BAYESIAN SOURCE IMAGING OF PEDIATRIC EPILEPSY

小儿癫痫的贝叶斯源成像

• 批准号: 8363719
• 负责人: CHRISTOPHER R. JOHNSON
• 金额: $ 8.88万
• 依托单位: UNIVERSITY OF UTAH
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-08-01 至 2012-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8363719
• 关键词: Adverse effects; Affect; Algorithms; American; Biomedical Computing; Blinded; Childhood; Clinical; Curative Surgery; Data; Data Analyses; Epilepsy; Evaluation; Excision; Fiber; Focal Seizure; Funding; Grant; Health Care Costs; Image; Methods; Modality; Modeling; Morphologic artifacts; National Center for Research Resources; Noise; Operative Surgical Procedures; Outcome; Pathway interactions; Patients; Pharmaceutical Preparations; Physics; Principal Investigator; Research; Research Infrastructure; Resources; Seizures; Services; Solutions; Source; Structure; Technology; United States National Institutes of Health; base; clinical care; clinical practice; cost; data acquisition; design; improved; technological innovation

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.

该子项目是利用资源的众多研究子项目之一 由 NIH/NCRR 资助的中心拨款提供。子项目的主要支持 并且子项目的主要研究者可能是由其他来源提供的， 包括其他 NIH 来源。 子项目可能列出的总成本 代表子项目使用的中心基础设施的估计数量， NCRR 赠款不直接向子项目或子项目工作人员提供资金。 背景： 癫痫症影响超过 250 万美国人，估计每年的医疗保健总额 每年的成本接近 125 亿美元。治疗癫痫的药物通常有显着的副作用 但目前无法阻止多达 20% 的患者癫痫发作。大约 75% 癫痫患者第一次癫痫发作是在儿童时期。许多人只是成为候选人 长期部分有效的药物治疗后进行手术干预可能会导致 使人衰弱的教育和社会学副作用。 DBP 的总体目标是 开发定量分析算法以显着提高我们的检测能力 定位致癫痫病灶，以便为更多患者进行根治性手术。 理由： 正如本提案中所描述的，技术创新提供了改进的前景 病灶定位，从而显着改善患者的治疗效果。如果焦点是 被认为远离口才皮层，而不是在关键纤维中或附近 途径，它们可以被成功治疗，例如，通过切除或横断 相关纤维。这些评估依赖于了解癫痫病灶的位置以及 它们与周围结构的关系。由于定位不良，一些患者可能会 认为无法操作。如果可以开发出更准确的病灶定位，可以帮助更多患者 将被视为手术候选人。 问题： 今天，利用复杂的物理学和现实的正演模型已经 现代工作站的计算能力呈指数级增长，因此变得实用。 此外，使用计算成本较高的方法可以显着提高 逆解的可靠性，实现更真实的偶极子模型并允许更好的 噪声和伪影抑制。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癫痫患者进行评估的患者 将联系手术候选者并给予其参与此活动的机会 学习。如果患者选择参加研究，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， 涉及对每种方式的独立评估。专家对临床视而不见 对数据的解释将审查多模态数据融合并确定是否 根据局灶性癫痫发作的情况，患者适合接受手术干预 区。