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

Tomography. 2022 Jan 27;8(1):267-280. doi: 10.3390/tomography8010021.

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.

Keywords: functional connectivity; glioma; longitudinal study; network localization; resting-state fMRI.

Publication types

  • Review

MeSH terms

  • Brain / diagnostic imaging
  • Brain Mapping / methods
  • Data Analysis
  • Glioma* / diagnostic imaging
  • Humans
  • Magnetic Resonance Imaging* / methods