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Quantitative water/fat separation in MRI requires careful modeling of the acquired signal. Multiple signal models have been proposed in recent years, but their relative performance has not yet been established. This article presents a comparative study of 12 signal models for quantitative water/fat separation. These models were selected according to three main criteria: magnitude or complex fitting, use of single-peak or multipeak fat spectrum, and modeling of T(2)(*) decay. The models were compared based on an analysis of the bias and standard deviation of their resulting estimates. Results from theoretical analysis, simulation, phantom experiments, and in vivo data were in good agreement. These results show that (a) complex fitting is uniformly superior to magnitude fitting, (b) multipeak fat modeling is able to remove the bias present in single-peak fat modeling, and (c) a single-T(2)(*) model performs best over a range of clinically relevant signal-to-noise ratios (SNRs) and water/fat ratios.
Hernando et al. (Tue,) studied this question.