Engineered heart tissues (EHTs) have shown great potential in recapitulating tissue organization, functions, and cell-cell interactions of the human heart in vitro. Currently, multiple EHT platforms are used by both industry and academia for different applications, such as drug discovery, disease modelling, and fundamental research. The tissues’ contractile force, one of the main hallmarks of tissue function and maturation level of cardiomyocytes, can be read out from EHT platforms by optically tracking the movement of elastic pillars induced by the contractile tissues. However, existing optical tracking algorithms which focus on calculating the contractile force are customized and platform-specific, often not available to the broad research community, and thus hamper head-to-head comparison of the model output. Therefore, there is the need for robust, standardized and platform-independent software for tissues’ force assessment. To meet this need, we developed ForceTracker: a standalone and computationally efficient software for analyzing contractile properties of tissues in different EHT platforms. The software uses a shape-detection algorithm to single out and track the movement of pillars’ tips for the most common shapes of EHT platforms. In this way, we can obtain information about tissues’ contractile performance. ForceTracker is coded in Python and uses a multi-threading approach for time-efficient analysis of large data sets in multiple formats. The software efficiency to analyze circular and rectangular pillar shapes is successfully tested by analyzing different format videos from two EHT platforms, developed by different research groups. We demonstrate robust and reproducible performance of the software in the analysis of tissues over time and in various conditions. ForceTracker’s detection and tracking shows low sensitivity to common incidental defects, such as alteration of tissue shape or air bubbles. Detection accuracy is determined via comparison with manual measurements using the software ImageJ. We developed ForceTracker as a tool for standardized analysis of contractile performance in EHT platforms to facilitate research on disease modeling and drug discovery in academia and industry.

Human heart tissues grown as three-dimensional spheroids and consisting of different cardiac cell types derived from pluripotent stem cells (hiPSCs) recapitulate aspects of human physiology better than standard two-dimensional models in vitro. They typically consist of less than 5000 cells and are used to measure contraction kinetics although not contraction force. By contrast, engineered heart tissues (EHTs) formed around two flexible pillars, can measure contraction force but conventional EHTs often require between 0.5 and 2 million cells. This makes large-scale screening of many EHTs costly. Our goals here were (i) to create a physiologically relevant model that required fewer cells than standard EHTs making them less expensive, and (ii) to ensure that this miniaturized model retained correct functionality. We demonstrated that fully functional EHTs could be generated from physiologically relevant combinations of hiPSC-derived cardiomyocytes (70%), cardiac fibroblasts (15%) and cardiac endothelial cells (15%), using as few as 1.6 × 10⁴ cells. Our results showed that these EHTs were viable and functional up to 14 days after formation. The EHTs could be electrically paced in the frequency range between 0.6 and 3 Hz, with the optimum between 0.6 and 2 Hz. This was consistent across three downscaled EHT sizes tested. These findings suggest that miniaturized EHTs could represent a cost-effective microphysiological system for disease modelling and examining drug responses particularly in secondary screens for drug discovery.