Analytical three-point Dixon method: With applications for spiral water-fat imaging.

PURPOSE

The goal of this work is to present a new three-point analytical approach with flexible even or uneven echo increments for water-fat separation and to evaluate its feasibility with spiral imaging.

THEORY AND METHODS

Two sets of possible solutions of water and fat are first found analytically. Then, two field maps of the B0 inhomogeneity are obtained by linear regression. The initial identification of the true solution is facilitated by the root-mean-square error of the linear regression and the incorporation of a fat spectrum model. The resolved field map after a region-growing algorithm is refined iteratively for spiral imaging. The final water and fat images are recalculated using a joint water-fat separation and deblurring algorithm.

RESULTS

Successful implementations were demonstrated with three-dimensional gradient-echo head imaging and single breathhold abdominal imaging. Spiral, high-resolution T1 -weighted brain images were shown with comparable sharpness to the reference Cartesian images.

CONCLUSION

With appropriate choices of uneven echo increments, it is feasible to resolve the aliasing of the field map voxel-wise. High-quality water-fat spiral imaging can be achieved with the proposed approach.