Artificial intelligence in emergency neuroradiology: Current applications and perspectives.

Journal: Diagnostic and interventional imaging
Published Date: Dec 12, 2024

Abstract

Emergency neuroradiology provides rapid diagnostic decision-making and guidance for management for a wide range of acute conditions involving the brain, head and neck, and spine. This narrative review aims at providing an up-to-date discussion about the state of the art of applications of artificial intelligence in emergency neuroradiology, which have substantially expanded in depth and scope in the past few years. A detailed analysis of machine learning and deep learning algorithms in several tasks related to acute ischemic stroke involving various imaging modalities, including a description of existing commercial products, is provided. The applications of artificial intelligence in acute intracranial hemorrhage and other vascular pathologies such as intracranial aneurysm and arteriovenous malformation are discussed. Other areas of emergency neuroradiology including infection, fracture, cord compression, and pediatric imaging are further discussed in turn. Based on these discussions, this article offers insight into practical considerations regarding the applications of artificial intelligence in emergency neuroradiology, calling for more development driven by clinical needs, attention to pediatric neuroimaging, and analysis of real-world performance.

Authors

  • Bo Gong
    MD Undergraduate Program, University of British Columbia, Vancouver, British Columbia, Canada; Department of Radiology, Vancouver General Hospital, University of British Columbia, Vancouver, 899 12th Avenue West, British Columbia V5Z 1M9, Canada. Electronic address: bogong.ustc@gmail.com.
  • Farzad Khalvati
    Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada. farzad.khalvati@utoronto.ca.
  • Birgit B Ertl-Wagner
    From the Department of Radiology, University of Wisconsin Madison School of Medicine and Public Health, 600 Highland Dr, Madison, WI 53792 (D.A.B., M.L.S.); Department of Radiology, New York University, New York, NY (L.M.); Department of Musculoskeletal Radiology (M.A.B.) and Institute for Technology Assessment (E.F.H.), Massachusetts General Hospital, Boston, Mass; Department of Medical Imaging, Hospital for Sick Children, University of Toronto, Toronto, Canada (B.B.E.W.); Department of Radiology, University of California-San Diego, San Diego, Calif (K.J.F.); Department of Cancer Imaging, Division of Imaging Sciences & Biomedical Engineering, Kings College London, London, England (V.J.G.); Department of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, Calif (C.P.H.); and Department of Radiology and Radiologic Science, The Johns Hopkins University School of Medicine, Baltimore, Md (C.R.W.).
  • Michael N Patlas
    Department of Radiology, McMaster University, Hamilton, Ontario, Canada.

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