Effectiveness of artificial intelligence-assisted colonoscopy for colorectal lesion detection: a systematic review and meta-analysis of randomized controlled trials
In brief
AI-assisted colonoscopy raises adenoma detection by 22%, not advanced adenoma detection
Across 46 randomized trials involving 37,012 people, AI-assisted colonoscopy was linked to a 22% higher adenoma detection rate and a 20% higher rate of finding sessile serrated lesions than standard colonoscopy. Advanced adenoma detection did not improve, and very low evidence certainty plus a lack of long-term outcomes limit what these gains mean for patients.
- Journal
- BMC medical imaging (Q2)
- Published
- 28 July 2026
- Study design
- Systematic review / meta-analysis of RCTs
- Evidence level
- Level 1, High (CEBM 1a)
- Authors
- Xia Liu, Jian Qin, Yuxia Zhao, Chen Zhang, Dengchao Wang, Tao Jiang
- PMID
- 42919249
- DOI
- 10.1186/s12880-026-02586-8
Why clinicians should know about it
- Picked for Health Informatics (top studies of the week, 25 October 2026): Randomized evidence evaluates AI-assisted clinical decision support in colonoscopy
Abstract
BACKGROUND: Colonoscopy is the gold standard for colorectal cancer detection and prevention, but its performance depends on operator skill and lesion features. Artificial intelligence (AI)-assisted colonoscopy has been introduced to improve adenoma detection. METHODS: A comprehensive search was conducted in PubMed, Embase, the Cochrane Library, Web of Science, ClinicalTrials.gov, and major Chinese databases to identify randomized controlled trials (RCTs) comparing AI-assisted and conventional colonoscopy. Meta-analyses were performed using Review Manager 5.4 and Stata 14.0. The quality of evidence was graded using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system, while trial sequential analysis (TSA) was applied to assess the robustness and information sufficiency of the results. RESULTS: A total of 46 RCTs encompassing 37,012 participants were included. Compared with conventional colonoscopy, AI-assisted colonoscopy was associated with a higher ADR (RR = 1.22, 95% CI = 1.17-1.27, P < 0.00001), polyp detection rate (PDR: RR = 1.22, 95% CI = 1.16-1.29, P < 0.00001), polyp detection per colonoscopy (PPC: MD = 0.28, 95% CI = 0.21-0.36), and adenoma detection per colonoscopy (APC: MD = 0.22, 95% CI = 0.15-0.29). The detection rate of sessile serrated lesions (SSL) was also higher in the AI-assisted group (RR = 1.20, 95% CI: 1.05-1.36, P = 0.007), whereas no significant difference was observed in advanced adenoma detection rate (AADR). CONCLUSIONS: AI-assisted colonoscopy was associated with improvements in several detection-related quality indicators, including ADR, PDR, PPC, APC, and SSL detection rate. However, given the very low GRADE certainty for ADR and PDR and the lack of long-term outcome data, these findings should be interpreted cautiously. CLINICAL TRIAL NUMBER: Not applicable.
Abstract as published, via PubMed.
For healthcare professionals. The summary is generated by AI from the published abstract, and the evidence level is assigned automatically from the study design on the Oxford CEBM hierarchy. Neither is medical advice. Read the full paper before changing practice.