Artificial intelligence-assisted colonoscopy for colorectal cancer screening: a multicenter randomized controlled trial
Abstract
BACKGROUND
Artificial intelligence (AI)-assisted colonoscopy improves polyp detection and characterization in colonoscopy. However, data from large scale multicenter randomized controlled trials (RCT) in an asymptomatic population are lacking.
METHODS
This multicenter RCT aimed to compare AI-assisted colonoscopy (AI) to conventional colonoscopy (CC) for adenoma detection in an asymptomatic population. Asymptomatic subjects aged 45 to 75 years undergoing colorectal cancer screening by direct colonoscopy or fecal immunochemical test (FIT) were recruited in 6 referral centers in Hong Kong, Jilin, Inner Mongolia, Xiamen and Beijing. In the AI group, an AI polyp detection system (Eagle-Eye, Xiamen InnoVision) with real time notification on the same monitor of the endoscopy system was used. Primary outcome was overall adenoma detection rate (ADR). Secondary outcomes were mean number of adenomas per colonoscopy (APC), ADR according to endoscopist's experience, and colonoscopy withdrawal time. This study received IRB approval (CRE-2019.393).
RESULTS
From November 2019 to August 2021, 3059 subjects were randomized to AI (1519) and CC (1540). Baseline characteristics and bowel preparation quality between the two groups were similar. The overall ADR (39.9% vs 32.4%, p<0.001), Advanced ADR (6.6% vs 4.9%, P=0.041), ADR of expert (42.3% vs 32.8%, p<0.001) and non-expert endoscopists (37.5% vs 32.1%, p=0.023) and APC (0.59+/-0.97 vs 0.45+/-0.81, p<0.001) were all significantly higher in AI…
How strong is the evidence?
Evidence Hub reads this as a randomized trial, done in people. Its evidence level is 2 of 5 (High · randomized trial). Randomized trials of a reasonable size are the strongest single-study design.
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