Despite advancements in device design and anti-coagulation treatments, there are numerous adverse events that may occur following implantation of LVADs. The most devastating involves the embolization of thrombus into the brain causing a stroke, with incidence of up to 14-47% over a 6–12-month period. This study aims to elucidate ways to reduce this risk by surgical maneuvers guided by a multi-scale computational fluid dynamics analysis wrapped around a multi-objective shape optimization scheme which optimizes the anastomosis location of the VAD outflow graft (OG) along the ascending aorta to minimize the incidence of thrombi reaching the cerebral vessels and reduce particle residence times. The computational model comprises of two coupled parts: a 50 degree of freedom 0-D lumped parameter model of the peripheral circulation that is loosely-coupled to a 3-D CFD model of the aortic circulation. Blood flow is modeled as laminar, incompressible and the non-Newtonian blood rheology is accounted for by the Carreau-Yasuda model. A Lagrangian particle tracking scheme is used to model thrombi as non-interacting particles. The results verify the hypothesis that a surgical maneuver that tailors the LVAD-OG anastomosis configuration can minimize the incidence of cerebral embolization. This is exemplified most in the case that considered particle release from the OG, as a fivefold decrease in cerebral embolization resulted from optimizing the implantation configuration. It was found that shallow orientations are most optimal in minimizing the cerebral embolization in the case where particles originate from the aortic root walls and the ventricle. In the last case, where particles were released from all three origins, the optimal implantations show a proclivity for intermediate implementations that direct the momentum of the VAD-jet towards the lumen of the aortic arch. Discrete coefficient of restitution sensitivity analysis reveals a negligible effect on cerebral embolization incidence as particle-wall collisions become less elastic.
If this is your thesis or dissertation, and want to learn how to access it or for more information about readership statistics, contact us at STARS@ucf.edu.
Master of Science in Mechanical Engineering (M.S.M.E.)
College of Engineering and Computer Science
Mechanical and Aerospace Engineering
Mechanical Engineering; Thermo-Fluids Track
Length of Campus-only Access
Masters Thesis (Open Access)
Dankano, Abubakar, "Tailoring of the Left Ventricular Assist Device Cannula Implantation Using Coupled Multi-Scale Multi-Objective Patient Specific Optimization." (2021). Electronic Theses and Dissertations, 2020-. 846.