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Porcu M, Cocco L, Marrosu F, Cau R, Puig J, Suri JS, Saba L. Hippocampus and olfactory impairment in Parkinson disease: a comparative exploratory combined volumetric/functional MRI study. Neuroradiology 2024:10.1007/s00234-024-03436-6. [PMID: 39046517 DOI: 10.1007/s00234-024-03436-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2024] [Accepted: 07/18/2024] [Indexed: 07/25/2024]
Abstract
INTRODUCTION Patients with Parkinson's Disease (PD) commonly experience Olfactory Dysfunction (OD). Our exploratory study examined hippocampal volumetric and resting-state functional magnetic resonance imaging (rs-fMRI) variations in a Healthy Control (HC) group versus a cognitively normal PD group, further categorized into PD with No/Mild Hyposmia (PD-N/MH) and PD with Severe Hyposmia (PD-SH). METHODS We calculated participants' relative Total Hippocampal Volume (rTHV) and performed Spearman's partial correlations, controlled for age and gender, to examine the correlation between rTHV and olfactory performance assessed by the Odor Stick Identification Test for the Japanese (OSIT-J) score. Mann-Whitney U tests assessed rTHV differences across groups and subgroups, rejecting the null hypothesis for p < 0.05. Furthermore, a seed-based rs-fMRI analysis compared hippocampal connectivity differences using a one-way ANCOVA covariate model with controls for age and gender. RESULTS Spearman's partial correlations indicated a moderate positive correlation between rTHV and OSIT-J in the whole study population (ρ = 0.406; p = 0.007), PD group (ρ = 0.493; p = 0.008), and PD-N/MH subgroup (ρ = 0.617; p = 0.025). Mann-Whitney U tests demonstrated lower rTHV in PD-SH subgroup compared to both HC group (p = 0.013) and PD-N/MH subgroup (p = 0.029). Seed-to-voxel rsfMRI analysis revealed reduced hippocampal connectivity in PD-SH subjects compared to HC subjects with a single cluster of voxels. CONCLUSIONS Although the design of the study do not allow to make firm conclusions, it is reasonable to speculate that the progressive involvement of the hippocampus in PD patients is associated with the progression of OD.
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Affiliation(s)
- Michele Porcu
- Department of Radiology, AOU Cagliari, University of Cagliari, Cagliari, Italy.
- Department of Medical Imaging, Azienda Ospedaliera Universitaria di Cagliari, S.S. 554, km 4.500, CAP 09042, Monserrato (Cagliari), Italy.
| | - Luigi Cocco
- Department of Radiology, AOU Cagliari, University of Cagliari, Cagliari, Italy
| | - Francesco Marrosu
- Department of Radiology, AOU Cagliari, University of Cagliari, Cagliari, Italy
| | - Riccardo Cau
- Department of Radiology, AOU Cagliari, University of Cagliari, Cagliari, Italy
| | - Josep Puig
- Department of Radiology (IDI), Hospital Universitari de Girona Dr Josep Trueta, Girona, Spain
| | - Jasjit S Suri
- Stroke Monitoring and Diagnostic Division, AtheroPoint™, Roseville, CA, USA
| | - Luca Saba
- Department of Radiology, AOU Cagliari, University of Cagliari, Cagliari, Italy
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2
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Tax CM, Genc S, MacIver CL, Nilsson M, Wardle M, Szczepankiewicz F, Jones DK, Peall KJ. Ultra-strong diffusion-weighted MRI reveals cerebellar grey matter abnormalities in movement disorders. Neuroimage Clin 2023; 38:103419. [PMID: 37192563 PMCID: PMC10199248 DOI: 10.1016/j.nicl.2023.103419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Revised: 02/28/2023] [Accepted: 04/23/2023] [Indexed: 05/18/2023]
Abstract
Structural brain MRI has proven invaluable in understanding movement disorder pathophysiology. However, most work has focused on grey/white matter volumetric (macrostructural) and white matter microstructural effects, limiting understanding of frequently implicated grey matter microstructural differences. Using ultra-strong spherical tensor encoding diffusion-weighted MRI, a persistent MRI signal was seen in healthy cerebellar grey matter even at high diffusion-weightings (b ≥ 10,000 s/mm2). Quantifying the proportion of this signal (denoted fs), previously ascertained to originate from inside small spherical spaces, provides a potential proxy for cell body density. In this work, this approach was applied for the first time to a clinical cohort, including patients with diagnosed movement disorders in which the cerebellum has been implicated in symptom pathophysiology. Five control participants (control group 1, median age 24.5 years (20-39 years), imaged at two timepoints, demonstrated consistency in measurement of all three measures - MD (Mean Diffusivity) fs, and Ds (dot diffusivity)- with intraclass correlation coefficients (ICC) of 0.98, 0.86 and 0.76, respectively. Comparison with an older control group (control group 2 (n = 5), median age 51 years (43-58 years)) found no significant differences, neither with morphometric nor microstructural (MD (p = 0.36), fs (p = 0.17) and Ds (p = 0.22)) measures. The movement disorder cohort (Parkinson's Disease, n = 5, dystonia, n = 5. Spinocerebellar Ataxia 6, n = 5) when compared to the age-matched control cohort (Control Group 2) identified significantly lower MD (p < 0.0001 and p < 0.0001) and higher fs values (p < 0.0001 and p < 0.0001) in SCA6 and dystonia cohorts respectively. Lobar division of the cerebellum found these same differences in the superior and inferior posterior lobes, while no differences were seen in either the anterior lobes or with Ds measurements. In contrast to more conventional measures from diffusion tensor imaging, this framework provides enhanced specificity to differences in restricted spherical spaces in grey matter (including small cells) by eliminating signals from cerebrospinal fluid and axons. In the context of human and animal histopathology studies, these findings potentially implicate the cerebellar Purkinje and granule cells as contributors to the observed signal differences, with both cell types having been implicated in several neurological disorders through both postmortem and animal model studies. This novel microstructural imaging approach shows promise for improving movement disorder diagnosis, prognosis, and treatment.
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Affiliation(s)
- Chantal M.W. Tax
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Physics and Astronomy, Cardiff University, Cardiff, UK
- University Medical Center Utrecht, Utrecht, The Netherlands
| | - Sila Genc
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
- Neuroscience Advanced Clinical Imaging Service (NACIS), Department of Neurosurgery, The Royal Children's Hospital, Parkville, Victoria, Australia
| | - Claire L MacIver
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
- Neuroscience and Mental Health Research Institute, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Markus Nilsson
- Diagnostic Radiology, Clinical Sciences Lund, Lund University, Lund, Sweden
| | - Mark Wardle
- Cardiff and Vale University Health Board, University Hospital of Wales Cardiff, Heath Park, Cardiff, UK
| | - Filip Szczepankiewicz
- Diagnostic Radiology, Clinical Sciences Lund, Lund University, Lund, Sweden
- Medical Radiation Physics, Clinical Sciences Lund, Lund University, Lund, Sweden
| | - Derek K. Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
| | - Kathryn J. Peall
- Neuroscience and Mental Health Research Institute, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
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Longitudinal corpus callosum microstructural decline in early-stage Parkinson’s disease in association with akinetic-rigid symptom severity. NPJ Parkinsons Dis 2022; 8:108. [PMID: 36038586 PMCID: PMC9424284 DOI: 10.1038/s41531-022-00372-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Accepted: 08/02/2022] [Indexed: 12/26/2022] Open
Abstract
Previous diffusion tensor imaging (DTI) studies of Parkinson’s disease (PD) show reduced microstructural integrity of the corpus callosum (CC) relative to controls, although the characteristics of such callosal degradation remain poorly understood. Here, we utilized a longitudinal approach to identify microstructural decline in the entire volume of the CC and its functional subdivisions over 2 years and related the callosal changes to motor symptoms in early-stage PD. The study sample included 61 PD subjects (N = 61, aged 45–82, 38 M & 23 F, H&Y ≤ 2) from the Parkinson’s Progressive Markers Initiative database (PPMI). Whole-brain voxel-wise results revealed significant fractional anisotropy (FA) and mean diffusivity (MD) changes in the CC, especially in the genu and splenium. Using individually drawn CC regions of interest (ROI), our analysis further revealed that almost all subdivisions of the CC show significant decline in FA to certain extents over the two-year timeframe. Additionally, FA seemed lower in the right hemisphere of the CC at both time-points, and callosal FA decline was associated with FA and MD decline in widespread cortical and subcortical areas. Notably, multiple regression analysis revealed that across-subject akinetic-rigid severity was negatively associated with callosal FA at baseline and 24 months follow-up, and the effect was strongest in the anterior portion of the CC. These results suggest that callosal microstructure alterations in the anterior CC may serve as a viable biomarker for akinetic-rigid symptomology and disease progression, even in early PD.
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Haghshomar M, Shobeiri P, Seyedi SA, Abbasi-Feijani F, Poopak A, Sotoudeh H, Kamali A, Aarabi MH. Cerebellar Microstructural Abnormalities in Parkinson's Disease: a Systematic Review of Diffusion Tensor Imaging Studies. CEREBELLUM (LONDON, ENGLAND) 2022; 21:545-571. [PMID: 35001330 DOI: 10.1007/s12311-021-01355-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 12/01/2021] [Indexed: 06/14/2023]
Abstract
Diffusion tensor imaging (DTI) is now having a strong momentum in research to evaluate the neural fibers of the CNS. This technique can study white matter (WM) microstructure in neurodegenerative disorders, including Parkinson's disease (PD). Previous neuroimaging studies have suggested cerebellar involvement in the pathogenesis of PD, and these cerebellum alterations can correlate with PD symptoms and stages. Using the PRISMA 2020 framework, PubMed and EMBASE were searched to retrieve relevant articles. Our search revealed 472 articles. After screening titles and abstracts, and full-text review, and implementing the inclusion criteria, 68 papers were selected for synthesis. Reviewing the selected studies revealed that the patterns of reduction in cerebellum WM integrity, assessed by fractional anisotropy, mean diffusivity, radial diffusivity, and axial diffusivity measures can differ symptoms and stages of PD. Cerebellar diffusion tensor imaging (DTI) changes in PD patients with "postural instability and gait difficulty" are significantly different from "tremor dominant" PD patients. Freezing of the gate is strongly related to cerebellar involvement depicted by DTI. The "reduced cognition," "visual disturbances," "sleep disorders," "depression," and "olfactory dysfunction" are not related to cerebellum microstructural changes on DTI, while "impulsive-compulsive behavior" can be linked to cerebellar WM alteration. Finally, higher PD stages and longer disease duration are associated with cerebellum white matter alteration depicted by DTI. Depiction of cerebellar white matter involvement in PD is feasible by DTI. There is an association with disease duration and severity and several clinical presentations with DTI findings. This clinical-imaging association may eventually improve disease management.
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Affiliation(s)
- Maryam Haghshomar
- Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran
- NeuroImaging Network (NIN), Universal Scientific Education and Research Network (USERN), Tehran, Iran
| | - Parnian Shobeiri
- Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
- NeuroImaging Network (NIN), Universal Scientific Education and Research Network (USERN), Tehran, Iran.
- Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, No. 10, Al-e-Ahmad and Chamran Highway intersection, Tehran, 1411713137, Iran.
| | | | | | - Amirhossein Poopak
- Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Houman Sotoudeh
- Department of Radiology and Neurology, University of Alabama at Birmingham (UAB), Birmingham, AL, USA
| | - Arash Kamali
- Department of Diagnostic and Interventional Radiology, University of Texas McGovern Medical School, Houston, TX, USA
| | - Mohammad Hadi Aarabi
- Department of Neuroscience (DNS), Padova Neuroscience Center-PNC, University of Padova, Padua, Italy
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5
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Tsai CC, Chen YL, Lu CS, Cheng JS, Weng YH, Lin SH, Wu YM, Wang JJ. Diffusion Tensor Imaging for the differential diagnosis of Parkinsonism by machine learning. Biomed J 2022; 46:100541. [DOI: 10.1016/j.bj.2022.05.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Revised: 04/28/2022] [Accepted: 05/27/2022] [Indexed: 11/02/2022] Open
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6
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A Review of Diagnostic Imaging Approaches to Assessing Parkinson's Disease. BRAIN DISORDERS 2022. [DOI: 10.1016/j.dscb.2022.100037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
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7
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Patel ZM, Holbrook EH, Turner JH, Adappa ND, Albers MW, Altundag A, Appenzeller S, Costanzo RM, Croy I, Davis GE, Dehgani-Mobaraki P, Doty RL, Duffy VB, Goldstein BJ, Gudis DA, Haehner A, Higgins TS, Hopkins C, Huart C, Hummel T, Jitaroon K, Kern RC, Khanwalkar AR, Kobayashi M, Kondo K, Lane AP, Lechner M, Leopold DA, Levy JM, Marmura MJ, Mclelland L, Miwa T, Moberg PJ, Mueller CA, Nigwekar SU, O'Brien EK, Paunescu TG, Pellegrino R, Philpott C, Pinto JM, Reiter ER, Roalf DR, Rowan NR, Schlosser RJ, Schwob J, Seiden AM, Smith TL, Soler ZM, Sowerby L, Tan BK, Thamboo A, Wrobel B, Yan CH. International consensus statement on allergy and rhinology: Olfaction. Int Forum Allergy Rhinol 2022; 12:327-680. [PMID: 35373533 DOI: 10.1002/alr.22929] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 01/01/2021] [Accepted: 11/19/2021] [Indexed: 12/11/2022]
Abstract
BACKGROUND The literature regarding clinical olfaction, olfactory loss, and olfactory dysfunction has expanded rapidly over the past two decades, with an exponential rise in the past year. There is substantial variability in the quality of this literature and a need to consolidate and critically review the evidence. It is with that aim that we have gathered experts from around the world to produce this International Consensus on Allergy and Rhinology: Olfaction (ICAR:O). METHODS Using previously described methodology, specific topics were developed relating to olfaction. Each topic was assigned a literature review, evidence-based review, or evidence-based review with recommendations format as dictated by available evidence and scope within the ICAR:O document. Following iterative reviews of each topic, the ICAR:O document was integrated and reviewed by all authors for final consensus. RESULTS The ICAR:O document reviews nearly 100 separate topics within the realm of olfaction, including diagnosis, epidemiology, disease burden, diagnosis, testing, etiology, treatment, and associated pathologies. CONCLUSION This critical review of the existing clinical olfaction literature provides much needed insight and clarity into the evaluation, diagnosis, and treatment of patients with olfactory dysfunction, while also clearly delineating gaps in our knowledge and evidence base that we should investigate further.
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Affiliation(s)
- Zara M Patel
- Otolaryngology, Stanford University School of Medicine, Stanford, California, USA
| | - Eric H Holbrook
- Otolaryngology, Massachusetts Eye and Ear Infirmary, Boston, Massachusetts, USA
| | - Justin H Turner
- Otolaryngology, Vanderbilt School of Medicine, Nashville, Tennessee, USA
| | - Nithin D Adappa
- Otolaryngology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Mark W Albers
- Neurology, Harvard Medical School, Boston, Massachusetts, USA
| | - Aytug Altundag
- Otolaryngology, Biruni University School of Medicine, İstanbul, Turkey
| | - Simone Appenzeller
- Rheumatology, School of Medical Sciences, University of Campinas, São Paulo, Brazil
| | - Richard M Costanzo
- Physiology and Biophysics and Otolaryngology, Virginia Commonwealth University School of Medicine, Richmond, Virginia, USA
| | - Ilona Croy
- Psychology and Psychosomatic Medicine, TU Dresden, Dresden, Germany
| | - Greg E Davis
- Otolaryngology, Proliance Surgeons, Seattle and Puyallup, Washington, USA
| | - Puya Dehgani-Mobaraki
- Associazione Naso Sano, Umbria Regional Registry of Volunteer Activities, Corciano, Italy
| | - Richard L Doty
- Smell and Taste Center, Otolaryngology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Valerie B Duffy
- Allied Health Sciences, University of Connecticut, Storrs, Connecticut, USA
| | | | - David A Gudis
- Otolaryngology, Columbia University Irving Medical Center, New York, USA
| | - Antje Haehner
- Smell and Taste, Otolaryngology, TU Dresden, Dresden, Germany
| | - Thomas S Higgins
- Otolaryngology, University of Louisville School of Medicine, Louisville, Kentucky, USA
| | - Claire Hopkins
- Otolaryngology, Guy's and St. Thomas' Hospitals, London Bridge Hospital, London, UK
| | - Caroline Huart
- Otorhinolaryngology, Cliniques universitaires Saint-Luc, Institute of Neuroscience, Université catholgique de Louvain, Brussels, Belgium
| | - Thomas Hummel
- Smell and Taste, Otolaryngology, TU Dresden, Dresden, Germany
| | | | - Robert C Kern
- Otolaryngology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Ashoke R Khanwalkar
- Otolaryngology, Stanford University School of Medicine, Stanford, California, USA
| | - Masayoshi Kobayashi
- Otorhinolaryngology-Head and Neck Surgery, Mie University Graduate School of Medicine, Mie, Japan
| | - Kenji Kondo
- Otolaryngology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Andrew P Lane
- Otolaryngology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Matt Lechner
- Otolaryngology, Barts Health and University College London, London, UK
| | - Donald A Leopold
- Otolaryngology, University of Vermont Medical Center, Burlington, Vermont, USA
| | - Joshua M Levy
- Otolaryngology, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Michael J Marmura
- Neurology Thomas Jefferson University School of Medicine, Philadelphia, Pennsylvania, USA
| | - Lisha Mclelland
- Otolaryngology, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
| | - Takaki Miwa
- Otolaryngology, Kanazawa Medical University, Ishikawa, Japan
| | - Paul J Moberg
- Psychiatry, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, USA
| | | | - Sagar U Nigwekar
- Division of Nephrology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Erin K O'Brien
- Otolaryngology, Mayo Clinic Rochester, Rochester, Minnesota, USA
| | - Teodor G Paunescu
- Division of Nephrology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | | | - Carl Philpott
- Otolaryngology, University of East Anglia, Norwich, UK
| | - Jayant M Pinto
- Otolaryngology, University of Chicago, Chicago, Illinois, USA
| | - Evan R Reiter
- Otolaryngology, Virginia Commonwealth University School of Medicine, Richmond, Virginia, USA
| | - David R Roalf
- Psychiatry, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, USA
| | - Nicholas R Rowan
- Otolaryngology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Rodney J Schlosser
- Otolaryngology, Medical University of South Carolina, Mt Pleasant, South Carolina, USA
| | - James Schwob
- Biomedical Sciences, Tufts University School of Medicine, Boston, Massachusetts, USA
| | - Allen M Seiden
- Otolaryngology, University of Cincinnati School of Medicine, Cincinnati, Ohio, USA
| | - Timothy L Smith
- Otolaryngology, Oregon Health and Sciences University, Portland, Oregon, USA
| | - Zachary M Soler
- Otolaryngology, Medical University of South Carolina, Mt Pleasant, South Carolina, USA
| | - Leigh Sowerby
- Otolaryngology, University of Western Ontario, London, Ontario, Canada
| | - Bruce K Tan
- Otolaryngology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Andrew Thamboo
- Otolaryngology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Bozena Wrobel
- Otolaryngology, Keck School of Medicine, USC, Los Angeles, California, USA
| | - Carol H Yan
- Otolaryngology, School of Medicine, UCSD, La Jolla, California, USA
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Lipp I, Mole JP, Subramanian L, Linden DEJ, Metzler-Baddeley C. Investigating the Anatomy and Microstructure of the Dentato-rubro-thalamic and Subthalamo-ponto-cerebellar Tracts in Parkinson's Disease. Front Neurol 2022; 13:793693. [PMID: 35401393 PMCID: PMC8987292 DOI: 10.3389/fneur.2022.793693] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Accepted: 02/07/2022] [Indexed: 11/17/2022] Open
Abstract
Cerebellar-thalamic connections play a central role in deep brain stimulation-based treatment of tremor syndromes. Here, we used diffusion Magnetic Resonance Imaging (MRI) tractography to delineate the main cerebellar peduncles as well as two main white matter tracts that connect the cerebellum with the thalamus, the dentato-rubro-thalamic tract (DRTT) and the subthalamo-ponto-cerebellar tract (SPCT). We first developed a reconstruction protocol in young healthy adults with high-resolution diffusion imaging data and then demonstrate feasibility of transferring this protocol to clinical studies using standard diffusion MRI data from a cohort of patients with Parkinson's disease (PD) and their matched healthy controls. The tracts obtained closely corresponded to the previously described anatomical pathways and features of the DRTT and the SPCT. Second, we investigated the microstructure of these tracts with fractional anisotropy (FA), radial diffusivity (RD), and hindrance modulated orientational anisotropy (HMOA) in patients with PD and healthy controls. By reducing dimensionality of both the microstructural metrics and the investigated cerebellar and cerebellar-thalamic tracts using principal component analyses, we found global differences between patients with PD and controls, suggestive of higher fractional anisotropy, lower radial diffusivity, and higher hindrance modulated orientational anisotropy in patients. However, separate analyses for each of the tracts did not yield any significant differences. Our findings contribute to the characterization of the distinct anatomical connections between the cerebellum and the diencephalon. Microstructural differences between patients and controls in the cerebellar pathways suggest involvement of these structures in PD, complementing previous functional and diffusion imaging studies.
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Affiliation(s)
- Ilona Lipp
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom
- Division of Psychological Medicine and Clinical Neurosciences (DPMCN), School of Medicine, Cardiff University, Cardiff, United Kingdom
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Jilu Princy Mole
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom
- Division of Psychological Medicine and Clinical Neurosciences (DPMCN), School of Medicine, Cardiff University, Cardiff, United Kingdom
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Leena Subramanian
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom
- Division of Psychological Medicine and Clinical Neurosciences (DPMCN), School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - David E. J. Linden
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom
- Division of Psychological Medicine and Clinical Neurosciences (DPMCN), School of Medicine, Cardiff University, Cardiff, United Kingdom
- Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, United Kingdom
- School for Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, Netherlands
| | - Claudia Metzler-Baddeley
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom
- Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, United Kingdom
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9
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Wei X, Luo C, Li Q, Hu N, Xiao Y, Liu N, Lui S, Gong Q. White Matter Abnormalities in Patients With Parkinson's Disease: A Meta-Analysis of Diffusion Tensor Imaging Using Tract-Based Spatial Statistics. Front Aging Neurosci 2021; 12:610962. [PMID: 33584244 PMCID: PMC7876070 DOI: 10.3389/fnagi.2020.610962] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Accepted: 12/28/2020] [Indexed: 02/05/2023] Open
Abstract
Background: Tract-based spatial statistics (TBSS) studies based on diffusion tensor imaging (DTI) have revealed extensive abnormalities in white matter (WM) fibers of Parkinson's disease (PD); however, the results were inconsistent. Therefore, a meta-analytical approach was used in this study to find the most prominent and replicable WM abnormalities of PD. Methods: Online databases were systematically searched for all TBSS studies comparing fractional anisotropy (FA) between patients with PD and controls. Subsequently, we performed the meta-analysis using a coordinate-based meta-analytic software called seed-based d mapping. Meanwhile, meta-regression was performed to explore the potential correlation between the alteration of FA and the clinical characteristics of PD. Results: Out of a total of 1,701 studies that were identified, 23 studies were included. Thirty datasets, including 915 patients (543 men) with PD and 836 healthy controls (449 men), were included in the current study. FA reduction was identified in the body of the corpus callosum (CC; 245 voxels; z = -1.739; p < 0.001) and the left inferior fronto-occipital fasciculus (IFOF) 118 voxels; z = -1.182; p < 0.001). Both CC and IFOF maintained significance in the sensitivity analysis. No increase in FA was identified, but the percentage of male patients with PD was positively associated with the value of FA in the body of the CC. Conclusions: Although some limitations exist, DTI is regarded as a valid way to identify the pathophysiology of PD. It could be more beneficial to integrate DTI parameters with other MRI techniques to explore brain degeneration in PD.
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Affiliation(s)
- Xia Wei
- Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, Chengdu, China.,Psychoradiology Research Unit of the Chinese Academy of Medical Sciences (2018RU011), West China Hospital of Sichuan University, Chengdu, China.,Department of Radiology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
| | - Chunyan Luo
- Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, Chengdu, China.,Psychoradiology Research Unit of the Chinese Academy of Medical Sciences (2018RU011), West China Hospital of Sichuan University, Chengdu, China.,Department of Radiology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
| | - Qian Li
- Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, Chengdu, China.,Psychoradiology Research Unit of the Chinese Academy of Medical Sciences (2018RU011), West China Hospital of Sichuan University, Chengdu, China.,Department of Radiology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
| | - Na Hu
- Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, Chengdu, China.,Psychoradiology Research Unit of the Chinese Academy of Medical Sciences (2018RU011), West China Hospital of Sichuan University, Chengdu, China.,Department of Radiology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
| | - Yuan Xiao
- Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, Chengdu, China.,Psychoradiology Research Unit of the Chinese Academy of Medical Sciences (2018RU011), West China Hospital of Sichuan University, Chengdu, China.,Department of Radiology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
| | - Nian Liu
- Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, Chengdu, China.,Psychoradiology Research Unit of the Chinese Academy of Medical Sciences (2018RU011), West China Hospital of Sichuan University, Chengdu, China.,Department of Radiology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
| | - Su Lui
- Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, Chengdu, China.,Psychoradiology Research Unit of the Chinese Academy of Medical Sciences (2018RU011), West China Hospital of Sichuan University, Chengdu, China.,Department of Radiology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
| | - Qiyong Gong
- Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, Chengdu, China.,Psychoradiology Research Unit of the Chinese Academy of Medical Sciences (2018RU011), West China Hospital of Sichuan University, Chengdu, China.,Department of Radiology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
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10
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Zhong L, Li T, Shu H, Huang C, Michael Johnson J, Schomer DF, Liu HL, Feng Q, Yang W, Zhu H. (TS) 2WM: Tumor Segmentation and Tract Statistics for Assessing White Matter Integrity with Applications to Glioblastoma Patients. Neuroimage 2020; 223:117368. [PMID: 32931941 PMCID: PMC7688588 DOI: 10.1016/j.neuroimage.2020.117368] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2019] [Revised: 08/23/2020] [Accepted: 09/08/2020] [Indexed: 11/24/2022] Open
Abstract
Glioblastoma (GBM) brain tumor is the most aggressive white matter (WM) invasive cerebral primary neoplasm. Due to its inherently heterogeneous appearance and shape, previous studies pursued either the segmentation precision of the tumors or qualitative analysis of the impact of brain tumors on WM integrity with manual delineation of tumors. This paper aims to develop a comprehensive analytical pipeline, called (TS)2WM, to integrate both the superior performance of brain tumor segmentation and the impact of GBM tumors on the WM integrity via tumor segmentation and tract statistics using the diffusion tensor imaging (DTI) technique. The (TS)2WM consists of three components: (i) A dilated densely connected convolutional network (D2C2N) for automatically segment GBM tumors. (ii) A modified structural connectome processing pipeline to characterize the connectivity pattern of WM bundles. (iii) A multivariate analysis to delineate the local and global associations between different DTI-related measurements and clinical variables on both brain tumors and language-related regions of interest. Among those, the proposed D2C2N model achieves competitive tumor segmentation accuracy compared with many state-of-the-art tumor segmentation methods. Significant differences in various DTI-related measurements at the streamline, weighted network, and binary network levels (e.g., diffusion properties along major fiber bundles) were found in tumor-related, language-related, and hand motor-related brain regions in 62 GBM patients as compared to healthy subjects from the Human Connectome Project.
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Affiliation(s)
- Liming Zhong
- Guangdong Provincial Key Laboratory of Medical Image Processing, School of Biomedical Engineering, Southern Medical University, Guangzhou, China
| | - Tengfei Li
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States; Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States
| | - Hai Shu
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States; Department of Biostatistics, School of Global Public Health, New York University, New York, United States
| | - Chao Huang
- Department of Statistics, Florida State University, Tallahassee, FL, United States
| | - Jason Michael Johnson
- Department of Diagnostic Radiology, Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States
| | - Donald F Schomer
- Department of Diagnostic Radiology, Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States
| | - Ho-Ling Liu
- Department of Imaging Physics, Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States
| | - Qianjin Feng
- Guangdong Provincial Key Laboratory of Medical Image Processing, School of Biomedical Engineering, Southern Medical University, Guangzhou, China
| | - Wei Yang
- Guangdong Provincial Key Laboratory of Medical Image Processing, School of Biomedical Engineering, Southern Medical University, Guangzhou, China
| | - Hongtu Zhu
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States; Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States; Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States.
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11
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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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12
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Wang J, Zhang F, Zhao C, Zeng Q, He J, O'Donnell LJ, Feng Y. Investigation of local white matter abnormality in Parkinson's disease by using an automatic fiber tract parcellation. Behav Brain Res 2020; 394:112805. [PMID: 32673707 DOI: 10.1016/j.bbr.2020.112805] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2019] [Revised: 07/01/2020] [Accepted: 07/08/2020] [Indexed: 11/18/2022]
Abstract
The deficits of white matter (WM) microstructure are involved during Parkinson's disease (PD) progression. Most current methods identify key WM tracts relying on cortical regions of interest (ROIs). However, such ROI methods can be challenged due to low diffusion anisotropy near the gray matter (GM), which could result in a low sensitivity of tract identification. This work proposes an automatic WM parcellation method to improve the accuracy of WM tract identification and locate abnormal tracts by using sensitive features. The proposed method consists of 1) whole brain WM parcellation using an established fiber clustering method, without using any ROIs, 2) features of fasciculus were calculated to quantify diffusion measures at each equal cross-section along the whole cluster. Then, we use the proposed features to investigate the WM difference in PD compared with healthy controls (HC). We also use these features to investigate the relationship of clinical symptoms and specific fiber tracts. The novelty of the proposed method is that it automatically identifies the abnormal WM fibers in cluster degree. Experiment results indicated that the proposed method had advantage in detecting the local WM abnormality by performing between-group statistical analysis in 30 patients with PD and 28 HC. We found 13 hemisphere clusters and 8 commissural clusters had significant group difference (p < 0.05, corrected by FDR method) in local regions, which belonged to multiple fiber tracts including cingulum bundle (CB), inferior occipito-frontal fasciculus (IoFF), corpus callosum (CC), external capsule (EC), uncinate fasciculus (UF), superior longitudinal fasciculus (SLF) and thalamo front (TF). We also found clusters that had relevance with clinical indices of cognitive function (2 clusters), athletic function (6 clusters), and depressive state (2 clusters) in these significant clusters. From the experiment results, it confirmed the ability of the proposed method to identify potential WM microstructure abnormality.
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Affiliation(s)
- Jingqiang Wang
- College of Information Engineering, Zhejiang University of Technology, Hangzhou, China
| | - Fan Zhang
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Changchen Zhao
- College of Information Engineering, Zhejiang University of Technology, Hangzhou, China
| | - Qingrun Zeng
- College of Information Engineering, Zhejiang University of Technology, Hangzhou, China
| | - Jianzhong He
- College of Information Engineering, Zhejiang University of Technology, Hangzhou, China
| | | | - Yuanjing Feng
- College of Information Engineering, Zhejiang University of Technology, Hangzhou, China
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13
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Nigro P, Chiappiniello A, Simoni S, Paolini Paoletti F, Cappelletti G, Chiarini P, Filidei M, Eusebi P, Guercini G, Santangelo V, Tarducci R, Calabresi P, Parnetti L, Tambasco N. Changes of olfactory tract in Parkinson's disease: a DTI tractography study. Neuroradiology 2020; 63:235-242. [PMID: 32918150 DOI: 10.1007/s00234-020-02551-4] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Accepted: 09/07/2020] [Indexed: 12/14/2022]
Abstract
PURPOSE Impaired olfactory function is one of the main features of Parkinson's disease. However, how peripheral olfactory structures are involved remains unclear. Using diffusion tensor imaging fiber tracking, we investigated for MRI microstructural changes in the parkinsonian peripheral olfactory system and particularly the olfactory tract, in order to seek a better understanding of the structural alternations underlying hyposmia in Parkinson's disease. METHODS All patients were assessed utilizing by the Italian Olfactory Identification Test for olfactory function and the Unified Parkinson's Disease Rating Scale-III part as well as Hoehn and Yahr rating scale for motor disability. Imaging was performed on a 3 T Clinical MR scanner. MRI data pre-processing was carried out by DTIPrep, diffusion tensor imaging reconstruction, and fiber tracking using Diffusion Toolkit and tractography analysis by TrackVis. The following parameters were used for groupwise comparison: fractional anisotropy, mean diffusivity, radial diffusivity, axial diffusivity, and tract volume. RESULTS Overall 23 patients with Parkinson's disease (mean age 63.6 ± 9.3 years, UPDRS-III 24.5 ± 12.3, H&Y 1.9 ± 0.5) and 18 controls (mean age 56.3 ± 13.7 years) were recruited. All patients had been diagnosed hyposmic. Diffusion tensor imaging analysis of the olfactory tract showed significant fractional anisotropy, and tract volume decreases for the Parkinson's disease group compared with controls (P < 0.05). Fractional anisotropy and age, in the control group, were significant for multiple correlations (r = - 0.36, P < 0.05, Spearman's rank correlation). CONCLUSIONS Fiber tracking diffusion tensor imaging analysis of olfactory tract was feasible, and it could be helpful for characterizing hyposmia in Parkinson's disease.
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Affiliation(s)
- Pasquale Nigro
- Movement Disorders Center, Neurology Department, Perugia General Hospital and University of Perugia, S. Maria della Misericordia Hospital, Perugia, Italy
| | | | - Simone Simoni
- Movement Disorders Center, Neurology Department, Perugia General Hospital and University of Perugia, S. Maria della Misericordia Hospital, Perugia, Italy
| | - Federico Paolini Paoletti
- Movement Disorders Center, Neurology Department, Perugia General Hospital and University of Perugia, S. Maria della Misericordia Hospital, Perugia, Italy
| | - Giulia Cappelletti
- Movement Disorders Center, Neurology Department, Perugia General Hospital and University of Perugia, S. Maria della Misericordia Hospital, Perugia, Italy
| | - Pietro Chiarini
- Neuroradiology Unit, Perugia General Hospital, Perugia, Italy
| | - Marta Filidei
- Movement Disorders Center, Neurology Department, Perugia General Hospital and University of Perugia, S. Maria della Misericordia Hospital, Perugia, Italy
| | - Paolo Eusebi
- Neurology Department, Perugia General Hospital and University of Perugia, Perugia, Italy
| | | | - Valerio Santangelo
- Department of Philosophy, Social Sciences & Education, University of Perugia, Perugia, Italy.,Neuroimaging Laboratory, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Roberto Tarducci
- Department of Medical Physics, Perugia General Hospital, Perugia, Italy
| | - Paolo Calabresi
- Neurologia, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy.,Dipartimento di Neuroscienze, Università Cattolica del Sacro Cuore, Rome, Italy
| | - Lucilla Parnetti
- Neurology Department, Perugia General Hospital and University of Perugia, Perugia, Italy
| | - Nicola Tambasco
- Movement Disorders Center, Neurology Department, Perugia General Hospital and University of Perugia, S. Maria della Misericordia Hospital, Perugia, Italy. .,Neurology Department, Perugia General Hospital and University of Perugia, Perugia, Italy.
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14
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A diffusion tensor imaging study to compare normative fractional anisotropy values with patients suffering from Parkinson’s disease in the brain grey and white matter. HEALTH AND TECHNOLOGY 2020. [DOI: 10.1007/s12553-020-00454-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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15
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Altered white matter microarchitecture in Parkinson's disease: a voxel-based meta-analysis of diffusion tensor imaging studies. Front Med 2020; 15:125-138. [PMID: 32458190 DOI: 10.1007/s11684-019-0725-5] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2019] [Accepted: 10/12/2019] [Indexed: 02/05/2023]
Abstract
This study aimed to define the most consistent white matter microarchitecture pattern in Parkinson's disease (PD) reflected by fractional anisotropy (FA), addressing clinical profiles and methodology-related heterogeneity. Web-based publication databases were searched to conduct a meta-analysis of whole-brain diffusion tensor imaging studies comparing PD with healthy controls (HC) using the anisotropic effect size-signed differential mapping. A total of 808 patients with PD and 760 HC coming from 27 databases were finally included. Subgroup analyses were conducted considering heterogeneity with respect to medication status, disease stage, analysis methods, and the number of diffusion directions in acquisition. Compared with HC, patients with PD had decreased FA in the left middle cerebellar peduncle, corpus callosum (CC), left inferior fronto-occipital fasciculus, and right inferior longitudinal fasciculus. Most of the main results remained unchanged in subgroup meta-analyses of medicated patients, early stage patients, voxel-based analysis, and acquisition with 30 diffusion directions. The subgroup meta-analysis of medication-free patients showed FA decrease in the right olfactory cortex. The cerebellum and CC, associated with typical motor impairment, showed the most consistent FA decreases in PD. Medication status, analysis approaches, and the number of diffusion directions have an important impact on the findings, needing careful evaluation in future meta-analyses.
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16
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Correia MM, Rittman T, Barnes CL, Coyle-Gilchrist IT, Ghosh B, Hughes LE, Rowe JB. Towards accurate and unbiased imaging-based differentiation of Parkinson's disease, progressive supranuclear palsy and corticobasal syndrome. Brain Commun 2020; 2:fcaa051. [PMID: 32671340 PMCID: PMC7325838 DOI: 10.1093/braincomms/fcaa051] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2019] [Revised: 01/17/2020] [Accepted: 02/12/2020] [Indexed: 12/20/2022] Open
Abstract
The early and accurate differential diagnosis of parkinsonian disorders is still a significant challenge for clinicians. In recent years, a number of studies have used magnetic resonance imaging data combined with machine learning and statistical classifiers to successfully differentiate between different forms of Parkinsonism. However, several questions and methodological issues remain, to minimize bias and artefact-driven classification. In this study, we compared different approaches for feature selection, as well as different magnetic resonance imaging modalities, with well-matched patient groups and tightly controlling for data quality issues related to patient motion. Our sample was drawn from a cohort of 69 healthy controls, and patients with idiopathic Parkinson’s disease (n = 35), progressive supranuclear palsy Richardson’s syndrome (n = 52) and corticobasal syndrome (n = 36). Participants underwent standardized T1-weighted and diffusion-weighted magnetic resonance imaging. Strict data quality control and group matching reduced the control and patient numbers to 43, 32, 33 and 26, respectively. We compared two different methods for feature selection and dimensionality reduction: whole-brain principal components analysis, and an anatomical region-of-interest based approach. In both cases, support vector machines were used to construct a statistical model for pairwise classification of healthy controls and patients. The accuracy of each model was estimated using a leave-two-out cross-validation approach, as well as an independent validation using a different set of subjects. Our cross-validation results suggest that using principal components analysis for feature extraction provides higher classification accuracies when compared to a region-of-interest based approach. However, the differences between the two feature extraction methods were significantly reduced when an independent sample was used for validation, suggesting that the principal components analysis approach may be more vulnerable to overfitting with cross-validation. Both T1-weighted and diffusion magnetic resonance imaging data could be used to successfully differentiate between subject groups, with neither modality outperforming the other across all pairwise comparisons in the cross-validation analysis. However, features obtained from diffusion magnetic resonance imaging data resulted in significantly higher classification accuracies when an independent validation cohort was used. Overall, our results support the use of statistical classification approaches for differential diagnosis of parkinsonian disorders. However, classification accuracy can be affected by group size, age, sex and movement artefacts. With appropriate controls and out-of-sample cross validation, diagnostic biomarker evaluation including magnetic resonance imaging based classifiers may be an important adjunct to clinical evaluation.
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Affiliation(s)
- Marta M Correia
- MRC Cognition and Brain Sciences Unit, University of Cambridge, UK
| | - Timothy Rittman
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Foundation Trust, University of Cambridge, Cambridge, UK
| | | | - Ian T Coyle-Gilchrist
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Foundation Trust, University of Cambridge, Cambridge, UK
| | - Boyd Ghosh
- Wessex Neurological Centre, University Hospital Southampton NHS Foundation Trust, UK
| | - Laura E Hughes
- MRC Cognition and Brain Sciences Unit, University of Cambridge, UK.,Department of Clinical Neurosciences and Cambridge University Hospitals NHS Foundation Trust, University of Cambridge, Cambridge, UK
| | - James B Rowe
- MRC Cognition and Brain Sciences Unit, University of Cambridge, UK.,Department of Clinical Neurosciences and Cambridge University Hospitals NHS Foundation Trust, University of Cambridge, Cambridge, UK.,Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Denmark
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17
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Mitchell T, Archer DB, Chu WT, Coombes SA, Lai S, Wilkes BJ, McFarland NR, Okun MS, Black ML, Herschel E, Simuni T, Comella C, Xie T, Li H, Parrish TB, Kurani AS, Corcos DM, Vaillancourt DE. Neurite orientation dispersion and density imaging (NODDI) and free-water imaging in Parkinsonism. Hum Brain Mapp 2019; 40:5094-5107. [PMID: 31403737 DOI: 10.1002/hbm.24760] [Citation(s) in RCA: 67] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2019] [Revised: 07/08/2019] [Accepted: 07/31/2019] [Indexed: 02/05/2023] Open
Abstract
Neurite orientation dispersion and density imaging (NODDI) uses a three-compartment model to probe brain tissue microstructure, whereas free-water (FW) imaging models two-compartments. It is unknown if NODDI detects more disease-specific effects related to neurodegeneration in Parkinson's disease (PD) and atypical Parkinsonism. We acquired multi- and single-shell diffusion imaging at 3 Tesla across two sites. NODDI (using multi-shell; isotropic volume [Viso]; intracellular volume [Vic]; orientation dispersion [ODI]) and FW imaging (using single-shell; FW; free-water corrected fractional anisotropy [FAt]) were compared with 44 PD, 21 multiple system atrophy Parkinsonian variant (MSAp), 26 progressive supranuclear palsy (PSP), and 24 healthy control subjects in the basal ganglia, midbrain/thalamus, cerebellum, and corpus callosum. There was elevated Viso in posterior substantia nigra across Parkinsonisms, and Viso, Vic, and ODI were altered in MSAp and PSP in the striatum, globus pallidus, midbrain, thalamus, cerebellum, and corpus callosum relative to controls. The mean effect size across regions for Viso was 0.163, ODI 0.131, Vic 0.122, FW 0.359, and FAt 0.125, with extracellular compartments having the greatest effect size. A key question addressed was if these techniques discriminate PD and atypical Parkinsonism. Both NODDI (AUC: 0.945) and FW imaging (AUC: 0.969) had high accuracy, with no significant difference between models. This study provides new evidence that NODDI and FW imaging offer similar discriminability between PD and atypical Parkinsonism, and FW had higher effect sizes for detecting Parkinsonism within regions across the basal ganglia and cerebellum.
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Affiliation(s)
- Trina Mitchell
- Laboratory for Rehabilitation Neuroscience, Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, Florida
| | - Derek B Archer
- Laboratory for Rehabilitation Neuroscience, Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, Florida
| | - Winston T Chu
- Laboratory for Rehabilitation Neuroscience, Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, Florida.,J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, Florida
| | - Stephen A Coombes
- Laboratory for Rehabilitation Neuroscience, Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, Florida
| | - Song Lai
- Department of Radiation Oncology & CTSI Human Imaging Core, University of Florida, Gainesville, Florida
| | - Bradley J Wilkes
- Laboratory for Rehabilitation Neuroscience, Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, Florida
| | - Nikolaus R McFarland
- Department of Neurology and Center for Movement Disorders and Neurorestoration, College of Medicine, University of Florida, Gainesville, Florida
| | - Michael S Okun
- Department of Neurology and Center for Movement Disorders and Neurorestoration, College of Medicine, University of Florida, Gainesville, Florida
| | - Mieniecia L Black
- Laboratory for Rehabilitation Neuroscience, Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, Florida
| | - Ellen Herschel
- Department of Physical Therapy and Human Movement Sciences, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Tanya Simuni
- Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Cynthia Comella
- Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois
| | - Tao Xie
- Department of Neurology, University of Chicago Medicine, Chicago, Illinois
| | - Hong Li
- Department of Public Health Sciences, Medical College of South Carolina, Charleston, South Carolina
| | - Todd B Parrish
- Department of Radiology, Northwestern Feinberg School of Medicine, Chicago, Illinois
| | - Ajay S Kurani
- Department of Radiology, Northwestern Feinberg School of Medicine, Chicago, Illinois
| | - Daniel M Corcos
- Department of Physical Therapy and Human Movement Sciences, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - David E Vaillancourt
- Laboratory for Rehabilitation Neuroscience, Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, Florida.,J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, Florida.,Department of Neurology and Center for Movement Disorders and Neurorestoration, College of Medicine, University of Florida, Gainesville, Florida
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18
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Mishra VR, Sreenivasan KR, Zhuang X, Yang Z, Cordes D, Walsh RR. Influence of analytic techniques on comparing DTI-derived measurements in early stage Parkinson's disease. Heliyon 2019; 5:e01481. [PMID: 31008407 PMCID: PMC6458486 DOI: 10.1016/j.heliyon.2019.e01481] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2018] [Revised: 03/08/2019] [Accepted: 04/02/2019] [Indexed: 11/16/2022] Open
Abstract
Diffusion tensor imaging (DTI) studies in early Parkinson's disease (PD) to understand pathologic changes in white matter (WM) organization are variable in their findings. Evaluation of different analytic techniques frequently employed to understand the DTI-derived change in WM organization in a multisite, well-characterized, early stage PD cohort should aid the identification of the most robust analytic techniques to be used to investigate WM pathology in this disease, an important unmet need in the field. Thus, region of interest (ROI)-based analysis, voxel-based morphometry (VBM) analysis with varying spatial smoothing, and the two most widely used skeletonwise approaches (tract-based spatial statistics, TBSS, and tensor-based registration, DTI-TK) were evaluated in a DTI dataset of early PD and Healthy Controls (HC) from the Parkinson's Progression Markers Initiative (PPMI) cohort. Statistical tests on the DTI-derived metrics were conducted using a nonparametric approach from this cohort of early PD, after rigorously controlling for motion and signal artifacts during DTI scan which are frequent confounds in this disease population. Both TBSS and DTI-TK revealed a significantly negative correlation of fractional anisotropy (FA) with disease duration. However, only DTI-TK revealed radial diffusivity (RD) to be driving this FA correlation with disease duration. HC had a significantly positive correlation of MD with cumulative DaT score in the right middle-frontal cortex after a minimum smoothing level (at least 13mm) was attained. The present study found that scalar DTI-derived measures such as FA, MD, and RD should be used as imaging biomarkers with caution in early PD as the conclusions derived from them are heavily dependent on the choice of the analysis used. This study further demonstrated DTI-TK may be used to understand changes in DTI-derived measures with disease progression as it was found to be more accurate than TBSS. In addition, no singular region was identified that could explain both disease duration and severity in early PD. The results of this study should help standardize the utilization of DTI-derived measures in PD in an effort to improve comparability across studies and time, and to minimize variability in reported results due to variation in techniques.
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Affiliation(s)
- Virendra R. Mishra
- Lou Ruvo Center for Brain Health, Cleveland Clinic Foundation, Las Vegas, Nevada, United States
| | - Karthik R. Sreenivasan
- Lou Ruvo Center for Brain Health, Cleveland Clinic Foundation, Las Vegas, Nevada, United States
| | - Xiaowei Zhuang
- Lou Ruvo Center for Brain Health, Cleveland Clinic Foundation, Las Vegas, Nevada, United States
| | - Zhengshi Yang
- Lou Ruvo Center for Brain Health, Cleveland Clinic Foundation, Las Vegas, Nevada, United States
| | - Dietmar Cordes
- Lou Ruvo Center for Brain Health, Cleveland Clinic Foundation, Las Vegas, Nevada, United States
- Departments of Psychology and Neuroscience, University of Colorado at Boulder, Boulder, Colorado, United States
| | - Ryan R. Walsh
- Muhammad Ali Parkinson Center, Barrow Neurological Institute, Phoenix, Arizona, United States
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19
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Xu S, He XW, Zhao R, Chen W, Qin Z, Zhang J, Ban S, Li GF, Shi YH, Hu Y, Zhuang MT, Liu YS, Shen XL, Li J, Liu JR, Du X. Cerebellar functional abnormalities in early stage drug-naïve and medicated Parkinson's disease. J Neurol 2019; 266:1578-1587. [PMID: 30923933 DOI: 10.1007/s00415-019-09294-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2018] [Revised: 03/18/2019] [Accepted: 03/21/2019] [Indexed: 12/27/2022]
Abstract
Parkinson's disease (PD) is a progressive neurological degenerative disorder characterized by impaired motor function and non-motor dysfunctions. While recent studies have highlighted the role of the cerebellum in PD, our understanding of its role in PD remains limited. In the present study, we used resting-state fMRI to evaluate dysfunctions within the cerebellum in PD patients treated with medication and drug-naïve PD patients. We applied amplitude of low-frequency fluctuation (ALFF) and degree centrality (DC) analysis methods. Thirty-one patients with early stage PD (22 drug-naïve and 9 medicated patients) and 31 gender- and age-matched healthy controls were recruited in this study. ALFFs increased in the left cerebellar areas (lobules VI/VIIb/CruI/CruII and the dentate gyrus) and right cerebellar areas (lobules VI/VIIb/VIIIa/CruI/CruII and the dentate gyrus) of all PD patients and in the left and right cerebellar areas (lobules VI/VIIb/CruI and the dentate gyrus) of drug-naive PD patients but were not significantly changed in medicated PD patients. DC increased in the right cerebellar areas of all PD patients and medicated PD patients. All PD patients and all drug-naive PD patients showed significantly weaker functional connectivity (FC) between the left cerebellum and the left medial frontal gyrus. However, FC was significantly stronger between the right cerebellum and the left precentral and right middle occipital gyri in the medicated PD patients than in controls. Furthermore, a correlation analyses revealed that ALFF z scores in the left cerebellum (lobule VI) and right cerebellum (lobule VI/CruI and dentate gyrus) were negatively correlated with Mini-Mental State Examination (MMSE) scores in all PD patients and drug-naive patients. These results indicate that the cerebellum plays an important role in PD, mainly by exerting a compensatory effect in early stage PD. Additionally, antiparkinsonian medication would modified PD-induced changes in local neural activity and FC in PD patients. The results of this study offer novel insights into the roles of the cerebellum in early stage drug-naïve PD.
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Affiliation(s)
- Shuai Xu
- Shanghai Key Laboratory of Magnetic Resonance and Department of Physics, School of Physics and Materials Science, East China Normal University, 3663 North Zhong-Shan Road, Shanghai, 200062, People's Republic of China
| | - Xin-Wei He
- Department of Neurology and Jiuyuan Municipal Stroke Center, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, 639 Zhizaoju Road, Shanghai, 200011, People's Republic of China.,Clinical Research Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, People's Republic of China
| | - Rong Zhao
- Department of Neurology and Jiuyuan Municipal Stroke Center, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, 639 Zhizaoju Road, Shanghai, 200011, People's Republic of China.,Clinical Research Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, People's Republic of China
| | - Wei Chen
- Department of Neurology and Jiuyuan Municipal Stroke Center, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, 639 Zhizaoju Road, Shanghai, 200011, People's Republic of China
| | - Zhaoxia Qin
- Shanghai Key Laboratory of Magnetic Resonance and Department of Physics, School of Physics and Materials Science, East China Normal University, 3663 North Zhong-Shan Road, Shanghai, 200062, People's Republic of China
| | - Jilei Zhang
- Shanghai Key Laboratory of Magnetic Resonance and Department of Physics, School of Physics and Materials Science, East China Normal University, 3663 North Zhong-Shan Road, Shanghai, 200062, People's Republic of China
| | - Shiyu Ban
- Shanghai Key Laboratory of Magnetic Resonance and Department of Physics, School of Physics and Materials Science, East China Normal University, 3663 North Zhong-Shan Road, Shanghai, 200062, People's Republic of China
| | - Ge-Fei Li
- Department of Neurology and Jiuyuan Municipal Stroke Center, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, 639 Zhizaoju Road, Shanghai, 200011, People's Republic of China.,Clinical Research Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, People's Republic of China
| | - Yan-Hui Shi
- Department of Neurology and Jiuyuan Municipal Stroke Center, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, 639 Zhizaoju Road, Shanghai, 200011, People's Republic of China.,Clinical Research Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, People's Republic of China
| | - Yue Hu
- Department of Neurology and Jiuyuan Municipal Stroke Center, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, 639 Zhizaoju Road, Shanghai, 200011, People's Republic of China.,Clinical Research Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, People's Republic of China
| | - Mei-Ting Zhuang
- Department of Neurology and Jiuyuan Municipal Stroke Center, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, 639 Zhizaoju Road, Shanghai, 200011, People's Republic of China
| | - Yi-Sheng Liu
- Department of Neurology and Jiuyuan Municipal Stroke Center, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, 639 Zhizaoju Road, Shanghai, 200011, People's Republic of China
| | - Xiao-Lei Shen
- Department of Neurology and Jiuyuan Municipal Stroke Center, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, 639 Zhizaoju Road, Shanghai, 200011, People's Republic of China
| | - Jianqi Li
- Shanghai Key Laboratory of Magnetic Resonance and Department of Physics, School of Physics and Materials Science, East China Normal University, 3663 North Zhong-Shan Road, Shanghai, 200062, People's Republic of China
| | - Jian-Ren Liu
- Department of Neurology and Jiuyuan Municipal Stroke Center, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, 639 Zhizaoju Road, Shanghai, 200011, People's Republic of China. .,Clinical Research Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, People's Republic of China.
| | - Xiaoxia Du
- Shanghai Key Laboratory of Magnetic Resonance and Department of Physics, School of Physics and Materials Science, East China Normal University, 3663 North Zhong-Shan Road, Shanghai, 200062, People's Republic of China.
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20
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Lorio S, Sambataro F, Bertolino A, Draganski B, Dukart J. The Combination of DAT-SPECT, Structural and Diffusion MRI Predicts Clinical Progression in Parkinson's Disease. Front Aging Neurosci 2019; 11:57. [PMID: 30930768 PMCID: PMC6428714 DOI: 10.3389/fnagi.2019.00057] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2018] [Accepted: 02/26/2019] [Indexed: 12/13/2022] Open
Abstract
There is an increasing interest in identifying non-invasive biomarkers of disease severity and prognosis in idiopathic Parkinson’s disease (PD). Dopamine-transporter SPECT (DAT-SPECT), diffusion tensor imaging (DTI), and structural magnetic resonance imaging (sMRI) provide unique information about the brain’s neurotransmitter and microstructural properties. In this study, we evaluate the relative and combined capability of these imaging modalities to predict symptom severity and clinical progression in de novo PD patients. To this end, we used MRI, SPECT, and clinical data of de novo drug-naïve PD patients (n = 205, mean age 61 ± 10) and age-, sex-matched healthy controls (n = 105, mean age 58 ± 12) acquired at baseline. Moreover, we employed clinical data acquired at 1 year follow-up for PD patients with or without L-Dopa treatment in order to predict the progression symptoms severity. Voxel-based group comparisons and covariance analyses were applied to characterize baseline disease-related alterations for DAT-SPECT, DTI, and sMRI. Cortical and subcortical alterations in de novo PD patients were found in all evaluated imaging modalities, in line with previously reported midbrain-striato-cortical network alterations. The combination of these imaging alterations was reliably linked to clinical severity and disease progression at 1 year follow-up in this patient population, providing evidence for the potential use of these modalities as imaging biomarkers for disease severity and prognosis that can be integrated into clinical trials.
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Affiliation(s)
- Sara Lorio
- Developmental Neurosciences, UCL Great Ormond Street Institute of Child Health, University College London, London, United Kingdom.,Roche Pharma and Early Development, Neuroscience, Ophthalmology and Rare Diseases, F. Hoffmann-La Roche Ltd., Basel, Switzerland.,Laboratory for Research in Neuroimaging, Department of Clinical Neurosciences, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland
| | - Fabio Sambataro
- Roche Pharma and Early Development, Neuroscience, Ophthalmology and Rare Diseases, F. Hoffmann-La Roche Ltd., Basel, Switzerland.,Department of Experimental and Clinical Medical Sciences, University of Udine, Udine, Italy
| | - Alessandro Bertolino
- Roche Pharma and Early Development, Neuroscience, Ophthalmology and Rare Diseases, F. Hoffmann-La Roche Ltd., Basel, Switzerland.,Department of Basic Medical Science, Neuroscience and Sense Organs, University of Bari, Bari, Italy
| | - Bogdan Draganski
- Laboratory for Research in Neuroimaging, Department of Clinical Neurosciences, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland.,Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Juergen Dukart
- Roche Pharma and Early Development, Neuroscience, Ophthalmology and Rare Diseases, F. Hoffmann-La Roche Ltd., Basel, Switzerland.,Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany.,Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
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21
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Cai X, Qiao J, Knox T, Iriah S, Kulkarni P, Madularu D, Morrison T, Waszczak B, Hartner JC, Ferris CF. In search of early neuroradiological biomarkers for Parkinson’s Disease: Alterations in resting state functional connectivity and gray matter microarchitecture in PINK1 −/− rats. Brain Res 2019; 1706:58-67. [DOI: 10.1016/j.brainres.2018.10.033] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2018] [Revised: 10/29/2018] [Accepted: 10/30/2018] [Indexed: 12/12/2022]
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22
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Huart C, Rombaux P, Hummel T. Neural plasticity in developing and adult olfactory pathways – focus on the human olfactory bulb. J Bioenerg Biomembr 2019; 51:77-87. [DOI: 10.1007/s10863-018-9780-x] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2018] [Accepted: 11/23/2018] [Indexed: 01/18/2023]
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23
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Pathophysiology of levodopa-induced dyskinesia: Insights from multimodal imaging and immunohistochemistry in non-human primates. Neuroimage 2018; 183:132-141. [DOI: 10.1016/j.neuroimage.2018.08.016] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2018] [Revised: 07/21/2018] [Accepted: 08/09/2018] [Indexed: 12/12/2022] Open
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24
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Pozorski V, Oh JM, Adluru N, Merluzzi AP, Theisen F, Okonkwo O, Barzgari A, Krislov S, Sojkova J, Bendlin BB, Johnson SC, Alexander AL, Gallagher CL. Longitudinal white matter microstructural change in Parkinson's disease. Hum Brain Mapp 2018; 39:4150-4161. [PMID: 29952102 DOI: 10.1002/hbm.24239] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2017] [Revised: 05/06/2018] [Accepted: 05/22/2018] [Indexed: 01/06/2023] Open
Abstract
Postmortem studies of Parkinson's disease (PD) suggest that Lewy body pathology accumulates in a predictable topographical sequence, beginning in the olfactory bulb, followed by caudal brainstem, substantia nigra, limbic cortex, and neocortex. Diffusion-weighted imaging (DWI) is sensitive, if not specific, to early disease-related white matter (WM) change in a variety of traumatic and degenerative brain diseases. Although numerous cross-sectional studies have reported DWI differences in cerebral WM in PD, only a few longitudinal studies have investigated whether DWI change exceeds that of normal aging or coincides with regional Lewy body accumulation. This study mapped regional differences in the rate of DWI-based microstructural change between 29 PD patients and 43 age-matched controls over 18 months. Iterative within- and between-subject tensor-based registration was completed on motion- and eddy current-corrected DWI images, then baseline versus follow-up difference maps of fractional anisotropy, mean, radial, and axial diffusivity were analyzed in the Biological Parametric Mapping toolbox for MATLAB. This analysis showed that PD patients had a greater decline in WM integrity in the rostral brainstem, caudal subcortical WM, and cerebellar peduncles, compared with controls. In addition, patients with unilateral clinical signs at baseline experienced a greater rate of WM change over the 18-month study than patients with bilateral signs. These findings suggest that rate of WM microstructural change in PD exceeds that of normal aging and is maximal during early stage disease. In addition, the neuroanatomic locations (rostral brainstem and subcortical WM) of accelerated WM change fit with current theories of topographic disease progression.
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Affiliation(s)
- Vincent Pozorski
- William S. Middleton Memorial Veterans Hospital, Madison, Wisconsin.,Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
| | - Jennifer M Oh
- William S. Middleton Memorial Veterans Hospital, Madison, Wisconsin.,Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
| | - Nagesh Adluru
- Waisman Laboratory for Brain Imaging and Behavior, Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin
| | - Andrew P Merluzzi
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
| | - Frances Theisen
- William S. Middleton Memorial Veterans Hospital, Madison, Wisconsin.,Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
| | - Ozioma Okonkwo
- William S. Middleton Memorial Veterans Hospital, Madison, Wisconsin.,Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
| | - Amy Barzgari
- William S. Middleton Memorial Veterans Hospital, Madison, Wisconsin.,Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
| | - Stephanie Krislov
- William S. Middleton Memorial Veterans Hospital, Madison, Wisconsin.,Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
| | - Jitka Sojkova
- Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin.,Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
| | - Barbara B Bendlin
- William S. Middleton Memorial Veterans Hospital, Madison, Wisconsin.,Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
| | - Sterling C Johnson
- William S. Middleton Memorial Veterans Hospital, Madison, Wisconsin.,Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
| | - Andrew L Alexander
- Waisman Laboratory for Brain Imaging and Behavior, Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin.,Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin.,Department of Psychiatry, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
| | - Catherine L Gallagher
- William S. Middleton Memorial Veterans Hospital, Madison, Wisconsin.,Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin.,Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
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25
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Zhou XX, Li XH, Chen DB, Wu C, Feng L, Chu JP, Yang ZY, Li XB, Qin H, Li GD, Huang HW, Liang YY, Liang XL. The asymmetry of neural symptoms in Wilson's disease patients detecting by diffusion tensor imaging, resting-state functional MRI, and susceptibility-weighted imaging. Brain Behav 2018; 8:e00930. [PMID: 29761003 PMCID: PMC5943770 DOI: 10.1002/brb3.930] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2017] [Revised: 10/25/2017] [Accepted: 01/04/2018] [Indexed: 12/13/2022] Open
Abstract
OBJECTIVE To investigate the cause of the motor asymmetry in Wilson's disease (WD) patients using functional MRI. METHODS Fifty patients with WD and 20 age-matched healthy controls were enrolled. Neurological symptoms were scored using the modified Young Scale. All study subjects underwent diffusion tensor imaging (DTI), susceptibility-weighted imaging (SWI), and resting-state functional MRI (rs-fMRI) of the brain. Six regions of interest (ROI) were chosen. Fiber volumes between ROIs on DTI, corrected phase (CP) values on SWI, amplitude of low-frequency fluctuation (ALFF), and regional homogeneity (REHO) values on rs-fMRI were determined. Asymmetry index (right or left value/left or right value) was evaluated. RESULTS Asymmetry of rigidity, tremor, choreic movement, and gait abnormality (asymmetry index = 1.33, 1.39, 1.36, 1.40), fiber tracts between the GP and substantia nigra (SN), GP and PU, SN and thalamus (TH), SN and cerebellum, head of the caudate nucleus (CA) and SN, PU and CA, CA and TH, TH and cerebellum (asymmetry index = 1.233, 1.260, 1.269, 1.437, 1.503, 1.138, 1.145, 1.279), CP values in the TH, SN (asymmetry index = 1.327, 1.166), ALFF values, and REHO values of the TH (asymmetry index = 1.192, 1.233) were found. Positive correlation between asymmetry index of rigidity and fiber volumes between the GP and SN, SN and TH (r = .221, .133, p = .043, .036), and tremor and fiber volumes between the CA and TH (r = .045, p = .040) was found. CONCLUSIONS The neurological symptoms of patients with WD were asymmetry. The asymmetry of fiber projections may be the main cause of motor asymmetry in patients with WD.
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Affiliation(s)
- Xiang-Xue Zhou
- Department of Neurology The East Area of the First Affiliated Hospital Sun Yat-Sen University Guangzhou China
| | - Xun-Hua Li
- Department of Neurology The First Affiliated Hospital Sun Yat-Sen University Guangzhou China
| | - Ding-Bang Chen
- Department of Neurology The First Affiliated Hospital Sun Yat-Sen University Guangzhou China
| | - Chao Wu
- Department of Neurology The First Affiliated Hospital Sun Yat-Sen University Guangzhou China
| | - Li Feng
- Department of Neurology The First Affiliated Hospital Sun Yat-Sen University Guangzhou China
| | - Jian-Ping Chu
- Department of Radiology The First Affiliated Hospital Sun Yat-Sen University Guangzhou China
| | - Zhi-Yun Yang
- Department of Radiology The First Affiliated Hospital Sun Yat-Sen University Guangzhou China
| | - Xin-Bei Li
- Department of Radiology The First Affiliated Hospital Sun Yat-Sen University Guangzhou China
| | - Haolin Qin
- Department of Radiology The East Area of the First Affiliated Hospital Sun Yat-Sen University Guangzhou China
| | - Gui-Dian Li
- Department of Radiology The East Area of the First Affiliated Hospital Sun Yat-Sen University Guangzhou China
| | - Hai-Wei Huang
- Department of Neurology The First Affiliated Hospital Sun Yat-Sen University Guangzhou China
| | - Ying-Ying Liang
- Department of Neurology The East Area of the First Affiliated Hospital Sun Yat-Sen University Guangzhou China
| | - Xiu-Ling Liang
- Department of Neurology The First Affiliated Hospital Sun Yat-Sen University Guangzhou China
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26
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Klein JC, Rolinski M, Griffanti L, Szewczyk-Krolikowski K, Baig F, Ruffmann C, Groves AR, Menke RAL, Hu MT, Mackay C. Cortical structural involvement and cognitive dysfunction in early Parkinson's disease. NMR IN BIOMEDICINE 2018; 31:e3900. [PMID: 29436039 DOI: 10.1002/nbm.3900] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/08/2017] [Revised: 12/13/2017] [Accepted: 01/03/2018] [Indexed: 06/08/2023]
Abstract
Magnetic resonance imaging (MRI) studies in early Parkinson's disease (PD) have shown promise in the detection of disease-related brain changes in the white and deep grey matter. We set out to establish whether intrinsic cortical involvement in early PD can be detected with quantitative MRI. We collected a rich, multi-modal dataset, including diffusion MRI, T1 relaxometry and cortical morphometry, in 20 patients with early PD (disease duration, 1.9 ± 0.97 years, Hoehn & Yahr 1-2) and in 19 matched controls. The cortex was reconstructed using FreeSurfer. Data analysis employed linked independent component analysis (ICA), a novel data-driven technique that allows for data fusion and extraction of multi-modal components before further analysis. For comparison, we performed standard uni-modal analysis with a general linear model (GLM). Linked ICA detected multi-modal cortical changes in early PD (p = 0.015). These comprised fractional anisotropy reduction in dorsolateral prefrontal, cingulate and premotor cortex and the superior parietal lobule, mean diffusivity increase in the mesolimbic, somatosensory and superior parietal cortex, sparse diffusivity decrease in lateral parietal and right prefrontal cortex, and sparse changes to the cortex area. In PD, the amount of cortical dysintegrity correlated with diminished cognitive performance. Importantly, uni-modal analysis detected no significant group difference on any imaging modality. We detected microstructural cortical pathology in early PD using a data-driven, multi-modal approach. This pathology is correlated with diminished cognitive performance. Our results indicate that early degenerative processes leave an MRI signature in the cortex of patients with early PD. The cortical imaging findings are behaviourally meaningful and provide a link between cognitive status and microstructural cortical pathology in patients with early PD.
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Affiliation(s)
- J C Klein
- Oxford Parkinson's Disease Centre, Nuffield Department of Clinical Neurosciences, Division of Clinical Neurology, University of Oxford, Oxford, UK
- Wellcome Centre for Integrative Neuroimaging (WIN), FMRIB Centre, University of Oxford, Oxford, UK
- Department of Clinical Neurology, John Radcliffe Hospital, Oxford, UK
| | - M Rolinski
- Oxford Parkinson's Disease Centre, Nuffield Department of Clinical Neurosciences, Division of Clinical Neurology, University of Oxford, Oxford, UK
- Department of Clinical Neurology, John Radcliffe Hospital, Oxford, UK
| | - L Griffanti
- Oxford Parkinson's Disease Centre, Nuffield Department of Clinical Neurosciences, Division of Clinical Neurology, University of Oxford, Oxford, UK
- Wellcome Centre for Integrative Neuroimaging (WIN), FMRIB Centre, University of Oxford, Oxford, UK
| | - K Szewczyk-Krolikowski
- Oxford Parkinson's Disease Centre, Nuffield Department of Clinical Neurosciences, Division of Clinical Neurology, University of Oxford, Oxford, UK
| | - F Baig
- Oxford Parkinson's Disease Centre, Nuffield Department of Clinical Neurosciences, Division of Clinical Neurology, University of Oxford, Oxford, UK
- Department of Clinical Neurology, John Radcliffe Hospital, Oxford, UK
| | - C Ruffmann
- Oxford Parkinson's Disease Centre, Nuffield Department of Clinical Neurosciences, Division of Clinical Neurology, University of Oxford, Oxford, UK
- Department of Clinical Neurology, John Radcliffe Hospital, Oxford, UK
| | - A R Groves
- Wellcome Centre for Integrative Neuroimaging (WIN), FMRIB Centre, University of Oxford, Oxford, UK
| | - R A L Menke
- Oxford Parkinson's Disease Centre, Nuffield Department of Clinical Neurosciences, Division of Clinical Neurology, University of Oxford, Oxford, UK
- Wellcome Centre for Integrative Neuroimaging (WIN), FMRIB Centre, University of Oxford, Oxford, UK
| | - M T Hu
- Oxford Parkinson's Disease Centre, Nuffield Department of Clinical Neurosciences, Division of Clinical Neurology, University of Oxford, Oxford, UK
- Department of Clinical Neurology, John Radcliffe Hospital, Oxford, UK
| | - C Mackay
- Oxford Parkinson's Disease Centre, Nuffield Department of Clinical Neurosciences, Division of Clinical Neurology, University of Oxford, Oxford, UK
- Department of Psychiatry, University of Oxford, Oxford, UK
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27
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Abbasi N, Mohajer B, Abbasi S, Hasanabadi P, Abdolalizadeh A, Rajimehr R. Relationship between cerebrospinal fluid biomarkers and structural brain network properties in Parkinson's disease. Mov Disord 2018; 33:431-439. [DOI: 10.1002/mds.27284] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2017] [Revised: 10/05/2017] [Accepted: 11/16/2017] [Indexed: 01/17/2023] Open
Affiliation(s)
- Nooshin Abbasi
- Interdisciplinary Neuroscience Research Program (INRP); Tehran University of Medical Sciences; Tehran Iran
- Multiple Sclerosis Research Center (MSRC), Sina Hospital; Tehran University of Medical Sciences; Tehran Iran
| | - Bahram Mohajer
- Interdisciplinary Neuroscience Research Program (INRP); Tehran University of Medical Sciences; Tehran Iran
- Multiple Sclerosis Research Center (MSRC), Sina Hospital; Tehran University of Medical Sciences; Tehran Iran
| | - Sima Abbasi
- Mashhad University of Medical Sciences; Mashhad Iran
| | | | - Amirhussein Abdolalizadeh
- Interdisciplinary Neuroscience Research Program (INRP); Tehran University of Medical Sciences; Tehran Iran
- Multiple Sclerosis Research Center (MSRC), Sina Hospital; Tehran University of Medical Sciences; Tehran Iran
| | - Reza Rajimehr
- McGovern Institute for Brain Research; Massachusetts Institute of Technology (MIT); Cambridge Massachusetts USA
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28
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Georgiopoulos C, Warntjes M, Dizdar N, Zachrisson H, Engström M, Haller S, Larsson EM. Olfactory Impairment in Parkinson's Disease Studied with Diffusion Tensor and Magnetization Transfer Imaging. JOURNAL OF PARKINSONS DISEASE 2018; 7:301-311. [PMID: 28482644 PMCID: PMC5438470 DOI: 10.3233/jpd-161060] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
Background: Olfactory impairment is an early manifestation of Parkinson’s disease (PD). Diffusion Tensor Imaging (DTI) and Magnetization Transfer (MT) are two imaging techniques that allow noninvasive detection of microstructural changes in the cerebral white matter. Objective: To assess white matter alterations associated with olfactory impairment in PD, using a binary imaging approach with DTI and MT. Methods: 22 PD patients and 13 healthy controls were examined with DTI, MT and an odor discrimination test. DTI data were first analyzed with tract-based spatial statistics (TBSS) in order to detect differences in fractional anisotropy, mean, radial and axial diffusivity between PD patients and controls. Voxelwise randomized permutation was employed for the MT analysis, after spatial and intensity normalization. Additionally, ROI analysis was performed on both the DTI and MT data, focused on the white matter adjacent to olfactory brain regions. Results: Whole brain voxelwise analysis revealed decreased axial diffusivity in the left uncinate fasciculus and the white matter adjacent to the left olfactory sulcus of PD patients. ROI analysis demonstrated decreased axial diffusivity in the right orbitofrontal cortex, as well as decreased mean diffusivity and axial diffusivity in the white matter of the left entorhinal cortex of PD patients. There were no significant differences regarding fractional anisotropy, radial diffusivity or MT between patients and controls. Conclusions: ROI analysis of DTI could detect microstructural changes in the white matter adjacent to olfactory areas in PD patients, whereas MT imaging could not.
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Affiliation(s)
- Charalampos Georgiopoulos
- Department of Radiology and Department ofMedical and Health Sciences, Linköping University, Linköping, Sweden.,Center for Medical ImageScience and Visualization (CMIV), Linköping University, Linköping, Sweden
| | - Marcel Warntjes
- Center for Medical ImageScience and Visualization (CMIV), Linköping University, Linköping, Sweden.,SyntheticMR AB, Linköping, Sweden
| | - Nil Dizdar
- Department of Neurologyand Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden
| | - Helene Zachrisson
- Center for Medical ImageScience and Visualization (CMIV), Linköping University, Linköping, Sweden.,Department of Clinical Physiology and Departmentof Medical and Health Sciences, Linköping University, Linköping, Sweden
| | - Maria Engström
- Center for Medical ImageScience and Visualization (CMIV), Linköping University, Linköping, Sweden.,Department of Medical andHealth Sciences, Linköping University, Linköping, Sweden
| | - Sven Haller
- Affidea CDRC Centre de Diagnostic Radiologiquede Carouge SA, Geneva, Switzerland.,Departmentof Surgical Sciences/Radiology, Uppsala University, AkademiskaSjukhuset, Uppsala, Sweden
| | - Elna-Marie Larsson
- Departmentof Surgical Sciences/Radiology, Uppsala University, AkademiskaSjukhuset, Uppsala, Sweden
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29
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Li C, Huang B, Zhang R, Ma Q, Yang W, Wang L, Wang L, Xu Q, Feng J, Liu L, Zhang Y, Huang R. Impaired topological architecture of brain structural networks in idiopathic Parkinson's disease: a DTI study. Brain Imaging Behav 2018; 11:113-128. [PMID: 26815739 DOI: 10.1007/s11682-015-9501-6] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Parkinson's disease (PD) is considered as a neurodegenerative disorder of the brain central nervous system. But, to date, few studies adopted the network model to reveal topological changes in brain structural networks in PD patients. Additionally, although the concept of rich club organization has been widely used to study brain networks in various brain disorders, there is no study to report the changed rich club organization of brain networks in PD patients. Thus, we collected diffusion tensor imaging (DTI) data from 35 PD patients and 26 healthy controls and adopted deterministic tractography to construct brain structural networks. During the network analysis, we calculated their topological properties, and built the rich club organization of brain structural networks for both subject groups. By comparing the between-group differences in topological properties and rich club organizations, we found that the connectivity strength of the feeder and local connections are lower in PD patients compared to those of the healthy controls. Furthermore, using a network-based statistic (NBS) approach, we identified uniformly significantly decreased connections in two modules, the limbic/paralimbic/subcortical module and the cognitive control/attention module, in patients compared to controls. In addition, for the topological properties of brain network topology in the PD patients, we found statistically increased shortest path length and decreased global efficiency. Statistical comparisons of nodal properties were also widespread in the frontal and parietal regions for the PD patients. These findings may provide useful information to better understand the abnormalities of brain structural networks in PD patients.
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Affiliation(s)
- Changhong Li
- Center for the Study of Applied Psychology, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, School of Psychology, Brain Study Institute, South China Normal University, Guangzhou, 510631, China
| | - Biao Huang
- Department of Radiology, Guangdong Academy of Medical Sciences, Guangdong General Hospital, Guangzhou, China.
| | - Ruibin Zhang
- Center for the Study of Applied Psychology, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, School of Psychology, Brain Study Institute, South China Normal University, Guangzhou, 510631, China
| | - Qing Ma
- Center for the Study of Applied Psychology, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, School of Psychology, Brain Study Institute, South China Normal University, Guangzhou, 510631, China
| | - Wanqun Yang
- Department of Radiology, Guangdong Academy of Medical Sciences, Guangdong General Hospital, Guangzhou, China
| | - Lijuan Wang
- Department of Neurology, Guangdong Academy of Medical Sciences, Guangdong General Hospital, Guangzhou, China
| | - Limin Wang
- Department of Neurology, Guangdong Academy of Medical Sciences, Guangdong General Hospital, Guangzhou, China
| | - Qin Xu
- Center for the Study of Applied Psychology, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, School of Psychology, Brain Study Institute, South China Normal University, Guangzhou, 510631, China
| | - Jieying Feng
- Department of Radiology, Guangdong Academy of Medical Sciences, Guangdong General Hospital, Guangzhou, China
| | - Liqing Liu
- Center for the Study of Applied Psychology, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, School of Psychology, Brain Study Institute, South China Normal University, Guangzhou, 510631, China
| | - Yuhu Zhang
- Department of Neurology, Guangdong Academy of Medical Sciences, Guangdong General Hospital, Guangzhou, China
| | - Ruiwang Huang
- Center for the Study of Applied Psychology, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, School of Psychology, Brain Study Institute, South China Normal University, Guangzhou, 510631, China.
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Rektor I, Svátková A, Vojtíšek L, Zikmundová I, Vaníček J, Király A, Szabó N. White matter alterations in Parkinson's disease with normal cognition precede grey matter atrophy. PLoS One 2018; 13:e0187939. [PMID: 29304183 PMCID: PMC5755732 DOI: 10.1371/journal.pone.0187939] [Citation(s) in RCA: 50] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2017] [Accepted: 10/27/2017] [Indexed: 12/03/2022] Open
Abstract
INTRODUCTION While progressive MRI brain changes characterize advanced Parkinson's disease (PD), little has been discovered about structural alterations in the earliest phase of the disease, i.e. in patients with motor symptoms and with normal cognition. Our study aimed to detect grey matter (GM) and white matter (WM) changes in PD patients without cognitive impairment. METHODS Twenty PD patients and twenty-one healthy controls (HC) were tested for attention, executive function, working memory, and visuospatial and language domains. High-resolution T1-weighted and 60 directional diffusion-weighted 3T MRI images were acquired. The cortical, deep GM and WM volumes and density, as well as the diffusion properties of WM, were calculated. Analyses were repeated on data flipped to the side of the disease origin. RESULTS PD patients did not show any significant differences from HC in cognitive functioning or in brain volumes. Decreased GM intensity was found in the left superior parietal lobe in the right (p<0.02) and left (p<0.01) flipped data. The analysis of original, un-flipped data demonstrated elevated axial diffusivity (p<0.01) in the superior and anterior corona radiata, internal capsule, and external capsule in the left hemisphere of PD relative to HC, while higher mean and radial diffusivity were discovered in the right (p<0.02 and p<0.03, respectively) and left (p<0.02 and p<0.02, respectively) in the fronto-temporal WM utilizing flipped data. CONCLUSIONS PD patients without cognitive impairment and GM atrophy demonstrated widespread alterations of WM microstructure. Thus, WM impairment in PD might be a sensitive sign preceding the neuronal loss in associated GM regions.
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Affiliation(s)
- Ivan Rektor
- Movement Disorders Center; First Department of Neurology, School of Medicine, Masaryk University and St. Anne’s University Hospital, Brno, Czech Republic
- Central European Institute of Technology (CEITEC) Masaryk University, Neuroscience Centre, Brno, Czech Republic
| | - Alena Svátková
- Central European Institute of Technology (CEITEC) Masaryk University, Neuroscience Centre, Brno, Czech Republic
- Department of Pediatrics, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Lubomir Vojtíšek
- Central European Institute of Technology (CEITEC) Masaryk University, Neuroscience Centre, Brno, Czech Republic
| | - Iva Zikmundová
- Movement Disorders Center; First Department of Neurology, School of Medicine, Masaryk University and St. Anne’s University Hospital, Brno, Czech Republic
| | - Jirí Vaníček
- Department of Imaging, School of Medicine, Masaryk University and St. Anne’s University Hospital, Brno, Czech Republic
| | - András Király
- Central European Institute of Technology (CEITEC) Masaryk University, Neuroscience Centre, Brno, Czech Republic
- Department of Neurology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Nikoletta Szabó
- Central European Institute of Technology (CEITEC) Masaryk University, Neuroscience Centre, Brno, Czech Republic
- Department of Neurology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
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Li XR, Ren YD, Cao B, Huang XL. Analysis of white matter characteristics with tract-based spatial statistics according to diffusion tensor imaging in early Parkinson's disease. Neurosci Lett 2017; 675:127-132. [PMID: 29199095 DOI: 10.1016/j.neulet.2017.11.064] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2017] [Revised: 11/09/2017] [Accepted: 11/29/2017] [Indexed: 12/20/2022]
Abstract
OBJECTIVE To analyze the microstructure of brain white matter according to diffusion tensor imaging (DTI) based on tract-based spatial statistics (TBSS) in early Parkinson's disease (PD). MATERIALS AND METHODS A total of 31 age- and sex-matched early PD patients and 22 healthy volunteers were recruited in the present study. DTI was performed, and the data analyzed with fsl4.0 software. The fractional anisotropy (FA) was compared between both groups with an independent t test, and the differential area was analyzed. White matter fiber tracts with significant difference in FA between the two groups were selected, and their FAs were measured. Pearson's correlation analysis was employed to analyze the unified Parkinson's disease rating scale (UPDRS) score and its association with FA of different tracts. RESULTS When compared with healthy volunteers, early PD patients had reduced FA in the following areas: bilateral anterior corona radiate, upper corona radiate, fasciculus arcuatus, crus anterius capsulae internae, crus posterius capsulae internae, capsula externa, posterior thalamic radiation, optic radiation, sagittal layer (including fasciculus arcuatus and inferior fronto-occipital fasciculus), crura fornicis, stria terminalis, fornix, genu, body and pad of corpus callosum, left unciform fasciculus, right cingulate bundle, right medipeduncle, and arcuate fibers in the bilateral frontal, temporal, and occipital lobes (P < 0.05). When compared with healthy volunteers, early PD patients showed abnormal FA of fasciculus in the white matter mainly in following areas: bilateral crus anterius capsulae internae, bilateral capsula externa, right anterior corona radiate, body and pad of bilateral corpus callosum, and left sagittal layer (including fasciculi longitudinalis inferior and fasciculus occipitofrontalis inferior) (P < 0.05). In addition, in early PD patients, the UPDRS score and movement score had no relationship with the FA of different fasciculi in the white matter (P > 0.05). CONCLUSION There is wide alteration of white matter microstructure in early PD patients, which is characterized by disruption of projection fibers in the descending pathway, limbic system-related fasciculi, corpus callosum, thalamus after radiation, posterior thalamic radiation, Gratiolet's bundle and other fasciculi in the white matter.
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Affiliation(s)
- Xiang-Rong Li
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Province 530021, PR China.
| | - Yan-De Ren
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, Shandong Province, 266003, PR China
| | - Bo Cao
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, Shandong Province, 266003, PR China
| | - Xuan-Li Huang
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Province 530021, PR China
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Mormina E, Petracca M, Bommarito G, Piaggio N, Cocozza S, Inglese M. Cerebellum and neurodegenerative diseases: Beyond conventional magnetic resonance imaging. World J Radiol 2017; 9:371-388. [PMID: 29104740 PMCID: PMC5661166 DOI: 10.4329/wjr.v9.i10.371] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2017] [Revised: 07/18/2017] [Accepted: 08/02/2017] [Indexed: 02/06/2023] Open
Abstract
The cerebellum plays a key role in movement control and in cognition and cerebellar involvement is described in several neurodegenerative diseases. While conventional magnetic resonance imaging (MRI) is widely used for brain and cerebellar morphologic evaluation, advanced MRI techniques allow the investigation of cerebellar microstructural and functional characteristics. Volumetry, voxel-based morphometry, diffusion MRI based fiber tractography, resting state and task related functional MRI, perfusion, and proton MR spectroscopy are among the most common techniques applied to the study of cerebellum. In the present review, after providing a brief description of each technique’s advantages and limitations, we focus on their application to the study of cerebellar injury in major neurodegenerative diseases, such as multiple sclerosis, Parkinson’s and Alzheimer’s disease and hereditary ataxia. A brief introduction to the pathological substrate of cerebellar involvement is provided for each disease, followed by the review of MRI studies exploring structural and functional cerebellar abnormalities and by a discussion of the clinical relevance of MRI measures of cerebellar damage in terms of both clinical status and cognitive performance.
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Affiliation(s)
- Enricomaria Mormina
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, United States
- Neuroradiology Unit, Department of Biomedical Sciences and Morphological and Functional Images, University of Messina, 98100 Messina, Italy
| | - Maria Petracca
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, United States
- Department of Neuroscience, Reproductive Sciences and Odontostomatology, University of Naples Federico II, 80138 Naples, Italy
| | - Giulia Bommarito
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, United States
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics and Maternal and Child Health (DINOGMI), University of Genoa, 16132 Genoa, Italy
| | - Niccolò Piaggio
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics and Maternal and Child Health (DINOGMI), University of Genoa, 16132 Genoa, Italy
- Department of Neuroradiology, San Martino Hospital, 16132 Genoa, Italy
| | - Sirio Cocozza
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, United States
- Department of Advanced Biomedical Sciences, University of Naples Federico II, 80138 Naples, Italy
| | - Matilde Inglese
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, United States
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics and Maternal and Child Health (DINOGMI), University of Genoa, 16132 Genoa, Italy
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Microstructural network alterations of olfactory dysfunction in newly diagnosed Parkinson's disease. Sci Rep 2017; 7:12559. [PMID: 28970540 PMCID: PMC5624890 DOI: 10.1038/s41598-017-12947-7] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2017] [Accepted: 09/12/2017] [Indexed: 12/28/2022] Open
Abstract
Olfactory dysfunction is a robust and early sign for Parkinson's disease (PD). Previous studies have revealed its association with dementia and related neural changes in PD. Yet, how olfactory dysfunction affects white matter (WM) microstructure in newly diagnosed and untreated PD remains unclear. Here we comprehensively examined WM features using unbiased whole-brain analyses. 88 newly diagnosed PD patients without dementia (70 with hyposmia and 18 without hyposmia) and 33 healthy controls underwent clinical assessment and diffusion tensor imaging (DTI) scanning. Tract-based special statistics (TBSS), graph-theoretic methods and network-based statistics (NBS) were used to compare regional and network-related WM features between groups. TBSS analysis did not show any differences in fractional anisotropy and mean diffusivity between groups. Compared with controls, PD patients without hyposmia showed a significant decrease in global efficiency, whilst PD patients with hyposmia exhibited significantly reduced global and local efficiency and additionally a disrupted connection between the right medial orbitofrontal cortex and left rectus and had poorer frontal-related cognitive functioning. These results demonstrate that hyposmia-related WM changes in early PD only occur at the network level. The confined disconnectivity between the bilateral olfactory circuitry may serve as a biomarker for olfactory dysfunction in early PD.
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de Oliveira RV, Pereira JS. The role of diffusion magnetic resonance imaging in Parkinson's disease and in the differential diagnosis with atypical parkinsonism. Radiol Bras 2017; 50:250-257. [PMID: 28894333 PMCID: PMC5586516 DOI: 10.1590/0100-3984.2016-0073] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/23/2023] Open
Abstract
Parkinson's disease is one of the most common neurodegenerative diseases.
Clinically, it is characterized by motor symptoms. Parkinson's disease should be
differentiated from atypical parkinsonism conditions. Conventional magnetic
resonance imaging is the primary imaging method employed in order to facilitate
the differential diagnosis, and its role has grown after the development of
advanced techniques such as diffusion-weighted imaging. The purpose of this
article was to review the role of magnetic resonance imaging in Parkinson's
disease and in the differential diagnosis with atypical parkinsonism,
emphasizing the diffusion technique.
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Affiliation(s)
- Romulo Varella de Oliveira
- Full Member of the Colégio Brasileiro de Radiologia e Diagnóstico por Imagem (CBR), Masters Student in the Graduate Program in Medical Sciences at the Faculdade de Ciências Médicas da Universidade do Estado do Rio de Janeiro (FCM-UERJ), MD, Radiologist at the Hospital Universitário Pedro Ernesto (HUPE) and at the Clínica Alta Excelência Diagnóstica (DASA), Rio de Janeiro, RJ, Brazil
| | - João Santos Pereira
- PhD, Full Member of the Academia Brasileira de Neurologia (ABN), Associate Professor, Coordinator of the Movement Disorders Sector of the Neurology Department of the Hospital Universitário Pedro Ernesto da Universidade do Estado do Rio de Janeiro (HUPE-UERJ), Rio de Janeiro, RJ, Brazil
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Shah A, Lenka A, Saini J, Wagle S, Naduthota RM, Yadav R, Pal PK, Ingalhalikar M. Altered Brain Wiring in Parkinson's Disease: A Structural Connectome-Based Analysis. Brain Connect 2017; 7:347-356. [DOI: 10.1089/brain.2017.0506] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Affiliation(s)
- Apurva Shah
- Department of Electronics and Telecommunications, Symbiosis Institute of Technology, Symbiosis International University, Pune, India
| | - Abhishek Lenka
- Department of Neurology, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, India
| | - Jitender Saini
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, India
| | - Shivali Wagle
- Department of Electronics and Telecommunications, Symbiosis Institute of Technology, Symbiosis International University, Pune, India
| | - Rajini M. Naduthota
- Department of Neurology, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, India
| | - Ravi Yadav
- Department of Neurology, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, India
| | - Pramod Kumar Pal
- Department of Neurology, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, India
| | - Madhura Ingalhalikar
- Department of Electronics and Telecommunications, Symbiosis Institute of Technology, Symbiosis International University, Pune, India
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Structural changes in Parkinson's disease: voxel-based morphometry and diffusion tensor imaging analyses based on 123I-MIBG uptake. Eur Radiol 2017; 27:5073-5079. [PMID: 28677058 DOI: 10.1007/s00330-017-4941-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2017] [Revised: 06/02/2017] [Accepted: 06/09/2017] [Indexed: 10/19/2022]
Abstract
OBJECTIVE Patients with Parkinson's disease (PD) may exhibit symptoms of sympathetic dysfunction that can be measured using 123I-metaiodobenzylguanidine (MIBG) myocardial scintigraphy. We investigated the relationship between microstructural brain changes and 123I-MIBG uptake in patients with PD using voxel-based morphometry (VBM) and diffusion tensor imaging (DTI) analyses. METHODS This retrospective study included 24 patients with PD who underwent 3 T magnetic resonance imaging and 123I-MIBG scintigraphy. They were divided into two groups: 12 MIBG-positive and 12 MIBG-negative cases (10 men and 14 women; age range: 60-81 years, corrected for gender and age). The heart/mediastinum count (H/M) ratio was calculated on anterior planar 123I-MIBG images obtained 4 h post-injection. VBM and DTI were performed to detect structural differences between these two groups. RESULTS Patients with low H/M ratio had significantly reduced brain volume at the right inferior frontal gyrus (uncorrected p < 0.0001, K > 90). Patients with low H/M ratios also exhibited significantly lower fractional anisotropy than those with high H/M ratios (p < 0.05) at the left anterior thalamic radiation, the left inferior fronto-occipital fasciculus, the left superior longitudinal fasciculus, and the left uncinate fasciculus. CONCLUSIONS VBM and DTI may reveal microstructural changes related to the degree of 123I-MIBG uptake in patients with PD. KEY POINTS • Advanced MRI methods may detect brain damage more precisely. • Voxel-based morphometry can detect grey matter changes in Parkinson's disease. • Diffusion tensor imaging can detect white matter changes in Parkinson's disease.
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Altered brain metabolic connectivity at multiscale level in early Parkinson's disease. Sci Rep 2017; 7:4256. [PMID: 28652595 PMCID: PMC5484707 DOI: 10.1038/s41598-017-04102-z] [Citation(s) in RCA: 58] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2017] [Accepted: 05/11/2017] [Indexed: 01/29/2023] Open
Abstract
To explore the effects of PD pathology on brain connectivity, we characterized with an emergent computational approach the brain metabolic connectome using [18F]FDG-PET in early idiopathic PD patients. We applied whole-brain and pathology-based connectivity analyses, using sparse-inverse covariance estimation in thirty-four cognitively normal PD cases and thirty-four age-matched healthy subjects for comparisons. Further, we assessed high-order resting state networks by interregional correlation analysis. Whole-brain analysis revealed altered metabolic connectivity in PD, with local decreases in frontolateral cortex and cerebellum and increases in the basal ganglia. Widespread long-distance decreases were present within the frontolateral cortex as opposed to connectivity increases in posterior cortical regions, all suggestive of a global-scale connectivity reconfiguration. The pathology-based analyses revealed significant connectivity impairment in the nigrostriatal dopaminergic pathway and in the regions early affected by α-synuclein pathology. Notably, significant connectivity changes were present in several resting state networks especially in frontal regions. These findings expand previous imaging evidence of altered connectivity in cognitively stable PD patients by showing pathology-based connectivity changes and disease-specific metabolic architecture reconfiguration at multiple scale levels, from the earliest PD phases. These alterations go well beyond the known striato-cortical connectivity derangement supporting in vivo an extended neural vulnerability in the PD synucleinopathy.
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Chiang PL, Chen HL, Lu CH, Chen PC, Chen MH, Yang IH, Tsai NW, Lin WC. White matter damage and systemic inflammation in Parkinson's disease. BMC Neurosci 2017; 18:48. [PMID: 28595572 PMCID: PMC5465562 DOI: 10.1186/s12868-017-0367-y] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2016] [Accepted: 05/31/2017] [Indexed: 01/02/2023] Open
Abstract
Background Systemic inflammation and white matter (WM) alterations have been noted as effects of Parkinson’s disease (PD). This study sought to evaluate WM integrity in PD patients using diffusion tensor imaging (DTI) and to assess its relationship with systemic inflammation. Methods Sixty-six patients with PD (23 men and 43 women) and 67 healthy volunteers (29 men and 38 women) underwent blood sampling to quantify inflammatory markers and DTI scans to determine fiber integrity. The inflammatory markers included leukocyte apoptosis, as well as cellular and serum adhesion molecules, in each peripheral blood sample. DTI-related indices [including fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD)] were derived from DTI scans. The resulting FA maps were compared using voxel-based statistics to determine differences between the PD and control groups. The differences in the DTI indices, clinical severity, and inflammatory markers were correlated. Results Exploratory group-wise comparison between the two groups revealed that the PD patients exhibited extensive DTI index differences. Low FA accompanied by high RD and MD, without significant differences in AD, suggesting a demyelination process, were found in the parietal, occipital, cerebellar, and insular WM of the PD patients. The declined DTI indices were significantly correlated with increased clinical disease severity, adhesion molecules, and leukocyte apoptosis. Conclusions Patients with PD experience WM integrity damage in vulnerable regions, and these impairments are associated with increased disease severity and systemic inflammation. The possible interactions among them may represent variant neuronal injuries and their consequent processes in PD. Electronic supplementary material The online version of this article (doi:10.1186/s12868-017-0367-y) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Pi-Ling Chiang
- Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, 123 Ta-Pei Road, Niao-Sung, Kaohsiung, 83305, Taiwan
| | - Hsiu-Ling Chen
- Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, 123 Ta-Pei Road, Niao-Sung, Kaohsiung, 83305, Taiwan
| | - Cheng-Hsien Lu
- Department of Neurology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan.,Department of Biological Science, National Sun Yat-Sen University, Kaohsiung, Taiwan
| | - Pei-Chin Chen
- Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, 123 Ta-Pei Road, Niao-Sung, Kaohsiung, 83305, Taiwan
| | - Meng-Hsiang Chen
- Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, 123 Ta-Pei Road, Niao-Sung, Kaohsiung, 83305, Taiwan
| | - I-Hsiao Yang
- Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, 123 Ta-Pei Road, Niao-Sung, Kaohsiung, 83305, Taiwan
| | - Nai-Wen Tsai
- Department of Neurology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Wei-Che Lin
- Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, 123 Ta-Pei Road, Niao-Sung, Kaohsiung, 83305, Taiwan.
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Imaging genetics approach to Parkinson's disease and its correlation with clinical score. Sci Rep 2017; 7:46700. [PMID: 28429747 PMCID: PMC5399369 DOI: 10.1038/srep46700] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2016] [Accepted: 03/24/2017] [Indexed: 12/27/2022] Open
Abstract
Parkinson's disease (PD) is a progressive neurodegenerative disorder associated with both underlying genetic factors and neuroimaging findings. Existing neuroimaging studies related to the genome in PD have mostly focused on certain candidate genes. The aim of our study was to construct a linear regression model using both genetic and neuroimaging features to better predict clinical scores compared to conventional approaches. We obtained neuroimaging and DNA genotyping data from a research database. Connectivity analysis was applied to identify neuroimaging features that could differentiate between healthy control (HC) and PD groups. A joint analysis of genetic and imaging information known as imaging genetics was applied to investigate genetic variants. We then compared the utility of combining different genetic variants and neuroimaging features for predicting the Movement Disorder Society-sponsored unified Parkinson's disease rating scale (MDS-UPDRS) in a regression framework. The associative cortex, motor cortex, thalamus, and pallidum showed significantly different connectivity between the HC and PD groups. Imaging genetics analysis identified PARK2, PARK7, HtrA2, GIGYRF2, and SNCA as genetic variants that are significantly associated with imaging phenotypes. A linear regression model combining genetic and neuroimaging features predicted the MDS-UPDRS with lower error and higher correlation with the actual MDS-UPDRS compared to other models using only genetic or neuroimaging information alone.
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Fjaeldstad A, Fernandes HM, Van Hartevelt TJ, Gleesborg C, Møller A, Ovesen T, Kringelbach ML. Brain fingerprints of olfaction: a novel structural method for assessing olfactory cortical networks in health and disease. Sci Rep 2017; 7:42534. [PMID: 28195241 PMCID: PMC5307346 DOI: 10.1038/srep42534] [Citation(s) in RCA: 65] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2016] [Accepted: 01/10/2017] [Indexed: 11/09/2022] Open
Abstract
Olfactory deficits are a common (often prodromal) symptom of neurodegenerative or psychiatric disorders. As such, olfaction could have great potential as an early biomarker of disease, for example using neuroimaging to investigate the breakdown of structural connectivity profile of the primary olfactory networks. We investigated the suitability for this purpose in two existing neuroimaging maps of olfactory networks. We found problems with both existing neuroimaging maps in terms of their structural connectivity to known secondary olfactory networks. Based on these findings, we were able to merge the existing maps to a new template map of olfactory networks with connections to all key secondary olfactory networks. We introduce a new method that combines diffusion tensor imaging with probabilistic tractography and pattern recognition techniques. This method can obtain comprehensive and reliable fingerprints of the structural connectivity underlying the neural processing of olfactory stimuli in normosmic adults. Combining the novel proposed method for structural fingerprinting with the template map of olfactory networks has great potential to be used for future neuroimaging investigations of olfactory function in disease. With time, the proposed method may even come to serve as structural biomarker for early detection of disease.
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Affiliation(s)
- A. Fjaeldstad
- Flavour Institute, Aarhus University, Aarhus, Denmark
- Department of Psychiatry, University of Oxford, Oxford, UK
- Department of Otorhinolaryngology, Regional Hospital Unit West Jutland, Holstebro, Denmark
- Center of Functionally Integrative Neuroscience, Aarhus University, Aarhus, Denmark
| | - H. M. Fernandes
- Flavour Institute, Aarhus University, Aarhus, Denmark
- Department of Psychiatry, University of Oxford, Oxford, UK
- Center of Functionally Integrative Neuroscience, Aarhus University, Aarhus, Denmark
- Center for Music in the Brain, Aarhus University, Aarhus, Denmark
| | - T. J. Van Hartevelt
- Flavour Institute, Aarhus University, Aarhus, Denmark
- Department of Psychiatry, University of Oxford, Oxford, UK
- Center of Functionally Integrative Neuroscience, Aarhus University, Aarhus, Denmark
- Center for Music in the Brain, Aarhus University, Aarhus, Denmark
| | - C. Gleesborg
- Flavour Institute, Aarhus University, Aarhus, Denmark
- Center of Functionally Integrative Neuroscience, Aarhus University, Aarhus, Denmark
| | - A. Møller
- Flavour Institute, Aarhus University, Aarhus, Denmark
- Center of Functionally Integrative Neuroscience, Aarhus University, Aarhus, Denmark
- Department of Nuclear Medicine & PET-Centre, Aarhus University Hospital, Aarhus, Denmark
| | - T. Ovesen
- Flavour Institute, Aarhus University, Aarhus, Denmark
- Department of Otorhinolaryngology, Regional Hospital Unit West Jutland, Holstebro, Denmark
| | - M. L. Kringelbach
- Flavour Institute, Aarhus University, Aarhus, Denmark
- Department of Psychiatry, University of Oxford, Oxford, UK
- Center of Functionally Integrative Neuroscience, Aarhus University, Aarhus, Denmark
- Center for Music in the Brain, Aarhus University, Aarhus, Denmark
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41
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Ehgoetz Martens KA, Lewis SJG. Pathology of behavior in PD: What is known and what is not? J Neurol Sci 2016; 374:9-16. [PMID: 28089250 DOI: 10.1016/j.jns.2016.12.062] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2016] [Accepted: 12/28/2016] [Indexed: 12/12/2022]
Abstract
Abnormal behavior in Parkinson's disease (PD) stems from a complex orchestration of impaired neural networks that result from PD-related neurodegeneration across multiple levels. Typically, cellular and tissue abnormalities generate neurochemical changes and disrupt specific regions of the brain, in turn creating impaired neural circuits and dysfunctional global networks. The objective of this chapter is to provide an overview of the array of pathological changes that have been linked to different behavioral symptoms of PD such as depression, anxiety, apathy, fatigue, impulse control disorders, psychosis, sleep disorders and dementia.
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Affiliation(s)
- Kaylena A Ehgoetz Martens
- Parkinson Disease Research Clinic, Brain and Mind Centre, University of Sydney, 100 Mallet Street, Camperdown, 2050, NSW, Australia.
| | - Simon J G Lewis
- Parkinson Disease Research Clinic, Brain and Mind Centre, University of Sydney, 100 Mallet Street, Camperdown, 2050, NSW, Australia
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42
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Jin Y, Huang C, Daianu M, Zhan L, Dennis EL, Reid RI, Jack CR, Zhu H, Thompson PM. 3D tract-specific local and global analysis of white matter integrity in Alzheimer's disease. Hum Brain Mapp 2016; 38:1191-1207. [PMID: 27883250 PMCID: PMC5299040 DOI: 10.1002/hbm.23448] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2016] [Revised: 10/13/2016] [Accepted: 10/13/2016] [Indexed: 12/04/2022] Open
Abstract
Alzheimer's disease (AD) is a chronic neurodegenerative disease characterized by progressive decline in memory and other aspects of cognitive function. Diffusion‐weighted imaging (DWI) offers a non‐invasive approach to delineate the effects of AD on white matter (WM) integrity. Previous studies calculated either some summary statistics over regions of interest (ROI analysis) or some statistics along mean skeleton lines (Tract Based Spatial Statistic [TBSS]), so they cannot quantify subtle local WM alterations along major tracts. Here, a comprehensive WM analysis framework to map disease effects on 3D tracts both locally and globally, based on a study of 200 subjects: 49 healthy elderly normal controls, 110 with mild cognitive impairment, and 41 AD patients has been presented. 18 major WM tracts were extracted with our automated clustering algorithm—autoMATE (automated Multi‐Atlas Tract Extraction); we then extracted multiple DWI‐derived parameters of WM integrity along the WM tracts across all subjects. A novel statistical functional analysis method—FADTTS (Functional Analysis for Diffusion Tensor Tract Statistics) was applied to quantify degenerative patterns along WM tracts across different stages of AD. Gradually increasing WM alterations were found in all tracts in successive stages of AD. Among all 18 WM tracts, the fornix was most adversely affected. Among all the parameters, mean diffusivity (MD) was the most sensitive to WM alterations in AD. This study provides a systematic workflow to examine WM integrity across automatically computed 3D tracts in AD and may be useful in studying other neurological and psychiatric disorders. Hum Brain Mapp 38:1191–1207, 2017. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- Yan Jin
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, California.,Department of Biostatistics and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.,Department of Biostatistics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Chao Huang
- Department of Biostatistics and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Madelaine Daianu
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, California
| | - Liang Zhan
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, California.,Computer Engineering Program, University of Wisconsin-Stout, Menomonie, Wisconsin
| | - Emily L Dennis
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, California
| | - Robert I Reid
- Department of Information Technology, Mayo Clinic, Rochester, Minnesota
| | | | - Hongtu Zhu
- Department of Biostatistics and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.,Department of Biostatistics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, California.,Departments of Neurology, Psychiatry, Pediatrics, Radiology, and Ophthalmology, Keck School of Medicine, University of Southern California, Los Angeles, California.,Viterbi School of Engineering, University of Southern California, Los Angeles, California
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43
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White matter microstructural characteristics in newly diagnosed Parkinson's disease: An unbiased whole-brain study. Sci Rep 2016; 6:35601. [PMID: 27762307 PMCID: PMC5071859 DOI: 10.1038/srep35601] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2016] [Accepted: 09/23/2016] [Indexed: 11/18/2022] Open
Abstract
Parkinson’s disease (PD) is a debilitating neurodegenerative disorder. Findings on specific white matter (WM) alterations in PD have been inconsistent. We hypothesized that WM changes occur in early PD patients and unbiased whole-brain analysis may provide additional evidence of pathological WM changes in PD. In this study, we examined various indexes of WM microstructure in newly diagnosed PD patients at the whole-brain level. 64 PDs with Hoehn & Yahr stage 1 (HY1PDs), 87 PDs with Hoehn & Yahr stage 2 (HYPD2s), and 60 controls (HCs) were recruited. Tract-based spatial statistics (TBSS) and diffusion connectometry were used to identify changes of WM pathways associated with PD. There were no significant differences in axial diffusivity, but HY1PDs exhibited greater fractional anisotropy (FA) and decreased mean and radial diffusivities (MD and RD) in callosal, projection, and association fibres than HCs and HY2PDs. Motor severity was inversely correlated with FA, but positively correlated with MD and RD in PD patients. Connectometry analysis also revealed increased WM density in the aforementioned tracts in PD patients, compared with HCs. Our study reveals WM enhancement, suggesting neural compensations in early PD. Longitudinal follow-up studies are warranted to identify the trajectory of WM changes alongside the progression of PD.
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44
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Hall JM, Ehgoetz Martens KA, Walton CC, O'Callaghan C, Keller PE, Lewis SJG, Moustafa AA. Diffusion alterations associated with Parkinson's disease symptomatology: A review of the literature. Parkinsonism Relat Disord 2016; 33:12-26. [PMID: 27765426 DOI: 10.1016/j.parkreldis.2016.09.026] [Citation(s) in RCA: 49] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/21/2016] [Revised: 07/28/2016] [Accepted: 09/26/2016] [Indexed: 01/06/2023]
Abstract
Parkinson's disease (PD) is a heterogeneous neurological disorder with a variety of motor and non-motor symptoms. The underlying mechanisms of these symptoms are not fully understood. An increased interest in structural connectivity analyses using diffusion tensor imaging (DTI) in PD has led to an expansion of our understanding of the impact of abnormalities in diffusivity on phenotype. This review outlines the contribution of these abnormalities to symptoms of PD including bradykinesia, tremor and non-tremor phenotypes, freezing of gait, cognitive impairment, mood, sleep disturbances, visual hallucinations and olfactory dysfunction. Studies have shown that impairments in cognitive functioning are related to diffusion abnormalities in frontal and parietal regions, as well as in the corpus callosum and major fibres connecting midbrain and subcortical structures with the neocortex. However, the impact of diffusion alterations on motor, mood and other symptoms of PD are less well understood. The findings presented here highlight the challenges faced and the potential areas of future research avenues where DTI may be beneficial. Larger cohort studies and standardized imaging protocols are required to investigate current promising preliminary findings.
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Affiliation(s)
- Julie M Hall
- Brain and Mind Centre, University of Sydney, Sydney, Australia; School of Social Sciences and Psychology, Western Sydney University, Sydney, Australia
| | | | | | - Claire O'Callaghan
- Brain and Mind Centre, University of Sydney, Sydney, Australia; Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, United Kingdom; Department of Psychology, University of Cambridge, Cambridge, UK
| | - Peter E Keller
- MARCS Institute, Western Sydney University, Sydney, Australia
| | - Simon J G Lewis
- Brain and Mind Centre, University of Sydney, Sydney, Australia.
| | - Ahmed A Moustafa
- School of Social Sciences and Psychology, Western Sydney University, Sydney, Australia; MARCS Institute, Western Sydney University, Sydney, Australia
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45
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Differentiating Patients with Parkinson’s Disease from Normal Controls Using Gray Matter in the Cerebellum. THE CEREBELLUM 2016; 16:151-157. [DOI: 10.1007/s12311-016-0781-1] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
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46
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Multimodal MRI Evaluation of the MitoPark Mouse Model of Parkinson's Disease. PLoS One 2016; 11:e0151884. [PMID: 27003179 PMCID: PMC4803323 DOI: 10.1371/journal.pone.0151884] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2015] [Accepted: 03/04/2016] [Indexed: 01/10/2023] Open
Abstract
The MitoPark mouse, a relatively new genetic model of Parkinson’s disease (PD), has a dopaminergic neuron-specific knock-out that inactivates the mitochondrial transcription factor A (Tfam), a protein essential for mitochondrial DNA expression and maintenance. This study used multimodal MRI to characterize the neuroanatomical correlates of PD-related deficits in MitoPark mice, along with functional behavioral tests. Compared with age-matched wild-type animals, MitoPark mice at 30 weeks showed: i) reduced whole-brain volume and increased ventricular volume, indicative of brain atrophy, ii) reduced transverse relaxation time (T2*) of the substantia nigra and striatum, suggestive of abnormal iron accumulation, iii) reduced apparent diffusion coefficient in the substantia nigra, suggestive of neuronal loss, iv) reduced fractional anisotropy in the corpus callosum and substantia nigra, indicative of white-matter damages, v) cerebral blood flow was not significantly affected, and vi) reduced motor activity in open-field tests, reduced memory in novel object recognition tests, as well as decreased mobility in tail suspension tests, an indication of depression. In sum, MitoPark mice recapitulate changes in many MRI parameters reported in PD patients. Multimodal MRI may prove useful for evaluating neuroanatomical correlates of PD pathophysiology in MitoPark mice, and for longitudinally monitoring disease progression and therapeutic interventions for PD.
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47
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Using Tractography to Distinguish SWEDD from Parkinson's Disease Patients Based on Connectivity. PARKINSONS DISEASE 2016; 2016:8704910. [PMID: 27034889 PMCID: PMC4789533 DOI: 10.1155/2016/8704910] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/28/2015] [Revised: 02/03/2016] [Accepted: 02/10/2016] [Indexed: 11/18/2022]
Abstract
Background. It is critical to distinguish between Parkinson's disease (PD) and scans without evidence of dopaminergic deficit (SWEDD), because the two groups are different and require different therapeutic approaches. Objective. The aim of this study was to distinguish SWEDD patients from PD patients using connectivity information derived from diffusion tensor imaging tractography. Methods. Diffusion magnetic resonance images of SWEDD (n = 37) and PD (n = 40) were obtained from a research database. Tractography, the process of obtaining neural fiber information, was performed using custom software. Group-wise differences between PD and SWEDD patients were quantified using the number of connected fibers between two regions, and correlation analyses were performed based on clinical scores. A support vector machine classifier (SVM) was applied to distinguish PD and SWEDD based on group-wise differences. Results. Four connections showed significant group-wise differences and correlated with the Unified Parkinson's Disease Rating Scale sponsored by the Movement Disorder Society. The SVM classifier attained 77.92% accuracy in distinguishing between SWEDD and PD using these identified connections. Conclusions. The connections and regions identified represent candidates for future research investigations.
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48
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Kassubek J, Müller HP. Computer-based magnetic resonance imaging as a tool in clinical diagnosis in neurodegenerative diseases. Expert Rev Neurother 2016; 16:295-306. [PMID: 26807776 DOI: 10.1586/14737175.2016.1146590] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Magnetic resonance imaging (MRI) is one of the core elements within the differential diagnostic work-up of patients with neurodegenerative diseases such as dementia syndromes, Parkinsonian syndromes, and motor neuron diseases. Currently, computerized MRI analyses are not routinely used for individual diagnosis; however, they have improved the anatomical understanding of pathomorphological alterations in various neurodegenerative diseases by quantitative comparisons between patients and controls at the group level. For multiparametric MRI protocols, including T1-weighted MRI, diffusion-weighted imaging, and intrinsic functional connectivity MRI, the potential as a surrogate marker is a subject of investigation. The additional value of MRI with respect to diagnosis at the individual level and for future disease-modifying multicentre trials remains to be defined. Here, we give an overview of recent applications of multiparametric MRI to patients with various neurodegenerative diseases. Starting from applications at the group level, continuous progress of a transfer to individual diagnostic classification is ongoing.
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Affiliation(s)
- Jan Kassubek
- a Department of Neurology , University of Ulm , Ulm , Germany
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49
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Diffusion tensor imaging of the extracorticospinal network in the brains of patients with Wilson disease. J Neurol Sci 2016; 362:292-8. [PMID: 26944166 DOI: 10.1016/j.jns.2016.02.006] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2015] [Revised: 01/20/2016] [Accepted: 02/02/2016] [Indexed: 12/13/2022]
Abstract
OBJECTIVE To evaluate damage to the extracorticospinal tract in Wilson disease (WD) patients using diffusion tensor imaging (DTI). METHODS 70 patients with WD, including 50 with cerebral type and 20 with hepatic type, and 20 age-matched healthy controls were enrolled. Neurological symptoms were scored using the modified Young Scale. Patients with cerebral type WD were divided into four subgroups: those with (1) hypokinesia, (2) parkinsonism, (3) mouth and throat dystonia, and (4) psychiatric symptoms. All study subjects underwent DTI of the brain. Five regions of interest (ROIs) were chosen. Fractional anisotropy (FA) and fiber volumes between ROIs were determined, and the relationships between DTI metrics and clinical status were evaluated. RESULTS FA values and fiber volumes between subcortical nuclei were lower in WD patients. Fiber volumes between the putamen (PU) and the globus pallidus (GP), substantia nigra (SN), and thalamus (TH); between the head of the caudate nucleus (CA) and the GP and TH; and between the TH and cerebellum were lower in group 1 than in the other groups of WD patients. Fiber volumes between the GP and the SN and TH were lower in group 2, and fiber volumes between the SN and TH were lower in group 3. DTI metrics differed between patients with the cerebral and hepatic types of WD. CONCLUSIONS DTI can reconstruct the network of the extracorticospinal tract. Fiber projection between subcortical nuclei was abnormal in WD patients. Damage to fiber connections may correlate with neurological symptoms in WD patients.
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50
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Planetta PJ, Ofori E, Pasternak O, Burciu RG, Shukla P, DeSimone JC, Okun MS, McFarland NR, Vaillancourt DE. Free-water imaging in Parkinson's disease and atypical parkinsonism. Brain 2015; 139:495-508. [PMID: 26705348 DOI: 10.1093/brain/awv361] [Citation(s) in RCA: 148] [Impact Index Per Article: 16.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2015] [Accepted: 10/26/2015] [Indexed: 12/11/2022] Open
Abstract
Conventional single tensor diffusion analysis models have provided mixed findings in the substantia nigra of Parkinson's disease, but recent work using a bi-tensor analysis model has shown more promising results. Using a bi-tensor model, free-water values were found to be increased in the posterior substantia nigra of Parkinson's disease compared with controls at a single site and in a multi-site cohort. Further, free-water increased longitudinally over 1 year in the posterior substantia nigra of Parkinson's disease. Here, we test the hypothesis that other parkinsonian disorders such as multiple system atrophy and progressive supranuclear palsy have elevated free-water in the substantia nigra. Equally important, however, is whether the bi-tensor diffusion model is able to detect alterations in other brain regions beyond the substantia nigra in Parkinson's disease, multiple system atrophy, and progressive supranuclear palsy and to accurately distinguish between these diseases. Free-water and free-water-corrected fractional anisotropy maps were compared across 72 individuals in the basal ganglia, midbrain, thalamus, dentate nucleus, cerebellar peduncles, cerebellar vermis and lobules V and VI, and corpus callosum. Compared with controls, free-water was increased in the anterior and posterior substantia nigra of Parkinson's disease, multiple system atrophy, and progressive supranuclear palsy. Despite no other changes in Parkinson's disease, we observed elevated free-water in all regions except the dentate nucleus, subthalamic nucleus, and corpus callosum of multiple system atrophy, and in all regions examined for progressive supranuclear palsy. Compared with controls, free-water-corrected fractional anisotropy values were increased for multiple system atrophy in the putamen and caudate, and increased for progressive supranuclear palsy in the putamen, caudate, thalamus, and vermis, and decreased in the superior cerebellar peduncle and corpus callosum. For all disease group comparisons, the support vector machine 10-fold cross-validation area under the curve was between 0.93-1.00 and there was high sensitivity and specificity. The regions and diffusion measures selected by the model varied across comparisons and are consistent with pathological studies. In conclusion, the current study used a novel bi-tensor diffusion analysis model to indicate that all forms of parkinsonism had elevated free-water in the substantia nigra. Beyond the substantia nigra, both multiple system atrophy and progressive supranuclear palsy, but not Parkinson's disease, showed a broad network of elevated free-water and altered free-water corrected fractional anisotropy that included the basal ganglia, thalamus, and cerebellum. These findings may be helpful in the differential diagnosis of parkinsonian disorders, and thereby facilitate the development and assessment of targeted therapies.
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Affiliation(s)
- Peggy J Planetta
- 1 Department of Applied Physiology and Kinesiology, University of Florida, USA
| | - Edward Ofori
- 1 Department of Applied Physiology and Kinesiology, University of Florida, USA
| | - Ofer Pasternak
- 2 Departments of Psychiatry and Radiology, Brigham and Women's Hospital, Harvard Medical School, USA
| | - Roxana G Burciu
- 1 Department of Applied Physiology and Kinesiology, University of Florida, USA
| | - Priyank Shukla
- 1 Department of Applied Physiology and Kinesiology, University of Florida, USA
| | - Jesse C DeSimone
- 1 Department of Applied Physiology and Kinesiology, University of Florida, USA
| | - Michael S Okun
- 3 Center for Movement Disorders and Neurorestoration, University of Florida, USA 4 Department of Neurology, University of Florida, USA 5 Department of Neurosurgery, University of Florida, USA
| | - Nikolaus R McFarland
- 3 Center for Movement Disorders and Neurorestoration, University of Florida, USA 4 Department of Neurology, University of Florida, USA
| | - David E Vaillancourt
- 1 Department of Applied Physiology and Kinesiology, University of Florida, USA 4 Department of Neurology, University of Florida, USA 6 Department of Biomedical Engineering, University of Florida, USA
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