Benefits and challenges in implementation of artificial intelligence in colonoscopy: World Endoscopy Organization position statement
Issued Date
2023-01-01
Resource Type
ISSN
09155635
eISSN
14431661
Scopus ID
2-s2.0-85149924848
Pubmed ID
36749036
Journal Title
Digestive Endoscopy
Rights Holder(s)
SCOPUS
Bibliographic Citation
Digestive Endoscopy (2023)
Suggested Citation
Mori Y., East J.E., Hassan C., Halvorsen N., Berzin T.M., Byrne M., von Renteln D., Hewett D.G., Repici A., Ramchandani M., Al Khatry M., Kudo S.e., Wang P., Yu H., Saito Y., Misawa M., Parasa S., Matsubayashi C.O., Ogata H., Tajiri H., Pausawasdi N., Dekker E., Ahmad O.F., Sharma P., Rex D.K. Benefits and challenges in implementation of artificial intelligence in colonoscopy: World Endoscopy Organization position statement. Digestive Endoscopy (2023). doi:10.1111/den.14531 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/82563
Title
Benefits and challenges in implementation of artificial intelligence in colonoscopy: World Endoscopy Organization position statement
Author's Affiliation
Siriraj Hospital
NIHR Oxford Biomedical Research Centre
Showa University Yokohama Northern Hospital
Humanitas University
Oslo Universitetssykehus
Renmin Hospital of Wuhan University
Sichuan Provincial People's Hospital
The Jikei University School of Medicine
The University of Queensland
Beth Israel Deaconess Medical Center
University of Kansas, School of Medicine
Keio University School of Medicine
Humanitas Research Hospital
University College London
Indiana University School of Medicine
National Cancer Center Hospital
Asian Institute of Gastroenterology India
Swedish Medical Center, Seattle
Faculty of Medicine Siriraj Hospital, Mahidol University
The University of British Columbia
Universitetet i Oslo
University of Montreal
Nuffield Department of Medicine
Universidade de São Paulo
Amsterdam UMC - University of Amsterdam
Mayo Clinic Healthcare
Obaidulla Hospital
NIHR Oxford Biomedical Research Centre
Showa University Yokohama Northern Hospital
Humanitas University
Oslo Universitetssykehus
Renmin Hospital of Wuhan University
Sichuan Provincial People's Hospital
The Jikei University School of Medicine
The University of Queensland
Beth Israel Deaconess Medical Center
University of Kansas, School of Medicine
Keio University School of Medicine
Humanitas Research Hospital
University College London
Indiana University School of Medicine
National Cancer Center Hospital
Asian Institute of Gastroenterology India
Swedish Medical Center, Seattle
Faculty of Medicine Siriraj Hospital, Mahidol University
The University of British Columbia
Universitetet i Oslo
University of Montreal
Nuffield Department of Medicine
Universidade de São Paulo
Amsterdam UMC - University of Amsterdam
Mayo Clinic Healthcare
Obaidulla Hospital
Other Contributor(s)
Abstract
The number of artificial intelligence (AI) tools for colonoscopy on the market is increasing with supporting clinical evidence. Nevertheless, their implementation is not going smoothly for a variety of reasons, including lack of data on clinical benefits and cost-effectiveness, lack of trustworthy guidelines, uncertain indications, and cost for implementation. To address this issue and better guide practitioners, the World Endoscopy Organization (WEO) has provided its perspective about the status of AI in colonoscopy as the position statement. WEO Position Statement: Statement 1.1: Computer-aided detection (CADe) for colorectal polyps is likely to improve colonoscopy effectiveness by reducing adenoma miss rates and thus increase adenoma detection; Statement 1.2: In the short term, use of CADe is likely to increase health-care costs by detecting more adenomas; Statement 1.3: In the long term, the increased cost by CADe could be balanced by savings in costs related to cancer treatment (surgery, chemotherapy, palliative care) due to CADe-related cancer prevention; Statement 1.4: Health-care delivery systems and authorities should evaluate the cost-effectiveness of CADe to support its use in clinical practice; Statement 2.1: Computer-aided diagnosis (CADx) for diminutive polyps (≤5 mm), when it has sufficient accuracy, is expected to reduce health-care costs by reducing polypectomies, pathological examinations, or both; Statement 2.2: Health-care delivery systems and authorities should evaluate the cost-effectiveness of CADx to support its use in clinical practice; Statement 3: We recommend that a broad range of high-quality cost-effectiveness research should be undertaken to understand whether AI implementation benefits populations and societies in different health-care systems.