Automated image analysis programs for the quantification of microvascular network characteristics

Kristen T. Morin, Paul D. Carlson, Robert T. Tranquillo

Research output: Contribution to journalReview articlepeer-review

9 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)76-83
Number of pages8
JournalMethods
Volume84
DOIs
StatePublished - Aug 1 2015

Bibliographical note

Funding Information:
The authors thank Pat Schaeffer for histological assistance. This work was supported by NIH R01 HL108670 (to RTT), AHA predoctoral fellowship 11PRE7610056 (to KTM) and a grant from the Undergraduate Research Opportunities Program at UMN (to PDC).

Keywords

  • Endothelial cells
  • Image analysis
  • Microvessels

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