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Characterizing white matter health and organization in atherosclerotic vascular disease: A diffusion tensor imaging study

Overview of attention for article published in Psychiatry Research: Neuroimaging, October 2013
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Article details
Title
Characterizing white matter health and organization in atherosclerotic vascular disease: A diffusion tensor imaging study
Published in
Psychiatry Research: Neuroimaging, October 2013
DOI 10.1016/j.pscychresns.2013.07.011
Pubmed ID
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Abstract

Atherosclerotic vascular disease (AVD) is endemic to the developed world, with known negative outcomes for cognition and brain health. The effects of AVD on the white matter fibers of the brain have not yet been studied using diffusion tensor imaging (DTI). This study examined differences in fractional anisotropy (FA) between AVD and healthy comparison (HC) participants, and described the regional patterns of FA in each group. AVD participants were hypothesized to have lower FA than HC participants, indicating abnormalities in white matter health or organization. 1.5 T diffusion tensor imaging was performed in 35 AVD and 22 HC participants. Mean FA measures were calculated for the white matter of the whole brain, as well for individual lobes. Globally and in every brain region measured except the temporal lobes, there were significant effects of group where AVD participants had lower FA values than their HC counterparts. Group differences in FA remained significant when controlled for white matter hyperintensity (WMH) volume, suggesting that FA detects white matter abnormality above and beyond what is measurable using the older WMH technique. These findings suggest a likely neural substrate underlying the changes in cognition and mood reported in atherosclerotic vascular disease patients.

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The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Ireland 1 3%
Unknown 32 97%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 8 24%
Student > Master 5 15%
Professor > Associate Professor 5 15%
Researcher 4 12%
Professor 3 9%
Other 4 12%
Unknown 4 12%
Readers by discipline
Readers by discipline Count As %
Medicine and Dentistry 7 21%
Psychology 6 18%
Agricultural and Biological Sciences 3 9%
Neuroscience 3 9%
Engineering 2 6%
Other 5 15%
Unknown 7 21%