Improved slice-selective adiabatic excitation

Magn Reson Med. 2014 Jan;71(1):75-82. doi: 10.1002/mrm.24630. Epub 2013 Feb 11.

Abstract

Purpose: The purpose of this work is to design an improved Slice-selective Tunable-flip AdiaBatic Low peak-power Excitation (STABLE) pulse with shorter duration and increased off-resonance immunity to make it suitable for use in a greater range of applications and at higher field strengths. An additional aim is to design a variant of this pulse to achieve B1 -insensitive, fat-suppressed excitation.

Methods: The adiabatic SLR algorithm was used to generate a more uniform spectral pulse envelope for this improved radiofrequency pulse for adiabatic slice-selective excitation, called STABLE-2. Pulse parameters were adjusted to design a version of STABLE-2 with a spectral null centered on lipids.

Results: In vivo images obtained of the human brain at 3 and 7 T demonstrate that STABLE-2 provides robust, uniform, slice-selective excitation over a range of B1 values. Phantom and in vivo knee images obtained at 3 T demonstrate the effectiveness of STABLE-2 for fat suppression.

Conclusions: STABLE-2 achieves B1 -insensitive slice-selective excitation while providing greater off-resonance immunity and a shorter pulse duration, when compared to the original STABLE pulse. In particular, the 9.8-ms STABLE-2 pulse provides slice selectivity over 120 Hz whereas the 21-ms STABLE pulse is limited to 80 Hz off-resonance. B1 -Insensitive fat-suppressed excitation may also be achieved by using a variant of this pulse.

Keywords: B1-insensitive; RF excitation; STABLE; Shinnar Le-Roux; adiabatic; fat suppression; off-resonance; slice-selective.

Publication types

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

MeSH terms

  • Adipose Tissue / anatomy & histology*
  • Algorithms
  • Brain / anatomy & histology*
  • Humans
  • Image Enhancement / methods*
  • Image Interpretation, Computer-Assisted / methods*
  • Knee Joint / anatomy & histology*
  • Magnetic Resonance Imaging / methods*
  • Pattern Recognition, Automated / methods
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Subtraction Technique