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A Versatile Murine Model of Subcortical White Matter Stroke for the Study of Axonal Degeneration and White Matter Neurobiology
Published on: March 17, 2016
White Matter Microstructure Improves Stroke Risk Prediction in the General Population.
Tavia E Evans1, Michael J O'Sullivan1, Marius de Groot1
1From the Department of Epidemiology (T.E.E., M.d.G., A.H., M.L.P.P., D.B., M.W.V., M.A.I.), Department of Radiology and Nuclear Medicine (T.E.E., M.d.G., W.J.N., G.P.K., A.v.d.L., D.B., M.W.V., M.A.I.), Department of Medical Informatics (M.d.G., W.J.N.), and Department of Neurology (M.L.P.P., P.J.K., M.A.I.), Erasmus MC, Rotterdam, The Netherlands; Department of Basic and Clinical Neurosciences, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, United Kingdom (T.E.E., M.J.O.); Imaging Physics, Faculty of Applied Sciences, Delft University of Technology, The Netherlands (W.J.N.); and Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA (A.H., D.B.).
Subtle white matter changes predict future stroke risk, independent of traditional markers. Assessing white matter integrity improves stroke prediction models beyond current profiles.
Area of Science:
- Neurology
- Radiology
- Epidemiology
Background:
- Subclinical vascular brain disease, including white matter lesions and lacunar infarcts, elevates stroke risk.
- White matter microstructural integrity may serve as an early indicator of vascular brain disease burden.
- The association between white matter microstructural integrity and focal stroke risk is not well understood.
Purpose of the Study:
- To investigate the association between normal-appearing white matter microstructure and incident stroke risk.
- To determine if white matter microstructural integrity improves stroke risk prediction beyond established models.
Main Methods:
- Analysis of brain MRI data (including diffusion MRI) from 4259 stroke-free participants in the population-based Rotterdam Study.
- Follow-up for incident stroke, with Cox proportional hazards models used to assess associations.
- Adjustment for age, sex, cardiovascular risk factors, white matter lesions, and lacunar infarcts.
Main Results:
- Lower fractional anisotropy and higher mean diffusivity (MD) in normal-appearing white matter were associated with increased stroke risk, independent of other factors.
- Mean diffusivity (MD) significantly improved stroke risk prediction beyond the Framingham Stroke Risk Profile.
- The study included 4259 participants with 18,476 person-years of follow-up, during which 58 strokes occurred.
Conclusions:
- Subtle alterations in white matter microstructure predict future stroke risk.
- Incorporating white matter microstructural integrity into risk prediction models offers significant advantages over the Framingham Stroke Risk Profile.
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