Department of Neurology, School of Medicine, Emory University, Atlanta, Georgia, U.S.A.
Zucker School of Medicine at Hofstra/Northwell, Hempstead, New York, U.S.A.
J Clin Neurophysiol. 2024 May 1;41(4):317-321. doi: 10.1097/WNP.0000000000001071. Epub 2024 Feb 20.
Current preoperative evaluation of epilepsy can be challenging because of the lack of a comprehensive view of the network's dysfunctions. To demonstrate the utility of our multimodal neurophysiology and neuroimaging integration approach in the presurgical evaluation, we present a proof-of-concept for using this approach in a patient with nonlesional frontal lobe epilepsy who underwent two resective surgeries to achieve seizure control. We conducted a post-hoc investigation using four neuroimaging and neurophysiology modalities: diffusion tensor imaging, resting-state functional MRI, and stereoelectroencephalography at rest and during seizures. We computed region-of-interest-based connectivity for each modality and applied betweenness centrality to identify key network hubs across modalities. Our results revealed that despite seizure semiology and stereoelectroencephalography indicating dysfunction in the right orbitofrontal region, the maximum overlap on the hubs across modalities extended to right temporal areas. Notably, the right middle temporal lobe region served as an overlap hub across diffusion tensor imaging, resting-state functional MRI, and rest stereoelectroencephalography networks and was only included in the resected area in the second surgery, which led to long-term seizure control of this patient. Our findings demonstrated that transmodal hubs could help identify key areas related to epileptogenic network. Therefore, this case presents a promising perspective of using a multimodal approach to improve the presurgical evaluation of patients with epilepsy.
由于缺乏对网络功能障碍的全面了解,目前对癫痫的术前评估具有一定挑战性。为了展示我们的多模态神经生理学和神经影像学整合方法在术前评估中的效用,我们提供了一个概念验证,使用该方法对一名非病变性额叶癫痫患者进行了两次切除术以实现癫痫控制。我们使用了四种神经影像学和神经生理学模式进行了事后调查:弥散张量成像、静息状态功能 MRI 和静息和发作期间的立体脑电图。我们为每种模式计算了基于感兴趣区域的连通性,并应用了介数中心性来识别跨模式的关键网络枢纽。我们的结果表明,尽管癫痫发作的症状学和立体脑电图表明右侧眶额区域功能障碍,但跨模式枢纽的最大重叠延伸至右侧颞区。值得注意的是,右侧颞中回区域是弥散张量成像、静息状态功能 MRI 和静息立体脑电图网络的重叠枢纽,仅在第二次手术中被切除,这导致了该患者的长期癫痫控制。我们的研究结果表明,跨模态枢纽可以帮助确定与致痫网络相关的关键区域。因此,该病例提出了使用多模态方法来改善癫痫患者术前评估的有前景的观点。