Liver fibrosis estimated using extracellular volume fraction obtained from dual-energy CT as a risk factor for hepatocellular carcinoma after sustained virologic response: A preliminary case-control study

Estimating liver cirrhosis severity with extracellular volume fraction by spectral CT

To investigate the diagnostic value of spectral CT in calculating extracellular volume fraction (ECV) for assessing the severity of liver cirrhosis. This retrospective study enrolled 172 participants, including 127 patients diagnosed with liver cirrhosis and 45 matched controls, all of whom underwent spectral CT hepatic enhancement imaging. Disease severity stratification was performed using the Child-Pugh classification system. ECV values were derived from the iodine density map during the delayed phase. These ECV values were then compared across the control group and subclassified cirrhosis groups (Child-Pugh classes A-C). Furthermore, a correlation analysis was performed to assess the relationship between ECV values and Child-Pugh scores in liver cirrhosis. Receiver operating characteristic (ROC) curves were constructed to evaluate the diagnostic performance of ECV values and MELD-Na in the Child-Pugh classification of liver cirrhosis. The ECV values were 25.49 ± 3.15, 29.73 ± 3.20, 35.64 ± 3.15, and 45.30 ± 5.16 for the control, Child-Pugh A, Child-Pugh B, and Child-Pugh C group, respectively, demonstrating significant intergroup differences (F = 184.67 P < 0.001). A strong positive correlation was observed between ECV and Child-Pugh liver function classification (r = 0.791, P < 0.001). The diagnostic performance of ECV for differentiating between Child-Pugh classes A and B (AUC: 0.901), B and C (AUC: 0.966) was higher compared to the MELD-Na score (AUC: 0.772 and 0.868) (P < 0.05, respectively). Multivariate analyses showed that ECV was an independent factor for cirrhosis (OR 1.610, P < 0.001). ECV values measured using spectral CT can serve as a noninvasive biomarker for assessing the severity of liver cirrhosis.

A short-term predictive model for disease progression in acute-on-chronic liver failure: integrating spectral CT extracellular liver volume and clinical characteristics

BACKGROUND

Acute-on-chronic liver failure (ACLF) is a life-threatening hepatic syndrome. Therefore, this study aimed to develop a comprehensive model combining extracellular liver volume derived from spectral CT (ECVIC-liver) and sarcopenia, for the early prediction of short-term (90-day) disease progression in ACLF.

MATERIALS AND METHODS

A retrospective cohort of 126 ACLF patients who underwent hepatic spectral CT scans was included. According to the Asia-Pacific Association for the Study of the Liver (APASL) criteria, patients were divided into the progression group (n = 70) and the stable group (n = 56). ECVIC-liver was measured on the equilibrium period (EP) images of spectral CT, and L3-SMI was measured on unenhanced CT images, with sarcopenia assessed. A comprehensive model was developed by combining independent predictors. Model performance was evaluated using receiver operating characteristic (ROC) curve analysis, calibration curves, and decision curve analysis (DCA).

RESULTS

In the univariate analysis, BMI, WBC, PLT, PTA, L3-SMI, IC-EP, Z-EP, K140-EP, NIC-EP, ECVIC-liver, and Sarcopenia demonstrated associations with disease progression status at 90 days in ACLF patients. In multivariate logistic regression, white blood cell count (WBC) (OR = 1.19, 95% CI: 1.02-1.40; P = 0.026), ECVIC-liver (OR = 1.27, 95% CI: 1.15-1.40; P < 0.001), sarcopenia (OR = 4.15, 95% CI: 1.43-12.01; P = 0.009), MELD-Na score (OR = 1.06, 95%CI: 1.01-1.13;P = 0.042), and CLIF-SOFA score (OR = 1.37, 95%CI:1.15-1.64; P<0.001) emerged as independent risk factors for ACLF progression. The combined model exhibited superior predictive performance (AUCs = 0.910, sensitivity = 80.4%, specificity = 90.0%, PPV = 0.865, NPV = 0.851) compared to CLIF-SOFA, MELD-Na, MELD and CTP scores(both P < 0.001). Calibration curves and DCA confirmed the high clinical utility of the combined model.

CONCLUSIONS

Patients without sarcopenia and/or with a lower ECVIC-liver have a better prognosis, and the integration of WBC, ECVIC-liver, Sarcopenia, CLIF-SOFA and MELD-Na scores in a composite model offers a concise and effective tool for predicting disease progression in ACLF patients.

TRIAL REGISTRATION

Not Applicable.