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

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.