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Arnaldi D, Mattioli P, Raffa S, Pardini M, Massa F, Iranzo A, Perissinotti A, Niñerola-Baizán A, Gaig C, Serradell M, Muñoz-Lopetegi A, Mayà G, Liguori C, Fernandes M, Placidi F, Chiaravalloti A, Šonka K, Dušek P, Zogala D, Trnka J, Boeve BF, Miyagawa T, Lowe VJ, Miyamoto T, Miyamoto M, Puligheddu M, Figorilli M, Serra A, Hu MT, Klein JC, Bes F, Kunz D, Cochen De Cock V, de Verbizier D, Plazzi G, Antelmi E, Terzaghi M, Bossert I, Kulcsárová K, Martino A, Giuliani A, Pagani M, Nobili F, Morbelli S. Presynaptic Dopaminergic Imaging Characterizes Patients with REM Sleep Behavior Disorder Due to Synucleinopathy. Ann Neurol 2024. [PMID: 38466158 DOI: 10.1002/ana.26902] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Revised: 02/09/2024] [Accepted: 02/19/2024] [Indexed: 03/12/2024]
Abstract
OBJECTIVE To apply a machine learning analysis to clinical and presynaptic dopaminergic imaging data of patients with rapid eye movement (REM) sleep behavior disorder (RBD) to predict the development of Parkinson disease (PD) and dementia with Lewy bodies (DLB). METHODS In this multicenter study of the International RBD study group, 173 patients (mean age 70.5 ± 6.3 years, 70.5% males) with polysomnography-confirmed RBD who eventually phenoconverted to overt alpha-synucleinopathy (RBD due to synucleinopathy) were enrolled, and underwent baseline presynaptic dopaminergic imaging and clinical assessment, including motor, cognitive, olfaction, and constipation evaluation. For comparison, 232 RBD non-phenoconvertor patients (67.6 ± 7.1 years, 78.4% males) and 160 controls (68.2 ± 7.2 years, 53.1% males) were enrolled. Imaging and clinical features were analyzed by machine learning to determine predictors of phenoconversion. RESULTS Machine learning analysis showed that clinical data alone poorly predicted phenoconversion. Presynaptic dopaminergic imaging significantly improved the prediction, especially in combination with clinical data, with 77% sensitivity and 85% specificity in differentiating RBD due to synucleinopathy from non phenoconverted RBD patients, and 85% sensitivity and 86% specificity in discriminating PD-converters from DLB-converters. Quantification of presynaptic dopaminergic imaging showed that an empirical z-score cutoff of -1.0 at the most affected hemisphere putamen characterized RBD due to synucleinopathy patients, while a cutoff of -1.0 at the most affected hemisphere putamen/caudate ratio characterized PD-converters. INTERPRETATION Clinical data alone poorly predicted phenoconversion in RBD due to synucleinopathy patients. Conversely, presynaptic dopaminergic imaging allows a good prediction of forthcoming phenoconversion diagnosis. This finding may be used in designing future disease-modifying trials. ANN NEUROL 2024.
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Affiliation(s)
- Dario Arnaldi
- Department of Neuroscience (DINOGMI), University of Genoa, Genoa, Italy
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Pietro Mattioli
- Department of Neuroscience (DINOGMI), University of Genoa, Genoa, Italy
| | - Stefano Raffa
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Matteo Pardini
- Department of Neuroscience (DINOGMI), University of Genoa, Genoa, Italy
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Federico Massa
- Department of Neuroscience (DINOGMI), University of Genoa, Genoa, Italy
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Alex Iranzo
- Neurology Service, Sleep Disorder Centre, Hospital Clínic Barcelona, Universitat de Barcelona, IDIBAPS, CIBERNED: CB06/05/0018-ISCIII, Barcelona, Spain
| | - Andres Perissinotti
- Nuclear Medicine Service, Hospital Clínic Barcelona, Biomedical Research Networking Centre of Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), ISCIII, Barcelona, Spain
| | - Aida Niñerola-Baizán
- Nuclear Medicine Service, Hospital Clínic Barcelona, Biomedical Research Networking Centre of Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), ISCIII, Barcelona, Spain
| | - Carles Gaig
- Neurology Service, Sleep Disorder Centre, Hospital Clínic Barcelona, Universitat de Barcelona, IDIBAPS, CIBERNED: CB06/05/0018-ISCIII, Barcelona, Spain
| | - Monica Serradell
- Neurology Service, Sleep Disorder Centre, Hospital Clínic Barcelona, Universitat de Barcelona, IDIBAPS, CIBERNED: CB06/05/0018-ISCIII, Barcelona, Spain
| | - Amaia Muñoz-Lopetegi
- Neurology Service, Sleep Disorder Centre, Hospital Clínic Barcelona, Universitat de Barcelona, IDIBAPS, CIBERNED: CB06/05/0018-ISCIII, Barcelona, Spain
| | - Gerard Mayà
- Neurology Service, Sleep Disorder Centre, Hospital Clínic Barcelona, Universitat de Barcelona, IDIBAPS, CIBERNED: CB06/05/0018-ISCIII, Barcelona, Spain
| | - Claudio Liguori
- Department of Systems Medicine, University of Rome Tor Vergata, Rome, Italy
- Sleep Medicine Center, Neurology Unit, University Hospital of Rome Tor Vergata, Rome, Italy
| | - Mariana Fernandes
- Department of Systems Medicine, University of Rome Tor Vergata, Rome, Italy
| | - Fabio Placidi
- Department of Systems Medicine, University of Rome Tor Vergata, Rome, Italy
- Sleep Medicine Center, Neurology Unit, University Hospital of Rome Tor Vergata, Rome, Italy
| | - Agostino Chiaravalloti
- Department of Biomedicine and Prevention, University of Rome "Tor Vergata", Rome, Italy
- IRCCS Neuromed, Pozzilli, Italy
| | - Karel Šonka
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Petr Dušek
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - David Zogala
- Institute of Nuclear Medicine, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Jiri Trnka
- Institute of Nuclear Medicine, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Bradley F Boeve
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Toji Miyagawa
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Val J Lowe
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - Tomoyuki Miyamoto
- Department of Neurology, Dokkyo Medical University Saitama Medical Center, Saitama, Japan
| | - Masayuki Miyamoto
- Center of Sleep Medicine, Dokkyo Medical University Hospital, Tochigi, Japan
| | - Monica Puligheddu
- Sleep Disorder Center, Department of Public Health and Clinical and Molecular Medicine, University of Cagliari, Cagliari, Italy
| | - Michela Figorilli
- Sleep Disorder Center, Department of Public Health and Clinical and Molecular Medicine, University of Cagliari, Cagliari, Italy
| | - Alessandra Serra
- Nuclear Medicine Unit, Department of Medical Science and Public Health, University of Cagliari, Cagliari, Italy
| | - Michele T Hu
- Division of Neurology, Nuffield Department of Clinical Neurosciences, Oxford University, Oxford, UK
| | - Johannes C Klein
- Division of Neurology, Nuffield Department of Clinical Neurosciences, Oxford University, Oxford, UK
| | - Frederik Bes
- Clinic of Sleep & Chronomedicine, St. Hedwig-Hospital, Berlin, Germany
- Institute of Physiology, Sleep Research & Clinical Chronobiology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Dieter Kunz
- Clinic of Sleep & Chronomedicine, St. Hedwig-Hospital, Berlin, Germany
- Institute of Physiology, Sleep Research & Clinical Chronobiology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Valérie Cochen De Cock
- Sleep and Neurology Department, Beau Soleil Clinic, Montpellier, France
- EuroMov Digital Health in Motion, Univ Montpellier, IMT Mines Ales, Montpellier, France
| | | | - Giuseppe Plazzi
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio-Emilia, Modena, Italy
| | - Elena Antelmi
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Michele Terzaghi
- Sleep Medicine and Epilepsy Unit, IRCCS Mondino Foundation, Pavia, Italy
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Irene Bossert
- Nuclear Medicine Unit, ICS Maugeri SpA SB IRCCS, Pavia, Italy
| | - Kristína Kulcsárová
- Department of Neurology, P. J. Safarik University, Kosice, Slovak Republic
- Department of Neurology, University Hospital of L. Pasteur, Kosice, Slovak Republic
| | - Alessio Martino
- Department of Business and Management, LUISS University, Rome, Italy
| | - Alessandro Giuliani
- Department of Environment and Health, Istituto Superiore di Sanità (Italian National Institute of Health), Rome, Italy
| | - Marco Pagani
- Institute of Cognitive Sciences and Technologies, Consiglio Nazionale delle Ricerche, Rome, Italy
| | - Flavio Nobili
- Department of Neuroscience (DINOGMI), University of Genoa, Genoa, Italy
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Silvia Morbelli
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
- Nuclear Medicine Unit, Department of Medical Sciences, University of Turin, Turin, Italy
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2
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Evangelisti S, Boessenkool S, Pflanz CP, Basting R, Betts JF, Jenkinson M, Clare S, Muhammed K, LeHeron C, Armstrong R, Klein JC, Husain M, Nemeth AH, Hu MT, Douaud G. Subthalamic nucleus shows opposite functional connectivity pattern in Huntington's and Parkinson's disease. Brain Commun 2023; 5:fcad282. [PMID: 38075949 PMCID: PMC10699743 DOI: 10.1093/braincomms/fcad282] [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] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 05/26/2023] [Accepted: 11/06/2023] [Indexed: 02/12/2024] Open
Abstract
Huntington's and Parkinson's disease are two movement disorders representing mainly opposite states of the basal ganglia inhibitory function. Despite being an integral part of the cortico-subcortico-cortical circuitry, the subthalamic nucleus function has been studied at the level of detail required to isolate its signal only through invasive studies in Huntington's and Parkinson's disease. Here, we tested whether the subthalamic nucleus exhibited opposite functional signatures in early Huntington's and Parkinson's disease. We included both movement disorders in the same whole-brain imaging study, and leveraged ultra-high-field 7T MRI to achieve the very fine resolution needed to investigate the smallest of the basal ganglia nuclei. Eleven of the 12 Huntington's disease carriers were recruited at a premanifest stage, while 16 of the 18 Parkinson's disease patients only exhibited unilateral motor symptoms (15 were at Stage I of Hoehn and Yahr off medication). Our group comparison interaction analyses, including 24 healthy controls, revealed a differential effect of Huntington's and Parkinson's disease on the functional connectivity at rest of the subthalamic nucleus within the sensorimotor network, i.e. an opposite effect compared with their respective age-matched healthy control groups. This differential impact in the subthalamic nucleus included an area precisely corresponding to the deep brain stimulation 'sweet spot'-the area with maximum overall efficacy-in Parkinson's disease. Importantly, the severity of deviation away from controls' resting-state values in the subthalamic nucleus was associated with the severity of motor and cognitive symptoms in both diseases, despite functional connectivity going in opposite directions in each disorder. We also observed an altered, opposite impact of Huntington's and Parkinson's disease on functional connectivity within the sensorimotor cortex, once again with relevant associations with clinical symptoms. The high resolution offered by the 7T scanner has thus made it possible to explore the complex interplay between the disease effects and their contribution on the subthalamic nucleus, and sensorimotor cortex. Taken altogether, these findings reveal for the first time non-invasively in humans a differential, clinically meaningful impact of the pathophysiological process of these two movement disorders on the overall sensorimotor functional connection of the subthalamic nucleus and sensorimotor cortex.
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Affiliation(s)
- Stefania Evangelisti
- FMRIB Centre, Wellcome Centre for Integrative Neuroimaging, John Radcliffe Hospital, University of Oxford, OX3 9DU Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
- Department of Biomedical and Neuromotor Sciences, University of Bologna, 40127 Bologna, Italy
| | - Sirius Boessenkool
- FMRIB Centre, Wellcome Centre for Integrative Neuroimaging, John Radcliffe Hospital, University of Oxford, OX3 9DU Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
| | - Chris Patrick Pflanz
- FMRIB Centre, Wellcome Centre for Integrative Neuroimaging, John Radcliffe Hospital, University of Oxford, OX3 9DU Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
- Stroke Research Group, Department of Clinical Neuroscience, University of Cambridge, CB2 0QQ Cambridge, UK
| | - Romina Basting
- FMRIB Centre, Wellcome Centre for Integrative Neuroimaging, John Radcliffe Hospital, University of Oxford, OX3 9DU Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
- Department of Experimental Psychology, University of Oxford, OX2 6GG Oxford, UK
| | - Jill F Betts
- FMRIB Centre, Wellcome Centre for Integrative Neuroimaging, John Radcliffe Hospital, University of Oxford, OX3 9DU Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
| | - Mark Jenkinson
- FMRIB Centre, Wellcome Centre for Integrative Neuroimaging, John Radcliffe Hospital, University of Oxford, OX3 9DU Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
- School of Computer Science, Faculty of Engineering, University of Adelaide, 5005 Adelaide, Australia
| | - Stuart Clare
- FMRIB Centre, Wellcome Centre for Integrative Neuroimaging, John Radcliffe Hospital, University of Oxford, OX3 9DU Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
| | - Kinan Muhammed
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
| | - Campbell LeHeron
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
- New Zealand Brain Research Institute, 8011 Christchurch, New Zealand
| | - Richard Armstrong
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
| | - Johannes C Klein
- FMRIB Centre, Wellcome Centre for Integrative Neuroimaging, John Radcliffe Hospital, University of Oxford, OX3 9DU Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
| | - Masud Husain
- FMRIB Centre, Wellcome Centre for Integrative Neuroimaging, John Radcliffe Hospital, University of Oxford, OX3 9DU Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
- Department of Experimental Psychology, University of Oxford, OX2 6GG Oxford, UK
| | - Andrea H Nemeth
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
| | - Michele T Hu
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
| | - Gwenaëlle Douaud
- FMRIB Centre, Wellcome Centre for Integrative Neuroimaging, John Radcliffe Hospital, University of Oxford, OX3 9DU Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
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3
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Street D, Jabbari E, Costantini A, Jones PS, Holland N, Rittman T, Jensen MT, Chelban V, Goh YY, Guo T, Heslegrave AJ, Roncaroli F, Klein JC, Ansorge O, Allinson KSJ, Jaunmuktane Z, Revesz T, Warner TT, Lees AJ, Zetterberg H, Russell LL, Bocchetta M, Rohrer JD, Burn DJ, Pavese N, Gerhard A, Kobylecki C, Leigh PN, Church A, Hu MTM, Houlden H, Morris H, Rowe JB. Progression of atypical parkinsonian syndromes: PROSPECT-M-UK study implications for clinical trials. Brain 2023; 146:3232-3242. [PMID: 36975168 PMCID: PMC10393398 DOI: 10.1093/brain/awad105] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Revised: 02/11/2023] [Accepted: 02/21/2023] [Indexed: 03/29/2023] Open
Abstract
The advent of clinical trials of disease-modifying agents for neurodegenerative disease highlights the need for evidence-based end point selection. Here we report the longitudinal PROSPECT-M-UK study of progressive supranuclear palsy (PSP), corticobasal syndrome (CBS), multiple system atrophy (MSA) and related disorders, to compare candidate clinical trial end points. In this multicentre UK study, participants were assessed with serial questionnaires, motor examination, neuropsychiatric and MRI assessments at baseline, 6 and 12 months. Participants were classified by diagnosis at baseline and study end, into Richardson syndrome, PSP-subcortical (PSP-parkinsonism and progressive gait freezing subtypes), PSP-cortical (PSP-frontal, PSP-speech and language and PSP-CBS subtypes), MSA-parkinsonism, MSA-cerebellar, CBS with and without evidence of Alzheimer's disease pathology and indeterminate syndromes. We calculated annual rate of change, with linear mixed modelling and sample sizes for clinical trials of disease-modifying agents, according to group and assessment type. Two hundred forty-three people were recruited [117 PSP, 68 CBS, 42 MSA and 16 indeterminate; 138 (56.8%) male; age at recruitment 68.7 ± 8.61 years]. One hundred and fifty-nine completed the 6-month assessment (82 PSP, 27 CBS, 40 MSA and 10 indeterminate) and 153 completed the 12-month assessment (80 PSP, 29 CBS, 35 MSA and nine indeterminate). Questionnaire, motor examination, neuropsychiatric and neuroimaging measures declined in all groups, with differences in longitudinal change between groups. Neuroimaging metrics would enable lower sample sizes to achieve equivalent power for clinical trials than cognitive and functional measures, often achieving N < 100 required for 1-year two-arm trials (with 80% power to detect 50% slowing). However, optimal outcome measures were disease-specific. In conclusion, phenotypic variance within PSP, CBS and MSA is a major challenge to clinical trial design. Our findings provide an evidence base for selection of clinical trial end points, from potential functional, cognitive, clinical or neuroimaging measures of disease progression.
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Affiliation(s)
- Duncan Street
- University of Cambridge Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, Cambridge, CB2 OQQ, UK
| | - Edwin Jabbari
- Department of Clinical and Movement Neurosciences, University College London, Queen Square Institute of Neurology, London, WC1N 3BG, UK
- Movement Disorders Centre, University College London, Queen Square Institute of Neurology, London, WC1N 3BG, UK
| | - Alyssa Costantini
- Department of Clinical and Movement Neurosciences, University College London, Queen Square Institute of Neurology, London, WC1N 3BG, UK
- Movement Disorders Centre, University College London, Queen Square Institute of Neurology, London, WC1N 3BG, UK
| | - P Simon Jones
- University of Cambridge Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, Cambridge, CB2 OQQ, UK
| | - Negin Holland
- University of Cambridge Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, Cambridge, CB2 OQQ, UK
| | - Timothy Rittman
- University of Cambridge Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, Cambridge, CB2 OQQ, UK
| | - Marte T Jensen
- Department of Clinical and Movement Neurosciences, University College London, Queen Square Institute of Neurology, London, WC1N 3BG, UK
- Movement Disorders Centre, University College London, Queen Square Institute of Neurology, London, WC1N 3BG, UK
| | - Viorica Chelban
- Department of Neuromuscular Diseases, University College London, Queen Square Institute of Neurology, London, WC1N 3BG, UK
- Neurobiology and Medical Genetics Laboratory, ‘Nicolae Testemitanu’ State University of Medicine and Pharmacy, Chisinau 2004, Republic of Moldova
| | - Yen Y Goh
- Department of Neuromuscular Diseases, University College London, Queen Square Institute of Neurology, London, WC1N 3BG, UK
| | - Tong Guo
- Department of Clinical and Movement Neurosciences, University College London, Queen Square Institute of Neurology, London, WC1N 3BG, UK
| | - Amanda J Heslegrave
- Department of Neurodegenerative Disease, University College London, Queen Square Institute of Neurology, London, WC1N 3BG, UK
- UK Dementia Research Institute, University College London, London, W1T 7NF, UK
| | - Federico Roncaroli
- Geoffrey Jefferson Brain Research Centre, Division of Neuroscience, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, M6 8HD, UK
| | - Johannes C Klein
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Olaf Ansorge
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Kieren S J Allinson
- University of Cambridge Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, Cambridge, CB2 OQQ, UK
| | - Zane Jaunmuktane
- Department of Clinical and Movement Neurosciences, University College London, Queen Square Institute of Neurology, London, WC1N 3BG, UK
- Queen Square Brain Bank for Neurological Disorders, University College London, Queen Square Institute of Neurology, London, WC1N 3BG, UK
- Reta Lila Weston Institute, University College London, Queen Square Institute of Neurology, London, WC1N 3BG, UK
| | - Tamas Revesz
- Queen Square Brain Bank for Neurological Disorders, University College London, Queen Square Institute of Neurology, London, WC1N 3BG, UK
- Reta Lila Weston Institute, University College London, Queen Square Institute of Neurology, London, WC1N 3BG, UK
| | - Thomas T Warner
- Queen Square Brain Bank for Neurological Disorders, University College London, Queen Square Institute of Neurology, London, WC1N 3BG, UK
- Reta Lila Weston Institute, University College London, Queen Square Institute of Neurology, London, WC1N 3BG, UK
| | - Andrew J Lees
- Queen Square Brain Bank for Neurological Disorders, University College London, Queen Square Institute of Neurology, London, WC1N 3BG, UK
- Reta Lila Weston Institute, University College London, Queen Square Institute of Neurology, London, WC1N 3BG, UK
| | - Henrik Zetterberg
- Department of Neurodegenerative Disease, University College London, Queen Square Institute of Neurology, London, WC1N 3BG, UK
- UK Dementia Research Institute, University College London, London, W1T 7NF, UK
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, 431 30 Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Salhgrenska Academy at the University of Gothenburg, 413 45 Goteborg, Sweden
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong Science Park, Shatin, N.T., Hong Kong, China
| | - Lucy L Russell
- Department of Neurodegenerative Disease, University College London, Queen Square Institute of Neurology, London, WC1N 3BG, UK
| | - Martina Bocchetta
- Centre for Cognitive and Clinical Neuroscience, Division of Psychology, Department of Life Sciences, College of Health, Medicine and Life Sciences, Brunel University London, London, UB8 3PH, UK
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
| | - Jonathan D Rohrer
- Department of Neurodegenerative Disease, University College London, Queen Square Institute of Neurology, London, WC1N 3BG, UK
| | - David J Burn
- Faculty of Medical Sciences, Newcastle University, Newcastle, NE2 4HH, UK
| | - Nicola Pavese
- Clinical Ageing Research Unit, Newcastle University, Newcastle, NE4 5PL, UK
| | - Alexander Gerhard
- Division of Neuroscience, Wolfson Molecular Imaging Centre, University of Manchester, Manchester, N20 3LJ, UK
- Departments of Geriatric Medicine and Nuclear Medicine, Center for Translational Neuro- and Behavioral Sciences, University Medicine Essen, 45356 Essen, Germany
| | - Christopher Kobylecki
- Division of Neuroscience, Wolfson Molecular Imaging Centre, University of Manchester, Manchester, N20 3LJ, UK
- Department of Neurology, Manchester Academic Health Science Centre, Northern Care Alliance NHS Foundation Trust, Salford, M13 9NQ, UK
| | - P Nigel Leigh
- Department of Neuroscience, Brighton and Sussex Medical School, Brighton, BN1 9PX, UK
| | - Alistair Church
- Department of Neurology, Royal Gwent Hospital, Newport, NP20 2UB, UK
| | - Michele T M Hu
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
- Department of Physiology, Anatomy and Genetics, Oxford Parkinson’s Disease Centre, University of Oxford, Oxford, OX1 3QU, UK
| | - Henry Houlden
- Department of Clinical and Movement Neurosciences, University College London, Queen Square Institute of Neurology, London, WC1N 3BG, UK
- Movement Disorders Centre, University College London, Queen Square Institute of Neurology, London, WC1N 3BG, UK
- Department of Neuromuscular Diseases, University College London, Queen Square Institute of Neurology, London, WC1N 3BG, UK
| | - Huw Morris
- Department of Clinical and Movement Neurosciences, University College London, Queen Square Institute of Neurology, London, WC1N 3BG, UK
- Movement Disorders Centre, University College London, Queen Square Institute of Neurology, London, WC1N 3BG, UK
| | - James B Rowe
- University of Cambridge Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, Cambridge, CB2 OQQ, UK
- Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, CB2 7EF, UK
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4
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Whiteside DJ, Street D, Murley AG, Jones PS, Malpetti M, Ghosh BCP, Coyle-Gilchrist I, Gerhard A, Hu MT, Klein JC, Leigh PN, Church A, Burn DJ, Morris HR, Rowe JB, Rittman T. Network connectivity and structural correlates of survival in progressive supranuclear palsy and corticobasal syndrome. Hum Brain Mapp 2023. [PMID: 37269181 DOI: 10.1002/hbm.26342] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Revised: 04/27/2023] [Accepted: 05/01/2023] [Indexed: 06/04/2023] Open
Abstract
There is a pressing need to understand the factors that predict prognosis in progressive supranuclear palsy (PSP) and corticobasal syndrome (CBS), with high heterogeneity over the poor average survival. We test the hypothesis that the magnitude and distribution of connectivity changes in PSP and CBS predict the rate of progression and survival time, using datasets from the Cambridge Centre for Parkinson-plus and the UK National PSP Research Network (PROSPECT-MR). Resting-state functional MRI images were available from 146 participants with PSP, 82 participants with CBS, and 90 healthy controls. Large-scale networks were identified through independent component analyses, with correlations taken between component time series. Independent component analysis was also used to select between-network connectivity components to compare with baseline clinical severity, longitudinal rate of change in severity, and survival. Transdiagnostic survival predictors were identified using partial least squares regression for Cox models, with connectivity compared to patients' demographics, structural imaging, and clinical scores using five-fold cross-validation. In PSP and CBS, between-network connectivity components were identified that differed from controls, were associated with disease severity, and were related to survival and rate of change in clinical severity. A transdiagnostic component predicted survival beyond demographic and motion metrics but with lower accuracy than an optimal model that included the clinical and structural imaging measures. Cortical atrophy enhanced the connectivity changes that were most predictive of survival. Between-network connectivity is associated with variability in prognosis in PSP and CBS but does not improve predictive accuracy beyond clinical and structural imaging metrics.
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Affiliation(s)
- David J Whiteside
- Department of Clinical Neurosciences and Cambridge Centre for Parkinson-plus, University of Cambridge, Cambridge, UK
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Duncan Street
- Department of Clinical Neurosciences and Cambridge Centre for Parkinson-plus, University of Cambridge, Cambridge, UK
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Alexander G Murley
- Department of Clinical Neurosciences and Cambridge Centre for Parkinson-plus, University of Cambridge, Cambridge, UK
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - P Simon Jones
- Department of Clinical Neurosciences and Cambridge Centre for Parkinson-plus, University of Cambridge, Cambridge, UK
| | - Maura Malpetti
- Department of Clinical Neurosciences and Cambridge Centre for Parkinson-plus, University of Cambridge, Cambridge, UK
| | - Boyd C P Ghosh
- Wessex Neurological Centre, University Hospital Southampton, Southampton, UK
| | | | - Alexander Gerhard
- Division of Neuroscience and Experimental Psychology, Wolfson Molecular Imaging Centre, University of Manchester, Manchester, UK
- Departments of Geriatric Medicine and Nuclear Medicine, University of Duisburg-Essen, Duisburg, Germany
| | - Michele T Hu
- Oxford Parkinson's Disease Centre and Division of Neurology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Johannes C Klein
- Oxford Parkinson's Disease Centre and Division of Neurology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - P Nigel Leigh
- Department of Neuroscience, Brighton and Sussex Medical School, Brighton, UK
| | | | - David J Burn
- Faculty of Medical Sciences, Newcastle University, Newcastle, UK
| | - Huw R Morris
- Department of Clinical and Movement Neurosciences, University College London, Queen Square Institute of Neurology, London, UK
| | - James B Rowe
- Department of Clinical Neurosciences and Cambridge Centre for Parkinson-plus, University of Cambridge, Cambridge, UK
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Timothy Rittman
- Department of Clinical Neurosciences and Cambridge Centre for Parkinson-plus, University of Cambridge, Cambridge, UK
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
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5
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Barber TR, Muhammed K, Drew D, Bradley KM, McGowan DR, Klein JC, Manohar SG, Hu MTM, Husain M. Reward insensitivity is associated with dopaminergic deficit in rapid eye movement sleep behaviour disorder. Brain 2023; 146:2502-2511. [PMID: 36395092 PMCID: PMC10232265 DOI: 10.1093/brain/awac430] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 10/18/2022] [Accepted: 11/06/2022] [Indexed: 11/18/2022] Open
Abstract
Idiopathic rapid eye movement sleep behaviour disorder (iRBD) has now been established as an important marker of the prodromal stage of Parkinson's disease and related synucleinopathies. However, although dopamine transporter single photon emission computed tomography (SPECT) has been used to demonstrate the presence of nigro-striatal deficit in iRBD, quantifiable correlates of this are currently lacking. Sensitivity to rewarding stimuli is reduced in some people with Parkinson's disease, potentially contributing to aspects of the neuropsychiatric phenotype in these individuals. Furthermore, a role for dopaminergic degeneration is suggested by the fact that reward insensitivity can be improved by dopaminergic medications. Patients with iRBD present a unique opportunity to study the relationship between reward sensitivity and early dopaminergic deficit in the unmedicated state. Here, we investigate whether a non-invasive, objective measure of reward sensitivity might be a marker of dopaminergic status in prodromal Parkinson's disease by comparing with SPECT/CT measurement of dopaminergic loss in the basal ganglia. Striatal dopaminergic deficits in iRBD are associated with progression to Parkinsonian disorders. Therefore, identification of a clinically measurable correlate of this degenerative process might provide a basis for the development of novel risk stratification tools. Using a recently developed incentivized eye-tracking task, we quantified reward sensitivity in a cohort of 41 patients with iRBD and compared this with data from 40 patients with Parkinson's disease and 41 healthy controls. Patients with iRBD also underwent neuroimaging with dopamine transporter SPECT/CT. Overall, reward sensitivity, indexed by pupillary response to monetary incentives, was reduced in iRBD cases compared with controls and was not significantly different to that in patients with Parkinson's disease. However, in iRBD patients with normal dopamine transporter SPECT/CT imaging, reward sensitivity was not significantly different from healthy controls. Across all iRBD cases, a positive association was observed between reward sensitivity and dopaminergic SPECT/CT signal in the putamen. These findings demonstrate a direct relationship between dopaminergic deficit and reward sensitivity in patients with iRBD and suggest that measurement of pupillary responses could be of value in models of risk stratification and disease progression in these individuals.
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Affiliation(s)
- Thomas R Barber
- Nuffield Department of Clinical Neurosciences, University of Oxford, Level 6, West Wing, John Radcliffe Hospital, Oxford, OX3 9DU, UK
| | - Kinan Muhammed
- Nuffield Department of Clinical Neurosciences, University of Oxford, Level 6, West Wing, John Radcliffe Hospital, Oxford, OX3 9DU, UK
- Department of Experimental Psychology, University of Oxford, Anna Watts Building, Radcliffe Observatory Quarter, Oxford, OX2 6GG, UK
| | - Daniel Drew
- Nuffield Department of Clinical Neurosciences, University of Oxford, Level 6, West Wing, John Radcliffe Hospital, Oxford, OX3 9DU, UK
- Department of Experimental Psychology, University of Oxford, Anna Watts Building, Radcliffe Observatory Quarter, Oxford, OX2 6GG, UK
| | - Kevin M Bradley
- Wales Research and Diagnostic PET Imaging Centre, Cardiff University, School of Medicine, University Hospital Wales, Cardiff CF14 4XN, UK
| | - Daniel R McGowan
- Department of Medical Physics and Clinical Engineering, Oxford University Hospitals NHS Trust, Churchill Hospital, Oxford, OX3 7LE, UK
- Department of Oncology, University of Oxford, Oxford OX3 7DQ, UK
| | - Johannes C Klein
- Nuffield Department of Clinical Neurosciences, University of Oxford, Level 6, West Wing, John Radcliffe Hospital, Oxford, OX3 9DU, UK
| | - Sanjay G Manohar
- Nuffield Department of Clinical Neurosciences, University of Oxford, Level 6, West Wing, John Radcliffe Hospital, Oxford, OX3 9DU, UK
- Department of Experimental Psychology, University of Oxford, Anna Watts Building, Radcliffe Observatory Quarter, Oxford, OX2 6GG, UK
| | - Michele T M Hu
- Nuffield Department of Clinical Neurosciences, University of Oxford, Level 6, West Wing, John Radcliffe Hospital, Oxford, OX3 9DU, UK
| | - Masud Husain
- Nuffield Department of Clinical Neurosciences, University of Oxford, Level 6, West Wing, John Radcliffe Hospital, Oxford, OX3 9DU, UK
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6
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Zhao Y, van Heese E, Laansma MA, Al‐Bachari S, Anderson T, Assogna F, Berendse HW, Bright J, Cendes F, Dalrymple‐Alford J, Debove I, Dirkx M, Druzgal TJ, Emsley H, Fouche JP, Garraux G, Guimarães R, Helmich R, Jahanshad N, Kim HB, Klein JC, Lochner C, Mackay C, McMillan CT, Melzer TR, Newman BT, Owens‐Walton C, Parkes L, Piras F, Pitcher T, Poston KL, Rango M, Ribeiro LF, Rocha C, Roos A, Rummel C, Santos L, Schmidt R, Spalletta G, Squarcina L, Schwingenschuh P, Vecchio D, Vriend C, Wang J, Weintraub D, Wiest R, Yasuda C, Thompson PM, van der Werf YD, Gutman BA. TV‐L1 Ordinal Logistic Regression Reveals New Morphometric Patterns Related to Parkinsonian Symptom Severity: An ENIGMA‐PD study. Alzheimers Dement 2022. [DOI: 10.1002/alz.067037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Affiliation(s)
- Yuji Zhao
- Illinois Institute of Technology Chicago IL USA
| | | | | | | | | | | | - Henk W. Berendse
- Department of Neurology, Neuroscience Amsterdam, VU University Medical Center Amsterdam Netherlands
| | - Joanna Bright
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California Marina del Rey CA USA
| | | | | | | | | | | | | | - JP Fouche
- Stellenbosch University Stellenbosch South Africa
| | | | | | - Rick Helmich
- Radboud University Nijmegen Nijmegen Netherlands
| | - 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
| | | | | | | | | | - Corey T McMillan
- Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
- Penn Alzheimer’s Disease Research Center, Perelman School of Medicine Philadelphia PA USA
| | - Tracy R Melzer
- University of Otago Christchurch New Zealand
- Brain Research, Christchurch New Zealand New Zealand
| | | | - 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
| | - Laura Parkes
- University of Manchester Manchester United Kingdom
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Chris Vriend
- Vrije Universiteit Amsterdam Amsterdam Netherlands
| | | | | | | | | | | | - Ysbrand D. van der Werf
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC Amsterdam Netherlands
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7
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Lawton M, Tan MM, Ben-Shlomo Y, Baig F, Barber T, Klein JC, Evetts SG, Millin S, Malek N, Grosset K, Barker RA, Williams N, Burn DJ, Foltynie T, Morris HR, Wood N, Grosset DG, Hu MTM. Genetics of validated Parkinson's disease subtypes in the Oxford Discovery and Tracking Parkinson's cohorts. J Neurol Neurosurg Psychiatry 2022; 93:jnnp-2021-327376. [PMID: 35732412 PMCID: PMC9380504 DOI: 10.1136/jnnp-2021-327376] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Accepted: 05/25/2022] [Indexed: 11/04/2022]
Abstract
OBJECTIVES To explore the genetics of four Parkinson's disease (PD) subtypes that have been previously described in two large cohorts of patients with recently diagnosed PD. These subtypes came from a data-driven cluster analysis of phenotypic variables. METHODS We looked at the frequency of genetic mutations in glucocerebrosidase (GBA) and leucine-rich repeat kinase 2 against our subtypes. Then we calculated Genetic Risk Scores (GRS) for PD, multiple system atrophy, progressive supranuclear palsy, Lewy body dementia, and Alzheimer's disease. These GRSs were regressed against the probability of belonging to a subtype in the two independent cohorts and we calculated q-values as an adjustment for multiple testing across four subtypes. We also carried out a Genome-Wide Association Study (GWAS) of belonging to a subtype. RESULTS A severe disease subtype had the highest rates of patients carrying GBA mutations while the mild disease subtype had the lowest rates (p=0.009). Using the GRS, we found a severe disease subtype had a reduced genetic risk of PD (p=0.004 and q=0.015). In our GWAS no individual variants met genome wide significance (<5×10e-8) although four variants require further follow-up, meeting a threshold of <1×10e-6. CONCLUSIONS We have found that four previously defined PD subtypes have different genetic determinants which will help to inform future studies looking at underlying disease mechanisms and pathogenesis in these different subtypes of disease.
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Affiliation(s)
- Michael Lawton
- Population Health Sciences, University of Bristol Medical School, Bristol, UK
| | - Manuela Mx Tan
- Department of Clinical and Movement Neurosciences, Queen Square Institute of Neurology, University College London, London, UK
- UCL Movement Disorders Centre, University College London, London, UK
| | - Yoav Ben-Shlomo
- Population Health Sciences, University of Bristol Medical School, Bristol, UK
| | - Fahd Baig
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Molecular and Clinical Sciences Institute, St. George's University of London, London, UK
| | - Thomas Barber
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, UK
| | - Johannes C Klein
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, UK
| | - Samuel G Evetts
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, UK
| | - Stephanie Millin
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, UK
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK
| | - Naveed Malek
- Department of Neurology, Queen's Hospital, Romford, Essex, UK
| | - Katherine Grosset
- Department of Neurology, Institute of Neurological Sciences, Queen Elizabeth University Hospital and University of Glasgow, Glasgow, UK
| | - Roger A Barker
- Cambridge Centre for Brain Repair, University of Cambridge, Cambridge, UK
| | - Nigel Williams
- Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - David J Burn
- Faculty of Medical Sciences, Newcastle University, Newcastle, UK
| | - Thomas Foltynie
- Department of Clinical and Movement Neurosciences, Queen Square Institute of Neurology, University College London, London, UK
| | - Huw R Morris
- Department of Clinical and Movement Neurosciences, Queen Square Institute of Neurology, University College London, London, UK
- UCL Movement Disorders Centre, University College London, London, UK
| | - Nicholas Wood
- Department of Clinical and Movement Neurosciences, Queen Square Institute of Neurology, University College London, London, UK
| | - Donald G Grosset
- Department of Neurology, Institute of Neurological Sciences, Queen Elizabeth University Hospital and University of Glasgow, Glasgow, UK
| | - Michele Tao-Ming Hu
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, UK
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8
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Wang C, Martins-Bach AB, Alfaro-Almagro F, Douaud G, Klein JC, Llera A, Fiscone C, Bowtell R, Elliott LT, Smith SM, Tendler BC, Miller KL. Phenotypic and genetic associations of quantitative magnetic susceptibility in UK Biobank brain imaging. Nat Neurosci 2022; 25:818-831. [PMID: 35606419 PMCID: PMC9174052 DOI: 10.1038/s41593-022-01074-w] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [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: 08/11/2021] [Accepted: 04/11/2022] [Indexed: 12/17/2022]
Abstract
A key aim in epidemiological neuroscience is identification of markers to assess brain health and monitor therapeutic interventions. Quantitative susceptibility mapping (QSM) is an emerging magnetic resonance imaging technique that measures tissue magnetic susceptibility and has been shown to detect pathological changes in tissue iron, myelin and calcification. We present an open resource of QSM-based imaging measures of multiple brain structures in 35,273 individuals from the UK Biobank prospective epidemiological study. We identify statistically significant associations of 251 phenotypes with magnetic susceptibility that include body iron, disease, diet and alcohol consumption. Genome-wide associations relate magnetic susceptibility to 76 replicating clusters of genetic variants with biological functions involving iron, calcium, myelin and extracellular matrix. These patterns of associations include relationships that are unique to QSM, in particular being complementary to T2* signal decay time measures. These new imaging phenotypes are being integrated into the core UK Biobank measures provided to researchers worldwide, creating the potential to discover new, non-invasive markers of brain health.
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Affiliation(s)
- Chaoyue Wang
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
| | - Aurea B Martins-Bach
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Fidel Alfaro-Almagro
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Gwenaëlle Douaud
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Johannes C Klein
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, UK
| | - Alberto Llera
- Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Nijmegen, the Netherlands
| | - Cristiana Fiscone
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
| | - Richard Bowtell
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Lloyd T Elliott
- Department of Statistics and Actuarial Science, Simon Fraser University, Vancouver, British Columbia, Canada
| | - Stephen M Smith
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Benjamin C Tendler
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Karla L Miller
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
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9
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Liu Y, Lawton MA, Lo C, Bowring F, Klein JC, Querejeta-Coma A, Scotton S, Welch J, Razzaque J, Barber T, Ben-Shlomo Y, Hu MT. Longitudinal Changes in Parkinson's Disease Symptoms with and Without Rapid Eye Movement Sleep Behavior Disorder: The Oxford Discovery Cohort Study. Mov Disord 2021; 36:2821-2832. [PMID: 34448251 DOI: 10.1002/mds.28763] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [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: 04/16/2021] [Revised: 07/27/2021] [Accepted: 08/02/2021] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Parkinson's disease (PD) comorbid with rapid eye movement sleep behavior disorder (RBD) may show more severe motor and nonmotor symptoms, suggesting a distinct PD subtype. OBJECTIVE The aim of this study was to investigate the impact of RBD on the longitudinal change of motor and nonmotor symptoms in patients with PD. METHODS Patients with early PD (diagnosed within 3.5 years) recruited from 2010 to 2019 were followed every 18 months in the Oxford Parkinson's Disease Centre Discovery cohort. At each visit, we used standard questionnaires and measurements to assess demographic features and motor and nonmotor symptoms (including RBD, daytime sleepiness, mood, autonomic symptoms, cognition, and olfaction). Data were analyzed with linear mixed effects and Cox regression models. Possible RBD (pRBD) was longitudinally determined according to RBD Screening Questionnaire scores. RESULTS A total of 923 patients were recruited (mean age: 67.1 ± 9.59 years; 35.9% female), and 788 had follow-up assessment(s) (mean: 4.8 ± 1.98 years, range: 1.3-8.3). Among them, 33.3% were identified as pRBD (PD + pRBD). Patients with PD + pRBD had more severe baseline symptoms and showed faster progression on Movement Disorder Society-Unified Parkinson's Disease Rating Scale parts I and III, Purdue Pegboard test, and Beck Depression Inventory scores. Moreover, PD + pRBD was associated with an increased level of risk for mild cognitive impairment (hazard ratio [HR] = 1.36, 95% confidence interval [CI]: 1.01-1.83), freezing of gait (HR = 1.42, 95% CI: 1.10-1.86), and frequent falling (HR = 1.62, 95% CI: 1.02-2.60). CONCLUSIONS Patients with PD + pRBD progress faster on motor, mood, and cognitive symptoms, confirming a more aggressive PD subtype that can be identified at baseline and has major clinical implications. © 2021 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Yaping Liu
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, United Kingdom.,Li Chiu Kong Family Sleep Assessment Unit, Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China
| | - Michael A Lawton
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, United Kingdom.,Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Christine Lo
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, United Kingdom.,Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.,Department of Neurology, Royal Hallamshire Hospital, Sheffield, United Kingdom
| | - Francesca Bowring
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, United Kingdom
| | - Johannes C Klein
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, United Kingdom.,Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.,Department of Neurology, John Radcliffe Hospital, Oxford, United Kingdom
| | - Agustin Querejeta-Coma
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, United Kingdom.,Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.,Department of Neurology, John Radcliffe Hospital, Oxford, United Kingdom.,Department of Neurology, Infanta Elena University Hospital, Valdemoro, Spain.,Department of Neurology, Rey Juan Carlos University Hospital, Móstoles, Spain
| | - Sangeeta Scotton
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, United Kingdom
| | - Jessica Welch
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, United Kingdom
| | - Jamil Razzaque
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, United Kingdom
| | - Thomas Barber
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, United Kingdom.,Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.,Department of Neurology, John Radcliffe Hospital, Oxford, United Kingdom
| | - Yoav Ben-Shlomo
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, United Kingdom.,Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Michele T Hu
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, United Kingdom.,Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.,Department of Neurology, John Radcliffe Hospital, Oxford, United Kingdom
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10
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Whiteside DJ, Jones PS, Ghosh BCP, Coyle-Gilchrist I, Gerhard A, Hu MT, Klein JC, Leigh PN, Church A, Burn DJ, Morris HR, Rowe JB, Rittman T. Altered network stability in progressive supranuclear palsy. Neurobiol Aging 2021; 107:109-117. [PMID: 34419788 PMCID: PMC8599965 DOI: 10.1016/j.neurobiolaging.2021.07.007] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2020] [Revised: 06/15/2021] [Accepted: 07/08/2021] [Indexed: 01/18/2023]
Abstract
We investigated network dynamics in the tauopathy progressive supranuclear palsy Abnormal temporal properties of large-scale networks are related to phenotype Progressive supranuclear palsy paradoxically increases frontoparietal state time Reductions in neural signal complexity relate to altered network dynamics Dynamic network and topological changes occur distally to primary sites of atrophy
The clinical syndromes of Progressive Supranuclear Palsy (PSP) may be mediated by abnormal temporal dynamics of brain networks, due to the impact of atrophy, synapse loss and neurotransmitter deficits. We tested the hypothesis that alterations in signal complexity in neural networks influence short-latency state transitions. Ninety-four participants with PSP and 64 healthy controls were recruited from two independent cohorts. All participants underwent clinical and neuropsychological testing and resting-state functional MRI. Network dynamics were assessed using hidden Markov models and neural signal complexity measured in terms of multiscale entropy. In both cohorts, PSP increased the proportion of time in networks associated with higher cognitive functions. This effect correlated with clinical severity as measured by the PSP-rating-scale, and with reduced neural signal complexity. Regional atrophy influenced abnormal brain-state occupancy, but abnormal network topology and dynamics were not restricted to areas of atrophy. Our findings show that the pathology of PSP causes clinically relevant changes in neural temporal dynamics, leading to a greater proportion of time in inefficient brain-states.
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Affiliation(s)
- David J Whiteside
- Cambridge University Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, UK.
| | - P Simon Jones
- Cambridge University Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, UK
| | - Boyd C P Ghosh
- Wessex Neurological Centre, University Hospital Southampton, Southampton, UK
| | | | - Alexander Gerhard
- Division of Neuroscience and Experimental Psychology, University of Manchester, Manchester, UK
| | - Michele T Hu
- Oxford Parkinson's Disease Centre and Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Johannes C Klein
- Oxford Parkinson's Disease Centre and Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - P Nigel Leigh
- Department of Neuroscience, Brighton and Sussex Medical School, Brighton, UK
| | | | - David J Burn
- Faculty of Medical Sciences, Newcastle University, Newcastle, UK
| | - Huw R Morris
- Department of Clinical and Movement Neurosciences, University College London. Queen Square Institute of Neurology, London, UK
| | - James B Rowe
- Cambridge University Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, UK
| | - Timothy Rittman
- Cambridge University Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, UK
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11
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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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12
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Lo C, Arora S, Ben-Shlomo Y, Barber TR, Lawton M, Klein JC, Kanavou S, Janzen A, Sittig E, Oertel WH, Grosset DG, Hu MT. Olfactory Testing in Parkinson Disease and REM Behavior Disorder: A Machine Learning Approach. Neurology 2021; 96:e2016-e2027. [PMID: 33627500 DOI: 10.1212/wnl.0000000000011743] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Accepted: 01/15/2021] [Indexed: 12/31/2022] Open
Abstract
OBJECTIVE We sought to identify an abbreviated test of impaired olfaction amenable for use in busy clinical environments in prodromal (isolated REM sleep behavior disorder [iRBD]) and manifest Parkinson disease (PD). METHODS Eight hundred ninety individuals with PD and 313 controls in the Discovery cohort study underwent Sniffin' Stick odor identification assessment. Random forests were initially trained to distinguish individuals with poor (functional anosmia/hyposmia) and good (normosmia/super-smeller) smell ability using all 16 Sniffin' Sticks. Models were retrained using the top 3 sticks ranked by order of predictor importance. One randomly selected 3-stick model was tested in a second independent PD dataset (n = 452) and in 2 iRBD datasets (Discovery n = 241, Marburg n = 37) before being compared to previously described abbreviated Sniffin' Stick combinations. RESULTS In differentiating poor from good smell ability, the overall area under the curve (AUC) value associated with the top 3 sticks (anise/licorice/banana) was 0.95 in the Development dataset (sensitivity 90%, specificity 92%, positive predictive value 92%, negative predictive value 90%). Internal and external validation confirmed AUCs ≥0.90. The combination of the 3-stick model determined poor smell, and an RBD screening questionnaire score of ≥5 separated those with iRBD from controls with a sensitivity, specificity, positive predictive value, and negative predictive value of 65%, 100%, 100%, and 30%. CONCLUSIONS Our 3-Sniffin'-Stick model holds potential utility as a brief screening test in the stratification of individuals with PD and iRBD according to olfactory dysfunction. CLASSIFICATION OF EVIDENCE This study provides Class III evidence that a 3-Sniffin'-Stick model distinguishes individuals with poor and good smell ability and can be used to screen for individuals with iRBD.
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Affiliation(s)
- Christine Lo
- From the Oxford Parkinson's Disease Centre (C.L., S.A., T.R.B., J.C.K., M.T.H.), Nuffield Department of Clinical Neurosciences (C.L., T.R.B., J.C.K., M.T.H.), and Saïd Business School (S.A.), University of Oxford; Population Health Sciences (Y.B.-S., M.L., S.K.), University of Bristol, UK; Department of Neurology (A.J., E.S., W.H.O.), Philipps University Marburg; Institute for Neurogenomics (W.H.O.), München Helmholtz Center for Health and Environment, Neuherberg München, Germany; and Institute of Neurological Sciences (D.G.G.), Queen Elizabeth University Hospital, Glasgow, UK.
| | - Siddharth Arora
- From the Oxford Parkinson's Disease Centre (C.L., S.A., T.R.B., J.C.K., M.T.H.), Nuffield Department of Clinical Neurosciences (C.L., T.R.B., J.C.K., M.T.H.), and Saïd Business School (S.A.), University of Oxford; Population Health Sciences (Y.B.-S., M.L., S.K.), University of Bristol, UK; Department of Neurology (A.J., E.S., W.H.O.), Philipps University Marburg; Institute for Neurogenomics (W.H.O.), München Helmholtz Center for Health and Environment, Neuherberg München, Germany; and Institute of Neurological Sciences (D.G.G.), Queen Elizabeth University Hospital, Glasgow, UK
| | - Yoav Ben-Shlomo
- From the Oxford Parkinson's Disease Centre (C.L., S.A., T.R.B., J.C.K., M.T.H.), Nuffield Department of Clinical Neurosciences (C.L., T.R.B., J.C.K., M.T.H.), and Saïd Business School (S.A.), University of Oxford; Population Health Sciences (Y.B.-S., M.L., S.K.), University of Bristol, UK; Department of Neurology (A.J., E.S., W.H.O.), Philipps University Marburg; Institute for Neurogenomics (W.H.O.), München Helmholtz Center for Health and Environment, Neuherberg München, Germany; and Institute of Neurological Sciences (D.G.G.), Queen Elizabeth University Hospital, Glasgow, UK
| | - Thomas R Barber
- From the Oxford Parkinson's Disease Centre (C.L., S.A., T.R.B., J.C.K., M.T.H.), Nuffield Department of Clinical Neurosciences (C.L., T.R.B., J.C.K., M.T.H.), and Saïd Business School (S.A.), University of Oxford; Population Health Sciences (Y.B.-S., M.L., S.K.), University of Bristol, UK; Department of Neurology (A.J., E.S., W.H.O.), Philipps University Marburg; Institute for Neurogenomics (W.H.O.), München Helmholtz Center for Health and Environment, Neuherberg München, Germany; and Institute of Neurological Sciences (D.G.G.), Queen Elizabeth University Hospital, Glasgow, UK
| | - Michael Lawton
- From the Oxford Parkinson's Disease Centre (C.L., S.A., T.R.B., J.C.K., M.T.H.), Nuffield Department of Clinical Neurosciences (C.L., T.R.B., J.C.K., M.T.H.), and Saïd Business School (S.A.), University of Oxford; Population Health Sciences (Y.B.-S., M.L., S.K.), University of Bristol, UK; Department of Neurology (A.J., E.S., W.H.O.), Philipps University Marburg; Institute for Neurogenomics (W.H.O.), München Helmholtz Center for Health and Environment, Neuherberg München, Germany; and Institute of Neurological Sciences (D.G.G.), Queen Elizabeth University Hospital, Glasgow, UK
| | - Johannes C Klein
- From the Oxford Parkinson's Disease Centre (C.L., S.A., T.R.B., J.C.K., M.T.H.), Nuffield Department of Clinical Neurosciences (C.L., T.R.B., J.C.K., M.T.H.), and Saïd Business School (S.A.), University of Oxford; Population Health Sciences (Y.B.-S., M.L., S.K.), University of Bristol, UK; Department of Neurology (A.J., E.S., W.H.O.), Philipps University Marburg; Institute for Neurogenomics (W.H.O.), München Helmholtz Center for Health and Environment, Neuherberg München, Germany; and Institute of Neurological Sciences (D.G.G.), Queen Elizabeth University Hospital, Glasgow, UK
| | - Sofia Kanavou
- From the Oxford Parkinson's Disease Centre (C.L., S.A., T.R.B., J.C.K., M.T.H.), Nuffield Department of Clinical Neurosciences (C.L., T.R.B., J.C.K., M.T.H.), and Saïd Business School (S.A.), University of Oxford; Population Health Sciences (Y.B.-S., M.L., S.K.), University of Bristol, UK; Department of Neurology (A.J., E.S., W.H.O.), Philipps University Marburg; Institute for Neurogenomics (W.H.O.), München Helmholtz Center for Health and Environment, Neuherberg München, Germany; and Institute of Neurological Sciences (D.G.G.), Queen Elizabeth University Hospital, Glasgow, UK
| | - Annette Janzen
- From the Oxford Parkinson's Disease Centre (C.L., S.A., T.R.B., J.C.K., M.T.H.), Nuffield Department of Clinical Neurosciences (C.L., T.R.B., J.C.K., M.T.H.), and Saïd Business School (S.A.), University of Oxford; Population Health Sciences (Y.B.-S., M.L., S.K.), University of Bristol, UK; Department of Neurology (A.J., E.S., W.H.O.), Philipps University Marburg; Institute for Neurogenomics (W.H.O.), München Helmholtz Center for Health and Environment, Neuherberg München, Germany; and Institute of Neurological Sciences (D.G.G.), Queen Elizabeth University Hospital, Glasgow, UK
| | - Elisabeth Sittig
- From the Oxford Parkinson's Disease Centre (C.L., S.A., T.R.B., J.C.K., M.T.H.), Nuffield Department of Clinical Neurosciences (C.L., T.R.B., J.C.K., M.T.H.), and Saïd Business School (S.A.), University of Oxford; Population Health Sciences (Y.B.-S., M.L., S.K.), University of Bristol, UK; Department of Neurology (A.J., E.S., W.H.O.), Philipps University Marburg; Institute for Neurogenomics (W.H.O.), München Helmholtz Center for Health and Environment, Neuherberg München, Germany; and Institute of Neurological Sciences (D.G.G.), Queen Elizabeth University Hospital, Glasgow, UK
| | - Wolfgang H Oertel
- From the Oxford Parkinson's Disease Centre (C.L., S.A., T.R.B., J.C.K., M.T.H.), Nuffield Department of Clinical Neurosciences (C.L., T.R.B., J.C.K., M.T.H.), and Saïd Business School (S.A.), University of Oxford; Population Health Sciences (Y.B.-S., M.L., S.K.), University of Bristol, UK; Department of Neurology (A.J., E.S., W.H.O.), Philipps University Marburg; Institute for Neurogenomics (W.H.O.), München Helmholtz Center for Health and Environment, Neuherberg München, Germany; and Institute of Neurological Sciences (D.G.G.), Queen Elizabeth University Hospital, Glasgow, UK
| | - Donald G Grosset
- From the Oxford Parkinson's Disease Centre (C.L., S.A., T.R.B., J.C.K., M.T.H.), Nuffield Department of Clinical Neurosciences (C.L., T.R.B., J.C.K., M.T.H.), and Saïd Business School (S.A.), University of Oxford; Population Health Sciences (Y.B.-S., M.L., S.K.), University of Bristol, UK; Department of Neurology (A.J., E.S., W.H.O.), Philipps University Marburg; Institute for Neurogenomics (W.H.O.), München Helmholtz Center for Health and Environment, Neuherberg München, Germany; and Institute of Neurological Sciences (D.G.G.), Queen Elizabeth University Hospital, Glasgow, UK
| | - Michele T Hu
- From the Oxford Parkinson's Disease Centre (C.L., S.A., T.R.B., J.C.K., M.T.H.), Nuffield Department of Clinical Neurosciences (C.L., T.R.B., J.C.K., M.T.H.), and Saïd Business School (S.A.), University of Oxford; Population Health Sciences (Y.B.-S., M.L., S.K.), University of Bristol, UK; Department of Neurology (A.J., E.S., W.H.O.), Philipps University Marburg; Institute for Neurogenomics (W.H.O.), München Helmholtz Center for Health and Environment, Neuherberg München, Germany; and Institute of Neurological Sciences (D.G.G.), Queen Elizabeth University Hospital, Glasgow, UK
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13
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Reitz SC, Luger S, Lapa S, Eibach M, Filmann N, Seifert V, Weise L, Klein JC, Kang JS, Baudrexel S, Quick-Weller J. Comparing Programming Sessions of Vim-DBS. Front Neurol 2020; 11:987. [PMID: 33013651 PMCID: PMC7494809 DOI: 10.3389/fneur.2020.00987] [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: 04/30/2020] [Accepted: 07/28/2020] [Indexed: 11/13/2022] Open
Abstract
Background: Essential Tremor (ET) is a progressive neurological disorder characterized by postural and kinetic tremor most commonly affecting the hands and arms. Medically intractable ET can be treated by deep brain stimulation (DBS) of the ventral intermediate nucleus of thalamus (VIM). We investigated whether the location of the effective contact (most tremor suppression with at least side effects) in VIM-DBS for ET changes over time, indicating a distinct mechanism of loss of efficacy that goes beyond progression of tremor severity, or a mere reduction of DBS efficacy. Methods: We performed programming sessions in 10 patients who underwent bilateral vim-DBS surgery between 2009 and 2017 at our department. In addition to the intraoperative (T1) and first clinical programming session (T2) a third programming session (T3) was performed to assess the effect- and side effect threshold (minimum voltage at which a tremor suppression or side effects occurred). Additionally, we compared the choice of the effective contact between T1 and T2 which might be affected by a surgical induced “brain shift.” Discussion: Over a time span of about 4 years VIM-DBS in ET showed continuous efficacy in tremor suppression during stim-ON compared to stim-OFF. Compared to immediate postoperative programming sessions in ET-patients with DBS, long-term evaluation showed no relevant change in the choice of contact with respect to side effects and efficacy. In the majority of the cases the active contact at T2 did not correspond to the most effective intraoperative stimulation site T1, which might be explained by a brain-shift due to cerebral spinal fluid loss after neurosurgical procedure.
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Affiliation(s)
- Sarah C Reitz
- Department of Neurology, University Hospital, Frankfurt, Germany
| | - Sebastian Luger
- Department of Neurology, University Hospital, Frankfurt, Germany
| | - Sriramya Lapa
- Department of Neurology, University Hospital, Frankfurt, Germany
| | - Michael Eibach
- Department of Neurosurgery, University Hospital, Frankfurt, Germany
| | - Natalie Filmann
- Division of Neurosurgery, Dalhouse University Halifax, Halifax, NS, Canada.,Institute of Biostatistics and Mathematical Modeling, University Hospital, Goethe University, Frankfurt, Germany
| | - Volker Seifert
- Department of Neurosurgery, University Hospital, Frankfurt, Germany
| | - Lutz Weise
- Division of Neurosurgery, Dalhouse University Halifax, Halifax, NS, Canada
| | - Johannes C Klein
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Jun-Suk Kang
- Department of Neurology, University Hospital, Frankfurt, Germany
| | - Simon Baudrexel
- Department of Neurology, University Hospital, Frankfurt, Germany
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14
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Abstract
BACKGROUND Despite a body of evidence demonstrating reduced incidence of post-lumbar puncture headache associated with pencil-point (vs bevelled-edge) needles, their use remains variable in the UK. METHODS A multimodal longitudinal intervention was performed over a 12-month period at a tertiary neurology referral centre. In addition to simulation training using pencil-point needles and an electronic documentation pro forma, a change in the default needles presented in clinical environments was performed. RESULTS Prior to the intervention, pencil-point needle usage was minimal. Documentation significantly improved throughout the intervention period. Simulation training interventions only resulted in transient, moderate improvements in pencil-point needle usage. However, changing the default produced a marked increase in use that was sustained. No significant changes in operator success rate were found. CONCLUSIONS In the context of wider literature on the power of default options in driving behavioural choices, changing defaults may be an effective, inexpensive and acceptable intervention to improve lumbar puncture practice.
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Affiliation(s)
| | - Evan C Edmond
- University of Oxford, Oxford, UK and Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | | | - Vanessa Tobert
- Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Johannes C Klein
- University of Oxford, Oxford, UK and Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Martin R Turner
- University of Oxford, Oxford, UK and Oxford University Hospitals NHS Foundation Trust, Oxford, UK
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15
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Seiler A, Schöngrundner S, Stock B, Nöth U, Hattingen E, Steinmetz H, Klein JC, Baudrexel S, Wagner M, Deichmann R, Gracien RM. Cortical aging - new insights with multiparametric quantitative MRI. Aging (Albany NY) 2020; 12:16195-16210. [PMID: 32852283 PMCID: PMC7485732 DOI: 10.18632/aging.103629] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [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: 04/16/2020] [Accepted: 06/22/2020] [Indexed: 02/07/2023]
Abstract
Understanding the microstructural changes related to physiological aging of the cerebral cortex is pivotal to differentiate healthy aging from neurodegenerative processes. The aim of this study was to investigate the age-related global changes of cortical microstructure and regional patterns using multiparametric quantitative MRI (qMRI) in healthy subjects with a wide age range. 40 healthy participants (age range: 2nd to 8th decade) underwent high-resolution qMRI including T1, PD as well as T2, T2* and T2′ mapping at 3 Tesla. Cortical reconstruction was performed with the FreeSurfer toolbox, followed by tests for correlations between qMRI parameters and age. Cortical T1 values were negatively correlated with age (p=0.007) and there was a widespread age-related decrease of cortical T1 involving the frontal and the parietotemporal cortex, while T2 was correlated positively with age, both in frontoparietal areas and globally (p=0.004). Cortical T2′ values showed the most widespread associations across the cortex and strongest correlation with age (r= -0.724, p=0.0001). PD and T2* did not correlate with age. Multiparametric qMRI allows to characterize cortical aging, unveiling parameter-specific patterns. Quantitative T2′ mapping seems to be a promising imaging biomarker of cortical age-related changes, suggesting that global cortical iron deposition is a prominent process in healthy aging.
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Affiliation(s)
- Alexander Seiler
- Department of Neurology, Goethe University, Frankfurt am Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt am Main, Germany
| | - Sophie Schöngrundner
- Department of Neurology, Goethe University, Frankfurt am Main, Germany.,Department of Neuroradiology, Goethe University, Frankfurt am Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt am Main, Germany
| | - Benjamin Stock
- Department of Neurology, Goethe University, Frankfurt am Main, Germany.,Department of Neuroradiology, Goethe University, Frankfurt am Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt am Main, Germany
| | - Ulrike Nöth
- Brain Imaging Center, Goethe University, Frankfurt am Main, Germany
| | - Elke Hattingen
- Department of Neuroradiology, Goethe University, Frankfurt am Main, Germany
| | - Helmuth Steinmetz
- Department of Neurology, Goethe University, Frankfurt am Main, Germany
| | - Johannes C Klein
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Simon Baudrexel
- Department of Neurology, Goethe University, Frankfurt am Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt am Main, Germany
| | - Marlies Wagner
- Department of Neuroradiology, Goethe University, Frankfurt am Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt am Main, Germany
| | - Ralf Deichmann
- Brain Imaging Center, Goethe University, Frankfurt am Main, Germany
| | - René-Maxime Gracien
- Department of Neurology, Goethe University, Frankfurt am Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt am Main, Germany
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16
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Griffanti L, Klein JC, Szewczyk-Krolikowski K, Menke RAL, Rolinski M, Barber TR, Lawton M, Evetts SG, Begeti F, Crabbe M, Rumbold J, Wade-Martins R, Hu MT, Mackay C. Cohort profile: the Oxford Parkinson's Disease Centre Discovery Cohort MRI substudy (OPDC-MRI). BMJ Open 2020; 10:e034110. [PMID: 32792423 PMCID: PMC7430482 DOI: 10.1136/bmjopen-2019-034110] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
PURPOSE The Oxford Parkinson's Disease Centre (OPDC) Discovery Cohort MRI substudy (OPDC-MRI) collects high-quality multimodal brain MRI together with deep longitudinal clinical phenotyping in patients with Parkinson's, at-risk individuals and healthy elderly participants. The primary aim is to detect pathological changes in brain structure and function, and develop, together with the clinical data, biomarkers to stratify, predict and chart progression in early-stage Parkinson's and at-risk individuals. PARTICIPANTS Participants are recruited from the OPDC Discovery Cohort, a prospective, longitudinal study. Baseline MRI data are currently available for 290 participants: 119 patients with early idiopathic Parkinson's, 15 Parkinson's patients with pathogenic mutations of the leucine-rich repeat kinase 2 or glucocerebrosidase (GBA) genes, 68 healthy controls and 87 individuals at risk of Parkinson's (asymptomatic carriers of GBA mutation and patients with idiopathic rapid eye movement sleep behaviour disorder-RBD). FINDINGS TO DATE Differences in brain structure in early Parkinson's were found to be subtle, with small changes in the shape of the globus pallidus and evidence of alterations in microstructural integrity in the prefrontal cortex that correlated with performance on executive function tests. Brain function, as assayed with resting fMRI yielded more substantial differences, with basal ganglia connectivity reduced in early Parkinson'sand RBD. Imaging of the substantia nigra with the more recent adoption of sequences sensitive to iron and neuromelanin content shows promising results in identifying early signs of Parkinsonian disease. FUTURE PLANS Ongoing studies include the integration of multimodal MRI measures to improve discrimination power. Follow-up clinical data are now accumulating and will allow us to correlate baseline imaging measures to clinical disease progression. Follow-up MRI scanning started in 2015 and is currently ongoing, providing the opportunity for future longitudinal imaging analyses with parallel clinical phenotyping.
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Affiliation(s)
- Ludovica Griffanti
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, Oxfordshire, UK
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, Department of Psychiatry, University of Oxford, Oxford, Oxfordshire, UK
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, UK
| | - Johannes C Klein
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, Oxfordshire, UK
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, Oxfordshire, UK
| | - Konrad Szewczyk-Krolikowski
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, Oxfordshire, UK
| | - Ricarda A L Menke
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, Oxfordshire, UK
| | - Michal Rolinski
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, Oxfordshire, UK
- Institute of Clinical Neurosciences, University of Bristol, Bristol, UK
| | - Thomas R Barber
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, Department of Psychiatry, University of Oxford, Oxford, Oxfordshire, UK
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, Oxfordshire, UK
| | - Michael Lawton
- Population Health Sciences, University of Bristol, Bristol, UK
| | - Samuel G Evetts
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, Oxfordshire, UK
| | - Faye Begeti
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, Oxfordshire, UK
| | - Marie Crabbe
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, Oxfordshire, UK
| | - Jane Rumbold
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, Oxfordshire, UK
| | - Richard Wade-Martins
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, UK
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, Oxfordshire, UK
| | - Michele T Hu
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, Oxfordshire, UK
| | - Clare Mackay
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, Department of Psychiatry, University of Oxford, Oxford, Oxfordshire, UK
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, UK
- Oxford Health, NHS Foundation Trust, Oxford, Oxfordshire, UK
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17
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Seiler A, Lauer A, Deichmann R, Nöth U, Herrmann E, Berkefeld J, Singer OC, Pfeilschifter W, Klein JC, Wagner M. Signal variance-based collateral index in DSC perfusion: A novel method to assess leptomeningeal collateralization in acute ischaemic stroke. J Cereb Blood Flow Metab 2020; 40:574-587. [PMID: 30755069 PMCID: PMC7025396 DOI: 10.1177/0271678x19831024] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
As a determinant of the progression rate of the ischaemic process in acute large-vessel stroke, the degree of collateralization is a strong predictor of the clinical outcome after reperfusion therapy and may influence clinical decision-making. Therefore, the assessment of leptomeningeal collateralization is of major importance. The purpose of this study was to develop and evaluate a quantitative and observer-independent method for assessing leptomeningeal collateralization in acute large-vessel stroke based on signal variance characteristics in T2*-weighted dynamic susceptibility contrast (DSC) perfusion-weighted MR imaging (PWI). Voxels representing leptomeningeal collateral vessels were extracted according to the magnitude of signal variance in the PWI raw data time series in 55 patients with proximal large-artery occlusion and an intra-individual collateral vessel index (CVIPWI) was calculated. CVIPWI correlated significantly with the initial ischaemic core volume (rho = -0.459, p = 0.0001) and the PWI/DWI mismatch ratio (rho = 0.494, p = 0.0001) as an indicator of the amount of salvageable tissue. Furthermore, CVIPWI was significantly negatively correlated with NIHSS and mRS at discharge (rho = -0.341, p = 0.015 and rho = -0.305, p = 0.023). In multivariate logistic regression, CVIPWI was an independent predictor of favourable functional outcome (mRS 0-2) (OR = 16.39, 95% CI 1.42-188.7, p = 0.025). CVIPWI provides useful rater-independent information on the leptomeningeal collateral supply in acute stroke.
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Affiliation(s)
- Alexander Seiler
- Department of Neurology, Goethe University Frankfurt, Frankfurt, Germany
| | - Arne Lauer
- Institute of Neuroradiology, Goethe University Frankfurt, Frankfurt, Germany
| | - Ralf Deichmann
- Brain Imaging Center, Goethe University Frankfurt, Frankfurt, Germany
| | - Ulrike Nöth
- Brain Imaging Center, Goethe University Frankfurt, Frankfurt, Germany
| | - Eva Herrmann
- Institute of Biostatistics and Mathematical Modelling, Goethe University Frankfurt, Frankfurt, Germany
| | - Joachim Berkefeld
- Institute of Neuroradiology, Goethe University Frankfurt, Frankfurt, Germany
| | - Oliver C Singer
- Department of Neurology, Goethe University Frankfurt, Frankfurt, Germany
| | | | - Johannes C Klein
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.,Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Marlies Wagner
- Institute of Neuroradiology, Goethe University Frankfurt, Frankfurt, Germany
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18
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Jabbari E, Holland N, Chelban V, Jones PS, Lamb R, Rawlinson C, Guo T, Costantini AA, Tan MMX, Heslegrave AJ, Roncaroli F, Klein JC, Ansorge O, Allinson KSJ, Jaunmuktane Z, Holton JL, Revesz T, Warner TT, Lees AJ, Zetterberg H, Russell LL, Bocchetta M, Rohrer JD, Williams NM, Grosset DG, Burn DJ, Pavese N, Gerhard A, Kobylecki C, Leigh PN, Church A, Hu MTM, Woodside J, Houlden H, Rowe JB, Morris HR. Diagnosis Across the Spectrum of Progressive Supranuclear Palsy and Corticobasal Syndrome. JAMA Neurol 2020; 77:377-387. [PMID: 31860007 PMCID: PMC6990759 DOI: 10.1001/jamaneurol.2019.4347] [Citation(s) in RCA: 88] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2019] [Accepted: 10/27/2019] [Indexed: 12/29/2022]
Abstract
Importance Atypical parkinsonian syndromes (APS), including progressive supranuclear palsy (PSP), corticobasal syndrome (CBS), and multiple system atrophy (MSA), may be difficult to distinguish in early stages and are often misdiagnosed as Parkinson disease (PD). The diagnostic criteria for PSP have been updated to encompass a range of clinical subtypes but have not been prospectively studied. Objective To define the distinguishing features of PSP and CBS subtypes and to assess their usefulness in facilitating early diagnosis and separation from PD. Design, Setting, Participants This cohort study recruited patients with APS and PD from movement disorder clinics across the United Kingdom from September 1, 2015, through December 1, 2018. Patients with APS were stratified into the following groups: those with Richardson syndrome (PSP-RS), PSP-subcortical (including PSP-parkinsonism and progressive gait freezing subtypes), PSP-cortical (including PSP-frontal and PSP-CBS overlap subtypes), MSA-parkinsonism, MSA-cerebellar, CBS-Alzheimer disease (CBS-AD), and CBS-non-AD. Data were analyzed from February 1, through May 1, 2019. Main Outcomes and Measures Baseline group comparisons used (1) clinical trajectory; (2) cognitive screening scales; (3) serum neurofilament light chain (NF-L) levels; (4) TRIM11, ApoE, and MAPT genotypes; and (5) volumetric magnetic resonance imaging measures. Results A total of 222 patients with APS (101 with PSP, 55 with MSA, 40 with CBS, and 26 indeterminate) were recruited (129 [58.1%] male; mean [SD] age at recruitment, 68.3 [8.7] years). Age-matched control participants (n = 76) and patients with PD (n = 1967) were included for comparison. Concordance between the antemortem clinical and pathologic diagnoses was achieved in 12 of 13 patients with PSP and CBS (92.3%) undergoing postmortem evaluation. Applying the Movement Disorder Society PSP diagnostic criteria almost doubled the number of patients diagnosed with PSP from 58 to 101. Forty-nine of 101 patients with reclassified PSP (48.5%) did not have the classic PSP-RS subtype. Patients in the PSP-subcortical group had a longer diagnostic latency and a more benign clinical trajectory than those in PSP-RS and PSP-cortical groups. The PSP-subcortical group was distinguished from PSP-cortical and PSP-RS groups by cortical volumetric magnetic resonance imaging measures (area under the curve [AUC], 0.84-0.89), cognitive profile (AUC, 0.80-0.83), serum NF-L level (AUC, 0.75-0.83), and TRIM11 rs564309 genotype. Midbrain atrophy was a common feature of all PSP groups. Eight of 17 patients with CBS (47.1%) undergoing cerebrospinal fluid analysis were identified as having the CBS-AD subtype. Patients in the CBS-AD group had a longer diagnostic latency, relatively benign clinical trajectory, greater cognitive impairment, and higher APOE-ε4 allele frequency than those in the CBS-non-AD group (AUC, 0.80-0.87; P < .05). Serum NF-L levels distinguished PD from all PSP and CBS cases combined (AUC, 0.80; P < .05). Conclusions and Relevance These findings suggest that studies focusing on the PSP-RS subtype are likely to miss a large number of patients with underlying PSP tau pathology. Analysis of cerebrospinal fluid defined a distinct CBS-AD subtype. The PSP and CBS subtypes have distinct characteristics that may enhance their early diagnosis.
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Affiliation(s)
- Edwin Jabbari
- Department of Clinical and Movement Neurosciences, UCL (University College London) Queen Square Institute of Neurology, London, United Kingdom
- Movement Disorders Centre, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Negin Holland
- Department of Clinical Neurosciences and MRC (Medical Research Council) Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom
| | - Viorica Chelban
- Department of Clinical and Movement Neurosciences, UCL (University College London) Queen Square Institute of Neurology, London, United Kingdom
- Movement Disorders Centre, UCL Queen Square Institute of Neurology, London, United Kingdom
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - P. Simon Jones
- Department of Clinical Neurosciences and MRC (Medical Research Council) Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom
| | - Ruth Lamb
- Department of Clinical and Movement Neurosciences, UCL (University College London) Queen Square Institute of Neurology, London, United Kingdom
- Movement Disorders Centre, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Charlotte Rawlinson
- Department of Clinical and Movement Neurosciences, UCL (University College London) Queen Square Institute of Neurology, London, United Kingdom
- Movement Disorders Centre, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Tong Guo
- Department of Clinical and Movement Neurosciences, UCL (University College London) Queen Square Institute of Neurology, London, United Kingdom
- Movement Disorders Centre, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Alyssa A. Costantini
- Department of Clinical and Movement Neurosciences, UCL (University College London) Queen Square Institute of Neurology, London, United Kingdom
- Movement Disorders Centre, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Manuela M. X. Tan
- Department of Clinical and Movement Neurosciences, UCL (University College London) Queen Square Institute of Neurology, London, United Kingdom
- Movement Disorders Centre, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Amanda J. Heslegrave
- UK Dementia Research Institute, UCL Queen Square Institute of Neurology, London, United Kingdom
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Federico Roncaroli
- Department of Neurology, Manchester Academic Health Science Centre, Salford Royal NHS (National Health Service) Foundation Trust, University of Manchester, Manchester, United Kingdom
| | - Johannes C. Klein
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Olaf Ansorge
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Kieren S. J. Allinson
- Department of Clinical Neurosciences and MRC (Medical Research Council) Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom
| | - Zane Jaunmuktane
- Reta Lila Weston Institute, UCL Queen Square Institute of Neurology, London, United Kingdom
- Queen Square Brain Bank for Neurological Disorders, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Janice L. Holton
- Reta Lila Weston Institute, UCL Queen Square Institute of Neurology, London, United Kingdom
- Queen Square Brain Bank for Neurological Disorders, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Tamas Revesz
- Reta Lila Weston Institute, UCL Queen Square Institute of Neurology, London, United Kingdom
- Queen Square Brain Bank for Neurological Disorders, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Thomas T. Warner
- Reta Lila Weston Institute, UCL Queen Square Institute of Neurology, London, United Kingdom
- Queen Square Brain Bank for Neurological Disorders, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Andrew J. Lees
- Reta Lila Weston Institute, UCL Queen Square Institute of Neurology, London, United Kingdom
- Queen Square Brain Bank for Neurological Disorders, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Henrik Zetterberg
- UK Dementia Research Institute, UCL Queen Square Institute of Neurology, London, United Kingdom
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, United Kingdom
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
| | - Lucy L. Russell
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Martina Bocchetta
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Jonathan D. Rohrer
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Nigel M. Williams
- Institute of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom
| | - Donald G. Grosset
- Institute of Neurological Sciences, Queen Elizabeth University Hospital, Glasgow, United Kingdom
| | - David J. Burn
- Faculty of Medical Sciences, Newcastle University, Newcastle, United Kingdom
| | - Nicola Pavese
- Faculty of Medical Sciences, Newcastle University, Newcastle, United Kingdom
| | - Alexander Gerhard
- Departments of Geriatrics and Nuclear Medicine, Universitätsklinikum Essen, Essen, Germany
- Division of Neuroscience and Experimental Psychology, University of Manchester, Manchester, United Kingdom
| | - Christopher Kobylecki
- Department of Neurology, Manchester Academic Health Science Centre, Salford Royal NHS (National Health Service) Foundation Trust, University of Manchester, Manchester, United Kingdom
| | - P. Nigel Leigh
- Department of Neuroscience, Brighton and Sussex Medical School, Brighton, United Kingdom
| | - Alistair Church
- Department of Neurology, Royal Gwent Hospital, Newport, United Kingdom
| | - Michele T. M. Hu
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - John Woodside
- Department of Clinical and Movement Neurosciences, UCL (University College London) Queen Square Institute of Neurology, London, United Kingdom
- Movement Disorders Centre, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Henry Houlden
- Department of Clinical and Movement Neurosciences, UCL (University College London) Queen Square Institute of Neurology, London, United Kingdom
- Movement Disorders Centre, UCL Queen Square Institute of Neurology, London, United Kingdom
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - James B. Rowe
- Department of Clinical Neurosciences and MRC (Medical Research Council) Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom
| | - Huw R. Morris
- Department of Clinical and Movement Neurosciences, UCL (University College London) Queen Square Institute of Neurology, London, United Kingdom
- Movement Disorders Centre, UCL Queen Square Institute of Neurology, London, United Kingdom
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19
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Wilson GS, Zhang Y, Reach G, Moatti-Sirat D, Poitout V, Thévenot DR, Lemonnier F, Klein JC. Progress Toward the Development of an Implantable Sensor for Glucose. Clin Chem 2019. [DOI: 10.1093/clinchem/38.9.1613] [Citation(s) in RCA: 74] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Abstract
The development of an electrochemically based implantable sensor for glucose is described. The sensor is needle-shaped, about the size of a 28-gauge needle. It is flexible and must be implanted subcutaneously by using a 21-gauge catheter, which is then removed. When combined with a monitoring unit, this device, based on the glucose oxidase-catalyzed oxidation of glucose, reliably monitors glucose concentrations for as long as 10 days in rats. Various design considerations, including the decision to monitor the hydrogen peroxide produced in the enzymatic reaction, are discussed. Glucose constitutes the most important future target analyte for continuous monitoring, but the basic methodology developed for glucose could be applied to several other analytes such as lactate or ascorbate. The success in implementation of such a device depends on a reaction of the tissue surrounding the implant so as not to interfere with the proper functioning of the sensor. Histochemical evidence indicates that the tissue response leads to enhanced sensor performance.
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Affiliation(s)
- G S Wilson
- Department of Chemistry, University of Kansas, Lawrence 66045
| | - Y Zhang
- Department of Chemistry, University of Kansas, Lawrence 66045
| | - G Reach
- Department of Chemistry, University of Kansas, Lawrence 66045
| | - D Moatti-Sirat
- Department of Chemistry, University of Kansas, Lawrence 66045
| | - V Poitout
- Department of Chemistry, University of Kansas, Lawrence 66045
| | - D R Thévenot
- Department of Chemistry, University of Kansas, Lawrence 66045
| | - F Lemonnier
- Department of Chemistry, University of Kansas, Lawrence 66045
| | - J C Klein
- Department of Chemistry, University of Kansas, Lawrence 66045
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20
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Barber TR, Griffanti L, Bradley KM, McGowan DR, Lo C, Mackay CE, Hu MT, Klein JC. Nigrosome 1 imaging in REM sleep behavior disorder and its association with dopaminergic decline. Ann Clin Transl Neurol 2019; 7:26-35. [PMID: 31820587 PMCID: PMC6952317 DOI: 10.1002/acn3.50962] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [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: 04/15/2019] [Revised: 10/18/2019] [Accepted: 11/08/2019] [Indexed: 12/22/2022] Open
Abstract
OBJECTIVES Rapid eye movement sleep behavior disorder (RBD) patients have a high risk of developing a Parkinsonian disorder, offering an opportunity for neuroprotective intervention. Predicting near-term conversion, however, remains a challenge. Dopamine transporter imaging, while informative, is expensive and not widely available. Here, we investigate the utility of susceptibility-weighted MRI (SWI) to detect abnormalities of the substantia nigra in RBD, and explore their association with striatal dopaminergic deficits. METHODS SWI of the substantia nigra was performed in 46 RBD patients, 27 Parkinson's patients, and 32 control subjects. Dorsal nigral hyperintensity (DNH) was scored by two blinded raters, and separately quantified using a semiautomated process. Forty-two RBD patients were also imaged with 123 I-ioflupane single-photon emission computed tomography (DaT SPECT/CT). RESULTS Consensus visual DNH classification was possible in 87% of participants. 27.5% of RBD patients had lost DNH, compared with 7.7% of control subjects and 96% of Parkinson's patients. RBD patients lacking DNH had significantly lower putamen dopaminergic SPECT/CT activity compared to RBD patients with DNH present (specific uptake ratios 1.89 vs. 2.33, P = 0.002). The mean quantified DNH signal intensity declined in a stepwise pattern, with RBD patients having lower intensity than controls (0.837 vs. 0.877, P = 0.01) but higher than PD patients (0.837 vs. 0.765, P < 0.001). INTERPRETATION Over one quarter of RBD patients have abnormal substantia nigra SWI reminiscent of Parkinson's, which is associated with a greater dopaminergic deficit. This modality may help enrich neuroprotective trials with early converters.
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Affiliation(s)
- Thomas R. Barber
- Oxford Parkinson’s Disease CentreOxfordUnited Kingdom
- Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUnited Kingdom
- Oxford Centre for Human Brain ActivityWellcome Centre for Integrative NeuroimagingDepartment of PsychiatryUniversity of OxfordOxfordUnited Kingdom
| | - Ludovica Griffanti
- Oxford Parkinson’s Disease CentreOxfordUnited Kingdom
- Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUnited Kingdom
- Oxford Centre for Functional MRI of the BrainWellcome Centre for Integrative NeuroimagingNuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUnited Kingdom
| | | | - Daniel R. McGowan
- Radiation Physics & Protection DepartmentChurchill HospitalOxfordUnited Kingdom
| | - Christine Lo
- Oxford Parkinson’s Disease CentreOxfordUnited Kingdom
- Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUnited Kingdom
| | - Clare E. Mackay
- Oxford Parkinson’s Disease CentreOxfordUnited Kingdom
- Oxford Centre for Human Brain ActivityWellcome Centre for Integrative NeuroimagingDepartment of PsychiatryUniversity of OxfordOxfordUnited Kingdom
| | - Michele T. Hu
- Oxford Parkinson’s Disease CentreOxfordUnited Kingdom
- Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUnited Kingdom
| | - Johannes C. Klein
- Oxford Parkinson’s Disease CentreOxfordUnited Kingdom
- Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUnited Kingdom
- Oxford Centre for Human Brain ActivityWellcome Centre for Integrative NeuroimagingDepartment of PsychiatryUniversity of OxfordOxfordUnited Kingdom
- Oxford Centre for Functional MRI of the BrainWellcome Centre for Integrative NeuroimagingNuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUnited Kingdom
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21
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Kelly MJ, Lawton MA, Baig F, Ruffmann C, Barber TR, Lo C, Klein JC, Ben‐Shlomo Y, Hu MT. Predictors of motor complications in early Parkinson's disease: A prospective cohort study. Mov Disord 2019; 34:1174-1183. [PMID: 31283854 PMCID: PMC6771533 DOI: 10.1002/mds.27783] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [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: 01/31/2019] [Revised: 05/21/2019] [Accepted: 06/12/2019] [Indexed: 12/28/2022] Open
Abstract
OBJECTIVE The objective of this study was to identify clinical predictors of motor complications (dyskinesia and motor fluctuations) of levodopa in a prospectively recruited PD cohort using longitudinal analysis. METHODS An inception cohort (Oxford Discovery) of 734 patients was followed to a maximum of 10 years from diagnosis using a discrete-time survival analysis. A subset analysis was used to validate an online dyskinesia-risk calculator developed from the results of the Stalevo Reduction in Dyskinesia Evaluation PD trial. RESULTS A total of 186 cases of dyskinesia and 254 cases of motor fluctuations were observed. Dyskinesia incidence increased with time (risk per 100 participants [95% confidence interval] 13 [11-16] <3.5 years, 16 [13-21] 3.5-5.0 years, 19 [14-26] 5-6.5 years, and 23 [16-33] >6.5 years from diagnosis). Motor complication predictors were grouped as medication predictors, disease predictors and patient predictors. Baseline nonmotor feature severity, low mood, anxiety, and age at symptom onset were associated with motor complications among a number of previously identified predictors. Replication of the Stalevo Reduction in Dyskinesia Evaluation PD calculator was reasonable with the area under the curve for dyskinesia risk score as a predictor of dyskinesia being 0.68 (95% confidence interval, 0.55-0.81). CONCLUSIONS This study quantifies risk of motor complications, finds consistent predictors, and demonstrates the novel finding that nonmotor features of PD, particularly low mood and anxiety, are significant risk factors for motor complications. Further validation of dyskinesia risk scores are required as well as evidence to determine if the routine use of such scores can be clinically valuable in enhancing patient care and quality of life. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Mark J. Kelly
- Oxford Parkinson's Disease CentreUniversity of OxfordOxfordUK
- Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUK
| | | | - Fahd Baig
- Oxford Parkinson's Disease CentreUniversity of OxfordOxfordUK
- Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUK
| | - Claudio Ruffmann
- Oxford Parkinson's Disease CentreUniversity of OxfordOxfordUK
- Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUK
- Neurology DepartmentHampshire Hospitals National Health Service (NHS) Foundation TrustBasingstokeUK
| | - Thomas R. Barber
- Oxford Parkinson's Disease CentreUniversity of OxfordOxfordUK
- Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUK
| | - Christine Lo
- Oxford Parkinson's Disease CentreUniversity of OxfordOxfordUK
- Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUK
| | - Johannes C. Klein
- Oxford Parkinson's Disease CentreUniversity of OxfordOxfordUK
- Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUK
| | | | - Michele T. Hu
- Oxford Parkinson's Disease CentreUniversity of OxfordOxfordUK
- Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUK
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22
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Lo C, Arora S, Baig F, Lawton MA, El Mouden C, Barber TR, Ruffmann C, Klein JC, Brown P, Ben-Shlomo Y, de Vos M, Hu MT. Predicting motor, cognitive & functional impairment in Parkinson's. Ann Clin Transl Neurol 2019; 6:1498-1509. [PMID: 31402628 PMCID: PMC6689691 DOI: 10.1002/acn3.50853] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2019] [Revised: 06/26/2019] [Accepted: 07/03/2019] [Indexed: 01/17/2023] Open
Abstract
OBJECTIVE We recently demonstrated that 998 features derived from a simple 7-minute smartphone test could distinguish between controls, people with Parkinson's and people with idiopathic Rapid Eye Movement sleep behavior disorder, with mean sensitivity/specificity values of 84.6-91.9%. Here, we investigate whether the same smartphone features can be used to predict future clinically relevant outcomes in early Parkinson's. METHODS A total of 237 participants with Parkinson's (mean (SD) disease duration 3.5 (2.2) years) in the Oxford Discovery cohort performed smartphone tests in clinic and at home. Each test assessed voice, balance, gait, reaction time, dexterity, rest, and postural tremor. In addition, standard motor, cognitive and functional assessments and questionnaires were administered in clinic. Machine learning algorithms were trained to predict the onset of clinical outcomes provided at the next 18-month follow-up visit using baseline smartphone recordings alone. The accuracy of model predictions was assessed using 10-fold and subject-wise cross validation schemes. RESULTS Baseline smartphone tests predicted the new onset of falls, freezing, postural instability, cognitive impairment, and functional impairment at 18 months. For all outcome predictions AUC values were greater than 0.90 for 10-fold cross validation using all smartphone features. Using only the 30 most salient features, AUC values greater than 0.75 were obtained. INTERPRETATION We demonstrate the ability to predict key future clinical outcomes using a simple smartphone test. This work has the potential to introduce individualized predictions to routine care, helping to target interventions to those most likely to benefit, with the aim of improving their outcome.
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Affiliation(s)
- Christine Lo
- Oxford Parkinson's Disease Centre (OPDC), University of Oxford, Oxford, UK.,Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Siddharth Arora
- Oxford Parkinson's Disease Centre (OPDC), University of Oxford, Oxford, UK.,Somerville College, University of Oxford, Oxford, UK
| | - Fahd Baig
- Oxford Parkinson's Disease Centre (OPDC), University of Oxford, Oxford, UK.,Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | | | - Claire El Mouden
- Oxford Parkinson's Disease Centre (OPDC), University of Oxford, Oxford, UK.,Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Thomas R Barber
- Oxford Parkinson's Disease Centre (OPDC), University of Oxford, Oxford, UK.,Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Claudio Ruffmann
- Oxford Parkinson's Disease Centre (OPDC), University of Oxford, Oxford, UK.,Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Johannes C Klein
- Oxford Parkinson's Disease Centre (OPDC), University of Oxford, Oxford, UK
| | - Peter Brown
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.,Medical Research Council Brain Network Dynamics Unit, University of Oxford, Oxford, UK
| | - Yoav Ben-Shlomo
- Population Health Sciences, University of Bristol, Bristol, UK
| | - Maarten de Vos
- Institute of Biomedical Engineering, University of Oxford, Oxford, UK
| | - Michele T Hu
- Oxford Parkinson's Disease Centre (OPDC), University of Oxford, Oxford, UK.,Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
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23
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Baig F, Kelly MJ, Lawton MA, Ruffmann C, Rolinski M, Klein JC, Barber T, Lo C, Ben-Shlomo Y, Okai D, Hu MT. Impulse control disorders in Parkinson disease and RBD: A longitudinal study of severity. Neurology 2019; 93:e675-e687. [PMID: 31311842 PMCID: PMC6715510 DOI: 10.1212/wnl.0000000000007942] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2018] [Accepted: 03/28/2019] [Indexed: 11/17/2022] Open
Abstract
Objective To describe the prevalence, natural history, and risk factors for impulse control behaviors (ICBs) among people with Parkinson disease (PD), those with REM sleep behavior disorder (RBD), and controls. Methods Participants with early PD (within 3.5 years of diagnosis), those with RBD, and controls were clinically phenotyped and screened for ICBs longitudinally (with the Questionnaire for Impulsivity in Parkinson's Disease). ICB-positive individuals were invited for a semistructured interview, repeated 1 year later. The severity of the ICB was assessed with the Parkinson's Impulse Control Scale. Multiple imputation and regression models were used to estimate ICB prevalence and associations. Results Data from 921 cases of PD at baseline, 768 cases at 18 months, and 531 cases at 36 months were included, with 21% to 25% screening positive for ICBs at each visit. Interviews of ICB screen–positive individuals revealed that 10% met formal criteria for impulse control disorders (ICD), while 33% had subsyndromal ICD (ICB symptoms without reaching the formal diagnostic criteria for ICD). When these data were combined through the use of multiple imputation, the prevalence of PD-ICB was estimated at 19.1% (95% confidence interval 10.1–28.2). On follow-up, 24% of cases of subsyndromal ICD had developed full symptoms of an ICD. PD-ICD was associated with dopamine agonist use, motor complications, and apathy but not PD-RBD. ICD prevalence in the RBD group (1%) was similar to that in controls (0.7%). Conclusions ICBs occur in 19.1% of patients with early PD, many persisting or worsening over time. RBD is not associated with increased ICD risk. Psychosocial drivers, including mood and support networks, affect severity.
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Affiliation(s)
- Fahd Baig
- From the Oxford Parkinson's Disease Centre (F.B., M.J.K., M.A.L., C.R., M.R., J.C.K., T.B., C.L., Y.B.-S., D.O., M.T.H.), and Nuffield Department of Clinical Neurosciences (F.B., M.J.K.), University of Oxford; Population Health Sciences (M.A.L., Y.B.-S.) and Translational Health Sciences (M.R.), University of Bristol; and Department of Psychological Medicine (D.O.), Oxford University Hospitals NHS Trust, UK
| | - Mark J Kelly
- From the Oxford Parkinson's Disease Centre (F.B., M.J.K., M.A.L., C.R., M.R., J.C.K., T.B., C.L., Y.B.-S., D.O., M.T.H.), and Nuffield Department of Clinical Neurosciences (F.B., M.J.K.), University of Oxford; Population Health Sciences (M.A.L., Y.B.-S.) and Translational Health Sciences (M.R.), University of Bristol; and Department of Psychological Medicine (D.O.), Oxford University Hospitals NHS Trust, UK
| | - Michael A Lawton
- From the Oxford Parkinson's Disease Centre (F.B., M.J.K., M.A.L., C.R., M.R., J.C.K., T.B., C.L., Y.B.-S., D.O., M.T.H.), and Nuffield Department of Clinical Neurosciences (F.B., M.J.K.), University of Oxford; Population Health Sciences (M.A.L., Y.B.-S.) and Translational Health Sciences (M.R.), University of Bristol; and Department of Psychological Medicine (D.O.), Oxford University Hospitals NHS Trust, UK
| | - Claudio Ruffmann
- From the Oxford Parkinson's Disease Centre (F.B., M.J.K., M.A.L., C.R., M.R., J.C.K., T.B., C.L., Y.B.-S., D.O., M.T.H.), and Nuffield Department of Clinical Neurosciences (F.B., M.J.K.), University of Oxford; Population Health Sciences (M.A.L., Y.B.-S.) and Translational Health Sciences (M.R.), University of Bristol; and Department of Psychological Medicine (D.O.), Oxford University Hospitals NHS Trust, UK
| | - Michal Rolinski
- From the Oxford Parkinson's Disease Centre (F.B., M.J.K., M.A.L., C.R., M.R., J.C.K., T.B., C.L., Y.B.-S., D.O., M.T.H.), and Nuffield Department of Clinical Neurosciences (F.B., M.J.K.), University of Oxford; Population Health Sciences (M.A.L., Y.B.-S.) and Translational Health Sciences (M.R.), University of Bristol; and Department of Psychological Medicine (D.O.), Oxford University Hospitals NHS Trust, UK
| | - Johannes C Klein
- From the Oxford Parkinson's Disease Centre (F.B., M.J.K., M.A.L., C.R., M.R., J.C.K., T.B., C.L., Y.B.-S., D.O., M.T.H.), and Nuffield Department of Clinical Neurosciences (F.B., M.J.K.), University of Oxford; Population Health Sciences (M.A.L., Y.B.-S.) and Translational Health Sciences (M.R.), University of Bristol; and Department of Psychological Medicine (D.O.), Oxford University Hospitals NHS Trust, UK
| | - Thomas Barber
- From the Oxford Parkinson's Disease Centre (F.B., M.J.K., M.A.L., C.R., M.R., J.C.K., T.B., C.L., Y.B.-S., D.O., M.T.H.), and Nuffield Department of Clinical Neurosciences (F.B., M.J.K.), University of Oxford; Population Health Sciences (M.A.L., Y.B.-S.) and Translational Health Sciences (M.R.), University of Bristol; and Department of Psychological Medicine (D.O.), Oxford University Hospitals NHS Trust, UK
| | - Christine Lo
- From the Oxford Parkinson's Disease Centre (F.B., M.J.K., M.A.L., C.R., M.R., J.C.K., T.B., C.L., Y.B.-S., D.O., M.T.H.), and Nuffield Department of Clinical Neurosciences (F.B., M.J.K.), University of Oxford; Population Health Sciences (M.A.L., Y.B.-S.) and Translational Health Sciences (M.R.), University of Bristol; and Department of Psychological Medicine (D.O.), Oxford University Hospitals NHS Trust, UK
| | - Yoav Ben-Shlomo
- From the Oxford Parkinson's Disease Centre (F.B., M.J.K., M.A.L., C.R., M.R., J.C.K., T.B., C.L., Y.B.-S., D.O., M.T.H.), and Nuffield Department of Clinical Neurosciences (F.B., M.J.K.), University of Oxford; Population Health Sciences (M.A.L., Y.B.-S.) and Translational Health Sciences (M.R.), University of Bristol; and Department of Psychological Medicine (D.O.), Oxford University Hospitals NHS Trust, UK
| | - David Okai
- From the Oxford Parkinson's Disease Centre (F.B., M.J.K., M.A.L., C.R., M.R., J.C.K., T.B., C.L., Y.B.-S., D.O., M.T.H.), and Nuffield Department of Clinical Neurosciences (F.B., M.J.K.), University of Oxford; Population Health Sciences (M.A.L., Y.B.-S.) and Translational Health Sciences (M.R.), University of Bristol; and Department of Psychological Medicine (D.O.), Oxford University Hospitals NHS Trust, UK
| | - Michele T Hu
- From the Oxford Parkinson's Disease Centre (F.B., M.J.K., M.A.L., C.R., M.R., J.C.K., T.B., C.L., Y.B.-S., D.O., M.T.H.), and Nuffield Department of Clinical Neurosciences (F.B., M.J.K.), University of Oxford; Population Health Sciences (M.A.L., Y.B.-S.) and Translational Health Sciences (M.R.), University of Bristol; and Department of Psychological Medicine (D.O.), Oxford University Hospitals NHS Trust, UK.
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24
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Barber TR, Griffanti L, Muhammed K, Drew DS, Bradley KM, McGowan DR, Crabbe M, Lo C, Mackay CE, Husain M, Hu MT, Klein JC. Apathy in rapid eye movement sleep behaviour disorder is associated with serotonin depletion in the dorsal raphe nucleus. Brain 2019; 141:2848-2854. [PMID: 30212839 PMCID: PMC6158712 DOI: 10.1093/brain/awy240] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [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] [Received: 05/21/2018] [Accepted: 08/01/2018] [Indexed: 11/13/2022] Open
Abstract
Apathy is a common and under-recognized disorder that often emerges in the prodromal phase of Parkinsonian diseases. The mechanism by which this occurs is not known, but recent evidence from patients with established Parkinson's disease suggests that serotonergic dysfunction may play a role. The integrity of the raphe serotonergic system can be assessed alongside dopaminergic basal ganglia imaging using the radioligand 123I-ioflupane, which binds both serotonin and dopamine transporters. To investigate the relative roles of these neurotransmitters in prodromal parkinsonism, we imaged patients with idiopathic rapid eye movement sleep behaviour disorder, the majority of whom will develop a parkinsonian disorder in future. Forty-three patients underwent brain imaging with 123I-ioflupane single photon emission computed tomography and structural MRI. Apathy was quantified using the Lille Apathy Rating Scale. Other clinical parkinsonian features were assessed using standard measures. A negative correlation was observed between apathy severity and serotonergic 123I-ioflupane signal in the dorsal raphe nucleus (r = -0.55, P < 0.001). There was no significant correlation between apathy severity and basal ganglia dopaminergic signal, nor between dorsal raphe signal and other neuropsychiatric scores. This specific association between apathy and raphe 123I-ioflupane signal suggests that the serotonergic system might represent a target for the treatment of apathy.
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Affiliation(s)
- Thomas R Barber
- Oxford Parkinson's Disease Centre, Oxford, UK.,Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.,Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, UK
| | - Ludovica Griffanti
- Oxford Parkinson's Disease Centre, Oxford, UK.,Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.,Oxford Centre for Functional MRI of the Brain, Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Kinan Muhammed
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.,Department of Experimental Psychology, University of Oxford, Oxford, UK
| | - Daniel S Drew
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.,Department of Experimental Psychology, University of Oxford, Oxford, UK
| | | | - Daniel R McGowan
- Radiation Physics and Protection Department, Churchill Hospital, Oxford, UK
| | - Marie Crabbe
- Oxford Parkinson's Disease Centre, Oxford, UK.,Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Christine Lo
- Oxford Parkinson's Disease Centre, Oxford, UK.,Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Clare E Mackay
- Oxford Parkinson's Disease Centre, Oxford, UK.,Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, UK
| | - Masud Husain
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.,Department of Experimental Psychology, University of Oxford, Oxford, UK
| | - Michele T Hu
- Oxford Parkinson's Disease Centre, Oxford, UK.,Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Johannes C Klein
- Oxford Parkinson's Disease Centre, Oxford, UK.,Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.,Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, UK.,Oxford Centre for Functional MRI of the Brain, Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
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25
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Seiler A, Blockley NP, Deichmann R, Nöth U, Singer OC, Chappell MA, Klein JC, Wagner M. The relationship between blood flow impairment and oxygen depletion in acute ischemic stroke imaged with magnetic resonance imaging. J Cereb Blood Flow Metab 2019; 39:454-465. [PMID: 28929836 PMCID: PMC6421246 DOI: 10.1177/0271678x17732448] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Oxygenation-sensitive spin relaxation time T2' and relaxation rate R2' (1/T2') are presumed to be markers of the cerebral oxygen extraction fraction (OEF) in acute ischemic stroke. In this study, we investigate the relationship of T2'/R2' with dynamic susceptibility contrast-based relative cerebral blood flow (rCBF) in acute ischemic stroke to assess their plausibility as surrogate markers of the ischemic penumbra. Twenty-one consecutive patients with internal carotid artery and/or middle cerebral artery occlusion were studied at 3.0 T. A physiological model of the cerebral vasculature (VM) was used to process PWI raw data in addition to a conventional deconvolution technique. T2', R2', and rCBF values were extracted from the ischemic core and hypoperfused areas. Within hypoperfused tissue, no correlation was found between deconvolved rCBF and T2' ( r = -0.05, p = 0.788), or R2' ( r = 0.039, p = 0.836). In contrast, we found a strong positive correlation with T2' ( r = 0.444, p = 0.006) and negative correlation with R2' ( r = -0.494, p = 0.0025) for rCBFVM, indicating increasing OEF with decreasing CBF and that rCBF based on the vascular model may be more closely related to metabolic disturbances. Further research to refine and validate these techniques may enable their use as MRI-based surrogate markers of the ischemic penumbra for selecting stroke patients for interventional treatment strategies.
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Affiliation(s)
- Alexander Seiler
- 1 Department of Neurology, Goethe University Frankfurt, Frankfurt, Germany
| | - Nicholas P Blockley
- 2 Nuffield Department of Clinical Neurosciences, Oxford Center for Functional MRI of the Brain, University of Oxford, Oxford, UK
| | - Ralf Deichmann
- 3 Brain Imaging Center, Goethe University Frankfurt, Frankfurt, Germany
| | - Ulrike Nöth
- 3 Brain Imaging Center, Goethe University Frankfurt, Frankfurt, Germany
| | - Oliver C Singer
- 1 Department of Neurology, Goethe University Frankfurt, Frankfurt, Germany
| | - Michael A Chappell
- 2 Nuffield Department of Clinical Neurosciences, Oxford Center for Functional MRI of the Brain, University of Oxford, Oxford, UK.,4 Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford, UK
| | - Johannes C Klein
- 5 Nuffield Department of Clinical Neurosciences, Oxford University, and Department of Neurology, Oxford University Hospitals NHS Trust, Oxford, UK
| | - Marlies Wagner
- 6 Institute of Neuroradiology, Goethe University Frankfurt, Frankfurt, Germany
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26
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Griffanti L, Stratmann P, Rolinski M, Filippini N, Zsoldos E, Mahmood A, Zamboni G, Douaud G, Klein JC, Kivimäki M, Singh-Manoux A, Hu MT, Ebmeier KP, Mackay CE. Exploring variability in basal ganglia connectivity with functional MRI in healthy aging. Brain Imaging Behav 2018; 12:1822-1827. [PMID: 29442271 PMCID: PMC6302142 DOI: 10.1007/s11682-018-9824-1] [Citation(s) in RCA: 12] [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] [Indexed: 11/28/2022]
Abstract
Changes in functional connectivity (FC) measured using resting state fMRI within the basal ganglia network (BGN) have been observed in pathologies with altered neurotransmitter systems and conditions involving motor control and dopaminergic processes. However, less is known about non-disease factors affecting FC in the BGN. The aim of this study was to examine associations of FC within the BGN with dopaminergic processes in healthy older adults. We explored the relationship between FC in the BGN and variables related to demographics, impulsive behavior, self-paced tasks, mood, and motor correlates in 486 participants in the Whitehall-II imaging sub-study using both region-of-interest- and voxel-based approaches. Age was the only correlate of FC in the BGN that was consistently significant with both analyses. The observed adverse effect of aging on FC may relate to alterations of the dopaminergic system, but no unique dopamine-related function seemed to have a link with FC beyond those detectable in and linearly correlated with healthy aging.
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Affiliation(s)
- Ludovica Griffanti
- Centre for the functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Oxford Parkinson's Disease Centre (OPDC), Oxford, UK
| | - Philipp Stratmann
- Department of Psychiatry, University of Oxford, Oxford, UK
- Department of Informatics, Germany and Institute of Robotics and Mechatronics, German Aerospace Center (DLR), Technical University of Munich, Wessling, Germany
| | - Michal Rolinski
- Oxford Parkinson's Disease Centre (OPDC), Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Institute of Clinical Neurosciences, University of Bristol, Bristol, UK
| | - Nicola Filippini
- Centre for the functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Enikő Zsoldos
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Abda Mahmood
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Giovanna Zamboni
- Centre for the functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Gwenaëlle Douaud
- Centre for the functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Johannes C Klein
- Centre for the functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Oxford Parkinson's Disease Centre (OPDC), Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Mika Kivimäki
- Department of Epidemiology and Public Health, University College London, London, UK
| | - Archana Singh-Manoux
- Department of Epidemiology and Public Health, University College London, London, UK
- INSERM, U 1018, Hôpital Paul-Brousse, Villejuif, France
| | - Michele T Hu
- Oxford Parkinson's Disease Centre (OPDC), Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | | | - Clare E Mackay
- Oxford Parkinson's Disease Centre (OPDC), Oxford, UK.
- Oxford Health NHS Foundation Trust, Oxford, UK.
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, OX3 7JX, UK.
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27
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Lawton M, Ben-Shlomo Y, May MT, Baig F, Barber TR, Klein JC, Swallow DMA, Malek N, Grosset KA, Bajaj N, Barker RA, Williams N, Burn DJ, Foltynie T, Morris HR, Wood NW, Grosset DG, Hu MTM. Developing and validating Parkinson's disease subtypes and their motor and cognitive progression. J Neurol Neurosurg Psychiatry 2018; 89:1279-1287. [PMID: 30464029 PMCID: PMC6288789 DOI: 10.1136/jnnp-2018-318337] [Citation(s) in RCA: 91] [Impact Index Per Article: 15.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/02/2018] [Revised: 06/05/2018] [Accepted: 06/13/2018] [Indexed: 01/30/2023]
Abstract
OBJECTIVES To use a data-driven approach to determine the existence and natural history of subtypes of Parkinson's disease (PD) using two large independent cohorts of patients newly diagnosed with this condition. METHODS 1601 and 944 patients with idiopathic PD, from Tracking Parkinson's and Discovery cohorts, respectively, were evaluated in motor, cognitive and non-motor domains at the baseline assessment. Patients were recently diagnosed at entry (within 3.5 years of diagnosis) and were followed up every 18 months. We used a factor analysis followed by a k-means cluster analysis, while prognosis was measured using random slope and intercept models. RESULTS We identified four clusters: (1) fast motor progression with symmetrical motor disease, poor olfaction, cognition and postural hypotension; (2) mild motor and non-motor disease with intermediate motor progression; (3) severe motor disease, poor psychological well-being and poor sleep with an intermediate motor progression; (4) slow motor progression with tremor-dominant, unilateral disease. Clusters were moderately to substantially stable across the two cohorts (kappa 0.58). Cluster 1 had the fastest motor progression in Tracking Parkinson's at 3.2 (95% CI 2.8 to 3.6) UPDRS III points per year while cluster 4 had the slowest at 0.6 (0.1-1.1). In Tracking Parkinson's, cluster 2 had the largest response to levodopa 36.3% and cluster 4 the lowest 28.8%. CONCLUSIONS We have found four novel clusters that replicated well across two independent early PD cohorts and were associated with levodopa response and motor progression rates. This has potential implications for better understanding disease pathophysiology and the relevance of patient stratification in future clinical trials.
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Affiliation(s)
- Michael Lawton
- Department of Population Health Sciences, University of Bristol, Bristol, UK
| | - Yoav Ben-Shlomo
- Department of Population Health Sciences, University of Bristol, Bristol, UK
| | - Margaret T May
- Department of Population Health Sciences, University of Bristol, Bristol, UK
| | - Fahd Baig
- Nuffield Department of Clinical Neurosciences, Division of Clinical Neurology, University of Oxford, Oxford, UK.,Oxford Parkinson's Disease Centre, University of Oxford, Oxford, UK
| | - Thomas R Barber
- Nuffield Department of Clinical Neurosciences, Division of Clinical Neurology, University of Oxford, Oxford, UK.,Oxford Parkinson's Disease Centre, University of Oxford, Oxford, UK
| | - Johannes C Klein
- Nuffield Department of Clinical Neurosciences, Division of Clinical Neurology, University of Oxford, Oxford, UK.,Oxford Parkinson's Disease Centre, University of Oxford, Oxford, UK
| | - Diane M A Swallow
- Institute of Applied Health Sciences, University of Aberdeen, Aberdeen, UK
| | - Naveed Malek
- Department of Neurology, Institute of Neurological Sciences, Glasgow, UK
| | | | - Nin Bajaj
- Department of Neurology, Queen's Medical Centre, Nottingham, UK
| | - Roger A Barker
- Clinical Neurosciences, John van Geest Centre for Brain Repair, Cambridge, UK
| | - Nigel Williams
- Cardiff University, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff, UK
| | - David J Burn
- Faculty of Medical Sciences, Newcastle University, Newcastle, UK
| | - Thomas Foltynie
- Sobell Department of Motor Neuroscience, UCL Institute of Neurology, London, UK
| | - Huw R Morris
- Department of Clinical Neuroscience, UCL Institute of Neurology, London, UK
| | - Nicholas W Wood
- Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK
| | - Donald G Grosset
- Department of Neurology, Institute of Neurological Sciences, Glasgow, UK
| | - Michele T M Hu
- Nuffield Department of Clinical Neurosciences, Division of Clinical Neurology, University of Oxford, Oxford, UK.,Oxford Parkinson's Disease Centre, University of Oxford, Oxford, UK
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28
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Seiler A, You SJ, Wagner M, Klein JC. Teaching Neuro Images: HIV-associated cerebral vasculopathy with multiple nodular aneurysms. Neurology 2018; 88:e143-e144. [PMID: 28373376 DOI: 10.1212/wnl.0000000000003793] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Affiliation(s)
- Alexander Seiler
- From the Departments of Neurology (A.S.) and Neuroradiology (S.-J.Y., M.W.), Goethe University Frankfurt, Germany; Nuffield Department of Clinical Neurosciences (J.C.K.), Oxford University; and Department of Neurology (J.C.K.), Oxford University Hospitals NHS Trust, UK.
| | - Se-Jong You
- From the Departments of Neurology (A.S.) and Neuroradiology (S.-J.Y., M.W.), Goethe University Frankfurt, Germany; Nuffield Department of Clinical Neurosciences (J.C.K.), Oxford University; and Department of Neurology (J.C.K.), Oxford University Hospitals NHS Trust, UK
| | - Marlies Wagner
- From the Departments of Neurology (A.S.) and Neuroradiology (S.-J.Y., M.W.), Goethe University Frankfurt, Germany; Nuffield Department of Clinical Neurosciences (J.C.K.), Oxford University; and Department of Neurology (J.C.K.), Oxford University Hospitals NHS Trust, UK
| | - Johannes C Klein
- From the Departments of Neurology (A.S.) and Neuroradiology (S.-J.Y., M.W.), Goethe University Frankfurt, Germany; Nuffield Department of Clinical Neurosciences (J.C.K.), Oxford University; and Department of Neurology (J.C.K.), Oxford University Hospitals NHS Trust, UK
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29
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Arora S, Baig F, Lo C, Barber TR, Lawton MA, Zhan A, Rolinski M, Ruffmann C, Klein JC, Rumbold J, Louvel A, Zaiwalla Z, Lennox G, Quinnell T, Dennis G, Wade-Martins R, Ben-Shlomo Y, Little MA, Hu MT. Smartphone motor testing to distinguish idiopathic REM sleep behavior disorder, controls, and PD. Neurology 2018; 91:e1528-e1538. [PMID: 30232246 PMCID: PMC6202945 DOI: 10.1212/wnl.0000000000006366] [Citation(s) in RCA: 67] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2018] [Accepted: 07/12/2018] [Indexed: 11/28/2022] Open
Abstract
Objective We sought to identify motor features that would allow the delineation of individuals with sleep study-confirmed idiopathic REM sleep behavior disorder (iRBD) from controls and Parkinson disease (PD) using a customized smartphone application. Methods A total of 334 PD, 104 iRBD, and 84 control participants performed 7 tasks to evaluate voice, balance, gait, finger tapping, reaction time, rest tremor, and postural tremor. Smartphone recordings were collected both in clinic and at home under noncontrolled conditions over several days. All participants underwent detailed parallel in-clinic assessments. Using only the smartphone sensor recordings, we sought to (1) discriminate whether the participant had iRBD or PD and (2) identify which of the above 7 motor tasks were most salient in distinguishing groups. Results Statistically significant differences based on these 7 tasks were observed between the 3 groups. For the 3 pairwise discriminatory comparisons, (1) controls vs iRBD, (2) controls vs PD, and (3) iRBD vs PD, the mean sensitivity and specificity values ranged from 84.6% to 91.9%. Postural tremor, rest tremor, and voice were the most discriminatory tasks overall, whereas the reaction time was least discriminatory. Conclusions Prodromal forms of PD include the sleep disorder iRBD, where subtle motor impairment can be detected using clinician-based rating scales (e.g., Unified Parkinson's Disease Rating Scale), which may lack the sensitivity to detect and track granular change. Consumer grade smartphones can be used to accurately separate not only iRBD from controls but also iRBD from PD participants, providing a growing consensus for the utility of digital biomarkers in early and prodromal PD.
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Affiliation(s)
- Siddharth Arora
- From the Oxford Parkinson's Disease Centre (OPDC) (S.A., F.B., C.L., T.R.B., M.R., C.R., J.C.K., J.R., A.L., R.W.-M, M.T.H.), University of Oxford, UK; Engineering and Applied Science (S.A., M.A.L.), Aston University, Birmingham, UK; Somerville College (S.A.), University of Oxford, UK; Nuffield Department of Clinical Neurosciences (F.B., C.L., T.R.B., M.A.L., M.T.H.), University of Oxford, UK; Population Health Sciences (M.A.L.), University of Bristol, UK; andDepartment of Computer Science (A.Z.), Johns Hopkins University, Baltimore; Department of Neurology and Neurophysiology (Z.Z., G.L., M.T.H.), Oxford University Hospitals NHS Trust, UK; Respiratory Support and Sleep Centre (T.Q.), Papworth Hospital, Cambridge, UK; Department of Neurology (G.D.), Royal Hallamshire Hospital, Sheffield, UK; and Media Lab (M.A.L.), Massachusetts Institute of Technology, Cambridge, MA
| | - Fahd Baig
- From the Oxford Parkinson's Disease Centre (OPDC) (S.A., F.B., C.L., T.R.B., M.R., C.R., J.C.K., J.R., A.L., R.W.-M, M.T.H.), University of Oxford, UK; Engineering and Applied Science (S.A., M.A.L.), Aston University, Birmingham, UK; Somerville College (S.A.), University of Oxford, UK; Nuffield Department of Clinical Neurosciences (F.B., C.L., T.R.B., M.A.L., M.T.H.), University of Oxford, UK; Population Health Sciences (M.A.L.), University of Bristol, UK; andDepartment of Computer Science (A.Z.), Johns Hopkins University, Baltimore; Department of Neurology and Neurophysiology (Z.Z., G.L., M.T.H.), Oxford University Hospitals NHS Trust, UK; Respiratory Support and Sleep Centre (T.Q.), Papworth Hospital, Cambridge, UK; Department of Neurology (G.D.), Royal Hallamshire Hospital, Sheffield, UK; and Media Lab (M.A.L.), Massachusetts Institute of Technology, Cambridge, MA
| | - Christine Lo
- From the Oxford Parkinson's Disease Centre (OPDC) (S.A., F.B., C.L., T.R.B., M.R., C.R., J.C.K., J.R., A.L., R.W.-M, M.T.H.), University of Oxford, UK; Engineering and Applied Science (S.A., M.A.L.), Aston University, Birmingham, UK; Somerville College (S.A.), University of Oxford, UK; Nuffield Department of Clinical Neurosciences (F.B., C.L., T.R.B., M.A.L., M.T.H.), University of Oxford, UK; Population Health Sciences (M.A.L.), University of Bristol, UK; andDepartment of Computer Science (A.Z.), Johns Hopkins University, Baltimore; Department of Neurology and Neurophysiology (Z.Z., G.L., M.T.H.), Oxford University Hospitals NHS Trust, UK; Respiratory Support and Sleep Centre (T.Q.), Papworth Hospital, Cambridge, UK; Department of Neurology (G.D.), Royal Hallamshire Hospital, Sheffield, UK; and Media Lab (M.A.L.), Massachusetts Institute of Technology, Cambridge, MA
| | - Thomas R Barber
- From the Oxford Parkinson's Disease Centre (OPDC) (S.A., F.B., C.L., T.R.B., M.R., C.R., J.C.K., J.R., A.L., R.W.-M, M.T.H.), University of Oxford, UK; Engineering and Applied Science (S.A., M.A.L.), Aston University, Birmingham, UK; Somerville College (S.A.), University of Oxford, UK; Nuffield Department of Clinical Neurosciences (F.B., C.L., T.R.B., M.A.L., M.T.H.), University of Oxford, UK; Population Health Sciences (M.A.L.), University of Bristol, UK; andDepartment of Computer Science (A.Z.), Johns Hopkins University, Baltimore; Department of Neurology and Neurophysiology (Z.Z., G.L., M.T.H.), Oxford University Hospitals NHS Trust, UK; Respiratory Support and Sleep Centre (T.Q.), Papworth Hospital, Cambridge, UK; Department of Neurology (G.D.), Royal Hallamshire Hospital, Sheffield, UK; and Media Lab (M.A.L.), Massachusetts Institute of Technology, Cambridge, MA
| | - Michael A Lawton
- From the Oxford Parkinson's Disease Centre (OPDC) (S.A., F.B., C.L., T.R.B., M.R., C.R., J.C.K., J.R., A.L., R.W.-M, M.T.H.), University of Oxford, UK; Engineering and Applied Science (S.A., M.A.L.), Aston University, Birmingham, UK; Somerville College (S.A.), University of Oxford, UK; Nuffield Department of Clinical Neurosciences (F.B., C.L., T.R.B., M.A.L., M.T.H.), University of Oxford, UK; Population Health Sciences (M.A.L.), University of Bristol, UK; andDepartment of Computer Science (A.Z.), Johns Hopkins University, Baltimore; Department of Neurology and Neurophysiology (Z.Z., G.L., M.T.H.), Oxford University Hospitals NHS Trust, UK; Respiratory Support and Sleep Centre (T.Q.), Papworth Hospital, Cambridge, UK; Department of Neurology (G.D.), Royal Hallamshire Hospital, Sheffield, UK; and Media Lab (M.A.L.), Massachusetts Institute of Technology, Cambridge, MA
| | - Andong Zhan
- From the Oxford Parkinson's Disease Centre (OPDC) (S.A., F.B., C.L., T.R.B., M.R., C.R., J.C.K., J.R., A.L., R.W.-M, M.T.H.), University of Oxford, UK; Engineering and Applied Science (S.A., M.A.L.), Aston University, Birmingham, UK; Somerville College (S.A.), University of Oxford, UK; Nuffield Department of Clinical Neurosciences (F.B., C.L., T.R.B., M.A.L., M.T.H.), University of Oxford, UK; Population Health Sciences (M.A.L.), University of Bristol, UK; andDepartment of Computer Science (A.Z.), Johns Hopkins University, Baltimore; Department of Neurology and Neurophysiology (Z.Z., G.L., M.T.H.), Oxford University Hospitals NHS Trust, UK; Respiratory Support and Sleep Centre (T.Q.), Papworth Hospital, Cambridge, UK; Department of Neurology (G.D.), Royal Hallamshire Hospital, Sheffield, UK; and Media Lab (M.A.L.), Massachusetts Institute of Technology, Cambridge, MA
| | - Michal Rolinski
- From the Oxford Parkinson's Disease Centre (OPDC) (S.A., F.B., C.L., T.R.B., M.R., C.R., J.C.K., J.R., A.L., R.W.-M, M.T.H.), University of Oxford, UK; Engineering and Applied Science (S.A., M.A.L.), Aston University, Birmingham, UK; Somerville College (S.A.), University of Oxford, UK; Nuffield Department of Clinical Neurosciences (F.B., C.L., T.R.B., M.A.L., M.T.H.), University of Oxford, UK; Population Health Sciences (M.A.L.), University of Bristol, UK; andDepartment of Computer Science (A.Z.), Johns Hopkins University, Baltimore; Department of Neurology and Neurophysiology (Z.Z., G.L., M.T.H.), Oxford University Hospitals NHS Trust, UK; Respiratory Support and Sleep Centre (T.Q.), Papworth Hospital, Cambridge, UK; Department of Neurology (G.D.), Royal Hallamshire Hospital, Sheffield, UK; and Media Lab (M.A.L.), Massachusetts Institute of Technology, Cambridge, MA
| | - Claudio Ruffmann
- From the Oxford Parkinson's Disease Centre (OPDC) (S.A., F.B., C.L., T.R.B., M.R., C.R., J.C.K., J.R., A.L., R.W.-M, M.T.H.), University of Oxford, UK; Engineering and Applied Science (S.A., M.A.L.), Aston University, Birmingham, UK; Somerville College (S.A.), University of Oxford, UK; Nuffield Department of Clinical Neurosciences (F.B., C.L., T.R.B., M.A.L., M.T.H.), University of Oxford, UK; Population Health Sciences (M.A.L.), University of Bristol, UK; andDepartment of Computer Science (A.Z.), Johns Hopkins University, Baltimore; Department of Neurology and Neurophysiology (Z.Z., G.L., M.T.H.), Oxford University Hospitals NHS Trust, UK; Respiratory Support and Sleep Centre (T.Q.), Papworth Hospital, Cambridge, UK; Department of Neurology (G.D.), Royal Hallamshire Hospital, Sheffield, UK; and Media Lab (M.A.L.), Massachusetts Institute of Technology, Cambridge, MA
| | - Johannes C Klein
- From the Oxford Parkinson's Disease Centre (OPDC) (S.A., F.B., C.L., T.R.B., M.R., C.R., J.C.K., J.R., A.L., R.W.-M, M.T.H.), University of Oxford, UK; Engineering and Applied Science (S.A., M.A.L.), Aston University, Birmingham, UK; Somerville College (S.A.), University of Oxford, UK; Nuffield Department of Clinical Neurosciences (F.B., C.L., T.R.B., M.A.L., M.T.H.), University of Oxford, UK; Population Health Sciences (M.A.L.), University of Bristol, UK; andDepartment of Computer Science (A.Z.), Johns Hopkins University, Baltimore; Department of Neurology and Neurophysiology (Z.Z., G.L., M.T.H.), Oxford University Hospitals NHS Trust, UK; Respiratory Support and Sleep Centre (T.Q.), Papworth Hospital, Cambridge, UK; Department of Neurology (G.D.), Royal Hallamshire Hospital, Sheffield, UK; and Media Lab (M.A.L.), Massachusetts Institute of Technology, Cambridge, MA
| | - Jane Rumbold
- From the Oxford Parkinson's Disease Centre (OPDC) (S.A., F.B., C.L., T.R.B., M.R., C.R., J.C.K., J.R., A.L., R.W.-M, M.T.H.), University of Oxford, UK; Engineering and Applied Science (S.A., M.A.L.), Aston University, Birmingham, UK; Somerville College (S.A.), University of Oxford, UK; Nuffield Department of Clinical Neurosciences (F.B., C.L., T.R.B., M.A.L., M.T.H.), University of Oxford, UK; Population Health Sciences (M.A.L.), University of Bristol, UK; andDepartment of Computer Science (A.Z.), Johns Hopkins University, Baltimore; Department of Neurology and Neurophysiology (Z.Z., G.L., M.T.H.), Oxford University Hospitals NHS Trust, UK; Respiratory Support and Sleep Centre (T.Q.), Papworth Hospital, Cambridge, UK; Department of Neurology (G.D.), Royal Hallamshire Hospital, Sheffield, UK; and Media Lab (M.A.L.), Massachusetts Institute of Technology, Cambridge, MA
| | - Amandine Louvel
- From the Oxford Parkinson's Disease Centre (OPDC) (S.A., F.B., C.L., T.R.B., M.R., C.R., J.C.K., J.R., A.L., R.W.-M, M.T.H.), University of Oxford, UK; Engineering and Applied Science (S.A., M.A.L.), Aston University, Birmingham, UK; Somerville College (S.A.), University of Oxford, UK; Nuffield Department of Clinical Neurosciences (F.B., C.L., T.R.B., M.A.L., M.T.H.), University of Oxford, UK; Population Health Sciences (M.A.L.), University of Bristol, UK; andDepartment of Computer Science (A.Z.), Johns Hopkins University, Baltimore; Department of Neurology and Neurophysiology (Z.Z., G.L., M.T.H.), Oxford University Hospitals NHS Trust, UK; Respiratory Support and Sleep Centre (T.Q.), Papworth Hospital, Cambridge, UK; Department of Neurology (G.D.), Royal Hallamshire Hospital, Sheffield, UK; and Media Lab (M.A.L.), Massachusetts Institute of Technology, Cambridge, MA
| | - Zenobia Zaiwalla
- From the Oxford Parkinson's Disease Centre (OPDC) (S.A., F.B., C.L., T.R.B., M.R., C.R., J.C.K., J.R., A.L., R.W.-M, M.T.H.), University of Oxford, UK; Engineering and Applied Science (S.A., M.A.L.), Aston University, Birmingham, UK; Somerville College (S.A.), University of Oxford, UK; Nuffield Department of Clinical Neurosciences (F.B., C.L., T.R.B., M.A.L., M.T.H.), University of Oxford, UK; Population Health Sciences (M.A.L.), University of Bristol, UK; andDepartment of Computer Science (A.Z.), Johns Hopkins University, Baltimore; Department of Neurology and Neurophysiology (Z.Z., G.L., M.T.H.), Oxford University Hospitals NHS Trust, UK; Respiratory Support and Sleep Centre (T.Q.), Papworth Hospital, Cambridge, UK; Department of Neurology (G.D.), Royal Hallamshire Hospital, Sheffield, UK; and Media Lab (M.A.L.), Massachusetts Institute of Technology, Cambridge, MA
| | - Graham Lennox
- From the Oxford Parkinson's Disease Centre (OPDC) (S.A., F.B., C.L., T.R.B., M.R., C.R., J.C.K., J.R., A.L., R.W.-M, M.T.H.), University of Oxford, UK; Engineering and Applied Science (S.A., M.A.L.), Aston University, Birmingham, UK; Somerville College (S.A.), University of Oxford, UK; Nuffield Department of Clinical Neurosciences (F.B., C.L., T.R.B., M.A.L., M.T.H.), University of Oxford, UK; Population Health Sciences (M.A.L.), University of Bristol, UK; andDepartment of Computer Science (A.Z.), Johns Hopkins University, Baltimore; Department of Neurology and Neurophysiology (Z.Z., G.L., M.T.H.), Oxford University Hospitals NHS Trust, UK; Respiratory Support and Sleep Centre (T.Q.), Papworth Hospital, Cambridge, UK; Department of Neurology (G.D.), Royal Hallamshire Hospital, Sheffield, UK; and Media Lab (M.A.L.), Massachusetts Institute of Technology, Cambridge, MA
| | - Tim Quinnell
- From the Oxford Parkinson's Disease Centre (OPDC) (S.A., F.B., C.L., T.R.B., M.R., C.R., J.C.K., J.R., A.L., R.W.-M, M.T.H.), University of Oxford, UK; Engineering and Applied Science (S.A., M.A.L.), Aston University, Birmingham, UK; Somerville College (S.A.), University of Oxford, UK; Nuffield Department of Clinical Neurosciences (F.B., C.L., T.R.B., M.A.L., M.T.H.), University of Oxford, UK; Population Health Sciences (M.A.L.), University of Bristol, UK; andDepartment of Computer Science (A.Z.), Johns Hopkins University, Baltimore; Department of Neurology and Neurophysiology (Z.Z., G.L., M.T.H.), Oxford University Hospitals NHS Trust, UK; Respiratory Support and Sleep Centre (T.Q.), Papworth Hospital, Cambridge, UK; Department of Neurology (G.D.), Royal Hallamshire Hospital, Sheffield, UK; and Media Lab (M.A.L.), Massachusetts Institute of Technology, Cambridge, MA
| | - Gary Dennis
- From the Oxford Parkinson's Disease Centre (OPDC) (S.A., F.B., C.L., T.R.B., M.R., C.R., J.C.K., J.R., A.L., R.W.-M, M.T.H.), University of Oxford, UK; Engineering and Applied Science (S.A., M.A.L.), Aston University, Birmingham, UK; Somerville College (S.A.), University of Oxford, UK; Nuffield Department of Clinical Neurosciences (F.B., C.L., T.R.B., M.A.L., M.T.H.), University of Oxford, UK; Population Health Sciences (M.A.L.), University of Bristol, UK; andDepartment of Computer Science (A.Z.), Johns Hopkins University, Baltimore; Department of Neurology and Neurophysiology (Z.Z., G.L., M.T.H.), Oxford University Hospitals NHS Trust, UK; Respiratory Support and Sleep Centre (T.Q.), Papworth Hospital, Cambridge, UK; Department of Neurology (G.D.), Royal Hallamshire Hospital, Sheffield, UK; and Media Lab (M.A.L.), Massachusetts Institute of Technology, Cambridge, MA
| | - Richard Wade-Martins
- From the Oxford Parkinson's Disease Centre (OPDC) (S.A., F.B., C.L., T.R.B., M.R., C.R., J.C.K., J.R., A.L., R.W.-M, M.T.H.), University of Oxford, UK; Engineering and Applied Science (S.A., M.A.L.), Aston University, Birmingham, UK; Somerville College (S.A.), University of Oxford, UK; Nuffield Department of Clinical Neurosciences (F.B., C.L., T.R.B., M.A.L., M.T.H.), University of Oxford, UK; Population Health Sciences (M.A.L.), University of Bristol, UK; andDepartment of Computer Science (A.Z.), Johns Hopkins University, Baltimore; Department of Neurology and Neurophysiology (Z.Z., G.L., M.T.H.), Oxford University Hospitals NHS Trust, UK; Respiratory Support and Sleep Centre (T.Q.), Papworth Hospital, Cambridge, UK; Department of Neurology (G.D.), Royal Hallamshire Hospital, Sheffield, UK; and Media Lab (M.A.L.), Massachusetts Institute of Technology, Cambridge, MA
| | - Yoav Ben-Shlomo
- From the Oxford Parkinson's Disease Centre (OPDC) (S.A., F.B., C.L., T.R.B., M.R., C.R., J.C.K., J.R., A.L., R.W.-M, M.T.H.), University of Oxford, UK; Engineering and Applied Science (S.A., M.A.L.), Aston University, Birmingham, UK; Somerville College (S.A.), University of Oxford, UK; Nuffield Department of Clinical Neurosciences (F.B., C.L., T.R.B., M.A.L., M.T.H.), University of Oxford, UK; Population Health Sciences (M.A.L.), University of Bristol, UK; andDepartment of Computer Science (A.Z.), Johns Hopkins University, Baltimore; Department of Neurology and Neurophysiology (Z.Z., G.L., M.T.H.), Oxford University Hospitals NHS Trust, UK; Respiratory Support and Sleep Centre (T.Q.), Papworth Hospital, Cambridge, UK; Department of Neurology (G.D.), Royal Hallamshire Hospital, Sheffield, UK; and Media Lab (M.A.L.), Massachusetts Institute of Technology, Cambridge, MA
| | - Max A Little
- From the Oxford Parkinson's Disease Centre (OPDC) (S.A., F.B., C.L., T.R.B., M.R., C.R., J.C.K., J.R., A.L., R.W.-M, M.T.H.), University of Oxford, UK; Engineering and Applied Science (S.A., M.A.L.), Aston University, Birmingham, UK; Somerville College (S.A.), University of Oxford, UK; Nuffield Department of Clinical Neurosciences (F.B., C.L., T.R.B., M.A.L., M.T.H.), University of Oxford, UK; Population Health Sciences (M.A.L.), University of Bristol, UK; andDepartment of Computer Science (A.Z.), Johns Hopkins University, Baltimore; Department of Neurology and Neurophysiology (Z.Z., G.L., M.T.H.), Oxford University Hospitals NHS Trust, UK; Respiratory Support and Sleep Centre (T.Q.), Papworth Hospital, Cambridge, UK; Department of Neurology (G.D.), Royal Hallamshire Hospital, Sheffield, UK; and Media Lab (M.A.L.), Massachusetts Institute of Technology, Cambridge, MA
| | - Michele T Hu
- From the Oxford Parkinson's Disease Centre (OPDC) (S.A., F.B., C.L., T.R.B., M.R., C.R., J.C.K., J.R., A.L., R.W.-M, M.T.H.), University of Oxford, UK; Engineering and Applied Science (S.A., M.A.L.), Aston University, Birmingham, UK; Somerville College (S.A.), University of Oxford, UK; Nuffield Department of Clinical Neurosciences (F.B., C.L., T.R.B., M.A.L., M.T.H.), University of Oxford, UK; Population Health Sciences (M.A.L.), University of Bristol, UK; andDepartment of Computer Science (A.Z.), Johns Hopkins University, Baltimore; Department of Neurology and Neurophysiology (Z.Z., G.L., M.T.H.), Oxford University Hospitals NHS Trust, UK; Respiratory Support and Sleep Centre (T.Q.), Papworth Hospital, Cambridge, UK; Department of Neurology (G.D.), Royal Hallamshire Hospital, Sheffield, UK; and Media Lab (M.A.L.), Massachusetts Institute of Technology, Cambridge, MA.
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Klein JC, Rolinski M, Griffanti L, Szewczyk-Krolikowski K, Baig F, Ruffmann C, Groves AR, Menke RAL, Hu MT, Mackay C. Cortical structural involvement and cognitive dysfunction in early Parkinson's disease. NMR Biomed 2018; 31:e3900. [PMID: 29436039 DOI: 10.1002/nbm.3900] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [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: 05/08/2017] [Revised: 12/13/2017] [Accepted: 01/03/2018] [Indexed: 06/08/2023]
Abstract
Magnetic resonance imaging (MRI) studies in early Parkinson's disease (PD) have shown promise in the detection of disease-related brain changes in the white and deep grey matter. We set out to establish whether intrinsic cortical involvement in early PD can be detected with quantitative MRI. We collected a rich, multi-modal dataset, including diffusion MRI, T1 relaxometry and cortical morphometry, in 20 patients with early PD (disease duration, 1.9 ± 0.97 years, Hoehn & Yahr 1-2) and in 19 matched controls. The cortex was reconstructed using FreeSurfer. Data analysis employed linked independent component analysis (ICA), a novel data-driven technique that allows for data fusion and extraction of multi-modal components before further analysis. For comparison, we performed standard uni-modal analysis with a general linear model (GLM). Linked ICA detected multi-modal cortical changes in early PD (p = 0.015). These comprised fractional anisotropy reduction in dorsolateral prefrontal, cingulate and premotor cortex and the superior parietal lobule, mean diffusivity increase in the mesolimbic, somatosensory and superior parietal cortex, sparse diffusivity decrease in lateral parietal and right prefrontal cortex, and sparse changes to the cortex area. In PD, the amount of cortical dysintegrity correlated with diminished cognitive performance. Importantly, uni-modal analysis detected no significant group difference on any imaging modality. We detected microstructural cortical pathology in early PD using a data-driven, multi-modal approach. This pathology is correlated with diminished cognitive performance. Our results indicate that early degenerative processes leave an MRI signature in the cortex of patients with early PD. The cortical imaging findings are behaviourally meaningful and provide a link between cognitive status and microstructural cortical pathology in patients with early PD.
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Affiliation(s)
- J C Klein
- Oxford Parkinson's Disease Centre, Nuffield Department of Clinical Neurosciences, Division of Clinical Neurology, University of Oxford, Oxford, UK
- Wellcome Centre for Integrative Neuroimaging (WIN), FMRIB Centre, University of Oxford, Oxford, UK
- Department of Clinical Neurology, John Radcliffe Hospital, Oxford, UK
| | - M Rolinski
- Oxford Parkinson's Disease Centre, Nuffield Department of Clinical Neurosciences, Division of Clinical Neurology, University of Oxford, Oxford, UK
- Department of Clinical Neurology, John Radcliffe Hospital, Oxford, UK
| | - L Griffanti
- Oxford Parkinson's Disease Centre, Nuffield Department of Clinical Neurosciences, Division of Clinical Neurology, University of Oxford, Oxford, UK
- Wellcome Centre for Integrative Neuroimaging (WIN), FMRIB Centre, University of Oxford, Oxford, UK
| | - K Szewczyk-Krolikowski
- Oxford Parkinson's Disease Centre, Nuffield Department of Clinical Neurosciences, Division of Clinical Neurology, University of Oxford, Oxford, UK
| | - F Baig
- Oxford Parkinson's Disease Centre, Nuffield Department of Clinical Neurosciences, Division of Clinical Neurology, University of Oxford, Oxford, UK
- Department of Clinical Neurology, John Radcliffe Hospital, Oxford, UK
| | - C Ruffmann
- Oxford Parkinson's Disease Centre, Nuffield Department of Clinical Neurosciences, Division of Clinical Neurology, University of Oxford, Oxford, UK
- Department of Clinical Neurology, John Radcliffe Hospital, Oxford, UK
| | - A R Groves
- Wellcome Centre for Integrative Neuroimaging (WIN), FMRIB Centre, University of Oxford, Oxford, UK
| | - R A L Menke
- Oxford Parkinson's Disease Centre, Nuffield Department of Clinical Neurosciences, Division of Clinical Neurology, University of Oxford, Oxford, UK
- Wellcome Centre for Integrative Neuroimaging (WIN), FMRIB Centre, University of Oxford, Oxford, UK
| | - M T Hu
- Oxford Parkinson's Disease Centre, Nuffield Department of Clinical Neurosciences, Division of Clinical Neurology, University of Oxford, Oxford, UK
- Department of Clinical Neurology, John Radcliffe Hospital, Oxford, UK
| | - C Mackay
- Oxford Parkinson's Disease Centre, Nuffield Department of Clinical Neurosciences, Division of Clinical Neurology, University of Oxford, Oxford, UK
- Department of Psychiatry, University of Oxford, Oxford, UK
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31
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Barber TR, Lawton M, Rolinski M, Evetts S, Baig F, Ruffmann C, Gornall A, Klein JC, Lo C, Dennis G, Bandmann O, Quinnell T, Zaiwalla Z, Ben-Shlomo Y, Hu MTM. Prodromal Parkinsonism and Neurodegenerative Risk Stratification in REM Sleep Behavior Disorder. Sleep 2017; 40:3796343. [PMID: 28472425 PMCID: PMC5806544 DOI: 10.1093/sleep/zsx071] [Citation(s) in RCA: 111] [Impact Index Per Article: 15.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Objectives Rapid eye movement (REM) sleep behavior disorder (RBD) is the most specific marker of prodromal alpha-synucleinopathies. We sought to delineate the baseline clinical characteristics of RBD and evaluate risk stratification models. Methods Clinical assessments were performed in 171 RBD, 296 control, and 119 untreated Parkinson's (PD) participants. Putative risk measures were assessed as predictors of prodromal neurodegeneration, and Movement Disorders Society (MDS) criteria for prodromal PD were applied. Participants were screened for common leucine-rich repeat kinase 2 (LRRK2)/glucocerebrosidase gene (GBA) gene mutations. Results Compared to controls, participants with RBD had higher rates of solvent exposure, head injury, smoking, obesity, and antidepressant use. GBA mutations were more common in RBD, but no LRRK2 mutations were found. RBD participants performed significantly worse than controls on Unified Parkinson's Disease Rating Scale (UPDRS)-III, timed "get-up-and-go", Flamingo test, Sniffin Sticks, and cognitive tests and had worse measures of constipation, quality of life (QOL), and orthostatic hypotension. For all these measures except UPDRS-III, RBD and PD participants were equally impaired. Depression, anxiety, and apathy were worse in RBD compared to PD participants. Stratification of people with RBD according to antidepressant use, obesity, and age altered the odds ratio (OR) of hyposmia compared to controls from 3.4 to 45.5. 74% (95% confidence interval [CI] 66%, 80%) of RBD participants met the MDS criteria for probable prodromal Parkinson's compared to 0.3% (95% CI 0.009%, 2%) of controls. Conclusions RBD are impaired across a range of clinical measures consistent with prodromal PD and suggestive of a more severe nonmotor subtype. Clinical risk stratification has the potential to select higher risk patients for neuroprotective interventions.
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Affiliation(s)
- Thomas R Barber
- Oxford Parkinson's Disease Centre (OPDC), University of Oxford, UK.,Nuffield Department of Clinical Neurosciences, University of Oxford, UK
| | - Michael Lawton
- School of Social and Community Medicine, University of Bristol, UK
| | - Michal Rolinski
- Oxford Parkinson's Disease Centre (OPDC), University of Oxford, UK.,Nuffield Department of Clinical Neurosciences, University of Oxford, UK.,Institute of Clinical Neurosciences, University of Bristol, UK
| | - Samuel Evetts
- Oxford Parkinson's Disease Centre (OPDC), University of Oxford, UK.,Nuffield Department of Clinical Neurosciences, University of Oxford, UK
| | - Fahd Baig
- Oxford Parkinson's Disease Centre (OPDC), University of Oxford, UK.,Nuffield Department of Clinical Neurosciences, University of Oxford, UK
| | - Claudio Ruffmann
- Oxford Parkinson's Disease Centre (OPDC), University of Oxford, UK.,Nuffield Department of Clinical Neurosciences, University of Oxford, UK
| | - Aimie Gornall
- Oxford Parkinson's Disease Centre (OPDC), University of Oxford, UK.,Department of Psychiatry, University of Oxford, UK
| | - Johannes C Klein
- Oxford Parkinson's Disease Centre (OPDC), University of Oxford, UK.,Nuffield Department of Clinical Neurosciences, University of Oxford, UK
| | - Christine Lo
- Sheffield Institute of Translational Neuroscience, University of Sheffield, UK.,Department of Neurology, Sheffield Teaching Hospitals, Sheffield, UK
| | - Gary Dennis
- Department of Neurology, Sheffield Teaching Hospitals, Sheffield, UK
| | - Oliver Bandmann
- Sheffield Institute of Translational Neuroscience, University of Sheffield, UK.,Department of Neurology, Sheffield Teaching Hospitals, Sheffield, UK
| | - Timothy Quinnell
- Respiratory Support and Sleep Centre, Papworth Hospital, Cambridge, UK
| | - Zenobia Zaiwalla
- Department of Clinical Neurophysiology, John Radcliffe Hospital, Oxford, UK
| | - Yoav Ben-Shlomo
- School of Social and Community Medicine, University of Bristol, UK
| | - Michele T M Hu
- Oxford Parkinson's Disease Centre (OPDC), University of Oxford, UK.,Nuffield Department of Clinical Neurosciences, University of Oxford, UK
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Heise V, Firouzian A, Thomas DL, Newbould RD, Aigbirhio FI, Williams GB, Lucatelli C, Macnaught G, Waldman A, Hallett W, Rabiner EA, Marsden P, Charles‐Edwards G, Matthews J, Parkes L, Brooks DJ, Firbank MJ, Klein JC, Gunn RN, Mackay CE. [IC‐P‐088]: DEEP AND FREQUENT PHENOTYPING STUDY: PET AND MR IMAGING PROTOCOL. Alzheimers Dement 2017. [DOI: 10.1016/j.jalz.2017.06.2361] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Affiliation(s)
| | - Azadeh Firouzian
- IMANOVA Ltd.LondonUnited Kingdom
- Imperial College LondonLondonUnited Kingdom
| | - David L. Thomas
- Neuroradiological Academic Unit, Department of Brain Repair and RehabilitationUCL Institute of NeurologyLondonUnited Kingdom
| | | | | | | | | | | | | | - William Hallett
- IMANOVA Ltd.LondonUnited Kingdom
- Imperial College LondonLondonUnited Kingdom
| | - Eugenii A. Rabiner
- IMANOVA Ltd.LondonUnited Kingdom
- King's College LondonLondonUnited Kingdom
| | | | | | | | - Laura Parkes
- University of ManchesterManchesterUnited Kingdom
| | | | | | | | - Roger N. Gunn
- IMANOVA Ltd.LondonUnited Kingdom
- Imperial College LondonLondonUnited Kingdom
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33
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Heise V, Firouzian A, Thomas DL, Newbould RD, Aigbirhio FI, Williams GB, Lucatelli C, Macnaught G, Waldman A, Hallett W, Rabiner EA, Marsden P, Charles‐Edwards G, Matthews J, Parkes L, Brooks DJ, Firbank MJ, Klein JC, Gunn RN, Mackay CE. [P4–265]: DEEP AND FREQUENT PHENOTYPING STUDY: PET AND MR IMAGING PROTOCOL. Alzheimers Dement 2017. [DOI: 10.1016/j.jalz.2017.06.2134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Affiliation(s)
| | - Azadeh Firouzian
- IMANOVA Ltd.LondonUnited Kingdom
- Imperial College LondonLondonUnited Kingdom
| | - David L. Thomas
- Neuroradiological Academic Unit, Department of Brain Repair and RehabilitationUCL Institute of NeurologyLondonUnited Kingdom
| | | | | | | | | | | | | | - William Hallett
- IMANOVA Ltd.LondonUnited Kingdom
- Imperial College LondonLondonUnited Kingdom
| | - Eugenii A. Rabiner
- IMANOVA Ltd.LondonUnited Kingdom
- King's College LondonLondonUnited Kingdom
| | | | | | | | - Laura Parkes
- University of ManchesterManchesterUnited Kingdom
| | | | | | | | - Roger N. Gunn
- IMANOVA Ltd.LondonUnited Kingdom
- Imperial College LondonLondonUnited Kingdom
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Seiler A, Deichmann R, Nöth U, Pfeilschifter W, Berkefeld J, Singer OC, Klein JC, Wagner M. Oxygenation-Sensitive Magnetic Resonance Imaging in Acute Ischemic Stroke Using T2'/R2' Mapping: Influence of Relative Cerebral Blood Volume. Stroke 2017; 48:1671-1674. [PMID: 28455319 DOI: 10.1161/strokeaha.117.017086] [Citation(s) in RCA: 11] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2016] [Revised: 02/16/2017] [Accepted: 03/08/2017] [Indexed: 11/16/2022]
Abstract
BACKGROUND AND PURPOSE Quantitative T2'/R2' mapping detect locally increased concentrations of deoxygenated hemoglobin-causing a decrease of T2' and increase of R2'-and might reflect increased cerebral oxygen extraction fraction. Because increases of (relative) cerebral blood volume (rCBV) may influence T2' and R2' through accumulation of deoxygenated hemoglobin, we aimed to investigate the impact of rCBV on T2'/R2' in patients with ischemic stroke. METHODS Data from patients with acute internal carotid artery and middle cerebral artery occlusion were analyzed. T2', R2', and rCBV were measured within the ischemic core, slightly and severely hypoperfused areas, and their relationship was examined. RESULTS A strong negative correlation with rCBV was found for R2' (r=-0.544; P=0.002), and T2' correlated positively with rCBV (r=0.546; P=0.001) in time-to-peak-delayed areas. T2'/R2' within hypoperfused tissue remained unchanged at normal or elevated rCBV levels. CONCLUSIONS T2' decrease/R2' increase within hypoperfused areas in ischemic stroke is not caused by local elevations of rCBV but most probably only by increased cerebral oxygen extraction fraction. However, considering rCBV is crucial to assess extent of oxygen extraction fraction changes by means of T2'/R2'.
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Affiliation(s)
- Alexander Seiler
- From the Department of Neurology (A.S., W.P., O.C.S.), Brain Imaging Center and Institute of Neuroradiology (R.D., U.N.), and Institute of Neuroradiology (J.B., M.W.), Goethe University Frankfurt, Germany; Nuffield Department of Clinical Neurosciences, Oxford University, United Kingdom (J.C.K.); and Department of Neurology, Oxford University Hospitals NHS Trust, United Kingdom (J.C.K.).
| | - Ralf Deichmann
- From the Department of Neurology (A.S., W.P., O.C.S.), Brain Imaging Center and Institute of Neuroradiology (R.D., U.N.), and Institute of Neuroradiology (J.B., M.W.), Goethe University Frankfurt, Germany; Nuffield Department of Clinical Neurosciences, Oxford University, United Kingdom (J.C.K.); and Department of Neurology, Oxford University Hospitals NHS Trust, United Kingdom (J.C.K.)
| | - Ulrike Nöth
- From the Department of Neurology (A.S., W.P., O.C.S.), Brain Imaging Center and Institute of Neuroradiology (R.D., U.N.), and Institute of Neuroradiology (J.B., M.W.), Goethe University Frankfurt, Germany; Nuffield Department of Clinical Neurosciences, Oxford University, United Kingdom (J.C.K.); and Department of Neurology, Oxford University Hospitals NHS Trust, United Kingdom (J.C.K.)
| | - Waltraud Pfeilschifter
- From the Department of Neurology (A.S., W.P., O.C.S.), Brain Imaging Center and Institute of Neuroradiology (R.D., U.N.), and Institute of Neuroradiology (J.B., M.W.), Goethe University Frankfurt, Germany; Nuffield Department of Clinical Neurosciences, Oxford University, United Kingdom (J.C.K.); and Department of Neurology, Oxford University Hospitals NHS Trust, United Kingdom (J.C.K.)
| | - Joachim Berkefeld
- From the Department of Neurology (A.S., W.P., O.C.S.), Brain Imaging Center and Institute of Neuroradiology (R.D., U.N.), and Institute of Neuroradiology (J.B., M.W.), Goethe University Frankfurt, Germany; Nuffield Department of Clinical Neurosciences, Oxford University, United Kingdom (J.C.K.); and Department of Neurology, Oxford University Hospitals NHS Trust, United Kingdom (J.C.K.)
| | - Oliver C Singer
- From the Department of Neurology (A.S., W.P., O.C.S.), Brain Imaging Center and Institute of Neuroradiology (R.D., U.N.), and Institute of Neuroradiology (J.B., M.W.), Goethe University Frankfurt, Germany; Nuffield Department of Clinical Neurosciences, Oxford University, United Kingdom (J.C.K.); and Department of Neurology, Oxford University Hospitals NHS Trust, United Kingdom (J.C.K.)
| | - Johannes C Klein
- From the Department of Neurology (A.S., W.P., O.C.S.), Brain Imaging Center and Institute of Neuroradiology (R.D., U.N.), and Institute of Neuroradiology (J.B., M.W.), Goethe University Frankfurt, Germany; Nuffield Department of Clinical Neurosciences, Oxford University, United Kingdom (J.C.K.); and Department of Neurology, Oxford University Hospitals NHS Trust, United Kingdom (J.C.K.)
| | - Marlies Wagner
- From the Department of Neurology (A.S., W.P., O.C.S.), Brain Imaging Center and Institute of Neuroradiology (R.D., U.N.), and Institute of Neuroradiology (J.B., M.W.), Goethe University Frankfurt, Germany; Nuffield Department of Clinical Neurosciences, Oxford University, United Kingdom (J.C.K.); and Department of Neurology, Oxford University Hospitals NHS Trust, United Kingdom (J.C.K.)
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Abstract
The process of neurodegeneration in Parkinson's disease begins long before the onset of clinical motor symptoms, resulting in substantial cell loss by the time a diagnosis can be made. The period between the onset of neurodegeneration and the development of motoric disease would be the ideal time to intervene with disease modifying therapies. This pre-motor phase can last many years, but the lack of a specific clinical phenotype means that objective biomarkers are needed to reliably detect prodromal disease. In recent years, recognition that patients with REM sleep behaviour disorder (RBD) are at particularly high risk of future parkinsonism has enabled the development of large prodromal cohorts in which to investigate novel biomarkers, and neuroimaging has generated some of the most promising results to date. Here we review investigations undertaken in RBD and other pre-clinical cohorts, including modalities that are well established in clinical Parkinson's as well as novel imaging methods. Techniques such as high resolution MRI of the substantia nigra and functional imaging of Parkinsonian brain networks have great potential to facilitate early diagnosis. Further longitudinal studies will establish their true value in quantifying prodromal neurodegeneration and predicting future Parkinson's.
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Affiliation(s)
- Thomas R Barber
- Oxford Parkinson's Disease Centre (OPDC), University of Oxford, UK; Nuffield Department of Clinical Neurosciences, University of Oxford, UK.
| | - Johannes C Klein
- Oxford Parkinson's Disease Centre (OPDC), University of Oxford, UK; Nuffield Department of Clinical Neurosciences, University of Oxford, UK
| | - Clare E Mackay
- Oxford Parkinson's Disease Centre (OPDC), University of Oxford, UK; Department of Psychiatry, University of Oxford, UK; Oxford Centre for Human Brain Activity (OHBA), University of Oxford, UK
| | - Michele T M Hu
- Oxford Parkinson's Disease Centre (OPDC), University of Oxford, UK; Nuffield Department of Clinical Neurosciences, University of Oxford, UK.
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36
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Gracien RM, Reitz SC, Hof SM, Fleischer V, Droby A, Wahl M, Steinmetz H, Groppa S, Deichmann R, Klein JC. Longitudinal quantitative MRI assessment of cortical damage in multiple sclerosis: A pilot study. J Magn Reson Imaging 2017; 46:1485-1490. [PMID: 28240801 DOI: 10.1002/jmri.25685] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2016] [Accepted: 02/06/2017] [Indexed: 12/15/2022] Open
Abstract
PURPOSE Quantitative MRI (qMRI) allows assessing cortical pathology in multiple sclerosis (MS) on a microstructural level, where cortical damage has been shown to prolong T1 -relaxation time and increase proton density (PD) compared to controls. However, the evolution of these changes in MS over time has not been investigated so far. In this pilot study we used an advanced method for the longitudinal assessment of cortical tissue change in MS patients with qMRI in comparison to cortical atrophy, as derived from conventional MRI. MATERIALS AND METHODS Twelve patients with relapsing-remitting MS underwent 3T T1 /PD-mapping at two timepoints with a mean interval of 12 months. The respective cortical T1 /PD-values were extracted from the middle of the cortical layer and the cortical thickness was measured for surface-based identification of clusters with increasing/decreasing values. RESULTS Statistical analysis showed clusters with increasing PD- and T1 -values over time (annualized rate for T1 /PD increase in these clusters: 3.4 ± 2.56% for T1 , P = 0.0007; 2.3 ± 2.59% for PD, P = 0.01). Changes are heterogeneous across the cortex and different patterns of longitudinal PD and T1 increase emerged. Analysis of the cortical thickness yielded only one small cluster indicating a decrease of cortical thickness. CONCLUSION Changes of cortical tissue composition in MS seem to be reflected by a spatially inhomogeneous, multifocal increase of the PD values, indicating replacement of neural tissue by water, and of the T1 -relaxation time, a surrogate of demyelination, axonal loss, and gliosis. qMRI changes were more prominent than cortical atrophy, showing the potential of qMRI techniques to quantify microstructural alterations that remain undetected by conventional MRI. LEVEL OF EVIDENCE 1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1485-1490.
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Affiliation(s)
- René-Maxime Gracien
- Department of Neurology, Goethe University, Frankfurt/Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
| | - Sarah C Reitz
- Department of Neurology, Goethe University, Frankfurt/Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
| | - Stephanie-Michelle Hof
- Department of Neurology, Goethe University, Frankfurt/Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
| | - Vinzenz Fleischer
- Department of Neurology, Johannes Gutenberg University, Mainz, Germany.,Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), Johannes Gutenberg-University, Mainz, Germany
| | - Amgad Droby
- Department of Neurology, Johannes Gutenberg University, Mainz, Germany.,Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), Johannes Gutenberg-University, Mainz, Germany
| | - Mathias Wahl
- Department of Neurology, Goethe University, Frankfurt/Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
| | | | - Sergiu Groppa
- Department of Neurology, Johannes Gutenberg University, Mainz, Germany.,Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), Johannes Gutenberg-University, Mainz, Germany
| | - Ralf Deichmann
- Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
| | - Johannes C Klein
- Department of Neurology, Goethe University, Frankfurt/Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt/Main, Germany.,Nuffield Department of Clinical Neurosciences, University of Oxford, UK
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37
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Baig F, Lawton MA, Rolinski M, Ruffmann C, Klein JC, Nithi K, Okai D, Ben-Shlomo Y, Hu MTM. Personality and addictive behaviours in early Parkinson's disease and REM sleep behaviour disorder. Parkinsonism Relat Disord 2017; 37:72-78. [PMID: 28173973 PMCID: PMC5380654 DOI: 10.1016/j.parkreldis.2017.01.017] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/27/2016] [Revised: 11/17/2016] [Accepted: 01/27/2017] [Indexed: 11/30/2022]
Abstract
Introduction Changes in personality have been described in Parkinson's disease (PD), with suggestion that those with established disease tend to be risk averse with a disinclination for addictive behaviour. However, little is known about the earliest and prodromal stages. Personality and its relationship with addictive behaviours can help answer important questions about the mechanisms underlying PD and addiction. Methods 941 population-ascertained PD subjects within 3.5 years of diagnosis, 128 patients with rapid eye movement sleep behaviour disorder (RBD) and 292 control subjects were fully characterised for motor symptoms, non-motor symptoms and across the following 5 personality domains: 1) neuroticism 2) extraversion 3) conscientiousness 4) agreeableness 5) openness using the Big Five Inventory. Results Patients with early PD were more neurotic (p < 0.001), less extraverted (p < 0.001) and less open than controls (p < 0.001). RBD subjects showed the same pattern of being more neurotic (p < 0.001), less extraverted (p = 0.03) and less open (p < 0.001). PD patients had smoked less (p = 0.02) and drunk less alcohol (p = 0.03) than controls, but caffeine beverage consumption was similar. Being more extraverted (p < 0.001), more open (p < 0.001), and less neurotic (p < 0.001) predicted higher alcohol use, while being more extravert (p = 0.007) and less agreeable (p < 0.001) was associated with smoking more. Conclusions A similar pattern of personality changes is seen in PD and RBD compared to a control population. Personality characteristics were associated with addictive behaviours, suggestive of a common link, but the lower rates of addictive behaviours before and after the onset of motor symptoms in PD persisted after accounting for personality. A similar pattern of personality change is seen in PD and RBD compared to controls. The similar pattern found suggests these personality changes occur before motor symptoms. Extraversion, linked with reward sensitivity, is associated with smoking and alcohol. Lower addictive behaviours before and after motor symptoms are not explained by personality alone. This suggests that inherent factors other than simple dopamine dysfunction drive these differences.
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Affiliation(s)
- Fahd Baig
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, UK; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Michael A Lawton
- School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Michal Rolinski
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, UK; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Claudio Ruffmann
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, UK; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Johannes C Klein
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, UK; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Kannan Nithi
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, UK; Department of Neurology, Northampton General Hospital NHS Trust, Northampton, UK
| | - David Okai
- Psychological Medicine Service, Oxford University Hospitals NHS Trust, Oxford, UK
| | - Yoav Ben-Shlomo
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, UK; School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Michele T M Hu
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, UK; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
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38
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Nürnberger L, Gracien RM, Hok P, Hof SM, Rüb U, Steinmetz H, Hilker R, Klein JC, Deichmann R, Baudrexel S. Longitudinal changes of cortical microstructure in Parkinson's disease assessed with T1 relaxometry. Neuroimage Clin 2016; 13:405-414. [PMID: 28116233 PMCID: PMC5226811 DOI: 10.1016/j.nicl.2016.12.025] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [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: 09/13/2016] [Revised: 11/23/2016] [Accepted: 12/19/2016] [Indexed: 12/11/2022]
Abstract
BACKGROUND Histological evidence suggests that pathology in Parkinson's disease (PD) goes beyond nigrostriatal degeneration and also affects the cerebral cortex. Quantitative MRI (qMRI) techniques allow the assessment of changes in brain tissue composition. However, the development and pattern of disease-related cortical changes have not yet been demonstrated in PD with qMRI methods. The aim of this study was to investigate longitudinal cortical microstructural changes in PD with quantitative T1 relaxometry. METHODS 13 patients with mild to moderate PD and 20 matched healthy subjects underwent high resolution T1 mapping at two time points with an interval of 6.4 years (healthy subjects: 6.5 years). Data from two healthy subjects had to be excluded due to MRI artifacts. Surface-based analysis of cortical T1 values was performed with the FreeSurfer toolbox. RESULTS In PD patients, a widespread decrease of cortical T1 was detected during follow-up which affected large parts of the temporo-parietal and occipital cortices and also frontal areas. In contrast, age-related T1 decrease in the healthy control group was much less pronounced and only found in lateral frontal, parietal and temporal areas. Average cortical T1 values did not differ between the groups at baseline (p = 0.17), but were reduced in patients at follow-up (p = 0.0004). Annualized relative changes of cortical T1 were higher in patients vs. healthy subjects (patients: - 0.72 ± 0.64%/year; healthy subjects: - 0.17 ± 0.41%/year, p = 0.007). CONCLUSIONS In patients with PD, the development of widespread changes in cortical microstructure was observed as reflected by a reduction of cortical T1. The pattern of T1 decrease in PD patients exceeded the normal T1 decrease as found in physiological aging and showed considerable overlap with the pattern of cortical thinning demonstrated in previous PD studies. Therefore, cortical T1 might be a promising additional imaging marker for future longitudinal PD studies. The biological mechanisms underlying cortical T1 reductions remain to be further elucidated.
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Affiliation(s)
- Lucas Nürnberger
- Department of Neurology, Goethe University, Frankfurt/Main, Germany
- Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
| | - René-Maxime Gracien
- Department of Neurology, Goethe University, Frankfurt/Main, Germany
- Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
| | - Pavel Hok
- Department of Neurology, Goethe University, Frankfurt/Main, Germany
- Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
- Department of Neurology, Palacky University, Olomouc, Czech Republic
| | - Stephanie-Michelle Hof
- Department of Neurology, Goethe University, Frankfurt/Main, Germany
- Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
| | - Udo Rüb
- Dr. Senckenberg Chronomedical Institute, Goethe University, Frankfurt/Main, Germany
| | | | - Rüdiger Hilker
- Department of Neurology, Goethe University, Frankfurt/Main, Germany
- Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
| | - Johannes C. Klein
- Department of Neurology, Goethe University, Frankfurt/Main, Germany
- Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
- Nuffield Department of Clinical Neurosciences, University of Oxford, UK
| | - Ralf Deichmann
- Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
| | - Simon Baudrexel
- Department of Neurology, Goethe University, Frankfurt/Main, Germany
- Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
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39
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Gracien RM, Reitz SC, Wagner M, Mayer C, Volz S, Hof SM, Fleischer V, Droby A, Steinmetz H, Groppa S, Hattingen E, Klein JC, Deichmann R. Comparison of two quantitative proton density mapping methods in multiple sclerosis. MAGMA 2016; 30:75-83. [PMID: 27544270 DOI: 10.1007/s10334-016-0585-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/19/2016] [Revised: 08/06/2016] [Accepted: 08/09/2016] [Indexed: 01/11/2023]
Abstract
OBJECTIVE Proton density (PD) mapping requires correction for the receive profile (RP), which is frequently performed via bias-field correction. An alternative RP-mapping method utilizes a comparison of uncorrected PD-maps and a value ρ(T1) directly derived from T1-maps via the Fatouros equation. This may be problematic in multiple sclerosis (MS), if respective parameters are only valid for healthy brain tissue. We aimed to investigate whether the alternative method yields correct PD values in MS patients. MATERIALS/METHODS PD mapping was performed on 27 patients with relapsing-remitting MS and 27 healthy controls, utilizing both methods, yielding reference PD values (PDref, bias-field method) and PDalt (alternative method). RESULTS PDalt-values closely matched PDref, both for patients and controls. In contrast, ρ(T1) differed by up to 3 % from PDref, and the voxel-wise correlation between PDref and ρ(T1) was reduced in a patient subgroup with a higher degree of disability. Still, discrepancies between ρ(T1) and PDref were almost identical across different tissue types, thus translating into a scaling factor, which cancelled out during normalization to 100 % in CSF, yielding a good agreement between PDalt and PDref. CONCLUSION RP correction utilizing the auxiliary parameter ρ(T1) derived via the Fatouros equation provides accurate PD results in MS patients, in spite of discrepancies between ρ(T1) and actual PD values.
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Affiliation(s)
- René-Maxime Gracien
- Department of Neurology, Goethe University, Frankfurt/Main, Germany. .,Brain Imaging Center, Goethe University, Frankfurt/Main, Germany.
| | - Sarah C Reitz
- Department of Neurology, Goethe University, Frankfurt/Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
| | - Marlies Wagner
- Department of Neuroradiology, Goethe University, Frankfurt/Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
| | - Christoph Mayer
- Department of Neurology, Goethe University, Frankfurt/Main, Germany
| | - Steffen Volz
- Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
| | - Stephanie-Michelle Hof
- Department of Neurology, Goethe University, Frankfurt/Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
| | - Vinzenz Fleischer
- Department of Neurology, Johannes Gutenberg University, Mainz, Germany.,Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), Johannes Gutenberg University, Mainz, Germany
| | - Amgad Droby
- Department of Neurology, Johannes Gutenberg University, Mainz, Germany.,Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), Johannes Gutenberg University, Mainz, Germany
| | | | - Sergiu Groppa
- Department of Neurology, Johannes Gutenberg University, Mainz, Germany.,Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), Johannes Gutenberg University, Mainz, Germany
| | - Elke Hattingen
- Department of Neuroradiology, Goethe University, Frankfurt/Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
| | - Johannes C Klein
- Department of Neurology, Goethe University, Frankfurt/Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt/Main, Germany.,Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Ralf Deichmann
- Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
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40
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Gracien RM, Jurcoane A, Wagner M, Reitz SC, Mayer C, Volz S, Hof SM, Fleischer V, Droby A, Steinmetz H, Zipp F, Hattingen E, Deichmann R, Klein JC. The Relationship between Gray Matter Quantitative MRI and Disability in Secondary Progressive Multiple Sclerosis. PLoS One 2016; 11:e0161036. [PMID: 27513853 PMCID: PMC4981438 DOI: 10.1371/journal.pone.0161036] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [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: 01/11/2016] [Accepted: 07/28/2016] [Indexed: 11/18/2022] Open
Abstract
PURPOSE In secondary progressive Multiple Sclerosis (SPMS), global neurodegeneration as a driver of disability gains importance in comparison to focal inflammatory processes. However, clinical MRI does not visualize changes of tissue composition outside MS lesions. This quantitative MRI (qMRI) study investigated cortical and deep gray matter (GM) proton density (PD) values and T1 relaxation times to explore their potential to assess neuronal damage and its relationship to clinical disability in SPMS. MATERIALS AND METHODS 11 SPMS patients underwent quantitative T1 and PD mapping. Parameter values across the cerebral cortex and deep GM structures were compared with 11 healthy controls, and correlation with disability was investigated for regions exhibiting significant group differences. RESULTS PD was increased in the whole GM, cerebral cortex, thalamus, putamen and pallidum. PD correlated with disability in the whole GM, cerebral cortex, putamen and pallidum. T1 relaxation time was prolonged and correlated with disability in the whole GM and cerebral cortex. CONCLUSION Our study suggests that the qMRI parameters GM PD (which likely indicates replacement of neural tissue with water) and cortical T1 (which reflects cortical damage including and beyond increased water content) are promising qMRI candidates for the assessment of disease status, and are related to disability in SPMS.
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Affiliation(s)
- René-Maxime Gracien
- Department of Neurology, Goethe University, Frankfurt/Main, Germany
- Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
- * E-mail:
| | - Alina Jurcoane
- Department of Neuroradiology, Goethe University, Frankfurt/Main, Germany
- Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
| | - Marlies Wagner
- Department of Neuroradiology, Goethe University, Frankfurt/Main, Germany
- Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
| | - Sarah C. Reitz
- Department of Neurology, Goethe University, Frankfurt/Main, Germany
- Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
| | - Christoph Mayer
- Department of Neurology, Goethe University, Frankfurt/Main, Germany
| | - Steffen Volz
- Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
| | - Stephanie-Michelle Hof
- Department of Neurology, Goethe University, Frankfurt/Main, Germany
- Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
| | - Vinzenz Fleischer
- Department of Neurology, Johannes Gutenberg University, Mainz, Germany
- Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), Johannes Gutenberg-University, Mainz, Germany
| | - Amgad Droby
- Department of Neurology, Johannes Gutenberg University, Mainz, Germany
- Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), Johannes Gutenberg-University, Mainz, Germany
| | | | - Frauke Zipp
- Department of Neurology, Johannes Gutenberg University, Mainz, Germany
- Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), Johannes Gutenberg-University, Mainz, Germany
| | - Elke Hattingen
- Department of Neuroradiology, Goethe University, Frankfurt/Main, Germany
- Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
| | - Ralf Deichmann
- Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
| | - Johannes C. Klein
- Department of Neurology, Goethe University, Frankfurt/Main, Germany
- Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
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41
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Gracien RM, Nürnberger L, Hok P, Hof SM, Reitz SC, Rüb U, Steinmetz H, Hilker-Roggendorf R, Klein JC, Deichmann R, Baudrexel S. Evaluation of brain ageing: a quantitative longitudinal MRI study over 7 years. Eur Radiol 2016; 27:1568-1576. [PMID: 27379992 DOI: 10.1007/s00330-016-4485-1] [Citation(s) in RCA: 21] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2016] [Revised: 05/27/2016] [Accepted: 06/21/2016] [Indexed: 12/31/2022]
Abstract
OBJECTIVES T1 relaxometry is a promising tool for the assessment of microstructural changes during brain ageing. Previous cross-sectional studies demonstrated increasing T1 values in white and decreasing T1 values in grey matter over the lifetime. However, these findings have not yet been confirmed on the basis of a longitudinal study. In this longitudinal study over 7 years, T1 relaxometry was used to investigate the dynamics of age-related microstructural changes in older healthy subjects. METHODS T1 mapping was performed in 17 healthy subjects (range 51-77 years) at baseline and after 7 years. Advanced cortical and white matter segmentation was used to determine mean T1 values in the cortex and white matter. RESULTS The analysis revealed a decrease of mean cortical T1 values over 7 years, the rate of T1 reduction being more prominent in subjects with higher age. T1 decreases were predominantly localized in the lateral frontal, parietal and temporal cortex. In contrast, mean white matter T1 values remained stable. CONCLUSIONS T1 mapping is shown to be sensitive to age-related microstructural changes in healthy ageing subjects in a longitudinal setting. Data of a cohort in late adulthood and the senescence period demonstrate a decrease of cortical T1 values over 7 years, most likely reflecting decreasing water content and increased iron concentrations. KEY POINTS • T1 mapping is sensitive to age-related microstructural changes in a longitudinal setting. • T1 decreases were predominantly localized in the lateral frontal, parietal and temporal cortex. • The rate of T1 reduction was more prominent in subjects with higher age. • These changes most likely reflect decreasing cortical water and increasing iron concentrations.
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Affiliation(s)
- René-Maxime Gracien
- Department of Neurology, Goethe University, Frankfurt/Main, Germany. .,Brain Imaging Center, Goethe University, Frankfurt/Main, Germany.
| | - Lucas Nürnberger
- Department of Neurology, Goethe University, Frankfurt/Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
| | - Pavel Hok
- Department of Neurology, Goethe University, Frankfurt/Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt/Main, Germany.,Department of Neurology, Palacky University, Olomouc, Czech Republic
| | - Stephanie-Michelle Hof
- Department of Neurology, Goethe University, Frankfurt/Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
| | - Sarah C Reitz
- Department of Neurology, Goethe University, Frankfurt/Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
| | - Udo Rüb
- Dr. Senckenberg Chronomedical Institute, Goethe University, Frankfurt/Main, Germany
| | | | - Rüdiger Hilker-Roggendorf
- Department of Neurology, Goethe University, Frankfurt/Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
| | - Johannes C Klein
- Department of Neurology, Goethe University, Frankfurt/Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt/Main, Germany.,Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Ralf Deichmann
- Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
| | - Simon Baudrexel
- Department of Neurology, Goethe University, Frankfurt/Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
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42
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Rolinski M, Griffanti L, Piccini P, Roussakis AA, Szewczyk-Krolikowski K, Menke RA, Quinnell T, Zaiwalla Z, Klein JC, Mackay CE, Hu MTM. Basal ganglia dysfunction in idiopathic REM sleep behaviour disorder parallels that in early Parkinson's disease. Brain 2016; 139:2224-34. [PMID: 27297241 PMCID: PMC4958897 DOI: 10.1093/brain/aww124] [Citation(s) in RCA: 90] [Impact Index Per Article: 11.3] [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: 02/03/2016] [Accepted: 04/05/2016] [Indexed: 12/02/2022] Open
Abstract
See Postuma (doi:10.1093/aww131) for a scientific commentary on this article. Resting state functional magnetic resonance imaging dysfunction within the basal ganglia network is a feature of early Parkinson’s disease and may be a diagnostic biomarker of basal ganglia dysfunction. Currently, it is unclear whether these changes are present in so-called idiopathic rapid eye movement sleep behaviour disorder, a condition associated with a high rate of future conversion to Parkinson’s disease. In this study, we explore the utility of resting state functional magnetic resonance imaging to detect basal ganglia network dysfunction in rapid eye movement sleep behaviour disorder. We compare these data to a set of healthy control subjects, and to a set of patients with established early Parkinson’s disease. Furthermore, we explore the relationship between resting state functional magnetic resonance imaging basal ganglia network dysfunction and loss of dopaminergic neurons assessed with dopamine transporter single photon emission computerized tomography, and perform morphometric analyses to assess grey matter loss. Twenty-six patients with polysomnographically-established rapid eye movement sleep behaviour disorder, 48 patients with Parkinson’s disease and 23 healthy control subjects were included in this study. Resting state networks were isolated from task-free functional magnetic resonance imaging data using dual regression with a template derived from a separate cohort of 80 elderly healthy control participants. Resting state functional magnetic resonance imaging parameter estimates were extracted from the study subjects in the basal ganglia network. In addition, eight patients with rapid eye movement sleep behaviour disorder, 10 with Parkinson’s disease and 10 control subjects received 123I-ioflupane single photon emission computerized tomography. We tested for reduction of basal ganglia network connectivity, and for loss of tracer uptake in rapid eye movement sleep behaviour disorder and Parkinson’s disease relative to each other and to controls. Connectivity measures of basal ganglia network dysfunction differentiated both rapid eye movement sleep behaviour disorder and Parkinson’s disease from controls with high sensitivity (96%) and specificity (74% for rapid eye movement sleep behaviour disorder, 78% for Parkinson’s disease), indicating its potential as an indicator of early basal ganglia dysfunction. Rapid eye movement sleep behaviour disorder was indistinguishable from Parkinson’s disease on resting state functional magnetic resonance imaging despite obvious differences on dopamine transported single photon emission computerized tomography. Basal ganglia connectivity is a promising biomarker for the detection of early basal ganglia network dysfunction, and may help to identify patients at risk of developing Parkinson’s disease in the future. Future risk stratification using a polymodal approach could combine basal ganglia network connectivity with clinical and other imaging measures, with important implications for future neuroprotective trials in rapid eye movement sleep behaviour disorder.
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Affiliation(s)
- Michal Rolinski
- 1 Oxford Parkinson's Disease Centre (OPDC), Oxford, UK 2 Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Ludovica Griffanti
- 3 Centre for the functional MRI of the Brain (FMRIB), University of Oxford, Oxford, UK
| | - Paola Piccini
- 4 Division of Clinical Neurosciences and MRC Clinical Sciences Centre, Faculty of Medicine, Hammersmith Hospital, Imperial College London, London, UK
| | - Andreas A Roussakis
- 4 Division of Clinical Neurosciences and MRC Clinical Sciences Centre, Faculty of Medicine, Hammersmith Hospital, Imperial College London, London, UK
| | - Konrad Szewczyk-Krolikowski
- 1 Oxford Parkinson's Disease Centre (OPDC), Oxford, UK 2 Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Ricarda A Menke
- 3 Centre for the functional MRI of the Brain (FMRIB), University of Oxford, Oxford, UK
| | - Timothy Quinnell
- 5 Respiratory Support and Sleep Centre, Papworth Hospital, Cambridge, UK
| | - Zenobia Zaiwalla
- 6 Department of Clinical Neurophysiology, John Radcliffe Hospital, Oxford, UK
| | - Johannes C Klein
- 1 Oxford Parkinson's Disease Centre (OPDC), Oxford, UK 2 Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK 3 Centre for the functional MRI of the Brain (FMRIB), University of Oxford, Oxford, UK
| | - Clare E Mackay
- 1 Oxford Parkinson's Disease Centre (OPDC), Oxford, UK 3 Centre for the functional MRI of the Brain (FMRIB), University of Oxford, Oxford, UK 7 Department of Psychiatry, University of Oxford, Oxford, UK
| | - Michele T M Hu
- 1 Oxford Parkinson's Disease Centre (OPDC), Oxford, UK 2 Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
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43
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Gracien RM, Jurcoane A, Wagner M, Reitz SC, Mayer C, Volz S, Hof SM, Fleischer V, Droby A, Steinmetz H, Groppa S, Hattingen E, Deichmann R, Klein JC. Multimodal quantitative MRI assessment of cortical damage in relapsing-remitting multiple sclerosis. J Magn Reson Imaging 2016; 44:1600-1607. [DOI: 10.1002/jmri.25297] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2016] [Accepted: 04/19/2016] [Indexed: 11/05/2022] Open
Affiliation(s)
- René-Maxime Gracien
- Department of Neurology; Goethe University; Frankfurt/Main Germany
- Brain Imaging Center; Goethe University; Frankfurt/Main Germany
| | - Alina Jurcoane
- Department of Neuroradiology; Goethe University; Frankfurt/Main Germany
- Brain Imaging Center; Goethe University; Frankfurt/Main Germany
| | - Marlies Wagner
- Department of Neuroradiology; Goethe University; Frankfurt/Main Germany
- Brain Imaging Center; Goethe University; Frankfurt/Main Germany
| | - Sarah C. Reitz
- Department of Neurology; Goethe University; Frankfurt/Main Germany
- Brain Imaging Center; Goethe University; Frankfurt/Main Germany
| | - Christoph Mayer
- Department of Neurology; Goethe University; Frankfurt/Main Germany
| | - Steffen Volz
- Brain Imaging Center; Goethe University; Frankfurt/Main Germany
| | - Stephanie-Michelle Hof
- Department of Neurology; Goethe University; Frankfurt/Main Germany
- Brain Imaging Center; Goethe University; Frankfurt/Main Germany
| | - Vinzenz Fleischer
- Department of Neurology; Johannes Gutenberg University; Mainz Germany
- Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN); Johannes Gutenberg-University; Mainz Germany
| | - Amgad Droby
- Department of Neurology; Johannes Gutenberg University; Mainz Germany
- Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN); Johannes Gutenberg-University; Mainz Germany
| | | | - Sergiu Groppa
- Department of Neurology; Johannes Gutenberg University; Mainz Germany
- Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN); Johannes Gutenberg-University; Mainz Germany
| | - Elke Hattingen
- Department of Neuroradiology; Goethe University; Frankfurt/Main Germany
- Brain Imaging Center; Goethe University; Frankfurt/Main Germany
| | - Ralf Deichmann
- Brain Imaging Center; Goethe University; Frankfurt/Main Germany
| | - Johannes C. Klein
- Department of Neurology; Goethe University; Frankfurt/Main Germany
- Brain Imaging Center; Goethe University; Frankfurt/Main Germany
- Nuffield Department of Clinical Neurosciences; University of Oxford; UK
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44
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Gracien RM, Reitz SC, Hof SM, Fleischer V, Zimmermann H, Droby A, Steinmetz H, Zipp F, Deichmann R, Klein JC. Assessment of cortical damage in early multiple sclerosis with quantitative T2 relaxometry. NMR Biomed 2016; 29:444-450. [PMID: 26820580 DOI: 10.1002/nbm.3486] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/28/2015] [Revised: 11/24/2015] [Accepted: 12/16/2015] [Indexed: 06/05/2023]
Abstract
T2 relaxation time is a quantitative MRI in vivo surrogate of cerebral tissue damage in multiple sclerosis (MS) patients. Cortical T2 prolongation is a known feature in later disease stages, but has not been demonstrated in the cortical normal appearing gray matter (NAGM) in early MS. This study centers on the quantitative evaluation of the tissue parameter T2 in cortical NAGM in a collective of early MS and clinically isolated syndrome (CIS) patients, hypothesizing that T2 prolongation is already present at early disease stages and variable over space, in line with global and focal inflammatory processes in MS. Additionally, magnetization transfer ratio (MTR) mapping was performed for further characterization of the expected cortical T2 alteration. Quantitative T2 and MTR maps were acquired from 12 patients with CIS and early MS, and 12 matched healthy controls. The lesion-free part of the cortical volume was identified, and the mean T2 and MTR values and their standard deviations within the cortical volume were determined. For evaluation of spatial specificity, cortical lobar subregions were tested separately for differences of mean T2 and T2 standard deviation. We detected significantly prolonged T2 in cortical NAGM in patients. T2 prolongation was found across the whole cerebral cortex and in all individual lobar subregions. Significantly higher standard deviations across the respective region of interest were found for the whole cerebral cortex and all subregions, suggesting the occurrence of spatially inhomogeneous cortical damage in all regions studied. A trend was observed for MTR reduction and increased MTR variability across the whole cortex in the MS group, suggesting demyelination. In conclusion, our results suggest that cortical damage in early MS is evidenced by spatially inhomogeneous T2 prolongation which goes beyond demyelination. Iron deposition, which is known to decrease T2, seems less prominent.
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Affiliation(s)
- René-Maxime Gracien
- Department of Neurology, Goethe University, Frankfurt/Main, Germany
- Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
| | - Sarah C Reitz
- Department of Neurology, Goethe University, Frankfurt/Main, Germany
- Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
| | - Stephanie-Michelle Hof
- Department of Neurology, Goethe University, Frankfurt/Main, Germany
- Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
| | - Vinzenz Fleischer
- Department of Neurology, Johannes Gutenberg University, Mainz, Germany
- Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), Johannes Gutenberg-University, Mainz, Germany
| | - Hilga Zimmermann
- Department of Neurology, Johannes Gutenberg University, Mainz, Germany
- Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), Johannes Gutenberg-University, Mainz, Germany
| | - Amgad Droby
- Department of Neurology, Johannes Gutenberg University, Mainz, Germany
- Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), Johannes Gutenberg-University, Mainz, Germany
| | | | - Frauke Zipp
- Department of Neurology, Johannes Gutenberg University, Mainz, Germany
- Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), Johannes Gutenberg-University, Mainz, Germany
| | - Ralf Deichmann
- Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
| | - Johannes C Klein
- Department of Neurology, Goethe University, Frankfurt/Main, Germany
- Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
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45
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Baudrexel S, Reitz SC, Hof S, Gracien RM, Fleischer V, Zimmermann H, Droby A, Klein JC, Deichmann R. Quantitative T1 and proton density mapping with direct calculation of radiofrequency coil transmit and receive profiles from two-point variable flip angle data. NMR Biomed 2016; 29:349-360. [PMID: 26756673 DOI: 10.1002/nbm.3460] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2015] [Revised: 11/10/2015] [Accepted: 11/16/2015] [Indexed: 06/05/2023]
Abstract
Quantitative T1 mapping of brain tissue is frequently based on the variable flip angle (VFA) method, acquiring spoiled gradient echo (GE) datasets at different excitation angles. However, accurate T1 calculation requires a knowledge of the sensitivity profile B1 of the radiofrequency (RF) transmit coil. For an additional derivation of proton density (PD) maps, the receive coil sensitivity profile (RP) must also be known. Mapping of B1 and RP increases the experiment duration, which may be critical when investigating patients. In this work, a method is presented for the direct calculation of B1 and RP from VFA data. Thus, quantitative maps of T1 , PD, B1 and RP can be obtained from only two spoiled GE datasets. The method is based on: (1) the exploitation of the linear relationship between 1/PD and 1/T1 in brain tissue and (2) the assumption of smoothly varying B1 and RP, so that a large number of data points can be fitted across small volume elements where B1 and RP are approximately constant. The method is tested and optimized on healthy subjects. Copyright © 2016 John Wiley & Sons, Ltd.
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Affiliation(s)
- Simon Baudrexel
- Brain Imaging Center, Goethe University Frankfurt, Frankfurt/Main, Germany
- Department of Neurology, Goethe University Frankfurt, Frankfurt/Main, Germany
| | - Sarah C Reitz
- Brain Imaging Center, Goethe University Frankfurt, Frankfurt/Main, Germany
- Department of Neurology, Goethe University Frankfurt, Frankfurt/Main, Germany
| | - Stephanie Hof
- Brain Imaging Center, Goethe University Frankfurt, Frankfurt/Main, Germany
- Department of Neurology, Goethe University Frankfurt, Frankfurt/Main, Germany
| | - René-Maxime Gracien
- Brain Imaging Center, Goethe University Frankfurt, Frankfurt/Main, Germany
- Department of Neurology, Goethe University Frankfurt, Frankfurt/Main, Germany
| | - Vinzenz Fleischer
- Department of Neurology, Johannes Gutenberg University, Mainz, Germany
- Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), Johannes Gutenberg University, Mainz, Germany
| | - Hilga Zimmermann
- Department of Neurology, Johannes Gutenberg University, Mainz, Germany
- Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), Johannes Gutenberg University, Mainz, Germany
| | - Amgad Droby
- Department of Neurology, Johannes Gutenberg University, Mainz, Germany
- Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), Johannes Gutenberg University, Mainz, Germany
| | - Johannes C Klein
- Brain Imaging Center, Goethe University Frankfurt, Frankfurt/Main, Germany
- Department of Neurology, Goethe University Frankfurt, Frankfurt/Main, Germany
| | - Ralf Deichmann
- Brain Imaging Center, Goethe University Frankfurt, Frankfurt/Main, Germany
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46
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Kang JS, Klein JC, Baudrexel S, Deichmann R, Nolte D, Hilker R. White matter damage is related to ataxia severity in SCA3. J Neurol 2013; 261:291-9. [PMID: 24272589 DOI: 10.1007/s00415-013-7186-6] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2013] [Revised: 11/05/2013] [Accepted: 11/05/2013] [Indexed: 12/31/2022]
Abstract
Spinocerebellar ataxia type 3 (SCA3) is the most frequent inherited cerebellar ataxia in Europe, the US and Japan, leading to disability and death through motor complications. Although the affected protein ataxin-3 is found ubiquitously in the brain, grey matter atrophy is predominant in the cerebellum and the brainstem. White matter pathology is generally less severe and thought to occur in the brainstem, spinal cord, and cerebellar white matter. Here, we investigated both grey and white matter pathology in a group of 12 SCA3 patients and matched controls. We used voxel-based morphometry for analysis of tissue loss, and tract-based spatial statistics (TBSS) on diffusion magnetic resonance imaging to investigate microstructural pathology. We analysed correlations between microstructural properties of the brain and ataxia severity, as measured by the Scale for the Assessment and Rating of Ataxia (SARA) score. SCA3 patients exhibited significant loss of both grey and white matter in the cerebellar hemispheres, brainstem including pons and in lateral thalamus. On between-group analysis, TBSS detected widespread microstructural white matter pathology in the cerebellum, brainstem, and bilaterally in thalamus and the cerebral hemispheres. Furthermore, fractional anisotropy in a white matter network comprising frontal, thalamic, brainstem and left cerebellar white matter strongly and negatively correlated with SARA ataxia scores. Tractography identified the thalamic white matter thus implicated as belonging to ventrolateral thalamus. Disruption of white matter integrity in patients suffering from SCA3 is more widespread than previously thought. Moreover, our data provide evidence that microstructural white matter changes in SCA3 are strongly related to the clinical severity of ataxia symptoms.
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Affiliation(s)
- J-S Kang
- Department of Neurology, Goethe-University of Frankfurt, Schleusenweg 2-16, 60528, Frankfurt am Main, Germany
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47
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Baudrexel S, Seifried C, Penndorf B, Klein JC, Middendorp M, Steinmetz H, Grünwald F, Hilker R. The value of putaminal diffusion imaging versus 18-fluorodeoxyglucose positron emission tomography for the differential diagnosis of the Parkinson variant of multiple system atrophy. Mov Disord 2013; 29:380-7. [PMID: 24243813 DOI: 10.1002/mds.25749] [Citation(s) in RCA: 45] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2013] [Revised: 10/02/2013] [Accepted: 10/18/2013] [Indexed: 11/08/2022] Open
Abstract
Differentiating the Parkinson variant of multiple system atrophy (MSA-P) from idiopathic Parkinson's disease (PD) and other forms of atypical parkinsonism can be difficult because symptoms overlap considerably. 18-Fluorodeoxyglucose positron emission tomography (FDG-PET) is a powerful imaging technique that can assist in the diagnosis of MSA-P via detection of putaminal and cerebellar hypometabolism. Recent studies suggest that diffusion-weighted imaging (DWI) might be of similar diagnostic value, as it can detect microstructural damage in the putamen by means of an increased mean diffusivity (MD). The aim of this study was a direct comparison of DWI and FDG-PET by using both methods on the same subject cohort. To this end, combined DWI and FDG-PET were employed in patients with MSA-P (n = 11), PD (n = 13), progressive supranuclear palsy (n = 8), and in 6 control subjects. MD values and FDG uptake ratios were derived from volumetric parcellations of the putamen and subjected to further analysis of covariance (ANCOVA) and receiver operating characteristics analyses. MSA-P was found to be associated with an increased posterior putaminal MD (P < 0.001 in all subgroup comparisons) that correlated strongly with local reductions in FDG uptake (r = -0.85, P = 0.002). DWI discriminated patients with MSA-P from other subgroups nearly as accurately as FDG-PET (area under the curve = 0.89 vs 0.95, P = 0.27 [pooled data]). Our data suggest a close association between the amount of putaminal microstructural damage and a reduced energy metabolism in patients with MSA-P. The clinical use of DWI for the differential diagnosis of MSA-P is encouraged.
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Affiliation(s)
- Simon Baudrexel
- Department of Neurology, University Hospital, Goethe University Frankfurt am Main, Frankfurt am Main, Germany; Brain Imaging Center, Goethe University Frankfurt am Main, Frankfurt am Main, Germany
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48
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Meng FG, Zhang JG, Kao CC, Klein JC, Hilker R. The tremor network targeted by successful VIM deep brain stimulation in humans. Neurology 2012; 79:953; author reply 953. [PMID: 22927683 DOI: 10.1212/01.wnl.0000419345.94406.07] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
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49
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Hübers A, Klein JC, Kang JS, Hilker R, Ziemann U. The relationship between TMS measures of functional properties and DTI measures of microstructure of the corticospinal tract. Brain Stimul 2012; 5:297-304. [DOI: 10.1016/j.brs.2011.03.008] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2010] [Revised: 03/21/2011] [Accepted: 03/26/2011] [Indexed: 10/18/2022] Open
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50
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Singer OC, Melber J, Hattingen E, Jurcoane A, Keil F, Neumann-Haefelin T, Klein JC. MR volumetric changes after diagnostic CSF removal in normal pressure hydrocephalus. J Neurol 2012; 259:2440-6. [PMID: 22592285 DOI: 10.1007/s00415-012-6525-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2011] [Revised: 04/13/2012] [Accepted: 04/17/2012] [Indexed: 10/28/2022]
Abstract
Although diagnostic CSF removal in patients with suspected normal pressure hydrocephalus (NPH) is performed frequently, its impact on changes of the global brain volume and volume of the ventricles has not been studied in detail. We examined 20 patients with clinical and radiological signs of NPH. These received MRI prior to and immediately after diagnostic CSF removal, either via lumbar puncture (TAP, n = 10) or via external lumbar drainage (ELD, n = 10). Changes in global brain volume were assessed using SIENA, a tool from the FSL software library. Additionally, we determined the change of the lateral ventricles' volume by manual segmentation. Furthermore, we recorded systematic clinical assessments of the key features of NPH. The median volume of CSF removed was 35 ml in TAP patients and 406 ml in ELD patients. Changes in global brain volume were found in both patient groups. Brain volume change was significantly larger in ELD patients than in TAP patients (p = 0.022), and correlated with the volume of CSF removal (r = 0.628, p = 0.004). Brain volume expansion was most pronounced adjacent to the lateral ventricles, but also detectable in the temporal and frontal regions. The median ventricular volume decreased after CSF removal. Ventricular volume reduction was more pronounced in ELD patients than in TAP patients. This study quantifies for the first time immediate volumetric changes of global brain tissue and of ventricles after diagnostic CSF removal in NPH patients. In particular, we report evidence that CSF removal results in a change of the brain volume rather than only a change of the brain's shape.
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Affiliation(s)
- Oliver C Singer
- Department of Neurology, Goethe-University Frankfurt, Schleusenweg 2-16, 60528, Frankfurt/Main, Germany.
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