Shah Harshal A, Duehr James, Abramyan Arevik, Mittelman Laura, Galvez Rosivel, Winby Taylor, Silverstein Justin W, D'Amico Randy S
Department of Neurosurgery, Lenox Hill Hospital/Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Manhasset, NY, USA.
Department of Neurosurgery, Lenox Hill Hospital/Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Manhasset, NY, USA.
Clin Neurol Neurosurg. 2025 Feb;249:108760. doi: 10.1016/j.clineuro.2025.108760. Epub 2025 Jan 25.
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.
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.
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.
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.
语言是人类认知和功能的关键方面，其保留是左侧额盖神经外科手术干预的首要任务。然而，即使采用电刺激图谱，语言区域的识别也可能不一致。结合术中神经监测使用多模态结构和功能神经影像学检查，可能会增强对皮质语言区域的识别，以指导左侧额盖病变的切除。
使用机器学习软件生成结构和功能连接组扫描，以基于通过解剖、扩散和静息态功能磁共振成像（rs-fMRI）确定的个体结构和功能连接性，重新划分人类连接组计划多模态分区（HCP-MMP）图谱的有效模式。分析结构连接性成像以确定有风险的分区，并对感兴趣区域（ROI）进行基于种子点的分析以识别功能关系。
分析了两名左侧额叶病变患者，一名患有世界卫生组织IV级胶质肉瘤，另一名患有脑内脓肿。通过功能神经影像学检查确定了个体功能连接模式，揭示了语言网络分区之间的独特关系。进行了多模态、连接组引导的手术切除并术中进行神经监测，两名患者在随访时相对于基线均显示语言功能完整或改善。随访成像显示在布罗德曼44区和45区以及语言网络的其他分区之间观察到功能重组。
语言区域结构和功能连接性的术前可视化可纳入多模态手术方法并术中进行神经监测，以促进颅内神经外科手术期间语言区域的保留。这些方法还可用于监测功能恢复。
