基于动态增强MRI影像组学模型鉴别非肝硬化背景下乏脂肪型肝血管平滑肌脂肪瘤和甲胎蛋白阴性肝细胞癌的价值  

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

作　　者：张源 赵香田 王明亮 韩路军[4] 毛丽 李秀丽 梁长虹[2] 刘再毅 Zhang Yuan;Zhao Xiangtian;Wang Mingliang;Han Lujun;Mao Li;Li Xiuli;Liang Changhong;Liu Zaiyi(The Second School of Clinical Medicine,Southern Medical University,Guangzhou 510515,China;Department of Radiology,Guangdong Provincial People′s Hospital,Guangdong Academy of Medical Sciences,Guangzhou 510080,China;Department of Radiology,Zhongshan Hospital,Fudan University,Shanghai 200032,China;Department of Radiology,Sun Yat‑sen University Cancer Center,Guangzhou 510060,China;AI Lab,Deepwise Healthcare,Beijing 100080,China)

机构地区：[1]南方医科大学第二临床医学院,广州510515 [2]广东省人民医院放射科广东省医学科学院,广州510080 [3]复旦大学附属中山医院放射科,上海200032 [4]中山大学肿瘤防治中心放射科,广州510060 [5]深睿医疗人工智能研究院,北京100080

出　　处：《中华医学杂志》2022年第3期196-200,共5页National Medical Journal of China

基　　金：广东省重点领域研发计划(2021B0101420006);国家重点研发计划(2017YFC1309100);国家自然科学基金杰出青年科学基金(81925023);国家自然科学基金(81771912、82071892);广东省医学科研基金(A2021086)。

摘　　要：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。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 di

关 键 词：动态增强MRI 肝血管平滑肌脂肪瘤 影像组学 放射科医生 非肝硬化背景 诊断经验 肝细胞癌 肿瘤防治中心 

分 类 号：R735.7[医药卫生—肿瘤] R445.2[医药卫生—临床医学]