Patients with coronary artery disease develop restricted blood flow, causing chest pain and limited lifestyle. Doctors reply upon angiogram images of the artery to estimate deficient flow, but this is unreliable. We can directly measure pressure gradients across narrowed arteries with a pressure-sensitive wire (the fractional flow reserve, FFR). This system is of clinical benefit to guide treatment with percutaneous coronary intervention (PCI; stenting); but it is cumbersome and invasive, and is done for few patients. There is a single threshold value (<0.80) for treatment, which may not be relevant to less active subjects. Also there are three major coronary arteries, with many branches, and it is rare to have FFRs measured in all vessels, so we lack information on cumulative flow limitation or ‘total ischemic burden’ of the myocardium.
Computational modelling of total cardiac ischemic burden can predict the impact of PCI in patients’ everyday lives.
- Construct vFFRs in major vessels and calculate ischemic burden before and after PCI.
- Assess patients’ symptom burden before and after PCI.
- Measure activity and energy usage before and after PCI.
- Relate change in ischemic burden at PCI to change in functional performance.
Patients requiring PCI will be identified and recruited in the primary supervisor’s clinical practice. They will be undergo questionnaire evaluation of quality of life and symptom burden before and 6 weeks after PCI. They will have activity monitoring before and 6 weeks after PCI. The baseline coronary angiogram will be processed to calculate vFFRs and measures of total ischemic burden. After PCI, the final angiogram will be similarly processed. The difference in total ischemic burden produced by PCI will be calculated and correlated with measures of quality of life and activity.
Coronary physiology is barely used in clinical practice. Computational modelling, combined with real measures of everyday activity, will usher in a new era in personalised treatment planning for patients with heart disease.