1
|
Gallina P, Lolli F. Fluctuation in body size and glymphatic system derangement in obesity. Int J Obes (Lond) 2024; 48:1351-1352. [PMID: 38879727 DOI: 10.1038/s41366-024-01567-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2024] [Revised: 06/04/2024] [Accepted: 06/10/2024] [Indexed: 08/28/2024]
Affiliation(s)
- Pasquale Gallina
- Department of Neurosciences, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy.
| | - Francesco Lolli
- Department of Clinical and Experimental Biomedical Sciences "Mario Serio", University of Florence, Florence, Italy
| |
Collapse
|
2
|
Huang P, Liu L, Zhang Y, Zhong S, Liu P, Hong H, Wang S, Xie L, Lin M, Jiaerken Y, Luo X, Li K, Zeng Q, Cui L, Li J, Chen Y, Zhang R. Development and validation of a perivascular space segmentation method in multi-center datasets. Neuroimage 2024; 298:120803. [PMID: 39181194 DOI: 10.1016/j.neuroimage.2024.120803] [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: 05/22/2024] [Revised: 08/16/2024] [Accepted: 08/20/2024] [Indexed: 08/27/2024] Open
Abstract
BACKGROUND Perivascular spaces (PVS) visible on magnetic resonance imaging (MRI) are significant markers associated with various neurological diseases. Although quantitative analysis of PVS may enhance sensitivity and improve consistency across studies, the field lacks a universally validated method for analyzing images from multi-center studies. METHODS We annotated PVS on multi-center 3D T1-weighted (T1w) images acquired using scanners from three major vendors (Siemens, General Electric, and Philips). A neural network, mcPVS-Net (multi-center PVS segmentation network), was trained using data from 40 subjects and then tested in a separate cohort of 15 subjects. We assessed segmentation accuracy against ground truth masks tailored for each scanner vendor. Additionally, we evaluated the agreement between segmented PVS volumes and visual scores for each scanner. We also explored correlations between PVS volumes and various clinical factors such as age, hypertension, and white matter hyperintensities (WMH) in a larger sample of 1020 subjects. Furthermore, mcPVS-Net was applied to a new dataset comprising both T1w and T2-weighted (T2w) images from a United Imaging scanner to investigate if PVS volumes could discriminate between subjects with differing visual scores. We also compared the mcPVS-Net with a previously published method that segments PVS from T1 images. RESULTS In the test dataset, mcPVS-Net achieved a mean DICE coefficient of 0.80, with an average Precision of 0.81 and Recall of 0.79, indicating good specificity and sensitivity. The segmented PVS volumes were significantly associated with visual scores in both the basal ganglia (r = 0.541, p < 0.001) and white matter regions (r = 0.706, p < 0.001), and PVS volumes were significantly different among subjects with varying visual scores. Segmentation performance was consistent across different scanner vendors. PVS volumes exhibited significant associations with age, hypertension, and WMH. In the United Imaging scanner dataset, PVS volumes showed good associations with PVS visual scores evaluated on either T1w or T2w images. Compared to a previously published method, mcPVS-Net showed a higher accuracy and improved PVS segmentation in the basal ganglia region. CONCLUSION The mcPVS-Net demonstrated good accuracy for segmenting PVS from 3D T1w images. It may serve as a useful tool for future PVS research.
Collapse
Affiliation(s)
- Peiyu Huang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China; Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Lingyun Liu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China; Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Yao Zhang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Siyan Zhong
- Department of Neurology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Peng Liu
- Department of Radiology, Linyi Traditional Chinese Medicine Hospital, Linyi, China
| | - Hui Hong
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Shuyue Wang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Linyun Xie
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Miao Lin
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yeerfan Jiaerken
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xiao Luo
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Kaicheng Li
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Qingze Zeng
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Lei Cui
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jixuan Li
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yanxing Chen
- Department of Neurology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Ruiting Zhang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
| |
Collapse
|
3
|
Waymont JMJ, Valdés Hernández MDC, Bernal J, Duarte Coello R, Brown R, Chappell FM, Ballerini L, Wardlaw JM. Systematic review and meta-analysis of automated methods for quantifying enlarged perivascular spaces in the brain. Neuroimage 2024; 297:120685. [PMID: 38914212 DOI: 10.1016/j.neuroimage.2024.120685] [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: 03/18/2024] [Revised: 05/20/2024] [Accepted: 06/10/2024] [Indexed: 06/26/2024] Open
Abstract
Research into magnetic resonance imaging (MRI)-visible perivascular spaces (PVS) has recently increased, as results from studies in different diseases and populations are cementing their association with sleep, disease phenotypes, and overall health indicators. With the establishment of worldwide consortia and the availability of large databases, computational methods that allow to automatically process all this wealth of information are becoming increasingly relevant. Several computational approaches have been proposed to assess PVS from MRI, and efforts have been made to summarise and appraise the most widely applied ones. We systematically reviewed and meta-analysed all publications available up to September 2023 describing the development, improvement, or application of computational PVS quantification methods from MRI. We analysed 67 approaches and 60 applications of their implementation, from 112 publications. The two most widely applied were the use of a morphological filter to enhance PVS-like structures, with Frangi being the choice preferred by most, and the use of a U-Net configuration with or without residual connections. Older adults or population studies comprising adults from 18 years old onwards were, overall, more frequent than studies using clinical samples. PVS were mainly assessed from T2-weighted MRI acquired in 1.5T and/or 3T scanners, although combinations using it with T1-weighted and FLAIR images were also abundant. Common associations researched included age, sex, hypertension, diabetes, white matter hyperintensities, sleep and cognition, with occupation-related, ethnicity, and genetic/hereditable traits being also explored. Despite promising improvements to overcome barriers such as noise and differentiation from other confounds, a need for joined efforts for a wider testing and increasing availability of the most promising methods is now paramount.
Collapse
Affiliation(s)
- Jennifer M J Waymont
- Centre for Clinical Brain Sciences, the University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK; UK Dementia Research Institute Centre at the University of Edinburgh, UK
| | - Maria Del C Valdés Hernández
- Centre for Clinical Brain Sciences, the University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK; UK Dementia Research Institute Centre at the University of Edinburgh, UK.
| | - José Bernal
- Centre for Clinical Brain Sciences, the University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK; UK Dementia Research Institute Centre at the University of Edinburgh, UK; German Centre for Neurodegenerative Diseases (DZNE), Germany; Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke University Magdeburg, Germany
| | - Roberto Duarte Coello
- Centre for Clinical Brain Sciences, the University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK; UK Dementia Research Institute Centre at the University of Edinburgh, UK
| | - Rosalind Brown
- Centre for Clinical Brain Sciences, the University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK; UK Dementia Research Institute Centre at the University of Edinburgh, UK
| | - Francesca M Chappell
- Centre for Clinical Brain Sciences, the University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK; UK Dementia Research Institute Centre at the University of Edinburgh, UK
| | | | - Joanna M Wardlaw
- Centre for Clinical Brain Sciences, the University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK; UK Dementia Research Institute Centre at the University of Edinburgh, UK
| |
Collapse
|
4
|
Walter AE, Savalia K, Yoon J, Morrison J, Schneider ALC, Diaz-Arrastia R, Sandsmark DK. Change in Enlarged Perivascular Spaces over Time and Associations with Outcomes After Traumatic Brain Injury. Neurotrauma Rep 2024; 5:738-748. [PMID: 39144451 PMCID: PMC11319858 DOI: 10.1089/neur.2024.0026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/16/2024] Open
Abstract
Enlarged perivascular spaces (EPVs) can be seen on magnetic resonance imaging (MRI) scans in various neurological diseases, including traumatic brain injury (TBI). EPVs have been associated with cognitive dysfunction and sleep disturbances; however, their clinical significance remains unclear. The goal of this study was to identify MRI burden of EPVs over time following TBI and to explore their relationship with postinjury outcomes. Individuals with TBI underwent postinjury data collection at Day 1 (blood), 2 weeks (blood, MRI, outcomes), and 6 months (blood, MRI, outcomes). EPV burden was assessed using T1 and FLAIR sequences on representative slices in the centrum semiovale, basal ganglia, and midbrain. Serum blood was assayed to measure concentrations of neurofilament light (NfL) and glial fibrillary acidic protein (GFAP). Thirty-two participants with TBI were included (mean age 36.8 years, 78% male, 50% White). Total EPVs count did not significantly change from 2 weeks (23.5 [95% confidence interval or CI = 22.0-32.0]) to 6 months (26.0 [95% CI = 22.0-30.0], p = 0.16). For self-reported measures of sleep, there were no significant associations between EPVs count and Insomnia Severity Index (2 weeks: β = -0.004; 95% CI = -0.094, 0.086; 6 months: β = 0.002; 95% CI = -0.122, 0.125) or the subset of sleep questions on the Rivermead Post-Concussion Symptoms Questionnaire (2 weeks: β = -0.005; 95% CI = -0.049, 0.039; 6 months: β = -0.019; 95% CI = -0.079, 0.042). Functional outcome, determined by 6 months incomplete recovery (Glasgow Outcome Scale-Extended [GOS-E < 8]) versus complete recovery (GOS-E = 8), was significantly associated with a higher number of EPVs at 2 weeks (odds ratio = 0.94, 95% CI = 0.88-0.99). Spearman correlations showed no significant relationship between EPVs count and GFAP or NfL. This study used commonly acquired MRI sequences to quantify EPVs and investigated their utility as a potential imaging biomarker in TBI. Given the minimal change in EPVs over time, this period may not be long enough for potential recovery or may indicate that EPVs are structural findings that do not significantly change over time.
Collapse
Affiliation(s)
- Alexa E. Walter
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Krupa Savalia
- Departments of Neurology and Neurological Surgery, University of California Davis, Davis, California, USA
| | - Jason Yoon
- Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Justin Morrison
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Andrea L. C. Schneider
- Departments of Neurology and Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Ramon Diaz-Arrastia
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Danielle K. Sandsmark
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| |
Collapse
|
5
|
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.
Collapse
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
| |
Collapse
|
6
|
Gallina P, Porfirio B, Caini S, Lolli F, Scollato A. Aqueductal CSF stroke volume is associated with the burden of perivascular space enlargement in chronic adult hydrocephalus. Sci Rep 2024; 14:12966. [PMID: 38839864 PMCID: PMC11153584 DOI: 10.1038/s41598-024-63926-8] [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: 09/14/2023] [Accepted: 06/03/2024] [Indexed: 06/07/2024] Open
Abstract
The inflow of CSF into perivascular spaces (PVS) in the brain is crucial for clearing waste molecules. Inefficiency in PVS flow leads to neurodegeneration. Failure of PVS flushing is associated with CSF flow impairment in the intracranial hydrodynamic condition of CSF hypo-pulsatility. However, enlarged PVS (ePVS), a finding indicative of PVS flow dysfunction, is also present in patients with derangement of CSF dynamics characterized by CSF hyper-pulsatility, which increases CSF flow. Intriguingly, two opposite intracranial hydrodynamic conditions would lead to the same result of impairing the PVS flushing. To investigate this issue, we assessed the subsistence of a dysfunctional interplay between CSF and PVS flows and, if the case, the mechanisms preventing a hyper-pulsatile brain from providing an effective PVS flushing. We analyzed the association between phase contrast MRI aqueductal CSF stroke volume (aqSV), a proxy of CSF pulsatility, and the burden of ePVS in chronic adult hydrocephalus, a disease involving a broad spectrum of intracranial hydrodynamics disturbances. In the 147 (85 males, 62 females) patients, the age at diagnosis ranged between 28 and 88 years (median 73 years). Ninety-seven patients had tri-ventriculomegaly and 50 tetra-ventriculomegaly. According to the extent of ePVS, 113 patients had a high ePVS burden, while 34 had a low ePVS burden. aqSV, which ranged between 0 and 562 μL (median 86 μL), was increased with respect to healthy subjects. Patients presenting with less ePVS burden had higher aqSV (p < 0.002, corrected for the multiple comparisons) than those with higher ePVS burden. The present study confirmed the association between CSF dynamics and PVS flow disturbances and demonstrated this association in intracranial hyper-pulsatility. Further studies should investigate the association between PVS flow failure and CSF hypo- and hyper-pulsatility as responsible/co-responsible for glymphatic failure in other neurodegenerative diseases, particularly in diseases in which CSF disturbances can be corrected, as in chronic adult hydrocephalus.
Collapse
Affiliation(s)
- Pasquale Gallina
- Neurosurgery Unit, CTO Hospital, Careggi University Hospital, Largo P Palagi 1, 50139, Florence, Italy.
- Department of Neurosciences, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy.
| | - Berardino Porfirio
- Department of Clinical and Experimental Biomedical Sciences "Mario Serio", University of Florence, Florence, Italy
| | - Saverio Caini
- Cancer Risk Factors and Lifestyle Epidemiology Unit, Institute for Cancer Research, Prevention, and Clinical Network, Florence, Italy
| | - Francesco Lolli
- Department of Clinical and Experimental Biomedical Sciences "Mario Serio", University of Florence, Florence, Italy
- Neurophysiology Unit, Careggi University Hospital, Florence, Italy
| | - Antonio Scollato
- Neurosurgery Unit, "Cardinale Panico" Hospital, Tricase, Lecce, Italy
| |
Collapse
|
7
|
Braun M, Sevao M, Keil SA, Gino E, Wang MX, Lee J, Haveliwala MA, Klein E, Agarwal S, Pedersen T, Rhodes CH, Jansson D, Cook D, Peskind E, Perl DP, Piantino J, Schindler AG, Iliff JJ. Macroscopic changes in aquaporin-4 underlie blast traumatic brain injury-related impairment in glymphatic function. Brain 2024; 147:2214-2229. [PMID: 38802114 PMCID: PMC11146423 DOI: 10.1093/brain/awae065] [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: 09/22/2023] [Revised: 01/10/2024] [Accepted: 02/06/2024] [Indexed: 05/29/2024] Open
Abstract
Mild traumatic brain injury (mTBI) has emerged as a potential risk factor for the development of neurodegenerative conditions such as Alzheimer's disease and chronic traumatic encephalopathy. Blast mTBI, caused by exposure to a pressure wave from an explosion, is predominantly experienced by military personnel and has increased in prevalence and severity in recent decades. Yet the underlying pathology of blast mTBI is largely unknown. We examined the expression and localization of AQP4 in human post-mortem frontal cortex and observed distinct laminar differences in AQP4 expression following blast exposure. We also observed similar laminar changes in AQP4 expression and localization and delayed impairment of glymphatic function that emerged 28 days following blast injury in a mouse model of repetitive blast mTBI. In a cohort of veterans with blast mTBI, we observed that blast exposure was associated with an increased burden of frontal cortical MRI-visible perivascular spaces, a putative neuroimaging marker of glymphatic perivascular dysfunction. These findings suggest that changes in AQP4 and delayed glymphatic impairment following blast injury may render the post-traumatic brain vulnerable to post-concussive symptoms and chronic neurodegeneration.
Collapse
Affiliation(s)
- Molly Braun
- VISN 20 Northwest Mental Illness Research, Education and Clinical Center (MIRECC), VA Puget Sound Health Care System, Seattle, WA 98108, USA
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
- Department of Neurosurgery, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA
| | - Mathew Sevao
- VISN 20 Northwest Mental Illness Research, Education and Clinical Center (MIRECC), VA Puget Sound Health Care System, Seattle, WA 98108, USA
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Samantha A Keil
- VISN 20 Northwest Mental Illness Research, Education and Clinical Center (MIRECC), VA Puget Sound Health Care System, Seattle, WA 98108, USA
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Elizabeth Gino
- VISN 20 Northwest Mental Illness Research, Education and Clinical Center (MIRECC), VA Puget Sound Health Care System, Seattle, WA 98108, USA
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Marie X Wang
- VISN 20 Northwest Mental Illness Research, Education and Clinical Center (MIRECC), VA Puget Sound Health Care System, Seattle, WA 98108, USA
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Janet Lee
- VISN 20 Geriatric Research, Education and Clinical Center (GRECC), VA Puget Sound Health Care System, Seattle, WA 98108, USA
| | - Mariya A Haveliwala
- VISN 20 Northwest Mental Illness Research, Education and Clinical Center (MIRECC), VA Puget Sound Health Care System, Seattle, WA 98108, USA
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Emily Klein
- VISN 20 Northwest Mental Illness Research, Education and Clinical Center (MIRECC), VA Puget Sound Health Care System, Seattle, WA 98108, USA
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Sanjana Agarwal
- VISN 20 Northwest Mental Illness Research, Education and Clinical Center (MIRECC), VA Puget Sound Health Care System, Seattle, WA 98108, USA
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Taylor Pedersen
- VISN 20 Northwest Mental Illness Research, Education and Clinical Center (MIRECC), VA Puget Sound Health Care System, Seattle, WA 98108, USA
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - C Harker Rhodes
- Henry M. Jackson Foundation for the Advancement of Military Medicine Inc., Bethesda, MD 20817, USA
- Department of Pathology, F Edward Hébert School of Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA
- DoD/USU Brain Tissue Repository, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA
| | - Deidre Jansson
- VISN 20 Northwest Mental Illness Research, Education and Clinical Center (MIRECC), VA Puget Sound Health Care System, Seattle, WA 98108, USA
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - David Cook
- VISN 20 Geriatric Research, Education and Clinical Center (GRECC), VA Puget Sound Health Care System, Seattle, WA 98108, USA
- Department of Medicine, Division of Gerontology and Geriatric Medicine, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Elaine Peskind
- VISN 20 Northwest Mental Illness Research, Education and Clinical Center (MIRECC), VA Puget Sound Health Care System, Seattle, WA 98108, USA
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Daniel P Perl
- Department of Pathology, F Edward Hébert School of Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA
- DoD/USU Brain Tissue Repository, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA
| | - Juan Piantino
- Division of Child Neurology, Department of Pediatrics, Doernbecher Children’s Hospital, Oregon Health & Science University, Portland, OR 97239, USA
| | - Abigail G Schindler
- VISN 20 Northwest Mental Illness Research, Education and Clinical Center (MIRECC), VA Puget Sound Health Care System, Seattle, WA 98108, USA
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
- VISN 20 Geriatric Research, Education and Clinical Center (GRECC), VA Puget Sound Health Care System, Seattle, WA 98108, USA
- Department of Medicine, Division of Gerontology and Geriatric Medicine, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Jeffrey J Iliff
- VISN 20 Northwest Mental Illness Research, Education and Clinical Center (MIRECC), VA Puget Sound Health Care System, Seattle, WA 98108, USA
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
- Department of Neurology, University of Washington School of Medicine, Seattle, WA 98195, USA
| |
Collapse
|
8
|
Barisano G, Iv M, Choupan J, Hayden-Gephart M. Cerebral perivascular spaces as predictors of dementia risk and accelerated brain atrophy. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.25.24306324. [PMID: 38712073 PMCID: PMC11071547 DOI: 10.1101/2024.04.25.24306324] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Cerebral small vessel disease, an important risk factor for dementia, lacks robust, in vivo measurement methods. Perivascular spaces (PVS) on brain MRI are surrogates for small parenchymal blood vessels and their perivascular compartment, and may relate to brain health. We developed a novel, robust algorithm to automatically assess PVS count and size on MRI, and investigated their relationship with dementia risk and brain atrophy. We analyzed 46,478 clinical measurements of cognitive functioning and 20,845 brain MRI scans from 10,004 participants (71.1±9.7 years-old, 56.6% women). Fewer PVS and larger PVS diameter at baseline were associated with higher dementia risk and accelerated brain atrophy. Longitudinal trajectories of PVS markers were significantly different in non-demented individuals who converted to dementia compared with non-converters. In simulated placebo-controlled trials for treatments targeting cognitive decline, screening out participants less likely to develop dementia based on our PVS markers enhanced the power of the trial. These novel radiographic cerebrovascular markers may improve risk-stratification of individuals, potentially reducing cost and increasing throughput of clinical trials to combat dementia.
Collapse
Affiliation(s)
| | - Michael Iv
- Department of Radiology, Stanford University, Stanford, CA, USA
| | | | - Jeiran Choupan
- Laboratory of Neuro Imaging, University of Southern California, Los Angeles, CA, USA
| | | |
Collapse
|
9
|
Valdés Hernández MDC, Duarte Coello R, Xu W, Bernal J, Cheng Y, Ballerini L, Wiseman SJ, Chappell FM, Clancy U, Jaime García D, Arteaga Reyes C, Zhang JF, Liu X, Hewins W, Stringer M, Doubal F, Thrippleton MJ, Jochems A, Brown R, Wardlaw JM. Influence of threshold selection and image sequence in in-vivo segmentation of enlarged perivascular spaces. J Neurosci Methods 2024; 403:110037. [PMID: 38154663 DOI: 10.1016/j.jneumeth.2023.110037] [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: 09/30/2023] [Revised: 12/06/2023] [Accepted: 12/17/2023] [Indexed: 12/30/2023]
Abstract
BACKGROUND Growing interest surrounds perivascular spaces (PVS) as a clinical biomarker of brain dysfunction given their association with cerebrovascular risk factors and disease. Neuroimaging techniques allowing quick and reliable quantification are being developed, but, in practice, they require optimisation as their limits of validity are usually unspecified. NEW METHOD We evaluate modifications and alternatives to a state-of-the-art (SOTA) PVS segmentation method that uses a vesselness filter to enhance PVS discrimination, followed by thresholding of its response, applied to brain magnetic resonance images (MRI) from patients with sporadic small vessel disease acquired at 3 T. RESULTS The method is robust against inter-observer differences in threshold selection, but separate thresholds for each region of interest (i.e., basal ganglia, centrum semiovale, and midbrain) are required. Noise needs to be assessed prior to selecting these thresholds, as effect of noise and imaging artefacts can be mitigated with a careful optimisation of these thresholds. PVS segmentation from T1-weighted images alone, misses small PVS, therefore, underestimates PVS count, may overestimate individual PVS volume especially in the basal ganglia, and is susceptible to the inclusion of calcified vessels and mineral deposits. Visual analyses indicated the incomplete and fragmented detection of long and thin PVS as the primary cause of errors, with the Frangi filter coping better than the Jerman filter. COMPARISON WITH EXISTING METHODS Limits of validity to a SOTA PVS segmentation method applied to 3 T MRI with confounding pathology are given. CONCLUSIONS Evidence presented reinforces the STRIVE-2 recommendation of using T2-weighted images for PVS assessment wherever possible. The Frangi filter is recommended for PVS segmentation from MRI, offering robust output against variations in threshold selection and pathology presentation.
Collapse
Affiliation(s)
- Maria Del C Valdés Hernández
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK.
| | - Roberto Duarte Coello
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| | - William Xu
- College of Medicine and Veterinary Medicine, University of Edinburgh, Edinburgh, UK
| | - José Bernal
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK; German Centre for Neurodegenerative Diseases (DZNE), Magdeburg, Germany; Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke University Magdeburg, Magdeburg, Germany
| | - Yajun Cheng
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, China
| | - Lucia Ballerini
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK; University for Foreigner of Perugia, Perugia, Italy
| | - Stewart J Wiseman
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| | - Francesca M Chappell
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| | - Una Clancy
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| | - Daniela Jaime García
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| | - Carmen Arteaga Reyes
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| | - Jun-Fang Zhang
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK; Department of Neurology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiaodi Liu
- Division of Neurology, Department of Medicine, The University of Hong Kong, Hong Kong
| | - Will Hewins
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| | - Michael Stringer
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| | - Fergus Doubal
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| | - Michael J Thrippleton
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| | - Angela Jochems
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| | - Rosalind Brown
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| | - Joanna M Wardlaw
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| |
Collapse
|
10
|
Richmond SB, Seidler RD, Iliff JJ, Schwartz DL, Luther M, Silbert LC, Wood SJ, Bloomberg JJ, Mulder E, Lee JK, De Luca A, Piantino J. Dynamic changes in perivascular space morphology predict signs of spaceflight-associated neuro-ocular syndrome in bed rest. NPJ Microgravity 2024; 10:24. [PMID: 38429289 PMCID: PMC10907584 DOI: 10.1038/s41526-024-00368-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Accepted: 02/15/2024] [Indexed: 03/03/2024] Open
Abstract
During long-duration spaceflight, astronauts experience headward fluid shifts and expansion of the cerebral perivascular spaces (PVS). A major limitation to our understanding of the changes in brain structure and physiology induced by spaceflight stems from the logistical difficulties of studying astronauts. The current study aimed to determine whether PVS changes also occur on Earth with the spaceflight analog head-down tilt bed rest (HDBR). We examined how the number and morphology of magnetic resonance imaging-visible PVS (MV-PVS) are affected by HDBR with and without elevated carbon dioxide (CO2). These environments mimic the headward fluid shifts, body unloading, and elevated CO2 observed aboard the International Space Station. Additionally, we sought to understand how changes in MV-PVS are associated with signs of Spaceflight Associated Neuro-ocular Syndrome (SANS), ocular structural alterations that can occur with spaceflight. Participants were separated into two bed rest campaigns: HDBR (60 days) and HDBR + CO2 (30 days with elevated ambient CO2). Both groups completed multiple magnetic resonance image acquisitions before, during, and post-bed rest. We found that at the group level, neither spaceflight analog affected MV-PVS quantity or morphology. However, when taking into account SANS status, persons exhibiting signs of SANS showed little or no MV-PVS changes, whereas their No-SANS counterparts showed MV-PVS morphological changes during the HDBR + CO2 campaign. These findings highlight spaceflight analogs as models for inducing changes in MV-PVS and implicate MV-PVS dynamic compliance as a mechanism underlying SANS. These findings may lead to countermeasures to mitigate health risks associated with human spaceflight.
Collapse
Affiliation(s)
- Sutton B Richmond
- Department of Applied Physiology and Kinesiology, University of Florida, 1864, Stadium Rd., Gainesville, FL, USA
| | - Rachael D Seidler
- Department of Applied Physiology and Kinesiology, University of Florida, 1864, Stadium Rd., Gainesville, FL, USA
- Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, USA
| | - Jeffrey J Iliff
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Department of Neurology, University of Washington School of Medicine, Seattle, WA, USA
- VISN 20 Mental Illness Research, Education and Clinical Center (MIRECC), VA Puget Sound Health Care System, Seattle, WA, USA
| | - Daniel L Schwartz
- Layton-NIA Oregon Aging and Alzheimer's Disease Research Center, Department of Neurology, Oregon Health & Science University, Portland, OR, USA
- Advanced Imaging Research Center, Oregon Health & Science University, Portland, OR, USA
| | - Madison Luther
- Department of Pediatrics, Division of Child Neurology, Doernbecher Children's Hospital, Oregon Health and Science University, Portland, OR, USA
| | - Lisa C Silbert
- Layton-NIA Oregon Aging and Alzheimer's Disease Research Center, Department of Neurology, Oregon Health & Science University, Portland, OR, USA
- Veteran's Affairs Portland Health Care System, Neurology, Portland, OR, USA
| | | | | | | | - Jessica K Lee
- Department of Applied Physiology and Kinesiology, University of Florida, 1864, Stadium Rd., Gainesville, FL, USA
- German Aerospace Center (DLR), Cologne, Germany
| | - Alberto De Luca
- Department of Radiology, University Medical Center Utrecht, Utrecht, Netherlands
| | - Juan Piantino
- Department of Pediatrics, Division of Child Neurology, Doernbecher Children's Hospital, Oregon Health and Science University, Portland, OR, USA.
| |
Collapse
|
11
|
Seehafer S, Larsen N, Aludin S, Jansen O, Schmill LPA. Perivascular spaces and where to find them - MR imaging and evaluation methods. ROFO-FORTSCHR RONTG 2024. [PMID: 38408476 DOI: 10.1055/a-2254-5651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/28/2024]
Abstract
BACKGROUND Perivascular spaces (synonym: Virchow-Robin spaces) were first described over 150 years ago. They are defined as the fluid-filled spaces surrounding the small penetrating cerebral vessels. They gained growing scientific interest especially with the postulation of the so-called glymphatic system and their possible role in neurodegenerative and neuroinflammatory diseases. METHODS PubMed was used for a systematic search with a focus on literature regarding MRI imaging and evaluation methods of perivascular spaces. Studies on human in-vivo imaging were included with a focus on studies involving healthy populations. No time frame was set. The nomenclature in the literature is very heterogeneous with terms like "large", "dilated", "enlarged" perivascular spaces whereas borders and definitions often remain unclear. This work generally talks about perivascular spaces. RESULTS This review article discusses the morphologic MRI characteristics in different sequences. With the continual improvement of image quality, more and tinier structures can be depicted in detail. Visual analysis and semi or fully automated segmentation methods are briefly discussed. CONCLUSION If they are looked for, perivascular spaces are apparent in basically every cranial MRI examination. Their physiologic or pathologic value is still under debate. KEY POINTS · Perivascular spaces can be seen in basically every cranial MRI examination.. · Primarily T2-weighend sequences are used for visual analysis. Additional sequences are helpful for distinction from their differential diagnoses.. · There are promising approaches for the semi or fully automated segmentation of perivascular spaces with the possibility to collect more quantitative parameters.. CITATION FORMAT · Seehafer S, Larsen N, Aludin S et al. Perivascular spaces and where to find them - MRI imaging and evaluation methods. Fortschr Röntgenstr 2024; DOI: 10.1055/a-2254-5651.
Collapse
Affiliation(s)
- Svea Seehafer
- Clinic for Radiology and Neuroradiology, University Hospital Schleswig-Holstein - Campus Kiel, Germany
| | - Naomi Larsen
- Clinic for Radiology and Neuroradiology, University Hospital Schleswig-Holstein - Campus Kiel, Germany
| | - Schekeb Aludin
- Clinic for Radiology and Neuroradiology, University Hospital Schleswig-Holstein - Campus Kiel, Germany
| | - Olav Jansen
- Clinic for Radiology and Neuroradiology, University Hospital Schleswig-Holstein - Campus Kiel, Germany
| | | |
Collapse
|
12
|
Zhuo J, Raghavan P, Shao M, Roys S, Liang X, Tchoquessi RLN, Rhodes CS, Badjatia N, Prince JL, Gullapalli RP. Automatic Quantification of Enlarged Perivascular Space in Patients With Traumatic Brain Injury Using Super-Resolution of T2-Weighted Images. J Neurotrauma 2024; 41:407-419. [PMID: 37950721 PMCID: PMC10837035 DOI: 10.1089/neu.2023.0082] [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] [Indexed: 11/13/2023] Open
Abstract
The perivascular space (PVS) is important to brain waste clearance and brain metabolic homeostasis. Enlarged PVS (ePVS) becomes visible on magnetic resonance imaging (MRI) and is best appreciated on T2-weighted (T2w) images. However, quantification of ePVS is challenging because standard-of-care T1-weighted (T1w) and T2w images are often obtained via two-dimensional (2D) acquisition, whereas accurate quantification of ePVS normally requires high-resolution volumetric three-dimensional (3D) T1w and T2w images. The purpose of this study was to investigate the use of a deep-learning-based super-resolution (SR) technique to improve ePVS quantification from 2D T2w images for application in patients with traumatic brain injury (TBI). We prospectively recruited 26 volunteers (age: 31 ± 12 years, 12 male/14 female) where both 2D T2w and 3D T2w images were acquired along with 3D T1w images to validate the ePVS quantification using SR T2w images. We then applied the SR method to retrospectively acquired 2D T2w images in 41 patients with chronic TBI (age: 41 ± 16 years, 32 male/9 female). ePVS volumes were automatically quantified within the whole-brain white matter and major brain lobes (temporal, parietal, frontal, occipital) in all subjects. Pittsburgh Sleep Quality Index (PSQI) scores were obtained on all patients with TBI. Compared with the silver standard (3D T2w), in the validation study, the SR T2w provided similar whole-brain white matter ePVS volume (r = 0.98, p < 0.0001), and similar age-related ePVS burden increase (r = 0.80, p < 0.0001). In the patient study, patients with TBI with poor sleep showed a higher age-related ePVS burden increase than those with good sleep. Sleep status is a significant interaction factor in the whole brain (p = 0.047) and the frontal lobe (p = 0.027). We demonstrate that images produced by SR of 2D T2w images can be automatically analyzed to produce results comparable to those obtained by 3D T2 volumes. Reliable age-related ePVS burden across the whole-brain white matter was observed in all subjects. Poor sleep, affecting the glymphatic function, may contribute to the accelerated increase of ePVS burden following TBI.
Collapse
Affiliation(s)
- Jiachen Zhuo
- Center for Advanced Imaging Research, Neurosurgery, and Anesthesiology, University of Maryland School of Medicine, Baltimore, Maryland, USA
- Department of Diagnostic Radiology and Nuclear Medicine, Neurosurgery, and Anesthesiology, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Prashant Raghavan
- Department of Diagnostic Radiology and Nuclear Medicine, Neurosurgery, and Anesthesiology, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Muhan Shao
- Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, Maryland, USA
| | - Steven Roys
- Center for Advanced Imaging Research, Neurosurgery, and Anesthesiology, University of Maryland School of Medicine, Baltimore, Maryland, USA
- Department of Diagnostic Radiology and Nuclear Medicine, Neurosurgery, and Anesthesiology, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Xiao Liang
- Center for Advanced Imaging Research, Neurosurgery, and Anesthesiology, University of Maryland School of Medicine, Baltimore, Maryland, USA
- Department of Diagnostic Radiology and Nuclear Medicine, Neurosurgery, and Anesthesiology, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Rosy Linda Njonkou Tchoquessi
- Center for Advanced Imaging Research, Neurosurgery, and Anesthesiology, University of Maryland School of Medicine, Baltimore, Maryland, USA
- Department of Diagnostic Radiology and Nuclear Medicine, Neurosurgery, and Anesthesiology, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Chandler Sours Rhodes
- National Intrepid Center of Excellence, Walter Reed National Military Medical Cent5r, Bethesda, Maryland, USA
| | - Neeraj Badjatia
- Department of Neurology, Neurosurgery, and Anesthesiology, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Jerry L. Prince
- National Intrepid Center of Excellence, Walter Reed National Military Medical Cent5r, Bethesda, Maryland, USA
| | - Rao P. Gullapalli
- Center for Advanced Imaging Research, Neurosurgery, and Anesthesiology, University of Maryland School of Medicine, Baltimore, Maryland, USA
- Department of Diagnostic Radiology and Nuclear Medicine, Neurosurgery, and Anesthesiology, University of Maryland School of Medicine, Baltimore, Maryland, USA
| |
Collapse
|
13
|
Hlauschek G, Nicolo J, Sinclair B, Law M, Yasuda CL, Cendes F, Lossius MI, Kwan P, Vivash L. Role of the glymphatic system and perivascular spaces as a potential biomarker for post-stroke epilepsy. Epilepsia Open 2024; 9:60-76. [PMID: 38041607 PMCID: PMC10839409 DOI: 10.1002/epi4.12877] [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: 04/03/2023] [Accepted: 11/29/2023] [Indexed: 12/03/2023] Open
Abstract
Stroke is one of the most common causes of acquired epilepsy, which can also result in disability and increased mortality rates particularly in elderly patients. No preventive treatment for post-stroke epilepsy is currently available. Development of such treatments has been greatly limited by the lack of biomarkers to reliably identify high-risk patients. The glymphatic system, including perivascular spaces (PVS), is the brain's waste clearance system, and enlargement or asymmetry of PVS (ePVS) is hypothesized to play a significant role in the pathogenesis of several neurological conditions. In this article, we discuss potential mechanisms for the role of perivascular spaces in the development of post-stroke epilepsy. Using advanced MR-imaging techniques, it has been shown that there is asymmetry and impairment of glymphatic function in the setting of ischemic stroke. Furthermore, studies have described a dysfunction of PVS in patients with different focal and generalized epilepsy syndromes. It is thought that inflammatory processes involving PVS and the blood-brain barrier, impairment of waste clearance, and sustained hypertension affecting the glymphatic system during a seizure may play a crucial role in epileptogenesis post-stroke. We hypothesize that impairment of the glymphatic system and asymmetry and dynamics of ePVS in the course of a stroke contribute to the development of PSE. Automated ePVS detection in stroke patients might thus assist in the identification of high-risk patients for post-stroke epilepsy trials. PLAIN LANGUAGE SUMMARY: Stroke often leads to epilepsy and is one of the main causes of epilepsy in elderly patients, with no preventative treatment available. The brain's waste removal system, called the glymphatic system which consists of perivascular spaces, may be involved. Enlargement or asymmetry of perivascular spaces could play a role in this and can be visualised with advanced brain imaging after a stroke. Detecting enlarged perivascular spaces in stroke patients could help identify those at risk for post-stroke epilepsy.
Collapse
Affiliation(s)
- Gernot Hlauschek
- Division of Clinical Neuroscience, National Centre for Epilepsy, member of ERN EpicareOslo University HospitalNorway
- The University of OsloOsloNorway
- Department of Neurosciences, Central Clinical SchoolMonash UniversityMelbourneVictoriaAustralia
| | - John‐Paul Nicolo
- Department of Neurosciences, Central Clinical SchoolMonash UniversityMelbourneVictoriaAustralia
- Department of NeurologyThe AlfredMelbourneVictoriaAustralia
- Departments of Medicine and NeurologyThe University of Melbourne, Royal Melbourne HospitalParkvilleVictoriaAustralia
| | - Benjamin Sinclair
- Department of Neurosciences, Central Clinical SchoolMonash UniversityMelbourneVictoriaAustralia
- Department of NeurologyThe AlfredMelbourneVictoriaAustralia
| | - Meng Law
- Department of Neurosciences, Central Clinical SchoolMonash UniversityMelbourneVictoriaAustralia
- Department of RadiologyThe AlfredMelbourneVictoriaAustralia
| | | | | | - Morten Ingvar Lossius
- Division of Clinical Neuroscience, National Centre for Epilepsy, member of ERN EpicareOslo University HospitalNorway
- The University of OsloOsloNorway
| | - Patrick Kwan
- Department of Neurosciences, Central Clinical SchoolMonash UniversityMelbourneVictoriaAustralia
- Department of NeurologyThe AlfredMelbourneVictoriaAustralia
- Departments of Medicine and NeurologyThe University of Melbourne, Royal Melbourne HospitalParkvilleVictoriaAustralia
| | - Lucy Vivash
- Department of Neurosciences, Central Clinical SchoolMonash UniversityMelbourneVictoriaAustralia
- Department of NeurologyThe AlfredMelbourneVictoriaAustralia
- Departments of Medicine and NeurologyThe University of Melbourne, Royal Melbourne HospitalParkvilleVictoriaAustralia
| |
Collapse
|
14
|
Hlauschek G, Lossius MI, Schwartz DL, Silbert LC, Hicks AJ, Ponsford JL, Vivash L, Sinclair B, Kwan P, O'Brien TJ, Shultz SR, Law M, Spitz G. Reduced total number of enlarged perivascular spaces in post-traumatic epilepsy patients with unilateral lesions - a feasibility study. Seizure 2023; 113:1-5. [PMID: 37847935 DOI: 10.1016/j.seizure.2023.10.006] [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: 06/30/2023] [Revised: 09/21/2023] [Accepted: 10/12/2023] [Indexed: 10/19/2023] Open
Abstract
BACKGROUND We investigated the value of automated enlarged perivascular spaces (ePVS) quantification to distinguish chronic traumatic brain injury (TBI) patients with post-traumatic epilepsy (PTE+) from chronic TBI patients without PTE (PTE-) in a feasibility study. METHODS Patients with and without PTE were recruited and underwent an MRI post-TBI. Multimodal auto identification of ePVS algorithm was applied to T1-weighted MRIs to segment ePVS. The total number of ePVS was calculated and corrected for white matter volume, and an asymmetry index (AI) derived. RESULTS PTE was diagnosed in 7 out of the 99 participants (male=69) after a median time of less than one year since injury (range 10-22). Brain lesions were observed in all 7 PTE+ cases (unilateral=4, 57%; bilateral=3, 43%) as compared to 40 PTE- cases (total 44%; unilateral=17, 42%; bilateral=23, 58%). There was a significant difference between PTE+ (M=1.21e-4, IQR [8.89e-5]) and PTE- cases (M=2.79e-4, IQR [6.25e-5]) in total corrected numbers of ePVS in patients with unilateral lesions (p=0.024). No differences in AI, trauma severity and lesion volume were seen between groups. CONCLUSION This study has shown that automated quantification of ePVS is feasible and provided initial evidence that individuals with PTE with unilateral lesions may have fewer ePVS compared to TBI patients without epilepsy. Further studies with larger sample sizes should be conducted to determine the value of ePVS quantification as a PTE-biomarker.
Collapse
Affiliation(s)
- Gernot Hlauschek
- Division of Clinical Neuroscience, National Centre for Epilepsy, Oslo University Hospital, Oslo, Norway; The University of Oslo, Oslo, Norway; Department of Neurosciences, Central Clinical School, Monash University, Melbourne, Australia.
| | - Morten I Lossius
- Division of Clinical Neuroscience, National Centre for Epilepsy, Oslo University Hospital, Oslo, Norway; The University of Oslo, Oslo, Norway.
| | - Daniel L Schwartz
- Oregon Health & Science University, Oregon Alzheimer's Disease Research Center, Neurology, Advanced Imaging Research Center, USA.
| | - Lisa C Silbert
- Oregon Health & Science University, Oregon Alzheimer's Disease Research Center, Neurology, Advanced Imaging Research Center, USA.
| | - Amelia J Hicks
- Monash-Epworth Rehabilitation Research Centre, Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Australia.
| | - Jennie L Ponsford
- Monash-Epworth Rehabilitation Research Centre, Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Australia.
| | - Lucy Vivash
- Department of Neurosciences, Central Clinical School, Monash University, Melbourne, Australia; Department of Neurology, The Alfred, Melbourne, Australia,; Departments of Medicine and Neurology, The University of Melbourne, Royal Melbourne Hospital, Parkville, Australia.
| | - Benjamin Sinclair
- Department of Neurosciences, Central Clinical School, Monash University, Melbourne, Australia; Department of Neurology, The Alfred, Melbourne, Australia,.
| | - Patrick Kwan
- Department of Neurosciences, Central Clinical School, Monash University, Melbourne, Australia; Department of Neurology, The Alfred, Melbourne, Australia,; Departments of Medicine and Neurology, The University of Melbourne, Royal Melbourne Hospital, Parkville, Australia.
| | - Terrence J O'Brien
- Department of Neurosciences, Central Clinical School, Monash University, Melbourne, Australia; Department of Neurology, The Alfred, Melbourne, Australia,; Departments of Medicine and Neurology, The University of Melbourne, Royal Melbourne Hospital, Parkville, Australia.
| | - Sandy R Shultz
- Department of Neurosciences, Central Clinical School, Monash University, Melbourne, Australia; Department of Neurology, The Alfred, Melbourne, Australia,; Department of Medicine, Royal Melbourne Hospital, The University of Melbourne, Parkville, Australia; Health Sciences, Vancouver Island University, Nanaimo, Canada.
| | - Meng Law
- Department of Neurosciences, Central Clinical School, Monash University, Melbourne, Australia; Department of Radiology, The Alfred, Melbourne, Australia.
| | - Gershon Spitz
- Department of Neurosciences, Central Clinical School, Monash University, Melbourne, Australia; Monash-Epworth Rehabilitation Research Centre, Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Australia.
| |
Collapse
|
15
|
Garic D, McKinstry RC, Rutsohn J, Slomowitz R, Wolff J, MacIntyre LC, Weisenfeld LAH, Kim SH, Pandey J, St. John T, Estes AM, Schultz RT, Hazlett HC, Dager SR, Botteron KN, Styner M, Piven J, Shen MD. Enlarged Perivascular Spaces in Infancy and Autism Diagnosis, Cerebrospinal Fluid Volume, and Later Sleep Problems. JAMA Netw Open 2023; 6:e2348341. [PMID: 38113043 PMCID: PMC10731509 DOI: 10.1001/jamanetworkopen.2023.48341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Accepted: 11/03/2023] [Indexed: 12/21/2023] Open
Abstract
Importance Perivascular spaces (PVS) and cerebrospinal fluid (CSF) are essential components of the glymphatic system, regulating brain homeostasis and clearing neural waste throughout the lifespan. Enlarged PVS have been implicated in neurological disorders and sleep problems in adults, and excessive CSF volume has been reported in infants who develop autism. Enlarged PVS have not been sufficiently studied longitudinally in infancy or in relation to autism outcomes or CSF volume. Objective To examine whether enlarged PVS are more prevalent in infants who develop autism compared with controls and whether they are associated with trajectories of extra-axial CSF volume (EA-CSF) and sleep problems in later childhood. Design, Setting, and Participants This prospective, longitudinal cohort study used data from the Infant Brain Imaging Study. Magnetic resonance images were acquired at ages 6, 12, and 24 months (2007-2017), with sleep questionnaires performed between ages 7 and 12 years (starting in 2018). Data were collected at 4 sites in North Carolina, Missouri, Pennsylvania, and Washington. Data were analyzed from March 2021 through August 2022. Exposure PVS (ie, fluid-filled channels that surround blood vessels in the brain) that are enlarged (ie, visible on magnetic resonance imaging). Main Outcomes and Measures Outcomes of interest were enlarged PVS and EA-CSF volume from 6 to 24 months, autism diagnosis at 24 months, sleep problems between ages 7 and 12 years. Results A total of 311 infants (197 [63.3%] male) were included: 47 infants at high familial likelihood for autism (ie, having an older sibling with autism) who were diagnosed with autism at age 24 months, 180 high likelihood infants not diagnosed with autism, and 84 low likelihood control infants not diagnosed with autism. Sleep measures at school-age were available for 109 participants. Of infants who developed autism, 21 (44.7%) had enlarged PVS at 24 months compared with 48 infants (26.7%) in the high likelihood but no autism diagnosis group (P = .02) and 22 infants in the control group (26.2%) (P = .03). Across all groups, enlarged PVS at 24 months was associated with greater EA-CSF volume from ages 6 to 24 months (β = 4.64; 95% CI, 0.58-8.72; P = .002) and more frequent night wakings at school-age (F = 7.76; η2 = 0.08; P = .006). Conclusions and Relevance These findings suggest that enlarged PVS emerged between ages 12 and 24 months in infants who developed autism. These results add to a growing body of evidence that, along with excessive CSF volume and sleep dysfunction, the glymphatic system could be dysregulated in infants who develop autism.
Collapse
Affiliation(s)
- Dea Garic
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill
- Department of Psychiatry, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill
| | - Robert C. McKinstry
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Missouri
| | - Joshua Rutsohn
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill
| | | | - Jason Wolff
- Department of Educational Psychology, University of Minnesota Twin Cities College of Education and Human Development, Minneapolis
| | - Leigh C. MacIntyre
- McGill Centre for Integrative Neuroscience, Montreal Neurological Institute-Hospital, McGill University, Montreal, Canada
| | - Leigh Anne H. Weisenfeld
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill
| | - Sun Hyung Kim
- Department of Psychiatry, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill
| | - Juhi Pandey
- Center for Autism Research, Children’s Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Tanya St. John
- Department of Speech and Hearing Science, University of Washington, Seattle
- University of Washington Autism Center, University of Washington, Seattle
| | - Annette M. Estes
- Department of Speech and Hearing Science, University of Washington, Seattle
- University of Washington Autism Center, University of Washington, Seattle
| | - Robert T. Schultz
- University of Washington Autism Center, University of Washington, Seattle
| | - Heather C. Hazlett
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill
- Department of Psychiatry, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill
| | - Stephen R. Dager
- Department of Radiology, University of Washington Medical Center, Seattle
| | - Kelly N. Botteron
- Department of Psychiatry, Washington University School of Medicine in St Louis, St Louis, Missouri
| | - Martin Styner
- Department of Psychiatry, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill
| | - Joseph Piven
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill
- Department of Psychiatry, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill
| | - Mark D. Shen
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill
- Department of Psychiatry, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill
| |
Collapse
|
16
|
Zhong J, Lin W, Chen J, Gao Q. Higher critical closing pressure is independently associated with enlarged basal ganglia perivascular spaces. Front Neurol 2023; 14:1165469. [PMID: 37920831 PMCID: PMC10619908 DOI: 10.3389/fneur.2023.1165469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Accepted: 09/18/2023] [Indexed: 11/04/2023] Open
Abstract
Objective This study aimed to explore the association between cerebral hemodynamic parameters focused on the critical closing pressure (CCP) and enlarged perivascular spaces (EPVS). Methods Cerebral blood velocity in the middle cerebral artery (MCAv) and non-invasive continuous blood pressure (NIBP) were measured using a transcranial Doppler (TCD) and Finometer, followed by the calculation of cerebral hemodynamic parameters including CCP, resistance area product (RAP), pulsatility index (PI), and pulse pressure (PP). EPVS were graded separately in the basal ganglia (BG) and centrum semiovale (CSO), using a visual semiquantitative ordinal scale. Patients with EPVS >10 were classified into the severe BG-EPVS group and severe CSO-EPVS group, and the remainder into the mild BG-EPVS group and the mild CSO-EPVS group. Spearman's correlation and binary logistic regression analysis were performed to analyze the relationship between hemodynamic parameters and BG-EPVS and CSO-EPVS, respectively. Results Overall, 107 patients were enrolled. The severe BG-EPVS group had higher CCP, mean arterial blood pressure (MABP), systolic blood pressure (SBP), and diastolic blood pressure (DBP) than that in the mild BG-EPVS group (p < 0.05). There was no statistical difference in hemodynamic parameters between the severe CSO-EPVS group and the mild CSO-EPVS group. Spearman's correlation analysis showed that CCP was positively associated with BG-EPVS (rho = 0.331, p < 0.001) and CSO-EPVS (rho = 0.154, p = 0.044). The binary logistic regression analysis showed that CCP was independently associated with severe BG-EPVS (p < 0.05) and not with CSO-EPVS (p > 0.05) after adjusting for confounders. Conclusion CCP representing cerebrovascular tension was independently associated with BG-EPVS.
Collapse
Affiliation(s)
| | | | | | - Qingchun Gao
- Department of Neurology, The Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| |
Collapse
|
17
|
Hicks AJ, Sinclair B, Shultz SR, Pham W, Silbert LC, Schwartz DL, Rowe CC, Ponsford JL, Law M, Spitz G. Associations of Enlarged Perivascular Spaces With Brain Lesions, Brain Age, and Clinical Outcomes in Chronic Traumatic Brain Injury. Neurology 2023; 101:e63-e73. [PMID: 37156615 PMCID: PMC10351302 DOI: 10.1212/wnl.0000000000207370] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 03/17/2023] [Indexed: 05/10/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Enlarged perivascular spaces (ePVS) have been identified as a key signature of glymphatic system dysfunction in neurologic conditions. The incidence and clinical implications of ePVS after traumatic brain injury (TBI) are not yet understood. We investigated whether individuals with chronic moderate-to-severe TBI had an increased burden of ePVS and whether ePVS burden is modulated by the presence of focal lesions, older brain age, and poorer sleep quality. We examined whether an increased burden of ePVS was associated with poorer cognitive and emotional outcomes. METHODS Using a cross-sectional design, participants with a single moderate-to-severe chronic TBI (sustained ≥10 years ago) were recruited from an inpatient rehabilitation program. Control participants were recruited from the community. Participants underwent 3T brain MRI, neuropsychological assessment, and clinical evaluations. ePVS burden in white matter was quantified using automated segmentation. The relationship between the number of ePVS, group membership, focal lesions, brain age, current sleep quality, and outcome was modeled using negative binomial and linear regressions. RESULTS This study included 100 participants with TBI (70% male; mean age = 56.8 years) and 75 control participants (54.3% male; mean age = 59.8 years). The TBI group had a significantly greater burden of ePVS (prevalence ratio rate [PRR] = 1.29, p = 0.013, 95% CI 1.05-1.57). The presence of bilateral lesions was associated with greater ePVS burden (PRR = 1.41, p = 0.021, 95% CI 1.05-1.90). There was no association between ePVS burden, sleep quality (PRR = 1.01, p = 0.491, 95% CI 0.98-1.048), and sleep duration (PRR = 1.03, p = 0.556, 95% CI 0.92-1.16). ePVS was associated with verbal memory (β = -0.42, p = 0.006, 95% CI -0.72 to -0.12), but not with other cognitive domains. The burden of ePVS was not associated with emotional distress (β = -0.70, p = 0.461, 95% CI -2.57 to 1.17) or brain age (PRR = 1.00, p = 0.665, 95% CI 0.99-1.02). DISCUSSION TBI is associated with a greater burden of ePVS, especially when there have been bilateral brain lesions. ePVS was associated with reduced verbal memory performance. ePVS may indicate ongoing impairments in glymphatic system function in the chronic postinjury period.
Collapse
Affiliation(s)
- Amelia J Hicks
- From the Monash-Epworth Rehabilitation Research Centre (A.J.H., J.L.P., G.S.), Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Department of Neuroscience (A.J.H., B.S., S.R.S., W.P., M.L., G.S.), Central Clinical School, Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton; Department of Neurology (B.S.), Alfred Health, Melbourne, Australia; Health and Human Services (S.S.), Vancouver Island University, Nanaimo; Division of Medical Sciences (S.S.), University of Victoria, British Columbia, Canada; NIA-Layton Oregon Aging & Alzheimer's Disease Research Center (L.C.S., D.L.S.), Oregon Health & Science University; Department of Neurology (L.C.S.), Portland Veterans Affairs Health Care System; Advanced Imaging Research Center (D.L.S.), Oregon Health & Science University, Portland; Department of Molecular Imaging and Therapy (C.C.R.), Austin Health, Heidelberg; Florey Department of Neuroscience and Mental Health (C.C.R.), University of Melbourne, Parkville; and Department of Radiology (M.L.), Alfred Health, Melbourne, Australia
| | - Benjamin Sinclair
- From the Monash-Epworth Rehabilitation Research Centre (A.J.H., J.L.P., G.S.), Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Department of Neuroscience (A.J.H., B.S., S.R.S., W.P., M.L., G.S.), Central Clinical School, Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton; Department of Neurology (B.S.), Alfred Health, Melbourne, Australia; Health and Human Services (S.S.), Vancouver Island University, Nanaimo; Division of Medical Sciences (S.S.), University of Victoria, British Columbia, Canada; NIA-Layton Oregon Aging & Alzheimer's Disease Research Center (L.C.S., D.L.S.), Oregon Health & Science University; Department of Neurology (L.C.S.), Portland Veterans Affairs Health Care System; Advanced Imaging Research Center (D.L.S.), Oregon Health & Science University, Portland; Department of Molecular Imaging and Therapy (C.C.R.), Austin Health, Heidelberg; Florey Department of Neuroscience and Mental Health (C.C.R.), University of Melbourne, Parkville; and Department of Radiology (M.L.), Alfred Health, Melbourne, Australia
| | - Sandy R Shultz
- From the Monash-Epworth Rehabilitation Research Centre (A.J.H., J.L.P., G.S.), Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Department of Neuroscience (A.J.H., B.S., S.R.S., W.P., M.L., G.S.), Central Clinical School, Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton; Department of Neurology (B.S.), Alfred Health, Melbourne, Australia; Health and Human Services (S.S.), Vancouver Island University, Nanaimo; Division of Medical Sciences (S.S.), University of Victoria, British Columbia, Canada; NIA-Layton Oregon Aging & Alzheimer's Disease Research Center (L.C.S., D.L.S.), Oregon Health & Science University; Department of Neurology (L.C.S.), Portland Veterans Affairs Health Care System; Advanced Imaging Research Center (D.L.S.), Oregon Health & Science University, Portland; Department of Molecular Imaging and Therapy (C.C.R.), Austin Health, Heidelberg; Florey Department of Neuroscience and Mental Health (C.C.R.), University of Melbourne, Parkville; and Department of Radiology (M.L.), Alfred Health, Melbourne, Australia
| | - William Pham
- From the Monash-Epworth Rehabilitation Research Centre (A.J.H., J.L.P., G.S.), Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Department of Neuroscience (A.J.H., B.S., S.R.S., W.P., M.L., G.S.), Central Clinical School, Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton; Department of Neurology (B.S.), Alfred Health, Melbourne, Australia; Health and Human Services (S.S.), Vancouver Island University, Nanaimo; Division of Medical Sciences (S.S.), University of Victoria, British Columbia, Canada; NIA-Layton Oregon Aging & Alzheimer's Disease Research Center (L.C.S., D.L.S.), Oregon Health & Science University; Department of Neurology (L.C.S.), Portland Veterans Affairs Health Care System; Advanced Imaging Research Center (D.L.S.), Oregon Health & Science University, Portland; Department of Molecular Imaging and Therapy (C.C.R.), Austin Health, Heidelberg; Florey Department of Neuroscience and Mental Health (C.C.R.), University of Melbourne, Parkville; and Department of Radiology (M.L.), Alfred Health, Melbourne, Australia
| | - Lisa C Silbert
- From the Monash-Epworth Rehabilitation Research Centre (A.J.H., J.L.P., G.S.), Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Department of Neuroscience (A.J.H., B.S., S.R.S., W.P., M.L., G.S.), Central Clinical School, Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton; Department of Neurology (B.S.), Alfred Health, Melbourne, Australia; Health and Human Services (S.S.), Vancouver Island University, Nanaimo; Division of Medical Sciences (S.S.), University of Victoria, British Columbia, Canada; NIA-Layton Oregon Aging & Alzheimer's Disease Research Center (L.C.S., D.L.S.), Oregon Health & Science University; Department of Neurology (L.C.S.), Portland Veterans Affairs Health Care System; Advanced Imaging Research Center (D.L.S.), Oregon Health & Science University, Portland; Department of Molecular Imaging and Therapy (C.C.R.), Austin Health, Heidelberg; Florey Department of Neuroscience and Mental Health (C.C.R.), University of Melbourne, Parkville; and Department of Radiology (M.L.), Alfred Health, Melbourne, Australia
| | - Daniel L Schwartz
- From the Monash-Epworth Rehabilitation Research Centre (A.J.H., J.L.P., G.S.), Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Department of Neuroscience (A.J.H., B.S., S.R.S., W.P., M.L., G.S.), Central Clinical School, Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton; Department of Neurology (B.S.), Alfred Health, Melbourne, Australia; Health and Human Services (S.S.), Vancouver Island University, Nanaimo; Division of Medical Sciences (S.S.), University of Victoria, British Columbia, Canada; NIA-Layton Oregon Aging & Alzheimer's Disease Research Center (L.C.S., D.L.S.), Oregon Health & Science University; Department of Neurology (L.C.S.), Portland Veterans Affairs Health Care System; Advanced Imaging Research Center (D.L.S.), Oregon Health & Science University, Portland; Department of Molecular Imaging and Therapy (C.C.R.), Austin Health, Heidelberg; Florey Department of Neuroscience and Mental Health (C.C.R.), University of Melbourne, Parkville; and Department of Radiology (M.L.), Alfred Health, Melbourne, Australia
| | - Christopher C Rowe
- From the Monash-Epworth Rehabilitation Research Centre (A.J.H., J.L.P., G.S.), Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Department of Neuroscience (A.J.H., B.S., S.R.S., W.P., M.L., G.S.), Central Clinical School, Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton; Department of Neurology (B.S.), Alfred Health, Melbourne, Australia; Health and Human Services (S.S.), Vancouver Island University, Nanaimo; Division of Medical Sciences (S.S.), University of Victoria, British Columbia, Canada; NIA-Layton Oregon Aging & Alzheimer's Disease Research Center (L.C.S., D.L.S.), Oregon Health & Science University; Department of Neurology (L.C.S.), Portland Veterans Affairs Health Care System; Advanced Imaging Research Center (D.L.S.), Oregon Health & Science University, Portland; Department of Molecular Imaging and Therapy (C.C.R.), Austin Health, Heidelberg; Florey Department of Neuroscience and Mental Health (C.C.R.), University of Melbourne, Parkville; and Department of Radiology (M.L.), Alfred Health, Melbourne, Australia
| | - Jennie L Ponsford
- From the Monash-Epworth Rehabilitation Research Centre (A.J.H., J.L.P., G.S.), Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Department of Neuroscience (A.J.H., B.S., S.R.S., W.P., M.L., G.S.), Central Clinical School, Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton; Department of Neurology (B.S.), Alfred Health, Melbourne, Australia; Health and Human Services (S.S.), Vancouver Island University, Nanaimo; Division of Medical Sciences (S.S.), University of Victoria, British Columbia, Canada; NIA-Layton Oregon Aging & Alzheimer's Disease Research Center (L.C.S., D.L.S.), Oregon Health & Science University; Department of Neurology (L.C.S.), Portland Veterans Affairs Health Care System; Advanced Imaging Research Center (D.L.S.), Oregon Health & Science University, Portland; Department of Molecular Imaging and Therapy (C.C.R.), Austin Health, Heidelberg; Florey Department of Neuroscience and Mental Health (C.C.R.), University of Melbourne, Parkville; and Department of Radiology (M.L.), Alfred Health, Melbourne, Australia
| | - Meng Law
- From the Monash-Epworth Rehabilitation Research Centre (A.J.H., J.L.P., G.S.), Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Department of Neuroscience (A.J.H., B.S., S.R.S., W.P., M.L., G.S.), Central Clinical School, Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton; Department of Neurology (B.S.), Alfred Health, Melbourne, Australia; Health and Human Services (S.S.), Vancouver Island University, Nanaimo; Division of Medical Sciences (S.S.), University of Victoria, British Columbia, Canada; NIA-Layton Oregon Aging & Alzheimer's Disease Research Center (L.C.S., D.L.S.), Oregon Health & Science University; Department of Neurology (L.C.S.), Portland Veterans Affairs Health Care System; Advanced Imaging Research Center (D.L.S.), Oregon Health & Science University, Portland; Department of Molecular Imaging and Therapy (C.C.R.), Austin Health, Heidelberg; Florey Department of Neuroscience and Mental Health (C.C.R.), University of Melbourne, Parkville; and Department of Radiology (M.L.), Alfred Health, Melbourne, Australia
| | - Gershon Spitz
- From the Monash-Epworth Rehabilitation Research Centre (A.J.H., J.L.P., G.S.), Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Department of Neuroscience (A.J.H., B.S., S.R.S., W.P., M.L., G.S.), Central Clinical School, Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton; Department of Neurology (B.S.), Alfred Health, Melbourne, Australia; Health and Human Services (S.S.), Vancouver Island University, Nanaimo; Division of Medical Sciences (S.S.), University of Victoria, British Columbia, Canada; NIA-Layton Oregon Aging & Alzheimer's Disease Research Center (L.C.S., D.L.S.), Oregon Health & Science University; Department of Neurology (L.C.S.), Portland Veterans Affairs Health Care System; Advanced Imaging Research Center (D.L.S.), Oregon Health & Science University, Portland; Department of Molecular Imaging and Therapy (C.C.R.), Austin Health, Heidelberg; Florey Department of Neuroscience and Mental Health (C.C.R.), University of Melbourne, Parkville; and Department of Radiology (M.L.), Alfred Health, Melbourne, Australia.
| |
Collapse
|
18
|
Park CH, Shin NY, Nam Y, Yoon U, Ahn K, Lee SK. Characteristics of perivascular space dilatation in normal aging. Hum Brain Mapp 2023; 44:3232-3240. [PMID: 36930038 PMCID: PMC10171536 DOI: 10.1002/hbm.26277] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 02/09/2023] [Accepted: 03/01/2023] [Indexed: 03/18/2023] Open
Abstract
The increased incidence of dilated perivascular spaces (dPVSs) visible on MRI has been observed with advancing age, but the relevance of PVS dilatation to normal aging across the lifespan has yet to be fully clarified. In the current study, we sought to find out the age dependence of dPVSs by exploring changes in different characteristics of PVS dilatation across a wide range of age. For 1220 healthy subjects aged between 18 and 100 years, PVSs were automatically segmented and characteristics of PVS dilatation were assessed in terms of the burden, location, and morphology of PVSs in the white matter (WM) and basal ganglia (BG). A machine learning model using the random forests method was constructed to estimate the subjects' age by employing the PVS features. The constructed machine learning model was able to estimate the age of the subjects with an error of 9.53 years on average (correlation = 0.875). The importance of the PVS features indicated the primary contribution of the burden of PVSs in the BG and the additional contribution of locational and morphological changes of PVSs, specifically peripheral extension and reduced linearity, in the WM to age estimation. Indeed, adding the PVS location or morphology features to the PVS burden features provided an improvement to the performance of age estimation. The age dependence of dPVSs in terms of such various characteristics of PVS dilatation in healthy subjects could provide a more comprehensive reference for detecting brain disease-related PVS dilatation.
Collapse
Affiliation(s)
- Chang-Hyun Park
- Division of Artificial Intelligence and Software, College of Engineering, Ewha Womans University, Seoul, South Korea
| | - Na-Young Shin
- Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, College of Medicine, Yonsei University, Seoul, South Korea
| | - Yoonho Nam
- Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Gyeonggi, South Korea
| | - Uicheul Yoon
- Department of Biomedical Engineering, College of Bio and Medical Sciences, Daegu Catholic University, Gyeongsan, Gyeongbuk, South Korea
| | - Kookjin Ahn
- Department of Radiology, College of Medicine, Catholic University of Korea, Seoul, South Korea
| | - Seung-Koo Lee
- Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, College of Medicine, Yonsei University, Seoul, South Korea
| |
Collapse
|
19
|
Moses J, Sinclair B, Law M, O'Brien TJ, Vivash L. Automated Methods for Detecting and Quantitation of Enlarged Perivascular spaces on MRI. J Magn Reson Imaging 2023; 57:11-24. [PMID: 35866259 PMCID: PMC10083963 DOI: 10.1002/jmri.28369] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Revised: 07/06/2022] [Accepted: 07/08/2022] [Indexed: 02/03/2023] Open
Abstract
The brain's glymphatic system is a network of intracerebral vessels that function to remove "waste products" such as degraded proteins from the brain. It comprises of the vasculature, perivascular spaces (PVS), and astrocytes. Poor glymphatic function has been implicated in numerous diseases; however, its contribution is still unknown. Efforts have been made to image the glymphatic system to further assess its role in the pathogenesis of different diseases. Numerous imaging modalities have been utilized including two-photon microscopy and contrast-enhanced magnetic resonance imaging (MRI). However, these are associated with limitations for clinical use. PVS form a part of the glymphatic system and can be visualized on standard MRI sequences when enlarged. It is thought that PVS become enlarged secondary to poor glymphatic drainage of metabolites. Thus, quantitating PVS could be a good surrogate marker for glymphatic function. Numerous manual rating scales have been developed to measure the PVS number and size on MRI scans; however, these are associated with many limitations. Instead, automated methods have been created to measure PVS more accurately in different diseases. In this review, we discuss the imaging techniques currently available to visualize the glymphatic system as well as the automated methods currently available to measure PVS, and the strengths and limitations associated with each technique. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 1.
Collapse
Affiliation(s)
- Jasmine Moses
- Department of Neurosciences, Central Clinical School, Monash University, Melbourne, Australia
| | - Ben Sinclair
- Department of Neurosciences, Central Clinical School, Monash University, Melbourne, Australia.,Department of Neurology, Alfred Hospital, Melbourne, Australia.,Department of Medicine, Royal Melbourne Hospital, University of Melbourne, Melbourne, Australia
| | - Meng Law
- Department of Neurosciences, Central Clinical School, Monash University, Melbourne, Australia.,Department of Radiology, Alfred Health, Melbourne, Victoria, Australia.,Department of Electrical and Computer Systems Engineering, Monash University, Melbourne, Victoria, Australia
| | - Terence J O'Brien
- Department of Neurosciences, Central Clinical School, Monash University, Melbourne, Australia.,Department of Neurology, Alfred Hospital, Melbourne, Australia.,Department of Medicine, Royal Melbourne Hospital, University of Melbourne, Melbourne, Australia.,Department of Neurology, Royal Melbourne Hospital, University of Melbourne, Victoria, Australia
| | - Lucy Vivash
- Department of Neurosciences, Central Clinical School, Monash University, Melbourne, Australia.,Department of Neurology, Alfred Hospital, Melbourne, Australia.,Department of Medicine, Royal Melbourne Hospital, University of Melbourne, Melbourne, Australia.,Department of Neurology, Royal Melbourne Hospital, University of Melbourne, Victoria, Australia
| |
Collapse
|
20
|
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.
Collapse
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
| |
Collapse
|
21
|
Vikner T, Karalija N, Eklund A, Malm J, Lundquist A, Gallewicz N, Dahlin M, Lindenberger U, Riklund K, Bäckman L, Nyberg L, Wåhlin A. 5-Year Associations among Cerebral Arterial Pulsatility, Perivascular Space Dilation, and White Matter Lesions. Ann Neurol 2022; 92:871-881. [PMID: 36054261 PMCID: PMC9804392 DOI: 10.1002/ana.26475] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 08/01/2022] [Accepted: 08/01/2022] [Indexed: 01/05/2023]
Abstract
OBJECTIVE High cerebral arterial pulsatility index (PI), white matter lesions (WMLs), enlarged perivascular spaces (PVSs), and lacunar infarcts are common findings in the elderly population, and considered indicators of small vessel disease (SVD). Here, we investigate the potential temporal ordering among these variables, with emphasis on determining whether high PI is an early or delayed manifestation of SVD. METHODS In a population-based cohort, 4D flow MRI data for cerebral arterial pulsatility was collected for 159 participants at baseline (age 64-68), and for 122 participants at follow-up 5 years later. Structural MRI was used for WML and PVS segmentation, and lacune identification. Linear mixed-effects (LME) models were used to model longitudinal changes testing for pairwise associations, and latent change score (LCS) models to model multiple relationships among variables simultaneously. RESULTS Longitudinal 5-year increases were found for WML, PVS, and PI. Cerebral arterial PI at baseline did not predict changes in WML or PVS volume. However, WML and PVS volume at baseline predicted 5-year increases in PI. This was shown for PI increases in relation to baseline WML and PVS volumes using LME models (R ≥ 0.24; p < 0.02 and R ≥ 0.23; p < 0.03, respectively) and LCS models ( β = 0.28; p = 0.015 and β = 0.28; p = 0.009, respectively). Lacunes at baseline were unrelated to PI. INTERPRETATION In healthy older adults, indicators of SVD are related in a lead-lag fashion, in which the expression of WML and PVS precedes increases in cerebral arterial PI. Hence, we propose that elevated PI is a relatively late manifestation, rather than a risk factor, for cerebral SVD. ANN NEUROL 2022;92:871-881.
Collapse
Affiliation(s)
- Tomas Vikner
- Department of Radiation SciencesUmeå UniversityUmeåSweden
| | - Nina Karalija
- Department of Radiation SciencesUmeå UniversityUmeåSweden
- Umeå Center for Functional Brain Imaging (UFBI)Umeå UniversityUmeåSweden
| | - Anders Eklund
- Department of Radiation SciencesUmeå UniversityUmeåSweden
- Umeå Center for Functional Brain Imaging (UFBI)Umeå UniversityUmeåSweden
| | - Jan Malm
- Department of Clinical Science, NeurosciencesUmeå UniversityUmeåSweden
| | - Anders Lundquist
- Umeå Center for Functional Brain Imaging (UFBI)Umeå UniversityUmeåSweden
- Department of Statistics, USBEUmeå UniversityUmeåSweden
| | | | - Magnus Dahlin
- Department of Radiation SciencesUmeå UniversityUmeåSweden
| | - Ulman Lindenberger
- Center for Lifespan PsychologyMax Planck Institute for Human DevelopmentBerlinGermany
- Max PlanckUCL Centre for Computational Psychiatry and Ageing ResearchBerlinGermany
- Max PlanckUCL Centre for Computational Psychiatry and Ageing ResearchLondonUK
| | - Katrine Riklund
- Department of Radiation SciencesUmeå UniversityUmeåSweden
- Umeå Center for Functional Brain Imaging (UFBI)Umeå UniversityUmeåSweden
| | - Lars Bäckman
- Ageing Research CenterKarolinska Institutet and Stockholm UniversityStockholmSweden
| | - Lars Nyberg
- Department of Radiation SciencesUmeå UniversityUmeåSweden
- Umeå Center for Functional Brain Imaging (UFBI)Umeå UniversityUmeåSweden
- Department of Integrative Medical Biology (IMB)Umeå UniversityUmeåSweden
| | - Anders Wåhlin
- Department of Radiation SciencesUmeå UniversityUmeåSweden
- Umeå Center for Functional Brain Imaging (UFBI)Umeå UniversityUmeåSweden
- Department of Applied Physics and ElectronicsUmeå UniversityUmeåSweden
| |
Collapse
|
22
|
Moses J, Sinclair B, Schwartz DL, Silbert LC, O’Brien TJ, Law M, Vivash L. Perivascular spaces as a marker of disease severity and neurodegeneration in patients with behavioral variant frontotemporal dementia. Front Neurosci 2022; 16:1003522. [PMID: 36340772 PMCID: PMC9633276 DOI: 10.3389/fnins.2022.1003522] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Accepted: 10/06/2022] [Indexed: 11/19/2022] Open
Abstract
Background Behavioural Variant Frontotemporal Dementia (bvFTD) is a rapidly progressing neurodegenerative proteinopathy. Perivascular spaces (PVS) form a part of the brain’s glymphatic clearance system. When enlarged due to poor glymphatic clearance of toxic proteins, PVS become larger and more conspicuous on MRI. Therefore, enlarged PVS may be a useful biomarker of disease severity and progression in neurodegenerative proteinopathies such as bvFTD. This study aimed to determine the utility of PVS as a biomarker of disease progression in patients with bvFTD. Materials and methods Serial baseline and week 52 MRIs acquired from ten patients with bvFTD prospectively recruited and followed in a Phase 1b open label trial of sodium selenate for bvFTD were used in this study. An automated algorithm quantified PVS on MRI, which was visually inspected and validated by a member of the study team. The number and volume of PVS were extracted and mixed models used to assess the relationship between PVS burden and other measures of disease (cognition, carer burden scale, protein biomarkers). Additional exploratory analysis investigated PVS burden in patients who appeared to not progress over the 12 months of selenate treatment (i.e., “non-progressors”). Results Overall, PVS cluster number (ß = −3.27, CI [−7.80 – 1.27], p = 0.267) and PVS volume (ß = −36.8, CI [−84.9 – 11.3], p = 0.171) did not change over the paired MRI scans 12 months apart. There was association between cognition total composite scores and the PVS burden (PVS cluster ß = −0.802e–3, CI [9.45e–3 – −6.60e–3, p ≤ 0.001; PVS volume ß = −1.30e–3, CI [−1.55e–3 – −1.05e–3], p ≤ 0.001), as well as between the change in the cognition total composite score and the change in PVS volume (ß = 4.36e–3, CI [1.33e–3 – 7.40e–3], p = 0.046) over the trial period. There was a significant association between CSF t-tau and the number of PVS clusters (ß = 2.845, CI [0.630 – 5.06], p = 0.036). Additionally, there was a significant relationship between the change in CSF t-tau and the change in the number of PVS (ß = 1.54, CI [0.918 – 2.16], p < 0.001) and PVS volume (ß = 13.8, CI [6.37 – 21.1], p = 0.003) over the trial period. An association was found between the change in NfL and the change in PVS volume (ß = 1.40, CI [0.272 – 2.52], p = 0.045) over time. Within the “non-progressor” group (n = 7), there was a significant relationship between the change in the CSF total-tau (t-tau) levels and the change in the PVS burden (PVS cluster (ß = 1.46, CI [0.577 – 2.34], p = 0.014; PVS volume ß = 14.6, CI [3.86 – 25.4], p = 0.032) over the trial period. Additionally, there was evidence of a significant relationship between the change in NfL levels and the change in the PVS burden over time (PVS cluster ß = 0.296, CI [0.229 – 0.361], p ≤ 0.001; PVS volume ß = 3.67, CI [2.42 – 4.92], p = 0.002). Conclusion Analysis of serial MRI scans 12 months apart in patients with bvFTD demonstrated a relationship between PVS burden and disease severity as measured by the total cognitive composite score and CSF t-tau. Further studies are needed to confirm PVS as a robust marker of neurodegeneration in proteinopathies.
Collapse
Affiliation(s)
- Jasmine Moses
- Department of Neuroscience, Central Clinical School, Monash University, 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, Royal Melbourne Hospital, University of Melbourne, Melbourne, VIC, Australia
| | - Daniel L. Schwartz
- NIA-Layton Oregon Aging and Alzheimer’s Disease Research Center, Oregon Health & Science University, Portland, OR, United States
- Advanced Imaging Research Center, Oregon Health and Science University, Portland, OR, United States
| | - Lisa C. Silbert
- NIA-Layton Oregon Aging and Alzheimer’s Disease Research Center, Oregon Health & Science University, Portland, OR, United States
- Department of Neurology, Portland Veterans Affairs Health Care System, Portland, OR, United States
| | - Terence J. O’Brien
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia
- Department of Neurology, Alfred Hospital, Melbourne, VIC, Australia
- Department of Medicine, Royal Melbourne Hospital, University of Melbourne, Melbourne, VIC, Australia
- Department of Neurology, 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, Melbourne, VIC, Australia
- Department of Electrical and Computer Systems Engineering, Monash University, 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, Royal Melbourne Hospital, University of Melbourne, Melbourne, VIC, Australia
- Department of Neurology, Royal Melbourne Hospital, University of Melbourne, Melbourne, VIC, Australia
- *Correspondence: Lucy Vivash,
| |
Collapse
|
23
|
Barisano G, Lynch KM, Sibilia F, Lan H, Shih NC, Sepehrband F, Choupan J. Imaging perivascular space structure and function using brain MRI. Neuroimage 2022; 257:119329. [PMID: 35609770 PMCID: PMC9233116 DOI: 10.1016/j.neuroimage.2022.119329] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 05/04/2022] [Accepted: 05/19/2022] [Indexed: 12/03/2022] Open
Abstract
In this article, we provide an overview of current neuroimaging methods for studying perivascular spaces (PVS) in humans using brain MRI. In recent years, an increasing number of studies highlighted the role of PVS in cerebrospinal/interstial fluid circulation and clearance of cerebral waste products and their association with neurological diseases. Novel strategies and techniques have been introduced to improve the quantification of PVS and to investigate their function and morphological features in physiological and pathological conditions. After a brief introduction on the anatomy and physiology of PVS, we examine the latest technological developments to quantitatively analyze the structure and function of PVS in humans with MRI. We describe the applications, advantages, and limitations of these methods, providing guidance and suggestions on the acquisition protocols and analysis techniques that can be applied to study PVS in vivo. Finally, we review the human neuroimaging studies on PVS across the normative lifespan and in the context of neurological disorders.
Collapse
Affiliation(s)
- Giuseppe Barisano
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, USA; Neuroscience Graduate Program, University of Southern California, Los Angeles, CA, USA.
| | - Kirsten M Lynch
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, USA
| | - Francesca Sibilia
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, USA
| | - Haoyu Lan
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, USA; Neuroscience Graduate Program, University of Southern California, Los Angeles, CA, USA
| | - Nien-Chu Shih
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, USA
| | - Farshid Sepehrband
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, USA
| | - Jeiran Choupan
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, USA
| |
Collapse
|
24
|
Jiang J, Wang D, Song Y, Sachdev PS, Wen W. Computer-Aided Extraction of Select MRI Markers of Cerebral Small Vessel Disease: A Systematic Review. Neuroimage 2022; 261:119528. [PMID: 35914668 DOI: 10.1016/j.neuroimage.2022.119528] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 07/18/2022] [Accepted: 07/28/2022] [Indexed: 11/30/2022] Open
Abstract
Cerebral small vessel disease (CSVD) is a major vascular contributor to cognitive impairment in ageing, including dementias. Imaging remains the most promising method for in vivo studies of CSVD. To replace the subjective and laborious visual rating approaches, emerging studies have applied state-of-the-art artificial intelligence to extract imaging biomarkers of CSVD from MRI scans. We aimed to summarise published computer-aided methods for the examination of three imaging biomarkers of CSVD, namely cerebral microbleeds (CMB), dilated perivascular spaces (PVS), and lacunes of presumed vascular origin. Seventy classical image processing, classical machine learning, and deep learning studies were identified. Transfer learning and weak supervision techniques have been applied to accommodate the limitations in the training data. While good performance metrics were achieved in local datasets, there have not been generalisable pipelines validated in different research and/or clinical cohorts. Future studies could consider pooling data from multiple sources to increase data size and diversity, and evaluating performance using both image processing metrics and associations with clinical measures.
Collapse
Affiliation(s)
- Jiyang Jiang
- Centre for Healthy Brain Ageing, Discipline of Psychiatry and Mental Health, School of Clinical Medicine, Faculty of Medicine, University of New South Wales, NSW 2052, Australia.
| | - Dadong Wang
- Quantitative Imaging Research Team, Data61, CSIRO, Marsfield, NSW 2122, Australia
| | - Yang Song
- School of Computer Science and Engineering, University of New South Wales, NSW 2052, Australia
| | - Perminder S Sachdev
- Centre for Healthy Brain Ageing, Discipline of Psychiatry and Mental Health, School of Clinical Medicine, Faculty of Medicine, University of New South Wales, NSW 2052, Australia; Neuropsychiatric Institute, Prince of Wales Hospital, Randwick, NSW 2031, Australia
| | - Wei Wen
- Centre for Healthy Brain Ageing, Discipline of Psychiatry and Mental Health, School of Clinical Medicine, Faculty of Medicine, University of New South Wales, NSW 2052, Australia; Neuropsychiatric Institute, Prince of Wales Hospital, Randwick, NSW 2031, Australia
| |
Collapse
|
25
|
Libecap TJ, Zachariou V, Bauer CE, Wilcock DM, Jicha GA, Raslau FD, Gold BT. Enlarged Perivascular Spaces Are Negatively Associated With Montreal Cognitive Assessment Scores in Older Adults. Front Neurol 2022; 13:888511. [PMID: 35847209 PMCID: PMC9283758 DOI: 10.3389/fneur.2022.888511] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Accepted: 06/06/2022] [Indexed: 11/30/2022] Open
Abstract
Emerging evidence suggests that enlarged perivascular spaces (ePVS) may be a clinically significant neuroimaging marker of global cognitive function related to cerebral small vessel disease (cSVD). We tested this possibility by assessing the relationship between ePVS and both a standardized measure of global cognitive function, the Montreal Cognitive Assessment (MoCA), and an established marker of cSVD, white matter hyperintensity volume (WMH) volume. One hundred and eleven community-dwelling older adults (56-86) underwent neuroimaging and MoCA testing. Quantification of region-specific ePVS burden was performed using a previously validated visual rating method and WMH volumes were computed using the standard ADNI pipeline. Separate linear regression models were run with ePVS as a predictor of MoCA scores and whole brain WMH volume. Results indicated a negative association between MoCA scores and both total ePVS counts (P ≤ 0.001) and centrum semiovale ePVS counts (P ≤ 0.001), after controlling for other relevant cSVD variables. Further, WMH volumes were positively associated with total ePVS (P = 0.010), basal ganglia ePVS (P ≤ 0.001), and centrum semiovale ePVS (P = 0.027). Our results suggest that ePVS burden, particularly in the centrum semiovale, may be a clinically significant neuroimaging marker of global cognitive dysfunction related to cSVD.
Collapse
Affiliation(s)
- Timothy J. Libecap
- Department of Neuroscience, College of Medicine, University of Kentucky, Lexington, KY, United States
| | - Valentinos Zachariou
- Department of Neuroscience, College of Medicine, University of Kentucky, Lexington, KY, United States
| | - Christopher E. Bauer
- Department of Neuroscience, College of Medicine, University of Kentucky, Lexington, KY, United States
| | - Donna M. Wilcock
- Department of Physiology, College of Medicine, University of Kentucky, Lexington, KY, United States
- Sanders-Brown Center on Aging, College of Medicine, University of Kentucky, Lexington, KY, United States
| | - Gregory A. Jicha
- Sanders-Brown Center on Aging, College of Medicine, University of Kentucky, Lexington, KY, United States
- Department of Neurology, College of Medicine, University of Kentucky, Lexington, KY, United States
| | - Flavius D. Raslau
- Department of Radiology, College of Medicine, University of Kentucky, Lexington, KY, United States
| | - Brian T. Gold
- Department of Neuroscience, College of Medicine, University of Kentucky, Lexington, KY, United States
- Sanders-Brown Center on Aging, College of Medicine, University of Kentucky, Lexington, KY, United States
- Magnetic Resonance Imaging and Spectroscopy Center, College of Medicine, University of Kentucky, Lexington, KY, United States
| |
Collapse
|
26
|
Hupfeld KE, Richmond SB, McGregor HR, Schwartz DL, Luther MN, Beltran NE, Kofman IS, De Dios YE, Riascos RF, Wood SJ, Bloomberg JJ, Mulavara AP, Silbert LC, Iliff JJ, Seidler RD, Piantino J. Longitudinal MRI-visible perivascular space (PVS) changes with long-duration spaceflight. Sci Rep 2022; 12:7238. [PMID: 35513698 PMCID: PMC9072425 DOI: 10.1038/s41598-022-11593-y] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Accepted: 04/20/2022] [Indexed: 01/07/2023] Open
Abstract
Humans are exposed to extreme environmental stressors during spaceflight and return with alterations in brain structure and shifts in intracranial fluids. To date, no studies have evaluated the effects of spaceflight on perivascular spaces (PVSs) within the brain, which are believed to facilitate fluid drainage and brain homeostasis. Here, we examined how the number and morphology of magnetic resonance imaging (MRI)-visible PVSs are affected by spaceflight, including prior spaceflight experience. Fifteen astronauts underwent six T1-weighted 3 T MRI scans, twice prior to launch and four times following their return to Earth after ~ 6-month missions to the International Space Station. White matter MRI-visible PVS number and morphology were calculated using an established, automated segmentation algorithm. We validated our automated segmentation algorithm by comparing algorithm PVS counts with those identified by two trained raters in 50 randomly selected slices from this cohort; the automated algorithm performed similarly to visual ratings (r(48) = 0.77, p < 0.001). In addition, we found high reliability for four of five PVS metrics across the two pre-flight time points and across the four control time points (ICC(3,k) > 0.50). Among the astronaut cohort, we found that novice astronauts showed an increase in total PVS volume from pre- to post-flight, whereas experienced crewmembers did not (p = 0.020), suggesting that experienced astronauts may exhibit holdover effects from prior spaceflight(s). Greater pre-flight PVS load was associated with more prior flight experience (r = 0.60-0.71), though these relationships did not reach statistical significance (p > 0.05). Pre- to post-flight changes in ventricular volume were not significantly associated with changes in PVS characteristics, and the presence of spaceflight associated neuro-ocular syndrome (SANS) was not associated with PVS number or morphology. Together, these findings demonstrate that PVSs can be consistently identified on T1-weighted MRI scans, and that spaceflight is associated with PVS changes. Specifically, prior spaceflight experience may be an important factor in determining PVS characteristics.
Collapse
Affiliation(s)
- Kathleen E. Hupfeld
- grid.15276.370000 0004 1936 8091Department of Applied Physiology and Kinesiology, University of Florida, 1864 Stadium Rd., Gainesville, FL USA
| | - Sutton B. Richmond
- grid.15276.370000 0004 1936 8091Department of Applied Physiology and Kinesiology, University of Florida, 1864 Stadium Rd., Gainesville, FL USA
| | - Heather R. McGregor
- grid.15276.370000 0004 1936 8091Department of Applied Physiology and Kinesiology, University of Florida, 1864 Stadium Rd., Gainesville, FL USA
| | - Daniel L. Schwartz
- grid.5288.70000 0000 9758 5690Layton-NIA Oregon Aging and Alzheimer’s Disease Research Center, Department of Neurology, Oregon Health and Science University, Portland, OR USA ,grid.5288.70000 0000 9758 5690Advanced Imaging Research Center, Oregon Health and Science University, Portland, OR USA
| | - Madison N. Luther
- grid.5288.70000 0000 9758 5690Division of Child Neurology, Department of Pediatrics, Doernbecher Children’s Hospital, Oregon Health and Science University, 707 SW Gaines St., CDRC-P, Portland, OR 97239 USA
| | | | | | | | - Roy F. Riascos
- grid.267308.80000 0000 9206 2401Department of Diagnostic and Interventional Imaging, University of Texas Health Science Center at Houston, Houston, TX USA
| | - Scott J. Wood
- grid.419085.10000 0004 0613 2864NASA Johnson Space Center, Houston, TX USA
| | - Jacob J. Bloomberg
- grid.419085.10000 0004 0613 2864NASA Johnson Space Center, Houston, TX USA
| | | | - Lisa C. Silbert
- grid.5288.70000 0000 9758 5690Layton-NIA Oregon Aging and Alzheimer’s Disease Research Center, Department of Neurology, Oregon Health and Science University, Portland, OR USA ,grid.484322.bNeurology, Veteran’s Affairs Portland Health Care System, Portland, OR USA
| | - Jeffrey J. Iliff
- grid.34477.330000000122986657Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA USA ,grid.34477.330000000122986657Department of Neurology, University of Washington School of Medicine, Seattle, WA USA ,grid.413919.70000 0004 0420 6540VISN 20 Mental Illness Research, Education and Clinical Center (MIRECC), VA Puget Sound Health Care System, Seattle, WA USA
| | - Rachael D. Seidler
- grid.15276.370000 0004 1936 8091Department of Applied Physiology and Kinesiology, University of Florida, 1864 Stadium Rd., Gainesville, FL USA ,grid.15276.370000 0004 1936 8091Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL USA
| | - Juan Piantino
- grid.5288.70000 0000 9758 5690Division of Child Neurology, Department of Pediatrics, Doernbecher Children’s Hospital, Oregon Health and Science University, 707 SW Gaines St., CDRC-P, Portland, OR 97239 USA
| |
Collapse
|
27
|
The Bidirectional Link Between Sleep Disturbances and Traumatic Brain Injury Symptoms: A Role for Glymphatic Dysfunction? Biol Psychiatry 2022; 91:478-487. [PMID: 34481662 PMCID: PMC8758801 DOI: 10.1016/j.biopsych.2021.06.025] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Revised: 06/28/2021] [Accepted: 06/29/2021] [Indexed: 12/14/2022]
Abstract
Mild traumatic brain injury (mTBI), often referred to as concussion, is a major cause of morbidity and mortality worldwide. Sleep disturbances are common after mTBI. Moreover, subjects who develop subjective sleep complaints after mTBI also report more severe somatic, mental health, and cognitive impairment and take longer to recover from mTBI sequelae. Despite many previous studies addressing the role of sleep in post-mTBI morbidity, the mechanisms linking sleep to recovery after mTBI remain poorly understood. The glymphatic system is a brainwide network that supports fluid movement through the cerebral parenchyma and the clearance of interstitial solutes and wastes from the brain. Notably, the glymphatic system is active primarily during sleep. Clearance of cellular byproducts related to somatic, mental health, and neurodegenerative processes (e.g., amyloid-β and tau, among others) depends in part on intact glymphatic function, which becomes impaired after mTBI. In this viewpoint, we review the current knowledge regarding the association between sleep disturbances and post-mTBI symptoms. We also discuss the role of glymphatic dysfunction as a potential link between mTBI, sleep disruption, and posttraumatic morbidity. We outline a model where glymphatic dysfunction and sleep disruption caused by mTBI may have an additive effect on waste clearance, leading to cerebral dysfunction and impaired recovery. Finally, we review the novel techniques being developed to examine glymphatic function in humans and explore potential interventions to alter glymphatic exchange that may offer a novel therapeutic approach to those experiencing poor sleep and prolonged symptoms after mTBI.
Collapse
|
28
|
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.
Collapse
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.)
| |
Collapse
|
29
|
Automated grading of enlarged perivascular spaces in clinical imaging data of an acute stroke cohort using an interpretable, 3D deep learning framework. Sci Rep 2022; 12:788. [PMID: 35039524 PMCID: PMC8764081 DOI: 10.1038/s41598-021-04287-4] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Accepted: 12/13/2021] [Indexed: 01/10/2023] Open
Abstract
Enlarged perivascular spaces (EPVS), specifically in stroke patients, has been shown to strongly correlate with other measures of small vessel disease and cognitive impairment at 1 year follow-up. Typical grading of EPVS is often challenging and time consuming and is usually based on a subjective visual rating scale. The purpose of the current study was to develop an interpretable, 3D neural network for grading enlarged perivascular spaces (EPVS) severity at the level of the basal ganglia using clinical-grade imaging in a heterogenous acute stroke cohort, in the context of total cerebral small vessel disease (CSVD) burden. T2-weighted images from a retrospective cohort of 262 acute stroke patients, collected in 2015 from 5 regional medical centers, were used for analyses. Patients were given a label of 0 for none-to-mild EPVS (< 10) and 1 for moderate-to-severe EPVS (≥ 10). A three-dimensional residual network of 152 layers (3D-ResNet-152) was created to predict EPVS severity and 3D gradient class activation mapping (3DGradCAM) was used for visual interpretation of results. Our model achieved an accuracy 0.897 and area-under-the-curve of 0.879 on a hold-out test set of 15% of the total cohort (n = 39). 3DGradCAM showed areas of focus that were in physiologically valid locations, including other prevalent areas for EPVS. These maps also suggested that distribution of class activation values is indicative of the confidence in the model's decision. Potential clinical implications of our results include: (1) support for feasibility of automated of EPVS scoring using clinical-grade neuroimaging data, potentially alleviating rater subjectivity and improving confidence of visual rating scales, and (2) demonstration that explainable models are critical for clinical translation.
Collapse
|
30
|
Yim Y, Moon WJ. An Enlarged Perivascular Space: Clinical Relevance and the Role of Imaging in Aging and Neurologic Disorders. JOURNAL OF THE KOREAN SOCIETY OF RADIOLOGY 2022; 83:538-558. [PMID: 36238506 PMCID: PMC9514531 DOI: 10.3348/jksr.2022.0049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Revised: 04/28/2022] [Accepted: 05/05/2022] [Indexed: 11/15/2022]
Affiliation(s)
- Younghee Yim
- Department of Radiology, Chung-Ang University Hospital, Chung-Ang University College of Medicine, Seoul, Korea
| | - Won-Jin Moon
- Department of Radiology, Konkuk University Medical Center, Konkuk University School of Medicine, Seoul, Korea
| |
Collapse
|
31
|
Piantino J, Schwartz DL, Luther M, Newgard C, Silbert L, Raskind M, Pagulayan K, Kleinhans N, Iliff J, Peskind E. Link between Mild Traumatic Brain Injury, Poor Sleep, and Magnetic Resonance Imaging: Visible Perivascular Spaces in Veterans. J Neurotrauma 2021; 38:2391-2399. [PMID: 33599176 PMCID: PMC8390772 DOI: 10.1089/neu.2020.7447] [Citation(s) in RCA: 48] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Impaired clearance of perivascular waste in the brain may play a critical role in morbidity after mild traumatic brain injury (mTBI). We aimed to determine the effect of mTBI on the burden of magnetic resonance imaging (MRI)-visible perivascular spaces (PVSs) in a cohort of U.S. military veterans and whether sleep modulates this effect. We also investigated the correlation between PVS burden and severity of persistent post-concussive symptoms. Fifty-six Iraq/Afghanistan veterans received 3 Tesla MRI as part of a prospective cohort study on military blast mTBI. White matter PVS burden (i.e., number and volume) was calculated using an established automated segmentation algorithm. Multi-variate regression was used to establish the association between mTBIs sustained in the military and PVS burden. Covariates included age, blood pressure, number of impact mTBIs outside the military, and blast exposures. Correlation coefficients were calculated between PVS burden and severity of persistent post-concussive symptoms. There was a significant positive relationship between the number of mTBIs sustained in the military and both PVS number and volume (p = 0.04). A significant interaction was found between mTBI and poor sleep on PVS volume (p = 0.04). A correlation was found between PVS number and volume, as well as severity of postconcussive symptoms (p = 0.03). Further analysis revealed a moderate correlation between PVS number and volume, as well as balance problems (p < 0.001). In Iraq/Afghanistan veterans, mTBI is associated with an increase in PVS burden. Further, an interaction exists between mTBI and poor sleep on PVS burden. Increased PVS burden, which may indicate waste clearance dysfunction, is associated with persistent post-concussive symptom severity.
Collapse
Affiliation(s)
- Juan Piantino
- Department of Pediatrics, Division of Child Neurology, Doernbecher Children's Hospital, Department of Emergency Medicine, Oregon Health & Science University, Portland, Oregon, USA
| | - Daniel L. Schwartz
- Layton Aging and Alzheimer's Disease Center, Neurology, Department of Emergency Medicine, Oregon Health & Science University, Portland, Oregon, USA
- Advanced Imaging Research Center, Department of Emergency Medicine, Oregon Health & Science University, Portland, Oregon, USA
| | - Madison Luther
- Department of Pediatrics, Division of Child Neurology, Doernbecher Children's Hospital, Department of Emergency Medicine, Oregon Health & Science University, Portland, Oregon, USA
| | - Craig Newgard
- Center for Policy and Research in Emergency Medicine, Department of Emergency Medicine, Oregon Health & Science University, Portland, Oregon, USA
| | - Lisa Silbert
- Layton Aging and Alzheimer's Disease Center, Neurology, Department of Emergency Medicine, Oregon Health & Science University, Portland, Oregon, USA
- Portland Veterans Affairs Medical Center, Neurology, Portland, Oregon, USA
| | - Murray Raskind
- Veterans Affairs Northwest Network Mental Illness, Research, Education, and Clinical Center, Veterans Affairs Puget Sound Health Care System, Seattle, Washington, USA
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, Washington, USA
| | - Kathleen Pagulayan
- Veterans Affairs Northwest Network Mental Illness, Research, Education, and Clinical Center, Veterans Affairs Puget Sound Health Care System, Seattle, Washington, USA
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, Washington, USA
| | - Natalia Kleinhans
- Department of Radiology, University of Washington School of Medicine, Seattle, Washington, USA
| | - Jeffrey Iliff
- Veterans Affairs Northwest Network Mental Illness, Research, Education, and Clinical Center, Veterans Affairs Puget Sound Health Care System, Seattle, Washington, USA
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, Washington, USA
- Department of Neurology, University of Washington School of Medicine, Seattle, Washington, USA
| | - Elaine Peskind
- Veterans Affairs Northwest Network Mental Illness, Research, Education, and Clinical Center, Veterans Affairs Puget Sound Health Care System, Seattle, Washington, USA
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, Washington, USA
| |
Collapse
|
32
|
Boutinaud P, Tsuchida A, Laurent A, Adonias F, Hanifehlou Z, Nozais V, Verrecchia V, Lampe L, Zhang J, Zhu YC, Tzourio C, Mazoyer B, Joliot M. 3D Segmentation of Perivascular Spaces on T1-Weighted 3 Tesla MR Images With a Convolutional Autoencoder and a U-Shaped Neural Network. Front Neuroinform 2021; 15:641600. [PMID: 34262443 PMCID: PMC8273917 DOI: 10.3389/fninf.2021.641600] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Accepted: 05/24/2021] [Indexed: 11/13/2022] Open
Abstract
We implemented a deep learning (DL) algorithm for the 3-dimensional segmentation of perivascular spaces (PVSs) in deep white matter (DWM) and basal ganglia (BG). This algorithm is based on an autoencoder and a U-shaped network (U-net), and was trained and tested using T1-weighted magnetic resonance imaging (MRI) data from a large database of 1,832 healthy young adults. An important feature of this approach is the ability to learn from relatively sparse data, which gives the present algorithm a major advantage over other DL algorithms. Here, we trained the algorithm with 40 T1-weighted MRI datasets in which all "visible" PVSs were manually annotated by an experienced operator. After learning, performance was assessed using another set of 10 MRI scans from the same database in which PVSs were also traced by the same operator and were checked by consensus with another experienced operator. The Sorensen-Dice coefficients for PVS voxel detection in DWM (resp. BG) were 0.51 (resp. 0.66), and 0.64 (resp. 0.71) for PVS cluster detection (volume threshold of 0.5 within a range of 0 to 1). Dice values above 0.90 could be reached for detecting PVSs larger than 10 mm3 and 0.95 for PVSs larger than 15 mm3. We then applied the trained algorithm to the rest of the database (1,782 individuals). The individual PVS load provided by the algorithm showed a high agreement with a semi-quantitative visual rating done by an independent expert rater, both for DWM and for BG. Finally, we applied the trained algorithm to an age-matched sample from another MRI database acquired using a different scanner. We obtained a very similar distribution of PVS load, demonstrating the interoperability of this algorithm.
Collapse
Affiliation(s)
| | - Ami Tsuchida
- UMR 5293, GIN, IMN, Univ. Bordeaux, Bordeaux, France
- UMR 5293, GIN, IMN, CNRS, Bordeaux, France
- UMR 5293, GIN, IMN, CEA, Bordeaux, France
| | - Alexandre Laurent
- UMR 5293, GIN, IMN, Univ. Bordeaux, Bordeaux, France
- UMR 5293, GIN, IMN, CNRS, Bordeaux, France
- UMR 5293, GIN, IMN, CEA, Bordeaux, France
| | - Filipa Adonias
- UMR 5293, GIN, IMN, Univ. Bordeaux, Bordeaux, France
- UMR 5293, GIN, IMN, CNRS, Bordeaux, France
- UMR 5293, GIN, IMN, CEA, Bordeaux, France
| | - Zahra Hanifehlou
- Genesislab, Bordeaux, France
- Faculty of Computer Engineering, University of Isfahan, Isfahan, Iran
| | - Victor Nozais
- Genesislab, Bordeaux, France
- UMR 5293, GIN, IMN, Univ. Bordeaux, Bordeaux, France
- UMR 5293, GIN, IMN, CNRS, Bordeaux, France
- UMR 5293, GIN, IMN, CEA, Bordeaux, France
| | - Violaine Verrecchia
- Genesislab, Bordeaux, France
- UMR 5293, GIN, IMN, Univ. Bordeaux, Bordeaux, France
- UMR 5293, GIN, IMN, CNRS, Bordeaux, France
- UMR 5293, GIN, IMN, CEA, Bordeaux, France
| | - Leonie Lampe
- Integrative Model-based Cognitive Neuroscience Research Unit Universiteit van Amsterdam, Amsterdam, Netherlands & Max Planck Institute for Human Cognitive and Brain Sciences Leipzig, Germany
| | - Junyi Zhang
- Department of Neurology, Peking Union Medical College Hospital, Beijing, China
| | - Yi-Cheng Zhu
- Department of Neurology, Peking Union Medical College Hospital, Beijing, China
| | - Christophe Tzourio
- U1219, INSERM, Bordeaux Population Health, University Bordeaux, Bordeaux, France
- Centre Hospitalier Universitaire de Bordeaux, Bordeaux, France
| | - Bernard Mazoyer
- Genesislab, Bordeaux, France
- UMR 5293, GIN, IMN, Univ. Bordeaux, Bordeaux, France
- UMR 5293, GIN, IMN, CNRS, Bordeaux, France
- UMR 5293, GIN, IMN, CEA, Bordeaux, France
- Centre Hospitalier Universitaire de Bordeaux, Bordeaux, France
| | - Marc Joliot
- Genesislab, Bordeaux, France
- UMR 5293, GIN, IMN, Univ. Bordeaux, Bordeaux, France
- UMR 5293, GIN, IMN, CNRS, Bordeaux, France
- UMR 5293, GIN, IMN, CEA, Bordeaux, France
| |
Collapse
|
33
|
Gouveia-Freitas K, Bastos-Leite AJ. Perivascular spaces and brain waste clearance systems: relevance for neurodegenerative and cerebrovascular pathology. Neuroradiology 2021; 63:1581-1597. [PMID: 34019111 PMCID: PMC8460534 DOI: 10.1007/s00234-021-02718-7] [Citation(s) in RCA: 58] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Accepted: 04/12/2021] [Indexed: 12/28/2022]
Abstract
Perivascular spaces (PVS) of the brain, often called Virchow-Robin spaces, comprise fluid, cells and connective tissue, and are externally limited by astrocytic endfeet. PVS are involved in clearing brain waste and belong to the "glymphatic" system and/or the "intramural periarterial drainage" pathway through the basement membranes of the arteries. Related brain waste clearance systems include the blood-brain barrier, scavenger cells, cerebrospinal fluid, perineural lymphatic drainage pathways and the newly characterised meningeal lymphatic vessels. Any functional abnormality of PVS or related clearance systems might lead to accumulation of brain waste. It has been postulated that PVS enlargement can be secondary to accumulation of β-amyloid. Lack of integrity of the vascular wall, microbleeds, cerebral amyloid angiopathy (CAA) and enlarged PVS often occur in the preclinical stages of Alzheimer's disease, preceding substantial brain atrophy. PVS enlargement in the form of état criblé at the basal ganglia has also been considered to reflect focal atrophy, most probably secondary to ischaemic injury, based upon both pathological and imaging arguments. In addition, distinct topographic patterns of enlarged PVS are related to different types of microangiopathy: CAA is linked to enlarged juxtacortical PVS, whereas subjects with vascular risk factors tend to have enlarged PVS in the basal ganglia. Therefore, enlarged PVS are progressively being regarded as a marker of neurodegenerative and cerebrovascular pathology. The present review addresses the evolving concept of PVS and brain waste clearance systems, the potential relevance of their dysfunction to neurodegenerative and cerebrovascular pathology, and potential therapeutic approaches of interest.
Collapse
Affiliation(s)
- Kaylene Gouveia-Freitas
- Faculty of Medicine, University of Porto, Alameda do Professor Hernâni Monteiro, 4200-319, Porto, Portugal
| | - António J Bastos-Leite
- Faculty of Medicine, University of Porto, Alameda do Professor Hernâni Monteiro, 4200-319, Porto, Portugal.
| |
Collapse
|
34
|
Piantino J, Boespflug EL, Schwartz DL, Luther M, Morales AM, Lin A, Fossen RV, Silbert L, Nagel BJ. Characterization of MR Imaging-Visible Perivascular Spaces in the White Matter of Healthy Adolescents at 3T. AJNR Am J Neuroradiol 2020; 41:2139-2145. [PMID: 33033050 PMCID: PMC7658833 DOI: 10.3174/ajnr.a6789] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Accepted: 07/17/2020] [Indexed: 01/30/2023]
Abstract
BACKGROUND AND PURPOSE Perivascular spaces play a role in cerebral waste removal and neuroinflammation. Our aim was to provide data regarding the burden of MR imaging-visible perivascular spaces in white matter in healthy adolescents using an automated segmentation method and to establish relationships between common demographic characteristics and perivascular space burden. MATERIALS AND METHODS One hundred eighteen 12- to 21-year-old subjects underwent T1- and T2-weighted 3T MR imaging as part of the National Consortium on Alcohol and Neurodevelopment in Adolescence. Perivascular spaces were identified in WM on T2-weighted imaging using a local heterogeneity approach coupled with morphologic constraints, and their spatial distribution and geometric characteristics were assessed. RESULTS MR imaging-visible perivascular spaces were identified in all subjects (range, 16-287). Males had a significantly higher number of perivascular spaces than females: males, mean, 98.4 ± 50.5, versus females, 70.7 ± 36.1, (P < .01). Perivascular space burden was bilaterally symmetric (r > 0.4, P < .01), and perivascular spaces were more common in the frontal and parietal lobes than in the temporal and occipital lobes (P < .01). Age and pubertal status were not significantly associated with perivascular space burden. CONCLUSIONS Despite a wide range of burden, perivascular spaces are present in all healthy adolescents. Perivascular space burden is higher in adolescent males than in females, regardless of age and pubertal status. In this population, perivascular spaces are highly symmetric. Although widely reported as a feature of the aging brain, awareness of the presence of perivascular spaces in a cohort of healthy adolescents provides the foundation for further research regarding the role of these structural variants in health and disease.
Collapse
Affiliation(s)
- J Piantino
- From the Department of Pediatrics (J.P., M.L.), Division of Child Neurology, Doernbecher Children's Hospital
| | - E L Boespflug
- Department of Neurology (E.L.B., D.L.S., L.S.), Layton Aging and Alzheimer's Disease Center
| | - D L Schwartz
- Department of Neurology (E.L.B., D.L.S., L.S.), Layton Aging and Alzheimer's Disease Center
- Advanced Imaging Research Center (D.L.S.)
| | - M Luther
- From the Department of Pediatrics (J.P., M.L.), Division of Child Neurology, Doernbecher Children's Hospital
| | - A M Morales
- Department of Psychiatry (A.M.M., R.V.F., B.J.N.)
| | - A Lin
- Department of Emergency Medicine (A.L.), Center for Policy and Research in Emergency Medicine
| | - R V Fossen
- Department of Psychiatry (A.M.M., R.V.F., B.J.N.)
| | - L Silbert
- Department of Neurology (E.L.B., D.L.S., L.S.), Layton Aging and Alzheimer's Disease Center
- Department of Neurology (L.S.), Portland Veterans Affairs Medical Center, Portland, Oregon
| | - B J Nagel
- Department of Psychiatry (A.M.M., R.V.F., B.J.N.)
| |
Collapse
|
35
|
Badai J, Bu Q, Zhang L. Review of Artificial Intelligence Applications and Algorithms for Brain Organoid Research. Interdiscip Sci 2020; 12:383-394. [PMID: 32833194 DOI: 10.1007/s12539-020-00386-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Revised: 08/04/2020] [Accepted: 08/12/2020] [Indexed: 02/07/2023]
Abstract
The human brain organoid is a miniature three-dimensional tissue culture that can simulate the structure and function of the brain in an in vitro culture environment. Although we consider that human brain organoids could be used to understand brain development and diseases, experimental models of human brain organoids are so highly variable that we apply artificial intelligence (AI) techniques to investigate the development mechanism of the human brain. Therefore, this study briefly reviewed commonly used AI applications for human brain organoid-magnetic resonance imaging, electroencephalography, and gene editing techniques, as well as related AI algorithms. Finally, we discussed the limitations, challenges, and future study direction of AI-based technology for human brain organoids.
Collapse
Affiliation(s)
- Jiayidaer Badai
- College of Computer Science, Sichuan University, Chengdu, 610065, China
| | - Qian Bu
- Department of Food Engineering, College of Biomass Science and Engineering, Sichuan University, Chengdu, 610065, China
| | - Le Zhang
- College of Computer Science, Sichuan University, Chengdu, 610065, China. .,Medical Big Data Center of Sichuan University, Chengdu, 610065, China. .,PERA Corporation Ltd., Beijing, 100025, China.
| |
Collapse
|
36
|
Enlarged perivascular spaces in multiple sclerosis on magnetic resonance imaging: a systematic review and meta-analysis. J Neurol 2020; 267:3199-3212. [PMID: 32535680 PMCID: PMC7577911 DOI: 10.1007/s00415-020-09971-5] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2020] [Revised: 05/29/2020] [Accepted: 06/01/2020] [Indexed: 01/24/2023]
Abstract
BACKGROUND Perivascular spaces can become detectable on magnetic resonance imaging (MRI) upon enlargement, referred to as enlarged perivascular spaces (EPVS) or Virchow-Robin spaces. EPVS have been linked to small vessel disease. Some studies have also indicated an association of EPVS to neuroinflammation and/or neurodegeneration. However, there is conflicting evidence with regards to their potential as a clinically relevant imaging biomarker in multiple sclerosis (MS). METHODS To perform a systematic review and meta-analysis of EPVS as visualized by MRI in MS. Nine out of 299 original studies addressing EPVS in humans using MRI were eligible for the systematic review and meta-analysis including a total of 457 MS patients and 352 control subjects. RESULTS In MS, EPVS have been associated with cognitive decline, contrast-enhancing MRI lesions, and brain atrophy. Yet, these associations were not consistent between studies. The meta-analysis revealed that MS patients have greater EPVS prevalence (odds ratio = 4.61, 95% CI = [1.84; 11.60], p = 0.001) as well as higher EPVS counts (standardized mean difference [SMD] = 0.46, 95% CI = [0.26; 0.67], p < 0.001) and larger volumes (SMD = 0.88, 95% CI = [0.19; 1.56], p = 0.01) compared to controls. CONCLUSIONS Available literature suggests a higher EPVS burden in MS patients compared to controls. The association of EPVS to neuroinflammatory or -degenerative pathology in MS remains inconsistent. Thus, there is currently insufficient evidence supporting EPVS as diagnostic and/or prognostic marker in MS. In order to benefit future comparisons of studies, we propose recommendations on EPVS assessment standardization in MS. PROSPERO No: CRD42019133946.
Collapse
|
37
|
Jie W, Lin G, Liu Z, Zhou H, Lin L, Liang G, Ou M, Lin M. The Relationship Between Enlarged Perivascular Spaces and Cognitive Function: A Meta-Analysis of Observational Studies. Front Pharmacol 2020; 11:715. [PMID: 32499704 PMCID: PMC7243265 DOI: 10.3389/fphar.2020.00715] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Accepted: 04/30/2020] [Indexed: 01/11/2023] Open
Abstract
Enlarged perivascular spaces (ePVS), visible on magnetic resonance imaging (MRI), are associated with aortic pulse wave changes produced by arterial stiffening. However, the relationship between ePVS and cognition is still unclear. We aimed to benchmark current knowledge of associations between ePVS and cognitive function using a meta-analysis of all available published data. We searched three databases for studies examining ePVS and cognition, identified seven studies involving 7,816 participants, plotted multivariate-adjusted odds ratio (OR) and 95% CI and generated summary OR with a fixed effects model. EPVS were related to the risk of impaired cognition (OR = 1.387, 95% CI = 1.198–1.606, z=4.38, P<0.001) with low heterogeneity. There was publication bias, which could be corrected by trimming and supplementation (OR=1.297, 95% CI= 1.130–1.490). EPVS were associated with impaired cognition and may be a sign of cognitive impairment rather than particular diseases. More studies are required to validate ePVS as a measurable risk marker for cognition using consistent methods to determinea characteristic appearance of ePVS.
Collapse
Affiliation(s)
- Wanxin Jie
- Department of Neurology, Institute of Neurology, Guangdong Key Laboratory of Age-Related Cardiac and Cerebral Diseases, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
| | - Guanghong Lin
- Medical Intensive Care Unit, Central People's Hospital of Zhanjiang, Zhanjiang, China
| | - Zhou Liu
- Department of Neurology, Institute of Neurology, Guangdong Key Laboratory of Age-Related Cardiac and Cerebral Diseases, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
| | - Haihong Zhou
- Department of Neurology, Institute of Neurology, Guangdong Key Laboratory of Age-Related Cardiac and Cerebral Diseases, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
| | - Lifeng Lin
- Department of Neurology, Institute of Neurology, Guangdong Key Laboratory of Age-Related Cardiac and Cerebral Diseases, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
| | - Guocong Liang
- Department of Neurology, Institute of Neurology, Guangdong Key Laboratory of Age-Related Cardiac and Cerebral Diseases, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
| | - Mingqian Ou
- Department of Neurology, Institute of Neurology, Guangdong Key Laboratory of Age-Related Cardiac and Cerebral Diseases, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
| | - Meijun Lin
- Department of Neurology, Institute of Neurology, Guangdong Key Laboratory of Age-Related Cardiac and Cerebral Diseases, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
| |
Collapse
|