PREDICTING SEIZURE RECURRENCE USING BASELINE FUNCTIONAL NETWORK CHANGES IN EARLY

利用早期基线功能网络变化预测癫痫发作复发

• 批准号: 8877654
• 负责人: Luigi Maccotta
• 金额: $ 18.13万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-07-01 至 2019-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8877654
• 关键词: Adult; Affect; Age; Antiepileptic Agents; Attention; Biological Neural Networks; Blood; Brain; Brain imaging; Brain region; Clinical; Data; Development; Disease; Disease Progression; Disease remission; Early Intervention; Epilepsy; Freedom; Future; Goals; Health; Imaging Techniques; Individual; Intervention; Knowledge; Life; Longitudinal Studies; MRI Scans; Magnetic Resonance Imaging; Medical; Methods; Morbidity - disease rate; Motor; Onset of illness; Operative Surgical Procedures; Pathologic Processes; Patient risk; Patients; Pattern; Pharmaceutical Preparations; Pharmacotherapy; Physicians; Process; Property; Recurrence; Relapse; Research; Research Design; Research Project Grants; Resistance; Rest; Risk; Risk Factors; Seizures; Series; Severity of illness; Source; Staging; System; Techniques; Therapeutic; Time; Training; Translating; Universities; Washington; aggressive therapy; base; clinical practice; cohort; collaborative environment; cost; indexing; mortality; neuroimaging; pre-clinical; programs; prospective; response; somatosensory; statistics

DESCRIPTION (provided by applicant): Seizure recurrence and intractability cause significant morbidity and mortality in patients with epilepsy, as well as significant individual and societal costs. Antiepileptic drug (AED) therapy often follows a course of remission and relapse, and many patients do not achieve seizure freedom. What increases patient's risk for seizure recurrence remains incompletely understood, except for specific risk factors. Critically, the pathologic process that ultimately leads to epilepsy likely begins well before the clinical onset o the disease, making early intervention attractive. The functional organization of the brain of patients with late stage epilepsy is fundamentally altered. The long-term goal of this research is to use functional neuroimaging techniques to identify patterns of brain function reorganization in early epilepsy (and ideally preclinical epilepsy) that predict future disease severity and can be used by physicians to guide early intervention and more aggressive therapy. The central hypothesis is that the functional reorganization of epileptic brains near the clinical onset of the disease reflects the underlying epileptogenic process, including an individual's propensity for seizure recurrence, while changes that occur in later stages of the disease reflect disease progression/seizure burden. This project has thus two objectives. The first objective is for the candidate to use a prospective, longitudinal study of adults to assess functional network changes in early epilepsy and determine whether they can predict seizure recurrence or intractability. The second objective is to leverage the extremely supportive environment at Washington University to provide the candidate with training in 1) methods of longitudinal study design and conduction and 2) methods of multivariate statistics applied to multidimensional systems, such as those studied with functional connectivity. The goal is to support the development of an R01 application and a progression to independence with a research program that uses advanced neuroimaging techniques to study epilepsy prospectively, beginning in the early stages of the disease. Findings from this project would have great applicability to clinical practice. Specifically the ability to predict disease severity at an early stage using abnormal functional network properties could significantly reduce morbidity and mortality by leading clinicians to pursue more aggressive AED therapy earlier in the course, and by allowing tracking of disease progression and early consideration of other therapeutic options, including epilepsy surgery. Furthermore the data obtained with this proposal will be the basis of a larger prospective longitudinal study in the functional network changes of early epilepsy, with the goal of translating this knowledge into individually tailored interventions targeting the disease before it produces irreversible damage.

描述（由申请人提供）：癫痫病的癫痫发作和顽固性导致癫痫患者以及重要的个人和社会成本引起明显的发病率和死亡率。抗癫痫药（AED）疗法通常遵循缓解和复发的过程，许多患者无法获得癫痫发作自由。除特定的风险因素外，增加患者癫痫发作的风险的原因尚不完全理解。至关重要的是，最终导致癫痫病的病理过程可能始于疾病临床发作之前，使早期干预具有吸引力。晚期癫痫患者大脑的功能组织从根本上改变了。这项研究的长期目标是使用功能性神经影像学技术来识别早期癫痫病（理想情况下是临床前癫痫）中脑功能重组模式，这些模式可以预测未来的疾病严重程度，并且可以被医生使用来指导早期干预和更具侵略性的治疗。中心假设是在临床开始附近癫痫大脑的功能重组 疾病反映了潜在的癫痫发作过程，包括个人癫痫发作的倾向，而在疾病后期发生的变化反映了疾病进展/癫痫发作负担。因此，该项目有两个目标。第一个目标是候选人使用对成年人的前瞻性纵向研究来评估早期癫痫病的功能网络变化，并确定他们是否可以预测癫痫发作复发或棘手性。第二个目标是利用华盛顿大学极为支持的环境为候选人提供培训1）纵向研究设计和传导方法以及2）应用于多维系统的多元统计方法，例如具有功能连接性的研究。目的是支持R01应用的开发，并通过研究计划的发展计划，该计划使用先进的神经影像学技术来前瞻性地研究癫痫病，始于疾病的早期阶段。该项目的发现将非常适用于临床实践。特别是，使用异常功能网络特性预测早期疾病严重程度的能力可以显着降低该课程早期早期进行更具侵略性AED治疗的发病率和死亡率，并允许跟踪疾病进展并早期考虑其他治疗选择，包括癫痫手术。此外，通过该提案获得的数据将是早期癫痫的功能网络变化中的一项前瞻性纵向研究的基础，目的是将这些知识转化为针对该疾病的单独定制干预措施 它会产生不可逆转的损害。