The overall goal of this proposal is to develop and validate a novel technique for Magnetic Resonance Imaging (MRI)-based Quantitative Susceptibility Mapping (QSM) of the abdomen, for non-invasive assessment of liver iron deposition. In this work, we will develop and optimize advanced data acquisition and image reconstruction methods to enable QSM of the abdomen. Further, we will determine the accuracy, repeatability, and reproducibility of abdominal QSM for iron quantification in patients with liver iron overload. Excessive accumulation of iron in various organs, including the liver, which affects both adult and pediatric populations, is toxic and requires treatment aimed at reducing body iron stores. Accurate assessment of liver iron concentration is critical for the detection and staging of iron overload as well as for longitudinal monitoring during treatment. MRI is a widely available technology and highly sensitive to the presence of iron. Unfortunately, current MRI relaxometry methods are fundamentally limited by their poorly understood relationship to iron concentration, which depends on the type of iron overload and also varies during treatment. In contrast, MRI is also exquisitely sensitive to the magnetic susceptibility of tissue, which has a well-understood relationship to iron concentration. Magnetic susceptibility distorts the main magnetic field in a well-characterized manner, and this magnetic field distortion can be measured in-vivo. MRI-based QSM methods estimate the susceptibility of tissues based on measuring the magnetic field distortion produced by the tissues themselves. MRI- based QSM methods have been developed and validated in the brain. However, translation of QSM to the abdomen has been unsuccessful. We have identified four major technical barriers for development of QSM of the abdomen: 1) the presence of fat throughout the abdomen, which introduces additional phase shifts and confounds the susceptibility estimates, 2) the potential for very high iron concentration in the liver (compared to the brain), which results in rapid signal decay, 3) respiratory and other physiological motion, which introduces artifacts in the acquired images and estimated susceptibility maps, and 4) recently identified spatial resolution effects, which introduce bias in QSM when insufficient spatial resolution is acquired. By addressing these four barriers, we will develop a novel MRI-based QSM method for use in the abdomen to quantify liver iron overload. Preliminary validation studies are very promising and have shown excellent promise for the quantification of LIC in patients. In this proposal, we aim to [1] complete development of MRI-based abdominal QSM for measurement of LIC, [2] determine the repeatability and reproducibility of QSM at 1.5T and 3T in patients with liver iron overload, [3] determine the accuracy of abdominal QSM at 1.5T and 3T in patients with liver iron overload using superconducting quantum interference device (SQUID) biomagnetic liver susceptometry as the reference standard. In summary, this project will develop a novel MRI-based QSM technique designed for the abdomen and will validate it in pediatric and adult patients with liver iron overload. Upon successful validation, QSM will provide accurate, repeatable, and reproducible quantification of LIC based on a fundamental property of tissue.

Public Health Relevance

The overall goal of this research is to develop and validate a new, rapid, and non-invasive method to measure iron concentration in the liver with magnetic resonance imaging (MRI). Toxic levels of iron can accumulate in the liver due to many conditions such as certain hereditary diseases and in patients who receive a large number of blood transfusions. We will test the performance of the new method in patients at two different institutions, in order to translate it into widespread clinical practice and provide physicians with a validated method for diagnosis and treatment monitoring of iron overload.

National Institute of Health (NIH)
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Research Project (R01)
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Biomedical Imaging Technology Study Section (BMIT)
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Sherker, Averell H
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University of Wisconsin Madison
Schools of Medicine
United States
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