- NAFLD
- NASH
- Liver
- MR
The Challenges of NAFLD and NASH
- Nonalcoholic fatty liver disease (NAFLD) is the most common liver disease, with a worldwide prevalence of 25%.2
- In the United States, NAFLD and its subtype, nonalcoholic steatohepatitis (NASH), affect 30% and 5% of the population, respectively.2
- NAFLD patients with evidence of NASH and advanced fibrosis are at markedly increased risk of adverse outcomes, including overall mortality.2
- Identification of NASH patients is paramount, given the associated poorer outcomes, in order to target resources to those who need it most.2
Advanced Imaging and Quantitative Analysis for Liver Health Assessment
LiverMultiScan (LMSv5) is designed to utilize DICOM 3.0 compliant magnetic resonance image data-sets, acquired from compatible MR systems, to display the internal structure of the abdomen including the liver. Other physical parameters derived from the images may also be produced. LiverMultiScan (LMSv5) provides a number of tools, such as automated liver segmentation and region of interest (ROI) placements, to be used for the assessment of selected regions of an image.1
Quantitative assessments of selected regions include the determination of triglyceride fat fraction in the liver (PDFF), T2*, Liver Iron Concentration (LIC) and iron corrected T1 (cT1) measurements. These images and the physical parameters derived from the images, when interpreted by a trained clinician, yield information that may assist in diagnosis.1
1 LiverMultiScan v5.0 operator user guide PDM0399
2 Cotter TG, Rinella M. Nonalcoholic Fatty Liver Disease 2020: The State of the Disease. Gastroenterology. 2020 May;158(7):1851-1864. doi: 10.1053/j.gastro.2020.01.052. Epub 2020 Feb 13. PMID: 32061595.
3 Hoad C, Palaniyappan N, Kaye P, Chernova Y, James M, Costigan C, et al. A study of T₁ relaxation time as a measure of liver fibrosis and the influence of confounding histological factors. NMR Biomed. 2015;28(6):706–14.
4 Pavlides M., Banerjee R., Sellwood J., Kelly CJ., Robson MD., Booth JC., et al. Multiparametric magnetic resonance imaging predicts clinical outcomes in patients with chronic liver disease. J Hepatol. 2016;64(2):308– 15.
5 Bradley CR, Cox EF, Scott RA, James MW, Kaye P, Aithal GP, et al. Multi organ assessment of compensated cirrhosis patients using quantitative magnetic resonance imaging. J Hepatol. 2018 Jun;69(5):1015–24.
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