Improved olefinic fat suppression in skeletal muscle DTI using a magnitude‐based dixon method
It should also be noted that standard Dixon‐based methods cannot be readily used in diffusion‐weighted acquisitions because they rely on phase data, which is changed to a pseudo‐random value by the diffusion gradients and cannot be deconvoluted when the chemical shift of the main fat peak is larger than a few millimeters 2; therefore, a different approach is necessary.
Williams et al. proposed a method for fat‐suppressed diffusion‐weighted imaging (DWI) in which the main peak is suppressed using a combination of SPAIR and slice‐selection gradient reversal (SSGR), whereas the olefinic fat peak is suppressed with a second spectral fat saturation method 11. This technique offers good suppression for most of the fat spectrum, although it is susceptible to main field (B0) inhomogeneities and causes the loss of approximately 10% of the water signal due to the spectral proximity of the olefinic fat and water peaks 11. For brevity, through the rest of this work we refer to this method as spectral olefinic fat suppression (SOFS).
Hernando et al. also used SPAIR to suppress the −CH2 and −CH3 peaks and described how magnitude‐only diffusion‐weighted data from a six‐echo (commonly described as 6‐point) acquisition can be separated into images corresponding to water and olefinic fat with a multiparameter fit, using the diffusion‐free (b = 0) image for initialization of the fitting parameters 2. Because this method involves a nonlinear multi‐parameter fit performed on the data to separate water and fat, it has a potential to be unstable if only a few echoes are used. In addition, it requires either using a partial Fourier acquisition to reconstruct complex data, which decreases the resolution in the phase domain 12, or making a full k‐space acquisition, which in a typical acquisition means an echo time (TE) increase of 30 ms.