BACKGROUND: Magnetic resonance imaging (MRI) and MRI-based elastography (MRE) are the most promising noninvasive techniques in assessing liver diseases. The purpose of this study was to evaluate an advanced multiparametric imaging method for staging disease and assessing treatment response in realistic preclinical alcohol-associated liver disease (ALD). METHODS: We utilized four different preclinical mouse models in our study: Model 1-mice were fed a fast-food diet and fructose water for 48 weeks to induce nonalcoholic fatty liver disease; Model 2-mice were fed chronic-binge ethanol (EtOH) for 10 days or 8 weeks to induce liver steatosis/inflammation. Two groups of mice were treated with interleukin-22 at different time points to induce disease regression; Model 3-mice were administered CCl4 for 2 to 4 weeks to establish liver fibrosis followed by 2 or 4 weeks of recovery; and Model 4-mice were administered EtOH plus CCl4 for 12 weeks. Mouse liver imaging biomarkers including proton density fat fraction (PDFF), liver stiffness (LS), loss modulus (LM), and damping ratio (DR) were assessed. Liver and serum samples were obtained for histologic and biochemical analyses. Ordinal logistic regression and generalized linear regression analyses were used to model the severity of steatosis, inflammation, and fibrosis, and to assess the regression of these conditions. RESULTS: Multiparametric models with combinations of biomarkers (LS, LM, DR, and PDFF) used noninvasively to predict the histologic severity and regression of steatosis, inflammation, and fibrosis were highly accurate (area under the curve > 0.84 for all). A three-parameter model that incorporates LS, DR, and ALT predicted histologic fibrosis progression (r = 0.84, p < 0.0001) and regression (r = 0.79, p < 0.0001) as measured by collagen content in livers. CONCLUSION: This preclinical study provides evidence that multiparametric MRI/MRE can be used noninvasively to assess disease severity and monitor treatment response in ALD.
BACKGROUND: Magnetic resonance imaging (MRI) and MRI-based elastography (MRE) are the most promising noninvasive techniques in assessing liver diseases. The purpose of this study was to evaluate an advanced multiparametric imaging method for staging disease and assessing treatment response in realistic preclinical alcohol-associated liver disease (ALD). METHODS: We utilized four different preclinical mouse models in our study: Model 1-mice were fed a fast-food diet and fructose water for 48 weeks to induce nonalcoholic fatty liver disease; Model 2-mice were fed chronic-binge ethanol (EtOH) for 10 days or 8 weeks to induce liver steatosis/inflammation. Two groups of mice were treated with interleukin-22 at different time points to induce disease regression; Model 3-mice were administered CCl4 for 2 to 4 weeks to establish liver fibrosis followed by 2 or 4 weeks of recovery; and Model 4-mice were administered EtOH plus CCl4 for 12 weeks. Mouse liver imaging biomarkers including proton density fat fraction (PDFF), liver stiffness (LS), loss modulus (LM), and damping ratio (DR) were assessed. Liver and serum samples were obtained for histologic and biochemical analyses. Ordinal logistic regression and generalized linear regression analyses were used to model the severity of steatosis, inflammation, and fibrosis, and to assess the regression of these conditions. RESULTS: Multiparametric models with combinations of biomarkers (LS, LM, DR, and PDFF) used noninvasively to predict the histologic severity and regression of steatosis, inflammation, and fibrosis were highly accurate (area under the curve > 0.84 for all). A three-parameter model that incorporates LS, DR, and ALT predicted histologic fibrosis progression (r = 0.84, p < 0.0001) and regression (r = 0.79, p < 0.0001) as measured by collagen content in livers. CONCLUSION: This preclinical study provides evidence that multiparametric MRI/MRE can be used noninvasively to assess disease severity and monitor treatment response in ALD.
Authors: Ziying Yin; Matthew C Murphy; Jiahui Li; Kevin J Glaser; Amy S Mauer; Taofic Mounajjed; Terry M Therneau; Heshan Liu; Harmeet Malhi; Armando Manduca; Richard L Ehman; Meng Yin Journal: Eur Radiol Date: 2019-03-18 Impact factor: 5.315
Authors: Michael S Middleton; Elhamy R Heba; Catherine A Hooker; Mustafa R Bashir; Kathryn J Fowler; Kumar Sandrasegaran; Elizabeth M Brunt; David E Kleiner; Edward Doo; Mark L Van Natta; Joel E Lavine; Brent A Neuschwander-Tetri; Arun Sanyal; Rohit Loomba; Claude B Sirlin Journal: Gastroenterology Date: 2017-06-15 Impact factor: 22.682
Authors: Beth A Davison; Stephen A Harrison; Gad Cotter; Naim Alkhouri; Arun Sanyal; Christopher Edwards; Jerry R Colca; Julie Iwashita; Gary G Koch; Howard C Dittrich Journal: J Hepatol Date: 2020-06-28 Impact factor: 25.083
Authors: Hannah L Paish; Lee H Reed; Helen Brown; Mark C Bryan; Olivier Govaere; Jack Leslie; Ben S Barksby; Marina Garcia Macia; Abigail Watson; Xin Xu; Marco Y W Zaki; Laura Greaves; Julia Whitehall; Jeremy French; Steven A White; Derek M Manas; Stuart M Robinson; Gabriele Spoletini; Clive Griffiths; Derek A Mann; Lee A Borthwick; Michael J Drinnan; Jelena Mann; Fiona Oakley Journal: Hepatology Date: 2019-05-28 Impact factor: 17.425