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  • PMID: 21928307 was deleted because it is a duplicate of PMID: 22025886
J Magn Reson Imaging. 2011 Oct;34(4):729-749. doi: 10.1002/jmri.22580. Epub 2011 Sep 16.

Quantitative Assessment of Liver Fat with Magnetic Resonance Imaging and Spectroscopy.

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Liver Imaging Research Group, Departments of Radiology, Medical Physics, Biomedical Engineering and Medicine, University of Wisconsin, Madison, WI.


Hepatic steatosis is characterized by abnormal and excessive accumulation of lipids within hepatocytes. It is an important feature of diffuse liver disease, and the histological hallmark of non-alcoholic fatty liver disease (NAFLD). Other conditions associated with steatosis include alcoholic liver disease, viral hepatitis, HIV and genetic lipodystrophies, cystic fibrosis liver disease, and hepatotoxicity from various therapeutic agents. Liver biopsy, the current clinical gold standard for assessment of liver fat, is invasive and has sampling errors, and is not optimal for screening, monitoring, clinical decision making, or well-suited for many types of research studies. Non-invasive methods that accurately and objectively quantify liver fat are needed. Ultrasound (US) and computed tomography (CT) can be used to assess liver fat but have limited accuracy as well as other limitations. Magnetic resonance (MR) techniques can decompose the liver signal into its fat and water signal components and therefore assess liver fat more directly than CT or US. Most magnetic resonance (MR) techniques measure the signal fat-fraction (the fraction of the liver MR signal attributable to liver fat), which may be confounded by numerous technical and biological factors and may not reliably reflect fat content. By addressing the factors that confound the signal fat-fraction, advanced MR techniques measure the proton density fat-fraction (the fraction of the liver proton density attributable to liver fat), which is a fundamental tissue property and a direct measure of liver fat content. These advanced techniques show promise for accurate fat quantification and are likely to be commercially available soon.


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