Functional network alterations in young brain tumor patients with radiotherapy-induced memory impairments and vascular injury

Abstract

Background: Cognitive impairment and cerebral microbleeds (CMBs) are long-term side-effects of cranial radiation therapy (RT). Previously we showed that memory function is disrupted in young patients and that the rate of cognitive decline correlates with CMB development. However, vascular injury alone cannot explain RT-induced cognitive decline. Here we use resting-state functional MRI (rsfMRI) to further investigate the complex mechanisms underlying memory impairment after RT.

Methods: Nineteen young patients previously treated with or without focal or whole-brain RT for a brain tumor underwent cognitive testing followed by 7T rsfMRI and susceptibility-weighted imaging for CMB detection. Global brain modularity and efficiency, and rsfMRI signal variability within the dorsal attention, salience, and frontoparietal networks were computed. We evaluated whether MR metrics could distinguish age- and sex-matched controls (N = 19) from patients and differentiate patients based on RT exposure and aggressiveness. We also related MR metrics with memory performance, CMB burden, and risk factors for cognitive decline after RT.

Results: Compared to controls, patients exhibited widespread hyperconnectivity, similar modularity, and significantly increased efficiency (p < 0.001) and network variability (p < 0.001). The most abnormal values were detected in patients treated with high dose whole-brain RT, having supratentorial tumors, and who did not undergo RT but had hydrocephalus. MR metrics and memory performance were correlated (R = 0.34-0.53), though MR metrics were more strongly related to risk factors for cognitive worsening and CMB burden with evidence of functional recovery.

Conclusions: MR metrics describing brain connectivity and variability represent promising candidate imaging biomarkers for monitoring of long-term cognitive side-effects after RT.

Keywords: 7T MRI; brain connectivity; brain tumors; fMRI; memory; radiation therapy; vascular injury.

Figure 1

Functional connectivity matrix generation. Following fMRI data preprocessing (A) and warping of the brain atlas regions-of-interest (ROIs) to subject space (B), connectivity matrices were generated via Pearson correlations between all pairs of brain ROIs (C).

Figure 2

Network variability is a reproducible and stable MR metric. Upon increasing the number of ICA components, the dorsal attention network (DAN) was reduced to left and right hemisphere sub-networks (A), with corresponding variability metrics remaining significantly correlated (B) and relatively stable across different data filtering bandwidths and spatial smoothing kernels (C).

Figure 3

ICA-derived brain networks for all subjects and seed-based analysis confirming altered networks connectivity in patients. For each patient, BOLD variability was computed as the standard deviation of network-specific timeseries data (A). Seed-based analysis confirmed that patients had significantly altered connectivity (relative to controls) involving nodes of the networks of interest (B). In (B), orange corresponds to brain areas that are hyperconnected to respective network nodes in patients (relative to controls), while purple represents hypoconnected areas.

Figure 4

MR metrics can distinguish healthy controls and patient subgroups. Scaled and Fisher transformed functional connectivity (FC) matrices reveal notable group differences in global connectivity (A). MR metrics derived from FC matrices and ICA brain networks show significant group trends related to group exposure to radiation therapy (RT) and/or the degree of RT treatment aggressiveness (B, C). HC, healthy controls; no RT, non-irradiated patients; WVRT, whole-ventricular focal RT; Focal, focal RT to the supratentorial brain; WBRT, whole-brain RT.

Figure 5

Age-normalized MR metrics and ISL test scores are correlated. Age-normalized network variability (A) and functional connectivity (B) metrics show a positive correlative trend with the age-normalized International Shopping List (ISL) test scores, representative of neurocognitive memory performance. As shown in B, only modularity and efficiency are significantly correlated with ISL. SN, salience network; FPN, frontoparietal network; L-DAN, left hemisphere dorsal attention network; R-DAN, right hemisphere DAN.

Figure 6

MR metrics change parabolically with increasing CMB burden. Degree of cerebral microbleed (CMB) burden detected on SWI (A) reveals parabolic-like changes in left hemisphere dorsal attention network (L-DAN) variability and modularity (B) with increasing CMB burden (based on within-group averages). Isolated plots for L-DAN variability and modularity are shown respectively in the top row of (C, D); the bottom rows show the individual patient data points for CMB counts ranging 1–50 (magnified) and 1–205 (full range). In (B), modularity values have been reduced by a factor of 5 for visualization purposes. Two of the 19 patients had poor SWI data quality and therefore CMB burden could not be evaluated. SN, salience network; FPN, frontoparietal network; L-DAN, left hemisphere dorsal attention network; R-DAN, right hemisphere DAN; Mod, modularity; Effi, efficiency; ISL, International Shopping List test score.

Figure 7

Age-normalized MR metrics are strongly associated with risk factors for cognitive decline after RT. Neurocognitive memory performance measured via the international shopping list (ISL) task is less associated with known risk factors for neurocognitive decline after RT (A) than MR metrics (B) representing surrogate markers of neurocognitive status.