An Optical-Flow-Based Method to Quantify Dynamic Behavior of Human Pluripotent Stem Cell-Derived Cardiomyocytes in Disease Modeling Platforms

Abstract

Human pluripotent stem cell-derived cardiomyocytes (hPSC-CMs) hold great promise for cardiovascular disease modeling, drug screening and personalized medicine. A crucial requirement to establish an hPSC-CM-based disease model is the availability of a reliable differentiation protocol and a functional assessment of phenotypic properties of CMs in a disease context. Characterization of relative changes in contractile behavior of CMs can provide insight not only about drug effects but into the pathogenesis of cardiovascular diseases. Image-based optical-flow analysis, which applies a speckle tracking algorithm to videomicroscopy of hPSC-CMs, is a noninvasive method to quantitatively assess the dynamics of mechanical contraction of the CMs. This method offers an efficient characterization of contractile cycles. It quantifies contraction velocity field, beat rate, contractile strain and contraction-relaxation strain rate profile, which are important phenotypic characteristics of CMs.