Deep learning-enabled coronary CT angiography for plaque and stenosis quantification and cardiac risk prediction: an international multicentre study.

Journal: The Lancet. Digital health
Published Date: Apr 1, 2022

Abstract

BACKGROUND: Atherosclerotic plaque quantification from coronary CT angiography (CCTA) enables accurate assessment of coronary artery disease burden and prognosis. We sought to develop and validate a deep learning system for CCTA-derived measures of plaque volume and stenosis severity.

Authors

  • Andrew Lin
    Biomedical Imaging Research Institute, Cedars-Sinai Medical Center , Los Angeles, CA, USA.
  • Nipun Manral
    Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
  • Priscilla McElhinney
    Department of Biomedical Sciences, Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, 116 N Robertson Blvd, Los Angeles, CA 90048, USA.
  • Aditya Killekar
    Division of Artificial Intelligence, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
  • Hidenari Matsumoto
    Division of Cardiology, Showa University School of Medicine, Tokyo, Japan.
  • Jacek Kwiecinski
    Division of Artificial Intelligence in Medicine, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California.
  • Konrad Pieszko
    Department of Cardiology, Nowa Sól Multidisciplinary Hospital, Nowa Sól, Poland.
  • Aryabod Razipour
    Biomedical Imaging Research Institute (P.A.M., F.C., X.C., M.G., A.R., D.D.), Cedars-Sinai Medical Center, Los Angeles, CA.
  • Kajetan Grodecki
    Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California.
  • Caroline Park
    Institute of Medical Science, University of Toronto, Toronto, Canada; Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, Canada; Brain and Cognition Discovery Foundation, Toronto, Canada.
  • Yuka Otaki
    Department of Imaging, Medicine, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California.
  • Mhairi Doris
  • Alan C Kwan
    Department of Cardiology, Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA.
  • Donghee Han
    Division of Cardiology, Severance Cardiovascular Hospital, Yonsei University Health System, Seoul, Republic of Korea.
  • Keiichiro Kuronuma
    Department of Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, USA; Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
  • Guadalupe Flores Tomasino
    Department of Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, USA; Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
  • Evangelos Tzolos
    Division of Artificial Intelligence in Medicine, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California.
  • Aakash Shanbhag
    Division of Artificial Intelligence, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
  • Markus Goeller
    Biomedical Imaging Research Institute, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Taper building, A238, 8700 Beverly Blvd, Los Angeles, 90048, USA.
  • Mohamed Marwan
    Department of Cardiology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Ulmenweg 18, Erlangen, Germany.
  • Heidi Gransar
    Departments of Imaging, Medicine, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California.
  • Balaji K Tamarappoo
  • Sebastien Cadet
  • Stephan Achenbach
    Department of Cardiology, Friedrich-Alexander Universitat Erlangen-Nurnberg, Erlangen, Germany.
  • Stephen J Nicholls
    Monash Cardiovascular Research Centre, Victorian Heart Institute, Monash University, Melbourne, VIC, Australia; MonashHeart, Monash Health, Melbourne, VIC, Australia.
  • Dennis T Wong
    Monash Cardiovascular Research Centre, Victorian Heart Institute, Monash University, Melbourne, VIC, Australia; MonashHeart, Monash Health, Melbourne, VIC, Australia.
  • Daniel S Berman
    Departments of Imaging and Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
  • Marc Dweck
    British Heart Foundation Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK.
  • David E Newby
    Edinburgh Imaging Facility QMRI, Edinburgh, EH16 4TJ, UK; Centre for Cardiovascular Science, Edinburgh, EH16 4TJ, UK.
  • Michelle C Williams
    British Heart Foundation Centre for Cardiovascular Science, University of Edinburgh, Chancellor's Building, 49 Little France Cres, Edinburgh, UK.
  • Piotr J Slomka
    Department of Imaging, Medicine, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California Piotr.Slomka@cshs.org.
  • Damini Dey
    Departments of Imaging and Medicine, and Cedars-Sinai Heart Institute, Cedars-Sinai Medical Center, 8700 Beverly Blvd, Taper A238, Los Angeles, CA, 90048, USA.

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