scholarly journals Numerical evaluation of image homogeneity, signal-to-noise ratio, and specific absorption rate for human brain imaging at 1.5, 3, 7, 10.5, and 14T in an 8-channel transmit/receive array

2014 ◽  
Vol 41 (5) ◽  
pp. 1432-1439 ◽  
Author(s):  
Zhipeng Cao ◽  
Joshua Park ◽  
Zang-Hee Cho ◽  
Christopher M. Collins
Keyword(s):  
Human Brain ◽  
Brain Imaging ◽  
Numerical Evaluation ◽  
Absorption Rate ◽  
Specific Absorption Rate ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Specific Absorption ◽  
Receive Array ◽  
Image Homogeneity

scholarly journals Towards an integrated neonatal brain and cardiac examination capability at 7 T: electromagnetic field simulations and early phantom experiments using an 8-channel dipole array

2022 ◽  
Author(s):  
Jérémie Clément ◽  
Raphaël Tomi-Tricot ◽  
Shaihan J. Malik ◽  
Andrew Webb ◽  
Joseph V. Hajnal ◽  
...  
Keyword(s):  
Absorption Rate ◽  
Specific Absorption Rate ◽  
Signal To Noise Ratio ◽  
Birdcage Coil ◽  
Rf Coil ◽  
Neonatal Brain ◽  
Specific Absorption ◽  
Safe Operating ◽  
Phantom Experiments ◽  
Rf Performances

Abstract Objective Neonatal brain and cardiac imaging would benefit from the increased signal-to-noise ratio levels at 7 T compared to lower field. Optimal performance might be achieved using purpose designed RF coil arrays. In this study, we introduce an 8-channel dipole array and investigate, using simulations, its RF performances for neonatal applications at 7 T. Methods The 8-channel dipole array was designed and evaluated for neonatal brain/cardiac configurations in terms of SAR efficiency (ratio between transmit-field and maximum specific-absorption-rate level) using adjusted dielectric properties for neonate. A birdcage coil operating in circularly polarized mode was simulated for comparison. Validation of the simulation model was performed on phantom for the coil array. Results The 8-channel dipole array demonstrated up to 46% higher SAR efficiency levels compared to the birdcage coil in neonatal configurations, as the specific-absorption-rate levels were alleviated. An averaged normalized root-mean-square-error of 6.7% was found between measured and simulated transmit field maps on phantom. Conclusion The 8-channel dipole array design integrated for neonatal brain and cardiac MR was successfully demonstrated, in simulation with coverage of the baby and increased SAR efficiency levels compared to the birdcage. We conclude that the 8Tx-dipole array promises safe operating procedures for MR imaging of neonatal brain and heart at 7 T.

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

2021 ◽  
Author(s):  
Nader Tavaf
Keyword(s):  
Human Brain ◽  
High Field ◽  
Signal To Noise Ratio ◽  
Noise Correlation ◽  
Resonance Imaging ◽  
Mr Images ◽  
Signal To Noise ◽  
Ultra High Field ◽  
Noise Ratio ◽  
Receive Array

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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