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• W4206142227 abstract "Objective: To explore the value of radiomics model based on dynamic contrast-enhanced magnetic resonance imaging (MRI) in differentiation fat-poor angiomyolipoma (fp-AML) from alpha-fetoprotein-negative hepatocellular carcinoma (n-HCC) in the background of non-cirrhotic liver. Methods: The complete data of 121 patients from Guangdong Provincial People's Hospital, Zhongshan Hospital Affiliated to Fudan University and Sun Yat-sen University Cancer Center with hepatic fp-AML and n-HCC confirmed by pathology from October 2010 to July 2020 were retrospectively analyzed. Among them, 75 were males and 46 were females, aged from 23 to 80 (55±12) years. A total of 93 patients from Zhongshan Hospital Affiliated to Fudan University were divided into the training cohort (n=75) and internal test cohort (n=18) according to entry time, and the patients of other 2 hospitals were divided into external test cohort (n=28). The radiomics features were extracted from the preoperative triple-phase contrast-enhanced images. The feature selection algorithm based on Joint Mutual Information Maximisation (JMIM) was used to extract the optimal feature subset, and support vector machine (SVM) was used to build the radiomics model. The diagnostic performance of radiomics model was evaluated using the receiver operating characteristic (ROC) curve, and was compared with that of two radiologists. Results: In the internal cohort, the area under the curve (AUC) for the differential diagnosis between fp-AML and n-HCC of the radiomics model was 0.819 (with an accuracy of 72.2%), outperforming than radiologist 1 with 10 years of diagnostic experience (AUC=0.542, P=0.029) and radiologist 2 with 2 years of diagnostic experience (AUC=0.375, P=0.004). In the external cohort, the AUC of the radiomics model was 0.772 (with and accuracy of 71.4%), which was comparable to that of radiologist 1 (AUC=0.661, P=0.442) and better than that of radiologist 2 (AUC=0.400, P=0.008). Conclusion: The radiomics model based on dynamic contrast-enhanced MRI is of high accuracy for preoperatively differentiating hepatic fp-AML from n-HCC in the noncirrhotic liver.目的： 探讨基于动态增强MRI影像组学模型术前鉴别非肝硬化背景下乏脂肪型肝血管平滑肌脂肪瘤（fp-AML）和甲胎蛋白阴性肝细胞癌（n-HCC）的价值。 方法： 回顾性分析2010年10月至2020年7月广东省人民医院、中山大学肿瘤防治中心、复旦大学附属中山医院经手术病理证实的121例肝fp-AML和n-HCC患者完整资料，其中男75例，女46例，年龄23~80（55±12）岁。按入组时间顺序，将复旦大学附属中山医院（n=93）的患者划分为训练集（n=75）和内部测试集（n=18），广东省人民医院、中山大学肿瘤防治中心的患者作为外部测试集（n=28）。基于术前三期增强图像提取影像组学特征，使用联合互信息最大化（JMIM）特征选择算法提取最优特征子集，运用支持向量机（SVM）建立影像组学模型，绘制受试者工作特征（ROC）曲线评价模型诊断效能，并与2名放射科医生进行比较。 结果： 影像组学模型鉴别肝fp-AML和n-HCC的曲线下面积（AUC）在内部测试集中为0.819（准确度72.2%），优于诊断经验10年的医生1（AUC=0.542，P=0.029）及2年的医生2（AUC=0.375，P=0.004）；在外部测试集中AUC为0.772（准确度71.4%），与医生1表现相当（AUC=0.661，P=0.442），优于医生2（AUC=0.400，P=0.008）。 结论： 基于动态增强MRI影像组学模型对于术前鉴别非肝硬化背景下肝fp-AML和n-HCC准确度高。." @default.
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• W4206142227 date "2022-01-18" @default.
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• W4206142227 title "[Value of radiomics model based on dynamic contrast-enhanced magnetic resonance imaging in differentiation fat-poor angiomyolipoma from alpha-fetoprotein-negative hepatocellular carcinoma in the background of non-cirrhotic liver]." @default.
• W4206142227 doi "https://doi.org/10.3760/cma.j.cn112137-20211110-02495" @default.
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