Automated Quantification of Capillary Microhemodynamic Parameters from Intravital Microscopy Videos
Microcirculatory aberrations have been implicated as a driving force in the pathogenesis of sepsis and other diseases, but have only recently come under scrutiny with the development of novel visualization techniques. The heterogeneity of the microcirculation necessitates that a thorough assessment of capillary hemodynamics requires large sample sizes, inhibiting manual analysis, but no method presently exists to analyze capillary flow velocity or hematocrit in an automated manner without significant restrictions. A self-validating software application was developed that tracks capillary flow velocity and approximates capillary hematocrit from intravital microscopy videos, requiring minimal input from the user once calibrated. Additionally, data detailing the path taken by each successfully tracked cell may be stored, and the software outputs a copy of the input video with capillary outlines overlaid and with successfully tracked cells marked. In this manner, the user may choose to validate, accept, reject, and segregate the raw data as they wish.