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

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.