ReviewMethods (San Diego, Calif.)2015
Automated image analysis programs for the quantification of microvascular network characteristics.
Review in Methods (San Diego, Calif.), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- Plant Exosome Injection with or without Low Level Laser Therapy Promotes Skin Wound Healing: An Experimental Study.Plastic and reconstructive surgery. Global open · 2026Article
- Mice Models for Peripheral Denervation to Enhance Vascular Regeneration.Tissue engineering. Part C, Methods · 2025Article
- Pattern recognition of microcirculation with super-resolution ultrasound imaging provides markers for early tumor response to anti-angiogenic therapy.Theranostics · 2024Article
- Fully automated platelet differential interference contrast image analysis via deep learning.Scientific reports · 2022Article
- Methods to label, image, and analyze the complex structural architectures of microvascular networks.Microcirculation (New York, N.Y. : 1994) · 2019Review
- Intracellular adenosine regulates epigenetic programming in endothelial cells to promote angiogenesis.EMBO molecular medicine · 2017Article
- Article
Corrections and comments
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Authors and funding
3 authors.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.