NISTIR 7487

Manufacturing Metrology and 

Standards for the Health Care 

Enterprise Program Summary 

Ram D. Sriram and Steven J. Fenves, Editors 

Manufacturing Systems Integration Division 

Manufacturing Engineering Laboratory

April 2008

U.S. Department of Commerce 

Carlos M. Gutierrez, Secretary 

National Institute of Standards and Technology 

 James M. Turner, Acting Director 

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Manufacturing Metrology and Standards for the Health Care Enterprise Program report 

TABLE OF CONTENTS 

1. INTRODUCTION............................................................................................................................... 3

1.1 RATIONALE FOR THE REPORT ....................................................................................................... 3

1.2 ORGANIZATION OF THE REPORT ................................................................................................... 3

2. THE PROGRAM................................................................................................................................ 4

2.1 PROGRAM GOAL ........................................................................................................................... 4

2.2 MOTIVATION................................................................................................................................ 4

2.3 PROGRAM ORGANIZATION AND CONDUCT.................................................................................... 4

3. MEDICAL DEVICE PROJECTS..................................................................................................... 6

3.1 MOBILITY DEVICES ...................................................................................................................... 6

3.2 HEARING DEVICES........................................................................................................................ 8

3.3 SURFACE CHARACTERIZATION OF BIOMEDICAL DEVICES ........................................................... 10

3.4 INTELLIGENT ASSISTIVE SURGICAL DEVICES .............................................................................. 11

3.5 NANO-BIO DEVICES .................................................................................................................... 12

4. HEALTHCARE INFORMATICS PROJECTS............................................................................. 14

4.1 CLINICAL INFORMATICS ..................................................................................................................... 14

4.2 BIOINFORMATICS: SYSTEMS MEDICINE .............................................................................................. 16

4.3 ENTERPRISE MODELING AND SIMULATION .......................................................................................... 19

4.4 MANUFACTURING AND VALUE CHAIN MANAGEMENT ....................................................................... 21

4.5 BIOIMAGING ....................................................................................................................................... 23

5. CONCLUDING COMMENTS........................................................................................................ 25

APPENDIX. PROJECT PARTICIPANTS AND OUTPUTS ................................................................................... 26

REFERENCES............................................................................................................................................. 28

STANDARDS PUBLISHED BY COMMITTEES IN WHICH PROGRAM MEMBERS PARTICIPATED......................... 30

ACRONYMS .............................................................................................................................................. 31

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Manufacturing Metrology and Standards for the Health Care Enterprise Program report 

Manufacturing Metrology and Standards 

for the Health Care Enterprise 

Program Summary 

Ram D. Sriram and Steven J. Fenves, editors 

Project leads: Roger V. Bostelman, Nicholas G. Dagalakis, John A. Dagata, Shaw C. 

Feng, Steven J. Fenves, Charles R. McLean, Victor Nedzelnitsky, Ram D. Sriram, 

Eswaran Subrahmanian, Theodore V. Vorburger, and Randall Wagner 

Abstract 

The Manufacturing Metrology and Standards for the Health Care Enterprise program was 

initiated in FY2005 as part of the overall reorganization of the Manufacturing 

Engineering Laboratory (MEL), with Ram D. Sriram as the Program Manager. The goal 

of the program was stated as follows “to apply proven MEL manufacturing technology 

and expertise to healthcare systems, biomedical devices and equipment, and biomedical 

data management.” This report summarizes the activities, achievements and impacts of 

the program. 

1. Introduction 

1.1 Rationale for the report 

The Manufacturing Metrology and Standards for the Health Care Enterprise program was 

initiated in FY2005 as part of the overall strategic reorganization of the Manufacturing 

Engineering Laboratory (MEL), with Ram D. Sriram as the Program Manager. It became 

one of the new exploratory programs in MEL. 

Since the program is conducted through a number of largely autonomous research 

projects, this report provides a comprehensive overview of the program as a whole since 

the program planning report was submitted in August 2004. 

1.2 Organization of the report 

After a brief overview of the program in Section 2, the individual projects are 

summarized in Sections 3 and 4. The concluding comments in Section 5 summarize the 

program as a whole. 

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Manufacturing Metrology and Standards for the Health Care Enterprise Program report 

2. The program 

2.1 Program goal 

The goal of the program is to apply proven MEL manufacturing technology and expertise 

to healthcare1 systems, biomedical devices and equipment, and biomedical data 

management. 

The program is predicated on the observation that the healthcare and manufacturing 

industries share many similar organizational, technological and informational aspects. 

Thus, the healthcare industry as a whole is a customer for the metrology, standard-setting 

support and technology approaches and solutions that MEL has developed for the 

manufacturing sector that are transferable or adaptable to the healthcare sector. 

The benefit of the program to the healthcare industry is an infrastructure for the 

development of improved organizational, technological and informational support 

methodologies for health care delivery. NIST’s contributions are intended to enable more 

effective development and application of biological and medical knowledge to practical 

problems. 

2.2 Motivation 

The healthcare industry is perennially facing major challenges: increasing costs, 

unacceptable error rates, and dissatisfied patients and providers. Healthcare costs in the 

United States were about 14.9% of the GDP - $1.6 trillion - in 2002, estimated to be 1.9 

trillion in 2005 and projected to rise to 3.6 trillion by 2014. These costs are also a major 

concern for U.S. industry, as escalating healthcare costs are impeding our ability to 

globally compete. 

It is the expectation of the program that importation, adaptation, and application of 

technology and expertise from the manufacturing sector can jump-start the applicable 

aspects of healthcare delivery and the improvement of medical devices. 

2.3 Program organization and conduct 

The program is organized along two dimensions: 

1. Medical devices and 

2. Healthcare informatics. 

Within each of the two dimensions, the program is conducted through a number of 

largely autonomous research projects. The program manager oversees the project 

activities and identifies issues of shared interest among projects. The various projects 

proposed in August 2004 were as follows: 

1

 We use the words “healthcare” and “health care” interchangeably. 

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Manufacturing Metrology and Standards for the Health Care Enterprise Program report 

1. Medical devices 

1.1 Mobility devices. Develop test methods and performance metrics, sensor data, 

standards and specifications necessary for intelligent assistive devices for 

wheelchair dependents and the blind. 

1.2 Hearing devices. Develop test and measurement methods, data, standards and 

specifications necessary for the characterization, manufacturing, and testing of 

hearing devices and related diagnostic equipment. 

1.3 Surface characterization of biomedical devices. Develop test procedures for 

characterizing the surfaces of medical devices that relate to device function and 

failure behavior. 

1.4 Intelligent assistive surgical devices (medical robots). Work with an American 

Standards for Testing of Materials (ASTM) committee, the Food and Drug 

Administration (FDA), medical robotic research groups and University Hospitals 

for the establishment of Intelligent Assistive Surgical Device standards. This work 

will extrapolate on our previous work on industrial robot performance and safety 

standards, related metrology, instrumentation, and artifact and marker design.

1.5 Nano-bio devices. Develop protocols for high-resolution imaging of individual 

components and associated complexes of the constituents of nanoparticle drug 

delivery systems (NDS). Demonstrate imaging of the cell transfection process with 

fixed and live cells using such systems. Nano scale devices have components with 

features which range between 1 micrometer and 1 nanometer. 

2. Healthcare informatics 

2.1 Clinical informatics. Extrapolate from MEL’s experience in information modeling 

and research supporting information interchange standards development for the 

manufacturing industry to provide experience, assistance and leadership for related 

activities in the health care informatics field. 

2.2 Bioinformatics. Adapt and extend NIST’s expertise in information modeling, 

information interchange and standards development in the manufacturing arena to 

the field of bioinformatics, leading to synergisms with bioinformatics research and 

practice and consolidation of the bioinformatics knowledge base. 

2.3 Enterprise modeling and simulation. Explore the applicability of the modeling and 

simulation technologies developed in MEL to healthcare systems; explore means 

for disseminating this information to the shareholders in the healthcare industry.

2.4 Manufacturing and value chain management. Develop interface specifications and 

interaction protocols for integrating manufacturing and e-commerce software 

solutions into biomedical device value chain and enhance existing standards for 

device integration. 

An additional project on Bioimaging, funded as part of the American Competitive 

Initiative (ACI), was added to the Healthcare informatics portfolio. The goals of this 

project are: 

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Manufacturing Metrology and Standards for the Health Care Enterprise Program report 

1) develop standardized representation schemes and archival techniques for a webbased data storage system that will enable semantic annotation, content-based 

search and retrieval, visual browsing, cross linking between pathological states 

and image features, and appropriate levels of security, and 

2) develop an ontology to represent the semantics of archived images that can be 

used as the basis for open standard implementations of archive systems. 

3. Medical device projects 

3.1 Mobility devices

Introduction and goals 

Mobility must be viewed as being essential to the outcome of the rehabilitation process of 

wheelchair-dependent persons and to their successful (re-)integration into society. Just as 

important are the lift devices that lift patients into wheelchairs and other seats. In 2005, 

NIST ISD (Intelligent Systems Division) began the Healthcare Mobility Project to target 

patient lift and mobility. ISD researchers looked at currently available technology 

through a survey of patient lift and mobility devices. The survey showed that there is a 

need for technology that (a) includes mobility devices that can lift and maneuver patients 

to other seats and (b) can provide for rehabilitation to help the patient become 

independent of the wheelchair. The survey also noted that there are no standards nor 

performance metrics for either technology. 

Technical overview: 

Six major activities were undertaken: 

1) HLPR chair concept. NIST designed an HLPR (Home Lift, Position, and Rehab) 

Chair testbed to investigate patient transfer including specific areas of mobility, lift 

and rehabilitation toward safety standards, performance measurements of such 

devices, and advanced autonomous controls. The HLPR Chair testbeds are based on a 

manual, steel, inexpensive, off-the-shelf, and sturdy forklift. The forklift includes a 

U-frame base with casters in the front and rear and a rectangular vertical frame. The 

lift and chair frame is small enough to pass through even the smallest residential 

bathroom doors. 

2) Seat/stand. The patient seat/stand mechanism is a double, nested and inverted Lshape where the outer L is a seat base frame that provides a lift and rotation point for 

the inner L seat frame. The L frames are made of square, aluminum tubing. The 

outer L is bolted to the lift device while the inner L rotates with respect to the seat 

base frame at the end of the L. Drive and steering motors, batteries and control 

electronics along with their aluminum support frame provide counterweight for the 

patient to rotate beyond the wheelbase. When not rotated, the center of gravity 

remains near the middle of the HLPR Chair. When rotated to 180o with a 136 kg 

(300 lb) patient on board, the center of gravity remains within the wheelbase for safe 

seat access. Heavier patients would require additional counterweight. 

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Manufacturing Metrology and Standards for the Health Care Enterprise Program report 

3) Propulsion. The HLPR Chair is powered similarly to typical powered chairs on the 

market. However, the HLPR Chair has a tricycle design to simplify the need to 

provide steering and drive linkages and to provide for a more vertical and compact 

drive system design. The front of the robot has two casters mounted to a U-shaped 

frame. Steering is a novel single wheel design, hard stopping the wheel at just 

beyond 180o for safety. 

4) Patient placement on other seats. Healthcare providers explained that caregivers 

placing patients on toilets provide the worst condition for injuries to caregivers 

because of confined spaces. To place an HLPR Chair user on another seat, they can 

drive to it. Once there, the HLPR Chair rotates the footrest up and beneath the seat 

and the patient’s feet are placed on the floor personally or by a caregiver. The HLPR 

Chair inner L-frame can then be rotated manually with respect to the chair frame 

allowing the patient to be above the toilet. Padded torso lifts then lift the patient from 

beneath his/her arm joints similar to crutches. The seat, with the footrest beneath, 

then rotates from horizontal to vertical behind the patients back clearing the area 

beneath the patient to be placed on the other seat. 

5) Patient lift. Patient lift is designed into the HLPR Chair to allow user access to high 

shelves or other tall objects while seated. The HLPR Chair’s patient lift is 

approximately 1 m (36 in) to reach what a typical standing 2 m (6 ft) tall person could 

reach. The additional height comes at no additional cost of frame and only minimally 

for actuator cost. Lift is achieved by a 227 kg (500 lb) max. lift actuator that can 

support 681 (1500 lb) statically. The actuator can be replaced with a higher capacity 

unit if needed. The actuator connects to a lift plate with a steel chain that is fixmounted at one end to the HLPR Chair frame and to the lift plate at the other end. 

6) Patient rehabilitation. HLPR Chair enhances patient rehabilitation through a load 

sensor and control on the lift actuator. The researchers designed rehabilitation into 

the HLPR Chair to allow, for example, stroke patients to keep their legs active 

without supporting the entire load of the patient’s body weight. The patient, once 

lifted, could walk while supported by the HLPR Chair driving at a slow walking pace 

towards regaining leg control and eliminating the need for a wheelchair. 

For further details see http://www.isd.mel.nist.gov/healthcaremobility/. 

Achievements 

Two HLPR chairs have been built: (a) the first to study the advanced autonomous control 

and transfer to the University of Pittsburgh for collaboration on future standards, and (b) 

the second to study manufacturability, ergonomics. The latter was transferred to the 

Florida Gulf Coast University for collaboration on future interoperable controls and to 

study static and dynamic stability performance testing. 

Achievements also included: 

1) Five published papers 

2) Two NIST Internal Reports 

3) Several presentations 

4) Workshop presentation at ICDR 07 in Arlington, VA 

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Manufacturing Metrology and Standards for the Health Care Enterprise Program report 

5) Meetings with Walter Reed Army Medical Center, University of Pittsburgh and 

Florida Gulf Coast University 

6) Two videos of the HLPR Chair 

7) HLPR Chair Tech Beat Article which provided over 1000 initial Google hits 

8) Application for patent on “Modifications to the HLPR Chair.” The HLPR Chair 1 is 

in the public domain. 

Impacts 

The HLPR Chair impacts healthcare service providers, reducing the need for manual 

labor in transferring patients. In this field 1 in 3 nurses becomes injured from patient 

transfer, a rate that is about 2 1/2 times higher than that of all other general industries. 

Injuries in Nursing Homes alone this year will reach 200,000 incidents at a cost of almost 

$1 billion.

3.2 Hearing devices 

Introduction and goals 

Hearing loss afflicts approximately 30 million Americans of all age groups. The Better 

Hearing Institute (2005) quantified that the impact of untreated hearing loss is “in excess 

of $100 billion annually” for America’s 24 million hearing-impaired who do not use 

hearing instruments, and that the corresponding annual “cost to society could be well in 

excess of $18 billion due to unrealized taxes.” The diagnosis and treatment of hearing 

loss and the currently excessive incidence of failures of hearing devices must be 

improved: nearly one of every five aids dispensed in 2000 was returned to the 

manufacturer for credit, totaling $500 million in 2000. 

Auditory diagnostic and prosthetic devices include a wide variety of analog instruments 

and programmable digital devices that contain analog components and are capable of 

digital signal processing. The greatly enhanced features and capabilities of evolving 

devices call for suitable methods and standards enabling performance specification, 

replicable measurements, production testing, and quality assurance. 

The goal of this project is to develop test and measurement methods, data, standards and 

specifications necessary for the characterization, manufacturing, and testing of hearing 

devices and related diagnostic equipment so as to help designers, diagnosticians, and 

dispensers to control the very large societal costs of untreated hearing loss as well as the 

excessive incidence of failures in patient outcomes. 

Technical Overview 

Hearing devices include hearing aids, cochlear and brainstem implants, and related 

diagnostic equipment. Product design, production quality control, and acceptance 

testing/conformity assessment require well-defined and replicable measurement 

procedures. Often, a given type of device is characterized by many parameters that must 

be adjusted to meet the needs of individual patients. Proper determinations of these 

individual needs, as well as the verifications of parameter selections, adjustments, and 

patient outcomes, often require complicated diagnostic equipment and procedures 

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Manufacturing Metrology and Standards for the Health Care Enterprise Program report 

designed and optimized for that type of device. Lack of compatibility of devices, 

equipment, or procedures from different manufacturers can be an important issue. 

The Department of Veterans Affairs (VA) needs NIST to characterize hearing aids that 

the VA submits. Hearing aid characteristics are determined by means of measurements 

conducted in accordance with the criteria and procedures established or approved by the 

VA. In addition, the VA needs NIST to make any necessary alterations in test methods 

based on new developments and designs in the field of hearing aids and related diagnostic 

equipment and techniques. These needs are met by Interagency Agreements between the 

VA and NIST. The technical approach applies the experience, specialized laboratory 

facilities and equipment of NIST to the task. Personnel at NIST participate in national 

and international standardization activities in this area through the American National 

Standards Institute (ANSI) and the International Electrotechnical Commission (IEC), 

which leverage the effect of the NIST work. Specialized laboratory facilities and 

equipment include anechoic chambers, acoustical measurement instrumentation including 

custom-designed systems and computer programs, and anthropometric manikins designed 

for hearing aid and related acoustic research. 

Achievements 

Achievements included: 

1) Completed directivity index measurements on two directional hearing aids which 

were circulated among several laboratories involved in a directional measurement 

round-robin organized within the ANSI Hearing Aid Working Group S3/WG48. 

2) Performed special testing on audio headsets designed to meet the requirements of The 

National Library Service for the Blind and Physically Handicapped (NLS). 

3) Received an A rating (numerical score of 100) in every category included on the 

NIST Customer Satisfaction Report Card completed by the VA. 

4) Developed test procedures for measuring the insertion gain of open-fit hearing aids. 

5) Developed preliminary plans with the VA to conduct tests of open ear and fullysealed deep-fitting postauricular hearing aids. 

6) Performed measurements using vented earmold and E-A-R® plugs in the occlusion 

effect simulator with the system in its current configuration. 

7) Developed plans to acquire occlusion effect data with vented earmolds as a function 

of vent size for comparison with data reported from a clinical study that examined the 

magnitude of the occlusion effect as a function of vent size for real ears. 

8) Worked with an audiologist at the Washington, DC VA Medical Center to produce 

ear impressions required to fabricate earmolds for testing in the occlusion effect 

simulator. 

9) Participated in the publication of ANSI S3.35-2004 Method of Measurement of 

Performance Characteristics of Hearing Aids Under Simulated Real-Ear Working 

Conditions. 

10) Participated in meetings of the ANSI Hearing Aids Working Group S3/WG48. 

11) As Technical Advisor to the U.S. National Committee of the International 

Electrotechnical Commission (USNC/IEC) for IEC TC 29, Electroacoustics, provided 

recommendations to the USNC/IEC and participated in the publication of seven 

international standards. 

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Manufacturing Metrology and Standards for the Health Care Enterprise Program report 

12) Provided the recommended USNC/IEC positions and comments on fourteen draft 

IEC standards on hearing devices and related equipment. 

13) Provided comments and votes on six ANSI draft standards and documents. 

Impacts 

Services performed by NIST for the VA play a key role in helping VA officials make 

purchasing decisions regarding hearing aids, including the way in which the VA specifies 

the types of aids it purchases and the characteristics of these aids. These services affect 

an even larger population than veterans with hearing impairment, since the VA has a 

major effect on the way in which technology and services are provided to all persons in 

the U.S. with hearing-related problems. According to The Hearing Journal (February 

2001), the audiology program of the VA is “far reaching in its goals and has a strong 

ripple effect throughout the whole U.S. hearing healthcare community.” 

The development of measurement techniques and recognized, widely accepted standards 

for characterizing hearing devices is supporting improved production and quality control 

of these devices, as well as improved selection and adjustment of these devices to meet 

the diverse needs of individual patients. 

3.3 Surface characterization of biomedical devices 

Introduction and goals 

We aim to develop test procedures for characterizing the surfaces of biomedical devices 

that relate to device function and failure behavior. The function of medical devices is 

critically dependent on their surface topography. These devices include transcutaneous 

pretreatment devices, orthopedic implants, heart pacemaker electrodes, dental 

preparations, and intravascular stents. In addition, the properties of test cultures may be 

strongly correlated with their surface topography. 

Technical overview 

We are investigating the importance of surface roughness and geometry for two 

applications: 

1) The correlation of surface roughness of vascular smooth muscle cells to their 

response under macroscopic strain. 

2) The effect of surface topography on the function of transcutaneous pretreatment 

devices. 

Optical confocal microscopy is being tested as the surface roughness measurement tool. 

Achievements 

The work emphasized the first direction described above. In collaboration with the 

Polymers Division in the NIST Material Science and Engineering Laboratory (MSEL), 

we studied the roughness of extracellular matrix proteins coated onto substrates of 

deformable polydimethylsiloxane elastomer modified by different surface treatment 

methods. Results from physically adsorbed, chemically attached, and covalently bonded 

proteins were compared to determine the best surface treatment for high coverage and 

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Manufacturing Metrology and Standards for the Health Care Enterprise Program report 

uniformity. Surface topography images and profiles were obtained using a NanoFocus 

μSurf confocal microscope with a rotating Nipkow disk and a xenon light source over a 

field of view of 800 μm x 800 μm with an x and y pixel resolution of 1.56 μm. 

A number of alternative surface treatments were investigated. We note the results for two 

of these. A treatment of silane followed by glutaraldehyde produced protein surfaces 

with higher surface roughness (≈32 nm) and lower protein coverage than the others and 

therefore this treatment seemed less effective than the others. By comparison, the 

pretreatment of silane incubated at 70oC produced high protein coverage and high 

uniformity along with modest surface roughness (≈10 nm). This type of treatment will be 

explored more fully in subsequent tests on smooth muscle cells in future studies 

involving mechanical stress of the protein coatings. The surface roughness measurements 

were useful for characterizing the quality of the protein structures. 

Impacts 

The Precision Engineering Division’s confocal microscope contributed successfully to 

the assessment of the surface quality of protein coatings and will be effective in future 

studies of these systems in collaboration with bio-engineering researchers. 

3.4 Intelligent assistive surgical devices 

Introduction and goals 

Approximately one million arthroplasty (joint reconstruction) operations are performed 

per year throughout the world. Sources indicate that 8.8 % of revision joint surgery could 

be attributed to malpositioning of the implant. Computer Assisted Orthopaedic Surgery 

(CAOS) systems help reduce the variability of the positioning of prosthetic components. 

The project objective is to work with representatives of the users and manufacturers of 

these systems and tools in order to develop standards and tests which can help minimize 

surgical problems and achieve optimum performance results. 

Technical overview 

CAOS systems help reduce the variability of the positioning of prosthetic components, 

thus permitting a more consistent placement of the prosthetic components. CAOS 

systems consist of tracking sensors, tracking markers, a computer and other electronics. 

During an operation the markers are attached to bones, surgical tools and implants. The 

position of the markers is determined with respect to a reference frame and based on that 

information the position and orientation of tools, bones and implants is calculated. 

We have developed a simple, lightweight, easy to use operating room high precision 

artifact, called phantom by medical professionals, which can be used at the beginning of 

each operation for a quick calibration and performance test of most CAOS systems. A 

longer and more thorough calibration and performance test can be performed early in the 

morning before the first surgical operation. 

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Manufacturing Metrology and Standards for the Health Care Enterprise Program report 

Achievements 

Achievements included: 

1) Conducted a Medical Devices Metrology and Standards Needs workshop. 

2) Submitted for review five USMS Medical Devices Metrology and Standards Needs. 

3) Completed the machining of the Horizontal Joint-Computer Assisted Orthopaedic 

Hip Surgery (HJ-CAOHS) artifact. This artifact is using a commercially available 

precision magnetic ball and socket to simulate the human hip joint. The phantom is 

made of a femur bar, a magnetic ball and socket and an L shape XY coordinate frame. 

4) Completed the calibration of the HJ-CAOHS Phantom. 

5) Published two papers. 

Impacts 

The workshop on "Medical Devices Metrology and Standard Needs," was attended by a 

large number of medical professionals and medical devices suppliers and researchers. 

Acting as a catalyst, the workshop has created potential collaborations among the 

participants and has attracted a lot of attention by NIST, FDA and NIH researchers. For 

further details see http://www.isd.mel.nist.gov/medical_devices/. 

Adoption of the NIST CAOS phantoms has the potential to significantly reduce the 

number of malpositioning failures of arthroplasty surgical operations. This will reduce 

the suffering of hundreds of thousands of patients and save tens of millions of dollars 

annually. 

3.5 Nano-bio devices

Introduction and goals 

Nanoparticle delivery systems (NDS) -- multicomponent, multifunctional vehicles for 

targeted delivery of diagnostics and therapeutics -- represent one of the most promising 

developments in nano-medicine. Imaging as physical measurement is expected to play a 

crucial role in future drug discovery and development processes. However, the 

technology for characterizing nano-bioparticles, biologically functional and organized 

structures in the size range of 10-200 nm, is still in its infancy. The National Cancer 

Institute (NCI) and Food & Drug Administration (FDA) are seeking to replace slow and 

expensive biological and biochemical assays. NCI’s Nanotechnology Characterization 

Laboratory’s (NCL) “characterization cascade” is intended to qualify NDS prior to FDA 

approval, but there are no structure-function relationships that currently link individual 

physical measurements to in-vitro and in-vivo biological properties. In collaboration with 

Georgetown University Medical Center (GUMC) and the University of Akron, we have 

developed a systematic methodology for directly correlating physical and biological 

information about NDS from imaging data. This approach utilizes fluid scanning probe 

microscopy (SPM) as a versatile tool for high-resolution imaging of, and obtaining 

dynamical information about, functional biological systems in solution. Fluid SPM refers 

to the operation of a scanning probe microscope under solution conditions. It includes the 

development of specialized techniques for sample preparation, stable feedback operation 

of an oscillating probe tip in solution, and quantitative force measurements of chemical, 

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Manufacturing Metrology and Standards for the Health Care Enterprise Program report 

mechanical, electrical, hydrodynamic, and magnetic interactions of the molecular 

constituents of an NDS. Appropriate preparation and measurement techniques for 

physical characterization of nano-bioparticles have been developed in parallel with invitro and in-vivo GUMC efficacy studies in order to facilitate drug discovery and 

development. 

Technical overview 

Two major activities were undertaken: 

1) Fabrication of standard phantoms for magnetic resonance imaging. Optimal design 

and formulation of a nanoparticle delivery system for biomedical applications 

requires development of a systematic methodology for directly correlating physical 

and biological information through high-resolution imaging of functional biological 

entities. We have achieved our goal of calibrating spatial resolution and threshold 

detection limits for iron-oxide and gadolinium-containing Magnetic resonance 

imaging (MRI) contrast agents and have validated the nanoscale size dependence of 

GUMC formulations based upon magnetic measurements at NIST. 

2) Advanced imaging for targeted nanoparticle delivery systems (NDS). Fluid scanning 

probe microscopy uniquely satisfies the needs for high-resolution imaging of 

dynamical biological systems in solution. We have achieved our goal of providing an 

essential linkage between biomedical and physical disciplines using functional NDS 

by successfully performing size, size distribution, particle aggregation, and physical 

activity on systems with encapsulated gene therapy, chemotherapy, and magnetic 

resonance imaging contrast agents. 

Achievements 

Achievements included: 

1) Demonstrated optimized methods for immobilizing intact liposome-based 

nanoparticle delivery systems (NDS) for scanning probe microscope (SPM) imaging 

and characterization under fluid conditions: 

• Optimized mica, poly-L-lysine (PLL)-mica, and silane-modified silicon substrate 

preparation 

• Demonstrated UV/ozone tuning of surface potential of PLL-mica substrates 

• Developed surface-potential patterning techniques for PLL-mica substrates 

• Evaluated rotating disk method for surface potential determination of substrates 

• NDS compressibility 

2) Fabricated and evaluated improved magnetic coatings for fluid and dry magnetic 

force microscopy (MFM) for characterizing dispersed and aggregated MRI contrast 

enhancement agents: 

• Quantitative methods for establishing iron concentration and particle density of 

NDS-encapsulated SPIOs 

• Magnetic characterization of GUMC SPIOs (MFM, SQUID, MRI) 

3) Investigated quantitative particle size analysis of gold reference nanoparticles, NDS 

and SPIOs from SPM images and comparison with dynamic light scattering (DLS): 

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Manufacturing Metrology and Standards for the Health Care Enterprise Program report 

• Lift-mode techniques for validating intactness and measuring compressibility of 

adsorbed liposomes 

• Quantitative particle size analysis from SPM images and inter-comparison with 

DLS 

4) Participated as the NIST representative on the organizing committee of a National 

Science Foundation-sponsored workshop on Nano-Bio-manufacturing, March/April 

2008. 

Impacts 

1) The rotating disk method for measuring surface zeta potentials of substrates as a 

critical step in optimizing the attachment of liposome-based NDS will enable highmagnification imaging techniques to perform quality assurance and potency 

assessment of nanoparticle delivery systems at both individual and bulk particle level 

during drug development and optimization. 

2) Correlation of size, aggregation, and functionality of magnetic nanoparticles as 

magnetic resonance imaging contrast agents will hasten the implementation of their 

diagnostic use and improve early detection of disease. 

3) Fluid SPM imaging provides a unique means of validating statistical size distributions 

obtained from dynamic light scattering and those obtained by electron microscopy, 

thus reducing reporting discrepancies that arise during the drug approval process. 

4) The standardization and measurement work enables repeatable and reproducible 

measurement of physical properties of nanoparticle delivery systems and their 

components. This will help accelerate drug discovery and development.

4. Healthcare informatics projects 

4.1 Clinical Informatics 

Introduction and goals 

The goal of the project is to extrapolate from MEL’s experience in information 

interchange standards development to provide assistance for related activities in the 

healthcare informatics field. 

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Manufacturing Metrology and Standards for the Health Care Enterprise Program report 

Technical overview 

Three major activities were undertaken. 

1) Survey of opportunities. As initially proposed, an extensive survey of the strategic 

focus area in healthcare informatics was completed. The report presents three aspects 

of clinical informatics of most immediate interest: 

• Approaches and standards for the integration and interchange of health 

information 

• Controlled vocabularies of concepts that cover medical knowledge and 

• Evidence-based medicine (EBM), filtering and disseminating healthcare 

knowledge. 

2) Assistance to the Office of the National Coordinator for Health Information 

Technology (ONC). The Architecture Development Facilitator (ADF) was developed 

to assist the Office of Network Coordinator for Health Information Technology of 

the Department of Health and Human Services (HHS) and its agents in the 

deployment of the Nationwide Health Information Network (NHIN). ADF was 

intended to serve as the repository of a set of predefined compatible health care IT 

components, called artifacts, which can then be combined to design, configure and 

deploy a large variety of health care IT system architectures. 

3) Analysis of workflow in physicians’ offices. The goal of this study is to understand 

and map detailed workflow for small physician offices. The study is to be performed 

with in-situ interviews and use of questionnaires. Our goal to confirm and elaborate 

some of the findings about use and adoption of EHR and other automation in small 

physician offices. 

Achievements 

Achievements included: 

1) The strategic focus survey served as both an inventory of capabilities and a plan for 

action. The ONC project on the ADF was a direct outgrowth of both the contacts 

made between MEL and ITL and of the capabilities described in the report. 

2) The design of ADF responded to the evolving nature of the NHIN envisaged by 

ONC. It made absolutely no assumptions about the upper levels of the NHIN 

architecture and did not impose any constraints on any architecture that may evolve, 

from the most highly centralized one to the fully decentralized one. ONC chose to 

redirect its efforts towards a network of networks, which made the repository of 

small, atomic components redundant. 

3) A questionnaire was developed and submitted to the Department of Commerce for 

required clearances. A report on the workflow and sources of delay in processing 

patients and documents will be written after we get the required clearances. 

Impacts 

1) The impact of the strategic focus survey has been largely internal to NIST by 

identifying compatible interests and specific focus areas to pursue. 

15 
Manufacturing Metrology and Standards for the Health Care Enterprise Program report 

2) While the directions of ONC and the ADF project paralleled each other, the ADF 

team had multiple opportunities to impact a number of ONC initiatives beyond the 

ADF proper. 

3) The main impact of the workflow studies of small offices will be on the identification 

of benefits and causes for EHR implementations in small physician offices and the 

need for an information network infrastructure to facilitate their integration. 

4.2 Bioinformatics: Systems Medicine 

Introduction and goals 

The Human Genome project has provided us with a map of the human genome, the study 

of which is called genomics. This has led to developments of a wide variety of 

technologies for profiling a person’s DNA. It is predicted that we will be able to provide 

the complete genetic profile of a person in a cost effective manner in the near future. 

Genomics, along with the evolving fields of proteomics - which involves the study of the 

functions of all expressed proteins and protein networks - and metabolomics - which 

involves the rapid, high throughput characterization of the small molecule metabolites 

found in an organism - is changing the practice of medicine. 

The integration of various “omics” to understand a biological system is the field of 

systems biology (SB). Essentially, systems biology involves gathering comprehensive 

sets of data that define and quantify the elements of a particular biological system and 

computationally analyze them to establish functional and dynamic connections. The 

premise is that no molecule in biology acts alone. Systems biology in a clinical context is 

called systems medicine (SM). We will use the term SB&M to denote systems biology 

and medicine. As Leroy Hood, a member of NIST’s VCAT, put it, “Systems approaches 

to medicine are transforming current diagnostic and therapeutic approaches to medicine, 

and together with new technologies, will enable a predictive and preventive medicine that 

will lead to personalized medicine.” 

Technical overview 

Biological systems are characterized by multiple interlinked pathways of interaction at 

various levels. These levels span the molecular level to the cellular level and to the 

multi-cellular organism level. The interactions within and across these levels are critical 

to the fundamental understanding of SB. The goal of SB is to formalize descriptions of 

these processes and interactions. The state of art in SB and absence of a grand theory 

open the space of exploration to extending the traditional systems engineering (SE) 

principles to better understand the challenges of SB. This work is directed at a survey of 

accomplishments in SB and exploring the feasibility of applying SE approaches to this 

emerging field. The approach will be based on feasibility of applications of current 

computational formalisms available is SE, their limitations, and the requirements for 

extending these formalisms for developing a deeper understanding of biological 

functions. 

Three major activities were undertaken: 

1) Identification of proteins involved in diabetes condition change after stomach 

stapling. The Hershey Medical Center (HMC) recently discovered that some 

16 
Manufacturing Metrology and Standards for the Health Care Enterprise Program report 

morbidly obese patients, who were initially diabetic, found themselves free of 

diabetes after stomach stapling surgery. HMC was interested in understanding the 

mechanism involved in this process. Differential Protein Expression Profiling, which 

uses mass spectrometry, makes it possible to get a “snapshot” of the biological state 

of the patient before and after the surgery in terms of relative protein levels. Using 

this information and various statistical methods and wavelet analysis we can generate 

a protein-protein interaction network that can be used to determine the pathways 

involved in the curing of diabetes. 

2) Evaluating protein-protein interaction software. The primary goal of this project is to 

develop metrics for evaluating protein-protein interaction software. We ventured into 

this by selecting a problem and then evaluating various tools for this problem. The 

problem we selected involves the interaction of two proteins involved in Alzheimer’s 

disease (AD): Cdk5 and p25. Cdk5 (cyclic dependent kinase 5) plays a significant 

role in Alzheimer’s disease (AD) and other neurodegenerative diseases; Cdk5 was 

discovered at the National Institutes of Health, while studying the regulation of 

neuronal cytoskeletral proteins by phosphorylation. Essentially, Cdk5 

phosphorylates another protein tau at AD-specific phospho-eptiopes when it 

associates with a protein p25. p25 is a truncated activator, which is produced from 

another protein p35—a neuron specific cdk5 activator—when exposed to amyloid 

beta peptides. However, another peptide called CIP (Cdk5 Inhibitor Protein) will 

make the Cdk5/p25 combination inactive. Our goal is to better understand the role of 

geometry in the interactions between Cdk5, p25, and tau, so as to develop metrics for 

evaluating various docking programs. To do this we first obtained the various 

trajectories of conformational transition for Cdk5, p25 and CIP and then we defined a 

procedure to perform a preliminary comparison of the relative abilities of p25 and 

CIP to conform to the kinase. Our procedure compares the geometric affinity of p25 

and CIP with Cdk5 for each given conformation. It consists of aligning a given Cdk5 

conformation with the corresponding p25 or CIP conformation in compliance with 

the conservation hypothesis. This means that Cdk5 and CIP or p25 should be aligned 

such that their interface interaction is as close as possible to Cdk5/p25 active 

conformation. A distance function is finally evaluated after the alignment, and it 

yields the geometric affinity between CIP or p25 with Cdk5. 

3) Extracting protein-protein interaction sentences from literature. Protein-Protein 

Interaction (PPI) information is critical to understanding the function of individual 

proteins and the organization of entire biological processes. Therefore, current 

biomedical literature is replete with articles that describe PPI experiments, which 

specify individual interaction proteins and the corresponding interaction types. 

Protein interaction databases also have been developed by utilizing these biomedical 

articles. However, the rapid growth of the literature makes it difficult to manually 

find the necessary information. In addition, the dynamic nature of biology makes 

building the ontology or the database more difficult. We undertook the development 

of a machine learning-based framework called PIE (Protein Interaction information 

Extraction system), which identifies PPI information automatically from the 

biomedical literature. PIE consists of two procedures: article filter and sentence filter. 

In the article filter, documents are roughly classified to reduce the overhead of the 

second procedure. The AdaCost algorithm with naive Bayes classifiers is used for the 

17 
Manufacturing Metrology and Standards for the Health Care Enterprise Program report 

article filter, and the SVM classifier with tree kernels is used to identify PPI-relevant 

sentences for the sentence filter. 

Achievements 

Achievements included: 

1) Evaluating protein-protein interaction software. We determined theoretically based 

trajectories of Cdk5, p25 and CIP conformational transitions through FIRST/FRODA 

technique and geometry-based algorithms implemented in Matlab. Then, based on the 

obtained Cdk5, p25 and CIP trajectories, we defined a procedure to perform a 

preliminary comparison of the relative abilities of p25 and CIP to conform to the 

kinase. In the late stages of the activation trajectory our preliminary comparisons 

indicate -consistent with our hypothesis - that CIP is more able than p25 to conform 

to the kinase. Therefore it can be inferred that CIP is less rigid than p25. 

2) Extracting protein-protein interaction sentences from literature. The experimental 

results confirm that the PPI articles are successfully classified using word-based 

probability distributions. According to the sentence-level experiments, it is shown 

that the PPI sentences have their own grammatical structures, and can be represented 

by a general full parser even without tuning for the PPI domain. The structural 

patterns are successfully classified using support vector machines with tree kernels. In 

contrast to the previous rule-based approaches, the machine learning approaches can 

discover new patterns which are not captured in the known trigger word list. And 

their automatic way can reduce human efforts and database development cost because 

the biological databases frequently add or modify new information. These techniques 

can also incorporate corpus statistics to achieve good performance. 

3) Identification of proteins involved in diabetes condition change after stomach stapling.

Pennsylvania State University, with a support grant from us, obtained the required 

data from the Hershey Medical Center. The following tasks were undertaken: 1) 

Identified the required peptide ratios; 2) Grouped the ratios with respect to range 

(different ratio ranges); 3) Clustered the different proteins in a particular range; 4) 

Compared the clusters across all the patients; 5) Identified the significant protein from 

the cluster properties; and 6) Applied associative rule mining algorithm to identify the 

other significant proteins. 

Impacts 

SB&M is an emerging field and its impact on the pharmaceutical industry and medical 

practice will be significant. Interoperability and testing concerns have been repeatedly 

voiced in several NIH and NIST workshops. Integration of genomics, proteomics, and 

clinical medicine will lead to innovation in drug discovery and health care delivery, and 

will result in higher health care quality and lower costs. This will result in significant 

savings for the $1.7 trillion dollar health care industry. We believe that we have made a 

first step toward achieving these benefits. 

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Manufacturing Metrology and Standards for the Health Care Enterprise Program report 

4.3 Enterprise modeling and simulation 

Introduction and goals 

Simulation, modeling, and game technology can be used to support a broad range of 

applications pertaining to the health care industry. Our first objective was to conduct a 

background study to identify needs, issues, and tools with respect to health care 

simulation. Our second objective was to hold a conference to bring together simulation 

users from the healthcare industry, academia, and government that have an interest in 

healthcare simulation standards. 

Technical overview 

Principal users of healthcare simulations and standards include healthcare facilities, 

simulation software vendors, and researchers that will need new interface standards to 

help develop healthcare simulations or use them to improve facilities and operations. 

A detailed background study is currently under review for publication as a NIST 

technical report. The focus has been to identify healthcare simulation applications. A 

brief summary of the study follows. 

Both discrete-event simulation and system dynamics models are recommended for 

application at team, organization, and environment levels, leaving out only the individual 

patient level. Discrete event and system dynamics simulations are recommended for 

evaluations in health care when interactions between individuals are important for the 

system aspect being studied. 

Simulation tools for application to health care have a higher potential of adoption by 

health care professionals than other systems analysis tools that may be seen as black 

boxes. The methodology of simulation tools can be explained much more easily 

compared to say, mathematical programming. The ability to communicate the simulation 

methodology is further helped by available visualization facilities with most simulation 

tools. 

Recent literature on simulation applications in health care are surveyed in the study. 

Emphasis is placed on recent literature and efforts that have not been identified in other 

reviews of the field. 

A classification of types of simulations that are included in the review is described below. 

Other sections of the report review the literature for successive relevant simulation types. 

The individual simulation applications are followed by a discussion of some related 

developments such as integrated simulations and simulation infrastructure issues. The 

concluding section identifies emerging directions for simulation applications in health 

care. The relevant simulation techniques for the field of health care are listed below. 

1) Computer simulations include models that represent the behavior of a physical system 

using computer programs that allow limited, if any, interaction during execution. The 

following types are included: 

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Manufacturing Metrology and Standards for the Health Care Enterprise Program report 

• System dynamics simulation represents a system using causal relationships that 

determine system behavior over time using differential equations. 

• Discrete event simulation representation uses events that make step changes in the 

status of the system over time. 

• Agent-based simulation uses representations of behavior of independent entities 

forming the system to determine the status of the system over time. 

• Monte Carlo simulation uses random distributions to represent the outcomes of a 

system without modeling the passage of time. 

• Continuous simulation uses differential equations to represent the physical 

phenomenon being studied over time. 

2) Simulators and simulated environments are built with the objective of training and in 

some cases assessing clinical skills. This category includes the following types: 

• Virtual reality and gaming use highly interactive three-dimensional computer-based 

graphics and human interaction devices to allow trainees to practice clinical skills. 

• Patient simulator devices include the use of mannequins that represent the behavior 

of full or part of a human body under various conditions. 

• Simulated environments include the use of hospital rooms designed to represent real 

functional rooms such as patient visit rooms with humans role playing as patients or 

operation theatres with mannequins as the patient. 

Achievements 

Achievements included:

1) Reports and Presentations. Prepared two draft journal papers, an in-depth survey 

presentation (150 slides) and a presentation paper.

2) Conferences and Workshops. Held three workshops and a seminar; participated in 

five conferences; chaired a session on health care simulation cases; organized two 

conference sessions; attended meetings at the US Dept of Health and Human Services 

Headquarters and at Johns Hopkins University Medical School; participated in the 

Nurse Work Environment Innovation Summit and the TATRC 7th annual Advanced 

Medical Technology Review. 

3) Prototype Simulations and Models. Developed a discrete event simulation model of a 

hospital emergency room in Promodel-Medmodel; collaborated with Dartmouth 

College on the Triage training software; and provided 3D Scanning support for the 

Surgical Devices project reported in Section 3.4. 

Impacts 

The most important impact of the project has been in educating the public on the need for 

standards to enable the more widespread use of simulation in the healthcare industry. 

There has been significant interest in a NIST-led activity to help establish data standards 

that would enable healthcare facilities to model and simulate their organizations. 

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Manufacturing Metrology and Standards for the Health Care Enterprise Program report 

4.4 Manufacturing and Value Chain Management 

Introduction and goals 

The worldwide revenue in the biomedical device and equipment market was $176.2 

billion in 2003 and was expected to grow 6.5% over the next three years. The medical 

device industry employs over 310,000 people. Approximately $62 billion worth of goods 

a year is traded. In 1996, a study entitled Efficiency Healthcare Consumer Response 

concluded that $11 billion was wasted annually because of healthcare supply chain 

inefficiency, such as inadequate quantities being shipped, supplies not reaching their 

destination, etc. Furthermore, competition and global economic pressures have led to 

consolidation in the medical equipment vendor community and the use of manufacturing 

outsourcing as a cost-containment measure. 

The goal of the project is to support the biomedical device industry in developing critical 

information and communication standards that will enable integrating and optimizing the 

value chain performance, ensuring product quality and safety, and providing the 

traceability of a medical device and its components throughout the device life cycle. 

Specifically, we participated in relevant standard development organizations to develop 

an XML schema of medical device manufacturing and e-commerce using semantic-based 

information modeling methods. 

Technical overview

We conducted a workshop to acquire industry and research needs on standards in 

manufacturing and value chain management in healthcare. Using this workshop results 

we plan to aid in the development of needed standards for supply chain management for 

medical and pharmaceutical products. The standards will enable robust e-business 

transactions and tracing and tracking of timely delivery. In the standard development 

process, available text-based e-commerce standards, ANSI, and ISO/IEC standards will 

be harmonized with the new standards. The standards will be tested at NIST and 

implemented by the partnering companies. Types of standard include business 

transaction, auto-identification, product specification (for regulation and auditing), 

process documentation and notification to FDA for regulation and auditing, and quality 

standards (for regulation and auditing). Tasks to complete these standards include: 

standards development, standards harmonization, conformance testing, semantic models, 

interaction protocol, and product/process identification repository service. Infrastructure 

research includes: dynamic representation and implementation of services, information 

models, interactions, terminologies, and business rules. A workshop is to be held to 

identify industry needs. 

Achievements 

Achievements included:

1) Surveyed industry needs on medical value chain management. The Institute of 

Medicine (IOM) reports medical errors result in approximately $29 billion in excess 

healthcare expenditures and lost productivity each year. The Efficient Healthcare 

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Manufacturing Metrology and Standards for the Health Care Enterprise Program report 

Consumer Response (EHCR), a broad-based industry effort to promote efficient 

practice in the healthcare supply chain, estimated there to be $11 billion in attainable 

savings annually by reducing medical errors with appropriate standards for using 

currently available information technology. Various other reports from the Medical 

Device and Diagnostic Industry (MDDI) also reports more than $6 billion can be save 

with appropriate information standards and technology to better buy products, track 

delivery, and monitor the use of medical devices in hospitals and clinics. 

2) Attended the Medical Design and Manufacturing Expositions. Interacted with stent, 

catheter, surgical tool, artificial hip/joint, diagnostic tool, and endoscope 

manufacturing company representatives. 

3) Conducted a symposium to study industry needs. The symposium was held in 

November 2006 in Minneapolis, organized with the University of Minnesota. Over 

100 persons attended from major medical device companies, their suppliers, 

governments, and universities. The symposium provided an open forum for industry, 

government, health providers, and academia to discuss technological and standards 

issues. Information and communication standards were identified as a critical 

component in the medical device industry for supporting supply chain optimization, 

tracing and tracking expensive medical devices, and ensuring product quality and 

safety. 

4) Contributed to the HIBCC (Health Industry Business Communications Council) in 

the development of a draft XML-based specification on selected e-business 

transaction messages commonly used in supply chains. Drafted XML schema 

documents on invoices and orders to support the HIBCC e-Business standards for 

healthcare supply chains. The XML schemas provide internet-based e-Business 

transactions that will free companies from transaction fees using the Value Added 

Network. Also, the World Wide Web Consortium (W3C) markup language provides 

defining interaction protocols and service descriptions and announcements. We also 

conducted a literature study on healthcare supply chain management. The standard 

suites studied include ANSI X.12, UN/EDIFACT, ebXML, and UBL. 

Impacts 

1) Expedited HIBCC’s transition from using EDI standard to XML-based standard. 

Since XML-based e-business standards are central to solve healthcare efficiency 

problems, the NIST involvement helped save heath care costs. Member HIBCC 

companies include John and John Healthcare, Cardinal Health, BD, Hospira, GHX, 

Henry Schein Inc., Abbott, and CR Bard. 

2) The medical device supply chain symposium held in Minneapolis provided a forum 

for medical device companies, government representatives, and academia to discuss 

critical supply chain management issues and look for opportunities for standard 

development and research. 

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Manufacturing Metrology and Standards for the Health Care Enterprise Program report 

4.5 Bioimaging 

Introduction and goals 

Medical imaging is a multibillion dollar industry and is making major strides into current 

medical diagnosis and therapy. The market in 2004 (source: Business Communications 

Co., Inc, www.bccresearch.com) for imaging equipment, picture archiving and 

communication systems, and computer-aided detection systems was $7.9 billion dollars 

with an average annual growth rate (AAGR) of 5.5%. According to this report “the 

fastest growing category of the imaging market consists not of imaging equipment, but of 

computer systems that are used as adjuncts to imaging equipment, which is expected to 

grow at a 14.9% AAGR.” Key technical barriers that are hampering progress in medical 

imaging are: 1) lack of standards for data collection and analysis across an array of 

different commercial imaging platforms including associated metadata; 2) lack of 

validated and robust software methods for measurement of change in computed extracted 

features such as tumor volume or other anatomical, functional or metabolic metrics, 3) 

inadequate physical performance standards and related image quality standards 

particularly for qualifying image attributes for measuring change; and 4) lack of technical 

interoperability standards for ensuring standard image rendering, related meta data, data 

storage and retrieval. 

To address the above barriers NIST has embarked on a bioimaging initiative as part of 

NIST’s American Competitive Initiative (ACI) program, which will continue beyond the 

conclusion of the MEL healthcare program. One of the components of the bioimaging 

initiative is “Standards and Validation for Software,” which is being undertaken by ITL 

(Information Technology Laboratory) and MEL. The goal of the MEL project is to 

improve the quality of image acquisition, analysis, and storage through effective 

standardization, improved software, and rigorous testing. We have been working closely 

with NIH (NCI, NIBIB and NCRR), Pharma, FDA, and other concerned government 

agencies and industry representatives such as NEMA to achieve our goals. The project is 

intended to support clinical decision making by highlighting deviations from normal 

conditions by image analysis of diseased organs and to suggest potential disease 

conditions. The intention is not to provide an automated diagnosis. While providing a 

general framework for building clinical decision support systems through image analysis, 

the initial project focuses on images captured through wireless endoscopy of the 

gastrointestinal system. The framework will then be extended to the lung cancer 

databases. 

Technical overview 

There are several stages to the image analysis project: 

1) Collect images with metadata that includes information about modality, spatial 

resolution, compression, and other attributes in a Health Insurance Portability and 

Accountability Act (HIPAA) format 

2) Develop a representation scheme for image ontologies 

3) Develop an image analysis program for extracting features and 

4) Test and validate. 

23 
Manufacturing Metrology and Standards for the Health Care Enterprise Program report 

The sequence of steps for Stage 3, starting from image analysis to identification of a 

diagnostic suggestion, is: 

1) Image segmentation. The partitioning of a digital image locates a set of regions that 

collectively cover the image. The pixels in a region are similar with respect to some 

visual properties, such as color, intensity or texture while adjacent regions are 

significantly different. The segmentation method and the feature selection described 

below are organ and modality specific. 

2) Feature vector computation. Sets of numbers are calculated respectively for each 

image region. These numbers, called features, describe a variety of region properties 

in numerical form. 

3) Mapping into disease ontology. Mapping is performed by comparing feature vectors 

with predefined vectors associated with specific nodes in the ontology representing 

disease conditions and vectors associated with normal conditions. 

4) Highlighting lesions. The region with feature vectors similar to the feature vectors of 

known lesions is highlighted so as to attract the attention of the physician. 

5) Diagnostic suggestion. If a given region is similar to a known lesion, a suggestion of 

a diagnosis can be provided to the physician. 

Testing and validation will be done by our industry affiliates at Texas Tech University 

Health Sciences Center and Asian Institute of Gastroenterology. 

Achievements 

Achievements include: 

1) A workshop was held at NIST in 2006 to determine the need to standardize imaging 

methods for data collection and data analysis in the context of drug or radiation 

therapy trials. The NIST meeting was a stakeholders meeting attended by 230+ 

scientists from academia, imaging and pharmaceutical companies, contract research 

and trade organizations, representatives from imaging societies, and agencies of the 

Federal Government. 

2) The image analysis experiment is being performed with video records from Wireless 

Capsule Endoscopy (WCE), a revolutionary technique which allows the visualization 

of the entire gastrointestinal (GI) tract. Our current project focuses on two aspects: 

discovering lesions and aiding in diagnosis. Our aim is not to replace a trained 

specialist but help him/her during the examination of the recorded video. The image 

segmentation and feature vector extraction components of the system are becoming 

mature and more robust. The disease mapping and diagnostic components are just 

beginning to take shape. 

Impacts 

The bioimaging workshop report has generated considerable interest in the radiology 

community. The Radiological Society of North America is planning on implementing 

some of the recommendations of the workshop. The image analysis work has elicited 

24 
Manufacturing Metrology and Standards for the Health Care Enterprise Program report 

25 

interest in applying the methodology to large databases of medical images such as the 

RIDER (Reference Image Database to Evaluate Response) project. 

5. Concluding comments 

The original goal of the program has been to apply proven MEL manufacturing 

technology and expertise to healthcare systems, biomedical devices and equipment, and 

biomedical data management. MEL provided a small amount of seed funding each year, 

with additional funding obtained from the Department of Health and Human Services and 

the American Competitiveness Initiative. We believe that the program was extremely 

successful in achieving its goals. Additionally, the knowledge gained in some of the 

projects, such as ADF, will allow us to develop similar frameworks in the manufacturing 

domain. 

Disclaimer: No approval or endorsement of any commercial product by the National 

Institute of Standards and Technology is intended or implied. Certain commercial 

equipments, instruments, or materials are identified in this report to facilitate better 

understanding. Such identification does not imply recommendations or endorsement by 

the National Institute of Standards and Technology nor does it imply the materials or 

equipment identified are necessarily the best available for the purpose. 
Manufacturing Metrology and Standards for the Health Care Enterprise Program report 

Appendix. Project participants and outputs (project leads are identified by PL) 

1. MEDICAL DEVICE PROJECTS 

Project 1.1 Mobility 

devices 

1.2 Hearing devices 1.3 Surface 

characterization of 

biomedical devices 

1.4 Intelligent 

assistive surgical 

devices 

Participants •Roger Bostelman (PL) 

• James Albus • U. of Pittsburgh • U. of Delaware • Florida Gulf 

Coast 

• Veterans 

Administration 

•Robotic 

Rehabilitation Resources 

● Victor Nedzelnitsky 

(PL) 

• Randall P. Wagner 

(PL) 

• Dept. of Veterans 

Affairs (VA) 

• Members of ANSI 

Accredited (ASA) Standards Committee S3 Bioacoustics and its Working Groups, especially S3/WG48 Hearing Aids 

• Theodore 

Vorburger (PL) 

• Alan Zheng • Lisa Pakstis • Joy Dunkers • Marcus Cicerone • Timothy Quinn 

•Nicholas 

Dagalakis (PL) 

•Yongsik Kim •Damien Bertot •Junhwan Kim •D. Sawyer •S. Phillips •Bruce Borchard •Dana 

Strawbridge 

•Marvin 

Kingsbury 

• • • • • • • 

Outputs 1) through 10) 33) through 40) 11) 12), 13) 1

26 
Manufacturing Metrology and Standards for the Health Care Enterprise Program report 

27 

2. HEALTHCARE INFORMATICS PROJECTS 

Project 2.1 Clinical 

informatics 

2.2 Bioinformatics 2.3 Enterprise 

modeling and 

simulation 

2.4 Manufacturing 

and value chain 

management 

2

Participants • Steven Fenves (PL) 

• E. Subrahmanian 

(PL) 

• Puja Goyal • Jean-Cyrus 

Angbo 

• Fauzi Daoud •Ram Sriram • ONCHIT 

• Ram Sriram 

(PL) 

• E. Subrahmanian • Antonio Cardone • Soo-Yong Shin • Penn. State U. 

• Charles McLean 

(PL) 

• Damien Bertot • Sanjay Jain • Tina Lee • Swee Leong • Guodong Shao • Benjamin Raverdy 

• Shaw Feng (PL) • U of. Minnesota 

•R• S• E• M• M• T• A

Outputs 25), 26) 27), 28) 29), 30), 31) 32) 
Manufacturing Metrology and Standards for the Health Care Enterprise Program report 

References 

1) Bostelman, R., Albus, J., “Survey of Patient Mobility and Lift Technologies Toward 

Advancements and Standards,” NISTIR 7384, National Institute of Standards and 

Technology, Gaithersburg, MD, 2006. 

2) Bostelman, R., Albus, J., “HLPR Chair – A Service Robot for the Healthcare 

Industry,” 3rd International Workshop on Advances in Service Robotics, Vienna, 

Austria, July 7, 2006. 

3) Bostelman, R., Russo, P., Albus, J., Hong., T., Madhavan, R., “Applications of a 3D 

Camera Towards Healthcare Mobility Aids,” IEEE International Conference on 

Networking, Sensing and Control, Ft. Lauderdale, FL, April 2006. 

4) Bostelman, R., Albus, J., Recent Developments of the HLPR Chair, International 

Conference on Rehabilitation Robotics (ICORR 2007), Noordwijk aan Zee, The 

Netherlands, June 13-15, 2007. 

5) Bostelman, R., J. Albus, J.,HLPR Chair: A Novel Indoor Mobility-Assist and Lift 

System, ASME 2007 International Design Engineering Technical Conferences & 

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6) Bostelman, R., Albus, J., A Novel Patient Mobility and Rehabilitation Robot, 

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11) Pakstis, L. M., Dunkers, J. P., Zheng, A., Vorburger, T., Quinn, T. and Cicerone, M., 

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Systems," PerMIS ’07, Gaithersburg, MD, August 28-30, 2007. 

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f) 

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Manufacturing Metrology and Standards for the Health Care Enterprise Program report 

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Nanotechnology 16 262, 2005. 

16) Chien, F.S., Hsieh, W.F., Gwo, Jun, J. S., Silver, R. M., Vladar, A. E. and Dagata, 

J.A., “Characterization of Prototype Silicon Pitch artifacts by Scanning Probe 

Oxidation and Anisotropic wet Etching,” J Vac. Sci. Technol. B, 23 66, 2005. 

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parallel writing on iron nitride thin films,” JVSTA 24 1340, 2006. 

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19) Pirollo, K. P., Dagata, J., Wang, P., Freedman, M., Vladar, A., Fricke, S., Ileva, L., 

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MRI detection of cancer,” Molecular Imaging 5 41, 2006. 

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Electrical and electromechanical phenomena at the nanoscale, (Springer, NY 2006) p. 

858. 

21) Pirollo, K. F., Rait, A., Zhou, Q., Hwang, S., Dagata, J. A., Zon, G., Hogrefe, R. I., 

Palchik, G. and Chang, E. H., “Materializing the potential of small interfering RNA 

via a tumor-targeting nanodelivery system,” Cancer Research 67 2938, 2007. 

22) Kuramochi H., Tokizaki T., Dagata J.A. and Yokoyama H., “Why nano-oxidation 

with carbon nanotube probes is so stable. I. Linkage between hydrophobicity and 

stability,” Nanotechnology 18 135703, 2007. 

23) Kuramochi H., Tokizaki T., Ando K., Yokoyama H. and Dagata J.A., “Why nanooxidation with carbon nanotube probes is so stable. II. Bending behaviour of CNT 

probes during nano-oxidation,” Nanotechnology 18 135704, 2007. 

24) Yu, W., Pirollo, K. F., Dagata, J. A. Rait, A., Yu, B., Huang, W. and Chang, E. H., 

“Structural differences between oligopeptides influence the biological activity of 

nanoimmunoliposome complexes,” submitted to Nucleic Acids Research. 

25) Bock, C., Carnahan, L., Fenves, S. J., Gruninger, M., Kashyap, V., Lide, B., Nell, J., 

Raman, R. and Sriram, R. D., “Healthcare Strategic Focus Area: Clinical Informatics, 

“NISTIR 7263, National Institute of Standards and Technology, Gaithersburg, MD, 

2005.

29 
Manufacturing Metrology and Standards for the Health Care Enterprise Program report 

26) Fenves, S. J., Subrahmanian, E., Goyal, P., Angbo, J.-C., Daoud, F. and Sriram, R. 

D., “The Architecture Development Facilitator (ADF): First year report,” NISTIR 

7411, National Institute of Standards and Technology, Gaithersburg, MD, 2007. 

27) Ravichandran, V. and Sriram, R.D., “Toward Data Standards for Proteomics,” 

Nature Biotechnology, Volume 23, Number 3, pages 373-376, March 2005. 

28) Shin, S-Y., Kim, S., Eom, J-H., Zhang, B-T. and Sriram, R.D., “Identifying ProteinProtein Interaction Sentences Using Boosting and Kernel Methods,” Second 

BioBreAtivE Challenge Workshop - Critical Assessment of Information Extraction in 

Molecular Biology, Madrid, Spain, 2007. 

29) Jain, S. and Mclean, C., “Simulation Applications in Health Care: A Survey of 

Recent Advances,” submitted for publication. 

30) Shao, G. and Lee, T., “Applying Software Product Line Technology to Simulation 

Modeling of Emergency Response Facility,” under review by Journal of Defense 

Modeling and Simulation. 

31) Jain, S., “Movement in emergency room of a hospital using the High Level 

Architecture IEEE 1516,” 2006 Winter Simulation Conference. 

32) Clarke, L. and Sriram, R.D., “Imaging as a Biomarker: Standards for Change 

Measurements in Therapy”, Proceedings of the United States Measurement System 

(USMS) Workshop, NIST, Gaithersburg, MD, September 14-15, 2006, 2007. 

Standards published by committees in w hich program members 

participated 

1) ANSI S3.35-2004 Method of Measurement of Performance Characteristics of 

Hearing Aids Under Simulated Real-Ear Working Conditions 

2) IEC 60118-13 (2004-11): Electroacoustics - Hearing aids - Part 13: Electromagnetic 

compatibility (EMC). 

3) IEC 60118-7 (2005-10): Electroacoustics – Hearing Aids – Part 7: Measurement of 

the performance characteristics of hearing aids for production, supply and delivery 

quality assurance purposes. 

4) IEC 60118-8 (2005-10): Electroacoustics – Hearing Aids – Part 8: Methods of 

measurement of performance characteristics of hearing aids under simulated [in situ] 

working conditions. 

5) IEC 60118-4 (2006-10): Electroacoustics - Hearing aids - Part 4: Induction loop 

systems for hearing aid purposes - Magnetic field strength. 

6) IEC 60645-5 (2004-11): Electroacoustics - Audiometric equipment - Part 5: 

Instruments for the measurement of aural acoustic impedance/admittance. 

7) IEC 60645-3 (2007-03): Electroacoustics - Audiometric equipment - Part 3: Test 

signals of short duration. 

30 
Manufacturing Metrology and Standards for the Health Care Enterprise Program report 

8) IEC 60318-5 (2006-08): Electroacoustics - Simulators of human head and ear - Part 

5: 2 cm3

 coupler for the measurement of hearing aids and earphones coupled to the 

ear by means of ear inserts. 

Acronyms 

AAGR Average Annual Growth Rate 

ACI American Competitive Initiative 

AD Alzheimer’s Disease 

ADF Architecture Development Facilitator 

AIG Asian Institute of Gastroenterology 

ANSI American National Standards Institute 

ASA Acoustical Society of America 

ASTM American Standards for Testing of Materials 

BD Becton, Dickinson and Company 

CAOS Computer Assisted Orthopedic Surgery 

CIP Cdk5 Inhibitor Protein 

DLS Dynamic Light Scattering 

DNA Deoxyribose Nucleic Acid 

E-A-R® A brand name for Aero Corp.’s foam insert ear plugs 

ebXML Electronic Business using eXtensible Markup Language 

EBM Evidence-Based Medicine 

EDI Electronic Data Interchange 

EHCR Efficient Healthcare Consumer Response 

EHR Electronic Health Record 

FDA Food and Drug Administration 

FIRST/FRODA Floppy Inclusions and Rigid Substructure Topography/ 

Framework Rigidity Optimized Dynamics Algorithm 

FY Fiscal Year 

GDP Gross Domestic Product 

GHX Global Healthcare Exchange 

GI Gastrointestinal 

GUMC Georgetown University Medical Center 

HHS Department of Health and Human Services 

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Manufacturing Metrology and Standards for the Health Care Enterprise Program report 

HIBCC Health Industry Business Communications Council 

HIPPA Health Insurance Portability and Accountability Act 

HJ-CAOHS Horizontal Joint-Computer Assisted Orthopedic Hip 

Surgery 

HLPR Home Lift, Position, and Rehab 

HMC Hershey Medical Center 

ICDR Interagency Committee on Disability Research 

ID Identification 

IEC International Electrotechnical Commission 

IOM Institute of Medicine 

ISD Intelligent Systems Division 

ISO/IEC International Organization for Standardization / 

International Electrotechnical Commission 

IT Information Technology 

ITL Information Technology Laboratory 

MDDI Medical Device and Diagnostic Industry 

MEL Manufacturing Engineering Laboratory 

MFM Magnetic Force Microscopy 

MRI Magnetic Resonance Imaging 

MSEL Material Science and Engineering Laboratory 

NCI National Cancer Institute 

NCL Nanotechnology Characterization Laboratory 

NCRR National Center for Research Resources 

NDS Nanoparticle Drug Delivery Systems 

NEMA National Electrical Manufacturers Association 

NHIN Nationwide Health Information Network 

NIBIB National Institute of Biomedical Imaging and 

Bioengineering 

NIST National Institute of Standards and Technology 

NIH National Institutes of Health 

NLS National Library Service 

OEM Original Equipment Manufacturer 

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Manufacturing Metrology and Standards for the Health Care Enterprise Program report 

33 

ONC Office of the National Coordinator for Health Information 

Technology 

ONCHIT Office of the National Coordinator for Health Information 

Technology 

PIE Protein Interaction information Extraction system 

PL Project Lead 

PPI Protein-Protein Interaction 

RIDER Reference Image Database to Evaluate Response 

SB Systems Biology 

SB&M Systems Biology and Medicine 

SE Systems Engineering 

SM Systems Medicine 

SPIO Super-Paramagnetic Iron-Oxide 

SPM Scanning Probe Microscopy 

SQUID Superconducting Quantum Interference Devices 

SVM Support Vector Machine 

TATRC Telemedicine and Advanced Technology Research Center 

UBL Universal Business Language 

UHS University Health Services 

UN/EDIFACT United Nations Directories for Electronic Data Interchange 

for Administration, Commerce, and Transport 

USMS United States Measurement System 

USNC/IEC United States National Committee of the International 

Electrotechnical Commission 

VA Veterans Affairs 

VCAT Visiting Committee on Advanced Technology 

W3C World Wide Web Consortium 

WCE Wireless Capsule Endoscopy 

XML Extensible Markup Language