Use of a Novel Artificial Intelligence System Leads to the Detection of Significantly Higher Number of Adenomas During Screening and Surveillance Colonoscopy: Results From a Large, Prospective, US Multicenter, Randomized Clinical Trial.

Autor:	Desai M; Department of Gastroenterology, Kansas City VA Medical Center, Kansas City, Missouri, USA., Ausk K; Gastroenterology, Swedish Health and Swedish Medical Center, Seattle, Washington, USA., Brannan D; Gastroenterology, Swedish Health and Swedish Medical Center, Seattle, Washington, USA., Chhabra R; Department of Gastroenterology, Saint Luke's Hospital of Kansas City, Kansas City, Missouri, USA., Chan W; Division of Gastroenterology, Hepatology and Endoscopy, Brigham and Women's Hospital, Boston, Massachusetts, USA., Chiorean M; Gastroenterology, Swedish Health and Swedish Medical Center, Seattle, Washington, USA., Gross SA; Gastroenterology, New York University Langone Health, New York, New York, USA., Girotra M; Gastroenterology, Swedish Health and Swedish Medical Center, Seattle, Washington, USA., Haber G; Gastroenterology, New York University Langone Health, New York, New York, USA., Hogan RB; GI Associates and Endoscopy Center, Jackson, Mississippi, USA., Jacob B; Gastroenterology, Largo Medical Center, Largo, Florida, USA., Jonnalagadda S; Department of Gastroenterology, Saint Luke's Hospital of Kansas City, Kansas City, Missouri, USA., Iles-Shih L; Gastroenterology, Swedish Health and Swedish Medical Center, Seattle, Washington, USA., Kumar N; Division of Gastroenterology, Hepatology and Endoscopy, Brigham and Women's Hospital, Boston, Massachusetts, USA., Law J; Gastroenterology, Virginia Mason Franciscan Health, Seattle, Washington, USA., Lee L; Division of Gastroenterology, Hepatology and Endoscopy, Brigham and Women's Hospital, Boston, Massachusetts, USA., Lin O; Gastroenterology, Virginia Mason Franciscan Health, Seattle, Washington, USA., Mizrahi M; Gastroenterology, Largo Medical Center, Largo, Florida, USA., Pacheco P; Gastroenterology, New York University Langone Health, New York, New York, USA., Parasa S; Gastroenterology, Swedish Health and Swedish Medical Center, Seattle, Washington, USA., Phan J; Departement of Gastroenterology, Keck Medicine University of Southern California, Los Angeles, California, USA., Reeves V; GI Associates and Endoscopy Center, Jackson, Mississippi, USA., Sethi A; Department of Gastroenterology, Columbia University Irving Medical Center, New York, New York, USA., Snell D; Gastroenterology, New York University Langone Health, New York, New York, USA., Underwood J; GI Associates and Endoscopy Center, Jackson, Mississippi, USA., Venu N; Gastroenterology, Virginia Mason Franciscan Health, Seattle, Washington, USA., Visrodia K; Department of Gastroenterology, Columbia University Irving Medical Center, New York, New York, USA., Wong A; Gastroenterology, Swedish Health and Swedish Medical Center, Seattle, Washington, USA., Winn J; Department of Gastroenterology, Kansas City VA Medical Center, Kansas City, Missouri, USA., Wright CH; GI Associates and Endoscopy Center, Jackson, Mississippi, USA., Sharma P; Department of Gastroenterology, Kansas City VA Medical Center, Kansas City, Missouri, USA.
Jazyk:	angličtina
Zdroj:	The American journal of gastroenterology [Am J Gastroenterol] 2024 Jul 01; Vol. 119 (7), pp. 1383-1391. Date of Electronic Publication: 2024 Jan 18.
DOI:	10.14309/ajg.0000000000002664
Abstrakt:	Introduction: Adenoma per colonoscopy (APC) has recently been proposed as a quality measure for colonoscopy. We evaluated the impact of a novel artificial intelligence (AI) system, compared with standard high-definition colonoscopy, for APC measurement. Methods: This was a US-based, multicenter, prospective randomized trial examining a novel AI detection system (EW10-EC02) that enables a real-time colorectal polyp detection enabled with the colonoscope (CAD-EYE). Eligible average-risk subjects (45 years or older) undergoing screening or surveillance colonoscopy were randomized to undergo either CAD-EYE-assisted colonoscopy (CAC) or conventional colonoscopy (CC). Modified intention-to-treat analysis was performed for all patients who completed colonoscopy with the primary outcome of APC. Secondary outcomes included positive predictive value (total number of adenomas divided by total polyps removed) and adenoma detection rate. Results: In modified intention-to-treat analysis, of 1,031 subjects (age: 59.1 ± 9.8 years; 49.9% male), 510 underwent CAC vs 523 underwent CC with no significant differences in age, gender, ethnicity, or colonoscopy indication between the 2 groups. CAC led to a significantly higher APC compared with CC: 0.99 ± 1.6 vs 0.85 ± 1.5, P = 0.02, incidence rate ratio 1.17 (1.03-1.33, P = 0.02) with no significant difference in the withdrawal time: 11.28 ± 4.59 minutes vs 10.8 ± 4.81 minutes; P = 0.11 between the 2 groups. Difference in positive predictive value of a polyp being an adenoma among CAC and CC was less than 10% threshold established: 48.6% vs 54%, 95% CI -9.56% to -1.48%. There were no significant differences in adenoma detection rate (46.9% vs 42.8%), advanced adenoma (6.5% vs 6.3%), sessile serrated lesion detection rate (12.9% vs 10.1%), and polyp detection rate (63.9% vs 59.3%) between the 2 groups. There was a higher polyp per colonoscopy with CAC compared with CC: 1.68 ± 2.1 vs 1.33 ± 1.8 (incidence rate ratio 1.27; 1.15-1.4; P < 0.01). Discussion: Use of a novel AI detection system showed to a significantly higher number of adenomas per colonoscopy compared with conventional high-definition colonoscopy without any increase in colonoscopy withdrawal time, thus supporting the use of AI-assisted colonoscopy to improve colonoscopy quality ( ClinicalTrials.gov NCT04979962). (Copyright © 2024 by The American College of Gastroenterology.)
Databáze:	MEDLINE
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