Research Article|Articles in Press

Performance and Attitudes Toward Real-time Computer-aided Polyp Detection during Colonoscopy in a Large Tertiary Referral Center in the United States

Published:February 17, 2023DOI:
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      Background and Aims

      Computer aided detection (CADe) has been shown to improve polyp detection in clinical trials. Limited data exists on the impact, utilization, and attitudes toward artificial intelligence (AI)-assisted colonoscopy in daily clinical practice. We aimed to evaluate the effectiveness of the first FDA-approved CADe device in the United States and the attitudes toward its implementation.


      Retrospective analysis of a prospectively maintained database of patients undergoing colonoscopy at a tertiary center in the United States before and after a real-time CADe system was made available. The decision to activate the CADe system was at the discretion of the endoscopist. An anonymous survey was circulated among endoscopy physicians and staff at the beginning and at the conclusion of the study period regarding their attitudes toward AI-assisted colonoscopy.


      CADe was activated in 52.1% of cases. Compared with historical controls, there was no statistically significant difference in adenomas detected per colonoscopy (APC) (1.08 vs 1.04, p=0.65), even after excluding diagnostic/therapeutic indications and cases where CADe was not activated (1.27 vs 1.17, p=0.45). In addition, there was no statistically significant difference in ADR, median procedure and withdrawal times. Survey results demonstrated mixed attitudes toward AI-assisted colonoscopy, of which main concerns included high number of false positive signals (82.4%), high level of distraction (58.8%), and impression it prolonged procedure time (47.1%).


      CADe did not improve adenoma detection in daily practice among endoscopists with high baseline ADR. Despite its availability, AI-assisted colonoscopy was only activated in half of cases, and multiple concerns were raised by staff and endoscopists. Future studies will help elucidate the patients and endoscopists that would benefit most from AI-assisted colonoscopy.


      Acronyms and abbreviations:

      CADe (Computer aided detection), AI (artificial intelligence), APC (adenomas detected per colonoscopy), ADR (adenoma detection rate), CRC (Colorectal cancer), RCT (randomized controlled trial), SSLDR (sessile serrated lesion detection rate)
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