A Cloud-Based System for Automated AI Image Analysis and Reporting.

Journal: Journal of imaging informatics in medicine
PMID: 39085717

Abstract

Although numerous AI algorithms have been published, the relatively small number of algorithms used clinically is partly due to the difficulty of implementing AI seamlessly into the clinical workflow for radiologists and for their healthcare enterprise. The authors developed an AI orchestrator to facilitate the deployment and use of AI tools in a large multi-site university healthcare system and used it to conduct opportunistic screening for hepatic steatosis. During the 60-day study period, 991 abdominal CTs were processed at multiple different physical locations with an average turnaround time of 2.8 min. Quality control images and AI results were fully integrated into the existing clinical workflow. All input into and output from the server was in standardized data formats. The authors describe the methodology in detail; this framework can be adapted to integrate any clinical AI algorithm.

Authors

  • Neil Chatterjee
    From the Departments of Bioengineering (M.S.Y.), Radiology (H.S., N.C., M.T.M., J.D., A.B., C.E.K., W.R.W., J.C.G.), Genetics (M.D.R.), and Medicine (D.R.), Perelman School of Medicine (A.C., M.S.Y., H.S., A.B., C.E.K., W.R.W., J.C.G.), University of Pennsylvania, 3400 Civic Center Blvd, Philadelphia, PA 19104; Department of Radiology, Loyola University Medical Center, Maywood, Ill (A.D.G.); Department of Information Services, University of Pennsylvania, Philadelphia, Pa (A.E.); and Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, Pa (A.B.).
  • Jeffrey Duda
    Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA.
  • James Gee
    Penn Image Computing and Science Laboratory, Department of Radiology, University of Pennsylvania, Philadelphia, PA.
  • Ameena Elahi
    From RAD-AID International, 8004 Ellingson Dr, Chevy Chase, MD 20815 (D.J.M., M.P.C., E.P., G.B., J.R.S., V.L.M., A.E., A.S., F.D.); Department of Radiology and Medical Imaging, Denver Health and Hospital Authority, Denver, Colo (E.P.); Departments of Radiology and Global Health, University of Washington, Seattle, Wash (J.R.S.); Fred Hutchinson Cancer Research Center, Seattle, Wash (J.R.S.); Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (V.L.M.); Department of Radiology, University of Pennsylvania Health System, Philadelphia, Pa (A.E.); and Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, Md (F.D.).
  • Kristen Martin
    Department of Information Services, University of Pennsylvania, Philadelphia, USA.
  • Van Doan
    Department of Information Services, University of Pennsylvania, Philadelphia, USA.
  • Hannah Liu
    Department of Bioengineering, University of Pennsylvania, Philadelphia, USA.
  • Matthew Maclean
    Department of Radiology, University of Pennsylvania, Philadelphia, USA.
  • Daniel Rader
    Department of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
  • Arijitt Borthakur
    Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
  • Charles Kahn
    Department of Radiology, University of Pennsylvania, Philadelphia, USA.
  • Hersh Sagreiya
    Perelman School of Medicine, University of Pennsylvania, Philadelphia 19104, USA.
  • Walter Witschey
    Department of Radiology, University of Pennsylvania, Philadelphia, USA.

Keywords

External Resources

Popular Topics
Recent Journals