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High and ultra-high resolution metabolite mapping of the human brain using 1H FID MRSI at 9.4T

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Nassirpour,  S
Max Planck Institute for Biological Cybernetics, Max Planck Society;
Research Group MR Spectroscopy and Ultra-High Field Methodology, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Chang,  P
Research Group MR Spectroscopy and Ultra-High Field Methodology, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Henning,  A
Max Planck Institute for Biological Cybernetics, Max Planck Society;
Research Group MR Spectroscopy and Ultra-High Field Methodology, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Citation

Nassirpour, S., Chang, P., & Henning, A. (2018). High and ultra-high resolution metabolite mapping of the human brain using 1H FID MRSI at 9.4T. NeuroImage, 168, 211-221. doi:10.1016/j.neuroimage.2016.12.065.


Cite as: https://hdl.handle.net/21.11116/0000-0000-794B-5
Abstract
Magnetic resonance spectroscopic imaging (MRSI) is a promising technique for mapping the spatial distribution of multiple metabolites in the human brain. These metabolite maps can be used as a diagnostic tool to gain insight into several biochemical processes and diseases in the brain. In comparison to lower field strengths, MRSI at ultra-high field strengths benefits from a higher signal to noise ratio (SNR) as well as higher chemical shift dispersion, and hence spectral resolution. This study combines the benefits of an ultra-high field magnet with the advantages of an ultra-short TE and TR single-slice FID-MRSI sequence (such as negligible J-evolution and loss of SNR due to T2 relaxation effects) and presents the first metabolite maps acquired at 9.4 T in the healthy human brain at both high (voxel size of 97.6 µL) and ultra-high (voxel size of 24.4 µL) spatial resolutions in a scan time of 11 and 46 min respectively. In comparison to lower field strengths, more anatomically-detailed maps with higher SNR from a larger number of metabolites are shown. A total of 12 metabolites including glutamate (Glu), glutamine (Gln), N-acetyl-aspartyl-glutamate (NAAG), Gamma-aminobutyric acid (GABA) and glutathione (GSH) are reliably mapped. Comprehensive description of the methodology behind these maps is provided.