Data_Sheet_1_Radiomics Analysis on Multiphase Contrast-Enhanced CT: A Survival Prediction Tool in Patients With Hepatocellular Carcinoma Undergoing Transarterial Chemoembolization.pdf

Patients with HCC receiving TACE have various clinical outcomes. Several prognostic models have been proposed to predict clinical outcomes for patients with hepatocellular carcinomas (HCC) undergoing transarterial chemoembolization (TACE), but establishing an accurate prognostic model remains necessary. We aimed to develop a radiomics signature from pretreatment CT to establish a combined radiomics-clinic (CRC) model to predict survival for these patients. We compared this CRC model to the existing prognostic models in predicting patient survival. This retrospective study included multicenter data from 162 treatment-naïve patients with unresectable HCC undergoing TACE as an initial treatment from January 2007 and March 2017. We randomly allocated patients to a training cohort (n = 108) and a testing cohort (n = 54). Radiomics features were extracted from intra- and peritumoral regions on both the arterial phase and portal venous phase CT images. A radiomics signature (Rad-signature) for survival was constructed using the least absolute shrinkage and selection operator method in the training cohort. We used univariate and multivariate Cox regressions to identify associations between the Rad- signature and clinical factors of survival. From these, a CRC model was developed, validated, and further compared with previously published prognostic models including four-and-seven criteria, six-and-twelve score, hepatoma arterial-embolization prognostic scores, and albumin-bilirubin grade. The CRC model incorporated two variables: The Rad-signature (composed of features extracted from intra- and peritumoral regions on the arterial phase and portal venous phase) and tumor number. The CRC model performed better than the other seven well-recognized prognostic models, with concordance indices of 0.73 [95% confidence interval (CI) 0.68–0.79] and 0.70 [95% CI 0.62–0.82] in the training and testing cohorts, respectively. Among the seven models tested, the six-and-12 score and four-and-seven criteria performed better than the other models, with C-indices of 0.64 [95% CI 0.58–0.70] and 0.65 [95% CI 0.55–0.75] in the testing cohort, respectively. The CT radiomics signature represents an independent biomarker of survival in patients with HCC undergoing TACE, and the CRC model displayed improved predictive performance.

针对接受经动脉化疗栓塞术（TACE）的肝细胞癌（HCC）患者，其临床预后存在多样性。已提出多种预后模型以预测此类患者接受TACE治疗后的临床预后，但建立一个精确的预后模型仍属必要。本研究旨在从治疗前CT影像中构建一个放射组学特征，以建立联合放射组学-临床（CRC）模型，预测患者的生存率。本研究将所构建的CRC模型与现有的预后模型在预测患者生存率方面进行了比较。此项回顾性研究纳入了2007年1月至2017年3月期间162例未接受过治疗的不可切除HCC患者，这些患者作为初始治疗接受了TACE。我们将患者随机分配至训练组（n = 108）和测试组（n = 54）。从动脉期和门脉期CT图像的肿瘤内及肿瘤周围区域提取放射组学特征。在训练组中，使用最小绝对收缩和选择算子法构建了生存放射组学特征（Rad-signature）。通过单变量和多变量Cox回归分析，识别了Rad-signature与临床生存因素之间的关联，并据此开发、验证了CRC模型，并进一步将其与先前发表的包括四项和七项标准、六项和十二项评分、肝动脉栓塞预后评分以及白蛋白-胆红素分级在内的预后模型进行了比较。CRC模型纳入了两个变量：Rad-signature（由动脉期和门脉期肿瘤内及肿瘤周围区域的特征组成）和肿瘤数量。CRC模型在训练组和测试组中的表现均优于其他七个已知的预后模型，分别具有0.73 [95%置信区间（CI）0.68–0.79]和0.70 [95% CI 0.62–0.82]的一致性指数。在七个测试模型中，六项和十二项评分以及四项和七项标准在测试组中的C-指数分别为0.64 [95% CI 0.58–0.70]和0.65 [95% CI 0.55–0.75]，表现优于其他模型。CT放射组学特征代表着接受TACE治疗的HCC患者生存的独立生物标志物，而CRC模型则显示出更佳的预测性能。