School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China.
Department of Radiology, The Third Affiliated Hospital of Shanghai Naval Military Medical University, Eastern Hepatobiliary Surgery Hospital, Shanghai, China.
Abdom Radiol (NY). 2024 Oct;49(10):3412-3426. doi: 10.1007/s00261-024-04283-y. Epub 2024 May 7.
Vessels Encapsulating Tumor Clusters (VETC) are now recognized as independent indicators of recurrence and overall survival in hepatocellular carcinoma (HCC) patients. However, there has been limited investigation into predicting the VETC pattern using hepatobiliary phase (HBP) features from preoperative gadobenate-enhanced MRI.
This study involved 252 HCC patients with confirmed VETC status from three different hospitals (Hospital 1: training set with 142 patients; Hospital 2: test set with 64 patients; Hospital 3: validation set with 46 patients). Independent predictive factors for VETC status were determined through univariate and multivariate logistic analyses. Subsequently, these factors were used to construct two distinct VETC prediction models. Model 1 included all independent predictive factors, while Model 2 excluded HBP features. The performance of both models was assessed using the Area Under the Curve (AUC), Decision Curve Analysis, and Calibration Curve. Prediction accuracy between the two models was compared using Net Reclassification Improvement (NRI) and Integrated Discriminant Improvement (IDI).
CA199, IBIL, shape, peritumoral hyperintensity on HBP, and arterial peritumoral enhancement were independent predictors of VETC. Model 1 showed robust predictive performance, with AUCs of 0.836 (training), 0.811 (test), and 0.802 (validation). Model 2 exhibited moderate performance, with AUCs of 0.813, 0.773, and 0.783 in the respective sets. Calibration and decision curves for both models indicated consistent predictions between predicted and actual VETC, benefiting HCC patients. NRI showed Model 1 increased by 0.326, 0.389, and 0.478 in the training, test, and validation sets compared to Model 2. IDI indicated Model 1 increased by 0.036, 0.028, and 0.025 in the training, test, and validation sets compared to Model 2.
HBP features from preoperative gadobenate-enhanced MRI can enhance the predictive performance of VETC in HCC.
肿瘤簇包绕血管（VETC）现在被认为是肝癌（HCC）患者复发和总生存的独立指标。然而，使用术前钆贝葡胺增强 MRI 的肝胆期（HBP）特征预测 VETC 模式的研究还很有限。
本研究纳入了来自三家医院的 252 例 HCC 患者（医院 1：训练集 142 例；医院 2：测试集 64 例；医院 3：验证集 46 例），他们的 VETC 状态得到了确认。通过单变量和多变量逻辑分析确定 VETC 状态的独立预测因素。随后，使用这些因素构建了两个不同的 VETC 预测模型。模型 1 包含所有独立预测因素，而模型 2 则排除了 HBP 特征。使用曲线下面积（AUC）、决策曲线分析和校准曲线评估两种模型的性能。使用净重新分类改善（NRI）和综合判别改善（IDI）比较两种模型的预测准确性。
CA199、IBIL、形状、HBP 上的肿瘤周高信号和动脉肿瘤周增强是 VETC 的独立预测因素。模型 1 表现出稳健的预测性能，在训练集、测试集和验证集中的 AUC 分别为 0.836、0.811 和 0.802。模型 2 表现出中等性能，在各自的组中 AUC 分别为 0.813、0.773 和 0.783。两种模型的校准和决策曲线均表明，预测的 VETC 与实际的 VETC 之间存在一致的预测，这对 HCC 患者有益。NRI 显示与模型 2 相比，模型 1 在训练集、测试集和验证集中分别增加了 0.326、0.389 和 0.478。IDI 表明与模型 2 相比，模型 1 在训练集、测试集和验证集中分别增加了 0.036、0.028 和 0.025。
术前钆贝葡胺增强 MRI 的 HBP 特征可以增强 HCC 中 VETC 的预测性能。
