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.com
Volume 8
Journal of Alzheimers Disease & Parkinsonism
ISSN: 2161-0460
Dementia 2018
October 29-31, 2018
October 29-31, 2018 | Valencia, Spain
12
th
International Conference on
Alzheimer’s Disease & Dementia
Cortical thickness and surface area networks in Alzheimer's disease and behavioral variant
frontotemporal dementia
Vesna Vuksanovic
1
, R T Staff
2
, T Ahearn
2
, AD Murray
1
and
CM Wischik
3,4
1
Aberdeen Biomedical Imaging Centre—University of Aberdeen, Aberdeen, UK
2
NHS Grampian, UK
3
TauRx Therapeutics, UK
4
School of Medicine and Dentistry—University of Aberdeen, UK
M
otivated by prior data of cortical regional volume differences, we investigated changes in cortical structural networks
in Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD). We estimated structural
correlation from magnetic resonance image (MRI) measures of cortical thickness and surface area at 68 regions, in a total of
628 participants (202 healthy elderly (HE), 213 bvFTD and 213 AD). We used network modules (i.e., groups of regions that
have a high density of connections within them, with a lower density of connections between groups) to estimate changes in
cortical networks that attribute globally, locally and at the lobe level. We found that the strength of structural correlation differs
in bvFTD and in AD group compared to HE. Global correlation of regional thinning is a marker of bvFTD condition and the
surface area correlation is a marker of AD. Cortical thickness and surface area correlational networks show a quite distinctive
hub like organization, which also differs both from normal and between the two forms of dementia. We conclude that bvFTD
and AD are associated with structural imaging markers of brain network organization differently.
Biography
Vesna Vuksanovic is working as a Research Fellow at the University of Aberdeen, Biomedical Imaging Centre. She has her specialization in Neuroimaging in Health
and Neurodegenerative Diseases. Her research interests include developing models of the brain as a network of complex interacting components; application of
these models in the context of brain disorders in dementia and understanding the progression of neurodegenerative processes using computational modeling of
neuroimaging data.
vesna.vuksanovic@abdn.ac.ukVesna Vuksanovic et al., J Alzheimers Dis Parkinsonism 2018, Volume 8
DOI: 10.4172/2161-0460-C7-054