Assessing Language Lateralization through Gray Matter Volume: Implications for Preoperative Planning in Brain Tumor Surgery

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dc.contributor.authorSolomons, Daniel
dc.contributor.authorRodriguez-Fernandez, Maria
dc.contributor.authorMery-Munoz, Francisco
dc.contributor.authorArrano-Carrasco, Leonardo
dc.contributor.authorCostabal, Francisco Sahli
dc.contributor.authorMendez-Orellana, Carolina
dc.date.accessioned2025-01-20T16:05:04Z
dc.date.available2025-01-20T16:05:04Z
dc.date.issued2024
dc.description.abstractBackground/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.
dc.fuente.origenWOS
dc.identifier.doi10.3390/brainsci14100954
dc.identifier.eissn2076-3425
dc.identifier.urihttps://doi.org/10.3390/brainsci14100954
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/89864
dc.identifier.wosidWOS:001342970100001
dc.issue.numero10
dc.language.isoen
dc.revistaBrain sciences
dc.rightsacceso restringido
dc.subjectbrain tumor
dc.subjectgray matter volume
dc.subjectlanguage lateralization
dc.subjectregression analysis
dc.titleAssessing Language Lateralization through Gray Matter Volume: Implications for Preoperative Planning in Brain Tumor Surgery
dc.typeartículo
dc.volumen14
sipa.indexWOS
sipa.trazabilidadWOS;2025-01-12
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