Development of an experimental image processing tool and flow-cytometry based electromagnetic scattering analysis for medical diagnosis of red blood cell pathology

The morphological, biophysical and biochemical properties of biological cells are critical markers for many fields, including life sciences, medical diagnosis, etc. Label-free, high-throughput classification and detection of cellular information at the single-cell level are invaluable for medical diagnostics. In particular, an efficient algorithm for image analytics plays an important role in biomedical research and in vitro diagnostics with grow importance for healthcare. Morphological/biophysical alterations in single biological cells have been associated with hematologic diseases, such as sickle cell disease. Anemia, which has multiple causes, such as iron deficiency, chronic blood loss and hemolysis, is a prevalent health problem affecting an estimated two billion people or 30% of the world’s population. The ability to measure hemoglobin concentration in anemic patients continuously has significant potential to facilitate hemoglobin monitoring, improve the detection of acute anemia, and avoid the complications and expense. Currently, a major challenge in many clinical laboratories, quantification of cellular information at the single-cell level requires complex laboratory sample preparation and data analysis procedures. Here, we demonstrate that the combination of a novel incubation procedure with rapid gas exchange, image-based flow cytometry (IFC) and a computational cell morphology framework, based on the boundary integral equation method (with the use of Muller Boundary Integral Equation Method) is presented to improve the accuracy of classification of red blood cells (RBCs) subtypes (including normal, intermediate and sickled RBCs) as they appear in time under low oxygen. In this dissertation, the results of the following numerical simulations and experiments are presented: We have investigated the changes in time to follow the rate of sickling with IFC as cells undergo deoxygenation. We have proposed a new shape quantification feature criteria as a Sickle Index parameter obtained from a user-defined custom mask in the IFC data to provide better identification of “true” normal, intermediate and sickle cell region boundaries in IFC. Especially, the main merit of the study lies in showing for the first time that the light scattering analysis based on boundary shape structures is correlated with the measured side scattering (SSC-A) pattern realized by IFC to provide the refractive index distribution for each RBC subtypes. Moreover, we applied different ionic strengths and osmolarity conditions to control the ratio of Discocyte/Stomatocyte/Echinocyte (D/S/E) subtypes in murine RBCs. Analysis of samples were performed using conventional and image-based flow cytometry (FC). The predicted cellular information showed good agreement with the expected results of our experimental data extracted from bright-field and dark-field images in IFC. The rich information on the predicted scattering pattern makes our angle-resolved light scattering technique for the purpose of the automatic RBC morphological profile in conventional FC, and discover RBC subpopulation target areas for the label-free analysis of conventional FC data. With this approach, we are able to notably reduce the data analysis procedure to identify RBC subtypes from a cell population in a given experiment through IFC or conventional FC with an angle-resolved light scattering method. Our approach could lead to replacing current manual protocols in the clinical procedure to avoid complex laboratory processes, and manual gating analysis and fluorescent stains in light microscopy or FCs. This study shows that our method has the potential to be used robust and objective characterization, and follow-up care of anemia status, and to provide a rapid action for the conditions that would lead to chronic anemia condition causing to a reduced lifespan, organ damage or painful crisis, and will be useful for the evaluation of anti-sickling agents which are currently proposed or are in clinical trials.