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Lövdal SS, Carli G, Orso B, Biehl M, Arnaldi D, Mattioli P, Janzen A, Sittig E, Morbelli S, Booij J, Oertel WH, Leenders KL, Meles SK. Investigating the aspect of asymmetry in brain-first versus body-first Parkinson's disease. NPJ Parkinsons Dis 2024; 10:74. [PMID: 38555343 PMCID: PMC10981719 DOI: 10.1038/s41531-024-00685-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 03/13/2024] [Indexed: 04/02/2024] Open
Abstract
Parkinson's disease (PD) is characterized by a progressive loss of dopaminergic neurons in the substantia nigra. Recent literature has proposed two subgroups of PD. The "body-first subtype" is associated with a prodrome of isolated REM-sleep Behavior Disorder (iRBD) and a relatively symmetric brain degeneration. The "brain-first subtype" is suggested to have a more asymmetric degeneration and a prodromal stage without RBD. This study aims to investigate the proposed difference in symmetry of the degeneration pattern in the presumed body and brain-first PD subtypes. We analyzed 123I-FP-CIT (DAT SPECT) and 18F-FDG PET brain imaging in three groups of patients (iRBD, n = 20, de novo PD with prodromal RBD, n = 22, and de novo PD without RBD, n = 16) and evaluated dopaminergic and glucose metabolic symmetry. The RBD status of all patients was confirmed with video-polysomnography. The PD groups did not differ from each other with regard to the relative or absolute asymmetry of DAT uptake in the putamen (p = 1.0 and p = 0.4, respectively). The patient groups also did not differ from each other with regard to the symmetry of expression of the PD-related metabolic pattern (PDRP) in each hemisphere. The PD groups had no difference in symmetry considering mean FDG uptake in left and right regions of interest and generally had the same degree of symmetry as controls, while the iRBD patients had nine regions with abnormal left-right differences (p < 0.001). Our findings do not support the asymmetry aspect of the "body-first" versus "brain-first" hypothesis.
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Affiliation(s)
- S S Lövdal
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, Groningen, Netherlands.
- Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence, University of Groningen, Groningen, Netherlands.
| | - G Carli
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, Groningen, Netherlands
| | - B Orso
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - M Biehl
- Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence, University of Groningen, Groningen, Netherlands
- SMQB, Institute of Metabolism and Systems Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK
| | - D Arnaldi
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
- Neurophysiopathology Unit, IRCCS Ospedale Policlinico S. Martino, Genoa, Italy
| | - P Mattioli
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
- Neurophysiopathology Unit, IRCCS Ospedale Policlinico S. Martino, Genoa, Italy
| | - A Janzen
- Department of Neurology, Philipps-University Marburg, Marburg, Germany
| | - E Sittig
- Department of Neurology, Philipps-University Marburg, Marburg, Germany
| | - S Morbelli
- Department of Health Sciences, University of Genoa, Genoa, Italy
- Nuclear Medicine Unit, IRCCS Ospedale Policlinico S. Martino, Genoa, Italy
| | - J Booij
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - W H Oertel
- Department of Neurology, Philipps-University Marburg, Marburg, Germany
| | - K L Leenders
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, Groningen, Netherlands
| | - S K Meles
- Department of Neurology, University Medical Center Groningen, Groningen, Netherlands
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2
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Li XL, Gao RX, Zhang Q, Li A, Cai LN, Zhao WW, Gao SL, Wang Y, Yue J. A bibliometric analysis of neuroimaging biomarkers in Parkinson disease based on Web of Science. Medicine (Baltimore) 2022; 101:e30079. [PMID: 35984119 PMCID: PMC9388009 DOI: 10.1097/md.0000000000030079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND This study aimed to analyze and summarize the research hotspots and trends in neuroimaging biomarkers (NMBM) in Parkinson disease (PD) based on the Web of Science core collection database and provide new references for future studies. METHODS Literature regarding NMBM in PD from 1998 to 2022 was analyzed using the Web of Science core collection database. We utilized CiteSpace software (6.1R2) for bibliometric analyses of countries/institutions/authors, keywords, keyword bursts, references, and their clusters. RESULTS A total of 339 studies were identified with a continually increasing annual trend. The most productive country and collaboration was the United States. The top research hotspot is PD cognitive disorder. NMBM and artificial intelligence medical imaging have been applied in the clinical diagnosis, differential diagnosis, treatment, and prognosis of PD. The trends in this field include research on T1 weighted structure magnetic resonance imaging in accordance with voxel-based morphometry, PD cognitive disorder, and neuroimaging features of Lewy body dementia and Alzheimer disease. CONCLUSION The development of NMBM in PD will be effectively promoted by drawing on international research hotspots and cutting-edge technologies, emphasizing international collaboration and institutional cooperation at the national level, and strengthening interdisciplinary research.
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Affiliation(s)
- Xiao-Ling Li
- Division of CT and MRI, First Affiliated Hospital of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Rui-Xue Gao
- Graduate School of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Qinhong Zhang
- Department of Tuina, Acupuncture and Moxibustion, Shenzhen Jiuwei Chinese Medicine Clinic, Shenzhen, China
| | - Ang Li
- Sanofi-Aventis China Investment Co., Ltd, Beijing, China
| | - Li-Na Cai
- Graduate School of Heilongjiang University of Chinese Medicine, Harbin, China
| | | | - Sheng-Lan Gao
- Graduate School of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Yang Wang
- Division of CT and MRI, First Affiliated Hospital of Heilongjiang University of Chinese Medicine, Harbin, China
- Graduate School of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Jinhuan Yue
- Department of Tuina, Acupuncture and Moxibustion, Shenzhen Jiuwei Chinese Medicine Clinic, Shenzhen, China
- *Correspondence: Jinhuan Yue, Department of Tuina, Acupuncture and Moxibustion, Shenzhen Jiuwei Chinese Medicine Clinic, Shenzhen 518000, China (e-mail: )
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3
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Martini AL, Carli G, Kiferle L, Piersanti P, Palumbo P, Morbelli S, Calcagni ML, Perani D, Sestini S. Time-dependent recovery of brain hypometabolism in neuro-COVID-19 patients. Eur J Nucl Med Mol Imaging 2022; 50:90-102. [PMID: 35984451 PMCID: PMC9388976 DOI: 10.1007/s00259-022-05942-2] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Accepted: 08/08/2022] [Indexed: 12/30/2022]
Abstract
Purpose We evaluated brain metabolic dysfunctions and associations with neurological and biological parameters in acute, subacute and chronic COVID-19 phases to provide deeper insights into the pathophysiology of the disease. Methods Twenty-six patients with neurological symptoms (neuro-COVID-19) and [18F]FDG-PET were included. Seven patients were acute (< 1 month (m) after onset), 12 subacute (4 ≥ 1-m, 4 ≥ 2-m and 4 ≥ 3-m) and 7 with neuro-post-COVID-19 (3 ≥ 5-m and 4 ≥ 7–9-m). One patient was evaluated longitudinally (acute and 5-m). Brain hypo- and hypermetabolism were analysed at single-subject and group levels. Correlations between severity/extent of brain hypo- and hypermetabolism and biological (oxygen saturation and C-reactive protein) and clinical variables (global cognition and Body Mass Index) were assessed. Results The “fronto-insular cortex” emerged as the hypometabolic hallmark of neuro-COVID-19. Acute patients showed the most severe hypometabolism affecting several cortical regions. Three-m and 5-m patients showed a progressive reduction of hypometabolism, with limited frontal clusters. After 7–9 months, no brain hypometabolism was detected. The patient evaluated longitudinally showed a diffuse brain hypometabolism in the acute phase, almost recovered after 5 months. Brain hypometabolism correlated with cognitive dysfunction, low blood saturation and high inflammatory status. Hypermetabolism in the brainstem, cerebellum, hippocampus and amygdala persisted over time and correlated with inflammation status. Conclusion Synergistic effects of systemic virus-mediated inflammation and transient hypoxia yield a dysfunction of the fronto-insular cortex, a signature of CNS involvement in neuro-COVID-19. This brain dysfunction is likely to be transient and almost reversible. The long-lasting brain hypermetabolism seems to reflect persistent inflammation processes. Supplementary Information The online version contains supplementary material available at 10.1007/s00259-022-05942-2.
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Affiliation(s)
- Anna Lisa Martini
- Nuclear Medicine Unit, Department of Diagnostic Imaging, N.O.P. - S. Stefano, U.S.L. Toscana Centro, Prato, Italy
| | - Giulia Carli
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Lorenzo Kiferle
- Neurology Unit, N.O.P. - S. Stefano, U.S.L. Toscana Centro, Prato, Italy
| | - Patrizia Piersanti
- Neurology Unit, N.O.P. - S. Stefano, U.S.L. Toscana Centro, Prato, Italy
| | - Pasquale Palumbo
- Neurology Unit, N.O.P. - S. Stefano, U.S.L. Toscana Centro, Prato, Italy
| | - Silvia Morbelli
- Nuclear Medicine Unit, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.,Department of Health Sciences, University of Genoa, Genoa, Italy
| | | | - Daniela Perani
- School of Psychology, Vita-Salute San Raffaele University, Milan, Italy.,In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Nuclear Medicine Unit, San Raffaele Hospital, Milan, Italy
| | - Stelvio Sestini
- Nuclear Medicine Unit, Department of Diagnostic Imaging, N.O.P. - S. Stefano, U.S.L. Toscana Centro, Prato, Italy.
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Xian WB, Shi XC, Luo GH, Yi C, Zhang XS, Pei Z. Co-registration Analysis of Fluorodopa and Fluorodeoxyglucose Positron Emission Tomography for Differentiating Multiple System Atrophy Parkinsonism Type From Parkinson's Disease. Front Aging Neurosci 2021; 13:648531. [PMID: 33958998 PMCID: PMC8093399 DOI: 10.3389/fnagi.2021.648531] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Accepted: 02/22/2021] [Indexed: 11/13/2022] Open
Abstract
It is difficult to differentiate between Parkinson's disease and multiple system atrophy parkinsonian subtype (MSA-P) because of the overlap of their signs and symptoms. Enormous efforts have been made to develop positron emission tomography (PET) imaging to differentiate these diseases. This study aimed to investigate the co-registration analysis of 18F-fluorodopa and 18F-flurodeoxyglucose PET images to visualize the difference between Parkinson's disease and MSA-P. We enrolled 29 Parkinson's disease patients, 28 MSA-P patients, and 10 healthy controls, who underwent both 18F-fluorodopa and 18F-flurodeoxyglucose PET scans. Patients with Parkinson's disease and MSA-P exhibited reduced bilateral striatal 18F-fluorodopa uptake (p < 0.05, vs. healthy controls). Both regional specific uptake ratio analysis and statistical parametric mapping analysis of 18F-flurodeoxyglucose PET revealed hypometabolism in the bilateral putamen of MSA-P patients and hypermetabolism in the bilateral putamen of Parkinson's disease patients. There was a significant positive correlation between 18F-flurodeoxyglucose uptake and 18F-fluorodopa uptake in the contralateral posterior putamen of MSA-P patients (rs = 0.558, p = 0.002). Both 18F-flurodeoxyglucose and 18F-fluorodopa PET images showed that the striatum was rabbit-shaped in the healthy control group segmentation analysis. A defective rabbit-shaped striatum was observed in the 18F-fluorodopa PET image of patients with Parkinson's disease and MSA-P. In the segmentation analysis of 18F-flurodeoxyglucose PET image, an intact rabbit-shaped striatum was observed in Parkinson's disease patients, whereas a defective rabbit-shaped striatum was observed in MSA-P patients. These findings suggest that there were significant differences in the co-registration analysis of 18F-flurodeoxyglucose and 18F-fluorodopa PET images, which could be used in the individual analysis to differentiate Parkinson's disease from MSA-P.
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Affiliation(s)
- Wen-Biao Xian
- Department of Neurology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Diagnosis and Treatment of Major Neurological Diseases, National Key Clinical Department and Key Discipline of Neurology, Guangzhou, China
| | - Xin-Chong Shi
- Department of Nuclear Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Gan-Hua Luo
- Department of Nuclear Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Chang Yi
- Department of Nuclear Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Xiang-Song Zhang
- Department of Nuclear Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Zhong Pei
- Department of Neurology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Diagnosis and Treatment of Major Neurological Diseases, National Key Clinical Department and Key Discipline of Neurology, Guangzhou, China
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5
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Paredes-Pacheco J, López-González FJ, Silva-Rodríguez J, Efthimiou N, Niñerola-Baizán A, Ruibal Á, Roé-Vellvé N, Aguiar P. SimPET-An open online platform for the Monte Carlo simulation of realistic brain PET data. Validation for 18 F-FDG scans. Med Phys 2021; 48:2482-2493. [PMID: 33713354 PMCID: PMC8252452 DOI: 10.1002/mp.14838] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Revised: 03/03/2021] [Accepted: 03/04/2021] [Indexed: 12/11/2022] Open
Abstract
Purpose SimPET (www.sim‐pet.org) is a free cloud‐based platform for the generation of realistic brain positron emission tomography (PET) data. In this work, we introduce the key features of the platform. In addition, we validate the platform by performing a comparison between simulated healthy brain FDG‐PET images and real healthy subject data for three commercial scanners (GE Advance NXi, GE Discovery ST, and Siemens Biograph mCT). Methods The platform provides a graphical user interface to a set of automatic scripts taking care of the code execution for the phantom generation, simulation (SimSET), and tomographic image reconstruction (STIR). We characterize the performance using activity and attenuation maps derived from PET/CT and MRI data of 25 healthy subjects acquired with a GE Discovery ST. We then use the created maps to generate synthetic data for the GE Discovery ST, the GE Advance NXi, and the Siemens Biograph mCT. The validation was carried out by evaluating Bland‐Altman differences between real and simulated images for each scanner. In addition, SPM voxel‐wise comparison was performed to highlight regional differences. Examples for amyloid PET and for the generation of ground‐truth pathological patients are included. Results The platform can be efficiently used for generating realistic simulated FDG‐PET images in a reasonable amount of time. The validation showed small differences between SimPET and acquired FDG‐PET images, with errors below 10% for 98.09% (GE Discovery ST), 95.09% (GE Advance NXi), and 91.35% (Siemens Biograph mCT) of the voxels. Nevertheless, our SPM analysis showed significant regional differences between the simulated images and real healthy patients, and thus, the use of the platform for converting control subject databases between different scanners requires further investigation. Conclusions The presented platform can potentially allow scientists in clinical and research settings to perform MC simulation experiments without the need for high‐end hardware or advanced computing knowledge and in a reasonable amount of time.
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Affiliation(s)
- José Paredes-Pacheco
- Radiology and Psychiatry Department, Faculty of Medicine, Universidade de Santiago de Compostela, Galicia, Spain.,Molecular Imaging Unit, Centro de Investigaciones Médico-Sanitarias, General Foundation of the University of Málaga, Málaga, Spain
| | - Francisco Javier López-González
- Radiology and Psychiatry Department, Faculty of Medicine, Universidade de Santiago de Compostela, Galicia, Spain.,Molecular Imaging Unit, Centro de Investigaciones Médico-Sanitarias, General Foundation of the University of Málaga, Málaga, Spain
| | - Jesús Silva-Rodríguez
- Nuclear Medicine Department & Molecular Imaging Research Group, University Hospital (SERGAS) & Health Research Institute of Santiago de Compostela (IDIS), Galicia, Spain.,R&D Department, Qubiotech Health Intelligence SL, A Coruña, Galicia, Spain
| | - Nikos Efthimiou
- Positron Emission Tomography Research Centre, University of Hull, Hull, HU6 7RX, UK
| | - Aida Niñerola-Baizán
- Nuclear Medicine Department, Hospital Clinic Barcelona, Universitat de Barcelona, Barcelona, Spain.,Biomedical Research Networking Center of Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Barcelona, Spain
| | - Álvaro Ruibal
- Radiology and Psychiatry Department, Faculty of Medicine, Universidade de Santiago de Compostela, Galicia, Spain.,Nuclear Medicine Department & Molecular Imaging Research Group, University Hospital (SERGAS) & Health Research Institute of Santiago de Compostela (IDIS), Galicia, Spain
| | - Núria Roé-Vellvé
- Biomedical Research Networking Center of Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Barcelona, Spain
| | - Pablo Aguiar
- Radiology and Psychiatry Department, Faculty of Medicine, Universidade de Santiago de Compostela, Galicia, Spain.,Nuclear Medicine Department & Molecular Imaging Research Group, University Hospital (SERGAS) & Health Research Institute of Santiago de Compostela (IDIS), Galicia, Spain
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6
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Verwer EE, Golla SSV, Kaalep A, Lubberink M, van Velden FHP, Bettinardi V, Yaqub M, Sera T, Rijnsdorp S, Lammertsma AA, Boellaard R. Harmonisation of PET/CT contrast recovery performance for brain studies. Eur J Nucl Med Mol Imaging 2021; 48:2856-2870. [PMID: 33517517 PMCID: PMC8263427 DOI: 10.1007/s00259-021-05201-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Accepted: 01/10/2021] [Indexed: 12/24/2022]
Abstract
PURPOSE In order to achieve comparability of image quality, harmonisation of PET system performance is imperative. In this study, prototype harmonisation criteria for PET brain studies were developed. METHODS Twelve clinical PET/CT systems (4 GE, 4 Philips, 4 Siemens, including SiPM-based "digital" systems) were used to acquire 30-min PET scans of a Hoffman 3D Brain phantom filled with ~ 33 kBq·mL-1 [18F]FDG. Scan data were reconstructed using various reconstruction settings. The images were rigidly coregistered to a template (voxel size 1.17 × 1.17 × 2.00 mm3) onto which several volumes of interest (VOIs) were defined. Recovery coefficients (RC) and grey matter to white matter ratios (GMWMr) were derived for eroded (denoted in the text by subscript e) and non-eroded grey (GM) and white (WM) matter VOIs as well as a mid-phantom cold spot (VOIcold) and VOIs from the Hammers atlas. In addition, left-right hemisphere differences and voxel-by-voxel differences compared to a reference image were assessed. RESULTS Systematic differences were observed for reconstructions with and without point-spread-function modelling (PSFON and PSFOFF, respectively). Normalising to image-derived activity, upper and lower limits ensuring image comparability were as follows: for PSFON, RCGMe = [0.97-1.01] and GMWMre = [3.51-3.91] for eroded VOI and RCGM = [0.78-0.83] and GMWMr = [1.77-2.06] for non-eroded VOI, and for PSFOFF, RCGMe = [0.92-0.99] and GMWMre = [3.14-3.68] for eroded VOI and RCGM = [0.75-0.81] and GMWMr = [1.72-1.95] for non-eroded VOI. CONCLUSIONS To achieve inter-scanner comparability, we propose selecting reconstruction settings based on RCGMe and GMWMre as specified in "Results". These proposed standards should be tested prospectively to validate and/or refine the harmonisation criteria.
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Affiliation(s)
- E E Verwer
- Department of Radiology & Nuclear Medicine, Amsterdam University Medical Centers, location VUmc, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands.
| | - S S V Golla
- Department of Radiology & Nuclear Medicine, Amsterdam University Medical Centers, location VUmc, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - A Kaalep
- Department of Medical Technology, North Estonia Medical Centre Foundation, Tallinn, Estonia.,EANM Research Limited (EARL), Vienna, Austria
| | - M Lubberink
- Department of Surgical Sciences / Nuclear Medicine & PET, Uppsala University, Uppsala, Sweden
| | - F H P van Velden
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - V Bettinardi
- IRCCS Scientific Institute San Raffaele Hospital, Milan, Italy
| | - M Yaqub
- Department of Radiology & Nuclear Medicine, Amsterdam University Medical Centers, location VUmc, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - T Sera
- EANM Research Limited (EARL), Vienna, Austria.,Department of Nuclear Medicine, University of Szeged, Szeged, Hungary
| | - S Rijnsdorp
- Department of Medical Physics, Catharina Hospital Eindhoven, Eindhoven, The Netherlands
| | - A A Lammertsma
- Department of Radiology & Nuclear Medicine, Amsterdam University Medical Centers, location VUmc, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - R Boellaard
- Department of Radiology & Nuclear Medicine, Amsterdam University Medical Centers, location VUmc, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
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7
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Martí-Andrés G, van Bommel L, Meles SK, Riverol M, Valentí R, Kogan RV, Renken RJ, Gurvits V, van Laar T, Pagani M, Prieto E, Luquin MR, Leenders KL, Arbizu J. Multicenter Validation of Metabolic Abnormalities Related to PSP According to the MDS-PSP Criteria. Mov Disord 2020; 35:2009-2018. [PMID: 32822512 DOI: 10.1002/mds.28217] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2020] [Revised: 05/31/2020] [Accepted: 06/22/2020] [Indexed: 01/08/2023] Open
Abstract
It remains unclear whether the supportive imaging features described in the diagnostic criteria for progressive supranuclear palsy (PSP) are suitable for the full clinical spectrum. The aim of the current study was to define and cross-validate the pattern of glucose metabolism in the brain associated with a diagnosis of different PSP variants. A retrospective multicenter cohort study performed on 73 PSP patients who were referred for a fluorodeoxyglucose positron emission tomography PET scan: PSP-Richardson's syndrome, n = 47; PSP-parkinsonian variant, n = 18; and progressive gait freezing, n = 8. In addition, we included 55 healthy controls and 58 Parkinson's disease (PD) patients. Scans were normalized by global mean activity. We analyzed the regional differences in metabolism between the groups. Moreover, we applied a multivariate analysis to obtain a PSP-related pattern that was cross-validated in independent populations at the individual level. Group analysis showed relative hypometabolism in the midbrain, basal ganglia, thalamus, and frontoinsular cortices and hypermetabolism in the cerebellum and sensorimotor cortices in PSP patients compared with healthy controls and PD patients, the latter with more severe involvement in the basal ganglia and occipital cortices. The PSP-related pattern obtained confirmed the regions described above. At the individual level, the PSP-related pattern showed optimal diagnostic accuracy to distinguish between PSP and healthy controls (sensitivity, 80.4%; specificity, 96.9%) and between PSP and PD (sensitivity, 80.4%; specificity, 90.7%). Moreover, PSP-Richardson's syndrome and PSP-parkinsonian variant patients showed significantly more PSP-related pattern expression than PD patients and healthy controls. The glucose metabolism assessed by fluorodeoxyglucose PET is a useful and reproducible supportive diagnostic tool for PSP-Richardson's syndrome and PSP-parkinsonian variant. © 2020 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Gloria Martí-Andrés
- Department of Neurology, Clínica Universidad de Navarra, University of Navarra, Pamplona, Spain.,IdiSNA (Navarra Institute for Health Research), Pamplona, Spain
| | - Liza van Bommel
- Department of Neurology, University Medical Center Groningen, Groningen, the Netherlands
| | - Sanne K Meles
- Department of Neurology, University Medical Center Groningen, Groningen, the Netherlands
| | - Mario Riverol
- Department of Neurology, Clínica Universidad de Navarra, University of Navarra, Pamplona, Spain.,IdiSNA (Navarra Institute for Health Research), Pamplona, Spain
| | - Rafael Valentí
- Department of Neurology, Clínica Universidad de Navarra, University of Navarra, Pamplona, Spain.,IdiSNA (Navarra Institute for Health Research), Pamplona, Spain
| | - Rosalie V Kogan
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, Groningen, the Netherlands
| | - Remco J Renken
- NeuroImaging Center, University Medical Center Groningen, Groningen, the Netherlands
| | - Vita Gurvits
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, Groningen, the Netherlands
| | - Teus van Laar
- Department of Neurology, University Medical Center Groningen, Groningen, the Netherlands
| | - Marco Pagani
- Institute of Cognitive Sciences and Technologies, CNR, Rome, Italy
| | - Elena Prieto
- Department of Medical Physics, Clínica Universidad de Navarra, Pamplona, Spain
| | - M Rosario Luquin
- Department of Neurology, Clínica Universidad de Navarra, University of Navarra, Pamplona, Spain.,IdiSNA (Navarra Institute for Health Research), Pamplona, Spain
| | - Klaus L Leenders
- Department of Neurology, University Medical Center Groningen, Groningen, the Netherlands.,Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, Groningen, the Netherlands
| | - Javier Arbizu
- IdiSNA (Navarra Institute for Health Research), Pamplona, Spain.,Department of Nuclear Medicine and Molecular Imaging, Clínica Universidad de Navarra, University of Navarra, Pamplona, Spain
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8
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Wei H, Zhou Y, Zhao J, Zhan L. Risk Factors and Metabolism of Different Brain Regions by Positron Emission Tomography in Parkinson Disease with Disabling Dyskinesia. Curr Neurovasc Res 2019; 16:310-320. [PMID: 31622205 DOI: 10.2174/1567202616666191009102112] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2019] [Revised: 07/08/2019] [Accepted: 07/25/2019] [Indexed: 11/22/2022]
Abstract
Objective:Dyskinesia is the most common motor complication in advanced Parkinson’s Disease (PD) and has a severe impact on daily life. But the mechanism of dyskinesia is still poorly understood. This study aims to explore risk factors for disabling dyskinesia in PD and further analyze the Vesicular Monoamine Transporter 2 (VMAT2) distribution (labeled with 18F-AV133) in the corpus striatum and the 18F-fluorodeoxyglucose (18F-FDG) metabolism of different brain regions by PET-CT.Methods:This is a cross-sectional study involving 135 PD patients. They were divided into disabling dyskinesia group (DD group, N=22) and non-dyskinesia group (ND group, N=113). All the patients were agreed to undergo PET-CT scans. Clinical data were analyzed between two groups by using multivariate logistic regression analysis, and risk factors for disabling dyskinesia were then determined. The standard uptake value ratios (SUVr) of 18F-AV133 in the corpus striatum and the 18F-FDG metabolism of different brain regions were identified and calculated by the software.Results:6.3% patients have disabling dyskinesia. DD group were more likely to have longer Disease Duration, higher Hoehn-Yahr degree, more severe clinic symptoms, more frequent sleep behavior disorder, and higher levodopa dose equivalency than ND group (P < 0.05). After adjusting confounding factors by multivariate logistic regression, DD group had longer PD duration and high levodopa dose equivalency compared with ND group (P < 0.05). There is no significant difference between the VMAT2 distribution (labeled with 18F- AV133) in the putamen and caudate between two groups. And the 18F-FDG metabolic changes in cortical and subcortical regions did not show a significant difference between the two groups either (P > 0.05).Conclusion:Long PD duration and high levodopa dose equivalency were two independent risk factors for disabling dyskinesia in PD patients. Compared to non-dyskinesia PD patients, there was no significant dopamine decline of the nigrostriatal system in disabling dyskinesia PD patients. Activities of different brain regions were not different between the two groups by 18F-FDG PETCT.
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Affiliation(s)
- Huan Wei
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Yongtao Zhou
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Junwu Zhao
- Department of Neurology, Weihai Municipal Hospital, Shandong, China
| | - Liping Zhan
- Department of Neurology, The Affiliated Yan'an Hospital of Kunming Medical University, Kunming, China
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Abnormal pattern of brain glucose metabolism in Parkinson's disease: replication in three European cohorts. Eur J Nucl Med Mol Imaging 2019; 47:437-450. [PMID: 31768600 PMCID: PMC6974499 DOI: 10.1007/s00259-019-04570-7] [Citation(s) in RCA: 52] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2019] [Accepted: 10/03/2019] [Indexed: 12/15/2022]
Abstract
Rationale In Parkinson’s disease (PD), spatial covariance analysis of 18F-FDG PET data has consistently revealed a characteristic PD-related brain pattern (PDRP). By quantifying PDRP expression on a scan-by-scan basis, this technique allows objective assessment of disease activity in individual subjects. We provide a further validation of the PDRP by applying spatial covariance analysis to PD cohorts from the Netherlands (NL), Italy (IT), and Spain (SP). Methods The PDRPNL was previously identified (17 controls, 19 PD) and its expression was determined in 19 healthy controls and 20 PD patients from the Netherlands. The PDRPIT was identified in 20 controls and 20 “de-novo” PD patients from an Italian cohort. A further 24 controls and 18 “de-novo” Italian patients were used for validation. The PDRPSP was identified in 19 controls and 19 PD patients from a Spanish cohort with late-stage PD. Thirty Spanish PD patients were used for validation. Patterns of the three centers were visually compared and then cross-validated. Furthermore, PDRP expression was determined in 8 patients with multiple system atrophy. Results A PDRP could be identified in each cohort. Each PDRP was characterized by relative hypermetabolism in the thalamus, putamen/pallidum, pons, cerebellum, and motor cortex. These changes co-varied with variable degrees of hypometabolism in posterior parietal, occipital, and frontal cortices. Frontal hypometabolism was less pronounced in “de-novo” PD subjects (Italian cohort). Occipital hypometabolism was more pronounced in late-stage PD subjects (Spanish cohort). PDRPIT, PDRPNL, and PDRPSP were significantly expressed in PD patients compared with controls in validation cohorts from the same center (P < 0.0001), and maintained significance on cross-validation (P < 0.005). PDRP expression was absent in MSA. Conclusion The PDRP is a reproducible disease characteristic across PD populations and scanning platforms globally. Further study is needed to identify the topography of specific PD subtypes, and to identify and correct for center-specific effects. Electronic supplementary material The online version of this article (10.1007/s00259-019-04570-7) contains supplementary material, which is available to authorized users.
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Trošt M, Perovnik M, Pirtošek Z. Correlations of Neuropsychological and Metabolic Brain Changes in Parkinson's Disease and Other α-Synucleinopathies. Front Neurol 2019; 10:1204. [PMID: 31798525 PMCID: PMC6868095 DOI: 10.3389/fneur.2019.01204] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2019] [Accepted: 10/28/2019] [Indexed: 12/14/2022] Open
Abstract
Cognitive impairment is a common feature in Parkinson's disease (PD) and other α-synucleinopathies as 80% of PD patients develop dementia within 20 years. Early cognitive changes in PD patients present as a dysexecutive syndrome, broadly characterized as a disruption of the fronto-striatal dopamine network. Cognitive deficits in other domains (recognition memory, attention processes and visuospatial abilities) become apparent with the progression of PD and development of dementia. In dementia with Lewy bodies (DLB) the cognitive impairment develops early or even precedes parkinsonism and it is more pronounced in visuospatial skills and memory. Cognitive impairment in the rarer α-synucleinopathies (multiple system atrophy and pure autonomic failure) is less well studied. Metabolic brain imaging with positron emission tomography and [18F]-fluorodeoxyglucose (FDG-PET) is a well-established diagnostic method in neurodegenerative diseases, including dementias. Changes in glucose metabolism precede those seen on structural magnetic resonance imaging (MRI). Reduction in glucose metabolism and atrophy have been suggested to represent consecutive changes of neurodegeneration and are linked to specific cognitive disorders (e.g., dysexecutive syndrome, memory impairment, visuospatial deficits etc.). Advances in the statistical analysis of FDG-PET images enabling a network analysis broadened our understanding of neurodegenerative brain processes. A specific cognitive pattern related to PD was identified by applying voxel-based network modeling approach. The magnitude of this pattern correlated significantly with patients' cognitive skills. Specific metabolic brain changes were observed also in patients with DLB as well as in a prodromal phase of α-synucleinopathy: REM sleep behavior disorder. Metabolic brain imaging with FDG-PET is a reliable biomarker of neurodegenerative brain diseases throughout their course, precisely reflecting their topographic distribution, stage and functional impact.
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Affiliation(s)
- Maja Trošt
- Department for Neurology, University Medical Center Ljubljana, Ljubljana, Slovenia.,Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia.,Department for Nuclear Medicine, University Medical Center Ljubljana, Ljubljana, Slovenia
| | - Matej Perovnik
- Department for Neurology, University Medical Center Ljubljana, Ljubljana, Slovenia
| | - Zvezdan Pirtošek
- Department for Neurology, University Medical Center Ljubljana, Ljubljana, Slovenia.,Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
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