and is less sensitive to isolated large extraneous echoes thereby reducing the consequent error. For these reasons, we will consider mostly <r> instead of <n> in the following paragraphs. However, to ob- tain an estimate of <n> one need only compute

(1 + Y^)<r>2 using the average measured value of

0.6 for Y instead of the theoretical value of 0.52.

C. Backscatter Dependence on Lipid and Protein Content

Values of <r> were compared with the lipid and protein contents of both the normal and abnormal

samples. Figure 2 shows the 2.25 MHz values of

<r> as a function of the protein content (P) for

normal samples. The value of the simple linear

correlation coefficient rj-p = 0.776 and is significant at the 1 percent level (t-test assuming rpp = 0; ten samples). Comparable results were obtained

at the higher frequencies. This implies that in normal liver inherent differences in the protein

content may result in <r> varying as much as 9 dB.

(Conversely, taking the protein into account and assuming the scattering processes add in quadrature,

the 12 dB range of the 2.25 MHz values in figure

1(a) and (b) can, in principle, be reduced by 4.5 dB.)

2.0

0.0

Fig. 2

fr = 2.25 MHz

14

Protein

16

(7o nitrogen

20

6.25)

Dependence of <r> on protein content in normal liver; the correlation coefficient

r^p = 0.776.

160
No significant correlation was observed at 1.1 MHz. This fact coupled with the previous observations would seem to indicate that frequencies below

about 2 MHz should be avoided for quantitative mea- surements of volume backscatter from liver tissue.

In contrast to the correlation of the backscatter with protein content, the correlation of <r> with the lipid content of the normal samples was

not significant. The presence of glycogen and other minor hepatic constituents (moisture tends

to correlate inversely with lipid and protein) has been neglected but their contribution is not likely

to be significant in normal liver. The effect of the lipid becomes apparent in the fatty liver samples, which ranged from 7.7 to 45.6 percent lipid. The backscatter and lipid content

(L) are highly correlated (rp^ = 0.980 and 0.978

at 2.25 and 3.56 MHz, respectively) and suggest a roughly linear relationship between the two as shown in figure 3 for the 2.25 MHz values. However, in view of the limited number of mea- surements and the possibility that the 45.6 percent

lipid sample may have contained gas bubbles, the latter is probably at least partly due to coincidence since a linear dependence for a lipid content aoproaching 50 percent would seem unlikely.

The histological appearance of mildly and severely fatty livers are shown in figure 4(a) and (b). It can be seen from these pictures that the structural changes that occur in hepatic tissue with in- creasing lipid content span the spectrum from nearly

normal to grossly abnormal. If we combine the two

Fig. 4. (a) Mildly fatty liver in an alcoholic. Many of the hepatocytes contain large lipid globules

(clear areas in the stained cytoplasm). Magnification 25X.

(b) Severe fatty liver in an alcoholic. The nuclei of the cells are displaced by large lipid

globules; little cytoplasm remains. Magnification 25X.

5,0

4.0

3.0

20

1,0

0.0 20 30

Total Lipid ( % )

40 50

Fig. 3 Dependence of <r> on lipid content in fatty

liver; the correlation coefficient rpL = 0.980; ff = 2.25 MHz.

groups of samples and take the protein content into

account, the multiple linear regression equation

for <r> at 2.25 MHz becomes <r> = -1.4 + O.IOL + 0.12P with rp Lp

= 0.966. This indicates that the effective scattering contributions by the protein

and lipid (either directly or indirectly) are roughly comparable on a percentage weight basis, with

the protein contributing about 40 percent more to

<fi> at this frequency than the lipid for equal per161
cent.ages of the two constituents. The corresponding result at 3.56 MHz was <r> = -1.9 + O.IOL + 0.17P with rp |_p = 0.939. In this case, data was available for'only eight normal and six fatty

samples. Additional measurements will be needed to establish if the difference in the relative contributions implied by these two regressions (and there- fore the frequency dependence of the normal and fatty samples) is signif icaitit. For predictive purposes we require the percent

lipid as a function of <r> and the percent protein.

Moreover, the remaining abnormal nonfatty samples,

listed in table 2, should also be included in the regression. The resultant linear regression equation obtained at 2.25 MHz was L = 15.1 + 9.2<r>

-1.2P, with r|_ j,p = 0,971. This regression with

18 degrees of freedom (21 samples) and F-test value

= 157 is significant at the 1 percent level. Com- paring it to the previous 2.25 MHz regression, the effect of the additional samples is seen to be minimal

.

5 0 (-

0 10 20 30 40 50

Total Lipid ( % )

Fig. 5 Dependence of <r> on the lipid content

for the combined group of normal and ab- normal samples; the correlation coefficient rj,^ = 0.943.

In potential diagnostic applications the percent

protein would most likely not be available. The re- sultant simple two variable linear regression equation obtained, L = -442 + 11.0<r>, is graphed in figure 5. The correlation coefficient = 0.943

is essentially the same as when the nonfatty ab- normal samples were excluded. Figure 5 shows that

the backscatter coefficients are substantially

greater for the moderately and extremely fatty

livers. The corresponding regression at 3.56 MHz, based on 17 samples, resulted in L = -6.2 + 11.3

<r> and rL^ = 0.914. In view of the limited number

of samples and the large weighting by the two ex- tremely fatty livers, these regressions can only be considered preliminary. Nevertheless, they seem to suggest that a simple quantitative diagnostic test

based on the magnitude of the backscatter is feasible in principle.

4. Summary

Experimental values of the volume backscatter

coefficients and estimates of their distribution

and frequency dependence were obtained for normal

liver. These were discussed and compared from the point of view of the underlying scattering processes, the liver composition and potential diagnostic

requirements. The results indicate that in the case of liver, frequencies under 2 MHz should be avoided for quantitative diagnostic backscatter

measurements. Significant correlations of the backscatter with

protein content were observed in normal liver and with both protein and lipid content in abnormal

fatty liver. In the case of the latter, regressions

significant at the 1 percent level were obtained.

Acknowledgment

This work was supported in part by the Depart- ment of Environment, Freshwater Institute, Winnipeg,

Canada

.

References

[1] Wells, P. N. T., McCarthy, C. F., Ross, F. M. G., and Read, A. E. A., Comparison of A-scan

and compound B-scan ultrasonography in the diagnosis of liver disease, Br. J. Radiol . 42 , 818-823 (1969).

[2] Freese, M. and Hamid, M. A. K. , Lipid Content Determination in Whole Fish Using Ultrasonic

Pulse Backscatter, 1974 Ultrasonics Symp . Proc , IEEE Cat. #74 CHO-896 15U, 69-76 (1974).

[3] Freese, M. , Quantitative diagnostic measurements of ultrasound tissue scattering (in

preparation).

[4] Ol'shevskii, V. V., Characteristics of Sea Reverberation (Consultants Bureau, New York,

1967).

[5] Freese, M. , Comparison of Near- and Far- Field Measurements of Diffuse Ultrasonic Tissue Volume Backscatter, 1975 Ultrasonics

Symp. Proc . IEEE Cat. #75 CHO-994 45U, 33-

36 (1975).

[6] Freese, M. and Lyons, E. A., Ultrasonic back- scatter from human liver tissue; its de- pendence on frequency and protein/1 ipid com- position, J. Clin. Ultrasound (in press).

[7] Schiff, L., ed.. Diseases of the Liver, 3rd

ed. (Lippencott Co. , New York, 1969).

[8] Wells, P. N. T., Physical Principles of Ultrasonic Diagnosis (Academic Press, London

and New York, 1969).

[9] Nicholas, D. and Hill, C. R., Acoustic Bragg

diffraction from human tissues. Nature 257 , 305 (1975).

162
[10] Lele, P. P., Mansfield, A. B., Murphy, A. I., Namery, J., and Senapati, N., Tissue Characterization by Ultrasonic Frequency-Dependent

Attenuation and Scattering, in Ultrasonic

Tissue Characterization , M. Linzer, ed.. National Bureau of Standards, Spec. Publ.

453, pp. 167-196 (U.S. Government Printing

Office, Washington, D.C., 1976).

[11] Gramiak, R., Hunter, L. P., Lee, P. P. K., Lerner, R. M. , Schenk, E., and Waag, R. C,

Diffraction Characterization of Tissue Using

Ultrasound, 1976 Ultrasonics Symp. Proc , IEEE Cat. #76 CH1120-5SU, 60-63 (1976).

[12] Nicholas, D., The Application of Acoustic

Scattering Parameters to the Characterization of Human Soft Tissues, 1976 Ultrasonics

Symp. Proc , IEEE Cat. #76 CH1120-5SU, 64-

69 (1976).

163

Reprinted from Ultrasonic Tissue Characterization II, M. Linzer, ed.. National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C., 1979).

ULTRASOUND BACKSCATTERING FROM BLOOD: HEMATOCRIT AND

ERYTHROCYTE AGGREGATION DEPENDENCE

M. Hanss and M. Boynard

Laboratoire de Biophysique

UER Exp^rimentale de M^decine et de Biologie

74, rue Marcel Cachin - 93000 Bobigny

and

UER Biom^dicale des Saints-Peres

45, rue des Saints-Peres - 75006 Paris

The ultrasound back-scattering of blood has been shown to be increased when

the erythrocytes sedimentation rate is high. Moreover, in this case, temporal

fluctuations of the back-scattered intensity have been also demonstrated. To explain these results, a simplified theory of ultrasound back-scattering by blood is presented. The model of the blood structure used is: the erythrocytes

are associated to form spherical transient aggregates having the same cell number, m. The acoustic wave is scattered by these clusters called "scattering

units." The scattered intensity is calculated for one scattering unit taking a spherical elastic model, then for a blood unit volume, when the hemotocrit H is very low. It is found that the back-scattered intensity is proportional to H and to m. When H is not negligible, a simplified statistical theory is proposed

The main result is that the back-scattered intensity is still proportional to m

but that it passes through a maximum value when H get near 0.3. An explicit

relation between the mean relative value of the intensity fluctuation, H and m

is given. Therefore, the aggregation state of blood can in principle be determined through ultrasound scattering studies. Further theoretical developments are in progress so as to take into account the distribution of the number

of erythrocytes in each kinetic units and the variation of this number with H.

Key words: Blood erythrocytes aggregation; blood hemotocrit; ultrasound back- scattering from blood.

When an ultrasound echographic probe is placed

on top of a vertical cylindrical tube filled with

blood, it has been found that the echo pattern of

the sedimenting blood varies according to its sedimentation rate [1]^. For high sedimentation

rate samples, the mean back-scattered intensity

is larger; furthermore the echo amplitude at a given depth in the erythrocyte column presents

characteristic temporal fluctuations. We wish to present a simple theoretical approach in order to explain these phenomena. Though the scattering

of ultrasound by blood is increasingly used in clinical medicine, the fundamental data on this

property are very scarce, and mainly due to Reid

and co-workers [2-5]. Fluctuations (temporal and spatial) in the echo amplitude have also been re- ported by Atkinson and Berry [6]. However, none

of these studies can give a straightforward explanation of our experimental results.

^Figures in brackets indicate literature

references at the end of this paper.

Blood Model

The red blood cell (RBC) concentration is usually defined by the hematocrit H, that is, the time average of the RBC volume fraction in a given

blood volume. For a normal blood sample, H is rather large (H = 0.45) so that the RBC interact

each with the other. We will describe these in- teractions by assuming that m RBC are mechanically correlated during a period tc larger than the ultrasound pulse, giving rise to a transient ag- gregate which we assume to be spherical, with

radius A; this dimension could be thought of as a correlation length. We will also suppose that each aggregate has the same number m of RBC. The ultrasound wave is scattered by these aggregates

which therefore will be called the scattering

units (S.U.).

If V is the number of S.U. per unit volume and

V|^ the RBC volume, the usual hematocrit number H is given by:

H = mv,\) n)

165
However we are interested in the volume fraction

of the S.U. and not the static hematocrit H. We will introduce a "dynamic" hematocrit number H' as follows:

H' = vv'

su

where viy is the excluded volume of the S.U.

(fig. 1) which takes into account the S.U. volume,

vsu. and the trapped plasma between the S.U.:

da = — dfi

i

In back-scattering experiments, the angles 6 and (j) values are 180° and 90° respectively (fig.

2). The detecting solid angle depends on the probe surface S and the distance x between the probe and the S.U. One can take into account

these parameters by introducing a geometrical

factor g(x) = S/x^.

su su

where p^^ is a dimensionless number greater than

or equal to 1. The volume of one S.U. must also

take into account the trapped plasma inside the

S.U.:

su "^^hPh

where p^ is another dimensionless quantity greater than or equal to 1. If the RBC were perfectly

packed without free volume for the plasma, pj^

and ph would be equal to 1. For an imperfect

packing, they are greater than 1. The dynamic

hematocrit H' is greater than H because in the course of their motions the RBC's and S.U.'s carry with them a fraction of the plasma. Its value

is:

H' 'hPhPh

Using this model, the S.U. radius is given by:

A

= 4^ "^^Ph

ll3

(2)

(3)

Trapped plasma

Inside the S.U. one S.U.

' Trapped

, '

' plasma between

^the S.U.

Fig. 1. Blood model used, showing the transient

spherical aggregation (scattering unit

S.U.).

Ultrasound Back-Scattering by One S.U.

Let io be the incident wave intensity per unit

area of a spherical scattering center, with radius A smaller than the wavelength. The scattered

intensity per unit solid angle in the direction e is i[). The detecting solid angle being du, the differential scattering cross-section is:

Emetting probe

Receiving probe

\

Fig. 2. Scattering coordinates.

We can only measure intensities emitted and received by the probe, Iq and Iq. They differ

from io and ip because of the attenuation of the incident and scattered beams by the medium be- tween the probe and the S.U. They also differ

because the ultrasonic field varies with distance.

We can lump all these factors in a general function of the distance x, G(x) so that one can write

(4)

The factor G(x) is not essential in our final results. It could be determined by a substitution method as described, for instance, by Sigel- mann and Reid [3]. The differential scattering cross-section is known for some simple models [7]. Using the re- sults for an elastic sphere, the back-scattered

intensity is finally:

I,G(x)

w'^A^ 9c^ V C2p

+ 3 2p + P.

(5)

where c and Cg are the sound wave velocities in the S.U. and the plasma respectively, and p and

Pp the corresponding densities. We assume that the S.U. coefficients, c and p, are identical to the RBC coefficients, cp, and p^.

Back-Scattering by Whole Blood

The scattering of dense particle medium is a complex theoretical problem which has already

been treated by Twersky [8-10] and applied by

Shung, Sigelmann and Reid [4,5]. The following

simplified approach can be used. Let s' = qjuS

be the functional diametral area of one S.U.,

166
where s is the diametral area of one S.U. and qsu is a dimensionless number, usually greater

than 1, and which is characteristic of the S.U. packing. For a spherical S.U. one has:

s' = qsu'fA^. We are interested by the intensity I^x scattered by a cylindrical volume element having the same axis as the ultrasonic wave with height Ax and base area S at a distance x from the probe

(fig. 3).

ProbeIf 1

cylindrical tube

tilled with blood

Fig. 3. Simplified diagram of the sedimentation

tube with the echographic probe.

We will consider in this volume an elementary

slab (S, 4A) defined by the two sections with

distances (x + 2A) and (x - 2A). The maximum

number of S.U. which can exist in this slab is 2N = 2S/s'; we will call N the number of sites,

each composed of two cells, which can be occupied

by 0 or 1 or 2 S.U. Figure 4 shows a simplified slab with 7 sites

occupied in such a way that the ensemble average

of the hematocrit is 4/7. Eq. (5) only applies

to the sites "f"; for the other ones, eq. (5) in- dicates that the scattered intensity is zero.

2A

X +2A

Fig. 4. Statistical model. The slab (x - 2A,

x + 2A) has 7 sites with an occupation

probability of 4/7. Only the "f" emplacements have a favorable configuration for backscattering.

By a simple calculation in order to find the probability that a given site is in a favorable

configuration (as regards back-scattering), it can

easily be shown that the number of sites, Nf, which

have a favorable configuration in an elementary

slab 2A is:

NH' (1 - H' ) (6)

Assuming that Iq and Iq do not depend on x in the volume Ax (this point is justified by the low values of the attenuation and reflexion coefficients in blood), each slab 2A back-scatters with

the intensity:

I^^ = NH'(1 - H')Ip (7)

As there are Ax/2A elementary slabs in the in- terrogated volume (Ax, S), one has:

Iax

Ax ^(1

2A H')I

D

This expression can be further transformed by

replacing N by S/s', and H' by PsuPhH. using eq.

(5) for I[). As we have used an impenetrable

spheres model with a cubic packing, the factor

Psu/Psu is equal to 3/2. Finally one obtains:

Ax G(x)Kmv^p2H(l - P^Psu") (8)

In this derivation we have added the individual

intensities and not the wave amplitudes, thus ignoring the interference problem. This is justified in a first approach because the distribution

of the scatterers in the interrogated volume is random.

Back-Scattering Fluctuations

Examination of eq. (8) shows that the only

fluctuating quantities are H or H' (the packing

factors do not fluctuate as we have assumed a spherical model for the aggregates. It is also assumed in the model that m is constant. For an elementary variation dH' of H' in a slab (2A), the scattered intensity will vary according to eq.

(7):

^^2A " ^d"^'^

" 2H' )dH'

The relative mean quadratic fluctuation F2A

is defined as follows:

<(dl2A)'>^'

2A <I2A>

and can be written:

'^2A <H' (1 - H' )>

^

2A a<(dH' )2>i/2

167
If one transforms dH' into dv, one obtains:

As in the initial model the site occupancy probabilities are independent, the S.U. dis,tribution

obeys Boltzmann statistics and <(dv)2>^ is given

by [11]:

<(dv)2>i/2 = (2AS)i'2

Therefore F2/\ can be written:

= a(2ASv^p^p^^m)V2<H.>i/2

The corresponding fluctuation coefficient for the blood column Ax is F^^: <(dl^^

Assuming independent fluctuations for the Ax/2A elementary slabs in Ax, the total fluctuation is given by:

to = 2 IT 5.2 10^ s'l Po = 1.078; p = 1.223

Co = 1550 m s-i; c = 1610 m s"! G(x) = 1 (negligible attenuation)

m =2 (slight aggregation)

—theoretical curve

, SHUNG et al results

10 M Ml 40 50 60 H( percent)

'^.-C^Wlu^'y (9)

<H'>ife<(l - 2H')2>ig

<H'(1 - H')> Ax^

This relation shows that the standard deviation

of the fluctuations, given by F^^ *^ax^' ''^ P'"'^" portional to m''/^.Ax''2.

Discussion

In our model, the interactions between RBC

lead to monodisperse spherical aggregates. In- deed, microscopic observations show a '^eversible aggregation in normal and pathological blood [12]. Our picture may be oversimplified, as these transient aggregates are polydispersed in dimension and shape. We feel however that introducing

polydispersity function would not change our treatment fundamentally.

Eguation (8) is very similar to a previous re- sult obtained by Shung et al. [4] using Twersky's

theory [8-10]. However, as this theory predicts

that the back-scattering goes through a maximum

for H = 0.50, Shung et al . introduced an empirical fitting constant as their experimental re- sults showed a maximum for hematocrit values be- tween 0.25 and 0.30

We have plotted on figure 5 their experimental

results and a theoretical curve obtained by using

eq. (8) and the following values:

Fig. 5. Back scattering of whole blood as a function of hematocrit: correlation between

the experimental results of Shung et al . [4,5] and theoretical values calculated

according to eq. (8).

Shung et al

.

'

s

scattering coefficient a is identical to:

I SAx

The quantitative agreement between the two re- sults seems satisfactory, our treatment can di- rectly explain the experimental results of Shung

et al. [4,5]. The aggregation dependence of the scattered

intensity by whole blood is also shown in eq. (8) and has recently been demonstrated by Shung and Reid [13].

In order to derive the fluctuation coefficient,

it has been assumed that the probability of finding a S.U. in a given elementary volume is proportional to the S.U. number concentration and in- dependent of the occupation state of the neighbouring elementary volumes. This would be the case

for pure Brownian motion. However, as has already

been pointed out by Atkinson and Berry [6], the thermal diffusion of RBC's is much too slow (10^ s) to travel one wavelength.

Two other mechanisms could be postulated. The first one is convection streams which break apart,

associate, rotate and translate the aggregates,

so that the occupancy of a given elementary volume | fluctuates to and fro in the occupation probability.

The second explanation can be found in the dissociation-association kinetic of the S.U. In that

| case it is m which would fluctuate. Further ex- I

168
periments are needed in order to assess the respective importance of the mechanisms.

Summary

The ultrasound back-scattering of blood has been

shown to be increased when the erythrocyte sedimentation rate is high (fig. 1). Moreover, in this

case, temporal fluctuations of the back-scattered

intensity have also been demonstrated. In order

to explain these results, a simplified theory of ultrasound back-scattering by blood is presented.

The following model of the blood structure is used: the erythrocytes are associated to form

spherical transient aggregates having the same cell number, m. The acoustic wave is scattered by these

clusters called "scattering units".

The scattered intensity is calculated for one

kinetic unit taking a spherical elastic model,

then for a blood unit volume, when the hematocrit

H is very low. It is found that the back-scattered

intensity is proportional to H and to m. When H is not negligible, a simplified statistical theory is proposed. The main result is that

the back-scattered intensity is still proportional

to m but that it passes through a maximum value

when H gets near 0.3. An explicit relation between the mean relative

value of the intensity fluctuation, H and m is given.

Therefore, the aggregation state of blood can

in principle be determined through ultrasound scattering studies. Further theoretical developments

are in progress so as to take into account the dis- tribution of the number of erythrocytes in each kinetic unit and the variation of this number with

H.

[8] Twersky, V., On scattering of waves by random

distribution: I. Free space scatterer

formalism, J. Math. Phys . 3^, 700 (1962).

[9] Twersky, V., On scattering of waves by random

distribution: II. Two space scatterer

formalism, J. Math. Phys . 3, 724 (1962).

[10] Twersky, V., Acoustic bulk parameters of random volrame distributions of small scat- terers, J. Acoust. Soc. Am . 36, 1314 (1964).

[11] Landau-Lifchitz, Statistical Physics (Mir

ed., Moscow, 1967")^

[12] Schmid-Schonbein, M. , Gallasch, G., Gosen,

J. v., Volger, E. , and Klose, M. J., Red

cell aggregation in blood flow, Klin. Wschr . 54, 149 (1976).

[13] Shung, K. K. and Reid, J. M., Ultrasonic

detection of erythrocyte aggregation, 29th ACEMB Sheraton-Boston, Boston, Massachusetts,

6-10 November 1976.

References

[1] Hanss, M. , Boynard, M. , and Perrin, J. Erythrocyte sedimentation by an echographic

method, Biomedicine 25 (3), 81 (1976).

[2] Reid, J. M., Sigelmann, R. A., Nasser, M. G., and Baker, D. W. , The Scattering of Ultrasound

by Human Blood. Proceedings of the 8th Inter- national Conference in Medicine and Biological

Engineering (1969).

'j [3] Sigelmann, R. A. and Reid, J. M. Analysis

and measurement of ultra-sound backscattering from an ensemble of scatterers excited

by sine wave bursts, J. Acoust. Soc. Am . 53,

1351-1355 (1973).

[4] Shung, K. K. , Sigelmann, R. A., and Reid,

J. M. , The scattering of ultrasound by red blood cells, Applied Radiology 77 (Jan.,

Feb. 1976).

[5] Shung, K. P., Sigelmann, R. A., and Reid,

J. M., The scattering of ultrasound by

blood, I.E.E.E. trans, on biomed. Enain.

BME 23 (6), 460 (1976).

^

[6] Atkinson, P. and Berry, M. V., Random noise

in ultrasonic echoes diffracted by blood,

J. Phys. Math. Nucl . 7 (11), 1293-1302 (1974).

[7] Morse, P. M. and Ingard, K. U., Theoretical

Acoustics (McGraw Hill, New York, 1968).

169

CHAPTER 6

TUMOR DOPPLER SIGNATURES

171

Reprinted from Ultrasonic Tissue Characterization II, M. Linzer, ed., National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C., 1979)

TUMOUR DETECTION BY ULTRASONIC DOPPLER BLOOD-FLOW SIGNALS

P. N. T. Wells, M. Halliwell, R. A. Mountford,

R. Skidmore, A. J. Webb and J. P. Woodcock

Bristol General Hospital and Bristol Royal Infirmary

Bristol, United Kingdom

An in situ cancer is avascular and harmless. Vascul ari sation is necessary before

a tumour is potentially capable of rapid growth. Distinctive continuous-wave ultrasonic

Doppler signals have been obtained transcutaneously from malignant breast tumours. Similar signals have been detected from abdominal malignancy, by means of a pulsed

Doppler. These signals may form the basis of a practicable method of screening for breast cancer, and of improving the accuracy of cancer diagnosis.

Key words: Blood flow; breast cancer; diagnosis; Doppler; screening; ultrasonics.

1. Tumour Blood Flow

A single aberrant cell is almost certainly the origin of every solid malignant tumour. This

cell divides to form a colony of malignant cells, called an i_n situ cancer. An ijT_ situ cancer is avascular and harmless, and cannot grow beyond

the volume limited by diffusion of nutrients and wastes. The event which converts an in_ si tu cancer into a "tumour" is apparently the release

by the malignant cells of a diffusable chemical

substance, called the "tumour angiogenesis factor" [1]^. Once the tumour is vascul ari sed it is potentially capable of rapid growth. The blood flow in normal tissue like that of the breast is

in the range 10 to 30 ml min-i kg-^ [2]. The blood

flow in lymphomas is about 380 ml min~^ kg"^, in differentiated tumours, 140 ml min"^ kg"^, and in anaplastic tumours, 110 ml min"^ kg"i [3]. The possibility that changes in blood flow might be used to detect malignant tumours is dis- cussed in this paper, and some preliminary results

are presented. Most of the experimental work was

done with breast lesions, because of their acces- sibility and the potential importance of the method

in screening for breast cancer.

The blood vessels which serve the breast are il- lustrated in figure 1. The mass of a typical fe- male breast is about 0.3 kg. Assuming that the three main arteries each serve one third of the breast, the normal flow rate in each artery would

be around 1 to 4 ml min"^. A malignant tumour with

diameter of 20 mm would require a flow rate of about 0.5 to 1.5 ml min*^. Therefore, in an in- dividual, there might be a significant difference

between the flow in an artery supplying a tumour

and part of the breast, and the flow in the cor- responding artery serving the other normal breast. There is at present no non-invasive method of measuring blood flow volume which would enable this

^Figures in brackets indicate literature

references at the end of this paper.

Fig. 1. Principal blood vessels serving the right

breast.

to be tested. It may be that a change might occur

in the pulsatility index of the flow [4], but this

would be difficult to establish since every pair of arteries (serving the two breasts) would need to

be studied.

In biomedicine, liquid flow through small ducts

has previously been recognised in backscattered

ultrasonic Doppler frequency-shifted signals [5] in two situations. The first of these is in the placenta [6] and the second, in the fetal lung during breathing [7]. Recently it has been reported

that characteristic blood flow signals are asso- ciated with neovascular flow in malignant tumours

[8j and additional data are presented in this paper.

2. Breast Investigations

Breasts were examined as illustrated in figure

2. A regular continuous-wave ultrasonic Doppler

blood-flow detector [5] was used. The hand-held

probe had a diameter of about 10 mm, and contained

two separate 8 MHz transducers, one for transmitting and one for receiving. The transducers were

173
HJNO-Hilll HKOBl

IRANSMIIIINC

IfiiHSOUCtB

Fig. 2. Method of obtaining ultrasonic Doppler

blood-flow signals from the breast.

(a)

(kHz)

(b)

fREOUEHC? Ikm)

FREOUEdCt

IkHi]

aligned so that the volume sensitive to motion ex- tended axial ly beyond the end of the probe. For each patient, the Doppler signals obtained from over the lesion were compared with those from the corresponding site on the opposite breast. Both breasts of each normal individual were thoroughly

explored to search for Doppler signals which were

asymmetrical and characteristic of neither normal arterial nor venous flow. The results are summarised in table 1. Sono- grams of the signals recorded from a normal mam- mary artery, a malignant breast tumour, and tis- sues at the corresponding site in a normal breast,

are shown in figure 3.

Table 1. Ultrasonic Doppler signals obtained from breast in various clinical conditions.

Confirmed diagnosis^ Number of patients with

neovascularisation signals

None Weak Strong

Normal 2 0 0 Mastitis 1 0 0 Mammary duct

pa pi 1 lomatosis

1 0 0

Mammary duct ectasia2 0 0

Benign mammary

dysplasia

2 1 0

Cyst 1 2 0

Fi broadenoma 0 1 0 Lymphoma 0 0 1 Carcinoma 0 0 2

Number of patients = 16.

3. Investigations of Other Tumours

Signals apparently associated with malignant

neovascularisation have been detected in the ab- domen. Two-dimensional scanning was used to locate

a pancreatic tumour. The ultrasonic beam of the scanner probe was directed through the tumour.

The probe was then connected to a 2 MHz pulsed

Doppler [5]. Blood flow signals were detected when

the Doppler was range-gated into the tumour.

Fig. 3. Sonograms of ultrasonic Doppler blood-flow

signals obtained from the breast, (a) Normal individual: branch of internal mammary artery; (b) malignant tumour; and

(c) flow at site corresponding to (b) in other breast of the same patient.

4. Discussion

A. Breast Cancer

Breast cancer is the most common malignancy in Western women. In the United Kingdom, breast cancer affects at least 80 in 100,000 females;

it kills 1 in 50 women, 1 in 75 women between the ages of 35 and 60 years, and 1 in 3,500 females

of all ages every year. Breast cancer is the main cause of all deaths among women between the ages of 40 and 44. Extrapolating from 1973 U.S. data [9], the present economic cost of breast cancer in the United Kingdom is in the order of

$40 million per year (and $200 million per year

in the United States).

Earlier diagnosis and treatment of breast cancer

might improve the survival time of the patient

[10]. If the cancer is removed whilst it is still

in situ , the patient is cured. The next step in the natural progress of the disease is when the growing cancer begins to invade the surrounding

tissue. For a time, the cancer cells remain localised. If diagnosed and treated at this stage, the 5-year survival rate is around 85 percent. If un- treated, the cancer metastases, with regional in- volvement of the lymph nodes which drain the breast,

and the 5-year survival rate falls to about 53 percent. If left untreated, metastases occur in more distant parts of the body. This advanced cancer is virtually incurable, although the time taken for

the patient to die is variable.

The treatment of patients with early breast cancer is more successful than that of those in whom the disease is advanced. Breast cancer is usually discovered when the patient herself feels

a lump. Even in a "suitable" breast, the smallest

lump which can be detected by manual palpation is not much less than 10 mm in diameter [11]. The risk of the presence of distant metastases from a tumour with a doubling time of 1.5 months increases from 22 percent when its diameter is 1 mm, to 43 percent, when it is 10 mm. Once a lump has been discovered in a breast, present diagnostic procedures are already adequate, although there may be

174
disagreement about the best course of treatment if the lump is a malignant tumour. The possibility

exists, howt.^r, that diagnosis of pre-symptomatic

lesions by an effective screening procedure might

lead to a reduction in breast cancer mortality as

a result of earlier treatment. Mammography, either conventional or xeroradiographic, seems to be the best contemporary method

of detecting early breast cancer [12]. Unfortunately, however, mammography as a screening procedure

confers no benefit on women who are well and under

the age of 50 [13]. In these women only 19 percent

of cancers would not have been detected without

mammography, and so the benefit (which has to be set against the risk of radiation-induced cancer

as a consequence of mamography [14]) is small.

Even if technical developments were to result in a reduction in x-ray exposure to an acceptable level,

the logistics of interpreting the vast number of mammograms which would be obtained in a screening

programme pose apparently insoluble problems of manpower, boredom and expense. Thermography has been used to study breast

tumours [15] but initial enthusiasm for the method

has declined. Thus, in a series [16] of 2523 volunteers, 1 patient out of 4 who developed cancer

within 18 months of the examination was detected by

thermography; 344 had abnormal or suspicious scans,

but no abnormality. These and other results are so poor that the method (at least when used alone)

seems to have no role in screening for breast

cancer. Conventional two-dimensional pulse-echo ultra- sonography is capable of producing images of the breast of quite high resolution [17-20]. Un- fortunately, the normal breast is a complex ir- regular structure, the recognition without prior

knowledge of small tumours is very unreliable, and there seems to be no way of automating the analysis

of the vast number of scans which would result from

even only a modest screening programme. The re- sults reported in the present paper indicate that characteristic Doppler signals may be a cancerspecific ultrasonic tissue signature. They might

form the basis of a practicable breast cancer

screening method.

B. Other Tumours

Cancer-specific Doppler signals could have an important place in the interpretation of the in- adequate data which sometimes results from conventional diagnostic tests such as radiography,

echography, scintigraphy, and computerised tomography. These opportunities, which are quite

distinct from screening, include, for example,

the differentiation of small solid and cystic

renal lesions, and the differentiation of ophthalmic tumours and organised haematomas.

References

[1] Folkman, J. and Cotran, R. , Relation of Vascular Proliferation to Tumor Growth, in International Review of Experimental Pathology , C. W. Richter and N. A. Epstein, eds.. Vol. 16,

pp. 207-48 (Academic Press, New York, 1976).

[2] Woodcock, J. P., Theory and Practice of Blood Flow Measurement (Butterworths , London, 1975).

[3] Mantyla, M. , Kuikka, J., and Rekonen, A., Regional blood flow in human tumours with

special reference to the effect of radiotherapy, Br. J. Radiol . 49, 335-8 (1976).

[4] Woodcock, J. P., The Significance of Changes

in the Velocity/Time Waveform in Occlusive

Arterial Disease of the Leg in Ultrasonics in Medicine , L. Pi 1 i pczyiiski , ed., pp. 243-50

(Polish Scientific Publishers, Warsaw, 1970).

[5] Wells, P. N. T. , Biomedical Ultrasonics

(Academic Press, London, 1977).

[6] Hunt, K. M. , Placental localization using the Doptone foetal pulse detector, J. Obstet . Gynaec. Br. Commonw . 76^, 144-7 (1969).

[7] Boyce, E. S., Dawes, G. S., Gough, J. D., and Poore, E. D., Doppler ultrasound method for detecting human fetal breathing in utero, Br . Med. J . 2, 17-8 (1976).

[8] Wells, P. N. T., Halliwell, M., Skidmore, R., Webb, A. J., and Woodcock, J. P., Tumour

detection by ultrasonic Doppler blood-flow

signals. Ultrasonics (to be published).

[9] Scitovsky, A. A. and McCall, N., Economic

Impact of Breast Cancer in Frontiers of Radiation Therapy and Oncology , J. M. Vaeth, ed..

Vol. 11, pp. 90-101 (Karger, Basel, 1976).

[10] Brinkley, D. and Haybittle, J. L., A 15-year

follow-up study of patients treated for carcinoma of the breast, Br. J. Radiol . 41 215-21 (1968).

[11] Slack, N. H., Blumenson, L. E., and Bross,

I. D. J., Therapeutic implications from a mathematical model characterizing the course

of breast cancer. Cancer, N.Y . 24 , 960-71

(1969).

[12] Feig, S. A., Shaker, G. S., Schwartz, G. F.

Patchefsky, A., Libshitz, H. I., Edeiken, J., Nerlinger, R. , Curley, R. F., and Wallace,

J. D. , Thermography, mammography and clinical

examination in breast cancer screening.

Radiology 122. 123-7 (1977).

[13] Strax, P., Venet, L., and Shapiro, S., Value

. of mammography in reduction of mortality from breast cancer in mass screening. Am. J . Roentg . 117 , 686-9 (1973).

[14] , Radiation-Induced Breast Cancer,

Br. Med. J . I, 191-2 (1977).

[15] Williams, K. L., Lloyd Williams, F. J., and Handley, R. S. , Infra-red thermometers in the diagnosis of breast disease. Lancet 2, 1378-81 (1961).

[16] Hitchcock, C. R., Hickok, D. F. , Soucheray,

J., Moulton, T. , and Baker, R. C. , Thermography in mass screening for occult breast disease, J. Am. Med. Ass . 204, 419-22 (1968).

175
[17] Wells, P. N. T. and Evans, K. T. , An immersion scanner for two-dimensional ultrasonic

examination of the human breast. Ultrasonics

6, 220-8 (1968).

[18] Jellins, J., Kossoff, G., Reeve, T. S., and Barraclough, B. H., Ultrasonic gray scale visualization of breast disease, Ul trasound

Med. Biol . U 393-404 (1975).

[19] Baum, G., Ultrasound mammography. Radiology

122, 199-205 (1977).

[20] Kobayaski, T. , Gray-scale echography for breast disease. Radiology 122, 207-14 (1977).

176
CHAPTER 7

PROPAGATION THROUGH BONE AND SKULL

177

Reprinted from Ultrasonic Tissue Characterization II, M. Linzer , ed.. National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C., 1979).

A THEORY RELATING SONIC VELOCITY TO MINERAL CONTENT IN BONE

Sidney Lees

Forsyth Dental Center

Boston, Massachusetts 02115, U.S.A.

and

Carel L. Davidson

University of Amsterdam

Amsterdam, The Netherlands

Bony tissues consist primarily of mineral hydroxyapati te (HAP) crystallites em- bedded in a matrix of a much softer material, collagen. Currey and others suggested

that bone is a two-phase composite, like mineral filled plastics, but the known laws

of mixtures give at best a crude approximation of the observed elastic properties of bone. We have investigated the problem by measuring the ultrasonic velocity in mineral filled particulate composites as a function of the mineral concentration.

It was found that the ultrasonic velocity can be predicted for some mineral filled

plastics by applying the Reuss formalism to the longitudinal elastic modulus, indicating that these are families of Reuss solids in some sense. Other mineral filled

plastics do not seem to obey this rule, the ultrasonic velocity being greater than predicted. Bone appears to belong to this latter class of particulate composites.

The literature indicates that in certain situations the mineral filler affects

the plastic matrix, giving the plastic constituent a higher modulus. A maximum

longitudinal modulus is ultimately attained so that two Reuss formalism bounds can

be obtained, the lower one calculated from the modulus of the unfilled plastic, the upper using the maximum modulus. The ultrasonic velocities of a system of fluorapatite (FAR) filled epoxy was found to lie between such bounds. Currey and his successors assumed bone collagen has the same elastic properties

as tendon collagen and that these are invariant with respect to contained HAP. The literature shows the contrary, that bone collagen, even when demineral ized , is more highly cross linked than any other collagen. Moreover, the literature indicates that

HAP crystallites are chemically bonded to the collagen molecules.

It is postulated that bone collagen is stiffened because HAP crystallites form on the intermolecular cross links, encasing them and making their effective lengths very

short. It is shown that the sonic velocity for bone can be bounded by two Reuss formalism curves in the same manner as for FAP epoxy.

Keywords: Bone; collagen; crosslinking modification; curve! i nki ng ; hydroxyapatite;

sonic velocity.

1. Bony Tissues

Bony tissues are essentially a mineral,

hydroxyapatite (HAP), embedded in an organic matrix, mostly collagen. HAP is an hexagonal

crystallite which in bone and dentin is usually

less than 100 nm in any dimension. The shape

and size distribution of the crystallite in bone

has been studied for many years with inconclusive

results, except that they are small. Certain x- ray diffraction studies indicate the crystallites

are needlelike, others that they are platelets.

Electron micrographs show platelets, but the needle form is not thereby excluded. There is reason to believe both forms are present de- pending on the site of formation. There is also

a strong contention that a significant fraction

of the mineral is amorphous [1]^.

Collagen is a generic term for a class of protein that make up much of the body tissue.

Bone collagen differs from other collagens in the body because it is so insoluble, indicating

a high degree of intermolecular cross linking.

The organic part of bone constitutes about 65 percent by volume of the tissue of which 95 per- cent is collagen. The mineral occupies 35 per- cent of the volume. Since collagen is such an important body constituent, its chemistry has been studied intensively for many years and is

^Figures in brackets indicate literature

references at the end of this paper.

179
still a major field of biochemistry. Very re- cently the sonic and elastic properties of some types of collagen have begun to be studied be- cause of the need to determine the presence of collagen in tissues and to identify its extent.

All collagens are highly structured materials

in a multilevel hierarchal order. The molecular

weight of the basic collagen molecule, defined

as tropocollagen, is approximately 300,000

daltons, which is a very large molecule even in organic chemistry. The molecule is much like a piece of spaghetti having a wet diameter of

1.5 mm and a length of about 300 nm. It is difficult to draw to scale and all figures in this paper are purely schematic. As noted, bone collagen differs from other body tissue collagens

by an extensive network of intermolecular cross

links that render it insoluble in even the most

potent of solvents. On the other hand, tendon collagen is reported to be mostly lacking in intermolecular bonds but having many hydrogen

bonded intramolecular links, so that it can be dissolved and reconstituted readily. While other

tissues like arteries and joints calcify, there

is reason to think that the special structural characteristics of bone collagen cause it to calcify in a unique manner [2].

2. Two Phase Mi neral -Fi 1 led Plastic Composites

It is the contention of this paper that the mechanical properties of bone can only be understood in the light of the chemical interrelationship between the mineral crystallites and bone collagen. Previously Currey [3], Welch [4] and

Katz [5] have considered bone to be a mechanically mixed two phase mineral-filled polymer

composite. Their concept yields a crude rep- resentation of the variation of elastic modulus

with mineral content, but the detailed correlation is not good. Currey [6] even suggested

that the crystallites are much longer than ob- served in order to attribute a fibrous mineral structure to bone to account for the observed

elastic and strength properties.

We believe that the difficulties of our pred- ecessors are due to several causes. The elastic

modulus of collagen is not well known and there

has been no distinction among the various types.

Previous investigators used estimates for tendon

fibers rather than bone collagen. Except for Mason's [7] sonic velocity measurement on kan- garoo tail tendon fibers, the estimates of the elastic modulus were based on low strain rate

tests. Secondly, there was no attempt to examine

the chemical structure of collagen or the effect

of the structure on the properties of bone. Col- lagen was considered a structureless homogeneous

isotropic continuum and the short range order of body tissue collagen was ignored. Thirdly,

there is little understanding even at this date

how the HAP crystallites are laid down despite a long and intensive investigation over many years

by many investigators. Fourth, the estimates of the elastic modulus of bone have been mostly

those obtained by standard stress-strain testers. Bone is vi scoelasti c . Strain rates and the magni- tude of the strain in conventional stress-strain

testing causes hysteresis and often permanent

distortion. In this paper we use only ultrasonic

velocity measurements where the amplitude of displacement is of the order of an angstrom and the period is much less than any relaxation time of the medium.

3. Ultrasonic Measurements

It was the availability of measurements of the ultrasonic velocity of several hard tissues that

led to the elastic theory presented here. Con- ventional procedures for measuring elastic prop- erties are difficult because bone is a viscoelastic material and the data must include the rate of change of strain as well as the strain

itself. Moreover, the sample is significantly

affected by the test process, so that repeated

tests are not consistent. Such a situation re- quires further interpretation to make sense of the data which is particularly difficult where

the material (bone) varies widely due to its biological origin. Ultrasonic velocity measurements, on the other hand, can be repeatedly per- formed on the same sample with an uncertainty

that depends mostly on the measurement technique

and not on the sample. The contribution of biological variation can be treated separately

apart from the measurement process. There is a need to relate the elastic prop- erties obtained at high strain rates with the more conventional techniques. Papadakis [8] has designed and tested an infrasonic resonator for testing plastics at about one hertz but which

he says can be increased to 1000 hertz. It will

be useful to find the sonic velocity measurements

in bone at these low frequencies, but the limitations imposed by the inhomogeneities of biological material will require considerable modification of the Papadakis equipment.

4. Rule of Mixtures

It is reasonable to consider bone to be a two- phase mineral-filled composite as Currey did,

but it is necessary to know the relationship by

which the elastic properties of the composite

can be calculated from those of the constituents.

A number of rules of mixtures have been proposed

for estimating the elastic moduli of the composite but each has limited applicability. Generally they work reasonably well when the properties

of the two constituents are nearly alike but when there is a tenfold or greater ratio in density, the mixing rules do not seem to apply.

A number of mineral filled plastics were

studied to determine a relationship between longitudinal sonic velocity and mineral content. The first series included tungstenfilled vinyl, crystabolite-filled polymethylmethacrylate, and crystabolite-filled epoxy.

It was discovered that one of the known mixing rules did apply. Reuss postulated an ex- pression of the form:

1 _ Vj_ V2. K

" Ki K2 (1)

where

^1

'

volume fraction of the plastic

consti tuent volume fraction of the mineral

constituent = 1 - Vj elastic modulus of composite

elastic moduli of constituents.

180
In this application the longitudinal modulus

was used rather than the bulk and shear moduli

which was Reuss's intention. Since

K k + 4/3 (2)

where k = bulk modulus and u

= shear modulus,

another value for the longitudinal modulus can

be calculated from Reuss's expression applied

first to the bulk modulus and then to the shear modulus, but it will be quite different from the value yielded by eq. (1) for the longitudinal

modulus directly inserted. Consequently, the expression in eq. (1) is designated the Reuss

formal i sm. The sonic velocity is calculated as usual from the relation:

c = K/p (3)

where p = Vjpj + P2V2 and p = density.

Figures 1, 2 and 3 taken from Lees and Davidson [9] show how well Reuss's formalism applies

to these examples. It is not obvious why and we

do not have an explanation. It is characteristic

of these figures that the sonic velocity de- creased, or at best does not increase much, as the mineral content increases on the left hand

side of the curve, even though calculations show

the longitudinal modulus of the composite is in- creasing. It was found that the density in this regime increases much more rapidly than the elastic modulus. When Vj is large and K2 is ten times Kj the first term on the right side of eq.

(1 ) dominates.

1-

VOIGT

REUSS

+ EXPERIMENTAL VALUE

0 10 20 30 40 50 60 70 80 90 100 VOLUME % CRYSTABOLITE

Fig. 2. Polymethylmethacrylate-crystabol ite system (from Lees and Davidson [9]).

6

0 H 1 1 1 1 1 1 1 1 1 —

0 10 20 30 40 50 60 70 80 90 100 VOLUME, PERCENT TUNGSTEN

Fig. 1. Voigt-Ruess bounds for vinyl -tungsten

composite system with experimentally

determined curve (from Lees and Davidson [9]).

+ EXPERIMENTAL VALUE

1 -

0 -I 1 1 1 1 1 1 1 1 1 0 10 20 30 40 50 60 70 80 90 100

VOLUME, PERCENT CRYSTABOLITE

Fig. 3. Epoxy-crystabol i te composite system

(from Lees and Davidson [9]).

181
5. Modified Conditions for Rule of Mixtures

As the investigation proceeded a new kind of mineral-filled plastic, f 1 uorapati te-fi 1 1 ed epoxy, was found which apparently does not follow Reuss's formalism. Fluorapatite (FAP)

closely resembles HAP but unlike HAP it can be obtained in large crystals. Powdered FAP is much more crystalline and well behaved crystal lo- graphically than HAP. Both FAP and HAP are surface active materials. In figure 4, the lower curve shows the variation of sonic velocity of the composite with mineral content when

the longitudinal modulus of the unfilled plastic

is taken as the value of Kj . It may be observed

that all the measured values are above the lower curve and that there is some scatter among them.

Q J I I 1 I I I I I I

7-

LIMITING SONIC VELOCITY BOUNDARY

1 -

0-1 1 1 1 1 1 1 1 1 1 0 10 20 30 40 50 60 70 80 90 100 VOLUME, PERCENT FLUORAPATITE

Fig. 4. Epoxy-f 1 uorapatite composite system

(from Lees and Davidson [9]).

The only difference between the situations of figures 3 and 4 is the replacement of one mineral

filler by another. It must be concluded that sometimes the filler can influence the mechanical

behavior of the plastic matrix. Now it is well known that polymers become stiffer as the cross linking density increases so it is inferred that

FAP must cause the epoxy to increase the cross linking density. A similar situation was de- scribed by Kumins [10] who found that titanium

dioxide causes an increase in cross linking

density in epoxy, apparently by a factor of ten

when about 3 volume percent titanium dioxide was added. Burhans et al . [11] showed a strong de- pendence of the elastic moduli on the maximum

cross link length, so that either an increased

cross linking density, or a decreased maximum

cross link length, or both can increase the elastic modul i

.

In order to see how this could be applied to the FAP-epoxy composite system, the maximum

value for the compressive modulus reported by Burhans et al . was used as a basis for estimating the corresponding maximum value for the longitudinal modulus. A new Reuss curve was calculated using the higher modulus. When plotted on figure 4 it provided an upper bound, so that all the experimentally determined velocities

fell between two Reuss curves. This is interpreted to mean that FAP can affect the cross

linking density of the matrix. The scattered

values of the ultrasonic velocity indicates a variability in the cross linking density from

one experiment to the next. The samples were not always prepared the same way and the changed

conditions could possibly modify the influence

of the filler. For example, the samples were compressed, after mixing, in an attempt to achieve higher mineral content. This caused a gray exudate to ooze from the mold, the gray color being attributed to the very fine FAP particles. But these fine particles are most

likely to have maximum influence on cross linking density because of their increased surface

area

.

6. Structure of Collagen

It is now possible to study ultrasonic wave propagation in bone with these two concepts in mind. First, that for a specific two phase

mineral-filled polymer the longitudinal modulus

of the composite can be found from the Reuss formalism and, second, the longitudinal modulus

of the matrix can be affected by the presence

of the f i Her.

While collagen is a polymer and bone may be considered a two-phase mineral-filled polymer,

bone is not formed by starting with a mix of mineral and monomer. Collagen is laid down

first and then it becomes mineralized when the

HAP crystallites are deposited. When bone is demineral ized the collagen matrix can be re- covered as a rubbery solid having the form and shape of the original bone. However, when collagen is removed the mineral structure left behind is a weak solid that easily crumbles

into a powder. It must be concluded that the collagen forms a continuous medium but the mineral does not. The mineral fills voids in the collagen.

Collagen has been studied for many years and much is now understood about its chemistry and

ul trastructure but many unresolved problems re- main such as the three-dimensional order, the chemical character of the i ntermol ecul ar cross

links and the location of the cross links (Ramachandran [13], Gallop and Paz [14], Veis [15]).

Collagen exhibits many levels of order terminating in a fibrous structure. The successive

levels of organization can be understood with

the aid of figure 5a from Lees and Davidson [2]. The smallest element is the a-helix which

spontaneously combines in triplets to form a

182
AXIS OF EXTENDED

CHAIN\

TRIPLE AXESOF

THREE HELICES

A 2.8 A

3.1 A

(a)

(a) The a-helix is left handed. Each spot is a residue and repeat length

is 3.1 A. (b) The a-helix is twisted into a right handed helix which reduces repeat

length between residues to 2.8 K and the repeat of the supercoil is 10 times residue length, or 28 K. (c) Three a-helices are threaded to form

a single tropocol lagen (TC) unit. (Adapted from Glimcher and Krane, . 1968 [12]).

Fig. 5a. The tropocol lagen unit (from

Lees and Davidson [2] )

.

superhelix molecule, the tropocol 1 agen (TC) unit. In turn TC forms microfibril ropes, which

in their turn form three-dimensional fibrils.

Fibrils join to form fibers seen in tendon.

1. The basic element, the a-helix chain, has

a molecular weight of about 100,000 and several types have been identified depending on the amino acid composition. The aj chain has 1052 amino residues of which 1011 are in triplet sets where the first term is glycine. The N terminus

has 16 nonhelical residues beginning with an

amino (NH2) group while the C end has 25 non- helical residues terminating in a COOH group. Gallop and Paz [14] as well as Hulmes et al . [16] show the residue map. It is the triplet with

first term glycine that defines the characteristic pattern through all subsequent hierarchal

levels.

2. Three a-helices are wound into a superhelix about 300 nm long, 1.5 nm diameter (wet) and a molecular weight of about 300,000 (Ramachandran). This is the basic molecule, the TC unit. In experiments, the a-helix spontaneously

links up to form collageneous materials which

have important industrial and medical uses but the product is not the ordered collagen of bone

and tissue. It does demonstrate that the hydrogen bonded state between the a-helices is stable and the basis for interaction between TC units in the higher levels of structure.

3. TC units join in sets that exhibit

"quarter staggering" in tissue as illustrated

in figure 5b, based on a submolecular length

of 67 nm or 234 residues, the D-length (Hodge

[17]). A TC unit is 4.4 D units long and packs

into a structure exhibiting a repeated 0.6 D unit

gap between TC ends. It is a requirement of Hodge's scheme that no two quarter stagger gaps

can be adjacent, which imposes a severe restriction on the three-dimensional structure that has not yet been resolved (Segrest and Cunningham

[18]).

4. The nonhelical chains at each end of the

TC unit and some of the adjacent glycine coded triplets are probably the links between molecule

ends but may also serve to link helices within

a single molecule, i.e ., the inter and intramolecular links are similar. However, many of

the intramolecular links must be hydrogen bonds,

while much of the intermol ecular links between

parallel molecules must be chains covalently

bonded as side chains to residues in the back- bone of the molecule.

5. A number of three-dimensional structures

have been proposed for the microfibrils, fibrils

and fibers. We use Smith's five strand rope of

TC units [19] as modified by Miller and Parry

[20]. It is shown in figure 5c as Smith pro- posed the model with a 67 nm axial stagger, 72° aximuthal displacement between axes of nearest neighbors and 43 nm hole between colinear TC units. It incorporates a repeating pattern

after 5 x 67 nm and a helix with a five-fold

1 —HwA

2—H 3—H 4—1

0.6 D HOLE REGION

N I C

-A V

N END = 16 RESIDUE LONG NONHELICAL END + TRANSITION HELICAL REGION

C END = 25 RESIDUE LONG NONHELICAL END + TRANSITION HELICAL REGION

D = REPEAT LENGTH OF 234 RESIDUES

(Adapted from Gallop and Paz, 1975 [14])

Fig. 5b. "Quarter" staggering scheme (from Lees and Davidson [2]).

183
40 A

s

CROSS LINK

Fig. 5c. Smith's five stranded rope model

for the microfibril (from Lees and Davidson [2]).

UNIT CELL 80x 80A

Fig. 5d. Miller and Parry model of the structure

and packing of a fibril (from Lees and Davidson [2]).

screw axis (five subunits per screw turn char- acterized by the holes). The pentagonal unit

is 4 nm in diameter when the wet TC unit is 1.5 nm diameter and the lumen is 1.1 nm.

6. Miller and Parry indicated that the five- strand rope must be twisted to produce a fourfold symmetrical supercoil, where the holes are

now 90° apart, but there is still a pentagonal

packing of the strands. The colinear TC units are inclined about 2.5° to the rope axis to accom- modate the twist.

7. Miller and Parry have deduced a fibril packing structure based on a square or tetragonal

cell of four microfibrils as in figure 5d. While

Miller and Parry did not say so, the pattern of successive helical structures suggests that the microfibrils are coiled about each other while

maintaining the four unit cell.

On the basis of this description, the ultra- structure of collagen can be schematically rep- resented as in figure 6 where the microfibrils

Si: INTERMOLECULAR

CROSS LINK

Fig. 6. Schematic representation of the ultra-structure of collagen showing

intermolecular cross links.

184
are tied together with cross links of organic

chains. The TC units are probably very stiff

along their major axis. Enemoto and Krimm [21] calculated a value for the Young's modulus of a very similar molecule, polyglycine II, which

they found to be 41 GPa, a value far in excess of any reported value for collagen or even for bone

(26 GPa). Polyglycine II has a triple helix

hydrogen bonded molecule and closely resembles

collagen in its structure (Ramachandran [13]). The Young's modulus for TC is probably about the same value, which indicates that the collagen

structure is more yielding than the TC units be- cause the cross links are softer. Moreover,

the long skinny TC units must bend quite easily

unless they are severely restrained, which makes

collagen tissue softer than its component molecules.

7. Mineralization of Bone

As the tissue mineralizes, HAP crystallites

begin to fill the voids in the quarter stagger

gaps, between microfibrils and between fibrils. The loci are inferred because they have been sited definitely only between fibrils (White et

al . [1]). It is our contention that the crystallites form on the cross links until they grow to

a size that fills the voids. It is implied that

the crystallites start with the cross links as the nucleating seeds, which further implies that

the stereochemistry of the organic chain must be favorable to the hexagonal habit of HAP. There

is no accepted theory to explain how crystallites

PLATELIKE CRYSTALLITE

NEEDLELIKE ^CRYSTALLITE

Fig. 7. Schematic representation of mineralized bone collagen showing

crystallites embedding the cross

1 inks.

form and grow in tissue but some workers indicate

that the process is mediated by a sequence of chemical stages rather than precipitating from a saturated solution. Whatever the process it en- tails a mineralization of the organic cross links

until the crystallite encases the links. In figure 7 a schematic representation of the mineralized microfibrils shows the crystallites

embedding the cross links and effectively short- ening them. There is a cross link from one microfibril to a crystallite and its continuation on the other side connects the crystallite

to a second microfibril. The connections are made to TC units in the strands of the microfibrils, hence to side chains of the residues on the a-hel ix. The effect of mineralization in bone is to shorten the cross links and thereby increase the longitudinal modulus of the matrix. There may

well be additional cross links formed at the

same time or prior to mineralization, but the cross linking is most likely mediated by a different chemical process than that for mineralization. The stiffening of the collagen matrix need

not necessarily be associated with a greater

cross linking density.

8. Ultrasonic Velocity of Mineralized Tissues

In order to apply the theory it has been neces- sary to estimate the equivalent isotropic sonic

velocity for hard tissues. Since bone and dentin

are anisotropic the estimates are not well based

and the ultimate test and evaluation of this theory requires a better way to find the iso- tropic velocity equivalent. Alternatively, it may be possible to extend the theory to deal with

the anisotropy as Yoon and Katz [22] are attempting to do but the theory is still incomplete.

Figure 8 shows representative values for the longitudinal sonic velocity of bone, dentin and enamel. There are four bone values, one for normal bovine bone by Lang [23], and three by

Abendschein and Hyatt [24]. The latter include

one normal human bone and two of lower density

from ill people. It is interesting that the normal human and normal bovine bone values coincide

despite the quite different methods for making

the measurements. Unlike the mineral filled composites we do not yet have good values for the elastic properties

of the constituents of bone, particularly bone collagen. Several Reuss curves were calculated

based on the different published estimates for the elastic modulus of collagen, usually the Young's modulus which was converted to the longitudinal modulus by assuming Poisson's ratio

to be 0.35 (Katz [5]).

Three Reuss curves are shown in figure 8. The lowest bound is based on the longitudinal

modulus suggested by Currey [3] and Katz [5], 3.75 GPa. The intermediate bound is calculated

from Mason's value [7] measured ul trasonical ly

on kangaroo tail tendon. The upper bound was obtained by using Reuss 's formalism backward on the sonic velocity and density of normal bone.

It can be seen from figure 7 that the intermediate and upper curves bound the experimental

data, much like the two bounding curves in figure 4. The lowest bound is based on a value of longitudinal modulus based on low strain rate

test data, a technique that characteristically

185
3-

1-

INTERMEDIATE COLLAGEN

K MODULUS

—[—

10 —\—20 —I30 —I40 50 —I

60 70 —1

80

much greater than isolated collagen because in- timate association with the mineral raises the collagen's tensile stiffness."

References

[1] White, S. W., Hulmes, D. J. S. , Miller, A., and Tinmins, P. A., Collagen-mineral axial relationship in calcified turkey leg tendon

by x-ray and neutron diffraction. Nature 266 , 421-425 (1977).

[2] Lees, S. and Davidson, C. L., The role of collagen in the elastic properties of cal- cified tissues, J. Biomech . 10, 475-486

(1977).

[3] Currey, J. D., Three analogies to explain the mechanical properties of bone, Biorheol ogy

2, 1-10 (1964).

- [4]

[5]

90 100 [6] VOLUME, PERCENT H YDROXYAPATI TE

Fig. 8. Ultrasonic velocity in mineralized

tissues (from Lees and Davidson [2]).

yields low values compared to ultrasonic mea- surement techniques.

The data represented in figure 8 can only be regarded as indicative and not definitive. In particular the value of enamel cannot be taken

as properly a member of this class of materials

because it is not a collageneous tissue. Enamel

is formed by a totally different process than that for bone and dentin. The HAP content of enamel is so high that the mineral component of

eq. (1) dominates, which will be true for a com- parable mineralized collageneous tissue. How- ever, the theory developed here shows that it is unlikely to have so much mineralization in bony

tissues.

Acknowledgment

S. L. is pleased to acknowledge support from

NSF Grant GH-42515 and National Institute of Dental Research, NIH, Research Grant Number ROl-DE-3992. Some of the experimental data was obtained while at the Department of Materials

Science, University of Amsterdam with funds from

the National Science Foundation and the University of Amsterdam.

Note added in proof: The authors have recently learned that some

of the concepts presented here were surmised

by McCutchen [25]. In his paper he says "I sug- gest that collagen is the prime tension carrier

in bone, and that bone's stiffness modulus is

Welch, P. 0., The composite structure of bone and its response to mechanical stress,

in Recent Advances in Engineering Science , A. C. Eringer, ed. , Vol. 5, pp. 245-262

(Gordon and Breach,

Katz, J. L., Hard tissue as a composite

material - I. Bounds on the elastic be- havior, J. Biomech . 4, 455-473 (1971).

Currey, J. D., The relationship between

the stiffness and the mineral content of bone, J. Biomech . 2, 477-480 (1969).

[7] Mason, P., Viscoelasticity and structure

of keratin and collagen, Kol loid , Z. , A . Polymere 202 , 139-147 (1966T;

[8] Papadakis, E. P., Balanced resonator for infrasonic measurement of Young's modulus

and damping in flexure, J . Test and Eval . 1, 126-132 (1973).

[9] Lees, S. and Davidson, C. L., Ultrasonic measurement of some mi neral -f i 1 1 ed plastics, IEEE Trans. Sonics and Ultrasonics SU-24 , 222-225 (1977).

[10] Kumins, C. A., Long range effects of polymer pigment interaction in the solid

state, J. Paint Technology Engineering 37 , Pt. 1, pp. 1314-1336 (1965).

[11] Burhans, A. S., Pitt, C. F., Sellers, R. F., and Smith, S. G. , High performance epoxy

resin systems for fiber-reinforced com- posites. Prelim. Paper, 21st Annual Mtg.

Reinforced Plastics Division, Soc. Plastics Ind. (1965).

[12] Glimcher, M. J. and Krane, S. M. , in Treati se

on Collagen , B. S. Gould, ed.. Vol. 2 (Academic Press, New York, 1968).

[13] Ramachandran , C. N., in Treatise on Col1 agen , C. N. Ramachandran, ed.. Vol. 1, Chap. 3 (Academic Press, New York, 1967).

[14] Gallop, P. M. and Paz, M. A., Posttranlational protein modifications with special

186
attention to collagen and elastin, Physiol . Rev . 55, 418-487 (1975).

[15] Veis, A., Collagen Biosynthesis, in CRC Critical Reviews in Biochemistry, Vol. 2,

p. 443 (The Chemical Rubber Co., Cleveland,

Ohio, 1974).

[16] Hulnies, D. J. S., Miller, A., Parry, D. A. D., Piez, K. A., and Woodhead-Gal loway

J. W. , Analysis of the primary structure

of collagen for the origin of molecular

packing, J. MoT . Biol . 79, 137-148 (1973).

[17] Hodge, A. J., in Treatise on Collagen , C. N. Ramachandran, ed., Vol. 1, Chap. 4 (Academic

Press, New York, 1967).

[18] Segrest, J. P. and Cunningham, L. W. , Unit

figril models derived from the molecular

topography of collagen, Biopoly . 12 , 825-834

(1973).

[19] Smith, J. W., Molecular pattern in native

collagen. Nature 219 , 157-158 (1968).

[20] Miller, A. and Parry, D. A. D., Structure

and packing of microfibrils in collagen,

J. Mol . Biol . 75, 441-447 (1973).

[21] Enemeto, S. and Krimm, S., Elastic moduli of

helical polypeptide chain structures,

Biophys . J. 2, 317-325 (1962).

[22] Yoon, H. S. and Katz, J. K. , Ultrasonic wave propagation in human cortical bone, J_. Bio- mech 9_, I. Theoretical considerations for hexagonal sysmmetry 407-412; II. Measurements

of elastic properties and microhardness

459-464 (1976).

[23] Lang, S. B., On the anisotropic elastic coef- ficients of bone and results on fresh and dried bovine bones. IEEE Trans. Biomed . Engineering 17, 101-105 (1970).

[24] Abendschein, W. and Hyatt, G. W., Ultrasonics and selected physical properties of

bone, Clin. Orthop . 69, 294-301 (1970).

[25] McCutchen, C. W. , Do mineral crystals

stiffen bone by straitjacketing its collagen?

J. Theor. Biol . 51, 51-58 (1975).

187

Reprinted from Ultrasonic Tissue Characterization II, M. Linzer, ed., National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C., 1979).

ULTRASONIC PROPERTIES AND MICROTEXTURE OF HUMAN CORTICAL BONE

Hyo Sub Yoon and J. Lawrence Katz

Center for Biomedical Engineering

Rensselaer Polytechnic Institute

Troy, New York 12181, U.S.A.

The wave propagation in human cortical bone (dried) was investigated, using an ultrasonic pulse transmission method at room temperature. Firstly, it has been found

that the symmetry of human cortical bone is consistent with the hexagonal system,

based on the ultrasonic velocity measurement and microscopic observations. The five

independent elastic stiffnesses were determined at 5 MHz, and they are (in GPa):

Cii = 23.4 ± 0.31, C33 = 32.5 ± 0.44, c^i, = 8.71 ± 0.13, Cjj = 9.06 ± 0.38,

Ci3 = 9.11 ± 0.55. Secondly, this study shows that bone filters and polarizes ultrasonic waves. Thirdly, since, in a piezoelectric medium such as bone, the wave propagation (or

elastic stiffnesses) is modified by the piezoelectric coupling, the piezoelectric

contribution or "stiffening" was calculated for bone, employing the piezoelectric

and dielectric constants of bone reported in the literature. Compared with the corresponding values of two well-known piezoelectric materials, a-quartz (single

crystal) and "poled" barium titanate ceramic (polycrystal 1 ine )

, it has been found that the piezoelectric "stiffening" in bone is negligible. Finally, the sound velocities were measured over the frequency range of 1 to 5 MHz for the transverse

mode and of 2 to 10 MHz for the longitudinal mode. For all the eight independent

modes the ultrasonic velocities are found to increase with increasing frequency,

implying that bone is viscoelastic even at these high frequencies.

Key words: Anisotropy; dispersion; elasticity; human bone; microhardness ; micro- structure; piezoelectricity; thermodynamics; ultrasound; viscoelasticity; wave propagation.

1. Introduction

The material symmetry is an important concept

for interpreting and analyzing the structure- property relationships of a material, from both theoretical and practical points of view. This

is especially true when one has to deal with many

tensorial properties of a multiphase-composite

material such as bones and teeth. The maximum

use of symmetry elements in the medium simplifies

the analysis enormously and provides a clearer

physical picture for any phenomenon than otherwise.

It is known that bone has a remarkably well organized structure, consisting mainly of the protein (collagen, not well crystallized), the inorganic phases (crystalline hydroxyapatite and possibly a type of amorphous calcium phosphate)

and a fluid phase (in vivo ). Therefore, one can expect that several crystal-physical phenomena

occur in bone. It has, in fact, been reported

that bone is both pyroelectric (first-rank

tensor) and piezoelectric (third-rank tensor).

When employing ultrasonic waves of low strain

levels much less than 10"^, as in diagnostic

ultrasound, one must take into account these interactions between thermal and electrical

properties, and between elastic and electrical

properties, respectively. In other words, it is necessary to regard bone as a thermodynamic system. However, the situation becomes more com- plicated for a more realistic case than the above idealized one because bone appears to be viscoelastic even at ultrasonic frequencies.

It is now clear from the above information

that one cannot treat each physical or thermodynamic property independent of the others, as has been done in the past, e.g . , [l,2]i. Instead,

one should start with a simple situation when

studying bone, then move to a more complex model

by adding one or more independent variables, as was followed in the present investigation on human compact bone. For this purpose it is con- venient to assign hierarchal levels of structural organization to bone, that is, molecular,

ul trastructural , microscopic and macroscopic.

The wavelengths of ultrasound employed (3.7 x 10" 1 to 2.2 mm) are of the order of magnitude

appropriate to the microscopic level. This is the level at which conventional metal lographic

techniques are best suited to study the micro- structure or microtexture of bone. Note that

the microtexture of human bone is different from

^Figures in brackets indicate literature

references at the end of this paper.

189
that of bovine, canine, or any other mammalian

bone.The simplest situation for ultrasonic studies

of bone is one in which temperature (room) and frequency (5 MHz) are kept constant. This cir- cumstance corresponds very closely to the situation of plane wave propagation in an elastic

medium and yields a set of elastic stiffnesses

for bone. As the next step, the piezoelectric

contribution was considered for the ultrasonic

wave propagation in bone. So far, bone has been treated as an elastic dielectric. In order to determine the existence of a frequency dependence

or dispersion of the ultrasonic velocities at room temperature, the sound velocities were measured over the frequency range of 1 to 5 MHz

for the transverse mode and of 2 to 10 MHz for

the longitudinal mode. These results are im- portant when it is necessary to accurately de- lineate ultrasonic paths, as in ultrasonic ence- phalography, monitoring of fracture healing, and other medical and dental diagnoses since the at- tenuation of ultrasonic waves in calcified tissue

is substantially larger than that in soft tissue.

2. Theoretical Background:

The Thermodynamics of Bone

In order to derive the relationships between

the mechanical, electrical and thermal properties of bone, i.e . to establish the thermo- dynamic aspects of bone, let us, following Voigt

[3], introduce a thermodynamic potential per unit volume, E, as a function of ten independent variables: stress T^, electric field

strength E^- and entropy a, combined with the ap- propriate coefficients, elastic stiffness c^v^ dielectric permittivity e-jj, specific heat C, piezoelectric stress constant e-jy, thermal stress coefficient q^ pyroelectric constant p-j and absolute temperature 0. Thus:

1 E,a r c X 1 S,0 r.r. , I ^ ^ c

' S S + ly £ . Ei E-i + y -^-F (1)

6 qt + e^ EiS„ +

IP ' y CE

S,,a +

e p-: J\ cs

EiO,

where summation over repeated indices is implied,

and i ,j = 1, 2, 3; M, V = 1, 2, . . . , 6. A superscript indicates the quantity to be kept constant. Here magnetic effects are not included in eq. (1) because they are usually very small compared to electric effects. Also, bone is treated as an anisotropic linear elastic solid,

i.e . as a linear elastic dielectric, rather than

as either metallic, ferromagnetic, or ferro- electric solids. That is, for simplicity the viscoelastic properties are considered separately.

Since the propagation of ultrasonic waves

through a medium is an adiabatic process (isentropic), eq. (1) is simplified to

ic^'° S S

2 pv V \

1 y EiSy (2)

Differentiation of eq. (2) with respect to Sp and E-j, respectively, gives the well-known equations of state (or constitutive equations) for a piezoelectric medium:

T = c^'^ S

^ yv

eV

i / T,a

S,a

(3)

(4)

which now define stress T^ and electric displacement D.. Note that the coefficients on the leading diagonal represent the principal effects while the off-diagonal coefficients (equal to each other) measure the coupled effects.

For the pulsed ultrasonic measurements of thickness vibration, the elastic stiffness ap- propriate for the vibration would properly be designated as Dn,Et,a

^y V '

meaning that the normal component of the electric

displacement and the transverse components of the electric field are constant (usually zero). By

combining Newton's second law of motion with the constitutive eqs. (3) and (4) and substituting

plane wave solutions uj (= Uj exp i(a)t - k-x)) for the medium of density p, it may be shown that:

3t2

c

.

Dn,Et,a

ijk?. ax .3x,

where

:

°n'^t'° ^ Dn'EfO ^ E,a

^

'^i'jk? "-yv

with m being fixed.

e p my. "ly ,S,a mm

(5)

(6)

Note that the directions i, n, m are parallel to one another, and that

Dn'^t'°

D,o

(7)

is, in general, different from c^^^ which is given by:

D,a E,o ^iy^jv

C = C + r

' yv yv b,CT

= ij

For more details the reader is referred to references [4-6].

3. Experimental Procedure

A. Specimen preparation

Bone samples were cut with a band saw out of

the right femoral mid-diaphysi s from the cadaver

of a 57-year-old male who died of gastric adenocarcinoma. Two wel 1 -oriented specimens in the shape of a rectangular parallelepiped (0.5461 cm

x 0.8933 cm x 0.6233 cm for X1X2X3 cut and 0.4750 cm x 0.5641 cm x 0.7645 cm for 45° cut), were then cut using an Isomet low speed saw with

a diamond blade 10.16 cm diameter and 0.03048 cm

thick. Distilled water was used as the lubricant

190
and coolant during cutting. The specimens were

oriented using a straight surface in the medial

quadrant, which is always parallel to the bone

axis (X3 axis) in any femur, taking the axis

along the radial direction and the axis per- pendicular to both, thus forming a right-handed

rectangular coordinate system. The lateral quadrant of the mid-di aphysi s was selected for obtaining the specimens because, for this particular bone, this quadrant was macroscopically

more uniform than was the rest of the cross

section.

Conventional metal lographic techniques were

then employed for grinding and polishing the specimens. In order to prepare a pair of parallel surfaces for ultrasonic measurements, the specimen, mounted on a parallel -face device with

double-stick tape, was ground under a flow of cooling water, with an AB Handimet Grinder on which a 600 grit silicon carbide paper strip was pasted. This was followed by polishing with 0.3

pm alumina slurry on a 20.32 cm diameter bronze

wheel covered with wool broadcloth. Each time after grinding and polishing, the specimen was cleaned in an ultrasonic cleaner for 3 minutes.

The orientation of a specimen was checked by

microscopic observation of osteon arrangement in the transverse cross section.

Each specimen, wrapped with soft tissue papers,

was dried very slowly to avoid undesirable results

such as cracks and distortions. This was done by

keeping the specimen in a glass vial whose plastic

lid was tightly closed, for a day, followed by

placing it first in a desiccator for 10 days, and subsequently in a vacuum oven at 24 °C and 533 Pa for 4 days. Finally, the specimen was dried in a vacuum line equipped with both a mechanical pump

and a diffusion pump at room temperature for 3 days. Before proceeding with the ultrasonic

velocity measurements, the moisture content of

the specimen was stabilized by keeping it in air

until changes in the specimen's dimensions were recorded as less than 0.1 percent.

B. Micrographs and microhardness

measurements

From the same mid-diaphysi s of human bone,

another cylindrical specimen 0.5 cm long was pre- pared in the identical manner as described before.

This specimen was used both for obtaining micrographs (75X) of the transverse cross section and

for Vickers (HV) microhardness measurements, em- ploying a Bausch & Lomb Metal loqraph and a Kentron Tester, respectively. A typical micro- structure of the transverse cross section is shown in figure la. Compare it with that of young bovine bone shown in figure lb. The hardness of the bone specimen was measured with a 200 g load at locations equally spaced radially

on the four quadrants: anterior, posterior,

lateral and medial. Care was taken to make all indentations away from Haversian canals or lacunae. r

(a) HUMAN (b) BOVINE

Fig. 1. Microstructures of human and bovine demora, 75X (transverse cross section),

(a) human and (b) bovine.

C. Ultrasonic setup and measurements

A block diagram for the pulse through-transmission technique is shown in figure 2. For each frequency step, a pair of PZT-5A piezoelectric

transducers (chromium-gold plated on both faces)

was used to transmit and receive the ultrasonic

pulses. For the specimen holder, a pair of parallel faces of aluminum buffer disc was prepared by hand-grinding it on 400- and 600-grit

silicon carbide paper strips, as explained pre- viously, and by polishing with a 3 pm diamond

compound; the disc was cleaned ul trasonical ly

after each step. The transducer was cemented on one face of the buffer disc with salol (melting

point 43 °C), the other face being in contact

with a face of the specimen during the transittime measurements. No coupling medium was used

191
RF PULSED OSCILLATOR

(ARENBERC P&- 65UCI

PRECISION ATTENUATOR

lARENBERG ATT-6931

J2^_TRANSM TRANSDUCER

( PZT 5A

I

OSCILLOSCOPE

ITEKTRONII 5431

IZ,^ RECEIV TRANSDUCER

(PZT 5A)

WIDE BAND AMPLIFIER

(H P 460 A)

Fig. 2. Block diagram of pulse transmission method.

between the buffer disc and the specimen surface

since dried bone is porous and the specimen volume

was very small. Instead, the acoustic coupling

was formed by lightly pressing down the upper

part of the specimen holder with a screw. For more details see reference [7]. Pulse transit (or delay) times in the specimen

were measured from the shift of the pulse positions as observed on the horizontal axis of the oscilloscope with and without the specimen be- tween the aluminum alloy buffer discs. The horizontal (time) axis of the oscilloscope was calibrated with a Time-Mark Generator 180A. The accuracy of the pulse transmission method was checked by measuring the transit times both of

AT cut quartz oscillator plates of known frequencies, and a beryl single crystal whose values

were determined previously by Yoon and Newnham

[8] using a pulse superposition method [9].

4. Experimental Results and Discussion

A. The homogeneity and microtextural

symmetry of human cortical bone

Figure 3 shows that the bone is "intrinsically"

homogeneous within the limit of experimental errors along the radial direction on the four quadrants. Weaver [10] has also observed a wide

zone of mid-cortical bone of uniform hardness for autopsy and surgical bone specimens. Kallieris' results [11] show no significant differences in hardness between fresh human bones of various structural designs in different layers of compact

bones. These findings justify somewhat the use of

small specimens for measurements of the physical

or mechanical properties of bone. Rauber [12] and Dempster and Liddicoat [13] have shown that bone has different physical and mechanical properties along and perpendicular to

its long axis. Therefore, the symmetry (or

pseudosymmetry ) of the microstructural texture of bone may be either orthorhombic, tetragonal, trigonal, or hexagonal. Since bone is an opaque, microstructural composite, neither optical nor single crystalline x-ray diffraction techniques

can be employed to determine its full textural symmetry. An ultrasonic wave propagation method

can provide information about both the symmetry

and the elastic (and viscoelastic) properties of either crystalline or non-crystalline materials.

The microstructure on the transverse cross section of bone shows a pseudo-hexagonal closeBOr

40-

ANTERIOR

Relative scale

80

r 40

• • • • • • •

POSTERIOR

_L Relative scale

ci. BOir 40-

LATERAL

Relative scale

80

40

• • •

MEDIAL

Relative scale

Fig. 3. Microhardness (Vickers Hardness) of human femur (dried).

P = periosteum and E = endosteum.

192
packing of Haversian systems or osteons. Pre- viously, Katz [14] and Katz and Ukraincik [15]

suggested that the arrangements of osteons and interstitial lamellae could be considered to be pseudo-hexagonal. Thus, the tetragonal and trigonal systems can be eliminated. The ultrasonic measurements have shown that Cn and C22 or c,^l^ and C55 are equal to each other, thereby leaving

only hexagonal symmetry as appropriate for bone.

B. The elastic stiffness of bone

Table 1 shows the ultrasonic velocities to- gether with their standard deviations at room temperature and 5 MHz along various directions

in the human femur specimens. The eight in- dependent velocity measurements provide four in- ternal cross-checks. For comparison the cor- responding sound velocities in a Durango fluo- rapatite single crystal [16] are included. From

these velocities and the independently measured

mass density p, the elastic stiffnesses of bone were calculated, as shown in table 2 where the pseudo-single crystal elastic stiffnesses of hydroxyapatite (HAP) [15], enamel and dentin

[17] are included, in addition to the elastic

stiffnesses of fluorapatite (FAP) [16]. Note in the case of the mineralized tissues that the stiffnesses, in general, increase with the amount

of apatite.

Table 1. Sound velocities in human compact bone and fluorapatite crystal at room temperature.

Mode Propagation Displacement Sound velocity (km/s) direction, direction, Fl uorapati te^ Human femur

N U (dried)

aL

aT

yL

TT3

45L

45Th

45T„

[001] [001]

[100]

[100]

[100]

[A oi]

[001]

[100] or [010]

[100]

[010] [001]

1/2 "i]

[0 -1 0]

7.586

3.635 6.842

3.978 3.638

7.020

3.811

4.033

4.18

2.16

3.55

1 .98 2.17

3.86

0.03

0.01 0.02

0.01 0.02

0.03

2.06 ± 0.01

2.24 ± 0.02

See reference [16].

^ 1

1 1 1

aL

1 1 1 1 1

--.^,^^^451

_

yL

-aT

51 —

45Tv

0

YT3-

<i 1111

45Th

1 1 1

>; YTh

1 1 0 10 20 30 40 50 60 70 Colatitude, (f) (degree)

80 90

Fig. 4. Angular dependence of the elastic stiffnesses of human bone.

while the degenerate transverse mode aT along the bone axis (X3) is separated out into the two branches, 45Tv ^ YT3 and ISJ^ ^ yT^^. In a hexagonal medium there exists, in general,

three pure mode directions (a, g, y) along each of which one purely longitudinal and two purely transverse modes of propagation occur, forming a mutually orthogonal set. Of these the a and y directions (see table 1) are known from the sym- metry of the hexagonal medium. The 6 direction,

which lies on a conical surface between the X3 axis and its perpendicular, is given in terms of

the elastic stiffnesses of the material. It has been found that no 6 direction exists in bone.

It may be that in bone the structural arrangement

of the collagen fibrils and fibers and the osteons may not allow any direction of high symmetry for

the 6 pure mode. This can explain the observed

phenomena that bone polarizes and filters the ultrasonic waves.

Table 2. Elastic stiffnesses of calcified tissues and apatite

single crystals at room temperature.

Cuu Fluorapatite Hydroxyapatite Enamel Dentin Bone

(GPa) [16] [15] [17] [17] (dried)

150 5 137 115 37 0 23 4 ± 0.31

C33 185 0 172 125 39 0 32 5 ± 0.44

42 51 39 6 22 8 5 70 8 71 + 0.13

C12 48 8 42 5 42 4 16 6 9 06 ± 0.38

62 2 54 9 30 0 8 7 9 11 ± 0.55 p(g/cm5) 3 2147 3 17 2 9 2 2 1 86

In figure 4 are plotted the elastic stiffnesses of bone as a function of angle 4) from the

X3 axis. This shows how the elastic stiffnesses

are interrelated to the orientation in a plane

parallel to the X3 axis. In other words, the longitudinal modes aL, 45L and yl are related,

C. The piezoelectric "stiffening"

Following Fukada and Yasuda [18] and Fukada

[19], point group 6^ was chosen as the piezoelectric class of symmetry for bone, which is also consistent with the pyroelectric measurements on bovine bone by Lang [1]. In table 3 is summarized the piezoelectric contribution to the elastic stiffnesses of bone, except for the two

^While it is true that bone does not exhibit

crystalline symmetry in the usual sense, as would

be demonstrated by x-ray diffraction analysis, 6 is the appropriate point symmetry to describe the microstructural level of the organization of bone

in that it is consistent both with the morphological observations and with the ultrasonic data within the precision of the measurements.

193
Table 3. Piezoelectric corrections to elastic stiffnesses of bone.

Mode -Dn,Et,a ^Dn.Et.a _ E,a

JJV_

aL ^33

aT

yL

TTh

YT3 cE

45Th

2 633

£33

2 ei5

-11

£11 + £33

1.9 X 10-8

0

0

0

3.9 X 10-7

2.3 X 10-6

mixed modes (45L and 45Ty), employing the piezoelectric constants for horse femur [19] and the permittivities of bovine bone by Gundjian and Chen [20] with the correction for frequency de- pendence following Liboff and Shamos [21]. Note that the piezoelectric "stiffening" in bone is very small and may therefore be neglected within

the experimental errors. Table 4 compares the values

(cD'° - cE'<')/cE.«

of the typical piezoelectric materials a-quartz

and polarized barium titanate ceramic, with the corresponding values of bone (see 2. Theoretical

background).

Table 4. Comparison of the piezoelectric contribution

to the elastic stiffnesses of bone, a-quartz and

and BaTi03 ceramic.

E,a\ / E.o

Bone (room temp.) a-Quartz (20 °C) BaTiO, ceramic (25 °C) Point group, 6 Point group, 32 Point group, 6 mm

(x 10-') (x io-2) (x 10-2)

11 0.18 0.86 0 93

33 0.19 0 17 0

44 82.0 0.072 28 0

12 0.46 -11.0 2 0

13 0.56 0 - 8 4

14 - 0.99

66 0 1.9 0

D. The frequency dependence of ultrasonic velocities

Figure 5 shows how the eight sound velocities

in dried human bone change with frequency at room temperature. In all cases the ultrasonic velocities are found to increase with increasing fre- quency. All the transverse modes exhibit almost

^ 4.0-

3.5

3.0

2.4

45L

J L 1_L

1 23456789 10 Frequency, MHz

2.2-

2.0-

1.8

45T,

J

Fig. 5.

1 2 3 4 5 Frequency, MHz

Frequency dependence of sound velocities

in human bone (dried).

similar dispersion behavior, while one of the longitudinal modes (yL) has a steeper slope than

the rest of modes

.

Brillouin [22] summarizes the explanations of

the geometric dispersion due to a periodic or discrete lattice, which were originated by Cauchy

and refined by Powell and Kelvin. This book also includes Brillouin's own research on the subject. More recently, Sutherland and Lingle [23] reported the geometric dispersion of acoustic waves by

an elastic-elastic composite of tungsten wires

embedded in an aluminum matrix over the incident

frequency range of 0.63 to 8.57 MHz. They also

194
reported the existence of pass- and forbiddenbands, in addition to the shift of the incident

frequency upon propagating through the material.

In their case the phase velocity always decreases

with increasing frequency within each pass band. For a linear viscoelastic solid, e.g . , polymethyl methacrylate, Asay, Lamberson and Guenther

[24] reported on the viscoelastic dispersion of ultrasonic waves, in which the phase velocity

increases with increasing frequency and approaches

a plateau. These results can be explained by re- laxation phenomenon of "molecular" units (see Gross [25]).

As mentioned earlier, bone is a hierarchal

composite on many levels of structure. Of principal concern here is the microstructural level of organization. In this case the osteons be- have as stiff hollow elastic fibers ensheathed

by a compliant viscoelastic material, mainly col- lagen and protein polysaccharides.

It is clear that much additional data are needed with respect to ultrasonic attenuation in bone over a wide frequency range as well as spectral

analysis of both transmitted and reflected pulses.

In addition it would be valuable to perform

studies on synthetic composites of collagen and hydroxyapatite in various combinations in order

to obtain dispersion data from controlled com- posites. Still from the modelling described

above, it is reasonable at present to explain the dispersion of the phase velocities in human com- pact bone in terms of its viscoelastic components.

Acknowledgment

Contribution No. 94 from the Laboratory

for Crystallographic Biophysics; this work

was supported by US PHS through NIDR Grant

No. 5Tl-DE-n7-14.

References

[1] Lang, S. B., Pyroelectric effect in bone

and tendon. Nature 212 , 704-705 (1966).

[2] Lang, S. B., Ultrasonic method for measuring elastic coefficients of bone and re- sults on fresh and dried bovine bones,

IEEE Trans. Bio-Med. Engng. 17, 101-105 TTW:

^ —

[3] Voigt, W., Lehrbuch der Kristal Iphysik

(B. G. Teubner, Leipzig, 1910); reprinted

with an additional appendix, 1928 (Johnson

Reprint Corp., New York, 1966).

[4] Cady, W. G. , Piezoelectricity (Dover Pub- lications, New York, 1964).

[5] Yoon, H. S. and Katz, J. L., Ultrasonic

wave propagation in human cortical bone -

I. Theoretical considerations for hexagonal symmetry, J. Biomech . 9^, 407-

412 (1976).

[6] Yoon, H. S. and Katz, J. L. , Ultrasonic

wave propagation in human cortical bone - III. Piezoelectric contribution, J_. Biomech . 9, 537-540 (1976).

[7] Yoon, H. S. and Katz, J. L., Ultrasonic

wave propagation in human cortical bone - II. Measurements of elastic properties

and microhardness , J. Biomech . 9, 459- 464 (1976).

[8] Yoon, H. S. and Newnham, R. E., The elastic

properties of beryl , Acta Cryst . A29 , 507-

509 (1973).

[9] McSkimin, H. J., Pulse superposition

method for measuring ultrasonic wave velo- cities in solids, J. Acoust. Soc. Am . 33 , 12-16 (1961).

[10] Weaver, J. K., The microscopic hardness of bone, J. Bone Joint Surg . 48A , 273-288

(1966).

[11] Kallieris, D., Hartemessungen an frischen

menschlichen Knochen, Z. Rechtsmed . 68 , 164-170 (1971).

[12] Rauber, A. A., Elasticitat und Festigkeit

der Knochen (Engelmann, Leipzig, 1876).

[13] Dempster, W. T. and Liddicoat, R. T., Compact bone as a non-isotropic material.

Am. J. Anat . 9^, 331-362 (1952).

[14] Katz, J. L. , Anisotropic elastic properties

of calcified tissues, lADR Program and Abstracts of Papers , p. 71, Abstract No. 73 (1971) (49th General Session, Intern. Assoc. Dent. Res., Chicago, Illinois).

[15] Katz, J. L. and Ukraincik, K. , On the anisotropic elastic properties of hydroxyapatite, J. Biomech . 4, 221-227 (1971).

[16] Yoon, H. S. and Newnham, R. E., Elastic

properties of f 1 uorapati te , Am. Mineral . 54, 1193-1197 (1969); Yoon, H. S., Elastic

properties of fluorapatite and beryl, Ph.D. Thesis (Pennsylvania State University,

University Park, PA, 1971).

[17] Lees, S. and Rollins, F. R. , Jr., Anisotropy

in hard dental tissues, J. Biomech . 5^, 557-

566 (1972).

[18] Fukada, E. and Yasuda, I., Piezoelectric ef- fects in collagen, Jap. J. Appl. Phys . 2» 117-121 (1964).

[19] Fukada, E., Mechanical deformation and electrical polarization in biological sub- stances, Biorheology 5_, 199-208 (1968).

[20] Gundjian, A. and Chen, L. L., Standardization and Interpretation of the Electromechanical Properties of Bone, IEEE Trans . Biomed. Engng . 21,, 177-182 (1974T;

[21] Liboff, A. R. and Shamos, M. H. , Solid State Physics of Bone, in Biological Mineralization , I. Zipkin, ed.. Chap. 14, pp. 335-395 (Wiley, New York, 1973).

[22] Brillouin, L. Wave Propagation in Periodic

Structures (Dover Publications, New York,

1953). ^

195
[23] Sutherland, H. J. and Lingle, R. , Geometric

dispersion of acoustic waves by a fibrous

composite, J. Composite Mater . 6_, 490-502

(1972).

[24] Asay, J. R., Lamberson, D. L., and Guenther,

A. H., Pressure and temperature dependence

of the acoustic velocities in polymethylmethacrylate, J. Appl. Phys . 40, 1768-1783

(1969).

[25] Gross, B., Mathematical Structure of the Theories of Viscoelasticity (Hermann & Cie. , Paris, 1953).

196
Reprinted from Ultrasonic Tissue Characterization II, M. Linzer, ed. , National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C., 1979).

ATTENUATION AND DISPERSION OF ULTRASOUND IN CANCELLOUS BONE

James E. Barger

Bolt Beranek and Newman Inc. Cambridge, Massachusetts 02138

Measurements of the insertion loss and insertion phase shift for ultrasound

transmitted through sections of cancellous bone from human skull are reported as functions of frequency over the range extending from 0.3 MHz to 3.0 MHz. The frequency dependence of insertion loss and of phase speed are both found to be caused principally by scattering of sound by the blood and fat filled interstices

in the bone matrix. Independent scattering measurements made at all observation

angles confirm the scattering phenomenon. It is concluded that both the high

attenuation and the significant dispersion at frequencies above about 1 MHz will limit the ability to characterize brain tissue by its backscatter at these high

frequencies. Also, most reported sound speeds in cancellous bone have been calculated from the time-of-f 1 ight of broad-band pulses, and are therefore group speeds. These group speeds will exceed the phase speeds by about 15 percent in magnitude.

Keywords: Attenuation; dispersion; skull bone; sound speed; ultrasound.

1. Introduction

The objective of this research was to measure,

as a continuous function of frequency in the range extending from 250 kHz to 2.5 MHz, both the insertion loss and the phase speed of ultrasound in cancellous bone. These measurements are especially

Important as design data for ultrasound systems

that are to characterize tissue through skull bone,

which comprises two outer tables of ivory bone and

an inner layer of cancellous bone, called diploe.

This diploe layer is known to contribute most of

the ultrasonic attenuation, as well as pulse waveform distortions, at diagnostic system frequencies

Successful tissue characterization involves fre- quency spectrum analysis, over a rather broad band

of frequency, of the sound scattered by a range- gated segment of tissue [2]. The attenuation that

occurs when scattered sound is transmitted through

diploe can change the spectrum in the band in which

signal amplitude exceeds noise amplitude by an amount sufficient to permit spectrum identification

Also, the pulse waveform distortions owing to fre- quency-dependent sound speed, also called dispersion, can substantially reduce the range resolution

of the broadband scattered sound. The experiments reported in this paper were all performed on cancellous bone samples obtained by

removing the ivory tables from a 9.5-mm thick sec- tion of human skull that had been fixed for about

six months in buffered formalin.

The experimental apparatus is described schemati

cally in figure 1. A pulse generator applies a

^Figures in brackets indicate literature

references at the end of this paper.

PULSE

GENERATOR

PDPll /40

RF OUTPUT

TRIGGER

INPUT

Focused

Transducer

Diploe Section

Glass-Walled

tonk

Ultrosonic Probe at Focus

Fig. 1. Schematic diagram of experimental ap- paratus for measuring insertion loss and phase through bone samples.

broadband, high-voltage pulse to a focused transducer. This transducer generates at its focus a pulse having a peak pressure of about eight bars

and a bandwidth (defined at 10 dB down points) of about 300 kHz to 2.5 MHz. The pulse is captured

and digitized at 20 MHz and subsequently transmit

ted to a PDPll/40 computer for spectral analysis. The ultrasonic waveforms are measured at the focus of the transducer with a small piezoelectri

197
disc probe 3 mm in diameter and 0.3 rrm thick. The disc is positioned with its major response axis

colli near with the axis of the ultrasonic beam. The disc diameter is equal to the diameter of the sound beam at about its 6-dB down points, so that

the probe output voltage is proportional to the sound pressure averaged over the sound beam. The insertion loss and phase of the diploe

sample are functions of the Fourier coefficients

T(f) of the pulse at the focus beyond the diploe

sample and of the Fourier coefficients S(f) of the pulse also measured at the focus, but without the diploe sample. The insertion loss in dB and the insertion phase angle are defined in eq. (1). Both functions are calculated at 19.5-kHz intervals of frequency by the computer.

IL = -20 log |T/S| (1) (})EargT-argS.

The phase speed of sound, Cj, in the diploe

sample can be calculated from the frequency ratio

of the insertion phase angle, ((i/f = (j)'. The insertion phase angle is the increase in phase of sound transmitted through the diploe layer less the in- crease in phase of sound transmitted through a water

layer having the same thickness, h, as the diploe

layer. This increase is expressed in eq. (2),

where 41 is the phase angle in degrees and Cq is the phase speed of sound in water.

<}. = 360 f h (CT' - c-i) . (2)

Solving for the phaee speed in diploe, we have

ci = Cq{1 + <l)' c^/SeOh)-' . (3)

If the phase speed Ci is a function of frequency,

which it will be if ^' is not constant, the trans- mission is said to be dispersive.

2. Experimental Results

A. Insertion Loss

The insertion loss for a 4-mm thick sample of diploe as a function of frequency is shown on figure 2. These data show very little loss at 0.3

MHz, with a sharply increasing loss between 0.7 and about 1.3 MHz. At higher frequencies, loss in-

-lol 1 1 1 1 1 0 3 07 II 15 19 FREQUENCY (MHz)

Fig. 2. Insertion loss of a 4-rran thick sample of

diploe compared with calculated loss due

to scattering and to absorption (A).

creases more slowly with increasing frequency,

reaching about 40 dB at 2 MHz,

B. Phase Speed

The insertion phase angle for a 4-mm thick

diploe sample is shown as a function of frequency

on figure 3. We see that the phase angle does not

1000

1 1 1 1

Cp - 2800 m/s »y -

800

600

400 ^^Cp- 2530 m/s

200

Cp" 2190nv*

1 1 1

1 ol i

I ' ^

"0 0 5 10 15 20 FREQUENCY (MHz)

Fig. 3. Insertion phase shift of a 4-mm thick

sample of diploe showing three tangent

regions of different group speed Cg.

increase linearly with frequency. Three different

values of phase angle are noted at three different

frequencies. The phase-frequency ratios are used together with eq. (3) to calculate the phase

speeds at the three different frequencies. The results at 0.5 MHz and 1.5 MHz are Ci = 2190 m/s

and Ci = 2530 m/s. Similar data on the 4-rim thick

diploe sample at 3.5 MHz showed c^ = 2800 m/s [3]. This tangent is sketched on figure 3, where it is seen to match with the data for frequencies above

2 MHz.

C. Scattered Sound

The insertion-loss measurement apparatus was modified, as follows, to measure the sound scat- tered by the diploe layer. A 6-mm diameter core

was cut from the skull sample and positioned coaxial ly at the focus. The probe was then scanned around a 9-cm radius circle centered on the focus

and including the incident sound axis. The sound pressure levels at 9 cm relative to the sound pressure level at the focus are shown on figure 4 as a function of observation angle. The narrow

beam directed back towards the source is sound reflected from the outer table. The small in- crease in sound pressure level at 180° is the transmitted sound. Sound reaching the probe at

all other angles has been scattered by the skull

core.

3. Discussion of Results

A. Insertion Loss

The insertion loss is shown on figure 2 to be a ( rapidly increasing function of frequency. The scattered sound shown on figure 4 is approximately

omnidirectional. Both of these experimental facts

lead us to suspect that sound is being scattered

by the fat- and blood-filled interstices in the spongy bone matrix. Omnidirectional scattering is caused by small discontinuities in the bulk modu198
ieo°

Fig. 4. Sound pressure levels measured 9 cm from

a core of diploe caused by 20-ps pulses

of 1-MHz sound incident from the direction

of 0 degrees.

lus of the medium. If the average bulk modulus

of diploe is represented by Bq and the bulk modulus of the material in the interstices by B, we

can write the scattering cross-sectional area a of

a single interstice having volume V [4] as

a

= 4^3X-^V2(B-B^/Bq)2 . (4)

We consider a plane wave having intensity I in- cident upon a layer of diploe that is i units

thick and having lateral area A. The total power,

Wg, scattered out of this slice having volume Aj, is the sum of power scattered by all N interstices

therein:

N N Ws = lE CTj = I 4it3x-MaB/B^)2 ^ V2 . (5) j=0 j

We simplify the expression for scattered power by

observing that the volume of the slice M is equal

to the total volume of scatterers NV, where the average volume is

N

V = N-l ^ Vj .

j

We define also the normalized variance B of the interstitial volumes.

6 = V2/V2 (6)

Combining eq. (5) with eq. (5), upon defining the product AI as the power, W^, incident upon the slice, we have the following result for the ratio

of power scattered from the slice to power incident

upon the slice.

W^/W. = 4Tr3x-'*3 V (aB/Bjj)25, (7)

Equation 7 is equal to the product ai, where a

is the intensity attenuation coefficient, because

the power balance for the power, W^-, transmitted

through a thin slice is W^ = Wi - Ws.

W^/w. = 1 - W^/W. = e-"^ ^ 1 - al (8)

Dividing by incident power and equating to the definition of attenuation coefficient, we have the desired equality. The average bulk modulus of the diploe sample

was calculated from measured mass density and sound

speed. The result was Bq = pqCo^ = 7.81- IQi" ybar.

The bulk modulus of the interstitial contents was taken to resemble blood, B = pc2 = 2.54-10io ybar.

The average interstitial volume was calculated

from the average diameter d of the interstices,

namely, 0.6 mm. The probability density distribution for interstice volumes is not known, but we

will assume it to be a Rayleigh distribution, for which B = 4/tt. When these quantities are substituted into eq. (7), we have for the attenuation due to scattering

ll/l (dB/cm) = 4.34a = 13.2 F** , (9)

where F is frequency in MHz. The fundamental result, eq. (4), is valid only for scattering elements that have diameters smaller

than about one-third wavelength. For our sample,

then, valid results occur at frequencies less than

1.3 MHz. At higher frequencies, the scattering

law saturates and changes to a frequency-squared

increase [4]. Therefore, the complete analytical

representation of scattering is given by eq. (10).

Il/l (dB/cm) = 13.2 F** F<F

° (10) =13.2 F2F2 F>F^ ,

where Fo(MHz) = (ci/3d) 10"^.

In addition to attenuation by scattering, there

is attenuation by absorption. A typical value of

the pressure attenuation coefficient in bone is 1.5 nepers/cm at 1 MHz [5]. The associated insertion loss per cm is ll/i = 13. 2F. The total at- tenuation, namely, the sum of absorption and scat- tering attenuation, is plotted on figure 2 for a 4-mm thick section. The agreement is very good between the experimental and the theoretical values of loss, indicating general accuracy of the scattering theory.

B. Sound Power Balance

The sound power balance used to obtain eq. (10) can be checked with the data shown on figure 4. The incident sound power, W-j , is given in terms of

the incident sound Intensity, I, and the radius, a, of the focus, W-j = ira^ I. The reflected sound power, Wp, is given in terms of the reflected half- beamwidtn, 9, and the reflected inteREity, Ip, measured at distance ro, W^- = •iT(rosine)2 l„. Tne scattered sound power, Wg, is given in terms of

the scattered sound intensity, Ig, measured at distance rg, = 4TTr§ Ig. The sound power balance requires power incident,

Wi , to equal the power scattered, Wg, plus power

reflected, Wf, plus power absorbed, Wg. We ob- served in the preceding section that attenuation by

absorption is equal to attenuation by scattering

at a frequency of 1 MHz. The scatter data on figure 4 are for this frequency, so we take Wg =

199
Wg. Dividing both sides of the power balance by the incident power, , we have eq. (11).

Wi

= 8{r^/a)Hl^/l.)

+ (rpSin6/a)2(I^/I.;

(11)

The value of Tq is 9 cm, the value of e is about

5° (at 3-dB down point), and the focal radius is

2 mm. The value of Is/Ii is equal to 10"'*-^ = 5,0- 10"5 and the value of Ip/Ii is equal to 10"^-^ = 1.2-10"^, because the reflected pressure is 19 dB

less than the incident pressure and the average

scattered pressure is 43 dB less than the incident

pressure. Substitution of all parameters into

eq. (11) gives the result (W^+Wf+Wa)/!^! = 0.994. Since a value of 1.0 confirms the hypothesis, this

result is very good, and the sound power is ac- curately accounted for by reflection, scattering,

and absorption. The transmitted power was neglected, since it is scarcely more intense than the forward-scattered sound.

C. Sound Speed

The phase speed, Cp, is defined in terms of the wavenumber, k: Cp = lo/k. This is the speed that

an observer of an harmonic wave would travel in order to see a constant wave pressure. The group

speed, Cg, is defined also in terms of the wavenumber: Cg = dio/dk. This is the speed that an observer of a "packet" of sound energy, having by

necessity a finite bandwidth, would travel in order to see a constant wave pressure. The two speeds are different whenever the medium is dispersive or whenever k is not a linear function of frequency. We see clearly from the data on figure

3 that sound propagation in diploe is dispersive.

This result is consistent with our finding that attenuation is due mainly to scattering, for sound propagation is then dispersive [6]. Experimental measurements of sound speed in bone, including diploe, have almost universally

used the time-of-flight of a sound impulse from

which to calculate sound speed. This method

yields the group speed, although experimenters

have not generally noted this. Their results can- not properly be compared with measurements of phase speed in diploe, unless the difference is accounted for. The definition of group speed yields eq. (12),

which expresses the group speed in terms of phase

speed.

Cp df

1- 1 (12)

The phase speed calculation from our data on the 4~mm skull sample (fig. 3 and ref. [3]) are plotted

on figure 5. We see that a simple frequency-power

law fits the experimental data quite well, according to Cp f", where n = 0.131. In this case

eq. (12) gives

n)-i = 1.15 c^

This calculated group speed is plotted on figure 5 together with the experimental values of phase

speed.

MEASURED GROUP SPEED,, CALCULATED GROUP SPEED Cg

MEASURED PHASE SPEED Cp

FREQUENCY (MHz)

Fig. 5. Measured values of phase speed and group speed in diploe shown with group speed

calculated from the phase speed.

The sound speed of the 4-mm diploe sample was measured by the time-of-flight method, using three pulses containing most of their energy between 0.3

to 0.4 MHz, 1.0 to 1.5 MHz, and 2.0 to 3.0 MHz

[3]. These measurements give the group speed, and

the values are plotted also in figure 5. It can

be seen that the measured values of group speed

are higher than measured values of phase speed,

and that they agree rather well with the calculated values.

D. Use of Focused Beam

A focused beam was used to make the measurements

reported herein because only in this way can a nar- row beam be generated several transducer-diameters

away from the transducer. The scattering of sound

by the bone adversely affects the beam shape at the focus only if a parameter g = /tT k^aL exceeds

unity [7]. The mean square deviation of the index

of refraction is v^, the average diameter of a scatterer is a, and the distance traversed by the sound beam is L. For the 4 mm thick diploe sample,

the value of the parameter g is only about 0.01,

so that no sensible beam distortion or phase aber- ration is caused at the focus by the scattering in the diploe layer.

4. Conclusions

We conclude that scattering of diagnostic ultrasound by the blood- and fat-filled interstices in diploe dominates sound attenuation at frequencies

above about 0.7 MHz and also introduces dispersion.

The detrimental effects of large diploe attenuation can be largely avoided by using interrogation

pulses that contain no frequency components greater

than about 0.7 MHz. Attenuation due to scattering

in the diploe studied equals the attenuation due

to absorption at 1 MHz and exceeds it at higher

frequences.

The detrimental effects due to diploe dispersion are confined only to the higher frequency

range, where scattering dominates attenuation.

Therefore, if low-frequency pulses are used, there

will be little dispersion. If, however, high

frequencies are necessary to obtain trans-skull tissue characteristics by spectral analysis, dispersion can significantly reduce range resolution.

For example, if a pulse contained energy in the band from 0.5 to 2.0 MHz, and was transmitted

through a 6-mm thick diploe layer, the depth

200
smearing in the brain due to dispersion would be 0.73 mm, but the nominal depth resolution of the same 1.5-MHz bandwidth pulse in an undispersive

water- like medium is 0.5 mm. We find that almost all reported sound speeds

in bone have been obtained by the time-of-flight

pulse method and are, therefore, actually group

speed. There is no evidence that sound propagation in ivory bone is dispersive, so these data

are equivalent to phase speed. Since we find

sound propagation in diploe to be dispersive, most published sound speed values in diploe will be higher than correct values for phase speed.

References

[1] White, D. N., Clark, J. M. , Curry, G. R. , and Stevenson, R. J., The Effects of the Skull Upon the Spatial and Temporal Distribution of

a Generated and Reflected Ultrasound Beam (Ultramedison, Kingston, Ontario, 1976).

[2] Lizzi, F. L. and Laviola, M. A., Ultrasonic

Spectral Investigations for Tissue Characterization in Ultrasound in Medicine , Denis

White and Ralph Barnes, eds.. Vol. 11, pp. 427-39 (Plenum Press, New York, 1976).

[3] Fry, F. J. and Barger, J. E., Acoustical

properties of human skull, to be published

in J. Acoust. Soc. Amer .

[4] Mason, W. P. and McSkimin, H. J., Attenuation and scattering of high frequency sound waves in metals and glasses, J. Acoust. Soc . Amer . 19, 472 (1947).

[5] Goldman, D. E. and Hueter, T. F. , Tabular

data of the velocity and absorption of high

frequency sound in mammalian tissue, J. Acoust . Soc. Amer . 28, 35-37 (1956).

[6] Howe, M. S., Wave propagation in random media,

J. Fluid Mech . 45, 769-83 (1971).

[7] Chernov, L. A., Wave Propagation in a Random

Medium (Dover Publications, Inc., New York,

1967).

201

Reprinted from Ultrasonic Tissue Characterization II, M. Linzer, ed., National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C., 1979).

TRANSKULL TRANSMISSION OF AXISYMMETRIC FOCUSED ULTRASONIC BEAfIS

IN THE 0.5 TO 1 MHZ FREQUENCY RANGE:

IMPLICATIONS FOR BRAIN TISSUE VISUALIZATION, INTERROGATION, AND THERAPY

F. J. Fry

Ultrasound Research Laboratories of the Indianapolis Center for Advanced Research

Indianapolis, Indiana 46202, U.S.A.

In order for ultrasound to become a practical clinical technique for diagnosis of many intracerebral diseases in the adult human, it has been necessary to answer questions concerning insertion loss of skull, temporal and spatial characteristics of beams operating in the 0.5 to 1.0 MHz range (the requisite frequency is a function

of the particular adult skull) have a maximum single pass skull insertion loss of nearly 10 dB (20 dB for a pulse echo system) which can be handled with present tech- niques to provide adequate signal strength from normal and pathological features of

brain. In this frequency range, for skulls in our studies, the appropriately se- lected frequency is unchanged after double pass skull transmission, the 6 dB beam width is increased by a maximum of 40 percent and the beam focus is shifted laterally

by a maximum of 3 mm. Resolution of string targets or live brain targets has been demonstrated to be in the 2 to 3 mm range at 1 MHz and at 0.5 MHz it appears that

4 to 6 mm resolution can be achieved.

A high intensity focused ultrasonic beam (1 MHz) has been transmitted through an excised adult skull and used to produce a focal thermal flaw in lucite. This simulation test indicates that the induction of transkull focal lesions in live adult

brain may now be possible.

Keywords: Axisymmetric; beams; focal thermal flaw; skull transmission; ultrasound.

1. Introduction

In the adult human skull the diploe layer is a dominant factor in determining the magnitude of insertion loss for a transmitted ultrasonic beam. Insertion loss characteristics for human skull as

a function of frequency have been documented in the literature [1-4]^ but only recently has the acoustic character of the specific skull layers

been more clearly defined [5]. These measurements indicate that frequencies less than 0.5

j MHz are necessary to have a single pass insertion

I loss less than 10 dB for some adult human skulls,

i Skulls we have studied with a loss of this magnii| tude at a given frequency will transmit an ultraI sonic signal of this same frequency with minimal

jj temporal distortion. For infants, the skull inf sertion loss at ordinarily used diagnostic fre- quencies (2.25 MHz) is less than 20 dB since

there is essentially no diploe layer. Since the two-way insertion loss is twice the one-way loss

in a pulse echo regime, the 20 dB maximum skull insertion loss (at the appropriate frequency) is not a serious impediment to pulse echo visual i-

^Figures in brackets indicate literature

references at the end of this paper.

zation and interrogation of brain features. Preservation of temporal coherence in the wave

is also an important feature and this can be achieved when the appropriate ultrasonic fre- quency range is selected.

Use of an axisymmetric focused beam in pre- vious studies indicated that preservation of the beam spatial focal character was achieved in a qualitative sense and that the maximum lateral displacement of the beam was of the order of

3 mm. Studies with phased array systems indi- cated a need for phase compensation at the re- ceiver array to correct for local skull thickness variations which change the arrival time of the waves at the receiver elements [6-8]. Such variations also lead to variable insertion

1 osses over the skul 1 . This report covers studies in which low in- tensity axisymmetric focused ultrasonic beams suitable for diagnostic medicine have been transmitted through excised adult human skull sections. The beams have been studied for their

temporal and spatial preservation as well as displacement after skull transmission.

Transkull B-scan presentations of physical

targets and live human brain indicate considerable potential for clinical diagnostic

medicine.

203
No previous literature seems to exist which

indicates the possibility of transmitting an intense focused ultrasound beam through an adult

human skull which would be capable of producing

focal lesions in brain. A series of experiments

reported here shows that a high intensity fo- cused ultrasonic beam of a frequency appro- priate for a given skull can be transmitted

through the excised adult human skull and pro- duce a thermal focal "lesion" in lucite [9]. Previous studies show that lucite, in the physical model sense used here, can simulate

1 ive brain tissue [10]

.

2. Materials and Methods

Measurement of frequency dependent attenuation loss in skull was made with a system de- scribed elsewhere [5]. A schematic diagram of the essential components is shown in figure 1.

Fig. 1. Schematic diagram for skull insertion loss measurements as a function of frequency.

PA = pul ser

T

= focused transducer

S = skull (formalin fixed)

P

= probe

D

= digitizer (8 bit 100 MHz Biomation

8100)

C

= computer (PDP-11/45)

PP = printer/ploter (Versatec 1100) x-y-z = (3 orthogonal) motion coordinate

system

Sound from the transducer passes through the

skull section under study and is received on a 3 mm diameter ferroelectric probe (10 MHz fun- damental resonance). The acoustic signal from

the probe is analyzed by an FFT (Fast Fourier

Transform) method in the skull and non-skull

case, and the difference of the Fourier coefficients at each frequency is taken as the insertion loss at that frequency. Measurements of beam configuration and displacement after skull transmission were made

by moving the probe in a direction perpendicular to the sound transmission axis. The skull

is also mounted on a coordinate system so that

it can be moved in 3 orthogonal directions.

Rotational axes are also provided so that the central ray of the transducer can be angulated

with respect to the skull surface. B-scans of physical models or patients were made with the apparatus shown schematically in figure 2. This apparatus provides a mechaniFig. 2. Schematic diagram for B-scan imaging.

PA = patient

T = tranceiver

W = water bath

X = mechanically driven linear motion

P = pul ser

A = ampl if ier

D = detector

SC = scan converter

M = monitor

cally driven linear scan path. Such a path is very limiting for scans involving skull since

it is important to approximately follow the

skull contour so that the central transducer

ray is normal to the skull surface for minimal

insertion loss. In order to have minimal beam displacement, this normal angulation configuration should be preserved.

For the high intensity focused beam study

involving production of thermal "lesions" in lucite (lucite used here as a brain simulation

target) the system configuration is shown in figure 3. A 1 MHz high power transducer [11]

with a 6 dB down (ultrasound intensity) beam diameter of 2.2 mm was used for this part of the study. The skulls used were obtained from

Fig. 3. Schematic diagram for high power

transkull test.

T = high power focused transducer

S = skull (formalin fixed)

L

= lucite block (2 inch x 2 inch x

2 inch)

W

= temperature-controlled water bath

PA = power amplifier (1 kW) TG = timing gate

FS = frequency source

204
patients at autopsy and were immediately placed

in Ringer's solution and stored in the refrigerator. By the time the experiments reported

here were conducted, the skulls had been placed

in formalin and stored at room temperature.

The storage procedure has been shown to provide

the necessary conditions for long-term stability of the acoustical properties of skull starting from the fresh excised state properties [12].

3. Results

One particular adult human skull has been selected from a group used in the preparation of

an extensive manuscript [5] on acoustic properties

of skull to illustrate the frequency filtering

properties of adult skull having a diploe layer.

Figure 4 shows the free field probe received

waveform transmitted from a focused transducer

with a damped resonant frequency of 2.5 MHz. When the skull is inserted between the transducer and the probe the signal strength is greatly attenuated, as will be described later.

A

•| 0. 5 ys/division

Fig. 4. Probe received waveforms (using setup

shown on fig. 1 with an oscilloscope

connected in fromt of D).

B = without skull (2.5 MHz)

A = with intervening skull (skull filtering permits 0.56 MHz transmission)

and the dominant transmitted frequency is 0.56

MHz. When a 0.5 MHz frequency damped pulse is transmitted through the skull, reflected from

a glass plate and passed again through the skull, the received waveform recorded from the original transducer is shown on figure 5. The double pass transmission loss is 10 dB for this skull. Use of ultrasonic frequencies in this range (0.5 MHz) is an advantage because of the temporal coherence preservation.

Spatial aspects of beam displacement and distortion after skull transmission for a 0.5 MHz focused beam is demonstrated on figure 6. These beam aspects have been studied with skull- to-probe distances from 2 to 10 cm, which is the range needed for brain target delineation in the

intact skull case with the live patient. In these two adult skulls the maximum beam disA

i 0.5 ys/division

Fig. 5. Transceiver waveforms after reflection

from glass plate (using setup shown on

fig. 1 with an oscilloscope connected

in front of D)

.

A = without skull (0.5 MHz, distortion

is due to the electrical driving

network)

B = after skull transmission (0.5 MHz,

skull has filtered out the high

frequency components in the A waveform but the 0.5 MHz fundamental

has been preserved.

205
100

90 80

•70

1-60

50

1-40

30

500 kHz tranducer

4 mm diameter disc probe

free field plot

L = 2 cm (skull in place)

L = 4 cm

L = 6 cm

L = 8 cm

F = L = 10 cm

Fig. 6. Beam distortion and displacement after single pass skull transmission as a function of probe- to-skull distance (L) for a fixed transducer-to-probe distance (20 cm). Lateral beam plots

and beam displacement obtained by moving the probe for the field plots (using setup shown on fig. 1 with oscilloscope connected in front of D to display the receiving probe output as a function of space coordinate). Insertion loss variations for skulls 6 and 8 were within

± 0.1 dB of the mean insertion loss value for all skull-to-probe distances L. Curves for each L distance are shown vertically displaced on the graph for reading convenience.

placement from the free field condition is 2.5 mm for any probe-to-skull position, and the maximum insertion loss variations for the same

range were within ± 0.1 dB of the mean value for

all axial distances studied. These studies also show that the 6 dB beam width is increased by a maximum of 40 percent. Other studies show [5] that when a focused transceiver is used with the probe as a target, the 6 dB beam widths de- crease in all cases over the 6 dB beam widths

in the single pass transmission case with the probe as receiver.

On the basis of temporal and spatial coherence and beam displacement, a 0.5 MHz frequency

is appropriate for adult human skulls. The in- sertion loss characteristic as a function of frequency for adult human skull, shown on figure

7, indicates the desirability of this frequency

(0.5 MHz) from a system sensitivity viewpoint if skull insertion loss is to be minimized. Given

these indicators for using 0.5 MHz ultrasonic

frequency for transkull visualization and interrogation of brain, the important remaining aspect

is resolution. Within the scope of these studies,

using a very preliminary transceiver prototype

(0.5 MHz) and no signal processing to provide

image enhancement, the scan of a string target

without intervening skull is shown on figure 8. Although the image quality is not ideal, it can

be seen that targets spaced 5 mm apart in real space can be resolved. Note also that range resolution has not been optimized since this

prototype transceiver is not highly damped.

+->

+->

Fig. 7.

28-

24

20

16

12

0.6 1.0 Frequency, MHz

1.4 1 .8

Insertion loss as a function of frequency

for single pass skull transmission (skull

6 section - formalin fixed).

206
Skull

Fig. 8. Monofilament nylon string target (0.01 inch string diameter) with 0.5 MHz focused transducer visualized with

system shown on fig. 2. A = without skull lowest set of 3 x 5 array has strings 1 cm apart on centers

.

B = with skull

This resolution will be improved with a larger

aperture angle, and with appropriate signal

processing this resolution will be apparent

over a wide dynamic range of signal strengths.

When the skull is interposed there are targets

which show evidence of lateral resolution similar to that in the non-skull case. Note that because of this scanning system's inability to follow the skull contour not all strings can be visualized. A scan mode in which the scanning

transducer axis is maintained perpendicular to the skull surface at the point of passage of

the central ray of the focused beam will resolve

this problem.

Our studies include a transkull visualization

ofa glioblastoma in a live adult patient in which an x-ray transaxial tomographic scan was also made. Results of these scans are shown on figure 9. In this case the skull insertion loss was small enough so that a 1 MHz focused trans- ceiver could be used (this unit is somewhat more

optimal than the 0.5 MHz prototype). The tumor

tissue was verified by pathological examination

at the time of surgery. The computerized axial

lateral ventricles

presumed

tumor region

EMI scan, live patient

focus marker

lateral ventricl

e

hard gristle

surgical ly

excised

pathologically

verified

tumor tissue (1

)

Fig. 9. B-scan of live human patient brain tumor compared to CAT (computerized axial tomography) scan. These scans are of a horizontal section through the brain. The ultrasound scans were made with the system shown on fig. 2. A = CAT scan

B = ultrasonic scan

tomographic scan showed presumed evidence of a tumor on normal brain structural grounds (ventricular outlines and displacement), but not on

a tissue density difference basis. The ultrasound scan clearly shows tissue differentiation.

The linear motion scan mode used does not follow

the skull contour so that the patient-transceiver

angle was selected to permit best viewing over

the tumor region. Spatial resolution of some targets in the lateral direction is 2 mm and in the longitudinal direction is 3 mm. It is an- ticipated that resolution using an appropriate

0.5 MHz transceiver will be no worse than twice these dimensions.

The above material is relevant to ultrasonic

regimes for transkull diagnostic purposes and

as such uses ultrasonic intensities appropriate

to that usage (low milliwatt average intensity

range). The subsequent material covers experiments demonstrating transmission through excised

adult human skull of intense ultrasonic focal beams suitable for such interactions as focal lesion production in brain.

For this study, the high power transducer was

used to produce focal thermal "lesions" in the

lucite block brain tissue simulator [10]. These

lesions were first produced with no skull intervening in the acoustic path. The human skull section was then inserted in the acoustic path

207
and focal lesions were produced of a size similar to those produced in the non-skull case.

A number of focal thermal lesions were produced

at various distances from the lucite surface

(typically 2 cm deep). The skull intervening

beam plot compared to the free field case is shown on figure 10. The single pass insertion

loss was 12 dB for this skull at the 1 MHz operating frequency of the transducer. More extensive coverage of this work is provided in other material [9]

.

2 10 1 Distance, mm

Fig. 10. Lateral beam plot obtained with high

intensity focused ultrasonic transducer, with and without intervening

skull. Measurements made with systems

shown on fig. 1

.

A = without skul

1

B = with skull, the beam axis was shifted 2 mm laterally from the free field position (A) and the insertion loss was 12 dB so no direct intensity comparisons

should be made from this figure.

4. Conclusion

This work has shown that for ultrasound to have a significant impact in medicine for diagnosis and/or therapeutics of brain disorders, it

is necessary to use ultrasonic frequencies in the 0.5 to 1.0 MHz range. In this range, the single

pass insertion losses can be held to a maximum

of 10 to 12 dB and the temporal coherence of the wave can be maintained. It has also been shown

that the focused beam configuration can be maintained after skull transmission so that the ad- vantages of resolution and intensity gain can be utilized. In diagnosis, these advantages lead

to excellent pictorial images of brain structures and ability to perform tissue interrogation

on temporarily undisturbed waves due to skull transmission. For potential therapeutics in brain, these ultrasonic techniques offer the pos- sibility of transkull ablation of tumor tissue

or other tissues such as that involved for focal epilepsy and modification of blood-brain barrier

for enhancing chemotherapeutics of tumor therapy

or other brain disorders.

When appropriate ultrasonic frequencies and

focal beams are used, it seems apparent that a significant impact can now be made in brain diagnosis and possibly therapeutics with ultrasonic

devices and techniques.

Acknowledgments

Work reported here was supported by NIH Grant

No. NOl-NS-3-2319, NSF Grant No. APR75-14487 and The Indianapolis Center for Advanced Research. References

[I] Heuter, T. F., Cavlieri, A., Langmuir, B., Butkus, W., Kyrazia, D., Ballantine, H. T. and

Bolt, R. H., The Detection of Intracranial

Tumors by Use of Ultrasound, Qua rterl y Progress

Report , Acoustics Laboratory, Massachusetts

Institute of Technology, Cambridge, Mass.,

pp. 38-46, July/September (1951).

[2] Goldman, D. E. and Hueter, T. F., Tublar data

of the velocity and absorption of high fre- quency sound in mammalian tissue, J. Acoust . Soc. Amer. 28 (1), 35-37 (1956).

[3] Martin, B. and McElhaney, J. F., The Acoustic

Properties of Human Skull Bones, in Biomedical

Material Research , Vol. 5, pp. 325-333 (John~

Wiley & Sons, Inc., New York, 1971).

[4] Smith, J. W., Phillips, D. J., von Ramm, 0. T. and Thurstone, F. L., Real Time B-Mode Echo- Encephalography, in Ultrasound in Medicine , Vol. 2, D. White, ed., pp. 373-381 (Plenum

Press, New York, 1976).

[5] Fry, F. J. and Barger, J. E., Acoustical

Properties of Human Skull (submitted to

J. Ac oust. Soc. Amer . , 1977).

[6] Phillips, D. J., Smith, S. W. , von Ramm, 0. T. and Thurstone, F. L., A Phase Compensation

Technique for B-Mode Echo-encephalography , in Ultrasound in Medicine , D. White, ed.. Vol. 1, pp. 345-404 (Plenum Press, New York, 1975).

[7] Smith, S. W., Mitter, E. B., von Ramm, 0. T., and Thurstone, F. L., Signal Processing Techniques for Improving B-Mode Echo-encephalography, in Ultrasound in Medicine , D. White, ed. Vol. 1, pp. 405-414 (Plenum Press, New York,

1975).

[8] Phillips, D. J., Smith, W. W. , von Ramm, 0. T., and Thurstone, F. L., Sampled Aperture Techniques Applied to B-Mode Echo-encephalography,

in Acoustical Holography , N. Booth, ed.. Vol. 6, pp. 103-120 (Plenum Press, New York, 1975).

[9] Fry, F. J., Transkull Transmission of an In- tense Focused Ultrasonic Beam, Ultrasound Med . Biol 3 (2,3), 179-184 (1977).

[10] Lele, P. P., Irradiation of plastics with

focused ultrasound: a simple method for eval- uation of dosage factors in neurological applications, J. Acoust. Soc. Amer . , 34 (4), 412- 420 (1962y~ ~

[II] Fry, F. J., Heimburger, R. F., Gibbons, L. V., and Eggleton, R. C, Ultrasound for Visualization and Modification of Brain Tissue, I . E . E.

E

. Trans. Sonics and Ultrasonics SU-17 (3), 165-

169 (1970y: ~ ~~

[12] White, D. N., Clark, J. M., Curry, G. R., and Stevenson, R. J., The Effects of the Skull Upon

the Spatial and Temporal Distribution of a Generated and Reflected Ultrasonic Beam, avail- able from Ul tramedi son. Box 763, Kingston,

Ontario, Canada (1976).

208
Reprinted from Ultrasonic Tissue Characterization II, M. Linzer, ed. , National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C., 1979).

SOME ADVANCES IN ACOUSTIC IMAGING THROUGH SKULL

S. W. Smith

Food and Drug Administration

Rockville, Maryland 20852, U.S.A.

D. J. Phillips

Center for Biomedical Engineering

University of Washington

Seattle, Washington 98105, U.S.A.

0. T- von Ramm and F. L. Thurstone

Department of Biomedical Engineering

Duke University

Durham, North Carolina 27706, U.S.A.

Previous attempts to image the adult brain through the skull using diagnostic

ultrasound have resulted in images of poor lateral resolution and limited dynamic

range.. The skull can be modeled as an acoustic lens whose attenuation increases

rapidly above 1 MHz and whose thickness variations introduce phase aberrations on the order of several wavelengths across the transducer aperture. Statistical analysis of skull thickness data indicate that an electronic sector scanner using a 1 MHz linear array transducer is less sensitive to these effects of the skull than traditional pulse echo systems operating at higher frequencies. Representative ultrasound tomograms of the brain are shown. In addition, water tank experiments are de- scribed in which the skull phase aberration, ^{x), was measured on line and removed

by incorporating a compensating phase variation, -<t>(x), into the transmit and re- ceive timing of a digitally controlled real time phased array imaging system. Pre- liminary results show that the lateral resolution of the imaging system is restored

in both the transmit and receive modes.

Key words: Brain scanning; echoencephalography ; neurology; phase compensation.

1, Introduction

Since the initial development of B-mode ultra- sonography, there have been many attempts (Fry et_ al . [1]^; Brinker and Taveras [2]) to produce

TiTgh quality cross-sectional images of the brain

through the intact adult skull. Real time B-mode echoencephalography was initially demonstrated by Somer in 1968 using phased array techniques. De- spite these efforts, B-mode echoencephalography

is seldom used clinically because of the poor quality of the images obtained with current techniques. One reason for the immediate widespread

application of computerized tomography in the head has been the failure of B-mode ultrasonic

imaging of the brain. The intervening presence

, of the skull results in poor signal to noise

ratio, limited dynamic range and reduced lateral resolution.

^Figures in brackets indicate literature

references at the end of this paper.

Three characteristics of skull bone are re- sponsible for poor quality brain images: (1) substantial attenuation of diagnostic ultrasound

by the skull bone; (2) rapid increase of that at- tenuation with the frequency of ultrasound; and

(3) the variation of thickness of the inner table

of the skull. In order to optimize B-mode ultrasound images of the brain, these aberrating ef- fects of the skull bone must be overcome. By a proper choice of transducer frequency, aperture

size, image format, and the use of effective

signal processing techniques, significant im- provement may be achieved in ultrasound tomograms

of the brain. In this manuscript these three problems of acoustic imaging through the skull will be examined. In addition one promising

technique will be described in which the effects

of phase variations due to the skull have been removed by a phase compensation process implemented with the real time, swept focus, phased array imaging system under current evaluation at Duke University (von Ramm and Thurstone [3]).

209
2. Ultrasound Attenuation of the Skull

A propagating ultrasonic pulse is strongly at- tenuated after two passages through the skull by such phenomena as diffractive scattering, mode

conversion, absorption, and the impedance mismatch at the skull-brain interface (White [4]).

Previous measurements (Hueter [5]; Smith et al . [11]; Fry et al . [6]) indicate that the attenuation of ultrasound by the skull is strongly fre- quency dependent increasing from approximately

10 to 20 dB/cm at 1 MHz to 50 to 60 dB/cm at

2 MHz.

In figure 1 the solid curve shows skull at- tenuation data from Hueter [5] normalized to a

1 cm thickness. The dashed line shows similar

data which we obtained from a preserved segment

of the adult skull. The data indicate that a 2 MHz signal is attenuated approximately 50 dB/cm

of travel through skull bone. The attenuation at

1 MHz is approximately 12 dB/cm. Much of the energy lost from the interrogating pulse returns

to the imaging system as unwanted acoustic noise.

FREQUENCY (MHz)

Fig. 1. Attenuation of skull bone versus frequency.

Such a high background reduces the signal to noise ratio, obscuring low level echo information

and restricting the useful dynamic range of the imaging system. The result is usually a high contrast B-mode image of the brain in which only

the strong specular echoes are displayed. From

the figure it can be seen that using a 1 MHz transducer substantially reduces the problem of high attenuation due to the skull. The rapid increase of attenuation with fre- quency also degrades the lateral resolution of a B-mode imaging system (Smith et al . [11]). For

a typical broadband diagnostic transducer, the ultrasonic pulse contains significant amounts of energy above and below the center-frequency.

After two passes through an adult skull the high

frequency content of the pulse has been significantly reduced relative to the low frequency

components. The center frequency of the ultrasound is effectively shifted to a lower fre- quency. For a fixed transducer aperture, such a frequency shift will result in degraded lateral resolution. Our experience with linear array transducers and broadband piston transducers

has indicated that an interrogating 2 MHz pulse

will show a center frequency of approximately

.8 MHz after two passes through the temporal

region of an adult skull. This results in more

than a twofold loss in resolution capability in the lateral dimensions. A 1 MHz ultrasonic pulse

is also shifted to approximately .8 MHz but the resultant loss of resolution is not as significant since the original transducer aperture will normally be larger at 1 MHz. For acoustic imaging through the skull, a 1 MHz transducer would appear to be a reasonable compromise considering

the requirements of system resolution, adequate

sensitivity and transducer size.

3. Thickness Variation of the Skull Bone

Of equal importance is a consideration of the effects of the thickness variation of the skull bone on image quality. In the temporal and parietal areas of the skull where most neurological ultrasound examinations are made, the inner table of the skull bone undergoes variation

in thickness on the order of 1 to 2 mm. It has been shown that phase variations are introduced

across the transducer aperture when acoustic

energy propagates through such a section of skull (Phillips et al . [8]). Figure 2 (Phillips et al . [8]) shows two elements of a one dimensional

transducer array simultaneously transmitting an acoustic pulse through a section of skull. (An analogous situation would apply in the receive

mode.) Since the acoustic velocity differs be- tween bone and soft tissue, variations in skull thickness will produce relative changes in the phases of the acoustic wavelets emerging from the inner table of the skull. The velocity of sound

has been reported to be approximately 3050 m/s

in skull bone (Martin and McElhaney [9]) while

the velocity in brain has been measured to be ap- proximately 1540 m/s (Wells [10]). The phase

variation H can be described by

^^-_2^f(pL-m (1)

where Ay is the thickness variations of the skull bone; Cs is the velocity of sound in the skull

210

1
TRANSDUCER SKULL

AY

Fig. 2. Phase aberrations introduced by the presence of skul 1

bone and Cg is the velocity of sound in brain. Based on the attenuation data and skull thickness variation, the skull bone can be modeled as an attenuating plate of varying thickness positioned in front of the transducer array. The validity of this model has been demonstrated by

studies of acoustic transmission through skull flaps performed in a water tank environment with

a linear array transducer (Phillips et al . [8]).

Acoustic field plots, experimentally measured

through skull, were compared with calculated

field plots using thickness data from the same

skulls. If the proposed model of the skull is valid as a first order approximation, then the character of the calculated plots should correlate closely with the experimental field measurements. Sections of skull from the temporal re- gion were frozen upon removal , thawed before

experimental use and then continuously stored in water. A diagram of the experimental arrangement

is shown in figure 3. The multielement array measured 24 mm in length and consists of 16,

equally-spaced, transducer elements. Each ele- ment is 0.35 mm in width and 14 mm in elevation.

The center frequency was experimentally measured

to be 1.8 MHz in water. The linear array was

placed just under the surface of the water with

the skull flap positioned in close proximity.

Independent control of the transmit timing delay

for each element was provided by continuously

variable, mono-stable multivibrators whose outputs were directly coupled into the solid state transmitter pulsers. The acoustic field patterns

of the array were recorded using a small trans- ducer probe which could resolve small spatial

variations of acoustic pressure. A Helix transducer probe measuring 0.46 mm in diameter was

used for this purpose. The acoustic pressure

was displayed on a cathode ray tube and recorded

on photographic film as a function of the lateral position of the translated field probe. The Helix probe was then moved aside and a simple piston transducer 12.5 mm in diameter was used as an illuminating transducer which provided

TRANSDUCER

Fig. 3. Measurement system for transducer field

plots

a smooth acoustic wavefront incident at the inner table of the skull. The relative arrival times

of the acoustic energy were recorded at the in- dividual array elements. The arrival time or phase variations are directly related to the variations in thickness of the skull across the transducer aperture. As a theoretical check of the proposed model of skull bone, computer simulations of acoustic field pressure were con- structed using the relative phase shifts of the acoustic pulses which had traveled through the

skull to the individual array elements. Figure 4 compares the experimental and cal- culated acoustic field plots which are used to evaluate the ultrasound beam character. Relative

acoustic pressure was normalized to the spatial

maximum of each scan and plotted as a function

of lateral position. The extent of the lateral translation is 25 mm. The element transmit delays were set for a 10 cm Gaussian focus, and the experimental field plot was recorded in the

focal plane. The upper plot shows the measured acoustic pressure at a range of 10 cm without the presence

of a skull flap; the middle plot shows the measured acoustic pressure when the adult skull is placed in front of the linear array. Of parti- cular interest is an azimuthal shift of the main

lobe to the right and the broad main lobe beamwidth. The bottom plot shows the computer cal- culation where the experimentally measured arrival times were incorporated into the transmit

timing sequence to simulate the acoustic field

pattern. In each simulation a transmit pulse

character was specified along with an attenuation factor for each element to more accurately

represent the experimental situation. However,

the amplitude variations across the transducer

aperture appeared to be of little significance

for thickness variations on the order of ultrasonic wavelengths. If the proposed model of the

skull is valid as a first order approximation,

then the character of the simulation should cor- relate closely with the acoustic field plot

obtained experimentally. The computer simulation shows an azimuthal shift of 4.9 mm to the

211
0

1 1 — 10 0

1 i 8

1 1 f u

1

/I

1 1

ft0 1 91 L

UJ 1.0 THROUGH

'LITUC .75

. SKULL

2: .50

UJ>

1—

a:

_]

UJ

.25

0

1 1

1 I 1 1 1 12 8 4 0 4 8 12

PHASE COMPENSATION

Fig. 4. Comparison of experimental versus cal- culated transducer field plots through

the skull.

right compared with the 5.0 mm shift in the experimental plot. The 6 dB beamwidths in both plots are noted to be 7.0 mm. The overall geo- metrical similarities lend considerable support

to the proposed first order model of the skull.

4. Resolution Limitations in the Presence of Phase Variations

One should now consider what is the extent of image degradation due to skull thickness variation in B-mode echoencephal ography . As has been briefly discussed in a previous publication

(Smith et al . [7]), the skull thickness itself

and hence the phase across a one-dimensional

transducer can be written as an polynomial

:

,th order

A + C2

x D3 + E"^ X x (2)

where <^ is the phase variation and x is the loca- tion on the skull or transducer. Thus the phase

variation due to the skull can be described as the sum of a mean phase shift, a linear phase

variation and higher order terms. On the average

the magnitude of the coefficients will decrease

with higher orders, i.e ., the finer grain variations will have smaller amplitudes than, for in- stance, the linear thickness variation of the

skull across the transducer. It is also evident

that the thickness variations of the skull will have less significance for imaging systems using

longer wavelengths.

The mean thickness and the 1st order thickness

variation of the skull make up the first two terms of the phase polynomial. The mean thickness of the skull with its acoustic velocity of 3050 m/s results in a range shift in an individual A-mode or B-mode line. A linear thickness

variation of the skull results in a refraction

of an A-mode or B-mode line according to Snell 's law. A range shift or an azimuthal shift does

not alter the beam width of a transducer. Hence, these effects do not degrade the resolution of an A-mode line or individual line of a B-mode image.

However, for a linear B-scan or a compound B-scan,

a linear skull phase variation which changes as

a transducer is moved across the skull can cause distortions and misregistration in both the range and lateral dimensions. A phased array

sector scanner as described by Somer [11] or Thurstone and von Ramm [12] produces a B-scan

image in real time through a single fixed spot

on the skull. Targets comprising such a sector

image are shifted uniformly in range and azimuth

by the first two terms of the phase polynomial

and consequently there is no image distortion.

Second and higher order skull phase variations

across the transducer aperture act like an undesired lens and degrade the lateral resolution of

a single A-mode line and every type of B-mode

scanner. The more random the phase variations,

the more disrupted is the diffraction pattern of the transducer. In fact, an upper limit can be put on the resolution capability of conventional

imaging through a phase aberrating medium (Good- man [13]). If A is the average linear dimension

of the transducer over which the phase aberration is constant to within, say, one radian,

then the resolution capability of the system is approximately that of a diffraction limited sys- tem with an effective transducer aperture, Dg^^, related to A by

Deff A (3)

where F is the distance from the transducer to

its focal point, and p is the distance from the transducer to the aberrating medium. Transducer

apertures of size greater than Deff collect more energy but have no greater resolution capability.

Note that the most severe resolution limitation

occurs for p - 0. that is, when the perturbing

medium is directly adjacent to the transducer

in which case Dgff = A. Thus, a contact scanner,

no matter what its aperture size, is limited to the same resolution as a transducer of size A. Long path, focussed, mechanical water bath scanners such as have been described by Fry et al . [1] and Thurstone et al . [14] can maintain

larger effective apertures, since the trans- ducer is sufficiently removed from the head so that the surface area of the skull subtended by the beam is very small and the relative phase

variation is less significant. However, these

mechanical scanners must move over the surface

of the skull making them susceptible to reg- istration errors due to refraction effects

212
from linear phase variations as explained above. Tomograms from a contact electronic sector scanner suffer no distortions from linear phase

variations. Therefore, if much of the thickness variation of the skull is a linear variation, an electronic sector scanner will be able

to maintain much of its normal resolution

capabi 1 ity

One should now consider how large the thickness variation or phase variation is in the skull in the areas most commonly used for acoustic windows.

For a conventional imaging system, the amount

of deviation of <fi(x) from the constant value A,

in eq. (2) , wi 1 1 be a good predictor of how badly

the image resolution will be degraded by phase

aberrations

Fried [15] has considered this question for astronomical imaging, wherein the changing re- fractive index of the moving air causes a phase

aberration affecting optical telescopes. One function which can be used to predict resolution

limitation is the root mean square phase variation, normalized to aperture size plotted as a function of aperture size.

D/2

/ [

<j;(x) - ^ury

-D/2

dx (4)

< > is an ensemble average, T(xT is the mean phase

across the aperture, and (()(x) is the phase shift

due to the skull at some point, x, within the aperture. To examine this function, phase variations were measured for the 16 elements of a linear array which are separated by 1.5 mm. Sets

of readings were taken at 10 different positions

in the temporal regions from an adult skull and a pediatric skull. The measurements were made by

recording the time of flight of an acoustic pulse

as it propagates through the skull and arrives at the elements of the linear array. For a given aperture size, the mean phase was first determined, and then the squares of the de- viations were calculated for each element within

that aperture. The sum of the squares was taken

and then normalized to the aperture size. This

was done for every possible aperture of elements

within one set of measurements e.g . , for an aperture size of eight elements there are nine pos- sible apertures within each 16 element array. The procedure was performed for each of the ten sets of measurements; a final ensemble average

was made, and the square root was taken. Figure 5 shows the result of the calculations

for two frequencies. The root mean square phase

variation is plotted in terms of radians versus aperture size for 1.8 MHz and 1 MHz. The function is monotonically increasing at least up to

an aperture size of 24 mm. It will level off at some larger size since the maximum thickness

variations of the bone are not more than a couple

of millimeters.

Fried [16] chooses the criterion that for root mean square (rms) phase variations of 1 radian

(a/2tt), the resolution capability has reached an upper limit no matter what the aperture size. Increasing the aperture dimension beyond this point, increases the phase variation so rapidly

that many elements on the aperture are always out

of phase. From figure 5, the phase variation is

8 16 24 APERTURE SIZE (mm)

Fig. 5. Root mean square skull phase deviation

from mean phase shift versus aperture

size.

one radian for an aperture of 6 mm at 1.8 MHz. Therefore, the maximum effective aperture for a conventional contact ultrasonic scanner at 1.8 MHz is 6 mm, i.e ., a numerical aperture of 7.3 wavelengths (ratio of aperture size to wavelength) and a resolution capability of 7.8 de- grees using the Rayleigh criterion. At 1 MHz

the rms phase variation reaches one radian for

an aperture size of 18 mm. Therefore, the maxi- mum effective aperture for a conventional con- tact ultrasonic scanner at 1 MHz is 18 mm or a numerical aperture of 12.2 wavelengths and a re- solution capability of 4.6 degrees. One con- cludes then that in the presence of such skull variations a conventional contact B-scanner can achieve a larger useful numerical aperture and hence better lateral resolution at 1 MHz than

at 1.8 MHz. At this point it would be interesting to make

another set of calculations which would be ap- plicable to an electronic sector scanner using

a contact transducer. It has been mentioned that

such an imaging system is insensitive to linear

phase variations across its aperture. Conse- quently, the relevant function to be calculated

is the rms phase deviation, R^, from the phase

slope for a given aperture size; i.e ., the de- viation from

<^l{x) = A + Bx (5)

Following the same line of thought as above, we now calculate

D/2

-D/2

(t)(x) - (f>|^(x) dx > , (6)

where (j)|_(x) is the slope of the phase data for a given aperture size. In this series of calculations, using the same data as above, the slope

and intercept were determined by the least squares methods, and the calculations proceeded as above. Figure 6 shows the results to be as expected.

For an electronic sector scanner at 1.8 MHz, the

rms phase variation reaches a critical value of

213
LU

a.o

Ui 1.5r

APERTURE SIZE (mm)

Fig. 6. Root mean square skull phase deviation

from phase slope versus aperture size.

one radian at an aperture size of approximately

14 mm. Therefore, on the average, the maximum

effective aperture size will be 14 mm or 17 wavelengths and the resolution capability will be 3.4 degrees. Now at 1 MHz, the rms phase variation for a sector scanner never reaches one radian for the

Fig. 7. Horizontal cross sectional ultrasound

image of brain through adult skull compared to anatomical brain section.

aperture data which we measured. If we extrapolate this curve, we find that it will reach one radian near 1.25 inches or 32 mm. This cor- responds to a maximum effective numerical aperture of 21 wavelengths and a resolution capa- bility of 2.7 degrees.

These calculations, based on limited data,

have yielded consistent results. For the one- dimensional skull data analyzed here, a 1 MHz transducer can achieve a larger effective numerical aperture and hence better lateral resolution than can a transducer operating at a higher

frequency. The considerations of the increasing

attenuation with frequency of ultrasound by the

skull lend added support to the choice of a

1 MHz transducer for transkull imaging. In ad- dition since a phased array sector scanner is insensitive to linear phase variations due to the skull, such a system would offer advantages

in maintaining its resolution capability over conventional B-scanners.

A representative image is shown in figure 7 using the real time phased array B-scan system

with a 1 MHz, 31 mm linear array transducer.

A horizontal ultrasound tomogram through the

skull of a 45 year old female is compared to an anatomical cross-section (Roberts and Hanaway

[17]). As indicated, one can see the far skull,

the mid-cerebral fissure, the posterior areas

of the lateral ventricles, mid-line structures

and echoes from the sylvian fissure. The corpus callosum appears as the relatively echo free

band between the mid-cerebral fissure and the posterior areas of the lateral ventricles.

Images of similar quality along with real time

anterior horns of lateral ventricles

Fig. 8. Coronal cross sectional ultrasound image

of brain through skull compared to ana- tomical brain section.

214
display or pulsating cephalic blood vessels have

been obtained in both horizontal and coronal sections

Figure 8 shows a coronal scan in a ten year

old normal female taken slightly posterior to the pinna of the ear. In this view the far skull, the mid-cerebral fissure, the anterior

horns of the lateral ventricles, the third

ventricle and the near side sylvian fissure are visualized. Furthermore, the corpus callosum

is again seen as a relatively echo-free band above the anterior portions of the lateral ventricles. In this view the posterior cerebral arteries are consistently seen as pulsating

echoes in the lower portion of the scan on both sides of the mid-line. In addition, the branch

of the middle cerebral artery is also seen quite

frequently in the area of the sylvian fissure.

5. Resolution Improvement via Phase Compensation

Having arrived at an improved transducer con- figuration to overcome partially the attenuation

and phase aberration effects of the skull, signal

processing techniques have been used in preliminary experiments to remove more completely the effects of skull thickness variations in a phased

array imaging system.

Perhaps the most logical signal processing

method is to measure the phase variation <i>{x) of the aberrating-medium before an image is made,

determine a compensating phase variation, -<t>(x), and then add such a phase compensation to the imaging system in the form of an acoustic lens. Independent control over each element of the transducer array in transmit and receive modes

provided a method to produce any desired wavefront response within the limitations imposed by

element size and spacing with respect to the wavelength of ultrasound used. Such a process

has long been recommended to compensate for lens aberrations in optical telescopes (Tsujiuchi

[18]).

Recently several groups have reported con- struction of large sampled aperture telescopes

whose mirror elements will move to compensate

for the time varying phase aberrations of the turbulent atmosphere in real time (Muller and Buffington [19]; Hardy et a1 . [20]).

Figure 9 illustrates the basic principle of the phase compensation technique in an elec- tronic phased array scanner (Phillips et al . [8]). Five representative elements of the trans- ducer array are chosen with a section of skull placed in front of them. Part A shows the phase

aberrated wavefronts emerging from a variable

thickness skull when the elements are phased to produce a focussed wavefront in a medium of constant acoustic velocity. In B, an acoustic

wavefront provided by another source passes from

the inner table of the skull to the transducer

elements. Knowledge of the spatial character

of the incident wavefront and the arrival times

at each transducer element allows for the de- termination of the relative changes in skull thickness in front of the elements comprising

the aperture. When these relative phase variations are incorporated into the transmit timing

as shown in C, the emergent wavefronts exhibit

a restored phase character similar to that originally intended.

received echo programmable

Fig. 9. Principle of the phase compensation

technique.

The following experiment using the equipment

configuration of figure 3 is presented to il- lustrate preliminary findings (Phillips et al . [8]) utilizing phase compensation. As shown in figure 10a the control field plot was recorded

at a range of 10 cm when the transducer elements

were phased for a 10 cm focus and the skull re- moved. The 6 dB beamwidth was experimentally

measured to be 4.5 mm compared with a calculated

4.3 beamwidth for the diffraction limited aperture. Figure 10b shows the beam plot with the adult skull positioned between the array and field probe. The 6 dB beamwidth was increased

to 14.0 mm, and a main lobe refraction of 3.0 mm

to the right is also apparent. The relative

phase changes as a function of skull position

in front of the linear array were measured, and

the phase compensated beam profile is shown in figure 10c. Although the acoustic beam is at- tenuated due to a single transmission through

skull bone, the phase character due to variations

in skull thickness is restored. The refracted

lobe was returned to within 0.5 mm of the axis defined in the control, and the 6 dB beamwidth

was significantly improved and measured to be 4.5 cm. Although the foregoing studies were performed for the transmit mode in a direction

normal to the face of the transducer, it was hoped that similar improvements could be realized when the ultrasound pulse was electronically steered and focussed in the receive mode. The next step was to perform phase com- pensation studies for the transmit-receive

mode in the water tank environment through a

215
mm

Fig. 10. Acoustic field plots demonstrating phase

compensation in the transmit mode.

preserved skull segment. A phased array B-scan system capable of 2 to 4 mm resolution in range

and azimuth throughout a 15 cm field of view

was used (von Ramm and Thurstone [3]). A 31 mm,

1 MHz, linear array was used to minimize the ef- fects of skull attenuation and reduce the relative phase variation across the transducer as has been described above. To implement the phase

compensation technique, pulses from the array

passed through the skull and were reflected by a wire target located at a range of 7 cm. Not- withstanding the aberrated character of the initial transmitted pulse, the echoes from the wire

target return to the skull as spherical waves

since the wire approximates a line reflector of infinitesimal size. Figure 11 illustrates the process of phase

compensation. Part A in figure 11 shows the re- ceived echoes for five representative channels.

The returning echoes arrive at individual ele- ments of the array according to the spherical

character of the incident wavefront. Since the programmable delay lines are sequenced to pro- vide a focus for all points throughout the ob- ject volume of interest, the electronic pulses

corresponding to the received echoes emerge from

the delay lines at identical times as shown to the right. In part B a skull sample was placed

in front of the linear array. Due to the aber- rating nature of the skull the emerging wavefront

no longer resembles a diverging spherical wave. Since the delay times are sequenced for a focus

in a homogeneous medium it is not surprising that

Fig. 11. Principle of phase compensation tech- nique in the receive mode.

the outputs from the delay lines are unable to provide phase coherence for an echo returning

from a point target when the skull is interposed.

In part C the received echoes from the same point

target through the skull flap are restored to phase coherence by adjusting the delays of each delay line under software control, so that all outputs arrive in time coincidence with that of one channel chosen as reference. This procedure

removes the timing errors caused when imaging

through skull of varying thickness or composition.

Results are shown in the images of figure 12. Each image was made with the gain and reject

controls set for optimum resolution. The left hand control image shows the ultrasound image of

a line target used to produce the illuminating

wavefront and a series of strings of variable

spacing (5 mm to 10 mm) without the presence of

a skull. The center image shows clearly the de- graded resolution in the image of the same targets

through a section of bone from the temporal area

of the skull. The right hand image shows a significant restoration of image resolution for the

line target and the strings in the center of the field of view. Decreased off -axis sensitivity

216
CONTROL THROUGH SKULL THROUGH SKULL WITH

PHASE COMPENSATION

Fig. 12. Resolution targets through skull using phase compensation.

through the skull as the critical angle was ap- proached was responsible for the target dropout

at the edges of the field of view. The phase

compensation technique clearly reduced the spot

size of the targets imaged through the skull,

thus restoring much of the azimuthal resolution

of the system.

Implementation of the phase compensation technique in a clinical environment will be more complex since additional procedures and techniques must be utilized for ease of clinical use. Of basic importance is the necessity of producing

a smooth acoustic wavefront incident at the inner

table, within a live, intact head. One can speculate that the pineal gland which is calcified in most adults or the relatively planar structures

of the third ventricle or the far side of the

skull may serve as adequate reflectors to use to measure the phase variation of the inner table

of the skul 1

The results presented here are still preliminary. It is difficult to predict how much im- provement will be necessary in lateral resolution and target dynamic range before B-mode images

of cephalic structures routinely provide information of diagnostic value. However, the improve- ments presented here are encouraging and may lead

to new techniques of acoustic imaging of cephalic

structures having acceptable resolution for diagnostic evaluation.

Acknowledgments

This work was supported by USPHS grants

HL-12715, HL-14228, HS-01613, and by the Food

and Drug Administration, Bureau of Radiological

Health. References

[1] Fry, F. J., Eggleton, R. C. , and Heim- burger, R. F., Transkull Visualization

of Brain Using Ultrasound: An Experimental Study, in Ultrasonics in Medicine , M. de Vlieger, D. N. White, and V. R. McCready, eds., pp. 97-103 (American

Elsevier Publishing Company, Inc., New

York, 1974).

[2] Brinker, R. A. and Taveras, J. M., Ultrasound cross-sectional pictures of the head,

Acta. Radiol. Diag . 5, 745-753 (1966).

[3] Von Ramm, 0. T. and Thurstone, F. L., Cardiac imaging using a phased array ultrasound system I: system design. Circulation

53 (2), 258-262 (1976).

[ 4 ] Wh i te , D . N . , Ultrasonic Echo-encephal o- graphy . Medical Ultrasonic Laboratory,

Kingston, Ontario, Queen's University, 1970.

[5] Hueter, T. F., Messung der Ul traschal 1 ab- sorption in menschlichen Schadel knochen und ihre Abhangigkeit von der Frequenz, Natur- wissenschaften 39, 21-22 (1952).

[6] Fry, F. J., Barger, J. E., and Sanghivi,

N. T., Acoustic Properties of Human Skull

Bone. (Proceedings of the World Federation

of Ultrasound in Medicine and Biology), in Ultrasound in Medicine , D. N. White and R. Brown, eds.. Vol. 3, p. 2095 (Plenum Press, New York, 1977).

[7] Smith, S. W. , Phillips, D. J., von Ramm,

0. T., and Thurstone, F. L., Real Time B- mode Echoencephalography , in Ultrasound in Medicine , D. N. White, ed.. Vol. II, pp. 373-382 (Plenum Press, New York, 1976).

[8] Phillips, D. J., Smith, S. W., von Ramm,

0. T., and Thurstone, F. L. , Sampled Aperture Techniques Applied to B-mode Echo- encephalography, in Acoustical Holography , N. Booth, ed.. Vol. 6, pp. 106-119 (Plenum

Press, New York, 1975).

[9] Martin, B. and McElhaney, J. N. , The Acoustic properties of human skull bone,

J. Biomed Mater. Res . 5, 325-333 (1971).

[10] Wells, P. N. T., Physical Principles of Ultrasonic Diagnosis (Academic Press, New

York, 1969).

[11] Somer, J. C, Electronic sector scanning

for ultrasonic diagnosis. Ultrasonics 6, 153-159 (1968).

[12] Thurstone, F. L. and von Ramm, 0. T. A New Ultrasound Imaging Technique Employing

Two-Dimensional Electronic Beam Steering,

in Acoustical Holography , P. S. Green, ed..

Vol. 5, pp. 249-250 (Plenum Press, New York,

1974).

217
[13] Goodman, J. W. , Huntley, W. H. Jr., Jackson,

D. W., and Lehman, M., Wavefront-Reconstruction Imaging Through Random Media, Appl ied Physics Lett . 8, 311-313 (1966).

[14] Thurstone, F. L., Kjosnes, N. I., and McKinney, W. M., Ultrasonic scanning of biologic tissue by a new technique, Science 149,-302-303 (1965).

[15] Fried, D. L., Optical resolution through a randomly i nhomogeneous medium for very long and very short exposures, J. Opt. Soc . Amer. 56, 1372-1379 (1966).

[16] Fried, D. L., Statistics of a geometric

representation of a wavefront distortion,

J. Opt. Soc. Amer . 55, 1427-1435 (1965).

[17] Roberts, M. and Hanaway, J., Atlas of the Human Brain in Section , pp. 22-47 (Lea and Feiberger, Philadelphia, 1970).

[18] Tsujiuchi, J., Correction of Optical Images

of Compensation of Aberrations and bv Spatial Frequency Filtering, in Progress in Optics, II , E. Wolf, ed., pp. 133-182

(John Wiley and Sons, New York, 1963).

[19] Muller, R. A. and Buffington, A., Real time

correction of atmospherically degraded

telescope images through image sharpening,

J. Opt. Soc. Amer . 64, 1200-1210 (1974).

[20] Hardy, J. W., Feibleib, J., and Wyant,

J. C, Real Time Phase Correction of Optical Imaging Systems, in Digest of Optical Propagation Through Turbulence

(abstract only). July 9-11, 1974, Boul der

,

Colorado, ThBl-l-ThBl-4.

218
Chapter 8

IMAGE RECONSTRUCTION

J

219

Reprinted from Ultrasonic! Tissue Characterization II, M. Linzer, ed.. National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C., 1979).

CHARACTERIZATION OF IN VIVO BREAST TISSUE BY ULTRASONIC

TIME-OF-FLIGHT COMPUTED TOMOGRAPHY

G. H. Glover

General Electric Company

Medical Systems Division

Applied Science and Diagnostic Imaging Lab Milwaukee, Wisconsin 53201, U.S.A.

The use of ultrasonic time-of-f 1 ight (TOF) computed tomography for characterization of tissue in live breasts is reported. Quantitative distributions of the re- fractive index within a tomogram of the specimen were obtained by reconstruction from

5 MHz TOF projection data. Fifteen breast cancer patients and five asymptomatic

volunteers were scanned during the clinical feasibility study. The results indicate

that young, dense breasts have wide variation in the refractive index distributions.

In older subjects, however, various lesions are found to have distinctive indices.

Histograms of the reconstructions show differences between pathological and normal breasts.

Keywords: Breast cancer; computerized tomography; mammography; time-of-f 1 ight;

tissue characterization; ultrasonic imaging; ultrasound.

1. Introduction

Ultrasonic energy potentially provides an at- tractive modality for mass screening programs

in breast cancer detection. Its advantage is particularly evident in light of the recent publicity concerning suspected hazards of radiographic procedures. It is, therefore, of in- terest to characterize quantitatively the ultrasonic properties of breast tissue, with an eye towards differentiation of various neoplasms and breast parenchyma. A useful vehicle for this purpose (and perhaps for mass screening as well)

is computerized time-of-f1

i ght (TOF) tomography.

TOF tomography was first published by Greenleaf et al . [l]i in 1975. Since then, several other workers [2,3] have published reports on other aspects of this technology. In this technique, the speed of propagation of an ultrasonic

wave is accurately measured along many uniformly

sampled paths through the specimen (see fig. 1). The data are obtained from measurements of the time delay for reception of a short pulse traversing the path. In the parallel-scan geometry

shown in figure 1, the set of values corresponding

to a given angle relative to the specimen collectively form one TOF projection (or view). Other

projections are then obtained by rotating the scanner relative to the specimen. A two- dimensional refractive index distribution is then obtained from the projection data by computerized

image reconstruction techniques [4]. The result-

^Figures in brackets indicate literature

references at the end of this paper.

SIDE VIEW

Fig. 1. Geometry of scanner. A single pair of transducers are translated in 1 mm steps

to form one projection. One hundred projections are obtained by rotation of

the scanner through 180 degrees. Other

slices are acquired with the scanner

lowered relative to the breast (side view).

221
ing images are displayed as an array of square

pixels, each of which represents the local speed

of propagation supported by the tissue. The process is very much analogous to x-ray computed

tomography methods.

The speed of propagation of an ultrasound wave

depends upon the elasticity and mass density of

the propagating medium. Thus, the TOF reconstructions directly provide quantitative, localized in- formation about significant mechanical properties

of the bulk tissue. (By contrast, echo amplitude

is a very complicated function of interfacial and bulk tissue ultrasonic characteristics, as well

as of geometry.) The propagation velocity has been found to vary by several percent in various

types of soft tissue [5]. In this paper, velocity measurements of tissue structure in in vivo breasts

are presented and analyzed with the aid of histograms. In the following section, the experimental

technique is described.

2. Experiment

A. Technique

Only a brief description is given here as the details have been presented elsewhere [3,6]. The scanner used in the study is shown in figure 2. A transmitter and a receiver transducer (Panametrics

,

5 MHz) were rigidly mounted on a carriage which

could be translated by a stepping motor. Samples were acquired at 1 mm intervals (163 samples/

projection). The tank was mounted under a canvas

sling supported by a metal and wooden structure so that the subject lay prone with the breast im- mersed in the water of the inner tank. Thus, horizontal slices 5 mm thick transaxial to the breast

were obtained as shown in figure 1. After the first projection was acquired, additional projections were measured as the tank was rotated through

180 degrees in 1.8 degree steps by a second motor.

The TOF data (n seconds of delay) were stored on digital cassette tape for later reconstruction.

Fig. 2. Scanner mechanism mounted in wooden frame. Both tanks are water filled. The breast

is immersed in inner tank, which is isolat- ed for electrical precaution.

The reconstructions were obtained using the con- volution algorithm [4]. The original reconstruction utilized time-sharing software and were displayed in a 57 x 57 matrix format [61. For the present work, the images were re-reconstructed in

a 64 x 64 matrix representing 12 x 12 cm with a minicomputer. Reconstruction time was about 60 seconds using conventional FORTRAN coding.

The velocity values v are given in CTU values,

defined as [6]

CTU

VO

'0

x 1000, (1)

where vg is the velocity of propagation in the water (at about 34 °C). Thus, +10 CTU corresponds

to a velocity 1 percent greater than for water.

The clinical study was performed at the Albany

Medical College. Fifteen symptomatic patients and five asymptomatic volunteers were scanned. Mam- mograms and clinical reports for the patients were available before the scans to help localize the region of interest. Generally, three slices 1 cm apart for the pathological breast and one slice of

the contralateral breast were acquired. After the TOF scans, biopsies were performed on the suspicious breasts. These results were then made available for comparison with the reconstructions. A thorough historical comparison would have been desirable, but was outside the scope of this study.

B. Results

Figures 3 and 4 show typical reconstructions of breasts having lesions. In these pictures, high

velocities are depicted as black. Figure 3 shows

,a right breast (age 53) containing a large (benign) fibroadenoma. The CTU values for the lesion

are 20-28, while the mammory fat (white areas) has CTU values of about -60. The left breast depicted

on figure 4 (age 44) contains infiltrating ductal carcinoma with CTU numbers 40-45. The mammory fat

has CTU values similar to those in figure 3. The streaking artifacts in these pictures de- rive from patient motion during the long scan time

required to obtain the data (about 9 minutes/

slice). As a result, the pictures are much noisier

(standard deviation, 10 CTU in the water bath) than the intrinsic velocity resolution of the system determined with a stationary phantom (a

2 CTU). Nevertheless, the reconstructions are of sufficient accuracy to characterize the large-mass

lesions studied here. Table 1 presents a summary of the CTU values for several types of lesions as well as fat and asympTable 1. Summary of CTU values for several types

of lesions, fat and asymptomatic breast parenchyma

.

Symptomatic patients (ages 33 to 85) mammary fat

normal parenchyma

f i broadenoma/f ibrocystic disease

(benign

)

carcinoma

inflammatory skin thickening

Asymptomatic subjects (ages 24 to 29)

fibrotic mammary glands, ducts

CTU numbers

-50 to -70

0 to 15

12 to 30

40 to 60 40 to 65

8 to 60

222
Fig. 3. Reconstruction of breast with large

fibroadenoma (black region).

tomatic (presumed normal) breast parenchyma. In the older patients, the CTU values were found to

be distinctive for fat, normal parenchyma, fibrotic

tissue, and carcinoma. Malignant lesions and in- flammatory skin thickening due to the presence of

an internal malignant neoplasm have characteristic

CTU numbers greater than 40, while benign lesions

(fibrocystic disease, fibroadenoma) have CTU values

less than 30. However, the CTU values for the dense breasts of the younger asymptomatic subjects

span the entire range. It is, therefore, impossible to differentiate solely on the basis of CTU value neoplastic tissue from normal fibrotic

parenchyma in such cases.

In several slices wherein the lesion did not completely fill the 5 mm axial slice thickness, the

CTU values were less than the bulk numbers in the

table. These partial volume effects arise because

the component of transmitted signal which arrives

earlier due to traversal through the high velocity

lesion ultimately becomes too low in amplitude to

be detected relative to the signal components which

exclude the lesion. The transition is not perfectly sharp due to refraction and tissue dependent

attenuation effects. Excluding such cases, however,

there were no counter-examples to the CTU values classifications in the table.

3. Statistical Analysis

A rudimentary statistical analysis of the re- constructions was performed by computing the histograms and cumulative distribution functions.

For this purpose, a program was developed which

searched the matrix for the edge of the breast,

fit an arbitrary ellipse to the boundary points

by regression, and calculated the histogram for those elements within the ellipse. The class

interval was chosen as 3 CTU numbers in com- puting the histograms. The results were normalized to remove variations in specimen size. Figure 5 shows histograms for a young, asympFig. 4. Reconstruction showing infiltrating ductal carcinoma (lower quadrant) and in- flammatory carcinoma central region.

tomatic subject. Note that the two normal breasts have similar tissue distributions. This

was not always the case, although generally the skew and kurtosis of the histograms were similar.

The distributions are peaked near CTU = 0 and contain considerable fibrotic tissue with high

CTU numbers. The variations in the histograms

for different young subjects were quite wide.

This is illustrated by plotting the (inverse)

cumulative probability function.

0j = E fi (2)

-80 -60 -40 -20 0 20 40 60 CTU VALUES

Fig. 5. Histograms of right (solid) and left

(dashed) breasts of 24 year old asymptomatic subject. The distributions are very similar and centered near CTU = 0. Considerable fibrotic structure is evident

from the peak position and area under the

high valued tails.

223
where f-; is the frequency for the i^'^ CTU value. Curves for three of the subjects are shown in figure 6. As may be seen, the curves span a large range of CTU values.

10°

CTU VALUES

Fig. 6. Inverse cumulative probability function

for three normal, young subjects. The zero asymptotes (which reflect peak CTU

values) show wide variation.

Figure 7 shows histograms for a 58 year old patient with carcinoma in the right breast and a normal left breast. Note that the peak for the normal histogram has shifted position to low negative values relative to figure 5. This reflects

the atrophy of glandular structure (high CTU) and

CTU VALUES

Fig. 7. Histograms of 58 year old patient with

carcinoma in right breast (solid) and

normal (dashed) left breast. The normal distribution is peaked near CTU = -40,

indicating atrophy of the glandular tissue and replacement by fat. The kurtosis

and skew of the histogram for the pathological breast are markedly dissimilar to the normal one.

replacement by fat (low CTU) in the post-menopausal breast. Although not enough data is available from this study, undoubtedly the peak position is a decreasing function of age [7]. The histogram for the pathological breast has markedly dissimilar shape (skew and kurtosis) and extends to higher CTU values. The carcinoma is contained in the high valued region. (The peak

near zero probably represents some water being in- cluded in the histogram by the algorithm.) Figure

8 shows examples of cumulative distribution plots

-80 -60 -40 -20 0 20 40 60 CTU VALUES

Fig. 8. Inverse cumulation probability function

for a representative sampling of the older patients. The zero asymptotic values can

be roughly correlated with tissue type.

- - - = normal, = fibroceptic/

adenoma, = carcinoma.

for older normal breasts, and breasts containing

fibrotic and carcinoma tissue. In general, figures

6 and 8 tend to reflect the results of all the scans summarized in table 1.

4. Discussion

Human female breasts are constituted of time varying fractions of various components. It ap- pears plausible that each of these components

(parenchyma, glands, fat, etc . ) have ultrasonic

properties which are relatively similar between different subjects. Indeed, the wide variation in average and peak CTU numbers observed for young

dense breasts probably represents an incomplete

analysis of the volumetric fractions of glandular

tissue, fat, and ducts present in any given subject. In any case, a single number representing

velocity values averaged over the volume of a breast [7] is probably too simplistic to be rep- resentative of the breast.

The symptomatic subjects examined in this study were chosen to have large, unambiguous lesions in order to acquire data on the various tissue com- ponents. These data, however, represent a statistically insignificant number of cases on which to

224
base any absolute conclusions. In fact, a larger

data base will probably show wider variation in values than was found in this study. Nevertheless,

the present results suggest a distinction between

normal and neoplastic tissue which is encouraging

for mammographic application.

There are potentially several methods of utilizing the TOF data in cancer detection suggested by the histograms. When available, histograms of the contralateral breast provide a reference which

could form part of a comparative basis. Alternatively or additionally, a reference base which de- pends on age and other variables can be accumulated.

Besides the histograms, which present a volumetric

picture of the constitutive elements, the individual pixel values, rates of change, and geometry can

be searched for characteristic patterns. Application of such speculation, however, must await the acquisition of more massive amounts of data.

Acknowledgments

The clinical data was acquired with the help of

R. W. Sponzo, M.D., his staff and colleagues at the Albany Medical College.

References

[1] Greenleaf, J. F. et al . , Algebraic Reconstruction of Spatial Distributions of Acoustic

Velocities in Tissue from their Time of Flight

Profiles, in Acoustic Holography , W. Booth,

ed.. Vol. VI, pp. 71-89 (Pergamon Press, New

York, 1975).

[2] Carson, P. L., Oughton, T. V., and Hendee,

W. R., Ultrasonic Transaxial Tomography by

Reconstruction, in Ultrasound in Medicine , D. White and R. Barns, eds.. Vol. II, pp. 341-350 (Plenum Press, New York, 1976).

[3] Glover, G. H. and Sharp, J. C, Reconstruction of Ultrasound Propagation Speed Distributions in Soft Tissue: Time-Of-Fl ight Tomo- graphy, IEEE Trans. Sonics and Ultrasonics

SU-24 , 229-234 (1977).

[4] Gordon, R. and Herman, G. T., Three dimensional reconstruction from projections: a review of algorithms, Internat. Rev . Cytology

38, 111-151 (1974).

[5] See, e^. , Wells, P. N. T. , Review: absorption and dispersion of ultrasound in biological tissue. Ultrasound in Med , and Biol. 1, 369-376 (1975T: ~

[6] Glover, G. H., Computerized time-of-fl ight

ultrasonic tomography for breast examination.

Ultrasound in Med, and Biol , (in press).

[7] Kossoff, G., Fry, E. K., and Jellins, J., Average velocity of ultrasound in the human female breast, J. Acoust. Soc. Am. 53, 1730-

1736 (1973). ~

225
I 11 I
Reprinted from Ultrasonic Tissue Characterization II, M. Linzer, ed. , National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C., 1979).

VARIATION OF ACOUSTIC SPEED WITH TEMPERATURE IN VARIOUS EXCISED

HUMAN TISSUES STUDIED BY ULTRASOUND COMPUTERIZED TOMOGRAPHY

B. Rajagopalan, J. F. Greenleaf, P. J. Thomas,

S. A. Johnson, and R. C. Bahn

Biodynamics Research Unit

Departments of Physiology and Biophysics, and Department of Pathology and Anatomy

Mayo Clinic and Mayo Foundation

Rochester, Minnesota 55901, U.S.A.

Variation of acoustic speed as a function of temperature was measured in fresh ex- cised human liver, psoas muscle, spleen, spinal cord, kidney and fat, parenchyma and muscles associated with female breasts. Tissues were encased in rubber finger cots

and suspended in a temperature controlled water bath. A prototype clinical ultrasound

breast scanner was used to obtain data required to reconstruct distributions of acoustic speed within two-dimensional planes through the tissue specimens over a temperature range of 20 to 40 °C. Quantitative images (printer listings of acoustic speed)

of 64 X 64 pixels were used to obtain averages of up to 16 speed measurements within

the image of each tissue. The acoustic speed in most tissues increased monotonical ly

with temperature following the behavior of water. Acoustic speed of fat showed an anomalous decrease in acoustic speed around 34 °C suggesting possible phase transition.

Key words: Aperture synthesis; computed tomography; Doppler; fluid flow; high

resolution; reconstruction; temperature reconstruction; ultrasound.

1. Introduction

Historically, production of images by ultrasound scanning has been done by displaying either

the pulse echo reflected from an object (B-scan)

or by displaying the attenuated signal (C-scans)

transmitted by an object [l]i. These modalities,

although useful, give only a qualitative mapping

of tissue interfaces and geometries. Images

representing quantitative distributions of basic

mechanical tissue properties as characterized by

ultrasound scattering cross section, impedance

[2,3] and acoustic speed [4] may be intrinsically

more valuable than the qualitative images rep- resenting tissue borders and geometries. A quantitative imaging modality would eliminate

operator-dependent variations one often finds in the qualitative imaging modalities. Ultrasound

computerized tomography [4] is one such imaging

modality by which the distribution of one fundamental mechanical parameter, i.e ., acoustic

speed, in a tissue can be studied.

The purpose of this report is to describe

methods and initial results of applying computerized tomography to the problem of obtaining

quantitative images representing the distribution

of acoustic speed and the effect of temperature

on these values for tissues from various parts of

^Figures in brackets indicate literature

references at the end of this paper.

the body, especially the human breast. The knowledge of temperature coefficients of acoustic

speed in tissues may be useful in estimating the temperature change in a region of tissue occurring due to external causes such as ultrasonic

heating or drugs. Since various disease processes alter tissue temperature, the temperature co- efficients may also be helpful in the interpretation of computerized tomography images of live tissues. The reconstruction problem in ultrasound com- puterized tomography has been described else- where [4] and will not be described in detail

here. A good introduction to the basic mathematics of computerized tomography and a general

overview of the analytical and iterative algorithms can be found in the review articles by

Gordon and Herman [5] and Brooks and Dichiro [6]. The convolution reconstruction algorithm for the divergent beam geometry was first derived by

Lakshminarayanan [7] and later a mathematically

rigorous treatment of the same problem leading to identical results was given by Herman and his co- workers [8]. This divergent beam convolution re- construction algorithm is used exclusively for

all the reconstruction images in this paper.

2. Experimental Arrangement

In ultrasound computerized tomography the profile data consist of measurements of time-of227
flight of an acoustic pulse through the sample

along different rays or directions. The data

are obtained by divergent beam scanning with a single pair of transducers one on each side of

the region of interest. The schematic of the data collection geometry is shown in figure 1. The scan angle is a and is incremented at 0.15°

intervals using a stepping motor. After the scan

the ultrasound transmitter-receiver arm is rotated to a new e position and another scan is ini- tiated. Thus, for each e position there is one profile of time-of-f1

i ght data. One hundred

twenty profiles separated in view by 3° increments

are gathered over the 360° range. —transmitter locus

profile data V P(a,e2)

Jy\\/

tissue] / /

profile data P(a,ei) receiver loci

Fig. 1. Data collection geometry for ultrasound

tomography, ej and 63 are the angles

made by the central ray in the scan with

X-axis for two different scans. Profile

data P(a,ei) is gathered by rotating the receiver-transmitter arm about an axis

passing through the apex of the sector and perpendicular to the plane of the figure.

Thus, the receiver loci are arcs. The transmitter mounted at the axis of the scan describes a circle as profile data from different views (e) are gathered.

The schematic of the experimental arrangement

for collecting computerized tomography data is shown in figure 2. The system is driven by an Interdata 7/32 minicomputer which controls the height and rotation angle (e) of the scanner arm

and collects the time-of-f 1 ight data from the digital output of the time-of-f1 ight (TOF) clock

and control box. This TOF clock and control box

is interfaced to the digital I-O of the minicomputer and upon a command from the computer

collects time-of-fl ight data, outputs the data,

steps the scanner arm to the next orientation in the scan and repeats this process until one profile

of data are collected. At the end of the scan the scanner arm is rotated to the new 6 position by a command from the minicomputer and the process of collecting profile data resumed by a trigger to the TOF clock and control box. These time-offl ight profiles representing propagation delay of acoustic pulses along many rays through the tissue under examination are input to the reconstruction

programs to obtain quantitative distributions of

keyboard

height

control rotate

interdata

7/32

O

CRT camera

^

strobe

16

TOF

signal Time-of-Fl ight

clock & control

receive (((V^((

^rotatef

|hei ght|

trigger| transmitf*—

^

scanh

Fig. 2. Ultrasound computed tomography system:

Data collection and control. Computer

controls transmi t-del ay-and position.

Time-of-f 1 ight of signal is measured with

a 16-bit 100 MHz clock and counter which

is read by the computer at up to 400 points

along a scan profile, each point separated

by 0.15°. One hundred views each containing 400 samples and each sample containing

eight channels of 16-bit time-of-f1 ight data can be obtained in a period of 2.5 'minutes.

acoustic speed in the transverse plane through

the tissue.

3. Reconstruction Algorithm

The mathematical steps to arrive at the recon- struction picture from the set of profile data

are given in this section without attempting to derive any of them. These steps known as the re- construction algorithm are treated extensively in the literature and the derivation for divergent

beam geometry starting from Radon transform [9] can be found in the reference mentioned earlier

[8].The raw data of each profile consist of time measurements (in seconds x 10"^) at each incre- ment along the arc of the scan. The data for the 20 or more points closest to each end of the pro- file are the time- of-fl ight for sound through

water, and never vary by more than one unit

(10"^ s) from the lowest to the highest. The average of the first few points is subtracted from

each point of the profile and the differences

P(j,e) represent the profile data for reconstruction. Here 6 is the angle made by the central ray of the scan with x-axis (arbitrarily chosen) and

j = -n . . . -1 , 0, 1 , . . . +n indexes the angles of

the 2n+l individual rays of the scan with j = 0 at the center of the scan. For each rotation

angle e the profile data are reduced by the cosines of the angles of the individual rays from

the center line.

P(j,e) modified = P*(j,e) = P(j,e) cos(j£) (i)

where e is the constant angular increment in the scanning motion (0.15°). The modified profile

228
P* (j>9) is convolved with a kernel to give the convolved modified profile C(k,e), i .e .

,

kmax C(k,6) = Z P (2)

''"'^min

The kernel is given by

Ao = (3)

A-j = 0 for even i and i = 0

where D is the distance from the axis of rotation

for the scanning motion to the axis of rotation

for rotate motion and kmin and kpiax indicate the lower and upper limits of the scan. Finally,

the back-projection is formed, along the lines

of the acoustic rays, converging at the axis of

scan motion, with the back-projected C(k,e)

weighted with inverse square of the relative

distance of the point from the axis of the scan

to distance D. Thus, for each time-of-f1 ight

profile at an angle e the matrix f(x,y) forming

the reconstructed picture is incremented by

Af(x,y)e = I

C(k,e) ^ (4)

where r = distance of the point (x,y) from the

axis of the scan. C(k,e) is interpolated if no

ray goes through the point (x,y). The sum of all the back-projected Af(x,y)Q for all e values yields the reconstructed image at (x,y).

f(x,y)= Z fC(k,e)Di (5) sum over Q

When the back-projection is finished, the value

for each pixel will be the increase or decrease

in time per centimeter at that point, compared

with water. The time-of-f1 ight for water (in the

same units, calculated from the measured time and known distance, and verified by the known velocity of sound in water for the particular temperature) is then added to the value of each pixel,

and the reciprocal of the sum is scaled to give

the final result in meters per second. The re- constructed digital images represented by a matrix

of 64 X 64 pixels can be displayed in gray scale

in a Ramtek display system.

4. Experimental Results and Discussion

The accuracy with which the acoustic speed can

be determined using ultrasound computerized tomography is demonstrated in figure 3 in the high

correlation of our data with the literature value

'(10) for 2.5 percent salt solution. Thin rubber

finger cots filled with saline served as the test

object. The agreement of the literature values

with the experimental results over the entire

temperature range is within ± 0.3 percent. Since

the reconstructed image is a matrix giving the acoustic speed in each pixel (pixel size ^ 1.5

mm^) mean and root mean square deviation of the

Fig. 3. Comparison of acoustic speed in 2.5 per- cent salt solution (2.5 g salt in 100 cm^

of water), as determined by ultrasound

computerized tomography, with the literature values. The literature values have

an accuracy of ± 4 cm/s. Acoustic speed values were taken as the average of 20 samples in the reconstructed image.

oUltrasound computerized tomograph data •Millero, F. J. and Kubinski, T.,

J_. Acoust . Soc . Am. 57^, 312 (1975).

acoustic speed are easily determined by analyzing

the quantitative distribution of acoustic speed

in the image. Similar statistical analysis was done on the reconstruction images of all the tissues that were studied and reported in this paper. Tissues were obtained and selected by a pathologist as being representative of selected tissue

types. Samples of tissue acquired were about 2 to 3 centimeter square and 5 centimeter long and were suspended in a bath of normal saline. Ref- erence objects such as finger cots filled with

saline of known concentrations were also suspended with the tissues. Later in the study the tissues were packed into finger cots under normal saline and suspended in the water bath. This

procedure simplified the tissue handling con- siderably and the effect of finger cots on the quantitative results was found to be negligible.

The temperature of the water bath was in- creased in increments of about 2 °C and the tissues were allowed to equilibrate with the bath water prior to each new scan. The temperature

of the bath was controlled ±0.1 °C and experiments were done over a range of approximately

22 to 42 °C. The ultrasound computerized tomography images for the acoustic speeds in spleen, kidney, liver,

spinal cord and psoas muscle at two different

temperatures are displayed in figure 4. Since

the two pictures are displayed in the same gray

scale any increase in the acoustic speed with

temperature is seen as an increase in the brightness of the corresponding regions of the image.

The water background is brighter in the image for

33.2 °C for the same reason. Figure 5 gives a similar picture for breast tissues at temperatures 14 °C and 41 °C. Because of the very large

temperature change, the corresponding changes in the acoustic speeds are seen strikingly in this picture. The water background goes from dark to bright and the image of salt solution gets brighter at the higher temperature. Images of the breast fat which were brighter than the water

229
®0

1 = spleen

2 = kidney

3 = 1 i ver

4 = spinal cord

5 = psoas muscle

Fig. 4. Ultrasound computerized tomography images

of acoustic speed distribution in various

tissues, in vitro , at two different different temperatures. Same gray scale used

for both the pictures. Higher acoustic

speed is displayed brighter. Reconstruction size is 15 cm square. Tissues were

encased in rubber finger cots to prevent

solutes from diffusing into or out of the tissues. Tissues were unfixed and maintained at 10 to 14 °C until used some 12 to 24 hours after autopsy. (Reproduced

with permission from Greenleaf, et al .

,

Proceedings of the Vth International

Conference on Information Processing in Medical Imaging (in press).)

background at the lower temperature become darker

at the higher temperature since the acoustic speed

in the breast fat has decreased with increasing

temperature. The dark streak from fat to fat in the picture for 41 °C is an artifact caused by

the lens effect of the cyl indrically shaped tissue. The increase in the acoustic speed in

1 = 2.5 g/100 ml salt

sol ution

2 = breast fat with

parenchyma

3 = breast fat

Fig. 5. Ultrasound computerized tomography

pictures of acoustic speed distributions

in breast tissues, in vitro , at two different temperatures. Reconstruction size

is 15 cm square. Fat exhibits acoustic

speed higher than water at 14 °C and lower than water at 41 °C.

parenchyma with temperature is also seen from

this picture. Results of the statistical analysis of the re- construction images giving the mean and standard

deviation of the acoustic speeds at various tem- peratures in all the tissues studied are given in tables 1 and 2. These data are graphically il- lustrated in figures 6, 7, and 8. From figure 6 it is clear that the tissues liver, psoas muscle,

spleen, spinal cord and kidney have higher acoustic speeds than water and their temperature variations are similar to that of water. The breast muscle and parenchymal tissue are about 3 per- cent higher in acoustic speed than normal saline.

Their temperature behavior is also very similar

Table 1. Temperature variation of acoustic speed in excised human breast tissues.

Temperature

Tissue 22.5 °C 25.8 °C 27.8 °C 30.2 °C 32.2 °C 35.1 °C 38.0 °C 40.1 °C 42.5 °C

Salt finger

{2.5%) 1516.73

(2.1)b

1523.2

(2.1) 1529(2.6) 1533.6(2.1) 1538.4

(2.8) 1544.8(3.1) 1549.6

(3) 1552.8

(4.2) 1556.5(3.8)

Fat breast 1480.7

(2.5) 1466.9

(9.9) 1472.1

(9.8) 1477.4(9.9) 1478.1(11.4) 1436.3(15.6) 1435.6(18.4) 1438.7(18.1) 1441.8

(17.5)

Fat with parenchyma

1494.7

(4.1) 1487.5

(5.5) 1491.5(5.5) 1497.8(5.7) 1500.9

(6.2) 1471.3(9.7) 1471.3(13.1) 1474.2(13.4) 1475.9(12.8)

Parenchyma 1539.4

(4.5) 1545.7(4.0) 1551 (4.6) 1558.1

(3.9) 1562.1(4.1) 1564.5(7.6) 1564.3(6.4) 1569.6(6.3) 1571.9

(6.4)

Muscle 1543.

1

(5.2) 1551.4(6.2) 1554.2(6.5) 1562.4(7.1) 1565.5

(6.4) 1566.9(4.5) 1570.7

(6.9) 1574.6(6.7) 1579.5(5.4)

Background

(normal saline) 1504.0

(3.2) 1512.5

(3.6) 1519.2(2.8) 1523.7(2.5) 1528.4(2.4) 1535.4(4.0) 1539.1(2.9) 15^1.9(3.0) 1546.4

(2.8)

fvelocity, m/s. Standard deviation.

230
Table 2. Temperature variation of acoustic speed in selected excised human tissues.

Temperature

Tissue 17.0 °C 22.0 °C 23.5 °C 26.2 °C 30.2 °C 33.2 °C 35.2 °C 37.2 °C 39.0 °C 40.8 °

Liver 1547.0^

(2.5)b 1555.5

(1.8) 1563.1(3.0) 1564.6(2.8) 1571.1

(2.5) 1573.5(1.8) 1575.3

(2.5) 1578.1(2.9) 1580.0

(2.2) 1581.7(1.5)

Kidney 1508.5

(4.3) 1523.8(4.6) 1536.1

(2.1) 1536.3(5.2) 1545.2(2.7) 1551.4(1.4) 1555.8(1.8) 1560.2(1.8) 1562.6(1.2) 1564.3

(0.9)

Spleen 1528.0

(1.8) 1538.8(1.8) 1544.3

(1.8) 1549.1(1.6) 1556.4(2.0) 1561.9(1.7) 1546.0(2.1) 1567.1(2.3) 1569.3

(2.6) 1573.0(2.1)

Psoas muscle

1542.5

(3.0) 1459.5(3.0) 1554.8

(1.1) 1560.2(1.7) 1566.4(2.2) 1571.6(1.8) 1573.5(1.8) 1575.6(1.1) 1577.6

(2.1) 1580.3(1.8)

Spinal cord 1509.0

(4.5) 1523.0

(4.6) 1523.0(5.3) 1526.0(3.0) 1532.6(3.2) 1538.0(2.6) 1538.0(3.5) 1542.4(3.3) 1543.8

(3.0)

1-156.5 (2.0)

^Velocity, m/s. Standard deviation.

Temperature, °C

Fig. 6. Variation of velocity of sound with temper- ature in various tissues. Ultrasound com- puterized tomography data. Values are averages of about 15 values taken in the visually defined center of respective tis- sue samples within the image. Bars are

± RMSD.

to that of saline or water as seen in figure 7. However, breast fat and parenchymatous fat have acoustic speeds below that of normal saline and show a complex behavior with temperature as il- lustrated in figure 8. Initially the acoustic

speed increases slowly with temperature and around

^35 °C decreases markedly and then increases with a 'small slope of about 1 meter per second per °C. Similar decrease but much less pronounced is seen around 27 °C also. A plot of the variation of the temperature coefficient versus temperature for

fat and muscle shown in figure 9 illustrates the strikingly different temperature behavior of fat. This complex behavior is suggestive of possible

•muscle

parenchyma

isalt solution, 2.5 g/100 ml salt solution

Temperature, °C

Fig. 7. Variation of acoustic speed within pectoral is muscle and normal parenchyma of breast. Values obtained in the manner

described in figure 6.

phase transitions just below the body temperature (37 °C). Hoyer and Nolle [11] studied the behavior of nematic and cholesteric liquid crystals near the isotropic to liquid crystal transition by measuring the propagation constants of ultrasonic waves. Their study indicates that the acoustic speed goes through a minimum at the temperature of the phase transition. Dyro and Edmonds [12] investigated ultrasonic dispersion

in cholesteryl esters and their results show that

the acoustic speed exhibits markedly different

behavior around the phase transition. Though the fat sample in the present study is not a homo- geneous, "clean", one-component system, the pos- sibility of a phase transition of some kind cannot be excluded. More detailed studies using

different physical chemistry techniques such as differential scanning calorimetry may shed some light into the anomalous temperature behavior of

the breast fat.

231
Temperature, °C

Fig. 8. Variation of acoustic speed in normal breast fat. Slope of alteration in acoustic speed with temperature is negative for

fat in certain regions of temperature.

Vertical shift in curves is apparently due

to presence of parenchyma which has tem- perature dependence much like water (see

fig. 7).

Alterations of temperature within various

tissues can be expected under various inflammatory

processes such as infections. It is also well

_

known that certain carcinomas are associated with

a high temperature due to their increased metabolism. Knowledge about the temperature variations

of acoustic speed in diseased tissues and in normal tissues should be valuable in future studies of acoustic speed distributions within

patients whose tissues are undergoing various

disease processes. Computerized ultrasound tomo- graphy may provide the possibility of quantitatively measuring acoustic speed in breast tissues

in vivo.

Acknowledgments

The support from Dr. Earl H. Wood, Dr. Erik L. Ritman, and the staff of the Biodynamics Research

Unit, Mayo Clinic, is appreciated. This research

was supported by Grants HL-07111, HL-00170, HL- 00060, RR-00007, HL-04664, NIH-HT-4-2904 from the National Institutes of Health, United States Public Health Service, and NCI-CB-64041 from the National Cancer Institute.

References

[l] Green, P. S., Schaefer, L. F., Jones, E. D. , and Suarez, J. R., A New Hi gh-Performance

Ultrasonic Camera, in Acoustical Holography , Vol. 5, pp. 493-503 (Plenum Press, New York,

1973).

[2] Jones, J. P., Impedi ography : A New Ultrasonic Technique for Non-Destructive Testing

and Medical Diagnosis, in Ultrasonics Inter- national (1973), Conference Proceedings , p. 214 (PIC Science and Technology Press

,

U.K., 1974).

[3] Kak, A. C. and Frye, F. J., Acoustic Im- pedance Profiling: An Analytical and Physical Model Study, in Ultrasound Tissue

-16l 1 I I I I I I I I L_ 20 24 28 32 36 40 Temperature, °C

Fig. 9. Variation of temperature coefficient of acoustic speed with temperature in pectoral is muscle and in fat from breast. Negative temperature dependence of fat

in certain regions of water is visualized

by plotting slope of figure 8.

Characterization , M. Linzer, ed. , National Bureau of Standards Spec. Pub. 453, p. 231

(U.S. Government Printing Office, Washington, D.C., 1976).

[4] Greenleaf, J. F. and Johnson, S. A., Algebraic Reconstruction of Spatial Distributions

of Refractive Index and Attenuation in Tissues from Time-Of-Fl ight and Amplitude

Profiles, in Ultrasonic Tissue Characteriza - tions , M. Linzer, ed. , National Bureau of Standards Spec. Pub. 453, pp. 109-119 (U.S. Government Printing Office, Washington,

D.C., 1976). j

[5] Gordon, R. and Herman, G. T. , Three- dimensional reconstruction from projections:

A review of algorithms. International Re- j view of Cytology 38, 111-151 (1974).

'

I [6] Brooks, R. A. and Di Chiro, G., Principles ! of computer assisted tomography (CAT) in radiographic and radioisotopic imaging,

Phys. Med. Biol , n, 689-732 (1976).

[7] Lakshminarayanan, A. V., Reconstruction

from Divergent Ray Data. Department of Computer Science, State University of New

York at Buffalo, Technical Report 92 (1975).

[8] Herman, G. T., Lakshminarayanan, A. V., and Naparstek, A., Convolution reconstruction

techniques for divergent beams, Comput . Biol. Med . 6, 259-271 (1976).

[9] Radon, J., Ueber die Bestimmung von Funktion 'j durch ihre Integralwerte Langs gewisser

Mannigfaltigkeiten, Berichte Saechsische

Akademie der Wi ssenschaf ten 69, 262 (1917).

232
[10] Millero, F. J. and Kubinski, T., Speed of

sound in seawater as a function of temperature and salinity at 1 atmosphere, J. Acoust . Soc. Am . 57, 312-319 (1975).

[11] Hoyer, W. A. and Nolle, A. W. , Behavior of liquid crystal compounds near the isotropicanisotropic transition, J. Chem. Phys. 2A^, 803-811 (1956).

[12] Dyro, J. F. and Edmonds, P. D. , Ultrasonic

absorption and dispersion in cholesteryl

esters, MoT. Cryst. Liq. Cryst . 25 , 175- 193 (1974T:

233

Reprinted from Ultrasonic Tissue Characterization II, M. Linzer, ed. , National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C., 1979).

HIGH SPATIAL RESOLUTION ULTRASONIC MEASUREMENT TECHNIQUES

FOR CHARACTERIZATION OF STATIC AND MOVING TISSUES

Steven A. Johnson, James F. Greenleaf, and B. Rajagopalan

Biodynamics Research Unit

Department of Physiology and Biophysics

Mayo Foundation

Rochester, Minnesota 55901, U.S.A.

Robert C. Bahn

Department of Pathology

Mayo Clinic and Mayo Foundation

Rochester, Minnesota 55901, U.S.A.

Brent Baxter

Department of Computer Science

University of Utah

Salt Lake City, Utah 84112, U.S.A.

Douglas Christensen

Departments of Bioengineering and Electrical Engineering

University of Utah

Salt Lake City, Utah 84112, U.S.A.

Clinical and pathology-based arguments are presented for the need for higher resolution ultrasound images. The theoretical foundation and experimental characteristics

of a high resolution, sampled aperture, reflection technique termed "synthetic focus" imaging are given. It is shown by theory and simulation that such synthetic focus

images may be corrected for attenuation and refraction effects and thereby approach

one-half wavelength resolution. The similarity between synthetic focus and seismic

migration techniques is discussed. An example of a high resolution, seismic processed ( i.e ., migrated) image obtained from real data at medical ultrasound frequencies

is shown. Synthetic focus imaging theory is extended to moving coordinate systems

and the effect of Doppler shift effects on echo pulse shape is discussed. A generalized wide aperture Doppler imaging theory is presented which suggests further improve- ments in signal-to-noise ratio, spatial resolution and flow velocity over narrow aperture systems is possible. A new computed tomographic flow measurement and recon- struction technique based on transmission measurements is presented. This technique

permits imaging the three flow velocity components and temperature of homogeneous

fluids in a three-dimensional domain.

Key words: Aperture synthesis; computed tomography; Doppler; fluid flow; high

resolution; reconstruction; temperature reconstruction; ultrasound.

1. Introduction

This paper presents theoretical and experimental evidence that useful measurements of tissue characteristics with limiting spatial re- solutions of about one-half wavelength are pos- sible in static and moving media ( e.g. , tissues).

This paper has three objectives: First, to present the case for striving for higher re- solution images of tissue parameters, second,

to describe the theoretical and experimental

techniques whereby such high resolution images may be obtained and, third, to report progress

toward obtaining such high resolution images.

235
2. The Case for Seeking Higher

Resolution Images

A. Higher Resolution Images of Static Tissues

The first goal or purpose of this paper is in part philosophical, yet is demonstrable, and calls attention to an important area of investigation

(improved resolution) where future research progress can be made. It can be argued that reliable

tissue characterization requires attention to at least three independent requirements: First,

choosing an adequate set of tissue dependent acoustic parameters to be measured; second, measuring

the parameters with accuracy and precision in some

set of regions in the tissue; and third, making

this measurement region as small as possible and

as densely arranged or packed as possible (i.e.,

forming an image). The third requirement is not always necessary

to gain some information on tissue type but its inclusion improves the certainty of characterization. Certainly, it is clear that an early diagnosis of a disease state (such as cancer) is en- hanced by detection of smaller masses made pos- sible by higher resolution and better tissue

identification. In some cases the tissue type may

well be primarily determined by the morphology and pattern of its structure and the change in pattern

of the surrounding tissue [l,2]i. This has its analog in microscopic pathologic techniques where

both stain (acoustic tissue characterization

parameter is its analog) and pattern are important

in tissue typing or characterization.

In the long range, the improvement of resolution may be the most important objective for future research progress. At present, the pri- mary attempt to detect small focal processes such

as cancers, abscesses, infarcts of less than 0.5

to 1 cm in diameter is difficult and may not be justified economically. However, often more fundamental than the focal lesion itself, regardless of its size, is the state of the tissue sur- rounding circumscribed lesions. The pattern of

the adjacent tissue plays a crucial role in the identification of specific diseases by supplying

the physician with information concerning the

local context of the process under consideration.

Compared to tumor nodules, the structures of

the surrounding "normal" tissues are relatively

delicate. Their patterns are essentially deter- mined by the dimensions of the fibrous and vascular framework of an organ. It would be desirable

to image such delicate patterns associated with

the tertiary branching of major arteries of the heart, brain, kidneys, and lungs, the bronchial

tree, the biliary ducts of the liver and the ductular system of the breast. Since vascular

or ductal systems at the level of tertiary branching involve tubular structures approximately 0.5

to 1.0 mm in diameter, this objective fixes the upper limit of useful picture element size at about 0.25 to 0.5 mm. From a practical point of view, this level of resolution would provide at least 20 resolutable picture elements (pixels) over an area 2.5 millimeters in diameter. Such

an area would correspond roughly to the crosssectional area of the lumen and portions of the wall of a coronary artery.

^Figures in brackets indicate literature

references at the end of this paper.

In this manner, imaging studies can eventually

become focused upon pathogenesis, prevention, and early detection of disease rather than upon the diagnosis of gross advanced lesions.

B. The Case for Seeking High Resolution

Images of Moving Tissues

The velocity of moving tissue may be obtained

by two general methods. First, by a differential

method in which velocity is computed from images

of the location of the tissue at two separate

times separated by a short time interval (this could be done by comparing two separate real-time

B-scans of the heart, for example), and second,

by direct methods which make use of alterations

in frequency or phase in the received ultrasound

signals. Examples of images produced by this latter method are the familiar pulsed Doppler B- scan technique [3] and the new fluid velocity vector reconstruction technique developed by

Johnson et a1 . [4]. Images produced by the first or differential

method have application in understanding moving

solid tissues such as the heart and circulatory

system and their components ( e.g . , valves, vessel walls, etc . ) . Any improvement in the spatial

and temporal resolution of methods for imaging these moving structures would produce a corre- sponding improvement in imaging the velocity of these structures at high spatial resolution. The effort which has been and now is being made in the field of x-ray angiography [5] is an indication of the potential contribution which such high spatial and temporal ultrasound imaging

methods could make to health care. Images produced by the direct velocity imaging

techniques (based on frequency or phase shift

techniques) have application in measuring the velocity of fluid produced or modified by tissues

( e.g . , air in the respiratory system, urine, etc.

)

or the velocity of fluid tissues ( e.g . , the blood). The well-known Doppler technique (a reflection

method) measures the velocity of scattering centers ( e.g . , the red and white cells) in the blood. The new velocity vector reconstruction method (a transmission method) measures the velocity of the carrier ( i.e ., the plasma) of the scattering centers or a combination of the velocity of the two constitutive components. Thus, the two methods

are complementary. The ability to obtain images

at high spatial and temporal resolution of blood

flows promises to be of great value for several reasons. First, it may be argued that since the x-ray angiographic method is of proven worth,

then any competitive ultrasound techniques would

also be valuable. Second, the new pulsed Doppler

systems now in development or use, although of limited to moderate imaging capability, are proving to be of great value [6]. For example, the SRI-built carotid scanner, now undergoing clinical

trials at Mayo, is proving the value of its Doppler

flow measuring features (the scanner has real- time B-scan capability also) [7]. Third, ultrasound procedures are noninvasive and have no demonstrable cumulative toxic effect when power

and energy levels are controlled. Fourth, ultrasound procedures are painless and usually can be completed quickly.

236
3. Imaging Methods for Static Media

A new high resolution reflection imaging mode

has been developed in the Mayo laboratory to image or characterize tissue structures in the body where a full 360 degree data collection

geometry is precluded by the ribs, the spine, and other body structures [7,8]. This new mode is termed synthetic focus imaging [7]. The mathematics for synthetic aperture imaging

may be derived by reference to figure 1. Let define a measure of the probability for acoustic

amplitude scattering or reflection toward the de- tector aperture from picture element k when il- lumination from each transmitter element in the

water tank Gmk 9jk

\ n

:\

1

\f k

1 — —

Tik

11

(M,M)

(M,0)

transducer array

Vijm 12 3 i(j,k,m)-l

d

=

i (j,k,m) + l

Fig. 1. Geometry for derivated of equations for ultrasonic imaging by generalized

synthetic aperture methods. A transducer

array with N elements is in acoustic con- tact with a water tank. Positions in the tank are described by coordinate system

XY. A typical ray path is shown for energy transmitted by the mth transducer

and scattered by picture element k into

the jth transducer. Here rji^ and r^k are the distances from j to k and from

m to k, respectively. Angle 6j|< is measured from rj|<; to the Y axis counterclockwise. V-jjni is the voltage sample

from the jth transducer at time after transmission of the signal by the mth transducer. Here s and d are start and end times of a time interval 2w which

contains the echo from k at its midpoint.

Time L is greater than the maximum time

associated with all paths defined by j, m, and k. (Reproduced with permission

from [7].)

array aperture, measured at picture element k, is normalized. The probability for energy scat- tering is the square of P^. For the case of a very narrow pulse of ultrasonic energy, P|^ is given by

NE

m=l

N

j = l

t+w E

i=t-v\

^i,j,mRj,kTk,mKt-l (D

where Vi,j^ni is the ith voltage sample from the

j'^n array element when the mtn array element was used as the transmitter. Rj^|< is the receiverrange azimuth illumination normalization factor

between the k^n picture element and the jth array

element. Thus, Rj^|^ is independent of time, but

is an approximate function of some power of the magnitude of rj^|< (where rj^^ is the vector from

array element j to picture e'l_ement k) and of the cosine of the angle between fj ^ and n-; (the unit vector normal to array element'j). Thus, R,- i, may be written '

exp (/a(s)ds)

- j

" q /ds n. • S, .

'-k

-1

(2)

where a is the attenuation coefficient along the ray path connecting k and j, q is a rational number from 0.5 for cylindral waves to 1.0 for

spherical waves, and is the unit tanget vec- tor at j of the ray which passes from k to j.

T)^

u, is the corresponding transmitter function

belween the k^h pixel and mth array (transmitter)

element. Thus, |^ and T|^^rn affect the energy normalizations referred to in the definition of

P|<. N is the number of array elements. The factor K^_-j is a kernel function for performing con- volution or cross correlation operations on the

raw data V| h If V-j is of the appropriate

pre-transmi{ted form or 'post-received processed

form, then K^.-j may be of the form of a delta function 6q = 6t,i. The limits t ± w are related to {he transmitter pulsewidth t^ which is less than some arbitrary bracketing interval tB which contains the transmitted pulse of width t^. Then,

/ k j ds At

tw/2At

(3)

(4)

where At is the sampling interval time between

successive samples in the digitized signal, and u is the effective velocity of sound in the insonified medium. The two line integrals are taken along the rays connecting transmitter m to k and

k to receiver j respectively.

An important modification to the synthetic

focus equations above would change the sum over i to allow for refraction or bending of acoustic

rays. The effect of this bending is manifest in shifts in the values of s and d compared to that obtained by computing the round trip pulse time in

a homogeneous medium. This effect is illustrated

in figure 2. The value of t would be replaced by the correct round trip time computed using curved

rays obtained from ray tracing techniques [9,10]. The coordinate system set up by the intersection

of rays and wavefronts and the corresponsi ng slight shift in round trip (a few percent) will allow a low spatial resolution perturbation cor- rection to be made to the basic homogeneous media

round trip time equations.

Another useful modification to the basic

synthetic-focusing scheme presented above would

237
Fig. 2. Orthogonal coordinate systems for describing ray paths from transducer elements in constant (left) and variable (right) re- fractive index media. On the left the ray paths between each transducer element and receiver element are segments of straight

lines. The lines of equal time of propa- gation are circles. On the right the ray path and equal time lines are from trans- mitter element m to scattering site k and

the time tj|^ from k to receiver element j is shown as a heavy line. (Reproduced

with permission from [9]).

be to replace ^\,j,m with the output of a hard- ware or software correlator, allowing transmission

not only of pulses of energy, but arbitrary waveforms as well. This may be a faster method for obtaining the optimum resolution waveforms than

performing the inner products in software using

the kernel Kt-i as indicated by equation (1). Figure 3 shows the similarities between the x- ray computer assisted tomography and synthetic

focus ultrasound algorithms. It is seen that back projection in both instances can be thought of as

a line integral in data space:

1) In the x-ray case the reconstructed value

at each pixel in the tomogram is obtained by in- tegration along a unique path in the convolved

data space. The convolved data space is composed

of the collected projection profiles convolved

with a kernel function. The curved path associated with each pixel is a sine wave modified in phase and amplitude for the special case of parallel ray projections, hence, the name "sinogram" space for this representation of the data.

2) In the ultrasound synthetic focus method,

the image value at each pixel in the tomogram is obtained by integration along a unique path, also

in a convolved data space. The values in the con- volved data space can be obtained by either trans- mitting the required waveform or by digital proc- essing or equalization of the received data. In the case of a homogeneous material in the object

space, e.g . , water, the set of echoes from each receiver element for a fixed transmitter position

falls on a hyperbolic curve in data space . The synthetic focus algorithm reconstructs the scat- tering amplitude at each pixel by integration

along the hyperbolic curve which is unique to that

pixel

.

Back projection, as just described, may be termed "pixel driven" because the value at each

pixel is computed to completion before a value is

0 a -> TT 21T

Fig. 3. Illustration of the similarity between "back projection" reconstruction in the x-ray

case and echo mode synthetic focus image formation with ultrasound.

Left panel - Reflection Ultrasound Data Space - Pixel driven synthetic focus algorithm

generates a unique hyperbolic curve along which "back projection" algorithm performs

a line integral for the data value at each pixel value. Right panel - Transmission X-ray Data Space - Pixel driven convolution algorithm

generates unique sine wave like curve along which "back projection" algorithm per- forms a line integral for the data value at each pixel value.

238
assigned to a new pixel. The line integration

along curves in data space is assigned to each

pixel in this mode of computation.

An alternative conceptualization of back pro- jection is possible in which each data point in data space is used to influence the value of all pixels in the image space before a new data point

is processed. This formulation may be termed

"profile driven" back projection for the reasons

just given, or termed "smear and add" back pro- jection because the pixels which are influenced

most by each data point are located on or near a curve in image space. The "smear" may refer to convolution. In the x-ray case, the "smear and

add" occurs back along the original x-ray path

which produced the data value at the detector.

This is a very strong intuitive reason for the term "back projection". In the ultrasound case,

the back projection in the image space occurs along an ellipse ( not a hyperbole ) for each data

space. The ellipse, of course, represents the

locus of points of equal transmitter-receiver

pair round trip time. The superposition of the

set of values along all ellipses for all such transducer pairs constitutes the final ultrasound scatter amplitude image in an analogous manner to the formation of an x-ray convolution

algorithm image by the sum of all back projected

convolved projections. This viewpoint is further

explained in figure 4.

r-i source

Vl.5(t)

data space

14,11 (t) -t

ul trasound

transducer array

A. Diffraction Considerations

Although no diffraction theory has been used

in the derivation of the synthetic focus equations,

it is still true that images obtained from their

application are very nearly diffraction limited

(at least qualitatively and quantitatively in some cases). The reason for this, perhaps surprising, result lies in the use of an extremum ray

path time between the scattering center (image

point) and transducer element in the synthetic

focus method. These ray paths are often identical

to, or very nearly equal to, the characteristic

solution lines to the wave equation (the wave

equation includes diffraction effects). Thus,

although some energy travels by diffracted paths,

a large fraction usually will travel by the ex- tremum paths used by the synthetic focus method.

B. Comparison With Seismic Methods

Many similarities exist between the synthetic

focus ultrasound algorithm developed by Johnson

et al [7] and classical seismic migration methods

[ 11 ] . One similarity is in the method of collecting data. Both migration and synthetic focus methods use the concept of separate source or transmitting points and geophone or receiving

points respectively. This is illustrated in figure 5 for the case of a linear geophone and circular synthetic focus ultrasound arrays.

source circle

ray source

projection

profile

convol ved projection

profile

Fig. 4. Illustration of the ultrasound analog of back projection of a convolved

projection profile.

The left figure shows the signal voltage 5(t) received on element 5 when transmitting from element 1 as a function of time. Also shown is the voltage V14 ii(t) for receiver 11 and transmitter 14. For simplicity, it

is assumed {hat the object space contains only one scattering point Q. The data Vi,j(t) is assumed to be ready for back projection. The right

figure shows an x-ray source and object with a dense point at P which

produces the sharply peaked projection profile. Reconstruction of the object is achieved by back projection of the convolved profiles for all source positions around 360°. In the ultrasound case, the receiver echo

data is projected along ellipses in the object space (note that this is equivalent to summing along a set of hyperbolae in the data space). As

in the x-ray case, back projection of non-negative unconvolved raw projection profile data does not give optimum resolution but instead gives the true object convolved with a blurring function. The effect of the blurring

function may be nearly removed (deconvolved) if the projection profiles are first convolved with a deblurring kernel. Such kernels usually have a strong central maxima with symmetric heavily damped bipolar side lobes.

In the ultrasound case maximum resolution (the Rayleigh limit and even much

better) is achieved when the impulse response of a single scatterer is made

to look like such a kernel in the data space.

239
s

?

'f=2

.5d

transmission mode

receiver array

f J

I

I

reflection mode

receiver

y [—

y

'

I -1 9+1 1

= -1

DATA COLLECTION

GEOMETRY

-3

-2 -1 0 +1 +2

—I—I—I—I

'^^^ si^':^a'% gc gd 9e

-4

+4 ^ 3

.d ^

0 - • c

. b

• a

DATA DISPLAY DOMAIN

0 12 3 4 source axis

prof i 1

e

(common source] common receiver

prof i 1

e

^ommon midpoint

gather

seismic section

(common offset)

DATA COLLECTION

SCHEMES

"IL w 0 1

2 2 source angle axis —

J circular profile

I (common source) common receiver

circular profile

(^common midangle

gather

acoustic

circular section

Fig. 5. Illustration of the similarities between

classical seismic data collection with

linear geophone arrays and ultrasound

imaging with circular transducer arrays. The left most column of figures illustrates

the major parameters used to describe seismic data collection in one-dimensional,

i.e ., linear, arrangements of source positions (shot point = s) and receivers

(geophone = g). The right most column of figures illustrates how the ci rcumgerence

of a circular arrangement of sources and receivers may be described in terms of the analogous parameters in the left column.

The shot position s is replaced by source

angle 65 and geophone position g is replaced by the receiver angle eg.

In the top most left figure, typical source

s is located at position -3 and typical

geophone g^ is located at position +1 (arbitrary units). The mid point of the

(s,g(j) pair is at position -1 and is de- fined as the mid point y ( i.e ., y = -1). The separation of s and gj from the midpoint is -2 and +2 respectively and is de- fined as the offset f (f for "offset" )

.

Note f is positive when g is on the positive side of the midpoint.

Also shown is a typical seismic data collection geometry with a source (dynamite

blast) located at -3 and geophones at -2, -1, 0, 1, 2. This particular source- receiver combination is plotted as points

a, b, c, d, e on the g-s plane. Point d at (-3,1) in the g-s plane, represents

time history data for a source at -3 and

a geophone at +1. The midpoint and offset

coordinates (-1,2) of data point d can be found from its projection onto the midpoint

and offset axes respectively. The directions of straight line sets of data points

at angles of 0, 45°, 90°, and 135° to the s-axis have important properties and are given characteristic names. A vertical

line is a prof i 1

e

and corresponds to a data point with a common source (the usual mode

of seismic collection). A horizontal line

is a common receiver profile (rarely used),

a line at 45° is a seismic section (common

offset) and is often obtained by rearrange- ment of multiple profiles. A seismic sec- tion is also commonly generated by towing

a geophone at a fixed separation behind a source in the ocean. A line at 135° is called a common midpoint gather .

The top most drawing on the right shows how

the concepts described in the left column

can be applied to circular geometries. The

240
Fig. 5. (continued)

linear parameters s, g, angular analogues, 9$,

respectively.

and f have their

Gw, and Gf

The s-g plane, which extends to infinity

on all sides, is replaced by a finite and bounded Qs-Qg plane (bounded by ± tt). The

Gs-eq plane provides a convenient means

for displaying the data collected for x-ray

or ultrasound transmission computed recon- struction tomography. In the top right

figure, a circular receiving array covering

180° is shown opposite the source s. Trans- mission data collected by this array is contained in the trapazoids DEFG and HIJK.

Reflection data for s coincident with g is found on the line AOB. Reflection data for

the receiver offset from the source line

AOB. Reflection data for the receiver offset from the source as shown is found along

lines mnp and qu. (This is one line mnpqr

when the periodic nature of the data space

is considered).

The direction of straight line data sets in the Gs) Gg plane can be given analogous

names as those defined in the s-g plane.

These data sets are shown at the bottom of

the right column ( i.e ., circular profile , common receiver circular profile , common midangle gather , and acoustic circular

sections)

typical

signal

reflection, scatter and Doppler Scatter space above EAT surface

earliest arrival

time (EAT) surface

transmi ssion

mode array

domain null space beneath EAT surface

Fig. 6. Illustration of the mathematical properties of acoustic data collected from source-receiver pairs on a circular

boundary. The time dependent voltage

of the signal received by receiver g is plotted as an amplitude (fourth amplitude

dimension not shown) v_s_. , Gs, Gg, and time t. The coordinates 9$, Gg are source and receiver positions as defined

by the drawing at the right. For any two points s and g on the circumference, there

exists an earliest arrival time (EAT) for acoustic energy to propagate from s to g. This time is zero if s is coincident with

g but is maximum (or near maximum for non- homogenous substances) when s and g are on opposite ends of a diameter. Thus, for

times t 1 ess than EAT, the values in the range (not the domain) of (Gs, Gg, t) are

The similarity between linear array seismic

methods and synthetic focus medical ultrasound

methods exists for both linear and circular

scanning geometries. Circular geometries are found in x-ray computed tomographic reconstruction instruments and in their ultrasound counterparts developed at Mayo Clinic by Greenleaf and Johnson [121. This similarity is explored and developed in figure 5 and its legend. Many of

the important features of transmission mode

reconstruction imaging such as "sinogram" space,

or transformation from fan beam to parallel beam geometries, can be analyzed with the aid of the well-known seismic s-g plane data representation

(s-g means source and geophone pair location for each data record).

zero (no signal has as yet arrived). Thus,

the EAT value assigned to each pair (Gs,

Gg) defines a surface below which all values in the same range are zero. This

surface is called the EAT surface. The

region above the 0-z axis (2j_e. , the

9s ~ 9q line) provides maximum time separation of echoes from most neighboring points

and provides maximum Doppler shifts for

fluid flows. The region above areas abed and ehij corresponds to receiver positions

nearly opposite from the source and are used for computed tomographic ( i.e ., C.T.)

transmission data collection. A maximum

arrival time (MAT) surface (not shown) also can be drawn for which all points

above this surface correspond to multiple

reflections or multiple scattering events,

or both.

The nature of the s-g data domain representation in circular geometries can be extended to include the time variable. An explanation of the features of this three-dimensional data domain is given in figure 6. There it is shown that the domain can be partitioned into two regions by a surface which corresponds to the earliest arrival

time of an acoustic pulse or signal. The distance

between a point P on this surface and the s-g plane corresponds (nearly inversely proportionally) to the "merit" of the echo spatial resolution

information contained in the signal associated

with the point P ( i.e ., a receiver opposite a source can have no or little echo information).

The synthetic focus method reported by Johnson

et al . [7], according to the seismic nomenclature.

241
collects a profile for each transmitter position.

The side looking radars or side looking synthetic

aperture radars can be classified in seismic terms

as producing one zero-offset section per flight

path. It is well-known that superior focused

(i.e., "migrated") seismic images can be obtained

by the use of multiple profiles rather than by the use of one zero-offset section [11]. Thus, our synthetic focus method should produce images

superior to those produced by literal adaptation

of side looking radar or synthetic aperture tech- niques to medical imaging.

Also, in radar technology, refraction ( i.e ., normal moveout corrections) are not usually, if ever, made (but should be for medical imaging).

4. Imaging in Moving Media

A. General Considerations

Imaging in the presence of moving media re- quires that certain changes be made to the basic

image forming equations for both reflection and transmission modes of imaging. We will show that consideration of these requirements provides not only a method for imaging structures embedded in the moving media (points in the moving media) but also methods for imaging the velocity distribution of the moving media itself. The equations of synthetic focusing can be adapted to the case of moving media by using the time of travel associated with the ray paths

which have been bent by the moving media. Thus,

the expression for the time t of travel must be replaced by an expression containing the velocity

of the media. For the case where the velocity of

the media is small compared to the acoustic speed,

this may be written as (by modifying equation 3)

m k

Here, u is acoustic speed, \f is fluid velocity,

and T is a unit tanget vector along the ray path

connecting k to the transducer elements m or j. A more exact expression for t, in the case when t

is not very small in comparison to u, has been given by Johnson and others [10,13]. In addition

to time shifts, a moving media also produces a com- pression or expansion of the shape of a waveform.

When more exact imaging is required, the effect of

this stretching may be removed by use of an appro- priate compensating algorithm as is now shown. Let g(y) = b • h(t-to) be the received synthetic

focus waveform for \? = 0. Here, b is the scat- tering strength and h is the transmitted waveform

(for simplicity, the frequency dependence of the scattering process is assumed to be found in

H (•))• Let an upper case letter represent the Fourier transform of a corresponding lower case

letter. Then, the corresponding expression in frequency space is G(f) = b • exp(-2iTrfto)H(f )

.

The Doppler frequency shift due to motion of the media has the effect of replacing f by (f + Af).

I^lere, Af is given by Af = f ^ • (Tr + Ts)/u, where

V is the velocity of the flow and where Tr and Ts are the unit tanget vectors from the scattering

center in the flow to the receiver and transmitter

(source) respectively. For |V|/u <<1, the effect

of this frequency shift changes the form of G(f)

to GD(f) given by GD(f) = b • exp(-2^fto)H(l - 6)(f)

where 6f = Af. The corresponding time functions

are given by

gp(t) = (b/|l - 6|)h((t - to)/(l - 6)). (6)

Thus, movement of a scattering center toward a source and receiver produces a shortening of pulse

width and an increase in pulse amplitude.

B. Synthetic Focus Doppler Imaging

The principle of synthetic focusing may be ap- plied to Doppler velocity imaging to improve the spatial and velocity resolution and to capture

more of the Doppler scattered signal (by the use of a larger receiving aperture) and thereby in- creasing the signal-to-noise ratio in the final velocity image. Simply increasing the aperture

of a single transducer may not improve Doppler

resolution and signal-to-noise ratio because the Doppler shift will not be constant over the large

aperture. A method is needed which will make

use of the different Doppler shifts on a large

sampled aperture.

For simplicity, a method suitable for flows re- stricted to a plane will be given first. It is assumed that the transmitting and receiving transducers are also restricted to this plane and are located on part of, or on the complete, circumference of a circle. Assume that the transmitter

produces a narrow beam of pulsed-energy which

constitutes a cord of this circle. Let the velocity of the flow at e|ch point along the cord be ^(q). Let Ts(q) and Tj(q) be the unit tanget

vectors from the scattering center q to the trans- mitter source s and receiver j respectively. The

use of time gates to achieve spatial resolution is assumed. Then the Doppler shift Af is given by

(f/u)V • (Ts + Tj). This may be written as Af(q) = (f/u(q)) [(cos ot + cos ej)Vx + (sin et +

sin ej)Vy]q. Then this constitutes a set of

simultaneous equations in Vx and Vy. This set is usually over determined since the set can be spanned with only two independent values of e j

,

but the over-determination provides for better signal-to-noise level. The above equation may

also be written as

Af(q)j = [f/u(q)] (|V(q)|) [cos(\r,fs) (7)

+ COs(V,Tj)], j = 1,2...

Note that the first term is a frequency bias and the second term has a period of 2-n in ej. The direction of the flow ? and its magnitude may

be found from this set of equation by several schemes

:

1) The Fourier transform of the |.bQve equation

may be taken with respect to angle (V,Tj). The square root of the sum of the squares of sin and

cos terms with pet;ii}d 2-n is equal to (|V|f/u)

while the angle (V,Ts) is proportional to the arc tangent of the ratio of these terms.

2) A least squares fit of a phase shifted

cosine function can be made to the data. This least squares technique can also be applied to three-dimensional flows and two-dimensional de- tectors. The velocity V can then be obtained. These two schemes and the theory presented up

to this point assume that a unique value of Af may be obtained for each point q and detector j.

242
This is not exactly true because in practice, the frequency measure is broadened due to: 1) noise,

2) ambiguity due to range gating, and 3) turbulence in the flow. In most or many cases, the broadening may be tolerated by the use of offset

frequency quadrature Doppler detection schemes which produce an output voltage whose mean is proportional to the mean Doppler shift of a broadened signal [3].

C. Flow Reconstruction by Acoustic Transmission

We have previously suggested that fluid flow within a measurement region may be determined by

transmitting and receiving acoustic energy through

the measurement region along a plurality of rays

such that each volume element is transversed by a set of rays having components in each direction

for which flow components are to be reconstructed

[10]. The propagation time of the acoustic energy

along the plurality of rays constitutes the only measurements required by this method which has now

been verified for flows with velocities small com- pared to the speed of sound [4]. Since this method is analogous to computed reconstruction

tomography methods and has been reported elsewhere,

the corresponding theory is not reported here.

D. Synergistic Flow Reconstruction

It is clear that both transmission reconstruction and Doppler methods could be applied simultaneously with sufficient parallel data collection

and processing capability. Such an approach, com- bining larger apertures and both imaging modes,

although perhaps impractical at this time, has several theoretical advantages: 1) greater signalto-noise ratios, 2) greater spatial and velocity

resolutions, 3) the transmission reconstruction

mode can provide refractive index information for correction of the Doppler imaging mode, and 4) drag velocity might be calculated from the dif- ference between the Doppler mode velocity image

(scattering center velocity) transmission mode velocity image. These principles could be applied

to statistically steady-state flow using one Doppler channel and one transmission channel by time multiplex methods.

5. Computer Simulation and Experimental Studies

An example of the resolution capability of the synthetic focus technique is demonstrated in

[ figure 7. This figure is very significant because

I it presents experimental evidence that resolution

1 of less than one-half wavelength (at the center

I frequency of a pulse) can be obtained with ultra1 sound; at 3 MHz this corresponds to 0.25 rrm. It

I is expected that, when synthetic focusing, refracI tive index reconstruction and other ultrasound

imaging modalities are combined, a synergistic

union will result. Thus, each mode will not only

add its own form of new information but will also

help remove some of the limitations of other

' forms of imaging. For example, knowledge of re-

) fractive index can correct for defocusing effects

i in echo imaging mode [9,11].

Thus, a major limitation to applying the com1 plete capabilities of the synthetic focus technique to complex tissues can be solved by the synergistic treatment of the problem of refracraw data deconvolved data

Fig. 7 Synthetic focus images of a nylon thread from data taken from one view angle and from multiple view angles. The top left image represents the raw data from 26 re- ceiver elements for each of five trans- mitters. Left image A is the corresponding synthesized image. The lower left image B is obtained from simulating the effect of many such 32 element arrays on

a circle or radius corresponding to geo- metry of image A. Top right is the re- sult of deconvolving the ray data of top

left with impulse response of the system.

Middle right A and lower right are images

synthesized from deconvolved data and cor- responding to A and B, respectively. The labeled line segments and circles in the center are the relative wavelength of sound drawn to the same scale as the re- constructed images. Note that the full width at half maximum of the peak in image

B' (FWHMg') is less than one-half wave- length (a/2) while that in image B is larger and more nearly A/2. Each picture

element is .04 mm square. The resonant frequency of the transducer elements is about 3 MHz. (Reproduced with permission

from Johnson et al . , Digital Processing

of Biomedical Images, 1976, pp. 203-226.)

tion of ultrasound. Consequently, an iterative

correction of refraction has been developed. This

ray tracing technique has also been approached

from established geophysical seismic imaging

theory. The corrections used by seismologists to unscramble their seismographic results indicate

the feasibility of this approach. An example of

the order of improvement attending images originally collected by synthetic focus methods, when

seismic image correction techniques are used, is given in figure 8. This image is significant be- cause it represents (to our knowledge) the first

application of seismic wave migration techniques

to real ultrasound data. This image has been presented in an earlier paper [9].

In these images presented in figures 7 and 8, no attempt has been made to accurately control

the waveform of the echo from a single point to maximize resolution. Although, the right-hand

243
plastic wedge part of "MAYO"

Fig. 8 Refraction corrected synthetic focus image. The bottom portion of figure shows a plastic wedge and pattern of nylon threads which spell "Mayo", however, only the "MA" portion is visible in the figure. An array of 32 transducer elements is located

to the left but is not shown. Sonic waves produced by the array refract through the wedge, reflect or scatter from the threads,

pass back through the wedge and are then received by the array. No recognizable

image was produced when the corresponding

data was processed with a simple synthetic

focus algorithm which assumed constant

speed of the ultrasound waves. The out-offocus image produced by this simple algorithm is not shown here.

The image at the top is the result of ap- plication of a geophysical data processing

algorithm which corrects for refraction

without prior information of the presence

of the wedge. This is accomplished by "wave front migration" techniques which

determine the effective refractive index

layer by layer as the algorithm works it- self away from the array. Such algorithms

work for layered materials but could be ex- tended to structures found in the human

body. The center frequency of the damped

burst transmitted from the array is 3 MHz. The target is the same one reported in Volume 6 of Acoustical Holography by S. A. Johnson et aT. [7 ]

.

side of figure 7 shows the image produced by a deconvolution process which satisfies only the

general requirements. Therefore, a computer

simulation study was undertaken to investigate

the maximum 2-D resolution limit which can be obtained with a signal constrained to have no frequency components greater than an upper fre- quency limit fm- This transmitted kernel signal

h(t) was chosen to have a frequency distribution

given by H(f) = Hglfl for |f| < fm and H(f) =

0 for |f| > fm. This function is the well-known

Ramachandran Lakshminaraynan kernel [iSl. A data collection geometry of a 12 cm radius ring of 120 common transmitter and receiver positions equally

spaced on 360 degrees was simulated. Imaging was confined within a concentric 7 cm circle. The value of fjTi was set at 1 MHz and the simulated re- ceived echo signals were sampled at 100 ns intervals. The simulated received echo signals were

back projected along ellipses in the image space

as per figure 4. The 2-D point response function

(2-D PRF) was found not to differ significantly

between points near the center and edge of the

7 cm radius imaging region. Various (time) fre- quency filtered versions of the above kernel were

tried also. Only slight improvement in 2-D PRF was observed with some kernels but reduction in 2-D side lobe response could be obtained with an attendant slight loss in resolution with other

kernels. Some of the results of these studies

are presented in figure 9. Since the experimental image obtained by ap- plication of the new transmission mode fluid

temperature and vector velocity technique have

been published in more detail previously [4], only

one example reconstruction is presented here. Figure 10 shows reconstructions of fluid flows made in the refractive index reconstruction breast scanner at Mayo Clinic. Applications of these techniques, for example, for measurement and re- construction of tissue temperatures during hyperthermia cancer therapy have been reported else- where [16].

Data on X.i£.2 Image on

Fig. 9 Illustration of simulated data and cor- responding synthetic focus resolution test. Top left: gray scale plot of received

data for two scattering centers separated

by 1/2 wavelength (measured at the maxi- mum frequency limit of transmitted kernel). The amplitude for 120 views on 360° vs time is shown. Bottom left: amplitude

plot of above data along brightened line

l]^l2. Top right - 0 mm by 9.6 mm synthetic

focus image (64 by 64 pixels) from these

data. Bottom right: amplitude plot along

the white line I3I4 in the above image

demonstrating the resolution of the two point targets. In the gray scale images

above, gray = zero, black = negative, and white = positive amplitudes.

244
Fig. 10. Experimental data and reconstruction of vector components of fluid

vortex. Top left shows experimental data and is an image of the difference between the time of arrival with flow and without flow

(fast arrival = white, no change gray, slow = black) vs^. scan position (left to right) vs_. angle of view (top to bottom). Top

right shows reconstructed planar fluid speed (v^ + V^)''5, black is zero, white is positive. Bottom left shows x component of velocity

Vx- Bottom right shows y component of velocity Vy. In Vx and Vy, black is negative, gray is zero and white is positive. Reconstruced

flow is maximum (73 cm/s) at a radium of 0.62 cm. Reconstructions

are 64 pixels per side. Geometry of vortex scanning plane, and vortex generator are shown in top and side views in right margin.

(Reproduced with permission from Greenleaf et al . , Quantitative

Imaging from Transmission Ultrasound (in press ) .

6. Conclusion

We suggest that instruments capable of producing higher resolution images of specific ultrasound tissue parameters would provide a valuable

service in clinical applications. Wide aperture

techniques are known which can provide this high

resolution. To be successfully applied in the human body, these wide aperture techniques must

be modified to compensate for refraction and possibly, in some cases, also diffraction effects. Candidate techniques can be found in the synthetic

focusing methods developed in our laboratory and

in analogous geophysical or seismic methods.

These techniques can provide resolution of one- half wavelength in homogeneous, isotropic media.

It seems reasonable that this degree of resolution may De approached in the body by use of wide

apertures and improved refraction and absorption

compensating algorithms. Improvement of resolution from one wavelength to one-half wavelength

is difficult because knowledge of the spatial and temporal history of the transmitted and received

waveform is necessary for application of these algorithms. This knowledge may, in principle,

be obtained with the proper transducer design and scanner geometry. Our computer simulation and laboratory experiments provide encouragement and evidence that resolutions of about one to one- half wavelength should be feasible in some ap- plications. We further predict that efforts to design economical scanners to provide this resolution will be a fruitful research and development

endeavor. We believe such endeavors will rely

heavily upon the use of high speed digital data processing methods and sophisticated mechanically

and electronically scanned apertures with large

solid angles.

Acknowl edgment

The support from Dr. Earl H. Wood, Dr. Erik

Ritman, and the staff of the Biodynamics Research

Unit, Mayo Clinic, is appreciated. The refraction

corrected image of the "MA" shown in figure 9 was computed using seismic migration techniques with

the help of John Parr, of Houston, Texas, and his help is greatly appreciated. This research was supported by Grants HL-00170, HL-00060, RR-000Q7.

Hl-04664, NIH-HT-42904 from the National Insti- tutes of Health, United States Public Health

Service; NCI-CB-64041 from the National Cancer

Institute.

References

[1] Wolfe, J. N. , Risk for breast cancer development determined by mammographic parenchymal

pattern. Cancer 37. 2486-2492 (1976).

[2] Wolfe, J. N., Breast patterns as an index of

risk for developing breast cancer. Am. J . Roentgenol . 126 , 1130-1139 (1976).

245
[3] Woodcock, J. P., Development of the ultra- [lO] sonic flowmeter. Ultrasound in Medicine and Biology 2. 11-18 (1975).

[4] Johnson, S. A., Greenleaf, J. F. , Tanaka, M., and Flandro, G., Reconstructing three- dimensional temperature and fluid velocity

vector fields from acoustic transmission [ll] measurements. Instrument Society of America

Transactions, March 1977 (in press).

[5] Sandler, H. and Rasmussen, D. , Angiographic

analysis of heart geometry, in Roentgen- , [i2]

Cine-, and Videodensitometry , Paul H. Heintzen, ed., pp. 212-223 (Georg Thieme

Verlag, Stuttgart, 1971).

[6] Cardiovascular applications of ultrasound. Proceedings of an International Symposium

held at Janssen Pharmaceutics, Beerse,

Belgium, May 29-30, 1973. Robert S. Reneman,

ed. (American Elsevier Publishing Company,

Inc., New York, 1974). [13]

[7] Johnson, S. A., Greenleaf, J. P., Duck,

F. A., Chu, A., Samayoa, W. F., and Gilbert,

B. K., Digital Computer Simulation Study of [14]

a Real-Time Collection, Postprocessing

Synthetic Focusing Ultrasound Cardiac Camera,

in Acoustical Holography , Newell Booth, ed..

Vol. 6, pp. 193-211 (Plenum Press, New York,

1975).

[15]

[8] Duck, F., Johnson, S. A., Greenleaf, J. F.

,

and Samayoa, W. , Digital image focusing in the near field of a sampled acoustic aperture. Ultrasonics , 83-88 (March, 1977).

[9] Johnson, S. A., Greenleaf, J. F., Bahn,

R. C, Samayoa, W. F., Duck, F., Hansen, C, [16]

Tanaka, M., and Lent, A., Reconstruction of three-dimensional ultrasound tissue properties from transmission and other data. American College of Radiology Conferesce on Computerized Tomography and Radiology, St. Louis, Missouri, April 25-28, 1976, pp. 149-162.

Johnson, S. A., Greenleaf, J. F., Samayoa,

W. F., Duck, F. A., and Sjostrand, J., Reconstruction of three-dimensional velocity

fields and other parameters by acoustic ray

tracing. 1975 Ultrasonics Symposium Proceedings, IEEE Cat. #75 CHO 994-4SU.

Claerbout, J. F., Fundamentals of Geophysical Data Processing with Applications to Petroleum Prospecting (McGraw-Hill, New

York, 1976).

Greenleaf, J. F., and Johnson, S. A., Algebraic Reconstruction of Spatial Distributions of Refractive Index and Attenuation

in Tissues from Time-of-Fl ight and Amplitude

Profiles, in Ultrasonic Tissue Characterization , M. Linzer, ed., National Bureau of Standards Spec. Publ. 453, pp. 109-119,

October, 1976. (U.S. Government Printing

Office, Washington, D.C., 1976).

White, R. W., Acoustic ray tracing in moving

inhomogeneous fluids. Acoustical Society of America 53 (6), 1700-1703 (1973).

Brooks, Rodney A. and Di Chiro, Giovanni,

Principles of computer assisted tomography

(CAT) in radiographic and radioisotopic

imaging, Phys. Med. Biol . 2j[ (5), 689-732

(1976).

Ramachandran , G. N., and Lakshminarayanan

,

A. v.. Three-dimensional reconstruction from radiographs and electron micrographs: ap- plication of convolutions instead of Fourier

transforms, Proc. Natl. Acad. Sci., U.S . 68

(9), 2236-2240 (1971).

Johnson, S. A., Greenleaf, J. F., Rajagopalan, B., Christensen, D. A., and Baxter,

B. , Nonintrusive acoustic temperature tomo- graphy for measurement of microwave and ultrasound-induced hyperthermia. Workshop

on Electromagnetics and Cancer, 1977 lEEE- MTTS International Microwave Symposium,

June 24, 1977. (Submitted to the Journal

of Bioengineering .

)

246
Reprinted from Ultrasonic Tissue Characterization II, M. Linzer, ed., National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C., 1979).

MAPPING TRUE ULTRASONIC BACKSCATTER AND ATTENUATION DISTRIBUTION IN TISSUE -

A DIGITAL RECONSTRUCTION APPROACH

F. A. Duck and C. R. Hill

Physics Divisiorij Institute of Cancer Research

Clifton Avenue, Sutton, Surrey, United Kingdom

The back-scattered intensity from any location in an ultrasonically irradiated

medium is dependent upon both the local back-scattering cross-section and the attenuation by the overlying medium. An iterative digital reconstruction technique has been investigated which is capable of mapping quantitatively and separately the distributions of attenuation coefficient and back-scatter cross-section using multiple pulseecho data. Such a technique will enable tissue to be characterised on the basis of these two separate acoustic parameters. A description of the technique is given,

together with results from simulation studies leading to an improved processing technique. The potential and limitations of the method are discussed.

Key words: Attenuation; back-scattering cross-section; digital reconstruction;

iterative; ultrasound.

1. Introduction

A major deficiency of currently used pulse-echo

techniques for tissue characterisation and imaging

is their failure to give truly quantitative mea- surements of tissue-specific acoustic parameters.

The problem arises since the observed timedependent echo amplitudes result from two sets of unknown quantities. These are back-scattering

cross-sections of the interrogated volumes and attenuation coefficients of the volume in the transmission path. In conventional B-Scan practice it is usual to emphasise the use of back- scattering cross-section as the useful tissue

characterisation parameter, and suppress, or com- pensate for, the amplitude changes due to the tis- sue attenuation. This latter is done in two ways.

In the first place, a time-gain-compensation (TGC)

amplifier is used which compensates for attenuation

under the assumption that attenuation, if not uniform, varies in a way which is identical irrespective of transducer position and orientation. The precise form of the attenuation versus time (or

depth) variation is often under operator control. Secondly, compound scanning techniques are used which result in an evening-out of the shadowing

effects of overlying tissue layers, with any given

TGC function. Automatic methods have been de- veloped for adaptive gain compensation (McDicken

et al . [l]i; De Clercq et al . [2]). These have shown that some improvement in gain compensation

can be obtained, and presumably the TGC function

generated could be used diagnostical ly. However

such techniques are designed to operate on multiple

^Figures in brackets indicate literature

references at the end of this paper.

pulse-echo data taken from a particular orientation,

assume uniform back-scattering and have an operating time constant of several seconds. In contrast,

the method we have developed, and which is described below, generates separately two-dimensional

maps of attenuation coefficient and back-scattering cross-section, from multiple orientated pulseecho data which may be gathered very rapidly for subsequent processing. The two clear incentives

for investigating this technique are:

1) It provides a quantitative map of acoustic

attenuation coefficients which may be used dfagnostically for tissue characterisation.

2) It provides a correctly attenuationcompensated B-Scan, a map which can now be correctly referred to as a back-scatter map.

2. The Method

As noted above little or no diagnostic information from local attenuation variations is available when compound B-Scanning is used. In simple

scanning, however, regions which differ significantly from the expected local attenuation will,

by virtue of the pre-set TGC used throughout the

scan, result in modified signal levels from re- gions beyond them. For example a local, dense

athero-sclerotic lesion will cast a shadow below

it, and a fluid filled cyst of low attenuation will result in increased amplitude signals from tissue

beyond it since the gain is over-compensating for attenuation losses. Such signs are used clinically

for diagnosis but only under those circumstances

where the local effects are clear. The basic con- cepts are shown simply in diagrammatic form in figure 1, which shows images of a localised in- crease in attenuation (at A) in a uniform scattering medium. A simple linear scan results in an

247
Primary images

a) Linear scan 1 b) Linear scan 2

Secondary images

c) Scatter map d) Attenuation map

vestigated in ultrasound for the reconstruction of

acoustic attenuation from transmitted pulse amplitudes (Greenleaf et al . [3]) and for the reconstruction of acoustic refractive indices from transmitted pulse times-of-fl ight (Greenleaf et al . [4]). The analytic description for this problem was formulated by Radon [5] and a range of computational techniques, based on this analysis or on the

use of iterative techniques, have been reported

( e.g . , Gordon et al . [6]). In transmission imaging

the reduction in intensity (or shadow) in the transmitted energy can be measured directly. In the present situation however this reduced intensity signal cannot be measured directly but is re- radiated with a strength depending upon the local back-scatter cross-section. A new set of unknown

quantities is therefore introduced. Although the values of these back-scattered cross-sections are unknown their related positions in space are known since the position and orientation of the trans- ducer and time delay can be measured.

3. Theory

Fig. 1. The generation of separate maps of back- scatter cross-section and attenuation co- efficient from multiple pulse echo data.

A local increase in attenuation at A within a scattering medium casts shadows S and

T in simple linear scan images (a) and (b). The combination of these by peak detection

gives a first guess at a scatter map (c). The differences as between this and a, b are used to generate d, the attenuation

coefficient map and correct c.

image (fig. la) in which a shadow (S) is cast through the image behind the local attenuating

site. In this simple case it would normally be assumed that there was indeed a locally high at- tenuation at A. However, an identical image could

have been generated if there was an elongated re- gion of low back-scatter cross-section which was coincident with the shadow region S. These two situations can be easily distinguished by carrying out a second simple linear scan at a new angle

(9) (fig. lb). Now the region which was in shadow

(S) is imaged clearly and there is a new shadow

(T). Combining the two simple scans gives a com- pounds scan (fig. Ic) which may destroy the at- tenuation information. Comparing the simple and compound scans enables the true attenuation map to

be inferred.

In general of course, all tissue layers will cast an acoustic shadow on tissue layers behind them to a greater or lesser extent, and the real situation is additionally complicated because the scattering characteristics of the medium vary. However, as seen below, account can be taken of both sets of parameters simultaneously.

The physical situation described is in many

ways conceptually similar to the problem handled

in axial tomography, and whose computed solutions

are exploited widely in clinical medicine for the reconstruction of x-ray attenuation coefficients

from transmitted x-ray intensities. Here the problem of the reconstruction in 3 dimensions of

a parameter map from a set of 2-dimensional pro- files is reduced to that of the reconstruction of

a set of parallel, 2-dimensional distributions of the parameter from related 1-dimensional profiles.

Such transmission imaging techniques have been inThe mathematical formulation of the problem is designed to establish a set of simultaneous equations based upon an assumed model; the equations

may then be solved iteratively by computational

techniques. At present there is no equivalent

formulation to that of Radon for the reconstruction of distributions of parameters from transmitted profiles. Indeed it may well be that if there were it would not be of direct use computationally

because of the necessary assumptions made in the

model

.

The back-scattered intensity Ip received from

any position r in an ultrasonically irradiated

field, can be given as

I = I ref

A(r) exp a It'

r

(1)

where A(r) is a factor depending upon the beam geometry;

r = the distance of the scattering target from

the acoustic centre of the transducer;

c = the local attenuation coefficient; and

a = the local back-scattering cross-section per unit volume per steradian.

In logarithmic forms this becomes

2.n (2)

In order that the situation is amenable to a digital solution the region to be imaged can be modelled as a rectangular grid of n elements, within

each of which and a are constant, with the only

changes being at the boundaries of the elements.

This geometry is illustrated in figure 2. In ad- dition it is assumed that there are no losses from

absorption and scattering processes outside the region to be imaged. Then, for any image element within this set, eq. (2) can be rewritten as

In (Vef)

= K 2L + ^n(0^

n=l

(3)

248
—

—

i

Transducer

Fig. 2. Image grid geometry. The image consists

of n cells Pi...Pn. Each cell Pf has as- sociated with it acoustic parameters of attenuation coefficient a-j and back- scatter cross-section, o-jWp^ is the ray/

cell intersection length.

where K,- is a potentially known geometric factor,

and where W-j , i = l...n, are a set of geometric

weighting factors related to the image grid and beam geometry. If ray geometry is assumed then

W-j is the length of intersection of the ray with

the image element Pi. In general W-j = 0 for many i. If a multiplicity of measurements 1^ are made, from a number of directions then eq. (3) extends

to a set of simultaneous equations in which a-j,

i = l...n and a-j, i = l...n are the unknowns.

One characteristic of this set of equations is that it is sparse since, as pointed out above,

many values of Wi are zero. A digital iterative

technique is suited to the solution since it can handle such large sets of equations under conditions where exact solutions may be multiple, or

not exist at all. As pointed out above, such techniques have already been used highly successfully in medicine for the reconstruction of the distribution of x-ray attenuation coefficients

from transmitted profiles and in radiation emission tomography.

4. Computational Procedure and Results

As presented, the problem is closer to that

posed in emission than in transmission tomography.

In the former case the isotopic distribution is to be mapped in the presence of attenuation. In general however the techniques described in emission tomography either ignore the effect of at- tenuation or compensate for it simply by comparing

opposed views. In general no serious attempt is made to generate attenuation maps for diagnostic

use. Clearly, our formulation set out above allows for the computation of both back-scatter

cross-sections and attenuation coefficients

simultaneously. The successful implementation of

this approach is described later.

A variety of iterative approaches are available

and are under investigation. The technique which

at present appears most promising and has been in- vestigated most fully generates the (n + l)th value of attenuation coefficient from the nth value a" by

n+1 W

1 + Z(W2) +V) (4)

where e is the difference between the data value

from any location and the predicted value from the current image arrays, and c is a weighting factor

for the back-scatter cross-section. (WH is sum- med only over the image elements in the beam up to the position related to the data value used. Simi- larly, the (n + l)th value of o.j is generated from

the nth value using eq. (5)

n+1

(5)

These expressions are similar to those used by

Gordon et al. [7] in the transmission reconstruction algorithms ART. The program set up to investigate this approach

can receive either simulated or real data. Simulation enables up to 10 circular fields of specified radius, position and acoustic properties to

be used. Figure 3 shows a reconstructed image

using simulated data from a cylindrical scattering

region containing smaller cylindrical regions of increased attenuation. The larger region is of

12 mm radius and has an attenuation coefficient of

Fig. 3. Reconstructed attenuation coefficient map from simulated data after 4 cycles. The image is on a 33 x 33 matrix of 1 mm square

cells. The object was a cylindrical region

12 mm diameter, attenuation coefficient

0.2 neper cm"i including 4 regions 4, 3,

2, 1 mm diameter, attenuation coefficient

0.1 neper cm"^. Data was from 10 linear

scans with pulse spacing 0.5 mm. The as- sociated scatter field was uniform.

249
0.2 neper cm"i. The smaller regions have radii

4, 3, 2, and 1 mm and attenuation coefficients of

0.1 neper cm"i. The image shown was generated

after 4 iterative cycles, i.e . after all the data

had been used 4 times. The convergence and numerical accuracy of the computation is indicated in figure 4. The attenuation coefficient values in pixels along column 18 are plotted for the second, fourth and sixth iterative cycles. There is little

alteration in the values from the third to the fifth cycle and the solution clearly is converging

to values which are numerically correct.

Such rapid convergence to a low noise image is dependent very largely upon the choice of iterative

procedure used. In particular it has been found

that the most rapid convergence has been from a primary scatter map generated from all the data either averaged or peak detected, with a primary

attenuation map set to zero. Convergence did oc- cur from a primary scatter map generated from a single linear scan, but was very slow and oscillatory in pattern. The sequence of iterative cor- rections has also been observed to alter the noise

characteristics of the final image. Several se- quence orders have been investigated including se- quencing along a pulse train, in a forward or re5 10) 15 20 25 30 Image cell

Fig. 4. The convergence of attenuation values along

column 18 of figure 3 after 2, 4 and 6 cycles compared with the simulated object

values. The starting assumption was a = 0 everywhere. Pulses taken in sequence and pulse values in reverse sequence.

z!5

Fig. 5. Reconstructed maps of backscatter cross-section (upper) and attenuation coefficient (lower) from overlapping regions. The objects are shown on the left. The reconstructed maps with

high threshold are shown in the center. An edge artifact appears in the attenuation map. Low threshold images (right) are less noisy and show suppression of the artifact.

250
verse direction, and changing order in which pulses

are used. An additional weighting not included in eqs. (4) and (5) has also been used which improved convergence, to compensate for the fact that pixel values close to the transducer are modified more

often than those at a distance along a sampled

pulse.

Abrupt changes in the scatter level have been found to result in edge artifacts occurring in the attenuating field. This is illustrated in figure

5, which shows reconstruction of a 3-component sim- ulated field with overlapping regions of altered a and a. A ring artifact in the attenuation plot is clearly evident, associated with the perimeter of

the small scattering region. However, when a threshold is introduced to limit the conditions

under which eqs. (4) and (5) operate (as in fig. 5, right) the edge artifact is suppressed. It is clear that in tissue it is unlikely that such an abrupt change will occur but such a threshold also enables a control to be kept on the effect of highly directional spectral reflections.

5. Discussion

A convergent iterative computational procedure

has been developed to solve the set of equations

describing quantitatively the back-scatter of sound from a distributed scattering and attenuating medium. It has been shown that, under simulation conditions, accurate reconstructed maps of both back-scatter and attenuation distributions

can be obtained. Some problems posed by the ap- plication of the techniques to real data have al- ready been investigated. Since an iterative pro- cedure is being used, it is possible to include

controls which limit the range of application within the iterative process to include only those which are deemed to force the process to converge

effectively. It is clear however that the success

of the application in tissue will depend upon the extent of validity of some of the assumptions used

in the model, and this is yet to be evaluated. Anisotropy in o or a, position errors caused by

refractions and the effects of a finite beam width

and diffraction errors must all place some ulti- mate limitation on the method. Within these limi- tations however the techniques offer the potential

of a quantitative imaging of back-scatter crosssection and attenuation coefficients from pulseecho data.

6. References

[1] McDicken, W. N., Evans, D. H., and Robertson,

D. A. R. , Automatic sensitivity control in diagnostic ultrasonics. Ultrasonics 12, 173-

176 (1974).

[2] DeClercq, A. and Maginness, M. G. Adaptive

Gain Control for Dynamic Ultrasound Imaging,

in IEEE Ultrasonics Symposium Proceedings

pp. 59-63 (1975).

[3] Greenleaf, J. F., Johnson, S. A., Lee, S. L., Herman, G. T., and Wood, E. H., Algebraic

Reconstruction of Spatial Distributions of Acoustic Absorption within Tissue from Their

Two-Dimensional Acoustic Projections, in Acoustical Holography , P. S. Green ed., vol.

5. , p. 591 (Plenum Press, New York, 1974).

[4] Greenleaf, J. F. and Johnson, S. A., Algebraic Reconstruction of Spatial Distributions of Refractive Index and Attenuation

in Tissues from Time-of-Fl ight and Profiles,

in Ultrasonic Tissue Characterisation , M. Linzer ed.. National Bureau of Standards

Spec. Publ. 453, p. 109 (U.S. Government

Printing Office, Washington, D.C., 1976).

[5] Radon, J., Uber die Bestimmung von Funktionen

durch ihre Integralwerte langs gewisser

Mannigfaltigkeiten. (On the determination

of functions from their integrals along certain manifolds.) Berichte Sachsische Aka- demie der Wissenschaften (Leipzig), Mathematische-Physische Klasse 69. 262-277 (1917).

[6] Gordon, R. and Herman, G. T. , Three-dimensional reconstruction from projections: a review

of algorithms. International Revi ew of Cytology. 38 , 111-151 (1974).

[7] Gordon, R. , A tutorial on ART, IEEE Trans . Nuc. Sci . . NS-21, 78-93 (1974).

251

CHAPTER 9

SIGNAL PROCESSING AND PATTERN RECOGNITION

253

Reprinted from Ultrasonic Tissue Characterization II, M. Linzer, ed. , National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C., 1979).

A COMPREHENSIVE ULTRASONIC TISSUE ANALYSIS SYSTEM

M. Linzer, S. I. Parks, S. J. Norton,

F. P. Higgins', D. R. Dietz^ and R. W. Shideler

National Measurement Laboratory

National Bureau of Standards

Washington, D.C. 20234

and

T. H. Shawker and J. L. Doppman

Clinical Center

National Institutes of Health Bethesda, Maryland 20014

A progress report on the development of a comprehensive system for ultrasonic

tissue characterization is presented. Major elements of the program include com- puterized tomography studies, particularly for breast cancer detection; opto-acoustic

visualization of ultrasonic fields, for testing of new imaging schemes, studies of propagation through inhomogeneous media, in vitro measurements, and transducer calibration; electronic focusing, especially annular array imaging; sensitivity enhancement, using digital signal averaging and pulse compression techniques; computer and chirp waveform techniques for compensation of frequency-dependent attenuation; the SonoChromascope, a digital device for real-time acquisition, processing, and display

of B-scan images; and computer-based image processing.

Key words: Annular array; breast cancer; chirp signals; imaging; opto-acoustic;

pulse compression; sensitivity; signal averaging; signal processing;

tissue characterization; tomography; transducers; ultrasonics.

I. INTRODUCTION

This paper reports on the progress of a Com- prehensive Ultrasonic Tissue Analysis System

(CUTAS) which is being developed by the Signal

Processing and Imaging Group, Center for Materials

Science, NBS, and clinically-evaluated by the Department of Diagnostic Radiology, Clinical

Center, NIH. Three principal areas are being

emphasized in this work:

1. Computerized tomography studies, particularly

for breast imaging,

2. Optical visualization of ultrasonic fields.

3. General purpose clinical studies.

II. COMPUTERIZED TOMOGRAPHY STUDIES

Major emphasis to date has been the development of backprojection algorithms for reconstruction of cross-sectional images of reflectivity

using a circular array of transducer elements

enclosing the object. Three basic modes of data acquisition and image reconstruction were

analyzed (fig. 1): (1) the same element serves

as transmitter and receiver and data is backprojected along circular paths centered at the

'Present address: Western Electric Company,

Princeton, New Jersey

^Present address: McDonnell Douglas Corporation,

St. Louis, Missouri

0 2p/c 0 (P,+p,l/c

Fig. 1. (a) Operation of circular array with

same element serving as transmitter

and receiver. Each point in the A-scan is the sume of echoes arising

from scatterers along a circular arc centered at the active element, (b) Operation of circular array with separate transmitter and receiver elements.

Each point in the A-scan is the sum of echoes arising from points lying along

an elliptical arc whose foci are the transmitter and receiver.

element; (2) distinct transmitter and receiver

with fixed separation and backprojection along

elliptical paths with the elements at the foci;

and (3) distinct transmitter and receiver with

varying separations and backprojection along

corresponding elliptical paths. Point spread

functions (PSF's) were evaluated for narrowband,

wideband, and an analytically-derived optimum

pulse which yields the best sidelobe response

and a mainlobe width equal to one-third of the

255
1.00

0.75

0.50

1 0.25

-0.25

—-—si'Nyx/y , y\/\,^Nv ^

-4 -2 0 2

r Imm)

Fig. 2. Point spread function obtained by back- projecting an analytically-derived

optimum pulse along circular paths in image space.

including that of the transducer face. The ultra- sonic wavefronts at other planes were also measured and compared to the calculated values.

Both narrowband (gated-cw) and wideband (pulsed)

waveforms were used to excite the transducer. Computerized holographic reconstructions of several model targets were also made. An example

of a reconstructed plane in the field of a pulsed

transducer is shown in figure 3. Other planned

NORMALIZED

DISPLACEMEfjT

AMPLITUtSE

96 mm X 6 4 ps 96 mm X 6,4 ps

wavelength corresponding to the cut-off frequency

of the pulse (fig. 2). When backprojection is performed along elliptical paths, corresponding

to two separate elements, the mainlobe of the PSF was shown to be broadened by a factor proportional

to the cosine of half the angle subtending the

two elements at the center of the array. This

behavior places a practical restriction of about

45° on the angular separation of the elements. Computer simulations confirmed the salient

properties predicted by the analytically-derived

PSF's. The characteristics of the PSF's were calculated as a function of the number of array elements, the position of the reflecting point

within the object, and the shape of the pulse. The backprojection analysis has been extended

to three-dimensional reconstructions (using

spherical transducer arrays) and to incorporate

corrections for velocity inhomogeneities in the medium. Work in progress includes the develop- ment of a perturbation approach for correcting

velocity images and algorithms for frequencydependent time-gain compensation. A prototype

breast scanner is now under construction and will

be used to evaluate these various developments

in ultrasound tomography.

III. OPTICAL VISUALIZATION OF ULTRASONIC FIELDS

A major laboratory facility for reconstruction

and optical visualization of ultrasonic fields

has been developed. The system is based on the

use of a Michel son interferometric system which

is capable of measuring the displacement of a thin metallized 150 mm diameter pellicle immersed

in water. Major advances of the NBS development

over previous designs include measurement of both

the amplitude and phase of the displacement, and absolute calibration of the displacement to approximately one percent accuracy.

This capability of measuring the complex ultrasound field over a large aperture, coupled with

computer acquisition and analysis of the experimental data, has provided us with a powerful

research tool for visualization and reconstruction

of ultrasonic wavefronts. In our initial work,

the ultrasonic field of a transducer was measured

at the plane of the pellicle placed near the transducer face. The exact (plane wave) solution

was used to reconstruct the field at other planes.

Fig. 3. (a) Computer reconstruction of a propagat

ing wideband pulse at 100 mm (far-field) from transducer face. Reconstruction was based on measurement of the time-dependence of the amplitude and phase of the pulse in a near-field plane, (b) Actual measurement of pulse at 100 mm plane.

uses of the system include studies of new ultrasonic imaging schemes, measurements of ultrasonic

parameters of tissue in vitro , and examination of ultrasonic propagation through inhomogeneous

media.

IV. GENERAL-PURPOSE CLINICAL STUDIES

A general -purpose clinical scanner is now under

active development (fig. 4). Major components

of the system include annular array focusing for improving resolution; sensitivity enhancement

techniques using A- and B-scan averaging, chirpradar approaches and focusing; first-order

corrections for frequency-dependent attenuation

in the medium; and improved signal processing

approaches combining the real-time acquisition,

processing, and display capability of the Sono- Chromascope with computer post-processing. To date, our approach has been to evaluate each component separately as it is developed. Even- tually, we expect to integrate these various

elements into a unified facility for clinical

ultrasound examinations.

A. Annular Array

1. Expanding-Aperture Annular Array

A dynamically-focused annular array system for contact B-scanning has been developed (fig. 5). The design is based on a constant F-number

approach, whereby, at short focal lengths, the aperture is expanded in proportion to the focal length. This approach allows the use of wider

array elements, thus increasing the sensitivity

of the system and reducing radial -mode coupling. Other major advantages include a substantial

reduction in the delays and refocusing rates required for the lens synthesis with a corresponding reduction in the electronic complexity of the system. The initial design employs an array.

256
ULTBAFAST

SIGNAL ENHANCER

A SCAN DIGITIZATION AND AVERAGING

ANNULAR

ARRAY

SCANNER RFSUBSYSTEM PREPROCESSING SONOCHROMASCOPE

MULTIPARAMETER

ACQUISITION PROCESSING AND DISPLAY NONLINEAR

STUDIES VIDEOTAPE

A SCAN

RECORDER

Fig. 4. Block diagram of general purpose clinical ultrasound system.

FREQUENCY 25MHi

DIAMETER 3 9 CM

MUMBER OF RINGS 12

Fig. 5. Operation of the expanding-aperture

array with dynamic focusing on receive.

operating at 2.25 MHz, with four annul i active

at the near focal length of 1.5 cm. As the focal length increases, the array expands to a maximum

of twelve rings, with 4.0 cm outer diameter, for

focal lengths greater than 12 cm. A single,

tapped delay line with 1 \is total duration pro- vides the time delays for focusing on receive.

A continuously-variable point or line focus is provided on transmit. Experimental measurements

vides the time delays for focusing on receive.

A continuously-variable point or line focus is provided on transmit. Experimental measurements

of the focusing properties of the system have been

made. Some of these results are shown in figures

6 and 7. Clinical evaluation of the annular array

scanner is now underway.

Fig. 6. B-scans of AIUM test object with a single

fixed-focus transducer (a) and with the dynamically-focused annular array (b).

>

1 1 1

' A

-r I 1

'

Uni

:rary

(Arbil / ^'^

\

j mm \

IGNAL

.1 1 1 1 1 1 1 -8 -6 -4 -2 0 2 4 6 8 OFF-AXIS DISTANCE IN FOCAL PLANE (mm)

Fig. 7. Measured response of the annular array

focused at 10 cm on transmit and receive.

2. Wideband Annular Array Response

Theoretical studies of the effect of bandwidth

on the focal plane response of a circular lens

and annular array were carried out. Particular

emphasis was placed on lens systems operating at approximately 50 percent bandwidth, typical of those used in ultrasound imaging. An analytical

model of the focal plane response of both the circular lens and annulus, driven by an impulse,

was developed. The wideband response was then calculated by convolving the impulse response

with the driving function. For a circular lens,

the beam width in the focal plane, as well as the position and height of the sidelobes, was analyzed

as a function of bandwidth and aperture weighting.

The wide bandwidth model of an annulus was used to calculate the response of an annular array. A detailed comparison was made of this model with

the experimentally-measured response of an array, operating at 2.25 MHz with 40 percent bandwidth

(fig. 8).

B. Ultrafast Signal Averaging and Pulse Compression Techniques

A signal averager and pulse compression system

has been developed for sensitivity enhancement

in ultrasonic diagnosis. Potential applications

include the use of transducers which are ineffi257
-8 -6 -4 -2 0 2 4 6 8 OFF-AXIS DISTANCE p (mm)

Fig. 9. Ultrasonic reflection from posterior

cortex of tibia; (a) no averaging;

(b) after averaging for scans.

Fig. 8. Field pattern at 10 cm generated by a 0.4 diameter piston transmitter and a thin, 1.4 cm diameter, annulus receiver.

The solid line is the calculated

response and the dashed line is the measured response.

cient but otherwise have very desirable features

( e.g. , point and line sources, polymer trans- ducers, CdS phase-insensitive transducers);

higher frequency operation for improved pattern

recognition and increased resolution; detection

of small reflections; examination of obese

patients; and penetration through skull and bone. These systems also make it possible to reduce

peak power while keeping average power, and hence sensitivity, constant.

1 . Signal Averager

The signal averager is capable of real-time

(unbuffered) averaging at 50 MHz rates. To our knowledge, this device is the fastest digital

averaging device in existence. Major features include 4K 24-bit words, 12.5 kHz maximum repetition rate, computer interface, 6-digit cursor

readout of signal amplitude, region of interest

expansion (up to a factor of 16), 3-digit setta- bility of sample rate, internal/external trigger,

internal delay, segmented memory capability (full,

halves, quadrants, octants), plug-in ADC's (4 bit,

50 MHz; 8 bit, 20 MHz), ADC resolution enhancement

(via_ ordered dither), display normalization and semi-real time display at high frequencies. The sensitivity-enhancement capability of the averager

was demonstrated on a PZT line source and on a number of highly-attenuating biomaterial s, including human tibia (fig. 9), and a fiber composite

(fig. 10) used in synthetic implants.

2. Pulse Compression

The pulse compression circuit incorporates a surface acoustic wave (SAW) "chirp" filter. Pulse compression ratios of 30:1 and 8:1 have been obtained in the case of 8 MHz and 3 MHz filter

bandwidths, respectively. An example of both an expanded and compressed (8:1 compression ratio) echo from a human heart in vivo is shown in figure 11. The chirp system was also used to compensate for frequency-dependent attenuation in the medium by modulating the amplitude of the

(a)

(b)

Fig. 10. Backwall reflection from 5 cm thick

fiber composite: (a) no averaging;

(b) after averaging for 2^^ scans.

Fig. n. Preamplified echo from a human heart in vivo . The initial transient is the clipped transmission pulse; the remaining

echoes are from tissue: (a) expanded

pulse; (b) pulse after 8:1 compression.

expanded stimulus pulse as a function of time. Since the frequency of this pulse was also timedependent, the strongly-attenuated frequencies

were enhanced. This approach has important implications for improving range resolution and for tissue characterization and is now under detailed

investigation.

258
C. SonoChromascope

The SonoChromascope (fig. 12) is a state-ofthe-art device for the digital acquisition,

processing, recording, and display of ultrasonic

B-scaii images.

Fig. 12. Clinical ultrasound examination using

the SonoChromascope.

imaging, including electronic focusing and com- puterized tomography; sensitivity enhancement; measurement of tissue parameters in vitro ; studies of ultrasound propagation through inhomogeneous media; computer and chirp techniques for compensation of frequency-dependent attenuation;

real-time digital processing and display techniques; and computer-based image processing.

Several of these developments have already been completed, and, v/here appropriate, are undergoing

clinical testing. Complete descriptions of this work will be published shortly.

Acquisition algorithms include a choice of

log or linear detection; recording the minimum

and/or maximum echo for each pass through a pixel

(thus, for example, providing a measure of scattering anisotropy); unconditionally writing

the last value; and summing with normalization

(thereby improving sensitivity). A combination

of up to four different algorithms may be applied

simultaneously to produce different spatiallycongruent images during the same B-scan. After acquisition, the image or images are displayed on two color-TV monitors. Images in complementary colors may be overlaid to permit

visual discrimination of subtle differences. A variety of thresholding and display modes, aug- mented by a lightpen, permit semiquantitative

measurements of ultrasound echo intensity. To use the lightpen, the operator "paints in" the area of interest. As he does so, the average

image intensity (or intensities) and the area painted in are displayed on digital readouts.

If more sophisticated processing or storage

is required, the data may be transferred to a minicomputer. Processed or stored images may be returned to the SonoChromascope for display.

Spatial and amplitude resolution depend upon

the acquisition mode. For example, in the "un- conditional write" mode, the word size is 8 bits and the picture contains 480 x 480 pixels; in the sum mode, the word size is 14 bits and there

are 480 x 240 pixels.

The SonoChromascope is presently interfaced

to a commercial B-scan system, from which it receives the rf^or- log -detected A-scan signal

and appropriate information about transducer

position. It is now undergoing clinical evaluation.

V. SUMMA.RY

A major effort is now underway in developing

a comprehensive system for ultrasonic tissue

characterization. The program encompasses

Reprinted from Ultrasonic Tissue Characterization II, M. Linzer, ed.. National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C., 1979).

THEORETICAL ANALYSIS OF INSTANTANEOUS POWER SPECTRA

AS APPLIED TO SPECTRA-COLOR ULTRASONOGRAPHY

W. D. Jennings, E. Holasek, and E. W. Purnell

Department of Surgery, Division of Ophthalmology

School of Medicine

Case Western Reserve University

Cleveland, Ohio 44106, U.S.A.

Spectra-color ultrasonography (SCU), a technique for two-dimensional (B-mode) display of ultrasonic spectral data, has been analyzed theoretically. The analysis in- cludes the use of an instantaneous power spectrum calculated from broadband gated echo spectra produced by an analog spectrum analyzer. The results of the analysis indicate

that additional signal processing factors must be added to the SCU system as it was originally designed. With the inclusion of these modifications, the SCU scan rep- resents a true low resolution instantaneous spectral analysis of ultrasonic echo waveforms. An experiment was performed to test the theoretical equations we have developed relating SCU to an instantaneous spectral analysis. The comparison of the SCU signals and the computed SCU equivalent based on an instantaneous power spectrum is presented.

Key words: Instantaneous power spectra: Color-coded B-scan; spectra-color ultra- sonography (SCU); spectrum analysis; ultrasonic spectroscopy.

1. Introduction

Several years ago we developed spectra-color

ultrasonography (SCU) which was originally de- signed as an approximate spectroscopic technique

to display two-dimensional (B-mode) spectroscopic

information from a sector scanned tissue segment

[l,2]i. Originally, the SCU image was formed by

first passing a broadband B-scan ultrasonic echo

train through a voltage tuned filter set at three different center frequencies (bandpass positions).

Each of the three resultant filtered B-scans was

then assigned a color (red, green or blue). The

three colored B-scans were then superimposed to form a single frequency-dependent color coded

B-scan display. The final colored B-mode image

displayed frequency-dependent properties of the tissue being scanned, though the precise meaning of the display was not apparent.

The subject of this presentation is an analysis

of the SCU process in terms of an instantaneous

power spectrum. An instantaneous power spectrum

is a time dependent spectral decomposition of a signal. The conventional Fourier Power Spectrum

of a signal is defined by an integral of the signal over all time, and thus, is independent of

time. An instantaneous power spectrum, however,

is a function of both time and frequency. It is the dual functionality of instantaneous power

spectra that makes them applicable to signals that

^Figures in brackets indicate literature

references at the end of this paper.

originate from spatially distributed sources with

varying spectral content, such as ultrasonic echo waveforms.

Several definitions of an instantaneous power spectrum have been devised. We began our work on instantaneous power spectra by attempting to adapt

a particular instantaneous power spectrum, the one defined by Chester Page [3], to spectra-color

ultrasonography. During our investigations, ex- perimental evidence led us to the conclusion that

for spectra-color ultrasonography to represent a true instantaneous power spectrum, it is appro- priate to use Morris Levin's modification of Page's definition of an instantaneous power spectrum, rather than Page's original definition.

This paper is an account of those investigations.

2. Theory

Essential to the analysis of spectra-color

ultrasonography, is the concept of an instantaneous

power spectrum. We began with the approach of Chester Page [3] which we will briefly review here. For any time domain signal g(t)2, the running

Fourier transform of g(t) is defined as

t

G^(co) = f

g(x)e-J'^^dx . (1)

2ln our case, g(t) is the receiving transducer

voltage corresponding to the instantaneous

acoustic pressure on the transducer face.

261
That is, G^((;)) is the Fourier transform of the semi-infimte signal g(x) taken from x = -«> to

X = t. Note here that x is a dummy variable, al- lowing us to use the time variable t as the trail- ing edge of the gate on g(t). The instantaneous

power spectrum of g(t) can then be defined as

p(t,co) = 3t

|G^(a))

Page also shows that p(t,to) can be represented by

p(t,co) = 2g(t)Re Jwt

xle-J-^^dx (3)

By combining the exponential terms, and interchanging the order of integration we get

J.(t) = 2g(t)Re

(2) or

Ji(t) = 2g(t)Re

Jj C.(a))g(x)eJ'^'^"'')da)dx

/

g(x)/ C.(a,)ej'^(^-^)da)dx

(9)

(10)

By use of eq. (4), eq. (10) becomes

Using eq. (3) as a starting point, we have ana- lyzed SCU as follows: In the original SCU implementation, the signal g(t) was passed through a voltage

tuned filter set at three different bandpass positions. In the frequency domain, the i**^ filter can

be described by some function C-j(u). In general,

Ci(u)) is a complex function, including phase delays

introduced by the filter as a function of frequency.

The time domain representation of the filter will be designated by c-j(t), which is also complex in general

The function c-j(t), is the inverse Fourier transform

of C-j(u), and is the impulse response of the filter

J.(t) = 4TTg(t)Re J

g(x)c.(t- x)dx (11)

For a filter that

(ci(t) = 0 for t

is causal in the time domain

: 0) , eq. (11) becomes

Ji(t) 4TTg(t)Re j g(x)c.(t-x)dx (12)

:.(t) = J-/c.(.)eJjwtdto (4)

Thus, the filtered signal can be described in the time domain by

S.(t) = Re[c.(t)*g(t)j (5)

What we would like to display is the band-limited

instantaneous power spectrum of the signal. That

is, the desired display is

Ji(t) = j p(t,w)C.(aj)dco (6)

Ji(t) is the instantaneous power (as defined by

Page) of the signal g(t) in the frequency band de- scribed by C-i(a)). Substituting eq. (3) into eq.

(6) and rearranging we get

J.(t) = 2g(t) j C.(w)Re e^^^^y g(x)e"J^^dx dw . (7)

If we assume at this point that the filter function

Ci(u)) is a real valued function, rather than complex, we can write

J.(t) = 2g(t)Re

or

J.(t) = 2g(t)Re

/

C.(a3)ejut /g(^x)e '^'^^dxdw

(8) jj C.(a))eJ'^S(x)e"^'''dxdw

The integral in eq. (12) is the convolution in- tegral for g(t) and c-j(t). Using the notation of

eq. (5), eq. (12) becomes

J^(t) = 4^g(t)S.(t) (13)

Thus, we come to the conclusion that for SCU to represent a true color coded low resolution in- stantaneous spectral analysis we must modify the original system in two ways:

(1) The filters used must have filter functions

that are real in the frequency domain, or be modified so as to be effectively real.

(2) The filtered waveforms must be multiplied

by the broadband signal before video processing

and display.

3. Experimental Approach

We have tested the theory by comparing J-j(t)

calculated by eq. (6) with J-j(t) defined by eq. (13), which mathematically represents the modified

SCU system.

Calculation of J-j(t) by eq. (6) requires mea- surement of the filter functions C-j(a)). We used

three fixed filters with 1.6 MHz bandwidths centered at 7, 9, and 11 MHz. The fixed filters re- placed the voltage tuned filter used in earlier

implementations of spectra-color ultrasonography.

The spectrum of the ultrasonic echo from a glass block was used as a reference spectrum, and the spectrum of the signal passed through each filter

was recorded. The filtered spectra and reference

are shown in figure 1. The spectra are plotted

from 5 to 15 MHz. A 5 MHz crystal controlled

oscillator was used to provide a frequency marker

for accurate spectral measurements. All spectra were recorded by our automated data acquisition

262
wideband

9 10 11 12 13 Frequency (MHz)

14

Fig. 1. Wideband reference spectrum and spectra of the low, middle and hiqh bandpass filtered

reference signals.

system [4] controlled by a programmable calculator.

A natural sponge was used as the target material because of its stability and similarity to human tissue in acoustical properties. The in- stantaneous power spectrum, p(t,a)) required by

eq. (6), was calculated by eq. (2). To produce

the semi-infinite signal gt(x) we constructed a programmable gating system. Using the crystal

controlled 5 MHz source as a clock, the gate could

be automatically varied in length in 200 nanosecond increments. Power spectra |G^((o)|2 of the

signal gated at increasing lengths were recorded.

The value of (3/3t) |Gt(uj)|2 was calculated by sub- tracting spectra of gated signals of increasing

length to approximate the differential. Ji(t)

was then calculated as the summation of

Ci(io) • (8/9^.) |Gt(a)) |2 over all frequencies to ap- proximate the integral in eq. (6). To determine Ji(t) by eq. (13), the filtered

signal, Si(t), was multiplied by the broadband

signal, g(t), using a double balanced modulator.

A broadband pulse amplifier was used to bring the

level of g(t) into the operating range (approximately one volt) of the modulator. The modulator

provided bipolar multiplication of the two signals,

as shown in figure 2, The multiplied signal for

each of the three bandpass filters is shown in figure 3. For each filter, an appropriate precision delay line was added to the broadband signal before

multiplication in the modulator. The delay lines

Fig. 2.

2cAnalog signal multiplication for the middle frequency band, a) multiplied

signal, J(t); b) wideband signal, g(t):

c) filtered waveform, Si(t).

3a

3b u i

3c

Fig. 3. Analog multiplied signals, J^(t) fot the three frequency bands, a) high frequency

band; b) middle frequency band; c) low frequency band.

were necessary to compensate for the group delay

through the filters. Group delays were approximately 1 microsecond, but were different for each filter. Thus, the requirement that the filter

functions be real was approximately satisfied.

4. Results and Discussion

Figures 4a, 4b, and 4c, show J-i(t) calculated by

eq. (6), and J-j(t) determined by the signal multiplication described in eq. (13) for the three

filters. The time resolution of the calculated

signals is one point every 200 nanoseconds, while

the analog multiplied J^{t) is a continuous function of time. The calculated Ji(t) represents the average of J-j(t) over the 200 nanosecond interval.

Noise in the system was reduced by averaging in the case of the calculated Ji(t). The plots shown

in figure 4, represent an average of 40 scans through the 5 microsecond section of sponge. Fig- ure 5 shows the individual scans before averaging,

and figure 6 shows plots of the averaged signals. The noise becomes progressively higher with deeper

signal penetration, as shown in figure 5, This

effect is due to the internal noise of the spectrum

analyzer. The signal to noise ratio of the spec- trum analyzer was constant for all signal levels,

since the spectrum analyzer was used in the logarithmic mode. Thus, for higher signal levels

263
4c

[l 1

1 0 1 2 3 4 5 Microseconds

Fig. 4. Comparison of J-j(t) calculated by eq. (6) (upper trace) with the multiplied J-j(t) de- fined by eq. (13) (lower trace) for the three filters, a) high frequency signals;

b) middle frequency signals; c) low fre- quency signals.

(longer gates) the absolute noise level increased.

This resulted in a decreased signal to noise ratio

for the differential power spectrum of higher level signals.

It is interesting to note that the time resolution of the multiplied signal J-j(t) is better than

the resolution of the broadband signal g(t) and significantly better than the resolution of the filtered signals, S-j(t) used in the original SCU implementation (see fig. 2). This is interpreted

as a result of having increased the information

bandwidth of the broadband signal g(t) by the band- width of the filtered waveform Si(t) in the multiplied signal Ji(t).

We can also observe that agreement between the calculated Ji(t) and the analog multiplied Ji(t)

progressively improves as we go from the high

frequency band to the low frequency band. This trend is probably due to the fact that the assumption of a real filter function is better justified

for the low frequency filter than for the high

frequency filter. The time delay error which was approximately constant for the three filters, is most disruptive to the high bandpass filter, be- cause of the shorter repeat period of the filtered

si gnal

.

The results of this experiment show only fair

agreement between the band limited instantaneous

power calculated by eq. (6), and the band limited

instantaneous power produced according to eq. (13).

This result demands that we reexamine the assumptions made in the theoretical analysis. The first

assumption of a real valued filter function is reasonably valid because of the broadband delay

line compensation for the group delay through the filters. The appearance of predominately positive

signals in the multiplied waveforms indicates that

the filtered and broadband waveforms are largely

in phase, though the filters have some dispersive

effects. The second assumption was that the filter

is causal in the time domain. This assumption also appears valid for passive filters. However, close examination reveals that the two assumptions above

are mutually exclusive. That is, if a filter func- tion is real valued in the frequency domain, it must be noncausal in the time domain. This is true

2 3 Microseconds

2 3 Microseconds

Fig. 5. Individual calculator plots of J-j(t) for 40 scans through the sponge, a) high fre- quency band; b) middle frequency band;

c) low frequency band.

Fig. 6. Calculator plot of the average J^-(t) for

the 40 scans in figure 5. a) high fre- quency band; b) middle frequency band;

c) low frequency band.

264
because a real valued function, when transformed by

eq. (4), must have a real part (the integral of the cosine terms) that is an even function of time. An even function of time must be noncausal. Hence,

the transition from eq. (12) to eq. (13) is not

val id.

5. Time Reversal Symmetry

From the above discussion, it appears impossible

to display Page's instantaneous power spectrum by

simple signal filtering and broadband multiplication. The restriction to non-causal filters re- quired by eq. (8) introduces a contribution to the instantaneous power from the signal at future

times. The time reversal symmetry of the filter

function in the time domain means that eq. (13) corresponds to an average of Page's instantaneous

power and a similar instantaneous power with the time scale reversed ( i.e. , a signal taken from

to time t). An instantaneous power spectrum of this type has been introduced by Morris Levin [5]. Levin defines an instantaneous power spectrum

analogous to Page's except with the added property of time reversal symmetry. According to Levin,

the symmetric iriStantaneous power spectrum is given by

where

1

2 3t

2^(03)12 - |G^(a))

G^(a)) x)e-J"^dx

(14)

(15)

Ji(t) = f g(t)Re C^. (a))du (20)

Again, assuming C^{u) is real valued rather than complex, eq. (20) becomes

J.(t) = g(t)Re y G(,o)C.(aOej'"^da) (21)

The integral in eq. (21) is the inverse Fourier

transform of the product G(o))Ci (u) , and hence be- comes the convolution of the two corresponding

time domain signals

J.(t) = 2^g(t)Re[g(t)*c.(t)j

or

J.(t) = 2ug(t)S.(t)

(22)

(23)

where S^-(t) is defined by eq. (5). No assumption

of causality of c-j(t) is required in the derivation

of eq. (23) because of the time reversal symmetry

of Levin's instantaneous power spectrum.

Thus the two modifications of the SCU system

stated above (broadband delay and signal multiplication) produce a band limited instantaneous power corresponding to Levin's instantaneous power spectrum, rather than Page's spectrum as initially

intended.

6. Conclusions

and

g:J(co) = / g(x)e-j"^dx . (16)

t

Levin also shows that p^{t,ui) is given by

Ps(t,a>) = g(t)Re [6(^)6^"^*] (17)

where

00 G(w) = f

g(t)e"J'"tdt . (18)

G(u) is simply the frequency spectrum of the complete waveform g(t). By analogy to eq. (6) above,

we redefine the band limited instantaneous power

Ji(t) (for Levin's spectrum) to be

The analysis we have presented indicates that spectra-color ultrasonography should be modified

in two ways. First, the filters used must have

real filter functions in the frequency domain, in- cluding compensation for the time delays through

the filter. Second, the appropriate signals to color code and display are the products of the filtered signals with the broadband echo waveform,

rather than the simple filtered waveforms.

With these two modifications in effect, SCU rep- resents a true low resolution instantaneous spectral

analysis of ultrasonic echoes corresponding to the instantaneous power spectrum of Morris Levin. In addition, the time resolution of the new system

exceeds that of the broadband signal.

Acknowledgments

This work was supported in part by National In- stitute of Health Grant #EY 00224-15 and The Ohio

Lions Research Foundation.

References

J^it) = / P5(t,a))C.(a))dw (19)

where C^(u)) is defined as before. Substituting

eq. (17) into eq. (19) gives

[1] Holasek, E., Gans, L. A., Purnell, E. W., and Sokollu, A., A method for spectra-color B-scan ultrasonography, J. Clinical Ultrasound , 3^, 175-178 (1975).

[2] Purnell, E. W., Sokollu, A., Holasek, E., and Cappaert, W. E., Clinical spectra-color ultra- sonography, J. Clinical Ultrasound , 3^, 187-189

(1975).

265
[3] Page, C. H. , Instantaneous power spectra, J_. Applied Physics, 23, 103-106 (1952).

[4] Holasek, E., Jennings, W. D., Sokollu, A., and Purnell , E. W., Recognition of Tissue Patterns

by Ultrasonic Spectroscopy , Ultrasonic Symposium Proceedings, 'IEEE Cat. #73 CH 0807-8SU,

73-76 (1973).

[51 Levin, M. J., I nstantaneous Spectra and Ambiguity Functions , IEEE Transactions Information

Theory, Vol. IT-10, 95-97, (1964).

266
Reprinted from Ultrasonic Tissue Characterization II, M. Linzer, ed., National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C. , 1979).

IDENTIFICATION OF TISSUE PARAMETERS BY DIGITAL PROCESSING OF

REAL-TIME ULTRASONIC CLINICAL CARDIAC DATA

L. Joynt, D. Boyle, H. Rakowski, R. Popp, and W. Beaver

Center for Integrated Electronics in Medicine

and Division of Cardiology

Stanford University

Stanford, California 94305, U.S.A.

A study to assess the feasibility of obtaining diagnostical ly useful tissue characterization information by digitally processing clinical cardiac data is described.

Normal subjects, myocardial infarction, IHSS, and amyloid patients were studied. The

data acquisition system used to record data from a real-time scanner is also described.

Significant changes in the RF signals and frequency spectra as the heart moves were

noted over very short time intervals, indicating the need for a dynamic tissue characterization measure. Wide variation in the spectral characteristics of the signals from

the normal population were found. Behavior of the spectra for the MI patient data were

noted which differentiated them from the other subjects.

Key words: CI inical cardiac data; Fast Fourier Transform; digital processing; frequency

spectra; in vivo ; microprocessor-controlled data acquisition; myocardial in- farction; real-time; tissue characterization; ultrasound diagnosis.

1. Introduction

The possibility of obtaining diagnostic information by processing clinical ultrasound data from cardiac patients is explored in this paper. Lele

et al. [l]i and Yuhas et al. [2] have differentiated between normal and ischemic or infarcted heart muscle in vitro on the basis of measurements of acoustic attenuation. Extension of these methods

to clinical ultrasound examinations is complicated

by factors including cardiac motion, intervening

tissue, and the angle of incidence of the ultrasound beam to the interrogated tissue [3]. The most direct approach to exploring the effects of these difficulties in the clinical environment is to interface to an instrument in clinical use. Coupling a real-time scanner to a high-speed data acquisition system makes it possible to obtain in- formation on the dynamic state of the heart. A preliminary study on a limited number of patients

and normal subjects was done in order to assess the feasibility of deriving diagnostically useful in- formation about the type and state of cardiac tis- sue by digital processing of clinically acquired

data.

2. Data Acquisition

A. The Data Acquisition System

The design of the data collection system for

this project is based on a number of considerations.

^Figures in brackets indicate literature

references at the end of this paper.

In order to eliminate possible information loss due

to the detection process, the rf signal is digitized

for off-line computer processing. Experience with

an earlier version of the data system had shown that

large changes occur in signals recorded at 100 ms intervals. Accordingly, the current version was designed to record as continuously as feasible so that these changes could be observed in more detail.

Thus, large quantities of data must be recorded at

a very high rate. A compromise solution, trading

off the speed of semiconductor memory for the low cost of tape memory by using both high and low speed semiconductor memory to buffer the input to a magnetic tape drive, is used in the present system.

A Biomation 8100 Transient Recorder is used as the A/D converter and high speed buffer. The data is then transferred to a large slow speed buffer, con- sisting of 32 kilobytes of microcomputer memory, which stores data from a number of scan lines for subsequent recording on a magnetic tape drive having

a transfer rate of 30 kilobytes/second. This device

provides mass storage and convenient input to a com- puter for later processing.

The data acquisition performance of the system

is determined by the limitations of the digital hard- ware and by the characteristics of the scanner. When the Varian real-time sector scanner is used as the signal source, data may be acquired from any one cursor-selected scan line every 600 microseconds or from the sequence of scan lines comprising a frame

every 30 milliseconds. The rf signal is digitized

at 20 MHz so that about 100 microseconds or 7 cm of data can be stored in the transient recorder's 2048 word memory. Only those samples actually corresponding to the area of interest are transferred to the microcomputer memory buffer. The total time to re267
cord data from one scan line is under 2 milliseconds.

Thus, a substantial portion of a frame can be digitized at real-time rates. The system also includes

the option to record a sequence of lines at 30 ms intervals in order to cover a complete cardiac cycle

in one buffer. When the data buffer is filled the recording process is interrupted for a few seconds while the data is transferred to magnetic tape. Data acquisition is triggered at a pre-selected

point of the cardiac cycle. A simultaneous Polaroid

picture can be obtained. If more than one buffer is required, subsequent buffers also begin at the selected point of the cardiac cycle.

CRT

TERMINAL

ULTRASONIC SCANNER

MICRO-COMPUTER

TRANSFER AT 30 KB/s

INTERFACE AND DMA CONTROLLER

9-TRACK MAGNETIC

TAPE

TRANSFER AT 2 MB/s

SAMPLED AT 20 MB/s

BIOMATION 8100 TRANSIENT RECORDER

MAGUS SYSTEM

- CROSS-ASSEMBLER

- SIGNAL PROCESSING

- GRAPHIC OUTPUT

Fig. 1. Block diagram of the data acquisition

system. The RF signal is sampled at 20 MHz, filling up the transient recorder

buffer at 20 Megabytes/second, trans- ferred to microcomputer memory at 2 Megabytes/second, and transferred to magnetic tape at 30 kilobytes/second.

The data system has been designed to be easy to use in a clinical environment. The operator can interact with the microcomputer software system to specify the data-taking procedure. Information

about the portion of the frame to be digitized is stored in a table and written on the tape along with

the data for use in processing. Comments can be ad- ded from the operator's CRT terminal to record ad- ditional information about the tissue under study.

B. Data Acquisition Procedure

A variety of patients with different myocardial

pathologies were chosen to exhibit various degrees

of focal or diffuse replacement of normal myocardium.

Included were patients with transmural myocardial

infarction (2), idiopathic hypertrophic subaortic

stenosis (IHSS) (3), and cardiac amyloidosis (1). Three normal subjects were studied as controls. Consideration of changes in the echoes due to motion and muscle contraction during the cardiac

cycle is particularly important in a clinical study

of cardiac patients. In order to study these changes

single scan lines through the septum and posterior

wall of the left ventricle were recorded at 2 ms and

30 ms intervals. Data-taking was synchronized with

the patient's electrocardiogram to commence at end systole and end diastole. In the patients with

myocardial infarction, the area of infarction was identified as an akinetic left ventricular segment

corresponding to the region denoted by Q waves on the electrocardiogram. Data was collected from this segment and compared to normally contracting seg- ments in the same patient. In the patients with

IHSS, the region of asymmetric septal hypertrophy

could easily be identified and often has an abnormal ground-glass appearance when viewed in the real-time

image [4]. Again, comparison was made with adjacent

areas of normal myocardial appearance and thickness

and with the posterior left ventricular wall. In the patient with diffuse myocardial involvement with

cardiac amyloidosis, representative areas of interventricular septum and posterior left ventricular

free wall were studied.

3. Data Analysis

The recorded ultrasonic data was processed on an HP21MX minicomputer. Fourier transforms of each re- corded data trace were computed using the Fast Fourier Transform (FFT) algorithm. By taking the Fourier transform of a single echo, one obtains in- formation about the overlying tissue through which

the acoustic pulse has passed, while the Fourier

transform over an interval containing several echoes gives information about the spatial structure of the tissue through interference effects. Periodicities

of the spectral peaks due to constructive interference between scatterers spaced by a distance d will be spaced by Af = c/2d, where c is the acoustic

velocity. The system impulse response of the Varian scanner

is illustrated in figure 2. The limited bandwidth,

from about 1.8 to 2.9 MHz, has implications for

both kinds of tissue information sought. In vitro

studies by other workers [1-8] have shown that dif- ferences in frequency-dependent attenuation between

normal and ischemic or infarcted heart tissue are

small over this range. Only periodicities cor- responding to spatial separations larger than .75 mm will appear in this narrow bandwidth. Thus the available tissue characterization information would

be derived from observing shifts in the overall shape of the spectrum.

A primary interest was to note the effects of cardiac motion on the spectra of returned echoes.

We tried to assess changes in the spectra as a function of time in order to see possible differences in the spectra corresponding to the anatomic

differences between the normal and diseased heart

muscle. Figures 3 through 7 show examples of the data processing sequence for the long axis view of the septum at end diastole for one patient in each

of the groups studied.

4. Results

Substantial changes in the RF signals returned

from the heart and their spectra were observed over > time intervals short compared to the cardiac cycle. Data recorded at 2 ms intervals appeared to ade- quately represent the dynamically varying signal,

whereas data recorded at 30 ms changed abruptly and apparently randomly between traces. Figures 8 and

9 demonstrate this effect. A dynamic characterization of heart tissue is probably indicated since

parameter measurements derived from the frequency

268
02468 10 0 1 2 3 4 5 MICROSECONDS FREQUENCY (MHz)

Fig. 2. a) Impulse response of Varian Real-time Sector Scanner measured by recording a single

echo returned from the front side of a Lucite block in a water tank. This echo was digitized at 100 MHz. b) 1024 point FFT of impulse response.

MICROSECONDS FREQUENCY (MHz)

Fig. 3. a) Photograph of the scanner image. The rf signal was recorded along the scan line indicated by the bright cursor line on the image, b) The recorded rf trace is synchronized

to the desired point in ECG and to the picture of the scanner image. The operator chooses

the origin of the time scale. Here, echoes from the septum were recorded, c) 512 point FFT. The portion of the rf trace used in the FFT is outlined in figure b.

spectrum at one instant of time may not adequately

describe the same tissue 30 milliseconds later. The first, second, and third central moments

were used to characterize the spectrum of each tissue sample, permitting study of changes in the shape

of the spectrum. Differential frequency-dependent

attenuation, as indicated by a shift in the first

moment, for normal versus damaged myocardium was not observed. In fact, attenuation/centimeter appeared

to be constant across the frequency range involved.

It is likely that frequency dependent effects are overshadowed by the effects of imaging a tissue

volume deep within the body, due to overlying tis-

.sue, diffraction spreading of the beam, and orientation of the tissue to the ultrasound beam. There

was a wide range of normal spectral moments which

overlapped those of the diseased patients. Disappointingly, the IHSS tissue, which presents a dif- ferent appearance on the scanner image, was not distinguishable from the normal by the shape of the Fourier spectra. A comparison of normal and IHSS tissue spectra is depicted in figure 10. The myocardial infarction (MI) patients were set apart

from the others by much less fluctuation in their

spectral mean and variance curves (fig. 11). This

implies that the tissue is moving or contracting

less than normal tissue which correlates well with

the observed image on the real-time display. There

269
(c)

0 10 20 30 40 0 1 2 3 4 5 MICROSECONDS FREQUENCY (MHz)

Fig. 4. a) Photograph of scanner image, b) Recorded rf signal from selected scan line, c) 512 point FFT

AMYLOID

(b) (c)

Mil*-

10 20 30 MICROSECONDS

40 0 1 2 3 4 FREQUENCY (MHz)

Fig. 5. a) Photograph of scanner image, b) Recorded rf signal from selected scan line, c) 512 point FFT

(a)

NORMAL A

10 20 30 MICROSECONDS

40 0 12 3 4 FREQUENCY (MHz)

Fig. 6. a) Photograph of scanner image, b) Recorded rf signal from selected scan line, c) 512 point FFT

270
(a1 NORMAL

(b)

0 10 20 30 MICROSECONDS

40

Fig. 7.

2 3 FREQUENCY (MHz)

a) Photograph of sccinner image, b) Recorded rf signal from selected scan line, c) 512 point FFT.

Fig. 8.

10 20 30 MICROSECONDS

0 12 3 FREQUENCY (MHz)

a) Sequence of rf echo traces from normal septum. Signals were recorded

at 2 ms intervals. Bottom trace occurred first in time, b) FFT spectra

of signals in a.

was also a spectral shift of approximately 100 kHz

in the means of the spectra between the long axis and short axis views for the MI data. This is likely due to a more tangential view of the tissue in short axis, demonstrating the substantial effect of orientation to the ultrasound beam.

5. Conclusions

Straightforward application of methods [1,2,8]

which have differentiated between normal and ischemic or infarcted myocardium in vitro to in vivo

data derived from current clinical instruments is not likely to be successful due to the triple

whammy of limited bandwidth, overlying tissue, and cardiac motion. Spectrum skewing due to broad fre- quency interference effects and analysis of the time sequence of spectral changes may show some utility.

The substantial changes in the rf and frequency

spectra over very short time intervals lead to speculation that they reflect the state of contraction of cardiac muscle as well as changes in geometry. The data acquisition system described in this paper represents a significant advance in the state

271
2.32 MHz

2.30 MHz

2.25 MHz

Fig. 9. a) Four frequency components of the FFT of normal septum data recorded at 2 ms intervals.

Each component is plotted as a function of time, b) Same four frequency components plotted

as a function of time for data recorded at 30 ms intervals.

2.60-

2.40

2.20

MEAN

VARIANCE

42 MILLISECONDS

Fig. 10. Comparison of mean and variance of spectra of normal and IHSS spetal tissue. Moments are plotted as a function, 2 ms per point.

of the art of the digital recording of ultrasound

rf in terms of flexibility and ease of use as well

as in the kind of data it makes available.

Acknowledgment

This work was supported by the U.S. Department

of Health, Education, and Welfare under grant GM- 17940.

References

[1] Lele, P. P., Mansfield, A. B., Murphy, A. I., Namery, J., and Senapti , N., Tissue Charac- terization by Ultrasonic Frequency-Dependent

Attenuation and Scattering, in Ultrason ic Tissue Characterization , M. Linzer, ed.. National Bureau of Standards Spec. Publ . 453, pp. 167-

196 (U.S. Government Printing Office, Washing272
LONG AXIS

MYOCARDIAL INFARCTION A

SHORT AXIS

28 42 MILLISECONDS

LONG AXIS

MYOCARDIAL INFARCTION B

SHORT AXIS

Fig. 11. Means of the spectra of data from two infarcted spetums. Data is plotted

at 2 millisecond/point for the long and short axis views for both patients.

ton, D.C., 1976). [6]

Yuhas, D. E., Mimb, J. N., Miller, J. G., Wiess,

A. N. , and Sobel , B. E., Changes in Ultrasonic

Attenuation Indicative of Regional Myocardial [7] Infarction in Ultrasound in Medicine , D. White,

ed. , Vol. 3 (Plenum Press, New York, 1977).

[8] Chivers, R. C. and Hill, C. R. , A spectral ap- proach to ultrasonic scattering from human tissue: methods, objective and backscatteri ng measurements, Phys. Med. Biol . 20 (5), 799-815

(1975). [9]

Rossen, R. M. , Goodman, D. J., Ingam, R. E.,

and Popp, R. L., Echocardiographi c criteria in the diagnosis of idiopathic hypertrophic sub- aortic stenosis, Circulation 50, 747-751 (Oct.

1974). [10]

Cooley, J. W. and Tukey, J. W., An algorithm

for the machine calculation of complex Fourier

series. Math. Computation 19, 297-301 (1965).

Oppenheim, A. V. and Schaefer, R. V., Digital

Signal Processing (Prentice-Hall, Inc., Englewood Cliffs, N. J., 1975).

Crawford, F., Waves (McGraw-Hill, New York,

1968)

.

Namery, J. and Lele, P. P., Ultrasonic Detection of Myocardial Infarction in Dog, in Proceedings of 1974 Ultrasonic Symposium, p. 491 (IEEE Cat. No. 72 CHO 7088 SU, 1974).

Mohammed, A. and Smith, R. G., Data Windowing

in Spectral Analysis, DREA Report 75/2, De- fense Research Establishment Atlantic, Dart- mouth, N. S., Research and Development Branch,

Department of National Defense, Canada.

Fields, S. and Dunn, F., Correlation of echo- graphic visualizability of tissue with bio- logical composition and physiological state,

J. Acoust. Soc. Am . 54, 809-811 (1973).

273
i'f

fl Ip

il

pi

fi

ii

tt

fl

Ii

ii

SI

II
Reprinted from Ultrasonic Tissue Characterization II, M. Linzer, ed. , National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C., 1979).

DYNAMIC AUTOCORRELATION ANALYSIS OF A-SCANS IN VIVO

J. C. Gore,^ S. Leeman,^ C. Metreweli,^ N. J. Plessner,^

and K. Willsoni

^Department of Medical Physics

2 Department of Diagnostic Radiology

Royal Postgraduate Medical School Hammersmith Hospital, London, England

A realistic tissue model has been analysed to indicate the information that may be derived from autocorrelation studies of in vivo A-scan echograms, as well as to show

some of the limitations of such techniques. Although many of these difficulties are not easily overcome when considering single, or even averaged, realisations of the autocorrelation function (ACF), an analysis of the time course of the ACF is less subject to such objections.

Several potentially useful clinical applications of such temporal changes are being

investigated. These include measurements of echoes from within heart muscle throughout the cardiac cycle as a possible indicator of cardiac disease; similar variations

in echoes from the stomach wall during gastric emptying are demonstrated, and a relationship to contractile state is postulated.

Results are also presented which indicate that the perfusion of tissues with blood may be assessed by this technique, and, on a different physiological time scale, changes

in the placenta throughout pregnancy have been investigated. The technique is being

extended to the study of the response of malignant tumours to treatment.

Key words: A-scan; correlation analysis; temporal changes.

1. Introduction

Tissue characterisation may be defined as the attempt to establish what quantitative parameters,

other than range information, may be extracted

from ultrasound probing of human tissue; the quantities derived should reflect intrinsic tissue

properties and in particular its physiological

state, be useful diagnostically, or for pre- and post-operative assessment, or for monitoring

response to treatment. The attempt is not necessarily restricted to an ultrasound technique, but

this modality is particularly attractive, not only

for the usual reasons, but also because it provides the facility for receiving and analysing a signal from a reasonably localised region of tissue, as well as providing images to enable that region to be accurately placed. Clearly, only

physical properties of tissue, or their possible

change with time, are amenable to detection--often

micro-structural features are of interest, but

1 other possibilites ( e.g . , temperature measurement)

are certainly not excluded. Isolated echo structure may be probed in tissue

' characterisation analyses [l-3]3, even though the

extracting of purely physical, as opposed to geo- metrical, data is more complicated than may appear

at first sight [3]. Here we will restrict our- selves, as have many others, to the scattered lowlevel signals from a region of tissue, and perform

what may be termed tissue characterisation by "echo ensemble" analysis. The extent to which

these two methods are complementary is not known

at present, but it may be noted that both are im- plicit in qualitative attempts to extract diagnostically useful data from grey-scale images.

2. Some Theoretical Ideas

A conceptual basis for the empirical approach

may be laid from theoretical considerations, just

as the impedance mismatch concept simplifies the interpretation of much of conventional ultrasound

scanning.

The tissue model adopted here comprises an in-

^Figures in brackets indicate literature

references at the end of this paper.

275
homogeneous medium, with local density and com- pressibility fluctuations generating the ultrasound scattering. In this context, the aim of tissue characterisation by echo ensemble analysis is to uncover the three-dimensional spatial, and even temporal, distribution of these fluctuations; while

the hope of the technique is that all, or preferably some, of the information is sufficient to establish unambiguously the state of the tissue.

A convenient starting point is the wave equation for ultrasound propagation in a medium with

stationary inhomogeneities of the type described

above [4].

^^P-E^0=H^T(r)0+V,[p(r)Vp] (1)

where p{r_,t) is the acoustic pressure at location

£ and time t; v{r) is the density fluctuation,

y = (p - Pq)/p

with po the mean, and p(r) the exact local density;

y(r) is the compressibility fluctuation,

Y = (k - K^)/K^

with Kp the mean, and K{rJ the exact local com- press ibi 1 ity.

Cq is the mean velocity,

'I - (Vo)-^ •

The right-hand side of eq. (1) is conventionally called the source term, since it is easily de- monstrated [5] to be a "source" of waves, and it describes the interaction of the medium with the ultrasound field. The source term depends on both

the fluctuations in the medium and the local, in- stantaneous value of the pressure wave, as it must

do if it is to describe a scattering situation.

The tissue model described by eq. (1) may be shown

[5], to contain that of Waag and Lerner [6] as a special case. Since the scattering is known to be weak, both y and y may be taken to be small quantities. Any scattering calculation requires the initial conditions to be clearly specified, and we have adopted an initial pul se pin i ncident

along the Z-direction, of the form:

p^^(r,t) = a(z - CQt)b(h)exp|i(k^z - co^t)} (2)

where a is the (axial) pulse shape, b is the beam

profile, h is the spatial coordinate transverse to

Z, ko is the carrier wave vector amplitude, and

'"0 ~ Coko- Eq. (2) is a good approximation to pulses from diagnostic machines over much of the range of interest. For weak scattering, and for weakly focused in- cident fields, the far-field final result [7] shows

that the back-scattered pressure amplitude is generated by the pulse-smoothed density/compressibility fluctuations in the medium. The power spectrum, of the backscattered echoes (with boundary effects neglected), is given by:

|p^(.)|....||A(^.ko)p |r(|)p (3)

where A is the Fourier transform of the axial pulse shape, u'* represents a "Rayleigh" factor,

and the effect of the medium is contained only in the structure factor.

oo 211

<V> = f f dehb(h)y(h,e,z)

0 0

and similarly for r . 6 is the angle variable in the cylindrical polar coordinates (h,e,Z) used in the calculation. The Z-integration may be extended to infinite limits, since the fluctuations are presumed to vanish outside the (finite) scattering

volume. The structure factor r is the spatial

frequency spectrum of the beam-profile smoothed

tissue structure, and it is seen that, for the backscattering case, the density and compressibility fluctuations contribute equally, but with different phase. At other scattering angles the two types of fluctuations will contribute with differently varying magnitudes, and they may be regarded as two different types of scattering element:

the one (compressibility) scattering as an acoustic monopole, and the other (density) behaving as an acoustic dipole. This behaviour may be deduced

from the form of the source term in eq. (1), or more directly, from straightforward physical argu- ments [5]. Since the relative importance of the

two types of scattering element varies with direction, different observers employing a fixed-angle

scattering technique may obtain apparently con- flicting results from the same tissue. In general,

at least six independent one-dimensional experimental functions would have to be measured in order to reconstruct both y and u from the data,

and since this would seem to be impracticable, it

is emphasized that, for the characterization of anisotropic tissues by fewer independent functions, it is essential to specify internal tis- sue landmarks with respect to which scanning

planes and directions may be fixed. If not, in- tercomparison of results between different workers, and the repeatability of a single investigator's findings, cannot be established.

Quite apart from difficulties inherent in trying to quantitate the effect of overlying tissues and interfaces, the above calculation shows

that pulse shape, beam profile, and carrier fre- quency are important quantities which fundamentally influence the scattered pressure power spectrum, and which must be specified or, better, de- convoluted from the data. Moreover, in regions

where the incident pulse is sharply focused

(|vp^p| large), scattering from the density fluc- tuations becomes more prominent; this may well prescribe a suitable technique for mapping the density and compressibility scattering elements

individually, if so desired. In addition, the measured backscattering is further modified by the transfer properties of the receiver [8], but

276
all these "system" artifacts are measurable, and should be prescribed, if not specifically allowed

for.Pulse smoothing implies a certain loss of fine

detail: scattering experiments do not indicate

the tissue micro-structure (<<A) as such. It is quite clear from the above that measured pressure

power spectra from the same tissue may differ with

different transducer apertures and excitations,

but it is also worth emphasizing that, in principle, the same backscattered power spectrum may

be seen from di ff erent tissues, with different

density and compressibility fluctuations, provided that Ty-ry remains the same. This merely underlines the fact that, even for isotropic media, a single backscattering experiment is in general in- sufficient to characterize tissue unambiguously.

Fortunately, in practice, the situation may be less complicated as there is some indication that,

for most tissues, only the compressibility ( i.e ., elasticity) fluctuations are of importance for

the production of echoes [9].

pen (SAC Graf Pen), interfaced to a HP 2100A com- puter via a Tektronix 4010 visual display unit. With this arrangement effective sampling rates of

up to 15 MHz are achieved, although at present it

is more usual to sample echoes from a region

'V 2 cm in extent at a rate of Ih MHz, consistent

with providing estimates of the ACF at lag intervals corresponding to 100 pm of tissue. The discrete, normalised ACF, cj, is estimated

from N echo samples. Pi, using the unbiased esti- mator [10],

r=— Vp-P P -P

J N 1 i-,M i+j i+j,M

where

1 i+M ^•,M = (2M + 1) .^^ Pi

3. Method

As indicated in eq. (3), by measuring the power

spectrum of echoes, the structure factor, r, may

in principle be determined over a limited band of spatial frequencies to within an accuracy set only

by noise and the uncertainty in knowledge of |A|.

However, we have chosen to explore the use of the time-domain autocorrelation function (ACF) of echo amplitudes; as well as being easier to cal- culate, the ACF contains all the information in- cluded in the power spectrum, and although the errors inherent in its estimation differ from

those in power spectrum calculations, it seems

likely that on-line ACF measurement may be at least as suitable for "in vivo" tissue characterization in real time as Fourier methods. The de- sired autocorrelation function is given by

c(t) = / p(t)p(t + T)dt

where p(t) = the backscattered acoustic pressure

amplitude at time t.

From eq. (3), it can be shown that

c(t) - 6(t)*?(t)

where * denotes convolu^tion,_

6(t) = the ACF of <y> - <y> and is an indicator of tissue structure.

5(t) = the ACF of the second derivative of the impulse response of the pulse-echo sys- tem [8].

The convolution with the system function, limits

the information available unless steps are taken to remove its influence, but such further processing

has not yet been attempted by us. The equipment used in these studies is a Nuclear

Enterprises NE 4102 Diasonograph , operated with

weakly focused transducers centred on 2.5 MHz, with

total system bandwidth approximately W MHz. Signals from the A-scan receiver are at present re- corded photographically from an oscilloscope, and

the echo envelope is then digitised with a sonic

is the running mean of the echo amplitude. The moving average is calculated over a distance that

is sufficiently large not to influence the fine structure of the ACF estimate but which filters

spurious low frequency fluctuations and strengthens

stationari ty. Such detrending is performed typically over intervals of v 1 cm.

4. Data Analysis

In general, the entire ACF must be considered

when characterizing a single train of echoes, but

one or more particular features of each ACF may

be extracted in order to summarise quantitatively

any given set of echo samples. For example, the positions (and to a lesser extent the shapes) of peaks within the ACF indicate distances over which

there exists structural coherence; prominent and regular peaks indicate a regular arrangement of scattering sites. The mean number of crossings, moments of the function, or curve fitting tech- niques using small numbers of parameters, may each

be used to describe, concisely, essential details

of an estimated ACF, but the method of feature ex- traction chosen will depend on the particular appl ication.

In order to overcome some of the objections

that have been indicated above against the use of single realisations of echo characteristics in one dimension, the analysis has been restricted

to situations where the tissue investigated has been found to be isotropic, or where only the changes with time of echo characteristics are deemed to be clinically useful. In this way, by

following the time course of echo features, each tissue acts as its own internal standard and less reliance need be placed on the values of individual, single measurements. Time-plots of echo features such as those described above depict

changes in scattering structure, whilst polar

phase diagrams are useful when the change is periodic. Cross correlation of the ACFs realized

at different times are calculated to yield informat'lon about changes, relative to a chosen ref- erence time, and examples are given below.

In analysing echoes in this fashion, the ACF features to be emphasized have often to be chosen

arbitrarily, and caution has to be exercised when attaching significance to any particular one.

277
There are some reliable guidelines that may be derived bv standard techniques to suggest which

ACF values may be regarded as spurious, but a final decision as to the significance (or otherwise) of any derived result can be made only on the basis of clinical, in vivo investigations.

However, as an interim indicator of our awareness of artifactual correlations, the results

given below are marked with the 95 percent con- fidence limits (a) for an autocorrelation function generated with N data points from a random

process [11],

5. Results

There are several clinical problems which may

be explored by using temporal characteristics of

the ACFs of echoes to indicate changes within tis- sues and three classes may be distinguished.

First, there are cyclic events in which echo

characteristics alter in synchronism with some physiologically significant, repetitive process,

such as respiration, or with the cardiac cycle,

whose phase is easily monitored on the electrocardiograph (ECG). It is, for example, reasonable

to suppose that myocardial activity will be associated with a redistribution of scattering centres

in the tissue, since it necessarily involves

changes in both its elastic state and density. The time course of scattered echoes from within

the left ventricular posterior wall is easily fol- lowed in the conventional mitral valve echogram

scanning direction. Figure 1 depicts the ACFs measured from a normal heart in end-systole and end-diastole, showing typical changes from one phase to the other. The interpretation of this in

MM

Fig. 1. The ACFs of echoes from the left ventricular posterior wall of a normal heart, measured in end-systole (S) and end-diastole

(D).

terms of alterations in muscle fibre dimensions or elastic state remains to be confirmed, whilst the degree of change in disease remains to be established, but the possibility clearly exists of mea- suring in vivo characteristics which may be related to myocardial contractility.

The flow of blood in the systemic circulation

is also directly coupled with cardiac events. Following the notion that the perfusion of cer- tain organs with blood proceeds in synchronism

with the heart's action, the possibility of identifying poorly perfused transplanted kidneys is under investigation. Figure 2 indicates how echoes from the anterior region of the upper pole

of a viable kidney, investigated some months after

successful transplantation, change with time. The obvious changes between phases, and the reversion

in the subsequent cycle, is suggestive of a cyclic,

cardiac-synchronised structural reorganisation

within the kidney. This approach to the quantitation of echo characteristics may also be applicable to other organs, such as the liver and placenta, and possibly to tumours.

Fig. 2. Characterisation of echoes from cortex of transplanted kidney at different times. Three autocorrelations were measured, at (cardiac) end-diastole, end-systole, and the subsequent end-diastole. Curve A is the cross-correlation of the first diastolic ACF with itself, curve B is the cross- correlation of the first diastolic and systolic ACFs, whilst curve C is the cross- correlation of the two diastolic functions,

and shows a reversion back to the original

state in synchronism with the heart.

A different cyclic process with less regular

period is the muscular activity associated with

gastric emptying. The contraction of the stomach

wall in normal digestion (which may be monitored

over cycles with periods of approximately 20 seconds with conventional M- and B-scan tech- niques) [12] produces changes in echo charac- teristics not dissimilar to those associated with

myocardial contraction, and this lends support to our interpretation of the origin of heart wall echo changes. Thus, a similar model, viz . , con- traction of muscle elements causing changes to their acoustic scattering properties, may be em- ployed to interpret the results of both cardiac

and gastric measurements. ACFs of echoes from

the anterior stomach wall are shown in figure 3, and cross correlations of the ACFs from different

phases in figure 4: the position of the first

principal minimum is plotted as a rotating phasor

in figure 5.

278
Fig. 3. The ACFs of echoes from the anterior

stomach wall, contracted (C) and relaxed

(R).

Fig. 5. Phasor diagram showing locus of the position of the first minimum of the function

produced by cross-correlating the ACFs of echoes from stomach wall measured at different times (as in fig. 5). Total cycle

time 20 seconds. The radius of the circle corresponds to a correlation lag of 4.8 mm.

.5- MM

Fig. 4. Characteristics of echoes from stomach

wall at different times. The ACF at time

0 is cross-correlated with itself (A), with

the ACF at a time 4 seconds later when

the stomach is contracted (B), and with

the ACF at a time 8 seconds after con- traction, when the muscle has again re- laxed (C). These events were chosen by

reference to the stomach M-scan. Note

the general shape of the cross-correlation

function does not change but the first

minimum moves with contraction.

A second class of time change being investigated is the alteration in scattering characteristics

of tissues with age or maturity, and of particular

interest are changes in the placenta throughout

pregnancy. Ageing placentas present different grey

scale B-scan appearances: cross-correlation of ACFs obtained at different stages of normal pregnancy

are shown in figure 6. This technique may also

reveal differences between normal and insufficient

placentas of the same maturity.

A third class of application is the monitoring

of structural changes in tumours during and after

treatment. Such changes have already been observed in B-scan images of irradiated malignant tumours

and in vivo ultrasonic tissue characterization

using the techniques outlined above may provide a clinically useful method of assessing tumour kinetics [13].

.5-

1 ' \

\ f\ \

\

i\ \\ .7 \ /

, V 2/ \. /6

V // \ /

V

' MM

\* / / V R 7

1

1 '/ \

C/

_i—/ , \ -usy V'v

\ / 2 \ / 4 •'.^ / \ ' 1/ \ 1 ^<k»'' \

Fig. 6. Characteristics of echoes from placenta

at different stages of pregnancy. ACFs were obtained at 15, 24, 38 and 41 weeks,

and each of these ACFs was cross-correlated with the 15 week ACF to produce curves

A, B, C and D respectively. There appears

to be little change between 15 and 24 weeks, or between 38 and 41 weeks, whereas there is a clear change between 24 and

38 weeks.

279
6. Conclusions

The use of single autocorrelation functions to characterize complex, three-dimensional scattering

media may be severely limited because different

tissues may realise similar results. Many of the objections raised against the use of one-dimensional techniques, however, are overcome if the time course of events is followed and only changes

in echo characteristics are regarded as significant. Whilst the ACF sunsnarises the information

contained in a single train of echoes, the cross correlation of sequentially produced ACFs sum- marises dynamic features of scattering. New diagnostic information may possibly be derived from

a study of cyclic changes in gastric and cardiac

muscle, and in other organs blood perfusion may

be assessed. Changes in the nature of tissues

with age or treatment may have important significance which, as yet, we are unable to evaluate.

A limited number of patients and volunteers

have so far been investigated with this "dynamic"

technique, and it is impossible to unequivocally

claim success in any particular application; but there is equally no cause to reject the original

concept that echo ACFs reveal changes in the physiological state of tissues. The influence of factors such as tissue movement or anisotropy and the relative merits of different transducers and methods of signal processing will have to be carefully evaluated, and the optimal choice of echo ACF features to be extracted remains uncertain.

Despite the problems, there is every reason to hope that dynamic tissue characterization is an appropriate path to obtaining information of genuine clinical utility.

Acknowledgements

We gratefully acknowledge Mr. George Hooker's

help with the analysis of data, and thank Dr.

E. W. Emery for his useful discussions and com^

ments. S. L. is in receipt of a Wellcome Fellowship.

References

[1] Lizzi, F., Katz, L., St. Louis, L., and Coleman, D. J., Applications of Spectral

Analysis in Medical Ultrasonography,

Ultrasonics , 77-80, March 1976.

[2] Trier, H. G., Decker, D., Reuter, R.

,

Epple, E., Lepper, R. D., and Nagel , M.

,

Frequency-modulated Portions of the Timeamplitude Ultrasonogram of Models, in Proceedings of the Second European Congress

on Ultrasonics in Medicine , pp. 121-128

(Excerpta Medica, Amsterdam-Oxford, 1975).

[3] Gore, J. C. and Leeman, S., Echo structure

in medical ultrasonic pulse-echo scanning,

Phys. Med. Biol . 22^ (3), 431-443 (1977).

[4] Morse, P. M. and Ingard, K. N., Theoretical

Acoustics (McGraw-Hill, New York, 1968).

[5] Leeman, S. , Simple Physical Ideas on Ultrasound Pulse Scattering from Tissue, R.P.M.S.

Medical Physics Reports, US76/3 (1976).

(Available by request only)

[6] Waag, R. C. and Lerner, R. M., in Ultrasonics Symposium Proceedings , I . E . E . E

.

Cat. 73, CHO 807-850.

[7] Gore, J. C. and Leeman, S., Ultrasonic back- scattering from human tissue: A realistic

model, Phys. Med. Biol . 22 (2), 317-326

(1977).

[8] Gore, J. C. and Leeman, S., New Criteria

for the Assessment of the Resolution of Ultrasonic Scanners, in Ultrasonics in Medicine , E. Kazner, M. de Vlieger, H. R. Muller, and V. R. McCready, eds., pp. 197-

203 (Excerpta Medica, Amsterdam, 1975).

[9] Fields, S. and Dunn, F. , J. Acoust. Soc . Am. 54, 809-813 (1973).

[10] Jenkins, G. M. and Watts, D. G., Spectral

Analysis and its Applications (Holden-Day,

San Francisco, 1968).

[11] Chatfield, C. , The Analysis of Time Series : Theory and Practice , Chap. 4 (Chapman and Hall, London, 19/b).

[12] Bateman, D. N., Leeman, S., Metreweli, C,

and Willson, K. , A noninvasive technique

for gastric motility measurement, Brit. J . Radiol . 50, 526-527 (1977).

[13] Leeman, S., Badcock, P. C, Gore, J. C,

Plessner, N. J., and Willson, K., Ultrasonic Backscattering Assessment of Tumour Response to Treatment, presented to Tumour Ultrasound 77, International Conference,

London, 1977. (Copy available by request.)

280
Reprinted from Ultrasonic Tissue Characterization II, M. Linzer , ed.. National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C., 1979).

COMPUTER SPECTRAL ANALYSIS OF ULTRASONIC A MODE ECHOES

D. E. Robinson

Ultrasonics Institute

Sydney, Australia

Tissue attenuation as a function of frequency measured by the effect on the power density spectrum of the echo off glass shadowed by the tissue sample is shown to give results comparable to those published previously. A method of measuring attenuation

within tissue by comparison of the scattered echoes from shallow and deep scatterers

is investigated and shown to have limitations. An assessment of properties of the scatterers from investigation of the spectral properties of the echoes from a scattering region is suggested.

Key words: Acoustic; computer processing; digital acquisition; digital signal

processing; pulse-echo techniques; spectrum analysis; ultrasonics.

1. Introduction

At present the bulk of tissue characterisation

by ultrasound in clinical practice is done by

qualitative examination of the grey scale B Mode

echogram. The current work is directed to deriving quantitative characterisation data by spectral analysis of 180° backscattered echoes, or ultrasonic A Mode, following the approach of

Lizzi [l]i.

2. Measuring Equipment

The transducer beam pattern requires to be narrow to give good spatial resolution and with a well behaved spectrum to avoid complications in spectral analysis techniques [2]. This is achieved in the focal zone of a focussed transducer of aperture 65 mm and curvature 35 cm and usable fre- quency range from 1.5 to 4 MHz. The 20 dB echo beamwidth at the focus is 6.7 mm. The receiver amplifier gain is variable in 1 dB steps allowing an input dynamic range of 100 dB without overload. Receiver gain variation is used instead of transmitter power control as it is found

that due to non-linearities in the transmitter, the transducer or the medium, significant changes in echo wave shape occur with changes in transmitter

power. The signals are digitised at 10 MHz sam- pling rate using an 8 bit Biomation 8100 waveform

recorder interfaced to an Interdata Model 85 computer. The computer and an interactive signal

processing program have been described elsewhere

[3].The spectrum used here is the square magnitude

of the Discrete Fourier Transform (DFT) of the echo signal or Power Density Spectrum. All spectra

shown in this paper have been interpolated as de- scribed by Rabiner et al. [4] by extending the set

^Figures in brackets indicate literature

references at the end of this paper.

of 128 or 256 recorded time samples with zero- valued samples up to a total signal length of 1024 before computing the DFT. Comparisons between

spectra are made by calculating the logarithm of the ratio of the spectra (log ratio) and observing

the ordinate at 2.5 MHz in dB and the slope in dB/MHz. The log ratio for point and plane target

echoes remain within 3 dB and the slope within

2 dB/MHz for distances from the transducer focus

of ± 30 mm. A B-Mode display of the examined tissue is pro- vided for A mode beam position selection and guidance. An example of input data and corresponding

B mode display is shown in figure 1.

3. Experimental Techniques

First the echo from a thick glass block at the focus with no intervening tissue is recorded, and regarded as the impulse response of the system. The tissue specimen is then placed in a polyethylene bag in front of the glass block and echoes from a series of 30 adjacent beam positions at 3 mm

intervals were recorded from three locations; from

the glass block behind the tissue and from shallow

and deep within the examined tissue. In each case

the transducer was moved so that the echoes were

recorded from the focal area of the transducer

beam. In the case of the scattered echoes, a region was selected which did not have large dis- crete echoes on the B Mode scan.

4. Signal Processing

When measuring the spectrum of a statistical signal, some form of averaging is required to obtain a smooth and stable spectral estimate [5]. This can

be done in the spatial domain by translating the beam

axis as described by Lizzi [1] and adding the spectra

corresponding to a number of adjacent lines of sight

to obtain an average spectrum. This has the effect

of reducing the amplitude of ripples in the spectrum.

281
Fig. 1. B-Mode echogram showing tissue sample

in front of glass block. The two lines indicate the area used for A Mode acquisition. The complete A mode

signal and the part of the signal near

the focal region are also shown.

It should be noted that the "fine structure" in the spectrum of individual echo signals may be a function, not of the statistical nature of the sample,

nor of the local tissue structure, but simply of the length of the time window. For instance, given a signal x(t) with transform X(f) and spectrum X(F)2

the sum of two identical shifted signals x(t) + x(t - t) has a spectrum 2X(f)2 (1 + cos wt). The

factor (1 + cos wt) gives rise to "wiggles" in the measured spectrum which are not directly related to local tissue "structure" but are merely phase ef- fects between widely spaced echoes. Figure 2a and

2b show the spectra for a single echo and two identical echoes separated by 5 mm. This effect is re- duced by windowing in the autocorrelation domain, or

lag windowing. The autocorrelation function is the Inverse Fourier Transform of the Power Density Spectrum. The Autocorrelation functions of the single

echo and two identical echoes spaced at 5 mm (66

sample intervals) are shown in figure 2c and 2d. Also shown in figure 2d is a Hamming window in the Autocorrelation (lag) domain suitable for removing

the effect of widely spaced echoes. Multiplication

by the window function has the effect of removing

contributions to the Autocorrelation function of

lags greater than 32 sample intervals (2.5 mm) and leaving only the contributions from closely spaced

echoes. The smoothed Power Density Spectrum ob- tained by re-transforming the weighted Autocorrelation function into the frequency domain is shown in figure 2e. The effect of this procedure on tissue echoes is shown in figure 3 where the original time

sample of scattered echo data is windowed with a Hamming window of length 128 (corresponding to 10 mm

of tissue). The lag windows are of length 64, 32 and 16 samples increments corresponding to correlation lengths of 5, 2.5 and 1.25 mm and thus limiting the effect on the spectrum to structures of these sizes.

In the analysis of the echoes off glass no time

windowing or spectral smoothing is necessary since we are dealing with only deterministic single echo waveforms and not statistical signals. The power density spectra of the echo off glass with and without shadowing by the tissue were calculated, and the

log ratio formed. A typical set of results is shown

in figure 4. The log ratio is a measure of the at- tenuation due to the tissue as a function of fre- quency. The values are only significant for fre- quencies contained in the original power density

spectrum of the unshadowed glass echo. A line of best fit was computed on a least total weighted

squared error basis with the weighting function being the original power density spectrum values for the echo off glass at the focus. The parameters of the line y = ax + b where y is the best fit to the log ratio value and x the fre- quency value are given by:

a

= ? W. ? x. y. W. - ? x. W. ? y. W.

1 11 1-^11 1 11111

and b

=

? W. ^ x? W.

? W. ^ x. W. ? w.

1 1 ? w.

1 1

282
Fig. 2. a) Power density spectrum of a single

echo off glass; b) spectrum of two echoes separated by .5 mm; c) auto- correlation function corresponding to spectrum in a; d) autocorrelation

function of spectrum shown in b and

64 point Hamming lag window;

e) smoothed spectrum obtained from

the lag windowed autocorrelation

function shown in d.

where the x., y. and W. are the values of the fre- quency, logVatIo and vveighting function for the successive frequency samples.

For echoes from scatterers within the tissue

the echo signal was windowed using a time window

of length 128 samples or 10 mm and the spectrum

was smoothed by a lag window of 64 lags corresponding to 5 mm. The log ratio between deep and shallow echo spectra was formed and the weighted best

fit line calculated as before. A typical result is shown in figure 5.

5. Results

Being initial experiments readily available animal material was used. The material was skeletal beef muscle along and across the fibre direction

and calf liver. The results are shown in table 1. The log ratio curve, indicating tissue attenuation was approximately linear within the pass band

for all tissue samples using the shadowed glass ap- proach. For this reason more confidence is placed

in the determination of attenuation slope by this

283
Fig. 3. Effect of lag windowing on echo spectrum. A single line of data was windowed

with a 1 cm Hamming window and the spectrum a) smoothed with a Hamming lag

window of b) 5 mm, c) 2.5 mm and d) 1.25 mm.

Table 1. Tissue attenuation determined by the shadowed glass

method and by the scattered echo comparison method.

Tissue Quoted atten. Shadowed glass Scattered

(Wells [6]) Slope Atten. at 2.5 MHz Slope Atten. at 2.5 MHz dB/cm MHz dB/cm MHz dB/cm dB/cm MHz dB/cm

Muscle along

f i bres 1.3 1.5 4 .9 1.2 5.8

Muscle across

f i bres 3.3 (1) .65 1.5 .28 2.8

(2) .78 1.8 .15 1.7

Li ver .94 (1) .82 2.2 .72 3.0

(2) .73 3.1 .53 4.2

284
Fig. 4. Results of shadowed glass measurement on muscle across fibre direction showing

a) unshadowed and b) shadowed spectra, c) ratio of spectra and d) log ratio

with weighted best fit line superimposed. Note that the ripple amplitude is small in the linear region.

method. The values attenuation versus frequency

in dB/cm MHz were in reasonable agreement with pre- viously published values for the muscle along the fibres and for liver. The values for muscle across

the fibres were similar to the other values but not

in agreement with Wells [6]. The log ratio curves

for the scattered echo measurements all showed significant ripples, indicating that some phasing

effects still remain. The values for liver and muscle along the fibres agreed reasonably well with

the shadowed glass method, but the muscle along

fibres gave widely different results.

6. Discussion

It is obvious that further work is needed before

the scattered echo comparison method will be useful

for attenuation determination. The shadowed glass

method appears to give repeatable results but is not suitable for clinical examinations.

The current approach in scattered echo analysis

is to average in the power spectral domain with the aim of reducing the ripples in the spectrum to ob- tain a smooth and stable spectral estimate. It appears that an alternative approach is to average

in another domain to obtain a stable estimate of the underlying spectral ripple, which is a measure

of the "structure" of the echo signal. Two obvious

candidates are the Autocorrelation and the cepstral

domains. This structure can be postulated from the same model of distributed discrete point scatterers

that is used to justify the single frequency scat- tering versus angle approach to tissue characterisation .

References

[1] Lizzi, F., Katz, L. , St. Louis, L., and Coleman, D. J., Applications of spectral analysis

in medical ultrasonography. Ultrasoni cs 14, 77- 80 (1976).

[2] Robinson, D. E. and Williams, B. G., Computer

Analysis of Ultrasonic Pulse Echo Signals, in Ultrasound in Medicine and Biology , D. White

and R. E. Brown, eds., p. 1443 (Plenum Press, New York 1977).

285
6db

j M 1

* m

Fig. 5. Results of scattered measurement showing a) shallow and b) deep echo spectra,

c) the ratio and d) log ratio with best fit line superimposed. Note the large ripple content of the log ratio.

1 n

[3] Robinson, D. E., Williams, B. G., and Horn,

P. R., Digital acquisition and interactive

processing of ultrasonic echoes. Ultrasound

Med. S Biol . 2, 199-212 (1976).

[4] Rabiner, L. R. , Gold, B., and McGonegal, C. A. An Approach to the Approximation Problem for Nonrecursive Digital Filters, in IEEE Trans . Audio Electroacoustics , AV-IS, 83-106 ( 1970).

[5]

[6]

Jenkins, G. M. and Watts, D. G., Spectral

Analysis and its Application, p. 209 (HolderDay 1968).

Wells, P. N. T.

,

sonic Diagnosis.

Physical Principles of Ultra- Academy Press 1969.

286
Reprinted from Ultrasonic Tissue Characterization II, M. Linzer, ed., National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C., 1979).

CEPSTRAL SIGNAL PROCESSING FOR TISSUE SIGNATURE ANALYSIS

J. Eraser and G. S. Kino

Stanford University

Stanford, California 94305, U.S.A.

J. Birnholz

Harvard Medical School Boston, Massachusetts 02115, U.S.A.

The reflected signal received by an ultrasonic transducer is modeled as a convolution of a transducer response with a reflection function for the target region.

Cepstral analysis translates that signal into a domain where those components interact additively rather than through convolution and where separation can be accomplished with simple bandpass filtering operations. The cepstral transform of the pulse echo signal also provides direct access to any periodic behavior Ci' reflectors arising from their spacing. As an example of these capabilities, the technique is used experimentally to describe the characteristic spacing of macrostructural reflecting

elements in the pig liver in vitro and to determine the frequency dependent attenuation behavior of normal human liver in vivo.

Keywords: Attenuation; B-scan; cepstrum; computer; convolution; de-convolution;

liver; power spectrum; signal processing; tissue characterization;

tissue parameters; ultrasound.

1. Introduction

We describe in this paper preliminary experiments with new types of non-linear signal processing used for eliminating certain types of signal

distortion in conventional acoustic imaging systems which preclude unambiguous identification of specific tissue features.

An acoustic propagation path through a tissue

region can be treated as a one-dimensional array

of reflectors. While each individual reflector

may be expected to replicate the time characteristics of a self convolved transducer impulse response (assuming an impulsive excitation), that pulse form is altered or distorted during propagation by the frequency dependent attenuation

processes of the medium intervening between re- flector and transducer. Previous studies have in- dicated that tissue specific information is de- rived from both attenuation properties of the region, as well as the distribution and backscatter features of the individual reflectors [1]^.

Therefore, an effective signal processing scheme must provide a means of eliminating the trans- ducer response and separating frequency dependent

attenuation effects from target signal components.

Our approach has been to take advantage of certain

properties of the cepstrum, or Fourier transform,

of the signal log power spectrum [2]. The rationale for this choice derives from previous uses in

^Figures in brackets indicate literature

references at the end of this paper.

comparable signal processing tasks: (1) homo- morphic deconvol ution of speech and music waveforms for improved recording fidelity [3]; (2) dereverberation enhancement of seismic data [4]; and (3) recognition and characterization of flaw

configuration in nondestructive testing [5]. This method has not been applied to medical diagnostic ultrasound previously.

2. Analysis of the Return Echoes

We consider first what occurs when a signal is incident on body tissue. We will mainly be in- terested in the situation in which we observe a reflected signal with the same transducer used to iTluminate the tissue. Techniques for looking at off axis reflections can, in principle, provide a great deal more information. But, in practice,

they are extremely difficult to employ without the

use of arrays of transducers to carry out repeatable measurements of this kind. Even with the use

of arrays of transducers, because of the distortions along the body path to an organ of interest,

the problems are very severe in terms of repeatability. In that case, it is probably better to concentrate on the development of imaging systems

first, then process the images in some detail.

Thus, the method described here is entirely devoted to the use of a single transducer operating in

a reflection mode. The signal received by a reflection mode system

can be considered to arise from a one-dimensional

reflection function R of distance z along the beam

path R(z). In the far field of a plane transducer.

287
or the focal zone of a focused transducer, the phase fronts are roughly planar and normal to the beam. Under these conditions, it can be shown by

perturbation theory that R(z) is the weighted sum across the beam of the component along the beam

of the gradient of the acoustic impedance of the tissue. That is, if the beam pattern is P(r), and

the impedance is Z(r,z) which varies slightly

around an average value of Zg,

R(z) - y 2TTrdrP{r)z • v|z(r,z)f . (D

° 0

We wish to work in the time domain, using R(t),

where, with V the acoustic velocity in tissue

t = 2z/V (2)

since the time required is for a round trip. Any

information about R(t) which can be obtained will

be related to changes of impedance in the tissue,

and, hence, may be of use in tissue characterization.

A region of tissue is interrogated by passing

a pulse A(t)of ultrasound through it and observing the return signal S(t). S(t) is given by the convolution of A(t) and R(t):

S(t) = /A(t) R(t - T)dt (3)

which can be represented symbolically as

S{t) = A(t) * R(t). (4)

We do not necessarily seek to recover R(t) exactly, but rather to derive statistical information

about it. We are interested in knowing the distribution sizes of the objects response for the re- flected signal, and how regularly they are spaced

in the tissue. We may also be interested in the evolution of A(t) as the pulse passes through tis- sue with frequency dependent attenuation.

Since the autocorrelation function responds to structures with strong peaks, it could be con- sidered a possible processing technique to extract

structure information from S(t). However, it can

be shown that the autocorrelation of two convolved

functions is the convolution of their autocorrelations. Using -A" to represent correlation,

S(t)*S(t) = (A(t)*A(t)) * (R(t)*R(t)) . (5)

Since A(t) is an oscillatory function, A(t)*A(t)

is also, and the autocorrelation of R is confused

by the convolution. The best that can be done in this case is to recover the envelope of the auto- correlation. A convenient technique for this pur- pose is to find the envelope of the analytic function associated with the autocorrelation by taking

the Fourier transform, zeroing negative frequency

components, and taking the magnitude of the inverse

transform [6]. Since the autocorrelation is normally performed by inverse transforming the power spectrum, very little additional effort is needed.

One merely zeros the negative frequencies in the power spectrum.

An example of a typical ultrasound echo is shown in figure 1. This echo represents the re- turn from a pig liver, using a 3.5 MHz transducer.

A pattern of multiple echoes is evident, but not readily quantifiable. The envelope of the autoTIME , MICROSECONDS

Fig. 1. The recorded ultrasonic echo from a section of fresh pig liver, in vitro , using a nominally 3.5 MHz transducer.

This represents 1.9 cm of tissue.

0 12.8 TIME , MICROSECONDS

Fig. 2. The envelope of the autocorrelation

function of the signal in figure 1.

correlation of this signal is shown in figure 2. Several peaks are discernable, but none is dominant.

A more sophisticated technique is sought.

3. The Inversion Process

In tissue signature analysis, responses from

the tissue are weighted by the form of the trans- ducer response. In addition, there is distortion

due to the tissues on the way to the organ of interest. So a process is desired which, given

S(t), can separate A(t) and R(t). Under ideal conditions, if one of two convolved functions is known, the other may be found. Deconvolution is performed by Fourier transforming, inverse filtering, and inverse Fourier transforming.

If eq. (4) is Fourier transformed, the convolution leads to a product, and rearranging gives:

RM = iM. . (6)

Several factors prevent the use of this formal in- version process in the present case. The presence

of finite noise in the recorded signal means that

S(oj) is not known exactly. In addition, as the ultrasonic transducer responses are band-limited,

A(u) becomes vanishingly small in the same frequency ranges where S(a)) is dominated by noise, so the noise has a disproportionate influence on the re- covery of R(a)). Finally, since the signal has prop propagated through a tissue of unknown and frequency dependent attenuation, A(a)) is not known. A different approach is, therefore needed.

288
4. Homomorphic Processing

We have used so-called homomorphic processing,

or cepstral analysis, for this purpose. At the present time, we have by no means developed this type of processing to its limit, but we have made

a start on techniques employing it and our intention is to develop the techniques further.

The basic idea behind homomorphic processing

is to turn a nonlinear process into a linear

process. Consider the convolution to the signal from

the transducer A(t) with the tissue response

R(t) in the time domain

S(t) = A(t) * R(t) (7)

In the frequency domain, the two components de- rived from these signals are

A(a)) • R(a)) (8)

A product form is also obtained for the power spectrum

tS(a,)|2 = |A(a.)|2 . |R{^)|2 (9)

By taking the logarithm of |S(q))|2, the multiplication is converted to a sum. This enables

normal linear signal processing techniques to be used.Let

then

S(a>) = log|S(a))|2

A{o)) = log|A(a>)|2

R(a)) = log|R(a))|2 ,

S(a)) = A(a)) + R(oj) .

(10)

(11)

(12)

(13)

Finally, if we take the Fourier transform of

S(a)) defined as S(t), we can write

S(t) = A(t) + R(t) (14)

S(t) is called the cepstrum of S(t). The notation is used to distinguish it from S(t).

Figures 3, 4, and 5 demonstrate the convolution

of a simulated transducer impulse response with

an impulse pair, and the additive property of

the log power spectra and cepstra.

We note that in the log power spectrum domain

the system is linear and subject to all the rules

and techniques of linear filtering. Such filtering may be accomplished by taking one more Fourier transform, yielding the cepstrum of the

LjJ Q

Z)

CL<

CO

(a)

(b)

(c)

TIME

Fig. 3. (a) A simulated transducer impulse response of the form g-^(t/8)2 2TT(t/8).

(b) An impulse pair with spacing 16.

(c) The convolution of (a) and (b).

AA

FREQUENCY

Fig. 4. The log power spectra of figure 2(a),

(b), and (c) respectively.

289
(a)

(b)

(c)

TIME

Fig. 5. The cepstra of figure 3(a), (b), and

(c) respectively.

ceps'trum of the reflection pattern is not known

and varies from tissue to tissue. Some examples of the cepstra of impulse trains

can yield insight into what may happen in tissue,

and suggest features which will be meaningful.

Two im.pulses with separation t will yield a string

of impulses with separation t and of strength de- caying fairly rapidly toward zero away from the origin, as seen in figures 3(b) and 5(b). If more

than two impulses exist with the same spaces, the cepstrum is similar, but with a slower decay rate. This is depicted in figure 6. Figure 6 also de- monstrates a problem which often arises in the digital implementation of the cepstrum. When the logarithm of the power spectrum is taken, the non- linear process generates harmonics in the time

domain which can cause aliasing in the cepstrum,

even though the original spectrum bandwidth was

well within the Nyquist bandwidth of the sampling

process. In general, any repetitive pattern in a signal will lead to a peak at a time equal to that spacing in the spectrum, as well as lesser peaks

at multiples of that spacing. The cepstrum itself may not be easy to interpret for ultrasound echoes

from tissue unless the tissue has a fairly simple

and distinct structure. But the decay rate of the cepstrum is related to the spacings and numbers of periodic reflections in the tissue, and hence, may

be useful for tissue characterization.

If the minimum spacing between strong reflections in the tissue is somewhat greater than the wavelength of the interrogating sound, all information about the periodicities of reflections will

be separated from the information about the character of an individual reflection in the cepstrum.

In this case, it should be possible to filter the cepstrum and recover the average of the power

spectral densities of the individual reflections

from a region of tissue. This should be a good

original signal. Filtering may then be performed by multiplying the cepstrum by a weighting

function to select a desired portion, then re- versing as many processing steps as necessary to reach a useful and recognizable domain. Since

information was lost in taking the power spec- trum complete inversion is not possible. This restriction is removed by the use of the complex

cepstrum, in which the real logarithm of the power spectrum is replaced by the complex logarithm of the complex spectrum. However, this technique, which has been demonstrated in seismographic and speech processing applications, is much more difficult to use in practice. If, in- stead, we reconstruct the signals from the real cepstrum, we obtain the correlation function of

the original signals, or of the tissue impedance

variations.

5. Possible Applications

Filtering in the cepstrum domain is useful only

if the cepstra of the two components fall in dif- ferent regions of the domain. The spectrum of a broadband transducer impulse response can be close

to a Gaussian response in frequency. So its logarithm is close to a parabolic response in fre- quency, and cepstrum is a relatively narrow pulse

centered at the origin, which has a time width

of the same order as the original impulse. This

effect can be seen in figures 3(a) and 5(a). The

(a)

(b)

TIME

Fig. 6. (a) Four impulses with spacing 16.

(b) The cepstrum of the convolution

of the impulse response of 3(a),

with the impulse train of 6(a).

290
approximation to the spectrum of the transmitted

ultrasound pulse as it passes through the region

of tissue within an unknown constant. If such a calculation is carried out on signals from two succeeding regions of tissue along the line of sight, the difference between them will contain

information about the frequency dependence of the attenuation of ultrasound in the tissue between

these two regions.

6. Experimental Techniques

A surplus B-scan imaging system, loaned by the Radiology Department of the Stanford University

Medical Center, was obtained, originally as a means of positioning the ultrasound transducers

and generating images for identification of the source of echoes to be processed. It was found

that the pulse generator and receiving amplifier

of the system, a Picker, were of excellent quality. Also, a depth marker was available, which

could be used to select a portion of a trace.

By tapping a small amount of the received signal

with a high impedance isolation transformer at a low impedance point in the receiver, a high quality radio frequency signal was obtained without

compromising either the operation or safety of the existing B-scan system. The tapped R-F signal was further amplified and monitored by an oscilloscope

and a Biomation 8100 transient recorder, which

was set to record when armed by a pushbutton ac- cessible to the operator of the B-scan system.

A PDPll/10 minicomputer was used to store the digitized R-F signals from the transient recorder

on a magnetic disc, and later to read the stored

records and process them as desired. In practice,

the operator manipulated the transducer until

the beam passed through the desired area, using

the B-scan image, if desired; then placed the depth marker at the beginning of the region of interest, checked the signal on the oscilloscope,

and initiated recording with the pushbutton.

This was found to be quite fast and convenient.

The system is depicted schematically in figure 7. After some experimentation, it was decided to standardize the format of recorded data in order

to simplify the signal processing programs.

A sample rate of 20 MHz was chosen, giving a

B-SCAN

SYSTEM

TRONSOUCER

PUL5ER —r~

DATA ACQUISITION PROCESSING a STORAGE

OSCILLOSCOPE

TRANSIENT RECORDER n -J MANUAL

ARMING CONTROL

[— MINICOMPUTER

MAGNETIC

DISC

ANALOG SIGNAL PATH

DIGITAL SIGNAL PATH

Fig. 7. A schematic diagram of the system used

to obtain, store, and process ultrasonic

echoes

usable signal bandwidth of 10 MHz. Record

lenngth was standardized at 512 samples, which

represented 25.6 ys, or about 1.9 cm of tissue.

This was found to be long enough for most purposes, but a provision was made to store four consecutive records if desired, representing

7.7 cm of tissue. Fourier transforms could be calculated on 512 point records in 10 seconds,

and cepstra in 23 seconds, fast enough for interactive studies on the effects of various types

of filtering.

Two types of experiments have been run to collect data for various purposes. In the first

type, the scanning arm of the B-scan system is not

used. The transducer is fixed in a water tank,

suspended from a micrometer adjustable frame.

The transducer's beam could be aligned to reflect

from the water surface for transducer characterization and reference purposes, on targets suspended

from a rotatable mount, or on tissue samples pinned to a sponge on the bottom of the tank. In the second mode, the scanning arm was used and identification of tissues was made using the images

formed. Single reflections from the surface of the water tank were used to obtain data on the efficiency and spectral characteristics of both pur- chased and fabricated transducers, and to verify

the structure of the cepstrum of a transducer im- pulse response. Impulse responses and cepstra for

two commercial transducers are shown in figures 8 and 9. A transducer was then aimed at the rotating mount, and a fixture holding three 1.1 mm diameter rods side by side in the beam at a spacing of 2.5 mm was attached, as shown in figure 10. The array of rods was rotated from perpendicular

to the beam to parallel, and on to perpendicular

again, and the reflections recorded at five degree

increments in angle to provide reflections of various spacings. The envelope of these cepstra

is plotted as a function of angle in figure 11. The sinusoidal dependence of spacing on angle can

be clearly seen. The short spacing is seen best

on one side of 90°, and the long spacing on the

(a)

(b)

25.6 TIME . MICROSECONDS

Fig. 8. (a) Impulse response of a commercial

2.25 MHz transducer.

(b) Impulse response of a commercial

3.5 MHz transducer.

291
12.8 TIME , MICROSECONDS

Fig. 9. (a), (b) Cepstra of the impulse responses

of 8(a) and (b) respectively.

3.2 6.4 9.6 TIME, MICROSECONDS

ANGLE B

Fig. 11. Moduli of cepstra recovered from the scheme of figure 10, as a function of angle.

ROTATING

MOUNT

CYLINDRICAL

RODS

TRANSDUCER

Fig. 10. Schematic diagram of a scheme to produce

three identical echoes with variable spacing. Three 1.1 mm diameter steel rods are mounted 2.5 mm apart center to center.

other because a slight misalignment of the rods caused the reflections to be unequal in strength

and to depend on angle. At angles where the separation between the reflections is comparable

to the pulse width (that is, about .5 ys), inter- ference can be seen to occur between the peak rep- resenting the pulse shape and that representing

the periodicity.

In order to demonstrate the ability of the cep- strum to detect a periodic structure in biological

tissue, a particularly simple sample was chosen:

pig liver. Pig liver is a large organ, readily

available in a fairly fresh state, and having a characteristic and simple period structure [8]. Our sample was several centimeters thick, and was observed to have an internal structure consisting

largely of spherical lobules of fairly uniform

size, about 2 mm in diameter. Several echoes were recorded from various parts of the liver, using a 3.5 MHz focused transducer in the water tank. The best of the cepstra recovered is shown in figure

TIME , MICROSECONDS

Fig, 12. The modulus of the cepstrum of the signal shown in figure 1

.

12. The signal from which it was derived was

shown in figure 1. The strong peak at 2.5 ys cor- responds to a spacing of 1.9 mm between reflectors,

which corresponds well with the observed size of the lobules. Other cepstra were not always so simple.

Cepstra were also calculated for signals from

various regions of human livers from autopsies,

as well as from thigh muscles and the area of the liver, in vivo . The details of the structure of

both the power spectrum and the cepstrum were

found to vary markedly among the samples, and even between two consecutive 5 mm long regions of single records. Some cepstra showed substantial

single peaks; some did not. The decay rates of

the cepstra varied substantially also. We conclude

that the tissues studied are sufficiently inhomo- geneous to prevent easy interpretation of these

results. A broad statistical study of a large number of signals documented as to the location and possible pathology of the tissue, original trans- ducer response, and thickness of intervening tissue, will be needed to prove the usefulness, or lack thereof, of such techniques.

292
7. Attenuation Estimation

Since the cepstrum is the Fourier transform of

the log power spectrum, low pass filtering, or smoothing, of the log power spectrum may be done

by multiplying the cepstrum by a window function

which leaves short time responses untouched and eliminates long time values. The resultant gated

signal may then be Fourier transformed to the frequency domain again. If the variations in the spectrum are due to reflections with relatively

large spacing tissue, and, hence, are rapid compared to the finite bandwidth of the incident beam

of sound, the rapidly varying spectral components

can be filtered out, leaving a good approximation

to the log power spectrum of the incident beam distorted by the average attenuation in the tissue. If such an approximation is made for two consecutive regions of tissue along the same ultrasonic beam path, the difference between them

should exhibit the frequency dependence of the at- tenuation of ultrasound through the path between

them. Such a calculation does not require as strong an assumption about the variations in the

log power spectrum due to the tissue reflections.

There may be slow variations; if they are the same

in the two regions of tissue, their difference

will be zero. Since slow variations in the log power spectrum arise from structure fine compared

to the ultrasonic pulse length, the success or failure of this technique to predict a plausible

frequency dependence for the attenuation of ultrasound will give a measure of the similarity of the structure of the two regions of tissue on the scale of the ultrasonic pulse length.

Since the advantage of this technique would be

its ability to measure attenuation in vivo non- invasively, it was applied to the data recorded

-+20r

UJo

clCDo

(b)

201-

FREQUENCY (MHz)

Fig. 13. (a) and (b), log power spectra from two consecutive 1 cm long regions of in vivo

human liver tissue with 2 cm center spacing, recorded with a 2.25 MHz transducer.

1" This procedure is illustrated in figures

13 and 14. First the data is windowed to the pro- per length and Fourier transformed, and log power

and spectra obtained. The signal to noise ratio

has been artifically decreased to 20 dB to de-em- phasize the random spectral components outside the useful bandwidth of the transducer, 1 to 3 MHz. The cepstra are then computed and low pass filtered

with a sine-squared window, which closely approximates a Gaussian window, but completely cuts off

long time components. Fourier transforming again yields the smoothed log power spectrum. Subtracting one such spectrum from the other and dividing

by the path length between them yields a curve

which, over the useful bandwidth of the transducer,

estimates the frequency dependence of the loss over

that path. The absolute loss is not estimated here, although with attention to time-gain control settings and assumption of equal reflection amplitudes in the two regions, it could be. In this example in which the signals were taken from two regions about 1 cm long and 2 cm apart in the area

of the liver of a person with a presumed normal

liver, the estimated loss follows fairly well a linear frequency dependence, although with a coef- ficient of 0.8 dB/cm MHz, slightly lower than the previously reported in in vitro value [9]

20r

UJo

Q.O

T3

<

ZD

111 >

<

FREQUENCY (MHz)

Fig. 14. (a) Solid line, the cepstrally smoothed

log power spectrum derived from that

of figure 13(a). Dashed line, the same function of the spectrum of figure 13(b).

(b) Solid line, the difference between

the two smoothed spectra, divided

by the path length. Dashed line,

the slope of the attenuation in the frequency range where both spectra

are above noise. This slope is

.8 dB/cm.

293
-+ 20

LU 20

0

•20r

(a)

FREQUENCY (MHz)

Fig. 15. Log power spectra analogous to those of figure 13, but from a different region

of the liver.

An interesting phenomenon has been found in the two vn_ vivo livers and the one i_n_ vitro liver

studied with this technique so far. In many of

the log power spectra calculated, there is a deep

notch, representing an absence of reflection at frequencies varying from 2.4 to 2.7 MHz. This notch has been seen with both focused and unfo- cused transducers of both 2.25 and 3.5 MHz center

frequency. This phenomenon violates the conditions under which one can get a good estimate of attenuation. It occurs only once in the useful bandwidth of the transducers used, and so cannot

be considered rapidly varying. Its frequency

varies enough from region to region that it does not cancel when two spectra are subtracted. The very deep notch is almost, but not quite, re- moved by the smoothing operation. Since the attenuation calculation takes the difference be- tween two similar functions, it is sensitive to the small error which remains. An example of this problem is shown in figures 15 and 16. Such a phenomenon probably arises because most of the reflections in a region are coming from a single

type of structure: one with a constant size of

a fraction of a millimeter. Measurements over a broader bandwidth could determine more exactly

what type of structure this is. If it could be identified, there might be clinically useful in- formation available.

8. Conclusions

From this limited study, we conclude that:

(a) Cepstral analysis, by converting ultrasonic signals from a domain in which the output is the convolution of an impulse response with a re- flection function to a domain in which it is a sum, allows the separation of information about

the distribution of spacings between reflectors

from information about the incident impulse.

LUB

a.o

o

20

- / \

\ \

\ / \ ^

\

1 1 I

(a)

o

<

UJ>

UJ

cr FREQUENCY (MHz)

Fig. 16. (a) Smoothed log power spectra from those

of figure 15. (b) Attenuation estimated from figure

16(a). No estimate is possible in this case.

(b) Two potentially useful parameters for tis- sue characterization in vivo are the form of the cepstrum of ultrasound echoes from tissue, which

can identify periodicities in the tissue; and at- tenuation coefficient estimation by cepstral

smoothing of log power spectra.

A lack of consistency from one region to another within a tissue suggests considerable

variability in the tissue. Further work, utilizing statistical studies on large data bases, will

be required to verify the usefulness of these techniques. Cepstral analysis should prove useful, since averaging over similar samples will en- hance the tissue-dependent information. This is in marked contrast to the power spectral domain,

where averaging over similar samples tends to eliminate tissue-dependent information and approxi- mate the power spectrum of the measuring system.

Acknowledgments

The work reported in this paper was supported

in part by the National Science Foundation under Grant No. ENG 75-18681, and in part by the Kaiser

Foundation.

References

[1] Several of these studies are reviewed in: Dunn, F., Ultrasonics Attenuation, Absorption,

and Velocity in Tissues and Organs; and,

Reid, J.M., The Scattering of Ultrasound by

Tissues, in Ultrasonic Tissue Characterization . M. Linzer, ed.. National Bureau of Standards

Spec. Publ. 453, pp. 21-28 and 29-47 (U.S. Government Printing Office, Washington, D.C.,

1976).

294
[2] Bogert, B. P., Healy, M. J. R., and Tukey,

J. W., The Frequency Analysis of Time Series

for Echoes: Cepstrum, Pseudo-Autocovariance,

Cross-Cepstrum, and Saphe Cracking, in Proc . Sym. Time Series Analysis , M. Rosenblatt, ed.

,

pp. 209-243 (John Wiley and Sons, Inc., New

York, 1963).

[3] Stockham, T. C, Jr., Restoration of Old Acoustic Recordings by Means of Digital Signal

Processing, Preprint, 41st Convention, Audio

Engineering Society, New York, October 1971.

[4] Ulrych, T. J., Application of homomorphic

deconvolution to seismology. Geophysics 36

(4), 650-660 (August 1971).

[5] Adaptive Nonlinear Signal Processing for Characterization of Ultrasonic NDE Waveforms,

Task 2: Measurement of Subsurface Fatigue

Crack Size, in Technical Report AFML-TR-76-44,

April 1976, Section 6.4, p. 54.

[6] Bracewell , R., The Fouri er Transform and Its Application, pp. 269-27MMcGraw-Hi 1 1

, New

York, 1965).

[7] Oppenheim, A. V. and Schafer, R. W., Digital

S ignal Processing Chap. 10, pp. 480-531 TPrentice-Hall , Inc., Princeton, 1975).

[8] Lele, P. P., Mansfield, A. B., Murphy, A. I., Namery, J., and Senapati , N., Tissue Characterization by Ultrasonic Frequency Dependent

Attenuation and Scattering, in Ultrasonic

Tissue Characterization , M. Linzer, ed..

National Bureau of Standards Spec. Publ. 453,

pp. 167-196 (U.S. Government Printing Office,

Washington, D.C., 1976).

[9] Goldman, D. E. and Heuter, T. F., Tabular

data of the velocity and absorption of high

frequency sound in mammalian tissues, J_. Acoust. Soc. Am . 28, 35 (1956).

295
1

t

li

ij

If

is
Reprinted from Ultrasonic Tissue Characterization II, M. Linzer, ed. , National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C., 1979).

RECOGNITION OF PATTERNS IN ULTRASONIC SECTIONAL PICTURES

OF THE PROSTATE FOR TUMOR DIAGNOSIS

W. von Seelen,^ A. Gaca,^ E. Loch,^ W. Scheiding,^ and G. Wessels^

ilnstitut f(Jr Zoologie

Arbei tsgruppe III (Biophysik)

D-6500 Mainz, Federal Republic of Germany

^Deutsche Klinik fUr Diagnostik

D-6200 Wiesbaden, Federal Republic of Germany

^Battelle Institut e.V. D-600 Frankfurt/M. , Federal Republic of Germany

We examined the prostate with ultrasonics to diagnose tumorous alterations of the

organ. We scanned directly from the abdominal wall through the filled bladder (transvesical). The research is aimed at: 1) improvement and mathematical preparation of the ultrasonic pictures to assist the physician in his diagnosis; and 2) ascertainment

of significant parameters which allow the classes "normal prostate," "adenoma" and "carcinoma" to be distinguished in screening examinations. The results show that with

ultrasonics, adenomas and carcinomas are recognizable in 96 percent of the examined

patients and can be differentiated from normal prostate tissue. The palpation finding

was used as a reference in most cases.

Key words: Pattern recognition; prostate tumors; ultrasound.

1. Introduction

Carcinoma of the prostate ranges third in cancer mortality in the Federal Republic of Germany. Be- sides the subjective rectal palpation findings which

give the physician signs of organic alterations, it

is useful to look for other examination methods.

The aim of this investigation is to analyze the value of the ultrasonic scan for differential diagnosis and treatment control of tumor diseases and

to check in establishing preclinic findings the possibility of a screening procedure allowing a guick separation between suspect and non-suspect

cases in large groups of patients. The apparatus available for the methodical part

of the investigations are two ultrasonic scanners: Combison II Kretz (Compound-Scanner) Vidoson, Siemens (Realtime-Scanner) as well as a computer (PDP

11/34). The apparatus is shown schematically in figure 1. This study includes both examinations in vivo and some examinations in vitro. Transvesical

representation of the prostate was chosen for in vivo examination. The ultrasonic pictures are

taken from above the organ by scanning in sections

of 3 mm; the angle at which the sound waves enter

is either « = 15° or a = 20° from the vertical.

Figure 2 shows the position of the organ as well

as the direction of entry of the sound used to pro- duce the pictures discussed below. The freguencies

are 2.25 MHz and 4 MHz. Linear scanning is used

to cover the area of the organ with a slightly al- tered angle of entry for the forward and reverse

runs. The B pictures gained in this way are re- corded on a video tape which serves as mass storage

For the computer analysis the video signal can be digitized by a specially developed interface and read into a 512 x 512 matrix; a region of interest

can be marked out within the picture. In addition,

it is possible to feed the non-demodulated HF signal or the A signal into the PDP 11 computer. Two

control techniques were employed in the analysis of the ultrasonic pictures: comparison with the urolo

gists' palpation findings and in vitro examinations

of dissection material taken during operations.

The ultrasonic pictures reproduce the geometrical arrangement and form of the density gradients

in the tissue which are situated perpendicular to the direction of the sound. Since not enough is known about the reflecting properties of the various tissues, the picture features for the different

picture classes cannot be defined exactly a priori . The study was therefore carried out in the following stages:

1. Definition of a limited learning sample

which can be diagnosed as certainly as possible

with the palpation findings and histological

control s

.

2. Determination of as many apparently significant features as possible.

3. Generation of an adaptive classifier which

begins with a fixed initial weighting of the features. This weighting is changed in the course

of the classification of the learning sample so as to eliminate errors. In this way the physician

297
Fig. 3. Ultrasonic picture of a normal prostate.

Fig. 4. Ultrasonic picture of an adenomatous

prostate.

Ultrasonic picture of a carcinomatous

prostate.

supervises the determination of features and class

1 imits.

4. Ascertainment of the validity of the individual features to determine a precise set of distinguishing features which does not involve too difficult or costly application. The criterion for validity is provided by the alteration in detection

rate for the relevant feature. Figures 3, 4 and 5 each show one representative

of the classes normal, adenomatous and carcinomatous

respectively. While the normal organ's interior is characteristically largely echo free, the adenoma

appears highly structured. The carcinoma in the right half causes a "shadow" which penetrates the capsule areas. Other features of the pictures will

be discussed below.

2. Preprocessing of the Pictures

Preprocessing the pictures is intended to allow

the doctor to make the most certain possible diagnosis. For this it is necessary to eliminate disturbances and distortions in the picture and to create the possibility of accentuating features re- levant to suspected cases, if this is required. To

this end the operations described below were im298
plemented on the digital computer and then first

tested by subjecting them to the same classification procedure as the original pictures. The fol- lowing operations were carried out on the pictures

(for different numbers of patients in each case).

a. Definition of a "region of interest." This

operation consists in limiting the organ area on the screen and reducing the amount of data taken over in the computer from the picture to 128 x 128 picture points (8 bits per point) which thus refer

to the region of interest. This limitation of the picture is carried out by the physician treating

the case.

b. Standardizing the intensity of the picture.

The space dependent intensity of the picture x(r,s)

in the B scan picture varies a great deal from

patient to patient (age, corpulence, etc.) and also depends on the amplification of the experimental

device. Therefore, parameters dependent on in- tensity should only be used in the d iagno sis when

x(r,s) is divided by the mean value x(r ,s ) deter- mined in a defined organ area. The resulting picture is the basis for several computer operations.

c. Inverse filtering. To eliminate the loss

in lateral focus due to the form H, (r,s) of the sound beam as far as possible, the values ascertained under water for this space dependent cou- pling were used to determine the filter charac- teristic value H.(r,s). The conditions for the realization of (r ,s)

F(H|^(r,s)) • F(H.(r,s)) = 1

were replaced by

E(H|^(r,s)) = 1

1 + F(H.(r,s)) (b)

for numerical reasons. F characterizes the Fourier

transform according to the two space coordinates

r,s. Figure 5a shows the sectional picture of a 0.5 mm thick wire in the tank of water as well as its filtered representation with improved radial focus

.

d. Symmetrical filtering. The convolution of the picture X(r,s) with any optional symmetrical,

and thus phase free transmission function H(r,s) allows a far-reaching alteration of the pictures,

when one varies the parameters nix, ni2> ^i' ^2 in

Y(r,s) = X(r,s) * H(r,s]

with

H(r,s) = Um^e

Two phase free band pass filters with different

mean frequencies Umj and Um2 were realized for

miBi = m2B2 and B2 > B^. Figures 6b (F) and 5c (G) show the result of the operation for Um2 > Umj. The classes can be better distinguished in the filtered

version of the picture (F, Umj) than in the original

picture (cf. Section 4). The second filter operation (G) is interpreted so that the picture amplitude is approximately proportional to the gradient

of the intensity in the original picture. This

variable has to be taken into consideration at the boundary of carcinomas.

(c)

Fig. 6. Sectional picture of a wire before and after inverse filtering (a); band pass filtered sectional picture of a carcinomatous organ with Umi (F) (b); and Uma

(G) (c).

299
e. Phase dependent filters. It is easier to judge the pictures, if the function H(r,s) is not symmetric, i.e.:

H(r,s) = Umie-(^'"^')/Bf . ^„^,-i(r-r,)^ns-s,)^)/4

with Bf<< Bj. In this case the Fourier transform

F (H(r,s)) is complex and a phase shift exists. In this way a picture is produced which is interpreted

as pseudo three-dimensional when viewed. If H(r,s)

characterizes a differentiating space filter com- bined with a nonlinear characteristic curve, then

the same effect occurs together with an accentuation

of the intensity modulation. Figure 7 shows two examples for different H(r,s) (paper in preparation).

All filter operations, insofar as they are linear,

can be combined to one ooeration.

Fig. 7. Filtering with asymmetrical functions

H(r,s).

f. Equidensities . It is easier to analyze the weak modulations in the area of the organ more

exactly when the low pass filtered original pic- ture is provided with lines of equal intensity.

Figure 8 shows an example with an increased number

of picture points.

Fig. 8. Carcinomatous prostate represented in equidensities in a low pass filtered

sectional picture.

It depends on the problem in question which of the procedures described is best suited for the physician's diagnosis. Only the F and G pictures

have been tested with the classification procedure

(cf . Section 4)

.

3. Feature Extraction

The problem of feature extraction has to be solv

ed in two ways. The reference vectors are deter- mined on the basis of the physician's palpation

findings and the vectors x- ai"e obtained from the ultrasonic pictures. The palpation finding takes

into consideration size, consistency, surface state

and simple form parameters [1-5]^. The analysis of the ultrasonic picture refers to global and local features which in the first phase are still partly

obtained by visual scrutiny of the ^reen picture.

Should these features prove to be effective in dis- tinguishing classes, the procedure will be complete

ly automated.

In particular, the following features are quanti

fied:

1. Longitudinal diameter of the organ.

2. Rise in the base of the bladder.

3. Local gaps in the capsule.

4. Coarse parallel fibrous structure in the interior of the organ.

5. Fine fibrous structure in the interior. The automatic determination of features 4 and 5 by multiple correlation of the picture with texture

pictures in which the form of the elements is op- tional (e.g., elliptical) but their location is statistical, is being implemented at present.

After the pictur'e has been transferred from the video recorder to the computer, the following param

eters are extracted according to the definition of the region of interest:

6. Surface of the sectional picture Fg.

7. Autocorrelation (^^^(O'O)

8. The standardized signal power in the region

of interest, i.e., <j)^^(o,o)/x(r,s)2.

^Figures in brackets indicate literature

references at the end of this paper.

300
9. The amplitude density distribution p(x(r,s))

with the relevant first three moments or central moments respectively

E(x(r,s)), E(x(r,s) - x(r,s))2,

E(x(r,s) - x(r,s))3.

10. Curve of the autocorrelation function along

a line through the suspect zones (j) (r'). ^r^r

11. Coherence width and relative extremes of the autocorrelation function <t)xx('^) along a line through suspect zones.

12. Power and energy above a threshold or within an amplitude window respectively. This

operation has so far only been implemented

on 60 statistically selected patients.

In order to include local form parameters in the consideration, the features 6 through 11 were de- termined in the original picture and in two filtered pictures (F,G) and classified separately. In this way the efficiency of the filtering in distinguishing these features was tested. The effect

of picture standardization and parameter 12 have

so far only been studied on 60 patients. The va- idity of all the parameters mentioned is being

tested with an adaptive classifier.

4. Classification

If is a feature vector, then classification

consists in the division of feature space by class

limits so that

1 Dj(^) i,j = 1,2, ... m, i M

when is correctly classified; D is a discriminating function [6]. In this project an adaptive

linear classifier was chosen at first with

Di(Zi) = E + ""^w.

k=l

^

The variable W-j designates the kth component of the reference vector W'l which is generated in p steps with the aid of a learning sample according

to the rule

-i,6+i ^ -i 6

'^'^ ^i correctly classified

and

-i,6+i " -i,6 ^ "^6 * ^i,6 ''^ i^i incorrectly

classified with

In the case of a Gaussian distortion of the features, the decision rule minimizes the quadratic

distance between the reference vector and the vector

to be classified. The decisions on a correct or incorrect classification in the adaptive process de- scribed above are based on the physician's palpation findings. After generation of the reference

vector, the pictures were classified in stages.

First, the set of features 1 through 5 was applied

(Part I), then the parameters 6 through 11 for the original pictures as well as two filtered versions

of the picture (Part II) and then parameter 12 on intensity standardized pictures for 60 patients.

A classification on the basis of the complete

featureset (I + II + III) will be realized if feature 12 is determined for all patients. The class-specific reference-vectors were established

with 25 patients per class in the first stage of

the project. Therefore the following number of patients can be considered as a test data set. Part I. After taking palpation findings from

500 patients, the parameters 1 through 5 (Section

3) were extracted and the classes normal (N) and suspect (adenomatous (A), carcinomous (C)) distinguished. The physician's diagnoses were:

a) 97 patients normal

b) 324 patients adenomatous or carcinomatous

c) 79 patients nonspecif ical ly suspect (prostatitis, congestion etc.).

If P(N/A + c) characterizes the probability that

a patient classed as normal nevertheless has an adenoma or carcinoma (false negative) one obtains

the following results for false classification. In the case of unequivocal diagnosis:

P(N/A + C) = 3.2 % (false negative)

P(A + C/N) = 7.4 % (false positive)

If the nonspecific suspect cases are also taken

into consideration then P(N/A + C) = 7.2 percent. The increase in error due to group c can be further

lowered with more precise examination. If the total number of false classifications is considered, the probability of error is 3.9 percent. In the 3 group problem the mean error rate increases to 8 percent.

Part II. The classification of the pictures

from 198 patients according to the features 6 through 11 resulted in a mean error of 11.9 per- cent for the 2 group problem (normal /not normal)

with the original pictures and 10 percent for the filtered version F and 14 percent for the filtered

version G. First results are now available for studying the weighting of the individual features

and altered decision strategies but the analysis

has not been completed. Part III. Using feature 12 presupposes stand- ardizing the picture intensity. In a set of 60 patients selected statistically the rate of error

for the 2 group problem was 0 percent. The mean error for the 3 group problem was 7 percent and P(C/N + A) = 0 percent. This study is at present

being extended to the whole group of patients (500).

An improvement in the classification can be expected.

As the features in the three classification ex- periments are at least partially independent from

each other, it is to be expected that the rate of error can be reduced with a combined set of features. The systematic study of these combinations,

which are intended to attain a better feature vector

with a few easily calculable components has not yet

been completed.

The further studies are concerned with ascer- taining a histologically tested learning sample,

determining the sharpest distinguishing parameter

and obtaining a classifier which takes the statistical parameters of the features into consideration.

301
References

[1] Gaca, A., Loch, t. G., Scheiding, U., von Seelen, W. , and Wessels, G. , Ultraschalluntersuchungen der Prostata zur Erkennung von Tumor- erkrankungen. Report BF-R-62. 991-3 (1977)

Bundesministerium fUr Forschung, Bonn, KennedyAllee. (This report contains a comprehensive

list of the relevant literature.)

[2] King, W. , Kieineyer, W. , Mark, R. , Boyce, W. H., and McKinney, W. M. , Current status of prostatic echography, J. Amer. Med. Ass . 226 (4),

(1973).

[3] Takahashi , H. and Ouchi , T., Ultrasonic diagnosis in the field of urology. First Report,

Japanese Medical Ultrasonics , pp. 7-10,

Tokyo, (1963).

[4] Takahashi, H., and Ouchi, T., Ultrasonic diagnosis in the field of urology. Second Report,

J apanese Medical Ultrasonics , pp. 35-37, Tokyo,

T1964).

[5] Watanabe, H., Igari, D. , Tanahashi , Y., Hasada,

K. , and Saitoh, M. , Diagnostic application of ultrasonography to the prostate. Invest. Urol . 8, 548-559 (1971).

[6] Fu, K. S., Digital Pa ttern Recognition

(Springer-Verlag, Berlin 1976)

.
Reprinted from Ultrasonic Tissue Characterization II, M. Linzer, ed.. National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C., 1979).

RECENT DEVELOPMENTS IN OBTAINING HISTOPATHOLOGICAL INFORMATION

FROM ULTRASOUND TISSUE SIGNATURES

K. Preston, Jr.,^ M. J. Czerwinski,^ M. L. Skolnik,^ and D. E. Leb^

^Department of Electrical Engineering

Carnegie-Mellon University

Pittsburgh, Pennsylvania 15213, U.S.A.

^Ultrasound Laboratory

University of Pittsburgh Medical Center

Pittsburgh, Pennsylvania 15213, U.S.A.

^Department of Medicine

University of Pittsburgh

Pittsburgh, Pennsylvania 15261 U.S.A.

Statistical, signal -analytic techniques may be applied to ultrasonic pulse-echoes

received from organs of the human body. Simultaneous tissue biopsies of these organs may be sectioned, stained, and measured by the computerized optical microscope using

various image-analytic techniques. This paper reports some preliminary work along

these lines as related to the kidney and liver.

Keywords: Picture processing; signal analysis; ultrasound.

1. Introduction

In the 1950s Wild and Reid noticed that there appeared to be a correlation between the properties of the A-scan in mammography and the histopathology of breast tissue in human subjects. Later Fry [2] compared the histopathology of animal tissue (feline and porcine) with the B-scan

echogram. More recently Mountford and Wells [3],

using digitized A-scans from both normal and cirrhotic subjects, found that specific signal

parameters (amplitude, rise time, etc.) correlated with liver pathology. Ossoinig [4],

Fields et al. [5], and Taylor and Milan [6] made

further observations of B-scan texture, amplitudes

and positions of the peaks in the demodulated A- scan, and A-scan amplitude probability distribution functions ("histograms"), respectively.

The advent of high-speed digitizers and inexpensive digital computers has now opened this field

to many new investigations. One of these investigations was commenced by the authors under a grant

from the National Science Foundation (APR75-08154)

in mid-1975. A preliminary report was presented by

Preston[7] at the first meeting of this international seminar at Gai thersburgh in 1975. The CarnegieMellon University program is being conducted along

the lines of a project in classical pattern recognition in distinction to a project in biological

modeling. The work is being conducted on both humans and animals in vivo in cooperation with the

^Figures in brackets indicate literature

references at the end of this paper.

Departments of Radiology, Penology, and Pathology

of the University of Pittsburgh Health Center. Each subject, or more specifically, the target organ within the subject, is considered to reside in Signal Space. This space is interrogated in three

ways. A standard B-scan is made using commercial

equipment (Picker Echoview) and, at the same time, several A-scans are digitized using a specialpurpose, digitizing system (Stahl Research Labs.).

Finally, in addition to the ultrasonogram and the digitally recorded A-scan, a tissue biopsy is made

of the organ under examination. These interrogations furnish information which constitutes what we

term "Data Space.

A visual diagnosis is made from the ultrasonogram by the staff of the Ultrasound Laboratory and

is combined with the histopathological diagnosis

carried out by the Department of Pathology. This

furnishes information on disease type and severity.

At the same time a numerical analysis is performed

on the digitized A-scan using the statistical methods described below. These various methods of analysis of the information in Data Space provide

us with numerical information which is contained in Measurement Space. These measurements, taken over

a population of patients, are then processed in a supervised fashion (correlation of measurements with predetermined disease types) using a standard

discriminant function software package (University

of California BMD07M) to generate points in Classification Space. Finally, images of the tissue biopsy are digitized by the Biomedical Image Processing

Group at Jet Propulsion Laboratory and analyzed

using the Biomedical Image Processing Unit of the Department of Radiation Health at the University of

303
Pittsburgh. The balance of this paper discusses

A-scan digitizations, A-scan analysis, image digitization and processing, and reports results to date

in these areas.

2. Materials and Methods

The ultrasound digitizer is the basic unit used

for digitizing A-scans. The digitizer (Stahl Re- search Labs, model 4036) is a complete digitizing

system rather than a simple analog/digital con- verter. Its block diagram is shown in figure 1. The unit requires only two inputs, namely a syn- chronizing or gating signal and the analog wave- form to be digitized and stored. The digitizer

runs under control of an internal 15 megahertz clock. Burst length and skip burst values are entered using digi switches on the control panel of the model

4036. When a synchronizing pulse is received, the digitizer proceeds to sample and digitize the input

data at a 15 megahertz rate until the number of words stored equals the burst length. The unit then begins counting additional synchronizing pulses until the count has reached the number set for the skip

burst. When this count has been reached, the next synchronizing pulse causes another burst to be digitized. This continues until the 4096 word memory is full (each word is one 8-bit byte). At the present

time we are using a burst length of 128 which cor- responds to 8.5 microseconds of recorded signal over which the pulse-echoes are received from about

0.65 centimeter of tissue.

The digitizer incorporates a modem and complete memory teletype (Texas Instruments model 700) having

twin digital cassettes each of which is capable of storing 250,000 words of digitized A-scan data. When the user desires to transmit data to a remote

computer, the modem is interfaced via the telephone

system, a dial-up connection is made, and the digital cassettes are activated and transfer their data

via the communication link. In our present program

the computer used is a Digital Equipment Corporation PDPIO model KA at Carnegie-Mellon University.

In all experiments to date, the A-scan is digitized directly from the output of the radio frequency (rf) amplifier. The unit employed for both pulsing the transducer and amplifying the A-scan is a Panametrics model 5055 custom-modified to provide

bandwidth to 20 MHz. In our experiments we have used the model 5055 at its full gain setting (60 dB) and with full bandwidth with the interval damping

resistor set to 250 ohms. The organs of interest

have been the liver and kidney for which we obtain

signal levels at the output of the model 5055 rf amplifier ranging from a few tens to a few hundreds

of millivolts. (The least significant digit of the digitizer corresponds to approximately 8 millivolts.)

The transducer utilized is a Panametrics custom- made biopsy transducer whose characteristics have

been measured by the Acoustics Branch, National Bureau of Standards, and are presented in figure 2. As can be seen, the resonant frequency is close to

4 MHz with a 25 percent 3 dB bandwidth.

Fig. 2. Transducer 1-way frequency response as determined by the National Bureau of Standards

.

MODE CONTROL EXTERNAL TRIGGER EXTERNAL SYNC ANALOG DATA

BURST

WORD

AUDIT

15 MHz CLOCK SKIP BURST CONTROL

0,32, •• , 512 BURST LENGTH

1 28,256, ••4096

BURSTS PER BLOCK

RECYCLE RATE

MEMORY UPDATE (FIXED RECYCLE)

PITCH CONTROL

DIGITAL/ANALOG CONVERTER UART

SINGLE SIDEBAND MODULATOR TI700

TELETYPE

SLOW AGC MODEM

4096 WORD

HIGH-SPEED MEMORY

TWIN

DIGITAL CASSETTES

EAPHONES DIGITAL COMMUNICATIONS CHANNEL

Fig. 1. Block diagram showing the three modes of operation of the Stahl Research

Laboratory model 4036 digitizer.

304
SAMPl ( IHC( 5 J

Fig. 3. Five signal regimes for the normal liver:

(a) normalized rf waveform; (b) rectified;

(c) video; (d) frequency spectrum; (e) deconvolved spectrum. Here time samples

are taken each 100 ns with the frequency

domain covering 0 to 5 MHz in 0.08 MHz intervals.

3. A-Scan Analysis

Five signal regimes (see figs. 3 and 4) are used

in the analysis of the waveform: (1) Direct rf waveform, (2) Rectified rf waveform, (3) Video waveform (the rf envelope), (4) The rf Wiener spectrum,

(5) The selectively deconvolved rf Wiener spectrum.

For regime (5) the frequency spectrum of the trans- mitted signal is used to normalize the spectrum of the received A-scan, except at those frequencies

where the uncertainty in determining the transmitted

spectrum is large. Computationally, the selectively

deconvolved spectrum D(a)) is given by

S.(co) / 1 \ / \

D(co) = + S . (t.) S fo)) \l + c2/ ' \1 + c2/

Fig. 4. The five signal regimes in the same order

as in figure 7 for the normal kidney.

Figure 5 shows a computer generated graph of four sequential pulse echoes from a phantom consisting

of a multiplicity of polyethylene disks immersed in water. This figure shows the graphical plot (above) and (below) a graytone M-scan rendition. The slight

shift in pulse position which is evident in the M- scan output is an artifact due to synchronization

problems. The pulse consists of about four cycles

at the resonant frequency of the transducer and is,

therefore, about one microsecond in duration. Fig- ure 6 shows the Wiener spectra of the same four

pulses presented in figure 5.

Fig. 5. Digitally produced A-scan plots and M-mode

graphs of pulse-echoes reflected from a plane surface.

where S^-(a)) is the spectrum of the direct rf signal,

Sp(u) is the spectrum of the transmitted signal from which the A-scan echoes are produced, and quantity

c is the coefficient of variation of the transmitted

pulsed (taken over an ensemble of transmitted

(pulses). This quantity is in itself a function

of the frequency o). Fig. 6. The frequency spectra corresponding to the pulse-echoes shown in figure 9.

305
Using a burst length of 128 words, the full memory holds 32 bursts. We are currently employing two settings of skip burst, namely, 0 and 256.

At a skip burst setting of 0 the entire recording

takes place during 32 pulses which, with the Picker Echoview running at a PRF of 1 kHz, takes 32 milliseconds. The skip burst setting of 256 lengthens the recording interval to 8 seconds.

A comparison of recordings taken at the two skip burst settings provides a measure of signal sta- tionarity (see figs. 7 through 14).

\y\A^/^— --w\/^^^

\/\/\/\— \I^J\/^/^^^—^— — —-^.'v^

Fig. 7. Thirty-two pulse-echoes obtained from a normal region of the human kidney in vivo . Echo separation is a 0.001 second.

Observation of figures 12 and 14, which were

taken at the skip burst 256 setting, indicate that long-term stability of the frequency spectrum does

not exist. This observation raises some doubt as to the validity of spectral measurements which have

been previously reported in the literature for use

in tissue identification. Most researchers using

spectral signatures have neither considered nor even discussed short-term versus long-term stability problems. In using the A-scan as a tissue signature, these researchers must remember that all observations in vivo are of a dynamic system. Even with held inspiration, the organ in the patient is moving throughout the cardiac cycle and, in typical

clinical ultrasound laboratories using scanners with

hand-held transducers, further movement is intro- duced through the inability of the ultrasonographer

to hold the transducer steady.

~'j;^\^\/'^-~-'^~^\f\/^ sA^ ^^^.A^—-^-^N^^vVXy

^ ^/V^

^-^Aa /V^--^\/Va^-— ——/-vysy^w'-'- ^^\/^--^^>^^^v\AFig. 8, Thirty-two pulse-echoes obtained from a carcinomic region of the same kidney en- sonified in preparing the data shown in figure 11. Pulse-to-pulse separation is 0.001 second.

Fig. 9. The thirty-two frequency spectra corresponding to the A-scans shown in figure 11.

306
--W^/\/\a.^^yV5{/\/\A/V/%^ --v-^V— -^^^

—\/\y\/\/^^v—v/\yV--N/\^—^yAyvx/^.-^^^—-—^-—

^''^-^-^YA-yv——^-7—

^XXAA/^-^^"^ ^~—^—~\^^\yx^v^\/v — —-—-^yY\7V'-V\/\AA^^-~-'^^wV\^~—.^v—

Fig. 10. The thirty-two frequency spectra corre- Fig. 12. Thirty-two pulse-echoes obtained from spending to the A-scans shown in figure 12. a carcinomic region of the same kidney,

again with a pulse-to-pulse separation

of 0.25 second.

Fig. n Thirty-two pulse-echoes obtained on a long-term basis from a normal region of the same kidney ensonified in preparing

the data shown in figure 11. Pulse-topulse separation is 0.25 second.

2.W1HI 3,9nHi

Fig. 13. The thirty-two frequency spectra corre- sponding to the A-scans shown in figure 16.

307
Fig. 14. The thirty-two frequency spectra corre- sponding to the A-scans shown in figure 16.

4. Data Reduction

In the early 1970s Mountford and Wells [3,8,9]

described their work in the quantitative analysis

of A-scans taken from normal and cirrhotic livers. Initially their data was obtained from oscilloscope

photographs of the rf A-scan obtained from the sub- coastal examination of supine patients through the anterior abdominal wall (the same physiological ap- proach taken in our own work). Thirty A-scan oscillograms were recorded per patient over a population

of 30 normal and 13 cirrhotics using an ultrasonic

frequency of 1.5 MHz (with an unrecorded bandwidth). One hundred data points were recorded for each A- scan over a time-span of 65 microseconds which cor- responds to approximately 4.8 centimeters of tissue

(digitizations started at approximately 5 centi- meters beyond the anterior abdominal wall). Mea- sures were made which related to signal amplitude,

the rate of change of signal amplitude, frequencies,

rise-times, fall-times, peak-to-peak amplitudes,

etc. The most significant of these measures in separating the normal from the cirrhotic liver

(using Student's t-test) are tabulated below.

Measure t-test

Rate of mean amplitude decay 1 28 Mean echo amplitude at intercept 12 38 Mean echo amplitude at mid-point 13 31 Mean trough-to-peak rise-time 4 20 Mean peak-to-trough fall-time 2 39 Mean trough-to-peak amplitude 2 07 Total number of troughs 3 55 Total number of peaks 3 59

As can be seen the most successful measure is the mean echo amplitude at the mid-point of the timewindow. The associated t-test value indicates an extremely high success rate in separating normals

from cirrhotics over this particular patient population. Other significant measures are the mean risetime and the total number of peaks and troughs. It

is somewhat surprising, since these measures directly relate to the frequency of the signal, that the authors state that "(the) restricted bandwidth of the system used in the present study appears to prejudice the possible use of frequency spectrum

analysis as a diagnostic index."

Subsequent to the above-reported experiment the authors modified their experimental approach, dis- carded photographic recording of the A-scan, and de- veloped equipment for real-time digitization. In their second experiment 100 time-samples were extracted per patient the sampling interval being 0.1 microsecond (corresponding to a tissue span of 2 centimeters). The initiation point of their digitizations

was 6.5 centimeters beyond the anterior abdominal

wall. Ten normals and three cirrhotics were examined with 180 A-scans recorded in interrupted quiet

respiration and an additional 180 A-scans recorded

at held maximal inspiration (except for cirrhotics in which recordings were made only at held maximal in- spiration). In the second experiment the only mea- sures reported were the rate of mean echo amplitude

decay and the mean echo amplitude and intercept. The frequency utilized was 1.67 MHz and it can be inferred from the authors' discussion that the pulse

duration was approximately 3 microseconds. The sam- pling aperture was 12 ns with digitization at 6-bits. Because of the small sample size the t-test was not calculated, but it was found, as before, that the mean echo amplitude at mid-point (for held maximal

inspiration) could successfully be used to separate

normals from cirrhotics. Interestingly, the data spread in this experiment appears to be far greater

than in the initial experiment indicating that the earlier low error rate values may be subject to question. After these first two experiments were conducted, no further investigations apparently have

been carried out. Our own analysis has gone beyond that of Mountford and Wells in that there is equal emphasis on both frequency-domain analysis and time-series

analysis. The analysis has been carried out according to traditional statistical lines (see, for ex- ample, Wilks [10]). This approach also appears to have been taken by Decker et al. [11] at the University of Bonn, in the analysis of A-scans taken from the eye. In our own work we consider each of the five regimes of our data as a tissue signature

and, for each A-scan recording for each subject,

make the same statistical measures. The signature

is represented as follows:

Signature = f (x^

)

i = 1,. .

. ,128

The function f may represent any one of the five

signal regimes. In other words, it may be either

the rf recording, the rectified rf, the envelope of the rf, or the Wiener spectrum or deconvolved Wiener

spectrum of the rf.

Measures With Respect to the Argument

Eight measures are made with respect to the argu- ment X. Before making these measures the function

is normalized in the following manner:

308
= 1

This normalization is applied to both time-series

and frequency-domain data and can be thought of as

a normalization to a standard acoustic pressure for

the time-series data and to a standard acoustic

povver for the frequency-domain data. After normalization sunmations are carried out over four "bins"

of the data points as follov/s:

N th

i 3M

N = 1 n = 2 N = 3 N = 4

= 0-15

= 16-31

= 32-47

= 48-63

This produces the first 4 measures for each regime. Next the moments of f are calculated as follows:

„th Moment = T. - 0^f{x.) N = 2,3,4

x.f(x.)

The above equations produce 8 measures v/ith re- spect to the argument x. Next the statistical

properties of the values of f are computed. A histogram or probability density function of the

values of f is calculated and called p(yj) v/here

p is the likelihood that f has the value yj. The

probability density function is normalized to 0 mean and unit variance as follov/s:

0 1

This normalization once again insures that arbitrary

settings in acoustic amplification and on received

power levels do not effect the results. (Note that,

in contradistinction to the experiments by Mountford

and Wells, we do not operate a system which has open-loop control on the transmitted and received

signal levels but, rather, operate in an arbitrary

level mode). Once the function p has been computed, we record its third and fourth moment v/hich, of

course, are proportional to the skew and kurtosis of

this function, respectively.

Then the co-occurrence matrix or diagram is generated, i.e., p(yj,y|^) which is the likelihood

that two adjacent values of f have precisely the values yj and y|^. This function is tv/o-dimensional

and may be represented using a scatter plot of the values yj and y|^ as is shov;n in figure 15. As can

be seen from figure 15, an ellipse may be fitted to the data from which v/e compute eigenvectors (the

major and minor axes), eigenangle (the angle made to the yj axis), and the eigenvolume (area of the el- lipse) . Finally, the 3-gram is computed. Since there are

only 128 values of f, a three-dimensional scattergram is sparsely filled from a statistical point of view so that, rather than fitting a three-dimensional ellipsoid, an 8-bin histogram is computed with

the values of f inarized with respect to a threshold

equal to the mean value of f so that the bins of the histogram are given by

(yj.yk^y^)

= 000,000,. ..,111

Fig. 15. The di-gram (scatter plot) corresponding

to a single A-scan taken from a normal liver using 5-bit digitization over 28 points taken at 100 ns intervals.

The range of this binary 3-gram is then entered as the final measurement. This leads to 8 measures

with respect to the argument x, 2 measures related

to first order probability, 3 measures related to second order probability, and 1 measure of third

order probability. Since all of these measures are computed for each of the five data regimes, a total of 14 measures are made per regime, leading to 70 measurements per A-scan.

5. Biopsy Tissue Image Analysis

As mentioned in Section 1, biopsied tissue is being prepared not only for visual examination but also computer analysis. Using standard 4 m thick

tissue slices stained with hematoxyl in-eosin and mounted on microscope slides, the Automatic Light

Microscope Scanner (ALMS) at the Jet Propulsion

Laboratory produces 512 x 512 pixel (picture point)

digitizations of the previously ensonified sample

as shown in figures 16 and 17. Each image field is approximately 0.5 millimeter square selected so that

a statistically sufficient number of various tissue

cell types are displayed. A software system, called AUTOPIC, was written incorporating cellular logic

commands for image analysis in the Cartesian tes- sellation patterned after the hexagonal parallel

pattern transforms of Golay [12]. These transforms

have been found useful by Preston [l3,14] in the analysis of images of human white blood cells, chest

x-rays, ophthalmol ogical ultrasonograms, etc. Using AUTOPIC applied to the images shown in figures 16 and 17 normal cell nuclei and i nf 1 anmatory cell nuclei v;ere located (figs. 18 and 19) using a com- mand sequence which caused the analysis flow-charted

in figure 20 to be carried out. Since an increase

of inflammatory cells (called "microcytes" in fig.

20) is an indicator of disease, this analysis pro- vides an index of histopathology which may be cor- related with the A-scan measures to determine the relevance of these measures in assaying disease

entities.

309
Fig. 16. Computer generated graytone image

of a 0.5 X 0.5 mm region in an eosin-hematoxyl in stained tissue

section from a normal rabbit kidney.

Fig. 17. Graytone image (0.5 x 0.5 mm) of

pyel onephri tic rabbit kidney tissue.

Fig. 18. Computer analysis of the normal rabbit kidney tissue image shown

in figure 16 showing an overlay

of white squares and white circles

to indicate nuclei classified as microcytes and macrocytes,

respectively.

Fig. 19. Computer analysis of the pyelonephritic rabbit kidney tissue image

(fig. 17) showing a microcytes and macrocytes as in figure 18.

6. Results

Most of the program to date has been allocated to both the construction and calibration of hardware

and to the development of a software system for both

the computation and graphical display of the data gathered. In this paper we report on our first

human biopsy patient, a female aged 64 years, whose

pathology was a large carcinoma of the kidney. By

observation of the B-scan the region to be digitized

is readily located. Using the equipment described

in Section 2, the A-scans given in figures 7 through

14 were recorded. Thirty-two of these A-scans were of normal kidney

tissue and 32 of the carcinoma. Using the short- term data given in fig ures 7 through 10, all 70 mea- sures were examined for the 64 recordings and the two measures most useful in differentiating normal

and pathological tissue were found to be the second moment with respect to the argument x where x was selected in the frequency-domain and the contents of the second bin (or quartile) of the rectified time310
GRAY SCALE IMAGE COPY

[5]

^ MASK

SELECT 128 WINDOW [l]_ rBLOCKLj

i] —

I—n L

THRESHOLD

FOR DARK OBJECTS [2]

REMOVE SMALL DARK OBJECTS FORM MASK HFOR LARGE DARK OBJECTS [5-6] THRESHOLD FOR MODERATELY DARK|_

OBJECTS [9]

REPLICATE POSSIBLE M I CR0CY1ES

[10-45] MICROCYTES

REPLICATE NON MACROCYTES

[6 9-88]

DECREMENT AND CONTINUE REPLI- COPY THRESHOLD CATION OF POSSIBLE RESULT

AGAIN [48] MICROCYTES [49-64] [46]

SUBTRACT

[65-66]

STEREO TYPE MACROCYTE

RESIDUES [1 31 - I 34]

COUNT

AND OUTPUT

[136-1 37

COPY 1 SUBTRACT [I27]t— [129-130]

REMOVE

NOISE

[68]

REDUCE TO RESIDUES

[126-126]

ERASE

RESIDUES

[128]

SUBTRACT REMOVE REDUCE IN [89-90] NOISE [91 ] SIZE[i08] THRESHOLD FOR MODERATELY

DARK OBJECTS [92]

OBTAIN MACROCYTES

[12 4]

FORM MICROCYTE MASK [121-123]

COPY SUBTRACT COMBINE REDUCE TO RESIDUES

[10 3]

f

[1O5-IO6]

t -

[109- 111] [112-114] REMOVE

NOISE [95-99]

REDUCE SMALL -H OBJECTS TO

RESIDUEs[lOO-l02]

ERASE

RESIDUES

[104]

GENERATE

MICROCYTE

STEREO TYPE

[11 5-1 1 7]

COUNT

AND OUTPUT

[119-120]

Fig. 20. Block flow chart of the image analysis program carried out in the digital

computer analysis of the tissue images shown in figures 16 and 17.

series. Scatter plots of these measures are shown

in figure 21 for the 32 A-scans of both the normal kidney and the abnormal kidney under short-term con- ditions. The Mahalanobis Distance was taken as a measure of separability and indicates a high degree

of confidence in telling these two types of tissues

apart. However, when the A-scan data taken under long-term conditions (figs. 11 through 14) were

utilized, the Mahalanobis Distance indicated some- what worse differentiation between the two types

of tissue (fig. 22) typifying the effects of the dynamic variability of the A-scan. The other experiment which is reported here in- volved the introduction of pyelonephritis in the

animal kidney and the comparative analysis of A- scan data and histologic data derived from images

of biopsies of the ensonified tissue. The animal

model selected was the rabbit. The disease was introduced unilaterally. At the acute stage, four weeks after introduction of the disease, the kidneys (both normal and abnormal) were operatively exposed and 128 A-scans were re- corded for each organ via a 6 cm water bath coupler

suggested by Dr. Goans of the Oak Ridge National

Laboratory. This avoided signal corruption by in- - tervening tissue. Results of the A-scan analysis (for animal R06) are shown in figure 23, which is a scattergram of the data on 256 A-scans taken in groups of 32 in 8 second intervals over several minutes using the

two best computer measures for separating normal from abnormal. The Mahalanobis Distance is 3.2

and the classification success rate is 98 percent.

Similar results (100% classification) were ob- tained for the tissue image analysis (fig. 24) using

a single measure, i.e., the count of microcyte density in the four 0.25 x 0.25 mm regions shown in figures 17 and 19. Pictorial and A-scan data taken

from six other animals is now being analyzed.

' .0 75.0 150.0 225.0 300.0 375.0 450. 0 525.0 PSM2

104: Tumor vs. Normal (32 ms )

Fig. 21. Scatter plot of 64 points in a 2-coordinate

space representing the best measures for differentiating ultrasonic pulse echoes

from those received from carcinomic human kidney tissue in vivo . The coordinates

are the variance of the power spectrum

(PSM2) and the second quartile sum of the rectified waveform (RED2). The plot is derived from the short-term data shown in figures 7-10.

311
Fig.

75.0 150.0 225.0 300.0 375.0 450.0 525.0 PSMZ

104: Tumor us. Normal

22. Scatter plot similar to figure 23 using

data extracted from figures 11-14 showing A-scan information gathered in the long- term (8 seconds). Dynamic variance of the data causes the classification success to drop to 87 percent for normal human kidney

tissue and to 91 percent for carcinomic

human kidney tissue.

SJ I

I I I

^ Normal

I I Abnormal

55 220Number of microcytes

per quadrant

Fig. 24. Histogram based on the microcyte count per quadrant (0.25 x 25 mm) in figures 18 and

19 showing 100 percent success in computerized differentiation between normal and pyelonephri tic rabbit kidney tissue images. The microcyte count is indicative of in- flammation and is significantly higher in pyel onephri ti s

.

o

log

log(Pr,D4) n06: Pyalo vs. Normal

Fig. 23. Scatter plot of 256 points using the two measures which were found to be best for distinguishing ultrasonic echoes from

normal and pyelonephritic rabbit kidney

in vivo . These measures are the fourth moment of the power spectrum (PSD4) and

the variance (second moment) of the rec- tified signal data histogram. Classification success for this long-term data

is 100 percent for normal tissue; 93 percent for pyelonephritic.

7. Acknowledgements _

In addition to the workers and colleagues

acknowledged in the text, the authors would like

to acknowledge the work of Dr. Niel Wald, Chairman

of the Department of Radiation Health, University

of Pittsburgh and the staff of his Biomedical Image

Processing Group, Jet Propulsion Laboratories for assistance in image analysis and recording; Dr. Donald Eitzen, Ultrasonic Standard Group, National

Engineering Laboratory, National Bureau of Standards,

and his staff for performing the calibration of our tranducer; Dr. Frank Fry, Ultrasound Research

Laboratories, Indianapolis Center for Advanced

Research, and his students for calibration of the beam pattern of the transducer and measurements of

its performance using phantoms; Drs. Andrew Dekker,

Denis Borochovitz, Jeffrey D. Hubbard, University

of Pittsburgh Health Center, for visual reading

and reporting on tissue section pathology; Dr. Terrance Matzuk, consultant, for providing ultra- sound interface electronics; Mr. Gilbert Arnold,

Mellon Institute, and his staff for providing the illustrations; Mrs. Tanya Rogers, Department of

E-lectrical Engineering, Carnegie-Mellon University

for typing the manuscript.

312
References

[1] Wild, J. J. and Reid, J. M., Application of echo ranging techniques to the determination

of structure of biological tissue. Science

115 . 226 (1952).

[2] Fry, E., Okuyama , D. , and Fry, F. J., Ultrasonic differentiation of normal liver structure as a function of age and species, Proc. 6th Inte rn' 1. Cong, on Acoustics , Tokyo (1968).

[3] Mountford, R. A. et al . , Ultrasonic liver

scanning: automatic A-scan analysis. Physics

in Medicine and Biology 17, 559-569 (1973).

[4] Ossoinig, K. C, Quantitative echography - the basis of tissue differentiation, J. Clin . Ultrasound 1, 190 (1973).

[5] Fields, S. and Dunn, F., Correlation of echo- graphic visualizability of tissue with bio- logical composition and physiological state,

J. Acoust. Soc. Amer . 54, 809 (1973).

[6] Taylor, K. J. W. and Milan, J., Digital A- Scan Analysis in the Diagnosis of Chronic

Splenic Etilargement, in Ultrason ic Tissue

Characterization , M. Linzer, ed.. National Bureau of Standards Special Publication

453, pp. 71-80 (U.S. Government Printing

Office, Washington, D.C., 1976).

[7] Preston, K. , Jr., Use of Pattern Recognition

for Signal Processing in Ultrasonic Histopathology, in Ultrasonic Tissue Characterization , M. Linzer, ed.. National Bureau of Standards Special Publication 453, pp. 51-60

(U.S. Government Printing Office, Washington,

D.C., 1976).

[8] Mountford, R. A. and Wells, P. N. T., Ultrasonic liver scanning: the quantitative

analysis of the normal A-scan, Physics in Medicine and Biology 17, 14-24 (1972a).

[9] Mountford, R. A. and Wells, P. N. T., Ultrasonic liver scanning: the A-scan in cir- rhosis. Physics in Medicine and Biology 17, 261-269 (1972b).

[10] Wilks, W., Mathematical Statistics , Wiley

(1963).

[11] Decker, D. , Epple, E., Leiss, W., and Nagel

,

M. , Digital computer analysis of timeamplitude ultrasonograms from the human eye,

J. Clin. Ultrasound 1 (2), 150 (1973).

[12] Golay, M. J. E. , Hexagonal parallel pattern

transforms, IEEE Trans. Comput . C-18 , 733

(1969)

[13] Preston, K. , Jr. and Onoe, M. , Digital Proc - essing of Biomedical Images , Plenum Press

(1976).

[14] Preston, K., Jr., Application of the Golay

Transform to Image Analysis, in Digital

Image Processing and Analysis , 1' Institute

de Recherche d Informatique et d ' Automatique

,

Paris (1976).

313

CHAPTER 10

TISSUE VIABILITY AND TISSUE PHANTOMS

315
i

!

i,
Reprinted from Ultrasonic Tissue Characterization II, M. Linzer, ed., National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C., 1979).

DAMAGE AND DEATH IN TISSUES AND ASSOCIATED CHANGES IN THEIR MECHANICAL PROPERTIES

L. Weiss

Roswell Park Memorial Institute

Buffalo, New York 14263, U.S.A.

Mechanical effects of tissue damage associated with artefactual change during

examination, and that developing naturally during tumor development, have been de- monstrated by a quantitated cell detachment test. Although the precise relationship

between this semi-destructive test of tissue properties and ultrasonic, nondestructive tests is uncertain, it appears feasible to consider the following points In studies of the interaction of ultrasound with tissue specimens: a) thin specimens

should be examined quickly to avoid anoxic and hypoxic damage; b) note must be made

of the heterogeneities within solid tumors, particularly those produced by necrosis;

c) degenerative changes in a tumor and surrounding non-malignant tissues may act as image-enhancers

Key words: Cell detachment; mechanical properties; tissue damage; tissue death.

1. Introduction 2. Cell Detachment from Tissues

The interactions of ultrasound with tissues. Cylinders are punched from tissues using a 13 depends in a sense on their mechanical properties. gauge ("^ 2 mm) trocar and cannula, and these are then divided into 1 or 2 mm lengths over a scale, under magnification. Two such cylinders are placed

into each of a number of screw-capped, glass vials,

4.5 cm long and 1.3 cm diameter, containing 2 ml of cold Hanks' balanced saline solution. These operations, which take 20 to 30 minutes, are all done in solutions at 4 °C to minimize metabolic

di fferences

The vials are clamped onto a reciprocating

shaker, making 275 oscillations per minute, with

an excursion of 4.5 cm, for 40 minutes, at room temperature (25 °C). In some experiments, tissue

cylinders were shaken for 10 minutes only. After

shaking, 0.25 ml of 10 percent buffered formaldehyde is added to each vial and mixed by gentle

inversion. When present, the macroscopic remains

of the cylinders rapidly settle to the bottoms of

the vials, and the released cells and cell clusters

in the supernatant fluid are counted in a Fuchs- Rosenthal chamber, and their diameters measured

with an image-splitting eyepiece (Vickers-A. E. I .

England) at a final magnification of X300. It has previously been demonstrated that the described

formaldehyde-fixation does not affect these two numerical determinations.

An estimate of the volume of tissue liberated

by shaking was obtained from the product of the cube of the mean "particle" radius and the mean

number of such cell units. Volume functions of

this type are used for purposes of comparison.

Small pieces of tissue were fixed in formalin

and subsequently examined in 4 ym stained sections.

Aliquots of liberated cells are centrifuged onto

In this presentation, tv;o facets of tissue damage

will be examined from a mechanical viewpoint.

The first is a consideration of the hypoxia which

results and its possible artefactual effects, when

pieces of tissue are examined. The second is a consideration of the mechanical heterogeneity in and around solid cancers.

The mechanical properties of tissues depend

partially on the properties of their individual

cells and partially on the properties of the material lying between them, in much the same way

as the properties of a brick wall depends on the properties of the bricks, the mortar and the bonds between them. Tissue properties may be measured

by nondestructive techniques, such as those in- volving ultrasound, or by destructive techniques

which result in reduction of the tissue into either

subcellular dimensions, or into its component living cells. The release of living cells from tissues have been studied, particularly solid cancers,

as part of a program on the mechanisms of metastasis [1-3]^. In this work, quite sensitive

quantitative techniques have been developed to measure cell detachment, which is dependent on the strength of the intercellular material. In tissues,

the intercellular material represents a modification of the extramembranous , peripheral regions of cells which is rich in glycoproteins.

^Figures in brackets indicate literature

references at the end of this paper.

317
slides (Cytospin: Shandon-Ell iott, England), and morphologically characterized after reaction with

Wright's stain. A full description of the tech- nique and its use is given elsewhere [4]. The cell detachment test described here is non- destructive as far as the component cells of a tissue are concerned, and their viscoelastic properties must play a role in cell detachment. However, as- suming that the plane of detachment lies within the

cell periphery/intercellular region, then the tests

are destructive for this tissue component in the sense that they are essentially concerned with ob- taining a "yield-point". In contrast, the ultrasonic techniques discussed here are completely non- destructive. Thus, although the precise relationship of the two techniques is problematical and the results are expected to be somewhat different in general terms it would be expected that changes in tissues detected by one procedure might well be re- flected in the other. Proposed work will hopefully

clarify this relationship, which at present is simply presented as a working hypothesis.

3. Examination Artefacts

In determining parameters of the interactions

of ultrasound with tissues, the tissues them- selves are held in a tank of fluid in the ultrasonic beam, for varying periods of time. From many biologically oriented studies, it is wellknown that unless the fluid is of physiologic

tonicity and pH, and that unless the tissues themselves are well -oxygenated , tissue damage will occur. The relevant question is, how much artefactual alteration will be produced in the ultra- sound/tissue interaction by this damage?

From a practical viewpoint, it is unnecessary

to investigate the effects of unphysiologic fluids

on the interactions, because many solutions are available which maintain optimal conditions of ionic strength and constitution, pH etc . [5]. However, one outstanding problem is the possibility

of inadequate tissue oxygenation, and the con- sequences of it. In the case of isolated tissue

slices, Warburg [6] showed that their limiting

thickness in cm (H) for O2 consumption, where D is the diffusion coefficient, A is the rate of respiration of the tissue (ml O2 uptake/ml

tissue/minute), and [O2] is the oxygen concentration in the atmosphere surrounding the tissue,

then:

H = (8-D-[02]/A)''= .

Thus, in pure oxygen, the maximum thickness of tissue permitting the passive penetration of O2 to its center is 0.47 mm. In air ([O2] = 21 percent) the corresponding maximal thickness of tissue is only

0.21 mm. Similar considerations have to be taken

into account in determining the depth of fluid

covering examined tissues. Studies on the kinetics

of gas diffusion in cell culture systems by Mc- Limans et al . [7] have demonstrated that as pre- dicted by Fick's Law, the passive diffusion of oxygen through unstirred fluid to actively metabolizing tissues is very sensitive to the depth of fluid, and that in the case of isolated liver cells covered by only 1.6 mm of physiologic saline, the

total initial equilibrated concentration of oxygen

will be exhausted in only 1280 seconds, normal biologic syntheses will be impaired and, if left under these conditions, the cells will die.

In order to get a feeling for ti ssue-oxygenation

under the conditions in which ultrasonic tissue

characterization experiments will be made, freshly

isolated cylinders of rat liver 1 cm in diameter

and 0.5 cm in length, were obtained from exsanguinated rats. These were then placed in a beaker

containing 100 ml Hanks' balanced saline solution,

a commonly used mammalian "physiologic" solution,

buffered at pH 7.2, and maintained at 37 °C. The

PO2 was measured at various depths in the liver

cylinder determined with a micrometer, with oxygen ultramicroelectrodes having a tip diameter of

15 pm. The electrode has been described elsewhere

[8]. It was shown that in the five minutes re- quired to start measurements after removal of the liver cylinders, the oxygen tensions at depths of

1 to 2.5 mm were near zero, and at a depth of 0.5 mm, they were approximately 60 mmHg. These measurements compare with mean values for the liver

in the unanesthetized, spontaneously respiring rat of 20 to 30 mmHq [9]. Thus, there is good reason

for considering the effects of hypoxia in ultra- sonic experiments, since in most of these, com- paratively thick pieces of tissues are used.

It has been shown that lysosomal changes in rat hepatic parenchymal cells are induced by sub- jecting animals to hypoxia [10]. It has also

been shown that activation of lysosomes with re- lease of lysosomal enzymes into the tissues can cause massive tissue degradation [11] within

hours, and changes detectable by cell detachment

tests on cellular monolayers, within 2 minutes

[12].

In order to determine if the treatment of the

1 cm diameter cylinders leading to anoxia or hypoxia resulted in analogous changes, shakingtests of the type described earlier were made on this material. After incubation in Hanks' solution at 37 °C for periods up to 2 hours, plugs were cut from the 1 cm cylinders, and the volumes

of cells released at the different times, from the outermost 1 mm regions near to the cut surface and

the innermost 2 mm thick regions at the center of

the 5 mm thick cylinder were compared. The re- sults shown in table 1 indicate that greater

(.02 > p > .01) volumes of parenchymal cells are released from the inner anoxic region at the center of liver cylinders than from the outer

parts. During the experiments, detectable amounts

of protein and acid phosphatase (a lysosomal hydrolase) are released into the medium, but this facet

of the experiments needs developing.

It should be noted that examination of standard histologic preparations of the liver revealed no clear-cut evidence of damage after 2 hours incubation, and would not have permitted predictions of the detachment experiments. It is of interest

that Hueter, in experiments cited by Dunn [13] was unable to detect changes in the ultrasonic absorption coefficient of liver, measured over the range

of 1 to 6 MHz, until 9 hours after death, when it progressively decreased. It is difficult to com- pare these experiments with those reported here,

since Hueter 's were made at 25 °C (c.f. 37°) and

the tissue was maintained at 10 °C between measurements, and it is well-known that reduction in tem- perature retards post-mortem change. Future work

will hopefully clarify the correlation between changes detected by the shaking test and ultrasound.

If degenerative, autolytic changes due to lysosomal mobilization prove to be an inconvenience

318
Table 1. Release of liver parenchymal cells.

Incubation Sites Numbers of cells Unit diameters Comparative

time released (xlOOO) (pm) + SE volumes released

(minutes) ± SE (n) (n) Inner : Outer

Experiment 1

30 Inner 57 + 7. 3 (13) 10.5 + 0. 14 (161) 1 1 8 30 Outer 37 + 4. 9 (16) 10.0 + 0. 13 (110)

60 Inner 20 + 3 5 (14) 10.0 + 0. 15 (131) 1 1 4 60 Outer 15 + 1 5 (13) 9.9 + 0 13 (107)

120 Inner 16 + 0 7 (8) 10.5 + 0. 39 (100) 1 1 5 120 Outer 12 + 1 9 (12) 10.0 + 0 27 (105)

Experiment 2

30 Inner 16 + 2 8 (8) 10.0 + 0 11 (102) 1 1 9 30 Outer 10 + 2 7 (9) 9.5 + 0 11 (94)

60 Inner 15 + 4 0 (6) 9.6 + 0 13 (136) 1 1 2 60 Outer 13 + 3 4 (6) 9.4 + 0 08 (154)

120 Inner 13 + 1 9 (9) 9.9 + 0 09 (111) 1 1 .5 120 Outer 10 + 2 4 (8) 9.4 + 0 12 (98)

in ultrasonic measurements, it is worthy of note

that the analogous changes observed in vitro [11,

12] were inhibited and/or retarded by adding small quantities (c. 10 yg/ml ) of hydrocortisone hexisuccinate to the medium.

4. Mechanical Heterogeneity in Tumors

The essence of the successful treatments of cancer is early diagnosis. In the breast for ex- ample it can be seen (fig. 1) that depending on the clinical type [14], the probability of metastasis varies considerably with the size of the cancer at the time of diagnosis. In the most malignant (Type A) the slowest rate of increased

probability of metastasis, where therapeutic in- tervention would be most effective, is in lesions

of 1 to 7 mm diameter. In the least malignant

(Type B), there is an increased probability of metastasis from 22 to 36 percent, as the lesion

increases in diameter from 1 to 5 mm. It is therefore pertinent to ask whether changes in or around

a cancer as it develops can so modify the mechanical properties of the cancer itself or the sur- rounding nonmalignant tissues, that the image of

the tumor is enhanced and/or changes in the sur- rounding tissues effectively increase the "lesion"

size. From previous considerations of examination of artefacts, the question arises of whether various

tissue interactions caused by, or resulting in de- generative change in a solid cancer could fill this role of "image enhancer". Cell death, or necrosis

is a salient feature of many solid cancers. One contributory cause of this is that blood vessels entering or leaving cancers from their peripheries,

tend to be occluded by tissue pressures associated

with growth, leading to vascular stasis and thrombosis. The inward diffusion of nutrients, and the outward diffusion of metabolic products becomes

inadequate, and tissue death results. There are

other contributory causes of necrosis in and around

tumors; including cell and humorally mediated

cytotoxicity associated with inflammatory change,

but the end result is the same. In a cancer with

54-

3 -

1

0.8

0.6

0.2

O.lL

type B , type A

Fig. 1.

0 20 40 60 80 100 Probability of distant metastasis

The probability of distant metastases in breast cancers of types A and B, of different size at the time of diagnosis.

319
well-developed necrosis, the necrotic material

liquefies and the lesion becomes cystic. The different absorptive properties of the liquefied and solid regions lead to image enhancement--as is well-recognized on a macroscopic scale, and rep- resents an example of the heterogeneity of tumors

[15].Much previous work has not taken into account

the heterogeneity of normal , and particularly

pathologic tissues. This heterogeneity may be due

to normal anatomic structures such as large blood vessels, fascial planes etc . , or to local pathological situations such as necrosis, cyst formation, cellular infiltrations, tissue edema etc . Very few pathologic lesions consist of a "pure"

tissue type, and for this reason average, integrated interaction data collected from a large volume

of tissue may be inappropriate for tissue signature studies. In any general consideration of ultrasonic tissue characterization it is mandatory

to consider not only the macroscopic or average

features of lesions, but also their individual

"microscopic" components. By "microscopic", a region of a lesion is implied which has the dimensions of the narrowest ultrasonic beam used for tissue characterization experiments. With this in mind, the mechanical properties of different

regions of the same tumor, and the nonmalignant

tissues around it have been determined by the cell detachment technique, on Walker 256 "carcinosarcomas" transplanted in livers of rats.

A. Effect of Site Within Tumor

Cystic, subcutaneous Walker 256 tumors were

selected, with necrotic centers of approximately

3 cm mean diameter, and with wall thicknesses of

2 to 5 mm of "healthy" cancerous tissue. The re- lease of cells from the inner and outer 1 mm

lengths of cylinders taken radially through the cyst walls are shown in table 2. In the two rep- resentative examples shown, 3 and 6 times greater

volumes of tumor were released from the inner,

juxta-necrotic regions of the cyst walls than from

their outer parts.

B. Effects of Necrotic Extract

on Tumor Cel 1 Release

The subcutaneous tumors from which material

was obtained fell into two groups. The first were roughly spherical, with diameters of approximately

1 cm, and contained minimal, friable necrotic

cores. The second group, were roughly egg-shaped

with diameters of approximately 4 cm and 6 cm in

Table 2. Tumor cel 1

s

released from inner and outer

parts of walls of subcutaneous cystic

Walker 256 tumors

.

"Cel 1 "- 1 c I era J c 1 itrdil b I Zc Vol ume

(X 1000) ± SE (n) ym ± SE (n) ra 1 1

0

Inner Outer Inner Outer Inner/Outer

1 mm 1 mm 1 mm 1 mm

202 + 65 77 + 12 7"7j.O CT 1 A ^ ") 1 11 ±J.D /4±J.I 3:1

(9) (9) (99) (99)

90 + 26 36 ± 8.2 110 + 3.3 83 ± 3.5 6:1

(9) (10) (100) (100)

the short and long axes respectively, and were largely necrotic, with healthy cancerous "rims" varying from 2 to 4 mm in depth.

Cylinders obtained from the peripheral regions

of the tumors were first incubated with 1/10 dilutions of necrotic extracts in HBSS for 20 minutes

at 37 °C and then shaken for 10 minutes at room temperature (24 °C). The representative results

of 6 separate experiments with 3 separate batches

of necrotic extract are summarized in table 3. In the case of the 1 cm diameter tumors, 8 to 11 times greater volume of tumor was released after exposure to necrotic material than in the appro- priate controls. In the case of the largely

necrotic tumors, it is seen that pretreatment

with necrotic extract produced no significant

increase in the volume of tumor released by shaking, compared with controls.

C. Effects of Tumor on Surrounding

"Normal" Tissues

Following the direct injection of Walker

ascites cells (10^ cells in 0.2 ml HBSS) into the liver, tumors of approximately 1 cm diameter grew within 10 days. The tumors and the surrounding

liver were bisected, and cylinders of liver were removed at its junction with the tumor, and at 0.5 and 1.0 cm from this interface. The results

of 10 separate experiments, together with re- lease data from 2 normal livers are given in table

4. It is shown that a greater volume of parenchymal cells are released from tumor-bearing than

normal livers. In addition the closer the normal liver samples are to the tumor interface, the more readily are cells detached from them.

Table 3. Tumor cylinders incubated with necrotic extract

for 20 minutes at 37 °C; then shaken for 10 minutes.

Exper imenta' (E) Control (0

Tumors Numbers CI ump Numbers Clump Volume

rel eased diameter rel eased diameter ratio

(X 1000) (ym) (X 1000) (ym) E:C

± SE (n) + SE (n) ± SE (n) ± SE (n)

c. 1 cm 171 ± 56 57 ± 2.0 245 ± 16 23 ± 0.3 10:1

(17) (100) (17) (100)

> 4 cm 376 + 56 23 ± 1.0 477 ± 61 21 ± 0.6 1.0:1

(10) (199) (10) (197)

320
Table 4. Release of "normal" liver parenchymal cells surrounding tumors as function

of distance from tumor interface.

Distance

from tumor edge

Numbers released

(X 1000)

± SE (n)

CI ump size

(ym)

± SE (n)

Vol ume ratio

(cf. normal)

0 cm 324 ± 16 (65)42 ± 0.6

(510) 4.1:1

0.5 cm 256 ± 20

(36)

43 ± 0.6

(306) 3.7:1

1.0 cm 224 ± 17 (19)38 ± 0.5

(204)

2.3:1

Normal liver

350 ± 16 (84)

25 ± 0.2

(400)

1.0

D. Effects of Necrotic Extract on Liver Cell Release

Standard tissue cylinders were obtained from

the livers of normal rats. These were incubated

for 20 minutes at 37 °C, in either 10 percent

necrotic extract in HBSS, or in BSA control solutions. The cylinders were shaken for either 10 or

40 minutes. Representative results of 4 separate

experiments given in table 5 show that after 10 minutes shaking, 3 times greater volume of cells were released from liver cylinders pretreated with

necrotic extract than from the control series; after 40 minutes shaking, the ratios of extracttreated to controls increased to 50:1. The results of experiments (A) through (D) show clear-cut differences in the mechanical properties of different parts of the same tumor, and in the tissues surrounding them. The changes appear

to be related to the presence and diffusion of necrotic material. If the increased detachment

patterns is due to liberated lysosomal enzymes in which the necrotic material is rich, then it must

be remembered that some of these may be contributed by macrophages and polymorphs [16] which are frequently found in association with tumors and necrotic tissues.

5. Conclusions

If these results, based on cell detachment, are indicative of changes detectable by ultrasound,

and studies presently underway will hopefully

clarify this, then three positive suggestions come from this work:

A. Attention must be given to the microenvironmental conditions under which specimens are maintained while being examined, and the time

spent on examination must be minimized.

B. It is not enough to determine the characteristics of whole tumors; individual regions must be characterized and identified at a "microscopic level".

C. Changes consequent to degeneration, occurring in a cancer, and in the nonmalignant tissues

surrounding it, may enhance its detection by ultrasound by creating new differentials within these

tissues.

Acknowledgments

My thanks are due to Dr. H. Bicher and Mr. L. D'Agostino, Department of Radiotherapy for making

measurements of oxygen-tension, and to Ms. J. Holmes, D. Lombardo and Mr. D. Graham for their

technical assistance.

This work was partially supported by Grants #PDT-14 from the American Cancer Society Inc. and CA-17609 from the National Institutes of

Health.

Table 5. Release of parenchymal cells from normal liver ± nectotic extract.

Experimental (E) Controls (C)

Time Numbers Clump Numbers Clump Volume

shaken released diameter rel eased diameter ""atio

(X 1000) (pm) (X 1000) (ym) E:C

± SE (n) ± SE (n) ± SE (n) ± SE (n)

10 m 88 ± 4.4 31 + 1.2 60 ± 3.5 19 ± 0.9 3:1 (10) (137) (9) (127)

40 m 250 ± 4.9 51.3 ± 2.9 40 ± 4.8 25.6 ± 1.6 50:1

(10) (100) (10) (100)

References

[1] Weiss, L. , The Cell Periphery, Metastasis

and other Contact Phenomena (N. Holland

Press, Amsterdam, 1967).

[2] Weiss, L. , ed.. Fundamental Aspects of Metastasis (North-Holland/American Elsevier,

19761::

[3] Weiss, L., Cell detachment and metastasis,

Gann (1977a) (in press).

[4] Weiss, L., Tumor necrosis and cell detachment,

Internat. J. Cancer (1977b) (in press).

[5] Altman, P. L. and Katz, D. D., eds.. Cell Biology, p. 61 et seq. , F.A.S.E.B., Bethesda,

Maryland (1976).

[6] Warburg, 0., Ober den Stattwechsel der Tumoren (Springer, Berlin, 1956).

[7] McLimans, W. P., Crouse, E. J., Tunnah,

K. B., and Moore, G. E., Kinetics of gas

321
diffusion in mammalian cell culture systems.

1. Experimental, Biotech. Bioeng . 10 , 725-

740 (1968).

[8] Cater, D. B., Silver, I. A., and Wilson,

G. M. , Apparatus and technique for the quantitative measurement of oxygen tension

in living tissues, Proc. Roy. Soc. Lond . (Series B) 151, 256-276 (1959/1960):

[9] Gornandt, L. and Kessler, M. , PO2 Histograms in Regenerating Liver Tissue, in Oxygen in Tissues , M. Kessler, D. F. Birnley,

L. C. Clark, D. W. Lubbers, I. A. Silver,

and J. Strauss, eds., p. 288 (Urban & Schwarzenberg, Miinchen-Berl in-Wien , 1973).

[10] Ericsson, J. L. E., Mechanism of Cellular

Autophagy, in Lysosomes in Biology and Pathology , J. T. Dingle and H. B. Fell, eds.. Vol. 2, pp. 345-394 (North-Holland,

Amsterdam, 1969).

[11] Fell, H. B. and Weiss, L., The effect of antiserum, alone and with hydrocortisone,

on foetal mouse bones in culture, J. Exptl . Med, 121, 551-560 (1965).

[12] Weiss, L. , Studies on cellular adhesion in tissue culture. VIII. Some effects of antisera on cell detachment. Exptl. Cell

Res. 37, 540-551 (1965).

[13] Dunn, F. , Ultrasonic Absorption by Bio- logical Materials, in Ultrasonic Energy , E. Kelly, ed. , pp. 51-65 (Univ. of Illinois

Press, Urbana, 1965).

[14] Slack, N. H., Blumenson, L. E., and Bross,

I. D. J., Therapeutic implications from a mathematical model characterizing the course

of breast cancer. Cancer 24, 960-971 (1969).

[15] Blumenson, L. E. (1972) Cited by L. Weiss,

Some Patho-biological Considerations of Breast Cancer by Ultrasonic Holography, in Ultrasonic imaging and holography , G. W. Stroke, W. E. Kock, Y. Kikuchi, and J. Tsujinchi, pp. 567-585 (Plenum Press, New

York, 1974).

[16] Davies, P. and Allison, A. C, The Secretion of Lysosomal Enzymes, in Lysosomes in Biology and Pathology , J. T. Dinqle and

R. T. Dean, eds.. Vol. 5, pp. 61-98 (NorthHolland, Amsterdam, 1976).

322
Reprinted from Ultrasonic Tissue Characterization II, M. Linzer, ed. , National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C., 1979)

A HUMAN ABDOMINAL TISSUE PHANTOM

P. D. Edmonds, Z. Reyes, D. B. Parkinson

Stanford Research Institute International

Menlo Park, California 94025, U.S.A.

R. A. Filly ;

University of California Medical Center

San Francisco, California 94122, U.S.A.

H. Busey

Picker Corporation

Northford, Connecticut 06472, U.S.A.

The objective of this work was to determine the feasibility of constructing a phantom that would simulate human abdominal tissues when interrogated by advanced

B-scan diagnostic ultrasound equipment operating at 2.25 and 3.5 MHz. Satisfactory

results were obtained with gelatin based components having dispersed scatterers

and embedded sponge, plastic tubes and rubber bulbs filled with saline solution.

Stability of the gelatin was achieved by addition of a stabilizing agent, a pre- servative and impervious coatings to prevent water evaporation.

Key words: Gelatin; human abdominal tissues; phantom.

In the course of producing and installing ultrasonic diagnostic equipment, a need arises for a phantom object with stable acoustic properties,

that will generate displays suitable for optimizing

the adjustment of various pre-set equipment levels,

particularly in the grey-scale circuitry. The need

extends beyond the concerns of a single company be- cause there is a lack of basic standardization in the industry. The general availability of a suitable phantom would improve uniformity of displays

obtained with different ultrasonic imaging systems.

This paper describes the evolution of a phantom

object intended to simulate many of the ultrasonic

properties of human abdominal tissue when imaged

by a Picker Echoview System 801 Laminograph.

Figure 1 is an abdominal B-scan showing the variety

of textures to be simulated.

The design specification called for:

• attenuation coefficient at 2.25 MHz = 1.7 ± 0.1 dB/cm;

• velocity of propagation at 22 °C (72 °F) = 1540 ± 50 m/s;

• simulation of fine and coarse texture of

normal and pathological liver, as well as the specular reflection of capsular interfaces

and blood vessels, cysts with or without

sediment, and abdominal aorta, utilizing the

full range of grey levels;

• density = 1.05 +0.1 g/cm^;

• mechanical stability up to 65 °C (150 ^F);

• flexible exterior surface permitting limited sector scanning;

• abrasion resistant surface in the presence

of mineral oil and aqueous gels.

Fig. 1. Human abdominal B-scan showing variety

of textures to be simulated.

Less importance was attached to reproducing spe- cific organ geometries or spatial relationships.

Initial work focused on the selection of a base material. Classes of materials considered were room temperature vulcanizing (RTV) silicone

rubbers, "pc" rubbers, gelatin gels, 3M® percussion pads and "Hydron®" polymer. In order to simulate "texture", it would be necessary to in- corporate scattering centers in the base material

Hence, some part of the overall attenuation co- efficient, A, of an acceptable simulating material would be attributable to scattering and the residual absorption coefficient, a, of the base

323
material without scattering had to be correspondingly less than the desired overall attenuation

coefficient: a = A - a^, where is the at- tenuation per centimeter due to scattering.

Measured absorption coefficients and propagation velocities of the candidate base materials

are given in table 1. The absorption data were obtained by the substitution method and the velocity data by the pulse travel time method

[1]^. The techniques of sample preparation as

Table 1. Measured material properties

at 2.25 MHz, 22 °C.

Material Absorption

coefficient

(dB cm-i)

Propagation

velocity

Notes

General Electric

RTV 602

RTV 515 Goodrich

#35080 "pc" rubber 3M® percussion

pad, style 3290 "Hydron® "

, dry

"Hydron® "

, wet

10% gelatin/water

+ 1% chrome alum

Specification

1 .34 ± 0.2 2.55 ± 0.3

2.84 ± 0.11

1.7 ± 0.2

16 ± 2 13 ± 2 <0.5

<0.1 <1.7 ± 0.1

980 ± 10 980 ± 10

1546 ± 3

1490 ± 10

2050 ± 12 1950 ± 12

1539 ± 10 1540 ± 50

0.25% SRC05 catalyst; cured 48 hours at room temperature.

10% 615B catalyst; cured 48 hours at room temperature.

Sample formed from uncured rubber stock by milling

,and molding for 45 minutes at 6.6 kg/m^ and 150 °C. Measured as received in sheet form. ^The sample from Hydron, Inc. (2-hydroxy ethyl

methacrylate polymer in water) was dried and then molded at 175 °C under pressure. This produced a hard, brittle, opaque cylinder which was immersed

in distilled water to swell and soften. The re- sultant swelling was irregular. Internal bubbles

and interfaces became visible. The attenuation

was greater than 10 dB/cm at 2.25 MHz, 22 °C. This sample was then recovered by dissolving in ethanol ; the solution was placed in a dessicator

in the presence of ethanol and dried over a period

of 2 months to yield a translucent 1/8 inch thick

disc. The "dry" sample was this disc equilibrated

j,with air.

A portion of the disc was cut and immersed in distilled water for 24 hours. It became opaque white

and evidently different from contact lens material.

This was the "wet" sample.

^Photographic gelatin swollen in water and softened

by heating. Diluted to 10% solution in distilled

water; 0.1% sodium benzoate added as a preserva-

,tive. Softening point 25 °C (77 °F). 1% chrome alum added as a stabilizer. Softening

point > 95 (203 °F).

^Figures in brackets indicate literature

references at the end of this paper.

described in the notes may have influenced the data. It is evident that only RTV 602 and gelatin had sufficiently low absorption coefficients

to permit additional attenuation due to scattering without exceeding the specified overall at- tenuation coefficient. Both these materials had disadvantages. The velocity of RTV compounds is only two thirds of the desired figure. The gelatin is liable to drastic changes of dimensions

and properties as water evaporates from the gel.

Consideration was given to accepting a base material (such as RTV) with a velocity outside

the specified range, and scaling the sizes of phantom components so that the travel times of pulsed signals would correspond to those in the organs being simulated. However, this approach

was judged inherently unacceptable and it was anticipated that a base material could be found

or formulated with the desired combination of properties. Also the RTV silicone rubber was be- lieved to suffer from long term instability of acoustic properties [2]. In retrospect, it seems probable that the same precautions to combat instability that are described below for gelatin-based compounds would be applicable to RTV silicones in applications where scaling sizes

might be acceptable.

Gelatin gels were considered suitable for sub- sidiary experiments in which various scattering

materials were dispersed in the gelatin before molding; the objective was to produce a fine

textured image and the specified attenuation co- efficient. From both laboratory measurements

and imaging, with the controls on the diagnostic

equipment set for abdominal imaging, it was found

that a 1 percent dispersion of a cellulose fiber

or a 0.05 percent dispersion of glass microspheres in 10 percent gelatin in water produced

the desired results. The cellulose fiber had an average fiber length of 70 to 140 ym; the glass

microspheres ranged from 10 to 250 \m in diameter.The next objective was to identify materials

which, when embedded in gelatin, would simulate

the acoustic aspects of abdominal organs. Trial

and evaluation led to a selection of materials

each of which was embedded separately in a gelatin block containing scatterers. These blocks could then be stacked in various sequences and coupled with mineral oil for trial imaging.

Figure 2 illustrates the various inclusions

imaged at 3.5 MHz. The top block contains the base scattering material consisting of 1 percent

cellulose fiber in 10 percent gelatin in water.

A gelatin filled natural sponge is placed near

the left edge. The middle layer contains a soft rubber bulb

filled with saline solution to simulate a large

cyst or fluid filled organ. The bright spot in the center of the bulb is an artifact caused ap- parently by a focusing action. The right side

of the center layer contains a natural sponge

filled with the gelatin containing scatterers,

which might be used to simulate metastatic liver

disease.

The lowest level contains a variety of tubing. The parallel lines display the 1/8 inch wall of a soft rubber tube filled with clear gelatin. The upper wall is seen near the junction between the blocks and the lower wall in the center of the block. This is offered as an example of the resolution available at a depth of 14 cm through

324
Fig. 2. Phantom components imaged at 3.5 MHz.

the various phantom components. At the lower

right, some cross sectional images of tubes compare favorably with normal images of the portal

vein or abdominal aorta. The tubes are polyolefine shrink tubing 5/16 inch o.d. with 0.02

inch wall and clear vinyl tubing 7/16 inch diam- eter with 1/16 inch wall. These phantom com- ponents were scanned at both 2.25 MHz and 3.5 MHz with improvements in resolution at the higher

frequency corresponding to that found in bio- logical tissue. Figure 3 shows an image at 2.25 MHz with resolution clearly inferior to that of figure 2.

Fig. 3. Phantom components imaged at 2.25 MHz.

The echo discontinuities and interfaces be- tween layers should be eliminated when a con- tinuously molded phantom is produced rather

than the individual blocks shown here. Gelatin gels were originally considered un- desirable as the base material because of their

obvious instability under heat and evaporation

of water and their susceptibility to degradation

while nourishing mold organisms. However, the addition of chrome alum as a thermal stabilizer

and sodium benzoate as a preservative eliminated

two of these undesirable features. The problem

of evaporation of water is not so easily solved

if it is required that the propagation velocity

remain in the range 1540 ± 50 m/s. Two solutions appear possible: a substantial fraction of the water can be replaced by hydrophilic compounds

that have at least as high a boiling point as water and preferably higher. Table 2 shows some results of this approach; all the velocities

are too high. Alternatively, samples can be coated to prevent the water from evaporating;

this approach was undertaken.

Table 2. Velocities at 2.25 MHz, 22 °C.

Composition Velocity (m/s) 10% gelatin, 89% water

1% chrome alum

1539 ± 10

10% gelatin,

70% glycerol

20% water 1900

10% gelatin,

67% glycerol

20% water

3% PEG 200 1900

10% gelatin,

45% PEG 600

45% water 1770

10% gelatin,

60% PEOa 200, 20% water10% sorbitol

1749

10% gelatin,

45% PEG 200

45% water 1 746

10% gelatin,

45% DEG 45% water 1717

10% gelatin,

70% DEGb

20% water 1703

10% gelatin,

60% carbitol

30% v-;ater 1644

^PEG = Polyethylene glycol

DEG = Diethylene glycol

First the base material was slightly modified

by inclusion of 5 percent polyethylene glycol 200

in the formulation, to provide compatibility with

the first of five coatings that were applied to the test blocks of gelatin. Then, successive

coatings of a butadiene-acrylic rubber, a mixture

of this rubber with paraffin, and two coats of a mixture of the same rubber with polyvinyl acetate were applied. By grading the coatings in this manner, good adhesion and acoustic contact be- tween coatings was obtained, while providing the desired properties in succession. The paraffin

prevented water evaporation, and the polyvinyl acetate provided the tough flexible exterior surface. Water evaporation through this coated

specimen has been reduced to 0.25 percent per day

with the specimen open to air. It is expected

that a practical phantom would be enclosed in a protective case, within which the humidity can

be somewhat controlled as long as a reservoir of water is replenished. Consequently, the problem

of water evaporation is considered to be under

control, although further improvements in coating

formulations are under study.

In conclusion, specific combinations of materials have been identified to make possible the construction of a phantom object to simulate

many of the acoustic characteristics of human abdominal tissue. Such a phantom should aid in the standardization of operating conditions of ultrasonic diagnostic equipment.

325
Acknowledgments References

The authors wish to acknowledge the invaluable

assistance of William Mullen in performing acoustical measurements, Marie Comas and Irving Illing

in preparing test samples, and Linda McKay, Cheryl

Wilson and Diane Eskelson in scanning the many

test components.

The work reported in this paper was carried out

on behalf of the Picker Corporation.

[1] McSkimin, H. J., Ultrasonic Methods for Measurement, in Physical Acoustics , W. P. Mason, ed. , Vol. lA, pp. 271-334 (Van

Nostrand, New York, 1965).

l"2] Private communication at WFUMB Workshop,

August 1976.

326
Reprinted from Ultrasonic Tissue Characterization II, M. Linzer , ed. , National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C., 1979).

TISSUE SIMULATORS FOR DIAGNOSTIC ULTRASOUND

Reginald C. Eggleton and James A. Whitcomb

Ultrasound Research Laboratories of The Indianapolis Center for Advanced Research, Inc. Indianapolis, Indiana 46202, U.S.A.

Factors are presented related to the design, construction and use of phantoms to replace human patients or subjects in the development, testing, clinical training and promotion of ultrasonic diagnostic equipment. Materials are described which match

the acoustic properties of tissue. Realistic echograms can be obtained by scanning

properly configured phantoms using such materials.

The phantoms may be simple geometric test patterns, sections of human torso or complete human torsos simulating dynamic cardiovascular and respiratory movements to evaluate the real-time systems.

Key words: Training phantoms; tissue signature; tissue simulators; ultrasonic

phantoms

1. Introduction

Tissue simulators or phantoms, as they are sometimes called, may be utilized in the field

of medical ultrasound for purposes of quantitatively and qualitatively evaluating the perfor- mance of diagnostic or therapeutic equipment.

They may also be used for purposes of training.

Yet another application is basic study of the interaction of sound with tissues for purposes

of improving existing diagnostic criteria, understanding the mechanisms of acoustic image formation and for devising new diagnostic methods.

The design and construction of realistic

ultrasonic phantoms to substitute for human pa- tients or subjects during the early training of technicians and physicians is based upon knowledge

from several diverse fields of study. The anatomy

of the phantom must be correct with respect to the details visualized by ultrasound. Landmark fea- tures used by ul trasonographers to orient and identify the scan planes must be accurately rep- resented. The acoustic properties of biological

materials important to the appearance of the image must be catalogued for the tissues that will

be represented in the phantoms. A knowledge of materials that can be used in the construction of

the phantoms is necessary. It is essential to know how to control various acoustic properties

such as attenuation, scattering, speed of sound,

impedance, etc . Likewise it is necessary to have

a knowledge of the chemistry of the materials to select components which will give the phantoms

adequate stability and a useful life. A knowledge of fabricating techniques required

in the construction of the phantoms is also necessary. The methods for casting and welding of phantom materials to obtain the shapes and contours necessary to adequately model the human

anatomy are also required. It is also desirable

to have the necessary artistic ability to create

an aesthetically acceptable model which will have

the feel and appearance of the structures it pur- ports to represent.

2. Materials and Methods

Hydrocolloid gels are ideally suited for con- struction of ultrasound tissue phantoms because of

the flexibility and control over acoustic param- eters and the stability with respect to time. There are two hydrocolloid systems which are par- ticularly suitable for this application; one which

is reversible, and the other irreversible. A com- bination of the two allows great flexibility in fabricating techniques.

Irreversible Hydrocolloid - Alginic acid was first prepared and analyzed by Stanford in 1886

[1]^ who established it as a weak organic acid

that readily forms salts and bases. Nelson and Cretcher [2] hydrolyzed alginic acid to obtain the salt of D-mannuronic acid. X-ray and chemical

evidence suggest that alginic acid is a high molecular weight polymer made up of D-mannuronic acid. Several different methods indicate that the com- mercial sodium alginates have a molecular weight

between 3200 and 200,000 and a degree of polymerization from 0.180 to 0.930. Recent evidence has been obtained showing that the polymer molecule is entirely linear, consisting of linked mannuronic

acid units and a!?.(l-^4) linked glutamic acid units

[3-5]. Models constructed from x-ray diffraction

data indicate that the D-mannuronic acid units are

in the C-1 chair configuration, whereas the t-glutamic acid units are in the 1-C configuration [6];

^Figures in brackets indicate literature

references at the end of this paper.

327
thus algin is a copolymer and not simply a mixture of mannuronic acid and gluronan.

1/1

OH

Ic=o

Ic 0

OH

,1

I I H H

H

I -CN H °M

c

c=o

I c H /I \/\r /\/v OH/

1/

The copolymers are linked together with an alternating composition. The statistical description of the structure of algin is best obtained

by assuming that the copolymer is formed according to the penultimate-unit theory of addition

copolymerization [7]. Water soluble salts of alginic acid include

those of alkaline metals, ammonia and low molecular weight amines. Sodium alginate is the most

common salt and is readily available. Solutions

can be made in either hot or cold water. Alginates dissolve most easily when sifted into water

and vigorously agitated. High speed stirring and gradual addition of solid increases the rate of dissolution. Facilitation of the process can be achieved by wetting the alginate with ethanol or glycerol or other water-miscible liquid before it

is added to the water. With a good dispersion

the alginate dissolution should be completed in

a few minutes.

The properties of alginate solutions can be changed readily to provide either slow, fast or intermediate types of flow [8]. Algin solutions

are strongly influenced by covalent ions such as calcium which increase the viscosity and lower the flow properties, with little change in the acoustic properties. Alginates show increasing non- Newtonian flow characteristics with increased de- gree of polymerization and substitution of calcium

for sodium [9], and become thixotropic at low

levels of calcium. The effect of this ion in causing increased viscosity is more pronounced in alginates with higher D-mannuronic acid content

[10]. The viscosity of sodium alginate solutions

can be depressed by using sodium with potassium

salts. The high viscosity alginate can attain a viscosity of at least 2000 cps at a concentration of 1 percent in water, whereas a low viscosity product will have a viscosity of less than 10 cps at the same concentration as a function of molecular weight. Algin solutions behave like other fluids in their dependence of viscosity on temperature and may decrease approximately 2.5 percent per °C with increasing temperature. The viscosity of water soluble algin salts changes

only slightly as a function of changes in pH, in the range of 4 to 10. The cross-linking created by the substitution

of calcium for sodium renders the alginate in- soluble. When the insoluble salt is formed by the reaction of the sodium alginate in solution

with a calcium salt, for example, the calcium ion may replace the sodium ions in two adjacent molecules to produce a cross-linking between the two molecules. As the reaction progresses, a crosslinked molecular complex or polymer network forms. Such a network constitutes the micelles structure

of the gel. Solutions of sodium alginate are stable for long periods at room temperature but.

like other polysaccharides, are depolymerized in the presence of a number of autoxidizable sub- stances such as phenolic compounds. Sodium alginates tend to retard the growth of many microorganisms or are passive with respect to others. Al- though the algin is resistant to the attack of microorganisms, its solutions are subject to some bacterial action during prolonged storage. Agents

such as Zepharin chloride can be added in small quantities to further decrease the bacterial

growth. Small amounts of calcium increase the stability of sodium alginate solutions.

Pure algins in water form gels having excellent

optical clarity. By altering the formulation,

gels can be varied in texture from those which are soft and exhibit flow characteristics to those which are tough and elastic. This range of prop- erties exhibits little effect on the acoustic im- pedance or acoustic velocity characteristics of the material. As a result, algin gels are ideally suited to tissue simulation in that structures

can be molded and the attenuation and scattering

properties can be independently controlled.

In general, the gels are formed by the gradual

and uniform release of either calcium or hydrogen

ions, or a combination of the two throughout the algin solution. The setting time can be controlled by the addition of a limited amount of a com- pound such as phosphate or polyphosphate that is capable of combining with calcium. Frequently

calcium sulphate and a phosphate buffer are com- bined to control the gelation rate of the alginate solutions. The acoustic properties of the gel are deter- mined largely by the water. Two percent sodium

alginate solution is the usual concentration in combination with small quantities of salts. The acoustic velocity using the phase method [13] is approximately 1550 meters per second at 37 °C; the density of the 2 percent gel is approximately

1.04 grams per cubic centimeter, thus the acoustic impedance falls in the center of the plot of tissue characteristics (see figure 5). The at- tenuation for the gel without the scatterers in- corporated is approximately 0.5 dB cm"^ MHz"i.

Reversible Hydrocolloid - An organic hydrophilic colloid of polysaccharide can also be utilized for construction of acoustic test objects.

A commonly available form utilizes the sulphuric ester of a linear polymer of galactose. This

material undergoes a reversible reaction, sol t

gel, under the influence of temperature changes.

In the gel state the binding forces are secondary forces, e.g ., dipole interactions or van der

Waals forces. When the concentration of the dispersed phase in the hydrocolloid is of the proper

amount, the sol can be changed to a semisolid gel when the temperature is decreased below the critical point (^^ 110°F). The gelation is complete at approximately 100°F. In this process the dis- persed phase agglomerates to form chain fibrils,

referred to as "micelles." The process continues

until a three-dimensional matrix is formed with

much branching and intermeshing of the micelles

to form a "brush heap" structure. The intermeshing and weak binding forces contribute strength

to the structure. The interstices of this structure are filled with water; the water predominantly contributes to the acoustic properties of the

gel. It will be noted upon warming that the sol

st-ate is again attained but the temperature must

be maintained at 120°F for a period of time be328
fore liquefaction is achieved. The temperature

lag between gelation and liquefaction is described

as a hysteresis phenomenon.

In the gel state the structure exhibits both elastic and viscous properties. If the gel is de- formed it requires time to recover. Likev/ise, if the gel loses water, it will tend to absorb water

approaching the initial state. The strength of the gel is decreased at elevated temperatures,

but can be substantially increased with the addition of a small amount of borax. The borax ac- complishes this by increasing the interaction of the micelle framev^ork. The borax also increases

the viscosity in the sol state. The addition of absorbers and scatterers also increases the viscosity, as well as adding to the strength of the

gel. A suitable composition would consist of

v/ater (83.5 percent), polysaccharide (14.2 percent), potassium sulphate (2 percent) and borax

(0.2 percent). The potassium sulphate is intro- duced to minimize the amount of syneresis as well

as imbibition. The introduction of soluble salts

into the gel adjusts the osmotic pressure of the dispersion medium and thus helps to stabilize the system. The polysaccharide frequently used is ex- tracted from seaweed and is a linear polymer of

galactose, shown below.

Ic—

OH/I / OH

c\c —

I

H

Ic—

OH/1 V l/OH i/\ K

Fig. 1. Scattering test objects are constructed

with Dextran spheres dispersed in a re- versible hydrocolloid (polysaccharide).

The relative concentration ranges from

0.1 to 100 as marked to produce a range

of scattering intensities. To scan the test object the transducer is placed

against a thin plastic window at the top

of the device.

The acoustic properties of the gel with embedded scatterers and absorbers closely match those

of tissue. The specific acoustic properties can

be adjusted by varying the composition of the gel. The choice of whether to use the reversible or irreversible hydrocolloid will be dictated by the fabrication requirements. For example, an inclusion within a simulated organ could be constructed from an irreversible hydrocolloid and then later cast in the reversible hydrocolloid so that

the temperature of the embedding material would

not affect the shape of the inclusion. One obvious advantage of the reversible hydrocolloid during the development phase is that the materials

can be re-used, and it is therefore more economical, but once the design has been established,

this advantage disappears.

The acoustic properties of the reversible polysaccharide hydrocolloid gels are: density - 1.044 g/cm3; velocity of sound - 1,540 m/s; at- tenuation - 0.4 dB cm"i MHz"i. These values are remarkably close to those measured for the ir- reversible hydrocolloid and for tissue. Test objects utilizing this material were con- structed in which various concentrations of scat- terers were incorporated as layers. Because there

is no difference in the characteristic acoustic

impedance across interfaces, the only reflection

produced is due to the scattering (no specular

reflection is obtained). Figure 1 shows tv;o test objects developed to display a wide dynamic range

of backscattering targets. The relative concentration of scatterers is indicated for each level,

and ranges from 0.1 to 100 as marked on the test

object.

Silastic Phantoms - A tissue simulator not

previously described in a publication was submitted to the AIUM Standards Committee in 1970 [12].

This silastic device contained both interfaces of

graded reflectivity and scattering sources. The test block v;as constructed as indicated in figure

2 using silicone rubber (RTV 3110) and a silicone

TEST BLOCK

97% 915 88% 8S% 100%

0.2 0.4 0.6 0.8 1.0 0.0

100%

COMPOSITION OF TEST SPECIMEN

Composition of mixture Sound velocity Characteristic

Sil icone Sil icone Density at 37.0 °C impedance

rubber fluid g/cm' m/s X 10-3 rayl « 10-5

RTV 3110 DE200-20CS P C Z 100 % 0 % 1 .129 0.960 1 .084

97 3 1.124 0.962 1.082

94 6 1 .120 0.964 1.080

91 9 1.115 0.967 1.078

88 12 1.110 0.969 1.076

85 15 1 .105 0.971 1.073

100 0.971 0.975 0.947

Fig. 2. The tissue simulator shown schematically

above was constructed using mixtures of silastic and fluid to achieve a range of impedance differences across an interface.

329
Fig. 3. Materials exhibiting a range of acoustic

impedances are achieved by varying the ratio of a two-component plastic system

where the individual components have dif- ferent acoustic properties. In this in- stance, silicone rubber and silicone fluid

are mixed to vary the acoustic impedance

over a I percent range. These components

are then assembled in a test block to provide interfaces of varying reflectivity

fluid (DC200-20CS) . This mixture provided a range of acoustic impedances (fig. 3). Suspended

in the silicone fluid were particles whose mean diameter was 7 pm. These particles represented

a source of acoustic scattering, thus an ultra- sound B-mode scan of the test block revealed the interface between silastic blocks of various com- position and scattering which occurs in the bulk medium (fig. 4). Panels A, B, C and D show the test block at four gain levels 40, 30, 20 and

10 dB. An adjustment was then madd to the visualization system which sacrifices sensitivity for higher longitudinal resolution, better signal-tonoise ratio and dynamic range compression, but displays the weak specular reflectors at the interfaces with good "gray scale" and resolution, but without displaying the scatterers. Panel E shows

the effect of optimizing the system response for visualizing the interfaces within the test block. The response curve was adjusted to give an output

of 1 volt for an interface with 1.0 percent difference in acoustic impedance (minimum detectable

brightness on the display). The echoes from the scatterers then fell below 0.1 volt level. This

is an example of the way in which the test object

can be used to standardize the equipment perfor- mance so as to optimize the display of a particular type of target, organ or condition.

Plastisol Phantoms - Phantoms constructed of plastisol are more suitable for basic studies on the interaction of sound and tissue because of their inherent stability and the precision with

which the characteristic acoustic impedance,

velocity and density can be controlled to achieve

precise acoustic properties. Because of its re- latively high attenuation it is not ideally suited

for construction of training phantoms where prop- erties and distances of 15 to 20 cm are required.

By using various plasticizers and by adjusting the resin/plasticizer ratio, it is possible

to modify the characteristic acoustic impedance

of the system throughout the range of soft tissue

structures. The acoustic properties of a system

E

Fig. 4. Ultrasonic scan (at various sensitivities)

of test block shows low intensity specular

reflections at interfaces and scattering

from particles in the bulk material.

using epoxy soya plasticizer are shown in figure

5. Also plotted are a number of tissue charac- teristics for reference. It will be noted that

it is possible to match the impedance, velocity

or density of most any tissue and that the other

parameters will be nearly equivalent. The at- tenuation of this plastisol system is higher than tissue and ranges from about 2 dB cm"i MHz'i to

4 dB cm"i MHz"i for the materials shown in figure 6. Analysis of the frequency characteristics is achieved by making measurements with a range of transducers operating in a pulsed mode. A Fast Fourier Transform (FFT) for displaying the fre- quency spectrum of the pulse transmitted through

the specimen is compared with the spectrum ob- tained for a pulse transmitted through water

[13]. Figure 7 shows the normalized frequency

response for both the reference and sample waveforms. Amplitude comparison between the reference

and sample transformed responses yields the nor- malized attenuation as a function of frequency,

as shown in figure 8. Additional transducers may

be utilized to extend the frequency range. Phase comparisons between the reference and sample re- sponses give the phase velocity, as plotted in figure 9.

330
1.15 -

1.10

1.05 -

1 .00

0.95

1 .45

Fig. 5. Acoustic properties of a plastisol system

in which the resi n/pl asti ci zer ratio is adjusted to match the impedance of biological materials.

n.e 5. FREOUENC

S.e 7.3 MEGftHERTZ

Fig. 7.

2 3 4 Frequency (MHz)

Fig. 6. The normalized attenuation as a function

of frequency is shown for two plastisol

samples having impedances of 1.52 and 1.63

X 105 Rayl r^espectively. Note that the former closely matches the impedance of water so that the reflection losses at the interface are minimal. In the second specimen, the reflection losses average

1.4 dB per surface. Inasmuch as most

normal soft tissue has a much lower at- tenuation rate than that shown for these

two samples, materials of this type would

be utilized to represent highly attenuating pathological states such as those com- monly found in breast tumors.

The method for evaluating tissue simulators includes measurement of the fre- quency response characteristics of the specimen using a computer-generated

Fourier transform of the pulse propagated

through the specimen. The S201 sample

used here is from the epoxy soya plastisol

family having an acoustic impedance of about 1.56 X 10^ Rayl. The upper curve,

"S", is the reference response without

the sample. Below it are four sample responses for four closely spaced points

on the sample. The signal-to-noise ratio

for this run is such that the data in the

3 to 6 MHz range is valid, with the best accuracy assumed around 4.2 MHz, the fre- quency of maximum sample signal amplitude.

The sample and reference responses may be compared both in magnitude and phase.

Magnitude comparison yields the sample

attenuation (see fig. 8) while phase com- parison gives the sample phase velocity

(see fig. 9)

Scatterers - The vast majority of echoes ob- tained by scanning a patient are from scatterers

rather than specular reflectors. These scatterers produce echoes which are not individually re- solved but add constructively when they are in phase to produce a spot on the display. To dupli- cate this phenomenon in tissue phantoms, it is necessary to embed small scatterers (like the cells in tissue) whose dimensions are small com- pared to the wavelength of the sound. Spherical scatterers adequately represent cells whose geometry is essentially spherical, but elongated scatterers are required to represent tissues in which

331
51O

X

2:

2;o

c.

) f •> *^ I—

,—4;

i

I

3.0 3.6 4.2 FREQUENCY4.8 5.4 MEGAHERTZ6.C

Fig. 8. The attenuation, normalized in the customary manner, for the Fast Fourier

Transform responses given in figure 7,

is given here. Only data in the assumed

valid data range of 3 to 6 MHz is pre- sented; however, the variation in attenuation seen here is still partly due to the low signal amplitudes near 3 and 6 MHz. The solid bar at the bottom of the plot

indicates the range of frequencies over which a least squares curve fit was per- formed on the attenuation (in dB) vs_. frequency data. The arrow is on the fre- quency of maximum amplitude, as described

in figure 7.

the cellular makeup is other than spherical, like

in muscle, for example.

Small plastic microspheres are available in a variety of material types which can be embedded

in the acoustic medium to produce scattering.

The particles come in a variety of sizes. In general the particle size should approximate the dimensions of the scatterers of tissue, if the frequency dependence of scattering is important.

One of the common sources is the Dextran par- ticles (Sigma Chemical Company, for example) used

in Sephadex columns. This type of particle tends

to imbibe water, thus the dimension in the dry

state will be different than the dimension in the aqueous medium. Particles can be sized by putting

the powder through graded sieves. Waag et al . [14] have used three grades, each of which con- tains a wide range of sizes. There may be occasions when the range of sizes would be desirable

in simulating tissue. It is characteristic of tissues to have rather uniform cellular dimensions.

Grade

G50M

G50F G50SF

Size

86 - 257 ym

34 - 137 ym

17 - 68 ym

The uniformity of unscreened microspheres com- pared with screened microspheres is shown in figure 10. A uniform population of microspheres

may be used to study the frequency dependence of scattering and will simulate tissues having

05\

o

_JLd>„

>-

>-

r

3.0

Fig. 9.

3.6 4.2 FREQUENCY

4.8 5.4 MEGAHERTZ

The phase velocity of the sample examined

in figures 7 and 8 is presented here. This phase velocity is defined by the equation

Cs - (l/C^ + d(fi/df)(l/2Trt) where C^ is the velocity of the reference

medium, t is the thickness through which

the acoustic pulse travels in the sample,

and d^/df is the slope of the phase angle

vs . frequency data. This latter value is determined by the least squares technique

over the range of frequencies indicated

by the solid bar at the bottom of the

plot. The arrow is on the frequency of maximum amplitude, as described in figure

7. For comparison, the group velocity,

that is, the velocity of the pulse con- taining all frequencies as shown by the Fourier transform of figure 7, for this sample is 1.558 m/ms.

spherical cells. The range of frequencies for

the transition from Rayleigh to Bragg scattering

is very broad if the distribution of microspheres as shown in figure lOA is used in a tissue phantom, but is abrupt with scatterers in figure lOB. This point will be further developed

later (see fig. 14). Acrylic microspheres are available as a dental repair material. These microspheres can also be sifted through graded sieves to obtain uniform

size distribution. In some instances the more

intense scattering provided by the acrylic microspheres is desirable. Further, the dimensional

stability is very much greater, therefore, for applications in which dimensional stability is crucial, the acrylic microsphere should be considered.

Another source of microspherical particles is Teflon microspheres, which are similar to the acrylic microspheres in terms of scattering,

strength and dimensional stability. Both the Teflon and acrylic microspheres may need to be mixed with a wetting agent, such as alcohol, to promote suspension. Since these spheres are denser than water, they tend to settle out faster

than the Dextran.
Fig. 10. The Sephadex column packing spheres are

useful sources of acoustic scatterers

and are available in three size ranges;

however, each of the size ranges has a spectrum of scatterer sizes. The photograph on the left shows the distribution

of sizes obtained for the medium range. The photograph on the right shows the

20 ym sizes selected by a screening

process

.

Hollow glass microspheres show the greatest

difference in impedance compared with the medium

(fig. IIA). The glass microspheres are lower in density than water and tend to float. Between these four spherical scatterers with

their various acoustic properties, it is possible

lj to simulate many different tissue conditions.

? Scatterers are added to the medium in a concentraI tion of approximately 1 percent per unit volume.

' For Dextran this gives a backscattering characr teristic equivalent to a highly reflecting tissue,

j In many cases less than 1 percent is adequate to '•mimic the desired tissue.

The angular dependence of scattering can reveal information on the orientation of asymmetrical

I scatterers. It is therefore important to include

ji such sources in the test target that are aligned

in a specific direction. Targets containing such

Fig. 11. Scattering particles consist of cellulose acetate filaments or plastic spheres. The acetate fibers are 5 um in diameter

and 0.1 mm in length, and the spheres

shown in the photograph are approximately

10 pm in diameter, but other sizes can readily be obtained by putting the random

spheres through screens of the appropriate

size mesh. Alignment of the fibers is achieved by flowing the medium prior to curing. The number of scatterers per unit

volume, the size of the scatterers, the difference in acoustic index of refraction

of the scatterers compared with the em- bedding medium, the form factor, the diameter/length ratio and the degree of order are all factors which influence the statistical distribution of scattering. scatterers will exhibit angular dependence of scat- tering more like that of muscle. Rod-like scatterers can be obtained by using

flocking, which is a cellulose acetate material

(see fig. UB). The flocking is an acetate fila- ment and is available in various size ranges. Alignment of the rods can be achieved by causing

the material to flow, then gelling the substrate

before diffusion reorients the rods. The rods exhibit an angular dependence of scattering when

333
they are all aligned in the same direction.

Flocking is available in a variety of size ranges,

but typical dimensions are 15 micrometers by 1 mi 1 1 imeter. Attenuators - The attenuation of the hydrocolloid materials is low and comparable to water.

The addition of scatterers increases the attenuation, but this may still be below the level needed

to simulate many tissues; therefore, it is necessary to add a substance to further increase the attenuation without increasing the scattering prop- erties. A substance to achieve this property would

be any insoluble powder whose particle size is very

small compared with the wavelength of the examining

beam. Numerous powders will fulfill this requirement. Among those used is diatomaceous earth, tal- cum powder, powdered chalk, graphite, lamp black,

etc . We have used diatomaceous earth for this principally because of its availability. The powder

is mixed with the scattering spheres and hydrocolloid until the desired attenuation has been achieved. Using this technique the scattering and at- tenuation can be adjusted independently over some range of acoustic characteristics.

Fabrication Techniques - Organs can readily be molded by using natural organs or models of natural organs. Any of several molding techniques is suitable, including gel molds. The positive replica of the organ is cast in the gel and the mold is par- tially opened. The replica is extracted by deforming the gel mold.

The surface of the mold may be covered with

glycerin or other suitable parting agent and the warm sol solution is poured into the mold. Sprues

can be provided to carry away gas as the gas in the mold is displaced by the sol.

If the organ is to represent a kidney, for in- stance, it would be desirable to cast the organ in several stages to build up a structure which simulates the internal architecture of the kidney. In this case the core is held in place by struts while

the cortex is b^ing cast in the mold. Afterwards,

the struts are removed and the void is filled with

sol, using a syringe. The completed kidney is then encapsulated in a film to minimize evaporation and

add stability and convenience of handling. The

film can be applied by dipping or by sealing the material with such as a thin polyethylene over the surface of the organ and heat sealing the edges. The very thin polyethylene is easily stretched over

the organ and if the procedure is carefully done,

it is possible to avoid inclusion of air between

the skin and the kidney. The thickness of the skin

will determine the specular reflection from the surface of the organ. Specular reflectors can also be generated by

casting smooth interfaces between materials having

different acoustic impedances and scatterers are introduced by mixing plastic microspheres or rods

in the compound before the heat treating (solvation). The plastic microspheres should be of a size which is very small compared to the wavelength and comparable in dimensions to cells in tissue, i.e ., in the order of 10 micrometers in diameter. The material of the microsphere could

be chosen so that it will not be affected by the embedding material. In order to avoid introducing

gas bubbles into the mixture it is necessary to wet the microspheres with a small quantity of liquid which is miscible with the plasticizer and which does not interfere with its properties,

such as alcohol

.

3. Classification of Tissue Simulators

As noted in the Introduction there are three major applications for tissue simulators, or phantoms: 1) a training device to be used in place of human subjects; 2) a device for evaluating the performance of ultrasonic visualization systems;

and 3) a model for studying the basic interactions

between sound and tissue. Each of the three areas of application imposes

design requirements on the construction of tissue

simulators. The training device should yield

realistic echograms when scanned with conventional

diagnostic equipment so that the trainee can learn scanning techniques and the interpretation of echograms. The training device should also be fabri- cated to include both normal and abnormal anatomy

(fig. 12) illustrating the diagnostic criteria.

The phantom should contain all of the necessary

landmarks and reference points used by ultrasonographers in their diagnostic protocol. The dimensions of the training device should hold a 1:1 correspondence with the dimensions of the structures represented, therefore, the attenuation in the tissue simulator should correspond closely

with the attenuation experienced in the corresponding human anatomy.

Fig. 12. Simulation of a cross-sectional slice of

the human torso which can be scanned with

an ultrasonic transducer. The resulting

echograms exhibit a 1:1 correspondence to the same section through the human body. The training device would be constructed » to show both "normal" anatomy and simulate! pathology. '

II Tissue simulators used to check the performance i, of ultrasonic diagnostic equipment should include >. means for examining the sensitivity and resolution c (both lateral and longitudinal) of the equipment ; over the dynamic range of signal intensities en- li countered in clinical applications (fig. 13). It

is desirable that these test objects be stable ' with respect to time so that instabilities in the diagnostic equipment can be measured. Using the i simulator as a standard, equipment adjustments can i}

334
10

Fig. 13. A test block incorporating low re- flectivity specular reflectors, scatterers and wedges for resolution measurements are cast in a plastic

block which can be utilized to examine

the performance of visualization

equipment.

be made to optimize the system performance for displaying certain tissue characteristics, such as was done in optimizing the display of weak scattering interfaces in figure 4, panel E. Tissue simulators used for basic studies will vary widely in their design as dictated by the ex- perimental conditions under study. We have been using simple disc-shaped test objects of unifonri thickness with known scattering densities and im- pedance characteristics to examine the angular and frequency dependence of scattering in tissue. It

is important to control the size of the scatterer.

For scatterers which are very small compared to the wavelength of sound, scattering is of the Rayleigh type and has a fourth pov/er cross section.

In the range of Bragg scattering, there is a power

of two dependence of frequency on the scattering

cross section (fig. 14). This plot is an extension

of data presented by Freese et al . [15] and nicely

illustrates the regions of Rayleigh and Bragg scat- tering for oil droplets in gelatin and lipid filled

cells in fish muscle.

4. Conclusion

Tissue simulators are necessary to meet various

requirements with respect to the application of ultrasound to medicine which are not fulfilled by test targets such as the AIUM 100 mm test object.

Recently there has been an interest in developing

tissue equivalent targets from several sources

and this interest stems from both a requirement

to provide more quantitative diagnostic methods

as well as an interest in reducing unnecessary ex- posure of patients to ultrasound. Although as yet

no toxic effects have been documented for visuali-

'zation systems used in the customary manner, it is prudent to minimize unnecessary exposure whenever

possible. Because it is possible to accurately

simulate body structures for ultrasonic scanning,

construction of such phantoms would appear to be

an important current objective.

.01 -

.001 -

.0001

(coho)muscle

with 2% lipid content

\im droplet

backscatter coefficient

Q for oil droplets in gelatin as a function

of frequency

I I I I I

Fig. 14.

1 10 100 Frequency (MHz)

The plot of the backscatterers ' cross section vs^. frequency for oil droplets

in gelatin and for lipid droplets in muscle display both Rayleigh and Bragg

scattering phenomena. The Rayleigh

scattering has a fourth power dependence,

whereas the Bragg scattering has a second power dependence on frequency.

Acknowl edgments

This work was supported in part by NSF Grant APR75-15908, a Smith-Kline Fellowship, and by The Indianapolis Center for Advanced Research. The computer processing technique was developed by

Francis J. Fry and Narendra T. Sanghvi.

References

[1] Stanford, E. C. C, J. Soc. Chem. I nd. 5, 218 (1886). ~

[2] Nelson, W. L. and Cretcher, L. H., J. Amer . Chem. Soc . 51_, 1914 (1929).

[3] Atkins, E. D. T., Mackie, W., and Smolko,

E. E., Nature 225 , 626 (1970).

[4] Atkins, E. D. T., Mackie, W. , Parker, K. D., and Smolko, E. E., Polymer Lett. 9, 311 (1971).

[5] Rees, D. A. and Samuel, J. W. B., J. Chem . Soc. C, 2295 (1967).

[6] Larsen, B., Painter, T. , Haug, A., and Smidsr^d, 0., Acta Chem. Scand . 23, 355

(1969).

' Painter, T. , Smidsreid, 0., Larsen, B., and Haug, A., Acta Chem. Scand . 22, 1637 (1968).

[8] McDowell, R. H. , J. Soc. Chem. Ind . (London),

Monograph No. 24, 19 (1966).

335
[9] Hirst, E. L., Percival, E., and Wold, J. K., Chem. Ind. (London), 257 (1963).

[10] Smidsrjid, 0. and Haug, A., Acta Chem. Scand.

19, 329 (1965).

[11] Skinner, E. W. and Phillips, R. W., eds.. The Science of Dental Materials , pp. 101-

135 (W. B. Saunders Co. , Philadelphia, 1967).

[12] Eggleton, R. C, Fabrication of Ultrasonic

Test Specimen for Evaluating the Performance

of Echo-Ranging Equipment, submitted to AIUM Standards Committee (1970).

[13] Franklin, T. D., Jr., Sanghvi, N. T., Fry,

F. J., Egenes, K. M., and Weyman, A. E., Ultrasonic tissue characterization studies

of ischemic and infarcted myocardium,

presented at 2nd International Symposium on Ultrasonic Tissue Characterization , Session

5; June 13-15, 1977, Gaithersburg, Maryland.

[14] Waag, R. C. et al . , personal communication

(advanced copy of manuscript).

[15] Freese, M. L. and Hamid, M. A. K., Lipid content determination in whole fish using

ultrasonic pulse backscatter, in 1974 Ultra - sonics Symposium Proceedings , pp. 69-76,

IEEE Cat. No. 74 CH0896-1SU.

336
Reprinted from Ultrasonic Tissue Characterization II, M. Linzer , ed., National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C., 1979).

TISSUE EQUIVALENT TEST OBJECTS FOR COMPARISON OF ULTRASOUND

TRANSMISSION TOMOGRAPHY BY RECONSTRUCTION WITH PULSE

ECHO ULTRASOUND IMAGING

Paul L. Carson and Leonard Shabason

Department of Radiology

University of Colorado Medical Center

Denver, Colorado 80020, U.S.A.

Donald E. Dick

Department of Physical Medicine

University of Colorado Medical Center

Denver, Colorado 80020, U.S.A.

and

Wi 1 1 iam dayman

Alderson Research Laboratories, Inc. Stamford, Connecticut 06903, U.S.A.

Tissue equivalent materials have been investigated for evaluation and comparison of pulse echo ultrasound imaging and ultrasound transmission tomography by reconstruction

(UTTR). Investigations have centered primarily on various urethane polymers and 3M Reston Brand Flotation Pad material. Attenuation coefficients of the urethane polymers

still are somewhat too high, and thus initial test objects or "phantoms" have been con- structed from the flotation pad material. One phantom chosen to simulate several char- acteristics of human breast tissue consists of an annulus of unaltered flotation pad

material surrounding a center region in which scattering polystyrene microspheres are

embedded. Contrasting material such as polyethylene rods can be inserted between the inner and outer areas of the phantom. The UTTR technique clearly delineates polyethelene rods in the phantom as small as .6 mm in diameter. The scattering at 2.2 to 3.5 MHz nominal frequency exhibits a pulse echo appearance, similar to that of liver

tissue, and causes only approximately a 5 percent increase in the attenuation coefficient of the pure flotation pad material

.

Key words: Computed tomography-ultrasonic; diagnosis-ultrasonic; tissue equivalent

test objects and phantoms; ultrasound imaging; ultrasonic tissue char- acterization.

1. Introduction

Among the various properties of tissue that

can be detected with ultrasound, attenuation and velocity have attracted a great deal of attention. This interest has been intensified by

evidence that malignant and benign breast tumors

can be distinguished from each other and from

normal tissue by significant differences in at- tenuation of ultrasound by these different tissues [1]^. The goal of the main project leading to this study has been to develop a system

for the quantitative estimation of the spatial

'Figures in brackets indicate literature

references at the end of this paper.

distribution of attenuation and velocity co- efficients in living tissue. This instrumentation development has been accompanied by the development of various tissue-equivalent test objects or phantoms to help ensure accurate and

rel iable results. Simultaneous measurement of velocity and at- tenuation can be performed with direct ap- proaches to ultrasound computerized tomography

(CT), although many questions exist as to the accuracy of these measurements. To study the potential of quantitative and visual diagnosis

with the technique, a system for performing

ultrasound transmission tomography by recon- struction (UTTR) has been designed and con- structed [2]. The attenuation image shown

here was obtained with this new instrumentation,

337
using principles delineated in reference [3]. Basically, opposed transmitting and receiving

transducers are scanned on either side of the imaged object in the translate-rotate motion

of early x-ray CT scanners. The amplitude of the rectified and integrated pulse waveform

was linearized and used as the input variable

in a convolution reconstruction program. The complete UTTR system soon will include the capability for simultaneous generation of pulse-echo images as well as CT scans of velocity, and attenuation. The system has enough

flexibility to serve as a general purpose re- search instrument, but the initial investigations will focus on breast imaging. This em- phasis was chosen because of the high incidence

of breast cancer in women coupled with the need for more reliable, non-invasive techniques to detect and characterize breast lesions. Another

factor is the existence of preliminary encouraging results obtained by others with ultrasound

velocity CT images [4]. To provide a controlled comparison of the various imaging approaches, tissue equivalent

objects have been developed. This development

has followed three approaches which have been pursued concurrently:

1. Development and identification of stable plastics which are equivalent

to tissue in terms of physical density,

sound propagation velocity, and atten- uation as a function of frequency.

2. Simulation of pulse echo scattering

using small reflectors embedded in available plastics.

3. Molding the available tissue equivalent

plastics and scattering materials into

phantoms to allow evaluation and com- parison of alternative imaging approaches.

2. Developments

To date, most of the investigation on tissue

equivalent plastic has been directed to various

urethane polymers such as TDI polyether urethane

prepolymer with high molecular weight polyol

chain-extenders, and to the 3M Company material

used in Reston Flotation Pads. The urethane

polymers can be made with densities and ultra- sound propagation velocities in the soft tissue

range. Shown in figure la is an example of at- tenuation measurements on one of these polymers,

which has a density and ultrasound propagation

velocity at 27 ^C of 1.1 x 10^ kg/m3 and 1544 m/s, respectively. Work is progressing on reducing the ultrasound attenuation coefficient in these materials to that of various soft tissues.

Advantages of this class of polymer are that the materials are rigid enough to support test ob- jects in known locations, properties can be varied, and the materials are stable in time. The 3M Flotation Pad material exhibits ultrasound

interaction characteristics similar to that of fat except for a somewhat higher attenuation co- efficient as shown in figure lb. The amplitude

attenuation coefficient in SI units is related

to the attenuation coefficient in dB/cm by

)j(m-M = 11.513 • a(dB/cm). Also, p/f (s/m) = 1.1513 X 10-- 5 • a/f (dB/cm-MHz). The speed of ultrasound propagation in the flotation pad material at 27 "^C is 1461 m/s and its density is

9 X 10^ kg/m^. Figure 1 was obtained using

broadband transmitters with working frequencies

of 2.2 and 4 MHz with diameters of 19 and 13 mm, respectively. A 0.25 mm diameter miniature

hydrophone was employed as a receiver in the far field of the transmitter, and attenuation of gated sine waves was measured by interposing and removing samples of the materials under study.

Polystyrene microspheres in the range of 15 to 300 )im in diameter have been embedded in various plastics, and their pulse echo imaging

characteristics have been studied in densities

of 0.2 to 2.0 spheres per um^. At these den- sities, 80 ym diameter polystyrene microspheres

scatter more weakly than normal liver, as de- termined with commercially available pulse echo imaging systems at 2.2 - 5 MHz. Consequently,

polystyrene microspheres of 175 ym diameter, in densities of approximately 0.3 spheres per mm^, have been chosen for initial simulation of soft tissue scattering.

The phantom designed for comparisons of the various ultrasound imaging techniques is diaf(MHz)

Fig. 1. Semilogarithmic plots of attenuation coefficient as a function of frequency at two temperatures

(a) urethane polymer; (b) 3M flotation pad material.

338
Fig. 2. Top view and side view of the Tissue

Equivalent Test Object. The central cylinder contains isotropic scatterers.

Rods and tubes may be inserted between

the central cylinder and the outer an- nulus. The three nylon bolts shown in the drawing have been replaced by 0.13 mm diameter nylon monofilament.

grammed in figure 2. An annulus of 10 cm outside

diameter consisting of unaltered flotation pad

material surrounds a 4 cm diameter of cylinder of

the flotation pad material containing the scattering microspheres. This 5 cm thick cylinder is sandwiched between two acrylic plates for geometrical stability. Holes in the acrylic plate located conveniently at the interface between the outer

annulus and the central cylinder allow rods and liquid-filled cylinders of various attenuating

materials to be inserted between the scattering and nonscattering materials.

3. Examples of Use

Pulse echo images of the phantom obtained with

a commercial ultrasound scanner are shown in figure 3. Polyethylene rods of 1.9, 2.7 and 3.3 mm diameter are displayed from left to right at the edge of the inner cylinder. In this image,

the polyethylene rods are in the focal zone of the 3.5 MHz transducer and the shadowing of the scattering material by the rods is visualized

easily. Figure 4 is an UTTR image of attenuation

in the same phantom with rods of 3.3, 2.7, 1.9 and 0.6 mm diameter. As may be seen, each of the four rods was delineated clearly. Phase cancellation at the receiver due to the increased speed

of sound in the rods may have contributed to their detectabi 1 ity in both the attenuation image

and the pulse echo shadowing of discrete scatterers. The same effect should contribute to the detection of highly attenuating lesions in the body.

Attenuation coefficients for the flotation pad

material obtained in this reconstruction are

a = 2.88 ± 0.01 dB/cm or p = 33.2 ± 0.2 m-i. The

quoted errors are the standard error of the mean

of several hundred pixels in the reconstructed

image. These attenuation coefficients correspond

to a/f = 0.82 dB/cm-MHz at the 3.5 MHz working

frequency employed for the reconstruction. If the frequency averaged attenuation coefficient

of a/f = 0.9 dB/cm-MHz at 21 °C is accepted from figure lb as the true value for the flotation pad

material, then the effective frequency of the

Fig. 3. Pulse echo image of the tissue equivalent phantom using a conventional scanner with a 3.5 MHz transducer focused

at the top side of the central cylinder

containing scattering particles.

Shadowing of the scatterers by 3.3, 2.7, and 1.9 mm polyethylene rods is apparent.

Fig. 4. Attenuation image of the phantom by

ultrasound transmission tomography by

reconstruction. The polyethylene rods visible in the image range in diameter

from 0.6 to 3.3 mm.

339
broadband ultrasound pulses used to create the UTTR image may be taken to be 3.2 MHz. By com- parison, the mean attenuation coefficient of the flotation pad material containing scatterers is 3.02 ± 0.02 dB/cm. This measured value in the central scattering region may be slightly low due

to beam hardening effects. Nevertheless, the measured difference in the attenuation coefficient

of the material with and without scatterers is only 5 percent, and the real difference probably

is not much greater. The greater attenuation in the scattering material is visualized easily in UTTR images displayed at high contrast.

The maximum reconstructed attenuation coefficients at the centers of the 3.3, 2.7, i.9 and 0.6 mm diameter polyethylene rods are 20, 12, 12 and 6 dB/cm, respectively. Clearly, these ap- parent attenuation coefficients for the smaller

rods are reduced by resolution effects. Bulk measurements of attenuation coefficients of the polyethylene rods were not obtained, because the

rods were made by heating and stretching larger,

low density polyethylene rods. This process probably would affect the density of the polyethylene, and consequently the ultrasound attenuation coefficient.

Pulse echo imaging of large samples of the flotation pad material containing polystyrene

microspheres has indicated that the flotation

pad material at 21 °C attenuates ultrasound some- what more rapidly than normal liver tissue in vivo . It was assumed, therefore, that the flotation pad phantom would be a rigorous test of UTTR

and pulse echo systems for breast imaging. Initial measurements on the female breast in vivo , indicate that there are relatively large quantities of tissues in many young, female breasts which are much more attenuating than anticipated.

These materials, presumably dense, fibrous tis- sues, often may be aligned parallel to the skin

surface and thus provide a long, attenuating

path for transmission imaging in coronal sections

of the breast. Attenuation coefficients averaging 15 dB/cm in these highly attenuating tissues

have been measured with the 3.5 MHz pulses. It should be noted, however, that much of the at- tenuation obtained in the UTTR system is due to phase cancellation and refraction at the inter- face between tissues or phantom materials with

relatively low and relatively high speeds of ultrasound propagation.

The breast phantom developed to date will be useful for comparing UTTR and pulse echo imaging under the best conditions, but much more complex

phantoms will be required to simulate many im- portant features of normal and abnormal breasts.

Acknowl edgments

This investigation was supported in part by

grants APR 76-05944 from the National Science

Foundation and 5T32 CA 9073 awarded by the National Cancer Institute, Department of Health,

Education, and Welfare.

We gratefully acknowledge the contributions

of the University of Colorado Medical Center

personnel: Will Carter, Tom Oughton, Mary Dick,

Elliott Bayly, Gary Thieme, and William R. Hendee, as well as the contributions of Paul E. Hansen, of the 3M Company, who provided sample

materials and useful information.

References

[1] Calderon, C, Vilkomerson, D., Mezrich, R., Etzold, K. F., Kingsley, B., and Haskin, M. , Differences in the attenuation of ultrasound by normal, benign and malignant

breast tissue, J. Clin. Ultras . 4, 249-254

(1976).

[2] Dick, D. E., Bay, H. P., and Carson, P. L., Hardware Design of an Ultrasound CT Scanner,

Proceedings , Rocky Mountain Biomedical En - gineering Symposium , published April 1977

by the Instrument Society of America.

[3] Carson, P. L., Oughton, T. V., Hendee, W. R., and Ahuja, A. S., Imaging soft tissue

through bone with ultrasound transmission

tomography by reconstruction. Medical Physics

4, 302-309 (1977).

[4] Greenleaf, J. F., Johnson, S. A., Samayoa

,

W. P., Duck, F. A., and Wood, E. H. , Algebraic Reconstruction of Spatial Distributions

of Acoustic Velocities in Tissue from their

Time of Flight Profiles, in Acoustical

Holography , N. Booth, ed.. Vol. 6, pp. 71-90

(Plenum Press, New York, 1975).

340
APPENDIX

I

341

Reprinted from Ultrasonic Tissue Characterization II, M. Linzer , ed.. National Bureau

of Standards, Spec. Publ. 525 (U.S. Government Printing Office, Washington, D.C., 1979).

APPENDIX

DATA OF THE VELOCITY AND ATTENUATION OF ULTRASOUND IN

MAMMALIAN TISSUES - A SURVEY

R. J. Parry and R. C. Chivers

Physics Department

University of Surrey

Guildford, England

A compilation of the reported values of velocity and attenuation of ultrasound in mammalian tissues is presented to give a clear picture of the state of knowledge and enable it to be assessed. In the twenty years since the last such compilation, the progress in estimating the relative contributions of the animal species, tissue con- dition, temperature and frequency at which measurements were made and the method of measurement to the observed variation has been small. It is hoped that this compilation will both be of practical use and also encourage the establishment of a stronger

body of fundamental information for the application of ultrasound in medicine and biology.

Keywords: Attenuation; mammalian tissues; ultrasound; velocity.

1. Introduction

With the increasingly recognized importance of fundamental work on the interaction of ultrasound

with tissue there is a need for ready access to currently available data of the acoustic parameters

of mammalian tissues. There are summaries of ve- locity and attenuation data [1-3]^ but all lack

some of the information needed to make a critical assessment of the present state of knowledge. In view of this we have attempted here to produce a survey which is both accurate - not always a feature of previous surveys - and useful in providing

such information.

The grouping of the data is primarily by type

of tissue and mammalian species and subsequently

by tissue condition and temperature. Tissue condition in vitro is categorized as fresh, fixed or refrigerated (though for comparisons to be properly valid more precise details of the history of the tissues must be known).

It is assumed that the measurements were made at sufficiently low intensity such that non-linear effects were not significant. However, only Dussik

et a1 . [4] and Fry and Fry [5] report values for ultrasonic intensity. This may arise from the present state of the literature on the measurement

of intensity [6].

, The quoted attention coefficient, a, is defined

by A = Aoe""^, where A is the amplitude of a plane

i, wave of initial amplitude Ag after travelling a

;' distance x in the tissue. Assuming a realistic

ll plane wave, or that any geometrical effect on the

I amplitude has been removed, this represents the

^Figures in brackets indicate literature

references at the end of this paper.

sum of the energy absorbed within the tissue and

the energy scattered by inhomogeneities in the tissue [7]. It must also be assumed that the in- tensities used were low enough for there to be no irreversible changes caused in the tissue and thus that a is not dependent on the intensity. To convert the values quoted to decibels they should be multiplied by 8.686.

The tables include the number of measurements,

N, and some indication of the spread of values

about the quoted mean: where possible the standard deviation (SO) or standard error (SE) of the

set of measurements, other'wise the range of values

or some unspecified "variation".

As a guide to what may be expected of the mea- surements reported, it was thought useful to in- dicate the measurement technique used. For the velocity measurements these have been divided into pulse transmission or reflection (pulse), in- terferometric and sing-around techniques and for attenuation into broadband, using pulses containing only a few cycles of vibration, or narrow band,

with 20 or more cycles. Results obtained with

broadband pulses [10-12] are usually quoted as being at one particular frequency without any detail of how this frequency was selected. For pref- erence the frequency specified should be that of

the maximum amplitude in the frequency spectrum of

the pulse. Recently the whole frequency spectrum

of a broadband pulse has been used to measure at- tenuation [7,13] and there is the possibility of using swept frequency techniques [60]. Further

consideration o1^ measurement methods is out of place in the present context and the reader is referred to the review article by McSkimin [8] and

the work of Wehr [9,14] for discussion of the various techniques and the relative errors in- volved.

343
The information collected in the tables below

is that relating to whole tissues only. Thus much

data on blood is excluded as it is concerned with

the constituents rather than whole blood (see Hus- sey [3] for a summary), and in other reports the "whole blood" is a dilution with plasma of centrifuged red blood cells [57,59]. Nor was it felt ap- propriate to include all the data from isolated

references on the variation of parameters with

other features of the tissues, for example the variation of velocity in fat with water content

[15,16] and the work on liver homogenates [17,18]. For such information the reader is referred to the original literature.

Summary

The result of a survey such as this should per- haps be some set of values of parameters or curves

that may be taken to be characteristic of the various tissues considered. However, considering the data presented here, all that may be concluded is that at the present time it is virtually impossible

to separate any variation between different types

of tissue from those variations due to the many

other factors involved, such as the measurement

technique, temperature, condition and treatment of the tissue, the species from which the tissue came

and its pathological condition. To produce any "characteristic" values many assumptions would have

to be made, the validity of which cannot be assessed

from the information available. Thus all that the present authors have set out to do is to present

the data with the relevant information, where possible, in order that each worker may draw his own conclusions about average values and their' limitations. The table A, for velocity data and B, for at- tenuation data contain this information; blank (--)

indicates that the appropriate information is not stated in the original paper. To examine the frequency and temperature dependence of velocity, the

( a priori unwarranted) assumption is made that the results for different species and conditions may

be directly compared and the measurements for two temperature ranges are then represented in figures

1 and 2. The ranges chosen were 23 + 3 °C and

36 ± 1 °C, the former being rather wide in order

to encompass the large body of measurements made at

20 °C and 26 °C. It is left to the reader to opine

about the existence of velocity dispersion or to assess temperature dependence of velocity from

significant differences between figures 1 and 2 - a task made difficult by the lack of data at 36 ±

1 °C (although some data in the tables does not ap- pear in these figures as it was averaged over a wide

frequency range [10]). The remaining figures (3-9) show plots of a/f against f for various tissues - no account being taken of species, condition or temperature. This presentation was chosen as it readily permits assessment of the oft-quoted linear

relation between a and f. Comments on the temperature dependence of a are limited by the consistent

disinclination of authors to specify this parameter

when reporting their results and their tendency to average over wide temperature ranges.

In conclusion, it is only possible to echo Goldman and Hueter's statement of 20 years ago, "No critical discussion is indicated at this time, but

it is anticipated that the accumulation of further

data on the basis of more precise and extensive measurements should permit important generalizations on the acoustic characteristics of living matter." [1], and in doing so express the hope that future reports in the literature will include suf- ficient information about tissue condition and mea- surement technique to enable valid conclusions about their contribution to the spread of parameter values

to be assessed and thus permit the "important

generalizations on the acoustic characteristics of

1 iving matter.

Table. Compilation of (A) velocity and (B) attenuation of various

tissues under various conditions.

Species Condi ti on

Velocity of ultrasound in various tissues under various conditions

Temp N Technique

.

(°C)

f (MHz) (m/s)

Variation

(m/s)

Precision Source

it)

Normal Blood

man heparini sed 22 4 2 1565 125 12 sing-around 1 19 22. 6 1570 24 10 23 2 1549 6 10.8 10 24 2 1556 4 4.7 11

Normal Fat

man, orbit fresh 20 6

-* 14 1582 SD = 20.4 65 pulse 1 5 10

37 1462 SD = 23.7 16 man, breast fresh/dry 25 2 0 1470 pul se 0 2 20 man, breast refrigerated 24 1 8 1465 SE = 2 interferometric 0 5 16

man 24 1 8 1476 SE = 2 2752 interferometric 0 5 16 pig fresh 24 1 8 1444 SE = 2 58 interferometric 0 5 16 pig fresh 37 .5^7 1440 21 cow fresh 24 1 8 1465 SE = 3 21 i nterferometri c 0 5 16 horse fresh 24 1 8 1443 SE = 4 56 i nterferometri c 0 5 16

344
Species Condition Temp. f c Variation N Technique Precision Source

{°C) (MHz) (m/s) (m/s) (%)

Normal Liver

man — 24 1.8 1585 SE = 2 -- i nterferometri c 0. 5 16 pig fresh 24 1.8 1587 SE = 3 -- i nterferometri

0. 5 16 pig fresh 25 2.5 1553 SD = 15.5 7 sing-around 0 5 22 cow fresh 24 1.8 1590 SE = 2 -- i nterferometri

0 5 16 cow fresh 24 1.8 1578 SE = 3 i nterferometri c 0 5 16 horse fresh 1 Q

i . O iooU i nter ferome trie u

C ID dog fresh 26 4 & 12 1581 SD = 16.8 8 i nterferometri c 0 2 23

rabbi t fresh 24 1.8 1599 SE = 1 i nterferometri

0 5 16 rabbi t fresh 26 4 & 12 1575 SD = 9.4 13 i nterferometri c 0 2 23 guinea pig fresh 24 1.8 1575 SE = 3 i nterferometri c 0 5 16

Abnormal Liver

man, healthy refrigerated 24 1.8 1570 SE = 4 18 interferometric 0. 5 16

rabbit, bled fres h

9/1 1 . o 1607 SE = 2 1 n eerie rome ir i

u D

1 f\ guinea pig, bled fresh 1 o

1 .8 1589

Norma'

SE = 2

Kidney

interferometri c 0. 5 16

pig fresh 24 1.8 1560 SE = 4 — interferometric 0 5 16 pig fresh 25 2.5 1558 SD = 15.6 5 si ng-around 0 5 22 cow fresh 1.8 1568 SE = 3 i nterferometri c U

c3 i D cow fresh 24 1.8 1572 SE = 3 i nterferometri c 0 5 16 horse fresh 24 1.8 1558 SE = 3 interferometric 0 5 16 doq fresh 26 4 & 12 1559 2 interferometric 0 2 23 rabbit 5 1566 1560 - 1571 2 24

Norma Spleen

pig fresh 24 1.8 1578 SE = 3 interferometric 0 5 16 pig fresh c . b 1515 SD = 15.2 4 SI ng-around u

c

D LL09 cow fresh 24 1.8 1577 SE = 2 interferometric 0 5 16 cow fresh 24 1.8 1578 SE = 3 — interferometric 0 5 16 horse fresh 24 1.8 1595 SE = 3 interferometric 0 5 16 dog fresh 26 4 & 12 1570 2 interferometric 0 2 23

Normal Lung

dog fresh 35.0 ± .5 0.98 650 0 2 ref lecti on coefficient^25

dog fresh 35.0 ± .5 1

5

658

812

1180

— reflection

coeff i ci ent^

less than

10 ms'i

52

doa 0. 39

1 300 580 pulse 55

Abnormal Lung

dog, pneu- monitic

fresh 35 0.98 340 0 1 reflection

coefficient^

25

Normal Connective Tissue

man, breast fresh/dry 25 2.0 1545

Norma' Muscle

pul se 0. 2 20

Skeletal muscle: parallel to muscle f i bres

dog fresh 26 4 & 12 1592 SD = 5.0 7 interferometric 0 2 23 rabbit fresh 26 4 & 12 1603 SD ^ 7.9 13 interferometric 0 2 23

345
Species Condition Ternp. f c Variation N Technique Precision Source

(°C) (MHz) (m/s) (m/s) (%)

Skeletal muscle: perpendicular to muscle fibres

man, external fresh 20 6 14 1612 SD 12.5 83 pul se 1 5 10 eye 37 1631 SD _ 15.3 13 man, breast fresh/dry 25 2 0 1545 pul se 0 2 20 dog fresh 26 4 & 12 1576 SD - 9.6 8 i nterferonietri c 0 2 23 rabbi t fresh 26 4 & 12 1587 SD 5.5 18 i nter ferometri c 0 2 23

Skeletal muscle : direction unspecified

man, pectoral ref ri gerated 24 1 8 1568 SE = 5.5 -- interferometric 0 5 16 man -- 24 1 8 1585 SE = 6 interferometric 0 5 16 pig fresh 24 1 8 1580 SE 3 interferometric 0 5 16 cow fresh C H 1 8 1581 SE 4 i nterferometri c 0 5 16 cow fresh 9/1 11 8 1580 SE 4 interferometric 0 5 16 cow refrigerated 25 2 5 1580 SD = 16 12 sing-around 0 5 22 horse fresh 24 1. 8 1598 SE 4

_ _ interferometric 0 5 16

Cardiac muscle

pig fresh 24 1 8 1587 SE 3 i nterferometri c 0 5 16 cow f re s h 24 1 8 1584 SE 3 "i rThprfpyrirnptri c 0 5 16 cow fresh 24 1 8 1570 SE 2 interferometric nu

c

J

110F. horse fresh 24 1 8 1584 SE 3 * ~ interferometric 0 5 16 dog fresh 26 4 & 12 1572 3 interferometric 0 2 23

Normal Nervous Tissues

man, brain fresh 24 5 1524 pul se 0 1 26" (term foetus) 24 1521

il 1540 man, brain 1525 27 (foetus

)

man, brain 24 1 8 1564 SE 4 — interferometric 0 5 16 pig, brain fresh 24 1 8 1565 SE 2 i nterferometric 0 5 16 pig, brain fresh 25 2 5 1506 SD 15 7 interferometric 0 5 22

cow, brain fresh 24 1 8 1560 SE 2 i nterferometri c 0 5 16 cow, brain fresh 9/1 1 8 1569 SE 3 inter icruiMcLi \l n J 1 u horse, brain fresh 24 1 8 1560 SE 2 IMLtri IcrUllltrLi IL I u dog, brain fresh 25 2 5 1515 SD 15 5 si ng-around U

rb 99LC cat, brain 1 i vi ng/fresh 24 4 2 1557 pul se -

"

11

37 1570

60 1574 rabbit, brain -- 5 1508 1380 - 1570 3 24

man, optic fresh 20 6

->• 14 1644 SD 25.4 30 pulse 1 5 10 nerve 37 1615 SD 3.1 13 man, cerebro- fresh 21.8 2 1499 30 11 sing-around 0 1 19 spinal fluid 24.4 1515 45 9 25.0 1509 5 7 .5 11

Abnormal Nervous Tissues

man, fixed 3 h 19.0 2 1524 2 6 .1 20 sing-around 0. 1 19 meningioma 48 h 19.8 1524 5 7 .5 20 man

,

19.7 2 1557 31 20 sing-around 0. 1 19 meningioma 1546 15 20

(5 sections 1569 31 21 of 1 tumor) 1548 31 14 1569 39 14 man, glioma fresh 22.2 2 1529 1 9 .1 20 sing-around 0. 1 19 man, glioma fixed 22.3 2 1500 45 17 si ng--around 0. 1 19

346
Species Condition Temp. f c Variation N Technique Precision Source

(°C) (MHz) (m/s) (m/s) (%)

man

fresh 27.5 2 1545 4 6.2 41 sing-around 0.1 19 astrocytoma

man 19

T 1 xeci 2 1517 121 27 <^ 1 n n - ri mi in H 0.1 astrocytoma

man

f i xed 20.0 2 1501 45 18 sing-around 0.1 19 ependymoma

Normal Ophthalmic Tissues

man, lens in vivo body -- 1585 ± 74b 53 — — 28 man, lens fresh 34.1 4 1641 SD = 16^ 7 i nterferometric __ 29 (mean

man, lens fresh 37 4 i nterferometri c 0.6 30 (autopsy) 1641 0 SD = 1.3 35 (operative) 1638 4 SD = 3.0 12 (autopsy + operative) 1640 5 SD = 1.2 47 pig, lens fresh 23 4 i OD J = fie interferometric 29

1 n JU 1673 SD = 56 10

35 1677 SD = 3^ 10 cow, lens fresh 22 4 iODU 1 nterferometri c 0.5 31 cow, lens refrigerated 26-31 5 ID iO iOUU iOOU i nterferometri c 1 12 rabbit lens 5 i J H-U OU DO RJ 24

man, vitreous in vivo body 7 lb44 ± ii c 0 bi 28 man, vitreous fresh 35.2(mean) 4 1530 SD =

5'= 10 interferometric -- 29 man, vitreous fresh 3/ 4 i n ter ferome tr i c 0.6 30'- (autopsy) 1532 SD = 0.6 35 (operative) 1531. 7 SD = 0.9 14 (autopsy + operative) T C 0 0 A c n — n c 4 oU - (J . b 4y

pig, vitreous fresh 23 4 1510 SD = 3^ 10 interferometric -- 29

30 1522 SD = 3^ 9 35 1531 SD = 3e 10 cow, vitreous fresh 22 4 1495 interferometric 0.5 31 cow, vitreous refrigerated 26-31 5 1516 1490 - 1544^ interferometric 1 12 rabbit. 5 1472 SD = 16 6 — 24 vitreous

vitreous + hyal uronidase 1494 SD = 11 6 cow, aqueous fresh 22 4 1495 interferometric 0.5 31 cow, aqueous refrigerated 26-31 5 1497 1481 - 1525^ 12 man, cornea/ in vivo body 1502 ± 45b 53 28 aqueous

cow, cornea fresh 22 4 1550 interferometric C.5 31 cow, sclera fresh 22 4 1630 interferometric 0.5 31

Abnormal Ophthalmic Tissues

man, lens- fresh 35.8 4 1643 1 interferometric — 29 cataractous 1688 1

Normal Bone

Long bones: a long axis

cow, phalanx fresh 5 4030 SD = 110 252 pulse SD 3 32 cow, phalanx dried 5 4360 SD = 170 120 pul se SD 3 32 cow, femur dried 5 4060 SD = 40 144 pul se SD -x. 3 32 guinea pig. .1 3158 2870 - 35419 40 pul se — 33 femur

Long bones: across axis

cow, phalanx fresh 5 3160 SD = 170 252 pulse SD -v- 3 32 cow, phalanx dried 5 3270 SD = 160 120 pulse SD 3 32

cow, femur dried 5 3420 SD = 340 144 pul se SD -x. 3 32

347
Species Condition Temp.

(°C)

f c Variation

(MHz) (m/s) (m/s)

Technique Precision Source

(%)

Long bones: direction unspecified

man, cortical in vivo body

bone 5.0 3406

fresh

fixed

dog, tibia horse

Skull bone

man

manouter layer

diploe layer

inner layer

guinea pig, fresh completely healed

broken femur partially healed

broken femur

refrigerated 22

body

& 5 -- 3210 3700

0.8 3360

._h 2920 SD 3198 SD 3098 SD

SD = 126

36209

18

160

93220

23

9

5

6

man, pre- menopausein vTvo body

Abnormal Bone

0.1 2968 2788 - 33719 15

2551 2442 - 27249 I6

Normal Breast Tissue

2.0 1510 1450 - 1570J ^ 110 pulse

pulse

pulse

pulse

continuous wave reflection

pulse

pulse

post-menopause 1468 1430 - 1520J

Abnormal Breast Tissue

'x- 40

brain

17 weeks

(2 samples)

28 weeks

(2 samples)

40 weeks

(2 samples)

24

24

37372424

37

3724

24

37

37

1490

1495

1520

1523

1498

1502 1528

1529

1521 1524

1540

1540

6

0.2

34

35

36

37

38 i

33

20^

man, carcinoma refrigerated 24 1 8 1573 SE = 7 interferometric 0 5 16 man, carcinoma in vivo body 2 0 1478 SD = 28 17 pulse 0 2 20^ man, fibrocystic

in vivo body 2 0 1531 SD = 23 28 pul se 0 2

20''

man, fibroadenosisin vivo body 2 0 1529 SD = 30 6 pul se 0 2 20^

man, fibro

adenoma

in vivo body 2 0 1529 SD = 21 6 pul se 0 2 20^

Obstetric Tissues

man, cervixpregnant

nonpregnant

in vivo body 5 1525

1633

SD = 1.63

SD = 2.86

108

29

pulse 006 39

man, amniotic

fluid

25 5 1510 40

man, milk 30 2 1540 pul se 0 2 20 man, foetal fresh 5 pul se 0 1 26^

348
Species

Attenuation of ultrasound in various tissues under various conditions.

Condition Temp. f a Variation N Technique Precision Source

(°C) f a. Variation(MHz) (m-i) (m'M

Norma D 1 ooci 58 1.09 -- -- -- —

i! 0 1.73

1. 8 3.22

3. 0 6. 33

4'. 8 12!l

DO 1.15

1. 0 1.78

1. 8 3.45

3. 0 6.91

4. 8 12.7

Normal Fat

5.

gHl 230 SD = 22 9 - 13 broadband —

6. 2 220 SD = 15

7. 5 330 SD = 24

7. 7 250 SD = 18

8. 4 320 SD = 26

8. 8 360 SD = 15

9. 8 430 SD = 20

9. 8 450 SD = 24

10 46 500 SD = 30

13. 9 D/U c n - OQ

0 180P -- bjJcL-Lr Ulll ailu lj'-> ' J

4. 4- Ul a ur UClUUaMU

1 7 360 n 1 1 1 c |J U 1 b tr

1 10 typi cally at least spectrum 5m" 1 2 22 SD = 3 6 per a 1 1 a 1 y J 1 J u 1 3 35 point: a broadband

4 47 pul se'^ 5 63 1 point

6 84 per 100

7 115 kHz

8 5

i 6.9 SD = 2.3 narrow band . 25

3 18 SD = 2.3

5 26 SD = 8.1

1 rD 6.9 --

2 8 21

4 40

6 56

7 75

87 4.6 10%

1 7 8.7

3 4 16

Norma' Liver

11 0

20.3 900 broadband

1 13.8 typically at least spectrum analysis 5m" 1

2 27.6 SD = 6 6 per of a broadband

3 43 point: pulse"

A

't 56

5 69 1 point

6 81 per 100

7 93 kHz

1 5 16

2 4 18

4 5 40

1 5 15

2 4 18

4 5 38

dog fresh (citrated)

30

40

man, orbit fresh 37

man, orbit

man

in vivo

fi xed 18 ± 2

man man/cow

pig

fresh

fresh

cow

man

man

(melted)

in VIVO

f i xed

37

20 - 35

body

18 ± 2

cow

cow

fresh

fresh

20 - 35

41

10

61

42

4

21

43

44

7

45

46

349
Species Condi tion Temp.

(°C)

f (MHz) (m-i)

Variation

(m-i)

Technique Precision Source

cow fresh 25 7.7 + 10% 17

cow

cow

ground (± ^ 0.5)

refrigerated

fixed

20 - 35

.35

.575

.6

.7

.3.87

1320

29

54

71

104

4

610

9

11

9.

10%

47

43

1 7 1

97

cow 2 12 — -.r 54

12 narrow band^

Normal Kidney

man/mouse fresh/frozen/ 22 - 31 96 1000 SD = 86 7 -- + 25% 48

fixed 222 5000 SD = 760 4

cow fresh 20 - 35 1.5 19 — — — 45

2.4 26

4.5 51

cow fresh 1 t; i . D

1 Q 46

9 A CO 4.5 53

cow fixed .25 5 — — 47

.3 4

. 35 5 'a 6 .5 7 .6 5 .7 9 .8 7

pig 2 18 __r — 54

16 narrow band^

Norma' Spleen

man fixed 18+2 1 3.5 typically at least spectrum 5m

7

2 13 SD = 4.6 6 per analysis

3 26 point: of a broadband

4 40 1 point pul se"

5 56 per 100

6 74 kHz

7 96

Normal Lung

man fresh 1 350 narrow band 0.25 dB 4

dog fresh 35.0 ± .5 .98 470.0 10.0 2 25

dog fresh 35.0 ± .5 1 430 410 - 470^' 52

2.25 590 560 - 640J

5 1160 L040 - 1210J

dog fresh 27 ± 2 2.4 440 SE = 160 broadband 0.1 dB 56t

5.0 900 SE = 140

7.4 1000 SE = 130

dog, pneumoni tic

fresh 35.0 ± .5

Abnormal Lung

350 25

350
Species Condition Temp

.

f (MHz) (m-i)

Variation

(m-i)

Technique Precision Source

Normal Connective Tissues

man, skin fresh — 1 40 SD = 14

3 85 SD = 14

5 106 SD = 25

man/cow, tendon fresh 1 54 SD = 12 across grain 3 125 SD = 23

5 195 SD = 28

along grain 1 58 SD = 21

man/cow fresh — 1 38 SD = 10

articular 3 81 SD = 9 capsule 5 130 SD = 62 maMail/n / rnui uuw "fyf^ 1 Q h 1 Coll I 58 SD = Ij

cartilage 3 144 SD = 23

5 220 SD = 62

cow, elastic fresh 1 73 SD = 2 tendon, across 3 188 SD = 2 grain 5 286 SD = 53

along grain 1 41 SD = 8

3 137 SD = 3

5 235 SD = 66

cow, rectum fresh 1 6.9 SD = 1.7

wall 3 18 SD = 2

5 28 SD = 5

Norma' Muscle

^l/ala^al jKc miicr'To* naval lol 1 c Lo 1 IIIUbv.,lc> parallel to muscle fibres

man fresh 37 5. gm 180 SD = 18

6. 2 210 SD = 18

7. 5

0/1 n SD = 15

7. 7 220 SD = 16

8. 4 310 SD = 24

8. 8 320 SD = 25

9. 8 410 SD = 22

9. 8 400 SD = 24

10. 46 440 SD = 20

13 9 590 SD = 17 man/cow fresh 1 16 SD = 3

3 48 SD = 9

5 71 SD = 17

cow 20 - 35 3 9.0

87 18.0

1. 7 25.4

3 4 62.1

Skeletal muscle: perpendicular to muscle fibres

man fresh 37 5 gm 120 SD = 16

6 2 170 SD = 21

7 5 200 SD = 22

7 7 130 SD = 18

8 4 220 SD = 33

8 8 280 SD = 35

9 8 290 SD = 20

9 8 300 SD = 23

10 46 370 SD = 24

13 9 480 SD = 18

man/cow fresh 1 8 SD = 1 3 30 SD = 6

5 40 SD = 1 cow 20 - 35 .3 7.5

.87 5.5

3 .4 26.5

narrow band 0.25 dB 4

9-13 broadband 10

narrow band 0.25 dB 4

10% 43

9-13 broadband 10

narrow band 0.25 dB 4

10% 43

351
Species Condition Temp. f a Variation N Technique Precision Source

(°C) (MHz) (m-i (m-i)

Skeletal muscle: direction unspecified

man __ 8 9.5 -- -- 42 cow 2 -- 21 - 1159 r 54 — 21 - 249 narrow band^

Cardiac muscle

cow fresh 20 - 35 1 5 30 - — 45

2 4 45

4 5 80 cow T rs s n — 1i 5 30 _. 46

0

L. 4 45

A 5 80 cow fixed O

CD 35 5 4 8 575 10

6 10

7 14 8 14 dog fresh ?c 20 SD = 10 12 per spectrum analysis -- 62

4 32 SD = 14 point: of a broadband

6 50 SD = 14 1 point pulsei^

8 66 SD = 14 per 500

10 92 SD = 20 kHz

Tongue: parallel to fibres

cow iresn cu - jd 11 5 23 45

2 4 32

4 5 65

Tongue: perpendicular to fibres

cow fresh 20 - 35 1 5 45 45

2 4 65

Tongue: direction unspecified

cow fresh 1.5 20 2.4 32 4.5 62

dog, infarcted fresh -- 2 cardiac 4 muscle 6810

Abnormal Muscle

0 SE = 10 7 per spectrum analysis

20 SE = 10 point: of a broadband

60 SE = 15 1 point pulse"

115 SE = 15 per 500

190 SE = 10 kHz

man, brain

man, brain

pig, (whole

brain)

(whi te matter)

pig, brain

cow, brain

fixed

fresh

fresh

fixed

fresh

20 - 35

20 - 35

.3.87 1.7 3.4

12.5

2.5

.35

.6

.8.87

1.7 3.4

Nerve Tissues

8.5

14.0

18.0 36.5

1740

18

34

5 8.5

14.0 33.5

10%

36 - 51

16 - 21

12

6

10%

43

49

50

47

43

352
Species Condition Temp. f a Variation N Technique Precision Source

(°C) (MHz) (m-i) (m-i)

dog, brain in vivo body 97 5.4 -- 1% 41 LaLi Urdin vivu 37 2 28 50 — hrriri U 1 Hhfln <J U 1 1 d<-! — 11 rat, spinal in vivo 30-31.5 98 10 8 12 7 narrow band 5 cord

mouse, spinal in vivo 2 ± .1 1 1.7 — 53 cord 10 ± . 1 5.0

28 ± . 1 9.5

Parallel to nerve fibres

man, optic fresh 37 5. gm 290 SO 14 9 - 13 broadband — 10 nerve 6. 2 280 SO 16

7. 5 430 SD 22

7 7 400 SD 47

8. 4 600 SD = 38

8. 8 500 SD 38

g 8 620 SD 38

9 8 670 SD = 36 10 46 600 SD = 21

13 9 740 SD 28 man, medulla 20-35 1 7 14 10% 43 oblongata 3 4 34 cow, sciatic 20-35 3 4 40 nerve

Perpendicular to nerve fibres

man, optic fresh 37 5 gm 210 SD = 20 9-13 broadband 10 nerve 6 2 240 SD = 20

7 5 310 SD = 28

7 7 230 SD = 22

8 4 370 SD = 43

8 8 350 SD = 29

y

Q

. O Jdu c n oU

9 8 410 SD 33

10 46 500 SD = 29

13 .9 630 SD 33 man, medulla 20-35 1 7 21 - - 10% 43

obi ongata 3 4 46 cow, sciatic 20-35 3 4 55 10% 43 nerve

Normal Ophthalmic Tissues

man

,

lens 10° 92P spectrum analysis — 13

i + of a broadband

17 156 pul se'^ cow

,

lens fresh 28 3.25 64 6 4 12 cow, lens 22 10 230 58 13.5 310

cow. vitreous 22 6 6 58

10 12 18 20

30 29 cow. aqueous/ fresh 25-28 30 33 9 large broadband 15% 12 vitreous

Normal Bone

man

,

skull fresh .3 23 7 broadband 51

.6 52 16

.8 92 28

1.2 170 51 1.6 320 96 1.8 430 130

353
Species Condition Temp. f a Variation N Technique Precision Source

(°C) (MHz) (m-i) (m-i)

2

3 255 530 780

160 230

man, skull fresh/fixed 8 150 _ _ __ 37 man, skull outer

diploe

inner

fixed _..h 1919

1616 2460

SD = 474

SD = 293

SD = 1250

24

9

56

25% 38^

man, skull 1 150 49 man/cow fresh 1 144 narrow band 0.25 dB 4 dog, tibia refrigerated 22 3

c0 150 220 — — — 35

horse q 12

4

4386

5

250

920 460 - 580

36

Obstetric Tissues

cow, uterus fresh 1 19.6 SD = 2 narrow band 0.25 dB 4

The velocity was calculated from measurements of the reflection coefficient made with a thermo- couple probe in a standing wave field.

'^The authors do not indicate what this figure

represents

.

"Measurements were made on samples from eyes with

a variety of tumors although no pathological

condition was seen in the components of the eye.

"^Reference 30 contains information on the variation

of velocity with time after death.

'Data for the calculation of the standard deviation

were taken from the graphs in the reference.

''calculation of the standard deviation was not possible since each figure quoted by the author

is a mean of 16 to 25 measurements.

""The authors do not give individual measurements

but only quote this range. The authors do not specify the frequency used,

except that the pulse used "contained substantial

components in the range 3 to 4 MHz."

'The "average value" for bone quoted by these authors must be disregarded because of the manner

in which it was obtained.

^Only the range can be obtained from the data which

are represented graphically.

^This includes data from U.S.A. and Australia, and

a study comparing measurements with radiographic

findings.

Data used to calculate the mean and standard deviation were those marked "a" in tables II to V of reference 20 ( i .e . those breasts diagnosed by

pathology studies of excised tissue).

'"These figures refer to the dominant frequency in the acoustic pulse from a reflector in water, but the authors comment that this may change by as much as 12 percent.

"This method gives the attenuation as a continuous

function of frequency, but the authors did not include diffraction corrections necessary for accurate results. °Frequency resolution 300 kHz. ^The attenuation coefficient was assumed to be linear with frequency.

"^This author also gives some indication of the tem- perature variation of the attenuation coefficient.

r Pulse technique using piezoelectric receiver.

^Continuous wave technique using radiation balance

receiver. ^These authors also give information on the variation of the attenuation coefficient with the degree of inflation of the lung. '^Reference 26 contains further information on the variation of velocity in foetal brain with the gestational age of the foetus.

354
oSpleen oCardiac muscle o Fat Oliver "Kidney •Skeletal muscle 1700p I 1 r 1 I 1 ( 1 I

I .

8

1650

1600

1550

1500

1450-

1400L I I I I I I

I

1 I I I I I L

o • o

Sclera o Brain o Vitreous o Cornea • CSF •Lens •Aqueous

1 I n r

1231231 _ J 1 I L I I I I 231231 2345634534 5 Frequency (MHz)

Fig. 1. Frequency dependence of the velocity of ultrasound in various normal tissues at 23 ± 3 °C.

Spleen Cardiac muscle

Fat Liver Kidney Skeletal muscle 1700p I 1 I 1 I 1 I 1 I

1650

1600

^ 1550

1500

1450

1400

Sclera o Brain oVitreous Cornea

CSF •Lens Aqueous

1

I I I 1

I L I I I I \ I I L I I I I J I L ( L

1 231 2 31 231 231 2 3 4 5634 534 5 Frequency (MHz)

Fig. 2. Frequency dependence of the velocity of ultrasound in various normal tissues at 36 ± 1 °C.

355
100 Buschmann et al . [10] — Chivers and Hill [7] 0 Pohlman [42]

1 Dussik et al . [4]

a Schwan et al . [21 ] • Colombati and Petralia [43] Q Goldman and Hueter [1] (pooled data)

/

Fig. 3. Attenuation of ultrasound in normal fat.

0.1 Frequency (MHz)

100

100

Mountford and Wells [44] — Chivers and Hill [7] V Hueter [45]

T Hueter and Pohlman [46] o Pauly and Schwan [17] iEsche [47] • Colombati and Petralia [43] C3 Goldman and Hueter [1] (pooled data)

Fig. 4. Attenuation of ultrasound in normal liver.

1|_

0.1

lOOr

100 Frequency (MHz)

Kidney: i. Kessler [48] 7 Hueter [45]

T Hueter and Pohlman [46] i Esche [47] Spleen: —Chivers and Hill [7] Uterus: • Dussik et al . [4]

Fig. 5. Attenuation of ultrasound in normal abdominal organ tissue (other than liver).

0.1 Frequency (MHz)

100

356
100

Fig. 6. Attenuation of ultrasound in normal muscle.

O tfn

Skeletal: along • Buschmann et al . [10] across a along Dussik et al . [4] across o

along •Colombati and Petralia [43] across o

oPohlman [42] Cardiac: Allueter [45] AEsche [47] Tongue: along THueter [45] across vCjGoldman and Hueter [1] (pooled data)

Frequency (MHz)

100

(Man)

(Cow) oColombati and Petralia [43]

(White matter) v

iBallantine et al . [49] 'Hueter and Bolt [50]

Vosioka et al . [41] ^Esche [47]

I Robinson and Lei e [11] QGoldman and Hueter [1] (pooled data)

Fig, 7. Attenuation of ultrasound in normal brain.

iL_

0.1

lOOr

Frequency (MHz)

0

o a

100

Medulla oblongata:

Spinal cord:

along DBuschmann et al. [10] across

along oColombati and Petralia [43] across

along OColombati and Petralia [43] across •vFry and Fry [5]

Fig. 8. Attenuation of ultrasound in normal nervous

tissues (other than brain).

0.1 100 Frequency (MHz)

357
1000

vDussik et al. [4] oAdler and Cook [35] Kishimoto [36]

Skull bone • Hueter [51] Theismann and Plander [37] iBallantine et al . [49]

100

Fig. 9. Attenuation of ultrasound in normal bone.

10 100 Frequency (MHz)

References

[1] Goldman, D. E. and Hueter, T. F., Tabular

data of the velocity and absorption of highfrequency sound in mammalian tissues, J. Acoust. Soc. Am . 28, 35-37 (1956). Errata: J. Acoust. Soc. Am . 29, 655 (1957).

[2] Wells, P. N. T., Absorption and dispersion

of ultrasound in biological tissue. Ultrasound in Med. Biol . 1, 369-376 (1975y^

[3] Hussey, M. , Diagnostic ultrasound (Blackie,

Glasgow, 1975).

[4] Dussik, K. T., Fritch, D. J., Kyriazidou, M.

,

and Sears, R. S., Measurements of articular

tissues with ultrasound. Am. J. Phys. Med . 3^, 160-165 (1958).

[5] Fry, W. J. and Fry, R. B., Temperature

changes produced in tissue during ultrasonic

irradiation, J. Acoust. Soc. Am . 25 , 6-11

(1953).

[6] Zieniuk, J. and Chivers, R. C, Measurement

of ultrasonic exposure with radiation force

and thermal methods, Ultrasonics 14 , 161-

172 (1976).

[7] Chivers, R. C. and Hill, C. R., Ultrasonic

attenuation in human tissue, Ultrasound in Med. Biol . 2, 25-29 (1975).

[8] McSkimin, H. J., Ultrasonic Methods for Measuring the Mechanical Properties of Liquids and Solids in Physical Acoustics , W. P. Mason, ed. , Vol. 1, Part A, pp. 271- 334 (Academic Press, New York, 1964).

[9] Wehr, J. S., Classification and discussion

of interference methods for measuring the propagation velocity of ultrasonic waves, in Proceedings of the Fourth International

Conference on Acoustics, Copenhagen, Paper

K15 (1962).

[10] Buschmann, W., Voss, M. , and Kemmerling, S., Acoustic properties of normal human orbit

tissues, Ophthal. Res. 1, 354-364 (1970).

[11] Robinson, T. C. and Lele, P. P., An analysis

of lesion development in the brain and in plastics by high-intensity focussed ultrasound at low-megahertz frequencies, J. Acoust. Soc. Am . 5^, 1333-1351 (1972T.

[12] Begui, Z. E. , Acoustic properties of the refractive media of the eye, J. Acoust. Soc . Am. 2i, 365-368 (1954).

[13] Lizzi, F., Katz, L. , St. Louis, L. , and Coleman, D. J., Applications of spectral analysis

in medical ultrasonography. Ultrasonics 14 , 77-80 (1976).

[14] Wehr, J. S., Error analysis as a factor in the choice of the proper method of measuring the attenuation and the reflection coef- ficient of ultrasonic waves in solids, in Proceedings of the Conference on Acoustics

of Solid Media (PWN Warsaw, 1964), pp. 239-

245.

[15] Frucht, A. H. , Die Geschwindigkeit des Ultra- schalls in menschlichen und tierischen Ge- weben, Naturwi ssenschaften 39, 491-492

(1952).

[16] Frucht, A. H., Die Schallgeschwindigkeit in menschlichen und tierischen Geweben, Ze i

t

. Ges. Exptl. Med . 120, 526-557 (1953).

[17] Pauly, H. and Schwan, H. P., Mechanism of absorption of ultrasound in liver tissue,

J. Acoust. Soc. Am . 50, 692-699 (1971).

[18] Danckwerts, H. J., Discrete relaxation

processes as a model of the absorption of ultrasound in liver homogenate, J. Acoust . Soc. Am . 55_, 1098-1099 (1974).

358
[19] Van Venrooij, G. E. P. M. , Measurement of ultrasound velocity in human tissue. Ultrasonics 9. 240-242 (1971).

[20] Kossoff, G., Fry, E. K. , and Jellins, J., Average velocity of ultrasound in the human female breast, J. Acoust. Soc. Am. 53, 1730-1736 (1973y:

[21] Schwan, H. P., Carstensen, E. L. , and Li, K.

,

Heating of fat-muscle layers by electromagnetic and ultrasonic diathermy. Trans. Am . Inst. Elec. Engrs . 1, 72, 483-488 (1953).

[22] Ludwig, G. D. , The velocity of sound through

tissues and the acoustic impedance of tissues,

J. Acoust. Soc. Am . 22, 862-866 (1950).

[23] Goldman, D. E. and Richards, J. R., The mea- surement of high frequency sound velocity in mammalian soft tissue, J. Acoust. Soc. Am . 26, 981-984 (1954).

[24] Nakajima, A., Nishi, S., Amano, K. , Uesugi

,

T. , and Wakai , T. , Measurement of the axial length of the eye by ultrasonic device, (in

Japanese), J. Clin. Ophth . 14, 1594-1599

(1960).

[25] Dunn, F. and Fry, W. J., Ultrasonic absorption and reflexion by lung tissue, Phys. Med . Biol. 5, 401-410 (1961).

[26] Wladimiroff, J. W., Craft, I. L., and Talbert,

D. G. , In vitro measurements of sound velocity

in human fetal brain tissue. Ultrasound in Med. Biol . U 377-382 (1975).

[27] Willocks, J., Donald, I., Duggan, T. C, and

Day, N. , Foetal cephalometry by ultrasound,

J. Obs tet. Gynaec. Br it. Cwlth . 71., 11-20

(1964).

[28] Nakajima, A., Kimura, T., and Yamazaki, M., Applications of Ultrasound in Biometry of

the Eye in Ultrasonics in Ophthalmology , R. E. Goldberg and L. K. Sarin, eds., pp. 124-144 (W. B. Saunders, London and New York,

1967).

[29] Jansson, F. and Sundmark, E., Determination

of the velocity of ultrasound in ocular tissues at different temperatures. Acta Ophthal . 39, 899-910 (1961).

[30] Jansson, F. and Kock, E., Determination of

the velocity of ultrasound in the human lens

and vitreous. Acta Ophtal . 40, 420-433 (1962).

[31] Oksala, A. and Lehtinen, A., Measurement of

the velocity of sound in some parts of the eye. Acta Ophtal . 36, 633-639 (1958).

[32] Lang, S. B., Ultrasonic method for measuring

elastic coefficients of bone and results on fresh and dried bovine bones, I.E.E.E. Trans . Bio-Med. Eng . BME-17 , 101-105 (1970).

[33] Floriani, L. P., Debevoise, N. T., and Hyatt,

G. W. , Mechanical properties of healing bone

by the use of ultrasound, Surg. Forum 18 , 468-

470 (1967).

[34] Craven, D. A., Constantini, M. A., Greenfield,

M. A., and Stern, R., Measurement of the velocity of ultrasound in human cortical bone

and its potential clinical importance. An

in vivo preliminary study. Invest. Radiol. 8, 72-77 (1973).

[35] Adler, L. and Cook, K. V., Ultrasonic para- meters of freshly frozen dog tibia, J. Acoust . Soc. Am . 58, 1107-1108 (1975).

[36] Kishimoto, T. , Ultrasonic absorption in bones,

Acustica 8, 179-180 (1958).

[37] Theismann, H. and Pfander, F. , Uber die

DurchlHssigkeit des Knochens fUr Ultraschall, Strahlentherapie 80, 607-610 (1949).

[38] Martin, B. and McElhaney, J. H., The acoustic properties of human skull bone,

J. Biomed. Mater. Res . 5, 325-333 (1971).

[39] Bakke, T. and Gytre, T. , Ultrasonic measurement of the sound velocity in the pregnant

and the non-pregnant cervix uteri, Scand . J. Clin. Lab. Invest 33, 341-346 (1974).

[40] Zana, R. and Lang, J., Interaction of ultrasound with amniotic liquid, J. Acoust. Soc . Am. 55, 391 (1974).

[41] Yosioka, K. , Ohmura, A., Hasegawa, T. , and

Oka, M., Absorption coefficient of ultrasound in soft tissues and their biological

conditions, in Proceedings of the 6th Inter- national Congress on Acoustics, Tokyo, 1968,

pp. M5-M8.

[42] Pohlman, R., Uber die Absorption des Ultraschalls im menschlichen Gewebe und ihre Abhclngigkeit von der Frequenz, Physi kal i sche

Zeit. 40, 159-161 (1939).

[43] Colombati, S. and Petralia S. , Assorbimento

di ultrasuoni in tessuti animal i. La Ricerca Scientifica 20, 71-78 (1950).

[44] Mountford, R. A. and Wells, P. N. T. , Ultrasonic liver scanning: the quantitative

analysis of the normal A-scan, Phys. Med . Biol . 17_, 14-25 (1972).

[45] Hueter, T. F., Messung der Ul traschal 1 absorption in tierischen Geweben und ihre Abh^ngigkeit von der Frequenz, Naturwi ssenschaften

35, 285-287 (1948).

[46] Hueter, T. F. and Pohlman, R. , Eine optische

Methode zur Bestimmung der Ultraschal labsorption in undurchsichtigen , schal Iwei chen Medien, Z. Angew. Phys . I, 405-411 (1949).

[47] Esche, R., Untersuchungen zur Ultraschallabsorption in tierischen Geweben und Kunst- stoffen, Akust. Beih . 2, 71-74 (1952).

[48] Kessler, L. W., VHF ultrasonic attenuation

in mammalian tissue, J. Acoust. Soc. Am . 53 , 1759-1760 (1973).

[49] Ballantine, H. T., Hueter, T. F., and Bolt,

R. H., On the use of ultrasound for tumour

359
detection, J. Acoust. Soc. Am . 26, 581 (1954).

[50] Hueter, T. F. and Bolt, R. H., An ultrasonic

method for outlining the cerebral ventricles,

J. Acoust. Soc. Am . 23, 160-167 (1951).

[51] Hueter, T. F., Messung der Ul traschal 1 absorption im menschlichen SchSdel knochen und ihre AbhSngigkeit von der Frequenz, Naturwissen - schaften 39, 21-22 (1952).

[52] I Dunn, F., Attenuation and speed of ultrasound

in lung, J. Acoust. Soc. Am . 56 , 1638-1639

(1974) .

[53] Dunn, F., Temperature and amplitude dependence of acoustic absorption in tissue, J^. Acoust. Soc. Am . 34, 1545-1547 (1962).

[54] Marcus, P. W. and Carstensen, E. L., Problems

with absorption measurements of inhomogeneous

solids, J. Acoust. Soc. Am . 58, 1334-1335

(1975) .

[55] Reid, J. M., (1965), reported in F. Dunn,

P. D. Edwards and W. J. Fry, Absorption and Dispersion of Ultrasound in Biological Media , H. P. Schwan ed., pp. 205-332 (McGraw-Hill

Book Co., New York, 1969).

[56] Bauld, T. J. and Schwan, H. P., Attenuation

and reflection of ultrasound in canine lung

tissue, J. Acoust. Soc. Am . 56, 1630-1637

(1974).

[57] Carstensen, E. L., Li, K. , and Schwan, H. P., Determination of the acoustic properties of blood and its components, J. Acoust. Soc. Am . 25, 286-289 (1953).

[58] Filipczynski , L., Etienne, J., Lypacewicz, G., and Salkowski, J., Visualizing internal structures of the eye by means of ultrasonics, Proc . Vibration Problems 8, 357-368 (1967).

[59] Urick, R. J., A sound velocity measurement for determining the compressibility of finely di- vided substances, J. Appl. Phys . 18^, 983-987

(1947).

[60] Heyser, R. C. and Le Croissette, D. H., A new ultrasonic imaging technique using time delay

spectrometry, Ultrasound in Med. Biol . U

119-131 (1975).

[61] Lizzi, F. L. and Laviola, M. A., Power spectra measurements of ultrasonic backscatter from ocular tissues, in Proceedings of 1975 I.E.E.E. Ultrasonics Symposium, pp. 29-32 (1975).

[62] Yuhas, D. E., Mimbs, J. W., Miller, J. G., Weiss, A. N., and Sobel , B. E., Changes in ultrasonic attenuation indicative of regional

myocardial infarction, in Proceedings of World Federation of Ultrasound in Medicine

and Biology, San Francisco, 1976, pp. 1883- 1894 (1976).

360
SUBJECT INDEX

Absorption, 19, 29, 43, 153 Acoustoel ectri c effect, 63 Amino acids, 19 Anisotropy, 73, 189 Attenuation, 19, 37, 43, 63, 73, 81,

85, 93, 101, 121, 125, 153, 157

197, 203, 209, 247, 255, 281, 287, 343 Backscattering, 153, 157, 165, 247,

275, 327 Beam displacement, 203 Beam distortion, 203 Blood, 165, 173 Bone, 19, 179, 189, 197 Brain, 81, 203, 209 Breast, 13-16, 85, 93, 173, 221, 255

Cell detachment, 317 Cepstrum, 287 Collagen, 19, 73, 179, 189 Color-coded B-scan, 255, 261 Computed tomography, 227, 235, 247,

255, 337 Convolution, 287 Correlation analysis, 275 De-convolution, 287 Dispersion, 81 , 189, 197 Doppler, 173, 227, 235 Dynamic autocorrelation analysis, 275 Elasticity, 73, 189 Estimation theory, 125 Eye, 19, 111 Filtering, 299-300

Hamming window, 281 Heart, 43, 73, 153, 267 Homomorphic processing, 287 Hydroxyapatite, 179, 189 Hyperthermia, 57 Image analysis, 255, 303 Imaging,

annular array, 255 brain (transkul 1 )

, 235 Doppler (moving media), 235 image reconstruction (see computed

tomography)

synthetic focus, 235 Impedance, 81 Inhomogenei ty thermal losses, 37 Interferogram, 73 Kidney, 303

Lag windows, 281 Lipids, 157 Liver, 125, 153, 157, 287, 303 Lung, 19, 135, (see scattering)

Microscopy, myocardium, 73 Myocardium, 63, 73, 153, 267 Opto-acoustic visualization, 255 Pattern recognition, 297, 303 Phantoms, 179, 323, 327, 337 Phase compensation, 209, 235 Polypeptides, 19 Probability density functions, 125 Prostate, 297 Proteins, 19, 157 Pulse compression, 255 Relaxation phenomenon, 29 Scattering, 37, 111 , 135, 143, 153,

157, 281 (see also backscattering)

Sensitivity enhancement, 255

Signal averaging, 255

Skull , 197, 203, 209 Spectral analysis, 43, 111, 125, 143,

261 , 267, 281 , 287 Speed, (see velocity)

Temperature dependence of ultrasonic

properties, 57, 63, 203, 227, 235 Temporal changes, 267, 275 Thermal "lesions", 203 Thermal wave, 37 Thermodynamics, 189 Tissue death, 317 Tomography, (see computed tomography)

Transducer calibration, 255 Velocity, 19, 43, 53, 57, 63, 73, 81,

179, 189, 197, 343 Visco-elasticity, 189 Viscous relative motion, 37

361
AUTHOR INDEX

Bahn, R. C, 227 ,235

Barger, J. E. , 197 Barnes, R. W. , 81 Baxter, B. , 235 Beaver, W. , 267 Birnholz, J. , 287 Bowen , T . , 57 Boyle, D. , 267 Boynard, M. , 165 Brady, J. K. , 19 Busey, H. , 323

Carson, P. L. , 337 Cartensen , E . L . , 29 Christensen, D. , 235 Chivers, R. C. , 343 dayman, W. , 337 Connor, W. G. , 57 Czerwinsk i , M. J. , 303

Dain P., 125 Davidson, C. L. , 179 Dick, D. E. , 337 Dietz, D. R. , 255 Doppman , J . L . , 255 Duck, F. A. , 247 Dunn, F. , 19,43

Edmonds, P. D. , 323

Eggletoti, R. C. , 327 Elbaum, M. E. , 111

Filly, R. A. , 323 Finby, N. , 125 Eraser, J. , 287 Freese, M. , 157 Frizzell , L. A. , 19,43

Fry, E. K. , 85 Fry, F. J. , 85,203

Gaca, A. , 297 Gallagher H. S. , 85 Gammell , P. M. , 101 Glover, G. H., 221 Gore, J. C. , 275 Goss, S. A. , 19,43

Graniiak, R. , 143 Greenleaf , J. F. , 227,235

Halliwell, M., 173 Hanss, M. , 165 Heyser , R. C. , 101 Higgins, F. P. , 255

Hill , C. R. , 247 Holasek, E. , 261 Hunter, L. P. , 143

Jennings, W. D. , 261 Johnson, S. A. , 227,235

Johnston, R. L., 19,43

Joynt, L. , 267

Katz, J, L. , 189 Kessler, L. W. , 73 Keuwez, J. , 121 Kino, G. S. , 287 Kobayashi , T. , 93 Kremkau, F. W. , 81 Kuc, R., 125

Leb, D. E., 303

Le Croissette, D. H. , 101 Lee, P. P. K., 143 Leeman, S. , 275 Lees, S., 179 Lerner, R. M. , 143 Levi, S,, 121 Linzer , M. , 255 Lizzi, F. L., Ill Lock, E., 297 Lyons, E. A. , 157

Maynard, V. , 19,43

McGraw, C. P. , 81 Metrewel i

, C. , 275 Miller, J. G., 37,63

Mimbs, J. W., 63 Mountford, R. A. , 173

Nasoni , R. L. , 57 Nider, L., 43 Norton, S. J. , 255

O'Brien, W. D. , Jr. , 19,43

O'Donnell, M., 37,63

Parkinson, D. B. , 323 Parks, S. I., 255 Parry, R. J. . 343 Phillips, D. J., 209 Pifer, A. E., 57 Plessner, N. J. , 275 Popp, R. , 267 Preston, K. , Jr. , 303 Purnell, E. W., 261

Rakowski, H., 267 Reid, J. M. , 153 Reyes, Z. , 323 Rhyne, T. L., 135 Robinson, D. E. , 281 Rajagopalan, B., 227,235

Roseboro, J. A. , 101

Sanghvi , N. T Scheiding, W. Schenk, E. A. Schwartz, M.

,

Shabason, L.

,

Shawker, T. H Shideler, R. Sholes, R. R. Shung, K. K.

,

Skidmore, R.

,

Skolnik, M. L Smith, S. W.

,

Sobel, B. E., Sollish, B. D

., 85

, 297

, 143

125

337

., 255

W., 255

, 57 153

173

., 303

209

63

., 53

Thomas, P. J., 227 Thurstone, F. L., 209

von Ramm, 0. T. , 209 von Seelen , W. , 297

Waag, R. C, 143 Webb, A. J., 173 Weiss, L. , 317 Wells, P. N. T. , 173 Wessels, G. , 297 Whitcomb, J. A. , 327 Willson, K. , 275 Wilson, R. L. , 101 Woodcock, J. P. , 173

Yoon, H. S., 189 Yuhas, D. E. , 73 ^

•

362
NBS-114A IREV. 0-761

U.S. DEPT. OF COMM. 1. PUBLICATION OR REPORT NO. l||^t||H|||p|P tiOj BIBLIOGRAPHIC DATA

SHEET NBS SP 525

p-..*-^r^-->f^-%

li .... .• s 4. TITLE AND SUBTITLE Ultrasonic Tissue Characterization II

5. Publication Date April 1979

rmwmiog Orgamnioon Code

7. AUTHOR(S)

Edited by Melvin Linzer

8. Performing Organ, Report No.

9. PERFORMING ORGANIZATION NAME AND ADDRESS 1ft, Pro|ect/Ta«J(/*<Kt( Onii No.

NATIONAL BUREAU OF STANDARDS

DEPARTMENT OF COMMERCE

WASHINGTON, DC 20234

11. Contract/Grant No.

12. SPONSORING ORGANIZATION NAME AND COMPLETE ADDRESS fStreef, city. State. ZIP) National Science Foundation

Washington, D.C.

and National Institutes of Health

Bethesda, Maryland

13. Type of Report & Period Covered

14. Sponsoring Agency Code

b.^.^.....--........:. : 15. SUPrLEMENTARY NOTES

Library of Congress Catalog Card Number: 79-600026

I I Document describes a computer program; SF-185, FIPS Software Summary, is attached.

16. ABSTRACT (A 200-word or leaa tactual aumrnary of most significant Information. If document includes a significant bibliography or

literature survey, mention it here.)

The Second International *^vmDosium on Ultrasonic Imaging and Tissue

Characterization was held at the National Bureau of Standards on June 13-15, 1977.

The meeting was cosponsored by the National Bureau of Standards, the National

Science Foundation, and the National Institutes of Health. This volume contains

extended and reviewed papers based on 43 of the 53 talks presented at the

Symposium. Topics covered include techniques for measurement of ultrasonic

tissue parameters, the dependence of tissue properties on physical and biological

variables ^e.g., ultrasonic frequency, temperature), mechanisms of ultrasonic

tissue interactions, propagation through bone and skull, tumpr Doppler signatures,

computerized tomography, signal processing and pattern recognition, and tissue

phantoms. A survey of velocity and attenuation data in mammalian tissue is included

in an appendix.

17. KEY WORDS fs/x to twelve entries; alphabetical order; capitalize only the first letter of the first key word unless a proper name;

separated by semicolons) Absorption; attenuation; computerized tomography; Doppler; impedance; medical

diagnosis; microscopy; pattern recognition; scattering; signal processing;

tissue characterization; tissue parameters; ultrasound; velocity.

18. AVAILABILITY |3 Unlimited 19. SECURITY CLASS

(THIS REPORT)

21. NO. OF

PRINTED PAGES

1 1 For Official Distribution. Do Not Release to NTIS UNCLASSIFIED 339

rrp Order From Sup. of Doc, Government Printing Office, Washington, DC ^ 20402, SD Stocl< No. SN003-003-0258-3

20. SECURITY CLASS

(THIS PAGE)

22. Price

1 1 Order From National Technical Information Service (NTIS), Springfield, VA. 22161 UNCLASSIFIED $5.50

ir U.S. GOVERNMENT PRINTING OFFIfE: 1979 O—291-026
Ii IIiiI

1. 1i
NBS TECHNICAL PUBLICATIONS

PERIODICALS

JOURNAL OF RESEARCH—The Journal of Research

of the National Bureau of Standards reports NBS research and development in those disciplines of the physical and

engineering sciences in which the Bureau is active. These

include physics, chemistry, engineering, mathematics, and

computer sciences. Papers cover a broad range of subjects, with major emphasis on measurement methodology, and

the basic technology underlying standardization. Also in- cluded from time to time are survey articles on topics closely

related to the Bureau's technical and scientific programs. As

a special service to subscribers each issue contains complete

citations to all recent NBS publications in NBS and non- NBS media. Issued six times a year. Annual subscription: domestic $17.00; foreign $21.25. Single copy, $3.00 domestic;

$3.75 foreign. Note: The Journal was formerly published in two sections: Section A "Physics and Chemistry" and Section B "Mathematical Sciences."

I DIMENSIONS/NBS

\ This monthly magazine is published to inform scientists,

I engineers, businessmen, industry, teachers, students, and

I consumers of the latest advances in science and technology,

with primary emphasis on the work at NBS. The magazine

[highlights and reviews such issues as energy research, fire protection, building technology, metric conversion, pollution

,i abatement, health and safety, and consumer product per-

'{formance. In addition, it reports the results of Bureau pro- grams in measurement standards and techniques, properties

jof matter and materials, engineering standards and services, jinstrumentation, and automatic data processing.

y Annual subscription: Domestic, $1 1.00; Foreign $13.75

NONPERIODICALS

IMonographs—Major contributions to the technical liter- ature on various subjects related to the Bureau's scientific and technical activities. •Handbooks—Recommended codes of engineering and industrial practice (including safety codes) developed in cooperation with interested industries, professional organizations,

i md regulatory bodies.

jipecial Publications—Include proceedings of conferences ponsored by NBS, NBS annual reports, and other special

publications appropriate to this grouping such as wall charts, TOcket cards, and bibliographies.

Applied Mathematics Series—Mathematical tables, manijials, and studies of special interest to physicists, engineers,

' hemists, biologists, mathematicians, computer programmers,

nd others engaged in scientific and technical work,

''lational Standard Reference Data Series—Provides quantiative data on the physical and chemical properties of

naterials, compiled from the world's literature and critically valuated. Developed under a world-wide program cordinated by NBS. Program under authority of National

tandard Data Act (Public Law 90-396).

NOTE: At present the principal publication outlet for these data is the Journal of Physical and Chemical Reference Data (JPCRD) published quarterly for NBS by the American Chemical Society (ACS) and the American Institute of Physics (AIP). Subscriptions, reprints, and supplements

available from ACS, 1155 Sixteenth St. N.W., Wash., D.C.

20056.

Building Science Series—Disseminates technical information developed at the Bureau on building materials, components,

systems, and whole structures. The series presents research

results, test methods, and performance criteria related to the

structural and environmental functions and the durability

and safety characteristics of building elements and systems. Technical Notes—Studies or reports which are complete in themselves but restrictive in their treatment of a subject.

Analogous to monographs but not so comprehensive in scope or definitive in treatment of the subject area. Often

serve as a vehicle for final reports of work performed at NBS under the sponsorship of other government agencies.

Voluntary Product Standards—Developed under procedures

published by the Department of Commerce in Part 10, Title 15, of the Code of Federal Regulations. The purpose

of the standards is to establish nationally recognized require- ments for products, and to provide all concerned interests with a basis for common understanding of the characteristics of the products. NBS administers this program as a supple- ment to the activities of the private sector standardizing

organizations.

Consumer Information Series—Practical information, based on NBS research and experience, covering areas of interest to the consumer. Easily understandable language and

illustrations provide useful background knowledge for shopping in today's technological marketplace.

Order above NBS publications from: Superintendent of Documents, Government Printing Office, Washington, D.C.

20402. Order following NBS publications—NBSIR's and FIPS from

the National Technical Information Services, Springfield, Va. 22161.

Federal Information Processing Standards Publications (FIPS PUB)—Publications in this series collectively constitute the Federal Information Processing Standards Register.

Register serves as the official source of information in the Federal Government regarding standards issued by NBS

pursuant to the Federal Property and Administrative Services Act of 1949 as amended. Public Law 89-306 (79 Stat. 1127), and as implemented by Executive Order 11717

(38 FR 12315, dated May 11, 1973) and Part 6 of Title 15 CFR (Code of Federal Regulations).

NBS Interagency Reports (NBSIR)—^A special series of

interim or final reports on work performed by NBS for outside sponsors (both government and non-government).

In general, initial distribution is handled by the sponsor;

public distribution is by the National Technical Information

Services (Springfield, Va. 22161) in paper copy or microfiche form.

BIBLIOGRAPHIC SUBSCRIPTION SERVICES

e following current-awareness and literature-survey bibli- aphies are issued periodically by the Bureau:

Cryogenic Data Center Current Awareness Service. A litera- ture survey issued biweekly. Annual subscription: Domestic, $25.00; Foreign, $30.00.

iquified Natural Gas. A literature survey issued quarterly,

jnnual subscription: $20.00.

Superconducting Devices and Materials. A literature survey

issued quarterly. Annual subscription: $30.00. Send subscription orders and remittances for the preceding bibliographic

services to National Bureau of Standards, Cryogenic Data

Center (275.02) Boulder, Colorado 80302.
U.S. DEPARTMENT OF COMMERCE

National Bureau of Standards

Washington. D.C. 20234

OFFICIAL BUSINESS

Penalty for Private Use, S300

POSTAGE AND FEES PAID

U.S. DEPARTMENT OF COMMERCE COM-219

SPECIAL FOURTH-CLASS RATE

BOOK

i