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首页> 外文期刊>Annals of Internal Medicine >Real-Time Use of Artificial Intelligence in Identification of Diminutive Polyps During Colonoscopy: A Prospective Study.
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Real-Time Use of Artificial Intelligence in Identification of Diminutive Polyps During Colonoscopy: A Prospective Study.

机译:在结肠透视技术期间,实时使用人工智能识别小息肉:前瞻性研究。

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摘要

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.
机译:用于结肠镜检查的计算机辅助诊断(CAD)可以帮助内窥镜息镜分辨率区分肿瘤息肉(腺瘤)需要从不需要切除的非润肤息肉中切除的肿瘤息肉(腺瘤),可能降低成本。为了评估实时CAD与内镜(×520超声镜张相镜检查的实时CAD分别在施用窄带成像[NBI]和亚甲基蓝染色模式后提供微血管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]临床试验登记处:UMIN000027360)。大学医院。 791连续患者接受结肠镜检查和23位内窥镜师。在结肠镜检查期间实时使用CAD。基于实时输出的检测到的小息肉(≤5mm)的CAD预测病理(肿瘤或非脂肪塑料)与切除试样的病理诊断(金标准)进行了实时输出。主要终点是CAD是否具有染色模式的负面预测值(NPV)90%或更高,用于鉴定小直粒异常腺瘤,“诊断和留下”非宝洁息肉所需的阈值。最佳和最差别的情况,假设缺乏CAD诊断或病理学的息肉分别是真实的或假阳性或真实的或假阴性的。总体而言,CAD评估了来自325名患者的466例(包括250例矫肌)息肉,病理预测率为98.1%(457例466)。对于小直粒剂腺瘤的CAD的NPV为96.4%(95%CI,91.8%至98.8%)(最佳情况情况)和93.7%(CI,88.3%至97.1%)(最差的情况),具有染色模式和96.5%(CI,92.1%至98.9%)(最佳案例方案)和95.2%(CI,90.3%至98.0%)(最差的情况),具有NBI。由每个经验丰富的200多内织形镜下的专家进行三分之二的结肠镜检查; CAD未评估的186个息肉被排除在外。实时CAD可以实现诊断和留下策略的性能水平,用于小型非塑料直肠果皮息肉息肉。日本科学促进学会。

著录项

  • 来源
    《Annals of Internal Medicine》 |2018年第6期|共10页
  • 作者单位

    Showa University Northern Yokohama Hospital Yokohama Japan (Y.M. S.K. M.M. F.U. S.K. Y.O. Y;

    Showa University Northern Yokohama Hospital Yokohama Japan (Y.M. S.K. M.M. F.U. S.K. Y.O. Y;

    Showa University Northern Yokohama Hospital Yokohama Japan (Y.M. S.K. M.M. F.U. S.K. Y.O. Y;

    National Cancer Center Hospital Tokyo Japan (Y.S.);

    National Cancer Center Hospital East Kashiwa Japan (H.I.);

    Shizuoka Cancer Center Shizuoka Japan (K.H.);

    Tokyo Medical and Dental University Tokyo Japan (K.O.);

    Showa University Northern Yokohama Hospital Yokohama Japan (Y.M. S.K. M.M. F.U. S.K. Y.O. Y;

    Showa University Northern Yokohama Hospital Yokohama Japan (Y.M. S.K. M.M. F.U. S.K. Y.O. Y;

    Showa University Northern Yokohama Hospital Yokohama Japan (Y.M. S.K. M.M. F.U. S.K. Y.O. Y;

    Showa University Northern Yokohama Hospital Yokohama Japan (Y.M. S.K. M.M. F.U. S.K. Y.O. Y;

    Showa University Northern Yokohama Hospital Yokohama Japan (Y.M. S.K. M.M. F.U. S.K. Y.O. Y;

    Showa University Northern Yokohama Hospital Yokohama Japan (Y.M. S.K. M.M. F.U. S.K. Y.O. Y;

    Showa University Northern Yokohama Hospital Yokohama Japan (Y.M. S.K. M.M. F.U. S.K. Y.O. Y;

    Showa University Northern Yokohama Hospital Yokohama Japan (Y.M. S.K. M.M. F.U. S.K. Y.O. Y;

    Showa University Northern Yokohama Hospital Yokohama Japan (Y.M. S.K. M.M. F.U. S.K. Y.O. Y;

    Showa University Northern Yokohama Hospital Yokohama Japan (Y.M. S.K. M.M. F.U. S.K. Y.O. Y;

    Showa University Northern Yokohama Hospital Yokohama Japan (Y.M. S.K. M.M. F.U. S.K. Y.O. Y;

    Showa University Koto-Toyosu Hospital Tokyo Japan (H.I.);

    Nagoya University Nagoya Japan (H.I. M.O. K.M.);

    Nagoya University Nagoya Japan (H.I. M.O. K.M.);

    Nagoya University Nagoya Japan (H.I. M.O. K.M.);

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 内科学;
  • 关键词

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