Fighting a cardiac arrhythmia with mathematical optimization

What is it about?

Atrial fibrillation (AF) is an arrhythmia that substantially increases the risk of heart failure, stroke, and dementia. Contraction of the atria is controlled by electrochemical excitation waves propagating through the muscle tissue. During AF, the waves propagate chaotically leading to incoherent contraction and severe degradation of the pumping action of the atria. A common AF therapy relies on strong electric shocks which produce serious side effects such as pain and tissue damage. With the help of an optimization algorithm applied to a mathematical model of the atria we found electric signals capable of terminating AF that require a thousand times less energy than existing therapies, completely eliminating their side effects.

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Photo by Europeana on Unsplash

Photo by Europeana on Unsplash

Why is it important?

AF is characterized by multiple interacting spiral waves rotating clockwise or counterclockwise around so-called phase singularities. The larger the number of phase singularities, the more complex the arrhythmia and the harder it is to terminate it. We found weak electric signals that promote pairwise annihilation of phase singularities, one clockwise with one counterclockwise, until all phase singularities disappear. Such signals are capable of terminating AF by exploiting the sensitivity of the wave propagation through regions of tissue that have been recently excited and have not completely recovered to minute perturbations. This dynamical mechanism we have identified provides the foundation for a new generation of therapies applicable to treatment of atrial and possibly even ventricular fibrillation.