Evidence map›Paper›PMID 26862936›Full record

ArticleJournal of visualized experiments : JoVE2016

Using Digital Image Correlation to Characterize Local Strains on Vascular Tissue Specimens.

Boran Zhou, Suraj Ravindran, Jahid Ferdous, Addis Kidane, Michael A Sutton, Tarek Shazly

Open access · bronzeAbstract readVideo-Audio Media
In one paragraph

Article in Journal of visualized experiments : JoVE, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.0field-weighted citation impact, top 24% of its field
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

6 citing papers in PubMed, 19 citations in OpenAlex.

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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 at 1 institution in 1 country.

Boran ZhouBiomedical Engineering Program, University of South Carolina.
Suraj RavindranDepartment of Mechanical Engineering, University of South Carolina.
Jahid FerdousDepartment of Mechanical Engineering, University of South Carolina.
Addis KidaneDepartment of Mechanical Engineering, University of South Carolina.
Michael A SuttonDepartment of Mechanical Engineering, University of South Carolina.
Tarek ShazlyBiomedical Engineering Program, University of South Carolina; Department of Mechanical Engineering, University of South Carolina; SHAZLY@cec.sc.edu.
University of South Carolina · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Characterization of the mechanical behavior of biological and engineered soft tissues is a central component of fundamental biomedical research and product development. Stress-strain relationships are typically obtained from mechanical testing data to enable comparative assessment among samples and in some cases identification of constitutive mechanical properties. However, errors may be introduced through the use of average strain measures, as significant heterogeneity in the strain field may result from geometrical non-uniformity of the sample and stress concentrations induced by mounting/gripping of soft tissues within the test system. When strain field heterogeneity is significant, accurate assessment of the sample mechanical response requires measurement of local strains. This study demonstrates a novel biomechanical testing protocol for calculating local surface strains using a mechanical testing device coupled with a high resolution camera and a digital image correlation technique. A series of sample surface images are acquired and then analyzed to quantify the local surface strain of a vascular tissue specimen subjected to ramped uniaxial loading. This approach can improve accuracy in experimental vascular biomechanics and has potential for broader use among other native soft tissues, engineered soft tissues, and soft hydrogel/polymeric materials. In the video, we demonstrate how to set up the system components and perform a complete experiment on native vascular tissue.

Indexed as

AnimalsAorta, AbdominalBiomechanical PhenomenaBiophysicsBlood VesselsImage Processing, Computer-AssistedMaleStress, MechanicalSurface PropertiesSwine

Identifiers

PMID26862936
PMCPMC4781695
OpenAlexW2253985362

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.