Anil M Tuladhar1, Andrew T Reid1, Elena Shumskaya1, Karlijn F de Laat1, Anouk G W van Norden1, Ewoud J van Dijk1, David G Norris1, Frank-Erik de Leeuw2. 1. From the Department of Neurology, Center for Neuroscience (A.M.T., A.G.W.v.N., E.J.v.D., F.-E.d.L.), Centre for Cognitive Neuroimaging (E.S., D.G.N.), Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands; Institute of Neuroscience and Medicine (INM-1), Research Center Julich, Julich, Germany (A.T.R.); Department of Neurology, HagaZiekenhuis Den Haag, Den Haag, The Netherlands (K.F.d.L.); Erwin L. Hahn Institute for Magnetic Resonance Imaging, University of Duisburg-Essen, Essen, Germany (D.G.N.); and MIRA Institute for Biomedical Technology and Technical Medicine, University of Twente, Enschede, The Netherlands (D.G.N.). 2. From the Department of Neurology, Center for Neuroscience (A.M.T., A.G.W.v.N., E.J.v.D., F.-E.d.L.), Centre for Cognitive Neuroimaging (E.S., D.G.N.), Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands; Institute of Neuroscience and Medicine (INM-1), Research Center Julich, Julich, Germany (A.T.R.); Department of Neurology, HagaZiekenhuis Den Haag, Den Haag, The Netherlands (K.F.d.L.); Erwin L. Hahn Institute for Magnetic Resonance Imaging, University of Duisburg-Essen, Essen, Germany (D.G.N.); and MIRA Institute for Biomedical Technology and Technical Medicine, University of Twente, Enschede, The Netherlands (D.G.N.). FrankErik.deLeeuw@radboudumc.nl.
Abstract
BACKGROUND AND PURPOSE: White matter hyperintensities (WMH) are associated with clinically heterogeneous symptoms that cannot be explained by these lesions alone. It is hypothesized that these lesions are associated with distant cortical atrophy and cortical thickness network measures, which can result in an additional cognitive impairment. Here, we investigated the relationships between WMH, cortical thickness, and cognition in subjects with cerebral small vessel disease. METHODS: A total of 426 subjects with cerebral small vessel disease were included, aged between 50 and 85 years, without dementia, and underwent MRI scanning. Cortical thickness analysis was performed, and WMH were manually segmented. Graph theory was applied to examine the relationship between network measures and WMH, and structural covariance matrices were constructed using inter-regional cortical thickness correlations. RESULTS: Higher WMH load was related to lower cortical thickness in frontotemporal regions, whereas in paracentral regions, this was related to higher cortical thickness. Network analyses revealed that measures of network disruption were associated with WMH and cognitive performance. Furthermore, WMH in specific white matter tracts were related to regional-specific cortical thickness and network measures. Cognitive performances were related to cortical thickness in frontotemporal regions and network measures, and not to WMH, while controlling for cortical thickness. CONCLUSIONS: These cross-sectional results suggest that cortical changes (regional-specific damage and network breakdown), mediated (in)directly by WMH (tract-specific damage) and other factors (eg, vascular risk factors), might lead to cognitive decline. These findings have implications in understanding the relationship between WMH, cortical morphology, and the possible attendant cognitive decline and eventually dementia.
BACKGROUND AND PURPOSE: White matter hyperintensities (WMH) are associated with clinically heterogeneous symptoms that cannot be explained by these lesions alone. It is hypothesized that these lesions are associated with distant cortical atrophy and cortical thickness network measures, which can result in an additional cognitive impairment. Here, we investigated the relationships between WMH, cortical thickness, and cognition in subjects with cerebral small vessel disease. METHODS: A total of 426 subjects with cerebral small vessel disease were included, aged between 50 and 85 years, without dementia, and underwent MRI scanning. Cortical thickness analysis was performed, and WMH were manually segmented. Graph theory was applied to examine the relationship between network measures and WMH, and structural covariance matrices were constructed using inter-regional cortical thickness correlations. RESULTS: Higher WMH load was related to lower cortical thickness in frontotemporal regions, whereas in paracentral regions, this was related to higher cortical thickness. Network analyses revealed that measures of network disruption were associated with WMH and cognitive performance. Furthermore, WMH in specific white matter tracts were related to regional-specific cortical thickness and network measures. Cognitive performances were related to cortical thickness in frontotemporal regions and network measures, and not to WMH, while controlling for cortical thickness. CONCLUSIONS: These cross-sectional results suggest that cortical changes (regional-specific damage and network breakdown), mediated (in)directly by WMH (tract-specific damage) and other factors (eg, vascular risk factors), might lead to cognitive decline. These findings have implications in understanding the relationship between WMH, cortical morphology, and the possible attendant cognitive decline and eventually dementia.
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Authors: Anil M Tuladhar; Ewoud van Dijk; Marcel P Zwiers; Anouk G W van Norden; Karlijn F de Laat; Elena Shumskaya; David G Norris; Frank-Erik de Leeuw Journal: Hum Brain Mapp Date: 2015-10-15 Impact factor: 5.038