Title
White matter microstructure improves stroke risk prediction in the general population
Author
Evans, Tavia E. (Erasmus MC)
O'Sullivan, Michael J. (King’s College London)
De Groot, Marius (Erasmus MC)
Niessen, W.J. (TU Delft ImPhys/Quantitative Imaging; Erasmus MC) 
Hofman, Albert (Harvard T.H. Chan School of Public Health; Erasmus MC)
Krestin, Gabriel P. (Erasmus MC)
Van Der Lugt, Aad (Erasmus MC)
Portegies, Marileen L P (Erasmus MC)
Koudstaal, Peter J. (Erasmus MC)
Bos, Daniel (Harvard T.H. Chan School of Public Health; Erasmus MC)
Vernooij, Meike W. (Erasmus MC)
Ikram, M. Arfan (Erasmus MC)
Date
2016-11-01
Abstract
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.
Subject
aging
diffusion tensor imaging
prediction
quality of life
stroke
To reference this document use:
http://resolver.tudelft.nl/uuid:86b73693-ed03-4ecd-a729-f70b019fb13c
DOI
https://doi.org/10.1161/STROKEAHA.116.014651
ISSN
0039-2499
Source
Stroke, 47 (11), 2756-2762
Part of collection
Institutional Repository
Document type
journal article
Rights
© 2016 Tavia E. Evans, Michael J. O'Sullivan, Marius De Groot, W.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