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Microstructural abnormalities of substantia nigra in Parkinson's disease: A neuromelanin sensitive MRI atlas based study
Microstructural changes associated with degeneration of dopaminergic neurons of the substantia nigra pars compacta (SNc) in Parkinson's disease (PD) have been studied using Diffusion Tensor Imaging (DTI). However, these studies show inconsistent results, mainly due to methodological variations...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons, Inc.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7267920/ https://www.ncbi.nlm.nih.gov/pubmed/31778276 http://dx.doi.org/10.1002/hbm.24878 |
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author | Safai, Apoorva Prasad, Shweta Chougule, Tanay Saini, Jitender Pal, Pramod K. Ingalhalikar, Madhura |
author_facet | Safai, Apoorva Prasad, Shweta Chougule, Tanay Saini, Jitender Pal, Pramod K. Ingalhalikar, Madhura |
author_sort | Safai, Apoorva |
collection | PubMed |
description | Microstructural changes associated with degeneration of dopaminergic neurons of the substantia nigra pars compacta (SNc) in Parkinson's disease (PD) have been studied using Diffusion Tensor Imaging (DTI). However, these studies show inconsistent results, mainly due to methodological variations in delineation of SNc. To mitigate this, our work aims to construct a probabilistic atlas of SNc based on a 3D Neuromelanin Sensitive MRI (NMS‐MRI) sequence and demonstrate its applicability to investigate microstructural changes on a large dataset of PD. Using manual segmentation and deformable registration we created a novel SNc atlas in the MNI space using NMS‐MRI sequences of 27 healthy controls (HC). We first quantitatively evaluated this atlas and then employed it to investigate the micro‐structural abnormalities in SNc using diffusion MRI from 133 patients with PD and 99 HCs. Our results demonstrated significant increase in diffusivity with no changes in anisotropy. In addition, we also observed an asymmetry of the diffusion metrics with a higher diffusivity and lower anisotropy in the left SNc than the right. Finally, a multivariate classifier based on SNc diffusion features could delineate patients with PD with an average accuracy of 71.7%. Overall, from this work we establish a normative baseline for the SNc region of interest using NMS‐MRI while the application on PD data emphasizes on the contribution of diffusivity measures rather than anisotropy of white matter in PD. |
format | Online Article Text |
id | pubmed-7267920 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | John Wiley & Sons, Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-72679202020-06-12 Microstructural abnormalities of substantia nigra in Parkinson's disease: A neuromelanin sensitive MRI atlas based study Safai, Apoorva Prasad, Shweta Chougule, Tanay Saini, Jitender Pal, Pramod K. Ingalhalikar, Madhura Hum Brain Mapp Research Articles Microstructural changes associated with degeneration of dopaminergic neurons of the substantia nigra pars compacta (SNc) in Parkinson's disease (PD) have been studied using Diffusion Tensor Imaging (DTI). However, these studies show inconsistent results, mainly due to methodological variations in delineation of SNc. To mitigate this, our work aims to construct a probabilistic atlas of SNc based on a 3D Neuromelanin Sensitive MRI (NMS‐MRI) sequence and demonstrate its applicability to investigate microstructural changes on a large dataset of PD. Using manual segmentation and deformable registration we created a novel SNc atlas in the MNI space using NMS‐MRI sequences of 27 healthy controls (HC). We first quantitatively evaluated this atlas and then employed it to investigate the micro‐structural abnormalities in SNc using diffusion MRI from 133 patients with PD and 99 HCs. Our results demonstrated significant increase in diffusivity with no changes in anisotropy. In addition, we also observed an asymmetry of the diffusion metrics with a higher diffusivity and lower anisotropy in the left SNc than the right. Finally, a multivariate classifier based on SNc diffusion features could delineate patients with PD with an average accuracy of 71.7%. Overall, from this work we establish a normative baseline for the SNc region of interest using NMS‐MRI while the application on PD data emphasizes on the contribution of diffusivity measures rather than anisotropy of white matter in PD. John Wiley & Sons, Inc. 2019-11-28 /pmc/articles/PMC7267920/ /pubmed/31778276 http://dx.doi.org/10.1002/hbm.24878 Text en © 2019 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Articles Safai, Apoorva Prasad, Shweta Chougule, Tanay Saini, Jitender Pal, Pramod K. Ingalhalikar, Madhura Microstructural abnormalities of substantia nigra in Parkinson's disease: A neuromelanin sensitive MRI atlas based study |
title | Microstructural abnormalities of substantia nigra in Parkinson's disease: A neuromelanin sensitive MRI atlas based study |
title_full | Microstructural abnormalities of substantia nigra in Parkinson's disease: A neuromelanin sensitive MRI atlas based study |
title_fullStr | Microstructural abnormalities of substantia nigra in Parkinson's disease: A neuromelanin sensitive MRI atlas based study |
title_full_unstemmed | Microstructural abnormalities of substantia nigra in Parkinson's disease: A neuromelanin sensitive MRI atlas based study |
title_short | Microstructural abnormalities of substantia nigra in Parkinson's disease: A neuromelanin sensitive MRI atlas based study |
title_sort | microstructural abnormalities of substantia nigra in parkinson's disease: a neuromelanin sensitive mri atlas based study |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7267920/ https://www.ncbi.nlm.nih.gov/pubmed/31778276 http://dx.doi.org/10.1002/hbm.24878 |
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