Dimopoulou K, Spinou M, Ioannou A, Nakou E, Zormpas P, Tribonias G. Artificial intelligence in colonoscopy: Enhancing quality indicators for optimal patient outcomes. World J Gastroenterol 2025; 31(40): 111499 [DOI: 10.3748/wjg.v31.i40.111499]
Corresponding Author of This Article
Konstantina Dimopoulou, MD, PhD, Consultant, Department of Gastroenterology, Red Cross Hospital, 1, Athanasaki str, Athens 11526, Greece. conu_med@hotmail.com
Research Domain of This Article
Gastroenterology & Hepatology
Article-Type of This Article
Review
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This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Oct 28, 2025 (publication date) through Oct 30, 2025
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Journal Information of This Article
Publication Name
World Journal of Gastroenterology
ISSN
1007-9327
Publisher of This Article
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
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Dimopoulou K, Spinou M, Ioannou A, Nakou E, Zormpas P, Tribonias G. Artificial intelligence in colonoscopy: Enhancing quality indicators for optimal patient outcomes. World J Gastroenterol 2025; 31(40): 111499 [DOI: 10.3748/wjg.v31.i40.111499]
Konstantina Dimopoulou, Marianna Spinou, Eleni Nakou, Petros Zormpas, George Tribonias, Department of Gastroenterology, Red Cross Hospital, Athens 11526, Greece
Alexandros Ioannou, Department of Gastroenterology, Alexandra, General Hospital of Athens, Athens 11528, Greece
Co-first authors: Konstantina Dimopoulou and Marianna Spinou.
Author contributions: Dimopoulou K, Spinou M, Tribonias G contributed to conceptualization; Dimopoulou K, Spinou M, Ioannou A, Nakou E, Zormpas P, Tribonias G contributed to methodology, data acquisition, investigation, writing draft preparation, writing review and editing; Dimopoulou K, Spinou M, Tribonias G contributed to supervision and project administration; All authors have read and approved the final version of the manuscript; Dimopoulou K and Spinou M contributed equally as first authors. Both shared responsibility for the conception and design of the study, acquisition and analysis of data, interpretation of results, and drafting and critical revision of the manuscript. Their equal contributions meet the criteria typically attributed to the first author, reflecting substantial intellectual involvement in all key stages of the research and publication process.
Conflict-of-interest statement: The authors declare that they have no conflict of interest.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Konstantina Dimopoulou, MD, PhD, Consultant, Department of Gastroenterology, Red Cross Hospital, 1, Athanasaki str, Athens 11526, Greece. conu_med@hotmail.com
Received: July 1, 2025 Revised: August 9, 2025 Accepted: September 18, 2025 Published online: October 28, 2025 Processing time: 118 Days and 12 Hours
Abstract
Colonoscopy remains the cornerstone of colorectal cancer prevention and surveillance, but the procedure’s effectiveness is entirely dependent upon various quality indicators, such as detection rates, withdrawal time, adequate bowel preparation, cecal intubation rate and patient outcomes. Despite progress in endoscopic techniques, challenges persist in maintaining endoscopists’ consistent performance and improving quality metrics. Artificial intelligence (AI) has emerged as a “game changer” in the gastroenterology field, offering the opportunity to significantly increase colonoscopy quality. This review highlights the role of AI-driven technologies such as deep learning, computer vision, and real-time feedback mechanisms in optimizing key quality indicators of colonoscopy. The implementation of AI in colonoscopy may reduce human error, improve endoscopist’s consistency in real-time decision making, ensuring higher reliability and standardization during the procedure. Furthermore, AI has the potential to reshape how endoscopists perform and evaluate procedures, while improved lesion characterization may enable more precise selection for resection, reducing morbidity and the incidence of interval cancers. The review also addresses challenges and limitations in AI integration, including cost-effectiveness and its impact on endoscopist training. AI holds substantial promise for advancing colonoscopy quality and elevating overall patient care, paving the way for more effective and personalized medical approaches.
Core Tip: Artificial intelligence (AI) has emerged as a breakthrough innovation in modern colonoscopy, offering significant improvements in key quality indicators, including adenoma detection rate, polyp detection rate, adenoma miss rate, bowel preparation assessment, withdrawal time, and cecal intubation recognition. By optimizing lesion characterization, supporting optical diagnosis and assisting in invasion depth prediction, AI may lead to early diagnosis and prevention of colorectal cancer. This review summarizes the current evidence on the application of AI in key colonoscopy quality indicators, highlighting its role in standardizing practice, improving patient outcomes, and advancing personalized care while also addressing the challenges of training, cost-effectiveness, and ethical considerations.
