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Zou K, Deng Q, Zhang H, Huang C. Glymphatic system: a gateway for neuroinflammation. Neural Regen Res 2024; 19:2661-2672. [PMID: 38595285 PMCID: PMC11168510 DOI: 10.4103/1673-5374.391312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 09/15/2023] [Accepted: 11/09/2023] [Indexed: 04/11/2024] Open
Abstract
The glymphatic system is a relatively recently identified fluid exchange and transport system in the brain. Accumulating evidence indicates that glymphatic function is impaired not only in central nervous system disorders but also in systemic diseases. Systemic diseases can trigger the inflammatory responses in the central nervous system, occasionally leading to sustained inflammation and functional disturbance of the central nervous system. This review summarizes the current knowledge on the association between glymphatic dysfunction and central nervous system inflammation. In addition, we discuss the hypothesis that disease conditions initially associated with peripheral inflammation overwhelm the performance of the glymphatic system, thereby triggering central nervous system dysfunction, chronic neuroinflammation, and neurodegeneration. Future research investigating the role of the glymphatic system in neuroinflammation may offer innovative therapeutic approaches for central nervous system disorders.
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Affiliation(s)
- Kailu Zou
- Department of Anesthesiology, Xiangya Hospital, Central South University, Changsha, Hunan Province, China
| | - Qingwei Deng
- Department of Anesthesiology, Xiangya Hospital, Central South University, Changsha, Hunan Province, China
| | - Hong Zhang
- Xiangya School of Medicine, Central South University, Changsha, Hunan Province, China
| | - Changsheng Huang
- Department of Anesthesiology, Xiangya Hospital, Central South University, Changsha, Hunan Province, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan Province, China
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2
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Bayoumi A, Hasan KM, Thomas JA, Yazdani A, Lincoln JA. Glymphatic dysfunction in multiple sclerosis and its association with disease pathology and disability. Mult Scler 2024; 30:1609-1619. [PMID: 39344166 DOI: 10.1177/13524585241280842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/01/2024]
Abstract
BACKGROUND The role of the glymphatic system in multiple sclerosis (MS)-related disability remains underexplored. Diffusion-tensor image analysis along the perivascular space (DTI-ALPS) offers a non-invasive method to assess glymphatic function. OBJECTIVE To evaluate glymphatic function in MS patients with lower and higher disability. METHODS This study included 118 MS patients who underwent structural, diffusion-weighted imaging, and clinical assessment. The participants were divided into lower (MS-L, n = 57) and higher disability (MS-H, n = 61) subgroups. Brain parenchymal fraction (BPF), lesion load (LL), and DTI-ALPS index were measured. Subgroup differences and correlations between DTI-ALPS index and other measures were explored. Logistic regression was performed to evaluate BPF, LL, and DTI-ALPS index in classifying lower and higher disability patients. RESULTS Significant differences in DTI-ALPS index between MS-H and MS-L (d = -0.71, false discovery rate-corrected p-value (p-FDR) = 0.001) were found. The DTI-ALPS index correlated significantly with disease duration (rp = -0.29, p-FDR = 0.002) and EDSS (rsp = -0.35, p-FDR = 0.0002). It also showed significant correlations with BPF and LL. DTI-ALPS index and LL were significant predictors of disability subgroup (DTI-ALPS: odds ratio (OR) = 1.77, p = 0.04, LL: OR = 0.94, p = 0.02). CONCLUSION Our findings highlight DTI-ALPS index as an imaging biomarker in MS, suggesting the involvement of glymphatic impairment in MS pathology, although further research is needed to elucidate its role in contributing to MS-related disability.
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Affiliation(s)
- Ahmed Bayoumi
- Department of Neurology, McGovern Medical School at UTHealth Houston, Houston, TX, USA
| | - Khader M Hasan
- Department of Diagnostic and Interventional Imaging, McGovern Medical School at UTHealth Houston, Houston, TX, USA
| | - Joseph A Thomas
- Department of Neurology, McGovern Medical School at UTHealth Houston, Houston, TX, USA
| | - Akram Yazdani
- Department of Clinical and Translational Sciences, McGovern Medical School at UTHealth Houston, Houston, TX, USA
| | - John A Lincoln
- Department of Neurology, McGovern Medical School at UTHealth Houston, Houston, TX, USA
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3
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Borrelli S, Leclercq S, Pasi M, Maggi P. Cerebral small vessel disease and glymphatic system dysfunction in multiple sclerosis: A narrative review. Mult Scler Relat Disord 2024; 91:105878. [PMID: 39276600 DOI: 10.1016/j.msard.2024.105878] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2024] [Revised: 09/03/2024] [Accepted: 09/04/2024] [Indexed: 09/17/2024]
Abstract
As the multiple sclerosis (MS) population ages, the prevalence of vascular comorbidities increases, potentially accelerating disease progression and brain atrophy. Recent studies highlight the prevalence of cerebral small vessel disease (CSVD) in MS, suggesting a potential link between vascular comorbidities and accelerated disability. CSVD affects the brain's small vessels, often leading to identifiable markers on MRI such as enlarged perivascular spaces (EPVS). EPVS are increasingly recognized also in MS and have been associated with vascular comorbidities, lower percentage of MS-specific perivenular lesions, brain atrophy and aging. The exact sequence of event leading to MRI visible EPVS is yet to be determined, but an impaired perivascular brain fluid drainage appears a possible physiopathological explanation for EPVS in both CSVD and MS. In this context, a dysfunction of the brain fluid clearance system - also known as "glymphatic system" - appears associated in MS to aging, neuroinflammation, and vascular dysfunction. Advanced imaging techniques show an impaired glymphatic function in both MS and CSVD. Additionally, lifestyle factors such as physical exercise, diet, and sleep quality appear to influence glymphatic function, potentially revealing novel therapeutic strategies to mitigate microangiopathy and neuroinflammation in MS. This review underscores the potential role of glymphatic dysfunction in the complex and not-yet elucidated interplay between neuroinflammation and CSVD in MS.
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Affiliation(s)
- Serena Borrelli
- Neuroinflammation Imaging Lab (NIL), Institute of NeuroScience, Université catholique de Louvain, Brussels, Belgium; Department of Neurology, Hôpital Erasme, Hôpital Universitaire de Bruxelles, Université Libre de Brussels, Brussels, Belgium.
| | - Sophie Leclercq
- Laboratory of Nutritional Psychiatry, Institute of NeuroScience, Université catholique de Louvain, Brussels, Belgium
| | - Marco Pasi
- Stroke Unit, Department of Neurology, CIC-IT 1415, CHRU de Tours, INSERM 1253 iBrain, Tours, France
| | - Pietro Maggi
- Neuroinflammation Imaging Lab (NIL), Institute of NeuroScience, Université catholique de Louvain, Brussels, Belgium; Department of Neurology, Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Av. Hippocrate 10, Brussels 1200, Belgium.
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4
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Hashemi E, Srivastava IN, Aguirre A, Yoseph ET, Kaushal E, Awani A, Ryu JK, Akassoglou K, Talebian S, Chu P, Pisani L, Musolino P, Steinman L, Doyle K, Robinson WH, Sharpe O, Cayrol R, Orchard PJ, Lund T, Vogel H, Lenail M, Han MH, Bonkowsky JL, Van Haren KP. A Novel Mouse Model for Cerebral Inflammatory Demyelination in X-Linked Adrenoleukodystrophy: Insights into Pathogenesis and Potential Therapeutic Targets. Ann Neurol 2024. [PMID: 39467011 DOI: 10.1002/ana.27117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Revised: 10/04/2024] [Accepted: 10/04/2024] [Indexed: 10/30/2024]
Abstract
OBJECTIVE X-linked adrenoleukodystrophy (ALD) is caused by mutations in ABCD1, a peroxisomal gene. More than half of males with an ABCD1 mutation develop inflammatory cerebral demyelination (cALD), but underlying mechanisms remain unknown and therapies are limited. We sought to develop and characterize a mouse model of cALD to facilitate study of disease mechanisms and therapy development. METHODS We used immunoassays and immunohistochemistry to assess novel (interleukin 18 [IL-18]) and established molecular markers in cerebrospinal fluid (CSF) and postmortem brain tissue from cALD patients. We generated a cALD phenotype in Abcd1-knockout mice using a 2-hit method that combines cuprizone and experimental autoimmune encephalomyelitis models. We then used magnetic resonance imaging (MRI) and immunohistochemistry to assess the fidelity of cALD molecular markers in the mice. RESULTS Human and mouse cALD lesions shared histologic features of myelin phagocytosis, myelin loss, abundant microglial activation, T and B-cell infiltration, and astrogliosis. Compared to wild-type controls, Abcd1-knockout mice displayed more cerebral demyelination, blood-brain barrier disruption, and perivascular immune cell infiltration. This enhanced inflammatory response was associated with higher levels of fibrin deposition, oxidative stress, demyelination, and axonal injury. IL-18 immunoreactivity co-localized with perivascular monocytes/macrophages in both human and mouse brain tissue. In cALD patients, CSF IL-18 levels correlated with MRI lesion severity. INTERPRETATION Our results suggest loss of Abcd1 function in mice predisposes to more severe blood-brain barrier disruption, cerebral inflammation driven by the infiltration of peripheral immune cells, demyelination, and axonal damage, replicating human cALD features. This novel mouse model could shed light on cALD mechanisms and accelerate cALD therapy development. ANN NEUROL 2024.
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Affiliation(s)
- Ezzat Hashemi
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA
| | - Isha N Srivastava
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA
| | - Alejandro Aguirre
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA
| | - Ezra T Yoseph
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA
| | - Esha Kaushal
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA
| | - Avni Awani
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA
| | - Jae K Ryu
- Gladstone Institute for Neurological Disease, San Francisco, CA
- Center for Neurovascular Brain Immunology at Gladstone and UCSF, San Francisco, CA
- Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA
| | - Katerina Akassoglou
- Gladstone Institute for Neurological Disease, San Francisco, CA
- Center for Neurovascular Brain Immunology at Gladstone and UCSF, San Francisco, CA
- Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA
| | - Shahrzad Talebian
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA
| | - Pauline Chu
- Stanford Human Research Histology Core, Stanford University School of Medicine, Stanford, CA
| | - Laura Pisani
- Department of Radiology, Stanford University School of Medicine Stanford, Stanford, CA
| | - Patricia Musolino
- Department of Neurology, Massachusetts General Hospital, Boston, MA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
| | - Lawrence Steinman
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA
| | - Kristian Doyle
- Department of Immunobiology, University of Arizona, Tucson, AZ
| | - William H Robinson
- Department of Immunology and Rheumatology, Stanford University School of Medicine, Stanford, CA
| | - Orr Sharpe
- Department of Immunology and Rheumatology, Stanford University School of Medicine, Stanford, CA
| | - Romain Cayrol
- Department of Pathology, Clinical Department of Laboratory Medicine, University of Montreal, Quebec, Canada
| | - Paul J Orchard
- Division of Pediatric Blood and Marrow Transplantation, University of Minnesota, Minneapolis, MN
| | - Troy Lund
- Division of Pediatric Blood and Marrow Transplantation, University of Minnesota, Minneapolis, MN
| | - Hannes Vogel
- Department of Pathology, Stanford University School of Medicine, Stanford, CA
| | - Max Lenail
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA
| | - May H Han
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA
| | - Joshua L Bonkowsky
- Division of Pediatric Neurology, Department of Pediatrics, University of Utah School of Medicine, Salt Lake City, UT
- Brain and Spine Center, Primary Children's Hospital, Salt Lake City, UT
- Primary Children's Center for Personalized Medicine, Salt Lake City, UT
| | - Keith P Van Haren
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA
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Morozova A, Španiel F, Škoch A, Brabec M, Zolotarov G, Musil V, Zach P. Enlarged brain perivascular spaces correlate with blood plasma osmolality in the healthy population: A longitudinal study. Neuroimage 2024; 300:120871. [PMID: 39341473 DOI: 10.1016/j.neuroimage.2024.120871] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2024] [Revised: 09/19/2024] [Accepted: 09/25/2024] [Indexed: 10/01/2024] Open
Abstract
Enlarged perivascular spaces (EPVS) are increasingly recognized as an MRI detectable feature of neuroinflammatory processes and age-related neurodegenerative changes. Understanding perivascular characteristics in healthy individuals is crucial for their applicability as a reference for pathological changes. Limited data exists on the EPVS load and interhemispheric asymmetry in distribution among young healthy subjects. Despite the known impact of hydration on brain morphometric studies, blood plasma osmolality's effect on EPVS remains unexplored. This study investigated the influence of age, total intracranial volume (TIV), and blood plasma osmolality on EPVS characteristics in 59 healthy adults, each undergoing MRI and osmolality assessment twice within 14.8 months (mean ± 4 months). EPVS analysis was conducted in the centrum semiovale using high-resolution automated segmentation, followed by an optimization algorithm to enhance EPVS segmentation accuracy. Linear Mixed Effects model was used for the statistical analysis, which unveiled significant inter-individual variability in EPVS load and inter-hemispheric asymmetry. EPVS volume increased with age, higher TIV and lower blood plasma osmolality levels. Our findings offer valuable insights into EPVS characteristics among the healthy population, establishing a foundation to further explore age-related and pathological changes.
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Affiliation(s)
- Alexandra Morozova
- Department of Anatomy, Third Faculty of Medicine, Charles University, Prague, Czechia; National Institute of Mental Health, Klecany, Czechia.
| | - Filip Španiel
- National Institute of Mental Health, Klecany, Czechia
| | - Antonín Škoch
- National Institute of Mental Health, Klecany, Czechia
| | - Marek Brabec
- Department of Statistical Modeling, Institute of Computer Science, Academy of Sciences of the Czech Republic, Prague, Czechia
| | - Grygoriy Zolotarov
- Centre for Genomic Regulation, Barcelona Institute of Science and Technology, Barcelona, Spain; Pompeu Fabra University, Barcelona, Spain
| | - Vladimir Musil
- Centre of Scientific Information, Third Faculty of Medicine, Charles University, Prague, Czechia
| | - Petr Zach
- Department of Anatomy, Third Faculty of Medicine, Charles University, Prague, Czechia; National Institute of Mental Health, Klecany, Czechia
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6
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Rauch M, Lachner K, Frickel L, Lauer M, Adenauer SJ, Neuhaus E, Hattingen E, Porto L. Focally Enlarged Perivascular Spaces in Pediatric and Adolescent Patients with Polymicrogyria-an MRI Study. Clin Neuroradiol 2024:10.1007/s00062-024-01457-5. [PMID: 39269662 DOI: 10.1007/s00062-024-01457-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2024] [Accepted: 08/21/2024] [Indexed: 09/15/2024]
Abstract
PURPOSE Polymicrogyria (PMG) is a cortical malformation frequently associated with epilepsy. Our aim was to investigate the frequency and conspicuity of enlarged perivascular spaces (EPVS) underneath dysplastic cortex as a potentially underrecognized feature of PMG in pediatric and adolescent patients undergoing clinical magnetic resonance imaging (MRI). METHODS We analyzed data from 28 pediatric and adolescent patients with PMG and a matched control group, ranging in age from 2 days to 21 years, who underwent MRI at 1.5T or 3T. T2-weighted MR images were examined for the presence of EPVS underneath the dysplastic cortex. The quantity of EPVS was graded from 0 to 4 (0: none, 1: < 10, 2: 11-20, 3: 21-40, 4: > 40 EPVS). We then compared the presence and quantity of EPVS to the matched controls in terms of total EPVS scores, and EPVS scores underneath the dysplastsic cortex depending on the age groups, the localization of PMG, and the MRI field strength. RESULTS In 23/28 (82%) PMG patients, EPVS spatially related to the dysplastic cortex were identified. EPVS scores were significantly higher in PMG patients compared to controls, independent from age or PMG location. No significant differences were observed in EPVS scores in patients examined at 1.5T compared to those examined at 3T. CONCLUSION EPVS underneath the dysplastic cortex were identified in 82% of patients. EPVS may serve as an important clue for PMG and a marker for cortical malformation.
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Affiliation(s)
- Maximilian Rauch
- Institute for Neuroradiology, Johann Wolfgang Goethe-University, Theodor Stern Kai 7, 60590, Frankfurt am Main, Germany.
| | - Karsten Lachner
- Institute for Neuroradiology, Johann Wolfgang Goethe-University, Theodor Stern Kai 7, 60590, Frankfurt am Main, Germany
| | - Lea Frickel
- Institute for Neuroradiology, Johann Wolfgang Goethe-University, Theodor Stern Kai 7, 60590, Frankfurt am Main, Germany
| | - Monika Lauer
- Institute for Neuroradiology, Johann Wolfgang Goethe-University, Theodor Stern Kai 7, 60590, Frankfurt am Main, Germany
| | - Simon Jonas Adenauer
- Department of Radiology, Helios Klinikum Bonn/Rhein-Sieg, Von-Hompesch-Straße 1, 53123, Bonn, Germany
| | - Elisabeth Neuhaus
- Institute for Neuroradiology, Johann Wolfgang Goethe-University, Theodor Stern Kai 7, 60590, Frankfurt am Main, Germany
| | - Elke Hattingen
- Institute for Neuroradiology, Johann Wolfgang Goethe-University, Theodor Stern Kai 7, 60590, Frankfurt am Main, Germany
| | - Luciana Porto
- Institute for Neuroradiology, Johann Wolfgang Goethe-University, Theodor Stern Kai 7, 60590, Frankfurt am Main, Germany
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Yamamoto EA, Koike S, Wong C, Dennis LE, Luther MN, Scatena A, Khambadkone S, Iliff JJ, Lim MM, Levendovszky SR, Elliott JE, Barisano G, Müller-Oehring EM, Morales AM, Baker FC, Nagel BJ, Piantino J. Biological sex and BMI influence the longitudinal evolution of adolescent and young adult MRI-visible perivascular spaces. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.17.608337. [PMID: 39229241 PMCID: PMC11370374 DOI: 10.1101/2024.08.17.608337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2024]
Abstract
Background and Purpose An association recently emerged between magnetic resonance imaging (MRI)-visible perivascular spaces (MV-PVS) with intracerebral solute clearance and neuroinflammation, in adults. However, it is unknown how MV-PVS change throughout adolescence and what factors influence MV-PVS volume and morphology. This study assesses the temporal evolution of MV-PVS volume in adolescents and young adults, and secondarily evaluates the relationship between MV-PVS, age, sex, and body mass index (BMI). Materials and Methods This analysis included a 783 participant cohort from the longitudinal multicenter National Consortium on Alcohol and Neurodevelopment in Adolescence study that involved up to 6 imaging visits spanning 5 years. Healthy adolescents aged 12-21 years at study entry with at least two MRI scans were included. The primary outcome was mean MV-PVS volume (mm 3 /white matter cm 3 ). Results On average, males had greater MV-PVS volume at all ages compared to females. A linear mixed-effect model for MV-PVS volume was performed. Mean BMI and increases in a person's BMI were associated with increases in MV-PVS volume over time. In females only, changes in BMI correlated with MV-PVS volume. One unit increase in BMI above a person's average BMI was associated with a 0.021 mm 3 /cm 3 increase in MV-PVS volume (p<0.001). Conclusion This longitudinal study showed sex differences in MV-PVS features during adolescence and young adulthood. Importantly, we report that increases in BMI from a person's mean BMI are associated with increases in MV-PVS volume in females only. These findings suggest a potential link between MV-PVS, sex, and BMI that warrants future study.
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8
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Liu L, Tu L, Shen Q, Bao Y, Xu F, Zhang D, Xu Y. Meta-analysis of the relationship between the number and location of perivascular spaces in the brain and cognitive function. Neurol Sci 2024; 45:3743-3755. [PMID: 38459400 DOI: 10.1007/s10072-024-07438-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Accepted: 03/01/2024] [Indexed: 03/10/2024]
Abstract
BACKGROUND Cerebral perivascular spaces are part of the cerebral microvascular structure and play a role in lymphatic drainage and the removal of waste products from the brain. Relationships of the number and location of such spaces with cognition are unclear. OBJECTIVE To meta-analyze available data on potential associations of severity and location of perivascular spaces with cognitive performance. METHODS We searched PubMed, EMBASE, Web of Science and the Cochrane Central Registry of Controlled Trials for relevant studies published between January 2000 and July 2023. Performance on different cognitive domains was compared to the severity of perivascular spaces in different brain regions using comprehensive meta-analysis. When studies report unadjusted and adjusted means, we use adjusted means for meta-analysis. The study protocol is registered in the PROSPERO database (CRD42023443460). RESULTS We meta-analyzed data from 26 cross-sectional studies and two longitudinal studies involving 7908 participants. In most studies perivascular spaces was using a visual rating scale. A higher number of basal ganglia perivascular spaces was linked to lower general intelligence and attention. Moreover, increased centrum semiovale perivascular spaces were associated with worse general intelligence, executive function, language, and memory. Conversely, higher hippocampus perivascular spaces were associated with enhanced memory and executive function. Subgroup analyses revealed variations in associations among different disease conditions. CONCLUSIONS A higher quantity of perivascular spaces in the brain is correlated with impaired cognitive function. The location of these perivascular spaces and the underlying disease conditions may influence the specific cognitive domains that are affected. SYSTEMATIC REVIEW REGISTRATION The study protocol has been registered in the PROSPERO database (CRD42023443460).
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Affiliation(s)
- Ling Liu
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Liangdan Tu
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Qiuyan Shen
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yi Bao
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Fang Xu
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Dan Zhang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yanming Xu
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
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9
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Zhu Z, Zhang Y, Li C, Guo W, Chen Z, Chen W, Li S, Wang N, Chen X, Fu Y. Paramagnetic rim lesions as a biomarker to discriminate between multiple sclerosis and cerebral small vessel disease. Front Neurol 2024; 15:1429698. [PMID: 39081339 PMCID: PMC11286476 DOI: 10.3389/fneur.2024.1429698] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2024] [Accepted: 07/01/2024] [Indexed: 08/02/2024] Open
Abstract
Background Multiple sclerosis (MS) and Cerebral Small Vessel Disease (CSVD) exhibit some similarities in Magnetic resonance imaging (MRI), potentially leading to misdiagnosis and delaying effective treatment windows. It is unclear whether CSVD can be detected with Paramagnetic Rim Lesions (PRL), which is special in MS. Objective We aimed to investigate whether PRL can serve as a neuroimaging marker for discriminating between MS and CSVD. Methods In this retrospective study, 49 MS and 104 CSVD patients underwent 3.0 T Magnetic resonance imaging (MRI). Visual assessment of 37 MS patients and 89 CSVD patients with or without lacunes, cerebral microbleeds (CMBs), enlarged perivascular spaces (EPVS), white matter hyperintensity (WMH), central vein sign (CVS), and PRL. The distribution and number of PRL were then counted. Results Our study found that PRL was detected in over half of the MS patients but was entirely absent in CSVD patients (78.38 vs. 0%, p < 0.0001), and PRL showed high specificity with good sensitivity in discriminating between MS and CSVD (sensitivity: 78.38%, specificity: 100%, AUC: 0.96). Conclusion Paramagnetic Rim Lesions is a special imaging feature in MS, absent in CSVD. Detection of PRL can be very helpful in the clinical management of MS and CSVD.
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Affiliation(s)
- Zhibao Zhu
- Department of Neurology, Fujian Medical University Union Hospital, Fuzhou, Fujian, China
- Department of Neurology, Fujian Institute of Neurology, The First Affiliated Hospital, Fujian Medical University, Fuzhou, Fujian, China
- Fujian Key Laboratory of Molecular Neurology, Institute of Neuroscience, Fujian Medical University, Fuzhou, Fujian, China
- Department of Neurology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China
| | - Yuanyuan Zhang
- Department of Neurology, Fujian Institute of Neurology, The First Affiliated Hospital, Fujian Medical University, Fuzhou, Fujian, China
- Fujian Key Laboratory of Molecular Neurology, Institute of Neuroscience, Fujian Medical University, Fuzhou, Fujian, China
- Department of Neurology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China
| | - Chun Li
- Department of Neurology, Fujian Institute of Neurology, The First Affiliated Hospital, Fujian Medical University, Fuzhou, Fujian, China
- Fujian Key Laboratory of Molecular Neurology, Institute of Neuroscience, Fujian Medical University, Fuzhou, Fujian, China
- Department of Neurology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China
| | - Wenliang Guo
- Department of Neurology, Fujian Institute of Neurology, The First Affiliated Hospital, Fujian Medical University, Fuzhou, Fujian, China
- Fujian Key Laboratory of Molecular Neurology, Institute of Neuroscience, Fujian Medical University, Fuzhou, Fujian, China
| | - Zhili Chen
- Department of Neurology, Fujian Institute of Neurology, The First Affiliated Hospital, Fujian Medical University, Fuzhou, Fujian, China
- Fujian Key Laboratory of Molecular Neurology, Institute of Neuroscience, Fujian Medical University, Fuzhou, Fujian, China
- Department of Neurology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China
| | - Wei Chen
- Department of Neurology, Fujian Institute of Neurology, The First Affiliated Hospital, Fujian Medical University, Fuzhou, Fujian, China
- Fujian Key Laboratory of Molecular Neurology, Institute of Neuroscience, Fujian Medical University, Fuzhou, Fujian, China
- Department of Neurology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China
| | - Shaowu Li
- Department of Neurology, China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Ning Wang
- Department of Neurology, Fujian Institute of Neurology, The First Affiliated Hospital, Fujian Medical University, Fuzhou, Fujian, China
- Fujian Key Laboratory of Molecular Neurology, Institute of Neuroscience, Fujian Medical University, Fuzhou, Fujian, China
- Department of Neurology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China
| | - Xiaochun Chen
- Department of Neurology, Fujian Medical University Union Hospital, Fuzhou, Fujian, China
- Fujian Key Laboratory of Molecular Neurology, Institute of Neuroscience, Fujian Medical University, Fuzhou, Fujian, China
| | - Ying Fu
- Department of Neurology, Fujian Institute of Neurology, The First Affiliated Hospital, Fujian Medical University, Fuzhou, Fujian, China
- Fujian Key Laboratory of Molecular Neurology, Institute of Neuroscience, Fujian Medical University, Fuzhou, Fujian, China
- Department of Neurology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China
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Borrelli S, Guisset F, Vanden Bulcke C, Stölting A, Bugli C, Lolli V, Du Pasquier R, van Pesch V, Absinta M, Pasi M, Maggi P. Enlarged perivascular spaces are associated with brain microangiopathy and aging in multiple sclerosis. Mult Scler 2024; 30:983-993. [PMID: 38850029 DOI: 10.1177/13524585241256881] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/09/2024]
Abstract
BACKGROUND Growing evidence links brain-MRI enlarged perivascular spaces (EPVS) and multiple sclerosis (MS), but their role remains unclear. OBJECTIVE This study aimed to investigate the cross-sectional associations of EPVS with several neuroinflammatory and neurodegenerative features in a large multicentric-MS cohort. METHODS In total, 207 patients underwent 3T axial-T2-weighted brain-MRI for EPVS assessment (EPVS dichotomized into high/low according to ⩾ 2/< 2 rating categories). MRI biomarkers included brain-predicted age and brain-predicted age difference (brain-PAD), central vein sign (CVS)-positive lesion percentage (CVS%), paramagnetic rim and cortical lesions, T2-lesion load, and brain volumetry. The variable relative importance for EPVS-category prediction was explored using a classification random forest approach. RESULTS High EPVS patients were older (49 vs 44 years, p = 0.003), had ⩾ 1 vascular risk factors (VRFs; p = 0.005), lower CVS% (67% vs 78%, p < 0.001), reduced brain volumes (whole brain: 0.63 vs 0.73, p = 0.01; gray matter: 0.36 vs 0.40; p = 0.002), and older brain-predicted age (58 vs 50 years, p < 0.001). No differences were found for neuroinflammatory markers. After adjusting for age and VFRs (multivariate analyses), the high EPVS category correlated with lower CVS% (odds ratio (OR) = 0.98, 95% confidence interval (CI) = 0.96-0.99; p = 0.02), lower whole brain (OR = 0.01, 95% CI = 0.0003-0.5; p = 0.02), gray matter (OR = 0.0004, 95% CI = 0.0000004-0.4; p = 0.03) volumes, and higher brain-PAD (OR = 1.05, 95% CI = 1.01-1.09; p = 0.02). Random forest identified brain-PAD as the most important predictor of high EPVS. CONCLUSION EPVS in MS likely reflect microangiopathic disease rather than neuroinflammation, potentially contributing to accelerated neurodegeneration.
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Affiliation(s)
- Serena Borrelli
- Neuroinflammation Imaging Lab (NIL), Institute of NeuroScience, Université catholique de Louvain, Brussels, Belgium/Department of Neurology, Hôpital Erasme, Hôpital Universitaire de Bruxelles, Université Libre de Brussels, Brussels, Belgium
| | - François Guisset
- Neuroinflammation Imaging Lab (NIL), Institute of NeuroScience, Université catholique de Louvain, Brussels, Belgium
| | - Colin Vanden Bulcke
- Neuroinflammation Imaging Lab (NIL), Institute of NeuroScience, Université catholique de Louvain, Brussels, Belgium/ICTEAM Institute, Université catholique de Louvain, Louvain-la-Neuve, Belgium
| | - Anna Stölting
- Neuroinflammation Imaging Lab (NIL), Institute of NeuroScience, Université catholique de Louvain, Brussels, Belgium
| | - Céline Bugli
- Plateforme technologique de Support en Méthodologie et Calcul Statistique, Université catholique de Louvain, Brussels, Belgium
| | - Valentina Lolli
- Department of Radiology, Hôpital Erasme, Hôpital Universitaire de Bruxelles, Université Libre de Brussels, Brussels, Belgium
| | - Renaud Du Pasquier
- Neurology Service, Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland
| | - Vincent van Pesch
- Department of Neurology, Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium
| | - Martina Absinta
- Vita-Salute San Raffaele University, Milan, Italy/Translational Neuropathology Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy/Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Marco Pasi
- Stroke Unit, Department of Neurology, CIC-IT 1415, CHRU de Tours, INSERM 1253 iBrain, Tours, France
| | - Pietro Maggi
- Neuroinflammation Imaging Lab (NIL), Institute of NeuroScience, Université catholique de Louvain, Brussels, Belgium/Neurology Service, Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland/Department of Neurology, Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium
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11
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Caporale AS, Chiarelli AM, Biondetti E, Villani A, Lipp I, Di Censo D, Tomassini V, Wise RG. Changes of brain parenchyma free water fraction reflect tissue damage and impaired processing speed in multiple sclerosis. Hum Brain Mapp 2024; 45:e26761. [PMID: 38895882 PMCID: PMC11187860 DOI: 10.1002/hbm.26761] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 05/13/2024] [Accepted: 06/02/2024] [Indexed: 06/21/2024] Open
Abstract
Free water fraction (FWF) represents the amount of water per unit volume of brain parenchyma, which is not bound to macromolecules. Its excess in multiple sclerosis (MS) is related to increased tissue loss. The use of mcDESPOT (multicomponent driven single pulse observation of T1 and T2), a 3D imaging method which exploits both the T1 and T2 contrasts, allows FWF to be derived in clinically feasible times. However, this method has not been used to quantify changes of FWF and their potential clinical impact in MS. The aim of this study is to investigate the changes in FWF in MS patients and their relationship with tissue damage and cognition, under the hypothesis that FWF is a proxy of clinically meaningful tissue loss. To this aim, we tested the relationship between FWF, MS lesion burden and information processing speed, evaluated via the Symbol Digit Modalities Test (SDMT). In addition to standard sequences, used for T1- and T2-weighted lesion delineation, the mcDESPOT sequence with 1.7 mm isotropic resolution and a diffusion weighted imaging protocol (b = 0, 1200 s/mm2, 40 diffusion directions) were employed at 3 T. The fractional anisotropy map derived from diffusion data was used to define a subject-specific white matter (WM) atlas. Brain parenchyma segmentation returned masks of gray matter (GM) and WM, and normal-appearing WM (NAWM), in addition to the T1 and T2 lesion masks (T1L and T2L, respectively). Ninety-nine relapsing-remitting MS patients (age = 43.3 ± 9.9 years, disease duration 12.3 ± 7.7 years) were studied, together with twenty-five healthy controls (HC, age = 38.8 ± 11.0 years). FWF was higher in GM and NAWM of MS patients, compared to GM and WM of HC (both p < .001). In MS patients, FWF was the highest in the T1L and GM, followed by T2L and NAWM, respectively. FWF increased significantly with T1L and T2L volume (ρ ranging from 0.40 to 0.58, p < .001). FWF in T2L was strongly related to both T1L volume and the volume ratio T1L/T2L (ρ = 0.73, p < .001). MS patients performed worse than HC in the processing speed test (mean ± SD: 54.1 ± 10.3 for MS, 63.8 ± 10.8 for HC). FWF in GM, T2L, perilesional tissue and NAWM increased with SDMT score reduction (ρ = -0.30, -0.29, -0.33 respectively and r = -.30 for T2L, all with p < .005). A regional analysis, conducted to determine which NAWM regions were of particular importance to explain the relationship between FWF and cognitive impairment, revealed that FWF spatial variance was negatively related to SDMT score in the corpus callosum and the superior longitudinal fasciculus, WM structures known to be associated with cognitive impairment, in addition to the left corticospinal tract, the sagittal stratum, the right anterior limb of internal capsule. In conclusion, we found excess free water in brain parenchyma of MS patients, an alteration that involved not only MS lesions, but also the GM and NAWM, impinging on brain function and negatively associated with cognitive processing speed. We suggest that the FWF metric, derived from noninvasive, rapid MRI acquisitions and bearing good biological interpretability, may prove valuable as an MRI biomarker of tissue damage and associated cognitive impairment in MS.
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Affiliation(s)
- Alessandra Stella Caporale
- Department of Neuroscience, Imaging and Clinical Sciences‘G. d'Annunzio University’ of Chieti‐PescaraChietiItaly
- Institute for Advanced Biomedical Technologies (ITAB)‘G. d'Annunzio University’ of Chieti‐PescaraChietiItaly
| | - Antonio Maria Chiarelli
- Department of Neuroscience, Imaging and Clinical Sciences‘G. d'Annunzio University’ of Chieti‐PescaraChietiItaly
- Institute for Advanced Biomedical Technologies (ITAB)‘G. d'Annunzio University’ of Chieti‐PescaraChietiItaly
| | - Emma Biondetti
- Department of Neuroscience, Imaging and Clinical Sciences‘G. d'Annunzio University’ of Chieti‐PescaraChietiItaly
- Institute for Advanced Biomedical Technologies (ITAB)‘G. d'Annunzio University’ of Chieti‐PescaraChietiItaly
| | - Alessandro Villani
- Department of Neuroscience, Imaging and Clinical Sciences‘G. d'Annunzio University’ of Chieti‐PescaraChietiItaly
- Institute for Advanced Biomedical Technologies (ITAB)‘G. d'Annunzio University’ of Chieti‐PescaraChietiItaly
| | - Ilona Lipp
- Department of NeurophysicsMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Davide Di Censo
- Department of Neuroscience, Imaging and Clinical Sciences‘G. d'Annunzio University’ of Chieti‐PescaraChietiItaly
- Institute for Advanced Biomedical Technologies (ITAB)‘G. d'Annunzio University’ of Chieti‐PescaraChietiItaly
| | - Valentina Tomassini
- Department of Neuroscience, Imaging and Clinical Sciences‘G. d'Annunzio University’ of Chieti‐PescaraChietiItaly
- Institute for Advanced Biomedical Technologies (ITAB)‘G. d'Annunzio University’ of Chieti‐PescaraChietiItaly
- MS Centre, Department of Clinical Neurology‘SS. Annunziata’ University HospitalChietiItaly
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of PsychologyCardiff UniversityCardiffUK
| | - Richard Geoffrey Wise
- Department of Neuroscience, Imaging and Clinical Sciences‘G. d'Annunzio University’ of Chieti‐PescaraChietiItaly
- Institute for Advanced Biomedical Technologies (ITAB)‘G. d'Annunzio University’ of Chieti‐PescaraChietiItaly
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of PsychologyCardiff UniversityCardiffUK
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12
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Cai Y, Zhang Y, Leng S, Ma Y, Jiang Q, Wen Q, Ju S, Hu J. The relationship between inflammation, impaired glymphatic system, and neurodegenerative disorders: A vicious cycle. Neurobiol Dis 2024; 192:106426. [PMID: 38331353 DOI: 10.1016/j.nbd.2024.106426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2023] [Revised: 01/16/2024] [Accepted: 01/28/2024] [Indexed: 02/10/2024] Open
Abstract
The term "glymphatic" emerged roughly a decade ago, marking a pivotal point in neuroscience research. The glymphatic system, a glial-dependent perivascular network distributed throughout the brain, has since become a focal point of investigation. There is increasing evidence suggesting that impairment of the glymphatic system appears to be a common feature of neurodegenerative disorders, and this impairment exacerbates as disease progression. Nevertheless, the common factors contributing to glymphatic system dysfunction across most neurodegenerative disorders remain unclear. Inflammation, however, is suspected to play a pivotal role. Dysfunction of the glymphatic system can lead to a significant accumulation of protein and waste products, which can trigger inflammation. The interaction between the glymphatic system and inflammation appears to be cyclical and potentially synergistic. Yet, current research is limited, and there is a lack of comprehensive models explaining this association. In this perspective review, we propose a novel model suggesting that inflammation, impaired glymphatic function, and neurodegenerative disorders interconnected in a vicious cycle. By presenting experimental evidence from the existing literature, we aim to demonstrate that: (1) inflammation aggravates glymphatic system dysfunction, (2) the impaired glymphatic system exacerbated neurodegenerative disorders progression, (3) neurodegenerative disorders progression promotes inflammation. Finally, the implication of proposed model is discussed.
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Affiliation(s)
- Yu Cai
- Nurturing Center of Jiangsu Province for State Laboratory of AI Imaging & Interventional Radiology, Department of Radiology, Zhongda Hospital, Medical School of Southeast University, Nanjing 210009, China
| | - Yangqiqi Zhang
- School of Medicine, Southeast University, Nanjing 210009, China
| | - Shuo Leng
- Center of Interventional Radiology and Vascular Surgery, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, 87 Dingjiaqiao Road, Nanjing 210009, China
| | - Yuanyuan Ma
- Nurturing Center of Jiangsu Province for State Laboratory of AI Imaging & Interventional Radiology, Department of Radiology, Zhongda Hospital, Medical School of Southeast University, Nanjing 210009, China
| | - Quan Jiang
- Department of Neurology, Henry Ford Health System, 2799 W Grand Blvd, Detroit, MI 48202, USA
| | - Qiuting Wen
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 355 W.16th Street, Indianapolis, IN 46202-5188, USA
| | - Shenghong Ju
- Nurturing Center of Jiangsu Province for State Laboratory of AI Imaging & Interventional Radiology, Department of Radiology, Zhongda Hospital, Medical School of Southeast University, Nanjing 210009, China.
| | - Jiani Hu
- Department of Radiology, School of Medicine, Wayne State University, Detroit, MI 48201, USA.
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13
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Alghanimy A, Work LM, Holmes WM. The glymphatic system and multiple sclerosis: An evolving connection. Mult Scler Relat Disord 2024; 83:105456. [PMID: 38266608 DOI: 10.1016/j.msard.2024.105456] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2024] [Accepted: 01/18/2024] [Indexed: 01/26/2024]
Abstract
Multiple sclerosis (MS) is a complex autoimmune disorder that affects the central nervous system, resulting in demyelination and an array of neurological manifestations. Recently, there has been significant scientific interest in the glymphatic system, which operates as a waste-clearance system for the brain. This article reviews the existing literature, and explores potential links between the glymphatic system and MS, shedding light on its evolving significance in the context of MS pathogenesis. The authors consider the pathophysiological implications of glymphatic dysfunction in MS, the impact of disrupted sleep on glymphatic function, and the bidirectional relationship between MS and sleep disturbances. By offering an understanding of the intricate interplay between the glymphatic system and MS, this review provides valuable insights which may lead to improved diagnostic techniques and more effective therapeutic interventions.
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Affiliation(s)
- Alaa Alghanimy
- School of Psychology and Neuroscience, College of Medicine, Veterinary and Life Science, University of Glasgow, Glasgow G61 1QH, United Kingdom; Radiological Sciences Department, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia.
| | - Lorraine M Work
- School of Cardiovascular and Metabolic Health, College of Medicine, Veterinary and Life Science, University of Glasgow, Glasgow G12 8TA, United Kingdom
| | - William M Holmes
- School of Psychology and Neuroscience, College of Medicine, Veterinary and Life Science, University of Glasgow, Glasgow G61 1QH, United Kingdom
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14
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Bateman GA, Bateman AR. A perspective on the evidence for glymphatic obstruction in spaceflight associated neuro-ocular syndrome and fatigue. NPJ Microgravity 2024; 10:23. [PMID: 38418508 PMCID: PMC10901896 DOI: 10.1038/s41526-024-00365-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Accepted: 02/12/2024] [Indexed: 03/01/2024] Open
Abstract
Spaceflight associated neuro-ocular syndrome (SANS) alters the vision of astronauts during long-duration spaceflights. Previously, the current authors have discussed the similarities and differences between SANS and idiopathic intracranial hypertension to try to elucidate a possible pathophysiology. Recently, a theory has been advanced that SANS may occur secondary to failure of the glymphatic system caused by venous dilatation within the brain and optic nerves. There is recent evidence to suggest glymphatic obstruction occurs in childhood hydrocephalus, multiple sclerosis and syringomyelia due to venous outflow dilatation similar to that proposed in SANS. The purpose of the current paper is to discuss the similarities and differences between the known CSF and venous pathophysiology in SANS with these other terrestrial diseases, to see if they can shed any further light on the underlying cause of this microgravity-induced disease.
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Affiliation(s)
- Grant Alexander Bateman
- Department of Medical Imaging, John Hunter Hospital, Newcastle, NSW, Australia.
- Newcastle University Faculty of Health, Callaghan Campus, Newcastle, NSW, Australia.
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15
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Gueye M, Preziosa P, Ramirez GA, Bozzolo EP, Canti V, Margoni M, Meani A, Moiola L, Rovere-Querini P, Manfredi AA, Filippi M, Rocca MA. Choroid plexus and perivascular space enlargement in neuropsychiatric systemic lupus erythematosus. Mol Psychiatry 2024; 29:359-368. [PMID: 38036603 DOI: 10.1038/s41380-023-02332-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Revised: 11/08/2023] [Accepted: 11/15/2023] [Indexed: 12/02/2023]
Abstract
Choroid plexus (CP) enlargement is proposed as a marker of neuroinflammation in immune-mediated conditions. CP involvement has also been hypothesized in the immunopathology of systemic lupus erythematosus (SLE). We investigated whether CP enlargement occurs in SLE patients and its association with neuropsychiatric involvement. Additionally, we explored abnormalities along the glymphatic system in SLE patients through enlarged perivascular space (PVS) quantification. Clinical assessment and 3 Tesla brain dual-echo and T1-weighted MRI scans were obtained from 32 SLE patients and 32 sex and age-matched healthy controls (HC). CPs were manually segmented on 3D T1-weighted sequence and enlarged PVS (ePVS) were assessed through Potter's score. Compared to HC, SLE patients showed higher normalized CP volume (nCPV) (p = 0.023), with higher CP enlargement in neuropsychiatric SLE (NPSLE) (n = 12) vs. non-NPSLE (p = 0.027) patients. SLE patients with antiphospholipid antibodies (APA) positivity (n = 18) had higher nCPV compared to HC (p = 0.012), while APA negative ones did not. SLE patients also had higher Potter's score than HC (p < 0.001), with a tendency towards a higher number of basal ganglia ePVS in NPSLE vs. non-NPSLE patients. Using a random forest analysis, nCPV emerged as a significant predictor of NPSLE, together with T2-hyperintense white matter (WM) lesion volume (LV) and APA positivity (out-of-bag AUC 0.81). Our findings support the hypothesis of a role exerted by the CP in SLE physiopathology, especially in patients with neuropsychiatric involvement. The higher prevalence of ePVS in SLE patients, compared to HC, suggests the presence of glymphatic system impairment in this population.
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Affiliation(s)
- Mor Gueye
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Paolo Preziosa
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Giuseppe A Ramirez
- Unit of Immunology, Rheumatology, Allergy and Rare Diseases & Division of Immunology, Transplantation and Infectious Diseases, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Enrica P Bozzolo
- Unit of General Medicine and Advanced Care, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Valentina Canti
- Unit of Internal Medicine & Division of Immunology, Transplantation and Infectious diseases, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Monica Margoni
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Alessandro Meani
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Lucia Moiola
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Patrizia Rovere-Querini
- Vita-Salute San Raffaele University, Milan, Italy
- Unit of Internal Medicine & Division of Immunology, Transplantation and Infectious diseases, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Angelo A Manfredi
- Vita-Salute San Raffaele University, Milan, Italy
- Unit of Immunology, Rheumatology, Allergy and Rare Diseases & Division of Immunology, Transplantation and Infectious Diseases, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
- Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.
- Vita-Salute San Raffaele University, Milan, Italy.
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16
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Cohen I, Hoffmann C, Barash Y, Lekach R, Ben-Zeev B, Zohar-Dayan E, Shrot S. Assessment of glymphatic dysfunction in pediatric idiopathic intracranial hypertension: insights from quantitative diffusivity and perivascular spaces analysis-a case-control study. Quant Imaging Med Surg 2024; 14:653-661. [PMID: 38223125 PMCID: PMC10784093 DOI: 10.21037/qims-23-1043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2023] [Accepted: 11/21/2023] [Indexed: 01/16/2024]
Abstract
Background The impaired drainage of cerebrospinal fluid through the glymphatic system is thought to play a role in the idiopathic intracranial hypertension (IIH) pathophysiology. Limited data exist regarding the glymphatic system's involvement in pediatric patients with IIH. Therefore, the study's objective was to quantitatively evaluate alterations in parenchymal diffusivity and magnetic resonance imaging (MRI)-visible dilated perivascular spaces (PVS) as imaging indicators of glymphatic dysfunction in pediatric patients with IIH. Methods Patients diagnosed with IIH in 2017-2022 in a single tertiary center (Sheba Medical Center, Israel) were retrospectively reviewed. Twenty-four pediatric patients were enrolled. All patients underwent clinical 3-T brain MRI. The control group included 24 age- and gender-matched healthy subjects with a normal-appearing brain on imaging. We used automatic atlas-based diffusion-weighted imaging analysis to determine regional diffusivity of the thalamus, caudate, putamen, globus pallidus, hippocampus, amygdala, and brain stem. PVS were evaluated using a semi-quantitative rating scale on T2-weighted images. Variables were compared using the Mann-Whitney test. Multivariate analysis of covariance was used to test for differences between controls and IIH patients. Results No significant differences in regional brain diffusivity were observed between individuals with IIH and healthy controls (P=0.14-0.91 for various brain regions). The number of visible PVS was comparable between patients with IIH and the control group across all evaluated sites (P=0.12-0.74 for various brain regions). Conclusions Pediatric IIH patients exhibited similar patterns of parenchymal diffusivity and PVS compared to age-matched controls. These findings do not support the hypothesis that the glymphatic system may play a role in the pathophysiology of pediatric IIH, although previously postulated. However, employing more sophisticated magnetic resonance (MR) techniques could enhance the sensitivity in uncovering underlying glymphatic dysfunction. Further research is warranted to validate and explore this association in larger cohorts and investigate the underlying mechanisms involved in IIH.
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Affiliation(s)
- Israel Cohen
- Department of Diagnostic Imaging, Sheba Medical Center, Tel Hashomer, Israel
- Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Chen Hoffmann
- Department of Diagnostic Imaging, Sheba Medical Center, Tel Hashomer, Israel
- Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Yiftach Barash
- Department of Diagnostic Imaging, Sheba Medical Center, Tel Hashomer, Israel
- Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Ruth Lekach
- Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- Department of Nuclear Medicine, Tel-Aviv Sourasky Medical Center, Tel Aviv, Israel
| | - Bruria Ben-Zeev
- Department of Diagnostic Imaging, Sheba Medical Center, Tel Hashomer, Israel
- Pediatric Neurology Unit, Edmond and Lily Safra Children’s Hospital, Sheba Medical Center, Ramat Gan, Israel
| | - Efrat Zohar-Dayan
- Department of Diagnostic Imaging, Sheba Medical Center, Tel Hashomer, Israel
- Pediatric Neurology Unit, Edmond and Lily Safra Children’s Hospital, Sheba Medical Center, Ramat Gan, Israel
| | - Shai Shrot
- Department of Diagnostic Imaging, Sheba Medical Center, Tel Hashomer, Israel
- Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
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17
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Bateman GA, Bateman AR. The dilated cortical veins found in multiple sclerosis can explain the reduction in glymphatic flow. Mult Scler Relat Disord 2024; 81:105136. [PMID: 37979409 DOI: 10.1016/j.msard.2023.105136] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 10/11/2023] [Accepted: 11/12/2023] [Indexed: 11/20/2023]
Affiliation(s)
- Grant A Bateman
- Department of Medical Imaging, John Hunter Hospital, Newcastle, NSW, Australia; Faculty of Health, Newcastle University, Callaghan Campus, Newcastle, NSW, Australia.
| | - Alexander R Bateman
- School of Mechanical Engineering, University of New South Wales, Sydney, NSW, Australia
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18
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Zhang J, Liu S, Wu Y, Tang Z, Wu Y, Qi Y, Dong F, Wang Y. Enlarged Perivascular Space and Index for Diffusivity Along the Perivascular Space as Emerging Neuroimaging Biomarkers of Neurological Diseases. Cell Mol Neurobiol 2023; 44:14. [PMID: 38158515 DOI: 10.1007/s10571-023-01440-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Accepted: 11/12/2023] [Indexed: 01/03/2024]
Abstract
The existence of lymphatic vessels or similar clearance systems in the central nervous system (CNS) that transport nutrients and remove cellular waste is a neuroscientific question of great significance. As the brain is the most metabolically active organ in the body, there is likely to be a potential correlation between its clearance system and the pathological state of the CNS. Until recently the successive discoveries of the glymphatic system and the meningeal lymphatics solved this puzzle. This article reviews the basic anatomy and physiology of the glymphatic system. Imaging techniques to visualize the function of the glymphatic system mainly including post-contrast imaging techniques, indirect lymphatic assessment by detecting increased perivascular space, and diffusion tensor image analysis along the perivascular space (DTI-ALPS) are discussed. The pathological link between glymphatic system dysfunction and neurological disorders is the key point, focusing on the enlarged perivascular space (EPVS) and the index of diffusivity along the perivascular space (ALPS index), which may represent the activity of the glymphatic system as possible clinical neuroimaging biomarkers of neurological disorders. The pathological link between glymphatic system dysfunction and neurological disorders is the key point, focusing on the enlarged perivascular space (EPVS) and the index for of diffusivity along the perivascular space (ALPS index), which may represent the activity of the glymphatic system as possible clinical neuroimaging biomarkers of neurological disorders.
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Affiliation(s)
- Jun Zhang
- Department of Neurosurgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Shengwen Liu
- Department of Neurosurgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Yaqi Wu
- Department of Neurosurgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Zhijian Tang
- Department of Neurosurgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Yasong Wu
- Department of Neurosurgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Yiwei Qi
- Department of Neurosurgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Fangyong Dong
- Department of Neurosurgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Yu Wang
- Department of Neurosurgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
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Hashemi E, Narain Srivastava I, Aguirre A, Tilahan Yoseph E, Kaushal E, Awani A, Kyu. Ryu J, Akassoglou K, Talebian S, Chu P, Pisani L, Musolino P, Steinman L, Doyle K, Robinson WH, Sharpe O, Cayrol R, Orchard P, Lund T, Vogel H, Lenail M, Han MH, Bonkowsky JL, Van Haren KP. A novel mouse model of cerebral adrenoleukodystrophy highlights NLRP3 activity in lesion pathogenesis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.07.564025. [PMID: 37986739 PMCID: PMC10659266 DOI: 10.1101/2023.11.07.564025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
Objective We sought to create and characterize a mouse model of the inflammatory, cerebral demyelinating phenotype of X-linked adrenoleukodystrophy (ALD) that would facilitate the study of disease pathogenesis and therapy development. We also sought to cross-validate potential therapeutic targets such as fibrin, oxidative stress, and the NLRP3 inflammasome, in post-mortem human and murine brain tissues. Background ALD is caused by mutations in the gene ABCD1 encoding a peroxisomal transporter. More than half of males with an ABCD1 mutation develop the cerebral phenotype (cALD). Incomplete penetrance and absence of a genotype-phenotype correlation imply a role for environmental triggers. Mechanistic studies have been limited by the absence of a cALD phenotype in the Abcd1-null mouse. Methods We generated a cALD phenotype in 8-week-old, male Abcd1-null mice by deploying a two-hit method that combines cuprizone (CPZ) and experimental autoimmune encephalomyelitis (EAE) models. We employed in vivo MRI and post-mortem immunohistochemistry to evaluate myelin loss, astrogliosis, blood-brain barrier (BBB) disruption, immune cell infiltration, fibrin deposition, oxidative stress, and Nlrp3 inflammasome activation in mice. We used bead-based immunoassay and immunohistochemistry to evaluate IL-18 in CSF and post-mortem human cALD brain tissue. Results MRI studies revealed T2 hyperintensities and post-gadolinium enhancement in the medial corpus callosum of cALD mice, similar to human cALD lesions. Both human and mouse cALD lesions shared common histologic features of myelin phagocytosis, myelin loss, abundant microglial activation, T and B-cell infiltration, and astrogliosis. Compared to wild-type controls, Abcd1-null mice had more severe cerebral inflammation, demyelination, fibrin deposition, oxidative stress, and IL-18 activation. IL-18 immunoreactivity co-localized with macrophages/microglia in the perivascular region of both human and mouse brain tissue. Interpretation This novel mouse model of cALD suggests loss of Abcd1 function predisposes to more severe cerebral inflammation, oxidative stress, fibrin deposition, and Nlrp3 pathway activation, which parallels the findings seen in humans with cALD. We expect this model to enable long-sought investigations into cALD mechanisms and accelerate development of candidate therapies for lesion prevention, cessation, and remyelination.
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Affiliation(s)
- Ezzat Hashemi
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Isha Narain Srivastava
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Alejandro Aguirre
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Ezra Tilahan Yoseph
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Esha Kaushal
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Avni Awani
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Jae Kyu. Ryu
- Gladstone Institute for Neurological Disease; San Francisco, CA, USA
- Center for Neurovascular Brain Immunology at Gladstone and UCSF; San Francisco, CA USA
- Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco; San Francisco, CA, USA
| | - Katerina Akassoglou
- Gladstone Institute for Neurological Disease; San Francisco, CA, USA
- Center for Neurovascular Brain Immunology at Gladstone and UCSF; San Francisco, CA USA
- Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco; San Francisco, CA, USA
| | - Shahrzad Talebian
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Pauline Chu
- Stanford Human Research Histology Core, Stanford University School of Medicine, Stanford, CA, USA
| | - Laura Pisani
- Department of Radiology, Stanford University School of Medicine Stanford, CA, USA
| | - Patricia Musolino
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Lawrence Steinman
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Kristian Doyle
- Department of Immunobiology, University of Arizona, Tucson, AZ, USA
| | - William H Robinson
- Department of Immunology & Rheumatology, Stanford University School of Medicine, Stanford, CA, USA
| | - Orr Sharpe
- Department of Immunology & Rheumatology, Stanford University School of Medicine, Stanford, CA, USA
| | - Romain Cayrol
- Department of Pathology, Clinical Department of Laboratory Medicine, University of Montreal, Quebec, Canada
| | - Paul Orchard
- Division of Pediatric Blood & Marrow Transplantation, University of Minnesota, Minneapolis, MN, USA
| | - Troy Lund
- Division of Pediatric Blood & Marrow Transplantation, University of Minnesota, Minneapolis, MN, USA
| | - Hannes Vogel
- Departments of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Max Lenail
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - May Htwe Han
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Joshua Leith Bonkowsky
- Division of Pediatric Neurology, Department of Pediatrics, University of Utah School of Medicine, Salt Lake City, Utah
- Brain and Spine Center, Primary Children’s Hospital, Salt Lake City, Utah
- Primary Children’s Center for Personalized Medicine, Salt Lake City, Utah
| | - Keith P. Van Haren
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
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Bateman GA, Bateman AR. Syringomyelia Is Associated with a Reduction in Spinal Canal Compliance, Venous Outflow Dilatation and Glymphatic Fluid Obstruction. J Clin Med 2023; 12:6646. [PMID: 37892782 PMCID: PMC10607592 DOI: 10.3390/jcm12206646] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 10/17/2023] [Accepted: 10/18/2023] [Indexed: 10/29/2023] Open
Abstract
The cause of the cystic dilatation of the cord found in syringomyelia has been a source of conjecture for a considerable time. Recent studies have shown that there is a reduction in craniospinal compliance in both childhood hydrocephalus and multiple sclerosis which leads to venous outflow dilatation. Both diseases are associated with glymphatic outflow obstruction. Venous dilatation will narrow the perivenous glymphatic outflow pathway and lead to an increase in glymphatic outflow resistance. Syringomyelia has been shown to be associated with reduced spinal canal compliance. This paper discusses the possibility that venous dilatation and obstructed glymphatic outflow within the cord may be behind the cystic dilatation found within syringomyelia.
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Affiliation(s)
- Grant Alexander Bateman
- Department of Medical Imaging, John Hunter Hospital, Newcastle, NSW 2305, Australia
- Faculty of Health, Callaghan Campus, University of Newcastle, Newcastle, NSW 2308, Australia
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21
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Cao S, Zhu Y, Xia M, Xue Q. Enlarged perivascular spaces in autoimmune glial fibrillary acidic protein astrocytopathy. Neurol Sci 2023; 44:3751-3754. [PMID: 37358690 DOI: 10.1007/s10072-023-06892-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Accepted: 06/01/2023] [Indexed: 06/27/2023]
Affiliation(s)
- Shugang Cao
- Department of Neurology, Second People's Hospital of Hefei, Hefei Hospital Affiliated to Anhui Medical University, Hefei, 230011, China
| | - Yunfei Zhu
- Department of Neurology, First Affiliated Hospital of Soochow University, Suzhou, 215006, China
| | - Mingwu Xia
- Department of Neurology, Second People's Hospital of Hefei, Hefei Hospital Affiliated to Anhui Medical University, Hefei, 230011, China
| | - Qun Xue
- Department of Neurology, First Affiliated Hospital of Soochow University, Suzhou, 215006, China.
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22
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Gill AJ, Schorr EM, Gadani SP, Calabresi PA. Emerging imaging and liquid biomarkers in multiple sclerosis. Eur J Immunol 2023; 53:e2250228. [PMID: 37194443 PMCID: PMC10524168 DOI: 10.1002/eji.202250228] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 04/10/2023] [Accepted: 05/12/2023] [Indexed: 05/18/2023]
Abstract
The advent of highly effective disease modifying therapy has transformed the landscape of multiple sclerosis (MS) care over the last two decades. However, there remains a critical, unmet need for sensitive and specific biomarkers to aid in diagnosis, prognosis, treatment monitoring, and the development of new interventions, particularly for people with progressive disease. This review evaluates the current data for several emerging imaging and liquid biomarkers in people with MS. MRI findings such as the central vein sign and paramagnetic rim lesions may improve MS diagnostic accuracy and evaluation of therapy efficacy in progressive disease. Serum and cerebrospinal fluid levels of several neuroglial proteins, such as neurofilament light chain and glial fibrillary acidic protein, show potential to be sensitive biomarkers of pathologic processes such as neuro-axonal injury or glial-inflammation. Additional promising biomarkers, including optical coherence tomography, cytokines and chemokines, microRNAs, and extracellular vesicles/exosomes, are also reviewed, among others. Beyond their potential integration into MS clinical care and interventional trials, several of these biomarkers may be informative of MS pathogenesis and help elucidate novel targets for treatment strategies.
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Affiliation(s)
- Alexander J. Gill
- Johns Hopkins University School of Medicine, Department of Neurology, Baltimore, MD, US
| | - Emily M. Schorr
- Johns Hopkins University School of Medicine, Department of Neurology, Baltimore, MD, US
| | - Sachin P. Gadani
- Johns Hopkins University School of Medicine, Department of Neurology, Baltimore, MD, US
| | - Peter A. Calabresi
- Johns Hopkins University School of Medicine, Department of Neurology, Baltimore, MD, US
- Department of Neuroscience, Baltimore, MD, US
- Department of Ophthalmology, Baltimore, MD, US
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23
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Ding Z, Fan X, Zhang Y, Yao M, Wang G, Dong Y, Liu J, Song W. The glymphatic system: a new perspective on brain diseases. Front Aging Neurosci 2023; 15:1179988. [PMID: 37396658 PMCID: PMC10308198 DOI: 10.3389/fnagi.2023.1179988] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2023] [Accepted: 05/29/2023] [Indexed: 07/04/2023] Open
Abstract
The glymphatic system is a brain-wide perivascular pathway driven by aquaporin-4 on the endfeet of astrocytes, which can deliver nutrients and active substances to the brain parenchyma through periarterial cerebrospinal fluid (CSF) influx pathway and remove metabolic wastes through perivenous clearance routes. This paper summarizes the composition, overall fluid flow, solute transport, related diseases, affecting factors, and preclinical research methods of the glymphatic system. In doing so, we aim to provide direction and reference for more relevant researchers in the future.
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24
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Okar SV, Hu F, Shinohara RT, Beck ES, Reich DS, Ineichen BV. The etiology and evolution of magnetic resonance imaging-visible perivascular spaces: Systematic review and meta-analysis. Front Neurosci 2023; 17:1038011. [PMID: 37065926 PMCID: PMC10098201 DOI: 10.3389/fnins.2023.1038011] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 03/15/2023] [Indexed: 04/03/2023] Open
Abstract
ObjectivesPerivascular 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.MethodsIn 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.ResultsFour 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.ConclusionCollectively, 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.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?RecordID=346564, identifier CRD42022346564.
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Affiliation(s)
- Serhat V. Okar
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Fengling Hu
- Department of Biostatistics, Epidemiology, and Informatics, Penn Statistics in Imaging and Visualization Center, University of Pennsylvania, Philadelphia, PA, United States
| | - Russell T. Shinohara
- Department of Biostatistics, Epidemiology, and Informatics, Penn Statistics in Imaging and Visualization Center, University of Pennsylvania, Philadelphia, PA, United States
| | - Erin S. Beck
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Daniel S. Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Benjamin V. Ineichen
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Center for Reproducible Science, University of Zurich, Zurich, Switzerland
- *Correspondence: Benjamin V. Ineichen, , ; orcid.org/0000-0003-1362-4819
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25
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Kim HG, Shin NY, Nam Y, Yun E, Yoon U, Lee HS, Ahn KJ. MRI-visible Dilated Perivascular Space in the Brain by Age: The Human Connectome Project. Radiology 2023; 306:e213254. [PMID: 36378031 DOI: 10.1148/radiol.213254] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background Dilated perivascular spaces (dPVS) are associated with aging and various disorders; however, the effect of age on dPVS burden in young populations and normative data have not been fully evaluated. Purpose To investigate the dPVS burden and provide normative data according to age in a healthy population, including children. Materials and Methods In this retrospective study, three-dimensional T2-weighted brain MRI scans from the Human Connectome Project data sets were used for visual grading (grade 0, 1, 2, 3, 4 for 0, 1-10, 11-20, 21-40, and >40 dPVS on a single section of either hemispheric region) and automated volumetry of dPVS in basal ganglia (BGdPVS) and white matter (WMdPVS). Linear and nonlinear regression were performed to assess the association of dPVS volume with age. Optimal cutoff ages were determined with use of the maximized continuous-scale C-index. Participants were grouped by cutoff values. Linear regression was performed to assess the age-dPVS volume relationship in each age group. Normative data of dPVS visual grades were provided per age decade. Results A total of 1789 participants (mean age, 35 years; age range, 8-100 years; 1006 female participants) were evaluated. Age was related to dPVS volume in all regression models (R2 range, 0.41-0.55; P < .001). Age-dPVS volume relationships were altered at the mid-30s and age 55 years; BGdPVS and WMdPVS volumes negatively correlated with age until the mid-30s (β, -1.2 and -7.8), then positively until age 55 years (β, 3.3 and 54.1) and beyond (β, 3.9 and 42.8; P < .001). The 90th percentile for dPVS grades was grade 1 for age 49 years and younger, grade 2 for age 50-69 years, and grade 3 for age 70 years and older (overall, grade 2) for BGdPVS, and grade 3 for age 49 years and younger and grade 4 for age 50 years and older (overall, grade 3) for WMdPVS. Conclusion Dilated perivascular spaces (dPVS) showed a biphasic volume pattern with brain MRI, lower volumes until the mid-30s, then higher afterward. Grades of 3 or higher and 4 might be considered pathologic dPVS in basal ganglia and white matter, respectively. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Bapuraj and Chaudhary in this issue.
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Affiliation(s)
- Hyun Gi Kim
- From the Department of Radiology, Eunpyeong St Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea (H.G.K.); Department of Radiology, Seoul St Mary's Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea (N.Y.S., K.J.A.); Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea (Y.N.); Department of Biomedical Engineering, College of Bio and Medical Sciences, Daegu Catholic University, Daegu, Republic of Korea (E.Y., U.Y.); and Biostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, Republic of Korea (H.S.L.)
| | - Na-Young Shin
- From the Department of Radiology, Eunpyeong St Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea (H.G.K.); Department of Radiology, Seoul St Mary's Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea (N.Y.S., K.J.A.); Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea (Y.N.); Department of Biomedical Engineering, College of Bio and Medical Sciences, Daegu Catholic University, Daegu, Republic of Korea (E.Y., U.Y.); and Biostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, Republic of Korea (H.S.L.)
| | - Yoonho Nam
- From the Department of Radiology, Eunpyeong St Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea (H.G.K.); Department of Radiology, Seoul St Mary's Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea (N.Y.S., K.J.A.); Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea (Y.N.); Department of Biomedical Engineering, College of Bio and Medical Sciences, Daegu Catholic University, Daegu, Republic of Korea (E.Y., U.Y.); and Biostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, Republic of Korea (H.S.L.)
| | - Eunkyeong Yun
- From the Department of Radiology, Eunpyeong St Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea (H.G.K.); Department of Radiology, Seoul St Mary's Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea (N.Y.S., K.J.A.); Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea (Y.N.); Department of Biomedical Engineering, College of Bio and Medical Sciences, Daegu Catholic University, Daegu, Republic of Korea (E.Y., U.Y.); and Biostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, Republic of Korea (H.S.L.)
| | - Uicheul Yoon
- From the Department of Radiology, Eunpyeong St Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea (H.G.K.); Department of Radiology, Seoul St Mary's Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea (N.Y.S., K.J.A.); Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea (Y.N.); Department of Biomedical Engineering, College of Bio and Medical Sciences, Daegu Catholic University, Daegu, Republic of Korea (E.Y., U.Y.); and Biostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, Republic of Korea (H.S.L.)
| | - Hye Sun Lee
- From the Department of Radiology, Eunpyeong St Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea (H.G.K.); Department of Radiology, Seoul St Mary's Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea (N.Y.S., K.J.A.); Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea (Y.N.); Department of Biomedical Engineering, College of Bio and Medical Sciences, Daegu Catholic University, Daegu, Republic of Korea (E.Y., U.Y.); and Biostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, Republic of Korea (H.S.L.)
| | - Kook Jin Ahn
- From the Department of Radiology, Eunpyeong St Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea (H.G.K.); Department of Radiology, Seoul St Mary's Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea (N.Y.S., K.J.A.); Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea (Y.N.); Department of Biomedical Engineering, College of Bio and Medical Sciences, Daegu Catholic University, Daegu, Republic of Korea (E.Y., U.Y.); and Biostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, Republic of Korea (H.S.L.)
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Ineichen BV, Cananau C, Platt N M, Ouellette R, Moridi T, Frauenknecht KBM, Okar SV, Kulcsar Z, Kockum I, Piehl F, Reich DS, Granberg T. Dilated Virchow-Robin Spaces are a Marker for Arterial Disease in Multiple Sclerosis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.24.529871. [PMID: 36945422 PMCID: PMC10028816 DOI: 10.1101/2023.02.24.529871] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/02/2023]
Abstract
Virchow-Robin spaces (VRS) have been associated with neurodegeneration and neuroinflammation. However, it remains uncertain to what degree non-dilated or dilated VRS reflect specific features of neuroinflammatory pathology. Thus, we aimed at investigating the clinical relevance of VRS as imaging biomarker in multiple sclerosis (MS) and to correlate VRS to their histopathologic signature. In a cohort study comprising 205 MS patients (including a validation cohort) and 30 control subjects, we assessed the association of non-dilated and dilated VRS to clinical and magnetic resonance imaging (MRI) out-comes. Brain blocks from 6 MS patients and 3 non-MS controls were histopathologically processed to correlate VRS to their tissue substrate. The count of dilated centrum semiovale VRS was associated with increased T1 and T2 lesion volumes. There was no systematic spatial colocalization of dilated VRS with MS lesions. At tissue level, VRS mostly corresponded to arteries and were not associated with MS pathological hallmarks. Interestingly, dilated VRS in MS were associated with signs of small vessel disease. Contrary to prior beliefs, these observations suggest that VRS in MS do not associate with accumulation of immune cells. But instead, these findings indicate vascular pathology as a driver and/or consequence of neuroinflammatory pathology for this imaging feature.
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27
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Evans TE, Knol MJ, Schwingenschuh P, Wittfeld K, Hilal S, Ikram MA, Dubost F, van Wijnen KMH, Katschnig P, Yilmaz P, de Bruijne M, Habes M, Chen C, Langer S, Völzke H, Ikram MK, Grabe HJ, Schmidt R, Adams HHH, Vernooij MW. Determinants of Perivascular Spaces in the General Population: A Pooled Cohort Analysis of Individual Participant Data. Neurology 2023; 100:e107-e122. [PMID: 36253103 PMCID: PMC9841448 DOI: 10.1212/wnl.0000000000201349] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Accepted: 08/19/2022] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Perivascular spaces (PVS) are emerging markers of cerebral small vessel disease (CSVD), but research on their determinants has been hampered by conflicting results from small single studies using heterogeneous rating methods. In this study, we therefore aimed to identify determinants of PVS burden in a pooled analysis of multiple cohort studies using 1 harmonized PVS rating method. METHODS Individuals from 10 population-based cohort studies with adult participants from the Uniform Neuro-Imaging of Virchow-Robin Spaces Enlargement consortium and the UK Biobank were included. On MRI scans, we counted PVS in 4 brain regions (mesencephalon, hippocampus, basal ganglia, and centrum semiovale) according to a uniform and validated rating protocol, both manually and automated using a deep learning algorithm. As potential determinants, we considered demographics, cardiovascular risk factors, APOE genotypes, and other imaging markers of CSVD. Negative binomial regression models were used to examine the association between these determinants and PVS counts. RESULTS In total, 39,976 individuals were included (age range 20-96 years). The average count of PVS in the 4 regions increased from the age 20 years (0-1 PVS) to 90 years (2-7 PVS). Men had more mesencephalic PVS (OR [95% CI] = 1.13 [1.08-1.18] compared with women), but less hippocampal PVS (0.82 [0.81-0.83]). Higher blood pressure, particularly diastolic pressure, was associated with more PVS in all regions (ORs between 1.04-1.05). Hippocampal PVS showed higher counts with higher high-density lipoprotein cholesterol levels (1.02 [1.01-1.02]), glucose levels (1.02 [1.01-1.03]), and APOE ε4-alleles (1.02 [1.01-1.04]). Furthermore, white matter hyperintensity volume and presence of lacunes were associated with PVS in multiple regions, but most strongly with the basal ganglia (1.13 [1.12-1.14] and 1.10 [1.09-1.12], respectively). DISCUSSION Various factors are associated with the burden of PVS, in part regionally specific, which points toward a multifactorial origin beyond what can be expected from PVS-related risk factor profiles. This study highlights the power of collaborative efforts in population neuroimaging research.
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Affiliation(s)
- Tavia E Evans
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Maria J Knol
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Petra Schwingenschuh
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Katharina Wittfeld
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Saima Hilal
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - M Arfan Ikram
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Florian Dubost
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Kimberlin M H van Wijnen
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Petra Katschnig
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Pinar Yilmaz
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Marleen de Bruijne
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Mohamad Habes
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Christopher Chen
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Sönke Langer
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Henry Völzke
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - M Kamran Ikram
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Hans J Grabe
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Reinhold Schmidt
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Hieab H H Adams
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile.
| | - Meike W Vernooij
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
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Pham W, Lynch M, Spitz G, O’Brien T, Vivash L, Sinclair B, Law M. A critical guide to the automated quantification of perivascular spaces in magnetic resonance imaging. Front Neurosci 2022; 16:1021311. [PMID: 36590285 PMCID: PMC9795229 DOI: 10.3389/fnins.2022.1021311] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Accepted: 11/16/2022] [Indexed: 12/15/2022] Open
Abstract
The glymphatic system is responsible for waste clearance in the brain. It is comprised of perivascular spaces (PVS) that surround penetrating blood vessels. These spaces are filled with cerebrospinal fluid and interstitial fluid, and can be seen with magnetic resonance imaging. Various algorithms have been developed to automatically label these spaces in MRI. This has enabled volumetric and morphological analyses of PVS in healthy and disease cohorts. However, there remain inconsistencies between PVS measures reported by different methods of automated segmentation. The present review emphasizes that importance of voxel-wise evaluation of model performance, mainly with the Sørensen Dice similarity coefficient. Conventional count correlations for model validation are inadequate if the goal is to assess volumetric or morphological measures of PVS. The downside of voxel-wise evaluation is that it requires manual segmentations that require large amounts of time to produce. One possible solution is to derive these semi-automatically. Additionally, recommendations are made to facilitate rigorous development and validation of automated PVS segmentation models. In the application of automated PVS segmentation tools, publication of image quality metrics, such as the contrast-to-noise ratio, alongside descriptive statistics of PVS volumes and counts will facilitate comparability between studies. Lastly, a head-to-head comparison between two algorithms, applied to two cohorts of astronauts reveals how results can differ substantially between techniques.
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Affiliation(s)
- William Pham
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia
| | - Miranda Lynch
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia
| | - Gershon Spitz
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia
- Monash-Epworth Rehabilitation Research Centre, Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, VIC, Australia
| | - Terence O’Brien
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia
- Department of Neurology, Alfred Hospital, Melbourne, VIC, Australia
- Department of Medicine, The Royal Melbourne Hospital, University of Melbourne, Melbourne, VIC, Australia
- Department of Neurology, The Royal Melbourne Hospital, University of Melbourne, Melbourne, VIC, Australia
| | - Lucy Vivash
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia
- Department of Neurology, Alfred Hospital, Melbourne, VIC, Australia
- Department of Medicine, The Royal Melbourne Hospital, University of Melbourne, Melbourne, VIC, Australia
- Department of Neurology, The Royal Melbourne Hospital, University of Melbourne, Melbourne, VIC, Australia
| | - Benjamin Sinclair
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia
- Department of Neurology, Alfred Hospital, Melbourne, VIC, Australia
- Department of Medicine, The Royal Melbourne Hospital, University of Melbourne, Melbourne, VIC, Australia
| | - Meng Law
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia
- Department of Radiology, Alfred Health Hospital, Melbourne, VIC, Australia
- Department of Electrical and Computer Systems Engineering, Monash University, Melbourne, VIC, Australia
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29
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Scollato A, Lolli F, Lastrucci G, Repice A, De Santis G, Nicoletti C, Porfirio B, Gallina P. Case report: A multiple sclerosis patient with imaging features of glymphatic failure benefitted from CSF flow shunting. Front Neurosci 2022; 16:863117. [PMID: 36389221 PMCID: PMC9663833 DOI: 10.3389/fnins.2022.863117] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Accepted: 09/29/2022] [Indexed: 11/30/2022] Open
Abstract
The derangement of CSF circulation impacts the functions of the glymphatic-lymphatic system (G-Ls), which regulates solute trafficking and immune surveillance in the CNS. The G-Ls failure leads to the dysregulation of clearance of waste molecules in the brain and to an altered CNS immune response. The imaging features of dilated perivascular spaces imply the impairment of the G-Ls. We report on the case of a patient with primary progressive multiple sclerosis and dilatation of perivascular spaces, who transiently improved after CSF shunt diversions. The underlying mechanisms remain to be determined and at this stage, it is not possible to link CSF diversion to an effect on MS pathology. However, this observation provides the rationale to incentivize research in the largely unknown area of CSF dynamic disturbances on G-Ls failure and ultimately in neurodegeneration.
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Affiliation(s)
| | - Francesco Lolli
- Department of Clinical and Experimental Biomedical Sciences “Mario Serio”, University of Florence, Florence, Italy
- Neurophysiology Unit, Careggi University Hospital, Florence, Italy
| | - Giancarlo Lastrucci
- Department of Neurosciences, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
| | - Anna Repice
- Neurology Unit, Careggi University Hospital, Florence, Italy
| | | | - Claudio Nicoletti
- Department of Experimental and Clinical Medicine, Section of Anatomy, University of Florence, Florence, Italy
| | - Berardino Porfirio
- Department of Clinical and Experimental Biomedical Sciences “Mario Serio”, University of Florence, Florence, Italy
| | - Pasquale Gallina
- Department of Neurosciences, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
- Neurosurgery Unit, Careggi University Hospital, Florence, Italy
- *Correspondence: Pasquale Gallina
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30
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Yao XY, Gao MC, Bai SW, Xie L, Song YY, Ding J, Wu YF, Xue CR, Hao Y, Zhang Y, Guan YT. Enlarged perivascular spaces, neuroinflammation and neurological dysfunction in NMOSD patients. Front Immunol 2022; 13:966781. [PMID: 36248814 PMCID: PMC9557144 DOI: 10.3389/fimmu.2022.966781] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2022] [Accepted: 08/31/2022] [Indexed: 11/22/2022] Open
Abstract
Background and objectives Cerebrospinal fluid (CSF) and interstitial fluid exchange along a brain-wide network of perivascular spaces (PVS) termed the ‘glymphatic system’. The aquaporin-4 (AQP4) water channels abundantly expressed on astrocytic endfeet play a key role in the CSF circulation in the glymphatic system. Neuromyelitis optica spectrum disorder (NMOSD) is an inflammatory demyelinating autoimmune disease of the central nervous system (CNS) featured with a specific autoantibody directed against AQP4 in most of patients. Anti-AQP4 antibodies are likely resulting in the impairment of the brain glymphatic system and the enlargement of PVS in NMOSD patients. In the current study, we aimed to demonstrate the features of EPVS detected by MRI and its association with the CSF anti-AQP4 antibody titer, CNS inflammatory markers, and disease severity in NMOSD patients. Methods We conducted a retrospective review of a consecutive cohort of 110 patients with NMOSD who had brain MRI. We assessed the correlation of EPVS with markers of neuroinflammation, blood-brain barrier (BBB) function and severity of neurological dysfunction in patients. We used multivariate logistic regression analysis to determine the independent variables associated with disease severity. Results The median number of total-EPVS was 15.5 (IQR, 11-24.2) in NMOSD patients. The number of total-EPVS was significantly related to EDSS score after correcting for the effects of age and hypertension (r=0.353, p<0.001). The number of total-EPVS was also significantly associated with the titer of CSF anti-AQP4 antibody, the albumin rate (CSF/serum ratios of albumin), the CSF albumin, IgG and IgA levels. Logistic regression analysis showed that total-EPVS and serum albumin level were two independent factors to predict disease severity in NMOSD patients (OR=1.053, p=0.028; OR=0.858, p=0.009 respectively). Furthermore, ROC analysis achieved AUC of 0.736 (0.640-0.831, p<0.001) for total-EPVS to determine severe NMOSD (EDSS 4.5-9.5). Discussion In our cohort, we found a relationship between EPVS and neuroinflammation and BBB function in NMOSD. Moreover, EPVS might independently predict neurological dysfunction in patients with NMOSD.
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Affiliation(s)
- Xiao-Ying Yao
- Department of Neurology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Mei-Chun Gao
- Department of Neurology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Shu-Wei Bai
- Department of Neurology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Li Xie
- Clinical Research Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Ya-Ying Song
- Department of Neurology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Jie Ding
- Department of Neurology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Yi-Fan Wu
- Department of Neurology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Chun-Ran Xue
- Department of Neurology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Yong Hao
- Department of Neurology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Ying Zhang
- Department of Neurology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Yang-Tai Guan
- Department of Neurology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
- *Correspondence: Yang-Tai Guan,
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31
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Zou Q, Wang M, Wei X, Li W. Prevalence and Risk Factors for Enlarged Perivascular Spaces in Young Adults from a Neurology Clinic-Based Cohort. Brain Sci 2022; 12:brainsci12091164. [PMID: 36138900 PMCID: PMC9497082 DOI: 10.3390/brainsci12091164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 08/23/2022] [Accepted: 08/29/2022] [Indexed: 11/16/2022] Open
Abstract
(1) Background: This study aimed to investigate the prevalence and risk factors for enlarged perivascular spaces (EPVS) in young adults from a neurology clinic-based cohort (≤45 years old) via unenhanced brain MRI. (2) Methods: A total of 931 young adults from a neurology clinic-based cohort who underwent unenhanced brain MRI between 1 January 2021 and 30 June 2021 were retrospectively included in this study. The EPVS were rated in the centrum semiovale (CSO-EPVS), basal ganglia (BG-EPVS), and midbrain (MB-EPVS) using a visual rating scale. The degrees of the CSO-EPVS, BG-EPVS, and MB-EPVS were all divided by a cutoff value of 1. Demographic factors, vascular risk factors, and symptoms were analyzed using the chi-square test and logistic regression to determine the risk factors of EPVS. (3) Results: The overall prevalence of EPVS was 99.8% (929/931). The CSO-EPVS, BG-EPVS, and MB-EPVS were predominantly scored as 1 (52.1%, 79.1%, and 58.3%, respectively). Logistic regression analysis identified age and hypertension as factors affecting the degrees of CSO-EPVS and BG-EPVS (p < 0.05). Hypertension (p < 0.001) and diabetes (p = 0.014) were revealed to be factors affecting the degree of BG-EPVS. Furthermore, patients with headache (OR = 1.807; p = 0.001) and dizziness (OR = 1.574; p = 0.025) were associated with MB-EPVS. (4) Conclusions: EPVS were frequently found in young adults and could be related to the symptoms. Age, hypertension, and diabetes were the risk factors for the severity of EPVS in the corresponding brain regions.
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32
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Haider L, Hametner S, Endmayr V, Mangesius S, Eppensteiner A, Frischer JM, Iglesias JE, Barkhof F, Kasprian G. Post-mortem correlates of Virchow-Robin spaces detected on in vivo MRI. J Cereb Blood Flow Metab 2022; 42:1224-1235. [PMID: 35581687 PMCID: PMC9207491 DOI: 10.1177/0271678x211067455] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The purpose of our study is to quantify the extent to which Virchow-Robin spaces (VRS) detected on in vivo MRI are reproducible by post-mortem MRI.Double Echo Steady State 3T MRIs were acquired post-mortem in 49 double- and 32 single-hemispheric formalin-fixed brain sections from 12 patients, who underwent conventional diagnostic 1.5 or 3T MRI in median 22 days prior to death (25% to 75%: 12 to 134 days). The overlap of in vivo and post-mortem VRS segmentations was determined accounting for potential confounding factors.The reproducibility of VRS found on in vivo MRI by post-mortem MRI, in the supratentorial white matter was in median 80% (25% to 75%: 60 to 100). A lower reproducibility was present in the basal ganglia, with a median of 47% (25% to 75%: 30 to 50).VRS segmentations were histologically confirmed in one double hemispheric section.Overall, the majority of VRS found on in vivo MRI was stable throughout death and formalin fixation, emphasizing the translational potential of post-mortem VRS studies.
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Affiliation(s)
- Lukas Haider
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London Institute of Neurology, London, UK.,Department of Biomedical Imaging and Image Guided Therapy, Medical University of Vienna, Wien, Austria
| | - Simon Hametner
- Clinical Institute of Neurology, Centre for Brain Research, Medical University of Vienna, Wien, Austria
| | - Verena Endmayr
- Clinical Institute of Neurology, Centre for Brain Research, Medical University of Vienna, Wien, Austria
| | - Stephanie Mangesius
- Department of Neuroradiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Andrea Eppensteiner
- Department of Neuroradiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Josa M Frischer
- Department of Neurosurgery, Medical University Vienna, Wien, Austria
| | - Juan Eugenio Iglesias
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Frederik Barkhof
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London Institute of Neurology, London, UK.,Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London, UK.,National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre, London, UK.,Department of Radiology and Nuclear Medicine, VU University Medical Centre, Amsterdam, Netherlands
| | - Gregor Kasprian
- Department of Biomedical Imaging and Image Guided Therapy, Medical University of Vienna, Wien, Austria
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33
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Breaching Brain Barriers: B Cell Migration in Multiple Sclerosis. Biomolecules 2022; 12:biom12060800. [PMID: 35740925 PMCID: PMC9221446 DOI: 10.3390/biom12060800] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Revised: 06/03/2022] [Accepted: 06/05/2022] [Indexed: 12/25/2022] Open
Abstract
Multiple sclerosis (MS) is an inflammatory disease of the central nervous system (CNS) known for the manifestation of demyelinated lesions throughout the CNS, leading to neurodegeneration. To date, not all pathological mechanisms that drive disease progression are known, but the clinical benefits of anti-CD20 therapies have put B cells in the spotlight of MS research. Besides their pathological effects in the periphery in MS, B cells gain access to the CNS where they can contribute to disease pathogenesis. Specifically, B cells accumulate in perivascular infiltrates in the brain parenchyma and the subarachnoid spaces of the meninges, but are virtually absent from the choroid plexus. Hence, the possible migration of B cells over the blood-brain-, blood-meningeal-, and blood-cerebrospinal fluid (CSF) barriers appears to be a crucial step to understanding B cell-mediated pathology. To gain more insight into the molecular mechanisms that regulate B cell trafficking into the brain, we here provide a comprehensive overview of the different CNS barriers in health and in MS and how they translate into different routes for B cell migration. In addition, we review the mechanisms of action of diverse therapies that deplete peripheral B cells and/or block B cell migration into the CNS. Importantly, this review shows that studying the different routes of how B cells enter the inflamed CNS should be the next step to understanding this disease.
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34
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Kolbe S, Garcia L, Yu N, Boonstra F, Clough M, Sinclair B, White O, van der Walt A, Butzkueven H, Fielding J, Law M. Lesion Volume in Relapsing Multiple Sclerosis is Associated with Perivascular Space Enlargement at the Level of the Basal Ganglia. AJNR Am J Neuroradiol 2022; 43:238-244. [PMID: 35121585 PMCID: PMC8985682 DOI: 10.3174/ajnr.a7398] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Accepted: 10/19/2021] [Indexed: 02/03/2023]
Abstract
BACKGROUND AND PURPOSE Perivascular spaces surround the blood vessels of the brain and are involved in neuroimmune functions and clearance of metabolites via the glymphatic system of the brain. Enlarged perivascular spaces could be a marker of dysfunction in these processes and, therefore, are highly relevant to monitoring disease activity in MS. This study aimed to compare the number of enlarged perivascular spaces in people with relapsing MS with MR imaging markers of inflammation and brain atrophy. MATERIALS AND METHODS Fifty-nine patients (18 with clinically isolated syndrome, 22 with early and 19 with late relapsing-remitting MS) were scanned longitudinally (mean follow-up duration = 19.6 [SD, 0.5] months) using T2-weighted, T1-weighted, and FLAIR MR imaging. Two expert raters identified and counted enlarged perivascular spaces on T2-weighted MR images from 3 ROIs (the centrum semiovale, basal ganglia, and midbrain). Baseline and change with time in the number of enlarged perivascular spaces were correlated with demographics and lesion and brain volumes. RESULTS Late relapsing-remitting MS had a greater average number of enlarged perivascular spaces at baseline at the level of the basal ganglia (72.3) compared with early relapsing-remitting MS (60.5) and clinically isolated syndrome (54.7) (F = 3.4, P = .042), and this finding correlated with lesion volume (R = 0.44, P = .0004) but not brain atrophy (R = -0.16). Enlarged perivascular spaces increased in number with time in all regions, and the rate of increase did not differ among clinical groups. CONCLUSIONS Enlarged perivascular spaces at the level of the basal ganglia are associated with greater neuroinflammatory burden, and the rate of enlargement appears constant in patients with relapsing-remitting disease phenotypes.
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Affiliation(s)
- S.C. Kolbe
- From the Department of Neuroscience (S.C.K., L.M.G., N.Y., F.M.B., M.C., B.S., O.W., A.v.d.W., H.B., J.F., M.L.) Monash University, Melbourne, Victoria, Australia,Departments of Radiology (S.C.K., M.L.)
| | - L.M. Garcia
- From the Department of Neuroscience (S.C.K., L.M.G., N.Y., F.M.B., M.C., B.S., O.W., A.v.d.W., H.B., J.F., M.L.) Monash University, Melbourne, Victoria, Australia
| | - N. Yu
- From the Department of Neuroscience (S.C.K., L.M.G., N.Y., F.M.B., M.C., B.S., O.W., A.v.d.W., H.B., J.F., M.L.) Monash University, Melbourne, Victoria, Australia,Department of Neurology (N.Y.), The Nanjing Brain Hospital Affiliated with Nanjing Medical University, Nanjing, Jiangsu, China
| | - F.M. Boonstra
- From the Department of Neuroscience (S.C.K., L.M.G., N.Y., F.M.B., M.C., B.S., O.W., A.v.d.W., H.B., J.F., M.L.) Monash University, Melbourne, Victoria, Australia
| | - M. Clough
- From the Department of Neuroscience (S.C.K., L.M.G., N.Y., F.M.B., M.C., B.S., O.W., A.v.d.W., H.B., J.F., M.L.) Monash University, Melbourne, Victoria, Australia
| | - B. Sinclair
- From the Department of Neuroscience (S.C.K., L.M.G., N.Y., F.M.B., M.C., B.S., O.W., A.v.d.W., H.B., J.F., M.L.) Monash University, Melbourne, Victoria, Australia
| | - O. White
- From the Department of Neuroscience (S.C.K., L.M.G., N.Y., F.M.B., M.C., B.S., O.W., A.v.d.W., H.B., J.F., M.L.) Monash University, Melbourne, Victoria, Australia,Neurology (O.W., A.v.d.W., H.B.), Alfred Hospital, Melbourne, Victoria, Australia
| | - A. van der Walt
- From the Department of Neuroscience (S.C.K., L.M.G., N.Y., F.M.B., M.C., B.S., O.W., A.v.d.W., H.B., J.F., M.L.) Monash University, Melbourne, Victoria, Australia,Neurology (O.W., A.v.d.W., H.B.), Alfred Hospital, Melbourne, Victoria, Australia
| | - H. Butzkueven
- From the Department of Neuroscience (S.C.K., L.M.G., N.Y., F.M.B., M.C., B.S., O.W., A.v.d.W., H.B., J.F., M.L.) Monash University, Melbourne, Victoria, Australia,Neurology (O.W., A.v.d.W., H.B.), Alfred Hospital, Melbourne, Victoria, Australia
| | - J. Fielding
- From the Department of Neuroscience (S.C.K., L.M.G., N.Y., F.M.B., M.C., B.S., O.W., A.v.d.W., H.B., J.F., M.L.) Monash University, Melbourne, Victoria, Australia
| | - M. Law
- From the Department of Neuroscience (S.C.K., L.M.G., N.Y., F.M.B., M.C., B.S., O.W., A.v.d.W., H.B., J.F., M.L.) Monash University, Melbourne, Victoria, Australia,Departments of Radiology (S.C.K., M.L.)
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Jones O, Cutsforth-Gregory J, Chen J, Bhatti MT, Huston J, Brinjikji W. Idiopathic Intracranial Hypertension is Associated with a Higher Burden of Visible Cerebral Perivascular Spaces: The Glymphatic Connection. AJNR Am J Neuroradiol 2021; 42:2160-2164. [PMID: 34824096 DOI: 10.3174/ajnr.a7326] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Accepted: 08/22/2021] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Research suggests a connection between idiopathic intracranial hypertension and the cerebral glymphatic system. We hypothesized that visible dilated perivascular spaces, possible glymphatic pathways, would be more prevalent in patients with idiopathic intracranial hypertension. This prevalence could provide a biomarker and add evidence to the glymphatic connection in the pathogenesis of idiopathic intracranial hypertension. MATERIALS AND METHODS We evaluated 36 adult (older than 21 years of age) patients with idiopathic intracranial hypertension and 19 controls, 21-69 years of age, who underwent a standardized MR imaging protocol that included high-resolution precontrast T2- and T1-weighted images. All patients had complete neuro-ophthalmic examinations for papilledema. The number of visible perivascular spaces was evaluated using a comprehensive 4-point qualitative rating scale, which graded the number of visible perivascular spaces in the centrum semiovale and basal ganglia; a 2-point scale was used for the midbrain. Readers were blinded to patient diagnoses. Continuous variables were compared using a Student t test. RESULTS The mean number of visible perivascular spaces overall was greater in the idiopathic intracranial hypertension group than in controls (4.5 [SD, 1.9] versus 2.9 [SD, 1.9], respectively; P = .004). This finding was significant for centrum semiovale idiopathic intracranial hypertension (2.3 [SD, 1.4] versus controls, 1.3 [SD, 1.1], P = .003) and basal ganglia idiopathic intracranial hypertension (1.7 [SD, 0.6] versus controls, 1.2 [SD, 0.7], P = .009). There was no significant difference in midbrain idiopathic intracranial hypertension (0.5 [SD, 0.5] versus controls, 0.4 [SD, 0.5], P = .47). CONCLUSIONS Idiopathic intracranial hypertension is associated with an increased number of visible intracranial perivascular spaces. This finding provides insight into the pathophysiology of idiopathic intracranial hypertension, suggesting a possible relationship between idiopathic intracranial hypertension and glymphatic dysfunction and providing another useful biomarker for the disease.
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Affiliation(s)
- O Jones
- From the Departments of Radiology (O.J., J.H., W.B.)
| | | | - J Chen
- Neurology (J.C.-G., J.C., M.T.B.)
- Ophthalmology (J.C., M.T.B.), Mayo Clinic, Rochester, Minnesota
| | - M T Bhatti
- Neurology (J.C.-G., J.C., M.T.B.)
- Ophthalmology (J.C., M.T.B.), Mayo Clinic, Rochester, Minnesota
| | - J Huston
- From the Departments of Radiology (O.J., J.H., W.B.)
| | - W Brinjikji
- From the Departments of Radiology (O.J., J.H., W.B.)
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36
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Zhang Z, Zhou H, Liu X, Liu L, Shu S, Fang F. Identification of the clinical and neuroimaging characteristics in children with neuromyelitis optica spectrum disorders: a case series. Transl Pediatr 2021; 10:2459-2466. [PMID: 34765469 PMCID: PMC8578765 DOI: 10.21037/tp-21-370] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Accepted: 09/07/2021] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Childhood neuromyelitis optica spectrum disorders (NMOSDs) may cause visual impairment and brain or spinal cord damage, and the effects may be permanent if left untreated. Since the incidence of NMOSD cases in children is relatively low, the understanding of NMOSD among children is inadequate. METHODS This investigation examined the clinical and neuroimaging characteristics of childhood NMOSD. We retrospectively analyzed the clinical information of 11 NMOSD patients admitted to our centre from 2012 to 2021. The disease status was assessed by the Expanded Disability Status Scale (EDSS) score. RESULTS The two major symptoms observed in the study cohort were optic neuritis (ON) (9/11) and encephalopathy (7/11). Antibody tests were performed on 8 children, 2 of whom showed serum aquaporin 4 (AQP4) antibody positivity, and another 2 presented with serum myelin oligodendrocyte glycoprotein (MOG) antibody positivity. All patients showed white matter hyperintensity on magnetic resonance imaging (MRI) scans. Interestingly, a rare radiological sign, enlarged perivascular space (PVS), which is more commonly observed in the elderly or adults, was found in 4 participants with more severe clinical manifestations. CONCLUSIONS While NMOSD in children is less commonly diagnosed through clinical evaluations, the symptoms of ON and encephalopathy should raise the possibility of the disease. As the diagnosis of NMOSD in children is relatively difficult, enlarged PVS may represent a promising biomarker for the diagnosis and evaluation of NMOSD.
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Affiliation(s)
- Zhan Zhang
- Department of Paediatrics, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Hua Zhou
- Department of Paediatrics, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xinglou Liu
- Department of Paediatrics, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Lingling Liu
- Department of Paediatrics, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Sainan Shu
- Department of Paediatrics, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Feng Fang
- Department of Paediatrics, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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37
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Immune cell compartmentalization for brain surveillance and protection. Nat Immunol 2021; 22:1083-1092. [PMID: 34429552 DOI: 10.1038/s41590-021-00994-2] [Citation(s) in RCA: 101] [Impact Index Per Article: 33.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Accepted: 07/08/2021] [Indexed: 02/07/2023]
Abstract
For decades, it was commonly accepted that the brain is secluded from peripheral immune activity and is self-sufficient for its maintenance and repair. This simplistic perception was based on the presence of resident immune cells, the microglia, and barrier systems within the brain, and the assumption that the central nervous system (CNS) lacks lymphatic drainage. This view was revised with the discoveries that higher functions of the CNS, homeostasis and repair are supported by peripheral innate and adaptive immune cells. The findings of bone marrow-derived immune cells in specialized niches, and the renewed observation that a lymphatic drainage system exists within the brain, further contributed to this revised model. In this Review, we describe the immune niches within the brain, the contribution of professional immune cells to brain functions, the bidirectional relationships between the CNS and the immune system and the relevance of immune components to brain aging and neurodegenerative diseases.
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38
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Beaudoin AM, Rheault F, Theaud G, Laberge F, Whittingstall K, Lamontagne A, Descoteaux M. Modern Technology in Multi-Shell Diffusion MRI Reveals Diffuse White Matter Changes in Young Adults With Relapsing-Remitting Multiple Sclerosis. Front Neurosci 2021; 15:665017. [PMID: 34447292 PMCID: PMC8383891 DOI: 10.3389/fnins.2021.665017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2021] [Accepted: 07/20/2021] [Indexed: 11/13/2022] Open
Abstract
Objective To characterize microstructural white matter changes related to relapsing-remitting multiple sclerosis using advanced diffusion MRI modeling and tractography. The association between imaging data and patient’s cognitive performance, fatigue severity and depressive symptoms is also explored. Methods In this cross-sectional study, 24 relapsing-remitting multiple sclerosis patients and 11 healthy controls were compared using high angular resolution diffusion imaging (HARDI). The imaging method includes a multi-shell scheme, free water correction to obtain tissue-specific measurements, probabilistic tracking algorithm robust to crossing fibers and white matter lesions, automatic streamlines and bundle dissection and tract-profiling with tractometry. The neuropsychological evaluation included the Symbol Digit Modalities Test, Paced Auditory Serial Addition Test, Modified Fatigue Impact Scale and Beck Depression Inventory-II. Results Bundle-wise analysis by tractometry revealed a difference between patients and controls for 11 of the 14 preselected white matter bundles. In patients, free water corrected fractional anisotropy was significantly reduced while radial and mean diffusivities were increased, consistent with diffuse demyelination. The fornix and left inferior fronto-occipital fasciculus exhibited a higher free water fraction. Eight bundles showed an increase in total apparent fiber density and four bundles had a higher number of fiber orientations, suggesting axonal swelling and increased organization complexity, respectively. In the association study, depressive symptoms were associated with diffusion abnormalities in the right superior longitudinal fasciculus. Conclusion Tissue-specific diffusion measures showed abnormalities along multiple cerebral white matter bundles in patients with relapsing-remitting multiple sclerosis. The proposed methodology combines free-water imaging, advanced bundle dissection and tractometry, which is a novel approach to investigate cerebral pathology in multiple sclerosis. It opens a new window of use for HARDI-derived measures and free water corrected diffusion measures. Advanced diffusion MRI provides a better insight into cerebral white matter changes in relapsing-remitting multiple sclerosis, namely diffuse demyelination, edema and increased fiber density and complexity.
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Affiliation(s)
- Ann-Marie Beaudoin
- Department of Neurology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - François Rheault
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Guillaume Theaud
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Frédéric Laberge
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Kevin Whittingstall
- Department of Radiology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Albert Lamontagne
- Department of Neurology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Université de Sherbrooke, Sherbrooke, QC, Canada
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39
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George IC, Arrighi-Allisan A, Delman BN, Balchandani P, Horng S, Feldman R. A Novel Method to Measure Venular Perivascular Spaces in Patients with MS on 7T MRI. AJNR Am J Neuroradiol 2021; 42:1069-1072. [PMID: 33858821 DOI: 10.3174/ajnr.a7144] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Accepted: 01/25/2021] [Indexed: 11/07/2022]
Abstract
In MS, inflammatory cells accumulate within the perivascular spaces of acute and chronic lesions. Reliance on perivascular spaces as biomarkers for MS remains uncertain because various studies have reported inconsistencies in perivascular space anatomy. Distinguishing between venular and arteriolar perivascular spaces is pathophysiologically relevant in MS. In this pilot study, we leverage susceptibility-weighted imaging at 7T to better identify perivascular spaces of venular distribution on corresponding high-resolution T2 images.
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Affiliation(s)
- I C George
- Drom the Department of Neurology (I.C.G.), Massachusetts General Hospital, Boston, Massachusetts
| | - A Arrighi-Allisan
- Department of Medical Education (A.A.-A.), Icahn School of Medicine at Mount Sinai, New York, New York
| | - B N Delman
- Department of Diagnostic, Molecular and Interventional Radiology (B.N.D., P.B.), Icahn School of Medicine at Mount Sinai, New York, New York
| | - P Balchandani
- BioMedical Engineering and Imaging Institute (P.B.), Icahn School of Medicine at Mount Sinai, New York, New York
| | - S Horng
- Department of Neurology (S.H.), Icahn School of Medicine at Mount Sinai, New York, New York
| | - R Feldman
- Departments of Computer Science, Mathematics, Physics, and Statistics (R.F.), University of British Columbia, Kelowna, British Columbia, Canada
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40
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Wooliscroft L, Boespflug E, Hildebrand A, Shangraw K, Silbermann E, Bourdette D, Spain R. Enlarged perivascular spaces are not associated with vascular co-morbidities, clinical outcomes, and brain volumes in people with secondary progressive multiple sclerosis. Mult Scler J Exp Transl Clin 2020; 6:2055217320964502. [PMID: 33110618 PMCID: PMC7557790 DOI: 10.1177/2055217320964502] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Accepted: 09/15/2020] [Indexed: 11/27/2022] Open
Abstract
In secondary progressive multiple sclerosis (SPMS) significance of enlarged perivascular spaces (ePVS) is unknown. Objectives, Methods: Analysis of associations between vascular co-morbidities, clinical outcomes, and volumetrics with categorical ePVS scores in midbrain, basal ganglia (BG), and centrum semiovale (CSO) in SPMS(n-46). Results, Conclusion: In BG, advancing age (Z = 2.68) and lower Expanded Disability Status Scale (Z = −2.04) were associated with increasing ePVS score. In CSO, advancing age (Z = 2.66) and male gender (Z = 2.45) were associated with increasing ePVS score. No associations between ePVS score and vascular co-morbidities or volumetrics existed; ePVS may not be an informative marker for SPMS.
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Affiliation(s)
| | - Erin Boespflug
- Neurology, Oregon Health & Science University, Portland, OR, USA
| | | | - Kathleen Shangraw
- Neurology, Oregon Health & Science University, Portland, OR, USA.,Neurology, Veterans Affairs Portland Health Care System, Portland, OR, USA
| | | | - Dennis Bourdette
- Neurology, Oregon Health & Science University, Portland, OR, USA.,Neurology, Veterans Affairs Portland Health Care System, Portland, OR, USA
| | - Rebecca Spain
- Neurology, Oregon Health & Science University, Portland, OR, USA.,Neurology, Veterans Affairs Portland Health Care System, Portland, OR, USA
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