Evidence map›Paper›PMID 24306943›Full record

ArticleMedical & biological engineering & computing2014

High-quality conforming hexahedral meshes of patient-specific abdominal aortic aneurysms including their intraluminal thrombi.

J Tarjuelo-Gutierrez, B Rodriguez-Vila, D M Pierce, T E Fastl, P Verbrugghe, I Fourneau, G Maleux, P Herijgers, G A Holzapfel, E J Gomez

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Article in Medical & biological engineering & computing, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Fast in silico assessment of physical stress for peripheral nerves.Medical & biological engineering & computing · 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

10 authors.

J Tarjuelo-GutierrezBioengineering and Telemedicine Centre, ETSI de Telecomunicación, Universidad Politécnica de Madrid, Madrid, Spain, jtarjuelo@gbt.tfo.upm.es.
B Rodriguez-Vila
D M Pierce
T E Fastl
P Verbrugghe
I Fourneau
G Maleux
P Herijgers
G A Holzapfel
E J Gomez

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In order to perform finite element (FE) analyses of patient-specific abdominal aortic aneurysms, geometries derived from medical images must be meshed with suitable elements. We propose a semi-automatic method for generating conforming hexahedral meshes directly from contours segmented from medical images. Magnetic resonance images are generated using a protocol developed to give the abdominal aorta high contrast against the surrounding soft tissue. These data allow us to distinguish between the different structures of interest. We build novel quadrilateral meshes for each surface of the sectioned geometry and generate conforming hexahedral meshes by combining the quadrilateral meshes. The three-layered morphology of both the arterial wall and thrombus is incorporated using parameters determined from experiments. We demonstrate the quality of our patient-specific meshes using the element Scaled Jacobian. The method efficiently generates high-quality elements suitable for FE analysis, even in the bifurcation region of the aorta into the iliac arteries. For example, hexahedral meshes of up to 125,000 elements are generated in less than 130 s, with 94.8 % of elements well suited for FE analysis. We provide novel input for simulations by independently meshing both the arterial wall and intraluminal thrombus of the aneurysm, and their respective layered morphologies.

Indexed as

AlgorithmsAortaAortic Aneurysm, AbdominalComputer SimulationFinite Element AnalysisHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingSoftwareThrombosis

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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.