Predicting survival from colorectal cancer histology slides using deep learning: A retrospective multicenter study.

Journal: PLoS medicine
Published Date: Jan 24, 2019

Abstract

BACKGROUND: For virtually every patient with colorectal cancer (CRC), hematoxylin-eosin (HE)-stained tissue slides are available. These images contain quantitative information, which is not routinely used to objectively extract prognostic biomarkers. In the present study, we investigated whether deep convolutional neural networks (CNNs) can extract prognosticators directly from these widely available images.

Authors

  • Jakob Nikolas Kather
    Department of Medicine III, University Hospital RWTH Aachen, Aachen, Germany.
  • Johannes Krisam
    Institute of Medical Biometry and Informatics, University Hospital Heidelberg, Heidelberg, Germany.
  • Pornpimol Charoentong
    Department of Medical Oncology and Internal Medicine VI, National Center for Tumor Diseases, University Hospital Heidelberg, Heidelberg, Germany.
  • Tom Luedde
    Division of Gastroenterology, Hepatology and Hepatobiliary Oncology, University Hospital RWTH Aachen, Aachen, Germany.
  • Esther Herpel
    Institute of Pathology, Heidelberg University, Heidelberg, Germany.
  • Cleo-Aron Weis
    Institute of Pathology, University Medical Center Mannheim, Mannheim, Germany.
  • Timo Gaiser
    Institute of Pathology, University Medical Center Mannheim, Mannheim, Germany.
  • Alexander Marx
    Institute of Pathology, University Medical Center Mannheim, Mannheim, Germany.
  • Nektarios A Valous
    Department of Medical Oncology and Internal Medicine VI, National Center for Tumor Diseases, University Hospital Heidelberg, Heidelberg, Germany.
  • Dyke Ferber
    Department of Medical Oncology and Internal Medicine VI, National Center for Tumor Diseases, University Hospital Heidelberg, Heidelberg, Germany.
  • Lina Jansen
    Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Constantino Carlos Reyes-Aldasoro
    Senior Lecturer in Biomedical Image Analysis giCentre, Department of Computer Science, School of Science and Technology City, University of London, London, United Kingdom.
  • Inka Zörnig
    Department of Medical Oncology and Internal Medicine VI, National Center for Tumor Diseases, University Hospital Heidelberg, Heidelberg, Germany.
  • Dirk Jäger
    Department of Medical Oncology and Internal Medicine VI, National Center for Tumor Diseases, University Hospital Heidelberg, Heidelberg, Germany.
  • Hermann Brenner
    German Cancer Consortium (DKTK), Heidelberg, Germany.
  • Jenny Chang-Claude
    Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Michael Hoffmeister
    Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Niels Halama
    Department of Medical Oncology and Internal Medicine VI, National Center for Tumor Diseases, University Hospital Heidelberg, Heidelberg, Germany.

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