Predictors of Lesion Cavitation After Recent Small Subcortical Stroke
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C. Enzinger | F. Fazekas | J. Wardlaw | M. V. Valdés Hernández | F. Doubal | P. Armitage | F. Chappell | D. Pinter | S. Makin | A. Heye | T. Gattringer | C. Enzinger
[1] M E Bastin,et al. Temporal evolution of water diffusion parameters is different in grey and white matter in human ischaemic stroke , 2004, Journal of Neurology, Neurosurgery & Psychiatry.
[2] J. Wardlaw,et al. Blood-brain barrier failure as a core mechanism in cerebral small vessel disease and dementia: evidence from a cohort study , 2017, Alzheimer's & Dementia.
[3] C. Enzinger,et al. Serum neurofilament light is sensitive to active cerebral small vessel disease , 2017, Neurology.
[4] P. Sandercock,et al. Is Breakdown of the Blood-Brain Barrier Responsible for Lacunar Stroke, Leukoaraiosis, and Dementia? , 2003, Stroke.
[5] John D Pickard,et al. Increased Anisotropy in Acute Stroke: A Possible Explanation , 2002, Stroke.
[6] Francesca M Chappell,et al. Counting Cavitating Lacunes Underestimates the Burden of Lacunar Infarction , 2010, Stroke.
[7] S. Mori,et al. Principles of Diffusion Tensor Imaging and Its Applications to Basic Neuroscience Research , 2006, Neuron.
[8] A. Alavi,et al. MR signal abnormalities at 1.5 T in Alzheimer's dementia and normal aging. , 1987, AJR. American journal of roentgenology.
[9] L. Kappos,et al. Black holes in multiple sclerosis: definition, evolution, and clinical correlations , 2009, Acta neurologica Scandinavica.
[10] Hans Lassmann,et al. Inflammatory central nervous system demyelination: Correlation of magnetic resonance imaging findings with lesion pathology , 1997, Annals of neurology.
[11] C. Enzinger,et al. Longitudinal MRI dynamics of recent small subcortical infarcts and possible predictors , 2019, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.
[12] J. Wardlaw,et al. Cavitation of Deep Lacunar Infarcts in Patients With First-Ever Lacunar Stroke: A 2-Year Follow-Up Study With MR , 2012, Stroke.
[13] H. Markus,et al. Lacunar Infarcts, but Not Perivascular Spaces, Are Predictors of Cognitive Decline in Cerebral Small-Vessel Disease , 2018, Stroke.
[14] Joanna M. Wardlaw,et al. Blood–brain barrier: Ageing and microvascular disease – systematic review and meta-analysis , 2009, Neurobiology of Aging.
[15] Kirsten Shuler,et al. Blood–Brain Barrier Permeability and Long-Term Clinical and Imaging Outcomes in Cerebral Small Vessel Disease , 2013, Stroke.
[16] Eleni Sakka,et al. Blood pressure and sodium: Association with MRI markers in cerebral small vessel disease , 2016, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.
[17] S. Koch,et al. Imaging evolution of acute lacunar infarction , 2011, Neurology.
[18] H. An,et al. Signal Evolution and Infarction Risk for Apparent Diffusion Coefficient Lesions in Acute Ischemic Stroke Are Both Time- and Perfusion-Dependent , 2011, Stroke.
[19] M. Dichgans,et al. Mechanisms of sporadic cerebral small vessel disease: insights from neuroimaging , 2013, The Lancet Neurology.
[20] P. Koudstaal,et al. Silent brain infarcts: a systematic review , 2007, The Lancet Neurology.
[21] Joanna M. Wardlaw,et al. Tracer kinetic modelling for DCE-MRI quantification of subtle blood–brain barrier permeability , 2016, NeuroImage.
[22] J. Garcìa,et al. Incomplete infarct and delayed neuronal death after transient middle cerebral artery occlusion in rats. , 1997, Stroke.
[23] P. A. Armitage,et al. Development and initial testing of normal reference MR images for the brain at ages 65–70 and 75–80 years , 2008, European Radiology.
[24] M. L. Lauzon,et al. Cavitation After Acute Symptomatic Lacunar Stroke Depends on Time, Location, and MRI Sequence , 2012, Stroke.
[25] J. Wardlaw,et al. Cerebral Perivascular Spaces Visible on Magnetic Resonance Imaging: Development of a Qualitative Rating Scale and its Observer Reliability , 2015, Cerebrovascular Diseases.
[26] J. Wardlaw,et al. Long-Term Morphological Changes of Symptomatic Lacunar Infarcts and Surrounding White Matter on Structural Magnetic Resonance Imaging , 2018, Stroke.
[27] Arthur W. Toga,et al. Blood-Brain Barrier Breakdown in the Aging Human Hippocampus , 2015, Neuron.
[28] D. Altman,et al. STATISTICAL METHODS FOR ASSESSING AGREEMENT BETWEEN TWO METHODS OF CLINICAL MEASUREMENT , 1986, The Lancet.
[29] P. J. Hand,et al. MR diffusion-weighted imaging and outcome prediction after ischemic stroke , 2006, Neurology.
[30] J. Ryu,et al. Fibrinogen in neurological diseases: mechanisms, imaging and therapeutics , 2018, Nature Reviews Neuroscience.
[31] F. Barkhof,et al. Histopathologic correlate of hypointense lesions on T1-weighted spin-echo MRI in multiple sclerosis , 1998, Neurology.
[32] Eleni Sakka,et al. Integrity of normal-appearing white matter: Influence of age, visible lesion burden and hypertension in patients with small-vessel disease , 2017, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.
[33] J. Wardlaw,et al. Rationale, design and methodology of the image analysis protocol for studies of patients with cerebral small vessel disease and mild stroke , 2015, Brain and behavior.
[34] John R Hodges,et al. The Addenbrooke's Cognitive Examination Revised (ACE‐R): a brief cognitive test battery for dementia screening , 2006, International journal of geriatric psychiatry.
[35] Joanna M. Wardlaw,et al. Use of dynamic contrast-enhanced MRI to measure subtle blood–brain barrier abnormalities , 2011, Magnetic resonance imaging.
[36] C. Enzinger,et al. Predicting the severity of relapsing-remitting MS: The contribution of cross-sectional and short-term follow-up MRI data , 2011, Multiple sclerosis.
[37] Nick C Fox,et al. Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration , 2013, The Lancet Neurology.
[38] R. Agati,et al. Leukoaraiosis and dementia. , 1990, Stroke.
[39] Nasser H. Kashou,et al. Evaluation of Interpolation Effects on Upsampling and Accuracy of Cost Functions-Based Optimized Automatic Image Registration , 2013, Int. J. Biomed. Imaging.