Role of Artificial Intelligence in Colonoscopy Detection of Advanced Neoplasias : A Randomized Trial

Abstract

Background: The role of computer-aided detection in identifying advanced colorectal neoplasia is unknown.

Objective: To evaluate the contribution of computer-aided detection to colonoscopic detection of advanced colorectal neoplasias as well as adenomas, serrated polyps, and nonpolypoid and right-sided lesions.

Design: Multicenter, parallel, randomized controlled trial. (ClinicalTrials.gov: NCT04673136).

Setting: Spanish colorectal cancer screening program.

Participants: 3213 persons with a positive fecal immunochemical test.

Intervention: Enrollees were randomly assigned to colonoscopy with or without computer-aided detection.

Measurements: Advanced colorectal neoplasia was defined as advanced adenoma and/or advanced serrated polyp.

Results: The 2 comparison groups showed no significant difference in advanced colorectal neoplasia detection rate (34.8% with intervention vs. 34.6% for controls; adjusted risk ratio [aRR], 1.01 [95% CI, 0.92 to 1.10]) or the mean number of advanced colorectal neoplasias detected per colonoscopy (0.54 [SD, 0.95] with intervention vs. 0.52 [SD, 0.95] for controls; adjusted rate ratio, 1.04 [99.9% CI, 0.88 to 1.22]). Adenoma detection rate also did not differ (64.2% with intervention vs. 62.0% for controls; aRR, 1.06 [99.9% CI, 0.91 to 1.23]). Computer-aided detection increased the mean number of nonpolypoid lesions (0.56 [SD, 1.25] vs. 0.47 [SD, 1.18] for controls; adjusted rate ratio, 1.19 [99.9% CI, 1.01 to 1.41]), proximal adenomas (0.94 [SD, 1.62] vs. 0.81 [SD, 1.52] for controls; adjusted rate ratio, 1.17 [99.9% CI, 1.03 to 1.33]), and lesions of 5 mm or smaller (polyps in general and adenomas and serrated lesions in particular) detected per colonoscopy.

Limitations: The high adenoma detection rate in the control group may limit the generalizability of the findings to endoscopists with low detection rates.

Conclusion: Computer-aided detection did not improve colonoscopic identification of advanced colorectal neoplasias.

Primary funding source: Medtronic.