General Linear Modeling For Magnetic Resonance Spectroscopy

NIH Pandemic-Era Grants

Pandemic Era Grants

2024

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Principal Investigator: Georg  Oeltzschner
Organization: JOHNS HOPKINS UNIVERSITY
Fiscal Year: 2024
Award: $245,254
Funding agency: National Institute of Biomedical Imaging and Bioengineering

Project Summary
Advanced multi-spectrum magnetic resonance spectroscopy (MRS) methods allow the non-invasive
measurement of the concentration of neurochemicals, but also of other biophysical properties. The currently
available one-dimensional modeling tools cannot adequately model such data because they are incapable of
incorporating prior knowledge about the relationships between sub-spectra into a single multi-dimensional model.
Additional parameters that can be encoded in the acquisition, but not adequately accommodated within the
quantification model include metabolite relaxation times, metabolite diffusion tensors, and physiological
metabolic response to external stimulation.
This project addresses the gap in currently available modeling tools for MRS by introducing a generalized linear
combination modeling framework for MRS. This avoids the overfitting that arises from serial application of current
one-dimensional models, dramatically increasing model parsimony. All code developed will be made available
to the community open-source, and the modeling framework will be made available in the cloud via a web user
interface.

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