COMPUTATION OF ELECTRIC FIELD IN TORSO OF CHILD

该子项目是利用 由NIH/NCRR资助的中心赠款提供的资源。子项目和 研究者（PI）可能从另一个NIH来源获得主要资金， 因此可以在其他CRISP条目中表示。列出的机构是 中心，不一定是研究者的机构。 植入式心脏除颤器（ICD）在儿童中的放置是一个独特且具有挑战性的问题，因为从新生儿到青少年的形状和尺寸多种多样，需要预期生长，由于电池耗尽导致的设备更换成本以及该人群对设备的心理不耐受。 成人ICD植入虽然更常规，但显然也不是最佳的，会浪费能量，增加疼痛程度，缩短电池寿命。 在儿童中的结果是基于稀疏的经验和对生物物理学原理的无知的一系列设备放置策略。虽然在许多情况下，这种方法最终是成功的，因为其结果是临床上可接受的纤颤保护，但缺乏连贯的策略导致整体管理效率低下。 此外，在成人和儿童中，当器械植入失败时，没有强有力的指南来建议替代方案，也没有工具来评估这些替代方案。 有限元建模已被证明在成人躯干模型与临床结果相关，但尚未享受在儿科人群中使用。 也没有出现一个普遍验证的软件工具，临床医生可以使用它来评估设备放置选项，无论是在植入之前还是之后。 因此，这项合作的目标是在儿童躯干模型中模拟除颤，以开发优化策略和软件，帮助医生深入了解这一重要问题。 波士顿儿童医院心脏病科的John Triedman博士是该项目的合作研究者，Matthew Jolley博士协助该项目，Matthew Jolley博士现在是斯坦福大学医学中心的麻醉科住院医师。 该项目还通过来自湖城初级儿童医院心脏科的Elizabeth Saarel、Tom Pilcher和Michael Puchalski博士获得了当地的合作支持。 因此，主要临床目标是确定ICD的最佳、患者特定电极导线和器械放置策略。从该临床目标中得出本项目的三个具体工程目标： (1)基于CT和MRI数据集创建儿童的受试者特定3D模型，用于在SCIRun环境中对内部和外部除颤进行建模;（2）探索可以从ICD放置模拟中得出的成功除颤的不同指标。 (3)从临床测量中获得模拟结果。 该项目的技术进展解决了创建基于医学成像数据并包括不同组织区域的受试者特定模型的更大问题。 该项目还将推动SCIRun环境中新算法、模块和用户界面元素的开发，这些新算法、模块和用户界面元素将应用于其他基于图像的电场建模和模拟情况（参见骨科骨植入物刺激项目的描述，以了解为心脏除颤创建的软件如何直接用于截然不同的应用）。 该项目也是SCI（http：//www.sci.utah.edu/）与 SPL（http：//splweb.bwh.harvard.edu：8000/），其目标是创建兼容性集成开源工具，用于从基于图像的患者特定模型创建、可视化和计算模拟。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Placement of Implantable Cardiac Defibrillators (ICDs) in children is a unique and challenging problem due to the variety of shapes and sizes, ranging from neonate to adolescent, the need for anticipating growth, the cost of device replacement due to battery drainage, and the psychological intolerance of the device by this population. ICD placement in adults, while more routine, is also clearly suboptimal, producing wasted energy, increased pain levels, and reduced battery life. The result in children is an ad hoc array of device placement strategies, based on sparse experience and ignorant of biophysical principles. Although in many cases this approach is ultimately successful in as much as the result is clinically acceptable fibrillation protection, the lack of cohesive strategy leads to inefficient overall management. Moreover, when, in adults and children, a device implant fails, there are no robust guidelines to suggest alternatives and no tools to evaluate such alternatives. Finite element modeling has been shown in adult torso models to correlate well with clinical results but has not enjoyed use in the pediatric population. Nor has there emerged a generally validated software tool that clinicians can use to evaluate device placement options, neither before nor after implantation. Thus, the goal of this collaboration is to model defibrillation in child torso models to develop optimization strategies and software that could help physicians gain insight into this important problem. Dr. John Triedman at the Department of Cardiology, Children's Hospital Boston is the collaborative investigator of this project, assisted in the project by Dr. Matthew Jolley, now an anesthesiology resident at Stanford University Medical Center. The project also has local collaborative support through Drs. Elizabeth Saarel, Tom Pilcher, and Michael Puchalski, all from the Department of Cardiology at Primary Childrens' Hospital in Salt Lake City. The main clinical goal is thus to Determine strategies for optimal, patient specific lead and device placements of ICDs. From this clinical goal come three specific engineering aims of this project: (1) Create subject specific 3D models of children based on CT and MRI data sets for modeling internal and external defibrillation in the SCIRun environment; (2) Explore different metrics of successful defibrillation that can be derived from simulations of ICD placement. (3) Validate simulation results from clinical measurements. Technical progress in this project addresses the larger question of creating subject specific models that are based on medical imaging data and that include different tissue regions. The project will also drive the development of new algorithms, modules, and user interface elements in the SCIRun environment that will find application in other cases of image based modeling and simulation of electric fields (see description of the project on orthopedic bone implant stimulation for an example of how software created for cardiac defibrillation was directly useful for a dramatically different application). The project also represents part of an expanding collaboration between SCI (http://www.sci.utah.edu/) and SPL (http://splweb.bwh.harvard.edu:8000/), the goal of which is to create compatibility integrated open source tools for the creation, visualization, and computational simulation from image based, patient specific models.