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Abstract #0067

A method for quantifying average metabolite concentrations in anatomically-defined brain regions

Ryan J. Larsen 1 , Michael Newman 1,2 , Chao Ma 3,4 , and Bradley Sutton 1,5

1 Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, United States, 2 Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL, United States, 3 Beckman Institute, Urbana, IL, United States, 4 Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States, 5 Department of Biomedical Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States

Much work has been performed to use structural MRI scans as prior knowledge to construct anatomically-constrained metabolites maps from multi-voxel Magnetic Resonance Spectroscopy Imaging scans. In many implementations, the anatomical reconstruction is performed on the signal from the metabolite, without quantitation. We demonstrate a post-processing pipeline that combines both quantitation and anatomical reconstruction based on prior knowledge. Our technique employs water-scaling to quantify the distribution of metabolites. We then apply a Projection on a Convex Set (POCS) algorithm that revises the metabolite distribution by using prior knowledge from the MRI scan. The final result is average metabolite concentration values within anatomically distinct regions of the brain.

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