Multimodal imaging of memory in epilepsy from whole brain networks to local neuronal responses: Implications for surgical decision-making

从全脑网络到局部神经元反应的癫痫记忆多模态成像：对手术决策的影响

• 批准号: 10333627
• 负责人: CARRIE R MCDONALD
• 金额: $ 86.42万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-12-15 至 2025-11-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10333627
• 关键词: Ablation; Address; Age; Amygdaloid structure; Anatomy; Anterior; Anterior Temporal Lobectomy; Benchmarking; Bilateral; Blood Vessels; Brain; Brain region; Clinical; Cognitive; Contralateral; Decision Making; Diffusion; Diffusion Magnetic Resonance Imaging; Electroencephalography; Elements; Employment Status; Epilepsy; Episodic memory; Event; Excision; Face; Fiber; Frequencies; Functional Imaging; Functional Magnetic Resonance Imaging; Functional disorder; Funding; Goals; Grain; Grant; Health; Health Care Costs; Health Status; Healthcare Systems; Hippocampus (Brain); Image; Impairment; Individual; Individual Differences; Investigation; Ipsilateral; Language; Lasers; Lead; Learning; Left; Longevity; Magnetic Resonance Imaging; Measures; Medial; Memory; Memory Loss; Memory impairment; Modeling; Morbidity - disease rate; Multimodal Imaging; Names; National Institute of Neurological Disorders and Stroke; Neocortex; Neurons; Operative Surgical Procedures; Outcome; Parahippocampal Gyrus; Pathology; Patient Care; Patients; Pattern; Performance; Postoperative Period; Predictive Factor; Procedures; Process; Public Health; Quality of life; Refractory; Research; Residual state; Risk; Risk Assessment; Risk Estimate; Role; Sampling; Seizures; Semantic memory; Specificity; Stress; Structure; Technology; Temporal Lobe; Temporal Lobe Epilepsy; Testing; Time; Tissues; Validation; adverse outcome; base; classical conditioning; cognitive neuroscience; dentate gyrus; diffusion weighted; executive function; experience; functional outcomes; high risk; imaging approach; improved; individual patient; innovation; language impairment; minimally invasive; multi-scale modeling; multimodal neuroimaging; multimodality; neocortical; nervous system disorder; neural network; novel; personalized approach; predictive modeling; preservation; prevent; resilience; response; risk minimization; sex; spatiotemporal; surgery outcome; white matter

Anterior temporal lobectomy (ATL) is a highly sucessful treatment for eliminating seizures in patients with temporal lobe epilepsy (TLE). However, ATL-induced memory decline is frequent and often severe, having a deleterious impact on quality of life and functional outcomes. Stereotactic laser amygdalohippocampectomy (SLAH) has been introduced as a minimally-invasive alternative that could minimize risk of memory decline. However, it is unclear which patients would benefit the most from SLAH and whether SLAH decreases risk for critical aspects of episodic memory decline compared to ATL. During the previous grant funding period, we demonstrated the clinical value of combining information from structural (sMRI), diffusion- weighted (dMRI), and functional (fMRI) imaging to better characterize the neural networks that underlie preoperative language and memory impairment and (re)organization and in TLE. We propose that the same multimodal imaging (MMI) approach can be used to quantify risk for postoperative memory decline. In this R01, we extend our MMI approach, combining sMRI/dMRI/fMRI with intracranial recordings (iEEG), enabling us to delve deep into the spatial and temporal dynamics of episodic memory networks in TLE. We employ multimodal associative learning tasks with real-world implications (i.e., pairing a face with a name) that have not before been studied in the surgical context. In addition, we draw from cognitive neurosicence models of hippocampal functioning that may inform why many patients struggle to make fine-grain distinctions in memory (i.e., impaired pattern separation), even when simple item memory appears intact. We propose that our MMI approach will yield a more complete characterization of episodic memory networks in TLE, reveal patterns of structural and functional reorganization in individual patients, and enable a personalized approach to risk assessment when considering surgical options. Finally, we will track cognitive and imaging changes post-ATL and SLAH and identify patient-specific factors that promote reorganization and improved cognitive outcomes. The goals of this renewal are perfectly aligned with the 2020 NINDS Benchmarks for Epilepsy Research (Part IV), which stress the critical need for reseach to limit or prevent adverse consequences of seizures and their treatments across the lifespan. Our renewal directly addresses this request, striving to improve surgical decision-making, which will have an immediate and sustained impact on patient care. Epilepsy is a common neurological disease that costs the healthcare system approximately $15.5 billion annually and can negatively impact quality of life, employment, and health status. The current project has strong implications for public health because it strives to improve health outcomes in patients with epilepsy by using advanced, noninvasive technology to identify individual predictors of memory decline that can help to guide surgical decisions and possibly reduce morbidity associated with removal or ablation of eloquent brain regions.

前颞叶切除术（ATL）是一种非常成功的治疗方法，可消除患者的癫痫发作 颞叶癫痫（TLE）。但是，ATL诱导的记忆下降频繁，通常很严重，具有 对生活质量和功能结果的有害影响。立体定向激光杏仁核膜切除术 （slah）已被引入最小侵入性替代方案，可以最大程度地降低记忆的风险 衰退。但是，目前尚不清楚哪个患者将从slah中受益最大，以及是否slah 与ATL相比，降低了情节记忆下降的关键方面的风险。在上一个赠款期间 资助期，我们证明了结合结构（SMRI），扩散 - 的临床价值 加权（DMRI）和功能性（fMRI）成像，以更好地表征基于的神经网络 术前语言和记忆力障碍以及（重新）组织和TLE。我们提出相同的 多模式成像（MMI）方法可用于量化术后记忆下降的风险。在这个R01中， 我们扩展了MMI方法，将SMRI/DMRI/FMRI与颅内记录（IEEG）相结合，使我们能够 深入研究TLE中情节内存网络的时空动力学。我们采用多模式 具有现实世界中的含义（即将面孔与名称配对）的关联学习任务 在手术环境中进行了研究。此外，我们借鉴了海马的认知神经模型 功能可能会告知为什么许多患者难以在记忆中进行细粒度区分（即受损 模式分离），即使简单的项目内存完好无损。我们建议我们的MMI方法将 在TLE中产生情节记忆网络的更完整表征，揭示结构和 单个患者的功能重组，并启用一种个性化的风险评估方法 考虑手术选择。最后，我们将跟踪ATL和Slah后的认知和成像变化，并确定 促进重组并改善认知结果的患者特异性因素。目标的目标 续签与2020 Ninds基准的癫痫研究（第四部分）完全一致，这 强调提议的关键需求，以限制或防止癫痫发作的不利后果 整个生命周期的治疗。我们的续约直接解决了此请求，努力改善手术 决策将对患者护理产生直接和持续的影响。癫痫是常见的 每年耗费医疗系统的神经疾病，每年约155亿美元 影响生活质量，就业和健康状况。当前的项目对公共卫生有很大的影响 因为它努力通过使用先进的无创，致力于改善癫痫患者的健康结果 确定记忆下降的个体预测因素的技术，可以帮助指导手术决策和 可能会降低与清除或消除雄辩的大脑区域有关的发病率。