PT  - JOURNAL ARTICLE
AU  - N. Yahyavi-Firouz-Abadi
AU  - J.J. Pillai
AU  - M.A. Lindquist
AU  - V.D. Calhoun
AU  - S. Agarwal
AU  - R.D. Airan
AU  - B. Caffo
AU  - S.K. Gujar
AU  - H.I. Sair
TI  - Presurgical Brain Mapping of the Ventral Somatomotor Network in Patients with Brain Tumors Using Resting-State fMRI
AID  - 10.3174/ajnr.A5132
DP  - 2017 May 01
TA  - American Journal of Neuroradiology
PG  - 1006--1012
VI  - 38
IP  - 5
4099  - http://www.ajnr.org/content/38/5/1006.short
4100  - http://www.ajnr.org/content/38/5/1006.full
SO  - Am. J. Neuroradiol.2017 May 01; 38
AB  - BACKGROUND AND PURPOSE: Resting-state fMRI readily identifies the dorsal but less consistently the ventral somatomotor network. Our aim was to assess the relative utility of resting-state fMRI in the identification of the ventral somatomotor network via comparison with task-based fMRI in patients with brain tumor.MATERIALS AND METHODS: We identified 26 surgically naïve patients referred for presurgical fMRI brain mapping who had undergone both satisfactory ventral motor activation tasks and resting-state fMRI. Following standard preprocessing for task-based fMRI and resting-state fMRI, general linear model analysis of the ventral motor tasks and independent component analysis of resting-state fMRI were performed with the number of components set to 20, 30, 40, and 50. Visual overlap of task-based fMRI and resting-state fMRI at different component levels was assessed and categorized as full match, partial match, or no match. Rest-versus-task-fMRI concordance was calculated with Dice coefficients across varying fMRI thresholds before and after noise removal. Multithresholded Dice coefficient volume under the surface was calculated.RESULTS: The ventral somatomotor network was identified in 81% of patients. At the subject level, better matches between resting-state fMRI and task-based fMRI were seen with an increasing order of components (53% of cases for 20 components versus 73% for 50 components). Noise-removed group-mean volume under the surface improved as component numbers increased from 20 to 50, though ANOVA demonstrated no statistically significant difference among the 4 groups.CONCLUSIONS: In most patients, the ventral somatomotor network can be identified with an increase in the probability of a better match at a higher component number. There is variable concordance of the ventral somatomotor network at the single-subject level between resting-state and task-based fMRI.BOLDblood oxygen level–dependentICAindependent component analysisrs-fMRIresting-state fMRItb-fMRItask-based fMRIVSMNventral somatomotor networkVUSvolume under the surface