摘要
目的探讨术前增强MRI影像组学分析的列线图模型预测肝细胞癌(hepatocellular carcinoma,HCC)切除术后复发风险的价值。材料与方法回顾性分析2015年8月至2020年8月在常州市第一人民医院进行HCC切除术的患者资料,共纳入164例于术前2周内进行增强MRI检查的患者病例,随机分为训练集(115例)和测试集(49例)。单因素及多因素Cox回归分析术前临床、病理及影像学特征与术后复发关系。运用最小绝对收缩和选择算子的Cox回归进行影像组学分析。联合影像组学标签及肿瘤复发的独立预测因素建立列线图预测模型,并在测试集进行验证。校准曲线观察模型预测概率与实际观察值一致性。根据训练集影像组学标签界值对HCC术后肿瘤复发风险分层,Kaplan-Meier法绘制生存曲线、Log-rank检验比较风险亚组间的生存差异。结果肿瘤边界、肿瘤坏死、影像组学标签为预测HCC术后肿瘤复发独立因素(风险比分别为2.1、2.5、64.1,95%可信区间分别为1.3~3.3、1.5~4.3、20.6~199.9,P<0.05)。列线图模型预测肿瘤复发风险的C-index分别为训练集0.796(0.738~0.854)和测试集0.784(0.684~0.885)。模型预测概率与实际观察值有较好一致性。按影像组学标签界值进行复发风险分层,低危组无复发生存率较高,较高危组差异在训练集及测试集中均具有统计学意义(训练集:χ^(2)=52.88,P<0.001;测试集:χ^(2)=4.14,P=0.042)。结论基于术前增强MRI影像组学分析的预测模型可有效预测HCC切除术后复发风险,有助于HCC术后患者个体化管理。
Objective:To develop a preoperative MRI model based on radiomics analysis for predicting recurrence of hepatocellular carcinoma(HCC)patients after resection.Materials and Methods:This retrospective study included 164 HCC patients(training set:n=115,testing set:n=49)who performed hepatectomy and preoperative gadoxetic acid-enhanced MRI within 2 weeks before resection between August 2015 and August 2020.The univariable and multivariable Cox regression analyses were performed to identify clinical-pathologic-radiologic factors associated with recurrence-free survival(RFS).The radiomics models were constructed using least absolute shrinkage and selection operator Cox regression.The combined nomogram model merging independent factors and radscore was built to predict the RFS of HCC patients after resection and the predictive performance of nomogram model was evaluated with C-index and calibration curves.Kaplan-Meier survival analysis was used to assess the association of the models with RFS.Results:The combined nomogram model integrating the tumor margin[HR=2.1,95%confidence interval(CI):1.3 to 3.3],necrosis(HR=2.5,95%CI:1.5 to 4.3)and the radscore(HR=64.1,95%CI:20.6 to 199.9)showed good predictive efficacy for recurrence of HCC patients after resection with a C-index of 0.796(0.738 to 0.854)in the training set and 0.784(0.684 to 0.885)in the test set.Calibration curves demonstrated good agreement between model-predicted probabilities and observed outcomes.There was significant difference for recurrence rates between predicted low-risk group and high-risk group in the training set(χ^(2)=52.88,P<0.001)and the test set(χ^(2)=4.14,P=0.042).Conclusions:The nomogram model demonstrated good performance for predicting recurrence of HCC patients after resection,thus may help personalized clinical management of HCC patients.
作者
王晴
盛晔
刘海峰
朱祖辉
邢伟
WANG Qing;SHENG Ye;LIU Haifeng;ZHU Zuhui;XING Wei(Department of Radiology,the Third Affiliated Hospital of Soochow University(Changzhou First People's Hospital),Changzhou 213200,China;Department of Interventional Radiology,the Third Affiliated Hospital of Soochow University(Changzhou First People's Hospital),Changzhou 213200,China)
出处
《磁共振成像》
CAS
CSCD
北大核心
2022年第12期93-99,共7页
Chinese Journal of Magnetic Resonance Imaging
基金
常州市卫健委青年基金(编号:QN202111)。
关键词
肝细胞肝癌
复发预测
磁共振成像
影像组学
列线图
hepatocellular carcinoma
recurrence
magnetic resonance imaging
radiomics
nomogram
