Quantitative, noninvasive MRI characterization of disease progression in a mouse model of non-alcoholic steatohepatitis

作者
Philip A. Waghorn,Diêgo S. Ferreira,Derek J. Erstad,Nicholas J. Rotile,Ricard Masia,Chloe M. Jones,Chuantao Tu,Mozhdeh Sojoodi,Yin-Ching I. Chen,Franklin Schlerman,Jeremy Wellen,Robert V. Martinez,Kenneth K. Tanabe,Bryan C. Fuchs,Peter Caravan
出处
期刊:Scientific Reports [Nature Portfolio]
卷期号:11 (1): 6105-6105 被引量:14
标识
DOI:10.1038/s41598-021-85679-4
摘要

Non-alcoholic steatohepatitis (NASH) is an increasing cause of chronic liver disease characterized by steatosis, inflammation, and fibrosis which can lead to cirrhosis, hepatocellular carcinoma, and mortality. Quantitative, noninvasive methods for characterizing the pathophysiology of NASH at both the preclinical and clinical level are sorely needed. We report here a multiparametric magnetic resonance imaging (MRI) protocol with the fibrogenesis probe Gd-Hyd to characterize fibrotic disease activity and steatosis in a common mouse model of NASH. Mice were fed a choline-deficient, L-amino acid-defined, high-fat diet (CDAHFD) to induce NASH with advanced fibrosis. Mice fed normal chow and CDAHFD underwent MRI after 2, 6, 10 and 14 weeks to measure liver T1, T2*, fat fraction, and dynamic T1-weighted Gd-Hyd enhanced imaging of the liver. Steatosis, inflammation, and fibrosis were then quantified by histology. NASH and fibrosis developed quickly in CDAHFD fed mice with strong correlation between morphometric steatosis quantification and liver fat estimated by MRI (r = 0.90). Sirius red histology and collagen quantification confirmed increasing fibrosis over time (r = 0.82). Though baseline T1 and T2* measurements did not correlate with fibrosis, Gd-Hyd signal enhancement provided a measure of the extent of active fibrotic disease progression and correlated strongly with lysyl oxidase expression. Gd-Hyd MRI accurately detects fibrogenesis in a mouse model of NASH with advanced fibrosis and can be combined with other MR measures, like fat imaging, to more accurately assess disease burden.

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