Abstract Purpose To evaluate the test–retest repeatability of a rapid, free‐breathing two‐dimensional (2D) MR elastography (MRE) technique and to assess the reliability of the liver‐stiffness measurements compared with conventional breath‐hold MREs. Methods Fifteen and 115 participants were enrolled in the technical repeatability and measurement equivalence assessment cohorts, respectively. All participants underwent rapid free‐breathing and conventional breath‐hold 2D MRE (twice in repeatability cohort) on 1.5T scanners. Both methods have four phase offsets over one harmonic motion cycle at 60 Hz; one and 10 cycles were collected and processed in breath‐hold and free‐breathing MREs, respectively. The liver stiffness measurements of free‐breathing (LS F ) and breath‐hold MRE (LS B ) were calculated from manually drawn regions of interest. The repeatability coefficients and Spearman correlation were used to assess technical repeatability and measurement agreement between LS F and LS B . Univariable and multivariable linear regressions were performed to identify potential influencing factors, including age, sex, body mass index, and fat fraction, in the measurement agreement between LS B and LS F . Results The repeatability coefficient of free‐breathing 2D MRE is comparable to breath‐hold MRE (LS F : 20.8%, LS B : 20.4%). LS F showed a strong agreement and significant correlation with LS B (LS F = 1.01 × LS B , ρ = 0.94, p < 0.001). The measurement agreement between LS F and LS B was only significantly affected by sex ( p = 0.047) after adjusting for confounding factors of age, body mass index, and fat fraction. Conclusions The nongated, free‐breathing, multislice 2D MRE technique can provide reliable liver stiffness measurements compared with conventional breath‐hold 2D MRE. It could provide a comfortable alternative method with reliable liver stiffness measurements for patients who have difficulty in suspending respiration.
Multiparametric magnetic resonance imaging/magnetic resonance elastography assesses progression and regression of steatosis, inflammation, and fibrosis in alcohol‐associated liver disease
Abstract 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 CCl 4 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 CCl 4 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.