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Abstract #0401

Fat and Iron Quantification Using a Multi-Step Adaptive Fitting Approach with Multi-Echo GRE Imaging

Xiaodong Zhong1, Marcel D. Nickel2, Stephan A.R. Kannengiesser2, Brian M. Dale3, Berthold Kiefer2, Mustafa Bashir4

1MR R&D Collaborations, Siemens Healthcare, Atlanta, GA, United States; 2MR Applications Development, Siemens AG, Healthcare Sector, Erlangen, Germany; 3MR R&D Collaborations, Siemens Healthcare, Cary, NC, United States; 4Division of Abdominal Imaging, Duke University Medical Center, Durham, NC, United States

In this work, a multi-step adaptive fitting approach was developed for fat and iron quantification using multi-echo 3D GRE data, which accounts for various factors such as T2* decay, T1 bias, multi-peak fat modeling, and noise bias. Numeric phantoms were created and used to validate the results measured by this approach with the ground truth, and showed that this approach is relatively insensitive to different field strengths, field inhomogeneity, monopolar/bipolar readout, and TE selections. An in vivo patient study showed consistency between the FP results measured with the proposed approach and a spectroscopy-based method.