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.

Public Health Relevance

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.

National Institute of Health (NIH)
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Research Project (R01)
Project #
Application #
Study Section
Biomedical Imaging Technology Study Section (BMIT)
Program Officer
Doo, Edward
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
University of Wisconsin Madison
Schools of Medicine
United States
Zip Code
Hernando, Diego; Sharma, Samir D; Aliyari Ghasabeh, Mounes et al. (2016) Multisite, multivendor validation of the accuracy and reproducibility of proton-density fat-fraction quantification at 1.5T and 3T using a fat-water phantom. Magn Reson Med :
Sharma, Samir D; Fischer, Roland; Schoennagel, Bjoern P et al. (2016) MRI-based quantitative susceptibility mapping (QSM) and R2* mapping of liver iron overload: Comparison with SQUID-based biomagnetic liver susceptometry. Magn Reson Med :
Colgan, Timothy J; Hernando, Diego; Sharma, Samir D et al. (2016) The effects of concomitant gradients on chemical shift encoded MRI. Magn Reson Med :
Grayev, Allison; Reeder, Scott; Hanna, Amgad (2016) Use of chemical shift encoded magnetic resonance imaging (CSE-MRI) for high resolution fat-suppressed imaging of the brachial and lumbosacral plexuses. Eur J Radiol 85:1199-207
Schubert, Tilman; Motosugi, Utaroh; Kinner, Sonja et al. (2016) Crossover comparison of ferumoxytol and gadobenate dimeglumine for abdominal MR-angiography at 3.0 tesla: Effects of contrast bolus length and flip angle. J Magn Reson Imaging :
Kinner, Sonja; Reeder, Scott B; Yokoo, Takeshi (2016) Quantitative Imaging Biomarkers of NAFLD. Dig Dis Sci 61:1337-47
Kasza, Ildiko; Hernando, Diego; Roldán-Alzate, Alejandro et al. (2016) Thermogenic profiling using magnetic resonance imaging of dermal and other adipose tissues. JCI Insight 1:e87146
Wang, Xiaoke; Hernando, Diego; Reeder, Scott B (2016) Sensitivity of chemical shift-encoded fat quantification to calibration of fat MR spectrum. Magn Reson Med 75:845-51
Mahlke, Christoph; Hernando, Diego; Jahn, Christina et al. (2016) Quantification of liver proton-density fat fraction in 7.1T preclinical MR systems: Impact of the fitting technique. J Magn Reson Imaging :
Rehm, Jennifer L; Wolfgram, Peter M; Hernando, Diego et al. (2015) Proton density fat-fraction is an accurate biomarker of hepatic steatosis in adolescent girls and young women. Eur Radiol 25:2921-30

Showing the most recent 10 out of 73 publications