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The American College of Radiology Data Science Institute™ is collaborating with radiology professionals, industry leaders, government agencies, patients, and other stakeholders to facilitate the development and implementation of artificial intelligence (AI) applications that will help radiology professionals provide improved medical care.

ACR DSI is developing a framework for implementation of machine learning in the radiological professions that:

  • Defines clinically relevant use cases for the development of AI algorithms in medical imaging, interventional radiology, and radiation oncology
  • Establishes a methodology and provides tools and metrics for creating algorithm training, testing, and validation data sets around these use cases
  • Develops standardized pathways for implementing AI algorithms in clinical practice
  • Creates opportunities for monitoring the effectiveness of AI algorithms in clinical practice
  • Addresses the regulatory, legal, and ethical issues associated with AI in medical imaging, interventional radiology, and radiation oncology

ACR DSI Mission

ACR DSI empowers the advancement, validation, and implementation of artificial intelligence (AI) in medical imaging for the benefit of our patients, society, and the radiological professions. Its mission is to:

Leverage the value of radiology professionals through clinically relevant use case development and clinical workflow integration as AI evolves

Ensure patient safety through algorithm validation and by advising government agencies, such as the FDA, to enhance the regulatory approval process in ways that benefit and protect patients

Establish industry relationships by defining clinically valuable use cases, working with the FDA and other agencies to develop an effective regulatory process for algorithm approval, and creating pathways to integrate AI models into the clinical workflow

Educate radiology professionals and other stakeholders about artificial intelligence and the ACR’s role in data science for the good of our patients

Read the ACR DSI Strategic Plan

ACR DSI Leadership

Bibb Allen

Bibb Allen Jr., MD, FACR

ACR DSI Chief Medical Officer
Keith J. Dreyer

Keith J. Dreyer, DO, PhD, FACR

ACR DSI Chief Science Officer
Laura Coombs

Laura Coombs, PhD

ACR Senior Director of Informatics
Mike Tilkin

Mike Tilkin

ACR Executive Vice President and Chief Information Officer

ACR AI Advisory Group

Geraldine B. McGinty, MD, MBA, FACR, vice chair of the ACR Board of Chancellors, chairs the ACR AI Advisory Group. The group convenes representatives of various stakeholder contingents within the radiological professions to ensure ACR DSI and other College initiatives around AI are supported by and supportive of the membership. The group brings together voices from radiology’s diverse membership communities, including physicians in both private and academic settings, members in training, young physicians, radiation oncologists and physicists, and physicians in small and rural practices, ensuring that the value each contingent delivers has been recognized and included in the discussion. Representing a broad spectrum of members in this way maintains ACR’s position as a credible voice in advocating for our patients and helps radiologists embrace their roles as stewards of AI and other advanced tools that may augment our practice. The group also includes representatives from three ACR commissions: the Commission for Women and Diversity, the Commission on Quality and Safety, and the Commission on Economics. Patient members from the Informatics Committee of the Commission on Patient- and Family-Centered Care are also being recruited to ensure that the needs of our patients are fully considered as AI evolves. ACR AI Advisory Group members include:

  • Geraldine B. McGinty, MD, MBA, FACR, Chair, New York, NY
  • Timothy L. Swan, MD, FACR, Marshfield, WI
  • Jennifer E. Nathan, MD, Great Falls, VA
  • Nathan M. Cross, MD, MS, Seattle, WA
  • Judy W. Gichoya, MD, Indianapolis, IN
  • Katarzyna J. Macura, MD, PhD, Catonsville, MD
  • Ezequiel Silva III, MD, FACR, San Antonio, TX
  • Richard L. Morin, PhD, FACR, Jacksonville, FL
  • Michael A. Bruno, MD, FACR, Hershey, PA
  • Shawn Teague, MD, FACR, Denver, CO
  • Daniel P. Barboriak, MD, Durham, NC
  • Alan D. Kaye, MD, FACR, Bridgeport, CT
  • Bruce J. Hillman, MD, FACR, Wake Forest, NC
  • H. Benjamin Harvey, MD, JD, Boston, MA
  • Reid F. Thompson, MD, PhD, Portland, OR
  • Robert S. Pyatt Jr., MD, FACR, Chambersburg, PA
  • Christoph Wald, PhD, MBA, FACR, Nahant, MA
  • Amanda Itliong, EdM, Detroit, MI
  • Stephen H. Hobbs, PhD, Augusta, GA

ACR DSI Senior Scientists

ACR DSI Senior Scientists make up a council of physicians, medical physicists, data scientists, and software engineers selected to provide expert support for the activities of the institute. ACR DSI Senior Scientists use their experience and skills in the areas of data science, framework, terminology, methodology, and clinical integration to guide AI use case development for the radiological sciences. ACR DSI Senior Scientists also serve as institute ambassadors to promote collaborations with other professional organizations, industry, governmental agencies, and patient groups around the safe and effective implementation of AI in ways that augment patient care. ACR DSI Senior Scientists are leading educational efforts that broaden the understanding of AI in the radiological sciences for physicians, other healthcare providers, regulatory agencies, and industry. ACR DSI Senior Scientists, collaborating with the ACR Research and Innovation Center, promote the use of AI in clinical and health services research and population health management, and they ensure AI is developed and implemented with the diversity of our patient population in mind and that algorithms are effective for all population demographics and free of unconscious bias in their development. ACR DSI Senior Scientists are:

  • Tarik Alkasab, MD, Boston, MA
  • Chris L. Sistrom, MD, MPH, PhD, Gainesville, FL
  • Neil Tenenholtz, PhD, Boston, MA
  • C. Matthew Hawkins, MD, Atlanta, GA
  • J. Raymond Geis, MD, FACR, Fort Collins, CO
  • Mark H. Michalski, MD, Boston, MA
  • Katherine P. Andriole, PhD, Boston, MA
  • Adam E. Flanders, MD, Philadelphia, PA
  • Garry Choy, MD, Sunnyvale, CA
  • Curtiland Deville Jr, MD, Baltimore, MD
  • Gregory Nicola, MD, Hackensack, NJ

ACR DSI Proof Of Concept Panel Chairs

ACR DSI is developing a series of “Proof of Concept” cases to illustrate its AI use case development strategy. ACR DSI has chosen four topics that illustrate how ACR DSI Use Cases will look, with data elements for training algorithms, testing algorithms, validating algorithms, and deploying and monitoring algorithms in clinical practice. These topics are: 1) Determination of pediatric bone age, 2) Population of the TBI-RADS Reporting Structure in patients with head injuries, 3) Population of the LI-RADS Reporting Structure for characterization of liver lesions, and 4) Population of the Lung-RADS Reporting Structure in patients undergoing lung cancer screening. In addition to serving as examples of how AI can positively impact important areas of radiologic practice, these use cases provide the basis and technical framework for the refinement of ACR DSI’s use case development platform, TOUCH-AI, and the development of a wide array of ACR DSI Use Cases that will become ACR Assist modules. Current ACR DSI Proof of Concept Workgroup chairs are:

  • C. Matthew Hawkins, MD, Atlanta, GA
  • Alexander M. Norbash, MD, FACR, San Diego, CA
  • Arun Krishnaraj, MD, MPH, Charlottesville, VA

ACR DSI Data Science Subspecialty Panel Chairs

Panels of professionals with both clinical expertise and background in informatics and data science are developing an array of ACR DSI Use Cases. These panels primarily focus on the clinical areas of pediatric radiology, neuroradiology, musculoskeletal radiology, abdominal radiology, thoracic cardiology, cardiac radiology, interventional radiology, and breast radiology. Additionally, they focus on oncology (including radiation oncology) and quality and safety (including areas related to medical physics, exam protocols, and radiation exposure.) Current Data Science Subspecialty Panel Chairs are:

  • C. Matthew Hawkins, MD, Atlanta, GA
  • Alexander M. Norbash, MD, FACR, San Diego, CA
  • Jay W. Patti, MD, Charlotte, NC
  • Arun Krishnaraj, MD, MPH, Charlottesville, VA
  • Eric J. Stern, MD, FACR, Seattle, WA
  • Carlo De Cecco, MD, Charleston, SC
  • Reid F. Thompson, MD, PhD, Portland, OR
  • Elizabeth Burnside, MD, MPH, FACR, Madison, WI
  • Edward Lee, MD, PhD, Santa Monica, CA
  • Jonathan Kruskal, MD, PhD, FSAR, Boston, MA