Disrupted structural connectivity of fronto-deep gray matter pathways in progressive supranuclear palsy
Background: Structural connectivity is a promising methodology to detect patterns of neural network dysfunction in neurodegenerative diseases. This approach has not been tested in progressive supranuclear palsy (PSP). Objectives: The aim of this study is reconstructing the structural connectome to c...
| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2019-01-01
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| Series: | NeuroImage: Clinical |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2213158219302499 |
| _version_ | 1819229756196913152 |
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| author | Alexandra Abos Barbara Segura Hugo C. Baggio Anna Campabadal Carme Uribe Alicia Garrido Ana Camara Esteban Muñoz Francesc Valldeoriola Maria Jose Marti Carme Junque Yaroslau Compta |
| author_facet | Alexandra Abos Barbara Segura Hugo C. Baggio Anna Campabadal Carme Uribe Alicia Garrido Ana Camara Esteban Muñoz Francesc Valldeoriola Maria Jose Marti Carme Junque Yaroslau Compta |
| author_sort | Alexandra Abos |
| collection | DOAJ |
| description | Background: Structural connectivity is a promising methodology to detect patterns of neural network dysfunction in neurodegenerative diseases. This approach has not been tested in progressive supranuclear palsy (PSP). Objectives: The aim of this study is reconstructing the structural connectome to characterize and detect the pathways of degeneration in PSP patients compared with healthy controls and their correlation with clinical features. The second objective is to assess the potential of structural connectivity measures to distinguish between PSP patients and healthy controls at the single-subject level. Methods: Twenty healthy controls and 19 PSP patients underwent diffusion-weighted MRI with a 3T scanner. Structural connectivity, represented by number of streamlines, was derived from probabilistic tractography. Global and local network metrics were calculated based on graph theory. Results: Reduced numbers of streamlines were predominantly found in connections between frontal areas and deep gray matter (DGM) structures in PSP compared with controls. Significant changes in structural connectivity correlated with clinical features in PSP patients. An abnormal small-world architecture was detected in the subnetwork comprising the frontal lobe and DGM structures in PSP patients. The classification procedure achieved an overall accuracy of 82.23% with 94.74% sensitivity and 70% specificity. Conclusion: Our findings suggest that modelling the brain as a structural connectome is a useful method to detect changes in the organization and topology of white matter tracts in PSP patients. Secondly, measures of structural connectivity have the potential to correctly discriminate between PSP patients and healthy controls. Keywords: Progressive supranuclear palsy, Structural connectivity, Tractography, Graph theory |
| first_indexed | 2024-12-23T11:18:14Z |
| format | Article |
| id | doaj.art-3f0ac98415294268a76c440133d1e9ba |
| institution | Directory Open Access Journal |
| issn | 2213-1582 |
| language | English |
| last_indexed | 2024-12-23T11:18:14Z |
| publishDate | 2019-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | NeuroImage: Clinical |
| spelling | doaj.art-3f0ac98415294268a76c440133d1e9ba2022-12-21T17:49:10ZengElsevierNeuroImage: Clinical2213-15822019-01-0123Disrupted structural connectivity of fronto-deep gray matter pathways in progressive supranuclear palsyAlexandra Abos0Barbara Segura1Hugo C. Baggio2Anna Campabadal3Carme Uribe4Alicia Garrido5Ana Camara6Esteban Muñoz7Francesc Valldeoriola8Maria Jose Marti9Carme Junque10Yaroslau Compta11Medical Psychology Unit, Department of Medicine, Institute of Neuroscience, University of Barcelona.Barcelona, Catalonia, SpainMedical Psychology Unit, Department of Medicine, Institute of Neuroscience, University of Barcelona.Barcelona, Catalonia, Spain; Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Hospital Clínic de Barcelona. Barcelona, Catalonia, SpainMedical Psychology Unit, Department of Medicine, Institute of Neuroscience, University of Barcelona.Barcelona, Catalonia, SpainMedical Psychology Unit, Department of Medicine, Institute of Neuroscience, University of Barcelona.Barcelona, Catalonia, SpainMedical Psychology Unit, Department of Medicine, Institute of Neuroscience, University of Barcelona.Barcelona, Catalonia, SpainMovement Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Institute of Neuroscience, University of Barcelona, Barcelona, Catalonia, SpainMovement Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Institute of Neuroscience, University of Barcelona, Barcelona, Catalonia, SpainCentro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Hospital Clínic de Barcelona. Barcelona, Catalonia, Spain; Movement Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Institute of Neuroscience, University of Barcelona, Barcelona, Catalonia, Spain; Institute of Biomedical Research August Pi i Sunyer (IDIBAPS). Barcelona, Catalonia, SpainCentro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Hospital Clínic de Barcelona. Barcelona, Catalonia, Spain; Movement Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Institute of Neuroscience, University of Barcelona, Barcelona, Catalonia, Spain; Institute of Biomedical Research August Pi i Sunyer (IDIBAPS). Barcelona, Catalonia, SpainCentro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Hospital Clínic de Barcelona. Barcelona, Catalonia, Spain; Movement Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Institute of Neuroscience, University of Barcelona, Barcelona, Catalonia, Spain; Institute of Biomedical Research August Pi i Sunyer (IDIBAPS). Barcelona, Catalonia, SpainMedical Psychology Unit, Department of Medicine, Institute of Neuroscience, University of Barcelona.Barcelona, Catalonia, Spain; Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Hospital Clínic de Barcelona. Barcelona, Catalonia, Spain; Institute of Biomedical Research August Pi i Sunyer (IDIBAPS). Barcelona, Catalonia, SpainCentro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Hospital Clínic de Barcelona. Barcelona, Catalonia, Spain; Movement Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Institute of Neuroscience, University of Barcelona, Barcelona, Catalonia, Spain; Institute of Biomedical Research August Pi i Sunyer (IDIBAPS). Barcelona, Catalonia, Spain; Corresponding author at: Parkinson's Disease and Movement Disorders Unit of the Neurology Service of Hospital Clinic, Carrer de Villarroel 170, 08036 Barcelona, Catalonia, Spain.Background: Structural connectivity is a promising methodology to detect patterns of neural network dysfunction in neurodegenerative diseases. This approach has not been tested in progressive supranuclear palsy (PSP). Objectives: The aim of this study is reconstructing the structural connectome to characterize and detect the pathways of degeneration in PSP patients compared with healthy controls and their correlation with clinical features. The second objective is to assess the potential of structural connectivity measures to distinguish between PSP patients and healthy controls at the single-subject level. Methods: Twenty healthy controls and 19 PSP patients underwent diffusion-weighted MRI with a 3T scanner. Structural connectivity, represented by number of streamlines, was derived from probabilistic tractography. Global and local network metrics were calculated based on graph theory. Results: Reduced numbers of streamlines were predominantly found in connections between frontal areas and deep gray matter (DGM) structures in PSP compared with controls. Significant changes in structural connectivity correlated with clinical features in PSP patients. An abnormal small-world architecture was detected in the subnetwork comprising the frontal lobe and DGM structures in PSP patients. The classification procedure achieved an overall accuracy of 82.23% with 94.74% sensitivity and 70% specificity. Conclusion: Our findings suggest that modelling the brain as a structural connectome is a useful method to detect changes in the organization and topology of white matter tracts in PSP patients. Secondly, measures of structural connectivity have the potential to correctly discriminate between PSP patients and healthy controls. Keywords: Progressive supranuclear palsy, Structural connectivity, Tractography, Graph theoryhttp://www.sciencedirect.com/science/article/pii/S2213158219302499 |
| spellingShingle | Alexandra Abos Barbara Segura Hugo C. Baggio Anna Campabadal Carme Uribe Alicia Garrido Ana Camara Esteban Muñoz Francesc Valldeoriola Maria Jose Marti Carme Junque Yaroslau Compta Disrupted structural connectivity of fronto-deep gray matter pathways in progressive supranuclear palsy NeuroImage: Clinical |
| title | Disrupted structural connectivity of fronto-deep gray matter pathways in progressive supranuclear palsy |
| title_full | Disrupted structural connectivity of fronto-deep gray matter pathways in progressive supranuclear palsy |
| title_fullStr | Disrupted structural connectivity of fronto-deep gray matter pathways in progressive supranuclear palsy |
| title_full_unstemmed | Disrupted structural connectivity of fronto-deep gray matter pathways in progressive supranuclear palsy |
| title_short | Disrupted structural connectivity of fronto-deep gray matter pathways in progressive supranuclear palsy |
| title_sort | disrupted structural connectivity of fronto deep gray matter pathways in progressive supranuclear palsy |
| url | http://www.sciencedirect.com/science/article/pii/S2213158219302499 |
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