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Waymont JMJ, Valdés Hernández MDC, Bernal J, Duarte Coello R, Brown R, Chappell FM, Ballerini L, Wardlaw JM. Systematic review and meta-analysis of automated methods for quantifying enlarged perivascular spaces in the brain. Neuroimage 2024; 297:120685. [PMID: 38914212 DOI: 10.1016/j.neuroimage.2024.120685] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Revised: 05/20/2024] [Accepted: 06/10/2024] [Indexed: 06/26/2024] Open
Abstract
Research into magnetic resonance imaging (MRI)-visible perivascular spaces (PVS) has recently increased, as results from studies in different diseases and populations are cementing their association with sleep, disease phenotypes, and overall health indicators. With the establishment of worldwide consortia and the availability of large databases, computational methods that allow to automatically process all this wealth of information are becoming increasingly relevant. Several computational approaches have been proposed to assess PVS from MRI, and efforts have been made to summarise and appraise the most widely applied ones. We systematically reviewed and meta-analysed all publications available up to September 2023 describing the development, improvement, or application of computational PVS quantification methods from MRI. We analysed 67 approaches and 60 applications of their implementation, from 112 publications. The two most widely applied were the use of a morphological filter to enhance PVS-like structures, with Frangi being the choice preferred by most, and the use of a U-Net configuration with or without residual connections. Older adults or population studies comprising adults from 18 years old onwards were, overall, more frequent than studies using clinical samples. PVS were mainly assessed from T2-weighted MRI acquired in 1.5T and/or 3T scanners, although combinations using it with T1-weighted and FLAIR images were also abundant. Common associations researched included age, sex, hypertension, diabetes, white matter hyperintensities, sleep and cognition, with occupation-related, ethnicity, and genetic/hereditable traits being also explored. Despite promising improvements to overcome barriers such as noise and differentiation from other confounds, a need for joined efforts for a wider testing and increasing availability of the most promising methods is now paramount.
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Affiliation(s)
- Jennifer M J Waymont
- Centre for Clinical Brain Sciences, the University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK; UK Dementia Research Institute Centre at the University of Edinburgh, UK
| | - Maria Del C Valdés Hernández
- Centre for Clinical Brain Sciences, the University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK; UK Dementia Research Institute Centre at the University of Edinburgh, UK.
| | - José Bernal
- Centre for Clinical Brain Sciences, the University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK; UK Dementia Research Institute Centre at the University of Edinburgh, UK; German Centre for Neurodegenerative Diseases (DZNE), Germany; Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke University Magdeburg, Germany
| | - Roberto Duarte Coello
- Centre for Clinical Brain Sciences, the University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK; UK Dementia Research Institute Centre at the University of Edinburgh, UK
| | - Rosalind Brown
- Centre for Clinical Brain Sciences, the University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK; UK Dementia Research Institute Centre at the University of Edinburgh, UK
| | - Francesca M Chappell
- Centre for Clinical Brain Sciences, the University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK; UK Dementia Research Institute Centre at the University of Edinburgh, UK
| | | | - Joanna M Wardlaw
- Centre for Clinical Brain Sciences, the University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK; UK Dementia Research Institute Centre at the University of Edinburgh, UK
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Duarte Coello R, Valdés Hernández MDC, Zwanenburg JJM, van der Velden M, Kuijf HJ, De Luca A, Moyano JB, Ballerini L, Chappell FM, Brown R, Jan Biessels G, Wardlaw JM. Detectability and accuracy of computational measurements of in-silico and physical representations of enlarged perivascular spaces from magnetic resonance images. J Neurosci Methods 2024; 403:110039. [PMID: 38128784 DOI: 10.1016/j.jneumeth.2023.110039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 11/27/2023] [Accepted: 12/17/2023] [Indexed: 12/23/2023]
Abstract
BACKGROUND Magnetic Resonance Imaging (MRI) visible perivascular spaces (PVS) have been associated with age, decline in cognitive abilities, interrupted sleep, and markers of small vessel disease. But the limits of validity of their quantification have not been established. NEW METHOD We use a purpose-built digital reference object to construct an in-silico phantom for addressing this need, and validate it using a physical phantom. We use cylinders of different sizes as models for PVS. We also evaluate the influence of 'PVS' orientation, and different sets of parameters of the two vesselness filters that have been used for enhancing tubular structures, namely Frangi and RORPO filters, in the measurements' accuracy. RESULTS PVS measurements in MRI are only a proxy of their true dimensions, as the boundaries of their representation are consistently overestimated. The success in the use of the Frangi filter relies on a careful tuning of several parameters. Alpha= 0.5, beta= 0.5 and c= 500 yielded the best results. RORPO does not have these requirements and allows detecting smaller cylinders in their entirety more consistently in the absence of noise and confounding artefacts. The Frangi filter seems to be best suited for voxel sizes equal or larger than 0.4 mm-isotropic and cylinders larger than 1 mm diameter and 2 mm length. 'PVS' orientation did not affect measurements in data with isotropic voxels. COMPARISON WITH EXISTENT METHODS Does not apply. CONCLUSIONS The in-silico and physical phantoms presented are useful for establishing the validity of quantification methods of tubular small structures.
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Affiliation(s)
- Roberto Duarte Coello
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| | - Maria Del C Valdés Hernández
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK.
| | | | | | - Hugo J Kuijf
- Image Sciences Institute, UMC Utrecht, Utrecht, Netherlands
| | | | - José Bernal Moyano
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK; German Centre for Neurodegenerative Diseases, Magdeburg, Germany; Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke University Magdeburg, Magdeburg, Germany
| | - Lucia Ballerini
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK; University for Foreigner of Perugia, Perugia, Italy
| | - Francesca M Chappell
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| | - Rosalind Brown
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| | | | - Joanna M Wardlaw
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
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Valdés Hernández MDC, Duarte Coello R, Xu W, Bernal J, Cheng Y, Ballerini L, Wiseman SJ, Chappell FM, Clancy U, Jaime García D, Arteaga Reyes C, Zhang JF, Liu X, Hewins W, Stringer M, Doubal F, Thrippleton MJ, Jochems A, Brown R, Wardlaw JM. Influence of threshold selection and image sequence in in-vivo segmentation of enlarged perivascular spaces. J Neurosci Methods 2024; 403:110037. [PMID: 38154663 DOI: 10.1016/j.jneumeth.2023.110037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Revised: 12/06/2023] [Accepted: 12/17/2023] [Indexed: 12/30/2023]
Abstract
BACKGROUND Growing interest surrounds perivascular spaces (PVS) as a clinical biomarker of brain dysfunction given their association with cerebrovascular risk factors and disease. Neuroimaging techniques allowing quick and reliable quantification are being developed, but, in practice, they require optimisation as their limits of validity are usually unspecified. NEW METHOD We evaluate modifications and alternatives to a state-of-the-art (SOTA) PVS segmentation method that uses a vesselness filter to enhance PVS discrimination, followed by thresholding of its response, applied to brain magnetic resonance images (MRI) from patients with sporadic small vessel disease acquired at 3 T. RESULTS The method is robust against inter-observer differences in threshold selection, but separate thresholds for each region of interest (i.e., basal ganglia, centrum semiovale, and midbrain) are required. Noise needs to be assessed prior to selecting these thresholds, as effect of noise and imaging artefacts can be mitigated with a careful optimisation of these thresholds. PVS segmentation from T1-weighted images alone, misses small PVS, therefore, underestimates PVS count, may overestimate individual PVS volume especially in the basal ganglia, and is susceptible to the inclusion of calcified vessels and mineral deposits. Visual analyses indicated the incomplete and fragmented detection of long and thin PVS as the primary cause of errors, with the Frangi filter coping better than the Jerman filter. COMPARISON WITH EXISTING METHODS Limits of validity to a SOTA PVS segmentation method applied to 3 T MRI with confounding pathology are given. CONCLUSIONS Evidence presented reinforces the STRIVE-2 recommendation of using T2-weighted images for PVS assessment wherever possible. The Frangi filter is recommended for PVS segmentation from MRI, offering robust output against variations in threshold selection and pathology presentation.
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Affiliation(s)
- Maria Del C Valdés Hernández
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK.
| | - Roberto Duarte Coello
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| | - William Xu
- College of Medicine and Veterinary Medicine, University of Edinburgh, Edinburgh, UK
| | - José Bernal
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK; German Centre for Neurodegenerative Diseases (DZNE), Magdeburg, Germany; Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke University Magdeburg, Magdeburg, Germany
| | - Yajun Cheng
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, China
| | - Lucia Ballerini
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK; University for Foreigner of Perugia, Perugia, Italy
| | - Stewart J Wiseman
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| | - Francesca M Chappell
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| | - Una Clancy
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| | - Daniela Jaime García
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| | - Carmen Arteaga Reyes
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| | - Jun-Fang Zhang
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK; Department of Neurology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiaodi Liu
- Division of Neurology, Department of Medicine, The University of Hong Kong, Hong Kong
| | - Will Hewins
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| | - Michael Stringer
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| | - Fergus Doubal
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| | - Michael J Thrippleton
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| | - Angela Jochems
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| | - Rosalind Brown
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| | - Joanna M Wardlaw
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
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Seehafer S, Larsen N, Aludin S, Jansen O, Schmill LPA. Perivascular spaces and where to find them - MR imaging and evaluation methods. ROFO-FORTSCHR RONTG 2024. [PMID: 38408476 DOI: 10.1055/a-2254-5651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/28/2024]
Abstract
BACKGROUND Perivascular spaces (synonym: Virchow-Robin spaces) were first described over 150 years ago. They are defined as the fluid-filled spaces surrounding the small penetrating cerebral vessels. They gained growing scientific interest especially with the postulation of the so-called glymphatic system and their possible role in neurodegenerative and neuroinflammatory diseases. METHODS PubMed was used for a systematic search with a focus on literature regarding MRI imaging and evaluation methods of perivascular spaces. Studies on human in-vivo imaging were included with a focus on studies involving healthy populations. No time frame was set. The nomenclature in the literature is very heterogeneous with terms like "large", "dilated", "enlarged" perivascular spaces whereas borders and definitions often remain unclear. This work generally talks about perivascular spaces. RESULTS This review article discusses the morphologic MRI characteristics in different sequences. With the continual improvement of image quality, more and tinier structures can be depicted in detail. Visual analysis and semi or fully automated segmentation methods are briefly discussed. CONCLUSION If they are looked for, perivascular spaces are apparent in basically every cranial MRI examination. Their physiologic or pathologic value is still under debate. KEY POINTS · Perivascular spaces can be seen in basically every cranial MRI examination.. · Primarily T2-weighend sequences are used for visual analysis. Additional sequences are helpful for distinction from their differential diagnoses.. · There are promising approaches for the semi or fully automated segmentation of perivascular spaces with the possibility to collect more quantitative parameters.. CITATION FORMAT · Seehafer S, Larsen N, Aludin S et al. Perivascular spaces and where to find them - MRI imaging and evaluation methods. Fortschr Röntgenstr 2024; DOI: 10.1055/a-2254-5651.
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Affiliation(s)
- Svea Seehafer
- Clinic for Radiology and Neuroradiology, University Hospital Schleswig-Holstein - Campus Kiel, Germany
| | - Naomi Larsen
- Clinic for Radiology and Neuroradiology, University Hospital Schleswig-Holstein - Campus Kiel, Germany
| | - Schekeb Aludin
- Clinic for Radiology and Neuroradiology, University Hospital Schleswig-Holstein - Campus Kiel, Germany
| | - Olav Jansen
- Clinic for Radiology and Neuroradiology, University Hospital Schleswig-Holstein - Campus Kiel, Germany
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Agarwal N, Lewis LD, Hirschler L, Rivera LR, Naganawa S, Levendovszky SR, Ringstad G, Klarica M, Wardlaw J, Iadecola C, Hawkes C, Octavia Carare R, Wells J, Bakker EN, Kurtcuoglu V, Bilston L, Nedergaard M, Mori Y, Stoodley M, Alperin N, de Leon M, van Osch MJ. Current Understanding of the Anatomy, Physiology, and Magnetic Resonance Imaging of Neurofluids: Update From the 2022 "ISMRM Imaging Neurofluids Study group" Workshop in Rome. J Magn Reson Imaging 2024; 59:431-449. [PMID: 37141288 PMCID: PMC10624651 DOI: 10.1002/jmri.28759] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 04/18/2023] [Accepted: 04/18/2023] [Indexed: 05/05/2023] Open
Abstract
Neurofluids is a term introduced to define all fluids in the brain and spine such as blood, cerebrospinal fluid, and interstitial fluid. Neuroscientists in the past millennium have steadily identified the several different fluid environments in the brain and spine that interact in a synchronized harmonious manner to assure a healthy microenvironment required for optimal neuroglial function. Neuroanatomists and biochemists have provided an incredible wealth of evidence revealing the anatomy of perivascular spaces, meninges and glia and their role in drainage of neuronal waste products. Human studies have been limited due to the restricted availability of noninvasive imaging modalities that can provide a high spatiotemporal depiction of the brain neurofluids. Therefore, animal studies have been key in advancing our knowledge of the temporal and spatial dynamics of fluids, for example, by injecting tracers with different molecular weights. Such studies have sparked interest to identify possible disruptions to neurofluids dynamics in human diseases such as small vessel disease, cerebral amyloid angiopathy, and dementia. However, key differences between rodent and human physiology should be considered when extrapolating these findings to understand the human brain. An increasing armamentarium of noninvasive MRI techniques is being built to identify markers of altered drainage pathways. During the three-day workshop organized by the International Society of Magnetic Resonance in Medicine that was held in Rome in September 2022, several of these concepts were discussed by a distinguished international faculty to lay the basis of what is known and where we still lack evidence. We envision that in the next decade, MRI will allow imaging of the physiology of neurofluid dynamics and drainage pathways in the human brain to identify true pathological processes underlying disease and to discover new avenues for early diagnoses and treatments including drug delivery. Evidence level: 1 Technical Efficacy: Stage 3.
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Affiliation(s)
- Nivedita Agarwal
- Neuroradiology Unit, Scientific Institute IRCCS E. Medea, Bosisio Parini, Italy
| | - Laura D. Lewis
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, Massachusetts, USA
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Lydiane Hirschler
- C.J. Gorter MRI Center, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Leonardo Rivera Rivera
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Shinji Naganawa
- Department of Radiology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | | | - Geir Ringstad
- Department of Radiology, Oslo University Hospital Rikshospitalet, Oslo, Norway
- Department of Geriatrics and Internal Medicine, Sorlandet Hospital, Arendal, Norway
| | - Marijan Klarica
- Department of Pharmacology and Croatian Institute of Brain Research, University of Zagreb School of Medicine, Zagreb, Croatia
| | - Joanna Wardlaw
- Centre for Clinical Brain Sciences and UK Dementia Research Institute Centre, University of Edinburgh, Edinburgh, UK
| | - Costantino Iadecola
- Department of Pharmacology and Croatian Institute of Brain Research, University of Zagreb School of Medicine, Zagreb, Croatia
| | - Cheryl Hawkes
- Biomedical and Life Sciences, Lancaster University, Lancaster, UK
| | | | - Jack Wells
- UCL Centre for Advanced Biomedical Imaging, University College of London, London, UK
| | - Erik N.T.P. Bakker
- Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, The Netherlands
| | | | - Lynne Bilston
- Neuroscience Research Australia and UNSW Medicine, Sydney, Australia
| | - Maiken Nedergaard
- Center for Translational Neuromedicine, University of Rochester Medical Center, Rochester, New York, USA
- Center for Translational Neuromedicine, University of Copenhagen, Copenhagen, Denmark
| | - Yuki Mori
- Center for Translational Neuromedicine, University of Copenhagen, Copenhagen, Denmark
| | - Marcus Stoodley
- Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, Australia
- Department of Neurosurgery, Macquarie University Hospital, Sydney, Australia
| | - Noam Alperin
- Department of Radiology and Biomedical Engineering, Miller School of Medicine, University of Miami, Miami, Florida, USA
| | - Mony de Leon
- Weil Cornell Medicine, Department of Radiology, Brain Health Imaging Institute, New York City, New York, USA
| | - Matthias J.P. van Osch
- C.J. Gorter MRI Center, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
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Bernal J, Schreiber S, Menze I, Ostendorf A, Pfister M, Geisendörfer J, Nemali A, Maass A, Yakupov R, Peters O, Preis L, Schneider L, Herrera AL, Priller J, Spruth EJ, Altenstein S, Schneider A, Fliessbach K, Wiltfang J, Schott BH, Rostamzadeh A, Glanz W, Buerger K, Janowitz D, Ewers M, Perneczky R, Rauchmann BS, Teipel S, Kilimann I, Laske C, Munk MH, Spottke A, Roy N, Dobisch L, Dechent P, Scheffler K, Hetzer S, Wolfsgruber S, Kleineidam L, Schmid M, Berger M, Jessen F, Wirth M, Düzel E, Ziegler G. Arterial hypertension and β-amyloid accumulation have spatially overlapping effects on posterior white matter hyperintensity volume: a cross-sectional study. Alzheimers Res Ther 2023; 15:97. [PMID: 37226207 DOI: 10.1186/s13195-023-01243-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Accepted: 05/09/2023] [Indexed: 05/26/2023]
Abstract
BACKGROUND White matter hyperintensities (WMH) in subjects across the Alzheimer's disease (AD) spectrum with minimal vascular pathology suggests that amyloid pathology-not just arterial hypertension-impacts WMH, which in turn adversely influences cognition. Here we seek to determine the effect of both hypertension and Aβ positivity on WMH, and their impact on cognition. METHODS We analysed data from subjects with a low vascular profile and normal cognition (NC), subjective cognitive decline (SCD), and amnestic mild cognitive impairment (MCI) enrolled in the ongoing observational multicentre DZNE Longitudinal Cognitive Impairment and Dementia Study (n = 375, median age 70.0 [IQR 66.0, 74.4] years; 178 female; NC/SCD/MCI 127/162/86). All subjects underwent a rich neuropsychological assessment. We focused on baseline memory and executive function-derived from multiple neuropsychological tests using confirmatory factor analysis-, baseline preclinical Alzheimer's cognitive composite 5 (PACC5) scores, and changes in PACC5 scores over the course of three years (ΔPACC5). RESULTS Subjects with hypertension or Aβ positivity presented the largest WMH volumes (pFDR < 0.05), with spatial overlap in the frontal (hypertension: 0.42 ± 0.17; Aβ: 0.46 ± 0.18), occipital (hypertension: 0.50 ± 0.16; Aβ: 0.50 ± 0.16), parietal lobes (hypertension: 0.57 ± 0.18; Aβ: 0.56 ± 0.20), corona radiata (hypertension: 0.45 ± 0.17; Aβ: 0.40 ± 0.13), optic radiation (hypertension: 0.39 ± 0.18; Aβ: 0.74 ± 0.19), and splenium of the corpus callosum (hypertension: 0.36 ± 0.12; Aβ: 0.28 ± 0.12). Elevated global and regional WMH volumes coincided with worse cognitive performance at baseline and over 3 years (pFDR < 0.05). Aβ positivity was negatively associated with cognitive performance (direct effect-memory: - 0.33 ± 0.08, pFDR < 0.001; executive: - 0.21 ± 0.08, pFDR < 0.001; PACC5: - 0.29 ± 0.09, pFDR = 0.006; ΔPACC5: - 0.34 ± 0.04, pFDR < 0.05). Splenial WMH mediated the relationship between hypertension and cognitive performance (indirect-only effect-memory: - 0.05 ± 0.02, pFDR = 0.029; executive: - 0.04 ± 0.02, pFDR = 0.067; PACC5: - 0.05 ± 0.02, pFDR = 0.030; ΔPACC5: - 0.09 ± 0.03, pFDR = 0.043) and WMH in the optic radiation partially mediated that between Aβ positivity and memory (indirect effect-memory: - 0.05 ± 0.02, pFDR = 0.029). CONCLUSIONS Posterior white matter is susceptible to hypertension and Aβ accumulation. Posterior WMH mediate the association between these pathologies and cognitive dysfunction, making them a promising target to tackle the downstream damage related to the potentially interacting and potentiating effects of the two pathologies. TRIAL REGISTRATION German Clinical Trials Register (DRKS00007966, 04/05/2015).
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Affiliation(s)
- Jose Bernal
- Institute of Cognitive Neurology and Dementia Research, Otto-Von-Guericke University Magdeburg, Magdeburg, Germany.
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany.
| | - Stefanie Schreiber
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany
- Department of Neurology, Medical Faculty, University Hospital Magdeburg, Magdeburg, Germany
| | - Inga Menze
- Institute of Cognitive Neurology and Dementia Research, Otto-Von-Guericke University Magdeburg, Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany
| | - Anna Ostendorf
- Institute of Cognitive Neurology and Dementia Research, Otto-Von-Guericke University Magdeburg, Magdeburg, Germany
| | - Malte Pfister
- Department of Neurology, Medical Faculty, University Hospital Magdeburg, Magdeburg, Germany
| | - Jonas Geisendörfer
- Department of Neurology, Medical Faculty, University Hospital Magdeburg, Magdeburg, Germany
| | - Aditya Nemali
- Institute of Cognitive Neurology and Dementia Research, Otto-Von-Guericke University Magdeburg, Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany
| | - Anne Maass
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany
| | - Renat Yakupov
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany
| | - Oliver Peters
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität Zu Berlin-Institute of Psychiatry and Psychotherapy, Berlin, Germany
| | - Lukas Preis
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität Zu Berlin-Institute of Psychiatry and Psychotherapy, Berlin, Germany
| | - Luisa Schneider
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität Zu Berlin-Institute of Psychiatry and Psychotherapy, Berlin, Germany
| | - Ana Lucia Herrera
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität Zu Berlin-Institute of Psychiatry and Psychotherapy, Berlin, Germany
| | - Josef Priller
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Berlin, Germany
- School of Medicine, Department of Psychiatry and Psychotherapy, Technical University of Munich, Munich, Germany
- University of Edinburgh and UK DRI, Edinburgh, UK
| | - Eike Jakob Spruth
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Slawek Altenstein
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Anja Schneider
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Clinic for Neurodegenerative Diseases and Geriatric Psychiatry, University of Bonn, Bonn, Germany
| | - Klaus Fliessbach
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Clinic for Neurodegenerative Diseases and Geriatric Psychiatry, University of Bonn, Bonn, Germany
| | - Jens Wiltfang
- German Center for Neurodegenerative Diseases (DZNE), Goettingen, Germany
- Department of Psychiatry and Psychotherapy, University Medical Center Goettingen, University of Goettingen, Goettingen, Germany
- Neurosciences and Signaling Group, Institute of Biomedicine (iBiMED), Department of Medical Sciences, University of Aveiro, Aveiro, Portugal
| | - Björn H Schott
- German Center for Neurodegenerative Diseases (DZNE), Goettingen, Germany
- Department of Psychiatry and Psychotherapy, University Medical Center Goettingen, University of Goettingen, Goettingen, Germany
| | - Ayda Rostamzadeh
- Department of Psychiatry, University of Cologne, Cologne, Germany
| | - Wenzel Glanz
- Institute of Cognitive Neurology and Dementia Research, Otto-Von-Guericke University Magdeburg, Magdeburg, Germany
| | - Katharina Buerger
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Daniel Janowitz
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Michael Ewers
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Robert Perneczky
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy) Munich, Munich, Germany
- Ageing Epidemiology Research Unit (AGE), School of Public Health, Imperial College London, London, UK
- Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, UK
| | - Boris-Stephan Rauchmann
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Stefan Teipel
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany
- Department of Psychosomatic Medicine, Rostock University Medical Center, Rostock, Germany
| | - Ingo Kilimann
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany
- Department of Psychosomatic Medicine, Rostock University Medical Center, Rostock, Germany
| | - Christoph Laske
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
- Section for Dementia Research, Hertie Institute for Clinical Brain Research and Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Matthias H Munk
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
- Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Annika Spottke
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Clinic for Neurodegenerative Diseases and Geriatric Psychiatry, University of Bonn, Bonn, Germany
| | - Nina Roy
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Laura Dobisch
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany
| | - Peter Dechent
- MR-Research in Neurosciences, Department of Cognitive Neurology, Georg-August-University Goettingen, Göttingen, Germany
| | - Klaus Scheffler
- Department for Biomedical Magnetic Resonance, University of Tübingen, Tübingen, Germany
| | - Stefan Hetzer
- Berlin Center for Advanced Neuroimaging, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Steffen Wolfsgruber
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Clinic for Neurodegenerative Diseases and Geriatric Psychiatry, University of Bonn, Bonn, Germany
| | - Luca Kleineidam
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Clinic for Neurodegenerative Diseases and Geriatric Psychiatry, University of Bonn, Bonn, Germany
| | - Matthias Schmid
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Institute for Medical Biometry, Informatics and Epidemiology, University Hospital Bonn, Bonn, Germany
| | - Moritz Berger
- Institute for Medical Biometry, Informatics and Epidemiology, University Hospital Bonn, Bonn, Germany
| | - Frank Jessen
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Psychiatry, University of Cologne, Cologne, Germany
- Excellence Cluster On Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, Cologne, Germany
| | - Miranka Wirth
- German Center for Neurodegenerative Diseases (DZNE), Tatzberg 41, Dresden, 01307, Germany.
| | - Emrah Düzel
- Institute of Cognitive Neurology and Dementia Research, Otto-Von-Guericke University Magdeburg, Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany
- Institute of Cognitive Neuroscience, University College London, London, UK
| | - Gabriel Ziegler
- Institute of Cognitive Neurology and Dementia Research, Otto-Von-Guericke University Magdeburg, Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany
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7
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Schreiber S, Bernal J, Arndt P, Schreiber F, Müller P, Morton L, Braun-Dullaeus RC, Valdés-Hernández MDC, Duarte R, Wardlaw JM, Meuth SG, Mietzner G, Vielhaber S, Dunay IR, Dityatev A, Jandke S, Mattern H. Brain Vascular Health in ALS Is Mediated through Motor Cortex Microvascular Integrity. Cells 2023; 12:957. [PMID: 36980297 PMCID: PMC10047140 DOI: 10.3390/cells12060957] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 03/07/2023] [Accepted: 03/15/2023] [Indexed: 03/30/2023] Open
Abstract
Brain vascular health appears to be critical for preventing the development of amyotrophic lateral sclerosis (ALS) and slowing its progression. ALS patients often demonstrate cardiovascular risk factors and commonly suffer from cerebrovascular disease, with evidence of pathological alterations in their small cerebral blood vessels. Impaired vascular brain health has detrimental effects on motor neurons: vascular endothelial growth factor levels are lowered in ALS, which can compromise endothelial cell formation and the integrity of the blood-brain barrier. Increased turnover of neurovascular unit cells precedes their senescence, which, together with pericyte alterations, further fosters the failure of toxic metabolite removal. We here provide a comprehensive overview of the pathogenesis of impaired brain vascular health in ALS and how novel magnetic resonance imaging techniques can aid its detection. In particular, we discuss vascular patterns of blood supply to the motor cortex with the number of branches from the anterior and middle cerebral arteries acting as a novel marker of resistance and resilience against downstream effects of vascular risk and events in ALS. We outline how certain interventions adapted to patient needs and capabilities have the potential to mechanistically target the brain microvasculature towards favorable motor cortex blood supply patterns. Through this strategy, we aim to guide novel approaches to ALS management and a better understanding of ALS pathophysiology.
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Affiliation(s)
- Stefanie Schreiber
- Department of Neurology, Otto von Guericke University Magdeburg, Medical Faculty, 39120 Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE) within the Helmholtz Association, 39120 Magdeburg, Germany
- Center for Behavioral Brain Sciences (CBBS), 39106 Magdeburg, Germany
| | - Jose Bernal
- Department of Neurology, Otto von Guericke University Magdeburg, Medical Faculty, 39120 Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE) within the Helmholtz Association, 39120 Magdeburg, Germany
| | - Philipp Arndt
- Department of Neurology, Otto von Guericke University Magdeburg, Medical Faculty, 39120 Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE) within the Helmholtz Association, 39120 Magdeburg, Germany
| | - Frank Schreiber
- Department of Neurology, Otto von Guericke University Magdeburg, Medical Faculty, 39120 Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE) within the Helmholtz Association, 39120 Magdeburg, Germany
| | - Patrick Müller
- German Center for Neurodegenerative Diseases (DZNE) within the Helmholtz Association, 39120 Magdeburg, Germany
- Department of Internal Medicine/Cardiology and Angiology, Otto von Guericke University Magdeburg, 39120 Magdeburg, Germany
| | - Lorena Morton
- Institute of Inflammation and Neurodegeneration, Otto von Guericke University Magdeburg, 39120 Magdeburg, Germany
| | | | | | - Roberto Duarte
- Centre for Clinical Brain Sciences, The University of Edinburgh, UK Dementia Research Institute Centre, Edinburgh EH16 4UX, UK
| | - Joanna Marguerite Wardlaw
- Centre for Clinical Brain Sciences, The University of Edinburgh, UK Dementia Research Institute Centre, Edinburgh EH16 4UX, UK
| | - Sven Günther Meuth
- Department of Neurology, Medical Faculty, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
| | - Grazia Mietzner
- Department of Neurology, Otto von Guericke University Magdeburg, Medical Faculty, 39120 Magdeburg, Germany
| | - Stefan Vielhaber
- Department of Neurology, Otto von Guericke University Magdeburg, Medical Faculty, 39120 Magdeburg, Germany
- Center for Behavioral Brain Sciences (CBBS), 39106 Magdeburg, Germany
| | - Ildiko Rita Dunay
- Center for Behavioral Brain Sciences (CBBS), 39106 Magdeburg, Germany
- Institute of Inflammation and Neurodegeneration, Otto von Guericke University Magdeburg, 39120 Magdeburg, Germany
| | - Alexander Dityatev
- German Center for Neurodegenerative Diseases (DZNE) within the Helmholtz Association, 39120 Magdeburg, Germany
- Center for Behavioral Brain Sciences (CBBS), 39106 Magdeburg, Germany
- Medical Faculty, Otto von Guericke University, 39120 Magdeburg, Germany
| | - Solveig Jandke
- Department of Neurology, Otto von Guericke University Magdeburg, Medical Faculty, 39120 Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE) within the Helmholtz Association, 39120 Magdeburg, Germany
| | - Hendrik Mattern
- German Center for Neurodegenerative Diseases (DZNE) within the Helmholtz Association, 39120 Magdeburg, Germany
- Center for Behavioral Brain Sciences (CBBS), 39106 Magdeburg, Germany
- Department of Biomedical Magnetic Resonance, Faculty of Natural Sciences, Otto von Guericke University Magdeburg, 39120 Magdeburg, Germany
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8
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Pham W, Lynch M, Spitz G, O’Brien T, Vivash L, Sinclair B, Law M. A critical guide to the automated quantification of perivascular spaces in magnetic resonance imaging. Front Neurosci 2022; 16:1021311. [PMID: 36590285 PMCID: PMC9795229 DOI: 10.3389/fnins.2022.1021311] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Accepted: 11/16/2022] [Indexed: 12/15/2022] Open
Abstract
The glymphatic system is responsible for waste clearance in the brain. It is comprised of perivascular spaces (PVS) that surround penetrating blood vessels. These spaces are filled with cerebrospinal fluid and interstitial fluid, and can be seen with magnetic resonance imaging. Various algorithms have been developed to automatically label these spaces in MRI. This has enabled volumetric and morphological analyses of PVS in healthy and disease cohorts. However, there remain inconsistencies between PVS measures reported by different methods of automated segmentation. The present review emphasizes that importance of voxel-wise evaluation of model performance, mainly with the Sørensen Dice similarity coefficient. Conventional count correlations for model validation are inadequate if the goal is to assess volumetric or morphological measures of PVS. The downside of voxel-wise evaluation is that it requires manual segmentations that require large amounts of time to produce. One possible solution is to derive these semi-automatically. Additionally, recommendations are made to facilitate rigorous development and validation of automated PVS segmentation models. In the application of automated PVS segmentation tools, publication of image quality metrics, such as the contrast-to-noise ratio, alongside descriptive statistics of PVS volumes and counts will facilitate comparability between studies. Lastly, a head-to-head comparison between two algorithms, applied to two cohorts of astronauts reveals how results can differ substantially between techniques.
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Affiliation(s)
- William Pham
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia
| | - Miranda Lynch
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia
| | - Gershon Spitz
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia
- Monash-Epworth Rehabilitation Research Centre, Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, VIC, Australia
| | - Terence O’Brien
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia
- Department of Neurology, Alfred Hospital, Melbourne, VIC, Australia
- Department of Medicine, The Royal Melbourne Hospital, University of Melbourne, Melbourne, VIC, Australia
- Department of Neurology, The Royal Melbourne Hospital, University of Melbourne, Melbourne, VIC, Australia
| | - Lucy Vivash
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia
- Department of Neurology, Alfred Hospital, Melbourne, VIC, Australia
- Department of Medicine, The Royal Melbourne Hospital, University of Melbourne, Melbourne, VIC, Australia
- Department of Neurology, The Royal Melbourne Hospital, University of Melbourne, Melbourne, VIC, Australia
| | - Benjamin Sinclair
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia
- Department of Neurology, Alfred Hospital, Melbourne, VIC, Australia
- Department of Medicine, The Royal Melbourne Hospital, University of Melbourne, Melbourne, VIC, Australia
| | - Meng Law
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia
- Department of Radiology, Alfred Health Hospital, Melbourne, VIC, Australia
- Department of Electrical and Computer Systems Engineering, Monash University, Melbourne, VIC, Australia
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