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Establishing a Physiologic Human Vascularized Micro-Tumor Model for Cancer Research
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Published on: September 15, 2023

Computer-supported angiogenesis quantification using image analysis and statistical averaging.

Charalampos N Doukas1, Ilias Maglogiannis, Aristotelis A Chatziioannou

  • 1Department of Information and Communication Systems Engineering, University of the Aegean, 81100 Mytilene, Greece. doukas@aegean.gr

IEEE Transactions on Information Technology in Biomedicine : a Publication of the IEEE Engineering in Medicine and Biology Society
|September 10, 2008
PubMed
Summary

This study introduces an automated method to quantify angiogenesis, crucial for tumor growth. The developed tool accurately detects tumor progression and the inhibitory effects of drugs on microvessel development.

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Kinetic Analysis of Vasculogenesis Quantifies Dynamics of Vasculogenesis and Angiogenesis In Vitro

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Area of Science:

  • Biomedical Engineering
  • Cancer Research
  • Developmental Biology

Background:

  • Angiogenesis is vital for tumor growth, supplying oxygen and nutrients.
  • Measuring angiogenic activity serves as a marker for tumor progression or inhibition.
  • The chick embryo chorioallantoic membrane (CAM) is a common model for studying angiogenesis.

Purpose of the Study:

  • To develop an automated image analysis method for quantifying angiogenesis.
  • To create a web-based tool for unbiased measurement of microvessel density and growth.
  • To validate the tool's efficacy in detecting tumor growth and anti-angiogenic effects.

Main Methods:

  • Automated image analysis and statistical processing of CAM images.
  • Development of a web-based tool for microvessel quantification.
  • Testing the tool on datasets involving tumor growth and dexamethasone treatment.

Main Results:

  • The automated method efficiently extracts features relevant to angiogenesis.
  • The web-based tool provides unbiased quantification of microvessel density.
  • The system successfully detected tumor growth and dexamethasone's inhibitory effects on CAM angiogenesis.

Conclusions:

  • The proposed automated quantification method is effective for analyzing angiogenesis.
  • The developed tool offers a reliable approach for assessing tumor growth and anti-angiogenic therapies.
  • This technology aids in understanding and potentially controlling tumor development through angiogenesis modulation.