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Functional network correlates of aphasia and compensation in brain tumor patients: A graph theoretical analysis of
Saeed Rahmani1, Samra Iftikhar1, Amirali Aali2
1Clinical Neuroplasticity Laboratory, Yale University School of Medicine, New Haven, CT, USA; Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA.
Objective:
To characterize functional network alterations associated with aphasia and preserved language function in patients with left-hemispheric brain tumors using resting-state fMRI graph-theoretical analysis, with secondary evaluation of whether whole-brain network metrics are associated with aphasia status within the tumor cohort.
Materials And Methods:
This retrospective IRB-approved study included 120 participants: 40 aphasic patients, 40 non-aphasic patients with left-hemispheric intra-axial tumors, and 40 matched healthy controls. ROI-to-ROI rs-fMRI connectivity across seven canonical networks yielded graph metrics (global/local efficiency, clustering, path length, centrality) at whole-brain, hemispheric, and network levels with FDR-corrected comparisons. Multinomial logistic regression compared healthy controls, non-aphasic patients, and aphasic patients. A secondary exploratory patient-only binary logistic regression examined aphasia status using whole-brain graph metrics and demographic covariates, including age, sex, and handedness.
Results:
The whole-brain multinomial model did not significantly distinguish healthy controls, non-aphasic patients, and aphasic patients (χ²=21.622, df=18, p = 0.249; classification accuracy=57.5%). Therefore, individual graph-metric coefficients from this model were treated as exploratory rather than confirmatory. In a secondary exploratory patient-only regression, the model did not significantly distinguish aphasic from non-aphasic tumor patients after adjustment for age, sex, and handedness (Omnibus χ²=7.147, df=10, p = 0.712; Nagelkerke R²=0.114; Hosmer-Lemeshow p = 0.508; accuracy=62.5%). Whole-brain graph metrics were not independently associated with aphasia after demographic adjustment. ROI-level analyses showed focal differences in non-aphasic patients, including greater left IFG closeness, posterior parietal centrality, and anterior cerebellar connectivity, but these findings were interpreted as exploratory network correlates rather than definitive evidence of compensation.
Conclusion:
Rs-fMRI graph-theoretical measures characterized network-level differences among aphasic patients, non-aphasic patients, and healthy controls, but the three-group multinomial model did not significantly distinguish the groups and the secondary patient-only regression did not independently distinguish aphasic from non-aphasic tumor patients after demographic adjustment. These findings suggest that graph metrics should be interpreted as exploratory system-level correlates of aphasia status and preserved language rather than stand-alone predictors or definitive markers of compensation.
