Altered functional connectivity of the default mode network in diffuse gliomas measured with pseudo-resting state fMRI

Abstract

The purpose of the current study was to explore whether brain tumors disrupt the integrity of the default mode network (DMN), a well-characterized resting-state fMRI network. We evaluated whether tumor grade, volume, post-surgical/clinical status, or location decreased the functional connectivity within the DMN in patients with gliomas. Task-based fMRI data was obtained from 68 diffuse glioma patients and 12 healthy volunteers. Pseudo-resting state fMRI data was calculated from task-based fMRI data using standard techniques. Data was preprocessed and DMN integrity was compared across WHO grade, tumor volume surgical status (new vs. recurrent tumors), age, and KPS using univariate and multivariate linear models. WHO grade was the most significant predictor of DMN integrity (P = 0.004), whereas T2 hyperintense lesion volume was not a predictor (P = 0.154). DMN integrity was lower in high-grade (WHO III–IV) compared with low-grade (WHO II) patients (P = 0.020). Tumors in the left parietal lobe showed a more impaired DMN compared with tumors in the frontal lobe, while tumors within and outside the network nodes did not differ significantly. Results suggest higher tumor grade along with prior surgery and/or treatment cause the largest reduction in DMN functional connectivity in patients with primary gliomas, and that tumor location has an impact on connectivity.

Fig. 1

a Task-based fMRI data consists of rapid echoplanar (EPI) acquisition over time during a stimulus. b To isolate the pseudo-resting state fMRI signal, the fMRI stimulus block design (gray dashed line) is first convolved with a hemodynamic response function and then deconvolved with the fMRI time-series data in each image voxel (black). c The residual signal after deconvolution is used to as pseudo-resting state fMRI data. From this pseudo-resting state fMRI data, voxels in each region of interest identified as part of the default mode network nodes are averaged to get a single fMRI time-series for each node. The functional connectivity between the average pseudo-resting state fMRI time series in each node is then calculated using a Pearson’s correlation coefficient, r. d Recognized nodes within the DMN include the ACC, PCC, LLPC, and RLPC

Fig. 2

a Global DMN connectivity for healthy volunteers and tumor patients by grade (One-way ANOVA, P < 0.0001). b Global DMN connectivity in low grade (WHO II) and high-grade (WHO III-IV) gliomas (t test, P = 0.020)

Fig. 3

Global DMN connectivity by tumor location in high-grade gliomas (One-way ANOVA, P = 0.006)

Fig. 4

a Global DMN connectivity in newly diagnosed and recurrent glioma patients for all tumor grades (t test, P = 0.015). b Global DMN connectivity for newly diagnosed and recurrent glioma patients stratified by high- (WHO III–IV; t test, P = 0.051) or low-grade (WHO II; t test, P = 0.839)