How does artificial intelligence in radiology improve efficiency and health outcomes?

Journal: Pediatric radiology
Published Date: Jun 12, 2021

Abstract

Since the introduction of artificial intelligence (AI) in radiology, the promise has been that it will improve health care and reduce costs. Has AI been able to fulfill that promise? We describe six clinical objectives that can be supported by AI: a more efficient workflow, shortened reading time, a reduction of dose and contrast agents, earlier detection of disease, improved diagnostic accuracy and more personalized diagnostics. We provide examples of use cases including the available scientific evidence for its impact based on a hierarchical model of efficacy. We conclude that the market is still maturing and little is known about the contribution of AI to clinical practice. More real-world monitoring of AI in clinical practice is expected to aid in determining the value of AI and making informed decisions on development, procurement and reimbursement.

Authors

  • Kicky G van Leeuwen
    Department of Medical Imaging, Radboud university medical center, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands. kicky.vanleeuwen@radboudumc.nl.
  • Maarten de Rooij
    Department of Medical Imaging, Radboud university medical center, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands.
  • Steven Schalekamp
    From the Diagnostic Image Analysis Group, Radboud University Medical Center, Geert Groteplein 10, Nijmegen 6500 HB, the Netherlands (K.M., E.T.S., S.S., C.M.S., B.v.G.); Department of Radiology, Bernhoven Hospital, Uden, the Netherlands (H.S.); Department of Radiology, Jeroen Bosch Hospital, 's-Hertogenbosch, the Netherlands (A.J.G.K., M.B.J.M.K., T.S., M.R.); Department of Radiology, Meander Medisch Centrum, Amersfoort, the Netherlands (C.M.S.); and Thirona, Nijmegen, the Netherlands (R.H.H.M.P., A.M., J.M.).
  • Bram van Ginneken
    Diagnostic Image Analysis Group, Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands; Fraunhofer Mevis, Bremen, Germany.
  • Matthieu J C M Rutten
    Department of Medical Imaging, Radboud university medical center, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands.

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