4.7 Article

Noninvasive prediction of HCC with progenitor phenotype based on gadoxetic acid-enhanced MRI

Journal

EUROPEAN RADIOLOGY
Volume 30, Issue 2, Pages 1232-1242

Publisher

SPRINGER
DOI: 10.1007/s00330-019-06414-2

Keywords

Hepatocellular carcinoma; Cytokeratin 19; Epithelial cell adhesion molecule; Magnetic resonance imaging; Nomogram

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Objectives To explore the noninvasive prediction of hepatocellular carcinoma (HCC) with progenitor phenotype based on gadoxetic acid-enhanced magnetic resonance imaging (MRI). Methods This retrospective study included 115 surgery-proven HCCs with preoperative gadoxetic acid-enhanced MRI from August 2015 to September 2018. Image features were reviewed. Quantitative image analysis was performed using histogram analysis. HCC with progenitor phenotype was defined as positive for either cytokeratin 19 (CK19) or epithelial cell adhesion molecule (EpCAM) expression. Statistically significant variables for identifying HCCs with progenitor phenotype were determined at multivariate analyses. ROC analyses were used to determined cutoff values and the diagnostic performance of significant variables and combinations. Prediction nomogram was constructed based on multivariate analysis. Results At multivariate regression analyses, AFP >= 155.25 ng/mL (p < 0.001), skewness on T2WI <= 1.10 (p = 0.024), uniformity on pre-T1WI <= 0.91 (p = 0.024), irregular tumor margin (p = 0.006), targetoid appearance (p = 0.001), and the absence of mosaic architecture (p = 0.014) were significant predictors of HCCs expressing progenitor cell markers. Combing any three of those significant variables, it provides a diagnostic accuracy of 0.86 (95% CI 0.78-0.92) with sensitivity of 0.97 (95% CI 0.86-1.00), and specificity of 0.74 (95% CI 0.63-0.83). The C-index of the regression coefficient-based nomogram was 0.94 (95% CI 0.91-0.98). Conclusions Noninvasive prediction of HCCs with progenitor phenotype can be achieved with high accuracy by integrated interpretation of biochemical and radiological information, representing a handy tool for precise patient management and the prediction of prognosis.

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