Whole-Body Dynamic Tracking of Single Cells with Positron Emission Particle Tracking

Introduction: Cell trafficking plays a critical role in both physiological and pathological processes within the body. While several in vivo imaging modalities have been explored to study cell trafficking, they often face limitations such as shallow penetration depth, low sensitivity, and temporal resolution. In a recent study, we demonstrated real-time whole-body tracking of a single cancer cell in vivo using positron emission tomography (PET).1 However, this method can only trace one single cell per acquisition, logistically hindering the effective study of cell circulation patterns. Positron Emission Particle Tracking (PEPT), a nuclear tracking technique that measures flow characteristics of dynamic opaque systems using radioactive particles, offers a promising alternative that can track multiple moving cells. Like PET, PEPT relies on the detection of coincident pairs of 511 keV gamma rays traveling in opposite directions (coincidence data) to map the location of radioactive decay events. However, unlike traditional tomographic image reconstruction techniques that use coincidence data to provide a volumetric image of the radiotracer distribution within the body, PEPT uses this data for precise 3D localization of individual radiolabeled particles.2 Our recent study explores the adaptation of PEPT to biomedical applications and has demonstrated that a novel algorithm based on Expectation Maximization (PEPT-EM)3 can detect static single cells labeled with as low as 4 Bq,4 a five-fold improvement in sensitivity compared to the previous study. In this study, we report for the first time the application of PEPT-EM with one-second temporal resolution for whole-body dynamic tracking of multiple moving single cells in vivo.

Materials and

Methods: We employed a previously developed workflow to prepare viable fluorodeoxyglucose (FDG)-labeled single cells.4 Murine melanoma cells (B16) were incubated in glucose-free medium for 1 hour prior to radiolabeling. Following this fasting period, the medium was replaced with fresh medium containing FDG at a concentration of 370 MBq/ml. Single cells were subsequently isolated using a microfluidic-based single-cell dispenser device. Cells exhibiting high radioactivity were screened using a Geiger survey meter, and the radioactivity of each cell was quantified using a gamma counter. Approximately 3-5 single cells, each with activity above 100 Bq, were combined and intravenously infused into a nude mouse (Foxn1nu) using a syringe pump. During the slow infusion of the FDG-labeled single cells, the mouse was concurrently imaged within a micro-PET scanner. A CT scan was conducted 2 minutes after the PET scan. The raw output from the PET scanner was divided into frames of approximately one second and processed using PEPT-EM to derive the trajectories of these single cells within the body.

Results, Conclusions, and Discussions: Using the proposed approach, we demonstrated the feasibility of whole-body tracking of multiple single cells in vivo, achieving velocities of up to 20 mm/s and temporal resolution within one second. This tracking was enabled by the consistent isolation of 6-14 single cells with radioactivity above 100 Bq, constituting approximately 6.5% of the total 160 screened cells per experiment. Employing the PEPT-EM algorithm, we reconstructed the trajectories of two single cells: one arrested in the lung (~78 Bq), and another that traveled from the tail, where it was introduced, to its eventual arrest in the lung (~207 Bq). When we compared the trajectory of the moving cell with the vascular anatomy mapped using contrast-enhanced CT imaging, the cell trajectory mirrored the path from peripheral venules in the tail through the caudal veins and inferior vena cava. However, we were unable to observe the cell as it entered the right atrium and moved into the pulmonary circulation, where the blood velocity exceeds 20 mm/s—currently a limitation of our approach that might be resolved by enhancing FDG uptake in the cells. This observation aligns with our previous study involving a single cell labeled with 68Ga-loaded into mesoporous nanoparticles, which was tracked through most of the circulation except for its journey within the heart of the mouse.1
In conclusion, we have demonstrated, for the first time, the application of the PEPT-EM algorithm in mapping the trajectories of single cells throughout the entire body of a mouse, from the tail to their arrest in the lung capillaries. Although there are limitations in capturing parts of the circulation with high blood flow, our results demonstrate the potential for high-throughput, whole-body tracking of multiple single cells in vivo. This opens new avenues for studying dynamic trafficking patterns that underpin key biological phenomena and diseases within the body.

Acknowledgements (Optional): References

1 Jung, K. O. et al. Whole-body tracking of single cells via positron emission tomography. Nature Biomedical Engineering 4, 835-844 (2020). https://doi.org/10.1038/s41551-020-0570-5
2 Windows-Yule, C. R. K. et al. Recent advances in positron emission particle tracking: a comparative review. Rep Prog Phys 85 (2022). https://doi.org/10.1088/1361-6633/ac3c4c
3 Manger, S., Renaud, A. & Vanneste, J. An expectation–maximization algorithm for positron emission particle tracking. Review of Scientific Instruments 92, 085102 (2021). https://doi.org/10.1063/5.0053545
4 Hieu, T. M. N. et al. Efficient and multiplexed tracking of single cells using whole-body PET/CT. bioRxiv, 2023.2008.2023.554536 (2023). https://doi.org/10.1101/2023.08.23.554536