The overall goal of this proposal is to develop and validate non-invasive quantitative methods for early diagnosis and quantitative grading of Non-Alcoholic Fatty Liver Disease (NAFLD), using magnetic resonance imaging (MRI). NAFLD is an emerging condition now recognized as the most common type of chronic liver disease, afflicting an estimated 90-100 million (>30%) people in the United States alone, including 10% of all children. The earliest and hallmark feature of NAFLD is intracellular fatty infiltration of hepatocytes (steatosis). In many patients, steatosis leads to inflammation and fibrosis. These patients develop cirrhosis and may succumb to liver failure and/or hepatocellular carcinoma, necessitating liver transplant. Diagnosis of NAFLD is limited because it relies on biopsy, which is expensive, risky, and is highly variable for grading of steatosis. There is an urgent unmet need for accurate quantitative non-invasive methods to facilitate early detection and quantitative grading of NAFLD. We seek to address this unmet need by developing MRI methods that quantify hepatic """"""""fat-fraction"""""""" as a biomarker of steatosis. Importantly, hepatic iron overload coexists in many patients with NAFLD. Although the role of iron in NAFLD is unknown, its presence confounds MRI estimates of fat due to iron-induced accelerated signal decay (T2* decay). Therefore, a secondary goal of this work is to quantify T2* as a biomarker of hepatic iron overload, through methods that decouple the effects of iron and fat by estimating T2* and fat-fraction simultaneously. Other important confounding factors must also be addressed. These include: T1 relaxation, image noise, the multiple NMR spectral peaks of fat, and eddy currents. We will use an established qualitative water-fat separation method developed by the PI as a foundation from which new methods are developed. To achieve our goals, we aim to 1) develop new quantitative MRI biomarkers of hepatic steatosis (fat-fraction) and iron overload (T2*) in a single breath- hold (20s), with complete liver coverage. We will accelerate these methods with parallel imaging to achieve clinically acceptable scan times (20s). We will then validate these methods in 2a) a combined mouse model of steatosis and iron overload, and in 2b) explanted human livers rejected for transplantation due to steatosis, with a rigorous biopsy-imaging correlation study. Finally, we will perform 3) a prospective clinical pilot study that compares our quantitative MRI methods with biopsy in patients with suspected NAFLD. This proposal responds to the NIDDK program announcement PA-09-181 for development of non-invasive methods for diagnosis and grading of diseases of interest to the NIDDK, which includes NAFLD.
We aim to meet the urgent unmet need for biomarkers that non-invasively quantify steatosis, and secondarily iron, without the inaccuracy, danger, and cost of biopsy. Successful development of these quantitative MRI biomarkers will provide an unprecedented opportunity for pre-emptive intervention for the treatment of this important and increasingly prevalent cause of cirrhosis, liver failure and hepatocellular carcinoma.
The goal of this proposal is to develop, implement and validate methods to measure the amount of fat and iron in the livers of people with Non-Alcoholic Fatty Liver Disease (NAFLD) using magnetic resonance imaging (MRI). NAFLD is an increasingly important cause of liver failure and liver cancer, and currently there are no reliable and safe methods to diagnose and evaluate the severity of this disease, which affects nearly 1 in 3 adults and 1 in 10 children. We aim to develop new MRI methods that will provide early detection and evaluation of the severity of NAFLD in order to guide treatments that halt or reverse liver damage.
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|Campo, Camilo A; Hernando, Diego; Schubert, Tilman et al. (2017) Standardized Approach for ROI-Based Measurements of Proton Density Fat Fraction and R2* in the Liver. AJR Am J Roentgenol 209:592-603|
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|Wang, Xiaoke; Reeder, Scott B; Hernando, Diego (2017) An acetone-based phantom for quantitative diffusion MRI. J Magn Reson Imaging 46:1683-1692|
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