Helena M van der Holst1, Inge W M van Uden1, Anil M Tuladhar1, Karlijn F de Laat1, Anouk G W van Norden1, David G Norris1, Ewoud J van Dijk1, Rianne A J Esselink1, Bram Platel1, Frank-Erik de Leeuw2. 1. From the Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Center for Neuroscience, Department of Neurology (H.M.v.d.H., I.W.M.v.U., A.M.T., E.J.v.D., R.A.J.E., F.-E.d.L.), and Radboud University, Donders Institute for Brain, Cognition and Behaviour, Center for Cognitive Neuroimaging (A.M.T., D.G.N.), Nijmegen, the Netherlands; Department of Neurology (K.F.d.L.), HagaZiekenhuis Den Haag, the Netherlands; Department of Neurology (A.G.W.v.N.), Amphia Ziekenhuis Breda, the Netherlands; Erwin L. Hahn Institute for Magnetic Resonance Imaging (D.G.N.), UNESCO-Weltkulturerbe Zollverein, Leitstand Kokerei Zollverein, Essen, Germany; MIRA Institute for Biomedical Technology and Technical Medicine (D.G.N.), University of Twente, Enschede, the Netherlands; and Department of Radiology and Nuclear Medicine (B.P.), Radboud University Medical Center, Nijmegen, the Netherlands. 2. From the Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Center for Neuroscience, Department of Neurology (H.M.v.d.H., I.W.M.v.U., A.M.T., E.J.v.D., R.A.J.E., F.-E.d.L.), and Radboud University, Donders Institute for Brain, Cognition and Behaviour, Center for Cognitive Neuroimaging (A.M.T., D.G.N.), Nijmegen, the Netherlands; Department of Neurology (K.F.d.L.), HagaZiekenhuis Den Haag, the Netherlands; Department of Neurology (A.G.W.v.N.), Amphia Ziekenhuis Breda, the Netherlands; Erwin L. Hahn Institute for Magnetic Resonance Imaging (D.G.N.), UNESCO-Weltkulturerbe Zollverein, Leitstand Kokerei Zollverein, Essen, Germany; MIRA Institute for Biomedical Technology and Technical Medicine (D.G.N.), University of Twente, Enschede, the Netherlands; and Department of Radiology and Nuclear Medicine (B.P.), Radboud University Medical Center, Nijmegen, the Netherlands. frankerik.deleeuw@radboudumc.nl.
Abstract
OBJECTIVE: To investigate the relation between baseline cerebral small vessel disease (SVD) and the risk of incident parkinsonism using different MRI and diffusion tensor imaging (DTI) measures. METHODS: In the Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Cohort (RUN DMC) study, a prospective cohort study, 503 elderly participants with SVD and without parkinsonism were included in 2006. During follow-up (2011-2012), parkinsonism was diagnosed according to UK Brain Bank criteria. Cox regression analysis was used to investigate the association between baseline imaging measures and incident all-cause parkinsonism and vascular parkinsonism (VP). Tract-based spatial statistics analysis was used to identify differences in baseline DTI measures of white matter (WM) tracts between participants with VP and without parkinsonism. RESULTS: Follow-up was available from 501 participants (mean age 65.6 years; mean follow-up duration 5.2 years). Parkinsonism developed in 20 participants; 15 were diagnosed with VP. The 5-year risk of (any) parkinsonism was increased for those with a high white matter hyperintensity (WMH) volume (hazard ratio [HR] 1.8 per SD increase, 95% confidence interval [CI] 1.3-2.4) and a high number of lacunes (HR 1.4 per number increase, 95% CI 1.1-1.8) at baseline. For VP, this risk was also increased by the presence of microbleeds (HR 5.7, 95% CI 1.9-16.8) and a low gray matter volume (HR 0.4 per SD increase, 95% CI 0.2-0.8). Lower fractional anisotropy values in bifrontal WM tracts involved in movement control were observed in participants with VP compared to participants without parkinsonism. CONCLUSIONS: SVD at baseline, especially a high WMH volume and a high number of lacunes, is associated with incident parkinsonism. Our findings favor a role of SVD in the etiology of parkinsonism.
OBJECTIVE: To investigate the relation between baseline cerebral small vessel disease (SVD) and the risk of incident parkinsonism using different MRI and diffusion tensor imaging (DTI) measures. METHODS: In the Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Cohort (RUN DMC) study, a prospective cohort study, 503 elderly participants with SVD and without parkinsonism were included in 2006. During follow-up (2011-2012), parkinsonism was diagnosed according to UK Brain Bank criteria. Cox regression analysis was used to investigate the association between baseline imaging measures and incident all-cause parkinsonism and vascular parkinsonism (VP). Tract-based spatial statistics analysis was used to identify differences in baseline DTI measures of white matter (WM) tracts between participants with VP and without parkinsonism. RESULTS: Follow-up was available from 501 participants (mean age 65.6 years; mean follow-up duration 5.2 years). Parkinsonism developed in 20 participants; 15 were diagnosed with VP. The 5-year risk of (any) parkinsonism was increased for those with a high white matter hyperintensity (WMH) volume (hazard ratio [HR] 1.8 per SD increase, 95% confidence interval [CI] 1.3-2.4) and a high number of lacunes (HR 1.4 per number increase, 95% CI 1.1-1.8) at baseline. For VP, this risk was also increased by the presence of microbleeds (HR 5.7, 95% CI 1.9-16.8) and a low gray matter volume (HR 0.4 per SD increase, 95% CI 0.2-0.8). Lower fractional anisotropy values in bifrontal WM tracts involved in movement control were observed in participants with VP compared to participants without parkinsonism. CONCLUSIONS:SVD at baseline, especially a high WMH volume and a high number of lacunes, is associated with incident parkinsonism. Our findings favor a role of SVD in the etiology of parkinsonism.
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