Slice-selective RF pulses for in vivo B1+ inhomogeneity mitigation at 7 tesla using parallel RF excitation with a 16-element coil

Magn Reson Med. 2008 Dec;60(6):1422-32. doi: 10.1002/mrm.21739.


Slice-selective RF waveforms that mitigate severe B1+ inhomogeneity at 7 Tesla using parallel excitation were designed and validated in a water phantom and human studies on six subjects using a 16-element degenerate stripline array coil driven with a butler matrix to utilize the eight most favorable birdcage modes. The parallel RF waveform design applied magnitude least-squares (MLS) criteria with an optimized k-space excitation trajectory to significantly improve profile uniformity compared to conventional least-squares (LS) designs. Parallel excitation RF pulses designed to excite a uniform in-plane flip angle (FA) with slice selection in the z-direction were demonstrated and compared with conventional sinc-pulse excitation and RF shimming. In all cases, the parallel RF excitation significantly mitigated the effects of inhomogeneous B1+ on the excitation FA. The optimized parallel RF pulses for human B1+ mitigation were only 67% longer than a conventional sinc-based excitation, but significantly outperformed RF shimming. For example the standard deviations (SDs) of the in-plane FA (averaged over six human studies) were 16.7% for conventional sinc excitation, 13.3% for RF shimming, and 7.6% for parallel excitation. This work demonstrates that excitations with parallel RF systems can provide slice selection with spatially uniform FAs at high field strengths with only a small pulse-duration penalty.

Publication types

  • Evaluation Study
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Artifacts*
  • Brain / anatomy & histology*
  • Image Enhancement / methods*
  • Image Interpretation, Computer-Assisted / methods*
  • Magnetic Resonance Imaging / instrumentation*
  • Magnetic Resonance Imaging / methods*
  • Phantoms, Imaging
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Signal Processing, Computer-Assisted