Red blood cells are biomarkers of various diseases and pathological conditions and are affected by medical treatments. Most blood-derived diagnostics are performed in stasis – a condition that does not reflect the constant flow that red blood cells undergo in the circulatory system. In addition, the parameters currently used are based on average values obtained from a heterogeneous population of red blood cells. These limitations prevent a representative and complete analysis of their characteristics.
Here, we introduce the Erysense technology – a diagnostic approach based on the dynamic morphologies of red blood cells in capillary flow. The red blood cell morphology is highly sensitive to external influences as well as intrinsic properties, such as the cytoplasm viscosity, cytoskeletal structure, membrane permeability, and stiffness. These parameters determine red blood cell shapes in flow, which can result dramatically altered in diseases, after medical treatment, or induced by drugs.
Erysense uses in vitro microfluidic techniques and automated methods, including artificial neural networks, for an unbiased analysis of red blood cell shape and flow properties. In this proof-of-concept study, we demonstrate the applicability of Erysense:

(i) as a diagnostic tool of diseases

(ii) for dialysis monitoring

(iii) to assess the quality of stored blood

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