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Correia Guedes L, Reimão S, Paulino P, Nunes RG, Bouça-Machado R, Abreu D, Gonçalves N, Soares T, Fabbri M, Godinho C, Pita Lobo P, Neutel D, Quadri M, Coelho M, Rosa MM, Campos J, Outeiro TF, Sampaio C, Bonifati V, Ferreira JJ. Neuromelanin magnetic resonance imaging of the substantia nigra in LRRK2
-related Parkinson's disease. Mov Disord 2017; 32:1331-1333. [DOI: 10.1002/mds.27083] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2017] [Revised: 05/17/2017] [Accepted: 05/31/2017] [Indexed: 11/06/2022] Open
Affiliation(s)
- Leonor Correia Guedes
- Department of Neurosciences and Mental Health, Neurology; Hospital de Santa Maria-CHLN; Lisbon Portugal
- Clinical Pharmachology Unit; Instituto de Medicina Molecular; Lisbon Portugal
| | - Sofia Reimão
- Clinical Pharmachology Unit; Instituto de Medicina Molecular; Lisbon Portugal
- Neurological Imaging Department; Hospital de Santa Maria-CHLN; Lisbon Portugal
| | - Patrícia Paulino
- Instituto de Biofísica e Engenharia Biomédica, Faculty of Science; University of Lisbon; Portugal
- Faculty of Science and Technology; Nova University of Lisbon; Campus da Caparica Portugal
| | - Rita G. Nunes
- Instituto de Biofísica e Engenharia Biomédica, Faculty of Science; University of Lisbon; Portugal
| | | | - Daisy Abreu
- Clinical Pharmachology Unit; Instituto de Medicina Molecular; Lisbon Portugal
| | - Nilza Gonçalves
- Clinical Pharmachology Unit; Instituto de Medicina Molecular; Lisbon Portugal
| | - Tiago Soares
- Clinical Pharmachology Unit; Instituto de Medicina Molecular; Lisbon Portugal
| | - Margherita Fabbri
- Clinical Pharmachology Unit; Instituto de Medicina Molecular; Lisbon Portugal
| | - Catarina Godinho
- Clinical Pharmachology Unit; Instituto de Medicina Molecular; Lisbon Portugal
| | - Patrícia Pita Lobo
- Clinical Pharmachology Unit; Instituto de Medicina Molecular; Lisbon Portugal
| | - Dulce Neutel
- Clinical Pharmachology Unit; Instituto de Medicina Molecular; Lisbon Portugal
| | - Marialuisa Quadri
- Department of Clinical Genetics; Erasmus MC; Rotterdam The Netherlands
| | - Miguel Coelho
- Department of Neurosciences and Mental Health, Neurology; Hospital de Santa Maria-CHLN; Lisbon Portugal
- Clinical Pharmachology Unit; Instituto de Medicina Molecular; Lisbon Portugal
| | - Mario M. Rosa
- Department of Neurosciences and Mental Health, Neurology; Hospital de Santa Maria-CHLN; Lisbon Portugal
- Clinical Pharmachology Unit; Instituto de Medicina Molecular; Lisbon Portugal
- Laboratory of Clinical Pharmachology and Therapeutics, Faculty of Medicine; University of Lisbon; Portugal
| | - Jorge Campos
- Neurological Imaging Department; Hospital de Santa Maria-CHLN; Lisbon Portugal
| | - Tiago F. Outeiro
- CEDOC, Chronic Diseases Research Centre, Nova Medical School; Nova University of Lisbon; Lisboa Portugal
- Department of Experimental Neurodegeneration, Center for Biostructural Imaging of Neurodegeneration, Center for Nanoscale Microscopy and Molecular Physiology of the Brain (CNMPB); University Medical Center Gottingen; Germany
- Max Planck Institute for Experimental Medicine; Gottingen Germany
| | - Cristina Sampaio
- Laboratory of Clinical Pharmachology and Therapeutics, Faculty of Medicine; University of Lisbon; Portugal
| | - Vincenzo Bonifati
- Department of Clinical Genetics; Erasmus MC; Rotterdam The Netherlands
| | - Joaquim J. Ferreira
- Clinical Pharmachology Unit; Instituto de Medicina Molecular; Lisbon Portugal
- Laboratory of Clinical Pharmachology and Therapeutics, Faculty of Medicine; University of Lisbon; Portugal
- CNS-Campus Neurológico Sénior; Torres Vedras Portugal
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102
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Osadebey M, Pedersen M, Arnold D, Wendel-Mitoraj K. Bayesian framework inspired no-reference region-of-interest quality measure for brain MRI images. J Med Imaging (Bellingham) 2017. [PMID: 28630885 DOI: 10.1117/1.jmi.4.2.025504] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
We describe a postacquisition, attribute-based quality assessment method for brain magnetic resonance imaging (MRI) images. It is based on the application of Bayes theory to the relationship between entropy and image quality attributes. The entropy feature image of a slice is segmented into low- and high-entropy regions. For each entropy region, there are three separate observations of contrast, standard deviation, and sharpness quality attributes. A quality index for a quality attribute is the posterior probability of an entropy region given any corresponding region in a feature image where quality attribute is observed. Prior belief in each entropy region is determined from normalized total clique potential (TCP) energy of the slice. For TCP below the predefined threshold, the prior probability for a region is determined by deviation of its percentage composition in the slice from a standard normal distribution built from 250 MRI volume data provided by Alzheimer's Disease Neuroimaging Initiative. For TCP above the threshold, the prior is computed using a mathematical model that describes the TCP-noise level relationship in brain MRI images. Our proposed method assesses the image quality of each entropy region and the global image. Experimental results demonstrate good correlation with subjective opinions of radiologists for different types and levels of quality distortions.
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Affiliation(s)
- Michael Osadebey
- NeuroRx Research Inc., MRI Reader Group, Montreal, Québec, Canada
| | - Marius Pedersen
- Norwegian University of Science and Technology, Department of Computer Science, Gjøvik, Norway
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103
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Tuite P. Brain Magnetic Resonance Imaging (MRI) as a Potential Biomarker for Parkinson's Disease (PD). Brain Sci 2017; 7:E68. [PMID: 28621758 PMCID: PMC5483641 DOI: 10.3390/brainsci7060068] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2017] [Revised: 06/09/2017] [Accepted: 06/13/2017] [Indexed: 12/14/2022] Open
Abstract
Magnetic resonance imaging (MRI) has the potential to serve as a biomarker for Parkinson's disease (PD). However, the type or types of biomarker it could provide remain to be determined. At this time there is not sufficient sensitivity or specificity for MRI to serve as an early diagnostic biomarker, i.e., it is unproven in its ability to determine if a single individual is normal, has mild PD, or has some other forms of degenerative parkinsonism. However there is accumulating evidence that MRI may be useful in staging and monitoring disease progression (staging biomarker), and also possibly as a means to monitor pathophysiological aspects of disease and associated response to treatments, i.e., theranostic marker. As there are increasing numbers of manuscripts that are dedicated to diffusion- and neuromelanin-based imaging methods, this review will focus on these topics cursorily and will delve into pharmacodynamic imaging as a means to get at theranostic aspects of PD.
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Affiliation(s)
- Paul Tuite
- Neurology Department, University of Minnesota, MMC 295, 420 Delaware St SE, Minneapolis, MN 55455, USA.
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104
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Schwarz ST, Xing Y, Tomar P, Bajaj N, Auer DP. In Vivo Assessment of Brainstem Depigmentation in Parkinson Disease: Potential as a Severity Marker for Multicenter Studies. Radiology 2017; 283:789-798. [DOI: 10.1148/radiol.2016160662] [Citation(s) in RCA: 64] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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105
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Abstract
New methods for the diagnosis and new treatments for Parkinson's disease (PD) were explained. As imaging tools, neuromelanin imaging using brain MRI, meta-iodobenzylguanidine (MIBG) cardiac scintigraphy, dopamine transporter scintigraphy, and transcranial sonography were introduced. Olfactory dysfunction and REM sleep behavior disorders (RBD), which are important non-motor symptoms, and the new Clinical Criteria for PD launched by Movement Disorder Society (MDS) were also described. Investigative new medications and new anti-PD medications, which recently became available in Japan, were introduced. I explained the rationale of early treatment, strategy of initial treatment, the significance of continuous dopaminergic stimulation, strategy of treatment for advanced PD, and deep brain stimulation as a surgical treatment together with promising new treatments including gene therapy and cell transplantation.
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106
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Martin-Bastida A, Pietracupa S, Piccini P. Neuromelanin in parkinsonian disorders: an update. Int J Neurosci 2017; 127:1116-1123. [PMID: 28460588 DOI: 10.1080/00207454.2017.1325883] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
Neuromelanin (NM) is a dark pigment that accumulates linearly with aging in substantia nigra (SN) and locus coeruleus (LC). The dual protective and toxic role of NM has been hypothesized according to its intraneuronal or extraneuronal deposition. The melanized dopaminergic neurons in SN and LC seem to have special vulnerability to neurodegeneration in Parkinson's disease (PD). The paramagnetic properties of NM due to its association to metals like iron induce T1 prolongation; hence the measurement of SN-sensitive contrast could be a useful diagnostic biomarker in neurodegenerative disease like PD and other atypical parkinsonisms. This paper will review NM histopathology and neurochemistry studies in health and diseases and the role of imaging targeting NM load in parkinsonian disorders.
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Affiliation(s)
- Antonio Martin-Bastida
- a Centre for Neurodegeneration and Neuroinflammation, Division of Brain Sciences , Imperial College London , London , United Kingdom
| | - Sara Pietracupa
- b Department of Neurology , IRCCS Neuromed , Pozzilli , Italy
| | - Paola Piccini
- a Centre for Neurodegeneration and Neuroinflammation, Division of Brain Sciences , Imperial College London , London , United Kingdom
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107
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Barber TR, Klein JC, Mackay CE, Hu MTM. Neuroimaging in pre-motor Parkinson's disease. Neuroimage Clin 2017; 15:215-227. [PMID: 28529878 PMCID: PMC5429242 DOI: 10.1016/j.nicl.2017.04.011] [Citation(s) in RCA: 55] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2016] [Revised: 04/10/2017] [Accepted: 04/15/2017] [Indexed: 12/23/2022]
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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108
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Saeed U, Compagnone J, Aviv RI, Strafella AP, Black SE, Lang AE, Masellis M. Imaging biomarkers in Parkinson's disease and Parkinsonian syndromes: current and emerging concepts. Transl Neurodegener 2017; 6:8. [PMID: 28360997 PMCID: PMC5370489 DOI: 10.1186/s40035-017-0076-6] [Citation(s) in RCA: 135] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2017] [Accepted: 02/28/2017] [Indexed: 12/24/2022] Open
Abstract
Two centuries ago in 1817, James Parkinson provided the first medical description of Parkinson’s disease, later refined by Jean-Martin Charcot in the mid-to-late 19th century to include the atypical parkinsonian variants (also termed, Parkinson-plus syndromes). Today, Parkinson’s disease represents the second most common neurodegenerative disorder with an estimated global prevalence of over 10 million. Conversely, atypical parkinsonian syndromes encompass a group of relatively heterogeneous disorders that may share some clinical features with Parkinson’s disease, but are uncommon distinct clinicopathological diseases. Decades of scientific advancements have vastly improved our understanding of these disorders, including improvements in in vivo imaging for biomarker identification. Multimodal imaging for the visualization of structural and functional brain changes is especially important, as it allows a ‘window’ into the underlying pathophysiological abnormalities. In this article, we first present an overview of the cardinal clinical and neuropathological features of, 1) synucleinopathies: Parkinson’s disease and other Lewy body spectrum disorders, as well as multiple system atrophy, and 2) tauopathies: progressive supranuclear palsy, and corticobasal degeneration. A comprehensive presentation of well-established and emerging imaging biomarkers for each disorder are then discussed. Biomarkers for the following imaging modalities are reviewed: 1) structural magnetic resonance imaging (MRI) using T1, T2, and susceptibility-weighted sequences for volumetric and voxel-based morphometric analyses, as well as MRI derived visual signatures, 2) diffusion tensor MRI for the assessment of white matter tract injury and microstructural integrity, 3) proton magnetic resonance spectroscopy for quantifying proton-containing brain metabolites, 4) single photon emission computed tomography for the evaluation of nigrostriatal integrity (as assessed by presynaptic dopamine transporters and postsynaptic dopamine D2 receptors), and cerebral perfusion, 5) positron emission tomography for gauging nigrostriatal functions, glucose metabolism, amyloid and tau molecular imaging, as well as neuroinflammation, 6) myocardial scintigraphy for dysautonomia, and 7) transcranial sonography for measuring substantia nigra and lentiform nucleus echogenicity. Imaging biomarkers, using the ‘multimodal approach’, may aid in making early, accurate and objective diagnostic decisions, highlight neuroanatomical and pathophysiological mechanisms, as well as assist in evaluating disease progression and therapeutic responses to drugs in clinical trials.
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Affiliation(s)
- Usman Saeed
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, Canada.,LC Campbell Cognitive Neurology Research Unit, Sunnybrook Research Institute, Toronto, Canada
| | - Jordana Compagnone
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, Canada.,LC Campbell Cognitive Neurology Research Unit, Sunnybrook Research Institute, Toronto, Canada
| | - Richard I Aviv
- Department of Medical Imaging, University of Toronto and Division of Neuroradiology, Sunnybrook Health Sciences Centre, Toronto, Canada
| | - Antonio P Strafella
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Canada.,Division of Brain, Imaging & Behaviour - Systems Neuroscience, Toronto Western Hospital, Toronto, Canada.,Division of Neurology, Department of Medicine, University of Toronto, Toronto, Canada
| | - Sandra E Black
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, Canada.,LC Campbell Cognitive Neurology Research Unit, Sunnybrook Research Institute, Toronto, Canada.,Division of Neurology, Department of Medicine, University of Toronto, Toronto, Canada.,Heart & Stroke Foundation Canadian Partnership for Stroke Recovery, Sunnybrook Health Sciences Centre, Toronto, Canada
| | - Anthony E Lang
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, Canada.,Movement Disorders Centre, Toronto Western Hospital, Toronto, Canada.,Edmond J. Safra Program in Parkinson's Disease, University Health Network, Toronto, Canada
| | - Mario Masellis
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, Canada.,LC Campbell Cognitive Neurology Research Unit, Sunnybrook Research Institute, Toronto, Canada.,Division of Neurology, Department of Medicine, University of Toronto, Toronto, Canada.,Cognitive & Movement Disorders Clinic, Sunnybrook Health Sciences Centre, 2075 Bayview Ave., Room A4-55, Toronto, Ontario M4N 3 M5 Canada
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109
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Lehericy S, Vaillancourt DE, Seppi K, Monchi O, Rektorova I, Antonini A, McKeown MJ, Masellis M, Berg D, Rowe JB, Lewis SJG, Williams-Gray CH, Tessitore A, Siebner HR. The role of high-field magnetic resonance imaging in parkinsonian disorders: Pushing the boundaries forward. Mov Disord 2017; 32:510-525. [PMID: 28370449 DOI: 10.1002/mds.26968] [Citation(s) in RCA: 86] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2016] [Revised: 12/22/2016] [Accepted: 01/15/2017] [Indexed: 12/28/2022] Open
Abstract
Historically, magnetic resonance imaging (MRI) has contributed little to the study of Parkinson's disease (PD), but modern MRI approaches have unveiled several complementary markers that are useful for research and clinical applications. Iron- and neuromelanin-sensitive MRI detect qualitative changes in the substantia nigra. Quantitative MRI markers can be derived from diffusion weighted and iron-sensitive imaging or volumetry. Functional brain alterations at rest or during task performance have been captured with functional and arterial spin labeling perfusion MRI. These markers are useful for the diagnosis of PD and atypical parkinsonism, to track disease progression from the premotor stages of these diseases and to better understand the neurobiological basis of clinical deficits. A current research goal using MRI is to generate time-dependent models of the evolution of PD biomarkers that can help understand neurodegeneration and provide reliable markers for therapeutic trials. This article reviews recent advances in MRI biomarker research at high-field (3T) and ultra high field-imaging (7T) in PD and atypical parkinsonism. © 2017 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Stéphane Lehericy
- Institut du Cerveau et de la Moelle épinière - ICM, Centre de NeuroImagerie de Recherche - CENIR, Sorbonne Universités, Groupe Hospitalier Pitié-Salpêtrière, Paris, France
| | - David E Vaillancourt
- Department of Applied Physiology and Kinesiology, Department of Neurology and Centre for Movement Disorders and Neurorestoration, Department of Biomedical Engineering, University of Florida, Gainesville, Florida, USA
| | - Klaus Seppi
- Department of Neurology, Medical University Innsbruck, Innsbruck, Austria and Neuroimaging Research Core Facility, Medical University Innsbruck, Innsbruck, Austria
| | - Oury Monchi
- Department of Clinical Neurosciences, Department of Radiology, Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Irena Rektorova
- First Department of Neurology, School of Medicine, St. Anne's University Hospital, Brain and Mind Research Program, Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Angelo Antonini
- Parkinson and Movement Disorders Unit, istituto di ricovero e cura a carattere scientifico (IRCCS) Hospital San Camillo, Venice and Department of Neurosciences (DNS), Padova University, Padova, Italy
| | - Martin J McKeown
- Pacific Parkinson's Research Center, Department of Medicine (Neurology), University of British Columbia Vancouver, BC, Canada
| | - Mario Masellis
- Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - Daniela Berg
- Department of Neurology, Christian-Albrechts-University of Kiel and Hertie-Institute for Clinical Brain Research, University of Tuebingen, Tuebingen, Germany
| | - James B Rowe
- Department of Clinical Neurosciences, Cambridge University, and Medical Research Council Cognition and Brain Sciences Unit, Cambridge, UK
| | - Simon J G Lewis
- Parkinson's Disease Research Clinic, Brain and Mind Centre, University of Sydney, Sydney, Australia
| | - Caroline H Williams-Gray
- John Van Geest Centre for Brain Repair, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Alessandro Tessitore
- Department of Medical, Surgical, Neurological, Metabolic and Aging Sciences, Second University of Naples, Naples, Italy
| | - Hartwig R Siebner
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Department of Neurology, Copenhagen University Hospital Bispebjerg, Hvidovre, Denmark
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110
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Hatano T, Okuzumi A, Kamagata K, Daida K, Taniguchi D, Hori M, Yoshino H, Aoki S, Hattori N. Neuromelanin MRI is useful for monitoring motor complications in Parkinson’s and PARK2 disease. J Neural Transm (Vienna) 2017; 124:407-415. [DOI: 10.1007/s00702-017-1688-9] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2016] [Accepted: 01/23/2017] [Indexed: 11/29/2022]
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111
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Xiang Y, Gong T, Wu J, Li J, Chen Y, Wang Y, Li S, Cong L, Lin Y, Han Y, Yin L, Wang G, Du Y. Subtypes evaluation of motor dysfunction in Parkinson’s disease using neuromelanin-sensitive magnetic resonance imaging. Neurosci Lett 2017; 638:145-150. [DOI: 10.1016/j.neulet.2016.12.036] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2016] [Revised: 11/16/2016] [Accepted: 12/15/2016] [Indexed: 10/20/2022]
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112
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Matsuura K, Maeda M, Tabei KI, Umino M, Kajikawa H, Satoh M, Kida H, Tomimoto H. A longitudinal study of neuromelanin-sensitive magnetic resonance imaging in Parkinson’s disease. Neurosci Lett 2016; 633:112-117. [DOI: 10.1016/j.neulet.2016.09.011] [Citation(s) in RCA: 43] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2016] [Revised: 08/28/2016] [Accepted: 09/09/2016] [Indexed: 11/26/2022]
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113
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T2-relaxometry predicts outcome of DBS in idiopathic Parkinson's disease. NEUROIMAGE-CLINICAL 2016; 12:832-837. [PMID: 27843765 PMCID: PMC5097958 DOI: 10.1016/j.nicl.2016.09.019] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/22/2016] [Revised: 09/26/2016] [Accepted: 09/28/2016] [Indexed: 12/25/2022]
Abstract
Introduction Deep brain stimulation (DBS) nowadays is a well-established treatment of motor symptoms in Parkinson's disease. The subthalamic nucleus (STN) is a common target for DBS, because motor improvements have been shown to be superior to best medical therapy, if DBS electrodes have been appropriately positioned. DBS target identification can be assisted by MRI beyond structural imaging by spatially resolved measurement of T2-relaxation times (T2r). Aim We pose the question, whether T2r of the STN is linked to the severity of the disease and whether outcome of DBS may be correlated to an asymmetric manifestation of the disease. Further, we investigated if abnormal T2r in the STN may be predictive for outcome of DBS. Methods Twelve patients underwent preoperative MR imaging including a multi echo relaxometry sequence (3 Tesla, Siemens Medical Systems, Erlangen, Germany) ahead of DBS. T2r were determined for STN, substantia nigra (SN), red nucleus (RN) and centrum semiovale (CSO). Unified Parkinson's disease Rating Scale (UPDRS) scores were tested before and after DBS. Patients' T2r and deduced values representing left-right asymmetry of measurements were correlated with UPDRS scores and measures for outcome of DBS. Furthermore, patients' T2r were compared with T2r measurements in 12 healthy controls (HC). Results Patients' T2r for SN (mean 45.4 ms ± 4.4 ms) and STN (mean 56.4 ms ± 3.8 ms) were significantly shorter than T2r in HCs for SN (mean 60.7 ± 4.6) and STN (mean 66.1 ms ± 4.0 ms). While no mean T2r asymmetry was found in the SN, patients' mean T2r for STN showed a weakened left-right correlation (Pearson correlation coefficient 0.19 versus 0.72 in HC) indicating asymmetric degeneration. T2r asymmetry was not linked to the more severely affected hemisphere. The respective lower T2r within the left or right target region was significantly correlated to the outcome in terms of UPDRS III improvement in “off” state (Pearson correlation 0.82 corresponding to p ≪ 0.01). Patients with T2r of STN lower than 50 ms showed no response to DBS in the UPDRS. The maximum T2r for SN correlated to the improvement between UPDRS “off” minus and “on” (Dopamine response) but failed to predict DBS outcome. Conclusions The lower boundaries of T2r in the STN predict motor outcome in DBS. T2r asymmetry in the STN is not associated with increased clinical symptoms, but with response to therapy. Thus, patients with very low T2r may be inappropriate candidates for DBS. Parkinson's disease features are reflected in spatially resolved measurement of MR T2-relaxation times. Deep brain stimulation therapy target identification can be assisted by measurement of MR T2-relaxation times. T2r asymmetry in the subthalamic nucleus is not associated with increased clinical symptoms, but with response to therapy. Lower boundaries of T2r in the STN predict motor outcome in Deep brain stimulation therapy Patient selection criteria may be improved by including parameters based on MR relaxometry.
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114
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Reproducibility of locus coeruleus and substantia nigra imaging with neuromelanin sensitive MRI. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2016; 30:121-125. [PMID: 27687624 DOI: 10.1007/s10334-016-0590-z] [Citation(s) in RCA: 52] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/22/2016] [Revised: 08/30/2016] [Accepted: 09/12/2016] [Indexed: 10/20/2022]
Abstract
OBJECTIVES The purpose of this study was to assess the reproducibility of substantia nigra pars compacta (SNpc) and locus coeruleus (LC) delineation and measurement with neuromelanin-sensitive MRI. MATERIALS AND METHODS Eleven subjects underwent two neuromelanin-sensitive MRI scans. SNpc and LC volumes were extracted for each scan. Reproducibility of volume and magnetization transfer contrast measurements in SNpc and LC was assessed using intraclass correlation coefficients (ICC) and dice similarity coefficients (DSC). RESULTS SNpc and LC volume measurements showed excellent reproducibility (SNpc-ICC: 0.94, p < 0.001; LC-ICC: 0.96, p < 0.001). SNpc and LC were accurately delineated between scans (SNpc-DSC: 0.80 ± 0.03; LC-DSC: 0.63 ± 0.07). CONCLUSION Neuromelanin-sensitive MRI can consistently delineate SNpc and LC.
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115
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Tuite P. Magnetic resonance imaging as a potential biomarker for Parkinson's disease. Transl Res 2016; 175:4-16. [PMID: 26763585 DOI: 10.1016/j.trsl.2015.12.006] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/21/2015] [Revised: 12/09/2015] [Accepted: 12/10/2015] [Indexed: 01/01/2023]
Abstract
Although a magnetic resonance imaging (MRI) biomarker for Parkinson's disease (PD) remains an unfulfilled objective, there have been numerous developments in MRI methodology and some of these have shown promise for PD. With funding from the National Institutes of Health and the Michael J Fox Foundation there will be further validation of structural, diffusion-based, and iron-focused MRI methods as possible biomarkers for PD. In this review, these methods and other strategies such as neurochemical and metabolic MRI have been covered. One of the challenges in establishing a biomarker is in the selection of individuals as PD is a heterogeneous disease with varying clinical features, different etiologies, and a range of pathologic changes. Additionally, longitudinal studies are needed of individuals with clinically diagnosed PD and cohorts of individuals who are at great risk for developing PD to validate methods. Ultimately an MRI biomarker will be useful in the diagnosis of PD, predicting the course of PD, providing a means to track its course, and provide an approach to select and monitor treatments.
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Affiliation(s)
- Paul Tuite
- Department of Neurology, University of Minnesota, Minneapolis, Minnesota.
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116
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Isaias IU, Trujillo P, Summers P, Marotta G, Mainardi L, Pezzoli G, Zecca L, Costa A. Neuromelanin Imaging and Dopaminergic Loss in Parkinson's Disease. Front Aging Neurosci 2016; 8:196. [PMID: 27597825 PMCID: PMC4992725 DOI: 10.3389/fnagi.2016.00196] [Citation(s) in RCA: 130] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2016] [Accepted: 08/02/2016] [Indexed: 11/18/2022] Open
Abstract
Parkinson's disease (PD) is a progressive neurodegenerative disorder in which the major pathologic substrate is a loss of dopaminergic neurons from the substantia nigra. Our main objective was to determine the correspondence between changes in the substantia nigra, evident in neuromelanin and iron sensitive magnetic resonance imaging (MRI), and dopaminergic striatal innervation loss in patients with PD. Eighteen patients and 18 healthy control subjects were included in the study. Using neuromelanin-MRI, we measured the volume of the substantia nigra and the contrast-to-noise-ratio between substantia nigra and a background region. The apparent transverse relaxation rate and magnetic susceptibility of the substantia nigra were calculated from dual-echo MRI. Striatal dopaminergic innervation was measured as density of dopamine transporter (DAT) by means of single-photon emission computed tomography and [123I] N-ω-fluoropropyl-2b-carbomethoxy-3b-(4-iodophenyl) tropane. Patients showed a reduced volume of the substantia nigra and contrast-to-noise-ratio and both positively correlated with the corresponding striatal DAT density. The apparent transverse relaxation rate and magnetic susceptibility values of the substantia nigra did not differ between patients and healthy controls. The best predictor of DAT reduction was the volume of the substantia nigra. Clinical and imaging correlations were also investigated for the locus coeruleus. Our results suggest that neuromelanin-MRI can be used for quantifying substantia nigra pathology in PD where it closely correlates with dopaminergic striatal innervation loss. Longitudinal studies should further explore the role of Neuromelanin-MRI as an imaging biomarker of PD, especially for subjects at risk of developing the disease.
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Affiliation(s)
- Ioannis U Isaias
- Department of Neurology, University Hospital WuerzburgWürzburg, Germany; Centro Parkinson, Pini-CTOMilan, Italy
| | - Paula Trujillo
- Department of Neuroradiology, Fondazione IRCCS Ca' Granda Ospedale Maggiore PoliclinicoMilan, Italy; Department of Electronics, Information and Bioengineering, Politecnico di MilanoMilan, Italy
| | - Paul Summers
- Department of Neuroradiology, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico Milan, Italy
| | - Giorgio Marotta
- Department of Nuclear Medicine, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico Milan, Italy
| | - Luca Mainardi
- Department of Electronics, Information and Bioengineering, Politecnico di Milano Milan, Italy
| | | | - Luigi Zecca
- Italian National Research Council, Institute of Biomedical Technologies Segrate, Italy
| | - Antonella Costa
- Department of Neuroradiology, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico Milan, Italy
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Langley J, Huddleston DE, Merritt M, Chen X, McMurray R, Silver M, Factor SA, Hu X. Diffusion tensor imaging of the substantia nigra in Parkinson's disease revisited. Hum Brain Mapp 2016; 37:2547-56. [PMID: 27029026 DOI: 10.1002/hbm.23192] [Citation(s) in RCA: 58] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2016] [Accepted: 03/11/2016] [Indexed: 12/12/2022] Open
Abstract
OBJECTIVE To analyze diffusion tensor imaging (DTI) data in the substantia nigra (SN) using a more consistent region of interest (ROI) defined by neuromelanin-sensitive MRI in order to assess Parkinson's disease (PD) related changes in diffusion characteristics in the SN. METHODS T1 -weighted and DTI data were obtained in a cohort of 37 subjects (17 control subjects and 20 subjects with PD). The subjects in the PD group were clinically diagnosed PD patients with an average Unified Parkinsonian Disease Rating Scale (UPDRS)-III score of 23.2 ± 9.3. DTI data were analyzed using SN ROIs defined by neuromelanin-sensitive MRI and, for comparison, with ROIs defined on T2 -weighted images (b = 0 images). RESULTS Compared with control subjects, significantly lower fractional anisotropy was observed in PD in the neuromelanin SN ROI but not in the ROI derived from the T2 -weighted image. This decrease was largest in the rostral and lateral portions of the neuromelanin volume, which were found to have more hypointensity in the T2 -weighted image and, presumably, higher iron content in the PD group. In addition, a larger decrease in fractional anisotropy was seen in the SN region of interest on the side contralateral to the side exhibiting more severe symptoms. These results indicate that the use of neuromelanin sensitive MRI to define the ROI in the SN for analyzing DTI data leads to more significant results, enhancing the robustness of DTI study and DTI based biomarkers of PD. Hum Brain Mapp 37:2547-2556, 2016. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- Jason Langley
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia
| | | | - Michael Merritt
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia
| | - Xiangchuan Chen
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia
| | | | - Michael Silver
- Department of Neurology, Emory University, Atlanta, Georgia
| | | | - Xiaoping Hu
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia
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Detection of changes in the ventral tegmental area of patients with schizophrenia using neuromelanin-sensitive MRI. Neuroreport 2016; 27:289-94. [DOI: 10.1097/wnr.0000000000000530] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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119
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The substantia nigra and ventral tegmental dopaminergic neurons from development to degeneration. J Chem Neuroanat 2016; 76:98-107. [PMID: 26859066 DOI: 10.1016/j.jchemneu.2016.02.001] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2015] [Revised: 01/25/2016] [Accepted: 02/03/2016] [Indexed: 12/20/2022]
Abstract
The pathology of Parkinson's disease (PD) is characterised by the loss of neurons in the substantia nigra parcompacta (A9), which results in the insufficient release of dopamine, and the appearance of motor symptoms. Not all neurons in the A9 subregions degenerate in PD, and the dopaminergic (DA) neurons located in the neighboring ventral tegmental area (A10) are relatively resistant to PD pathogenesis. An increasing number of quantitative studies using human tissue samples of these brain regions have revealed important biological differences. In this review, we first describe current knowledge on the multi-segmental neuromere origin of these DA neurons. We then compare the continued transcription factor and protein expression profile and morphological differences distinguishing subregions within the A9 substantia nigra, and between A9 and A10 DA neurons. We conclude that the expression of three types of factors and proteins contributes to the diversity observed in these DA neurons and potentially to their differential vulnerability to PD. In particular, the specific axonal structure of A9 neurons and the way A9 neurons maintain their DA usage makes them easily exposed to energy deficits, calcium overload and oxidative stress, all contributing to their decreased survival in PD. We highlight knowledge gaps in our understanding of the cellular biomarkers for and their different functions in DA neurons, knowledge which may assist to identify underpinning disease mechansims that could be targeted for the treatment of any subregional dysfunction and loss of these DA neurons.
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Algarni MA, Stoessl AJ. The role of biomarkers and imaging in Parkinson’s disease. Expert Rev Neurother 2016; 16:187-203. [DOI: 10.1586/14737175.2016.1135056] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
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Sung YH, Noh Y, Lee J, Kim EY. Drug-induced Parkinsonism versus Idiopathic Parkinson Disease: Utility of Nigrosome 1 with 3-T Imaging. Radiology 2015; 279:849-58. [PMID: 26690908 DOI: 10.1148/radiol.2015151466] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Purpose To explore the utility of nigrosome 1 with 3-T magnetic resonance (MR) imaging to differentiate idiopathic Parkinson disease (IPD) from drug-induced parkinsonism (DIP). Materials and Methods The institutional review board approved this study, and participants gave informed consent. This study enrolled patients with DIP (n = 20) and IPD (n = 29) who underwent N-3-fluoropropyl-2-β-carbomethoxy-3-β-(4-iodophenyl)nortropane ((18)F-FP-CIT) positron emission tomography (PET) and healthy participants (n = 20). All participants underwent 0.5 × 0.5 × 1.0 mm(3) oblique axial three-dimensional multiecho-data image combination imaging to view the nigrosome 1 with 3-T imaging. Two reviewers independently assessed the nigrosome 1 without clinical information. DIP was diagnosed when no abnormality was seen at (18)F-FP-CIT PET. Diagnostic sensitivity, specificity, and accuracy of the nigrosome 1 imaging were evaluated between the IPD and DIP patients and between the IPD patients and healthy participants. Interrater agreement was assessed with Cohen κ. Results Both reviewers agreed in 63 of 69 participants (91.3%) for the presence of any abnormality on either side of the nigrosome 1 (κ = 0.825). Findings in all 29 IPD patients (100%) and three of 20 DIP patients (15%) were rated as abnormal and in 17 of 20 DIP patients (85%) they were interpreted as normal on the basis of imaging of the nitgrosome 1 (sensitivity, 100% (29 of 29); specificity, 85.0% (17 of 20); accuracy, 93.9% (46 of 49) between IPD and DIP patients). Findings in 3 of 20 healthy participants (15.0%) were interpreted as abnormal on the basis of imaging the nigrosome 1 while in the other 17 of 20 healthy participants (85.0%) they were rated as normal (sensitivity, 100% [29 of 29]; specificity, 85.0% [17 of 20]; accuracy, 93.9% [46 of 49] between IPD patients and healthy participants [κ = 0.831]). Conclusion The imaging of nigrosome 1 with 3-T imaging can differentiate DIP from IPD with high accuracy and may help to screen patients who need dopamine transporter imaging in those suspected of having DIP. (©) RSNA, 2015 Online supplemental material is available for this article.
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Affiliation(s)
- Young Hee Sung
- From the Departments of Neurology (Y.H.S., Y.N.) and Radiology (E.Y.K.), Gachon University Gil Medical Center, 21 Namdong-daero 774 beon-gil, Namdong-gu, Incheon 21565, South Korea; and Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea (J.L.)
| | - Young Noh
- From the Departments of Neurology (Y.H.S., Y.N.) and Radiology (E.Y.K.), Gachon University Gil Medical Center, 21 Namdong-daero 774 beon-gil, Namdong-gu, Incheon 21565, South Korea; and Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea (J.L.)
| | - Jongho Lee
- From the Departments of Neurology (Y.H.S., Y.N.) and Radiology (E.Y.K.), Gachon University Gil Medical Center, 21 Namdong-daero 774 beon-gil, Namdong-gu, Incheon 21565, South Korea; and Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea (J.L.)
| | - Eung Yeop Kim
- From the Departments of Neurology (Y.H.S., Y.N.) and Radiology (E.Y.K.), Gachon University Gil Medical Center, 21 Namdong-daero 774 beon-gil, Namdong-gu, Incheon 21565, South Korea; and Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea (J.L.)
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Weingarten CP, Sundman MH, Hickey P, Chen NK. Neuroimaging of Parkinson's disease: Expanding views. Neurosci Biobehav Rev 2015; 59:16-52. [PMID: 26409344 PMCID: PMC4763948 DOI: 10.1016/j.neubiorev.2015.09.007] [Citation(s) in RCA: 101] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2015] [Revised: 09/07/2015] [Accepted: 09/15/2015] [Indexed: 12/14/2022]
Abstract
Advances in molecular and structural and functional neuroimaging are rapidly expanding the complexity of neurobiological understanding of Parkinson's disease (PD). This review article begins with an introduction to PD neurobiology as a foundation for interpreting neuroimaging findings that may further lead to more integrated and comprehensive understanding of PD. Diverse areas of PD neuroimaging are then reviewed and summarized, including positron emission tomography, single photon emission computed tomography, magnetic resonance spectroscopy and imaging, transcranial sonography, magnetoencephalography, and multimodal imaging, with focus on human studies published over the last five years. These included studies on differential diagnosis, co-morbidity, genetic and prodromal PD, and treatments from L-DOPA to brain stimulation approaches, transplantation and gene therapies. Overall, neuroimaging has shown that PD is a neurodegenerative disorder involving many neurotransmitters, brain regions, structural and functional connections, and neurocognitive systems. A broad neurobiological understanding of PD will be essential for translational efforts to develop better treatments and preventive strategies. Many questions remain and we conclude with some suggestions for future directions of neuroimaging of PD.
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Affiliation(s)
- Carol P Weingarten
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, United States.
| | - Mark H Sundman
- Brain Imaging and Analysis Center, Duke University Medical Center, United States
| | - Patrick Hickey
- Department of Neurology, Duke University School of Medicine, United States
| | - Nan-kuei Chen
- Brain Imaging and Analysis Center, Duke University Medical Center, United States; Department of Radiology, Duke University School of Medicine, United States
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