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What Can Resting-State fMRI Data Analysis Explain about the Functional Brain Connectivity in Glioma Patients?
Resting-state functional MRI has been increasingly implemented in imaging protocols for the study of functional connectivity in glioma patients as a sequence able to capture the activity of brain networks and to investigate their properties without requiring the patients’ cooperation. The present re...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8878995/ https://www.ncbi.nlm.nih.gov/pubmed/35202187 http://dx.doi.org/10.3390/tomography8010021 |
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author | Sighinolfi, Giovanni Mitolo, Micaela Testa, Claudia Martinoni, Matteo Evangelisti, Stefania Rochat, Magali Jane Zoli, Matteo Mazzatenta, Diego Lodi, Raffaele Tonon, Caterina |
author_facet | Sighinolfi, Giovanni Mitolo, Micaela Testa, Claudia Martinoni, Matteo Evangelisti, Stefania Rochat, Magali Jane Zoli, Matteo Mazzatenta, Diego Lodi, Raffaele Tonon, Caterina |
author_sort | Sighinolfi, Giovanni |
collection | PubMed |
description | Resting-state functional MRI has been increasingly implemented in imaging protocols for the study of functional connectivity in glioma patients as a sequence able to capture the activity of brain networks and to investigate their properties without requiring the patients’ cooperation. The present review aims at describing the most recent results obtained through the analysis of resting-state fMRI data in different contexts of interest for brain gliomas: the identification and localization of functional networks, the characterization of altered functional connectivity, and the evaluation of functional plasticity in relation to the resection of the glioma. An analysis of the literature showed that significant and promising results could be achieved through this technique in all the aspects under investigation. Nevertheless, there is room for improvement, especially in terms of stability and generalizability of the outcomes. Further research should be conducted on homogeneous samples of glioma patients and at fixed time points to reduce the considerable variability in the results obtained across and within studies. Future works should also aim at establishing robust metrics for the assessment of the disruption of functional connectivity and its recovery at the single-subject level. |
format | Online Article Text |
id | pubmed-8878995 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-88789952022-02-26 What Can Resting-State fMRI Data Analysis Explain about the Functional Brain Connectivity in Glioma Patients? Sighinolfi, Giovanni Mitolo, Micaela Testa, Claudia Martinoni, Matteo Evangelisti, Stefania Rochat, Magali Jane Zoli, Matteo Mazzatenta, Diego Lodi, Raffaele Tonon, Caterina Tomography Review Resting-state functional MRI has been increasingly implemented in imaging protocols for the study of functional connectivity in glioma patients as a sequence able to capture the activity of brain networks and to investigate their properties without requiring the patients’ cooperation. The present review aims at describing the most recent results obtained through the analysis of resting-state fMRI data in different contexts of interest for brain gliomas: the identification and localization of functional networks, the characterization of altered functional connectivity, and the evaluation of functional plasticity in relation to the resection of the glioma. An analysis of the literature showed that significant and promising results could be achieved through this technique in all the aspects under investigation. Nevertheless, there is room for improvement, especially in terms of stability and generalizability of the outcomes. Further research should be conducted on homogeneous samples of glioma patients and at fixed time points to reduce the considerable variability in the results obtained across and within studies. Future works should also aim at establishing robust metrics for the assessment of the disruption of functional connectivity and its recovery at the single-subject level. MDPI 2022-01-27 /pmc/articles/PMC8878995/ /pubmed/35202187 http://dx.doi.org/10.3390/tomography8010021 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Sighinolfi, Giovanni Mitolo, Micaela Testa, Claudia Martinoni, Matteo Evangelisti, Stefania Rochat, Magali Jane Zoli, Matteo Mazzatenta, Diego Lodi, Raffaele Tonon, Caterina What Can Resting-State fMRI Data Analysis Explain about the Functional Brain Connectivity in Glioma Patients? |
title | What Can Resting-State fMRI Data Analysis Explain about the Functional Brain Connectivity in Glioma Patients? |
title_full | What Can Resting-State fMRI Data Analysis Explain about the Functional Brain Connectivity in Glioma Patients? |
title_fullStr | What Can Resting-State fMRI Data Analysis Explain about the Functional Brain Connectivity in Glioma Patients? |
title_full_unstemmed | What Can Resting-State fMRI Data Analysis Explain about the Functional Brain Connectivity in Glioma Patients? |
title_short | What Can Resting-State fMRI Data Analysis Explain about the Functional Brain Connectivity in Glioma Patients? |
title_sort | what can resting-state fmri data analysis explain about the functional brain connectivity in glioma patients? |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8878995/ https://www.ncbi.nlm.nih.gov/pubmed/35202187 http://dx.doi.org/10.3390/tomography8010021 |
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