Supplementary Material for: Clinical-Radiomic Analysis for Pretreatment Prediction of Objective Response to First Transarterial Chemoembolization in Hepatocellular Carcinoma

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 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 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.背景：术前筛选有望从首次经动脉化疗栓塞（transarterial chemoembolization, TACE）中获得客观缓解的中间期肝细胞癌（hepatocellular carcinoma, HCC）患者仍颇具挑战。 目的：开发并验证一款用于术前预测中间期肝细胞癌患者首次TACE治疗应答的临床放射组学模型（clinical-radiomic model, CR模型）。 方法：本回顾性研究共纳入595例中间期肝细胞癌患者。基于4个感兴趣区（regions of interest, ROI）提取的3404个放射组学特征，构建瘤周（10mm）放射组学特征（TPR-signature）。采用多变量logistic回归构建基于TPR-signature及临床因素的预测性CR模型。通过校准曲线及受试者工作特征曲线下面积（area under the receiver operating characteristic curves, AUCs）评估模型性能。 结果：最终的CR模型包含5个独立预测因素，分别为TPR-signature（p=0.004）、巴塞罗那临床肝癌分期（Barcelona Clinic Liver Cancer System Stage B, BCLC B）亚分期（p=0.01）、肿瘤位置（p=0.039）及动脉期高强化（p=0.050）。内部验证与外部验证结果均证实该模型具有优异性能，内部AUC与外部AUC分别为0.94与0.90。此外，在外部验证队列中，通过CR模型预测的客观缓解与患者生存改善显著相关（风险比（hazard ratio, HR）：2.43；95%置信区间（95% confidence interval, 95%CI）：1.60–3.69；p 结论：该CR模型在预测中间期肝细胞癌患者首次TACE应答方面表现优异，可为辅助筛选适合TACE治疗的患者提供可靠的预测工具。