Artificial intelligence trained with optical mapping to improve detection of cardiac arrhythmia sources

Abstract

Disclosed are various embodiments of methods, components and systems configured to determine a location of a source of cardiac arrhythmia in a patient's heart. In some embodiments, to determine a source location, electrogram signals are acquired from a region of the patients' heart using a first set of electrodes; and then a pre-trained artificial intelligence (AI) model is applied to predict the location of the cardiac arrhythmia source by using the signals. Importantly, pre-training of the AI model comprises acquiring electrogram signals from explanted human hearts, the signals are generated by a second set of electrodes assembled into an electrode array that covers at least a part of the explanted human heart, and acquiring co-registered functional and/or structural imaging data in the part of the explanted human heart covered with the electrode array, wherein the functional and/or structural imaging data provide location of at least one source of cardiac arrhythmia.