Liver fibrosis and its most advanced stage, cirrhosis, are consequences of chronic and acute hepatic disease. Fibrosis leads to a loss of liver function and both regional and global perfusion changes. Currently, the gold standard for assessing fibrosis is liver biopsy, which is an invasive technique. The long-term goal is to develop a robust and accurate non-invasive method for detecting and staging liver fibrosis and cirrhosis. The objective of this research, as part of that goal, is to develop a dynamic contrast enhanced magnetic resonance imaging (DCE MRI) that is highly reproducible. Our hypothesis is that a high reproducibility of DCE-MRI perfusion parameter measurement can be achieved using by using a continuous MR data acquisition and a contrast concentration measurement based on susceptibility. The rationale for the proposed research is that the proposed perfusion method will enable the quantification of subtle and early changes in liver function induced by fibrosis to allow for intervention prior to progression to cirrhosis or malignancies at a later stage. To test the hypothesis, the following two specific aims are pursued: 1) the development a MR perfusion imaging method using a continuous high frame rate image acquisition and susceptibility based concentration measurement and 2) the evaluation of its test-retest reproducibility in a group of healthy subjects as well as a group of patients with biopsy proven cirrhoses. It is expected that this method will ultimately lead to the ability to distinguish intermediate from advanced stages of liver fibrosis. This is likely to have a positive impact, because it would provide the ability to monitor disease progression and treatment efficacy for chronic liver disease.

Public Health Relevance

The proposed research is relevant to public health because, if completed successfully, it would present a first step towards a non-invasive method for the detection and staging of liver fibrosis. It would thus reduce the reliance on liver biopsy for the diagnosis and monitoring of chronic liver disease, whose burden on the public health is expected to increase in the next decade.

National Institute of Health (NIH)
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Exploratory/Developmental Grants (R21)
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Special Emphasis Panel (ZRG1-SBIB-J (80))
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Serrano, Jose
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Weill Medical College of Cornell University
Schools of Medicine
New York
United States
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Cooper, Mitchell A; Nguyen, Thanh D; Xu, Bo et al. (2014) Patch based reconstruction of undersampled data (PROUD) for high signal-to-noise ratio and high frame rate contrast enhanced liver imaging. Magn Reson Med :
Zhou, Dong; Liu, Tian; Spincemaille, Pascal et al. (2014) Background field removal by solving the Laplacian boundary value problem. NMR Biomed 27:312-9