Functional MRI characterization of lesion-induced plasticity and improved acquisition techniques
Abstract/Contents
- Abstract
- Functional magnetic resonance imaging (fMRI) is an indispensable imaging method for studying human central nervous system (CNS) by detecting blood-oxygen-level- dependent (BOLD) signal induced by neural activity. It has enabled an understanding of intrinsic connectivity in the brain and the spinal cord and can generate biomarkers for CNS disorders including brain diseases and chronic pain. FMRI can be employed to study brain connectivity not only in healthy controls, but also in patients with brain lesions. For brain fMRI on a patient with a lesion, conventional analysis methods for fMRI (e.g., ICA, seed-based analysis) have been applied in previous studies to demonstrate abnormal brain connectivity in the patients. However, no prior study has performed lesion-specific analysis, which means placing a seed in the lesion area to see how the lesion affects brain connectivity. In the first work in this dissertation, resting state fMRI is used for a patient with hemorrhagic traumatic axonal injury (hTAI) lesions. Seed based analysis provides evidence of resting state network changes in a patient and demonstrates that seed placement within a lesion's periphery or in the contralesional hemisphere may be necessary for lesion-specific analysis. In addition, despite many improved techniques in fMRI acquisition and reconstruction, there remain image artifacts or drawbacks depending on the techniques. One of the widely used data acquisition methods is partial Fourier (PF) reconstruction, which depends on Hermitian symmetry to eliminate the need for full k-space acquisition. This technique has the benefit of shortened scan time or echo time and therefore, it is worthwhile and often employed in fMRI. However, the conventional partial Fourier reconstruction, homodyne, results in signal loss in air/tissue interfaces due to large susceptibility variations which violate k-space symmetry assumptions. In the second work, a novel PF reconstruction method is introduced that is more robust to off-resonance compared to existing methods. With a simple modification of the conventional PF method, reduced signal drop out and more activation from breath-holding task fMRI is demonstrated. Since the beginning of fMRI studies of study human CNS, much research has ensued on fMRI techniques, such as sequence developments, data analysis methods, and noise reduction. As many of these developments have been optimized for brain fMRI, they may not be the optimal methods for spinal cord fMRI. The spinal cord has different structure and it is affected much more by physiological noise and motion from nearby structures and/or itself compared to the brain. Spinal cord fMRI has not been standardized due to challenges that include substantial cardiac-synchronized motion and still more works are required to be optimized. In the third work, cardiac related noise in spinal cord fMRI is reduced using cardiac gating together with correction for signal fluctuation from variations in heart rate. Two means for the latter correction are introduced, using multiple echoes and independent component analysis (ICA). With a fist clenching task, it is demonstrated that ICA effectively mitigates the fluctuations compared to the division method.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2020; ©2020 |
| Publication date | 2020; 2020 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Lee, Seul |
|---|---|
| Degree supervisor | Glover, Gary H |
| Degree supervisor | Nishimura, Dwight George |
| Degree supervisor | Pauly, John (John M.) |
| Thesis advisor | Glover, Gary H |
| Thesis advisor | Nishimura, Dwight George |
| Thesis advisor | Pauly, John (John M.) |
| Associated with | Stanford University, Department of Electrical Engineering |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Seul Lee. |
|---|---|
| Note | Submitted to the Department of Electrical Engineering. |
| Thesis | Thesis Ph.D. Stanford University 2020. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2020 by Seul Lee
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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