Title: Comprehensive modelling of myocardial ischaemic burden
Funder: The Academy of Medical Sciences

Abstract: Aims To develop a comprehensive model of myocardial ischaemia applicable to cardiac disease states. Objectives 1.)Use computational modelling to investigate the relationship between coronary flow, left ventricular haemodynamics and myocardial ischaemia in different disease states. 2.)Develop a model that can identify relative contributions to ischaemic burden in patients with arterial, valvular, arrhythmic and myocardial disease. 3.)Develop a model that can predict the change in ischaemia observed following a particular treatment strategy. Background Treatment of ischaemia is largely focused on the treatment of epicardial CAD. However, ischaemia also occurs secondary to other factors including microvascular disease, valvular heart disease and arrhythmia. As we increasingly manage older patients with multiple co-morbidities, aetiology of ischaemia is often multifactorial and discerning relative contributions is complex. Therefore, predicting the response to treatment is challenging and moves beyond physiological lesion assessment. An enhanced understanding of the relationship between coronary flow, microvascular resistance and myocardial perfusion in different disease states would allow a more personalised assessment of ischaemia that could improve patient management. Methods Patients with symptoms suggestive of ischaemia will undergo coronary angiography with physiological assessment (including FFR, LVEDP and VIRTU Q) and CMR stress-perfusion before and after treatment. Computational modelling techniques will be employed to explore the key relationships between anatomical data, coronary flow, microvascular resistance, LV haemodynamics and myocardial ischaemia. Where PCI has been performed, VCI will be used to predict the response to revascularisation, initially in terms of FFR and coronary flow but subsequently in terms of ischaemia.

Lay abstract: The aim of this work is to use computer modelling to improve decision making in patients with reduced blood supply to the heart (ischaemia). Angina is a common condition in which patients experience chest pain due to reduced blood supply to the heart muscle. This is usually caused by build-up of fatty plaque in the coronary arteries (the blood vessels that supply the heart). But it can also be caused by disease in the small branches (microvascular disease), heart valves, heart muscle, or heart rhythm apparatus. Often patients have a number of contributing factors and it is difficult to determine to what extent each contributes to their symptoms. As a result, we don’t always know which patients will improve with treatment and to what extent. We can use computer modelling to predict the improvement in blood flow that can be achieved with stenting in a single vessel, however there is no way to link this to the total blood supply to the heart. In this study, patients will undergo coronary angiography (imaging of the coronary arteries) with invasive measurement of blood flow in the main vessels using a pressure wire and VIRTU-Q modelling. They will also undergo cardiac MRI to quantify the total ischaemia. Both of these will be performed before and after treatment. Computer modelling will be used to explore the relationships between imaging, blood flow and ischaemia. The goal is to create a model that can predict relative contributions to ischemia and likely improvement with various treatment strategies.

Research activity codes: 2.1 BIOLOGICAL AND ENDOGENOUS FACTORS;2.5 RESEARCH DESIGN AND METHODOLOGIES (AETIOLOGY)
Health categories: CARDIOVASCULAR