摘要
目的本研究旨在评估钆塞酸二钠在MRI中对肝细胞肝癌(HCC)患者手术前微血管侵犯(MVI)的出现和分级的预测价值。方法对138例术后病理诊断为肝细胞肝癌(HCC)的患者进行了回顾性的临床和影像学数据分析,从而找出HCC患者MVI的影响因素。将这些数据以7︰3的比例划分为训练组(96例)和验证组(42例)。并构建了一个临床-影像模型,以预测MVI的发生和分级。运用受试者工作特征曲线(receiver operating characteristic,ROC)检验其诊断能力。结果临床-影像模型AFP、肿瘤边界、强化方式、瘤内坏死、瘤周低信号、瘤内动脉和中性粒细胞与淋巴细胞的比值(NLR)是HCC患者出现MVI的独立危险因素。训练组M0、M1、M2的诊断效能ROC曲线下面积(AUC)值分别是0.84、0.82、0.80,测试组M0、M1、M2的AUC值分别为0.75、0.73、0.90。结论基于钆塞酸二钠增强MRI建立的临床-影像模型对术前预测肝癌患者微血管浸润的发生及分级具有较高的价值。
Objective This study aimed to evaluate the predictive value of gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid(Gd-EOB-DTPA)in MRI for the occurrence and grading of preoperative microvascular invasion(MVI)in patients with hepatocellular carcinoma(HCC).Methods Retrospective clinical and imaging data analysis was performed on 138 patients with postoperative pathological diagnosis of hepatocellular carcinoma(HCC)to identify the influencing factors of MVI in HCC patients.These data were then divided into a training group(96 cases)and a validation group(42 cases)in a ratio of 7:3.Next,we constructed a clinical-imaging model to predict the occurrence and grading of MVI,and we used receiver operating characteristic(ROC)curves to test their diagnostic capabilities.Results Clinical-imaging models such as AFP,tumor boundaries,reinforcement mode,intratumoral necrosis,peritumor low signal,intratumoral artery,and neutrophil-to-lymphocyte ratio(NLR)were independent risk factors for MVI in HCC patients.The AUC values under the ROC curve of diagnostic performance of M0,M1,and M2 in the training group were 0.84,0.82,and 0.80,respectively,and the AUC values of M0,M1,and M2 in the test group were 0.75,0.73 and 0.90,respectively.Conclusion The clinical-imaging model based on Gd-EOB-DTPA enhanced MRI has a high value in predicting the occurrence and grade of microvascular infiltration in patients with liver cancer.
作者
王皖皖
徐运军
郑鑫
蔡圣贤
WANG Wan-wan;XU Yun-jun;ZHENG Xin;CAI Sheng-xian(Department of Imaging,Anhui Provincial Hospital,Anhui Medical University,Hefei 230001,Anhui Province,China;Department of Imaging,The First Affiliated Hospital of Guangzhou Medical University,Guangzhou 510000,Guangdong Province,China)
出处
《中国CT和MRI杂志》
2024年第11期98-101,共4页
Chinese Journal of CT and MRI
基金
安徽省自然科学基金项目资助(2208085MH259)。