Introduction: Many stroke survivors who suffer from aphasia in the acute period experience spontaneous recovery within the first six months post-stroke. About 20% sustain permanent and disabling language problems and the factors that drive incomplete recovery are not clear. Cortical dysfunction may occur in areas seemingly spared by the stroke due to changes to metabolism as well as loss of white matter connectivity and disruption of cortical and subcortical network integrity. We hypothesized that residual white matter connectivity could provide a personalized predictor of the severity of chronic aphasia.
Methods: We reconstructed the individual structural whole-brain connectome from 90 right handed participants with a single left hemisphere ischemic or hemorrhagic stroke. All participants underwent language assessment using the Western Aphasia Battery (WAB-AQ). Data analysis was performed on each subject’s individual connectome, a weighted adjacency matrix M of size 189 x 189. We measured comprehensive white matter topological network organization using Newman’s modularity algorithm and calculated the probability of brain regions clustering together though a community affiliation index, which was used to determine the structural fragmentation of white matter networks in the left hemisphere relative to right hemisphere, expressed by a fragmentation index.
Results: Patients with greater post-stroke left hemisphere network fragmentation and higher modularity index had more severe chronic aphasia, controlling for the size of the stroke lesion. Modularity and fragmentation index significantly increased with aphasia severity (r = -0.42), and (r = -0.43) respectively. Even when the left hemisphere was relatively spared, patients with disorganized community structure had significantly worse aphasia.
Conclusion: Our findings confirm that residual white matter integrity and disorganization of neuronal networks are important determinants of chronic aphasia severity. Furthermore, the assessment of residual connectome white matter organization through modularity provides a comprehensive and personalized measurement that may be used as a marker for clinical staging and aphasia treatment planning.