Performance and attitudes toward real-time computer-aided polyp detection during colonoscopy in a large tertiary referral center in the United States.

BACKGROUND AND AIMS: Computer-aided detection (CADe) has been shown to improve polyp detection in clinical trials. Limited data exist 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 U.S. Food and Drug Administration-approved CADe device for polyp detection in the United States and the attitudes toward its implementation. METHODS: We performed a 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 conclusion of the study period regarding their attitudes toward AI-assisted colonoscopy. RESULTS: CADe was activated in 52.1% of cases. Compared with historical control subjects, there was no statistically significant difference in adenomas detected per colonoscopy (1.08 vs 1.04, P = .65), even after excluding diagnostic and therapeutic indications and cases where CADe was not activated (1.27 vs 1.17, P = .45). In addition, there was no statistically significant difference in adenoma detection rate (ADR), median procedure, and withdrawal times. Survey results demonstrated mixed attitudes toward AI-assisted colonoscopy, of which main concerns were high number of false-positive signals (82.4%), high level of distraction (58.8%), and impression it prolonged procedure time (47.1%). CONCLUSIONS: CADe did not improve adenoma detection in daily practice among endoscopists with high baseline ADRs. Despite its availability, AI-assisted colonoscopy was only activated in half of the 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.

Full-thickness resection: troubleshooting, tips, and tricks for success in the colorectum.

Video 1Difficult scenarios encountered during colorectal full thickness resection and their management: (1) Inability to advance device to target lesion; (2) injury to extraluminal structures; (3) anal trauma; (4) anal stenosis; (5) luminal edema after resection; (6) difficulty in grasping lesion; (7) recommendation for "mini time-out"; (8) Summary.

Education, training, and knowledge of infection control among endoscopy technicians and nurses.

Our survey of 88 endoscopy technicians and nurses to determine their experience, training, and knowledge of infection control found that few personnel (<15%) received formal training in endoscope reprocessing or infection prevention before or after joining an endoscopy unit. While self-reported confidence in endoscope reprocessing was high (9 out of 10), knowledge of best practices in this regard lagged (average assessment score of 62%).