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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