| Literature DB >> 26413205 |
Madelaine Daianu1, Adam Mezher1, Neda Jahanshad1, Derrek P Hibar1, Talia M Nir1, Clifford R Jack2, Michael W Weiner3, Matt A Bernstein2, Paul M Thompson1.
Abstract
Our understanding of network breakdown in Alzheimer's disease (AD) is likely to be enhanced through advanced mathematical descriptors. Here, we applied spectral graph theory to provide novel metrics of structural connectivity based on 3-Tesla diffusion weighted images in 42 AD patients and 50 healthy controls. We reconstructed connectivity networks using whole-brain tractography and examined, for the first time here, cortical disconnection based on the graph energy and spectrum. We further assessed supporting metrics - link density and nodal strength - to better interpret our results. Metrics were analyzed in relation to the well-known APOE-4 genetic risk factor for late-onset AD. The number of disconnected cortical regions increased with the number of copies of the APOE-4 risk gene in people with AD. Each additional copy of the APOE-4 risk gene may lead to more dysfunctional networks with weakened or abnormal connections, providing evidence for the previously hypothesized "disconnection syndrome".Entities:
Keywords: APOE-4; Alzheimer’s disease; disconnection syndrome; energy; graph spectrum
Year: 2015 PMID： 26413205 PMCID： PMC4578320 DOI： 10.1109/ISBI.2015.7163910
Source DB: PubMed Journal: Proc IEEE Int Symp Biomed Imaging ISSN： 1945-7928