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Abstract #4465

Estimation of T2* in Severe Iron Overload Patients with Weighed Least Squares T2*-IDEAL

Huanzhou Yu1, Ann Shimakawa1, Scott B. Reeder2, Jean H. Brittain3, Charles A. McKenzie4, Shreyas Vasanawala5

1Applied Science Laboratory, GE Healthcare, Menlo Park, CA, USA; 2Departments of Radiology, Medical Physics, Biomedical Engineering and Medicine, University of Wisconsin, Madison, WI, USA; 3Applied Science Laboratory, GE Healthcare, Madison, WI, USA; 4Department of Medical Biophysics, University of Western Ontario, London, ON, Canada; 5Department of Radiology, Stanford University, Stanford, CA, USA

Hepatic iron overload is a common chronic liver disease. Excess amounts of iron reduce T2* of liver from above 20ms to shorter than 1ms. We have previously demonstrated that T2* mapping can be achieved simultaneously with water-fat separation using a multi-echo T2*-IDEAL algorithm. However, in the presence of very short T2*, the images at late echoes have poor SNR, leading to substantial errors. In this work, we introduce a weighted least squares algorithm, which automatically decreases the impact of later, noisier echoes. We demonstrate in simulations and in-vivo studies that T2* values as short as 1ms can be effectively estimated.