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In Gut ; h5-index 124.0

BACKGROUND AND AIMS : Artificial intelligence has been shown to increase adenoma detection rate (ADR) as the main surrogate outcome parameter of colonoscopy quality. To which extent this effect may be related to physician experience is not known. We performed a randomised trial with colonoscopists in their qualification period (AID-2) and compared these data with a previously published randomised trial in expert endoscopists (AID-1).

METHODS : In this prospective, randomised controlled non-inferiority trial (AID-2), 10 non-expert endoscopists (<2000 colonoscopies) performed screening/surveillance/diagnostic colonoscopies in consecutive 40-80 year-old subjects using high-definition colonoscopy with or without a real-time deep-learning computer-aided detection (CADe) (GI Genius, Medtronic). The primary outcome was ADR in both groups with histology of resected lesions as reference. In a post-hoc analysis, data from this randomised controlled trial (RCT) were compared with data from the previous AID-1 RCT involving six experienced endoscopists in an otherwise similar setting.

RESULTS : In 660 patients (62.3±10 years; men/women: 330/330) with equal distribution of study parameters, overall ADR was higher in the CADe than in the control group (53.3% vs 44.5%; relative risk (RR): 1.22; 95% CI: 1.04 to 1.40; p<0.01 for non-inferiority and p=0.02 for superiority). Similar increases were seen in adenoma numbers per colonoscopy and in small and distal lesions. No differences were observed with regards to detection of non-neoplastic lesions. When pooling these data with those from the AID-1 study, use of CADe (RR 1.29; 95% CI: 1.16 to 1.42) and colonoscopy indication, but not the level of examiner experience (RR 1.02; 95% CI: 0.89 to 1.16) were associated with ADR differences in a multivariate analysis.

CONCLUSIONS : In less experienced examiners, CADe assistance during colonoscopy increased ADR and a number of related polyp parameters as compared with the control group. Experience appears to play a minor role as determining factor for ADR.


Repici Alessandro, Spadaccini Marco, Antonelli Giulio, Correale Loredana, Maselli Roberta, Galtieri Piera Alessia, Pellegatta Gaia, Capogreco Antonio, Milluzzo Sebastian Manuel, Lollo Gianluca, Di Paolo Dhanai, Badalamenti Matteo, Ferrara Elisa, Fugazza Alessandro, Carrara Silvia, Anderloni Andrea, Rondonotti Emanuele, Amato Arnaldo, De Gottardi Andrea, Spada Cristiano, Radaelli Franco, Savevski Victor, Wallace Michael B, Sharma Prateek, Rösch Thomas, Hassan Cesare


adenoma, artificial Intelligence, colonoscopy, colorectal cancer, screening