Simula Research Laboratory, Norway.
Organos, Inc, Berkeley, CA, United States of America.
Biomed Phys Eng Express. 2024 Sep 5;10(6). doi: 10.1088/2057-1976/ad7268.
Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) are an effective tool for studying cardiac function and disease, and hold promise for screening drug effects on human tissue. Understanding alterations in motion patterns within these cells is crucial for comprehending how the administration of a drug or the onset of a disease can impact the rhythm of the human heart. However, quantifying motion accurately and efficiently from optical measurements using microscopy is currently time consuming. In this work, we present a unified framework for performing motion analysis on a sequence of microscopically obtained images of tissues consisting of hiPSC-CMs. We provide validation of our developed software using a synthetic test case and show how it can be used to extract displacements and velocities in hiPSC-CM microtissues. Finally, we show how to apply the framework to quantify the effect of an inotropic compound. The described software system is distributed as a python package that is easy to install, well tested and can be integrated into any python workflow.
人诱导多能干细胞衍生的心肌细胞（hiPSC-CMs）是研究心脏功能和疾病的有效工具，并有望用于筛选药物对人体组织的影响。了解这些细胞内运动模式的变化对于理解药物的给药或疾病的发生如何影响人类心脏的节律至关重要。然而，目前使用显微镜进行光学测量来准确高效地量化运动非常耗时。在这项工作中，我们提出了一个统一的框架，用于对由 hiPSC-CMs 组成的组织的一系列显微镜获得的图像进行运动分析。我们使用合成测试案例验证了我们开发的软件，并展示了如何使用它来提取 hiPSC-CM 微组织中的位移和速度。最后，我们展示了如何应用该框架来量化变力化合物的作用。所描述的软件系统作为一个易于安装、经过良好测试的 python 包进行分发，并可以集成到任何 python 工作流程中。
