Particle counting finds many industrial applications especially in medical healthcare. In particular, cell counting from whole blood is used pervasively for disease diagnostics. Microfluidic impedance cytometry is fast, requires a small volume of blood, can be used at point of care and can perform absolute enumeration of different cell types in the sample. Coincidence detection is very essential for accurate counting results and becomes more significant while counting specific target cells, e.g. CD4+ or CD8+ T cell count in HIV/AIDS patient blood samples. In heterogeneous samples, e.g. blood, cell differentiation for all coincidence occurrences is essential in addition to the coincidence detection for accurate cell enumeration. In this paper, we have characterized the coincidence detection with cell differentiation using a microfluidic impedance biochip. The pure population of leukocytes is obtained after all erythrocytes are lysed on-chip from whole blood. Leukocytes were counted electrically as they pass over coplanar microfabricated electrodes bonded to the 15 μm × 15 μm cross section counting channel while generating a bipolar pulse for each cell passage. We have developed a mathematical model to simulate the electrical cell pulse and its coincidences. We show that coincidence detection can be characterized into three main types based on the range of time delay at which the coincidence occurs. We have also characterized cell differentiation for all the three coincidence types and show that multiple coincidences of different types can also occur. We used healthy and HIV-infected patient blood samples and used our coincidence detection technique to count CD4+ and CD8+ T cells and show the improvement in accuracy of cell counts compared to that without coincidence detection. We have also shown the improvement in the erythrocyte counting with coincidence detection in diluted whole blood samples.
ASJC Scopus subject areas
- Biomedical Engineering