Quantitative brain tissue oxygenation mapping using magnetic resonance spin relaxation
Abstract/Contents
- Abstract
- Oxygenation, as quantified by the parameter of oxygen saturation, is a vital property that reflects the functional status of brain tissues. It enables effective assessment of the health and salvageability of tissues affected by pathology, and allows for better understanding of physiological and neuronal mechanisms in the brain. Magnetic resonance imaging (MRI), a safe, non-invasive and flexible imaging modality, may be utilized for mapping brain tissue oxygenation. This dissertation focuses on the clinical translation and validation of one class of MRI-based techniques, which derives oxygenation information from a transverse relaxation rate of MRI signal denoted R2'. We found that the measurement of R2' is highly dependent on the MRI technique used. Having identified gradient-echo sampling of free induction decay and echo (GESFIDE) as a good candidate for simultaneous quantitation of the three transverse relaxation rates (R2', R2* and R2), we benchmarked their intra-scan reproducibility and assessed their changes during gas challenges in normal subjects, finding strong hypoxia to be the recommended gas challenge for validating oxygenation mapping methods, and tissue R2' change to be the recommended relaxation-based metric for studying brain tissue oxygenation. Finally, we assessed the changes in these three relaxation rates in Moyamoya disease, along with measuring acetazolamide-induced cerebrovascular reactivity, finding regions with limited perfusion augmentation also displayed reduction in R2', suggesting a potential for baseline oxygenation measurement to replace the acetazolamide challenge, and again recommending R2' over R2* and R2 as the preferred tissue oxygenation metric.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2016 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Ni, Wendy Wei |
|---|---|
| Associated with | Stanford University, Department of Electrical Engineering. |
| Primary advisor | Zaharchuk, Greg |
| Thesis advisor | Zaharchuk, Greg |
| Thesis advisor | Moseley, Michael E. (Michael Eugene), 1951- |
| Thesis advisor | Nishimura, Dwight George |
| Thesis advisor | Spielman, Daniel (Daniel Mark) |
| Advisor | Moseley, Michael E. (Michael Eugene), 1951- |
| Advisor | Nishimura, Dwight George |
| Advisor | Spielman, Daniel (Daniel Mark) |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Wendy Wei Ni. |
|---|---|
| Note | Submitted to the Department of Electrical Engineering. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2016. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2016 by Wendy Wei Ni
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
Also listed in
Loading usage metrics...