Publication Date:
2017-02-11
Description:
The ultimate intrinsic signal-to-noise ratio (SNR) is a coil independent performance measure to compare different receive coil designs. To evaluate this benchmark in a sample, a complete electromagnetic basis set is required. The basis set can be obtained by curl-free and divergence-free surface current distributions, which excite linearly independent solutions to Maxwell's equations. In this work, we quantitatively investigate the contribution of curl-free current patterns to the ultimate intrinsic SNR in a spherical head-sized model at 9.4 T. Therefore, we compare the ultimate intrinsic SNR obtained with having only curl-free or divergence-free current patterns, with the ultimate intrinsic SNR obtained from a combination of curl-free and divergence-free current patterns. The influence of parallel imaging is studied for various acceleration factors. Moreover results for different field strengths (1.5 T up to 11.7 T) are presented at specific voxel positions and acceleration factors. The full-wave electromagnetic problem is analytically solved using dyadic Green's functions. We show, that at ultra-high field strength (B 0 ⩾7T) a combination of curl-free and divergence-free current patterns is required to achieve the best possible SNR at any position in a spherical head-sized model. On 1.5- and 3T platforms, divergence-free current patterns are sufficient to cover more than 90% of the ultimate intrinsic SNR. We quantitatively compare the ultimate intrinsic SNR obtained with having only curl-free or divergence-free current patterns, with the ultimate intrinsic SNR obtained from a combination of curl-free and divergence-free current patterns. At ultra-high field strength ( B 0 ≥ 7 T) a combination of curl-free and divergence-free current patterns is required to achieve the best possible SNR at any position in a head-sized sphere. On 1.5- and 3T platforms divergence-free current patterns are sufficient to cover more than 90% of the ultimate intrinsic SNR.
Print ISSN:
0952-3480
Electronic ISSN:
1099-1492
Topics:
Medicine
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