Impact of computer-aided polyp detection in screening and diagnostic colonoscopy: A multicenter randomized controlled trial

BACKGROUND Colonoscopy is the reference standard for the diagnosis of polyps and neoplasms of the lower gastrointestinal tract. Recently, real-time artificial intelligence algorithms have been developed to minimize human error in detecting lesions during colonoscopy. Although the performance of these systems on still images and real-time video appears extremely promising, robust evidence of their ability to improve everyday clinical practice is still lacking. AIM To evaluate the use of a computer-aided detection (CADe) system on polyp detection rate, adenoma detection rate (ADR), advanced ADR, and sessile serrated lesion detection rate, in addition to ultra-high-definition (UHD) systems in screening and diagnostic procedures, stratified by expertise and fatigue. METHODS Between August 2023 and September 2024, patients were randomized (1:1) to UHD colonoscopy with or without CADe (DISCOVERY (TM)) at five Italian tertiary centers. Endoscopists were categorized by annual volume (< 200 or >= 200 procedures) and assessed for work-related fatigue (i.e., daily working hours and number of procedures). RESULTS Of 421 randomized patients, 409 were included in the per-protocol population. The CADe group were similar in polyp detection rate [CADe: 41.2% vs conventional colonoscopy (CC): 45.4%], ADR (CADe: 29.4% vs CC: 32.2%), advanced ADR (CADe: 5.9% vs CC: 5.4%), or sessile serrated lesion detection rate (CADe: 6.3% vs CC: 8.7%). Results remained consistent across different indications, operator expertise, and fatigue levels. CONCLUSION CADe did not improve detection rates over UHD colonoscopy in tertiary centers. No robust evidence of effect modification by operator volume or workload-related fatigue was observed, although the findings in low-volume endoscopists may warrant further investigation in larger studies.