Characterization of Platelet Adhesion under Flow using Microscopic Image Sequence Analysis

Numerical and experimental evaluation of platelet deposition to collagen coated surface at low shear rates

Platelet deposition to collagen-coated surface under low shear conditions was investigated using an experimental model. The flow chamber was created by combining a stationary and a rotational glass plates spaced 50 μm apart. Blood filled into this space was subjected to a simple Couette flow. Both glass plates were covered with albumin to render them anti-thrombogenic. However, one spot 1×1 mm in size was covered with collagen. This spot was where the platelets deposited. The device was mounted on an inverted microscope and the platelet deposition was recorded. Platelets were dyed to render them fluorescent. The blood used was human blood from healthy volunteers. It was subjected to a range of low shear rates (below 7001/s) to find out how they act on platelet deposition. The results show a characteristic curve with elevated platelet deposition in the range of 1501/s. For the interpretation of these results a numerical model was developed. It applies the Monte Carlo method to model a random walk of platelets. This diffusive motion was superimposed on the convective motion by the Couette flow. A satisfactory match to the experimental data was achieved.

Single particle tracking across sequences of microscopical images: application to platelet adhesion under flow

A versatile and automated image processing technique and data extraction procedure from videomicroscopic data is presented. The motivation is a detailed quantification of blood platelet adhesion from laminar flow onto a surface. The characteristics of the system under observation (type of cells, their speed of movement, and the quality of the optical image to analyze) provided the criteria for developing a new procedure enabling tracking for long image sequences. Specific features of the novel method include: automatic segmentation methodology which removes operator bias; platelet recognition across the series of images based on a probability density function (two-dimensional, Gaussian-like) tailored to the physics of platelet motion on the surface; options to automatically tune the procedure parameters to explore different applications; integrated analysis of the results (platelet trajectories) to obtain relevant information, such as deposition and removal rates, displacement distributions, pause times and rolling velocities. Synthetic images, providing known reference conditions, are used to test the method. The algorithm operation is illustrated by application to images obtained by fluorescence microscopy of the interaction between platelets and von Willebrand factor-coated surfaces in parallel-plate flow chambers. Potentials and limits are discussed, together with evaluation of errors resulting from an inaccurate tracking.