Electromagnetic simulation of a 16‐channel head transceiver at 7 T using circuit‐spatial optimization

Li, Xin; Pan, Jullie W.; Avdievich, NI; Hetherington, Hoby P.; Rispoli, Joseph V.

doi:10.1002/mrm.28672

Cited by 7 publications

(17 citation statements)

References 39 publications

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“…With this strategy, the decoupling of all coil pairs is routinely better than À14 dB, with the n + 1 (nearest neighbor) and n + 2 pairs between À20 and À39 dB. 4 This two-row and decoupled design has been successfully simulated using a hybrid circuit-spatial domain optimization and was found to be consistent with experimental results acquired from N = 100 different volunteers. 14 These data have found a coefficient of variation (CoV) of $11% in the B 1 + amplitude over the intracranial brain volume.…”

supporting

confidence: 62%

Evaluation of the performance of a 7‐T 8 × 2 transceiver array

Kim,

Sun,

Moon

et al. 2024

NMR in Biomedicine

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The decoupled 8 × 2 transceiver array has been shown to achieve a mean B1+ of 11.7 uT with a coefficient of variation of ~11% over the intracranial brain volume for 7‐T MR imaging. However, this array may be thought to give lower signal‐to‐noise ratio (SNR) and higher g‐factors for parallel imaging compared with a radio frequency (RF) receive‐only coil due to the latter's higher coil count and use of coil overlap to reduce the mutual impedance. Nonetheless, because the transceiver's highly decoupled design (pertinent for transmission) should also be constructive for reception, we measured the noise correlation, g‐factors, and SNR for the decoupled transceiver in comparison with a commercial reference coil. We found that although the transceiver has half the number of receive elements in comparison with the reference coil (16 vs. 32), comparable g‐factors and SNR over the head were obtained. From five subjects, the transceiver versus reference coil SNR was 65 ± 10 versus 67 ± 15. The mean noise correlation for all coil pairs was 10% ± 5% and 12% ± 9% (transceiver and reference coil, respectively). As changes in load impedance may alter the S parameters, we also examined the performance of the transceiver with tuned and matched (TM) versus untuned and unmatched (UTM) conditions on five subjects. We found that the noise correlation and SNR are robust to load variation; a noise correlation of 10% ± 5% and 10% ± 6% was determined with TM versus UTM conditions (SNRUTM/SNRTM = 0.97 ± 0.08). Finally, we demonstrate the performance of the array in human brain using T2‐weighted turbo spin echo imaging, finding excellent SNR performance in both caudal and rostral brain regions.

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confidence: 62%

Evaluation of the performance of a 7‐T 8 × 2 transceiver array

Kim,

Sun,

Moon

et al. 2024

NMR in Biomedicine

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“…All data were acquired using a Siemens 7-T Terra in pTx mode with an 8 Â 2 transceiver array, 14 Siemens first-and second-order shims, and a third and fourth VHOS insert from Resonance Research Inc. 8 RF shimming was performed over the brain (entire cerebrum extending caudally to include the majority of the cerebellum) achieving a B 1 + homogeneity of less than 15% SD, 15,16 such that no additional RF optimization was used for individual acquisitions. For anatomical visualization and tissue segmentation, a 1 mm 3 isotropic magnetization-prepared 2 rapid gradient echo (MP2RAGE) image was acquired.…”

Section: Methodsmentioning

confidence: 99%

Map‐based B₀ shimming for single voxel brain spectroscopy at 7T

Pan,

Terpstra,

Moon

et al. 2023

NMR in Biomedicine

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While B0 shimming is an important requirement for in vivo brain spectroscopy, for single voxel spectroscopy (SVS), the role for advanced shim methods has been questioned. Specifically, with the small spatial dimensions of the voxel, the extent to which inhomogeneities higher than second order exist and the ability of higher order shims to correct them is controversial. To assess this, we acquired SVS from two loci of neurophysiological interest, the rostral prefrontal cortex (rPFC; 8 cc) and hippocampus (Hc; 9 cc). The rPFC voxel was placed using SUsceptibility Managed Optimization (SUMO) and an initial B0 map that covers the entire cerebrum to cerebellum. In each location, we compared map‐based shimming (Bolero) with projection‐based shimming (FAST(EST)MAP). We also compared vendor‐provided spherical harmonic first‐ and second‐order shims with additional third‐ and fourth‐order shim hardware. The 7T SVS acquisition used stimulated echo acquisition mode (STEAM) TR/TM/TE of 6 s/20 ms/8 ms, a tissue water acquisition for concentration reference, and LCModel for spectral analysis. In the rPFC (n = 7 subjects), Bolero shimming with first‐ and second‐order shims reduced the residual inhomogeneity from 9.8 ± 4.5 Hz with FAST(EST)MAP to 6.5 ± 2.0 Hz. The addition of third‐ and fourth‐order shims further reduced to 4.0 ± 0.8 Hz. In the Hc (n = 7 subjects), FAST(EST)MAP, Bolero with first‐ and second‐order shims, and Bolero with first‐ to fourth‐order shims achieved values of 8.6 ± 1.9, 5.6 ± 1.0, and 4.6 ± 0.9 Hz, respectively. The spectral linewidth, , was estimated with a Voigt lineshape using and T2 = 130 ms. significantly correlated with the Cramer–Rao lower bounds and concentrations of several metabolites, including glutamate and glutamine in the rPFC. In both loci, if the B0 distribution is well described by a Gaussian model, the variance of the metabolite concentrations is reduced, consistent with the LCModel fit based on a unimodal lineshape. Overall, the use of the high order and map‐based B0 shim methods improved the accuracy and consistency of spectroscopic data.

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“…The manual construction of RF coils may gradually be automated to minimize inevitable deviations from design, the constraints on the simulated versus experimental magnetic field match can arguably be relaxed in small, partial and calculated steps, or a paradigm shift or breakthrough in the electromagnetic/circuit co-simulation pipeline (e.g. from full-wave Maxwell solvers to statistical or data-driven models, see for example [113], or solving explicitly for parameters of the electromagnetic model that minimize the spatial field mismatch, see for example [114]) may help resolve the existing field mismatches. Given the interdisciplinary history of MR research, some of these advances will probably emerge from progress in tangent fields.…”

Section: Future Directionsmentioning

confidence: 99%

Improving Signal to Noise Ratio in Ultra High Field Magnetic Resonance Imaging

Tavaf¹

2021

Preprint

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Ultra-High Field (UHF) Magnetic Resonance Imaging (MRI) advantages, including higher image resolution, reduced acquisition time via parallel imaging, and better signal-to-noise ratio (SNR) have opened new opportunities for various clinical and research projects, including functional MRI, brain connectivity mapping, and anatomical imaging. The advancement of these UHF MRI performance metrics, especially SNR, was the primary motivation of this thesis. Unaccelerated SNR depends on receive array sensitivity profile, receiver noise correlation and static magnetic field strength. Various receive array decoupling technologies, including overlap/inductive and preamplifier decoupling, were previously utilized to mitigate noise correlation. In this dissertation, I developed a novel self-decoupling principle to isolate elements of a loop-based receive array and demonstrated, via full-wave electromagnetic/circuit co-simulations validated by bench measurements, that the self-decoupling technique provides inter-element isolation on par with overlap decoupling while self-decoupling improves SNR. I then designed and constructed the first self-decoupled 32 and 64 channel receiver arrays for human brain MR imaging at 10.5T / 447MHz. Experimental comparisons of these receive arrays with the industry’s gold-standard 7T 32 channel receiver resulted in 1.81 times and 3.53 times more average SNR using the 10.5T 32 and 64 channel receivers I built, respectively. To further improve the SNR of accelerated MR images, I developed a novel data-driven model using a customized conditional generative adversarial network (GAN) architecture for parallel MR image reconstruction and demonstrated that, when applied to human brain images subsampled with rate of 4, the GAN model results in a peak signal-to-noise ratio (PSNR) of 37.65 compared to GeneRalized Autocalibrating Partial Parallel Acquisition (GRAPPA)’s PSNR of 33.88.In summary, the works presented in this dissertation improved the SNR available for human brain imaging and provided the experimental realization of the advantages anticipated at 10.5T MRI. The insights from this thesis inform future efforts to build self-decoupled transmit arrays and high density, 128 channel loop-based receive arrays for human brain MRI especially at ultra-high field as well as future studies to utilize deep learning techniques for reconstruction and post-processing of parallel MR images.

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Electromagnetic simulation of a 16‐channel head transceiver at 7 T using circuit‐spatial optimization

Cited by 7 publications

References 39 publications

Evaluation of the performance of a 7‐T 8 × 2 transceiver array

Evaluation of the performance of a 7‐T 8 × 2 transceiver array

Map‐based B₀ shimming for single voxel brain spectroscopy at 7T

Improving Signal to Noise Ratio in Ultra High Field Magnetic Resonance Imaging

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Electromagnetic simulation of a 16‐channel head transceiver at 7 T using circuit‐spatial optimization

Cited by 7 publications

References 39 publications

Evaluation of the performance of a 7‐T 8 × 2 transceiver array

Evaluation of the performance of a 7‐T 8 × 2 transceiver array

Map‐based B0 shimming for single voxel brain spectroscopy at 7T

Improving Signal to Noise Ratio in Ultra High Field Magnetic Resonance Imaging

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Product

Resources

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Map‐based B₀ shimming for single voxel brain spectroscopy at 7T