BAYESIAN SOURCE IMAGING OF PEDIATRIC EPILEPSY

这个子项目是利用资源的许多研究子项目之一。 由NIH/NCRR资助的中心拨款提供。对子项目的主要支持 子项目的首席调查员可能是由其他来源提供的， 包括美国国立卫生研究院的其他来源。为子项目列出的总成本可能 表示该子项目使用的中心基础设施的估计数量， 不是由NCRR赠款提供给次级项目或次级项目工作人员的直接资金。 背景： 癫痫影响着250多万美国人，估计每年有总的医疗保健 每年的成本接近125亿美元。治疗癫痫的药物通常有重要的副作用 目前在高达20%的患者中未能阻止癫痫发作。约75%的 癫痫患者第一次发作是在童年。许多人只成为候选人 在长期部分有效的药物治疗后进行手术干预 衰弱的教育和社会学副作用。这个DBP的总体目标是 开发定量分析算法以显著提高我们的检测能力 和定位致痫灶，以使更多的患者能够进行根治性手术。 基本原理： 技术创新，如本提案所述，提供了改进的前景 病灶定位，从而极大地改善患者的预后。如果焦点是 被认为远离能言善辩的皮质，而不是在关键纤维或其附近 例如，通过切除或横断术，可以成功地治疗这些路径 相关纤维。这些评估依赖于了解癫痫发作灶的位置和 它们与周围结构的关系。由于定位不佳，一些患者可能 被认为是无法手术的。如果能够开发出更准确的病灶定位，更多的患者 将被认为是手术的候选人。 问题： 今天，复杂的物理和现实的正演模型的使用已经完成。 现代工作站的计算能力呈指数级增长，非常实用。 此外，使用计算代价高昂的方法可以显著提高 逆解的可靠性，实现了更真实的偶极子模型，并允许更好的 噪音和伪影排斥。不幸的是，这些技术还没有达到 临床实践。 设计与方法： 每个被临床癫痫服务机构确定为潜在评估的患者 手术候选人将被接洽，并有机会参与这一活动 学习。如果患者选择参与研究，则需要额外的数据采集和数据 将进行分析。所有患者都将接受标准的临床护理， 涉及对每种医疗模式的独立评估。专家对临床视而不见 对数据的解释将审查多通道数据融合并确定 患者是基于局灶性癫痫发作的外科干预的候选对象。 区域。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. Background: Epilepsy affects over 2.5 million Americans and has an estimated total annual health care cost close to $12.5 billion per year. Medications for epilepsy often have significant side effects and currently fail to halt seizures in up to 20% of patients. Approximately 75% of epilepsy patients have their first seizure in childhood. Many only become candidates for surgical intervention after a long period of partially-effective medication that can have debilitating educational and sociological side effects. The overall objective of this DBP is to develop quantitative analysis algorithms to dramatically improve our capacity to detect and localize epileptogenic foci, in order to enable curative surgery for more patients. Rationale: Technological innovations, as described in this proposal, offer the prospect of improving foci localization and thereby dramatically improving patient outcomes. If foci are considered to be away from eloquent cortex, rather than in or nearby critical fiber pathways, they may be successfully treated, for example, by resection or transection of related fibers. These assessments rely on knowing where the seizure foci are located and their relationship to surrounding structures. With poor localization, some patients may be considered inoperable. If more accurate foci localization can be developed, more patients will be considered candidates for surgery. Questions: Today, the use of sophisticated physics and realistic forward models has been made practical by the exponentially increasing compute capacity of modern workstations. Furthermore, the use of computationally expensive methods can dramatically improve the reliability of the inverse solution, enabling more realistic dipole models and allowing better noise and artifact rejection. Unfortunately, these technologies have not yet reached clinical practice. Design & Methods: Each patient who is identified by the clinical epilepsy service for evaluation as a potential candidate for surgery will be approached and given the opportunity to participate in this study. If a patient chooses to participate in the study, additional data acquisition and data analysis will be carried out. All patients will receive the standard clinical care, which involves independent assessment of each modality. Experts blinded to the clinical interpretation of the data will review the multi-modality data fusion and determine if the patient is a candidate for surgical intervention based on the presence of a focal seizure zone.