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.

项目概要/摘要 局灶性癫痫是最常见的癫痫形式，是一种影响 5000 万人的衰弱性疾病 全世界。大约 30-40% 的局灶性癫痫患者持续出现使人衰弱的癫痫发作，尽管 最大程度的药物治疗。癫痫手术可以通过切除、消融或切除来消除或减少癫痫发作 对产生癫痫发作的区域（“致癫痫区”，EZ）进行神经刺激。然而，33-50% 的患者 接受手术的患者术后仍会出现癫痫发作。术后的重要决定因素 结果是术前准确的 EZ 侧化和定位。 50% 的患者出现偏侧化和 定位需要在医院使用立体脑电图 (SEEG) 进行侵入性颅内监测 数天至数周来记录多次癫痫发作。这种侵入性诊断过程会导致显着的发病率 患者的发作（癫痫发作）活动有时可能具有挑战性、不准确、 并且无法捕获患者的所有癫痫类型。静息状态（癫痫发作之间）SEEG 分析可能 通过识别 EZ 来补充临床解释，无需进行发作记录。除了 SEEG，扩散 MRI (DWI) 和神经刺激也已被用于尝试 EZ 偏侧化和定位。这些研究 依赖于生成大脑区域的连接网络并提取预测 EZ 位置的特征，但是 这些数据的 EZ 侧化和定位精度并不理想。然而，很少有研究 评估涉及 EZ 的连接模式的方向性。因此，从之前的构建 神经生理学工作显示局灶性癫痫中 EZ 的强直性抑制，我们假设 与正常状态相比，EZ 的电生理静息态抑制性内向连接将显着增加。 与非 EZ 一样，因此是预测大脑区域致癫痫性的关键。进一步整合之前的工作 通过神经科学和神经心理学领域的研究，我们还假设特定的 DWI 衍生 结构网络的改变对于侧化 EZ 和预测手术结果非常重要。我们的首要目标是 开发定向连接措施，使用简短的静息态 SEEG 记录可靠地识别 EZ，以及 神经刺激课程（目标 1）。然后，我们寻求确定非侵入性结构连接措施 使用 DWI 使 EZ 偏侧化并预测手术结果，最终减少侵入性颅内手术的需要 监控。我们将通过对 DWI 生成的结构连通图进行高级网络分析来实现这一点 （目标 2）。拟议的奖学金将在合作研究氛围中提供研究培训 转化神经科学和工程研究的专家导师。研究培训将在 结合学术医疗中心和 4 级癫痫中心、世界一流成像的环境 研究所和工程都在一个校园内，确保了一个独特的环境，适合所有方面的优秀培训 这项拟议工作的各个方面。研究多种方式来表征癫痫网络并定位 EZ 有潜力大大改善患有这种破坏性神经系统疾病的患者的生活。