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Woods JG, Achten E, Asllani I, Bolar DS, Dai W, Detre JA, Fan AP, Fernández-Seara MA, Golay X, Günther M, Guo J, Hernandez-Garcia L, Ho ML, Juttukonda MR, Lu H, MacIntosh BJ, Madhuranthakam AJ, Mutsaerts HJ, Okell TW, Parkes LM, Pinter N, Pinto J, Qin Q, Smits M, Suzuki Y, Thomas DL, Van Osch MJP, Wang DJJ, Warnert EAH, Zaharchuk G, Zelaya F, Zhao M, Chappell MA. Recommendations for quantitative cerebral perfusion MRI using multi-timepoint arterial spin labeling: Acquisition, quantification, and clinical applications. Magn Reson Med 2024. [PMID: 38594906 DOI: 10.1002/mrm.30091] [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: 08/31/2023] [Revised: 02/09/2024] [Accepted: 03/07/2024] [Indexed: 04/11/2024]
Abstract
Accurate assessment of cerebral perfusion is vital for understanding the hemodynamic processes involved in various neurological disorders and guiding clinical decision-making. This guidelines article provides a comprehensive overview of quantitative perfusion imaging of the brain using multi-timepoint arterial spin labeling (ASL), along with recommendations for its acquisition and quantification. A major benefit of acquiring ASL data with multiple label durations and/or post-labeling delays (PLDs) is being able to account for the effect of variable arterial transit time (ATT) on quantitative perfusion values and additionally visualize the spatial pattern of ATT itself, providing valuable clinical insights. Although multi-timepoint data can be acquired in the same scan time as single-PLD data with comparable perfusion measurement precision, its acquisition and postprocessing presents challenges beyond single-PLD ASL, impeding widespread adoption. Building upon the 2015 ASL consensus article, this work highlights the protocol distinctions specific to multi-timepoint ASL and provides robust recommendations for acquiring high-quality data. Additionally, we propose an extended quantification model based on the 2015 consensus model and discuss relevant postprocessing options to enhance the analysis of multi-timepoint ASL data. Furthermore, we review the potential clinical applications where multi-timepoint ASL is expected to offer significant benefits. This article is part of a series published by the International Society for Magnetic Resonance in Medicine (ISMRM) Perfusion Study Group, aiming to guide and inspire the advancement and utilization of ASL beyond the scope of the 2015 consensus article.
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Affiliation(s)
- Joseph G Woods
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Center for Functional Magnetic Resonance Imaging, Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Eric Achten
- Ghent Institute for Functional and Metabolic Imaging (GIfMI), Ghent University, Ghent, Belgium
| | - Iris Asllani
- Department of Neuroscience, University of Sussex, Brighton, UK
- Department of Biomedical Engineering, Rochester Institute of Technology, Rochester, New York, USA
| | - Divya S Bolar
- Center for Functional Magnetic Resonance Imaging, Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Weiying Dai
- Department of Computer Science, State University of New York at Binghamton, Binghamton, New York, USA
| | - John A Detre
- Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Audrey P Fan
- Department of Biomedical Engineering, University of California Davis, Davis, California, USA
- Department of Neurology, University of California Davis, Davis, California, USA
| | - María A Fernández-Seara
- Department of Radiology, Clínica Universidad de Navarra, Pamplona, Spain
- IdiSNA, Instituto de Investigación Sanitaria de Navarra, Pamplona, Spain
| | - Xavier Golay
- UCL Queen Square Institute of Neurology, University College London, London, UK
- Gold Standard Phantoms, Sheffield, UK
| | - Matthias Günther
- Imaging Physics, Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany
- Department of Physics and Electrical Engineering, University of Bremen, Bremen, Germany
| | - Jia Guo
- Department of Bioengineering, University of California Riverside, Riverside, California, USA
| | | | - Mai-Lan Ho
- Department of Radiology, University of Missouri, Columbia, Missouri, USA
| | - Meher R Juttukonda
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Hanzhang Lu
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Bradley J MacIntosh
- Hurvitz Brain Sciences Program, Centre for Brain Resilience & Recovery, Sunnybrook Research Institute, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Computational Radiology & Artificial Intelligence unit, Oslo University Hospital, Oslo, Norway
| | - Ananth J Madhuranthakam
- Department of Radiology and Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, Texas, USA
| | - Henk-Jan Mutsaerts
- Department of Radiology and Nuclear Medicine, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
| | - Thomas W Okell
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Laura M Parkes
- School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Manchester, UK
| | - Nandor Pinter
- Dent Neurologic Institute, Buffalo, New York, USA
- University at Buffalo Neurosurgery, Buffalo, New York, USA
| | - Joana Pinto
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK
| | - Qin Qin
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Marion Smits
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
- Medical Delta, Delft, The Netherlands
- Erasmus MC Cancer Institute, Erasmus MC, Rotterdam, The Netherlands
| | - Yuriko Suzuki
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - David L Thomas
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Matthias J P Van Osch
- C.J. Gorter MRI Center, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Danny J J Wang
- Laboratory of FMRI Technology (LOFT), Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, California, USA
| | - Esther A H Warnert
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
- Erasmus MC Cancer Institute, Erasmus MC, Rotterdam, The Netherlands
| | - Greg Zaharchuk
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Fernando Zelaya
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, UK
| | - Moss Zhao
- Department of Radiology, Stanford University, Stanford, California, USA
- Maternal & Child Health Research Institute, Stanford University, Stanford, California, USA
| | - Michael A Chappell
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK
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Kerestes R, Laansma MA, Owens-Walton C, Perry A, van Heese EM, Al-Bachari S, Anderson TJ, Assogna F, Aventurato ÍK, van Balkom TD, Berendse HW, van den Berg KR, Mphys RB, Brioschi R, Carr J, Cendes F, Clark LR, Dalrymple-Alford JC, Dirkx MF, Druzgal J, Durrant H, Emsley HC, Garraux G, Haroon HA, Helmich RC, van den Heuvel OA, João RB, Johansson ME, Khachatryan S, Lochner C, McMillan CT, Melzer TR, Mosley P, Newman B, Opriessnig P, Parkes LM, Pellicano C, Piras F, Pitcher TL, Poston KL, Rango M, Roos A, Rummel C, Schmidt R, Schwingenschuh P, Silva LS, Smith V, Squarcina L, Stein DJ, Tavadyan Z, Tsai CC, Vecchio D, Vriend C, Wang JJ, Wiest R, Yasuda CL, Young CB, Jahanshad N, Thompson PM, van der Werf YD, Harding IH. Cerebellar Volume and Disease Staging in Parkinson's Disease: An ENIGMA-PD Study. Mov Disord 2023; 38:2269-2281. [PMID: 37964373 PMCID: PMC10754393 DOI: 10.1002/mds.29611] [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: 05/29/2023] [Revised: 08/14/2023] [Accepted: 09/11/2023] [Indexed: 11/16/2023] Open
Abstract
BACKGROUND Increasing evidence points to a pathophysiological role for the cerebellum in Parkinson's disease (PD). However, regional cerebellar changes associated with motor and non-motor functioning remain to be elucidated. OBJECTIVE To quantify cross-sectional regional cerebellar lobule volumes using three dimensional T1-weighted anatomical brain magnetic resonance imaging from the global ENIGMA-PD working group. METHODS Cerebellar parcellation was performed using a deep learning-based approach from 2487 people with PD and 1212 age and sex-matched controls across 22 sites. Linear mixed effects models compared total and regional cerebellar volume in people with PD at each Hoehn and Yahr (HY) disease stage, to an age- and sex- matched control group. Associations with motor symptom severity and Montreal Cognitive Assessment scores were investigated. RESULTS Overall, people with PD had a regionally smaller posterior lobe (dmax = -0.15). HY stage-specific analyses revealed a larger anterior lobule V bilaterally (dmax = 0.28) in people with PD in HY stage 1 compared to controls. In contrast, smaller bilateral lobule VII volume in the posterior lobe was observed in HY stages 3, 4, and 5 (dmax = -0.76), which was incrementally lower with higher disease stage. Within PD, cognitively impaired individuals had lower total cerebellar volume compared to cognitively normal individuals (d = -0.17). CONCLUSIONS We provide evidence of a dissociation between anterior "motor" lobe and posterior "non-motor" lobe cerebellar regions in PD. Whereas less severe stages of the disease are associated with larger motor lobe regions, more severe stages of the disease are marked by smaller non-motor regions. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Rebecca Kerestes
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia
| | - Max A. Laansma
- Amsterdam UMC, Dept. Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
| | - Conor Owens-Walton
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Andrew Perry
- Monash Bioinformatics Platform, Monash University, Melbourne, VIC, Australia
| | - Eva M. van Heese
- Amsterdam UMC, Dept. Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
| | - Sarah Al-Bachari
- Faculty of Health and Medicine, The University of Lancaster, Lancaster, UK
| | - Tim J. Anderson
- Department of Medicine, University of Otago, Christchurch, Christchurch, New Zealand
- New Zealand Brain Research Institute, Christchurch, New Zealand
- Neurology Department, Te Wahtu Ora - Health New Zealand Waitaha Canterbury, Christchurch, New Zew Zealand
| | - Francesca Assogna
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Ítalo K. Aventurato
- Department of Neurology, University of Campinas - UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Tim D. van Balkom
- Amsterdam UMC, Dept. Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
- Amsterdam UMC, Dept. Psychiatry, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Henk W. Berendse
- Amsterdam UMC, Dept. Neurology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Kevin R.E. van den Berg
- Department of Neurology and Center of Expertise for Parkinson & Movement Disorders, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands
- Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Rebecca Betts Mphys
- School of Physics and Astronomy, Faculty of Science and Engineering, The University of Manchester, Manchester, UK
| | - Ricardo Brioschi
- Department of Neurology, University of Campinas - UNICAMP, Campinas, Brazil
| | - Jonathan Carr
- Division of Neurology, Tygerberg Hospital and Stellenbosch University, Cape Town, South Africa
| | - Fernando Cendes
- Department of Neurology, University of Campinas - UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Lyles R. Clark
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - John C. Dalrymple-Alford
- New Zealand Brain Research Institute, Christchurch, New Zealand
- School of Psychology, Speech and Hearing, University of Canterbury, Christchurch, New Zealand
| | - Michiel F. Dirkx
- Department of Neurology and Center of Expertise for Parkinson & Movement Disorders, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands
| | - Jason Druzgal
- Department of Radiology and Medical Imaging, University of Virginia, USA
| | - Helena Durrant
- School of Physics and Astronomy, Faculty of Science and Engineering, The University of Manchester, Manchester, UK
| | - Hedley C.A. Emsley
- Lancaster Medical School, Lancaster University, Lancaster, UK
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Gaëtan Garraux
- GIGA-CRC in vivo imaging, University of Liège, Belgium
- Department of Neurology, CHU Liège, Liège, Belgium
| | - Hamied A. Haroon
- Division of Psychology, Communication & Human Neuroscience, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Rick C. Helmich
- Department of Neurology and Center of Expertise for Parkinson & Movement Disorders, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands
- Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Odile A. van den Heuvel
- Amsterdam UMC, Dept. Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
- Amsterdam UMC, Dept. Psychiatry, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Rafael B. João
- Department of Neurology, University of Campinas - UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Martin E. Johansson
- Department of Neurology and Center of Expertise for Parkinson & Movement Disorders, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands
| | - Samson Khachatryan
- Department of Neurology and Neurosurgery, National Institute of Health, Yerevan, Armenia
- Centers for Sleep and Movement Disorders, Somnus Neurology Clinic, Yerevan, Armenia
| | - Christine Lochner
- SA MRC Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry, Stellenbosch University, Cape Town, South Africa
| | - Corey T. McMillan
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Tracy R. Melzer
- Department of Medicine, University of Otago, Christchurch, Christchurch, New Zealand
- New Zealand Brain Research Institute, Christchurch, New Zealand
- School of Psychology, Speech and Hearing, University of Canterbury, Christchurch, New Zealand
| | - Philip Mosley
- Clinical Brain Networks Group, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- The Australian eHealth Research Centre, CSIRO Health and Biosecurity, Brisbane, Queensland, Australia
| | - Benjamin Newman
- Department of Radiology and Medical Imaging, University of Virginia, USA
| | - Peter Opriessnig
- Department of Neurology, Clinical Division of Neurogeriatrics, Medical University Graz, Graz, Austria
| | - Laura M. Parkes
- Division of Psychology, Communication and Human Neuroscience, 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 & University of Manchester, Manchester, UK
| | - Clelia Pellicano
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Fabrizio Piras
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Toni L. Pitcher
- Department of Medicine, University of Otago, Christchurch, Christchurch, New Zealand
- New Zealand Brain Research Institute, Christchurch, New Zealand
| | - Kathleen L. Poston
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, CA, USA
| | - Mario Rango
- Excellence Center for Advanced MR Techniques and Parkinson’s Disease Center, Neurology unit, Fondazione IRCCS Cà Granda Maggiore Policlinico Hospital, University of Milan, Milan, Italy
- Dept of Neurosciences, Neurology Unit, Fondazione Ca’ Granda, IRCCS, Ospedale Policlinico, Univeristy of Milan, Milano, Italy
| | - Annerine Roos
- SA MRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Christian Rummel
- Support Center for Advanced Neuroimaging, (SCAN) University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Reinhold Schmidt
- Department of Neurology, Medical University of Graz, Graz, Austria
| | | | - Lucas S. Silva
- Department of Neurology, University of Campinas - UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Viktorija Smith
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, CA, USA
| | - Letizia Squarcina
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Dan J. Stein
- SA MRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Zaruhi Tavadyan
- Department of Neurology and Neurosurgery, National Institute of Health, Yerevan, Armenia
- Centers for Sleep and Movement Disorders, Somnus Neurology Clinic, Yerevan, Armenia
| | - Chih-Chien Tsai
- Healthy Aging Research Center, Chang Gung University, Taoyuan, Taiwan
| | - Daniela Vecchio
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Chris Vriend
- Amsterdam UMC, Dept. Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam UMC, Dept. Psychiatry, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Brain imaging, Amsterdam, the Netherlands
| | - Jiun-Jie Wang
- Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan City, Taiwan
- Department of Diagnostic Radiology, Chang Gung Memorial Hospital, Keelung Branch Keelung City, Taiwan
- Healthy Ageing Research Center, ChangGung University, Taiwan
- Department of Chemical Engineering, Ming-Chi University of Technology, New Taipei City, Taiwan
| | - Roland Wiest
- Support Center for Advanced Neuroimaging, (SCAN) University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Clarissa L. Yasuda
- Department of Neurology, University of Campinas - UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Christina B. Young
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, CA, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Paul M. Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Ysbrand D. van der Werf
- Amsterdam UMC, Dept. Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
| | - Ian H. Harding
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia
- Monash Biomedical Imaging, Monash University, Melbourne, VIC, Australia
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Powell E, Dickie BR, Ohene Y, Maskery M, Parker GJM, Parkes LM. Blood-brain barrier water exchange measurements using contrast-enhanced ASL. NMR Biomed 2023; 36:e5009. [PMID: 37666494 PMCID: PMC10909569 DOI: 10.1002/nbm.5009] [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] [Subscribe] [Scholar Register] [Received: 02/04/2023] [Revised: 05/17/2023] [Accepted: 06/30/2023] [Indexed: 09/06/2023]
Abstract
A technique for quantifying regional blood-brain barrier (BBB) water exchange rates using contrast-enhanced arterial spin labelling (CE-ASL) is presented and evaluated in simulations and in vivo. The two-compartment ASL model describes the water exchange rate from blood to tissue,k b , but to estimatek b in practice it is necessary to separate the intra- and extravascular signals. This is challenging in standard ASL data owing to the small difference inT 1 values. Here, a gadolinium-based contrast agent is used to increase thisT 1 difference and enable the signal components to be disentangled. The optimal post-contrast bloodT 1 (T 1 , b post ) at 3 T was determined in a sensitivity analysis, and the accuracy and precision of the method quantified using Monte Carlo simulations. Proof-of-concept data were acquired in six healthy volunteers (five female, age range 24-46 years). The sensitivity analysis identified the optimalT 1 , b post at 3 T as 0.8 s. Simulations showed thatk b could be estimated in individual cortical regions with a relative error ϵ < 1 % and coefficient of variation CoV = 30 %; however, a high dependence on bloodT 1 was also observed. In volunteer data, mean parameter values in grey matter were: arterial transit timet A = 1 . 15 ± 0 . 49 s, cerebral blood flow f = 58 . 0 ± 14 . 3 mL blood/min/100 mL tissue and water exchange ratek b = 2 . 32 ± 2 . 49 s-1 . CE-ASL can provide regional BBB water exchange rate estimates; however, the clinical utility of the technique is dependent on the achievable accuracy of measuredT 1 values.
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Affiliation(s)
- Elizabeth Powell
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical EngineeringUniversity College LondonLondonUK
| | - Ben R. Dickie
- Division of Informatics, Imaging and Data Sciences, School of Health Sciences, Faculty of Biology, Medicine and HealthUniversity of ManchesterManchesterUK
- Geoffrey Jefferson Brain Research CentreUniversity of Manchester, Manchester Academic Health Science CentreManchesterUK
| | - Yolanda Ohene
- Geoffrey Jefferson Brain Research CentreUniversity of Manchester, Manchester Academic Health Science CentreManchesterUK
- Division of Psychology, Communication and Human Neuroscience, School of Health Sciences, Faculty of Biology, Medicine and HealthUniversity of ManchesterManchesterUK
| | - Mark Maskery
- Department of NeurologyLancashire Teaching Hospitals NHS Foundation TrustPrestonUK
| | - Geoff J. M. Parker
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical EngineeringUniversity College LondonLondonUK
- Queen Square MS Centre, Institute of NeurologyUniversity College LondonLondonUK
- Bioxydyn LimitedManchesterUnited Kingdom
| | - Laura M. Parkes
- Geoffrey Jefferson Brain Research CentreUniversity of Manchester, Manchester Academic Health Science CentreManchesterUK
- Division of Psychology, Communication and Human Neuroscience, School of Health Sciences, Faculty of Biology, Medicine and HealthUniversity of ManchesterManchesterUK
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Powell E, Ohene Y, Battiston M, Dickie BR, Parkes LM, Parker GJM. Blood-brain barrier water exchange measurements using FEXI: Impact of modeling paradigm and relaxation time effects. Magn Reson Med 2023; 90:34-50. [PMID: 36892973 PMCID: PMC10962589 DOI: 10.1002/mrm.29616] [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: 10/19/2022] [Revised: 01/25/2023] [Accepted: 01/25/2023] [Indexed: 03/10/2023]
Abstract
PURPOSE To evaluate potential modeling paradigms and the impact of relaxation time effects on human blood-brain barrier (BBB) water exchange measurements using FEXI (BBB-FEXI), and to quantify the accuracy, precision, and repeatability of BBB-FEXI exchange rate estimates at 3 T $$ \mathrm{T} $$ . METHODS Three modeling paradigms were evaluated: (i) the apparent exchange rate (AXR) model; (ii) a two-compartment model (2 CM $$ 2\mathrm{CM} $$ ) explicitly representing intra- and extravascular signal components, and (iii) a two-compartment model additionally accounting for finite compartmentalT 1 $$ {\mathrm{T}}_1 $$ andT 2 $$ {\mathrm{T}}_2 $$ relaxation times (2 CM r $$ 2{\mathrm{CM}}_r $$ ). Each model had three free parameters. Simulations quantified biases introduced by the assumption of infinite relaxation times in the AXR and2 CM $$ 2\mathrm{CM} $$ models, as well as the accuracy and precision of all three models. The scan-rescan repeatability of all paradigms was quantified for the first time in vivo in 10 healthy volunteers (age range 23-52 years; five female). RESULTS The assumption of infinite relaxation times yielded exchange rate errors in simulations up to 42%/14% in the AXR/2 CM $$ 2\mathrm{CM} $$ models, respectively. Accuracy was highest in the compartmental models; precision was best in the AXR model. Scan-rescan repeatability in vivo was good for all models, with negligible bias and repeatability coefficients in grey matter ofRC AXR = 0 . 43 $$ {\mathrm{RC}}_{\mathrm{AXR}}=0.43 $$ s - 1 $$ {\mathrm{s}}^{-1} $$ ,RC 2 CM = 0 . 51 $$ {\mathrm{RC}}_{2\mathrm{CM}}=0.51 $$ s - 1 $$ {\mathrm{s}}^{-1} $$ , andRC 2 CM r = 0 . 61 $$ {\mathrm{RC}}_{2{\mathrm{CM}}_r}=0.61 $$ s - 1 $$ {\mathrm{s}}^{-1} $$ . CONCLUSION Compartmental modelling of BBB-FEXI signals can provide accurate and repeatable measurements of BBB water exchange; however, relaxation time and partial volume effects may cause model-dependent biases.
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Affiliation(s)
- Elizabeth Powell
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical EngineeringUniversity College LondonLondonUK
| | - Yolanda Ohene
- Division of Psychology, Communication and Human Neuroscience, School of Health Sciences, Faculty of Biology, Medicine and HealthUniversity of ManchesterManchesterUK
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science CentreUniversity of ManchesterManchesterUK
| | - Marco Battiston
- Queen Square MS CentreUCL Institute of Neurology, University College LondonLondonUK
| | - Ben R. Dickie
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science CentreUniversity of ManchesterManchesterUK
- Division of Informatics, Imaging and Data SciencesSchool of Health Sciences, Faculty of Biology, Medicine and Health, University of ManchesterManchesterUK
| | - Laura M. Parkes
- Division of Psychology, Communication and Human Neuroscience, School of Health Sciences, Faculty of Biology, Medicine and HealthUniversity of ManchesterManchesterUK
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science CentreUniversity of ManchesterManchesterUK
| | - Geoff J. M. Parker
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical EngineeringUniversity College LondonLondonUK
- Queen Square MS CentreUCL Institute of Neurology, University College LondonLondonUK
- Bioxydyn LimitedManchesterUK
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Ohene Y, Harris WJ, Powell E, Wycech NW, Smethers KF, Lasič S, South K, Coutts G, Sharp A, Lawrence CB, Boutin H, Parker GJM, Parkes LM, Dickie BR. Filter exchange imaging with crusher gradient modelling detects increased blood-brain barrier water permeability in response to mild lung infection. Fluids Barriers CNS 2023; 20:25. [PMID: 37013549 PMCID: PMC10071630 DOI: 10.1186/s12987-023-00422-7] [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: 11/15/2022] [Accepted: 03/08/2023] [Indexed: 04/05/2023] Open
Abstract
Blood-brain barrier (BBB) dysfunction occurs in many brain diseases, and there is increasing evidence to suggest that it is an early process in dementia which may be exacerbated by peripheral infection. Filter-exchange imaging (FEXI) is an MRI technique for measuring trans-membrane water exchange. FEXI data is typically analysed using the apparent exchange rate (AXR) model, yielding estimates of the AXR. Crusher gradients are commonly used to remove unwanted coherence pathways arising from longitudinal storage pulses during the mixing period. We first demonstrate that when using thin slices, as is needed for imaging the rodent brain, crusher gradients result in underestimation of the AXR. To address this, we propose an extended crusher-compensated exchange rate (CCXR) model to account for diffusion-weighting introduced by the crusher gradients, which is able to recover ground truth values of BBB water exchange (kin) in simulated data. When applied to the rat brain, kin estimates obtained using the CCXR model were 3.10 s-1 and 3.49 s-1 compared to AXR estimates of 1.24 s-1 and 0.49 s-1 for slice thicknesses of 4.0 mm and 2.5 mm respectively. We then validated our approach using a clinically relevant Streptococcus pneumoniae lung infection. We observed a significant 70 ± 10% increase in BBB water exchange in rats during active infection (kin = 3.78 ± 0.42 s-1) compared to before infection (kin = 2.72 ± 0.30 s-1; p = 0.02). The BBB water exchange rate during infection was associated with higher levels of plasma von Willebrand factor (VWF), a marker of acute vascular inflammation. We also observed 42% higher expression of perivascular aquaporin-4 (AQP4) in infected animals compared to non-infected controls, while levels of tight junction proteins remain consistent between groups. In summary, we propose a modelling approach for FEXI data which removes the bias in estimated water-exchange rates associated with the use of crusher gradients. Using this approach, we demonstrate the impact of peripheral infection on BBB water exchange, which appears to be mediated by endothelial dysfunction and associated with an increase in perivascular AQP4.
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Affiliation(s)
- Yolanda Ohene
- Division of Psychology, Communication and Human Neuroscience, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Zochonis Building, Oxford Road, Manchester, M13 9PL, UK.
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK.
| | - William J Harris
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
- Division of Neuroscience, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Elizabeth Powell
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering and Department of Neuroinflammation, UCL, London, UK
| | - Nina W Wycech
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
- Division of Neuroscience, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Katherine F Smethers
- Division of Psychology, Communication and Human Neuroscience, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Zochonis Building, Oxford Road, Manchester, M13 9PL, UK
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
| | - Samo Lasič
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Copenhagen, Denmark
- Random Walk Imaging, Lund, Sweden
| | - Kieron South
- Division of Psychology, Communication and Human Neuroscience, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Zochonis Building, Oxford Road, Manchester, M13 9PL, UK
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
| | - Graham Coutts
- Division of Psychology, Communication and Human Neuroscience, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Zochonis Building, Oxford Road, Manchester, M13 9PL, UK
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
| | - Andrew Sharp
- Evotec (UK) Ltd., Alderley Park, Block 23F, Mereside, Cheshire, SK10 4TG, UK
| | - Catherine B Lawrence
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
- Division of Neuroscience, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Hervé Boutin
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
- Division of Neuroscience, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Geoff J M Parker
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering and Department of Neuroinflammation, UCL, London, UK
- Bioxydyn Limited, Manchester, UK
| | - Laura M Parkes
- Division of Psychology, Communication and Human Neuroscience, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Zochonis Building, Oxford Road, Manchester, M13 9PL, UK
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
| | - Ben R Dickie
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
- Division of Informatics, Imaging and Data Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
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6
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Davenport F, Gallacher J, Kourtzi Z, Koychev I, Matthews PM, Oxtoby NP, Parkes LM, Priesemann V, Rowe JB, Smye SW, Zetterberg H. Neurodegenerative disease of the brain: a survey of interdisciplinary approaches. J R Soc Interface 2023; 20:20220406. [PMID: 36651180 PMCID: PMC9846433 DOI: 10.1098/rsif.2022.0406] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [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: 05/28/2022] [Accepted: 12/16/2022] [Indexed: 01/19/2023] Open
Abstract
Neurodegenerative diseases of the brain pose a major and increasing global health challenge, with only limited progress made in developing effective therapies over the last decade. Interdisciplinary research is improving understanding of these diseases and this article reviews such approaches, with particular emphasis on tools and techniques drawn from physics, chemistry, artificial intelligence and psychology.
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Affiliation(s)
| | - John Gallacher
- Director of Dementias Platform, Department of Psychiatry, University of Oxford, Oxford, UK
| | - Zoe Kourtzi
- Professor of Cognitive Computational Neuroscience, Department of Psychology, University of Cambridge, UK
| | - Ivan Koychev
- Senior Clinical Researcher, Department of Psychiatry, University of Oxford, Oxford, UK
- Consultant Neuropsychiatrist, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Paul M. Matthews
- Department of Brain Sciences and UK Dementia Research Institute Centre, Imperial College London, Oxford, UK
| | - Neil P. Oxtoby
- UCL Centre for Medical Image Computing and Department of Computer Science, University College London, Gower Street, London, UK
| | - Laura M. Parkes
- School of Health Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Oxford Road, Manchester, M13 9PL, UK
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Manchester, UK
| | - Viola Priesemann
- Max Planck Group Leader and Fellow of the Schiemann Kolleg, Max Planck Institute for Dynamics and Self-Organization and Bernstein Center for Computational Neuroscience, Göttingen, Germany
| | - James B. Rowe
- Department of Clinical Neurosciences, MRC Cognition and Brain Sciences Unit and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, UK
| | | | - Henrik Zetterberg
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, People's Republic of China
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7
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Dickie BR, Jin T, Wang P, Hinz R, Harris W, Boutin H, Parker GJ, Parkes LM, Matthews JC. Quantitative kinetic modelling and mapping of cerebral glucose transport and metabolism using glucoCESL MRI. J Cereb Blood Flow Metab 2022; 42:2066-2079. [PMID: 35748031 PMCID: PMC9580170 DOI: 10.1177/0271678x221108841] [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] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Chemical-exchange spin-lock (CESL) MRI can map regional uptake and utilisation of glucose in the brain at high spatial resolution (i.e sub 0.2 mm3 voxels). We propose two quantitative kinetic models to describe glucose-induced changes in tissue R1ρ and apply them to glucoCESL MRI data acquired in tumour-bearing and healthy rats. When assuming glucose transport is saturable, the maximal transport capacity (Tmax) measured in normal tissue was 3.2 ± 0.6 µmol/min/mL, the half saturation constant (Kt) was 8.8 ± 2.2 mM, the metabolic rate of glucose consumption (MRglc) was 0.21 ± 0.13 µmol/min/mL, and the cerebral blood volume (vb) was 0.006 ± 0.005 mL/mL. Values in tumour were: Tmax = 7.1 ± 2.7 µmol/min/mL, Kt = 14 ± 1.7 mM, MRglc = 0.22 ± 0.09 µmol/min/mL, vb = 0.030 ± 0.035 mL/mL. Tmax and Kt were significantly higher in tumour tissue than normal tissue (p = 0.006 and p = 0.011, respectively). When assuming glucose uptake also occurs via free diffusion, the free diffusion rate (kd) was 0.061 ± 0.017 mL/min/mL in normal tissue and 0.12 ± 0.042 mL/min/mL in tumour. These parameter estimates agree well with literature values obtained using other approaches (e.g. NMR spectroscopy).
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Affiliation(s)
- Ben R Dickie
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.,Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Manchester, UK
| | - Tao Jin
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Ping Wang
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Rainer Hinz
- Division of Informatics, Imaging, and Data Science, Faculty of Biology Medicine and Health, University of Manchester, Manchester, UK
| | - William Harris
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.,Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Manchester, UK
| | - Hervé Boutin
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.,Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Manchester, UK
| | - Geoff Jm Parker
- Bioxydyn Limited, Manchester, UK.,Centre for Medical Image Computing, Department of Medical Physics & Biomedical Engineering and Department of Neuroinflammation, University College London, London, UK
| | - Laura M Parkes
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.,Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Manchester, UK
| | - Julian C Matthews
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.,Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Manchester, UK
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8
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Garg S, Williams S, Jung J, Pobric G, Nandi T, Lim B, Vassallo G, Green J, Evans DG, Stagg CJ, Parkes LM, Stivaros S. Non-invasive brain stimulation modulates GABAergic activity in neurofibromatosis 1. Sci Rep 2022; 12:18297. [PMID: 36316421 PMCID: PMC9622815 DOI: 10.1038/s41598-022-21907-9] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Accepted: 10/05/2022] [Indexed: 11/11/2022] Open
Abstract
Neurofibromatosis 1 (NF1) is a single-gene disorder associated with cognitive phenotypes common to neurodevelopmental conditions such as autism. GABAergic dysregulation underlies working memory impairments seen in NF1. This mechanistic experimental study investigates whether application of anodal transcranial direct current stimulation (atDCS) can modulate GABA and working memory in NF1. Thirty-one NF1 adolescents 11-18 years, were recruited to this single-blind sham-controlled cross-over randomized trial. AtDCS or sham stimulation was applied to the left Dorsolateral Prefrontal Cortex (DLPFC) and MR Spectroscopy was collected before and after intervention in the left DLPFC and occipital cortex. Task-related functional MRI was collected before, during, and after stimulation. Higher baseline GABA+ in the left DLPFC was associated with faster response times on baseline working memory measures. AtDCS was seen to significantly reduced GABA+ and increase brain activation in the left DLPFC as compared to sham stimulation. Task performance was worse in the aTDCS group during stimulation but no group differences in behavioural outcomes were observed at the end of stimulation. Although our study suggests aTDCS modulates inhibitory activity in the DLPFC, further work is needed to determine whether repeated sessions of atDCS and strategies such as alternating current stimulation offer a better therapeutic approach.
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Affiliation(s)
- Shruti Garg
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.
- Child and Adolescent Mental Health Services, Royal Manchester Children's Hospital, Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Sciences Centre, Manchester, UK.
| | - Steve Williams
- Division of Informatics, Imaging and Data Sciences, School of Health Sciences, University of Manchester, Manchester, UK
| | - JeYoung Jung
- School of Psychology, Precision Imaging Beacon, University of Nottingham, Nottingham, UK
| | - Gorana Pobric
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Tulika Nandi
- Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Ben Lim
- Child and Adolescent Mental Health Services, Royal Manchester Children's Hospital, Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Sciences Centre, Manchester, UK
| | - Grace Vassallo
- Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, UK
| | - Jonathan Green
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
- Child and Adolescent Mental Health Services, Royal Manchester Children's Hospital, Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Sciences Centre, Manchester, UK
| | - D Gareth Evans
- Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, UK
- Division of Evolution and Genomic Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Charlotte J Stagg
- Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Laura M Parkes
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Manchester, UK
| | - Stavros Stivaros
- Division of Informatics, Imaging and Data Sciences, School of Health Sciences, University of Manchester, Manchester, UK
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Manchester, UK
- Academic Unit of Paediatric Radiology, Royal Manchester Children's Hospital, Manchester University NHS Foundation Trust, Manchester, UK
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9
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Sawyer C, Green J, Lim B, Pobric G, Jung J, Vassallo G, Evans DG, Stagg CJ, Parkes LM, Stivaros S, Muhlert N, Garg S. Neuroanatomical correlates of working memory performance in Neurofibromatosis 1. Cereb Cortex Commun 2022; 3:tgac021. [PMID: 35673329 PMCID: PMC9169056 DOI: 10.1093/texcom/tgac021] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Revised: 05/09/2022] [Accepted: 05/11/2022] [Indexed: 11/25/2022] Open
Abstract
Introduction Neurofibromatosis 1 (NF1) is a single-gene disorder associated with cognitive impairments, particularly with deficits in working memory. Prior research indicates that brain structure is affected in NF1, but it is unclear how these changes relate to aspects of cognition. Methods 29 adolescents aged 11-17 years were compared to age and sex-matched controls. NF1 subjects were assessed using detailed multimodal measurements of working memory at baseline followed by a 3T MR scan. A voxel-based morphometry approach was used to estimate the total and regional gray matter(GM) volumetric differences between the NF1 and control groups. The working memory metrics were subjected to a principal component analysis (PCA) approach. Results The NF1 groups showed increased gray matter volumes in the thalamus, corpus striatum, dorsal midbrain and cerebellum bilaterally in the NF1 group as compared to controls. Principal component analysis on the working memory metrics in the NF1 group yielded three independent factors reflecting high memory load, low memory load and auditory working memory. Correlation analyses revealed that increased volume of posterior cingulate cortex, a key component of the default mode network (DMN) was significantly associated with poorer performance on low working memory load tasks. Conclusion These results are consistent with prior work showing larger subcortical brain volumes in the NF1 cohort. The strong association between posterior cingulate cortex volume and performance on low memory load conditions supports hypotheses of deficient DMN structural development, which in turn may contribute to the cognitive impairments in NF1.
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Affiliation(s)
- Cameron Sawyer
- Division of Neuroscience & Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Oxford Road, Manchester M13 9PL, United Kingdom
| | - Jonathan Green
- Division of Neuroscience & Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Oxford Road, Manchester M13 9PL, United Kingdom
| | - Ben Lim
- Child & Adolescent Mental Health Department, Royal Manchester Children's Hospital, Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Sciences Centre, Manchester, Oxford Road, M13 9WL, United Kingdom
| | - Gorana Pobric
- Division of Neuroscience & Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Oxford Road, Manchester M13 9PL, United Kingdom
| | - JeYoung Jung
- School of Psychology, Precision Imaging Beacon, University of Nottingham, University Park, Nottingham NG7 2RD, United Kingdom
| | - Grace Vassallo
- Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Oxford Road, Manchester M13 9WL, United Kingdom
| | - D Gareth Evans
- Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Oxford Road, Manchester M13 9WL, United Kingdom
| | - Charlotte J Stagg
- Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences & MRC Brain Network Dynamics Unit, University of Oxford, OX3 9DU, United Kingdom
| | - Laura M Parkes
- Division of Neuroscience & Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Oxford Road, Manchester M13 9PL, United Kingdom
| | - Stavros Stivaros
- Geoffrey Jefferson Brain Research Centre, Northern care Alliance NHS Foundation Trust, Stott Lane, Manchester M6 8HD, United Kingdom
| | - Nils Muhlert
- Division of Neuroscience & Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Oxford Road, Manchester M13 9PL, United Kingdom
| | - Shruti Garg
- Division of Neuroscience & Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Oxford Road, Manchester M13 9PL, United Kingdom
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Xing Y, Sapuan AH, Martín-Bastida A, Naidu S, Tench C, Evans J, Sare G, Schwarz ST, Al-Bachari S, Parkes LM, Kanavou S, Raw J, Silverdale M, Bajaj N, Pavese N, Burn D, Piccini P, Grosset DG, Auer DP. Neuromelanin-MRI to Quantify and Track Nigral Depigmentation in Parkinson's Disease: A Multicenter Longitudinal Study Using Template-Based Standardized Analysis. Mov Disord 2022; 37:1028-1039. [PMID: 35165920 PMCID: PMC9303322 DOI: 10.1002/mds.28934] [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] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2021] [Revised: 11/24/2021] [Accepted: 01/09/2022] [Indexed: 12/15/2022] Open
Abstract
Background Clinical diagnosis and monitoring of Parkinson's disease (PD) remain challenging because of the lack of an established biomarker. Neuromelanin‐magnetic resonance imaging (NM‐MRI) is an emerging biomarker of nigral depigmentation indexing the loss of melanized neurons but has unknown prospective diagnostic and tracking performance in multicenter settings. Objectives The aim was to investigate the diagnostic accuracy of NM‐MRI in early PD in a multiprotocol setting and to determine and compare serial NM‐MRI changes in PD and controls. Methods In this longitudinal case–control 3 T MRI study, 148 patients and 97 controls were included from six UK clinical centers, of whom 140 underwent a second scan after 1.5 to 3 years. An automated template‐based analysis was applied for subregional substantia nigra NM‐MRI contrast and volume assessment. A point estimate of the period of prediagnostic depigmentation was computed. Results All NM metrics performed well to discriminate patients from controls, with receiver operating characteristic showing 85% accuracy for ventral NM contrast and 83% for volume. Generalizability using a priori volume cutoff was good (79% accuracy). Serial MRI demonstrated accelerated NM loss in patients compared to controls. Ventral NM contrast loss was point estimated to start 5 to 6 years before clinical diagnosis. Ventral nigral depigmentation was greater in the most affected side, more severe cases, and nigral NM volume change correlated with change in motor severity. Conclusions We demonstrate that NM‐MRI provides clinically useful diagnostic information in early PD across protocols, platforms, and sites. It provides methods and estimated depigmentation rates that highlight the potential to detect preclinical PD and track progression for biomarker‐enabled clinical trials. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society
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Affiliation(s)
- Yue Xing
- School of Medicine, Mental Health & Clinical Neurosciences, Nottingham, United Kingdom.,Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom.,National Institute for Health Research, Nottingham Biomedical Research Centre, Nottingham, United Kingdom
| | - Abdul Halim Sapuan
- School of Medicine, Mental Health & Clinical Neurosciences, Nottingham, United Kingdom.,Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom.,National Institute for Health Research, Nottingham Biomedical Research Centre, Nottingham, United Kingdom
| | - Antonio Martín-Bastida
- Division of Neurology, Imperial College London, London, United Kingdom.,Department of Neurology and Neurosciences, Clínica Universidad de Navarra, Pamplona-Madrid, Spain
| | - Saadnah Naidu
- School of Medicine, Mental Health & Clinical Neurosciences, Nottingham, United Kingdom.,Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom.,Neurology, Nottingham University Hospital Trust, Nottingham, United Kingdom
| | - Christopher Tench
- School of Medicine, Mental Health & Clinical Neurosciences, Nottingham, United Kingdom.,Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom.,National Institute for Health Research, Nottingham Biomedical Research Centre, Nottingham, United Kingdom
| | - Jonathan Evans
- Neurology, Nottingham University Hospital Trust, Nottingham, United Kingdom
| | - Gillian Sare
- Neurology, Nottingham University Hospital Trust, Nottingham, United Kingdom
| | - Stefan T Schwarz
- School of Medicine, Mental Health & Clinical Neurosciences, Nottingham, United Kingdom.,Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom.,Department of Radiology, Cardiff and Vale University Health Board, Cardiff, United Kingdom
| | - Sarah Al-Bachari
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom.,Lancaster Medical School, Lancaster University, Lancaster, United Kingdom.,Department of Neurology, Lancashire Teaching Hospitals NHS Foundation Trust, Preston, United Kingdom
| | - Laura M Parkes
- Division of Neuroscience & Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Sofia Kanavou
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Jason Raw
- Pennine Acute Hospitals NHS Trust, Oldham, United Kingdom
| | - Monty Silverdale
- Division of Neurology, Salford Royal NHS Foundation Trust, Manchester Academic Health Science Centre, University of Manchester, Manchester, United Kingdom
| | - Nin Bajaj
- School of Medicine, Mental Health & Clinical Neurosciences, Nottingham, United Kingdom.,Spire Nottingham Hospital, Nottingham, United Kingdom
| | - Nicola Pavese
- Newcastle Magnetic Resonance Centre & Positron Emission Tomography Centre and Clinical Ageing Research Unit, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - David Burn
- Faculty of Medical Sciences, The Medical School, Framlington Place, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Paola Piccini
- Division of Neurology, Imperial College London, London, United Kingdom.,Department of Brain Science, Imperial College London, London, United Kingdom
| | - Donald G Grosset
- Institute for Neurological Sciences, Queen Elizabeth University Hospital, Glasgow, United Kingdom
| | - Dorothee P Auer
- School of Medicine, Mental Health & Clinical Neurosciences, Nottingham, United Kingdom.,Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom.,National Institute for Health Research, Nottingham Biomedical Research Centre, Nottingham, United Kingdom
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11
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Scott LA, Dickie BR, Rawson SD, Coutts G, Burnett TL, Allan SM, Parker GJ, Parkes LM. Characterisation of microvessel blood velocity and segment length in the brain using multi-diffusion-time diffusion-weighted MRI. J Cereb Blood Flow Metab 2021; 41:1939-1953. [PMID: 33325766 PMCID: PMC8323340 DOI: 10.1177/0271678x20978523] [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] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Multi-diffusion-time diffusion-weighted MRI can probe tissue microstructure, but the method has not been widely applied to the microvasculature. At long diffusion-times, blood flow in capillaries is in the diffusive regime, and signal attenuation is dependent on blood velocity (v) and capillary segment length (l). It is described by the pseudo-diffusion coefficient (D*=vl/6) of intravoxel incoherent motion (IVIM). At shorter diffusion-times, blood flow is in the ballistic regime, and signal attenuation depends on v, and not l. In theory, l could be estimated using D* and v. In this study, we compare the accuracy and repeatability of three approaches to estimating v, and therefore l: the IVIM ballistic model, the velocity autocorrelation model, and the ballistic approximation to the velocity autocorrelation model. Twenty-nine rat datasets from two strains were acquired at 7 T, with b-values between 0 and 1000 smm-2 and diffusion times between 11.6 and 50 ms. Five rats were scanned twice to assess scan-rescan repeatability. Measurements of l were validated using corrosion casting and micro-CT imaging. The ballistic approximation of the velocity autocorrelation model had lowest bias relative to corrosion cast estimates of l, and had highest repeatability.
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Affiliation(s)
- Lauren A Scott
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.,Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Northern Care Alliance & University of Manchester, Manchester, UK
| | - Ben R Dickie
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.,Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Northern Care Alliance & University of Manchester, Manchester, UK
| | - Shelley D Rawson
- The Henry Royce Institute, Department of Materials, The University of Manchester, Manchester, UK
| | - Graham Coutts
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.,Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Northern Care Alliance & University of Manchester, Manchester, UK
| | - Timothy L Burnett
- The Henry Royce Institute, Department of Materials, The University of Manchester, Manchester, UK
| | - Stuart M Allan
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.,Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Northern Care Alliance & University of Manchester, Manchester, UK
| | - Geoff Jm Parker
- The Henry Royce Institute, Department of Materials, The University of Manchester, Manchester, UK.,Bioxydyn Limited, Manchester, UK
| | - Laura M Parkes
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.,Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Northern Care Alliance & University of Manchester, Manchester, UK
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Laansma MA, Bright JK, Al-Bachari S, Anderson TJ, Ard T, Assogna F, Baquero KA, Berendse HW, Blair J, Cendes F, Dalrymple-Alford JC, de Bie RMA, Debove I, Dirkx MF, Druzgal J, Emsley HCA, Garraux G, Guimarães RP, Gutman BA, Helmich RC, Klein JC, Mackay CE, McMillan CT, Melzer TR, Parkes LM, Piras F, Pitcher TL, Poston KL, Rango M, Ribeiro LF, Rocha CS, Rummel C, Santos LSR, Schmidt R, Schwingenschuh P, Spalletta G, Squarcina L, van den Heuvel OA, Vriend C, Wang JJ, Weintraub D, Wiest R, Yasuda CL, Jahanshad N, Thompson PM, van der Werf YD. International Multicenter Analysis of Brain Structure Across Clinical Stages of Parkinson's Disease. Mov Disord 2021; 36:2583-2594. [PMID: 34288137 PMCID: PMC8595579 DOI: 10.1002/mds.28706] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [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: 02/21/2021] [Revised: 06/07/2021] [Accepted: 06/09/2021] [Indexed: 02/02/2023] Open
Abstract
BACKGROUND Brain structure abnormalities throughout the course of Parkinson's disease have yet to be fully elucidated. OBJECTIVE Using a multicenter approach and harmonized analysis methods, we aimed to shed light on Parkinson's disease stage-specific profiles of pathology, as suggested by in vivo neuroimaging. METHODS Individual brain MRI and clinical data from 2357 Parkinson's disease patients and 1182 healthy controls were collected from 19 sources. We analyzed regional cortical thickness, cortical surface area, and subcortical volume using mixed-effects models. Patients grouped according to Hoehn and Yahr stage were compared with age- and sex-matched controls. Within the patient sample, we investigated associations with Montreal Cognitive Assessment score. RESULTS Overall, patients showed a thinner cortex in 38 of 68 regions compared with controls (dmax = -0.20, dmin = -0.09). The bilateral putamen (dleft = -0.14, dright = -0.14) and left amygdala (d = -0.13) were smaller in patients, whereas the left thalamus was larger (d = 0.13). Analysis of staging demonstrated an initial presentation of thinner occipital, parietal, and temporal cortices, extending toward rostrally located cortical regions with increased disease severity. From stage 2 and onward, the bilateral putamen and amygdala were consistently smaller with larger differences denoting each increment. Poorer cognition was associated with widespread cortical thinning and lower volumes of core limbic structures. CONCLUSIONS Our findings offer robust and novel imaging signatures that are generally incremental across but in certain regions specific to disease stages. Our findings highlight the importance of adequately powered multicenter collaborations.
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Affiliation(s)
- Max A Laansma
- Department of Anatomy & Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Joanna K Bright
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, California, USA
| | - Sarah Al-Bachari
- Faculty of Health and Medicine, The University of Lancaster, Lancaster, UK.,Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.,Department of Neurology, Royal Preston Hospital, Preston, UK
| | - Tim J Anderson
- Department of Medicine, University of Otago, Christchurch, Christchurch, New Zealand
| | - Tyler Ard
- Department of Neurology, USC Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, California, USA
| | - Francesca Assogna
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | | | - Henk W Berendse
- Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Jamie Blair
- Department of Medical Imaging, University of Virginia Health System, Charlottesville, Virginia, USA
| | - Fernando Cendes
- Neuroimaging Laboratory, Department of Neurology, University of Campinas, Campinas, Brazil
| | - John C Dalrymple-Alford
- New Zealand Brain Research Institute, Christchurch, New Zealand.,School of Psychology, Speech and Hearing, University of Canterbury, Christchurch, New Zealand.,Brain Research New Zealand - Rangahau Roro Aotearoa, Centre of Research Excellence, Auckland, New Zealand
| | - Rob M A de Bie
- Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Ines Debove
- Department of Neurology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Michiel F Dirkx
- Department of Neurology and Center of Expertise for Parkinson & Movement Disorders, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands.,Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Jason Druzgal
- Department of Radiology and Medical Imaging, University of Virginia, Charlottesville, Virginia, USA
| | - Hedley C A Emsley
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.,Lancaster Medical School, Lancaster University, Preston, UK
| | - Gäetan Garraux
- GIGA-CRC In Vivo Imaging, University of Liège, Liège, Belgium.,Department of Neurology, CHU Liège, Liège, Belgium
| | - Rachel P Guimarães
- Neuroimaging Laboratory, Department of Neurology, University of Campinas, Campinas, Brazil
| | - Boris A Gutman
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, Illinois, USA
| | - Rick C Helmich
- Department of Neurology and Center of Expertise for Parkinson & Movement Disorders, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands.,Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Johannes C Klein
- Department of Clinical Neurosciences, Division of Clinical Neurology, Oxford Parkinson's Disease Centre, Nuffield, University of Oxford, Oxford, UK
| | - Clare E Mackay
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Corey T McMillan
- University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Tracy R Melzer
- Department of Medicine, University of Otago, Christchurch, Christchurch, New Zealand.,New Zealand Brain Research Institute, Christchurch, New Zealand.,Brain Research New Zealand - Rangahau Roro Aotearoa, Centre of Research Excellence, Auckland, New Zealand
| | - Laura M Parkes
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Fabrizio Piras
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Toni L Pitcher
- Department of Medicine, University of Otago, Christchurch, Christchurch, New Zealand.,New Zealand Brain Research Institute, Christchurch, New Zealand.,Brain Research New Zealand - Rangahau Roro Aotearoa, Centre of Research Excellence, Auckland, New Zealand
| | - Kathleen L Poston
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, California, USA
| | - Mario Rango
- Excellence Center for Advanced MR Techniques and Parkinson's Disease Center, Neurology Unit, Fondazione IRCCS Cà Granda Maggiore Policlinico Hospital, University of Milan, Milan, Italy
| | - Letícia F Ribeiro
- Neuroimaging Laboratory, Department of Neurology, University of Campinas, Campinas, Brazil
| | - Cristiane S Rocha
- Neuroimaging Laboratory, Department of Neurology, University of Campinas, Campinas, Brazil.,Department of Medical Genetics, University of Campinas, Campinas, Brazil
| | - Christian Rummel
- Support Center for Advanced Neuroimaging (SCAN), University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Bern, Switzerland
| | - Lucas S R Santos
- Neuroimaging Laboratory, Department of Neurology, University of Campinas, Campinas, Brazil
| | - Reinhold Schmidt
- Department of Neurology, Clinical Division of Neurogeriatrics, Medical University Graz, Graz, Austria
| | | | | | - Letizia Squarcina
- Excellence Center for Advanced MR Techniques and Parkinson's Disease Center, Neurology Unit, Fondazione IRCCS Cà Granda Maggiore Policlinico Hospital, University of Milan, Milan, Italy
| | - Odile A van den Heuvel
- Department of Anatomy & Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Psychiatry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Chris Vriend
- Department of Anatomy & Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Psychiatry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Jiun-Jie Wang
- Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan City, Taiwan.,Department of Diagnostic Radiology, Chang Gung Memorial Hospital, Keelung Branch, Keelung City, Taiwan
| | - Daniel Weintraub
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Roland Wiest
- Support Center for Advanced Neuroimaging (SCAN), University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Bern, Switzerland
| | - Clarissa L Yasuda
- Neuroimaging Laboratory, Department of Neurology, University of Campinas, Campinas, Brazil
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, California, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, California, USA
| | - Ysbrand D van der Werf
- Department of Anatomy & Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
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13
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Dickie BR, Boutin H, Parker GJM, Parkes LM. Alzheimer's disease pathology is associated with earlier alterations to blood-brain barrier water permeability compared with healthy ageing in TgF344-AD rats. NMR Biomed 2021; 34:e4510. [PMID: 33723901 DOI: 10.1002/nbm.4510] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Revised: 02/06/2021] [Accepted: 02/26/2021] [Indexed: 06/12/2023]
Abstract
The effects of Alzheimer's disease (AD) and ageing on blood-brain barrier (BBB) breakdown are investigated in TgF344-AD and wild-type rats aged 13, 18 and 21 months. Permeability surface area products of the BBB to water (PSw ) and gadolinium-based contrast agent (PSg ) were measured in grey matter using multiflip angle multiecho dynamic contrast-enhanced MRI. At 13 months of age, there was no significant difference in PSw between TgF344-AD and wild-types (p = 0.82). Between 13 and 18 months, PSw increased in TgF344-AD rats (p = 0.027), but not in wild-types (p = 0.99), leading to significantly higher PSw in TgF344-AD rats at 18 months, as previously reported (p = 0.012). Between 18 and 21 months, PSw values increased in wild-types (p = 0.050), but not in TgF344-AD rats (p = 0.50). These results indicate that BBB water permeability is affected by both AD pathology and ageing, but that changes occur earlier in the presence of AD pathology. There were no significant genotype or ageing effects on PSg (p > 0.05). In conclusion, we detected increases in BBB water permeability with age in TgF344-AD and wild-type rats, and found that changes occurred at an earlier age in rats with AD pathology.
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Affiliation(s)
- Ben R Dickie
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine, and Health, Stopford Building, University of Manchester, Manchester, UK
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Manchester, UK
| | - Hervé Boutin
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine, and Health, Stopford Building, University of Manchester, Manchester, UK
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Manchester, UK
- Wolfson Molecular Imaging Centre, Faculty of Biology, Medicine, and Health, University of Manchester, Manchester, UK
| | - Geoff J M Parker
- Bioxydyn Ltd, Manchester, UK
- Centre for Medical Image Computing, Department of Computer Science and Department of Neuroinflammation, University College London, London, UK
| | - Laura M Parkes
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine, and Health, Stopford Building, University of Manchester, Manchester, UK
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Manchester, UK
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14
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Kyrtata N, Emsley HCA, Sparasci O, Parkes LM, Dickie BR. A Systematic Review of Glucose Transport Alterations in Alzheimer's Disease. Front Neurosci 2021; 15:626636. [PMID: 34093108 PMCID: PMC8173065 DOI: 10.3389/fnins.2021.626636] [Citation(s) in RCA: 56] [Impact Index Per Article: 18.7] [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: 01/12/2021] [Accepted: 04/22/2021] [Indexed: 12/12/2022] Open
Abstract
Introduction: Alzheimer's disease (AD) is characterized by cerebral glucose hypometabolism. Hypometabolism may be partly due to reduced glucose transport at the blood-brain barrier (BBB) and across astrocytic and neuronal cell membranes. Glucose transporters (GLUTs) are integral membrane proteins responsible for moving glucose from the bloodstream to parenchymal cells where it is metabolized, and evidence indicates vascular and non-vascular GLUTs are altered in AD brains, a process which could starve the brain of glucose and accelerate cognitive decline. Here we review the literature on glucose transport alterations in AD from human and rodent studies. Methods: Literature published between 1st January 1946 and 1st November 2020 within EMBASE and MEDLINE databases was searched for the terms "glucose transporters" AND "Alzheimer's disease". Human and rodent studies were included while reviews, letters, and in-vitro studies were excluded. Results: Forty-three studies fitting the inclusion criteria were identified, covering human (23 studies) and rodent (20 studies). Post-mortem studies showed consistent reductions in GLUT1 and GLUT3 in the hippocampus and cortex of AD brains, areas of the brain closely associated with AD pathology. Tracer studies in rodent models of AD and human AD also exhibit reduced uptake of glucose and glucose-analogs into the brain, supporting these findings. Longitudinal rodent studies clearly indicate that changes in GLUT1 and GLUT3 only occur after amyloid-β pathology is present, and several studies indicate amyloid-β itself may be responsible for GLUT changes. Furthermore, evidence from human and rodent studies suggest GLUT depletion has severe effects on brain function. A small number of studies show GLUT2 and GLUT12 are increased in AD. Anti-diabetic medications improved glucose transport capacity in AD subjects. Conclusions: GLUT1 and GLUT3 are reduced in hippocampal and cortical regions in patients and rodent models of AD, and may be caused by high levels of amyloid-β in these regions. GLUT3 reductions appear to precede the onset of clinical symptoms. GLUT2 and GLUT12 appear to increase and may have a compensatory role. Repurposing anti-diabetic drugs to modify glucose transport shows promising results in human studies of AD.
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Affiliation(s)
- Natalia Kyrtata
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Manchester, United Kingdom
- University Hospitals of Morecambe Bay NHS Foundation Trust, Lancaster, United Kingdom
| | - Hedley C. A. Emsley
- Lancaster Medical School, Lancaster University, Lancaster, United Kingdom
- Department of Neurology, Lancashire Teaching Hospitals NHS Foundation Trust, Preston, United Kingdom
| | - Oli Sparasci
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Manchester, United Kingdom
- Greater Manchester Mental Health NHS Foundation Trust, Manchester, United Kingdom
| | - Laura M. Parkes
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Manchester, United Kingdom
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Ben R. Dickie
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Manchester, United Kingdom
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Manchester, United Kingdom
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15
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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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16
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McFadden JJ, Matthews JC, Scott LA, Parker GJM, Lohézic M, Parkes LM. Optimization of quantitative susceptibility mapping for regional estimation of oxygen extraction fraction in the brain. Magn Reson Med 2021; 86:1314-1329. [PMID: 33780045 DOI: 10.1002/mrm.28789] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [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: 10/06/2020] [Revised: 03/05/2021] [Accepted: 03/08/2021] [Indexed: 01/20/2023]
Abstract
PURPOSE We sought to determine the degree to which oxygen extraction fraction (OEF) estimated using quantitative susceptibility mapping (QSM) depends on two critical acquisition parameters that have a significant impact on acquisition time: voxel size and final echo time. METHODS Four healthy volunteers were imaged using a range of isotropic voxel sizes and final echo times. The 0.7 mm data were downsampled at different stages of QSM processing by a factor of 2 (to 1.4 mm), 3 (2.1 mm), or 4 (2.8 mm) to determine the impact of voxel size on each analysis step. OEF was estimated from 11 veins of varying diameter. Inter- and intra-session repeatability were estimated for the optimal protocol by repeat scanning in 10 participants. RESULTS Final echo time was found to have no significant effect on OEF. The effect of voxel size was significant, with larger voxel sizes underestimating OEF, depending on the proximity of the vein to the superficial surface of the brain and on vein diameter. The last analysis step of estimating vein OEF values from susceptibility images had the largest dependency on voxel size. Inter-session coefficients of variation on OEF estimates of between 5.2% and 8.7% are reported, depending on the vein. CONCLUSION QSM acquisition times can be minimized by reducing the final echo time but an isotropic voxel size no larger than 1 mm is needed to accurately estimate OEF in most medium/large veins in the brain. Such acquisitions can be achieved in under 4 min.
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Affiliation(s)
- John J McFadden
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine, and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Julian C Matthews
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine, and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Lauren A Scott
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine, and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Geoff J M Parker
- Bioxydyn Limited, Manchester, United Kingdom.,Centre for Medical Image Computing, Department of Computer Science and Department of Neuroinflammation, University College London, London, United Kingdom
| | - Maélène Lohézic
- Applications & Workflow, GE Healthcare, Manchester, United Kingdom
| | - Laura M Parkes
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine, and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom.,Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Manchester, United Kingdom
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17
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Al-Bachari S, Naish JH, Parker GJM, Emsley HCA, Parkes LM. Blood-Brain Barrier Leakage Is Increased in Parkinson's Disease. Front Physiol 2020; 11:593026. [PMID: 33414722 PMCID: PMC7784911 DOI: 10.3389/fphys.2020.593026] [Citation(s) in RCA: 98] [Impact Index Per Article: 24.5] [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: 08/09/2020] [Accepted: 11/24/2020] [Indexed: 12/21/2022] Open
Abstract
Background Blood–brain barrier (BBB) disruption has been noted in animal models of Parkinson’s disease (PD) and forms the basis of the vascular hypothesis of neurodegeneration, yet clinical studies are lacking. Objective To determine alterations in BBB integrity in PD, with comparison to cerebrovascular disease. Methods Dynamic contrast enhanced magnetic resonance images were collected from 49 PD patients, 15 control subjects with cerebrovascular disease [control positive (CP)] and 31 healthy control subjects [control negative (CN)], with all groups matched for age. Quantitative maps of the contrast agent transfer coefficient across the BBB (Ktrans) and plasma volume (vp) were produced using Patlak analysis. Differences in Ktrans and vp were assessed with voxel-based analysis as well as in regions associated with PD pathophysiology. In addition, the volume of white matter lesions (WMLs) was obtained from T2-weighted fluid attenuation inversion recovery (FLAIR) images. Results Higher Ktrans, reflecting higher BBB leakage, was found in the PD group than in the CN group using voxel-based analysis; differences were most prominent in the posterior white matter regions. Region of interest analysis confirmed Ktrans to be significantly higher in PD than in CN, predominantly driven by differences in the substantia nigra, normal-appearing white matter, WML and the posterior cortex. WML volume was significantly higher in PD compared to CN. Ktrans values and WML volume were similar in PD and CP, suggesting a similar burden of cerebrovascular disease despite lower cardiovascular risk factors. Conclusion These results show BBB disruption in PD.
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Affiliation(s)
- Sarah Al-Bachari
- Lancaster Medical School, Faculty of Health and Medicine, Lancaster University, Lancaster, United Kingdom.,Department of Neurology, Lancashire Teaching Hospitals NHS Foundation Trust, Preston, United Kingdom.,Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom
| | - Josephine H Naish
- Division of Cardiovascular sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom.,Bioxydyn Limited, Manchester, United Kingdom
| | - Geoff J M Parker
- Bioxydyn Limited, Manchester, United Kingdom.,Centre for Medical Image Computing, Department of Computer Science and Department of Neuroinflammation, University College London, London, United Kingdom
| | - Hedley C A Emsley
- Lancaster Medical School, Faculty of Health and Medicine, Lancaster University, Lancaster, United Kingdom.,Department of Neurology, Lancashire Teaching Hospitals NHS Foundation Trust, Preston, United Kingdom.,Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom
| | - Laura M Parkes
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom.,Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Manchester, United Kingdom
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18
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Lea-Carnall CA, Williams SR, Sanaei-Nezhad F, Trujillo-Barreto NJ, Montemurro MA, El-Deredy W, Parkes LM. GABA Modulates Frequency-Dependent Plasticity in Humans. iScience 2020; 23:101657. [PMID: 33163932 PMCID: PMC7599432 DOI: 10.1016/j.isci.2020.101657] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [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: 07/16/2020] [Revised: 08/27/2020] [Accepted: 10/05/2020] [Indexed: 11/18/2022] Open
Abstract
Frequency-dependent reorganization of the primary somatosensory cortex, together with perceptual changes, arises following repetitive sensory stimulation. Here, we investigate the role of GABA in this process. We co-stimulated two finger tips and measured GABA and Glx using magnetic resonance (MR) spectroscopy at the beginning and end of the stimulation. Participants performed a perceptual learning task before and after stimulation. There were 2 sessions with stimulation frequency either at or above the resonance frequency of the primary somatosensory cortex (23 and 39 Hz, respectively). Perceptual learning occurred following above resonance stimulation only, while GABA reduced during this condition. Lower levels of early GABA were associated with greater perceptual learning. One possible mechanism underlying this finding is that cortical disinhibition “unmasks” lateral connections within the cortex to permit adaptation to the sensory environment. These results provide evidence in humans for a frequency-dependent inhibitory mechanism underlying learning and suggest a mechanism-based approach for optimizing neurostimulation frequency. In the context of repetitive sensory stimulation, GABA release is frequency dependent Stimulating above the resonance frequency of the somatosensory cortex reduces GABA Perceptual learning is associated with a reduction in GABA Early GABA reduction opens a window for plasticity and learning
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Affiliation(s)
- Caroline A. Lea-Carnall
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
- Corresponding author
| | - Stephen R. Williams
- Division of Informatics, Imaging and Data Science, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Faezeh Sanaei-Nezhad
- Division of Informatics, Imaging and Data Science, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Nelson J. Trujillo-Barreto
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Marcelo A. Montemurro
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Wael El-Deredy
- Centro de Investigación y Desarrollo en Ingeniería en Salud, Universidad de Valparaíso, Valparaíso, Chile
- Corresponding author
| | - Laura M. Parkes
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
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Sanaei Nezhad F, Lea‐Carnall CA, Anton A, Jung J, Michou E, Williams SR, Parkes LM. Number of subjects required in common study designs for functional GABA magnetic resonance spectroscopy in the human brain at 3 Tesla. Eur J Neurosci 2020; 51:1784-1793. [PMID: 31705723 PMCID: PMC7216844 DOI: 10.1111/ejn.14618] [Citation(s) in RCA: 8] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Revised: 10/22/2019] [Accepted: 10/24/2019] [Indexed: 01/16/2023]
Abstract
Magnetic resonance spectroscopy (MRS) is a research tool for measuring the concentration of metabolites such as γ-aminobutyric acid (GABA) and glutamate in the brain. MEGA-PRESS has been the preferred pulse sequence for GABA measurements due to low physiological GABA concentrations, hence low signal. To compensate, researchers incorporate long acquisition durations (7-10 min) making functional measurements of this metabolite challenging. Here, the acquisition duration and sample sizes required to detect specific concentration changes in GABA using MEGA-PRESS at 3 T are presented for both between-groups and within-session study designs. 75 spectra were acquired during rest using MEGA-PRESS from 41 healthy volunteers in 6 different brain regions at 3 T with voxel sizes between 13 and 22 cm3 . Between-group and within-session variance was calculated for different acquisition durations and power calculations were performed to determine the number of subjects required to detect a given percentage change in GABA/NAA signal ratio. Within-subject variability was assessed by sampling different segments of a single acquisition. Power calculations suggest that detecting a 15% change in GABA using a 2 min acquisition and a 27 cm3 voxel size, depending on the region, requires between 8 and 93 subjects using a within-session design. A between-group design typically requires more participants to detect the same difference. In brain regions with suboptimal shimming, the subject numbers can be up to 4-fold more. Collecting data for longer than 4 min in brain regions examined in this study is deemed unnecessary, as variance in the signal did not reduce further for longer durations.
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Affiliation(s)
- Faezeh Sanaei Nezhad
- Division of Informatics, Imaging and Data ScienceUniversity of ManchesterManchesterUK
| | | | - Adriana Anton
- Division of Neuroscience and Experimental PsychologyUniversity of ManchesterManchesterUK
| | - JeYoung Jung
- School of PsychologyUniversity of NottinghamNottinghamUK
| | - Emilia Michou
- School of Rehabilitation SciencesUniversity of PatrasPatrasGreece
| | - Stephen R. Williams
- Division of Informatics, Imaging and Data ScienceUniversity of ManchesterManchesterUK
| | - Laura M. Parkes
- Division of Neuroscience and Experimental PsychologyUniversity of ManchesterManchesterUK
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Abstract
There is an important bidirectional relationship between seizures and cerebrovascular disease (CVD). Aside from poststroke epilepsy, Occult CVD is an important cause of late-onset seizures (LOS) and late-onset epilepsy (LOE). Late-onset seizures/LOE are associated with a threefold increased risk of subsequent clinical stroke. This relationship exists not only in later life, but with 'late-onset' seizures or epilepsy occurring from the fourth decade of life onwards. There is increasing evidence for the importance of hypertension and cerebral small vessel disease (SVD) in epileptogenesis, but there is a considerable need for further work to elucidate underlying mechanisms. There may be a disproportionately increased risk of intracerebral hemorrhage (ICH) after LOS/LOE; this too requires further study. There is also a bidirectional relationship between LOS/LOE and cognitive impairment/dementia: it is likely that there are important interactions between vascular and neurodegenerative pathological processes mediating LOE, stroke, and dementia. There is a pressing need for better epidemiological and natural history data as well as elucidation of epileptogenic mechanisms, in order to progress our understanding and to better inform clinical practice.
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Affiliation(s)
- Hedley C A Emsley
- Department of Neurology, Royal Preston Hospital, Lancashire Teaching Hospitals NHS Foundation Trust, Sharoe Green Lane, Fulwood, Preston PR2 9HT, UK; Lancaster Medical School, Lancaster University, Bailrigg, Lancaster LA1 4YW, UK; Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, University of Manchester, Stopford Building, Oxford Road, Manchester M13 9BG, UK.
| | - Laura M Parkes
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, University of Manchester, Stopford Building, Oxford Road, Manchester M13 9BG, UK
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21
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Dickie BR, Parker GJM, Parkes LM. Measuring water exchange across the blood-brain barrier using MRI. Prog Nucl Magn Reson Spectrosc 2020; 116:19-39. [PMID: 32130957 DOI: 10.1016/j.pnmrs.2019.09.002] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2019] [Revised: 09/04/2019] [Accepted: 09/09/2019] [Indexed: 05/11/2023]
Abstract
The blood-brain barrier (BBB) regulates the transfer of solutes and essential nutrients into the brain. Growing evidence supports BBB dysfunction in a range of acute and chronic brain diseases, justifying the need for novel research and clinical tools that can non-invasively detect, characterize, and quantify BBB dysfunction in-vivo. Many approaches already exist for measuring BBB dysfunction in man using positron emission tomography and magnetic resonance imaging (e.g. dynamic contrast-enhanced MRI measurements of gadolinium leakage). This review paper focusses on MRI measurements of water exchange across the BBB, which occurs through a wide range of pathways, and is likely to be a highly sensitive marker of BBB dysfunction. Key mathematical models and acquisition methods are discussed for the two main approaches: those that utilize contrast agents to enhance relaxation rate differences between the intravascular and extravascular compartments and so enhance the sensitivity of MRI signals to BBB water exchange, and those that utilize the dynamic properties of arterial spin labelling to first isolate signal from intravascular spins and then estimate the impact of water exchange on the evolving signal. Data from studies in healthy and pathological brain tissue are discussed, in addition to validation studies in rodents.
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Affiliation(s)
- Ben R Dickie
- Division of Neuroscience and Experimental Psychology, University of Manchester, Oxford Road, Manchester M13 9PT, United Kingdom.
| | - Geoff J M Parker
- Bioxydyn Limited, Manchester M15 6SZ, United Kingdom; Centre for Medical Image Computing, Department of Computer Science and Department of Neuroinflammation, University College London, London, United Kingdom
| | - Laura M Parkes
- Division of Neuroscience and Experimental Psychology, University of Manchester, Oxford Road, Manchester M13 9PT, United Kingdom
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Dickie BR, Vandesquille M, Ulloa J, Boutin H, Parkes LM, Parker GJM. Water-exchange MRI detects subtle blood-brain barrier breakdown in Alzheimer's disease rats. Neuroimage 2018; 184:349-358. [PMID: 30219292 DOI: 10.1016/j.neuroimage.2018.09.030] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [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: 05/24/2018] [Revised: 09/05/2018] [Accepted: 09/12/2018] [Indexed: 01/21/2023] Open
Abstract
Blood-brain barrier (BBB) breakdown has been hypothesized to play a key role in the onset and progression of Alzheimer's disease (AD). However, the question of whether AD itself contributes to loss of BBB integrity is still uncertain, as many in-vivo studies have failed to detect signs of AD-related BBB breakdown. We hypothesize AD-related BBB damage is subtle, and that these negative results arise from a lack of measurement sensitivity. With the aim of developing a more sensitive measure of BBB breakdown, we have designed a novel MRI scanning protocol to quantify the trans-BBB exchange of endogenous water. Using this method, we detect increased BBB water permeability in a rat model of AD that is associated with reduced expression of the tight junction protein occludin. BBB permeability to MRI contrast agent, assessed using dynamic contrast-enhanced (DCE)-MRI, did not differ between transgenic and wild-type animals and was uncorrelated with occludin expression. Our data supports the occurrence of AD-related BBB breakdown, and indicates that such BBB pathology is subtle and may be undetectable using existing 'tracer leakage' methods. Our validated water-exchange MRI method provides a new powerful tool with which to study BBB damage in-vivo.
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Affiliation(s)
- Ben R Dickie
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine, and Health, Stopford Building, University of Manchester, UK.
| | - Matthias Vandesquille
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine, and Health, Stopford Building, University of Manchester, UK
| | | | - Hervé Boutin
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine, and Health, Stopford Building, University of Manchester, UK
| | - Laura M Parkes
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine, and Health, Stopford Building, University of Manchester, UK
| | - Geoff J M Parker
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine, and Health, Stopford Building, University of Manchester, UK; Bioxydyn Ltd, Manchester, UK
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23
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Stefaniak JD, Parkes LM, Parry-Jones AR, Potter GM, Vail A, Jovanovic A, Smith CJ. Enzyme replacement therapy and white matter hyperintensity progression in Fabry disease. Neurology 2018; 91:e1413-e1422. [PMID: 30209238 PMCID: PMC6177273 DOI: 10.1212/wnl.0000000000006316] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [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: 09/21/2017] [Accepted: 07/12/2018] [Indexed: 12/05/2022] Open
Abstract
Objective To explore the association between enzyme replacement therapy (ERT), clinical characteristics, and the rate of progression of white matter hyperintensities (WMH) in patients with Fabry disease (FD). Methods Patients with a confirmed diagnosis of FD, aged 18 years or older, participating in an existing FD observational study (NCT00196742), with at least 2 serial MRI brain scans at least 2 years apart for the period between December 2006 and August 2016 were included in this cohort study. Total WMH volume was estimated for each image using a semiautomated procedure. We performed linear regression to calculate the primary outcome measure of WMH change rate for each participant. Associations between ERT, clinical characteristics, and the primary outcome were explored using multiple linear regression. Results Eight hundred sixty-three MRI time points were analyzed for the 149 included participants. Age (p < 0.0005; increasing age associated with faster WMH progression), total cholesterol (p = 0.03; increasing total cholesterol associated with slower WMH progression), and a history of peripheral pain (p = 0.02; peripheral pain associated with faster WMH progression) were independently associated with WMH change rate in the primary analysis. We did not find an association between “ERT at any point between baseline and final MRI” and WMH change rate (p = 0.22). Conclusion In a large cohort of patients with FD, we did not find an association between ERT and WMH progression, while higher total cholesterol was associated with slower WMH progression. Further research is needed into the pathogenesis and treatment of cerebrovascular disease in this rare condition.
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Affiliation(s)
- James D Stefaniak
- From the Greater Manchester Comprehensive Stroke Centre, Clinical Sciences Building (J.D.S., A.R.P.-J., C.J.S.), Department of Neuroradiology, Greater Manchester Neurosciences Centre (G.M.P.), and The Mark Holland Metabolic Unit (A.J.), Salford Royal NHS Foundation Trust, Manchester Academic Health Science Centre, Salford; and Neuroscience and Aphasia Research Unit, Division of Neuroscience and Experimental Psychology (J.D.S.), Division of Neuroscience and Experimental Psychology (L.M.P.), Division of Cardiovascular Sciences, School of Medical Sciences (A.R.P.-J., C.J.S.), and Centre for Biostatistics, Division of Population Health, Health Services Research and Primary Care (A.V.), University of Manchester, Manchester Academic Health Science Centre, UK
| | - Laura M Parkes
- From the Greater Manchester Comprehensive Stroke Centre, Clinical Sciences Building (J.D.S., A.R.P.-J., C.J.S.), Department of Neuroradiology, Greater Manchester Neurosciences Centre (G.M.P.), and The Mark Holland Metabolic Unit (A.J.), Salford Royal NHS Foundation Trust, Manchester Academic Health Science Centre, Salford; and Neuroscience and Aphasia Research Unit, Division of Neuroscience and Experimental Psychology (J.D.S.), Division of Neuroscience and Experimental Psychology (L.M.P.), Division of Cardiovascular Sciences, School of Medical Sciences (A.R.P.-J., C.J.S.), and Centre for Biostatistics, Division of Population Health, Health Services Research and Primary Care (A.V.), University of Manchester, Manchester Academic Health Science Centre, UK
| | - Adrian R Parry-Jones
- From the Greater Manchester Comprehensive Stroke Centre, Clinical Sciences Building (J.D.S., A.R.P.-J., C.J.S.), Department of Neuroradiology, Greater Manchester Neurosciences Centre (G.M.P.), and The Mark Holland Metabolic Unit (A.J.), Salford Royal NHS Foundation Trust, Manchester Academic Health Science Centre, Salford; and Neuroscience and Aphasia Research Unit, Division of Neuroscience and Experimental Psychology (J.D.S.), Division of Neuroscience and Experimental Psychology (L.M.P.), Division of Cardiovascular Sciences, School of Medical Sciences (A.R.P.-J., C.J.S.), and Centre for Biostatistics, Division of Population Health, Health Services Research and Primary Care (A.V.), University of Manchester, Manchester Academic Health Science Centre, UK
| | - Gillian M Potter
- From the Greater Manchester Comprehensive Stroke Centre, Clinical Sciences Building (J.D.S., A.R.P.-J., C.J.S.), Department of Neuroradiology, Greater Manchester Neurosciences Centre (G.M.P.), and The Mark Holland Metabolic Unit (A.J.), Salford Royal NHS Foundation Trust, Manchester Academic Health Science Centre, Salford; and Neuroscience and Aphasia Research Unit, Division of Neuroscience and Experimental Psychology (J.D.S.), Division of Neuroscience and Experimental Psychology (L.M.P.), Division of Cardiovascular Sciences, School of Medical Sciences (A.R.P.-J., C.J.S.), and Centre for Biostatistics, Division of Population Health, Health Services Research and Primary Care (A.V.), University of Manchester, Manchester Academic Health Science Centre, UK
| | - Andy Vail
- From the Greater Manchester Comprehensive Stroke Centre, Clinical Sciences Building (J.D.S., A.R.P.-J., C.J.S.), Department of Neuroradiology, Greater Manchester Neurosciences Centre (G.M.P.), and The Mark Holland Metabolic Unit (A.J.), Salford Royal NHS Foundation Trust, Manchester Academic Health Science Centre, Salford; and Neuroscience and Aphasia Research Unit, Division of Neuroscience and Experimental Psychology (J.D.S.), Division of Neuroscience and Experimental Psychology (L.M.P.), Division of Cardiovascular Sciences, School of Medical Sciences (A.R.P.-J., C.J.S.), and Centre for Biostatistics, Division of Population Health, Health Services Research and Primary Care (A.V.), University of Manchester, Manchester Academic Health Science Centre, UK
| | - Ana Jovanovic
- From the Greater Manchester Comprehensive Stroke Centre, Clinical Sciences Building (J.D.S., A.R.P.-J., C.J.S.), Department of Neuroradiology, Greater Manchester Neurosciences Centre (G.M.P.), and The Mark Holland Metabolic Unit (A.J.), Salford Royal NHS Foundation Trust, Manchester Academic Health Science Centre, Salford; and Neuroscience and Aphasia Research Unit, Division of Neuroscience and Experimental Psychology (J.D.S.), Division of Neuroscience and Experimental Psychology (L.M.P.), Division of Cardiovascular Sciences, School of Medical Sciences (A.R.P.-J., C.J.S.), and Centre for Biostatistics, Division of Population Health, Health Services Research and Primary Care (A.V.), University of Manchester, Manchester Academic Health Science Centre, UK
| | - Craig J Smith
- From the Greater Manchester Comprehensive Stroke Centre, Clinical Sciences Building (J.D.S., A.R.P.-J., C.J.S.), Department of Neuroradiology, Greater Manchester Neurosciences Centre (G.M.P.), and The Mark Holland Metabolic Unit (A.J.), Salford Royal NHS Foundation Trust, Manchester Academic Health Science Centre, Salford; and Neuroscience and Aphasia Research Unit, Division of Neuroscience and Experimental Psychology (J.D.S.), Division of Neuroscience and Experimental Psychology (L.M.P.), Division of Cardiovascular Sciences, School of Medical Sciences (A.R.P.-J., C.J.S.), and Centre for Biostatistics, Division of Population Health, Health Services Research and Primary Care (A.V.), University of Manchester, Manchester Academic Health Science Centre, UK.
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24
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Ball S, Al-Bachari S, Parkes LM, Emsley HC, McCollum CN. Extracranial arterial wall volume is increased and shows relationships with vascular MRI measures in idiopathic Parkinson’s disease. Clin Neurol Neurosurg 2018; 167:54-58. [DOI: 10.1016/j.clineuro.2018.02.013] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2017] [Revised: 01/02/2018] [Accepted: 02/09/2018] [Indexed: 10/18/2022]
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25
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Stivaros S, Garg S, Tziraki M, Cai Y, Thomas O, Mellor J, Morris AA, Jim C, Szumanska-Ryt K, Parkes LM, Haroon HA, Montaldi D, Webb N, Keane J, Castellanos FX, Silva AJ, Huson S, Williams S, Gareth Evans D, Emsley R, Green J. Randomised controlled trial of simvastatin treatment for autism in young children with neurofibromatosis type 1 (SANTA). Mol Autism 2018; 9:12. [PMID: 29484149 PMCID: PMC5824534 DOI: 10.1186/s13229-018-0190-z] [Citation(s) in RCA: 44] [Impact Index Per Article: 7.3] [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: 10/10/2017] [Accepted: 01/12/2018] [Indexed: 11/24/2022] Open
Abstract
Background Neurofibromatosis 1 (NF1) is a monogenic model for syndromic autism. Statins rescue the social and cognitive phenotype in animal knockout models, but translational trials with subjects > 8 years using cognition/behaviour outcomes have shown mixed results. This trial breaks new ground by studying statin effects for the first time in younger children with NF1 and co-morbid autism and by using multiparametric imaging outcomes. Methods A single-site triple-blind RCT of simvastatin vs. placebo was done. Assessment (baseline and 12-week endpoint) included peripheral MAPK assay, awake magnetic resonance imaging spectroscopy (MRS; GABA and glutamate+glutamine (Glx)), arterial spin labelling (ASL), apparent diffusion coefficient (ADC), resting state functional MRI, and autism behavioural outcomes (Aberrant Behaviour Checklist and Clinical Global Impression). Results Thirty subjects had a mean age of 8.1 years (SD 1.8). Simvastatin was well tolerated. The amount of imaging data varied by test. Simvastatin treatment was associated with (i) increased frontal white matter MRS GABA (t(12) = - 2.12, p = .055), GABA/Glx ratio (t(12) = - 2.78, p = .016), and reduced grey nuclei Glx (ANCOVA p < 0.05, Mann-Whitney p < 0.01); (ii) increased ASL perfusion in ventral diencephalon (Mann-Whitney p < 0.01); and (iii) decreased ADC in cingulate gyrus (Mann-Whitney p < 0.01). Machine-learning classification of imaging outcomes achieved 79% (p < .05) accuracy differentiating groups at endpoint against chance level (64%, p = 0.25) at baseline. Three of 12 (25%) simvastatin cases compared to none in placebo met 'clinical responder' criteria for behavioural outcome. Conclusions We show feasibility of peripheral MAPK assay and autism symptom measurement, but the study was not powered to test effectiveness. Multiparametric imaging suggests possible simvastatin effects in brain areas previously associated with NF1 pathophysiology and the social brain network. Trial registration EU Clinical Trial Register (EudraCT) 2012-005742-38 (www.clinicaltrialsregister.eu).
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Affiliation(s)
- Stavros Stivaros
- Academic Unit of Paediatric Radiology, Royal Manchester Children’s Hospital, Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Sciences Centre, Manchester, UK
- Division of Informatics, Imaging and Data Sciences, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Shruti Garg
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester University NHS Foundation Trust, Greater Manchester Mental Health NHS Foundation Trust, Room 3.311, Jean McFarlane Building, Oxford Road, Manchester, M13 9PL UK
| | - Maria Tziraki
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Ying Cai
- Departments of Neurobiology, Psychiatry and Biobehavioral Sciences and Psychology, Integrative Center for Learning and Memory, Brain Research Institute, Brain Research Institute, University of California, California, LA 90095 USA
| | - Owen Thomas
- Academic Unit of Radiology, Salford Royal Foundation NHS Trust, Manchester Academic Health Sciences Centre, Manchester, UK
| | - Joseph Mellor
- Computer Science, University of Manchester, Manchester, UK
| | - Andrew A. Morris
- Manchester University NHS Foundation Trust, Manchester Academic Health Sciences Centre, Manchester, UK
| | - Carly Jim
- Manchester Metropolitan University, Manchester, UK
| | - Karolina Szumanska-Ryt
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Laura M Parkes
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Hamied A. Haroon
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Daniela Montaldi
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Nicholas Webb
- Department of Paediatric Nephrology, Royal Manchester Children’s Hospital, Manchester University NHS Foundation Trust, Academic Health Sciences Centre, Manchester, UK
| | - John Keane
- Computer Science, University of Manchester, Manchester, UK
| | - Francisco X. Castellanos
- Hassenfeld Children’s Hospital at NYU Langone, Nathan S. Kline Institute for Psychiatric Research, New York, USA
| | - Alcino J. Silva
- Departments of Neurobiology, Psychiatry and Biobehavioral Sciences and Psychology, Integrative Center for Learning and Memory, Brain Research Institute, Brain Research Institute, University of California, California, LA 90095 USA
| | - Sue Huson
- Manchester Centre for Genomic Medicine, St Mary’s Hospital, Manchester University NHS Foundation Trust, Academic Health Sciences Centre, Manchester, UK
| | - Stephen Williams
- Division of Informatics, Imaging and Data Sciences, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - D. Gareth Evans
- Manchester Centre for Genomic Medicine, St Mary’s Hospital, Manchester University NHS Foundation Trust, Academic Health Sciences Centre, Manchester, UK
| | - Richard Emsley
- Centre for Biostatistics, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Jonathan Green
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester University NHS Foundation Trust, Greater Manchester Mental Health NHS Foundation Trust, Room 3.311, Jean McFarlane Building, Oxford Road, Manchester, M13 9PL UK
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26
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Sanaei Nezhad F, Anton A, Michou E, Jung J, Parkes LM, Williams SR. Quantification of GABA, glutamate and glutamine in a single measurement at 3 T using GABA-edited MEGA-PRESS. NMR Biomed 2018; 31:e3847. [PMID: 29130590 PMCID: PMC5765428 DOI: 10.1002/nbm.3847] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/03/2017] [Revised: 08/28/2017] [Accepted: 09/19/2017] [Indexed: 05/05/2023]
Abstract
γ-Aminobutyric acid (GABA) and glutamate (Glu), major neurotransmitters in the brain, are recycled through glutamine (Gln). All three metabolites can be measured by magnetic resonance spectroscopy in vivo, although GABA measurement at 3 T requires an extra editing acquisition, such as Mescher-Garwood point-resolved spectroscopy (MEGA-PRESS). In a GABA-edited MEGA-PRESS spectrum, Glu and Gln co-edit with GABA, providing the possibility to measure all three in one acquisition. In this study, we investigated the reliability of the composite Glu + Gln (Glx) peak estimation and the possibility of Glu and Gln separation in GABA-edited MEGA-PRESS spectra. The data acquired in vivo were used to develop a quality assessment framework which identified MEGA-PRESS spectra in which Glu and Gln could be estimated reliably. Phantoms containing Glu, Gln, GABA and N-acetylaspartate (NAA) at different concentrations were scanned using GABA-edited MEGA-PRESS at 3 T. Fifty-six sets of spectra in five brain regions were acquired from 36 healthy volunteers. Based on the Glu/Gln ratio, data were classified as either within or outside the physiological range. A peak-by-peak quality assessment was performed on all data to investigate whether quality metrics can discriminate between these two classes of spectra. The quality metrics were as follows: the GABA signal-to-noise ratio, the NAA linewidth and the Glx Cramer-Rao lower bound (CRLB). The Glu and Gln concentrations were estimated with precision across all phantoms with a linear relationship between the measured and true concentrations: R1 = 0.95 for Glu and R1 = 0.91 for Gln. A quality assessment framework was set based on the criteria necessary for a good GABA-edited MEGA-PRESS spectrum. Simultaneous criteria of NAA linewidth <8 Hz and Glx CRLB <16% were defined as optimum features for reliable Glu and Gln quantification. Glu and Gln can be reliably quantified from GABA-edited MEGA-PRESS acquisitions. However, this reliability should be controlled using the quality assessment methods suggested in this work.
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Affiliation(s)
- Faezeh Sanaei Nezhad
- Centre for Imaging Science and Manchester Academic Health Sciences CentreUniversity of ManchesterManchesterUK
| | - Adriana Anton
- Division of Neuroscience and Experimental Psychology and Manchester Academic Health Sciences CentreUniversity of ManchesterManchesterUK
| | - Emilia Michou
- School of Medical SciencesUniversity of ManchesterManchesterUK
| | - JeYoung Jung
- Division of Neuroscience and Experimental Psychology and Manchester Academic Health Sciences CentreUniversity of ManchesterManchesterUK
| | - Laura M. Parkes
- Division of Neuroscience and Experimental Psychology and Manchester Academic Health Sciences CentreUniversity of ManchesterManchesterUK
| | - Stephen R. Williams
- Centre for Imaging Science and Manchester Academic Health Sciences CentreUniversity of ManchesterManchesterUK
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27
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Abid KA, Sobowale OA, Parkes LM, Naish J, Parker GJM, du Plessis D, Brough D, Barrington J, Allan SM, Hinz R, Parry-Jones AR. Assessing Inflammation in Acute Intracerebral Hemorrhage with PK11195 PET and Dynamic Contrast-Enhanced MRI. J Neuroimaging 2017; 28:158-161. [PMID: 29064155 DOI: 10.1111/jon.12477] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [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: 08/07/2017] [Accepted: 09/17/2017] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND AND PURPOSE Studies in animal models suggest that inflammation is a major contributor to secondary injury after intracerebral hemorrhage (ICH). Direct, noninvasive monitoring of inflammation in the human brain after ICH will facilitate early-phase development of anti-inflammatory treatments. We sought to investigate the feasibility of multimodality brain imaging in subacute ICH. METHODS Acute ICH patients were recruited to undergo multiparametric MRI (including dynamic contrast-enhanced measurement of blood-brain barrier transfer constant (Ktrans ) and PET with [11 C]-(R)-PK11195). [11 C]-(R)-PK11195 binds to the translocator protein 18 kDa (TSPO), which is rapidly upregulated in activated microglia. Circulating inflammatory markers were measured at the time of PET. RESULTS Five patients were recruited to this feasibility study with imaging between 5 and 16 days after onset. Etiologies included hypertension-related small vessel disease, cerebral amyloid angiopathy (CAA), cavernoma, and arteriovenous malformation (AVM). [11 C]-(R)-PK11195 binding was low in all hematomas and 2 (patient 2 [probable CAA] and 4 [AVM]) cases showed widespread increase in binding in the perihematomal region versus contralateral. All had increased Ktrans in the perihematomal region (mean difference = 2.2 × 10-3 minute-1 ; SD = 1.6 × 10-3 minute-1 ) versus contralateral. Two cases (patients 1 [cavernoma] and 4 [AVM]) had delayed surgery (3 and 12 months post-onset, respectively) with biopsies showing intense microglial activation in perilesional tissue. CONCLUSIONS Our study demonstrates for the first time the feasibility of performing complex multimodality brain imaging for noninvasive monitoring of neuroinflammation for this severe stroke subtype.
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Affiliation(s)
- Kamran A Abid
- Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.,Greater Manchester Neurosciences Centre, Salford Royal NHS Foundation Trust, Manchester, UK
| | - Oluwaseun A Sobowale
- Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.,Greater Manchester Neurosciences Centre, Salford Royal NHS Foundation Trust, Manchester, UK
| | - Laura M Parkes
- Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
| | - Josephine Naish
- Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
| | - Geoff J M Parker
- Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.,Bioxydyn Limited, Manchester, UK
| | - Daniel du Plessis
- Greater Manchester Neurosciences Centre, Salford Royal NHS Foundation Trust, Manchester, UK
| | - David Brough
- Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
| | - Jack Barrington
- Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
| | - Stuart M Allan
- Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
| | - Rainer Hinz
- Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
| | - Adrian R Parry-Jones
- Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.,Greater Manchester Neurosciences Centre, Salford Royal NHS Foundation Trust, Manchester, UK
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Al-Bachari S, Vidyasagar R, Emsley HC, Parkes LM. Structural and physiological neurovascular changes in idiopathic Parkinson's disease and its clinical phenotypes. J Cereb Blood Flow Metab 2017; 37:3409-3421. [PMID: 28112022 PMCID: PMC5624390 DOI: 10.1177/0271678x16688919] [Citation(s) in RCA: 44] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Neurovascular changes are likely to interact importantly with the neurodegenerative process in idiopathic Parkinson's disease (IPD). Markers of neurovascular status (NVS) include white matter lesion (WML) burden and arterial spin labelling (ASL) measurements of cerebral blood flow (CBF) and arterial arrival time (AAT). We investigated NVS in IPD, including an analysis of IPD clinical phenotypes, by comparison with two control groups, one with a history of clinical cerebrovascular disease (CVD) (control positive, CP) and one without CVD (control negative, CN). Fifty-one patients with IPD (mean age 69.0 ± 7.7 years) (21 tremor dominant (TD), 24 postural instability and gait disorder (PIGD) and six intermediates), 18 CP (mean age 70.1 ± 8.0 years) and 34 CN subjects (mean age 67.4 ± 7.6 years) completed a 3T MRI scan protocol including T2-weighted fluid-attenuated inversion recovery (FLAIR) and ASL. IPD patients showed diffuse regions of significantly prolonged AAT, small regions of lower CBF and greater WML burden by comparison with CN subjects. TD patients showed lower WML volume by comparison with PIGD patients. These imaging data thus show altered NVS in IPD, with some evidence for IPD phenotype-specific differences.
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Affiliation(s)
- Sarah Al-Bachari
- 1 Department of Neurology, Salford Royal NHS Foundation Trust, Salford, UK.,2 Division of Informatics, Imaging and Data Sciences, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.,3 Faculty of Health and Medicine, Lancaster University, Lancaster, UK
| | - Rishma Vidyasagar
- 2 Division of Informatics, Imaging and Data Sciences, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.,4 Anatomy and Neuroscience Department, University of Melbourne, Melbourne, Australia.,5 Florey Institute of Neuroscience and Mental Health, Heidelberg, Melbourne, Australia
| | - Hedley Ca Emsley
- 6 Department of Neurology, Royal Preston Hospital, Preston, UK.,7 Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Laura M Parkes
- 2 Division of Informatics, Imaging and Data Sciences, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.,8 Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
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Defres S, Keller SS, Das K, Vidyasagar R, Parkes LM, Burnside G, Griffiths M, Kopelman M, Roberts N, Solomon T. A Feasibility Study of Quantifying Longitudinal Brain Changes in Herpes Simplex Virus (HSV) Encephalitis Using Magnetic Resonance Imaging (MRI) and Stereology. PLoS One 2017; 12:e0170215. [PMID: 28125598 PMCID: PMC5268482 DOI: 10.1371/journal.pone.0170215] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [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: 10/04/2016] [Accepted: 01/02/2017] [Indexed: 12/16/2022] Open
Abstract
OBJECTIVES To assess whether it is feasible to quantify acute change in temporal lobe volume and total oedema volumes in herpes simplex virus (HSV) encephalitis as a preliminary to a trial of corticosteroid therapy. METHODS The study analysed serially acquired magnetic resonance images (MRI), of patients with acute HSV encephalitis who had neuroimaging repeated within four weeks of the first scan. We performed volumetric measurements of the left and right temporal lobes and of cerebral oedema visible on T2 weighted Fluid Attenuated Inversion Recovery (FLAIR) images using stereology in conjunction with point counting. RESULTS Temporal lobe volumes increased on average by 1.6% (standard deviation (SD 11%) in five patients who had not received corticosteroid therapy and decreased in two patients who had received corticosteroids by 8.5%. FLAIR hyperintensity volumes increased by 9% in patients not receiving treatment with corticosteroids and decreased by 29% in the two patients that had received corticosteroids. CONCLUSIONS This study has shown it is feasible to quantify acute change in temporal lobe and total oedema volumes in HSV encephalitis and suggests a potential resolution of swelling in response to corticosteroid therapy. These techniques could be used as part of a randomized control trial to investigate the efficacy of corticosteroids for treating HSV encephalitis in conjunction with assessing clinical outcomes and could be of potential value in helping to predict the clinical outcomes of patients with HSV encephalitis.
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Affiliation(s)
- Sylviane Defres
- Clinical Infection, microbiology and immunology, Institute of Infection and Global Health, University of Liverpool, Liverpool, United Kingdom
- Tropical and Infectious diseases Unit, Liverpool and Broadgreen University Hospital Trust, Liverpool, United Kingdom
- NIHR HPRU in Emerging and Zoonotic Infections, University of Liverpool, Institute of infection and Global Health, Waterhouse Building, Liverpool, United Kingdom
| | - Simon S. Keller
- The Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Liverpool, United Kingdom
- The Department of Neuroradiology, The Walton Centre NHS Foundation Trust, Liverpool, Liverpool, United Kingdom
| | - Kumar Das
- The Department of Neuroradiology, The Walton Centre NHS Foundation Trust, Liverpool, Liverpool, United Kingdom
| | - Rishma Vidyasagar
- Florey Institute of Neuroscience and mental health, Heidelberg, Victoria, Australia
- Department of Anatomy and Neuroscience, University of Melbourne, Victoria, Australia
| | - Laura M. Parkes
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
| | - Girvan Burnside
- The department of Biostatistics, Institute of translational medicine, University of Liverpool, Liverpool, United Kingdom
| | - Michael Griffiths
- Clinical Infection, microbiology and immunology, Institute of Infection and Global Health, University of Liverpool, Liverpool, United Kingdom
- Alder Hey Children’s NHS Foundation Trust, Liverpool, United Kingdom
| | - Michael Kopelman
- Institute of Psychiatry, Kings College London, London, United Kingdom
| | - Neil Roberts
- Medical Physics and Imaging Science, University of Edinburgh, Edinburgh, United Kingdom
| | - Tom Solomon
- Clinical Infection, microbiology and immunology, Institute of Infection and Global Health, University of Liverpool, Liverpool, United Kingdom
- NIHR HPRU in Emerging and Zoonotic Infections, University of Liverpool, Institute of infection and Global Health, Waterhouse Building, Liverpool, United Kingdom
- The Department of Neuroradiology, The Walton Centre NHS Foundation Trust, Liverpool, Liverpool, United Kingdom
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Robson H, Specht K, Beaumont H, Parkes LM, Sage K, Lambon Ralph MA, Zahn R. Arterial spin labelling shows functional depression of non-lesion tissue in chronic Wernicke's aphasia. Cortex 2016; 92:249-260. [PMID: 28525836 PMCID: PMC5480775 DOI: 10.1016/j.cortex.2016.11.002] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [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: 05/25/2016] [Revised: 08/15/2016] [Accepted: 11/02/2016] [Indexed: 11/23/2022]
Abstract
Behavioural impairment post-stroke is a consequence of structural damage and altered functional network dynamics. Hypoperfusion of intact neural tissue is frequently observed in acute stroke, indicating reduced functional capacity of regions outside the lesion. However, cerebral blood flow (CBF) is rarely investigated in chronic stroke. This study investigated CBF in individuals with chronic Wernicke's aphasia (WA) and examined the relationship between lesion, CBF and neuropsychological impairment. Arterial spin labelling CBF imaging and structural MRIs were collected in 12 individuals with chronic WA and 13 age-matched control participants. Joint independent component analysis (jICA) investigated the relationship between structural lesion and hypoperfusion. Partial correlations explored the relationship between lesion, hypoperfusion and language measures. Joint ICA revealed significant differences between the control and WA groups reflecting a large area of structural lesion in the left posterior hemisphere and an associated area of hypoperfusion extending into grey matter surrounding the lesion. Small regions of remote cortical hypoperfusion were observed, ipsilateral and contralateral to the lesion. Significant correlations were observed between the neuropsychological measures (naming, repetition, reading and semantic association) and the jICA component of interest in the WA group. Additional ROI analyses found a relationship between perfusion surrounding the core lesion and the same neuropsychological measures. This study found that core language impairments in chronic WA are associated with a combination of structural lesion and abnormal perfusion in non-lesioned tissue. This indicates that post-stroke impairments are due to a wider disruption of neural function than observable on structural T1w MRI.
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Affiliation(s)
- Holly Robson
- Department of Psychology and Clinical Language Sciences, University of Reading, UK.
| | - Karsten Specht
- Department of Biological and Medical Psychology, University of Bergen, Norway; Department of Clinical Engineering, Haukeland University Hospital, Bergen, Norway
| | | | - Laura M Parkes
- Centre for Imaging Science, Institute of Population Health, University of Manchester, UK
| | - Karen Sage
- Centre for Health and Social Care Research, Sheffield Hallam University, Sheffield, UK
| | - Matthew A Lambon Ralph
- Neuroscience and Aphasia Research Unit, School Psychological Sciences, University of Manchester, UK
| | - Roland Zahn
- Department of Psychological Medicine, Kings College London, UK
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31
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Sanaei Nezhad F, Anton A, Parkes LM, Deakin B, Williams SR. Quantification of glutathione in the human brain by MR spectroscopy at 3 Tesla: Comparison of PRESS and MEGA-PRESS. Magn Reson Med 2016; 78:1257-1266. [PMID: 27797108 PMCID: PMC5469715 DOI: 10.1002/mrm.26532] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.1] [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: 08/05/2016] [Revised: 09/27/2016] [Accepted: 10/06/2016] [Indexed: 12/24/2022]
Abstract
PURPOSE Glutathione (GSH) is an important intracellular antioxidant in the brain. A number of studies report its measurement by localized 1 H spectroscopy using PRESS and STEAM. This study evaluates the reliability and accuracy of GSH measurements from PRESS at 3 Tesla (T) and compares the results to those obtained with MEGA-PRESS. METHODS Phantoms containing brain metabolites, identical except for variable GSH concentration between 0 and 24 mM, were scanned using PRESS (echo time (TE) = 35 ms) and MEGA-PRESS (optimized TE = 130 ms) at 3 T. Spectra of the anterior cingulate cortex and occipital cortex in seven healthy volunteers were also acquired. RESULTS Phantom GSH concentrations from 0 to 3mM were unreliably quantified using PRESS, although at 4 mM and above there was a linear relationship between measured and true concentrations (R2 = 0.99). Using MEGA-PRESS, there was no signal detected at 0 mM GSH, plus a linear relationship (R2 = 0.99) over the full range from 0-24 mM. In brain, concentrations calculated from MEGA-PRESS and PRESS were significantly different in occipital cortex (P < 0.001). Moreover, only MEGA-PRESS reported significant differences in GSH between the two brain regions (P = 0.003). CONCLUSION Due to uncertainties in GSH quantification raised by the study, the authors conclude that physiological concentrations (<4 mM) of GSH cannot be reliably quantified from PRESS (TE = 35 ms) spectra at 3 T. Magn Reson Med 78:1257-1266, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
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Affiliation(s)
- Faezeh Sanaei Nezhad
- Centre for Imaging ScienceManchester Academic Health Science Centre, University of ManchesterManchesterUnited Kingdom
| | - Adriana Anton
- Neuroscience and Psychiatry UnitManchester Academic Health Science Centre, University of ManchesterManchesterUnited Kingdom
| | - Laura M. Parkes
- Centre for Imaging ScienceManchester Academic Health Science Centre, University of ManchesterManchesterUnited Kingdom
| | - Bill Deakin
- Neuroscience and Psychiatry UnitManchester Academic Health Science Centre, University of ManchesterManchesterUnited Kingdom
| | - Stephen R. Williams
- Centre for Imaging ScienceManchester Academic Health Science Centre, University of ManchesterManchesterUnited Kingdom
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32
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Cousins JN, El-Deredy W, Parkes LM, Hennies N, Lewis PA. Cued Reactivation of Motor Learning during Sleep Leads to Overnight Changes in Functional Brain Activity and Connectivity. PLoS Biol 2016; 14:e1002451. [PMID: 27137944 PMCID: PMC4854410 DOI: 10.1371/journal.pbio.1002451] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.0] [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: 09/09/2015] [Accepted: 04/04/2016] [Indexed: 12/29/2022] Open
Abstract
Sleep plays a role in memory consolidation. This is demonstrated by improved performance and neural plasticity underlying that improvement after sleep. Targeted memory reactivation (TMR) allows the manipulation of sleep-dependent consolidation through intentionally biasing the replay of specific memories in sleep, but the underlying neural basis of these altered memories remains unclear. We use functional magnetic resonance imaging (fMRI) to show a change in the neural representation of a motor memory after targeted reactivation in slow-wave sleep (SWS). Participants learned two serial reaction time task (SRTT) sequences associated with different auditory tones (high or low pitch). During subsequent SWS, one sequence was reactivated by replaying the associated tones. Participants were retested on both sequences the following day during fMRI. As predicted, they showed faster reaction times for the cued sequence after targeted memory reactivation. Furthermore, increased activity in bilateral caudate nucleus and hippocampus for the cued relative to uncued sequence was associated with time in SWS, while increased cerebellar and cortical motor activity was related to time in rapid eye movement (REM) sleep. Functional connectivity between the caudate nucleus and hippocampus was also increased after targeted memory reactivation. These findings suggest that the offline performance gains associated with memory reactivation are supported by altered functional activity in key cognitive and motor networks, and that this consolidation is differentially mediated by both REM sleep and SWS. Slow-wave sleep and rapid eye movement sleep are associated with the reactivation and consolidation of a motor skill within distinct brain networks. After a motor skill is learned, the memory undergoes "offline" processing so that improvement occurs even without further practice. Sleep has been shown to enhance this consolidation and, in the process, to reorganize the brain regions involved. However, it remains unclear how sleep does this, and whether different sleep stages have different contributions. One popular idea is that the memory trace is reactivated during slow-wave sleep—a period of sleep characterized by synchronized activity at a slow frequency and high amplitude, as recorded by electroencephalography (EEG)—which drives memory reorganization within the brain. To test this in humans, we took advantage of "targeted memory reactivation," where replay of specific memories is cued by presentation of a sound that was present during learning. After sleep, motor performance was faster for cued memories, suggesting that the trace was consolidated during sleep. Coupled with this, brain activation and connectivity in several motor-learning areas was enhanced for the cued memory. Furthermore, some changes in brain activity were associated with time spent in slow-wave sleep, while others were associated with time spent in rapid-eye movement sleep. These observations provide further insight into sleep's unique role in memory consolidation by showing that offline skill enhancement depends on the reactivation of specific memories, and the associated changes in neural activity may rely upon processing that unfolds across different stages of sleep.
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Affiliation(s)
- James N Cousins
- School of Psychological Sciences, University of Manchester, Manchester, United Kingdom
- Cognitive Neuroscience Laboratory, Duke-NUS Graduate Medical School, Singapore
| | - Wael El-Deredy
- School of Psychological Sciences, University of Manchester, Manchester, United Kingdom
- School of Biomedical Engineering, University of Valparaiso, Valparaiso, Chile
| | - Laura M Parkes
- Centre for Imaging Sciences, University of Manchester, Manchester, United Kingdom
| | - Nora Hennies
- School of Psychological Sciences, University of Manchester, Manchester, United Kingdom
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf Martinistr, Hamburg, Germany
| | - Penelope A Lewis
- School of Psychological Sciences, University of Manchester, Manchester, United Kingdom
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33
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Vidyasagar R, Abernethy L, Pizer B, Avula S, Parkes LM. Quantitative measurement of blood flow in paediatric brain tumours-a comparative study of dynamic susceptibility contrast and multi time-point arterial spin labelled MRI. Br J Radiol 2016; 89:20150624. [PMID: 26975495 PMCID: PMC5258143 DOI: 10.1259/bjr.20150624] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [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] [Indexed: 11/23/2022] Open
Abstract
Objective: Arterial spin-labelling (ASL) MRI uses intrinsic blood water to quantify the cerebral blood flow (CBF), removing the need for the injection of a gadolinium-based contrast agent used for conventional perfusion imaging such as dynamic susceptibility contrast (DSC). Owing to the non-invasive nature of the technique, ASL is an attractive option for use in paediatric patients. This work compared DSC and multi-timepoint ASL measures of CBF in paediatric brain tumours. Methods: Patients (n = 23; 20 low-grade tumours and 3 high-grade tumours) had DSC and multi-timepoint ASL with and without vascular crushers (VC). VC removes the contribution from larger vessel blood flow. Mean perfusion metrics were extracted from control and T1-enhanced tumour regions of interest (ROIs): arterial arrival time (AAT) and CBF from the ASL images with and without VC, relative cerebral blood flow (rCBF), relative cerebral blood volume, delay time (DT) and mean transit time (MTT) from the DSC images. Results: Significant correlations existed for: AAT and DT (r = 0.77, p = 0.0002) and CBF and rCBF (r = 0.56, p = 0.02) in control ROIs for ASL-noVC. No significant correlations existed between DSC and ASL measures in the tumour region. Significant differences between control and tumour ROI were found for MTT (p < 0.001) and rCBF (p < 0.005) measures. Conclusion: Significant correlations between ASL-noVC and DSC measures in the normal brain suggest that DSC is most sensitive to macrovascular blood flow. The absence of significant correlations within the tumour ROI suggests that ASL is sensitive to different physiological mechanisms compared with DSC measures. Advances in knowledge: ASL provides information which is comparable with that of DSC in healthy tissues, but appears to reflect a different physiology in tumour tissues.
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Affiliation(s)
- Rishma Vidyasagar
- 1 Florey Institute of Neuroscience and Mental Health, Heidelberg, Melbourne, VIC, Australia.,2 Department of Anatomy and Neuroscience, University of Melbourne, Melbourne, VIC, Australia
| | - Laurence Abernethy
- 3 Department of Radiology, Alder Hey Children's NHS Foundation Trust, Liverpool, UK
| | - Barry Pizer
- 4 Department of Paediatric Oncology, Alder Hey Children's NHS Foundation Trust, Liverpool, UK
| | - Shivaram Avula
- 3 Department of Radiology, Alder Hey Children's NHS Foundation Trust, Liverpool, UK
| | - Laura M Parkes
- 5 Centre for Imaging Sciences, Faculty of Medicine and Human Sciences, University of Manchester, Manchester, UK
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Lea-Carnall CA, Montemurro MA, Trujillo-Barreto NJ, Parkes LM, El-Deredy W. Cortical Resonance Frequencies Emerge from Network Size and Connectivity. PLoS Comput Biol 2016; 12:e1004740. [PMID: 26914905 PMCID: PMC4767278 DOI: 10.1371/journal.pcbi.1004740] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [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: 09/15/2015] [Accepted: 01/06/2016] [Indexed: 11/25/2022] Open
Abstract
Neural oscillations occur within a wide frequency range with different brain regions exhibiting resonance-like characteristics at specific points in the spectrum. At the microscopic scale, single neurons possess intrinsic oscillatory properties, such that is not yet known whether cortical resonance is consequential to neural oscillations or an emergent property of the networks that interconnect them. Using a network model of loosely-coupled Wilson-Cowan oscillators to simulate a patch of cortical sheet, we demonstrate that the size of the activated network is inversely related to its resonance frequency. Further analysis of the parameter space indicated that the number of excitatory and inhibitory connections, as well as the average transmission delay between units, determined the resonance frequency. The model predicted that if an activated network within the visual cortex increased in size, the resonance frequency of the network would decrease. We tested this prediction experimentally using the steady-state visual evoked potential where we stimulated the visual cortex with different size stimuli at a range of driving frequencies. We demonstrate that the frequency corresponding to peak steady-state response inversely correlated with the size of the network. We conclude that although individual neurons possess resonance properties, oscillatory activity at the macroscopic level is strongly influenced by network interactions, and that the steady-state response can be used to investigate functional networks. When entrained using repetitive stimulation, sensory cortices appear to respond maximally, or resonate, at different driving frequencies: 10Hz in visual cortex; 20Hz and 40Hz in somatosensory and auditory cortices, respectively. The resonance frequencies are inversely correlated to the cortical volume of the respective regions, but it is unclear what drives this relationship. Here we used both computational and empirical data to demonstrate that resonance frequencies are emergent properties of the connectivity parameters of the underlying networks. The experimental paradigm stimulated large and small areas of visual cortex with different size objects made of flickering dots, and varied the driving frequency. Larger cortical areas exhibited maximum response at lower frequency than smaller areas, suggesting the inverse relationship between cortical size and resonance frequency holds, even within the same sensory modality. Computationally, we simulated cortical patches of different sizes and varied their connectivity parameters. We demonstrate that the size of the activated network is inversely related to its resonance frequency and that this change is due to the increased transmission delay and greater node degree within the larger network. The results are important for understanding the functional significance of oscillatory processes, and as a tool for probing changes in functional connectivity.
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Affiliation(s)
- Caroline A. Lea-Carnall
- Faculty of Medical and Human Sciences, University of Manchester, Manchester, United Kingdom
- * E-mail:
| | | | | | - Laura M. Parkes
- Faculty of Medical and Human Sciences, University of Manchester, Manchester, United Kingdom
| | - Wael El-Deredy
- Faculty of Medical and Human Sciences, University of Manchester, Manchester, United Kingdom
- School of Biomedical Engineering, University of Valparaiso, Valparaiso, Chile
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Michael BD, Griffiths MJ, Granerod J, Brown D, Keir G, Wnęk M, Cox DJ, Vidyasagar R, Borrow R, Parkes LM, Solomon T. The Interleukin-1 Balance During Encephalitis Is Associated With Clinical Severity, Blood-Brain Barrier Permeability, Neuroimaging Changes, and Disease Outcome. J Infect Dis 2015; 213:1651-60. [PMID: 26712949 DOI: 10.1093/infdis/jiv771] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.6] [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: 10/01/2015] [Accepted: 12/21/2015] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Encephalitis is parenchymal brain inflammation, commonly due to herpes simplex virus (HSV). Key host inflammatory mediators and their relationship to blood-brain barrier (BBB) permeability, neuroimaging changes, and disease outcome are poorly understood. METHODS We measured levels of 38 mediators in serum (n = 78) and cerebrospinal fluid (n = 37) specimens from patients with encephalitis, including 17 with disease due to HSV infection. Outcome measures were Glasgow coma and outcome scores; CSF to serum albumin ratio, reflecting BBB permeability; and, in patients with HSV infection, magnetic resonance imaging-based temporal lobe volume. RESULTS Serum interleukin 1 receptor antagonist (IL-1RA) levels were elevated in patients with a good outcome (P= .004). Among patients infected with HSV, the ratio of CSF IL-1β to IL-1RA was associated with a worse outcome (P= .009); a ratio of ≥0.55 pg/mL had high specificity and sensitivity for a poor outcome (100% and 83%;P= .015). Temporal lobe volume had a negative correlation with serum IL-1RA level (P= .012) and a positive correlation with serum IL-1α level (P= .0003) and CSF IL-1β level (P= .007). A normal coma score was associated with an elevated interleukin 10 (IL-10) level in serum specimens from HSV-infected patients (P= .007) and CSF specimens from all patients (P= .016); the IL-10 level correlated inversely with BBB permeability (P= .005). CONCLUSIONS A proinflammatory cytokine response is associated with greater clinical severity, BBB permeability, and neuroimaging damage during encephalitis. IL-1 antagonists should be investigated as adjunctive treatment in encephalitis.
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Affiliation(s)
- Benedict Daniel Michael
- Institute of Infection and Global Health Health Protection Research Unit in Emerging and Zoonotic Infections, National Institute for Health Research, University of Liverpool Walton Centre National Health Service (NHS) Foundation Trust
| | - Michael J Griffiths
- Institute of Infection and Global Health Health Protection Research Unit in Emerging and Zoonotic Infections, National Institute for Health Research, University of Liverpool Alderhey Children's NHS Foundation Trust, Liverpool
| | | | - David Brown
- Public Health England, London Influenza and Measles Laboratory, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil
| | - Geoff Keir
- Walton Centre National Health Service (NHS) Foundation Trust
| | | | - Daniel J Cox
- Faculty of Medical and Human Sciences, Centre for Imaging Sciences, Institute of Population Health, University of Manchester
| | - Rishma Vidyasagar
- Faculty of Medical and Human Sciences, Centre for Imaging Sciences, Institute of Population Health, University of Manchester
| | - Ray Borrow
- Vaccine Evaluation Unit, Public Health England, Manchester, United Kingdom
| | - Laura M Parkes
- Faculty of Medical and Human Sciences, Centre for Imaging Sciences, Institute of Population Health, University of Manchester
| | - Tom Solomon
- Institute of Infection and Global Health Health Protection Research Unit in Emerging and Zoonotic Infections, National Institute for Health Research, University of Liverpool Walton Centre National Health Service (NHS) Foundation Trust
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36
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Hanby MF, Al-Bachari S, Makin F, Vidyasagar R, Parkes LM, Emsley HCA. Structural and physiological MRI correlates of occult cerebrovascular disease in late-onset epilepsy. Neuroimage Clin 2015; 9:128-33. [PMID: 26413475 PMCID: PMC4556750 DOI: 10.1016/j.nicl.2015.07.016] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Late-onset epilepsy (LOE), with onset after 50 years of age, is often attributed to underlying occult cerebrovascular disease. LOE is associated with a three-fold increase in subsequent stroke risk, therefore it is important to improve our understanding of pathophysiology. In this exploratory study, we aimed to determine whether established structural magnetic resonance imaging markers and novel physiological imaging markers of occult cerebrovascular disease were more common in patients with LOE than age-matched controls. Sixteen patients with LOE (mean age ± SD: 67.6 ± 6.5 years) and 15 age-matched control subjects (mean age: 65.1 ± 3.9 years) underwent a 3 T MRI scan protocol. T1-weighted images and T2-weighted fluid attenuated inversion recovery (FLAIR) images were used to determine cortical grey matter volume and white matter hyperintensity (WMH) volume respectively, whilst multiple delay time arterial spin labelling (ASL) images were collected at rest and during a hypercapnic challenge. Cerebral blood flow (CBF) and arterial arrival time (AAT) were calculated from ASL data under both normocapnic and hypercapnic conditions. Cerebrovascular reactivity was also calculated for both CBF and AAT relative to the change in end-tidal CO2. Patients with LOE were found to have significantly lower cortical volume than control subjects (33.8 ± 3.8% of intracranial volume vs. 38.0 ± 5.5%, p = 0.02) and significantly higher WMH volume (1339 ± 1408 mm3 vs. 514 ± 481 mm3, p = 0.047). Baseline whole brain AAT was found to be significantly prolonged in patients with LOE in comparison to control subjects (1539 ± 129 ms vs. 1363 ± 167 ms, p = 0.005). Voxel-based analysis showed the significant prolongation of AAT to be predominantly distributed in the frontal and temporal lobes. Voxel-based morphometry showed the lower cortical volume to be localised primarily to temporal lobes. No significant differences in CBF or cerebrovascular reactivity were found between the two groups. Baseline whole brain AAT and cortical volume differences persisted upon further analysis to take account of differences in smoking history between patients and control subjects. These findings suggest that occult cerebrovascular disease is relevant to the pathophysiology of LOE. LOE patients were found to have increased WMHs and reduced GM volume on MRI imaging in comparison to HC. Baseline arterial arrival time was significantly longer in LOE patients than HC. Baseline cerebral blood flow did not differ between LOE patients and HC. Cerebrovascular reactivity did not differ between LOE patients and HC.
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Key Words
- AAT, arterial arrival time
- ASL, arterial spin labelling
- Arterial spin labelling
- CBF, cerebral blood flow
- CT, computerised tomography
- CVD, cerebrovascular disease
- CVR, cerebrovascular reactivity
- Cerebral blood flow
- Cerebrovascular disease
- EEG, electroencephalogram
- ETCO2, end-tidal CO2
- FLAIR, fluid attenuated inversion recovery image
- FWHM, full width half maximum
- GM, grey matter
- ICV, intracranial volume
- LOE, late-onset epilepsy
- Late-onset epilepsy
- MRI, magnetic resonance imaging
- MoCA, Montreal cognitive assessment
- SVD, small vessel disease
- Seizures
- VBA, voxel-based analysis
- VBM, voxel-based morphometry.
- Voxel-based morphometry
- WMH, white matter hyperintensity
- oCVD, occult cerebrovascular disease
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Affiliation(s)
- Martha F Hanby
- Centre for Imaging Science, Institute of Population Health, Faculty of Medical and Human Sciences, University of Manchester, Manchester, UK ; Department of Neurology, Royal Preston Hospital, Preston, UK
| | - Sarah Al-Bachari
- Centre for Imaging Science, Institute of Population Health, Faculty of Medical and Human Sciences, University of Manchester, Manchester, UK
| | - Fadiyah Makin
- Centre for Imaging Science, Institute of Population Health, Faculty of Medical and Human Sciences, University of Manchester, Manchester, UK
| | - Rishma Vidyasagar
- Centre for Imaging Science, Institute of Population Health, Faculty of Medical and Human Sciences, University of Manchester, Manchester, UK
| | - Laura M Parkes
- Centre for Imaging Science, Institute of Population Health, Faculty of Medical and Human Sciences, University of Manchester, Manchester, UK
| | - Hedley C A Emsley
- Department of Neurology, Royal Preston Hospital, Preston, UK ; Faculty of Medical and Human Sciences, University of Manchester, Manchester, UK
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Halai AD, Parkes LM, Welbourne SR. Dual-echo fMRI can detect activations in inferior temporal lobe during intelligible speech comprehension. Neuroimage 2015; 122:214-21. [PMID: 26037055 PMCID: PMC4627358 DOI: 10.1016/j.neuroimage.2015.05.067] [Citation(s) in RCA: 24] [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] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2014] [Revised: 05/22/2015] [Accepted: 05/24/2015] [Indexed: 11/29/2022] Open
Abstract
The neural basis of speech comprehension has been investigated intensively during the past few decades. Incoming auditory signals are analysed for speech-like patterns and meaningful information can be extracted by mapping these sounds onto stored semantic representations. Investigation into the neural basis of speech comprehension has largely focused on the temporal lobe, in particular the superior and posterior regions. The ventral anterior temporal lobe (vATL), which includes the inferior temporal gyrus (ITG) and temporal fusiform gyrus (TFG) is consistently omitted in fMRI studies. In contrast, PET studies have shown the involvement of these ventral temporal regions. One crucial factor is the signal loss experienced using conventional echo planar imaging (EPI) for fMRI, at tissue interfaces such as the vATL. One method to overcome this signal loss is to employ a dual-echo EPI technique. The aim of this study was to use intelligible and unintelligible (spectrally rotated) sentences to determine if the vATL could be detected during a passive speech comprehension task using a dual-echo acquisition. A whole brain analysis for an intelligibility contrast showed bilateral superior temporal lobe activations and a cluster of activation within the left vATL. Converging evidence implicates the same ventral temporal regions during semantic processing tasks, which include language processing. The specific role of the ventral temporal region during intelligible speech processing cannot be determined from this data alone, but the converging evidence from PET, MEG, TMS and neuropsychology strongly suggest that it contains the stored semantic representations, which are activated by the speech decoding process. Intelligible speech comprehension activates bilateral superior temporal lobe. Critically, intelligibility also activates anterior inferior temporal lobe. Phonological processing does not activate inferior temporal lobe. fMRI results converge with existing PET, MEG and neuropsychology. Anterior inferior temporal lobe is involved during speech comprehension.
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Affiliation(s)
- Ajay D Halai
- Neuroscience and Aphasia Research Unit, School of Psychological Sciences, University of Manchester, Zochonis Building, Brunswick Street, Manchester M13 9PL, UK.
| | - Laura M Parkes
- Centre for Imaging Sciences, Institute of Population Health, University of Manchester, Stopford Building, Oxford Road, Manchester M13 9PL, UK
| | - Stephen R Welbourne
- Neuroscience and Aphasia Research Unit, School of Psychological Sciences, University of Manchester, Zochonis Building, Brunswick Street, Manchester M13 9PL, UK
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Azadbakht H, Parkes LM, Haroon HA, Augath M, Logothetis NK, de Crespigny A, D'Arceuil HE, Parker GJM. Validation of High-Resolution Tractography Against In Vivo Tracing in the Macaque Visual Cortex. Cereb Cortex 2015; 25:4299-309. [PMID: 25787833 PMCID: PMC4816782 DOI: 10.1093/cercor/bhu326] [Citation(s) in RCA: 92] [Impact Index Per Article: 10.2] [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: 11/23/2022] Open
Abstract
Diffusion magnetic resonance imaging (MRI) allows for the noninvasive in vivo examination of anatomical connections in the human brain, which has an important role in understanding brain function. Validation of this technique is vital, but has proved difficult due to the lack of an adequate gold standard. In this work, the macaque visual system was used as a model as an extensive body of literature of in vivo and postmortem tracer studies has established a detailed understanding of the underlying connections. We performed probabilistic tractography on high angular resolution diffusion imaging data of 2 ex vivo, in vitro macaque brains. Comparisons were made between identified connections at different thresholds of probabilistic connection “strength,” and with various tracking optimization strategies previously proposed in the literature, and known connections from the detailed visual system wiring map described by Felleman and Van Essen (1991; FVE91). On average, 74% of connections that were identified by FVE91 were reproduced by performing the most successfully optimized probabilistic diffusion MRI tractography. Further comparison with the results of a more recent tracer study (
Markov et al. 2012) suggests that the fidelity of tractography in estimating the presence or absence of interareal connections may be greater than this.
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Affiliation(s)
- Hojjatollah Azadbakht
- Centre for Imaging Sciences, Faculty of Medical and Human Sciences, University of Manchester, Manchester Academic Health Sciences Centre, Manchester, UK
| | - Laura M Parkes
- Centre for Imaging Sciences, Faculty of Medical and Human Sciences, University of Manchester, Manchester Academic Health Sciences Centre, Manchester, UK
| | - Hamied A Haroon
- Centre for Imaging Sciences, Faculty of Medical and Human Sciences, University of Manchester, Manchester Academic Health Sciences Centre, Manchester, UK
| | - Mark Augath
- Max Planck Institute for Biological Cybernetics, Tübingen, Germany
| | - Nikos K Logothetis
- Centre for Imaging Sciences, Faculty of Medical and Human Sciences, University of Manchester, Manchester Academic Health Sciences Centre, Manchester, UK Max Planck Institute for Biological Cybernetics, Tübingen, Germany
| | - Alex de Crespigny
- Athinoula A. Martinos Center, Massachusetts General Hospital, Charlestown, MA, USA
| | - Helen E D'Arceuil
- Athinoula A. Martinos Center, Massachusetts General Hospital, Charlestown, MA, USA
| | - Geoffrey J M Parker
- Centre for Imaging Sciences, Faculty of Medical and Human Sciences, University of Manchester, Manchester Academic Health Sciences Centre, Manchester, UK
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Alsop DC, Detre JA, Golay X, Günther M, Hendrikse J, Hernandez-Garcia L, Lu H, MacIntosh BJ, Parkes LM, Smits M, van Osch MJP, Wang DJJ, Wong EC, Zaharchuk G. Recommended implementation of arterial spin-labeled perfusion MRI for clinical applications: A consensus of the ISMRM perfusion study group and the European consortium for ASL in dementia. Magn Reson Med 2015; 73:102-16. [PMID: 24715426 PMCID: PMC4190138 DOI: 10.1002/mrm.25197] [Citation(s) in RCA: 1457] [Impact Index Per Article: 161.9] [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: 10/02/2013] [Revised: 02/08/2014] [Accepted: 02/10/2014] [Indexed: 12/11/2022]
Abstract
This review provides a summary statement of recommended implementations of arterial spin labeling (ASL) for clinical applications. It is a consensus of the ISMRM Perfusion Study Group and the European ASL in Dementia consortium, both of whom met to reach this consensus in October 2012 in Amsterdam. Although ASL continues to undergo rapid technical development, we believe that current ASL methods are robust and ready to provide useful clinical information, and that a consensus statement on recommended implementations will help the clinical community to adopt a standardized approach. In this review, we describe the major considerations and trade-offs in implementing an ASL protocol and provide specific recommendations for a standard approach. Our conclusion is that as an optimal default implementation, we recommend pseudo-continuous labeling, background suppression, a segmented three-dimensional readout without vascular crushing gradients, and calculation and presentation of both label/control difference images and cerebral blood flow in absolute units using a simplified model.
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Affiliation(s)
- David C. Alsop
- Department of Radiology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - John A. Detre
- Departments of Neurology and Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Xavier Golay
- Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, London, UK
| | - Matthias Günther
- Fraunhofer MEVIS, Bremen, Germany
- University Bremen, Germany
- Mediri GmbH, Heidelberg, Germany
| | - Jeroen Hendrikse
- Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Luis Hernandez-Garcia
- FMRI Laboratory, Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA
| | - Hanzhang Lu
- Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, Texas, USA
| | - Bradley J. MacIntosh
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Department of Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada
| | - Laura M. Parkes
- Centre for Imaging Science, Institute of Population Health, Faculty of Medical and Human Sciences, University of Manchester, Manchester, UK
| | - Marion Smits
- Department of Radiology, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, The Netherlands
| | - Matthias J. P. van Osch
- C.J. Gorter Center for high field MRI, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Danny JJ Wang
- Department of Neurology, University of California Los Angeles, Los Angeles, California, USA
| | - Eric C. Wong
- Departments of Radiology and Psychiatry, University of California San Diego, La Jolla, California, USA
| | - Greg Zaharchuk
- Department of Radiology, Stanford University, Stanford, California, USA
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Alsop DC, Detre JA, Golay X, Günther M, Hendrikse J, Hernandez-Garcia L, Lu H, MacIntosh BJ, Parkes LM, Smits M, van Osch MJP, Wang DJJ, Wong EC, Zaharchuk G. Recommended implementation of arterial spin-labeled perfusion MRI for clinical applications: A consensus of the ISMRM perfusion study group and the European consortium for ASL in dementia. Magn Reson Med 2014. [DOI: 10.1002/mrm.25607] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
- David C. Alsop
- Department of Radiology; Beth Israel Deaconess Medical Center and Harvard Medical School; Boston Massachusetts USA
| | - John A. Detre
- Departments of Neurology and Radiology; University of Pennsylvania; Philadelphia Pennsylvania USA
| | - 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
| | - Jeroen Hendrikse
- Department of Radiology; University Medical Center Utrecht; Utrecht The Netherlands
| | - Luis Hernandez-Garcia
- FMRI Laboratory, Department of Biomedical Engineering; University of Michigan; Ann Arbor Michigan USA
| | - Hanzhang Lu
- Advanced Imaging Research Center; UT Southwestern Medical Center; Dallas Texas USA
| | - Bradley J. MacIntosh
- Department of Medical Biophysics; University of Toronto; Toronto Canada
- Department of Physical Sciences; Sunnybrook Research Institute; Toronto Canada
| | - Laura M. Parkes
- Centre for Imaging Science, Institute of Population Health, Faculty of Medical and Human Sciences; University of Manchester; Manchester UK
| | - Marion Smits
- Department of Radiology, Erasmus MC; University Medical Centre Rotterdam; Rotterdam The Netherlands
| | - Matthias J. P. van Osch
- C. J. Gorter Center for High Field MRI, Department of Radiology; Leiden University Medical Center; Leiden The Netherlands
| | - Danny J. J. Wang
- Department of Neurology; University of California Los Angeles; Los Angeles California USA
| | - Eric C. Wong
- Departments of Radiology and Psychiatry; University of California San Diego; La Jolla California USA
| | - Greg Zaharchuk
- Department of Radiology; Stanford University; Stanford California USA
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Beards SC, Cain JR, Parkes LM, Jackson A. 0918. Grey matter perfusion is preserved during normotensive hypovolaemia, despite reductions in total cerebral blood flow: evidence of local, pressure independent, intra-cerebral vascular autoregulatory response. Intensive Care Med Exp 2014. [PMCID: PMC4796410 DOI: 10.1186/2197-425x-2-s1-o26] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/04/2022] Open
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Beards SC, Brodie S, Cain J, Parkes LM, Jackson A. 0920. Cerebrovascular autoregulation in normotensive hypovolaemia: a study combining lower body negative pressure and MRI. Intensive Care Med Exp 2014. [PMCID: PMC4796068 DOI: 10.1186/2197-425x-2-s1-o28] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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Murray KN, Girard S, Holmes WM, Parkes LM, Williams SR, Parry-Jones AR, Allan SM. Systemic inflammation impairs tissue reperfusion through endothelin-dependent mechanisms in cerebral ischemia. Stroke 2014; 45:3412-9. [PMID: 25228257 DOI: 10.1161/strokeaha.114.006613] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
BACKGROUND AND PURPOSE Systemic inflammation contributes to diverse acute and chronic brain pathologies, and extensive evidence implicates inflammation in stroke susceptibility and poor outcome. Here we investigate whether systemic inflammation alters cerebral blood flow during reperfusion after experimental cerebral ischemia. METHODS Serial diffusion and perfusion-weighted MRI was performed after reperfusion in Wistar rats given systemic (intraperitoneal) interleukin-1β or vehicle before 60-minute transient middle cerebral artery occlusion. The expression and location of endothelin-1 was assessed by polymerase chain reaction, ELISA, and immunofluorescence. RESULTS Systemic interleukin-1 caused a severe reduction in cerebral blood flow and increase in infarct volume compared with vehicle. Restriction in cerebral blood flow was observed alongside activation of the cerebral vasculature and upregulation of the vasoconstricting peptide endothelin-1 in the ischemic penumbra. A microthrombotic profile was also observed in the vasculature of rats receiving interleukin-1. Blockade of endothelin-1 receptors reversed this hypoperfusion, reduced tissue damage, and improved functional outcome. CONCLUSIONS These data suggest patients with a raised inflammatory profile may have persistent deficits in perfusion after reopening of an occluded vessel. Future therapeutic strategies to interrupt the mechanism identified could lead to enhanced recovery of penumbra in patients with a heightened inflammatory burden and a better outcome after stroke.
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Affiliation(s)
- Katie N Murray
- From the Faculty of Life Sciences (K.N.M., S.M.A.) and Centre for Imaging Science (L.M.P., S.R.W.), University of Manchester, Manchester, United Kingdom; Sainte-Justine Hospital Research Centre, University of Montreal, Canada (S.G.); Glasgow Experimental MRI Centre, The University of Glasgow, Glasgow, United Kingdom (W.M.H.); and University of Manchester, Manchester Academic Health Sciences Centre, United Kingdom (A.R.P.-J.)
| | - Sylvie Girard
- From the Faculty of Life Sciences (K.N.M., S.M.A.) and Centre for Imaging Science (L.M.P., S.R.W.), University of Manchester, Manchester, United Kingdom; Sainte-Justine Hospital Research Centre, University of Montreal, Canada (S.G.); Glasgow Experimental MRI Centre, The University of Glasgow, Glasgow, United Kingdom (W.M.H.); and University of Manchester, Manchester Academic Health Sciences Centre, United Kingdom (A.R.P.-J.)
| | - William M Holmes
- From the Faculty of Life Sciences (K.N.M., S.M.A.) and Centre for Imaging Science (L.M.P., S.R.W.), University of Manchester, Manchester, United Kingdom; Sainte-Justine Hospital Research Centre, University of Montreal, Canada (S.G.); Glasgow Experimental MRI Centre, The University of Glasgow, Glasgow, United Kingdom (W.M.H.); and University of Manchester, Manchester Academic Health Sciences Centre, United Kingdom (A.R.P.-J.)
| | - Laura M Parkes
- From the Faculty of Life Sciences (K.N.M., S.M.A.) and Centre for Imaging Science (L.M.P., S.R.W.), University of Manchester, Manchester, United Kingdom; Sainte-Justine Hospital Research Centre, University of Montreal, Canada (S.G.); Glasgow Experimental MRI Centre, The University of Glasgow, Glasgow, United Kingdom (W.M.H.); and University of Manchester, Manchester Academic Health Sciences Centre, United Kingdom (A.R.P.-J.)
| | - Stephen R Williams
- From the Faculty of Life Sciences (K.N.M., S.M.A.) and Centre for Imaging Science (L.M.P., S.R.W.), University of Manchester, Manchester, United Kingdom; Sainte-Justine Hospital Research Centre, University of Montreal, Canada (S.G.); Glasgow Experimental MRI Centre, The University of Glasgow, Glasgow, United Kingdom (W.M.H.); and University of Manchester, Manchester Academic Health Sciences Centre, United Kingdom (A.R.P.-J.)
| | - Adrian R Parry-Jones
- From the Faculty of Life Sciences (K.N.M., S.M.A.) and Centre for Imaging Science (L.M.P., S.R.W.), University of Manchester, Manchester, United Kingdom; Sainte-Justine Hospital Research Centre, University of Montreal, Canada (S.G.); Glasgow Experimental MRI Centre, The University of Glasgow, Glasgow, United Kingdom (W.M.H.); and University of Manchester, Manchester Academic Health Sciences Centre, United Kingdom (A.R.P.-J.).
| | - Stuart M Allan
- From the Faculty of Life Sciences (K.N.M., S.M.A.) and Centre for Imaging Science (L.M.P., S.R.W.), University of Manchester, Manchester, United Kingdom; Sainte-Justine Hospital Research Centre, University of Montreal, Canada (S.G.); Glasgow Experimental MRI Centre, The University of Glasgow, Glasgow, United Kingdom (W.M.H.); and University of Manchester, Manchester Academic Health Sciences Centre, United Kingdom (A.R.P.-J.)
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Al-Bachari S, Parkes LM, Vidyasagar R, Hanby MF, Tharaken V, Leroi I, Emsley HCA. Arterial spin labelling reveals prolonged arterial arrival time in idiopathic Parkinson's disease. Neuroimage Clin 2014; 6:1-8. [PMID: 25379411 PMCID: PMC4215519 DOI: 10.1016/j.nicl.2014.07.014] [Citation(s) in RCA: 45] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/05/2014] [Revised: 07/24/2014] [Accepted: 07/29/2014] [Indexed: 12/30/2022]
Abstract
Idiopathic Parkinson's disease (IPD) is the second most common neurodegenerative disease, yet effective disease modifying treatments are still lacking. Neurodegeneration involves multiple interacting pathological pathways. The extent to which neurovascular mechanisms are involved is not well defined in IPD. We aimed to determine whether novel magnetic resonance imaging (MRI) techniques, including arterial spin labelling (ASL) quantification of cerebral perfusion, can reveal altered neurovascular status (NVS) in IPD. Fourteen participants with IPD (mean ± SD age 65.1 ± 5.9 years) and 14 age and cardiovascular risk factor matched control participants (mean ± SD age 64.6 ± 4.2 years) underwent a 3T MRI scan protocol. ASL images were collected before, during and after a 6 minute hypercapnic challenge. FLAIR images were used to determine white matter lesion score. Quantitative images of cerebral blood flow (CBF) and arterial arrival time (AAT) were calculated from the ASL data both at rest and during hypercapnia. Cerebrovascular reactivity (CVR) images were calculated, depicting the change in CBF and AAT relative to the change in end-tidal CO2. A significant (p = 0.005) increase in whole brain averaged baseline AAT was observed in IPD participants (mean ± SD age 1532 ± 138 ms) compared to controls (mean ± SD age 1335 ± 165 ms). Voxel-wise analysis revealed this to be widespread across the brain. However, there were no statistically significant differences in white matter lesion score, CBF, or CVR between patients and controls. Regional CBF, but not AAT, in the IPD group was found to correlate positively with Montreal cognitive assessment (MoCA) scores. These findings provide further evidence of alterations in NVS in IPD. Investigation of neurovascular status (NVS) in IPD using arterial spin labelling Diffuse prolonged arterial arrival time in IPD compared to controls Reduced regional CBF in the IPD group correlated with cognitive impairment. Clinical evidence of altered NVS in IPD warrants further research.
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Key Words
- 3T, 3 Tesla
- AAT, arterial arrival time
- AD, Alzheimer’s disease
- ASL, arterial spin labelling
- Arterial arrival time
- Arterial spin labelling
- CBF, cerebral blood flow
- CO2, carbon dioxide
- CV, cerebrovascular
- CVD, cerebrovascular disease
- CVR, cerebrovascular reactivity
- CVRAAT, cerebrovascular reactivity measures of arterial arrival time
- CVRCBF, cerebrovascular reactivity measures of cerebral blood flow
- Cerebral blood flow
- Cerebrovascular reactivity
- DS, digit span
- DSST, digit symbol substitution test
- DWMH, deep white matter hyperintensity
- EPI, echo planar imaging
- ETCO2, end-tidal carbon dioxide
- FAS, (verbal) fluency assessment scale
- FLAIR, fluid attenuation inversion recovery
- FWE, family-wise error
- HAM-D, Hamilton depression rating scale
- IPD, idiopathic Parkinson's disease
- Idiopathic Parkinson's disease
- L-dopa, levodopa
- LARS, Lille apathy rating scale
- LEDD, levodopa equivalent daily dose
- MCI, mild cognitive impairment
- MRI, magnetic resonance imaging
- MoCA
- MoCA, Montreal cognitive assessment
- NPI, neuropsychiatric inventory
- NVU, Neurovascular unit
- O2−, oxygen
- PET, positron emission tomography
- PIGD, Postural instability and gait disorder
- PL, parietal lobe
- PVH, periventricular hyperintensity
- ROI, region of interest
- SPECT, single positron emission computed tomography
- SPM, statistical parametric mapping
- STAR, signal targeting with alternating radiofrequency
- TD, tremor dominant
- TE, echo time
- TI, inversion time
- TL, temporal lobe
- TMT-B, trail making test B
- TR, repetition time
- UKPDS BB, United Kingdom Parkinson's Disease Society Brain Bank
- UPDRS, Unified Parkinson's disease Rating Scale
- WAIS-R, Wechsler adult intelligence scale-revised
- WML, white matter lesion
- fMRI, functional magnetic resonance imaging
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Affiliation(s)
- Sarah Al-Bachari
- Department of Neurology, Royal Preston Hospital, Preston, UK ; Centre for Imaging Science, Institute of Population Health, University of Manchester, UK
| | - Laura M Parkes
- Centre for Imaging Science, Institute of Population Health, University of Manchester, UK
| | - Rishma Vidyasagar
- Centre for Imaging Science, Institute of Population Health, University of Manchester, UK
| | - Martha F Hanby
- Department of Neurology, Royal Preston Hospital, Preston, UK
| | - Vivek Tharaken
- Institute of Brain, Behaviour and Mental Health, University of Manchester, UK
| | - Iracema Leroi
- Institute of Brain, Behaviour and Mental Health, University of Manchester, UK
| | - Hedley C A Emsley
- Department of Neurology, Royal Preston Hospital, Preston, UK ; School of Medicine, University of Manchester, UK
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Gibson LM, Hanby MF, Al-Bachari SM, Parkes LM, Allan SM, Emsley HCA. Late-onset epilepsy and occult cerebrovascular disease. J Cereb Blood Flow Metab 2014; 34:564-70. [PMID: 24517978 PMCID: PMC3982095 DOI: 10.1038/jcbfm.2014.25] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/06/2013] [Accepted: 01/13/2014] [Indexed: 11/09/2022]
Abstract
The interface between cerebrovascular disease (CVD) and epilepsy is complex and multifaceted. Late-onset epilepsy (LOE) is increasingly common and is often attributed to CVD, and is indeed associated with an increased risk of stroke. This relationship is easily recognizable where there is a history of stroke, particularly involving the cerebral cortex. However, the relationship with otherwise occult, subcortical CVD is currently less well established yet causality is often invoked. In this review, we consider the diagnosis of LOE in clinical practice--including its behaviour as a potential mimic of acute ischemic stroke and transient ischemic attack; evidence for an association between occult CVD and LOE; and potential mechanisms of epileptogenesis in occult CVD, including potential interrelationships between disordered cerebral metabolism and perfusion, disrupted neurovascular unit integrity, blood-brain barrier dysfunction, and inflammation. We also discuss recently recognized issues concerning antiepileptic drug treatment and vascular risk and consider a variety of less common CVD entities associated with seizures.
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Affiliation(s)
- Lorna M Gibson
- Division of Clinical Neurosciences, Western General Hospital, Edinburgh, UK
| | | | - Sarah M Al-Bachari
- 1] Department of Neurology, Royal Preston Hospital, Preston, UK [2] University of Manchester, Manchester, UK
| | - Laura M Parkes
- Biomedical Imaging Institute, University of Manchester, Manchester, UK
| | - Stuart M Allan
- Faculty of Life Sciences, University of Manchester, Manchester, UK
| | - Hedley C A Emsley
- 1] Department of Neurology, Royal Preston Hospital, Preston, UK [2] School of Medicine, University of Manchester, Manchester, UK
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Halai AD, Welbourne SR, Embleton K, Parkes LM. A comparison of dual gradient-echo and spin-echo fMRI of the inferior temporal lobe. Hum Brain Mapp 2014; 35:4118-28. [PMID: 24677506 DOI: 10.1002/hbm.22463] [Citation(s) in RCA: 78] [Impact Index Per Article: 7.8] [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: 05/20/2013] [Revised: 10/17/2013] [Accepted: 01/06/2014] [Indexed: 11/11/2022] Open
Abstract
Magnetic susceptibility differences at tissue interfaces lead to signal loss in conventional gradient-echo (GE) EPI. This poses a problem for fMRI in language and memory paradigms, which activate the most affected regions. Two methods proposed to overcome this are spin-echo EPI and dual GE EPI, where two EPI read-outs are serially collected at a short and longer echo time. The spin-echo method applies a refocusing pulse to recover dephased MR signal due to static field inhomogeneities, but is known to have a relatively low blood oxygenation level dependant (BOLD) sensitivity. In comparison, GE has superior BOLD sensitivity, and by employing an additional shorter echo, in a dual GE sequence, it can reduce signal loss due to spin dephasing. We directly compared dual GE and spin-echo fMRI during a semantic categorization task, which has been shown to activate the inferior temporal region-a region known to be affected by magnetic susceptibility. A whole brain analysis showed that the dual GE resulted in significantly higher activation within the left inferior temporal fusiform (ITF) cortex, compared to spin-echo. The inferior frontal gyrus (IFG) was activated for dual GE, but not spin-echo. Regions of interest analysis was carried out on the anterior and posterior ITF, left and right IFG, and part of the cerebellum. Dual GE outperformed spin-echo in the anterior and posterior ITF and bilateral IFG regions, whilst being equal in the cerebellum. Hence, dual GE should be the method of choice for fMRI studies of inferior temporal regions.
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Affiliation(s)
- Ajay D Halai
- Neuroscience and Aphasia Research Unit, School of Psychological Sciences, University of Manchester, Zochonis Building, Manchester, United Kingdom
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47
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Vidyasagar R, Folger SE, Parkes LM. Re-wiring the brain: increased functional connectivity within primary somatosensory cortex following synchronous co-activation. Neuroimage 2014; 92:19-26. [PMID: 24508649 PMCID: PMC4010953 DOI: 10.1016/j.neuroimage.2014.01.052] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [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: 10/25/2013] [Revised: 12/31/2013] [Accepted: 01/26/2014] [Indexed: 10/25/2022] Open
Abstract
The primary somatosensory cortex shows precise topographical organisation, but can be quickly modified by alterations to sensory inputs. Temporally correlated sensory inputs to the digits can result in the merging of digit representations on the cortical surface. Underlying mechanisms driving these changes are unclear but the strengthening of intra-cortical synaptic connections via Hebbian mechanisms has been suggested. We use fMRI measures of temporal coherence to infer alterations in the relative strength of neuronal connections between digit regions 2 and 4 following 3 hours of synchronous and asynchronous co-activation. Following synchronous co-activation we find a 20% increase in temporal coherence of the fMRI signal (p=0.0004). No significant change is seen following asynchronous co-activation suggesting that temporal coincidence between the two digit inputs during co-activation is driving this coherence change. In line with previous work we also find a trend towards reduced separation of the digit representations following synchronous co-activation and significantly increased separation for the asynchronous case. Increased coherence is significantly correlated with reduced digit separation for the synchronous case. This study shows that passive synchronous stimulation to the digits strengthens the underlying cortical connections between the digit regions in only a few hours, and that this mechanism may be related to topographical re-organisation.
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Affiliation(s)
- Rishma Vidyasagar
- Centre for Imaging Sciences, Institute of Population Health, University of Manchester, M13 9PT, UK; Magnetic Resonance Imaging and Analysis Research Centre (MARIARC), University of Liverpool, L69 3GE, UK.
| | - Stephen E Folger
- Department of Physical Therapy Education, Elon University, Campus Box 2085, Elon, NC 27244-2085, USA
| | - Laura M Parkes
- Centre for Imaging Sciences, Institute of Population Health, University of Manchester, M13 9PT, UK
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Sarsam M, Parkes LM, Roberts N, Reid GS, Kinderman P. The Queen and I: neural correlates of altered self-related cognitions in major depressive episode. PLoS One 2013; 8:e78844. [PMID: 24205330 PMCID: PMC3813625 DOI: 10.1371/journal.pone.0078844] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2013] [Accepted: 09/16/2013] [Indexed: 11/19/2022] Open
Abstract
Background Pervasive negative thoughts about the self are central to the experience of depression. Brain imaging studies in the general population have localised self-related cognitive processing to areas of the medial pre-frontal cortex. Aims To use fMRI to compare the neural correlates of self-referential processing in depressed and non-depressed participants. Method Cross-sectional comparison of regional activation using Blood Oxygen Level Dependent (BOLD) fMRI in 13 non-medicated participants with major depressive episode and 14 comparison participants, whilst carrying out a self-referential cognitive task. Results Both groups showed significant activation of the dorsomedial pre-frontal cortex and posterior cingulate cortex in the ‘self-referent’ condition. The depressed group showed significantly greater activation in the medial superior frontal cortex during the self-referent task. No difference was observed between groups in the ‘other-referent’ condition. Conclusions Major depressive episode is associated with specific neurofunctional changes related to self-referential processing.
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Affiliation(s)
- May Sarsam
- Institute of Psychology, Health and Society, University of Liverpool, Liverpool, United Kingdom
| | - Laura M. Parkes
- Centre for Imaging Sciences, Institute of Population Health, University of Manchester, Manchester, United Kingdom
| | - Neil Roberts
- Clinical Research Imaging Centre (CRIC), University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Graeme S. Reid
- Division of Health Research, Lancaster University, Lancaster, United Kingdom
| | - Peter Kinderman
- Institute of Psychology, Health and Society, University of Liverpool, Liverpool, United Kingdom
- * E-mail:
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Vidyasagar R, Greyling A, Draijer R, Corfield DR, Parkes LM. The effect of black tea and caffeine on regional cerebral blood flow measured with arterial spin labeling. J Cereb Blood Flow Metab 2013; 33:963-8. [PMID: 23486295 PMCID: PMC3677118 DOI: 10.1038/jcbfm.2013.40] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Black tea consumption has been shown to improve peripheral vascular function. Its effect on brain vasculature is unknown, though tea contains small amounts of caffeine, a psychoactive substance known to influence cerebral blood flow (CBF). We investigated the effects on CBF due to the intake of tea components in 20 healthy men in a double-blinded, randomized, placebo-controlled study. On separate days, subjects received a single dose of 184 mg caffeine (equivalent to one strong espresso coffee), 2,820 mg black tea solids containing 184 mg caffeine (equivalent to 6 cups of tea), 2,820 mg decaffeinated black tea solids, or placebo. The CBF and cerebrovascular reactivity (CVR) to hypercapnia were measured with arterial spin labeled magnetic resonance imaging (MRI) before and 2 hours after administration. We found a significant global reduction with caffeine (20%) and tea (21%) in gray matter CBF, with no effect of decaffeinated tea, suggesting that only caffeine influences CBF acutely. Voxelwise analysis revealed the effect of caffeine to be regionally specific. None of the interventions had an effect on CVR. Additional research is required to conclude on the physiologic relevance of these findings and the chronic effects of caffeine and tea intake on CBF.
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Affiliation(s)
- Rishma Vidyasagar
- Centre for Imaging Sciences, Institute of Population Health, University of Manchester, Manchester, UK.
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O'Connor JPB, Tofts PS, Miles KA, Parkes LM, Thompson G, Jackson A. Dynamic contrast-enhanced imaging techniques: CT and MRI. Br J Radiol 2012; 84 Spec No 2:S112-20. [PMID: 22433822 DOI: 10.1259/bjr/55166688] [Citation(s) in RCA: 123] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Over the last few decades there has been considerable research into quantifying the cerebral microvasculature with imaging, for use in studies of the human brain and various pathologies including cerebral tumours. This review highlights key issues in dynamic contrast-enhanced CT, dynamic contrast-enhanced MRI and arterial spin labelling, the various applications of which are considered elsewhere in this special issue of the British Journal of Radiology.
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Affiliation(s)
- J P B O'Connor
- Imaging Science, Proteomics and Genomics Research Group, University of Manchester, Manchester, UK. james.o‘
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