Fluid modelling helps predict heart disease outcomes
The same mathematical equations and supercomputers used to model airflow around passenger jet liners are finding important new applications in medicine. These week-long computations are being adapted to better prevent death and injury from Australia’s number one killer – coronary heart disease.
The project involves collaborators from two Melbourne hospitals and draws on researchers at the University of Melbourne’s Mechanical Engineering Department led by Professor Andrew Ooi.
Professor Ooi has used the equations of fluid dynamics to create models of blood flow that are based on the real state of a person’s arteries, including disturbances due to the presence of blockages.
An important innovation is the ability to extract information about the interior of someone’s arteries from two-dimensional medical images, using a combination of angiograms and optical coherence tomography (OCT).
The immediate goal is to use advanced fluid mechanics modelling technologies to predict the location and formation of plaques in coronary arteries, since the build-up of plaque has been shown to be closely linked to heart attacks. The longer-term goal is to develop computer and imaging tools for the early detection of heart disease and to create novel opportunities for preventative medicine.
To validate the predictive power of Professor Ooi’s mathematical model-based technology, it is being used on a special set of patient images made available by collaborators from St Vincent’s Hospital and the Northern Hospital.
This is real patient data, with about 100 images available for Professor Ooi to transform into predictive models. Information about patients collected two years after the images were taken has allowed the predictions to be tested against real-world outcomes.
“The preliminary data is looking good,” Professor Ooi says. “We are confident about the technology and we are even looking for funding to develop a cheaper version of the technology that can run on desktop computers.”
More information: Professor Andrew Ooi, +61 3 8344 6732, firstname.lastname@example.org