Virtual Resection to Treat Epilepsy

全球6500万癫痫患者中有三分之一以上(美国约330万)有癫痫发作，不能 被药物控制。手术和植入设备是许多人的选择，但它们的成功取决于 人工绘制癫痫网络图，这只对一些患者是可能的，而且标准化程度很低。 当确定手术靶点时，目前还没有严格的方法来选择最佳的手术入路。 这项建议的总体目标是开发严格、标准化、量化的方法来：(1)地图 来自成像和立体脑电(SEEG)的癫痫网络，(2)选择最佳区域进行切除、消融或 根据他们的数据和临床假说对个别患者的神经调节，以及(3)确定何时局部 干预不太可能成功。这些方法将对临床护理产生巨大的积极影响。 在这笔赠款的头四年里，我们在实现这些目标方面取得了实质性进展。我们的 交付成果包括：(1)源自颅内EEG(IEEG)的强大测量，可预测以下方面的结果 癫痫手术；(2)定位癫痫网络并预测不同影响的个性化方法 癫痫控制的干预措施；(3)结合MRI和iEEG预测癫痫传播路径的工具； 以及(4)在我们的平台http：//ieeg.org上公开分享我们的方法、数据、结果和代码的记录。 在下一阶段，我们为癫痫手术所需的三个基本挑战提出创新的解决方案。 为了将我们的工作转化为实践：(1)指导SEEG：我们必须使我们的方法适应较稀疏的采样 以及不同的立体脑电原理，它绘制了一个连接的大脑区域网络，并测试临床 关于癫痫发作起始和传播地点的假设；(2)评估抽样偏差和缺失 信息：我们将开发确定电极是否对癫痫患者的所有关键区域进行采样的方法 网络，以确保我们不会因信息缺失而错误定位；(3)在更大的人口中验证 跨中心：在改进上述方法的同时，我们将在较大范围内验证和优化我们的分析 为前瞻性临床试验准备这项工作的患者数量。在一个新的模型中，我们聘请了一个 由主要外科癫痫中心组成的小组公开合作，标准化方法，汇总数据，并 在http：//ieeg.org上共享所有算法、计算机代码、数据和结果。我们的中心假设是 指导癫痫手术的标准化、量化方法可以改善患者的预后，降低发病率， 降低成本并实现跨中心的统一、更高质量的护理。 这项工作意义重大，因为它融合了最先进的网络神经科学、工程学、神经学和 神经外科，使实用的工具，以改善和标准化病人护理。这个项目利用了一个蓬勃发展的 神经学、计算神经科学、神经外科、神经成像和 宾夕法尼亚大学的生物工程，已经产生了58篇与这项提议有关的出版物。 我们现在将这种合作扩展到美国和世界各地的癫痫学术中心。

More than 1/3 of the world’s 65 million people with epilepsy (~3.3 million in the U.S.) have seizures that cannot be controlled by medications. Surgery and implanted devices are options for many, but their success depends upon manually mapping epileptic networks, which is only possible for some patients, and poorly standardized. When surgical targets are identified, there is currently no rigorous way to select the best surgical approach. The overall aim of this proposal is to develop rigorous, standardized, quantitative methods to: (1) map epileptic networks from imaging and Stereo EEG (SEEG), (2) pick the best region for resection, ablation or neuromodulation for individual patients from their data and clinical hypotheses, and (3) to determine when focal intervention is unlikely to succeed. These methods would have tremendous positive impact on clinical care. Over the first four years of this grant we have made substantial progress towards these goals. Our deliverables include: (1) robust measures derived from intracranial EEG (IEEG) that predict outcome from epilepsy surgery; (2) personalized methods that localize epileptic networks and predict the impact of different interventions on seizure control; (3) tools that predict the path of seizure spread from combined MRI and iEEG; and (4) a track record of openly sharing our methods, data, results and code on our platform http: //ieeg.org. In the next phase, we propose innovative solutions to 3 fundamental challenges in epilepsy surgery required to translate our work into practice: (1) Guiding SEEG: We must adapt our methods to the sparser sampling and different philosophy of stereo EEG, which maps a network of connected brain regions and tests clinical hypotheses about where seizures initiate and propagate; (2) Assessing sampling bias and missing information: We will develop methods to determine if electrodes sample all key regions of the epileptic network, to ensure we do not falsely localize due to missing information; (3) Validating in a larger population across centers: In parallel to refining the above methods, we will validate and optimize our analyses in a large number of patients to ready this work for a prospective clinical trial. In a novel model, we have engaged a group of major surgical epilepsy centers to openly collaborate, standardize methods, aggregate data, and share all algorithms, computer code, data and results on http: //ieeg.org. Our central hypothesis is that standardized, quantitative methods to guide epilepsy surgery can improve patient outcomes, lower morbidity, reduce cost and enable uniform, higher quality care across centers. This work is significant because it merges state of the art network neuroscience, engineering, neurology and neurosurgery to make practical tools to improve and standardize patient care. This project leverages a thriving collaboration between experts in neurology, computational neuroscience, neurosurgery, neuroimaging and bioengineering at the University of Pennsylvania that has generated 58 publications related to this proposal. We now extend this collaboration to academic epilepsy centers across the United States and worldwide.