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Objectives: To explore which preoperative clinical data and conventional MRI findings may indicate microvascular invasion (MVI) of combined hepatocellular-cholangiocarcinoma (cHCC-CCA) and have clinical significance.Methods: The study enrolled 113 patients with histopathologically confirmed cHCC-CCA (MVI-positive group [n = 56], MVI-negative group [n = 57]). Two radiologists retrospectively assessed the preoperative MRI features (qualitative analysis of morphology and dynamic enhancement features), and each lesion was assigned according to the LI-RADS. Preoperative clinical data were also evaluated. Logistic regression analyses were used to assess the relative value of these parameters as potential predictors of MVI. Recurrence-free survival (RFS) rates after hepatectomy in the two groups were estimated using Kaplan-Meier survival curves and compared using the log-rank test.Results: The majority of cHCC-CCAs were categorized as LR-M. On multivariate analysis, a higher serum AFP level (OR, 0.523; 95% CI, 0.282-0.971; p = 0.040), intratumoral fat deposition (OR, 14.368; 95% CI, 2.749-75.098; p = 0.002), and irregular arterial peritumoral enhancement (OR, 0.322; 95% CI, 0.164-0.631; p = 0.001) were independent variables associated with the MVI of cHCC-CCA. After hepatectomy, patients with MVI of cHCC-CCA showed earlier recurrence than those without MVI (hazard ratio [HR], 0.402; 95% CI, 0.189-0.854, p = 0.013).Conclusion: A higher serum AFP level and irregular arterial peritumoral enhancement are potential predictive biomarkers for the MVI of cHCC-CCA, while intratumoral fat detected on MRI suggests a low risk of MVI. Furthermore, cHCC-CCAs with MVI may have worse surgical outcomes with regard to early recurrence than those without MVI.Key Points: • Higher serum levels of AFP combined with irregular arterial peritumoral enhancement are independent risk factors for the MVI of cHCC-CCA, while fat deposition might be a protective factor. • cHCC-CCA with MVI may have a higher risk of early recurrence after surgery. • Most cHCC-CCAs were categorized as LR-M in this study, and no significant difference was found in MVI based on LI-RADS category. [ABSTRACT FROM AUTHOR]

Objectives: We aimed to develop a radiomics-based model derived from gadoxetic acid-enhanced MR images to preoperatively identify cytokeratin (CK) 19 status of hepatocellular carcinoma (HCC).Methods: A cohort of 227 patients with single HCC was classified into a training set (n = 159) and a time-independent validated set (n = 68). A total of 647 radiomic features were extracted from multi-sequence MR images. The least absolute shrinkage and selection operator regression and decision tree methods were utilized for feature selection and radiomics signature construction. A multivariable logistic regression model incorporating clinico-radiological features and the fusion radiomics signature was built for prediction of CK19 status by evaluating area under curve (AUC).Results: In the whole cohort, 57 patients were CK19 positive and 170 patients were CK19 negative. By combining 11 and 6 radiomic features extracted in arterial phase and hepatobiliary phase images, respectively, a fusion radiomics signature achieved AUCs of 0.951 and 0.822 in training and validation datasets. The final combined model integrated a-fetoprotein levels, arterial rim enhancement pattern, irregular tumor margin, and the fusion radiomics signature, with a sensitivity of 0.818 and specificity of 0.974 in the training cohort and that of 0.769 and 0.818 in the validated cohort. The nomogram based on the combined model showed satisfactory prediction performance in training (C-index 0.959) and validation (C-index 0.846) dataset.Conclusions: The combined model based on a fusion radiomics signature derived from arterial and hepatobiliary phase images of gadoxetic acid-enhanced MRI can be a reliable biomarker for CK19 status of HCC.Key Points: • Arterial rim enhancement pattern and irregular tumor margin on hepatobiliary phase on gadoxetic acid-enhanced MRI can be useful for evaluating CK19 status of HCC. • A radiomics-based model performed better than the clinico-radiological model both in training and validation datasets for predicting CK19 status of HCC. • The nomogram based on the fusion radiomics signature can be easily used for CK19 stratification of HCC. [ABSTRACT FROM AUTHOR]

Objectives: To assess liver fibrosis in patients with chronic liver disease using diffusion kurtosis imaging (DKI) in comparison with conventional diffusion-weighted imaging, with histology as reference standard.Methods: This prospective study included 81 patients and DKI with b-values of 0, 200, 500, 1,000, 1,500, 2,000 s/mm2 were performed. Mean diffusivity (MD), mean kurtosis (MK) and apparent diffusion coefficient (ADC) maps were calculated. The diagnostic efficacy of MD, MK and ADC for predicting stage 2 fibrosis or greater, and stage 3 fibrosis or greater were compared.Results: The MD (rho=-0.491, p<0.001), MK (rho=0.537, p<0.001) and ADC (rho=-0.496, p<0.001) correlated significantly with fibrosis stages, and ADC exhibited a strong negative correlation with MK (rho=-0.968; p<0.001) and a moderate association with MD (rho=0.601, p<0.001). Areas under the curves (AUCs) for predicting stage 2 fibrosis or greater were not significantly different (p>0.05) between MK (0.809) and ADC (0.797) as well as between MD (0.715) and ADC. AUCs were also similar for MD (0.710), MK (0.768) and ADC (0.747) for predicting stage 3 fibrosis or greater.Conclusion: Although DKI is feasible for predicting liver fibrosis in patients with chronic liver disease, MD and MK offer similar diagnostic performance to ADC values.Key Points: • Diffusion kurtosis imaging is feasible for staging liver fibrosis. • Diffusion kurtosis and monoexponential model are highly correlated. • The kurtosis model offers no added value to the conventional, monoexponential model. [ABSTRACT FROM AUTHOR]