Artificial Intelligence-Assisted Colonoscopy for Detection of Colon Polyps: a Prospective, Randomized Cohort Study

• DOI: 10.1007/s11605-020-04802-4
• Publication Date: 2020-09-23T19:03:47Z
• Authors: Yuchen Luo; Yi Zhang; Ming Liu; Yihong Lai; Panpan Liu; Zhen Wang; Tongyin Xing; Ying Huang; Yue Li; Aiming Li; Yadong Wang; Xiaobei Luo; Side Liu; Zelong Han
• Keywords: Colon; Colonic Polyps; Colonoscopy; 3. Good health; Cohort Studies; 03 medical and health sciences; 0302 clinical medicine; Artificial Intelligence; Humans; Original Article; Prospective Studies; Colorectal Neoplasms; Follow-Up Studies

Improving the rate of polyp detection is an important measure to prevent colorectal cancer (CRC). Real-time automatic polyp detection systems, through deep learning methods, can learn and perform specific endoscopic tasks previously performed by endoscopists. The purpose of this study was to explore whether a high-performance, real-time automatic polyp detection system could improve the polyp detection rate (PDR) in the actual clinical environment.The selected patients underwent same-day, back-to-back colonoscopies in a random order, with either traditional colonoscopy or artificial intelligence (AI)-assisted colonoscopy performed first by different experienced endoscopists (> 3000 colonoscopies). The primary outcome was the PDR. It was registered with clinicaltrials.gov . (NCT047126265).In this study, we randomized 150 patients. The AI system significantly increased the PDR (34.0% vs 38.7%, p < 0.001). In addition, AI-assisted colonoscopy increased the detection of polyps smaller than 6 mm (69 vs 91, p < 0.001), but no difference was found with regard to larger lesions.A real-time automatic polyp detection system can increase the PDR, primarily for diminutive polyps. However, a larger sample size is still needed in the follow-up study to further verify this conclusion.clinicaltrials.gov Identifier: NCT047126265.