NSF/FDA SIR: Patient-Specific Computational Assessment of Inferior Vena Cava Filter Performance

下腔静脉（IVC）是将缺氧血液从下肢（中段和腿部）带回心脏的主要静脉。IVC过滤器是植入式医疗器械，旨在捕获由于深静脉血栓形成（静脉或动脉中形成的凝块）而从下肢逃逸的血栓，然后再到达肺部并导致潜在致命的肺栓塞（凝块导致流向肺部的血流阻塞）。尽管每年植入100，000个IVC过滤器，但尽管装置开发了50年，IVC过滤器并发症（包括过滤器断裂、装置迁移、静脉壁穿孔以及过滤器移位和装置向下游运输到心脏）仍然是未解决的问题。其主要原因可能是人体IVC中发生的复杂负载和血流条件，这在临床前试验中未得到考虑。位于查佩尔山的北卡罗来纳州大学和美国食品药品监督管理局之间的这一合作项目旨在建立、验证和确认一个开源计算平台，用于预测IVC过滤器的患者特定性能。该平台将应用于根据临床CT数据重建的多个患者特定模型，以解决有关IVC滤器安全性和有效性的重要问题。在项目完成时，计算平台将作为开源非临床评估模型提交给FDA医疗器械开发工具（MDDT）计划，以便行业可使用该模型预测临床前IVC滤器性能（例如，抗疲劳性、凝块捕获）。由于经过验证和确认的计算平台将作为开源软件发布，其他人可能会使用它来设计下一代IVC过滤器。通过临床验证和适当的监管批准或许可，患者特定建模平台还具有在医院环境中用于优化患者特定设备选择和放置的潜力。本项目的研究目标是建立、验证、确认和应用一个开源计算平台，用于使用FDA收集的数据预测IVC过滤器性能的患者特异性。研究计划有三个目标。第一个目标是建立一个开源计算平台，用于预测患者特定的IVC过滤器性能，该平台的特点是使用开源浸没边界（IB）软件IBAMR（由PI及其研究小组开发和维护），将刚性球形血凝块的高度理想化CFD/6-DOF模型替换为真实柔性凝块的流体-结构相互作用（FSI）模型。开发用于模拟IVC过滤器的凝块捕获的建模和模拟基础设施将是对循环系统中任何地方的真实血凝块建模的现有技术的显著进步（例如，在脑血管系统中用于预测缺血性中风），由于FSI的计算费用，其目前限于对多个刚性球形凝块或相对少量的可变形凝块进行建模。自适应网格细化的浸入边界法的使用将是一个显着的进步，使用单独的贴体网格的流体和结构的方法，因此，需要网格修复，以适应大的结构变形。该项目的方法允许在极其复杂的患者特定几何形状中模拟大量可变形凝块。第二个目标是使用在FDA获得的实验数据验证和确认开源计算平台，从而利用由FDA合作者及其同事设计并由镍钛合金医疗器械领先制造商Confluent Medical Technologies制造的现有通用IVC过滤器。因此，该项目还将推进验证和确认（V V）方法在计算生物力学中的使用，这将成为医疗器械行业正确使用V V技术的一个例子。&&第三个目标是应用开源计算平台来预测多个患者特定模型中的IVC过滤器性能，即，经过验证和确认的计算平台将被用于评估IVC过滤器力学，血流动力学，以及根据患者CT数据重建的多个解剖模型中的凝块捕获性能。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估来支持。

The inferior vena cava (IVC) is the primary vein that brings deoxygenated blood from the lower extremities (midsection and legs) back to the heart. IVC filters are implanted medical devices designed to capture blood clots, which can escape from the lower extremities due to deep vein thrombosis (a clot formed in a vein or an artery), before they reach the lungs and cause a potentially-fatal pulmonary embolism (occlusion of blood flow to the lung caused by a clot). Although 100,000 IVC filters are implanted each year, IVC filter complications (including filter fracture, device migration, perforation of the vein wall, and dislodgment of the filter and transport of the device downstream to the heart) remain unresolved problems despite 50 years of device development. A primary reason for this may be the complex loading and blood flow conditions that occur in the human IVC, which are unaccounted for in pre-clinical testing. This collaborative project between The University of North Carolina at Chapel Hill and the U.S. Food and Drug Administration seeks to establish, verify, and validate an open-source, computational platform for predicting patient-specific performance of IVC filters. This platform will be applied in multiple patient-specific models reconstructed from clinical CT data to address important questions about IVC filter safety and effectiveness. At the completion of the project, the computational platform will be submitted as an open-source non-clinical assessment model to the FDA Medical Device Development Tools (MDDT) program, so that it may be used by industry to predict pre-clinical IVC filter performance (e.g. fatigue resistance, clot trapping). Because the verified and validated computational platform will be released as open-source software, others may use it to design next-generation IVC filters. With clinical validation and appropriate regulatory approval or clearance, the patient-specific modeling platform also has the potential to be used in a hospital setting for optimized patient specific device selection and placement. The research objective of this project is to establish, verify, validate and apply an open-source computational platform for the patient-specific prediction of IVC filter performance using data collected by the FDA. The Research Plan is organized under three objectives. The first objective is to establish an open-source computational platform for predicting patient-specific IVC filter performance that features the replacement of the highly idealized CFD/6-DOF model of rigid, spherical blood clots with fluid-structure interaction (FSI) models of realistic, flexible clots using the open-source immersed boundary (IB) software IBAMR, which is developed and maintained by the PI and his research group. The modeling and simulation infrastructure developed to simulate clot capture by IVC filters will be a significant advance over the current state of the art for modeling realistic blood clots anywhere in the circulatory system (e.g., in the cerebral vasculature for predicting ischemic stroke), which is currently restricted to either modeling multiple rigid spherical clots or a relatively small number of deformable clots due to the computational expense of FSI. The use of the immersed boundary method with adaptive mesh refinement will be a significant advance over approaches that use separate body-fitted meshes for the fluid and structure and, consequently, require mesh repair to accommodate large structural deformations. The project's approach permits the simulation of a large number of deformable clots in extremely complex patient-specific geometries. The second objective is to verify and validate the open-source computational platform using experimental data being acquired at the FDA, thereby leveraging the existing generic IVC filter designed by the FDA collaborator and his colleagues and fabricated by Confluent Medical Technologies, a leading manufacturer of Nitinol medical devices. Thus, the project will also advance the use of verification and validation (V&V) methods in computational biomechanics that will serve as an example to the medical device industry on the proper use of V&V techniques. The third objective is to apply the open-source computational platform to predict IVC filter performance in multiple patient-specific models, i.e., the verified and validated computational platform will be used to evaluate IVC filter mechanics, hemodynamics, and clot trapping performance in multiple anatomical models reconstructed from patient CT data.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.