Self-navigated ideal water-fat separation with variable k-space averaging

Water-fat separation has been an important technique in MRI. IDEAL (Iterative Decomposition of water and fat with Echo Asymmetry and Least squares estimation) water-fat separation is a robust method to achieve water-fat separation, and has been adopted in quantitative analysis of adiposity. The presence of motion during acquisition causes artifacts, which can result in quantification inaccuracies. To overcome this challenge, a double-echo navigator technique was incorporated in the IDEAL sequence to monitor the signal fluctuation caused by motion. Retrospective motion correction led to a substantial reduction of motion artifacts, thereby improving the accuracy and robustness of the quantification. In addition, a variable k-space averaging for motion correction is proposed. By concentrating the averaging at the center of k-space, it achieved same motion correction performance with less acquired k-space profiles. Water/oil phantom data and animal hepatic adiposity data were acquired, and results were compared with and without motion correction. Simulated results were generated to evaluate the variable k-space averaging.