The imaging of shear-mediated dynamic platelet behavior interacting with surface-immobilized von Willebrand factor (vWF) has tremendous potential in characterizing changes in platelet function for clinical diagnostics purposes. However, the imaging output, a series of images representing platelets adhering and rolling on the surface, poses unique, non-trivial challenges for software algorithms that reconstruct the positional trajectories of platelets. We report on an algorithm that tracks platelets using the output of such flow run experiments, taking into account common artifacts encountered by previously-published methods, and we derive seven key metrics of platelet dynamics that can be used to characterize platelet function. Extensive testing of our method using simulated platelet flow run data was carried out to validate our tracking method and derived metrics in capturing key platelet-vWF interaction-dynamics properties. Our results show that while the number of platelets present on the imaged area is the leading cause of errors, flow run data from two experiments using whole blood samples showed that our method and metrics can detect platelet property changes/differences that are concordant with the expected biological outcome, such as inhibiting key platelet receptors such as P2Y1, glycoprotein (GP)Ib and GPIIb/IIIa. These findings support the use of our methodologies to characterize platelet function among a wide range of healthy and disease cohorts
