Neuroimaging Anomalies in Community-Dwelling Asymptomatic Adults With Very Early-Stage White Matter Hyperintensity

White matter hyperintensity (WMH) is common in healthy adults in their 60s and can be seen as early as in their 30s and 40s. Alterations in the brain structural and functional profiles in adults with WMH have been repeatedly studied but with a focus on late-stage WMH. To date, structural and functional MRI profiles during the very early stage of WMH remain largely unexplored. To address this, we investigated multimodal MRI (structural, diffusion, and resting-state functional MRI) profiles of community-dwelling asymptomatic adults with very early-stage WMH relative to age-, sex-, and education-matched non-WMH controls. The comparative results showed significant age-related and age-independent changes in structural MRI-based morphometric measures and resting-state fMRI-based measures in a set of specific gray matter (GM) regions but no global white matter changes. The observed structural and functional anomalies in specific GM regions in community-dwelling asymptomatic adults with very early-stage WMH provide novel data regarding very early-stage WMH and enhance understanding of the pathogenesis of WMH.

[1]  Zhijun Zhang,et al.  Functional Disorganization of Small-World Brain Networks in Patients With Ischemic Leukoaraiosis , 2020, Frontiers in Aging Neuroscience.

[2]  John D. Murray,et al.  Generative modeling of brain maps with spatial autocorrelation , 2020, NeuroImage.

[3]  Yumei Zhang,et al.  Low-Frequency Fluctuations Amplitude Signals Exhibit Abnormalities of Intrinsic Brain Activities and Reflect Cognitive Impairment in Leukoaraiosis Patients , 2019, Medical science monitor : international medical journal of experimental and clinical research.

[4]  M. Dichgans,et al.  Small vessel disease: mechanisms and clinical implications , 2019, The Lancet Neurology.

[5]  Hongyan Chen,et al.  Abnormal Interactions of the Salience Network, Central Executive Network, and Default-Mode Network in Patients With Different Cognitive Impairment Loads Caused by Leukoaraiosis , 2019, Front. Neural Circuits.

[6]  M. Keřkovský,et al.  Structural and functional MRI correlates of T2 hyperintensities of brain white matter in young neurologically asymptomatic adults , 2019, European Radiology.

[7]  Yumei Zhang,et al.  The Role of Disturbed Small-World Networks in Patients with White Matter Lesions and Cognitive Impairment Revealed by Resting State Function Magnetic Resonance Images (rs-fMRI) , 2019, Medical science monitor : international medical journal of experimental and clinical research.

[8]  Chuanming Li,et al.  Abnormal amplitude of low‐frequency fluctuations and functional connectivity of resting‐state functional magnetic resonance imaging in patients with leukoaraiosis , 2017, Brain and behavior.

[9]  Y. Bi,et al.  Resting-state functional magnetic resonance imaging in patients with leukoaraiosis-associated subcortical vascular cognitive impairment: a cross-sectional study , 2016, Neurological research.

[10]  H. Markus,et al.  Progression of MRI markers in cerebral small vessel disease: Sample size considerations for clinical trials , 2016, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[11]  Jian Wang,et al.  Abnormal intrinsic brain activity patterns in leukoaraiosis with and without cognitive impairment , 2015, Behavioural Brain Research.

[12]  Alexander Leemans,et al.  Decoupling of structural and functional brain connectivity in older adults with white matter hyperintensities , 2015, NeuroImage.

[13]  Christian Lambert,et al.  Characterising the grey matter correlates of leukoaraiosis in cerebral small vessel disease , 2015, NeuroImage: Clinical.

[14]  A. W. Chung,et al.  Structural network efficiency is associated with cognitive impairment in small-vessel disease , 2014, Neurology.

[15]  J. H. Lee,et al.  Cortical thickness and hippocampal shape in pure vascular mild cognitive impairment and dementia of subcortical type , 2014, European journal of neurology.

[16]  N. Toschi,et al.  The burden of microstructural damage modulates cortical activation in elderly subjects with MCI and leuko‐araiosis. A DTI and fMRI study , 2014, Human brain mapping.

[17]  Timothy O. Laumann,et al.  Methods to detect, characterize, and remove motion artifact in resting state fMRI , 2014, NeuroImage.

[18]  Nick C Fox,et al.  Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration , 2013, The Lancet Neurology.

[19]  R. Cameron Craddock,et al.  A comprehensive assessment of regional variation in the impact of head micromovements on functional connectomics , 2013, NeuroImage.

[20]  H. Markus,et al.  Mechanisms of Cognitive Impairment in Cerebral Small Vessel Disease: Multimodal MRI Results from the St George's Cognition and Neuroimaging in Stroke (SCANS) Study , 2013, PloS one.

[21]  Pengfei Xu,et al.  PANDA: a pipeline toolbox for analyzing brain diffusion images , 2013, Front. Hum. Neurosci..

[22]  Yong He,et al.  Structural and Functional Changes in Subcortical Vascular Mild Cognitive Impairment: A Combined Voxel-Based Morphometry and Resting-State fMRI Study , 2012, PloS one.

[23]  Bruce Fischl,et al.  FreeSurfer , 2012, NeuroImage.

[24]  M. Weiner,et al.  Cortical thinning related to periventricular and deep white matter hyperintensities , 2012, Neurobiology of Aging.

[25]  X. Ling,et al.  Abnormalities of magnetic resonance spectroscopy and diffusion tensor imaging are correlated with executive dysfunction in patients with ischemic leukoaraiosis , 2012, Journal of Clinical Neuroscience.

[26]  Sang Won Seo,et al.  Cortical Thinning in Vascular Mild Cognitive Impairment and Vascular Dementia of Subcortical Type , 2010, Journal of neuroimaging : official journal of the American Society of Neuroimaging.

[27]  Nikolaus Weiskopf,et al.  A comparison between voxel-based cortical thickness and voxel-based morphometry in normal aging , 2009, NeuroImage.

[28]  Keith A. Johnson,et al.  Cortical Hubs Revealed by Intrinsic Functional Connectivity: Mapping, Assessment of Stability, and Relation to Alzheimer's Disease , 2009, The Journal of Neuroscience.

[29]  Chaozhe Zhu,et al.  An improved approach to detection of amplitude of low-frequency fluctuation (ALFF) for resting-state fMRI: Fractional ALFF , 2008, Journal of Neuroscience Methods.

[30]  F. Howe,et al.  Diffusion tensor imaging and MR spectroscopy in hypertension and presumed cerebral small vessel disease , 2008, Magnetic resonance in medicine.

[31]  John Ashburner,et al.  A fast diffeomorphic image registration algorithm , 2007, NeuroImage.

[32]  Y. Zang,et al.  Altered baseline brain activity in children with ADHD revealed by resting-state functional MRI , 2007, Brain and Development.

[33]  Xiaohua Chen,et al.  Gray matter reduction is correlated with white matter hyperintensity volume: A voxel-based morphometric study in a large epidemiological sample , 2006, NeuroImage.

[34]  Leif Engqvist,et al.  The mistreatment of covariate interaction terms in linear model analyses of behavioural and evolutionary ecology studies , 2005, Animal Behaviour.

[35]  H. Kauczor,et al.  Intracerebral manifestation of an atypical monoclonal plasma cell hyperplasia depicted by MR perfusion and diffusion tensor imaging and MR spectroscopy. , 2005, AJR. American journal of roentgenology.

[36]  H. Christensen,et al.  White matter hyperintensities are related to physical disability and poor motor function , 2005, Journal of Neurology, Neurosurgery & Psychiatry.

[37]  H S Markus,et al.  Diffusion tensor MRI correlates with executive dysfunction in patients with ischaemic leukoaraiosis , 2004, Journal of Neurology, Neurosurgery & Psychiatry.

[38]  Derek K. Jones,et al.  Normal-appearing white matter in ischemic leukoaraiosis: A diffusion tensor MRI study , 2001, Neurology.

[39]  A M Dale,et al.  Measuring the thickness of the human cerebral cortex from magnetic resonance images. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[40]  A. Alavi,et al.  MR signal abnormalities at 1.5 T in Alzheimer's dementia and normal aging. , 1987, AJR. American journal of roentgenology.