Key result
A fully automated image analysis system reliably segmented cardiomyocytes with heterogeneous α-actinin signals, generating precision and recall scores of 0.81 and 0.93 compared to manual segmentation.
Why the study?
Fully automated high-throughput screening of drug toxicity on hiPSC-CMs by fluorescence image analysis is challenging due to clustered cell growth and variable fluorescent marker expression.
A fully automated image analysis system using fuzzy C-mean clustering reliably segments hiPSC-CMs with heterogeneous α-actinin signals, enabling high-throughput screening for drug-induced cardiotoxicity.
BACKGROUND: Cardiotoxicity, characterized by severe cardiac dysfunction, is a major problem in patients treated with different classes of anticancer drugs. Development of predictable human-based models and assays for drug screening are crucial for preventing potential drug-induced adverse effects. Current animal in vivo models and cell lines are not always adequate to represent human biology. Alternatively, human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) show great potential for disease modelling and drug-induced toxicity screenings. Fully automated high-throughput screening of drug toxicity on hiPSC-CMs by fluorescence image analysis is, however, very challenging, due to clustered cell growth patterns and strong intracellular and intercellular variation in the expression of fluorescent markers. RESULTS: In this paper, we report on the development of a fully automated image analysis system for quantification of cardiotoxic phenotypes from hiPSC-CMs that are treated with various concentrations of anticancer drugs doxorubicin or crizotinib. This high-throughput system relies on single-cell segmentation by nuclear signal extraction, fuzzy C-mean clustering of cardiac α-actinin signal, and finally nuclear signal propagation. When compared to manual segmentation, it generates precision and recall scores of 0.81 and 0.93, respectively. CONCLUSIONS: Our results show that our fully automated image analysis system can reliably segment cardiomyocytes even with heterogeneous α-actinin signals.
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Cao et al. (2020) studied Cardiotoxicity. Automated image analysis system vs. Manual segmentation was evaluated on Precision and recall scores for single-cell segmentation. A fully automated image analysis system reliably segmented cardiomyocytes with heterogeneous α-actinin signals, generating precision and recall scores of 0.81 and 0.93 compared to manual segmentation.
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