MRI and MRE for non-invasive quantitative assessment of hepatic steatosis and fibrosis in NAFLD and NASH: Clinical trials to clinical practice

Abstract

Non-alcoholic fatty liver disease (NAFLD) represents one of the most common causes of chronic liver disease, and its prevalence is rising worldwide. The occurrence of non-alcoholic steatohepatitis (NASH) is associated with a substantial increase in disease related morbidity and mortality. Accordingly, there has been a surge of innovation surrounding drug development in an effort to off-set the natural progression and long-term risks of this disease. Disease assessment within clinical trials and clinical practice for NAFLD is currently done with liver biopsies. Liver biopsy-based assessments, however, remain imprecise and are not without cost or risk. This carries significant implications for the feasibility and costs of bringing therapeutic interventions to market. A need therefore arises for reliable and highly accurate surrogate end-points that can be used in phase 2 and 3 clinical trials to reduce trial size requirements and costs, while improving feasibility and ease of implementation in clinical practice. Significant advances have now been made in magnetic resonance technology, and magnetic resonance imaging (MRI) and elastrography (MRE) have been demonstrated to be highly accurate diagnostic tools for the detection of hepatic steatosis and fibrosis. In this review article, we will summarize the currently available evidence regarding the use of MRI and MRE among NAFLD patients, and the evolving role these surrogate biomarkers will play in the rapidly advancing arena of clinical trials in NASH and hepatic fibrosis. Furthermore, we will highlight how these tools can be readily applied to routine clinical practice, where the growing burden of NAFLD will need to be met with enhanced monitoring algorithms.

Keywords: Magnetic resonance elastography; Magnetic resonance imaging; Non-alcoholic fatty liver disease; Non-alcoholic steatohepatitis.

Figure 1. Principles of MRI-PDFF assessment and quantification of hepatic steatosis

Moving left to right in the figure, you will first find the complex method of estimating PDFF, which acquires real and imaginary images to generate a PDFF map from 0–100%, labeled “C-MRI PDFF” here. Next are the magnitude images which are squared to generate a PDFF map from 0–50%, labeled “M-MRI PDFF” here. Both techniques acquire multiple images at echo times optimally spaced for fat water separation and T2* signal decay correction, and both apply a multi peak spectral model to correct for multi-frequency interference effects of fat proton signals. Note that for magnitude based PDFF, the calculated image only has a range of 0 to 50%. This is within the typical biological limits of liver fat content.

Figure 2. Co-localization of regions of interest and responsiveness of MRI-PDFF and MRE

Figures adapted and modified from Loomba et al. Figure 2A: Anatomical co-localization of regions of interest. Figure 2B: Whole liver fat mapping with magnetic resonance imaging proton density fat fraction (MRI-PDFF) at weeks 0 and 24. Figure 2C: Whole liver fibrosis mapping with magnetic resonance elastography (MRE) at weeks 0 and 24.

Figure 2. Co-localization of regions of interest and responsiveness of MRI-PDFF and MRE

Figures adapted and modified from Loomba et al. Figure 2A: Anatomical co-localization of regions of interest. Figure 2B: Whole liver fat mapping with magnetic resonance imaging proton density fat fraction (MRI-PDFF) at weeks 0 and 24. Figure 2C: Whole liver fibrosis mapping with magnetic resonance elastography (MRE) at weeks 0 and 24.