Article

Debette S., Markus H.S. The clinical importance of white matter hyperintensities on brain magnetic resonance imaging: systematic review and meta-analysis. BMJ, 341, C3666

Clinical Neuroscience, St George's University of London, London.
BMJ (online) (Impact Factor: 17.45). 07/2010; 341(jul26 1):c3666. DOI: 10.1136/bmj.c3666
Source: PubMed

ABSTRACT

To review the evidence for an association of white matter hyperintensities with risk of stroke, cognitive decline, dementia, and death.
Systematic review and meta-analysis.
PubMed from 1966 to 23 November 2009.
Prospective longitudinal studies that used magnetic resonance imaging and assessed the impact of white matter hyperintensities on risk of incident stroke, cognitive decline, dementia, and death, and, for the meta-analysis, studies that provided risk estimates for a categorical measure of white matter hyperintensities, assessing the impact of these lesions on risk of stroke, dementia, and death.
Population studied, duration of follow-up, method used to measure white matter hyperintensities, definition of the outcome, and measure of the association of white matter hyperintensities with the outcome.
46 longitudinal studies evaluated the association of white matter hyperintensities with risk of stroke (n=12), cognitive decline (n=19), dementia (n=17), and death (n=10). 22 studies could be included in a meta-analysis (nine of stroke, nine of dementia, eight of death). White matter hyperintensities were associated with an increased risk of stroke (hazard ratio 3.3, 95% confidence interval 2.6 to 4.4), dementia (1.9, 1.3 to 2.8), and death (2.0, 1.6 to 2.7). An association of white matter hyperintensities with a faster decline in global cognitive performance, executive function, and processing speed was also suggested.
White matter hyperintensities predict an increased risk of stroke, dementia, and death. Therefore white matter hyperintensities indicate an increased risk of cerebrovascular events when identified as part of diagnostic investigations, and support their use as an intermediate marker in a research setting. Their discovery should prompt detailed screening for risk factors of stroke and dementia.

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    • "However, the pathological substrates associated with cognitive impairment or dementia in cerebrovascular disease remain poorly defined. White matter hyperintensities as seen on brain T 2 -weighted MRI have been linked to varying degrees of cognitive impairment (Debette and Markus, 2010). The prevalence and the volume of white matter hyperintensities increase exponentially with age (de Leeuw et al., 2001), and are associated with variable severity of executive dysfunction (DeCarli et al., 1995; Vataja et al., 2003; Bolandzadeh et al., 2012). "
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    ABSTRACT: White matter hyperintensities as seen on brain T2-weighted magnetic resonance imaging are associated with varying degrees of cognitive dysfunction in stroke, cerebral small vessel disease and dementia. The pathophysiological mechanisms within the white matter accounting for cognitive dysfunction remain unclear. With the hypothesis that gliovascular interactions are impaired in subjects with high burdens of white matter hyperintensities, we performed clinicopathological studies in post-stroke survivors, who had exhibited greater frontal white matter hyperintensities volumes that predicted shorter time to dementia onset. Histopathological methods were used to identify substrates in the white matter that would distinguish post-stroke demented from post-stroke non-demented subjects. We focused on the reactive cell marker glial fibrillary acidic protein (GFAP) to study the incidence and location of clasmatodendrosis, a morphological attribute of irreversibly injured astrocytes. In contrast to normal appearing GFAP+ astrocytes, clasmatodendrocytes were swollen and had vacuolated cell bodies. Other markers such as aldehyde dehydrogenase 1 family, member L1 (ALDH1L1) showed cytoplasmic disintegration of the astrocytes. Total GFAP+ cells in both the frontal and temporal white matter were not greater in post-stroke demented versus post-stroke non-demented subjects. However, the percentage of clasmatodendrocytes was increased by >2-fold in subjects with post-stroke demented compared to post-stroke non-demented subjects (P = 0.026) and by 11-fold in older controls versus young controls (P < 0.023) in the frontal white matter. High ratios of clasmotodendrocytes to total astrocytes in the frontal white matter were consistent with lower Mini-Mental State Examination and the revised Cambridge Cognition Examination scores in post-stroke demented subjects. Double immunofluorescent staining showed aberrant co-localization of aquaporin 4 (AQP4) in retracted GFAP+ astrocytes with disrupted end-feet juxtaposed to microvessels. To explore whether this was associated with the disrupted gliovascular interactions or blood-brain barrier damage, we assessed the co-localization of GFAP and AQP4 immunoreactivities in post-mortem brains from adult baboons with cerebral hypoperfusive injury, induced by occlusion of three major vessels supplying blood to the brain. Analysis of the frontal white matter in perfused brains from the animals surviving 1-28 days after occlusion revealed that the highest intensity of fibrinogen immunoreactivity was at 14 days. At this survival time point, we also noted strikingly similar redistribution of AQP4 and GFAP+ astrocytes transformed into clasmatodendrocytes. Our findings suggest novel associations between irreversible astrocyte injury and disruption of gliovascular interactions at the blood-brain barrier in the frontal white matter and cognitive impairment in elderly post-stroke survivors. We propose that clasmatodendrosis is another pathological substrate, linked to white matter hyperintensities and frontal white matter changes, which may contribute to post-stroke or small vessel disease dementia.
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    • "Frequently the ageing brain is characterised by areas of hyperintense signal known as white matter hyperintsities (WMH) seen in the WM on T2 weighted MRI scans, particularly using the Fluid Attenuation Inversion Recovery (FLAIR) sequence (Grueter and Schulz 2012; O&apos;Sullivan 2008). The WMH load is associated with age and a number of comorbities such as stroke and cognitive decline (Debette and Markus 2010). Ischemia is considered as a leading pathological feature of WMH (Fernando et al. 2006; O&apos;Sullivan 2008) and a reduction in perfusion during hypercapnic challenge has been shown within tissue with a high density of WM lesions in elderly subjects, suggesting a possible causative link between selective hypoxia in watershed zones and white matter damage (Mandell et al. 2008). "
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    ABSTRACT: In late age, the autonomic nervous system (ANS) has diminished ability to maintain physiological homeostasis in the brain in response to challenges such as to systemic blood pressure changes caused by standing. We devised an fMRI experiment aiming to map the cerebral effects of an ANS challenge (Valsalva manoeuvre (VM)). We used dual-echo fMRI to measure the effective transverse relaxation rate (R2*, which is inversely proportional to brain tissue oxygenation levels) in 45 elderly subjects (median age 80 years old, total range 75-89) during performance of the VM. In addition, we collected fluid-attenuated inversion recovery (FLAIR) data from which we quantified white matter hyperintensity (WMH) volumes. We conducted voxelwise analysis of the dynamic changes in R2* during the VM to determine the distribution of oxygenation changes due to the autonomic stressor. In white matter, we observed significant decreases in oxygenation levels. These effects were predominantly located in posterior white matter and to a lesser degree in the right anterior brain, both concentrated around the border zones (watersheds) between cerebral perfusion territories. These areas are known to be particularly vulnerable to hypoxia and are prone to formation of white matter hyperintensities. Although we observed overlap between localisation of WMH and triggered deoxygenation on the group level, we did not find significant association between these independent variables using subjectwise statistics. This could suggest other than recurrent transient hypoxia mechanisms causing/contributing to the formation of WMH.
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    • "Magnetic resonance (MR) imaging is by far the most sensitive imaging technique for detection of white-matter lesions (Rocca et al., 2013), a pathological presence of which is highly associated with the clinical outcome of certain neurodegenerative and mental disorders, and cerebrovascular diseases (Rovira et al., 2015; Debette and Markus, 2010; Prins and Scheltens, 2015). Quantification of the number, size and spatial distribution of the lesions, which are valuable biomarkers, requires accurate segmentation of three-dimensional MR images of several conventional sequences, like T1-weighted (T1w), T2-weighted (T2w), proton density weighted (PD), and fluid attenuated inversion recovery (FLAIR). "
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    ABSTRACT: Accurate characterization of white-matter lesions from magnetic resonance (MR) images has increasing importance for diagnosis and management of treatment of certain neurological diseases, and can be performed in an objective and effective way by automated lesion segmentation. This usually involves modeling the whole-brain MR intensity distribution, however, capturing various sources of MR intensity variability and lesion heterogeneity results in highly complex whole-brain MR intensity models, thus their robust estimation on a large set of MR images presents a huge challenge. We propose a novel approach employing stratified mixture modeling, where the main premise is that the otherwise complex whole-brain model can be reduced to a tractable parametric form in small brain subregions. We show on MR images of multiple sclerosis (MS) patients with different lesion loads that robust estimators enable accurate mixture modeling of MR intensity in small brain subregions even in the presence of lesions. Recombination of the mixture models across strata provided an accurate whole-brain MR intensity model. Increasing the number of subregions and, thereby, the model complexity, consistently improved the accuracy of whole-brain MR intensity modeling and segmentation of normal structures. The proposed approach was incorporated into three unsupervised lesion segmentation methods and, compared to original and other three state-of-the-art methods, the proposed modeling approach significantly improved lesion segmentation according to increased Dice similarity indices and lower number of false positives on real MR images of 30 patients with MS.
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