Validation of artificial intelligence-based bowel preparation assessment in screening colonoscopy (with video).

Journal: Gastrointestinal endoscopy
PMID: 38636818

Abstract

BACKGROUND AND AIMS: Accurate bowel preparation assessment is essential for determining colonoscopy screening intervals. Patients with suboptimal bowel preparation are at a high risk of missing >5 mm adenomas and should undergo an early repeat colonoscopy. In this study, we used artificial intelligence (AI) to evaluate bowel preparation and validated the ability of the system to accurately identify patients who are at high risk of having >5 mm adenomas missed due to inadequate bowel preparation.

Authors

  • Liwen Yao
    Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China; Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China; Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China.
  • Huizhen Xiong
    Gastrointestinal Endoscopy Center, The Eighth Affiliated Hospital, Sun Yat-sen University, Shenzhen, China.
  • Qiucheng Li
    Gastrointestinal Endoscopy Center, The Eighth Affiliated Hospital, Sun Yat-sen University, Shenzhen, China.
  • Wen Wang
    Clinical and Research Center for Infectious Diseases, Beijing Youan Hospital, Capital Medical University, Beijing, China.
  • Zhifeng Wu
    From the Department of Radiology, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University.
  • Xia Tan
    Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China; Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China; Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China.
  • Chaijie Luo
    Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China.
  • Hang You
    Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China; Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China; Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China.
  • Chenxia Zhang
    Department of Gastroenterology, Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, and Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China.
  • Lihui Zhang
    College of Civil Engineering and Architecture, Zhejiang University, 866, Yuhangtang Road, Hangzhou, 310058, China.
  • Zihua Lu
    Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China; Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China; Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China.
  • Honggang Yu
    Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China.
  • Honglei Chen
    State Key Laboratory of Biobased Material & Green Papermaking, Qilu University of Technology, Shandong Academy of Sciences, Jinan, 250353, P. R. China.

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