A comprehensive computational model of myocardial blood flow

Abstract (Lay terminology)
Patients come in all shapes, sizes and ages, with a wide variety of lifestyles, activity levels and expectations. Medical interventions do not take these factors into account in a systematic
way. Patients with heart disease, the most common major illness of our time, are a case in point. They frequently have narrowings and blockages in several blood vessels in the heart.
Doctors' assessments of effect upon the patient are often inaccurate, and based upon medical imaging, which is often not good at assessing the effect of narrowings upon blood flow. The
cumulative effect of several narrowings in different vessels is particularly problematic. To solve these problems, in our group we have developed a model which can predict the impact
of a narrowing in a particular artery. The challenge in this proposal is to extend our mathematical model to predict the blood flow through all the major arteries of the heart. This
will enable doctors to plan the most effective treatment (such as balloon angioplasty or stenting, to open up the arteries) with maximum benefit to the patient, minimum risk of
complications, and least expense. We propose optimising care through effective diagnosis (virtual FFRs in all affected coronary arteries), to provide patient-specific prediction and
evidence-based intervention -coronary revascularisation, usually by percutaneous coronary intervention, guided by a positive FFR (<0.80).

Background
Physiological measures are of critical importance to make the right therapeutic decisions for individuals. For patients with coronary artery disease, fractional flow reserve (FFR), a
measure of the restriction of blood flow through a narrowed vessel using a pressure-sensitive wire, has proved more successful than simply making a visual assessment of the degree of
anatomical narrowing on medical images (the angiogram) because the human eye is inaccurate. In general, an FFR value of 0.80 has been validated as useful threshold at a given
lesion, below which treatment is valuable, and above which it confers little or no benefit. We have developed a track record in the computational estimation of FFR from medical
images (angiograms). Angiograms are obtained on almost all patients with severe coronary disease, (250,000 in the UK p.a.) whereas FFRs, using a pressure wire, are not. Therefore our
FFR models have the potential to dispense with the need for inserting the pressure wire, but more importantly provide an FFR for patients who otherwise would not have one at all. We
can currently accurately model FFR in a well imaged coronary artery. Other systems have been developed, but ours incorporates clinical parameters to allow personalised values. The
second supervisor, Dr Morris, has adapted our system, when used with a pressure wire, to calculate volumetric coronary artery blood flow. Absolute flow rather than pressure gradients
is arguably more relevant to myocardial perfusion, symptoms and improvement due to revascularisation.