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Related Experiment Video

Updated: Feb 2, 2026

Isolation and Propagation of Circulating Tumor Cells from a Mouse Cancer Model
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Background Modeling Method to Identify Interactions Between Circulating Tumor Cells and Dendritic Cells.

Xuejiao Zeng, Dan Wei, Xunbin Wei

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |November 17, 2018
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces an automated algorithm for tracking dendritic cells (DCs) and circulating tumor cells (CTCs) in vivo. The new method visualizes and quantifies DC-CTC interactions, advancing cancer immunotherapy research.

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    Area of Science:

    • Biomedical Engineering
    • Cancer Research
    • Immunology

    Background:

    • Interactions between dendritic cells (DCs) and circulating tumor cells (CTCs) are crucial in tumor immunity.
    • Noninvasive tracking and feature extraction of DCs and CTCs remain significant challenges in biomedicine.

    Purpose of the Study:

    • To develop an automated algorithm for identifying, counting, tracking, and segmenting fluorescently-labeled CTCs and DCs.
    • To enable real-time observation and analysis of DC-CTC interactions in vivo.

    Main Methods:

    • Constructed an in vivo image flow cytometry system for dual-channel fluorescence imaging.
    • Developed a motion detection algorithm based on codebook with background modeling and cone-shaped area search.
    • Utilized in vivo image sequencing and quantitative colocalization for validation.

    Main Results:

    • Successfully identified, counted, tracked, and segmented fluorescently-labeled CTCs and DCs in mouse ear blood vessels.
    • Observed and quantitatively analyzed the interactions between CTCs and DCs using image sequences.
    • Demonstrated the algorithm's capability for real-time analysis of dynamic cellular interactions.

    Conclusions:

    • The developed automatic algorithm provides a novel tool for studying DC-CTC interactions in vivo.
    • This technology holds promise for advancing research in cancer immunotherapy by enabling detailed visualization of cellular crosstalk.
    • Quantitative analysis of DC-CTC interactions can offer insights into tumor immunity and progression.