Quantification of liver extracellular volume using dual-energy CT for ruling out high-risk varices in cirrhosis

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.

Predictive value of high-risk esophageal varices in cirrhosis based on dual-energy CT combined with clinical and serologic features

OBJECTIVE

To investigate the predictive value of dual-energy CT (DECT) in combination with clinical and serologic features for noninvasive assessment of high-risk esophageal variceal (EV) in cirrhosis patients.

DATA AND METHODS

120 patients who had undergone DECT and gastroscopy were retrospectively enrolled. They were categorized into low-risk variceal (LRV) and high-risk variceal (HRV) groups by gastroscopy (LRV: none, mild, HRV: moderate, severe). Clinical data, serologic and DECT parameters were recorded respectively. Multifactorial logistic regression analyses were conducted to develop clinical, serological, DECT, and combined models. AUC was utilized to assess the diagnostic performance. Non-parametric tests were employed to analyze differences in DECT parameters among different grading of EV.

RESULTS

In clinical model, ascites was the independent risk predictor, with 78.3% accuracy,50% sensitivity, 100% specificity, and an AUC of 0.693. The serological model revealed white blood cell count, hematocrit, alanine aminotransferase, and platelet count as predictors for HRV, demonstrating 83.3% accuracy, 90.9% sensitivity, 76.9% specificity, and an AUC of 0.784. The DECT model, identified liver normalized iodine volume (NIV-L) and spleen volume (V-S) as key predictors, with 84% accuracy, 72.7% sensitivity, 92.9% specificity, and an AUC of 0.84. The combined model, integrating NIV-L, V-S, and Ascites, demonstrated superior performance with 82.6% accuracy, 90% sensitivity, 76.9% specificity, and an AUC of 0.878, compared to the other models. Additionally, severe EV had higher V-S and NIV-S values than other grades (p < 0.05), with AUC of 0.874 and 0.864, respectively.

CONCLUSION

DECT-based NIV-L, V-S, and presence of ascites can predict high-risk esophageal varices.

CLINICAL RELEVANCE STATEMENT

Quantitative parameters of DECT can predict high-risk esophageal varices in cirrhotic patients, avoid gastroscopy, if possible, continue hierarchical management.

TRIAL REGISTRATION

retrospectively registered.

Assessment of Spectral Computed Tomography Image Quality and Detection of Lesions in the Liver Based on Image Reconstruction Algorithms and Virtual Tube Voltage

Background: Spectral detector computed tomography (SDCT) has demonstrated superior diagnostic performance and image quality in liver disease assessment compared with traditional CT. Selecting the right reconstruction algorithm and tube voltage is essential to avoid increased noise and diagnostic errors. Objectives: This study evaluated improvements in image quality achieved using various virtual tube voltages and reconstruction algorithms for diagnosing common liver diseases with spectral CT. Methods: This retrospective study involved forty-seven patients who underwent spectral CT scans for liver conditions, including fatty liver, hemangiomas, and metastatic lesions. The assessment utilized signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), with images reconstructed using various algorithms (IMR, iDose) at different levels and virtual tube voltages. Three experienced radiologists analyzed the reconstructed images to identify the best reconstruction methods and tube voltage combinations for diagnosing these liver pathologies. Results: The signal-to-noise ratio (SNR) was highest for spectral CT images using the IMR3 algorithm in metastatic, hemangioma, and fatty liver cases. A strong positive correlation was found between IMR3 at 120 keV and 70 keV (p-value = 0.000). In contrast, iDOSE2 at 120 keV and 70 keV showed a low correlation of 0.291 (p-value = 0.045). Evaluators noted that IMR1 at 70 keV provided the best visibility for liver lesions (mean = 3.58), while IMR3 at 120 keV had the lowest image quality (mean = 2.65). Conclusions: Improvements in image quality were noted with SDCT, especially in SNR values for liver tissues at low radiation doses and a specific IMR level. The IMR1 algorithm reduced noise, enhancing the visibility of liver lesions for better diagnosis.

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.

Prediction of tumor regression grade in far-advanced gastric cancer after preoperative immuno-chemotherapy using dual-energy CT-derived extracellular volume fraction

OBJECTIVES

This study examines the effectiveness of dual-energy CT (DECT) delayed-phase extracellular volume (ECV) fraction in predicting tumor regression grade (TRG) in far-advanced gastric cancer (FAGC) patients receiving preoperative immuno-chemotherapy.

MATERIALS AND METHODS

A retrospective analysis was performed on far-advanced gastric adenocarcinoma patients treated with preoperative immuno-chemotherapy at our institution from August 2019 to March 2023. Patients were categorized based on their TRG into pathological complete response (pCR) and non-pCR groups. ECV was determined using the delayed-phase iodine maps. In addition, tumor iodine densities and standardized iodine ratios were meticulously analyzed using the triple-phase enhanced iodine maps. Univariate analysis with five-fold cross-validation and Spearman correlation determined DECT parameters and clinical indicators association with pCR. The predictive accuracy of these parameters for pCR was evaluated using a weighted logistic regression model with five-fold cross-validation.

RESULTS

Of the 88 patients enrolled (mean age 60.8 ± 11.1 years, 63 males), 21 (23.9%) achieved pCR. Univariate analysis indicated ECV's significant role in differentiating between pCR and non-pCR groups (average p value = 0.021). In the logistic regression model, ECV independently predicted pCR with an average odds ratio of 0.911 (95% confidence interval, 0.798-0.994). The model, incorporating ECV, tumor area, and IDAV (the relative change rate of iodine density from venous phase to arterial phase), showed an average area under curves (AUCs) of 0.780 (0.770-0.791) and 0.766 (0.731-0.800) for the training and validation sets, respectively, in predicting pCR.

CONCLUSION

DECT-derived ECV fraction is a valuable predictor of TRG in FAGC patients undergoing preoperative immuno-chemotherapy.

CLINICAL RELEVANCE STATEMENT

This study demonstrates that DECT-derived extracellular volume fraction is a reliable predictor for pathological complete response in far-advanced gastric cancer patients receiving preoperative immuno-chemotherapy, offering a noninvasive tool for identifying potential treatment beneficiaries.

Predicting High-Risk Esophageal Varices in Cirrhosis: A Multi-Parameter Splenic CT Study

RATIONALE AND OBJECTIVES

To explore the value of splenic hemodynamic parameters from low-dose one-stop dual-energy and perfusion CT (LD-DE&PCT) in non-invasively predicting high-risk esophageal varices (HREV) in cirrhotic patients.

METHODS

We retrospectively analyzed cirrhotic patients diagnosed with esophageal varices (EV) through clinical, laboratory, imaging, and endoscopic examinations from September 2021 to December 2023 in our hospital. All patients underwent LD-DE&PCT to acquire splenic iodine concentration and perfusion parameters. Radiation dose was recorded. Patients were classified into non-HREV and HREV groups based on endoscopy. Univariate and multivariate logistic regression analysis were performed, and the prediction model for HREV was constructed. P < 0.05 was considered statistically significant.

RESULTS

Univariate analysis revealed that significant differences were found in portal iodine concentration (PIC), blood flow (BF), permeability surface (PS), spleen volume (V-S), total iodine concentration (TIC), and total blood volume of the spleen (BV-S) between groups. TIC demonstrated the highest predictive value with an area under the curve (AUC) value of 0.87. Multivariate analysis showed that PIC, PS, and BV-S were independent risk factors for HREV. The logistic regression model for predicting HREV had an AUC of 0.93. The total radiation dose was 20.66 ± 4.07 mSv.

CONCLUSION

Splenic hemodynamic parameters obtained from LD-DE&PCT can non-invasively and accurately assess the hemodynamic status of the spleen in cirrhotic patients with EV and predict the occurrence of HREV. Despite the retrospective study design and limited sample size of this study, these findings deserve further validation through prospective studies with larger cohorts.

Assessment of high-risk gastroesophageal varices in cirrhotic patients using quantitative parameters from dual-source dual-energy CT

PURPOSE

To investigate the clinical value of dual-source dual-energy CT (dsDECT) quantitative parameters in evaluating hemodynamics and predicting high-risk gastroesophageal varices in cirrhotic patients.

METHODS

98 consecutive patients were collected in this prospectively study and all patients underwent an abdominal triple-phase contrasted-enhanced examination with dsDECT. Iodine concentration (IC) and normalized iodine concentration (NIC) of the liver parenchyma, spleen parenchyma and aorta at different phases were recorded, and arterial iodine fraction (AIF), iodine washout rate (IWR), and extracellular volume (ECV) were calculated. Using upper gastrointestinal endoscopy as the reference standard, patients who met the inclusion and exclusion criteria were divided into groups with varices need treatment (VNT) and non-VNT. The clinical characteristics, traditional CT features and quantitative dsDECT parameters were compared between the VNT group and the non-VNT group using univariate analysis. The binary logistics analysis was used to build a model for diagnosing VNT. The receiver operating characteristic (ROC) curve was used for analysis and the DeLong test was used to compare different ROC curves.

RESULTS

Finally, 57 patients were included in this study. Univariate analysis showed statistically significant differences in NIC of the liver at the portal venous phase (NIC-LPVP), IWR of the liver (IWR-L) and spleen volume between the VNT group and the non-VNT group (p < 0.05). The mixed-CT model was built by binary logistics analysis. The ROC curves of NIC-LPVP, IWR-L, spleen volume and the mixed-CT model were statistically significant (p < 0.05) for predicting VNT in cirrhotic patients, among which the area under the ROC curve of the mixed-CT model was the highest.

CONCLUSION

Dual-source dual-energy CT has added clinical value in evaluating hepatic hemodynamics and diagnosing VNT in patients with liver cirrhosis.

Survival prediction of hepatocellular carcinoma by measuring the extracellular volume fraction with single-phase contrast-enhanced dual-energy CT imaging

Purpose

This study aimed to investigate the value of quantified extracellular volume fraction (fECV) derived from dual-energy CT (DECT) for predicting the survival outcomes of patients with hepatocellular carcinoma (HCC) after transarterial chemoembolization (TACE).

Materials and methods

A total of 63 patients with HCC who underwent DECT before treatment were retrospectively included. Virtual monochromatic images (VMI) (70 keV) and iodine density images (IDI) during the equilibrium phase (EP) were generated. The tumor VMI-fECV and IDI-fECV were measured and calculated on the whole tumor (Whole) and maximum enhancement of the tumor (Maximum), respectively. Univariate and multivariate Cox models were used to evaluate the effects of clinical and imaging predictors on overall survival (OS) and progression-free survival (PFS).

Results

The correlation between tumor VMI-fECV and IDI-fECV was strong (both p< 0.001). The Bland-Altman plot between VMI-fECV and IDI-fECV showed a bias of 5.16% for the Whole and 6.89% for the Maximum modalities, respectively. Increasing tumor VMI-fECV and IDI-fECV were positively related to the effects on OS and PFS (both p< 0.05). The tumor IDI-fECV-Maximum was the only congruent independent predictor in patients with HCC after TACE in the multivariate analysis on OS (p = 0.000) and PFS (p = 0.028). Patients with higher IDI-fECV-Maximum values had better survival rates above the optimal cutoff values, which were 35.42% for OS and 29.37% for PFS.

Conclusion

The quantified fECV determined by the equilibrium-phase contrast-enhanced DECT can potentially predict the survival outcomes of patients with HCC following TACE treatment.