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Relaxation corrected simulated MM model for improved fitting and quantification of 1H FID MRSI data

MPS-Authors
/persons/resource/persons215127

Wright,  AM
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;

/persons/resource/persons215115

Murali Manohar,  S
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;

/persons/resource/persons215132

Ziegs,  T
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;

/persons/resource/persons84402

Henning,  A
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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Citation

Wright, A., Murali Manohar, S., Ziegs, T., & Henning, A. (2021). Relaxation corrected simulated MM model for improved fitting and quantification of 1H FID MRSI data. Poster presented at 2021 ISMRM & SMRT Annual Meeting & Exhibition (ISMRM 2021).


Cite as: http://hdl.handle.net/21.11116/0000-0008-8647-1
Abstract
Short TE MRS and very short TR (TR < 300) MRSI are popular methods to capture snapshots of the neurochemical profile; however, these popular methods suffer from strong influence from underlaying macromolecular signals. This work shows a simulation method developed at 9.4T and extendable to other field strengths to account for macromolecule signals. The method developed is compared to three more commonly used methods of accounting for macromolecule signals. Results show improved metabolite mapping by use of simulated macromolecule basis vectors.