Evidence map›Paper›PMID 36899069›Full record

ArticleScientific reports2023

Finite element modeling of meniscal tears using continuum damage mechanics and digital image correlation.

Derek Q Nesbitt, Dylan E Burruel, Bradley S Henderson, Trevor J Lujan

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Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 2 pooled it
–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

4 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. 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

4 authors.

Derek Q NesbittBiomedical Engineering Doctoral Program, Boise State University, Boise, ID, USA.
Dylan E BurruelDepartment of Mechanical and Biomedical Engineering, Boise State University, 1910 University Drive, Boise, ID, 83725-2085, USA.
Bradley S HendersonDepartment of Mechanical and Biomedical Engineering, Boise State University, 1910 University Drive, Boise, ID, 83725-2085, USA.
Trevor J LujanDepartment of Mechanical and Biomedical Engineering, Boise State University, 1910 University Drive, Boise, ID, 83725-2085, USA. trevorlujan@boisestate.edu.

Funding

VPS35 D620N inhibits autophagy through disrupted hyaluronic acid-CD44 signalingP20GM109095 · NIGMS · BOISE STATE UNIVERSITY · PI OXFORD, JULIA THOM · 2014 to 2023
$22.7M
NIGMS NIH HHS P20 GM109095NIGMS NIH HHS P20GM109095
6 · The paper itself

Abstract

Meniscal tears are a common, painful, and debilitating knee injury with limited treatment options. Computational models that predict meniscal tears may help advance injury prevention and repair, but first these models must be validated using experimental data. Here we simulated meniscal tears with finite element analysis using continuum damage mechanics (CDM) in a transversely isotropic hyperelastic material. Finite element models were built to recreate the coupon geometry and loading conditions of forty uniaxial tensile experiments of human meniscus that were pulled to failure either parallel or perpendicular to the preferred fiber orientation. Two damage criteria were evaluated for all experiments: von Mises stress and maximum normal Lagrange strain. After we successfully fit all models to experimental force-displacement curves (grip-to-grip), we compared model predicted strains in the tear region at ultimate tensile strength to the strains measured experimentally with digital image correlation (DIC). In general, the damage models underpredicted the strains measured in the tear region, but models using von Mises stress damage criterion had better overall predictions and more accurately simulated experimental tear patterns. For the first time, this study has used DIC to expose strengths and weaknesses of using CDM to model failure behavior in soft fibrous tissue.

Indexed as

Knee InjuriesLacerationsMeniscusBiomechanical PhenomenaFinite Element AnalysisHumansMenisci, Tibial

Identifiers

PMID36899069
PMCPMC10006193

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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.