An Efficient Microscale Technique for Determining the Erythrocyte Sedimentation Rate

Abstract

The erythrocyte sedimentation rate (ESR) is a commonly used test to screen for inflammatory conditions such as infections, autoimmune diseases, and cancers. However, it is a bulk macroscale test that requires a relatively large blood sample and takes a long time to run. Moreover, it provides no information regarding cell sizes or interactions, which can be highly variable. To overcome these drawbacks, we developed a microfluidic microscopy-based protocol to dynamically track settling red blood cells (RBCs) to quantify velocity of cell settling, as a surrogate for the ESR. We imaged individual cells in a vertical microfluidic channel and applied a hybrid cell detection and tracking algorithm to compute settling velocities. We combined eigenvalue background subtraction and centroid detection together with the Kalman filter and Hungarian assignment solver algorithms to increase accuracy and computational speed. Our algorithm is designed to track settling RBCs/aggregates in high cellularity samples rather than single cells in suspension. Detection accuracy was 79.3%, which is comparable to state-of-the-art cell-tracking techniques. Compared with conventional ESR tests, our approach has the advantages of being automated, using microliter volumes of blood samples, and rapid turnaround.