The use of deep learning on endoscopic images to assess the response of rectal cancer after chemoradiation.

Journal: Surgical endoscopy
PMID: 34642794

Abstract

BACKGROUND: Accurate response evaluation is necessary to select complete responders (CRs) for a watch-and-wait approach. Deep learning may aid in this process, but so far has never been evaluated for this purpose. The aim was to evaluate the accuracy to assess response with deep learning methods based on endoscopic images in rectal cancer patients after neoadjuvant therapy.

Authors

  • Hester E Haak
    Department of Surgery, Netherlands Cancer Institute-Antoni Van Leeuwenhoek, Amsterdam, The Netherlands.
  • Xinpei Gao
    Department of Radiology, Netherlands Cancer Institute-Antoni Van Leeuwenhoek, Amsterdam, The Netherlands.
  • Monique Maas
    Department of Radiology, Netherlands Cancer Institute-Antoni Van Leeuwenhoek, Amsterdam, The Netherlands.
  • Selam Waktola
    Department of Radiology, Netherlands Cancer Institute-Antoni Van Leeuwenhoek, Amsterdam, The Netherlands.
  • Sean Benson
    Department of Radiology, Netherlands Cancer Institute-Antoni Van Leeuwenhoek, Amsterdam, The Netherlands.
  • Regina G H Beets-Tan
    Department of Radiology, the Netherlands Cancer Institute, Amsterdam, The Netherlands.
  • Geerard L Beets
    Department of Surgery, Netherlands Cancer Institute-Antoni Van Leeuwenhoek, Amsterdam, The Netherlands.
  • Monique van Leerdam
    Department of Gastroenterology, Netherlands Cancer Institute-Antoni Van Leeuwenhoek, Amsterdam, The Netherlands.
  • Jarno Melenhorst
    GROW School for Oncology and Developmental Biology-Maastricht University, Maastricht, The Netherlands. jarno.melenhorst@mumc.nl.

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