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Abstract
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.
Trial registration number NCT:04260321.
- colonoscopy
- adenoma
- artificial Intelligence
- colorectal cancer
- screening
Data availability statement
Data are available upon reasonable request.
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Data availability statement
Data are available upon reasonable request.
Footnotes
Twitter @adegottardi
Contributors AR, MS and CH designed the study and drafted the manuscript. LC performed statistical analysis. AR, MS, GA, RM, PAG, AC, SMM, GL, MB, EF, AF, SC, AAn, AAm, ADG, CS, FR and CH recruited patients, performed colonoscopy procedures and/or participated in the data collection. MBW, PS, VS and TR critically revised the draft for important intellectual content. All the authors revised and approved the final manuscript.
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests Conflict of interest statement/disclosure(s): All authors for equipment loan by Medtronic. AR and CH received consultancy fee from Medtronic. MBW provides consulting activity to Medtronic and Cosmo on behalf of Mayo Clinic and has equity interest in Virgo.
Provenance and peer review Not commissioned; externally peer reviewed.
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