The study aims to develop a semi-automatic leukocyte tracking (SALT) method to efficiently quantify in vivo leukocyte rolling and adhesion, overcoming the time-consuming limitations of manual frame-by-frame analysis of time-lapse images. This computational approach enables the rapid processing of large data sets, facilitating the study of leukocyte rolling and adhesion, initial and important events for leukocyte recruitment during tissue inflammation. Leukocytes were detected and tracked using the customized SALT module in ImageJ/Fiji, following specified criteria. Leukocyte flux, rolling, and adhesion were quantified from the tracks using a conditional decision algorithm. To validate the SALT method, the same images were analyzed in parallel by independent analyzers using both the SALT method and the classical manual tracking technique for comparison. The novel SALT method demonstrated high inter-rater and intra-rater reliability for rolling velocity, with no significant differences observed. Strong correlations were found between SALT and manual measurements for leukocyte displacement and velocity (r = 0.96, r = 0.97; p < 0.001), total and rolling flux (r = 0.81, r = 0.89; p < 0.05), and adherent cells (r = 0.97, p < 0.001). The SALT technique will be implemented to eliminate subjective bias and enhance high-throughput in vivo leukocyte rolling and adhesion analysis using ImageJ/Fiji in future studies.
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