Pan Junhan, Huang Huizhen, Zhang Siying, Zhu Yanyan, Zhang Yuhao, Wang Meng, Zhang Cong, Zhao Yan-Ci, Chen Feng
Department of Radiology, The First Affiliated Hospital of Zhejiang University School of Medicine, No.79 Qingchun Road, Hangzhou, 310003, China.
Department of Pathology, The First Affiliated Hospital of Zhejiang University School of Medicine, No.79 Qingchun Road, Hangzhou, 310003, China.
Eur Radiol. 2025 Jan;35(1):61-72. doi: 10.1007/s00330-024-10944-9. Epub 2024 Jul 12.
To establish and validate scoring models for predicting vessels encapsulating tumor clusters (VETC) in hepatocellular carcinoma (HCC) using computed tomography (CT) and magnetic resonance imaging (MRI), and to intra-individually compare the predictive performance between the two modalities.
We retrospectively included 324 patients with surgically confirmed HCC who underwent preoperative dynamic CT and MRI with extracellular contrast agent between June 2019 and August 2020. These patients were then divided into a discovery cohort (n = 227) and a validation cohort (n = 97). Imaging features and Liver Imaging Reporting and Data System (LI-RADS) categories of VETC-positive HCCs were evaluated. Logistic regression analyses were conducted on the discovery cohort to identify clinical and imaging predictors associated with VETC-positive cases. Subsequently, separate CT-based and MRI-based scoring models were developed, and their diagnostic performance was compared using generalized estimating equations.
On both CT and MRI, VETC-positive HCCs exhibited a higher frequency of size > 5.0 cm, necrosis or severe ischemia, non-smooth tumor margin, targetoid appearance, intratumor artery, and heterogeneous enhancement with septations or irregular ring-like structure compared to VETC-negative HCCs (all p < 0.05). Regarding LI-RADS categories, VETC-positive HCCs were more frequently categorized as LR-M than VETC-negative cases (all p < 0.05). In the validation cohort, the CT-based model showed similar sensitivity (76.7% vs. 86.7%, p = 0.375), specificity (83.6% vs. 74.6%, p = 0.180), and area under the curve value (0.80 vs. 0.81, p = 0.910) to the MRI-based model in predicting VETC-positive HCCs.
Preoperative CT and MRI demonstrated comparable performance in the identification of VETC-positive HCCs, thus displaying promising predictive capabilities.
Both computed tomography and magnetic resonance imaging demonstrated promise in preoperatively identifying the vessel-encapsulating tumor cluster pattern in hepatocellular carcinoma, with no statistically significant difference between the two modalities, potentially adding additional prognostic value.
Computed tomography (CT) and magnetic resonance imaging (MRI) show promise in the preoperative identification of vessels encapsulating tumor clusters-positive hepatocellular carcinoma (HCC). HCC with vessels encapsulating tumor cluster patterns were more frequently LR-M compared to those without. These CT and MRI models showed comparable ability in identifying vessels encapsulating tumor clusters-positive HCC.
利用计算机断层扫描（CT）和磁共振成像（MRI）建立并验证预测肝细胞癌（HCC）中肿瘤簇包绕血管（VETC）的评分模型，并在个体内比较这两种检查方式的预测性能。
我们回顾性纳入了324例经手术确诊的HCC患者，这些患者在2019年6月至2020年8月期间接受了术前动态CT和使用细胞外对比剂的MRI检查。然后将这些患者分为发现队列（n = 227）和验证队列（n = 97）。评估VETC阳性HCC的影像学特征和肝脏影像报告与数据系统（LI-RADS）分类。在发现队列中进行逻辑回归分析，以确定与VETC阳性病例相关的临床和影像学预测因素。随后，分别建立基于CT和基于MRI的评分模型，并使用广义估计方程比较它们的诊断性能。
与VETC阴性的HCC相比，在CT和MRI上，VETC阳性的HCC在大小> 5.0 cm、坏死或严重缺血、肿瘤边缘不光滑、靶样表现、瘤内动脉以及伴有分隔或不规则环状结构的不均匀强化方面的出现频率更高（所有p < 0.05）。关于LI-RADS分类，VETC阳性的HCC比VETC阴性的病例更常被分类为LR-M（所有p < 0.05）。在验证队列中，基于CT的模型在预测VETC阳性HCC方面显示出与基于MRI的模型相似的敏感性（76.7%对86.7%，p = 0.375）、特异性（83.6%对74.6%，p = 0.180）和曲线下面积值（0.80对0.81，p = 0.910）。
术前CT和MRI在识别VETC阳性HCC方面表现出相当的性能，因此具有良好的预测能力。
计算机断层扫描和磁共振成像在术前识别肝细胞癌中肿瘤簇包绕血管模式方面均显示出前景，两种检查方式之间无统计学显著差异，可能增加额外的预后价值。
计算机断层扫描（CT）和磁共振成像（MRI）在术前识别肿瘤簇包绕血管阳性肝细胞癌（HCC）方面显示出前景。与没有这种模式的HCC相比，具有肿瘤簇包绕血管模式的HCC更常为LR-M。这些CT和MRI模型在识别肿瘤簇包绕血管阳性HCC方面具有相当的能力。
