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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