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Methods. 2015 Aug;84:76-83. doi: 10.1016/j.ymeth.2015.03.014. Epub 2015 Apr 2.

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

Author information

1
Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, United States.
2
Department of Chemical Engineering & Materials Science, University of Minnesota, Minneapolis, MN, United States.
3
Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, United States; Department of Chemical Engineering & Materials Science, University of Minnesota, Minneapolis, MN, United States. Electronic address: tranquillo@umn.edu.

Abstract

The majority of reports in which microvascular network properties are quantified rely on manual measurements, which are time consuming to collect and somewhat subjective. Despite some progress in creating automated image analysis techniques, the parameters measured by these methods are limited. For example, no automated system has yet been able to measure support cell recruitment, which is an important indicator of microvascular maturity. Microvessel alignment is another parameter that existing programs have not measured, despite a strong dependence of performance on alignment in some tissues. Here we present two image analysis programs, a semi-automated program that analyzes cross sections of microvascular networks and a fully automated program that analyzes images of whole mount preparations. Both programs quantify standard characteristics as well as support cell recruitment and microvascular network alignment, and were highly accurate in comparison to manual measurements for engineered tissues containing self-assembled microvessels.

KEYWORDS:

Endothelial cells; Image analysis; Microvessels

PMID:
25843608
PMCID:
PMC4526423
DOI:
10.1016/j.ymeth.2015.03.014
[Indexed for MEDLINE]
Free PMC Article

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