Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
8159911 | Magnetic Resonance Imaging | 2018 | 36 Pages |
Abstract
To assess the value of T1Ï,T1Ï on hepatobiliary phase (HBP) and diffusion metrics in staging of Non-alcoholic fatty liver disease (NAFLD) activity scores, inflammation, fibrosis in NASH rabbits model. Non-alcoholic steatohepatitis (NASH) rabbits model was induced by feeding a varied duration of high-fat, high-cholesterol diet. T1Ï,T1Ï (HBP) 20 min after administration of Gd-EOB-DTPA, and Intravoxel incoherent motion imaging (IVIM) diffusion-weighted imaging were performed on a 3.0 T magnetic resonance (MR) imaging unit. The diagnostic value of each parameter for NAS, inflammation and fibrosis severity were determined. T1Ï (r = 0.658) and T1Ï (HBP) (r = 0.750) have strong association with NASH overall activity, T1Ï (HBP) is strongly relevant to inflammation stage (r = 0.812). There was negative association between f and inflammation (r = â 0.480), whilst no significant relation between other three parameters (apparent diffusion coefficient (ADC), pseudo-diffusion coefficient (D*) and true diffusion coefficient (D)) and inflammation or overall activity. The areas under the receiver operating characteristic curves (AUCs) of f, ADC, T1Ï and T1Ï-HBP were 0.871, 0.728, 0.849 and 0.949 for differentiating NASH; 0.731, 0.552, 0.925 and 0.922 for G2-3 inflammation; and 0.767, 0.625, 0.816, and 0.882 for S1-2 fibrosis. Comparison of ROC curve showed T1Ï (HBP) had an optimal diagnostic performance for NASH [T1Ï (HBP) vs ADC, AUC:0.949 vs 0.728, P = 0.043], inflammation [T1Ï (HBP) vs ADC, AUC:0.922 vs 0.552, P = 0.003], fibrosis [T1Ï (HBP) vs ADC, AUC:0.882 vs 0.625, P = 0.046]. The combination of T1Ï (HBP) + perfusion fraction (f) showed highest diagnostic value for NASH (AUC:0.971), inflammation (AUC:0.935). Among T1Ï imaging and IVIM diffusion metrics, combination of T1rho (HBP) + f was found to be superior noninvasive imaging biomarker for NASH activity assessment.
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Authors
Yuanliang Xie, Hongfeng Zhang, Chaoling Jin, Xiang Wang, Xiaoqi Wang, Jingting Chen, Yikai Xu,