In silico model to assess thrombosis risk of TAVR with hemodynamic predictors using fluid structure interaction

Abstract

Abstract The promising results of transcatheter aortic valve replacement (TAVR) over the past two decades indicate an expansion of the patient cohort toward patients with intermediate or low surgical risk. Since some complications of TAVR have already been minimized, subclinical leaflet thrombosis (SLT) has gained importance in recent years. SLT is manifested by a thrombotic layer on the prosthetic leaflets that gradually reduces leaflet motion. The resulting decrease in functionality of the TAVR causes a need for re-intervention. The origin of SLT and approaches to prevent SLT are still unexplored. For this reason, we have developed an in silicomodel that can be used during the design development process of TAVR devices to estimate the thrombosis risk of the implant. Based on passive scalar transport, hemodynamic metrics are used to quantify platelet activation and aggregation which are associated with the formation of thrombosis. In conjunction with a numerical simulation model considering the fluid-structure interaction between the blood mimicking fluid and the TAVR implanted in an aortic root, the thrombosis risk can be modeled. The simulation model can be used to calculate the three-dimensional flow structures within the native sinus and neo-sinus and also provides the ability to derive metrics to assess the risk of thrombosis. We demonstrated that this in silicomodel is a time-effective tool to assess thrombosis risk in TAVR product development.