Artificial intelligence and colonoscopy experience: lessons from two randomised trials

被引:147
作者
Repici, Alessandro [1 ,2 ]
Spadaccini, Marco [1 ,2 ]
Antonelli, Giulio [3 ,4 ]
Correale, Loredana [2 ]
Maselli, Roberta [1 ,2 ]
Galtieri, Piera Alessia [2 ]
Pellegatta, Gaia [2 ]
Capogreco, Antonio [1 ,2 ]
Milluzzo, Sebastian Manuel [5 ]
Lollo, Gianluca [6 ]
Di Paolo, Dhanai [7 ]
Badalamenti, Matteo [2 ]
Ferrara, Elisa [2 ]
Fugazza, Alessandro [2 ]
Carrara, Silvia [2 ]
Anderloni, Andrea [2 ]
Rondonotti, Emanuele [7 ]
Amato, Arnaldo [7 ]
De Gottardi, Andrea [6 ]
Spada, Cristiano [5 ]
Radaelli, Franco [7 ]
Savevski, Victor [8 ]
Wallace, Michael B. [9 ]
Sharma, Prateek [10 ,11 ]
Roesch, Thomas [12 ]
Hassan, Cesare [3 ]
机构
[1] Humanitas Univ, Dept Biomed Sci, Milan, Italy
[2] IRCCS, Endoscopy Unit, Humanitas Clin & Res Ctr, Rozzano, Italy
[3] Osped Nuovo Regina Margherita, Gastroenterol & Digest Endoscopy Unit, Rome, Italy
[4] Sapienza Univ Rome, Dept Translat & Precis Med, Rome, Italy
[5] Poliambulanza Brescia Hosp, Digest Endoscopy Unit, Brescia, Lombardia, Italy
[6] Univ Svizzera Italiana, Dept Gastroenterol & Hepatol, Lugano, Switzerland
[7] Valduce Hosp, Div Digest Endoscopy & Gastroenterol, Como, Italy
[8] IRCCS, Humanitas Clin & Res Ctr, Artificial Intelligence Res, Rozzano, Italy
[9] Mayo Clin, Endoscopy Unit, Jacksonville, FL 32224 USA
[10] Univ Kansas, Kansas City, KS USA
[11] Univ Kansas, Endoscopy Unit, Kansas City, KS USA
[12] Univ Hosp Hamburg Eppendorf, Interdisciplinary Endoscopy, Hamburg, Germany
关键词
colonoscopy; adenoma; artificial Intelligence; colorectal cancer; screening; COMPUTER-AIDED DETECTION; ADENOMA DETECTION; DETECTION RATES; QUALITY INDICATORS; COLORECTAL-CANCER; SCREENING-PROGRAM; PERFORMANCE; COMPETENCE; SYSTEM; TRENDS;
D O I
10.1136/gutjnl-2021-324471
中图分类号
R57 [消化系及腹部疾病];
学科分类号
摘要
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.
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页码:757 / 765
页数:9
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