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Abstract #0144

Rician-noise based R2* Estimation for Severe Hepatic Iron Overload: Simulation, Phantom, and Early Clinical Experience

Takeshi Yokoo 1,2 , Qing Yuan 1 , Julien Senegas 3 , Andrea Wiethoff 2,4 , and Ivan M Pedrosa 1,2

1 Radiology, UT Southwestern Medical Center, Dallas, TX, United States, 2 Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, United States, 3 Philips Research Laboratories, Hamburg, Germany, 4 Philips Research North America, Briarcliff Manor, NY, United States

Patients with severe hepatic iron overload are at risk for developing end-stage liver disease and in greatest need for therapy. An R2*-based measure has been proposed as a surrogate for liver iron, but its estimation is challenging in severe iron overload due to rapid signal decay. In this series of simulation, phantom, and human studies, we compared R2* estimation performance of several existing methods: linear least squares, nonlinear least squares (NLS), weighted NLS, NLS with constant noise offset, and Rician-noise based. Our results show that Rician-noise based method is clinically feasible and may be necessary to accurately estimate R2* for severe iron overload.

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