An experimental investigation of fractional flow reserve of human coronary artery

Abstract

It was estimated that 17.9 million people died in the year 2019 due to cardiovascular diseases. The main cause of it came from people suffering from coronary artery disease, where their coronary arteries became narrower until blood could not reach the vital organs and the heart, eventually killing them. However, there are ways to prevent this from happening. Early detection of coronary artery disease and treatments like coronary angioplasty and coronary artery bypass graft can repair the coronary artery of a patient, who is suffering from coronary artery disease. Early detection is one of the key importance to figure out if a patient is suffering from coronary artery disease. With the advancement of medical equipment and knowledge, there are various ways to detect coronary artery disease, these are exercise electrocardiography, stress echocardiography, radionuclide myocardial perfusion imaging, cardiac magnetic resonance imaging, computed tomography coronary angiography and many other more. Out of all these methods, computed tomography coronary angiography is considered the best method to detect coronary artery disease in a person. However, there are times when a doctor will need to perform an FFR analysis on the patient as the image from the computed tomography coronary angiography might not be enough. In this FFR analysis two pressure catheter will be inserted into the patient’s coronary artery to measure the FFR between stenosis, if the value is below 0.8, it means that the stenosis is a huge threat to the patient. However, not all patients are able to undergo this analysis as it could be risky and dangerous for their health. This project aims to predict the FFR in a human coronary artery without the need for any invasive procedure. With the use of three 3D-printed silicon coronary artery, customise measuring tool to measure the diameters of the 3D-printed silicon coronary artery and an in-vitro set up to calculate the FFR. The data acquired will be use as a foundation to predict the FFR in a human coronary artery.