Improved data processing algorithm for laser ektacytometry of red blood cells

Background and Objectives: Red blood cells deliver oxygen to organs and tissues. In case of tropical malaria, blood anemia, diabetes mellitus and many other diseases, the cells become corrupted. These pathologies lead in altering deformability of the cells, i.e ability to change their shape under external forces. Precise measurement of cell’s deformability gives important medical information which helps to cure and monitor the most wide spread diseases more effectively. Thus, to improve the accuracy of modern techniques measuring the deformability of red blood cells is a task of great importance. The goal of this study is to enhance precision of laser diffractometry which is one of the basic tools for analyzing the deformability of red blood cells. Materials and Methods: The problem of measuring the deformability of red blood cells by laser diffraction in a shear flow (ektacytometry) is considered. Improved theoretical analysis of the laser beam scattering by inhomogeneous ensemble of particles mimicking red blood cells in a shear flow is performed. Results: New diffractometric equations establishing relations between characteristics of red blood cells and parameters of the diffraction pattern were derived. New data processing algorithm is presented for measuring the average deformability, as well as width and asymmetry of the erythrocyte deformability distribution. The numerical simulation of a bimodal ensemble of red blood cells was used for the algorithm verification. Conclusion: It has been shown that the new algorithm provides higher cells’s deformability measurement accuracy compared to the algorithm developed earlier.