New insights into the analysis of red blood cells from leukemia and anemia patients: Nonlinear quantifiers, fractal mathematics, and Wavelet Transform

Abstract

The alterations of red blood cells (RBCs) membrane in many hematological diseases prevent blood to accomplish its functions, but how these alterations occur is not completely understood. Hence, the development of a simple and accurate methodology for the characterization of different populations of RBCs is necessary for hematology and clinical diagnosis. In this work, we focus on different pathologies that affect the hemorheological properties of human beings blood. The results were obtained by studying healthy individuals, anemia and leukemia patient samples. Data analysis involved the use of non-linear methods, based on two different analytical strategies. On one hand, we used nonlinear mathematical quantifiers (False Nearest Neighbors, Embedding Dimension, May–Sugihara Correlation, and Hurst Exponent) on ektacytometrically recorded time series measuring the elongation of re-suspended RBCs subjected to well-defined shear stress. On the other hand, we developed an analytical methodology to aid in the diagnosis of those pathologies, based on the box-counting dimension from digital images of cells suspensions that were denoised standardly by application of Wavelet Transform. The results allowed preliminary discrimination of different populations studied and a correlation with its membrane damage.