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Related Concept Videos

Radiological Investigation III: Pulmonary Angiogram and PET Scan01:13

Radiological Investigation III: Pulmonary Angiogram and PET Scan

Radiological investigations are paramount in the diagnosis and management of various pulmonary diseases. Two essential investigations are the Pulmonary Angiogram and the Positron Emission Tomography (PET) Scan.
Pulmonary Angiogram
A Pulmonary Angiogram is an invasive procedure involving injecting a contrast medium through a catheter threaded into the pulmonary artery or the right side of the heart to visualize the pulmonary vasculature. Computed Tomography (CT) scans have mainly replaced this...

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Related Experiment Video

Updated: Jun 15, 2026

Improved Visualization of Lung Metastases at Single Cell Resolution in Mice by Combined In-situ Perfusion of Lung Tissue and X-Gal Staining of lacZ-Tagged Tumor Cells
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Lung cancer intravasation-on-a-chip: Visualization and machine learning-assisted automatic quantification.

Christy Wing Tung Wong1,2,3, Joyce Zhi Xuen Lee1,2, Anna Jaeschke1,2,3

  • 1Institute for Tissue Engineering and Regenerative Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China.

Bioactive Materials
|July 18, 2025
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Summary

Researchers developed an advanced lung cancer metastasis model using microfluidics and machine learning to study tumor cell intravasation. This innovative chip technology accelerates drug discovery and personalizes cancer treatments.

Keywords:
Cancer intravasationEpithelial-to-mesenchymal transition (EMT)Image segmentationLung cancerMachine learning-assisted image processingMacrophagesMicrofluidic devicesPattern recognitionRandom forestTransforming growth factor-beta 1 (TGF-β1)

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Area of Science:

  • Oncology
  • Biotechnology
  • Cell Biology

Background:

  • Lung cancer metastasis involves epithelial-to-mesenchymal transition (EMT), enabling tumor cells to invade blood vessels.
  • Understanding intravasation is crucial for developing effective anti-metastatic therapies.

Purpose of the Study:

  • To develop a human in vitro microphysiological model for studying EMT-driven lung cancer intravasation.
  • To utilize machine learning for automated identification and quantification of intravasation events.

Main Methods:

  • Formulation of an EMT-inducing cocktail (EMT-IC) using macrophage-conditioned medium and TGF-β1.
  • Co-culturing lung tumor micromasses with microvascular networks (MVNs) in microfluidic devices exposed to EMT-IC.
  • Employing machine learning-assisted vessel segmentation and co-localization analysis to detect intravasation.

Main Results:

  • EMT-IC promoted tumor cell membrane protrusion and intravasation into MVNs within 24 hours.
  • EMT-IC reduced basement membrane and vascular junction proteins (laminin, VE-Cadherin), increasing vessel permeability.
  • The model demonstrated cell-specific sensitivity, reflecting the metastatic potential of different lung cancer cell lines.

Conclusions:

  • The developed 'intravasation-on-a-chip' model offers a physiologically relevant platform for studying cancer metastasis.
  • This high-resolution, rapid model holds promise for accelerating drug development and informing personalized cancer treatment strategies.