<p>Alzheimer’s disease (AD) is a degenerative disease with progressive deterioration of neural networks in the brain. Fractal dimension analysis (FD) of resting state blood oxygen level dependent (BOLD) signals acquired using functional magnetic resonance imaging (fMRI) allows us to quantify complex signalling in the brain and may offer a window into the network erosion. This novel approach can provide a sensitive tool to examine early stages of AD. As AD progresses, we expect to see a reduction in brain connectivity and signal complexity concurrent with biochemical changes (e.g. altered levels of N-acetyl aspartate (NAA), myoinositol (mI) and glutamate as measured using magnetic resonance spectroscopy, MRS), volumetric changes and abnormally high levels of brain iron.</p> <p>Over a series of 4 studies we examined the relationship of BOLD signal complexity and functional connectivity with documented MRI markers of pathology in AD (n=38) as compared to normal controls (NC) (n=16). AD subjects were in early stage of illness (mild to moderate impairment on the mini mental state exam, MMSE). We validated the temporal (short term (within minutes) and longer term (over a number of months)) consistency of FD measurement and choice of BOLD acquisition method (spiral vs. EPI), provided MRI sequence repeat time (TR) was kept constant. FD reduction (decrease in signal complexity) correlated with worsening pathological values on MRS (NAA decrease and mI increase) and with a decrease in functional connectivity. This demonstrates that FD (signal complexity) reduces in proportion to AD severity. FD reduction is connected to functional connectivity measured through resting state network (RSN) analysis suggesting the reduction in FD relates to neuronal loss rather than altered vascularity. The narrow range of cognitive impairment (such as scores on the MMSE or the clinical dementia rating scale, CDR) likely precluded correlation between these measures and FD or RSN. Functional connectivity (RSN) was also reduced when brain iron levels were increased within certain network nodes (posterior cingulate cortex and lateral parietal cortex). Therefore iron deposition may play a role in network disruption of AD brains.</p> <p>The overall conclusion of this thesis is that signal complexity of BOLD fMRI signals, as measured with FD, may detect early pathology in the progression of AD. FD can detect neuronal changes in deep brain structures before volume loss in these structures and before significant changes in MRS markers were detectable between the AD and NC groups. An FD change mirrors disruptions in functional connectivity but detection is not limited to RSN nodes in the brain. This novel approach could further our understanding of AD and may be applied to other pathologies of the brain.</p> / Doctor of Philosophy (PhD)
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/12522 |
| Date | 10 1900 |
| Creators | Warsi, Mohammed A. |
| Contributors | Noseworthy, Michael D., Molloy, William, Hasey, Gary M., Biomedical Engineering |
| Source Sets | McMaster University |
| Detected Language | English |
| Type | thesis |
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