Prediction of lung cancer risk at follow-up screening with low-dose CT: a training and validation study of a deep learning method.

Journal: The Lancet. Digital health
PMID: 32864596

Abstract

BACKGROUND: Current lung cancer screening guidelines use mean diameter, volume or density of the largest lung nodule in the prior computed tomography (CT) or appearance of new nodule to determine the timing of the next CT. We aimed at developing a more accurate screening protocol by estimating the 3-year lung cancer risk after two screening CTs using deep machine learning (ML) of radiologist CT reading and other universally available clinical information.

Authors

  • Peng Huang
    College of Food Science, Sichuan Agricultural University, Ya'an 625014, China.
  • Cheng T Lin
    Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA.
  • Yuliang Li
    Department of Applied Mathematics & Statistics, Johns Hopkins University, Baltimore, Maryland, USA.
  • Martin C Tammemagi
    Department of Community Health Sciences, Brock University, St. Catharines, Ontario, Canada.
  • Malcolm V Brock
    Department of Surgery, Johns Hopkins University, Baltimore, Maryland, USA.
  • Sukhinder Atkar-Khattra
    British Columbia Cancer Agency, Vancouver, British Columbia, Canada.
  • Yanxun Xu
    Department of Applied Mathematics & Statistics, Johns Hopkins University, Baltimore, Maryland, USA.
  • Ping Hu
    Division of Cancer Prevention, National Cancer Institute, Canada.
  • John R Mayo
    University of British Columbia and Vancouver General Hospital, Vancouver, British Columbia, Canada.
  • Heidi Schmidt
    University Health Network-Princess Margaret Cancer Centre and Toronto General Hospital, Toronto, Ontario, Canada.
  • Michel Gingras
    Institut universitaire de cardiologie et, de pneumologie de Québec, Canada.
  • Sergio Pasian
    Institut universitaire de cardiologie et, de pneumologie de Québec, Canada.
  • Lori Stewart
    Department of Diagnostic Imaging, Juravinski Hospital, Hamilton, Ontario, Canada.
  • Scott Tsai
    Department of Diagnostic Imaging, Juravinski Hospital, Hamilton, Ontario, Canada.
  • Jean M Seely
    Ottawa Hospital Research Institute and the University of Ottawa, Ottawa, Ontario, Canada.
  • Daria Manos
    Dalhousie University, Halifax, Nova Scotia, Canada.
  • Paul Burrowes
    University of Calgary, Foothills Medical Centre, Calgary, Alberta, Canada.
  • Rick Bhatia
    Memorial University, Newfoundland, Canada.
  • Ming-Sound Tsao
    University Health Network-Princess Margaret Cancer Centre and Toronto General Hospital, Toronto, Ontario, Canada.
  • Stephen Lam
    University of British Columbia-British Columbia Cancer Agency and Vancouver General Hospital, Vancouver, British Columbia, Canada.

Keywords

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