Evidence map›Paper›PMID 32173962›Full record

ArticleMicrocirculation (New York, N.Y. : 1994)2020

REAVER: A program for improved analysis of high-resolution vascular network images.

Bruce A Corliss, Richard W Doty, Corbin Mathews, Paul A Yates, Tingting Zhang, Shayn M Peirce

Abstract read
In one paragraph

Article in Microcirculation (New York, N.Y. : 1994), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

47 citing papers in PubMed.

  1. Article
  2. AAV-NRF2 protects retinal and choroidal vasculature in a GDF15-dependent manner in an oxidative damage model of AMD.Proceedings of the National Academy of Sciences of the United States of America · 2026
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  19. Frontiers in neuroscience · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Bruce A CorlissDepartment of Biomedical Engineering, University of Virginia, Charlottesville, Virginia.ORCID 0000-0003-2962-7344
Richard W DotyDepartment of Biomedical Engineering, University of Virginia, Charlottesville, Virginia.
Corbin MathewsDepartment of Biomedical Engineering, University of Virginia, Charlottesville, Virginia.
Paul A YatesDepartment of Ophthalmology, University of Virginia School of Medicine, Charlottesville, Virginia.
Tingting ZhangDepartment of Statistics, University of Virginia, Charlottesville, Virginia.
Shayn M PeirceDepartment of Biomedical Engineering, University of Virginia, Charlottesville, Virginia.ORCID 0000-0001-5857-5606

Funding

Multiscale Models of Cardiac Growth, Remodeling, and Myocardial InfarctionU01HL127654 · NHLBI · UNIVERSITY OF VIRGINIA · PI HOLMES, JEFFREY W · 2015 to 2019
$2.7M
Multiscale Modeling for Treatment Discovery in Duchenne Muscular DystrophyU01AR069393 · NIAMS · UNIVERSITY OF VIRGINIA · PI BLEMKER, SILVIA SALINAS, PEIRCE-COTTLER, SHAYN · 2016 to 2020
$2.5M
Modeling to Design Treatments for Vascular Pericyte Disassociation in DiabetesR21EY028868 · NEI · UNIVERSITY OF VIRGINIA · PI PEIRCE-COTTLER, SHAYN · 2018 to 2019
$433k
NEI NIH HHS R21 EY028868NHLBI NIH HHS U01 HL127654NIAMS NIH HHS U01 AR069393
6 · The paper itself

Abstract

Alterations in vascular networks, including angiogenesis and capillary regression, play key roles in disease, wound healing, and development. The spatial structures of blood vessels can be captured through imaging, but effective characterization of network architecture requires both metrics for quantification and software to carry out the analysis in a high-throughput and unbiased fashion. We present Rapid Editable Analysis of Vessel Elements Routine (REAVER), an open-source tool that researchers can use to analyze high-resolution 2D fluorescent images of blood vessel networks, and assess its performance compared to alternative image analysis programs. Using a dataset of manually analyzed images from a variety of murine tissues as a ground-truth, REAVER exhibited high accuracy and precision for all vessel architecture metrics quantified, including vessel length density, vessel area fraction, mean vessel diameter, and branchpoint count, along with the highest pixel-by-pixel accuracy for the segmentation of the blood vessel network. In instances where REAVER's automated segmentation is inaccurate, we show that combining manual curation with automated analysis improves the accuracy of vessel architecture metrics. REAVER can be used to quantify differences in blood vessel architectures, making it useful in experiments designed to evaluate the effects of different external perturbations (eg, drugs or disease states).

Indexed as

Image Processing, Computer-AssistedSoftwareAnimalsMiceNeovascularization, Pathologicblood vesselimage analysisimage quantificationmicrovascular networks

Identifiers

PMID32173962
PMCPMC7507177

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.