Conference Paper

Self-Navigated Ideal Water-Fat Separation with Variable K-Space Averaging.

DOI: 10.1109/ISBI.2009.5192998 Conference: Proceedings of the 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Boston, MA, USA, June 28 - July 1, 2009
Source: DBLP

ABSTRACT 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.

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    ABSTRACT: PurposeTo 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 water–fat separation. Robust fat suppression is necessary for many GRE imaging applications; unfortunately, uniform fat suppression is challenging in the presence of B0 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.ResultsThe 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.ConclusionIDEAL-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. J. Magn. Reson. Imaging 2007;25:644–652. © 2007 Wiley-Liss, Inc.
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    ABSTRACT: This work describes a new approach to multipoint Dixon fat-water separation that is amenable to pulse sequences that require short echo time (TE) increments, such as steady-state free precession (SSFP) and fast spin-echo (FSE) imaging. Using an iterative linear least-squares method that decomposes water and fat images from source images acquired at short TE increments, images with a high signal-to-noise ratio (SNR) and uniform separation of water and fat are obtained. This algorithm extends to multicoil reconstruction with minimal additional complexity. Examples of single- and multicoil fat-water decompositions are shown from source images acquired at both 1.5T and 3.0T. Examples in the knee, ankle, pelvis, abdomen, and heart are shown, using FSE, SSFP, and spoiled gradient-echo (SPGR) pulse sequences. The algorithm was applied to systems with multiple chemical species, and an example of water-fat-silicone separation is shown. An analysis of the noise performance of this method is described, and methods to improve noise performance through multicoil acquisition and field map smoothing are discussed.
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