ROADMAP FOR MEDICAL IMAGING

RESEARCH AND DEVELOPMENT

A Report by the

Interagency Working Group on Medical Imaging

Committee on Science

NATIONAL SCIENCE AND TECHNOLOGY COUNCIL

December 2017
INTERAGENCY WORKING GROUP ON MEDICAL IMAGING

Roadmap for Medical Imaging Research and Development ii

About the National Science and Technology Council

The National Science and Technology Council (NSTC) is the principal means by which the Executive 

Branch coordinates science and technology policy across the diverse entities that make up the Federal 

research and development enterprise. A primary objective of the NSTC is to ensure science and 

technology policy decisions and programs are consistent with the President's stated goals. The NSTC 

prepares research and development strategies that are coordinated across Federal agencies aimed 

at accomplishing multiple national goals. The work of the NSTC is organized under committees that 

oversee subcommittees and working groups focused on different aspects of science and technology. 

More information is available at http://www.whitehouse.gov/ostp/nstc.

About the Office of Science and Technology Policy

The Office of Science and Technology Policy (OSTP) was established by the National Science and 

Technology Policy, Organization, and Priorities Act of 1976 to provide the President and others within 

the Executive Office of the President with advice on the scientific, engineering, and technological 

aspects of the economy, national security, homeland security, health, foreign relations, the 

environment, and the technological recovery and use of resources, among other topics. OSTP leads 

interagency science and technology policy coordination efforts, assists the Office of Management and 

Budget with an annual review and analysis of Federal research and development in budgets, and 

serves as a source of scientific and technological analysis and judgment for the President with respect 

to major policies, plans, and programs of the Federal Government. More information is available at 

http://www.whitehouse.gov/ostp.

About the Interagency Working Group on Medical Imaging

The Interagency Working Group on Medical Imaging (IWGMI) under the NSTC Committee on Science

coordinates Federal investments in medical imaging research. Representatives from more than 

twelve departments and agencies participate in the IWGMI to enhance Federal efforts related to 

advancing research and improving fundamental understanding of medical imaging; accelerating 

technology advancement to combat disease; and supporting the development of a high-skilled 

workforce in medical imaging technologies.

About this Document 

This report is responsive to the Senate committee report accompanying the Departments of 

Commerce and Justice, Science, and Related Agencies Appropriations Bill, 2015, S. Rep. No. 113-181, 

at 104-105 (2014), directing OSTP, in cooperation with the National Institutes of Health as the lead 

agency, to develop a roadmap for the full scope of medical imaging research and development (R&D), 

including: basic science, technology, engineering, and math science and technology creation, medical 

and translational research, evidence generation, clinical implementation, workforce and training 

support, and export-oriented manufacturing incentives. This roadmap presents a snapshot of key

Federal R&D programs related to medical imaging, and provides a set of recommendations intended

to generate better value for patients, optimize health care outcomes, and reduce costs. 

Copyright Information

This document is a work of the United States Government and is in the public domain (see 17 U.S.C. 

§105). Subject to the stipulations below, it may be distributed and copied with acknowledgment to 

OSTP. Copyrights to graphics included in this document are reserved by the original copyright holders 

or their assignees and are used here under the government’s license and by permission. Requests to 

use any images must be made to the provider identified in the image credits or to OSTP if no provider 

is identified. Printed in the United States of America, 2017.
INTERAGENCY WORKING GROUP ON MEDICAL IMAGING

Roadmap for Medical Imaging Research and Development iii

NATIONAL SCIENCE & TECHNOLOGY COUNCIL

Chair

Ted Wackler, Deputy Chief of Staff and 

Assistant Director, OSTP

Staff

Chloe Kontos, Executive Director, NSTC

COMMITTEE ON SCIENCE

Co-Chairs

Francis S. Collins, Director, NIH

France A. Córdova, Director, NSF

Michael J. Kratsios, Deputy Assistant to the 

President, OSTP

OSTP Liaison

Lloyd J. Whitman, Assistant Director, OSTP

Executive Secretary

Sara Mazur, EPA

INTERAGENCY WORKING GROUP ON MEDICAL IMAGING

Co-Chairs

Roderic I. Pettigrew, NIH

Richard Cavanagh, NIST

Executive Secretary

Denis E. Bergeron, NIST

Editor

Michael J. Cheetham, NIH

Members

Todd Anderson, DOE

Peter Basser, NIH

James Brown, DOTreas

Jeff Buchsbaum, NIH

Sylvain Cardin, DOD

Angi Christensen, FBI

Janet Eary, NIH

Rachel Evans, NSF

Christine Farquharson, OMB

Lori Henderson, NIH

Sidney Hinds, DOD

Joseph Hutter, CMS

Paula Jacobs, NIH

Kris Kandarpa, NIH

Lisa Karam, NIST

Maren Laughlin, NIH

Gayle Lester, NIH

Shadi Mamaghani, NIH

Brandon Martin, DOD

Patrick Mason, DOD

Kyle Myers, FDA

Kate Nassauer, DOD

Robert Ochs, FDA

James Olds, NSF

Vinay Pai, NIH

Joshua Palotay, FBI

Mary Pastel, FDA

James Petro, DOD

Azhar Rafiq, NASA

Edward Ramos, NIH

Sohi Rastegar, NSF

Antonio Sastre, NIH

Lalitha Shankar, NIH

Jerry Sheehan, NIH

David Smith, FBI

Prem Srivastava, DOE

Bhadrasain Vikram, NIH

Brian Zimmerman, NIST
Table of Contents

Executive Summary ......................................................................................................................... 1

Summary of Recommendations....................................................................................................... 3

Advancing High-Value Imaging: A Roadmap for Medical Imaging Research and Development ...... 4

1. Standardize Image Acquisition and Storage ........................................................................... 5

Recommendation 1.1: Develop and promote adoption of standards for collecting, annotating, 

and archiving clinical imaging data. ........................................................................................ 6

Recommendation 1.2: Coordinate public and private efforts that combine, archive, and 

disseminate clinical data from multiple diagnostic studies....................................................... 6

Recommendation 1.3: Establish an infrastructure that will provide validation and quality 

assurance for clinical imaging data. ........................................................................................ 7

2. Apply Advanced Computation and Machine Learning to Medical Imaging ............................ 7

Recommendation 2.1: Support focused artificial intelligence research and development for 

applications in medical imaging. ............................................................................................. 8

Recommendation 2.2: Establish a public-private forum to coordinate efforts and interests in 

the artificial intelligence and medical imaging communities. ................................................... 9

Recommendation 2.3: Support the development of a diagnostic cockpit as both a clinical and 

research tool that integrates imaging data with other electronic medical data sets................. 9

3. Accelerate the Development and Translation of New, High-Value Imaging Techniques........ 9

Recommendation 3.1: Get to diagnosis more quickly and cost-effectively.............................. 11

Recommendation 3.2: Make high-value imaging techniques more accessible........................ 11

Recommendation 3.3: Conduct regular outreach efforts to increase dialogue among Federal, 

academic, clinical, and industrial stakeholders on their respective roles, evidence-based 

research, trial design, and clinical translation of high-value techniques. ................................ 12

4. Promote Best Practices in Medical Imaging.......................................................................... 12

Recommendation 4.1: Define methodologies that support dissemination of knowledge, 

competencies, and operational skills towards efficient use of innovative technologies........... 13

Recommendation 4.2: Employ cost-effective, accredited tools that promote wider engagement 

of practitioner populations. ................................................................................................... 13

Recommendation 4.3: Establish best training practices and priorities for educational 

institutions to prepare students for success in health care research and delivery. .................. 13

Conclusion ..................................................................................................................................... 14

List of Acronyms............................................................................................................................ 15
INTERAGENCY WORKING GROUP ON MEDICAL IMAGING

Roadmap for Medical Imaging Research and Development 1

Executive Summary

Medical imaging guides the course of much of patient care and is an essential element of 

biomedical research. From x-rays and ultrasound to computerized tomography (CT), functional 

magnetic resonance imaging (fMRI), and positron emission tomography (PET), medical imaging 

helps clinicians diagnose, treat, and understand a range of diseases and conditions, including 

cancer, cardiovascular disease, and neurodegenerative disorders.

The Federal government invests in medical imaging research and plays an important role in 

developing and deploying imaging technology that will help lengthen and improve the quality of 

American lives, open new areas of scientific discovery, and ensure the United States remain a global 

leader in medical innovation. The Interagency Working Group on Medical Imaging (IWGMI) 

coordinates these Federal investments and developed this roadmap for future medical imaging 

research and development (R&D) as required by the Senate committee report accompanying the 

Departments of Commerce and Justice, Science, and Related Agencies Appropriations Bill, 2015,S. 

Rep. No. 113-181, at 104-105 (2014).

1

The IWGMI has identified “advancing high-value imaging” as an overarching theme for efforts to 

achieve better health outcomes and smarter health care spending through medical imaging. It has 

identified four objectives that should guide future Federal R&D activities in order to generate better 

value for patients from medical imaging and to optimize health care outcomes and reduce costs.

1. Standardize image acquisition and storage. Uniform data acquisition and storage standards will 

allow the creation of curated, trustworthy imaging databases that enable medical imaging research 

to capitalize on advances in big data and data sharing. There is broad consensus that advances in 

medical research and care hinge on a large data ecosystem to collect and organize vast amounts of 

data from patient studies and basic research. To be useful, imaging data must be trustworthy, able 

to be queried in a logical and consistent way, and accessible to those with a legitimate need. The 

first step in ensuring these criteria are met is to coordinate the development and adoption of 

standard operating procedures for collecting, annotating, and archiving medical imaging data. The 

second step is to establish approaches for curating, storing, and providing access to medical imaging 

data that has been verified and validated.

2. Apply advanced computation and machine learning to medical imaging. Techniques such as 

artificial intelligence, machine learning, and deep learning offer considerable promise for medical 

imaging. Curated data sets can be used to develop and test algorithms for accurate and 

sophisticated machine-assisted analysis of images, identifying disease subtypes and correlations

with known genetic and metabolic pathways. These new analytic approaches can help identify 

relationships that a human observer alone might never discover, helping improve diagnosis and 

suggesting optimal interventions and likely drug targets. Imaging data can be organized and 

presented in conjunction with other patient data in a comprehensive diagnostic “cockpit”—a future 

digital interface for medical teams to facilitate optimal and tailored management of each patient.

3. Accelerate the development and translation of new, high-value imaging techniques. 

Streamlined medical imaging techniques can provide quicker diagnoses and lower health care costs. 

Future research should aim to develop imaging protocols that decrease time in the scanner and 

improve work flow. These new protocols can be combined with quality improvements and 

appropriate use criteria initiatives to better target diagnostic tests for patients. Appropriate use 

 1 https://www.congress.gov/113/crpt/srpt181/CRPT-113srpt181.pdf
INTERAGENCY WORKING GROUP ON MEDICAL IMAGING

Roadmap for Medical Imaging Research and Development 2

criteria assess whether advanced diagnostic imaging is indicated for a particular clinical scenario 

and, when it is, in what combination diagnostic tests should be performed.

Make high value imaging more accessible. Reducing the cost of medical imaging equipment and 

increasing its portability can increase patient access to imaging for research, diagnosis, and 

treatment, particularly at smaller clinics and research centers.

Accelerate the translation of new technologies into the marketplace. Greater collaboration and 

knowledge sharing among Federal agencies during the development of new medical imaging 

technologies could accelerate the evaluation and approval of high-value, innovative technologies 

and accelerate their translation from the laboratory to the marketplace—from the bench to the 

bedside, in medical parlance. Improved coordination among Federal bodies on their related health 

care missions may reveal new ways to best leverage limited resources.

4. Promote best practices in medical imaging. Technology is driving innovation in clinical decision 

support, but new imaging practices will require education and training so that health care

professionals employ value-driven approaches. Evolving analytical software systems and 

technologies for sharing medical imaging data will increase demand for new skills and training in 

the workforce. Priorities include disseminating knowledge about new imaging practices, developing 

competencies and operational skills for effective use of innovative technologies, and reorganizing 

workflows to improve the productivity of medical imaging operations as practices change.

These objectives provide a framework for prioritizing future medical imaging research and related 

Federal activities, as determined by the IWGMI based on information and perspectives gathered 

from the broad community of medical imaging stakeholders, including patient advocacy groups, 

academics, professional societies, industry, and government representatives.
INTERAGENCY WORKING GROUP ON MEDICAL IMAGING

Roadmap for Medical Imaging Research and Development 3

Summary of Recommendations

1. Standardize image acquisition and storage

1.1. Develop and promote adoption of standards for collecting, annotating, and archiving 

clinical imaging data.

1.2. Coordinate public and private efforts to combine, archive, and disseminate clinical data 

from multiple diagnostic studies. 

1.3. Establish an infrastructure that will provide validation and quality assurance for clinical 

imaging data.

2. Apply advanced computation and machine learning to medical imaging

2.1. Support focused artificial intelligence research and development for applications in medical 

imaging.

2.2. Establish a public-private forum to coordinate efforts and interests in the artificial 

intelligence and medical imaging communities. 

2.3. Support the development of a diagnostic cockpit as both a clinical and research tool that 

integrates imaging data with other electronic medical data sets. 

3. Accelerate the development and translation of new, high-value imaging techniques

3.1. Get to diagnosis more quickly and cost-effectively.

3.2. Make high-value imaging techniques more accessible.

3.3. Conduct regular outreach efforts to increase dialogue among Federal, academic, clinical, 

and industrial stakeholders on their respective roles, evidence-based research, trial design, 

and clinical translation of high-value techniques.

4. Promote best practices in medical imaging

4.1. Define methodologies that support dissemination of knowledge, competencies, and 

operational skills towards efficient use of innovative technologies. 

4.2. Employ cost-effective, accredited tools that promote wider engagement of practitioner 

populations.

4.3. Establish best training practices and priorities for educational institutions to prepare 

students for success in health care research and delivery.

Agency R&D Interests.

Agencies can collaboratively support recommendations that fall within their designated missions.

CMS DOD DOE FBI FDA NASA NIH NIST NSF

1.1 X X X

1.2 X X X X X X

1.3 X X

2.1 X X X X X X X

2.2 X X X X X X X

2.3 X X X X X X X X

3.1 X X X X X

3.2 X X X X X X

3.3 X X X X X X X X X

4.1 X X X

4.2 X X X

4.3 X X X X
INTERAGENCY WORKING GROUP ON MEDICAL IMAGING

Roadmap for Medical Imaging Research and Development 4

Advancing High-Value Imaging: A Roadmap for Medical Imaging Research and 

Development

Medical imaging guides the course of much patient care and is an essential element of biomedical 

research. With modalities ranging from x-rays and ultrasound to computerized tomography (CT), 

magnetic resonance imaging (MRI), single-photon emission computed tomography, and positron 

emission tomography (PET), medical imaging helps clinicians diagnose, treat, and understand a 

range of injuries, diseases, and conditions, including cancer, cardiovascular disease, musculoskeletal 

complaints, and neurodegenerative disorders. As a measure of scale, 79 million CT scans, 39 million 

MRI scans, and 1.7 million PET scans were performed in the United States in 2015.

2

The Federal government invests in medical imaging research and plays an important role in 

developing and deploying imaging technology to lengthen and improve the quality of American lives 

and to open new areas of scientific discovery. In response to the Senate committee report 

accompanying the Departments of Commerce and Justice, Science, and Related Agencies 

Appropriations Bill, 2015 [S. Rep. No. 113-181, at 104-105 (2014)],3 in 2015, the National Science 

and Technology Council (NSTC) established an Interagency Working Group on Medical Imaging

(IWGMI) co-chaired by the National Institutes of Health (NIH) National Institute of Biomedical 

Imaging and Bioengineering (NIBIB) and the Department of Commerce National Institute of 

Standards and Technology (NIST). 

The IWGMI coordinates Federal investments in medical imaging research and development (R&D) 

and developed this roadmap. In developing the roadmap, the IWGMI solicited individual input from 

a range of relevant stakeholders from scientific and professional societies, industry, academia, and 

patient advocacy groups, and identified several emerging themes in medical imaging.

The IWGMI has identified “advancing highvalue imaging” as the key theme for

achieving more efficient and effective health 

care, a greater impact on research, and 

better health outcomes. This theme is 

supported by four interlocking objectives 

that should guide Federal R&D: 1) 

standardize image acquisition and storage; 2) 

apply advanced computation and machine 

learning to medical imaging; 3) accelerate 

the development and translation of new, 

high-value imaging techniques; and 4) 

promote best practices in medical imaging.

These four interlocking objectives are the 

foundation for a concept and tool that can 

support both clinical practice and research: 

the “diagnostic cockpit.” The diagnostic 

cockpit is a future digital interface that 

would organize and simplify medical imaging 

results and help to interpret them in the 

context of related clinical data to support 

 2 http://stats.oecd.org/index.aspx?DataSetCode=HEALTH_STAT#

3 https://www.congress.gov/congressional-report/113th-congress/senate-report/181

Data

Standardization

Best Practices

in Imaging

High-Value Imaging

Techniques

Advanced Computation

& Machine Learning

Figure 1. Four Objectives for Advancing

High-Value Imaging
INTERAGENCY WORKING GROUP ON MEDICAL IMAGING

Roadmap for Medical Imaging Research and Development 5

early detection of disease, precision diagnosis, image-guided interventions, and improved

downstream clinical management of the patient.

Standardization of data acquisition and storage will make images more clinically usable and 

shareable across research and clinical care centers. Standardization will then focus the power of 

advanced computation on improving medical imaging. Application of artificial intelligence (AI) 

techniques, such as machine learning, will support more efficient and accurate diagnoses and assist 

clinicians and patients in shared decision-making by providing evidence-based, patient-specific 

recommendations. Improved interagency collaboration will accelerate the translation of advances 

in AI and other imaging and diagnostic technologies into clinical practice while maintaining high

standards for evaluation of technical efficacy and clinical utility, enabling innovations to contribute 

more rapidly to better patient care. Finally, getting better, faster, and cheaper imaging technologies 

to the patient requires the adoption of recognized best practices by care facilities and research 

laboratories across the country, which can be achieved through workforce education and is 

predicated on clinician buy-in and leadership.

1. Standardize Image Acquisition and Storage

Improved standardization of image acquisition is needed to assure the comparability of quantitative 

imaging data so that changes in a patient’s condition over time are measurable and comparable to 

observations from other patients. Standardization will allow imaging to better guide patient care 

and for medical images to potentially serve as “surrogate markers” to predict downstream patient 

health outcomes. This development in turn could reduce the duration, complexity, and cost of large 

clinical trials. Surrogate markers could similarly improve the efficiency of basic research which also 

relies heavily on medical imaging. 

Standardized data coding, storage, and retrieval will improve the portability of a patient’s health 

record and allow the creation of curated, trustworthy imaging databases that enable medical 

imaging research to leverage advances in big data and data sharing. Multiple NIH national health 

care activities, including the All of Us Research Program4 and key initiatives of the National Cancer 

Institute,

5 have identified the benefits of a large data ecosystem in which data from clinical and 

basic research along with real patient clinical data from electronic health records (EHRs) are 

aggregated, organized, and made accessible for both machine and human analysis. Inclusion of 

quantitative imaging data would strengthen both initiatives.

The first step to achieving standardization is to coordinate the development and adoption of 

standard operating procedures for collecting, annotating, and archiving medical imaging data. The 

second step is to establish approaches for federating, storing, querying, and providing reliable 

access to medical imaging data. In addition, the data must be verified, validated, and secure to 

assure users of their integrity (i.e., that the data is trustworthy and accurate). Steps must also be 

taken to protect the data to assure patients that their private data are properly anonymized and 

stored securely without risk of compromise. Ultimately, the imaging data should meet the FAIR 

principles of being Findable, Accessible, Interoperable, and Reusable.

6

 4 https://www.nih.gov/research-training/allofus-research-program 5 https://www.cancer.gov/research/key-initiatives/ 6 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4792175/
INTERAGENCY WORKING GROUP ON MEDICAL IMAGING

Roadmap for Medical Imaging Research and Development 6

Recommendation 1.1: Develop and promote adoption of standards for collecting, annotating, and 

archiving clinical imaging data.

Uniform procedures in image acquisition, incorporating accepted quality assurance and calibration 

protocols, will assure that imaging results are comparable from site-to-site, time-to-time, and 

patient-to-patient. Federal employees can play an important role in standards development and 

their participation should be encouraged consistent with Federal policy and agency priorities. For 

example, Federal employees have in the past worked with various bodies to develop guidelines and 

protocols for imaging studies that might serve as templates for further standardization of advanced 

imaging techniques, and current work at NIST aims to facilitate implementation of these guidelines 

by providing the measurement tools to demonstrate compliance. New and continued support of 

such activities should be encouraged, particularly in areas in which new technologies are entering 

clinical practice. Adoption of standard operating procedures (SOPs) for patient preparation, image 

acquisition, and data handling could be encouraged by funding agencies if studies that incorporate 

these activities were prioritized. Further, funding agencies should promote the clinical adoption of 

SOPs for the most common imaging procedures, including through outreach to professional 

societies. NIST and the NIH have experience in developing data standards and should work with 

external stakeholders to assure that the needs of the entire imaging community are met.

A consistent vocabulary with a standardized methodology is needed to interpret and annotate data.

As the central coordinating body for clinical terminology standards within the Department of Health 

and Human Services (HHS), the National Library of Medicine should work with stakeholders to

ensure the availability of a consistent vocabulary for annotating images. As the agency responsible 

for coordinating the development of documentary standards for data structure, transmission, and 

security, NIST should work to ensure that the annotated data sets are uniformly accessible.

Recommendation 1.2: Coordinate public and private efforts that combine, archive, and 

disseminate clinical data from multiple diagnostic studies. 

The integration of clinical data with imaging data for more patient-centric analytics aligns with the 

Office of the National Coordinator for Health Information Technology7 (ONC) initiative to ensure 

interoperability among digital health datasets maintained by health care organizations. The 

integration of various datasets should also include a definition of standards for usage and 

dissemination of lessons learned. Additionally, efforts to advance analysis of medical images could 

benefit from collaborations with national efforts to employ machine learning, such as Department 

of Energy (DOE) work to process large, complex datasets from experiments, simulations and 

observational facilities.

Federating existing medical imaging databases will promote innovation and provide a richer set of 

reference outcomes to guide patient care. The National Cancer Institute at NIH supports The Cancer 

Imaging Archive (TCIA),

8 a large archive of medical images of cancer accessible for public download, 

which could serve as a model for a federated medical imaging database. Under the All of Us 

research program, participants can share their EHR data through a pilot that leverages open 

standards to deliver data in a structured format with standardized vocabularies from disparate 

health records. This pilot could lend valuable expertise to efforts to federate imaging databases.

 7 https://www.healthit.gov/newsroom/about-onc 8 http://www.cancerimagingarchive.net/
INTERAGENCY WORKING GROUP ON MEDICAL IMAGING

Roadmap for Medical Imaging Research and Development 7

Refined standards for metadata and data formats are needed to enable cross-database 

communications and additional user resources. Tagging raw images could provide investigators 

with greater insight into the operational and situational conditions that generated the images.

Promoting coordination across Federal agencies and public entities could encourage barrier-free yet 

secure access to the data. Previous efforts like TCIA could provide valuable examples of how to 

balance the need for data encryption and access controls with ease of access for the user—

particularly while databases under development contain personal health information. An additional 

source of guidance from ONC is A Shared Nationwide Interoperability Roadmap9 developed to 

facilitate the secure, efficient, and effective sharing and use of electronic health information. 

Recommendation 1.3: Establish an infrastructure that will provide validation and quality 

assurance for clinical imaging data. 

For a federated database to be trusted (and therefore used), strict quality assurance and curation of 

the data are critical. Curation should include ensuring that reported quantities are traceable to 

appropriate national measurement standards and should verify the appropriateness and 

implementation of reconstruction and analysis methods. To support curation, encryption standards 

and digital and physical phantoms should be developed and adopted that meet the unique needs of 

clinical imaging data. New encryption standards are needed that enable easy access to the data and 

a mechanism to add additional patient-specific records to data sets (e.g., to correlate diagnostics, 

treatments, and outcomes), while simultaneously protecting the integrity of the data and hiding 

patient identities. Physical phantoms are objects with precisely known properties that can be 

scanned by an imaging device to test performance, accuracy, resolution, etc. They are needed to

provide the basis for comparison among datasets through traceability to national standards.

Similarly, digital phantoms are datasets with precisely known properties that that are needed to 

validate image analysis software and reconstruction/correction algorithms.

2. Apply Advanced Computation and Machine Learning to Medical Imaging

There is an opportunity to transform the current standard of medical care by applying artificial 

intelligence computational capacities such as machine learning and deep learning to the analysis of 

medical images. Curated data sets would serve as the basis for developing and testing algorithms 

for accurate and sophisticated machine-assisted analysis of images, correlation with disease 

subtypes, and linkage with genetic and metabolic pathways. These enhanced analytic capacities can 

help improve image acquisition and decision making toward diagnoses and suggest clinical 

interventions as well as drug treatment options. A diagnostic cockpit that combines imaging data in 

a digital interface with other patient data such as clinical, laboratory, and genomic findings would 

facilitate optimal and tailored management of each patient. Cumulatively, these computational 

processes will enhance clinical decision making and refine predictive analytics for wider support of 

health care delivery.

 9 https://www.healthit.gov/sites/default/files/hie-interoperability/nationwide-interoperability-roadmap-finalversion-1.0.pdf
INTERAGENCY WORKING GROUP ON MEDICAL IMAGING

Roadmap for Medical Imaging Research and Development 8

Figure 2. New Tools for Medical Imaging

The application of AI techniques to large, standardized databases is foundational for a concept the 

IWGMI enthusiastically supports: the diagnostic cockpit, a tool that would tie together diverse 

research efforts, timely data, and evidence-based approaches. Specifically, the medical imaging 

community must work with the medical informatics and clinical quality improvement and research 

communities to ensure that imaging is included in efforts to improve clinical decision support. 

Inside the cockpit, emerging and novel multi-parametric computational and analytical methods, 

including deep machine learning, both supervised and unsupervised, would scrutinize large, 

standardized databases that combine patient-specific and population-based clinical, laboratory, 

genomic, demographic, and quantitative imaging data. With targeted investment in R&D, the 

cockpit could become a valuable tool for both clinical and research applications.

For the clinician, the diagnostic cockpit would:

• Assist the physician interpreting the imaging scan, e.g., through quantitative image analysis;

• Integrate the current scan result with results of all prior patient imaging and diagnostic 

tests, known patient-specific clinical and demographic data, and population-based data;

• Update individual patient risks and health priorities in real time; 

• Present management options with probabilities grounded in evidence-based appropriate 

use criteria to better inform patient-doctor shared decision-making; and

• Prioritize and streamline the information presented to the physician in order to speed 

accurate diagnosis.

This next-generation clinical decision support would result in a “personalized,” evidence-based 

guideline, attuned to the needs and values of the individual patient at hand. 

In turn, researchers could employ this tool to efficiently generate numerous observational studies, 

which, through appropriate design and extremely large sample sizes, could approach the narrow 

confidence intervals and validity usually seen only in randomized controlled trials (RCTs). Although 

such studies would not render the RCT obsolete, they would have the advantage of stronger 

generalizability (the traditional weakness of RCTs). The strategies underlying the diagnostic cockpit, 

in both its clinical and research dimensions, apply to and could help accelerate national health care

activities such as All of Us and the key initiatives of the National Cancer Institute.

Recommendation 2.1: Support focused artificial intelligence research and development for 

applications in medical imaging.

AI technology is developing and maturing at a rapid pace. There have been considerable private 

investments in AI, with applications crossing many disciplines, including medicine. Still, strategically 

directed R&D funds could accelerate advances in AI that would directly support improved value in 

medical imaging. The relevant research efforts would also be furthered by the availability of 

federated databases (Recommendation 1.2) that could provide a wealth of past outcomes on which 

Human Input

Software Tools

AI

Machine

Learning

Deep

Learning
INTERAGENCY WORKING GROUP ON MEDICAL IMAGING

Roadmap for Medical Imaging Research and Development 9

to base predictions and prescriptions. In addition, participation of funding recipients in performance 

tests could help to benchmark progress and provide measured feedback on the current state-ofthe-art. Funding agencies will contribute to shaping the future of medical imaging applications

through support of the basic research needed to apply AI to image analysis. 

Recommendation 2.2: Establish a public-private forum to coordinate efforts and interests in the 

artificial intelligence and medical imaging communities.

Innovative algorithms are required that can integrate logic, evolution, statistics, and neural network 

frameworks, similar to human thought processes. A public-private forum is recommended to bring 

together relevant participants to align efforts to develop standards for interoperability and effective 

information exchange regarding patient records. Expertise in pattern recognition in images and in 

machine learning should be sought with the aim of bringing lessons learned in related fields to bear 

on the challenges faced in AI-assisted clinical decision support. The IWGMI has opened discussions 

with the NSTC Machine Learning/Artificial Intelligence subcommittee of the Committee on 

Technology to plan such a joint forum.

Recommendation 2.3: Support the development of a diagnostic cockpit as both a clinical and 

research tool that integrates imaging data with other electronic medical data sets.

The diagnostic cockpit would integrate diverse data feeds in a single digital interface to allow 

imaging data to be analyzed in the fullest contexts possible. To maintain the most comprehensive 

analyses, the diagnostic cockpit must flexibly accommodate and ultimately suggest new and 

innovative diagnostic strategies. Advances in reconstruction algorithms, for example, enabled by 

increased computational capacity can now reduce a 45 minute MRI of the brain involving multiple

types of scans to a few minutes without sacrificing quality or accuracy. This improvement is 

achieved by focusing on a few key scans and then shortening the image acquisition and processing 

times. For example, a 2014 study found that a condensed breast imaging protocol with 2 scans 

taking 3 minutes to acquire can be fully and accurately interpreted in 30 seconds.10 This approach 

compares favorably to a conventional breast MRI of 8 scans taking 30 minutes or longer to acquire 

and interpret. With similar examples in cardiac and brain imaging protocols, the potential clinical 

and economic impacts of efficient protocols are significant.

R&D into high-speed and highly efficient diagnostic protocols should be prioritized across multiple

Federal agencies. The development of appropriate reconstruction algorithms (tailored to judiciously 

streamlined scanning protocols) will be critical and will ultimately enable drastic acceleration of 

clinical workflows, resulting in more efficient and cost-effective health care. The ideal diagnostic 

cockpit will assist in the development of streamlined protocols by analyzing which data are and are 

not critical to diagnoses, making connections that the human observer alone might miss.

3. Accelerate the Development and Translation of New, High-Value Imaging Techniques

Greater collaboration and knowledge sharing among Federal agencies during the development of 

new medical imaging techniques could accelerate the evaluation and approval of high-value, 

innovative technologies and accelerate translation from laboratory to market—from bench to 

bedside, in medical parlance. Better communication among Federal agencies can facilitate 

awareness of new studies or ideas and clarity about which agency is cultivating those areas of 

expertise. Improved coordination among Federal bodies on their related health care missions may 

 10 https://www.ncbi.nlm.nih.gov/pubmed/24958821
INTERAGENCY WORKING GROUP ON MEDICAL IMAGING

Roadmap for Medical Imaging Research and Development 10

reveal new ways to best leverage limited resources. Harmonizing Federal efforts to promote 

innovation and facilitate clinical evaluation of emerging imaging products will make for a more 

efficient journey through the multiple regulatory processes and translation into clinical practice.

Ultimately, improved coordination should bring innovations to patients more quickly and at lower 

cost. 

Currently, much research is conducted without sufficient consideration of commercialization 

potential or reimbursement concerns. Academic and industrial investigators often submit research 

proposals to funding agencies such as the National Science Foundation (NSF), the Department of 

Defense (DOD), or NIH without knowing what clinical trial designs and outcomes may ultimately be 

needed for Food and Drug Administration (FDA) approval or Centers for Medicare & Medicaid 

Services (CMS) reimbursement. The relatively narrow requirements for a biomedical research grant 

can differ from the broader evidence required to make policy decisions about regulation or 

reimbursement. Better coordination and education among academic and industry investigators, 

science funding agencies, FDA, and CMS could remove some of the barriers that slow the 

translation of useful products (including imaging) into clinical practice by harmonizing the needs of 

biomedical scientific research with evidence-based policymaking. 

Figure 3. Select Federal Stakeholder Roles in Medical Imaging and Coordination Opportunities

To remove some of the barriers to translation, Federal agencies could better coordinate their 

different missions. Figure 3 highlights some of the opportunities for closer coordination among 

Federal agencies based on the overlapping roles they play in research and translation along the 

development pathway. The blue lines illustrate the R&D pathways from discovery through

commercialization, and red the regulatory pathways from standards development through

reimbursement, with the thickness of each line indicating the relative size of that agency’s role over 

time. The graphic illustrates that DOD, DOE, the National Aeronautics and Space Administration 

(NASA), NIH, and NSF all fund basic and early-stage applied research that often provides the 

scientific discoveries underlying new imaging technologies and therefore should be well 

coordinated. NIH funds basic and clinical research to improve human health while NIST is 

simultaneously developing the data and measurement infrastructure—methods and standards—

CMS

DOD

DOE

FBI

FDA

NASA

NIH

NIST

NSF

VA

Discovery Development Commercialization

Standards Development Regulatory Process Reimbursement
INTERAGENCY WORKING GROUP ON MEDICAL IMAGING

Roadmap for Medical Imaging Research and Development 11

that enable the future clinical evaluations. FDA regulates new imaging technologies and develops 

evaluation strategies through research to support regulatory decision-making. CMS and the 

Department of Veterans Affairs are primarily payers for medical products and services. Note that

FDA and CMS have different mandates reflecting different statutory authority making coordination 

key to successful translation of new imaging technologies. FDA thresholds are based on “safety and 

effectiveness,” with a focus on technical and analytical validity. In contrast, the CMS threshold is 

“reasonable and necessary,” with a focus on clinical utility that is supported by evidence in the

peer-reviewed medical literature.

Recommendation 3.1: Get to diagnosis more quickly and cost-effectively.

Streamlined medical imaging techniques can arrive at the right diagnosis more quickly, lowering 

health care costs. Future research should aim to develop imaging protocols that decrease time in 

the scanner and improve work flow. These new protocols may be combined with quality 

improvements and appropriate use criteria initiatives to better select optimal diagnostic tests for 

patients. Appropriate use criteria assess whether advanced diagnostic imaging is indicated for a 

particular clinical scenario and, when it is, in what combination diagnostic tests should be 

performed. These appropriate use criteria are embedded within the evidence-based, best practice 

care pathways that are incorporated and constantly improved inside the diagnostic cockpit.

Research dollars can be more effectively directed to establish best practices and criteria for the 

appropriate use of medical imaging.

Recommendation 3.2: Make high-value imaging techniques more accessible.

Reducing the cost of medical imaging equipment and 

increasing its portability can increase access to medical 

imaging for research, diagnosis, and treatment 

purposes. In particular, more affordable systems will 

increase patient access to medical imaging at smaller 

clinics and research centers. Lower cost point-of-care 

systems, designed for the battlefield or emergency 

use, have already proven valuable in extending care to 

underserved populations. DOD, NIBIB, NASA, and 

others support research portfolios to develop lowercost, lightweight MRI and portable ultrasound, an 

example of which is shown in Figure 4.11 The same 

agencies have supported efforts in telemedicine, 

leveraging modern networking technologies to make 

world-class diagnostic capabilities accessible in the 

most remote settings. The drive towards increased 

accessibility will make systems smaller, cheaper, 

faster, and potentially better diagnostic tools. 

 11 https://www.nibib.nih.gov/news-events/newsroom/pocket-sized-imaging-device-improves-accuracy-epiduralplacement

Figure 4. A new pocket-sized, ultrasound 

imaging device developed with NIH/NIBIB 

support will help doctors more safely and 

easily perform epidural blocks and spinal 

taps.
INTERAGENCY WORKING GROUP ON MEDICAL IMAGING

Roadmap for Medical Imaging Research and Development 12

Recommendation 3.3: Conduct regular outreach efforts to increase dialogue among Federal, 

academic, clinical, and industrial stakeholders on their respective roles, evidence-based research, 

trial design, and clinical translation of high-value techniques.

For newly developed technologies to have clinical impact, they must first navigate the regulatory 

and reimbursement approval processes. For recommendations 3.1 and 3.2 to ultimately improve 

the American health care system, the bench-to-bedside pipeline must be streamlined. The IWGMI 

has identified some areas where this goal can be achieved through improved interagency 

coordination, but a landscape analysis is needed to identify additional areas for improvement.

Some mechanisms for interagency coordination already exist (e.g., FDA-CMS parallel review), but a 

detailed analysis would assess where gaps exist or current programs could be bolstered. 

Mechanisms such as an existing memorandum of understanding (MOU) among agencies allows

experts to participate in discussions with manufacturers or other stakeholders during regulatory 

submissions when that adds value to the agencies or the private sector. For example, firms and/or 

CMS staff may benefit from CMS participation in FDA pre-submission discussions of a clinical trial 

for a new imaging product. Expanding on this concept, an MOU could be drafted to allow, for 

example, NSF, NIST, CMS, and FDA staff to participate in NIH concept or protocol reviews that build

on a technology developed through an NSF grant. NSF could help clarify technical points in the grant 

application while NIST, CMS, and FDA could advise on studies that, if funded and conducted as 

designed or with some modification, could support FDA approval and CMS policy in the same trial.

Collaboration can build on existing relationships, facilitating sharing of experts among agencies 

through, for example, interagency personnel exchanges or the HHS Entrepreneur-in-Residence 

program.12 The NSF-FDA Scholars-in-Residence program13 is another mechanism to heighten 

awareness of the regulatory process for academic innovators. An expansion of this program could 

increase the opportunities for medical imaging technology developers to gain access and expertise 

in regulatory and reimbursement pathways through on-site collaboration and training.

Federal agencies should encourage their subject matter experts to participate in outreach and 

collaborative activities to support specific technology development needs. For example, in 

telemedicine applications, NASA could play a central role. In image recognition, processing, and 

data mining, NASA, the Federal Bureau of Investigation, NIST, and other agencies have expertise to 

share. DOE capabilities in advanced computing and data handling are already being used to 

accelerate discovery in cancer research and DOE contributions to developing biomarkers are 

helping facilitate disease detection.

4. Promote Best Practices in Medical Imaging

As standards and advancing technologies drive new imaging practices through a streamlined 

translational pipeline, the impact on health care will depend on their adoption by clinical 

practitioners. Technology is driving innovation in clinical decision support, but new imaging 

practices will require education and training so that health care professionals can maximize value to 

achieve optimal health outcomes, knowing which types of imaging studies are most effective and 

clinically relevant in different circumstances. In addition, evolving analytic software systems and 

technologies for sharing medical imaging data will increase demand for new skills and training in

the workforce. Priorities include disseminating knowledge about new imaging practices, developing

 12 https://www.hhs.gov/idealab/eir-program/ 13 https://www.nsf.gov/funding/pgm_summ.jsp?pims_id=5605
INTERAGENCY WORKING GROUP ON MEDICAL IMAGING

Roadmap for Medical Imaging Research and Development 13

Figure 5. A New Paradigm in Medical Imaging

competencies and operational skills for effective use of innovative technologies, and reorganizing 

workflows to improve the productivity of medical imaging operations as practices change. In light of 

advances in medical imaging, a well-trained workforce is essential. Figure 5 illustrates a possible 

future for medical imaging.

Recommendation 4.1: Define methodologies that support dissemination of knowledge, 

competencies, and operational skills towards efficient use of innovative technologies.

Methodologies include, but are not be limited to, outreach programs to professional societies and 

user populations to increase knowledge and operational skills, inclusion of knowledge metrics for 

professional/academic accreditation, and inclusion of appropriate use criteria for health care

delivery reimbursement and research support. As clinical workflows evolve to leverage innovations 

in imaging, the roles of practitioners will undergo seismic shifts. Outreach, especially to professional 

societies, will be essential to promoting acceptance of the changing roles of researchers, 

imagers/technicians, and requesting physicians.

Recommendation 4.2: Employ cost-effective, accredited tools that promote wider engagement of 

practitioner populations. 

Evolving analytic software systems when applied to medical imaging, such as the recommended 

diagnostic cockpit and technologies for sharing medical image data, will increase demand for new 

skills and competencies in the workforce needed to effectively evaluate and utilize these new 

technologies. Professional societies can be an effective means of reaching the clinical community. 

Recipients of Federal research funds can also be encouraged to participate in continuing education 

programs, both as lecturers and as attendees. Similar participation by Federal employees with

research, standards, and regulatory backgrounds should also be prioritized.

Recommendation 4.3: Establish best training practices and priorities for educational institutions 

to prepare students for success in health care research and delivery.

Projections for workforce growth of radiology technologists and MRI technologists are 12 % and 

14 %, respectively, between 2016 and 2026.

14 This growth alone represents over 20,000 new jobs. 

The field of health information technicians is projected to add another 27,800 jobs during this time 

 14 https://www.bls.gov/ooh/healthcare/radiologic-technologists.htm#tab-6

Referral Scan Interpretation Next Steps

Current 

Practice

Driven by professional 

habit, time pressure, 

defensive medicine, 

networks

Lengthy techniques or 

imaging series

Qualitative: much 

information is 

discarded

Further imaging or 

surgical consultation

Future 

Possibility

Driven by evidencebased criteria for 

appropriate use 

Faster, high-value 

techniques with 

shorter targeted 

protocols

Quantitative 

assessments: 

analytical tools mine 

image data for more 

useful information

Reduced need for 

further imaging: more 

timely and precise 

diagnostics and 

treatment
INTERAGENCY WORKING GROUP ON MEDICAL IMAGING

Roadmap for Medical Imaging Research and Development 14

period.

15 Because workforce needs are changing rapidly with technology advances, these represent 

only a fraction of the new positions likely to be created.

Outreach to professional societies and institutes of higher education to establish best training 

practices and encourage their adoption should be prioritized. Diagnostic imaging technologists 

typically enter the field with an Associate’s degree,16 so it is critical to establish efficient 

communication with community colleges and professional societies to assure that the next 

generation of technologists are equipped with the diverse skill sets required by rapidly advancing 

medical imaging technologies.

Conclusion

To reach a goal of improved value in medical imaging research and practice, the IWGMI 

recommends adoption of standards for image acquisition and data handling, which will allow 

improved leveraging of advanced computation paradigms. Advances in artificial intelligence and 

deep machine learning will be critical to optimizing value and access to modern diagnostics. To 

improve translation of resulting innovations to clinical practice, the IWGMI recommends focused 

investment of research dollars and improved coordination among Federal agencies to streamline 

the bench-to-bedside pipeline. Finally, to assure full utilization of the most cost-efficient, highimpact innovations in medical imaging, the IWGMI recommends extensive outreach focused on 

promotion of best practices in imaging. In summary, the effective use of smaller, faster, and 

cheaper imaging technologies defines our vision for the future of medical research and practice. 

This document is intended to serve as a roadmap to guide and improve the coordination of Federal 

R&D efforts toward realizing this vision and ensuring America’s global leadership in medical 

innovation.

 15 https://www.bls.gov/ooh/Healthcare/Medical-records-and-health-information-technicians.htm 16 https://www.bls.gov/ooh/healthcare/diagnostic-medical-sonographers.htm
INTERAGENCY WORKING GROUP ON MEDICAL IMAGING

Roadmap for Medical Imaging Research and Development 15

List of Acronyms

AI artificial intelligence

CMS Centers for Medicare and Medicaid Services

CT computerized tomography

DOD Department of Defense

DOE Department of Energy

DOTreas Department of the Treasury

EHR electronic health record

EPA Environmental Protection Agency

FBI Federal Bureau of Investigation

FDA Food and Drug Administration

fMRI functional magnetic resonance imaging

HHS Department of Health and Human Services

IWGMI Interagency Working Group on Medical Imaging

MOU memorandum of understanding

MRI magnetic resonance imaging

NASA National Aeronautics and Space Administration

NIBIB National Institute of Biomedical Imaging and Bioengineering

NIH National Institutes of Health

NIST National Institute of Standards and Technology

NSF National Science Foundation

NSTC National Science and Technology Council

OMB Office of Management and Budget

ONC Office of the National Coordinator for Health Information Technology

OSTP Office of Science and Technology Policy

PET positron emission tomography

R&D research and development

RCT randomized controlled trial

SOP standard operating procedure

TCIA The Cancer Imaging Archive