Abstract #2007

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

Andrew Martin Wright^1,2, Saipavitra Murali Manohar^1,3, Theresia Ziegs^1,2, and Anke Henning^1,4

¹Max Planck Institute for Biological Cybernetics, Tübingen, Germany, ²IMPRS for Cognitive and Systems Neuroscience, Tübingen, Germany, ³University of Tübingen, Faculty of Science, Tübingen, Germany, ⁴Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, United States

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.

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