Shaukat Aasma, Colucci Daniel, Erisson Lavi, Phillips Sloane, Ng Jonathan, Iglesias Juan Eugenio, Saltzman John R, Somers Samuel, Brugge William
University of Minnesota - GI, Minneapolis, Minnesota, United States.
Iterative Scopes, Cambridge, Massachusetts, United States.
Endosc Int Open. 2021 Feb;9(2):E263-E270. doi: 10.1055/a-1321-1317. Epub 2021 Feb 3.
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. 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. 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 ( = 0.028) and 53.6 % and 30.8 %, respectively, in screening exams ( = 0.024). Overall, APC rate with and without Skout was 1.46 and 1.01, respectively, ( = 0.104) and 1.18 and 0.50, respectively, in screening exams ( = 0.002). Overall, true histology rate (THR) with and without Skout was 73.8 % and 78.4 %, respectively, ( = 0.463) and 75.0 % and 71.0 %, respectively, in screening exams ( = 0.731). 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.
检测结直肠肿瘤是高质量筛查和监测结肠镜检查的目标，高腺瘤检出率（ADR）和每次结肠镜检查的腺瘤数（APC）反映了这一点。我们研究的目的是评估一种新型人工智能（AI）辅助息肉检测设备Skout在常规结肠镜检查中以ADR和APC作为主要终点的性能。我们比较了一组接受常规高分辨率结肠镜检查的门诊患者在使用和不使用实时AI辅助息肉检测设备情况下的ADR和APC。使用Skout进行结肠镜检查的患者被纳入一项单臂、非盲、前瞻性试验，并将结果与一个历史队列进行比较。所有切除的息肉均进行组织学检查。83例在门诊内镜中心接受筛查和监测结肠镜检查的患者被纳入研究，并将结果与283例历史对照患者进行比较。总体而言，使用和不使用Skout时的ADR分别为54.2%和40.6%（P = 0.028），在筛查检查中分别为53.6%和30.8%（P = 0.024）。总体而言，使用和不使用Skout时的APC率在筛查检查中分别为1.46和1.01（P = 0.104），以及1.18和0.50（P = 0.002）。总体而言，使用和不使用Skout时的真实组织学率（THR）在筛查检查中分别为73.8%和78.4%（P = 0.463），以及75.0%和71.0%（P = 0.731）。我们已经证明，我们的新型AI辅助息肉检测设备在一组接受筛查和监测结肠镜检查患者中提高了ADR，同时增生性息肉切除率没有显著增加。AI辅助结肠镜检查有可能改善接受结肠镜检查患者的结局。
