Particle Detection in Free-Falling Nanoliter Droplets.

Abstract

Sorting and dispensing distinct numbers of cellular aggregates enables the creation of three-dimensional (3D) in vitro models that replicate in vivo tissues, such as tumor tissue, with realistic metabolic properties. One method for creating these models involves utilizing Drop-on-Demand (DoD) dispensing of individual Multicellular Spheroids (MCSs) according to material jetting processes. In the DoD approach, a droplet dispenser ejects droplets containing these MCSs. For the reliable printing of tissue models, the exact number of dispensed MCSs must be determined. Current systems are designed to detect MCSs in the nozzle region prior to the dispensing process. However, due to surface effects, in some cases the spheroids that are detected adhere to the nozzle and are not dispensed with the droplet as expected. In contrast, detection that is carried out only after the droplet has been ejected is not affected by this issue. This work presents a system that can detect micrometer-sized synthetic or biological particles within free-falling droplets with a volume of about 30 nanoliters. Different illumination modalities and detection algorithms were tested. For a glare point projection-based approach, detection accuracies of an average of 95% were achieved for polymer particles and MCF-7 spheroids with diameters above 75 μm. For smaller particles the detection accuracy was still in the range of 70%. An approach with diffuse white light illumination demonstrated an improvement for the detection of small opaque particles. Accuracies up to 96% were achieved using this concept. This makes the two demonstrated methods suitable for improving the accuracy and quality control of particle detection in droplets for Drop-on-Demand techniques and for bioprinting.