Abstract
Characterization of cardiomyocyte beat patterns is needed for quality control of cells intended for surgical injection as well as to establish phenotypes in disease modeling or toxicity studies. Optical-flow based analysis of videomicroscopic recordings offer a manipulation-free and efficient characterization of contractile cycles, an important characteristics of cardiomyocyte phenotype. We demonstrate that by appropriate computational analysis of optical flow data one can identify distinct contractile centers and distinguish active cell contractility from passive elastic tissue deformations. Our proposed convergence measure correlates with myosin IIa immuno-localization and is capable to resolve contractile waves and their synchronization within maturing, unlabeled induced pluripotent stem cell-derived cardiomyocyte cultures.