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Updated: May 28, 2026

Electrophysiological Analysis of human Pluripotent Stem Cell-derived Cardiomyocytes (hPSC-CMs) Using Multi-electrode Arrays (MEAs)
Published on: May 12, 2017
Characterisation of electrophysiological conduction in cardiomyocyte co-cultures using co-occurrence analysis
Michael Q Chen1, Jonathan Wong, Ellen Kuhl
1Department of Bioengineering, Stanford University, Stanford, CA 94305, USA.
Insights
Co-occurrence analysis quantifies cardiac electrical conduction patterns, offering a new algorithmic method to assess cell integration and reduce arrhythmia risks. This technique aids in understanding excitation wave uniformity and homogeneity.
Area of Science:
- Cardiovascular Research
- Biophysics
- Computational Biology
Background:
- Cardiac arrhythmias stem from electrical conduction disturbances, posing significant clinical risks.
- Cell damage or transplantation can disrupt heart's functional pathways, increasing arrhythmia susceptibility.
- Current methods lack quantitative, algorithmic approaches to analyze conduction patterns.
Purpose of the Study:
- To introduce co-occurrence analysis as a novel method for quantitative assessment of cardiac conduction patterns.
- To demonstrate the utility of co-occurrence analysis in evaluating the uniformity and homogeneity of excitation waves.
- To explore the application of co-occurrence analysis in cardiomyocyte-fibroblast co-culture systems.
Main Methods:
- Utilized co-occurrence analysis, a texture analysis technique, for feature recognition.
- Performed in vitro conduction analysis using microelectrode arrays on co-cultured murine HL-1 cardiomyocytes and 3T3 fibroblasts.
- Conducted in silico analysis using the finite element method for co-cultured electrically active cardiomyocytes and non-conductive fibroblasts.
Main Results:
- Co-occurrence analysis effectively quantifies excitation wave uniformity and homogeneity.
- Demonstrated a powerful ability to establish purity-conduction relationships.
- Quantified conduction patterns using co-occurrence energy and contrast metrics.
Conclusions:
- Co-occurrence analysis is a potent tool for rapid, quantitative assessment of cardiac conduction patterns.
- This method provides valuable insights into the integration of foreign cells, particularly relevant for stem cell therapies.
- The study serves as a foundation for advanced analyses in diverse co-culture systems and cardiac research.
Abstract:
Cardiac arrhythmias are disturbances of the electrical conduction pattern in the heart with severe clinical implications. The damage of existing cells or the transplantation of foreign cells may disturb functional conduction pathways and may increase the risk of arrhythmias. Although these conduction disturbances are easily accessible with the human eye, there is no algorithmic method to extract quantitative features that quickly portray the conduction pattern. Here, we show that co-occurrence analysis, a well-established method for feature recognition in texture analysis, provides insightful quantitative information about the uniformity and the homogeneity of an excitation wave. As a first proof-of-principle, we illustrate the potential of co-occurrence analysis by means of conduction patterns of cardiomyocyte-fibroblast co-cultures, generated both in vitro and in silico. To characterise signal propagation in vitro, we perform a conduction analysis of co-cultured murine HL-1 cardiomyocytes and murine 3T3 fibroblasts using microelectrode arrays. To characterise signal propagation in silico, we establish a conduction analysis of co-cultured electrically active, conductive cardiomyocytes and non-conductive fibroblasts using the finite element method. Our results demonstrate that co-occurrence analysis is a powerful tool to create purity-conduction relationships and to quickly quantify conduction patterns in terms of co-occurrence energy and contrast. We anticipate this first preliminary study to be a starting point for more sophisticated analyses of different co-culture systems. In particular, in view of stem cell therapies, we expect co-occurrence analysis to provide valuable quantitative insight into the integration of foreign cells into a functional host system.
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