51
|
Jian X, Xu F, Yang M, Zhang M, Yun W. Correlation between enlarged perivascular space and brain white matter hyperintensities in patients with recent small subcortical infarct. Brain Behav 2023; 13:e3168. [PMID: 37464257 PMCID: PMC10498058 DOI: 10.1002/brb3.3168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 06/28/2023] [Accepted: 07/08/2023] [Indexed: 07/20/2023] Open
Abstract
BACKGROUND This study aimed to investigate the correlation between enlarged perivascular space (EPVS) and white matter hyperintensities (WMH) at different locations in patients with recent small subcortical infarct (RSSI). METHODS Data were collected from patients with RSSI who were hospitalized at Changzhou Second People's Hospital between October 2020 and December 2021. All patients underwent cranial magnetic resonance imaging, and the grades of EPVS and WMH were assessed, including basal ganglia EPVS (BG-EPVS), centrum semiovale EPVS (CSO-EPVS), deep WMH (DWMH), and periventricular WMH (PWMH). The volumes of EPVS and WMH at different locations were quantified using 3D Slicer software. Patients were grouped according to the severity of BG-EPVS and CSO-EPVS. Univariate and multivariate analyses were used to analyze the relationship between EPVS and WMH. RESULTS A total of 215 patients with RSSI were included in the analysis. Patients with moderate-to-severe BG-EPVS had higher DWMH and PWMH severity than those with mild BG-EPVS, both in terms of volume and grade. There was no significant difference in WMH severity between patients with mild CSO-EPVS and those with moderate-to-severe CSO-EPVS. Multivariate analysis indicated that after adjustments were made for confounding factors, DWMH volume (β = 0.311; 95% CI, 0.089-0.400; p = .002) and PWMH volume (β = 0.296; 95% CI, 0.083-0.424; p = .004) were independently associated with BG-EPVS. Pearson correlation showed that PWMH volume (r = .589; p < .001) and DWMH volume (r = .596; p < .001) were positively related to BG-EPVS volume. CONCLUSION DWMH and PWMH are closely related to BG-EPVS in patients with RSSI.
Collapse
Affiliation(s)
- Xiuli Jian
- Department of NeurologyChangzhou Second People's Hospital, Changzhou Medical Center, Nanjing Medical UniversityChangzhouChina
| | - Fubiao Xu
- Department of CardiologyHeze Municipal HospitalHezeChina
| | - Mi Yang
- Department of NeurologyChangzhou Second People's Hospital, Changzhou Medical Center, Nanjing Medical UniversityChangzhouChina
| | - Min Zhang
- Department of NeurologyChangzhou Second People's Hospital, Changzhou Medical Center, Nanjing Medical UniversityChangzhouChina
| | - Wenwei Yun
- Department of NeurologyChangzhou Second People's Hospital, Changzhou Medical Center, Nanjing Medical UniversityChangzhouChina
| |
Collapse
|
52
|
Affleck AJ, Sachdev PS, Halliday GM. Past antihypertensive medication use is associated with lower levels of small vessel disease and lower Aβ plaque stage in the brains of older individuals. Neuropathol Appl Neurobiol 2023; 49:e12922. [PMID: 37431095 PMCID: PMC10947144 DOI: 10.1111/nan.12922] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Revised: 05/22/2023] [Accepted: 06/24/2023] [Indexed: 07/12/2023]
Abstract
AIMS This study assesses the association of antihypertensive medication use on the severities of neuropathological cerebrovascular disease (CVD excluding lobar infarction) in older individuals. METHODS Clinical and neuropathological data were retrieved for 149 autopsy cases >75 years old with or without CVD or Alzheimer's disease and no other neuropathological diagnoses. Clinical data included hypertension status, hypertension diagnosis, antihypertensive medication use, antihypertensive medication dose (where available) and clinical dementia rating (CDR). Neuropathological CVD severity was evaluated for differences with anti-hypertensive medication usage. RESULTS Antihypertensive medication use was associated with less severe white matter small vessel disease (SVD, mainly perivascular dilatation and rarefaction), with a 5.6-14.4 times greater likelihood of less severe SVD if medicated. No significant relationship was detected between infarction (presence, type, number and size), lacunes or cerebral amyloid angiopathy and antihypertensive medication use. Only increased white matter rarefaction/oedema and not perivascular dilation was associated with Alzheimer's pathology, with a 4.3 times greater likelihood of reduced Aβ progression through the brain if white matter rarefaction severity was none or mild. Antihypertensive medication use was associated with reduced Aβ progression but only in those with moderate to severe white matter SVD. CONCLUSIONS This histopathological study provides further evidence that antihypertensive medication use in older individuals is associated with white matter SVD and not with other CVD pathologies. This is mainly due to a reduction in white matter perivascular dilation and rarefaction/oedema. Even in those with moderate to severe white matter SVD, antihypertensive medication use reduced rarefaction and Aβ propagation through the brain.
Collapse
Affiliation(s)
- Andrew J. Affleck
- Neuroscience Research Australia (NeuRA)SydneyAustralia
- Centre for Health Brain Ageing (CHeBA), Discipline of Psychiatry and Mental Health, Faculty of MedicineUniversity of New South WalesSydneyAustralia
| | - Perminder S. Sachdev
- Centre for Health Brain Ageing (CHeBA), Discipline of Psychiatry and Mental Health, Faculty of MedicineUniversity of New South WalesSydneyAustralia
- Neuropsychiatric InstituteThe Prince of Wales HospitalSydneyAustralia
| | - Glenda M. Halliday
- Neuroscience Research Australia (NeuRA)SydneyAustralia
- School of Medical Sciences, Faculty of MedicineUniversity of New South WalesSydneyAustralia
- Brain and Mind Centre & Faculty of Medicine and Health School of Medical SciencesUniversity of SydneySydneyAustralia
| |
Collapse
|
53
|
Kapoor A, Gaubert A, Yew B, Jang JY, Dutt S, Li Y, Alitin JPM, Nguyen A, Ho JK, Blanken AE, Sible IJ, Marshall A, Shenasa F, Rodgers KE, Martini AC, Head E, Nation DA. Enlarged perivascular spaces and plasma Aβ42/Aβ40 ratio in older adults without dementia. Neurobiol Aging 2023; 128:43-48. [PMID: 37156179 PMCID: PMC10852216 DOI: 10.1016/j.neurobiolaging.2023.04.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 03/30/2023] [Accepted: 04/10/2023] [Indexed: 05/10/2023]
Abstract
Dilation of perivascular spaces (PVS) in the brain may indicate poor fluid drainage due to the accumulation of perivascular cell debris, waste, and proteins, including amyloid-beta (Aβ). No prior study has assessed whether plasma Aβ levels are related to PVS in older adults without dementia. Independently living older adults (N = 56, mean age = 68.2 years; Standard deviation (SD) = 6.5; 30.4% male) free of dementia or clinical stroke were recruited from the community and underwent brain MRI and venipuncture. PVS were qualitatively scored and dichotomized to low PVS burden (scores 0-1,) or high PVS burden (score>1). Plasma was assayed using a Quanterix Simoa Kit to quantify Aβ42 and Aβ40 levels. A significant difference was observed in plasma Aβ42/Aβ40 ratio between low and high PVS burden, controlling for age (F[1, 53] = 5.59, p = 0.022, η2 = 0.10), with lower Aβ42/Aβ40 ratio in the high PVS burden group. Dilation of PVS is associated with a lower plasma Aβ42/Aβ40 ratio, which may indicate higher cortical amyloid deposition. Future longitudinal studies examining PVS changes, and the pathogenesis of AD are warranted.
Collapse
Affiliation(s)
- Arunima Kapoor
- Department of Psychological Science, University of California, Irvine, Irvine, CA, USA
| | - Aimée Gaubert
- Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, Irvine, CA, USA
| | - Belinda Yew
- Department of Psychology, University of Southern California, Los Angeles, CA, USA
| | - Jung Yun Jang
- Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, Irvine, CA, USA
| | - Shubir Dutt
- Department of Psychology, University of Southern California, Los Angeles, CA, USA
| | - Yanrong Li
- Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, Irvine, CA, USA
| | - John Paul M Alitin
- Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, Irvine, CA, USA
| | - Amy Nguyen
- Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, Irvine, CA, USA
| | - Jean K Ho
- Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, Irvine, CA, USA
| | - Anna E Blanken
- San Francisco Veterans Affairs Health Care System & Department of Psychiatry, University of California, San Francisco, San Francisco, CA, USA
| | - Isabel J Sible
- Department of Psychology, University of Southern California, Los Angeles, CA, USA
| | - Anisa Marshall
- Department of Psychology, University of Southern California, Los Angeles, CA, USA
| | - Fatemah Shenasa
- Department of Psychological Science, University of California, Irvine, Irvine, CA, USA
| | - Kathleen E Rodgers
- Center for Innovations in Brain Science, Department of Pharmacology, University of Arizona, Tucson, AZ, USA
| | - Alessandra C Martini
- Department of Pathology and Laboratory Medicine, University of California, Irvine, Irvine, CA, USA
| | - Elizabeth Head
- Department of Pathology and Laboratory Medicine, University of California, Irvine, Irvine, CA, USA
| | - Daniel A Nation
- Department of Psychological Science, University of California, Irvine, Irvine, CA, USA; Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, Irvine, CA, USA.
| |
Collapse
|
54
|
Hayden MR. Brain Injury: Response to Injury Wound-Healing Mechanisms and Enlarged Perivascular Spaces in Obesity, Metabolic Syndrome, and Type 2 Diabetes Mellitus. MEDICINA (KAUNAS, LITHUANIA) 2023; 59:1337. [PMID: 37512148 PMCID: PMC10385746 DOI: 10.3390/medicina59071337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Revised: 07/15/2023] [Accepted: 07/18/2023] [Indexed: 07/30/2023]
Abstract
Embryonic genetic mechanisms are present in the brain and ready to be placed into action upon cellular injury, termed the response to injury wound-healing (RTIWH) mechanism. When injured, regional brain endothelial cells initially undergo activation and dysfunction with initiation of hemostasis, inflammation (peripheral leukocytes, innate microglia, and perivascular macrophage cells), proliferation (astrogliosis), remodeling, repair, and resolution phases if the injurious stimuli are removed. In conditions wherein the injurious stimuli are chronic, as occurs in obesity, metabolic syndrome, and type 2 diabetes mellitus, this process does not undergo resolution and there is persistent RTIWH with remodeling. Indeed, the brain is unique, in that it utilizes its neuroglia: the microglia cell, along with peripheral inflammatory cells and its astroglia, instead of peripheral scar-forming fibrocytes/fibroblasts. The brain undergoes astrogliosis to form a gliosis scar instead of a fibrosis scar to protect the surrounding neuropil from regional parenchymal injury. One of the unique and evolving remodeling changes in the brain is the development of enlarged perivascular spaces (EPVSs), which is the focus of this brief review. EPVSs are important since they serve as a biomarker for cerebral small vessel disease and also represent an impairment of the effluxing glymphatic system that is important for the clearance of metabolic waste from the interstitial fluid to the cerebrospinal fluid, and disposal. Therefore, it is important to better understand how the RTIWH mechanism is involved in the development of EPVSs that are closely associated with and important to the development of premature and age-related cerebrovascular and neurodegenerative diseases with impaired cognition.
Collapse
Affiliation(s)
- Melvin R Hayden
- Diabetes and Cardiovascular Disease Center, Department of Internal Medicine, Endocrinology Diabetes and Metabolism, University of Missouri School of Medicine, One Hospital Drive, Columbia, MO 65211, USA
| |
Collapse
|
55
|
Duering M, Biessels GJ, Brodtmann A, Chen C, Cordonnier C, de Leeuw FE, Debette S, Frayne R, Jouvent E, Rost NS, Ter Telgte A, Al-Shahi Salman R, Backes WH, Bae HJ, Brown R, Chabriat H, De Luca A, deCarli C, Dewenter A, Doubal FN, Ewers M, Field TS, Ganesh A, Greenberg S, Helmer KG, Hilal S, Jochems ACC, Jokinen H, Kuijf H, Lam BYK, Lebenberg J, MacIntosh BJ, Maillard P, Mok VCT, Pantoni L, Rudilosso S, Satizabal CL, Schirmer MD, Schmidt R, Smith C, Staals J, Thrippleton MJ, van Veluw SJ, Vemuri P, Wang Y, Werring D, Zedde M, Akinyemi RO, Del Brutto OH, Markus HS, Zhu YC, Smith EE, Dichgans M, Wardlaw JM. Neuroimaging standards for research into small vessel disease-advances since 2013. Lancet Neurol 2023; 22:602-618. [PMID: 37236211 DOI: 10.1016/s1474-4422(23)00131-x] [Citation(s) in RCA: 338] [Impact Index Per Article: 169.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 03/03/2023] [Accepted: 03/28/2023] [Indexed: 05/28/2023]
Abstract
Cerebral small vessel disease (SVD) is common during ageing and can present as stroke, cognitive decline, neurobehavioural symptoms, or functional impairment. SVD frequently coexists with neurodegenerative disease, and can exacerbate cognitive and other symptoms and affect activities of daily living. Standards for Reporting Vascular Changes on Neuroimaging 1 (STRIVE-1) categorised and standardised the diverse features of SVD that are visible on structural MRI. Since then, new information on these established SVD markers and novel MRI sequences and imaging features have emerged. As the effect of combined SVD imaging features becomes clearer, a key role for quantitative imaging biomarkers to determine sub-visible tissue damage, subtle abnormalities visible at high-field strength MRI, and lesion-symptom patterns, is also apparent. Together with rapidly emerging machine learning methods, these metrics can more comprehensively capture the effect of SVD on the brain than the structural MRI features alone and serve as intermediary outcomes in clinical trials and future routine practice. Using a similar approach to that adopted in STRIVE-1, we updated the guidance on neuroimaging of vascular changes in studies of ageing and neurodegeneration to create STRIVE-2.
Collapse
Affiliation(s)
- Marco Duering
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany; Medical Image Analysis Center, University of Basel, Basel, Switzerland; Department of Biomedical Engineering, University of Basel, Basel, Switzerland.
| | - Geert Jan Biessels
- Department of Neurology, University Medical Center Utrecht, Utrecht, Netherlands
| | - Amy Brodtmann
- Cognitive Health Initiative, Central Clinical School, Monash University, Melbourne, VIC, Australia; Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, VIC, Australia
| | - Christopher Chen
- Department of Pharmacology, Memory Aging and Cognition Centre, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Psychological Medicine, Memory Aging and Cognition Centre, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Charlotte Cordonnier
- Université de Lille, INSERM, CHU Lille, U1172-Lille Neuroscience and Cognition (LilNCog), Lille, France
| | - Frank-Erik de Leeuw
- Department of Neurology, Donders Center for Medical Neuroscience, Radboudumc, Nijmegen, Netherlands
| | - Stéphanie Debette
- Bordeaux Population Health Research Center, University of Bordeaux, INSERM, UMR 1219, Bordeaux, France; Department of Neurology, Institute for Neurodegenerative Diseases, CHU de Bordeaux, Bordeaux, France
| | - Richard Frayne
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada; Department of Radiology, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada; Seaman Family MR Research Centre, Foothills Medical Centre, University of Calgary, Calgary, AB, Canada
| | - Eric Jouvent
- AP-HP, Lariboisière Hospital, Translational Neurovascular Centre, FHU NeuroVasc, Université Paris Cité, Paris, France; Université Paris Cité, INSERM UMR 1141, NeuroDiderot, Paris, France
| | - Natalia S Rost
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | | | | | - Walter H Backes
- School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, Netherlands; School for Cardiovascular Diseases, Maastricht University Medical Center, Maastricht, Netherlands; Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, Netherlands
| | - Hee-Joon Bae
- Department of Neurology, Seoul National University College of Medicine, Seoul, South Korea; Cerebrovascular Disease Center, Seoul National University Bundang Hospital, Seongn-si, South Korea
| | - Rosalind Brown
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK; UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Hugues Chabriat
- Centre Neurovasculaire Translationnel, CERVCO, INSERM U1141, FHU NeuroVasc, Université Paris Cité, Paris, France
| | - Alberto De Luca
- Image Sciences Institute, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, Netherlands
| | - Charles deCarli
- Department of Neurology and Center for Neuroscience, University of California, Davis, CA, USA
| | - Anna Dewenter
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Fergus N Doubal
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Michael Ewers
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Thalia S Field
- Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada; Vancouver Stroke Program, Division of Neurology, University of British Columbia, Vancouver, BC, Canada
| | - Aravind Ganesh
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada; Department of Community Health Sciences, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada; Mathison Centre for Mental Health Research and Education, University of Calgary, Calgary, AB, Canada
| | - Steven Greenberg
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Karl G Helmer
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Athinoula A Martinos Center for Biomedical Imaging, Boston, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Saima Hilal
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
| | - Angela C C Jochems
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK; UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Hanna Jokinen
- Division of Neuropsychology, HUS Neurocenter, Helsinki University Hospital, University of Helsinki, Helsinki, Finland; Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Hugo Kuijf
- Image Sciences Institute, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, Netherlands
| | - Bonnie Y K Lam
- Division of Neurology, Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Gerald Choa Neuroscience Institute, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Margaret KL Cheung Research Centre for Management of Parkinsonism, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Therese Pei Fong Chow Research Centre for Prevention of Dementia, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Lui Che Woo Institute of Innovative Medicine, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Lau Tat-chuen Research Centre of Brain Degenerative Diseases in Chinese, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Jessica Lebenberg
- AP-HP, Lariboisière Hospital, Translational Neurovascular Centre, FHU NeuroVasc, Université Paris Cité, Paris, France; Université Paris Cité, INSERM UMR 1141, NeuroDiderot, Paris, France
| | - Bradley J MacIntosh
- Sandra E Black Centre for Brain Resilience and Repair, Hurvitz Brain Sciences, Physical Sciences Platform, Sunnybrook Research Institute, Toronto, ON, Canada; Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada; Computational Radiology and Artificial Intelligence Unit, Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Pauline Maillard
- Department of Neurology and Center for Neuroscience, University of California, Davis, CA, USA
| | - Vincent C T Mok
- Division of Neurology, Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Gerald Choa Neuroscience Institute, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Margaret KL Cheung Research Centre for Management of Parkinsonism, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Therese Pei Fong Chow Research Centre for Prevention of Dementia, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Lui Che Woo Institute of Innovative Medicine, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Lau Tat-chuen Research Centre of Brain Degenerative Diseases in Chinese, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Leonardo Pantoni
- Department of Biomedical and Clinical Science, University of Milan, Milan, Italy
| | - Salvatore Rudilosso
- Comprehensive Stroke Center, Department of Neuroscience, Hospital Clinic and August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain
| | - Claudia L Satizabal
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA; Department of Population Health Sciences, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA; Department of Neurology, Boston University Medical Center, Boston, MA, USA; Framingham Heart Study, Framingham, MA, USA
| | - Markus D Schirmer
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | | | - Colin Smith
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Julie Staals
- School for Cardiovascular Diseases, Maastricht University Medical Center, Maastricht, Netherlands; Department of Neurology, Maastricht University Medical Center, Maastricht, Netherlands
| | - Michael J Thrippleton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK; Edinburgh Imaging and Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | | | | | - Yilong Wang
- Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - David Werring
- Stroke Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Marialuisa Zedde
- Neurology Unit, Stroke Unit, Department of Neuromotor Physiology and Rehabilitation, Azienda Unità Sanitaria-IRCCS di Reggio Emilia, Reggio Emilia, Italy
| | - Rufus O Akinyemi
- Neuroscience and Ageing Research Unit, Institute for Advanced Medical Research and Training, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Oscar H Del Brutto
- School of Medicine and Research Center, Universidad de Especialidades Espiritu Santo, Ecuador
| | - Hugh S Markus
- Stroke Research Group, Department of Clinical Neuroscience, University of Cambridge, Cambridge, UK
| | - Yi-Cheng Zhu
- Department of Neurology, Peking Union Medical College Hospital, Beijing, China
| | - Eric E Smith
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada; Department of Community Health Sciences, University of Calgary, Calgary, AB, Canada; Department of Radiology, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Martin Dichgans
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany; German Center for Neurodegenerative Diseases (DZNE), Munich, Germany; German Centre for Cardiovascular Research (DZHK), Munich, Germany
| | - Joanna M Wardlaw
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK; UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK.
| |
Collapse
|
56
|
Aribisala BS, Valdés Hernández MDC, Okely JA, Cox SR, Ballerini L, Dickie DA, Wiseman SJ, Riha RL, Muñoz Maniega S, Radakovic R, Taylor A, Pattie A, Corley J, Redmond P, Bastin ME, Deary I, Wardlaw JM. Sleep quality, perivascular spaces and brain health markers in ageing - A longitudinal study in the Lothian Birth Cohort 1936. Sleep Med 2023; 106:123-131. [PMID: 37005116 DOI: 10.1016/j.sleep.2023.03.016] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 03/07/2023] [Accepted: 03/11/2023] [Indexed: 03/18/2023]
Abstract
BACKGROUND Sleep is thought to play a major role in brain health and general wellbeing. However, few longitudinal studies have explored the relationship between sleep habits and imaging markers of brain health, particularly markers of brain waste clearance such as perivascular spaces (PVS), of neurodegeneration such as brain atrophy, and of vascular disease, such as white matter hyperintensities (WMH). We explore these associations using data collected over 6 years from a birth cohort of older community-dwelling adults in their 70s. METHOD We analysed brain MRI data from ages 73, 76 and 79 years, and self-reported sleep duration, sleep quality and vascular risk factors from community-dwelling participants in the Lothian Birth Cohort 1936 (LBC1936) study. We calculated sleep efficiency (at age 76), quantified PVS burden (at age 73), and WMH and brain volumes (age 73 to 79), calculated the white matter damage metric, and used structural equation modelling (SEM) to explore associations and potential causative pathways between indicators related to brain waste cleaning (i.e., sleep and PVS burden), brain and WMH volume changes during the 8th decade of life. RESULTS Lower sleep efficiency was associated with a reduction in normal-appearing white matter (NAWM) volume (β = 0.204, P = 0.009) from ages 73 to 79, but not concurrent volume (i.e. age 76). Increased daytime sleep correlated with less night-time sleep (r = -0.20, P < 0.001), and with increasing white matter damage metric (β = -0.122, P = 0.018) and faster WMH growth (β = 0.116, P = 0.026). Shorter night-time sleep duration was associated with steeper 6-year reduction of NAWM volumes (β = 0.160, P = 0.011). High burden of PVS at age 73 (volume, count, and visual scores), was associated with faster deterioration in white matter: reduction of NAWM volume (β = -0.16, P = 0.012) and increasing white matter damage metric (β = 0.37, P < 0.001) between ages 73 and 79. On SEM, centrum semiovale PVS burden mediated 5% of the associations between sleep parameters and brain changes. CONCLUSION Sleep impairments, and higher PVS burden, a marker of impaired waste clearance, were associated with faster loss of healthy white matter and increasing WMH in the 8th decade of life. A small percentage of the effect of sleep in white matter health was mediated by the burden of PVS consistent with the proposed role for sleep in brain waste clearance.
Collapse
Affiliation(s)
- Benjamin S Aribisala
- Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK; Lothian Birth Cohort Studies, Department of Psychology, University of Edinburgh, Edinburgh, UK; Department of Computer Science, Lagos State University, Lagos, Nigeria
| | - Maria Del C Valdés Hernández
- Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK; Lothian Birth Cohort Studies, Department of Psychology, University of Edinburgh, Edinburgh, UK; UK Dementia Research Institute Centre at the University of Edinburgh, UK
| | - Judith A Okely
- Lothian Birth Cohort Studies, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Simon R Cox
- Lothian Birth Cohort Studies, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Lucia Ballerini
- Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK; Lothian Birth Cohort Studies, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | | | - Stewart J Wiseman
- Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK; UK Dementia Research Institute Centre at the University of Edinburgh, UK
| | - Renata L Riha
- Lothian Birth Cohort Studies, Department of Psychology, University of Edinburgh, Edinburgh, UK; Department of Sleep Medicine, Royal Infirmary of Edinburgh, NHS Lothian, UK
| | - Susana Muñoz Maniega
- Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK; Lothian Birth Cohort Studies, Department of Psychology, University of Edinburgh, Edinburgh, UK; UK Dementia Research Institute Centre at the University of Edinburgh, UK
| | - Ratko Radakovic
- Lothian Birth Cohort Studies, Department of Psychology, University of Edinburgh, Edinburgh, UK; Faculty of Health and Medical Sciences, University of East Anglia, Norwich, UK; Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, UK; Euan MacDonald Centre for MND Research, University of Edinburgh, Edinburgh, UK
| | - Adele Taylor
- Lothian Birth Cohort Studies, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Alison Pattie
- Lothian Birth Cohort Studies, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Janie Corley
- Lothian Birth Cohort Studies, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Paul Redmond
- Lothian Birth Cohort Studies, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Mark E Bastin
- Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK; Lothian Birth Cohort Studies, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Ian Deary
- Lothian Birth Cohort Studies, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Joanna M Wardlaw
- Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK; Lothian Birth Cohort Studies, Department of Psychology, University of Edinburgh, Edinburgh, UK; UK Dementia Research Institute Centre at the University of Edinburgh, UK.
| |
Collapse
|
57
|
Ineichen BV, Cananau C, Plattén M, Ouellette R, Moridi T, Frauenknecht KBM, Okar SV, Kulcsar Z, Kockum I, Piehl F, Reich DS, Granberg T. Dilated Virchow-Robin spaces are a marker for arterial disease in multiple sclerosis. EBioMedicine 2023; 92:104631. [PMID: 37253317 DOI: 10.1016/j.ebiom.2023.104631] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Revised: 04/28/2023] [Accepted: 05/11/2023] [Indexed: 06/01/2023] Open
Abstract
BACKGROUND Virchow-Robin spaces (VRS) have been associated with neurodegeneration and neuroinflammation. However, it remains uncertain to what degree non-dilated or dilated VRS reflect specific features of neuroinflammatory pathology. Thus, we aimed at investigating the clinical relevance of VRS as imaging biomarker in multiple sclerosis (MS) and to correlate VRS to their histopathologic signature. METHODS In a cohort study comprising 142 MS patients and 30 control subjects, we assessed the association of non-dilated and dilated VRS to clinical and magnetic resonance imaging (MRI) outcomes. Findings were corroborated in a validation cohort comprising 63 MS patients. Brain blocks from 6 MS patients and 3 non-MS controls were histopathologically processed to correlate VRS to their tissue substrate. FINDINGS In our actively treated clinical cohort, the count of dilated centrum semiovale VRS was associated with increased T1 and T2 lesion volumes. There was no systematic spatial colocalization of dilated VRS with MS lesions. At tissue level, VRS mostly corresponded to arteries and were not associated with MS pathological hallmarks. Interestingly, in our ex vivo cohort comprising mostly progressive MS patients, dilated VRS in MS were associated with signs of small vessel disease. INTERPRETATION Contrary to prior beliefs, these observations suggest that VRS in MS do not associate with an accumulation of immune cells. But instead, these findings indicate vascular pathology as a driver and/or consequence of neuroinflammatory pathology for this imaging feature. FUNDING NIH, Swedish Society for Medical Research, Swiss National Science Foundation and University of Zurich.
Collapse
Affiliation(s)
- Benjamin V Ineichen
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden; Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden; Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland; Center for Reproducible Science, University of Zurich, Zurich, Switzerland; Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden; Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institute of Health (NIH), Bethesda, MA, USA.
| | - Carmen Cananau
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden; Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - Michael Plattén
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden; Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - Russell Ouellette
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden; Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - Thomas Moridi
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden; Center of Neurology, Academic Specialist Center, Stockholm Health Services, Stockholm, Sweden
| | - Katrin B M Frauenknecht
- National Centre for Pathology (NCP), Laboratoire National de Santé, Dudelange, Luxembourg; Luxembourg Centre for Neuropathology (LCNP), Laboratoire National de Santé, Dudelange, Luxembourg
| | - Serhat V Okar
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institute of Health (NIH), Bethesda, MA, USA
| | - Zsolt Kulcsar
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Ingrid Kockum
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden; Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Fredrik Piehl
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden; Center of Neurology, Academic Specialist Center, Stockholm Health Services, Stockholm, Sweden
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institute of Health (NIH), Bethesda, MA, USA
| | - Tobias Granberg
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden; Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| |
Collapse
|
58
|
Shulyatnikova T, Hayden MR. Why Are Perivascular Spaces Important? MEDICINA (KAUNAS, LITHUANIA) 2023; 59:medicina59050917. [PMID: 37241149 DOI: 10.3390/medicina59050917] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Revised: 05/05/2023] [Accepted: 05/09/2023] [Indexed: 05/28/2023]
Abstract
Perivascular spaces (PVS) and their enlargement (EPVS) have been gaining interest as EPVS can be visualized non-invasively by magnetic resonance imaging (MRI) when viewing T-2-weighted images. EPVS are most commonly observed in the regions of the basal ganglia and the centrum semiovale; however, they have also been identified in the frontal cortex and hippocampal regions. EPVS are known to be increased in aging and hypertension, and are considered to be a biomarker of cerebral small vessel disease (SVD). Interest in EPVS has been significantly increased because these PVS are now considered to be an essential conduit necessary for the glymphatic pathway to provide the necessary efflux of metabolic waste. Metabolic waste includes misfolded proteins of amyloid beta and tau that are known to accumulate in late-onset Alzheimer's disease (LOAD) within the interstitial fluid that is delivered to the subarachnoid space and eventually the cerebral spinal fluid (CSF). The CSF acts as a sink for accumulating neurotoxicities and allows clinical screening to potentially detect if LOAD may be developing early on in its clinical progression via spinal fluid examination. EPVS are thought to occur by obstruction of the PVS that associates with excessive neuroinflammation, oxidative stress, and vascular stiffening that impairs flow due to a dampening of the arterial and arteriolar pulsatility that aids in the convective flow of the metabolic debris within the glymphatic effluxing system. Additionally, increased EPVS has also been associated with Parkinson's disease and non-age-related multiple sclerosis (MS).
Collapse
Affiliation(s)
- Tatyana Shulyatnikova
- Department of Pathological Anatomy and Forensic Medicine, Zaporizhzhia State Medical University, Mayakovsky Avenue, 26, 69035 Zaporizhzhia, Ukraine
| | - Melvin R Hayden
- Department of Internal Medicine, Endocrinology Diabetes and Metabolism, Diabetes and Cardiovascular Disease Center, University of Missouri School of Medicine, One Hospital Drive, Columbia, MO 65211, USA
| |
Collapse
|
59
|
Charisis S, Rashid T, Liu H, Ware JB, Jensen PN, Austin TR, Li K, Fadaee E, Hilal S, Chen C, Hughes TM, Romero JR, Toledo JB, Longstreth WT, Hohman TJ, Nasrallah I, Bryan RN, Launer LJ, Davatzikos C, Seshadri S, Heckbert SR, Habes M. Assessment of Risk Factors and Clinical Importance of Enlarged Perivascular Spaces by Whole-Brain Investigation in the Multi-Ethnic Study of Atherosclerosis. JAMA Netw Open 2023; 6:e239196. [PMID: 37093602 PMCID: PMC10126873 DOI: 10.1001/jamanetworkopen.2023.9196] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/20/2022] [Accepted: 03/07/2023] [Indexed: 04/25/2023] Open
Abstract
Importance Enlarged perivascular spaces (ePVSs) have been associated with cerebral small-vessel disease (cSVD). Although their etiology may differ based on brain location, study of ePVSs has been limited to specific brain regions; therefore, their risk factors and significance remain uncertain. Objective Toperform a whole-brain investigation of ePVSs in a large community-based cohort. Design, Setting, and Participants This cross-sectional study analyzed data from the Atrial Fibrillation substudy of the population-based Multi-Ethnic Study of Atherosclerosis. Demographic, vascular risk, and cardiovascular disease data were collected from September 2016 to May 2018. Brain magnetic resonance imaging was performed from March 2018 to July 2019. The reported analysis was conducted between August and October 2022. A total of 1026 participants with available brain magnetic resonance imaging data and complete information on demographic characteristics and vascular risk factors were included. Main Outcomes and Measures Enlarged perivascular spaces were quantified using a fully automated deep learning algorithm. Quantified ePVS volumes were grouped into 6 anatomic locations: basal ganglia, thalamus, brainstem, frontoparietal, insular, and temporal regions, and were normalized for the respective regional volumes. The association of normalized regional ePVS volumes with demographic characteristics, vascular risk factors, neuroimaging indices, and prevalent cardiovascular disease was explored using generalized linear models. Results In the 1026 participants, mean (SD) age was 72 (8) years; 541 (53%) of the participants were women. Basal ganglia ePVS volume was positively associated with age (β = 3.59 × 10-3; 95% CI, 2.80 × 10-3 to 4.39 × 10-3), systolic blood pressure (β = 8.35 × 10-4; 95% CI, 5.19 × 10-4 to 1.15 × 10-3), use of antihypertensives (β = 3.29 × 10-2; 95% CI, 1.92 × 10-2 to 4.67 × 10-2), and negatively associated with Black race (β = -3.34 × 10-2; 95% CI, -5.08 × 10-2 to -1.59 × 10-2). Thalamic ePVS volume was positively associated with age (β = 5.57 × 10-4; 95% CI, 2.19 × 10-4 to 8.95 × 10-4) and use of antihypertensives (β = 1.19 × 10-2; 95% CI, 6.02 × 10-3 to 1.77 × 10-2). Insular region ePVS volume was positively associated with age (β = 1.18 × 10-3; 95% CI, 7.98 × 10-4 to 1.55 × 10-3). Brainstem ePVS volume was smaller in Black than in White participants (β = -5.34 × 10-3; 95% CI, -8.26 × 10-3 to -2.41 × 10-3). Frontoparietal ePVS volume was positively associated with systolic blood pressure (β = 1.14 × 10-4; 95% CI, 3.38 × 10-5 to 1.95 × 10-4) and negatively associated with age (β = -3.38 × 10-4; 95% CI, -5.40 × 10-4 to -1.36 × 10-4). Temporal region ePVS volume was negatively associated with age (β = -1.61 × 10-2; 95% CI, -2.14 × 10-2 to -1.09 × 10-2), as well as Chinese American (β = -2.35 × 10-1; 95% CI, -3.83 × 10-1 to -8.74 × 10-2) and Hispanic ethnicities (β = -1.73 × 10-1; 95% CI, -2.96 × 10-1 to -4.99 × 10-2). Conclusions and Relevance In this cross-sectional study of ePVSs in the whole brain, increased ePVS burden in the basal ganglia and thalamus was a surrogate marker for underlying cSVD, highlighting the clinical importance of ePVSs in these locations.
Collapse
Affiliation(s)
- Sokratis Charisis
- Neuroimage Analytics Laboratory and the Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio
- Department of Neurology, University of Texas Health Science Center at San Antonio
| | - Tanweer Rashid
- Neuroimage Analytics Laboratory and the Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio
| | - Hangfan Liu
- Neuroimage Analytics Laboratory and the Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio
- AI2D Center for AI and Data Science for Integrated Diagnostics, and Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia
| | - Jeffrey B. Ware
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Paul N. Jensen
- Department of Medicine, University of Washington, Seattle
| | | | - Karl Li
- Neuroimage Analytics Laboratory and the Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio
| | - Elyas Fadaee
- Neuroimage Analytics Laboratory and the Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio
| | - Saima Hilal
- Department of Pharmacology, National University of Singapore, Singapore
| | - Christopher Chen
- Memory Aging and Cognition Centre, National University Health System, Singapore
| | - Timothy M. Hughes
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Jose Rafael Romero
- Department of Neurology, School of Medicine, Boston University, Boston, Massachusetts
| | - Jon B. Toledo
- Nantz National Alzheimer Center, Stanley Appel Department of Neurology, Houston Methodist Hospital, Houston, Texas
| | - Will T. Longstreth
- Department of Epidemiology, University of Washington, Seattle
- Department of Neurology, University of Washington, Seattle
| | - Timothy J. Hohman
- Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Ilya Nasrallah
- AI2D Center for AI and Data Science for Integrated Diagnostics, and Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - R. Nick Bryan
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Lenore J. Launer
- Intramural Research Program, Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Bethesda, Maryland
| | - Christos Davatzikos
- AI2D Center for AI and Data Science for Integrated Diagnostics, and Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Sudha Seshadri
- Neuroimage Analytics Laboratory and the Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio
- Department of Neurology, University of Texas Health Science Center at San Antonio
| | | | - Mohamad Habes
- Neuroimage Analytics Laboratory and the Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio
- AI2D Center for AI and Data Science for Integrated Diagnostics, and Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia
| |
Collapse
|
60
|
Okar SV, Hu F, Shinohara RT, Beck ES, Reich DS, Ineichen BV. The etiology and evolution of magnetic resonance imaging-visible perivascular spaces: Systematic review and meta-analysis. Front Neurosci 2023; 17:1038011. [PMID: 37065926 PMCID: PMC10098201 DOI: 10.3389/fnins.2023.1038011] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 03/15/2023] [Indexed: 04/03/2023] Open
Abstract
ObjectivesPerivascular spaces have been involved in neuroinflammatory and neurodegenerative diseases. Upon a certain size, these spaces can become visible on magnetic resonance imaging (MRI), referred to as enlarged perivascular spaces (EPVS) or MRI-visible perivascular spaces (MVPVS). However, the lack of systematic evidence on etiology and temporal dynamics of MVPVS hampers their diagnostic utility as MRI biomarker. Thus, the goal of this systematic review was to summarize potential etiologies and evolution of MVPVS.MethodsIn a comprehensive literature search, out of 1,488 unique publications, 140 records assessing etiopathogenesis and dynamics of MVPVS were eligible for a qualitative summary. 6 records were included in a meta-analysis to assess the association between MVPVS and brain atrophy.ResultsFour overarching and partly overlapping etiologies of MVPVS have been proposed: (1) Impairment of interstitial fluid circulation, (2) Spiral elongation of arteries, (3) Brain atrophy and/or perivascular myelin loss, and (4) Immune cell accumulation in the perivascular space. The meta-analysis in patients with neuroinflammatory diseases did not support an association between MVPVS and brain volume measures [R: −0.15 (95%-CI −0.40–0.11)]. Based on few and mostly small studies in tumefactive MVPVS and in vascular and neuroinflammatory diseases, temporal evolution of MVPVS is slow.ConclusionCollectively, this study provides high-grade evidence for MVPVS etiopathogenesis and temporal dynamics. Although several potential etiologies for MVPVS emergence have been proposed, they are only partially supported by data. Advanced MRI methods should be employed to further dissect etiopathogenesis and evolution of MVPVS. This can benefit their implementation as an imaging biomarker.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?RecordID=346564, identifier CRD42022346564.
Collapse
Affiliation(s)
- Serhat V. Okar
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Fengling Hu
- Department of Biostatistics, Epidemiology, and Informatics, Penn Statistics in Imaging and Visualization Center, University of Pennsylvania, Philadelphia, PA, United States
| | - Russell T. Shinohara
- Department of Biostatistics, Epidemiology, and Informatics, Penn Statistics in Imaging and Visualization Center, University of Pennsylvania, Philadelphia, PA, United States
| | - Erin S. Beck
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Daniel S. Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Benjamin V. Ineichen
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Center for Reproducible Science, University of Zurich, Zurich, Switzerland
- *Correspondence: Benjamin V. Ineichen, , ; orcid.org/0000-0003-1362-4819
| |
Collapse
|
61
|
Jones HE, Coelho-Santos V, Bonney SK, Abrams KA, Shih AY, Siegenthaler JA. Meningeal origins and dynamics of perivascular fibroblast development on the mouse cerebral vasculature. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.23.533982. [PMID: 36993587 PMCID: PMC10055392 DOI: 10.1101/2023.03.23.533982] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Perivascular fibroblasts (PVFs) are a fibroblast-like cell type that reside on large-diameter blood vessels in the adult meninges and central nervous system (CNS). PVFs drive fibrosis following injury but their homeostatic functions are not well detailed. In mice, PVFs were previously shown to be absent from most brain regions at birth and are only detected postnatally within the cerebral cortex. However, the origin, timing, and cellular mechanisms of PVF development are not known. We used Col1a1-GFP and Col1a2-CreERT transgenic mice to track PVF developmental timing and progression in postnatal mice. Using a combination of lineage tracing and in vivo imaging we show that brain PVFs originate from the meninges and are first seen on parenchymal cerebrovasculature at postnatal day (P)5. After P5, PVF coverage of the cerebrovasculature rapidly expands via mechanisms of local cell proliferation and migration from the meninges, reaching adult levels at P14. Finally, we show that PVFs and perivascular macrophages (PVMs) develop concurrently along postnatal cerebral blood vessels, where the location and depth of PVMs and PVFs highly correlate. These findings provide the first complete timeline for PVF development in the brain, enabling future work into how PVF development is coordinated with cell types and structures in and around the perivascular spaces to support normal CNS vascular function. Summary Brain perivascular fibroblasts migrate from their origin in the meninges and proliferate locally to fully cover penetrating vessels during postnatal mouse development.
Collapse
|
62
|
Lynch KM, Sepehrband F, Toga AW, Choupan J. Brain perivascular space imaging across the human lifespan. Neuroimage 2023; 271:120009. [PMID: 36907282 PMCID: PMC10185227 DOI: 10.1016/j.neuroimage.2023.120009] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 03/02/2023] [Accepted: 03/08/2023] [Indexed: 03/12/2023] Open
Abstract
Enlarged perivascular spaces (PVS) are considered a biomarker for vascular pathology and are observed in normal aging and neurological conditions; however, research on the role of PVS in health and disease are hindered by the lack of knowledge regarding the normative time course of PVS alterations with age. To this end, we characterized the influence of age, sex and cognitive performance on PVS anatomical characteristics in a large cross-sectional cohort (∼1400) of healthy subjects between 8 and 90 years of age using multimodal structural MRI data. Our results show age is associated with wider and more numerous MRI-visible PVS over the course of the lifetime with spatially-varying patterns of PVS enlargement trajectories. In particular, regions with low PVS volume fraction in childhood are associated with rapid age-related PVS enlargement (e.g., temporal regions), while regions with high PVS volume fraction in childhood are associated with minimal age-related PVS alterations (e.g., limbic regions). PVS burden was significantly elevated in males compared to females with differing morphological time courses with age. Together, these findings contribute to our understanding of perivascular physiology across the healthy lifespan and provide a normative reference for the spatial distribution of PVS enlargement patterns to which pathological alterations can be compared.
Collapse
Affiliation(s)
- Kirsten M Lynch
- Laboratory of Neuro Imaging (LONI), USC Mark and Mary Stevens Institute for Neuroimaging and Informatics, USC Keck School of Medicine, Los Angeles, CA, 90033, USA.
| | - Farshid Sepehrband
- Laboratory of Neuro Imaging (LONI), USC Mark and Mary Stevens Institute for Neuroimaging and Informatics, USC Keck School of Medicine, Los Angeles, CA, 90033, USA; NeuroScope Inc., New York, USA
| | - Arthur W Toga
- Laboratory of Neuro Imaging (LONI), USC Mark and Mary Stevens Institute for Neuroimaging and Informatics, USC Keck School of Medicine, Los Angeles, CA, 90033, USA
| | - Jeiran Choupan
- Laboratory of Neuro Imaging (LONI), USC Mark and Mary Stevens Institute for Neuroimaging and Informatics, USC Keck School of Medicine, Los Angeles, CA, 90033, USA; NeuroScope Inc., New York, USA
| |
Collapse
|
63
|
Kim HG, Shin NY, Nam Y, Yun E, Yoon U, Lee HS, Ahn KJ. MRI-visible Dilated Perivascular Space in the Brain by Age: The Human Connectome Project. Radiology 2023; 306:e213254. [PMID: 36378031 DOI: 10.1148/radiol.213254] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background Dilated perivascular spaces (dPVS) are associated with aging and various disorders; however, the effect of age on dPVS burden in young populations and normative data have not been fully evaluated. Purpose To investigate the dPVS burden and provide normative data according to age in a healthy population, including children. Materials and Methods In this retrospective study, three-dimensional T2-weighted brain MRI scans from the Human Connectome Project data sets were used for visual grading (grade 0, 1, 2, 3, 4 for 0, 1-10, 11-20, 21-40, and >40 dPVS on a single section of either hemispheric region) and automated volumetry of dPVS in basal ganglia (BGdPVS) and white matter (WMdPVS). Linear and nonlinear regression were performed to assess the association of dPVS volume with age. Optimal cutoff ages were determined with use of the maximized continuous-scale C-index. Participants were grouped by cutoff values. Linear regression was performed to assess the age-dPVS volume relationship in each age group. Normative data of dPVS visual grades were provided per age decade. Results A total of 1789 participants (mean age, 35 years; age range, 8-100 years; 1006 female participants) were evaluated. Age was related to dPVS volume in all regression models (R2 range, 0.41-0.55; P < .001). Age-dPVS volume relationships were altered at the mid-30s and age 55 years; BGdPVS and WMdPVS volumes negatively correlated with age until the mid-30s (β, -1.2 and -7.8), then positively until age 55 years (β, 3.3 and 54.1) and beyond (β, 3.9 and 42.8; P < .001). The 90th percentile for dPVS grades was grade 1 for age 49 years and younger, grade 2 for age 50-69 years, and grade 3 for age 70 years and older (overall, grade 2) for BGdPVS, and grade 3 for age 49 years and younger and grade 4 for age 50 years and older (overall, grade 3) for WMdPVS. Conclusion Dilated perivascular spaces (dPVS) showed a biphasic volume pattern with brain MRI, lower volumes until the mid-30s, then higher afterward. Grades of 3 or higher and 4 might be considered pathologic dPVS in basal ganglia and white matter, respectively. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Bapuraj and Chaudhary in this issue.
Collapse
Affiliation(s)
- Hyun Gi Kim
- From the Department of Radiology, Eunpyeong St Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea (H.G.K.); Department of Radiology, Seoul St Mary's Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea (N.Y.S., K.J.A.); Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea (Y.N.); Department of Biomedical Engineering, College of Bio and Medical Sciences, Daegu Catholic University, Daegu, Republic of Korea (E.Y., U.Y.); and Biostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, Republic of Korea (H.S.L.)
| | - Na-Young Shin
- From the Department of Radiology, Eunpyeong St Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea (H.G.K.); Department of Radiology, Seoul St Mary's Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea (N.Y.S., K.J.A.); Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea (Y.N.); Department of Biomedical Engineering, College of Bio and Medical Sciences, Daegu Catholic University, Daegu, Republic of Korea (E.Y., U.Y.); and Biostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, Republic of Korea (H.S.L.)
| | - Yoonho Nam
- From the Department of Radiology, Eunpyeong St Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea (H.G.K.); Department of Radiology, Seoul St Mary's Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea (N.Y.S., K.J.A.); Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea (Y.N.); Department of Biomedical Engineering, College of Bio and Medical Sciences, Daegu Catholic University, Daegu, Republic of Korea (E.Y., U.Y.); and Biostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, Republic of Korea (H.S.L.)
| | - Eunkyeong Yun
- From the Department of Radiology, Eunpyeong St Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea (H.G.K.); Department of Radiology, Seoul St Mary's Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea (N.Y.S., K.J.A.); Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea (Y.N.); Department of Biomedical Engineering, College of Bio and Medical Sciences, Daegu Catholic University, Daegu, Republic of Korea (E.Y., U.Y.); and Biostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, Republic of Korea (H.S.L.)
| | - Uicheul Yoon
- From the Department of Radiology, Eunpyeong St Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea (H.G.K.); Department of Radiology, Seoul St Mary's Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea (N.Y.S., K.J.A.); Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea (Y.N.); Department of Biomedical Engineering, College of Bio and Medical Sciences, Daegu Catholic University, Daegu, Republic of Korea (E.Y., U.Y.); and Biostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, Republic of Korea (H.S.L.)
| | - Hye Sun Lee
- From the Department of Radiology, Eunpyeong St Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea (H.G.K.); Department of Radiology, Seoul St Mary's Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea (N.Y.S., K.J.A.); Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea (Y.N.); Department of Biomedical Engineering, College of Bio and Medical Sciences, Daegu Catholic University, Daegu, Republic of Korea (E.Y., U.Y.); and Biostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, Republic of Korea (H.S.L.)
| | - Kook Jin Ahn
- From the Department of Radiology, Eunpyeong St Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea (H.G.K.); Department of Radiology, Seoul St Mary's Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea (N.Y.S., K.J.A.); Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea (Y.N.); Department of Biomedical Engineering, College of Bio and Medical Sciences, Daegu Catholic University, Daegu, Republic of Korea (E.Y., U.Y.); and Biostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, Republic of Korea (H.S.L.)
| |
Collapse
|
64
|
Ineichen BV, Cananau C, Platt N M, Ouellette R, Moridi T, Frauenknecht KBM, Okar SV, Kulcsar Z, Kockum I, Piehl F, Reich DS, Granberg T. Dilated Virchow-Robin Spaces are a Marker for Arterial Disease in Multiple Sclerosis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.24.529871. [PMID: 36945422 PMCID: PMC10028816 DOI: 10.1101/2023.02.24.529871] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/02/2023]
Abstract
Virchow-Robin spaces (VRS) have been associated with neurodegeneration and neuroinflammation. However, it remains uncertain to what degree non-dilated or dilated VRS reflect specific features of neuroinflammatory pathology. Thus, we aimed at investigating the clinical relevance of VRS as imaging biomarker in multiple sclerosis (MS) and to correlate VRS to their histopathologic signature. In a cohort study comprising 205 MS patients (including a validation cohort) and 30 control subjects, we assessed the association of non-dilated and dilated VRS to clinical and magnetic resonance imaging (MRI) out-comes. Brain blocks from 6 MS patients and 3 non-MS controls were histopathologically processed to correlate VRS to their tissue substrate. The count of dilated centrum semiovale VRS was associated with increased T1 and T2 lesion volumes. There was no systematic spatial colocalization of dilated VRS with MS lesions. At tissue level, VRS mostly corresponded to arteries and were not associated with MS pathological hallmarks. Interestingly, dilated VRS in MS were associated with signs of small vessel disease. Contrary to prior beliefs, these observations suggest that VRS in MS do not associate with accumulation of immune cells. But instead, these findings indicate vascular pathology as a driver and/or consequence of neuroinflammatory pathology for this imaging feature.
Collapse
|
65
|
Markus HS. Perivascular Spaces: An Exciting Research Frontier in Cerebral Small Vessel Disease. Neurology 2023; 100:53-54. [PMID: 36253104 DOI: 10.1212/wnl.0000000000201447] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Accepted: 09/07/2022] [Indexed: 02/05/2023] Open
Affiliation(s)
- Hugh S Markus
- From the Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom.
| |
Collapse
|
66
|
Evans TE, Knol MJ, Schwingenschuh P, Wittfeld K, Hilal S, Ikram MA, Dubost F, van Wijnen KMH, Katschnig P, Yilmaz P, de Bruijne M, Habes M, Chen C, Langer S, Völzke H, Ikram MK, Grabe HJ, Schmidt R, Adams HHH, Vernooij MW. Determinants of Perivascular Spaces in the General Population: A Pooled Cohort Analysis of Individual Participant Data. Neurology 2023; 100:e107-e122. [PMID: 36253103 PMCID: PMC9841448 DOI: 10.1212/wnl.0000000000201349] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Accepted: 08/19/2022] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Perivascular spaces (PVS) are emerging markers of cerebral small vessel disease (CSVD), but research on their determinants has been hampered by conflicting results from small single studies using heterogeneous rating methods. In this study, we therefore aimed to identify determinants of PVS burden in a pooled analysis of multiple cohort studies using 1 harmonized PVS rating method. METHODS Individuals from 10 population-based cohort studies with adult participants from the Uniform Neuro-Imaging of Virchow-Robin Spaces Enlargement consortium and the UK Biobank were included. On MRI scans, we counted PVS in 4 brain regions (mesencephalon, hippocampus, basal ganglia, and centrum semiovale) according to a uniform and validated rating protocol, both manually and automated using a deep learning algorithm. As potential determinants, we considered demographics, cardiovascular risk factors, APOE genotypes, and other imaging markers of CSVD. Negative binomial regression models were used to examine the association between these determinants and PVS counts. RESULTS In total, 39,976 individuals were included (age range 20-96 years). The average count of PVS in the 4 regions increased from the age 20 years (0-1 PVS) to 90 years (2-7 PVS). Men had more mesencephalic PVS (OR [95% CI] = 1.13 [1.08-1.18] compared with women), but less hippocampal PVS (0.82 [0.81-0.83]). Higher blood pressure, particularly diastolic pressure, was associated with more PVS in all regions (ORs between 1.04-1.05). Hippocampal PVS showed higher counts with higher high-density lipoprotein cholesterol levels (1.02 [1.01-1.02]), glucose levels (1.02 [1.01-1.03]), and APOE ε4-alleles (1.02 [1.01-1.04]). Furthermore, white matter hyperintensity volume and presence of lacunes were associated with PVS in multiple regions, but most strongly with the basal ganglia (1.13 [1.12-1.14] and 1.10 [1.09-1.12], respectively). DISCUSSION Various factors are associated with the burden of PVS, in part regionally specific, which points toward a multifactorial origin beyond what can be expected from PVS-related risk factor profiles. This study highlights the power of collaborative efforts in population neuroimaging research.
Collapse
Affiliation(s)
- Tavia E Evans
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Maria J Knol
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Petra Schwingenschuh
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Katharina Wittfeld
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Saima Hilal
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - M Arfan Ikram
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Florian Dubost
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Kimberlin M H van Wijnen
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Petra Katschnig
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Pinar Yilmaz
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Marleen de Bruijne
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Mohamad Habes
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Christopher Chen
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Sönke Langer
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Henry Völzke
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - M Kamran Ikram
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Hans J Grabe
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Reinhold Schmidt
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Hieab H H Adams
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile.
| | - Meike W Vernooij
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| |
Collapse
|
67
|
Pase MP, Pinheiro A, Rowsthorn E, Demissie S, Hurmez S, Aparicio HJ, Rodriguez-Lara F, Gonzales MM, Beiser A, DeCarli C, Seshadri S, Romero JR. MRI Visible Perivascular Spaces and the Risk of Incident Mild Cognitive Impairment in a Community Sample. J Alzheimers Dis 2023; 96:103-112. [PMID: 37742645 PMCID: PMC10846532 DOI: 10.3233/jad-230445] [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: 09/26/2023]
Abstract
BACKGROUND Magnetic resonance imaging (MRI) visible perivascular spaces (PVS) are associated with the risk of incident dementia but their association with the early stages of cognitive impairment remains equivocal. OBJECTIVE We examined the association between MRI visible PVS and the risk of incident mild cognitive impairment (MCI) in the community-based Framingham Heart Study (FHS). METHODS FHS participants aged at least 50 years free of stroke, cognitive impairment, and dementia at the time of MRI were included. PVS were rated according to severity in the basal ganglia and centrum semiovale (CSO) using established criteria. Cox regression analyses were used to relate PVS to incident MCI adjusted for demographic and cardiovascular variables. RESULTS The mean age of the sample (1,314 participants) at MRI was 68 years (SD, 9; 54% women). There were 263 cases of incident MCI over a median 7.4 years follow-up (max, 19.8 years). MCI risk increased with higher PVS severity in the CSO. Relative to persons with the lowest severity rating, persons with the highest severity rating in the CSO had a higher risk of incident MCI (hazard ratio [HR] = 2.55; 95% confidence interval [CI], 1.48-4.37; p = 0.0007). In secondary analysis, this association seemed stronger in women. Risk of incident MCI was nominally higher for participants with the highest severity grade of PVS in the basal ganglia, though not statistically significant relative to the lowest grade (HR = 2.19; 95% CI, 0.78-6.14; p = 0.14). CONCLUSIONS PVS burden in the CSO may be a risk marker for early cognitive impairment.
Collapse
Affiliation(s)
- Matthew P. Pase
- Turner Institute for Brain and Mental Health, Monash University, Clayton, Australia
- Harvard T.H. Chan School of Public Health, Boston, MA, USA
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
| | - Adlin Pinheiro
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Ella Rowsthorn
- Turner Institute for Brain and Mental Health, Monash University, Clayton, Australia
| | - Serkalem Demissie
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Saoresho Hurmez
- Turner Institute for Brain and Mental Health, Monash University, Clayton, Australia
| | - Hugo J. Aparicio
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | | | - Mitzi M. Gonzales
- The Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
| | - Alexa Beiser
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Charles DeCarli
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, University of California at Davis, Davis, CA, USA
| | - Sudha Seshadri
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- The Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
| | - Jose Rafael Romero
- NHLBI’s Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| |
Collapse
|
68
|
Li K, Rashid T, Li J, Honnorat N, Nirmala AB, Fadaee E, Wang D, Charisis S, Liu H, Franklin C, Maybrier M, Katragadda H, Abazid L, Ganapathy V, Valaparla VL, Badugu P, Vasquez E, Solano L, Clarke G, Maestre G, Richardson T, Walker J, Fox PT, Bieniek K, Seshadri S, Habes M. Postmortem Brain Imaging in Alzheimer's Disease and Related Dementias: The South Texas Alzheimer's Disease Research Center Repository. J Alzheimers Dis 2023; 96:1267-1283. [PMID: 37955086 PMCID: PMC10693476 DOI: 10.3233/jad-230389] [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] [Accepted: 09/24/2023] [Indexed: 11/14/2023]
Abstract
BACKGROUND Neuroimaging bears the promise of providing new biomarkers that could refine the diagnosis of dementia. Still, obtaining the pathology data required to validate the relationship between neuroimaging markers and neurological changes is challenging. Existing data repositories are focused on a single pathology, are too small, or do not precisely match neuroimaging and pathology findings. OBJECTIVE The new data repository introduced in this work, the South Texas Alzheimer's Disease research center repository, was designed to address these limitations. Our repository covers a broad diversity of dementias, spans a wide age range, and was specifically designed to draw exact correspondences between neuroimaging and pathology data. METHODS Using four different MRI sequences, we are reaching a sample size that allows for validating multimodal neuroimaging biomarkers and studying comorbid conditions. Our imaging protocol was designed to capture markers of cerebrovascular disease and related lesions. Quantification of these lesions is currently underway with MRI-guided histopathological examination. RESULTS A total of 139 postmortem brains (70 females) with mean age of 77.9 years were collected, with 71 brains fully analyzed. Of these, only 3% showed evidence of AD-only pathology and 76% had high prevalence of multiple pathologies contributing to clinical diagnosis. CONCLUSION This repository has a significant (and increasing) sample size consisting of a wide range of neurodegenerative disorders and employs advanced imaging protocols and MRI-guided histopathological analysis to help disentangle the effects of comorbid disorders to refine diagnosis, prognosis and better understand neurodegenerative disorders.
Collapse
Affiliation(s)
- Karl Li
- Glenn Biggs Institute for Neurodegenerative Disorders, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Tanweer Rashid
- Glenn Biggs Institute for Neurodegenerative Disorders, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Jinqi Li
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Nicolas Honnorat
- Glenn Biggs Institute for Neurodegenerative Disorders, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Anoop Benet Nirmala
- Glenn Biggs Institute for Neurodegenerative Disorders, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Elyas Fadaee
- Glenn Biggs Institute for Neurodegenerative Disorders, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Di Wang
- Glenn Biggs Institute for Neurodegenerative Disorders, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Sokratis Charisis
- Glenn Biggs Institute for Neurodegenerative Disorders, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Hangfan Liu
- Glenn Biggs Institute for Neurodegenerative Disorders, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Crystal Franklin
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Mallory Maybrier
- Glenn Biggs Institute for Neurodegenerative Disorders, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Haritha Katragadda
- Glenn Biggs Institute for Neurodegenerative Disorders, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Leen Abazid
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Vinutha Ganapathy
- Department of Neurology, University of Texas Health Science Center, San Antonio, TX, USA
| | | | - Pradeepthi Badugu
- Glenn Biggs Institute for Neurodegenerative Disorders, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Eliana Vasquez
- Glenn Biggs Institute for Neurodegenerative Disorders, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Leigh Solano
- Glenn Biggs Institute for Neurodegenerative Disorders, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Geoffrey Clarke
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Gladys Maestre
- Department of Neuroscience, School of Medicine, University of Texas Rio Grande Valley, Harlingen, TX, USA
- Department of Human Genetics, School of Medicine, University of Texas Rio Grande Valley, Brownsville, TX, USA
| | - Tim Richardson
- Glenn Biggs Institute for Neurodegenerative Disorders, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
- Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jamie Walker
- Glenn Biggs Institute for Neurodegenerative Disorders, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
- Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Peter T. Fox
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Kevin Bieniek
- Glenn Biggs Institute for Neurodegenerative Disorders, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
- Department of Pathology, University of Texas Health Science Center, San Antonio, TX, USA
| | - Sudha Seshadri
- Glenn Biggs Institute for Neurodegenerative Disorders, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Mohamad Habes
- Glenn Biggs Institute for Neurodegenerative Disorders, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| |
Collapse
|
69
|
Abstract
Cerebral small vessel disease (SVD) causes lacunar stroke and intracerebral hemorrhage, and is the most common pathology underlying vascular cognitive impairment. Increasingly, the importance of other clinical features of SVD is being recognized including motor impairment, (vascular) parkinsonism, impaired balance, falls, and behavioral symptoms, such as depression, apathy, and personality change. Epidemiological data show a high prevalence of the characteristic magnetic resonance imaging (MRI) features of white matter hyperintensities and lacunar infarcts in community studies, and recent data suggest that it is also a major health burden in low- and middle-income countries. In this review, we cover advances in diagnosis, imaging, clinical presentations, pathogenesis, and treatment.The two most common pathologies underlying SVD are arteriolosclerosis caused by aging, hypertension, and other conventional vascular risk factors, and cerebral amyloid angiopathy (CAA) caused by vascular deposition of β-amyloid. We discuss the revised Boston criteria of CAA based on MRI features, which have been recently validated. Imaging is providing important insights into pathogenesis, including improved detection of tissue damage using diffusion tensor imaging (DTI) leading to its use to monitor progression and surrogate endpoints in clinical trials. Advanced MRI techniques can demonstrate functional or dynamic abnormalities of the blood vessels, while the high spatial resolution provided by ultrahigh field MRI at 7 T allows imaging of individual perforating arteries for the first time, and the measurement of flow velocity and pulsatility within these arteries. DTI and structural network analysis have highlighted the importance of network disruption in mediating the effect of different SVD pathologies in causing a number of symptoms, including cognitive impairment, apathy, and gait disturbance.Despite the public health importance of SVD, there are few proven treatments. We review the evidence for primary prevention, and recent data showing how intensive blood pressure lowering reduces white matter hyperintensities (WMH) progression and delays the onset of cognitive impairment. There are few treatments for secondary prevention, but a number of trials are currently evaluating novel treatment approaches. Recent advances have implicated molecular processes related to endothelial dysfunction, nitric oxide synthesis, blood-brain barrier integrity, maintenance and repair of the extracellular matrix, and inflammation. Novel treatment approaches are being developed to a number of these targets. Finally, we highlight the importance of large International collaborative initiatives in SVD to address important research questions and cover a number which have recently been established.
Collapse
Affiliation(s)
- Hugh S Markus
- Stroke Research Group, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Frank Erik de Leeuw
- Department of Neurology, Radboud University Medical Center, Nijmegen, The Netherlands.,Center for Medical Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands
| |
Collapse
|
70
|
Diffusion along perivascular spaces as marker for impairment of glymphatic system in Parkinson's disease. NPJ Parkinsons Dis 2022; 8:174. [PMID: 36543809 PMCID: PMC9772196 DOI: 10.1038/s41531-022-00437-1] [Citation(s) in RCA: 51] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 11/22/2022] [Indexed: 12/24/2022] Open
Abstract
The brain glymphatic system is involved in the clearance of misfolding α-synuclein, the impaired glymphatic system may contribute to the progression of Parkinson's disease (PD). We aimed to analyze the diffusion tensor image along the perivascular space (DTI-ALPS) and perivascular space (PVS) burden to reveal the relationship between the glymphatic system and PD. A cross-sectional study using a 7 T MRI of 76 PD patients and 48 controls was performed to evaluate the brain's glymphatic system. The DTI-ALPS and PVS burden in basal ganglia were calculated. Correlation analyses were conducted between DTI-ALPS, PVS burden and clinical features. We detected lower DTI-ALPS in the PD subgroup relative to controls, and the differences were more pronounced in patients with Hoehn & Yahr stage greater than two. The decreased DTI-ALPS was only evident in the left hemisphere in patients in the early stage but involved both hemispheres in more advanced PD patients. Decreased DTI-ALPS were also correlated with longer disease duration, higher Unified Parkinson's Disease Rating Scale motor score (UPDRS III) and UPDRS total scores, as well as higher levodopa equivalent daily dose. Moreover, the decreased DTI-ALPS correlated with increased PVS burden, and both indexes correlated with PD disease severity. This study demonstrated decreased DTI-ALPS in PD, which might initiate from the left hemisphere and progressively involve right hemisphere with the disease progression. Decreased DTI-ALPS index correlated with increased PVS burden, indicating that both metrics could provide supporting evidence of an impaired glymphatic system. MRI evaluation of the PVS burden and diffusion along PVS are potential imaging biomarkers for PD for disease progression.
Collapse
|
71
|
Ramaswamy S, Khasiyev F, Gutierrez J. Brain Enlarged Perivascular Spaces as Imaging Biomarkers of Cerebrovascular Disease: A Clinical Narrative Review. J Am Heart Assoc 2022; 11:e026601. [PMID: 36533613 PMCID: PMC9798817 DOI: 10.1161/jaha.122.026601] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Perivascular spaces or Virchow-Robin spaces form pathways along the subarachnoid spaces that facilitate the effective clearance of brain metabolic by-products through intracellular exchange and drainage of cerebrospinal fluid. Best seen on magnetic resonance imaging of the brain, enlarged perivascular spaces (EPVSs) are increasingly recognized as potential imaging biomarkers of neurological conditions. EPVSs are an established subtype of cerebral small-vessel disease; however, their associations with other cerebrovascular disorders are yet to be fully understood. In particular, there has been great interest in the association between the various parameters of EPVSs, such as number, size, and topography, and vascular neurological conditions. Studies have identified cross-sectional and longitudinal relationships between EPVS parameters and vascular events, such as ischemic stroke (both clinical and silent), intracerebral hemorrhage, vascular risk factors, such as age and hypertension, and neurodegenerative processes, such as vascular dementia and Alzheimer disease. However, these studies are limited by heterogeneity of data and the lack of consistent results across studied populations. Existing meta-analyses also fail to provide uniformity of results. We performed a qualitative narrative review with an aim to provide an overview of the associations between EPVSs and cerebrovascular diseases, which may help recognize gaps in our knowledge, inform the design of future studies, and advance the role of EPVSs as imaging biomarkers.
Collapse
Affiliation(s)
- Srinath Ramaswamy
- Department of NeurologySUNY Downstate Health Sciences UniversityBrooklynNY
| | - Farid Khasiyev
- Department of NeurologySt. Louis University School of MedicineSt. LouisMO
| | - Jose Gutierrez
- Department of NeurologyColumbia University Irving Medical CenterNew YorkNY
| |
Collapse
|
72
|
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: 17] [Impact Index Per Article: 5.7] [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
|
73
|
Wang ML, Zou QQ, Sun Z, Wei XE, Li PY, Wu X, Li YH. Associations of MRI-visible perivascular spaces with longitudinal cognitive decline across the Alzheimer's disease spectrum. Alzheimers Res Ther 2022; 14:185. [PMID: 36514127 PMCID: PMC9746143 DOI: 10.1186/s13195-022-01136-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2022] [Accepted: 12/05/2022] [Indexed: 12/15/2022]
Abstract
OBJECTIVE To investigate the characteristics and associations of MRI-visible perivascular spaces (PVS) with clinical progression and longitudinal cognitive decline across the Alzheimer's disease spectrum. METHODS We included 1429 participants (641 [44.86%] female) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. PVS number and grade in the centrum semiovale (CSO-PVS), basal ganglia (BG-PVS), and hippocampus (HP-PVS) were compared among the control (CN), mild cognitive impairment (MCI), and Alzheimer's disease (AD) groups. PVS were tested as predictors of diagnostic progression (i.e., CN to MCI/AD or MCI to AD) and longitudinal changes in the 13-item Alzheimer's Disease Assessment Scale-cognitive subscale (ADAS-Cog 13), Mini-Mental State Examination (MMSE), memory (ADNI-MEM), and executive function (ADNI-EF) using multiple linear regression, linear mixed-effects, and Cox proportional hazards modeling. RESULTS Compared with CN subjects, MCI and AD subjects had more CSO-PVS, both in number (p < 0.001) and grade (p < 0.001). However, there was no significant difference in BG-PVS and HP-PVS across the AD spectrum (p > 0.05). Individuals with moderate and frequent/severe CSO-PVS had a higher diagnostic conversion risk than individuals with no/mild CSO-PVS (log-rank p < 0.001 for all) in the combined CN and MCI group. Further Cox regression analyses revealed that moderate and frequent/severe CSO-PVS were associated with a higher risk of diagnostic conversion (HR = 2.007, 95% CI = 1.382-2.914, p < 0.001; HR = 2.676, 95% CI = 1.830-3.911, p < 0.001, respectively). A higher CSO-PVS number was associated with baseline cognitive performance and longitudinal cognitive decline in all cognitive tests (p < 0.05 for all). CONCLUSIONS CSO-PVS were more common in MCI and AD and were associated with cognitive decline across the AD spectrum.
Collapse
Affiliation(s)
- Ming-Liang Wang
- Department of Radiology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, No. 600, Yi Shan Road, Shanghai, 200233, China
| | - Qiao-Qiao Zou
- Department of Radiology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, No. 600, Yi Shan Road, Shanghai, 200233, China
| | - Zheng Sun
- Department of Radiology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, No. 600, Yi Shan Road, Shanghai, 200233, China
| | - Xiao-Er Wei
- Department of Radiology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, No. 600, Yi Shan Road, Shanghai, 200233, China
| | - Peng-Yang Li
- Division of Cardiology, Pauley Heart Center, Virginia Commonwealth University, Richmond, VA, USA
| | - Xue Wu
- Institute for Global Health Sciences, University of California San Francisco, San Francisco, CA, USA
| | - Yue-Hua Li
- Department of Radiology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, No. 600, Yi Shan Road, Shanghai, 200233, China.
| |
Collapse
|
74
|
Romero JR, Pinheiro A, Aparicio HJ, DeCarli CS, Demissie S, Seshadri S. MRI-Visible Perivascular Spaces and Risk of Incident Dementia: The Framingham Heart Study. Neurology 2022; 99:e2561-e2571. [PMID: 36175148 PMCID: PMC9754649 DOI: 10.1212/wnl.0000000000201293] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Accepted: 08/10/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES Perivascular spaces (PVS) visible on MRI scans may represent key aspects in the pathophysiology of stroke and dementia, including cerebral small vessel disease and glymphatic dysfunction. This study aimed to determine the association between MRI-visible PVS burden and the risk of incident dementia. METHODS This study included community-dwelling Framingham Heart Study Original and Offspring cohort participants with available brain MRI-PVS ratings, free of stroke and dementia. Multivariable Cox proportional hazard regression was used to obtain hazard ratios (HRs) and 95% CIs of the association between MRI-visible PVS and incident dementia. PVS were rated using validated methods in the basal ganglia (BG) and centrum semiovale (CSO). The outcomes included all-cause dementia, Alzheimer dementia (AD), and vascular dementia (VaD). RESULTS One thousand four hundred forty-nine participants 50 years or older (46% male) were included. Over a median follow-up period of 8.3 years, the incidence of all-cause dementia, AD, and VaD was 15.8%, 12.5%, and 2.5%, respectively. In models that adjusted for vascular risk factors and cardiovascular disease, the hazard for dementia increased steadily as PVS burden increased, rising 2-fold for those with grade II PVS (HR 2.44, 95% CI 1.51-3.93) to 5-fold in participants with grade IV (HR 5.05, 95% CI 2.75-9.26) compared with grade I PVS in CSO. In the BG, hazards increased 1.6-fold (HR 1.62, 95% CI 1.15-2.27) for grade II to 2.6-fold (HR 2.67, 95% CI 1.04-6.88) for grade IV compared with grade I PVS. The association remained significant for CSO but not for BG, after adjustment for white matter hyperintensity volume (WMHV), covert infarcts, and total brain volume. Similar findings were observed for AD, but VaD, limited by a small number of events, was not statistically significant. DISCUSSION Higher burden of PVS in CSO was associated with increased risk of developing dementia, independent of vascular risk factors, total brain volume, WMHVs, and covert infarcts. This finding supports a role for PVS as a subclinical MRI marker to identify individuals in subclinical stages at high risk of developing dementia who may benefit from early intervention.
Collapse
Affiliation(s)
- Jose Rafael Romero
- From the Department of Neurology (J.R.R., H.J.A.), Boston University School of Medicine, MA; Department of Biostatistics (A.P. S.D.), Boston University School of Public Health, MA; Department of Neurology (C.S.D.), University of California at Davis, CA; The Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases (S.S.), University of Texas Health Sciences Center, San Antonio, TX; and NHLBI's Framingham Heart Study (J.R.R., A.P., H.J.A., S.D., S.S.), MA.
| | - Adlin Pinheiro
- From the Department of Neurology (J.R.R., H.J.A.), Boston University School of Medicine, MA; Department of Biostatistics (A.P. S.D.), Boston University School of Public Health, MA; Department of Neurology (C.S.D.), University of California at Davis, CA; The Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases (S.S.), University of Texas Health Sciences Center, San Antonio, TX; and NHLBI's Framingham Heart Study (J.R.R., A.P., H.J.A., S.D., S.S.), MA
| | - Hugo J Aparicio
- From the Department of Neurology (J.R.R., H.J.A.), Boston University School of Medicine, MA; Department of Biostatistics (A.P. S.D.), Boston University School of Public Health, MA; Department of Neurology (C.S.D.), University of California at Davis, CA; The Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases (S.S.), University of Texas Health Sciences Center, San Antonio, TX; and NHLBI's Framingham Heart Study (J.R.R., A.P., H.J.A., S.D., S.S.), MA
| | - Charles S DeCarli
- From the Department of Neurology (J.R.R., H.J.A.), Boston University School of Medicine, MA; Department of Biostatistics (A.P. S.D.), Boston University School of Public Health, MA; Department of Neurology (C.S.D.), University of California at Davis, CA; The Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases (S.S.), University of Texas Health Sciences Center, San Antonio, TX; and NHLBI's Framingham Heart Study (J.R.R., A.P., H.J.A., S.D., S.S.), MA
| | - Serkalem Demissie
- From the Department of Neurology (J.R.R., H.J.A.), Boston University School of Medicine, MA; Department of Biostatistics (A.P. S.D.), Boston University School of Public Health, MA; Department of Neurology (C.S.D.), University of California at Davis, CA; The Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases (S.S.), University of Texas Health Sciences Center, San Antonio, TX; and NHLBI's Framingham Heart Study (J.R.R., A.P., H.J.A., S.D., S.S.), MA
| | - Sudha Seshadri
- From the Department of Neurology (J.R.R., H.J.A.), Boston University School of Medicine, MA; Department of Biostatistics (A.P. S.D.), Boston University School of Public Health, MA; Department of Neurology (C.S.D.), University of California at Davis, CA; The Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases (S.S.), University of Texas Health Sciences Center, San Antonio, TX; and NHLBI's Framingham Heart Study (J.R.R., A.P., H.J.A., S.D., S.S.), MA
| |
Collapse
|
75
|
Smith E. Perivascular Spaces: Clinically Relevant but Underappreciated. Neurology 2022; 99:1019-1020. [PMID: 36175152 DOI: 10.1212/wnl.0000000000201442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Accepted: 09/07/2022] [Indexed: 11/15/2022] Open
|
76
|
Kapoor A, Yew B, Jang JY, Dutt S, Li Y, Alitin JPM, Gaubert A, Ho JK, Blanken AE, Sible IJ, Marshall A, Shao X, Mather M, Wang DJJ, Nation DA. Older adults with perivascular spaces exhibit cerebrovascular reactivity deficits. Neuroimage 2022; 264:119746. [PMID: 36370956 PMCID: PMC10033456 DOI: 10.1016/j.neuroimage.2022.119746] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 10/12/2022] [Accepted: 11/08/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Perivascular spaces on brain magnetic resonance imaging (MRI) may indicate poor fluid drainage in the brain and have been associated with numerous neurological conditions. Cerebrovascular reactivity (CVR) is a marker of cerebrovascular function and represents the ability of cerebral blood vessels to regulate cerebral blood flow in response to vasodilatory or vasoconstrictive stimuli. We aimed to examine whether pathological widening of the perivascular space in older adults may be associated with deficits in CVR. METHODS Independently living older adults free of dementia or clinical stroke were recruited from the community and underwent brain MRI. Pseudo-continuous arterial spin labeling MRI quantified whole brain cerebral perfusion at rest and during CVR to hypercapnia and hypocapnia induced by visually guided breathing exercises. Perivascular spaces were visually scored using existing scales. RESULTS Thirty-seven independently living older adults (mean age = 66.3 years; SD = 6.8; age range 55-84 years; 29.7% male) were included in the current analysis. Multiple linear regression analysis revealed a significant negative association between burden of perivascular spaces and global CVR to hypercapnia (B = -2.0, 95% CI (-3.6, -0.4), p = .015), adjusting for age and sex. Perivascular spaces were not related to CVR to hypocapnia. DISCUSSION Perivascular spaces are associated with deficits in cerebrovascular vasodilatory response, but not vasoconstrictive response. Enlargement of perivascular spaces could contribute to, or be influenced by, deficits in CVR. Additional longitudinal studies are warranted to improve our understanding of the relationship between cerebrovascular function and perivascular space enlargement.
Collapse
Affiliation(s)
- Arunima Kapoor
- Department of Psychological Science, University of California, Irvine, CA, USA
| | - Belinda Yew
- Department of Psychology, University of Southern California, Los Angeles, CA, USA
| | - Jung Yun Jang
- Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, CA, USA
| | - Shubir Dutt
- Department of Psychology, University of Southern California, Los Angeles, CA, USA
| | - Yanrong Li
- Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, CA, USA
| | - John Paul M Alitin
- Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, CA, USA
| | - Aimee Gaubert
- Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, CA, USA
| | - Jean K Ho
- Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, CA, USA
| | - Anna E Blanken
- San Francisco Veterans Affairs Health Care System & Department of Psychiatry, University of California, San Francisco, CA, USA
| | - Isabel J Sible
- Department of Psychology, University of Southern California, Los Angeles, CA, USA
| | - Anisa Marshall
- Department of Psychology, University of Southern California, Los Angeles, CA, USA
| | - Xingfeng Shao
- Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA
| | - Mara Mather
- Davis School of Gerontology and Department of Psychology, University of Southern California, Los Angeles, CA, USA
| | - Danny J J Wang
- Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA
| | - Daniel A Nation
- Department of Psychological Science, University of California, Irvine, CA, USA; Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, CA, USA.
| |
Collapse
|
77
|
Baril AA, Pinheiro AA, Himali JJ, Beiser A, Sanchez E, Pase MP, Seshadri S, Demissie S, Romero JR. Lighter sleep is associated with higher enlarged perivascular spaces burden in middle-aged and elderly individuals. Sleep Med 2022; 100:558-564. [PMID: 36308914 PMCID: PMC9815141 DOI: 10.1016/j.sleep.2022.10.006] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 08/31/2022] [Accepted: 10/10/2022] [Indexed: 11/09/2022]
Abstract
BACKGROUND While healthy sleep is suggested to promote glymphatic clearance in the brain, poorer sleep may be associated with higher enlarged perivascular spaces (ePVS) burden, potentially representing impaired perivascular drainage. This study aims to evaluate the association between ePVS burden and polysomnographic sleep characteristics in a large community-based sample. METHODS 552 dementia and stroke-free Framingham Heart Study participants (age: 58.6 ± 8.9 years; 50.4% men) underwent a full-night in-home polysomnography. Three years later on average, participants underwent a brain MRI. ePVS were rated in the basal ganglia and centrum semiovale, and dichotomized as low burden (<20 counts, grades 1 and 2) or high burden (>20 counts, grades 3 and 4). Logistic regression analyses relating sleep variables to subsequent ePVS burden were used, adjusted for age, sex, time interval between polysomnography and MRI, ApoE ε4 allele carrier status, hypertension, and smoking. RESULTS Longer N1 sleep and shorter N3 sleep duration were associated with higher ePVS burden in the centrum semiovale. When stratifying these associations by subpopulations, longer N1 sleep duration with ePVS burden was observed especially in older individuals and hypertensive participants. Associations between ePVS burden and other sleep characteristics such as total sleep time and REM sleep duration varied according to ApoE ε4 allele carrier status. CONCLUSIONS Lighter sleep, as characterized by longer N1 sleep and shorter slow-wave sleep, is associated with higher ePVS burden. These findings suggest that sleep architecture may be involved in glymphatic clearance and cerebral small vessel disease, which could be an important biological link between sleep and dementia risk.
Collapse
Affiliation(s)
- Andrée-Ann Baril
- The Framingham Heart Study, Framingham, USA; Douglas Mental Health University Institute, Montreal, Canada; Department of Psychiatry, McGill University, Montreal, Canada
| | - Adlin A Pinheiro
- The Framingham Heart Study, Framingham, USA; Department of Biostatistics, Boston University School of Public Health, Boston, USA
| | - Jayandra J Himali
- The Framingham Heart Study, Framingham, USA; Department of Biostatistics, Boston University School of Public Health, Boston, USA; Department of Neurology, Boston University School of Medicine, Boston, USA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, UT Health San Antonio, San Antonio, USA; Department of Population Health Sciences, University of Texas Health Science Center, San Antonio, TX, USA
| | - Alexa Beiser
- The Framingham Heart Study, Framingham, USA; Department of Biostatistics, Boston University School of Public Health, Boston, USA
| | - Erlan Sanchez
- Sunnybrook Research Institute, University of Toronto, Toronto, Canada
| | - Matthew P Pase
- The Framingham Heart Study, Framingham, USA; Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, VIC, Australia; Harvard T.H. Chan School of Public Health, Boston, USA
| | - Sudha Seshadri
- The Framingham Heart Study, Framingham, USA; Department of Neurology, Boston University School of Medicine, Boston, USA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, UT Health San Antonio, San Antonio, USA
| | - Serkalem Demissie
- The Framingham Heart Study, Framingham, USA; Department of Biostatistics, Boston University School of Public Health, Boston, USA
| | - Jose R Romero
- The Framingham Heart Study, Framingham, USA; Department of Neurology, Boston University School of Medicine, Boston, USA.
| |
Collapse
|
78
|
Ineichen BV, Okar SV, Proulx ST, Engelhardt B, Lassmann H, Reich DS. Perivascular spaces and their role in neuroinflammation. Neuron 2022; 110:3566-3581. [PMID: 36327898 PMCID: PMC9905791 DOI: 10.1016/j.neuron.2022.10.024] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 08/17/2022] [Accepted: 10/13/2022] [Indexed: 11/19/2022]
Abstract
It is uncontested that perivascular spaces play critical roles in maintaining homeostasis and priming neuroinflammation. However, despite more than a century of intense research on perivascular spaces, many open questions remain about the anatomical compartment surrounding blood vessels within the CNS. The goal of this comprehensive review is to summarize the literature on perivascular spaces in human neuroinflammation and associated animal disease models. We describe the cell types taking part in the morphological and functional aspects of perivascular spaces and how those spaces can be visualized. Based on this, we propose a model of the cascade of events occurring during neuroinflammatory pathology. We also discuss current knowledge gaps and limitations of the available evidence. An improved understanding of perivascular spaces could advance our comprehension of the pathophysiology of neuroinflammation and open a new therapeutic window for neuroinflammatory diseases such as multiple sclerosis.
Collapse
Affiliation(s)
- Benjamin V Ineichen
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA; Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland; Center for Reproducible Science, University of Zurich, Zurich, Switzerland.
| | - Serhat V Okar
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - Steven T Proulx
- Theodor Kocher Institute, University of Bern, Bern, Switzerland
| | | | - Hans Lassmann
- Department of Neuroimmunology, Center for Brain Research, Medical University of Vienna, Spitalgasse 4, 1090 Vienna, Austria
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| |
Collapse
|
79
|
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: 20] [Impact Index Per Article: 6.7] [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
|
80
|
Bernal J, Valdés-Hernández MDC, Escudero J, Duarte R, Ballerini L, Bastin ME, Deary IJ, Thrippleton MJ, Touyz RM, Wardlaw JM. Assessment of perivascular space filtering methods using a three-dimensional computational model. Magn Reson Imaging 2022; 93:33-51. [PMID: 35932975 DOI: 10.1016/j.mri.2022.07.016] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 07/19/2022] [Accepted: 07/30/2022] [Indexed: 10/31/2022]
Abstract
Growing interest surrounds the assessment of perivascular spaces (PVS) on magnetic resonance imaging (MRI) and their validation as a clinical biomarker of adverse brain health. Nonetheless, the limits of validity of current state-of-the-art segmentation methods are still unclear. Here, we propose an open-source three-dimensional computational framework comprising 3D digital reference objects and evaluate the performance of three PVS filtering methods under various spatiotemporal imaging considerations (including sampling, motion artefacts, and Rician noise). Specifically, we study the performance of the Frangi, Jerman and RORPO filters in enhancing PVS-like structures to facilitate segmentation. Our findings were three-fold. First, as long as voxels are isotropic, RORPO outperforms the other two filters, regardless of imaging quality. Unlike the Frangi and Jerman filters, RORPO's performance does not deteriorate as PVS volume increases. Second, the performance of all "vesselness" filters is heavily influenced by imaging quality, with sampling and motion artefacts being the most damaging for these types of analyses. Third, none of the filters can distinguish PVS from other hyperintense structures (e.g. white matter hyperintensities, stroke lesions, or lacunes) effectively, the area under precision-recall curve dropped substantially (Frangi: from 94.21 [IQR 91.60, 96.16] to 43.76 [IQR 25.19, 63.38]; Jerman: from 94.51 [IQR 91.90, 95.37] to 58.00 [IQR 35.68, 64.87]; RORPO: from 98.72 [IQR 95.37, 98.96] to 71.87 [IQR 57.21, 76.63] without and with other hyperintense structures, respectively). The use of our computational model enables comparing segmentation methods and identifying their advantages and disadvantages, thereby providing means for testing and optimising pipelines for ongoing and future studies.
Collapse
Affiliation(s)
- Jose Bernal
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK; Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke University Magdeburg, Magdeburg, Germany; German Centre for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Maria D C Valdés-Hernández
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK; Lothian Birth Cohorts group, Department of Psychology, The University of Edinburgh, UK.
| | - Javier Escudero
- Institute for Digital Communications, The University of Edinburgh, Edinburgh, UK
| | - Roberto Duarte
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
| | - Lucia Ballerini
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
| | - Mark E Bastin
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK; Lothian Birth Cohorts group, Department of Psychology, The University of Edinburgh, UK
| | - Ian J Deary
- Lothian Birth Cohorts group, Department of Psychology, The University of Edinburgh, UK
| | | | - Rhian M Touyz
- Research Institute of the McGill University Health Centre, McGill University, Montréal, Canada
| | - Joanna M Wardlaw
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK; Lothian Birth Cohorts group, Department of Psychology, The University of Edinburgh, UK
| |
Collapse
|
81
|
Zhang Y, Zhang R, Wang S, Hong H, Jiaerken Y, Li K, Zeng Q, Luo X, Yu X, Zhang M, Huang P. Reduced coupling between the global blood-oxygen-level-dependent signal and cerebrospinal fluid inflow is associated with the severity of small vessel disease. Neuroimage Clin 2022; 36:103229. [PMID: 36252555 PMCID: PMC9668594 DOI: 10.1016/j.nicl.2022.103229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 10/10/2022] [Accepted: 10/10/2022] [Indexed: 11/11/2022]
Abstract
BACKGROUND Small vessel disease (SVD) is highly prevalent in the elderly and associated with an increased risk of dementia and stroke. SVD may have disturbed cerebrospinal fluid (CSF) flow, which can compromise waste clearance and accelerate disease progression. METHODS We retrospectively included 146 SVD patients from a prospectively collected dataset, with one- or two-year follow-up data in 61 patients. The coupling strength between the global blood-oxygen-level-dependent (gBOLD) signal and CSF inflow was used to reflect CSF dynamics. We performed regression analyses to investigate the association between the gBOLD-CSF coupling index and the severity of SVD and vascular risk factors. Longitudinal analysis was carried out to investigate causal relationships. RESULTS Patients with severe SVD had significantly decreased gBOLD-CSF coupling (β = -0.180, p = 0.032). Dilation of perivascular spaces in the basal ganglia area (β = -0.172, p = 0.033) and diabetes (β = -0.204, p = 0.014) were associated with reduced gBOLD-CSF coupling. In longitudinal analyses, diabetes was associated with faster decline in gBOLD-CSF coupling (β = 0.20, p = 0.039), while perivascular space (PVS) dilation in the centrum semiovale showed a opposite relationship (β = -0.20, p = 0.041). The gBOLD-CSF coupling could not predict SVD progression. CONCLUSION Altered CSF flow is associated with the severity of SVD.
Collapse
Affiliation(s)
- Yao Zhang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000 Hangzhou, China
| | - Ruiting Zhang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000 Hangzhou, China; Department of Neurology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000 Hangzhou, China
| | - Shuyue Wang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000 Hangzhou, China
| | - Hui Hong
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000 Hangzhou, China
| | - Yeerfan Jiaerken
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000 Hangzhou, China
| | - Kaicheng Li
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000 Hangzhou, China
| | - Qingze Zeng
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000 Hangzhou, China
| | - Xiao Luo
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000 Hangzhou, China
| | - Xinfeng Yu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000 Hangzhou, China
| | - Minming Zhang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000 Hangzhou, China.
| | - Peiyu Huang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000 Hangzhou, China.
| |
Collapse
|
82
|
Zhou M, Wang S, Jing J, Yang Y, Cai X, Meng X, Mei L, Lin J, Li S, Li H, Wei T, Wang Y, Pan Y, Wang Y. Insulin resistance based on postglucose load measure is associated with prevalence and burden of cerebral small vessel disease. BMJ Open Diabetes Res Care 2022; 10:10/5/e002897. [PMID: 36220196 PMCID: PMC9557259 DOI: 10.1136/bmjdrc-2022-002897] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Accepted: 09/25/2022] [Indexed: 11/05/2022] Open
Abstract
INTRODUCTION Cerebral small vessel disease (cSVD) is highly prevalent and results in irreversible cognitive impairment and reduced quality of life. Previous studies reported controversial associations between insulin resistance and cSVD. Here, we estimated the association between insulin resistance and cSVD in non-diabetic communities in southeastern China. RESEARCH DESIGN AND METHODS The Polyvascular Evaluation for Cognitive Impairment and Vascular Events study (NCT03178448) recruited 3670 community-dwelling adults. We estimated the association of insulin resistance, assessed by the insulin sensitivity index (ISI0,120) and the homeostatic model assessment for insulin resistance (HOMA-IR) based on the standard oral glucose tolerance test, with cSVD in those without a history of diabetes mellitus. cSVD was measured for both main neuroimaging manifestations of cSVD and total SVD burden scores. RESULTS A total of 2752 subjects were enrolled. In the multivariable logistic regression analysis, the first quartile of ISI0,120 was found to be potentially associated with an increased risk of lacunes (OR 1.96, 95% CI 1.15 to 3.36), severe age-related white matter changes (OR 1.97, 95% CI 1.15 to 3.38), and higher total SVD burden (4-point scale: common OR (cOR) 1.34, 95% CI 1.04 to 1.72; 6-point scale: cOR 1.43, 95% CI 1.14 to 1.79). The associations between HOMA-IR and lacunes (OR 1.90, 95% CI 1.11 to 3.25) and the 4-point scale of total SVD burden (cOR 1.33, 95% CI 1.04 to 1.70) were also significant after adjustment for age, gender, medical history, and medications. However, the associations were not statistically significant after further adjustment for blood pressure/hypertension and body mass index (BMI). CONCLUSIONS A potential association was found between insulin resistance and cSVD, and the ISI0,120 index presented a greater association with increased risk of cSVD as compared with the HOMA-IR. However, these associations were greatly influenced by blood pressure and BMI.
Collapse
Affiliation(s)
- Mengyuan Zhou
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Suying Wang
- Cerebrovascular Research Lab, Lishui Hospital, Zhejiang University School of Medicine, Lishui, China
| | - Jing Jing
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Yingying Yang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Xueli Cai
- Department of Neurology, Lishui Hospital, Zhejiang University School of Medicine, Lishui, China
| | - Xia Meng
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Lerong Mei
- Cerebrovascular Research Lab, Lishui Hospital, Zhejiang University School of Medicine, Lishui, China
| | - Jinxi Lin
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Shan Li
- Cerebrovascular Research Lab, Lishui Hospital, Zhejiang University School of Medicine, Lishui, China
| | - Hao Li
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Tiemin Wei
- Department of Cardiology, Lishui Hospital, Zhejiang University School of Medicine, Lishui, China
| | - Yongjun Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Yuesong Pan
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Yilong Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
- National Center for Neurological Diseases, Beijing, China
| |
Collapse
|
83
|
Gyanwali B, Tan CS, Petr J, Escobosa LLT, Vrooman H, Chen C, Mutsaerts HJ, Hilal S. Arterial Spin-Labeling Parameters and Their Associations with Risk Factors, Cerebral Small-Vessel Disease, and Etiologic Subtypes of Cognitive Impairment and Dementia. AJNR Am J Neuroradiol 2022; 43:1418-1423. [PMID: 36562454 PMCID: PMC9575536 DOI: 10.3174/ajnr.a7630] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Accepted: 07/01/2022] [Indexed: 01/26/2023]
Abstract
BACKGROUND AND PURPOSE Cerebral small-vessel disease may alter cerebral blood flow (CBF) leading to brain changes and, hence, cognitive impairment and dementia. CBF and the spatial coefficient of variation can be measured quantitatively by arterial spin-labeling. We aimed to investigate the associations of demographics, vascular risk factors, location, and severity of cerebral small-vessel disease as well as the etiologic subtypes of cognitive impairment and dementia with CBF and the spatial coefficient of variation. MATERIALS AND METHODS Three hundred ninety patients with a diagnosis of no cognitive impairment, cognitive impairment no dementia, vascular cognitive impairment no dementia, Alzheimer disease, and vascular dementia were recruited from the memory clinic. Cerebral microbleeds and lacunes were categorized into strictly lobar, strictly deep, and mixed-location and enlarged perivascular spaces into the centrum semiovale and basal ganglia. Total and region-specific white matter hyperintensity volumes were segmented using FreeSurfer. CBF (n = 333) and the spatial coefficient of variation (n = 390) were analyzed with ExploreASL from 2D-EPI pseudocontinuous arterial spin-labeling images in white matter (WM) and gray matter (GM). To analyze the effect of demographic and vascular risk factors as well as the location and severity of cerebral small-vessel disease markers on arterial spin-labeling parameters, we constructed linear regression models, whereas logistic regression models were used to determine the association between arterial spin-labeling parameters and cognitive impairment no dementia, vascular cognitive impairment no dementia, Alzheimer disease, and vascular dementia. RESULTS Increasing age, male sex, hypertension, hyperlipidemia, history of heart disease, and smoking were associated with lower CBF and a higher spatial coefficient of variation. Higher numbers of lacunes and cerebral microbleeds were associated with lower CBF and a higher spatial coefficient of variation. Location-specific analysis showed mixed-location lacunes and cerebral microbleeds were associated with lower CBF. Higher total, anterior, and posterior white matter hyperintensity volumes were associated with a higher spatial coefficient of variation. No association was observed between enlarged perivascular spaces and arterial spin-labeling parameters. A higher spatial coefficient of variation was associated with the diagnosis of vascular cognitive impairment no dementia, Alzheimer's disease, and vascular dementia. CONCLUSIONS Reduced CBF and an increased spatial coefficient of variation were associated with cerebral small-vessel disease, and more specifically lacunes, whereas cerebral microbleeds and white matter hyperintensities were associated with WM-CBF and GM spatial coefficient of variation. The spatial coefficient of variation was associated with cognitive impairment and dementia, suggesting that hypoperfusion might be the key underlying mechanism for vascular brain damage.
Collapse
Affiliation(s)
- B Gyanwali
- From the Memory Aging and Cognition Centre (B.G., C.C., S.H.), National University Health System, Singapore
| | - C S Tan
- Saw Swee Hock School of Public Health (C.S.T., L.L.T.E., S.H.), National University of Singapore, and National University Health System, Singapore
| | - J Petr
- Helmholtz-Zentrum Dresden-Rossendorf (J.P.), Institute of Radiopharmaceutical Cancer Research, Dresden, Germany
| | - L L T Escobosa
- Saw Swee Hock School of Public Health (C.S.T., L.L.T.E., S.H.), National University of Singapore, and National University Health System, Singapore
| | - H Vrooman
- Department of Radiology and Nuclear Medicine (H.V.), Erasmus University Medical Center, Rotterdam, The Netherlands
| | - C Chen
- From the Memory Aging and Cognition Centre (B.G., C.C., S.H.), National University Health System, Singapore
- Department of Pharmacology (C.C., S.H.), Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - H J Mutsaerts
- Department of Radiology (H.J.M.), VU University Medical Center, Amsterdam, the Netherlands
- Department of Radiology (H.J.M.), Brain Center Rudolf Magnus, University Medical Center, Utrecht, the Netherlands
| | - S Hilal
- From the Memory Aging and Cognition Centre (B.G., C.C., S.H.), National University Health System, Singapore
- Saw Swee Hock School of Public Health (C.S.T., L.L.T.E., S.H.), National University of Singapore, and National University Health System, Singapore
- Department of Pharmacology (C.C., S.H.), Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| |
Collapse
|
84
|
Diker S, Gelener P, Erem A, Balyemez U. Association of Dilated Perivascular Spaces With Lipid Indices in Ischemic Stroke Patients. Cureus 2022; 14:e28783. [PMID: 36225408 PMCID: PMC9532960 DOI: 10.7759/cureus.28783] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/04/2022] [Indexed: 11/24/2022] Open
Abstract
Background Dilated perivascular spaces (dPVS) in the basal ganglia are associated with aging, vascular risk factors, and other magnetic resonance imaging (MRI) markers of cerebral small vessel disease (cSVD). While high blood lipids are a well-demonstrated risk factor for large artery atherosclerosis, their role in cSVD remains largely elusive. Methods We evaluated lipid profiles, cardiovascular risk factors, and brain MRI findings in patients with ischemic stroke or transient ischemic attack. We analyzed the extent of dPVS, cerebral microbleed (CMB), and cerebral white matter hyperintensities (WMHs) as MRI indices of cSVD and investigated associations of dPVS with lipid parameters and other cSVD indices. Results Our study enrolled 173 patients with ischemic stroke or transient ischemic attack. The mean age was 68.38±14.31 (range 35-99) years, and 57.8% (n=100) of patients were male. dPVSwere detected in 97% (n=168) of the patients. Among the whole population, half of the patients (n=87) had moderate to severe dPVS. According to the univariate analysis, age, hypertension, previous antiaggregant and/or anticoagulant use, and the high-density lipoprotein to low-density lipoprotein (HDL/LDL) ratio but not other lipid profiles, cerebral microbleed load, and cerebral white matter hyperintensities severity were found to be positively associated with dPVS number in the basal ganglia. After multivariate logistic regression analysis, only age and WMH severity remained statistically significant. Conclusions dPVS are closely associated with other cSVD subtypes and aging. The studied lipid indices were not independently associated with moderate to severe dPVS in basal ganglia in ischemic stroke patients. The association of each lipid and HDL/LDL ratio needs to be further studied with a larger number of participants.
Collapse
|
85
|
Zou Q, Wang M, Wei X, Li W. Prevalence and Risk Factors for Enlarged Perivascular Spaces in Young Adults from a Neurology Clinic-Based Cohort. Brain Sci 2022; 12:brainsci12091164. [PMID: 36138900 PMCID: PMC9497082 DOI: 10.3390/brainsci12091164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 08/23/2022] [Accepted: 08/29/2022] [Indexed: 11/16/2022] Open
Abstract
(1) Background: This study aimed to investigate the prevalence and risk factors for enlarged perivascular spaces (EPVS) in young adults from a neurology clinic-based cohort (≤45 years old) via unenhanced brain MRI. (2) Methods: A total of 931 young adults from a neurology clinic-based cohort who underwent unenhanced brain MRI between 1 January 2021 and 30 June 2021 were retrospectively included in this study. The EPVS were rated in the centrum semiovale (CSO-EPVS), basal ganglia (BG-EPVS), and midbrain (MB-EPVS) using a visual rating scale. The degrees of the CSO-EPVS, BG-EPVS, and MB-EPVS were all divided by a cutoff value of 1. Demographic factors, vascular risk factors, and symptoms were analyzed using the chi-square test and logistic regression to determine the risk factors of EPVS. (3) Results: The overall prevalence of EPVS was 99.8% (929/931). The CSO-EPVS, BG-EPVS, and MB-EPVS were predominantly scored as 1 (52.1%, 79.1%, and 58.3%, respectively). Logistic regression analysis identified age and hypertension as factors affecting the degrees of CSO-EPVS and BG-EPVS (p < 0.05). Hypertension (p < 0.001) and diabetes (p = 0.014) were revealed to be factors affecting the degree of BG-EPVS. Furthermore, patients with headache (OR = 1.807; p = 0.001) and dizziness (OR = 1.574; p = 0.025) were associated with MB-EPVS. (4) Conclusions: EPVS were frequently found in young adults and could be related to the symptoms. Age, hypertension, and diabetes were the risk factors for the severity of EPVS in the corresponding brain regions.
Collapse
|
86
|
Barnes A, Ballerini L, Valdés Hernández MDC, Chappell FM, Muñoz Maniega S, Meijboom R, Backhouse EV, Stringer MS, Duarte Coello R, Brown R, Bastin ME, Cox SR, Deary IJ, Wardlaw JM. Topological relationships between perivascular spaces and progression of white matter hyperintensities: A pilot study in a sample of the Lothian Birth Cohort 1936. Front Neurol 2022; 13:889884. [PMID: 36090857 PMCID: PMC9449650 DOI: 10.3389/fneur.2022.889884] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Accepted: 08/01/2022] [Indexed: 11/13/2022] Open
Abstract
Enlarged perivascular spaces (PVS) and white matter hyperintensities (WMH) are features of cerebral small vessel disease which can be seen in brain magnetic resonance imaging (MRI). Given the associations and proposed mechanistic link between PVS and WMH, they are hypothesized to also have topological proximity. However, this and the influence of their spatial proximity on WMH progression are unknown. We analyzed longitudinal MRI data from 29 out of 32 participants (mean age at baseline = 71.9 years) in a longitudinal study of cognitive aging, from three waves of data collection at 3-year intervals, alongside semi-automatic segmentation masks for PVS and WMH, to assess relationships. The majority of deep WMH clusters were found adjacent to or enclosing PVS (waves-1: 77%; 2: 76%; 3: 69%), especially in frontal, parietal, and temporal regions. Of the WMH clusters in the deep white matter that increased between waves, most increased around PVS (waves-1-2: 73%; 2-3: 72%). Formal statistical comparisons of severity of each of these two SVD markers yielded no associations between deep WMH progression and PVS proximity. These findings may suggest some deep WMH clusters may form and grow around PVS, possibly reflecting the consequences of impaired interstitial fluid drainage via PVS. The utility of these relationships as predictors of WMH progression remains unclear.
Collapse
Affiliation(s)
- Abbie Barnes
- College of Medicine and Veterinary Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Lucia Ballerini
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Maria del C. Valdés Hernández
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Francesca M. Chappell
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Susana Muñoz Maniega
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Rozanna Meijboom
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Ellen V. Backhouse
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Michael S. Stringer
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Roberto Duarte Coello
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Rosalind Brown
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Mark E. Bastin
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Simon R. Cox
- Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom
| | - Ian J. Deary
- Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom
| | - Joanna M. Wardlaw
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| |
Collapse
|
87
|
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: 53] [Impact Index Per Article: 17.7] [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
|
88
|
Zeng Q, Li K, Luo X, Wang S, Xu X, Jiaerken Y, Liu X, Hong L, Hong H, Li Z, Fu Y, Zhang T, Chen Y, Liu Z, Huang P, Zhang M. The association of enlarged perivascular space with microglia-related inflammation and Alzheimer's pathology in cognitively normal elderly. Neurobiol Dis 2022; 170:105755. [PMID: 35577066 DOI: 10.1016/j.nbd.2022.105755] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Revised: 04/15/2022] [Accepted: 05/10/2022] [Indexed: 01/21/2023] Open
Abstract
BACKGROUND Glymphatic dysfunction may contribute to the accumulation of Alzheimer's disease (AD) pathologies. Conversely, AD pathologic change might also cause neuroinflammation and aggravate glymphatic dysfunction, forming a loop that accelerates AD progression. In vivo validations are needed to confirm their relationships. METHODS In this study, we included 144 cognitively normal participants with AD pathological biomarker data (baseline CSF Aβ1-42, T-Tau, P-Tau181; plasma P-Tau181 at baseline and at least one follow-up) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Each subject had completed structural MRI scans. Among them, 117 subjects have available neuroinflammatory biomarker (soluble triggering receptor expressed on myeloid cells 2 (sTREM2), and 123 subjects have completed two times [18F]-florbetapir PET. The enlarged PVS (EPVS) visual rating scores in basal ganglia (BG) and centrum semiovale (CS) were assessed on T1-weighted images to reflect glymphatic dysfunction. Intracranial volume and white matter hyperintensities (WMH) volume were also calculated for further analysis. We performed stepwise linear regression models and mediation analyses to estimate the association between EPVS severity, sTREM2, and AD biomarkers. RESULTS CS-EPVS degree was associated with CSF sTREM2, annual change of plasma P-tau181 and total WMH volume, whereas BG-EPVS severity was associated with age, gender and intracranial volume. The sTREM2 mediated the association between CSF P-tau181 and CS-EPVS. CONCLUSION Impaired glymphatic dysfunction could contribute to the accumulation of pathological tau protein. The association between tauopathy and glymphatic dysfunction was mediated by the microglia inflammatory process. These findings may provide evidence for novel treatment strategies of anti-neuroinflammation therapy in the early stage.
Collapse
Affiliation(s)
- Qingze Zeng
- Department of Radiology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Kaicheng Li
- Department of Radiology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xiao Luo
- Department of Radiology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Shuyue Wang
- Department of Radiology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaopei Xu
- Department of Radiology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Yeerfan Jiaerken
- Department of Radiology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaocao Liu
- Department of Radiology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Luwei Hong
- Department of Radiology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Hui Hong
- Department of Radiology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Zheyu Li
- Department of Neurology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Yanv Fu
- Department of Neurology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Tianyi Zhang
- Department of Neurology, Tongde Hospital of Zhejiang Province, Hangzhou, China
| | - Yanxing Chen
- Department of Neurology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Zhirong Liu
- Department of Neurology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Peiyu Huang
- Department of Radiology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.
| | - Minming Zhang
- Department of Radiology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.
| |
Collapse
|
89
|
Song Q, Zhao Y, Lin T, Yue J. Perivascular spaces visible on magnetic resonance imaging predict subsequent delirium in older patients. Front Aging Neurosci 2022; 14:897802. [PMID: 35923543 PMCID: PMC9340666 DOI: 10.3389/fnagi.2022.897802] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Accepted: 06/28/2022] [Indexed: 11/24/2022] Open
Abstract
Background It remains unknown whether perivascular spaces (PVS) are associated with delirium in older hospitalized patients. We aimed to determine the association between magnetic resonance imaging (MRI)-visible PVS and the risk of delirium in a cohort of older patients. Methods We consecutively recruited older patients (≥70 years) admitted to the Geriatric Department of West China Hospital between March 2016 and July 2017, and their imaging data within one year before admission were reviewed retrospectively. PVS was rated on axial T2-weighted images in the basal ganglia (BG) and centrum semiovale (CS) using the validated semiquantitative 4-point ordinal scale. Delirium was screened within 24 h of admission and three times daily thereafter, using the confusion assessment method. Binary logistic regression analyses were performed to investigate the associations between PVS and delirium. Results Among 114 included patients (mean age 84.3 years, 72.8% male), delirium occurred in 20 (17.5%). In patients with MRI examined within 6 months before admission, CS-PVS was found to be associated with delirium (odds ratio [OR] 3.88, 95% confidence interval [CI] 1.07-14.06, unadjusted; and OR 4.24, 95% CI 1.11-16.28, adjusted for age). The associations were enhanced and remained significant even after full adjustment of covariates (OR 7.16, 95% CI 1.16-44.32, adjusted for age, cognitive impairment, smoking, and Charlson Comorbidity Index). Similarly, the relationships between high CS-PVS and delirium were also strengthened after sequentially adjusting all variables of interest, with OR 4.17 (95% CI 1.04-16.73) in unadjusted model and OR 7.95 (95% CI 1.14-55.28) in fully-adjusted model. Adding CS-PVS to the established risk factors improved the risk reclassification for delirium (continuous net reclassification index 62.1%, P = 0.04; and integrated discrimination improvement 12.5%, P = 0.01). Conclusions CS-PVS on MRI acquired 6 months earlier predicts subsequent delirium in older patients and may have clinical utility in delirium risk stratification to enable proactive interventions.
Collapse
|
90
|
Lara FR, Scruton AL, Pinheiro A, Demissie S, Parva P, Charidimou A, Francis M, Himali JJ, DeCarli C, Beiser A, Seshadri S, Romero JR. Aging, prevalence and risk factors of MRI-visible enlarged perivascular spaces. Aging (Albany NY) 2022; 14:6844-6858. [PMID: 35852852 PMCID: PMC9512514 DOI: 10.18632/aging.204181] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Accepted: 05/30/2022] [Indexed: 11/25/2022]
Abstract
BACKGROUND AND PURPOSE Cerebral small vessel disease (CSVD) increases with age and is associated with stroke and cognitive decline. Enlarged Perivascular Spaces (ePVS) is an emerging marker of CSVD, but its prevalence over the life span remain unclear. We characterized the age and sex-specific prevalence of ePVS and relation to age-specific risk factors, in a large community-based sample. METHODS We included 3,710 Framingham Heart Study participants with available brain MRI (average age 61.4±14.6, 46% men). ePVS burden was rated in the centrum semiovale (CSO) and basal ganglia (BG) regions. Individual vascular risk factors were related to ePVS burden in the CSO, BG, and mixed CSO-BG regions using multivariable adjusted ordinal logistic regression analysis. RESULTS Severe ePVS prevalence increased with age in men and women, and paralleled increase in vascular risk factors, and prevention treatment use. Older age, hypertension (and resulting higher treatment use), higher systolic and diastolic blood pressure, and smoking were associated with higher burden of ePVS in the CSO, BG and mixed regions. CONCLUSIONS Our observations reinforce the hypothesis that ePVS may be a marker of aging-driven brain vascular pathologies, and its association with vascular risk factors support their role as CSVD imaging biomarker.
Collapse
Affiliation(s)
| | | | - Adlin Pinheiro
- NHLBI’s Framingham Heart Study, Framingham, MA 01702, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
| | - Serkalem Demissie
- NHLBI’s Framingham Heart Study, Framingham, MA 01702, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
| | - Pedram Parva
- Department of Radiology, Veterans Affairs Boston Health System, Boston, MA 02130, USA
| | - Andreas Charidimou
- Department of Neurology, Boston University School of Medicine, Boston, MA 02118, USA
| | | | - Jayandra J. Himali
- NHLBI’s Framingham Heart Study, Framingham, MA 01702, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA 02118, USA
- The Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX 78229, USA
| | - Charles DeCarli
- Department of Neurology, University of California at Davis, Davis, CA 95817, USA
| | - Alexa Beiser
- NHLBI’s Framingham Heart Study, Framingham, MA 01702, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA 02118, USA
| | - Sudha Seshadri
- NHLBI’s Framingham Heart Study, Framingham, MA 01702, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA 02118, USA
- The Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX 78229, USA
| | - Jose R. Romero
- NHLBI’s Framingham Heart Study, Framingham, MA 01702, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA 02118, USA
| |
Collapse
|
91
|
Zdanovskis N, Platkājis A, Kostiks A, Šneidere K, Stepens A, Naglis R, Karelis G. Combined Score of Perivascular Space Dilatation and White Matter Hyperintensities in Patients with Normal Cognition, Mild Cognitive Impairment, and Dementia. Medicina (B Aires) 2022; 58:medicina58070887. [PMID: 35888606 PMCID: PMC9318632 DOI: 10.3390/medicina58070887] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2022] [Revised: 06/27/2022] [Accepted: 06/29/2022] [Indexed: 11/16/2022] Open
Abstract
Background and Objectives: Cerebral perivascular spaces (PVS) are part of the cerebral microvascular structure and play a role in lymphatic drainage and the removal of waste products from the brain. White matter hyperintensities (WMH) are hyperintense lesions on magnetic resonance imaging that are associated with cognitive impairment, dementia, and cerebral vascular disease. WMH and PVS are direct and indirect imaging biomarkers of cerebral microvascular integrity and health. In our research, we evaluated WMH and PVS enlargement in patients with normal cognition (NC), mild cognitive impairment (MCI), and dementia (D). Materials and Methods: In total, 57 participants were included in the study and divided into groups based on neurological evaluation and Montreal Cognitive Assessment results (NC group 16 participants, MCI group 29 participants, D group 12 participants). All participants underwent 3T magnetic resonance imaging. PVS were evaluated in the basal ganglia, centrum semiovale, and midbrain. WMHs were evaluated based on the Fazekas scale and the division between deep white matter (DWM) and periventricular white matter (PVWM). The combined score based on PVS and WMH was evaluated and correlated with the results of the MoCA. Results: We found statistically significant differences between groups on several measures. Centrum semiovale PVS dilatation was more severe in MCI and dementia group and statistically significant differences were found between D-MCI and D-NC pairs. PVWM was more severe in patients with MCI and dementia group, and statistically significant differences were found between D-MCI and D-NC pairs. Furthermore, we found statistically significant differences between the groups by analyzing the combined score of PVS dilatation and WMH. We did not find statistically significant differences between the groups in PVS dilation of the basal ganglia and midbrain and DWM hyperintensities. Conclusions: PVS assessment could become one of neuroimaging biomarkers for patients with cognitive decline. Furthermore, the combined score of WMH and PVS dilatation could facilitate diagnostics of cognitive impairment, but more research is needed with a larger cohort to determine the use of PVS dilatation and the combined score.
Collapse
Affiliation(s)
- Nauris Zdanovskis
- Department of Radiology, Riga Stradins University, LV-1007 Riga, Latvia;
- Department of Radiology, Riga East University Hospital, LV-1038 Riga, Latvia;
- Military Medicine Research and Study Centre, Riga Stradins University, LV-1007 Riga, Latvia; (K.Š.); (A.S.)
- Correspondence:
| | - Ardis Platkājis
- Department of Radiology, Riga Stradins University, LV-1007 Riga, Latvia;
- Department of Radiology, Riga East University Hospital, LV-1038 Riga, Latvia;
| | - Andrejs Kostiks
- Department of Neurology and Neurosurgery, Riga East University Hospital, LV-1038 Riga, Latvia; (A.K.); (G.K.)
| | - Kristīne Šneidere
- Military Medicine Research and Study Centre, Riga Stradins University, LV-1007 Riga, Latvia; (K.Š.); (A.S.)
- Department of Health Psychology and Paedagogy, Riga Stradins University, LV-1007 Riga, Latvia
| | - Ainārs Stepens
- Military Medicine Research and Study Centre, Riga Stradins University, LV-1007 Riga, Latvia; (K.Š.); (A.S.)
| | - Roberts Naglis
- Department of Radiology, Riga East University Hospital, LV-1038 Riga, Latvia;
- Military Medicine Research and Study Centre, Riga Stradins University, LV-1007 Riga, Latvia; (K.Š.); (A.S.)
| | - Guntis Karelis
- Department of Neurology and Neurosurgery, Riga East University Hospital, LV-1038 Riga, Latvia; (A.K.); (G.K.)
- Department of Infectology, Riga Stradins University, LV-1007 Riga, Latvia
| |
Collapse
|
92
|
Gao Y, Deng W, Sun J, Yue D, Zhang B, Feng Y, Han J, Shen F, Hu J, Fu Y. The Association of Nocturnal Blood Pressure Patterns and Other Influencing Factors With Lacunes and Enlarged Perivascular Spaces in Hypertensive Patients. Front Neurol 2022; 13:879764. [PMID: 35677332 PMCID: PMC9168463 DOI: 10.3389/fneur.2022.879764] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2022] [Accepted: 04/12/2022] [Indexed: 11/13/2022] Open
Abstract
PurposeNocturnal blood pressure dipping patterns have been associated with an increased risk of Cerebral Small Vessel Disease (CSVD), which has not been well-studied. This study is aimed to explore the association of dipping patterns and other factors with lacunes and enlarged perivascular spaces (EPVS) in patients with hypertension.MethodsWe enrolled a total of 1,322 patients with essential hypertension in this study. Magnetic resonance imaging (MRI) scans and 24-h ambulatory blood pressure (BP) monitoring were completed. Nocturnal BP decline was calculated, and then dipping patterns were classified. Patients were classified into four groups according to the performance of lacunes and EPVS in the MRI scan for statistical analysis.Results(1) Nocturnal BP decline showed independent negative correlation with both lacunes and EPVS while mean systolic BP (mSBP) level showed an independent positive correlation with them (P < 0.05). (2) The frequency of reverse-dippers in the control group was significantly lower than that in other groups; the frequency of non-dippers in the lacunes group and EPVS group was significantly lower than that in the control group; the frequency of extreme-dippers in the EPVS group was significantly higher than that in the mixed (lacunes with EPVS) group (P < 0.05).ConclusionsBoth mSBP and dipping patterns might play an important role in developing lacunes and EPVS in patients with hypertension.
Collapse
Affiliation(s)
- Yang Gao
- Department of Neurology, The First Hospital of Jiaxing and The Affiliated Hospital of Jiaxing University, Jiaxing, China
| | - Weiping Deng
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jialan Sun
- Department of Neurology, Pudong New Area Gongli Hospital, Shanghai, China
| | - Dongqi Yue
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Bei Zhang
- Department of Radiology, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Yulan Feng
- Department of Neurology, Minhang Hospital, Fudan University, Shanghai, China
| | - Jun Han
- Department of Radiology, The First Hospital of Jiaxing and The Affiliated Hospital of Jiaxing University, Jiaxing, China
| | - Fanxia Shen
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jin Hu
- Department of Neurology, The First Hospital of Jiaxing and The Affiliated Hospital of Jiaxing University, Jiaxing, China
- Jin Hu
| | - Yi Fu
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- *Correspondence: Yi Fu
| |
Collapse
|
93
|
Cerebral small vessel disease alters neurovascular unit regulation of microcirculation integrity involved in vascular cognitive impairment. Neurobiol Dis 2022; 170:105750. [DOI: 10.1016/j.nbd.2022.105750] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Revised: 03/09/2022] [Accepted: 05/08/2022] [Indexed: 12/25/2022] Open
|
94
|
Yu J, Yan S, Niu P, Teng J. Relatively Early and Late-Onset Neuromyelitis Optica Spectrum Disorder in Central China: Clinical Characteristics and Prognostic Features. Front Neurol 2022; 13:859276. [PMID: 35493805 PMCID: PMC9046694 DOI: 10.3389/fneur.2022.859276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Accepted: 03/17/2022] [Indexed: 11/26/2022] Open
Abstract
Background We aimed to analyze the clinical characteristics and prognostic features of Chinese patients with relatively late-onset neuromyelitis optica spectrum disorder (RLO-NMOSD>40 years of age at disease onset), compared with patients with relatively early onset NMOSD (REO-NMOSD, ≤ 40 years of age at disease onset). Methods We retrospectively reviewed the medical records of patients with NMOSD in central China (with disease courses longer than 3 years) between January 2012 and January 2021. We further analyzed the clinical and prognostic differences between patients with REO-NMOSD and RLO-NMOSD. Results A total of 71 patients were included in this study. The results showed that 39 (54.9%) of the patients had RLO-NMOSD. The patients with RLO-NMOSD had higher expanded disability status scale (EDSS) scores than patients with REO-NMOSD at the initial (5.0 vs. 3.0, p = 0.01), 3-month (4.0 vs. 2.5, p = 0.001), 1-year (4.0 vs. 2.5, p = 0.003), 3rd-year (3.5 vs. 3.0, p = 0.0017), and final follow-up (4.0 vs. 2.5, P = 0.002) time points. The EDSS scores of visual function were 2.0 (1.0–3.0) in REO-NMOSD and 3.0 (2.0–3.0) in RLO-NMOSD (p = 0.038) at the final follow-up time point. The locations of spinal cord lesions at transverse myelitis (TM) onset were prone to cervical cord in patients with REO-NMOSD. There were no between-group treatment differences. The risk of requiring a cane to walk (EDSS score of 6.0) increased as the age of disease onset increased: for every 10-year increase in the age of disease onset, the risk of needing a cane to walk increased by 65% [hazard ratio (HR) = 1.65, 95% CI 1.15–2.38, p = 0.007]. Another significant predictor identified in the multivariate analysis was annualized relapse rate (ARR) (HR = 2.01, 95% CI 1.09–3.71, p = 0.025). In addition, we observed a positive correlation between age at onset and EDSS scores at the final follow-up (Spearman's r = 0.426, p < 0.0001) time point. EDSS scores at different periods were significantly different between patients with RLO-NMOSD and REO-NMOSD with anti-aquaporin-4 (AQP4) IgG positive. Conclusion The patients with RLO-NMOSD developed more severe disabilities than patients with REO-NMOSD at a variety of time periods. All of the patients may experience recurrent aggravated symptoms after their first year, with only patients with REO-NMOSD partly recovering from the 3rd year. The age at onset and ARR were the main predictors of outcomes.
Collapse
Affiliation(s)
- Jinbei Yu
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Shuai Yan
- Department of Neurology, Affiliated Hospital of Hebei University, Baoding, China
| | - Pengpeng Niu
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Junfang Teng
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- *Correspondence: Junfang Teng
| |
Collapse
|
95
|
Perosa V, Oltmer J, Munting LP, Freeze WM, Auger CA, Scherlek AA, van der Kouwe AJ, Iglesias JE, Atzeni A, Bacskai BJ, Viswanathan A, Frosch MP, Greenberg SM, van Veluw SJ. Perivascular space dilation is associated with vascular amyloid-β accumulation in the overlying cortex. Acta Neuropathol 2022; 143:331-348. [PMID: 34928427 PMCID: PMC9047512 DOI: 10.1007/s00401-021-02393-1] [Citation(s) in RCA: 82] [Impact Index Per Article: 27.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 11/10/2021] [Accepted: 12/02/2021] [Indexed: 12/14/2022]
Abstract
Perivascular spaces (PVS) are compartments surrounding cerebral blood vessels that become visible on MRI when enlarged. Enlarged PVS (EPVS) are commonly seen in patients with cerebral small vessel disease (CSVD) and have been suggested to reflect dysfunctional perivascular clearance of soluble waste products from the brain. In this study, we investigated histopathological correlates of EPVS and how they relate to vascular amyloid-β (Aβ) in cerebral amyloid angiopathy (CAA), a form of CSVD that commonly co-exists with Alzheimer's disease (AD) pathology. We used ex vivo MRI, semi-automatic segmentation and validated deep-learning-based models to quantify EPVS and associated histopathological abnormalities. Severity of MRI-visible PVS during life was significantly associated with severity of MRI-visible PVS on ex vivo MRI in formalin fixed intact hemispheres and corresponded with PVS enlargement on histopathology in the same areas. EPVS were located mainly around the white matter portion of perforating cortical arterioles and their burden was associated with CAA severity in the overlying cortex. Furthermore, we observed markedly reduced smooth muscle cells and increased vascular Aβ accumulation, extending into the WM, in individually affected vessels with an EPVS. Overall, these findings are consistent with the notion that EPVS reflect impaired outward flow along arterioles and have implications for our understanding of perivascular clearance mechanisms, which play an important role in the pathophysiology of CAA and AD.
Collapse
Affiliation(s)
- Valentina Perosa
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, J. Philip Kistler Stroke Research Center, Cambridge Str. 175, Suite 300, Boston, MA, 02114, USA.
- Department of Neurology, Otto-Von-Guericke University, Magdeburg, Germany.
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany.
| | - Jan Oltmer
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
| | - Leon P Munting
- Massachusetts General Hospital, MassGeneral Institute for Neurodegenerative Disease, Charlestown, MA, USA
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Whitney M Freeze
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Neuropsychology and Psychiatry, Maastricht University, Maastricht, The Netherlands
| | - Corinne A Auger
- Massachusetts General Hospital, MassGeneral Institute for Neurodegenerative Disease, Charlestown, MA, USA
| | - Ashley A Scherlek
- Massachusetts General Hospital, MassGeneral Institute for Neurodegenerative Disease, Charlestown, MA, USA
- Rush Alzheimer Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Andre J van der Kouwe
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
| | - Juan Eugenio Iglesias
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
- Centre for Medical Image Computing, University College London, London, UK
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Alessia Atzeni
- Centre for Medical Image Computing, University College London, London, UK
| | - Brian J Bacskai
- Massachusetts General Hospital, MassGeneral Institute for Neurodegenerative Disease, Charlestown, MA, USA
| | - Anand Viswanathan
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, J. Philip Kistler Stroke Research Center, Cambridge Str. 175, Suite 300, Boston, MA, 02114, USA
| | - Matthew P Frosch
- Massachusetts General Hospital, MassGeneral Institute for Neurodegenerative Disease, Charlestown, MA, USA
- Neuropathology Service, C.S. Kubik Laboratory for Neuropathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Steven M Greenberg
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, J. Philip Kistler Stroke Research Center, Cambridge Str. 175, Suite 300, Boston, MA, 02114, USA
| | - Susanne J van Veluw
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, J. Philip Kistler Stroke Research Center, Cambridge Str. 175, Suite 300, Boston, MA, 02114, USA
- Massachusetts General Hospital, MassGeneral Institute for Neurodegenerative Disease, Charlestown, MA, USA
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| |
Collapse
|
96
|
Li Y, Kalpouzos G, Laukka EJ, Dekhtyar S, Bäckman L, Fratiglioni L, Qiu C. Progression of neuroimaging markers of cerebral small vessel disease in older adults: a 6-year follow-up study. Neurobiol Aging 2022; 112:204-211. [DOI: 10.1016/j.neurobiolaging.2022.01.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 12/29/2021] [Accepted: 01/22/2022] [Indexed: 12/18/2022]
|
97
|
Yu N, Sinclair B, Posada LMG, Chen Z, Di Q, Lin X, Kolbe S, Hlauschek G, Kwan P, Law M. Asymmetric distribution of enlarged perivascular spaces in centrum semiovale may be associated with epilepsy after acute ischemic stroke. CNS Neurosci Ther 2022; 28:343-353. [PMID: 34981639 PMCID: PMC8841310 DOI: 10.1111/cns.13786] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Revised: 12/01/2021] [Accepted: 12/02/2021] [Indexed: 01/12/2023] Open
Abstract
Objective To investigate the factors influencing enlarged perivascular space (EPVS) characteristics at the onset of acute ischemic stroke (AIS), and whether the PVS characteristics can predict later post‐stroke epilepsy (PSE). Methods A total of 312 patients with AIS were identified, of whom 58/312 (18.6%) developed PSE. Twenty healthy participants were included as the control group. The number of PVS in the basal ganglia (BG), centrum semiovale (CS), and midbrain (MB) was manually calculated on T2‐weighted MRI. The scores and asymmetry index (AI) of EPVS in each region were compared among the enrolled participants. Other potential risk factors for PSE were also analyzed, including NIHSS at admission and stroke etiologies. Results The EPVS scores were significantly higher in the bilateral BG and CS of AIS patients compared to those of the control group (both p < 0.01). No statistical differences in EPVS scores in BG, CS, and MB were obtained between the PSE group and the nonepilepsy AIS group (all p > 0.01). However, markedly different AI scores in CS were found between the PSE group and the nonepilepsy AIS group (p = 0.004). Multivariable analysis showed that high asymmetry index of EPVS (AI≥0.2) in CS was an independent predictor for PSE (OR = 3.7, 95% confidence interval 1.5–9.1, p = 0.004). Conclusions Asymmetric distribution of EPVS in CS may be an independent risk factor and a novel imaging biomarker for the development of PSE. Further studies to understand the mechanisms of this association and confirmation with larger patient populations are warranted.
Collapse
Affiliation(s)
- Nian Yu
- Department of Neurology, The Affiliated Nanjing Brain Hospital of Nanjing Medical University, Nanjing, China.,Department of Neurology, Royal Melbourne Hospital, Melbourne, Vic., Australia.,Department of Radiology, Alfred Hospital, Melbourne, Vic., Australia
| | - Benjamin Sinclair
- Department of Neuroscience, Monash University, Melbourne, Vic., Australia.,Department of Neurology, Alfred Hospital, Melbourne, Vic., Australia
| | | | - Zhibin Chen
- Department of Neuroscience, Monash University, Melbourne, Vic., Australia
| | - Qing Di
- Department of Neurology, The Affiliated Nanjing Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Xingjian Lin
- Department of Neurology, The Affiliated Nanjing Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Scott Kolbe
- Department of Neuroscience, Monash University, Melbourne, Vic., Australia
| | - Gernot Hlauschek
- National Centre for Epilepsy, Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway
| | - Patrick Kwan
- Department of Neurology, Royal Melbourne Hospital, Melbourne, Vic., Australia.,Department of Neuroscience, Monash University, Melbourne, Vic., Australia.,Department of Neurology, Alfred Hospital, Melbourne, Vic., Australia.,Department of Medicine, University of Melbourne, Melbourne, Vic., Australia
| | - Meng Law
- Department of Radiology, Alfred Hospital, Melbourne, Vic., Australia.,Department of Neuroscience, Monash University, Melbourne, Vic., Australia.,Department of Neurological Surgery, University of Southern California, Los Angeles, California, USA
| |
Collapse
|
98
|
Rundek T, Del Brutto V, Goryawala M, Dong C, Agudelo C, Saporta AS, Merritt S, Camargo C, Ariko T, Loewenstein DA, Duara R, Haq I. Associations Between Vascular Risk Factors and Perivascular Spaces in Adults with Intact Cognition, Mild Cognitive Impairment, and Dementia. J Alzheimers Dis 2022; 89:437-448. [PMID: 35871327 PMCID: PMC10410400 DOI: 10.3233/jad-215585] [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: 11/15/2022]
Abstract
BACKGROUND Perivascular spaces (PVS) are fluid-filled compartments surrounding small intracerebral vessels that transport fluid and clear waste. OBJECTIVE We examined associations between PVS count, vascular and neurodegenerative risk factors, and cognitive status among the predominantly Hispanic participants of the FL-VIP Study of Alzheimer's Disease Risk. METHODS Using brain MRI (n = 228), we counted PVS in single axial image through the basal ganglia (BG) and centrum semiovale (CSO). PVS per region were scored as 0 (none), 1 (<10), 2 (11-20), 3 (21-40), and 4 (>40). Generalized linear models examined PVS associations with vascular risk factors and a composite vascular comorbidity risk (VASCom) score. RESULTS Our sample (mean age 72±8 years, 61% women, 60% Hispanic, mean education 15±4 years, 33% APOE4 carriers) was 59% hypertensive, 21% diabetic, 66% hypercholesteremic, and 30% obese. Mean VASCom score was 2.3±1.6. PVS scores ranged from 0-4 in the BG (mean 1.3±0.7) and CSO (mean 1.2±0.9), and 0-7 combined (mean 2.5±1.4). In multivariable regression models, BG PVS was associated with age (β= 0.03/year, p < 0.0001), Hispanic ethnicity (β= 0.29, p = 0.01), education (β= 0.04/year, p = 0.04), and coronary bypass surgery (β= 0.93, p = 0.02). CSO PVS only associated with age (β= 0.03/year, p < 0.01). APOE4 and amyloid-β were not associated with PVS. CONCLUSION BG PVS may be a marker of subclinical cerebrovascular disease. Further research is needed to validate associations and identify mechanisms linking BG PVS and cerebrovascular disease markers. PVS may be a marker of neurodegeneration despite our negative preliminary findings and more research is warranted. The association between BG PVS and Hispanic ethnicity also requires further investigation.
Collapse
Affiliation(s)
- Tatjana Rundek
- The Evelyn F. McKnight Brain Institute, University of Miami Miller School of Medicine, Miami, Florida, USA
- Department of Neurology, University of Miami Miller School of Medicine, Miami, Florida, USA
| | - Victor Del Brutto
- Department of Neurology, University of Miami Miller School of Medicine, Miami, Florida, USA
| | - Mohammed Goryawala
- The Evelyn F. McKnight Brain Institute, University of Miami Miller School of Medicine, Miami, Florida, USA
- Department of Radiology, University of Miami Miller School of Medicine, Miami, Florida, USA
| | - Chuanhui Dong
- The Evelyn F. McKnight Brain Institute, University of Miami Miller School of Medicine, Miami, Florida, USA
- Department of Neurology, University of Miami Miller School of Medicine, Miami, Florida, USA
| | - Christian Agudelo
- The Evelyn F. McKnight Brain Institute, University of Miami Miller School of Medicine, Miami, Florida, USA
- Department of Neurology, University of Miami Miller School of Medicine, Miami, Florida, USA
| | - Anita Seixas Saporta
- The Evelyn F. McKnight Brain Institute, University of Miami Miller School of Medicine, Miami, Florida, USA
- Department of Neurology, University of Miami Miller School of Medicine, Miami, Florida, USA
| | - Stacy Merritt
- The Evelyn F. McKnight Brain Institute, University of Miami Miller School of Medicine, Miami, Florida, USA
- Department of Neurology, University of Miami Miller School of Medicine, Miami, Florida, USA
| | - Christian Camargo
- The Evelyn F. McKnight Brain Institute, University of Miami Miller School of Medicine, Miami, Florida, USA
- Department of Neurology, University of Miami Miller School of Medicine, Miami, Florida, USA
| | - Taylor Ariko
- The Evelyn F. McKnight Brain Institute, University of Miami Miller School of Medicine, Miami, Florida, USA
| | - David A. Loewenstein
- The Evelyn F. McKnight Brain Institute, University of Miami Miller School of Medicine, Miami, Florida, USA
- The Center for Neurocognitive Sciences and Aging, University of Miami Miller School of Medicine, Miami, Florida, USA
- Department of Psychiatry, University of Miami Miller School of Medicine, Miami, Florida, USA
| | - Ranjan Duara
- Wien Center for Alzheimer’s Disease and Memory Disorders, Mount Sinai Medical Center, Miami Beach, FL, USA
| | - Ihtsham Haq
- The Evelyn F. McKnight Brain Institute, University of Miami Miller School of Medicine, Miami, Florida, USA
- Department of Neurology, University of Miami Miller School of Medicine, Miami, Florida, USA
| |
Collapse
|
99
|
Cousins O, Hodges A, Schubert J, Veronese M, Turkheimer F, Miyan J, Engelhardt B, Roncaroli F. The Blood‐CSF‐Brain Route of Neurological Disease: The Indirect Pathway into the Brain. Neuropathol Appl Neurobiol 2021; 48:e12789. [DOI: 10.1111/nan.12789] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Revised: 12/08/2021] [Accepted: 12/14/2021] [Indexed: 11/26/2022]
Affiliation(s)
- Oliver Cousins
- Department of Neuroimaging, IoPPN, King’s College London London United Kingdom
| | - Angela Hodges
- Department of Old Age Psychiatry, IoPPN, King’s College London London United Kingdom
| | - Julia Schubert
- Department of Neuroimaging, IoPPN, King’s College London London United Kingdom
| | - Mattia Veronese
- Department of Neuroimaging, IoPPN, King’s College London London United Kingdom
| | - Federico Turkheimer
- Department of Neuroimaging, IoPPN, King’s College London London United Kingdom
| | - Jaleel Miyan
- Division of Neuroscience and Experimental Psychology School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, M13 9PL
| | | | - Federico Roncaroli
- Division of Neuroscience and Experimental Psychology School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, M13 9PL
- Geoffrey Jefferson Brain Research Centre; Manchester Academic Health Science Centre Manchester UK
| |
Collapse
|
100
|
Lin CY, Jhan SR, Lee WJ, Chen PL, Chen JP, Chen HC, Chen TB. Imaging Markers of Subcortical Vascular Dementia in Patients With Multiple-Lobar Cerebral Microbleeds. Front Neurol 2021; 12:747536. [PMID: 34867731 PMCID: PMC8636110 DOI: 10.3389/fneur.2021.747536] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Accepted: 10/08/2021] [Indexed: 01/16/2023] Open
Abstract
Background and Purpose: Small vessel disease (SVD) imaging markers are related to ischemic and hemorrhage stroke and to cognitive dysfunction. This study aimed to clarify the relationship between SVD imaging markers and subcortical vascular dementia in severe SVD burden. Methods: A total of 57 subjects with multiple lobar cerebral microbleeds (CMBs) and four established SVD imaging markers were enrolled from the dementia and stroke registries of a single center. Visual rating scales that are used to semi-quantify SVD imaging changes were analyzed individually and compositely to make correlations with cognitive domains and subcortical vascular dementia. Results: Dementia group had higher subcortical and total white matter hyperintensities (WMHs) and SVD composite scores than non-dementia group. Individual imaging markers correlated differently with one another and had distinct cognitive correlations. After adjusting for demographic factors, multivariate logistic regression indicated associations of subcortical WMHs (odds ratio [OR] 2.03, CI 1.24–3.32), total WMHs (OR 1.43, CI 1.09–1.89), lacunes (OR 1.18, CI 1.02–1.35), cerebral amyloid angiopathy-SVD scores (OR 2.33, CI 1.01–5.40), C1 scores (imaging composite scores of CMB and WMH) (OR 1.41, CI 1.09–1.83), and C2 scores (imaging composite scores of CMB, WMH, perivascular space, and lacune) (OR 1.38, CI 1.08–1.76) with dementia. Conclusions: SVD imaging markers might have differing associations with cognitive domains and dementia. They may provide valuable complementary information in support of personalized treatment planning against cognitive impairment, particularly in patients with a heavy SVD load.
Collapse
Affiliation(s)
- Chia-Yen Lin
- Department of Neurology, Neurological Institute, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Song-Ru Jhan
- Division of Neuroradiology, Department of Radiology, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Wei-Ju Lee
- Department of Neurology, Neurological Institute, Taichung Veterans General Hospital, Taichung, Taiwan.,Dementia Center, Taichung Veterans General Hospital, Taichung, Taiwan.,School of Medicine, National Yang-Ming Chiao Tung University, Taipei, Taiwan
| | - Po-Lin Chen
- Department of Neurology, Neurological Institute, Taichung Veterans General Hospital, Taichung, Taiwan.,School of Medicine, National Yang-Ming Chiao Tung University, Taipei, Taiwan
| | - Jun-Peng Chen
- Biostatistics Task Force of Taichung Veterans General Hospital, Taichung, Taiwan
| | - Hung-Chieh Chen
- Division of Neuroradiology, Department of Radiology, Taichung Veterans General Hospital, Taichung, Taiwan.,School of Medicine, National Yang-Ming Chiao Tung University, Taipei, Taiwan
| | - Ting-Bin Chen
- Department of Neurology, Neurological Institute, Taichung Veterans General Hospital, Taichung, Taiwan.,Dementia Center, Taichung Veterans General Hospital, Taichung, Taiwan.,Department of Applied Cosmetology, Hungkuang University, Taichung, Taiwan
| |
Collapse
|