Quantification of Cardiomyocyte Beating Frequency Using Fourier Transform Analysis

Pacemaker cardiomyocytes of the sinoatrial node (SAN) beat more rapidly than cells of the working myocardium. Beating in SAN cells responds to beta-adrenergic and cholinergic signaling by speeding up or slowing, respectively. Beat rate has traditionally been assessed using voltage or calcium sensitive dyes, however these may not reflect the true rate of beating because they sequester calcium. Finally, in vitro differentiated cardiomyocytes sometimes briefly pause during imaging giving inaccurate beat rates. We have developed a MATLAB automation to calculate cardiac beat rates directly from video clips based on changes in pixel density at the edges of beating areas. These data are normalized to minimize the effects of secondary movement and are converted to frequency data using a fast Fourier transform (FFT). We find that this gives accurate beat rates even when there are brief pauses in beating. This technique can be used to rapidly assess beating of cardiomyocytes in organoid culture. This technique could also be combined with field scanning techniques to automatically and accurately assess beating within a complex cardiac organoid.