Artificial intelligence and colonoscopy experience: lessons from two randomised trials

Abstract

Background and aimsArtificial 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).MethodsIn 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.ResultsIn 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.ConclusionsIn 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 numberNCT:04260321.

Efficacy of a computer-aided detection system in a fecal immunochemical test-based organized colorectal cancer screening program: a randomized controlled trial (AIFIT study)

“…CADe seems to be effective in increasing adenoma detection regardless of the endoscopist's expertise, confirming a previous observation comparing experts and non-expert endoscopists [11].…”

“…The main distinctive feature of our study is represented by the study setting. Although recent randomized trials have demonstrated the effectiveness of CADe systems in patients undergoing colonoscopy for mixed indications 8 24 , data in FIT + patients are limited by underpowered subgroup analyses 7 11 . The population-based organized FIT-based CRC screening program is a unique setting as the population included has a high prevalence of precancerous lesions and endoscopists’ participation in the screening program is dependent on a high ADR, which is continuously monitored and audited.…”

How can we improve our operation?

“…

We read the study conducted by Zippelius et al [1] with great interest and thank the authors for revealing a comparable noninferior performance between an artificial intelligence (AI) system and endoscopists. Although the test in a hospital independent of the system development provides validation evidence, unlike other high-quality trials with larger sample sizes and different clinic levels, this research did not detect different performance [2][3][4][5]. To maximize the confidence of the comparison, we would like to get a closer look at the study and make some comments.

…”

PEACE: Perception and Expectations toward Artificial Intelligence in Capsule Endoscopy

“…Artificial intelligence (AI) is a disruptive technology, especially in medical image analysis [ 1 , 2 ]. AI is already assisting physicians in various clinical tasks and has shown promising results especially in digestive endoscopy [ 3 , 4 , 5 ]. To support and promote this technological innovation, the European Society of Gastrointestinal Endoscopy (ESGE) “suggests the possible incorporation of computer-aided diagnosis (CADx) to colonoscopy” [ 6 ].…”