Water-fat separation with IDEAL gradient-echo imaging

Purpose: To combine gradient-echo (GRE) imaging with a multipoint water-fat separation method known as iterative decomposition of water and fat with echo asymmetry and least squares estimation (IDEAL) for uniform waterfat separation. Robust fat suppression is necessary for many GRE imaging applications; unfortunately, uniform fat suppression is challenging in the presence of B-0 inhomogeneities. These challenges are addressed with the IDEAL technique. Materials and Methods: Echo shifts for three-point IDEAL were chosen to optimize noise performance of the water-fat estimation, which is dependent on the relative proportion of water and fat within a voxel. Phantom experiments were performed to validate theoretical SNR predictions. Theoretical echo combinations that maximize noise performance are discussed, and examples of clinical applications at 1.5T and 3.0T are shown. Results: The measured SNR performance validated theoretical predictions and demonstrated improved image quality compared to unoptimized echo combinations. Clinical examples of the liver, breast, heart, knee, and ankle are shown, including the combination of IDEAL with parallel imaging. Excellent water-fat separation was achieved in all cases. The utility of recombining water and fat images into in-phase, out-of-phase, and fat signal fraction images is also discussed. Conclusion: IDEAL-SPGR provides robust water-fat separation with optimized SNR performance at both 1.5T and 3.0T with multicoil acquisitions and parallel imaging in multiple regions of the body.