This proposal aims to (1) develop and evaluate novel methodologies for functional magnetic resonance imaging (fMRI) of the human cervical spinal cord at ultra-high field (7 Tesla), and (2) non-invasively detect and characterize functional networks in the human cervical spinal cord. These methods may be used clinically to establish the extent of spinal cord injuries and to monitor the progression of functional recovery afterwards, and may also facilitate earlier detection of central nervous system pathologies such as multiple sclerosis. We propose to develop 7T fMRI to detect and quantify low-frequency fluctuations in baseline BOLD (blood oxygenation level dependent) signals as indicators of resting state functional connectivity in spinal gray matter. To date, over 3500 studies have used similar fMRI approaches to study functional connectivity in the brain, and have provided compelling evidence that low-frequency BOLD signal fluctuations are inherent in normal, healthy brains and represent an important level of organization of cortical function. However, to date no corresponding studies have conclusively demonstrated similar low-frequency correlations in spinal gray matter. The precise functioning of the spinal cord in normal and pathological populations remains poorly understood even though studies of functional connectivity and spinal cord plasticity using methods other than MRI have been topics of intense research for the past two decades. The scarcity of spinal fMRI studies mainly reflects the technical difficulties of performing fMRI in the spinal cord, the failure to develop appropriate methods and coils, and the need for higher spatial resolution and greater sensitivity for imaging the spinal cord compared to the brain. We hypothesize that the proposed technical advances can be used to detect and characterize functional connectivity in the cervical spinal cord and changes that occur with injury, recovery and repair, and that these measures will complement information from other functional measures including task-based fMRI studies. We propose to address the need for high spatial resolution and greater BOLD sensitivity by using an ultra-high field (7 Tesla) scanner and a dedicated 16-channel cervical spine coil to develop (Aim 1) and validate (Aim 2) novel fMRI acquisition and data correction protocols. The applicant is a computer/biomedical engineer, so didactic training during the K99 phase is focused on neuroscience and neuroanatomy to develop the skills required for the R00 phase, namely interpretation of resting state spinal networks in healthy controls (Aim 3) and subjects with cervical spondylotic myelopathy (Aim 4). The higher signal-to-noise ratio and BOLD contrast from 7T fMRI have already shown significant advantages over lower field studies for detecting activation and connectivity at high spatial resolution in the brain, and parallel coil arrays permit faster image acquisitions. Thus, ultra-high field MRI is uniquely poised to provide insights into human spinal cord function that are not possible in practice at lower fields. The applicant's long term goal is o become an independent imaging scientist specializing in functional imaging of the brain and spinal cord and the development of advanced neuroimaging methods.

Public Health Relevance

This project will develop and evaluate novel magnetic resonance imaging methodologies to non-invasively detect and characterize functional networks in the human cervical spinal cord. These methods may be used clinically to establish the extent of injury to the spinal cord and to monitor the progression of functional recovery afterwards. These techniques may also facilitate earlier detection of central nervous system pathologies such as multiple sclerosis and transverse myelitis.

Agency
National Institute of Health (NIH)
Type
Career Transition Award (K99)
Project #
1K99EB016689-01A1
Application #
8635089
Study Section
Special Emphasis Panel (ZEB1)
Program Officer
Erim, Zeynep
Project Start
Project End
Budget Start
Budget End
Support Year
1
Fiscal Year
2014
Total Cost
Indirect Cost
Name
Vanderbilt University Medical Center
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
City
Nashville
State
TN
Country
United States
Zip Code
37212