Current imaging of PE and emerging techniques: is there a role for artificial intelligence?

Journal: Clinical imaging
Published Date: May 10, 2022

Abstract

Acute pulmonary embolism (PE) is a critical, potentially life-threatening finding on contrast-enhanced cross-sectional chest imaging. Timely and accurate diagnosis of thrombus acuity and extent directly influences patient management, and outcomes. Technical and interpretive pitfalls may present challenges to the radiologist, and by extension, pose nuance in the development and integration of artificial intelligence support tools. This review delineates imaging considerations for diagnosis of acute PE, and rationale, hurdles and applications of artificial intelligence for the PE task.

Authors

  • Lea Azour
    Department of Radiology, NYU Grossman School of Medicine, NYU Langone Health, New York, NY, United States of America. Electronic address: Lea.Azour@nyulangone.org.
  • Jane P Ko
    Department of Radiology (M.K., W.M., K.F., J.S.B., G.M., J.P.K.), Department of Medicine, Division of Hematology and Medical Oncology, Laura and Isaac Perlmutter Cancer Center (D.K.), and Center for Healthcare Innovation and Delivery Science (L.I.H.), NYU Langone Health, 550 First Ave, New York, NY 10016; Division of Healthcare Delivery Science, Department of Population Health and Division of General Internal Medicine and Clinical Innovation, Department of Medicine, NYU Grossman School of Medicine, New York, NY (L.I.H.); and Garden State Urology, Wayne, NJ (A.K.).
  • Danielle Toussie
    Department of Radiology, NYU Grossman School of Medicine, NYU Langone Health, New York, NY, United States of America.
  • Geraldine Villasana Gomez
    Department of Radiology, NYU Grossman School of Medicine, NYU Langone Health, New York, NY, United States of America.
  • William H Moore
    Department of Radiology, NYU Langone Health, New York, New York.

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