Diagnostic test accuracy study of a commercially available deep learning algorithm for ischemic lesion detection on brain MRIs in suspected stroke patients from a non-comprehensive stroke center.

Journal: European journal of radiology
PMID:

Abstract

PURPOSE: To estimate the ability of a commercially available artificial intelligence (AI) tool to detect acute brain ischemia on Magnetic Resonance Imaging (MRI), compared to an experienced neuroradiologist.

Authors

  • Christian H Krag
    Department of Radiology, Herlev and Gentofte Hospital, Herlev, Denmark; Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark. Electronic address: christian.hedeager.krag.01@regionh.dk.
  • Felix C Müller
    Department of Radiology, Herlev and Gentofte Hospital, Herlev, Denmark. Electronic address: christoph.felix.mueller@regionh.dk.
  • Karen L Gandrup
    Department of Radiology, Herlev and Gentofte Hospital, Herlev, Denmark.
  • Henriette Raaschou
    Department of Radiology, Herlev and Gentofte Hospital, Herlev, Denmark.
  • Michael B Andersen
    From the Department of Radiology, Herlev and Gentofte Hospital, Borgmester Ib Juuls vej 1, 2730 Herlev, Copenhagen, Denmark (L.L.P., F.C.M., L.C.L., M.B.A.); Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark (L.L.P., O.W.N., M.B., M.B.A.); Radiological Artificial Intelligence Testcenter, RAIT.dk, Capital region of Denmark (L.L.P., F.C.M., J.D.N., M.B., M.B.A.); Department of Radiology, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark (J.D.N., M.B.); Department of Radiology, Aarhus University Hospital, Aarhus, Denmark (F.R.); and Department of Cardiology, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark (O.W.N.).
  • Mathias W Brejnebøl
    Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark; Department of Radiology, Bispebjerg and Frederiksberg Hospital, Frederiksberg, Denmark.
  • Malini V Sagar
    Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark; Department of Neurology, Herlev and Gentofte Hospital, Herlev, Denmark.
  • Jonas A Bojsen
    Department of Radiology, Odense University Hospital, Odense, Denmark.
  • Benjamin S Rasmussen
    Department of Radiology, Odense University Hospital, Odense, Denmark.
  • Ole Graumann
  • Mads Nielsen
    Department of Computer Science, University of Copenhagen, Copenhagen Ø DK-2100, Denmark; Biomediq A/S, Copenhagen Ø DK-2100, Denmark.
  • Christina Kruuse
    Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark; Department of Neurology, Herlev and Gentofte Hospital, Herlev, Denmark.
  • Mikael Boesen
    From the Department of Radiology, Herlev and Gentofte Hospital, Borgmester Ib Juuls vej 1, 2730 Herlev, Copenhagen, Denmark (L.L.P., F.C.M., L.C.L., M.B.A.); Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark (L.L.P., O.W.N., M.B., M.B.A.); Radiological Artificial Intelligence Testcenter, RAIT.dk, Capital region of Denmark (L.L.P., F.C.M., J.D.N., M.B., M.B.A.); Department of Radiology, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark (J.D.N., M.B.); Department of Radiology, Aarhus University Hospital, Aarhus, Denmark (F.R.); and Department of Cardiology, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark (O.W.N.).