肝细胞癌首次经动脉化疗栓塞客观反应的治疗前预测的临床-影像组学分析
Clinical-Radiomic Analysis for Pretreatment Prediction of Objective Response to First Transarterial Chemoembolization in Hepatocellular Carcinoma.
作者信息
Chen Mingyu, Cao Jiasheng, Hu Jiahao, Topatana Win, Li Shijie, Juengpanich Sarun, Lin Jian, Tong Chenhao, Shen Jiliang, Zhang Bin, Wu Jennifer, Pocha Christine, Kudo Masatoshi, Amedei Amedeo, Trevisani Franco, Sung Pil Soo, Zaydfudim Victor M, Kanda Tatsuo, Cai Xiujun
机构信息
Department of General Surgery, Sir Run-Run Shaw Hospital, Zhejiang University, Hangzhou, China.
Engineering Research Center of Cognitive Healthcare of Zhejiang Province, Hangzhou, China.
出版信息
Liver Cancer. 2021 Feb;10(1):38-51. doi: 10.1159/000512028. Epub 2021 Jan 7.
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 ( < 0.001), AFP ( = 0.004), Barcelona Clinic Liver Cancer System Stage B (BCLC B) subclassification ( = 0.01), tumor location ( = 0.039), and arterial hyperenhancement ( = 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; < 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.
背景
对于可能对首次经动脉化疗栓塞术（TACE）产生客观反应的中期肝细胞癌（HCC）患者，术前选择仍具有挑战性。
目的
建立并验证一种临床-影像组学模型（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
本回顾性研究共纳入595例中期HCC患者。基于来自4个感兴趣区域的3404个影像组学特征构建了肿瘤及瘤周（10mm）影像组学特征（TPR特征）。使用多因素逻辑回归建立基于TPR特征和临床因素的预测CR模型。采用校准曲线和受试者操作特征曲线下面积（AUC）评估模型性能。
结果
最终的CR模型由5个独立预测因素组成，包括TPR特征（<0.001）、甲胎蛋白（AFP，=0.004）、巴塞罗那临床肝癌系统分期B（BCLC B）亚分类（=0.01）、肿瘤位置（=0.039）和动脉期强化（=0.050）。内部和外部验证结果表明该模型具有较高性能，内部和外部AUC分别为0.94和0.90。此外，在外部验证队列中，通过CR模型预测的客观反应与生存率提高相关（风险比：2.43；95%置信区间：1.60-3.69；<0.001）。预测的治疗反应也能在各BCLC B亚分类的Kaplan-Meier曲线之间进行显著区分。
结论
CR模型在预测中期HCC患者首次TACE反应方面表现优异，可为TACE患者选择提供有力的预测工具。
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