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Paschoal AM, Woods JG, Pinto J, Bron EE, Petr J, Kennedy McConnell FA, Bell L, Dounavi ME, van Praag CG, Mutsaerts HJMM, Taylor AO, Zhao MY, Brumer I, Chan WSM, Toner J, Hu J, Zhang LX, Domingos C, Monteiro SP, Figueiredo P, Harms AGJ, Padrela BE, Tham C, Abdalle A, Croal PL, Anazodo U. Reproducibility of arterial spin labeling cerebral blood flow image processing: A report of the ISMRM open science initiative for perfusion imaging (OSIPI)_and the ASL MRI challenge. Magn Reson Med 2024. [PMID: 38502108 DOI: 10.1002/mrm.30081] [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: 04/28/2023] [Revised: 02/20/2024] [Accepted: 02/21/2024] [Indexed: 03/20/2024]
Abstract
PURPOSE Arterial spin labeling (ASL) is a widely used contrast-free MRI method for assessing cerebral blood flow (CBF). Despite the generally adopted ASL acquisition guidelines, there is still wide variability in ASL analysis. We explored this variability through the ISMRM-OSIPI ASL-MRI Challenge, aiming to establish best practices for more reproducible ASL analysis. METHODS Eight teams analyzed the challenge data, which included a high-resolution T1-weighted anatomical image and 10 pseudo-continuous ASL datasets simulated using a digital reference object to generate ground-truth CBF values in normal and pathological states. We compared the accuracy of CBF quantification from each team's analysis to the ground truth across all voxels and within predefined brain regions. Reproducibility of CBF across analysis pipelines was assessed using the intra-class correlation coefficient (ICC), limits of agreement (LOA), and replicability of generating similar CBF estimates from different processing approaches. RESULTS Absolute errors in CBF estimates compared to ground-truth synthetic data ranged from 18.36 to 48.12 mL/100 g/min. Realistic motion incorporated into three datasets produced the largest absolute error and variability between teams, with the least agreement (ICC and LOA) with ground-truth results. Fifty percent of the submissions were replicated, and one produced three times larger CBF errors (46.59 mL/100 g/min) compared to submitted results. CONCLUSIONS Variability in CBF measurements, influenced by differences in image processing, especially to compensate for motion, highlights the significance of standardizing ASL analysis workflows. We provide a recommendation for ASL processing based on top-performing approaches as a step toward ASL standardization.
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Affiliation(s)
- Andre M Paschoal
- Institute of Physics, University of Campinas, Campinas, Brazil
- LIM44, Institute of Radiology, Department of Radiology and Oncology of Clinical Hospital, University of Sao Paulo, Sao Paulo, Brazil
| | - Joseph G Woods
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
- Department of Radiology, Center for Functional Magnetic Resonance Imaging, University of California, San Diego, La Jolla, California, USA
| | - Joana Pinto
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK
| | - Esther E Bron
- Department of Radiology & Nuclear Medicine, Erasmus MC-University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Jan Petr
- Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany
| | - Flora A Kennedy McConnell
- Radiological Sciences, Division of Clinical Neuroscience, School of Medicine, University of Nottingham, Nottingham, UK
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK
- Nottingham Biomedical Research Centre, Queens Medical Centre, Nottingham, UK
| | - Laura Bell
- Clinical Imaging Group, Genentech, Inc., South San Francisco, California, USA
| | | | - Cassandra Gould van Praag
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Henk J M M Mutsaerts
- Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands
| | | | - Moss Y Zhao
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Irène Brumer
- Computer Assisted Clinical Medicine, Mannheim Institute for Intelligent Systems in Medicine, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
| | - Wei Siang Marcus Chan
- Computer Assisted Clinical Medicine, Mannheim Institute for Intelligent Systems in Medicine, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
| | - Jack Toner
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK
- Mental Health & Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK
| | - Jian Hu
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK
- Mental Health & Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK
| | - Logan X Zhang
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK
| | - Catarina Domingos
- Institute for Systems and Robotics-Lisboa and Department of Bioengineering, Instituto Superior Técnico-Universidade de Lisboa, Lisbon, Portugal
| | - Sara P Monteiro
- Institute for Systems and Robotics-Lisboa and Department of Bioengineering, Instituto Superior Técnico-Universidade de Lisboa, Lisbon, Portugal
| | - Patrícia Figueiredo
- Institute for Systems and Robotics-Lisboa and Department of Bioengineering, Instituto Superior Técnico-Universidade de Lisboa, Lisbon, Portugal
| | - Alexander G J Harms
- Department of Radiology & Nuclear Medicine, Erasmus MC-University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Beatriz E Padrela
- Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands
| | - Channelle Tham
- Department of Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Ahmed Abdalle
- Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
| | - Paula L Croal
- Radiological Sciences, Division of Clinical Neuroscience, School of Medicine, University of Nottingham, Nottingham, UK
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK
| | - Udunna Anazodo
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Québec, Canada
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Griffanti L, Raman B, Alfaro-Almagro F, Filippini N, Cassar MP, Sheerin F, Okell TW, Kennedy McConnell FA, Chappell MA, Wang C, Arthofer C, Lange FJ, Andersson J, Mackay CE, Tunnicliffe EM, Rowland M, Neubauer S, Miller KL, Jezzard P, Smith SM. Adapting the UK Biobank Brain Imaging Protocol and Analysis Pipeline for the C-MORE Multi-Organ Study of COVID-19 Survivors. Front Neurol 2021; 12:753284. [PMID: 34777224 PMCID: PMC8586081 DOI: 10.3389/fneur.2021.753284] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [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: 08/04/2021] [Accepted: 10/06/2021] [Indexed: 01/08/2023] Open
Abstract
SARS-CoV-2 infection has been shown to damage multiple organs, including the brain. Multiorgan MRI can provide further insight on the repercussions of COVID-19 on organ health but requires a balance between richness and quality of data acquisition and total scan duration. We adapted the UK Biobank brain MRI protocol to produce high-quality images while being suitable as part of a post-COVID-19 multiorgan MRI exam. The analysis pipeline, also adapted from UK Biobank, includes new imaging-derived phenotypes (IDPs) designed to assess the possible effects of COVID-19. A first application of the protocol and pipeline was performed in 51 COVID-19 patients post-hospital discharge and 25 controls participating in the Oxford C-MORE study. The protocol acquires high resolution T1, T2-FLAIR, diffusion weighted images, susceptibility weighted images, and arterial spin labelling data in 17 min. The automated imaging pipeline derives 1,575 IDPs, assessing brain anatomy (including olfactory bulb volume and intensity) and tissue perfusion, hyperintensities, diffusivity, and susceptibility. In the C-MORE data, IDPs related to atrophy, small vessel disease and olfactory bulbs were consistent with clinical radiology reports. Our exploratory analysis tentatively revealed some group differences between recovered COVID-19 patients and controls, across severity groups, but not across anosmia groups. Follow-up imaging in the C-MORE study is currently ongoing, and this protocol is now being used in other large-scale studies. The protocol, pipeline code and data are openly available and will further contribute to the understanding of the medium to long-term effects of COVID-19.
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Affiliation(s)
- Ludovica Griffanti
- Department of Psychiatry, Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, University of Oxford, Oxford, United Kingdom
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford, United Kingdom
| | - Betty Raman
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, Oxford Biomedical Research Centre (BRC) National Institute for Health Research (NIHR), University of Oxford, Oxford, United Kingdom
- Radcliffe Department of Medicine, British Heart Foundation Centre for Research Excellence, University of Oxford, Oxford, United Kingdom
| | - Fidel Alfaro-Almagro
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford, United Kingdom
| | - Nicola Filippini
- Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) San Camillo Hospital, Venice, Italy
| | - Mark Philip Cassar
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, Oxford Biomedical Research Centre (BRC) National Institute for Health Research (NIHR), University of Oxford, Oxford, United Kingdom
| | - Fintan Sheerin
- Department of Radiology, Oxford University Hospitals National Health Service (NHS) Foundation Trust, Oxford, United Kingdom
| | - Thomas W. Okell
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford, United Kingdom
| | - Flora A. Kennedy McConnell
- Mental Health & Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, United Kingdom
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, United Kingdom
- Nottingham Biomedical Research Centre, Queens Medical Centre, University of Nottingham, Nottingham, United Kingdom
| | - Michael A. Chappell
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford, United Kingdom
- Mental Health & Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, United Kingdom
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, United Kingdom
- Nottingham Biomedical Research Centre, Queens Medical Centre, University of Nottingham, Nottingham, United Kingdom
| | - Chaoyue Wang
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford, United Kingdom
| | - Christoph Arthofer
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford, United Kingdom
| | - Frederik J. Lange
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford, United Kingdom
| | - Jesper Andersson
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford, United Kingdom
| | - Clare E. Mackay
- Department of Psychiatry, Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, University of Oxford, Oxford, United Kingdom
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Elizabeth M. Tunnicliffe
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, Oxford Biomedical Research Centre (BRC) National Institute for Health Research (NIHR), University of Oxford, Oxford, United Kingdom
| | - Matthew Rowland
- Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, United Kingdom
| | - Stefan Neubauer
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, Oxford Biomedical Research Centre (BRC) National Institute for Health Research (NIHR), University of Oxford, Oxford, United Kingdom
- Radcliffe Department of Medicine, British Heart Foundation Centre for Research Excellence, University of Oxford, Oxford, United Kingdom
| | - Karla L. Miller
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford, United Kingdom
| | - Peter Jezzard
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford, United Kingdom
| | - Stephen M. Smith
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford, United Kingdom
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Chappell MA, McConnell FAK, Golay X, Günther M, Hernandez-Tamames JA, van Osch MJ, Asllani I. Partial volume correction in arterial spin labeling perfusion MRI: A method to disentangle anatomy from physiology or an analysis step too far? Neuroimage 2021; 238:118236. [PMID: 34091034 DOI: 10.1016/j.neuroimage.2021.118236] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [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: 02/19/2021] [Revised: 05/25/2021] [Accepted: 06/02/2021] [Indexed: 11/30/2022] Open
Abstract
The mismatch in the spatial resolution of Arterial Spin Labeling (ASL) MRI perfusion images and the anatomy of functionally distinct tissues in the brain leads to a partial volume effect (PVE), which in turn confounds the estimation of perfusion into a specific tissue of interest such as gray or white matter. This confound occurs because the image voxels contain a mixture of tissues with disparate perfusion properties, leading to estimated perfusion values that reflect primarily the volume proportions of tissues in the voxel rather than the perfusion of any particular tissue of interest within that volume. It is already recognized that PVE influences studies of brain perfusion, and that its effect might be even more evident in studies where changes in perfusion are co-incident with alterations in brain structure, such as studies involving a comparison between an atrophic patient population vs control subjects, or studies comparing subjects over a wide range of ages. However, the application of PVE correction (PVEc) is currently limited and the employed methodologies remain inconsistent. In this article, we outline the influence of PVE in ASL measurements of perfusion, explain the main principles of PVEc, and provide a critique of the current state of the art for the use of such methods. Furthermore, we examine the current use of PVEc in perfusion studies and whether there is evidence to support its wider adoption. We conclude that there is sound theoretical motivation for the use of PVEc alongside conventional, 'uncorrected', images, and encourage such combined reporting. Methods for PVEc are now available within standard neuroimaging toolboxes, which makes our recommendation straightforward to implement. However, there is still more work to be done to establish the value of PVEc as well as the efficacy and robustness of existing PVEc methods.
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Affiliation(s)
- Michael A Chappell
- Radiological Sciences, Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK; Sir Peter Mansfield Imaging Center, School of Medicine, University of Nottingham, Nottingham, UK; Nottingham Biomedical Research Centre, Queens Medical Centre, University of Nottingham, Nottingham, UK; Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, UK.
| | - Flora A Kennedy McConnell
- Radiological Sciences, Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK; Sir Peter Mansfield Imaging Center, School of Medicine, University of Nottingham, Nottingham, UK; Nottingham Biomedical Research Centre, Queens Medical Centre, University of Nottingham, Nottingham, UK
| | - Xavier Golay
- Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, London, UK
| | - Matthias Günther
- Fraunhofer MEVIS, Bremen, Germany; University Bremen, Bremen, Germany; mediri GmbH, Heidelberg, Germany
| | | | - Matthias J van Osch
- C.J. Gorter Center for High Field MRI, Radiology Department, Leiden University Medical Center, Leiden, the Netherlands
| | - Iris Asllani
- Clinical Imaging Sciences Centre, Department of Neuroscience, University of Sussex, UK; Department of Biomedical Engineering, Rochester Institute of Technology, Rochester, NY, United States
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4
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Raman B, Cassar MP, Tunnicliffe EM, Filippini N, Griffanti L, Alfaro-Almagro F, Okell T, Sheerin F, Xie C, Mahmod M, Mózes FE, Lewandowski AJ, Ohuma EO, Holdsworth D, Lamlum H, Woodman MJ, Krasopoulos C, Mills R, McConnell FAK, Wang C, Arthofer C, Lange FJ, Andersson J, Jenkinson M, Antoniades C, Channon KM, Shanmuganathan M, Ferreira VM, Piechnik SK, Klenerman P, Brightling C, Talbot NP, Petousi N, Rahman NM, Ho LP, Saunders K, Geddes JR, Harrison PJ, Pattinson K, Rowland MJ, Angus BJ, Gleeson F, Pavlides M, Koychev I, Miller KL, Mackay C, Jezzard P, Smith SM, Neubauer S. Medium-term effects of SARS-CoV-2 infection on multiple vital organs, exercise capacity, cognition, quality of life and mental health, post-hospital discharge. EClinicalMedicine 2021; 31:100683. [PMID: 33490928 PMCID: PMC7808914 DOI: 10.1016/j.eclinm.2020.100683] [Citation(s) in RCA: 342] [Impact Index Per Article: 114.0] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Revised: 11/22/2020] [Accepted: 11/26/2020] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND The medium-term effects of Coronavirus disease (COVID-19) on organ health, exercise capacity, cognition, quality of life and mental health are poorly understood. METHODS Fifty-eight COVID-19 patients post-hospital discharge and 30 age, sex, body mass index comorbidity-matched controls were enrolled for multiorgan (brain, lungs, heart, liver and kidneys) magnetic resonance imaging (MRI), spirometry, six-minute walk test, cardiopulmonary exercise test (CPET), quality of life, cognitive and mental health assessments. FINDINGS At 2-3 months from disease-onset, 64% of patients experienced breathlessness and 55% reported fatigue. On MRI, abnormalities were seen in lungs (60%), heart (26%), liver (10%) and kidneys (29%). Patients exhibited changes in the thalamus, posterior thalamic radiations and sagittal stratum on brain MRI and demonstrated impaired cognitive performance, specifically in the executive and visuospatial domains. Exercise tolerance (maximal oxygen consumption and ventilatory efficiency on CPET) and six-minute walk distance were significantly reduced. The extent of extra-pulmonary MRI abnormalities and exercise intolerance correlated with serum markers of inflammation and acute illness severity. Patients had a higher burden of self-reported symptoms of depression and experienced significant impairment in all domains of quality of life compared to controls (p<0.0001 to 0.044). INTERPRETATION A significant proportion of patients discharged from hospital reported symptoms of breathlessness, fatigue, depression and had limited exercise capacity. Persistent lung and extra-pulmonary organ MRI findings are common in patients and linked to inflammation and severity of acute illness. FUNDING NIHR Oxford and Oxford Health Biomedical Research Centres, British Heart Foundation Centre for Research Excellence, UKRI, Wellcome Trust, British Heart Foundation.
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Affiliation(s)
- Betty Raman
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC), University of Oxford, Oxford, United Kingdom
- Radcliffe Department of Medicine, British Heart Foundation Centre for Research Excellence, University of Oxford, Oxford, United Kingdom
| | - Mark Philip Cassar
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC), University of Oxford, Oxford, United Kingdom
| | - Elizabeth M. Tunnicliffe
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC), University of Oxford, Oxford, United Kingdom
| | - Nicola Filippini
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Ludovica Griffanti
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, Department of Psychiatry, University of Oxford, Oxford, United Kingdom
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Fidel Alfaro-Almagro
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Thomas Okell
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Fintan Sheerin
- Department of Radiology, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Cheng Xie
- Department of Radiology, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Masliza Mahmod
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC), University of Oxford, Oxford, United Kingdom
| | - Ferenc E. Mózes
- Oxford Centre for Clinical Magnetic Resonance Research, Radcliffe Department of Medicine, John Radcliffe Hospital Oxford, University of Oxford, Oxford, United Kingdom
| | - Adam J. Lewandowski
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC), University of Oxford, Oxford, United Kingdom
| | - Eric O. Ohuma
- Maternal, Adolescent, Reproductive & Child Health (MARCH) Centre, London School of Hygiene & Tropical Medicine (LSHTM), London, United Kingdom
| | - David Holdsworth
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom
| | - Hanan Lamlum
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC), University of Oxford, Oxford, United Kingdom
| | - Myles J. Woodman
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC), University of Oxford, Oxford, United Kingdom
| | - Catherine Krasopoulos
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC), University of Oxford, Oxford, United Kingdom
| | - Rebecca Mills
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC), University of Oxford, Oxford, United Kingdom
| | - Flora A. Kennedy McConnell
- Division of Clinical Neuroscience, Faculty of Medicine & Health Sciences, University of Nottingham, Nottingham, United Kingdom
| | - Chaoyue Wang
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Christoph Arthofer
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Frederik J. Lange
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Jesper Andersson
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Mark Jenkinson
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Charalambos Antoniades
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC), University of Oxford, Oxford, United Kingdom
- Radcliffe Department of Medicine, British Heart Foundation Centre for Research Excellence, University of Oxford, Oxford, United Kingdom
| | - Keith M. Channon
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC), University of Oxford, Oxford, United Kingdom
- Radcliffe Department of Medicine, British Heart Foundation Centre for Research Excellence, University of Oxford, Oxford, United Kingdom
| | - Mayooran Shanmuganathan
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC), University of Oxford, Oxford, United Kingdom
| | - Vanessa M. Ferreira
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC), University of Oxford, Oxford, United Kingdom
| | - Stefan K. Piechnik
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC), University of Oxford, Oxford, United Kingdom
| | - Paul Klenerman
- Nuffield Department of Medicine, NIHR Oxford BRC, University of Oxford, Oxford, United Kingdom
| | - Christopher Brightling
- Institute for Lung Health, Department of Respiratory Sciences, NIHR Leicester BRC, University of Leicester, Leicester, United Kingdom
| | - Nick P. Talbot
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom
| | - Nayia Petousi
- Nuffield Department of Medicine, NIHR Oxford BRC, University of Oxford, Oxford, United Kingdom
| | - Najib M. Rahman
- Nuffield Department of Medicine, NIHR Oxford BRC, University of Oxford, Oxford, United Kingdom
| | - Ling-Pei Ho
- Weatherall Institute of Molecular Medicine, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Kate Saunders
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - John R. Geddes
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Paul J. Harrison
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Kyle Pattinson
- Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, United Kingdom
| | - Matthew J. Rowland
- Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, United Kingdom
| | - Brian J. Angus
- Experimental Medicine, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Fergus Gleeson
- Department of Oncology, Medical Science Department, University of Oxford, Oxford, United Kingdom
| | - Michael Pavlides
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC), University of Oxford, Oxford, United Kingdom
- Translational Gastroenterology Unit, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Ivan Koychev
- Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, United Kingdom
| | - Karla L. Miller
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Clare Mackay
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, Department of Psychiatry, University of Oxford, Oxford, United Kingdom
- Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, United Kingdom
| | - Peter Jezzard
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Stephen M. Smith
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Stefan Neubauer
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC), University of Oxford, Oxford, United Kingdom
- Radcliffe Department of Medicine, British Heart Foundation Centre for Research Excellence, University of Oxford, Oxford, United Kingdom
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Kennedy McConnell FA, Payne SJ. Autoregulating Cerebral Tissue Selfishly Exploits Collateral Flow Routes Through the Circle of Willis. Acta Neurochir Suppl 2018; 126:275-279. [PMID: 29492574 DOI: 10.1007/978-3-319-65798-1_54] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
OBJECTIVE Ischemic stroke is a leading cause of death and disability. Autoregulation and collateral blood flow through the circle of Willis both play a role in preventing tissue infarction. A steady-state model of the cerebral arterial network was used to investigate the interaction of these mechanisms when autoregulation is impaired ipsilateral to an occluded artery. MATERIALS AND METHODS Twelve structural variants of the circle of Willis were modelled with left internal carotid artery occlusion and coupled with (1) a passive model of the cerebral vascular bed, (2) a steady-state model of an autoregulating cerebral vascular bed, and (3) a model in which the contralateral hemisphere autoregulates and the ipsilateral hemisphere does not. RESULTS Results showed that if the autoregulatory response is impaired ipsilaterally, then, in the autoregulating hemisphere, cerebral flows are preserved at the expense of those on the ipsilateral side. CONCLUSIONS Thus, although autoregulation is an essential facilitator of collateral flow through the circle of Willis, contralateral autoregulation can exacerbate flow reductions if not balanced by the same response in the vascular beds on the ipsilateral side. The status of the autoregulatory response in both hemispheres can strongly influence cerebral blood flows and tissue survival and should, therefore, be monitored in stroke.
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Affiliation(s)
- Flora A Kennedy McConnell
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, OX1 3PJ, UK.
| | - Stephen J Payne
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, OX1 3PJ, UK
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