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Abstract #2007

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

Andrew Martin Wright1,2, Saipavitra Murali Manohar1,3, Theresia Ziegs1,2, and Anke Henning1,4
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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