OBJECTIVES: To develop a non-invasive MRI method for evaluation of liver fibrosis, with histological analysis as the reference standard. METHODS: The study protocol was approved by the Institutional Review Board for Human Studies of our hospital, and written informed consent was obtained from all subjects. Seventy-nine subjects who received dynamic contrast-enhanced MRI (DCE-MRI) with Gd-EOB-DTPA were divided into three subgroups according to Metavir score: no fibrosis (n = 30), mild fibrosis (n = 34), and advanced fibrosis (n = 15). The DCE-MRI parameters were measured using two models: (1) dual-input single-compartment model for arterial blood flow (F (a)), portal venous blood flow, total liver blood flow, arterial fraction (ART), distribution volume, and mean transit time; and (2) curve analysis model for Peak, Slope, and AUC. Statistical analysis was performed with Student's t-test and the nonparametric Kruskal-Wallis test. RESULTS: Slope and AUC were two best perfusion parameters to predict the severity of liver fibrosis (>F2 vs. ≦F2). Four significantly different variables were found between non-fibrotic versus mild-fibrotic subgroups: F (a), ART, Slope, and AUC; the best predictor for mild fibrosis was F (a) (AUROC:0.701). CONCLUSIONS: DCE-MRI with Gd-EOB-DTPA is a noninvasive imaging, by which multiple perfusion parameters can be measured to evaluate the severity of liver fibrosis.
OBJECTIVES: To develop a non-invasive MRI method for evaluation of liver fibrosis, with histological analysis as the reference standard. METHODS: The study protocol was approved by the Institutional Review Board for Human Studies of our hospital, and written informed consent was obtained from all subjects. Seventy-nine subjects who received dynamic contrast-enhanced MRI (DCE-MRI) with Gd-EOB-DTPA were divided into three subgroups according to Metavir score: no fibrosis (n = 30), mild fibrosis (n = 34), and advanced fibrosis (n = 15). The DCE-MRI parameters were measured using two models: (1) dual-input single-compartment model for arterial blood flow (F (a)), portal venous blood flow, total liver blood flow, arterial fraction (ART), distribution volume, and mean transit time; and (2) curve analysis model for Peak, Slope, and AUC. Statistical analysis was performed with Student's t-test and the nonparametric Kruskal-Wallis test. RESULTS: Slope and AUC were two best perfusion parameters to predict the severity of liver fibrosis (>F2 vs. ≦F2). Four significantly different variables were found between non-fibrotic versus mild-fibrotic subgroups: F (a), ART, Slope, and AUC; the best predictor for mild fibrosis was F (a) (AUROC:0.701). CONCLUSIONS:DCE-MRI with Gd-EOB-DTPA is a noninvasive imaging, by which multiple perfusion parameters can be measured to evaluate the severity of liver fibrosis.
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