Virchow-Robin Spaces: Correlations with Polysomnography-Derived Sleep Parameters

Berezuk, Courtney; Ramirez, Joel; Gao, Fuqiang; Scott, Christopher J.; Huroy, Menal; Swartz, Richard H.; Murray, Brian J.; Black, Sandra E.; Boulos, Mark I.

doi:10.5665/sleep.4726

Cited by 72 publications

(92 citation statements)

References 27 publications

(32 reference statements)

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“…This association may occur through the interaction between sleep disorders, cardiovascular risk factors, and depression. Although not fully elucidated, there is a growing body of evidence suggesting that sleep is crucial for the removal of neurotoxic byproducts (Berezuk, et al, 2015,Lucey and Bateman, 2014,Sanchez-Espinosa, et al, 2014,Spira, et al, 2013,Sprecher, et al, 2015,Xie, et al, 2013). However, poor sleep (reduced, fragmented, with apneas) leads to metabolic and cardiovascular dysfunction (Mesas, et al, 2014,Mullington, et al, 2009,Roux, et al, 2000,Strand, et al, 2015), which are also associated with imaging (Goldstein, et al, 2002,Kharabian Masouleh, et al, 2016,Kumar, et al, 2015,Langbaum, et al, 2012,Moran, et al, 2015,Peng, et al, 2015,Soininen, et al, 1992,Villeneuve, et al, 2014) and neuropathological (Gelber, et al, 2015) findings of neurodegeneration, to which depression may also contribute (Elcombe, et al, 2015).…”

Section: Discussionmentioning

confidence: 99%

Excessive daytime sleepiness and fatigue may indicate accelerated brain aging in cognitively normal late middle-aged and older adults

et al. 2017

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Excessive daytime sleepiness (EDS) and fatigue increases with age. The aim of this study was to investigate the association between EDS and fatigue with cortical thickness and hippocampal volume in cognitively normal, late middle-aged and older adults. We performed a cross-sectional observational study of 1374 cognitively-normal subjects aged 50 years and older who had a structural MRI. Regional cortical thickness and hippocampal volume were measured. Multiple linear regression models were fit to explore associations between EDS and fatigue and structural MRI measures in different brain regions, adjusting for multiple covariates. EDS was defined as Epworth Sleepiness Scale ≥10. Fatigue severity was assessed with the Beck Depression Inventory-2. 208 participants had EDS, 27 had significant fatigue, and 11 had both. Participants with EDS or fatigue had significantly lower cognitive scores, more disturbed sleep, and medical comorbidities. The presence of EDS was associated with both global and regional atrophy, whereas fatigue was more associated with frontal and temporal changes. Cortical thinning predicted by EDS and fatigue was maximal in the temporal region with average reduction of 34.2 µm (95% CI, −54.1, −14.3; P=.001) and 90.2 µm (95% CI, −142.1, −38.2; P=.001), respectively. Fatigue was also associated with hippocampal volume reduction of −374.2 mm3 (95%CI, −670.8, −77.7; P=.013). Temporal cortical thinning predicted by presence of EDS and fatigue was equivalent to more than 3.5 and nine additional years of aging, respectively. EDS and fatigue were associated with cortical thickness reduction primarily in regions with increased age-susceptibility, which may indicate accelerated brain aging.

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Section: Discussionmentioning

confidence: 99%

Excessive daytime sleepiness and fatigue may indicate accelerated brain aging in cognitively normal late middle-aged and older adults

et al. 2017

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“…It may provide important insight into the pathophysiology of disease to understand the age dependent changes of PVS morphology within the white matter and also characterize its possible abnormality in Alzheimer’s disease and mild cognitive impairment. In our future work, instead of using the white-matter ROI, we will also segment the PVSs in whole brain, which may have broader clinical applications in intracerebral haemorrhage [41], Alzheimer’s disease [42], stroke [43], general elderly population analysis [44], and sleep [45]. …”

Section: Parameter Analysis and Discussionmentioning

confidence: 99%

Structured Learning for 3-D Perivascular Space Segmentation Using Vascular Features

Zhang

Gao

Park

et al. 2017

IEEE Trans. Biomed. Eng.

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Objective The goal of this paper is to automatically segment perivascular spaces (PVSs) in brain from high-resolution 7T MR images. Methods We propose a structured-learning-based segmentation framework to extract the PVSs from high-resolution 7T MR images. Specifically, we integrate three types of vascular filter responses into a structured random forest for classifying voxels into two categories, i.e., PVS and background. In addition, we propose a novel entropy-based sampling strategy to extract informative samples in the background for training an explicit classification model. Since the vascular filters can extract various vascular features, even thin and low-contrast structures can be effectively extracted from noisy backgrounds. Moreover, continuous and smooth segmentation results can be obtained by utilizing patch-based structured labels. Results The performance of our proposed method is evaluated on 19 subjects with 7T MR images, with the Dice similarity coefficient reaching 66%. Conclusion The joint use of entropy-based sampling strategy, vascular features, and structured learning can improve the segmentation accuracy. Significance Instead of manual annotation, our method provides an automatic way for PVS segmentation. Moreover, our method can be potentially used for other vascular structure segmentation because of its data-driven property.

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“…Sleep disturbances have been associated with WML burden(119–121). Subsequently, the presence of EPVS, negatively correlate with sleep efficiency(122). EPVS volume, especially in the basal ganglia, tends to be larger as duration of non-rapid eye movement stage 3 sleep decreases (122).…”

Section: Targeting Glymphatics For Treatment and Prevention Of Svdmentioning

confidence: 99%

“…Subsequently, the presence of EPVS, negatively correlate with sleep efficiency(122). EPVS volume, especially in the basal ganglia, tends to be larger as duration of non-rapid eye movement stage 3 sleep decreases (122). All these findings are particularly interesting considering the strong connection between sleep and glymphatic system function.…”

Section: Targeting Glymphatics For Treatment and Prevention Of Svdmentioning

confidence: 99%

Perivascular spaces, glymphatic dysfunction, and small vessel disease

2017

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Cerebral small vessel diseases (SVD) range broadly in etiology but share a remarkably overlapping pathology. Features of SVD including enlarged perivascular spaces and formation of abluminal protein deposits cannot be completely explained by the putative pathophysiology. The recently discovered glymphatic system provides a new perspective to potentially address these gaps. This work provides a comprehensive review of the known factors that regulate glymphatic function and the disease mechanisms underlying glymphatic impairment emphasizing the role that aquaporin-4 (AQP4)-lined perivascular spaces, cerebrovascular pulsatility, and metabolite clearance play in normal CNS physiology. This review also discusses the implications that glymphatic impairment may have on SVD inception and progression with the aim of exploring novel therapeutic targets and highlighting the key questions that remain to be answered.

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Virchow-Robin Spaces: Correlations with Polysomnography-Derived Sleep Parameters

Abstract: These preliminary results suggest that sleep may play a role in perivascular clearance in ischemic brain disease, and invite future research into the potential relevance of Virchow-Robin spaces as an imaging biomarker for nocturnal metabolite clearance.

Cited by 72 publications

References 27 publications

Excessive daytime sleepiness and fatigue may indicate accelerated brain aging in cognitively normal late middle-aged and older adults

Excessive daytime sleepiness and fatigue may indicate accelerated brain aging in cognitively normal late middle-aged and older adults

Structured Learning for 3-D Perivascular Space Segmentation Using Vascular Features

Perivascular spaces, glymphatic dysfunction, and small vessel disease

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