The goal of this proposal is to develop and integrate a high spatial/spectral resolution reproducible whole-brain
magnetic resonance spectroscopic imaging (MRSI) framework on 3T scanners to improve our understanding
of metabolic changes that occur in Alzheimer’s disease and related dementias. While MRSI has been shown to
provide great utility to study metabolic changes associated with neurodegenerative disorders, its widespread
adaption as a clinical tool has not been realized due to several technical challenges, such as low sensitivity,
low spatial resolution (often just single voxel), B0 field inhomogeneity, and lack of complete integration with the
scanner. The goal of this study is to develop novel methods of acquiring, processing, quantifying, and
analyzing MR spectral data that overcome these technical challenges. This work will be undertaken by a
collaborative team of investigators from the University of Iowa, University of California San Francisco, and GE
Healthcare.
To achieve our goals, we are proposing the following specific aims: 1) Develop and validate a high-resolution
5D MRSI framework on 3T scanners; 2) Develop tools for quantitative regional assessment of MRSI data; and
3) Evaluate the reliability and utility of the MRSI tools in a cohort of mild cognitive impairment (MCI), early
Alzheimer’s disease, and a matched control sample without memory issues. Aims 1 and 2 will generate a
normative metabolic atlas for ages 40-80 years old, which is composed of equal representation by gender. The
resulting tools will also be applied to Aim 3 to evaluate brain metabolic profiles in MCI and early Alzheimer’s
disease as compared to the matched control sample. The successful completion of this proposal will result in a
whole brain MRSI protocol capable of collecting high quality data in less than 20 minutes, which can be used to
study metabolic changes associated with Alzheimer’s disease and related dementias. The tools developed
here will be distributed through the GE collaboration portal where they will be shared as a work in progress
(WIP) package where feedback from the broader user community will be gathered to further refine the tools. In
addition, the tools will also be distributed in an open format allowing them to be readily ported to MR scanners
from other vendors. Ultimately, the tools will provide the ability to identify metabolic changes that occur in the
brain associated with neurodegenerative disorders, which could be used to identify potential targets for new
therapeutic agents as well as a marker for response to such therapies.