基于影像学和血清学特征构建的列线图模型可较好预测原发性肝细胞癌的微血管浸润  

Construction of a prediction model for predicting microvascular invasion in primary hepatocellular carcinoma

作　　者：张泳欣 张水兴 肖学红[1] 黄晓星[1] 杨昂[1] 唐秉航[1] 卢扬柏[3] ZHANG Yongxin;ZHANG Shuixing;XIAO Xuehong;HUANG Xiaoxing;YANG Ang;TANG Binghang;LU Yangbo(Imaging Center,Zhongshan People's Hospital,Zhongshan 528403,China;Imaging Center,the First Affiliated Hospital of Jinan University,Guangzhou 510630,China;Department of Surgery,Zhongshan People's Hospital,Zhongshan 528403,China)

机构地区：[1]中山市人民医院影像中心,广东中山528403 [2]暨南大学附属第一医院影像中心,广东广州510630 [3]中山市人民医院外科,广东中山528403

出　　处：《分子影像学杂志》2022年第4期518-525,共8页Journal of Molecular Imaging

基　　金：中山市人民医院放射影像中心重点专科科研项目(T2020016)。

摘　　要：目的探讨术前基于影像学和血清学特征构建的列线图模型对肝癌微血管浸润(MVI)的预测价值。方法回顾性分析2015年1月~2020年12月于中山市人民医院接受切除或肝移植的548例肝细胞癌(HCC)患者的临床资料,最终纳入315例肝癌MVI患者,年龄53.2±11.5岁,肿瘤最大直径3.7~7.0 cm。收集患者临床及影像学资料并进行分析,采取单因素与多因素Logistic分析,筛查出能预测MVI的独立风险因素,构建预测HCC中MVI的列线图模型,利用ROC曲线、校准曲线和决策曲线对模型进行评估。结果MVI(+)患者的中位生存时间为13月(95%CI:8.1~17.9),1、3、5年无病生存率分别为50.6%、38.5%和30.9%(P<0.05);MVI(-)患者的中位生存时间为47月(95%CI:32.7~61.3),1、3、5年无病生存率分别为77.9%、62.3%和38.8%(P<0.05)。多因素Logistic回归分析显示,更大的肿瘤体积、突破肝外生长、缺乏或不完整假包膜、存在动脉期瘤周强化以及术前过高的球蛋白值是MVI(+)的独立危险因素(P<0.05)。最终模型效能曲线下面积为0.895,95%CI为0.859-0.930,准确性为85.1%,敏感度为85.9%,特异性为84.1%。校准曲线显示预测概率与病理结果MVI(+)/MVI(-)概率有良好的一致性。决策曲线显示模型具有良好的临床应用价值。结论构建的列线图及预测模型能较好地术前预测MVI(+)的概率,可以根据MVI发生的风险调整HCC的治疗计划,以优化生存结果。Objective To investigate the value of a preoperative nomograph and prediction model based on imaging and serological characteristics for predicting microvascular invasion(MVI)in hepatocellular carcinoma(HCC).Methods Clinical data of 548 patients with HCC who underwent liver resection or liver transplantation from January 2015 to December 2020 in our Hospital were retrospectively included.A total of 315 patients with HCC(MVI+or MVI-)with an average age of 53.2±11.5 years old and a maximum direct tumour of 3.7-7.0 cm were included.Clinical and imaging data were analyzed.Univariate and multivariate logistic analyses were used to screen out independent risk factors that could predict MVI,and a nomograph model was constructed to predict MVI in HCC,which was evaluated using a subject operating curve,calibration curve and decision curve.Results The median survival time of patients with MVI(+)was 13 months(95%CI:8.1-17.9)while that of patients with MVI(-)was 47 months(95%CI:32.7-61.3).The 1-year,3-year and 5-year disease-free survival rates of patients with MVI(+)were 50.6%、38.5%and 30.9%,while that of patients with MVI(-)were 77.9%、62.3%and 38.8%,respectively.Multivariate logistic regression analysis showed that larger tumour size,extrahepatic growth,absence or incomplete pseudocapsule,presence of arterial peritumoral enhancement and high preoperative globulin value were independent risk factors for MVI(+).The final model efficacy were as follows:AUC=0.895,95%CI:0.859-0.930,accuracy:85.1%,sensitivity:85.9%,specificity:84.1%.The calibration curve showed that the predicted probability was in good agreement with the MVI(+)/MVI(-)probability of the pathological results.Thus,the decision curve model displayed good clinical application value.Conclusion The constructed Nomograph and prediction model can better predict the probability of MVI(+)before surgery.It can aid in adjusting the treatment plan of HCC according to the risk of MVI to optimize the survival outcome.

关 键 词：肝细胞癌 微血管浸润 危险因素 列线图 

分 类 号：R735.7[医药卫生—肿瘤] R445[医药卫生—临床医学]