Automated image analysis system for studying cardiotoxicity in human pluripotent stem cell-Derived cardiomyocytes

BMC Bioinformatics, vol. 21, pp. 187

Abstract

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.

Authors 4

1. Lu Cao Aachen Imaging and Bioinformatics Group Leiden Institute of Advanced Computer Science

   Leiden University

   Affiliation as printed

   Imaging and Bioinformatics group, Leiden Institute of Advanced Computer Science (LIACS), Leiden University, Niels Bohrweg 1, Leiden, 2333 CA, The Netherlands

2. Andries D. van der Meer

   University of Twente

   Affiliation as printed

   Dept of Applied Stem Cell Technologies, MIRA Institute, University of Twente, Drienerlolaan 5, Enschede, 7522 NB, The Netherlands

3. Fons J. Verbeek corresponding Aachen Imaging and Bioinformatics Group Leiden Institute of Advanced Computer Science

   Leiden University

   Affiliation as printed

   Imaging and Bioinformatics group, Leiden Institute of Advanced Computer Science (LIACS), Leiden University, Niels Bohrweg 1, Leiden, 2333 CA, The Netherlands. f.j.verbeek@liacs.leidenuniv.nl

   Imaging and Bioinformatics group, Leiden Institute of Advanced Computer Science (LIACS), Leiden University, Niels Bohrweg 1, Leiden, 2333 CA, The Netherlands

4. Robert C. J. J. Passier corresponding Aachen Department of Anatomy and Embryology

   Leiden University Medical Center · University of Twente

   Affiliation as printed

   Dept of Anatomy and Embryology, Leiden University Medical Center, Albinusdreef 2, Leiden, 2333 ZA, The Netherlands. robert.passier@utwente.nl

   Dept of Applied Stem Cell Technologies, MIRA Institute, University of Twente, Drienerlolaan 5, Enschede, 7522 NB, The Netherlands. robert.passier@utwente.nl

   Dept of Applied Stem Cell Technologies, MIRA Institute, University of Twente, Drienerlolaan 5, Enschede, 7522 NB, The Netherlands