Evaluation of a 16-Channel Transmitter for Head Imaging at 10.5T

Adriany, Gregor; Radder, Jerahmie; Tavaf, Nader; Lagore, Russell; Jungst, Steve; Woo, Myung Kyun; Grant, Andrea; Eryaman, Yiğitcan; Zhang, Bei; Gundamony, Shajan; Lattanzi, Riccardo; Uğurbil, Kâmil; Moortele, Pierre-François Van de

doi:10.1109/iceaa.2019.8879131

Cited by 8 publications

(19 citation statements)

References 18 publications

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“…The loops were tuned to 447MHz (proton resonance at 10.5T) and matched to 50 Ohm. The simulation pipeline has been discussed in more detail in previous works [62].…”

Section: Methodsmentioning

confidence: 99%

“…Coaxial cables may present a significant conductor barrier to the transmitter. Based on previous experience with loop transmitter designs [50], knowledge of transmit field patterns [62], and prototype experiments explained above, we observed that collecting coaxial cables in five paths along the z-axis parallel to the center of the transmit loops would result in minimum Tx/Rx interaction.…”

Section: Transmit-receive Interactionmentioning

confidence: 96%

“…The primary focus of this chapter is on the contribution of receiver coil self-decoupling and B 0 field strength to SNR and parallel imaging performance. Therefore, the transmitter design is covered here only briefly, with its detailed characterization published separately [62]. A 16-channel transmitter comprising two rows of 8 inductively decoupled rectangular loops was used [49,62].…”

Section: The Transmittermentioning

confidence: 99%

“…Therefore, the transmitter design is covered here only briefly, with its detailed characterization published separately [62]. A 16-channel transmitter comprising two rows of 8 inductively decoupled rectangular loops was used [49,62]. The 2-row design of the transmitter array [49,75,76] has the potential of increasing degrees of freedom in Parallel Transmit (pTx) RF pulse design especially for Specific Absorption Rate (SAR) control [77][78][79].…”

Section: The Transmittermentioning

confidence: 99%

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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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“…The loops were tuned to 447MHz (proton resonance at 10.5T) and matched to 50 Ohm. The simulation pipeline has been discussed in more detail in previous works [62].…”

Section: Methodsmentioning

confidence: 99%

Section: Transmit-receive Interactionmentioning

confidence: 96%

Section: The Transmittermentioning

confidence: 99%

Section: The Transmittermentioning

confidence: 99%

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

Tavaf¹

2021

Preprint

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“…However, solutions that include the decoupling circuits have been less discussed in the literature. The dual‐row head coil modeled by Adriany 31 and Hoffmann 32 included transformer decoupling (TD) circuits modeled using the built‐in toolbox offered in CST Microwave Studio 2018 (Dassault Systémes, Vélizy‐Villacoublay, France). However, more complex features, such as the Q factors and isolated resonant frequencies of the TD circuits, are not well modeled and optimized in the electromagnetic simulation or circuit analysis software 33 …”

Section: Introductionmentioning

confidence: 99%

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

Pan

Avdievich

et al. 2021

Magnetic Resonance in Med

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Purpose With increased interest in parallel transmission in ultrahigh‐field MRI, methods are needed to correctly calculate the S‐parameters and complex field maps of the parallel transmission coil. We present S‐parameters paired with spatial field optimization to fully simulate a double‐row 16‐element transceiver array for brain MRI at 7 T. Methods We implemented a closed‐form equation of the coil S‐parameters and overall spatial B1+ field. We minimized a cost function, consisting of coil S‐parameters and the B1+ homogeneity in brain tissue, by optimizing transceiver components, including matching, decoupling circuits, and lumped capacitors. With this, we are able to compare the in silico results determined with and without B1+ homogeneity weighting. Using the known voltage range from the host console, we reconstructed the B1+ maps of the array and performed RF shimming with four realistic head models. Results As performed with B1+ homogeneity weighting, the optimized coil circuit components were highly consistent over the four heads, producing well‐tuned, matched, and decoupled coils. The mean peak forward powers and B1+ statistics for the head models are consistent with in vivo human results (N = 8). There are systematic differences in the transceiver components as optimized with or without B1+ homogeneity weighting, resulting in an improvement of 28.4 ± 7.5% in B1+ homogeneity with a small 1.9 ± 1.5% decline in power efficiency. Conclusion This co‐simulation methodology accurately simulates the transceiver, predicting consistent S‐parameters, component values, and B1+ field. The RF shimming of the calculated field maps match the in vivo performance.

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A self‐decoupled 32‐channel receive array for human‐brain MRI at 10.5 T

Tavaf

Lagore

Jungst

et al. 2021

Magnetic Resonance in Med

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Purpose Receive array layout, noise mitigation, and B0 field strength are crucial contributors to SNR and parallel‐imaging performance. Here, we investigate SNR and parallel‐imaging gains at 10.5 T compared with 7 T using 32‐channel receive arrays at both fields. Methods A self‐decoupled 32‐channel receive array for human brain imaging at 10.5 T (10.5T‐32Rx), consisting of 31 loops and one cloverleaf element, was co‐designed and built in tandem with a 16‐channel dual‐row loop transmitter. Novel receive array design and self‐decoupling techniques were implemented. Parallel imaging performance, in terms of SNR and noise amplification (g‐factor), of the 10.5T‐32Rx was compared with the performance of an industry‐standard 32‐channel receiver at 7 T (7T‐32Rx) through experimental phantom measurements. Results Compared with the 7T‐32Rx, the 10.5T‐32Rx provided 1.46 times the central SNR and 2.08 times the peripheral SNR. Minimum inverse g‐factor value of the 10.5T‐32Rx (min[1/g] = 0.56) was 51% higher than that of the 7T‐32Rx (min[1/g] = 0.37) with R = 4 × 4 2D acceleration, resulting in significantly enhanced parallel‐imaging performance at 10.5 T compared with 7 T. The g‐factor values of 10.5 T‐32 Rx were on par with those of a 64‐channel receiver at 7 T (eg, 1.8 vs 1.9, respectively, with R = 4 × 4 axial acceleration). Conclusion Experimental measurements demonstrated effective self‐decoupling of the receive array as well as substantial gains in SNR and parallel‐imaging performance at 10.5 T compared with 7 T.

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Evaluation of a 16-Channel Transmitter for Head Imaging at 10.5T

Cited by 8 publications

References 18 publications

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

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

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

A self‐decoupled 32‐channel receive array for human‐brain MRI at 10.5 T

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