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Dickie BR, Ahmed Z, Arvidsson J, Bell LC, Buckley DL, Debus C, Fedorov A, Floca R, Gutmann I, van der Heijden RA, van Houdt PJ, Sourbron S, Thrippleton MJ, Quarles C, Kompan IN. A community-endorsed open-source lexicon for contrast agent-based perfusion MRI: A consensus guidelines report from the ISMRM Open Science Initiative for Perfusion Imaging (OSIPI). Magn Reson Med 2024; 91:1761-1773. [PMID: 37831600 DOI: 10.1002/mrm.29840] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 07/25/2023] [Accepted: 08/04/2023] [Indexed: 10/15/2023]
Abstract
This manuscript describes the ISMRM OSIPI (Open Science Initiative for Perfusion Imaging) lexicon for dynamic contrast-enhanced and dynamic susceptibility-contrast MRI. The lexicon was developed by Taskforce 4.2 of OSIPI to provide standardized definitions of commonly used quantities, models, and analysis processes with the aim of reducing reporting variability. The taskforce was established in February 2020 and consists of medical physicists, engineers, clinicians, data and computer scientists, and DICOM (Digital Imaging and Communications in Medicine) standard experts. Members of the taskforce collaborated via a slack channel and quarterly virtual meetings. Members participated by defining lexicon items and reporting formats that were reviewed by at least two other members of the taskforce. Version 1.0.0 of the lexicon was subject to open review from the wider perfusion imaging community between January and March 2022, and endorsed by the Perfusion Study Group of the ISMRM in the summer of 2022. The initial scope of the lexicon was set by the taskforce and defined such that it contained a basic set of quantities, processes, and models to enable users to report an end-to-end analysis pipeline including kinetic model fitting. We also provide guidance on how to easily incorporate lexicon items and definitions into free-text descriptions (e.g., in manuscripts and other documentation) and introduce an XML-based pipeline encoding format to encode analyses using lexicon definitions in standardized and extensible machine-readable code. The lexicon is designed to be open-source and extendable, enabling ongoing expansion of its content. We hope that widespread adoption of lexicon terminology and reporting formats described herein will increase reproducibility within the field.
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Affiliation(s)
- Ben R Dickie
- Division of Informatics, Imaging, and Data Sciences, School of Health Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
- Geoffrey Jefferson Brain Research Center, Manchester Academic Health Science Center, The University of Manchester, Manchester, UK
| | - Zaki Ahmed
- Corewell Health William Beaumont University Hospital, Royal Oak, Michigan, USA
| | - Jonathan Arvidsson
- Department of Medical Radiation Sciences, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Laura C Bell
- Clinical Imaging Group, Genentech, Inc., South San Francisco, California, USA
| | | | | | - Andrey Fedorov
- Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Ralf Floca
- National Center for Radiation Research in Oncology, Heidelberg Institute for Radiation Oncology, Heidelberg, Germany
| | - Ingomar Gutmann
- Faculty of Physics, Physics of Functional Materials, University of Vienna, Vienna, Austria
| | - Rianne A van der Heijden
- Department of Radiology & Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Petra J van Houdt
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Steven Sourbron
- Department of Infection, Immunity, and Cardiovascular Diseases, University of Sheffield, Sheffield, UK
| | - Michael J Thrippleton
- Edinburgh Imaging and Center for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Chad Quarles
- Department of Cancer Systems Imaging, UT MD Anderson Cancer Center, Houston, Texas, USA
| | - Ina N Kompan
- Division of Medical Image Computing, German Cancer Research Center, Heidelberg, Germany
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van Houdt PJ, Ragunathan S, Berks M, Ahmed Z, Kershaw LE, Gurney-Champion OJ, Tadimalla S, Arvidsson J, Sun Y, Kallehauge J, Dickie B, Lévy S, Bell L, Sourbron S, Thrippleton MJ. Contrast-agent-based perfusion MRI code repository and testing framework: ISMRM Open Science Initiative for Perfusion Imaging (OSIPI). Magn Reson Med 2024; 91:1774-1786. [PMID: 37667526 DOI: 10.1002/mrm.29826] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 06/30/2023] [Accepted: 07/25/2023] [Indexed: 09/06/2023]
Abstract
PURPOSE Software has a substantial impact on quantitative perfusion MRI values. The lack of generally accepted implementations, code sharing and transparent testing reduces reproducibility, hindering the use of perfusion MRI in clinical trials. To address these issues, the ISMRM Open Science Initiative for Perfusion Imaging (OSIPI) aimed to establish a community-led, centralized repository for sharing open-source code for processing contrast-based perfusion imaging, incorporating an open-source testing framework. METHODS A repository was established on the OSIPI GitHub website. Python was chosen as the target software language. Calls for code contributions were made to OSIPI members, the ISMRM Perfusion Study Group, and publicly via OSIPI websites. An automated unit-testing framework was implemented to evaluate the output of code contributions, including visual representation of the results. RESULTS The repository hosts 86 implementations of perfusion processing steps contributed by 12 individuals or teams. These cover all core aspects of DCE- and DSC-MRI processing, including multiple implementations of the same functionality. Tests were developed for 52 implementations, covering five analysis steps. For T1 mapping, signal-to-concentration conversion and population AIF functions, different implementations resulted in near-identical output values. For the five pharmacokinetic models tested (Tofts, extended Tofts-Kety, Patlak, two-compartment exchange, and two-compartment uptake), differences in output parameters were observed between contributions. CONCLUSIONS The OSIPI DCE-DSC code repository represents a novel community-led model for code sharing and testing. The repository facilitates the re-use of existing code and the benchmarking of new code, promoting enhanced reproducibility in quantitative perfusion imaging.
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Affiliation(s)
- Petra J van Houdt
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | | | - Michael Berks
- Quantitative Biomedical Imaging Laboratory, Division of Cancer Sciences, The University of Manchester, Manchester, UK
| | - Zaki Ahmed
- Corewell Health William Beaumont University Hospital, Diagnostic Radiology, Royal Oak, USA
| | - Lucy E Kershaw
- Edinburgh Imaging and Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK
| | - Oliver J Gurney-Champion
- Department of Radiology and Nuclear Medicine, Amsterdam UMC location University of Amsterdam, Amsterdam, The Netherlands
- Cancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, The Netherlands
| | - Sirisha Tadimalla
- Institute of Medical Physics, The University of Sydney, Sydney, Australia
| | - Jonathan Arvidsson
- Department of Medical Radiation Sciences, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Yu Sun
- Institute of Medical Physics, The University of Sydney, Sydney, Australia
| | - Jesper Kallehauge
- Aarhus University Hospital, Danish Centre for Particle Therapy, Aarhus, Denmark
- Aarhus University, Department of Clinical Medicine, Aarhus, Denmark
| | - Ben Dickie
- Division of Informatics, Imaging, and Data Science, School of Health Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Northern Care Alliance NHS Group, The University of Manchester, Manchester, UK
| | - Simon Lévy
- MR Research Collaborations, Siemens Healthcare Pty Ltd, Melbourne, Australia
| | - Laura Bell
- Genentech, Inc, Clinical Imaging Group, South San Francisco, USA
| | - Steven Sourbron
- University of Sheffield, Department of Infection, Immunity and Cardiovascular Disease, Sheffield, UK
| | - Michael J Thrippleton
- University of Edinburgh, Edinburgh Imaging and Centre for Clinical Brain Sciences, Edinburgh, UK
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Jiménez-Sánchez L, Blesa Cábez M, Vaher K, Corrigan A, Thrippleton MJ, Bastin ME, Quigley AJ, Fletcher-Watson S, Boardman JP. Infant attachment does not depend on neonatal amygdala and hippocampal structure and connectivity. Dev Cogn Neurosci 2024; 67:101387. [PMID: 38692007 PMCID: PMC11070590 DOI: 10.1016/j.dcn.2024.101387] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Revised: 03/13/2024] [Accepted: 04/17/2024] [Indexed: 05/03/2024] Open
Abstract
Infant attachment is an antecedent of later socioemotional abilities, which can be adversely affected by preterm birth. The structural integrity of amygdalae and hippocampi may subserve attachment in infancy. We aimed to investigate associations between neonatal amygdalae and hippocampi structure and their whole-brain connections and attachment behaviours at nine months of age in a sample of infants enriched for preterm birth. In 133 neonates (median gestational age 32 weeks, range 22.14-42.14), we calculated measures of amygdala and hippocampal structure (volume, fractional anisotropy, mean diffusivity, neurite dispersion index, orientation dispersion index) and structural connectivity, and coded attachment behaviours (distress, fretfulness, attentiveness to caregiver) from responses to the Still-Face Paradigm at nine months. After multiple comparisons correction, there were no significant associations between neonatal amygdala or hippocampal structure and structural connectivity and attachment behaviours: standardised β values - 0.23 to 0.18, adjusted p-values > 0.40. Findings indicate that the neural basis of infant attachment in term and preterm infants is not contingent on the structure or connectivity of the amygdalae and hippocampi in the neonatal period, which implies that it is more widely distributed in early life and or that network specialisation takes place in the months after hospital discharge.
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Affiliation(s)
- Lorena Jiménez-Sánchez
- Translational Neuroscience PhD Programme, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK; Salvesen Mindroom Research Centre, University of Edinburgh, Edinburgh, UK
| | - Manuel Blesa Cábez
- Centre for Reproductive Health, Institute for Regeneration and Repair, University of Edinburgh, Edinburgh, UK; Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Kadi Vaher
- Centre for Reproductive Health, Institute for Regeneration and Repair, University of Edinburgh, Edinburgh, UK; Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Amy Corrigan
- Centre for Reproductive Health, Institute for Regeneration and Repair, University of Edinburgh, Edinburgh, UK
| | | | - Mark E Bastin
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Alan J Quigley
- Department of Radiology, Royal Hospital for Children and Young People, Edinburgh, UK
| | - Sue Fletcher-Watson
- Salvesen Mindroom Research Centre, University of Edinburgh, Edinburgh, UK; Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - James P Boardman
- Centre for Reproductive Health, Institute for Regeneration and Repair, University of Edinburgh, Edinburgh, UK; Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.
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Galdi P, Cabez MB, Farrugia C, Vaher K, Williams LZJ, Sullivan G, Stoye DQ, Quigley AJ, Makropoulos A, Thrippleton MJ, Bastin ME, Richardson H, Whalley H, Edwards AD, Bajada CJ, Robinson EC, Boardman JP. Feature similarity gradients detect alterations in the neonatal cortex associated with preterm birth. Hum Brain Mapp 2024; 45:e26660. [PMID: 38488444 PMCID: PMC10941526 DOI: 10.1002/hbm.26660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Revised: 01/18/2024] [Accepted: 02/29/2024] [Indexed: 03/18/2024] Open
Abstract
The early life environment programmes cortical architecture and cognition across the life course. A measure of cortical organisation that integrates information from multimodal MRI and is unbound by arbitrary parcellations has proven elusive, which hampers efforts to uncover the perinatal origins of cortical health. Here, we use the Vogt-Bailey index to provide a fine-grained description of regional homogeneities and sharp variations in cortical microstructure based on feature gradients, and we investigate the impact of being born preterm on cortical development at term-equivalent age. Compared with term-born controls, preterm infants have a homogeneous microstructure in temporal and occipital lobes, and the medial parietal, cingulate, and frontal cortices, compared with term infants. These observations replicated across two independent datasets and were robust to differences that remain in the data after matching samples and alignment of processing and quality control strategies. We conclude that cortical microstructural architecture is altered in preterm infants in a spatially distributed rather than localised fashion.
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Affiliation(s)
- Paola Galdi
- MRC Centre for Reproductive HealthUniversity of EdinburghEdinburghUK
- School of InformaticsUniversity of EdinburghEdinburghUK
| | | | - Christine Farrugia
- Faculty of EngineeringUniversity of MaltaVallettaMalta
- University of Malta Magnetic Resonance Imaging Platform (UMRI)VallettaMalta
| | - Kadi Vaher
- MRC Centre for Reproductive HealthUniversity of EdinburghEdinburghUK
| | - Logan Z. J. Williams
- Centre for the Developing BrainKing's College LondonLondonUK
- School of Biomedical Engineering and Imaging ScienceKing's College LondonLondonUK
| | - Gemma Sullivan
- MRC Centre for Reproductive HealthUniversity of EdinburghEdinburghUK
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUK
| | - David Q. Stoye
- MRC Centre for Reproductive HealthUniversity of EdinburghEdinburghUK
| | | | | | | | - Mark E. Bastin
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUK
| | - Hilary Richardson
- School of Philosophy, Psychology and Language SciencesUniversity of EdinburghEdinburghUK
| | - Heather Whalley
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUK
- Centre for Genomic and Experimental MedicineUniversity of EdinburghEdinburghUK
| | - A. David Edwards
- Centre for the Developing BrainKing's College LondonLondonUK
- MRC Centre for Neurodevelopmental DisordersKing's College LondonLondonUK
| | - Claude J. Bajada
- University of Malta Magnetic Resonance Imaging Platform (UMRI)VallettaMalta
- Department of Physiology and Biochemistry, Faculty of Medicine and SurgeryUniversity of MaltaVallettaMalta
| | - Emma C. Robinson
- Centre for the Developing BrainKing's College LondonLondonUK
- School of Biomedical Engineering and Imaging ScienceKing's College LondonLondonUK
| | - James P. Boardman
- MRC Centre for Reproductive HealthUniversity of EdinburghEdinburghUK
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUK
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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] [What about the content of this article? (0)] [Affiliation(s)] [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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Jochems ACC, Muñoz Maniega S, Clancy U, Arteaga C, Jaime Garcia D, Chappell FM, Hewins W, Locherty R, Backhouse EV, Barclay G, Jardine C, McIntyre D, Gerrish I, Kampaite A, Sakka E, Valdés Hernández M, Wiseman S, Bastin ME, Stringer MS, Thrippleton MJ, Doubal FN, Wardlaw JM. Magnetic Resonance Imaging Tissue Signatures Associated With White Matter Changes Due to Sporadic Cerebral Small Vessel Disease Indicate That White Matter Hyperintensities Can Regress. J Am Heart Assoc 2024; 13:e032259. [PMID: 38293936 PMCID: PMC11056146 DOI: 10.1161/jaha.123.032259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Accepted: 12/21/2023] [Indexed: 02/01/2024]
Abstract
BACKGROUND White matter hyperintensities (WMHs) might regress and progress contemporaneously, but we know little about underlying mechanisms. We examined WMH change and underlying quantitative magnetic resonance imaging tissue measures over 1 year in patients with minor ischemic stroke with sporadic cerebral small vessel disease. METHODS AND RESULTS We defined areas of stable normal-appearing white matter, stable WMHs, progressing and regressing WMHs based on baseline and 1-year brain magnetic resonance imaging. In these areas we assessed tissue characteristics with quantitative T1, fractional anisotropy (FA), mean diffusivity (MD), and neurite orientation dispersion and density imaging (baseline only). We compared tissue signatures cross-sectionally between areas, and longitudinally within each area. WMH change masks were available for N=197. Participants' mean age was 65.61 years (SD, 11.10), 59% had a lacunar infarct, and 68% were men. FA and MD were available for N=195, quantitative T1 for N=182, and neurite orientation dispersion and density imaging for N=174. Cross-sectionally, all 4 tissue classes differed for FA, MD, T1, and Neurite Density Index. Longitudinally, in regressing WMHs, FA increased with little change in MD and T1 (difference estimate, 0.011 [95% CI, 0.006-0.017]; -0.002 [95% CI, -0.008 to 0.003] and -0.003 [95% CI, -0.009 to 0.004]); in progressing and stable WMHs, FA decreased (-0.022 [95% CI, -0.027 to -0.017] and -0.009 [95% CI, -0.011 to -0.006]), whereas MD and T1 increased (progressing WMHs, 0.057 [95% CI, 0.050-0.063], 0.058 [95% CI, 0.050 -0.066]; stable WMHs, 0.054 [95% CI, 0.045-0.063], 0.049 [95% CI, 0.039-0.058]); and in stable normal-appearing white matter, MD increased (0.004 [95% CI, 0.003-0.005]), whereas FA and T1 slightly decreased and increased (-0.002 [95% CI, -0.004 to -0.000] and 0.005 [95% CI, 0.001-0.009]). CONCLUSIONS Quantitative magnetic resonance imaging shows that WMHs that regress have less abnormal microstructure at baseline than stable WMHs and follow trajectories indicating tissue improvement compared with stable and progressing WMHs.
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Affiliation(s)
- Angela C. C. Jochems
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
| | - Susana Muñoz Maniega
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
| | - Una Clancy
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
| | - Carmen Arteaga
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
| | - Daniela Jaime Garcia
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
| | - Francesca M. Chappell
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
| | - Will Hewins
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
| | - Rachel Locherty
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
| | - Ellen V. Backhouse
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
| | - Gayle Barclay
- Edinburgh Imaging Facility, Royal Infirmary of EdinburghEdinburghUnited Kingdom
| | - Charlotte Jardine
- Edinburgh Imaging Facility, Royal Infirmary of EdinburghEdinburghUnited Kingdom
| | - Donna McIntyre
- Edinburgh Imaging Facility, Royal Infirmary of EdinburghEdinburghUnited Kingdom
| | - Iona Gerrish
- Edinburgh Imaging Facility, Royal Infirmary of EdinburghEdinburghUnited Kingdom
| | - Agniete Kampaite
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
| | - Eleni Sakka
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
| | - Maria Valdés Hernández
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
| | - Stewart Wiseman
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
| | - Mark E. Bastin
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
| | - Michael S. Stringer
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
| | - Michael J. Thrippleton
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
- Edinburgh Imaging Facility, Royal Infirmary of EdinburghEdinburghUnited Kingdom
| | - Fergus N. Doubal
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
| | - Joanna M. Wardlaw
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
- Edinburgh Imaging Facility, Royal Infirmary of EdinburghEdinburghUnited Kingdom
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Mckinnon K, Jardine C, Barclay G, Thrippleton MJ, Abel S, Wardlaw JM, Bastin ME, Whalley HC, Richardson H, Boardman JP. An unexpected ferromagnetic foreign body in a paediatric research participant undergoing 3T MRI. BMJ Case Rep 2024; 17:e258969. [PMID: 38272527 PMCID: PMC10826474 DOI: 10.1136/bcr-2023-258969] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2024] Open
Abstract
Metallic foreign bodies (FBs) are a safety risk during MRI. Here, we describe a boy in early childhood with an unexpected ferromagnetic FB discovered during a research brain MRI. Safety precautions included written and oral safety screening checklists and visual check during a structured safety pause. During introduction to the scanner, he was lifted to look at the bore. Staff became aware of an object flying into the bore. The child reached for his ear, and a 5 mm diameter ball bearing was found in the bore. The child had no external injury. We have introduced a 0.1 T handheld magnet to check for metallic FBs not known to the parent. FBs are a common paediatric emergency department presentation, particularly in younger children or those with cognitive or behavioural problems. This case highlights the importance of safety screening in paediatric MRI scanning, along with its fallibility.
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Affiliation(s)
- Katie Mckinnon
- Centre for Reproductive Health, Institute for Regeneration and Repair, University of Edinburgh, Edinburgh, UK
| | | | - Gayle Barclay
- Edinburgh Imaging Facility, University of Edinburgh, Edinburgh, UK
| | - Michael J Thrippleton
- Edinburgh Imaging Facility, University of Edinburgh, Edinburgh, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Selina Abel
- School of Philosophy, Psychology, and Language Sciences, University of Edinburgh, Edinburgh, UK
| | - Joanna M Wardlaw
- Edinburgh Imaging Facility, University of Edinburgh, Edinburgh, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Mark E Bastin
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Heather C Whalley
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Hilary Richardson
- School of Philosophy, Psychology, and Language Sciences, University of Edinburgh, Edinburgh, UK
| | - James P Boardman
- Centre for Reproductive Health, Institute for Regeneration and Repair, University of Edinburgh, Edinburgh, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
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Harper JG, York EN, Meijboom R, Kampaite A, Thrippleton MJ, Kearns PKA, Valdés Hernández MDC, Chandran S, Waldman AD. Quantitative T 1 brain mapping in early relapsing-remitting multiple sclerosis: longitudinal changes, lesion heterogeneity and disability. Eur Radiol 2023:10.1007/s00330-023-10351-6. [PMID: 37943312 DOI: 10.1007/s00330-023-10351-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 07/20/2023] [Accepted: 08/29/2023] [Indexed: 11/10/2023]
Abstract
OBJECTIVES To quantify brain microstructural changes in recently diagnosed relapsing-remitting multiple sclerosis (RRMS) using longitudinal T1 measures, and determine their associations with clinical disability. METHODS Seventy-nine people with recently diagnosed (< 6 months) RRMS were recruited from a single-centre cohort sub-study, and underwent baseline and 1-year brain MRI, including variable flip angle T1 mapping. Median T1 was measured in white matter lesions (WML), normal-appearing white matter (NAWM), cortical/deep grey matter (GM), thalami, basal ganglia and medial temporal regions. Prolonged T1 (≥ 2.00 s) and supramedian T1 (relative to cohort WML values) WML voxel counts were also measured. Longitudinal change was assessed with paired t-tests and compared with Bland-Altman limits of agreement from healthy control test-retest data. Regression analyses determined relationships with Expanded Disability Status Scale (EDSS) score and dichotomised EDSS outcomes (worsening or stable/improving). RESULTS Sixty-two people with RRMS (mean age 37.2 ± 10.9 [standard deviation], 48 female) and 11 healthy controls (age 44 ± 11, 7 female) contributed data. Prolonged and supramedian T1 WML components increased longitudinally (176 and 463 voxels, respectively; p < .001), and were associated with EDSS score at baseline (p < .05) and follow-up (supramedian: p < .01; prolonged: p < .05). No cohort-wide median T1 changes were found; however, increasing T1 in WML, NAWM, cortical/deep GM, basal ganglia and thalami was positively associated with EDSS worsening (p < .05). CONCLUSION T1 is sensitive to brain microstructure changes in early RRMS. Prolonged WML T1 components and subtle changes in NAWM and GM structures are associated with disability. CLINICAL RELEVANCE STATEMENT MRI T1 brain mapping quantifies disability-associated white matter lesion heterogeneity and subtle microstructural damage in normal-appearing brain parenchyma in recently diagnosed RRMS, and shows promise for early objective disease characterisation and stratification. KEY POINTS • Quantitative T1 mapping detects brain microstructural damage and lesion heterogeneity in recently diagnosed relapsing-remitting multiple sclerosis. • T1 increases in lesions and normal-appearing parenchyma, indicating microstructural damage, are associated with worsening disability. • Brain T1 measures are objective markers of disability-relevant pathology in early multiple sclerosis.
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Affiliation(s)
- James G Harper
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh BioQuarter: Chancellors Building, Edinburgh, EH16 4SB, UK
| | - Elizabeth N York
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh BioQuarter: Chancellors Building, Edinburgh, EH16 4SB, UK.
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK.
- Anne Rowling Regenerative Neurology Clinic, Edinburgh, UK.
| | - Rozanna Meijboom
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh BioQuarter: Chancellors Building, Edinburgh, EH16 4SB, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Agniete Kampaite
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh BioQuarter: Chancellors Building, Edinburgh, EH16 4SB, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Michael J Thrippleton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh BioQuarter: Chancellors Building, Edinburgh, EH16 4SB, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Patrick K A Kearns
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh BioQuarter: Chancellors Building, Edinburgh, EH16 4SB, UK
- Anne Rowling Regenerative Neurology Clinic, Edinburgh, UK
| | - Maria Del C Valdés Hernández
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh BioQuarter: Chancellors Building, Edinburgh, EH16 4SB, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Siddharthan Chandran
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh BioQuarter: Chancellors Building, Edinburgh, EH16 4SB, UK
- Anne Rowling Regenerative Neurology Clinic, Edinburgh, UK
- UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Adam D Waldman
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh BioQuarter: Chancellors Building, Edinburgh, EH16 4SB, UK.
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK.
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Kopczak A, Stringer MS, van den Brink H, Kerkhofs D, Blair GW, van Dinther M, Reyes CA, Garcia DJ, Onkenhout L, Wartolowska KA, Thrippleton MJ, Kampaite A, Duering M, Staals J, Lesnik-Oberstein S, Muir KW, Middeke M, Norrving B, Bousser MG, Mansmann U, Rothwell PM, Doubal FN, van Oostenbrugge R, Biessels GJ, Webb AJS, Wardlaw JM, Dichgans M. Effect of blood pressure-lowering agents on microvascular function in people with small vessel diseases (TREAT-SVDs): a multicentre, open-label, randomised, crossover trial. Lancet Neurol 2023; 22:991-1004. [PMID: 37863608 DOI: 10.1016/s1474-4422(23)00293-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 06/15/2023] [Accepted: 08/01/2023] [Indexed: 10/22/2023]
Abstract
BACKGROUND Hypertension is the leading risk factor for cerebral small vessel disease. We aimed to determine whether antihypertensive drug classes differentially affect microvascular function in people with small vessel disease. METHODS We did a multicentre, open-label, randomised crossover trial with blinded endpoint assessment at five specialist centres in Europe. We included participants aged 18 years or older with symptomatic sporadic small vessel disease or cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) and an indication for antihypertensive treatment. Participants were randomly assigned (1:1:1) to one of three sequences of antihypertensive treatment using a computer-generated multiblock randomisation, stratified by study site and patient group. A 2-week washout period was followed by three 4-week periods of oral monotherapy with amlodipine, losartan, or atenolol at approved doses. The primary endpoint was change in cerebrovascular reactivity (CVR) determined by blood oxygen level-dependent MRI response to hypercapnic challenge in normal-appearing white matter from the end of washout to the end of each treatment period. Efficacy analyses were done by intention-to-treat principles in all randomly assigned participants who had at least one valid assessment for the primary endpoint, and analyses were done separately for participants with sporadic small vessel disease and CADASIL. This trial is registered at ClinicalTrials.gov, NCT03082014, and EudraCT, 2016-002920-10, and is terminated. FINDINGS Between Feb 22, 2018, and April 28, 2022, 75 participants with sporadic small vessel disease (mean age 64·9 years [SD 9·9]) and 26 with CADASIL (53·1 years [7·0]) were enrolled and randomly assigned to treatment. 79 participants (62 with sporadic small vessel disease and 17 with CADASIL) entered the primary efficacy analysis. Change in CVR did not differ between study drugs in participants with sporadic small vessel disease (mean change in CVR 1·8 × 10-4%/mm Hg [SE 20·1; 95% CI -37·6 to 41·2] for amlodipine; 16·7 × 10-4%/mm Hg [20·0; -22·3 to 55·8] for losartan; -7·1 × 10-4%/mm Hg [19·6; -45·5 to 31·1] for atenolol; poverall=0·39) but did differ in patients with CADASIL (15·7 × 10-4%/mm Hg [SE 27·5; 95% CI -38·3 to 69·7] for amlodipine; 19·4 × 10-4%/mm Hg [27·9; -35·3 to 74·2] for losartan; -23·9 × 10-4%/mm Hg [27·5; -77·7 to 30·0] for atenolol; poverall=0·019). In patients with CADASIL, pairwise comparisons showed that CVR improved with amlodipine compared with atenolol (-39·6 × 10-4%/mm Hg [95% CI -72·5 to -6·6; p=0·019) and with losartan compared with atenolol (-43·3 × 10-4%/mm Hg [-74·3 to -12·3]; p=0·0061). No deaths occurred. Two serious adverse events were recorded, one while taking amlodipine (diarrhoea with dehydration) and one while taking atenolol (fall with fracture), neither of which was related to study drug intake. INTERPRETATION 4 weeks of treatment with amlodipine, losartan, or atenolol did not differ in their effects on cerebrovascular reactivity in people with sporadic small vessel disease but did result in differential treatment effects in patients with CADASIL. Whether antihypertensive drug classes differentially affect clinical outcomes in people with small vessel diseases requires further research. FUNDING EU Horizon 2020 programme.
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Affiliation(s)
- Anna Kopczak
- Institute for Stroke and Dementia Research, University Hospital, LMU Munich, Munich, Germany
| | - Michael S Stringer
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK; UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Hilde van den Brink
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, Netherlands
| | - Danielle Kerkhofs
- Department of Neurology and School for Cardiovascular Diseases, Maastricht University Medical Center+, Maastricht, Netherlands
| | - Gordon W Blair
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Maud van Dinther
- Department of Neurology and School for Cardiovascular Diseases, Maastricht University Medical Center+, Maastricht, Netherlands
| | - Carmen Arteaga Reyes
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK; UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Daniela Jaime Garcia
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK; UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Laurien Onkenhout
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, Netherlands
| | - Karolina A Wartolowska
- Wolfson Centre for Prevention of Stroke and Dementia, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Michael J Thrippleton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK; UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Agniete Kampaite
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK; UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Marco Duering
- Institute for Stroke and Dementia Research, University Hospital, LMU Munich, Munich, Germany; Medical Image Analysis Center and Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Julie Staals
- Department of Neurology and School for Cardiovascular Diseases, Maastricht University Medical Center+, Maastricht, Netherlands
| | | | - Keith W Muir
- School of Psychology and Neuroscience, University of Glasgow, Queen Elizabeth University Hospital, Glasgow, UK
| | - Martin Middeke
- Hypertoniezentrum München, Excellence Centre of the European Society of Hypertension, Munich, Germany
| | - Bo Norrving
- Department of Clinical Sciences Lund, Neurology, Skåne University Hospital, Lund University, Lund, Sweden
| | | | - Ulrich Mansmann
- Institute for Medical Information Processing, Biometry, and Epidemiology, LMU Munich, Munich, Germany
| | - Peter M Rothwell
- Wolfson Centre for Prevention of Stroke and Dementia, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Fergus N Doubal
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK; UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Robert van Oostenbrugge
- Department of Neurology and School for Cardiovascular Diseases, Maastricht University Medical Center+, Maastricht, Netherlands
| | - Geert Jan Biessels
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, Netherlands
| | - Alastair J S Webb
- Wolfson Centre for Prevention of Stroke and Dementia, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Joanna M Wardlaw
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK; UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Martin Dichgans
- Institute for Stroke and Dementia Research, University Hospital, LMU Munich, Munich, Germany; Munich Cluster for Systems Neurology, Munich, Germany; German Center for Neurodegenerative Diseases, Munich, Germany; German Centre for Cardiovascular Research, Munich, Germany.
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10
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Sleight E, Stringer MS, Clancy U, Arteaga C, Jaime Garcia D, Hewins W, Jochems AC, Hamilton OK, Manning C, Morgan AG, Locherty R, Cheng Y, Liu X, Zhang J, Hamilton I, Jardine C, Brown R, Sakka E, Kampaite A, Wiseman S, Valdés-Hernández MC, Chappell FM, Doubal FN, Marshall I, Thrippleton MJ, Wardlaw JM. Cerebrovascular Reactivity in Patients With Small Vessel Disease: A Cross-Sectional Study. Stroke 2023; 54:2776-2784. [PMID: 37814956 PMCID: PMC10589433 DOI: 10.1161/strokeaha.123.042656] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Revised: 09/06/2023] [Accepted: 09/19/2023] [Indexed: 10/11/2023]
Abstract
BACKGROUND Cerebrovascular reactivity (CVR) is inversely related to white matter hyperintensity severity, a marker of cerebral small vessel disease (SVD). Less is known about the relationship between CVR and other SVD imaging features or cognition. We aimed to investigate these cross-sectional relationships. METHODS Between 2018 and 2021 in Edinburgh, we recruited patients presenting with lacunar or cortical ischemic stroke, whom we characterized for SVD features. We measured CVR in subcortical gray matter, normal-appearing white matter, and white matter hyperintensity using 3T magnetic resonance imaging. We assessed cognition using Montreal Cognitive Assessment. Statistical analyses included linear regression models with CVR as outcome, adjusted for age, sex, and vascular risk factors. We reported regression coefficients with 95% CIs. RESULTS Of 208 patients, 182 had processable CVR data sets (median age, 68.2 years; 68% men). Although the strength of association depended on tissue type, lower CVR in normal-appearing tissues and white matter hyperintensity was associated with larger white matter hyperintensity volume (BNAWM=-0.0073 [95% CI, -0.0133 to -0.0014] %/mm Hg per 10-fold increase in percentage intracranial volume), more lacunes (BNAWM=-0.00129 [95% CI, -0.00215 to -0.00043] %/mm Hg per lacune), more microbleeds (BNAWM=-0.00083 [95% CI, -0.00130 to -0.00036] %/mm Hg per microbleed), higher deep atrophy score (BNAWM=-0.00218 [95% CI, -0.00417 to -0.00020] %/mm Hg per score point increase), higher perivascular space score (BNAWM=-0.0034 [95% CI, -0.0066 to -0.0002] %/mm Hg per score point increase in basal ganglia), and higher SVD score (BNAWM=-0.0048 [95% CI, -0.0075 to -0.0021] %/mm Hg per score point increase). Lower CVR in normal-appearing tissues was related to lower Montreal Cognitive Assessment without reaching convention statistical significance (BNAWM=0.00065 [95% CI, -0.00007 to 0.00137] %/mm Hg per score point increase). CONCLUSIONS Lower CVR in patients with SVD was related to more severe SVD burden and worse cognition in this cross-sectional analysis. Longitudinal analysis will help determine whether lower CVR predicts worsening SVD severity or vice versa. REGISTRATION URL: https://www.isrctn.com; Unique identifier: ISRCTN12113543.
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Affiliation(s)
- Emilie Sleight
- Centre for Clinical Brain Sciences (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
- UK Dementia Research Institute (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
| | - Michael S. Stringer
- Centre for Clinical Brain Sciences (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
- UK Dementia Research Institute (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
| | - Una Clancy
- Centre for Clinical Brain Sciences (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
- UK Dementia Research Institute (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
| | - Carmen Arteaga
- Centre for Clinical Brain Sciences (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
- UK Dementia Research Institute (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
| | - Daniela Jaime Garcia
- Centre for Clinical Brain Sciences (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
- UK Dementia Research Institute (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
| | - Will Hewins
- Centre for Clinical Brain Sciences (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
- UK Dementia Research Institute (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
| | - Angela C.C. Jochems
- Centre for Clinical Brain Sciences (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
- UK Dementia Research Institute (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
| | - Olivia K.L. Hamilton
- Centre for Clinical Brain Sciences (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
- UK Dementia Research Institute (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
| | - Cameron Manning
- Centre for Clinical Brain Sciences (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
- UK Dementia Research Institute (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
| | - Alasdair G. Morgan
- Centre for Clinical Brain Sciences (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
- UK Dementia Research Institute (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
| | - Rachel Locherty
- Centre for Clinical Brain Sciences (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
- UK Dementia Research Institute (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
| | - Yajun Cheng
- Centre for Clinical Brain Sciences (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
- UK Dementia Research Institute (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
- Department of Neurology, West China Hospital of Sichuan University, Chengdu (Y.C.)
| | - Xiaodi Liu
- Centre for Clinical Brain Sciences (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
- UK Dementia Research Institute (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
- Department of Medicine, University of Hong Kong (X.L.)
| | - Junfang Zhang
- Centre for Clinical Brain Sciences (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
- UK Dementia Research Institute (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
- Department of Neurology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, China (J.Z.)
| | - Iona Hamilton
- Edinburgh Imaging Facility RIE (I.H., C.J., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
| | - Charlotte Jardine
- Edinburgh Imaging Facility RIE (I.H., C.J., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
| | - Rosalind Brown
- Centre for Clinical Brain Sciences (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
- UK Dementia Research Institute (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
| | - Eleni Sakka
- Centre for Clinical Brain Sciences (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
- UK Dementia Research Institute (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
| | - Agniete Kampaite
- Centre for Clinical Brain Sciences (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
- UK Dementia Research Institute (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
| | - Stewart Wiseman
- Centre for Clinical Brain Sciences (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
- UK Dementia Research Institute (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
| | - Maria C. Valdés-Hernández
- Centre for Clinical Brain Sciences (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
- UK Dementia Research Institute (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
| | - Francesca M. Chappell
- Centre for Clinical Brain Sciences (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
- UK Dementia Research Institute (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
| | - Fergus N. Doubal
- Centre for Clinical Brain Sciences (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
- UK Dementia Research Institute (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
| | - Ian Marshall
- Centre for Clinical Brain Sciences (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
- UK Dementia Research Institute (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
| | - Michael J. Thrippleton
- Centre for Clinical Brain Sciences (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
- UK Dementia Research Institute (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
- Edinburgh Imaging Facility RIE (I.H., C.J., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
| | - Joanna M. Wardlaw
- Centre for Clinical Brain Sciences (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
- UK Dementia Research Institute (E. Sleight, M.S.S., U.C., C.A., D.J.G., W.H., A.C.C.J., O.K.L.H., C.M., A.G.M., R.L., Y.C., X.L., J.Z., R.B., E. Sakka, A.K., S.W., M.C.V.-H., F.M.C., F.N.D., I.M., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
- Edinburgh Imaging Facility RIE (I.H., C.J., M.J.T., J.M.W.), University of Edinburgh, United Kingdom
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11
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Needham N, Campbell IH, Grossi H, Kamenska I, Rigby BP, Simpson SA, McIntosh E, Bahuguna P, Meadowcroft B, Creasy F, Mitchell-Grigorjeva M, Norrie J, Thompson G, Gibbs MC, McLellan A, Fisher C, Moses T, Burgess K, Brown R, Thrippleton MJ, Campbell H, Smith DJ. Pilot study of a ketogenic diet in bipolar disorder. BJPsych Open 2023; 9:e176. [PMID: 37814952 PMCID: PMC10594182 DOI: 10.1192/bjo.2023.568] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Revised: 08/11/2023] [Accepted: 08/22/2023] [Indexed: 10/11/2023] Open
Abstract
BACKGROUND Recent evidence from case reports suggests that a ketogenic diet may be effective for bipolar disorder. However, no clinical trials have been conducted to date. AIMS To assess the recruitment and feasibility of a ketogenic diet intervention in bipolar disorder. METHOD Euthymic individuals with bipolar disorder were recruited to a 6-8 week trial of a modified ketogenic diet, and a range of clinical, economic and functional outcome measures were assessed. Study registration number: ISRCTN61613198. RESULTS Of 27 recruited participants, 26 commenced and 20 completed the modified ketogenic diet for 6-8 weeks. The outcomes data-set was 95% complete for daily ketone measures, 95% complete for daily glucose measures and 95% complete for daily ecological momentary assessment of symptoms during the intervention period. Mean daily blood ketone readings were 1.3 mmol/L (s.d. = 0.77, median = 1.1) during the intervention period, and 91% of all readings indicated ketosis, suggesting a high degree of adherence to the diet. Over 91% of daily blood glucose readings were within normal range, with 9% indicating mild hypoglycaemia. Eleven minor adverse events were recorded, including fatigue, constipation, drowsiness and hunger. One serious adverse event was reported (euglycemic ketoacidosis in a participant taking SGLT2-inhibitor medication). CONCLUSIONS The recruitment and retention of euthymic individuals with bipolar disorder to a 6-8 week ketogenic diet intervention was feasible, with high completion rates for outcome measures. The majority of participants reached and maintained ketosis, and adverse events were generally mild and modifiable. A future randomised controlled trial is now warranted.
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Affiliation(s)
- Nicole Needham
- Centre for Clinical Brain Sciences, University of Edinburgh, UK
| | | | - Helen Grossi
- Department of Nutrition and Dietetics, Royal Hospital for Children and Young People, NHS Lothian, UK
| | | | | | | | - Emma McIntosh
- Health Economics and Health Technology Assessment, University of Glasgow, UK
| | - Pankaj Bahuguna
- Health Economics and Health Technology Assessment, University of Glasgow, UK
| | | | | | | | - John Norrie
- Usher Institute, University of Edinburgh, UK
| | - Gerard Thompson
- Centre for Clinical Brain Sciences, University of Edinburgh, UK
| | | | - Ailsa McLellan
- Department of Paediatric Neurology, Royal Hospital for Children and Young People, NHS Lothian, UK
| | - Cheryl Fisher
- Department of Nutrition and Dietetics, Royal Hospital for Children and Young People, NHS Lothian, UK
| | - Tessa Moses
- Centre for Engineering Biology, University of Edinburgh, UK
| | - Karl Burgess
- Centre for Engineering Biology, University of Edinburgh, UK
| | | | | | | | - Daniel J. Smith
- Centre for Clinical Brain Sciences, University of Edinburgh, UK
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12
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Sennfält S, Thrippleton MJ, Stringer M, Reyes CA, Chappell F, Doubal F, Garcia DJ, Zhang J, Cheng Y, Wardlaw J. Visualising and semi-quantitatively measuring brain fluid pathways, including meningeal lymphatics, in humans using widely available MRI techniques. J Cereb Blood Flow Metab 2023; 43:1779-1795. [PMID: 37254892 PMCID: PMC10581238 DOI: 10.1177/0271678x231179555] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Revised: 04/17/2023] [Accepted: 04/25/2023] [Indexed: 06/01/2023]
Abstract
Brain fluid dynamics remains poorly understood with central issues unresolved. In this study, we first review the literature regarding points of controversy, then pilot study if conventional MRI techniques can assess brain fluid outflow pathways and explore potential associations with small vessel disease (SVD). We assessed 19 subjects participating in the Mild Stroke Study 3 who had FLAIR imaging before and 20-30 minutes after intravenous Gadolinium (Gd)-based contrast. Signal intensity (SI) change was assessed semi-quantitatively by placing regions of interest, and qualitatively by a visual scoring system, along dorsal and basal fluid outflow routes. Following i.v. Gd, SI increased substantially along the anterior, middle, and posterior superior sagittal sinus (SSS) (82%, 104%, and 119%, respectively), at basal areas (cribriform plate, 67%; jugular foramina, 72%), and in narrow channels surrounding superficial cortical veins separated from surrounding cerebrospinal fluid (CSF) (96%) (all p < 0.001). The SI increase was associated with higher intraparenchymal perivascular spaces (PVS) scores (Std. Beta 0.71, p = 0.01). Our findings suggests that interstitial fluid drainage is visible on conventional MRI and drains from brain parenchyma via cortical perivenous spaces to dural meningeal lymphatics along the SSS remaining separate from the CSF. An association with parenchymal PVS requires further research, now feasible in humans.
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Affiliation(s)
- Stefan Sennfält
- Department of Neurology, Karolinska University Hospital, Stockholm, Sweden
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | | | - Michael Stringer
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | | | - Francesca Chappell
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Fergus Doubal
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Daniela J Garcia
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Junfang Zhang
- Department of Neurology, Shanghai General Hospital and Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yajun Cheng
- Department of Neurology, West China Hospital and Sichuan University, Chengdu, China
| | - Joanna Wardlaw
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- UK Dementia Research Institute at the University of Edinburgh, Edinburgh, UK
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13
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Meijboom R, York EN, Kampaite A, Harris MA, White N, Valdés Hernández MDC, Thrippleton MJ, MacDougall NJJ, Connick P, Hunt DPJ, Chandran S, Waldman AD. Patterns of brain atrophy in recently-diagnosed relapsing-remitting multiple sclerosis. PLoS One 2023; 18:e0288967. [PMID: 37506096 PMCID: PMC10381059 DOI: 10.1371/journal.pone.0288967] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 07/07/2023] [Indexed: 07/30/2023] Open
Abstract
Recurrent neuroinflammation in relapsing-remitting MS (RRMS) is thought to lead to neurodegeneration, resulting in progressive disability. Repeated magnetic resonance imaging (MRI) of the brain provides non-invasive measures of atrophy over time, a key marker of neurodegeneration. This study investigates regional neurodegeneration of the brain in recently-diagnosed RRMS using volumetry and voxel-based morphometry (VBM). RRMS patients (N = 354) underwent 3T structural MRI <6 months after diagnosis and 1-year follow-up, as part of the Scottish multicentre 'FutureMS' study. MRI data were processed using FreeSurfer to derive volumetrics, and FSL for VBM (grey matter (GM) only), to establish regional patterns of change in GM and normal-appearing white matter (NAWM) over time throughout the brain. Volumetric analyses showed a decrease over time (q<0.05) in bilateral cortical GM and NAWM, cerebellar GM, brainstem, amygdala, basal ganglia, hippocampus, accumbens, thalamus and ventral diencephalon. Additionally, NAWM and GM volume decreased respectively in the following cortical regions, frontal: 14 out of 26 regions and 16/26; temporal: 18/18 and 15/18; parietal: 14/14 and 11/14; occipital: 7/8 and 8/8. Left GM and NAWM asymmetry was observed in the frontal lobe. GM VBM analysis showed three major clusters of decrease over time: 1) temporal and subcortical areas, 2) cerebellum, 3) anterior cingulum and supplementary motor cortex; and four smaller clusters within the occipital lobe. Widespread GM and NAWM atrophy was observed in this large recently-diagnosed RRMS cohort, particularly in the brainstem, cerebellar GM, and subcortical and occipital-temporal regions; indicative of neurodegeneration across tissue types, and in accord with limited previous studies in early disease. Volumetric and VBM results emphasise different features of longitudinal lobar and loco-regional change, however identify consistent atrophy patterns across individuals. Atrophy measures targeted to specific brain regions may provide improved markers of neurodegeneration, and potential future imaging stratifiers and endpoints for clinical decision making and therapeutic trials.
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Affiliation(s)
- Rozanna Meijboom
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
| | - Elizabeth N York
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh, United Kingdom
| | - Agniete Kampaite
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
| | - Mathew A Harris
- Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom
| | - Nicole White
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
| | - Maria Del C Valdés Hernández
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
| | - Michael J Thrippleton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
| | - N J J MacDougall
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh, United Kingdom
| | - Peter Connick
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh, United Kingdom
| | - David P J Hunt
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- UK Dementia Research Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Siddharthan Chandran
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh, United Kingdom
| | - Adam D Waldman
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
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14
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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: 80] [Impact Index Per Article: 80.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [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.
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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.
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15
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Morgan AG, Thrippleton MJ, Stringer M, Jin N, Wardlaw JM, Marshall I. Repeatability and comparison of 2D and 4D flow MRI measurement of intracranial blood flow and pulsatility in healthy individuals and patients with cerebral small vessel disease. Front Psychol 2023; 14:1125038. [PMID: 37325748 PMCID: PMC10262051 DOI: 10.3389/fpsyg.2023.1125038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 05/09/2023] [Indexed: 06/17/2023] Open
Abstract
Introduction While 2D phase-contrast MRI is often used to examine intracranial vessels in neurovascular disease contexts, the ability of 4D flow to assess many vessels at once makes it an attractive alternative. We aimed to assess the repeatability, reliability, and conformity of 2D and 4D flow across intracranial vessels. Methods Using correlation analyses and paired t-tests, test-retest repeatability, intra-rater reliability, and inter-method conformity for measurements of pulsatility index (PI) and mean flow were assessed in the arteries and veins of 11 healthy volunteers. Inter-method conformity was also assessed in 10 patients with small vessel disease. Results Repeatability for PI measurements was mostly classed as good using both 2D (median ICC = 0.765) and 4D (0.772) methods, and for mean flow was mostly moderate across both (2D: 0.711, 4D: 0.571). 4D reliability was good for PI (0.877-0.906) and moderate for mean flow (0.459-0.723). Arterial PI measurements were generally higher using the 2D method, while mean flow was mostly higher using 4D flow. Discussion These results imply that PI measurement using 4D flow is repeatable and reliable across intracranial arteries and veins, but care should be paid to absolute flow measurements as they are susceptible to variation depending on slice placement, resolution, and lumen segmentation practices.
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Affiliation(s)
- Alasdair G. Morgan
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- UK Dementia Research Institute, University of Edinburgh, Edinburgh, United Kingdom
- Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
| | - Michael J. Thrippleton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- UK Dementia Research Institute, University of Edinburgh, Edinburgh, United Kingdom
- Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
| | - Michael Stringer
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- UK Dementia Research Institute, University of Edinburgh, Edinburgh, United Kingdom
- Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
| | - Ning Jin
- Siemens Medical Solutions USA, Inc., Cleveland, OH, United States
| | - Joanna M. Wardlaw
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- UK Dementia Research Institute, University of Edinburgh, Edinburgh, United Kingdom
- Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
| | - Ian Marshall
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- UK Dementia Research Institute, University of Edinburgh, Edinburgh, United Kingdom
- Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
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16
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Hubbard Cristinacce PL, Markus JE, Punwani S, Mills R, Lopez MY, Grech-Sollars M, Fasano F, Waterton JC, Thrippleton MJ, Hall MG, O'Connor JPB, Francis ST, Statton B, Murphy K, So PW, Hyare H. Steps on the Path to Clinical Translation: A workshop by the British and Irish Chapter of the ISMRM. Magn Reson Med 2023. [PMID: 37222226 DOI: 10.1002/mrm.29704] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 03/24/2023] [Accepted: 04/24/2023] [Indexed: 05/25/2023]
Abstract
The British and Irish Chapter of the International Society for Magnetic Resonance in Medicine (BIC-ISMRM) held a workshop entitled "Steps on the path to clinical translation" in Cardiff, UK, on 7th September 2022. The aim of the workshop was to promote discussion within the MR community about the problems and potential solutions for translating quantitative MR (qMR) imaging and spectroscopic biomarkers into clinical application and drug studies. Invited speakers presented the perspectives of radiologists, radiographers, clinical physicists, vendors, imaging Contract/Clinical Research Organizations (CROs), open science networks, metrologists, imaging networks, and those developing consensus methods. A round-table discussion was held in which workshop participants discussed a range of questions pertinent to clinical translation of qMR imaging and spectroscopic biomarkers. Each group summarized their findings via three main conclusions and three further questions. These questions were used as the basis of an online survey of the broader UK MR community.
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Affiliation(s)
- Penny L Hubbard Cristinacce
- Quantitative Biomedical Imaging Laboratory, Division of Cancer Sciences, School of Health Sciences, Faculty of Biology Medicine & Health, University of Manchester, Manchester Academic Health Sciences Centre, Manchester, UK
| | - Julia E Markus
- Centre for Medical Imaging, Division of Medicine, University College London, London, UK
| | - Shonit Punwani
- Centre for Medical Imaging, Division of Medicine, University College London, London, UK
| | - Rebecca Mills
- University of Oxford, Centre for Clinical Magnetic Resonance Research, The John Radcliffe Hospital, Oxford, UK
| | - Maria Yanez Lopez
- MR Physics Group, Department of Medical Physics and Clinical Engineering, Swansea Bay University Health Board, Singleton Hospital, Swansea, UK
| | - Matthew Grech-Sollars
- Department of Computer Science, University College London, London, UK
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
| | | | - John C Waterton
- Centre for Imaging Sciences, Division of Informatics Imaging & Data Sciences, School of Health Sciences, Faculty of Biology Medicine & Health, University of Manchester, Manchester Academic Health Sciences Centre, Manchester, UK
- Bioxydyn Limited, Rutherford House, Manchester Science Park, Manchester, UK
| | - Michael J Thrippleton
- Edinburgh Imaging/Centre for Clinical Brain Sciences, University of Edinburgh, The Chancellor's Building, Edinburgh, UK
| | - Matt G Hall
- National Physical Laboratory, Teddington, UK
| | - James P B O'Connor
- Quantitative Biomedical Imaging Laboratory, Division of Cancer Sciences, School of Health Sciences, Faculty of Biology Medicine & Health, University of Manchester, Manchester Academic Health Sciences Centre, Manchester, UK
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, UK
| | - Susan T Francis
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Ben Statton
- MRC London Institute of Medical Sciences, Du Cane Road, Imperial College London, London, UK
| | - Kevin Murphy
- Cardiff University Brain Research Imaging Centre, School of Physics and Astronomy, Cardiff, UK
| | - Po-Wah So
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Harpreet Hyare
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
- Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, London, UK
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17
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Conole ELS, Vaher K, Cabez MB, Sullivan G, Stevenson AJ, Hall J, Murphy L, Thrippleton MJ, Quigley AJ, Bastin ME, Miron VE, Whalley HC, Marioni RE, Boardman JP, Cox SR. Immuno-epigenetic signature derived in saliva associates with the encephalopathy of prematurity and perinatal inflammatory disorders. Brain Behav Immun 2023; 110:322-338. [PMID: 36948324 DOI: 10.1016/j.bbi.2023.03.011] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Revised: 02/12/2023] [Accepted: 03/16/2023] [Indexed: 03/24/2023] Open
Abstract
BACKGROUND Preterm birth is closely associated with a phenotype that includes brain dysmaturation and neurocognitive impairment, commonly termed Encephalopathy of Prematurity (EoP), of which systemic inflammation is considered a key driver. DNA methylation (DNAm) signatures of inflammation from peripheral blood associate with poor brain imaging outcomes in adult cohorts. However, the robustness of DNAm inflammatory scores in infancy, their relation to comorbidities of preterm birth characterised by inflammation, neonatal neuroimaging metrics of EoP, and saliva cross-tissue applicability are unknown. METHODS Using salivary DNAm from 258 neonates (n = 155 preterm, gestational age at birth 23.28 - 34.84 weeks, n = 103 term, gestational age at birth 37.00 - 42.14 weeks), we investigated the impact of a DNAm surrogate for C-reactive protein (DNAm CRP) on brain structure and other clinically defined inflammatory exposures. We assessed i) if DNAm CRP estimates varied between preterm infants at term equivalent age and term infants, ii) how DNAm CRP related to different types of inflammatory exposure (maternal, fetal and postnatal) and iii) whether elevated DNAm CRP associated with poorer measures of neonatal brain volume and white matter connectivity. RESULTS Higher DNAm CRP was linked to preterm status (-0.0107 ± 0.0008, compared with -0.0118 ± 0.0006 among term infants; p < 0.001), as well as perinatal inflammatory diseases, including histologic chorioamnionitis, sepsis, bronchopulmonary dysplasia, and necrotising enterocolitis (OR range |2.00 | to |4.71|, p < 0.01). Preterm infants with higher DNAm CRP scores had lower brain volume in deep grey matter, white matter, and hippocampi and amygdalae (β range |0.185| to |0.218|). No such associations were observed for term infants. Association magnitudes were largest for measures of white matter microstructure among preterms, where elevated epigenetic inflammation associated with poorer global measures of white matter integrity (β range |0.206| to |0.371|), independent of other confounding exposures. CONCLUSIONS Inflammatory-related DNAm captures the allostatic load of inflammatory burden in preterm infants. Such DNAm measures complement biological and clinical metrics when investigating the determinants of neurodevelopmental differences.
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Affiliation(s)
- Eleanor L S Conole
- Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, UK; Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, UK; Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK.
| | - Kadi Vaher
- MRC Centre for Reproductive Health, Queen's Medical Research Institute, Edinburgh BioQuarter, University of Edinburgh, Edinburgh EH16 4TJ, UK
| | - Manuel Blesa Cabez
- MRC Centre for Reproductive Health, Queen's Medical Research Institute, Edinburgh BioQuarter, University of Edinburgh, Edinburgh EH16 4TJ, UK
| | - Gemma Sullivan
- MRC Centre for Reproductive Health, Queen's Medical Research Institute, Edinburgh BioQuarter, University of Edinburgh, Edinburgh EH16 4TJ, UK
| | - Anna J Stevenson
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Jill Hall
- MRC Centre for Reproductive Health, Queen's Medical Research Institute, Edinburgh BioQuarter, University of Edinburgh, Edinburgh EH16 4TJ, UK
| | - Lee Murphy
- Edinburgh Clinical Research Facility, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Michael J Thrippleton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK; Edinburgh Clinical Research Facility, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Alan J Quigley
- Imaging Department, Royal Hospital for Children and Young People, Edinburgh, EH16 4TJ, UK
| | - Mark E Bastin
- Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, UK; Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Veronique E Miron
- MRC Centre for Reproductive Health, Queen's Medical Research Institute, Edinburgh BioQuarter, University of Edinburgh, Edinburgh EH16 4TJ, UK
| | - Heather C Whalley
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - James P Boardman
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK; MRC Centre for Reproductive Health, Queen's Medical Research Institute, Edinburgh BioQuarter, University of Edinburgh, Edinburgh EH16 4TJ, UK
| | - Simon R Cox
- Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, UK.
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18
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Kopczak A, Stringer MS, van den Brink H, Kerkhofs D, Blair GW, van Dinther M, Onkenhout L, Wartolowska KA, Thrippleton MJ, Duering M, Staals J, Middeke M, André E, Norrving B, Bousser MG, Mansmann U, Rothwell PM, Doubal FN, van Oostenbrugge R, Biessels GJ, Webb AJS, Wardlaw JM, Dichgans M. The EffecTs of Amlodipine and other Blood PREssure Lowering Agents on Microvascular FuncTion in Small Vessel Diseases (TREAT-SVDs) trial: Study protocol for a randomised crossover trial. Eur Stroke J 2023; 8:387-397. [PMID: 37021189 PMCID: PMC10069218 DOI: 10.1177/23969873221143570] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Accepted: 11/16/2022] [Indexed: 12/23/2022] Open
Abstract
Background Hypertension is the leading modifiable risk factor for cerebral small vessel diseases (SVDs). Yet, it is unknown whether antihypertensive drug classes differentially affect microvascular function in SVDs. Aims To test whether amlodipine has a beneficial effect on microvascular function when compared to either losartan or atenolol, and whether losartan has a beneficial effect when compared to atenolol in patients with symptomatic SVDs. Design TREAT-SVDs is an investigator-led, prospective, open-label, randomised crossover trial with blinded endpoint assessment (PROBE design) conducted at five study sites across Europe. Patients aged 18 years or older with symptomatic SVD who have an indication for antihypertensive treatment and are suffering from either sporadic SVD and a history of lacunar stroke or vascular cognitive impairment (group A) or CADASIL (group B) are randomly allocated 1:1:1 to one of three sequences of antihypertensive treatment. Patients stop their regular antihypertensive medication for a 2-week run-in period followed by 4-week periods of monotherapy with amlodipine, losartan and atenolol in random order as open-label medication in standard dose. Outcomes The primary outcome measure is cerebrovascular reactivity (CVR) as determined by blood oxygen level dependent brain MRI signal response to hypercapnic challenge with change in CVR in normal appearing white matter as primary endpoint. Secondary outcome measures are mean systolic blood pressure (BP) and BP variability (BPv). Discussion TREAT-SVDs will provide insights into the effects of different antihypertensive drugs on CVR, BP, and BPv in patients with symptomatic sporadic and hereditary SVDs. Funding European Union's Horizon 2020 programme. Trial registration NCT03082014.
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Affiliation(s)
- Anna Kopczak
- Institute for Stroke and Dementia
Research, University Hospital, LMU Munich, Munich, Germany
| | - Michael S Stringer
- Centre for Clinical Brain Sciences,
University of Edinburgh, Edinburgh, UK
| | - Hilde van den Brink
- Department of Neurology, UMC Utrecht
Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Danielle Kerkhofs
- Department of Neurology and School for
cardiovascular diseases (CARIM), Maastricht University Medical Center+, Maastricht,
The Netherlands
| | - Gordon W Blair
- Centre for Clinical Brain Sciences,
University of Edinburgh, Edinburgh, UK
| | - Maud van Dinther
- Department of Neurology and School for
cardiovascular diseases (CARIM), Maastricht University Medical Center+, Maastricht,
The Netherlands
| | - Laurien Onkenhout
- Department of Neurology, UMC Utrecht
Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Karolina A Wartolowska
- Wolfson Centre for Prevention of Stroke
and Dementia, Nuffield Department of Clinical Neurosciences, University of Oxford,
Oxford, UK
| | | | - Marco Duering
- Institute for Stroke and Dementia
Research, University Hospital, LMU Munich, Munich, Germany
- Medical Image Analysis Center (MIAC AG)
and Department of Biomedical Engineering, University of Basel, Basel,
Switzerland
| | - Julie Staals
- Department of Neurology and School for
cardiovascular diseases (CARIM), Maastricht University Medical Center+, Maastricht,
The Netherlands
| | - Martin Middeke
- Hypertoniezentrum München, Excellence
Centre of the European Society of Hypertension (ESH), Munich, Germany
| | - Elisabeth André
- Münchner Studienzentrum, Faculty of
Medicine, Technical University Munich (TUM), Munich, Germany
| | - Bo Norrving
- Neurology, Department of Clinical
Sciences Lund, Lund University, and Neurology, Skåne University Hospital Lund/Malmö,
Sweden
| | | | - Ulrich Mansmann
- Institute for Medical Information
Processing, Biometry, and Epidemiology, LMU Munich, Munich, Germany
| | - Peter M Rothwell
- Wolfson Centre for Prevention of Stroke
and Dementia, Nuffield Department of Clinical Neurosciences, University of Oxford,
Oxford, UK
| | - Fergus N Doubal
- Centre for Clinical Brain Sciences,
University of Edinburgh, Edinburgh, UK
| | - Robert van Oostenbrugge
- Department of Neurology and School for
cardiovascular diseases (CARIM), Maastricht University Medical Center+, Maastricht,
The Netherlands
| | - Geert Jan Biessels
- Department of Neurology, UMC Utrecht
Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Alastair JS Webb
- Wolfson Centre for Prevention of Stroke
and Dementia, Nuffield Department of Clinical Neurosciences, University of Oxford,
Oxford, UK
| | - Joanna M Wardlaw
- Centre for Clinical Brain Sciences,
University of Edinburgh, Edinburgh, UK
- UK Dementia Research Institute,
University of Edinburgh, Edinburgh, UK
| | - Martin Dichgans
- Institute for Stroke and Dementia
Research, University Hospital, LMU Munich, Munich, Germany
- Munich Cluster for Systems Neurology
(SyNergy), Munich, Germany
- German Center for Neurodegenerative
Diseases (DZNE), Munich, Germany
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19
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Sullivan G, Vaher K, Blesa M, Galdi P, Stoye DQ, Quigley AJ, Thrippleton MJ, Norrie J, Bastin ME, Boardman JP. Breast Milk Exposure is Associated With Cortical Maturation in Preterm Infants. Ann Neurol 2023; 93:591-603. [PMID: 36412221 DOI: 10.1002/ana.26559] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 11/14/2022] [Accepted: 11/18/2022] [Indexed: 11/23/2022]
Abstract
OBJECTIVE Breast milk exposure is associated with improved neurocognitive outcomes following preterm birth but the neural substrates linking breast milk with outcome are uncertain. We tested the hypothesis that high versus low breast milk exposure in preterm infants results in cortical morphology that more closely resembles that of term-born infants. METHODS We studied 135 preterm (<32 weeks' gestation) and 77 term infants. Feeding data were collected from birth until hospital discharge and brain magnetic resonance imaging (MRI) was performed at term-equivalent age. Cortical indices (volume, thickness, surface area, gyrification index, sulcal depth, and curvature) and diffusion parameters (fractional anisotropy [FA], mean diffusivity [MD], radial diffusivity [RD], axial diffusivity [AD], neurite density index [NDI], and orientation dispersion index [ODI]) were compared between preterm infants who received exclusive breast milk for <75% of inpatient days, preterm infants who received exclusive breast milk for ≥75% of inpatient days and term-born controls. To investigate a dose response effect, we performed linear regression using breast milk exposure quartile weighted by propensity scores. RESULTS In preterm infants, high breast milk exposure was associated with reduced cortical gray matter volume (d = 0.47, 95% confidence interval [CI] = 0.14 to 0.94, p = 0.014), thickness (d = 0.42, 95% CI = 0.08 to 0.84, p = 0.039), and RD (d = 0.38, 95% CI = 0.002 to 0.77, p = 0.039), and increased FA (d = -0.38, 95% CI = -0.74 to -0.01, p = 0.037) after adjustment for age at MRI, which was similar to the cortical phenotype observed in term-born controls. Breast milk exposure quartile was associated with cortical volume (ß = -0.192, 95% CI = -0.342 to -0.042, p = 0.017), FA (ß = 0.223, 95% CI = 0.075 to 0.372, p = 0.007), and RD (ß = -0.225, 95% CI = -0.373 to -0.076, p = 0.007) following adjustment for age at birth, age at MRI, and weighted by propensity scores, suggesting a dose effect. INTERPRETATION High breast milk exposure following preterm birth is associated with a cortical imaging phenotype that more closely resembles the brain morphology of term-born infants and effects appear to be dose-dependent. ANN NEUROL 2023;93:591-603.
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Affiliation(s)
- Gemma Sullivan
- MRC Centre for Reproductive Health, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Kadi Vaher
- MRC Centre for Reproductive Health, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Manuel Blesa
- MRC Centre for Reproductive Health, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Paola Galdi
- MRC Centre for Reproductive Health, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - David Q Stoye
- MRC Centre for Reproductive Health, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Alan J Quigley
- Department of Radiology, Royal Hospital for Children and Young People, Edinburgh, UK
| | - Michael J Thrippleton
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK.,Centre for Clinical Brain Sciences, Chancellor's Building, University of Edinburgh, Edinburgh, UK
| | - John Norrie
- Usher Institute, Edinburgh Clinical Trials Unit, University of Edinburgh, Edinburgh, UK
| | - Mark E Bastin
- Centre for Clinical Brain Sciences, Chancellor's Building, University of Edinburgh, Edinburgh, UK
| | - James P Boardman
- MRC Centre for Reproductive Health, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK.,Centre for Clinical Brain Sciences, Chancellor's Building, University of Edinburgh, Edinburgh, UK
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20
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Sleight E, Stringer MS, Mitchell I, Murphy M, Marshall I, Wardlaw JM, Thrippleton MJ. Cerebrovascular reactivity measurements using 3T BOLD MRI and a fixed inhaled CO 2 gas challenge: Repeatability and impact of processing strategy. Front Physiol 2023; 14:1070233. [PMID: 36814481 PMCID: PMC9939770 DOI: 10.3389/fphys.2023.1070233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 01/19/2023] [Indexed: 02/09/2023] Open
Abstract
Introduction: Cerebrovascular reactivity (CVR) measurements using blood oxygen level dependent (BOLD) magnetic resonance imaging (MRI) are commonly used to assess the health of cerebral blood vessels, including in patients with cerebrovascular diseases; however, evidence and consensus regarding reliability and optimal processing are lacking. We aimed to assess the repeatability, accuracy and precision of voxel- and region-based CVR measurements at 3 T using a fixed inhaled (FI) CO2 stimulus in a healthy cohort. Methods: We simulated the effect of noise, delay constraints and voxel- versus region-based analysis on CVR parameters. Results were verified in 15 healthy volunteers (28.1±5.5 years, female: 53%) with a test-retest MRI experiment consisting of two CVR scans. CVR magnitude and delay in grey matter (GM) and white matter were computed for both analyses assuming a linear relationship between the BOLD signal and time-shifted end-tidal CO2 (EtCO2) profile. Results: Test-retest repeatability was high [mean (95% CI) inter-scan difference: -0.01 (-0.03, -0.00) %/mmHg for GM CVR magnitude; -0.3 (-1.2,0.6) s for GM CVR delay], but we detected a small systematic reduction in CVR magnitude at scan 2 versus scan 1, accompanied by a greater EtCO2 change [±1.0 (0.4,1.5) mmHg] and lower heart rate [-5.5 (-8.6,-2.4] bpm]. CVR magnitude estimates were higher for voxel- versus region-based analysis [difference in GM: ±0.02 (0.01,0.03) %/mmHg]. Findings were supported by simulation results, predicting a positive bias for voxel-based CVR estimates dependent on temporal contrast-to-noise ratio and delay fitting constraints and an underestimation for region-based CVR estimates. Discussion: BOLD CVR measurements using FI stimulus have good within-day repeatability in healthy volunteers. However, measurements may be influenced by physiological effects and the analysis protocol. Voxel-based analyses should be undertaken with care due to potential for systematic bias; region-based analyses are more reliable in such cases.
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Affiliation(s)
- Emilie Sleight
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom,UK Dementia Research Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Michael S. Stringer
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom,UK Dementia Research Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Isla Mitchell
- Edinburgh Imaging Facility, Royal Infirmary of Edinburgh, University of Edinburgh, Edinburgh, United Kingdom
| | - Madeleine Murphy
- Edinburgh Imaging Facility, Royal Infirmary of Edinburgh, University of Edinburgh, Edinburgh, United Kingdom
| | - Ian Marshall
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom,UK Dementia Research Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Joanna M. Wardlaw
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom,UK Dementia Research Institute, University of Edinburgh, Edinburgh, United Kingdom,Edinburgh Imaging Facility, Royal Infirmary of Edinburgh, University of Edinburgh, Edinburgh, United Kingdom
| | - Michael J. Thrippleton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom,UK Dementia Research Institute, University of Edinburgh, Edinburgh, United Kingdom,Edinburgh Imaging Facility, Royal Infirmary of Edinburgh, University of Edinburgh, Edinburgh, United Kingdom,*Correspondence: Michael J. Thrippleton,
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21
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Wiseman SJ, Zhang JF, Gray C, Hamid C, Valdés Hernández MDC, Ballerini L, Thrippleton MJ, Manning C, Stringer M, Sleight E, Muñoz Maniega S, Morgan A, Cheng Y, Arteaga C, Jaime Garcia D, Clancy U, Doubal FN, Dhillon B, MacGillivray T, Wu YC, Wardlaw JM. Retinal capillary microvessel morphology changes are associated with vascular damage and dysfunction in cerebral small vessel disease. J Cereb Blood Flow Metab 2023; 43:231-240. [PMID: 36300327 PMCID: PMC9903216 DOI: 10.1177/0271678x221135658] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 09/05/2022] [Accepted: 09/06/2022] [Indexed: 01/24/2023]
Abstract
Cerebral small vessel disease (SVD) is a cause of stroke and dementia. Retinal capillary microvessels revealed by optical coherence tomography angiography (OCTA) are developmentally related to brain microvessels. We quantified retinal vessel density (VD) and branching complexity, investigating relationships with SVD lesions, white matter integrity on diffusion tensor imaging (DTI) and cerebrovascular reactivity (CVR) to CO2 in patients with minor stroke. We enrolled 123 patients (mean age 68.1 ± SD 9.9 years), 115 contributed retinal data. Right (R) and left (L) eyes are reported. After adjusting for age, eye disease, diabetes, blood pressure and image quality, lower VD remained associated with higher mean diffusivity (MD) (standardized β; R -0.16 [95%CI -0.32 to -0.01]) and lower CVR (L 0.17 [0.03 to 0.31] and R 0.19 [0.02 to 0.36]) in normal appearing white matter (NAWM). Sparser branching remained associated with sub-visible white matter damage shown by higher MD (R -0.24 [-0.08 to -0.40]), lower fractional anisotropy (FA) (L 0.17 [0.01 to 0.33]), and lower CVR (R 0.20 [0.02 to 0.38]) in NAWM. OCTA-derived metrics provide evidence of microvessel abnormalities that may underpin SVD lesions in the brain.
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Affiliation(s)
- Stewart J Wiseman
- Centre for Clinical Brain Sciences, University of Edinburgh,
Edinburgh, UK
- UK Dementia Research Institute, University of Edinburgh,
Edinburgh, UK
- Edinburgh Imaging Facilities, Edinburgh Imaging, University of
Edinburgh, UK
| | - Jun-Fang Zhang
- Department of Neurology, Shanghai General Hospital, Shanghai
Jiao Tong University School of Medicine, Shanghai, China
| | - Calum Gray
- Edinburgh Imaging Facilities, Edinburgh Imaging, University of
Edinburgh, UK
| | - Charlene Hamid
- Centre for Clinical Brain Sciences, University of Edinburgh,
Edinburgh, UK
- Edinburgh Imaging Facilities, Edinburgh Imaging, University of
Edinburgh, UK
| | - Maria del C Valdés Hernández
- Centre for Clinical Brain Sciences, University of Edinburgh,
Edinburgh, UK
- UK Dementia Research Institute, University of Edinburgh,
Edinburgh, UK
| | - Lucia Ballerini
- Centre for Clinical Brain Sciences, University of Edinburgh,
Edinburgh, UK
- UK Dementia Research Institute, University of Edinburgh,
Edinburgh, UK
| | - Michael J Thrippleton
- Centre for Clinical Brain Sciences, University of Edinburgh,
Edinburgh, UK
- UK Dementia Research Institute, University of Edinburgh,
Edinburgh, UK
- Edinburgh Imaging Facilities, Edinburgh Imaging, University of
Edinburgh, UK
| | - Cameron Manning
- Centre for Clinical Brain Sciences, University of Edinburgh,
Edinburgh, UK
| | - Michael Stringer
- Centre for Clinical Brain Sciences, University of Edinburgh,
Edinburgh, UK
- UK Dementia Research Institute, University of Edinburgh,
Edinburgh, UK
- Edinburgh Imaging Facilities, Edinburgh Imaging, University of
Edinburgh, UK
| | - Emilie Sleight
- Centre for Clinical Brain Sciences, University of Edinburgh,
Edinburgh, UK
- UK Dementia Research Institute, University of Edinburgh,
Edinburgh, UK
| | | | - Alasdair Morgan
- Centre for Clinical Brain Sciences, University of Edinburgh,
Edinburgh, UK
| | - Yajun Cheng
- Centre for Clinical Brain Sciences, University of Edinburgh,
Edinburgh, UK
- Department of Neurology, West China Hospital, Sichuan
University, Chengdu, China
| | - Carmen Arteaga
- Centre for Clinical Brain Sciences, University of Edinburgh,
Edinburgh, UK
| | - Dany Jaime Garcia
- Centre for Clinical Brain Sciences, University of Edinburgh,
Edinburgh, UK
| | - Una Clancy
- Centre for Clinical Brain Sciences, University of Edinburgh,
Edinburgh, UK
| | - Fergus N Doubal
- Centre for Clinical Brain Sciences, University of Edinburgh,
Edinburgh, UK
| | - Baljean Dhillon
- Centre for Clinical Brain Sciences, University of Edinburgh,
Edinburgh, UK
- NHS Lothian Princess Alexandra Eye Pavilion, UK
| | - Tom MacGillivray
- Centre for Clinical Brain Sciences, University of Edinburgh,
Edinburgh, UK
- Edinburgh Imaging Facilities, Edinburgh Imaging, University of
Edinburgh, UK
| | - Yun-Cheng Wu
- Department of Neurology, Shanghai General Hospital, Shanghai
Jiao Tong University School of Medicine, Shanghai, China
| | - Joanna M Wardlaw
- Centre for Clinical Brain Sciences, University of Edinburgh,
Edinburgh, UK
- UK Dementia Research Institute, University of Edinburgh,
Edinburgh, UK
- Edinburgh Imaging Facilities, Edinburgh Imaging, University of
Edinburgh, UK
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22
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Sleight E, Stringer MS, Marshall I, Wardlaw JM, Thrippleton MJ. Corrigendum: Cerebrovascular reactivity measurement using magnetic resonance imaging: A systematic review. Front Physiol 2022; 13:1105285. [PMID: 36569753 PMCID: PMC9780690 DOI: 10.3389/fphys.2022.1105285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Accepted: 11/29/2022] [Indexed: 12/13/2022] Open
Abstract
[This corrects the article DOI: 10.3389/fphys.2021.643468.].
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Affiliation(s)
- Emilie Sleight
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom,UK Dementia Research Institute, Edinburgh, United Kingdom
| | - Michael S. Stringer
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom,UK Dementia Research Institute, Edinburgh, United Kingdom,*Correspondence: Michael S. Stringer,
| | - Ian Marshall
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom,UK Dementia Research Institute, Edinburgh, United Kingdom
| | - Joanna M. Wardlaw
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom,UK Dementia Research Institute, Edinburgh, United Kingdom
| | - Michael J. Thrippleton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom,UK Dementia Research Institute, Edinburgh, United Kingdom
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23
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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: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [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.
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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
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24
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York EN, Meijboom R, Thrippleton MJ, Bastin ME, Kampaite A, White N, Chandran S, Waldman AD. Longitudinal microstructural MRI markers of demyelination and neurodegeneration in early relapsing-remitting multiple sclerosis: Magnetisation transfer, water diffusion and g-ratio. Neuroimage Clin 2022; 36:103228. [PMID: 36265199 PMCID: PMC9668599 DOI: 10.1016/j.nicl.2022.103228] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 10/07/2022] [Accepted: 10/08/2022] [Indexed: 11/11/2022]
Abstract
INTRODUCTION Quantitative microstructural MRI, such as myelin-sensitive magnetisation transfer ratio (MTR) or saturation (MTsat), axon-sensitive water diffusion Neurite Orientation Dispersion and Density Imaging (NODDI), and the aggregate g-ratio, may provide more specific markers of white matter integrity than conventional MRI for early patient stratification in relapsing-remitting multiple sclerosis (RRMS). The aim of this study was to determine the sensitivity of such markers to longitudinal pathological change within cerebral white matter lesions (WML) and normal-appearing white matter (NAWM) in recently diagnosed RRMS. METHODS Seventy-nine people with recently diagnosed RRMS, from the FutureMS longitudinal cohort, were recruited to an extended MRI protocol at baseline and one year later. Twelve healthy volunteers received the same MRI protocol, repeated within two weeks. Ethics approval and written informed consent were obtained. 3T MRI included magnetisation transfer, and multi-shell diffusion-weighted imaging. NAWM and whole brain were segmented from 3D T1-weighted MPRAGE, and WML from T2-weighted FLAIR. MTR, MTsat, NODDI isotropic (ISOVF) and intracellular (ICVF) volume fractions, and g-ratio (calculated from MTsat and NODDI data) were measured within WML and NAWM. Brain parenchymal fraction (BPF) was also calculated. Longitudinal change in BPF and microstructural metrics was assessed with paired t-tests (α = 0.05) and linear mixed models, adjusted for confounding factors with False Discovery Rate (FDR) correction for multiple comparisons. Longitudinal changes were compared with test-retest Bland-Altman limits of agreement from healthy control white matter. The influence of longitudinal change on g-ratio was explored through post-hoc analysis in silico by computing g-ratio with realistic simulated MTsat and NODDI values. RESULTS In NAWM, g-ratio and ICVF increased, and MTsat decreased over one year (adjusted mean difference = 0.007, 0.005, and -0.057 respectively, all FDR-corrected p < 0.05). There was no significant change in MTR, ISOVF, or BPF. In WML, MTsat, NODDI ICVF and ISOVF increased over time (adjusted mean difference = 0.083, 0.024 and 0.016, respectively, all FDR-corrected p < 0.05). Group-level longitudinal changes exceeded test-retest limits of agreement for NODDI ISOVF and ICVF in WML only. In silico analysis showed g-ratio may increase due to a decrease in MTsat or ISOVF, or an increase in ICVF. DISCUSSION G-ratio and MTsat changes in NAWM over one year may indicate subtle myelin loss in early RRMS, which were not apparent with BPF or NAWM MTR. Increases in NAWM and WML NODDI ICVF were not anticipated, and raise the possibility of axonal swelling or morphological change. Increases in WML MTsat may reflect myelin repair. Changes in NODDI ISOVF are more likely to reflect alterations in water content. Competing MTsat and ICVF changes may account for the absence of g-ratio change in WML. Longitudinal changes in microstructural measures are significant at a group level, however detection in individual patients in early RRMS is limited by technique reproducibility. CONCLUSION MTsat and g-ratio are more sensitive than MTR to early pathological changes in RRMS, but complex dependence of g-ratio on NODDI parameters limit the interpretation of aggregate measures in isolation. Improvements in technique reproducibility and validation of MRI biophysical models across a range of pathological tissue states are needed.
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Affiliation(s)
- Elizabeth N York
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom; Anne Rowling Regenerative Neurology Clinic, Edinburgh, United Kingdom.
| | - Rozanna Meijboom
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
| | - Michael J Thrippleton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
| | - Mark E Bastin
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
| | - Agniete Kampaite
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
| | - Nicole White
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
| | - Siddharthan Chandran
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Anne Rowling Regenerative Neurology Clinic, Edinburgh, United Kingdom; UK Dementia Research Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Adam D Waldman
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom.
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25
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Vaher K, Galdi P, Blesa Cabez M, Sullivan G, Stoye DQ, Quigley AJ, Thrippleton MJ, Bogaert D, Bastin ME, Cox SR, Boardman JP. General factors of white matter microstructure from DTI and NODDI in the developing brain. Neuroimage 2022; 254:119169. [PMID: 35367650 DOI: 10.1016/j.neuroimage.2022.119169] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 03/15/2022] [Accepted: 03/30/2022] [Indexed: 10/18/2022] Open
Abstract
Preterm birth is closely associated with diffuse white matter dysmaturation inferred from diffusion MRI and neurocognitive impairment in childhood. Diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) are distinct dMRI modalities, yet metrics derived from these two methods share variance across tracts. This raises the hypothesis that dimensionality reduction approaches may provide efficient whole-brain estimates of white matter microstructure that capture (dys)maturational processes. To investigate the optimal model for accurate classification of generalised white matter dysmaturation in preterm infants we assessed variation in DTI and NODDI metrics across 16 major white matter tracts using principal component analysis and structural equation modelling, in 79 term and 141 preterm infants at term equivalent age. We used logistic regression models to evaluate performances of single-metric and multimodality general factor frameworks for efficient classification of preterm infants based on variation in white matter microstructure. Single-metric general factors from DTI and NODDI capture substantial shared variance (41.8-72.5%) across 16 white matter tracts, and two multimodality factors captured 93.9% of variance shared between DTI and NODDI metrics themselves. General factors associate with preterm birth and a single model that includes all seven DTI and NODDI metrics provides the most accurate prediction of microstructural variations associated with preterm birth. This suggests that despite global covariance of dMRI metrics in neonates, each metric represents information about specific (and additive) aspects of the underlying microstructure that differ in preterm compared to term subjects.
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Affiliation(s)
- Kadi Vaher
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh EH16 4TJ, United Kingdom
| | - Paola Galdi
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh EH16 4TJ, United Kingdom
| | - Manuel Blesa Cabez
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh EH16 4TJ, United Kingdom
| | - Gemma Sullivan
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh EH16 4TJ, United Kingdom
| | - David Q Stoye
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh EH16 4TJ, United Kingdom
| | - Alan J Quigley
- Department of Paediatric Radiology, Royal Hospital for Children and Young People, Edinburgh EH16 4TJ, United Kingdom
| | - Michael J Thrippleton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, United Kingdom
| | - Debby Bogaert
- Centre for Inflammation Research, University of Edinburgh, Edinburgh EH16 4TJ, United Kingdom
| | - Mark E Bastin
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, United Kingdom
| | - Simon R Cox
- Lothian Birth Cohort Studies group, Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, United Kingdom
| | - James P Boardman
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh EH16 4TJ, United Kingdom; Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, United Kingdom.
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26
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Rzechorzek NM, Thrippleton MJ, Chappell FM, Mair G, Ercole A, Cabeleira M, Rhodes J, Marshall I, O'Neill JS. A daily temperature rhythm in the human brain predicts survival after brain injury. Brain 2022; 145:2031-2048. [PMID: 35691613 PMCID: PMC9336587 DOI: 10.1093/brain/awab466] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Revised: 11/03/2021] [Accepted: 11/20/2021] [Indexed: 02/06/2023] Open
Abstract
Patients undergo interventions to achieve a 'normal' brain temperature; a parameter that remains undefined for humans. The profound sensitivity of neuronal function to temperature implies the brain should be isothermal, but observations from patients and non-human primates suggest significant spatiotemporal variation. We aimed to determine the clinical relevance of brain temperature in patients by establishing how much it varies in healthy adults. We retrospectively screened data for all patients recruited to the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) High Resolution Intensive Care Unit Sub-Study. Only patients with direct brain temperature measurements and without targeted temperature management were included. To interpret patient analyses, we prospectively recruited 40 healthy adults (20 males, 20 females, 20-40 years) for brain thermometry using magnetic resonance spectroscopy. Participants were scanned in the morning, afternoon, and late evening of a single day. In patients (n = 114), brain temperature ranged from 32.6 to 42.3°C and mean brain temperature (38.5 ± 0.8°C) exceeded body temperature (37.5 ± 0.5°C, P < 0.0001). Of 100 patients eligible for brain temperature rhythm analysis, 25 displayed a daily rhythm, and the brain temperature range decreased in older patients (P = 0.018). In healthy participants, brain temperature ranged from 36.1 to 40.9°C; mean brain temperature (38.5 ± 0.4°C) exceeded oral temperature (36.0 ± 0.5°C) and was 0.36°C higher in luteal females relative to follicular females and males (P = 0.0006 and P < 0.0001, respectively). Temperature increased with age, most notably in deep brain regions (0.6°C over 20 years, P = 0.0002), and varied spatially by 2.41 ± 0.46°C with highest temperatures in the thalamus. Brain temperature varied by time of day, especially in deep regions (0.86°C, P = 0.0001), and was lowest at night. From the healthy data we built HEATWAVE-a 4D map of human brain temperature. Testing the clinical relevance of HEATWAVE in patients, we found that lack of a daily brain temperature rhythm increased the odds of death in intensive care 21-fold (P = 0.016), whilst absolute temperature maxima or minima did not predict outcome. A warmer mean brain temperature was associated with survival (P = 0.035), however, and ageing by 10 years increased the odds of death 11-fold (P = 0.0002). Human brain temperature is higher and varies more than previously assumed-by age, sex, menstrual cycle, brain region, and time of day. This has major implications for temperature monitoring and management, with daily brain temperature rhythmicity emerging as one of the strongest single predictors of survival after brain injury. We conclude that daily rhythmic brain temperature variation-not absolute brain temperature-is one way in which human brain physiology may be distinguished from pathophysiology.
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Affiliation(s)
| | - Michael J Thrippleton
- Edinburgh Imaging (Royal Infirmary of Edinburgh) Facility, Edinburgh EH16 4SA, UK.,Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Francesca M Chappell
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Grant Mair
- Edinburgh Imaging (Royal Infirmary of Edinburgh) Facility, Edinburgh EH16 4SA, UK.,Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Ari Ercole
- Division of Anaesthesia, University of Cambridge, Box 93 Addenbrooke's Hospital, Cambridge CB2 0QQ, UK
| | - Manuel Cabeleira
- Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Box 167, Cambridge Biomedical Campus, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK
| | | | - Jonathan Rhodes
- Department of Anaesthesia, Critical Care and Pain Medicine, NHS Lothian, Room No. S8208 (2nd Floor), Royal Infirmary of Edinburgh, Edinburgh EH16 4SA, UK
| | - Ian Marshall
- Edinburgh Imaging (Royal Infirmary of Edinburgh) Facility, Edinburgh EH16 4SA, UK.,Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - John S O'Neill
- MRC Laboratory of Molecular Biology, Cambridge CB2 0QH, UK
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27
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Wheater ENW, Galdi P, McCartney DL, Blesa M, Sullivan G, Stoye DQ, Lamb G, Sparrow S, Murphy L, Wrobel N, Quigley AJ, Semple S, Thrippleton MJ, Wardlaw JM, Bastin ME, Marioni RE, Cox SR, Boardman JP. DNA methylation in relation to gestational age and brain dysmaturation in preterm infants. Brain Commun 2022; 4:fcac056. [PMID: 35402911 PMCID: PMC8984700 DOI: 10.1093/braincomms/fcac056] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Revised: 12/10/2021] [Accepted: 03/04/2022] [Indexed: 11/14/2022] Open
Abstract
Preterm birth is associated with dysconnectivity of structural brain networks and is a leading cause of neurocognitive impairment in childhood. Variation in DNA methylation is associated with early exposure to extrauterine life but there has been little research exploring its relationship with brain development. Using genome-wide DNA methylation data from the saliva of 258 neonates, we investigated the impact of gestational age on the methylome and performed functional analysis to identify enriched gene sets from probes that contributed to differentially methylated probes or regions. We tested the hypothesis that variation in DNA methylation could underpin the association between low gestational age at birth and atypical brain development by linking differentially methylated probes with measures of white matter connectivity derived from diffusion MRI metrics: peak width skeletonized mean diffusivity, peak width skeletonized fractional anisotropy and peak width skeletonized neurite density index. Gestational age at birth was associated with widespread differential methylation at term equivalent age, with genome-wide significant associations observed for 8870 CpG probes (P < 3.6 × 10-8) and 1767 differentially methylated regions. Functional analysis identified 14 enriched gene ontology terms pertaining to cell-cell contacts and cell-extracellular matrix contacts. Principal component analysis of probes with genome-wide significance revealed a first principal component that explained 23.5% of the variance in DNA methylation, and this was negatively associated with gestational age at birth. The first principal component was associated with peak width of skeletonized mean diffusivity (β = 0.349, P = 8.37 × 10-10) and peak width skeletonized neurite density index (β = 0.364, P = 4.15 × 10-5), but not with peak width skeletonized fraction anisotropy (β = -0.035, P = 0.510); these relationships mirrored the imaging metrics' associations with gestational age at birth. Low gestational age at birth has a profound and widely distributed effect on the neonatal saliva methylome that is apparent at term equivalent age. Enriched gene ontology terms related to cell-cell contacts reveal pathways that could mediate the effect of early life environmental exposures on development. Finally, associations between differential DNA methylation and image markers of white matter tract microstructure suggest that variation in DNA methylation may provide a link between preterm birth and the dysconnectivity of developing brain networks that characterizes atypical brain development in preterm infants.
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Affiliation(s)
- Emily N. W. Wheater
- MRC Centre for Reproductive Health, The University of Edinburgh, Queen’s Medical Research Institute, Edinburgh EH16 4TJ, UK
| | - Paola Galdi
- MRC Centre for Reproductive Health, The University of Edinburgh, Queen’s Medical Research Institute, Edinburgh EH16 4TJ, UK
| | - Daniel L. McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Manuel Blesa
- MRC Centre for Reproductive Health, The University of Edinburgh, Queen’s Medical Research Institute, Edinburgh EH16 4TJ, UK
| | - Gemma Sullivan
- MRC Centre for Reproductive Health, The University of Edinburgh, Queen’s Medical Research Institute, Edinburgh EH16 4TJ, UK
| | - David Q. Stoye
- MRC Centre for Reproductive Health, The University of Edinburgh, Queen’s Medical Research Institute, Edinburgh EH16 4TJ, UK
| | - Gillian Lamb
- MRC Centre for Reproductive Health, The University of Edinburgh, Queen’s Medical Research Institute, Edinburgh EH16 4TJ, UK
| | - Sarah Sparrow
- MRC Centre for Reproductive Health, The University of Edinburgh, Queen’s Medical Research Institute, Edinburgh EH16 4TJ, UK
| | - Lee Murphy
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Nicola Wrobel
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Alan J. Quigley
- Department of Paediatric Radiology, Royal Hospital for Sick Children, NHS Lothian, Edinburgh, UK
| | - Scott Semple
- Edinburgh Imaging, University of Edinburgh, EH16 4SB Edinburgh, UK
- Centre for Cardiovascular Science, The University of Edinburgh, Queen’s Medical Research Institute, Edinburgh EH16 4TJ, UK
| | - Michael J. Thrippleton
- Edinburgh Imaging, University of Edinburgh, EH16 4SB Edinburgh, UK
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
| | - Joanna M. Wardlaw
- 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
| | - Riccardo E. Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Simon R. Cox
- Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - James P. Boardman
- MRC Centre for Reproductive Health, The University of Edinburgh, Queen’s Medical Research Institute, Edinburgh EH16 4TJ, UK
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
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Stringer MS, Heye AK, Armitage PA, Chappell F, Valdés Hernández MDC, Makin SDJ, Sakka E, Thrippleton MJ, Wardlaw JM. Tracer kinetic assessment of blood-brain barrier leakage and blood volume in cerebral small vessel disease: Associations with disease burden and vascular risk factors. Neuroimage Clin 2022; 32:102883. [PMID: 34911189 PMCID: PMC8607271 DOI: 10.1016/j.nicl.2021.102883] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Accepted: 11/16/2021] [Indexed: 12/01/2022]
Abstract
Permeability surface area (PS) was higher, even in normal appearing tissue. PS was higher in patients with more white matter hyperintensities. Tissue damage affecting vascular surface area may affect how we interpret tracer kinetic results.
Subtle blood–brain barrier (BBB) permeability increases have been shown in small vessel disease (SVD) using various analysis methods. Following recent consensus recommendations, we used Patlak tracer kinetic analysis, considered optimal in low permeability states, to quantify permeability-surface area product (PS), a BBB leakage estimate, and blood plasma volume (vP) in 201 patients with SVD who underwent dynamic contrast-enhanced MRI scans. We ran multivariable regression models with a quantitative or qualitative metric of white matter hyperintensity (WMH) severity, demographic and vascular risk factors. PS increased with WMH severity in grey (B = 0.15, Confidence Interval (CI): [0.001,0.299], p = 0.049) and normal-appearing white matter (B = 0.015, CI: [−0.008,0.308], p = 0.062). Patients with more severe WMH had lower vP in WMH (B = -0.088, CI: [−0.138,-0.039], p < 0.001), but higher vP in normal-appearing white matter (B = 0.031, CI: [−0.004,0.065], p = 0.082). PS and vP were lower at older ages in WMH, grey and white matter. We conclude higher PS in normal-appearing tissue with more severe WMH suggests impaired BBB integrity beyond visible lesions indicating that the microvasculature is compromised in normal-appearing white matter and WMH. BBB dysfunction is an important mechanism in SVD, but associations with clinical variables are complex and underlying damage affecting vascular surface area may alter interpretation of tracer kinetic results.
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Affiliation(s)
- Michael S Stringer
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK; UK DRI at the University of Edinburgh, University of Edinburgh, Edinburgh, UK
| | - Anna K Heye
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK; Edinburgh Clinical Trials Unit, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Paul A Armitage
- Academic Unit of Radiology, Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Royal Hallamshire Hospital, Sheffield, UK
| | - Francesca Chappell
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK; UK DRI at the University of Edinburgh, University of Edinburgh, Edinburgh, UK
| | - Maria Del C Valdés Hernández
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK; UK DRI at the University of Edinburgh, University of Edinburgh, Edinburgh, UK
| | | | - Eleni Sakka
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK; UK DRI at the University of Edinburgh, University of Edinburgh, Edinburgh, UK
| | - Michael J Thrippleton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK; UK DRI at the University of Edinburgh, University of Edinburgh, Edinburgh, UK.
| | - Joanna M Wardlaw
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK; UK DRI at the University of Edinburgh, University of Edinburgh, Edinburgh, UK
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York EN, Thrippleton MJ, Meijboom R, Hunt DPJ, Waldman AD. Quantitative magnetization transfer imaging in relapsing-remitting multiple sclerosis: a systematic review and meta-analysis. Brain Commun 2022; 4:fcac088. [PMID: 35652121 PMCID: PMC9149789 DOI: 10.1093/braincomms/fcac088] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 12/17/2021] [Accepted: 03/31/2022] [Indexed: 11/28/2022] Open
Abstract
Myelin-sensitive MRI such as magnetization transfer imaging has been widely used in multiple sclerosis. The influence of methodology and differences in disease subtype on imaging findings is, however, not well established. Here, we systematically review magnetization transfer brain imaging findings in relapsing-remitting multiple sclerosis. We examine how methodological differences, disease effects and their interaction influence magnetization transfer imaging measures. Articles published before 06/01/2021 were retrieved from online databases (PubMed, EMBASE and Web of Science) with search terms including 'magnetization transfer' and 'brain' for systematic review, according to a pre-defined protocol. Only studies that used human in vivo quantitative magnetization transfer imaging in adults with relapsing-remitting multiple sclerosis (with or without healthy controls) were included. Additional data from relapsing-remitting multiple sclerosis subjects acquired in other studies comprising mixed disease subtypes were included in meta-analyses. Data including sample size, MRI acquisition protocol parameters, treatments and clinical findings were extracted and qualitatively synthesized. Where possible, effect sizes were calculated for meta-analyses to determine magnetization transfer (i) differences between patients and healthy controls; (ii) longitudinal change and (iii) relationships with clinical disability in relapsing-remitting multiple sclerosis. Eighty-six studies met inclusion criteria. MRI acquisition parameters varied widely, and were also underreported. The majority of studies examined the magnetization transfer ratio in white matter, but magnetization transfer metrics, brain regions examined and results were heterogeneous. The analysis demonstrated a risk of bias due to selective reporting and small sample sizes. The pooled random-effects meta-analysis across all brain compartments revealed magnetization transfer ratio was 1.17 per cent units (95% CI -1.42 to -0.91) lower in relapsing-remitting multiple sclerosis than healthy controls (z-value: -8.99, P < 0.001, 46 studies). Linear mixed-model analysis did not show a significant longitudinal change in magnetization transfer ratio across all brain regions [β = 0.12 (-0.56 to 0.80), t-value = 0.35, P = 0.724, 14 studies] or normal-appearing white matter alone [β = 0.037 (-0.14 to 0.22), t-value = 0.41, P = 0.68, eight studies]. There was a significant negative association between the magnetization transfer ratio and clinical disability, as assessed by the Expanded Disability Status Scale [r = -0.32 (95% CI -0.46 to -0.17); z-value = -4.33, P < 0.001, 13 studies]. Evidence suggests that magnetization transfer imaging metrics are sensitive to pathological brain changes in relapsing-remitting multiple sclerosis, although effect sizes were small in comparison to inter-study variability. Recommendations include: better harmonized magnetization transfer acquisition protocols with detailed methodological reporting standards; larger, well-phenotyped cohorts, including healthy controls; and, further exploration of techniques such as magnetization transfer saturation or inhomogeneous magnetization transfer ratio.
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Affiliation(s)
- Elizabeth N. York
- Centre for Clinical Brain Sciences, University of
Edinburgh, Edinburgh, UK
- Correspondence to: Elizabeth N. York Centre for Clinical
Brain Sciences University of Edinburgh, Edinburgh BioQuarter Chancellors
Building, Edinburgh EH16 4SB, UK E-mail:
| | | | - Rozanna Meijboom
- Centre for Clinical Brain Sciences, University of
Edinburgh, Edinburgh, UK
| | - David P. J. Hunt
- Centre for Clinical Brain Sciences, University of
Edinburgh, Edinburgh, UK
- UK Dementia Research Institute, University of
Edinburgh, Edinburgh, UK
- Anne Rowling Regenerative Neurology Clinic,
University of Edinburgh, Edinburgh, UK
| | - Adam D. Waldman
- Centre for Clinical Brain Sciences, University of
Edinburgh, Edinburgh, UK
- UK Dementia Research Institute, University of
Edinburgh, Edinburgh, UK
- Correspondence may also be addressed to: Adam D. Waldman
E-mail:
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Meijboom R, Wiseman SJ, York EN, Bastin ME, Valdés Hernández MDC, Thrippleton MJ, Mollison D, White N, Kampaite A, Ng Kee Kwong K, Rodriguez Gonzalez D, Job D, Weaver C, Kearns PKA, Connick P, Chandran S, Waldman AD. Rationale and design of the brain magnetic resonance imaging protocol for FutureMS: a longitudinal multi-centre study of newly diagnosed patients with relapsing-remitting multiple sclerosis in Scotland. Wellcome Open Res 2022; 7:94. [PMID: 36865371 PMCID: PMC9971644 DOI: 10.12688/wellcomeopenres.17731.1] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/02/2022] [Indexed: 12/22/2022] Open
Abstract
Introduction: Multiple sclerosis (MS) is a chronic neuroinflammatory and neurodegenerative disease. MS prevalence varies geographically and is notably high in Scotland. Disease trajectory varies significantly between individuals and the causes for this are largely unclear. Biomarkers predictive of disease course are urgently needed to allow improved stratification for current disease modifying therapies and future targeted treatments aimed at neuroprotection and remyelination. Magnetic resonance imaging (MRI) can detect disease activity and underlying damage non-invasively in vivo at the micro and macrostructural level. FutureMS is a prospective Scottish longitudinal multi-centre cohort study, which focuses on deeply phenotyping patients with recently diagnosed relapsing-remitting MS (RRMS). Neuroimaging is a central component of the study and provides two main primary endpoints for disease activity and neurodegeneration. This paper provides an overview of MRI data acquisition, management and processing in FutureMS. FutureMS is registered with the Integrated Research Application System (IRAS, UK) under reference number 169955. Methods and analysis: MRI is performed at baseline (N=431) and 1-year follow-up, in Dundee, Glasgow and Edinburgh (3T Siemens) and in Aberdeen (3T Philips), and managed and processed in Edinburgh. The core structural MRI protocol comprises T1-weighted, T2-weighted, FLAIR and proton density images. Primary imaging outcome measures are new/enlarging white matter lesions (WML) and reduction in brain volume over one year. Secondary imaging outcome measures comprise WML volume as an additional quantitative structural MRI measure, rim lesions on susceptibility-weighted imaging, and microstructural MRI measures, including diffusion tensor imaging and neurite orientation dispersion and density imaging metrics, relaxometry, magnetisation transfer (MT) ratio, MT saturation and derived g-ratio measures. Conclusions: FutureMS aims to reduce uncertainty around disease course and allow for targeted treatment in RRMS by exploring the role of conventional and advanced MRI measures as biomarkers of disease severity and progression in a large population of RRMS patients in Scotland.
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Affiliation(s)
- Rozanna Meijboom
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Stewart J. Wiseman
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Elizabeth N. York
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Mark E. Bastin
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Maria del C. Valdés Hernández
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Michael J. Thrippleton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Daisy Mollison
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Nicole White
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Agniete Kampaite
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Koy Ng Kee Kwong
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - David Rodriguez Gonzalez
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Dominic Job
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Christine Weaver
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh, UK
| | - Patrick K. A. Kearns
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh, UK
| | - Peter Connick
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh, UK
| | - Siddharthan Chandran
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh, UK
| | - Adam D. Waldman
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
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31
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Ng Kee Kwong KC, Mollison D, Meijboom R, York EN, Kampaite A, Martin SJ, Hunt DPJ, Thrippleton MJ, Chandran S, Waldman AD. Rim lesions are demonstrated in early relapsing-remitting multiple sclerosis using 3 T-based susceptibility-weighted imaging in a multi-institutional setting. Neuroradiology 2022; 64:109-117. [PMID: 34664112 PMCID: PMC8724059 DOI: 10.1007/s00234-021-02768-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Accepted: 07/06/2021] [Indexed: 12/01/2022]
Abstract
PURPOSE Rim lesions, characterised by a paramagnetic rim on susceptibility-based MRI, have been suggested to reflect chronic inflammatory demyelination in multiple sclerosis (MS) patients. Here, we assess, through susceptibility-weighted imaging (SWI), the prevalence, longitudinal volume evolution and clinical associations of rim lesions in subjects with early relapsing-remitting MS (RRMS). METHODS Subjects (n = 44) with recently diagnosed RRMS underwent 3 T MRI at baseline (M0) and 1 year (M12) as part of a multi-centre study. SWI was acquired at M12 using a 3D segmented gradient-echo echo-planar imaging sequence. Rim lesions identified on SWI were manually segmented on FLAIR images at both time points for volumetric analysis. RESULTS Twelve subjects (27%) had at least one rim lesion at M12. A linear mixed-effects model, with 'subject' as a random factor, revealed mixed evidence for the difference in longitudinal volume change between rim lesions and non-rim lesions (p = 0.0350 and p = 0.0556 for subjects with and without rim lesions, respectively). All 25 rim lesions identified showed T1-weighted hypointense signal. Subjects with and without rim lesions did not differ significantly with respect to age, disease duration or clinical measures of disability (p > 0.05). CONCLUSION We demonstrate that rim lesions are detectable in early-stage RRMS on 3 T MRI across multiple centres, although their relationship to lesion enlargement is equivocal in this small cohort. Identification of SWI rims was subjective. Agreed criteria for defining rim lesions and their further validation as a biomarker of chronic inflammation are required for translation of SWI into routine MS clinical practice.
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Affiliation(s)
- Koy Chong Ng Kee Kwong
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh bioQuarter, Chancellor’s Building, 49 Little France Crescent, Edinburgh, EH16 4SB UK
| | - Daisy Mollison
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh bioQuarter, Chancellor’s Building, 49 Little France Crescent, Edinburgh, EH16 4SB UK
| | - Rozanna Meijboom
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh bioQuarter, Chancellor’s Building, 49 Little France Crescent, Edinburgh, EH16 4SB UK
| | - Elizabeth N. York
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh bioQuarter, Chancellor’s Building, 49 Little France Crescent, Edinburgh, EH16 4SB UK
| | - Agniete Kampaite
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh bioQuarter, Chancellor’s Building, 49 Little France Crescent, Edinburgh, EH16 4SB UK
| | | | - David P. J. Hunt
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh bioQuarter, Chancellor’s Building, 49 Little France Crescent, Edinburgh, EH16 4SB UK
| | - Michael J. Thrippleton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh bioQuarter, Chancellor’s Building, 49 Little France Crescent, Edinburgh, EH16 4SB UK
| | - Siddharthan Chandran
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh bioQuarter, Chancellor’s Building, 49 Little France Crescent, Edinburgh, EH16 4SB UK
| | - Adam D. Waldman
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh bioQuarter, Chancellor’s Building, 49 Little France Crescent, Edinburgh, EH16 4SB UK
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32
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Blair GW, Janssen E, Stringer MS, Thrippleton MJ, Chappell F, Shi Y, Hamilton I, Flaherty K, Appleton JP, Doubal FN, Bath PM, Wardlaw JM. Effects of Cilostazol and Isosorbide Mononitrate on Cerebral Hemodynamics in the LACI-1 Randomized Controlled Trial. Stroke 2021; 53:29-33. [PMID: 34847709 PMCID: PMC8700302 DOI: 10.1161/strokeaha.121.034866] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
Supplemental Digital Content is available in the text. Cerebral small vessel disease—a major cause of stroke and dementia—is associated with cerebrovascular dysfunction. We investigated whether short-term isosorbide mononitrate (ISMN) and cilostazol, alone or in combination, improved magnetic resonance imaging–measured cerebrovascular function in patients with lacunar ischemic stroke.
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Affiliation(s)
- Gordon W Blair
- Brain Research Imaging Centre, Centre for Clinical Brain Sciences, UK Dementia Institute Centre at the University of Edinburgh, United Kingdom (G.W.B., M.S.S., M.J.T., F.C., Y.S., I.H., F.N.D., J.M.W.)
| | - Esther Janssen
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Donders Centre for Medical Neuroscience, Radboud University Medical Center, Nijmegen, the Netherlands (E.J.)
| | - Michael S Stringer
- Brain Research Imaging Centre, Centre for Clinical Brain Sciences, UK Dementia Institute Centre at the University of Edinburgh, United Kingdom (G.W.B., M.S.S., M.J.T., F.C., Y.S., I.H., F.N.D., J.M.W.)
| | - Michael J Thrippleton
- Brain Research Imaging Centre, Centre for Clinical Brain Sciences, UK Dementia Institute Centre at the University of Edinburgh, United Kingdom (G.W.B., M.S.S., M.J.T., F.C., Y.S., I.H., F.N.D., J.M.W.)
| | - Francesca Chappell
- Brain Research Imaging Centre, Centre for Clinical Brain Sciences, UK Dementia Institute Centre at the University of Edinburgh, United Kingdom (G.W.B., M.S.S., M.J.T., F.C., Y.S., I.H., F.N.D., J.M.W.)
| | - Yulu Shi
- Brain Research Imaging Centre, Centre for Clinical Brain Sciences, UK Dementia Institute Centre at the University of Edinburgh, United Kingdom (G.W.B., M.S.S., M.J.T., F.C., Y.S., I.H., F.N.D., J.M.W.)
| | - Iona Hamilton
- Brain Research Imaging Centre, Centre for Clinical Brain Sciences, UK Dementia Institute Centre at the University of Edinburgh, United Kingdom (G.W.B., M.S.S., M.J.T., F.C., Y.S., I.H., F.N.D., J.M.W.)
| | - Katie Flaherty
- Stroke Trials Unit, Division of Clinical Neuroscience, University of Nottingham, United Kingdom (K.F., J.P.A., P.M.B.)
| | - Jason P Appleton
- Stroke Trials Unit, Division of Clinical Neuroscience, University of Nottingham, United Kingdom (K.F., J.P.A., P.M.B.).,Stroke, University Hospitals Birmingham NHS Foundation Trust, Queen Elizabeth Hospital, Mindelsohn Way, United Kingdom (J.P.A.)
| | - Fergus N Doubal
- Brain Research Imaging Centre, Centre for Clinical Brain Sciences, UK Dementia Institute Centre at the University of Edinburgh, United Kingdom (G.W.B., M.S.S., M.J.T., F.C., Y.S., I.H., F.N.D., J.M.W.)
| | - Philip M Bath
- Stroke Trials Unit, Division of Clinical Neuroscience, University of Nottingham, United Kingdom (K.F., J.P.A., P.M.B.).,Stroke, Queen's Medical Centre Campus, Nottingham University Hospitals NHS Trust, United Kingdom (P.M.B.)
| | - Joanna M Wardlaw
- Brain Research Imaging Centre, Centre for Clinical Brain Sciences, UK Dementia Institute Centre at the University of Edinburgh, United Kingdom (G.W.B., M.S.S., M.J.T., F.C., Y.S., I.H., F.N.D., J.M.W.)
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33
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Ng Kee Kwong KC, Mollison D, Meijboom R, York EN, Kampaite A, Martin SJ, Hunt DPJ, Thrippleton MJ, Chandran S, Waldman AD. Correction to: Rim lesions are demonstrated in early relapsing-remitting multiple sclerosis using 3 T‑based susceptibility‑weighted imaging in a multi‑institutional setting. Neuroradiology 2021; 64:211. [PMID: 34738181 DOI: 10.1007/s00234-021-02844-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Affiliation(s)
- Koy Chong Ng Kee Kwong
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh bioQuarter, Chancellor's Building, 49 Little France Crescent, Edinburgh, EH16 4SB, UK
| | - Daisy Mollison
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh bioQuarter, Chancellor's Building, 49 Little France Crescent, Edinburgh, EH16 4SB, UK
| | - Rozanna Meijboom
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh bioQuarter, Chancellor's Building, 49 Little France Crescent, Edinburgh, EH16 4SB, UK
| | - Elizabeth N York
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh bioQuarter, Chancellor's Building, 49 Little France Crescent, Edinburgh, EH16 4SB, UK
| | - Agniete Kampaite
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh bioQuarter, Chancellor's Building, 49 Little France Crescent, Edinburgh, EH16 4SB, UK
| | | | - David P J Hunt
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh bioQuarter, Chancellor's Building, 49 Little France Crescent, Edinburgh, EH16 4SB, UK
| | - Michael J Thrippleton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh bioQuarter, Chancellor's Building, 49 Little France Crescent, Edinburgh, EH16 4SB, UK
| | - Siddharthan Chandran
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh bioQuarter, Chancellor's Building, 49 Little France Crescent, Edinburgh, EH16 4SB, UK
| | - Adam D Waldman
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh bioQuarter, Chancellor's Building, 49 Little France Crescent, Edinburgh, EH16 4SB, UK.
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34
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York EN, Martin SJ, Meijboom R, Thrippleton MJ, Bastin ME, Carter E, Overell J, Connick P, Chandran S, Waldman AD, Hunt DPJ. MRI-derived g-ratio and lesion severity in newly diagnosed multiple sclerosis. Brain Commun 2021; 3:fcab249. [PMID: 34877533 PMCID: PMC8643503 DOI: 10.1093/braincomms/fcab249] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2021] [Revised: 08/24/2021] [Accepted: 08/30/2021] [Indexed: 01/19/2023] Open
Abstract
Myelin loss is associated with axonal damage in established multiple sclerosis. This relationship is challenging to study in vivo in early disease. Here, we ask whether myelin loss is associated with axonal damage at diagnosis by combining non-invasive neuroimaging and blood biomarkers. We performed quantitative microstructural MRI and single-molecule ELISA plasma neurofilament measurement in 73 patients with newly diagnosed, immunotherapy naïve relapsing-remitting multiple sclerosis. Myelin integrity was evaluated using aggregate g-ratios, derived from magnetization transfer saturation and neurite orientation dispersion and density imaging diffusion data. We found significantly higher g-ratios within cerebral white matter lesions (suggesting myelin loss) compared with normal-appearing white matter (0.61 versus 0.57, difference 0.036, 95% CI: 0.029-0.043, P < 0.001). Lesion volume (Spearman's rho rs= 0.38, P < 0.001) and g-ratio (rs= 0.24, P < 0.05) correlated independently with plasma neurofilament. In patients with substantial lesion load (n = 38), those with higher g-ratio (defined as greater than median) were more likely to have abnormally elevated plasma neurofilament than those with normal g-ratio (defined as less than median) [11/23 (48%) versus 2/15 (13%), P < 0.05]. These data suggest that, even at multiple sclerosis diagnosis, reduced myelin integrity is associated with axonal damage. MRI-derived g-ratio may provide useful additional information regarding lesion severity and help to identify individuals with a high degree of axonal damage at disease onset.
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Affiliation(s)
- Elizabeth N York
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Sarah-Jane Martin
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
- Department of Neurosciences, University of Glasgow, Glasgow G51 4LB, UK
| | - Rozanna Meijboom
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
| | | | - Mark E Bastin
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Edwin Carter
- Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - James Overell
- Department of Neurosciences, University of Glasgow, Glasgow G51 4LB, UK
| | - Peter Connick
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Siddharthan Chandran
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
- UK Dementia Research Institute, University of Edinburgh, Edinburgh EH16 4SB, UK
- Anne Rowling Clinic, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Adam D Waldman
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
- Anne Rowling Clinic, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - David P J Hunt
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
- UK Dementia Research Institute, University of Edinburgh, Edinburgh EH16 4SB, UK
- Anne Rowling Clinic, University of Edinburgh, Edinburgh EH16 4SB, UK
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Ng Kee Kwong KC, Mollison D, Meijboom R, York EN, Kampaite A, Thrippleton MJ, Chandran S, Waldman AD. The prevalence of paramagnetic rim lesions in multiple sclerosis: A systematic review and meta-analysis. PLoS One 2021; 16:e0256845. [PMID: 34495999 PMCID: PMC8425533 DOI: 10.1371/journal.pone.0256845] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Accepted: 08/17/2021] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND Recent findings from several studies have shown that paramagnetic rim lesions identified using susceptibility-based MRI could represent potential diagnostic and prognostic biomarkers in multiple sclerosis (MS). Here, we perform a systematic review and meta-analysis of the existing literature to assess their pooled prevalence at lesion-level and patient-level. METHODS Both database searching (PubMed and Embase) and handsearching were conducted to identify studies allowing the lesion-level and/or patient-level prevalence of rim lesions or chronic active lesions to be calculated. Pooled prevalence was estimated using the DerSimonian-Laird random-effects model. Subgroup analysis and meta-regression were performed to explore possible sources of heterogeneity. PROSPERO registration: CRD42020192282. RESULTS 29 studies comprising 1230 patients were eligible for analysis. Meta-analysis estimated pooled prevalences of 9.8% (95% CI: 6.6-14.2) and 40.6% (95% CI: 26.2-56.8) for rim lesions at lesion-level and patient-level, respectively. Pooled lesion-level and patient-level prevalences for chronic active lesions were 12.0% (95% CI: 9.0-15.8) and 64.8% (95% CI: 54.3-74.0), respectively. Considerable heterogeneity was observed across studies (I2>75%). Subgroup analysis revealed a significant difference in patient-level prevalence between studies conducted at 3T and 7T (p = 0.0312). Meta-regression analyses also showed significant differences in lesion-level prevalence with respect to age (p = 0.0018, R2 = 0.20) and disease duration (p = 0.0018, R2 = 0.48). Other moderator analyses demonstrated no significant differences according to MRI sequence, gender and expanded disability status scale (EDSS). CONCLUSION In this study, we show that paramagnetic rim lesions may be present in an important proportion of MS patients, notwithstanding significant variation in their assessment across studies. In view of their possible clinical relevance, we believe that clear guidelines should be introduced to standardise their assessment across research centres to in turn facilitate future analyses.
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Affiliation(s)
| | - Daisy Mollison
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Rozanna Meijboom
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Elizabeth N. York
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Agniete Kampaite
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | | | - Siddharthan Chandran
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Adam D. Waldman
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
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Stringer MS, Blair GW, Shi Y, Hamilton I, Dickie DA, Doubal FN, Marshall IM, Thrippleton MJ, Wardlaw JM. A Comparison of CVR Magnitude and Delay Assessed at 1.5 and 3T in Patients With Cerebral Small Vessel Disease. Front Physiol 2021; 12:644837. [PMID: 34149442 PMCID: PMC8207286 DOI: 10.3389/fphys.2021.644837] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Accepted: 04/15/2021] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Cerebrovascular reactivity (CVR) measures blood flow change in response to a vasoactive stimulus. Impairment is associated with several neurological conditions and can be measured using blood oxygen level-dependent (BOLD) magnetic resonance imaging (MRI). Field strength affects the BOLD signal, but the effect on CVR is unquantified in patient populations. METHODS We recruited patients with minor ischemic stroke and assessed CVR magnitude and delay time at 3 and 1.5 Tesla using BOLD MRI during a hypercapnic challenge. We assessed subcortical gray (GM) and white matter (WM) differences using Wilcoxon signed rank tests and scatterplots. Additionally, we explored associations with demographic factors, WM hyperintensity burden, and small vessel disease score. RESULTS Eighteen of twenty patients provided usable data. At 3T vs. 1.5T: mean CVR magnitude showed less variance (WM 3T: 0.062 ± 0.018%/mmHg, range 0.035, 0.093; 1.5T: 0.057 ± 0.024%/mmHg, range 0.016, 0.094) but was not systematically higher (Wilcoxon signal rank tests, WM: r = -0.33, confidence interval (CI): -0.013, 0.003, p = 0.167); delay showed similar variance (WM 3T: 40 ± 12 s, range: 12, 56; 1.5T: 31 ± 13 s, range 6, 50) and was shorter in GM (r = 0.33, CI: -2, 9, p = 0.164) and longer in WM (r = -0.59, CI: -16, -2, p = 0.010). Patients with higher disease severity tended to have lower CVR at 1.5 and 3T. CONCLUSION Mean CVR magnitude at 3T was similar to 1.5T but showed less variance. GM/WM delay differences may be affected by low signal-to-noise ratio among other factors. Although 3T may reduce variance in CVR magnitude, CVR is readily assessable at 1.5T and reveals comparable associations and trends with disease severity.
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Affiliation(s)
- Michael S. Stringer
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- UK Dementia Research Institute at the University of Edinburgh, Edinburgh, United Kingdom
| | - Gordon W. Blair
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- UK Dementia Research Institute at the University of Edinburgh, Edinburgh, United Kingdom
| | - Yulu Shi
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Beijing Tiantan Hospital Affiliated to Capital Medical University, Beijing, China
| | - Iona Hamilton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- UK Dementia Research Institute at the University of Edinburgh, Edinburgh, United Kingdom
| | - David A. Dickie
- College of Medical, Veterinary, and Life Sciences, University of Glasgow, Glasgow, United Kingdom
| | - Fergus N. Doubal
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- UK Dementia Research Institute at the University of Edinburgh, Edinburgh, United Kingdom
| | - Ian M. Marshall
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- UK Dementia Research Institute at the University of Edinburgh, Edinburgh, United Kingdom
| | - Michael J. Thrippleton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- UK Dementia Research Institute at the University of Edinburgh, Edinburgh, United Kingdom
| | - Joanna M. Wardlaw
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- UK Dementia Research Institute at the University of Edinburgh, Edinburgh, United Kingdom
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Manning C, Stringer M, Dickie B, Clancy U, Valdés Hernandez MC, Wiseman SJ, Garcia DJ, Sakka E, Backes WH, Ingrisch M, Chappell F, Doubal F, Buckley C, Parkes LM, Parker GJM, Marshall I, Wardlaw JM, Thrippleton MJ. Sources of systematic error in DCE-MRI estimation of low-level blood-brain barrier leakage. Magn Reson Med 2021; 86:1888-1903. [PMID: 34002894 DOI: 10.1002/mrm.28833] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 03/19/2021] [Accepted: 04/16/2021] [Indexed: 12/29/2022]
Abstract
PURPOSE Dynamic contrast-enhanced (DCE) -MRI with Patlak model analysis is increasingly used to quantify low-level blood-brain barrier (BBB) leakage in studies of pathophysiology. We aimed to investigate systematic errors due to physiological, experimental, and modeling factors influencing quantification of the permeability-surface area product PS and blood plasma volume vp , and to propose modifications to reduce the errors so that subtle differences in BBB permeability can be accurately measured. METHODS Simulations were performed to predict the effects of potential sources of systematic error on conventional PS and vp quantification: restricted BBB water exchange, reduced cerebral blood flow, arterial input function (AIF) delay and B 1 + error. The impact of targeted modifications to the acquisition and processing were evaluated, including: assumption of fast versus no BBB water exchange, bolus versus slow injection of contrast agent, exclusion of early data from model fitting and B 1 + correction. The optimal protocol was applied in a cohort of recent mild ischaemic stroke patients. RESULTS Simulation results demonstrated substantial systematic errors due to the factors investigated (absolute PS error ≤ 4.48 × 10-4 min-1 ). However, these were reduced (≤0.56 × 10-4 min-1 ) by applying modifications to the acquisition and processing pipeline. Processing modifications also had substantial effects on in-vivo normal-appearing white matter PS estimation (absolute change ≤ 0.45 × 10-4 min-1 ). CONCLUSION Measuring subtle BBB leakage with DCE-MRI presents unique challenges and is affected by several confounds that should be considered when acquiring or interpreting such data. The evaluated modifications should improve accuracy in studies of neurodegenerative diseases involving subtle BBB breakdown.
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Affiliation(s)
- Cameron Manning
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom.,UK Dementia Research Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Michael Stringer
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom.,UK Dementia Research Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Ben Dickie
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Una Clancy
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom.,UK Dementia Research Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Maria C Valdés Hernandez
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom.,UK Dementia Research Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Stewart J Wiseman
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom.,UK Dementia Research Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Daniela Jaime Garcia
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom.,UK Dementia Research Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Eleni Sakka
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom.,UK Dementia Research Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Walter H Backes
- Department of Radiology & Nuclear Medicine, School for Mental Health & Neuroscience and School for Cardiovascular Diseases, Maastricht University Medical Centre, Maastricht, Netherlands
| | - Michael Ingrisch
- Department of Radiology, Ludwig-Maximilians-University Hospital Munich, Munich, Germany
| | - Francesca Chappell
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom.,UK Dementia Research Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Fergus Doubal
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom.,UK Dementia Research Institute, University of Edinburgh, Edinburgh, United Kingdom
| | | | - Laura M Parkes
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Geoff J M Parker
- Centre for Medical Image Computing and Department of Neuroinflammation, UCL, London, United Kingdom
| | - Ian Marshall
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom.,UK Dementia Research Institute, University of Edinburgh, Edinburgh, United Kingdom.,Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
| | - Joanna M Wardlaw
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom.,UK Dementia Research Institute, University of Edinburgh, Edinburgh, United Kingdom.,Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
| | - Michael J Thrippleton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom.,UK Dementia Research Institute, University of Edinburgh, Edinburgh, United Kingdom.,Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
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Stewart CR, Stringer MS, Shi Y, Thrippleton MJ, Wardlaw JM. Associations Between White Matter Hyperintensity Burden, Cerebral Blood Flow and Transit Time in Small Vessel Disease: An Updated Meta-Analysis. Front Neurol 2021; 12:647848. [PMID: 34017302 PMCID: PMC8129542 DOI: 10.3389/fneur.2021.647848] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Accepted: 04/01/2021] [Indexed: 12/16/2022] Open
Abstract
Cerebral small vessel disease (SVD) is a major contributor to stroke and dementia, characterized by white matter hyperintensities (WMH) on neuroimaging. WMH are associated with reduced cerebral blood flow (CBF) cross-sectionally, though longitudinal associations remain unclear. We updated a 2016 systematic review, identifying 30 new studies, 27 cross-sectional (n = 2,956) and 3 longitudinal (n = 440). Cross-sectionally, 10/27 new studies (n = 1,019) included sufficient data for meta-analysis, which we meta-analyzed with 24 previously reported studies (n = 1,161), total 34 (n = 2,180). Our meta-analysis showed that patients with lower CBF had worse WMH burden (mean global CBF: standardized mean difference (SMD): −0.45, 95% confidence interval (CI): −0.64, −0.27). Longitudinally, associations between baseline CBF and WMH progression varied: the largest study (5 years, n = 252) found no associations, while another small study (4.5 years, n = 52) found that low CBF in the periventricular WMH penumbra predicted WMH progression. We could not meta-analyse longitudinal studies due to different statistical and methodological approaches. We found that CBF was lower in WMH than in normal-appearing white matter in an additional meta-analysis (5 cross-sectional studies; n = 295; SMD: −1.51, 95% CI: −1.94, −1.07). These findings highlight that relationships between resting CBF and WMH are complex. Further longitudinal studies analyzing regional CBF and subsequent WMH change are required to determine the role of CBF in SVD progression.
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Affiliation(s)
- Catriona R Stewart
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Michael S Stringer
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom.,UK Dementia Research Institute at the University of Edinburgh, Edinburgh Medical School, Edinburgh, United Kingdom
| | - Yulu Shi
- Beijing Tian Tan Hospital Affiliated to Capital Medical University, Beijing, China
| | - Michael J Thrippleton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom.,UK Dementia Research Institute at the University of Edinburgh, Edinburgh Medical School, Edinburgh, United Kingdom
| | - Joanna M Wardlaw
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom.,UK Dementia Research Institute at the University of Edinburgh, Edinburgh Medical School, Edinburgh, United Kingdom
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van den Brink H, Kopczak A, Arts T, Onkenhout L, Siero JC, Zwanenburg JJ, Duering M, Blair GW, Doubal FN, Stringer MS, Thrippleton MJ, Kuijf HJ, de Luca A, Hendrikse J, Wardlaw JM, Dichgans M, Biessels GJ. Zooming in on cerebral small vessel function in small vessel diseases with 7T MRI: Rationale and design of the "ZOOM@SVDs" study. Cereb Circ Cogn Behav 2021; 2:100013. [PMID: 36324717 PMCID: PMC9616370 DOI: 10.1016/j.cccb.2021.100013] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Revised: 04/14/2021] [Accepted: 04/15/2021] [Indexed: 06/01/2023]
Abstract
Background Cerebral small vessel diseases (SVDs) are a major cause of stroke and dementia. Yet, specific treatment strategies are lacking in part because of a limited understanding of the underlying disease processes. There is therefore an urgent need to study SVDs at their core, the small vessels themselves. Objective This paper presents the rationale and design of the ZOOM@SVDs study, which aims to establish measures of cerebral small vessel dysfunction on 7T MRI as novel disease markers of SVDs. Methods ZOOM@SVDs is a prospective observational cohort study with two years follow-up. ZOOM@SVDs recruits participants with Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL, N = 20), sporadic SVDs (N = 60), and healthy controls (N = 40). Participants undergo 7T brain MRI to assess different aspects of small vessel function including small vessel reactivity, cerebral perforating artery flow, and pulsatility. Extensive work-up at baseline and follow-up further includes clinical and neuropsychological assessment as well as 3T brain MRI to assess conventional SVD imaging markers. Measures of small vessel dysfunction are compared between patients and controls, and related to the severity of clinical and conventional MRI manifestations of SVDs. Discussion ZOOM@SVDs will deliver novel markers of cerebral small vessel function in patients with monogenic and sporadic forms of SVDs, and establish their relation with disease burden and progression. These small vessel markers can support etiological studies in SVDs and may serve as surrogate outcome measures in future clinical trials to show target engagement of drugs directed at the small vessels.
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Key Words
- ASL, Arterial Spin Labeling
- BOLD, Blood Oxygenation Level-Dependent
- CADASIL
- CADASIL, Cerebral Autosomal Dominant Arteriopathy with Leukoencephalopathy and Subcortical Infarcts
- CDR, Clinical Dementia Rating scale
- CERAD+, Consortium to Establish a Disease Registry for Alzheimer's Disease Plus battery
- CES-D, Center for Epidemiologic Studies Depression Scale
- CO2, Carbon Dioxide
- CSF, Cerebrospinal Fluid
- Cerebral small vessel disease
- DTI, Diffusion Tensor Imaging
- EPIC, European Prospective Investigation into Cancer and Nutrition
- EtCO2, End-tidal Carbon Dioxide
- FLAIR, Fluid Attenuated Inversion Recovery
- FOV, Field Of View
- FWHM, Full-Width-at-Half-Maximum
- GE, Gradient Echo
- GM, Grey Matter
- GPRS, General Packet Radio Service
- HRF, Hemodynamic Response Function
- High field strength MRI
- LMU, Ludwig-Maximilians-Universität
- MMSE, Mini-Mental State Examination
- NAWM, Normal Appearing White Matter
- NIHSS, National Institute for Health Stroke Scale
- PI, Pulsatility Index
- ROI, Region Of Interest
- SPPB, Short Physical Performance Battery
- SVDs, Small Vessel Diseases
- SWI, Susceptibility Weighted Imaging
- Small vessel function
- Sporadic SVD
- Stroke
- TE, Echo Time
- TI, Inversion Time
- TR, Repetition Time
- TSE, Turbo Spin Echo
- UMCU, University Medical Center Utrecht
- Vmax, Maximum velocity
- Vmean, Mean velocity
- Vmin, Minimum velocity
- WM, White Matter
- WMH, White Matter Hyperintensity
- fMRI, Functional Magnetic Resonance Imaging
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Affiliation(s)
- Hilde van den Brink
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, 3508 GA, the Netherlands
| | - Anna Kopczak
- Institute for Stroke and Dementia Research, University Hospital, Ludwig-Maximilians-Universität, Munich, Germany
| | - Tine Arts
- Department of Radiology, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Laurien Onkenhout
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, 3508 GA, the Netherlands
| | - Jeroen C.W. Siero
- Department of Radiology, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands
- Spinoza Centre for Neuroimaging Amsterdam, Amsterdam, the Netherlands
| | - Jaco J.M. Zwanenburg
- Department of Radiology, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Marco Duering
- Institute for Stroke and Dementia Research, University Hospital, Ludwig-Maximilians-Universität, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
- German Center for Neurodegenerative Disease (DZNE), Munich, Germany
| | - Gordon W. Blair
- Brain Research Imaging Centre, Centre for Clinical Brain Sciences, UK Dementia Research Institute Centre at the University of Edinburgh, Edinburgh, United Kingdom
| | - Fergus N. Doubal
- Brain Research Imaging Centre, Centre for Clinical Brain Sciences, UK Dementia Research Institute Centre at the University of Edinburgh, Edinburgh, United Kingdom
| | - Michael S. Stringer
- Brain Research Imaging Centre, Centre for Clinical Brain Sciences, UK Dementia Research Institute Centre at the University of Edinburgh, Edinburgh, United Kingdom
| | - Michael J. Thrippleton
- Brain Research Imaging Centre, Centre for Clinical Brain Sciences, UK Dementia Research Institute Centre at the University of Edinburgh, Edinburgh, United Kingdom
| | - Hugo J. Kuijf
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Alberto de Luca
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, 3508 GA, the Netherlands
- Brain Research Imaging Centre, Centre for Clinical Brain Sciences, UK Dementia Research Institute Centre at the University of Edinburgh, Edinburgh, United Kingdom
| | - Jeroen Hendrikse
- Department of Radiology, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Joanna M. Wardlaw
- Brain Research Imaging Centre, Centre for Clinical Brain Sciences, UK Dementia Research Institute Centre at the University of Edinburgh, Edinburgh, United Kingdom
| | - Martin Dichgans
- Institute for Stroke and Dementia Research, University Hospital, Ludwig-Maximilians-Universität, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
- German Center for Neurodegenerative Disease (DZNE), Munich, Germany
| | - Geert Jan Biessels
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, 3508 GA, the Netherlands
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Valdés Hernández MDC, Grimsley-Moore T, Sakka E, Thrippleton MJ, Chappell FM, Armitage PA, Makin S, Wardlaw JM. Lacunar Stroke Lesion Extent and Location and White Matter Hyperintensities Evolution 1 Year Post-lacunar Stroke. Front Neurol 2021; 12:640498. [PMID: 33746892 PMCID: PMC7976454 DOI: 10.3389/fneur.2021.640498] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Accepted: 02/08/2021] [Indexed: 11/13/2022] Open
Abstract
Lacunar strokes are a common type of ischemic stroke. They are associated with long-term disability, but the factors affecting the dynamic of the infarcted lesion and the brain imaging features associated with them, reflective of small vessel disease (SVD) severity, are still largely unknown. We investigated whether the distribution, volume and 1-year evolution of white matter hyperintensities (WMH), one of these SVD features, relate to the extent and location of these infarcts, accounting for vascular risk factors. We used imaging and clinical data from all patients [n = 118, mean age 64.9 (SD 11.75) years old] who presented to a regional hospital with a lacunar stroke syndrome within the years 2010 and 2013 and consented to participate in a study of stroke mechanisms. All patients had a brain MRI scan at presentation, and 88 had another scan 12 months after. Acute lesions (i.e., recent small subcortical infarcts, RSSI) were identified in 79 patients and lacunes in 77. Number of lacunes was associated with baseline WMH volume (B = 0.370, SE = 0.0939, P = 0.000174). RSSI volume was not associated with baseline WMH volume (B = 3.250, SE = 2.117, P = 0.129), but predicted WMH volume change (B = 2.944, SE = 0.913, P = 0.00184). RSSI location was associated with the spatial distribution of WMH and the pattern of 1-year WMH evolution. Patients with the RSSI in the centrum semiovale (n = 33) had significantly higher baseline volumes of WMH, recent and old infarcts, than patients with the RSSI located elsewhere [median 33.69, IQR (14.37 50.87) ml, 0.001 ≤ P ≤ 0.044]. But patients with the RSSI in the internal/external capsule/lentiform nucleus experienced higher increase of WMH volume after a year [n = 21, median (IQR) from 18 (11.70 31.54) ml to 27.41 (15.84 40.45) ml]. Voxel-wise analyses of WMH distribution in patients grouped per RSSI location revealed group differences increased in the presence of vascular risk factors, especially hypertension and recent or current smoking habit. In our sample of patients presenting to the clinic with lacunar strokes, lacunar strokes extent influenced WMH volume fate; and RSSI location and WMH spatial distribution and dynamics were intertwined, with differential patterns emerging in the presence of vascular risk factors. These results, if confirmed in wider samples, open potential avenues in stroke rehabilitation to be explored further.
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Affiliation(s)
| | - Tara Grimsley-Moore
- College of Medicine and Veterinary Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Eleni Sakka
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | | | - Francesca M. Chappell
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Paul A. Armitage
- Academic Unit of Radiology, University of Sheffield, Sheffield, United Kingdom
| | - Stephen Makin
- Centre for Rural Health, University of Aberdeen, Aberdeen, United Kingdom
| | - Joanna M. Wardlaw
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
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Valdés Hernández MDC, Grimsley-Moore T, Chappell FM, Thrippleton MJ, Armitage PA, Sakka E, Makin S, Wardlaw JM. Post-stroke Cognition at 1 and 3 Years Is Influenced by the Location of White Matter Hyperintensities in Patients With Lacunar Stroke. Front Neurol 2021; 12:634460. [PMID: 33732208 PMCID: PMC7956970 DOI: 10.3389/fneur.2021.634460] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2020] [Accepted: 02/05/2021] [Indexed: 12/22/2022] Open
Abstract
Lacunar strokes are a common type of ischemic stroke. They are known to have long-term cognitive deficits, but the influencing factors are still largely unknown. We investigated if the location of the index lacunar stroke or regional WMH and their change at 1 year could predict the cognitive performance at 1 and 3 years post-stroke in lacunar stroke patients. We used lacunar lesion location and WMH-segmented data from 118 patients, mean age 64.9 who had a brain MRI scan soon after presenting with symptoms, of which 88 had a repeated scan 12 months later. Premorbid intelligence (National Adult Reading Test) and current intelligence [Addenbrooke's Cognitive Exam-Revised (ACE-R)] were measured at 1, 12, and 36 months after the stroke. ANCOVA analyses adjusting for baseline cognition/premorbid intelligence, vascular risk factors, age, sex and total baseline WMH volume found that the recent small subcortical infarcts (RSSI) in the internal/external capsule/lentiform nucleus and centrum semiovale did not predict cognitive scores at 12 and 36 months. However, RSSI location moderated voxel-based associations of WMH change from baseline to 1 year with cognitive scores at 1 and 3 years. WMH increase in the external capsule, intersection between the anterior limb of the internal and external capsules, and optical radiation, was associated with worsening of ACE-R scores 1 and 3 years post-stroke after accounting for the location of the index infarct, age and baseline cognition.
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Affiliation(s)
- Maria Del C Valdés Hernández
- Centre for Clinical Brain Sciences, UK Dementia Research Institute at the University of Edinburgh, Edinburgh, United Kingdom
| | - Tara Grimsley-Moore
- College of Medicine and Veterinary Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Francesca M Chappell
- Centre for Clinical Brain Sciences, UK Dementia Research Institute at the University of Edinburgh, Edinburgh, United Kingdom
| | - Michael J Thrippleton
- Centre for Clinical Brain Sciences, UK Dementia Research Institute at the University of Edinburgh, Edinburgh, United Kingdom
| | - Paul A Armitage
- Academic Unit of Radiology, University of Sheffield, Sheffield, United Kingdom
| | - Eleni Sakka
- Centre for Clinical Brain Sciences, UK Dementia Research Institute at the University of Edinburgh, Edinburgh, United Kingdom
| | - Stephen Makin
- Centre for Rural Health, University of Aberdeen, Aberdeen, United Kingdom
| | - Joanna M Wardlaw
- Centre for Clinical Brain Sciences, UK Dementia Research Institute at the University of Edinburgh, Edinburgh, United Kingdom
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42
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Sleight E, Stringer MS, Marshall I, Wardlaw JM, Thrippleton MJ. Cerebrovascular Reactivity Measurement Using Magnetic Resonance Imaging: A Systematic Review. Front Physiol 2021; 12:643468. [PMID: 33716793 PMCID: PMC7947694 DOI: 10.3389/fphys.2021.643468] [Citation(s) in RCA: 52] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Accepted: 02/01/2021] [Indexed: 12/27/2022] Open
Abstract
Cerebrovascular reactivity (CVR) magnetic resonance imaging (MRI) probes cerebral haemodynamic changes in response to a vasodilatory stimulus. CVR closely relates to the health of the vasculature and is therefore a key parameter for studying cerebrovascular diseases such as stroke, small vessel disease and dementias. MRI allows in vivo measurement of CVR but several different methods have been presented in the literature, differing in pulse sequence, hardware requirements, stimulus and image processing technique. We systematically reviewed publications measuring CVR using MRI up to June 2020, identifying 235 relevant papers. We summarised the acquisition methods, experimental parameters, hardware and CVR quantification approaches used, clinical populations investigated, and corresponding summary CVR measures. CVR was investigated in many pathologies such as steno-occlusive diseases, dementia and small vessel disease and is generally lower in patients than in healthy controls. Blood oxygen level dependent (BOLD) acquisitions with fixed inspired CO2 gas or end-tidal CO2 forcing stimulus are the most commonly used methods. General linear modelling of the MRI signal with end-tidal CO2 as the regressor is the most frequently used method to compute CVR. Our survey of CVR measurement approaches and applications will help researchers to identify good practice and provide objective information to inform the development of future consensus recommendations.
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Affiliation(s)
- Emilie Sleight
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom,UK Dementia Research Institute, Edinburgh, United Kingdom
| | - Michael S. Stringer
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom,UK Dementia Research Institute, Edinburgh, United Kingdom,*Correspondence: Michael S. Stringer
| | - Ian Marshall
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom,UK Dementia Research Institute, Edinburgh, United Kingdom
| | - Joanna M. Wardlaw
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom,UK Dementia Research Institute, Edinburgh, United Kingdom
| | - Michael J. Thrippleton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom,UK Dementia Research Institute, Edinburgh, United Kingdom
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43
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Morgan AG, Thrippleton MJ, Wardlaw JM, Marshall I. 4D flow MRI for non-invasive measurement of blood flow in the brain: A systematic review. J Cereb Blood Flow Metab 2021; 41:206-218. [PMID: 32936731 PMCID: PMC8369999 DOI: 10.1177/0271678x20952014] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/13/2020] [Revised: 06/22/2020] [Accepted: 07/05/2020] [Indexed: 01/25/2023]
Abstract
The brain's vasculature is essential for brain health and its dysfunction contributes to the onset and development of many dementias and neurological disorders. While numerous in vivo imaging techniques exist to investigate cerebral haemodynamics in humans, phase-contrast magnetic resonance imaging (MRI) has emerged as a reliable, non-invasive method of quantifying blood flow within intracranial vessels. In recent years, an advanced form of this method, known as 4D flow, has been developed and utilised in patient studies, where its ability to capture complex blood flow dynamics within any major vessel across the acquired volume has proved effective in collecting large amounts of information in a single scan. While extremely promising as a method of examining the vascular system's role in brain-related diseases, the collection of 4D data can be time-consuming, meaning data quality has to be traded off against the acquisition time. Here, we review the available literature to examine 4D flow's capabilities in assessing physiological and pathological features of the cerebrovascular system. Emerging techniques such as dynamic velocity-encoding and advanced undersampling methods, combined with increasingly high-field MRI scanners, are likely to bring 4D flow to the forefront of cerebrovascular imaging studies in the years to come.
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Affiliation(s)
- Alasdair G Morgan
- Brain Research Imaging Centre, Centre for Clinical Brain
Sciences, University of Edinburgh, Edinburgh, UK
- UK Dementia Research Institute at The University of Edinburgh,
Edinburgh Medical School, Edinburgh, UK
| | - Michael J Thrippleton
- Brain Research Imaging Centre, Centre for Clinical Brain
Sciences, University of Edinburgh, Edinburgh, UK
- UK Dementia Research Institute at The University of Edinburgh,
Edinburgh Medical School, Edinburgh, UK
| | - Joanna M Wardlaw
- Brain Research Imaging Centre, Centre for Clinical Brain
Sciences, University of Edinburgh, Edinburgh, UK
- UK Dementia Research Institute at The University of Edinburgh,
Edinburgh Medical School, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology,
University of Edinburgh, Edinburgh, UK
| | - Ian Marshall
- Brain Research Imaging Centre, Centre for Clinical Brain
Sciences, University of Edinburgh, Edinburgh, UK
- UK Dementia Research Institute at The University of Edinburgh,
Edinburgh Medical School, Edinburgh, UK
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44
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Bernal J, Valdés-Hernández MDC, Escudero J, Heye AK, Sakka E, Armitage PA, Makin S, Touyz RM, Wardlaw JM, Thrippleton MJ. A four-dimensional computational model of dynamic contrast-enhanced magnetic resonance imaging measurement of subtle blood-brain barrier leakage. Neuroimage 2021; 230:117786. [PMID: 33497771 PMCID: PMC8065875 DOI: 10.1016/j.neuroimage.2021.117786] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2020] [Revised: 12/17/2020] [Accepted: 01/19/2021] [Indexed: 01/24/2023] Open
Abstract
Dynamic contrast-enhanced MRI (DCE-MRI) is increasingly used to quantify and map the spatial distribution of blood-brain barrier (BBB) leakage in neurodegenerative disease, including cerebral small vessel disease and dementia. However, the subtle nature of leakage and resulting small signal changes make quantification challenging. While simplified one-dimensional simulations have probed the impact of noise, scanner drift, and model assumptions, the impact of spatio-temporal effects such as gross motion, k-space sampling and motion artefacts on parametric leakage maps has been overlooked. Moreover, evidence on which to base the design of imaging protocols is lacking due to practical difficulties and the lack of a reference method. To address these problems, we present an open-source computational model of the DCE-MRI acquisition process for generating four dimensional Digital Reference Objects (DROs), using a high-resolution brain atlas and incorporating realistic patient motion, extra-cerebral signals, noise and k-space sampling. Simulations using the DROs demonstrated a dominant influence of spatio-temporal effects on both the visual appearance of parameter maps and on measured tissue leakage rates. The computational model permits greater understanding of the sensitivity and limitations of subtle BBB leakage measurement and provides a non-invasive means of testing and optimising imaging protocols for future studies.
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Affiliation(s)
- Jose Bernal
- Centre for Clinical Brain Sciences, Dementia Research Institute, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Maria D C Valdés-Hernández
- Centre for Clinical Brain Sciences, Dementia Research Institute, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Javier Escudero
- School of Engineering, University of Edinburgh, Edinburgh EH9 3FB, UK
| | - Anna K Heye
- Centre for Clinical Brain Sciences, Dementia Research Institute, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Eleni Sakka
- Centre for Clinical Brain Sciences, Dementia Research Institute, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Paul A Armitage
- Academic Unit of Radiology, University of Sheffield, Sheffield S10 2RX, UK
| | - Stephen Makin
- University of Aberdeen, Centre for Rural Health, Inverness, UK
| | - Rhian M Touyz
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow G12 8TA, UK
| | - Joanna M Wardlaw
- Centre for Clinical Brain Sciences, Dementia Research Institute, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Michael J Thrippleton
- Centre for Clinical Brain Sciences, Dementia Research Institute, University of Edinburgh, Edinburgh EH16 4SB, UK.
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45
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Blesa M, Galdi P, Cox SR, Sullivan G, Stoye DQ, Lamb GJ, Quigley AJ, Thrippleton MJ, Escudero J, Bastin ME, Smith KM, Boardman JP. Hierarchical Complexity of the Macro-Scale Neonatal Brain. Cereb Cortex 2020; 31:2071-2084. [PMID: 33280008 PMCID: PMC7945030 DOI: 10.1093/cercor/bhaa345] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023] Open
Abstract
The human adult structural connectome has a rich nodal hierarchy, with highly diverse connectivity patterns aligned to the diverse range of functional specializations in the brain. The emergence of this hierarchical complexity in human development is unknown. Here, we substantiate the hierarchical tiers and hierarchical complexity of brain networks in the newborn period, assess correspondences with hierarchical complexity in adulthood, and investigate the effect of preterm birth, a leading cause of atypical brain development and later neurocognitive impairment, on hierarchical complexity. We report that neonatal and adult structural connectomes are both composed of distinct hierarchical tiers and that hierarchical complexity is greater in term born neonates than in preterms. This is due to diversity of connectivity patterns of regions within the intermediate tiers, which consist of regions that underlie sensorimotor processing and its integration with cognitive information. For neonates and adults, the highest tier (hub regions) is ordered, rather than complex, with more homogeneous connectivity patterns in structural hubs. This suggests that the brain develops first a more rigid structure in hub regions allowing for the development of greater and more diverse functional specialization in lower level regions, while connectivity underpinning this diversity is dysmature in infants born preterm.
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Affiliation(s)
- Manuel Blesa
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh EH16 4TJ, UK
| | - Paola Galdi
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh EH16 4TJ, UK
| | - Simon R Cox
- Lothian Birth Cohorts Group, Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, UK
| | - Gemma Sullivan
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh EH16 4TJ, UK
| | - David Q Stoye
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh EH16 4TJ, UK
| | - Gillian J Lamb
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh EH16 4TJ, UK
| | - Alan J Quigley
- Department of Radiology, Royal Hospital for Sick Children, Edinburgh EH9 1LF, UK
| | - Michael J Thrippleton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK.,Edinburgh Imaging, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Javier Escudero
- School of Engineering, Institute for Digital Communications, University of Edinburgh, Edinburgh EH9 3FG, UK
| | - Mark E Bastin
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Keith M Smith
- Usher Institute, University of Edinburgh, Edinburgh EH16 4UX, UK.,Health Data Research UK, London NW1 2BE, UK
| | - James P Boardman
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh EH16 4TJ, UK.,Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
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46
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Stoye DQ, Blesa M, Sullivan G, Galdi P, Lamb GJ, Black GS, Quigley AJ, Thrippleton MJ, Bastin ME, Reynolds RM, Boardman JP. Maternal cortisol is associated with neonatal amygdala microstructure and connectivity in a sexually dimorphic manner. eLife 2020; 9:60729. [PMID: 33228850 PMCID: PMC7685701 DOI: 10.7554/elife.60729] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2020] [Accepted: 10/25/2020] [Indexed: 12/21/2022] Open
Abstract
The mechanisms linking maternal stress in pregnancy with infant neurodevelopment in a sexually dimorphic manner are poorly understood. We tested the hypothesis that maternal hypothalamic-pituitary-adrenal axis activity, measured by hair cortisol concentration (HCC), is associated with microstructure, structural connectivity, and volume of the infant amygdala. In 78 mother-infant dyads, maternal hair was sampled postnatally, and infants underwent magnetic resonance imaging at term-equivalent age. We found a relationship between maternal HCC and amygdala development that differed according to infant sex. Higher HCC was associated with higher left amygdala fractional anisotropy (β = 0.677, p=0.010), lower left amygdala orientation dispersion index (β = −0.597, p=0.034), and higher fractional anisotropy in connections between the right amygdala and putamen (β = 0.475, p=0.007) in girls compared to boys. Furthermore, altered amygdala microstructure was only observed in boys, with connectivity changes restricted to girls. Maternal cortisol during pregnancy is related to newborn amygdala architecture and connectivity in a sexually dimorphic manner. Given the fundamental role of the amygdala in the emergence of emotion regulation, these findings offer new insights into mechanisms linking maternal health with neuropsychiatric outcomes of children. Stress during pregnancy, for example because of mental or physical disorders, can have long-term effects on child development. Epidemiological studies have shown that individuals exposed to stress in the womb are at higher risk of developmental and mood conditions, such as ADHD and depression. This effect is different between the sexes, and the biological mechanisms that underpin these observations are poorly understood. One possibility is that a baby’s developing amygdala, the part of the brain that processes emotions, is affected by a signal known as cortisol. This hormone is best known for its role in coordinating the stress response, but it also directs the growth of a fetus. Tracking fetal amygdala changes as well as cortisol levels in the pregnant individual could explain how stress during pregnancy affects development. To investigate, Stoye et al. recruited nearly 80 volunteers and their newborn children. MRI scans were used to examine the structure of the amygdala, and how it is connected to other parts of the brain. In parallel, the amount of cortisol was measured in hair samples collected from the volunteers around the time of birth, which reflects stress levels during the final three months of pregnancy. Linking the brain imaging results to the volunteers’ cortisol levels showed that being exposed to higher cortisol levels in the womb affected babies in different ways based on their sex: boys showed alterations in the fine structure of their amygdala, while girls displayed changes in the way that brain region connected to other neural networks. The work by Stoye et al. potentially reveals a biological mechanism by which early exposure to stress could affect brain development differently between the sexes, potentially informing real-world interventions.
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Affiliation(s)
- David Q Stoye
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, United Kingdom
| | - Manuel Blesa
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, United Kingdom
| | - Gemma Sullivan
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, United Kingdom
| | - Paola Galdi
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, United Kingdom
| | - Gillian J Lamb
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, United Kingdom
| | - Gill S Black
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, United Kingdom
| | - Alan J Quigley
- Department of Radiology, Royal Hospital for Sick Children, Edinburgh, United Kingdom
| | - Michael J Thrippleton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Mark E Bastin
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Rebecca M Reynolds
- Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, United Kingdom
| | - James P Boardman
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, United Kingdom.,Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
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47
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Clancy U, Garcia DJ, Stringer MS, Thrippleton MJ, Valdés-Hernández MC, Wiseman S, Hamilton OK, Chappell FM, Brown R, Blair GW, Hewins W, Sleight E, Ballerini L, Bastin ME, Maniega SM, MacGillivray T, Hetherington K, Hamid C, Arteaga C, Morgan AG, Manning C, Backhouse E, Hamilton I, Job D, Marshall I, Doubal FN, Wardlaw JM. Rationale and design of a longitudinal study of cerebral small vessel diseases, clinical and imaging outcomes in patients presenting with mild ischaemic stroke: Mild Stroke Study 3. Eur Stroke J 2020; 6:81-88. [PMID: 33817338 PMCID: PMC7995323 DOI: 10.1177/2396987320929617] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Accepted: 04/14/2020] [Indexed: 12/21/2022] Open
Abstract
Background Cerebral small vessel disease is a major cause of dementia and stroke, visible on brain magnetic resonance imaging. Recent data suggest that small vessel disease lesions may be dynamic, damage extends into normal-appearing brain and microvascular dysfunctions include abnormal blood–brain barrier leakage, vasoreactivity and pulsatility, but much remains unknown regarding underlying pathophysiology, symptoms, clinical features and risk factors of small vessel disease. Patients and Methods: The Mild Stroke Study 3 is a prospective observational cohort study to identify risk factors for and clinical implications of small vessel disease progression and regression among up to 300 adults with non-disabling stroke. We perform detailed serial clinical, cognitive, lifestyle, physiological, retinal and brain magnetic resonance imaging assessments over one year; we assess cerebrovascular reactivity, blood flow, pulsatility and blood–brain barrier leakage on magnetic resonance imaging at baseline; we follow up to four years by post and phone. The study is registered ISRCTN 12113543. Summary Factors which influence direction and rate of change of small vessel disease lesions are poorly understood. We investigate the role of small vessel dysfunction using advanced serial neuroimaging in a deeply phenotyped cohort to increase understanding of the natural history of small vessel disease, identify those at highest risk of early disease progression or regression and uncover novel targets for small vessel disease prevention and therapy.
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Affiliation(s)
- Una Clancy
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | | | - Michael S Stringer
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | | | | | - Stewart Wiseman
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Olivia Kl Hamilton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | | | - Rosalind Brown
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Gordon W Blair
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Will Hewins
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Emilie Sleight
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Lucia Ballerini
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Mark E Bastin
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | | | - Tom MacGillivray
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | | | - Charlene Hamid
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Carmen Arteaga
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Alasdair G Morgan
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Cameron Manning
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Ellen Backhouse
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Iona Hamilton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Dominic Job
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Ian Marshall
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Fergus N Doubal
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Joanna M Wardlaw
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
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48
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Blair GW, Thrippleton MJ, Shi Y, Hamilton I, Stringer M, Chappell F, Dickie DA, Andrews P, Marshall I, Doubal FN, Wardlaw JM. Intracranial hemodynamic relationships in patients with cerebral small vessel disease. Neurology 2020; 94:e2258-e2269. [PMID: 32366534 PMCID: PMC7357294 DOI: 10.1212/wnl.0000000000009483] [Citation(s) in RCA: 76] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2019] [Accepted: 12/10/2019] [Indexed: 02/06/2023] Open
Abstract
Objective To investigate cerebrovascular reactivity (CVR), blood flow, vascular and CSF pulsatility, and their independent relationship with cerebral small vessel disease (SVD) features in patients with minor ischemic stroke and MRI evidence of SVD. Methods We recruited patients with minor ischemic stroke and assessed CVR using blood oxygen level–dependent MRI during a hypercapnic challenge, cerebral blood flow (CBF), vascular and CSF pulsatility using phase-contrast MRI, and structural magnetic resonance brain imaging to quantify white matter hyperintensities (WMHs) and perivascular spaces (PVSs). We used multiple regression to identify parameters associated with SVD features, controlling for patient characteristics. Results Fifty-three of 60 patients completed the study with a full data set (age 68.0% ± 8.8 years, 74% male, 75% hypertensive). After controlling for age, sex, and systolic blood pressure, lower white matter CVR was associated with higher WMH volume (−0.01%/mm Hg per log10 increase in WMH volume, p = 0.02), basal ganglia PVS (−0.01%/mm Hg per point increase in the PVS score, p = 0.02), and higher venous pulsatility (superior sagittal sinus −0.03%/mm Hg, p = 0.02, per unit increase in the pulsatility index) but not with CBF (p = 0.58). Lower foramen magnum CSF stroke volume was associated with worse white matter CVR (0.04%/mm Hg per mL increase in stroke volume, p = 0.04) and more severe basal ganglia PVS (p = 0.09). Conclusions Lower CVR, higher venous pulsatility, and lower foramen magnum CSF stroke volume indicate that dynamic vascular dysfunctions underpin PVS dysfunction and WMH development. Further exploration of microvascular dysfunction and CSF dynamics may uncover new mechanisms and intervention targets to reduce SVD lesion development, cognitive decline, and stroke.
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Affiliation(s)
- Gordon W Blair
- From the Brain Research Imaging Centre (G.W.B., M.J.T., Y.S., I.H., M.S., F.C., P.A., I.M., F.N.D., J.M.W.), Centre for Clinical Brain Sciences, University of Edinburgh, United Kingdom; UK Dementia Research Institute at The University of Edinburgh (G.W.B., M.J.T., Y.S., I.H., M.S., F.N.D., J.M.W.), Edinburgh Medical School, United Kingdom; Beijing Tiantan Hospital Affiliated to Capital Medical University (Y.S.), China; Institute of Cardiovascular and Medical Sciences (D.A.D.), University of Glasgow, United Kingdom; and Centre for Cognitive Ageing and Cognitive Epidemiology (J.M.W.), University of Edinburgh, United Kingdom
| | - Michael J Thrippleton
- From the Brain Research Imaging Centre (G.W.B., M.J.T., Y.S., I.H., M.S., F.C., P.A., I.M., F.N.D., J.M.W.), Centre for Clinical Brain Sciences, University of Edinburgh, United Kingdom; UK Dementia Research Institute at The University of Edinburgh (G.W.B., M.J.T., Y.S., I.H., M.S., F.N.D., J.M.W.), Edinburgh Medical School, United Kingdom; Beijing Tiantan Hospital Affiliated to Capital Medical University (Y.S.), China; Institute of Cardiovascular and Medical Sciences (D.A.D.), University of Glasgow, United Kingdom; and Centre for Cognitive Ageing and Cognitive Epidemiology (J.M.W.), University of Edinburgh, United Kingdom
| | - Yulu Shi
- From the Brain Research Imaging Centre (G.W.B., M.J.T., Y.S., I.H., M.S., F.C., P.A., I.M., F.N.D., J.M.W.), Centre for Clinical Brain Sciences, University of Edinburgh, United Kingdom; UK Dementia Research Institute at The University of Edinburgh (G.W.B., M.J.T., Y.S., I.H., M.S., F.N.D., J.M.W.), Edinburgh Medical School, United Kingdom; Beijing Tiantan Hospital Affiliated to Capital Medical University (Y.S.), China; Institute of Cardiovascular and Medical Sciences (D.A.D.), University of Glasgow, United Kingdom; and Centre for Cognitive Ageing and Cognitive Epidemiology (J.M.W.), University of Edinburgh, United Kingdom
| | - Iona Hamilton
- From the Brain Research Imaging Centre (G.W.B., M.J.T., Y.S., I.H., M.S., F.C., P.A., I.M., F.N.D., J.M.W.), Centre for Clinical Brain Sciences, University of Edinburgh, United Kingdom; UK Dementia Research Institute at The University of Edinburgh (G.W.B., M.J.T., Y.S., I.H., M.S., F.N.D., J.M.W.), Edinburgh Medical School, United Kingdom; Beijing Tiantan Hospital Affiliated to Capital Medical University (Y.S.), China; Institute of Cardiovascular and Medical Sciences (D.A.D.), University of Glasgow, United Kingdom; and Centre for Cognitive Ageing and Cognitive Epidemiology (J.M.W.), University of Edinburgh, United Kingdom
| | - Michael Stringer
- From the Brain Research Imaging Centre (G.W.B., M.J.T., Y.S., I.H., M.S., F.C., P.A., I.M., F.N.D., J.M.W.), Centre for Clinical Brain Sciences, University of Edinburgh, United Kingdom; UK Dementia Research Institute at The University of Edinburgh (G.W.B., M.J.T., Y.S., I.H., M.S., F.N.D., J.M.W.), Edinburgh Medical School, United Kingdom; Beijing Tiantan Hospital Affiliated to Capital Medical University (Y.S.), China; Institute of Cardiovascular and Medical Sciences (D.A.D.), University of Glasgow, United Kingdom; and Centre for Cognitive Ageing and Cognitive Epidemiology (J.M.W.), University of Edinburgh, United Kingdom
| | - Francesca Chappell
- From the Brain Research Imaging Centre (G.W.B., M.J.T., Y.S., I.H., M.S., F.C., P.A., I.M., F.N.D., J.M.W.), Centre for Clinical Brain Sciences, University of Edinburgh, United Kingdom; UK Dementia Research Institute at The University of Edinburgh (G.W.B., M.J.T., Y.S., I.H., M.S., F.N.D., J.M.W.), Edinburgh Medical School, United Kingdom; Beijing Tiantan Hospital Affiliated to Capital Medical University (Y.S.), China; Institute of Cardiovascular and Medical Sciences (D.A.D.), University of Glasgow, United Kingdom; and Centre for Cognitive Ageing and Cognitive Epidemiology (J.M.W.), University of Edinburgh, United Kingdom
| | - David Alexander Dickie
- From the Brain Research Imaging Centre (G.W.B., M.J.T., Y.S., I.H., M.S., F.C., P.A., I.M., F.N.D., J.M.W.), Centre for Clinical Brain Sciences, University of Edinburgh, United Kingdom; UK Dementia Research Institute at The University of Edinburgh (G.W.B., M.J.T., Y.S., I.H., M.S., F.N.D., J.M.W.), Edinburgh Medical School, United Kingdom; Beijing Tiantan Hospital Affiliated to Capital Medical University (Y.S.), China; Institute of Cardiovascular and Medical Sciences (D.A.D.), University of Glasgow, United Kingdom; and Centre for Cognitive Ageing and Cognitive Epidemiology (J.M.W.), University of Edinburgh, United Kingdom
| | - Peter Andrews
- From the Brain Research Imaging Centre (G.W.B., M.J.T., Y.S., I.H., M.S., F.C., P.A., I.M., F.N.D., J.M.W.), Centre for Clinical Brain Sciences, University of Edinburgh, United Kingdom; UK Dementia Research Institute at The University of Edinburgh (G.W.B., M.J.T., Y.S., I.H., M.S., F.N.D., J.M.W.), Edinburgh Medical School, United Kingdom; Beijing Tiantan Hospital Affiliated to Capital Medical University (Y.S.), China; Institute of Cardiovascular and Medical Sciences (D.A.D.), University of Glasgow, United Kingdom; and Centre for Cognitive Ageing and Cognitive Epidemiology (J.M.W.), University of Edinburgh, United Kingdom
| | - Ian Marshall
- From the Brain Research Imaging Centre (G.W.B., M.J.T., Y.S., I.H., M.S., F.C., P.A., I.M., F.N.D., J.M.W.), Centre for Clinical Brain Sciences, University of Edinburgh, United Kingdom; UK Dementia Research Institute at The University of Edinburgh (G.W.B., M.J.T., Y.S., I.H., M.S., F.N.D., J.M.W.), Edinburgh Medical School, United Kingdom; Beijing Tiantan Hospital Affiliated to Capital Medical University (Y.S.), China; Institute of Cardiovascular and Medical Sciences (D.A.D.), University of Glasgow, United Kingdom; and Centre for Cognitive Ageing and Cognitive Epidemiology (J.M.W.), University of Edinburgh, United Kingdom
| | - Fergus N Doubal
- From the Brain Research Imaging Centre (G.W.B., M.J.T., Y.S., I.H., M.S., F.C., P.A., I.M., F.N.D., J.M.W.), Centre for Clinical Brain Sciences, University of Edinburgh, United Kingdom; UK Dementia Research Institute at The University of Edinburgh (G.W.B., M.J.T., Y.S., I.H., M.S., F.N.D., J.M.W.), Edinburgh Medical School, United Kingdom; Beijing Tiantan Hospital Affiliated to Capital Medical University (Y.S.), China; Institute of Cardiovascular and Medical Sciences (D.A.D.), University of Glasgow, United Kingdom; and Centre for Cognitive Ageing and Cognitive Epidemiology (J.M.W.), University of Edinburgh, United Kingdom
| | - Joanna M Wardlaw
- From the Brain Research Imaging Centre (G.W.B., M.J.T., Y.S., I.H., M.S., F.C., P.A., I.M., F.N.D., J.M.W.), Centre for Clinical Brain Sciences, University of Edinburgh, United Kingdom; UK Dementia Research Institute at The University of Edinburgh (G.W.B., M.J.T., Y.S., I.H., M.S., F.N.D., J.M.W.), Edinburgh Medical School, United Kingdom; Beijing Tiantan Hospital Affiliated to Capital Medical University (Y.S.), China; Institute of Cardiovascular and Medical Sciences (D.A.D.), University of Glasgow, United Kingdom; and Centre for Cognitive Ageing and Cognitive Epidemiology (J.M.W.), University of Edinburgh, United Kingdom.
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Jochems ACC, Blair GW, Stringer MS, Thrippleton MJ, Clancy U, Chappell FM, Brown R, Jaime Garcia D, Hamilton OKL, Morgan AG, Marshall I, Hetherington K, Wiseman S, MacGillivray T, Valdés-Hernández MC, Doubal FN, Wardlaw JM. Relationship Between Venules and Perivascular Spaces in Sporadic Small Vessel Diseases. Stroke 2020; 51:1503-1506. [PMID: 32264759 PMCID: PMC7185057 DOI: 10.1161/strokeaha.120.029163] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Supplemental Digital Content is available in the text. Perivascular spaces (PVS) around venules may help drain interstitial fluid from the brain. We examined relationships between suspected venules and PVS visible on brain magnetic resonance imaging.
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Affiliation(s)
- Angela C C Jochems
- From the Centre for Clinical Brain Sciences (A.C.C.J., G.W.B., M.S.S., M.J.T., U.C., F.M.C., R.B., D.J.G., O.K.L.H., A.G.M., I.M., K.H., S.W., T.M., M.C.V.-H., F.N.D., J.M.W.), University of Edinburgh, Scotland.,UK Dementia Research Institute (A.C.C.J., G.W.B., M.S.S., M.J.T., U.C., F.M.C., D.J.G., O.K.L.H., S.W., M.C.V.-H., F.N.D., J.M.W.), University of Edinburgh, Scotland
| | - Gordon W Blair
- From the Centre for Clinical Brain Sciences (A.C.C.J., G.W.B., M.S.S., M.J.T., U.C., F.M.C., R.B., D.J.G., O.K.L.H., A.G.M., I.M., K.H., S.W., T.M., M.C.V.-H., F.N.D., J.M.W.), University of Edinburgh, Scotland.,UK Dementia Research Institute (A.C.C.J., G.W.B., M.S.S., M.J.T., U.C., F.M.C., D.J.G., O.K.L.H., S.W., M.C.V.-H., F.N.D., J.M.W.), University of Edinburgh, Scotland
| | - Michael S Stringer
- From the Centre for Clinical Brain Sciences (A.C.C.J., G.W.B., M.S.S., M.J.T., U.C., F.M.C., R.B., D.J.G., O.K.L.H., A.G.M., I.M., K.H., S.W., T.M., M.C.V.-H., F.N.D., J.M.W.), University of Edinburgh, Scotland.,UK Dementia Research Institute (A.C.C.J., G.W.B., M.S.S., M.J.T., U.C., F.M.C., D.J.G., O.K.L.H., S.W., M.C.V.-H., F.N.D., J.M.W.), University of Edinburgh, Scotland
| | - Michael J Thrippleton
- From the Centre for Clinical Brain Sciences (A.C.C.J., G.W.B., M.S.S., M.J.T., U.C., F.M.C., R.B., D.J.G., O.K.L.H., A.G.M., I.M., K.H., S.W., T.M., M.C.V.-H., F.N.D., J.M.W.), University of Edinburgh, Scotland.,UK Dementia Research Institute (A.C.C.J., G.W.B., M.S.S., M.J.T., U.C., F.M.C., D.J.G., O.K.L.H., S.W., M.C.V.-H., F.N.D., J.M.W.), University of Edinburgh, Scotland
| | - Una Clancy
- From the Centre for Clinical Brain Sciences (A.C.C.J., G.W.B., M.S.S., M.J.T., U.C., F.M.C., R.B., D.J.G., O.K.L.H., A.G.M., I.M., K.H., S.W., T.M., M.C.V.-H., F.N.D., J.M.W.), University of Edinburgh, Scotland.,UK Dementia Research Institute (A.C.C.J., G.W.B., M.S.S., M.J.T., U.C., F.M.C., D.J.G., O.K.L.H., S.W., M.C.V.-H., F.N.D., J.M.W.), University of Edinburgh, Scotland
| | - Francesca M Chappell
- From the Centre for Clinical Brain Sciences (A.C.C.J., G.W.B., M.S.S., M.J.T., U.C., F.M.C., R.B., D.J.G., O.K.L.H., A.G.M., I.M., K.H., S.W., T.M., M.C.V.-H., F.N.D., J.M.W.), University of Edinburgh, Scotland.,UK Dementia Research Institute (A.C.C.J., G.W.B., M.S.S., M.J.T., U.C., F.M.C., D.J.G., O.K.L.H., S.W., M.C.V.-H., F.N.D., J.M.W.), University of Edinburgh, Scotland
| | - Rosalind Brown
- From the Centre for Clinical Brain Sciences (A.C.C.J., G.W.B., M.S.S., M.J.T., U.C., F.M.C., R.B., D.J.G., O.K.L.H., A.G.M., I.M., K.H., S.W., T.M., M.C.V.-H., F.N.D., J.M.W.), University of Edinburgh, Scotland
| | - Daniela Jaime Garcia
- From the Centre for Clinical Brain Sciences (A.C.C.J., G.W.B., M.S.S., M.J.T., U.C., F.M.C., R.B., D.J.G., O.K.L.H., A.G.M., I.M., K.H., S.W., T.M., M.C.V.-H., F.N.D., J.M.W.), University of Edinburgh, Scotland.,UK Dementia Research Institute (A.C.C.J., G.W.B., M.S.S., M.J.T., U.C., F.M.C., D.J.G., O.K.L.H., S.W., M.C.V.-H., F.N.D., J.M.W.), University of Edinburgh, Scotland
| | - Olivia K L Hamilton
- From the Centre for Clinical Brain Sciences (A.C.C.J., G.W.B., M.S.S., M.J.T., U.C., F.M.C., R.B., D.J.G., O.K.L.H., A.G.M., I.M., K.H., S.W., T.M., M.C.V.-H., F.N.D., J.M.W.), University of Edinburgh, Scotland.,UK Dementia Research Institute (A.C.C.J., G.W.B., M.S.S., M.J.T., U.C., F.M.C., D.J.G., O.K.L.H., S.W., M.C.V.-H., F.N.D., J.M.W.), University of Edinburgh, Scotland
| | - Alasdair G Morgan
- From the Centre for Clinical Brain Sciences (A.C.C.J., G.W.B., M.S.S., M.J.T., U.C., F.M.C., R.B., D.J.G., O.K.L.H., A.G.M., I.M., K.H., S.W., T.M., M.C.V.-H., F.N.D., J.M.W.), University of Edinburgh, Scotland
| | - Ian Marshall
- From the Centre for Clinical Brain Sciences (A.C.C.J., G.W.B., M.S.S., M.J.T., U.C., F.M.C., R.B., D.J.G., O.K.L.H., A.G.M., I.M., K.H., S.W., T.M., M.C.V.-H., F.N.D., J.M.W.), University of Edinburgh, Scotland
| | - Kirstie Hetherington
- From the Centre for Clinical Brain Sciences (A.C.C.J., G.W.B., M.S.S., M.J.T., U.C., F.M.C., R.B., D.J.G., O.K.L.H., A.G.M., I.M., K.H., S.W., T.M., M.C.V.-H., F.N.D., J.M.W.), University of Edinburgh, Scotland
| | - Stewart Wiseman
- From the Centre for Clinical Brain Sciences (A.C.C.J., G.W.B., M.S.S., M.J.T., U.C., F.M.C., R.B., D.J.G., O.K.L.H., A.G.M., I.M., K.H., S.W., T.M., M.C.V.-H., F.N.D., J.M.W.), University of Edinburgh, Scotland.,UK Dementia Research Institute (A.C.C.J., G.W.B., M.S.S., M.J.T., U.C., F.M.C., D.J.G., O.K.L.H., S.W., M.C.V.-H., F.N.D., J.M.W.), University of Edinburgh, Scotland
| | - Tom MacGillivray
- From the Centre for Clinical Brain Sciences (A.C.C.J., G.W.B., M.S.S., M.J.T., U.C., F.M.C., R.B., D.J.G., O.K.L.H., A.G.M., I.M., K.H., S.W., T.M., M.C.V.-H., F.N.D., J.M.W.), University of Edinburgh, Scotland
| | - Maria C Valdés-Hernández
- From the Centre for Clinical Brain Sciences (A.C.C.J., G.W.B., M.S.S., M.J.T., U.C., F.M.C., R.B., D.J.G., O.K.L.H., A.G.M., I.M., K.H., S.W., T.M., M.C.V.-H., F.N.D., J.M.W.), University of Edinburgh, Scotland.,UK Dementia Research Institute (A.C.C.J., G.W.B., M.S.S., M.J.T., U.C., F.M.C., D.J.G., O.K.L.H., S.W., M.C.V.-H., F.N.D., J.M.W.), University of Edinburgh, Scotland
| | - Fergus N Doubal
- From the Centre for Clinical Brain Sciences (A.C.C.J., G.W.B., M.S.S., M.J.T., U.C., F.M.C., R.B., D.J.G., O.K.L.H., A.G.M., I.M., K.H., S.W., T.M., M.C.V.-H., F.N.D., J.M.W.), University of Edinburgh, Scotland.,UK Dementia Research Institute (A.C.C.J., G.W.B., M.S.S., M.J.T., U.C., F.M.C., D.J.G., O.K.L.H., S.W., M.C.V.-H., F.N.D., J.M.W.), University of Edinburgh, Scotland
| | - Joanna M Wardlaw
- From the Centre for Clinical Brain Sciences (A.C.C.J., G.W.B., M.S.S., M.J.T., U.C., F.M.C., R.B., D.J.G., O.K.L.H., A.G.M., I.M., K.H., S.W., T.M., M.C.V.-H., F.N.D., J.M.W.), University of Edinburgh, Scotland.,UK Dementia Research Institute (A.C.C.J., G.W.B., M.S.S., M.J.T., U.C., F.M.C., D.J.G., O.K.L.H., S.W., M.C.V.-H., F.N.D., J.M.W.), University of Edinburgh, Scotland.,Centre for Cognitive Ageing and Cognitive Epidemiology (J.M.W.), University of Edinburgh, Scotland
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Blesa M, Galdi P, Sullivan G, Wheater EN, Stoye DQ, Lamb GJ, Quigley AJ, Thrippleton MJ, Bastin ME, Boardman JP. Peak Width of Skeletonized Water Diffusion MRI in the Neonatal Brain. Front Neurol 2020; 11:235. [PMID: 32318015 PMCID: PMC7146826 DOI: 10.3389/fneur.2020.00235] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Accepted: 03/11/2020] [Indexed: 12/22/2022] Open
Abstract
Preterm birth is closely associated with cognitive impairment and generalized dysconnectivity of neural networks inferred from water diffusion MRI (dMRI) metrics. Peak width of skeletonized mean diffusivity (PSMD) is a metric derived from histogram analysis of mean diffusivity across the white matter skeleton, and it is a useful biomarker of generalized dysconnectivity and cognition in adulthood. We calculated PSMD and five other histogram based metrics derived from diffusion tensor imaging (DTI) and neurite orientation and dispersion imaging (NODDI) in the newborn, and evaluated their accuracy as biomarkers of microstructural brain white matter alterations associated with preterm birth. One hundred and thirty five neonates (76 preterm, 59 term) underwent 3T MRI at term equivalent age. There were group differences in peak width of skeletonized mean, axial, and radial diffusivities (PSMD, PSAD, PSRD), orientation dispersion index (PSODI) and neurite dispersion index (PSNDI), all p < 10-4. PSFA did not differ between groups. PSNDI was the best classifier of gestational age at birth with an accuracy of 81±10%, followed by PSMD, which had 77±9% accuracy. Models built on both NODDI metrics, and on all dMRI metrics combined, did not outperform the model based on PSNDI alone. We conclude that histogram based analyses of DTI and NODDI parameters are promising new image markers for investigating diffuse changes in brain connectivity in early life.
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Affiliation(s)
- Manuel Blesa
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, United Kingdom
| | - Paola Galdi
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, United Kingdom
| | - Gemma Sullivan
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, United Kingdom
| | - Emily N. Wheater
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, United Kingdom
| | - David Q. Stoye
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, United Kingdom
| | - Gillian J. Lamb
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, United Kingdom
| | - Alan J. Quigley
- Department of Radiology, Royal Hospital for Sick Children, Edinburgh, United Kingdom
| | - Michael J. Thrippleton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
| | - Mark E. Bastin
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - James P. Boardman
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
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