FLINT, MI – Researchers at the University of Michigan are using high-productivity computing (HPC) systems to conduct pioneering research aimed at predicting and preventing heart arrhythmias.

Using HPC systems from SiCortex, a Maynard, Mass.-based provider of energy-efficient computers, researchers aim to understand the causes of cardiac arrhythmias.

The project, led by Omer Berenfeld and funded in part by grants from the National Institutes of Health, the American Heart Association and the Heart Rhythm Society, runs mathematical modeling applications on two SiCortex systems, one that serves as the mainframe system and the other as an auxiliary development unit.  The numerical simulation studies produced so far provide new insight by presenting data in visual displays.

Historically, fibrillation was thought to be caused by random electrical disturbances in the heart, but new research shows that the electrical activity during fibrillation is not completely random.  The seemingly chaotic disturbances are found to originate in many cases from organizing centers in the form of spiral vortices, also called rotors. 

The University of Michigan team will study computer simulations generated by the SiCortex systems to evaluate the many combinations of variables that can cause rotors and determine their dynamics.
 
The simulations are studied together with electrical data collected from various modalities, including fluorescence imaging and electrodes threaded into the heart’s chambers.  

“We are studying the conditions of numerous variables that can interrupt the heart’s regular rhythm and lead to an arrhythmia,” said Berenfeld, an assistant professor of internal medicine and biomedical engineering at the Center for Arrhythmia Research.  “Through sophisticated mathematical modeling and parallel computations running on the SiCortex systems, we can reproduce the heart’s electrical activity to pinpoint more precisely where and how abnormal rhythms originate within the heart muscle.  Understanding the origin is an important step in determining the underlying cause of the problem.”