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

<b><i>Background:</i></b> 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. <b><i>Objective:</i></b> To develop and validate a clinical-radiomic model (CR model) for preoperatively predicting treatment response to first TACE in patients with intermediate-stage HCC. <b><i>Methods:</i></b> 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. <b><i>Results:</i></b> The final CR model consisted of 5 independent predictors, including TPR-signature (<i>p</i> &lt; 0.001), AFP (<i>p</i> = 0.004), Barcelona Clinic Liver Cancer System Stage B (BCLC B) subclassification (<i>p</i> = 0.01), tumor location (<i>p</i> = 0.039), and arterial hyperenhancement (<i>p</i> = 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; <i>p</i> &lt; 0.001). The predicted treatment response also allowed for significant discrimination between the Kaplan-Meier curves of each BCLC B subclassification. <b><i>Conclusions:</i></b> 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**：对于中期肝细胞癌（hepatocellular carcinoma, HCC）患者，术前筛选出有望对首次经动脉化疗栓塞（transarterial chemoembolization, TACE）产生客观应答的人群仍是临床难题。
**目的**：构建并验证一款临床-放射组学模型（clinical-radiomic model, CR模型），用于术前预测中期肝细胞癌患者对首次经动脉化疗栓塞的治疗应答情况。
**方法**：本回顾性研究共纳入595例中期肝细胞癌患者。基于4个感兴趣区域（region of interest, ROI）提取的3404个放射组学特征，构建肿瘤及瘤旁（10mm范围）放射组学特征（TPR-signature）。采用多因素logistic回归，基于TPR-signature与临床因素构建预测性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 curve, AUC）评估模型性能。
**结果**：最终构建的CR模型包含5个独立预测因子，分别为TPR-signature（p < 0.001）、甲胎蛋白（alpha-fetoprotein, AFP，p = 0.004）、巴塞罗那临床肝癌分期（Barcelona Clinic Liver Cancer, BCLC）B期亚分类（p = 0.01）、肿瘤位置（p = 0.039）以及动脉期高强化（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，内部验证受试者工作特征曲线下面积为0.94，外部验证为0.90。此外，在外部验证队列中，通过CR模型预测的客观应答与患者生存期改善显著相关（风险比：2.43；95%置信区间：1.60~3.69；p < 0.001）。该模型预测的治疗应答还可显著区分各BCLC B期亚分类的卡普兰-迈耶（Kaplan-Meier）曲线。
**结论**：本研究构建的CR模型在预测中期肝细胞癌患者首次经动脉化疗栓塞应答方面表现优异，可为筛选适合行经动脉化疗栓塞的患者提供可靠的预测工具。