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Publication year
2020Author(s)
Number of pages
8 p.
Source
Journal of Neurology, Neurosurgery, and Psychiatry, 91, 2, (2020), pp. 196-203ISSN
Publication type
Article / Letter to editor

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Organization
Neurology
SW OZ DCC NRP
Medical Psychology
PI Group MR Techniques in Brain Function
Biophysics
Journal title
Journal of Neurology, Neurosurgery, and Psychiatry
Volume
vol. 91
Issue
iss. 2
Languages used
English (eng)
Page start
p. 196
Page end
p. 203
Subject
150 000 MR Techniques in Brain Function; Neuropsychology and rehabilitation psychology; Radboudumc 1: Alzheimer`s disease DCMN: Donders Center for Medical Neuroscience; Radboudumc 3: Disorders of movement DCMN: Donders Center for Medical Neuroscience; Neuro- en revalidatiepsychologieAbstract
Objectives: To investigate whether longitudinal structural network efficiency is associated with cognitive decline and whether baseline network efficiency predicts mortality in cerebral small vessel disease (SVD). Methods: A prospective, single-centre cohort consisting of 277 non-demented individuals with SVD was conducted. In 2011 and 2015, all participants were scanned with MRI and underwent neuropsychological assessment. We computed network properties using graph theory from probabilistic tractography and calculated changes in psychomotor speed and overall cognitive index. Multiple linear regressions were performed, while adjusting for potential confounders. We divided the group into mild-to-moderate white matter hyperintensities (WMH) and severe WMH group based on median split on WMH volume. Results: The decline in global efficiency was significantly associated with a decline in psychomotor speed in the group with severe WMH (ß=0.18, p=0.03) and a trend with change in cognitive index (ß=0.14, p=0.068), which diminished after adjusting for imaging markers for SVD. Baseline global efficiency was associated with all-cause mortality (HR per decrease of 1 SD 0.43, 95% CI 0.23 to 0.80, p=0.008, C-statistic 0.76). Conclusion: Disruption of the network efficiency, a metric assessing the efficiency of network information transfer, plays an important role in explaining cognitive decline in SVD, which was however not independent of imaging markers of SVD. Furthermore, baseline network efficiency predicts risk of mortality in SVD that may reflect the global health status of the brain in SVD. This emphasises the importance of structural network analysis in the context of SVD research and the use of network measures as surrogate markers in research setting.
This item appears in the following Collection(s)
- Academic publications [204024]
- Donders Centre for Cognitive Neuroimaging [3409]
- Electronic publications [102375]
- Faculty of Medical Sciences [80459]
- Faculty of Science [32153]
- Faculty of Social Sciences [27316]
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