Background and study aims: Artificial intelligence (AI)-based polyp detection systems during colonoscopy aim at increasing lesion detection and improving colonoscopy quality. Patients and methods: We performed a systematic review and meta-analysis of prospective trials to determine the value of AI-based polyp detection systems for detection of polyps and colorectal cancer. We performed systematic searches in MEDLINE, EMBASE and Cochrane CENTRAL. Independent reviewers screened studies and assessed eligibility, certainty of evidence, and risk of bias. We compared colonoscopy with and without AI by calculating relative and absolute risk and mean differences for detection of polyps, adenomas, and colorectal cancer. Results: Five randomized trials were eligible for analyses. Colonoscopy with AI increased adenoma detection rates (ADRs) and polyp detection rates (PDRs) compared to colonoscopy without AI: ADR with AI 29.6% [95% confidence interval, 22.2-37.0], versus 19.3% [12.7-25.9] without AI (relative risk (RR) 1.52, [1.31-1.77], high certainty); PDR 45.4% [41.1-49.8] with AI, versus 30.6% [26.5-34.6] without AI (RR 1.48, [1.37-1.60], high certainty). There was no difference in detection of advanced adenomas between the two groups (mean number of advanced adenomas per colonoscopy 0.03 for each, high certainty). Mean number of adenomas per colonoscopy were higher for small adenomas (≤5 mm) with AI compared to non-AI colonoscopy (mean difference 0.15, [0.12-0.18]), but not for larger adenomas (>5-≤10mm: mean difference 0.03, [0.01-0.05]; >10 mm: mean difference 0.01, [0.00-0.02], high certainty). Data on cancer are unavailable. Conclusions: AI-based polyp detection systems during colonoscopy increase detection of small, non-advanced adenomas and polyps, but not advanced adenomas.

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