A11103 Ofifl?m

'"'srnat/onal'^ll^ 0308871

Vau of

NBS SPECIAL PUBLICATION 453

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

QC

100

.057

N0./I53

1976

C.2

Ultrasonic

Tissue Characterization
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

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THE INSTITUTE FOR BASIC STANDARDS provides the central basis within the United

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" — Cryogenics "' — Electromagnetics - — Time and Frequency -'. THE INSTITUTE FOR MATERIALS RESEARCH conducts materials research leading to improved methods of measurement, standards, and data on the properties of well-characterized materials needed by industry, commerce, educational institutions, and Government; provides

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' Headquarters and Laboratories at Gaitliersburg. Maryland, unless otherwise noted; mailing address Washington, DC. 20234.

- Located at Boulder, Colorado 80302.
6 1S7S

5*^ Ultrasonic Tissue Characterization

-"Proceedings of a Seminar held at the

o National Bureau of Standards,

Gaithersburg, Md., May 28 - 30, 1975

Edited by

Melvin Linzer

Institute for Materials Research

National Bureau of Standards

Washington, D.C. 20234

Cosponsored by

National Science Foundation (Research Applied

to National Needs, RANN)

National Institutes of Health (Diagnostic

Radiology Department, Clinical Center)

National Bureau of Standards

(Institute for Materials Research)

U.S. DEPARTMENT OF COMMERCE, Elliot L. Richardson, Secretary

Edward O. Vetter, Under Secreiary

Dr. Betsy Ancker-Johnson, Assisianf Secrefary for Science and Technology

VA^ C .NATIONAL BUREAU OF STANDARDS, Ernest Ambler, Acting Director

' ' ' Issued October 1976
Library of Congress Cataloging in Publication Data

Seminar on Ultrasonic Tissue Characterization, 1st, National Bureau of Standards, 1975. Ultrasonic tissue characterization. (NBS special publication ; 453)

Includes indexes. Supt. of Docs, no.; C 13.10:453

1. Diagnosis, Ultrasonic—Congresses. 2. Ultrasonic waves

Measurement—Congresses. 3. Tissues—Analysis

Congresses. I. Linzer, Melvin. II United States. National

Science Foundation. Ill United States. National Institutes of

Health. Clinical Center. IV. United States. National Bureau of Standards. V. Title. VI. Series: United States. National Bureau of Standards. Special publication ; 453. QC100.U57 no. 453 [RC78.7.U4] 602". Is [616.07'583] 76-608298

National Bureau of Standards Special Publication 453

Nat. Bur. Stand. (U.S.), Spec. Publ. 453, 274 pages (Oct. 1976)

CODEN: XNBSAV

U.S. GOVERNMENT PRINTING OFFICE

WASHINGTON: 1976

For sale by the Superintendent of Documents, U.S. Government Printing Office, Washington, D.C. 20402

(Order by SD Catalog No. C13.10: 453). Stock No. 003-003-01700-1 Price $3.55 cents. (Add 25 percent additional for other than U.S. mailing)
iii
iv
FOREWORD

The primary function of the National Bureau of Standards is to provide measurement

methods, standards, and data to assure the reliability and effective use of measurements.

Among the many areas requiring improved measurement reliability, none is more important

than that which supports the Nation's health care system. The application of the physical

and engineering sciences to improve the quality of medical diagnosis and treatment is already

having enormous impact. Much, however, remains to be done. To fully exploit the advances

in these sciences, it will be necessary to foster and maintain an active dialogue among

the many diverse groups working to promote improved health care. The materials scientist

can also contribute to this goal. In the field of nondestructive evaluation, for example,

many of the ultrasonic methods for assessing structural reliability are remarkably similar

to those used for medical diagnosis.

The prospect for a synergistic development of techniques for non-invasive medical

diagnosis and nondestructive evaluation of materials is an exciting one. The National

Bureau of Standards has programs in both areas and thus can play a role in bringing together

the biomedical and materials communities in a common effort to improve these two measurement systems.

This Conference makes a truly outstanding contribution to the advancement of these

techniques and to their more effective utilization. The National Bureau of Standards is proud to be a cosponsor along with the National Institutes of Health and the National

Science Foundation in this important undertaking.

John D. Hoffman

Director

Institute for Materials Research

National Bureau of Standards

V
PREFACE

This book is the formal report on the proceedings of the first international Seminar

on Ultrasonic Tissue Characterization. The meeting was held at the National Bureau of

Standards on May 28-30, 1975, and was cosponsored by the National Science Foundation, the

National Institutes of Health, and the National Bureau of Standards.

Participants in the Seminar included the foremost researchers in ultrasonic tissue

characterization both from within the United States and from abroad. The meeting served as

a forum for the examination of the state-of-the-art and prospects for research in the newlyemerging field of ultrasonic parameter measurement.

This volume contains extended versions of 21 of the 22 talks presented at the Seminar. The first chapter of the book covers the introductory session and is followed by

chapters on tissue properties, A-scan pattern recognition techniques, attenuation and

velocity techniques, absorption techniques, scattering techniques, impedance-profile

techniques, and acoustic microscopy.

These proceedings bring together for the first time a comprehensive compilation of

definitive articles on ultrasonic tissue parameters and methods for measurement of these

properties. It is our belief that publication of this landmark volume will provide directed stimulus to this new and exciting area of medical diagnosis.

An undertaking of this magnitude would not have been possible without the assistance

of many individuals. The editor is greatly indebted to his conference co-chairperson,

Gil Devey, who originally conceived of the Seminar and provided major financial support

through NSF/RANN. His farsighted management of the RANN Instrumentation Program has had

considerable impact on establishing a nationally-integrated research effort in medical

ultrasound. For this achievement, Gil recently received the first AAMI Foundation Award

for distinguished contribution to the advancement of medical instrumentation. In the week

following the Seminar, Gil moved to the Office for International Programs at NSF. His

presence in the medical ultrasound area will certainly be missed.

Acknowledgement is also given to the contributions of John Doppman (NIH Clinical

Center), as well as to Peter Wells (Bristol General Hospital) and Judy Prewitt (NIH) who

served as chairpersons of the "Summary and Critique Panel" and "Tissue Signature Panel",

respectively. Particular appreciation is due Ron Johnson (NBS/Institute for Materials

Research), whose very capable handling of the logistics of the Seminar helped to ensure

the physical comfort of the participants and the smooth progress of the meeting. In this

effort, he was enthusiastically aided by Gloria Serig and others in the Institute office

as well as Sara Torrence and the other members of the NBS conference staff. Finally,

special acknowlegement is expressed to Ellen Ring and the staff of the Institute Text- Editing Facility for their skillful typing of the manuscript, to Rosemary Maddock for

valuable editorial suggestions, and to Betty Hurdle for coordinating the final stages of

publication of these proceedings.

Melvin Linzer

Conference Chairperson

and Moderator

vi
ABSTRACT

An international Seminar on Ultrasonic Tissue Characterization was held

at the National Bureau of Standards on May 28-30, 1975. The meeting was co- sponsored by the National Bureau of Standards, the National Science Foundation

and the National Institutes of Health. This volume contains extended versions

of 21 of the 22 talks presented at the Seminar. Topics covered include techniques for measurement of ultrasonic tissue parameters, the dependence of tissue

properties on physical and biological variables {e.g., ultrasonic frequency, tem- perature) and pattern recognition techniques.

Key Words: A-scan; absorption; acoustic; attenuation; B-scan; frequency; image

reconstruction; impedance; medical diagnosis; microscopy; pattern recognition;

scattering; tissue characterization; tissue parameters, tissue signature; tumor; ultrasonic spectroscopy; ultrasound; velocity.

vii

CONTENTS

Page

INTRODUCTION 1

CHAPTER 1 - OVERVIEW

1.1 The NSF (RANN) Integrated Program on Medical Ultrasonics - G. B. Devey 7

1.2 Challenges and Opportunities in Ultrasound (Keynote Address) - J. M. Reid n

CHAPTER 2 - TISSUE PARAMETERS

2.1 Ultrasonic Attenuation, Absorption, and Velocity in Tissues and

Organs - F. Dunn 21

2.2 The Scattering of Ultrasound by Tissues - J. M. Reid 29

CHAPTER 3 - A-SCAN PATTERN RECOGNITION TECHNIQUES

3.1 Use of Pattern Recognition for Signal Processing in Ultrasonic Histopathology - K. Preston, Jr., 51

3.2 Quantitative A-Scan Analysis of Normal and Cirrhotic Liver - P. N. T. Wells, R. A. Mountford, M. Halliwell, and

P. Atkinson 61

3.3 Digital A-Scan Analysis in the Diagnosis of Chronic Splenic

Enlargement - K. J. W. Taylor and J. Milan 71

CHAPTER 4 - ATTENUATION AND VELOCITY TECHNIQUES

4.1 Attenuation and Velocity Measurements in Tissue Using Time

Delay Spectrometry - D. H. Le Croissette and R. C. Heyser 81

4.2 Methods of Tissue Identification by Ultrasonic Spectra - ^ A. Sokollu, E. W. Purnell, E. Holasek, W. Jennings, and

A. Kaya 97

4.3 Algebraic Reconstruction of Spatial Distributions of Refractive

Index and Attenuation in Tissues from Time-of-Fl ight and

Amplitude Profiles - J. F. Greenleaf and S. A. Johnson 109

4.4 Measurement of Ultrasonic Tissue Characteristics by Direct

and Phase-Contrast Imaging - R. S. Mezrich, D. H. R. Vilkomerson,

and K. F. Etzold 121

4.5 Reflection Techniques for Measurement of Attenuation and

Velocity - G. Kossoff 135

CHAPTER 5 - ABSORPTION TECHNIQUES

5.1 Ul trasonical ly-Induced Transient Thermal Gradients: Their

Potential Role in Acoustic Parameter Characterization of

Tissue - F. J. Fry 143

5.2 TAST: A Non-Invasive Tissue Analytic System - T. D. Sachs,

P. T. Anderson, R. S. Grimes, S. J. Wright, Jr., and

R. M. P. Donaghy 153

ix

i
Page

CHAPTER 6 - SCATTERING TECHNIQUES

6.1 Tissue Characterization by Ultrasonic Frequency-Dependent

Attenuation and Scattering - P. P. Lele, A. B. Mansfield,

A. I. Murphy, J. Namery, and N. Senapati 167

6.2 Frequency and Angular Dependence of Ultrasonic Scattering

from Tissue - C. R. Hill 197

6.3 The Scattering of Ultrasound by Red Blood Cells - K. K. Shung, \/

R. A, Sigelmann, and J. M. Reid 207

6.4 Swept-Frequency Ultrasonic Determination of Tissue Macrostructure - R. C. Waag, R. M. Lerner and R. Gramiak 213

CHAPTER 7 - IMPEDANCE PROFILE TECHNIQUES

7.1 Acoustic Impedance Profiling: An Analytical and Physical Model

Study - A. C. Kak and F. J. Fry 231

7.2 Current Problems in Ultrasonic Impediography - J. P. Jones 253

CHAPTER 8 - ACOUSTIC MICROSCOPY

8.1 Tissue Characterization by Means of Acoustic Microscopy - L. W. Kessler 261

REGISTRATION LIST 271

AUTHOR INDEX 283

SUBJECT INDEX 287

X
INTRODUCTION

Recent developments in ultrasonic imaging and grey-scale technology have made it possible

to visualize at high resolution the internal texture of tissue and relate the texture to tissue pathology. In spite of these impressive successes, however, current clinical instruments provide data on only two tissue properties, backscattered echo strength and medium

attenuation, neither of which is separated experimentally. Because there are many different

modes of interaction of ultrasonic energy with tissue, a vast amount of additional information is potentially available from an ultrasonic signal. This includes such basic acoustic

parameters as absorption, velocity, attenuation, scattering, impedance, and their dependence

on frequency and other physical variables. In principle, suitable in vivo techniques could

be devised which will extract and separate many of the medically-significant features of the

ultrasound interactions. The development of such quantitative techniques for measurement of

ultrasonic tissue parameters is only now receiving the attention of the research community

and is perhaps the last major frontier in medical ultrasound.

In order to provide focus and direction to this emerging field, an international Seminar

on Ultrasonic Tissue Characterization was held at the National Bureau of Standards on May

29-31, 1975. The conference was cosponsored by the National Science Foundation (NSF),

National Bureau of Standards (NBS), and National Institutes of Health (NIH). The principal

objective of the Seminar was to assess the current status of and prospects for research into

the non-invasive characterization of normal and pathological tissue using ultrasound. The

Seminar was the first devoted to a comprehensive examination of tissue parameter measurement

techniques. Additional topics included the dependence of tissue properties on physical and

biological variables {e.g., ultrasonic frequency, temperature), pattern recognition, and the

development of a tissue signature library. Because of the extensive coverage of imaging and

Doppler techniques provided in the periodic International Symposia on Acoustical Imaging

and Holography, these areas were specifically excluded from consideration at the Seminar.

The Seminar was especially noteworthy for the participation of the world's leading

researchers in ultrasonic tissue characterization. The attendees, who numbered more than

220, came from the United States, Canada, Europe, Japan, South America and Australia. The

group was truly interdisciplinary, comprising life, physical, and materials scientists,

physicians, engineers, and physical science and health care administrators. For many of

these individuals, the Seminar afforded a first opportunity to communicate with fellow

researchers in divergent fields on problems of mutual interest in tissue characterization.

All of the speakers were carefully selected so as to provide a coherent program. Following the introductory remarks and keynote address, the technical program opened with a session

on tissue parameters. This was followed by sessions devoted to techniques for measuring individual tissue properties. A major criterion for inclusion of a particular technique was

that it be suitable for eventual application to in vivo clinical diagnosis.

Two panel discussions followed the technical sessions. The first panel attempted to assess the relative potential of the various methods presented during the Seminar and to delineate the most promising directions for future research. The second panel considered the

steps necessary to establish a tissue signature library, including the formulation of stan- dardized test methodology and standardized reporting procedures for diagnostic results.

Lively and extensive floor participation occurred throughout both the technical sessions and

panel discussions.

The introductory session opened with a welcome address by J. D. Hoffman, Director

of the Institute for Materials Research (NBS). Dr. Hoffman noted the similarities between

standardization and measurement needs in ultrasound for medical non-invasive diagnosis and for

nondestructive evaluation of materials. NBS has programs in both areas and perhaps could

serve as a bridge between the biomedical and materials communities in ultrasound technology.

G. B. Devey, NSF/RANN (Research Applied to National Needs), reviewed the key role which NSF

has played in organizing a nationally-integrated program in medical ultrasound. Current RANN

programs emphasize tissue characterization techniques and high resolution imaging, with over

$1.4 million to be made available in 1976 to support research in these areas. The keynote

speaker, J. M. Reid (Institute of Applied Physiology and Medicine, Seattle) spoke of the great

promise of ultrasonic parameter measurements for medical diagnosis but deplored the lack of

substantive implementation of this approach in current clinical practice. He also discussed

some of the problems associated with research on in vitro specimens.

1
The session of tissue parameters (p. 21) was partly tutorial. It opened with a discussion by F. Dunn (University of Illinois, Urbana) on the mechanisms of and available data

on attenuation, absorption, and velocity parameters, followed by a talk by J. M. Reid on the

basic physics of scattering. Dr. Dunn pointed out that the attenuation values observed in

tissue fall naturally into categories determined by the relative concentrations of water and

structural protein within the tissue.

The major portion of the scientific program was devoted to tissue characterization methods and opened with a session on A-saan pattern recognition techniques (p. 51). The session

dealt with both human- and computer-based aspects of pattern recognition. The talk by K. C. Ossoinigi (University of Iowa, Iowa City) demonstrated how a trained operator, using carefully

calibrated equipment, can successfully identify eye pathology from subtle differences in complex A-patterns. This approach is essentially the one-dimensional equivalent of the

application of the sophisticated human eye-brain complex in picture pattern recognition, as employed in traditional x-ray and ultrasonic radiology. K. Preston (Carnegie-Mellon University, Pittsburgh) discussed a recently-initiated program concerned with the development

of computer-based techniques for in vivo liver diagnosis in which biopsies from the insonified

regions are being used to establish correlations. He reported some preliminary results on the down-conversion of ultrasonic A-scan signals to the audio frequency range so as to utilize

the ear-brain complex for pattern recognition. This approach is borrowed from a target

classification scheme employed in sonar. At the end of his talk, the audience was treated

to a conference "first" - the opportunity to hear an audio recording of a transformed A-scan

from a normal liver.

Two papers by P. N. T. Wells and coworkers (Bristol General Hospital and Bristol Royal

Infirmary, Bristol, U.K.) and K. J. W. Taylor and J. Milan (Yale University, New Haven, and

Royal Marsden Hospital, Surrey, U.K.) dealt with digital A-scan analysis of echo amplitudes

to differentiate liver and splenic pathology, respectively. Because of statistical variations of absolute echo amplitudes among different individuals, this approach would be most

useful in monitoring response to therapy.

The session on attenuation and velocity techniques (p. 81) covered a variety of methods

providing either integrated or localized values of these parameters. The first two talks,

by D. H. Le Croissette and R. C. Heyser (Jet Propulsion Lab, Pasadena) and A. Sokollu and

coworkers (Case Western Reserve University, Cleveland), discussed transmission measurements

in the frequency and time domains and transformations between these domains. Dr. Sokollu

also reported on some recent clinical results using chromatic encoding of frequency response.

J. F. Greenleaf and S. A. Johnson (Mayo Clinic, Rochester) described a transmission measure- ment of tissue velocity distributions using computerized axial tomography. Attenuation

profiling, however, is much more difficult to achieve with this approach. R. S. Mezrich and

coworkers (R.C.A. Labs, Princeton) combined transmission attenuation and velocity measurements with a real-time imaging system exhibiting wide frequency and angular response. The

velocity measurement was accomplished by means of a phase-contrast technique which minimizes

effects of intervening tissue. G. Kossoff (National Acoustics Lab, Sydney, Australia) sug- gested several reflection techniques for obtaining velocity and attenuation parameters and

their frequency dependence. One of the velocity methods employs two transducers on the same

side of the tissue separated by a known distance and is similar in concept to the image re- construction approach.

The session on absorption techniques (p. 143) dealt with two indirect methods for in

vivo measurement of this parameter. Both methods depend on the detection of the velocity

change induced by the temperature increase associated with absorption of ultrasonic energy.

In the first talk, F. J. Fry (Fortune-Fry Labs, Indianapolis) described early work and some recent experimental results on the creation of a velocity gradient by ultrasonical ly heating

an absorption gradient within the tissue. Since impedance is proportional to velocity, the

resulting change in impedance across the absorption interface could be probed by pulse-echo

techniques. T. D. Sachs and coworkers (University of Vermont, Burlington) discussed an ex- tension of this technique to homogenous tissue using a differential velocity measurement

and reported experimental results on detecting ventricles and other structures within an excised brain.

ifhe manuscript of this talk was unavailable at time of publication.

2
The session on scattering techniques (p. 167) covered theoretical and experimental as- pects of both frequency and angular dependence of scattering and included some preliminary

clinical results. Talks were presented by P. P. Lele (MIT, Cambridge), C. R. Hill (Institute

for Cancer Research, Sutton, U. K.), K. K. Shung and coworkers (University of Washington,

Seattle), and R. C. Waag and coworkers (University of Rochester, Rochester). Excellent

agreement between theory and experiment was reported by Dr. Shung for scattering from blood

and by Dr. Hill for scattering from muscle tissue.

The session on impedance profile techniques (p. 231) opened with a talk by A. C. Kak

(Purdue University, West Lafayette) and F. J. Fry who described deconvolution techniques for

deriving the impulse response of tissue. The idealized model considered was a dispersionless

medium consisting of plane-parallel interfaces insonified at normal incidence. In the absence

of multiple reflections, integration of the impulse response yields the impedance profile of

the medium. Current problems and future directions of impediography were outlined by J. P. Jones (Bolt Beranek and Newman, Cambridge) who pioneered the development of the technique.

The final technical session was on acoustic microscopy (p. 261 ) and featured a description by L. Kessler (Sonoscan, Bensenville, Illinois) of a commercial device capable of measuring impedance, velocity, and attenuation of tissue samples up to 500 MHz. Although not

an in vivo technique, acoustic microscopy was included on the program because it can provide

acoustic parameter information on a more microscopic scale and at higher frequencies. Such

studies can serve to clarify the acoustic interactions observed at clinical diagnostic frequencies .

The talks, audience comments, and panel discussions at the Seminar succeeded in presenting a comprehensive picture of the state-of-the art in ultrasonic tissue characterization. It was evident, however, that although the field is now undergoing rapid change, it

is still in a preliminary stage of development. Much of the methodology is unable to provide sufficiently quantitative information on the ultrasonic properties of tissue in an ex- perimental or clinical environment For example, the underlying theory for the interpretation

of scattering data is as yet unable to cope with the complexities of tissue structure, while

for other parameters, such as absorption, the techniques are not sufficiently developed for

in vivo application. One can only hope that the improved scientific communication engendered

by the Seminar will provide the impetus to overcome many of these hurdles. Increasing

support now being given by federal funding agencies such as NSF and NIH, as well as new thrusts

underway on quantitative ultrasonic nondestructive evaluation of materials are also certain

to stimulate considerable research activity in ultrasonic parameter measurement.

The conference undoubtedly marked a milestone in the development of medical ultrasound

as a major non-invasive diagnostic technique. The consensus among the distinguished participants was that the meeting was one of the most significant in the history of ultrasound. As

an indication of their enthusiasm, the attendees voted unanimously to return to NBS in about

December, 1976 for another Tissue Characterization Seminar. It is anticipated that future

Seminars will be convened at eighteen-month intervals and will serve as the principal forums

for reporting new advances in ultrasonic parameter measurement. These Seminars would be

complemented by the International Synosia on Acoustical Imaging and Holography, also held at

18-month intervals, which are recogn zed as the major conferences devoted to imaging and

Doppler technology. In the periods between these topical meetings, the researchers in ultrasonic parameter and imaging techniques would have the opportunity to communicate results at clinically-oriented conferences, such as the annual AIUM meetings, or physics- and engineering- oriented meetings such as the annual IEEE Ultrasonic Symposia.

The Proceedings of the Seminar, published in this volume, should play a landmark role

in the future development of the field. Speakers were invited to submit extended papers to

the Proceedings based on their oral presentations at the Seminar. With the cooperation of

the authors, these contributions were carefully reviewed and edited to provide a cohesive

picture of the current status and potential of ultrasonic tissue parameter measurement.

It is anticipated that by the next Tissue Characterization Seminar, substantial progress

will have been made in placing the various techniques on firm theoretical bases and in the

refinement of the methodology and instrumentation to permit in vivo diagnosis. Success in the clinical measurement of ultrasonic tissue parameters is likely to be accompanied by

the development of simultaneous tomographic displays of the parameters in a format suitable

3
for interpretation by a physician. Such displays could take the form of a color TV presentation in place of the familiar grey-scale display; the different colors would represent

basic acoustic parameters, or such physical variables as frequency or temperature response.

Regardless of the degree of sophistication achieved in the immediate future, however,

there is no question that research into quantitative tissue characterization will ultimately

result in dramatic improvements in the capability of medical ultrasound. When combined

with real time, high-resolution imaging and implemented routinely in a clinical environment,

these techniques could revolutionize medical diagnosis.

Melvin Linzer

Conference Chairman and

Moderator
CHAPTER 1

OVERVIEW

5
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1

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National Bureau of Standards Special Publication 453. Proceedings of Seminar on Ultrasonic

Tissue Characterization held at NBS, Gaithersburg, MD, May 28-30, 1975. (Issued Oct. 1976)

CHAPTER 1. OVERVIEW

Paper 1.1: THE NSF (RANN) INTEGRATED PROGRAM ON MEDICAL ULTRASONICS

G. B. Deveyi

Instrumentation Technology Program

Research Applied to National Needs (RANN)

National Science Foundation

Washington, D. C. 20550

Recommendations made by the National Science Foundation (NSF)

Survey Team on Ultrasonic Imaging for the conduct of a Medical Instru- mentation Experiment to provide incentives to commercial firms and

for the preparation of an R & D agenda for future developments in medical

ultrasonics have been implemented. Projects emphasizing substantial

improvements in resolution of medical ultrasonic images and investigations

into ultrasonic tissue characterization are listed at high priority. The

NSF (RANN) Instrumentation Technology program supports research in these

areas. In addition to having good potential for making substantial

technological advances, the funded projects must also develop the criteria

which should be met before results of the research are introduced into

clinical medicine. Successful results from a coordinated research and

development program in ultrasonic tissue characterization could

revolutionize medical diagnosis.

Key Words: Applied research; imaging; instrumentation technology; medical

ultrasonics; NSF; RANN; R&D incentives; tissue characterization; tissue

signature; ultrasonic diagnosis; ultrasound

1. Introduction

In 1973, the RANN (Research Applied to National Needs) Program of the National Science

Foundation (NSF) organized a survey team for the purpose of evaluating the state-ofdevelopment of medical ultrasonic diagnostic instruments. The results of the survey are

found in the report, "Prospecti ves for Ultrasonic Imaging in Medical Diagnosis" [1]."^

One outcome of the NSF survey team recommendations was the establishment of a Medical

Instrumentation Experiment (No. 5) by the NSF Office of Experimental Research and Development

Incentives (RDI). Twelve industrial firms agreed to participate in the experiment, which

was implemented in 1974; the objective is to promote the development of advanced medical

ultrasonic diagnostic instruments using existing technology to meet the advanced performance

specifications included in the protocol of Experiment No. 5. The incentive to industrial

firms is the opportunity for no-cost clinical validation to be made of the instruments

to be developed to meet these specifications. The essential validation tests would be

conducted by the Veterans Administration (VA) under a $3 million agreement with NSF. An important element of the VA program is the conduct of an extensive training program in medical ultrasonics.

^Present address: Office of International Programs, National Science Foundation,

Washington, DC 20550.

^Figures in brackets indicate the literature references at the end of this paper.

7
The "Prospecti ves Report" includes a recommendation that an R & D agenda be prepared

for future developments in ultrasound. The agenda should include four elements, viz.,

(1) interaction of ultrasonic energy with biological structures; (2) ultrasonic transducers;

(3) displays and scans; and (4) signal processing.

These elements have been examined by four task groups established by the Alliance for

Engineering in Medicine and Biology (AEMB) under a grant (ATA 73-03255A03) from NSF. The

report, "A 5-Year Research and Development Agendum for Ultrasonic Imaging Diagnostic

Instrumentation," is the result of this examination and is available from the NTIS [2]. i

! 2. The NSF (RANN) Instrumentation Technology Program

I This program area seeks to support applied research projects that hold high promise to make substantial improvements (not incremental improvements) in instrumentation technology.

There is a willingness to support "high risk" research. An adequate and unexploited ; scientific/technological base must exist from which the applied research project can draw. i RANN emphasis is on applied research rather than on basic research.

Another feature of RANN-supported applied-research projects is that "exit criteria"

' must be stated clearly. That is, we want to know in advance how to determine when the

project should move from applied research to development to clinical application. An important factor is to determine how and when the results of the research are to be I transferred to user groups.

3. Areas of Support

In the current fiscal year (1975), areas of support in medical ultrasound are:

(1) high-resolution imaging research, and (2) tissue characterization. Both of these

areas are noted as high priority areas by the AEMB Task Groups. The goal for resolution I capability, as noted by the AEMB Task Group on "Ultrasonic Transducers: Signal Detection

and Preprocessing," is:

! Field of view (minimum) 25x25x25 cm^

Range (minimum) 25 cm Resolution (minimum) 1x1x1 mm. \

I The second area of support, tissue characterization, is viewed as developing new, i more powerful non-invasive techniques based upon the measurement of ultrasonic parameters I of tissue. Successful results from research in the area of ultrasonic tissue characterization would revolutionize medical diagnosis, thereby providing great economic and social

benefits.

4. Current RANN Projects '

s The RANN Instrumentation Technology program activity added $715,000 to Federal support

j of research in medical ultrasonics during fiscal year 1975, as shown in Table 1. The NSF

budget request to Congress would increase allocations for the Instrumentation Technology

Program area to $1,400,000 in fiscal year 1976. \

The area of ultrasonic tissue characterization is viewed as being one where sufficient i scientific and technological information exists on which to base a coordinated investigation \ to develop the concept for introduction into clinical medicine. The scientific and techno- i logical base began to be developed some twenty years ago with the pioneering work of , Dr. J. M. Reid. Since then, he and a growing number of other investigators have added to the base of knowledge, as demonstrated in the papers read at this Seminar. Important

contributions to the advancement of ultrasonic tissue characterization for introduction to \ clinical medicine have developed in areas unrelated to biology and ultrasound. Developments I in low-cost high-capability data processing, pattern recognition, information theory, and

large-scale integrated electronic circuits from research and development conducted in the i mathematical and physical sciences have provided the technologies needed to demonstrate the \ concept of tissue characterization. Another important aspect of applied research in ultra- | sonic tissue characterization is that a reasonable cost and time period for federal support

is involved to reach a "go - no go" decision point in determining the value of the concept.

'

8
Table 1 Breakdown of RANN-Supported Research in Medical Ultrasound

in Fiscal Year 1975

Princi pal

Investigator

K. Preston, Jr.

C. F. Quate

J. H. Busser

Institution

Carnegie-Mel Ion

Uni versity

Stanford University

Alliance for

Engineering in

Medicine and

Biology

M. Linzer

D.H.R. Vilkomerson RCA Laboratories

National Bureau

of Standards

R. C. Waag University of

Rochester

Ti t1 e Amount

Signal Processing for Ultra- $127,000

sonic Histopathology

Scanning Acoustic Microscope 108,700

Information Exchange and 118,800

Problem Assessments in

Medical Ultrasound

Seminar on Ultrasonic Tissue 12,000

Characterization

High Resolution Ultrasonic 99,000

Annular-Array Imaging

Tissue Characterization with 249,000

Ultrasound.

In NSF (RANN) terminology, a "milestone chart of accomplishments" can be designed, the

objectives can be stated with precision, there is an existing data base, and the expected

results can be described concisely.

Two policy issues need to be examined during the course of the conduct of applied research

projects in tissue characterization. These are: (1) proper "exit criteria" for federal

support, and (2) criteria for introduction into clinical medicine. Such issues are becoming

more important as we attempt to cope with allocations of limited national resources. The

Federal Government should not be expected to support the development of ultrasonic tissue

characterization indefinitely, and the concept should not be introduced into the health care

system until the consequences of doing so have been thoroughly assessed.

5. Necessary Action

What is needed to accomplish all of this? First, it is important to have a formal

mechanism whereby investigators all over the world can exchange information on developments

in ultrasonic tissue characterization. Secondly, it is important to establish a formal

mechanism for the preparation of plans for the utilization of the results of research in

ultrasonic tissue characterization; detailed plans for the operation of a tissue signature

library should be drawn. Such plans should be based on the assumption that ultrasonic

tissue characterization will be introduced into clinical practice. The cost of doing so

is small; little would be lost if the great promise of ultrasonic tissue characterization

fails to be realized, but great progress in clinical medicine could happen quickly if

the results occur as anticipated.

6. A Challenge

The preparation of criteria for the introduction of a new procedure or technique into

clinical medicine is something that researchers and clinicians are unlikely to accept with

alacrity. The concept of "acceptance criteria" perhaps is counter to the common view that

highly-beneficial developments are adopted quickly and that unsuccessful developments are

ignored. But what of mediocre advances? Can the United States (or the World) long afford

the luxury of haphazardously subjecting new developments to the vagaries of the clinical

medicine marketplace?

To develop criteria for the introduction of new procedures into clinical medicine

requires the concerted attention of a mul ti disci pi i nary group of scientists, engineers.

9
physicians, health care administrators, health economists (academic and private insurers i representatives), and lawyers. A possible mechanism for examining these issues would be I the establishment of an ad hoc Committee for Ultrasonic Research Evaluation (CURE). i

7. Conclusion

1 The next few years hold high promise for additional substantial advances to be made

in non-invasive medical diagnosis through ultrasonics. Ultrasonic tissue characterization

is an area of scientific investigation wherein advances in medicine would "be manifest

through the development of practical automated test (diagnostic) instruments and new technique^

which will be vastly more efficient and effective than those available today, thereby

contributing substantially to our ability to provide quality medical care for all. This

well might be one of the most important contributions that engineering can make to the

welfare of mankind..." [3].

References

^ [1] Prospectives for Ultrasonic Imaging in Medical Diagnosis, Report of the NSF Survey I Team on Ultrasonic Imaging, National Science Foundation, Washington, DC (1973).

[2] A 5-YeaT Research and Development Agendum for Ultrasonic Imaging Diagnostic Instrumentation, (The Alliance for Engineering in Medicine and Biology, Chevy Chase, MD,

Publication No. N-1975-1, April 1975), available from the National Technical

Information Service, 5285 Port Royal Road, Springfield, Virginia 22151, Publication

No. PB-230010/AS.

[3] Devey, G. B., The conference in retrospect, in Proceedings of the International

Conference on Engineering in Automated Multiphase Health Testing, p. 431 (Engineering

Foundation, New York, 1971), Library of Congress Catalog Number 79-175127.

10
National Bureau of Standards Special Publication 453. Proceedings of Seminar on Ultrasonic

Tissue Characterization held at NBS, Gaithersburg, MD, May 28-30, 1975. (Issued Oct. 1976)

Paper 1.2: CHALLENGES AND OPPORTUNITIES IN ULTRASOUND

Keynote Address

John M. Reid

Institute of Applied Physiology and Medicine

and Providence Hospital

Seattle, Washington 98122

The scientific study of the ultrasonic properties of tissue is on the threshold of being able to contribute useful knowledge needed

to improve the utility of ultrasonic medical diagnostic instruments.

There is ample evidence to support these contentions and to guide our

future course.

Key Words: Diagnosis; Doppler effect; optimization; resonance;

scattering; tissue characterization; tissue parameters; tumor detection; ultrasound.

Traditional keynote addresses begin by considering why we are here, how we got here, or

where we are going. I will follow this format today. This is not a research paper; it

nearly always end with the conclusion that "more research needs to be done." The previous

speakers have made excellent statements of why we are here. I think it is very exciting to note that this is the first conference devoted entirely to the topic of the passive, that is,

information-containing, interactions of ultrasound and tissue. The idea that information

could be gathered from tissues through their interactions with sound waves is an old one,

but one that certainly was not as accepted as the enthusiastic, sizeable audience here today

indicates. In one of the early papers on the effect of tissues on ultrasound, the manuscript

suffered a curious change [1].^ The editor had reversed the title in accordance with long

habit and instead of reading "The Effects of Tissues upon the Ultrasound," it was entitled

"The Effects of Ultrasound on Tissues!" Of course, we wrote back that this was not what we intended at all, that the ultrasound was doing nothing to the tissues and would they please

reverse the caption to have it read the way we had intended. This was done; the title of

the paper appeared as we intended, but the running lead on each of the succeeding pages on

that article was entitled "The Effects of Ultrasound on Tissues."

1 . Present Status

The very existence of this meeting, I believe, signals an end to the empirical era

through which most diagnostic equipment and techniques evolved. This was a process of

"trying out" what seemed to be good ideas. Equipment parameters were changed in the clinic

in attempts, that were not always successful, to contribute useful information about the

state of a patient.

Today we are on a threshold. Meetings such as this one present new opportunities which

will lead, if followed, to new ways to contribute to the effectiveness of non-invasive diagnosis. This threshold consists of a series of new challenges. Many of the challenges derive

from the fact that this is a new field, and that we are involved in establishing a new scientific field of study. We have all seen the symptoms of the birth of this new science. We

have had difficulty with the editorial boards of existing publications, our efforts have had

difficulty fitting into the organized departmental structure at both universities and hospitals. Our industrial members have seen dismay in the faces of market researchers and sales

people as they try to assess the possibilities of diagnostic ultrasound. In many ways, we

Figures in brackets indicate the literature references at the end of this paper.

11
have been fighting to get new ideas into closed minds, minds that were certain that all that

was worthwhile had been discovered, and that nothing new could be added.

To cross this threshold, however, we must face up to the demands placed on a truly

scientific field. The medical profession expects a great deal of the underlying sciences.

Medicine has dealt largely with fields with scientific foundations for almost the past 100

years and some expectations have developed. These other fields have recently arrived at or passed over their own thresholds. They thus can contribute mightily to the medical practice

of the future, and it might be instructive to consider just how and why these fields achieved

their present stature.

We now know that x-rays are able to image soft tissue structures. The development of

image-reconstruction techniques such as the EMI scanner was due to the ability of some workers in this field to overcome their a priori assumptions that x-rays could not image

soft tissues. We all knew that this could not be done, and scientific boards governing the

allocation of research money refused several times to put money into such an obviously Im- possible device! It was due to the vision of private industry that this development came

about. The ability to image soft structures in completely inaccessible locations such as the head has led to large strides in the diagnosis and care of cerebral disorders. This

ability is now available for the whole body. Multi-tube stop-action images appear to be

possible for the heart.

The field of nuclear medicine has made a number of specific contributions to diagnosis,

but many current workers are not satisfied with these. They are working with carbon com- pounds which are awkward to use and cannot be stored because of their extremely short halflife. The reason that these heroic efforts are being expended in a very difficult field is not too difficult to appreciate. The use of radioactive carbon compounds will make the entire

field of known knowledge in organic chemistry available to the diagnostician. If these

efforts of the nuclear medicine field are successful, we can look forward to a tremendous

increase in the knowledge of the function of the human body obtained non-invasi vely with

very minimal radioactive dose.

2. The Road Ahead

Our path is littered with questions: Just what is it that we want to do? Why should

it be done? And how can we do it? The hardest question is, does evidence exist that knowledge of acoustic properties of tissue will lead to successful characterization? That is, i will it increase the ability of ultrasonic diagnostic instruments to perform diagnoses, will 1 it lead to new concepts and new types of equipment? These could be just pious hopes, al- 1 though we certainly think not. The possibility of self-deception reminds me of W. C. Fields' ! temperance lecture, which says something like "every drunk thinks the world revolves around I himself, and it usually does!". I have some examples which indicate to me that there is con-

|

siderable promise in the field. This personal conviction arises from that fact that most of j these examples are my own, but I hope you will bear with me.

The first example is on the diagnosis of cancer. The first quantitative measurement

j which characterized a tissue was a measurement from the A-scope trace derived by Wild and I Reid in 1952 [2], The suggestion that cancer diagnosis can be done with ultrasound has not achieved clinical success anywhere except in Japan. Why does present equipment not function

well in the diagnosis of cancer? The answer must be that the design of conventional clini-

| cal apparatus was based on a priori assumptions; mainly, that high resolution and the achieve-(

ment of geometric localization were the most important design criteria. This led to the use of somewhat lower frequencies to obtain penetration, coupled with wider fractional bandwidths

to restore resolution. To further aid in the outlining of structures, fast time-constant,

or differentiator circuits were introduced into the video amplifiers. It was subsequently

shown that this type of circuit will remove the criteria used by Wild and Reid in their

attempt to quantitate the A-scope [3]. The result has been equipment which does some jobs

very well. When we are asked why we cannot detect cancer with the equipment, the reply

must be that most of the design assumptions are wrong for this application and that a com- pletely different type of machine should be used. We then complete the circular argument by

saying "but if we made it that way it wouldn't sell because the pictures would look different. "

12
Why have the Japanese been successful? Their equipment is more like the present clinical machines than like the Wild and Reid equipment, yet papers on the successful diagnosis

of breast cancer continue to come from Japan [4]. The techniques used by these workers,

however, are considerably different from the techniques used by others. By using a simple

parallel or sector scan, they have demonstrated that the shadows (which show the transmission

properties of the tumor) contain enough data to make diagnostic decisions. In our usual

practice, however, the presence of shadows destroys resolution, and compound scanning is used

to fill in the shadows to obtain better looking pictures! Suggestions that compound scanning

in some applications can be deleterious to the information are met with skepticism and a firm

resolve to increase the use of compound scanning by providing automatic machine-driven compound scans so the operator will have no choice.

There are other, very positive examples of the information that is lurking just around

I the corner. I refer to the possibility of optimizing the design of present apparatus as well as of suggesting new apparatus based upon knowledge of the mechanism of the ultrasonic

tissue interactions with which we are dealing. The first optimization example is the selec-

! tion of ultrasonic frequency to detect red blood cells. If we know the frequency dependence

I of the scattering cross-section, as well as of the absorption constants and other factors

which govern the strength of the echo, we can look for an optimum frequency.

As reported by K. K. Shung in our paper "The Scattering of Ultrasound By Red Blood Cells,"

(p. 207, this volume) the frequency dependence of the scattering cross-section per unit volume

of red blood cells varies as the 4th power of the frequency. We also know from the accumulated experiences on the absorption of ultrasound (see F. Dunn; "Ultrasonic Attenuation, Absorption, and Velocity in Tissues and Organs," p. 21, this volume) that the product of absorpI tion constant, a, and wavelength. A, is a constant over the useful frequency range. Since

1 the absorption loss increases with the frequency (decreasing the received signal) and the

scattering increases with frequency (increasing the received signal), the product of these

two curves will have a maximum. The frequency at this maximum can be found by differentiating the appropriate equations. (See "The Scattering of Ultrasound By Tissues," p. 29, this

volume.) For scatterers which "fill" the beam, we use eq. [A-8],

4aARf

dP r + J- 9 -4aR r4.,9j:4"c=0 (1) = Constant ne = Constant f e ^

'

at f = c/axR, where c = velocity and R = range to scatterers. For a single scatterer, we use

eq. [A-6] similarly, 4aARf

1^ = Constant |f f ^ =0 (2)

at f = 1.5 c/aAR. The resulting optimum frequency is inversely proportional to the depth

and is plotted for aA = 0.03 in figure 1. The two lines apply to the cases of individual

cells in the beam of ultrasound and of a collection of cells completely filling the beam.

All other practical cases appear to be intermediate between these two. We see that there

is a considerable latitude in the frequency which achieves the maximum signal strength, but

also that the operating frequencies of present Doppler flowmeters could be substantially

reduced and better depth of penetration obtained.

The other example comes from study of the frequency dependence, using continuous waves,

of the reflections from a stretched calf mitral valve. The result is shown in figure 2,

which shows the reflection strength in dB below a perfect reflector as a function of frequency corrected for transducer diffraction and frequency response. Note a dip at about

2.9 MHz which indicates that a half-wave resonance effect is taking place in the substance

of the mitral valve. This curve explains why the 2 MHz transducers originally used when

echocardiography was first introduced in this country always gave stronger signals than the

2.25 to 2.5 MHz transducers currently used in echocardiography. The advantage of the lower

frequency ranges between 10 and 20 dB depending on whether we consider the gain at the center

frequency or some average over the band.

The absorption constant of the connective tissue comprising the substance of the valve

appears to be very low. An absorption per wavelength, aA, of about 0.003 was calculated

from the dip of figure 2. If other thin, layered connective tissue structures in the body

have such low loss, then the possibilities of highly frequency-selective resonances cannot

be discounted.

13
New knowledge of ultrasonic tissue properties would be put to use because there is room

for improvement in the field as it presently exists. Consider that the same transducer frequencies have been used in medical applications as were previously used in materials-testing

applications. These frequencies, at 2, 5 and 10 MHz, are in approximately 2:1 steps. The

very coarseness of the steps indicates that not much selective optimization has been done.

The design of the apparatus, as stated earlier, has been largely on a "suck it and see" approach. There is considerable room here for improvement. The aircraft industry does not

find it necessary to crash many planes these days to prove that a new design can fly. They

are able to determine not only that it can fly, but also its profit potential under present

fare schedules, while it is still on the drawing board. We are still, in contrast, at the

embryonic stage of crashing our designs in the clinic!

100

.0 1 .0 2 .OS 1.0 2.0 5.0 10

DEPTH, cm MUSCLE

Figure 1. Ultrasound frequency for maximum scattered amplitude for Rayleigh scatterers.

j Upper limit of optimum frequency area applies to single scatterers and the lower limit , to randomly-distributed scatterers which fill the sound beam. The curve predicts the

[ optimum operating frequency for ultrasound Doppler flowmeters.

Further optimization is possible if we understand the effect of tissue parameters in setting fundamental limits to the operation of our equipment. Calculations show that frequency dependence of absorption can result in pulse-stretching by a factor of about 2, that

refraction due to subcutaneous fat can deviate the beam by nearly the beam width and hence

badly blur the pictures at maximum range of present equipment, and that the possible dispersion of the velocity of sound in absorbing tissues can lead to a considerable spectrum

distortion and further pulse stretching at maximum ranges [5].

Another reason for thinking there is considerable hope is the realization that has been

forced upon me that engineers and medical doctors are not trained as scientists. Although

scientists exist in both fields, they undergo a rather long and rigorous training program.

Those without this training have found it even more difficult than those with training to impress medical scientists that the work they propose is valuable and can be done by them.

When we speak to our peers in an unfamiliar tongue, we must speak with great clarity to get our points across. Let us increase our communication skills.

14
(dB)

10

20

30

40

50

60 L_

REFLECTION FROM CALF MITRAL VALVE (dB BELOW INCIDENT WAVE)

1.0 2.0 FREQUENCY MHz

3.0 4.0

Figure 2. Frequency dependence of continuous wave reflections from calf mitral valves

relative to the reflections from a perfect reflector at the same range. Dots are experimental points taken using gated bursts of more than ten cycles. Solid line was calculated for the reflection coefficient of a 1/2 wave, one-dimensional transmission line section. Losses in the model section correspond to aX = 0.003.

3. What To Do?

The principal task before us, I believe, is to get on with it. Our job is to plow the corners of our field which are most amenable to our resources and our techniques in the

positive expectation that both expected and unexpected benefits will flow from our efforts.

A caution I must add is to please examine the basis for the experiments which you do,

so that your work will have the highest possible scientific value and hence the greatest

future utility to the field. To obtain system design information which has a scientific

basis, and is most useful, requires that the data be gathered in a manner which is independent of the gathering equipment. This is more easily said than done, particularly in the

case of scattering measurements where changes in wave shape upon reflection introduce un- expected dependence upon aperture, range and frequency (see "The Scattering of Ultrasound by

Tissues," p. 29, this volume).

Scientifically, only measurements which are independent of the measuring system characterize the tissue. Observations, such as the often-made observation of echo strength on angle, which are not so reduced, characterize the equipment as well as the tissue. Such

observations have limited utility in the exchange of information which is the life-blood of

science. Even worse, such observations are practically useless in equipment design.

Only if we have tissue parameters which are independent of the measuring equipment can

we choose equipment parameters when designing optimum diagnostic systems. This comes about

because the design process consists of steps taken in reverse order to that followed when

reducing measurement data to an equipment- independent form. Reduction starts with the raw

15
measurements obtained in terms of pulse heights or wave energy. Tissue parameters are derived by correcting for the effects of transducer aperture, range, pulse lengths, frequency

and so on. The result is a value for scattering cross-section or reflectivity which is independent of the measuring equipment. Consider now the task confronting a designer of a new

device. Depending on its intended application, the reflections from a particular tissue may

be considered either to contain the information or to be interference and noise which must be

suppressed. With both the "noise" and the "signal" parameters available for characterizing

the tissues in the propagation path, the designer can choose values for frequency, aperture,

range and so on, which will maximize the desired signal.

The very knowledge of the interaction equations will be a great aid in equipment design

and use. Consider the transmission or continuous-wave "camera" type imaging systems. The

effects of velocity differentials in forming diffraction images have been considered very

little. Large organs, such as the kidney, have a near field determined by the size of the

organ similar to the near field of a transducer. Diffraction effects will thus be responsible for some detail of the image at distances from the organ which are considerably greater

than the size of the human body. This may explain why semi -permeable structures can appear

to be either sonolucent or opaque depending on their position in the sound field. Also, the

illuminating field for each organ in the abdomen consists of the diffraction fields of all the organs which shadow it. This may be the reason that in vivo imaging with these devices

has not yielded pictures at all comparable with promising images obtained from the early in

vitro work. Understanding of the physics of the image-forming process thus could lead to far greater utility for these intriguing devices.

We should give some thought to the parameters which we will choose for tissue characterization and with the definitions that we will use for "tissue signature." The classical

parameters of absorption, velocity, scattering cross-section and reflectivity will be covered

in the next two papers. The literature abounds, however, with different meanings appended

to the term "signature." In the radar field, the target signature is regarded to be the

model for the fluctuations of scattering strength. Typical terms are Rayleigh, log normal,

etc., depending upon the statistical fluctuations. (There may well be a lesson here for

us in that statistical models of tissue parameter fluctuations are almost entirely lacking.

A Rayleigh distribution is to be expected from the observed frequency dependence of the

scattering from red cells, but we really know nothing about fluctuations from other tissues

except that practically all ultrasonic reflections do fluctuate.) We can consider various

heirarchies of signatures as used in ultrasonic diagnosis [6]. These range from a B-scan picture obtained on a particular apparatus, to the response of a tissue to a short pulse,

to the response to a true impulse which can, theoretically, be derived from the response to

a short pulse. The impulse response of the tissue is related through the Fourier transform

to the frequency-domain characterization of a tissue, but only if the data are corrected

(in both cases) to be independent of equipment parameters which are functions of frequency.

4. Scientific Standards

To perform adequately-detailed scientific studies, inlcuding the studies of mechanisms,

will probably require the use of in vitro specimens or animals other than man. We must be ever alert to the biological problems posed in the use of such preparations. We are con- cerned with mechanical properties and must be certain that these are preserved in our specimens. Biomechanics investigators seeking to establish the mechanical properties of blood

vessel walls discovered a few years ago, for example, that the state of contraction of the

smooth muscles was different in many of the arterial specimens that they were pulling and

twisting. The large but accepted biological variability was greatly reduced with pretreatment of the muscles to insure a repeatable contraction state. Apparatus for performing the

measurements must be designed with knowledge that tissue is a living thing with requirements \ of temperature, salinity and nourishment. The equipment must also allow our data to be

^ gathered in a convenient and repeatable fashion. The field will undoubtedly develop concepts,)

such as useful approximations, and equipment as we learn. j

These problems are simply a part of working in a new discipline. As we continue to open | this new field, we must always remember to keep our minds as open as we wish the minds of \ others had been when we began. A closed mind is, perhaps, our worst enemy and it is nowhere , as damaging as when the closed mind is our own. I

16 1
References

Wild, J. J. and Reid, J. M., The effects of biological tissues on 15 mc pulsed

ultrasound, J. Acoust. Soc. Am., 25^, 270 (1953).

Wild, J. J. and Reid, J. M., Further pilot echographic studies on the histologic

structures of tumors of the living intact human breast. Am. J. Path., 28, 839 (1952).

Reid, J. M., An evaluation of intensity-modulated recording for ultrasonic diagnosis,

J. Aooust. Soc. Am., 44, 1319 (1968).

Kobayashi , T., Takatani, 0., Hattori , N., Kimura, K., Watanabe, H., and Abe, 0.,

Clinical investigation for the differential diagnosis of breast tumor by means of

the degraded sensitivity method of ul trasonotomogram (II), Medical Ultrasonics, 10^, 81 (1972).

Task Group 4: Ultrasonic Diagnostic Signal Processing, in 4 5-Year Research and Development Agendvm for Ultrasonic Imaging Diagnostic Instrumentation, (The Alliance

for Engineering in Medicine and Biology, Chevy Chase, MD, Publication No. N-1975-1,

April 1975), available from the National Technical Information Service, 5285 Port Royal

Road, Springfield, Virginia 22151, Publication No. PB-230010/AS.

Task Group 1: Interaction of Ultrasonic Energy with Biological Structures, in A 5-Year

Research and Development Agendum for Ultrasonic Imaging Diagnostic Instrumentation, (The

Alliance for Engineering in Medicine and Biology, Chevy Chase, MD, Publication No. N-1975-1, April 1975), available from the National Technical Information Service, 5285

Port Royal Road, Springfield, Virginia 22151, Publication No. PB-230010/AS.

17

CHAPTER 2

TISSUE PARAMETERS

19
I

I

I

I
National Bureau of Standards Special Publication 453. Proceedings of Seminar on Ultrasonic

Tissue Characterization held at NBS, Gaithersburg, MD, May 28-30, 1975. (Issued Oct. 1976)

CHAPTER 2. TISSUE PARAMETERS

Paper 2."1: ULTRASONIC ATTENUATION, ABSORPTION, AND VELOCITY IN TISSUES AND ORGANS

F. Dunn

Bioacoustics Research Laboratory

University of Illinois

Urbana, Illinois 61801

Propagation relations for compressional waves in isotropic, elastic

media are described briefly and discussed with reference to ultrasonic

propagation in biological structures. A selected review of experimentally

obtained results from. tissues and organs is presented. It is shown

that characterization of tissues and organs by their acoustic parameters

should be possible.

Key Words: Absorption; attenuation; mammalian tissues; tissue parameters;

ultrasound; velocity.

1. Introduction

The "ultrasonic propagation properties of tissues and organs" include the behavior of

those measurable acoustic parameters, as functions of state and acoustic variables, which

characterize the fate of acoustic signals propagating within the biological environment.

The speed with which the signal propagates in the biological medium, the attenuation

and/or absorption of wave energy by the medium, and features of the medium responsible for

reflection and scattering phenomena, generally embodied in the impedance concept, constitute

the properties of interest. The present discussion treats briefly these properties with

the view toward identifying characteristics of tissues and organs essential in clinical

ultrasonic diagnostic procedures.

2. Propagation Relations

The pertinent relations describing acoustic phenomena in ideal fluid media are presented first. A brief discussion then follows on the alterations that must be made in order to describe events occurring in media which extract energy from the propagating wave

process

.

The wave equation describing propagation of mechanical disturbances in dissipationless , isotropic, elastic media is ^ = ^ vv-c - G V X V X ^ (1)

3t2 Po

where ? is the instantaneous displacement of an element of the medium from its equilibrium

position, t is time, K is the adiabatic bulk modulus, G is the modulus of shear rigidity,

and p is the mean density of the medium. The specialization for lossless fluid media is obtained by setting G equal to zero since these are characterized by an inability to

21
support an elastic shear strain. The one-dimensional elastic wave equation, as it applies

to an ideal, linear, homogeneous, perfectly elastic (dissi pationless ) liquid medium, is

3t2 Po^ 3X2

where Q^, the adiabatic compressibility, is the reciprocal of the adiabatic elastic bulk

modulus. The relations are approximations of the more general hydrodynamic equations

valid under the conditions that the particle velocity amplitude, (3c/3t)fjiax' ""S small

compared with the speed of sound in the medium and that the adiabatic compressibility is not significantly dependent upon pressure over the range of pressure variations occurring

in the sound field. Under such conditions, the free-field sound propagation velocity for

compressional waves is

1

The solution to eq. (2) is

(3) ,

which includes waves propagating along both directions of x. k is the wave number u/v,

and A and B are the amplitudes of the two wave components. The acoustic pressure in the

field can be defined as

P = P-Pq (5)

where P is the instantaneous pressure at a point of concern in the field and Pq is the

constant equilibrium pressure in the medium. The acoustic pressure and the particle

displacement are related by

P

= -P„v^ f . (6)

The quantity pqv, the product of the medium density and the sound velocity, is the

characteristic impedance of the medium, i.e._,

For plane traveling waves, this quantity is numerically equal to the specific acoustic

impedance which is defined as the ratio of the sound pressure p to the particle velocity

\ at any point in the field. For other field configurations, e.g., standing waves, the

specific acoustic impedance differs numerically from PqV and is, in general, a function of

position. Further, the characteristic acoustic impedance is dependent upon the type of wave propagating since the velocity of, for example, shear waves is different from that of

compressional waves.

The intensity I of the acoustic wave is defined as the time average of the rate of

transport of energy through unit area normal to the direction of propagation. It is related to the sound pressure amplitude and the particle velocity amplitude Eg for

plane traveling waves

P

^ jBaaoa P 5 Z H

i q\ 0

22
The energy density Eq of the wave motion at a specific position in the field is the sum of

the kinetic energy per unit volume of the moving element and the potential energy per unit

volume of compression (or expansion) of the element. For plane traveling waves, this

becomes equal to the ratio of the intensity to the wave velocity, i.e.^

P ^

0 2 „ 2 V

• 2pqV

When an ultrasonic wave propagates in a real fluid, wave energy is irreversibly

absorbed by the medium, by any of a variety of physical mechanisms. The occurrence of

this phenomenon modifies the phenomenological description of lossless plane-wave propagation

by the introduction of an absorption factor, i.e.^ eq. (4) becomes, for unidirectional

propagation in the positive x-direction

5(x,t) = Ae-«V('^^-^^) (10)

where a is the amplitude absorption coefficient per unit path length. When other loss

mechanisms occur, such as scattering (see "The Scattering of Ultrasound by Tissues,"

p. 29, this volume), a can be redefined as the total attenuation coefficient. The

Stokes-Kirchhoff classical absorption coefficient is

2PqV ^ p

/

where w is the angular frequency, os is the shear viscosity coefficient, hb is the bulk

viscosity coefficient, y is the ratio of specific heats, Cp 'is the heat capacity at constant pressure, and K is the thermal conductivity. This relation expresses the view

that energy transported by the wave process is converted to heat by virtue of the medium

possessing finite viscosity and thermal conductivity. The losses due to viscosity result

from the fact that, though a fluid cannot support a static shear, it can support a dynamic

one in the form of a viscous drag. The thermal conductivity process occurs because during

passage of an ultrasonic wave, temperatures will be greater in the regions of higher

acoustic pressure than in the neighboring regions of lower pressure, and heat will flow in

response to such gradients. The thermal conductivity term is, for biological media, very

much less than the viscosity terms and can be ignored. Equation (11) indicates that the

absorption coefficient should vary with the square of the frequency and that the temperature

dependence should follow that of the viscosity. However, liquids in general and biological

media in particular, do not often exhibit these dependencies in so simple a fashion and it

is necessary to consider that other relaxation processes are involved. Such processes

reflect the presence of mechanisms of energy transfer which require time [1].^ In the

following equation, the term A represents the classical absorption terms and the second

term describes a single relaxation process with f,- being the relaxation frequency:

A +

^

2

• 02)

f 1+(f/f^)

With regard to the second term, it is seen that at very low frequencies, such that the

period of the wave is long compared to the time required for energy transfer, it is constant

and has the value B, while at very high frequencies, such that the period of the wave is short compared to the time required for energy transfer, energy is not extracted from the wave process and this term vanishes leaving only the classical term. Again, it does not often happen that a single relaxation process is present and in order to describe observed

absorption spectra, it is necessary to consider a number of such processes occurring and

to sum on all of them [1], giving

^Figures in brackets indicate the literature references at the end of this paper.

23
i+(f/fi)'

(13)

3. Velocity of Ultrasound in Tissues

Goldman and Heuter [2] compiled a detailed list of ultrasonic velocity and attenuation

data in animal tissues. Therein, it is seen that the velocity in soft tissues, excluding

lung, is very nearly that of dilute salt solutions and varies only slightly among the

various tissues, with the exception being that fatty tissue has a velocity about 10% less

than that of non-fatty tissues. The reflection properties, which are of considerable

importance in clinical diagnostic procedures, can be discussed in terms of elementary

considerations for unbounded, lossless, homogeneous and isotropic media for which the

magnitude of the reflection coefficient R is, in terms of the characteristic impedances

{li, I-2) of the two contiguous media (see eq. (7)),

lyl^ (Pl/gsl)"" - (P2/^S2)''

^r^2 (p-,/B3-,)^ + (P2/es2)^

As the inertial property exhibits minimal variation among tissues, viz., variations less

than about 1% in density, Pi « P2 and eq. (14) can be written

(15)

It is apparent that the reflection characteristics of these media are dependent, for the

most part, upon the elastic properties of their components [3]. The speed of sound in lung tissue increases nearly linearly with frequency, in the low megahertz frequency

region, but has a value considerably less than other soft tissues [4] and depends upon

inflation [5].

Theismann and Pfander [6] measured the speed of sound in specimens of human skull and

found it to be approximately twice that of the soft tissues. As the density of bone is considerably greater than that of soft tissues, its impedance thus becomes nearly four

times greater (see eq. (7)). More recent studies provide a shear velocity, for freshly

frozen dog tibia, or approximately one-half that for longitudinal velocity [7,8].

4. Attenuation and Absorption of Ultrasound in Tissues and Organs

The following is a selected review of the experimentally-observed ultrasonic attenuationi

and absorption characteristics of biological tissues. Figure 1 shows the dependence of

the ultrasonic attenuation coefficient on frequency for a number of tissues [2]. Here,

the attenuation per cycle is plotted against the logarithm of frequency, for which classical

theory would predict a linear dependence with positive slope if the attenuation were due

solely to absorption. The broad shaded regions of figure 1 are partially accounted for by

the inclusion of all available data (at time of preparation), i.e., the figure includes

measurements by numerous investigators employing different experimental techniques under a variety of physical and biological conditions. Nevertheless, it is possible to discern

several relatively simple relationships, e.g., the attenuation per cycle is generally

constant over the frequency range considered. In a more recent investigation [9], mammalian

kidney tissue was shown to continue this linear dependence of the attenuation on frequency

to approximately 100 MHz, after which a quadratic (or greater) dependence prevails.

Further, this quantity increases slightly from 1 to 10 MHz for fat, and striated muscle

and liver appear to exhibit minima in the neighborhood of 2 MHz.

The important dependence of the absorption coefficient upon temperature has been

established as a function of frequency only recently [10,11]. Figure 2 includes observations'

on mammalian central nervous tissue of neonatal mice (essential poikilotherms) and adult

cats (homoeotherms ) . These data suggest a family of curves whose maxima decrease in magnitude and occur at ever higher temperatures as the frequency increases.

24
2.5

I r——^

1

'

[—I—I I I

I

1 r

0 I 1 \ I i ! I I I I I 1 I : : :

'

'

0.1 2 4 6 8 10 2 4 6 8 10 FREQUENCY(MHz)

Figure 1. Acoustic attenuation per wavelength (in dB/cm MHz) for several

mamalian tissues versus frequency [2].

0.8r

T(°C)

Figure 2. Frequency and temperature dependence of ultrasonic absorption

in mammalian central nervous tissue [11].

Several tissues are known to exhibit unique properties. An early study of speciallyprepared skull bone in the frequency range 0.6 to 3.5 MHz (25 to 35°C) exhibited a quadratic

dependence of the attenuation coefficient upon frequency, with a transition to lower power

dependence at high frequencies [12]. The average value for the acoustic amplitude attenuation coefficient per unit path length in skull bone, in the neighborhood of 1 MHz, was

found to be of the order of 1 Np cm~^ (1 Np = 8.68 dB), approximately an order of magnitude

greater than that of soft tissue at the same temperature. Recent observations have called

these values into question. Adler and Cook [7] have obtained attenuation measurements of

1.5 Np cm"i and 2.2 Np cm~i, in freshly-frozen dog tibia at, respectively, 3 and 5 MHz. Kishimoto [13] observed a positive temperature coefficient for the ultrasonic attenuation

25
in horse bone, and values of the shear velocity, approximately one-half that of the

longitudinal velocity, have been obtained [7,8]. Tissues such as cartilage, tendon, skin,

etc., having high concentrations of collagen, exhibit attenuation values approximating the

root-mean-square of those of organs and bone [14]. The acoustic amplitude attenuation

coefficient in freshly-excised dog lung at a fraction of residual inflation has recently

been shown to increase exponentially with frequency from 4.3 Np cm~^ at 1 MHz to 11.6 Np cm"^ at 5 MHz [4]. This frequency dependence has also been found for formalin-fixed preparations

which have provided some information on the dependence of attenuation on inflation [5].

The acoustic propagation properties of the refractive media of excised calf eyes have

have been studied [15], and table 1 is a summary of the data. It is noted that the

attenuation for the humors is approximately 50% greater than that of dilute salt solution,

suggesting that these media may possess a viscous-type frequency dependence, viz.,

increasing quadratical ly with frequency. As the lens contains a relatively high concentration of protein, it is tempting, in the absence of further information, to consider that

its frequency dependence resembles that of other soft tissues for which the absorption

properties are dominated by the protein content, viz., that it varies approximately

linearly with frequency. Investigators concerned with diagnosing disorders of the eye by

ultrasonic means feel that Begui's in vitro attenuation values are greater than those of

the human lens in vivo and speciation and measurement and handling techniques, no doubt,

provide explanations for the differences.

Table 1. Acoustic Properties of Refractive Media of the Eye [15]

Media T (°C) f (MHz) v (cm/s x IQS) a(Np cm-^)

Aqueous 27.5 30 1.497 0.35

Vitreous 1.516 0.35

Lens 28.0 3 1.616 0.70

5. Concluding Remarks

The above discussion was intended only as a selected review of the pertinent literature

dealing with ultrasonic propagation in tissues and organs. The comprehensive treatment

by Dunn et at., [16] and the definitive Workshop Proceedings of the Seattle Conference

[17] should be consulted for details. Therein, it will be seen that recent studies have

dealt with investigation of protein solutions for clues to the ultrasonic absorption

behavior of tissues and organs. It is apparent that a great deal must be accomplished

before a complete understanding of ultrasonic velocity and absorption by biological media

is obtained. From the previous work, it is possible to determine types of dependencies of

the attenuation and/or absorption as a function of some of the important field and state variables and it is possible to classify tissues into rather general categories as regards

these dependencies. However, the present state of experimental data does not allow for

the desired understanding of the mechanisms for any tissue structure or component relative

to even a single physical variable.

Table 2, following Dussik [14], is an attempt to characterize tissues according to their ultrasonic attenuation. It is seen that tissues can be grouped in apparent

teleologic fashion with a relatively narrow range of attenuation values within each group.

The attenuation approximately doubles from group to group in direction of increasing attenuation. Further, proceeding from group to group in the same direction, tissues of ever- decreasing water content and ever-increasing structural protein content become involved.

Thus, it is seen that ultrasonic attenuation can be invoked to characterize tissues according

to functional criteria. Possibly, detailed measurements will allow assignment of resolvably

unique values to each tissue structure including usefully differentiable values for

pathological states. Should this be the case, then ultrasonic attenuation and impedance

values, as functions of state and acoustic parameters, media, etc., should specify uniquely

tissues for diagnostic purposes.

26
Table 2. Ultrasonic Attenuation Characterization of Tissues

Attenuation

Classification

Attenuation

at 1 MHz (Np cm-i; Tissue

Tissue

Classification

Very low 0.003 serum Transport of metabolic

nu. mU 1 bl ood ma "f" o T 3 1 c llld Lcr 1 d 1 b

LUW 1 r\\Ai

Medium 0.1 brain Protoplasmic activity,

0.12 1 i ver physiological function

0.24 muscle

0.12 kidney

High 0.4 integument Structural, supporting.

0.5 tendon stress conveying, high

0.6 cartilage structural proteins

(collagen)

Very high 1 or more mineralized Framework protection (high

in collagen)

> 4 pulmonary Gaseous exchange

References

[1] Herzfeld, K. F. and Litovitz, T. A., Absorption and Dispersion of Ultrasonic Waves

(Academic Press, NY, 1959).

[2] Goldman, D. E. and Hueter, T. F., Tabular data of the velocity and absorption of highfrequency sound in mammalian tissues, J. Acoust. Soo. Am. 28, 35 (1956).

[3] Fields, S. and Dunn, F., Correlation of echographic visual izabil ity of tissue with

biological composition and physiological state, J. Acoust. Soc. Am. 5£, 809 (1973).

[4] Dunn, F., Attenuation and speed of ultrasound in lung, J. Acoust. Soo. Am. 56, 1638

(1974).

[5] Bauld, T. J. and Schwan, H. P., Attenuation and reflection of ultrasound in canine

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

[6] Theismann, H. and Pfander F., Uber die durchlassigkeit des knochens fur ultraschall,

Strahlentherapie, 80, 607 (1949).

[7] Adler, L. and Cook, K. W. , Ultrasonic parameters of freshly frozen dog tibia, J. Acoust. Soc. Am. 58, 1107 (1975).

[8] Lang, S. B., Ultrasonic method for measuring elastic coefficiency of bone and results

on fresh and dried bovine bones, IEEE Trans. Biomed. Engr. BME-1

7

, 101 (1970).

[9] Kessler, L. W., VHF ultrasonic attenuation in mammalian tissue, J. Acoust. Soc. Am.

53, 1759 (1973).

[10] Dunn, F. and Brady, J. K., Pogloshchenie ul'trazvyeka v biologicheski kh sredakh,

Biofizika 1063 (1973).

[11] Dunn, F. and Brady, J. K. , Temperature and frequency dependence of ultrasonic

absorption in tissue, in Proceedings of 8th International Congress on Acoustics^

p. 366c (1974).

27
[12] Hueter, T. F., Messung der ultraschall absorption im menschlichen schadel knocken

und ihre abhangegkeit von der frequenz, Naturwissensohaften, 39^, 21 (1952).

[13] Kishimoto, T., Ultrasonic absorption in bones, Acoustica, 8, 179 (1958).

[14] Dussik, K. T., Kyriazidov, M., Fritch, D. J., and Sear, R. S., Measurement of

articular tissues with ultrasound, Amer. J. Phys. Med. J7_, 160 (1958).

[15] Begui , Z. E., Acoustic properties of the refractive media of the eye, J. Aooust.

Soo. Am. 26, 365 (1954).

[16] Dunn, F., Edmonds, P. 0., and Fry, W. J., Absorption and dispersion of ultrasound

in biological media, in Biological Engineering, H. P. Schwan, ed.. Chapter 3, p. 205

(McGraw-Hill, NY, 1969).

[17] Interaction of Ultrasound and Biological Tissues, Workshop Proceedings, J. M. Raid

and M. R. Sikov, eds. (Bureau of Radiological Health, 73-8008, 1973).

28
National Bureau of Standards Special Publication 453 . Proceedings of Seminar on Ultrasonic

Tissue Characterization held at NBS, Gaithersburg , MD, May 28-30, 1975. (Issued Oct. 1976 )

Paper 2.2: THE SCATTERING OF ULTRASOUND BY TISSUES

John M. Reid

Institute of Applied Physiology and Medicine

Seattle, Washington 98122

Most ultrasonic diagnostic equipment are based on the observation of

the waves scattered by tissues. Although these instruments generally

perform useful cl inicaldiagnosis , they do not provide quantitative

measurements of the detailed characteristics of the scattered waves.

Such measurements should significantly improve the diagnostic capability

of medical ultrasound. The properties responsible for scattering have

been shown to be differences in compressibility and density between

adjacent tissue structures. The rationale of scattering measurements is considered through a review of direct measurements and substitution

techniques which correct for wave shape changes. The necessity of correcting

for apparatus parameters and the effects of overlying tissue attenuation

is considered. Equations are derived which relate the scattered power

to the scattering parameters of tissues and the measuring equipment

constants for a number of useful cases.

Key Words: Blood; cross-section; diagnosis; scattering; standardization;

tissue characterization; ultrasound.

1. Introduction

The scattering of ultrasound by tissues was established experimentally long before the

mechanism of scattering, could be ascertained with certainty and before any practical utility

of the scattered waves could be found in clinical medicine. Today, the subject of scattering

by tissues is extremely important from a practical sense. Pulse-echo and Doppler apparatus

which employ these scattered waves to investigate the structure and function of tissues

have found secure places in clinical medicine. Tissue identification and diagnosis are being routinely performed by observation of scattered ultrasonic waves in most hospitals.

The excellent probability that even more useful systems can be devised has been dealt with

in the Keynote Address (p. 11, this volume). For example, the introduction of grey scale

apparatus has refocused attention on the small amplitude echoes which are observed from the

interior of many organs within the body. Knowledge of the exact structures and tissue

properties responsible for these echoes would be immediately useful since clinicians using

existing technology could exploit this knowledge.

This paper will attempt a clear distinction between obsevvation and measurement of

scattering. As useful as observation has been, there are many differences of opinion between

laboratories and clinics about what can be diagnosed. This results since observations are

not quantitative and cannot be compared readily. Measurements are quantitative and can be

compared. More importantly, measurements of tissue properties, by definition, should be

independent of the apparatus used. This is not easily achieved in the case of scattering

measurements. Both observations and measurements are made with a particular piece of

equipment arid the results are colored by the particular acoustical and electronic characteristics of the apparatus.

Scattering measurements are inherently more difficult to make than are transmission mea- surements such as velocity and attenuation; these measurements result, at any given frequency,

in two numbers. In the scattering process, however, a new wave is generated and must be

29
specified. A number is also required to express the scattering strength. The scattered

wave thus requires a function and an amplitude for characterization, both of which are frequency-dependent.

Fortunately, approximations for ideal types of scatterers exist which are very useful

in characterizing interfaces and cellular scattering. Agreement between theory and careful

experiment is excellent. Work on the red cell (See Shung, Sigelmann, and Reid, p. 207, this

volume) has achieved excellent correspondence between scattering measurements and fundamental physical properties of the cell. Further extension of these methods to tissue is being pursued.

The basic thesis of measurement, as expanded below, is that one must separate the

properties of the tissues from the properties of the equipment. By reducing the data

ob'.ained with a particular apparatus to a form which is independent of the parameters

chosen for that apparatus, one may express the scattering parameters in a form which applies

to the tissue alone. This step insures comparable results between laboratories if the

jther biological precautions have been taken properly.

The data reduction may be accomplished in two ways; by the use of substitution methods

of measurement (see below), or by the use of exact equations expressing the echo strength

as a function of the apparatus parameters as well as of the tissue properties. An unexpected

benefit of the mathematical approach is that the equations will also be useful to the

equipment designer. By using them "backwards" from the data reduction approach, new equipment parameters can be chosen so as to allow the equipment to achieve the visualization

or differentiation of particular types of structure. The substitution method can be used

today with any type of equipment which is linear in echo amplitude. The analytic approach

has been solved only for far- field conditions (see Appendix).

One example of the necessity of separating the influence of equipment parameters from

tissue parameters will be developed later. Briefly, it will be shown that the observations

of the influence of angle of incidence on echo amplitude, as has been made in a number of

laboratories, primarily gives information about the beam pattern of the transducer that was

used. The statement that the echo falls off so many dB in so many degrees, thus, is a characterization of the transducer and says nothing at all about the properties of approximately-plane tissue interfaces. If we had design equations relating transducer response to interface tilt, we could approach the design of transducers capable of imaging interfaces

at angles of incidence considerably away from normal incidence. An intensity-responsive

receiver processing with large apertures is an excellent possibility. There are many large

aperture transducer systems in use which employ lenses or phased arrays. When an interface examined with such a system is tilted, the reflected energy is usually still reaching

some portion of the transducer over a larger angular range than is possible with a smaller

aperture transducer. As long as such angular-dependent reflection properties are considered

to be related to the tissue interface, attention is diverted away from the transducer

design question where the problem might be solved.

2. Scattering Mechanisms

Since the original observations [1,2]^ that echoes could be received from biological

tissues, a lively debate has centered around the mechanisms causing such reflections. It was known that the densities of many soft tissues varied little from that of water. Early

investigations of tissue velocity showed by implication that the elastic properties would

not vary greatly from water [3]. Since the velocity of sound in soft tissues is approximately the same as in water, we usually use the equations which apply to compressional

waves in a liquid. The velocity, c, is given by

c = yfTJV (1)

Figures in brackets indicate the literature references at the end of this paper.

30
where k is the adiabatic bulk elastic modulus and p is the density of the medium,

the specific acoustic impedance, Z, is given by

Since

Z

= pC (2)

we can write

(3)

for unbounded plane waves normally incident on the interface between media of differing

properties. The fraction of the incident intensity which is reflected is given by k^,

where, at normal incidence.

The subscripts refer to the media on the two sides of the interface. These equations

describe the relationships between the basic medium parameters of elastic modulus or density

and the observed quantities of reflection constant and velocity. Interface echoes can be

produced by tissue elements whose elastic modulus or density differs from the adjacent

tissues. Equations are also known which apply to structures much smaller than the acoustic

wavelength, to the red cell, and possibly to other tissue structures. The importance of

these equations for smal 1 -scatterers is that they can be extended to structures of arbitrary

shape. The scattering from complicated structures is the vector sum of the scattering from

its component elements, if these elements are small. The elemental scattering is calculated

from [4]

= differential scattering cross-section

X = wavelength

a = scatterer radius, << A K = adiabatic compressibility of embedding medium = 1/k

Ke = adiabatic compressibility of scatterer

p = density of medium

Pe = density of scatterer

G = angle between scattered ray and direction of incident plane wave (6=0° for

backscatter)

.

The scattered power per unit solid angle is given by the product of incident intensity and

aj. Integration over the face of the receiving transducer then yields the acoustic power

in the echo. Measurement of Ofj is discussed in the next section. Equation (5) applies

strictly to media without viscosity. If viscosity is present, the second term in parentheses is replaced by a more complicated function of viscosity, scatterer size, and density

with the same cos e dependence [5].

The scattering from some structures is explained by the preceding equations for cases where material properties are known and where scattering has been investigated quantitatively.

In other cases, useful inferences can be drawn from extensive clinical experience. Both

approaches are combined to provide a good understanding of scattering. Ultrasound scattering is produced by very small differences in density and in elastic modulus (or compressibility). This energy may be used to detect variations caused by disease processes.

(4)

(5)

where,

31
The reflection coefficient of biological interfaces may be calculated from basic data

using eq. (4) [6]. The amplitudes of the reflected wave range between 30-40 dB less than

that of the incident wave for all soft tissue interfaces. It is extremely fortunate that

the value is small, since the abstraction of energy from the propagating wave by these

interfaces is negligible and thuSj interrogations are possible at appreciable depths

of tissue. The calculated values have been measured in vitro for mitral valves (see Keynote

Address, fig. 2, p. 11, this volume). Transcutaneous determinations in vivo have shown

that a value of impedance differing from blood by 1-5% would, when corrected for absorption,

account for the observed echo strength [7].

Such small impedance variations could be produced by differences in either density or bulk elastic modulus for tissue organizational elements of a size on the order of 1 mm. Generally, values of compressibility and density are not obtained for tissue elements this

small by conventional methods. Thus, one must use ultrasonic means of measurement. The use

of ultrasonic velocity to measure particle compressibility is well known. Effective values

of density and elastic modulus must be considered, since if these properties undergo

relaxational changes, they become functions of frequency. Changes in elastic modulus which

affect sound waves are not the static values, but rather the high-frequency values. At frequencies of several Hz, these values are functions of the general level of stress and,

for some biological tissues, the stress history of the material [8].

Early in the development of diagnostic ultrasound, some experiments were done which

shed light on the mechanism of echo production from within skeletal muscle and tumors [9].

The strength of muscle echoes was highly dependent upon orientation and was strongest when

the sound beam was normally incident upon the muscle bundles. This anisotropy implicated

the muscle bundles in the echo-production process. It was not clear, however, whether the

extra-cellular fluid between the bundles was the origin of the echoes or whether the elastic

and connective tissues which organized the contractile elements into bundles were responsible.

This same investigation showed that internal echoes could be observed within tumors and that

these could be used in diagnosis. During the intervening years, a number of clinical

observations, primarily by those using grey scale apparatus, have helped delineate the fact

that different echo patterns arise from the interior of many organs.

Many of the clinical observations and investigations into the origin of scattering

within tissues by E. Kelly Fry and G, Kossoff were considered in a review by Fields and Dunn [10]. Based on the correlation between connective tissue growth and disease processes,

they showed that impedance discontinuties between connective tissue with high collagen

content and other soft tissue play a primary role in producing echoes from within tissues.

Although their argument refers to the large differences in the static Young's modulus of

elasticity within these tissues rather than to the small differences in the high-frequency

bulk modulus which governs the impedance, their general conclusion is still valid. Investigations of the approximate value of the velocity in high-collagen-content tissues such as blood vessel walls and mitral valve structures have found variations only up to 10% from

the average velocity of other soft tissue. However, these differences are near the upper

range of velocity differences observed within soft tissue. Furthermore, in analogy to the case of red blood cells (see Shung's paper, p. 207, this volume), differences in the

compressibility and density of these structures and other soft tissue could be of the same order of magnitude.

3. Tissue Scattering

Many organs within the body can be visualized by means of the echoes which arise from

their surfaces. These organs, such as kidney, liver, stomach, bowel, etc., have connective

tissue membranes enclosing their structure. The echoes are strong and highly angledependent, indicating that specular or mirrorlike reflections from the surface are responsible. The role of half-wave resonance within these membranes, which has been demonstrated

for the mitral valve (see Keynote Address, p. 11, this volume) is not known for these

other connective tissue structures. These echoes are widely used by clinical pulse-echo

machines to determine the shape and position of normal body structures. Blood vessel walls

may also be in this category, although reflections from internal layers probably contribute.

The scattering patterns of the interior of muscle have some interesting properties.

The apparent size of the scattering centers and their distribution leads to different

32
textures in the grey-scale echo pattern [11]. This texture difference is useful in allowing

the differentiation of muscles which lie close to each other. The primary clinical utility

of this information is the differentiation of the placenta from the uterine wall. This

ability to locate the placenta has made the pulse-echo device almost a standard fixture in obstetrical departments. The scattering from heart muscle interior has been shown to be

quite independent of angle at 5 MHz [12]. These myocardial echoes may not even appear on standard echocardiographic machines which usually display the strong surface reflections.

At high gain, however, the muscles can be observed by means of these internal echoes. The

influence of infarct on internal myocardium echoes is being investigated.

Many efforts have been made to characterize tumors by their scattering, as observed

with B-mode scanners. If such characterization could show not only the presence but the

nature, e.g., malignancy or non-malignancy, of a tumor, the method would be extremely

valuable. These efforts are distinguished by a considerable lack of agreement between

investigators, and illustrate the difficulties involved when interpreting simple echo

strength and position data as representing tissue properties. The height of the echo on the A-mode display (or the brightness of a B-mode display) is the result of the interaction

of all factors present. These include not only the scattering parameters, but the attenuation

of the tissue being investigated and of all overlying tissues, as well as the frequency,

beamwidth, pulse length, and signal processing of the examining equipment.

It is not our purpose to review the state of cancer detection. Various investigators

have generally used equipment whose characteristics differ considerably. The result is that a number of equipment parameters make intercomparison difficult. These are: the

frequency of operation, transducer aperture, pulse length, receiver/detector law, video

processing, and characteristics of the display. Frequency is an extremely important

variable since the attenuation for all tissues is known to be frequency-dependent. The

echo height could be influenced differently in different frequency ranges because of this

effect. The effects of aperture and pulse length are to average the signals received over different volumes of tissue. The ultrasound carrier frequency is converted to a frequency

suitable for the display in a detector which is highly nonlinear in most clinical equipment.

Low-level thresholds, high-level limiting, and a frequency-dependent response are the rule

rather than the exception. Video processing can involve differentiation or integration of

the raw video signal plus signal compression. The display apparatus ranges from bistable

memory tubes to grey-scale apparatus and color displays. These may be nonlinear and can include other effects such as integration due to finite spot size and proportional or super-proportional response.

It is clear that more work needs to be done in the tumor field, one of the most

promising for clinical payoff of tissue-characterization studies. Quantitative measurements

of echo height as well as scattering will be discussed below. These techniques appear to

be suitable for application to the tumor characterization problems. Many examples of

scattering observations can be found in any issue of the Journal of Clinical Ultrasound

and Ultrasound in Medicine and Biology. Similar articles are appearing with increasing

frequency in various medical specialty journals.

The differentiation of tumors by scattering measurement has been more successful [9].

In an extensive review of his work on ultrasound in ophthalmology [13], Ossoinig shows how

it is possible to differentiate malignant melanoma of the choroid and to categorize other

lesions into five groups. He uses both blood and the smooth scleral surface for substitution standards.

The primary tissue which is well characterized with regard to scattering is blood.

(See Shung, "The Scattering of Ultrasound by Red Blood Cells," p. 207, this volume). The

scatterii^g has been measured from blood as a function of frequency and angle, and from

these quantities exact tissue parameters have been derived. Comparison of scattering

cross-section of the red cell with the results of calculation from relatively simple models

shows excellent agreement. We are able to separate the contributions due to the changes of

compressibility from those due to changes in density. Fluctuations in blood scattering

were studied by Atkinson and Berry [14]. They found that a two-particle correlation

function satisfactorily defines the fluctuations, so that multiple scattering may be

neglected.

33
Whole blood is less well characterized than is the cell. The angular dependence has

only been observable in dilute concentrations. This work obviously needs extension to higher hematocrits and must consider the influence of flow rate. Fluctuation as a function

of flow rate has prevented quantitative work from being done at high hematocrits, although

this effect may be an artifact due to the measuring apparatus. One item which is under

scrutiny at present is the observation that the scattering from suspensions of red cell

ghosts, that is the membranes alone, is nearly the same as the scattering from whole blood.

This finding does not invalidate the theoretical model since the values of compressibility

which were used were derived basically from sound velocity measurements in which the cell was treated as a unit. The implication seems to be that the compressibility may well be a property of the membrane rather than of the interior of the cells.

The most inconsistent data has been obtained for lung tissue. Lung containing the

normal amounts of air present due to respiration strongly scatters sound and distorts the

sound beam in space as well as the pulse shape in time [15]. Scattering measurements

reported to date, however, have used relatively short pulses which have not allowed the

steady state to be reached. This situation precludes the exact application of theories of

propagation or scattering. Measurements on cut lung samples are consistent [16,17]. There

is little hope of using the lung as a propagation path to reach the heart with present

techniques, since indications are that the lung diffuses sound passing through it. Considerable interest is attached to the detection of fluid in the lung and the possibility

of detecting clinically- significant emboli in the lung. These applications, which have

shown some preliminary clinical feasibility, appear to warrant expenditure of more effort

on lung scattering.

Measurements of the angular dependence of scattering hold great promise since these

are basically relative determinations that could be applied clinically. The work of Lele,

Waag, and of Hill in this area are reported in this volume.

4. Scattering Measurements - General

Measurements of scattering from biological tissues present challenging problems.

Techniques exist to solve some of these, and can clearly be developed to handle most cases. This section considers in some detail the nature of scattering measurements and how they

are made. This discussion attempts to relate various types of scattering measurements to each other and to the basic physics upon which these measurements depend.

Scattering is difficult to specify, primarily because the scattered wave is a new wave

which depends on frequency and angle, as well as on the fundamental elastic properties that

give rise to the scattered wave. This contrasts with the case of velocity and absorption

measurement where waves of essentially the same shape are compared for arrival time and

amp! itude.

Additional problems associated with measuring scattering from biological tissues arise

from three factors. First, the tissue of interest may not be in the far field of the

apertures used to generate and receive the scattered waves, so the known equations and

approximations do not apply. In other fields, e.g., military radar, investigation of

planets, etc., the targets are all at a considerable distance relative to the dimensions of

the aperture. Large aperture medical systems average angular variations in the wave over

the aperture. Diagnostical ly-significant angular variations may well be destroyed by the

averaging process.

The second problem is the extremely wide bandwidth of the pulses which are generally

used. Fractional bandwidths of approximately 50% are in common use, and are often necessary

to obtain time separation of the echoes from closely-spaced structures. To analyze such

structure echoes requires short time-duration pulses and the information is obtained over a very wide bandwidth. Unless spectrum analysis is used to separate the effects of the

scattering on the discrete frequencies of the pulse, the wide bandwidth may also act to smear or obscure highly frequency-dependent terms in the scattered wave. (Spectrum analysis

is only one step in the measurement process outlined here.)

The third problem comes from the presence of significant absorption in the medium

being investigated. Most microwave radar and optical propagation are characterized by a

34
loss due to inverse-square spreading only. We, however, must deal with a strong frequencydependent absorption in the material we are investigating. This absorption interacts with

the reflections so that, although we can observe the amplitude of a scattered wave, we have

some difficulty in separating the effects of absorption and scattering strength that

contribute to the observed amplitude. This latter problem has been solved for cases where

the absorption is known (see Appendix). Analytic methods are available which allow the

complete separation of absorption and scattering-strength effects under some experimental

conditions. The formalism exists to extend these techniques eventually to in vivo measurements, as is shown in table 1, below.

Table 1. Levels of Scattering Measurement

Level

1 . Observed wave

2. Source function

3. Effective values

4. Actual values

a

n

5. Per cell or structure o

Correction Required

None

Overlying tissue

absorption

Wave-shape, equipment

parameter interaction

Standards or Methods

External

Reflection:

Absorption

;

Reflection;

known reflectivity,

orknown or negl igible

known reflectivity

l<2 _____________________ plane (Calculations

needed unless

o sphere p^.^^^ standard

^ _____________________ distribution is used)

Sample tissue absorption

Concentration effect

Same as # 3, plus known

absorption

Same as above, plus variation

of sample concentration or

vol ume

To measure scattering requires two sequential steps to overcome these problems. The

first is to define the functional dependence of the scattered wave, i.e., to determine

the shape of this wave. The second step is to measure the amplitude of the scattered wave.

The functional dependence can be defined by making measurements of the effect of range and

transducer aperture on the received echoes. A small transducer can be used to probe the

angular dependence of the wave. The functional dependence for far-field conditions for

spherical waves and plane waves is known (see Appendix).

To measure the scattering properties of the tissue requires reducing the actual

scattering data for comparison to a ui table absolute measure of scattering. The standard

of acoustic reflectivity is the perfect reflector, i.e., an interface which returns all of

the energy which is incident upon i i: without changing the shape of the wave. This is

realized in a practical form by a plane interface of known reflectivity [18]. Thus, a scattering measurement is a relative quantity. This is really not different from the

measurement of absorption where the wave leaving the region is specified relative to the wave entering the region.

Such a standard of acoustic reflectivity requires modification for use in cases where

the shape of the scattered wave is changed. A plane-reflecting surface reflects a wave of

unchanged shape whose strength is specified relative to that of a wave reflected from a perfect interface. In the case of a very small scatterer, a non-planar wave is radiated.

The strength of the scattering source is then conveniently specified in terms of a "piece"

of a perfect reflector. This area is referred to as a scattering cross-section.

35
Cross-sections are expressed in several forms and sometimes the literature does not carefully identify which form is being used. The total scattering cross-section, a, is usually given without subscript and refers to the total scattered power. This cannot be

related to the power received by the receiving transducer unless the angular dependence is

known. If the scattering is a function of angle, the differential scattering cross-section,

a(j(e) is used. This scattering cross-section gives the power scattered per unit solid

angle in the direction e. This scattered wave must be integrated over the surface of the

transducer and is treated further in the Appendix. The backscattering cross-section is the

scattering cross-section observed by the usual pulse-echo technique where the transmitter

and receiver are at the same location. In the case of an isotropic scatterer, in the farfield, the backscattering cross-section is equal to the total scattering cross-section, a, or 47TOd (180°).

The scattering cross-section equations for discrete scatterers are extremely useful

since such scatterers are elementary wave sources. Theoretically, more complicated

scatterers can be regarded as a distribution of elementary discrete scatterers and the

scattering found by a summation over the individual scatterers. Summation generally

requires the use of computers if the object is at all large, but randomly-distributed

scatterers can be handled analytically in closed form. In the case of volume distributions, the scattering is described by a scattering cross-section per unit volume of tissue.

These scattering cross-sections per unit volume are usually designated by n and there are obviously as many forms of n as there are of a, as described above.

The second step of the measuring procedure, the determination of the scattered amplitude once the shape of a scattered wave is known, can be done in three basic ways. The

first two involve analytical reduction of the data so that suitable equations relating the

observed wave amplitudes and the equipment parameters are needed. Reducing the data to terms involving the standards of reflectivity mentioned above can make the measurements

independent of the parameters of the measuring apparatus. Because, at the present time, we have only equations which are suitable for analysis in the far- field region (see Appendix),

these two methods have limited utility. The transition zone between the near- and farfield regions of the transducers is often used. This zone is the region of narrowest field

and maximum intensity. It is not very different from the far field and future workers may

be able to derive suitable corrections and approximations to allow analytical design to be

done in this region. Through the use of the substitution method, to be discussed below, it

is possible to use any region of the transducer field to make scattering measurements.

The most straightforward means of measuring the scattering is to measure the field

incident upon the scattering tissue volume and separately to measure the scattered field at the location of the receiving transducer. These two quantities can then be inserted into a suitable scattering equation to derive either the interface reflectivity or the scattering

cross-section. The equations can be written only for the strict far-field case at present.

This restriction and the reduced accuracy which results from the separate measurements

severely limit the utility of the separate measurement technique; it is not recommended

because simpler and better methods exist.

The most useful measurement technique is based on a substitution method. In its basic

form, it has been used to measure the scattering cross-section of the red cell and is applicable to many types of scattering problems. The measurement is performed by measuring

the amplitude of the wave scattered from a particular region of tissue. The tissue is then

replaced by a standardized scattering target and a second determination made of the signal

from the known scattering target. If the far-field restriction has been met in the measurement, then equations giving the scattering strength in terms of the equipment parameters

and the tissue scattering parameter apply (see Appendix). These equations can be solved

for the scattering parameter in terms of the equipment parameters and the ratio of the wave amplitudes received in the two cases just mentioned. The result is that the tissue scattering parameter is obtained independent of the apparatus parameters and without the necessity

of making absolute measurements of acoustic power. Another advantage of this method over

the separate measurement of the acoustic waves is that the substitution method can eliminate

all corrections due to the frequency response of the transducers and electronic equipment.

Pulse methods can be used for the time-selection of adjacent structures, and the spectrum

of gated echoes can be obtained. Corrections are needed, however, if the wavelength or other frequency-dependent terms do not divide out of the equations. To obtain the true spectrum, the observed spectrum must be weighted to account for this effect.

36
An exceedingly simple measurement situation results if the standardizing target and

the biological tissue scatter waves are of the same shape. By the same shape, we refer to the characterization of the wave as spherical, cylindrical, or plane. In this case, when

the scattered power from the tissue is compared to the scattered power from the target

(typical equations that govern the scattering are given the Appendix), it is found that all of the terms involving the transducer, frequency, and other apparatus parameters divide

out. This is rather obvious when measuring the reflectivity of an interface using a planar

standardizing reflector. The ratio of the two scattered waves can be expressed in decibels

below a perfect reflector and no geometrical corrections are necessary.

In summary, the substitution method of scattering involves replacing the actual

scatterer by a standardized scattering target and making a comparison of the two amplitudes.

If the observation is done under conditions in which the dependence of the received echo

upon the geometrical factors, such as transducer aperture and range and operating frequency,

are all known, then any target, e.g. , a standardizing target giving any conveniently shaped

wave, can be used as a standardizing means for the actual scatterers. This has been done

in the quantitative measurement of scattering by red blood cells in which the plane wave

target was used to standardize the scattering from distribution of red blood cells. Suitable

equations (eq. (12), multiplied by the ratio of pulse length to pulse period, and eq. (A-11), in the Appendix) were solved for the scattering cross-section per unit volume in terms of the ratio of the received power. Had a distribution been chosen for standardizing,

two equations of the form of eq. (A-11) would have resulted. All the apparatus terms would

divide out in the final results. Therefore, if similar equations exist for other ultrasonic field regions, the equipment terms will similarly divide out. It is necessary that

tissue and target be at the same range, not only for the range to divide out, but also for wave shape identity in both cases.

Various standardizing targets are available which have a known scattered wave shape,

e.g., plane standardizing targets of glass or stainless steel. Spherical wave scattering

can be standardized by using a perfectly-reflecting sphere. If such a sphere is much

larger than the wavelength, the scattering cross-section equals the geometrical crosssection, and is independent of frequency. Many biological materials appear to be distributions of scatterers, and substitution methods can be used, provided that suitable distributions can be found.

Original observations by Wild and Reid [9] were quantitative in that the scattering

from pathological tissues in the human breast was compared to the scattering from the

normal tissue at the same range in the opposite side. This is a substitution scattering

measurement in which the scattering can be expressed in decibels relative to normal tissue.

If the scattering from the normal tissues had been known, this would also have been a true quantitative measurement. A considerable field exists in the characterization of both in

vivo and in vitro secondary standards by the more exact methods outlined here.

Some of the earliest work on measuring scattering used packed red blood cells as a standardizing means [13]. This was not a true absolute measurement since absolute reflectivity of the packed red cells has not been measured. This extension is certainly possible

and will undoubtedly be done in the future, although artificial distributions of scatterers

will probably be more convenient.

5. Scattering Measurements - Corrections

A number of steps are necessary for reducing raw observations of scattered power to scattering parameters which characterize the tissue. It is necessary to correct the observed

scattering for the effects of attenuation due to both the overlying tissue (in the case of

in vivo measurements) and to the tissue of interest, and as has been noted, for changes in shape of wave caused by the use of various types of standardizing objects. The steps are summarized in table 1. This table shows the five levels of scattering measurements which

have been reached so far.

The first level consists of the external measurement of the power of the ultrasonic

waves scattered by the tissue. The measurements may be made relative to suitable standards,

e.g. J an externally-mounted perfect reflector. Thus, the scattered power is determined

relative to the incident power in decibels below that scattered by the perfect reflector.

37
Any of the other types of reflector discussed above may be used. Measurements have also

been made of the scattering by using the signal loss in a column of paraffin oil to obtain

a factor which expresses the ratio of the' scattered wave to the incident wave. It is usually more useful to reach the second level in Table 1, the determination of what is termed the source-scattering function.

The source-scattering function, level 2, is the scattering from a region of tissue

corrected for the absorption caused by the overlying tissue. If the absorption of the

overlying tissue is so small that it can be neglected, this source function is the same as the scattered power measured in the first level. It is a reasonable assumption to neglect

this loss in the case of the eyeball and perhaps also for low-loss organs such as the liver

and spleen (see papers by Wells and by Taylor, pages 61, 71, this volume). If the absorption

of the overlying tissue can be determined from a separate measurement or by a calculation

from known values, this correction can be made. To perform the correction for an in vivo

situation will eventually require the use of internal standards. These standards must have

a known reflectivity, but no wel 1 -characterized internal standardizing structures are available at the present time. It is quite possible, however, that in vitro work may

determine that tissue structures, such as smooth lining membranes, bones or even red blood

cells, might be used for internal standardization. It is necessary, of course, for these

internal standards to be so positioned that the tissue between the standard and the trans- ducer has the same absorption as the tissue between the tissue being measured and the

transducer.

It is of great practical importance to correct measurements to the second level. Not only may the loss of overlying tissue be high, but the frequency and angular dependence may

be controlled by this tissue. An example is the strong influence of the frequency dependence of absorption which can mask even the fourth-power dependence of frequency of the

scatter from blood (or any small scatterers). It has been shown (see Keynote Address,

p. 11, this volume) that the received power increases with frequency, peaks, and then

decreases

!

The third level of the table is the first level at which a scattering parameter can be

determined independent of the measuring apparatus. In this step, effective measures of

scattering strength, that is, k^, a, or n, can be determined. The third step differs from

the second only by the use of a scattering standard which has the same scattered wave shape

as the tissue being investigated or subjecting the fields being measured to calculated

corrections. In this latter case, equations which govern the influence of equipment parameters on the observed echo strength are needed. These effective values of scattering

parameters are corrected for the equipment parameters and, thus, characterize the tissue.

The values can be used for equipment design or for the derivation of diagnostic criteria.

They will be most useful in equipment design if the equations which relate the observed

echo height with the tissue and equipment parameters are found for both the transition- and

near-field cases. In this case, the designer can manipulate his equations to maximize

particular echo information with respect to whatever constitutes the noise in his particular

system.

It is of great interest, however, to reduce the data to the fourth level, which allows

comparison with theory. Only if this step is taken, can the scattering mechanisms be

determined with certainty and the full predictive power of this knowledge be applied to the

design of new equipment and the development of diagnostic methods. This fourth level is the derivation of the actual scattering magnitudes by separating out the effects of absorption in the tissue being investigated. The analytical expressions required to obtain actual

values of o or n are known only for the case of randomly-distributed scatterers which

scatter spherical waves (see Appendix). The various formulas for scattering cross-sections

found in textbooks can be compared with measured values only if this stage of data reduction

is reached.

One further step is possible in the case of distributions of scatterers, the extraction

of the a value per scatterer. Although determination of the volumetric scattering cross- section is useful, in the case of red blood cells it was necessary to go to this final

fifth level, the derivation of the scattering cross-section per cell to compare with theory.

This step is necessary to determine the scattering mechanism for the small structural

elements responsible for volumetric scattering. To reach this level, the law of combination

of waves must be determined. In the case of blood, the law was determined by varying the

38
concentration of red cells and extrapolating the a value per cell to zero concentration.

This technique cannot be done for more highly-organized tissue, although the sample volume

could be varied and similarly extrapolated to zero.

One subject not covered here is the fluctuation in range or time of scattering from

small fixed-position structures. It is well known in radar that the range fluctuations are Rayleigh-distributed, a characteristic of truly random scatterers. Since it is doubtful

that organized biological tissue is truly random, knowledge of actual statistics may very

well be useful in tissue characterization.

6. Measuring Equipment

It is important to use suitable equipment and techniques in connection with the measurements. Electronic units of sufficiently wide bandwidth, linearity and so on are available.

In general, clinical apparatus is not useful for making measurements unless the waves can

be recorded and suitably processed prior to detection. Most clinical apparatus contains

thresholding, fast time-constant circuits, and, in some cases, detectors of special characteristics which do considerable processing of the echo information. If this processing is included when measuring tissue parameters, then some of the a priori assumptions made by

the designer of the equipment are automatically adopted and the measurements no longer

characterize the tissue alone.

Special transducers designed to help separate the echoes to be measured from interfering

echoes are of great help in both in vivo and in vitro work. Those interested in making

measurements should give some thought to acquiring sets of transducers whose focusing and

frequency-response characteristics are designed to ease the data gathering step. Transducers and mountings should allow the range and aperture parameters to be varied to find

the shape of the scattered wave.

Control of the geometry of the sample while making reflection measurements is particularly important. The area of the sample being measured, i.e., the region where the sound

beam investigates the sample, must be determinable and stay constant as frequency, range,

aperture, and angle are varied. For illustration, the apparatus used in our laboratory is shown in figure 1. It is a dovetail channel in which alignment jigs and sample holders are

inserted. A ball-ended rod is used for the initial alignment of the investigating sound

beam. The transducer is moved back and forth to vary the range. Adjustments to make the

sound beam parallel to the axis of the apparatus are made at the transducer. When tissue

is to be mounted onto the holder, the pointed rod is mounted from the left (figure 1) to

Figure 1. Apparatus for holding tissue specimens which allows accurate determination

of region being examined. Ball-ended rod for transducer alignment is shown mounted.

A holder for heart valves is on the table. Pointed rod is a transfer marker used

only for initial alignment. This apparatus is suspended in a temperaturecontrolled saline bath for measurements.

39
indicate the exact center of the ball-ended rod. The tissue is tied, pinned, or otherwise

fastened to a holder. A valve holder, suitably baffled with sound absorbing rubber, is shown on the table in front of the apparatus. When the tissue is mounted in place of the

ball-ended rod, the area of the tissue to be investigated is selected by reference to the

pointed rod. The pointed rod can then be removed and the measurement made. If an internal

region is to be measured, the pointed rod can be offset toward the transducer. Both the

vertical and horizontal axes of rotation of the apparatus are carefully adjusted with the

aid of a dial indicator to intersect at the exact tip of the pointed rod. Other holders

are used for standardizing targets.

To maintain the biological integrity of in vitro samples requires the maintenance of

normal values of fluid content, temperature, and elasticity of the sample. This last item

is new to such a list and is necessary to insure that the variational values of elastic

modulus are similar to those found in life. Since the variational value of elastic constants

of biological materials is a function of the stress level, the degree of tonus in muscle,

for example, may turn out to be important. The influence of age must also be considered,

since death of the tissue liberates decay enzymes to attack the normal structures.

Fluid balance is necessary for two reasons. First, fluid-filled spaces such as arteries

veins, lymph channels and interstitial spaces should be maintained. This may require

techniques to keep these from collapsing. Secondly, to avoid osmotic gradients and retain

normal water balance, the sample should be maintained in normal saline, i.e., water of 9 grams per liter NaCl content.

Body temperature (37°C) must also be maintained unless the process studied is independent of temperature.

7. Conclusion

The quantitative study of scattering characteristics appears to be a fruitful field

for further investigation. Recent studies in this field are discussed in this volume (see

Chapter 6, "Scattering Techniques," p. 167, this volume), as well as in References 19 and

20. Information derived from scattering measurements could very well be clinically useful

in a relatively short period of time. Further implementation of clinical and in vivo

experiments for determining scattering is required. Relatively few tissues have been

measured in a comprehensive manner, which is probably normal for a developing field. As new information-exchange mechanisms, such as this Conference and the proposed Tissue

Characterization Library, are developed, we may expect the state of knowledge to increase

rapidly. Work remains to be done at the theoretical, laboratory, and clinical levels.

Fortunately, the means to obtain good data and understanding of mechanisms are at hand.

40
Appendix

Tissue Interaction Equations

The emphasis throughout this development is on methods to obtain measurable quantities

which characterize scattering tissues. Most of the literature dealing with scattering

problems in random media use a theoretical approach which is based on many-particle

correlation or probability functions. These functions are completely unknown for biological

tissues. They may become known (heuristically, at least) by comparing the theoretical

results with the results of measurement. Thus, the determinations of measurable quantities

should have a high priority.

To be of greatest utility, tissue scattering parameters must be measured in a quantitative sense and be independent of the apparatus used to perform the scattering measurements.

This independence frequently requires knowledge of the equations which describe the interaction between tissue parameters and equipment parameters.

It is important to know these interaction equations for two purposes. First is the

reduction of the output of the data to provide the tissue parameters. The second purpose

is the design of equipment to maximize the probability of detecting echoes from any

particular type of tissue. Knowledge of scattering parameters as well as of interactions

may very well suggest new possibilities for system design.

The simplest interaction equations are derived by considering continuous-wave operation

in the far-field of a transducer for the cases of plane and spherical waves. Three classes

of targets can be handled by these equations; the reflecting interface, the spherical

scatterer, and distributions of spherical scatterers [21]. Angle-dependent scattering

from large scatterers can be handled later through the formalism of the differential

scattering cross-section. We begin with the case of the simplest echo-ranging equation

which yields the received echo power in terms of the transmitted power and the various

parameters describing the transducers, propagating medium, and the target or reflecting

tissue structure.

The intensity on the axis of the main beam of radiation at a distance, d, from the

transducer can be written:

(A-1)

where Pt is the transmitted acoustic power and x the wavelength. The first factor is the

intensity of d if all the power were radiated isotropical ly. The second factor is the

gain of a directional radiator over an isotropic radiator. This factor holds for acoustic

radiators larger than two wavelengths in diameter. The factor A is the effective area of

the transducer, which equals the geometric area if it vibrates as a piston.

The effect of the medium in which the waves propagate on their way to the target will

be taken as that of attenuation alone, that is, scattering by these tissues will be

included only insofar as they weaken the wave. The received intensity is thus reduced by

a factor:

where a is the plane wave amplitude attenuation coefficient and R is the range to the

reflecting tissue structure being considered. The received intensity from a particular

target structure will depend upon the shape and composition of the structure, but the

three limiting cases discussed above can be treated. First, we consider a target which is small compared to the beamwidth and sufficiently small compared to the wavelength so that

the wave can be considered to be scattered isotropical ly and to propagate as a spherical

wave. The reradiated power is found by multiplying the "scattering cross-section," an area,

by the incident intensity. The received intensity is thus obtained from

41
^ e-^"'^ R2a2 4^R2

(A-3)

where the first factor is eq. (A-1) with d = R. In the second, or target factor, a = the

total scattering cross-section.

The second limiting case is exemplified by the scattering or reflection from relatively

large smooth tissue interfaces. This is also the case which applies to the perfect

reflector block which is often used for calibration. The model for such large area targets

is a plane mirror. For normal orientation to the beam, the fraction of the incident

intensity which is reflected is given by the reflection coefficient. Since we are considering far-field radiation and nearly plane wavefronts, the fractional reflectivity of the

interface between two media of different acoustic impedance is k^, where k is the usual

amplitude-reflection coefficient. With mirror reflection, the incident field is folded

back toward the receiving transducer by the interface and the geometrical factors governing

received intensity are the same as if the receiving transducer were in front of the

transmitted transducer at a distance d = 2R. Making this substitution in eq. (A-1)

and including the absorption factor, we obtain the received intensity: —^ k2 e"^"*^ . (A-4)

4R2x2

The third type of target is a distribution of isotropic scatterers. For first-order

scattering, we find the echo intensity by summing eq. (A-3) over the scatterers. The

total scattering cross-section is given by the product of a volume occupied by the outgoing

pulse and the scattering cross-section per unit volume, n. In the far-field, the width

of the pulse volume is KRx/a, where K is a factor defining the effective beamwidth and is

usually taken as 1.2 for round transducers. Since the pulse length in distance is ct/2,

where c is the velocity of propagation and t is the pulse length, the pulse volume is

^[—) 2r

Substituting the above in eq. (A-1) and including the absorption factor, we find the

returned intensity to be

2 P.ttK Ct »

55 -^ ne-^"'^ . (A-5)

4R^ 2

Equations (A-3), (A-4), and (A-5) above yield only the received intensity. We can put them in a final form in terms of the electrical transmitted and received power. The

actual power received is the product of the reflected intensity at the position of the

receiving transducer and the same effective area, A, previously discussed in connection

with eq. (A-1). This received acoustic power is an available power. It is the power that

would be absorbed by a matched transducer. If we define a receiving available power

efficiency, T, we can find the electrical power available, P^, by multiplying the received

acoustic power by T. This is the electrical power which would be delivered to a matched

load and is given by the square of the open circuit voltage divided by four times the real

part of the transducer impedance. It is a measurable quantity which can be obtained by

purely electrical measurements on the terminals of a transducer. The transmitted acoustic power, P-j- in eq. (A-1), is found by multiplying the electrical power output of the

transmitter, Pq, by the transmitting power efficiency. This transmitting power efficiency

has the same value as the available power efficiency of the receiver.

Making the above substitutions, which introduce Pq and P^, and multiplying the previous

equations by an additional factor as T^A, we obtain the final equations:

42
for an isotropic radiator.

Pr . e-^"'^ ^0 4ttX^

a (A-e;

for a plane interface. ^ T^A^e-^-'^ ,2

for a distribution of isotropic scatterers,

!r k\ e-^"'^ cx

^0

" r2 4 2

(A-7)

(A-8)

Modifications to these equations are required for transducer frequency response, sample

volume effects, pulse operation, attenuation in the sample volume, and angular variation.

Examples are given below, with no intention of being exhaustive.

In actual measurements, the open circuit voltage is not observed. The actual voltage

is related to open circuit voltage by a function involving the complex transducer impedance

as well as the complex value of impedance connected across the transducer terminals due to both the transmitting device and the receiver input circuits. To make corrections for

this electrical loading over the full frequency range of short pulses not only requires

computer methods, but also can lead to considerable inaccuracies. The ratio between the

open circuit voltages found with reflection standards and with the actual tissues, however,

is the same as the ratio between the loaded voltages in these same two conditions. The

substitution method of scattering measurement, thus, eliminates the entire problem of

correcting for frequency response of the transducer. If the substitution method is not

used, T and A must be known. A separate experiment and eq. (A-2) can be used to find T and the effective area, A. This is equivalent to a self-reciprocity calibration, but is more complete [22].

If masks or apertures in the measurement system define the beamwidth, then the

actual beam area, S, should be retained in eq. (A-8) to yield

r _ T A S e ct /» Q\

0 4^ x"^

The main difference in this case is that the frequency dependence is changed because we

have eliminated the effects of the variation in beamwidth with frequency in the far

field.

The extension of these equations to pulse-echo systems is relatively simple. Equations

(A-6) through (A-9) apply to the peak values of power during the pulse. To apply to average values, the equations must be multiplied by the ratio of the observation time to the total interpulse period time. The observation time in the case of an oscillographic

display is simply the pulse length, x. For quantitative measurements, it is more convenient

to use recording instruments such as rms voltmeters followed by recording devices for

averaging out the fluctuations. When this is done, the observation time is the width of

the time slot through which the instruments observe the scattered echoes. This is usually

a gate in the receiver which is "on" for some time interval At.

This correction to eqs. (A-8) or (A-9) is only an approximate one if the medium

containing the scatterers is lossy. With loss, the field at each scatterer will progressively diminish as the pulse traverses the volume of scatterers. The exact equation for this

43
case was derived analytically by Sigelman [23] and the result will be summarized here. We can interpret eq. (A-9) as applying to a situation in which the loss factor a over the

range R accounts for all the loss to the wave up to the first surface of the distribution

of scatterers. We will change the notation at this point to let describe the absorption

constant in the media outside the distribution of scatterers and retain a as the absorption

coefficient which is effective within the distribution. This absorption inside the

distribution must include losses due to all sources, particularly scattering losses. Two new terms must be introduced. We let ti stand for the time during which the interrogating

wave travels between the first surface of the scattering volume and the opening of the

observation gate. Also, t2 is the time between the wave entering the scattering volume

and the closing of the observation gate. The actual observation time. At, is given by:

At h

- (A-IO)

The average value of our ratio P^/Pq is now

r _ T A S n e

''o 32^ Tp R^ c

-2aCt, „-2aCtp \ /„aCT „-aCT'

e ^)(e - e (A-n)

In the case of small absorption within the scattering medium, eq. (A-11) can be shown to reduce to eq. (A-9) as modified by the ratio of observation time. At, to the interpulse

period time, Tp. Equation (A-11) differs from equations in reference 23, which used the

differential volumetric scattering cross-section. (See eq. (23) in reference 23.)

Further modifications of the previous equations are needed if the scatterer is not

isotropic. We shall now derive another form of eq. (A-6) which applies to a small scat- terer whose scattering function varies with angle. This is a very practical case since,

as has been determined by Shung (p. 207, this volume), the red cell is of this type. Now

we return to the discussion preceding eq. (A-3) to consider the power incident upon our non-isotropic scatterer which is

^t^ -2aR

2 2 d^X^

(A-12)

where the terms have all been defined previously. Non-isotropic scattering objects can be

described by a scattering cross-section which is a function of angle. This differential

scattering cross-section is usually termed 0^(0). This scattering cross-section is an area which, when multiplied by the incident intensity, yields the power scattered per unit

solid angle in the direction 0. The power scattered per unit solid angle toward the

receiving transducer can then be written as

r2x2

oj(0)e'

2aR (A-13)

in units of watts per steradian. The power which is received by any receiving transducer

at any angle 0 can be obtained by integrating eq. (A-13) over the face of the receiving

transducer. Assume for simplicity that the receiving transducer is at a sufficient distancej

from the non-isotropic scatterer so that the scattered field varies slowly with 0 over

the face of the receiving transducer. If this transducer is at a range D from the scattereri

and has an area A^, the solid angle which it subtends at the scatterer is given by

(A-14)

steradians. The total received power thus can be written;

44
(A-15!

In the particular case of backscattering, 0 = 180°, and, assuming we use the same transducer

for both transmission and reception, we obtain the ratio between the received and trans- mitted electrical powers as

^ = I?4 oMSOne-"^^^ . (A-16)

Equation (A-16) can be compared directly with eq. (A-6), which is written for the same case,

and we see that

a = 4^ a^(180°) . (A-17)

By analogy, we can also write

n = 47Tnd (180°). (A-18)

The more general treatment of angular-dependent scattering can be written following

the above discussion, but will not be expanded here. Briefly, the field incident upon the

distribution of simple scatterers with a known angular scattering function must be treated

point by point. For each point in the scattering volume, the scattered wave must be

integrated over the receiving transducer aperture. The appropriate distance and area functions are introduced into the calculation and this summation repeated over all points

of scattering volume. For some measurement purposes, it is obviously much simpler to arrange the apparatus so that the approximations leading to eq. (A-16) are valid. This

same formulation can be extended to take account of absorption by using eq. (A-ll) with

eq. (A-18).

Two cases of angular variation should be carefully distinguished. We know that many

biological structures have a scattering function which varies with angle. If these are rotated in front of a pulse-echo system, the received scattered wave will change in amplitude.

The angle-dependent scattering which has been found with red cells, however, is due to the

dipole term introduced by the density difference (see eq. (5)). This angular variation is defined with respect to the direction of the incident wave and is thus "frozen" into a wave coordinate system rather than the target coordinate system. Rotation of a red cell

in front of a pulse-echo system would thus result in no change of received wave with

angle, although translation of a separate receiving transducer around the red cell would

record the angular variation which was actually observed [24].

Equations expressing the influence of apparatus parameters on angular dependence of

interface reflections have apparently not been worked out but would be extremely valuable.

As figure 2 shows, when an interface is inclined to the sound beam of a pulse echo apparatus,

a reflection is sent back toward the transducer displaced by twice the angle of rotation

of the interface. Thus, all plane interfaces at a particular range will appear to have the

same angular-distribution function. The angular-distribution function, in the case of

large ranges, is identical with the beam spread function of the transducer as integrated

over an area whose solid angle equals that subtended by the transducer at twice the range

of the actual interface. This change with range has been observed by Wells [25].

A number of clinical measurements of the angular dependence of the scattering from

biological interfaces have been made and interpreted as if the interfaces possessed this

angular dependence of scattering. As figure 2 should make clear, the angular dependence

on scattering is a property of the transducer and its beam shape. The angular scattering

function of an interface for plane waves should be strictly an impulse function. The

observed response is the convolution of the impulse response and the actual beam pattern.

A deconvol ution operation is needed to derive the angular distribution functions which

45
TRANSDUCER

[

e'

REFLEaOR

E

\

e 0 0

Figure 2. Typical apparatus arrangement for measuring angular dependence of

interface reflectivity. As the interface tilts through the angle 0, the

reflected beam sweeps past the send-receive transducer (top). The transducer

output, E, varies as a function of angle and transducer directivity function.

The true interface directivity function is an impulse (bottom right).

Measurements such as these define transducer, not interface, properties.

characterize biological interfaces. Since increasing the angular range over which interface reflections can be received without sacrificing lateral resolution is a high priority

design goal for most pulse-echo apparatus, a better understanding of the interactions of

the transducer beam pattern parameters and the tissue angular dependence scattering

parameters would be very useful.

[1] Wild, J. J., Use of ultrasonic pulses for measurement of biological tissues and

detection of tissue density changes. Surgery, 2J_, 183 (1950).

[2] Ludwig, G. E. and Struthers , F. W. , Considerations underlying the use of ultrasound

to detect gallstones and foreign bodies in tissues. Naval Medical Research Institute

Project, MM 004 001 Report #4, June 1949; Ludwig, G. E. in Re-port of 81st Meeting of

the Society of Clinical Surgery, (Boston, MA, November 4-5, 1949).

[3] Ludwig, G. E., The velocity of sound through tissues and the acoustic impedance of

tissues, J. Aooust. SoQ. Am. 22, 862 (1950).

[4] Morse, P. M. and Ingard, K. U., Theoretical Acoustics (McGraw-Hill Book Co., NY,

1968).

[5] Ahuja, A. S., Effect of particle viscosity on propagation of sound in suspensions

and emulsions, J. Aaoust. Soc. Am. 51, 182 (1972).

[6] Wells, P. N. T., Physical Principles of Ultrasonic Diagnosis, p. 13 (Academic Press,

London, 1969).

[7] Reid, J. M., Ultrasonic Diagnostic Methods in Cardiology, Ph.D. Thesis, University

of Pennsylvania, p. 91, Order No. 66-4638 (University Microfilms, Ann Arbor,

[8] Fung, Y. C. B. , Stress-strain-history relations of soft tissues in simple elongation,

in Biomechanics : Its Foundations and Objectives, Y. C. B. Fung, et al., eds

.

(Prentice-Hall, Inc., NJ, 1972).

[9] Wild, J. J. and Reid, J. M., The effect of biological tissue on 15 Mc pulsed ultrasound, J. Acoust. Soc. Am. 25^, 270 (1953).

References

MI, 1965).

46
Fields, S. and Dunn, F., Correlation of echographic visualizability of tissue with

biological composition and physiological state, J. Acoust. Soa. Am. 54^, 809 (1973).

Reid, J. M., Diagnostic applications of ultrasound. Proa. IRE, 47, 1963 (1959).

Sigelmann, R. A. and Reid, J. M., Scattering of ultrasound by biological tissues, in

Interaction of Ultrasound and Biological Tissues, Workshop proceedings, J. M. Reid

and M. R. Sikov, eds., p. 245 (Bureau of Radiological Health, 73-8008, 1973).

Ossoinig, K. C, Quantitative echography--the basis of tissue differentiation, J. Clin. Ultrasound, 2, 33 (1974).

Atkinson, P. and Berry, M, V., Random noise in ultrasonic echoes diffracted by blood,

J. Phys. A: Math., Nual. Gen. 7_, 1293 (1974).

Reid, J. M., ultrasonic Diagnostic Methods in Cardiology, Ph.D. Thesis, University

of Pennsylvania, Appendix I, Order No. 66-4638 (University Microfilms, Ann Arbor,

MI, 1965).

Bauld, T. J. and Schwan, H. P., Attenuation and reflection of ultrasound in canine

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

Dunn, F., Attenuation and speed of ultrasound in lung, J. Acoust. Soc. Am. 56^, 1638

(1974).

Standard Specification of Echoscope Sensitivity and Noise Level, Including Recommended

Practice for Such Measurements (American Institute for Ultrasound in Medicine, 1973).

Chivers, R. C. and Hill, C. R., A spectral approach to ultrasonic scattering from

human tissue: methods, objectives and backscattering measurements, Phys. Med. Biol.

20, 799 (1975).

Nicholas, D. and Hill, C. R., Acoustic Bragg diffraction from human tissues. Nature,

257, 305 (1975).

This derivation of the echo-ranging equation is based on the development used in

radar. The rationale is discussed at greater length in: Skolnik, M. I., Introduction

to Radar Systems, Chapters 1 and 2 (McGraw-Hill, NY, 1962); and Radar System

Engineering, L. N. Ridenour, ed., Chapter 2 (McGraw-Hill, NY, 1947). References to radar practice refer to these sources.

Reid, J. M., Self- reciprocity calibration of echo ranging transducers, J. Acoust.

Soc. Am. 55, 862 (1974).

Sigelmann, R. A. and Reid, J. M., Analysis of ultrasound backscattering from an ensemble of scatterers excited by sinewave bursts, J. Acoust. Soc. Am. 53, 1351 (1973).

Shung, K, K. , Sigelmann, R. A., and Reid, J. M., Angular dependence of scattering

of ultrasound from blood, IEEE Trans. Biomed. Engnr. (in press).

Wells, P. N. T., Physical Principles of Ultrasonic Diagnosis, p. 90 (Academic Press,

London, 1969).

47
I

i

I
CHAPTER 3

A-SCAN PATTERN RECOGNITION TECHNIQUES

49

National Bureau of Standards Special Publication 453. Proceedings of Seminar on Ultrasonic

Tissue Characterization held at NBS, Gaithersburg, MD, May 28-30, 1975. (Issued Oct. 1976)

CHAPTER 3. A-SCAN PATTERN RECOGNITION TECHNIQUES

Paper 3.1: USE OF PATTERN RECOGNITION FOR SIGNAL PROCESSING

IN ULTRASONIC HISTOPATHOLOGY

K. Preston, Jr. Department of Electrical Engineering

Carnegie-Mellon University

Pittsburgh, Pennsylvania 15213

New developments in high-speed electronics have made possible

real-time digitization of the ultrasonic A-scan as a block of

binary words. This makes computer processing of such blocks

feasible using techniques previously developed in time-series

analysis for communications, speech processing, word recognition,

etc. The research reported here is concentrating on: (1) advanced

digitization techniques having variable block length and skip-block

capability; (2) application of speech spectrogram representation

and analysis to A-scan processing; and (3) use of human audition

(of the recorded A-scan, properly frequency- transl ated) to assist

in defining the features most useful for A-scan pattern recognition.

Key Words: Analog-digital converter; A-scan; digitization;

pattern recognition; speech spectrogram; ultrasound.

1. Introduction

The purpose of the research reported here is to determine the feasibility of conducting

useful tissue analysis by computer processing of ultrasonic pulse echoes. At the present

time, only the gross macrostructure of organs is observable through either the ordinary or "grey-level" ultrasonic B-scan. However, it has been reported by many researchers and

quantitated by some that detailed features of individual A-scans may be useful in analyzing

the structure of the tissue to be examined [1-5].^

Under a grant from the National Science Foundation (NSF), the Department of Electrical

Engineering of Carnegie-Mellon University has been funded to conduct a study of the utility

of detailed computer analysis of A-scans in determining tissue characteristics in vivo.

This will be accomplished by 12-bit digitization at 10 megasamples per second using

a total storage of 4096 words, and a 1 kHz interrogation rate. The record length will be

variable from 128 to 4096 words [i.e., a depth of 2 to 60 centimeters). Record spacing

will be variable from 1 interpulse interval to 1024 interpulse intervals making possible

recordings over periods of time as long as 32 seconds (and as short as 12.8 microseconds).

Blocks, i.e., the number of records digitized per patient, will be variable from 1 to 32 within the existing memory capacity. Synchronization with the cardiac cycle will also

be included. By means of this instrumentation, both liver and kidney in normal and abnormal

patients are to be studied over a population of approximately 100 patients. For most of

the abnormal patients, a biopsy core will be obtained coaxial with the A-scan.

2. Pattern Recognition

A flowchart of the program to be conducted is shown in figure 1. This flowchart is diagrammed in terms of the basic pattern recognition formalism which shows a series of

four mappings from signal space to data space to measurement space to classification space.

•^Figures in brackets indicate the literature references at the end of this paper.
£. J2 SS ^ in — => CO

<; o "o

Q

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— 1 o

a> TO I

QJ

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CD - c

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-)-> -i- •r- +-> (/I

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(U •!- > -o c <+- ZD O n3 C CO X O 1- ro 1— </) O

.— >^

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fO Q- 3 O S _E O

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52
In the case of the study undertaken for NSF, the individual patient (or, more exactly,

the organ to be examined in the individual patient) is the signal space, the ultrasonic

transmit-recei ve system is used to gather data (the digitized A-scans), measurements are generated from digitized data by time-series analysis, and classification is determined

either in a deterministic learning mode or by means of comparison with the simultaneouslyextracted biopsy core as analyzed by traditional pathology. Hence, the term "ultrasonic

histopathology.

3. Histopathology

Figure 2 shows a field of view of abnormal liver tissue. The purpose of this

illustration is to indicate the structural levels at which the pathologist examines an abnormal tissue sample. This particular sample represents a case of toxic hepatitis.

2.25 MHz

4.50MHz

h-H 9.00 MHz

Figure 2. Photomicrograph of a portion (0.5 mm x 0.5 mm) of a section of

liver tissue of a patient exhibiting toxic hepatitis. Hepatic cell nuclei,

leukocytes, fatty cells, balloon cells and sinusoids are evident. The

ultrasonic resolution at various frequencies in liver tissue is given on the bar chart for purposes of scale.

It is useful to compare optical with ultrasonic resolution, i.e., the resolution

achievable under the optical microscope with that achievable by the A-scan. In ultrasonic

pulse-echo systems, the maximum achievable resolution is the reciprocal of twice the 3 dB

bandwidth of the pulse. The 3 bars in figure 2 are made to correspond to half wavelengths

at 2, 4, and 8 MHz. It is clear from the dimensions of the ultrasonic wavelength that

considerable averaging will be carried out over the structural details observable in the

photomicrograph. For example, leukocyte nuclei, even at 8 MHz, are an order of magnitude

smaller than the acoustic resolution. Even the hepatic cell is smaller than the acoustic

resolution as are the fatty cells shown. This means that acoustic scattering will be from

a more of less random collection of scattering sites whose dimensions are considerably

below the acoustic resolution. However, leukocyte clusters within the tissue from infl amatory leukocyte infiltration, such structures as biliary ducts, clusters of fatty cells,

etc., will in many cases be of the order of, or greater, than the acoustic resolution. Thus,

the full spectrum of structural detail must be considered in studying its effect on the

received and digitized A-scan. The computer can be used in this analysis, as is shown in figure 3.

53
it

*

(b)

(c) (d)

Figure 3. Computer analysis performed of the upper right hand portion of

figure 2 at Carnegie-Mellon University using a program coded in PICPAC.

The program has separated (a) fatty cells, (b) sinusoids and balloon cells,

(c) leukocytes, and (d) hepatic cell nuclei.

4. A-Scan Statistics

Another purpose of this research is to determine the uniqueness of the statistical

properties of both normal and abnormal liver and kidney over a statistically-significant

population of patients. At this present writing, since the program is only 6 weeks past

its starting date, statistically-significant results are not available. Only technique

and approach can be reported here. Typical statistical measurements which may be made

on the probability density function of the A-scan voltage waveform include not only its mean and standard deviation but also such measures as skew and kurtosis. These measures

have been found useful in the analysis of other biological structures [6]. Other

statistical measures which are useful in this type of analysis include the n-gram

statistics which provide first-order correlation of nearest neighbors in the A-scan

time-series. This statistic is also known as the transitional probability density function.

It is a two-dimensional function and is best shown in matrix form, as is indicated in figure 4, which shows the transitional probability density function for the first 8 letters

of the alphabet in English text. The utility of this statistic in treating digitized

A-scans is under investigation.

54
First Letter of Pi-Gram

A B C D E F

0.02

0.32

0.39

0.15

0.10

0.08

0.58

0.44

0.12

0.55

0.01

Figure 4.

.45 1.31 0 21

.18 0.11 0 02

.04 0.64 0 09

.10 1.07 0 01

.39 0.39 0 25

.12 0.23 0 14

(Di- Gram) of Englist text

Other quasi-statistical measures on the A-scan include the Wiener spectrum. Its properties are being investigated by many workers [7-10]. The Wiener spectrum is simply

a projection of the time-series on the Fourier polynomials and represents a graph of the

magnitude of the resultant Fourier coefficients. Whether the Fourier polynomials form a valuable basis for the analysis of A-scans is unknown and an investigation of other bases

is planned. For example, we intend to study the eigenvectors of the A-scan time-series

itself using the Karhunen-Loeve expansion. If this expansion yields a basis similar

to the Fourier polynomials, then the validity of these polynomials will be proven.

5, Auditory Analysis

Each digitized echo is akin to a word or, perhaps, to a phoneme. Thus, a single echo

or a series of echoes may be represented in "speech-spectrogram" form as shown in figure 5.

5288-

4808-

N 4488-

c 4808-

o 3S08-

c

(Ug- 3208- ^ 2888- "

i 2480- :

2008-;;'nii iiiiir' H"- 1B88- n \(\^ ijii:

''''

808-iL,;; ^:Ji:sJi!l„

828 84

Figure 5. An ultrasonic A-scan time-series (obtained from Dr. R. A. Mountford,

British Royal Infirmary, Great Britain) presented in speech spectrogram format

for the purpose of applying speech analysis to medical ultrasonic pulse echoes.

55
Echoes in this form may be analyzed using "voiceprint" recognition techniques as pioneered

by Kersta [11]. A single echo or a series of echoes may be converted to audible sound and

analyzed by the most sophisticated of all acoustic pattern recognition systems, the human

ear-brain complex. It is well known that the human cannot only recognize the wellenunciated speech of his fellows but also distinguish a wide variety of noises: the bark

of a dog, the meow of a cat, the trill of a bird, the chirp of a cricket, etc. This may

also be done (to some extent) by computer processing of the audible signal, as exemplified

by the HEARSAY project at Carnegie-Mellon University [12]. But the ear-brain complex is more sophisticated than the computer and can also distinguish much more subtle features

such as the bark of one (well-known) dog from a pack of the same species. Thus, it is logical to use the human ear-brain system in studies of A-scan time-series recognition.

To do this, requires a careful selection of the transduction method employed to convert the

string of binary words, which are the digital representation of the echo, into the audible

signal or "enunciation" presented to the listener. Also, it would be particularly useful

if the researchers were familiar with sonar, a field in which there are many skilled workers

familiar with the problem of classifying undersea objects by listening to the pulse-echo

signal

.

Let us consider the characteristics of human speech and determine how the ultrasonic

time-series may be treated as a speech signal. The power spectrum of human speech is shown

in figure 6. As can be seen, the speech spectrum covers a range of 6 octaves (approximately

128 to 4096 Hertz) with the majority of the spectral energy concentrated in the two-octave

region from 128 to 512 Hertz. In order to produce speech-like sounds in the familiar

spectrum, it is necessary to shift the A-scan time-series both in frequency and time.

A

0 1000 2000 3000

Frequency

ENERGY FREQUENCY DISTRIBUTION

OF AVERAGE SPEECH

Figure 6. The power spectrum (Wiener spectrum) of male human speech.

56
Let us assume that there are N samples of the time-series. A Fourier analysis of this

time-series will result in N spectral components of which the first is the value of the mean and, since the values of the time-series are real, only (N-l)/2 are significant in determining the amplitude and phase of the spectral components. Neglecting the mean value, we can then state that the time-series represents a signal occupying a number of octaves

given by the equation:

Vt = ^°92[(N-l)/2] log2(N/2) (1)

For typical commercial time-series digitizers, the number N ranges from 128 to 1024

and therefore noct ""s between 7 and 10. The distribution of energy in the spectrum is unknown, but we can assume that it is not concentrated in the first 2 octaves. It is therefore likely that both frequency redistribution and time multiplication are necessary

in translating the recorded time-series into the speech spectrum. If we assume that the

Fourier analysis of the spectrum has produced the coefficients a^ and <i,^, then linear

frequency translation leads to

s(t.

n=N/2

n=l E a^cos (2)

where s(t|^) is the frequency-translated signal sampled at time t|<, f^ is the "carrier"

frequency, using the terminology of a single-sideband communications [13], and T is the

enunciation time. If we let fc = c/T, the number of octaves occupied by the signal expressed

in the above equation is log2(q+c)/c where q

= (N-l)/2. Therefore, the number of octaves

by which the original signal is reduced is given approximately by log2C.

One of the first choices to be made, of course, is the value of the enunciation time

of the "word" represented by the A-scan time-series. The other choice is of the quantity

c which provides an approximation to the lowest frequency in the audible playback. This

frequency is given by (c+l)/T. Table 1 provides enunciation times (in milliseconds) for

many practical cases. The table gives the reader some idea as to the range of choices

of enunciation times as a function of the lowest frequency, (fc+l/T), of the audible

signal as a function of the number of octaves present in the audible signal and the number

of words in the original time-series.

Table 1. Enunciation Times for Linear Frequency Translation

64 128 q = 512

f,(Hz) %ct T(ms) c T(ms) T(ms)

64 1 64 1000 128 2000 512 8000

2 21 333 43 667 171 2667

3 9 143 18 286 73 1143

128 1 64 500 128 1000 512 4000

2 21 167 43 333 171 1333

3 9 71 18 143 73 571

256 1 64 250 128 500 512 2000

2 21 83 43 167 171 667

3 9 36 18 71 73 286

57
Linear Frequency Translation (LIFT), as can be seen from table 1, exhibits a rapid

decrease in the enunciation time as the number of octaves utilized are increased from unity. LIFT does not take into account the fact that the resolution of the human ear is logarithmic

not linear, and provides a nonuniform number of samples per octave. In the higher octaves,

this produces more samples than the human ear can resolve. If we utilize the tonal scale common in Western music, then only 12 frequencies should be utilized per octave, independent

of the octave selected. The resultant enunciation would be given by the equation:

'k+j-1

n=12n

En=l

oct

^nj^°^ (3)

where fo is comparable to the "carrier" frequency of eq. (1). The quantity a is 0.06, i.e.^ one minus the 12th root of 2. This yields LOgarithmic Frequency Translation (LOFT) wherein

the frequencies utilized are not harmonics. In determining the enunciation time, therefore, we can only approximate the situation treated in eq. (1) by defining a "pseudo-enunciation

time" given simply by

T' = (0.06f,

1

(4)

Table 2 provides pseudo enunciation times in a format comparable to table 1

Table 2. Pseudo-Enunciation Times for Logarithmic Frequency Translation

q = 64 q = 128 q = 512

fmin("^) "oct T(ms) T(ms) T(ms)

64 1 1000 2000 8000

2 500 1000 4000

3 333 667 2667

128 1 500 1000 4000

2 250 500 2000

3 168 333 1333

256 1 250 500 2000

2 125 250 1000

3 83 168 667

6. Illustrative Example

As part of the oral presentation of this paper, several audible playbacks were rendered

which were generated from LIFT renditions of audible signals produced from recordings taken

of ultrasonic pulse echoes from human liver in vivo.

References

[1] King, J. C. and Wang, A. K. C, Computer analysis of transcranial somotographic B-scans

J. Comp. Biomed. Res. ^, 190 (1972).

[2] Mountford, R. A. and Wells, P. N. T., Ultrasonic linear scanning: the quantitative

analysis of the normal A-scan, Phys. Med. Biol. yj_, 14 (1972).

58
[3] Mountford, R. A., et al^ Ultrasonic linear scanning: automatic A-scan analysis, Vhys.

Med. Biol. 17_, 559 (1973).

[4] Waag, R. C. and Gramiak, R., New concepts for acquiring, processing, and imaging

cardiac data, in Ultrasonics in Medicine, M. de Vlieger, et at., eds., p. 239

(Excerpta Medica, Amsterdam, 1974).

[5] Goldstein, A., University of Kansas (personal communication).

[6] Hall, E. L., Crawford, W. 0., Preston, K., and Roberts, F. E., Computer classification

of coal workers' pneumoconiosis, in Proceedings of the 1st International Conference

on Pattern Recognition, p. 77 (Washington, D.C., 1973).

[7] Gericke, 0. R., Defect determination by ultrasonic spectroscopy, J. Metals, 932 (1966).

[8] Lele, P. P. and Namery, Jr., Detection of myocardial infarction by ultrasound, in

Proceedings of 25th Annual Conference on Engineering in Medicine and Biology, p. 135

(1972).

[9] Chi vers, R. C, Hill, C. R., and Nicholas, D., Frequency dependence of ultrasound

backscattering cross-section: an indicator of tissue structure characteristics, in

Ultrasound in Medicine, M. de Vlieger, et al., eds., p. 300 (Excerpta Medica,

Amsterdam, 1974).

[10] Jones, J. P., Impediography : a new ultrasonic technique for diagnostic medicine, in

Proceedings of AIUM Fall Conference (1974).

[11] Kersta, L. N., Voiceprints, Inc., N. J.

[12] Lesser, R. R., et al. Organization of the HEARSAY II speech understanding system, in Proc. IEEE Symp. on Speech Recognition, (Pittsburgh, PA, 1974).

[13] Taub, H. and Schilling, D. L., Principles of Communications Systems, Ch. 3 (McGrawHill, Inc., 1971).

59

National Bureau of Standards Special Publ ication 453 . Proceedings of Seminar on Ultrasonic

Tissue Characterization held at NBS, Gaithersburg, MD, May 28-30, 1975. (Issued Oct. 1976)

Paper 3.2: QUANTITATIVE A-SCAN ANALYSIS OF NORMAL AND CIRRHOTIC LIVER

P. N. T. Wells, R. A. Mountford,i M. Halliwell,

and P. Atkinson

Department of Medical Physics

Bristol General Hospital

Bristol, BSl 6SY, United Kingdom

The development of quantitative methods of analyzing ultrasonic

liver scans is reviewed. These methods are based on measurements of

intrahepatic echo amplitudes or echo spacings. Simple techniques

indicate that the echo amplitude tends to be increased in cirrhosis.

Using a frequency of approximately 1-5 MHz, this was confirmed by

computer analysis of the measurements of 100 consecutive cycles of

the ultrasonic echo wavetrains in each of 30 separate scans from

each of 30 individuals with normal livers, and 13 with cirrhosis.

These data were acquired manually. In cirrhotics, the mean echo

amplitude was 6 dB greater than in normals. Similar results were obtained with an automated system of data acquisition. The results

are compatible with a model in which the observed structure is a random noise effect; the dimensions of the pulse determines the

scale of the fluctuation which is observed. The echoes from

cirrhotic liver, higher in amplitude but otherwise very similar

to those from the normal, could be due to similar targets with

greater characteristic impedance mismatches.

Key Words: A-scan; attenuation; computer analysis; impedance;

liver cirrhosis; ultrasonics.

1. Introduction

Although the early literature refers to the visualization of liver abnormalities in

two-dimensional B-scans [1-3],^ the interpretation of these scans was left to the judgement of the observer. Likewise, the assessment of early A-scans was subjective [4].

The first quantitative approach to the possibility of distinguishing between normal and

abnormal liver seems to be that of Schentke and Renger [5], who reported that both the mean echo amplitude and the echo frequency are increased in various abnormalities

including cirrhosis. Following this. Wells, et at. [6] took up a suggestion made by

Wild and Reid [7] in connection with the diagnosis of breast disease, and for a series

of normal patients, and a series of patients with various liver abnormalities, they

calculated an index

Eh^/T ,

^Department of Radiodiagnosis , Bristol Royal Infirmary, Bristol, BS2 8HW, United Kingdom.

^Figures in brackets indicate the literature references at the end of this paper.

61
where hi is the amplitude of the i internal echo and T is the duration of the echo train

subjected to analysis. For each individual, they used two demodulated A-scans made

along different paths through the liver, and they standardized the system operating

conditions, including swept gain rate and sensitivity. The positions of the A-scans were marked by intensifying the corresponding lines on two-dimensional compound B-scans made

in the same subcostal planes, and echoes of large amp! itude--supposed, probably often

erroneously, to arise from the concave inferior surface of the liver--were "identified"

on the B-scans, and the corresponding echoes were somewhat arbitrarily neglected in the

A-scan analyses. The mean index for each abnormal liver was compared with the value

for a corresponding normal control, and found to be greater in 25 out of 32 patients

with cirrhosis.

A rather similar method of analysis was used by Czarnecki and Kubicki [8], who

not surprisingly found that the diagnosis was more reliable, the more advanced the

Jisease.

2. Quantitative Analysis of the A-Scan

Mountford and Wells [9,10] used a refinement of earlier methods of quantitatively

analyzing the A-scan to determine variations in the echo amplitudes in normal liver and

in cirrhosis, and to estimate the effective attenuation of ultrasound in the liver

assuming a random spatial distribution of intrahepatic targets. They also investigated

the effects of variations in the characteristics of the anterior abdominal wall, since

it had been suggested by Wells et al. [6] that, at a frequency of 1.5 MHz, an increase

of 10 mm in fat thickness might cause an increase of 0.5 dB in intrahepatic echo amplitude, while the same increase in muscle thickness might cause a decrease of 4.5 dB.

The obliquity of the scan angle and the air bubble content of the pores of the skin,

could also introduce errors.

A block diagram of the measuring apparatus is shown in figure 1. Provision was made for standardizing the system sensitivity, but this is not shown in the diagram.

The pulse repetition rate was 1000 S"^, and the transducer had a diameter of 20 mm, a zero-crossing frequency of 1.67 MHz, and a 20 dB bandwidth of 1.2 MHz. The field was reasonably regular at ranges beyond 50 mm. The waveform displayed on the cathode ray oscilloscope corresponded to echoes selected by the adjustable delay to have originated

from the range interval commencing at 50 mm and extending to approximately 100 mm. The

parts of the circuitry which processed this signal were linear. The conventional demodulated

A-scan was presented on a second cathode ray tube, and with experience it was possible to

be certain, by studying this display, that the ultrasonic beam was passing through the

liver, and that the range interval 50-100 mm lay entirely within the liver.

For each individual examined, the cathode ray oscilloscope display was photographed

30 times, each with a new position of the probe. These photographs were analyzed by

measuring the amplitude of each cycle from the peak to the succeeding trough. The measurements were begun at the graticule line corresponding to a range of 50 mm, and were repeated

sequentially for 100 cycles. Generally, these cycles were regularly spaced, and occupied

a range interval of about 47.5 mm. Each amplitude was measured to the nearest millimeter;

the maximum amplitude which could be contained on the photograph was 56 mm, so that the

maximum measurement precision was equivalent to a word length of between 5 and 6 bits.

There were 3,000 data points for each individual.

Thus, each scan consisted of 100 data points. These data points may be regarded as samples of echo amplitude y at regular intervals of distance x. Therefore, for each

individual, there were 100 x-values, each with 30 data point estimates of y. The analysis

was based on the assumption that these echoes originated from targets within the liver,

randomly distributed spatially.

Since the echo amplitude might be expected a priori to decay exponentially with

range, then the regression of the logarithm of the mean values of the 30 data point

estimates of y for each value of x {i.e.. In y) against x should be linear. Moreover,

the slope of the regression line should reflect the attenuation of ultrasound within the

1 i ver.

62
>-

CJ LjJ s:

LlJ Li_ o

o- 1 LU Q.

cy Li_

O) CL) x: S +-> <u o

c: •!- o

•rO -)-> ^ •- 3: o •>

O) Ol 3 73

•r-' "O (A Cm +-> -C

"O cn

S- -r- o s- O

s: ^CD

>>. 3

-Q

O

S_ o -C

O) -(-> o o

f) •!— +J o

fo o)

S- 00

fCQ.1

Q- (13 (C C o -a

•r- 3 C 4-> o •-

(/) CD

rO

C

s- o

+-> I— 3 (O

OJ >> ^ J3

cn 0) c +-> •1- ra 2 S- o +-> -c: </)

i/i :3 E

<XS <-'

S-CD CO fO TT3 OJo • O i- +J O Q-MI— O) CQ U I

C OJ • O ^ 1— (/)+-> to

<u s- E +-> o 3 I— S- 01 3 lies
Thirty individuals with normal livers were studied [9]. Pooling the results

for the whole groups revealed a very good linear relationship between In y and x. Echo amplitude was approximately log-normally distributed about this line. The apparent

attenuation rate of the pooled group was 1.76 dB cm"i. Investigation of the echo

amplitude values failed to confirm the anxiety of Wells et at. [6], referred to previously

in this section, concerning the possible importance of variations in the characteristics

of the body wall according to somatotype. On the contrary, individuals with high meso- morphy ratings tended to have higher echo amplitudes.

The results obtained with normal livers were compared with corresponding measurements

in 13 patients with cirrhosis. The differences between the slopes of the regression lines were not significant (although generally the attenuation was lower in cirrhosis than in normals), but the echo amplitudes in the cirrhotics were always greater than those in the normals, the separation being greatest when the amplitudes corresponding to the In y

intercepts of the regression lines at x = 50 were compared. (In this scheme, x is the

cycle number, and the limits of range of the sampled tissue are 0 < x < 100.) This

separation is illustrated in figure 2, and is equivalent to 6 dB.

15 r

10

NUMBERS OF INDIVIDUALS

WITHIN

AMPLITUDE

INTERVAL

5

-

n

0 LNORMALS

CIRRHOTICS

J_L t i I I I J—

I

2.5 3.0 3.5 INTERVAL LIMITS OF LOG AMPLITUDE

4.0

Figure 2. Histogram showing the distribution of midpoint amplitude (In y at

X = 50) for all 43 individuals in Mountford and Wells' [9,10] study. The

absolute values of amplitude were determined by the conditions of measurement,

but the data illustrate that the cirrhotic group does not overlap the

normals. (From Mountford and Wells [10].)

64
For each individual set of data, the effect of the exponential regression was removed by adding the appropriate factor to each value of In y. Consecutive values of

In y may be regarded as equidistant samples of the echo envelope. A typical result is given in figure 3. Averaging all the data in the normal group and in the cirrhotic

group allowed the mean echo envelope shapes (trough-to-trough) to be compared, as shown

in figure 4. In relation to the normals, the cirrhotics had significantly faster risetimes, and significantly fewer peaks and troughs.

5r

CORRECTED

In y

J I 50

CYCLE NUMBER, x

100

Figure 3. Typical graph (for one scan) of In y, corrected for regression (mean

value for 30 scans of the same individual). Normal liver. The corrections

are referred to x = 0. (From Mountford and Wells [10].)

ENVELOPE

(LOG AMPLITUDE)

CIRRHOTICS

0.0

TIME, CYCLES

Figure 4. Mean echo envelope shapes for 30 normals and 13 cirrhotics. The envelope

(log amplitude) is expressed in units of difference values in In y. The time

is expressed in units of cycles, one cycle corresponding to approximately 0.6 ys. (From Mountford and Wells [10].)

65
3. Automated Data Acquisition and Analysis

In the method of analysis described in the previous section, large numbers of measurements were made manually from the photographs of the scans, and these were punched onto

cards for processing by computer. Four techniques of analyzing liver echograms, which

avoid most of the drudgery of manual work, have been described.

Grossman [11] has developed an instrument, using analog circuits, in which the

number of echoes occurring along a gated section of the A-scan is counted automatically.

This does not seem to have been used clinically, nor would it be expected to be helpful

since the echo frequency is not a good index of diffuse abnormality, nor can it be related

to localized abnormalities unless it is presented as a pattern on a two-dimensional scan.

Two-dimensional grey-scale liver scans have been used by Rettenmaier [12] to identify

appropriate areas of the image for analysis, the brightnesses of the intrahepatic diffuse

echo patterns being correlated with clinical conditions. In relation to normals, scans of slightly fatty livers have lower brightness, while the brightness becomes increasingly

greater in chronic hepatitis, moderately and severely fatty liver, and cirrhosis. To this extent, the method is similar to that of McCarthy et al. [13], who concluded from

subjective comparisons of echo patterns that scans of cirrhotic livers were indistinguishable from those of normals made with an increase of 2.5 dB in system sensitivity.

(Subsequently, Mountford and Wells [10] estimated this difference to be equivalent to

6 dB; see previous section.) Furthermore, Rettenmaier [12] estimated attenuation from

the change in brightness with increasing range (using a parallel line scan pattern).

Slightly fatty livers have lower attenuation than normals, and the attenuation becomes

increasingly greater in chronic hepatitis, severe and moderately fatty liver, and

cirrhosis.

Having similarly localized an area for analysis on a two-dimensional B-scan,

Fields et al. [14] photographed a series of separate A-scans through this area. From

the illustrations of their article, it appears that the demodulated A-scan was used. An image of this was projected onto a screen where the amplitudes and positions of the

peaks were digitized with a GRAF/pen interfaced with a PDP-11 computer. They seem to have analyzed only six A-scans from each patient, and so it is hardly surprising that

the standard deviations of their results were rather large.

Mountford et al. [15] automated the method used previously by Mountford and

Wells [9,10]. Figure 5 is a block diagram of the arrangement. Again the system operated

linearly at 1.5 MHz without swept gain, but the receiver output was demodulated before

being digitized by a 128-word, 6-bit transient recorder. Satisfactory recording of the

video waveform required a sampling frequency of 5 MHz, and this corresponds to about

25 us of storage time, or a range of only about 20 mm in soft tissues. Since the earlier

study had demonstrated that the analysis at a range of 75 mm was most efficient, it was arranged that the transient recorder commenced sampling after a delay of 85 ps corres- ponding to a range of about 65 mm. The data from a single A-scan having been stored in the transient recorder, the words were punched onto 8-column paper tape. Complete word

sequences were separated by lengths of blank paper. The sequences were arranged in blocks

of 30, each block representing a single set of measurements. Six blocks were collected

for each individual studied. An individual could be examined in about 10 min.

The first 120 words in each sequence were used for analysis by an IBM 1130 computer

with 16 K store. From each word, the mean recorded baseline level was subtracted to yield the true sample amplitude. Logarithms of these amplitudes were taken and a regression line was fitted by the method of least squares. The slope and midpoint

amplitude of this line were calculated. Thus for each block, one value of slope and

one of amplitude were calculated.

Ten individuals with normal livers, and three with cirrhosis, were examined using

this method. At maximal inspiration, the mean amplitudes of the cirrhotic group were

all greater than those of the normals, and there was no overlap between the two groups

at the level of one standard deviation. With only one exception, the mean amplitudes of

the normals fell as a result of inspiration.

66

/
COUNTER

TRANSMITTER MANUAL

TRIGGER

PROBE

RECEIVER

DEMODULATOR

VIDEO

AMPLIFIER

TRANSIENT

RECORDER

DELAY

PARITY CHECK > f

N f

PAPER TAPE < BLANK TAPE

PUNCH FEED

Figure 5. Block diagram of the -utomatic data analysis system (Mountford et al. [15]). The counter records the number of single shots which have been made in collecting the complete set o1 data. The circuit is arranged as a conventional

A-scope while the operator ir. searching to satisfy the criteria of echogram

acceptabil ity.

The estimates of slope using the automated system were subject to rather large

values of standard deviation. Doubtless, the chief cause of this was the relatively

short length of data available for analysis.

4. Discussion

In an unlimited lossless homogeneous medium, the wave velocity c = (K/p) % where

K is the bulk modulus, and p is the density. Furthermore, the characteristic impedance

Z = pc. Combining these two equations yields the result Z = (Kp)^.

According to Fields and Dunn [16], the density variation of soft tissues is 1% or less. They concluded that it is variations in elasticity which largely account for

67
echoes from within soft tissue structures. (Note that the density of fat is 0.92 g ml'i,

and that of muscle is 1.07 g ml"i; this is a difference of more than 15%. Moreover, the

different constituents of tissue of the cellular level have a larger range of densities.

Therefore, it may not be valid to neglect variations in density as contributors to echoes.) Collagenous fibers exhibit an elastic modulus greater by a factor of about

1,000 than that of other soft tissues, and they hypothesized that the amount of collagen

may be the dominant factor in determining characteristic impedance. This could account

for the observation of Fry et at. [17] that pig liver, with well -developed connective

tissue between lobules, returns high-amplitude echoes, whereas echoes from cat liver,

in which the connective tissue is poorly developed, are of low amplitude. Similarly,

there is an increase in echo density in the post-menopausal breast [18], in which

there is an increase in fibrous tissue in relation to the pre-menopausal breast. The

data for liver cirrhosis are consistent with the finding of Boyett and Sullivan [19]

that there may be a three-fold increase in collagen content in the disease. On the other

hand, Rettenmaier [12] concluded that the high-amplitude echoes seen in cirrhotic

liver should not be considered to result from an increase in connective tissue, because

comparable echo amplitudes occur in high-degree fatty liver without essential fibrosis.

He suggested that the pattern originates at the interfaces between hepatocytic plates

and the fine vascular network. A similar mechanism was proposed by Mountford and

Wells [10], who wrote that the echoes produced by cirrhotic liver, higher in amplitude

but otherwise very similar to those of the normal, could be due to similar targets

with greater characteristic impedance mismatches.

Although there are no sharp distinctions, biological targets may be considered to fall into three categories. The extensive boundaries of major structures and organs

represent a large-obstacle situation: the reflection is specular at frequencies at which

the surface irregularities are very small in relation to the wavelength. Subcellular,

cellular and tissue structures are small in relation to the wavelength, and the scattering

is a statistical function of both space and time. Thirdly, other biological targets lie

between these two extremes.

The echo wavetrain received from liver tissue irradiated by a short ultrasonic pulse

consists of cycles quite regularly spaced in time at a frequency corresponding to that

of the ultrasonic pulse. The amplitude decays at a rate which is approximately

exponential with range. At first sight, the echo amplitude spacing on the A-scan suggests

that liver has a structure on the corresponding scale. While this might be the case, it

would remain remarkable that there seems to be such a close relationship between the

pattern and the wavelength, in terms of the regular cyclical spacing of successive

peaks and troughs. The implication is that the observed structure is a random noise

effect, in which the dimensions of the ultrasonic pulse determine the scale of the

fluctuation which is observed. Considerable support for this theory exists in relation

to the echoes from blood [20]. The situation in blood is certainly much less complicated

than that in liver, which contains blood vessels and bile ducts of dimensions varying

from the relatively large down to the cellular organization of the parenchyma. In liver, the echo is the sum of a great number of statistically-independent contributions,

because there are many reflectors of very different shapes within the relatively large

resolution cell. Moreover, in life, blood flow and other physiological movements change

the target orientation so that the echo pattern fluctuates with time.

The method of Mountford and Wells [9,10] was not sensitive to echo shape, although,

as mentioned in Section 2, it did show that the echo envelope has a significantly longer

trough-to-trough duration in cirrhotics than in normals. This suggests that the actual

target spacing may be slightly increased in cirrhosis--perhaps due to portal

hypertension--and this may provide the basis for any success which might be achieved in liver tissue- characterization in terms of measurements of the dependence of scattering on frequency or direction. These possibilities have been discussed by Hill [21], and in this connection it may be helpful to point out that all attempts at tissue characterization up to the present time seem to have been essentially two-dimensional. This paper

deals mainly with measurements of amplitude with changing range at a particular frequency,

or group of frequencies. Other investigators have studied velocity, absorption and

dispersion: see, for example, Kossoff [22] and Wells [23]. Finally, the spectral

studies of scattering are concerned with measurements, at a fixed range, of changes

in amplitude either with frequency or with angle. Some of these approaches are more 68
promising than others; all have limitations. Some of the methods are capable of refinement: thus, areas of interest identified on two-dimensional scans could be subjected to numerical analyses. The time has now come to begin to use these various methods in parallel: for example, it might be useful to generate three-dimensional displays,

illustrating the variation of the frequency spectrum with range. More generally,

computer-based pattern recognition methods, now being developed in geophysics [24],

could be used to identify the features which distinguish the echoes produced by

different tissues.

We are grateful for grants from the Board of Governors of the United Bristol

Hospitals, the Department of Health and Social Security, and the Medical Research

Council

.

References

Howry, D. H., A brief atlas of diagnostic ultrasonic radiologic results, Radiol.

Clin. N. Am., 3, 433 (1965).

Holmes, J. H., Ultrasonic diagnosis of liver disease, in Diagnostic Ultrasound,

C. C. Grossman et al., ed., p. 249 (Plenum Press, New York, 1966).

Evans, K. T. , McCarthy, C. F., Read, A. E. A., and Wells, P. N. T. , Ultrasound in the diagnosis of liver disease, Br. Med. J., 1, 1368 (1966).

An, S., Wang, T., An, S., Chu, S., Wu, H., Hsu, C, and Yu, K. , The use of pulsed

ultrasound in clinical diagnosis. Chin. Med. J., 81_, 315 (1962).

Schentke, K. U. and Renger, F., Uber die diagnostische verwertbarkeit des ultraschallhepatogramms, Z. Ges. Inn. Med., 21_, 239 (1964).

Wells, P. N. T., McCarthy, C. R., Ross, F. G. M. , 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 (1969).

Wild, J. J. and Reid, J. M., Further pilot echographic studies on the histologic

structure of tumors of the living intact human breast. Am. J. Path., 28, 839 (1952).

Czarnecki , T. and Kubicki, S., Observations on the application of ultrasounds in

the diagnosis of diffuse liver disease, Pol. Med. J., 9_, 79 (1970).

Mountford, R. A. and Wells, P. N. T., Ultrasonic liver scanning: the quantitative

analysis of the normal A-scan, Phys. Med. Biol., ]]_, 14 (1972).

Mountford, R. A. and Wells, P. N. T. , Ultrasonic liver scanning: the A-scan in

the normal and cirrhosis, Phys. Med. Biol. Vl_, 261 (1972).

Grossman, H., Automatische echc jrammauswertung bei der ultraschall-leberdiagnostik,

Naahriahtenteohnik, 21_, 64 (1971 ).

Rettenmaier, G., Quantitative criteria of intrahepatic echo patterns correlated

with structural alterations, in Ultrasonics in Medicine, M. de Vlieger et al. , ed.,

p. 199 (Excerpta Medica, Amsterdam, 1974).

McCarthy, C. F., Read, A. E. A., Ross, F. G. M., and Wells, P. N. T., Ultrasonic

scanning of the liver. Quart. Med. J., 36_, 517 (1967).

Fields, S. I., Bowie, J. D., Pai , A. L., and Lichtor, J. L., Tissue differentiation

by semi -automated quantitative analysis of A-scan echography, in Ultrasound in

Medicine, Vol. 1, D. N. White, ed., p. 439 (1975).

Mountford, R. A., Halliwell, M. , and Atkinson, P., Ultrasonic liver scanning:

automated A-scan analysis, Phys. Med. Biol., 18, 559 (1973).

69
[16] Fields, S. and Dunn, F., Correlation of echographic vizualizability of tissue with

biological composition and physiological state, J. Acoust. Soo. Am., 54, 809 (1973).

[17] Fry, E. K. , Okuyama, D., and Fry, F. J., The influence of biological and instrumentation variables on the characteristics of echosonograms , in Ultrasonographia

Medioa, J. Bock, et al. , ed.. Vol. 1, p. 387 (Wiener Medizinischen Akademie,

Vienna, 1971).

[18] Fry, E. K. , Kossoff, G., and Lindeman, H. A., The potential of ultrasound vizualization for detecting the presence of abnormal structures within the female breast.

Proceedings of IEEE Ultrasonics Symposium, p. 25 (IEEE Cat. No. 72CH0 708-8 SU, IEEE, New York, 1972).

[19] Boyett, J. D. and Sullivan, J. F., Zinc and collagen content of cirrhotic liver.

Am. J. Dig. Dis., Jl, 797 (1970).

[20] Atkinson, P. and Berry, M. V., Random noise in ultrasonic echoes diffracted by

blood, J. Phys. A, 7, 1293 (1974).

[21] Hill, C. R., Interactions of ultrasound with tissues, in ultrasonics in Medicine,

M. de Vlieger et al., ed., p. 14 (Excerpta Medica, Amsterdam, 1974).

[22] Kossoff, G., Progress in pulse-echo techniques, in ultrasonics in Medicine,

M. de Vlieger et al. , ed., p. 37 (Excerpta Medica, Amsterdam, 1974).

[23] Wells, P. N. T., Absorption and dispersion of ultrasound in biological tissues.

Ultrasound Med. Biol., \, 369 (1975).

[241 Pace N G., Sediment identification using acoustic techniques, in ultrasonics

International 1975 Abstracts, p. 20 (IPC Science and Technology Press, Guildford,

1975).

70
National Bureau of Standards Special Publication 453. Proceedings of Seminar on Ultrasonic

Tissue Characterization held at NBS, Gaithersburg, MD, May 28-30, 1975. (Issued Oct. 1976)

Paper 3.3: DIGITAL A-SCAN ANALYSIS IN THE DIAGNOSIS OF CHRONIC

SPLENIC ENLARGEMENT

K. J. W. Taylor

Yale University School of Medicine

New Haven, Connecticut 06510

and

J. Milan

Department of Physics

Royal Marsden Hospital and Institute of Cancer Research

Sutton, Surrey, United Kingdom

Before the availability of grey-scale ultrasound machines, signal

processing only permitted the display of the layer echoes which were specularly reflected at large discontinuities of acoustic impedance.

The enhanced signal-to-noise ratio inherent in the grey-scale technique

permits, in addition, the display of the internal structure of soft

tissue. The amplitude of these low-level echoes is relatively independent of beam orientation and appears to be more dependent on the

nature of the interface so that the pattern of the tissue may be

specific to each pathology. From clinical observations, high-level

echoes are usually associated with benign causes of splenic

enlargement, while cellular infiltration, as in many malignancies,

results in decreased echo amplitude. Digital A-scan analysis concerns

and quantitates this difference.

Key Words: A-scan analysis; digital; grey-scale ultrasound; spleen;

splenomegaly.

1. Introduction

An important feature of recent developments in grey-scale ultrasonography is the re- tention and display of low-amplitude echo information [1]^. Conventional machines, developed

mainly for displaying specular echoes originating at large discontinuities of acoustic

impedance such as the fetal skull or placental/fluid interfaces, reject low-level echoes

as "noise" or "grass" either in the signal processing or display system. Indeed, the

disparity between the range of echoes from tissues and the dynamic range of the display

systems makes it easier to suppress the smaller echoes, thereby decreasing the range for

display.

Conventional systems largely involve the display of specular echoes and the quantitative analysis of these is unlikely to be informative on the nature of the tissue being

interrogated. This is because the amplitude of specular echoes largely depends upon the

rather random orientation of the reflecting surface with respect to the beam and this, in turn, is markedly affected by the scanning technique of the operator and the degree of

compounding involved.

However, although the precise mechanisms involved are far from clear, the physical

principles pertaining to the low-level echoes displayed in grey-scale ultrasonography appear

to be different from those pertaining to specular reflections. The grey-scale technique'

involves the selective amplification of low-level echoes and these appear to be much less

^Figures in brackets indicate the literature references at the end of this paper.

71
dependent on the angle of incidence. Although these may be backscattered echoes, it is also possible they could be specular ones from small, spherical reflectors which would thus

be more omnidirectional. Whatever the mechanism, the important conclusion is that the amplitude of these low-level echoes that are retained and displayed in grey-scale techniques

are relatively independent of the orientation of the beam and this raises the possibility

that the echo amplitude is mainly dependent upon the nature of the interface and hence

on the consistency of the tissue. In this situation, an analysis of the amplitude of

echoes arising from tissues could produce quantitative data which may have diagnostic value.

There is considerable clinical and empirical evidence to encourage this view; from the B- scan display, it is known that in some clinical conditions such as cirrhosis of the liver

and other states producing an increased fibrous content of the liver, brighter echoes are

produced. Mountford and Wells [2] quantitated the echoes emanating from cirrhotic livers

and found them to be significantly higher than those from normal livers. This raises

the possibility of identifying certain disease states from the echo amplitude returned

and, by serial scanning, to produce an objective measure of progressive pathology. Such

data would be of great interest in monitoring industrial exposure to a wide variety of

potentially hepato-toxic chemicals.

Before considering the means of digital A-scan analysis, it is interesting and of

great importance clinically in connection with interpretation of scans, to consider the

possible sites of echo formation and how the echo amplitude may vary with the nature of

the interface. The classical formula for the magnitude of the reflected component R of

an incident ultrasound beam is:

where oj, 02 are the densities and C^, C, the velocities of sound in the media at the

interface. Fields and Dunn [3] pointed out that this expression made it difficult to account for the magnitude of the reflected component, since, to a first approximation, there

is little variation in the velocity of sound in different soft tissues. Thus, a possible

site of echo formation becomes more apparent if the expression:

is substituted in Eq. (1). Thus, assuming little variation in density between the different

tissues

,

where B^ and B2 are the bulk moduli of the media at the interface. Fields and Dunn [3]

examined the figures available for the bulk moduli of various soft tissues and found that

these did vary by several orders of magnitude. In particular, tissue elements of a supporting nature, such as collagen and elastin, could constitute a major site of echo formation.

This is consistent with past clinical observations and those reported in this paper.

When a tumor replaces the normal fibrous skeleton of an organ, a defect is apparent in the normal anatomy while various causes of increased fibrous tissue within the liver, such

as inflammatory states and the rare, successfully treated metastases, produce increased

echo amplitudes [4,5].

This concept is also supported quantitatively by the work of Mountford and Wells [2]

who reported that the amplitude of echoes from the livers of patients with cirrhosis were significantly higher than those with normal livers. This quantitated past clinical observations on the ultrasonic appearance of cirrhosis [6,7]. However, it seems unlikely that all data on echo amplitude can be ascribed merely to the supporting tissue content and indeed we have noted that fatty infiltration is also associated with high-level echoes but in a recognizably different pattern from those seen in established cirrhosis or chronic inflamR

=

P]^-| _ ^2 2

p-|C-j +

(1)

(2)

72
matory states. It, therefore, appears that the spatial distribution of echoes is of equal

importance to the amplitude of echoes in the differential diagnosis of liver disease. Such

pattern recognition is easier for the trained diagnostician whose interpretation at present

is superior to that obtained by computer technology. Interest is focused on the spleen

as an experimental model, since the pattern seems relatively constant in different pathologies while the relative echo amplitude permits differentiation of various pathologies.

The clinical results obtained on ultrasound scanning of enlarged spleens were reported

by Taylor and Milan [8]. They found that of 30 large spleens returning very low-level

echoes, all were malignant (either leukemias or lymphomas). Conversely, of nine spleens

returning very high-level echoes, six were chronic inflammatory states and hence contained

abnormal amounts of fibrous tissue, while two of the remaining three were benign causes

of splenic enlargement in patients with malignancy elsewhere. Furthermore, one of these

was found in a myeloproliferative disorder in which excessive collagen is present in the

spleen. Thus, in pathologies in which an increase of fibrous tissue could be expected,

there were high-level echoes, while abnormal cellular masses were characterized by echoes

of similar or lower amplitude than the normal spleen. A third intermediate group was also described, again largely benign, in which the amplitudes of the echoes returned lay

between the two previous groups--the commonest disease in this group was splenic enlargement due to cirrhosis of the liver with consequent portal hypertension. Digital analysis

was undertaken on these groups of patients to confirm and quantitate these clinical

observations. The method and the preliminary results are reported here.

2. Method

The equipment used in these studies was custom-built [9] on the principles described

by Kossoff [1]. The resulting scans have markedly more signal-to-noise ratio than conventional equipment available and to date it is not clear whether the commercially-available

grey-scale systems are equally suitable for this examination. The ultrasound equipment

was used to produce a B-scan display of the spleen by scanning either longitudinally,

transversely or obliquely, depending on the size of the spleen. The computer was then

switched on-line and the scan repeated. During this process, the signals from the scanner

were digitized and stored in a Digital Equipment Corporation PDP 8/E computer, which had

12 k words of memory and 1.6 M word magnetic disc.

In order to produce standardized data when the computer was on-line, a constant tissue

absorption correction was maintained, no attenuation was used, and the echo signal range

was compressed by means of a full-range logarithmic amplifier. The output from this was processed by means of a peak detector and 128 samples of each A-scan contributing to the

B-scan display were digitized to a precision of 6 bits. The signals from the positional

potentiometers were digitized separately to a precision of 12 bits and both sets of data were stored on the magnetic disc in real time.

When the scan was complete, the data stored on the disc were processed to produce a B-scan display on a color television display system. This display has a resolution of

96 x 96 points and uses the temperature scale (red-orange-yellow-white) to represent echo

amplitude [10]. An advantage of such a color scheme is that half-tone photographs are meaningful. A facility was provided in the processing program to superimpose on the display

a pair of crosswires which were positioned to delineate a particular area of interest.

The data stored on the disc were then processed to extract quantitative information on all the echoes within the delineated area. The mean and standard deviation of echo size were calculated and a histogram produced of echo amplitude against frequency of occurrence.

3. Results

Typical results of the B-scans in the three groups of patients are shown in figures

1, 2, and 3. Figure 1 shows moderate enlargement of the spleen while the consistency

returns very low-level echoes which, with, the present signal-to-noise ratio, cannot be

reliably distinguished from the normal consistency. In both situations, the echoes are

too low to be recorded although this will obviously vary with the machine settings, and

in particular, with the type of equipment used. However, with the same equipment settings,

there is an obvious difference between the brightness of the echoes seen in figure 1 from

those seen in figures 2 and 3. Figure 2 is a case of non-tropical splenomegaly--a benign

73
Figure 1. Oblique ultrasonogram of enlarged spleen (S) which appears black indicating

that very low level echoes emanate from within it. This was an acute leukemic spleen.

Figure 2. Transverse ultrasonogram of spleen (S) lying to the left of the vertebra

(V) and an enlarged splenic artery (a) is seen. Note the medium level echoes which

are found in benign conditions and in this patient was due to non-tropical splenomegaly.

Figure 3. Longitudinal scan of spleen (S) showing very high-level echoes from within

it so that the consistency appears white. This patient suffered from a chronic

inflammatory state.

74
condition--whi le figure 3 shows the scan of the patient with tuberculosis and the very highlevel echoes are apparent on the brightness-modulated scan.

The digital analysis permits these results to be substantiated and quantitated without

operator bias or modification by equipment settings. The histogram corresponding to figure

1 is shown in figure 4, which confirms that low-level echoes are produced. Figure 5 is the histogram obtained from the type of splenic consistency displayed in figure 2 when

intermediate echoes are obtained. The apparent bimodal distribution on the histogram we believe to be due to the lower tail of the Gaussian curve appearing in the first bin

because of insufficient signal-to-noise ratio. Figure 6 is striking since the echo

amplitudes in this case are of a similar magnitude to those seen in cirrhosis of the liver

using this equipment. Thus, the difference between most malignant consistencies are vastly

different from those seen in most of the benign causes of splenic enlargement. Although

this is apparent on the B-scans, the difference can be confirmed and quantitated by this

technique, free of operator bias.

Normal Spleen

o

JZ

u

0)

o

» »

• *

• * » »

*

* » *»»» »

o

u

O

c

echo amp

*

* )(• *

* * * * * ** *

* * *

•X- * * *

* * * *

* * *

* * *

* * * *

* * * * *

* * * *

* * * * * * •X- *

* * * * * * *

* * * * * * *

* * * * * * * * *

* * * * * * * » * * echo am p

NO. OF ECHOES = 10* 189

MEAN = 16 S.D. = 10

NO. OF ECHOES = 7,244

MEAN = S S.D. = S

Figure 4. Histogram of echo amplitudes Figure 5. Histogram of echo amplitude

corresponding to the spleen shown in corresponding to the spleen seen in

figure 1 . figure 2.

75
* * *

*

* *

*

* * * * ******

******

*******

*******

*******

********

*********

*********

***********

************ • •••••••••••••

echo amp.

NO. OF ECHOES = 12*079

MEAN = 27 S.D. = 12

Figure 6. Histogram of echo amplitudes corresponding to the spleen seen in figure 3. Note the progressive shift towards the right in these three

figures.

4. Discussion

The main value of a computer system such as we have described here is that it may be

used to provide objective information about echo signal strength. The mean amplitude of

the echoes from the splenic tissue will depend partly upon the pathological state in a particular patient and partly upon other factors, including the quantity and nature of

the tissue between the analyzed area of the spleen and the transducer in contact with the

patient's skin. The passage of the beam through the intervening tissue may cause signifi- t cant variations within groups of normal or abnormal patients and thus, although the mean f echo amplitude is a useful aid to the diagnosis of gross abnormalities, it is of less ; value when the abnormalities are slight.

However, in individual cases, the factors other than splenic pathology which contribute to variations in echo amplitude may be expected to remain relatively constant with

respect to time so that small variations in echo intensity may be significant. For example,!; we have noted that successful and energetic treatment of the leukemias is frequently

accompanied by an apparent increase in the low- level echoes which is more marked in the

deeper tissues (fig. 7) due to depth-attenuation compensation. This may provide an objective means for monitoring response to treatment. A similar change may be found in the

liver when there appears to be an increase in echo amplitude in response to therapy. Such

a change may precede the clinical improvement in the patient's involvement by malignancy [5]j

There are further possibilities in monitoring progressive liver damage occurring through r social exposure to alcohol or industrial exposure to hepato-toxic agents such as vinyl

chloride. There is also evidence that grey-scale ultrasonography may be valuable in | the latter respect [11].

76
Figure 7. Longitudinal scan of spleen in chronic lymphatic leukemia after extensive

treatment. Low-level echoes are apparent compared with figure 1 and these are accentuated by the depth-attenuation correction (TGC). Thus, effective treatment of

malignancies may cause some increase in echo amplitude towards medium-level echoes.

The histograms in figures 4 through 6 show wide standard deviations. Despite this,

given a sufficiently large sample, small differences in mean amplitude will nonetheless

be significant. However, the versatility of the technique would be extended if the standard

deviation could be reduced. In this preliminary work, in which we were not able to digitize in real time, much of the variation apparent in the histograms is due to the

digitization process rather than variations in echo amplitude. Improvements in the

digitization technique, currently under development, will produce true histograms of echo

intensity and also allow comparison of different sections of the same A-scan. The latter

will be the first step towards recognizing changes in the patterns as well as changes

in intensity which occur with progressive pathology in soft tissues.

References

[1] Kossoff, G., Display techniques in ultrasound pulse echo investigations:

J. Clin. Ultrasound, 2, 61 (1974).

a review.

[2] Mountford, R. A. and Wells, P. N. T., Ultrasonic liver scanning: the A-scan in the

normal and in cirrhosis, Phys. Med. Biol. YJ_, 261 (1972).

[3] Fields, S. and Dunn, F., Correlation of echographic visualizability of tissue with

biological composition and physiological state, J. Acoust. Soa. Am., 54, 809

(1973).

[4] Taylor, K. J. W., Carpenter, D. A., McCready, V. R., Grey-scale echography in the

diagnosis of intrahepatic disease, J. Clin. Ultrasound, 284 (1973).

[5] Gilby, E. D. and Taylor, K. J. W. , Ultrasound monitoring of hepatic metastases during

chemotherapy, Brit. Med. J., 1, 371 (1975).

[6] Holmes, J. H., Ultrasonic diagnosis in liver disease, in Diagnostic Ultrasound,

C. C. Grossman, J. H. Holmes, C. Joyner, and E. W. Purnell, eds., p. 249 (Plenum

Press, New York, 1966).

[7] Holm, H. H., Ultrasonic scanning in the diagnosis of space-occupying lesions of the

upper abdomen, Brit. J. Radiol. 44, 24 (1971).

77
[8] Taylor, K. J. W. and Milan, J., Differential diagnosis of chronic splenomegaly:

clinical observations and digital A-scan analysis, Brit. J. Radiol, (in press).

[9] Hill, C. R. and Carpenter, D. A., Ultrasonic echo imaging of tissue: instrumentation,

Brit. J. Radiol, (in press).

[10] Milan, J. and Taylor, K. J. W. , The application of the temperature colour scale to ultrasonic imaging, J. Clin. Ultrasound^ 2_, 171 (1975).

[11] Taylor, K. J. W. , Williams, D. M. J., Smith, P. M. and Duck, B., Grey-scale ultrasonography for monitoring industrial exposure to hepato-toxic agents, Lanoet, ]_, 1222 (1975).

78
CHAPTER 4

ATTENUATION AND VELOCITY TECHNIQUES

79

National Bureau of Standards Special Publication 453- Proceedings of Seminar on Ultrasonic

Tissue Characterization held at NBS, Gaithersburg, MD, May 28-30, 1975. (Issued Oct. 1976)

CHAPTER 4. ATTENUATION AND VELOCITY TECHNIQUES

Paper 4.1: ATTENUATION AND VELOCITY MEASUREMENTS IN TISSUE USING

TIME DELAY SPECTROMETRY

D. H. Le Croissette and R. C. Heyser

Jet Propulsion Laboratory

California Institute of Technology

Pasadena, California 91103

A practical ultrasound system is described which is capable of

making measurements of attenuation and velocity in tissue as a function of frequency. This method is based upon a technique

known as Time Delay Spectrometry which employs a swept frequency

signal and has the ability to provide anechoic ultrasonic measurements. A system operating between 2 and 3 MHz has already

been shown to be capable of producing images in soft tissue with

a resolution of less than 2 mm. Preliminary measurements on excised

tissue using this system have indicated a frequency dependence of

attenuation in pathological tissue that is substantially different

from that of normal tissue. The method generates the time domain

response simultaneously with the received frequency sweep. It is shown that the time response in the apparatus is available as a displayed phasor quantity and that the arrival time of the directlyreceived signal can therefore be measured to within a few nano- seconds.

Key Words: Attenuation; phase; swept frequency; time delay spectrometry;

tissue; transmission; velocity.

1. Introduction

The possibilities of using ultrasound measurements for detection and identification

of the pathological state of soft tissue have recently received attention [1-5],^ although

the feasibility of the concept has been shown much earlier [6]. There are a number of

ultrasonic transmission and reflection characteristics which might give information

concerning the pathological or morphological status of tissue. If one or more of these

can be identified, the tissue can be said to have a signature. In this paper, the

following definition will be made.

SIGNATURE - The set of identifiable properties or attributes that

places one thing apart from another.

Tissue characteristics that might produce signature data are listed in Table 1 [3].

Table 1. Tissue Characteristics That Might Produce Signature Data [3]

Reflectivity

Absorptivity

Scattering parameters

Propagation velocity

Specific acoustic impedance

Density.

Figures in brackets indicate the literature references at the end of this paper.

81
Although medical ultrasound in the pulse-echo reflection mode has been used for

diagnosis for more than twenty years, there is not a great deal of knowledge of the

characteristics listed above. There are several reasons for this. First, many of

the quantities vary widely with age, sex and physical condition of the subject.

Secondly, the measurements are difficult to make accurately with most of the existing

equipment. Thirdly, absorption and scattering, which together constitute attenuation,

are difficult to separate in conventional measurements. Lastly, and perhaps the most

important factor to date, there has so far been little need expressed for an accurate measure of these quantities in the design and operation of pulse-echo diagnostic ultrasound

imaging devices.

If tissue identification is to become a reality, signature identifiers must be

found and enough data gathered for confidence to be established in the method. At the

present time, some well-known identifiers are already being used in a subjective manner

by ultrasonographers in clinical practice. The recognition of these characteristic

signatures is based upon years of clinical experience in interpreting ultrasonograms.

Scientific measurements on which interpretations can be based, however, are lacking.

One of the principal uses of ultrasound in providing tissue identification at the

present time is in the differentiation of solid and cystic masses. In general, a cystic

mass may be recognized by the absence of echoes as the receiver sensitivity is increased.

By contrast, solid masses are not sonically homogeneous and show an abundance of echoes.

This method is not completely reliable, however, as discussed by Birnholz [7], who shows

that solid but cellularly-homogeneous masses may be confused with cysts using this

criterion.

Two other methods are used to identify a homogeneous tumor mass. Both rely upon

the known higher attenuation of sound in tumor tissue versus the minimal attenuation in

a fluid-filled cyst. The two methods are (1) to observe whether there is "shadowing"

in the image behind the mass which, if present, indicates that a substantial fraction of

the energy is attenuated, and (2) to observe the ratio of the amplitudes of the reflection

from the front and back surfaces of the mass as given on an A-scan trace.

In all three of these methods, the presence of the mass, whether cystic or solid

has first to be observed in the B-scan image. Thus, a mass which has dimensions less

than the resolution of the system (typically 10 mm) is unlikely to be noticed. Furthermore, the presence or absence of a solid tumor or cyst is inferred from a secondary measure

ment such as loss of energy with distance in the ultrasonic beam. The diagnosis is therefore critically dependent on the skill and experience of the ul trasonographer/physician.

In order to distinguish one tissue from another, it is necessary to be able to identify characteristics in the signature that can be correlated with the type or status of the tissue. In the pulse-echo systems presently available, the signal

processing through the system allows very few signal characteristics to be retained in the final image. In a bistable imaging system, only the presence of an echo above the

threshold level can be detected. In a system which displays a grey-scale image, there

is amplitude information on the echo returns but nothing more. Any changes in shape

of the returning pulse, indicating frequency or phase changes in transit or upon reflection, are lost. Furthermore, signal shaping to give some edge enhancement occurs in most

units. The emphasis is placed on producing a clear, sharp picture even at the expense

of losing information.

The shape of the transmitted pulse in a commercial pulse-echo system is mainly

determined by the characteristics of the transducer. Since the primary object in current

pulse-echo systems is time discrimination, the transducer is heavily damped to produce

a short pulse and no attempt is made to control the frequency spectrum. As the ultrasonic energy travels through soft tissue, it suffers attenuation which increases with

frequency. As the path length increase?, the total attenuation is increased and the

relative reduction in the high-frequency components is greater. In the time domain,

the pulse broadens and its amplitude decreases. In a typical pulse-echo system,

therefore, the propagating signal decreases in amplitude, the pulse width broadens and

the high-frequency components preferentially diminish along the path.

82
Although the pulse-echo system does not seem to be the optimum method for obtaining

tissue characteristic information, it may be used for this purpose. This may be done

by comparing the received pulse with the transmitted pulse and so determine the

transfer function of the medium, including reflection from a tissue boundary if that

occurs. The correlation of this with the morphological or pathological state of the

tissue will allow the signature characteristic to be determined.

Since there is a considerable amount of signal processing carried out after the

signal is received back at the transducer in a commercial pulse-echo system, a conventional

ultrasonic unit cannot be used for this measurement without considerable modification. It

is necessary to obtain the raw transducer output before processing has taken place.

Comparison and analysis of the signals can then be made bearing in mind that the shape

of the pulse is determined, in practice, by the transducer characteristics which are normally selected for high spatial acuity only. A computer analysis of the data will

probably be required because of the need for sampling and conversion of the inputs into

other formats.

Measurements of some tissue properties (velocity, attenuation, etc.) have also been

made at a number of discrete frequencies using continuous-wave techniques. These

measurements, although useful, have suffered from the problems of reverberation,

unwanted echoes, standing waves, etc. There is no way of distinguishing among any one wave in a continuous wave train of single frequency and so it is difficult to select

only the direct signal. To use the continuous-wave technique successfully, an anechoic

method is required which has the capability of making measurements over the frequency

range of interest in medical ultrasound. A method of this type was devised in 1967

by Heyser [8] to make anechoic acoustical measurements on audio transducers. This system

overcomes most of the usual problems encountered with continuous-wave systems. It employs a swept-frequency measuring technique called Time Delay Spectrometry [9],

The method will be only briefly outlined here since its adaptation to medical ultrasound systems has been published elsewhere [10].

2. Time Delay Spectrometry (TDS)

The system presently in use at JPL utilizes an ultrasonic transmission signal

repetitively swept in a linear manner from 3 to 2 MHz approximately 25 times per second.

At the receiver, the signal has the same format, delayed by the transmission time through

the subject. Under conditions of no velocity dispersion, the transmission time is

constant throughout the sweep. Since the frequency is a linear function of time through

the sweep, there is a constant offset frequency between the transmitted signal and the

received signal at each moment that will be proportional to the time delay between them.

A frequency-shifted version of the transmitted signal can be heterodyned against the

received signal to produce a nearly constant frequency difference that contains the

received signal information. This narrow bandwidth signal may in turn be passed through a narrow passband filter to remove those signal components that did not arrive with the time

delay that is selected for the measurement. Using oscillators with suitable phase

stability, a repetitive frequency spectrum including both amplitude and phase is set by

the operator and direct measurements of the characteristics of the medium may be obtained

as the sweep progresses.

TDS is a dynamic system- testing process which breaks away from the rigid concepts

of a steady-state sinewave excitation on the one hand and wide bandwidth impulse

excitation on the other hand. It is a coherent communication process in which both

the time domain and frequency domain are utilized, even if interest centers wholly on one domain. The transmitted signal discussed above has a predetermined frequency spectrum

with the equivalent of a time tag to each frequency component. In the simplest case considered here, this consists of a linear frequency sweep with time in which the tag

is the moment of occurrence of each frequency. Upon emergence from the specimen, the

frequency components with a given time delay are reassembled to yield the frequency

spectrum. This is the time-delayed spectrum for which the process is named.

This method provides the amplitude and phase of the complex signal over the

spectrum. In addition, signal components due to longer path lengths, such as those

caused by scattering, are effectively suppressed because their spectrum time tags reject

83
them. The accepted signal is therefore the anechoic frequency response of the combined

transducers and tissue path. If a multipath situation is encountered in which the

desired signal is closely followed by an undesired signal which traveled a slightly

different path, it is possible to center the acceptance of TDS to the specific arrival

time of interest and narrow the time window to the extent necessary to insure that the

appropriate path is selected, within the limits of the experimental equipment.

Time Delay Spectrometry has been used for visualization of soft biological tissue.

Resolution of at least 2 mm was obtained together with a dynamic range in intensity of about

80 dB. This was electronically compressed down to the 20 dB range available for CRT

display and subsequent photographic reproduction [10].

Because of the linear relationship between time and frequency, there is an easy

transformation between the two domains. The operator has control over the range of

frequencies being utilized and can thus bound the frequency range over which the measurement or analysis is carried out. The significance of this to medical ultrasound measurements is that Time Delay Spectrometry simultaneously yields data on the time-domain vector

and frequency-domain vector that represent wave propagation through the body. In so doing,

a wide range of measurements at high sensitivity is available for time-of-arri val measurements and their spectrum measure.

3. Attenuation Measurements

The system outlined above has been used to make preliminary measurements of the change

in attenuation as a function of frequency over the range of 1.5 to 4.0 MHz. As presently

configured, the apparatus can be used for imaging and tissue measurements over the frequencies from 2 to 3 MHz and for measurement only over the remainder of the range.

One of the possible ultrasound properties that may yield tissue information is the

frequency dependence of attenuation. In order to check this property by means of Time

Delay Spectrometry, the transmitting and receiving crystals are placed a convenient

distance apart, such as 20 cm. The transmitter is swept through the frequency range,

causing the transmitting crystal to emit an acoustic signal with the same frequency sweep.

The first sound due to this signal will arrive at the receiving crystal with a definite

delay due to the finite propagation velocity in the material interposed between the

transmitting and receiving crystals. The first sound that arrives will always be due to the direct transmission path through the intervening medium. The later arriving sound is

generally composed of either reverberant signal components or of longer path length signals

such as those due to off-axis crystal sounds that are reflected or refracted through a longer path from transmitter to receiver.

All of these received signals are amplified and passed through a narrow bandwidth

tracking filter. This filter is tuned so that only the first sound arrivals, due to the

direct path, are passed on for further analysis. Reverberant sounds are minimized, if not eliminated from the measurement, and crystal polar response is effectively sharpened

without the need for external focusing lenses.

The output of the tracking filter is processed to produce a cathode ray tube display

of the frequency response of the first sound arrivals. Since the whole process is continuously repeated, the observer can move the probes to different portions of a specimen

and tune the delay path for optimum display and observe the results almost instantaneously.

The resultant response will naturally include the imperfect response of the ultrasound

crystals. This does not compromise the data since the entire system can be used to measure

the response of the crystals and associated electronics for subsequent data removal.

In the frequency domain, the net frequency response is the product of the individual

frequency responses. If the response of the transmitting crystal is Fx(w), the response

of the tissue is Fj(to) and FR(a)) is the receiver response, then the combined response is

S(a)) = F^(co) . F-^(a)) • Fp(a)) . (1)

84
If the logarithm of the combined response is taken, this can be expressed as

In S(a)) = In F^(cu) + In F^(a)) + In F^{u^)

= [In F^{^) + In Fp(a.)] + In F-^((.) . (2)

If a measurement is made by removing the tissue and replacing its displaced volume

with an equal volume of water, then this is a measure of the system response and is identical to the term

[In F^M + In F^(a))].

This term can then be readily subtracted from the tissue measurement to remove the imperfections due to the crystal frequency response.

The manner in which this is done is shown in figure 1. The figure displays the system

response over the frequency range of 1.5 to 4.0 MHz. The crystals have a nominal 2.5 MHz resonance.

Figure 1. System response over 1.5 to 4.0 MHz. The top curve is the frequency

response of the system with a water path between the transducers. Each faint

curve below this represents a 2 dB drop in energy of excitation. The bright

curve is the response when the specimen is inserted.

A logarithmic amplifier is used for the display of signal amplitude. The top curve is the

frequency response of the system with a water path between the transducers. Each faint

curve below this represents a 2 dB drop in energy of excitation. The bright curve is the

response when the specimen is inserted and the system excitation is the same as that for

the top curve.

The data are accumulated for convenience as a multiple exposure on a Polaroid film

taken of the sweeping spectrum analyzer. All that is necessary to determine the tissue

ultrasound attenuation versus frequency is a decibel subtraction of the bright curve from

the top curve. By using a precision attenuator with multiple exposures to determine the

system response in dB or fractional dB steps, even the possible errors in the analyzer

logarithmic amplifier or in reading the cathode ray screen are minimized.

85
An example of one data measurement using this technique is shown in figure 2. The

frequency dependence of the central portion of a glioblastoma is compared against a

FREQ.

4.0 (IN MHz)

Figure 2. Attenuation as a function of frequency for two regions in a fixed

specimen from the posterior thalamus.

measurement made on the white matter adjacent to the tumor. The brain section was formalinfixed for this measurement. An interesting point of this measurement is that the frequency

dependence of attenuation of the tumor shows a decided departure from that of non-tumorous

tissue. If this behavior should prove to be general, then we could infer a possible

signature in this frequency dependence. This data is also consistent with an overall

attenuation that has been reported elsewhere [11].

A few of the data on variation in tissue attenuation with frequency measured with

time delay spectrometry methods are shown in figure 3. These data are preliminary since

2 6

10

-(0

2.T)'

1.5 2.5

_ _ LIVER — - TCIRRHOTIC) KIDNEY

3.0 Z3 4.0 pRgQ

CYST ' (IN MHz)

' IN KIDNEY

Figure 3. Variation of tissue attenuation with frequency.

measurements have been taken on only one or two specimens of each type of tissue at the

present time. The data are taken on unfixed autopsy specimens which had a known pathology.

Of considerable interest are the data for the cyst, which shows not as an attenuation

but a gain of 1 or 2 dB cm"i. To understand this phenomena it must be realized that the

system is accepting only the energy which arrives with the minimum time delay. It is believed that the cyst which has a near spherical shape and is filled with fluid acts as

a focusing lens and permits more energy to be received by the receiving transducer than in the case of normal tissue. In the case of a pulse-echo system "anti-shadowing" has been

reported to occur behind a cyst [12]." Since most pulse-echo units operate with swept-gain

in the B-scan system, it is difficult to evaluate the magnitude of the effect. The use of

a TDS transmission measuring system allows the measurement of this effect in detail. At

the present time, our preliminary measurements indicate that we have a method of distinguishing between a solid mass and a cyst. In one instance, a tissue measurement gave such

86
a strong indication of a cyst signature that the specimen was opened by scalpel at the

indicated location and a cyst was found exactly as indicated.

I. 4. Time Measurement

The process of swept-frequency measurement is in effect a frequency-domain technique.

By taking the Fourier transform of the frequency spectrum during the frequency sweep, it

is possible to generate the time-domain response simultaneously with the frequency- domain

response.

There are several advantages to doing this. First, the fact that the time response

is computed from the frequency response means that it is possible to measure in a noncausal manner. That is, since the time coordinate is computed rather than corresponding

to laboratory time, it is possible to dwell on a measurement representing one moment in time

or even to present the results of a reversed time axis. Of course, the computed measurement always results after the swept stimulus giving rise to it. A second advantage lies

in the fact that the computation may readily be made for the single-sided frequency

spectrum. This yields a time response that is a phasor quantity consisting of an amplitude

and a phase. Furthermore, the frequency spectrum chosen for this computation can be a rectangular band with a predetermined low frequency and high frequency cutoff and no spectrum component existing beyond these limits. This is another noncausal measurement

but the results, rather than being merely of theoretical interest, are actually of great

practical value.

The fact that the time response is a phasor can lead to some new signature characteristics that are not apparent from pulse-echo measurements. The magnitude of the timeresponse phasor is a direct measurement of the total energy density of the received energy

as a function of time. The phase of the time response phasor is a direct measurement of

the partitioning of that total energy density into kinetic and potential energy density

components. A computation of the received time signal for a specific moment in time, say

90 microseconds after the transmitter pulse is sent, will have a phase angle that is a very sensitive measurement of the path length and acoustic velocity of the tissue through

which the ultrasound passed on its way to the receiving pulse. In the case of the equipment described in this paper, one degree of phase retardation of this phasor corresponds

to approximately one nanosecond of additional path delay. Thus, the probes may be positioned

at a desired point for transmission measurement and the computation made for the peak

energy of the first sound passing through the specimen. An oscilloscope display of such a time phasor measurement is shown in figure 4. This display is refreshed 25 times per

second and, so long as the probes remain fixed in location, is steady on the screen. If

the probes are now moved to an adjacent position on the test specimen, the phasor will

change its amplitude and phase corresponding to the attenuation and time retardation of

Figure 4. Time phasor recorded on a cathode ray tube.

87
the new portion transinsonif led. If the velocity of the first sound in the new test position is such as to cause an arrival time change of 5 nanoseconds relative to the

previous position, the phasor will swing by 5 degrees in a direction indicating whether

it is a retardation or advance in arrival time.

Some measure of the sensitivity offered can be appreciated by the fact that a full

360 degrees of phasor angle change is brought about by a change corresponding to 0.5 mm

of equivalent water path delay, independent of the total separation between transmitting

and receiving probes. If the direct path component passes through a medium which is, for

example, 10 cm in extent with an average acoustic velocity of 1500 m/s, then a 1 mm thick

inclusion with an average velocity of 1540 m/s will cause an advancement of 18 nano- seconds of arrival time over that of the bulk tissue. The resultant 18 degrees of phase

change is readily discerned in a time delay spectrometer, while it is unlikely that a comparable arrival time advancement would be evident with conventional pulse technology.

A 3 MHz continuous wave system would show the same phase change but would not be capable

of isolating the direct path from other flanking and reverberant sound paths.

With such an enormous sensitivity to arrival time, it might appear at first glance

that in vivo measurements would be unnecessarily restrictive on subject mobility. This

is not the case as has been determined by laboratory measurements. A reasonable amount of

motion along the direct path length of ultrasound incurs no net phase change because the net path length of the subject medium always remains constant. Motion perpendicular to the

ultrasound path causes a change only if it is sufficient magnitude to cause a different

part of the tissue to come under measurement.

In the practical matter of tissue signatures, the time-domain phasor has a greater

spatial resolution than the frequency-domain phasor. This is because the Fourier trans- formation process effectively collapses the measurement to a particular moment in time with

a very narrow acceptance of time components prior to and subsequent to the selected moment. For a frequency sweep of 1 MHz and an average acoustic velocity of propagation corresponding

to water, the time measurement effectively rejects path lengths which differ by more than

1.5 mm from the selected path. For wider frequency sweeps, the path acceptance is correspondingly reduced. This rejection, incidently, takes place even for ultrasound

crystals that have little or no polar angle selectivity in their own right as has been

demonstrated previously [10].

Tissue characteristics relating to absorptivity and scattering may be obtained from

the time phasor. A homogeneous tissue structure definitely shows a uniform phasor trans- mission as the direct sound path is scanned through the specimen. Disrupted tissue structure

tends to show a very erratic phase angle change with little or no amplitude change.

A homogeneous inclusion has a tendency to create a transmission characteristic known

as minimum phase in communication theory. A highly scattering inclusion, creating a large

number of closely-spaced multipath arrivals, produces a non-minimum phase transmission

characteristic.

By changing the frequency sweep width, the "window" of the computed time response may

be altered to include more scattered energy in order to examine the probable extent of a non-minimum phase inclusion. In a similar fashion, the average sweep frequency can be

altered to observe the amount of dispersion in a given region.

With a wide frequency sweep, dispersion may be determined from observing the phase

behavior of either the complex frequency response or, what amounts to the same thing, the

detailed behavior of the Fourier integral from which the time phasor is computed. The j: oscilloscope picture of figure 4 is actually the trajectory of the complex Fourier transform | as it is in process of computation. That is why there is a curve from the center of the ;' screen to the terminal position rather than a straight line. The spot at the center of the ji screen is mathematically that component of the Fourier transform from negative infinite

^ frequency to positive 2 MHz. It is zero simply because no signal frequency components are

j allowed below 2 MHz. The arching curve is the component of the Fourier transform from

positive 2 MHz to positive 3 MHz, and is the data of interest. The terminal of this curve, i which is a point, corresponds to the remainder of the Fourier integral from positive 3 MHz \ to positive infinity. Again, because no frequency components exist above 3 MHz, this is a i null addition to the phasor.

88
Exactly as in the case of the frequency response, the imperfections of the crystal

and electronics can be removed from a time-domain measurement by first measuring the system

with a known acoustic medium, then removing those characteristics from a measurement made

through the unknown tissue.

5. Summary

A practical system of measurement has been described which is capable of great flexibility in determining tissue ultrasound characteristics. While a substantial amount of

experimental data on tissue visualization and measurement using this technique has been

accumulated in the past few years by the authors, this paper has primarily been directed

at the description of the manner in which tissue signatures may be obtained. Particular

emphasis has been placed on the important roles played by both the frequency domain and

time domain, and in the advantage of recognizing the complex phasor representation in both

domai ns

The capability of simultaneous measurement in the time and frequency domain has been

found to give a synergism not presently found with conventional analysis.

We acknowledge the medical advice and assistance of Robert L. Wilson, M.D. of the

Los Angeles County - University of Southern California Medical Center. This paper presents

the results of one phase of research carried out at the Jet Propulsion Laboratory,

California Institute of Technology, under Contract No. NAS7-100, sponsored by the National

Aeronautics and Space Administration.

References

[1] Interaction of Ultrasonic Energy with Biological Structures in 5-Year Research

and Development Agendum for Ultrasonic Imaging Diagnostic Instrumentation, (The

Alliance for Engineering in Medicine and Biology, Chevy Chase, MD, Publication No. N-1975-1, April 1975), available from the National Technical Information Service,

5285 Port Royal Road, Springfield, Virginia 22151, Publication No. PB-230010/AS.

[2] Ultrasonic Transducers: Signal Detection and Preprocessing \x\ A 5-Year Research

and Development Agendum for Ultrasonic Imaging Diagnostic Instrumentation, (The

Alliance for Engineering in Medicine and Biology, Chevy Chase, MD, Publication

No. N-1975-1, April 1975), available from the National Technical Information

Service, 5285 Port Royal Road, Springfield, Virginia 22151, Publication No. PB-230010/AS.

[3] Ultrasonic Diagnostic Scanning and Display Systems ^r\ A 5-Year Research and De- velopment Agendum for Ultrasonic Imaging Diagnostic Instrumentation, (The Alliance

for Engineering in Medicine and Biology, Chevy Chase, MD, Publication No. N-1975-1,

April 1975), available from the National Technical Information Service, 5285

Port Royal Road, Springfield, Virginia 22151, Publication No. PB-230010/AS.

[4] Ultrasonic Diagnostic Signal Processing in A 5-Year Research and Development

Agendum for Ultrasonic Imaging Diagnostic Instrumentation, (The Alliance for

Engineering in Medicine and Biology, Chevy Chase, MD, Publication No. N-1975-1,

April 1975), available from the National Technical Information Service, 5285

Port Royal Road, Springfield, Virginia 22151, Publication No. PB-230010/AS.

[5] Summary ^x\ A 5-Year Research and Development Agendum for Ultrasonic Imaging

Diagnostic Instrumentation, (The Alliance for Engineering in Medicine and Biology,

Chevy Chase, MD, Publication No. N-1975-1, April 1975), available from the

National Technical Information Service, 5285 Port Royal Road, Springfield,

Virginia 22151, Publication No. PB-230010/AS.

[6] Wild, J. J. and Reid, J. M., Progress in the techniques of soft tissue examination

by 15 Mc pulsed ultrasound, in Ultrasound in Biology and Medicine, E. Kelly, ed.,

p. 30 (Am. Inst, of Biol. Sciences, Washington, 1957).

[7] Birnholz, J. C, Sonic differentiation of cysts and homogeneous solid masses. Radiology, 108, 699 (1973).

89
Heyser, R. C Acoustical measurements by time delay spectrometry, J. Audio Eng.

Soo. li, 370 (1967).

Heyser, R. C, Time delay spectrometer, U. S. Patent 3,466,652 (1969).

Heyser, R. C. and Le Croissette, D. H., A new ultrasonic imaging system using time

delay spectrometry, ultrasound in Med. and Biol. U liy

Fishman, L. S., Heyser, R. C, and Le Croissette, D Ultrasonic transmission

measurements on human brain sections, Rad%ology> U^,

Kossoff, G., Display techniques in ultrasound pulse echo investigations: a review,

J. Clin. Ultrasound, 2, 61 (1974).

90
below:

Appendix

Time and Frequency Relationships

Let a signal, w(t), be applied to a network with impulse response, s(t), as shown

w(t) s(t) r(t) (A-1)

The output, r(t), is the convolution of w(t) and s(t) and is given by

CO

r(t) = Jw(x-t) s(x) dx = w(t) * s(t).

(y^_2)

— oo

If, in particular, w(t) is a constant-amplitude, linear frequency sweep given by

w(t)

ift^

then the output r(t) is

00 Ht) - /

if(x-t)^ i|t^ y

e s(x) dx = e / iV , V 2^ -iatx , s(x) e e dx.

Since it is known that the Fourier transform of a product of functions is the

convolution of the transforms of the functions, it follows that

(A-3)

(A-4)

The frequency response, S(a)), of the network with impulse response s(t) is

00

S(a)) = js(t) e""""^^ dt. (A-5)

r(t) = w(t) [S(at) * W(at)], (A-6)

where W(co) is the Fourier transform of w(t).

This is a remarkable result since it demonstrates that a special excitation applied

to a network produces an output which is expressible as a time dependence, but has the

functional form of the Fourier transform. Functionally, the two domains have been interchanged.

If a fixed delay of t seconds is experienced by the signal, and if it is desired

that the epoch defined at t = 0 occur at the network output, then the following figure

shows how this can be achieved. The excitation w(t) must now be advanced in time

dependence to become w(t-x).

W(t-T) s(t)

1 UT w(t) [S(at) * W(at)], (A-7)

If this signal is now multiplied by a frequency- translated version of the complex

conjugate of w(t), and this product used as a signal input to a filter network with

impulse response i(t), the signals are as shown below:

91
w(t) [S(at) * W(at)]—^(X;—^[S(at) * W(at)]e

iw-t ioj.t

i(t) '-*-[S(at) * W(at) * i(t)]e

1

(A-8)

Multiplying by a complex conjugate removed the product dependence of w(t). The offset

frequency multiplication performs a translation in what is commonly referred to as a 'leterodyne of all signal components upward by a fixed frequency, w-j . The network with

response i(t) is a narrow bandwidth filter centered at frequency w-j and hence is what is commonly called the intermediate-frequency selectivity network. This signal, after selectivity

can be translated downward by multiplying by the complex conjugate of the up-conversion

signal as shown below:

iw-t

[S(at) * W(at) * i (t)] e ^ - -[S(at) * W(at) * i(t)]. (A-9)

ico^.t

The function w(t) has the further remarkable property that it is its own Fourier

transform with complex conjugation. That is,

W(at)

a t)

i|t2

(A-10)

Thus, the output of the process shown in the equation above is the convolution, omitting

constant multipliers.

where,

S(at) * A(t)

-i^t^

A(t) = e ^ * i(t), (A-ll)

This is the desired result of a Time Delay Spectrometer. A signal w(t) which is of

constant energy but with defined time-dependent frequency is fed to a network to be

analyzed. The signal in passing through this network will undergo a spectrum change by

S(to) and suffer a time delay, x. The signal thus emerging from the network is multiplied

by the complex conjugate of the original signal delayed by a time x. This product is passed through a narrow bandwidth filter. The result is that the output signal is the

Fourier transform of the impulse response of that network with the delay x. The timedomain selectivity producing the apodization of the desired signal, A(t), is performed by

the joint action of filter bandwidth and excitation. Signals with an earlier or later

arrival time than x will be suppressed by A(t) while signals arriving at time x will be

shaped (apodized) in a manner producing the best representation of S(u)) consistent with

suppression of improper arrival times.

The signal w(t) represents one sweep through all frequencies. Since interest normally

is centered on a restricted band of frequencies, w(t) may be allowed to become repetitive

92
in this band in a sawtooth fashion of frequency versus time with no loss of generality in

the foregoing analysis. When this is done, the output of the network of the above figure

may be displayed on one axis of an oscilloscope with the other axis driven by a sawtooth

signal synchronized to the sawtooth excitation w(t). This repetitive display now indicates

the frequency spectrum of that path representing a fixed and known time delay--hence,

the name Time Delay Spectrometry.

In order to yield the time-domain information from this frequency-domain display, it

is necessary to perform a Fourier transform. Because the time- and frequency-domain

representations are interchanged in a TDS, this is readily accomplished by the method shown

below:

S(at) * A(t)—^1 y[S(at) * A(t)] e"""^ dt = s A(t). (A-12)

ifit e

The frequency spectrum S(at) is convolved with its time apodization, A(t), then multiplied by a cisoid representing the desired epoch, a, and integrated from the beginning

of the sweep w(t) to its end. The output of this integration at the end of the sweep is the desired Fourier transform as can be seen from the figure above. A single complex

number is produced which corresponds to the moment of arrival selected by the frequency

a. If this frequency is zero (d.c), then the moment selected is t sections after the system

excitation by w(t)

.

The foregoing analysis presumes that the system has been optimized for the proper path

delay. If the delay adjustment is not optimum, then the measured response, both for

frequency domain and time domain, will be diminished from the optimum response. The

selectivity of a TDS is determined by the reduction in response as a function of offset

from optimum delay.

The selectivity of the frequency domain measurement yielding S(a)) is determined by

the frequency selectivity of the intermediate-frequency network. Since the frequency

of excitation is proportional to time, and since the distance traveled at constant

velocity is also proportional to time, it follows that distance may be equated to frequency.

With a sweep rate of aF/aT hertz per second, propagation velocity c and offset frequency

B hertz, the distance AX, traveled by the signal is.

aX

B • C ;af/at) (A-13)

If B is the electrical bandwidth of the selectivity network, then aX is a spaceequivalent bandwidth measuring the amount by which longer pathlength signals are suppressed

from an optimum adjustment for direct path. Besides determining the space-equivalent

selectivity, the sweep rate and electrical bandwidth perform a smoothing operation on the resultant spectrum S((jj). This smoothing is the apodization A(a)) developed above.

Because we are using information in both the time domain for selectivity and the frequency

domain for measurement, it is not surprising that there is an uncertainty relationship

governing the choice of bandwidth and sweep rate. The amount by which the frequency

spectrum is smoothed, B, and the amount of space, aX, from which signals are smoothed due

to velocity c is such that

aX-B ^ c. (A-14)

This relationship is not unique to TDS but derives quite generally from the physics of

the measurement.

93
The time-domain measurement is derived from the f':='l"^"^y.<'°"f "

' 'j?"'!,!'' trans'flation Accordih,|y f^^/^f-^l^i'^^.i^ir^^^ralSr^s' oftf^t ue^n°?h:rit

ZZ^^VT^J^r 1hir?I IraJTraJi^fr t on r^-L Le^p ,n Us.

?lle Fourier integral may be broken into three integrals as follows.

•F f n oo //•/• f,

•^.co •'-co •'fi f2

By definition, the integrand for the integration from to

J, and

'llXllsTorlltZ"io

Thus, the only active integral is t at Jj^^^fi^J^/?^ ^ ^^^'e Jo ^ th the transform of

rir^::nSTu^trpI? r:h?cS°?ri^n %o:

"^^^ f- f. and nil elsewhere.

This term ^hus becomes the time-domain selectivity and is of the form

^Esinc(X).

A

The equivocation of time and distance still holds and the offset distance at which the

first null^of the sine function occurs is still the uncertainty relation,

(AX)(Af) = c. (^-^6)

The ability of Time Delay Spectrometry to resolve muU^

figure A-1 . Time-domain resolution is of the form (sin aj/a me pt^a^

typically 1.5 mm for a water path and 1 MHz in spectrum width.

,„ the tre,uehC, doma,n the ener,,-.^ -f""

XlZ %lluZtZlV:X. For a constant signal velocity, the distance

resolution is given by

Be (A-17)

^ " TdF/dt)

^rsjs^/r- ot .0 «r;:r-^o;rana?^^^

velocity of 1,500 meters per second. This yields a distance resolution

94
1 ENERGY

TIME

DOMAIN / \ SHAPE OF CURVE

\ J^^ THE FORM:

SIN X

X

|<-C/AF

DISTANCE

SPECTRUM ANALYZER BANDWIDTH, Hz

VELOCITY OF SOUND IN METERS • SEC"

SWEEP RATE IN Hz • SEC"^

FREQUENCY SPECTRUM WIDTH IN Hz

A-1 . Theoretical system resolution.

B = C =

dF

dt

AF =

95

National Bureau of Standards Special Publication 453. Proceedings of Seminar on Ultrasonic

Tissue Characterization held at NBS, Gaithersburg, MD, May 28-30, 1975. (Issued Oct. 1976)

Paper 4.2: METHODS OF TISSUE IDENTIFICATION BY ULTRASONIC SPECTRA

A. Sokollu, E. W. Purnell , E. Holasek, and W. Jennings

Case Western Reserve University

Cleveland, Ohio 44106

and

A. Kaya

University of Akron

Akron, Ohio 44304

Ultrasonic spectral characterization of tissue is based

on the retrieval of latent frequency information not normally

detected in intensity-modulated B-scan displays. The results

of tissue studies and tissue-model studies are presented and

discussed. A method for color coding this frequency information

into a B-scan display for clinical use is described.

Key Words: Color-coded B-scan; Fourier transform; spectral

analysis; tissue structure; ultrasound.

1. Introduction

Recent technological developments have brought the display capabilities of B-scan

ultrasonography close to the theoretical boundaries delimited by the frequency range and

intensity level of ultrasonic pulses needed to safely penetrate to the required tissue

depth. In spite of our technological achievements, we remain dissatisfied with our accuracy

in interpreting the displayed pattern. There are a variety of reasons for this displeasure.

Some investigators are displeased with the lack of resolution, and others with the distorted

signal display.

Since the phosphors of cathode ray tubes are not capable of presenting echoes in

their true intensity (over a range of 80 dB), we resort to various electronic stratagems

to compress this range into the 25 dB capability of the phosphors. As a result of this

compression, there is signal degradation. Distorted signals affect the outcome of tissue

evaluation.

Until recent years, all abdominal scans were displayed on storage scopes without any

detailed intensity information. Only after the recent introduction of scan converters

and grey-scale storage tubes, have some physicians been able to see tissue in grey-scale.

Ophthalmologists, on the other hand, were fortunate enough to have had grey-scale display

for many years; the short distances examined made possible faster scan times which permitted the use of long-persistence CRT's with grey-scale capability.

During the last two decades of development in medical ultrasound, major efforts have

centered about the improvement of resolving power and patient comfort but no significant

breakthrough in the area of basic principles has occurred. We thus learned to recognize

pathology in tissue by the abnormal geometry of displayed images, and to conclude from,

a

certain shadow cast what the character of a tissue complex may be. Even with improvements

in grey-scale and the use of color-coded amplitude display, there remains considerable

uncertainty in interpreting disease states on the basis of ultrasound alone. These and

other shortcomings of B-scan methods make it imperative to explore other interactions of

sound with tissue as the basis for improving our reliability in diagnosis.

97
In B-mode scanning, ultrasonic signals are usually sent through the tissue and the

received echoes are displayed according to their amplitudes. We totally disregard the

frequency components actually reflected from various types of tissue, although we know

that all tissues do not reflect all frequencies of sound with equal intensity.

Motivated by these thoughts, we decided to approach the problem of tissue identification from a totally different point of view. We attempted to apply the method of spectral

analysis, as used in optics, to ultrasonic diagnosis. The fundamental idea of ultrasonic

spectral analysis of tissue is based on the retrieval of the latent frequency information

hidden in the shape of echo pulses which is normally not extracted in the processing of

intensity-modulated B-scan displays. Feasibility studies were carried out in a series of

experiments by measuring the spectral attenuation of various tissue samples in the throughtransmission mode [l,2].i

The block diagram of the experimental arrangement is shown in figure 1. Two trans- ducers of similar frequency characteristics were placed so as to face each other in axial

alignment. Tissues samples were placed between the two transducers. One of the trans- ducers was pulsed to generate wide band sound while the other acted as a receiver. The

receiving transducer was connected to a spectrum analyzer (Tektronix, Model 7L12) and the

signal gated through a double-balanced mixer to permit only the original pulse to enter

the spectrum analyzer, screening out all reverberation echoes that might have been created

in the path between the transducers. Several matched transducer pairs were tried to achieve the broadest frequency. The transducers were separated by about 75 mm in a water

tank designed for this purpose with all the necessary alignment screws.

TRANSMITTING

PULSER

TRANSDUCER K--^

TEST SAMPLE

DOUBLE BALANCED

MIXER

SPECTRUM ANALYZER

GATE DATA

ACQUIS.

PAPER TAPE PUNCH

DELAY GENERATOR

PROGRAMMABLE

X-Y PLOTTER CALCULATOR

Figure 1. Through-transmission spectrum analysis instrumentation.

To aid in our interpretation of spectral data, we employed a Hewlett Packard 9820

Programmable Calculator with an X-Y plotter in our laboratory. We designed a data

acquisition system to accommodate a large volume of data necessary for statistically

Figures in brackets inaicate the literature references at the end of this paper.

98
significant spectral-analysis studies. The data acquisition system consists of a highspeed (6 microsecond) analog-to-digital converter which has a resolution of one part

in 4096 (12 binary bits). Peak-detected analog data is converted into digital information

at the rate of 2000 samples per second. Our data acquisition system has been designed

with the capacity to store a maximum of 960 words (12 bits each). The data acquisition

memory transfers stored data either to the programmable calculator or to the paper tape

punch. The data record, in standard ASCII code, is then available for use with a variety

of computers.

2. Preliminary Results of Through-Transmission Studies

We first established the energy spectrum of the system (figure 1) without any

tissue sample. Then we introduced the tissue and determined the spectral distribution.

The ratio in dB between the two spectra was the attenuation spectrum of the sample relative

to water.

We used natural sponges as tissue models for ease of experimentation [3]. Sponges

do not degenerate with time and thus lend themselves to repeatable evaluations. We first discovered that the sponge attenuation spectra were independent of the shape of

the incident pulse. Two pulses of radically different spectral content were transmitted

through the same sponge (modifications in the frequency content of the pulse were made

by changing the energy and damping constants of the excitation pulses). The same attenuation curve was obtained for both.

Secondly, we found the essential shape and nature of the spectral attenuation curve

were not significantly altered by repositioning the sponge or by testing different pieces

of the same sponge. A thicker piece showed greater overall attenuation but the general

shape of the attenuation curve remained unchanged. This observation was of crucial value,

since it supports the thesis that tissue types may be identified according to their

spectral attenuation characteristics.

The spectral curves of two different sponges are shown in figure 2. Although the curves appear similar in overall shape, the difference curve, figure 3, reveals a significant difference in attenuation.

Deformation of a sponge by compression was tried next as a means of demonstrating

that structural changes in a material induce spectral changes in the material. Figure 4 shows the attenuation spectra of a sponge before and after compression. The difference

curve, figure 5, shows the expected changes in the spectrum due to compression.

99
.2

0 1 2 3 4 5 6 7 FREQUENCY (MHz)

Figure 3. Curve of attenuation difference between sponges A-2 and B-2.

<

a

z 4 w

Eh

Eh<

2

U! ICOMPRE 3SED

C OMPRES.;ed 01234S47B

FREQUENCY (MHz)

Figure 4. Attenuation versus frequency for uncompressed and compressed sponge.

1.2

FREQUENCY (MHz)

Figure 5. Compression difference curve taken from curves of figure 4.

100
3. Computer Studies

Our first analysis consisted of taking a polynomial regression of various degrees

on our spectral attenuation curves. We were looking for a signature of tissue types in terms of the coefficients of the various powers of frequencies present in the spectral

curve.

It was assumed that the linear term corresponds to the non-structural absorption,

as classically measured by homogenizing the tissue [4], and that deviations from this

dependence represents structural variations in the tissue. This analysis was applied to several sponge types, and each had a very different set of coefficients.

From the literature [5], we found spectral absorption curves for liver homogenate.

We compared these values to our own results for spectral attenuation for a particular

sponge. This comparison, along with the computed linear approximation to our own data,

is shown in figure 6. The computed difference between the slopes of these two straight

lines is only 0.2%. The deviation from the linear approximation to the sponge attenuation

curve represent the heterogeneities of the sponge due to its coarse texture.

, •

LI' <« LINlEAR APPR OX.

H«SPO^IGE A -2

9

87

24

<13

3 4

FREQUENCY (MHz)

Figure 6. Attenuation versus frequency for homogeneous liver and sponge A-2,

and linear approximation to sponge A-2.

4. Determination of Energy Attenuation Spectra of Tissue by Fourier Transform

In parallel to the spectrum analyzer studies, a Fourier-transform computer study

has been performed to determine attenuation spectra from time-domain signals. The same

sponge samples were used for both studies and the results were compared. Only two sponge samples from several tested are shown. Figure 7 indicates the time-domain

pulse shapes observed from a typical test. Figure 7a is the time-domain display of a signal in a through-transmission system with water as the sonic medium. Figure 7b is the pulse shape after passage through the sponge sample A-2. Figure 7c shows the change

in the shape and pulse amplitude after passage through a different sponge sample, D-2.

Spectral analysis of these time-domain signals were obtained by means of Fouriertransformation, utilizing an IBM-370 computer.

The frequency response of tissue A(juj) can be determined from the Fourier

transform of the signal through the tissue in water divided by the Fourier transform

of the signal through water.

P

101
A 50 nS

\

20 OmV

B 50 nS

1^4- 1 l"

50 mV

C 50 nS

11 1 4-H4- r

50 mV

Figure 7. Time-domain pulse shapes received for wide band transmission:

(a) through water medium, only; (b) through water and A-2; and (c) through

water and D-2.

. ^. n^- ^ - ( signal through tissue)

Freguency Response of Tissue - AU^j - (signal through water] ^

Of course, A(ja.) carries both amplitude and phase information. The energy attenuation

spectrum of the tissue (energy lost in tissue for each frequency) can be calculated

from:

1A(3'

Energy Loss of Tissue = —

(2)

where Z

= 50 was assumed as the equivalent impedance The energy f

tenuation of sponge A

is given in figure 8. Similar results were obtained for sponge D-2, as shown in figure y

102
-35 I 1 1 1 ! 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 2 4 6 8 10 12 14 16 18 20

FREQUENCY (MHz)

Figure 8. Energy absorption of sponge A-2, obtained by computer, compared with

absorption obtained by spectrum analyzer.

-35 I 1 1 1 ! 1 1 1 1 1 1 1—I 1 1 1

\ J—I 1 1 0 2 4 6 8 10 12 14 16 18 20

FREQUENCY (MHz)

Figure 9. Energy absorption of sponge D-2, obtained by computer, compared with

absorption obtained by spectrum analyzer.

103
The analytical results obtained by means of the spectrum analyzer approach agreed

with the Fourier-transform calculations within the frequency range of the spectrum

analyzer, 1-16 MHz, as shown in the figures. However, the Fourier-transform results were obtained for sponges A-2 and D-2 over a larger frequency range, 0.1-40 MHz, as shown

in figures 10 and 11, respectively.

-35 I 1

1

I I I I II 1 i—II I I I 1 1 ^ ^—'

' ' ' ' 1.0 10 100

FREQUENCY (MHz)

Figure 10. Energy absorption plotted by computer for sponge A-2.

1.0 10 100

FREQUENCY (MHz)

Figure 11. Energy absorption plotted by computer for sponge D-2.

104
The capability of the Fourier- transform approach in determining phase information

in addition to the energy spectrum will be useful in understanding energy transmission

in tissue and hence will lead to better recognition of tissue structures.

5. Frequency-Selective Color-Coding of Echoes

Echo analysis presented new problems for spectral identification. The most notable

is that of gating specific parts of the echo complex for analysis in order to determine

spatial information. The gate shape and duration has been found to influence greatly

the echo spectra. We are currently working on a solution to this problem. In the meantime, we have resorted to a more pragmatic approach by separating the echo response into

three frequency sub-bands, using analog filtering. Each band was assigned a certain

color of light, thus providing the basis for a frequency color-coded B-mode display.

We call this Spectra-Color Ultrasonography (S.C.U.), to distinguish it from methods

employing amplitude-color coding.

The instrumentation for S.C.U. is composed of a high resolution, digitally-controlled,

sector scanner designed for ophthalmic application. A full sector scan of 22.5 degrees

is performed in 0.5 seconds. Each sector contains 400 lines of intensity modulated B- scan. The transducer is mounted in a mechanical stage and coupled to a water bath which

permits immersion of various experimental target and physical models. For clinical use,

it is coupled to a special pair of goggles which are worn by patients for scans of the

eye and orbit.

A block diagram of the instrumentation is shown in figure 12. The transmitter sends

a high-energy pulse which excites the ultrasonic transducer. The transducer is wideFigure 12. Block diagram of instrumentation for Spectra-Color Ultrasonography.

105
band, with a center frequency of 9 MHz and a fractional bandwidth of 66%, covering the

frequency range from 6 MHz to 12 MHz. The ultrasound is focused by an acoustic lens with

a focal length of 77 mm. Axial resolution is 0.3 mm in soft tissue. Lateral resolution

varies from 0.4 mm to 1.0 mm, depending on the signal strength. Eighty decibels of

amplification is provided by two amplifiers of 35 MHz bandwidth. The range of amplification is controlled by an attenuator. The intensity-modulated display has a five

inch diameter and a spot size of approximately 0.1 mm. The S.C.U. is taken by a camera mounted in front of the display. A voltage-tuned filter receives three successive

DC voltages and, operating on the varactor principle, generates the component frequency

bands. Figure 13 shows the three component bands, designated low, middle and high,

having center frequencies of 7 MHz, 9 MHz, and 11 MHz, with 2 MHz bandwidth. These

frequencies are arbitrarily assigned the three primary colors of light, red, green, and

blue, respectively, by introducing light filters between the video display and the eamera (fig. 12). The filters are mounted in a light filter wheel which is rotated by

a stepping motor to sequentially interpose each of the filters in coordination with each

of three successive sector scans. The filters are Kodak Wratten Gelatin, No. 25 (red),

No. 57 (green), and No. 47 (blue).

9MHi

7MHz IIMHz

6 MHz

The color control device (fig. 12) opens the camera shutter, sequentially applies

the DC voltage corresponding to each frequency band, positions the light filter wheel to interpose the respective light filter for three successive sector scans, and controls

a programmahle amplifier for normalizing the signals of the three bands. A single

frame of film records the low-frequency response through the red filter, the middlefrequency response through the green filter, and the high-frequency response through

the blue filter. Where the primary colors are equally represented, the result is pure white. Where the proportion of the three primary colors is varied, the SpectraColor Ultrasonogram will record that hue of the light spectrum which is specific to that

proportion.

The S.C.U. is recorded on Kodak high-speed Ektachrome, ASA 125 tungsten type,

exposed over three sector scan sweeps at a lens opening of f2.8, and processed for a film speed of ASA 300. This emulsion type provided the proper color balance.

106
Our preliminary investigations indicate that the various color patterns observed

j with S.C.U. depend on a number of factors. Some of these include the signal strength,

jl the structure of tissue, the resolution of the system, and the shadowing of one tissue

I by another.

The clinical system was calibrated by adjustments of the gain and attenuator

controls so that echoes of the combined three frequency ranges from the major re- flecting structures in the normal eye, produced a near-white spectra color ultrasonogram.

A number of patients with diseased eyes were studied by S.C.U. to correlate the

spectral reflectivity of these abnormal eyes with a specific pathological diagnosis,

j Spectra-Color Ultrasonograms of diseased eyes have been characterized by a "breakdown"

j in the white display, and yield patterns with a variety of hues.

I The choroidal melanomas have consistently been represented by spectral color

combinations of the mid- and lower- frequency ranges. Separated retinal tissue has

I consistently been represented by the predominance of the lower frequency range. However,

! as yet, there is insufficient experience with this method to compare abnormal tissue of

different cell types with similar size and location within the eye.

At this stage of the investigation, the many parameters which affect the spectral

display are not completely understood. However, the results of this investigation have

I shown this method workable and easily adaptable to clinical application, and should

I further our ability to more precisely identify tissue by diagnostic ultrasound.

References

[1] Sokollu, A., Purnell, E. W. , Holasek, E. , and Jennings, W. D. , Tissue identification

by ultrasonic spectra, in Abstracts of the Annual Meeting of Am. Inst, of Ultrasonics

in Medicine, p. 10 (Ann Arbor, Michigan, 1973).

j [2] Holasek, E., Jennings, W. D., Sokollu, A., Purnell, E. W., Recognition of tissue

patterns by ultrasonic spectroscopy, in Proceedings of 1973 Ultrasonics Symposium,

p. 73 (IEEE Cat. No. 73 CHO 807-8 SU, 1973).

[3] Sokollu, A. and Holasek, E., Model study of propagation of ultrasonic waves in ocular

media, in Opthalmic Ultrasound, Gitter, Keely, Sarin, and Meyer, eds., p. 88

(The C. V. Mosby Company, 1964).

[4] Dunn, F. , Edmonds, P. D., and Fry, W. J., Absorption and dispersion of ultrasound

in biological media, in Biological Engineering, Herman P. Schwan, ed. , p. 205

(McGraw Hill Book Company, 1969).

[5] Pauly, H. and Schwan, H. P., Mechanism of absorption of ultrasound in liver tissue,

J. Acoust. Soc. Am. 50, 692 (1971).

I

I

107

National Bureau of Standards Special Publication 453. Proceedings of Seminar on Ultrasonic

Tissue Characterization held at NBS, Gaithersburg, MD, May 28-30, 1975. (Issued Oct. 1976)

Paper 4.3: ALGEBRAIC RECONSTRUCTION OF SPATIAL DISTRIBUTIONS OF REFRACTIVE INDEX AND ATTENUATION IN TISSUES FROM TIME-OF-FLIGHT AND AMPLITUDE PROFILES

J. F. Greenleaf and S. A. Johnson

Biophysical Sciences Unit

Mayo Medical School

Rochester, Minnesota 55901

Two-dimensional distributions of refractive index and attenuation

were measured in transverse sections through intact isolated organs,

using reconstruction techniques. Profiles of time-of-fl ight (TOF)

and/or amplitude of 10 MHz pulses through the specimen were obtained

by rectilinearly scanning two opposing transducers along either side

of the specimen in the plane of interest. The received pulses were digitized at a rate of one 8-bit sample per 10 ns for 512 samples,

and were analyzed with a computer algorithm which calculated the

TOF of the pulse to within ± 10 ns and/or its amplitude. Typically,

256 measurements of TOF and/or amplitude were made in each profile

scan for each of 37 angles of view separated by 5°. TOF's through

tissue, normalized by TOF through water, were used to calculate

velocity and, hence, refractive index within the specimen, using

an algebraic reconstruction technique (ART). A similar approach

was taken to calculate attenuation distributions. Images obtained

represented acoustic velocities and/or attenuation in individual

cross sections within the tissue specimen with a resolution of 64

by 64 elements (< 2 mm^). The disadvantage of TOF and attenuation

reconstruction is that transmission scanning is required. Advantages

over B- and C-scan imaging are: (1) dynamic changes in receiver gain

are not required; (2) attenuation occurs on only one traversal through

tissue; and (3) the absolute values of important acoustic parameters

(velocity and attenuation) are determined which may have significant

diagnostic value.

Key Words: Acoustic attenuation; acoustic velocity; breast tumor; computerized tomography; heart; reconstruction; refractive index;

synthetic focus; tissues; ultrasound.

1. Introduction

It has been known for some time that three-dimensional functions can be determined from

their two-dimensional projections, i.e., line integrals along paths through the threedimensional function [1].^ Obtaining a solution for three-dimensional distributions of

j functions from their two-dimensional projections is popularly called "reconstruction" or computer-assisted tomography (CAT). The recent uses of CAT in medical radiology have

i had a tremendous impact on the field of neuroradiology [2]. For the first time in the

history of roentgenography, the radiologist can obtain quantitative measures of the

spatial distribution of roentgen absorption coefficients within the body. Medicallyvaluable applications of reconstruction methods have been developed in many areas of

medical research using forms of energy such as x-radiation [3,4], electrons [5], and

more recently, ultrasound [6,7].

Figures in brackets indicate the literature references at the end of this paper.

109
Historically, ultrasound has been used to obtain images such as B-scans, which

correspond to geometric distributions of the gradient of acoustic impedance, and trans- mission C-scans, which produce images corresponding to acoustic attenuation [8]. Images

representing quantitative distributions of basic mechanical tissue properties or values

of acoustic parameters such as those recently obtained in this laboratory [7], may be

intrinsically more valuable than qualitative images representing only tissue interfaces

and geometries. Since fundamental mechanical tissue parameters such as adiabatic compressibility and density can be calculated from measured values of other acoustic parameters [9],

quantitative images representing two-dimensional distributions of such fundamental properties

may be possible with the reconstruction techniques recently developed in this laboratory.

The purpose of this paper is to describe initial results of applying reconstruction

techniques for obtaining quantitative images representing acoustic refractive indices and

attenuation coefficients within isolated tissues and phantoms. These images are calculated

from profiles of propagation delay time and acoustic intensity obtained by transmission

scanning with a single pair of transducers, one on each side of the region of interest.

The theory for mathematically and quantitatively reconstructing two-dimensional spatial

distributions of acoustic parameters such as attenuation, speed of sound, and other functions

which can be related through line integrals to their shadow images, will be described. In figure 1, an acoustic ray traverses a space divided into n^ finite elements or picture cells

(pixels). We assume that the local value of some acoustic parameter in pixel i is constant

Figure 1. Geometry of ultrasound transmission for algebraic reconstruction. Grid

is fixed to coordinates of object. Speed of sound, Vi , is assumed to be constant

and isotropic within each pixel. Lij can be varied according to curvature of

ray path, which need not be straight. The equation represents propagation delay

of pulse through reconstruction region (grid). Number of measurements {i.e.,

equations) required for solution of set of linear equations is obtained by

rectil inearly scanning object at many angles of view.

within the pixel and is denoted by F-j . Let Lij be the length of the path of ray j as

'

it traverses pixel i. Further, let us suppose that the cumulative effectof the interaction f of the acoustic energy with the material along ray j can be measured as an integral or sum

and has a value Gn. Then the following relationship holds: '

Gj = ^ L.jF. for each ray j = 1,2,..., M. (1)

i = l We note that each ray j has an associated value Gj and that given sufficient independence

and a sufficient number of equations M, the set of simultaneous equations representing

these measurements can be solved for the values of Fi since the Lij are known from geometric

110
considerations. Although eq. (1) appears to be merely a set of linear simultaneous equations,

the fact that n is 64 or greater precludes direct solutions to the set of equations and

requires special treatment of the problem. However, many techniques for solving this set

of equations have been devised [10]. In general, the solutions shown in this paper will be

for conditions in which n is 64 and the set of equations have been solved using an iterative

technique (algebraic reconstruction technique, ART) [3,4].

The specific equations for applying this technique to solutions of attenuation and

index of refraction are given below and are derived relative to the geometry shown in figure 1

.

Attenuation: assume attenuation can be described by the relationship

I

.

-j^ = exp (2)

i-1 where Iq is the incident intensity, a-j is the acoustic attenuation in pixel i and Lij is the length of ray j in pixel i. Then the acoustic "density" D can be obtained from the

following set of linear equations with some suitable reconstruction algorithm,

,2

D.

J In j = 1,2, (3) i=l Index of Refraction: assume the propagation time for an acoustic ray j traversing a length Lij of pixel i is x-j. Then the total time of propagation of the ray through the grid

of figure 1 is

(4) i=l i=l where ni is the acoustic index of refraction defined as Vp/V-ti , the ratio of acoustic

velocity in the surrounding fluid to the velocity in tissue for pixel i.

In practice, the difference between the arrival time of the pulse through a fluidfilled gap (xp = L/Vp, figure 1) and that of the pulse through the tissue (eq. (4)) is the actual values measured by the equipment giving

1

1

(5)

^ i = l for each ray j = 1,2,...,M, where

'ti ^ti

The procedure of obtaining solutions for ai and nti ^^om eqs. (3) and (4), respectively,

requires one to obtain at least as many measurements (i.e.^ independent equations) as there

are unknowns. The way in which this is done is to make measurements of propagation time

or intensity for as many rays through the tissue as possible, given the available geometry.

Typically, this is accomplished by rectil inearly scanning the tissue at each of several

angles of r*otation (about an axis perpendicular to the scan plane) of the tissue relative

to the scanning transducers.

2. Data Acquisition

Data for reconstructing acoustic properties within phantoms and excised organs were

obtained by transmitting acoustic pulses through the tissue to be studied utilizing transmit

and receive transducers arranged in the geometry shown in figure 2. The use of a focused lens

111
on the transmitter maximizes the energy intensity, while minimizing the area being

illuminated by ultrasound, thus minimizing the probability of measuring pulses arriving

at the receiver through multiple pathways. The use of a focused lens on the receiving

assembly insures that the acoustic energy passes through a relatively small window in space before being detected by the receiver transducer. The normalized error response of

this particular geometry as a function of the distance of the transmitter-receiver axis

(with fixed gap length) from the center of a cylinder having an index of refraction of 0.94,

is also shown in figure 2. Note that the error is smallest for the geometry in which the

receiver is next to the cylinder and the transmitter is furthest away from the radius of

the cylinder (Bx = 4 cm). These calculations did not include the effects of total reflection

at the critical angle.

D = I4cm

0 0.5 I DISTANCE from CENTER, h/r

Figure 2. Lens-transducer system used to obtain ultrasound reconstruction data.

Cylindrical model is used for analysis of acoustic refraction. Central ray of

beam is refracted by amount aH depending on distance AH/r from center of

cylinder and depending on distance from transmitter to cylinder By. is the

focal length in water. Gap length D was fixed for error analysis.

The transmitter- receiver assembly was scanned on either side of the region being studied

using a specially-modified computer-controlled Magna IV scintiscanner [7]. The sample was rotated utilizing a computer-controlled stepper motor (Fig. 3) which was rotated in integer ! multiples of 1.8°. Signals from the receiver were amplified with a Panametrics PR 50 50

amplifier and subsequently input into a Biomation Model 8100 transient recorder (BTR) and

digitized at rates of up to one 8 bit sample per 10 nanoseconds for up to 1,024 consecutive

samples. Specific details of the data acquisition system are described elsewhere [7].

Figure 4 illustrates representative examples of digitized signals detected by the

receiver and digitized by the BTR and demonstrates the change in propagation time of acoustici

pulses through various materials. The arrival times through this particular tissue (canine i heart) vary over a range of about 2.5 microseconds, indicating that a digitizing resolution i of 10 nanoseconds gives an accuracy of one part in 200 over the signal range. However, since|

the total propagation time was approximately 100 microseconds, the absolute accuracy of

the measurement was about one part in 10"^.

An example of the entire set ofdata obtained during one scan across the tissue is shown in figure 5. A computer algorithm was utilized which scanned each horizontal line

depicted in figure 5 and calculated the point at which the signal changed in amplitude

more negative than two standard deviations of the background noise (defined as the noise

in the first 12 samples representing the baseline). The algorithm then searched backwards

down the first pulse to that point representing the zero crossover (baseline average) using
COMPUTER

CDC 3500

Trigger

Strobe BUFFER

2,048 WORD

Busy

-DELAY- ADC

SCAN

DRIVE

Figure 3. Schematic of computer-controlled data acquisition system which obtains

digitized ultrasonic pulses from transmission scans to be used for reconstruction.

Pulser and A/D converter are triggered by computer at 256 equally-spaced points

along the scan length of about 12 cm. Received signal is digitized at rates of up to 100 samples-per-microsecond. After digitization of pulses received

along one rectilinear scan, sample is rotated by stepper motor and the process

is repeated through 180°.

(Canine Heart, 22^0, 10 nsec /sample)

Saline

O 1.28 2.55 /isec

Figure 4. Digitized ultrasound pulses after transmission through saline and two different path lengths of tissue. Received signal is digitized into 256 8-bit

samples separated by 10 nanoseconds. Arrival time, determined by computer

algorithm, is defined as earliest negative-going portion of signal to emerge from

noise. Arrival time through tissues such as cardiac muscle are usually earlier

than for saline-filled gap. 113
(Canine Heart, 22^ C, 10 nsec / sample )

Figure 5. Digitized ultrasonic pulses: arrival time (left-to-right) versus position along scan traversal (top- to-bottom) . Intensity of image is proportional to received signal intensity (black < 0.0, white > 0.0 volts).

Arrival time through saline (top several lines) is relatively stable and later

than arrival times through tissue. Brightened line indicates waveform depicted

in A-scan format in bottom panel of figure 4.

the nearest sample time as the arrival time. In certain experiments, the gain of the

amplifiers was set so as not to clip the signal, in which case the computer program also

calculated the amplitude of the peak of the first negative-going portion of the pulse and

utilized the logarithm of this value in calculating profiles representing the acoustic

attenuation of the arriving ultrasonic pulse. Computer analysis of the data depicted in figure 5 results in a set of profiles for the propagation delays through the tissue and,

depending on the experiment, another set of profiles representing the amplitudes of the

arriving ultrasound pulses to be utilized for subsequent reconstruction of two-dimensional

distributions of acoustic refractive indices and/or acoustic attenuation coefficients,

respectively.

An example of "time-of-fl ight" profiles obtained by computer analysis of the data

shown in figure 5 is represented in figure 6. In general, these profiles are adjusted so that their value for the time-of-fl ight or intensity through the immersing liquid is zero giving a background in the subsequent reconstruction images which depicts the representative

parameter in the immersing fluid as black. In general, 36 to 60 profiles, each containing

about 256 time-of-fl i ght or intensity values, were obtained representing time-of-fl ight

or intensity profiles for the multiple views around the object through a range of

180°.

255

Relative

Pulse Arrival

Time / 10 nsec

0 256

Coordinates of Pulse Along Scan

Figure 6. Computer-generated profile of ultrasound propagation delay through salineimmersed, saline-filled canine heart. Computer algorithm calculated arrival times

from digitized pulses represented in figure 5. Dynamic range of arrival times is about 2.5 microseconds.

114
3. Results

The ability to quantitatively determine the value of acoustic indices of refraction

was tested using a phantom consisting of rubber finger cots filled with different concentrations of saline. Concentrations of saline ranging from 1 to 8 gm of sodium chloride per

100 ml of distilled water were utilized. Thirty-six angles of view separated by 5.4 degrees

were obtained with the scanning system described previously, resulting in measurements of

the propagation delay time at 256 points along each prof"'le. The resulting reconstruction

is shown in figure 7. Although it is not clear that the various regions of saline have a

Figure 7. Reconstruction of acoustic index of refraction in saline-filled phantom.

Five finger cots were filled with saline concentrations of 1, 2, 4, 6, and 8 gm

of sodium chloride per 100 ml distilled water. Phantom was scanned in manner

described previously. Speed of sound is proportional to salinity, the highest

speed of sound in brightest region of image is 0.64% greater than that of

surrounding water.

direct relationship to acoustic velocity, it seems evident that the size of the regions

imaged varies with the acoustic velocity. This is apparently the net result of the particular

parameters chosen for display and photographic reproduction acting in combination with the

refractive properties of the transducer-lens system which was not designed to obtain optimal

spatial resolution for this particular test of velocity resolution. The relationship

between the averaged reconstructed velocities (five values from the 64 x 64 array of

reconstructed velocities were averaged from each finger cot image) and the concentration of

sodium chloride is shown in figure 8. The acoustic velocity in water is proportional to sodium chloride concentration in this region of concentrations [11] and, therefore, the

plot should be a straight line. It is clear that the errors encountered in this technique

are relatively small considering that the change in acoustic velocity was 0.16% between

the 2 g/100 ml saline solution and the surrounding water. The high accuracy of the results

of this test are not too surprising considering one can measure arrival times of acoustic

pulses to within one part in several thousand. Whether this accuracy can be obtained

in vivo is yet to be proven.

To test the reconstruction technique on tissue models, we first chose to reconstruct

the regional distributions of acoustic index of refraction within an isolated canine heart.

The isolated heart was immersed in water, filled with water and recti 1 inearly scanned for

each view as it was rotated in five degree increments about its vertical axis through a range of 180°. The left panel on figure 9 represents a reconstruction of the refractive

indices through a transverse plane at which the tissue was subsequently sliced after

freezing. A photograph of the surface of the sliced heart is shown in the right panel.

One can see the ventricular papillary muscles, the endocardial surface of the right

ventricle, and the epicardial surface. That the variations in index of refraction within

the interior of the myocardial wall are true variations in velocity is suspected but unproven.

115
( 20°C

)

to O

16

1.0080

/ O

i 8

/O

- \.0040

rn\

to

t)rnmo

I

J I I L. 1.0000

Grams NaCI / 100 ml HgO

* Millero end Kubinski, J Acoust Soc Am 57 ( 2 ): 3 1 2 - 319 , 1975

Figure 8. Reconstruction of speed of sound within rubber finger cot phantom

containing different saline concentrations. Five points in the center of each

finger cot image shown in figure 7 were averaged to obtain values shown by

circles in this graph. Filled circles indicate acoustic velocities of selected

saline concentrations obtained from literature. Accuracy of results is due to ability to measure pulse arrival time to 1 part in lO'*, allowing extremely

accurate measurements of refractive index (right ordinate).

Figure 9. Reconstructions of refractive index within canine heart (left) compared

to photograph of section through corresponding level (right). Reconstruction of ' 64 X 64 array of pixels was linearly interpolated up to 128 x 128 pixels.

Papillary, epi cardial and endocardial surfaces are represented with good

fidelity; however, detail shown here of acoustic velocity within the myocardial ' tissue is not yet substantiated. j!

I' Figure 10 illustrates reconstructions of acoustic attenuation (left panel) and acoustic

index of refraction (right panel) within a coronal section through a human female breast i obtained from subcutaneous mastectomy post mortem. The distribution of reconstructed , refractive indices correlated in a qualitative way with the distribution of fat (dark areas) d and connective tissue (light areas) in the breast as judged from the gross specimen. The

116
position of the nipple and associated ducts can be seen as the dark hole in the upper left

central region of both images. The ring-like region around each reconstruction probably

occurred as a result of critical -angle reflection causing inconsistencies in the reconstruction

equations.

Figure 10. Reconstruction of refractive index (right) and acoustic attenuation

coefficients (left) within normal excised human breast tissue obtained from

post mortem subcutaneous mastectomy in a 21 -year-old woman. Scan data were obtained in a manner similar to that described in figure 1. However, both

arrival time and amplitude profiles were calculated from the digitized pulses

to obtain velocity and attenuation images, respectively. Although these

images are uncorrected for refraction errors, the detail seems promising. The

ducts associated with the nipple can be seen in the upper left central region of

each image. The dissimilarity of these two images indicate that these two acoustic parameters are relatively independent.

Although the quantitative details of these reconstructions cannot yet be correlated

with individual breast tissues, it is clear that the two types of reconstruction images

represent nearly independent acoustic parameters. It is the independence of acoustic

parameters such as refractive index and attenuation which may allow accurate differential

characterization of tissue types in healthy and diseased organs, particularly the breast.

4. Discussion

Computer-assisted tomography (CAT) has been applied to the measurement of the

two-dimensional spatial distribution of two acoustic parameters, attenuation and refractive

index. Arrival times of acoustic pulses propagated by transmission through a tissue

specimen at many angles of view have been used to reconstruct the refractive indices within

selected excised tissue samples. The intensities of acoustic pulses have been used as an indication of attenuation and have been utilized for reconstruction of the two-dimensional

distribution of attenuation coefficients within breast tissues.

The use of the arrival time of the pulse as an indication of propagation delay tends

to minimize the undesirable effects of refraction since in a homogeneous material such as tissue, whose index of refraction varies less than a few percent, the earliest arrival time

will in general represent the shortest and thus straightest path through the tissue. The

use of arrival time is particularly sensitive to detection of small inclusions or regions

in which the speed of sound is higher than its surroundings since in this case the straight

ray through the inclusion is the first to arrive at the detector. The fidelity of the

reconstruction of distributions of index of refraction was qualitatively shown to be good in

tissue and the accuracy of calculated refractive indices within a phantom was shown to be accurate to within a few parts in a thousand. Reconstructions of the two-dimensional

distributions of attenuation coefficient could only be qualitatively described since the

assumption was made that attenuation is an exponential function, independent of the

117
direction of propagation. This assumption is probably true for situations where the major

portion of attenuation is caused by absorption and isotropic scattering, while reflection and j anisotropic scatter are minimal, I

The effect of refraction on the assumption that the paths of acoustic energy through i the tissue are straight lines seemed to be minimal, especially for the relatively coarse reconstruction resolution of 64 x 64 pixels per image. For reconstructions of higher ' spatial resolution, it will become imperative that the effect of refraction on the ray i paths be taken into account. The use of the algebraic reconstruction technique (ART) > allows one to use curved ray paths in reconstruction. This may allow one to use ray

j tracing [12] in order to solve for the actual paths of the rays through the tissue and thus I obtain higher-fidelity reconstructions.

j Accurate reconstructions of the refractive index may lead to a method of correcting } for refraction in compound B-scans and allow for the subsequent calculation of acoustic ! impedance. It is clear that all acoustic images are distorted to some degree due to I refraction; therefore, techniques of obtaining accurate distributions of refractive index

could be utilized for the reduction of distortion in almost all types of acoustic images.

( A technique termed "synthetic-focus imaging," developed in our laboratory [13], has the 1 property of retaining maximum information as to the nature of reflection and scattering over ' wide angles because it retains intensity and phase information by digitization of the total

[ signal received by an array of transducers. Since "synthetic focusing" is accomplished by

computer algorithms, aberrations due to refraction can be corrected for using refractive- ; index distributions determined by the image reconstruction technique. (

I- Although arrival times and intensities of the acoustic pulses were calculated using

computer algorithms, analog techniques could be used after optimal methods of finding these

^ parameters have been determined by computer simulation. Complex algorithms for calculation j of arrival times from digitized pulses could also be implemented on special -purpose digital j' devices such as microprocessors in order to decrease the calculation time.

i The use of high-speed, high-fidelity signal processing methods [14] in combination with

techniques of computer-assisted tomography may allow quantitative imaging of basic acoustic ! properties within the intact human. The quantitative determination of two-dimensional spatial

j distributions of parameters relating to the basic mechanical properties of tissues may provide ! significant increases in the ability to distinguish and characterize the various tissues of

| the body in both healthy and diseased states.

[

I

I The authors wish to thank Dr. Richard A. Robb for assistance in programming the BTR

| and Mrs. Jean Frank and coworkers for their secretarial and graphic assistance. Mr. William | Samayoa and Mr. Francis Duck assisted in algorithm programming and data collection.

Dr. Gary Glover of General Electric Corporation assisted in the design of the saline

phantom. Dr. Titus Evans has provided valuable administrative and technical assistance.

This research was supported by grants NOl-HT-4-2904, HL04664, and RR-7 and HL00060 I from the National Institutes of Health, United States Public Health Service: AF 44620-71- I C-0069 from the United States Air Force. i

References

| [1] Bracewell, R. N., Strip integration in radio astronomy, Austral. J. Phys. 9_, 198

'

(1956). I

I [2] Baker, H. L., Jr., Campbell, J. K. , and Houser, 0. W. , Computer-assisted tomography

^ of the head: an early evaluation, Mayo Clinio Proceedings, 49^, 17 (1974). j'

[3] Gordon, R. and Herman, G. T., Three-dimensional reconstruction from projections:- a

j review of algorithms. International Reviews of Cytology, 38, 111 (1974). |

[4] Johnson, S. A., Robb, R. A. and Greenleaf, J. F., Dynamic three-dimensional reconstructioi

of beating heart and lungs from multiplanar roentgen-television images. Mayo Clinic l Proceedings, 49, 958 (1974). , 118
[5] Klug, A. and Crowther, R. A., Three-dimensional image reconstruction from the viewpoint

of information theory, Nature (London), 238 , 435 (1972).

[6] 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, Vol. 5, P. S. Green,

ed., p. 591 (Plenum Press, New York, 1974).

[7] Greenleaf, J. F., Johnson, S. A,, Samayoa, W. F., and Duck, F. A., Algebraic recon- struction of spatial distributions of acoustic velocities in tissue from their time of

flight profiles, in Acoustical Holography, Vol. 6, N. Booth, ed., p. 71 (Plenum

Press, New York, 1975).

[8] Green, P. S., Schaefer, L. F., Jones, E. D, and Suarez, J. R., A new high performance

ultrasonic camera system, in Acoustical Holography, Vol. 5, P. S. Green, ed., p. 493

(Plenum Press, New York, 1974).

[9] Kinsler, L. E. and Frey, A. R., Fundamentals of Acoustics, (John Wiley and Sons, Inc.,

New York, 1950).

[10] Gordon, R. and Herman, G. T., Reconstruction of pictures from their projections.

Communications of the ACM, 14^, 759 (1971 ).

[11] Millero, F. J. and Kubinski, T., Speed sound in sea water as a function of temperature

and salinity at 1 atm, J. Acoust. Sac. Am. 57^, 312 (1975).

[12] Jacobson, M. J., Siagmann, W. L., Weinberg, M. L. and Clark, J. G., Pertubation

method for determining acoustic rays in a two-dimensional sound speed medium, J. Acoust.

Soc. Am. 57, 843 (1975).

[13] Johnson, S. A., Greenleaf, J. F. , Duck, F. A., Chu, A., Samayoa, W. F., and Gilbert,

B. K. , Digital computer simulation study of a real-time collection, post-processing

synthetic focusing ultrasound cardiac camera, in Acoustical Holography, Vol. 6, N. Booth, ed,, p. 193 (Plenum Press, New York, 1975).

[14] Gilbert, B. K., Storma, M. T., James, C. E., Hobrock, L. W., Yang, E. S., Ballard, K. C,

and Wood, E. H., A real-time hardware system for digital processing of wideband video

images, IEEE Trans Computers (manuscript in preparation).

119

National Bureau of Standards Special Publication 453. Proceedings of Seminar on Ultrasonic

Tissue Characterization held at NBS, Gaithersburg , MD, May 28-30, 1975. (Issued Oct. 1976)

Paper 4.4: MEASUREMENT OF ULTRASONIC TISSUE CHARACTERISTICS BY DIRECT

AND PHASE-CONTRAST IMAGING

R. S. Mezrich, D. H. R. Vilkomerson, and K. F. Etzold

RCA Laboratories

Princeton, New Jersey 08540

This paper describes methods for measurement of the ultrasonic

attenuation and acoustic velocity of biological tissue. Initial

results are given for a series of measurements on excised breast

tissue that quantitatively demonstrate the correlation between ultrasonic attenuation and pathological state. A method for measuring

changes in phase (due to velocity and thickness differences) in a wave as it passes through tissue, based on the phase-contrast

technique, is described and demonstrated. The principal advantage

of this method over other phase measurement techniques is that

it is not as sensitive to the effects of structure overlying the

region of interest.

Key Words: Attenuation; breast tissue; broadband; high resolution;

imaging; large aperture; pathology; pellicle; phase-contrast;

transmission; ultrasound; velocity.

1. Introduction

One of the goals of the research on ultrasonic interactions with biological tissue

has been to develop methods of acoustical characterization in order to be able to determine pathological states and as an aid to the design of new instruments for ultrasonic

visualization. Since 1952, when Wild and Reid [1]^ reported on differences between the

ultrasonic echoes from malignant and benign tumors, there have been a number of studies

of the characteristic interaction of sound including, for example, such effects as attenuation [2], scattering [3], and variations in acoustic velocity [4]. These studies

have not been complete and, more important, lack the quantitative nature needed for the

effective determination of tissue characteristics.

This report describes the application of a new system [5] for the measurement

and visualization of ultrasonic waves to the study of attenuation and acoustic wave

velocity in tissue. The important characteristics of the system are: a uniform

frequency response from 0.5 to 10 MHz; a large angular acceptance (0-40°) which, with

acoustic lenses, allows wavelength-limited resolution; a large aperture (to 6 inches);

and the ability to measure the tissue characteristic reproducibly and accurately while

the acoustic image is displayed. The ultrasonic transmissi vity of tissues is measured

by detecting the ultrasonic intensity at each point of the acoustic image. Acoustic

velocity differences in tissue can be measured by using the principles of phasecontrast microscopy.

Figure 1 illustrates one application of the system to tissue characterization.

Part A is an optical image of an excised breast section with a malignant tumor. Part

B is an ultrasonic image (at 3 MHz) to the same scale, photographed from the display

CRT of the system. Regions of high acoustic transmissi vity appear light while reg[ions

of low relative transmissi vity are darker. The section was held on a plastic frame and

the metal screws, seen in both images, were used as markers. As will be discussed

Figures in brackets indicate the literature references at the end of this paper.

121

I
below, the electrical signal used to modulate the brightness of the CRT at each point of the

image is directly proportional to the acoustic intensity and is measured as the signal

is displayed to determine the relative tissue transmissi vity. In this particular tissue,

the transmissi vity through the normal region of the section (1 cm thick) was -4 dB

(relative to the transmission through water) while that through the malignant region was -20 dB. It is important to note that these values are not averages over large cross- sections of tissue, but rather accurate measurements of the local tissue transmissi vity;

the lateral resolution in the image, limited by the F:2 acoustic lenses, was < 2 mm.

Figure 1. Optical and acoustic image of excised breast tissue with malignancy

(dark region in acoustic image). Screws were used as markers.

In the following sections, we shall briefly describe the operation of the ultrasonic imaging system, discuss and illustrate its application to tissue characterization,

including recent results on the measurement of differing ultrasonic attenuation in benign and malignant breast tumors, and demonstrate the implementation of the phasecontrast method to display and measure ultrasonic velocity differences.

The arrangement used to display and measure ultrasonic waves is schematically

illustrated in figure 2. The structure to be displayed (tissue section, phantom,

etc.) is placed on the object plane, insonified, and imaged by plastic acoustic lenses onto a thin metallized plastic film (pellicle). The pellicle is so thin {'-^ 5 ym) that

its motion at every point is almost exactly equal (> 99%) to the displacement amplitude

of the ultrasonic wave passing through it. The ultrasonic displacement amplitude is measured by interferometrically detecting the motion of the pellicle. By scanning a laser beam over the pellicle, a signal is produced which is proportional to the displacement amplitude. This signal can be measured and simultaneously processed to modulate the brightness of a CRT.

The following analysis demonstrates the sensitivity and linearity and indicates

the means for achieving stability in an interferometric detection system. The arrangement used is the Michelson interferometer, the essential elements of which are shown

in figure 3.

2. Ultrasonic System

122

!
—D4- T

^^-\—

0

///////

0

Y Z SIGNAL DISPLAY

BEAM BEAM

SPLITTER DEFLECTOR

0-"

I 1 • PELLICLE OBJECT

REFERENCE MIRROR

(WIGGLER)

Figure 2. Schematic of practical interferometer for image display and measurement.

Beam deflector, consisting of two-mirror galvanometers, is in one leg of the

interferometer and "wiggler" (described below in text) is in the other leg.

Current from photodiode, proportional to light intensity, is displayed and

measured on signal scope and then processed to modulate the brightness of the

display CRT.

/777777 Ml

Figure 3. Michelson interferometer used to detect acoustic displacement amplitude.

As pellicle (M2) moves, the relative phase between and M2 varies, causing

intensity changes at photodiode (D). Laser beam is scanned to measure displacement at every point of pellicle (6 in diameter).

If the displacement amplitude of the acoustic wave at any point of the aperture

is A sin ut (which is related to the local acoustic intensity (I) by I = JgZto^A^), then

the motion of the pellicle at that point is also A sin oat. The phase of the light

reflected from that point (the pellicle is gold coated and is one mirror of the interferometer) is

123
\> = 2a • sin wt

P

^ (1)

and the amplitude of the light wave at the detector due to the pellicle is

jl^pQ + 2a . ^ sin a)t) (2)

The amplitude of the light reflected from the reference mirror is

A = A e

r ro

ro

(3)

where (pyQ and (t>po are arbitrary phases which are measures of how far each mirror is from

the beam splitter.

The light intensity at the photodiode, I = |A + A |2, is

r" p

1 = 1+1+ 2A A „ cos((^_ - + ^

sin cot) r p ro po po ^ro A (4)

where Ir (=|Arol^) ^nd Ip {=\l^po\^) are the average light intensities in each leg of

the interferometer.

This intensity, which is related to the current in the photodiode by n (the quantum

efficiency), is plotted as a function of <ppQ - (j)^Q for the situation A 0 (fig. 4).

BRIGHTNESS

RELATIVE PHASE DIFFERENCE

Figure 4. Interferometer response curve as function oj relative mirror spacing.

Maximum path difference for 180° phase shift is 1 580A for He-Ne laser. The

slope of the curve is maximum at A (90° relative phase shift).

At the point - i^^-q = 90°, we note that the slope of the curve is linear and any change in phase, due to motion of the pellicle, causes a corresponding change in brightness and hence a change in photocurrent. The photocurrent at this point, neglecting the

124
contributions of the dc terms + Ip (which, in practice, are electrically filtered out),

is

and for the situation a/a << 1 {i.e.^ acoustic intensities less than 1 W/cm^) this

becomes

The photocurrent is directly proportional to the displacement amplitude and can be easily

calibrated by measuring the light intensity in each leg of the interferometer. As a check, the system accuracy was compared with a calibrated Navy reference transducer

(NAL/USRD-E8) and the results agreed within ± 5%.

The sensitivity is proportional to the total light available and above about

k mW is limited by shot noise in the photocurrent. With a 15 mW He-Ne laser, the

minimum detectable displacement is .07^, corresponding to 5 nW/cm^ acoustic intensity

at 1.5 MHz, and with a 1 watt argon laser, acoustic intensity of lO'^^W/cm^ should

be detected. The upper limit of the linear range is determined by the linearity

of the slope of the curve of figure 4, which is within 1% for pellicle motions as large as lOOA.

The accuracy of the system depends on the condition i>pQ - (^^q = 90°. At other

values, the slope of the response curve varies, even going to zero at 0° or 180°.

To prevent inaccuracies, a novel open-loop stabilization scheme was developed.

In this method, the reference mirror is mounted on a piezoelectric disc and vibrated,

or "wiggled" so that the phase constantly varies between 0° and 180°. At least once

per cycle (the mirror vibrates at about 50 kHz), the operating point of the system

passes through the condition cjipQ - 4)^0 ~ 90° and the response appears stable even in

the presence of deleterious mechanical or thermal disturbances.

The signal at every point of the pellicle aperture (which can be as large as

6 in) is measured by scanning the laser beam over the pellicle. Once the signal is detected, it is amplified, measured, and processed for display on a CRT.

An example of the system operation, which illustrates the method by which measurements are made, is shown in figure 5. The object was a metal sheet with large ('x- 6 mm)

and small ('v 2.5 mm) holes which was insonified at 3 MHz and imaged onto the pellicle

with F:2 acoustic lenses. The acoustic image is seen in A. B is the electrical signal

from one scan along the image of the row of small holes, while C shows the same line

but with the length of the scan reduced. Once the light is measured, the electrical

signal is an accurate measure of the sound intensity at each point. Further details

on the operation and construction of the system can be found in reference 5.

The system has been used to study acoustic properties of tissue sections, especially

excised breast sections, with differing pathology. Figure 6 shows three such tissues

(the optical and acoustic images are to the same scale), including a normal tissue, one

with a benign fibrocystic structure, and one with a malignant structure. The acoustic

attenuation (defined in dB/wavel ength ^of ultrasound), measured as illustrated in figure

5, was 0.10 dB/A in the normal tissue, 0.8 dB/A in the benign fibrocystic tissue, and

1.4 dB/A and 0.15 dB/A in the cancerous and normal regions, respectively, of the malignant

tissue.

(5)

3. Transmission of Ultrasound through Biological Tissue

125
Kigure 5. Acoustic image of test object with 2.7 mm diameter small holes and 6.4 mm

large holes. Frequency was 3 MHz (0.5 mm wavelength) and lenses were F:2. A

is picture on display CRT. B (lower trace) is amplified photocurrent signal

from one scan through image of row of small holes. C is similar but with

width of laser scan reduced. When system is calibrated (by measuring light),

acoustic intensity at each point can be measured.

The tissues came from Hahnemann Hospital (Philadelphia, PA) and each tissue section

was from similar patients. The tissues were examined by a pathologist (Dr. C. Calderone

at Hahnemann) before and after our imaging experiments. The screws, seen in figure 6, were used as markers to identify particular structures of interest.

The results for a series of 18 tissue sections, prepared and measured as described

above, are summarized in figure 7. (Details of the experiment are given in reference

6.) In this graph, the tissue transmissi vity is normalized to the acoustic wavelength, as above.

The results fall in three clearly identifiable segments:

(1) Normal tissue, such as sample # 102 and sample # 109, had attenuation less than

0.25 dB/A.

(2) The attenuation of benign tumors, such as the dark region of sample # 103 in figure 6, was from 0.45 to 0.8 dB/A.

(3) The attenuation of the malignant tumors, with the exception of # 108, was between ' 1.1 to 1.6 dB/A.

I There was only one case, a medullary carcinoma which has a soft cellular structure, \ where the acoustic attenuation fell in the range of benign tumor and led to an erroneous , classification. This is a relatively rare tumor and we are trying to get some samples I for further studies. In all other types, the results were unambiguous. ,

126

'

I

i
A. NORMAL

B. BENIGN FIBROCYSTIC

C. MALIGNANT

Figure 6. Optical and acoustic images, to same scale of breast sections, with

normal, benign and malignant structures. Attenuation at 1.5 MHz was -2 dB in

normal, -6 dB in benign fibrocystic structure, and -14 dB in malignant tumor.

Several theories have been proposed to explain the difference in acoustic transmission

through such tissue. One, discussed in a paper by Fields and Dunn [7], is that any neoplasm

triggers an inflammatory response resulting in the growth of fibrous connective tissue (as

if the body were trying to wall off the cancerous cells). Cancer, an invasive neoplasm,

stimulates greater fibrous tissue growth. As fibrous tissue is believed to be more strongly

attenuating, benign tumors would show less attenuation than cancerous tumors, in agreement

with our experimental results.

Regardless of the reason, the different tissue types interact differently with the

acoustic wave, and these changes can be visualized and measured in detail with the ultrasonic imaging system. The important feature of the system is that it can measure

such structures with high lateral resolution. In one instance, tumors as small as 2 mm

were observed in the system and then verified as malignant by the pathologist.

These studies are being continued both with breast tissue and other structures.

The system is also being adapted for reflective imaging, by using a "top lighting"

technique as in optical microscopes, in order to more fully characterize the interaction of ultrasonic waves with tissues.

127
1.8

1.7

1 AI.D

1 (\

HI 1.4

1.3

LlI _J 1.2

LlI >

< I.I

1.0

Cl. LlI .9 Q.

CD .8 U

CO .7 CO0

_l .6

CD0 .5

.4 <

CD

.3 <

"I 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 r

BENIGN

N t N

-I- o }

MALIGNANT

.2

-i 1 1 i 1 1 1 I I I I I I I I I I I I

i

102 103 i05 107 109 110 113 114 125 101 104 106 108 III 115 121 122 124 SAMPLE

Figure 7. The transmissi vity versus sample pathology. Table I lists the

histological analysis of the samples. The transmissi vity is defined here as the decibels loss, i.e., -10 log^o Transmitted Intensity/Incident Intensity

per wavelength of ultrasound, i.e., if J^q is 1, there is 10 dB loss in traversing 10 mm of tissue with 1 mm ultrasound. (The samples were numbered

in chronological order starting with 101. Sample 112 is missing because of

uncertainty in the records as to its pathology, and samples 116-120 were not

cut as flat slices, so that the thickness was indeterminate and the data

not incl uded.

)

4. Phase-Contrast Velocity Measurements

The preceding examples have been those where the amplitude of the acoustic wave

was modified by the tissue. In many cases, the velocity of the wave passing through

the tissue is also modified. Since the velocity is a function of tissue elasticity

and density, and since both (especially the elasticity) can be modified by disease,

the detection of velocity differences could be an aid to the determination of pathological state. Furthermore, many structures are either too thin, or have so little

absorption that they do not substantially change the amplitude of the acoustic wave,

but yet such tissues can show velocity differences. An important example is atherosclerotic plaque, which in the early stages of the disease consists of small (1-5 mm)

fatty deposits on the interior wall of the artery. The fatty deposits have too little

attenuation or reflectivity to be detected by normal acoustic techniques [8] (especially

before they have calcified) but could be seen by a method sensitive to the phase of

the transmitted ultrasound.

128
The phase-contrast method [9,10], initially developed to image opticallytransparent biological specimens, can be applied to visualize and measure acoustic

velocity differences in tissue.

The method can be explained by the following simple argument.

Consider an object (tissue) with some spatially-varying elasticity but with no absorption. An acoustic wave transmitted through it will propagate with differing

velocities and as a result will have a spatially-varying phase. The amplitude of the wave as it leaves the tissue can then be written as

A = aeJ*^^) (7) 0

where (})(x) is the spatially-varying phase and a is the wave magnitude (a = 1 for non- absorbing tissue). In a system sensitive to the wave intensity (as a light microscope)

or magnitude (as our system is), the detected signal is proportional to

|A I I qI = a (8) \ /

and will not directly show the effects of the phase variation.

Now consider the situation when the phase variation is small; then eq. (7) may be

expanded as

A^ = aeJ*(^) « a(l + j>(x)) (9)

which consists of a nonvarying term which is in phase quadrature with the spatiallyvarying term.

If the phase cf the nonvarying term is advanced or delayed by 90°, the amplitude

becomes

Aq = a(±j + j*(x)) (10)

and the magnitude is

|A| = a(l ± <}.(x)) (11)

and directly displays the phase variation.

In figure 8, we show a method for acoustic imaging. The acoustically-transparent

object is insonified by a plane acoustic wave and imaged by acoustic lenses onto the

pellicle. As the wave propagates through the object, some of it passes directly through,

undisturbed, and is brought to a focus on the axis in the back focal plane of the first

lens (the object lens). The remainder of the acoustic wave is scattered by the phase

variations and is spread out over the back focal plane of the lens. It can be easily

shown [10] that these two waves, the scattered and undisturbed, are in phase quadrature

and that further, when they are combined at the pellicle by the second lens, they

reproduce the wave that existed at the object, exhibiting phase variations but no contrast. Since the waves are in quadrature, they cannot interfere to produce amplitude variations.

The phase-contrast method takes advantage of the fact that the two waves are spatially separated in the object lens focal plane. By insertion of a phase plate

(for example, a plastic disc of the proper thickness) over the focused "undisturbed"

129
Figure 8. Arrangement for normal amplitude and phase-contrast imaging. "Undisturbed" wave is focused by object lens while scattered wave is spread over focal plane.

Additional 90° phase shift can be obtained by inserting a plastic disc over focused

"undisturbed" wave.

wave, the relative phase between the two waves can be adjusted so that they interfere

at the pellicle. If the phase plate advances the undisturbed wave by 90°, the two waves will interfere constructively at the pellicle, giving a bright image. If the

phase plate retards the phase by 90°, the two waves will interfere destructively, giving

a dark image. Alternatively, the phase of the scattered wave could be modified giving

similar results.

Figure 9 gives an example of the phase-contrast method. The object was a thin

(0.5 mm) polystyrene strip which did not substantially absorb the sound (< 0.5 dB)

Figure 9. Phase-contrast image of test sample. Object (A) was 0.5 mm thick

polystyrene with < 0.5 dB attenuation and 30° phase shift. Normal image shows

edges (due to sound diffraction beyond edges) but no contrast. Phase-contrast

image shows full detail, with brightness proportional to phase shift.

130
but did advance the phase, relative to water, by 36°. Part A shows an optical image

and B a normal amplitude image of the object. Note that the edges of the object in

the normal acoustic image are seen, due to sound diffracted beyond the lens aperture,

but no detail is seen and there is no contrast against the background. Part C shows the

phase-contrast image. The phase plate was 24 mil (0.6 mm) polyethylene placed over the

focused "undisturbed" wave and at the frequency used (2.25 MHz) and at the temperature of

the water bath (37°C) advanced the phase by 91°. The object is seen in detail and not

just in outl ine.

This is an example of bright phase-contrast; the image is brighter than the

background. By using a phase plate that retards the undisturbed wave, a dark image

results. Alternatively, as mentioned above, the phase of the scattered wave can be

modified. Figure 10 shows the results in this case, obtained using a polyethylene sheet

with a hole in the acoustic axis. Part A shows the normal image, part B repeats the

previous bright image and part C shows the dark image of the same object.

A B C

Figure 10. Bright and dark phase-contrast imaging. Also shown are processed

acoustic signals from one line through image.

By a simple analysis [11], the change in amplitude at the image is

^ ^ [a^ + 2{1 + cose + a sine}]^

a

which, for small phase changes and a = 1, is (as in eq. (11))

A (1 + e) .

In polystyrene, the calculated phase change of the sound is 36°, which should give

an amplitude change of 1.8. This agrees well with the measured values, measured

as illustrated in figure 5.

A second example, with biological tissue, is seen in figure 11. The object, a section of calf liver containing several blood vessels, is seen in the photograph

(A). (The sample was cut after the imaging experiments.) The normal acoustic image

is seen in B and only the edges of the vessels can be seen, due to diffraction (the vessels

were allowed to fill with water). The phase-contrast image is seen in C, where now the

vessels can be seen in detail and with high contrast.

There is an important distinction between the phase-contrast method of velocity

measurement and those methods that insert an electronic reference to detect phase variations.

This becomes evident when considering a section to be examined surrounded by different

131

I
(a)

Figure 11. Phase-contrast image of calf liver section. A shows liver cross- section, cut after experiment, to show vessels. B is normal acoustic image

with poor detail. C is phase-contrast image, and blood vessels are seen bright and in detail

.

overlying tissues. When the wave propagates through the object, its phase is varied both

by the section to be observed and by the overlying tissue, and the phase variation due to the region of interest alone cannot easily be identified by using an electronic reference.

In the phase-contrast method, the reference (the "undisturbed" wave) and the scattered

waves propagate through the tissue together and phase variations common to both cancel

at the image. Unless the overlying tissue is very rough (rapid phase variation) or very

far removed from the region of interest, it will have little effect on the image. (The

situation is somewhat like looking through a shower glass; if the object is very close

to the glass or if the glass is not too rough, the structure beyond the glass can be

discerned.) By analogy to optical phase-contrast methods, it is expected that objects

up to 10 cm thick can be examined.

With the addition of the phase-contrast method, it is expected that the ability of

the technique to characterize and identify tissue will be extended. The study of atherosclerotic plaque is one example where phase-contrast may be applied, the visualization of

tumors and fatty structure elsewhere in the body is another. The important feature is that with this method, as with the method used to display amplitude variations, the effect

of the interaction of the tissue with ultrasound can be simultaneously displayed and

accurately measured.

132
We have described a system to visualize and measure ultrasonic waves and given

examples of its use in measuring and displaying ultrasonic tissue interactions, both

amplitude and velocity. We hope that through continued use of this system, both by us and others, the ability to characterize tissue will be increased and more sophisticated

devices based on a better understanding of the interaction of ultrasonic waves with

tissue will become available for clinical use.

References

[I] Wild, J. J. and Reid, J. M., Other pilot echographic studies on the histologic

structure of tumors of the lining intact human breast, Am. J. Path. 28, 839 (1952).

[2] Goldman, D. E. and Heuter, T. F., Tabular data on the velocity and absorption of

high frequency sound in mammalian tissues, J. Aaoust. Soo. Am. 28, 35 (1956).

[3] Freese, M. and Hamid, M. A. K., Lipid content in whole fish using ultrasonic

pulse backscatter, in Proa. IEEE Ultrasonics Syrnp., p. 69 (IEEE, New York, NY, 1974).

[4] Kossoff, G., Fry, E. K. , and Jellins, J., Average velocity of ultrasound in the

human female breast, J. Aaoust. Soa. Am. 53^, 1730 (1973).

[5] Mezrich, R. S., Etzold, K. F., and Vilkomerson, D. H. R., System for visualizing

and measuring ultrasonic wavefronts, RCA Rev. 35^, 483 (1974).

[6] Calderone, C, Vilkomerson, D., Mezrich, R., Etzold, K., Kingsley, B., and

Haskin, M., Differing ultrasonic attenuation in normal, benign and malignant

breast tissue. (Manuscript in preparation.)

[7] Fields, S. and Dunn, F., Correlation of echographic visualization of tissue with

biologic composition and physiological state, J. Aaoust. Soo. Am. 54, 809 (1973).

[8] Barber, F., Baker, D., Nation, A., Strandness, D., and Reid, J. M., Ultrasonic

duplex echo-doppler scanner, IEEE Trans Bio-Med. Eng. BMR-21 , 109 (1974).

[9] Zernike, F., Das phasen kontrastverfahren bei der mikroskopischen beobactung,

Z. Tech. Phys. 16_, 454 (1935).

[10] Bennett, A. H., Jupnik, H., Osterberg, H., and Richards, 0. W., Phase Microscopy,

(J. Wiley and Sons, New York, 1952).

[II] Born, M. and Wolf, E., Principle of Optics, p. 427 (Pergamon Press, Oxford, England,

(1965).

133
i

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!
\ National Bureau of Standards Special Publication 453. Proceedings of Seminar on Ultrasonic

I Tissue Characterization held at NBS, Gaithersburg, MD, May 28-30, 1975. (Issued Oct. 1976)

Paper 4.5: REFLECTION TECHNIQUES FOR MEASUREMENT OF ATTENUATION AND VELOCITY

G. Kossoff

Ultrasonics Institute

Sydney, Australia

Pulse reflection techniques may be used for in vivo measurement of

attenuation and velocity. Measurement of the two-dimensional distribution

of pulse attenuation may be obtained based on the equalization of internal

echoes, while the differential pulse attenuation of encapsulated tissues is obtained by noting the difference in the echo from the posterior boundary

at different frequencies. The average velocity in tissues may be measured

by a simple technique if a reflector may be positioned at the posterior

boundaries. A reflection technique for measurement of local values of

velocity in heterogeneous tissues using two forward transducers separated

by a known distance is suggested.

Key Words: Attenuation; breast; reflection techniques; ultrasound;

velocity.

1. Introduction

Reflection techniques are based on the measurement of amplitude and time delay of

echoes originating from discontinuities in acoustic impedance in the examined tissues.

These echoes are also carriers of information about other acoustic parameters of tissue

such as attenuation and velocity, and with suitable techniques, may be used to measure these

parameters. Reflection techniques have the advantage that the measurements may be performed

using only one transducer and in many instances are the only possible class of techniques

for non-invasive in vivo measurement of these parameters.

2. Measurement of Average Velocity

If the tissues are such that it is possible to get access to their anterior and

posterior boundaries, it is possible to use a reflection technique to measure the average

velocity of propagation based on an analogous transmission measurement technique [1].^ In this technique, a reflecting target is placed against the posterior boundary, replacing the

opposing transducer in the transmission technique, and the average velocity is obtained by

comparing the time of propagation in the tissues with the time taken for the energy to propa- gate in water, the distance between the transducer and the reflecting target being kept

constant. As in the transmission method, the average velocity of propagation in the tissue

Vj^ is given by

\-TTIt' (1)

where v^^ is the known velocity of propagation in the water. At the time difference between

the two measurements and ty^ the total time taken to travel in water. A schematic of the

method is illustrated in figure 1. In analogy with the transmission technique, the accuracy

of the measurement is relatively high, being of the order of 0.5%. In practice, refractive

processes limit the repeatability of the measurement, particularly in heterogeneous organs

^Figures in brackets indicate the literature references at the end of this paper.

135
such as the breast where the velocity of constituent tissues may vary by up to 15%. On repositioning, these affect the time of arrival of the pulse and in practice reduce the

accuracy to approximately 2%. Transducer

At = t^-tb

d = constant

i

Reflector w// /

/

Figure 1. Technique for measurement of average velocity.

In theory, a similar technique based on the measurement of the amplitude of the echo

from the reflecting target may be used for the measurement of average attenuation. In practice, refractive processes affect to a much greater degree the amplitude of the echo

and make the technique unsuitable for this application.

The measurement of attenuation may be made either from the echoes obtained from the

internal structural organization of the tissues or the echoes obtained from the boundaries

of the tissues [2].

The technique for measurement of attenuation from the A-mode, or unidimensional

amplitude-versus-time delay presentation of data, is described in the paper "Quantitative A-scan Analysis of Normal and Cirrhotic Livers" (this volume, p. 61 ). It is also

possible to measure attenuation from a special type of B-mode or two-dimensional presentation of the data. In this technique, the tissues are examined using simple scanning, such

as linear or sector scanning, and the receiver gain is increased progressively step-wise

by a known amount. If it can be postulated that the internal tissue distribution is homogeneous as, for example, in the case of a normal liver or a homogeneous tumor, then, after

allowing for the transducer beam pattern variations, one may expect that the internal

echoes should all be of the same strength and that the gradual decrease in the strength of

the echoes with penetration is due only to attenuation. This is indeed the postulate made

in the measurement of attenuation from the A-mode data. Therefore, if two echoes along

the same line of sight in different penetration bands are displayed with the same intensity,

then the known gain difference between the bands represents the loss of signal due to attenuation, since all the other factors such as receiver and display characteristics,

photographic exposure, developing, etc., are constant. Thus, as illustrated in figure 2,

the two-dimensional attenuation distribution is obtained by finding echoes of equal intensity

in penetration bands with differing gains, the attenuation being given by the quotient of

the gain difference and the distance between the echoes. The two-dimensional presentation

of the data provided by the B-mode echogram has the advantage that it allows the selection

of regions where the postulate of homogeneity of the tissues is most likely to be valid,

while the intercomparison of echoes between different bands permits an averaging of the

measurements

.

The application of the method on a scan of a sponge target and a breast containing a small benign mass is illustrated in figure 3. In these examples, a stepped-gain function

was approximated by superimposing a 3 dB gain reduction every second step on the normal

3. Measurement of Attenuation

3.1 Internal Echoes

136
Transducer

Gain

Two Echoes of Equal Intensity

1 2d B

1 5dB

18dB

6nnm

0 5dB/mm

Figure 2. Principle for measurement of pulse attenuation.

SPONGE TARGET BREAST

NORMAL TGC -3dB every 3mm NORMAL TGC -3dB every 3mm

Figure 3. Normal and stepped-gain linear scan echogram for measurement of pulse

attenuation.

137
gradually-increasing TGC (time-gain compensation) gain of the receiver. Although the size

of the step, the grey scale range within the step and the frequency of operation of the

equipment is not optimum for the application, the figure illustrates the typical striped

appearance of the echogram and illustrates the applicability of the method. With the greyscale presentation, the selection of echoes of equal strength may necessitate the use of a film densitometer since the human eye is not very effective in selecting regions of equal

grey level. As the eye is more capable of selecting equal colors, color presentation could

facilitate the recognition of echoes of equal strength and allow direct measurement from the

echogram.

Generally, attenuation figures are specified at a single frequency. Since the echo

pulse contains a relatively wide frequency spectrum, it is more appropriate to quote the

reflection-based measurement as the "pulse attenuation" as it is to some extent dependent

on the waveform of the pulse. Also, since in the reflection technique the energy has to go in both forward and backward directions, the figure corresponds to twice that obtained

by a transmission measurement.

The attenuation of encapsulated tissues cannot be determined by simple comparison of

amplitude from the front and back boundaries. The amplitude depends on the geometry of

the boundaries which, in general, are not similar, nor may it be assumed that the same impedance discontinuity exists at the two boundaries. A differential technique may be

employed to obtain the differential pulse attenuation. In this technique, the examination

is repeated at a different resonant frequency and the differential pulse attenuation is obtained by equating the amplitude of the echo from the front surface at the two frequencies

and noting the difference in the amplitude from the back boundary. Theoretically, it is also possible to undertake this measurement with a single pulse by separating the frequency

components of the pulse by filtering and comparing the amplitudes of the low and high frequency components of the pulse.

A schematic of the method is illustrated in figure 4, the differential pulse

attenuation being given by

3.2 Boundary Echoes

2 1

(2)

Differential Pulse

Attenuation

^ Back boundary

Figure 4. Principle for measurement of differential pulse attenuation.

138
where d is the distance between the boundaries, and V""^ , V"^^, V'"^; , V"^^ the amplitudes of

'1 ' ~2 '2 the echoes from the front and back boundaries at the resonant frequencies f^ and f2,

respectively.

4. Measurement of Velocity

Theoretically, the value of velocity of the constituent tissues in a heterogeneous

organ may be obtained by using two transducers separated by a known distance [2]. One

transducer is used as the transmitter and the receiver while the other transducer is used

as a receiver only and the measurement is obtained by noting the time delay of echoes

received from the same internal reflectors by the two transducers. The principle of the

method is illustrated in figure 5 which shows that the velocity in the first medium v^ is given by

" (t2(t2-t^))"^

where d is the separation distance and t2 and ti the respective time delays. If water is

used as the coupling medium, then v^ is known and this equation may be used to calculate the

separation distance d for the chosen transducer configuration and to check for any possible

dependence on the penetration depth.

Figure 5. Principle for measurement of internal values of velocity.

Simple mathematical analysis shows that the velocity in the underlying layer in tissue

Vb is given by a quadratic equation involving ti, ts, t^, Vv^, and d, and once v^ is determined,

an iterative process may be used to determine the velocity in the distal tissues.

This paper is published with permission of the Australian Director-General of Health.

References

[1] Kossoff, G., Kelly Fry, E., and Jellins, J., Average velocity of ultrasound in the human

female breast, J. Aaoust. Soo. Am. 52, 1730 (1973).

[2] Kossoff, G., Progress in pulse echo techniques, in ultrasonics in Medicine, M. de Vlieger,

et al., eds., p. 37 (Excerpta Medica, Amsterdam, 1974).

139

CHAPTER 5

ABSORPTION TECHNIQUES

141

National Bureau of Standards Special Publication 453. Proceedings of Seminar on Ultrasonic

Tissue Characterization held at NBS, Gaithersburg, MD, May 28-30, 1975. (Issued Oct. 1976)

CHAPTER 5. ABSORPTION TECHNIQUES

Paper 5.1: ULTRASONICALLY-INDUCED TRANSIENT THERMAL GRADIENTS:

THEIR POTENTIAL ROLE IN ACOUSTIC PARAMETER

CHARACTERIZATION OF TISSUE

F. J. Fry

Fortune-Fry Laboratories

Indianapolis Center for Advanced Research

Indiana University Medical Center

Indianapolis, Indiana 46202

Induction of transient thermal gradients by ultrasonic means with concurrent detection by ultrasound offers the possibility of

determining quantitatively some of the acoustic properties of live

tissue. The transient thermal gradient is related to the inherent

acoustic absorption property of the tissue. When used appropriately,

this gradient can be used to determine acoustic absorption,

attenuation, velocity, and to enhance acoustic impedance differences

at certain interfaces. Additional work beyond that reported here

is needed to explore essential application of this method in the area of acoustic parameter determination which could lead to an enhanced tissue differentiating capability.

Key Words: Absorption; attenuation; impedance gradient;

transient thermal gradients; ultrasonics; velocity.

1. Introduction

The idea of using ultrasound to induce a transient temperature rise in tissue for

the purpose of aiding in the identification of tissue types through ultrasonic interrogating

means was first suggested in 1962 [1].-^ In its original form, advantage was to be taken

of the fact that acoustic absorption in soft tissue has a much wider range of variation

than does acoustic impedance which is the primary acoustic parameter used qualitatively

or at most semi-quantitati vely in present medical diagnostic regimes. This reliance on acoustic impedance differences is slowly changing as other acoustic properties permit

ready presentation. It is anticipated that quantification of a spectrum of acoustic

properties in tissue will lead to greater differentiation capability. One suggested mode

of operation for the transient thermal gradient method was in the production of detectable

and quantitatively-measurable acoustic impedance differences across tissue interfaces

which normally would not have an acoustically-detectable difference. This effect would

be operative if the tissues on either side of the interface had acoustic absorption

differences which, if the tissue were acoustically irradiated at an appropriate intensity,

would produce a temperature gradient resulting in an acoustic velocity gradient which

would bring the interface into the detectable range. It is of course possible that there

might be acoustic impedance differences which would be brought closer in value by this

method. All of these temperature changes would, of necessity, need to be induced at acoustic intensity levels which produced no adverse biological effects in the tissue. It

^Figures in brackets indicate the literature references at the end of this paper.

143
was also recognized that irradiation in a homogeneous tissue itself would produce a temperature rise related directly to the intrinsic absorption property of the specific tissue

and that this method could potentially be used to characterize a homogeneous tissue through

appropriate interrogation means. An additional possibility arises which could lead to a tissue specific velocity determination since the thermal gradient induced by a focused

transducer can be moved by accurate known amounts thereby permitting the determination of

transit time measurements between targets of known separation. Conceivably, attenuation

could be measured in a homogeneous tissue by observing the amplitude of the reflected

signals from these known sites. This method requires a knowledge of the frequencydependent character of attenuation in the tissue since for different path lengths the

temperature-inducing beam will be absorbed differentially for the different sites. It would also be necessary that the reflection amplitude be quantitatively recorded. There

are other ways in which thermally-induced changes can be potentially useful in acoustic

interrogation for tissue parameter characterization which are covered by other authors in

this volume.

2. Theoretical Analysis

In this section, we consider the magnitude of the induced temperature rise needed to produce an acoustically-detectable interface. Sensitive acoustic interrogating systems

using focused transceivers will resolve acoustic impedance differences at interfaces of

the order of 0.1%. Assuming that the temperature coefficient for sound velocity in tissue

is substantially that of Ringer's solution (1% acoustic impedance change for a 10°C change:

30 to 40°C), it is apparent that a 1 °C change would produce a detectable impedance change.

The largest component of this impedance change is in the sound velocity rather than in the

material density.

An approximation to the maximum temperature rise T (°C) in tissue produced by a short

ultrasound exposure is given by:

where

alt

P C

a = acoustic intensity absorption coefficient (cm" ) I = intensity at the site (W/cm^)

t = sound pulse duration (seconds)

p = density

pC = heat capacity/unit volume ( joules/cm3/°C)

.

(1)

The short exposure time (t < 1 sec) is used so as to insure substantially no heat conduction

loss in the tissue.

Computation of the temperature rise in brain tissue is shown in Table I for a given

set of acoustic parameters. The resultant temperature rise of approximately 5°C or 10°C

Table 1. Computed Temperature Rise in White and Grey Matter of

Brain after 0.1 sec Irradiation with Ultrasound

Intensity at Site (W/cm2) Frequency (MHz) Time On (sec)

White

Matter

Temperature

Rise (°C)

Gray

Matter

1,000

2,000

1.0

1.0

0.1

0.1

5.0

10.0

3.0

6.0

is presumably a safe increment [2] under the conditions of the 0.1 sec. pulse duration.

Additionally, the 1 MHz ultrasonic beam used for raising the tissue temperature by 5°C

would be delivering an ultrasonic dose which is an order of magnitude below that which has

been identified as the threshold for lesion production in brain [3]. Since brain

144
white matter has an intensity absorption coefficient approximately 50% higher than that of

grey matter, a temperature difference of approximately 2°C or 4°C (depending on the acoustic

intensity values used as shown in Table I) would appear across a grey-white matter interface.

On the basis of these computations, it would appear possible to produce approximately 1%

acoustic impedance discontinuity in homogeneous brain tissue for a 10°C rise and an enhancement of grey-white matter interface of about 0.4% for a 10°C rise in the white matter.

All of the above considerations involve the concept of an abrupt discontinuity in

the acoustic impedance induced by a temperature rise. An idea of the abruptness of the

temperature transition in the tissue can be obtained by considering the temperature

distribution following induction of a one-dimensional unit temperature step function.

This temperature distribution (T(x)) centered at the plane X = 0 can be expressed as [2]

T(x) =U] + 0

X

2a /t,

(2)

where ^ is the error function defined by

2a /t

2a/t

e ^ dy (3)

and

X = space coordinate

t = time

s = heat capacity per unit mass

K = thermal conductivity coefficient

= diffusivity = . ps

For a value of a^ = 0.001 cm^/s, the normalized temperature distribution is shown in

figure 1 for time intervals measured in seconds after unit-temperature step-function

appl i cation.

= k/ps

a^ = 0.001 cm^/sec

(a^H 20=0.0014)

0.2 015 01 0.05 0.05 0.1 0.15 0.2

X(cm)

Figure 1. Temperature distribution as a function of distance from the X = 0 plane for various time intervals after unit- temperature step-function induction

centered at X = 0. 145
From the curves of figure 1, it is possible to estimate a structural resolution capability

assuming that an appropriate acoustic-sensing frequency is used. In this case, we take

the plane X = 0 as either the interface between two tissues of different acoustic absorption

coefficients and the surface corresponding to the center of the heating beam or as represent

ing a plane in a homogeneous tissue in which a step function temperature rise has been

produced. More sophisticated approaches to this problem of temperature rise in tissue

undergoing ultrasonic irradiation have been considered by others [4].

Resolution in the X direction is assumed as approximately the incremental X distance

for the time intervals on the specific curve. In a homogeneous tissue at t = 0.1 s, resolution would be of the order of 0.4 mm.

In order to see that these resolution values are achievable, it is necessary to select an interrogating frequency such that the magnitude of reflected energy at the

thermally-induced transition will approximate that from an abrupt acoustic impedance

change. A previous analysis [2] of the approximate relationship between the reflection

from an abrupt transition and a graded transition of the type delineated by the curves

of figure 1 indicates that a transition zone of the order of 1/4 wavelength or less of the

interrogating beam will be a good approximation to the abrupt transition. This means

that an interrogating frequency of 2 MHz is adequate, since A/4 in soft tissue is approximately 0.2 mm which is in the range of the structural resolution referred to previously.

The magnitude of the acoustic pressure reflection coefficient r at an interface between

two media (with acoustic impedances of p-jC-j and P2C2) is described by

Pl^2 P2C2

(4)

If a change is induced in c^ and due to a thermal gradient and if pi = P2, then the

reflection coefficient becomes

At

C2 + (ac-j AC2)

C-| + C2 + (AC-j + AC2)

(5)

Depending on the initial velocities, assuming generally a positive coefficient of velocity

with increasing temperature, and depending on which media has the larger velocity coefficient, it is possible to increase or decrease the reflection coefficient (Table II shows

several examples).

Case

Table II. Reflection Coefficient Change due to Temperature

Modi fi cation*

Relative Velocity

Ci C2

Relative Velocity Change

ACi AC2

Reflection

Coefficient

1.5

1.5

1.5

1.6

1.6

1.6

0.5

0.10

.10

.05

.0323

.0462

.0154

The densities in both tissues are assumed to be equal. In case 2, the thermal

perturbation provides an increased reflection while in case 3, it provides a decreased

reflection.

146
3. Experimental Results

A first observation of an ultrasonically-induced transient effect which was presumably

thermal in nature was made in an experimental animal brain [1] (adult cat). The experimental arrangement used for this observation is shown in figure 2. A 1 MHz focused beam was

used to irradiate the brain and a 5 MHz unfocused transceiver was used for detection of

the effect. Results of this first experiment are shown in figure 3. For this and all subsequently mentioned observations, a skull bone section was removed for the acoustic

interrogation implementation. If the high intensity irradiating beam remained on until

a permanent effect was observed, the results appear as in figure 4. Figure 5 shows a series

of three pictures taken on an excised human brain which has been fixed in formalin. In figure 5A, the reflections are shown before transient heating induction. The effect of

transient heating can be seen in figure 5B. After cessation of the heating beam irradiation,

the additionally observed reflection completely disappeared. If the duration of the

Figure 2. Schematic diagram of arrangement for ul trasonical ly inducing and detecting

a transient thermal gradient in a cat brain.

B

1

Figure 3. Echo pattern from interrogation of cat brain by examining transducer:

(A) preceding induction of transient-temperature distribution caused by 1.0 second

pulse of focused ultrasound; (B) two seconds after focused sound pulse; (C) five to six seconds after focused sound pulse; (D) one and one-half minutes after focused

sound pulse. Echo 1 is from the near surface of cat brain and echo 2 is from the

far surface of the brain. Echo 3 is transiently modified and echo 4 is transiently

induced.

147
7

a"

B

"c

4

Figure 4. Echo pattern from interrogation of cat brain by examining transducer:

(A) preceding induction of a lesion caused by a 6 s pulse of focused ultrasound;

(B) fifteen seconds after lesion induction (echo 4 is induced); (C) persisting echo

pattern.

Will III ^ft

'

Heated Region

Figure 5. Ultrasonic induction and detection of both transient-heating effect

and permanent-reflecting region in a formalin-fixed human brain.

heating beam was further increased, a permanent effect could be produced as shown in figure

5C. Another experimental observation involved ultrasonic visualization of a transientlycooled region in the occipital lobe of the Rhesus monkey brain. A cryoprobe used for

cryosurgery was placed in contact with the dura in the occipital area and the

brain tissue was slowly cooled (over a several minute time period). The two-dimensional

cross section images of the brain region before, during and after cooling are shown in figure 6. This cooling was sufficient to produce a subsequently observed brain lesion.

Physical model studies involving thermal heating in lucite with focused ultrasound

have shown that transient and permanent acoustically-detectable effects can be observed [2].

The setup for observing these effects^is rather similar to that used for the tissue

observations shown in figure 2. An example of an acoustic transiently-observable effect

in lucite is shown in figure 7. Figure 8 shows the echogram of a transient acousticallyobservable effect in lucite in which the opposite sides of the heated region can be

separated into two echoes. The peak-to-peak spacing distance for this picture is approximately 3.5 mm. These lucite observations of a transient nature are in general associated

with a permanently-observable optical effect.

148
22 dB 63 y = 83 22dB 121

gure 6A. Ultrasonic visualization of live Rhesus monkey brain subjected to cryoprobe cooling sequence.

y=64 22 db 12 22 db 8

P14 20 db 13 20

Figure 6B. Ultrasonic visualization of live Rhesus monkey brain subsequent (1-16

days) to cryoprobe cooling sequence.

149
TRANSIENT

REFLECTION

Figure 8. Ultrasonic detection of transiently-induced thermal gradient in lucite

block in which echoes appear from both sides of the cylindrically-heated region.

4. Conclusion

A number of acoustically-induced thermal effects having a transient or permanent

character (as determined acoustically) have been studied in physical models and in experimental animal tissues. For tissues, the possibility exists of using these effects to differentiate tissue types based on acoustic absorption spectra. Naturally, it would be

ideal if all this could be accomplished in a totally reversible manner from a physiological

perspective. It does not seem unreasonable to suggest the additional possibility of using

focused ultrasound even if it involved a small modified tissue volume, provided a definitive

tissue differentiation could be accomplished. Biopsy by mechanical means is a medicallyacceptable procedure which could find perhaps a less traumatic counterpart in either

reversible or irreversible ultrasonic biopsy.

Implementation of velocity determination or attenuation loss based on interrogation

of multiple thermal gradient sites would of course require additional experimental

investigation before any definitive statements can be made about its utility in tissue

differentiation.

i

I

I

150
References

Fry, W. J. and Fry, F. J., Ultrasonic visualization of soft-tissue structure based

on gradients in absorption characteristics, J. Aooust. Soc. Am. 35, 1788 (1963).

Fry, W. J., Fry, F. J., Kelly, E., Fry, T.A. , and Leichner, C. H., Ultrasound

transmission in tissue visualization, in Diagnostic Ultrasound, p. 13 (Plenum Press,

New York, 1966).

Dunn, F. and Fry, F. J., Ultrasonic threshold dosages for the mammalian central nervous

system, IEEE Trans. Biomed. Eng. BME-18, 253 (1971).

Robinson, T. C. and Lele, P. P., Analysis of lesion development in the brain and in

plastics by high intensity focused ultrasound at low megahertz frequencies, J. Aaoust.

Soc. Am. 5, 1333 (1972).

151

National Bureau of Standards Special Publication 453. Proceedings of Seminar on Ultrasonic

Tissue Characterization held at NBS, Gaithersburg, MD, May 28-30, 1975. (Issued Oct. 1976)

Paper 5.2: TAST: A NON-INVASIVE TISSUE ANALYTIC SYSTEM

T. D. Sachs, P. T. Anderson, R. S. Grimes

S. J. Wright, Jr., and R. M. P. Donaghy

University of Vermont

Burlington, Vermont 05401

The Thermo-Acoustic Sensing Technique (TAST) uses two intersecting

sound fields to measure the acoustic absorption of cerebral tissues at the point of intersection. A resolution of better than 1/8 inch was achieved in initial scans through the coronal plane of a fixed human

brain. The sylvian and cortical fissures, basal ganglia, and ventricular boundaries appeared to be profiled by the TAST values. Conceivably,

TAST may provide numerical tissue characteristics in 0.002 cubic inches

of selected cerebral tissue. Should predictions based on current theory

and data prove correct, TAST may become a repeatable non-invasive means of establishing intracerebral diagnosis.

Key Words: Absorption; attenuation; brain; neoplasm; TAST; thermal

effects; tissue; tumor; ultrasonic; velocity.

1. Introduction

Present day methods of obtaining biological information by means of ultrasound have

in general three principal difficulties: (1) the information obtained is not as closely

related to the biological function of the tissue as one might wish; (2) the measurements

are subject to severe interference and; (3) information can be obtained only where interfaces exist. The Thermo-Acoustic Sensing Technique (TAST) technique described here

appears to have advantages in all problem areas.

1.1 Velocity Versus Attenuation

Most present-day ultrasonic systems obtain their information through the measurement

of either the acoustic attenuation or impedance discontinuties in the tissue being examined.

Attenuation is composed of two components, absorption and scattering. The absorption part

of the attenuation exhibits a much larger percentage change in its value for a given biological difference than does the impedance, [1]^ and thus would appear to be the parameter of

preference in biological analysis. To date, however, the emphasis has been on the measurement of impedance discontinuties rather than on attenuation or absorption.

1.2 Attenuation

Hueter and Bolt [2] measured transmission losses through the head. They scanned the

transmitter and receiver together so as to produce a map comparable to an x-ray picture.

Thus, their technique measured the total attenuation along the beam, comprising the

superimposed effects of transmission through bone, having a high attenuation coefficient,

and soft tissue, whose coefficient is far lower. They found eventually that most of the

measured effect was due to bone and that little useful information was obtained on the

soft tissue of interest.

Fry and Fry [3] studied absorption gradients in tissues. They used a focused

sound field to heat the tissue of interest. This heating changed the sound velocity and

thus the acoustic impedance of the tissue. Where the heating field focus crossed a

Figures in brackets indicate the literature references at the end of this paper.

153
boundary between two media of differing absorption coefficients, the media are heated

differently and a reflecting surface is generated. If a reflecting surface is already

present, its characteristics will be modified. These surfaces can be detected by normal

echography apparatus. Thus, the Fry technique is sensitive to interfaces between tissues

having different absorption coefficients.

Fry and Fry were able to pinpoint the position of an absorption gradient but were

unable to determine the direction of the gradient. Hueter and Bolt's transmission system

could achieve high signal-to-noise ratios in the received signal in contrast to echography

even while working through the head, but was unable to localize the point of interest or

to distinguish its effects from those of the skull.

The extension of computerized axial tomography to acoustic attenuation measurements

such as those of Hueter, et al., was reported at this meeting by Greenleaf and Johnson [4].

Such a procedure would appear to eliminate many of the problems associated with the Hueter

technique.

2. The Thermo-Acoustic Sensing Technique

2.1 Principle

TAST [5-7] has the ability to sense tissue characteristics at a point by making use of the acoustic absorption and the temperature coefficient of velocity. Two sound fields

are utilized. One, referred to as the "thermometer beam," is a parallel beam which is propa

gated into the tissue from one side and on its emergence from the other side is picked up by a receiver. The other field, referred to as the "heating field," is a focused sound

field whose focal volume falls along the thermometer beam's path.

In operation, a burst of thermometer beam sound is passed through the tissue and its

transit time recorded. The heating field is then activated and warms the tissue in its

focal volume which is in the path of the thermometer beam. A second thermometer beam burst

is then passed through the tissue and its transit time subtracted from the transit time

of the first thermometer beam burst. The resulting difference in transit times is the

output parameter of the system. This difference occurs because the sound velocity is dependent on the tissue temperature, which increased. The temperature rise is proportional

to the intensity of the heating field as well as to the acoustic absorption coefficient of

the tissue. The measured transit-time difference thus depends on the tissue's acoustic

absorption coefficient for the heating field frequency, its temperature coefficient of

velocity, and the intensity of the heating field along the thermometer beam's path.

2.2 System Geometry

The basic system is shown in figure 1. Thermometer beam transmitting-transducer A propagates a wavefront through the tissue D to the receiver B. In the process of going

through the tissue, the wavefront will be greatly distorted and become the perturbed plane wave which arrives at the receiver and acts as a transit-time reference for the system. The

heating-field transmitting transducer with its focusing lens C produces a cigar-shaped focal

volume along the path of the thermometer beam. The temperature changes within the tissue

are dependent on both the geometry of the heating field and the absorption coefficient

distribution in the tissue.

2.3 Theory of Measurement

The transit-time difference between the two thermometer beam bursts is directly pro- portional to the acoustic absorption coefficient of the tissue, the intensity of the

heating field where it interacts with the thermometer beam, the temperature coefficient of

velocity in the tissue; and is inversely proportional to the specific heat of the tissue,

its mass density, and the distance the thermometer beam travels through the focal volume.

It is convenient to divide the parameters which affect the difference in thermometer beam

transit times into three groups: one having to do with the type of tissue, another having

to do with the parameters of the system used for making the measurement. It can be shown

that the transit time difference between thermometer beam bursts before and immediately

after the heating field burst is given by:

154
FOCAL

VOLUME .TISSUE

I 1 X m )

) i)

E

z r/ \ / . THERMOMETER BEAM

TRANSMITTING

TRANSDUCER

THERMOMETER BEAM

(Approximate Plane Wave)

Acoustic Lens

I Piezoelectric

I Material

RECEIVING

TRANSDUCER

THERMOMETER BEAM

(Tissue Perturbed Plane Wave)

'HEATING

FIELD

HEATING FIELD TRANSMITTING TRANSDUCER

Figure 1. TAST System Geometry.

tj = K f

I-P-dx (1)

where

and

K = x/J,

P = (3V/9T)2a/V'^pC

(2)

(3)

K contains the constants of the system, including the heating beam burst length t, and the

mechanical equivalent of heat J. I is the intensity of the heating field which is assumed to

be a function of the distance x along the thermometer beam. P is the perturbation factor

containing the tissue characteristics which are the temperature coefficient of velocity

(3V/3T), the acoustic amplitude absorption coefficient a, the mass density p, the specific

heat C of the tissue, and the velocity of propagation V at the tissue temperature T.

TAST's insensitivity to intervening structures arises from the nature of the integration which is carried out along the path of the thermometer beam. Only those portions of

its path which have been modified by the energy input from the heating beam contribute to

the arrival time difference which is the output parameter of the system. Those portions of

the thermometer beam which lie outside the volume affected by the heating field make identical contributions to the total transit time before and after the heating field burst and

thus the difference between the two contributions, and their contribution to the integral,

is zero. The only spatial points that contribute to the transit time difference are those

which are heated by the heating field. Thus, since the integrand is zero wherever the intensity is zero, namely outside the influence of the heating field, the limits of integration

can be extended to infinity in both directions without affecting the result. Because tjie

tissue outside the focal volume does not contribute to the output, it would appear that the

system should be capable of working through heavily-interfering tissues such as skull.

Stated another way, the initial thermometer beam burst of each measurement cycle is used as

a reference which takes into account all of the diffraction and scattering effects on the

thermometer beam and cancels them out of the system output.

155
2.4 Differential Transit-Time Measurement Electronics

The difference in transit time between two successive thermometer beam bursts is taken, and no attention need be paid to the absolute value of the transit time. Because

the difference in transit times of the two bursts is so small, one may make the measurement by performing a phase comparison resulting in an analog signal which is then analogto-digital converted. The differences are taken digitally.

The phase-measurement system is shown in figure 2, where the master oscillator signal

is shown being fed to the phase comparator by two different paths. One is a direct electrical path, the other makes use of the thermometer beam as a transmission element. The

output of phase comparators such as double-balanced mixers are harmonic functions of the

phese-angle difference. In order to linearize the output of the phase comparator, we make

the output of the comparator a sine function of the phase difference and utilize the small

aigle approximation in which we assume that the output is proportional to the angle itself

ather than to the sine of that angle. This is done by adjusting the phase shifter until

the output of the phase comparator is zero.

THERMOMETER

BEAM

BURST

GENERATOR Tissue

PHASE

COMPARATOR

PHASE

SHIFTER

lllllMllliiltiiialilMAiiiumuil

TIMING

CONTROL

SYSTEM

0-Hami!

B

HEATING

FIELD BURST

OSCILLATOR

MASTER

OSCILLATOR

READOUT REGISTERS

Figure 2. TAST block diagram.

LOW PASS

FILTER

AND GATED

INTEGRATOR

ANA

TO Dl

CONVI

iLOG

GITAL

ERTER

COMMUTATOR

AND ADDER

The micro-timing diagram figure 3 indicates the details of phase evaluation of a single

thermometer beam burst. Since the thermometer beam burst is generated by digital techniques,

the output of the transmitter contains harmonics. This mode of generation insures phase

coherence between the burst envelope and the reference rf signal and is necessary to avoid

stop and start transients. The received signal contains no visible trace of the harmonics

present in the transmitter waveform after it undergoes transmission through two transducers

and experiences frequency-discriminatory transmission through the intervening medium. The

comparator output consists of a pulse having the shape of the burst envelope with some additional components at the acoustic frequency and harmonics of that frequency. The

amplitude of the pulse is proportional to the phase angle, in the small angle approximation.

The high frequency components are first removed by a low-pass filter and the remaining

signal is'integrated over the period of the "sample" time slot. The integrator cannot keep

up with the high frequency signals, but it does collect an appropriate charge at its input

terminal. After the signal ends, it requires a few tens of microseconds to reach its final

value and damp out the transients generated by this abrupt signal. The defects in the

signal are greatly exaggerated in the figure for the sake of visibility. The analog-todigital conversion takes place after the signal has stabilized. Since the time slots are synchronous with the master oscillator, the period of integration will always be synchronous

with the received signal for a given measurement with a given amount of tissue in the

thermometer beam's path.

156
Total Elapsed Time 250 //sec

MASTER OSCILLATOR VWWWWWWWWWWWWW

"START" SIGNAL

THERMOMETER _J1

BEAM TRANSMITTER

If

RECEIVER OUTPUT

DATA WINDOW

PHASE

comparator output

integrator output

a/d converter

"Don't Sample

1 "Sample" f

'Not Operating' J "operating"

Figure 3. Micro-timing diagram.

The rr.aaro- timing diagram of figure 4 covers a period of time approximately 500 times

that shown in the micro-timing diagram of figure 3. Each of the thermometer beam bursts

shown as a single vertical line represents the entire cycle shown in figure 3. It is seen

that the micro-timing activities are repeated eight times before the heating field is turned on, during a total elapsed time of 3 milliseconds. Then the heating field is turned

on for 100 milliseconds, and after that, the micro-timing activities are again repeated

eight times. The digital result from the eight thermometer beam bursts which precede the

heating field burst, labelled A, are added to a register, while the result from the eight

bursts which occur after the heating field burst, labelled B, are subtracted from that

register. The difference remaining is the time-averaged representation of the time difference

td caused by the TAST interaction described above.

HEATING

FIELD

ON

OFF

100 msec

THERMOMETER

BEAM

1 micro time

(See Fig 3)

Figure 4. Macro-timing diagram.

157
3. P Factor, Absorption, and Temperature Coefficient of Velocity

The perturbation factor P (eq. (3)) is the product of the temperature coefficient of

velocity (3V/3T) times the acoustic absorption coefficient a, divided by the density p, the specific heat C, and the velocity of propagation V. We expect the density, specific

heat and velocity to be reasonably constant in tissues. The temperature coefficient of

velocity on the other hand could be expected to vary considerably from one material to another Further, the temperature coefficient of velocity of water is known to vary over

a three to one range from 0°C to 37°C [8], and thus it would not be surprising if it

varied from tissue to tissue.

The absorption coefficient is known to be extremely sensitive to tissue types. Thus,

t'le temperature jump caused by the heating field varies widely between tissues and in a different fashion for different tissues. For example, the ratio of temperature rises in water and bone, both exposed to the same ultrasonic field intensity, is of the order of

1:2800. Even various types of brain tumors exhibit greatly differing absorption coefficients. For example, [1] a meningioma has some 2.5 times the absorption coefficient of an oligodendroglioma. The degree of heating in the focal volume is thus a very good indication of

tissue types It is presently uncertain as to whether the temperature coefficient of

velocity does vary from tissue to tissue, but even if this is not the case, the P factor can

be expected to exhibit such variation £6], and therefore should be useful in the characterization of tissues.

5. Normal Anatomy

Of the three major body cavities, the intracranial cavity seemed desirable as an ex- perimental subject because of: (1) the lack of interfering gas pockets; (2) the potential

of limiting motion of the head by fixation; and (3) TAST's differential nature which allows

it to operate through interfering structures such as the skull. This is not to imply that

motion problems would not be a serious complication in the TAST system.

Readily-available formalin-fixed human brain was used in initial experiments. The

experiences of Hueter, Bolt and Ballantine [2] seem to indicate strongly that our thermometer beam would pass through in vivo skull when the next stage of experimentation was reached Fry [3] indicated that energy can be deposited in a localized volume of tissue

by a focused sound beam penetrating the in vivo skull as required for our heating field.

5.1 Experiment

This intial work was concerned only with the measurement of normal structures along

a line passing through cortical and Sylvian fissures, internal capsule, basal ganglia, and

ventricles, as shown in figures 6-8, to determine if these structures were distinguishable.

We placed an intact fixed human brain in the brain holder shown in figure 5. This was in turn enclosed in a plastic box to protect the transducer system from biological fluids.

The thermometer beam passed through the brain coronally in a side-to-side fashion. Ihe heating field penetrated through the top portion of the inverted brain. The scan was pro- duced by moving the focus of the heating field along the path of the fixed thermometer

beam. The point of measurement was always the intersection of the two fields. The heating

field focus was moved in 0.1 in steps through the brain. These increments were deliberately

chosen because they were smaller than the Airy circle (0.150 in) for the 940 KHz field,

formed by our f/2 lens. It will be seen below, that this predicted limit of resolution for our system may have been too conservative, interfering phenomena are of several types. A sound field passing through a fluid carries momentum. When the sound intensity decreases

due to absorption, the sound momentum cannot be lost and appears as a flow of fluid in the same direction as the sound beam. If this flow pattern is perpendicular to the thermometer

beam, as in this case, the interference takes the form of a slight second-order Doppler

shift of the type often described in connection with the Michaelson-Morley experiment.

When such a flow occurs, two different phenomena arise. One effect takes place when

the heating field is focused in fluid, and streaming through the focal point occurs. Such

streaming is sensed by the thermometer beam and results in large TAST numbers. These

numbers permit us to identify large fluid-filled cavities. Another effect occurs when an even larger-scale streaming pattern is generated by the heating field in the fluid outsxde

158
the tissue. This pattern may extend into the path of the thermometer beam far from the

focal point inside the tissues. These flow patterns disrupt the stability of the thermometer

beam's path and may completely obscure TAST data. The second effect can easily be prevented

by enclosing the thermometer beam in an undisturbed medium. This is the purpose of the

streaming shield tubes shown in figure 5. The flow patterns inside the box have been found

to be much more serious than those outside. An internal streaming shield appears to provide

adequate protection for the thermometer beam.

THERMOMETER

BEAM

TRANSMITTER

Illlllllllllll IIIMIIIIMIIIIMIIIIIIIIIIll IIIMIIIIIIIIIIIIMIMIIIIIIIII

STREAMING

SHIELD

TUBE

Figure 5. Brain mounting system.

€

THERMOMETER

BEAM

RECEIVER

STREAMING

SHIELD TUBE

HEATING FIELD

TRANSDUCER AND LENS

streaming phenomena which occur near bubbles also cause very serious interference when

they are excited in the heating field [10]. In addition, excited bubbles vibrate the

tissue and introduce interfering Doppler shifts.

In this preliminary experiment, the brain was not as rigidly secured as it might have

been and probably moved during the measurements. On this basis alone, it is to be expected

that the TAST values and brain structure will not correspond perfectly in all areas. The

validity of brain structure-TAST relationships is inferred by two observations: (1) the

close correlations of the two successive TAST measurements at given points in the same run; and (2) the fact that only minor displacements of the TAST curve are required to make large

segments of that curve correspond very closely to brain structures.

Data analysis of three runs (figs. 6-8) through the same brain loci and comparison of

TAST data and brain structure are facilitated by a composite representation. Superimposed

on top of the pertinent coronal section of brain are the measured relative values of time

delay tj plotted vertically. The best estimate of where the thermometer beam passes is shown by the heavy black line drawn across the coronal section. Variations of cerebral

anatomy are intended to lie perpendicularly below the TAST profile. Several aspects of the

data suggested this correspondence.

The expected streaming artifacts are seen. Streaming effects at the edge of the brain

are seen at the left side of the first run (fig. 6) and again on the right side of the brain

in the second run (fig. 7). Additional streaming phenomena show up in the ventricles and

give large peaks in all three runs.

A bubble artifact may also have been present. In each of the three runs, a large peak

was seen 1-1/2 to 1-3/4 in from the left. These peaks were over four times the height of

the ventricular peaks and therefore were truncated for scaling reasons in the profile. A reasonable explanation for these peaks would be a bubble lodged in the Sylvian fissure near

159
the heating focus. Since water has a calculated P factor of about l/300th that of brain,

it is not surprising that the slit-like water filled portions of the same fissure exhibited

low TAST values. This is in contrast to the situation in the ventricles where sufficient

volume exists for streaming phenomena.

Figure 7. Coronal section of fixed human brain. Dark lines through basal ganglia

indicates thermometer beam path, and superimposed curve with zero reference line

represents TAST measured values during run # 2.

160
The most obvious correlation between the TAST profile and the coronal brain structure

would appear to be the large notched central peak, surely representing the ventricles. The

interhemi spheric cleft would seem to be too narrow and asymmetrical to account for this

symmetrical peak. Also the interhemispheric cleft is nowhere near the supposed focus of the

system. The total width of the lateral ventricles where crossed by the thermometer beam

was 5/8 in. This correlates well with the large central peak in the TAST profile. First

inflection points were used in figures 7 and 8 and second inflection points in figure 6. At the present time, it is not clear why the second inflection points corresponded to ventricle edges in the latter case.

Figure 8. Coronal section of fixed human brain. Dark line through basal ganglia

indicates thermometer beam path, and superimposed curve with zero reference line

represents TAST measured values during run # 3.

The distance from the midpoint of the septum to either ventricular wall measured

5/16 in, placing the septum in the center of the lateral ventricles as expected. Within

an error of 1/32 in, the dip in the ventricular peak measured 5/16 in from the first inflection points in figures 7 and 8 or the second inflection points of figure 6. Therefore,

the dip, centrally placed in the ventricular peak, corresponds to the septum. It is theorized that TAST has the resolution to see the septum which is a little less than

3/16 in wide. This corresponds to a volume of 0.002 in^. Since the midpoint of the

interhemispheric cleft is 1-3/4 in above the presumed focus in the septum, it most likely

does not account for this dip. Furthermore, the thermometer beam is located well below

the cleft.

The lateral boundary of the internal capsule was 3/8 in from the lateral wall of the

lateral ventricle. Three-eight.s of an inch to either side of the first inflection point

in figures 7 and 8 and the second inflection point in figure 6 are a depression and rise.

Sharp peaks are seen within these bounds in figure 7. Whether the capsule is represented

by the low point or the higher shoulder is not clear.

The lateral boundary of the putamen (part of the basal ganglia) was 1-1/8 in from the

septum. This corresponds on the left §ide to a segment of the profile extending from the

lateral margin of the capsular Doundary to the initial rise of the off-scale peak thought to

be associated with the hypothetical bubble mentioned earlier. A mid-segment peak is more

prominent in figures 6 and 7 than in figure 8. The comparable TAST segment on the right side

encompasses one distinct peak in figures 6 and 7 and possibly a smaller one in figure 8.

161
These findings are of sufficient symmetry to suggest that capsular/putaminal and

putaminal/insular boundaries are recognized. From the data regarding internal capsule and

adjacent putamen, it is unclear as to which has the greater TAST value. To settle this

point, the signal-to noise-ratio of the system has been reduced and separate slices of grey

and white matter from a formalin-fixed brain are in the process of being evaluated.

The 3/8-in width of the insular and subinsular structures on the left are encompassed

by the off-scale peak thought to represent a bubble in recesses of nearby fissures. The

1/2-in width of insular and subinsular structures on the right, when superimposed on the

TAST profile, singles out a hump that is smoothest in figure 6, less so in figure 7, and

somewhat bimodal in figure 8.

There are three dips below the baseline in the TAST profile that correspond in width

to the two recesses of the sylvian fissure on the left and the larger recess on the right.

Although the matching is not perfect, the 5/16-in and 1/2-in gyri on the left are associated

with prominent peaks in the TAST profile of about the same width. The more medial peak in

each of these instances is higher than the more lateral bimodal peak. On the right, the

1/4-in gyrus matches the first rise and fall of the TAST profile superimposed above it.

Whether the final and most lateral TAST peak represents the dura or the dura/water effect

is unclear.

In all these profiles, the TAST baseline was increasing from left to right. Whether

this represents acoustical or electronic drift, is unclear. It might also represent an altered condition of the brain. However, with regard to either hemisphere of the brain, the

different tissue peaks do seem to have reproducible absolute and relative TAST values.

Throughout this analysis, it has been assumed that the superficial gyri pattern does not account for the TAST profile because the focus of the system was on the average two inches or more within the brain substance. Refraction of the heating field entering the convex surface of the brain is not thought to be a major consideration at this time.

Reviewing the TAST profile/coronal brain correlation, certain points seem tenable:

(1) the ventricles are readily identifiable and measurable; (2) the septum is discernible,

suggesting the resolution of the system to be at least 1/8 in or an equivalent volume of

0.002 in^; (3) intracerebral boundaries between grey and white matter can be distinguished;

and (4) a suggested difference in TAST values between putaminal grey and capsular white

matter was at the limit of resolution of the apparatus.

6. Abnormal Anatomy

TAST-obtained information may be particularly useful in the management of stroke,

head injury and tumors, and in the identification of lacunar infarcts in basal ganglia. In view of TAST's theoretical and tentatively demonstrated ability to differentiate tissue

types, detection of edema and infarction is conceivably within reach. Absence of cerebral

infarction in the first few hours following hemiparesis or aphasia would be particularly

valuable in deciding whether to do emergency cerebral revascularization— such as carotid

endarterectomy or superficial temporal -middle cerebral anastomosis. The effectiveness of

such procedures is thought to be less [11] if true infarction is underway. At the earliest,

brain scans do not turn positive until late in the first week following stroke. This is too late in many instances to be helpful in making this early surgical decision.

In head injuries, evaluation of the seriousness of the insult by current measures has

many inaccuracies. Intracranial pressure measurements alone, pressure/volume curves, and

cerebrospinal fluid biochemical determinations might be augmented by a numerical value for

the degree of injury at selected sites. TAST may supply such data.

In managing patients with tumors, it would be advantageous to distinguish the malignant

glioblastoma from the benign meningioma, and thus save operations in hopeless cases. P factors have been calculated (without regard to the variation of the temperature coefficients

of velocity [6]) indicating that various tumor types may well be identifiable. No information on glioblastomas per se is available.

TAST may also be able to identify radiologically-invisible lacunar infarcts in basal

gangl ia. 162
7. Summary

TAST measures a tissue property proportional to the product of the absorption

coefficient and the temperature coefficient of velocity, both of which appear to be highly

sensitive to tissue types. Initial measurements strongly suggest the system's ability to identify and differentiate between normal tissues in brain, and possibly to make identifications in volumes as small as 0.002 in Intracranial uses for the system may include the analysis of stroke, head injury, tumor, and perhaps identification of lacunar

infarcts.

The authors should like to express their appreciation to the Sloan Foundation for

its partial support of this work.

References

[I] Yukishita, K. , Tanaha, K., Ito, K., Ehara, K., and Watanabe, H., Ultrasonic diagnosis

of brain tumors, in Froaeedings In Eaho-Enoephalography, Proceedings of the Inter- national Symposium on Echo-Encephalography , Erlangen, Germany, 1967 (SpringerVerlag, 1967).

[2] Hueter, T. F. and Bolt, R. H., An ultrasonic method for outlining the cerebral

ventricles, J. Acoust. Soa. Am. 22_, 160 (1951 ).

[3] Fry, W. J. and Fry, F. J., Ultrasonic visualization of soft-tissue structure based

on gradients in absorption coefficients, J. Acoust. Soa. Am. 3b_, 1788 (1963).

[4] Greenleaf, J. F. and Johnson, S. A., Algebraic reconstruction of spatial distributions of acoustic velocity and attenuation in tissues from time-of-fl ight and

amplitude profiles, this volume (p. 109).

[5] Sachs, T. D., Welt, A. J. and Slayton, P. W., Thermo-acoustic sensing technique-TAST,

in Proceedings of IEEE Ultrasonics Symposium, P. 54, (IEEE, Cat. No. 72 CHO 708-8 SU,

New York, 1972).

[6] Sachs, T. D., Potential of TAST for measurements of perfusion, ultrasonic absorption and intensity- at a point, in Proceedings 197S IEEE Ultrasonic Symposium, p. 52

(Cat. No. 73 CHO 807-8 Su, IEEE, New York, 1973).

[7] Patents: U.S. 3,771,355, French 2, 155,465; other U.S. and foreign patents pending.

[8] McSkimmin, H. J., Velocity of sound in distilled water for the temperature range

20° - 75°C, J. Acoust. Soc. Am. 37, 325 (1965).

[9] Fry, W. J., personal communication (April 1973).

[10] Devin, C, Jr., Survey of then ~il , radiation, and viscous damping of pulsating air

bubbles in water, J. Acoust. S',j. Am. 31_, 1654 (1959).

[II] Crowell, R., personal communication (April 1975).

163

CHAPTER 6

SCATTERING TECHNIQUES

165

National Bureau of Standards Special Publication 453. Proceedings of Seminar on Ultrasonic

Tissue Characterization held at NBS, Gaithersburg, MD, May 28-30, 1975. (Issued Oct. 1976)

CHAPTER 6. SCATTERING TECHNIQUES

Paper 6.1: TISSUE CHARACTERIZATION BY ULTRASONIC FREQUENCY-DEPENDENT

ATTENUATION AND SCATTERING^

P. P. Lele, A. B. Mansfield, A. I. Murphy,

J. Namery, and N. Senapati

Laboratory for Medical Ultrasonics

Massachusetts Institute of Technology

Cambridge, MA 02139

Studies conducted in this laboratory to explore the feasibility of utilizing

acoustic impedance, attenuation, and scattering characteristics of tissues for

enhancing the diagnostic capabilities of ulirasound are described. Frequencydependent ultrasonic attenuation is found to be sufficiently greater in infarcted

or otherwise necrotized tissues than in normal controls to permit their positive

identification. Superficial and internal scattering properties of tissues hold

the promise of being significant for diagnostic applications. The difficulties

that will have to be overcome to successfully utilize these properties are discussed.

Key Words: Acoustic impedance; Bragg diffraction; computer processing; frequency

dependent attenuation; internal scattering; myocardial infarction; scattering;

surface scattering; tissue characterization; ultrasound diagnosis; ultrasonic

spectroscopy.

1. Introduction

This paper summarizes the work conducted in this laboratory on the utilization of the

acoustical impedance, attenuation and scattering properties for tissue characterization.

Differences in the acoustic impedance and attenuation of various normal and abnormal

tissues were studied under a variety of known and controlled ultrasonic field conditions.

These were found to be quantitatively significant and could be correlated with differences

in tissue structure and pathological changes. Differences in scattering from the surface

as well as the interior of normal and pathological tissues indicate that studies of acousti

cal scattering could provide important information on tissue structure in a non-invasive

manner.

Different amphibian and mammalian organ samples were studied in vitro and in vivo.

Heat, vascular occlusion and chemicals were used for induction of controlled pathological

changes in different experiments.

2. Acoustic Impedance

Fresh specimens of normal and infarcted myocardium were obtained from the heart of

thoracotomized dogs 20 to 30 minutes after the ligation of the circumflex branch of the

left coronary artery. Pieces of myocardium were excised and placed in a bath of normal

saline. Damped ultrasonic transducers with resonant frequencies of 1 to 5 MHz were coupled

to the specimens with a column of degassed normal saline which also acted as a delay line.

By means of conventional pulse-echo techniques, the orientation of the transducer with re- spect to the specimen was adjusted to obtain the maximum echo amplitude from the salinemyocardium interface. The echoes thus obtained were compared with echoes obtained from

targets of known acoustic impedance, e.g., glass, plexiglass, and soft polyethylene.

Comparison of figures la and b, typical of the results obtained, shows that the acoustic

impedance of infarcted myocardium is consistently lower than that of the normal myocardium.

^This work was supported in part by the U.S. Public Health Service (grants FD-00680, CA- 16111, GM-19706 and contract NOl-HV 22017).

167
These differences were also found to remain unchanged over a period of approximately 30

minutes during which observations were continued. The absence of progressive change in the acoustic impedance over periods of 30 minutes at temperatures of 37° C or lower is consistent with previous observations in the cat brain in vivo [1].^

Figure 1. Maximized echo (rectified envelope of the RF pattern) from front surface

of excised canine myocardium in saline: (a) normal myocardium, (b) infarcted

myocardium. Vertical bar = 5 volts; horizontal bar = 2 ys. Note that the

amplitude of the echo from the infarcted myocardium is 3.8 volts compared with 7 volts from the normal myocardium.

Since echo amplitude is highly dependent on target orientation [2], differences in the amplitudes of the echoes from the normal and infarcted myocardium are indicative of

the differences in the acoustic impedance of the tissues only when both are measured under

identical conditions of transducer-tissue surface orientation. In diagnostic situations

in vivo, the orientation of the interface with respect to the transducer will vary with

cardio-respi ratory movements from point to point and even at the same point. Simple,

direct measurement of the echo amplitude from the accessible surfaces of organs in vivo,

e.g., the myocardium, thus cannot be of diagnostic significance in clinical applications.

Ultrasonic attenuation in biological tissues has previously been shown to rise precipitously on heat necrotization or thermal denaturation [1,3,4] and a similar but slower

increase in attenuation was found to occur with sustained anemic damage in the cat brain.

It is, therefore, plausible that measurement of acoustical absorption or attenuation may

help to differentiate abnormal from normal tissues. The absorption coefficients of

tissues are also known to increase with frequency, the slope of this dependence varying

with the type of tissue [5]. In a previous study, the curves for absorption at different

frequencies were found to be significantly different in astrocytomas than in normal brain,

the absorption at any frequency being higher in the astrocytoma than in the normal brain

[6,7]. Thus, the frequency-absorption slope may be expected to change significantly when

the tissue is necrotized and thus permits the differentiation of this tissue from normal

tissue.

In the field of nondestructive evaluation (NDE) of materials, frequency-domain analys

of a single broadband ultrasonic echo before and after its passage through a specimen has

been shown to contain enough information on the frequency-dependent attenuation properties

of the specimen to permit its characterization [8,9]. Since with this technique, the

entire curve of the frequency-attenuation characteristics can be obtained with a single

Figures in brackets indicate the literature references at the end of this paper.

3. Acoustic Attenuation

3.1 Rationale

3.2 Broadband Ultrasonic Technique

168
interrogation, it should permit differentiation in vivo of normal from infarcted myocardium,

provided that the angle of incidence of the interrogating ultrasound is not a critical

factor and that the single echo could be captured and analyzed in the frequency domain.

Experiments were first conducted on "stationary" samples of skeletal and cardiac muscles

in vitro, using a slowly-sweeping spectrum analyzer. On finding that the technique, in

fact, does permit differentiation of infarcted from normal myocardium, a computer-based

data acquisition system for capturing and analyzing a single echo was developed.

The instrumentation used initially was basically that of a pulse-echo, A-scope ultrasonograph. A highly-damped (Q-1 ) broadband transducer (10 MHz bandwidth) was shockexcited by a pulser (300 volts step, 10 ns rise time). The echoes received by the same transducer were fed into a wideband, low-noise amplifier (-3dB at 50 kHz and 17 MHz; 40dB

gain). The transducer loop response was measured in the conventional manner by using a standard reflector, consisting of a flat, thick glass plate placed parallel to the face of

the transducer to ensure normal incidence of the interrogating beam of ultrasound. The

echoes were gated repetitively into a slowly-sweeping spectrum analyzer as well as into an oscilloscope. The A-scope display thus provided information on the echo amplitude or on

( the target impedance, whereas the spectrum analyzer displayed the spectral energy content,

I or the Fourier transform, of the echo signal, i.e., the loop response of the system (figs.

:' 2a, b). It should be emphasized that the reference reflector (or any other target) has to remain stationary over approximately 2000 interrogations by the ultrasonic pulse for the r spectrum analysis to be performed.

Figure 2. (a) Characteristic echo of broadband transducer (10 MHz bandwidth) re- ceived from the first surface of a flat reflector (aluminum in saline). Vertical,

100 mv/div; horizontal, 100 ns/div. (b) Fourier transform of calibration echo

in (a) measured by repetitively gating the above echo into a slowly-sweeping,

analog spectrum analyzer. Total sweep time is 2 seconds. Vertical scale,

linear amplitude; horizontal scale, linear frequency (bar = 1 MHz; vertical

marker at left is DC or 0 MHz)„

Introduction of a tissue specimen {e.g. , muscle) between the transducer and reflector

leads to frequency-dependent attenuation of ultrasonic energy and hence, to a change in both the amplitude and the shape (spectral energy content) of the echo from the reflector.

Figure 3 is the spectrum of the echoes through a freshly-excised, healthy, mammalian

skeletal muscle (approximately 1 cm thick). Figure 4 shows the spectrum obtained under

comparable experimental conditions from a freshly-excised muscle, the vascular supply of

which has been occluded 24 hours earlier. For comparison, figure 5 shows the spectrum

from a normal muscle stored in normal saline for three hours after excision. Note the

faster high-frequency roll -off in both figures 4 and 5. Comparable results were obtained

in similar experiments on skeletal muscles with localized areas of heat necrotization and

infarction by vascular occlusion and from in vitro experiments on specimens of normal

myocardium and anemic infarcts. The slope of the frequency-dependent attenuation {i.e.,

the slope gf the roll-off) characteristically is steeper for the infarcted tissue than in the normal control specimens. Thus, basically, the frequency spectrum of the ultrasonic

signal contains enough information on the tissue it has traversed to permit characterization

169
of the tissue as normal or necrotic. Additionally, it was observed that specimens of

skeletal muscle obtained 4 to 8 hours after vascular occlusion did not show attenuation

slopes characteristic of necrotization (compared to control specimens), whereas specimens

obtained 10 hours or later after vascular occlusion, invariably did so. This correlates

well with the results of Moore, et al. , [10] and Stenger, et at., [11]. Again, in the

heart, changes in attenuation slopes (and in the ECG) were absent or negligible with a low

L.A.D. ligation (which is known to cause a diffuse infarct) even after 6 hour survival,

whereas a high circumflex ligation (which produces a solid infarct) caused obvious changes

in the attenuation slopes (and ECG) even with relatively short survival times (2 to 3 hours). The ultrasonic diagnosis was confirmed by histological and ul trastructural examination

in each of these cases.

Figure 3. Spectrum of reflector echo after traversing 1 cm thick normal skeletal muscle,

freshly excised. Same scales as figure 2b.

f Figure 4. Spectrum of reflector echo after traversing same thickness of infarcted muscle

excised 24 hours after ligation. Same scales as figure 2b.

It is germane to point out here that the power density spectrum and pulse shape are analogous and that frequency-doman analysis does not generate new information that is not contained in th? (t'^me- domain) pulse itself. Frequency-spectrum analysis or Fourier

transformation, however, is the most effective and simplest way to study pulse shape

details and to differentiate between two almost identical pulse shapes. Differentiation

can be attempted - and was - by waveform pattern recognition (i.e., location of oulse

maxima, minima, zero crossing and slopes) which is much more complex than Fourier analysis.

Furthermore, comparison of the power density spectra yields a direct measurement of the

frequency-dependent attenuation which correlates well with histopathological changes in tissues

.

3.3 Target Orientation: Effect of Off-Normal Angles of Incidence

of the Interrogating Beam

With the interrogating beam of ultrasound incident on the reflecting interface at off-normal angles, not only does the amplitude of the echo diminish markedly [2] \to 1/10

with 6°, 1/100 with 12°), but also its shape (and Fourier transform) changes drastically

(fig. 6). The magnitude of this change is directly proportional to both the ultrasonic

170
Figure 5. Same as figure 3, but muscle was stored for 3 hours in 20 °C saline.

beamwidth and the degree of off-normal angulation and is due to phase cancellations resulting

from different path lengths between the transducer and target. Reduction of the ultrasonic

beamwidth at the target by the use of focused transducers effectively eliminates this

problem (fig. 7), extending the usefulness of the technique to off-normal target orientation.

Use of a focused beam also substantially improves the lateral resolution of the system

which is proportional to the diameter of the ultrasonic beam at the interface. Dynamic

tracking of a moving interface with a concentric annular-ring phased-array transducer [12]

to retain the interface at the focus can be expected to yield a lateral resolution of

approximately 1 wavelength.

In more than 50 skeletal muscles and 16 dog hearts with induced infarctions used in

these studies, the results obtained were very similar to those in skeletal muscle shown in

figs. 2 to 5. From measurements made on the photographs of the spectral energy content of

the second surface echo {i.e., after attenuation by 2 transits through the sample) as displayed on the spectrum analyzer, graphs of the energy content of the echo at different

frequencies were plotted. From fiqure 8, which is typical of results obtained in cardiac as

well as skeletal muscle, it can be seen that the amplitude, at 7 MHz, of the echoes that

had passed through an infarct is less than half that of the echo through the normal tissue.

The difference between the echoes through the infarcted and normal muscle becomes less

pronounced as the frequency decreases, being negligible at frequencies below 2 MHz. However, it should be noted that the energy content in the interrogating pulse itself

falls off rapidly below about 3.5 MHz, (see fig. 2b). This is presently corrected in the

software. A frequency-sweep (chirp) technique and amplitude modulation has been employed

in order to equalize the energy content at all frequencies above 1 MHz. It is planned to interrogate the tissue by paired bursts (approximately 5 ys in duration) at two frequencies.

The first burst, at about 2 MHz, will be used to compare successive targets and normalize

data; the energy in the echo at the higher frequency ('^'5 MHz) will characterize the taraet

as normal or necrotic. Matched filtering of the echoes will be digitally implemented to preserve the axial resolution - as is commonly done in other signal detection techniques.

3.4 Instrumentation for in vivo Applications

The application of this technique to tissues in vivo, however, presents several

problems due to the continual cardio-respiratory movements. As stated above, real-time

spectrum analysis requires that the same signal is fed repetitively (approximately 2,000

times which under normal operating conditions requires approximately 2 s) into the slowlysweeping spectrum analyzer. The motions of the body structures preclude the possibility

of obtaining a stable, repetitive signal. A digital, on-line, signal acquisition and

processing system has therefore been developed. The single, gated echo signal is directly

digitized, and fed into a computer for processing and into a disc for storage. The computer

performs a fast-Fourier-transform (FFT) of the echo and calculates the frequency-dependent

attenuation, taking into account the loop response characteristic of the transducer and

the specimen thickness at the focus of the interrogating ultrasonic beam in the tissue

specimen. To minimize electronic variability, FFT's of 16 consecutive echoes are averaged

in the computer for stationary targets. Various interrogation methods have been developed

171
for rapidly-moving structures, e.g. , the heart; some of these have been described in a previous paper [13]. The results yielded by these techniques are the same as those yielded

by analog spectrum analyzers with repetitive interrogation.

(a) Cb)

Figure 6. Effect of off-normal angles of incidence of unfocused interrogating

beam on Fourier transform of the echoes. The ultrasonic beam was incident

normal to the target in records al and bl . Records 2 and 3 were obtained when

the angle of incidence was increasingly off-normal.

3.4 Results in other Tissues

Results of some in vitro studies on bovine liver, kidney, skeletal muscle, and cardiac

muscle are shown in fig. 9. Each of the organs, obtained from freshly-killed animals, was

172
FREQUENCY (MHz)

Figure 7. Effect of off-normal incidence of a focused beam for ten different angles.

Target angulation, similar to that in figure 6, has relatively little effect on the Fourier transforms.

cut into several (6 to 10) blocks, 5 to 20mm in thickness and with parallel surfaces.

These were placed on glass block sample holders immersed in a controlled temperature bath

of normal saline. Attenuation curves were obtained at graded (15 to 30 minutes) intervals

over periods of up to 30 hours. Necrotization of tissues was effected by immersion into

normal saline at 55° C for 1 hour or by formalin-fixation. The results obtained showed

remarkable consistency and were not affected by time, provided the temperatures were below

40° C. In fig. 9, note that although the attenuation coefficients for each of the normal

tissues are different from each other at the lower frequencies, they increase markedly at

higher frequencies. The slope of the frequency-dependent attenuation is also different

for different tissues. The slopes are also markedly steeper for necrotized tissue as compared to the same normal tissue.

Comparable results have recently been obtained in measurements of the absorption co- efficients by the thermo-electric method. i\s discussed below, heat-necrotization or formalinfixation of tissues does not lead to an increase in the amount of energy scattered internally.

The increased attenuation in necrotized tissues thus appears to be primarily due to an increase

in absorption.

173
23456789 10 | FREQUENCY (MHz) |

i

Figure 8. Typical results showing the frequency-dependence of the amplitude of echoes

j that have made two passes through normal, ischemic and infarcted muscle of equal

thickness. Infarction was produced by vascular occlusion. The curves are obtained

' by dividing the observed spectra (such as those in figures 3 and 4) by the calibration^

spectrum (as in figure 2b).

These studies are being extended to tissues in vivo, in animals with induced pathology.

Hardwired, stand-alone instrumentation for the detection of the differences in slopes o-f

[ frequency-dependent attenuation in relatively stationary targets is also under development. ' Measurements on dynamically-moving structures, e.g., the heart, require the use of a ; computer. The design of such a computer-based system has been described previously [13] .

j;

r 4. Acoustical Scattering !'

Current ultrasonic techniques of tissue visualization are based on specular reflection

j of ultrasound from tissue interfaces. At frequencies of 5 MHz and above, the wavelength of \ ultrasound in the tissue is of the order of the tissue surface undulations. Hence, a signi- j' ficant amount of ultrasonic energy may undergo Rayleigh scattering. Detection of such '

174
NECROTIC LIVER

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NORMAL LIVER

NORMAL MUSCLE

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NORMAL KIDNEY^/^/

/ /

/

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8.0

CORTEX

A-—A NECROTIC

KIDNEY

CORTEX

6.0

4.0

FREQUENCY (MHz)

Figure 9. Frequency-dependent attenuation in normal and necrotized mammalian

liver, muscle, and kidney. Each line represents the results obtained in /50 or more measurements made in 15-20 specimens in each type of tissue. The

data were obtained using the computerized acquisition and processing system

described in the text. The variance in the results was small and is omitted

for clarity.

scattered radiation and knowledge of its functional dependence may yield information on tissue interface or organ surface characteristics that is not currently obtained from

pulse-echo techniques. Similarly, internal inhomogeneity in an organ, due to its microstructural organization, normal or pathological, may lead to internal scattering. Both of

these phenomena have been studied in this laboratory over several years.

4.1 - Surface Scattering

A theoretical model of the ultrasonic surface scattering was developed based on a statistical formulation of the rough surface as a function of the surface undulation

parameters [14, 15]. The functional dependence of ultrasonic scattering intensity from

rough surfaces on frequency, scattering angle, and surface root-mean-square roughness was

175
studied semi-empirically. The validity of the theoretical model was verified by experimental studies of ultrasonic scattering from aluminum surfaces of known roughness parameters

(figs. 10, 11). Experiments were then conducted on fresh, isolated muscles (gastrocnemius,

rectus abdominis) and liver of the frog. The results showed a characteristic angular

dependence and a distinct increase in scattered intensity with frequency as predicted by

the model and could be correlated with the differences in the surface texture of different

muscles (figs. 12, 13) and liver (figs. 14, 15a). In contrast, the surface scattering

from a specimen of a liver with red-leg disease, which leads to pitting of its surface,

showed diffuse scattering (fig. 15b), varying randomly, irrespective of the scattering

angle. Microscopically, liver with red-leg disease displays the presence of numerous irregularly-dispersed micro-emboli on the surface as well as in the parenchyma (fig. 16).

This randomly-distributed pitting is believed to lead to diffuse scattering. Details have

been presented elsewhere [14, 15]. Mountford and Wells [16] also found it possible to differentiate between normal and cirrhotic liver by processing A-scope echoes.

Figure 10. Ultrasound scattering from a rough (0.0025 in rms) aluminum surface.

4.2 Internal Scattering

4.2.1 Introduction and Theory

In contrast to the irregular spacing of the micro-emboli in the frog liver with red-leg

disease, the microscopic structures of normal as well as many pathological tissues show

characteristic patterns of organization. From an acoustic point of view, these patterns

may be regarded as exhibiting characteristic spacinqs of acoustically-different tarnets

,

which will behave as diffuse scatterers due to their small size relative to the ultrasonic

wavelength.

176
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o

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• 5 MHz

EXPERIMENTAL a 10 MHz

( o 30 MHz

THEORETICAL

-80 ' ^ ^ 1 0 5 10 15

SCATTERING ANGLE (Degrees)

Figure 11. Ultrasound scattering from a rough (0.005 in rms) aluminum surface.

Very little research has been aimed at characterization of tissue on the basis of its

scattering interactions with ultrasound. Scattering has been considered a nuisance which

blurs the images obtained in echo techniques, especially B-scan, but not as a useful

diagnostic parameter.

If changes in scattering characteristics could be correlated with specific tissue

structure and pathologies, this property could become a valuable diagnostic aid. Preliminary

to in vivo studies, tissue samples were examined in vitro to determine the feasibility of

detecting tissue structure differences on the basis of the internal scattering properties

of the various tissue samples investigated. The samples chosen exhibited great structural

differences which could cause a variation of scattering patterns, each characteristic for

the tissue under study. If these rather gross differences could be detected, it may prove

possible to investigate the smaller differences in scattering which occur in certain

pathological states, and correlate these with the specific disease processes.

The prediction that differences in scattering will be apparent for different tissues,

both normal and pathological, is based upon a physical theory of scattering and diffraction

of waves which has been used to great advantage in x-ray crystallography. Wavefronts impinging upon a regular array of small reflecting surfaces produce interference patterns which

depend quite specifically upon the physical parameters, such as the spacing of the array.

Beam components are selectively reinforced or cancelled according to the relative spacing and

orientation of scatterers in the beam.

177
100

0 2 4 6 8 10

SCATTERING ANGLE (Degrees)

Figure 12. Ultrasound scattering from surface of gastrocnemius muscle of frog.

Ultrasound may be used to determine the acoustical structure of tissue, on a scale

corresponding to the wavelengths employed, in a fashion completely analogous to x-ray

crystallography. The underlying concept is the relation between the spacing of tissue

elements, the ultrasonic wavelength, and the scattered signal. There is a selective

reinforcement of certain frequencies, such that the Bragg scattering condition,

nx = 2d sin 0,

where >^ = ultrasonic wavelength

n = integer

d = distance between adjacent scatters

0 = angle from the horizontal to the scattered signal,

is met. Integral multiples of the wavelength are required for constructive interference to occur.

The formula is derived by considering path length differences such that the scattered

waves are exactly in phase, yielding maximum constructive interference. This relationship '

is illustrated in figure 17. I

178
J L 0 2 4 6 8 10

SCATTERING ANGLE (Degrees)

Figure 13. Ultrasound scattering from surface of rectus-abdominis muscle of frog.

The tissue may be characterized by either fixing the frequency (and hence x), and then

varying the angle, or by fixing the angle 9 and sweeping the frequency so that differences

in rath length vary over a number of wavelengths. Theoretically, either technique should

yield a succession of signal amplitude peaks whose spacing is indicative of the target's

internal structure.

If one considers a perfect lattice in which the acoustical variations are a series of

uniformly-spaced impedance discontinuities, the scattered signal will exhibit a periodic

series of maxima as either the incident angle or the frequency is changed; each maxima

corresponds to a path length difference of an integral number of wavelengths. With this

single uniform reflector spacing, a sinusoidal variation of signal amplitude occurs. The

Fourier transform of this yields a single peak, whose location is a measure of reflector

spacing, and whose amplitude is a measure of the scatter number n.

In biological tissue, changes in acoustic impedance are expected to occur randomly.

In any particular tissue, the spacings between scatterers may vary widely, but still fall

within certain limits that can be statistically specified by the scattering profile shape.

In disease processes, when the structure is altered, the statistical values of d obtained

from the scattering profile should also be altered correspondingly.

179
0 2 4 6 8 10

SCATTERING ANGLE (Degrees)

Figure 14. Ultrasound scattering from frog liver.

(a) (b)

Figure 15. Surface scattering from liver at 15 MHz (a) Normal tissue. Vertical

scale, 5 v/div; horizontal scale-top, 20 ys/div, bottom, l°/div. (b) Diseased

tissue. Vertical scale, 5 v/div; horizontal scale-top, 20 ps/div, bottom,

5 ys/div.

180
Normal Red-leg disease

Figure 16. Photomicrographs of specimen of frog liver, hematoxylin

stained. Magnification is 150X.

and eosinSCATTERING ARRAY

Figure 17.

ABC = PATH LENGTH DIFFERENCE =

dsin 6 + dsin e FOR CONSTRUCTIVE INTERFERENCE:

2d sine = nA

Geometry for Bragg diffraction.

The effects of randomness introduced into a regular pattern are well described in x- ray crystallography, which operates on the same Bragg diffraction principle. An "imperfect"

lattice structure produces diffracted radiation which is not well-localized. There are

strong peaks corresponding to the average ideal lattice, but in other directions the

wavelets reflected by the individual scatters do not cancel perfectly by interference. The

peaks are broadened, and weaker diffuse scattering is seen in many directions not specified

by the Bragg formula. Thus, there is a corresponding decrease in the intensity of the

181
selective peaks specified by the Bragg law. This is, in general, the type of scattering

expected from structures such as seen in highly-organized tissues and organs, where there

exists a structural order which is marked by small perturbations, and statistical fluctuations

of inter-scatterer distance occur around a certain mean value.

From the earlier studies in this laboratory cited above [14, 15], as well as from the

work of Chivers, Hill and Nicholas [17-20] and of Waag, Gramiak and Lerner [21], it appears

likely that scattering and diffraction-based probing techniques can be used to characterize

the acoustical variations in tissue for medical diagnosis. It is not yet possible to know how much information about a tissue sample may be obtained in this manner. The

differences in the densities of many tissues constituents, e.g., collagen, elastogen, etc., are very small, although the differences in their bulk moduli are believed to be larre

[22]. Whether these differences yield sufficiently different ultrasonic signals at the

wavelengths involved to be of diagnostic value remains yet to be determined. Therefore,

the dependence of the scattered signal on angle was studied at several discrete frequencies

in phantoms and tissues of known structure.

4.2.2 Experimental Apparatus and Procedures

The specimen tank is shown in Figure IS. A cylindrical anechoic tank, with two rotating

arms for the transmitting and receiving transducers, respectively, was used. The tank and

each of the arms could be rotated independently around the vertical axis to permit anglesweep scanning as well as specimen rotation. The bottom and sides of the tank were lined

with soft polyethylene. The specimens were placed in the center and coupled to the transducers through degassed saline (or water) and a thin film of polyethylene.

The tissue specimens were carefully-cored cylindrical plugs 3 cm in diameter, which

permitted adequate separation of surface echoes from internally-scattered signals without

excessive attenuation of the latter in the sample itself.

Matched pairs of unfocused transducers, 1 to 4 MHz in frequency, were used. The

transmitting transducers were driven in a c.w. burst mode of 20 ums duration over the

frequencies used. This burst width was considered to be sufficiently long for the continuous

wave approximation to be valid, yet short enough for the signal to remain distinct from

any reflections from the walls of the specimen tank. The experiments were conducted with

specimens situated in the near field of the transducers since it was not feasible to fabricate a tank large enough to enable the measurement to be made in the far field.

The signals from the receiving transducer were amplified in a tuned amplifier in order to maximize the signal-to-noise ratio, then rectified and time-gated to eliminate

the echoes from the front surfaces of the specimen and the tank. The gated, internallyscattered signals were integrated in an operational amplifier and displayed on an oscilloscope (fig. 19). The magnitude of the integrated signal which, for a constant gating

time, was proportional to the average amplitude of the internal scattering signal, was recorded as a function of the transducer angle. This averaging process, as well as the

averaging due to the finite ultrasonic beamwidth, served to compensate for the intensity

variations in the near field as well as for any local inhomogeneity in the tissue specimens.

4.2.3 Angle-Scanning Procedure

Two different scanning procedures were used in the course of this experiment. The

first method tried was an arc scan and involved holding one transducer fixed and moving

the other in a large arc around the tank. Many problems were encountered in this approach,

the most important of which was the detection of the unmodified transmitting beam by the

receiving transducer, thus masking out the much smaller scattered signal. This procedure

failed to give very reproducible results, and the profile of amplitude vs. angle was very

random and erratic, with very large amplitude fluctuations occurring for small angular

changes.

If one considers the physics of Bragg scattering, the reason for the failure of arc scanning becomes apparent. As shown in figure 20a, there are various planes of scattering

elements which can serve as the basic "reflecting surface." Each of these has a different

value of d (distance between adjacent array elements), and therefore a different requirement

for fulfillment of the Bragg condition.

182
SIDE VIEW

POLYETHYLENE FILM

TRANSDUCER MOUNTING

ACOUSTIC ABSORBER

ANGLE MEASUREMENT

POST AND

SLEEVE ASSEMBLY

BASE PLATE

WINDOW

SUPPORT POST

POLYETHYLENE FILM

SPECIMEN

ACOUSTIC ABSORBER

TRANSDUCERS AND

MOUNTINGS

TOP VIEW

Figure 18. Specimen tank design (side and top views)

RECEIVE

TRANSDUCER TUNED AMPLIFIER

BANDPASS

- FILTER RECTIFIER

TRANSMIT

TRANSDUCER

RADIO

FREQUENCY

OSCILLATOR

TIME

GATE INTEGRATOR

SQUARE

WAVE

GENERATOR

OSCILLOSCOPE

Figure 19. Schematic of experimental apparatus.

The second method of conducting the angle-sweep scan involved moving both the transmitting and receiving transducers, each by an equal amount. Thus, the line of scatterers

from which the reflection and interference phenomena occur will be the same for the entire

scan, and there should be some valued of 0 for which the Bragg condition is met. This

"double-angle scan" method is illustrated in figure 20b.

183
»CATTERING

(a) (b)

Figure 20, (a) Arc scanning and the Bragg formula, (b) Double-angle scanning

method.

Several double-angle scans were made to characterize various specimens, and the

results were plotted as amplitude vs. total transducer angle (2e in the Bragg Law). These

scans were repeated at various frequencies to assess the effect of wavelength upon the

internal -scattering profile.

4.2.4 Results

4.2.4.1 Results Obtained from Phantom Targets of Known Geometry

To test the feasibility of making these internal-scattering measurements and the

correlation of the results with Bragg diffraction theory, phantom scattering targets of

precisely-known geometry were used. A target was made of steel pins (diameter 0.026 in)

spaced in a square grid with a distance of 0.10 inches between adjacent pins. If an ultrasonic frequency of 2.25 MHz is used, the Bragg formula predicts maxima at approximately

15°, 30°, 45°, 62°, 81°, 102° and 131° total transducer angle (20). These predicitons

correlate very well with the experimental result obtained by a double-angle scan, as shown

in figure 21. The values obtained were highly reproducible, with most of the fluctuations

being accountable on the basis of uncertainty in positioning the two transducers. The

values plotted are the mean of 5 separate runs, and the relative range of values obtained

was approximately 1% of the total signal amplitude. The scattered signals obtained were

very strong due to the large acoustic impedance mismatch between the steel pins and the

water surrounding them.

In order to better simulate the gross acoustic properties of biological tissues, a second phantom target was made of soft polyethylene with holes drilled through it in a regular array. The water-filled holes were 0.026 inches in diameter, and the spacing

between them was 0.05 inches. According to Bragg's law, the angular locations of expected

maxima are approximately 35° and 70° of total transducer angle, if these measurments are

taken at a frequency of 2.25 MHz. The experimental results correlated very well with

theory, and were very reproducible, as seen in figure 22. The points plotted are the mean

values of 5 experimental runs, and the average range of values was approximately 8% of the

total signal amplitude. The magnitude of the scattered signal was significantly reduced

from the values obtained with the pin-scatterer phantom, due to the fairly small acoustic

impedance difference at the water/ polyethylene interface, as well as to the increased

absorption of ultrasonic energy by the polyethylene. In both of these respects, the

polyethylene phantom appeared to be a good model of an idealized tissue sample. As a control, a cylindrical plug of soft polyethylene without any holes drilled into it was

used as the target. The oscilloscope recorded an echo from the front and back surfaces,

but no evidence of any scattering signal from the interior was found, even at very high

gain. This indicated that inhomogeneity is indeed the source of the internally-scattered

echoes, and the phenomenon which we wish to investigate was directly responsible for the

signals which we were measuring.

184
I_^^^_J I I I I I I I I 20 30 40 50 60 70 80 90 100 110

ANGLE 20

Figure 21. Scattering profile of pin-scatterer phantom target. Average of 5 runs. Frequency is 2.25 MHz.

4.2.4.2 Results Obtained from Various Biological Tissue Samples

Double-angle scans were performed with many different samples of mammalian tissue

from various organs and from various species. Samples of calf liver, pig liver, calf

skeletal muscle, and calf cardiac muscle were investigated to determine their characteristic

internal -scattering profiles. The most striking result was the periodicity of maxima and

minima which was evident in the angular dependence of the amplitudes of the scattered

signals. The precise values of the signal strength appear not to be important, and were

noted to change as the tissue was rotated. However, the average periodicity, the angular

distance by which maxima are separated, remained constant for a given tissue at a given

incident frequency. For example, at 2.25 MHz, calf liver produced a scattering profile

with an average angular separation of approximately 20° of arc (figs. 23, 24). There was

a fairly large spread of values for the average periodicity of the scatter profiles, due

largely to biological variations from one tissue sample to another. However, when statistical analysis was done on the data (student's t-test [23], calculated at the 5% sicnificance

level), the range of periodicity values evident in calf liver could be demonstrated

to be a separate population from the values obtained from other tissue samples.

The important parameter to consider in analyzing the scattering profiles appears to

be the average periodicity, and not the relative heights of the maxima. This is evident

in figures 23 and 24, which show two characteristic scans obtained from calf liver tissue.

Although the profiles may appear to be different due to the change in sample orientation,

the average angular separation of maxima remains roughly constant.

These double-angle scans were performed on many other different tissue samples, each

yielding a characteristic scattering profile with a certain average intermaximal separation

at the operating frequency of 2.25 MHz. Although these average periodicities were stati^stically recognizable as several significantly-different populations, it was often difficuTt

to tell by eye which type of tissue sample was under study, given the resulting scattering

profile. A more reliable method of discriminating tissue type based upon internal -scattering

properties utilized the frequency dependence of the angular profile patterns.

185
Mr

20 30 40 50 60 70 80 90 100 110

ANGLE 2 6*

Figure 22. Scattering profile of polyethylene phantom target. Average of 5 runs. Frequency is 2.25 MHz.

Q.

<

60 70 80

ANGLE 29

100 110 120

Figure 23. Double-angle scan at 2.25 MHz of fresh calf liver in degassed saline.

(Trial 1) Average of 5 runs. Average periodicity equals 20° of arc.

186
20 30 40 50 60 70 80 90 100 110 120

ANGLE 2 0

Figure 24. Double-angle scan at 2.25 MHz of fresh calf liver in degassed saline.

(Trial 2) Average of 5 runs, average periodicity equals 21.875° of arc.

4.2.4.3 Frequency-Dependent Characterization of Tissue Type

Double-angle scans were performed with various tissue samples as scattering targets,

and after each scattering profile was determined and its average periodicity calculated,

the ultrasonic frequency was changed and the test repeated. Thus, we were able to correlate

ultrasonic frequency with average peak separation. Orientation of the tissue appeared to affect the results very little, except in cases of marked tissue anisotropy. Again, the

scatter of the data was larger than can be expected purely on the basis of the instrumentation

and experimental design; the large variations appeared to be due entirely to natural

variations within tissue samples from different regions of one organ, or from different

animals.

The most evident trend exhibited by the frequency plots is the linearity of the

relationship between angle and frequency. This is seen in figure 25, which shows the

frequency dependence of fresh calf liver in degassed saline. The best linear fit to the

experimental data was determined by a least-squares regression analysis. The closeness of

fit can also be calculated by finding the coefficient of determination which is a direct

measure of accuracy of fit [24].

Almost all of the frequency-dependent plots which were made correlated very well with

the least-squares line, with coefficients of determination (r^) ranging in value from 0.80

to 0.93, all indicating excellent agreement of data and empirical line fit. There were

some exceptions, however; certain frequency plots correlated rather poorly with a linear

fit, with values in the vicinity of 0.50.

Frequency plots of pig liver and calf heart muscle are shown in figures 26 and 27,

respectively. The raw data points as well as the best line fits are shown. The frequency

dependencies of the tissues under study were quite characteristic. For example, calf

liver and pig liver may be differentiated easily by comparison of both slope and axial

intercept values, as can calf skeletal muscle and calf cardiac muscle. Thus, these two parameters may prove to be an accurate method of cataloguing tissue scattering properties.

187
30

0 1.0 2.0 3.0 4.0

FREQUENCY (MHz)

Figure 25. Frequency dependence of fresh calf liver in degassed saline.

4.2.4.4 Effect of Tissue State and Tissue Anisotropy

Calf liver tissue was used in a study of the effects of freezing and formalin-fixation

upon the scattering profile and the frequency dependence of biological tissues. Calf

liver that had been frozen and thawed and then examined in a series of double-angle scans

at various ultrasonic frequencies is not significantly different in its internal scattering

properties than the freshly-excised calf liver specimens. A trend may be seen toward a general lowering of the angular values obtained, but this difference is not statistically

significant at the 5% level of the t-test. Since the formation of ice crystals can produce

tissue structure changes, this may appear to be a surprising result; however, the only

changes observed when a histological examination was made were the breakage of cell

membranes and destruction on the scale of microns. The ultrasonic scattering phenomenon

measured in this experiment does not approach this level of resolution. The ultrasonic

wavelengths used were in the submi 1 1 imeter to millimeter range, and could not detect the

damage occuring on a cellular and subcellular level. However, as stated earlier, such

damage does result in an increase in frequency-dependent acoustical attenuation (and

absorption)

.

Similar results were obtained when formalin-fixed tissues were studied. Formalinfixation was not expected to change the tissue structure, but it could change the tissue

elasticity, and therefore the acoustic impedance. Scattered signal strength increased in the angle-scanning of formalin-fixed tissues, but the change in the frequency dependence

remained insignificant. Figure 28 compares the results for fresh, frozen, and formalinfixed calf liver samples.

Certain tissues exhibit structural anisotropy which was detectable by characterization

of the scattering. Calf skeletal muscle displays different frequency-dependent behavior

related to the direction at which the ultrasonic wavefront impinges upon the sample. If the cylindrical tissue plug was cut such that the muscle fiber bundles ran parallel to the

cylinder height (cut "across" the grain), the resulting angular separation was higher than

that of muscle cut longitudinally ("along" the grain). The differences are statistically

significant and readily recognizable, as shown in figures 29 and 30. This structural

anisotropy and the resulting dependence of scattering characteristics upon fiber orientation

188
30

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—I 20

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CD

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<

10

0 1.0 2.0 3.0 4.0

FREQUENCY (MHz)

Figure 26. Frequency dependence of pig liver in degassed saline.

0 1.0 2.0 3.0 4.0

FREQUENCY (MHz)

Figure 27. Frequency dependence of calf heart muscle in degassed saline.

were not seen in cardiac muscle samples, where no single predominant fiber orientation

exists. Cutting heart muscle specimens at varying planes resulted in the same frequency

dependence in all cases.

109
30

lU

LU

<

LU

20

10

FRESH LIVER (Calf)

FROZEN

LIVER

(Calf)

FORMALIN - FIXED LIVER

(Calf)

0 1.0 2.0 3.0 4.0

FREQUENCY (MHz)

Figure 28.

1 i ver. Frequency dependence comparison for fresh, frozen, and formalin-fixed calf

4.2.5 Statistical comparison of Experimental Data and Bragg Diffraction Theory

The experimentally-determined frequency dependence^

be linear. However, if one plots the expected dependence^

dependence more

^^^^^ely'th^n^JSJsl^wi^h^^^if rrt^:u^c?e^^prS!idirrhe J?os°est correlation between

experiment and theory, and calf liver being the most divergent.

TO facilitate the analysis of experimental data and its co-elation

Jo Br^gg theory, ^a.^

second type of plot is more useful : the ^^"^ o!,^J^^/^^%'^?^,f^^ft^a ght^^ passing

wavelength. On such a plot, Bragg diff;;;act on theory predicts

^^^^ through the origin. The fit obtained from a least-squa^ ^.^^^^

good, with coefficient of determination values (r

^, 'f ' ^^pected from simple Bragg

samples under study. Thus, the phenomenon "^^^^Jj^.^^h^ S%^^?f3'^-th frequency in a diffraction theory, yet it shows an ^PPf^"^ periodicity which vari^^^^^ M y^^^^

very linear

-^^^^^^J^^^^^^^ in the

Te^LncyTeien^e^l'scart^rfng ^"h^Jior^^hich may'well be of future diagnostic use.

By examining the best theoretical line fit to JJe experimental data one can calcu-^^

late the best value of d, the interscatterer array distance, by substitution

Bragg formula. One can also define limits for t e pos ib e va^^^^^^^J/.^^ the tissues

encompass the existing experimental data. Such ^" ^"^^^^^'..^'',33° 5' Xough 35. The sine

studied, and the ranges of d values obtained are ^^own in figures 31 ^hro^g

^^^^^.^^^ ^.^

The possible reasons for the discrepancy between Bragg theory and^

tions are many. The most probable explanation s Jhf

b o og cal tissue a P ^y^^^^

,

be ordered in an array which ^^/^gular enough at ^^^^j;^^^|TM^^Ss to confirm this. i O^ion^ ^^l/ll^ f:ma^^ler:care!^::rrde^^s apparent even at the

^9o
30

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LU<

LU>

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20

10

0 1.0 2.0 3.0 4.0

FREQUENCY (MHz)

Figure 29. Frequency dependence of calf skeletal muscle cut longitudinally.

30

CM

m

<

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<

20 -

10 -

0 1.0 2.0 3.0 4.0

FREQUENCY (MHz)

Figure 30. Frequency dependence* of calf skeletal muscle cut across-grain.

scale which is resolved by the ultrasonic scattering measurement apparatus; however, the

regularity with which the clusters of ordered elements are arranged is very slight. For example, muscle fibers are very well ordered, have the same orientation, and are grouped

together into bundles surrounded by sheaths of connective tissue. These bundles of fibers

191
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^ .10

CO

.05

• ' /

• / / /

/ / / • • ' • /

m

* «/ /

/ /

/ •

/ • / / 1 /

/ • / / / / BEST FIT

/ / / RANGE OF

/

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f /

If/ / / / D VALUES:

1 /

1.52 mm TO 3.24 mm

/ /

If// /

///

1 1 /

//

ly

r 0.5 1.0

WAVELENGTH (A) mm

Figure 31. Comparison of theory and experimental results for calf liver.

are not very consistent in diameter, and the ordered array which is seen is composed of

bundles of many varying diameters. It seems possible that enough regularity exists to give rise to the periodicity evidenced in the ultrasonic internal scattering profiles, but

perhaps not enough strict matrix ordering is present to give the full manifestations of

Bragg diffraction phenomena.

4.2.6 Diagnostic Implications of the Scattering Data

Despite the apparent disagreement between the experimental results and the predicted

values for Bragg diffraction, the internal scattering properties of biological tissues

hold the promise of being significant for diagnostic applications. Tissues which have

structural differences that occur within the resolving power of the ultrasound (limited by

the wavelength) are easily distinguished by means of their characteristic frequencydependent scattering. For example, calf and pig liver are structurally different in their

organization of cells into clusters. Pig liver, even with the unaided eye, appears to have a honeycombed, hexagonal organizational unit, which is probably the theorized scattering

element. These clusters, like the muscle fiber bundles, appear to vary in diameter. Calf

liver has far less obvious a unit of structural regularity. The cell clusters are present,

but are not as well defined in shape as are those of pig liver. It is interesting to note

that the most regular and organized of the tissue samples, cardiac muscle, also exhibited

the closest correlation to the ideal Bragg theory. The muscle fiber bundles were very

regular in diameter despite the lack of one predominant orientation direction. Another

factor that may lead to the non- ideal results is the irregularity introduced into the

array by the presence of blood vessels dispersed throughout the tissue, leading to discontinuities in the array structure.

192
0.5 1.0

WAVELENGTH (A) mm

Figure 32. Comparison of theory and experimental results for pig liver.

Work with tissue specimens of known pathology is necessary to determine more precisely

the diagnostic utility of scattering characterizations. An interesting extension of this

experiment might involve the scattering changes which occur in cirrhotic liver and in

fatty necrosis, both of which disrupt the structure by introducing fat globules and many

randomly-oriented fibers. Such pathologies can be induced in experimental animals by the

feeding of certain toxic substances, such as alcohol or CC^^^, to overload the liver's

detoxification apparatus. A study of the progression of the disease with time can then be

correlated to the changes in ultrasonic scattering properties.

Observation of the frequency-dependent phenomena exhibited by various tissues seem to be the best method of characterizing tissue type. It is superior to looking at either the

double-angle scan or at the surface scattering properties. From a diagnostic standpoint,

the best method might be to keep the transducers at a fixed angle, and to do a continuous

sweep of frequency to measure the amplitude vs. frequency profile. A scan such as this

should take less time, and could be performed using existing B-scan diagnostic equipment

with minor modifications.

It is still too early to assess the possible impact of frequency-dependent attenuation

and internal scattering measurements as new diagnostic tools. Certain limitations are already apparent: resolution and accessibility. As previously discussed, the resolving

power is limited by the ultrasonic wavelength. Use of higher frequencies would produce a system with increased tissue resolution; however, at higher frequencies, tissue absorption

becomes a problem, and there is also the related technical problem of a decreased signal

strength to be measured. Design of instrumentation to overcome these difficulties should

prove challenging.

193
0.5 1.0

WAVELENGTH (.\) mm

Figure 33. Comparison of theory and experimental results for calf cardiac muscle.

0.5 1.0

WAVELENGTH (.1) mm

Figure 34. Comparison of theory and experimental results for calf skeletal muscle,

cut across-grain.

194
0.5 1.0

wavelength! X)mm

Figure 35. Comparison of theory and experimental results for calf skeletal muscle, cut

longitudinally.

References

[1] Robinson, T. C. and Lele, P. P., An analysis of lesion development in the brain

and in plastics by high intensity focused ultrasound at low megahertz frequencies,

J. Acoust. Soa. M. , 51_, 1333 (1969).

[2] Howry, D. H. , Techniques used in ultrasonic visualization of soft tissues, in Ultrasound in Biology and Medicine, E. Kelly, ed., p. 49 (Am. Instit. of Biolog.

Science, Washington, DC, 1957)

[3] Robinson, T. C, An analysis o lesion development in plexiglas and nervous tissue using focused ultrasound. Ph.D. Thesis, M.I.T. (1968).

[4] Pauly, H. and Schwan, H. P., Mechanism of absorption of ultrasound in liver

tissue. J. Acoust. Soc. Am., 50, 695 (1971).

[5] Hueter, T. F., Viscoelastic losses in tissues in the ultrasonic range,

WADC Tech. Rept. 57-706 (1958).

[6] Lele, P. P., Unpublished data reported to the U.S. Army Medical Research

and Development Command (1963).

[7] Kikuchi, Y., Present aspects of ultrasonotomography for medical diagnostics,

in Ultrasonic Imaging and Holography, G. W. Stroke, W. E. Kock, Y. Kikuchi,

and J. Tsujiuchi, eds., p. 229 (Plenum Press, New York, 1974).

195
[8] Gericke, 0. R., Ultrasonic spectroscopy, in Research Techniques in Nondestructive

Testing, R. S. Sharpe, ed.. Chapter 2 (Academic Press, New York, 1970).

[9] Papadakis, E. P. and Fowler, K. A., Broadband transducers: radiation field and

selected applications, J. Aaoust. Soc. Am., 5£, 729 (1969).

[10] Moore, D. H., Ruska, H., and Copenhaver, W. M. , Electron microscopic and histochemical

observations of muscle degeneration after tourniquet, J. Biophys. Biochem. Cytol. , 2, 755 (1956).

[11] Stenger, R. J., Spiro, D., Scully, R. E., and Shannon, J. M., Ultrastructural and

physiological alterations in ischemic skeletal muscle. Am. J. Path. 40, 1 (1962).

[12] Conner, E. S., Hubelbank, M., and Lele, P. P., Acoustic field patterns of a digitally

programmed five-element, concentric ring phased array, in Froa. Third New England Bioeng

Conf., p. 342 (Tufts Univ., 1975).

[13] Lele, P. P. and Namery, J., A computer-based ultrasonic system for the detection and

mapping of myocardial infarcts, in Proc. San Diego Biomed. Symp. , 13^, 121 (1972).

[14] Senapati, N., Lele, P. P., and Woodin, A., A study of the scattering of sub-millimeter

ultrasound from tissues and organs, in Proc. IEEE Ultrasonics Symp., p. 59 (IEEE Cat.

No. 72 CH0708-8SU, IEEE, New York, 1972).

[15] Senapati, N., Some studies on scattering of ultrasonic waves by rough surfaces simuj lating body organs and tissue surfaces, M.S. Thesis, M.I.T. (1971).

[16] Mountford, R. and Wells, P. N. T., Ultrasonic liver scanning: the A-scan in the normal

and cirrhosis, Phys. Med. Biol., 17» 261 (1972).

[17] Hill, C. R. and Chivers, R. C, Investigations of backscattering in relation to ultra-

| sonic diagnosis, in Conf. Proc. UBIOMED 70 (Warsaw, 1970).

[18] Chivers, R. C, Hill, C. R., and Nicholas, D., Frequency dependence of ultrasonic , backscattering cross-sections: an indicator of tissue structure characteristics, in Ultrasonics in Medicine, M. deVlieger, D. N. White, and V. R. McCready, eds., p. 300

(Excerpta Medica, Amsterdam, 1974).

[19] Hill, C. R., Interactions of ultrasound with tissues, in Ultrasonics in Medicine,

M. deVlieger, D. N. White, and V. R. McCready, eds., p. 14 (Excerpta Medica,

Amsterdam, 1974).

[20] Chivers, R. C. and Hill, C. R. , A spectral approach to ultrasonic scattering from

human tissue: methods, objectives, and backscattering measurements, Phys. Med. Biol.,

20 799 (1975).

[21] Waag, R. C, Gramiak, R., and Lerner, R. L.', Ultrasonic determination of cardiac

macrostructure, in Cardiac Ultrasound, R. Gramiak and R. C, Waag, eds., p. 277

(C. V. Mosby, St. Louis, MO, 1975).

[22] Harkness, R. D. and Harkness, M. L. R., Some mechanical properties of collageneous

frameworks and their functional significance, Biorheology , 1_, 1 (1963).

[23] Snedecor, G. W. , Statistical Methods, 4th edition (Iowa State College Press, Ames,

Iowa, 1946).

[24] Draper, N. R. and Smith H., Applied Regression Analysis (John Wiley, New York, 1968).

I.

196
National Bureau of Standards Special Publication 453. Proceedings of Seminar on Ultrasonic

Tissue Characterization held at NBS, Gaithersburg, MD, May 28-30, 1975. (Issued Oct. 1976)

Paper 6.2: FREQUENCY AND ANGULAR DEPENDENCE OF ULTRASONIC

SCATTERING FROM TISSUE

C. R. Hill

Physics Division

Institute of Cancer Research

Royal Marsden Hospital

Sutton, Surrey, U.K.

This paper reports on an ongoing program of work that,

commencing in 1969, has been aimed at elucidating, and ultimately

applying in clinical investigation, the processes by which

ultrasound is scattered by volumes of human tissue. The report covers two related aspects of the work, concerned with the

specific patterns of dependence of volume backscattering cross- sections on, respectively, acoustic frequency and the relative

orientation between the axis of the interrogating ultrasonic

beam and the backscattering structure. These two aspects of

the subject have been treated from both theoretical and experimental points of view and both aspects show promise as possible

bases for practical tissue characterization. Particular interest

has centered in the orientation analysis approach, which

constitutes an acoustic analog of Bragg diffraction of x-rays

and has been shown to be capable of quantitatively significant

differentiation between different human tissue types. The

feasibility of applying this approach to in vivo tissue

characterization has been demonstrated.

Key Words: Bragg diffraction; diagnosis; frequency dependence;

orientation dependence; scattering; tissue characterization;

ultrasound.

This paper reports on an ongoing program of work that, commencing in 1969, has been

aimed at elucidating, and ultimately applying in clinical investigation, the processes by

which ultrasound is scattered by volumes of human tissue. This is a report on two aspects

of this work, which is a group activity to which major contributions have been made by a number of individuals, and particularly by R. C. Chivers, D. Nicholas, R. W. Huggins, and

J. Milan. Furthermore, it is work that has been carried out in close liaison with a parallel program of development and clinical application of grey-scale imaging methods for tumor diagnosis [1-3], and the scatt ring work has thus been carried out with the dual aim

of extending fundamental knowledge and evolving clinically-useful analytical techniques

complementary to tissue imaging.

At the time of commencement of this project, no significant published data were available on the ultrasonic scattering properties of human tissues. Even in other branches of

acoustics, reference to the literature yielded little of direct relevance [4,5] although

a possibly productive line of work was suggested by the interest, in the field of non- destructive testing, in target characterization by ultrasonic spectroscopy.

^Figures in brackets indicate the literature references at the end of this paper.

197
A full understanding of the processes of ultrasonic scattering by human tissues will

only come about by a combination of theoretical description and experimental measurement.

In practice, the structural complexity of real human tissues is such that achievement of

exact theoretical descriptions will be out of the question, but a promising method of

bridging this gap between theory and experiment will be to work with tissue models of

various kinds, for example, suspensions of spherical or cylindrical particles in liquid

or gel matrices. This type of synthesis between theory and experiment has been an ideal at which we have felt it is appropriate to aim.

Conceptually, the early stages of our work were concerned with the frequency dependence

of scattering. Our basic experimental system for this work, shown here in figure 1 as originally described in 1970 [6J and later elsewhere [5,7,8], has subsequently been modified

SPECTRUM

ANALYSER

Figure 1. Basic block diagram of system for measurement of frequency dependence

of ultrasonic scattering by human tissue [6].

only in detail as, for example, by being connected on line to a POP 8E computer for data

storage and processing. - As we pointed out earlier [6], there is a basic choice open between

using a broad or a narrow band system. For reasons of convenience and compatibility with

conventional pulse-echo techniques, we chose to use the broad band (short pulse) approach,

with spectrum analysis of a resulting time-gated echo packet, but there may well be ultimate

advantages in the alternative of narrow band (tone-burst) methods. The influence of timegating on information derived by spectral analysis has been examined elsewhere [4,9,10].

There is also an important choice to be made between limiting investigations to 180°

backscattering and covering a significant range of angles, as envisaged in our 1970 paper [6]! In the light of some of our recent findings, outlined below, it seems likely that useful

| information may be yielded by the multiple angle approach but, on analysis, it appears that | the geometry of the situation will place severe difficulties in the way of any exact j quantitative analysis of the resulting data [5,10]. i

Initial experimental measurements of the frequency dependence of volume backscattering

[ by human tissues have been reported elsewhere [8,10] and some examples are shown here in figure 2. Each spectrum contains considerable detail and, visually, there appear to be some characteristic differences between different tissues. However, without further analysis,

objective characterization by this approach does not appear to be possible and an important

and fundamental feature of the situation is illustrated by the changes in spectral detail

obtained by repositioning of the tissue specimens within the beam (compare the two columns

of spectra in figure 2). Evidently, this is the consequence of a diffraction phenomenon

corresponding to the existence of a complex array of scattering centers within the interrogated volume.

Possibilities for further analysis and useful exploitation of frequency spectra of

this type appear to lie in two related directions, both calling for statistical treatment

198
35

H 1 1- -t- 1 1— 10 20 30 10 2 0 30

FREQUENCY MHz

Figure 2. Frequency spectra of ultrasonic backscattering from three types of

human soft tissue (two samples of each type) compared with the interrogating

spectrum: (a) transducer reference spectrum, (b) fat, (c) liver, (d) spleen.

IF filter width, 30 kHz; gate length, 8 ps ["5].

of the data. On the one hand, this involves examining and looking for significant changes

in the envelope shape of the spectra, such as might be expected in the presence of a significant component of Rayleigh-type scattering. The complementary approach is to look

for characteristic properties of the spectral fine structure.

An interesting extra dimension to this situation can be obtained by systematizing

the process of repositioning the tissue with respect to the interrogating beam. Specifically,

this can be done by arranging for relative rotation between the tissue structure and beam

axis about a line intersecting the beam axis normally and passing through the center of the

interrogated volume. This technique and its application have already been described [5,11,12]

and are illustrated here in figures 3 and 4. The measurements originally reported (fig. 4) were carried out on nominally normal tissues obtained at autopsy from two different subjects

(identified as LF and ML) and it is quite clear from these and subsequent data that it is possible on this basis to obtain objective remote characterization of tissues. Evidently,

this technique is an acoustical analog of the classical x-ray crystallography of Bragg

and von Laue and, as discussed below, the implications of its results as to the mechanicalacoustical structure of human soft tissues seem quite intriguing.

Presentation of data in the form of the crude "Bragg traces" of figure 4 is visually

interesting but lacking in objectivity. For the purposes of practical tissue characterization, it will be desirable to obtain a method for categorizing data in a statisticallyobjective manner. A number of possible approaches exist, but one that seems attractive is to derive the Fourier transforms of the basic Bragg traces. With the data in this form,

it appears practicable to place confidence limits on the range of variations in data

measured for tissues of various types [13]. Examples of characteristically different

measured Bragg traces and their correspontiing Fourier transforms have been published [5,12,14]

and are reproduced here as figures 5 and 6.

199
'a' scan

TRANSDUCER

AIYIPLIFIER

GATE

FILTER

RECORDER

Time Gated Echo

V

• • • • • I • •

• • * • « 4 -I V

<

y

y

J L

40

r

60 80 100 120 140

Figure 3. Experimental arrangement for investigation of the backscattered Bragg

diffraction characteristics of human tissues [5].

SPLEEN

^ v/V M.L

-1 I 1 I I u

10 20 30 40" 50 40' 70* 60" 90" ANGLE OF ROTATION Figure 4. Angular dependence of backscatteri ng amplitude at 1 MHz for fresh

human spleen, brain, and liver, obtained from two different subjects, identified

as LF and ML [11].

200
NORMAL

LIVER

METASTATIC

LIVER

15dB.

15dB.

Figure 5. Observed backscattered Bragg diffraction patterns, taken at 1 MHz from normal and cancerous liver. Upper trace: normal liver parenchyma. Lower

trace: secondary liver tumor [5].

NORMAL

LIVER

METASTATIC

LIVER

-Shift0-5 Cyclesy/degree

10

Figure 6. Power spectra derived from the Bragg diffraction records of figure 5. Upper trace: normal liver parenchyma. Lower trace: secondary liver tumor.

As mentioned at the outset, it has been the aim of our work not only to el ucidate "the

volume scattering properties of human tissues, but also to evolve clinically practicable

methods of tissue characterization. An advantage of working with 180° backscattering and

broad band pulses is that the experimental system is compatible with pulse-echo imaging

equipment. On this basis, it is possible to build compatible, and even hybrid, imaging/

analysis systems. For superficial sites, such as the breast, this can fairly readily be

201
achieved in a water bath configuration. It is also possible, however, to instrument

this idea in a skin-contact mode of operation and we have recently constructed and

commenced trials on a machine of this kind intended for liver investigations. Technical

details of this device are described elsewhere [15] and it is illustrated here in figure 7. Simultaneously-obtained B-scans and Bragg traces obtained with this device

for a normal human liver are shown in figure 8. It is anticipated that this device will

be interfaced to a small computer and will enable both orientation- and frequency--

dependence data to be derived from selected tissue volumes within, for example, a liver,

under conditions compatible with conventional clinical B-scan investigations. Ultimately,

the development of a two-dimensional (acoustic Laue pattern) interrogation system is an interesting possibility here and, as Greguss has recently pointed out, such an approach

would lend itself well to information analysis by coherent optical techniques.

The interpretation of experimental observations in this field, in terms of their

relationships to the mechanical-acoustical properties of the echogenic tissue volumes, is

a formidable problem that calls for work on several fronts. One of these is theoretical

understanding of the acoustic scattering properties of complex three-dimensional matrices.

Figure 7. Skin-contact scanning device for simultaneous section scan imaging

and Bragg analysis.

20Z
(b) (c)

(dJ (e)

Figure 8. In vivo Bragg traces and corresponding section scans of normal human

liver: (a) conventional B-scan (saggital section), (b) and (c) the same section

imaged using the Bragg scanner with its focal point at its lowest position,

(d) section image and Bragg trace derived from echoes from the region of the

portal vein, (e) the same for a region of liver parenchyma.

Here, a number of results are available, either directly or in modified form, from work

in other areas of scattering physics and there is a possibility, partly from these various

existing strands and partly from original extensions, to synthesize a satisfactory

theoretical structure for the tissue scattering situation. Some work on this has already

been completed [4,5] and a further extension is in preparation [16].

The theoretical description of scattering by a complex three-dimensional matrix

such as a human tissue can be approached from the viewpoint of two different models,

that of a multiple array of discrete scatterers and that of an inhomogeneous continuum.

Both models have been quite extensively studied in other contexts and both may have a role

to play in the present situation. In particular, analysis of the multiple scatterer model

suggests that it may be useful to distinguish between coherent and incoherent components

of the scattered energy. Of these, the former apparently corresponds to that fraction

of the echo signals that arise from refraction and specular reflection and which are exploited in conventional organ outline imaging techniques, while the latter may comprise

the volume scattering that is of importance in grey-scale imaging of tissues.

The inhomogeneous continuum model has been developed in relation to hydroacoustics

but the results can be appropriately modified for application in this field. In cases

where the scale of the inhomogeneities is much greater than the wavelength, this model

can be shown to lead to the classical /ay approximation while, for a scale of homogeneities of the order of a wavelength, diffraction theory will hold. One interesting

result of our investigations has been to show that Rayleigh's original analysis of

diffraction phenomena due to discrete scatterers is much more generally applicable than

was originally realized and holds also for inhomogeneous continua. A practically interesting consequence of such theoretical analysis is that it leads to predictions, which

may be experimentally tested, for the form of the frequency dependence of scattering by

various matrix configurations.

203
Theoretical analyses of this kind are generally based on the assumption of time waveforms being continuous. The extent to which results may be carried over to the case of

interrogation by short pulses is open to question, although there are arguments in favor

of the validity of such a step [16].

As has already been suggested, the particular experimental results described above

in relation to the orientation dependence of backscattering (figs. 4, 5, and 6) invite

theoretical consideration along lines applicable in x-ray crystallography. The relationship of this approach to general scattering theory is now under investigation [16] and

certain specific attempts at interpretation of the findings have already been reported [5,12

Support for the usefulness of the crystal lographic hypothesis is provided by the very good

agreement found between experiment and computations from the theory for simple physical

models [12].

Such findings lead to renewed interest in the question of the identity of the discontinuities in tissue properties that constitute the acoustic scattering centers. The

suggestion made by Fields and Dunn [17] that this may specifically involve connective

tissues, seems plausible and can be applied usefully in testing the acoustic crystallography

hypothesis. Specifically, if one considers the known histology of two human tissues,

skeletal muscle and liver parenchyma, one finds that they consist of fibers and lobules,

respectively, whose boundaries are, in each case, defined by connective tissue structures.

These structures thus may constitute arrays which, in practice, exhibit an appreciable

degree of short range order. By assuming reasonable values for the parameters describing

such arrays, one may construct computational models for them and thus again compare

experimental observation with theoretically predicted crystal lographic behavior [5].

The results of such a comparison, illustrated here for skeletal muscle in figure 9,

lend considerable support to the general validity of the underlying hypothesis.

Figure 9. Acoustic Bragg diffraction records for skeletal muscle at 1 MHz (log

scale). Upper trace: measured. Lower trace: computed from parallel filament

array model with 1.8 mm spacing [5].

Experience in our hospital, over the past two years, of carrying out more than

3000 grey-scale ultrasound examinations on cancer patients, has served to emphasize the

need for complementary analytical techniques which will provide additional information,

on pathology and histo-anatomy , over and above that directly available from the grey-scale

images. The science of acoustic tissue characterization is a new one but our own limited

experience indicates that there are a number of interesting possibilities for applications

that are likely to be both practicable and clinically relevant. The present paper has

204
been concerned with only two aspects of tissue characterization involving frequency and

angular dependence of scattering, respectively, but there are evidently a number of other

possibilities, several of which are being actively investigated by our own research

group [18].

This is a report of a group effort to which contributions have been made by numerous

individuals. Financial support has been provided by the Medical Research Council and

Cancer Research Campaign.

References

[I] Hill, C. R. and Carpenter, D. A., Ultrasonic echo imaging of tissues: instrumentation,

Brit. J. Radiol, (in press).

[2] Taylor, K. J. W. and McCready, V. R. , A clinical evaluation of grey-scale ultrasonography, Brit. J. Radiol, (in press).

[3] Taylor, K. J. W., Carpenter, D. A., and McCready, V. R. , Grey-scale echography in the diagnosis of intrahepatic disease, J. Clinical Ultrasound, 1_, 284 (1973).

[4] Chivers, R. C, The scattering of ultrasound by human tissues, Ph.D. thesis,

(University of London, 1973).

[5] Hill, C. R., Chivers, R. C, Huggins, R. W., and Nicholas, D. , Scattering of ultrasound by human tissue, in Ultrasound: Its Applications in Medicine and Biology,

F. J. Fry, ed., Ch. 9 (Elsevier, in press).

[6] Hill, C. R. and Chivers, R. C, Investigations of backscattering in relation to ultrasonic diagnosis, in Proceedings of Conference on Ultrasound in Biology

and Medicine; UBlOMED-70, L. Fi 1 i pczi nski , ed . , p. 110 (Polish Academy of Sciences,

1972).

[7] Hill, C. R., New uses and developments: diagnosis, in Interaction of Ultrasound

and Biological Tissues, J. M. Ried and M. R. Sikov, eds., p. 251, DHEW Publication

(FDA) 73-8008 (U. S. Government, 1972).

[8] Chivers, R. C, Hill, C. R., and Nicholas, D., Frequency dependence of ultrasonic

backscattering cross-section: an indicator of tissue structure characteristics,

in Ultrasonics in Medicine, M. de Vlieger, et al., eds., p. 300 (Excerpta Medica,

Amsterdam, 1974).

[9] Chivers, R. C, Ultrasonic scattering properties of human tissues: some theoretical

considerations, in Proceedings of 8th International Congress of Acoustics, p. 359

(1974).

[10] Chivers, R. C. and Hill, C. R., A spectral approach to ultrasonic scattering from

human tissue: methods, objectives and backscattering measurements, Phys. Med.

Biol. 20, 799 (1975).

[II] Hill, C. R. , Interactions of ultrasound with tissues, in Ultrasonics in Medicine,

M. de Vlieger, et al., eds., p. 14 (Excerpta Medica, Amsterdam, 1974).

[12] Nicholas, D. and Hill, C. R., Tissue characterisation by an acoustic Bragg scattering

process, in Proceedings of the 1975 Ultrasonics International, (Iliffe, London,

in press).

[13] Nicholas, D. and Hill, C. R., Acoustic Bragg diffraction from human tissues. Nature,

257, 305 (1975).

[14] Hill, C. R. and Nicholas, D., Ultrasonic scattering characteristics of human tissues:

experimental investigations, in Proceedings of 8th International Congress of

Acoustics, p. 357 (1974),

^ 205
[15] Huggins, R. W. and Phelps, J. V., Bragg diffraction scanner for ultrasonic tissue

characterisation in vivo (manuscript in preparation).

[16] Nicholas, D. , Ultrasonic scattering and the structure of human tissues, Ph.D. thes

(University of London, in preparation).

[17] Fields, S. and Dunn, F., Correlation of echographic visualizability of tissue with

biological composition and physiological state, J. Acoust. Soc. Am. 54, 809 (1973)

[18] Hill, C. R., Echoes from human tissues, in Proceedings of the 1975 Ultrasonics

International, (Iliffe, London, in press).

206
National Bureau of Standards Special Publication 453. Proceedings of Seminar on Ultrasonic

Tissue Characterization held at NBS, Gaithersburg, MD, May 28-30, 1975. (Issued Oct. 1976)

Paper 6.3: THE SCATTERING OF ULTRASOUND BY RED BLOOD CELLS

K. K. Shung, R. A. Sigelmann,^ and J. M. Reid

Providence Hospital

Seattle, Washington 98122

This paper reviews the experimental results obtained on the

measurement of ultrasonic scattering properties of erythrocytes. The

scattering is proportional to the fourth power of the frequency, as predicted by Rayleigh's scattering theory, for frequencies below

15 MHz. The scattering is not linearly dependent upon the hematocrit

as would be expected for a single scattering process. Twersky's wave scattering theories are therefore applied to describe this result.

The magnitudes of the monopole scattering due to compressibility and

of the dipole scattering due to density are in good agreement with

theory. Blood is the first tissue for which a nearly complete

experimental and theoretical characterization of scattering exists.

Key Words: Angular dependence; blood; compressibility; density;

distribution function; erythrocytes; hematocrit; scattering; ultrasound.

1. Introduction

Because it is easier to characterize physically, the scattering of ultrasonic waves

by red blood cells is a unique problem compared with the ultrasonic scattering by other

biological tissues such as muscle, lung, etc. Blood can be considered as a suspension of

red blood cells in plasma as far as the mechanism of the scattering is concerned. The

scattering of ultrasound by other blood corpuscles was experimentally shown to be insignificant [1].^

The scattering of acoustic waves by suspensions of particles has been studied by many

investigators both theoretically and experimentally [2-4]. However, most of these studies

have been concentrated on sparse concentrations of scatterers. Few investigations were

reported on dense media such as normal whole blood. This is probably due to the complexity

of this problem. A complete solution requires the knowledge of multiple-particle distribution functions. Unfortunately, these are not available. Twersky solved this problem in terms of a one-particle distribution function [5-7]. Beard, et at. [8] performed a series

of measurements on the dependence of wave scattering upon concentration of the scatterers.

A serious discrepancy exists between their results and Twersky's theories. They therefore

resort to a heuristic "hole" approach. Similar results can also be acheived by a "twophase" approximation [9]. In this approximation, some of the scatterers are considered

randomly distributed, the others fixed in position. Only the random particles contribute

to the incoherent scattering. In a dense medium like blood, the blood cells are so close

to each other that the motion of the cell may be affected by the presence of other cells.

Thus, it is highly possible that some of the cells can no longer be considered randomly

located and the division of particles into random and non-random populations is comprehensible.

^University

^Figures in

of Washington, Seattle, Washington 98105.

brackets indicate the literature references at the end of this paper.

207
The objective for pursuing this research is that the information obtained can be used

to improve existing diagnostic instruments such as the Doppler flowmeter or to develop new methods for clinical use. See "The Scattering of Ultrasound by Tissues," this volume

(p. 29) for details of application.

2. Experimental Results and Theoretical Analysis

The experimental technique and arrangement employed in our measurements have been

described elsewhere [10-12]. Thus, they will not be repeated here. Essentially, in this

method, the scattering coefficient (scattering cross-section per unit volume of scatterers)

can be measured by comparing the RMS value of the gated backscattered wave from a specified

volume of blood with that of a stainless steel flat reflector.

Outdated citrated bank blood cells were suspended in Ringer's Injection solution in our measurements. Additional anticoagulant (Sodium Heparin) was added whenever necessary.

Great care was taken to prevent hemolysis during the experiment. Clumping and settling of

the red blood cells were prevented by pumping. All measurements were done at 37°C. We envisioned that results using outdated blood obtained in vitro may be different from those

using fresh blood obtained in vivo. We intend to repeat these measurements in vivo in the near future.

Our experimental data indicate that for frequencies below 15 MHz the scattering is proportional to the fourth power of the frequency and this relation is not affected by the

hematocrit (percentage packed-cell volume occupied by blood cells) of the blood (fig. 1).

This is predicted by Rayleigh's scattering theory because the ultrasonic wavelength is much longer than the dimension of the scatterer.

FREQUENCY. F(MHZ)

Figure 1. Volumetric backscattering coefficient versus frequency.

208
The scattering of ultrasound by blood was found to increase approximately linearly

with the number of red blood cells present in the blood sample for hematocrits less than

8%. After this point, the scattering process becomes more complicated. It reaches a maximum around a hematocrit of 26%, then decreases as the hematocrit increases (fig. 2).

14

12

K)

. 8 o

8

o

z

lii *

t-M

0^0- -i^ O

O DATA POINT

THEORETICAL CURVE

FITTED

J L

f • 5MHZ

J L

10 20 30 40

HMTC %

SO 60 70

Figure 2. Volumetric scattering coefficient versus hematocrit at 5 MHz.

The physical significance of these phenomena can be explained as follows: at low

hematocrits (less than 8%), the red blood cells behave as incoherent, randomly-distributed

scattering centers. The total scattered intensity is the sum of the intensities from each

cell, i.e. J a single scattering mechanism will suffice to describe the scattering process.

At very high hematocrits (greater than 58% or so),^ the blood resembles a perfect crystalline

solid. There would be no wave scattering if all cells were regularly spaced at very small

distances from each other. Although the cells can be considered as scattering centers,

the waves scattered from them will interfere destructively at any point of observation.

The reason for this is that the cells can be so paired that the waves from each pair

traveling in a particular direction are exactly out of phase. For intermediate hematocrits,

some of the cells can be considered in a random state while the others are in a crystalline

state. Only the random cells will contribute to incoherent scattering. Coherent scattering

by the crystalline cells contributes only to scattering in the forward direction.

Twersky [5-7] expressed the pair distribution function by the product of two one-

] particle distribution functions and solved the problem of wave propagation in a dense

medium. For the case of ka much less than 1, he obtained the following result:

2 0.21k^aV(1-w

' 0 0

e w 3 0 e (1)

^Beard et at. found that the maximum volume concentration that can be obtained without

the deformation of the scatterers is between 59% and 64% [14].

209
where = scattering coefficient

k = wave number

a = radius of the scatterer

6g = adiabatic compressibility of the scatterer

3 = adiabatic compressibility of the imbedding medium

Pg = density of the scatterer

p = density of the imbedding medium

Wq = volume concentration of scatterers.

It should be noted that for this expression to be valid the scatterers must be point

scatterers and independent of each other. This is physically unrealizable. To modify

this result, he therefore introduced two heuristic approximations [8,9]. In the so-called

"two-phase" system, he divided the scatterers into two phases, of them in gas phase

and Nx of them in crystal phase such that N^+Nx = N (the total number of scatterers in the

system). In the "hole" approach, the scattering was thought to occur at the cavity sites

(space not occupied by the scatterers) in the very dense situation, and the volume of each

"hole" was assumed to be

^h = ''o^^-K^ (2)

where = volume of the hole

V = volume of the scatterer

0

b = a fitting constant.

Using our experimental data and introducing the "hole" approximation, we obtained the

following theoretical result:

0.21k^a\ (1-w )(1 0 0 1.72w,0' Pe - P (3)

Equation (3) is also shown in figure 2 as a dotted line. We can also obtain the theoretical curve for the volumetric scattering cross-section by dividing eq. (3) by Wq. Both the data

points and the theoretical curve for the scattering cross-section are shown in figure 3. This figure indicates that the scattering contributed by each scatterer decreases as hematocrit

increases. The agreement between results at low hematocrits and the value calculated from

Morse and Ingard's formula [13], assuming the volume of a red blood cell to be 87 m [3],

is good. Our result is slightly larger than the theoretical value. However, it should be

pointed out that the volume of the red blood cell increases with age.

The angular scattering of ultrasound by blood was measured from 60° to 150° (fig. 4).

The theoretical curve based on Morse and Ingard's formula [13] and Ahuja's result [15] are also plotted in figure 4. It should be noted that the scattering angle in this figure is

| the angle between the direction of incidence and the direction of observation. In the i theoretical calculations, we have assumed that the angular dependence is independent of \ the number of the scatterers present in the medium. This may not be true [7] in dense ' media. However, in the hematocrit range of our measurements, this effect seems to be so small that it may be neglected. Comparing the experimental data with the theoretical

curves, we can see that very good agreement exists between our result and Ahuja's ex- • press ion, which includes the effects of viscosity. ,

210
10 o

K

1 eU

2

* u

o

z

£ 4

I-

\

O \

O

^

O data point

theory

8

f - 5MHZ

O

J L J L

10 20 30 40 50

HMTCX

60

Figure 3. The scattering cross-section per cell versus hematocrit at 5 MHz.

3

2

••

-I

-2 -

Relative scattering intensity (db)

Morse and Ingard

Atiuja 8 - - -

"

Data 7/ ^ 0 Oota

Data

X Data

-+- -+- -+- 30 50 70 90 no 130 150 170 B

Figure 4. Measured angular scattering intensity normalized with respect to 1(90°). Theoretical predictions are given by the curves.

211
3. Conclusion

This paper reviews the experimental data obtained so far on the scattering properties

of ultrasound in blood. We showed the frequency and angular dependence of the scattering

and the relation between the scattering and the volume concentration of the red blood cells.

However, most of our experiments have been limited to hematocrits below 45%. This is because, in the present experimental arrangement, effects other than the scattering due to blood cells may be present in the scattered signal at very high hematocrits. For instance,

the scattering is found to be heavily dependent upon the flow rate for samples with hematocrits greater than 45%. To eliminate this effect, some of the apparatus should be redesigned

such that a clear relation between the scattering and flow rate can be established.

References

[I] Reid, J. M., Sigelmann, R. A., Nasser, M. G., and Baker, D. W., The scattering of

ultrasound by human blood, in 'Proceedings 8th ICMBE (1969).

[2] Rayleigh, L., Phil. Mag. 41, 107, 274 (1871); 47, 375 (1899).

[3] Kol'tsova, I. S. and Mikhailov, I. G., Scattering of ultrasonic waves in heterogeneous

systems, Sov. Phys. Aaoust. 15_, 390 (1970).

[4] Allegra, T. R. and Howley, S. A., Attenuation of sound in suspensions and emulsions,

J. Aooust. Soa. Am. 51, 1545 (1972).

[5] Twersky, V., On scattering of waves by random distribution; I. free space scatterer

formalism, J. Math. Phys. 2, 700 (1962).

[6] Twersky, V., On scattering of waves by random distribution; II. two space scatterer

formalism, J. Math. Phys. 1, 724 (1962).

[7] Twersky, V., Acoustic bulk parameters of random volume distributions of small

scatterers, J. Aooust. Soc. Am. 36, 1314 (1964).

[8] Beard, C. I., Hays, T. H., and Twersky, V., Scattering by random distributions of

spheres versus concentrations, IEEE Trans. Antennas Propag. AP-1

5

, 99 (1967).

[9] Twersky, V., Multiple scattering of waves in dense distributions of large tennuous particles, in Electromagnetic Scattering, M. Kerker, ed. (1962).

[10] Sigelmann, R. A. and Reid, J. M., Analysis and measurement of ultrasound backscattering

from an ensemble of scatterers excited by sine wave bursts, J. Acoust. Soc. Am. 53,

1351 (1973).

[II] Shung, K. P., Sigelmann, R. A., and Reid, J. M., The angular dependence of the

scattering of ultrasound by blood, IEEE Trans. Biomed. Engr. (to be published).

[12] Shung, K. P., Sigelmann, R. A., and Reid, J. M., The scattering of ultrasound by

blood, IEEE Trans. Biomed. Engr., (September, 1976).

[13] Morse, P. M. and Ingard, K. U., Theoretical Acoustics (McGraw-Hill Book Co., New York, 1968).

[14] Hawley, S. W., Hays, T. K., and Twersky, V., Comparison of distribution functions from

scattering data on different sets of spheres, IEEE Trans. Antennas Propag. AP-1

5

, 118

(1967).

[15] Ahuja, A. S., Effect of particle viscosity on propagation of sound in suspensions and

emulsions, J. Acoust. Soc. Am. 51, 182 (1972).

212
National Bureau of Standards Special Publication 453. Proceedings of Seminar on Ultrasonic

Tissue Characterization held at NBS, Gaithersburg, MD, May 28-30, 1975. (Issued Oct. 1976)

Paper 6.4: SWEPT-FREQUENCY ULTRASONIC DETERMINATION OF TISSUE MACROSTRUCTUREi

R. C. Waag, R. M. Lerner, and R. Gramiak

University of Rochester

Rochester, New York 14627

Ultrasound may be used to determine the acoustic structure

of tissue on a scale corresponding to the wavelengths employed

by using scattered signal to infer the organization of tissue

elements. The underlying concept is the selective reinforcement

or cancellation of certain frequencies depending on the

relation of wavelength, reflector spacing, and orientation.

A Fourier analysis of the received signal as a function of

frequency or scattering angle reveals the acoustic variations

corresponding to structure. By employing a swept-frequency

ultrasonic signal, data similar to that obtained by angle

scanning at a fixed frequency in x-ray diffraction has been

obtained. Predicted deterministic interference patterns

have been demonstrated for aluminum plates. Random scattering

for two different sizes of dextran particles has also demonstrated

predicted differences in scattering spectra. Pilot studies of

liver specimens have shown marked variations in intensity-frequency

distributions for individual disease processes.

Key words: Diffraction; Fourier transform; scattering; tissue

characterization; ultrasound.

1. Introduction

There has been a long-standing interest in characterizing tissue remotely by its

ultrasonic properties. Evidence that there is considerably more information than simply

amplitude and time-of-arri val in ultrasonic echoes exists from studies of animals

such as bats and dolphins [1].^ One of the first medical demonstrations of tissue

characterization with ultrasound was by Wild and Reid [2], who distinguished malignant

and normal breast tissue through analysis of the area under A-mode echoes.

The ultrasonic properties of tissue can be determined in various ways. Bulk measurements have been made of impedance [3] and also of acoustic absorption and speed of

propagation as functions of frequency [4]. Experience has shown that variations in these

parameters due to disease processes are difficult to assess. However, it appears that

characterization of local variations of tissue properties can provide important information

about tissue structure and, therefore, pathology.

Recent research has been directed at a quantitative analysis of echo amplitude,

signal frequency analysis, and hitherto unexplored acoustic concepts. For example,

Baum [5] and Ossoinig [6] have both shown how echo amplitude can be used to distinguish

various eye lesions. Namery and Lele [7] have observed differences in absorption as a

^This work was supported in part by NIH Grant No. 5 ROl 150106 and NSF Grant No. APR75-14890.

^Figures in brackets indicate the literature references at the end of this paper.

213
function of frequency between diseased and normal heart muscle. Among the new concepts

have been measurement of backscatter amplitude as a function of angle [8] and also

impediography [9].

Our approach to tissue characterization with ultrasound involves the adaptation of

the concepts used in x-ray diffraction and atmospheric probing. It has begun with the

use of ultrasonic frequency scanning [10] to determine the acoustic properties of tissue

on a scale corresponding to the wavelengths employed. It is expected that additional

frequency scan studies will, with angle scan data, reveal optimal combinations of frequency

and angle interrogation for tissue characterization.

2. Theoretical Basis

Biological tissue is extremely complex and has many levels of organization progressing upwards in size from DNA through organelles, cells, groups of cells in a connective tissue matrix, and finally, organs.

The model we postulate relates scattering parameters of tissue to the acoustic

structure and indicates that the 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 we develop is analogous to that used in x-ray

diffraction of amorphous materials and allows the structure of the medium to be inferred

from measurements of the scattered acoustic wave.

Our analysis begins with consideration of a plane wave propagating through a lossless

unbounded medium which has small variations in refractive index. Tissue absorption

unnecessarily complicates the analysis and will be incorporated later. Our theory deals

with refractive index rather than impedance variations because there is evidence [11]

that the density variations in tissue are very small compared to variations in the speed

of sound and, therefore, refractive index variations are a direct indication of tissue

structure.

The refractive index, which is the ratio of the average bulk speed of sound in the

medium to the speed at a specific point in the medium, may be written as

= ^= "O " "i(^)

where no is the average refractive index and assumed to be 1 in this treatment and ni(_r) is the variation of n(r.) at a point jr in space.

The equation governing the time harmonic motion of a pressure field in a weakly

inhomogeneous medium is conveniently expressed in terms of a velocity potential ^ as

$(r,t) = Re[*(r)e"^''^^] .

^Acoustic pressure is proportional to this velocity potential and can be determined in terms of the velocity potential by the relation

p(l,t) = Pq $(r,t)

in which p is the average bulk density of the medium.

214
The spatial component of this velocity potential satisfies the equation

v2^(r) + k^{r)<p{r) =0 (2)

where

Pp is the medium density and is its compressibility. This is the well-known Helmholtz

equation with a spatially-varying wave number. Using the expression for refractive index

given in eq. (1), this equation becomes

vHir) + (1 + ni(r))2k2<j,(r) = 0 (3)

where now refers to average medium properties. For ni(_r) << 1, eq. (3) may be

approximated by

v2<i)(r) + k2<^(r) = -2ni(r)k2<^(r) (4)

which is the Helmholtz equation with a forcing term.

The total velocity potential may be written

<t)(r) = ^.(r) + (1,1 (r) (5)

where

= incident velocity potential

(1)1 H first-order scattered velocity potential.

Substituting this expression into the Helmholtz equation yields

vH.ir) + kH.ir) = -2ni(r)k2[$.(r) + <p,{rn (6)

because

v2<j,.(r) + k2o,.(r) = 0.

This inhomogeneous Helmholtz equation may be solved by using the Green's function for

unbounded space. The result is

^iiL)=^ J[l>.i(r') + ((.i(r')]2ni(r') ^j^j^.]^

' dV (7)

where the geometry is defined in figflre 1. Since the variations in refractive index give

rise to relatively small scattered waves, this equation may be approximated by

'^i(^) ^ '^i^L')^AL') dV (8)

215

i
Figure 1. Scattering model geometry. The scattering volume, V, is illuminated

by a plane wave traveling in the n direction and emitted from transducer T. The scattered signal traveling in direction m is received at point P by

transducer R. The angle between the direction of incidence and reflection

is V.

This expression gives the velocity potential <f>i(r) at the point P due to variations in refractive index in a source volume V.

If the point P is far from the scattering volume with dimension d and the Fraunhofer

condition holds, i.e..

the expression

r - r

may be replaced by

r

- r m

in the exponent of the equation and

r

- r

may be replaced by r in the denominator. The result is

(10)

Now, if <t>-{r) is taken as a plane wave.

*,(!' ) = A^e^'^-^' = A^e

ikn-r

216
and

A i kr

*i(L.k) = 2^^^ / eik(ll-ni)-Il' ni(r')dV' (11)

Defining

K = k(n-rn)

where

IKI = 2 k sin ^

the velocity potential for the received scattered wave becomes

Thus, the pressure at point P is defined by the product of the factor

0 0

2Trr

and the three-dimensional Fourier transform of ni(r.) with respect to the wave vector J<.

If the acoustic properties of ni(_r) are isotropic with respect to j<, eq. (12) may

be further simplified by allowing K to be the azimuthal axis for a spherical coordinate

system. Then,

K-r' = |K| I r'

[ cosijj

and -1 o J A k2e^'^'" r r

*i(r.k) = -^2^7— j J J

ni(r')e^^'^'^°^n'2sin^dr'd^de

6=0 ij=0 r'=0

which, for elastic scattering, reduces to

A ke^"^" ^z- 1>i(j:.k)=-^ — / r'ni(r')sin(Kr')dr' (13)

Equation (13) shows that the velocity potential or pressure at r^ is proportional to the

finite Fourier sine transform of r'ni(r') when the scattering volume is spherical and the

structure of ni(_r') is isotropic.

Many structures of interest are random and require statistical approaches to characterize them. Statistics of the medium may be taken into account by considering the

scattered wave intensity instead of the amplitude. In terms of eq. (12), the scattered

wave intensity is

A 2k'+ |c!)i(r,k)|2 = -0 // e''^*(^'i"^'2) ni(r'i)ni(r'2)dV',dV'2 (14)

4TT2r2 V V

This expression may be simplified by taking the ensemble average of both sides, interchanging the order of averaging and integration, and defining a medium correlation

217
function

,

ni(liJni(l2) = B^^(ri,r2) (15)

The result is

A *i(r,k)|2 f f

eiJ<-(ll'i-l'2)B (r' ,r' )dVidV'2 (16)

If the statistics of ni(r') are independent of spatial origin, then the correlation function

becomes only a function of the difference ri - £2 = ^ and eq. (16) can be written

A 2|<^ ^ r Ui(r,k)i2=-° / e^'^-^^B fp)[ j dV] dV

4.2r2 2'^, "1- V'(p) P

The correlation function is windowed by the bracketed volume integral which depends on p. When the volume of integration is rectilinear and the integration is carried out in a ~

Cartesian coordinate system with axes originating at the volume centroid and parallel

to the volume edges, the window takes the form

where ( £ = 1 , 2, and 3) are the dimensions of the volume.

If the correlation length is small compared to the dimensions of the scattering volume

so that the correlation function becomes small before the window variation becomes

appreciable, the average received intensity expression reduces to

|*i(r,k)|2 =-2 / e^^-P (p)dV . (17)

This shows that the average intensity of the scattered wave pressure is equal to the pro- duct of the frequency dependent factor

to2p^2A 2k'+V 0 0

4tt2^2

and the 3-dimensional spatial Fourier transform of the correlation function of the

refractive index fluctuations. If the correlation function is independent of direction,

eq. (17) takes the form

|<|,j(r,k)|2 = _o

(p)sin(Kp)dp (18)

47TSin(^) J "1

^2' 0 which is analogous to the well-known relation developed for x-ray diffraction studies of

materials [12].

'^The bar represents an ensemble or statistical average.

218
Our analysis permits measurements of <}>i(r,k) or | (_r,k) | ^ to be interpreted in terms

of the refractive index variations and is based on volume scattering. Although specular

reflections which are usually much larger than volume echoes can mask volume signals

arising from near interfaces, the method can, in principle, be applied to regions where

the scattering volume does include interfaces. In addition, principles discussed here may

also be applied to the measurement of surface roughness.

The transform relation between the velocity potential and acoustic refractive index

fluctuations enables us to relate measurements of scattered ultrasound signal to tissue

structure in a way analogous to x-ray crystallography. Since the wave vector J< can be

varied by changing angle or wavelength, measurements of the scattered wave potential

obtained either by varying angle or by frequency scanning can be used to deduce structure.

For example, in the classic flat plate x-ray diffraction experiment from isotropic materials

such as liquid metals [13], circular ring patterns appear on film as a result of interference of x-rays scattered by nearby centers. Measurements of ring diameters and

knowledge of geometry and x-ray wavelength allow computation of scattering center

separations and, thus, a determination of material structure. In the acoustic case, it

is convenient to use a single transducer as a point detector instead of film to map out

the scattering pattern. This mapping can be accomplished in a way directly analogous

to the film detector by moving the transducer around the sample or, alternatively, by

sweeping frequency with the transducer fixed.

The foregoing theory can be extended to show the effect of absorption, which is known to be appreciable in tissue [3]. The development of expressions for velocity

potential and average intensity considers the Helmholtz equation with a complex wave

number, i.e..

y

= k^'dl)' = kR[l+ni(r)] + ikj[l+n2(r)]

n^ = n2 = 0 ,

(19)

where ni and n2 are variations in the real and imaginary parts of the complex index of

refraction. The imaginary part of the wave number produces attenuation and allows

absorption to be taken into account. The Helmholtz equation when the wave number is complex becomes

v2<}>(r,k) + [kp2-kj2+i2k^kj]^(r,k)

(20)

= {-2ni(i:)k^2+2n2(r)kj2-i2k[^kj[ni(r)+n2(r)]}<|)(r,k)

where

V - ^l' ^ ^'2^1

represents bulk average properties. Proceeding as in the lossless case, the following

expressions for scattered wave potential and intensity result for unit amplitude:

-k^r ikpr

*i(r.k) = ^^-y-^^ 7 f(r')e ' dV (21)

219
2k,

r

kn^e r r _K .(r'i+r'2) iKn- (r' ^-r' 2) (^2)

ki(l.k)|2 = J y f(r'i)f*(r'2)e ^ " ~ ~ dVidV'2

where

4TT2r2 V V

f(r') = ni(r') - (^) 02(1') + i(^)[ni(r') + n2(r')]

and

Si nee

kj^Cri-m) = Kp, kj(n-m) = Kj

h

and the real fluctuations in acoustic refractive index are expected to be on the order

of those in the imaginary part, eqs. (21) and (22) may be approximated as

and

(t.i(r,k)

-k.r ikr,r

2T7r

-K,-r' iKp-r'

(r')e ^ e dV

kid.k)!

V

2kjr

/2V'

iKj^.p

(23)

2Kj-r

/

V'(p)

-iK.-£

e ^ dV dV (24)

where Bp (p^) again represents the correlation of the real part of the acoustic refractive

index variations and the correlation function is windowed by the bracketed function which

contains the effects of absorption on the Fourier integral. Evaluation of the window for

a rectilinear scattering volume in a Cartesian coordinate system chosen as in the lossless case yields

n -TT— sinh

.=0 ^1^

which decays faster than the window in the lossless case and also has a rate of decay that

increases with frequency.

Equations (23) and (24) show that, to within the approximation of |kj|/|k|^| « 1, only

the real variation in refractive index gives rise to scattering. The effects of

absorption are to reduce high frequency components of the scattered waves and to give more weight to scattering from closely-spaced centers. The real negative exponential terms outside the integrals represent attenuation through the medium.

220
3. Experiments

The relations that have been developed in the preceding section show that measurement

of the scattered pressure as a function of the scattering vector J< can be processed to yield tissue structure information. Although J< can be varied either by changing angle

or frequency, frequency scanning appears more advantageous for clinical use because the same transmission path is always used and path variations are avoided.

A system (fig. 2) that permits frequency scanning of tissue specimens has been

assembled (fig. 3). The transmitter consists of a variable frequency oscillator, adjustable

Figure 2. Instrumentation block diagram. The transmitter (left) consists of a variable frequency oscillator (OSC) which is gated to the transducer by a variable

length pulse, p(t). The received signal is range-gated by p(t-T) and its quadrature components are envelope detected and recorded digitally along with range

(t), frequency (w), and target identification information (aux) for the computation of swept-frequency spectra, I (right).

pulse width gate, and a power amplifier. The center frequency, which is essentially

constant over several pulses, is slowly swept from 1 MHz to 10 MHz. The receiver employs

a wideband, high-gain RF amplifier, a range gate with variable width and delay, and a quadrature detector. The two output signals of the quadrature detector along with range

and frequency information are sampled by high speed A/D conversion equipment under computer

control and are recorded on disk or magnetic tape. The form of the data is thus convenient

for subsequent digital processing and analysis. The tissue sample is mounted on a stage that

can be moved laterally and vertically between two supports holding the transducers. Data

was collected using wideband 1/2" diameter transducers. The distance between transducers

and scattering target was always about 10 cm.

Aluminum plates were employed to demonstrate that structure information on the order

of a wavelength can be obtained by frequency scanning. Sound reflecting from the front

and back surfaces of the plates produced interference effects (fig. 4) from which plate

thickness could be calculated using the known geometry and speeds of propagation. These

highly-reproducible patterns may be used for calibration of instrumentation before data

is obtained from randomly-organized scatterers.

221
Figure 3. Swept- frequency hardware. The rack of instrumentation generates, amplifies,

and detects swept-frequency ultrasound. It develops range, frequency, and

quadrature received signals for digital processing and recording. A tissue

handling stage, ultrasound transducers, and monitor oscilloscopes are displayed

on the left. (Reproduced from Gramiak, R., and Waag, R. C: Cardiaa Ultrasound,

The C. V. Mosby Co., St. Louis Mo., 1975).

Swept-frequency scattering data was also obtained from Sephadex^ suspensions. Whereas

individual spectral sample functions are highly random (fig. 5), averages of frequency

scans (fig. 6) from two different sizes of particles clearly demonstrate the effects of

particle size on the frequency spectrum.

Both normal and diseased liver specimens have been examined with swept-frequency ultrasound. Liver was chosen because of its clinical importance and because its relatively

large homogeneous size permits frequency scanning of many independent sample volumes.

Uniform slices from the right lobe were obtained at autopsy and mounted on the movable

stage. The transducers were oriented to give a J< vector direction 4 degrees from normal

and minimize surface scattering. The common volume of transmit and receive beams was

set at 1.0 cm below the tissue surface by means of a 10 ys wide receiver gate beginning

^Sephadex consists of cross-linked dextran particles which absorb water and scatter weakly.

222
1.0 mm

Figure 4. Scattering from aluminum plates. Received pressure intensity, I, as a function of frequency (in MHz) for 1.0 mm, 3.0 mm, and 9.0 mm thicknesses,

The absolute values of nulls and the spacings closely conform to predictions

obtained using the velocity of shear waves in aluminum.

I

4 5 6

f

Figure 5. Sample scattering spectra from random media. Scattered intensity, I, as a function of frequency (in MHz) for a single statistical realization of

200 micron (upper) and 60 micron (lower) Sephadex particles. Intensity

fluctuations obscure the increased scattering at higher frequencies by

smaller particles that is revealed by ensemble averaging.

223
2 3 4 5 6 7 8 9

f

Figure 6. Size-dependent scattering in random media. Average received intensity,

I, as a function of frequency (in MHz) for scattering from two different Sephadex

sizes. The data, which was obtained by averaging 6 swept-frequency runs for each

particle size, has a variance of about 15% of the distance from the horizontal

scale to the vertical scale mark. The predicted increase in intensity for smaller

scatterers at high frequency is evident.

at 108 ys after a transmitted pulse. The stage was adjusted vertically so that surface

scattering occurred at a delay of 100 ys from the emission of a pulse. A 6 ys transmitted

pulse length was chosen to avoid surface effects while maintaining maximum power. A

typical experiment consisted of recording swept-frequency spectra at 28 horizontal

positions spaced 1.4 mm apart. Swept-frequency data from normal liver and livers showing

cirrhosis and infiltration with myelogenous leukemia have revealed marked differences in spectra from both single (fig. 7) and averaged (fig. 8) scans.

Figure 7. Sample scattering spectra from liver. Single normalized scattered

intensity spectra realizations obtained from a normal (upper) and cirrhotic

(lower) liver. The differences in periodicities in the spectra suggest that the

cirrhotic liver contained scattering centers which were more regular and more widely spaced than in the normal liver.

8.5

224
1.0 f &5

Figure 8. Averaged scattering spectra from liver. Scattering from a cirrhotic liver

is shown in A while B represents scattering from a normal specimen and C is

scattering from a liver infiltrated by myelogenous leukemia cells. In each display,

the spectra is plotted on the same intensity (I) scale and is the result of

averaging 28 runs in which the frequency (f) was swept from 1.0 to 8,5 MHz. The three curves differ in both relative signal level as well as distribution

of peaks as a function of frequency.

4. Discussion

4.1 Experimental Results

The measured spectra obtained from aluminum plates demonstrate the inverse relationship

between plate thickness and interference periodicity in the frequency or K domain. The

data from the aluminum plates is in close agreement with predictions from an optical model

developed for wave interference in thin films [14] when the locations of peaks and

spacings are computed using the speed for shear wave propagation in aluminum. Longitudinal

waves did not propagate in the experimental configuration because the incident wave arrived

at greater than the critical angle.

The data from the Sephadex experiments agrees qualitatively with the predictions of an expression describing scattering from a cloud of particles [15]. The expression predicts

that smaller particles will scatter more power at higher frequencies than larger particles.

This is evident in the smoothed spectra which do not contain the fluctuations present in

a single swept- frequency run.

Volume scattering data from various livers indicates structural differences which may

be related to pathology. Scattered power from the one specimen of cirrhotic liver that

we examined was significantly greater than that from the one normal. This wideband finding

is consistent with A-mode results obtained by others [16]. The higher collagen content of

cirrhotic liver may be responsible for increased scattered power since elasticity increases

locally with collagen infiltration. Individual frequency scans of the cirrhotic liver

225
showed significant periodicities which are different from those observed in normal tissue.

The cirrhotic liver data implies a mean scatterer spacing considerably greater than for

the normal liver tissue. Additional studies are needed to correlate acoustic structural

differences with histological determinations of structure.

The one liver with myelogenous leukemia cells that we examined scattered less power

than the normal liver. This reduced scattering is probably due to invasion of leukemia

cells altering the structure.

Further investigation is required to determine the specific structural changes

observed acoustically and establish the reproducibility of the results that we have obtained

from these studies of three individual liver specimens.

There are a number of constraints which may affect the experimental determination of

tissue structure with ultrasound. Angle scanning and frequency scanning yield equivalent

information only when the medium is isotropic. Thus, in studies of anisotropic media,

knowledge of structure orientation is needed to relate angle and frequency scanning results.

A far-field approximation is made in the model, but experimental conditions may not always satisfy this approximation. In our experimental configuration, the Fraunhofer

condition was not satisfied at the high end of the frequency scans. However, even though

our data was not strictly from the far- field, the results obtained from aluminum plates

showed good agreement with far-field predictions. This implies that the far-field condition

which simplifies analysis may be more stringent than necessary to obtain meaningful tissue

characterization with ultrasound.

The finite extent of a physical receiver produces a signal that is a summation of the

incident spherical wave over its surface area, while the Fourier- transform relations between

scattered signal and variations in index of refraction have been derived for a point

receiver. It is therefore desirable to choose the receiver aperture in conjunction with

its distance from the scattering volume so that phase variations across the receiver face are negligible. Although this can be achieved in practice, our aluminum plate data showed

good agreement with point receiver analysis even though significant cancellation was expected at the high frequency end of the scan. This implies that a point receiver

requirement may also be unnecessarily restrictive for ultrasonic characterization of

tissue.

Finite scattering volumes always exist in practice so that the interpretation of

scattered pressure as a Fourier integral of the variations in index of refraction requires

assignment of values over an infinite region. However, the assignment of zero values to refractive index outside the common volume may result in a smearing of the l< value which

is negligible for the dimensions of interest. For example, a typical |J<| value at the

midpoint of a scan is

This value is broadened by convolution with a sine function resulting from the common volume window. The widening is approximately given by the reciprocal beamwidth and, for

the beams we used which are about 1 cm wide, the smearing is less than 1 part in a hundred.

Fourier inversion of the spectral data requires knowledge of the scattered pressure for

all values of |K| . The highest usable frequency is limited by tissue absorption which

increases linearly with frequency, while resolution limits the lowest frequency for

scanning. Although increased range of |J<| may be achieved by altering the scattering angle

in addition to sweeping the frequency, data covering only a finite range of |K| can be

obtained in practice. This data may be inverted using a known functional dependence to extend it outside the measurement range or by assuming zero values which may smear the

transform function. Laboratory studies employing angle and frequency scanning are necessary

4.2 Theoretical Limitations

226
to determine important ranges of K for tissue characterization and identification of various

abnormal structures resulting from disease processes.

In the analytical model, sine wave excitation was assumed for convenience. However,

finite length pulses are used in experiments to provide more control of scattering

volume. The error introduced by finite pulse duration is a spectral broadening resulting

from convolution with the transform of tne gate function and can be made small. For example, at a carrier frequency of 5 MHz, spectral broadening due to a gate length of

10 ys is about 100 kHz and introduces less than 2% uncertainty in the frequency.

Pulse-to-pulse averaging employed to increase signal-to-noise ratio with swept-frequency

measurements introduces a slight error because all the pulses in the averaging window do not have exactly the same frequency. This is not a fundamental limitation because

frequency can be changed in steps with the averaging window or the sweep can be made slow

enough to maintain the error below any specified limit. For a sweep rate of 1 MHz/s

and an averaging time of 100 ms, the frequency shift is 100 kHz over the averaging interval

and results in an error of less than 2% at 5 MHz.

5. Conclusion

A general theory has been developed to characterize tissue structure from data

obtained in ultrasound scattering experiments. The basic relation is that the scattered

pressure at a given scattering vector is the Fourier component of the refractive index

fluctuation. Thus, by sweeping frequency, the magnitude of the scattered wavevector

is varied and a spectrum of the refractive index fluctuations may be obtained for

statistical ly-isotropic tissue. Angle scanning may also be used to vary the scattering wavevector and this may give useful information for anisotropic tissue.

Swept-frequency experiments with known deterministic and random media have shown

the promise of the concept. Preliminary data from swept-frequency experiments with normal

and diseased liver tissue show that this technique may lead to a useful diagnostic tool.

However, additional data is needed, to characterize tissue more completely and thus point

the way to optimum parameters for clinical determinations of tissue structure with ultrasound.

References

[1] Animal Sonar Systems: Biology and Bionics, Vols. I & II, G.-G. Busnel , ed.,

(Jony-en-Josas-78, France: Laboratoire de Physiologie Acoustique, 1966).

[2] Wild, J. J. and Reid, J. M,, Further pilot echographic studies on the histologic

structure of tumors of the living intact human breast. Am. J. Path. 28, 829 (1952).

[3] Gregg, E. C. and PalagallOj G. L., Acoustic impedance of tissue, invest. Radiol. 4^, 357 (1969).

[4] Dunn, F. , Edmonds, P., and Fry: W. , Absorption and dispersion of ultrasound in biological media, in Biological Engineering, H. Schwan, ed. (McGraw-Hill, Inter- University Electronic Series, .ol. 9, 1969).

[5] Baum, G., Quantized ultrasonography, in Recent Advances in Diagnostic Ultrasound,

E. Rand, ed. (C. C. Thomas, Springfield, 111., 1971).

[6] Ossoinig, K. C, Quantitative echography - the basis of tissue differentiation,

J. Clin. Ultrasound, 2, 33 (1974).

[7] Namery, J. and Lele, P. P., Ultrasonic detection of myocardial infarction in dog, in

Proceedings of 1974 Ultrasonics Symposium, p. 491 (IEEE Cat. No. 72 CHO 708-8 SU,

1974).

[8] Chivers, R. C, Hill, C. R., and Nicholas, D., Frequency dependence of ultrasonic

backscattering cross-section: an indicator of tissue structure characteristics, in

Ultrasonics in Medicine, M, de Vlieger, D. N. White, and V. R. McCready, eds., p. 300

(Excerpta Medica, Amsterdam, 1974).

227
[9] Jones, J. P., Impediography: a new ultrasonic technique for diagnostic medicine,

presented at the Nineteenth Annual Conference of the American Institute of Ultrasound

in Medicine, 5-10 October 1974, Seattle, Washington.

[10] Waag, R. C. and Lerner, R. M., Tissue macrostructure determination with sweptfrequency ultrasound, in Proceedings of 1973 Ultrasonics Symposium, p. 63

(IEEE Cat. No. 73 CHO 807-8 SU, 1973).

[11] Fields, S. and Dunn, F., Correlation of echographic visual izabil ity of tissue with

biological composition and physiological state, J. Aooust. Soc. Am. 54, 809 (1973).

[12] Azaroff, L. V., Kaplow R., and Kato, N., X-Ray Diffraction, p. 85 (McGraw-Hill, Inc.,

New York, 1974).

[13] Kakudo, M. and Kasai, N., X-Ray Diffraction by Polymers, (American Elsevier

Publishing Co., New York, 1972).

[14] Jenkins, F. A. and White, H. E., Fundamentals of Optics, 3rd edition, p. 273

(McGraw-Hill, Inc., New York, 1957).

[15] Morse, P. M. and Ingard, K. U., Theoretical Acoustics, p. 439 (McGraw-Hill, Inc.,

New York, 1968).

[16] Mountford, R. A. and Wells, P. N. T., Ultrasonic liver scanning: the A-scan in

the normal and cirrhosis, Phys. Med. Biol. V7, 261 (1972).

228
CHAPTER 7

IMPEDANCE PROFILE TECHNIQUES

229

National Bureau of Standards Special Publication 453. Proceedings of Seminar on Ultrasonic

Tissue Characterization held at NBS, Gaithersburg , MD, May 28-30, 1975. (Issued Oct. 1976)

CHAPTER 7. IMPEDANCE PROFILE TECHNIQUES

Paper 7.1: ACOUSTIC IMPEDANCE PROFILING: AN ANALYTICAL AND

PHYSICAL MODEL STUDY*

A. C. Kak

School of Electrical Engineering

Purdue University

West Lafayette, Indiana 47906

and

F. J. Fry

Fortune-Fry Laboratories

Indianapolis Center for Advanced Research

Indiana University Medical Center

Indianapolis, Indiana 46202

Qualitative measurements of the acoustic impedance of tissue have

been extensively exploited for medical diagnosis. In this paper, we report on an analytical and physical model study directed towards

quantifying this parameter. The model selected is a medium having

plane-parallel impedance interfaces which is insonified at normal

incidence. Analytical expressions and computer algorithms are given

for determining the impulse response of the medium and the impedance

profile from this impulse response. Experimental data are presented

which shows the accuracy with which the method can presently be

applied.

Key Words: Attenuation; computer; deconvolution; impedance; impulse

response; layer model; lucite; ultrasound.

1. Introduction

Acoustic characterization of living tissue in a quantitative manner should be of

considerable significance to diagnostic medicine. The ability to accurately classify tissue

types in a non-invasive atraumatic manner is the sought-after goal. A variety of acoustic

techniques offer possibilities for tissue characterization, hopefully leading to precise

identification. Since no one acoustic parameter is likely to qualify as a unique

determinant in tissue characterization, it is important to assess a number of acoustic

properties in an attempt to identify indices which may be definitive. Under the circumstances presented in clinical diagnostic medicine, as differentiated from laboratory

measurements on excised specific tissue types, it is apparent that considerable problems

exist if an attempt is made to uniquely define only one specific acoustic parameter.

Acoustic impedance profiling is an example typifying this difficulty. In order to derive

this parameter, we consider a physical model of a lossless medium having acoustic impedance

transitions associated with discrete plane-parallel interfaces and an interrogating acoustic

pulse normally incident on these interfaces. The theory of linear systems implies applicability of the superposition integral which operationally convolves the impulse response

of the system with the input interrogating waveform to yield the output waveform. Thus,

we can derive the impulse response from a knowledge of the input and output waveform. From

this impulse response, the impedance profile for the idealized model can be derived in

a rigorous manner.

Work supported by National Institute of Health Contract NOl-NS-3-2319.

231
In any tissue or organ system, however, the medium is always lossy. This attenuation

loss is composed generally of a number of components {viz., intrinsic absorption, scattering

An average value of absorption loss of soft tissues of the human body is 1 dB per centimeter

of path length at 1 MHz frequency. Soft tissues also show an approximately linearlyincreasing absorption loss as a function of frequency. Since there is a characteristic

frequency dependence of attenuation in tissue, it is apparent that the temporal character

of the acoustic interrogating pulse will be modified depending on its bandwidth as it

passes through the tissue. Thus, in order to arrive at an appropriate acoustic impedance

profile for medically-relevant systems, practical methods must be developed which will

permit the simultaneous determination of the attenuation profile and the impedance profile.

In this work, the attenuation losses have been inserted in an a priori fashion and the

impedance values computed for the model material. Individual layer thickness variations

with variable amounts of insertion loss are computed from a determination of the transit

time between interfaces after an a priori insertion of sound velocity for individual

layers

.

Another approximation made in the idealized model is to ignore higher-order reflections

This approximation would be valid for tissues and organs which possess sufficient absorption

to highly attenuate such reflections. The rationale for using an idealized layer model is based on a number of factors including the fact that, to the present, substantially all medical diagnostic procedures using ultrasound have relied heavily on a qualitative

interpretation of acoustic impedance differences at tissue interfaces. Conceptually, the

individual layer methodology can be extended to include any number of reflective targets in

a tissue or organ system. It seems appropriate to perform the necessary research leading

to a more quantitative description of acoustic impedance as it seems apparent that this

will be one of the parameters of significance in a quantitative approach to differential

diagnosis of disease.

Methods of signal processing and computer technology have been applied to acoustic

interrogating pulses in this study so that ultimately real time, or near real time, quantitative descriptions of acoustic impedance profiles will be possible. Detailed descriptions

of the analytic approach to the layered model, specific algorithm considerations and

computer simulation studies are discussed later. The algorithm implemented for impulse

response determination for the experimental studies uses the matched filtering technique

which is applicable to a large class of acoustic waveforms.

The first major subdivision presents the analytical descriptions, from a physical

acoustics viewpoint, signal processing methods and computer simulations. Experimental

results are presented in the second major subdivision.

2. Relationship between the Impedance Profile and the Impulse Response

2.1 No Multiple Reflections and Lossless Media

Let us consider a target interrogated by a plane acoustic wave. In the linear regime

of operation, the reflected wave can be considered to be a convolution of the input signal

and an impulse response associated with the medium. (This is also true for the transmitted

wave for some different impulse response.) This impulse response is strictly a property

of the medium in the direction of propagation of the incident wave. Relationships between

the impulse response and the impedance profile of a medium have been a matter of investigation in the past [1,2]^. The relationships that have been developed in these investigations are iterative in nature. By this we mean a medium is considered to be composed

of a large number of layers, each of constant acoustic impedance, and one calculates the

impedance of one layer at a time starting from the first. The accuracy of the calculation

at each step depends upon how accurately the previous impedance values have been calculated.

In practice, these techniques cannot often be used because their recursive iterative

nature is a source of instability.

Non-recursive relationships are-a topic of current research. In a recent paper by Jones [3], one such relationship was presented for the restricted case of monotonical lyFigures in brackets indicate the literature references at the end of this paper. 232
increasing or decreasing impedance profiles in the absence of multiple reflections. We

will now show that the same relationship holds for any arbitrary impedance profile. We

will first rederive the non-iterative relationship for the monotonically-increasing profile

by a method different from that given by Jones. The derivation given here provides insight

for the general case of arbitrary impedance profiles, which will be presented later.

Let a monotonically-increasing or decreasing profile be approximated by discrete

layers of constant impedance. Evidently, as the number of layers in such an approximation

approaches infinity for an acoustic target of finite extent, the impulse response calculated

from the discrete approximation should approach that from the continuous profile. The

discrete approximation may be constructed in such a way that the reflection coefficient

at each impedance boundary is the same; let this value be denoted by r. It is easily

seen that the impulse response of such a discrete profile is a train of impulses. Let

the time instances at which the reflected impulses are received be denoted by tj, t2,

t3 If h(tni) denotes the strength of the reflected impulse at tf^, then it can be

shown that

h(t^) = rO-r^f-^ . (1)

Let us integrate the impulse response from 0 to a time t with 1 t <t^

t s(t) =/h(t) dt = V rd-r^)"^-! .

Substituting (1) in (2), we get

1 ^^ 2\m

. Then

(2)

For a given t as m « and r ^- 0, the discrete impedance profile will approach the

continuous profile. As m ^ the time intervals between successive reflections from

the impedance discontinuities approaches zero, so that t^ approaches t. Also, as m

r must approach zero in such a way that the following is always satisfied [4]

logj^

1+r m = (4)

log

where = Zp^/Zg, Zm being the impedance of the mth layer in the discrete profile, and Zn the impedance or the water bath in which the target is immersed. Substituting (4) in (3)

and taking the limit r 0, we get the following result (for details see [4])

s(t) = / h(t) dt = ^ log 2^ (5) 0 0

where Zt is the acoustic impedance of the medium at a point where the acoustic impulse

arrives in t/2 seconds (we assume the medium to be non-dispersive).

In deriving the impulse response-impedance profile relationship given by (5), we assumed in the discrete approximation that all reflection coefficients are equal. This

assumption constrains the impedance profile to be either monotonically-increasing or decreasing. We will now show that the equation (5) is valid even when the impedance

profile does not satisfy this condition. We will continue to assume the absence of

multiple reflections. In the discrete approximation of a continuous medium, let r^

be the reflection coefficient at the kth step, the kth step being a transition from

impedance Z|^_-] to Z|^.

233
By definition,

(6)

Clearly,

(7)

As the continuous medium is approximated by increasingly finer steps, each r|^ ^ 0. In such a limit, each log (l+rk)/(l-r|^) -> 2r\^ and, therefore, from eq. (7), we get

(l°9 ^m)r^.O

k=l

(8)

Again, in the absence of multiple reflections, each

h(t,) = r, V (l-r/ (9)

As each r^ ^ 0, we get from (9) and (7)

log h(t|^) - log h(t,^_^) = log

1

2 (log Zj^-log Z|^_^)

log

1

4

2 ^k-r^°9 ^k-2)

2 log z,^ - log Z|^_-|

The normalized impedance z is a function of distance. It can also be considered

to be a function of time, in the sense z(t) is the impedance of the medium at a position

which the incident wave takes t/2 seconds to arrive at. In fact, in the absence of any

knowledge of acoustic velocities in the medium, the best one can do is to find the impedance

profile as a function of time. Let At = t|^-t|^_i =

^i^..] "'t|^_2 ~ then

log h{t^)-log h(t^_J

At —rz = log At

log Z|^-log z,^_i At

log

(At)'

log z^.^-log z^_2

"

At

log Z|^-log Z|^_-, At

As t ^ 0, we get from the above equation

(11)

h(t) = C ^ log z(t) (12)

where C is a constant of integration. To evaluate this constant, we make use of the boundary;

condition that for some non-zero distance near the first change in impedance, the impedance

variation is increasing or decreasing, making eq. (5) valid for times t that correspond I to reflections from such regions. This implies C = 1/2. Substituting this in eq. (12)

234
and integrating, we get

which completes the proof.

2.2 Multiple Reflections Included

In the derivations in the preceding subsections, we assumed that multiple reflections

made negligible contributions to the reflected waveform at the receiver. There are experimental situations where such an assumption would be justified. For illustration, consider

a medium in which the impedance changes in discrete steps, and let all these changes be

of equal magnitude. The reflection coefficients at each impedance change will then be

the same and let r denote their value. It is easily seen that the ratio of third-order

reflections to first-order reflections is proportional to r^, the ratio of fifth-order to first-order reflections is r^, and so on. Evidently, if r is equal to, let us say, 0.1,

all the reflections higher than the first order can be neglected. By extending this

argument, one concludes that so long as the total impedance change is small, and so long

as its rate of change is small, neglecting higher-order reflections would introduce

negligible error. In biological experiments, soft tissue with tumors would often satisfy

this condition. But if the interrogation is made through bone, this assumption would be

grossly violated.

We will now derive a relationship between the impulse response and the impedance

profile for the case in which, in a discrete approximation to a continuous medium, all

the reflection coefficients can be considered to be equal.

To find the effect of third-order reflections on h(T)dT, consider the pulse bounce

diagram in figure 1. Each I^^j represents the amplitude of a positive traveling impulse

through section between times t-j and t-j+-[ where i is the largest integer less than

or equal to (j+T-i)/2. From the pulse bounce diagram, it can be shown that Ij_k j has k-1 second-order reflections. Therefore, each h(tj) has L(j) =1+2+...+...+ (j-3) +

(j-2) = ( ( j-2) ( j-1 ) )/2 third-order reflection components, each component having an amplitude

proportional to -r^{^-r^)j~^ . It is easily shown that each h(tj) is now given by

h(t„) = rd-r^)"^-^ - L(m) rh^-/f-^ (14)

where

. L(m) = lllllllimill . (15)

Therefore,

t

"1 /h(T)dT = ^

rd-r^)''"^ - ^

L(k) r^d-r^)'^-^ (16)

° k=l k=l

where tm £ t < t^+i . In the limit as the discrete profile becomes continuous, r -> 0 and

m -> 00 in such a way that eq. (4) is satisfied. The first term on the R.H.S. in (16) is the same as the expression in (2). The problem of finding the limit of this expression was rigorously solved earlier, the result being eq. (5). The result for this expression

could also be obtained by a not-so-rigorous method by recognizing that as r ^ 0 and m -> <», (l-r2)ni-i 4- 1. This makes the first term in (16) equal to mr. Now as r 0, we get from

(4), m ^- l/2r log Zm. This implies that as r ^ 0 and m ^ «=, mr = 1/2 log Zm, which

when substituted in

tf h(T) dx = mr,

*o 235
X —

Z2 Z3 Z4

r

1 2

• 3

' 4

r i-1 ^

i h(t)o

h(t),

h(t)2

<^

h(t)3

h(t)4

<^

h(t)5

<^i h( t)j.i

h(t)j

Figure 1. Pulse-bounce diagram for multiple reflections in a paral lei -plane

target of i layers.

leads to the same result as in (5). We will use this line of reasoning to find the limit of

the second term. We can write in the limit m ^ «> and r 0,

/h(T)dT = mr - r

mr - r

ZL(m)

k=l

3 m(m-l)(m-2)

(18)

where we have made use of (15). Since m -> 00, the above expression becomes

t / x3 /h(T)dT = mr - ^^p- . (19)

0

Substituting (17) in (19) and recognizing that in the limit t^ ^ t, we get

(20)

0 0 \ 0 /

It is immediately clear that in the presence of third-order reflections, the impedance

profile is not uniquely related to the integral of the impulse response. We refer to unique

ness in the sense that eq. (20) is a cubic equation in log Z(t), therefore, in general, it

f has three roots for every t.

One can similarly derive non-recursive relationships of the type (20) which would

include reflections of, say, nth order, the right-hand side in such a case being an nth

236

J
order polynomial in log Z(t). The futility of stjch an effort is clear from the fact that

for any value of t, /t h(T)dT would not yield a unique value for Z(t) because of reasons mentioned above. °

Limitations such as above should not reduce the importance of eq. (13) which holds

in the absence of multiple reflections. As had been mentioned, experimental situations of

importance do exist which satisfy this condition,

3. Determination of the Impulse Response

If a treatment of the subject of the impedance profile determination was to be done

in the order in which the data is processed, then the first topic to be discussed should

be the calculation of the impulse response from the reflected waveforms. Our reason for

first presenting the relationships between the impulse response and the impedance profile

was to provide the reader with motivation for the material to be presented in this section.

If the incident and the reflected ultrasound waveforms in a given direction through a medium are considered an input and output, respectively, of a linear system, then by the

theory of such systems the medium can be characterized by an impulse response in that

direction. Let x(t) and y(t) denote the input and output waveforms, respectively. And

let h(t) be the impulse response of the medium along the path of propagation. Then by

the theory of linear systems,

y(t) = /hd) x(t-T) dx . (21)

Evidently, given a knowledge of x(t) and y(t), the above integral equation can be solved

for h(t). Depending upon the extent of a priori information available, the above equation

can be solved by one of a large number of techniques that have been developed to date [5].

Let us consider the case in which the target can be assumed to be composed of a countable number of parallel layers. (In practice, for a focused transducer, this

assumption need to be strongly satisfied only in the region of the focus.) The impulse

response of such a target can be written as

h(t) ^La. 6(t-i.) (22)

where 6(t-Ti) represents an impulse located at t = i-j, and where, in the absence of

multiple reflections, xi is the time at which the reflection from the ith discontinuity

arrives at the receiver, the strength of this reflected impulse being A^ . Substituting (22)

in (21), we get for the received waveform y(t):

y(t) =I:a. x(t-x.) . (23)

Given the received waveform, the aim is to estimate the values of the coefficients A^.

.

The waveform y(t) is in practice recorded in the presence of noise. Also, in the digital

calculation of the impedance profiles, further noise is introduced by the sampling and

quantization of the waveforms. If the noise can be considered to be white Gaussian, the

following correlation technique yields the maximum likelihood estimate for the coefficients

A-j . In the presence of colored noise, the optimality of the estimate can be preserved by

using a prewhitening filter [6]. However, this case will not be treated here.

Multiplying both sides of (23) by x(t+x) and integrating over the entire time axis, we

get

R (x) =y^A.R (x-x.), (24) xy ^ ' ^ 1 XX ^ V ^

'

237
where Rxy('f) ^nd Rxx (T-^i) are the cross-correlation and autocorrelation functions,

respectively. If the cross-correlation function is sampled at t = xf, 13, we

can then generate a set of simultaneous equations given by

R (tX) =Va.r (t; - T.) . xy ^ 2' 1 XX ^ 2 V

(25)

In practice, it is useful to take the sampling instant if equal to the corresponding x- Substituting this in eq. (25), we get

^

XX

R (tt xx^ 1

R (t, - T„)

xx^ 1 2'

R (x, - xo) R (0) XX M 2' xx^ '

R (ti - T.,) xx^ 1 N'

R (to - T.,) XX ^ 2 N'

«xx(°>

(26

The coefficients A-j can thus be determined provided the x-j are known. An analysis of

the reflected waveform for the case of weakly-damped oscillatory inputs shows that the

times x-j correspond to the maxima of the envelope of the cross-correlation function Rxy(T)

with an uncertainty of a half a cycle. This is also true for non-oscillatory waveforms

provided the small est- layer transit time in a multilayer target is much greater than the

effective duration of the incident waveform. (By oscillatory waveform, we mean narrow-band

waveforms that take non-zero values over many cycles of oscillations. On the other hand,

the term non-oscillatory waveform is not restricted to unipolar pulses but includes highlydamped waveforms one or two cycles in duration.) For target layer thicknesses large

compared to a wavelength, the errors caused in the calculation of A-j by this assumption is

negligible. In this case, the diagonal term in the matrix of coefficients in eq. (26)

is much larger than the non-diagonal terms. (It is perhaps intuitively clear that as the ratio of the product of the diagonal terms in a matrix to the total determinant

approaches unity, the calculations become more insensitive to the noise in the non-diagonal

terms.) For illustration, we have shown in figure 2 an example of an oscillatory waveform.

Figure 2. Incident waveform used with lucite-water-qlass target.

238
x(t), that was used to interrogate targets for tissue profiling. In figure 3, we have shown

the reflected waveform, y(t), from a lucite-water-glass target. Figure 4a shows the

cross-correlation function Rxyd) for the waveforms in figures 2 and 3. The t/s required

in eq. (24) were determined by first rectifying the cross-correlation function and then

locating the peaks of the envelopes of the resulting function. The envelope function is shown in figure 4b.
For non-oscillatory waveforms, we have developed a new deconvol ution procedure that

appears very promising. This technique is essentially a modification of the direct

deconvolution techniques to reduce their extreme sensitivity to noise.

Let the input waveforms be digitized and let the samples of the waveform be represented

by Xi, X2, X3, as shown in figure 5 where the sample value 1 is the maximum at the

first peak and occurs for the Nth sample. The z transform of this waveform can be written

as*

X(z) = + X2Z + X3Z^ + ... (27)

if Y(z) denotes the z transform of the received waveform. If y^, y2, ... denote the samples

of the reflected waveform, then

Y(z) = y^ + y2Z + ... + ...

Figure 5. Broadband non-oscillatory waveform used for the determination of acoustic

impedance profile.

Then H(z), the z transform of the impulse response, is given by

H(z) = UH = \ ^ ^ T (28) ^ ' X(z) X"! + X2Z +... + ... ^

'

or

H(z) = ^

[(y^ + y2Z + ...) - H(z)(x2Z + x^z^ + ...)]. (29)

If hi, h2, ... denote the samples of the impulse response, then from the above equation,

the recursive relationship for the calculation of the samples h-j from the input and the

output waveforms is

h,. -'-[y, - (X2h..^ ^X3h._2^ ...)]. (30)

*Note that in eqs. (27) through (33), the symbol z does not stand for the normalized

acoustic impedance.

240
Note that Xi is the first sample of the incident waveform, and because of the way it appears

in the above recursive relationship, the calculation of all hi is critically dependent upon

the accuracy of this sample and also the sensitivity of the calculation to noise is dependent upon the magnitude of Xi.

To get around the difficulties mentioned above, some researchers take the first

sample of the incident waveform at the first maximum. For either unipolar or bipolar

waveforms, this usually means neglecting a significant portion of the waveform, leading to inaccuracies

.

We are currently developing techniques that use the a priori knowledge about the waveform to modify the above procedure in order to eliminate the difficulties mentioned there.

An explanation of some of the concepts that we have developed follows.

Let us assume that the first maximum occurs at the Nth sample and up to this sample

the incident waveform obeys the following relationship

which really means an exponential growth up to the first maximum. Therefore,

X(z) = k"-l.kN-2z.....zN-'*x„„z~.x„,/*'.... . (32)

where we have assumed that the waveform is normalized so that the first maximum has a value

of unity. By substituting eq. (32) in the relationship H(z) = Y(z)/X(z), it can be shown

that the recursive relationship for the samples of the impulse response can be written as

•^i l-XjIi+ik {^i+N-r'^^i+N " ^^^H+^ " "^^N+Z^^i-l

+ (V2 - ^V3)^•-2 ^ ^}' (33)

Note that X[\j+-|k will never be equal to 1 because: (i) X[\|+] - = 1, since X[\j+-| and are adjacent samples of the incident waveform, and, (ii) since k'^ - 0 for N not very large, so

k will, in practice, be much less than 1.

4. Experiments

Essentially all experimental data collected has been on physical models involving

layered media having plane-parallel faces, which can be considered of essentially infinite

extent in the direction perpendicular to the incident longitudinal acoustic wave propagation.

This wave is at normal incidence to the interfaces of the model. The exception to the

plane-parallel face structures involves acoustic wave transmission through excised sections

of human skull bone which can considerably modify the amplitude and temporal character of

the acoustic pulseAcoustic interrogation of the models has involved both damped oscillatory and non- oscillatory pulse type waveforms, as will be expanded on subsequently.

4.1 Instrumentation and Technique

A block diagram of the system components used for this study is shown in figure 6 and

a photograph of the equipment is shown in figure 7. For the damped oscillatory wave

interrogation, a focused transceiver is used. Non-oscillatory type pulses are generated by

an unfocused plane-face one-inch diameter disc, and input and output waves from the model

are received on a small probe. Each of these schemes is presented in figure 8.

241
z

Panametric 5050 PR

Pulser Receiver

BBN

Power

Source

_r\.

Coordinate System

Y

c Probe

Distilled Water

Source Target

BBN

Amplifiers

Temperature Controlled Tank

HP214A

Pulse Generator

Oscilloscope Biomation 8100

Oscilloscope Biomation 8100 PDP 11/45 Computer

Figure 6. Schematic diagram of system for acoustic impedance determination.

Figure 7. Acoustic interrogating system: (A) Panametrics 5050PR; (B) oscilloscope;

(C) Biomation 8100; (D) pulse generator; (E) power supply for BBN Unipolar Pulse

Generator; (F) coordinate system; (G) amplifiers for use with BBN style probe;

(H) interrogating tank, (see also figure 11.)

242
Probe

Non-oscillatory transducer

U

10 cmTarget

Figure 8a. Schematic diagram of non-oscillatory pulse interrogation.

Target

Figure 8b. Schematic diagram of focused-transcei ver interrogation.

When the non-oscillatory pulse system is used for interrogation, the system configuration

involves the non-oscillatory transducer source driven by an appropriate ramp voltage. The

small piezoceramic probe records the input wave before entering the target and the received

reflected wave from the target. An example of these waveforms for a single layer lucite

target is shown in figure 9. Transceiver operation involved a transducer having an on-axis

longitudinal beam plot (taken by recording reflections from a 1.0 mm diameter steel ball

target) and a lateral beam plot recorded with the same ball in the focal plane. These

plots are shown in figure 10. The resonant frequency of this particular transceiver is 1.7 MHz, and the focal plane is 20 cm from the transceiver face, with a total aperture

angle of 14 degrees. No programs have been implemented correcting for amplitude drop in

the longitudinal direction, angulation variations across the beam profile for planar

targets and out-of-phasing occurring as the targets move out of the focal zone for the

focusing transceiver. Of necessity, interrogated thin layered targets will yield data

with the greatest absolute accuracy under these circumstances.

Digitized waveforms are stored in the digitizer (8-bit with 10 ns minimum sample

interval) in 2,000 word lengths. This word sequence is transferred to DEC tape on the

dedicated PDP-11/45 computer. Two waveforms, the input waveform to the target and the

received waveform, are separately recorded. For the non-oscillatory pulse, the input waveform is recorded on the probe with no target in place, while for the transceiver arrangement,

the input waveform is recorded from an essentially perfectly reflecting target placed

at the focal plane. In either case, the target is then placed in position for the received

243
Front surface

of lucite Back surface

of lucite

Figure 9. Probe output for signals from a single-layer-lucite target in water with non- oscillatory acoustic interrogatory pulse.

Figure 10. Field plot of the interrogating beam from the focused transceiver.

waveform recording. This recording method facilitates the program methodology which performs

a cross-correlation as discussed previously. From this correlation function, the impulse

response of the system is computed. Subsequent processing, as discussed previously, yields

the impedance profile.

In order to project from the present status of these analytical and experimental

considerations to the realm of human tjssue parameter characterization, questions of

spatial resolution and sensitivity require discussion. Focused transceivers of the type

used for this experimental program have a lateral resolution which is substantially equal

to one wavelength at the transceiver resonant frequency operation. This resolution capability is demonstrated in figure 11. Two converging monofilament nylon threads (0.010 in diameter) are scanned by the transceiver and the position of coalescence of two separate

target delineations into one single reflection is taken as a meaningful indication of

244
Figure 11. Reflections from V configuration of 0.005 in diameter nylon filaments.

The two white dots in the middle of the left hand photographs just below the white

horizontal focus maker line correspond to the echoes received from the V element shown

on the right. (A) 3.5 mm nylon element spacing; (B) 2.0 mm spacing; (C) 1.2 mm

spacing; (D) 0.8 mm spacing.

lateral resolution. Depth resolution is determined by using a similar target. An indication

of depth resolution capability can be obtained from figure 12. With the electrical output

wave shown, it is evident that, depending on the type of target, spacing distances of one

or two wavelengths can be resolved.

Figure 12a. Electrical driving pulse to transducer. Spacing of vertical lines

is 0.5 vjS. 245
Figure 12b. Electrical output wave from transducer responding to reflection from

a plane target normal to direction of sound beam propagation.

Some soft tissue interface acoustic impedance differences are listed in table 1 [7].

It is apparent that the system sensitivity should be such that it should be capable of

detecting reflection differences at interfaces down to the order of one part per thousand.

Table 1. Absolute values of acoustic reflection coefficients [7]

Water Fat Muscle Skin Brain Liver Blood Skull Bone Lucite

Water 0.0 0.047 0.02 0.029 0.007 0.035 0.007 0.57 0.35 Fat 0.067 0.076 0.054 0.049 0.047 0.61 0.39

Muscle 0.009 0.013 0.015 0.02 0.56 0.33

Skin 0.022 0.0061 0.029 0.56 0.32

Brain 0.028

* 0.00 0.57 0.34

Liver 0.028 0.55 0.32

Blood 0.57 0.35

Skull Bone 0.29

*Clotted and freshly-injected blood can be detected ultrasonically in the live and formalin

fixed brain.

Sensitivity data taken with a typical transceiver used in these experiments are shown in

figure 13. A linear scan of the transceiver is made across a specially-constructed target

which has step gradations in acoustic impedance ranging from 0.2% to 1.0%. By appropriate

settings of the gain and reject controls in the electronic system, it is possible to detect

the 0.2% acoustic impedance mismatch in the target. Questions involving the accuracy with

which acoustic impedances can be determined at deep body sites remain to be answered. The

subsequently-presented experimental data on physical models will show the present status of

accuracy and repeatability as the targets are interrogated and the digitized data transmitted

to the computer for processing.

246
Figure 13. Reflection from a graded set of impedance mismatches. The impedance

changes are shown from 0.2% to 1.0% and the horizontal white line above these

numbers shows the relative strength of the reflection as a function of system

sensitivity indicated as ranging from 40 dB (least sensitive) to 10 dB (most

sensitive)

.

4.2 Experimental Data

All experiments were performed in distilled water maintained at 37 °C in the sound tank

Table 2 shows the results of runs involving damped oscillatory wave interrogation for single

layer lucite targets of different thicknesses. A single run is shown for one thickness

of lucite using the non-oscillatory pulse system. Values were inserted for the attenuation

coefficient. Because of the differing frequency content of the interrogating pulse, a different a(0.30 cm"^) was used for the non-oscillatory pulse interrogation than was used

for the oscillatory wave a(0.35 cm"^). When the same piece of lucite was interrogated

by resetting the target in the sound field and the signal reprocessed, the reproducibility

of the lucite acoustic impedance was within ±1% of the average of all runs. Table 3 shows

the results of separate interrogations of two different multilayer targets (lucite-waterlucite) in the interrogating tank. Since there was no correction for focusing or amplitude

drop-off in the interrogating field, the calculated value for water deviated from its true value by approximately 20%.

247
Table 2. 1.7 MHz interrogation of single lucite layer

in distilled water

Lucite Thickness

Measured (mm)

Oscillatory

Wave

Non- Oscillatory

Wave

6.64

9.33

12.28

6.64

Lucite Thickness

Computed (mm)

4.85

6.59

9.19

12.17

6.51

Derived Acoustic Impedance

(g cm"^sec^xlO"^)

Lucite Water

Zi

3.25 1 .46 3.23 1.52

3.25 1.58

3.17 1 .59

3.10 1.52

In the calculation, we have used a velocity of 2.68 mm/ys for lucite and have assumed

a = 0.35 cm"i and 0.30 cm"^ for the oscillatory and non-oscillatory waves, respectively.

Literature values [7] for lucite are a = 0.2 cm"i at 1 MHz and Z = 3.2 x 10^ g cm'^sec"^

Run

Table 3. Oscillatory-wave (1.7 MHz) interrogation of

lucite-water- lucite target

Model Thickness (mm)

Lucite Water Lucite

Computed Thickness (mm)

Derived Acoustic Impedance

(g cm"2sec"ixlO"^)

Lucite Water Lucite Lucite Water Lucite Water

Zi Z2 Z3 z.

1 5.98 9 07 6 12 5 98 9 06 6 21 3 14 1 .56 2 99 1 .93

2 5.98 9 07 6 12 5 98 9 05 6 22 3 05 1 .47 3 12 1 .81

3 4.86 9 07 4 86 4 88 8 90 4 77 3 22 1 .47 3 10 1 .77

Lucite in water is, of course, not a very appropriate model for soft tissues of the

human body because of its large reflection coefficient (approximately 30%). More appropriate

targets which have been interrogated include pC rubber in water and silastic rubber multilayer sandwiches in water. The silastic sandwiches have been constructed to have impedance

differences across the interfaces of approximately 1%. These targets have yielded values

which are approximately correct and the results of the ongoing studies will demonstrate

the validity of this approach.

This model study has additionally involved interrogation of layered media behind

human skull bone sections. Human skull itself presents a multilayered media which

considerably modifies the amplitude and temporal character of a transmitted ultrasonic

wave. An appreciation of this acoustic wave modification can be obtained by observing

the waveforms of figures 14, 15, and 16 [9]. In figure 14, the damped oscillatory wave

is that received on a large-aperture focused transceiver when the wave is reflected from

a multilayer target in water. Figures 15 and 16 show the result of inserting a human skull

bone section at two different skull regions between the transceiver and the target. Figure

17 shows the received signal from an approximately 1% acoustic impedance difference

silastic-silastic interface with an intervening human skull section. To date, the results

of interrogating a single lucite target in water behind a human skull section, with the

reference input waveform recorded on the transceiver from an aluminum block reflector

behind the skull, are shown in table 4. 248
Front surface

of lucite

Rear surface

of lucite Transducer

focus here

"Time Scale

1us/div.

Front surface

of glass plate

Figure 14. Focused transceiver output from a water-lucite-water-glass series of

interfaces without intervening skull bone.

Front surface

of lucite

Rear surface

of lucite Transducer

focus here

Front surface

of glass plate

Figure 15. Focused transceiver output from a water-lucite-water-glass series of

interfaces with intervening skull bone between the transceiver and the first

water-lucite interface.

249
Front

surface

of lucite

Rear

surface

of lucite

Time Scale

1 jus/div.

Front surface ol glass plate

for the data of figure 15.

Front Surface

of Silastic

Silasticsilastic interface

Time Scale

0.2 |us/div.

Silasticlucite interface

Table 4. Oscillatory-wave interrogation of a single layer

of lucite behind human skull section

Skull

Position

1

2

Test

Material

lucite

lucite

Derived Acoustic Impedance

(q cm~^sec"^xlO^)

Thickness

9.3 mm

9.3 mm

2.95

3.21

2.08

2.12

250
It is our feeling that this research in the quantitative determination of acoustic

impedance as it might be applied to soft tissues is in its early stages of development.

Much work needs to be done to relate this particular parameter to the other interacting

acoustic parameters mentioned previously. Progress towards the goal of tissue typing

through acoustic parameter characterization will be aided by accurate assessment of this

parameter.

The authors would like to thank Leland R. Beaumont, John Wolfley, and Kris A. Dines

for their contributions to the development of the theoretical ideas presented here, and

Narendra T. Sanghvi for help and assistance in implementing the experimental program.

References

Ware, J. A. and Aki , K., Continual and discrete inverse scattering problems in a stratified elastic medium, J. Acoust. Soa. Am. 45^, 911 (1969).

Boakye, K. A. and Wing, 0., On the analysis of realization of cascaded transmission

line networks in the time domain, IEEE Trans. Circuit Theory, CT-20 , 301 (1973).

Jones, J. P., Impediography : a new ultrasonic technique for nondestructive testing

and medical diagnosis, in Ultrasonics International 1973 Conference Proceedings,

p. 214 (IPC Science and Technology Press, U.K., 1974).

Kak, A. C, Beaumont, L. R., and Wolfley, J., Signal processing in the determination

of acoustic impedance profiles. School of Electrical Engineering, Purdue University,

Research Report TR-EE, 75 (1974).

Rosenfeld, A. and Kak, A. C, Digital Picture Processing (Academic Press, New York,

1976).

Van Trees, H. L., Detection, Estimation, and Modulation Theory (John Wiley and

Sons, Inc. , New York, 1968).

Erikson, K. R., Fry, F. J., and Jones, J. P., Ultrasound in medicine: a review,

IEEE Trans. Sonics Ultrason. $U-21 , 144 (1974).

Fry, W. J. and Dunn, F., Ultrasound: analysis and experimental methods in biological

research, in Physical Research in Biological Research, Vol. 4, p. 261 (Academic Press,

New York, 1962).

Fry, F. J. and Sanghir, N., Study and test of ultrasonic technique for diagnosis of

cerebral disorders. Final report - Phase 1. NIH Contract NOl -NS-3-231 9 (Feb. 1,

1975).

251

National Bureau of Standards Special Publication 453. Proceedings of Seminar on Ultrasonic

Tissue Characterization held at NBS, Gaithersburg, MD, May 28-30, 1975. (Issued Oct. 1976)

Paper 7.2: CURRENT PROBLEMS IN ULTRASONIC IMPEDIOGRAPHY

J. P. Jones

Bolt Beranek and Newman, Inc. Cambridge, Massachusetts 02138

The term impediography is used to describe a rather general

class of signal processing operations which, when applied to pulse-echo ultrasonic signals, yield quantitative information con- cerning the physical properties of the system under study. The

method uses deconvol ution of acoustical impulses and their echoes

to obtain the impulse response as a function of acoustical travel

time. The integral of the impulse response can then be analytically related to various physical parameters such as the specific

acoustical impedance. This paper provides a general discussion of

the problems associated with the practical implementation of

impediography and outlines a number of important research areas which require additional study. Major problem areas discussed

include: (1) corrections for non-planar geometry, (2) development of accurate deconvol ution algorithms, and (3) corrections

and/or development of impediographic processing procedures for

attenuation and scattering.

Key Words: Deconvol ution, impedance profiling, impediography,

impulse response, time-domain deconvol ution.

1. Introduction

The term impediography [1-9]^ has been coined to describe a rather general class of signal processing operations which, when applied to input/output signals, yield quantitative

information concerning the physical properties of the system under study. Ultrasonic impediography, then, describes signal processing operations upon incident and reflected acoustic

waveforms which can be used to determine acoustical properties as a function of spatial location. Ultrasonic impediography offers a means, at least in principle, for quantitatively

and non-invasively measuring tissue acoustical properties at appropriate anatomical sites

within the body. Such measurements are of diagnostic value since many types of normal and

abnormal tissues can be uniquely classified in terms of their acoustical properties [10-15].

Impediography involves (1) a processing operation upon both the incident and reflected

acoustical signals to obtain a time domain characterization of system dynamics known as the

system impulse response, and (2) a processing operation upon the system impulse response to obtain physical properties as a function of acoustic travel time. In our initial implementations [8-9], the impulse response was obtained by time-domain deconvol ution of short duration deterministic incident and reflected waveforms. A profile of specific acoustical impedance vs. acoustic travel time (or position) was generated through analytical relationships

involving the integral of the impulse response [8,9]. The term impediography is suggested

by the ability of the technique to generate profiles of impedance. The acoustical mapping

made with impediography, whether a simple A-scan plot of impedance vs. distance or an impedance profile of an arbitrary cross Section, is termed an impedogram.

iPresent address: School of Medicine, Case Western Reserve University, Cleveland, Ohio

44106

^Figures in brackets indicate the literature references at the end of this paper.
The basic principles of impediography can perhaps best be illustrated by a simple

example such as that shown in figure 1. Here, an initial medium of constant impedance, Zo abuts a test object consisting of two parallel layers each with a constant impedance of

and Z2, respectively. For purposes of argument, we assume Z2 < Zq < Z^. An acoustic source, which generates a short pulse, and a receiver, which observes the incident wave as well as the wave that is reflected from the test object, are located in the initial medium. The

incident wave produced by the source can be represented mathematically as a function of time

by x(t). A typical source-emitted waveform as might be observed at the receiver is shown in the top line of figure 1. The incident wave now propagates into the test object, where

impedance changes cause a portion of the incident wave to be reflected. This reflected wave

is also observed at the receiver. Given x(t) and the particular physical situation shown

schematically in figure 1, the reflected wave, represented by y(t), would appear as shown in the second line of this figure. If reflection is assumed to be a linear process, then the manner in which the test object responds to the incident wave can be characterized by an impulse response function h(t). It is a well-known result that the output of a linear

system is the convolution of the input and the impulse response of the system. Thus, the

reflected wave (or output) is equal to the convolution of the incident wave (or input) with

the impulse response. Given y(t) and x(t), h(t) can be obtained through appropriate deconvolution procedures. A typical result for the physical situation described in figure 1 is shown in the third line of that figure. It can be shown that the integral of the impulse

response can be related to various physical parameters, such as specific acoustical impedance

Thus, if we integrate the h(t) shown in figure 1 with respect to the acoustic travel time

and perform some simple algebra, we obtain the impedance plot as a function of time (or

position) shown in the fourth line of figure 1.

INCIDENT WAVE, X(t)

REFLECTED WAVE, Y(t)

DECONVOLUTION

IMPULSE RESPONSE, h(t) INTEGRATION

<^

SOURCE

INITIAL

RECEIVER

MEDIUM

(OF CONSTANT

IMPEDANCE

)

Zo

Figure 1. A simple example illustrating how impediography can quantitatively

measure the specific acoustic impedance as a continuous function of acoustic

travel time.

Although the concept of impediography is quite simple, its practical implementation has

proven to be fairly complicated. There are at least four problem areas of current interest:

first, appropriate corrections must be formulated for non-planar geometry; second, precise

analytical relationships must be obtained relating the impulse response to the specific

acoustical impedance and perhaps also to the frequency-dependent attenuation and the frequency-dependent scattering strength; third, accurate, well-conditioned, and stable deconvolution algorithms must be developed for measuring the impulse response; and fourth, the

effects of attenuation must either be taken into account or measured concurrently with

impediographic processing procedures. Let us now review each of these problem areas in more

detail

.

Our simple analytical model for impediography has assumed that all reflecting interfaces!; are plane-parallel structures. Such a model is probably adequate for many situations of in- - terest, particularly if the object is interrogated with a narrow focused beam of ultrasound. ,j For more complicated structures, scanning in conjunction with simple processing may be re- \ quired to properly account for the effects of non-planar geometry. The limitations of a planar geometry model have yet to be fully assessed.

254
The second problem area involves obtaining appropriate analytical relationships between

the reflected acoustic waveforms and the acoustical properties of the object. A number of

iterative methods have been proposed for determining the impedance profile from a knowledge

of the incident and reflected signals [16-19]. Such techniques have seen extensive application in geophysics and in the analysis of transmission lines. Although these methods provide

a simple means for removing the effects of multiple reflections, they are often inaccurate

and feature the rapid accumulation and propagation of errors. To avoid the errors associated

with a recursive estimation of impedance, we have developed an integral relationship between

the impulse response and the impedance. For example, if the impedance 1-1 is constant for

all times t <. 0 and Z is a continuous but arbitrary function of time for t > 0, then it can

be shown [1 ,7,8] that

/Jh^(T)dT = /n[Z(t)/ZQ]/2

where hi is the first-order impulse response {i.e., the impulse response which results from

only first-order reflections). This result is important since it allows us to obtain the

impedance profile of even an impedance continuum and does not require measurements based

upon reflections from finite layers of constant impedance.

In certain specialized situations, similar integral relationships can be derived which

include the effects of higher-order reflections [7-8]. However, in general such relationships are either indeterminate or non-unique. Fortunately, multiple reflections are usually

the result of abrupt, large magnitude impedance excursions. If such is the case, they can be

removed through a perturbation analysis on the impulse response in the original formalism [7].

The measurement of attenuation is intimately and irrevocably tied to the measurement of

impedance. In fact, in many cases, knowledge of the attenuation may be more important to tissue identification than knowledge of the impedance [8,10]. Although we will return to the question of attenuation later in our presentation, it should be clear that analytical

relationships exist between the impulse response and the attenuation. For example, if the

transmitted and the reflected impulse responses are measured, then profiles of both the

impedance and the attenuation, provided a spectrum analysis of the reflected waveform is obtained. Unfortunately, these procedures suggested for measurement of the attenuation have

yet to be implemented.

Impedance profiling is made possible because sound is reflected from the change in acoustical impedance which forms the boundary of the structure in question. In many situations, low amplitude echoes which are highly frequency dependent may be observed from the

interior of the structure. These mottling echoes are produced by the scattering of sound

from microstructural inhomogeneities, which are inherent to many biological tissues [20].

Since these echoes produced by scattering represent frequency-dependent interfaces, they produce errors in our impediographic profiling. Appropriate corrective measures are required.

Scattering, like impedance, velocity, and absorption, is a fundamental tissue property and

could well provide a basis for quantitative tissue characterization. Therefore, many situations may require that impediography also provide a measure of the scattering. Such a measure could be obtained either through analytical relationships between the impulse re- sponse and the scattering or through analysis of the reflected signal to yield the backscattering strength.

The third problem area to be discussed deals with the development of appropriate deconvolution algorithms for measuring the impulse response. In our initial work on impediography, we tried simple and well-known signal processing procedures that could be carried

out without extensive computation [7]. Thus, it was convenient to use a non-anticipatory

time-domain deconvol ution algorithm in which the convolution integral was approximated by

a sum using samples of the continuous functions and in which deconvol ution was accomplished

through matrix inversion.

If the impulse response is to be obtained from the incident and reflected waveforms

using a "standard" time-domain deconvol ution algorithm then requirements are placed on the

source-emitted waveform and on the manner in which data are sampled. Time-domain deconvol u- tion can be badly degraded if inappropriate input waveforms and/or inappropriate sampling

techniques are used. It can be shown [7] that criteria exist for the selection of input

waveforms, which, when employed with preferred sampling techniques, will greatly improve the

255
accuracy and, thereby, enhance the interpretabi 1 ity and utility of records obtained by

time-domain deconvol ution , especially in the presence of additive noise. A simple analysis

indicates that optimal results are obtained with an unconventional source which generates a pressure pulse that is unipolar in shape. Thus, the initial experimental studies of impediography [1-5] made use of a spark source (which easily generates a unipolar pulse). The numerous inconveniences associated with a spark source led to the development of a simple

piezoelectric device capable of generating a unipolar pulse [7]. This instrumentation has

been used successfully in a number of simple experiments [9]. Accurate impedograms were obtained for a number of highly idealized physical models and for several biological samples.

To obtain these results required careful hand analysis of the data as well as preprocessing

to remove the effects of multiple reflections and attenuation and to correct for low frequency source drift. Attempts to automate this processing procedure have thus far not been

successful. As might be expected, the eye-brain complex is apparently capable of making

judgments in the analysis that can be automated only with great difficulty. Obviously more sophisticated processing techniques are required which can circumvent problems of judgment,

preprocessing requirement, and the fundamental problem of illconditioning associated with

impulse response identification. Although, Prof. Kak has made significant progress in this direction [21], as was indicated in the previous paper, much work remains. There is a considerable literature in applied mathematics, geophysics, control sciences, electroacoustics, and radar/sonar applications which deals with this particular system identification problem and which we in ultrasound have yet to use to full advantage. The practical implementation of impediography would be hastened considerably by translating sophisticated

signal processing techniques presently available into impediographic processing procedures,

keeping in mind the unique problems associated with ultrasonics and with measurements on biological tissues. Techniques such as homomorphic deconvol ution [24] and Kalman filtering

[22-23] would seem to be especially promising.

Finally, we consider problems associated with attenuation. As mentioned previously the

accurate determination of impedance is dependent upon either the a priori knowledge of

attenuation or upon a means for its concurrent measurement, and vice versa. There are at least four ways in which both the impedance and the attenuation can be determined. First,

if either the impedance or attenuation are known, the unknown parameter can be determined

using present impediographic processing procedures. Second, as previously discussed, analyti

cal relationships between attenuation and the impulse response should allow the impedance

and attenuation to be concurrently determined. For example, if the reflected impulse re- sponse is used with present impediographic processing to obtain an impedance profile, analysi

of the transmitted impulse response should allow the attenuation to be determined and the

original impedogram to be corrected for attenuation. If the frequency dependence of the

attenuation is known, a spectrum analysis of the reflected waveform should be sufficient

for determination of the attenuation, provided the measurement is coupled with present im- ! pediographic processing. Third, if the properties of an internal reflecting interface or | structure are unknown, it might be possible in many situations to calibrate the measuring ] system on this known object and thereby obtain the necessary corrections to produce an accu- | rate profile of impedance and/or attenuation^. Fourth, more sophisticated signal processing

techniques may permit corrections for attenuation in the computation of the impulse response.

For example, processing techniques based on a time-varying filter and on nonstationary

j statistics may be useful. '

One of the more interesting attenuation problems of current interest involves making

quantitative acoustical measurements through human skull. Transskull impediography is

j difficult because of the rather unique aberrations introduced by the presence of skull bone.!

An analysis of the propagation of sound through skull shows that the width or spatial characteristics of a focused beam remains virtually unchanged, whereas the waveform is severely

' altered. Preliminary results of a study now in progress [25] indicate that transskull

signal degeneration is a result of frequency- dependent absorption and multipath propagation.;

Mul ti path propagation is apparently produced by nonuniform variations in skull thickness and; perhaps by mode conversion processes within the skull. Using the results of this study we hope to develop techniques or procedures for removing or taking into account the effects of i the skull on acoustical signals. I'

^Internal reflecting interfaces of known acoustical properties might include blood (e.g.^

underlying infarcted heart tissue) and normal structures of the ventricles.

256
In conclusion, ultrasonic impediography offers a means, at least in principle, for quantiely and non-invasi vely measuring tissue acoustical properties at appropriate anatosites within the body. However, a number of major problems remain to be solved before

iography can be implemented in any practical sense. These problems are extremely

enging, are perhaps approachable in the context of recent developments in signal prong and analysis, and deserve the attention of many more interested researchers.

References

Jones, J. P., and Wright, H. A., A new broad-band ultrasonic technique with biomedical

implications I: background and theoretical discussions, presented at the 83rd Meeting

of the Acoustical Society of America, Buffalo, NY, April 1972.

Jones, J. P., and Wright, H. A., A new broad-band ultrasonic technique with biomedical

implications II: preliminary experiments involving human skull bone, presented at

the 83rd Meeting of the Acoustical Society of America, Buffalo, NY, April 1972.

Jones, J. P., Impediography: a new approach to non-invasive ultrasonic diagnoses,

presented at the 25th Annual Conference on Engineering in Medicine and Biology, Bal Harbor, Florida, 1972.

Jones, J. P., Further experiments with impediography, a new ultrasonic technique with

biomedical implications, presented at the 84th Meeting of the Acoustical Society of

America, Miami Beach, FL, 1972.

Jones, J. P., Impediography: a new ultrasonic technique for nondestructive testing

and medical diagnosis, in Ultrasonias International 1973 Conference Proceedings, p. 214

(IPC Science and Technology Press, U.K., 1974).

Jones, J. P., In Vitro visualization of liver metastasis using ultrasonic impediography, presented at the 86th Meeting of the Acoustical Society of America, Los Angeles, CA, 1973.

Jones, J. v., A Study of Ultrasonic Techniques for the Diagnosis of Cerebral Disorders, Phase I: A Preliminary Investigation of Impediography , (BBN Report No. 2890,

NIH Contract No. NOl-NS-3-2319, Oct. 1974).

Jones, J. P., Impediography: a new ultrasonic technique for diagnostic medicine, in Proceedings of the I9th Annual Conference of the American Institute Of Ultrasound in

Medicine (Seattle, WA, Oct. 1974).

Jones, J. P., A preliminary experimental evaluation of ultrasonic impediography, in

Proceedings of the t9th Annual Conference of the American Institute of Ultrasound in

Medicine, (Seattle, WA, Oct. 1974).

Tanaka, K., Yukishita, K. , Ito, K., Ehara, K. , and Watanabe, H., Ultrasonic diagnosis

of brain tumors, in Proc. Int. Symp. on Echo-Encephalography , 38 (1967).

Fry, E. Kelly, Fry, F. J., and Okuyama, D., Ultrasonic differentiation of normal

liver structure as a function of age and species, in Reports of the 6th Int. Cong, on Acoustics, Ml -4 (Tokyo, Japan, August 1968).

Fry, E. Kelly, Eggleton, R. C, and Fry, F. J., Ultrasound echo patterns from

normal human and animal 1 i ver--relation to detection of pathological states of

liver, Proc. A.I.U.M. (Denver, CO, Oct. 1971).

Fry, E. Kelly, and Gibbons, L. V., A Study of Ultrasonic Detection of Breast Disease,

(Report No. PH 86-68-198, U.S. Public Health Service, Cancer Control Program, April

1969).

Fry, E. Kelly, Kossoff, G., and Hindman, H. A. Jr., The potential of ultrasound

visualization for detecting the presence of abnormal structures within the female

breast. Proceedings of IEEE Ultrasonics Symposiums , p. 25 (IEEE, Cat. No. 72 CHO

708-8 SU, New York, 1972).

257
[15] Fields, S., and Dunn, F. , Correlation of echographic visual izability of tissue and

biological composition and physiological state, J. Aooust. Soo. Am., 54, 809 (1972).

[16] Ware, J. A., and Aki, K., Continual and Discrete Inverse Scattering Problems in a Stratified Elastic Medium, J. Aaoust. Soo. Am., 45^, 911 (1969).

[17] Boakye, K. A., and Wing, 0., On the analysis and realization of cascaded transmission

line networks in the time domain, IEEE Trans. Circuit Theory, CT-20 , 301 (1973).

[18] Shanks, J. L., Recursion filters for digital frocessing. Geophysics 32^, 33 (1967).

[19] Tritel, S., and Robinson, E. A., The Stability of Digital Filters, IEEE Trans. Geosci. Electron. 2_, 6 (1964).

[20] Sigelmann, R. A., and Reid, J. M. , Ultrasonic scattering from biological tissues, in Interaction of Ultrasound and Biological Tissues, Workshop Proceedings, J. M. Reid

and M. R. Sikov, eds. p. 245, (DHEW Pub. 73-8008 BRH/DBE 73-1 1972).

[21] Kak, A. C, Beaumont, L. R., Wolfley, J., Signal Processing in the Determination of

Acoustic Impedance Profiles, (Purdue University Report TR-EE 75-7, 1974).

[22] Bayless, J. W., and Brigham, E. 0., Application of the Kalman Filter to Continuous

Signal Restoration, Geophysics, 35, 2 (1970).

[23] Crump, N. D., A kalman filter approach to the deconvol ution of seismic signals,

Geophysics, 39, 1 (1974).

[24] Ulrych, T. J., Application of homomorphic deconvol ution to seismology, Geophysics,

36, 650 (1974).

[25] Study conducted by the Fortune-Fry Research Labs, Indianapolis, IN, and Bolt Beranek

and Newman Inc., Cambridge, MA., and supported by the National Institute of Neurological Diseases and Stroke. (NIH Contract No. NOl-NS-3-2319)

.

258
CHAPTER 8

ACOUSTIC MICROSCOPY

259

National Bureau of Standards Special Publication 453. Proceedings of Seminar on Ultrasonic

Tissue Characterization held at NBS, Gaithersburg, MD, May 28-30, 1975. (Issued Oct. 1976)

CHAPTER 8. ACOUSTIC MICROSCOPY

Paper 8.1: TISSUE CHARACTERIZATION BY MEANS OF ACOUSTIC MICROSCOPY

L. W. Kessler

Sonoscan, Incorporated

Bensenville, Illinois 60106

The complete characterization of tissue is extremely important for

objectively identifying abnormalities and disease states. Optical methods

of microscopy have been exploited to a great degree and now the electron

microscope is being used in search of diagnostic clues at higher

magnification levels. It is well appreciated, however, that these

methods provide only limited access to the physical properties of

tissue. Furthermore, the physical nature of an abnormality may prohibit

its ever being revealed with visual observation techniques. Acoustic

microscopy, on the other hand, can reveal new information, the structural

elastic characteristics of viable tissue. Acoustic microscopy can also

provide quantitative data on these tissue characteristics. As this

additional information should have great diagnostic value, a general

discussion of the methods and procedures employed is presented.

Key Words: Acoustic imaging; acoustic microscopy; attenuation; frequency

dependence; impedance; microstructural analysis; tissue; ultrasound;

veloci ty.

1. Introduction

The application of acoustic microscopy to biological tissues is a new area of study

which addresses the problem of delineating the physical characteristics of tissue composition on a microscopic level. Knowledge of the physical characteristics of viable

tissue, instead of histologically fixed and stained tissue, can be rendered directly with

acoustic microscopy. This will undoubtedly play an important role in increasing our capacity to identify subtle changes in tissue architecture which occur in pathological

conditions

.

As a technique, acoustic microscopy is analogous to optical microscopy in that high

resolution and high magnification images are produced; however, ultrasonic energy, rather

than an "optical band" of electromagnetic energy, is transmitted through the sample.

Because very high ultrasonic frequencies are employed to produce high resolution, the

microscopy regime is new to the medical ultrasonics arena. The high frequencies are associated with large acoustic attenuation values in tissue, thus making small samples

necessary. On the other hand, the resolution obtainable is several orders of magnitude

better than that achieved in conventional diagnostic ultrasound and the applications are somewhat different. In particular, at frequencies of a few megahertz, i.e., the "macrorange", ultrasonic diagnosis profits from being able to penetrate optically opaque bodies

and differentiate soft tissue interfaces without ionizing radiation. The "micro-range"

described here, in addition to providing the just-mentioned capabilities on a finer

scale, more importantly provides direct access to the elastic properties of fresh tissue

I at a dimensional level where localized variations in mass density, modulus of elasticity

and acoustic attenuation, are much more abundant.

2. Description of the Technique

The following brief description of the technique employed for acoustic microscopy is presented for reference. Interested readers may review the listed references [1-5]^ for

more detailed accounts. In the most general sense, in order to produce an acoustic

micrograph, a sample is placed between sending and receiving ultrasonic transducers and

^Figures in brackets indicate the literature references at the end of this paper.

261
the point- by-point pattern of sonic transmission is displayed on a CRT. The procedures

for mounting specimens in this acoustic microscope (fig. 1) are very similar to those

Figure 1. Schematic block diagram and pliotograph of a completed Sonomicroscope [6]

apparatus for producing acoustic micrographs in real time. The instrument employs a scanning laser beam technique for detecting the amplitude and phase of acoustic trans- mission through a sample. As a by-product of this technique, an optical image of the

specimen is simultaneously produced and is presented on a separate TV monitor.

262
normally encountered in optical imaging. The acoustic energy is coupled directly to the

specimen without any need for an acoustically-lossy water bath, although the specimen may

be moistened with a thin layer of liquid to insure good acoustic transmission. Biological

specimens are placed on a sonical ly-acti vated glass stage and are covered with a partiallymirrored coverslip. The transmitted acoustic energy imparts slight oscillatory mechanical

perturbations to the coverslip surface. These disturbances, which occur at the acoustic

frequency, are proportional to the acoustic amplitudes in each region. These are detected

by a focused scanning laser beam probe which drives an opto-acoustic receiver.

An optical image of the specimen is produced simultaneously by detecting the throughtransmitted laser light. By virtue of this point-by-point scanning method, the optical

and acoustic signals are in perfect register electronically so that corresponding images

may be presented on separate side-by-side TV monitors or superimposed on separate color

channels of a single color TV monitor [7]. The latter has been especially useful for

sorting through and precisely correlating the abundant accstic and optical image details.

In addition to displaying the acoustic intensity or amplitude throughout the field

of view, the Sonomicroscope provides an acoustic interference mode of operation. Here,

the acoustic phase may be measured as the wave propagates through various structures

within the field of view. Thus, velocity of sound measurements can be made and, under

the appropriate conditions, fluctuations of mass density and elasticity can be observed

in microscopically-localized regions.

3. Sonomicroscopic Characterization of Tissues

The characterization of tissue microstructure is traditionally accomplished by

optical or electron microscopy methods. However, these methods are intrinsically capable

of revealing only the physical "electronic properties" of structure defined by the dielectric

constant. (The magnetic properties are usually unimportant.) Useful histological methods

which alter the natural state of tissues have been developed. These clarify, fix, and

selectively stain tissues in order to optically reveal otherwise unobservable aspects of

structure. In particular, size, shape, position, and staining characteristics of tissue

components encompass the body of information that has been diagnostical ly available.

However, methods have not been capable of translating actual elastic characteristics of

tissue to a visible format. The characterization of density and elasticity properties of

unaltered tissue structure is now available in acoustic microscopy through the determination

of localized attenuation coefficients, acoustic impedance, and velocity of sound. The

methods and procedures for producing these quantitative data are described briefly below.

4. Attenuation and Impedance Distribution

In general, the attenuation suffered by an acoustic beam propagating through tissue

results from several mechanisms, acting independently or synergistical ly [8]. As an acoustic beam propagates through an inhomogeneous medium, reflection and refraction at interfaces divert energy away from the primary beam. However, as the spatial extent of

acoustic impedance interfaces becomes comparable to or smaller than the dimension of the

acoustic wavelength, the process is referred to as scattering. It should be recognized

that structures which at clinical diagnostic frequencies may be considered scatterers,

may be reflectors at acoustic microscope frequencies. Frictional losses in tissue cause

a fraction of the acoustic energy to change into heat. Furthermore, since the physical state of the environment is altered with sound beam propagation, shifts occur in chemical

or structural reactions at a molecular level. The frictional and reaction losses are termed absorption.

Attenuation measurements can be made by means of a comparison technique [9]. With

the specimen in place and the acoustic image presented on the TV screen, the appropriate

region of interest is identified. Positive identification, of course, is made with the

assistance of the corresponding optical image as well. The relative image brightness

over the region of interest, compared to the situation of having no specimen in place, is

a measure of the attenuation. Experimentally, an image brightness level is established

with a light meter equipped with an appropriate optical aperture to control its field of

view spatially. With the specimen removed, the microscope is refocused on the illuminating

sound field alone. Electrical attenuation is then inserted in the signal path of the

263
irradiation transducer in order to restore the brightness to the previous level. The

electrical attenuation inserted is equal to the acoustic attenuation provided by the

specimen. Confidence in the method, established by measuring the absorption coefficient in

water, indicates that an overall accuracy of ± 10% can be achieved.

A measurement of that part of the attenuation due to reflection losses exclusively

will yield the acoustic impedance and scattering. In order to differentiate reflection

losses from absorption losses, this measurement procedure may be performed on several

samples of the same tissue. The sample can be made sufficiently thin so as to insure that

absorption and scattering losses are an insignificant fraction of the observed attenuation.

By way of example, if the attenuation of sound within tissue at 100 MHz is still of the

order of 1 dB/cm/MHz, then for sample thicknesses of 10, 100, and 1000 micrometers, the

expected absorption losses would be 0.1, 1.0, and 10 dB, respectively. Typical sections

p-epared for optical microscopy are sliced 5-10 micrometers in order to render them

reasonably translucent optically.

The velocity of sound has been measured for many soft tissues over the frequency

range of 1-10 MHz and the values observed do not vary by more than 100 m/s or less, even

though there may be substantial differences in the tissue types [10]. It may be reasoned

that at the bulk level of tissue, velocity of sound characteristics of small components

are masked by the predominant aqueous constituents. Microscopically, however, the velocity

of sound may be measured in individual components of the tissue with the acoustic interferometry mode of operation [3,4].

The principle of measuring changes in velocity of sound can be explained with

reference to figure 2. Consider the intersection of two plane, coherent sound beams at

Figure 2. Principle of acoustic interferometry . Two coherent sources of acoustic

energy, one passing through the sample and one bypassing the sample, constructively

interfere at the detection plane causing a series of fringe lines whose lateral

positions are determined by the velocity of sound in the sample. The detection

plane, which is shown as being located far away from the sample, is actually

located at the alternate position in order to circumvent the large acoustic

attenuation losses. However, in order to provide a reference signal for phase

detection (there is no room for a sound beam to bypass the sample), it is done

electronical ly

.

5. Velocity of Sound Distribution

DETECTOR PLANE

TRANSDUCER

264
the detector plane. Depending upon the angle between the beams, a series of regularlyspaced fringe lines, caused by mutual interference, will appear at the detector plane. If an object whose velocity of sound characteristics differ from that of the surrounding

medium interrupts one of the beams, localized lateral shifting of the fringe lines will

result. The displacement of a fringe, measured graphically, is related to a localized

disturbance in transmission time of one sound beam compared with the unperturbed or reference beam.

A simple formula has been derived [11] to calculate the velocity of sound in the

"unknown" sample. In the actual set up, high acoustic attenuation requires the object to

be placed in close proximity to the detector plane. This is accomplished with the alternate

position of the detector plane by electronically simulating a reference beam at normal

incidence. The schematic value of figure 2 is still correct, however, for deriving the

interferometry equation. An acoustic beam, nominally incident upon the specimen at angle

Qq from the normal will be refracted to angle ©x within the sample according to Snell's

Law,

sin sin

(1)

where Cq and Cx are the velocity of sound values in the unperturbed medium and the unknown

sample, respectively. If the thickness of the sample or of the unknown region of a sample

is denoted AT, then the lateral shift of the fringes, normalized by the unperturbed spacing

of the fringes, N, is given by

AT sin e. tan tan (2)

where Lq is the wavelength of sound in the reference material. Note that N is a dimensionless number, corresponding to the number of fringes of shift in the interferogram. By

solving for ex and then using the Snell's Law relationship, Cx is readily calculated.

Typically Gq is 10°; however, it depends upon the particular configuration of the stage

employed.

The capability for this technique for differentiating velocity of sound regions within

the matrix of a tissue is dependent upon the sample thickness. This is consistent with

other methods of velocity measurement such as "time of flight" techniques. For example,

if fringe line displacements can be measured to the nearest 1/10 fringe, then in a section

of tissue 300 micrometers thick, i.e.^ 20 wavelengths, 7.5 m/s variations in Cx may be

discriminated.

6. Results and Discussion

Over the last five years, during the course of development of the acoustic microscopy

technique, a variety of biomedical and biological studies were conducted and are still on- going. The purpose of this section will be to summarize just a few of the highlights,

particularly those which may be pertinent to microscopic characterization of the physical

properties of tissue.

One of the primary areas of study thus far has been the real-time visualization of

dynamic events. A variety of specimens maintained alive in an organ culture state have

been examined [2,7,12,13]. For example, isolated beating mouse embryo hearts are being

studied for localized sites of action of potentially useful cardioactive agents and drugs [14].

Furthermore, whole embryo specimens have been examined as well [13,15]. Here, the acoustic

microscope offers a way of circumventing optical opacity without interfering with the

activity and viability of the tissues. The technique permits visualization of soft tissue

structures as if they had been fixed and stained histologically.

A detailed study was also conducted on unstained specimens of mouse kidney at frequencies of 100 MHz and 220 MHz [16]. The acousticarl Jy-revealed structure has been examined

in relation to established microanatomy. High-contrast details corresponding to connective

265
tissue boundaries of supporting elements such as the cortex and the three medullary regions

can be differentiated. In this frequency range, the acoustically-exhibited structures are considered to result from scattering at connective tissue interfaces, resulting from local

acoustic impedance discontinuities, rather than from intrinsic acoustic absorption within

the microstructure of the tissue.

Acoustic attenuation measurements have also been made with the acoustic microscope.

It has been well established that for mammalian tissues such as kidney and brain, the

attenuation coefficient exhibits a linear dependence over the frequency range of investigation, i.e., 0.3-10 MHz, and the magnitude is of the order of 1 dB/cm/MHz. The absorption

coefficient for water is significantly less than for tissue and exhibits a square-law

frequency dependence. Projecting the linear dependence for tissue to higher frequencies

aid comparing this to the expected absorption in water, leads to speculation that beyond

.'.bout 500 MHz the attenuation for water might exceed that for tissue. Since tissue is composed mainly of water, this should not be possible.

The attenuation of sound in mammalian kidney tissue was measured at 100 MHz and

220 MHz [9]. The tissue samples were either fresh, fresh-frozen-thawed, or fixed in formalin. The measured attenuation values were found to be independent of preparation.

The result, presented graphically in figure 3, indicates that the acoustic attenuation in

I '

1

A)

1

Striated Musde

B) Kidney and Broin

iJ) CD) Kidney

Z.5

2.0 I

1.5 >=' """"1

Ill

D

1.0 B

///////////////////////////////III IC

0.5

0 1

1

. 1

FREQUENCY IN MHz.

Figure 3. VHF attenuation in mammalian kidney tissue. Data A and B taken from

reference 10 and data C and D taken from reference 9.

tissue continues to behave linearly up to a frequency of about 100 MHz. Beyond this

frequency, a square-law dependence (or greater) takes over, thereby indicating that the

hypothetical crossover point may never actually be reached. This is more in line with

intuition.

The use of acoustic microscopy to delineate mechanical variations in hard tissues has

been examined and preliminary qualitative results were published [17] for sections of

dental tissue. Dentyne and enamel components of this tissue differ greatly in their mechanical properties and this is demonstrated by the acoustic micrographs. Furthermore, in the

junction region, where dentyne and enamel components combine in varying proportions, the

smooth gradation of density and elasticity is revealed. This type of study is pertinent

to other hard tissue investigations, particularly bone pathologies and plaque formation

in vessels.

Velocity of sound measurements have recently been initiated with the acoustic microscope. At clinical diagnostic frequencies, only a 100 m/s range in sound velocity has

been observed within and among soft tissues. On the microscopic scale, however, we have

obtained some evidence which suggests that there are localized regions which are characterizes
zed by velocities of sound 200-800 m/s above that of neighboring tissue structures.

Since detailed studies are just getting underway, ^'lis conclusion should be regarded only

as preliminary.

References

[I] Korpel , A., Kessler, L. W. , and Palermo, P. R., An acoustic microscope operating at

100 MHz, Mature, 232, 110 (1971).

[2] Kessler, L. W. , Korpel, A., and Palermo, P. R., Simultaneous acoustic and optical

microscopy of biological specimens. Nature, 239 , 111 (1972).

[3] Kessler, L. W. , Palermo, P. R., and Korpel, A., Practical high resolution acoustic

microscopy, in Aaoustiaal Holography, Vol. 4, G. Wade, ed., p. 51 (Plenum Press,

New York, 1972).

[4] Kessler, L. W., Palermo, P. R. , and Korpel, A., Recent developments with the scanning

laser acoustic microscope, in Aaoustia Holography, Vol. 5, P. S. Green, ed., p. 15 (Plenum Press, New York, 1974).

[5] Kessler, L. W., The Sonomicroscope, in Proceedings of IEEE Ultrasonic Symposium,

J. de Klerk, ed., Cat. No. 74-CH0-896-1 SU, p. 735 (IEEE, New York, 1974).

[6] Manufactured by Sonoscan, Inc., under exclusive license from Zenith Radio Corp.

[7] Kessler, L. W. , High resolution visualization of tissue with acoustic microscopy, in

Ultrasonics in Medicine, M. de Vlieger, ed., p. 250 (Excerpta Medica, 1974).

[8] The synergistic effects of attenuation mechanisms have not received attention as far as this author is aware; however, they may play a significant role in causing the

attenuation values observed in tissue to exceed that which can be predicted.

[9] Kessler, L. W. , VHP ultrasonic attenuation in mammalian tissue, J. Aaoust. Soc. Am.

53, 1759 (1973).

[10] See for example: 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).

[II] Detailed account in preparation.

[12] Eggleton, R. C. and Kessler, L. W., Mouse embryo heart in organ culture visualized

by the acoustic microscope, in Proceedings 1974 meeting of American Institute of

Ultrasonics in Medicine, p. 537 (Plenum Press, New York, 1975).

[13] O'Brien, W. D. , Jr. and Kessler, L. W., Examination of mouse embryological development with an acoustic microscope, paper presented at American Society of Zoologists

Meeting, Corvallis, Oregon, August 1975. (Manuscript in preparation.)

[14] Study in progress directed by Prof. R. C. Eggleton, Fortune Fry Laboratories, Indiana

University Medical School with collaboration of Dr. G. Boder, Eli Lilly and Co.

[15] Ahmed, M. and Kessler, L. W., Microanatomy of a histologically unstained embryo as revealed by acoustic microscopy, in Acoustic Holography, Vol. 6, N. Booth, ed.,

p. 319 (Plenum Press, New York, 1975).

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

kidney, J. Clin. Ultrasound, 2, 317 (1974).

[17] Kessler, L. W., A review of progress and applications in acoustic microscopy, J. Acoust. Soc. Am. 53, 246 (1973).

267
I
REGISTRATION LIST

269

SEMINAR ON ULTRASONIC TISSUE CHARACTERIZATION

National Bureau of Standards

Gaithersburg, MD May 28-30, 1975

Registration List

K. Abel

Becton Dickinson & Co. P.O. Box 12016

Research Triangle, NC 27709

Robert C. Addison, Jr. American Optical Corp.

14 Mechanic Street

Southbridge, MA 01550

Jitsuo Akiyama

Dept. of OB-GYN

Okayama University Medical School

Okayama, Japan

Sami J. Al -Banna

Columbia University

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New York, NY 10027

W. Watson Alberts

National Institutes of Health

Bethesda, MD 20014

Harold Alsberg

Cal. Tech./JPC

4800 Oak Grove Drive

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Frank D. Altieri

National Heart and Lung Institute

Bethesda, MD 20014

Evan D. Anderson

National Science Foundation

1800 G Street, NW Washington, DC 20550

Thomas L. Anderson

Food and Drug Administration

5600 Fishers Lane Rockville, MD 20852

Robert Apfel

Yale University

Mason Lab. New Haven, CT 06520

E. Ronald Atkinson

National Institutes of Health

Bethesda, MD 20014

Richard Banjavic

3321 Sterling Hall

University of Wisconsin

Madison, WI 53706

James E. Barger

Bolt Beranek and Newman Inc. 50 Moulton Street

Cambridge, MA 02138

Ralph W. Barnes Bowman Gray School of Medicine

Hawthorne Road

Winston-Salem, NC 27103

Ian R. Bartky

Institute for Materials Research

National Bureau of Standards

Washington, DC 20234

G. B. Baum

Albert Einstein Medical School

Yeshiva University

Bronx, NY 10461

Irwin Berets ky

Technicon Instrument Corp.

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Harry Berger

Institute for Materials Research

National Bureau of Standards

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Richard B. Bernardi

Picker Corporation

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Stanford University Medical Center

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General Electric

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National Cancer Institute/NIH

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271
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Office of Naval Research

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Purdue University

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University of Illinois

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Indiana University of Medical Center

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A. C. Kak

Purdue University

W. Lafayette, IN 47907

Azmi Kaya

University of Akron

Akron, OH 44325

Edward M. Kerwin, Jr. Bolt Beranek and Newman Inc. 50 Moulton Street

Cambridge, MA 02138

L. W. Kessler

Sonoscan, Inc. 752 Foster Avenue

Bensenville, IL 60106

Donald L. King

Columbia-Presbyterian Medical Center

622 West 168th Street

New York, NY 10032

G. Kossoff

Ultrasonics Institute

Sydney, Austrialia

Frederick Kremkau

Bowman Gray School of Medicine

Winston-Salem, NC 27103

Roman Kuc Columbia University

St. Luke's Hospital New York, NY 10025

Ching-Ming Lai

Department of Chemistry

SUNY at Stony Brook

Stony Brook, NY 11794

David R. Larach

Columbia Univ. College of Phys. and Surg.

50 Haven Avenue

New York, NY 10032

John I. Lauritzen

Institute for Materials Research

National Bureau of Standards

Washington, DC 20234

Michael Laviola

Riverside Research Institute

80 West End Avenue

New York, NY 10023

275

James M. Lawther

Pennsylvania State University

P.O. Box 30

State College, PA 16801

Richard Lawton

General Electric

Schenectady, NY 12345

D. H. Le Croissette

Jet Propulsion Lab

Pasedena, CA 91103

Sidney Lees Forsyth Dental Center

140 Fenway

Boston, MA 02115

P. P. Lele

Massachusetts Institute of Technology

Cambridge, MA 02139

George K. Lewis

Searle Analytic Inc. 2000 Nuclear Drive

Des Plaines, IL 60018

Bernard Lichtenstein

Technicon Company

511 Benedict Avenue

Tarrytown, NY 10591

Will iam A. Lindgren

Xenotec, Ltd.

401 East Main Street

Middletown, MD 21769

Melvin Linzer

Inorganic Materials Division

National Bureau of Standards

Washington, DC 20234

Carol Lipson

National Bureau of Standards

Washington, DC 20234

Frederic Lizzi

Riverside Research Institute

80 West End Avenue

New York, NY 10023

John A. Long

Providence Hospital

1150 Varnum Street, NE Washington, DC

Michael L. McCartney

University of Viroinia Medical Center

Box 224

Charlottesville, VA 22901
Richard McLeary

Henry Ford Hospital

2799 West Grand Blvd.

Detroit, MI 48202

James S. Main

Lister Hill National Center for

Biomedical Communications

8600 Rockville Pike

Bethesda, MD 20014

John Marangola

Upstate Medical Center

Syracuse, NY 13210

Robert F. Martin

Institute for Materials Research

National Bureau of Standards

Washington, DC 20234

Hewlett E. Melton, Jr. Medical College of Wisconsin

8700 W. Wisconsin Avenue

Milwaukee, WI 53226

Robert F. Metzker

National Bureau of Standards

Boulder, CO 80302

Reuben S. Mezrich

RCA Labs

Princeton, NJ 08540

Eric B. Miller

National Bureau of Standards

Boulder, CO 80302

James G. Miller

Washington University

St. Louis, MO 63130

Courtney P. Mudd

University of Virginia

37 West Range

Charlottesville, VA 22901

Kiyoshi Nakayama

Johns Hopkins University

Baltimore, MD 21205

Anant K. Nigam

CBS Labs

High Ridge Road

Stamford, CT 06905

Mary B. Noyes

St. Luke's Hospital Center

Ft. Lee, NJ 07024

William O'Brien

University of Illinois

Bioacoustics Research Lab

Urbana, IL 61801

William Oldendorf

UCLA

Los Angeles, CA 90024

Larry Oline

University of South Florida

Flowler Avenue

Tampa, FL 33620

Charles P. Olinger

University of Cincinnati

Cincinnati, OH 45211

Karl C. Ossoinig

University of Iowa

Iowa City, lA

Stephen I. Parks

Inorganic Materials Division

National Bureau of Standards

Washington, DC 20234

M. Parver

NIH Clinical Center

Bethesda, MD 20014

D. M. Perozek

Hewlett Packard Company

Waltham, MA 02154

David J. Phillips

Duke University

Durham, NC 27701

G. J. Posakony

Battel! e-Northwest

Box 999

Richland, WA 99352

Roger S. Powell

National Heart and Lung Institute

Bethesda, MD 20014

Judith M. S. Prewitt

National Institutes of Health

Bethesda, MD 20014

Leslie A. Priebe

University of Texas Austin, TX 78712

T. Allen Pryor

Latter-Day Saints Hospital

Salt Lake City, UT 84143

Bernice T. Radovich

National Cancer Institute

Bethesda, MD 20014

Phillip Rauch

Henry Ford Hospital

2799 W. Grand Blvd.

Detroit, MI 48202

276
Henry J. L. Rechen

Bureau of Radiological Health/FDA

11113 Dewey Road

Kensington, MD 20795

J. M. Reid

Institute of Applied Physiology

and Medicine

566 18th Avenue

Seattle, WA 98122

Curt W. Reimann

Institute for Materials Research

National Bureau of Standards

Washington, DC 20234

Ron Robinson

Bureau of Radiological Health

Rockville, MD 20852

H. A. F. Rocha

General Electric

Schenectady, NY 12345

Donald S. Rodbell

RPI - Biomedical Engineering

North Hall

SAGE/Tibbetts

Troy, NY

David N. Rosensaft

161 Stouffer

3700 Spruce Street

University of Pennsylvania

Philadelphia, PA 19174

Gaylon S. Ross Institute for Materials Research

National Bureau of Standards

Washington, DC 20234

Wilfred Roth

University of Vermont

Burlington, VT 05401

Lawrence N. Rothenberg

Memorial Hospital

1275 York Avenue

New York, NY 10021

Robert E. Rousseau

University of Texas

133 Iowa Drive

Santa Cruz, CA 95060

Thomas D, Sachs

University of Vermont

Department of Physics

Burlington, VT 05401

Kiichi Sagawa

Johns Hopkins University

Baltimore, MD 21205

Willima F. Sample

UCLA

Center for the Health Sciences

Los Angeles, CA 90024

Roger C. Sanders

Johns Hopkins Hospital

Baltimore, MD 21205

W. H. Schwarz

Johns Hopkins University

Baltimore, MD 21218

Charles F. Serpan

Nuclear Regulatory Commission

Division of Reactor Safety Research

Washington, DC 20555

Bernard Shacter

National Institutes of Health

Bethesda, MD 20014

Ronald W. Shideler

Analytical Chemistry Division

National Bureau of Standards

Washington, DC 20234

Charles A. Shipley

Johns Hopkins University Applied

Physics Laboratory

Silver Spring, MD 20910

George E. Short, Jr. Veterans Administration

810 Vermont Avenue, NW Washington, DC 20420

KoPing K. Shung

Providence Medical Center

556 18th Avenue

Seattle, WA 98122

M. Leon Skolnick

Presbyterian Univ. Hospital

Pittsburgh, PA 15213

James J. Smith

Central Office

Veterans Adminstration

Washington, DC 20420

Stephen W. Smith

Duke University

500 Watts Street

Durham, NC 27701

Adman Sokollu

Case Western Reserve Univ.

School of Medicine

Cleveland, OH 44106

277
Sidney Soloway

Automation

36 Blue Berry Hill

Wilton, CT 06897

Harold Stewart

Bureau of Radiological Health

Rockville, MD 20852

Milton Stoller

Mediscan, Inc. 544 Tolland Street

East Hartford, CT 06108

Mel E. Stratmeyer

FDA/BRH

12709 Twinbrook Pkwy

Rockville, MD 20852

K. J. W. Taylor

Yale University Medical School

New Haven, CT 06510

Patricia Tornheim

University of Cincinnati

Eden and Bethesda Avenue

Cincinnati, OH 45257

H. Tyrer

Becton Dickinson and Company

P. 0. Box 12016

Research Triangle, NC 27709

George A, Uriano

Institute for Materials Research

National Bureau of Standards

Washington, DC 20234

Donald R. Van Deripe

Mallinckrodt Inc. St. Louis, MO 63147

Bill Varner

Purdue University

W. Lafayette, IN 47906

W. F. Via

University of North Carolina

School of Dentistry

Box 2006

Chapel Hill, NC 27514

Lajos J. Von Micsky

St. Luke's Hospital Center

New York, NY 10025

01 af T. Von Ramm

Duke University

Durham, NC 27706

Zarko M. Vucicevic

Schieie Eye Institute

University of Pennsylvania

Philadelphia, PA 19104

278

Robert C. Waag

University of Rochester

Rochester, NY 14627

Ray W. Ware Veterans Adminstration Hospital

Lexington, KY 40507

Richard L. Webber

NIDR/NIH

Bldg. 10, Room 2B09

Bethesda, MD 20014

P. N. T. Wells

Briston General Hospi

Department of Medical

Bristol, BSl 6SY

United Kingdom

Bryan Westerman

Northwestern Memorial Hospital

Chicago, IL 60611

D. N. White

Queens University

Kingston, Ontario

Canada K7L 3N6

Robert L. Wilson

1480 Poppy Peak Drive

Pasadena, CA 91105

William K. Wilson

Institute for Materials Research

National Bureau of Standards

Washington, DC 20234

Alan A. Winder

MSB Systems, Inc.

3 Evergreen Parkway

Westport, CT 06880

Robert N. Wolfson

1555 Belmar Road

East Cleveland, OH 44118

George J. Yang

Carnegie-Mellon University

Electrical Engineering Dept.

Schenley Park

Pittsburg, PA 15213

Lillian Yin

Food and Drug Adminstration

Rockville, MD 20854

Ellen Yorke

University of Maryland

5401 Wilkens Avenue

Baltimore, MD 21228

I

I

talPhysi cs
Donald E. Yuhas

Washington University

St, Louis, MO 63130

Ivan Zador

Cleveland Metropolitan General Hospital

Department of Ob-Gyn

Scranton Road

Cleveland, OH 44109

James A. Zagzebski

University Hospital

1300 University Avenue

Madison, WI 53706

Janis G. Ziedonis

Roche Medical Electronics

Brickyard Road

Cranbury, NJ 08519

Marvin C. Ziskin

Temple University Medical School

3400 N. Broad Street

Philadelphia, PA 19104

I

279

AUTHOR INDEX

281

AUTHOR INDEX

Adler, L., 25 Ahuja, A. S., 210

Anderson, P. T. , 153-163

Atkinson, P., 33,61-70

Beard, C. I., 207,211

Begui, Z. E., 26 Berry, M. V., 33

Birnholz, J. C. , 82

Bolt, R. H., 153-154

Busser, J. H., 9

Chivers, R. C, 182,197

Cook, K. W., 25

Devey, G. B. , 1,7-10

Donaghy, R. M. P., 153-163

Dunn, F., 2,13,21-28,32,72,127,204

Dussik, K. T., 26

Etzold, K. F., 121-133

Fields, S., 32,72,127,204

Fry, E. K. , 32 Fry, F. J., 2,3,143-151,158,231-251

Fry, W. J., 158

Goldman, D. E. , 24 Gramiak, R., 182,213-228

Greenleaf, J. T. , 2,109-119

Greguss, P. , 202

Grimes, R. S. , 153-163

Halliwell, M. , 61-70

Heuter, T. F., 24,153-154,158

Heyser, R. C. , 2,81-95

Hill, C. R., 2,3,34,182,197-212

Hoffman, J. D., 1 Holasek, E., 97-107

Huggins, R. W., 197

Ingard, K. U., 210

Jennings, W. , 97-107

Johnson, S. A., 2,109-119

Jones, J. P., 3,232-233,253-258

Kak, A. C, 3,231-251

Kaya, A., 97-107

Kersta, L. N., 56 Kessler, L. W., 3,261-267

Kishimoto, T. , 25

Kossoff, G., 2,32,73,135-139

LeCroissette, D. H., 2,81-95

Lele, P. P., 2,3,34,167-196

Lerner, R. L., 182

Lerner, R. M. , 213-228

Linzer, M. , 9

Mansfield, A. B., 167-196

Mezrich, R. S., 2,121-133

Milan, J., 2,197

Moore, D. H., 170

Morse, P. M., 210

Mountford, R. A., 55,61-70,72,176

Murphy, A. I., 167-196

Namery, J., 167-196

Nicholas, D., 182,197

Ossoinig, K. C, 2,33

Pfander, F., 24 Preston, K. , 2,9,51-70

Prewitt, J. H. S., 9 Purnell, E. W., 97-107

Reid, J. M., 1-2,11-17,29-47,61,207-212

Renger, F., 61

Sachs, T. D., 2,153-163

Schentke, K. U., 61 Senapati, N., 167-196

Shung, K. K., 2-3,44,207-212

Sigelmann, R. A., 44,207-212

Sokollu, A., 2,97-107

Stenger, R. J., 170

Taylor, K. J. W., 2,38,71-78

Theisman, H. , 24 Twersky, V., 207,209

Vilkomerson, D. H. R., 9,121-133

Waag, R. C, 3,9,34,182,213-228

Wells, P. N. T., 2,38,45,61-70,72,176

Wild, J. J., 11-13,37,61

Wright, S. J., Jr., 153-163

283

SUBJECT INDEX

285

I

SUBJECT

AEMB - see "Alliance for Engineering in Medicine and Biology"

AIUM - see "American Institute of Ultrasound

in Medicine"

ART - see "algebraic reconstruction"

A-scan pattern recognition - 2,51-60,61-70,

71-78

abdomen - 16

absorption - 1-3,13-14,21-28,34-35,38,42,

44-45,82,88,118,143-151 ,153-163,168,172,

192,214,219-220,226,232,255,263-264,266

absorption gradient - 2,143-151,153-154

acceptance criteria - 9 acoustic microscopy - 3,261-267

algebraic reconstruction - 109-119

Alliance for Engineering in Medicine and

Biology (AEMB) - 6,8

American Institute of Ultrasound in Medicine

(AIUM) - 3 anechoic method - 81-95

apodization - 92

arteries - 40

atherosclerotic plaque - 128,132

attenuation - 1-2,13,21-28,29,33,42-44,61-62,

64,81-95,97-107,109-119,121-133,135-139,

143-144,150,153,167-196,231-232,253-254,

256,261,263-264,266

attenuation distribution - 236-237

auditory analysis - 2,51,55-58

bile ducts - 68

blood - 3,13,16,27,29-34,37-39,44,68,207-212,

246,256

bone - 24-26,38,235,266

bowel - 32

Bragg diffraction - 167,175-194,197-206,

213-228

brain - 3,27,86,144-145,147-149,153-163,168,

200,246,256,266

breast - 13,61,109,116-117,121-122,125-127,

135-137,201

CAT - see "computerized axial tomography"

cartilage - 26-27

choroid - 33,107

cirrhosis - 61-70,72,75,193,224-226

collagen - 26-27,32,68,72-73,182,225-226

. color display - 2,4,73,97,105-107,138

compressibility - 22,29,31,34,110,207,215

computer analysis - 61,66,71-78,109-119,

231-251

computerized axial tomography - 2,109-119,

154

computerized tomography - see "computerized

axial tomography"

computer processing - 2,51-59,97,101-105,

167,169-173

connective tissue - 13,68,266

convolution - 91-95,226

correlation - 237-239,244

deconvolution - 3,45,231-251,253-258

INDEX density - 21,24,29,31,67-68,110,144,146,155

158,207,215,261,263,266

dental tissue - 266

dentyne - 266

di-gram - 55 distribution function - 207

Doppler effect - 1,3,11,13-14,158-159,208

echocardiography - 13,33

elasticity - 263,266

elastin - 72 elastogen - 182

emboli - 34,176

enamel - 266

erythrocytes - 207

exit criteria - 9 eye - 2,26,33,38,105

fat - 14,24,27,62-68,132,199-201,246

fibrosis - 68

Fourier transform - 16,55,87-88,90-94,97,

101 ,169-172,199,213,217-218,220-226

Fraunhofer condition - 216,226

frequency dependence - 1-4,13-15,23-26,30,

33-39,43,81-95,97-107,121 ,135,138-139,144,

167-196,197-206,207-212,213-228,232,254-

255,261 ,264,266

frequency translation - 51,57-58

geophysics - 69 glioblastoma - 86

Green's function - 215

grey-scale - 71-73,76,138

half-wave resonance - 13,32

heart - 13,34,109,112-113,115-116,167-171,

256,265

Helmholtz equation - 215,219

hematocrit - 34,207-212

hepatitis - 66

hepato- toxic chemicals - 72-76

histogram - 75-77

IEEE Ultrasonic Symposium - 3 image reconstruction - see "computerized

axial tomography"

impedance - 1-3,21-22,24,26,31-32,42-43,61,

67,71 ,110,118,143-151 ,153,167-168,214,

231-251 ,253-258,261 ,263-264,266

impedance distribution - 263-264

impedance gradient - 143-151

impedance profile - 3,231-251,253-258

impediography - 253-258

impulse response - 3,45,46,91,231-251,253-

258

Instrumentation Technology Program - 7-10

in vitro conditions - 1,16,40,188

International Symposium on Acoustical Imaging and Holography - 1,3

Kalman filtering - 256

Karhunen-Loeve expansion - 55 kidney - 16,24,27,32,51-52,265-266

287
lacunar infarct - 162-163

Laue pattern - 202

layer model - 231-251

leukemia - 73-74,76-77,224-226

Linear Frequency Translation (LIFT) - 57-58

liver - 2,24,27,32,51-54,58,61-70,72-73,76

101,131-132,176,180-181,185-190,192,199-

204,213,222,224-227,246

Logarithmic Frequency Translation (LOFT) - 57-58

lucite - 148,150,231,249,267

lung - 24,26-27,34

lymph channels - 40

lymphoma - 73

melanom.a - 107

mesomorphy - 64

Michel son interferometer - 122-123

Michelson-Morley experiment - 171 microscopy - 3,261-267

mitral valve - 13,15,32

modulus - 21,31-32,67-68,72,261

muscle - 3,24,27,32-33,40,62,68,169-171,174-

179,185,187-194,204,246

myocardial infarction - 33,167-171,173,256

NSF - see "National Science Foundation"

NSF Survey Team of Ultrasonic Imaging - 7 National Bureau of Standards (NBS) - 1 National Institutes of Health (NIH) - 1,3

National Science Foundation (NSF) - 1,3,7-

10, 51,53 nervous tissue - 24-25

nondestructive evaluation - 1,3,197

optimization - 11,13-14

P-factor - 155,158,160

paraffin oil - 38 pattern recognition - 1,51-59

phase-contrast imaging - 2,121,128-132

phasor - 81,87-89

phoneme - 55 placenta - 33 plaque - 266

polyethylene - 131 polystyrene - 130

portal hypertension - 68,73

portal vein - 203

protein - 2,26

RANN - 1,7-10

R&D incentives - 7 Rayleiqh scattering - 14,16,174,199-203,207-

212

refractive index - 109-119,215,218-220

relaxation - 23 resonance - 11 retina - 107

scattering - 1-3,11-12,14-16,21,29-47,53,68

72,82-83,88,118,153,155,167-196,197-206,

207-212,213-228,232,253-255,263-264,266

scattering, cross-section - 13,16,29,31,35,

36-38,41,42,44,45

scattering, surface - 174

sclera - 33 serum - 27 shear waves - 22-24,26,223

silastic rubber - 248

skin - 62,246

skull - 24,25,147,153-155,158,246,248-250,

256

somatotype - 64 sonar - 2,56

Sonomicroscope - 261-267

Spectra-Color Ultrasonography - 105-107

spectra analysis - 34,55,81-95,97-107,167-

196,197,255,256

speech spectrogram - 51,55

spleen - 2,38,71,73-75,77,199-200

splenomegaly - 71-78

sponge - 99-104,136-137

standardization - 29,35-38,42-43,256

statistical analysis - 54-55,61-70,71-78,

185,187-188,190,217-227,256

stomach - 32 streaming phenomena - 158-160

stroke - 162-163

synthetic focus imaging - 109-118

TAST - see "Thermo-Acoustic Sensing Technique"

temperature dependence - 1-2,4,23-25,40,143,

153-163

tendon - 26-27

thalamus - 86

thermal conductivity - 23 thermal effects, 153

thermal gradient, 143-151

Thermo-Acoustic Sensing Technique, 153-163

Time Delay Spectrometry - 81-95

tomography - see "computerized axial tomo- graphy"

tuberculosis - 75 tumor - 11,32-33,72-73,75-76,82,86,109,121-

122,125-127,132,136,153,158,162-163,201

,

235

uterus - 33

veins - 40

velocity - 1-3,14,21-28,29-30,34,72,81-95,

97-107,109-119,121-133,135-139,143-151,

1 53-163,21 5-217,219, 232 ,255 , 261 , 263, 265-

267

velocity distribution - 264

velocity gradient - 2 ventricle - 115

viscosity - 23,31-32,210

water - 2,246-247

Weiner snectrum - 55-56

z-transform - 240-241

288
NBS-114A (REV. 7-73)

U.S. DEPT. OF COMM. BIBLIOGRAPHIC DATA

SHEET

1. PUBLICATION OR REPORT NO. NBS SP=4532. Gov't Accession

No.

3. Recipient's Accession No.

4. TITLE AND SUBTITLE Ultrasonic Tissue Characterization

5. Publication Date October 1976

6. Performing Organization Code

7. AUTHOR(S)

Melvin T, Inzer

8. Performing Organ. Report No.

9. PERFORMING ORGANIZATION NAME AND ADDRESS

NATIONAL BUREAU OF STANDARDS

DEPARTMENT OF COMMERCE

WASHINGTON, D.C. 20234

10. Project/Task/Work Unit No. 3130114

11. Contract/Grant No.

12. Sponsoring Organization Name and Complete Address (Street, City, State, ZIP)

Same as 9.

13. Type of Report & Period Covered Final

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15. SUPPLEMENTARY NOTES

Library of Congress Catalog Card Number: 76-608298

16. ABSTRACT (A 200-word or less factual summary of most significant information. If document includes a significant bibliography or literature survey, mention it here.) An international Seminar on Ultrasonic Tissue Characterization was held at the

National Bureau of Standards on May 28-30, 1975. The meeting was co-sponsored by the

National Bureau of Standards, the National Science Foundation and the National

Institutes of Health. This volume contains extended versions of 20 of the 21 talks

presented at the Seminar. 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) and pattern recognition

techniques

17. KEY WORDS (six to twelve entries; alphabetical order; capitalize only the first letter of the first key word unless a proper name; separated by semicolons) A-scan; absorption; acoustic ; attenuation; B-scan; frequency;

image; reconstruction; impedance; medical diagnosis; microscopy; pattern recognition;

scattering; tissue characterization; tissue parameters, tissue signature; tumor; ultrasonic spectroscopy; ultrasound; velocity.

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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 proce- dures 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 rec- ognized requirements 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 supplement 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 PUBS)—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 stand- ards 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

The following current-awareness and literature-survey

bibliographies are issued periodically by the Bureau:

Cryogenic Data Center Current Awareness Service. A

literature survey issued biweekly. Annual subscription: Domestic, $20.00; Foreign, $25.00.

Liquified Natural Gas. A literature survey issued quarterly. Annual subscription: $20.00.

Superconducting Devices and Materials. A literature survey issued quarterly. Annual subscription: $20.00.

Send subscription orders and remittances for the pre- ceding bibliographic services to National Bureau of Standards, Cryogenic Data Center (275.02) Boulder,

Colorado 80302.
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