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)：癫痫复发和难治性导致癫痫患者的显著发病率和死亡率，以及巨大的个人和社会代价。抗癫痫药物(AED)治疗往往伴随着一个缓解和复发的过程，许多患者并没有达到癫痫发作的自由。除了特定的危险因素外，增加患者癫痫复发风险的原因尚不完全清楚。关键的是，最终导致癫痫的病理过程很可能在疾病临床发作之前就开始了，这使得早期干预变得有吸引力。晚期癫痫患者的大脑功能组织发生了根本性的改变。这项研究的长期目标是使用功能神经成像技术来确定早期癫痫(理想情况下是临床前癫痫)的脑功能重组模式，这些模式可以预测未来的疾病严重程度，并可被医生用来指导早期干预和更积极的治疗。中心假说是癫痫临床发作时大脑的功能重组。 疾病反映了潜在的癫痫形成过程，包括个人癫痫复发的倾向，而疾病后期发生的变化反映了疾病进展/癫痫负担。因此，该项目有两个目标。第一个目标是对成人进行前瞻性的纵向研究，以评估早期癫痫患者的功能网络变化，并确定它们是否可以预测癫痫复发或难治性。第二个目标是利用华盛顿大学极具支持性的环境，为候选人提供1)纵向研究设计和实施方法以及2)应用于多维系统的多变量统计方法的培训，例如那些与功能连接研究的系统。其目标是支持R01应用程序的开发，并通过一个研究计划支持向独立性的进展，该研究计划使用先进的神经成像技术来前瞻性地研究癫痫，从疾病的早期开始。该项目的研究结果将对临床实践有很大的适用性。具体地说，使用异常功能网络特性在早期阶段预测疾病严重程度的能力可以通过在疗程早期引导临床医生进行更积极的AED治疗，并允许跟踪疾病进展和及早考虑其他治疗方案，包括癫痫手术，从而显著降低发病率和死亡率。此外，通过这项建议获得的数据将成为一项更大规模的前瞻性纵向研究的基础，该研究旨在将这一知识转化为针对该疾病的个性化干预措施 它会造成不可逆转的损害。