Directed connectivity analysis of resting-state SEEG and DWI to improve lateralization and localization in focal epilepsy

静息态 SEEG 和 DWI 的定向连接分析可改善局灶性癫痫的偏侧化和定位

• 批准号: 10533285
• 负责人: Graham Walter Johnson
• 金额: $ 2.08万
• 依托单位: VANDERBILT UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-01 至 2023-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10533285
• 关键词: Ablation; Academic Medical Centers; Address; Adverse event; Affect; Area; Bilateral; Biological Markers; Brain; Brain region; Characteristics; Clinical; Community Networks; Data; Detection; Diagnostic; Diffusion; Diffusion Magnetic Resonance Imaging; Disease; Electrodes; Electroencephalography; Electrophysiology (science); Engineering; Ensure; Environment; Epilepsy; Evoked Potentials; Excision; Failure; Fellowship; Future; Generations; Goals; Handedness; Hospitalization; Image; Inpatients; Institutes; Intervention; Left; Length of Stay; Location; Magnetic Resonance Imaging; Maps; Measures; Medical; Mentors; Modality; Modeling; Molecular; Monitor; Morbidity - disease rate; Nature; Neuropsychology; Neurosciences; Operative Surgical Procedures; Outcome; Partial Epilepsies; Pathway Analysis; Patients; Pattern; Persons; Phenotype; Postoperative Period; Process; Recurrence; Refractory; Regulation; Research; Research Personnel; Research Training; Resolution; Rest; Sampling; Scalp structure; Seizures; Techniques; Temporal Lobe Epilepsy; Time; Training; Work; disease phenotype; experience; feature extraction; improved; independent component analysis; minimally invasive; nervous system disorder; network dysfunction; neuroimaging; neurophysiology; outcome prediction; prognostic; scientific atmosphere; specific biomarkers; success; surgery outcome; translational neuroscience

PROJECT SUMMARY/ABSTRACT Focal epilepsy is the most common form of epilepsy, a debilitating disorder that affects 50 million people worldwide. Approximately 30-40% of patients with focal epilepsy continue to have debilitating seizures despite maximal medical therapy. Epilepsy surgery can eliminate or reduce seizures using resection, ablation, or neurostimulation of regions that generate seizures (“Epileptogenic Zones”, EZs). However, 33-50% of patients that undergo surgery continue to have seizures post-operatively. An important determinate of post-operative outcome is accurate pre-surgical lateralization and localization of EZs. In 50% of patients, lateralization and localization requires invasive intracranial monitoring with stereo-electroencephalography (SEEG) in the hospital for days to weeks to record multiple seizures. This invasive diagnostic process causes significant morbidity to the patient, and interpretation of ictal (seizure) activity from SEEG may sometimes be challenging, inaccurate, and incapable of capturing all the patient’s seizure types. Resting-state (between seizures) SEEG analysis may supplement clinical interpretation by identifying EZs without requiring ictal recordings. Beyond SEEG, diffusion MRI (DWI) and neurostimulation have also been used to attempt EZ lateralization and localization. These studies rely on generating connectivity networks of brain regions and extracting features that predict EZ locations, but EZ lateralization and localization accuracy with these data has been suboptimal. However, few studies have evaluated the directionality of connectivity patterns involving EZs. Therefore, building from previous neurophysiological work that shows tonic inhibition of EZs in focal epilepsy, we hypothesize that electrophysiological resting-state inhibitory inward directed connectivity of EZs will be markedly increased vs. that of Non-EZs, and thus key to predicting epileptogenicity of brain regions. Further, integrating previous work done across the fields of neuroscience and neuropsychology, we also hypothesize specific DWI-derived structural network alterations that are important to lateralize EZs and predict surgical outcome. Our first goal is to develop directed connectivity measures to reliably identify EZs using brief resting-state SEEG recordings and neurostimulation sessions (Aim 1). We then seek to identify noninvasive structural connectivity measures to lateralize EZs and predict surgical outcome using DWI to ultimately reduce the need for invasive intracranial monitoring. We will do this through advanced network analysis of DWI-generated structural connectivity maps (Aim 2). This proposed fellowship will provide research training in a collaborative research atmosphere with expert mentors in translational neuroscience and engineering research. Research training will be conducted in an environment that combines an academic medical center with a level 4 epilepsy center, world class imaging institute, and engineering all on one campus, ensuring an environment uniquely suited to excellent training in all aspects of this proposed work. Studying multiple modalities to characterize epileptic networks and localize EZs has the potential to drastically improve the lives of patients living with this devastating neurological disorder.

项目摘要/摘要 局灶性癫痫是癫痫的最常见形式，这是一种使人衰弱的疾病，影响了5000万人 全世界。大约30-40％的局灶性癫痫患者继续具有使人衰弱的目的地 最大药物疗法。癫痫手术可以使用切除，消融或减少癫痫发作 产生癫痫发作的区域的神经刺激（“癫痫发作区”，EZS）。但是，有33-50％的患者 该手术在术后继续进行癫痫发作。术后的重要确定 结果是EZS的准确外侧侧向化和定位。在50％的患者中，横向化和 本地化需要在医院内用立体情绪摄影（SEEG）进行侵入性颅内监测 在数天到几周内记录多次癫痫发作。这种侵入性诊断过程导致明显的发病率 患者以及对Seeg的发作（癫痫发作）活性的解释有时可能具有挑战性，不准确， 并且无法捕获所有患者的癫痫发作类型。休息状态（在癫痫发作之间）seeg分析可能 通过识别EZ不需要发作记录来补充临床解释。超越seeg，扩散 MRI（DWI）和神经刺激也已用于尝试EZ横向化和定位。这些研究 依靠生成大脑区域的连接网络并提取预测EZ位置的功能，但是 这些数据的EZ横向化和定位精度是次优的。但是，很少有研究 评估了涉及EZ的连接模式的方向性。因此，从以前的 在局灶性癫痫中表现出强直抑制EZ的神经生理学工作，我们假设 电生理静止状态抑制EZS的内向连通性将显着增加VS。 非ezs，因此是预测大脑区域癫痫发作的关键。此外，整合以前的工作 在神经科学和神经心理学领域完成，我们还假设特定的DWI衍生 结构网络改变对于侧向EZ和预测手术结果很重要。我们的第一个目标是 制定定向连接措施以使用简短的休息状态seeg记录和 神经刺激会议（AIM 1）。然后，我们寻求确定无创结构连通性措施 侧向EZS并使用DWI预测手术结局，以最终减少侵入性颅内的需求 监视。我们将通过对DWI生成的结构连接图的高级网络分析来做到这一点 （目标2）。拟议的奖学金将在协作研究氛围中提供研究培训 转化神经科学与工程研究专家指导者。研究培训将在 一个将学术医学中心与4级癫痫中心（世界一流成像）结合起来的环境 研究所，以及一个在一个校园中的工程，确保环境独特地适合于所有人的出色培训 这项拟议工作的各个方面。研究多种方式以表征癫痫网络并定位EZ 有可能会大大改善这种毁灭性神经系统疾病的患者的生活。