The impact of patient factors and tumor characteristics on language neuroplasticity in left hemispheric diffuse gliomas prior to surgical resection

PurposeLanguage networks are reorganized during glioma growth, leading to varying language performance in patients with gliomas located in or around language-eloquent areas. Therefore, pre-treated language performance reflects the neuroplasticity potential. Different domains of language processing, such as speech expression, repetition, and comprehension, involving different neural networks. We analyzed the effects of patient factors and tumor characteristics on the pre-treated performance to investigate neuroplastic potential of different language domains.MethodsPatient age, sex, education level, tumor grade, language pathway involvement, T1 contrast enhanced (C+), and FLAIR (T2) volume were selected as variables. The correlation with abnormal language performance was verified using univariate and multivariate logistic regression.ResultsIn total, 104 left hemispheric glioma patients were enrolled in this study. 44% of patients had repetitive abnormalities, 34.9% had comprehensive abnormalities, and 32.1% had expressive abnormalities. The proportion of normal language performance was 60% in grade 2 and 3 gliomas and 16% in grade 4 gliomas. Tumor grade (p = 0.006) and T2 volume (p = 0.008) were associated with abnormal performance in the expressive domain, education level (p = 0.004) and T1 C+ volume (p = 0.049) in the repetitive domain, and education level (p = 0.013), T2 volume (p = 0.011), and tumor grade (p = 0.089) in the comprehensive domain.ConclusionDifferent clinical and radiological factors affected the abnormal performance of the three language domains, indicating their functional connectivity and neuroplastic potential are inherently varied. The dynamic interactions between patient factors, tumor characteristics, and language processing should be considered when resecting left hemispheric gliomas.

Automated summary

The reorganization of language networks during glioma growth leads to varying language performance in patients. Different language domains involving different neural networks were analyzed to investigate neuroplastic potential. Patient factors and tumor characteristics were found to affect the abnormal performance of different language domains.