Artificial intelligence–assisted colonoscopy for adenoma and polyp detection: an updated systematic review and meta-analysis

Background and Aims

There is a growing interest in the role of artificial intelligence in colonoscopy. The aim of this systematic review and meta-analysis was to evaluate the efficacy of computer-aided detection (CADe) of colorectal adenomas and polyps.

Methods

The MEDLINE, Embase, and Cochrane Central of Controlled Trials (from inception to December 2022) databases were searched for randomized controlled trials comparing colonoscopy with CADe versus standard colonoscopy (SC). We performed a random-effects meta-analysis and reported the results as relative risks (RRs) or mean difference with 95% confidence intervals (CIs).

Results

Twelve randomized controlled trials comprising 11,340 patients were included in the final analysis. The pooled adenoma detection rate was significantly higher in the CADe group compared with the SC group (41.4% vs 33%; RR, 1.26; 95% CI, 1.18-1.35). CADe increased the detection of adenomas regardless of their size (≤5 mm [RR, 1.56; 95% CI, 1.38-1.77], 6-9 mm [RR, 1.24; 95% CI, 1.05-1.47], and ≥10 mm [RR, 1.30; 95% CI, 1.11-1.53]), location (proximal colon [RR, 1.41; 95% CI, 1.26-1.58] and distal colon [RR, 1.44; 95% 1.29-1.61]), or morphology (polypoid [RR, 1.35; 95% CI, 1.17-1.56] and nonpolypoid [RR, 1.55; 95% CI, 1.25-1.93]). There was no difference between the CADe and SC groups in detecting advanced adenomas or sessile serrated lesions. Colonoscopy withdrawal time was longer in the CADe group compared with the SC group (mean difference, .34 minute; 95% CI, .17-.51).

Conclusions

Using CADe during colonoscopy is associated with a significant increase in adenoma detection rate and adenomas per colonoscopy, mainly due to the increased detection of diminutive adenomas.