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.

Project Narrative Modern magnetic resonance spectroscopy (MRS) experiments can measure various physical properties of chemicals in the brain. Current computer modeling tools are inadequate to extract the information that such experiments can deliver, and this project seeks to develop new modeling and quantification tools that will be freely accessible to the MRS community.