Relationship Between Venules and Perivascular Spaces in Sporadic Small Vessel Diseases

Background and Purpose— Perivascular spaces (PVS) around venules may help drain interstitial fluid from the brain. We examined relationships between suspected venules and PVS visible on brain magnetic resonance imaging. Methods— We developed a visual venular quantification method to examine the spatial relationship between venules and PVS. We recruited patients with lacunar stroke or minor nondisabling ischemic stroke and performed brain magnetic resonance imaging and retinal imaging. We quantified venules on gradient echo or susceptibility-weighted imaging and PVS on T2-weighted magnetic resonance imaging in the centrum semiovale and then determined overlap between venules and PVS. We assessed associations between venular count and patient demographic characteristics, vascular risk factors, small vessel disease features, retinal vessels, and venous sinus pulsatility. Results— Among 67 patients (69% men, 69.0±9.8 years), only 4.6% (range, 0%–18%) of venules overlapped with PVS. Total venular count increased with total centrum semiovale PVS count in 55 patients after accounting for venule-PVS overlap (β=0.468 [95% CI, 0.187–0.750]) and transverse sinus pulsatility (β=0.547 [95% CI, 0.309–0.786]) and adjusting for age, sex, and systolic blood pressure. Conclusions— Despite increases in both visible PVS and suspected venules, we found minimal spatial overlap between them in patients with sporadic small vessel disease, suggesting that most magnetic resonance imaging-visible centrum semiovale PVS are periarteriolar rather than perivenular

Influence of threshold selection and image sequence in in-vivo segmentation of enlarged perivascular spaces

BACKGROUND: Growing interest surrounds perivascular spaces (PVS) as a clinical biomarker of brain dysfunction given their association with cerebrovascular risk factors and disease. Neuroimaging techniques allowing quick and reliable quantification are being developed, but, in practice, they require optimisation as their limits of validity are usually unspecified.NEW METHOD: We evaluate modifications and alternatives to a state-of-the-art (SOTA) PVS segmentation method that uses a vesselness filter to enhance PVS discrimination, followed by thresholding of its response, applied to brain magnetic resonance images (MRI) from patients with sporadic small vessel disease acquired at 3 T.RESULTS: The method is robust against inter-observer differences in threshold selection, but separate thresholds for each region of interest (i.e., basal ganglia, centrum semiovale, and midbrain) are required. Noise needs to be assessed prior to selecting these thresholds, as effect of noise and imaging artefacts can be mitigated with a careful optimisation of these thresholds. PVS segmentation from T1-weighted images alone, misses small PVS, therefore, underestimates PVS count, may overestimate individual PVS volume especially in the basal ganglia, and is susceptible to the inclusion of calcified vessels and mineral deposits. Visual analyses indicated the incomplete and fragmented detection of long and thin PVS as the primary cause of errors, with the Frangi filter coping better than the Jerman filter.COMPARISON WITH EXISTING METHODS: Limits of validity to a SOTA PVS segmentation method applied to 3 T MRI with confounding pathology are given.CONCLUSIONS: Evidence presented reinforces the STRIVE-2 recommendation of using T2-weighted images for PVS assessment wherever possible. The Frangi filter is recommended for PVS segmentation from MRI, offering robust output against variations in threshold selection and pathology presentation.</p

Rationale and design of a longitudinal study of cerebral small vessel diseases, clinical and imaging outcomes in patients presenting with mild ischaemic stroke: Mild Stroke Study 3

Background: Cerebral small vessel disease is a major cause of dementia and stroke, visible on brain magnetic resonance imaging. Recent data suggest that small vessel disease lesions may be dynamic, damage extends into normal-appearing brain and microvascular dysfunctions include abnormal blood–brain barrier leakage, vasoreactivity and pulsatility, but much remains unknown regarding underlying pathophysiology, symptoms, clinical features and risk factors of small vessel disease. Patients and Methods: The Mild Stroke Study 3 is a prospective observational cohort study to identify risk factors for and clinical implications of small vessel disease progression and regression among up to 300 adults with non-disabling stroke. We perform detailed serial clinical, cognitive, lifestyle, physiological, retinal and brain magnetic resonance imaging assessments over one year; we assess cerebrovascular reactivity, blood flow, pulsatility and blood–brain barrier leakage on magnetic resonance imaging at baseline; we follow up to four years by post and phone. The study is registered ISRCTN 12113543. Summary: Factors which influence direction and rate of change of small vessel disease lesions are poorly understood. We investigate the role of small vessel dysfunction using advanced serial neuroimaging in a deeply phenotyped cohort to increase understanding of the natural history of small vessel disease, identify those at highest risk of early disease progression or regression and uncover novel targets for small vessel disease prevention and therapy

Cerebrovascular Reactivity in Patients With Small Vessel Disease: A Cross-Sectional Study

BACKGROUND: Cerebrovascular reactivity (CVR) is inversely related to white matter hyperintensity severity, a marker of cerebral small vessel disease (SVD). Less is known about the relationship between CVR and other SVD imaging features or cognition. We aimed to investigate these cross-sectional relationships. METHODS: Between 2018 and 2021 in Edinburgh, we recruited patients presenting with lacunar or cortical ischemic stroke, whom we characterized for SVD features. We measured CVR in subcortical gray matter, normal-appearing white matter, and white matter hyperintensity using 3T magnetic resonance imaging. We assessed cognition using Montreal Cognitive Assessment. Statistical analyses included linear regression models with CVR as outcome, adjusted for age, sex, and vascular risk factors. We reported regression coefficients with 95% CIs. RESULTS: Of 208 patients, 182 had processable CVR data sets (median age, 68.2 years; 68% men). Although the strength of association depended on tissue type, lower CVR in normal-appearing tissues and white matter hyperintensity was associated with larger white matter hyperintensity volume (BNAWM=−0.0073 [95% CI, −0.0133 to −0.0014] %/mm Hg per 10-fold increase in percentage intracranial volume), more lacunes (BNAWM=−0.00129 [95% CI, −0.00215 to −0.00043] %/mm Hg per lacune), more microbleeds (BNAWM=−0.00083 [95% CI, −0.00130 to −0.00036] %/mm Hg per microbleed), higher deep atrophy score (BNAWM=−0.00218 [95% CI, −0.00417 to −0.00020] %/mm Hg per score point increase), higher perivascular space score (BNAWM=−0.0034 [95% CI, −0.0066 to −0.0002] %/mm Hg per score point increase in basal ganglia), and higher SVD score (BNAWM=−0.0048 [95% CI, −0.0075 to −0.0021] %/mm Hg per score point increase). Lower CVR in normal-appearing tissues was related to lower Montreal Cognitive Assessment without reaching convention statistical significance (BNAWM=0.00065 [95% CI, −0.00007 to 0.00137] %/mm Hg per score point increase). CONCLUSIONS: Lower CVR in patients with SVD was related to more severe SVD burden and worse cognition in this cross-sectional analysis. Longitudinal analysis will help determine whether lower CVR predicts worsening SVD severity or vice versa

A multi-disciplinary commentary on preclinical research to investigate vascular contributions to dementia

Although dementia research has been dominated by Alzheimer's disease (AD), most dementia in older people is now recognised to be due to mixed pathologies, usually combining vascular and AD brain pathology. Vascular cognitive impairment (VCI), which encompasses vascular dementia (VaD) is the second most common type of dementia. Models of VCI have been delayed by limited understanding of the underlying aetiology and pathogenesis. This review by a multidisciplinary, diverse (in terms of sex, geography and career stage), cross-institute team provides a perspective on limitations to current VCI models and recommendations for improving translation and reproducibility. We discuss reproducibility, clinical features of VCI and corresponding assessments in models, human pathology, bioinformatics approaches, and data sharing. We offer recommendations for future research, particularly focusing on small vessel disease as a main underpinning disorder

A Multi-disciplinary Commentary on Preclinical Research to investigate Vascular Contributions to Dementia

Although dementia research has been dominated by Alzheimer's disease (AD), most dementia in older people is now recognised to be due to mixed pathologies, usually combining vascular and AD brain pathology. Vascular cognitive impairment (VCI), which encompasses vascular dementia (VaD) is the second most common type of dementia. Models of VCI have been delayed by limited understanding of the underlying aetiology and pathogenesis. This review by a multidisciplinary, diverse (in terms of sex, geography and career stage), cross-institute team provides a perspective on limitations to current VCI models and recommendations for improving translation and reproducibility. We discuss reproducibility, clinical features of VCI and corresponding assessments in models, human pathology, bioinformatics approaches, and data sharing. We offer recommendations for future research, particularly focusing on small vessel disease as a main underpinning disorder.</p

Understanding the role of the perivascular space in cerebral small vessel disease

Small vessel diseases are a group of disorders that result from pathological alteration of the small blood vessels in the brain, including the small arteries, capillaries and veins. Of the 35-36 million people that are estimated to suffer from dementia worldwide, up to 65% have an SVD component. Furthermore, SVD causes 20-25% of strokes, worsens outcome after stroke and is a leading cause of disability, cognitive impairment and poor mobility. Yet the underlying cause(s) of SVD are not fully understood.Magnetic resonance imaging (MRI) has confirmed enlarged perivascular spaces (PVS) as a hallmark feature of SVD. In healthy tissue, these spaces are proposed to form part of a complex brain fluid drainage system which supports interstitial fluid exchange and may also facilitate clearance of waste products from the brain. The pathophysiological signature of PVS, and what this infers about their function and interaction with cerebral microcirculation, plus subsequent downstream effects on lesion development in the brain has not been established. Here we discuss the potential of enlarged PVS to be a unique biomarker for SVD and related brain disorders with a vascular component. We propose that widening of PVS suggests presence of peri-vascular cell debris and other waste products that forms part of a vicious cycle involving impaired cerebrovascular reactivity (CVR), blood-brain barrier (BBB) dysfunction, perivascular inflammation and ultimately impaired clearance of waste proteins from the interstitial fluid (ISF) space, leading to accumulation of toxins, hypoxia and tissue damage.Here, we outline current knowledge, questions and hypotheses regarding understanding the brain fluid dynamics underpinning dementia and stroke through the common denominator of SVD