Identification and quantification of skeletal myotube contraction and association in vitro by video microscopy

Skeletal muscle is the largest tissue in the body by weight and plays many roles in maintaining homeostasis and health. Ex vivo cell-based experimental systems used to study muscle cell contraction, and others based on incorporation of cells into sensitive force transducers or electrophysiology equipment, are time-consuming, invasive, and not universally available, slowing the pace of research. Video microscopy provides a noninvasive way to record the contractile behavior of skeletal muscle cells in vitro. We have developed a numerical procedure using image processing and pattern recognition algorithms, that makes it possible to quantify contractile behavior of multiple myotubes simultaneously, based on video data. We examined the ability of the program to identify movement using a simplified graphical model of myotube contraction and found that the program's success is dependent on the morphology and movement characteristics of the objects. However, the program performs optimally over the types of motions approximating those observed in culture and identifies contracting myotubes in sample videomicrographs of muscle cells in vitro. This program quantifies contractility on a population level, can be adapted for use in laboratories capable of digital video capture from a microscope, and may be coupled with other experimental techniques to supplement existing research tools.