Abstract

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.

Notes

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Graduation Date

2021

Semester

Fall

Advisor

Kassab, Alain

Degree

Master of Science in Mechanical Engineering (M.S.M.E.)

College

College of Engineering and Computer Science

Department

Mechanical and Aerospace Engineering

Degree Program

Mechanical Engineering; Thermo-Fluids Track

Format

application/pdf

Identifier

CFE0008817; DP0026096

Language

English

Release Date

December 2021

Length of Campus-only Access

None

Access Status

Masters Thesis (Open Access)

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