Hemisphere-Specific Functional Remodeling and Its Relevance to Tumor Malignancy of Cerebral Glioma Based on Resting-State Functional Network Analysis

Systematic Review Between Resting-State fMRI and Task fMRI in Planning for Brain Tumour Surgery

As an alternative to task-based functional magnetic resonance imaging (T-fMRI), resting-state functional magnetic resonance imaging (Rs-fMRI) is suggested for preoperative mapping of patients with brain tumours, with an emphasis on treatment guidance and neurodegeneration prediction. A systematic review was conducted of 18 recent studies involving 1035 patients with brain tumours and Rs-fMRI protocols. This was accomplished by searching the electronic databases PubMed, Scopus, and Web of Science. For clinical benefit, we compared Rs-fMRI to standard T-fMRI and intraoperative direct cortical stimulation (DCS). The results of Rs-fMRI and T-fMRI were compared and their correlation with intraoperative DCS results was examined through a systematic review. Our exhaustive investigation demonstrated that Rs-fMRI is a dependable and sensitive preoperative mapping technique that detects neural networks in the brain with precision and identifies crucial functional regions in agreement with intraoperative DCS. Rs-fMRI comes in handy, especially in situations where T-fMRI proves to be difficult because of patient-specific factors. Additionally, our exhaustive investigation demonstrated that Rs-fMRI is a valuable tool in the preoperative screening and evaluation of brain tumours. Furthermore, its capability to assess brain function, forecast surgical results, and enhance decision-making may render it applicable in the clinical management of brain tumours.

The dynamic functional connectivity fingerprint of high-grade gliomas

Resting state fMRI has been used in many studies to investigate the impact of brain tumours on functional connectivity (FC). However, these studies have so far assumed that FC is stationary, disregarding the fact that the brain fluctuates over dynamic states. Here we utilised resting state fMRI data from 33 patients with high-grade gliomas and 33 healthy controls to examine the dynamic interplay between resting-state networks and to gain insights into the impact of brain tumours on functional dynamics. By employing Hidden Markov Models, we demonstrated that functional dynamics persist even in the presence of a high-grade glioma, and that patients exhibited a global decrease of connections strength, as well as of network segregation. Furthermore, through a multivariate analysis, we demonstrated that patients' cognitive scores are highly predictive of pathological dynamics, thus supporting our hypothesis that functional dynamics could serve as valuable biomarkers for better understanding the traits of high-grade gliomas.

Cerebrovascular Dysregulation in Patients with Glioma Assessed with Time-shifted BOLD fMRI

Background Microscopic vascular events, such as neovascularization and neurovascular uncoupling, are common in cerebral glioma. Mapping the cerebrovascular network remodeling at the macroscopic level may provide an alternative approach to assess hemodynamic dysregulation in patients with glioma. Purpose To investigate cerebrovascular dynamics and their relevance to tumor aggressiveness by using time-shift analysis (TSA) of the systemic low-frequency oscillation (sLFO) of the resting-state blood oxygenation level-dependent signal and a decision tree model. Materials and Methods In this retrospective study, 96 patients with histologically confirmed cerebral glioma were consecutively included (March 2012 to February 2017). TSA was performed to quantify the temporal properties of sLFO signals. Alteration in the time-shift properties was assessed in the tumor region and the contralesional hemisphere relative to the brains of healthy controls by using the Mann-Whitney U test. A decision tree model based on time-shift features was developed to predict the World Health Organization (WHO) glioma grade. Results A total of 88 patients with glioma (WHO grade II, 45; grade III, 21; grade IV, 22; mean age, 42 years; age range, 20-73 years; 51 men) and 40 healthy individuals from the 1000 Functional Connectomes Project (mean age, 32 years; age range, 24-49 years; 19 men) were included. The sLFO of the brain tissues was characterized by increased time shift in the tumor region and enhanced correlation with the global reference signal in the contralesional hemisphere compared with healthy brains. The proportion of tumor voxels with negative correlation to the reference signal significantly increased with the glioma malignancy grade. The decision tree model achieved an accuracy of 91% (80 of 88 patients) in predicting the glioma malignancy grade at the individual level (P = .004) based on the time-shift features. Conclusion Gliomas induced grade-specific cerebrovascular dysregulation in the entire brain, with altered time-shift features of systemic low-frequency oscillation signals. © RSNA, 2022 Online supplemental material is available for this article.

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 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.