In-silico study of the device-related thrombosis after transcatheter aortic valve implantation

Abstract

Transcatheter aortic valve implantation (TAVI) is a minimally invasive heart procedure that has emerged as a safe and effective treatment for patients with symptomatic aortic stenosis. However, there remain important challenges to improve patient outcomes, such as device-related thrombosis (DRT). Although there are some potential factors underlying thrombosis described by Virchow’s triad, DRT’s onset after this intervention is poorly understood. Computational methods can provide more information to understand why this happens, and help predict the occurrence of thrombosis. The objective of this Bachelor Thesis (BT) was to develop a computational workflow to evaluate TAVI thrombosis risk under patient-specific conditions by CFD simulations. The data of two patients, one with DRT and the other one healthy, both with transcatheter aortic valves implanted were provided by Montreal Heart Institute (Montreal, Canada). The methodological process involved: the (i) segmentation and reconstruction of computed tomography (CT) images; (ii) the interaction between the device and the anatomy; (iii) the discretization of all TAVI components; (iv) the set-up of the material properties and boundary conditions in fluid dynamic simulation and (v) the calculation of haemodynamic indices to assess the risk of thrombus formation. The results obtained on the healthy control and the DRT patient showed significant differences which were consistent with the area where the thrombus was found, leading to some relevant conclusions to set the basis for future works regarding the TAVI modeling for the prediction of DRT.