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Sun Y, Hu Y, Qiu Y, Zhang Y, Jiang C, Lu P, Xu Q, Shi Y, Wei H, Zhou Y. Characterization of white matter over 1–2 years in small vessel disease using MR-based quantitative susceptibility mapping and free-water mapping. Front Aging Neurosci 2022; 14:998051. [PMID: 36247993 PMCID: PMC9562046 DOI: 10.3389/fnagi.2022.998051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Accepted: 09/07/2022] [Indexed: 11/13/2022] Open
Abstract
PurposeThe aim of this study was to investigate alterations in white matter lesions (WMLs) and normal-appearing white matter (NAWM) with small vessel disease (SVD) over 1–2 years using quantitative susceptibility mapping (QSM) and free-water (FW) mapping.MethodsFifty-one SVD patients underwent MRI brain scans and neuropsychological testing both at baseline and follow-up. The main approach for treating these patients is the management of risk factors. Quantitative susceptibility (QS), fractional anisotropy (FA), mean diffusivity (MD), FW, FW-corrected FA (FAT), and FW-corrected MD (MDT) maps within WMLs and NAWM were generated. Furthermore, the JHU-ICBM-DTI label atlas was used as an anatomic guide, and the measurements of the segmented NAWMs were calculated. The average regional values were extracted, and a paired t-test was used to analyze the longitudinal change. Partial correlations were used to assess the relationship between the MRI indices changes (e.g., ΔQSfollowup − baseline/QSbaseline) and the cognitive function changes (e.g., ΔMoCAfollowup − baseline/MoCAbaseline).ResultsAfter SVD risk factor control, no gradual cognitive decline occurred during 1–2 years. However, we still found that the QS values (index of demyelination) increased in the NAWM at follow-up, especially in the NAWM part of the left superior frontal blade (SF), left occipital blade, right uncinate fasciculus, and right corticospinal tract (CST). FW (index of neuroinflammation/edema) analysis revealed that the follow-up group differed from the baseline group in the NAWM part of the right CST and inferior frontal blade (IF). Decreased FAT (index of axonal loss) was observed in the NAWM part of the right SF and IF at follow-up. In addition, the FAT changes in the NAWM part of the right IF were associated with overall cognitive performance changes. In contrast, no significant differences were found in the WMLs.ConclusionThe NAWM was still in the progressive injury process over time, while WMLs remained relatively stable, which supports the notion that SVD is a chronic progressive disease. The process of axonal loss in the NAWM part of the prefrontal lobe might be a biomarker of cognitive changes in the evolution of SVD.
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Affiliation(s)
- Yawen Sun
- Department of Radiology, School of Medicine, Ren Ji Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Ying Hu
- Department of Radiology, School of Medicine, Ren Ji Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Yage Qiu
- Department of Radiology, School of Medicine, Ren Ji Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Yuyao Zhang
- School of Information and Science and Technology, ShanghaiTech University, Shanghai, China
| | - Changhao Jiang
- School of Information and Science and Technology, ShanghaiTech University, Shanghai, China
| | - Peiwen Lu
- Department of Neurology, School of Medicine, Ren Ji Hospital, Shanghai Jiao Tong University, Shanghai, China
- Ren Ji-UNSW CHeBA Neurocognitive Center, School of Medicine, Ren Ji Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Qun Xu
- Department of Neurology, School of Medicine, Ren Ji Hospital, Shanghai Jiao Tong University, Shanghai, China
- Ren Ji-UNSW CHeBA Neurocognitive Center, School of Medicine, Ren Ji Hospital, Shanghai Jiao Tong University, Shanghai, China
- Department of Health Manage Center, School of Medicine, Ren Ji Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Yuting Shi
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Hongjiang Wei
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
- *Correspondence: Yan Zhou
| | - Yan Zhou
- Department of Radiology, School of Medicine, Ren Ji Hospital, Shanghai Jiao Tong University, Shanghai, China
- Hongjiang Wei
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Wang L, Wu P, Brown P, Zhang W, Liu F, Han Y, Zuo CT, Cheng W, Feng J. Association of Structural Measurements of Brain Reserve With Motor Progression in Patients With Parkinson Disease. Neurology 2022; 99:e977-e988. [PMID: 35667838 PMCID: PMC7613818 DOI: 10.1212/wnl.0000000000200814] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Accepted: 04/19/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES To investigate the relationship between baseline structural measurements of brain reserve and clinical progression in Parkinson disease (PD). To further provide a possible underlying mechanism for structural measurements of brain reserve in PD, we combined functional and transcriptional data and investigated their relationship with progression-associated patterns derived from structural measurements and longitudinal clinical scores. METHODS This longitudinal study collected data from June 2010 to March 2019 from 2 datasets. The Parkinson's Progression Markers Initiative (PPMI) included controls and patients with newly diagnosed PD from 24 participating sites worldwide. Results were confirmed using data from the Huashan dataset (Shanghai, China), which included controls and patients with PD. Clinical symptoms were assessed with Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS) scores and Schwab & England activities of daily living (ADL). Both datasets were followed up to 5 years. Linear mixed-effects (LME) models were performed to examine whether changes in clinical scores over time differed as a function of brain structural measurements at baseline. RESULTS A total of 389 patients with PD (n = 346, age 61.3 ± 10.03, 35% female, PPMI dataset; n = 43, age 59.4 ± 7.3, 38.7% female, Huashan dataset) with T1-MRI and follow-up clinical assessments were included in this study. Results of LME models revealed significant interactions between baseline structural measurements of subcortical regions and time on longitudinal deterioration of clinical scores (MDS-UPDRS Part II, absolute β > 0.27; total MDS-UPDRS scores, absolute β > 1.05; postural instability-gait difficulty (PIGD) score, absolute β > 0.03; Schwab & England ADL, absolute β > 0.59; all p < 0.05, false discovery rate corrected). The interaction of baseline structural measurements of subcortical regions and time on longitudinal deterioration of the PIGD score was replicated using data from Huashan Hospital. Furthermore, the β-coefficients of these interactions recapitulated the spatial distribution of dopaminergic, metabolic, and structural changes between patients with PD and normal controls and the spatial distribution of expression of the α-synuclein gene (SNCA). DISCUSSION Patients with PD with greater brain resources (that is, higher deformation-based morphometry values) had greater compensatory capacity, which was associated with slower rates of clinical progression. This knowledge could be used to stratify and monitor patients for clinical trials.
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Affiliation(s)
- Linbo Wang
- From the Institute of Science and Technology for Brain-inspired Intelligence (L.W., W.Z., W.C., J.F.), Fudan University; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University) (L.W., W.Z., W.C., J.F.), Ministry of Education; PET Center (P.W., C.-T.Z.), Huashan Hospital, Fudan University, Shanghai, China; Medical Research Council Brain Network Dynamics Unit (P.B.), and Nuffield Department of Clinical Neurosciences (P.B.), John Radcliffe Hospital, University of Oxford, United Kingdom; Department of Neurology (F.L., C.-T.Z.), Huashan Hospital North, Fudan University; Department of Neurology (Y.H.), Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine; Human Phenome Institute (C.-T.Z.), Fudan University; Zhangjiang Fudan International Innovation Center (W.C., J.F.), Shanghai, China; Department of Computer Science (W.C., J.F.), University of Warwick, Coventry, United Kingdom; and Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence (W.C., J.F.), Zhejiang Normal University, Jinhua, China
| | - Ping Wu
- From the Institute of Science and Technology for Brain-inspired Intelligence (L.W., W.Z., W.C., J.F.), Fudan University; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University) (L.W., W.Z., W.C., J.F.), Ministry of Education; PET Center (P.W., C.-T.Z.), Huashan Hospital, Fudan University, Shanghai, China; Medical Research Council Brain Network Dynamics Unit (P.B.), and Nuffield Department of Clinical Neurosciences (P.B.), John Radcliffe Hospital, University of Oxford, United Kingdom; Department of Neurology (F.L., C.-T.Z.), Huashan Hospital North, Fudan University; Department of Neurology (Y.H.), Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine; Human Phenome Institute (C.-T.Z.), Fudan University; Zhangjiang Fudan International Innovation Center (W.C., J.F.), Shanghai, China; Department of Computer Science (W.C., J.F.), University of Warwick, Coventry, United Kingdom; and Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence (W.C., J.F.), Zhejiang Normal University, Jinhua, China
| | - Peter Brown
- From the Institute of Science and Technology for Brain-inspired Intelligence (L.W., W.Z., W.C., J.F.), Fudan University; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University) (L.W., W.Z., W.C., J.F.), Ministry of Education; PET Center (P.W., C.-T.Z.), Huashan Hospital, Fudan University, Shanghai, China; Medical Research Council Brain Network Dynamics Unit (P.B.), and Nuffield Department of Clinical Neurosciences (P.B.), John Radcliffe Hospital, University of Oxford, United Kingdom; Department of Neurology (F.L., C.-T.Z.), Huashan Hospital North, Fudan University; Department of Neurology (Y.H.), Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine; Human Phenome Institute (C.-T.Z.), Fudan University; Zhangjiang Fudan International Innovation Center (W.C., J.F.), Shanghai, China; Department of Computer Science (W.C., J.F.), University of Warwick, Coventry, United Kingdom; and Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence (W.C., J.F.), Zhejiang Normal University, Jinhua, China
| | - Wei Zhang
- From the Institute of Science and Technology for Brain-inspired Intelligence (L.W., W.Z., W.C., J.F.), Fudan University; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University) (L.W., W.Z., W.C., J.F.), Ministry of Education; PET Center (P.W., C.-T.Z.), Huashan Hospital, Fudan University, Shanghai, China; Medical Research Council Brain Network Dynamics Unit (P.B.), and Nuffield Department of Clinical Neurosciences (P.B.), John Radcliffe Hospital, University of Oxford, United Kingdom; Department of Neurology (F.L., C.-T.Z.), Huashan Hospital North, Fudan University; Department of Neurology (Y.H.), Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine; Human Phenome Institute (C.-T.Z.), Fudan University; Zhangjiang Fudan International Innovation Center (W.C., J.F.), Shanghai, China; Department of Computer Science (W.C., J.F.), University of Warwick, Coventry, United Kingdom; and Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence (W.C., J.F.), Zhejiang Normal University, Jinhua, China
| | - Fengtao Liu
- From the Institute of Science and Technology for Brain-inspired Intelligence (L.W., W.Z., W.C., J.F.), Fudan University; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University) (L.W., W.Z., W.C., J.F.), Ministry of Education; PET Center (P.W., C.-T.Z.), Huashan Hospital, Fudan University, Shanghai, China; Medical Research Council Brain Network Dynamics Unit (P.B.), and Nuffield Department of Clinical Neurosciences (P.B.), John Radcliffe Hospital, University of Oxford, United Kingdom; Department of Neurology (F.L., C.-T.Z.), Huashan Hospital North, Fudan University; Department of Neurology (Y.H.), Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine; Human Phenome Institute (C.-T.Z.), Fudan University; Zhangjiang Fudan International Innovation Center (W.C., J.F.), Shanghai, China; Department of Computer Science (W.C., J.F.), University of Warwick, Coventry, United Kingdom; and Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence (W.C., J.F.), Zhejiang Normal University, Jinhua, China
| | - Yan Han
- From the Institute of Science and Technology for Brain-inspired Intelligence (L.W., W.Z., W.C., J.F.), Fudan University; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University) (L.W., W.Z., W.C., J.F.), Ministry of Education; PET Center (P.W., C.-T.Z.), Huashan Hospital, Fudan University, Shanghai, China; Medical Research Council Brain Network Dynamics Unit (P.B.), and Nuffield Department of Clinical Neurosciences (P.B.), John Radcliffe Hospital, University of Oxford, United Kingdom; Department of Neurology (F.L., C.-T.Z.), Huashan Hospital North, Fudan University; Department of Neurology (Y.H.), Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine; Human Phenome Institute (C.-T.Z.), Fudan University; Zhangjiang Fudan International Innovation Center (W.C., J.F.), Shanghai, China; Department of Computer Science (W.C., J.F.), University of Warwick, Coventry, United Kingdom; and Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence (W.C., J.F.), Zhejiang Normal University, Jinhua, China
| | - Chuan-Tao Zuo
- From the Institute of Science and Technology for Brain-inspired Intelligence (L.W., W.Z., W.C., J.F.), Fudan University; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University) (L.W., W.Z., W.C., J.F.), Ministry of Education; PET Center (P.W., C.-T.Z.), Huashan Hospital, Fudan University, Shanghai, China; Medical Research Council Brain Network Dynamics Unit (P.B.), and Nuffield Department of Clinical Neurosciences (P.B.), John Radcliffe Hospital, University of Oxford, United Kingdom; Department of Neurology (F.L., C.-T.Z.), Huashan Hospital North, Fudan University; Department of Neurology (Y.H.), Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine; Human Phenome Institute (C.-T.Z.), Fudan University; Zhangjiang Fudan International Innovation Center (W.C., J.F.), Shanghai, China; Department of Computer Science (W.C., J.F.), University of Warwick, Coventry, United Kingdom; and Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence (W.C., J.F.), Zhejiang Normal University, Jinhua, China
| | - Wei Cheng
- From the Institute of Science and Technology for Brain-inspired Intelligence (L.W., W.Z., W.C., J.F.), Fudan University; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University) (L.W., W.Z., W.C., J.F.), Ministry of Education; PET Center (P.W., C.-T.Z.), Huashan Hospital, Fudan University, Shanghai, China; Medical Research Council Brain Network Dynamics Unit (P.B.), and Nuffield Department of Clinical Neurosciences (P.B.), John Radcliffe Hospital, University of Oxford, United Kingdom; Department of Neurology (F.L., C.-T.Z.), Huashan Hospital North, Fudan University; Department of Neurology (Y.H.), Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine; Human Phenome Institute (C.-T.Z.), Fudan University; Zhangjiang Fudan International Innovation Center (W.C., J.F.), Shanghai, China; Department of Computer Science (W.C., J.F.), University of Warwick, Coventry, United Kingdom; and Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence (W.C., J.F.), Zhejiang Normal University, Jinhua, China
| | - Jianfeng Feng
- From the Institute of Science and Technology for Brain-inspired Intelligence (L.W., W.Z., W.C., J.F.), Fudan University; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University) (L.W., W.Z., W.C., J.F.), Ministry of Education; PET Center (P.W., C.-T.Z.), Huashan Hospital, Fudan University, Shanghai, China; Medical Research Council Brain Network Dynamics Unit (P.B.), and Nuffield Department of Clinical Neurosciences (P.B.), John Radcliffe Hospital, University of Oxford, United Kingdom; Department of Neurology (F.L., C.-T.Z.), Huashan Hospital North, Fudan University; Department of Neurology (Y.H.), Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine; Human Phenome Institute (C.-T.Z.), Fudan University; Zhangjiang Fudan International Innovation Center (W.C., J.F.), Shanghai, China; Department of Computer Science (W.C., J.F.), University of Warwick, Coventry, United Kingdom; and Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence (W.C., J.F.), Zhejiang Normal University, Jinhua, China.
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Xie L, Hu L. Research progress in the early diagnosis of Parkinson’s disease. Neurol Sci 2022; 43:6225-6231. [DOI: 10.1007/s10072-022-06316-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Accepted: 08/02/2022] [Indexed: 10/15/2022]
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Wei L, Ding M, Zhang Y, Wang H. Decoding transcriptional signatures of the association between free water and macroscale organizations in healthy adolescents. Neuroimage 2022; 261:119514. [PMID: 35901916 DOI: 10.1016/j.neuroimage.2022.119514] [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: 01/04/2022] [Revised: 07/11/2022] [Accepted: 07/22/2022] [Indexed: 11/16/2022] Open
Abstract
We leveraged a novel index of diffusion MRI to investigate the relationships among cortical free water, macro-organizations and gene expression in healthy adults. Few research has been conducted to investigate the role of free water in the healthy adults due to it can easily be affected also by aging diseases. High quality data of 350 subjects from Human Connectome Project were used in our study. Cortical free water was estimated by using a bi-tensor model. The free water was high in the limbic, insular and somatosensory cortex, while being lower in motor and association cortex. The negative correlation between the free water and cortical thickness has been consistently identified in almost all the cortical regions. Negative correlation between the cortical free water and structural covariance (rho=-0.38, pspin=0.005) revealed the free water was sensitive to cortical heterogeneity. Using human gene expression dataset, we found the gene expression pattern of the relationship between the free water and cortical thickness spatially coupled with primary gradient of structural covariance network (rho=0.40, pspin=0.004). Our findings indicated the free water was sensitive to the cortical cellular status. The relationship between free water and macroscale organization also reflected hierarchal structures of cerebral cortex.
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Affiliation(s)
- Lei Wei
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, PR China.
| | - Ming Ding
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, PR China
| | - Yuwen Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, PR China
| | - He Wang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, PR China; Human Phenome Institute, Fudan University, Shanghai, PR China; Department of Neurology, Zhongshan Hospital, Fudan University, Shanghai, PR China.
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Berger M, Pirpamer L, Hofer E, Ropele S, Duering M, Gesierich B, Pasternak O, Enzinger C, Schmidt R, Koini M. Free water diffusion MRI and executive function with a speed component in healthy aging. Neuroimage 2022; 257:119303. [PMID: 35568345 PMCID: PMC9465649 DOI: 10.1016/j.neuroimage.2022.119303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 05/06/2022] [Accepted: 05/09/2022] [Indexed: 11/12/2022] Open
Abstract
Extracellular free water (FW) increases are suggested to better provide pathophysiological information in brain aging than conventional biomarkers such as fractional anisotropy. The aim of the present study was to determine the relationship between conventional biomarkers, FW in white matter hyperintensities (WMH), FW in normal appearing white matter (NAWM) and in white matter tracts and executive functions (EF) with a speed component in elderly persons. We examined 226 healthy elderly participants (median age 69.83 years, IQR: 56.99–74.42) who underwent brain MRI and neuropsychological examination. FW in WMH and in NAWM as well as FW corrected diffusion metrics and measures derived from conventional MRI (white matter hyperintensities, brain volume, lacunes) were used in partial correlation (adjusted for age) to assess their correlation with EF with a speed component. Random forest analysis was used to assess the relative importance of these variables as determinants. Lastly, linear regression analyses of FW in white matter tracts corrected for risk factors of cognitive and white matter deterioration, were used to examine the role of specific tracts on EF with a speed component, which were then ranked with random forest regression. Partial correlation analyses revealed that almost all imaging metrics showed a significant association with EF with a speed component (r = −0.213 – 0.266). Random forest regression highlighted FW in WMH and in NAWM as most important among all diffusion and structural MRI metrics. The fornix (R2=0.421, p = 0.018) and the corpus callosum (genu (R2 = 0.418, p = 0.021), prefrontal (R2 = 0.416, p = 0.026), premotor (R2 = 0.418, p = 0.021)) were associated with EF with a speed component in tract based regression analyses and had highest variables importance. In a normal aging population FW in WMH and NAWM is more closely related to EF with a speed component than standard DTI and brain structural measures. Higher amounts of FW in the fornix and the frontal part of the corpus callosum leads to deteriorating EF with a speed component.
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Affiliation(s)
- Martin Berger
- Department of Neurology, Division of Neurogeriatrics, Medical University of Graz, Auenbruggerplatz 22, Graz 8036, Austria
| | - Lukas Pirpamer
- Department of Neurology, Division of Neurogeriatrics, Medical University of Graz, Auenbruggerplatz 22, Graz 8036, Austria
| | - Edith Hofer
- Department of Neurology, Division of Neurogeriatrics, Medical University of Graz, Auenbruggerplatz 22, Graz 8036, Austria; Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, Austria
| | - Stefan Ropele
- Department of Neurology, Division of Neurogeriatrics, Medical University of Graz, Auenbruggerplatz 22, Graz 8036, Austria
| | - Marco Duering
- Medical Image Analysis Center (MIAC AG) and Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Benno Gesierich
- Institute for Stroke and Dementia Research (ISD), University Hospital, Munich, Germany
| | - Ofer Pasternak
- Departments of Psychiatry and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Reinhold Schmidt
- Department of Neurology, Division of Neurogeriatrics, Medical University of Graz, Auenbruggerplatz 22, Graz 8036, Austria.
| | - Marisa Koini
- Department of Neurology, Division of Neurogeriatrics, Medical University of Graz, Auenbruggerplatz 22, Graz 8036, Austria
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Otani RTV, Yamamoto JYS, Nunes DM, Haddad MS, Parmera JB. Magnetic resonance and dopamine transporter imaging for the diagnosis of Parkinson´s disease: a narrative review. ARQUIVOS DE NEURO-PSIQUIATRIA 2022; 80:116-125. [PMID: 35976320 PMCID: PMC9491424 DOI: 10.1590/0004-282x-anp-2022-s130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 04/29/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND the diagnosis of Parkinson's disease (PD) can be challenging, especially in the early stages, albeit its updated and validated clinical criteria. Recent developments on neuroimaging in PD, altogether with its consolidated role of excluding secondary and other neurodegenerative causes of parkinsonism, provide more confidence in the diagnosis across the different stages of the disease. This review highlights current knowledge and major recent advances in magnetic resonance and dopamine transporter imaging in aiding PD diagnosis. OBJECTIVE This study aims to review current knowledge about the role of magnetic resonance imaging and neuroimaging of the dopamine transporter in diagnosing Parkinson's disease. METHODS We performed a non-systematic literature review through the PubMed database, using the keywords "Parkinson", "magnetic resonance imaging", "diffusion tensor", "diffusion-weighted", "neuromelanin", "nigrosome-1", "single-photon emission computed tomography", "dopamine transporter imaging". The search was restricted to articles written in English, published between January 2010 and February 2022. RESULTS The diagnosis of Parkinson's disease remains a clinical diagnosis. However, new neuroimaging biomarkers hold promise for increased diagnostic accuracy, especially in earlier stages of the disease. CONCLUSION Future validation of new imaging biomarkers bring the expectation of an increased neuroimaging role in the diagnosis of PD in the following years.
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Affiliation(s)
- Rafael Tomio Vicentini Otani
- Universidade de São Paulo, Faculdade de Medicina, Hospital das Clínicas, Departamento de Neurologia, São Paulo SP, Brazil
| | - Joyce Yuri Silvestre Yamamoto
- Universidade de São Paulo, Faculdade de Medicina, Hospital das Clínicas, Departamento de Neurologia, São Paulo SP, Brazil
| | - Douglas Mendes Nunes
- Universidade de São Paulo, Faculdade de Medicina, Hospital das Clínicas, Departmento de Radiologia e Oncologia, Instituto de Radiologia, São Paulo SP, Brazil
| | - Mônica Santoro Haddad
- Universidade de São Paulo, Faculdade de Medicina, Hospital das Clínicas, Departamento de Neurologia, São Paulo SP, Brazil
| | - Jacy Bezerra Parmera
- Universidade de São Paulo, Faculdade de Medicina, Hospital das Clínicas, Departamento de Neurologia, São Paulo SP, Brazil
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Ray NJ, Lawson RA, Martin SL, Sigurdsson HP, Wilson J, Galna B, Lord S, Alcock L, Duncan GW, Khoo TK, O’Brien JT, Burn DJ, Taylor JP, Rea RC, Bergamino M, Rochester L, Yarnall AJ. Free-water imaging of the cholinergic basal forebrain and pedunculopontine nucleus in Parkinson's disease. Brain 2022; 146:1053-1064. [PMID: 35485491 PMCID: PMC9976974 DOI: 10.1093/brain/awac127] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Revised: 02/22/2022] [Accepted: 02/25/2022] [Indexed: 11/13/2022] Open
Abstract
Free-water imaging can predict and monitor dopamine system degeneration in people with Parkinson's disease. It can also enhance the sensitivity of traditional diffusion tensor imaging (DTI) metrics for indexing neurodegeneration. However, these tools are yet to be applied to investigate cholinergic system degeneration in Parkinson's disease, which involves both the pedunculopontine nucleus and cholinergic basal forebrain. Free-water imaging, free-water-corrected DTI and volumetry were used to extract structural metrics from the cholinergic basal forebrain and pedunculopontine nucleus in 99 people with Parkinson's disease and 46 age-matched controls. Cognitive ability was tracked over 4.5 years. Pearson's partial correlations revealed that free-water-corrected DTI metrics in the pedunculopontine nucleus were associated with performance on cognitive tasks that required participants to make rapid choices (behavioural flexibility). Volumetric, free-water content and DTI metrics in the cholinergic basal forebrain were elevated in a sub-group of people with Parkinson's disease with evidence of cognitive impairment, and linear mixed modelling revealed that these metrics were differently associated with current and future changes to cognition. Free water and free-water-corrected DTI can index cholinergic degeneration that could enable stratification of patients in clinical trials of cholinergic interventions for cognitive decline. In addition, degeneration of the pedunculopontine nucleus impairs behavioural flexibility in Parkinson's disease, which may explain this region's role in increased risk of falls.
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Affiliation(s)
- Nicola J Ray
- Correspondence to: Nicola Jane Ray Brooks Building Manchester Metropolitan University Manchester M15 6GX, UK E-mail:
| | - Rachael A Lawson
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Sarah L Martin
- Health, Psychology and Communities Research Centre, Department of Psychology, Manchester Metropolitan University, Manchester, UK
| | - Hilmar P Sigurdsson
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Joanna Wilson
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Brook Galna
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK,Health Futures Institute, Murdoch University, Perth, Australia
| | - Sue Lord
- Auckland University of Technology, Auckland, New Zealand
| | - Lisa Alcock
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Gordon W Duncan
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK,NHS Lothian, Edinburgh, UK
| | - Tien K Khoo
- School of Medicine & Dentistry, Menzies Health Institute Queensland, Griffith University, Queensland, Australia,School of Medicine, University of Wollongong, Wollongong, New South Wales, Australia
| | - John T O’Brien
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - David J Burn
- Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - John-Paul Taylor
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| | - River C Rea
- Health, Psychology and Communities Research Centre, Department of Psychology, Manchester Metropolitan University, Manchester, UK
| | | | - Lynn Rochester
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK,The Newcastle upon Tyne NHS Foundation Trust, Newcastle upon Tyne, UK
| | - Alison J Yarnall
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK,The Newcastle upon Tyne NHS Foundation Trust, Newcastle upon Tyne, UK
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Mitchell T, Wilkes BJ, Archer DB, Chu WT, Coombes SA, Lai S, McFarland NR, Okun MS, Black ML, Herschel E, Simuni T, Comella C, Afshari M, Xie T, Li H, Parrish TB, Kurani AS, Corcos DM, Vaillancourt DE. Advanced diffusion imaging to track progression in Parkinson's disease, multiple system atrophy, and progressive supranuclear palsy. Neuroimage Clin 2022; 34:103022. [PMID: 35489192 PMCID: PMC9062732 DOI: 10.1016/j.nicl.2022.103022] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Revised: 03/29/2022] [Accepted: 04/24/2022] [Indexed: 12/02/2022]
Abstract
Advanced diffusion imaging which accounts for complex tissue properties, such as crossing fibers and extracellular fluid, may detect longitudinal changes in widespread pathology in atypical Parkinsonian syndromes. We implemented fixel-based analysis, Neurite Orientation and Density Imaging (NODDI), and free-water imaging in Parkinson's disease (PD), multiple system atrophy (MSAp), progressive supranuclear palsy (PSP), and controls longitudinally over one year. Further, we used these three advanced diffusion imaging techniques to investigate longitudinal progression-related effects in key white matter tracts and gray matter regions in PD and two common atypical Parkinsonian disorders. Fixel-based analysis and free-water imaging revealed longitudinal declines in a greater number of descending sensorimotor tracts in MSAp and PSP compared to PD. In contrast, only the primary motor descending sensorimotor tract had progressive decline over one year, measured by fiber density (FD), in PD compared to that in controls. PSP was characterized by longitudinal impairment in multiple transcallosal tracts (primary motor, dorsal and ventral premotor, pre-supplementary motor, and supplementary motor area) as measured by FD, whereas there were no transcallosal tracts with longitudinal FD impairment in MSAp and PD. In addition, free-water (FW) and FW-corrected fractional anisotropy (FAt) in gray matter regions showed longitudinal changes over one year in regions that have previously shown cross-sectional impairment in MSAp (putamen) and PSP (substantia nigra, putamen, subthalamic nucleus, red nucleus, and pedunculopontine nucleus). NODDI did not detect any longitudinal white matter tract progression effects and there were few effects in gray matter regions across Parkinsonian disorders. All three imaging methods were associated with change in clinical disease severity across all three Parkinsonian syndromes. These results identify novel extra-nigral and extra-striatal longitudinal progression effects in atypical Parkinsonian disorders through the application of multiple diffusion methods that are related to clinical disease progression. Moreover, the findings suggest that fixel-based analysis and free-water imaging are both particularly sensitive to these longitudinal changes in atypical Parkinsonian disorders.
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Affiliation(s)
- Trina Mitchell
- Laboratory for Rehabilitation Neuroscience, Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, USA
| | - Bradley J Wilkes
- Laboratory for Rehabilitation Neuroscience, Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, USA
| | - Derek B Archer
- Laboratory for Rehabilitation Neuroscience, Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, USA; Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Winston T Chu
- Laboratory for Rehabilitation Neuroscience, Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, USA; J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA
| | - Stephen A Coombes
- Laboratory for Rehabilitation Neuroscience, Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, USA
| | - Song Lai
- Department of Radiation Oncology & CTSI Human Imaging Core, University of Florida, Gainesville, FL, USA
| | - Nikolaus R McFarland
- Department of Neurology and the Norman Fixel Institute for Neurological Diseases, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Michael S Okun
- Department of Neurology and the Norman Fixel Institute for Neurological Diseases, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Mieniecia L Black
- Laboratory for Rehabilitation Neuroscience, Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, USA
| | - Ellen Herschel
- Department of Physical Therapy and Human Movement Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Tanya Simuni
- Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Cynthia Comella
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Mitra Afshari
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Tao Xie
- Department of Neurology, University of Chicago Medicine, Chicago, IL, USA
| | - Hong Li
- Department of Public Health Sciences, Medical College of South Carolina, Charleston, SC, USA
| | - Todd B Parrish
- Department of Radiology, Northwestern Feinberg School of Medicine, Chicago, IL, USA
| | - Ajay S Kurani
- Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Daniel M Corcos
- Department of Physical Therapy and Human Movement Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - David E Vaillancourt
- Laboratory for Rehabilitation Neuroscience, Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, USA; J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA; Department of Neurology and the Norman Fixel Institute for Neurological Diseases, College of Medicine, University of Florida, Gainesville, FL, USA.
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59
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Chougar L, Arsovic E, Gaurav R, Biondetti E, Faucher A, Valabrègue R, Pyatigorskaya N, Dupont G, Lejeune FX, Cormier F, Corvol JC, Vidailhet M, Degos B, Grabli D, Lehéricy S. Regional Selectivity of Neuromelanin Changes in the Substantia Nigra in Atypical Parkinsonism. Mov Disord 2022; 37:1245-1255. [PMID: 35347754 DOI: 10.1002/mds.28988] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Revised: 02/15/2022] [Accepted: 02/17/2022] [Indexed: 11/05/2022] Open
Abstract
BACKGROUND Neurodegeneration in the substantia nigra pars compacta (SNc) in parkinsonian syndromes may affect the nigral territories differently. OBJECTIVE The objective of this study was to investigate the regional selectivity of neurodegenerative changes in the SNc in patients with Parkinson's disease (PD) and atypical parkinsonism using neuromelanin-sensitive magnetic resonance imaging (MRI). METHODS A total of 22 healthy controls (HC), 38 patients with PD, 22 patients with progressive supranuclear palsy (PSP), 20 patients with multiple system atrophy (MSA, 13 with the parkinsonian variant, 7 with the cerebellar variant), 7 patients with dementia with Lewy body (DLB), and 4 patients with corticobasal syndrome were analyzed. volume and signal-to-noise ratio (SNR) values of the SNc were derived from neuromelanin-sensitive MRI in the whole SNc. Analysis of signal changes was performed in the sensorimotor, associative, and limbic territories of the SNc. RESULTS SNc volume and corrected volume were significantly reduced in PD, PSP, and MSA versus HC. Patients with PSP had lower volume, corrected volume, SNR, and contrast-to-noise ratio than HC and patients with PD and MSA. Patients with PSP had greater SNR reduction in the associative region than HC and patients with PD and MSA. Patients with PD had reduced SNR in the sensorimotor territory, unlike patients with PSP. Patients with MSA did not differ from patients with PD. CONCLUSIONS This study provides the first MRI comparison of the topography of neuromelanin changes in parkinsonism. The spatial pattern of changes differed between PSP and synucleinopathies. These nigral topographical differences are consistent with the topography of the extranigral involvement in parkinsonian syndromes. © 2022 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Lydia Chougar
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inria, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière, DMU DIAMENT, Department of Neuroradiology, F-75013, Paris, France, Paris, France.,ICM, Centre de NeuroImagerie de Recherche-CENIR, Paris, France.,ICM, Team "Movement Investigations and Therapeutics" (MOV'IT), Paris, France
| | - Emina Arsovic
- ICM, Centre de NeuroImagerie de Recherche-CENIR, Paris, France.,ICM, Team "Movement Investigations and Therapeutics" (MOV'IT), Paris, France.,Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière, DMU DIAMENT, Department of Neuroradiology, F-75013, Paris, France, Paris, France
| | - Rahul Gaurav
- ICM, Centre de NeuroImagerie de Recherche-CENIR, Paris, France.,ICM, Team "Movement Investigations and Therapeutics" (MOV'IT), Paris, France.,Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inserm, F-75013, Paris, France
| | - Emma Biondetti
- ICM, Centre de NeuroImagerie de Recherche-CENIR, Paris, France.,ICM, Team "Movement Investigations and Therapeutics" (MOV'IT), Paris, France.,Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inserm, F-75013, Paris, France
| | - Alice Faucher
- Dynamics and Pathophysiology of Neuronal Networks Team, Center for Interdisciplinary Research in Biology, Collège de France, CNRS UMR7241/INSERM U1050, Université PSL, Paris, France.,Service de Neurologie, Hôpital Avicenne, Hôpitaux Universitaires de Paris Seine-Saint-Denis, APHP, Bobigny, France
| | - Romain Valabrègue
- ICM, Centre de NeuroImagerie de Recherche-CENIR, Paris, France.,Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inserm, F-75013, Paris, France
| | - Nadya Pyatigorskaya
- ICM, Centre de NeuroImagerie de Recherche-CENIR, Paris, France.,ICM, Team "Movement Investigations and Therapeutics" (MOV'IT), Paris, France.,Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière, DMU DIAMENT, Department of Neuroradiology, F-75013, Paris, France, Paris, France
| | - Gwendoline Dupont
- Centre hospitalier universitaire François Mitterrand, Département de Neurologie, Université de Bourgogne, Dijon, France
| | - François-Xavier Lejeune
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inserm, F-75013, Paris, France.,ICM, Data and Analysis Core, Paris, France
| | - Florence Cormier
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inserm, F-75013, Paris, France.,Clinique des mouvements anormaux, Département de Neurologie, Assistance Publique Hôpitaux de Paris, Hôpital Pitié-Salpêtrière, Paris, France
| | - Jean-Christophe Corvol
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inserm, F-75013, Paris, France.,ICM, Centre d'Investigation Clinique Neurosciences, Paris, France
| | - Marie Vidailhet
- ICM, Team "Movement Investigations and Therapeutics" (MOV'IT), Paris, France.,Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inserm, F-75013, Paris, France.,Clinique des mouvements anormaux, Département de Neurologie, Assistance Publique Hôpitaux de Paris, Hôpital Pitié-Salpêtrière, Paris, France
| | - Bertrand Degos
- Dynamics and Pathophysiology of Neuronal Networks Team, Center for Interdisciplinary Research in Biology, Collège de France, CNRS UMR7241/INSERM U1050, Université PSL, Paris, France.,Service de Neurologie, Hôpital Avicenne, Hôpitaux Universitaires de Paris Seine-Saint-Denis, APHP, Bobigny, France
| | - David Grabli
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inserm, F-75013, Paris, France.,Clinique des mouvements anormaux, Département de Neurologie, Assistance Publique Hôpitaux de Paris, Hôpital Pitié-Salpêtrière, Paris, France
| | - Stéphane Lehéricy
- ICM, Centre de NeuroImagerie de Recherche-CENIR, Paris, France.,ICM, Team "Movement Investigations and Therapeutics" (MOV'IT), Paris, France.,Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière, DMU DIAMENT, Department of Neuroradiology, F-75013, Paris, France, Paris, France
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60
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Guttuso T, Sirica D, Tosun D, Zivadinov R, Pasternak O, Weintraub D, Baglio F, Bergsland N. Thalamic Dorsomedial Nucleus Free Water Correlates with Cognitive Decline in Parkinson's Disease. Mov Disord 2022; 37:490-501. [PMID: 34936139 PMCID: PMC8940677 DOI: 10.1002/mds.28886] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Revised: 11/19/2021] [Accepted: 11/22/2021] [Indexed: 11/07/2022] Open
Abstract
BACKGROUND Brain diffusion tensor imaging (DTI) has been shown to reflect cognitive changes in early Parkinson's disease (PD) but the diffusion-based measure free water (FW) has not been previously assessed. OBJECTIVES To assess if FW in the thalamic nuclei primarily involved with cognition (ie, the dorsomedial [DMN] and anterior [AN] nuclei), the nucleus basalis of Meynert (nbM), and the hippocampus correlates with and is associated with longitudinal cognitive decline and distinguishes cognitive status at baseline in early PD. Also, to explore how FW compares with conventional DTI, FW-corrected DTI, and volumetric assessments for these outcomes. METHODS Imaging data and Montreal Cognitive Assessment (MoCA) scores from the Parkinson's Progression Markers Initiative database were analyzed using partial correlations and ANCOVA. Primary outcome multiple comparisons were corrected for false discovery rate (q value). RESULTS Thalamic DMN FW changes over 1 year correlated with MoCA changes over both 1 and 3 years (partial correlations -0.222, q = 0.040, n = 130; and - 0.229, q = 0.040, n = 123, respectively; mean PD duration at baseline = 6.85 months). NbM FW changes over 1 year only correlated with MoCA changes over 3 years (-0.222, q = 0.040). Baseline hippocampal FW was associated with cognitive impairment at 3 years (q = 0.040) and baseline nbM FW distinguished PD-normal cognition (MoCA ≥26) from PD-cognitive impairment (MoCA ≤25), (q = 0.008). The exploratory comparisons showed FW to be the most robust assessment modality for all outcomes. CONCLUSIONS Thalamic DMN FW is a promising cognition progression biomarker in early PD that may assist in identifying cognition protective therapies in clinical trials. FW is a robust assessment modality for these outcomes. © 2021 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Thomas Guttuso
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY
| | - Daniel Sirica
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY
| | - Duygu Tosun
- University of California, San Francisco, San Francisco, CA
| | - Robert Zivadinov
- Department of Neurology, Buffalo Neuroimaging Analysis Center, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY,Center for Biomedical Imaging, Clinical and Translational Science Institute, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY
| | - Ofer Pasternak
- Departments of Psychiatry and Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
| | - Daniel Weintraub
- Departments of Psychiatry and Neurology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA,Parkinson’s Disease Research, Education and Clinical Center (PADRECC and MIRECC), Philadelphia Veterans Affairs Medical Center, Philadelphia, PA
| | | | - Niels Bergsland
- Department of Neurology, Buffalo Neuroimaging Analysis Center, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY,IRCCS, Fondazione Don Carlo Gnocchi, Milan, Italy
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61
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Mahlknecht P, Marini K, Werkmann M, Poewe W, Seppi K. Prodromal Parkinson's disease: hype or hope for disease-modification trials? Transl Neurodegener 2022; 11:11. [PMID: 35184752 PMCID: PMC8859908 DOI: 10.1186/s40035-022-00286-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Accepted: 02/01/2022] [Indexed: 12/24/2022] Open
Abstract
The ultimate goal in Parkinson's disease (PD) research remains the identification of treatments that are capable of slowing or even halting the progression of the disease. The failure of numerous past disease-modification trials in PD has been attributed to a variety of factors related not only to choosing wrong interventions, but also to using inadequate trial designs and target populations. In patients with clinically established PD, neuronal pathology may already have advanced too far to be modified by any intervention. Based on such reasoning, individuals in yet prediagnostic or prodromal disease stages, may provide a window of opportunity to test disease-modifying strategies. There is now sufficient evidence from prospective studies to define diagnostic criteria for prodromal PD and several approaches have been studied in observational cohorts. These include the use of PD-risk algorithms derived from multiple established risk factors for disease as well as follow-up of cohorts with single defined prodromal markers like hyposmia, rapid eye movement sleep behavior disorders, or PD gene carriers. In this review, we discuss recruitment strategies for disease-modification trials in various prodromal PD cohorts, as well as potential trial designs, required trial durations, and estimated sample sizes. We offer a concluding outlook on how the goal of implementing disease-modification trials in prodromal cohorts might be achieved in the future.
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Multimodal brain and retinal imaging of dopaminergic degeneration in Parkinson disease. Nat Rev Neurol 2022; 18:203-220. [PMID: 35177849 DOI: 10.1038/s41582-022-00618-9] [Citation(s) in RCA: 36] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/13/2022] [Indexed: 12/12/2022]
Abstract
Parkinson disease (PD) is a progressive disorder characterized by dopaminergic neurodegeneration in the brain. The development of parkinsonism is preceded by a long prodromal phase, and >50% of dopaminergic neurons can be lost from the substantia nigra by the time of the initial diagnosis. Therefore, validation of in vivo imaging biomarkers for early diagnosis and monitoring of disease progression is essential for future therapeutic developments. PET and single-photon emission CT targeting the presynaptic terminals of dopaminergic neurons can be used for early diagnosis by detecting axonal degeneration in the striatum. However, these techniques poorly differentiate atypical parkinsonian syndromes from PD, and their availability is limited in clinical settings. Advanced MRI in which pathological changes in the substantia nigra are visualized with diffusion, iron-sensitive susceptibility and neuromelanin-sensitive sequences potentially represents a more accessible imaging tool. Although these techniques can visualize the classic degenerative changes in PD, they might be insufficient for phenotyping or prognostication of heterogeneous aspects of PD resulting from extranigral pathologies. The retina is an emerging imaging target owing to its pathological involvement early in PD, which correlates with brain pathology. Retinal optical coherence tomography (OCT) is a non-invasive technique to visualize structural changes in the retina. Progressive parafoveal thinning and fovea avascular zone remodelling, as revealed by OCT, provide potential biomarkers for early diagnosis and prognostication in PD. As we discuss in this Review, multimodal imaging of the substantia nigra and retina is a promising tool to aid diagnosis and management of PD.
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Xing Y, Sapuan AH, Martín-Bastida A, Naidu S, Tench C, Evans J, Sare G, Schwarz ST, Al-Bachari S, Parkes LM, Kanavou S, Raw J, Silverdale M, Bajaj N, Pavese N, Burn D, Piccini P, Grosset DG, Auer DP. Neuromelanin-MRI to Quantify and Track Nigral Depigmentation in Parkinson's Disease: A Multicenter Longitudinal Study Using Template-Based Standardized Analysis. Mov Disord 2022; 37:1028-1039. [PMID: 35165920 PMCID: PMC9303322 DOI: 10.1002/mds.28934] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2021] [Revised: 11/24/2021] [Accepted: 01/09/2022] [Indexed: 12/15/2022] Open
Abstract
Background Clinical diagnosis and monitoring of Parkinson's disease (PD) remain challenging because of the lack of an established biomarker. Neuromelanin‐magnetic resonance imaging (NM‐MRI) is an emerging biomarker of nigral depigmentation indexing the loss of melanized neurons but has unknown prospective diagnostic and tracking performance in multicenter settings. Objectives The aim was to investigate the diagnostic accuracy of NM‐MRI in early PD in a multiprotocol setting and to determine and compare serial NM‐MRI changes in PD and controls. Methods In this longitudinal case–control 3 T MRI study, 148 patients and 97 controls were included from six UK clinical centers, of whom 140 underwent a second scan after 1.5 to 3 years. An automated template‐based analysis was applied for subregional substantia nigra NM‐MRI contrast and volume assessment. A point estimate of the period of prediagnostic depigmentation was computed. Results All NM metrics performed well to discriminate patients from controls, with receiver operating characteristic showing 85% accuracy for ventral NM contrast and 83% for volume. Generalizability using a priori volume cutoff was good (79% accuracy). Serial MRI demonstrated accelerated NM loss in patients compared to controls. Ventral NM contrast loss was point estimated to start 5 to 6 years before clinical diagnosis. Ventral nigral depigmentation was greater in the most affected side, more severe cases, and nigral NM volume change correlated with change in motor severity. Conclusions We demonstrate that NM‐MRI provides clinically useful diagnostic information in early PD across protocols, platforms, and sites. It provides methods and estimated depigmentation rates that highlight the potential to detect preclinical PD and track progression for biomarker‐enabled clinical trials. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society
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Affiliation(s)
- Yue Xing
- School of Medicine, Mental Health & Clinical Neurosciences, Nottingham, United Kingdom.,Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom.,National Institute for Health Research, Nottingham Biomedical Research Centre, Nottingham, United Kingdom
| | - Abdul Halim Sapuan
- School of Medicine, Mental Health & Clinical Neurosciences, Nottingham, United Kingdom.,Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom.,National Institute for Health Research, Nottingham Biomedical Research Centre, Nottingham, United Kingdom
| | - Antonio Martín-Bastida
- Division of Neurology, Imperial College London, London, United Kingdom.,Department of Neurology and Neurosciences, Clínica Universidad de Navarra, Pamplona-Madrid, Spain
| | - Saadnah Naidu
- School of Medicine, Mental Health & Clinical Neurosciences, Nottingham, United Kingdom.,Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom.,Neurology, Nottingham University Hospital Trust, Nottingham, United Kingdom
| | - Christopher Tench
- School of Medicine, Mental Health & Clinical Neurosciences, Nottingham, United Kingdom.,Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom.,National Institute for Health Research, Nottingham Biomedical Research Centre, Nottingham, United Kingdom
| | - Jonathan Evans
- Neurology, Nottingham University Hospital Trust, Nottingham, United Kingdom
| | - Gillian Sare
- Neurology, Nottingham University Hospital Trust, Nottingham, United Kingdom
| | - Stefan T Schwarz
- School of Medicine, Mental Health & Clinical Neurosciences, Nottingham, United Kingdom.,Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom.,Department of Radiology, Cardiff and Vale University Health Board, Cardiff, United Kingdom
| | - Sarah Al-Bachari
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom.,Lancaster Medical School, Lancaster University, Lancaster, United Kingdom.,Department of Neurology, Lancashire Teaching Hospitals NHS Foundation Trust, Preston, United Kingdom
| | - Laura M Parkes
- Division of Neuroscience & Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Sofia Kanavou
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Jason Raw
- Pennine Acute Hospitals NHS Trust, Oldham, United Kingdom
| | - Monty Silverdale
- Division of Neurology, Salford Royal NHS Foundation Trust, Manchester Academic Health Science Centre, University of Manchester, Manchester, United Kingdom
| | - Nin Bajaj
- School of Medicine, Mental Health & Clinical Neurosciences, Nottingham, United Kingdom.,Spire Nottingham Hospital, Nottingham, United Kingdom
| | - Nicola Pavese
- Newcastle Magnetic Resonance Centre & Positron Emission Tomography Centre and Clinical Ageing Research Unit, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - David Burn
- Faculty of Medical Sciences, The Medical School, Framlington Place, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Paola Piccini
- Division of Neurology, Imperial College London, London, United Kingdom.,Department of Brain Science, Imperial College London, London, United Kingdom
| | - Donald G Grosset
- Institute for Neurological Sciences, Queen Elizabeth University Hospital, Glasgow, United Kingdom
| | - Dorothee P Auer
- School of Medicine, Mental Health & Clinical Neurosciences, Nottingham, United Kingdom.,Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom.,National Institute for Health Research, Nottingham Biomedical Research Centre, Nottingham, United Kingdom
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64
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Arpin DJ, Mitchell T, Archer DB, Burciu RG, Chu WT, Gao H, Guttuso T, Hess CW, Lai S, Malaty IA, McFarland NR, Pasternak O, Price CC, Shukla AW, Wu SS, Okun MS, Vaillancourt DE. Diffusion Magnetic Resonance Imaging Detects Progression in Parkinson's Disease: A Placebo-Controlled Trial of Rasagiline. Mov Disord 2022; 37:325-333. [PMID: 34724257 PMCID: PMC9019575 DOI: 10.1002/mds.28838] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 08/30/2021] [Accepted: 09/26/2021] [Indexed: 11/07/2022] Open
Abstract
BACKGROUND Rasagiline has received attention as a potential disease-modifying therapy for Parkinson's disease (PD). Whether rasagiline is disease modifying remains in question. OBJECTIVE The main objective of this study was to determine whether rasagiline has disease-modifying effects in PD over 1 year. Secondarily we evaluated two diffusion magnetic resonance imaging pulse sequences to determine the best sequence to measure disease progression. METHODS This prospective, randomized, double-blind, placebo-controlled trial assessed the effects of rasagiline administered at 1 mg/day over 12 months in early-stage PD. The primary outcome was 1-year change in free-water accumulation in posterior substantia nigra (pSN) measured using two diffusion magnetic resonance imaging pulse sequences, one with a repetition time (TR) of 2500 ms (short TR; n = 90) and one with a TR of 6400 ms (long TR; n = 75). Secondary clinical outcomes also were assessed. RESULTS Absolute change in pSN free-water accumulation was not significantly different between groups (short TR: P = 0.346; long TR: P = 0.228). No significant differences were found in any secondary clinical outcomes between groups. Long TR, but not short TR, data show pSN free-water increased significantly over 1 year (P = 0.025). Movement Disorder Society Unified Parkinson's Disease Rating Scale testing of motor function, Part III increased significantly over 1 year (P = 0.009), and baseline free-water in the pSN correlated with the 1-year change in Movement Disorder Society Unified Parkinson's Disease Rating Scale testing of motor function, Part III (P = 0.004) and 1-year change in bradykinesia score (P = 0.044). CONCLUSIONS We found no evidence that 1 mg/day rasagiline has a disease-modifying effect in PD over 1 year. We found pSN free-water increased over 1 year, and baseline free-water relates to clinical motor progression, demonstrating the importance of diffusion imaging parameters for detecting and predicting PD progression. © 2021 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- David J. Arpin
- Laboratory for Rehabilitation Neuroscience, Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, Florida, USA
- Norman Fixel Institute for Neurological Diseases, Department of Neurology, University of Florida, Gainesville, Florida, USA
| | - Trina Mitchell
- Laboratory for Rehabilitation Neuroscience, Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, Florida, USA
- Norman Fixel Institute for Neurological Diseases, Department of Neurology, University of Florida, Gainesville, Florida, USA
| | - Derek B. Archer
- Vanderbilt Memory and Alzheimer’s Center, Department of Neurology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
- Department of Neurology, Vanderbilt Genetics Institute, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Roxana G. Burciu
- Department of Kinesiology and Applied Physiology, College of Health Sciences, University of Delaware, Newark, Delaware, USA
| | - Winston T. Chu
- Laboratory for Rehabilitation Neuroscience, Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, Florida, USA
- Norman Fixel Institute for Neurological Diseases, Department of Neurology, University of Florida, Gainesville, Florida, USA
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, Florida, USA
| | - Hanzhi Gao
- Department of Biostatistics, University of Florida, Gainesville, Florida, USA
| | - Thomas Guttuso
- Movement Disorder Center, Department of Neurology, Jacobs School of Medicine & Biomedical Sciences, University at Buffalo, Buffalo, New York, USA
| | - Christopher W. Hess
- Norman Fixel Institute for Neurological Diseases, Department of Neurology, University of Florida, Gainesville, Florida, USA
| | - Song Lai
- Department of Radiation Oncology & CTSI Human Imaging Core, University of Florida, Gainesville, Florida, USA
| | - Irene A. Malaty
- Norman Fixel Institute for Neurological Diseases, Department of Neurology, University of Florida, Gainesville, Florida, USA
| | - Nikolaus R. McFarland
- Norman Fixel Institute for Neurological Diseases, Department of Neurology, University of Florida, Gainesville, Florida, USA
| | - Ofer Pasternak
- Departments of Psychiatry and Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Catherine C. Price
- Norman Fixel Institute for Neurological Diseases, Department of Neurology, University of Florida, Gainesville, Florida, USA
- Departments of Clinical and Health Psychology and Anesthesiology, University of Florida College of Medicine, Gainesville, Florida, USA
| | - Aparna Wagle Shukla
- Norman Fixel Institute for Neurological Diseases, Department of Neurology, University of Florida, Gainesville, Florida, USA
| | - Samuel S. Wu
- Norman Fixel Institute for Neurological Diseases, Department of Neurology, University of Florida, Gainesville, Florida, USA
- Department of Biostatistics, University of Florida, Gainesville, Florida, USA
| | - Michael S. Okun
- Norman Fixel Institute for Neurological Diseases, Department of Neurology, University of Florida, Gainesville, Florida, USA
| | - David E. Vaillancourt
- Laboratory for Rehabilitation Neuroscience, Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, Florida, USA
- Norman Fixel Institute for Neurological Diseases, Department of Neurology, University of Florida, Gainesville, Florida, USA
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, Florida, USA
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Prasuhn J, Strautz R, Lemmer F, Dreischmeier S, Kasten M, Hanssen H, Heldmann M, Brüggemann N. Neuroimaging Correlates of Substantia Nigra Hyperechogenicity in Parkinson's Disease. JOURNAL OF PARKINSON'S DISEASE 2022; 12:1191-1200. [PMID: 35180131 DOI: 10.3233/jpd-213000] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
BACKGROUND Degeneration of dopaminergic neurons within the brainstem substantia nigra (SN) is both a pathological hallmark of Parkinson's disease (PD) and a major contributor to symptom expression. Therefore, non-invasive evaluation of the SN is critical for diagnosis and evaluation of disease progression. Hyperechogenicity (HE+) on midbrain transcranial sonography (TCS) supports the clinically established diagnosis of PD. Further, postmortem studies suggest involvement of neuromelanin (NM) loss and iron deposition in nigral neurodegeneration and HE+ emergence. However, the associations between HE+ and signs of nigral NM loss and iron deposition revealed by magnetic resonance imaging (MRI) have not been examined. OBJECTIVE To elucidate the magnetic resonance- (MR-) morphological representation of the HE+ by NM-weighted (NMI) and susceptibility-weighted MRI (SWI). METHODS Thirty-four PD patients and 29 healthy controls (HCs) received TCS followed by NMI and SWI. From MR images, two independent raters manually identified the SN, placed seeds in non-SN midbrain areas, and performed semi-automated SN segmentation with different thresholds based on seed mean values and standard deviations. Masks of the SN were then used to extract mean area, mean signal intensity, maximal signal area, maximum signal (for NMI), and minimum signal (for SWI). RESULTS There were no significant differences in NMI- and SWI-based parameters between patients and HCs, and no significant associations between HE+ extent and NMI- or SWI-based parameters. CONCLUSION HE+ on TCS appears unrelated to PD pathology revealed by NMI and SWI. Thus, TCS and MRI parameters should be considered complementary, and the pathophysiological correlates of the HE+ require further study.
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Affiliation(s)
- Jannik Prasuhn
- Institute of Neurogenetics, University of Lübeck, Lübeck, Germany
- Department of Neurology, University Medical Center Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
- Center for Brain, Behavior, and Metabolism, University of Lübeck, Lübeck, Germany
| | - Robert Strautz
- Institute of Neurogenetics, University of Lübeck, Lübeck, Germany
- Department of Neurology, University Medical Center Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Felicitas Lemmer
- Institute of Neurogenetics, University of Lübeck, Lübeck, Germany
- Department of Neurology, University Medical Center Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Shalida Dreischmeier
- Institute of Neurogenetics, University of Lübeck, Lübeck, Germany
- Department of Neurology, University Medical Center Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Meike Kasten
- Institute of Neurogenetics, University of Lübeck, Lübeck, Germany
- Center for Brain, Behavior, and Metabolism, University of Lübeck, Lübeck, Germany
- Department of Psychiatry, University Medical Center Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Henrike Hanssen
- Institute of Neurogenetics, University of Lübeck, Lübeck, Germany
- Department of Neurology, University Medical Center Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
- Center for Brain, Behavior, and Metabolism, University of Lübeck, Lübeck, Germany
| | - Marcus Heldmann
- Department of Neurology, University Medical Center Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
- Center for Brain, Behavior, and Metabolism, University of Lübeck, Lübeck, Germany
- Institute of Psychology II, University of Lübeck, Lübeck, Germany
| | - Norbert Brüggemann
- Institute of Neurogenetics, University of Lübeck, Lübeck, Germany
- Department of Neurology, University Medical Center Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
- Center for Brain, Behavior, and Metabolism, University of Lübeck, Lübeck, Germany
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Bae YJ, Kim JM, Choi BS, Song YS, Nam Y, Cho SJ, Kim JH, Kim SE. MRI Findings in Parkinson’s Disease: Radiologic Assessment of Nigrostriatal Degeneration. JOURNAL OF THE KOREAN SOCIETY OF RADIOLOGY 2022; 83:508-526. [PMID: 36238511 PMCID: PMC9514534 DOI: 10.3348/jksr.2022.0044] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Revised: 05/06/2022] [Accepted: 05/12/2022] [Indexed: 11/15/2022]
Abstract
파킨슨병은 중뇌 흑질에 위치한 도파민성 신경세포의 퇴행성 소실로 인해 발생하는 이상운동질환이다. 최근 다양한 자기공명영상기법의 발전으로 파킨슨병에서 일어나는 병리생태학적인 변화를 반영하는 여러 영상 소견들이 보고되었다. 여러 연구에서 이러한 영상 소견들은 파킨슨병의 진단 및 비정형 파킨슨증과의 감별 등에 유의미한 도움을 줄 수 있는 것이 밝혀졌다. 본 종설에서는, 파킨슨병에서 일어나는 흑질선조체 변성의 병태생리를 나타낼 수 있는 나이그로좀 영상 및 뉴로멜라닌 영상 등을 포함한 자기공명영상기법들과 각 영상에서 나타나는 소견에 대하여 자세히 다루었다.
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Affiliation(s)
- Yun Jung Bae
- Department of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
| | - Jong-Min Kim
- Department of Neurology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
| | - Byung Se Choi
- Department of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
| | - Yoo Sung Song
- Department of Nuclear Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
| | - Yoonho Nam
- Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Korea
| | - Se Jin Cho
- Department of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
| | - Jae Hyoung Kim
- Department of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
| | - Sang Eun Kim
- Department of Nuclear Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
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Salminen LE, Tubi MA, Bright J, Thomopoulos SI, Wieand A, Thompson PM. Sex is a defining feature of neuroimaging phenotypes in major brain disorders. Hum Brain Mapp 2022; 43:500-542. [PMID: 33949018 PMCID: PMC8805690 DOI: 10.1002/hbm.25438] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Revised: 03/22/2021] [Accepted: 03/23/2021] [Indexed: 12/12/2022] Open
Abstract
Sex is a biological variable that contributes to individual variability in brain structure and behavior. Neuroimaging studies of population-based samples have identified normative differences in brain structure between males and females, many of which are exacerbated in psychiatric and neurological conditions. Still, sex differences in MRI outcomes are understudied, particularly in clinical samples with known sex differences in disease risk, prevalence, and expression of clinical symptoms. Here we review the existing literature on sex differences in adult brain structure in normative samples and in 14 distinct psychiatric and neurological disorders. We discuss commonalities and sources of variance in study designs, analysis procedures, disease subtype effects, and the impact of these factors on MRI interpretation. Lastly, we identify key problems in the neuroimaging literature on sex differences and offer potential recommendations to address current barriers and optimize rigor and reproducibility. In particular, we emphasize the importance of large-scale neuroimaging initiatives such as the Enhancing NeuroImaging Genetics through Meta-Analyses consortium, the UK Biobank, Human Connectome Project, and others to provide unprecedented power to evaluate sex-specific phenotypes in major brain diseases.
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Affiliation(s)
- Lauren E. Salminen
- Imaging Genetics CenterMark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USCMarina del ReyCaliforniaUSA
| | - Meral A. Tubi
- Imaging Genetics CenterMark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USCMarina del ReyCaliforniaUSA
| | - Joanna Bright
- Imaging Genetics CenterMark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USCMarina del ReyCaliforniaUSA
| | - Sophia I. Thomopoulos
- Imaging Genetics CenterMark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USCMarina del ReyCaliforniaUSA
| | - Alyssa Wieand
- Imaging Genetics CenterMark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USCMarina del ReyCaliforniaUSA
| | - Paul M. Thompson
- Imaging Genetics CenterMark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USCMarina del ReyCaliforniaUSA
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Santos García D, Álvarez Sauco M, Calopa M, Carrillo F, Escamilla Sevilla F, Freire E, García Ramos R, Kulisevsky J, Gómez Esteban JC, Legarda I, Luquín MRI, Castrillo JCM, Martínez-Martin P, Martínez-Torres I, Mir P, Ignacio ÁS. MNCD: A New Tool for Classifying Parkinson’s Disease in Daily Clinical Practice. Diagnostics (Basel) 2021; 12:diagnostics12010055. [PMID: 35054222 PMCID: PMC8774369 DOI: 10.3390/diagnostics12010055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2021] [Revised: 12/19/2021] [Accepted: 12/23/2021] [Indexed: 11/16/2022] Open
Abstract
Background and objective: Parkinson’s disease (PD) is a clinically heterogeneous disorder in which the symptoms and prognosis can be very different among patients. We propose a new simple classification to identify key symptoms and staging in PD. Patients and Methods: Sixteen movement disorders specialists from Spain participated in this project. The classification was consensually approved after a discussion and review process from June to October 2021. The TNM classification and the National Institutes of Health Stroke Scale (NIHSS) were considered as models in the design. Results: The classification was named MNCD and included 4 major axes: (1) motor symptoms; (2) non-motor symptoms; (3) cognition; (4) dependency for activities of daily living (ADL). Motor axis included 4 sub-axes: (1) motor fluctuations; (2) dyskinesia; (3) axial symptoms; (4) tremor. Four other sub-axes were included in the non-motor axis: (1) neuropsychiatric symptoms; (2) autonomic dysfunction; (3) sleep disturbances and fatigue; (4) pain and sensory disorders. According to the MNCD, 5 stages were considered, from stage 1 (no disabling motor or non-motor symptoms with normal cognition and independency for ADL) to 5 (dementia and dependency for basic ADL). Conclusions: A new simple classification of PD is proposed. The MNCD classification includes 4 major axes and 5 stages to identify key symptoms and monitor the evolution of the disease in patients with PD. It is necessary to apply this proof of concept in a properly designed study.
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Affiliation(s)
- Diego Santos García
- Unidad de Trastornos de Movimiento, Servicio de Neurología, CHUAC, Complejo Hospitalario Universitario de A Coruña, 15009 A Coruña, Spain
- Neurología, Hospital San Rafael, 15009 A Coruña, Spain
- Correspondence: ; Tel.: +34-646173341
| | - María Álvarez Sauco
- Departamento de Neurología, Hospital General Universitario de Elche, 03203 Elche, Spain; (M.Á.S.); (E.F.)
| | - Matilde Calopa
- Unidad de Trastornos del Movimiento, Servicio de Neurología, Hospital Universitari de Bellvitge, 08907 Barcelona, Spain;
| | - Fátima Carrillo
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío, 41013 Sevilla, Spain; (F.C.); (P.M.)
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas CIBERNED, 28031 Madrid, Spain; (J.K.); (P.M.-M.)
| | - Francisco Escamilla Sevilla
- Unidad de Trastornos del Movimiento, Servicio de Neurología, Hospital Universitario Virgen de las Nieves, Instituto de Investigación Biosanitaria (ibs.Granada), 18013 Granada, Spain;
| | - Eric Freire
- Departamento de Neurología, Hospital General Universitario de Elche, 03203 Elche, Spain; (M.Á.S.); (E.F.)
- Departamento de Neurología, Hospital IMED Elche, 03203 Elche, Spain
| | - Rocío García Ramos
- Instituto de Investigación Sanitaria San Carlos (IdISCC), Hospital Clínico San Carlos, 28040 Madrid, Spain;
| | - Jaime Kulisevsky
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas CIBERNED, 28031 Madrid, Spain; (J.K.); (P.M.-M.)
- Departamento de Neurología, Unidad de Trastornos del Movimiento, Hospital de la Santa Creu i Sant Pau, 08041 Barcelona, Spain
| | | | - Inés Legarda
- Hospital Universitario Son Espases, 07120 Palma, Spain;
| | - María Rosario Isabel Luquín
- Departamento de Neurología, Clínica Universidad de Navarra, Instituto de Investigación Sanitaria de Navarra, 31008 Pamplona, Spain;
| | | | - Pablo Martínez-Martin
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas CIBERNED, 28031 Madrid, Spain; (J.K.); (P.M.-M.)
| | - Irene Martínez-Torres
- Unidad de Trastornos del Movimiento, Servicio de Neurología, Hospital Universitario y Politècnico La Fe, 46026 Valencia, Spain;
| | - Pablo Mir
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío, 41013 Sevilla, Spain; (F.C.); (P.M.)
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas CIBERNED, 28031 Madrid, Spain; (J.K.); (P.M.-M.)
| | - Ángel Sesar Ignacio
- Unidad de Trastornos del Movimiento, Servicio de Neurología, CHUS (Complejo Hospitalario Universitario de Santiago de Compostela), 15706 A Coruña, Spain;
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Johansson ME, Cameron IGM, van der Kolk NM, De Vries NM, Klimars E, Toni I, Bloem BR, Helmich RC. Aerobic exercise alters brain function and structure in Parkinson's disease a randomized controlled trial. Ann Neurol 2021; 91:203-216. [PMID: 34951063 PMCID: PMC9306840 DOI: 10.1002/ana.26291] [Citation(s) in RCA: 116] [Impact Index Per Article: 38.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Revised: 12/07/2021] [Accepted: 12/19/2021] [Indexed: 11/18/2022]
Abstract
Objective Randomized clinical trials have shown that aerobic exercise attenuates motor symptom progression in Parkinson's disease, but the underlying neural mechanisms are unclear. Here, we investigated how aerobic exercise influences disease‐related functional and structural changes in the corticostriatal sensorimotor network, which is involved in the emergence of motor deficits in Parkinson's disease. Additionally, we explored effects of aerobic exercise on tissue integrity of the substantia nigra, and on behavioral and cerebral indices of cognitive control. Methods The Park‐in‐Shape trial is a single‐center, double‐blind randomized controlled trial in 130 Parkinson's disease patients who were randomly assigned (1:1 ratio) to aerobic exercise (stationary home trainer) or stretching (active control) interventions (duration = 6 months). An unselected subset from this trial (exercise, n = 25; stretching, n = 31) underwent resting‐state functional and structural magnetic resonance imaging (MRI), and an oculomotor cognitive control task (pro‐ and antisaccades), at baseline and at 6‐month follow‐up. Results Aerobic exercise, but not stretching, led to increased functional connectivity of the anterior putamen with the sensorimotor cortex relative to the posterior putamen. Behaviorally, aerobic exercise also improved cognitive control. Furthermore, aerobic exercise increased functional connectivity in the right frontoparietal network, proportionally to fitness improvements, and it reduced global brain atrophy. Interpretation MRI, clinical, and behavioral results converge toward the conclusion that aerobic exercise stabilizes disease progression in the corticostriatal sensorimotor network and enhances cognitive performance. ANN NEUROL 2022;91:203–216
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Affiliation(s)
- M E Johansson
- Radboud University, Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands.,Radboud University Medical Centre; Donders Institute for Brain, Cognition and Behaviour, Centre for Medical Neuroscience; Department of Neurology; Centre of Expertise for Parkinson & Movement Disorders, Nijmegen, The Netherlands
| | - I G M Cameron
- Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands.,University of Twente, Faculty of Electrical Engineering, Mathematics and Computer Science, Enschede, The Netherlands.,OnePlanet Research Center, Nijmegen, The Netherlands
| | - N M van der Kolk
- Radboud University Medical Centre; Donders Institute for Brain, Cognition and Behaviour, Centre for Medical Neuroscience; Department of Neurology; Centre of Expertise for Parkinson & Movement Disorders, Nijmegen, The Netherlands
| | - N M De Vries
- Radboud University Medical Centre; Donders Institute for Brain, Cognition and Behaviour, Centre for Medical Neuroscience; Department of Neurology; Centre of Expertise for Parkinson & Movement Disorders, Nijmegen, The Netherlands
| | - E Klimars
- Radboud University, Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands.,Radboud University Medical Centre; Donders Institute for Brain, Cognition and Behaviour, Centre for Medical Neuroscience; Department of Neurology; Centre of Expertise for Parkinson & Movement Disorders, Nijmegen, The Netherlands
| | - I Toni
- Radboud University, Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands
| | - B R Bloem
- Radboud University Medical Centre; Donders Institute for Brain, Cognition and Behaviour, Centre for Medical Neuroscience; Department of Neurology; Centre of Expertise for Parkinson & Movement Disorders, Nijmegen, The Netherlands
| | - R C Helmich
- Radboud University, Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands.,Radboud University Medical Centre; Donders Institute for Brain, Cognition and Behaviour, Centre for Medical Neuroscience; Department of Neurology; Centre of Expertise for Parkinson & Movement Disorders, Nijmegen, The Netherlands
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70
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WANG LEI, LIU XIN, WU SHUOHUA, CHEN FANG, ZHENG YE, GUO GANG, XUAN YINGHUA, YAN GEN. CHANGES IN THE MICROSTRUCTURE AND FUNCTION OF BRAIN TISSUE IN PD BY DIFFUSION KURTOSIS IMAGING. J MECH MED BIOL 2021; 21. [DOI: 10.1142/s0219519421400625] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
This study proposed to detect changes in brain microstructure in patients with Parkinson’s disease (PD) using diffusion kurtosis imaging (DKI) to quantitatively diagnose early-stage PD. Conventional magnetic resonance imaging and DKI scanning were performed in 24 patients with PD and in 12 age- and sex-matched healthy participants. Hoehn and Yahr (H–Y) stage and Unified Parkinson’s Disease Rating Scale-III (UPDRS-III) scores were obtained from both groups. The mean kurtosis (MK), axial kurtosis, and radial kurtosis of the bilateral substantia nigra on DKI were measured and compared between the two groups. The correlations between MK, H–Y stage, and UPDRS-III scores were determined. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic efficacy of MK for PD in the substantia nigra. The MK value in the PD group was 0.971. The area under the ROC curve of the substantia nigra was 0.905; the sensitivity and specificity were 0.917 and 0.875, respectively, and the cutoff value was 1.046. The MK of the substantia nigra in the PD group had no significant correlation with the H–Y stages but was negatively correlated with the UPDRS-III scores ([Formula: see text]; [Formula: see text]). Our research identified DKI as a novel tool for the qualitative diagnosis of PD. The optimal MK value for PD diagnosis could be determined with ROC analysis.
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Affiliation(s)
- LEI WANG
- Department of Radiology, The Second Affiliated Hospital of Xiamen Medical College, Xiamen, P. R. China
| | - XIN LIU
- Department of Radiology, The Second Affiliated Hospital of Xiamen Medical College, Xiamen, P. R. China
| | - SHUOHUA WU
- Department of Medical Imaging, The 2nd Affiliated Hospital, Shantou University Medical College, Shantou, P. R. China
| | - FANG CHEN
- Department of Radiology, The Second Affiliated Hospital of Xiamen Medical College, Xiamen, P. R. China
| | - YE ZHENG
- Department of Radiology, The Second Affiliated Hospital of Xiamen Medical College, Xiamen, P. R. China
| | - GANG GUO
- Department of Radiology, The Second Affiliated Hospital of Xiamen Medical College, Xiamen, P. R. China
| | - YINGHUA XUAN
- Department of Basic Medicine, Xiamen Medical College, Xiamen, P. R. China
| | - GEN YAN
- Department of Radiology, The Second Affiliated Hospital of Xiamen Medical College, Xiamen, P. R. China
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Langley J, Huddleston DE, Hu X. Nigral diffusivity, but not free water, correlates with iron content in Parkinson's disease. Brain Commun 2021; 3:fcab251. [PMID: 34805996 PMCID: PMC8599079 DOI: 10.1093/braincomms/fcab251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 08/18/2021] [Accepted: 09/20/2021] [Indexed: 11/13/2022] Open
Abstract
The loss of melanized neurons in the substantia nigra pars compacta is a primary feature in Parkinson's disease. Iron deposition occurs in conjunction with this loss. Loss of nigral neurons should remove barriers for diffusion and increase diffusivity of water molecules in regions undergoing this loss. In metrics from single-compartment diffusion tensor imaging models, these changes should manifest as increases in mean diffusivity and reductions in fractional anisotropy as well as increases in the free water compartment in metrics derived from bi-compartment models. However, studies examining nigral diffusivity changes from Parkinson's disease with single-compartment models have yielded inconclusive results and emerging evidence in control subjects indicates that iron corrupts diffusivity metrics derived from single-compartment models. We aimed to examine Parkinson's disease-related changes in nigral iron and diffusion measures from single- and bi-compartment models as well as assess the effect of iron on these diffusion measures in two separate Parkinson's cohorts. Iron-sensitive data and diffusion data were analysed in two cohorts: First, a discovery cohort consisting of 71 participants (32 control participants and 39 Parkinson's disease participants) was examined. Second, an external validation cohort, obtained from the Parkinson's Progression Marker's Initiative, consisting of 110 participants (58 control participants and 52 Parkinson's disease participants) was examined. The effect of iron on diffusion measures from single- and bi-compartment models was assessed in both cohorts. Measures sensitive to the free water compartment (discovery cohort: P = 0.006; external cohort: P = 0.01) and iron content (discovery cohort: P < 0.001; validation cohort: P = 0.02) were found to increase in substantia nigra of the Parkinson's disease group in both cohorts. However, diffusion markers derived from the single-compartment model (i.e. mean diffusivity and fractional anisotropy) were not replicated across cohorts. Correlations were seen between single-compartment diffusion measures and iron markers in the discovery cohort (iron-mean diffusivity: r = -0.400, P = 0.006) and validation cohort (iron-mean diffusivity: r = -0.387, P = 0.003) but no correlation was observed between a measure from the bi-compartment model related to the free water compartment and iron markers in either cohort. In conclusion, the variability of nigral diffusion metrics derived from the single-compartment model in Parkinson's disease may be attributed to competing influences of increased iron content, which tends to drive diffusivity down, and increases in the free water compartment, which tends to drive diffusivity up. In contrast to diffusion metrics derived from the single-compartment model, no relationship was seen between iron and the free water compartment in substantia nigra.
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Affiliation(s)
- Jason Langley
- Center for Advanced Neuroimaging, University of California Riverside, Riverside, CA 92521, USA
| | | | - Xiaoping Hu
- Center for Advanced Neuroimaging, University of California Riverside, Riverside, CA 92521, USA.,Department of Bioengineering, University of California Riverside, Riverside, CA 92521, USA
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72
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Bergsland N, Pelizzari L, Laganá MM, Di Tella S, Rossetto F, Nemni R, Clerici M, Baglio F. Automated Assessment of the Substantia Nigra Pars Compacta in Parkinson's Disease: A Diffusion Tensor Imaging Study. J Pers Med 2021; 11:jpm11111235. [PMID: 34834587 PMCID: PMC8625460 DOI: 10.3390/jpm11111235] [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: 10/13/2021] [Revised: 11/12/2021] [Accepted: 11/18/2021] [Indexed: 12/04/2022] Open
Abstract
The substantia nigra (SN) pars compacta (SNpc) and pars reticulata (SNpr) are differentially affected in Parkinson’s disease (PD). Separating the SNpc and SNpr is challenging with standard magnetic resonance imaging (MRI). Diffusion tensor imaging (DTI) allows for the characterization of SN microstructure in a non-invasive manner. In this study, 29 PD patients and 28 healthy controls (HCs) were imaged with 1.5T MRI for DTI. Images were nonlinearly registered to standard space and SNpc and SNpr DTI parameters were measured. ANCOVA and receiver operator characteristic (ROC) analyses were performed. Clinical associations were assessed with Spearman correlations. Multiple corrections were controlled for false discovery rate. PD patients presented with significantly increased SNpc axial diffusivity (AD) (1.207 ± 0.068 versus 1.156 ± 0.045, p = 0.024), with ROC analysis yielding an under the curve of 0.736. Trends with Unified Parkinson’s Disease Rating Scale (UPDRS) III scores were identified for SNpc MD (rs = 0.449), AD (rs = 0.388), and radial diffusivity (rs = 0.391) (all p < 0.1). A trend between baseline SNpr MD and H&Y change (rs = 0.563, p = 0.081) over 2.9 years of follow-up was identified (n = 14). In conclusion, SN microstructure shows robust, clinically meaningful associations in PD.
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Affiliation(s)
- Niels Bergsland
- IRCCS, Fondazione Don Carlo Gnocchi ONLUS, 20148 Milan, Italy; (N.B.); (M.M.L.); (S.D.T.); (F.R.); (R.N.); (M.C.); (F.B.)
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY 14203, USA
| | - Laura Pelizzari
- IRCCS, Fondazione Don Carlo Gnocchi ONLUS, 20148 Milan, Italy; (N.B.); (M.M.L.); (S.D.T.); (F.R.); (R.N.); (M.C.); (F.B.)
- Correspondence: ; Tel.: +39-02-4030-8074
| | - Maria Marcella Laganá
- IRCCS, Fondazione Don Carlo Gnocchi ONLUS, 20148 Milan, Italy; (N.B.); (M.M.L.); (S.D.T.); (F.R.); (R.N.); (M.C.); (F.B.)
| | - Sonia Di Tella
- IRCCS, Fondazione Don Carlo Gnocchi ONLUS, 20148 Milan, Italy; (N.B.); (M.M.L.); (S.D.T.); (F.R.); (R.N.); (M.C.); (F.B.)
| | - Federica Rossetto
- IRCCS, Fondazione Don Carlo Gnocchi ONLUS, 20148 Milan, Italy; (N.B.); (M.M.L.); (S.D.T.); (F.R.); (R.N.); (M.C.); (F.B.)
| | - Raffaello Nemni
- IRCCS, Fondazione Don Carlo Gnocchi ONLUS, 20148 Milan, Italy; (N.B.); (M.M.L.); (S.D.T.); (F.R.); (R.N.); (M.C.); (F.B.)
- Department of Pathophysiology and Transplantation, Università degli Studi di Milano, 20122 Milan, Italy
| | - Mario Clerici
- IRCCS, Fondazione Don Carlo Gnocchi ONLUS, 20148 Milan, Italy; (N.B.); (M.M.L.); (S.D.T.); (F.R.); (R.N.); (M.C.); (F.B.)
- Department of Pathophysiology and Transplantation, Università degli Studi di Milano, 20122 Milan, Italy
| | - Francesca Baglio
- IRCCS, Fondazione Don Carlo Gnocchi ONLUS, 20148 Milan, Italy; (N.B.); (M.M.L.); (S.D.T.); (F.R.); (R.N.); (M.C.); (F.B.)
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Mitchell T, Lehéricy S, Chiu SY, Strafella AP, Stoessl AJ, Vaillancourt DE. Emerging Neuroimaging Biomarkers Across Disease Stage in Parkinson Disease: A Review. JAMA Neurol 2021; 78:1262-1272. [PMID: 34459865 PMCID: PMC9017381 DOI: 10.1001/jamaneurol.2021.1312] [Citation(s) in RCA: 74] [Impact Index Per Article: 24.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Importance Imaging biomarkers in Parkinson disease (PD) are increasingly important for monitoring progression in clinical trials and also have the potential to improve clinical care and management. This Review addresses a critical need to make clear the temporal relevance for diagnostic and progression imaging biomarkers to be used by clinicians and researchers over the clinical course of PD. Magnetic resonance imaging (diffusion imaging, neuromelanin-sensitive imaging, iron-sensitive imaging, T1-weighted imaging), positron emission tomography/single-photon emission computed tomography dopaminergic, serotonergic, and cholinergic imaging as well as metabolic and cerebral blood flow network neuroimaging biomarkers in the preclinical, prodromal, early, and moderate to late stages are characterized. Observations If a clinical trial is being carried out in the preclinical and prodromal stages, potentially useful disease-state biomarkers include dopaminergic imaging of the striatum; metabolic imaging; free-water, neuromelanin-sensitive, and iron-sensitive imaging in the substantia nigra; and T1-weighted structural magnetic resonance imaging. Disease-state biomarkers that can distinguish atypical parkinsonisms are metabolic imaging, free-water imaging, and T1-weighted imaging; dopaminergic imaging and other molecular imaging track progression in prodromal patients, whereas other established progression biomarkers need to be evaluated in prodromal cohorts. Progression in early-stage PD can be monitored using dopaminergic imaging in the striatum, metabolic imaging, and free-water and neuromelanin-sensitive imaging in the posterior substantia nigra. Progression in patients with moderate to late-stage PD can be monitored using free-water imaging in the anterior substantia nigra, R2* of substantia nigra, and metabolic imaging. Cortical thickness and gyrification might also be useful markers or predictors of progression. Dopaminergic imaging and free-water imaging detect progression over 1 year, whereas other modalities detect progression over 18 months or longer. The reliability of progression biomarkers varies with disease stage, whereas disease-state biomarkers are relatively consistent in individuals with preclinical, prodromal, early, and moderate to late-stage PD. Conclusions and Relevance Imaging biomarkers for various stages of PD are readily available to be used as outcome measures in clinical trials and are potentially useful in multimodal combination with routine clinical assessment. This Review provides a critically important template for considering disease stage when implementing diagnostic and progression biomarkers in both clinical trials and clinical care settings.
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Affiliation(s)
- Trina Mitchell
- Laboratory for Rehabilitation Neuroscience, Department of Applied Physiology and Kinesiology, University of Florida, Gainesville
| | - Stéphane Lehéricy
- Paris Brain Institute, Centre de NeuroImagerie de Recherche, INSERM 1127, CNRS 7225, Sorbonne Université, Groupe Hospitalier Pitié-Salpêtrière, Paris, France
| | - Shannon Y Chiu
- Fixel Institute for Neurological Diseases, Department of Neurology, University of Florida, Gainesville
| | - Antonio P Strafella
- Division of Brain, Imaging and Behaviour-Systems Neuroscience, Krembil Research Institute, University Health Network, University of Toronto, Toronto, Ontario, Canada
- Research Imaging Centre, Campbell Family Mental Health, Toronto, Ontario, Canada
- Morton and Gloria Shulman Movement Disorder Unit and E.J. Safra Parkinson Disease Program, Neurology Division, Department of Medicine, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada
| | - A Jon Stoessl
- Pacific Parkinson's Research Centre and Parkinson's Foundation Centre of Excellence, Division of Neurology and Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, British Columbia, Canada
| | - David E Vaillancourt
- Laboratory for Rehabilitation Neuroscience, Department of Applied Physiology and Kinesiology, University of Florida, Gainesville
- Fixel Institute for Neurological Diseases, Department of Neurology, University of Florida, Gainesville
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville
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Gaurav R, Yahia‐Cherif L, Pyatigorskaya N, Mangone G, Biondetti E, Valabrègue R, Ewenczyk C, Hutchison RM, Cedarbaum JM, Corvol J, Vidailhet M, Lehéricy S. Longitudinal Changes in Neuromelanin MRI Signal in Parkinson's Disease: A Progression Marker. Mov Disord 2021; 36:1592-1602. [PMID: 33751655 PMCID: PMC8359265 DOI: 10.1002/mds.28531] [Citation(s) in RCA: 49] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Revised: 01/07/2021] [Accepted: 01/25/2021] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Development of reliable and accurate imaging biomarkers of dopaminergic cell neurodegeneration is necessary to facilitate therapeutic drug trials in Parkinson's disease (PD). Neuromelanin-sensitive MRI techniques have been effective in detecting neurodegeneration in the substantia nigra pars compacta (SNpc). The objective of the current study was to investigate longitudinal neuromelanin signal changes in the SNpc in PD patients. METHODS In this prospective, longitudinal, observational case-control study, we included 140 PD patients and 64 healthy volunteers divided into 2 cohorts. Cohort I included 99 early PD patients (disease duration, 1.5 ± 1.0 years) and 41 healthy volunteers analyzed at baseline (V1), where 79 PD patients and 32 healthy volunteers were rescanned after 2.0 ± 0.2 years of follow-up (V2). Cohort II included 41 progressing PD patients (disease duration, 9.3 ± 3.7 years) and 23 healthy volunteers at V1, where 30 PD patients were rescanned after 2.4 ± 0.5 years of follow-up. Subjects were scanned at 3 T MRI using 3-dimensional T1-weighted and neuromelanin-sensitive imaging. Regions of interest were delineated manually to calculate SN volumes, volumes corrected by total intracranial volume, signal-to-noise ratio, and contrast-to-noise ratio. RESULTS Results showed (1) significant reduction in volume and volume corrected by total intracranial volume between visits, greater in progressing PD than nonsignificant changes in healthy volunteers; (2) no significant effects of visit for signal intensity (signal-to-noise ratio); (3) significant interaction in volume between group and visit; (4) greater volume corrected by total intracranial volume at baseline in female patients and greater decrease in volume and increase in the contrast-to-noise ratio in progressing female PD patients compared with male patients; and (5) correlations between neuromelanin SN changes and disease severity and duration. CONCLUSIONS We observed a progressive and measurable decrease in neuromelanin-based SN signal and volume in PD, which might allow a direct noninvasive assessment of progression of SN loss and could represent a target biomarker for disease-modifying treatments. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Rahul Gaurav
- Paris Brain Institute– ICMCenter for NeuroImaging Research – CENIRParisFrance
- ICM, Sorbonne University, UPMC Univ Paris 06, Inserm U1127, CNRS UMRParisFrance
- ICM Team “Movement Investigations and Therapeutics” (MOV'IT)ParisFrance
| | - Lydia Yahia‐Cherif
- Paris Brain Institute– ICMCenter for NeuroImaging Research – CENIRParisFrance
- ICM, Sorbonne University, UPMC Univ Paris 06, Inserm U1127, CNRS UMRParisFrance
| | - Nadya Pyatigorskaya
- Paris Brain Institute– ICMCenter for NeuroImaging Research – CENIRParisFrance
- ICM, Sorbonne University, UPMC Univ Paris 06, Inserm U1127, CNRS UMRParisFrance
- ICM Team “Movement Investigations and Therapeutics” (MOV'IT)ParisFrance
- Department of NeuroradiologyPitié‐Salpêtrière Hospital, AP‐HPParisFrance
| | - Graziella Mangone
- ICM, Sorbonne University, UPMC Univ Paris 06, Inserm U1127, CNRS UMRParisFrance
- INSERM, Clinical Investigation Center for Neurosciences, Pitié‐Salpêtrière HospitalParisFrance
| | - Emma Biondetti
- Paris Brain Institute– ICMCenter for NeuroImaging Research – CENIRParisFrance
- ICM, Sorbonne University, UPMC Univ Paris 06, Inserm U1127, CNRS UMRParisFrance
- ICM Team “Movement Investigations and Therapeutics” (MOV'IT)ParisFrance
| | - Romain Valabrègue
- Paris Brain Institute– ICMCenter for NeuroImaging Research – CENIRParisFrance
- ICM, Sorbonne University, UPMC Univ Paris 06, Inserm U1127, CNRS UMRParisFrance
| | - Claire Ewenczyk
- ICM, Sorbonne University, UPMC Univ Paris 06, Inserm U1127, CNRS UMRParisFrance
- ICM Team “Movement Investigations and Therapeutics” (MOV'IT)ParisFrance
- Department of NeurologyPitié‐Salpêtrière Hospital, AP‐HPParisFrance
| | | | | | - Jean‐Christophe Corvol
- ICM, Sorbonne University, UPMC Univ Paris 06, Inserm U1127, CNRS UMRParisFrance
- INSERM, Clinical Investigation Center for Neurosciences, Pitié‐Salpêtrière HospitalParisFrance
- Department of NeurologyPitié‐Salpêtrière Hospital, AP‐HPParisFrance
| | - Marie Vidailhet
- ICM, Sorbonne University, UPMC Univ Paris 06, Inserm U1127, CNRS UMRParisFrance
- ICM Team “Movement Investigations and Therapeutics” (MOV'IT)ParisFrance
- Department of NeurologyPitié‐Salpêtrière Hospital, AP‐HPParisFrance
| | - Stéphane Lehéricy
- Paris Brain Institute– ICMCenter for NeuroImaging Research – CENIRParisFrance
- ICM, Sorbonne University, UPMC Univ Paris 06, Inserm U1127, CNRS UMRParisFrance
- ICM Team “Movement Investigations and Therapeutics” (MOV'IT)ParisFrance
- Department of NeuroradiologyPitié‐Salpêtrière Hospital, AP‐HPParisFrance
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Abstract
Parkinson's disease is a recognisable clinical syndrome with a range of causes and clinical presentations. Parkinson's disease represents a fast-growing neurodegenerative condition; the rising prevalence worldwide resembles the many characteristics typically observed during a pandemic, except for an infectious cause. In most populations, 3-5% of Parkinson's disease is explained by genetic causes linked to known Parkinson's disease genes, thus representing monogenic Parkinson's disease, whereas 90 genetic risk variants collectively explain 16-36% of the heritable risk of non-monogenic Parkinson's disease. Additional causal associations include having a relative with Parkinson's disease or tremor, constipation, and being a non-smoker, each at least doubling the risk of Parkinson's disease. The diagnosis is clinically based; ancillary testing is reserved for people with an atypical presentation. Current criteria define Parkinson's disease as the presence of bradykinesia combined with either rest tremor, rigidity, or both. However, the clinical presentation is multifaceted and includes many non-motor symptoms. Prognostic counselling is guided by awareness of disease subtypes. Clinically manifest Parkinson's disease is preceded by a potentially long prodromal period. Presently, establishment of prodromal symptoms has no clinical implications other than symptom suppression, although recognition of prodromal parkinsonism will probably have consequences when disease-modifying treatments become available. Treatment goals vary from person to person, emphasising the need for personalised management. There is no reason to postpone symptomatic treatment in people developing disability due to Parkinson's disease. Levodopa is the most common medication used as first-line therapy. Optimal management should start at diagnosis and requires a multidisciplinary team approach, including a growing repertoire of non-pharmacological interventions. At present, no therapy can slow down or arrest the progression of Parkinson's disease, but informed by new insights in genetic causes and mechanisms of neuronal death, several promising strategies are being tested for disease-modifying potential. With the perspective of people with Parkinson's disease as a so-called red thread throughout this Seminar, we will show how personalised management of Parkinson's disease can be optimised.
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Affiliation(s)
- Bastiaan R Bloem
- Radboud University Medical Centre, Donders Institute for Brain, Cognition and Behaviour, Department of Neurology, Centre of Expertise for Parkinson and Movement Disorders, Nijmegen, Netherlands.
| | - Michael S Okun
- Department of Neurology, Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, USA
| | - Christine Klein
- Institute of Neurogenetics and Department of Neurology, University of Lübeck and University Hospital Schleswig-Holstein, Lübeck, Germany
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Update on neuroimaging for categorization of Parkinson's disease and atypical parkinsonism. Curr Opin Neurol 2021; 34:514-524. [PMID: 34010220 DOI: 10.1097/wco.0000000000000957] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
PURPOSE OF REVIEW Differential diagnosis of Parkinsonism may be difficult. The objective of this review is to present the work of the last three years in the field of imaging for diagnostic categorization of parkinsonian syndromes focusing on progressive supranuclear palsy (PSP) and multiple system atrophy (MSA). RECENT FINDINGS Two main complementary approaches are being pursued. The first seeks to develop and validate manual qualitative or semi-quantitative imaging markers that can be easily used in clinical practice. The second is based on quantitative measurements of magnetic resonance imaging abnormalities integrated in a multimodal approach and in automatic categorization machine learning tools. SUMMARY These two complementary approaches obtained high diagnostic around 90% and above in the classical Richardson form of PSP and probable MSA. Future work will determine if these techniques can improve diagnosis in other PSP variants and early forms of the diseases when all clinical criteria are not fully met.
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77
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Kamagata K, Andica C, Kato A, Saito Y, Uchida W, Hatano T, Lukies M, Ogawa T, Takeshige-Amano H, Akashi T, Hagiwara A, Fujita S, Aoki S. Diffusion Magnetic Resonance Imaging-Based Biomarkers for Neurodegenerative Diseases. Int J Mol Sci 2021; 22:ijms22105216. [PMID: 34069159 PMCID: PMC8155849 DOI: 10.3390/ijms22105216] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 05/10/2021] [Accepted: 05/10/2021] [Indexed: 12/27/2022] Open
Abstract
There has been an increasing prevalence of neurodegenerative diseases with the rapid increase in aging societies worldwide. Biomarkers that can be used to detect pathological changes before the development of severe neuronal loss and consequently facilitate early intervention with disease-modifying therapeutic modalities are therefore urgently needed. Diffusion magnetic resonance imaging (MRI) is a promising tool that can be used to infer microstructural characteristics of the brain, such as microstructural integrity and complexity, as well as axonal density, order, and myelination, through the utilization of water molecules that are diffused within the tissue, with displacement at the micron scale. Diffusion tensor imaging is the most commonly used diffusion MRI technique to assess the pathophysiology of neurodegenerative diseases. However, diffusion tensor imaging has several limitations, and new technologies, including neurite orientation dispersion and density imaging, diffusion kurtosis imaging, and free-water imaging, have been recently developed as approaches to overcome these constraints. This review provides an overview of these technologies and their potential as biomarkers for the early diagnosis and disease progression of major neurodegenerative diseases.
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Affiliation(s)
- Koji Kamagata
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (C.A.); (Y.S.); (W.U.); (T.A.); (A.H.); (S.F.); (S.A.)
- Correspondence:
| | - Christina Andica
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (C.A.); (Y.S.); (W.U.); (T.A.); (A.H.); (S.F.); (S.A.)
| | - Ayumi Kato
- Department of Multidisciplinary Internal Medicine, Faculty of Medicine, Tottori University, Yonago 683-8504, Japan;
| | - Yuya Saito
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (C.A.); (Y.S.); (W.U.); (T.A.); (A.H.); (S.F.); (S.A.)
| | - Wataru Uchida
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (C.A.); (Y.S.); (W.U.); (T.A.); (A.H.); (S.F.); (S.A.)
| | - Taku Hatano
- Department of Neurology, Juntendo University School of Medicine, Tokyo 113-8421, Japan; (T.H.); (T.O.); (H.T.-A.)
| | - Matthew Lukies
- Department of Diagnostic and Interventional Radiology, Alfred Health, Melbourne, VIC 3004, Australia;
| | - Takashi Ogawa
- Department of Neurology, Juntendo University School of Medicine, Tokyo 113-8421, Japan; (T.H.); (T.O.); (H.T.-A.)
| | - Haruka Takeshige-Amano
- Department of Neurology, Juntendo University School of Medicine, Tokyo 113-8421, Japan; (T.H.); (T.O.); (H.T.-A.)
| | - Toshiaki Akashi
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (C.A.); (Y.S.); (W.U.); (T.A.); (A.H.); (S.F.); (S.A.)
| | - Akifumi Hagiwara
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (C.A.); (Y.S.); (W.U.); (T.A.); (A.H.); (S.F.); (S.A.)
| | - Shohei Fujita
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (C.A.); (Y.S.); (W.U.); (T.A.); (A.H.); (S.F.); (S.A.)
| | - Shigeki Aoki
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (C.A.); (Y.S.); (W.U.); (T.A.); (A.H.); (S.F.); (S.A.)
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Zhou L, Li G, Zhang Y, Zhang M, Chen Z, Zhang L, Wang X, Zhang M, Ye G, Li Y, Chen S, Li B, Wei H, Liu J. Increased free water in the substantia nigra in idiopathic REM sleep behaviour disorder. Brain 2021; 144:1488-1497. [PMID: 33880500 DOI: 10.1093/brain/awab039] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2020] [Revised: 11/14/2020] [Accepted: 12/04/2020] [Indexed: 11/14/2022] Open
Abstract
Imaging markers sensitive to neurodegeneration in the substantia nigra are critically needed for future disease-modifying trials. Previous studies have demonstrated the utility of posterior substantia nigra free water as a marker of progression in Parkinson's disease. In this study, we tested the hypothesis that free water is elevated in the posterior substantia nigra of idiopathic REM sleep behaviour disorder, which is considered a prodromal stage of synucleinopathy. We applied free-water imaging to 32 healthy control subjects, 34 patients with idiopathic REM sleep behaviour disorder and 38 patients with Parkinson's disease. Eighteen healthy control subjects and 22 patients with idiopathic REM sleep behaviour disorder were followed up and completed longitudinal free-water imaging. Free-water values in the substantia nigra were calculated for each individual and compared among groups. We tested the associations between posterior substantia nigra free water and uptake of striatal dopamine transporter in idiopathic REM sleep behaviour disorder. Free-water values in the posterior substantia nigra were significantly higher in the patients with idiopathic REM sleep behaviour disorder patients than in the healthy control subjects, but were significantly lower in patients with idiopathic REM sleep behaviour disorder than in patients with Parkinson's disease. In addition, we observed significantly negative associations between posterior substantia nigra free-water values and dopamine transporter striatal binding ratios in the idiopathic REM sleep behaviour disorder patients. Longitudinal free-water imaging analyses were conducted with a linear mixed-effects model, and showed a significant Group × Time interaction in posterior substantia nigra, identifying increased mean free-water values in posterior substantia nigra of idiopathic REM sleep behaviour disorder over time. These results demonstrate that free water in the posterior substantia nigra is a valid imaging marker of neurodegeneration in idiopathic REM sleep behaviour disorder, which has the potential to be used as an indicator in disease-modifying trials.
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Affiliation(s)
- Liche Zhou
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Guanglu Li
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Yuyao Zhang
- School of Information and Science and Technology, Shanghai Tech University, Shanghai, China
| | - Miao Zhang
- Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Zhichun Chen
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Lina Zhang
- Department of Biostatistics, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xiaojin Wang
- Department of Biostatistics, Clinical Research Institute, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Ming Zhang
- Institute for Medical Imaging Technology, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Guanyu Ye
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Yuanyuan Li
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Shengdi Chen
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Biao Li
- Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Hongjiang Wei
- Institute for Medical Imaging Technology, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Jun Liu
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
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Prasuhn J, Brüggemann N. Genotype-driven therapeutic developments in Parkinson's disease. Mol Med 2021; 27:42. [PMID: 33874883 PMCID: PMC8056568 DOI: 10.1186/s10020-021-00281-8] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Accepted: 02/12/2021] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Remarkable advances have been reached in the understanding of the genetic basis of Parkinson's disease (PD), with the identification of monogenic causes (mPD) and a plethora of gene loci leading to an increased risk for idiopathic PD. The expanding knowledge and subsequent identification of genetic contributions fosters the understanding of molecular mechanisms leading to disease development and progression. Distinct pathways involved in mitochondrial dysfunction, oxidative stress, and lysosomal function have been identified and open a unique window of opportunity for individualized treatment approaches. These genetic findings have led to an imminent progress towards pathophysiology-targeted clinical trials and potentially disease-modifying treatments in the future. MAIN BODY OF THE MANUSCRIPT In this review article we will summarize known genetic contributors to the pathophysiology of Parkinson's disease, the molecular mechanisms leading to disease development, and discuss challenges and opportunities in clinical trial designs. CONCLUSIONS The future success of clinical trials in PD is mainly dependent on reliable biomarker development and extensive genetic testing to identify genetic cases. Whether genotype-dependent stratification of study participants will extend the potential application of new drugs will be one major challenge in conceptualizing clinical trials. However, the latest developments in genotype-driven treatments will pave the road to individualized pathophysiology-based therapies in the future.
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Affiliation(s)
- Jannik Prasuhn
- Department of Neurology, University Medical Center Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
- Institute of Neurogenetics, University of Lübeck, Lübeck, Germany
- Center of Brain, Behavior and Metabolism, University of Lübeck, Lübeck, Germany
| | - Norbert Brüggemann
- Department of Neurology, University Medical Center Schleswig-Holstein, Campus Lübeck, Lübeck, Germany.
- Institute of Neurogenetics, University of Lübeck, Lübeck, Germany.
- Center of Brain, Behavior and Metabolism, University of Lübeck, Lübeck, Germany.
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Kim DH, Kim R, Lee JY, Lee KM. Clinical, Imaging, and Laboratory Markers of Premanifest Spinocerebellar Ataxia 1, 2, 3, and 6: A Systematic Review. J Clin Neurol 2021; 17:187-199. [PMID: 33835738 PMCID: PMC8053554 DOI: 10.3988/jcn.2021.17.2.187] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2020] [Revised: 02/03/2021] [Accepted: 02/03/2021] [Indexed: 12/26/2022] Open
Abstract
Background and Purpose Premanifest mutation carriers with spinocerebellar ataxia (SCA) can exhibit subtle abnormalities before developing ataxia. We summarized the preataxic manifestations of SCA1, -2, -3, and -6, and their associations with ataxia onset. Methods We included studies of the premanifest carriers of SCA published between January 1998 and December 2019 identified in Scopus and PubMed by searching for terms including ‘spinocerebellar ataxia’ and several synonyms of ‘preataxic manifestation’. We systematically reviewed the results obtained in studies categorized based on clinical, imaging, and laboratory markers. Results We finally performed a qualitative analysis of 48 papers. Common preataxic manifestations appearing in multiple SCA subtypes were muscle cramps, abnormal muscle reflexes, instability in gait and posture, lower Composite Cerebellar Functional Severity scores, abnormalities in video-oculography and transcranial magnetic stimulation, and gray-matter loss and volume reduction in the brainstem and cerebellar structures. Also, decreased sensory amplitudes in nerve conduction studies were observed in SCA2. Eotaxin and neurofilament light-chain levels were revealed as sensitive blood biomarkers in SCA3. Concerning potential predictive markers, hyporeflexia and abnormalities of somatosensory evoked potentials showed correlations with the time to ataxia onset in SCA2 carriers. However, no longitudinal data were found for the other SCA gene carriers. Conclusions Our results suggest that preataxic manifestations vary among SCA1, -2, -3, and -6, with some subtypes sharing specific features. Combining various markers into a standardized index for premanifest carriers may be useful for early screening and assessing the risk of disease progression in SCA carriers.
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Affiliation(s)
- Dong Hoi Kim
- Seoul National University College of Medicine, Seoul, Korea.,Department of Neurology, Seoul National University-Seoul Metropolitan Government Boramae Medical Center, Seoul National University College of Medicine, Seoul, Korea
| | - Ryul Kim
- Department of Neurology, Inha University Hospital, Incheon, Korea
| | - Jee Young Lee
- Seoul National University College of Medicine, Seoul, Korea.,Department of Neurology, Seoul National University-Seoul Metropolitan Government Boramae Medical Center, Seoul National University College of Medicine, Seoul, Korea.
| | - Kyoung Min Lee
- Seoul National University College of Medicine, Seoul, Korea.,Department of Neurology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
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81
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Dadar M, Miyasaki J, Duchesne S, Camicioli R. White matter hyperintensities mediate the impact of amyloid ß on future freezing of gait in Parkinson's disease. Parkinsonism Relat Disord 2021; 85:95-101. [PMID: 33770671 DOI: 10.1016/j.parkreldis.2021.02.031] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Revised: 02/17/2021] [Accepted: 02/28/2021] [Indexed: 02/07/2023]
Abstract
BACKGROUND Freezing of gait (FOG) is a common symptom in Parkinson's Disease (PD) patients. Previous studies have reported relationships between FOG, substantia nigra (SN) degeneration, dopamine transporter (DAT) concentration, as well as amyloid β deposition. However, there is a paucity of research on the concurrent impact of white matter damage. OBJECTIVES To assess the inter-relationships between these different co-morbidities, their impact on future FOG and whether they act independently of each other. METHODS We used baseline MRI and longitudinal gait data from 423 de novo PD patients from the Parkinson's Progression Markers Initiative (PPMI). We used deformation based morphometry (DBM) from T1-weighted MRI to measure SN atrophy, and segmentation of white matter hyperintensities (WMH) as a measure of WM pathological load. Putamen and caudate DAT levels from SPECT as well as cerebrospinal fluid (CSF) amyloid β were obtained directly from the PPMI. Following correlation analyses, we investigated whether WMH burden mediates the impact of amyloid β on future FOG. RESULTS SN DBM, WMH load, putamen and caudate DAT activity and CSF amyloid β levels were significantly different between PD patients with and without future FOG (p < 0.008). Mediation analysis demonstrated an effect of CSF amyloid β levels on future FOG via WMH load, independent of SN atrophy and striatal DAT activity levels. CONCLUSIONS Amyloid β might impact future FOG in PD patients through an increase in WMH burden, in a pathway independent of Lewy body pathology.
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Affiliation(s)
- Mahsa Dadar
- CERVO Brain Research Center, Centre Intégré Universitaire Santé et Services Sociaux de La Capitale Nationale, Québec, QC, Canada.
| | - Janis Miyasaki
- Neuroscience and Mental Health Institute and Department of Medicine, Division of Neurology, University of Alberta, Edmonton, AB, Canada
| | - Simon Duchesne
- CERVO Brain Research Center, Centre Intégré Universitaire Santé et Services Sociaux de La Capitale Nationale, Québec, QC, Canada; Department of Radiology and Nuclear Medicine, Faculty of Medicine, Université Laval, Québec, QC, Canada
| | - Richard Camicioli
- Neuroscience and Mental Health Institute and Department of Medicine, Division of Neurology, University of Alberta, Edmonton, AB, Canada
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82
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Dzieciol K, Iordanishvili E, Abbas Z, Nahimi A, Winterdahl M, Shah NJ. A robust method for the detection of small changes in relaxation parameters and free water content in the vicinity of the substantia nigra in Parkinson's disease patients. PLoS One 2021; 16:e0247552. [PMID: 33626092 PMCID: PMC7904163 DOI: 10.1371/journal.pone.0247552] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Accepted: 02/09/2021] [Indexed: 11/19/2022] Open
Abstract
Alterations in the substantia nigra are strongly associated with Parkinson's disease. However, due to low contrast and partial volume effects present in typical MRI images, the substantia nigra is not of sufficient size to obtain a reliable segmentation for region-of-interest based analysis. To combat this problem, the approach proposed here offers a method to investigate and reveal changes in quantitative MRI parameters in the vicinity of substantia nigra without any a priori delineation. This approach uses an alternative method of statistical, voxel-based analysis of quantitative maps and was tested on 18 patients and 15 healthy controls using a well-established, quantitative free water mapping protocol. It was possible to reveal the topology and the location of pathological changes in the substantia nigra and its vicinity. Moreover, a decrease in free water content, T1 and T2* in the vicinity of substantia nigra was indicated in the Parkinson's disease patients compared to the healthy controls. These findings reflect a disruption of grey matter and iron accumulation, which is known to lead to neurodegeneration. Consequently, the proposed method demonstrates an increased sensitivity for the detection of pathological changes-even in small regions-and can facilitate disease monitoring via quantitative MR parameters.
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Affiliation(s)
- Krzysztof Dzieciol
- Institute of Neuroscience and Medicine 4 (INM-4), Forschungszentrum Jülich GmbH, Jülich, Germany
| | - Elene Iordanishvili
- Institute of Neuroscience and Medicine 4 (INM-4), Forschungszentrum Jülich GmbH, Jülich, Germany
| | - Zaheer Abbas
- Institute of Neuroscience and Medicine 4 (INM-4), Forschungszentrum Jülich GmbH, Jülich, Germany
| | - Adjmal Nahimi
- Department of Nuclear Medicine and PET Center, Aarhus University, Aarhus, Denmark
| | - Michael Winterdahl
- Department of Nuclear Medicine and PET Center, Aarhus University, Aarhus, Denmark
| | - N. Jon Shah
- Institute of Neuroscience and Medicine 4 (INM-4), Forschungszentrum Jülich GmbH, Jülich, Germany
- Institute of Neuroscience and Medicine 11 (INM-11), Forschungszentrum Jülich GmbH, Jülich, Germany
- Jülich Aachen Research Alliance (JARA-BRAIN)—Translational Medicine, Aachen, Germany
- Department of Neurology, RWTH Aachen University, Aachen, Germany
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83
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Vaillancourt DE, Mitchell T. Parkinson's disease progression in the substantia nigra: location, location, location. Brain 2021; 143:2628-2630. [PMID: 32947614 DOI: 10.1093/brain/awaa252] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
This scientific commentary refers to ‘Spatiotemporal changes in substantia nigra neuromelanin content in Parkinson’s disease’, by Biondetti et al. (doi:10.1093/brain/awaa216
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Affiliation(s)
- David E Vaillancourt
- Fixel Institute for Neurological Diseases, Department of Neurology, University of Florida, USA.,Laboratory for Rehabilitation Neuroscience, Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, USA.,J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA
| | - Trina Mitchell
- Laboratory for Rehabilitation Neuroscience, Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, USA
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84
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Del Campo N, Phillips O, Ory‐Magne F, Brefel‐Courbon C, Galitzky M, Thalamas C, Narr KL, Joshi S, Singh MK, Péran P, Pavy‐LeTraon A, Rascol O. Broad white matter impairment in multiple system atrophy. Hum Brain Mapp 2021; 42:357-366. [PMID: 33064319 PMCID: PMC7776008 DOI: 10.1002/hbm.25227] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2019] [Revised: 07/09/2020] [Accepted: 08/10/2020] [Indexed: 11/11/2022] Open
Abstract
Multiple system atrophy (MSA) is a rare neurodegenerative disorder characterized by the widespread aberrant accumulation of α-synuclein (α-syn). MSA differs from other synucleinopathies such as Parkinson's disease (PD) in that α-syn accumulates primarily in oligodendrocytes, the only source of white matter myelination in the brain. Previous MSA imaging studies have uncovered focal differences in white matter. Here, we sought to build on this work by taking a global perspective on whole brain white matter. In order to do this, in vivo structural imaging and diffusion magnetic resonance imaging were acquired on 26 MSA patients, 26 healthy controls, and 23 PD patients. A refined whole brain approach encompassing the major fiber tracts and the superficial white matter located at the boundary of the cortical mantle was applied. The primary observation was that MSA but not PD patients had whole brain deep and superficial white matter diffusivity abnormalities (p < .001). In addition, in MSA patients, these abnormalities were associated with motor (Unified MSA Rating Scale, Part II) and cognitive functions (Mini-Mental State Examination). The pervasive whole brain abnormalities we observe suggest that there is widespread white matter damage in MSA patients which mirrors the widespread aggregation of α-syn in oligodendrocytes. Importantly, whole brain white matter abnormalities were associated with clinical symptoms, suggesting that white matter impairment may be more central to MSA than previously thought.
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Affiliation(s)
- Natalia Del Campo
- CHU de Toulouse, Université de Toulouse‐Toulouse 3, INSERM, UMR1214 Toulouse NeuroImaging Centre “TONIC,” Center of Excellence in Neurodegeneration (CoEN), NeuroToul, Centre National de Reference AMS, Centre Expert Parkinson de Toulouse, Centre d'Investigation Clinique CIC1436, Services de Neurologie et de Pharmacologie Clinique, UMR 1048 Institute for Cardiovascular DiseasesToulouseFrance
| | - Owen Phillips
- CHU de Toulouse, Université de Toulouse‐Toulouse 3, INSERM, UMR1214 Toulouse NeuroImaging Centre “TONIC,” Center of Excellence in Neurodegeneration (CoEN), NeuroToul, Centre National de Reference AMS, Centre Expert Parkinson de Toulouse, Centre d'Investigation Clinique CIC1436, Services de Neurologie et de Pharmacologie Clinique, UMR 1048 Institute for Cardiovascular DiseasesToulouseFrance
- Division of Child and Adolescent Psychiatry, Department of PsychiatryStanford University School of MedicineStanfordCaliforniaUSA
- BrainKeySan FranciscoCaliforniaUSA
| | - Françoise Ory‐Magne
- CHU de Toulouse, Université de Toulouse‐Toulouse 3, INSERM, UMR1214 Toulouse NeuroImaging Centre “TONIC,” Center of Excellence in Neurodegeneration (CoEN), NeuroToul, Centre National de Reference AMS, Centre Expert Parkinson de Toulouse, Centre d'Investigation Clinique CIC1436, Services de Neurologie et de Pharmacologie Clinique, UMR 1048 Institute for Cardiovascular DiseasesToulouseFrance
| | - Christine Brefel‐Courbon
- CHU de Toulouse, Université de Toulouse‐Toulouse 3, INSERM, UMR1214 Toulouse NeuroImaging Centre “TONIC,” Center of Excellence in Neurodegeneration (CoEN), NeuroToul, Centre National de Reference AMS, Centre Expert Parkinson de Toulouse, Centre d'Investigation Clinique CIC1436, Services de Neurologie et de Pharmacologie Clinique, UMR 1048 Institute for Cardiovascular DiseasesToulouseFrance
| | - Monique Galitzky
- CHU de Toulouse, Université de Toulouse‐Toulouse 3, INSERM, UMR1214 Toulouse NeuroImaging Centre “TONIC,” Center of Excellence in Neurodegeneration (CoEN), NeuroToul, Centre National de Reference AMS, Centre Expert Parkinson de Toulouse, Centre d'Investigation Clinique CIC1436, Services de Neurologie et de Pharmacologie Clinique, UMR 1048 Institute for Cardiovascular DiseasesToulouseFrance
| | - Claire Thalamas
- CHU de Toulouse, Université de Toulouse‐Toulouse 3, INSERM, UMR1214 Toulouse NeuroImaging Centre “TONIC,” Center of Excellence in Neurodegeneration (CoEN), NeuroToul, Centre National de Reference AMS, Centre Expert Parkinson de Toulouse, Centre d'Investigation Clinique CIC1436, Services de Neurologie et de Pharmacologie Clinique, UMR 1048 Institute for Cardiovascular DiseasesToulouseFrance
| | - Katherine L. Narr
- Department of NeurologyAhmanson Lovelace Brain Mapping Center, David Geffen School of Medicine at UCLALos AngelesCaliforniaUSA
| | - Shantanu Joshi
- Department of NeurologyAhmanson Lovelace Brain Mapping Center, David Geffen School of Medicine at UCLALos AngelesCaliforniaUSA
| | - Manpreet K. Singh
- Division of Child and Adolescent Psychiatry, Department of PsychiatryStanford University School of MedicineStanfordCaliforniaUSA
| | - Patrice Péran
- CHU de Toulouse, Université de Toulouse‐Toulouse 3, INSERM, UMR1214 Toulouse NeuroImaging Centre “TONIC,” Center of Excellence in Neurodegeneration (CoEN), NeuroToul, Centre National de Reference AMS, Centre Expert Parkinson de Toulouse, Centre d'Investigation Clinique CIC1436, Services de Neurologie et de Pharmacologie Clinique, UMR 1048 Institute for Cardiovascular DiseasesToulouseFrance
| | - Anne Pavy‐LeTraon
- CHU de Toulouse, Université de Toulouse‐Toulouse 3, INSERM, UMR1214 Toulouse NeuroImaging Centre “TONIC,” Center of Excellence in Neurodegeneration (CoEN), NeuroToul, Centre National de Reference AMS, Centre Expert Parkinson de Toulouse, Centre d'Investigation Clinique CIC1436, Services de Neurologie et de Pharmacologie Clinique, UMR 1048 Institute for Cardiovascular DiseasesToulouseFrance
| | - Olivier Rascol
- CHU de Toulouse, Université de Toulouse‐Toulouse 3, INSERM, UMR1214 Toulouse NeuroImaging Centre “TONIC,” Center of Excellence in Neurodegeneration (CoEN), NeuroToul, Centre National de Reference AMS, Centre Expert Parkinson de Toulouse, Centre d'Investigation Clinique CIC1436, Services de Neurologie et de Pharmacologie Clinique, UMR 1048 Institute for Cardiovascular DiseasesToulouseFrance
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85
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Ji GJ, Liu T, Li Y, Liu P, Sun J, Chen X, Tian Y, Chen X, Dahmani L, Liu H, Wang K, Hu P. Structural correlates underlying accelerated magnetic stimulation in Parkinson's disease. Hum Brain Mapp 2020; 42:1670-1681. [PMID: 33314545 PMCID: PMC7978118 DOI: 10.1002/hbm.25319] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2020] [Revised: 11/12/2020] [Accepted: 12/03/2020] [Indexed: 01/02/2023] Open
Abstract
Repetitive transcranial magnetic stimulation (rTMS) is a noninvasive neuromodulation technique with great potential in the treatment of Parkinson's disease (PD). This study aimed to investigate the clinical efficacy of accelerated rTMS and to understand the underlying neural mechanism. In a double‐blinded way, a total of 42 patients with PD were randomized to receive real (n = 22) or sham (n = 20) continuous theta‐burst stimulation (cTBS) on the left supplementary motor area (SMA) for 14 consecutive days. Patients treated with real cTBS, but not with sham cTBS, showed a significant improvement in Part III of the Unified PD Rating Scale (p < .0001). This improvement was observed as early as 1 week after the start of cTBS treatment, and maintained 8 weeks after the end of the treatment. These findings indicated that the treatment response was swift with a long‐lasting effect. Imaging analyses showed that volume of the left globus pallidus (GP) increased after cTBS treatment. Furthermore, the volume change of GP was mildly correlated with symptom improvement and associated with the baseline fractional anisotropy of SMA‐GP tracts. Together, these findings implicated that the accelerated cTBS could effectively alleviate motor symptoms of PD, maybe by modulating the motor circuitry involving the SMA‐GP pathway.
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Affiliation(s)
- Gong-Jun Ji
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.,Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
| | - Tingting Liu
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.,Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
| | - Ying Li
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.,Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
| | - Pingping Liu
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.,Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
| | - Jinmei Sun
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.,Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
| | - Xingui Chen
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.,Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
| | - Yanghua Tian
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.,Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
| | - Xianwen Chen
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.,Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
| | - Louisa Dahmani
- Department of Neuroscience, Medical University of South Carolina, Charleston, South Carolina, USA
| | - Hesheng Liu
- Department of Neuroscience, Medical University of South Carolina, Charleston, South Carolina, USA
| | - Kai Wang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.,Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
| | - Panpan Hu
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.,Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
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86
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Abstract
Neurodegenerative diseases are a heterogeneous group of disorders characterized by gradual progressive neuronal loss in the central nervous system. Unfortunately, the pathogenesis of many of these diseases remains unknown. Synucleins are a family of small, highly charged proteins expressed predominantly in neurons. Following their discovery, much has been learned about their structure, function, interaction with other proteins and role in neurodegenerative disease over the last two decades. One of these proteins, α-Synuclein (α-Syn), appears to be involved in many neurodegenerative disorders. These include Parkinson's disease (PD), dementia with Lewy bodies (DLB), Rapid Eye Movement Sleep Behavior Disorder (RBD) and Pure Autonomic Failure (PAF), i.e., collectively termed α-synucleinopathies. This review focuses on α-Syn dysfunction in neurodegeneration and assesses its role in synucleinopathies from a biochemical, genetic and neuroimaging perspective.
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Affiliation(s)
- Anastasia Bougea
- Neurochemistry Laboratory, 1st Department of Neurology and Movement Disorders, Medical School, Aeginition Hospital, National and Kapodistrian University of Athens, Athens, Greece; Neuroscience Laboratory, Center for Basic Research, Biomedical Research Foundation of the Academy of Athens, Athens, Greece.
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87
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Saeed U, Lang AE, Masellis M. Neuroimaging Advances in Parkinson's Disease and Atypical Parkinsonian Syndromes. Front Neurol 2020; 11:572976. [PMID: 33178113 PMCID: PMC7593544 DOI: 10.3389/fneur.2020.572976] [Citation(s) in RCA: 58] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Accepted: 09/02/2020] [Indexed: 12/11/2022] Open
Abstract
Parkinson's disease (PD) and atypical Parkinsonian syndromes are progressive heterogeneous neurodegenerative diseases that share clinical characteristic of parkinsonism as a common feature, but are considered distinct clinicopathological disorders. Based on the predominant protein aggregates observed within the brain, these disorders are categorized as, (1) α-synucleinopathies, which include PD and other Lewy body spectrum disorders as well as multiple system atrophy, and (2) tauopathies, which comprise progressive supranuclear palsy and corticobasal degeneration. Although, great strides have been made in neurodegenerative disease research since the first medical description of PD in 1817 by James Parkinson, these disorders remain a major diagnostic and treatment challenge. A valid diagnosis at early disease stages is of paramount importance, as it can help accommodate differential prognostic and disease management approaches, enable the elucidation of reliable clinicopathological relationships ideally at prodromal stages, as well as facilitate the evaluation of novel therapeutics in clinical trials. However, the pursuit for early diagnosis in PD and atypical Parkinsonian syndromes is hindered by substantial clinical and pathological heterogeneity, which can influence disease presentation and progression. Therefore, reliable neuroimaging biomarkers are required in order to enhance diagnostic certainty and ensure more informed diagnostic decisions. In this article, an updated presentation of well-established and emerging neuroimaging biomarkers are reviewed from the following modalities: (1) structural magnetic resonance imaging (MRI), (2) diffusion-weighted and diffusion tensor MRI, (3) resting-state and task-based functional MRI, (4) proton magnetic resonance spectroscopy, (5) transcranial B-mode sonography for measuring substantia nigra and lentiform nucleus echogenicity, (6) single photon emission computed tomography for assessing the dopaminergic system and cerebral perfusion, and (7) positron emission tomography for quantifying nigrostriatal functions, glucose metabolism, amyloid, tau and α-synuclein molecular imaging, as well as neuroinflammation. Multiple biomarkers obtained from different neuroimaging modalities can provide distinct yet corroborative information on the underlying neurodegenerative processes. This integrative "multimodal approach" may prove superior to single modality-based methods. Indeed, owing to the international, multi-centered, collaborative research initiatives as well as refinements in neuroimaging technology that are currently underway, the upcoming decades will mark a pivotal and exciting era of further advancements in this field of neuroscience.
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Affiliation(s)
- Usman Saeed
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Anthony E Lang
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON, Canada.,Edmond J Safra Program in Parkinson's Disease and the Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
| | - Mario Masellis
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, ON, Canada.,Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON, Canada.,L.C. Campbell Cognitive Neurology Research Unit, Sunnybrook Health Sciences Center, Toronto, ON, Canada.,Cognitive and Movement Disorders Clinic, Sunnybrook Health Sciences Center, Toronto, ON, Canada
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88
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Zhang Y, Burock MA. Diffusion Tensor Imaging in Parkinson's Disease and Parkinsonian Syndrome: A Systematic Review. Front Neurol 2020; 11:531993. [PMID: 33101169 PMCID: PMC7546271 DOI: 10.3389/fneur.2020.531993] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2020] [Accepted: 08/18/2020] [Indexed: 12/21/2022] Open
Abstract
Diffusion tensor imaging (DTI) allows measuring fractional anisotropy and similar microstructural indices of the brain white matter. Lower than normal fractional anisotropy as well as higher than normal diffusivity is associated with loss of microstructural integrity and neurodegeneration. Previous DTI studies in Parkinson's disease (PD) have demonstrated abnormal fractional anisotropy in multiple white matter regions, particularly in the dopaminergic nuclei and dopaminergic pathways. However, DTI is not considered a diagnostic marker for the earliest Parkinson's disease since anisotropic alterations present a temporally divergent pattern during the earliest Parkinson's course. This article reviews a majority of clinically employed DTI studies in PD, and it aims to prove the utilities of DTI as a marker of diagnosing PD, correlating clinical symptomatology, tracking disease progression, and treatment effects. To address the challenge of DTI being a diagnostic marker for early PD, this article also provides a comparison of the results from a longitudinal, early stage, multicenter clinical cohort of Parkinson's research with previous publications. This review provides evidences of DTI as a promising marker for monitoring PD progression and classifying atypical PD types, and it also interprets the possible pathophysiologic processes under the complex pattern of fractional anisotropic changes in the first few years of PD. Recent technical advantages, limitations, and further research strategies of clinical DTI in PD are additionally discussed.
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Affiliation(s)
- Yu Zhang
- Department of Psychiatry, War Related Illness and Injury Study Center, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, United States
| | - Marc A Burock
- Department of Psychiatry, Mainline Health, Bryn Mawr Hospital, Bryn Mawr, PA, United States
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89
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Le H, Zeng W, Zhang H, Li J, Wu X, Xie M, Yan X, Zhou M, Zhang H, Wang M, Hong G, Shen J. Mean Apparent Propagator MRI Is Better Than Conventional Diffusion Tensor Imaging for the Evaluation of Parkinson's Disease: A Prospective Pilot Study. Front Aging Neurosci 2020; 12:563595. [PMID: 33192458 PMCID: PMC7541835 DOI: 10.3389/fnagi.2020.563595] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Accepted: 08/31/2020] [Indexed: 12/11/2022] Open
Abstract
Background and Purpose Mean apparent propagator (MAP) MRI is a novel diffusion imaging method to map tissue microstructure. The purpose of this study was to evaluate the diagnostic value of the MAP MRI in Parkinson’s disease (PD) in comparison with conventional diffusion tensor imaging (DTI). Methods 23 PD patients and 22 age- and gender-matched healthy controls were included. MAP MRI and DTI were performed on a 3T MR scanner with a 20-channel head coil. The MAP metrics including mean square displacement (MSD), return to the origin probability (RTOP), return to the axis probability (RTAP), and return to the plane probability (RTPP), and DTI metrics including fractional anisotropy (FA), and mean diffusivity (MD), were measured in subcortical gray matter and compared between the two groups. The receiver operating characteristic (ROC) curve was used to analyze the diagnostic performance of all the metrics. The association between the diffusion metrics and disease severity was assessed by Pearson correlation analysis. Results For MAP MRI, the mean values of MSD in the bilateral caudate, pallidum, putamen, thalamus and substantia nigra (SN) were higher in PD patients than in healthy controls (pFDR ≤ 0.001); the mean values of the zero displacement probabilities (RTOP, RTAP, and RTPP) in the bilateral caudate, pallidum, putamen and thalamus were lower in PD patients (pFDR < 0.001). For DTI, only FA in the bilateral SN was significantly higher in PD patients than those in the controls (pFDR < 0.001). ROC analysis showed that the areas under the curves of MAP MRI metrics (MSD, RTOP, RTAP, and RTPP) in the bilateral caudate, pallidum, putamen and thalamus (range, 0.85–0.94) were greater than those of FA and MD of DTI (range, 0.55–0.69) in discriminating between PD patients and healthy controls. RTAP in the ipsilateral pallidum (r = −0.56, pFDR = 0.027), RTOP in the bilateral and contralateral putamen (r = −0.58, pFDR = 0.019; r = −0.57, pFDR = 0.024) were negatively correlated with UPDRS III motor scores. Conclusion MAP MRI outperformed the conventional DTI in the diagnosis of PD and evaluation of the disease severity.
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Affiliation(s)
- Hongbo Le
- Department of Radiology, The Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai, China.,Department of Radiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Weike Zeng
- Department of Radiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Huihong Zhang
- Food Safety and Health Research Center, School of Public Health, Southern Medical University, Guangzhou, China
| | - Jianing Li
- Department of Radiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Xiaoyan Wu
- Department of Radiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Mingwei Xie
- Department of Radiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Xu Yan
- MR Scientific Marketing, Siemens Healthcare, Shanghai, China
| | - Minxiong Zhou
- College of Medical Imaging, Shanghai Key Laboratory of Molecular Imaging, Shanghai University of Medicine and Health Science, Shanghai, China
| | - Huiting Zhang
- MR Scientific Marketing, Siemens Healthcare, Shanghai, China
| | - Mengzhu Wang
- MR Scientific Marketing, Siemens Healthcare, Shanghai, China
| | - Guobin Hong
- Department of Radiology, The Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai, China
| | - Jun Shen
- Department of Radiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
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Biondetti E, Gaurav R, Yahia-Cherif L, Mangone G, Pyatigorskaya N, Valabrègue R, Ewenczyk C, Hutchison M, François C, Arnulf I, Corvol JC, Vidailhet M, Lehéricy S. Spatiotemporal changes in substantia nigra neuromelanin content in Parkinson’s disease. Brain 2020; 143:2757-2770. [DOI: 10.1093/brain/awaa216] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Revised: 04/11/2020] [Accepted: 05/08/2020] [Indexed: 02/03/2023] Open
Abstract
Abstract
This study aimed to investigate the spatiotemporal changes in neuromelanin-sensitive MRI signal in the substantia nigra and their relation to clinical scores of disease severity in patients with early or progressing Parkinson’s disease and patients with idiopathic rapid eye movement sleep behaviour disorder (iRBD) exempt of Parkinsonian signs compared to healthy control subjects. Longitudinal T1-weighted anatomical and neuromelanin-sensitive MRI was performed in two cohorts, including patients with iRBD, patients with early or progressing Parkinson’s disease, and control subjects. Based on the aligned substantia nigra segmentations using a study-specific brain anatomical template, parametric maps of the probability of a voxel belonging to the substantia nigra were calculated for patients with various degrees of disease severity and controls. For each voxel in the substantia nigra, probability map of controls, correlations between signal-to-noise ratios on neuromelanin-sensitive MRI in patients with iRBD and Parkinson’s disease and clinical scores of motor disability, cognition and mood/behaviour were calculated. Our results showed that in patients, compared to the healthy control subjects, the volume of the substantia nigra was progressively reduced for increasing disease severity. The neuromelanin signal changes appeared to start in the posterolateral motor areas of the substantia nigra and then progressed to more medial areas of this region. The ratio between the volume of the substantia nigra in patients with Parkinson’s disease relative to the controls was best fitted by a mono-exponential decay. Based on this model, the pre-symptomatic phase of the disease started at 5.3 years before disease diagnosis, and 23.1% of the substantia nigra volume was lost at the time of diagnosis, which was in line with previous findings using post-mortem histology of the human substantia nigra and radiotracer studies of the human striatum. Voxel-wise patterns of correlation between neuromelanin-sensitive MRI signal-to-noise ratio and motor, cognitive and mood/behavioural clinical scores were localized in distinct regions of the substantia nigra. This localization reflected the functional organization of the nigrostriatal system observed in histological and electrophysiological studies in non-human primates (motor, cognitive and mood/behavioural domains). In conclusion, neuromelanin-sensitive MRI enabled us to assess voxel-wise modifications of substantia nigra’s morphology in vivo in humans, including healthy controls, patients with iRBD and patients with Parkinson’s disease, and identify their correlation with nigral function across all motor, cognitive and behavioural domains. This insight could help assess disease progression in drug trials of disease modification.
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Affiliation(s)
- Emma Biondetti
- Institut du Cerveau – ICM, INSERM U 1127, CNRS UMR 7225, Sorbonne Université, Paris, France
- ICM, Centre de NeuroImagerie de Recherche – CENIR, Paris, France
- ICM, Team “Movement Investigations and Therapeutics” (MOV’IT), Paris, France
| | - Rahul Gaurav
- Institut du Cerveau – ICM, INSERM U 1127, CNRS UMR 7225, Sorbonne Université, Paris, France
- ICM, Centre de NeuroImagerie de Recherche – CENIR, Paris, France
- ICM, Team “Movement Investigations and Therapeutics” (MOV’IT), Paris, France
| | - Lydia Yahia-Cherif
- Institut du Cerveau – ICM, INSERM U 1127, CNRS UMR 7225, Sorbonne Université, Paris, France
- ICM, Centre de NeuroImagerie de Recherche – CENIR, Paris, France
| | - Graziella Mangone
- Institut du Cerveau – ICM, INSERM U 1127, CNRS UMR 7225, Sorbonne Université, Paris, France
- National Institute of Health and Medical Research - INSERM, Clinical Investigation Centre, Pitié-Salpêtrière Hospital, Paris, France
| | - Nadya Pyatigorskaya
- Institut du Cerveau – ICM, INSERM U 1127, CNRS UMR 7225, Sorbonne Université, Paris, France
- ICM, Team “Movement Investigations and Therapeutics” (MOV’IT), Paris, France
- Department of Neuroradiology, Pitié-Salpêtrière Hospital, Public Assistance - Paris Hospitals (AP-HP), Paris, France
| | - Romain Valabrègue
- Institut du Cerveau – ICM, INSERM U 1127, CNRS UMR 7225, Sorbonne Université, Paris, France
- ICM, Centre de NeuroImagerie de Recherche – CENIR, Paris, France
| | - Claire Ewenczyk
- Institut du Cerveau – ICM, INSERM U 1127, CNRS UMR 7225, Sorbonne Université, Paris, France
- ICM, Team “Movement Investigations and Therapeutics” (MOV’IT), Paris, France
- Department of Neurology, Pitié-Salpêtrière Hospital, Public Assistance - Paris Hospitals (AP-HP), Paris, France
| | | | - Chantal François
- Institut du Cerveau – ICM, INSERM U 1127, CNRS UMR 7225, Sorbonne Université, Paris, France
| | - Isabelle Arnulf
- Institut du Cerveau – ICM, INSERM U 1127, CNRS UMR 7225, Sorbonne Université, Paris, France
- ICM, Team “Movement Investigations and Therapeutics” (MOV’IT), Paris, France
- Sleep Disorders Unit, Pitié-Salpêtrière Hospital, Public Assistance – Paris Hospitals (AP-HP), Paris, France
| | - Jean-Christophe Corvol
- Institut du Cerveau – ICM, INSERM U 1127, CNRS UMR 7225, Sorbonne Université, Paris, France
- National Institute of Health and Medical Research - INSERM, Clinical Investigation Centre, Pitié-Salpêtrière Hospital, Paris, France
- Department of Neurology, Pitié-Salpêtrière Hospital, Public Assistance - Paris Hospitals (AP-HP), Paris, France
| | - Marie Vidailhet
- Institut du Cerveau – ICM, INSERM U 1127, CNRS UMR 7225, Sorbonne Université, Paris, France
- ICM, Team “Movement Investigations and Therapeutics” (MOV’IT), Paris, France
- Department of Neurology, Pitié-Salpêtrière Hospital, Public Assistance - Paris Hospitals (AP-HP), Paris, France
| | - Stéphane Lehéricy
- Institut du Cerveau – ICM, INSERM U 1127, CNRS UMR 7225, Sorbonne Université, Paris, France
- ICM, Centre de NeuroImagerie de Recherche – CENIR, Paris, France
- ICM, Team “Movement Investigations and Therapeutics” (MOV’IT), Paris, France
- Department of Neuroradiology, Pitié-Salpêtrière Hospital, Public Assistance - Paris Hospitals (AP-HP), Paris, France
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91
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Kamiya K, Hori M, Aoki S. NODDI in clinical research. J Neurosci Methods 2020; 346:108908. [PMID: 32814118 DOI: 10.1016/j.jneumeth.2020.108908] [Citation(s) in RCA: 133] [Impact Index Per Article: 33.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Revised: 08/08/2020] [Accepted: 08/09/2020] [Indexed: 12/11/2022]
Abstract
Diffusion MRI (dMRI) has proven to be a useful imaging approach for both clinical diagnosis and research investigating the microstructures of nervous tissues, and it has helped us to better understand the neurophysiological mechanisms of many diseases. Though diffusion tensor imaging (DTI) has long been the default tool to analyze dMRI data in clinical research, acquisition with stronger diffusion weightings beyond the DTI regimen is now possible with modern clinical scanners, potentially enabling even more detailed characterization of tissue microstructures. To take advantage of such data, neurite orientation dispersion and density imaging (NODDI) has been proposed as a way to relate the dMRI signal to tissue features via biophysically inspired modeling. The number of reports demonstrating the potential clinical utility of NODDI is rapidly increasing. At the same time, the pitfalls and limitations of NODDI, and general challenges in microstructure modeling, are becoming increasingly recognized by clinicians. dMRI microstructure modeling is a rapidly evolving field with great promise, where people from different scientific backgrounds, such as physics, medicine, biology, neuroscience, and statistics, are collaborating to build novel tools that contribute to improving human healthcare. Here, we review the applications of NODDI in clinical research and discuss future perspectives for investigations toward the implementation of dMRI microstructure imaging in clinical practice.
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Affiliation(s)
- Kouhei Kamiya
- Department of Radiology, The University of Tokyo, Tokyo, Japan; Department of Radiology, Juntendo University, Tokyo, Japan; Department of Radiology, Toho University, Tokyo, Japan.
| | - Masaaki Hori
- Department of Radiology, Juntendo University, Tokyo, Japan; Department of Radiology, Toho University, Tokyo, Japan
| | - Shigeki Aoki
- Department of Radiology, Juntendo University, Tokyo, Japan
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92
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Arribarat G, De Barros A, Péran P. Modern Brainstem MRI Techniques for the Diagnosis of Parkinson's Disease and Parkinsonisms. Front Neurol 2020; 11:791. [PMID: 32849237 PMCID: PMC7417676 DOI: 10.3389/fneur.2020.00791] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2020] [Accepted: 06/25/2020] [Indexed: 01/22/2023] Open
Abstract
The brainstem is the earliest vulnerable structure in many neurodegenerative diseases like in Multiple System Atrophy (MSA) or Parkinson's disease (PD). Up-to-now, MRI studies have mainly focused on whole-brain data acquisition. Due to its spatial localization, size, and tissue characteristics, brainstem poses particular challenges for MRI. We provide a brief overview on recent advances in brainstem-related MRI markers in Parkinson's disease and Parkinsonism's. Several MRI techniques investigating brainstem, mainly the midbrain, showed to be able to discriminate PD patients from controls or to discriminate PD patients from atypical parkinsonism patients: iron-sensitive MRI, nigrosome imaging, neuromelanin-sensitive MRI, diffusion tensor imaging and advanced diffusion imaging. A standardized multimodal brainstem-dedicated MRI approach at high resolution able to quantify microstructural modification in brainstem nuclei would be a promising tool to detect early changes in parkinsonian syndromes.
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Affiliation(s)
- Germain Arribarat
- ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, Toulouse, France.,Centre de Recherche Cerveau et Cognition (CNRS, Cerco, UMR5549), UPS, Toulouse, France
| | - Amaury De Barros
- ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, Toulouse, France.,Department of Anatomy, Toulouse Faculty of Medicine, Toulouse, France
| | - Patrice Péran
- ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, Toulouse, France
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94
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Patriat R, Niederer J, Kaplan J, Amundsen Huffmaster S, Petrucci M, Eberly L, Harel N, MacKinnon C. Morphological changes in the subthalamic nucleus of people with mild-to-moderate Parkinson's disease: a 7T MRI study. Sci Rep 2020; 10:8785. [PMID: 32472044 PMCID: PMC7260237 DOI: 10.1038/s41598-020-65752-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2020] [Accepted: 04/29/2020] [Indexed: 02/06/2023] Open
Abstract
This project investigated whether structural changes are present in the subthalamic nucleus (STN) of people with mild-to-moderate severity of Parkinson's disease (PD). Within-subject measures of STN volume and fractional anisotropy (FA) were derived from high-resolution 7Tesla magnetic resonance imaging (MRI) for 29 subjects with mild-to-moderate PD (median disease duration = 2.3±1.9 years) and 18 healthy matched controls. Manual segmentation of the STN was performed on 0.4 mm in-plane resolution images. FA maps were generated and FA values were averaged over the left and right STN separately for each subject. Motor sign severity was assessed using the Movement Disorders Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS). Linear effects models showed that STN volume was significantly smaller in the PD subjects compared to controls (p = 0.01). Further, after controlling for differences in STN volumes within or between groups, the PD group had lower FA values in the STN compared to controls (corrected p ≤ 0.008). These findings demonstrate that morphological changes occur in the STN, which likely impact the function of the hyperdirect and indirect pathways of the basal ganglia and movement control.
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Affiliation(s)
- Rémi Patriat
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA.
| | - Jacob Niederer
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Jordan Kaplan
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | | | - Matthew Petrucci
- Department of Neurology, University of Minnesota, Minneapolis, MN, USA
| | - Lynn Eberly
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Noam Harel
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Colum MacKinnon
- Department of Neurology, University of Minnesota, Minneapolis, MN, USA
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95
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Ryman SG, Poston KL. MRI biomarkers of motor and non-motor symptoms in Parkinson's disease. Parkinsonism Relat Disord 2020; 73:85-93. [PMID: 31629653 PMCID: PMC7145760 DOI: 10.1016/j.parkreldis.2019.10.002] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Revised: 10/03/2019] [Accepted: 10/05/2019] [Indexed: 12/19/2022]
Abstract
Parkinson's disease is a heterogeneous disorder with both motor and non-motor symptoms that contribute to functional impairment. To develop effective, disease modifying treatments for these symptoms, biomarkers are necessary to detect neuropathological changes early in the disease course and monitor changes over time. Advances in MRI scan sequences and analytical techniques present numerous promising metrics to detect changes within the nigrostriatal system, implicated in the cardinal motor symptoms of the disease, and detect broader dysfunction involved in the non-motor symptoms, such as cognitive impairment. There is emerging evidence that iron sensitive, neuromelanin sensitive, diffusion sensitive, and resting state functional magnetic imaging measures can capture changes within the nigrostriatal system. Iron, neuromelanin, and diffusion sensitive measures demonstrate high specificity and sensitivity in distinguishing Parkinson's disease relative to controls, with inconsistent results differentiating Parkinson's disease relative to atypical parkinsonian disorders. They may also serve as useful monitoring biomarkers, with each possibly detecting different aspects of the disease course (early nigrosome changes versus broader substantia nigra changes). Investigations of non-motor symptoms, such as cognitive impairment, require careful consideration of the nature of cognitive deficits to characterize regional and network specific impairment. While the early, executive dysfunction observed is consistent with nigrostriatal degeneration, the memory and visuospatial impairments, the harbingers of a dementia process reflect dopaminergic independent dysfunction involving broader regions of the brain.
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Affiliation(s)
- Sephira G Ryman
- Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford University, 300 Pasteur Dr. Room A343. MC-5235, Stanford, CA, 94305, USA.
| | - Kathleen L Poston
- Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford University, 300 Pasteur Dr. Room A343. MC-5235, Stanford, CA, 94305, USA.
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96
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Tsai CC, Lin YC, Ng SH, Chen YL, Cheng JS, Lu CS, Weng YH, Lin SH, Chen PY, Wu YM, Wang JJ. A Method for the Prediction of Clinical Outcome Using Diffusion Magnetic Resonance Imaging: Application on Parkinson's Disease. J Clin Med 2020; 9:jcm9030647. [PMID: 32121190 PMCID: PMC7141247 DOI: 10.3390/jcm9030647] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2020] [Revised: 02/10/2020] [Accepted: 02/18/2020] [Indexed: 01/06/2023] Open
Abstract
Robust early prediction of clinical outcomes in Parkinson's disease (PD) is paramount for implementing appropriate management interventions. We propose a method that uses the baseline MRI, measuring diffusion parameters from multiple parcellated brain regions, to predict the 2-year clinical outcome in Parkinson's disease. Diffusion tensor imaging was obtained from 82 patients (males/females = 45/37, mean age: 60.9 ± 7.3 years, baseline and after 23.7 ± 0.7 months) using a 3T MR scanner, which was normalized and parcellated according to the Automated Anatomical Labelling template. All patients were diagnosed with probable Parkinson's disease by the National Institute of Neurological Disorders and Stroke criteria. Clinical outcome was graded using disease severity (Unified Parkinson's Disease Rating Scale and Modified Hoehn and Yahr staging), drug administration (levodopa equivalent daily dose), and quality of life (39-item PD Questionnaire). Selection and regularization of diffusion parameters, the mean diffusivity and fractional anisotropy, were performed using least absolute shrinkage and selection operator (LASSO) between baseline diffusion index and clinical outcome over 2 years. Identified features were entered into a stepwise multivariate regression model, followed by a leave-one-out/5-fold cross validation and additional blind validation using an independent dataset. The predicted Unified Parkinson's Disease Rating Scale for each individual was consistent with the observed values at blind validation (adjusted R2 0.76) by using 13 features, such as mean diffusivity in lingual, nodule lobule of cerebellum vermis and fractional anisotropy in rolandic operculum, and quadrangular lobule of cerebellum. We conclude that baseline diffusion MRI is potentially capable of predicting 2-year clinical outcomes in patients with Parkinson's disease on an individual basis.
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Affiliation(s)
- Chih-Chien Tsai
- Healthy Aging Research Center, Chang Gung University, Taoyuan 33302, Taiwan;
| | - Yu-Chun Lin
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital, Linkou, Taoyuan 33375, Taiwan; (Y.-C.L.); (S.-H.N.); (Y.-L.C.); (Y.-M.W.)
- Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan 33302, Taiwan; (S.-H.L.); (P.-Y.C.)
| | - Shu-Hang Ng
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital, Linkou, Taoyuan 33375, Taiwan; (Y.-C.L.); (S.-H.N.); (Y.-L.C.); (Y.-M.W.)
- Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan 33302, Taiwan; (S.-H.L.); (P.-Y.C.)
| | - Yao-Liang Chen
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital, Linkou, Taoyuan 33375, Taiwan; (Y.-C.L.); (S.-H.N.); (Y.-L.C.); (Y.-M.W.)
- Department of Diagnostic Radiology, Chang Gung Memorial Hospital, Keelung City 20401, Taiwan
| | - Jur-Shan Cheng
- Clinical Informatics and Medical Statistics Research Center, College of Medicine, Chang Gung University, Taoyuan 33302, Taiwan;
- Department of Emergency Medicine, Chang Gung Memorial Hospital, Keelung City 20401, Taiwan
| | - Chin-Song Lu
- Professor Lu Neurological Clinic, Taoyuan 33375, Taiwan;
- Division of Movement Disorders, Department of Neurology, Chang Gung Memorial Hospital, Linkou, Taoyuan 33375, Taiwan;
- Neuroscience Research Center, Chang Gung Memorial Hospital, Linkou, Taoyuan 33375, Taiwan
| | - Yi-Hsin Weng
- Division of Movement Disorders, Department of Neurology, Chang Gung Memorial Hospital, Linkou, Taoyuan 33375, Taiwan;
- Neuroscience Research Center, Chang Gung Memorial Hospital, Linkou, Taoyuan 33375, Taiwan
- School of Medicine, Chang Gung University, Taoyuan 33302, Taiwan
| | - Sung-Han Lin
- Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan 33302, Taiwan; (S.-H.L.); (P.-Y.C.)
| | - Po-Yuan Chen
- Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan 33302, Taiwan; (S.-H.L.); (P.-Y.C.)
| | - Yi-Ming Wu
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital, Linkou, Taoyuan 33375, Taiwan; (Y.-C.L.); (S.-H.N.); (Y.-L.C.); (Y.-M.W.)
- Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan 33302, Taiwan; (S.-H.L.); (P.-Y.C.)
| | - Jiun-Jie Wang
- Healthy Aging Research Center, Chang Gung University, Taoyuan 33302, Taiwan;
- Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan 33302, Taiwan; (S.-H.L.); (P.-Y.C.)
- Department of Diagnostic Radiology, Chang Gung Memorial Hospital, Keelung City 20401, Taiwan
- Medical Imaging Research Center, Institute for Radiological Research, Chang Gung University/Chang Gung Memorial Hospital, Linkou 33375, Taoyuan, Taiwan
- Correspondence: ; Tel.: +886-3-211-8800 (ext. 5391); Fax: +886-3-397-1936
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Abstract
IMPORTANCE Parkinson disease is the most common form of parkinsonism, a group of neurological disorders with Parkinson disease-like movement problems such as rigidity, slowness, and tremor. More than 6 million individuals worldwide have Parkinson disease. OBSERVATIONS Diagnosis of Parkinson disease is based on history and examination. History can include prodromal features (eg, rapid eye movement sleep behavior disorder, hyposmia, constipation), characteristic movement difficulty (eg, tremor, stiffness, slowness), and psychological or cognitive problems (eg, cognitive decline, depression, anxiety). Examination typically demonstrates bradykinesia with tremor, rigidity, or both. Dopamine transporter single-photon emission computed tomography can improve the accuracy of diagnosis when the presence of parkinsonism is uncertain. Parkinson disease has multiple disease variants with different prognoses. Individuals with a diffuse malignant subtype (9%-16% of individuals with Parkinson disease) have prominent early motor and nonmotor symptoms, poor response to medication, and faster disease progression. Individuals with mild motor-predominant Parkinson disease (49%-53% of individuals with Parkinson disease) have mild symptoms, a good response to dopaminergic medications (eg, carbidopa-levodopa, dopamine agonists), and slower disease progression. Other individuals have an intermediate subtype. For all patients with Parkinson disease, treatment is symptomatic, focused on improvement in motor (eg, tremor, rigidity, bradykinesia) and nonmotor (eg, constipation, cognition, mood, sleep) signs and symptoms. No disease-modifying pharmacologic treatments are available. Dopamine-based therapies typically help initial motor symptoms. Nonmotor symptoms require nondopaminergic approaches (eg, selective serotonin reuptake inhibitors for psychiatric symptoms, cholinesterase inhibitors for cognition). Rehabilitative therapy and exercise complement pharmacologic treatments. Individuals experiencing complications, such as worsening symptoms and functional impairment when a medication dose wears off ("off periods"), medication-resistant tremor, and dyskinesias, benefit from advanced treatments such as therapy with levodopa-carbidopa enteral suspension or deep brain stimulation. Palliative care is part of Parkinson disease management. CONCLUSIONS AND RELEVANCE Parkinson disease is a heterogeneous disease with rapidly and slowly progressive forms. Treatment involves pharmacologic approaches (typically with levodopa preparations prescribed with or without other medications) and nonpharmacologic approaches (such as exercise and physical, occupational, and speech therapies). Approaches such as deep brain stimulation and treatment with levodopa-carbidopa enteral suspension can help individuals with medication-resistant tremor, worsening symptoms when the medication wears off, and dyskinesias.
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Affiliation(s)
- Melissa J Armstrong
- Department of Neurology, University of Florida College of Medicine, Gainesville
- Fixel Institute for Neurologic Diseases, University of Florida, Gainesville
| | - Michael S Okun
- Department of Neurology, University of Florida College of Medicine, Gainesville
- Fixel Institute for Neurologic Diseases, University of Florida, Gainesville
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98
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Abstract
Parkinson's disease (PD) is a chronic, debilitating neurodegenerative disorder characterized clinically by a variety of progressive motor and nonmotor symptoms. Currently, there is a dearth of diagnostic tools available to predict, diagnose or mitigate disease risk or progression, leading to a challenging dilemma within the healthcare management system. The search for a reliable biomarker for PD that reflects underlying pathology is a high priority in PD research. Currently, there is no reliable single biomarker predictive of risk for motor and cognitive decline, and there have been few longitudinal studies of temporal progression. A combination of multiple biomarkers might facilitate earlier diagnosis and more accurate prognosis in PD. In this review, we focus on the recent developments of serial biomarkers for PD from a variety of clinical, biochemical, genetic and neuroimaging perspectives.
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Affiliation(s)
- Anastasia Bougea
- Neurochemistry Laboratory, 1st Department of Neurology and Movement Disorders, Medical School, Aeginition Hospital, National and Kapodistrian University of Athens, Athens, Greece; Neuroscience Laboratory, Center for Basic Research, Biomedical Research Foundation of the Academy of Athens, Athens, Greece.
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99
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Diffusion magnetic resonance imaging-derived free water detects neurodegenerative pattern induced by interferon-γ. Brain Struct Funct 2020; 225:427-439. [PMID: 31894407 DOI: 10.1007/s00429-019-02017-1] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2019] [Accepted: 12/17/2019] [Indexed: 12/18/2022]
Abstract
Imaging biomarkers for immune activation may be valuable for early-stage detection, therapeutic testing, and research on neurodegenerative conditions. In the present study, we determined whether diffusion magnetic resonance imaging-derived free water signal is a sensitive marker for neuroinflammatory effects of interferon-gamma (Ifn-γ). Neonatal wild-type mice were injected in the cerebral ventricles with recombinant adeno-associated viruses expressing the inflammatory cytokine Ifn-γ. Groups of mice expressing Ifn-γ and age-matched controls were imaged at 1, 5 and 8 months. Mice deficient in Ifngr1-/- and Stat1-/- were scanned at 5 months as controls for the signaling cascades activated by Ifn-γ. The results indicate that Ifn-γ affected fractional anisotropy (FA), mean diffusivity (MD), and free water (FW) in white matter structures, midline cortical areas, and medial thalamic areas. In these structures, FA and MD decreased progressively from 1 to 8 months of age, while FW increased significantly. The observed reductions in FA and MD and increased FW with elevated brain Ifn-γ was not observed in Ifngr1-/- or Stat1-/- mice. These results suggest that the observed microstructure changes involve the Ifn-gr1 and Stat1 signaling. Interestingly, increases in FW were observed in midbrain of Ifngr1-/- mice, which suggests alternative Ifn-γ signaling in midbrain. Although initial evidence is offered in relation to the sensitivity of the FW signal to neurodegenerative and/or inflammatory patterns specific to Ifn-γ, further research is needed to determine applicability and specificity across animal models of neuroinflammatory and degenerative disorders.
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Kamagata K, Andica C, Hatano T, Ogawa T, Takeshige-Amano H, Ogaki K, Akashi T, Hagiwara A, Fujita S, Aoki S. Advanced diffusion magnetic resonance imaging in patients with Alzheimer's and Parkinson's diseases. Neural Regen Res 2020; 15:1590-1600. [PMID: 32209758 PMCID: PMC7437577 DOI: 10.4103/1673-5374.276326] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
The prevalence of neurodegenerative diseases is increasing as human longevity increases. The objective biomarkers that enable the staging and early diagnosis of neurodegenerative diseases are eagerly anticipated. It has recently become possible to determine pathological changes in the brain without autopsy with the advancement of diffusion magnetic resonance imaging techniques. Diffusion magnetic resonance imaging is a robust tool used to evaluate brain microstructural complexity and integrity, axonal order, density, and myelination via the micron-scale displacement of water molecules diffusing in tissues. Diffusion tensor imaging, a type of diffusion magnetic resonance imaging technique is widely utilized in clinical and research settings; however, it has several limitations. To overcome these limitations, cutting-edge diffusion magnetic resonance imaging techniques, such as diffusional kurtosis imaging, neurite orientation dispersion and density imaging, and free water imaging, have been recently proposed and applied to evaluate the pathology of neurodegenerative diseases. This review focused on the main applications, findings, and future directions of advanced diffusion magnetic resonance imaging techniques in patients with Alzheimer’s and Parkinson’s diseases, the first and second most common neurodegenerative diseases, respectively.
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Affiliation(s)
- Koji Kamagata
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Christina Andica
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Taku Hatano
- Department of Neurology, Juntendo University School of Medicine, Tokyo, Japan
| | - Takashi Ogawa
- Department of Neurology, Juntendo University School of Medicine, Tokyo, Japan
| | | | - Kotaro Ogaki
- Department of Neurology, Juntendo University School of Medicine, Tokyo, Japan
| | - Toshiaki Akashi
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Akifumi Hagiwara
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Shohei Fujita
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Shigeki Aoki
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
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