Cardiovascular cartography-a new non-invasive technique to detect coronary artery disease

A multi-variable mathematical model specific to each individual can be designed to obtain the nominal basal haemodynamic behavior. By superimposing the measured data obtained from the individuals on a predictive model, a pattern, called cardiovascular cartography (CCG), can be generated. In a pilot study, it was observed that coronary artery disease (CAD) characteristically altered the CCG pattern. These alterations were carefully analysed using artificial neural networks and the exact status of the coronary insufficiency was reconstructed on a realistic-geometry coronary model. A strong correlation was found to exist between functional structures and structural functions. This study was designed to assess the feasibility of using such modeling and cartography techniques to detect the primary presence of CAD and to assess its severity.