Abstract 211: Automated and Non-invasive Estimation of QT Interval from Microscopy Images of Stem Cell-Derived Cardiomyocytes

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A promising application of induced pluripotent stem cells (iPSCs) is the generation of patient-specific cardiomyocytes (CMs), which can be used for drug development and safety testing related to cardiovascular health. iPSC-derived CMs can be used for preclinical testing of new drugs that may cause drug-induced arrhythmia or long QT syndrome, as well as post-market safety testing of existing drugs. The measurement of QT interval for iPSC-derived CMs is commonly analyzed using electrophysiological potentials captured by a micro-electrode array (MEA). While such systems are the current standard for characterization, they can be expensive and low-throughput, require high cell plating density, and due to the direct contact between cells and electrodes, may cause undesirable cellular response.

Here, we present a new method to non-invasively measure the QT-interval in iPSC-derived CMs using video microscopy and computer vision analysis. Our algorithms can reliably and automatically extract beating signal characteristics such as frequency, irregularity, and duration through image analysis of cardiomyocyte motion. Through a correlative study with MEA, we demonstrate that a non-invasive measurement of QT interval can be derived from the duration of visible cellular motion that occurs during contraction and relaxation. We also show that our system can accurately characterize the cellular response from the addition of compounds known to modulate beating frequency and irregularity. Our measurement technique is robust, automated, and requires no physical or chemical contact with the cells, making it ideal for cardiovascular drug development and cardiotoxicity testing.

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