Flow Cytometry Visualization and Real-Time Processing with a CMOS SPAD Array and High-Speed Hardware Implementation Algorithm

Time-domain microfluidic fluorescence lifetime flow cytometry enables observation of fluorescence decay of particles or cells over time using time-correlated single photon counting (TCSPC). This method requires the fluorescence lifetime measured from a limited number of photons and in a short amount of time. In current implementations of the technique, the low throughput of state of the art detectors and lack of real-time statistical analysis of the current technology, the timedomain approaches are usually coupled with off-line analysis which impedes its use in flow cell sorting, tracking and capturing. In this work, we apply a 32×32 CMOS SPAD array (MegaFrame camera) for real-time imaging flow cytometry analysis. This technology is integrated into a 1024-beam multifocal fluorescence microscope and incorporating a microfluidic chip at the sample plane enables imaging of cell flow and identification. Furthermore, the 1.5% native pixel fill-factor of the MegaFrame camera is overcome using beamlet reprojection with <10 μW laser power at 490 nm for each beam. Novel hardware algorithms incorporating the center-of-mass method (CMM) with real-time background subtraction and division are implemented within the firmware, allowing lossless recording of TCSPC events at a 500 kHz frame rate with 1024 histogram bins at 52 ps time resolution. Live calculation of background compensated CMM-based fluorescence lifetime is realized at a user-defined frame rate (typically 0.001 ~ 27 kHz) for each SPAD pixel. The work in this paper considers the application of the SPAD array to confocal fluorescence lifetime imaging of multiple coincident particles flowing within a microfluidic channel. Compared to previous flow systems based on single-point detectors, the multi-beam flow system enables visualization, detection and categorization of multiple groups of cells or particles according to their fluorescence lifetime.