Explore the vast range of titles available.

•Non-invasive mALPS-index was closely related to the classical detected glymphatic clearance function, providing an alternative method in researches on glymphatic system.•WMHs, lacunas, microbleeds and EPVS in basal ganglia were related to glymphatic clearance function.•Glymphatic clearance function was related to cognitive function in CSVD patients. Few studies have focused on the connection between glymphatic dysfunction and cerebral small vessel disease (CSVD), partially due to the lack of non-invasive methods to measure glymphatic function. We established modified index for diffusion tensor image analysis along the perivascular space (mALPS-index), which was calculated on diffusion tensor image (DTI), compared it with the classical detection of glymphatic clearance function calculated on Glymphatic MRI after intrathecal administration of gadolinium (study 1), and analyzed the relationship between CSVD imaging markers and mALPS-index in CSVD patients from the CIRCLE study (ClinicalTrials.gov ID: NCT03542734) (study 2). Among 39 patients included in study 1, mALPS-index were significantly related to glymphatic clearance function calculated on Glymphatic MRI ( r  = -0.772~-0.844, p < 0.001). A total of 330 CSVD patients were included in study 2. Severer periventricular and deep white matter hyperintensities (β = -0.332, p < 0.001; β = -0.293, p < 0.001), number of lacunas (β = -0.215, p < 0.001), number of microbleeds (β = -0.152, p = 0.005), and severer enlarged perivascular spaces in basal ganglia (β = -0.223, p < 0.001) were related to mALPS-index. Our results indicated that non-invasive mALPS-index might represent glymphatic clearance function, which could be applied in clinic in future. Glymphatic clearance function might play a role in the development of CSVD.

Recent interest in enlarged perivascular spaces (ePVS) in the brain, which can be visualized on MRI and appear isointense to cerebrospinal fluid on all sequence weightings, has resulted in the necessity of reliable algorithms for automated segmentation to allow for whole brain assessment of ePVS burden. However, several publicly available datasets do not contain sequences required for recently published algorithms. This prospective study presents a method for identification of enlarged perivascular spaces (ePVS) in white matter using 3T T1 and FLAIR MR imaging (MAPS-T1), making the algorithm accessible to groups with valuable sets of limited data. The approach was applied identically to two datasets: 1) a repeated measurement in a dementia-free aged human population (N = 14), and 2) an aged sample of multisite ADNI datasets (N = 30). ePVS segmentation was accomplished by a stepwise local homogeneity search of white matter-masked T1-weighted data, constrained by FLAIR hyperintensity, and further constrained by width, volume, and linearity measurements. Pearson’s r was employed for statistical testing between visual (gold standard) assessment and repeated measures in cohort one. Visual ePVS counts were significantly correlated with MAPS-T1 (r = .72, P < .0001). Correlations between repeated measurements in cohort one were significant for both visual and automated methods in the single visually-rated slice (MAPS-T1: r = .87, P < .0001, visual: (r = .86, P < .0001) and for whole brain assessment (MAPS-T1: r = .77, P = .001). Results from each cohort were manually inspected and found to have positive predictive values of 77.5% and 87.5%, respectively. The approach described in this report is an important tool for detailed assessment of ePVS burden in white matter on routinely acquired MRI sequences. •Enlarged perivascular spaces can be reliably segmented using only T1 and FLAIR MRI.•The positive predictive value of segmentation was 77 and 87% in two separate cohorts.•Perivascular spaces can be differentiated from lacunes and hyperintensities in WM.•Automated segmentation counts matched single slice visual ratings.•Automated segmentation counts were correlated across repeated measurements.

Perivascular spaces (PVS) are compartments surrounding cerebral blood vessels that become visible on MRI when enlarged. Enlarged PVS (EPVS) are commonly seen in patients with cerebral small vessel disease (CSVD) and have been suggested to reflect dysfunctional perivascular clearance of soluble waste products from the brain. In this study, we investigated histopathological correlates of EPVS and how they relate to vascular amyloid-β (Aβ) in cerebral amyloid angiopathy (CAA), a form of CSVD that commonly co-exists with Alzheimer’s disease (AD) pathology. We used ex vivo MRI, semi-automatic segmentation and validated deep-learning-based models to quantify EPVS and associated histopathological abnormalities. Severity of MRI-visible PVS during life was significantly associated with severity of MRI-visible PVS on ex vivo MRI in formalin fixed intact hemispheres and corresponded with PVS enlargement on histopathology in the same areas. EPVS were located mainly around the white matter portion of perforating cortical arterioles and their burden was associated with CAA severity in the overlying cortex. Furthermore, we observed markedly reduced smooth muscle cells and increased vascular Aβ accumulation, extending into the WM, in individually affected vessels with an EPVS. Overall, these findings are consistent with the notion that EPVS reflect impaired outward flow along arterioles and have implications for our understanding of perivascular clearance mechanisms, which play an important role in the pathophysiology of CAA and AD.

Enlarged perivascular spaces (PVS) are structural brain changes visible in MRI, are common in aging, and are considered a reflection of cerebral small vessel disease. As such, assessing the burden of PVS has promise as a brain imaging marker. Visual and manual scoring of PVS is a tedious and observer-dependent task. Automated methods would advance research into the etiology of PVS, could aid to assess what a “normal” burden is in aging, and could evaluate the potential of PVS as a biomarker of cerebral small vessel disease. In this work, we propose and evaluate an automated method to quantify PVS in the midbrain, hippocampi, basal ganglia and centrum semiovale. We also compare associations between (earlier established) determinants of PVS and visual PVS scores versus the automated PVS scores, to verify whether automated PVS scores could replace visual scoring of PVS in epidemiological and clinical studies. Our approach is a deep learning algorithm based on convolutional neural network regression, and is contingent on successful brain structure segmentation. In our work we used FreeSurfer segmentations. We trained and validated our method on T2-contrast MR images acquired from 2115 subjects participating in a population-based study. These scans were visually scored by an expert rater, who counted the number of PVS in each brain region. Agreement between visual and automated scores was found to be excellent for all four regions, with intraclass correlation coefficients (ICCs) between 0.75 and 0.88. These values were higher than the inter-observer agreement of visual scoring (ICCs between 0.62 and 0.80). Scan-rescan reproducibility was high (ICCs between 0.82 and 0.93). The association between 20 determinants of PVS, including aging, and the automated scores were similar to those between the same 20 determinants of PVS and visual scores. We conclude that this method may replace visual scoring and facilitate large epidemiological and clinical studies of PVS.

Background The glymphatic system is reportedly involved in Parkinson’s disease (PD). Based on previous studies, we aimed to confirm the correlation between the glymphatic system and PD progression by combining two imaging parameters, diffusion tensor image analysis along the perivascular space (DTI-ALPS), and enlarged perivascular spaces (EPVS). Methods Fifty-one PD patients and fifty healthy control (HC) were included. Based on the Hoehn-Yahr scale, the PD group was divided into early-stage and medium-to late-stage. All PD patients were scored using the Unified PD Rating Scale (UPDRS). We assessed the DTI-ALPS indices in the bilateral hemispheres and EPVS numbers in bilateral centrum semiovale (CSO), basal ganglia (BG), and midbrain. Results The DTI-ALPS indices were significantly lower bilaterally in PD patients than in the HC group, and EPVS numbers in any of the bilateral CSO, BG, and midbrain were significantly higher, especially for the medium- to late-stage group and the BG region. In PD patients, the DTI-ALPS index was significantly negatively correlated with age, while the BG-EPVS numbers were significantly positively correlated with age. Furthermore, the DTI-ALPS index was negatively correlated with UPDRS II and III scores, while the BG-EPVS numbers were positively correlated with UPDRS II and III scores. Similarly, the correlation was more pronounced in the medium- to late-stage group. Conclusion The DTI-ALPS index and EPVS numbers (especially in the BG region) are closely related to age and PD progression and can serve as non-invasive assessments for glymphatic dysfunction and its interventions in clinical studies.

Background: The aim of this study was to evaluate the glymphatic system activity in patients with Parkinson’s disease (PD) using the diffusion tensor image analysis along the perivascular space (DTI-ALPS) methods. Methods: In total, 71 patients with idiopathic PD and 36 age- and sex-matched normal controls (NCs) were involved. Patients with PD were divided into early ( n = 35) and late ( n = 36) subgroups, based on Hoehn and Yahr (HY) stages. We calculated the diffusivity along the perivascular spaces (ALPS), as well as projection fibers and association fibers separately, to acquire the ALPS index. Enlarged perivascular spaces (EPVS) and periventricular white matter hyperintensities were also rated. Differences in ALPS index between the PD group and NCs and between two PD subgroups and NCs were compared. In addition, a multivariate logistic regression analysis was conducted to investigate the association between ALPS index and clinical variables. Results: Patients with PD revealed lower ALPS index than NCs ( p = 0.010). The late PD group exhibited significantly lower ALPS index than NCs ( p = 0.006). However, there were no marked differences noticed in ALPS index between NCs and early PD group and between the two PD subgroups. In the early PD group, there was a significantly positive correlation between ALPS index and Mini-Mental State Examination (MMSE) score (β = 0.021, p = 0.029) and a negative correlation between ALPS index and EPVS score (β = −0.050, p = 0.034), after controlling for multiple variables. In the late PD group, ALPS index was inversely associated with age (β = −0.012, p = 0.004). Conclusion: Impairment of the glymphatic system is involved in PD. DTI-ALPS index could be a promising biomarker of glymphatic system in PD.

Background Perivascular spaces can become detectable on magnetic resonance imaging (MRI) upon enlargement, referred to as enlarged perivascular spaces (EPVS) or Virchow-Robin spaces. EPVS have been linked to small vessel disease. Some studies have also indicated an association of EPVS to neuroinflammation and/or neurodegeneration. However, there is conflicting evidence with regards to their potential as a clinically relevant imaging biomarker in multiple sclerosis (MS). Methods To perform a systematic review and meta-analysis of EPVS as visualized by MRI in MS. Nine out of 299 original studies addressing EPVS in humans using MRI were eligible for the systematic review and meta-analysis including a total of 457 MS patients and 352 control subjects. Results In MS, EPVS have been associated with cognitive decline, contrast-enhancing MRI lesions, and brain atrophy. Yet, these associations were not consistent between studies. The meta-analysis revealed that MS patients have greater EPVS prevalence (odds ratio = 4.61, 95% CI = [1.84; 11.60], p  = 0.001) as well as higher EPVS counts (standardized mean difference [SMD] = 0.46, 95% CI = [0.26; 0.67], p  < 0.001) and larger volumes (SMD = 0.88, 95% CI = [0.19; 1.56], p  = 0.01) compared to controls. Conclusions Available literature suggests a higher EPVS burden in MS patients compared to controls. The association of EPVS to neuroinflammatory or -degenerative pathology in MS remains inconsistent. Thus, there is currently insufficient evidence supporting EPVS as diagnostic and/or prognostic marker in MS. In order to benefit future comparisons of studies, we propose recommendations on EPVS assessment standardization in MS. PROSPERO No: CRD42019133946.

Perivascular spaces have been involved in neuroinflammatory and neurodegenerative diseases. Upon a certain size, these spaces can become visible on magnetic resonance imaging (MRI), referred to as enlarged perivascular spaces (EPVS) or MRI-visible perivascular spaces (MVPVS). However, the lack of systematic evidence on etiology and temporal dynamics of MVPVS hampers their diagnostic utility as MRI biomarker. Thus, the goal of this systematic review was to summarize potential etiologies and evolution of MVPVS. In a comprehensive literature search, out of 1,488 unique publications, 140 records assessing etiopathogenesis and dynamics of MVPVS were eligible for a qualitative summary. 6 records were included in a meta-analysis to assess the association between MVPVS and brain atrophy. Four overarching and partly overlapping etiologies of MVPVS have been proposed: (1) Impairment of interstitial fluid circulation, (2) Spiral elongation of arteries, (3) Brain atrophy and/or perivascular myelin loss, and (4) Immune cell accumulation in the perivascular space. The meta-analysis in patients with neuroinflammatory diseases did not support an association between MVPVS and brain volume measures [R: -0.15 (95%-CI -0.40-0.11)]. Based on few and mostly small studies in tumefactive MVPVS and in vascular and neuroinflammatory diseases, temporal evolution of MVPVS is slow. Collectively, this study provides high-grade evidence for MVPVS etiopathogenesis and temporal dynamics. Although several potential etiologies for MVPVS emergence have been proposed, they are only partially supported by data. Advanced MRI methods should be employed to further dissect etiopathogenesis and evolution of MVPVS. This can benefit their implementation as an imaging biomarker. https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=346564, identifier CRD42022346564.

Since the discovery of the glymphatic system in 2012, research on this brain-wide fluid exchange pathway has focused on understanding its role in different neurological diseases. Mild traumatic brain injury (mTBI) is a prevalent, yet often undiagnosed, condition that increases the risk of developing debilitating neurodegenerative diseases. mTBI may lead to impaired glymphatic system function and, therefore, accumulation of metabolic waste in the brain. In this review, we summarize 24 studies (10 rodent, 13 human, 1 both) published during 2013–2025, reporting post-mTBI changes in the glymphatic system. According to pre-clinical models, potential post-mTBI drivers of glymphatic dysfunction include depolarization of aquaporin 4 water channels and sleep deprivation. In studies on humans, evidence is contradictory; some studies show reduced post-mTBI glymphatic activity, while others report increased activity. However, these studies used different patient populations, which were likely exposed to different mTBI types and post-injury time frames. Furthermore, studies on humans used non-invasive imaging techniques, which only indirectly measure glymphatic activity. Taken together, these inconsistencies point to major gaps in the field, highlighting the need for standardized injury classification and post-injury time frames, and more direct measurements of glymphatic activity in humans. Notably, sleep deprivation, post-concussive symptoms, and cognitive impairment have often been linked to post-injury glymphatic dysfunction. Nevertheless, to better understand mTBI implications on glymphatic system functioning, further research is needed. Such research could help develop novel diagnostics or treatment strategies for mTBI and potentially mitigate the long-term risks of developing neurodegenerative disorders.

Background and Objectives: Myelin oligodendrocyte glycoprotein antibody‐associated disease (MOGAD) is an immune‐mediated inflammatory demyelinating disease of the central nervous system, with a complex relapse mechanism involving various factors. The connection between enlarged perivascular spaces (EPVSs) and MOGAD is currently unclear. This study is aimed at exploring the risk factors associated with an increased number of EPVS in MOGAD patients and the association with relapse. Methods: A retrospective study was conducted on 23 patients with MOGAD. We analyzed the correlation between the number of EPVS and age, disease duration, cerebrospinal fluid (CSF) leukocytes, CSF protein, EDSS scores, albumin quotient, and MOG‐IgG titer. We employed linear regression to assess the independent risk factors for the number of EPVS, and Cox regression was used to elucidate the independent factors associated with relapse. Results: The median total EPVS counts were 8 (IQR 4–9) at the initial brain MRI in patients with MOGAD. The number of total EPVS in patients with MOGAD was significantly positively correlated with CSF protein ( ρ = 0.42, p = 0.044), EDSS ( r = 0.74, p < 0.0001), QAlb ( ρ = 0.48, p = 0.022), serum MOG‐IgG titer ( ρ = 0.48, p = 0.019), and CSF MOG‐IgG titer ( ρ = 0.46, p = 0.029). Univariate linear regression analysis indicated that CSF protein ( β = 0.45, p = 0.03), EDSS scores ( β = 0.6, p = 0.002), serum MOG‐IgG titer ( β = 0.51, p = 0.014), and CSF anti‐MOG‐IgG titer ( β = 0.64, p = 0.001) were independent factors associated with EPVS counts. EDSS scores ( β = 0.49, p = 0.002) and CSF MOG‐IgG titer ( β = 0.54, p = 0.001) were independent predictors associated with EPVS count in the multivariable linear regression model. Multivariable Cox regression analysis showed that the total number of EPVS was the only variable that revealed a significant effect on relapse (HR = 1.22, 95% CI 1.01–1.47, p = 0.04). Conclusion: In our cohort, we preliminary explored independent risk factors for increased EPVS. Moreover, EPVS might independently predict the risk of relapse in patients with MOGAD.