Clinical validation of deep learning algorithms for radiotherapy targeting of non-small-cell lung cancer: an observational study.

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

Abstract

BACKGROUND: Artificial intelligence (AI) and deep learning have shown great potential in streamlining clinical tasks. However, most studies remain confined to in silico validation in small internal cohorts, without external validation or data on real-world clinical utility. We developed a strategy for the clinical validation of deep learning models for segmenting primary non-small-cell lung cancer (NSCLC) tumours and involved lymph nodes in CT images, which is a time-intensive step in radiation treatment planning, with large variability among experts.

Authors

  • Ahmed Hosny
    Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
  • Danielle S Bitterman
    Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, United States.
  • Christian V Guthier
    Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, United States.
  • Jack M Qian
    Harvard Radiation Oncology Program, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Mass General Brigham, Boston, MA.
  • Hannah Roberts
    Harvard Radiation Oncology Program, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Mass General Brigham, Boston, MA.
  • Subha Perni
    Harvard Radiation Oncology Program, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Mass General Brigham, Boston, MA.
  • Anurag Saraf
    Department of Radiation Oncology, Massachusetts General Hospital & Harvard Medical School, Boston, MA, USA.
  • Luke C Peng
    Harvard Radiation Oncology Program, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Mass General Brigham, Boston, MA.
  • Itai Pashtan
    Department of Radiation Oncology, Brigham and Women's Hospital and Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
  • Zezhong Ye
    Artificial Intelligence in Medicine (AIM) Program, Harvard Medical School, Boston, Massachusetts, USA.
  • Benjamin H Kann
    Artificial Intelligence in Medicine (AIM) Program, Harvard Medical School, Boston, Massachusetts, USA.
  • David E Kozono
    Department of Radiation Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Boston, MA.
  • David Christiani
    Harvard T H Chan School of Public Health, Massachusetts General Hospital and Harvard Medical School, Baltimore, MD, USA.
  • Paul J Catalano
    Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
  • Hugo J W L Aerts
    Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, United States.
  • Raymond H Mak
    Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, United States.

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