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Resting-state functional connectivity predicts individual language impairment of patients with left hemispheric gliomas involving language network.

ABSTRACT: Language deficits following brain tumors should consider the dynamic interactions between different tumor growth kinetics and functional network reorganization. We measured the resting-state functional connectivity of 126 patients with left cerebral gliomas involving language network areas, including 77 patients with low-grade gliomas (LGG) and 49 patients with high-grade gliomas (HGG). Functional network mapping for language was performed by construction of a multivariate machine learning-based prediction model of individual aphasia quotient (AQ), a summary score that indicates overall severity of language impairment. We found that the AQ scores for HGG patients were significantly lower than those of LGG patients. The prediction accuracy of HGG patients (R² = 0.27, permutation P = 0.007) was much higher than that of LGG patients (R² = 0.09, permutation P = 0.032). The rsFC regions predictive of LGG's AQ involved the bilateral frontal, temporal, and parietal lobes, subcortical regions, and bilateral cerebro-cerebellar connections, mainly in regions belonging to the canonical language network. The functional network of language processing for HGG patients showed strong dependence on connections of the left cerebro-cerebellar connections, limbic system, and the temporal, occipital, and prefrontal lobes. Together, our findings suggested that individual language processing of glioma patients links large-scale, bilateral, cortico-subcortical, and cerebro-cerebellar functional networks with different network reorganizational mechanisms underlying the different levels of language impairments in LGG and HGG patients.

SUBMITTER: Yuan B

PROVIDER: S-EPMC6838935 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Although language difficulties are common in children born prematurely, robust neuroanatomical correlates of these impairments remain to be established. This study investigated whether the greater prevalence of language problems in preterm (versus term-born) children might reflect injury to major intra- or interhemispheric white matter pathways connecting frontal and temporal language regions. To investigate this, we performed a comprehensive assessment of language and academic abilities in a group of adolescents born prematurely, some of whom had evidence of brain injury at birth (n = 50, mean age: 16 years, mean gestational age: 27 weeks) and compared them to a term-born control group (n = 30). Detailed structural magnetic resonance imaging and diffusion-tractography analyses of intrahemispheric and interhemispheric white matter bundles were performed. Analysis of intrahemispheric pathways included the arcuate fasciculus (dorsal language pathway) and uncinate fasciculus/extreme capsule (ventral language pathway). Analysis of interhemispheric pathways (in particular, connections between the temporal lobes) included the two major commissural bundles: the corpus callosum and anterior commissure. We found language impairment in 38% of adolescents born preterm. Language impairment was not related to abnormalities of the arcuate fasciculus (or its subsegments), but was associated with bilateral volume reductions in the ventral language pathway. However, the most significant volume reduction was detected in the posterior corpus callosum (splenium), which contains interhemispheric connections between the occipital, parietal and temporal lobes. Diffusion tractography showed that of the three groups of interhemispheric fibres within the splenium, only those connecting the temporal lobes were reduced. Crucially, we found that language impairment was only detectable if the anterior commissure (a second temporal lobe commissural pathway) was also small. Regression analyses showed that a combination of anatomical measures of temporal interhemispheric connectivity (through the splenium of the corpus callosum and anterior commissure) explained 57% of the variance in language abilities. This supports recent theories emphasizing the importance of interhemispheric connections for language, particularly in the developing brain.

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Resting-state functional connectivity predicts individual language impairment of patients with left hemispheric gliomas involving language network.

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