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Yang Y, Li X, Lu J, Ge J, Chen M, Yao R, Tian M, Wang J, Liu F, Zuo C. Recent progress in the applications of presynaptic dopaminergic positron emission tomography imaging in parkinsonism. Neural Regen Res 2025; 20:93-106. [PMID: 38767479 PMCID: PMC11246150 DOI: 10.4103/1673-5374.391180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2023] [Accepted: 11/18/2023] [Indexed: 05/22/2024] Open
Abstract
Nowadays, presynaptic dopaminergic positron emission tomography, which assesses deficiencies in dopamine synthesis, storage, and transport, is widely utilized for early diagnosis and differential diagnosis of parkinsonism. This review provides a comprehensive summary of the latest developments in the application of presynaptic dopaminergic positron emission tomography imaging in disorders that manifest parkinsonism. We conducted a thorough literature search using reputable databases such as PubMed and Web of Science. Selection criteria involved identifying peer-reviewed articles published within the last 5 years, with emphasis on their relevance to clinical applications. The findings from these studies highlight that presynaptic dopaminergic positron emission tomography has demonstrated potential not only in diagnosing and differentiating various Parkinsonian conditions but also in assessing disease severity and predicting prognosis. Moreover, when employed in conjunction with other imaging modalities and advanced analytical methods, presynaptic dopaminergic positron emission tomography has been validated as a reliable in vivo biomarker. This validation extends to screening and exploring potential neuropathological mechanisms associated with dopaminergic depletion. In summary, the insights gained from interpreting these studies are crucial for enhancing the effectiveness of preclinical investigations and clinical trials, ultimately advancing toward the goals of neuroregeneration in parkinsonian disorders.
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Affiliation(s)
- Yujie Yang
- Key Laboratory of Arrhythmias, Ministry of Education, Department of Medical Genetics, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China
- Department of Neurology, National Research Center for Aging and Medicine, National Center for Neurological Disorders, and State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Xinyi Li
- Department of Neurology, National Research Center for Aging and Medicine, National Center for Neurological Disorders, and State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Jiaying Lu
- Department of Nuclear Medicine & PET Center, National Center for Neurological Disorders, and National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Jingjie Ge
- Department of Nuclear Medicine & PET Center, National Center for Neurological Disorders, and National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Mingjia Chen
- Department of Neurology, National Research Center for Aging and Medicine, National Center for Neurological Disorders, and State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Ruixin Yao
- Department of Neurology, National Research Center for Aging and Medicine, National Center for Neurological Disorders, and State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Mei Tian
- Department of Nuclear Medicine & PET Center, National Center for Neurological Disorders, and National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China
- International Human Phenome Institutes (Shanghai), Shanghai, China
- Human Phenome Institute, Fudan University, Shanghai, China
| | - Jian Wang
- Department of Neurology, National Research Center for Aging and Medicine, National Center for Neurological Disorders, and State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Fengtao Liu
- Department of Neurology, National Research Center for Aging and Medicine, National Center for Neurological Disorders, and State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Chuantao Zuo
- Department of Nuclear Medicine & PET Center, National Center for Neurological Disorders, and National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China
- Human Phenome Institute, Fudan University, Shanghai, China
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Radlicka-Borysewska A, Jabłońska J, Lenarczyk M, Szumiec Ł, Harda Z, Bagińska M, Barut J, Pera J, Kreiner G, Wójcik DK, Rodriguez Parkitna J. Non-motor symptoms associated with progressive loss of dopaminergic neurons in a mouse model of Parkinson's disease. Front Neurosci 2024; 18:1375265. [PMID: 38745938 PMCID: PMC11091341 DOI: 10.3389/fnins.2024.1375265] [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: 01/23/2024] [Accepted: 04/09/2024] [Indexed: 05/16/2024] Open
Abstract
Parkinson's disease (PD) is characterized by three main motor symptoms: bradykinesia, rigidity and tremor. PD is also associated with diverse non-motor symptoms that may develop in parallel or precede motor dysfunctions, ranging from autonomic system dysfunctions and impaired sensory perception to cognitive deficits and depression. Here, we examine the role of the progressive loss of dopaminergic transmission in behaviors related to the non-motor symptoms of PD in a mouse model of the disease (the TIF-IADATCreERT2 strain). We found that in the period from 5 to 12 weeks after the induction of a gradual loss of dopaminergic neurons, mild motor symptoms became detectable, including changes in the distance between paws while standing as well as the swing speed and step sequence. Male mutant mice showed no apparent changes in olfactory acuity, no anhedonia-like behaviors, and normal learning in an instrumental task; however, a pronounced increase in the number of operant responses performed was noted. Similarly, female mice with progressive dopaminergic neuron degeneration showed normal learning in the probabilistic reversal learning task and no loss of sweet-taste preference, but again, a robustly higher number of choices were performed in the task. In both males and females, the higher number of instrumental responses did not affect the accuracy or the fraction of rewarded responses. Taken together, these data reveal discrete, dopamine-dependent non-motor symptoms that emerge in the early stages of dopaminergic neuron degeneration.
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Affiliation(s)
- Anna Radlicka-Borysewska
- Department of Molecular Neuropharmacology, Maj Institute of Pharmacology of the Polish Academy of Sciences, Kraków, Poland
| | - Judyta Jabłońska
- Department of Molecular Neuropharmacology, Maj Institute of Pharmacology of the Polish Academy of Sciences, Kraków, Poland
| | - Michał Lenarczyk
- Faculty of Management and Social Communication, Institute of Applied Psychology, Jagiellonian University, Kraków, Poland
| | - Łukasz Szumiec
- Department of Molecular Neuropharmacology, Maj Institute of Pharmacology of the Polish Academy of Sciences, Kraków, Poland
| | - Zofia Harda
- Department of Molecular Neuropharmacology, Maj Institute of Pharmacology of the Polish Academy of Sciences, Kraków, Poland
| | - Monika Bagińska
- Department of Brain Biochemistry, Maj Institute of Pharmacology of the Polish Academy of Sciences, Kraków, Poland
| | - Justyna Barut
- Department of Brain Biochemistry, Maj Institute of Pharmacology of the Polish Academy of Sciences, Kraków, Poland
| | - Joanna Pera
- Department of Neurology, Jagiellonian University Medical College, Kraków, Poland
| | - Grzegorz Kreiner
- Department of Brain Biochemistry, Maj Institute of Pharmacology of the Polish Academy of Sciences, Kraków, Poland
| | - Daniel K. Wójcik
- Faculty of Management and Social Communication, Institute of Applied Psychology, Jagiellonian University, Kraków, Poland
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of the Polish Academy of Sciences, Warsaw, Poland
| | - Jan Rodriguez Parkitna
- Department of Molecular Neuropharmacology, Maj Institute of Pharmacology of the Polish Academy of Sciences, Kraków, Poland
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Camerino I, Ferreira J, Vonk JM, Kessels RPC, de Leeuw FE, Roelofs A, Copland D, Piai V. Systematic Review and Meta-Analyses of Word Production Abilities in Dysfunction of the Basal Ganglia: Stroke, Small Vessel Disease, Parkinson's Disease, and Huntington's Disease. Neuropsychol Rev 2024; 34:1-26. [PMID: 36564612 DOI: 10.1007/s11065-022-09570-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Revised: 10/13/2022] [Accepted: 11/16/2022] [Indexed: 12/25/2022]
Abstract
Clinical populations with basal ganglia pathologies may present with language production impairments, which are often described in combination with comprehension measures or attributed to motor, memory, or processing-speed problems. In this systematic review and meta-analysis, we studied word production in four (vascular and non-vascular) pathologies of the basal ganglia: stroke affecting the basal ganglia, small vessel disease, Parkinson's disease, and Huntington's disease. We compared scores of these clinical populations with those of matched cognitively unimpaired adults on four well-established production tasks, namely picture naming, category fluency, letter fluency, and past-tense verb inflection. We conducted a systematic search in PubMed and PsycINFO with terms for basal ganglia structures, basal ganglia disorders and language production tasks. A total of 114 studies were included, containing results for one or more of the tasks of interest. For each pathology and task combination, effect sizes (Hedges' g) were extracted comparing patient versus control groups. For all four populations, performance was consistently worse than that of cognitively unimpaired adults across the four language production tasks (p-values < 0.010). Given that performance in picture naming and verb inflection across all pathologies was quantified in terms of accuracy, our results suggest that production impairments cannot be fully explained by motor or processing-speed deficits. Our review shows that while language production difficulties in these clinical populations are not negligible, more evidence is necessary to determine the exact mechanism that leads to these deficits and whether this mechanism is the same across different pathologies.
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Affiliation(s)
- Ileana Camerino
- Donders Centre for Cognition, Radboud University, Nijmegen, The Netherlands
| | - João Ferreira
- Donders Centre for Cognition, Radboud University, Nijmegen, The Netherlands.
| | - Jet M Vonk
- Department of Neurology, Memory and Aging Center, University of California San Francisco (UCSF), San Francisco, CA, USA
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Roy P C Kessels
- Donders Centre for Cognition, Radboud University, Nijmegen, The Netherlands
- Vincent van Gogh Institute for Psychiatry, Venray, The Netherlands
- Donders Centre for Medical Neuroscience, Department of Medical Psychology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Frank-Erik de Leeuw
- Department of Neurology, Donders Centre for Medical Neuroscience, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Ardi Roelofs
- Donders Centre for Cognition, Radboud University, Nijmegen, The Netherlands
| | - David Copland
- School of Health and Rehabilitation Sciences, The University of Queensland, Saint Lucia, QLD, Australia
- Queensland Aphasia Research Centre, The University of Queensland, Herston, QLD, Australia
| | - Vitória Piai
- Donders Centre for Cognition, Radboud University, Nijmegen, The Netherlands
- Donders Centre for Medical Neuroscience, Department of Medical Psychology, Radboud University Medical Center, Nijmegen, The Netherlands
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Tian M, Zuo C, Cahid Civelek A, Carrio I, Watanabe Y, Kang KW, Murakami K, Prior JO, Zhong Y, Dou X, Yu C, Jin C, Zhou R, Liu F, Li X, Lu J, Zhang H, Wang J. International consensus on clinical use of presynaptic dopaminergic positron emission tomography imaging in parkinsonism. Eur J Nucl Med Mol Imaging 2024; 51:434-442. [PMID: 37789188 DOI: 10.1007/s00259-023-06403-0] [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: 06/23/2023] [Accepted: 08/15/2023] [Indexed: 10/05/2023]
Abstract
PURPOSE Presynaptic dopaminergic positron emission tomography (PET) imaging serves as an essential tool in diagnosing and differentiating patients with suspected parkinsonism, including idiopathic Parkinson's disease (PD) and other neurodegenerative and non-neurodegenerative diseases. The PET tracers most commonly used at the present time mainly target dopamine transporters (DAT), aromatic amino acid decarboxylase (AADC), and vesicular monoamine type 2 (VMAT2). However, established standards for the imaging procedure and interpretation of presynaptic dopaminergic PET imaging are still lacking. The goal of this international consensus is to help nuclear medicine practitioners procedurally perform presynaptic dopaminergic PET imaging. METHOD A multidisciplinary task group formed by experts from various countries discussed and approved the consensus for presynaptic dopaminergic PET imaging in parkinsonism, focusing on standardized recommendations, procedures, interpretation, and reporting. CONCLUSION This international consensus and practice guideline will help to promote the standardized use of presynaptic dopaminergic PET imaging in parkinsonism. It will become an international standard for this purpose in clinical practice.
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Affiliation(s)
- Mei Tian
- Department of Nuclear Medicine and PET Center, Huashan Hospital, Fudan University, Shanghai, 200235, China.
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, China.
- Human Phenome Institute, Fudan University, Shanghai, 201203, China.
| | - Chuantao Zuo
- Department of Nuclear Medicine and PET Center, Huashan Hospital, Fudan University, Shanghai, 200235, China.
- National Center for Neurological Disorders & National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, 200040, China.
| | - A Cahid Civelek
- Department of Radiology and Radiological Science, Division of Nuclear Medicine and Molecular Imaging, Johns Hopkins Medicine, Baltimore, MD, 21287, USA.
| | - Ignasi Carrio
- Research Institute and Department of Nuclear Medicine, Hospital Sant Pau, Autonomous University of Barcelona, 08025, Barcelona, Spain
| | - Yasuyoshi Watanabe
- Laboratory for Pathophysiological and Health Science, RIKEN Center for Biosystems Dynamics Research, Kobe, Hyogo, 650-0047, Japan
| | - Keon Wook Kang
- Department of Nuclear Medicine, Seoul National University College of Medicine, Seoul, 03080, Korea
| | - Koji Murakami
- Department of Radiology, Juntendo University Hospital, Tokyo, 113-8431, Japan
| | - John O Prior
- Department of Nuclear Medicine and Molecular Imaging, Lausanne University Hospital, Lausanne, Switzerland
| | - Yan Zhong
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, China
| | - Xiaofeng Dou
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, China
| | - Congcong Yu
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, China
| | - Chentao Jin
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, China
| | - Rui Zhou
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, China
| | - Fengtao Liu
- National Center for Neurological Disorders & National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, 200040, China
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, 200235, China
| | - Xinyi Li
- National Center for Neurological Disorders & National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, 200040, China
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, 200235, China
| | - Jiaying Lu
- Department of Nuclear Medicine and PET Center, Huashan Hospital, Fudan University, Shanghai, 200235, China
- National Center for Neurological Disorders & National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - Hong Zhang
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, China.
- Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, 310009, China.
- The College of Biomedical Engineering and Instrument Science of Zhejiang University, Hangzhou, 310007, China.
- Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, 310007, China.
| | - Jian Wang
- National Center for Neurological Disorders & National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, 200040, China.
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, 200235, China.
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5
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Huang X, He Q, Ruan X, Li Y, Kuang Z, Wang M, Guo R, Bu S, Wang Z, Yu S, Chen A, Wei X. Structural connectivity from DTI to predict mild cognitive impairment in de novo Parkinson's disease. Neuroimage Clin 2023; 41:103548. [PMID: 38061176 PMCID: PMC10755095 DOI: 10.1016/j.nicl.2023.103548] [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] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Revised: 11/27/2023] [Accepted: 11/28/2023] [Indexed: 01/01/2024]
Abstract
BACKGROUND Early detection of Parkinson's disease (PD) patients at high risk for mild cognitive impairment (MCI) can help with timely intervention. White matter structural connectivity is considered an early and sensitive indicator of neurodegenerative disease. OBJECTIVES To investigate whether baseline white matter structural connectivity features from diffusion tensor imaging (DTI) of de novo PD patients can help predict PD-MCI conversion at an individual level using machine learning methods. METHODS We included 90 de novo PD patients who underwent DTI and 3D T1-weighted imaging. Elastic net-based feature consensus ranking (ENFCR) was used with 1000 random training sets to select clinical and structural connectivity features. Linear discrimination analysis (LDA), support vector machine (SVM), K-nearest neighbor (KNN) and naïve Bayes (NB) classifiers were trained based on features selected more than 500 times. The area under the ROC curve (AUC), accuracy (ACC), sensitivity (SEN) and specificity (SPE) were used to evaluate model performance. RESULTS A total of 57 PD patients were classified as PD-MCI nonconverters, and 33 PD patients were classified as PD-MCI converters. The models trained with clinical data showed moderate performance (AUC range: 0.62-0.68; ACC range: 0.63-0.77; SEN range: 0.45-0.66; SPE range: 0.64-0.84). Models trained with structural connectivity (AUC range, 0.81-0.84; ACC range, 0.75-0.86; SEN range, 0.77-0.91; SPE range, 0.71-0.88) performed similar to models that were trained with both clinical and structural connectivity data (AUC range, 0.81-0.85; ACC range, 0.74-0.85; SEN range, 0.79-0.91; SPE range, 0.70-0.89). CONCLUSIONS Baseline white matter structural connectivity from DTI is helpful in predicting future MCI conversion in de novo PD patients.
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Affiliation(s)
- Xiaofei Huang
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangdong, China
| | - Qing He
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangdong, China
| | - Xiuhang Ruan
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangdong, China
| | - Yuting Li
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangdong, China; Affiliated Dongguan Hospital, Southern Medical University (Dongguan People's Hospital), Guangdong, China
| | - Zhanyu Kuang
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangdong, China
| | - Mengfan Wang
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangdong, China
| | - Riyu Guo
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangdong, China
| | - Shuwen Bu
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangdong, China
| | - Zhaoxiu Wang
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangdong, China
| | - Shaode Yu
- School of Information and Communication Engineering, Communication University of China, Beijing, China.
| | - Amei Chen
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangdong, China.
| | - Xinhua Wei
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangdong, China.
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Wu Y, Xu XJ, Sun X, Zhai H, Wang T, Cao XB, Xu Y. Integrated PET/MRI With 11C-CFT and 18F-FDG for levodopa response difference in Parkinson's disease. Behav Brain Res 2023; 454:114609. [PMID: 37532003 DOI: 10.1016/j.bbr.2023.114609] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 07/05/2023] [Accepted: 07/31/2023] [Indexed: 08/04/2023]
Abstract
AIM Parkinson's disease is one of the most common neurodegenerative diseases. Excellent levodopa responsiveness has been proposed as a characteristic supporting feature in substantiating the PD diagnosis. However, a small portion of clinically established PD patients shows poor levodopa response. This study aims to investigate brain function alterations of PD patients with poor levodopa responsiveness by PET/MRI. METHOD A total of 46 PD patients were recruited. They all completed 11C-CFT PET/MRI scans and the acute levodopa challenge test. Among these 46 PD patients, 42 participants further underwent 18F-FDG PET/MRI scans. Clinical variables regarding demographic data, disease features and cognition scales were also collected. Based on the improvement rate of UPDRS-III, PD patients were divided into non-responders (improvement rate < 33 %) and responders (improvement rate ≥ 33 %). Statistical parametric zapping was performed to analyze molecular imaging. Dopaminergic uptake and metabolism of 70 brain regions were converted to quantitative values and expressed as standard uptake value (SUV). SUV was further normalized by the cerebellum. The resulting SUV ratios and clinical variables were then compared by SPSS. RESULTS The difference between levodopa non-responders (n = 17) and responders (n = 29) in the UPDRS III baseline was statistically significant and the former had a lower UPDRS III baseline (19 (10, 32), p<0.05). In contrast, no statistical difference between these two groups was found in age, gender, disease duration, cognition, motor subtype and Hoehn-Yahr stage. Dopaminergic uptake differences between levodopa non-responders (n = 17) and responders (n = 29) were shown in the left inferior frontal cortex (1.00 ± 0.09 vs 1.07 ± 0.08, p < 0.05 and FDR < 0.2), the right posterior cingulum (1.10 ± 0.10 vs 1.20 ± 0.13, p < 0.05 and FDR < 0.2) and the right insula (1.21 ± 0.12 vs 1.30 ± 0.10, p < 0.05 and FDR < 0.2). The metabolic alterations between levodopa non-responders (n = 16) and responders (n = 26) were shown in the right supplementary motor area (1.30 (1.18, 1.39) vs 1.41 (1.31, 1.53), p < 0.05 and FDR < 0.2), right precuneus (1.37 ± 0.10 vs 1.47 ± 0.18, p < 0.05 and FDR < 0.2), right parietal cortex (1.14 ± 0.15 vs 1.27 ± 0.21, p < 0.05 and FDR < 0.2), right supramarginal gyrus (1.16 (1.12, 1.26) vs 1.25 (1.14, 1.46), p < 0.05 and FDR < 0.2), right postcentral gyrus (1.15 (1.08, 1.32) vs 1.24 (1.17, 1.39), p < 0.05 and FDR < 0.2), medulla (0.75 ± 0.07 vs 0.80 ± 0.07, p < 0.05 and FDR < 0.2), right rolandic operculum (1.25 (1.18, 1.32) vs 1.33 (1.25, 1.50), p < 0.05 and FDR < 0.2), right olfactory (0.95 (0.91, 1.01) vs 1.01 (0.95, 1.15), p < 0.05 and FDR < 0.2), the right insula (1.15 (1.06, 1.22) vs 1.21 (1.12, 1.35), p < 0.05 and FDR < 0.2) and the left cerebellum crus (0.96 (0.91, 1.01) vs 0.92 (0.86, 0.96), p < 0.05 and FDR < 0.2). CONCLUSIONS PD patients with poor response to levodopa showed less severe impairment of baseline motor symptoms, more severe dopaminergic deficits in the left inferior frontal, right posterior cingulate cortex and the right insula, and lower metabolism in the right supplementary motor area, right precuneus, right parietal cortex, right supramarginal gyrus, right postcentral gyrus, medulla, right rolandic operculum, right olfactory, the right insula and higher metabolism in the left cerebellum crus.
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Affiliation(s)
- Yi Wu
- Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiao-Jun Xu
- Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xun Sun
- Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Heng Zhai
- Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Tao Wang
- Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - Xue-Bing Cao
- Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - Yan Xu
- Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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Effects of monotherapy with a monoamine oxidase B inhibitor on motor symptoms in Parkinson's disease are dependent on frontal function. Neurol Sci 2023; 44:913-918. [PMID: 36376554 DOI: 10.1007/s10072-022-06499-6] [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: 09/30/2022] [Accepted: 11/05/2022] [Indexed: 11/16/2022]
Abstract
BACKGROUND Monotherapy with monoamine oxidase B (MAO-B) inhibitors enhances the level of endogenous dopamine in treatment for Parkinson's disease (PD) and provides some benefits. Certain neuropsychiatric functions are also regulated by central dopaminergic activity. AIM To investigate the relationship of the efficacy of monotherapy with MAO-B inhibitors on motor symptoms in PD with baseline cognitive function. PATIENTS AND METHODS Outcomes were examined for 27 consecutive drug-naïve PD patients who received initial treatment with a MAO-B inhibitor (selegiline: 11, rasagiline: 16). Selegiline was titrated to an optimal dose. The dose of rasagiline was fixed at 1 mg/day. Motor symptoms were assessed using the Movement Disorder Society-Unified Parkinson's Disease Rating Scale part III before treatment and after the efficacy reached a plateau within 19 weeks after drug initiation, and the % improvement in motor symptoms was calculated. Pre-treatment cognitive function was assessed using the Montreal Cognitive Assessment (MoCA) and Frontal Assessment Battery (FAB). Correlations of % improvement in motor symptoms and baseline cognitive assessments were examined using Spearman correlation coefficients and multiple regression analysis. RESULTS In all patients, the mean % improvement in motor symptoms was 46.5% (range 0-83.3%). Spearman correlation coefficients showed the % improvement in motor symptoms was correlated with FAB (r = 0.631, p < 0.001). In multiple regression analysis with patient background factors as independent variables, only FAB was associated with improvement in motor symptoms in the MAO-B group. CONCLUSION Better FAB scores predict a significant improvement in motor symptoms with treatment with MAO-B inhibitors, suggesting high activity of endogenous dopamine.
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Regional cortical hypoperfusion and atrophy correlate with striatal dopaminergic loss in Parkinson's disease: a study using arterial spin labeling MR perfusion. Neuroradiology 2023; 65:569-577. [PMID: 36376524 DOI: 10.1007/s00234-022-03085-7] [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: 07/26/2022] [Accepted: 11/08/2022] [Indexed: 11/15/2022]
Abstract
PURPOSE To investigate the relationship of the striatal dopamine transporter density to changes in the gray matter (GM) volume and cerebral perfusion in patients with Parkinson's disease (PD). METHODS We evaluated the regional cerebral blood flow (CBF) and GM volume, concurrently measured using arterial spin labeling and T1-weighted magnetic resonance imaging, respectively, as well as the striatal specific binding ratio (SBR) in 123I-N-ω-fluoropropyl-2β-carboxymethoxy-3β-(4-iodophenyl)nortropane (123I-FP-CIT) single-photon emission computed tomography in 30 non-demented patients with PD (15 men and 15 women; mean age, 67.2 ± 8.8 years; mean Hoehn-Yahr stage, 2.2 ± 0.9). Voxel-wise regression analyses using statistical parametric mapping (SPM) were performed to explore the brain regions that showed correlations of the striatal SBR to the GM volume and CBF, respectively, with a height threshold of p < 0.0005 at the voxel level and p < 0.05 family-wise error-corrected at the cluster level. RESULTS SPM analysis showed a significant positive correlation between the SBR and GM volume in the inferior frontal gyrus (IFG). Whereas, a positive correlation between the SBR and CBF was widely found in the frontotemporal and parietotemporal regions, including the IFG. Notably, the opercular part of the IFG showed significant correlations in both SPM analyses of the GM volume (r2 = 0.90, p < 0.0001) and CBF (r2 = 0.88, p < 0.0001). CONCLUSION The voxel-wise analyses revealed the brain regions, mainly the IFG, that showed hypoperfusion and atrophy related to dopaminergic loss, which suggests that the progression of dopaminergic neurodegeneration leads to regional cortical dysfunction in PD.
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Structural and metabolic correlates of neuropsychological profiles in multiple system atrophy and Parkinson's disease. Parkinsonism Relat Disord 2023; 107:105277. [PMID: 36621156 DOI: 10.1016/j.parkreldis.2022.105277] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 12/27/2022] [Accepted: 12/31/2022] [Indexed: 01/03/2023]
Abstract
BACKGROUND Despite increased recognition of cognitive impairment in Multiple System Atrophy (MSA), its neuroanatomical correlates are not well defined. We aimed to explore cognitive profiles in MSA with predominant parkinsonism (MSA-P) and Parkinson's disease (PD) and their relationship to frontostriatal structural and metabolic changes. METHODS Detailed clinical and neuropsychological evaluation was performed together with diffusion tensor imaging (DTI) and [18F]-fluoro-deoxyglucose positron emission tomography ([18F]-FDG-PET) in patients with MSA-P (n = 11) and PD (n = 11). We compared clinical and neuropsychological data to healthy controls (n = 9) and correlated neuropsychological data with imaging findings in MSA-P and PD. RESULTS Patients with MSA-P showed deficits in executive function (Trail Making Test B-A) and scored higher in measures of depression and anxiety compared to those with PD and healthy controls. Widespread frontostriatal white matter tract reduction in fractional anisotropy was seen in MSA-P and PD compared to an imaging control group. Stroop Test interference performance correlated with [18F]-FDG uptake in the bilateral dorsolateral prefrontal cortex (DLPFC) and with white matter integrity between the striatum and left inferior frontal gyrus (IFG) in PD. Trail Making Test performance correlated with corticostriatal white matter integrity along tracts from the bilateral IFG in MSA-P and from the right DLPFC in both groups. CONCLUSION Executive dysfunction was more prominent in patients with MSA-P compared to PD. DLPFC metabolism and frontostriatal white matter integrity seem to be a driver of executive function in PD, whereas alterations in corticostriatal white matter integrity may contribute more to executive dysfunction in MSA-P.
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Fan Y, Han J, Zhao L, Wu C, Wu P, Huang Z, Hao X, Ji Y, Chen D, Zhu M. Experimental Models of Cognitive Impairment for Use in Parkinson's Disease Research: The Distance Between Reality and Ideal. Front Aging Neurosci 2021; 13:745438. [PMID: 34912207 PMCID: PMC8667076 DOI: 10.3389/fnagi.2021.745438] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Accepted: 11/01/2021] [Indexed: 12/14/2022] Open
Abstract
Parkinson’s disease (PD) is the second most common neurodegenerative disease. Cognitive impairment is one of the key non-motor symptoms of PD, affecting both mortality and quality of life. However, there are few experimental studies on the pathology and treatments of PD with mild cognitive impairment (PD-MCI) and PD dementia (PDD) due to the lack of representative models. To identify new strategies for developing representative models, we systematically summarized previous studies on PD-MCI and PDD and compared differences between existing models and diseases. Our initial search identified 5432 articles, of which 738 were duplicates. A total of 227 articles met our inclusion criteria and were included in the analysis. Models fell into three categories based on model design: neurotoxin-induced, transgenic, and combined. Although the neurotoxin-induced experimental model was the most common type that was used during every time period, transgenic and combined experimental models have gained significant recent attention. Unfortunately, there remains a big gap between ideal and actual experimental models. While each model has its own disadvantages, there have been tremendous advances in the development of PD models of cognitive impairment, and almost every model can verify a hypothesis about PD-MCI or PDD. Finally, our proposed strategies for developing novel models are as follows: a set of plans that integrate symptoms, biochemistry, neuroimaging, and other objective indicators to judge and identify that the novel model plays a key role in new strategies for developing representative models; novel models should simulate different clinical features of PD-MCI or PDD; inducible α-Syn overexpression and SH-SY5Y-A53T cellular models are good candidate models of PD-MCI or PDD.
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Affiliation(s)
- Yaohua Fan
- Traditional Chinese Medicine Innovation Research Center, Shenzhen Hospital of Integrated Traditional Chinese and Western Medicine, Guangzhou University of Chinese Medicine, Shenzhen, China
| | - Jiajun Han
- Traditional Chinese Medicine Innovation Research Center, Shenzhen Hospital of Integrated Traditional Chinese and Western Medicine, Guangzhou University of Chinese Medicine, Shenzhen, China
| | - Lijun Zhao
- Traditional Chinese Medicine Innovation Research Center, Shenzhen Hospital of Integrated Traditional Chinese and Western Medicine, Guangzhou University of Chinese Medicine, Shenzhen, China
| | - Chunxiao Wu
- Traditional Chinese Medicine Innovation Research Center, Shenzhen Hospital of Integrated Traditional Chinese and Western Medicine, Guangzhou University of Chinese Medicine, Shenzhen, China.,Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Peipei Wu
- Traditional Chinese Medicine Innovation Research Center, Shenzhen Hospital of Integrated Traditional Chinese and Western Medicine, Guangzhou University of Chinese Medicine, Shenzhen, China
| | - Zifeng Huang
- Traditional Chinese Medicine Innovation Research Center, Shenzhen Hospital of Integrated Traditional Chinese and Western Medicine, Guangzhou University of Chinese Medicine, Shenzhen, China
| | - Xiaoqian Hao
- Traditional Chinese Medicine Innovation Research Center, Shenzhen Hospital of Integrated Traditional Chinese and Western Medicine, Guangzhou University of Chinese Medicine, Shenzhen, China
| | - YiChun Ji
- Shenzhen Bao'an Traditional Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen, China
| | - Dongfeng Chen
- Traditional Chinese Medicine Innovation Research Center, Shenzhen Hospital of Integrated Traditional Chinese and Western Medicine, Guangzhou University of Chinese Medicine, Shenzhen, China
| | - Meiling Zhu
- Guangzhou University of Chinese Medicine, Guangzhou, China
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