Deep learning-based automated quantification of goblet cell mucus using histological images as a predictor of clinical relapse of ulcerative colitis with endoscopic remission.

Journal: Journal of gastroenterology
PMID: 36184701

Abstract

BACKGROUND: Mucin depletion is one of the histological indicators of clinical relapse among patients with ulcerative colitis (UC). Mucin depletion is evaluated semiquantitatively by pathologists using histological images. Therefore, the interobserver concordance is not extremely high, and an objective evaluation method is needed. This study was conducted to demonstrate that our automated quantitative method using a deep learning-based model is useful in predicting the prognosis of patients with UC.

Authors

  • Jun Ohara
    Department of Pathology, Showa University, Tokyo, Japan. johara1729@med.showa-u.ac.jp.
  • Tetsuo Nemoto
    Department of Diagnostic Pathology, School of Medicine, Showa University Northern Yokohama Hospital, Kanagawa, Japan.
  • Yasuharu Maeda
    Digestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Japan.
  • Noriyuki Ogata
    Digestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Japan.
  • Shin-Ei Kudo
    Digestive Disease Center, Showa University Northern Yokohama Hospital, Tsuzuki-ku, Yokohama, 224-8503, Japan.
  • Toshiko Yamochi
    Department of Pathology, Showa University, Tokyo, Japan.

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