Improving a smartphone based droplet flow cytometry system with micro lens arrays integrated optofluidic chip

Abstract

Integration micro lens arrays (MLAs) into a microfluidic chip has presented outstanding performances in flow cytometry field due to capability of eliminating trade-off between sensitivity and field of view (FOV), allowing high throughput multiplex analysis, and enhancing signal-to-noise ratio (SNR). However, the practices are still remained inside high-end laboratory environment, restricting MLAs to be utilized in point-of-care (POC) based flow cytometry applications. A portable system for droplet flow cytometry was successfully developed, which consists of an optofluidic chip integrated with MLAs and a smartphone application (APP). To cater to the demand for point-of-care testing, a straightforward optical setup that employs inclined LED illumination and micro lens pairs was used. This configuration effectively amplifies fluorescence signals, allowing them to be captured and analyzed solely using a smartphone. Through a series of repeated experiments, clear and consistent results were obtained that highlight the system's capabilities: (1) the smartphone APP installed in the system enabled both quantitative and qualitative analyses of flowing fluorescence droplets. These analyses could be performed in real time, providing immediate detection results, (2) by incorporating MLAs into the detection process, a notable enhancement in detection sensitivity was achieved when compared to cases without MLAs. Specifically, in experiments involving droplet concentrations ranging from 10 µm to 25 µm, resolvability showed an increase, the sensitivity increased by up to 142%. and the SNR exhibited an 11 dB improvement, (3) the customized APP exhibited comparable droplet counting results to a commonly utilized object tracking program. The measurement differences between the two methods ranged from 1.08% to 4.14%, reaffirming the accuracy of our self-developed APP. In conclusion, this portable system, coupled with the smartphone APP and MLAs-based optical configuration, demonstrated the ability to perform real-time, on-site droplet flow cytometry analysis with competitive detection performance.