You are here

Article Text

Article menu
Download PDFPDF
Cerebrovascular disease
Original research
Structural network changes in cerebral small vessel disease
  1. Anil M Tuladhar1,
  2. Jonathan Tay2,
  3. Esther van Leijsen3,
  4. Andrew J Lawrence4,
  5. Ingeborg Wilhelmina Maria van Uden1,
  6. Mayra Bergkamp5,
  7. Ellen van der Holst6,
  8. Roy P C Kessels7,8,
  9. David Norris,
  10. Hugh S Markus9,
  11. Frank-Erik De Leeuw10
  1. 1 Department of Neurology, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
  2. 2 Department of Neurology, University of Cambridge Clinical Neurosciences, Cambridge, UK
  3. 3 Department of Neurology, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
  4. 4 Department of Psychiatry, King’s College Institute of Psychiatry, Psychology, and Neuroscience, London, UK
  5. 5 Department of Neurology, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
  6. 6 Department of Neurology, Jeroen Bosch Ziekenhuis, 's-Hertogenbosch, Den Bosch, The Netherlands
  7. 7 Department of Medical Psychology, Radboud University Medical Center, Nijmegen, The Netherlands
  8. 8 Department of Neuropsychology and Rehabilitation Psychology, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
  9. 9 Department on Neurology, University of Cambridge, Cambridge, UK
  10. 10 Department of Neurology, Radboud University Nijmegen Medical Centre, Donders Institute for Brain, Cognition and Behaviour, Centre for Neuroscience, Nijmegen, The Netherlands
  1. Correspondence to Anil M Tuladhar, Department of Neurology, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Cente, Nijmegen 6525 GC, The Netherlands; Anil.Tuladhar{at}radboudumc.nl

Abstract

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 (β=0.18, p=0.03) and a trend with change in cognitive index (β=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.

  • cerebral small vessel disease
  • structural neuroimaging
  • diffusion tensor imaging
  • cognitive decline
  • mortality

https://doi.org/10.1136/jnnp-2019-321767

Statistics from Altmetric.com

    Request Permissions

    If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

    View Full Text

    Footnotes

    • Contributors AMT was involved in data collection, analysis and interpretation of data, and drafting and revising the manuscript. JT was involved in analysis of data. EvL, IWMvU and MB were involved in data collection and revising the manuscript. AJL was involved in analysis and revising the manuscript. EvdH and RPCK were involved in data collection, data analysis and revising the manuscript. DN was involved in study concept and design and revising the manuscript. HSM was involved in data analysis and revising the manuscript. F-EDL was involved in study concept and design, interpretation of data, revising the manuscript and obtaining funding.

    • Funding AMT is supported by a junior staff member grant of the Dutch Heart Foundation (grant number 2016 T044). HSM is supported by an NIHR Senior Investigator award. F-EDL is supported by a clinical established investigator grant of the Dutch Heart Foundation (grant number 2014 T060) and by a VIDI innovational grant from The Netherlands Organisation for Health Research and Development (ZonMw grant 016.126.351).

    • Competing interests None declared.

    • Patient consent for publication Not required.

    • Ethics approval The Medical Review Ethics Committee region Arnhem-Nijmegen approved the study (ID: 2005/256).

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Data availability statement Data are available upon reasonable request.