Evidence map›Paper›PMID 30006003›Full record

ArticleMedical engineering & physics2018

Geometric surrogates of abdominal aortic aneurysm wall mechanics.

Jesús Urrutia, Anuradha Roy, Samarth S Raut, Raúl Antón, Satish C Muluk, Ender A Finol

Abstract read
In one paragraph

Article in Medical engineering & physics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Predictors of Abdominal Aortic Aneurysm Risks.Bioengineering (Basel, Switzerland) · 2020
    Review
  8. Article
  9. Article
  10. Article
  11. (PEAK) WALL STRESS AS AN INDICATOR OF ABDOMINAL AORTIC ANEURYSM SEVERITY.Proceedings. IEEE Western New York Image and Signal Processing Workshop · 2018
    Article
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.

Jesús UrrutiaThe University of Texas at San Antonio, Department of Biomedical Engineering, San Antonio, TX, USA; University of Navarra-Tecnun, Department of Mechanical Engineering, San Sebastian, Spain.
Anuradha RoyThe University of Texas at San Antonio, Department of Management Science and Statistics, San Antonio, TX, USA.
Samarth S RautCarnegie Mellon University, Department of Mechanical Engineering, Pittsburgh, PA, USA.
Raúl AntónUniversity of Navarra-Tecnun, Department of Mechanical Engineering, San Sebastian, Spain.
Satish C MulukAllegheny Health Network, Department of Thoracic and Cardiovascular Surgery, Pittsburgh, PA, USA.
Ender A FinolThe University of Texas at San Antonio, Department of Mechanical Engineering, Room EB 3.04.08, One UTSA Circle, San Antonio, TX 78249, USA. Electronic address: ender.finol@utsa.edu.

Funding

Geometric Surrogates for Clinical Management of Abdominal Aortic AneurysmsR01HL121293 · NHLBI · UNIVERSITY OF TEXAS SAN ANTONIO · PI FINOL, ENDER A · 2015 to 2018
$1.8M
NHLBI NIH HHS R01 HL121293
6 · The paper itself

Abstract

The maximum diameter criterion is the most important factor in the clinical management of abdominal aortic aneurysms (AAA). Consequently, interventional repair is recommended when an aneurysm reaches a critical diameter, typically 5.0 cm in the United States. Nevertheless, biomechanical measures of the aneurysmal abdominal aorta have long been implicated in AAA risk of rupture. The purpose of this study is to assess whether other geometric characteristics, in addition to maximum diameter, may be highly correlated with the AAA peak wall stress (PWS). Using in-house segmentation and meshing algorithms, 30 patient-specific AAA models were generated for finite element analysis using an isotropic constitutive material for the AAA wall. PWS, evaluated as the spatial maximum of the first principal stress, was calculated at a systolic pressure of 120 mmHg. The models were also used to calculate 47 geometric indices characteristic of the aneurysm geometry. Statistical analyses were conducted using a feature reduction algorithm in which the 47 indices were reduced to 11 based on their statistical significance in differentiating the models in the population (p < 0.05). A subsequent discriminant analysis was performed and 7 of these indices were identified as having no error in discriminating the AAA models with a significant nonlinear regression correlation with PWS. These indices were: D

Indexed as

Aortic Aneurysm, AbdominalMechanical PhenomenaBiomechanical PhenomenaFinite Element AnalysisHumansNonlinear DynamicsRegression AnalysisStress, MechanicalAneurysmsBiomechanicsGeometry quantificationMedical image analysisStress

Identifiers

PMID30006003
PMCPMC6103887

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Registered trials

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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.