Arrhythpy: An Automated Tool to Quantify and Classify Arrhythmias in Ca²⁺ Transients of iPSC-Cardiomyocytes

Arrhythmias constitute an intricate and clinically significant phenomenon of great importance in various research areas. Ca2+ homeostasis plays a pivotal role in forming rhythmic contractions in the heart, and its dysregulation has emerged as a critical component in the development of arrhythmias. However, the quantification of arrhythmias has been limited to indirect measurements via Ca2+ sparks, electrophysiological parameters, or manual classification, which can lead to human bias. We aimed to develop an analysis platform that automatically analyzes arrhythmias in human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs). Here, we present Arrhythpy, a robust and automated open-source program that quantifies and classifies confocal microscopy-based Fluo-4 Ca2+ transients to generate a measure of arrhythmia. In contrast to other automated and semi-automated analysis tools, which measure established parameters such as time-to-peak, Arrhythpy directly analyzes the degree of arrhythmia in a Ca2+ transient. We demonstrate its utility in monitoring Ca2+ transient-based arrhythmias in atrial and ventricular iPSC-CMs from healthy individuals and patients with cardiac disease, including dilated cardiomyopathy (DCM) and Takotsubo syndrome (TTS). Arrhythpy analysis of iPSC-CMs of TTS patients recapitulated TTS phenotypes, including atrial arrhythmia that could be normalized with β-blocker treatment. The program's adaptable framework enables the analysis of arrhythmic patterns in various cell types using periodic dye-based line scan measurement techniques, applicable to both single cells and layered cultures.