Water-fat separation from a single spatiotemporally encoded echo based on nominal k-space peaking and joint...

To present a new high-resolution single-point water-fat separation algorithm based on the spatiotemporally encoded chemical shift imaging technique.

Identifying water and fat peaks on the ensemble of the nominal k-space profiles of all spatiotemporally encoded lines enables evaluation of the mean off-resonance frequencies of the two components. With utilization of the spatial smoothness and filtering regularizations, the water/fat profiles can be discriminated with twice joint linear least squares estimations line-by-line.

The effectiveness of the proposed algorithm was assessed by experiments on oil-water phantoms and in vivo in rats at 7T using a spatiotemporally encoded variant of the multishot spin-echo sequence. The results were compared with those obtained from previously proposed 1-point Dixon, 2-point Dixon, and 3-point IDEAL methods.

The results demonstrate that the new technique can achieve high-quality water-fat separations, comparable in signal-to-noise ratio and contrast to the multipoint methods and is more robust in cases when large areas of low signals or motion artifacts jeopardize the results from the 1-point Dixon method.

The proposed technique is potentially a new viable alternative for single-point water-fat separation.