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Ortega-Robles E, de Celis Alonso B, Cantillo-Negrete J, Carino-Escobar RI, Arias-Carrión O. Advanced Magnetic Resonance Imaging for Early Diagnosis and Monitoring of Movement Disorders. Brain Sci 2025; 15:79. [PMID: 39851446 PMCID: PMC11763950 DOI: 10.3390/brainsci15010079] [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: 12/16/2024] [Revised: 01/09/2025] [Accepted: 01/14/2025] [Indexed: 01/26/2025] Open
Abstract
Advanced magnetic resonance imaging (MRI) techniques are transforming the study of movement disorders by providing valuable insights into disease mechanisms. This narrative review presents a comprehensive overview of their applications in this field, offering an updated perspective on their potential for early diagnosis, disease monitoring, and therapeutic evaluation. Emerging MRI modalities such as neuromelanin-sensitive imaging, diffusion-weighted imaging, magnetization transfer imaging, and relaxometry provide sensitive biomarkers that can detect early microstructural degeneration, iron deposition, and connectivity disruptions in key regions like the substantia nigra. These techniques enable earlier and more accurate differentiation of movement disorders, including Parkinson's disease, progressive supranuclear palsy, multiple system atrophy, corticobasal degeneration, Lewy body and frontotemporal dementia, Huntington's disease, and dystonia. Furthermore, MRI provides objective metrics for tracking disease progression and assessing therapeutic efficacy, making it an indispensable tool in clinical trials. Despite these advances, the absence of standardized protocols limits their integration into routine clinical practice. Addressing this gap and incorporating these techniques more systematically could bring the field closer to leveraging advanced MRI for personalized treatment strategies, ultimately improving outcomes for individuals with movement disorders.
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Affiliation(s)
- Emmanuel Ortega-Robles
- Unidad de Trastornos del Movimiento y Sueño, Hospital General Dr. Manuel Gea González, Calzada de Tlalpan 4800, Mexico City 14080, Mexico;
| | - Benito de Celis Alonso
- Facultad de Ciencias Físico Matemáticas, Benemérita Universidad Autónoma de Puebla, Puebla 72570, Mexico;
| | - Jessica Cantillo-Negrete
- Technological Research Subdirection, Instituto Nacional de Rehabilitación Luis Guillermo Ibarra Ibarra, Mexico City 14389, Mexico;
| | - Ruben I. Carino-Escobar
- Division of Research in Clinical Neuroscience, Instituto Nacional de Rehabilitación Luis Guillermo Ibarra Ibarra, Mexico City 14389, Mexico;
| | - Oscar Arias-Carrión
- Unidad de Trastornos del Movimiento y Sueño, Hospital General Dr. Manuel Gea González, Calzada de Tlalpan 4800, Mexico City 14080, Mexico;
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DeAngelo V, Hilliard JD, Chiang CH, Viventi J, McConnell GC. Cerebellar activity in PINK1 knockout rats during volitional gait. Brain Commun 2024; 6:fcae249. [PMID: 39464218 PMCID: PMC11503944 DOI: 10.1093/braincomms/fcae249] [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: 02/22/2023] [Revised: 01/26/2024] [Accepted: 10/16/2024] [Indexed: 10/29/2024] Open
Abstract
Preclinical models of Parkinson's disease are imperative to gain insight into the neural circuits that contribute to gait dysfunction in advanced stages of the disease. A PTEN-induced putative kinase 1 knockout early-onset model of Parkinson's disease may be a useful rodent model to study the effects of neurotransmitter degeneration caused by a loss of PTEN-induced putative kinase 1 function on brain activity during volitional gait. The goal of this study was to measure changes in neural activity at the cerebellar vermis at 8 months of age. It was found that gait deficits, except run speed, were not significantly different from age-matched wild-type controls, as previously reported. PTEN-induced putative kinase 1 knockout (n = 4) and wild-type (n = 4) rats were implanted with a micro-electrocorticographic array placed over cerebellar vermis Lobules VI (a-c) and VII. Local field potential recordings were obtained during volitional gait across a runway. Power spectral analysis and coherence analysis were used to quantify network oscillatory activity in frequency bands of interest. Cerebellar vermis power was hypoactive in the beta (VIb, VIc and VII) and alpha (VII) bands at cerebellar vermis Lobules VIb, VIc and VII in PTEN-induced putative kinase 1 knockout rats compared with wild-type controls during gait (P < 0.05). These results suggest that gait improvement in PTEN-induced putative kinase 1 knockout rats at 8 months may be a compensatory mechanism attributed to movement corrections caused by a decreased inhibition of the alpha band of cerebellar vermis Lobule VII and beta band of Lobules VIb, VIc and VII. The PTEN-induced putative kinase 1 knockout model may be a valuable tool for understanding the circuit mechanisms underlying gait dysfunction in patients with early-onset Parkinson's disease with a functional loss of PTEN-induced putative kinase 1. Future studies investigating the cerebellar vermis as a potential biomarker and therapeutic target for the treatment of gait dysfunction in Parkinson's disease are warranted.
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Affiliation(s)
- Valerie DeAngelo
- Department of Biomedical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, USA
- Semcer Center for Healthcare Innovation, Hoboken, NJ 07030, USA
| | - Justin D Hilliard
- Department of Neurosurgery, University of Florida, Gainesville, FL 32608, USA
| | - Chia-Han Chiang
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA
| | - Jonathan Viventi
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA
- Department of Neurosurgery, Duke School of Medicine, Durham, NC 27710, USA
- Department of Neurobiology, Duke School of Medicine, Durham, NC 27710, USA
- Duke Comprehensive Epilepsy Center, Duke School of Medicine, Durham, NC 27710, USA
| | - George C McConnell
- Department of Biomedical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, USA
- Semcer Center for Healthcare Innovation, Hoboken, NJ 07030, USA
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3
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He C, Yang R, Rong S, Zhang P, Chen X, Qi Q, Gao Z, Li Y, Li H, de Leeuw FE, Tuladhar AM, Duering M, Helmich RC, van der Vliet R, Darweesh SKL, Liu Z, Wang L, Cai M, Zhang Y. Temporal evolution of microstructural integrity in cerebellar peduncles in Parkinson's disease: Stage-specific patterns and dopaminergic correlates. Neuroimage Clin 2024; 44:103679. [PMID: 39366283 PMCID: PMC11489329 DOI: 10.1016/j.nicl.2024.103679] [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: 06/21/2024] [Revised: 09/25/2024] [Accepted: 09/28/2024] [Indexed: 10/06/2024]
Abstract
BACKGROUND Previous research revealed differences in cerebellar white matter integrity by disease stages, indicating a compensatory role in Parkinson's disease (PD). However, the temporal evolution of cerebellar white matter microstructure in patients with PD (PwPD) remains unclear. OBJECTIVE To unravel temporal evolution of cerebellar white matter and its dopaminergic correlates in PD. METHODS We recruited 124 PwPD from the PPMI study. The participants were divided into two subsets: Subset 1 (n = 41) had three MRI scans (baseline, 2 years, and 4 years), and Subset 2 (n = 106) had at least two MRI scans at baseline, 1 year, and/or 2 years. Free water-corrected diffusion metrics were used to measure the microstructural integrity in cerebellar peduncles (CP), the main white matter tracts connecting to and from the cerebellum. The ACAPULCO processing pipeline was used to assess cerebellar lobules volumes. Linear mixed-effect models were used to study longitudinal changes. We also examined the relationships between microstructural integrity in CP, striatal dopamine transporter specific binding ratio (SBR), and clinical symptoms. RESULTS Microstructural changes in CP showed a non-linear pattern in PwPD. Free water-corrected fractional anisotropy (FAt) increased in the first two years but declined from 2 to 4 years, while free water-corrected mean diffusivity exhibited the opposite trend. The initial increased FAt in CP correlated with cerebellar regional volume atrophy, striatal dopaminergic SBR decline, and worsening clinical symptoms, but this correlation varied across disease stages. CONCLUSIONS Our findings suggest a non-linear evolution of microstructural integrity in CP throughout the course of PD, indicating the adaptive structural reorganization of the cerebellum simultaneously with progressive striatal dopaminergic degeneration in PD.
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Affiliation(s)
- Chentao He
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong Province 510080, China; Guangzhou Key Laboratory of Diagnosis and Treatment for Neurodegenerative Diseases, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China; Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
| | - Rui Yang
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong Province 510080, China
| | - Siming Rong
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong Province 510080, China
| | - Piao Zhang
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong Province 510080, China
| | - Xi Chen
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong Province 510080, China
| | - Qi Qi
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong Province 510080, China
| | - Ziqi Gao
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong Province 510080, China
| | - Yan Li
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong Province 510080, China
| | - Hao Li
- Radboud University Medical Center, Nijmegen, Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, the Netherlands
| | - Frank-Erik de Leeuw
- Radboud University Medical Center, Nijmegen, Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, the Netherlands
| | - Anil M Tuladhar
- Radboud University Medical Center, Nijmegen, Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, the Netherlands
| | - Marco Duering
- Medical Image Analysis Center (MIAC AG) and Department of Biomedical Engineering, University of Basel, Basel, Switzerland; Institute for Stroke and Dementia Research (ISD), LMU University Hospital, LMU Munich, Germany
| | - Rick C Helmich
- Radboud University Medical Center, Nijmegen, Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, the Netherlands
| | - Rick van der Vliet
- Department of Neurology, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, the Netherlands
| | - Sirwan K L Darweesh
- Radboud University Medical Center, Nijmegen, Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, the Netherlands
| | - Zaiyi Liu
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China; Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong Province 510080, China
| | - Lijuan Wang
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong Province 510080, China; Guangzhou Key Laboratory of Diagnosis and Treatment for Neurodegenerative Diseases, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
| | - Mengfei Cai
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong Province 510080, China; Radboud University Medical Center, Nijmegen, Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, the Netherlands.
| | - Yuhu Zhang
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong Province 510080, China; Guangzhou Key Laboratory of Diagnosis and Treatment for Neurodegenerative Diseases, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China; Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China.
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Tchetchenian A, Zekelman L, Chen Y, Rushmore J, Zhang F, Yeterian EH, Makris N, Rathi Y, Meijering E, Song Y, O'Donnell LJ. Deep multimodal saliency parcellation of cerebellar pathways: Linking microstructure and individual function through explainable multitask learning. Hum Brain Mapp 2024; 45:e70008. [PMID: 39185598 PMCID: PMC11345609 DOI: 10.1002/hbm.70008] [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: 01/29/2024] [Revised: 07/18/2024] [Accepted: 08/10/2024] [Indexed: 08/27/2024] Open
Abstract
Parcellation of human cerebellar pathways is essential for advancing our understanding of the human brain. Existing diffusion magnetic resonance imaging tractography parcellation methods have been successful in defining major cerebellar fibre tracts, while relying solely on fibre tract structure. However, each fibre tract may relay information related to multiple cognitive and motor functions of the cerebellum. Hence, it may be beneficial for parcellation to consider the potential importance of the fibre tracts for individual motor and cognitive functional performance measures. In this work, we propose a multimodal data-driven method for cerebellar pathway parcellation, which incorporates both measures of microstructure and connectivity, and measures of individual functional performance. Our method involves first training a multitask deep network to predict various cognitive and motor measures from a set of fibre tract structural features. The importance of each structural feature for predicting each functional measure is then computed, resulting in a set of structure-function saliency values that are clustered to parcellate cerebellar pathways. We refer to our method as Deep Multimodal Saliency Parcellation (DeepMSP), as it computes the saliency of structural measures for predicting cognitive and motor functional performance, with these saliencies being applied to the task of parcellation. Applying DeepMSP to a large-scale dataset from the Human Connectome Project Young Adult study (n = 1065), we found that it was feasible to identify multiple cerebellar pathway parcels with unique structure-function saliency patterns that were stable across training folds. We thoroughly experimented with all stages of the DeepMSP pipeline, including network selection, structure-function saliency representation, clustering algorithm, and cluster count. We found that a 1D convolutional neural network architecture and a transformer network architecture both performed comparably for the multitask prediction of endurance, strength, reading decoding, and vocabulary comprehension, with both architectures outperforming a fully connected network architecture. Quantitative experiments demonstrated that a proposed low-dimensional saliency representation with an explicit measure of motor versus cognitive category bias achieved the best parcellation results, while a parcel count of four was most successful according to standard cluster quality metrics. Our results suggested that motor and cognitive saliencies are distributed across the cerebellar white matter pathways. Inspection of the final k = 4 parcellation revealed that the highest-saliency parcel was most salient for the prediction of both motor and cognitive performance scores and included parts of the middle and superior cerebellar peduncles. Our proposed saliency-based parcellation framework, DeepMSP, enables multimodal, data-driven tractography parcellation. Through utilising both structural features and functional performance measures, this parcellation strategy may have the potential to enhance the study of structure-function relationships of the cerebellar pathways.
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Affiliation(s)
- Ari Tchetchenian
- Biomedical Image Computing Group, School of Computer Science and EngineeringUniversity of New South Wales (UNSW)SydneyNew South WalesAustralia
| | - Leo Zekelman
- Department of Radiology, Brigham and Women's HospitalHarvard Medical SchoolBostonMassachusettsUSA
- Harvard UniversityCambridgeMassachusettsUSA
| | - Yuqian Chen
- Department of Radiology, Brigham and Women's HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Jarrett Rushmore
- Department of PsychiatryMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Department of NeurologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Department of RadiologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Department of Anatomy and NeurobiologyBoston University School of MedicineBostonMassachusettsUSA
| | - Fan Zhang
- School of Information and Communication EngineeringUniversity of Electronic Science and Technology of ChinaChengduChina
| | | | - Nikos Makris
- Department of PsychiatryMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Department of NeurologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Department of RadiologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Department of Psychiatry, Brigham and Women's HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Yogesh Rathi
- Department of Radiology, Brigham and Women's HospitalHarvard Medical SchoolBostonMassachusettsUSA
- Department of Psychiatry, Brigham and Women's HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Erik Meijering
- Biomedical Image Computing Group, School of Computer Science and EngineeringUniversity of New South Wales (UNSW)SydneyNew South WalesAustralia
| | - Yang Song
- Biomedical Image Computing Group, School of Computer Science and EngineeringUniversity of New South Wales (UNSW)SydneyNew South WalesAustralia
| | - Lauren J. O'Donnell
- Department of Radiology, Brigham and Women's HospitalHarvard Medical SchoolBostonMassachusettsUSA
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Shobeiri P, Hosseini Shabanan S, Haghshomar M, Khanmohammadi S, Fazeli S, Sotoudeh H, Kamali A. Cerebellar Microstructural Abnormalities in Obsessive-Compulsive Disorder (OCD): a Systematic Review of Diffusion Tensor Imaging Studies. CEREBELLUM (LONDON, ENGLAND) 2024; 23:778-801. [PMID: 37291229 DOI: 10.1007/s12311-023-01573-x] [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: 05/22/2023] [Indexed: 06/10/2023]
Abstract
Previous neuroimaging studies have suggested that obsessive-compulsive disorder (OCD) is associated with altered resting-state functional connectivity of the cerebellum. In this study, we aimed to describe the most significant and reproducible microstructural abnormalities and cerebellar changes associated with obsessive-compulsive disorder (OCD) using diffusion tensor imaging (DTI) investigations. PubMed and EMBASE were searched for relevant studies using the PRISMA 2020 protocol. A total of 17 publications were chosen for data synthesis after screening titles and abstracts, full-text examination, and executing the inclusion criteria. The patterns of cerebellar white matter (WM) integrity loss, determined by fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) metrics, varied across studies and symptoms. Changes in fractional anisotropy (FA) values were described in six publications, which were decreased in four and increased in two studies. An increase in diffusivity parameters of the cerebellum (i.e., MD, RD, and AD) in OCD patients was reported in four studies. Alterations of the cerebellar connectivity with other brain areas were also detected in three studies. Heterogenous results were found in studies that investigated cerebellar microstructural abnormalities in correlation with symptom dimension or severity. OCD's complex phenomenology may be characterized by changes in cerebellar WM connectivity across wide networks, as shown by DTI studies on OCD patients in both children and adults. Classification features in machine learning and clinical tools for diagnosing OCD and determining the prognosis of the disorder might both benefit from using cerebellar DTI data.
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Affiliation(s)
- Parnian Shobeiri
- Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
- NeuroImaging Network (NIN), Universal Scientific Education and Research Network (USERN), Tehran, Iran.
- Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
| | | | - Maryam Haghshomar
- NeuroImaging Network (NIN), Universal Scientific Education and Research Network (USERN), Tehran, Iran
- Department of Radiology, Northwestern University, Chicago, IL, USA
| | - Shaghayegh Khanmohammadi
- Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran
- Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Soudabeh Fazeli
- Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Houman Sotoudeh
- Department of Radiology and Neurology, University of Alabama at Birmingham (UAB), Birmingham, AL, USA
| | - Arash Kamali
- Department of Diagnostic and Interventional Radiology, University of Texas McGovern Medical School, Houston, TX, USA
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Zhong Y, Liu H, Liu G, Liang Y, Dai C, Zhao L, Lai H, Mo L, Tan C, Deng F, Liu X, Chen L. Cerebellar and cerebral white matter changes in Parkinson's disease with resting tremor. Neuroradiology 2023; 65:1497-1506. [PMID: 37548715 DOI: 10.1007/s00234-023-03206-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Accepted: 07/28/2023] [Indexed: 08/08/2023]
Abstract
PURPOSE Cerebellum modulates the amplitude of resting tremor in Parkinson's disease (PD) via cerebello-thalamo-cortical (CTC) circuit. Tremor-related white matter alterations have been identified in PD patients by pathological studies, but in vivo evidence is limited; the influence of such cerebellar white matter alterations on tremor-related brain network, including CTC circuit, is also unclear. In this study, we investigated the cerebral and cerebellar white matter alterations in PD patients with resting tremor using diffusion tensor imaging (DTI). METHODS In this study, 30 PD patients with resting tremor (PDWR), 26 PD patients without resting tremor (PDNR), and 30 healthy controls (HCs) from the Parkinson's Progression Markers Initiative (PPMI) cohort were included. Tract-based spatial statistics (TBSS) and region of interest-based analyses were conducted to determine white matter difference. Correlation analysis between DTI measures and clinical characteristics was also performed. RESULTS In the whole brain, TBSS and region of interest-based analyses identified higher fractional anisotropy (FA) value, lower mean diffusivity (MD) value, and lower radial diffusivity (RD) in multiple fibers. In the cerebellum, TBSS analysis revealed significantly higher FA value, decreased RD value as well as MD value in multiple cerebellar tracts including the inferior cerebellar peduncle (ICP) and middle cerebellar peduncle (MCP) when comparing the PDWR with HC, and higher FA value in the MCP when compared with PDNR. CONCLUSION We identified better white matter integrity in the cerebrum and cerebellum in PDWR indicating a potential association between the cerebral and cerebellar white matter and resting tremor in PD.
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Affiliation(s)
- Yuke Zhong
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, 74 Linjiang Road, Yuzhong District, Chongqing, 400010, China
| | - Hang Liu
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, 74 Linjiang Road, Yuzhong District, Chongqing, 400010, China
| | - Guohui Liu
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, 74 Linjiang Road, Yuzhong District, Chongqing, 400010, China
| | - Yi Liang
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, 74 Linjiang Road, Yuzhong District, Chongqing, 400010, China
| | - Chengcheng Dai
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, 74 Linjiang Road, Yuzhong District, Chongqing, 400010, China
| | - Lili Zhao
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, 74 Linjiang Road, Yuzhong District, Chongqing, 400010, China
| | - Hongyu Lai
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, 74 Linjiang Road, Yuzhong District, Chongqing, 400010, China
| | - Lijuan Mo
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, 74 Linjiang Road, Yuzhong District, Chongqing, 400010, China
| | - Changhong Tan
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, 74 Linjiang Road, Yuzhong District, Chongqing, 400010, China
| | - Fen Deng
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, 74 Linjiang Road, Yuzhong District, Chongqing, 400010, China
| | - Xi Liu
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, 74 Linjiang Road, Yuzhong District, Chongqing, 400010, China.
| | - Lifen Chen
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, 74 Linjiang Road, Yuzhong District, Chongqing, 400010, China.
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Zhou F, Tan C, Song C, Wang M, Yuan J, Liu Y, Cai S, Liu Q, Shen Q, Tang Y, Li X, Liao H. Abnormal intra- and inter-network functional connectivity of brain networks in early-onset Parkinson's disease and late-onset Parkinson's disease. Front Aging Neurosci 2023; 15:1132723. [PMID: 37032830 PMCID: PMC10080130 DOI: 10.3389/fnagi.2023.1132723] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Accepted: 03/13/2023] [Indexed: 04/11/2023] Open
Abstract
Objective The purpose of this study is to look into the altered functional connectivity of brain networks in Early-Onset Parkinson's Disease (EOPD) and Late-Onset Parkinson's Disease (LOPD), as well as their relationship to clinical symptoms. Methods A total of 50 patients with Parkinson' disease (28 EOPD and 22 LOPD) and 49 healthy controls (25 Young Controls and 24 Old Controls) were admitted to our study. Employing independent component analysis, we constructed the brain networks of EOPD and Young Controls, LOPD and Old Controls, respectively, and obtained the functional connectivity alterations in brain networks. Results Cerebellar network (CN), Sensorimotor Network (SMN), Executive Control Network (ECN), and Default Mode Network (DMN) were selected as networks of interest. Compared with their corresponding health controls, EOPD showed increased functional connectivity within the SMN and ECN and no abnormalities of inter-network functional connectivity were found, LOPD demonstrated increased functional connectivity within the ECN while decreased functional connectivity within the CN. Furthermore, in LOPD, functional connectivity between the SMN and DMN was increased. The functional connectivity of the post-central gyrus within the SMN in EOPD was inversely correlated with the Unified Parkinson's Disease Rating Scale Part III scores. Age, age of onset, and MMSE scores are significantly different between EOPD and LOPD (p < 0.05). Conclusion There is abnormal functional connectivity of networks in EOPD and LOPD, which could be the manifestation of the associated pathological damage or compensation.
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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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A review on pathology, mechanism, and therapy for cerebellum and tremor in Parkinson's disease. NPJ Parkinsons Dis 2022; 8:82. [PMID: 35750692 PMCID: PMC9232614 DOI: 10.1038/s41531-022-00347-2] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Accepted: 05/30/2022] [Indexed: 12/16/2022] Open
Abstract
Tremor is one of the core symptoms of Parkinson’s disease (PD), but its mechanism is poorly understood. The cerebellum is a growing focus in PD-related researches and is reported to play an important role in tremor in PD. The cerebellum may participate in the modulation of tremor amplitude via cerebello-thalamo-cortical circuits. The cerebellar excitatory projections to the ventral intermediate nucleus of the thalamus may be enhanced due to PD-related changes, including dopaminergic/non-dopaminergic system abnormality, white matter damage, and deep nuclei impairment, which may contribute to dysregulation and resistance to levodopa of tremor. This review summarized the pathological, structural, and functional changes of the cerebellum in PD and discussed the role of the cerebellum in PD-related tremor, aiming to provide an overview of the cerebellum-related mechanism of tremor in PD.
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Environmentally Toxic Solid Nanoparticles in Noradrenergic and Dopaminergic Nuclei and Cerebellum of Metropolitan Mexico City Children and Young Adults with Neural Quadruple Misfolded Protein Pathologies and High Exposures to Nano Particulate Matter. TOXICS 2022; 10:toxics10040164. [PMID: 35448425 PMCID: PMC9028025 DOI: 10.3390/toxics10040164] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Revised: 03/17/2022] [Accepted: 03/22/2022] [Indexed: 11/17/2022]
Abstract
Quadruple aberrant hyperphosphorylated tau, beta-amyloid, α-synuclein and TDP-43 neuropathology and metal solid nanoparticles (NPs) are documented in the brains of children and young adults exposed to Metropolitan Mexico City (MMC) pollution. We investigated environmental NPs reaching noradrenergic and dopaminergic nuclei and the cerebellum and their associated ultrastructural alterations. Here, we identify NPs in the locus coeruleus (LC), substantia nigrae (SN) and cerebellum by transmission electron microscopy (TEM) and energy-dispersive X-ray spectrometry (EDX) in 197 samples from 179 MMC residents, aged 25.9 ± 9.2 years and seven older adults aged 63 ± 14.5 years. Fe, Ti, Hg, W, Al and Zn spherical and acicular NPs were identified in the SN, LC and cerebellar neural and vascular mitochondria, endoplasmic reticulum, Golgi, neuromelanin, heterochromatin and nuclear pore complexes (NPCs) along with early and progressive neurovascular damage and cerebellar endothelial erythrophagocytosis. Strikingly, FeNPs 4 ± 1 nm and Hg NPs 8 ± 2 nm were seen predominantly in the LC and SN. Nanoparticles could serve as a common denominator for misfolded proteins and could play a role in altering and obstructing NPCs. The NPs/carbon monoxide correlation is potentially useful for evaluating early neurodegeneration risk in urbanites. Early life NP exposures pose high risk to brains for development of lethal neurologic outcomes. NP emissions sources ought to be clearly recognized, regulated, and monitored; future generations are at stake.
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