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Updated: Sep 8, 2025
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A Label-Free Segmentation Approach for Intravital Imaging of Mammary Tumor Microenvironment
Published on: May 24, 2022
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A Label-Free Segmentation Approach for Intravital Imaging of Mammary Tumor Microenvironment
Brian M Burkel1, David R Inman1, María Virumbrales-Muñoz2
1Department of Cell and Regenerative Biology, University of Wisconsin-Madison.
Journal of Visualized Experiments : Jove
|June 13, 2022
Summary
This study introduces a novel intravital imaging method to visualize the tumor microenvironment without fluorescent labels. The technique uses metabolic signatures to map tumor nests, stroma, and vasculature in live models.
Area of Science:
- Biomedical Imaging
- Cancer Biology
- Microenvironment Dynamics
Background:
- Visualizing the live tumor microenvironment is crucial for understanding tumor progression.
- Current intravital imaging faces challenges with tissue heterogeneity and spatial context.
- Non-invasive methods are needed, especially for patient-derived xenograft (PDX) models.
Purpose of the Study:
- To develop a non-invasive intravital imaging workflow for compartmentalizing the tumor microenvironment.
- To enable visualization of interactions between cell types and extracellular matrix (ECM) in live tumors.
- To leverage metabolic signatures for contextualizing the tumor microenvironment without exogenous labels.
Main Methods:
- Pairing collagen second harmonic generation imaging with endogenous fluorescence from NAD(P)H.
- Utilizing fluorescence lifetime imaging microscopy (FLIM) for compartmentalization.
- Developing a protocol for time-lapse image acquisition, post-processing, and segmentation of mammary tumor models.
Main Results:
- Successfully compartmentalized the tumor microenvironment into tumor nest, stroma/ECM, and vasculature.
- Demonstrated non-invasive visualization of dynamic physiological interactions.
- Validated the use of metabolic signatures (NAD(P)H) for spatial context.
Conclusions:
- The developed workflow provides a non-invasive method to visualize and analyze the live tumor microenvironment.
- Exploiting metabolic signatures offers an advantage over exogenous labels for PDX models and potential clinical applications.
- This technique enhances understanding of tumor progression mechanisms by providing spatial and metabolic context.
