A review of water exchange and artificial intelligence in improving adenoma detection
Chia-Pei Tang1, Paul P Shao2, Yu-Hsi Hsieh1, Felix W Leung2
1 Division of Gastroenterology, Department of Internal Medicine, Dalin Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Chiayi; School of Medicine, Tzu Chi University, Hualien, Taiwan
2 Sepulveda Ambulatory Care Center, Veterans Affairs Greater Los Angeles Healthcare System, North Hills; Division of Gastroenterology, Department of Medicine, David Geffen School of Medicine at University of California at Los Angeles, Los Angeles, CA, USA
Division of Gastroenterology, Department of Internal Medicine, Dalin Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, 2, Minsheng Road, Dalin, Chiayi
Source of Support: The study was supported by research fund from the Dalin Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation. Dr. Leung's research and publication effort is supported by VA Clinical Merit and ASGE Clinical Research Funds., Conflict of Interest: None
Water exchange (WE) and artificial intelligence (AI) have made critical advances during the past decade. WE significantly increases adenoma detection and AI holds the potential to help endoscopists detect more polyps and adenomas. We performed an electronic literature search on PubMed using the following keywords: water-assisted and water exchange colonoscopy, adenoma and polyp detection, artificial intelligence, deep learning, neural networks, and computer-aided colonoscopy. We reviewed relevant articles published in English from 2010 to May 2020. Additional articles were searched manually from the reference lists of the publications reviewed. We discussed recent advances in both WE and AI, including their advantages and limitations. AI may mitigate operator-dependent factors that limit the potential of WE. By increasing bowel cleanliness and improving visualization, WE may provide the platform to optimize the performance of AI for colonoscopies. The strengths of WE and AI may complement each other in spite of their weaknesses to maximize adenoma detection.