White matter microstructure improves stroke risk prediction in the general population

Tavia E. Evans, Michael J. O'Sullivan, Marius De Groot, Wiro J. Niessen, Albert Hofman, Gabriel P. Krestin, Aad Van Der Lugt, Marileen L P Portegies, Peter J. Koudstaal, Daniel Bos, Meike W. Vernooij, M. Arfan Ikram*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

22 Citations (Scopus)


Background and Purpose - The presence of subclinical vascular brain disease, including white matter lesions and lacunar infarcts, substantially increases the risk of clinical stroke. White matter microstructural integrity is considered an earlier, potentially better, marker of the total burden of vascular brain disease. Its association with risk of stroke, a focal event, remains unknown. Methods - From the population-based Rotterdam Study, 4259 stroke-free participants (mean age: 63.6 years, 55.6% women) underwent brain magnetic resonance imaging, including diffusion magnetic resonance imaging, between 2006 and 2011. All participants were followed up for incident stroke until 2013. Cox proportional hazards models were used to associate markers of the microstructure of normal-appearing white matter with risk of stroke, adjusting for age, sex, white matter lesion volume, lacunar infarcts, and additionally for cardiovascular risk factors. Finally, we assessed the predictive value of white matter microstructural integrity for stroke beyond the Framingham Stroke Risk Profile. Results - During 18 476 person-years of follow-up, 58 people experienced a stroke. Both lower fractional anisotropy and higher MD increased risk of stroke, independent of age, sex, cardiovascular risk factors, white matter lesion volume, and lacunar infarcts (hazard ratio per SD increase in: fractional anisotropy: 0.75 [95% confidence interval, 0.57-0.98] and MD: 1.50 [95% confidence interval, 1.08-2.09]). MD improved stroke prediction beyond the Framingham Stroke Risk Profile (continuous net reclassification improvement: 0.52 [95% confidence interval, 0.24-0.81]). Conclusions - Future stroke is predicted not only by prevalent vascular lesions but also by subtle alterations in the microstructure of normal-appearing white matter. Inclusion of this effect in risk prediction models produces a significant advantage in stroke prediction compared with the existing Framingham Stroke Risk Profile.

Original languageEnglish
Pages (from-to)2756-2762
Number of pages7
Issue number11
Early online date4 Oct 2016
Publication statusPublished - 1 Nov 2016


  • aging
  • diffusion tensor imaging
  • prediction
  • quality of life
  • stroke


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