New publications
Supercomputer simulation reveals causes of atrial fibrillation progression
Last reviewed: 03.08.2025
All iLive content is medically reviewed or fact checked to ensure as much factual accuracy as possible.
We have strict sourcing guidelines and only link to reputable media sites, academic research institutions and, whenever possible, medically peer reviewed studies. Note that the numbers in parentheses ([1], [2], etc.) are clickable links to these studies.
If you feel that any of our content is inaccurate, out-of-date, or otherwise questionable, please select it and press Ctrl + Enter.
Atrial fibrillation (AF) is the most common type of irregular heart rhythm, and over time it can worsen and become permanent — a serious disorder that is the leading preventable cause of ischemic stroke, according to the NIH.
Nicolae Moise, a postdoctoral fellow in the Department of Biomedical Engineering at The Ohio State University (OSU), is using the computing resources of NCSA and OSC to study the long-term progression of AF in hopes that his work will help develop treatments that can stop AF before it becomes a lifelong condition. His research was recently published in JACC : Clinical Electrophysiology.
AF is a type of irregular heart rhythm in which the upper chambers of the heart, the atria, beat out of sync with the lower chambers. What begins as an episodic phenomenon eventually becomes permanent. Conducting human experiments with the necessary detail is difficult, so Moise models the processes on a computer.
“We use cardiac electrophysiology models to investigate how short-term cardiac activity (milliseconds to seconds) drives long-term changes in cardiac tissue (days to weeks to months),” Moise said. “Our simulations are, to my knowledge, the longest to date: we model up to 24 hours of continuous 2D electrical activity.”
Simulations allow researchers to monitor all aspects of how the heart works over long periods of time. Although the heart may seem relatively simple, running a simulation at this level of detail requires a lot of computation.
“All 2D simulations were run using CUDA code on NCSA GPUs and DSP, which was critical for studying such long time scales,” Moise said.
“The NCSA resources we used included NVIDIA GPUs available through Delta. By running CUDA code on NVIDIA GPUs, we were able to speed up our simulations by about 250 times. Since our longest simulations in this study lasted about a week, they would have taken years on a typical PC or laptop.”
Moise’s team discovered an interesting feature of the heart in AF. As a person’s heart rate increases, the cells in the heart adapt to maintain calcium balance. This amazing ability of the cells comes with a serious drawback: These same adaptations make the heart prone to further arrhythmias. A vicious cycle ensues: More cells adapt to balance calcium as the condition continues, further increasing the susceptibility to arrhythmias and eventually leading to a persistent irregular heartbeat.
Moise's work shows why it is so important to detect AF early and treat it to maintain heart health.
“Our study focuses on the most common cardiac arrhythmia, atrial fibrillation, a major cause of stroke and high morbidity and mortality, through computer simulations of the heart’s electrical activity,” Moise said. “This work allows us to track for the first time the initiation and long-term progression of this disease, which will ultimately lead to the development of better drugs to prevent or stop its progression.”
Moise's research has the potential to significantly improve the treatment of AF by giving doctors and scientists a new perspective on the mechanisms that lead to its progression. This approach could inspire scientists working in related areas of cardiology and beyond.
“We believe that our work opens up a new temporal dimension in cardiac electrophysiology simulations, showing that single-day simulations (and even longer) are technically feasible,” Moise said. “This approach could be applied to a variety of diseases, such as sinus node dysfunction or arrhythmias caused by myocardial infarction. Additionally, this work directly advances research on atrial fibrillation by allowing for the first time to model its long-term progression caused by arrhythmic electrical activity, as well as opening the possibility of testing therapies that target the intracellular regulatory machinery. Finally, more broadly, we hope that our work will inspire other researchers to tackle biological challenges that span longer time scales.”
In future studies, Moise plans to refine his simulation to incorporate potential treatments and further validate his findings with additional experiments. Previous related work was published in the Biophysical Journal.