Presurgical brain mapping of the language network in patients with brain tumors using resting-state fMRI: Comparison with task fMRI

• Published in: Human brain mapping Vol. 37; no. 3; pp. 913 - 923
• Main Authors: Sair, Haris I., Yahyavi-Firouz-Abadi, Noushin, Calhoun, Vince D., Airan, Raag D., Agarwal, Shruti, Intrapiromkul, Jarunee, Choe, Ann S., Gujar, Sachin K., Caffo, Brian, Lindquist, Martin A., Pillai, Jay J.
• Format: Journal Article
• Language: English
• Published: United States Blackwell Publishing Ltd 01.03.2016; John Wiley & Sons, Inc; John Wiley and Sons Inc
• Subjects: Adolescent; Adult; Aged; Analysis of Variance; Brain - physiopathology; Brain - surgery; Brain Mapping - methods; Brain Neoplasms - physiopathology; Brain Neoplasms - surgery; brain tumor; Female; Humans; Language; language network; Linear Models; Magnetic Resonance Imaging - methods; Male; Mental Processes - physiology; Middle Aged; Neuropsychological Tests; Preoperative Care - methods; presurgical brain mapping; Rest; resting-state fMRI; Software; task-fMRI; Young Adult; brain tumor; language network; presurgical brain mapping; resting-state fMRI; task-fMRI
• ISSN: 1065-9471; 1097-0193; 1097-0193
• DOI: 10.1002/hbm.23075

Purpose To compare language networks derived from resting‐state fMRI (rs‐fMRI) with task‐fMRI in patients with brain tumors and investigate variables that affect rs‐fMRI vs task‐fMRI concordance. Materials and Methods Independent component analysis (ICA) of rs‐fMRI was performed with 20, 30, 40, and 50 target components (ICA20 to ICA50) and language networks identified for patients presenting for presurgical fMRI mapping between 1/1/2009 and 7/1/2015. 49 patients were analyzed fulfilling criteria for presence of brain tumors, no prior brain surgery, and adequate task‐fMRI performance. Rs‐vs‐task‐fMRI concordance was measured using Dice coefficients across varying fMRI thresholds before and after noise removal. Multi‐thresholded Dice coefficient volume under the surface (DiceVUS) and maximum Dice coefficient (MaxDice) were calculated. One‐way Analysis of Variance (ANOVA) was performed to determine significance of DiceVUS and MaxDice between the four ICA order groups. Age, Sex, Handedness, Tumor Side, Tumor Size, WHO Grade, number of scrubbed volumes, image intensity root mean square (iRMS), and mean framewise displacement (FD) were used as predictors for VUS in a linear regression. Results Artificial elevation of rs‐fMRI vs task‐fMRI concordance is seen at low thresholds due to noise. Noise‐removed group‐mean DiceVUS and MaxDice improved as ICA order increased, however ANOVA demonstrated no statistically significant difference between the four groups. Linear regression demonstrated an association between iRMS and DiceVUS for ICA30‐50, and iRMS and MaxDice for ICA50. Conclusion Overall there is moderate group level rs‐vs‐task fMRI language network concordance, however substantial subject‐level variability exists; iRMS may be used to determine reliability of rs‐fMRI derived language networks. Hum Brain Mapp 37:913–923, 2016. © 2015 Wiley Periodicals, Inc.