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.

该副本是利用资源的众多研究子项目之一 由NIH/NCRR资助的中心赠款提供。对该子弹的主要支持 而且，副投影的主要研究员可能是其他来源提供的 包括其他NIH来源。 列出的总费用可能 代表subproject使用的中心基础架构的估计量， NCRR赠款不直接向子弹或副本人员提供的直接资金。 背景： 癫痫影响超过250万美国人，估计有年度医疗保健 每年的费用接近125亿美元。癫痫的药物通常具有重要的一面 效果，目前未能停止多达20％的患者癫痫发作。约有75％ 癫痫患者在童年时期首次癫痫发作。许多人只成为候选人 长时间的部分有效的药物后，手术干预可能具有 衰弱的教育和社会学副作用。该DBP的总体目标是 开发定量分析算法，以显着提高我们检测的能力 并定位癫痫病灶，以便为更多患者提供治疗手术。 理由： 如本提案中所述，技术创新提供了改善的前景 焦点本地化，从而极大地改善了患者的结局。如果焦点是 被认为远离雄辩的皮质，而不是在临界纤维中或附近 途径，可以通过切除或横切成功地处理它们 相关纤维。这些评估依赖于知道癫痫发作的位置，并且 它们与周围结构的关系。由于本地化差，有些患者可能是 被认为无法手术。如果可以开发更准确的焦点定位，则更多的患者 将被视为手术的候选人。 问题： 如今，已经制定了复杂的物理和现实的远期模型 实用的是，实现现代工作站的计算能力成倍增加。 此外，使用计算昂贵的方法可以极大地改善 逆解决方案的可靠性，实现更逼真的偶极模型并使得更好 噪音和伪影排斥。不幸的是，这些技术尚未达到 临床实践。 设计与方法： 每位通过临床癫痫服务确定的患者，以评估作为潜力 将接触手术的候选人，并有机会参加此活动 学习。如果患者选择参加研究，请进行其他数据获取和数据 分析将进行。所有患者将获得标准的临床护理， 涉及每种方式的独立评估。专家对临床视而不见 数据的解释将审查多模式数据融合，并确定是否是否 患者是基于局灶性癫痫的存在的手术干预的候选者 区。