Evidence mapPaperPMID 23764176Full record

ArticleJournal of biomechanics2013

Mapping the longitudinal wall stiffness heterogeneities within intact canine aortas using Pulse Wave Imaging (PWI) ex vivo.

Danial Shahmirzadi, Prathyush Narayanan, Ronny X Li, William W Qaqish, Elisa E Konofagou

Open access · greenAbstract read
In one paragraph

Article in Journal of biomechanics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
4.0field-weighted citation impact, top 5% 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

9 citing papers in PubMed, 25 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

5 authors at 1 institution in 1 country.

Danial ShahmirzadiDepartment of Biomedical Engineering, Columbia University, New York, NY 10027, USA.
Prathyush Narayanan
Ronny X Li
William W Qaqish
Elisa E Konofagou
Columbia University · US

Funding

NHLBI NIH HHS R01 HL098830NHLBI NIH HHS R01-HL098830
6 · The paper itself

Abstract

The aortic stiffness has been found to be a useful independent indicator of several cardiovascular diseases such as hypertension and aneurysms. Existing methods to estimate the aortic stiffness are either invasive, e.g. catheterization, or yield average global measurements which could be inaccurate, e.g., tonometry. Alternatively, the aortic pulse wave velocity (PWV) has been shown to be a reliable marker for estimating the wall stiffness based on the Moens-Korteweg (M-K) formulation. Pulse Wave Imaging (PWI) is a relatively new, ultrasound-based imaging method for noninvasive and regional estimation of PWV. The present study aims at showing the application of PWI in obtaining localized wall mechanical properties by making PWV measurements on several adjacent locations along the ascending thoracic to the suprarenal abdominal aortic trunk in its intact vessel form. The PWV estimates were used to calculate the regional wall modulus based on the M-K relationship and were compared against conventional mechanical testing. The findings indicated that for the anisotropic aortic wall, the PWI estimates of the modulus are smaller than the circumferential modulus by an average of -32.22% and larger than the longitudinal modulus by an average of 25.83%. Ongoing work is focused on the in vivo applications of PWI in normal and pathological aortas with future implications in the clinical applications of the technique.

Indexed as

Models, CardiovascularAnimalsAorta, ThoracicBiomechanical PhenomenaComputer SimulationDogsElastic ModulusMalePulse Wave AnalysisVascular StiffnessCanine Aorta In SituPulse Wave Imaging (PWI)Pulse Wave Velocity (PWV)Regional Wall Stiffness

Identifiers

PMID23764176
PMCPMC4005917
OpenAlexW2131425961

What Socratic holds

Textmetadata
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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 Socratic graph.