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  • 1From the Departments of Neurology (A.M.T., I.W.M.v.U., H.v.d.H., E.v.D., F.-E.d.L.), Geriatrics (J.A.H.R.C., R.P.C.K.), and Medical Psychology (R.P.C.K.), Radboudumc, and Centre for Cognitive Neuroimaging, Radboud University Nijmegen (A.M.T., D.G.N.), Donders Institute for Brain, Cognition and Behaviour, Nijmegen, Netherlands; Department of Clinical Neurosciences, Neurology Unit (L.C.A.R.-J., A.L., H.S.M.), University of Cambridge, UK; Department of Neurology (A.v.N.), Amphia ziekenhuis Breda; Department of Neurology (K.d.L.), HagaZiekenhuis Den Haag, the Netherlands; Erwin L. Hahn Institute for Magnetic Resonance Imaging (D.G.N.), University of Duisburg-Essen, Essen, Germany; and MIRA Institute for Biomedical Technology and Technical Medicine (D.G.N.), University of Twente, Enschede, the Netherlands.

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Summary
This summary is machine-generated.

Structural network connectivity predicts dementia risk in elderly individuals with small vessel disease (SVD). Lower global network efficiency at baseline was independently associated with an increased risk of developing all-cause dementia.

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Area of Science:

  • Neuroimaging
  • Neurology
  • Geriatrics

Background:

  • Small vessel disease (SVD) is common in the elderly and a risk factor for dementia.
  • The role of structural brain network integrity in dementia development within SVD populations is not fully understood.

Purpose of the Study:

  • To investigate if baseline structural network connectivity predicts incident all-cause dementia in elderly individuals with SVD.
  • To assess the association between MRI markers of SVD and brain network properties.

Main Methods:

  • Used diffusion tensor imaging and graph theory to analyze structural brain networks in 436 elderly participants with SVD from the RUN DMC cohort.
  • Calculated network efficiency measures and employed Cox proportional regression for survival analysis over a 5-year follow-up period.

Main Results:

  • 32 participants developed dementia during follow-up.
  • Lower global network efficiency at baseline was independently associated with a higher risk of all-cause dementia (HR 0.63, p=0.032).
  • Individual SVD markers like lacunes and white matter hyperintensities were not independently associated with dementia risk.

Conclusions:

  • Brain network disruption plays a significant role in dementia development in individuals with SVD.
  • Network analysis of white matter connectivity shows potential as a predictive marker for dementia in SVD patients.