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Non-alcoholic fatty liver disease is a major health problem worldwide. It includes simple steatosis and NASH which has inflammation in the liver, with or without fibrosis. Fat content, fibrosis, and inflammation are three important components to evaluate NASH. Liver biopsy is the current gold standard for the diagnosis of NASH. Liver biopsy; however, is invasive. The existing non-invasive methods still have significant limitations to assess NASH. It was reported that quantification of fatty acid composition is feasible for evaluation of metabolic disorders and inflammatory conditions. However, this measurement cannot be used to evaluate fibrosis. Liver fibrosis is characterized by excessive deposition of collagen-rich connective tissues in the liver, which can be quantified by macromolecular proton fraction (MPF), an MRI parameter reflecting the macromolecular level in tissues. Although it has the potential to directly quantify fibrotic tissue, the effect of inflammation on MPF measurement was not well studied. In summary, NASH assessment using non-invasive imaging methods remains challenging. Based on our previous work of MPF imaging with spin-lock (MPF-SL) and chemical-shift encoding-based water-fat imaging in spin-lock MRI, the investigators will develop a fast acquisition technology to collect data for simultaneous quantification of liver fat content, fatty acid composition, and fibrosis within a single breath-hold less than 14 seconds. Our method does not require extra hardware and does not need to inject a contrast agent. The investigators will evaluate the repeatability and reproducibility of the proposed method on volunteers. To evaluate its clinical value, the investigators will recruit 120 subjects (60 with simple steatosis and 60 with NASH) in this study. The investigators will use histology analysis as the gold standard and evaluate the diagnostic value of our proposed method for detecting NASH. This project will provide a non-invasive diagnostic technology for the assessment of NASH. The proposed MRI technology also has the potential to be applied for other clinical purposes.
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140 participants in 3 patient groups
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Weitian Chen
Data sourced from clinicaltrials.gov
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