Abstract
OBJECTIVES: To validate the functional relevance of resting state networks (RSNs) by means of a comparison of resting state connectivity (RSC) between language regions elicited by direct cortical stimulation versus RSC between random regions; and to evaluate the accuracy of resting state fMRI in surgical planning by assessing the overlap between RSNs and intraoperative functional mapping results. METHODS: Sensorimotor and language eloquent sites were identified by direct electrical cortical stimulation in 98 patients with a diffuse low-grade glioma. A seed to voxel analysis with inter-language stimulation point connectivity versus inter-random ROIs connectivity was performed (19 patients). An independant component analysis (ICA) was also applied to rsfMRI data. Language and sensorimotor components were selected over 20 independent components and compared to the corresponding stimulation points and resected cortex masks (31 and 90 patients, respectively). RESULTS: Mean connectivity value between language seeds was significantly higher than the one between random seeds (0.68 ± 0.39 and 0.12 ± 0.21 respectively, P < 10(-10) ). 96 ± 11% of sensorimotor stimulation points were located within 10 mm from sensorimotor ICA maps versus 92 ± 21% for language. 3.1 and 15% of resected cortex overlapped sensorimotor and language networks, respectively. Mean sensorimotor stimulation points and resected cortex z-scores were 2.0 ± 1.2 and -0.050 ± 0.60, respectively (P < 10(-10) ). Mean language stimulation points and resected cortex z-scores were 1.6 ± 1.9 and 0.68 ± 0.91, respectively, P < 0.005. CONCLUSION: The significantly higher RSC between language seeds than between random seeds validated the functional relevance of RSC. ICA partly succeeded to distinguish eloquent versus surgically removable areas and may be possibly used as a complementary tool to intraoperative mapping. Hum Brain Mapp 37:3721-3732, 2016. © 2016 Wiley Periodicals, Inc.