Background: The preoperative selection of patients with intermediate-stage hepatocellular carcinoma (HCC) who are likely to have an objective response to first transarterial chemoembolization (TACE) remains challenging. Objective: To develop and validate a clinical-radiomic model (CR model) for preoperatively predicting treatment response to first TACE in patients with intermediate-stage HCC. Methods: A total of 595 patients with intermediate-stage HCC were included in this retrospective study. A tumoral and peritumoral (10 mm) radiomic signature (TPR-signature) was constructed based on 3,404 radiomic features from 4 regions of interest. A predictive CR model based on TPR-signature and clinical factors was developed using multivariate logistic regression. Calibration curves and area under the receiver operating characteristic curves (AUCs) were used to evaluate the model’s performance. Results: The final CR model consisted of 5 independent predictors, including TPR-signature (p #x3c; 0.001), AFP (p = 0.004), Barcelona Clinic Liver Cancer System Stage B (BCLC B) subclassification (p = 0.01), tumor location (p = 0.039), and arterial hyperenhancement (p = 0.050). The internal and external validation results demonstrated the high-performance level of this model, with internal and external AUCs of 0.94 and 0.90, respectively. In addition, the predicted objective response via the CR model was associated with improved survival in the external validation cohort (hazard ratio: 2.43; 95% confidence interval: 1.60–3.69; p #x3c; 0.001). The predicted treatment response also allowed for significant discrimination between the Kaplan-Meier curves of each BCLC B subclassification. Conclusions: The CR model had an excellent performance in predicting the first TACE response in patients with intermediate-stage HCC and could provide a robust predictive tool to assist with the selection of patients for TACE.
Liver Cancer

中文翻译：

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临床影像学分析预测肝细胞癌首次经动脉化疗栓塞治疗的客观反应

背景：对可能对首次经动脉化疗栓塞 (TACE) 有客观反应的中期肝细胞癌 (HCC) 患者的术前选择仍然具有挑战性。目的：开发和验证临床放射模型（CR 模型），用于术前预测中期 HCC 患者对首次 TACE 的治疗反应。方法：这项回顾性研究共纳入了 595 名中期 HCC 患者。基于来自 4 个感兴趣区域的 3,404 个放射组学特征构建了肿瘤和肿瘤周围（10 毫米）放射组学特征（TPR 特征）。使用多变量逻辑回归开发了基于 TPR 特征和临床因素的预测 CR 模型。校准曲线和接收者操作特征曲线下的面积 (AUC) 用于评估模型的性能。结果：最终的 CR 模型由 5 个独立预测因子组成，包括 TPR 特征（p #x3c；0.001）、AFP（p = 0.004）、巴塞罗那临床肝癌系统 B 期（BCLC B）亚分类（p = 0.01）、肿瘤位置 ( p= 0.039）和动脉高强化（p = 0.050）。内部和外部验证结果证明了该模型的高性能水平，内部和外部 AUC 分别为 0.94 和 0.90。此外，通过 CR 模型预测的客观反应与外部验证队列的生存率提高相关（风险比：2.43；95% 置信区间：1.60-3.69；p #x3c；0.001）。预测的治疗反应还允许在每个 BCLC B 亚分类的 Kaplan-Meier 曲线之间进行显着区分。结论：CR 模型在预测中期 HCC 患者的首次 TACE 反应方面具有出色的性能，并且可以提供强大的预测工具来帮助选择 TACE 患者。
肝癌