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.

Sighinolfi, G., Mitolo, M., Testa, C., Martinoni, M., Evangelisti, S., Rochat, M.J., et al. (2022). What Can Resting-State fMRI Data Analysis Explain about the Functional Brain Connectivity in Glioma Patients?. TOMOGRAPHY, 8(1), 267-280 [10.3390/tomography8010021].

What Can Resting-State fMRI Data Analysis Explain about the Functional Brain Connectivity in Glioma Patients?

Sighinolfi, Giovanni;Mitolo, Micaela;Testa, Claudia;Evangelisti, Stefania;Rochat, Magali Jane;Zoli, Matteo;Mazzatenta, Diego;Lodi, Raffaele;Tonon, Caterina
2022

Abstract

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.
2022
Sighinolfi, G., Mitolo, M., Testa, C., Martinoni, M., Evangelisti, S., Rochat, M.J., et al. (2022). What Can Resting-State fMRI Data Analysis Explain about the Functional Brain Connectivity in Glioma Patients?. TOMOGRAPHY, 8(1), 267-280 [10.3390/tomography8010021].
Sighinolfi, Giovanni; Mitolo, Micaela; Testa, Claudia; Martinoni, Matteo; Evangelisti, Stefania; Rochat, Magali Jane; Zoli, Matteo; Mazzatenta, Diego;...espandi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/897257
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