Li Pinxiong, Wu Lei, Li Zhenhui, Li Jiao, Ye Weitao, Shi Zhenwei, Xu Zeyan, Zhu Chao, Ye Huifen, Liu Zaiyi, Liang Changhong
The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China.
Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Front Oncol. 2021 Aug 13;11:716849. doi: 10.3389/fonc.2021.716849. eCollection 2021.
To explore the usefulness of spleen radiomics features based on contrast-enhanced computed tomography (CECT) in predicting early and late recurrences of hepatocellular carcinoma (HCC) patients after curative resection.
This retrospective study included 237 HCC patients who underwent CECT and curative resection between January 2006 to January 2016. Radiomic features were extracted from CECT images, and then the spleen radiomics signatures and the tumor radiomics signatures were built. Cox regression analysis was performed to identify the independent risk factors of early and late recurrences. Then, multiple models were built to predict the recurrence-free survival of HCC after resection, and the incremental value of the radiomics signature to the clinicopathologic model was assessed and validated. Kaplan-Meier survival analysis was used to assess the association of the models with RFS.
The spleen radiomics signature was independent risk factor of early recurrence of HCC. The mixed model that integrated microvascular invasion, tumor radiomics signature and spleen radiomics signature for the prediction of early recurrence achieved the highest C-index of 0.780 (95% CI: 0.728,0.831) in the primary cohort and 0.776 (95% CI: 0.716,0.836) in the validation cohort, and presented better predictive performance than clinicopathological model and combined model. In the analysis of late recurrence, the spleen radiomics signature was the only prognostic factor associated with late recurrence of HCC.
The identified spleen radiomics signatures are prognostic factors of both early and late recurrences of HCC patients after surgery and improve the predictive performance of model for early recurrence.
探讨基于对比增强计算机断层扫描(CECT)的脾脏影像组学特征在预测肝细胞癌(HCC)患者根治性切除术后早期和晚期复发中的应用价值。
本回顾性研究纳入了2006年1月至2016年1月期间接受CECT检查并进行根治性切除的237例HCC患者。从CECT图像中提取影像组学特征,然后构建脾脏影像组学特征和肿瘤影像组学特征。进行Cox回归分析以确定早期和晚期复发的独立危险因素。然后,建立多个模型来预测HCC切除术后的无复发生存率,并评估和验证影像组学特征对临床病理模型的增量价值。采用Kaplan-Meier生存分析评估模型与无复发生存率(RFS)的相关性。
脾脏影像组学特征是HCC早期复发的独立危险因素。在预测早期复发时,整合微血管侵犯、肿瘤影像组学特征和脾脏影像组学特征的混合模型在原始队列中的C指数最高,为0.780(95%CI:0.728,0.831),在验证队列中的C指数为0.776(95%CI:0.716,0.836),其预测性能优于临床病理模型和联合模型。在晚期复发分析中,脾脏影像组学特征是与HCC晚期复发相关的唯一预后因素。
所确定的脾脏影像组学特征是HCC患者术后早期和晚期复发的预后因素,并提高了早期复发模型的预测性能。