Panda K, Pati GK, Dash DP. Colonoscopy in the artificial intelligence era: Spotlight on adenoma miss rate. World J Gastroenterol 2025; 31(39): 110886 [DOI: 10.3748/wjg.v31.i39.110886]
Corresponding Author of This Article
Kalpana Panda, MD, Associate Professor, Division of Pediatric Gastroenterology and Hepatology, Institute of Medical Sciences and SUM Hospital, Kalinga Nagar, Bhubaneshwar 751003, Odisha, India. drkalpanapanda@gmail.com
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Gastroenterology & Hepatology
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Letter to the Editor
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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 21, 2025 (publication date) through Oct 21, 2025
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World Journal of Gastroenterology
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1007-9327
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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
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Panda K, Pati GK, Dash DP. Colonoscopy in the artificial intelligence era: Spotlight on adenoma miss rate. World J Gastroenterol 2025; 31(39): 110886 [DOI: 10.3748/wjg.v31.i39.110886]
World J Gastroenterol. Oct 21, 2025; 31(39): 110886 Published online Oct 21, 2025. doi: 10.3748/wjg.v31.i39.110886
Colonoscopy in the artificial intelligence era: Spotlight on adenoma miss rate
Kalpana Panda, Girish K Pati, Devi P Dash
Kalpana Panda, Division of Pediatric Gastroenterology and Hepatology, Institute of Medical Sciences and SUM Hospital, Bhubaneshwar 751003, Odisha, India
Girish K Pati, Department of Gastroenterology and Hepatology, Institute of Medical Sciences and SUM Hospital, Bhubaneshwar 751003, Odisha, India
Devi P Dash, Department of Critical Care Medicine, Kalinga Institute of Medical Sciences, Bhubaneshwar 751024, Odisha, India
Author contributions: Panda K and Pati GK designed the overall concept and outline of the manuscript; Panda K performed the literature search and wrote the initial draft; Pati GK and Dash DP provided the necessary intellectual inputs, reviewed, and edited the manuscript. All the authors have read and approved the final version of the manuscript.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
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: Kalpana Panda, MD, Associate Professor, Division of Pediatric Gastroenterology and Hepatology, Institute of Medical Sciences and SUM Hospital, Kalinga Nagar, Bhubaneshwar 751003, Odisha, India. drkalpanapanda@gmail.com
Received: June 17, 2025 Revised: July 23, 2025 Accepted: September 18, 2025 Published online: October 21, 2025 Processing time: 125 Days and 23.7 Hours
Abstract
This letter addresses the recent systematic review and meta-analysis by Wang et al, which evaluated the role of artificial intelligence-based computer-aided detection (CADe) in reducing adenoma and polyp miss rates during colonoscopy. We commend the authors for highlighting adenoma miss rate (AMR) as a more clinically meaningful endpoint than the traditionally used adenoma detection rate. Their findings demonstrate a significant reduction in AMR and polyp miss rate with CADe-assisted colonoscopy, particularly in small and sessile serrated lesions. However, limitations, including limited study numbers, tandem study design of included studies, and heterogeneity of CADe systems, warrant cautious interpretation. We discuss the broader implications of these findings for real-world practice and future research directions. This letter reinforces the importance of AMR as a performance metric and supports the continued integration and evaluation of artificial intelligence technologies in endoscopic practice to enhance colorectal cancer prevention strategies.
Core Tip: Artificial intelligence, particularly computer-aided detection, is increasingly being integrated into colonoscopy to improve neoplasia detection and reduce human error. While most prior meta-analyses have focused on adenoma detection rate, this systematic review and meta-analysis emphasize adenoma miss rate as a more sensitive and clinically relevant outcome. By analyzing five randomized-controlled trials involving 1624 patients, the study demonstrates that computer-aided detection-assisted colonoscopy significantly reduces adenoma miss rate, particularly for small-sized adenomas and sessile serrated lesions. These findings support broader adoption of artificial intelligence in colonoscopy, though real-world validation and long-term outcome studies are still needed to confirm its sustained clinical impact.
