Artificial intelligence-based automated surgical workflow recognition in esophageal endoscopic submucosal dissection: an international multicenter study (with video).

Journal: Surgical endoscopy
PMID:

Abstract

BACKGROUND: Endoscopic submucosal dissection (ESD) is a crucial yet challenging multi-phase procedure for treating early gastrointestinal cancers. This study developed an artificial intelligence (AI)-based automated surgical workflow recognition model for esophageal ESD and proposed an innovative training program based on esophageal ESD videos with or without AI labels to evaluate its effectiveness for trainees.

Authors

  • Ruide Liu
    Department of Pathology, The First Affiliated Hospital of Gannan Medical University, Ganzhou 341000, China.
  • Xianglei Yuan
    Department of Gastroenterology and Hepatology, Digestive Endoscopy Medical Engineering Research Laboratory, Wuhou District, West China Hospital, Sichuan University, No. 37, Guo Xue Alley, Chengdu City, 610041, Sichuan Province, China.
  • Kaide Huang
    Machine Intelligence Laboratory, College of Computer Science, Sichuan University, Chengdu, China; and.
  • Tingfa Peng
    Department of Gastroenterology and Hepatology, Digestive Endoscopy Medical Engineering Research Laboratory, Wuhou District, West China Hospital, Sichuan University, No. 37, Guo Xue Alley, Chengdu City, 610041, Sichuan Province, China.
  • Pavel V Pavlov
    Department of Diagnostic and Therapeutic Endoscopy of the University Clinical Hospital 2, Sechenov University, Moscow, Russia.
  • Wanhong Zhang
    Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
  • ChunCheng Wu
    Department of Gastroenterology, West China Hospital, Sichuan University, Chengdu, China.
  • Kseniia V Feoktistova
    Department of Diagnostic and Therapeutic Endoscopy of the University Clinical Hospital 2, Sechenov University, Moscow, Russia.
  • Xiaogang Bi
    Department of Gastroenterology, Zigong Fourth People's Hospital, Zigong, China.
  • Yan Zhang
    Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang, 110032, China.
  • Xin Chen
    University of Nottingham, Nottingham, United Kingdom.
  • Jeffey George
    Department of Gastroenterology, Medical Gastroenterology, Aster Medcity, Kochi, India.
  • Shuang Liu
    Key Laboratory for Applied Technology of Sophisticated Analytical Instruments of Shandong Province, Shandong Analysis and Test Center, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250014, China.
  • Wei Liu
    Department of Radiation Oncology, Mayo Clinic, Scottsdale, AZ, United States.
  • YuHang Zhang
    Institute of Health Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China. Electronic address: yhzhang@sibs.ac.cn.
  • Juliana Yang
    Department of Gastroenterology, The University of Texas Medical Branch at Galveston, Galveston, TX, USA.
  • Maoyin Pang
    Division of Gastroenterology and Hepatology, Mayo Clinic, Jacksonville, Florida, USA.
  • Bing Hu
    Department of Gastroenterology, West China Hospital, Sichuan University, Chengdu, China.
  • Zhang Yi
  • Liansong Ye
    Department of Gastroenterology and Hepatology, Digestive Endoscopy Medical Engineering Research Laboratory, West China Hospital, Sichuan University, Chengdu 610064, China.