Methods for processing and analyzing images of vascularized micro-organ and tumor systems Article Swipe
YOU?
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· 2025
· Open Access
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· DOI: https://doi.org/10.3389/fbioe.2025.1585003
Our group has developed and validated an advanced microfluidic platform to improve preclinical modeling of healthy and disease states, enabling extended culture and detailed analysis of tissue-engineered miniaturized organ constructs, or “organs-on-chips.” Within this system, diverse cell types self-organize into perfused microvascular networks under dynamic flow within tissue chambers, effectively mimicking the structure and function of native tissues. This setup facilitates physiological intravascular delivery of nutrients, immune cells, and therapeutic agents, and creates a realistic microenvironment to study cellular interactions and tissue responses. Known as the vascularized micro-organ (VMO), this adaptable platform can be customized to represent various organ systems or tumors, forming a vascularized micro-tumor (VMT) for cancer studies. The VMO/VMT system closely simulates in vivo nutrient exchange and drug delivery within a 3D microenvironment, establishing a high-fidelity model for drug screening and mechanistic studies in vascular biology, cancer, and organ-specific pathologies. Furthermore, the optical transparency of the device supports high-resolution, real-time imaging of fluorescently labeled cells and molecules within the tissue construct, providing key insights into drug responses, cell interactions, and dynamic processes such as epithelial-mesenchymal transition. To manage the extensive imaging data generated, we created standardized, high-throughput workflows for image analysis. This manuscript presents our image processing and analysis pipeline, utilizing a suite of tools in Fiji/ImageJ to streamline data extraction from the VMO/VMT model, substantially reducing manual processing time. Additionally, we demonstrate how these tools can be adapted for analyzing imaging data from traditional in vitro models and microphysiological systems developed by other researchers.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3389/fbioe.2025.1585003
- https://www.frontiersin.org/journals/bioengineering-and-biotechnology/articles/10.3389/fbioe.2025.1585003/pdf
- OA Status
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- Cited By
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- References
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- Related Works
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- OpenAlex ID
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Raw OpenAlex JSON
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https://openalex.org/W4411253707Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3389/fbioe.2025.1585003Digital Object Identifier
- Title
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Methods for processing and analyzing images of vascularized micro-organ and tumor systemsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-06-12Full publication date if available
- Authors
-
Stephanie J. Hachey, Christopher J. Hatch, Daniela Gaebler, Alexander G. Forsythe, Makena L. Ewald, Anil K. Chopra, Zehua Chen, Kapil Thapa, Melvin Hodanu, Jennifer S. Fang, W. C. HughesList of authors in order
- Landing page
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https://doi.org/10.3389/fbioe.2025.1585003Publisher landing page
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https://www.frontiersin.org/journals/bioengineering-and-biotechnology/articles/10.3389/fbioe.2025.1585003/pdfDirect link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://www.frontiersin.org/journals/bioengineering-and-biotechnology/articles/10.3389/fbioe.2025.1585003/pdfDirect OA link when available
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Computer science, Artificial intelligence, Computer visionTop concepts (fields/topics) attached by OpenAlex
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1Total citation count in OpenAlex
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2025: 1Per-year citation counts (last 5 years)
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34Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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