A deep learning approach versus expert clinician panel in the classification of posterior circulation infarction.

Journal: NeuroImage. Clinical
PMID:

Abstract

BACKGROUND: Posterior circulation infarction (POCI) is common. Imaging techniques such as non-contrast-CT (NCCT) and diffusion-weighted-magnetic-resonance-imaging commonly fail to detect hyperacute POCI. Studies suggest expert inspection of Computed Tomography Perfusion (CTP) improves diagnosis of POCI. In many settings, there is limited access to specialist expertise. Deep-learning has been successfully applied to automate imaging interpretation. This study aimed to develop and validate a deep-learning approach for the classification of POCI using CTP.

Authors

  • Leon S Edwards
    Department of Neurology and Neurophysiology, Liverpool Hospital, Sydney, NSW, Australia; South Western Sydney Clinical School, University of New South Wales, Sydney, NSW, Australia; Ingham Institute for Applied Medical Research, Sydney, NSW, Australia. Electronic address: Leon.Edwards@health.nsw.gov.au.
  • Milanka Visser
    Melbourne Brain Centre at the Royal Melbourne Hospital, University of Melbourne, Parkville, Australia.
  • Cecilia Cappelen-Smith
    Department of Neurology and Neurophysiology, Liverpool Hospital, Sydney, NSW, Australia; South Western Sydney Clinical School, University of New South Wales, Sydney, NSW, Australia; Ingham Institute for Applied Medical Research, Sydney, NSW, Australia.
  • Dennis Cordato
    Department of Neurology and Neurophysiology, Liverpool Hospital, Sydney, NSW, Australia; South Western Sydney Clinical School, University of New South Wales, Sydney, NSW, Australia; Ingham Institute for Applied Medical Research, Sydney, NSW, Australia.
  • Andrew Bivard
    Faculty of Health and Medicine, University of Newcastle, Callaghan, Australia.
  • Leonid Churilov
    Florey Institute of Neuroscience and Mental Health, University of Melbourne, Victoria, Australia.
  • Christopher Blair
    South Western Sydney Clinical School, University of New South Wales, Sydney, NSW, Australia; Ingham Institute for Applied Medical Research, Sydney, NSW, Australia.
  • James Thomas
    EPPI-Centre, Social Research Institute, University College London, London, England, UK.
  • Angela Dos Santos
    South Western Sydney Clinical School, University of New South Wales, Sydney, NSW, Australia.
  • Longting Lin
    Department of Neurology and Neurophysiology, Liverpool Hospital, Sydney, NSW, Australia; South Western Sydney Clinical School, University of New South Wales, Sydney, NSW, Australia.
  • Chushuang Chen
    Melbourne Brain Centre at the Royal Melbourne Hospital, University of Melbourne, Parkville, Australia.
  • Carlos Garcia-Esperon
    Department of Neurology, John Hunter Hospital, Newcastle, NSW, Australia; Hunter Medical Research Institute and University of Newcastle, Newcastle, NSW, Australia.
  • Kenneth Butcher
    Prince of Wales Clinical School, University of New South Wales, Sydney, NSW, Australia.
  • Tim Kleinig
    Department of Neurology, Royal Adelaide Hospital, Adelaide, SA, Australia.
  • Phillip Mc Choi
    Department of Neurosciences, Box Hill Hospital, Eastern Health Clinical School, Monash University, Melbourne, VIC, Australia.
  • Xin Cheng
    International Joint Laboratory for Embryonic Development & Prenatal Medicine Division of Histology and Embryology School of Medicine Jinan University Guangzhou China.
  • Qiang Dong
    Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China.
  • Richard I Aviv
    Department of Radiology and Medical Imaging, University of Ottawa, Ottawa, Canada.
  • Mark W Parsons
    5 Department of Neurology, John Hunter Hospital, University of Newcastle, Newcastle, NSW, Australia.