Waterafat separation with parallel imaging based on BLADE
Uniform suppression of fat signal is desired in clinical applications. Based on phase differences introduced by different chemical shift frequencies, Dixon method and its variations are used as alternatives of fat saturation methods, which are sensitive to B0 inhomogeneities. Iterative Decomposition...
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Published in | Magnetic resonance imaging Vol. 31; no. 5; pp. 656 - 663 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
01.06.2013
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Online Access | Get full text |
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Summary: | Uniform suppression of fat signal is desired in clinical applications. Based on phase differences introduced by different chemical shift frequencies, Dixon method and its variations are used as alternatives of fat saturation methods, which are sensitive to B0 inhomogeneities. Iterative Decomposition of water and fat with Echo Asymmetry and Least squares estimation (IDEAL) separates water and fat images with flexible echo shifting. Periodically Rotated Overlapping ParallEL Lines with Enhanced Reconstruction (PROPELLER, alternatively termed as BLADE), in conjunction with IDEAL, yields Turboprop IDEAL (TP-IDEAL) and allows for decomposition of water and fat signal with motion correction. However, the flexibility of its parameter setting is limited, and the related phase correction is complicated. To address these problems, a novel method, BLADE-Dixon, is proposed in this study. This method used the same polarity readout gradients (fly-back gradients) to acquire in-phase and opposed-phases images, which led to less complicated phase correction and more flexible parameter setting compared to TP-IDEAL. Parallel imaging and undersampling were integrated to reduce scan time. Phantom, orbit, neck and knee images were acquired with BLADE-Dixon. Waterafat separation results were compared to those measured with conventional turbo spin echo (TSE) Dixon and TSE with fat saturation, respectively, to demonstrate the performance of BLADE-Dixon. |
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Bibliography: | ObjectType-Article-2 SourceType-Scholarly Journals-1 content type line 23 ObjectType-Feature-1 |
ISSN: | 0730-725X |