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Patterns of gray and white matter functional networks involvement in glioblastoma patients: indirect mapping from clinical MRI scans
BACKGROUND: Resting-state functional-MRI studies identified several cortical gray matter functional networks (GMNs) and white matter functional networks (WMNs) with precise anatomical localization. Here, we aimed at describing the relationships between brain’s functional topological organization and...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10318144/ https://www.ncbi.nlm.nih.gov/pubmed/37409023 http://dx.doi.org/10.3389/fneur.2023.1175576 |
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author | Sansone, Giulio Pini, Lorenzo Salvalaggio, Alessandro Gaiola, Matteo Volpin, Francesco Baro, Valentina Padovan, Marta Anglani, Mariagiulia Facchini, Silvia Chioffi, Franco Zagonel, Vittorina D’Avella, Domenico Denaro, Luca Lombardi, Giuseppe Corbetta, Maurizio |
author_facet | Sansone, Giulio Pini, Lorenzo Salvalaggio, Alessandro Gaiola, Matteo Volpin, Francesco Baro, Valentina Padovan, Marta Anglani, Mariagiulia Facchini, Silvia Chioffi, Franco Zagonel, Vittorina D’Avella, Domenico Denaro, Luca Lombardi, Giuseppe Corbetta, Maurizio |
author_sort | Sansone, Giulio |
collection | PubMed |
description | BACKGROUND: Resting-state functional-MRI studies identified several cortical gray matter functional networks (GMNs) and white matter functional networks (WMNs) with precise anatomical localization. Here, we aimed at describing the relationships between brain’s functional topological organization and glioblastoma (GBM) location. Furthermore, we assessed whether GBM distribution across these networks was associated with overall survival (OS). MATERIALS AND METHODS: We included patients with histopathological diagnosis of IDH-wildtype GBM, presurgical MRI and survival data. For each patient, we recorded clinical-prognostic variables. GBM core and edema were segmented and normalized to a standard space. Pre-existing functional connectivity-based atlases were used to define network parcellations: 17 GMNs and 12 WMNs were considered in particular. We computed the percentage of lesion overlap with GMNs and WMNs, both for core and edema. Differences between overlap percentages were assessed through descriptive statistics, ANOVA, post-hoc tests, Pearson’s correlation tests and canonical correlations. Multiple linear and non-linear regression tests were employed to explore relationships with OS. RESULTS: 99 patients were included (70 males, mean age 62 years). The most involved GMNs included ventral somatomotor, salient ventral attention and default-mode networks; the most involved WMNs were ventral frontoparietal tracts, deep frontal white matter, and superior longitudinal fasciculus system. Superior longitudinal fasciculus system and dorsal frontoparietal tracts were significantly more included in the edema (p < 0.001). 5 main patterns of GBM core distribution across functional networks were found, while edema localization was less classifiable. ANOVA showed significant differences between mean overlap percentages, separately for GMNs and WMNs (p-values<0.0001). Core-N12 overlap predicts higher OS, although its inclusion does not increase the explained OS variance. DISCUSSION AND CONCLUSION: Both GBM core and edema preferentially overlap with specific GMNs and WMNs, especially associative networks, and GBM core follows five main distribution patterns. Some inter-related GMNs and WMNs were co-lesioned by GBM, suggesting that GBM distribution is not independent of the brain’s structural and functional organization. Although the involvement of ventral frontoparietal tracts (N12) seems to have some role in predicting survival, network-topology information is overall scarcely informative about OS. fMRI-based approaches may more effectively demonstrate the effects of GBM on brain networks and survival. |
format | Online Article Text |
id | pubmed-10318144 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-103181442023-07-05 Patterns of gray and white matter functional networks involvement in glioblastoma patients: indirect mapping from clinical MRI scans Sansone, Giulio Pini, Lorenzo Salvalaggio, Alessandro Gaiola, Matteo Volpin, Francesco Baro, Valentina Padovan, Marta Anglani, Mariagiulia Facchini, Silvia Chioffi, Franco Zagonel, Vittorina D’Avella, Domenico Denaro, Luca Lombardi, Giuseppe Corbetta, Maurizio Front Neurol Neurology BACKGROUND: Resting-state functional-MRI studies identified several cortical gray matter functional networks (GMNs) and white matter functional networks (WMNs) with precise anatomical localization. Here, we aimed at describing the relationships between brain’s functional topological organization and glioblastoma (GBM) location. Furthermore, we assessed whether GBM distribution across these networks was associated with overall survival (OS). MATERIALS AND METHODS: We included patients with histopathological diagnosis of IDH-wildtype GBM, presurgical MRI and survival data. For each patient, we recorded clinical-prognostic variables. GBM core and edema were segmented and normalized to a standard space. Pre-existing functional connectivity-based atlases were used to define network parcellations: 17 GMNs and 12 WMNs were considered in particular. We computed the percentage of lesion overlap with GMNs and WMNs, both for core and edema. Differences between overlap percentages were assessed through descriptive statistics, ANOVA, post-hoc tests, Pearson’s correlation tests and canonical correlations. Multiple linear and non-linear regression tests were employed to explore relationships with OS. RESULTS: 99 patients were included (70 males, mean age 62 years). The most involved GMNs included ventral somatomotor, salient ventral attention and default-mode networks; the most involved WMNs were ventral frontoparietal tracts, deep frontal white matter, and superior longitudinal fasciculus system. Superior longitudinal fasciculus system and dorsal frontoparietal tracts were significantly more included in the edema (p < 0.001). 5 main patterns of GBM core distribution across functional networks were found, while edema localization was less classifiable. ANOVA showed significant differences between mean overlap percentages, separately for GMNs and WMNs (p-values<0.0001). Core-N12 overlap predicts higher OS, although its inclusion does not increase the explained OS variance. DISCUSSION AND CONCLUSION: Both GBM core and edema preferentially overlap with specific GMNs and WMNs, especially associative networks, and GBM core follows five main distribution patterns. Some inter-related GMNs and WMNs were co-lesioned by GBM, suggesting that GBM distribution is not independent of the brain’s structural and functional organization. Although the involvement of ventral frontoparietal tracts (N12) seems to have some role in predicting survival, network-topology information is overall scarcely informative about OS. fMRI-based approaches may more effectively demonstrate the effects of GBM on brain networks and survival. Frontiers Media S.A. 2023-06-20 /pmc/articles/PMC10318144/ /pubmed/37409023 http://dx.doi.org/10.3389/fneur.2023.1175576 Text en Copyright © 2023 Sansone, Pini, Salvalaggio, Gaiola, Volpin, Baro, Padovan, Anglani, Facchini, Chioffi, Zagonel, D’Avella, Denaro, Lombardi and Corbetta. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neurology Sansone, Giulio Pini, Lorenzo Salvalaggio, Alessandro Gaiola, Matteo Volpin, Francesco Baro, Valentina Padovan, Marta Anglani, Mariagiulia Facchini, Silvia Chioffi, Franco Zagonel, Vittorina D’Avella, Domenico Denaro, Luca Lombardi, Giuseppe Corbetta, Maurizio Patterns of gray and white matter functional networks involvement in glioblastoma patients: indirect mapping from clinical MRI scans |
title | Patterns of gray and white matter functional networks involvement in glioblastoma patients: indirect mapping from clinical MRI scans |
title_full | Patterns of gray and white matter functional networks involvement in glioblastoma patients: indirect mapping from clinical MRI scans |
title_fullStr | Patterns of gray and white matter functional networks involvement in glioblastoma patients: indirect mapping from clinical MRI scans |
title_full_unstemmed | Patterns of gray and white matter functional networks involvement in glioblastoma patients: indirect mapping from clinical MRI scans |
title_short | Patterns of gray and white matter functional networks involvement in glioblastoma patients: indirect mapping from clinical MRI scans |
title_sort | patterns of gray and white matter functional networks involvement in glioblastoma patients: indirect mapping from clinical mri scans |
topic | Neurology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10318144/ https://www.ncbi.nlm.nih.gov/pubmed/37409023 http://dx.doi.org/10.3389/fneur.2023.1175576 |
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