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In-vivo and numerical analysis of the eigenmodes produced by a multi-level Tic-Tac-Toe head transmit array for 7 Tesla MRI

Author

Listed:
  • Tales Santini
  • Yujuan Zhao
  • Sossena Wood
  • Narayanan Krishnamurthy
  • Junghwan Kim
  • Nadim Farhat
  • Salem Alkhateeb
  • Tiago Martins
  • Minseok Koo
  • Tiejun Zhao
  • Howard J Aizenstein
  • Tamer S Ibrahim

Abstract

Radio-frequency (RF) field inhomogeneities and higher levels of specific absorption rate (SAR) still present great challenges in ultrahigh-field (UHF) MRI. In this study, an in-depth analysis of the eigenmodes of a 20-channel transmit Tic-Tac-Toe (TTT) RF array for 7T neuro MRI is presented. The eigenmodes were calculated for five different Z levels (along the static magnetic field direction) of the coil. Four eigenmodes were obtained for each Z level (composed of 4 excitation ports), and they were named based on the characteristics of their field distributions: quadrature, opposite-phase, anti-quadrature, and zero-phase. Corresponding finite-difference time-domain (FDTD) simulations were performed and experimental B1+ field maps were acquired using a homogeneous spherical phantom and human head (in-vivo). The quadrature mode is the most efficient and it excites the central brain regions; the opposite-phase mode excites the brain peripheral regions; anti-quadrature mode excites the head periphery; and the zero-phase mode excites cerebellum and temporal lobes. Using this RF array, up to five eigenmodes (from five different Z levels) can be simultaneously excited. The superposition of these modes has the potential to produce homogeneous excitation with full brain coverage and low levels of SAR at 7T MRI.

Suggested Citation

  • Tales Santini & Yujuan Zhao & Sossena Wood & Narayanan Krishnamurthy & Junghwan Kim & Nadim Farhat & Salem Alkhateeb & Tiago Martins & Minseok Koo & Tiejun Zhao & Howard J Aizenstein & Tamer S Ibrahim, 2018. "In-vivo and numerical analysis of the eigenmodes produced by a multi-level Tic-Tac-Toe head transmit array for 7 Tesla MRI," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-16, November.
  • Handle: RePEc:plo:pone00:0206127
    DOI: 10.1371/journal.pone.0206127
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