基于MRI肝脏影像报告和数据系统特征构建的列线图预测符合Milan标准肝细胞癌微血管侵犯的价值  

A nomogram model integrating LI-RADS features based on MRI for predicting microvascular invasion in hepatocellular carcinoma following Milan criteria

作　　者：钟文新[1] 刘海峰 邹立秋 张豪 麦晓飞 邢伟[2] Zhong Wenxin;Liu Haifeng;Zou Liqiu;Zhang Hao;Mai Xiaofei;Xing Wei(Department of Radiology,Huazhong University of Science and Technology Union Shenzhen Hospital,Shenzhen 518052,China;Department of Radiology,Third Affiliated Hospital of Soochow University,Changzhou 213003,China)

机构地区：[1]华中科技大学协和深圳医院放射科,深圳518052 [2]苏州大学第三附属医院放射科,常州213003

出　　处：《中华放射学杂志》2023年第12期1346-1352,共7页Chinese Journal of Radiology

基　　金：国家自然科学基金 (81771805)。

摘　　要：目的建立并验证基于MRI的肝脏影像报告和数据系统(LI-RADS)特征的列线图模型预测符合Milan标准的肝细胞癌(HCC)微血管侵犯(MVI)的价值。方法回顾性分析2016年6月至2022年6月在苏州大学第三附属医院118例经病理证实的HCC患者的资料,共121个病灶,包括47个病理诊断为MVI阳性病灶和74个MVI阴性病灶。采用交叉验证方法随机分为训练集(83例84个病灶,MVI阳性病灶31个、MVI阴性病灶53个)和测试集(35例37个病灶,MVI阳性病灶16个、MVI阴性病灶21个)。以2018版LI-RADS定义的征象评价每个病灶。在训练集中采用χ2检验比较MVI阳性组与MVI阴性组间LI-RADS征象的差异,采用logistic回归获得MVI阳性的独立危险因素并构建列线图模型。采用受试者操作特征曲线和决策曲线分析(DCA)评估列线图模型预测MVI的效能和临床受益。结果训练集中MVI阳性组与MVI阴性组间HCC大小、边缘、结中结、马赛克征、晕环状强化差异有统计学意义(P<0.05)。多因素logistic分析结果显示,HCC最大径>3 cm(OR=1.427,95%CI 1.314~12.227,P=0.009)、肿瘤边缘不光滑(OR=3.167,95%CI 1.227~461.232,P=0.041)、马赛克征(OR=1.769,95%CI 1.812~61.434,P=0.022)、晕环状强化(OR=4.015,95%CI 3.327~836.384,P=0.011)是MVI阳性的独立危险因素。基于以上4个参数构建的列线图模型预测MVI的曲线下面积在训练集和测试集中分别为0.863(95%CI 0.768~0.947)和0.887(95%CI 0.804~0.987)。DCA结果显示训练集中列线图的曲线在所有合理阈值概率中均高于默认线,表明患者能获得临床受益。结论基于MRI的LI-RADS征象列线图模型术前可有效预测符合Milan标准HCC的MVI,可使患者临床受益。Objective To establish and verify a nomogram model based on MRI liver imaging reporting and data system(LI-RADS)features for predicting microvascular invasion(MVI)in hepatocellular carcinoma(HCC)following the Milan criteria.Methods A retrospective analysis was conducted on data from 118 HCC patients(121 lesions)confirmed by pathology from June 2016 to June 2022 at the Third Affiliated Hospital of Soochow University.Forty-seven HCCs were diagnosed as MVI-positive and 74 HCCs as MVI-negative.The data was randomly divided into the training set(83 patients with 84 HCCs,including 31 MVI-positive and 53 MVI-negative HCCs)and the test set(35 patients with 37 HCCs,including 16 MVI-positive and 21 MVI-negative HCCs)using cross-validation method.HCC imaging features were evaluated based on LI-RADS(version 2018).In the training set,theχ2 test was used to compare the differences in LI-RADS features between the MVI-positive group and the MVI-negative group.The logistic regression analysis was conducted to identify independent risk factors for predicting MVI-positive and to construct the nomogram model.The receiver operating characteristic(ROC)curves and decision curve analysis(DCA)were used to evaluate the performance and clinical benefits of the nomogram model in predicting MVI tumors.Results There were statistically significant differences between the MVI-positive group and the MVI-negative group in terms of tumor size,tumor margin,mosaic architecture,and corona enhancement(P<0.05).Multivariate logistic analysis results showed that HCC maximum diameter>3 cm(OR=1.427,95%CI 1.314-12.227,P=0.009),nonsmooth tumor margin(OR=3.167,95%CI 1.227-461.232,P=0.041),mosaic architecture(OR=1.769,95%CI 1.812-61.434,P=0.022),and corona enhancement(OR=4.015,95%CI 3.327-836.384,P=0.011)were independent risk factors for predicting MVI-positive tumors.Based on the independent predictors,the constructed nomogram model demonstrated an area under the ROC curve of 0.863(95%CI 0.768-0.947)and 0.887(95%CI 0.804-0.987)in the training and test sets f

关 键 词：癌 肝细胞 磁共振成像 微血管侵犯 Milan标准 列线图 

分 类 号：R445.2[医药卫生—影像医学与核医学] R735.7[医药卫生—诊断学]