Signal quality as Achilles’ heel of graph theory in functional magnetic resonance imaging in multiple sclerosis

Abstract 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 q...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Johan Baijot, Stijn Denissen, Lars Costers, Jeroen Gielen, Melissa Cambron, Miguel D’Haeseleer, Marie B. D’hooghe, Anne-Marie Vanbinst, Johan De Mey, Guy Nagels, Jeroen Van Schependom
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/cea2d44cd7fc4326ac81b21ee7d45d63
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:cea2d44cd7fc4326ac81b21ee7d45d63
record_format	dspace
spelling	oai:doaj.org-article:cea2d44cd7fc4326ac81b21ee7d45d632021-12-02T14:25:26ZSignal quality as Achilles’ heel of graph theory in functional magnetic resonance imaging in multiple sclerosis10.1038/s41598-021-86792-02045-2322https://doaj.org/article/cea2d44cd7fc4326ac81b21ee7d45d632021-04-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-86792-0https://doaj.org/toc/2045-2322Abstract 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.Johan BaijotStijn DenissenLars CostersJeroen GielenMelissa CambronMiguel D’HaeseleerMarie B. D’hoogheAnne-Marie VanbinstJohan De MeyGuy NagelsJeroen Van SchependomNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-9 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Johan Baijot Stijn Denissen Lars Costers Jeroen Gielen Melissa Cambron Miguel D’Haeseleer Marie B. D’hooghe Anne-Marie Vanbinst Johan De Mey Guy Nagels Jeroen Van Schependom Signal quality as Achilles’ heel of graph theory in functional magnetic resonance imaging in multiple sclerosis
description	Abstract 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	article
author	Johan Baijot Stijn Denissen Lars Costers Jeroen Gielen Melissa Cambron Miguel D’Haeseleer Marie B. D’hooghe Anne-Marie Vanbinst Johan De Mey Guy Nagels Jeroen Van Schependom
author_facet	Johan Baijot Stijn Denissen Lars Costers Jeroen Gielen Melissa Cambron Miguel D’Haeseleer Marie B. D’hooghe Anne-Marie Vanbinst Johan De Mey Guy Nagels Jeroen Van Schependom
author_sort	Johan Baijot
title	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_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_sort	signal quality as achilles’ heel of graph theory in functional magnetic resonance imaging in multiple sclerosis
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/cea2d44cd7fc4326ac81b21ee7d45d63
work_keys_str_mv	AT johanbaijot signalqualityasachillesheelofgraphtheoryinfunctionalmagneticresonanceimaginginmultiplesclerosis AT stijndenissen signalqualityasachillesheelofgraphtheoryinfunctionalmagneticresonanceimaginginmultiplesclerosis AT larscosters signalqualityasachillesheelofgraphtheoryinfunctionalmagneticresonanceimaginginmultiplesclerosis AT jeroengielen signalqualityasachillesheelofgraphtheoryinfunctionalmagneticresonanceimaginginmultiplesclerosis AT melissacambron signalqualityasachillesheelofgraphtheoryinfunctionalmagneticresonanceimaginginmultiplesclerosis AT migueldhaeseleer signalqualityasachillesheelofgraphtheoryinfunctionalmagneticresonanceimaginginmultiplesclerosis AT mariebdhooghe signalqualityasachillesheelofgraphtheoryinfunctionalmagneticresonanceimaginginmultiplesclerosis AT annemarievanbinst signalqualityasachillesheelofgraphtheoryinfunctionalmagneticresonanceimaginginmultiplesclerosis AT johandemey signalqualityasachillesheelofgraphtheoryinfunctionalmagneticresonanceimaginginmultiplesclerosis AT guynagels signalqualityasachillesheelofgraphtheoryinfunctionalmagneticresonanceimaginginmultiplesclerosis AT jeroenvanschependom signalqualityasachillesheelofgraphtheoryinfunctionalmagneticresonanceimaginginmultiplesclerosis
_version_	1718391397164253184

Signal quality as Achilles’ heel of graph theory in functional magnetic resonance imaging in multiple sclerosis

Ejemplares similares