Optimizing predictions: improved performance of preoperative gadobenate-enhanced MRI hepatobiliary phase features in predicting vessels encapsulating tumor clusters in hepatocellular carcinoma-a multicenter study.

IF 2.3 3区医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Abdominal Radiology Pub Date : 2024-10-01 Epub Date: 2024-05-07 DOI:10.1007/s00261-024-04283-y

Huilin Chen, Hui Dong, Ruilin He, Mengting Gu, Xingyu Zhao, Kairong Song, Wenjie Zou, Ningyang Jia, Wanmin Liu

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Abstract

Background: 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.

Methods: 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).

Results: 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.

Conclusion: HBP features from preoperative gadobenate-enhanced MRI can enhance the predictive performance of VETC in HCC.

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优化预测：提高术前钆喷酸增强磁共振成像肝胆期特征在预测肝细胞癌中包裹肿瘤簇的血管方面的性能--一项多中心研究。

背景：血管包裹肿瘤簇（VETC）是目前公认的肝细胞癌（HCC）患者复发和总生存率的独立指标。然而，利用术前钆增强磁共振成像（Gadobenate-enhanced MRI）的肝胆期（HBP）特征预测 VETC 模式的研究还很有限：本研究涉及三家不同医院的 252 例确诊为 VETC 的 HCC 患者（医院 1：训练集，142 例患者；医院 2：测试集，64 例患者；医院 3：验证集，46 例患者）。通过单变量和多变量逻辑分析确定了 VETC 状态的独立预测因素。随后，利用这些因素构建了两个不同的 VETC 预测模型。模型 1 包括所有独立的预测因素，而模型 2 则不包括 HBP 特征。使用曲线下面积（AUC）、决策曲线分析和校准曲线对两个模型的性能进行了评估。使用净重分类改进（NRI）和综合判别改进（IDI）比较了两个模型的预测准确性：结果：CA199、IBIL、形状、HBP上的瘤周高密度和瘤周动脉强化是VETC的独立预测因子。模型 1 显示出强大的预测性能，AUC 分别为 0.836（训练）、0.811（测试）和 0.802（验证）。模型 2 显示出中等水平的性能，在各组中的 AUC 分别为 0.813、0.773 和 0.783。两个模型的校准和决策曲线显示，预测 VETC 和实际 VETC 之间的预测结果一致，有利于 HCC 患者。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显示，与模型2相比，模型1在训练集、测试集和验证集中的IDI分别增加了0.036、0.028和0.025：结论：术前钆增强 MRI 的 HBP 特征可提高 VETC 对 HCC 的预测性能。

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来源期刊

Abdominal Radiology Medicine-Radiology, Nuclear Medicine and Imaging

CiteScore

5.20

自引率

8.30%

发文量

334

期刊介绍： Abdominal Radiology seeks to meet the professional needs of the abdominal radiologist by publishing clinically pertinent original, review and practice related articles on the gastrointestinal and genitourinary tracts and abdominal interventional and radiologic procedures. Case reports are generally not accepted unless they are the first report of a new disease or condition, or part of a special solicited section. Reasons to Publish Your Article in Abdominal Radiology: · Official journal of the Society of Abdominal Radiology (SAR) · Published in Cooperation with: European Society of Gastrointestinal and Abdominal Radiology (ESGAR) European Society of Urogenital Radiology (ESUR) Asian Society of Abdominal Radiology (ASAR) · Efficient handling and Expeditious review · Author feedback is provided in a mentoring style · Global readership · Readers can earn CME credits