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Objective: Visualizing cell interactions in blood circulation is of great importance in studies of anticancer immunotherapy or drugs. However, the lack of a suitable imaging system hampers progress in this field. Methods: In this work, we built a dual-channel in vivo imaging flow cytometer to visualize the interactions of circulating tumor cells (CTCs) and dendritic cells (DCs) simultaneously in the bloodstream. Two artificial neural networks were trained to identify blood vessels and cells in the acquired images. Results and Conclusion: Using this technique, single CTCs and CTC clusters were readily distinguished by their morphology. Interactions of CTCs and DCs were identified, while their moving velocities were analyzed. The CTC-DC clusters moved at a slower velocity than that of single CTCs or DCs. This may provide new insights into tumor metastasis and blood rheology. Significance: This in vivo imaging flow cytometry system holds great potential for assessing the efficiency of targeting CTCs with anticancer immune cells or drugs. [ABSTRACT FROM AUTHOR]

Nanoparticles have been widely used in biomedical research as drug carriers or imaging agents for living animals. Blood circulation is crucial for the delivery of nanoparticles, which enter the bloodstream through injection, inhalation, or dermal exposure. However, the clearance kinetics of nanoparticles in blood circulation has been poorly studied, mainly because of the limitations of conventional detection methods, such as insufficient blood sample volumes or low spatial-temporal resolution. In addition, formation of nanoparticle aggregates is a key determinant for biocompatibility and drug delivery efficiency. Aggregation behavior of nanoparticles in blood is studied using dynamic light scattering in serum or serum protein solutions, which is still very different from in vivo condition. In this work, we monitored the dynamics of nanoparticle concentration and formation of nanoparticle aggregates in the bloodstream in live animals using in vivo flow cytometry (IVFC). The results indicated that nanoparticles in smaller size could stay longer in the bloodstream. Polyethylene glycol (PEG)-modification could prolong circulating time and reduce the formation of aggregates in the blood circulation. Our work shows that IVFC can be a powerful tool for pharmacokinetic studies of nanoparticles and other drug carriers, assessing cell-targeting efficiency, as well as potentially measuring cardiac output and hepatic function in vivo . [ABSTRACT FROM AUTHOR]

In biomedical research fields, the in vivo flow cytometry (IVFC) is a widely used technology which is able to monitor target cells dynamically in living animals. Although the setup of IVFC system has been well established, baseline drift is still a challenge in the process of quantifying circulating cells. Previous methods, i.e., the dynamic peak picking method, counted cells by setting a static threshold without considering the baseline drift, leading to an inaccurate cell quantification. Here, we developed a method of cell counting for IVFC data with baseline drift by interpolation fitting, automatic segmentation and wavelet-based denoising. We demonstrated its performance for IVFC signals with three types of representative baseline drift. Compared with non-baseline-correction methods, this method showed a higher sensitivity and specificity, as well as a better result in the Pearson's correlation coefficient and the mean-squared error (MSE). [ABSTRACT FROM AUTHOR]