In vitro analysis of multiple blood flow determinants using red blood cell dynamics under oscillatory flow

Abstract The flow behavior of blood is determined mainly by red blood cell (RBC) deformation and aggregation as well as blood viscoelasticity. These intricately interdependent parameters should be monitored by healthcare providers to understand all aspects of circulatory flow dynamics under numerous cases including cardiovascular and infectious diseases. Current medical instruments and microfluidic systems lack the ability to quantify these parameters all at once and in physiologically relevant flow conditions. This work presents a handheld platform and a measurement method for quantitative analysis of multiple of these parameters from 50 μl undiluted blood inside a miniaturized channel. The assay is based on an optical transmission analysis of collective RBC deformation and aggregation under near-infrared illumination during a 1 s damped oscillatory flow and at stasis, respectively. Measurements with blood of different hemo-rheological properties demonstrate that the presented approach holds a potential for initiating simultaneous and routine on-chip blood flow analysis even in resource-poor settings

Assessment of stored red blood cells through lab-on-a-chip technologies for precision transfusion medicine

Abstract Transfusion of red blood cells (RBCs) is one of the most valuable and widespread treatments in modern medicine. Lifesaving RBC transfusions are facilitated by the cold storage of RBC units in blood banks worldwide. Currently, RBC storage and subsequent transfusion practices are performed using simplistic workflows. More specifically, most blood banks follow the “first-in-first-out” principle to avoid wastage, whereas most healthcare providers prefer the “last-in-first-out” approach simply favoring chronologically younger RBCs. Neither approach addresses recent advances through -omics showing that stored RBC quality is highly variable depending on donor-, time-, and processing-specific factors. Thus, it is time to rethink our workflows in transfusion medicine taking advantage of novel technologies to perform RBC quality assessment. We imagine a future where lab-on-a-chip technologies utilize novel predictive markers of RBC quality identified by -omics and machine learning to usher in a new era of safer and precise transfusion medicine