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Automated image analysis programs for the quantification of microvascular network characteristics.

Kristen T Morin1, Paul D Carlson2, Robert T Tranquillo3

  • 1Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, United States.

Methods (San Diego, Calif.)
|April 7, 2015
PubMed
Summary

New image analysis software quantifies microvascular network properties, including support cell recruitment and alignment, overcoming limitations of manual methods. This automated approach offers high accuracy for engineered tissues.

Keywords:
Endothelial cellsImage analysisMicrovessels

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Area of Science:

  • Biomedical Engineering
  • Cell Biology
  • Image Analysis

Background:

  • Quantifying microvascular networks often relies on time-consuming and subjective manual measurements.
  • Existing automated image analysis techniques have limitations in the parameters they can measure, such as support cell recruitment and microvessel alignment.
  • These unmeasured parameters are crucial indicators of microvascular maturity and tissue performance.

Purpose of the Study:

  • To develop and validate novel image analysis programs for quantifying microvascular network properties.
  • To enable the measurement of support cell recruitment and microvessel alignment, which are not addressed by current automated methods.
  • To provide accurate and efficient tools for the analysis of microvascular networks in engineered tissues.

Main Methods:

  • Development of a semi-automated program for analyzing microvascular network cross-sections.
  • Development of a fully automated program for analyzing whole-mount microvascular preparations.
  • Comparison of program measurements against manual measurements for accuracy in engineered tissues.

Main Results:

  • Both programs accurately quantified standard microvascular characteristics compared to manual measurements.
  • The developed programs successfully quantified support cell recruitment, a key indicator of microvascular maturity.
  • Microvessel alignment, crucial for tissue performance, was also accurately measured by the new programs.

Conclusions:

  • The presented image analysis programs offer a significant advancement over existing methods for quantifying microvascular networks.
  • These tools provide accurate and automated measurement of critical parameters like support cell recruitment and microvessel alignment.
  • The software enhances the study of microvascular development and function, particularly in engineered tissue models.