The broad goal of the research is to develop a new magnetic resonance imaging (MRI) technique for quantifying body iron stores. Elevated body iron levels can develop in a variety of disorders, including hereditary hemochromatosis, thalassemia major, myelodysplasia, and sickle cell anemia. Excess body iron or """"""""iron overload"""""""" can be toxic and may lead to a variety of iron-induced complications, such as diabetes, cirrhosis, and heart disease. In diagnosing and managing iron overload, it is important to quantify body iron excess. The two generally available clinical methods for doing this, liver biopsy and blood serum ferritin measurement, suffer from significant shortcomings. Liver biopsy is invasive and may be inaccurate for liver with cirrhosis, while the serum ferritin level correlates poorly with total body iron. The research would develop a method for iron quantification based on the effect of iron on MRI signal decay. The research would optimize and validate the technique for liver tissue, since liver iron concentration is considered the best single indicator of iron overload. A major advantage of MRI quantification of iron overload is that this method is completely non-invasive, which allows the frequent monitoring of iron levels during therapy. The proposed approach differs markedly from prior attempts to use MRI for iron quantification, in that two independent MRI quantities, rather than one, are measured. This is critical for obtaining a high accuracy, as iron in the liver comes in two forms, ferritin iron and hemosiderin iron, which affect MRI signal decay in significantly different ways. Our research will be divided into two stages. First, we will develop and test the necessary MRI pulse sequences using a tissue model (phantom) consisting of a gel with suspended iron particles. Second the method will be applied to 150 iron overload patients. As validation, the MRI predictions will be correlated to results of needle biopsy of the liver, the current clinical gold standard. We will also compare the MRI data to iron measurements obtained with SQUID biosusceptometry.
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