A multiexponential T*2 correction method improves the accuracy of MRI-based fat quantification in phantom models, which may aid in noninvasive assessment of hepatic steatosis.
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Supports multiexponential T2 correction for phantom fat quantification; leaves open clinical translation for hepatic steatosis assessment.
Noninvasive biomarkers of intracellular accumulation of fat within the liver (hepatic steatosis) are urgently needed for detection and quantitative grading of nonalcoholic fatty liver disease, the most common cause of chronic liver disease in the United States. Accurate quantification of fat with MRI is challenging due the presence of several confounding factors, including T*(2) decay. The specific purpose of this work is to quantify the impact of T*(2) decay and develop a multiexponential T*(2) correction method for improved accuracy of fat quantification, relaxing assumptions made by previous T*(2) correction methods. A modified Gauss-Newton algorithm is used to estimate the T*(2) for water and fat independently. Improved quantification of fat is demonstrated, with independent estimation of T*(2) for water and fat using phantom experiments. The tradeoffs in algorithm stability and accuracy between multiexponential and single exponential techniques are discussed.
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Chebrolu et al. (2010) studied this question.
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