Fast spin echo sequences for BOLD functional MRI

Benedikt A Poser*, David G Norris

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

At higher field strengths, spin echo (SE) functional MRI (fMRI) is an attractive alternative to gradient echo (GE) as the increased weighting towards the microvasculature results in intrinsically better localization of the BOLD signal. Images are free of signal voids but the commonly used echo planar imaging (EPI) sampling scheme causes geometric distortions, and T2* effects often contribute considerably to the signal changes measured upon brain activation. Multiply refocused SE sequences such as fast spin echo (FSE) are essentially artifact free but their application to fast fMRI is usually hindered due to high energy deposition, and long sampling times. In the work presented here, a combination of parallel imaging and partial Fourier acquisition is used to shorten FSE acquisition times to near those of conventional SE-EPI, permitting sampling of eight slices (matrix 64 x 64) per second. Signal acquisition is preceded by a preparation experiment that aims at increasing the relative contribution of extravascular dynamic averaging to the BOLD signal. Comparisons are made with conventional SE-EPI using a visual stimulation paradigm. While the observed signal changes are approximately 30% lower, most likely due to the absence of T2* contamination, activation size and t-scores are comparable for both methods, suggesting that HASTE fMRI is a viable alternative, particularly if distortion free images are required. Our data also indicate that the BOLD post-stimulus undershoot is most probably attributable to persistent elevated oxygen metabolism rather than to delayed vascular compliance.

Original languageEnglish
Pages (from-to)11-7
Number of pages7
JournalMagnetic Resonance Materials in Physics Biology and Medicine
Volume20
Issue number1
DOIs
Publication statusPublished - Feb 2007
Externally publishedYes

Keywords

  • Brain
  • Data Interpretation, Statistical
  • Humans
  • Image Interpretation, Computer-Assisted
  • Magnetic Resonance Imaging
  • Sensitivity and Specificity

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