The proposal's broad, long-term objective is to improve the health of millions of Americans with or at risk for non-alcoholic fatty liver disease (NAFLD). The immediate goal is to technically validate magnetic resonance imaging (MRI) determined proton density fat fraction (PDFF) as a biomarker of liver fat by demonstrating:
Aim 1. Accuracy against an independent, definitive reference standard. We will determine and compare the accuracy of PDFF as measured by two MRI techniques, using tissue triglyceride concentration as the reference standard. We hypothesize that PDFF will accurately predict TG concentration. We will identify the more accurate technique.
Aim 2. Precision with high repeatability and reproducibility. We will assess the repeatability within subjects and reproducibility across sites, scanners and readers of PDFF values as measured by two MRI techniques. We hypothesize that PDFF will be repeatable and reproducible. We will identify the more repeatable and reproducible technique.
Aim 3. Clinical and research value. We will use PDFF as a biomarker to define the relationship between weight loss and liver fat in obese adults undergoing gastric banding, demonstrating its utility as an objective tool for repeated measures of liver fat content. We hypothesize that PDFF will decrease monotonically in response to weight loss. Factors that modulate this relationship will be identified. Significance: NAFLD is the most common chronic liver disease of adults and children in the United States. It may progress to cirrhosis and contribute to the development of cardiovascular disease and type 2 diabetes. Liver biopsy, the current clinical gold standard to assess liver fat and diagnose NAFLD, is invasive. This limitation has hindered progress in the diagnosis, treatment, and prevention of NAFLD. A valid non-invasive biomarker of liver fat content is needed for clinical care and research. New breath-hold MRI methods refined at the University of California, San Diego and the University of Wisconsin address the sources of errors in conventional MRI for measuring liver fat. These new methods permit rapid estimation of PDFF, the fraction of mobile protons in liver attributable to fat. Preliminary data suggests that PDFF accurately predicts liver TG concentration, the biochemical measure of liver fat content;but rigorous validation is required to establish MRI-determined PDFF as a reliable and useful biomarker. Research design and methods: We plan a two-site prospective cohort study. The two-site design provides unbiased comparison of competing techniques, adequate patient enrollment, and the ability to compare performance characteristics across sites. We will enroll 140 obese adults (70 per site) participating in a surgical weight loss program (laparoscopic adjustable gastric banding). Enrolled subjects will have variable baseline liver fat content;have multiple intra-operative biopsies providing a definitive reference standard with which to compare PDFF measurements;and lose weight and liver fat at variable rates. PDFF will be measured using two MRI techniques at multiple time points before and after surgery.

Public Health Relevance

This proposal will show that magnetic resonance imaging is a safe, rapid, relatively inexpensive, and accurate alternative to liver biopsy for measuring liver fat in the tens of millions of Americans affected by or at risk for fatty liver disease.

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Research Project (R01)
Project #
5R01DK088925-02
Application #
8142105
Study Section
Medical Imaging Study Section (MEDI)
Program Officer
Doo, Edward
Project Start
2010-09-15
Project End
2015-06-30
Budget Start
2011-07-01
Budget End
2012-06-30
Support Year
2
Fiscal Year
2011
Total Cost
$605,675
Indirect Cost
Name
University of California San Diego
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
804355790
City
La Jolla
State
CA
Country
United States
Zip Code
92093
Hong, Cheng William; Mamidipalli, Adrija; Hooker, Jonathan C et al. (2018) MRI proton density fat fraction is robust across the biologically plausible range of triglyceride spectra in adults with nonalcoholic steatohepatitis. J Magn Reson Imaging 47:995-1002
Yokoo, Takeshi; Serai, Suraj D; Pirasteh, Ali et al. (2018) Linearity, Bias, and Precision of Hepatic Proton Density Fat Fraction Measurements by Using MR Imaging: A Meta-Analysis. Radiology 286:486-498
Roberts, Nathan T; Hernando, Diego; Holmes, James H et al. (2018) Noise properties of proton density fat fraction estimated using chemical shift-encoded MRI. Magn Reson Med 80:685-695
Fazeli Dehkordy, Soudabeh; Fowler, Kathryn J; Wolfson, Tanya et al. (2018) Technical report: gadoxetate-disodium-enhanced 2D R2* mapping: a novel approach for assessing bile ducts in living donors. Abdom Radiol (NY) 43:1656-1660
Mamidipalli, Adrija; Hamilton, Gavin; Manning, Paul et al. (2018) Cross-sectional correlation between hepatic R2* and proton density fat fraction (PDFF) in children with hepatic steatosis. J Magn Reson Imaging 47:418-424
Caussy, Cyrielle; Reeder, Scott B; Sirlin, Claude B et al. (2018) Noninvasive, Quantitative Assessment of Liver Fat by MRI-PDFF as an Endpoint in NASH Trials. Hepatology 68:763-772
Kennedy, Paul; Wagner, Mathilde; Castéra, Laurent et al. (2018) Quantitative Elastography Methods in Liver Disease: Current Evidence and Future Directions. Radiology 286:738-763
Bydder, Mark; Hamilton, Gavin; de Rochefort, Ludovic et al. (2018) Sources of systematic error in proton density fat fraction (PDFF) quantification in the liver evaluated from magnitude images with different numbers of echoes. NMR Biomed 31:
Hong, Cheng William; Wolfson, Tanya; Sy, Ethan Z et al. (2018) Optimization of region-of-interest sampling strategies for hepatic MRI proton density fat fraction quantification. J Magn Reson Imaging 47:988-994
Schubert, Tilman; Bannas, Peter; Kinner, Sonja et al. (2017) Thrombus-mimicking artifacts in two-point Dixon MRI: Prevalence, appearance, and severity. J Magn Reson Imaging 45:229-236

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