Artificial Intelligence-Assisted Colonoscopy With or Without Mucosal Exposure Device for Detection of Colorectal Adenomas: A Meta-Analysis

Abstract

Background and study aims: Artificial intelligence (AI) and mucosal exposure devices like Endocuff have independently improved the adenoma detection rate (ADR) during colonoscopy. This meta-analysis evaluated the combined effect of Endocuff and AI versus AI alone on colorectal neoplasia detection rates. Methods: We searched PubMed, Embase, and Web of Science for randomized controlled trials (RCTs) comparing the impact of Endocuff+AI versus AI alone on colorectal neoplasia detection. Primary outcome was ADR; secondary outcomes included advanced adenoma detection rate (AADR), sessile serrated lesion detection rate (SSLDR), cecal intubation time, and withdrawal time. Pooled risk ratios (RRs) and mean differences (MDs) with 95% confidence intervals (CIs) were calculated using a random-effects model. Results: Three RCTs with 2404 subjects were included (n = 1198 Endocuff+AI vs. n = 1206 AI alone). ADR was significantly higher in the Endocuff+AI group than in the AI alone group (54% vs. 48%, respectively) (RR 1.12, 95% CI 1.03-1.21, P = 0.01, I 2 = 0%). There was a trend toward higher AADR (12.3% vs. 10%, RR 1.23, 95% CI 0.96-1.59, P = 0.10, I 2 = 17%) and SSLDR (17.6% vs. 15.5%, RR 1.16, 95% CI 0.96-1.40, P = 0.13, I 2 = 0%) in the Endocuff+AI group compared with the AI alone group, but it did not reach statistical significance. Both cecal intubation time (MD -0.61 minutes; 95% CI -1.54-0.33; P = 0.20; I 2 = 87%) and withdrawal time (MD -0.42 minutes; 95% CI -1.01-0.17; P = 0.17, I 2 = 60%) were similar between the two groups. Conclusions: Endocuff combined with AI was superior to AI alone in improving the adenoma detection rate without increasing intubation or withdrawal times.