TY - JOUR
T1 - Artificial intelligence and colonoscopy experience
T2 - Lessons from two randomised trials
AU - Repici, Alessandro
AU - Spadaccini, Marco
AU - Antonelli, Giulio
AU - Correale, Loredana
AU - Maselli, Roberta
AU - Galtieri, Piera Alessia
AU - Pellegatta, Gaia
AU - Capogreco, Antonio
AU - Milluzzo, Sebastian Manuel
AU - Lollo, Gianluca
AU - Di Paolo, Dhanai
AU - Badalamenti, Matteo
AU - Ferrara, Elisa
AU - Fugazza, Alessandro
AU - Carrara, Silvia
AU - Anderloni, Andrea
AU - Rondonotti, Emanuele
AU - Amato, Arnaldo
AU - De Gottardi, Andrea
AU - Spada, Cristiano
AU - Radaelli, Franco
AU - Savevski, Victor
AU - Wallace, Michael B.
AU - Sharma, Prateek
AU - Rösch, Thomas
AU - Hassan, Cesare
N1 - Publisher Copyright:
©
PY - 2022/4/1
Y1 - 2022/4/1
N2 - 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.
AB - 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.
KW - adenoma
KW - artificial Intelligence
KW - colonoscopy
KW - colorectal cancer
KW - screening
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U2 - 10.1136/gutjnl-2021-324471
DO - 10.1136/gutjnl-2021-324471
M3 - Article
C2 - 34187845
AN - SCOPUS:85108978872
SN - 0017-5749
VL - 71
SP - 757
EP - 765
JO - Gut
JF - Gut
IS - 4
ER -