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Signal quality as Achilles’ heel of graph theory in functional magnetic resonance imaging in multiple sclerosis
Graph-theoretical analysis is a novel tool to understand the organisation of the brain. We assessed whether altered graph theoretical parameters, as observed in multiple sclerosis (MS), reflect pathology-induced restructuring of the brain's functioning or result from a reduced signal quality in...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8016888/ https://www.ncbi.nlm.nih.gov/pubmed/33795779 http://dx.doi.org/10.1038/s41598-021-86792-0 |
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author | Baijot, Johan Denissen, Stijn Costers, Lars Gielen, Jeroen Cambron, Melissa D’Haeseleer, Miguel D’hooghe, Marie B. Vanbinst, Anne-Marie De Mey, Johan Nagels, Guy Van Schependom, Jeroen |
author_facet | Baijot, Johan Denissen, Stijn Costers, Lars Gielen, Jeroen Cambron, Melissa D’Haeseleer, Miguel D’hooghe, Marie B. Vanbinst, Anne-Marie De Mey, Johan Nagels, Guy Van Schependom, Jeroen |
author_sort | Baijot, Johan |
collection | PubMed |
description | Graph-theoretical analysis is a novel tool to understand the organisation of the brain. We assessed whether altered graph theoretical parameters, as observed in multiple sclerosis (MS), reflect pathology-induced restructuring of the brain's functioning or result from a reduced signal quality in functional MRI (fMRI). In a cohort of 49 people with MS and a matched group of 25 healthy subjects (HS), we performed a cognitive evaluation and acquired fMRI. From the fMRI measurement, Pearson correlation-based networks were calculated and graph theoretical parameters reflecting global and local brain organisation were obtained. Additionally, we assessed metrics of scanning quality (signal to noise ratio (SNR)) and fMRI signal quality (temporal SNR and contrast to noise ratio (CNR)). In accordance with the literature, we found that the network parameters were altered in MS compared to HS. However, no significant link was found with cognition. Scanning quality (SNR) did not differ between both cohorts. In contrast, measures of fMRI signal quality were significantly different and explained the observed differences in GTA parameters. Our results suggest that differences in network parameters between MS and HS in fMRI do not reflect a functional reorganisation of the brain, but rather occur due to reduced fMRI signal quality. |
format | Online Article Text |
id | pubmed-8016888 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-80168882021-04-05 Signal quality as Achilles’ heel of graph theory in functional magnetic resonance imaging in multiple sclerosis Baijot, Johan Denissen, Stijn Costers, Lars Gielen, Jeroen Cambron, Melissa D’Haeseleer, Miguel D’hooghe, Marie B. Vanbinst, Anne-Marie De Mey, Johan Nagels, Guy Van Schependom, Jeroen Sci Rep Article Graph-theoretical analysis is a novel tool to understand the organisation of the brain. We assessed whether altered graph theoretical parameters, as observed in multiple sclerosis (MS), reflect pathology-induced restructuring of the brain's functioning or result from a reduced signal quality in functional MRI (fMRI). In a cohort of 49 people with MS and a matched group of 25 healthy subjects (HS), we performed a cognitive evaluation and acquired fMRI. From the fMRI measurement, Pearson correlation-based networks were calculated and graph theoretical parameters reflecting global and local brain organisation were obtained. Additionally, we assessed metrics of scanning quality (signal to noise ratio (SNR)) and fMRI signal quality (temporal SNR and contrast to noise ratio (CNR)). In accordance with the literature, we found that the network parameters were altered in MS compared to HS. However, no significant link was found with cognition. Scanning quality (SNR) did not differ between both cohorts. In contrast, measures of fMRI signal quality were significantly different and explained the observed differences in GTA parameters. Our results suggest that differences in network parameters between MS and HS in fMRI do not reflect a functional reorganisation of the brain, but rather occur due to reduced fMRI signal quality. Nature Publishing Group UK 2021-04-01 /pmc/articles/PMC8016888/ /pubmed/33795779 http://dx.doi.org/10.1038/s41598-021-86792-0 Text en © The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Baijot, Johan Denissen, Stijn Costers, Lars Gielen, Jeroen Cambron, Melissa D’Haeseleer, Miguel D’hooghe, Marie B. Vanbinst, Anne-Marie De Mey, Johan Nagels, Guy Van Schependom, Jeroen Signal quality as Achilles’ heel of graph theory in functional magnetic resonance imaging in multiple sclerosis |
title | Signal quality as Achilles’ heel of graph theory in functional magnetic resonance imaging in multiple sclerosis |
title_full | Signal quality as Achilles’ heel of graph theory in functional magnetic resonance imaging in multiple sclerosis |
title_fullStr | Signal quality as Achilles’ heel of graph theory in functional magnetic resonance imaging in multiple sclerosis |
title_full_unstemmed | Signal quality as Achilles’ heel of graph theory in functional magnetic resonance imaging in multiple sclerosis |
title_short | Signal quality as Achilles’ heel of graph theory in functional magnetic resonance imaging in multiple sclerosis |
title_sort | signal quality as achilles’ heel of graph theory in functional magnetic resonance imaging in multiple sclerosis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8016888/ https://www.ncbi.nlm.nih.gov/pubmed/33795779 http://dx.doi.org/10.1038/s41598-021-86792-0 |
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