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首页> 外文期刊>Journal of magnetic resonance imaging: JMRI >Computer‐aided diagnosis program for classifying the risk of hepatocellular carcinoma on MR images following liver imaging reporting and data system (LI‐RADS)
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Computer‐aided diagnosis program for classifying the risk of hepatocellular carcinoma on MR images following liver imaging reporting and data system (LI‐RADS)

机译：计算机辅助诊断程序，用于对肝脏成像报告和数据系统（LI-RADS）后MR图像上的肝细胞癌的风险

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Purpose To develop and evaluate a computer‐aided diagnosis (CAD) program for liver lesions on magnetic resonance (MR) images for classification of the risk of hepatocellular carcinoma (HCC) following the liver imaging reporting and data system (LI‐RADS). Materials and Methods Liver MR images from 41 patients with hyperenhancing liver lesions categorized as LR 3, 4, and 5 were evaluated by two radiologists. The major LI‐RADS features of each index liver lesion were recorded, including size (maximum transverse diameter), presence of hyperenhancement, washout appearance, and capsule appearance. A CAD program was implemented to register MR images at different contrast‐enhancement phases, segment liver lesions, extract lesion features, and classify lesions according to LI‐RADS. The LI‐RADS features quantified by CAD were compared with those assessed by radiologists using the intraclass correlation coefficient (ICC) and receiver operator curve (ROC) analyses. The LI‐RADS categorization between CAD and radiologists was evaluated using the weighted Cohen's kappa coefficient. Results The mean and standard deviation of the lesion diameters were 21 ± 11 mm (range, 7–70 mm) by radiologists and 22 ± 11 mm (range, 8–72 mm) by CAD (ICC, 0.96–0.97). The area under the curve (AUC) for the washout assessment by CAD was 0.79–0.93 with sensitivity 0.69–0.82 and specificity 0.79–1. The AUC for the capsule assessment by CAD was 0.79–0.9 with sensitivity 0.75–0.9 and specificity 0.82–0.96. The classifications by the radiologists and CAD coincided in 76–83% lesions ( k = 0.57–0.71), while the agreements between radiologists were in 78% lesions ( k = 0.59). Conclusion We developed a CAD program for liver lesions on MR images and showed a substantial agreement in the LI‐RADS‐based classification of the risk of HCCs between the CAD and radiologists. Level of Evidence: 1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;47:710–722.
机译：目的要开发和评估肝脏病变（MR）图像的肝脏病变的计算机辅助诊断（CAD）程序，以便在肝脏成像报告和数据系统（LI-RADS）之后的肝细胞癌（HCC）的风险分类。材料和方法通过两个放射科医师评估了41例Hyperenshiancing肝病患者的肝硬化患者的肝硬化患者。记录每个指数肝病变的主要LI-RADS特征，包括尺寸（最大横向直径），血清损伤，冲洗外观和胶囊外观的存在。实施CAD程序以在不同对比度阶段，分段肝病变，提取病变特征处注册MR图像，并根据LI-RAD分类病变。使用CAD量化的Li-RADS特征与使用脑内相关系数（ICC）和接收器操作员曲线（ROC）分析的放射科学医生评估的那些。使用加权Cohen的Kappa系数评估CAD和放射科学家之间的LI-RAD分类。结果病变直径的平均值和标准偏差为21±11毫米（范围，7-70mm），通过CAD（ICC，0.96-0.97），22±11毫米（范围，8-72毫米）。 CAD的冲洗评估下的曲线（AUC）下的区域为0.79-0.93，灵敏度为0.69-0.82和特异性0.79-1。 CAD的胶囊评估AUC为0.79-0.9，灵敏度为0.75-0.9和特异性0.82-0.96。放射科学家和CAD的分类在76-83％的病变中（K = 0.57-0.71）一致，而放射科学医生之间的协议是78％病变（K = 0.59）。结论我们为MR图像开发了一个CAD计划，并在CAD和放射科学家之间的HCCS风险的基于LI-RADS的分类中显示了大量一致。证据水平：1技术疗效：第1阶段J. MANG。恢复。 2018年成像; 47：710-722。

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