Peng Yangling, Tang Hao, Huang Yuanying, Yuan Xiaoqian, Wang Xing, Ran Zijuan, Deng Wei, Liu Renwei, Lan Xiaosong, Shen Hesong, Zhang Jiuquan
Department of Radiology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, Chongqing, 400030, People's Republic of China.
Department of Hematology, Chongqing General Hospital, University of the Chinese Academy of Sciences, Chongqing, People's Republic of China.
Insights Imaging. 2023 Sep 12;14(1):145. doi: 10.1186/s13244-023-01496-5.
Posthepatectomy liver failure (PHLF) is a severe complication of liver resection. We aimed to develop and validate a model based on extracellular volume (ECV) and liver volumetry derived from computed tomography (CT) for preoperative predicting PHLF in resectable hepatocellular carcinoma (HCC) patients.
A total of 393 resectable HCC patients from two hospitals were enrolled and underwent multiphasic contrast-enhanced CT before surgery. A total of 281 patients from our hospital were randomly divided into a training cohort (n = 181) and an internal validation cohort (n = 100), and 112 patients from another hospital formed the external validation cohort. CT-derived ECV was measured on nonenhanced and equilibrium phase images, and liver volumetry was measured on portal phase images. The model is composed of independent predictors of PHLF. The under the receiver operator characteristic curve (AUC) and calibration curve were used to reflect the predictive performance and calibration of the model. Comparison of AUCs used the DeLong test.
CT-derived ECV, measured future liver remnant (mFLR) ratio, and serum albumin were independent predictors for PHLF in resectable HCC patients. The AUC of the model was significantly higher than that of the ALBI score in the training cohort, internal validation cohort, and external validation cohort (all p < 0.001). The calibration curve of the model showed good consistency in the training cohort and the internal and external validation cohorts.
The novel model contributes to the preoperative prediction of PHLF in resectable HCC patients.
The novel model combined CT-derived extracellular volume, measured future liver remnant ratio, and serum albumin outperforms the albumin-bilirubin score for predicting posthepatectomy liver failure in patients with resectable hepatocellular carcinoma.
• CT-derived ECV correlated well with the fibrosis stage of the background liver. • CT-derived ECV and mFLR ratio were independent predictors for PHLF in HCC. • The AUC of the model was higher than the CT-derived ECV and mFLR ratio. • The model showed a superior predictive performance than that of the ALBI score.
肝切除术后肝衰竭(PHLF)是肝切除的一种严重并发症。我们旨在开发并验证一种基于细胞外容积(ECV)和计算机断层扫描(CT)衍生的肝脏容积测量法的模型,用于术前预测可切除肝细胞癌(HCC)患者的PHLF。
来自两家医院的393例可切除HCC患者被纳入研究,并在手术前行多期增强CT检查。我院的281例患者被随机分为训练队列(n = 181)和内部验证队列(n = 100),另一家医院的112例患者组成外部验证队列。在平扫和平衡期图像上测量CT衍生的ECV,在门静脉期图像上测量肝脏容积。该模型由PHLF的独立预测因子组成。采用受试者操作特征曲线下面积(AUC)和校准曲线来反映模型的预测性能和校准情况。AUC的比较采用DeLong检验。
CT衍生的ECV、测量的未来肝残余(mFLR)比率和血清白蛋白是可切除HCC患者PHLF的独立预测因子。在训练队列、内部验证队列和外部验证队列中,该模型的AUC均显著高于ALBI评分(均p < 0.001)。该模型的校准曲线在训练队列以及内部和外部验证队列中显示出良好的一致性。
该新模型有助于术前预测可切除HCC患者的PHLF。
该新模型结合CT衍生的细胞外容积、测量的未来肝残余比率和血清白蛋白,在预测可切除肝细胞癌患者肝切除术后肝衰竭方面优于白蛋白-胆红素评分。
• CT衍生的ECV与背景肝脏的纤维化阶段密切相关。• CT衍生的ECV和mFLR比率是HCC患者PHLF的独立预测因子。• 该模型的AUC高于CT衍生的ECV和mFLR比率。• 该模型显示出比ALBI评分更好的预测性能。