Abstract
SIGNIFICANCE: Digital holographic microscopy (DHM) has proven effective for particle segmentation within a given volume, making it well-suited for rapid monitoring of bacterial growth in microfluidic cartridges-such as in single-cell-based antimicrobial susceptibility testing assays. However, the development of optimal assays depends on a range of factors related to the instrument, consumables, and the sample itself. Despite this, comprehensive investigations into how these parameters influence the quality of the resulting phase images remain limited. AIM: To address this problem, we systematically explore the effect of these factors, including the microfluidic chamber height and its material properties, the density of the suspension, and other sample-inherent properties, on the signal-to-noise ratio (SNR) of the reconstructed phase image. APPROACH: We constructed an off-axis digital holographic microscope and defined a robust numerical processing pipeline allowing for the numerical reconstruction, refocusing and counting of suspended particles in a measurement volume spanning roughly 120 × 120 × 400 μm3 , at 50× magnification. We analyzed the performance of this system using various dilution steps of silica microspheres, Gram-positive spherical Staphylococcus warneri and Gram-negative rod-shaped Escherichia coli bacteria, filled in commercial microfluidic chips with different chamber heights. RESULTS: Experimental results demonstrated the system's capability in reflecting the dilution steps over 2 to 3 orders of magnitude. Our SNR analysis highlighted the microfluidic chamber height and the density of the suspension as key contributors to the background noise, whereas the particles themselves seemed to have a negligible effect. From this insight, we were able to derive an analytical function to predict the SNR of a given DHM system for various concentrations, chamber heights, and particle types. CONCLUSIONS: We successfully built a DHM system for counting suspended particles over a wide concentration range and for various microfluidic chamber heights. We also derived an initial framework for predicting and optimizing the performance of a given DHM system.