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Valdés Hernández MDC, Armitage PA, Thrippleton MJ, Chappell F, Sandeman E, Muñoz Maniega S, Shuler K, Wardlaw JM. Rationale, design and methodology of the image analysis protocol for studies of patients with cerebral small vessel disease and mild stroke. Brain Behav 2015; 5:e00415. [PMID: 26807340 PMCID: PMC4714639 DOI: 10.1002/brb3.415] [Citation(s) in RCA: 51] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/28/2015] [Accepted: 10/16/2015] [Indexed: 01/25/2023] Open
Abstract
RATIONALE Cerebral small vessel disease (SVD) is common in ageing and patients with dementia and stroke. Its manifestations on magnetic resonance imaging (MRI) include white matter hyperintensities, lacunes, microbleeds, perivascular spaces, small subcortical infarcts, and brain atrophy. Many studies focus only on one of these manifestations. A protocol for the differential assessment of all these features is, therefore, needed. AIMS To identify ways of quantifying imaging markers in research of patients with SVD and operationalize the recommendations from the STandards for ReportIng Vascular changes on nEuroimaging guidelines. Here, we report the rationale, design, and methodology of a brain image analysis protocol based on our experience from observational longitudinal studies of patients with nondisabling stroke. DESIGN The MRI analysis protocol is designed to provide quantitative and qualitative measures of disease evolution including: acute and old stroke lesions, lacunes, tissue loss due to stroke, perivascular spaces, microbleeds, macrohemorrhages, iron deposition in basal ganglia, substantia nigra and brain stem, brain atrophy, and white matter hyperintensities, with the latter separated into intense and less intense. Quantitative measures of tissue integrity such as diffusion fractional anisotropy, mean diffusivity, and the longitudinal relaxation time are assessed in regions of interest manually placed in anatomically and functionally relevant locations, and in others derived from feature extraction pipelines and tissue segmentation methods. Morphological changes that relate to cognitive deficits after stroke, analyzed through shape models of subcortical structures, complete the multiparametric image analysis protocol. OUTCOMES Final outcomes include guidance for identifying ways to minimize bias and confounds in the assessment of SVD and stroke imaging biomarkers. It is intended that this information will inform the design of studies to examine the underlying pathophysiology of SVD and stroke, and to provide reliable, quantitative outcomes in trials of new therapies and preventative strategies.
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Affiliation(s)
| | - Paul A Armitage
- Department of Cardiovascular Sciences University of Sheffield Sheffield UK
| | - Michael J Thrippleton
- Department of Neuroimaging Sciences Centre for Clinical Brain Sciences University of Edinburgh Edinburgh UK
| | - Francesca Chappell
- Department of Neuroimaging Sciences Centre for Clinical Brain Sciences University of Edinburgh Edinburgh UK
| | - Elaine Sandeman
- Department of Neuroimaging Sciences Centre for Clinical Brain Sciences University of Edinburgh Edinburgh UK
| | - Susana Muñoz Maniega
- Department of Neuroimaging Sciences Centre for Clinical Brain Sciences University of Edinburgh Edinburgh UK
| | - Kirsten Shuler
- Department of Neuroimaging Sciences Centre for Clinical Brain Sciences University of Edinburgh Edinburgh UK
| | - Joanna M Wardlaw
- Department of Neuroimaging Sciences Centre for Clinical Brain Sciences University of Edinburgh Edinburgh UK
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Adams HHH, Hilal S, Schwingenschuh P, Wittfeld K, van der Lee SJ, DeCarli C, Vernooij MW, Katschnig-Winter P, Habes M, Chen C, Seshadri S, van Duijn CM, Ikram MK, Grabe HJ, Schmidt R, Ikram MA. A priori collaboration in population imaging: The Uniform Neuro-Imaging of Virchow-Robin Spaces Enlargement consortium. ALZHEIMER'S & DEMENTIA: DIAGNOSIS, ASSESSMENT & DISEASE MONITORING 2015; 1:513-20. [PMID: 27239529 PMCID: PMC4879491 DOI: 10.1016/j.dadm.2015.10.004] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Introduction Virchow-Robin spaces (VRS), or perivascular spaces, are compartments of interstitial fluid enclosing cerebral blood vessels and are potential imaging markers of various underlying brain pathologies. Despite a growing interest in the study of enlarged VRS, the heterogeneity in rating and quantification methods combined with small sample sizes have so far hampered advancement in the field. Methods The Uniform Neuro-Imaging of Virchow-Robin Spaces Enlargement (UNIVRSE) consortium was established with primary aims to harmonize rating and analysis (www.uconsortium.org). The UNIVRSE consortium brings together 13 (sub)cohorts from five countries, totaling 16,000 subjects and over 25,000 scans. Eight different magnetic resonance imaging protocols were used in the consortium. Results VRS rating was harmonized using a validated protocol that was developed by the two founding members, with high reliability independent of scanner type, rater experience, or concomitant brain pathology. Initial analyses revealed risk factors for enlarged VRS including increased age, sex, high blood pressure, brain infarcts, and white matter lesions, but this varied by brain region. Discussion Early collaborative efforts between cohort studies with respect to data harmonization and joint analyses can advance the field of population (neuro)imaging. The UNIVRSE consortium will focus efforts on other potential correlates of enlarged VRS, including genetics, cognition, stroke, and dementia.
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Affiliation(s)
- Hieab H H Adams
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands; Department of Radiology, Erasmus MC, Rotterdam, The Netherlands
| | - Saima Hilal
- Department of Ophthalmology, National University of Singapore, Singapore; Memory Aging and Cognition Center, National University Health System, Singapore
| | | | - Katharina Wittfeld
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/ Greifswald, Greifswald, Germany
| | - Sven J van der Lee
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - Charles DeCarli
- Imaging of Dementia and Aging (IDeA) Laboratory, Department of Neurology and Center for Neuroscience, University of California at Davis, Davis, CA, USA
| | - Meike W Vernooij
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands; Department of Radiology, Erasmus MC, Rotterdam, The Netherlands
| | | | - Mohamad Habes
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany; Section of Biomedical Image Analysis, Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Christopher Chen
- Memory Aging and Cognition Center, National University Health System, Singapore
| | - Sudha Seshadri
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA; Framingham Heart Study, Framingham, MA, USA
| | - Cornelia M van Duijn
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - M Kamran Ikram
- Department of Ophthalmology, National University of Singapore, Singapore; Memory Aging and Cognition Center, National University Health System, Singapore
| | - Hans J Grabe
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/ Greifswald, Greifswald, Germany; Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Reinhold Schmidt
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands; Department of Radiology, Erasmus MC, Rotterdam, The Netherlands; Department of Neurology, Erasmus MC, Rotterdam, The Netherlands
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Cai K, Tain R, Das S, Damen FC, Sui Y, Valyi-Nagy T, Elliott MA, Zhou XJ. The feasibility of quantitative MRI of perivascular spaces at 7T. J Neurosci Methods 2015; 256:151-6. [PMID: 26358620 DOI: 10.1016/j.jneumeth.2015.09.001] [Citation(s) in RCA: 50] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2015] [Revised: 08/05/2015] [Accepted: 09/01/2015] [Indexed: 01/05/2023]
Abstract
BACKGROUND Dilated brain perivascular spaces (PVSs) are found to be associated with many conditions, including aging, dementia, and Alzheimer's disease (AD). Conventionally, PVS assessment is mainly based on subjective observations of the number, size and shape of PVSs in MR images collected at clinical field strengths (≤3T). This study tests the feasibility of imaging and quantifying brain PVS with an ultra-high 7T whole-body MRI scanner. NEW METHOD 3D high resolution T2-weighted brain images from healthy subjects (n=3) and AD patients (n=5) were acquired on a 7T whole-body MRI scanner. To automatically segment the small hyperintensive fluid-filling PVS structures, we also developed a quantitative program based on algorithms for spatial gradient, component connectivity, edge-detection, k-means clustering, etc., producing quantitative results of white matter PVS volume densities. RESULTS The 3D maps of automatically segmented PVS show an apparent increase in PVS density in AD patients compared to age-matched healthy controls due to the PVS dilation (8.0±2.1 v/v% in AD vs. 4.9±1.3 v/v% in controls, p<0.05). COMPARISON WITH EXISTING METHOD We demonstrated that 7T provides sufficient SNR and resolution for quantitatively measuring PVSs in deep white matter that is challenging with clinical MRI systems (≤3T). Compared to the conventional visual counting and rating for the PVS assessment, the quantitation method we developed is automatic and objective. CONCLUSIONS Quantitative PVS MRI at 7T may serve as a non-invasive and endogenous imaging biomarker for diseases with PVS dilation.
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Affiliation(s)
- Kejia Cai
- Department of Radiology, College of Medicine, University of Illinois at Chicago, Chicago, IL, USA; Center for MR Research, College of Medicine, University of Illinois at Chicago, Chicago, IL, USA.
| | - Rongwen Tain
- Department of Radiology, College of Medicine, University of Illinois at Chicago, Chicago, IL, USA; Center for MR Research, College of Medicine, University of Illinois at Chicago, Chicago, IL, USA
| | - Sandhitsu Das
- Department of Radiology, School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Frederick C Damen
- Department of Radiology, College of Medicine, University of Illinois at Chicago, Chicago, IL, USA; Center for MR Research, College of Medicine, University of Illinois at Chicago, Chicago, IL, USA
| | - Yi Sui
- Center for MR Research, College of Medicine, University of Illinois at Chicago, Chicago, IL, USA; Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, USA
| | - Tibor Valyi-Nagy
- Department of Neuropathology, College of Medicine, University of Illinois at Chicago, Chicago, IL, USA
| | - Mark A Elliott
- Department of Radiology, School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Xiaohong J Zhou
- Department of Radiology, College of Medicine, University of Illinois at Chicago, Chicago, IL, USA; Center for MR Research, College of Medicine, University of Illinois at Chicago, Chicago, IL, USA
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Wardlaw JM, Valdés Hernández MC, Muñoz-Maniega S. What are white matter hyperintensities made of? Relevance to vascular cognitive impairment. J Am Heart Assoc 2015; 4:001140. [PMID: 26104658 PMCID: PMC4599520 DOI: 10.1161/jaha.114.001140] [Citation(s) in RCA: 521] [Impact Index Per Article: 57.9] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Affiliation(s)
- Joanna M Wardlaw
- Division of Neuroimaging Sciences and Brain Research Imaging Centre, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom (J.M.W., M.C.V.H., S.M.M.)
| | - Maria C Valdés Hernández
- Division of Neuroimaging Sciences and Brain Research Imaging Centre, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom (J.M.W., M.C.V.H., S.M.M.)
| | - Susana Muñoz-Maniega
- Division of Neuroimaging Sciences and Brain Research Imaging Centre, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom (J.M.W., M.C.V.H., S.M.M.)
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Potter GM, Chappell FM, Morris Z, Wardlaw JM. Cerebral perivascular spaces visible on magnetic resonance imaging: development of a qualitative rating scale and its observer reliability. Cerebrovasc Dis 2015; 39:224-31. [PMID: 25823458 PMCID: PMC4386144 DOI: 10.1159/000375153] [Citation(s) in RCA: 282] [Impact Index Per Article: 31.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2014] [Accepted: 01/12/2015] [Indexed: 11/19/2022] Open
Abstract
Background Perivascular spaces (PVS) are an important component of cerebral small vessel disease (SVD), several inflammatory disorders, hypertension and blood-brain barrier breakdown, but are difficult to quantify. A recent international collaboration of SVD experts has highlighted the need for a robust, easy-to-use PVS rating scale for the effective investigation of the diagnostic and prognostic significance of PVS. The purpose of the current study was to develop and extend existing PVS scales to provide a more comprehensive scale for the measurement of PVS in the basal ganglia, centrum semiovale and midbrain, and to test its intra- and inter-rater agreement, assessing reasons for discrepancy. Methods We reviewed previously published PVS scales, including site of PVS assessed, rating method, and size and morphological criteria. Retaining key features, we devised a more comprehensive scale in order to improve the reliability of PVS rating. Two neuroradiologists tested the new scale in MRI brain scans of 60 patients from two studies (stroke, ageing population), chosen to represent a full range of PVS, and demonstrating concomitant features of SVD such as lacunes and white matter hyperintensities. We rated basal ganglia, centrum semiovale, and midbrain PVS. Basal ganglia and centrum semiovale PVS were rated 0 (none), 1 (1–10), 2 (11–20), 3 (21–40) and 4 (>40), and midbrain PVS were rated 0 (none visible) or 1 (visible). We calculated kappa statistics for rating, assessed consistency in use of PVS categories (Bhapkar test) and reviewed sources of discrepancy. Results Intra- and inter-rater kappa statistics were highest for basal ganglia PVS (range 0.76–0.87 and 0.8–0.9, respectively) than for centrum semiovale PVS (range 0.68–0.75 and 0.61–0.8, respectively) or midbrain PVS (inter-rater range 0.51–0.52). Inter-rater consistency was better for basal ganglia compared to centrum semiovale PVS (Bhapkar statistic 2.49–3.72, compared to 6.79–21.08, respectively). Most inter-rater disagreements were due to very faint PVS, coexisting extensive white matter hyperintensities (WMH) or the presence of lacunes. Conclusions We developed a more inclusive and robust visual PVS rating scale allowing rating of all grades of PVS severity on structural brain imaging. The revised PVS rating scale has good observer reliability for basal ganglia and centrum semiovale PVS, best for basal ganglia PVS, and moderate reliability for midbrain PVS. Agreement is influenced by PVS severity and the presence of background features of SVD. The current scale can be used in further studies to assess the clinical implications of PVS.
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Affiliation(s)
- Gillian M Potter
- Brain Imaging Research Centre, University of Edinburgh, Edinburgh, UK
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Large anterior temporal Virchow-Robin spaces: unique MR imaging features. Neuroradiology 2015; 57:491-9. [DOI: 10.1007/s00234-015-1491-y] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2014] [Accepted: 01/07/2015] [Indexed: 11/26/2022]
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Visualization of Perivascular Spaces and Perforating Arteries With 7 T Magnetic Resonance Imaging. Invest Radiol 2014; 49:307-13. [DOI: 10.1097/rli.0000000000000027] [Citation(s) in RCA: 72] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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