Combining Multiple Complex Modelling Components to Create a Decision Support System for Heart Valve Disease

Valvular Heart Disease currently affects 2.5% of the population, but is overwhelmingly a disease of the elderly and consequently on the rise. It is dominated by two conditions, Aortic Stenosis and Mitral Regurgitation, both of which are associated with significant morbidity and mortality, yet which pose a truly demanding challenge for treatment optimisation. By combining multiple complex modelling components, a comprehensive, clinically-compliant decision-support system will be developed to meet this challenge, by quantifying individualised disease severity and patient impairment, predicting disease progression, ranking the effectiveness of alternative candidate procedures, and optimising the patient-specific intervention plan.

In addition the DSS will improve knowledge of disease mechanisms by applying a holistic assessment of cardiovascular function that includes hemodynamic data at all cardiovascular compartments (ventricle, valve, vessels) and multiscale components that couple organ with cell function.

DSS may have major impact on patients with borderline indications for treatment (valve replacement/repair), complex hemodynamic conditions such as combined aortic-mitral valve disease and valve geometries that are subject to valve repair.

The target user of this Decision Support System is the healthcare professional, in this case the surgeon or cardiologist, who will make the decision on the nature and timing of the intervention. The major advance of this system over current practice is that it integrates and interprets all heterogeneous data available about the patient, integrates population data where needed, and provides a consistent, repeatable, quantitative and auditable record of the information that contributes to the decision process.