Using computer simulations to examine long-term progression of atrial fibrillation
His research resides at the intersection of computational modeling and cardiac electrophysiology. Nicolae Moise, MD, a research scientist in the Weinberg Lab for Computational Physiology in the Department of Biomedical Engineering at The Ohio State University, uses mathematical modeling and computational modeling to further discover relationships between vast amounts of quantitative data and cardiovascular outcomes.
With a grant from the American Heart Association (AHA) for the project “Mechanistic modeling of atrial tissue remodeling and atrial fibrillation progression,” he will examine what happens to heart tissue when calcium levels increase, which leads to atrial fibrillation (AF). AF is the chaotic activation of heart cells which causes an influx of calcium that becomes overloaded and can lead to a feedback loop and more AF.
Moise and his team have already uncovered some interesting heart muscle behaviors when it is in the AF state. AF is the most common type of irregular heartbeat that develops and can worsen and become permanent. Because of this, the aim of the research is to be able to use new knowledge to develop new interventions and treatments. To accomplish this, Moise says it will take more than just analyzing data.
“We’re creating predictive models and recreating the dynamical systems themselves that lead to these physiological processes when they function normally, and then what happens when it goes wrong and leads to pathology and disease,” Dr. Moise says.
Seth Weinberg, PhD, the associate dean for Research and a professor of Biomedical Engineering in the College of Engineering, says Moise receiving this AHA Career Development Award is a significant achievement as the award recognizes both the exceptional quality of his work in biomedical science overall and his promise as a rising star in cardiovascular research.
“The aim is to capture how AF progresses, so data exists for pathological situations and for healthy situations,” Dr. Weinberg says. “Understanding long-term progression could play a huge role in developing treatments that can stop AF before it becomes a lifelong condition.”
Focusing on progression means starting with an examination of healthy cardiac cells and tissues, then those in the state of disease and other conditions of cardiac cells, as well.
“Instead of simulating seconds here and there, we’re simulating the whole,” Dr. Moise says. “We have 24 hours of actual, simulated activity in our model.”
Even though this research focuses on heart cells, the flexibility of these techniques provides the option to adapt them to study other diseases. And even with existing antiarrhythmic drugs to combat AF’s ability to recur, this research could lead to the ability — at the cellular level — to stop it all together.
To learn more, you can access recently published work, “Calcium Homeostatic Feedback Control Predicts Atrial Fibrillation Initiation, Remodeling, and Progression - ScienceDirect,” by Drs. Moise and Weinberg, on JACC: Clinical Electrophysiology.
