Optical cell tracking analysis using a straight-forward approach to minimize processing time for high frame rate data

Tracking of rolling cells via in vitro experiment is now commonly performed using customized computer programs. In most cases, two critical challenges continue to limit analysis of cell rolling data: long computation times due to the complexity of tracking algorithms and difficulty in accurately correlating a given cell with itself from one frame to the next, which is typically due to errors caused by cells that either come close in proximity to each other or come in contact with each other. In this paper, we have developed a sophisticated, yet simple and highly effective, rolling cell tracking system to address these two critical problems. This optical cell tracking analysis (OCTA) system first employs ImageJ for cell identification in each frame of a cell rolling video. A custom MATLAB code was written to use the geometric and positional information of all cells as the primary parameters for matching each individual cell with itself between consecutive frames and to avoid errors when tracking cells that come within close proximity to one another. Once the cells are matched, rolling velocity can be obtained for further analysis. The use of ImageJ for cell identification eliminates the need for high level MATLAB image processing knowledge. As a result, only fundamental MATLAB syntax is necessary for cell matching. OCTA has been implemented in the tracking of endothelial colony forming cell (ECFC) rolling under shear. The processing time needed to obtain tracked cell data from a 2 min ECFC rolling video recorded at 70 frames per second with a total of over 8000 frames is less than 6 min using a computer with an Intel (R) Core (TM) i7 CPU 2.80 GHz (8 CPUs). This cell tracking system benefits cell rolling analysis by substantially reducing the time required for post-acquisition data processing of high frame rate video recordings and preventing tracking errors when individual cells come in close proximity to one another. (C) 2016 AIP Publishing LLC.