Evidence map›Paper›PMID 29101897›Full record

ArticleJournal of the mechanical behavior of biomedical materials2018

Estimation of in vivo mechanical properties of the aortic wall: A multi-resolution direct search approach.

Minliang Liu, Liang Liang, Wei Sun

Abstract read
In one paragraph

Article in Journal of the mechanical behavior of biomedical materials, 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. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Characterizing atherosclerotic tissues:Frontiers in bioengineering and biotechnology · 2023
    Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Estimation ofComputer methods in applied mechanics and engineering · 2019
    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

3 authors.

Minliang LiuTissue Mechanics Laboratory, The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United States.
Liang LiangTissue Mechanics Laboratory, The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United States.
Wei SunTissue Mechanics Laboratory, The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United States. Electronic address: wei.sun@bme.gatech.edu.

Funding

Probabilistic Modeling of Stenotic Aortic Valve InterventionR01HL104080 · NHLBI · UNIVERSITY OF CONNECTICUT STORRS · PI SUN, WEI · 2011 to 2015
$1.9M
Biomechanical study on aortic-mitral coupling in transcatheter aortic valve replacementR21HL127570 · NHLBI · GEORGIA INSTITUTE OF TECHNOLOGY · PI SUN, WEI · 2016 to 2017
$441k
NHLBI NIH HHS R01 HL104080NHLBI NIH HHS R21 HL127570
6 · The paper itself

Abstract

The patient-specific biomechanical analysis of the aorta requires in vivo mechanical properties of individual patients. Existing approaches for estimating in vivo material properties often demand high computational cost and mesh correspondence of the aortic wall between different cardiac phases. In this paper, we propose a novel multi-resolution direct search (MRDS) approach for estimation of the nonlinear, anisotropic constitutive parameters of the aortic wall. Based on the finite element (FE) updating scheme, the MRDS approach consists of the following three steps: (1) representing constitutive parameters with multiple resolutions using principal component analysis (PCA), (2) building links between the discretized PCA spaces at different resolutions, and (3) searching the PCA spaces in a 'coarse to fine' fashion following the links. The estimation of material parameters is achieved by minimizing a node-to-surface error function, which does not need mesh correspondence. The method was validated through a numerical experiment by using the in vivo data from a patient with ascending thoracic aortic aneurysm (ATAA), the results show that the number of FE iterations was significantly reduced compared to previous methods. The approach was also applied to the in vivo CT data from an aged healthy human patient, and using the estimated material parameters, the FE-computed geometry was well matched with the image-derived geometry. This novel MRDS approach may facilitate the personalized biomechanical analysis of aortic tissues, such as the rupture risk analysis of ATAA, which requires fast feedback to clinicians.

Indexed as

AgedAlgorithmsAnisotropyAortaAorta, AbdominalAorta, ThoracicAortic Aneurysm, ThoracicBlood PressureComputer SimulationElasticityEndothelium, VascularFinite Element AnalysisHumansModels, CardiovascularPrincipal Component AnalysisSoftwareConstitutive parameter estimationFinite element analysisMulti-resolution direct searchPrincipal component analysis

Identifiers

PMID29101897
PMCPMC5696095

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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.