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Shah A, Prasad S, Indoria A, Pal PK, Saini J, Ingalhalikar M. Free water imaging in Parkinson's disease and atypical parkinsonian disorders. J Neurol 2024; 271:2521-2528. [PMID: 38265472 DOI: 10.1007/s00415-024-12184-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 12/28/2023] [Accepted: 12/30/2023] [Indexed: 01/25/2024]
Abstract
BACKGROUND Free water (FW)-corrected diffusion measures are more precise compared to standard diffusion measures. This study comprehensively evaluates FW and corrected diffusion metrics for whole brain white and deep gray matter (WM, GM) structures in patients with Parkinson's disease (PD), progressive supranuclear palsy (PSP) and multiple system atrophy (MSA) and attempts to ascertain the probable patterns of WM abnormalities. METHOD Diffusion MRI was acquired for subjects with PD (n = 133), MSA (n = 25), PSP (n = 30) and matched healthy controls (HC) (n = 99, n = 24, n = 12). Diffusion metrics of FA, MD, AD, RD were generated and FW, corrected FA maps were calculated using a bi-tensor model. TBSS was carried out at 5000 permutations with significance at p < 0.05. For GM, diffusivity maps were extracted from the basal ganglia, and analyzed at an FDR with p < 0.05. RESULTS Compared to HC, PD showed focal changes in FW. MSA showed changes in the cerebellum and brainstem, and PSP showed increase in FW involving supratentorial WM and midbrain. All three showed increased substantia nigra FW. MSA, PSP demonstrated increased FW in bilateral putamen. PD showed increased FW in left GP externa, and bilateral thalamus. Compared to HC, MSA had increased FW in bilateral GP interna, and left thalamic. PSP had an additional increase in FW of the right GP externa, right GP interna, and bilateral thalamus. CONCLUSION The present study demonstrated definitive differences in the patterns of FW alterations between PD and atypical parkinsonian disorders suggesting the possibility of whole brain FW maps being used as markers for diagnosis of these disorders.
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Affiliation(s)
- Apurva Shah
- Symbiosis Center for Medical Image Analysis and Symbiosis Institute of Technology, Symbiosis International University, Lavale, Mulshi, Pune, 412115, Maharashtra, India
| | - Shweta Prasad
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neuro Sciences (NIMHANS), Hosur Road, Bengaluru, 560029, Karnataka, India
| | - Abhilasha Indoria
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neuro Sciences (NIMHANS), Hosur Road, Bengaluru, 560029, Karnataka, India
| | - Pramod Kumar Pal
- Department of Neurology, National Institute of Mental Health and Neuro Sciences (NIMHANS), Hosur Road, Bengaluru, 560029, Karnataka, India
| | - Jitender Saini
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neuro Sciences (NIMHANS), Hosur Road, Bengaluru, 560029, Karnataka, India
| | - Madhura Ingalhalikar
- Symbiosis Center for Medical Image Analysis and Symbiosis Institute of Technology, Symbiosis International University, Lavale, Mulshi, Pune, 412115, Maharashtra, India.
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2
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Kawabata K, Krismer F, Heim B, Hussl A, Mueller C, Scherfler C, Gizewski ER, Seppi K, Poewe W. A Blinded Evaluation of Brain Morphometry for Differential Diagnosis of Atypical Parkinsonism. Mov Disord Clin Pract 2024; 11:381-390. [PMID: 38314609 PMCID: PMC10982602 DOI: 10.1002/mdc3.13987] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Accepted: 01/14/2024] [Indexed: 02/06/2024] Open
Abstract
BACKGROUND Advanced imaging techniques have been studied for differential diagnosis between PD, MSA, and PSP. OBJECTIVES This study aims to validate the utility of individual voxel-based morphometry techniques for atypical parkinsonism in a blinded fashion. METHODS Forty-eight healthy controls (HC) T1-WI were used to develop a referential dataset and fit a general linear model after segmentation into gray matter (GM) and white matter (WM) compartments. Segmented GM and WM with PD (n = 96), MSA (n = 18), and PSP (n = 20) were transformed into z-scores using the statistics of referential HC and individual voxel-based z-score maps were generated. An imaging diagnosis was assigned by two independent raters (trained and untrained) blinded to clinical information and final diagnosis. Furthermore, we developed an observer-independent index for ROI-based automated differentiation. RESULTS The diagnostic performance using voxel-based z-score maps by rater 1 and rater 2 for MSA yielded sensitivities: 0.89, 0.94 (95% CI: 0.74-1.00, 0.84-1.00), specificities: 0.94, 0.80 (0.90-0.98, 0.73-0.87); for PSP, sensitivities: 0.85, 0.90 (0.69-1.00, 0.77-1.00), specificities: 0.98, 0.94 (0.96-1.00, 0.90-0.98). Interrater agreement was good for MSA (Cohen's kappa: 0.61), and excellent for PSP (0.84). Receiver operating characteristic analysis using the ROI-based new index showed an area under the curve (AUC): 0.89 (0.77-1.00) for MSA, and 0.99 (0.98-1.00) for PSP. CONCLUSIONS These evaluations provide support for the utility of this imaging technique in the differential diagnosis of atypical parkinsonism demonstrating a remarkably high differentiation accuracy for PSP, suggesting potential use in clinical settings in the future.
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Affiliation(s)
- Kazuya Kawabata
- Department of NeurologyMedical University InnsbruckInnsbruckAustria
- Department of NeurologyNagoya University Graduate School of MedicineNagoyaJapan
| | - Florian Krismer
- Department of NeurologyMedical University InnsbruckInnsbruckAustria
- Neuroimaging Research Core FacilityMedical University InnsbruckInnsbruckAustria
| | - Beatrice Heim
- Department of NeurologyMedical University InnsbruckInnsbruckAustria
- Neuroimaging Research Core FacilityMedical University InnsbruckInnsbruckAustria
| | - Anna Hussl
- Department of NeurologyMedical University InnsbruckInnsbruckAustria
| | | | - Christoph Scherfler
- Department of NeurologyMedical University InnsbruckInnsbruckAustria
- Neuroimaging Research Core FacilityMedical University InnsbruckInnsbruckAustria
| | - Elke R. Gizewski
- Neuroimaging Research Core FacilityMedical University InnsbruckInnsbruckAustria
- Department of NeuroradiologyMedical University InnsbruckInnsbruckAustria
| | - Klaus Seppi
- Department of NeurologyMedical University InnsbruckInnsbruckAustria
- Neuroimaging Research Core FacilityMedical University InnsbruckInnsbruckAustria
| | - Werner Poewe
- Department of NeurologyMedical University InnsbruckInnsbruckAustria
- Neuroimaging Research Core FacilityMedical University InnsbruckInnsbruckAustria
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Virameteekul S, Revesz T, Jaunmuktane Z, Warner TT, De Pablo-Fernández E. Pathological Validation of the MDS Criteria for the Diagnosis of Multiple System Atrophy. Mov Disord 2023; 38:444-452. [PMID: 36606594 DOI: 10.1002/mds.29304] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 12/09/2022] [Accepted: 12/13/2022] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND The recent International Parkinson and Movement Disorder Society diagnostic criteria for multiple system atrophy (MDS-MSA) have been developed to improve diagnostic accuracy although their diagnostic properties have not been evaluated. OBJECTIVES The aims were to validate the MDS-MSA diagnostic criteria against neuropathological diagnosis and compare their diagnostic performance to previous criteria and diagnosis in clinical practice. METHODS Consecutive patients with sporadic, progressive, adult-onset parkinsonism, or cerebellar ataxia from the Queen Square Brain Bank between 2009 and 2019 were selected and divided based on neuropathological diagnosis into MSA and non-MSA. Medical records were systematically reviewed, and clinical diagnosis was documented by retrospectively applying the MDS-MSA criteria, second consensus criteria, and diagnosis according to treating clinicians at early (within 3 years of symptom onset) and final stages. Diagnostic parameters (sensitivity, specificity, positive/negative predictive value, and accuracy) were calculated using neuropathological diagnosis as gold standard and compared between different criteria. RESULTS Three hundred eighteen patients (103 MSA and 215 non-MSA) were included, comprising 248 patients with parkinsonism and 70 with cerebellar ataxia. Clinically probable MDS-MSA showed excellent sensitivity (95.1%), specificity (94.0%), and accuracy (94.3%), although their sensitivity at early stages was modest (62.1%). Clinically probable MDS-MSA outperformed diagnosis by clinicians and by second consensus criteria. Clinically established MDS-MSA showed perfect specificity (100%) even at early stages although to the detriment of low sensitivity. MDS-MSA diagnostic accuracy did not differ according to clinical presentation (ataxia vs. parkinsonism). CONCLUSIONS MDS-MSA criteria demonstrated excellent diagnostic performance against neuropathological diagnosis and are useful diagnostic tools for clinical practice and research. © 2023 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Sasivimol Virameteekul
- Queen Square Brain Bank for Neurological Disorders, UCL Queen Square Institute of Neurology, London, United Kingdom
- Reta Lila Weston Institute of Neurological Studies, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Tamas Revesz
- Queen Square Brain Bank for Neurological Disorders, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Zane Jaunmuktane
- Queen Square Brain Bank for Neurological Disorders, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Thomas T Warner
- Queen Square Brain Bank for Neurological Disorders, UCL Queen Square Institute of Neurology, London, United Kingdom
- Reta Lila Weston Institute of Neurological Studies, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Eduardo De Pablo-Fernández
- Queen Square Brain Bank for Neurological Disorders, UCL Queen Square Institute of Neurology, London, United Kingdom
- Reta Lila Weston Institute of Neurological Studies, UCL Queen Square Institute of Neurology, London, United Kingdom
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Watanabe H, Shima S, Mizutani Y, Ueda A, Ito M. Multiple System Atrophy: Advances in Diagnosis and Therapy. J Mov Disord 2023; 16:13-21. [PMID: 36537066 PMCID: PMC9978260 DOI: 10.14802/jmd.22082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2022] [Accepted: 08/28/2022] [Indexed: 12/24/2022] Open
Abstract
This review summarizes improvements in understanding the pathophysiology and early clinical symptoms of multiple system atrophy (MSA) and advancements in diagnostic methods and disease-modifying therapies for the condition. In 2022, the Movement Disorder Society proposed new diagnostic criteria to develop disease-modifying therapies and promote clinical trials of MSA since the second consensus was proposed in 2008. Regarding pathogenesis, cutting-edge findings have accumulated on the interactions of α-synuclein, neuroinflammation, and oligodendroglia with neurons. In neuroimaging, introducing artificial intelligence, machine learning, and deep learning has notably improved diagnostic accuracy and individual analyses. Advancements in treatment have also been achieved, including immunotherapy therapy against α-synuclein and serotonin-targeted and mesenchymal stem cell therapies, which are thought to affect several aspects of the disease, including neuroinflammation. The accelerated progress in clarifying the pathogenesis of MSA over the past few years and the development of diagnostic techniques for detecting early-stage MSA are expected to facilitate the development of disease-modifying therapies for one of the most intractable neurodegenerative diseases.
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Affiliation(s)
- Hirohisa Watanabe
- Department of Neurology, Fujita Health University, School of Medicine, Toyoake, Japan,Corresponding author: Hirohisa Watanabe, MD, PhD Department of Neurology, Fujita Health University, School of Medicine, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake 470-1192, Japan / Tel: +81- 562-93-9295 / Fax: +81-562-93-1856 / E-mail:
| | - Sayuri Shima
- Department of Neurology, Fujita Health University, School of Medicine, Toyoake, Japan
| | - Yasuaki Mizutani
- Department of Neurology, Fujita Health University, School of Medicine, Toyoake, Japan
| | - Akihiro Ueda
- Department of Neurology, Fujita Health University, School of Medicine, Toyoake, Japan,Department of Neurology, Fujita Health University Okazaki Medical Center, Okazaki, Japan
| | - Mizuki Ito
- Department of Neurology, Fujita Health University, School of Medicine, Toyoake, Japan,Department of Neurology, Fujita Health University Bantane Hospital, Nagoya, Japan
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Tinaz S. Magnetic resonance imaging modalities aid in the differential diagnosis of atypical parkinsonian syndromes. Front Neurol 2023; 14:1082060. [PMID: 36816565 PMCID: PMC9932598 DOI: 10.3389/fneur.2023.1082060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Accepted: 01/16/2023] [Indexed: 02/05/2023] Open
Abstract
Accurate and timely diagnosis of atypical parkinsonian syndromes (APS) remains a challenge. Especially early in the disease course, the clinical manifestations of the APS overlap with each other and with those of idiopathic Parkinson's disease (PD). Recent advances in magnetic resonance imaging (MRI) technology have introduced promising imaging modalities to aid in the diagnosis of APS. Some of these MRI modalities are also included in the updated diagnostic criteria of APS. Importantly, MRI is safe for repeated use and more affordable and accessible compared to nuclear imaging. These advantages make MRI tools more appealing for diagnostic purposes. As the MRI field continues to advance, the diagnostic use of these techniques in APS, alone or in combination, are expected to become commonplace in clinical practice.
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Affiliation(s)
- Sule Tinaz
- Division of Movement Disorders, Department of Neurology, Yale School of Medicine, New Haven, CT, United States
- Department of Neurology, Clinical Neurosciences Imaging Center, Yale School of Medicine, New Haven, CT, United States
- *Correspondence: Sule Tinaz ✉
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Yang XL, Guo Y, Chen SF, Cui M, Shao RR, Huang YY, Luo YF, Dong ZY, Dong Q, Wu DH, Yu JT. Cerebral Small Vessel Disease Is Associated with Motor, Cognitive, and Emotional Dysfunction in Multiple System Atrophy. JOURNAL OF PARKINSON'S DISEASE 2023; 13:1239-1252. [PMID: 37742661 PMCID: PMC10657662 DOI: 10.3233/jpd-230166] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 09/01/2023] [Indexed: 09/26/2023]
Abstract
BACKGROUND Cerebral small vessel disease (CSVD) has not been systematically studied in patients with multiple system atrophy (MSA). OBJECTIVE We sought to explore whether MSA patients suffer from a heavier CSVD burden relative to healthy individuals and whether CSVD has a relationship with motor, cognitive, and emotional dysfunction in patients with MSA. METHODS This study consecutively recruited 190 MSA patients and 190 matched healthy controls whose overall CSVD burden and single CSVD imaging markers (including white matter hyperintensity (WMH), microbleeds, lacunes, and enlarged perivascular spaces (EPVS)) were measured. Of the MSA patients, 118 completed multi-dimensional outcome assessments. Spearman's correlations and multivariable linear regressions were performed. RESULTS We observed a greater burden of overall CSVD, WMH, and EPVS in MSA patients compared with controls, but not for microbleeds and lacunes. Motor dysfunction and cognitive impairment were significantly worse in subjects with severe CSVD than those with none-to-mild CSVD. In patients with MSA, the severity of CSVD burden was positively associated with motor impairments as measured by the Unified Multiple System Atrophy Rating Scale-II (β= 2.430, p = 0.039) and Scale for the Assessment and Rating of Ataxia (β= 1.882, p = 0.015). Of CSVD imaging markers, different associations with MSA outcomes were displayed. WMH was associated with motor, cognitive, and emotional deficits, while the EPVS in the centrum semiovale, basal ganglia, and hippocampus regions was correlated only with motor severity, anxiety, and cognition, respectively. Similar findings were noted in MSA-cerebellar and MSA-parkinsonian patients. CONCLUSIONS Concomitant CSVD may be correlated with worse multi-dimensional dysfunction in patients with MSA.
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Affiliation(s)
- Xiao-Li Yang
- Department of Neurology, Shanghai Fifth People’s Hospital, Fudan University, Shanghai, China
| | - Yu Guo
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China
| | - Shu-Fen Chen
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China
| | - Mei Cui
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China
| | - Rong-Rong Shao
- Department of Neurology, Shanghai Fifth People’s Hospital, Fudan University, Shanghai, China
| | - Yu-Yuan Huang
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China
| | - Yu-Fan Luo
- Department of Neurology, Shanghai Fifth People’s Hospital, Fudan University, Shanghai, China
| | - Zhi-Yuan Dong
- Department of Neurology, Shanghai Fifth People’s Hospital, Fudan University, Shanghai, China
| | - Qiang Dong
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China
| | - Dan-Hong Wu
- Department of Neurology, Shanghai Fifth People’s Hospital, Fudan University, Shanghai, China
| | - Jin-Tai Yu
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China
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Pasquini J, Firbank MJ, Ceravolo R, Silani V, Pavese N. Diffusion Magnetic Resonance Imaging Microstructural Abnormalities in Multiple System Atrophy: A Comprehensive Review. Mov Disord 2022; 37:1963-1984. [PMID: 36036378 DOI: 10.1002/mds.29195] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2022] [Revised: 07/22/2022] [Accepted: 08/01/2022] [Indexed: 01/07/2023] Open
Abstract
Multiple system atrophy (MSA) is a neurodegenerative disease characterized by autonomic failure, ataxia, and/or parkinsonism. Its prominent pathological alterations can be investigated using diffusion magnetic resonance imaging (dMRI), a technique that exploits the characteristics of water random motion inside brain tissue. The aim of this report was to review currently available literature on the application of dMRI in MSA and to describe microstructural abnormalities, diagnostic applications, and pathophysiological correlates. Sixty-four published studies involving microstructural investigation using dMRI in MSA were included. Widespread microstructural abnormalities of white matter were described, especially in the middle cerebellar peduncle, corticospinal tract, and hemispheric fibers. Gray matter degeneration was identified as well, with diffuse involvement of subcortical structures, especially in the putamina. Diagnostic applications of dMRI were mostly explored for the differential diagnosis between MSA parkinsonism and Parkinson's disease. Recently, machine learning algorithms for image processing and disease classification have demonstrated high diagnostic accuracy, showing potential for translation into clinical practice. To a lesser extent, clinical correlates of microstructural abnormalities have also been investigated, and abnormalities related to motor, ocular, and cognitive impairments were described. dMRI in MSA has contributed to in vivo identification of known pathological abnormalities. Translation into clinical practice of the latest advancements for the differential diagnosis between MSA and other forms of parkinsonism seems feasible. Current limitations involve the possibility of correctly diagnosing MSA in the very early stages, when the clinical diagnosis is most uncertain. Furthermore, pathophysiological correlates of microstructural abnormalities remain understudied. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Jacopo Pasquini
- Clinical Ageing Research Unit, Newcastle University, Newcastle upon Tyne, United Kingdom.,Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Michael J Firbank
- Positron Emission Tomography Centre, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Roberto Ceravolo
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy.,Neurodegenerative Diseases Center, Azienda Ospedaliero Universitaria Pisana, Pisa, Italy
| | - Vincenzo Silani
- Department of Neurology and Laboratory of Neuroscience, Istituto Auxologico Italiano IRCCS, Milan, Italy.,Department of Pathophysiology and Transplantation, Dino Ferrari Center, Università degli Studi di Milano, Milan, Italy
| | - Nicola Pavese
- Clinical Ageing Research Unit, Newcastle University, Newcastle upon Tyne, United Kingdom.,Department of Nuclear Medicine and PET Centre, Aarhus University Hospital, Aarhus, Denmark
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Pang H, Yu Z, Yu H, Chang M, Cao J, Li Y, Guo M, Liu Y, Cao K, Fan G. Multimodal striatal neuromarkers in distinguishing parkinsonian variant of multiple system atrophy from idiopathic Parkinson's disease. CNS Neurosci Ther 2022; 28:2172-2182. [PMID: 36047435 PMCID: PMC9627351 DOI: 10.1111/cns.13959] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 08/10/2022] [Accepted: 08/11/2022] [Indexed: 02/06/2023] Open
Abstract
AIMS To develop an automatic method of classification for parkinsonian variant of multiple system atrophy (MSA-P) and Idiopathic Parkinson's disease (IPD) in early to moderately advanced stages based on multimodal striatal alterations and identify the striatal neuromarkers for distinction. METHODS 77 IPD and 75 MSA-P patients underwent 3.0 T multimodal MRI comprising susceptibility-weighted imaging, resting-state functional magnetic resonance imaging, T1-weighted imaging, and diffusion tensor imaging. Iron-radiomic features, volumes, functional and diffusion scalars of bilateral 10 striatal subregions were calculated and provided to the support vector machine for classification RESULTS: A combination of iron-radiomic features, function, diffusion, and volumetric measures optimally distinguished IPD and MSA-P in the testing dataset (accuracy 0.911 and area under the receiver operating characteristic curves [AUC] 0.927). The diagnostic performance further improved when incorporating clinical variables into the multimodal model (accuracy 0.934 and AUC 0.953). The most crucial factor for classification was the functional activity of the left dorsolateral putamen. CONCLUSION The machine learning algorithm applied to multimodal striatal dysfunction depicted dorsal striatum and supervening prefrontal lobe and cerebellar dysfunction through the frontostriatal and cerebello-striatal connections and facilitated accurate classification between IPD and MSA-P. The dorsolateral putamen was the most valuable neuromarker for the classification.
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Affiliation(s)
- Huize Pang
- Department of RadiologyThe first Affiliated Hospital of China Medical UniversityShenyangChina
| | - Ziyang Yu
- School of MedicineXiamen UniversityXiamenChina
| | - Hongmei Yu
- Department of NeurologyThe first Affiliated Hospital of China Medical UniversityShenyangChina
| | - Miao Chang
- Department of RadiologyThe first Affiliated Hospital of China Medical UniversityShenyangChina
| | - Jibin Cao
- Department of RadiologyThe first Affiliated Hospital of China Medical UniversityShenyangChina
| | - Yingmei Li
- Department of RadiologyThe first Affiliated Hospital of China Medical UniversityShenyangChina
| | - Miaoran Guo
- Department of RadiologyThe first Affiliated Hospital of China Medical UniversityShenyangChina
| | - Yu Liu
- Department of RadiologyThe first Affiliated Hospital of China Medical UniversityShenyangChina
| | - Kaiqiang Cao
- Department of RadiologyThe first Affiliated Hospital of China Medical UniversityShenyangChina
| | - Guoguang Fan
- Department of RadiologyThe first Affiliated Hospital of China Medical UniversityShenyangChina
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9
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Abstract
Multiple system atrophy (MSA) is a rare neurodegenerative disease that is characterized by neuronal loss and gliosis in multiple areas of the central nervous system including striatonigral, olivopontocerebellar and central autonomic structures. Oligodendroglial cytoplasmic inclusions containing misfolded and aggregated α-synuclein are the histopathological hallmark of MSA. A firm clinical diagnosis requires the presence of autonomic dysfunction in combination with parkinsonism that responds poorly to levodopa and/or cerebellar ataxia. Clinical diagnostic accuracy is suboptimal in early disease because of phenotypic overlaps with Parkinson disease or other types of degenerative parkinsonism as well as with other cerebellar disorders. The symptomatic management of MSA requires a complex multimodal approach to compensate for autonomic failure, alleviate parkinsonism and cerebellar ataxia and associated disabilities. None of the available treatments significantly slows the aggressive course of MSA. Despite several failed trials in the past, a robust pipeline of putative disease-modifying agents, along with progress towards early diagnosis and the development of sensitive diagnostic and progression biomarkers for MSA, offer new hope for patients.
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10
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Zhang P, Chen J, Cai T, He C, Li Y, Li X, Chen Z, Wang L, Zhang Y. Quantitative susceptibility mapping and blood neurofilament light chain differentiate between parkinsonian disorders. Front Aging Neurosci 2022; 14:909552. [PMID: 35992605 PMCID: PMC9389149 DOI: 10.3389/fnagi.2022.909552] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 06/27/2022] [Indexed: 11/13/2022] Open
Abstract
Objectives We employed quantitative susceptibility mapping (QSM) to assess iron deposition in parkinsonian disorders and explored whether combining QSM values and neurofilament light (NfL) chain levels can improve the accuracy of distinguishing Parkinson’s disease (PD) from multiple system atrophy (MSA) and progressive supranuclear palsy (PSP). Materials and methods Forty-seven patients with PD, 28 patients with MSA, 18 patients with PSP, and 28 healthy controls (HC) were enrolled, and QSM data were reconstructed. Susceptibility values in the bilateral globus pallidus (GP), putamen (PUT), caudate nucleus (CN), red nucleus (RN), substantia nigra (SN), and dentate nucleus (DN) were obtained. Plasma NfL levels of 47 PD, 18 MSA, and 14 PSP patients and 22 HC were measured by ultrasensitive Simoa technology. Results The highest diagnostic accuracy distinguishing MSA from PD patients was observed with increased susceptibility values in CN (AUC: 0.740). The susceptibility values in RN yielded the highest diagnostic performance for distinguishing PSP from PD patients (AUC: 0.829). Plasma NfL levels were significantly higher in the MSA and PSP groups than in PD and HC groups. Combining the susceptibility values in the RN and plasma NfL levels improved the diagnostic performance for PSP vs. PD (AUC: 0.904), whereas plasma NfL levels had higher diagnostic accuracy for MSA vs. PD (AUC: 0.877). Conclusion The exploratory study indicates different patterns of iron accumulation in deep gray matter nuclei in Parkinsonian disorders. Combining QSM values with NfL levels may be a promising biomarker for distinguishing PSP from PD, whereas plasma NfL may be a reliable biomarker for differentiating MSA from PD. QSM and NfL measures appeared to have low accuracy for separating PD from controls.
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Affiliation(s)
- Piao Zhang
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Junling Chen
- Department of Neurology, Shantou Central Hospital, Shantou, China
| | - Tongtong Cai
- Department of Neurology, Shantou Central Hospital, Shantou, China
| | - Chentao He
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Yan Li
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Xiaohong Li
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Zhenzhen Chen
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Lijuan Wang
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Yuhu Zhang
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- *Correspondence: Yuhu Zhang,
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Mazzucchi S, Del Prete E, Costagli M, Frosini D, Paoli D, Migaleddu G, Cecchi P, Donatelli G, Morganti R, Siciliano G, Cosottini M, Ceravolo R. Morphometric imaging and quantitative susceptibility mapping as complementary tools in the diagnosis of parkinsonisms. Eur J Neurol 2022; 29:2944-2955. [PMID: 35700041 PMCID: PMC9545010 DOI: 10.1111/ene.15447] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Revised: 06/02/2022] [Accepted: 06/09/2022] [Indexed: 11/26/2022]
Abstract
Background and purpose In the quest for in vivo diagnostic biomarkers to discriminate Parkinson's disease (PD) from progressive supranuclear palsy (PSP) and multiple system atrophy (MSA, mainly p phenotype), many advanced magnetic resonance imaging (MRI) techniques have been studied. Morphometric indices, such as the Magnetic Resonance Parkinsonism Index (MRPI), demonstrated high diagnostic value in the comparison between PD and PSP. The potential of quantitative susceptibility mapping (QSM) was hypothesized, as increased magnetic susceptibility (Δχ) was reported in the red nucleus (RN) and medial part of the substantia nigra (SNImed) of PSP patients and in the putamen of MSA patients. However, disease‐specific susceptibility values for relevant regions of interest are yet to be identified. The aims of the study were to evaluate the diagnostic potential of a multimodal MRI protocol combining morphometric and QSM imaging in patients with determined parkinsonisms and to explore its value in a population of undetermined cases. Method Patients with suspected degenerative parkinsonism underwent clinical evaluation, 3 T brain MRI and clinical follow‐up. The MRPI was manually calculated on T1‐weighted images. QSM maps were generated from 3D multi‐echo T2*‐weighted sequences. Results In determined cases the morphometric evaluation confirmed optimal diagnostic accuracy in the comparison between PD and PSP but failed to discriminate PD from MSA‐p. Significant nigral and extranigral differences were found with QSM. RN Δχ showed excellent diagnostic accuracy in the comparison between PD and PSP and good accuracy in the comparison of PD and MSA‐p. Optimal susceptibility cut‐off values of RN and SNImed were tested in undetermined cases in addition to MRPI. Conclusions A combined use of morphometric imaging and QSM could improve the diagnostic phase of degenerative parkinsonisms.
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Affiliation(s)
- Sonia Mazzucchi
- Neurology Unit, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Eleonora Del Prete
- Neurology Unit, Department of Medical Specialties, Azienda Ospedaliero-Universitaria Pisana, Pisa, Italy
| | - Mauro Costagli
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Sciences (DINOGMI), University of Genoa, Genoa, Italy.,Laboratory of Medical Physics and Magnetic Resonance, IRCCS Stella Maris Foundation, Pisa, Italy
| | - Daniela Frosini
- Neurology Unit, Department of Medical Specialties, Azienda Ospedaliero-Universitaria Pisana, Pisa, Italy
| | - Davide Paoli
- Neurology Unit, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | | | - Paolo Cecchi
- Neuroradiology Unit, Azienda Ospedaliero-Universitaria Pisana, Pisa, Italy
| | - Graziella Donatelli
- Neuroradiology Unit, Azienda Ospedaliero-Universitaria Pisana, Pisa, Italy.,Imago7 Research Foundation, Pisa, Italy
| | | | - Gabriele Siciliano
- Neurology Unit, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Mirco Cosottini
- Imago7 Research Foundation, Pisa, Italy.,Neuroradiology Unit, Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy
| | - Roberto Ceravolo
- Neurology Unit, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy.,Centre for Neurodegenerative Diseases, Parkinson's Disease and Movement Disorders, Azienda Ospedaliero-Universitaria Pisana, Pisa, Italy
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12
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Wenning GK, Stankovic I, Vignatelli L, Fanciulli A, Calandra-Buonaura G, Seppi K, Palma JA, Meissner WG, Krismer F, Berg D, Cortelli P, Freeman R, Halliday G, Höglinger G, Lang A, Ling H, Litvan I, Low P, Miki Y, Panicker J, Pellecchia MT, Quinn N, Sakakibara R, Stamelou M, Tolosa E, Tsuji S, Warner T, Poewe W, Kaufmann H. The Movement Disorder Society Criteria for the Diagnosis of Multiple System Atrophy. Mov Disord 2022; 37:1131-1148. [PMID: 35445419 PMCID: PMC9321158 DOI: 10.1002/mds.29005] [Citation(s) in RCA: 218] [Impact Index Per Article: 109.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Revised: 01/25/2022] [Accepted: 02/28/2022] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND The second consensus criteria for the diagnosis of multiple system atrophy (MSA) are widely recognized as the reference standard for clinical research, but lack sensitivity to diagnose the disease at early stages. OBJECTIVE To develop novel Movement Disorder Society (MDS) criteria for MSA diagnosis using an evidence-based and consensus-based methodology. METHODS We identified shortcomings of the second consensus criteria for MSA diagnosis and conducted a systematic literature review to answer predefined questions on clinical presentation and diagnostic tools relevant for MSA diagnosis. The criteria were developed and later optimized using two Delphi rounds within the MSA Criteria Revision Task Force, a survey for MDS membership, and a virtual Consensus Conference. RESULTS The criteria for neuropathologically established MSA remain unchanged. For a clinical MSA diagnosis a new category of clinically established MSA is introduced, aiming for maximum specificity with acceptable sensitivity. A category of clinically probable MSA is defined to enhance sensitivity while maintaining specificity. A research category of possible prodromal MSA is designed to capture patients in the earliest stages when symptoms and signs are present, but do not meet the threshold for clinically established or clinically probable MSA. Brain magnetic resonance imaging markers suggestive of MSA are required for the diagnosis of clinically established MSA. The number of research biomarkers that support all clinical diagnostic categories will likely grow. CONCLUSIONS This set of MDS MSA diagnostic criteria aims at improving the diagnostic accuracy, particularly in early disease stages. It requires validation in a prospective clinical and a clinicopathological study. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Gregor K Wenning
- Department of Neurology, Innsbruck Medical University, Innsbruck, Austria
| | - Iva Stankovic
- Neurology Clinic, University Clinical Center of Serbia, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | - Luca Vignatelli
- IRCCS, Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | | | - Giovanna Calandra-Buonaura
- IRCCS, Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy.,Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
| | - Klaus Seppi
- Department of Neurology, Innsbruck Medical University, Innsbruck, Austria
| | - Jose-Alberto Palma
- Department of Neurology, Dysautonomia Center, Langone Medical Center, New York University School of Medicine, New York, New York, USA
| | - Wassilios G Meissner
- French Reference Center for MSA, Department of Neurology for Neurodegenerative Diseases, University Hospital Bordeaux, 33076 Bordeaux and Institute of Neurodegenerative Diseases, University Bordeaux, CNRS, Bordeaux, France.,Department of Medicine, University of Otago, Christchurch, and New Zealand Brain Research Institute, Christchurch, New Zealand
| | - Florian Krismer
- Department of Neurology, Innsbruck Medical University, Innsbruck, Austria
| | - Daniela Berg
- Department of Neurodegeneration and Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany.,Department of Neurology, Christian-Albrechts-University Kiel, Kiel, Germany
| | - Pietro Cortelli
- IRCCS, Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy.,Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
| | - Roy Freeman
- Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Glenda Halliday
- Brain and Mind Centre, Faculty of Medicine and Health, School of Medical Sciences, The University of Sydney, Sydney, New South Wales, Australia
| | - Günter Höglinger
- Department of Neurology, Hanover Medical School, Hanover, Germany.,German Center for Neurodegenerative Diseases, Munich, Germany
| | - Anthony Lang
- Edmond J. Safra Program in Parkinson's Disease, University Health Network and the Division of Neurology, University of Toronto, Toronto, Canada
| | - Helen Ling
- Queen Square Brain Bank for Neurological Disorders, UCL Queen Square Institute of Neurology, London, United Kingdom.,Reta Lila Weston Institute of Neurological Studies, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Irene Litvan
- Department of Neurosciences, Parkinson and Other Movement Disorders Center, University of California, San Diego, California, USA
| | - Phillip Low
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Yasuo Miki
- Queen Square Brain Bank for Neurological Disorders, UCL Queen Square Institute of Neurology, London, United Kingdom.,Department of Neuropathology, Institute of Brain Science, Hirosaki University Graduate School of Medicine, Hirosaki, Japan
| | - Jalesh Panicker
- UCL Queen Square Institute of Neurology, London, United Kingdom.,Department of Uro-Neurology, The National Hospital for Neurology and Neurosurgery, Queen Square, London, United Kingdom
| | - Maria Teresa Pellecchia
- Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", Neuroscience Section, University of Salerno, Salerno, Italy
| | - Niall Quinn
- UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Ryuji Sakakibara
- Neurology, Internal Medicine, Sakura Medical Center, Toho University, Sakura, Japan
| | - Maria Stamelou
- Parkinson's Disease and Movement Disorders Department, HYGEIA Hospital, and Aiginiteion Hospital, University of Athens, Athens, Greece.,Philipps University Marburg, Germany and European University of Cyprus, Nicosia, Cyprus
| | - Eduardo Tolosa
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED) Hospital Clínic, IDIBAPS, Universitat de Barcelona, Catalonia, Spain.,Movement Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Catalonia, Spain
| | - Shoji Tsuji
- Department of Molecular Neurology, The University of Tokyo, Graduate School of Medicine, Tokyo, Japan.,International University of Health and Welfare, Chiba, Japan
| | - Tom Warner
- Queen Square Brain Bank for Neurological Disorders, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Werner Poewe
- Department of Neurology, Innsbruck Medical University, Innsbruck, Austria
| | - Horacio Kaufmann
- Department of Neurology, Dysautonomia Center, Langone Medical Center, New York University School of Medicine, New York, New York, USA
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13
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Jucaite A, Cselényi Z, Kreisl WC, Rabiner EA, Varrone A, Carson RE, Rinne JO, Savage A, Schou M, Johnström P, Svenningsson P, Rascol O, Meissner WG, Barone P, Seppi K, Kaufmann H, Wenning GK, Poewe W, Farde L. Glia Imaging Differentiates Multiple System Atrophy from Parkinson's Disease: A Positron Emission Tomography Study with [ 11 C]PBR28 and Machine Learning Analysis. Mov Disord 2021; 37:119-129. [PMID: 34609758 DOI: 10.1002/mds.28814] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 09/06/2021] [Accepted: 09/10/2021] [Indexed: 11/07/2022] Open
Abstract
BACKGROUND The clinical diagnosis of multiple system atrophy (MSA) is challenged by overlapping features with Parkinson's disease (PD) and late-onset ataxias. Additional biomarkers are needed to confirm MSA and to advance the understanding of pathophysiology. Positron emission tomography (PET) imaging of the translocator protein (TSPO), expressed by glia cells, has shown elevations in MSA. OBJECTIVE In this multicenter PET study, we assess the performance of TSPO imaging as a diagnostic marker for MSA. METHODS We analyzed [11 C]PBR28 binding to TSPO using imaging data of 66 patients with MSA and 24 patients with PD. Group comparisons were based on regional analysis of parametric images. The diagnostic readout included visual reading of PET images against clinical diagnosis and machine learning analyses. Sensitivity, specificity, and receiver operating curves were used to discriminate MSA from PD and cerebellar from parkinsonian variant MSA. RESULTS We observed a conspicuous pattern of elevated regional [11 C]PBR28 binding to TSPO in MSA as compared with PD, with "hotspots" in the lentiform nucleus and cerebellar white matter. Visual reading discriminated MSA from PD with 100% specificity and 83% sensitivity. The machine learning approach improved sensitivity to 96%. We identified MSA subtype-specific TSPO binding patterns. CONCLUSIONS We found a pattern of significantly increased regional glial TSPO binding in patients with MSA. Intriguingly, our data are in line with severe neuroinflammation in MSA. Glia imaging may have potential to support clinical MSA diagnosis and patient stratification in clinical trials on novel drug therapies for an α-synucleinopathy that remains strikingly incurable. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Aurelija Jucaite
- PET Science Centre, Personalized Medicine and Biosamples, R&D, AstraZeneca, Stockholm, Sweden.,Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet, Stockholm, Sweden
| | - Zsolt Cselényi
- PET Science Centre, Personalized Medicine and Biosamples, R&D, AstraZeneca, Stockholm, Sweden.,Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet, Stockholm, Sweden
| | - William C Kreisl
- Taub Institute, Department of Neurology, Columbia University Irving Medical Centre, New York, New York, USA
| | - Eugenii A Rabiner
- Invicro, London, UK.,Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Andrea Varrone
- Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet, Stockholm, Sweden
| | | | - Juha O Rinne
- Turku PET Centre, University of Turku and Turku University Hospital, Turku, Finland
| | | | - Magnus Schou
- PET Science Centre, Personalized Medicine and Biosamples, R&D, AstraZeneca, Stockholm, Sweden.,Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet, Stockholm, Sweden
| | - Peter Johnström
- PET Science Centre, Personalized Medicine and Biosamples, R&D, AstraZeneca, Stockholm, Sweden.,Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet, Stockholm, Sweden
| | - Per Svenningsson
- Section of Neurology, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Olivier Rascol
- French MSA Reference Centre, Clinical Investigation Centre CIC1436, Department of Neurosciences and Clinical Pharmacology, NeuroToul COEN Centre, UMR 1 214-ToNIC and University Hospital of Toulouse, INSERM and University of Toulouse 3, Toulouse, France
| | - Wassilios G Meissner
- CRMR AMS, Service de Neurologie-Maladies Neurodégénératives, CHU Bordeaux, Bordeaux, France.,University Bordeaux, CNRS, IMN, UMR 5293, Bordeaux, France.,Department of Medicine, University of Otago, Christchurch, New Zealand Brain Research Institute, Christchurch, New Zealand
| | - Paolo Barone
- Neurodegenerative Disease Centre, University of Salerno, Salerno, Italy
| | - Klaus Seppi
- Department of Neurology, Innsbruck Medical University, Innsbruck, Austria
| | - Horacio Kaufmann
- Department of Medicine, NYU Grossman School of Medicine, New York, New York, USA
| | - Gregor K Wenning
- Division of Clinical Neurobiology, Department of Neurology, Innsbruck Medical University, Innsbruck, Austria
| | - Werner Poewe
- Division of Clinical Neurobiology, Department of Neurology, Innsbruck Medical University, Innsbruck, Austria
| | - Lars Farde
- Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet, Stockholm, Sweden
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14
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Di Luca DG, Lang AE. Is clinical assessment enough? Moving towards early differentiation of neurodegenerative parkinsonisms. Brain 2021; 144:1040-1042. [PMID: 33725090 DOI: 10.1093/brain/awab115] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
This scientific commentary refers to ‘Identification of multiple system atrophy mimicking Parkinson’s disease or progressive supranuclear palsy’ by Miki et al. (doi:10.1093/brain/awab017).
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Affiliation(s)
- Daniel G Di Luca
- Division of Neurology, Department of Medicine, Edmond J Safra Program in Parkinson's Disease and the Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, University of Toronto, Toronto, ON, Canada
| | - Anthony E Lang
- Division of Neurology, Department of Medicine, Edmond J Safra Program in Parkinson's Disease and the Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, University of Toronto, Toronto, ON, Canada
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