Abstract
Aortic stenosis (AS) is one of the most prevalent types of valvular heart disease, costing more than $30 million annually in New Zealand. AS is an active process whereby the valve becomes calcified, stiffening the leaflets, impairing its ability to open normally. It is believed that the pathophysiology of AS is triggered by mechanical and adverse haemodynamic shear stress.
These stresses are unable to be measured in-vivo, with only experimental studies in-vitro being capable of indirectly measuring these stresses. Computational Fluid Dynamics (CFD), is a branch of applied mathematics that specialises in modelling fluid movement. Fluid movement is governed by a set of equations (Navier-Stokes and continuity equations), which can be solved using programs called CFD Solvers. This study aimed to produce a methodology to use CFD to estimate aortic valve shear stress. This study also aimed to develop an analysis pipeline for clinical use whereby cardiac MRI (CMR) images could be used to generate aortic valve shearstress measurements.
This study used the general-purpose solver ‘ANSYS’ and cardiovascular specific solver ‘CRIMSON’ to calculate shear stresses. We successfully generated aortic valve shear stress measurements, and succeeded in generating a pipeline by which shear stress measurements can be obtained from cardiac MRI. However, the pipeline was time-consuming, and the results generated were highly variable, and so unlikely to be feasible for clinical use. We discuss numerous improvements that must be made and tested before such a pipeline can be clinically useful.