CT-derived extracellular volume and liver volumetry can predict posthepatectomy liver failure in hepatocellular...

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.