COMPUTATION OF ELECTRIC FIELD IN TORSO OF CHILD

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 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，因为其种类繁多 形状和大小，从新生儿到青少年，对预期生长的需求，设备的成本 由于电池耗尽而更换，以及这一人群对该设备的心理不容忍。ICD放置 对于成年人来说，虽然更常规，但显然也不是最理想的，会产生浪费的能量，增加疼痛程度，并减少 电池续航时间。在儿童中，结果是基于稀疏经验和 对生物物理学原理一无所知。尽管在许多情况下，这种方法最终是成功的 是临床可接受的纤颤保护，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，当设备植入失败时，没有强有力的指导方针来建议替代方案和 没有工具来评估这种替代方案。 有限元建模已在成人躯干模型中被证明与临床结果有很好的相关性，但并不受欢迎 在儿科人群中使用。也没有出现一个经过普遍验证的软件工具，临床医生可以使用它来 评估装置放置选项，无论是植入前还是植入后。 因此，这种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 可以帮助医生洞察这一重要问题的软件。约翰·特里德曼博士 波士顿儿童医院的心脏病学是该项目的合作调查者，该项目由Dr。 马修·乔利现在是斯坦福大学医学中心的麻醉科住院医师。该项目还拥有当地的 通过伊丽莎白·萨雷尔博士、汤姆·皮尔彻博士和迈克尔·普查尔斯基博士提供的协作支持，他们都来自 盐湖城初级儿童医院的心脏科医生。 因此，主要的临床目标是确定ICD的最佳、患者特定的导联和装置放置的策略。 根据这一临床目标，该项目有三个具体的工程目标： (1)基于CT和MRI数据集创建特定于对象的儿童3D模型，用于内部和外部建模 在SCIRun环境中的除颤； (2)从ICD置入的模拟中探索成功除颤的不同指标； (3)验证临床测量的模拟结果。 该项目中的技术进步解决了创建特定于主题的模型的更大问题，这些模型基于 医学成像数据，包括不同的组织区域。该项目还将推动新的 SCIRun环境中的算法、模块和用户界面元素，它们将在其他情况下得到应用 基于图像的电场建模和仿真(见骨科植骨项目说明 刺激，举例说明为心脏除颤创建的软件如何直接对 不同的应用)。 该项目也代表了SCI(http://www.sci.utah.edu/)和SPL)之间不断扩大的合作的一部分 (http://splweb.bwh.harvard.edu:8000/)，，其目标是为 基于图像的患者特定模型的创建、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.