The study concerns the model-based simulation of the haemodynamic and myocardial consequences of a replacement heart valve in patients with valvular heart disease, including image-based (echo, CT, MR) data, cell physiology (proteomic) data and clinical information.
The study aims to show that a personalised computational model can predict the outcome of heart valve replacement surgery, for both the aortic and mitral valves.
The modelling is intended to provide information on the haemodynamics (the flow patterns and pressure fields) in the affected vessels, such that the haemodynamic effects of an intervention can be simulated and optimised for an individual patient.
The modelling of cell physiology should also provide information on the mechanisms of myocardial remodelling, which are connected to heart valve replacement. To enable a holistic view of cardiovascular function, the results of the haemodynamic and cell physiology models will be combined.
The study will combine data from 3D and 0D (lumped-parameter) models to yield a system that can predict responses to the effects of hemodynamic changes in the cardiovascular system.
The essential purpose of this observational clinical study is to determine the degree to which the computer prediction matches the surgical outcome.