Objectives: Language is a critical aspect of human cognition and function, and its preservation is a priority for neurosurgical interventions in the left frontal operculum. However, identification of language areas can be inconsistent, even with electrical mapping. The use of multimodal structural and functional neuroimaging in conjunction with intraoperative neuromonitoring may augment cortical language area identification to guide the resection of left frontal opercular lesions.
Methods: Structural and functional connectome scans were generated using a machine learning software to reparcellate a validated schema of the Human Connectome Project Multi-Modal Parcellation (HCP-MMP) atlas based on individual structural and functional connectivity identified through anatomic, diffusion, and resting-state functional MRI (rs-fMRI). Structural connectivity imaging was analyzed to determine at-risk parcellations and seed-based analysis of regions of interest (ROIs) was performed to identify functional relationships.
Results: Two patients with left frontal lesions were analyzed, one with a WHO Grade IV gliosarcoma, and the other with an intracerebral abscess. Individual patterns of functional connectivity were identified by functional neuroimaging revealing distinct relationships between language network parcellations. Multimodal, connectome-guided resections with intraoperative neuromonitoring were performed, with both patients demonstrating intact or improved language function relative to baseline at follow-up. Follow-up imaging demonstrated functional reorganization observed between Brodmann areas 44 and 45 and other parcellations of the language network.
Conclusion: Preoperative visualization of structural and functional connectivity of language areas can be incorporated into a multimodal operative approach with intraoperative neuromonitoring to facilitate the preservation of language areas during intracranial neurosurgery. These modalities may also be used to monitor functional recovery.