Computer-Aided Detection Improves Adenomas per Colonoscopy for Screening and Surveillance Colonoscopy: A Randomized Trial.

BACKGROUND & AIMS: Colonoscopy for colorectal cancer screening is endoscopist dependent, and colonoscopy quality improvement programs aim to improve efficacy. This study evaluated the clinical benefit and safety of using a computer-aided detection (CADe) device in colonoscopy procedures. METHODS: This randomized study prospectively evaluated the use of a CADe device at 5 academic and community centers by US board-certified gastroenterologists (n = 22). Participants aged ≥40 scheduled for screening or surveillance (≥3 years) colonoscopy were included; exclusion criteria included incomplete procedure, diagnostic indication, inflammatory bowel disease, and familial adenomatous polyposis. Patients were randomized by endoscopist to the standard or CADe colonoscopy arm using computer-generated, random-block method. The 2 primary endpoints were adenomas per colonoscopy (APC), the total number of adenomas resected divided by the total number of colonoscopies; and true histology rate (THR), the proportion of resections with clinically significant histology divided by the total number of polyp resections. The primary analysis used a modified intention-to-treat approach. RESULTS: Between January and September 2021, 1440 participants were enrolled to be randomized. After exclusion of participants who did not meet the eligibility criteria, 677 in the standard arm and 682 in the CADe arm were included in a modified intention-to-treat analysis. APC increased significantly with use of the CADe device (standard vs CADe: 0.83 vs 1.05, P = .002; total number of adenomas, 562 vs 719). There was no decrease in THR with use of the CADe device (standard vs CADe: 71.7% vs 67.4%, P for noninferiority < .001; total number of non-neoplastic lesions, 284 vs 375). Adenoma detection rate was 43.9% and 47.8% in the standard and CADe arms, respectively (P = .065). CONCLUSIONS: For experienced endoscopists performing screening and surveillance colonoscopies in the United States, the CADe device statistically improved overall adenoma detection (APC) without a concomitant increase in resection of non-neoplastic lesions (THR). CLINICALTRIALS: gov registration: NCT04754347.

Improvement in adenoma detection using a novel artificial intelligence-aided polyp detection device.

Background and study aims Detecting colorectal neoplasia is the goal of high-quality screening and surveillance colonoscopy, as reflected by high adenoma detection rate (ADR) and adenomas per colonoscopy (APC). The aim of our study was to evaluate the performance of a novel artificial intelligence (AI)-aided polyp detection device, Skout, with the primary endpoints of ADR and APC in routine colonoscopy. Patients and methods We compared ADR and APC in a cohort of outpatients undergoing routine high-resolution colonoscopy with and without the use of a real-time, AI-aided polyp detection device. Patients undergoing colonoscopy with Skout were enrolled in a single-arm, unblinded, prospective trial and the results were compared with a historical cohort. All resected polyps were examined histologically. Results Eighty-three patients undergoing screening and surveillance colonoscopy at an outpatient endoscopy center were enrolled and outcomes compared with 283 historical control patients. Overall, ADR with and without Skout was 54.2 % and 40.6 % respectively ( P  = 0.028) and 53.6 % and 30.8 %, respectively, in screening exams ( P  = 0.024). Overall, APC rate with and without Skout was 1.46 and 1.01, respectively, ( P  = 0.104) and 1.18 and 0.50, respectively, in screening exams ( P  = 0.002). Overall, true histology rate (THR) with and without Skout was 73.8 % and 78.4 %, respectively, ( P  = 0.463) and 75.0 % and 71.0 %, respectively, in screening exams ( P  = 0.731). Conclusion We have demonstrated that our novel AI-aided polyp detection device increased the ADR in a cohort of patients undergoing screening and surveillance colonoscopy without a significant concomitant increase in hyperplastic polyp resection. AI-aided colonoscopy has the potential for improving the outcomes of patients undergoing colonoscopy.