Predicting Risk of Arrhythmias and Sudden Cardiac Death: There's a Computer Model for That

A computer model of the heart wall predicted risk of irregular heart rhythms and sudden cardiac death in patients, paving the way for the use of more complex cardiac models to calculate the consequences of genetic, lifestyle and other changes to the heart.

Authors of the new study, published in the Journal of the American College of Cardiology, say this is the first report of cardiac modeling being used as an arrhythmic risk predictor for patients.

“This is a strong proof-of-principle study showing that computer simulation can be used to predict risk of cardiac arrhythmias, ” said Coeli M. Lopes, Ph.D., lead study author and assistant professor at the Aab Cardiovascular Research Institute at the University of Rochester Medical Center. “With this model we can determine the influence of a single mutation on the much bigger overall response of the heart.”

With this study under their belts, the research team, including several scientists from the Medical Center, the IBM T.J. Watson Research Center in Yorktown Heights, N.Y and the IBM Research Collaboratory for Life Sciences in Melbourne, Australia is pursuing a much more sophisticated model of the whole human heart. They plan to predict the effects of new drugs on the electrical activity of the heart – one of the most challenging hurdles in the development of new drugs and an extremely important part of keeping potentially dangerous drugs off the market.

The computer model, designed by IBM scientists Matthias Reumann, Ph.D., and J. Jeremy Rice, Ph.D., includes 192 heart cells made to function electrically like the ventricle wall by assigning varying properties to cells based on their position – inside, middle, or outside – in the heart wall. The IBM scientists used canine cardiac cells as a guide, adapting the model cells to act more like ours based on extensive data on the electrical properties of the human heart. In the end, the simulation requires the solution of more than 100,000 complex mathematical equations at least 1,000 times over just to simulate a single heartbeat.

The team turned to more than 600 patients with Long QT syndrome type 1 – an inherited disorder that puts patients at greater risk of arrhythmias and sudden cardiac death – to help test the model. Patients were drawn from Long QT syndrome registries from the United States, Japan, the Netherlands, Denmark and Sweden.

Patients with the disorder have mutations in a specific gene, KCNQ1, which helps heart cells appropriately generate and transmit electrical signals. The study used 34 different mutations to the gene, identified with patient blood samples and genetic tests. To better understand the characteristics of each mutation – how they act and the defects they cause – the team recreated all of the mutant proteins in the lab and tested them in various cell lines.

Researchers plugged each mutation’s electrical profile into the model to simulate the mutation’s effect on the heart wall. The model produced a one-dimensional, transmural (across the heart wall) electrocardiogram or ECG for each mutation, which predicts how the mutation influences the electrical properties of the heart wall as it is excited and relaxes after each beat.