
Proceedings Paper
Communication of brain network core connections altered in behavioral variant frontotemporal dementia but possibly preserved in early-onset Alzheimer's diseaseFormat | Member Price | Non-Member Price |
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Paper Abstract
Diffusion imaging and brain connectivity analyses can assess white matter deterioration in the brain, revealing the underlying patterns of how brain structure declines. Fiber tractography methods can infer neural pathways and connectivity patterns, yielding sensitive mathematical metrics of network integrity. Here, we analyzed 1.5-Tesla wholebrain diffusion-weighted images from 64 participants – 15 patients with behavioral variant frontotemporal dementia (bvFTD), 19 with early-onset Alzheimer’s disease (EOAD), and 30 healthy elderly controls. Using whole-brain tractography, we reconstructed structural brain connectivity networks to map connections between cortical regions. We evaluated the brain’s networks focusing on the most highly central and connected regions, also known as hubs, in each diagnostic group – specifically the “high-cost” structural backbone used in global and regional communication. The high-cost backbone of the brain, predicted by fiber density and minimally short pathways between brain regions, accounted for 81-92% of the overall brain communication metric in all diagnostic groups. Furthermore, we found that the set of pathways interconnecting high-cost and high-capacity regions of the brain’s communication network are globally and regionally altered in bvFTD, compared to healthy participants; however, the overall organization of the high-cost and high-capacity networks were relatively preserved in EOAD participants, relative to controls. Disruption of the major central hubs that transfer information between brain regions may impair neural communication and functional integrity in characteristic ways typical of each subtype of dementia.
Paper Details
Date Published: 20 March 2015
PDF: 8 pages
Proc. SPIE 9413, Medical Imaging 2015: Image Processing, 941322 (20 March 2015); doi: 10.1117/12.2082352
Published in SPIE Proceedings Vol. 9413:
Medical Imaging 2015: Image Processing
Sébastien Ourselin; Martin A. Styner, Editor(s)
PDF: 8 pages
Proc. SPIE 9413, Medical Imaging 2015: Image Processing, 941322 (20 March 2015); doi: 10.1117/12.2082352
Show Author Affiliations
Madelaine Daianu, The Univ. of Southern California (United States)
Neda Jahanshad, The Univ. of Southern California (United States)
Mario F. Mendez, Univ. of California, Los Angeles School of Medicine (United States)
Neda Jahanshad, The Univ. of Southern California (United States)
Mario F. Mendez, Univ. of California, Los Angeles School of Medicine (United States)
George Bartzokis, Univ. of California, Los Angeles School of Medicine (United States)
Elvira E. Jimenez, Univ. of California, Los Angeles School of Medicine (United States)
Paul M. Thompson, Univ. of Southern California (United States)
Elvira E. Jimenez, Univ. of California, Los Angeles School of Medicine (United States)
Paul M. Thompson, Univ. of Southern California (United States)
Published in SPIE Proceedings Vol. 9413:
Medical Imaging 2015: Image Processing
Sébastien Ourselin; Martin A. Styner, Editor(s)
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