Li Min, Zhang Ge, Li Jing, Ren Yufan, Jin Xuan, Ke Qiying, Guo Congyue, Lv Jiaqi, Lu Haojun, Xu Yongzhou, Liang Wen, Quan Xianyue, Li Xinming
Department of Radiology, Chengdu Sixth People's Hospital, Chengdu, Sichuan, People's Republic of China.
Department of Radiology, Zhujiang Hospital, Southern Medical University, Guangzhou, People's Republic of China.
J Hepatocell Carcinoma. 2025 Jun 11;12:1177-1190. doi: 10.2147/JHC.S519223. eCollection 2025.
Hepatocellular carcinoma (HCC) with vessels encapsulating tumor clusters (VETC) pattern presents a higher risk of recurrence and metastasis, and the unique vascular structure of the VETC pattern may affect the perfusion and diffusion, and the effect that can be captured by intravoxel incoherent motion (IVIM). Therefore, this study used preoperative IVIM to predict VETC pattern in HCC and performed preoperative noninvasive recurrence risk stratification.
Patients with suspicious HCC were included prospectively. Two radiologists independently evaluated radiologic features and measured apparent diffusion coefficient (ADC), true diffusion coefficient (), pseudo-diffusion coefficient (*), and pseudo-diffusion fraction (). Logistic regression analyses were used to identify the predictors associated with the VETC pattern. Receiver operating characteristic (ROC) curve analyses were conducted to assess the predictive performance. Recurrence-free survival was evaluated using the Kaplan-Meier analysis and the Log rank test.
The consecutive cohort included 116 patients (mean age, 55 years ± 11, 94 men). Twenty-nine of the 116 HCC (25.0%) were VETC HCC. The value (odds ratio [OR], 0.791; p < 0.001), serum α-fetoprotein level (>400 ng/mL) (OR, 2.962; p = 0.042), and intratumor necrosis (OR, 6.022; p = 0.015) were independent predictors of the VETC pattern. These characteristics were used to construct the combined model with area under the ROC curve of 0.854. Additionally, adding the value to the conventional imaging-clinical model substantially improved its predictive performance (p < 0.001). Moreover, patients with the combined model classified as VETC HCC also had a higher risk of early recurrence than those with non-VETC HCC (p < 0.001).
IVIM enhances the accuracy of preoperative prediction of the VETC pattern and provides preoperative noninvasive risk stratification for HCC recurrence.
具有肿瘤巢血管包绕（VETC）模式的肝细胞癌（HCC）具有较高的复发和转移风险，VETC模式独特的血管结构可能会影响灌注和扩散，以及体素内不相干运动（IVIM）能够捕捉到的效应。因此，本研究采用术前IVIM来预测HCC中的VETC模式，并进行术前非侵入性复发风险分层。
前瞻性纳入疑似HCC患者。两名放射科医生独立评估影像学特征并测量表观扩散系数（ADC）、真实扩散系数（）、伪扩散系数（*）和伪扩散分数（）。采用逻辑回归分析确定与VETC模式相关的预测因素。进行受试者工作特征（ROC）曲线分析以评估预测性能。采用Kaplan-Meier分析和对数秩检验评估无复发生存率。
连续队列包括116例患者（平均年龄55岁±11岁，男性94例）。116例HCC中有29例（25.0%）为VETC HCC。值（优势比[OR]，0.791；p<0.001）、血清甲胎蛋白水平（>400 ng/mL）（OR，2.962；p = 0.042）和肿瘤内坏死（OR，6.022；p = 0.015）是VETC模式的独立预测因素。这些特征用于构建ROC曲线下面积为0.854的联合模型。此外，将值添加到传统影像-临床模型中可显著提高其预测性能（p<0.001）。此外，联合模型分类为VETC HCC的患者早期复发风险也高于非VETC HCC患者（p<0.001）。
IVIM提高了术前预测VETC模式的准确性，并为HCC复发提供了术前非侵入性风险分层。
