Coronary Artery Disease

We are merging our computational biomechanics expertise with modern cardiovascular imaging modalities to improve the risk stratification methods used in the prognosis of coronary artery disease.

Coronary artery disease is caused by the accumulation of plaque in the arteries that supply the blood to the heart, and is the leading cause of death in developed countries. The prognostic capability of current clinical risk stratification methods for patients with acute coronary syndrome is limited, however, recent advancements in imaging capabilities are providing useful information to clinicians. Contemporary invasive methods such as intravascular ultrasound and optical coherence tomography provide added anatomical insights, and expert consensus deems them both superior to standard angiography in guiding treatment. While functional imaging methods such as sodium fluoride positron emission tomography are allowing us to better understand what drives atherosclerotic plaque development.

By leveraging the immense information that these imaging modalities provide, through close collaboration with Prof. Carl Schultz and his team at the Royal Perth Hospital, we are able to  pinpoint high-risk plaque morphologies using biomechanics modelling strategies. In addition to this, we are building robust, automatic image analysis tools using modern deep learning paradigms to facilitate new diagnostic and prognostic tools that meet clinical requirements.