Supercomputer using gaming tech simulates heart arrhythmia

Scientists from Sydney's Victor Chang Cardiac Research Institute have used the CSIRO's GPU-CPU Bragg supercomputer to simulate hundreds of thousands of heartbeats to help understand the variability in QT intervals found in patients with a type of inherited heart arrhythmia.

The Bragg supercomputer combines both central processing units (CPUs) and the graphics processing units (GPUs) more commonly used for powering video games. It also runs dual Linux and Windows operating systems to analyse data from different experiments.

Scientists from Victor Chang's computational cardiology laboratory led by Adam Hill have used the supercomputer to build a virtual heart and screen hundreds of thousands of heartbeats for abnormalities found in long QT syndrome type 2 (LQTS2).

LQTS2 is characterised by prolongation of the QT interval and the appearance of ‘bifid’ or notched T waves in electrocardiograms. However, finding a link between variable ECG characteristics and gene expression to understand the severity of the disease has been impossible due to the enormous computational burden required.

In a paper published in Nature, Dr Hill and his colleagues have described how using the supercomputer to run simulations can assist in doing quantitative analysis, with the hope of more accurately diagnosing disease and its severity.

“We were able to identify why some patients have abnormal ECG signals, and how a person’s genetic background can affect the severity of their disease,” Dr Hill said.

“We hope this will help doctors read ECGs more accurately, which will mean faster, more accurate diagnosis. By understanding why the same disease affects people differently, the right treatment can be given to the right patients.”

The simulation took 10 days, as opposed to the years it would take using standard computers.

“In the past we were limited because we didn’t have enough computational grunt to do an effective job,” Dr Hill said.

The team is hoping to use its discoveries to develop automatic computerised tools for diagnosing heart rhythm disorders.

Posted in Australian eHealth

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