In the United States, almost half a million people die every year because their hearts beat too fast or too slow--a disease called cardiac arrhythmia.
Although researchers and doctors have taken great strides to understand the heart, cardiovascular disease is still the primary cause of death in the
Scientists have long developed cardiac therapies through experience-based experimentations--often through trial and error. Yet, a new way of studying
the heart can perhaps provide new avenues to developing improved cardiac treatments.
Together with other researchers, Ellen Kuhl, professor at Stanford University, studies the heart through a simulation-based predictive method.
"By simulating the heart, we can better understand the complex pathways of cardiac disease. This can help us to improve current treatment
strategies," Kuhl said.
Simulating the heart
Kuhl and her team built a computational model of a student's heart, simulating how a real heart
works--a phenomenon where the flow of sodium and potassium controls the heart's electrical charge, which in turn, causes the heart to contract and
pump blood all over the body.
This simulation-based predictive method combines the implementation of new advanced continuum theories, modern imaging modalities and computational
techniques. The idea is that if researchers can simulate a heart, they can predict it, better understand it, and thus treat it more effectively.
"It would be a huge step forward if we could provide a true mechanistic understanding on how different interventions alter the interplay of physical
fields that characterizes the dynamics of the heart," said Kuhl. "It would allow us to virtually probe all kinds of different treatment scenarios
just by a mouse click."
In order to create a computational model that simulates a live human's heart, the team used equations to
establish a computational algorithm that can reliably predict the excitation-contraction patterns of a healthy heart. The electrocardiogram, a test
that records heart electrical activity, of the real heart is identical to that predicted by the computational model.
Kuhl's success in simulating the heart, together with first prototype experiments by her collaborator, Oscar Abilez, have led to an innovative way to
pace the heart: Using light.
"this would allow us to pace the heart with very high precision from a distance, unlike now, where pacing is done with electrical pacemakers that
have to sit on a constantly moving heart muscle."
Stalling heart failure
This methodology can also improve yet another form of cardiac disease. Today, treatment for
patients suffering from myocardial infarction, interruption of blood supply to the heart, is limited. The latter is caused by the local death of heart
muscle cells making the heart incapable of contracting. Consequently, the patient is treated with stem cell therapy, which injects cells into the
Unfortunately, the treatment is not always successful as it relies on the surgeon's individual ability and experience.
"The methods we use--predictive, quantitative, computational models--might change the way we design, improve and optimize medical treatment,"
said Kuhl. "There is a long way to go, and it is exciting to be a part of these developments."
Heart simulations present great insights to understanding the heart. In the future, with the advancement of computational techniques and other
technologies, we might have a set of disease-specific algorithms that could be translated into effective forms of treatment. Perhaps a different
approach of study is just what we