Researchers develop virtual heart to study atrial fibrillation
The creation of an advanced computational model of a sheep's heart is enabling researchers at the University of Manchester to discover new information about the development of atrial fibrillation, according to a paper published online this week in the British journal Interface Focus.
The researchers, led by Henggui Zhang, a professor at the university's school of physics and astronomy, developed the model to better understand the mechanisms of atrial fibrillation in hopes of eventually creating more effective treatments for the condition. They first used thin slices of an actual sheep's heart, then imaged those slices in 2-D, and finally used a computer program to create their 3-D model.
Using the model, the researchers were able to determine that AF is triggered, in part, because of "regional differences in the electrical activity across the tissue of the heart, known as electrical heterogeneity." They also found that a heart's fiber structure can be key to AF's development.
"The model provides a powerful tool for investigating the mechanisms underlying cardiac arrhythmias, as well as the actions of pharmacological agents on atrial excitation," the researchers wrote.
Zhang and his team, according to a university announcement, next plan to target the electrical conduction in specific regions of the heart to figure out how best to protect against AF.
"We're really excited about the potential that our virtual heart opens up for research into this incredibly complex organ," Zhang said. "By bringing together physics and biology, we hope to unlock some of the unanswered questions about atrial fibrillation--a condition which is only going to become more common as people live longer."
Biomedical engineering researchers at Arizona State University and physicians at Phoenix Children's Hospital and St. Joseph's Hospital and Medical Center already are developing custom heart models with the aid of a 3-D printer to aid in surgery planning. The models are based on information gleaned from CT and MRI scans.