Introduction: Gliomas are preeminent type of malignant primary brain tumours in adults. This study applies Co-Activation pattern (CAP) analysis in glioma patients and compare the results to healthy controls (HC) to characterize alterations in brain function.

Methods and Materials: The study comprehend 106 glioma patients (mean age 61.15 ± 8.95 years; 19 low-grade, 72 high-grade, 15 metastatic) and 100 HCs with comparable age, employing rs-fMRI. We used the CAP analysis, a data-driven clustering technique, to compute recurring states of brain configuration and associated metrics of persistence, transitions, kin and kout (Figure 1). Differences in CAP metrics between HC and patients were studied with t-tests (Figure 2).

Results: Six CAPs were identified and categorized into respective networks. Patients demonstrated higher transition, kin/kout metrics and lower persistence in CAPs involving ventral DMN (Default Mode Network) (p<0.0001), dorsal DMN (p<0.01) and ECN (Executive Control Network) (p<1e-06). The visuospatial network (VSN) demonstrated lower metrics values compared to HC (p<0.001). All tumour types demonstrated significant differences from HC, with higher kin/kout and transition for the DMN and ECN (p<0.05). No significant differences were found between tumours of different type in any of the CAP metrics.

Conclusions: Our study demonstrated that mental states of glioma patients transit more often through DMN and ECN compared to HC, suggesting higher engagement of complex cognitive functions in patients with brain tumours which may reflect compensatory mechanisms for clinical deficits. Limitations of the study include retrospective design and lack of complete neuropsychological testing.

Figure 1

Figure 2