A miniaturized wash-free microfluidic assay for electrical impedance-based assessment of red blood cell-mediated microvascular occlusion.

The production of HbS - an abnormal hemoglobin (Hb) - in sickle cell disease (SCD) results in poorly deformable red blood cells (RBCs) that are prone to microcapillary occlusion, causing tissue ischemia and organ damage. Novel treatments, including gene therapy, may reduce SCD morbidity, but methods to functionally evaluate RBCs remain limited. Previously, we presented the microfluidic impedance red cell assay (MIRCA) for rapid assessment of RBC deformability, employing electrical impedance-based readout to measure RBC occlusion of progressively narrowing micropillar openings. We describe herein the design, development, validation, and clinical utility of the next-generation MIRCA assay, featuring enhanced portability, rapidity, and usability. It incorporates a miniaturized impedance analyzer and features a simplified wash-free operation that yields an occlusion index (OI) within 15 min as a new metric for RBC occlusion. We show a correlation between OI and percent fetal hemoglobin (%HbF), other laboratory biomarkers of RBC hemolysis, and SCD severity. To demonstrate the assay's versatility, we tested RBC samples from treatment-naïve SCD patients in Uganda that yielded OI levels similar to those from hydroxyurea (HU)-treated patients in the U.S., highlighting the role of %HbF in protecting against microcapillary occlusion independent of other pharmacological effects. The MIRCA assay could also identify a subset of HU-treated patients with high occlusion risks, suggesting that they may require treatment adjustments including a second-line therapy to improve their outcomes. This work demonstrates the potential of the MIRCA assay for accelerated evaluation of RBC health, function, and therapeutic effect in an ex vivo model of the microcapillary networks.

iCLOTS: open-source, artificial intelligence-enabled software for analyses of blood cells in microfluidic and microscopy-based assays.

While microscopy-based cellular assays, including microfluidics, have significantly advanced over the last several decades, there has not been concurrent development of widely-accessible techniques to analyze time-dependent microscopy data incorporating phenomena such as fluid flow and dynamic cell adhesion. As such, experimentalists typically rely on error-prone and time-consuming manual analysis, resulting in lost resolution and missed opportunities for innovative metrics. We present a user-adaptable toolkit packaged into the open-source, standalone Interactive Cellular assay Labeled Observation and Tracking Software (iCLOTS). We benchmark cell adhesion, single-cell tracking, velocity profile, and multiscale microfluidic-centric applications with blood samples, the prototypical biofluid specimen. Moreover, machine learning algorithms characterize previously imperceptible data groupings from numerical outputs. Free to download/use, iCLOTS addresses a need for a field stymied by a lack of analytical tools for innovative, physiologically-relevant assays of any design, democratizing use of well-validated algorithms for all end-user biomedical researchers who would benefit from advanced computational methods.