The ageing brain undergoes many structural changes. High resolution imaging with MRI has allowed visualisation and quantification of many aspects of this neurological degeneration. One particular feature of the ageing brain is the increased presence of hyperintensities. These can be clearly visualised with T2-weighted imaging. Manual scoring of these lesions is time consuming and prone to inter- and intra-observers variability. We developed automatic methods for quantification and classification of the hyperintensity volumes using T1-weighted and fluid attenuation inversion recovery images of Aberdeen Birth Cohort of 1936. The hyperintensities were classified into different brain regions given by the local Scheltens’ scale, i.e., grey matter, infratentorial, deep white matter and periventricular white matter. The automatically generated hyperintensity volumes were compared with the local scores and investigated in relation to respiratory function and smoking history. Ageing is also associated with cognitive decline. We investigated the role of the structural complexity of ageing brains in the life course changes of cognitive ability. We hypothesised that fractal descriptors of white matter would be associated with childhood IQ, suggesting early cognitive maturation, better fluid cognitive performance and less decline in late life. This was done using fractal measures of white matter structure. Our results show that the automatic quantification and classification methods provide a promising alternative to manual grading with strong correlations (p<.05). The automatic hyperintensity volumes broadly show the same pattern association as shown by the local scores when investigating with the respiratory function, and stronger correlations with daily cigarette consumption and smoking burden than did the local scores. The results of fractal measures of brain complexity demonstrate the potential of fractal measures as an estimate of structural maturation.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:582736 |
| Date | January 2013 |
| Creators | Mustafa, Nazahah |
| Publisher | University of Aberdeen |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=201741 |
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