Showa University Northern Yokohama Hospital, Yokohama, Japan (Y.M., S.K., M.M., F.U., S.K., Y.O., Y.M., K.T., H.N., K.I., T.K., T.H., K.W., F.I.).
National Cancer Center Hospital, Tokyo, Japan (Y.S.).
Ann Intern Med. 2018 Sep 18;169(6):357-366. doi: 10.7326/M18-0249. Epub 2018 Aug 14.
Computer-aided diagnosis (CAD) for colonoscopy may help endoscopists distinguish neoplastic polyps (adenomas) requiring resection from nonneoplastic polyps not requiring resection, potentially reducing cost.
To evaluate the performance of real-time CAD with endocytoscopes (×520 ultramagnifying colonoscopes providing microvascular and cellular visualization of colorectal polyps after application of the narrow-band imaging [NBI] and methylene blue staining modes, respectively).
Single-group, open-label, prospective study. (UMIN [University hospital Medical Information Network] Clinical Trial Registry: UMIN000027360).
University hospital.
791 consecutive patients undergoing colonoscopy and 23 endoscopists.
Real-time use of CAD during colonoscopy.
CAD-predicted pathology (neoplastic or nonneoplastic) of detected diminutive polyps (≤5 mm) on the basis of real-time outputs compared with pathologic diagnosis of the resected specimen (gold standard). The primary end point was whether CAD with the stained mode produced a negative predictive value (NPV) of 90% or greater for identifying diminutive rectosigmoid adenomas, the threshold required to "diagnose-and-leave" nonneoplastic polyps. Best- and worst-case scenarios assumed that polyps lacking either CAD diagnosis or pathology were true- or false-positive or true- or false-negative, respectively.
Overall, 466 diminutive (including 250 rectosigmoid) polyps from 325 patients were assessed by CAD, with a pathologic prediction rate of 98.1% (457 of 466). The NPVs of CAD for diminutive rectosigmoid adenomas were 96.4% (95% CI, 91.8% to 98.8%) (best-case scenario) and 93.7% (CI, 88.3% to 97.1%) (worst-case scenario) with stained mode and 96.5% (CI, 92.1% to 98.9%) (best-case scenario) and 95.2% (CI, 90.3% to 98.0%) (worst-case scenario) with NBI.
Two thirds of the colonoscopies were conducted by experts who had each experienced more than 200 endocytoscopies; 186 polyps not assessed by CAD were excluded.
Real-time CAD can achieve the performance level required for a diagnose-and-leave strategy for diminutive, nonneoplastic rectosigmoid polyps.
Japan Society for the Promotion of Science.
结肠镜检查的计算机辅助诊断（CAD）可以帮助内镜医生区分需要切除的肿瘤性息肉（腺瘤）和不需要切除的非肿瘤性息肉，从而降低成本。
评估实时 CAD 与内镜的性能，这些内镜是指 520 倍超微结肠镜，在应用窄带成像（NBI）和亚甲蓝染色模式后，分别提供结直肠息肉的微血管和细胞可视化。
单组、开放标签、前瞻性研究。（UMIN [大学医院医疗信息网络]临床试验注册：UMIN000027360）。
大学医院。
791 名连续接受结肠镜检查的患者和 23 名内镜医生。
在结肠镜检查中实时使用 CAD。
根据实时输出，CAD 预测检测到的微小息肉（≤5mm）的病理（肿瘤性或非肿瘤性），并与切除标本的病理诊断（金标准）进行比较。主要终点是染色模式下的 CAD 是否能为识别微小直肠乙状结肠腺瘤提供 90%或更高的阴性预测值（NPV），这是“诊断并留下”非肿瘤性息肉的阈值。最佳和最差情况假设分别为缺乏 CAD 诊断或病理学的息肉为真阳性或假阳性、真阴性或假阴性。
总体而言，325 名患者的 466 个微小（包括 250 个直肠乙状结肠）息肉由 CAD 评估，其病理预测率为 98.1%（457/466）。CAD 对微小直肠乙状结肠腺瘤的 NPV 分别为 96.4%（95%CI，91.8%至 98.8%）（最佳情况）和 93.7%（CI，88.3%至 97.1%）（最差情况），染色模式为 96.5%（95%CI，92.1%至 98.9%）（最佳情况）和 95.2%（CI，90.3%至 98.0%）（最差情况），NBI 为 96.5%（95%CI，92.1%至 98.9%）（最佳情况）和 95.2%（CI，90.3%至 98.0%）（最差情况）。
三分之二的结肠镜检查由经验丰富的专家进行，他们每人都进行了 200 多次内镜检查；186 个未用 CAD 评估的息肉被排除在外。
实时 CAD 可以达到诊断并留下微小、非肿瘤性直肠乙状结肠息肉的策略所需的性能水平。
日本科学促进会。
