BACKGROUND/OBJECTIVES: Functional MRI (fMRI) is widely used to assess language lateralization, but its application in patients with brain tumors can be hindered by cognitive impairments, compensatory neuroplasticity, and artifacts due to patient movement or severe aphasia. Gray matter volume (GMV) analysis via voxel-based morphometry (VBM) in language-related brain regions may offer a stable complementary approach. This study investigates the relationship between GMV and fMRI-derived language lateralization in healthy individuals and patients with left-hemisphere brain tumors, aiming to enhance accuracy in complex cases.

METHODS

The MRI data from 22 healthy participants and 28 individuals with left-hemisphere brain tumors were analyzed. Structural T1-weighted and functional images were obtained during three language tasks. Language lateralization was assessed based on activation in predefined regions of interest (ROIs), categorized as typical (left) or atypical (right or bilateral). The GMV in these ROIs was measured using VBM. Linear regressions explored GMV-lateralization associations, and logistic regressions predicted the lateralization based on the GMV.

RESULTS

In the healthy participants, typical left-hemispheric language dominance correlated with higher GMV in the left pars opercularis of the inferior frontal gyrus. The brain tumor participants with atypical lateralization showed increased GMV in six right-hemisphere ROIs. The GMV in the language ROIs predicted the fMRI language lateralization, with AUCs from 80.1% to 94.2% in the healthy participants and 78.3% to 92.6% in the tumor patients.

CONCLUSIONS

GMV analysis in language-related ROIs effectively complements fMRI for assessing language dominance, particularly when fMRI is challenging. It correlates with language lateralization in both healthy individuals and brain tumor patients, highlighting its potential in preoperative language mapping. Further research with larger samples is needed to refine its clinical utility.