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Imaging analysis of Parkinson’s disease patients using SPECT and tractography
Parkinson’s disease (PD) is a degenerative disorder that affects the central nervous system. PD-related alterations in structural and functional neuroimaging have not been fully explored. This study explored multi-modal PD neuroimaging and its application for predicting clinical scores on the Moveme...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5128922/ https://www.ncbi.nlm.nih.gov/pubmed/27901100 http://dx.doi.org/10.1038/srep38070 |
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author | Son, Seong-Jin Kim, Mansu Park, Hyunjin |
author_facet | Son, Seong-Jin Kim, Mansu Park, Hyunjin |
author_sort | Son, Seong-Jin |
collection | PubMed |
description | Parkinson’s disease (PD) is a degenerative disorder that affects the central nervous system. PD-related alterations in structural and functional neuroimaging have not been fully explored. This study explored multi-modal PD neuroimaging and its application for predicting clinical scores on the Movement Disorder Society-sponsored Unified Parkinson’s Disease Rating Scale (MDS-UPDRS). Multi-modal imaging that combined (123)I-Ioflupane single-photon emission computed tomography (SPECT) and diffusion tensor imaging (DTI) were adopted to incorporate complementary brain imaging information. SPECT and DTI images of normal controls (NC; n = 45) and PD patients (n = 45) were obtained from a database. The specific binding ratio (SBR) was calculated from SPECT. Tractography was performed using DTI. Group-wise differences between NC and PD patients were quantified using SBR of SPECT and structural connectivity of DTI for regions of interest (ROIs) related to PD. MDS-UPDRS scores were predicted using multi-modal imaging features in a partial least-squares regression framework. Three regions and four connections within the cortico-basal ganglia thalamocortical circuit were identified using SBR and DTI, respectively. Predicted MDS-UPDRS scores using identified regions and connections and actual MDS-UPDRS scores showed a meaningful correlation (r = 0.6854, p < 0.001). Our study provided insight on regions and connections that are instrumental in PD. |
format | Online Article Text |
id | pubmed-5128922 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-51289222016-12-15 Imaging analysis of Parkinson’s disease patients using SPECT and tractography Son, Seong-Jin Kim, Mansu Park, Hyunjin Sci Rep Article Parkinson’s disease (PD) is a degenerative disorder that affects the central nervous system. PD-related alterations in structural and functional neuroimaging have not been fully explored. This study explored multi-modal PD neuroimaging and its application for predicting clinical scores on the Movement Disorder Society-sponsored Unified Parkinson’s Disease Rating Scale (MDS-UPDRS). Multi-modal imaging that combined (123)I-Ioflupane single-photon emission computed tomography (SPECT) and diffusion tensor imaging (DTI) were adopted to incorporate complementary brain imaging information. SPECT and DTI images of normal controls (NC; n = 45) and PD patients (n = 45) were obtained from a database. The specific binding ratio (SBR) was calculated from SPECT. Tractography was performed using DTI. Group-wise differences between NC and PD patients were quantified using SBR of SPECT and structural connectivity of DTI for regions of interest (ROIs) related to PD. MDS-UPDRS scores were predicted using multi-modal imaging features in a partial least-squares regression framework. Three regions and four connections within the cortico-basal ganglia thalamocortical circuit were identified using SBR and DTI, respectively. Predicted MDS-UPDRS scores using identified regions and connections and actual MDS-UPDRS scores showed a meaningful correlation (r = 0.6854, p < 0.001). Our study provided insight on regions and connections that are instrumental in PD. Nature Publishing Group 2016-11-30 /pmc/articles/PMC5128922/ /pubmed/27901100 http://dx.doi.org/10.1038/srep38070 Text en Copyright © 2016, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Son, Seong-Jin Kim, Mansu Park, Hyunjin Imaging analysis of Parkinson’s disease patients using SPECT and tractography |
title | Imaging analysis of Parkinson’s disease patients using SPECT and tractography |
title_full | Imaging analysis of Parkinson’s disease patients using SPECT and tractography |
title_fullStr | Imaging analysis of Parkinson’s disease patients using SPECT and tractography |
title_full_unstemmed | Imaging analysis of Parkinson’s disease patients using SPECT and tractography |
title_short | Imaging analysis of Parkinson’s disease patients using SPECT and tractography |
title_sort | imaging analysis of parkinson’s disease patients using spect and tractography |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5128922/ https://www.ncbi.nlm.nih.gov/pubmed/27901100 http://dx.doi.org/10.1038/srep38070 |
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