Predictive Cardiovascular Model With Blood Flow Measurements

Abstract

Cardiovascular disease is one of the leading causes of death in the world, accounting for 30% of all deaths worldwide and 40% of those occurring in New Zealand. In recent years, engineers and scientists have collaborated with the medical community to find new methodologies and approaches for assessing, investigating and understanding the development of cardiovascular diseases. Elements such as computational models developed with fluid dynamic elements (CFD/FE) have become excellent tools for this purpose. One of the important approaches is developing devices for investigating the central blood flow and pressure, and correlating the results to different heart diseases. Higher-valued changes in central blood flow and pressure mean that the heart must work harder. A computational model capable of predicting inlet and outlet locations of a blockage would be helpful to determine different stages of cardiovascular disease. By using reflection signals from the central blood flow that are detected at locations such as the brachial artery or subclavian artery, it is possible to model the effect of flow and pressure differences on heart diseases.