Evidence map›Paper›PMID 37433358›Full record

ArticleActa biomaterialia2023

A method for defining tissue injury criteria reveals that ligament deformation thresholds are multimodal.

Callan M Luetkemeyer, Corey P Neu, Sarah Calve

Open access · greenAbstract read
In one paragraph

Article in Acta biomaterialia, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.2field-weighted citation impact, top 23% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Callan M LuetkemeyerDepartment of Mechanical Engineering, University of Colorado Boulder, Boulder, CO, United States; Department of Mechanical Science and Engineering, University of Illinois Urbana-Champaign, Urbana, IL, United States. Electronic address: cluetke@illinois.edu.
Corey P NeuDepartment of Mechanical Engineering, University of Colorado Boulder, Boulder, CO, United States; Biomedical Engineering Program, University of Colorado Boulder, Boulder, CO, United States; BioFrontiers Institute, University of Colorado Boulder, Boulder, CO, United States.
Sarah CalveDepartment of Mechanical Engineering, University of Colorado Boulder, Boulder, CO, United States; Biomedical Engineering Program, University of Colorado Boulder, Boulder, CO, United States; BioFrontiers Institute, University of Colorado Boulder, Boulder, CO, United States; Materials Science and Engineering Program, University of Colorado Boulder, Boulder, CO, United States.
University of Colorado Boulder · USUniversity of Illinois Urbana-Champaign · US

Funding

Probing Osteoarthritis Pathogenesis by Noninvasive Imaging of Cartilage StrainR01AR063712 · NIAMS · UNIVERSITY OF COLORADO · PI NEU, COREY P · 2013 to 2023
$4.7M
Defining the mechanical link that unites the musculoskeletal system during limb developmentDP2AT009833 · NCCIH · UNIVERSITY OF COLORADO · PI CALVE, SARAH · 2017 to 2017
$2.2M
NCCIH NIH HHS DP2 AT009833NIAMS NIH HHS R01 AR063712
6 · The paper itself

Abstract

Soft tissue injuries (such as ligament, tendon, and meniscus tears) are the result of extracellular matrix damage from excessive tissue stretching. Deformation thresholds for soft tissues, however, remain largely unknown due to a lack of methods that can measure and compare the spatially heterogeneous damage and deformation that occurs in these materials. Here, we propose a full-field method for defining tissue injury criteria: multimodal strain limits for biological tissues analogous to yield criteria that exist for crystalline materials. Specifically, we developed a method for defining strain thresholds for mechanically-driven fibrillar collagen denaturation in soft tissues, using regional multimodal deformation and damage data. We established this new method using the murine medial collateral ligament (MCL) as our model tissue. Our findings revealed that multiple modes of deformation contribute to collagen denaturation in the murine MCL, contrary to the common assumption that collagen damage is driven only by strain in the direction of fibers. Remarkably, hydrostatic strain (computed here with an assumption of plane strain) was the best predictor of mechanically-driven collagen denaturation in ligament tissue, suggesting crosslink-mediated stress transfer plays a role in molecular damage accumulation. This work demonstrates that collagen denaturation can be driven by multiple modes of deformation and provides a method for defining deformation thresholds, or injury criteria, from spatially heterogeneous data. STATEMENT OF SIGNIFICANCE: Understanding the mechanics of soft tissue injuries is crucial for the development of new technology for injury detection, prevention, and treatment.  Yet, tissue-level deformation thresholds for injury are unknown, due to a lack of methods that combine full-field measurements of multimodal deformation and damage in mechanically loaded soft tissues. Here, we propose a method for defining tissue injury criteria: multimodal strain thresholds for biological tissues. Our findings reveal that multiple modes of deformation contribute to collagen denaturation, contrary to the common assumption that collagen damage is driven by strain in the fiber direction alone. The method will inform the development of new mechanics-based diagnostic imaging, improve computational modeling of injury, and be employed to study the role of tissue composition in injury susceptibility.

Indexed as

CollagenSoft Tissue InjuriesAnimalsBiomechanical PhenomenaExtracellular MatrixFibrillar CollagensLigamentsMiceStress, MechanicalCollagenFibrillar CollagensDamageExtracellular matrixFibrillar collagenFull-field methodTissue mechanics

Identifiers

PMID37433358
PMCPMC10530537
OpenAlexW4383671678

What OpenQuestion holds

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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 OpenQuestion graph.