Artificial intelligence for the detection of COVID-19 pneumonia on chest CT using multinational datasets.

Journal: Nature communications
Published Date: Aug 14, 2020

Abstract

Chest CT is emerging as a valuable diagnostic tool for clinical management of COVID-19 associated lung disease. Artificial intelligence (AI) has the potential to aid in rapid evaluation of CT scans for differentiation of COVID-19 findings from other clinical entities. Here we show that a series of deep learning algorithms, trained in a diverse multinational cohort of 1280 patients to localize parietal pleura/lung parenchyma followed by classification of COVID-19 pneumonia, can achieve up to 90.8% accuracy, with 84% sensitivity and 93% specificity, as evaluated in an independent test set (not included in training and validation) of 1337 patients. Normal controls included chest CTs from oncology, emergency, and pneumonia-related indications. The false positive rate in 140 patients with laboratory confirmed other (non COVID-19) pneumonias was 10%. AI-based algorithms can readily identify CT scans with COVID-19 associated pneumonia, as well as distinguish non-COVID related pneumonias with high specificity in diverse patient populations.

Authors

  • Stephanie A Harmon
    Clinical Research Directorate, Frederick National Laboratory for Cancer Research sponsored by the National Cancer Institute, Frederick, Maryland, USA.
  • Thomas H Sanford
    State University of New York-Upstate Medical Center, Syracuse, NY, USA.
  • Sheng Xu
    School of Physics and Information Engineering, Jiangsu Second Normal University, Nanjing, 211200, China.
  • Evrim B Turkbey
    Imaging Biomarkers and Computer-aided Diagnosis Laboratory and Clinical Image Processing Service, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD, 20892-1182, USA.
  • Holger Roth
    Graduate School of Informatics, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, 464-8601, Japan.
  • Ziyue Xu
    Center for Infectious Disease Imaging (CIDI), Radiology and Imaging Science Department, National Institutes of Health (NIH), Bethesda, MD 20892, United States.
  • Dong Yang
    College of Chemistry and Chemical Engineering, Shaanxi University of Science and Technology Xi'an 710021 China yangdong@sust.edu.cn.
  • Andriy Myronenko
  • Victoria Anderson
    Center for Interventional Oncology, Radiology and Imaging Sciences, NIH Clinical Center and National Cancer Institute, Center for Cancer Research, National Institutes of Health, Bethesda, MD, USA.
  • Amel Amalou
    Center for Interventional Oncology, Radiology and Imaging Sciences, NIH Clinical Center and National Cancer Institute, Center for Cancer Research, National Institutes of Health, Bethesda, MD, USA.
  • Maxime Blain
    Department of Radiology, Hopital Henri Mondor, AP-HP, 94000 Créteil, France.
  • Michael Kassin
    Center for Interventional Oncology, Radiology and Imaging Sciences, NIH Clinical Center and National Cancer Institute, Center for Cancer Research, National Institutes of Health, Bethesda, MD, USA.
  • Dilara Long
    Center for Interventional Oncology, Radiology and Imaging Sciences, NIH Clinical Center and National Cancer Institute, Center for Cancer Research, National Institutes of Health, Bethesda, MD, USA.
  • Nicole Varble
    Center for Interventional Oncology, Radiology and Imaging Sciences, NIH Clinical Center and National Cancer Institute, Center for Cancer Research, National Institutes of Health, Bethesda, MD, USA.
  • Stephanie M Walker
    Molecular Imaging Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
  • Ulas Bagci
    Department of Radiology, Feinberg School of Medicine, Northwestern University, 737 N Michigan Ave, Ste 1600, Chicago, IL 60611.
  • Anna Maria Ierardi
    Radiology Department, Foundation IRCCS Cà Granda-Ospedale Maggiore Policlinico, Milan, Italy.
  • Elvira Stellato
    Department of Radiology Fondazione IRCCS Cà Granda, Ospedale Maggiore Policlinico Milano, Milan, Italy.
  • Guido Giovanni Plensich
    Department of Radiology Fondazione IRCCS Cà Granda, Ospedale Maggiore Policlinico Milano, Milan, Italy.
  • Giuseppe Franceschelli
    Diagnostic and Interventional Radiology Service, ASST Santi Paolo e Carlo, San Paolo Hospital, Milan, Italy.
  • Cristiano Girlando
    Postgraduation School in Radiodiagnostics, Università Degli Studi di Milano, Via Festa del Perdono 7, 20122, Milan, Italy.
  • Giovanni Irmici
    Postgraduation School in Radiodiagnostics, Università Degli Studi di Milano, Via Festa del Perdono 7, 20122, Milan, Italy.
  • Dominic Labella
    State University of New York-Upstate Medical Center, Syracuse, NY, USA.
  • Dima Hammoud
    Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD, USA.
  • Ashkan Malayeri
    Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD, USA.
  • Elizabeth Jones
    Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD, USA.
  • Ronald M Summers
    National Institutes of Health, Clinical Center, Radiology and Imaging Sciences, 10 Center Drive, Bethesda, MD 20892, USA.
  • Peter L Choyke
    Molecular Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
  • Daguang Xu
    NVIDIA, Santa Clara, CA, USA.
  • Mona Flores
    NVIDIA Corporation, Bethesda, MD, USA.
  • Kaku Tamura
    Self-Defense Forces Central Hospital, Tokyo, Japan.
  • Hirofumi Obinata
    Self-Defense Forces Central Hospital, Tokyo, Japan.
  • Hitoshi Mori
    Self-Defense Forces Central Hospital, Tokyo, Japan.
  • Francesca Patella
    Diagnostic and Interventional Radiology Department, San Paolo Hospital, University of Milan, Milan, Italy.
  • Maurizio Cariati
    Diagnostic and Interventional Radiology Service, ASST Santi Paolo e Carlo, San Paolo Hospital, Milan, Italy.
  • Gianpaolo Carrafiello
    Radiology Department, Foundation IRCCS Cà Granda-Ospedale Maggiore Policlinico, Milan, Italy.
  • Peng An
    Department of Radiology, Xiangyang NO.1 People's Hospital Affiliated to Hubei University of Medicine Xiangyang, Hubei, China.
  • Bradford J Wood
    Molecular Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
  • Baris Turkbey
    Molecular Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.

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