Deployment of an Artificial Intelligence Histology Tool to Aid Qualitative Assessment of Histopathology Using the Nancy Histopathology Index in Ulcerative Colitis.

Journal: Inflammatory bowel diseases
Published Date:

Abstract

BACKGROUND: Ulcerative colitis (UC) is a chronic inflammatory bowel disease characterized by increased stool frequency, rectal bleeding, and urgency. To streamline the quantitative assessment of histopathology using the Nancy Index in UC patients, we developed a novel artificial intelligence (AI) tool based on deep learning and tested it in a proof-of-concept trial. In this study, we report the performance of a modified version of the AI tool.

Authors

  • David T Rubin
    Inflammatory Bowel Disease Center, The University of Chicago Medicine, Chicago, Illinois, USA.
  • Olga Kubassova
    Image Analysis Group, London, United Kingdom.
  • Christopher R Weber
    Organoid and Primary Culture Research Core, The University of Chicago, Chicago, Illinois, United States of America.
  • Shashi Adsul
    Takeda Pharmaceutical Company, Zurich, Switzerland.
  • Marcelo Freire
    Takeda, Cambridge, MA, USA.
  • Luc Biedermann
    Department of Gastroenterology and Hepatology, University Hospital Zurich, Rämistrasse 100, 8091, Zurich, Switzerland.
  • Viktor H Koelzer
    Institute of Cancer and Genomic Science, University of Birmingham, 6 Mindelsohn Way, Birmingham, B15 2SY, UK. vkoelzer@well.ox.ac.uk.
  • Brian Bressler
    Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada.
  • Wei Xiong
    Department of Nutrition and Health, China Agricultural University, Beijing 100193, China; Food Laboratory of Zhongyuan, Luohe, Henan 462300, China. Electronic address: xiongwei910702@126.com.
  • Jan H Niess
    Department of Biomedicine and University Digestive Healthcare Center, University of Basel, Clarunis, Basel, Switzerland.
  • Matthias S Matter
    Institute of Medical Genetics and Pathology, University Hospital Basel, Basel, Switzerland.
  • Uri Kopylov
    Department of Gastroenterology, Sheba Medical Center, Tel Hashomer, Israel.
  • Iris Barshack
  • Chen Mayer
    Institute of Pathology, Sheba Medical Center, Ramat Gan, Israel. chen.mayer@sheba.health.gov.il.
  • Fernando Magro
    Department of Biomedicine, Unit of Pharmacology and Therapeutics, Faculty of Medicine, University of Porto, Porto, Portugal.
  • Fatima Carneiro
    Faculty of Medicine, University of Porto and ULS São João, Porto, Portugal.
  • Nitsan Maharshak
    Tel Aviv Sourasky Medical Center affiliated with the Faculty of Medical and Health Sciences, Tel Aviv University, Tel Aviv, Israel.
  • Ariel Greenberg
    Institute of Pathology, Tel-Aviv Sourasky Medical Center, 6 Weizmann Street, 6423906, Tel Aviv, Israel.
  • Simon Hart
    Image Analysis Group, London, UK.
  • Jamshid Dehmeshki
    Image Analysis Group, Philadelphia, PA, USA; Kingston University, Kingston-upon-Thames, UK.
  • Laurent Peyrin-Biroulet
    Institut National de la Santé et de la Recherche Médicale U954 and Department of Gastroenterology, Nancy University Hospital, University of Lorraine, France. Electronic address: peyrinbiroulet@gmail.com.