Assessing the risk of cardiac arrhythmia using patient-specific models of the heart

Mathematical models of the heart have emerged as a powerful tool in understanding the mechanisms underlying proper heart function and dysfunction in cardiovascular diseases. One particular area of interest is the propagation of the action potential wave that precedes and synchronizes the heart's contraction, which is crucial for proper heart function. Disruptions in this process can lead to cardiac arrhythmia, a condition characterized by irregular heartbeats.
To better understand the mechanisms underlying cardiac arrhythmia, personalized patient-specific models of the heart can be generated by incorporating both personalized electrophysiological data, such as electrocardiogram (ECG), and geometric information from imaging techniques such as cardiac MRI. These models accurately capture the individualized anatomy and electrophysiology of the heart.
In this talk, we will highlight the benefits of patient-specific models for assessing the risk of arrhythmia and improving patient outcomes in the management of cardiac arrhythmia.