Quantitatively characterizing drug-induced arrhythmic contractile motions of human stem cell-derived cardiomyocytes

Area of Science:

• Cardiology
• Computational Biology
• Biomedical Engineering

Background:

• Assessing drug-induced arrhythmias like Torsades de pointes is challenging due to difficulties in quantifying cardiac tissue motion.
• Current methods analyzing cardiomyocyte contractile motion lack sufficient detail for objective classification of variations.

Purpose of the Study:

• To develop and implement a novel computational algorithm for characterizing cardiac contractile motion dynamics.
• To improve the objective assessment of drug-induced proarrhythmias using human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs).

Main Methods:

• Generated contractile motion data from beating hiPSC-CMs using optical flow-based motion tracking.
• Implemented phase space reconstruction (PSR) to derive embedding, regularity, and fractal dimensions.
• Applied known proarrhythmic drugs to assess changes in PSR-derived parameters.

Main Results:

• Phase space reconstruction analysis revealed significant changes in dimensional parameters upon drug application.
• The derived parameters provide a more detailed characterization of cardiac contractile motion dynamics.
• The method successfully differentiated drug-induced effects on cardiomyocyte contractility.

Conclusions:

• Phase space reconstruction offers a powerful computational tool to enhance the analysis of cardiac contractile motion.
• This approach enables a more automated, high-throughput, and quantifiable assessment of drug-induced cardiac arrhythmias.
• Integrating PSR into existing analytical toolboxes will advance objective evaluations of proarrhythmic potential.