Record #244742 - GSI Repository

OPTAVI

Adjoint-based OPTimization of deflection-based cerebral embolic protection devices for reducing stroke risk in Transcatheter Aortic Valve Implantation

Grant period	2021-10-01 - 2023-09-30
Funding body	European Union
Call number	H2020-MSCA-IF-2019
Grant number	895580
Identifier	G:(EU-Grant)895580

Note: Transcatheter aortic valve implantation (TAVI) has quickly become the clinical standard for patients with medium to high risk for surgery. Despite being a promising treatment for aortic valve disease in the elderly, stroke remains a major complication of TAVI. Large randomized clinical trials reported stroke within 30 days in 5-7% of the patients undergoing TAVI . TCD ultrasound imaging has showed cerebral embolic signals in 100% of the TAVI patients, mainly during valve deployment. Cerebral embolic protection devices (CEPD) have been developed to reduce the migration of debris to the brain during TAVI, and resulted in 44-46% decrease in brain lesions. Despite this progress, the risk still remains significant.  Current CEPDs are based on fairly simple-minded ideas, e.g. placing filters inside brachiocephalic and left common cartoid arteries (e.g. Sentinel), or simply covering the arteries in the aortic arch with a filter to deflect the debris downstream (e.g. TriGaurd HDH). Because the flow here is turbulent and laden with solid particles, more advanced physical understanding is needed to examine and/or enhance the hydrodynamic efficacy of CEPDs.  This project aims at creating a 3D nonlinear adjoint-based framework on top of an existing GPU-accelerated flow solver for optimization of the CEPDs performance when exposed to the particle-laden turbulent flow in the aorta. First, the flow through a model of a prosthetic heart valve will be extended to include the full geometry of the thoracic aorta using an Immersed Boundary Method. Second, a Lagrangian model for finite-sized particles representing embolic debris will be coupled into the flow solver. Third, a deflection-based CEPD geometry will be introduced into the model. Fourth, nonlinear adjoint-based variational capabilities will be added on top of the particle-laden turbulent flow solver. Iterative direct-adjoint looping simulations will be then performed to obtain a CEPD design with maximum cerebral protection.

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Record created 2021-10-10, last modified 2023-02-12

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