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Abstract #1422

Effects of trajectory and k-space undersampling in Compressed Sensing-Parallel Imaging 3D-GRASE

Alexandra Cristobal-Huerta1, Dirk H.J. Poot1,2, Mika Vogel3, and Juan A. Hernandez-Tamames1

1Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, Netherlands, 2Medical Informatics, Erasmus MC, Rotterdam, Netherlands, 3Healthcare Systems, GE Healthcare, Hoevelaken, Netherlands

Compressed sensing parallel imaging (CSPI) 3D-GRASE can reduce the acquisition time compared to CSPI 3D-FSE. Image quality of 3D-GRASE strongly depends on the sampling pattern used, since gradient-echoes (GREs) and spin-echo (SE) are combined in the same k-space. Moreover, successful CSPI relies on appropiate incoherent sampling patterns.

In this work we propose and investigate the influence of several sampling patterns on coherence and in-vivo image quality of $$$PD$$$-weighted knee CSPI 3D-GRASE. With the best sampling pattern CSPI 3D-GRASE obtain high image quality with significantly reduced acquisition time (57%) and SAR (66%) compared to CSPI 3D-FSE acquisitions.

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