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J Formos Med Assoc ; 118(11): 1522-1527, 2019 Nov.
Article in English | MEDLINE | ID: mdl-30621960

ABSTRACT

BACKGROUND/PURPOSE: The study aim to investigate the correlation between diffusion-weighted magnetic resonance imaging (DW-MRI) and transient elastography (TE) liver fibrosis findings in children with cholestatic liver diseases, and the utility of TE findings to predict cholestatic complications in children. METHODS: This cross-sectional study enrolled 36 cholestatic children (21 boys and 15 girls). All study subjects underwent TE and DW-MRI studies to assess liver stiffness. All study subjects were followed prospectively, and their cholestatic complications were analyzed. The optimum cut-off TE value for the prediction of cholestatic complications was determined by receiver operating characteristic (ROC) analysis. RESULTS: A significant negative correlation between liver stiffness measurements (LSMs) and right-liver-to-psoas apparent diffusion coefficient ratios (LTPARs) was found in the study cohort (correlation coefficient = -0.52, p = 0.001). An LSM cut-off > 8.6 kPa was optimal for predicting complications of cholestasis in 6 months of this cohort (p < 0.001). Survival analysis revealed that an LSM of >8.6 kPa was significantly predictive of cholestatic complications in 6 months (hazard ratio = 4.89; 95% CI = 1.41-16.97; p = 0.01). CONCLUSION: TE and DW-MRI findings showed a similar ability to predict liver fibrosis in cholestatic children. The LSMs measured by TE are predictive of the occurrence of cholestatic complications in 6 months in children with cholestatic liver diseases.


Subject(s)
Cholestasis/diagnostic imaging , Diffusion Magnetic Resonance Imaging/statistics & numerical data , Elasticity Imaging Techniques/statistics & numerical data , Liver Cirrhosis/diagnostic imaging , Child, Preschool , Cholestasis/complications , Cholestasis/pathology , Cross-Sectional Studies , Female , Humans , Infant , Liver/diagnostic imaging , Liver/pathology , Liver Cirrhosis/etiology , Male , Predictive Value of Tests , ROC Curve , Reproducibility of Results
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