Back

RF coil design strategies for improving SNR at theultrahigh magnetic field of 10.5 Tesla

Waks, M.; Lagore, R. L.; Auerbach, E.; Grant, A.; Sadeghi-Tarakameh, A.; DelaBarre, L.; Jungst, S.; Tavaf, N.; Lattanzi, R.; Giannakopoulos, I.; Moeller, S.; Wu, X.; Yacoub, E.; Vizioli, L.; Schmidt, S.; Metzger, G.; Eryaman, Y.; Adriany, G.; Ugurbil, K.

2024-05-26 neuroscience
10.1101/2024.05.23.595628 bioRxiv
Show abstract

PurposeTo develop multichannel transmit and receive arrays towards capturing the ultimate-intrinsic-SNR (uiSNR) at 10.5 Tesla (T) and to demonstrate the feasibility and potential of whole-brain, high-resolution human brain imaging at this high field strength. MethodsA dual row 16-channel self-decoupled transmit (Tx) array was converted to a 16Tx/Rx transceiver using custom transmit/receive switches. A 64-channel receive-only (64Rx) array was built to fit into the 16Tx/Rx array. Electromagnetic modeling and experiments were employed to define safe operation limits of the resulting 16Tx/80Rx array and obtain FDA approval for human use. ResultsThe 64Rx array alone captured approximately 50% of the central uiSNR at 10.5T while the identical 7T 64Rx array captured [~]76% of uiSNR at this lower field strength. The 16Tx/80Rx configuration brought the fraction of uiSNR captured at 10.5T to levels comparable to the performance of the 64Rx array at 7T. SNR data obtained at the two field strengths with these arrays displayed [Formula] dependent increases over a large central region. Whole-brain high resolution T2* and T1 weighted anatomical and gradient-recalled echo EPI BOLD fMRI images were obtained at 10.5T for the first time with such an advanced array, illustrating the promise of >10T fields in studying the human brain. ConclusionWe demonstrated the ability to approach the uiSNR at 10.5T over the human brain with a novel, high channel count array, achieving large SNR gains over 7T, currently the most commonly employed ultrahigh field platform, and demonstrate high resolution and high contrast anatomical and functional imaging at 10.5T.

Matching journals

The top 2 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.