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Computer-aided diagnosis of colorectal polyps using linked color imaging colonoscopy to predict histology

机译:使用链接的彩色成像结肠镜检查来预测组织学的计算机辅助诊断大肠息肉

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摘要

We developed a computer-aided diagnosis (CAD) system based on linked color imaging (LCI) images to predict the histological results of polyps by analyzing the colors of the lesions. A total of 139 images of adenomatous polyps and 69 images of non-adenomatous polyps obtained from our hospital were collected and used to train the CAD system. A test set of LCI images, including both adenomatous and non-adenomatous polyps, was prospectively collected from patients who underwent colonoscopies between Oct and Dec 2017; this test set was used to assess the diagnostic abilities of the CAD system compared to those of human endoscopists (two experts and two novices). The accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of this novel CAD system for the training set were 87.0%, 87.1%, 87.0%, 93.1%, and 76.9%, respectively. The test set included 115 adenomatous polyps and 66 non-adenomatous polyps that were prospectively collected. The CAD system identified adenomatous or non-adenomatous polyps in the test set with an accuracy of 78.4%, a sensitivity of 83.3%, a specificity of 70.1%, a PPV of 82.6%, and an NPV of 71.2%. The accuracy of the CAD system was comparable to that of the expert endoscopists (78.4% vs 79.6%; p = 0.517). In addition, the diagnostic accuracy of the novices was significantly lower to the performance of the experts (70.7% vs 79.6%; p = 0.018). A novel CAD system based on LCI could be a rapid and powerful decision-making tool for endoscopists.
机译:我们开发了一种基于链接的彩色成像(LCI)图像的计算机辅助诊断(CAD)系统,通过分析病变的颜色来预测息肉的组织学结果。收集了我院采集的139例腺瘤性息肉和69例非腺瘤性息肉,用于CAD系统的训练。前瞻性收集了2017年10月至2017年12月间接受结肠镜检查的患者的LCI图像测试集,包括腺瘤样息肉和非腺瘤样息肉;与人类内窥镜检查人员(两名专家和两名新手)相比,该测试集用于评估CAD系统的诊断能力。该新型CAD系统对训练集的准确性,敏感性,特异性,阳性预测值(PPV)和阴性预测值(NPV)分别为87.0%,87.1%,87.0%,93.1%和76.9%。测试组包括115例腺瘤性息肉和66例非腺瘤性息肉,这些均是前瞻性收集的。 CAD系统在测试集中识别出腺瘤性息肉或非腺瘤性息肉,准确性为78.4%,敏感性为83.3%,特异性为70.1%,PPV为82.6%,NPV为71.2%。 CAD系统的准确性与专业内镜医师的准确性相当(78.4%比79.6%; p = 0.517)。此外,新手的诊断准确性明显低于专家的表现(70.7%比79.6%; p = 0.018)。基于LCI的新型CAD系统可能成为内窥镜医师的快速而强大的决策工具。

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