Evidence map›Paper›PMID 25844153›Full record

ArticleInterface focus2015

Multiscale cartilage biomechanics: technical challenges in realizing a high-throughput modelling and simulation workflow.

Ahmet Erdemir, Craig Bennetts, Sean Davis, Akhil Reddy, Scott Sibole

Open access · bronzeAbstract read
In one paragraph

Article in Interface focus, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
3.5field-weighted citation impact, top 8% 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

13 citing papers in PubMed, 25 citations in OpenAlex.

  1. Article
  2. Article
  3. Use of Computational Modeling to Study Joint Degeneration: A Review.Frontiers in bioengineering and biotechnology · 2020
    Review
  4. Review
  5. Article
  6. Article
  7. Article
  8. ACS biomaterials science & engineering · 2017
    Article
  9. Systems approaches in osteoarthritis: Identifying routes to novel diagnostic and therapeutic strategies.Journal of orthopaedic research : official publication of the Orthopaedic Research Society · 2017
    Article
  10. Review
  11. Article
  12. Osteoarthritis year in review 2015: mechanics.Osteoarthritis and cartilage · 2016
    Review
  13. 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

5 authors at 2 institutions in 2 countries.

Ahmet ErdemirComputational Biomodeling (CoBi) Core , Lerner Research Institute, Cleveland Clinic , Cleveland, OH 44195 , USA ; Department of Biomedical Engineering , Lerner Research Institute, Cleveland Clinic , Cleveland, OH 44195 , USA.
Craig BennettsComputational Biomodeling (CoBi) Core , Lerner Research Institute, Cleveland Clinic , Cleveland, OH 44195 , USA ; Department of Biomedical Engineering , Lerner Research Institute, Cleveland Clinic , Cleveland, OH 44195 , USA.
Sean DavisComputational Biomodeling (CoBi) Core , Lerner Research Institute, Cleveland Clinic , Cleveland, OH 44195 , USA ; Department of Biomedical Engineering , Lerner Research Institute, Cleveland Clinic , Cleveland, OH 44195 , USA ; Department of Mechanical Engineering , University of Akron , Akron, OH 44325 , USA.
Akhil ReddyComputational Biomodeling (CoBi) Core , Lerner Research Institute, Cleveland Clinic , Cleveland, OH 44195 , USA ; Department of Biomedical Engineering , Lerner Research Institute, Cleveland Clinic , Cleveland, OH 44195 , USA ; Weill Cornell Medical College , New York, NY 10065 , USA.
Scott SiboleComputational Biomodeling (CoBi) Core , Lerner Research Institute, Cleveland Clinic , Cleveland, OH 44195 , USA ; Department of Biomedical Engineering , Lerner Research Institute, Cleveland Clinic , Cleveland, OH 44195 , USA ; Human Performance Laboratory, Faculty of Kinesiology , University of Calgary , Calgary, Alberta , Canada T2N 1N4.
Cleveland Clinic Lerner College of Medicine · USCornell University · US

Funding

Open Knee(s): Virtual Biomechanical Representations of the Knee JointR01GM104139 · NIGMS · CLEVELAND CLINIC LERNER COM-CWRU · PI ERDEMIR, AHMET · 2013 to 2016
$2.1M
Predicting cell deformation from body level mechanical loadsR01EB009643 · NIBIB · CLEVELAND CLINIC LERNER COM-CWRU · PI ERDEMIR, AHMET · 2009 to 2012
$1.7M
NIBIB NIH HHS R01 EB009643NIGMS NIH HHS R01 GM104139
6 · The paper itself

Abstract

Understanding the mechanical environment of articular cartilage and chondrocytes is of the utmost importance in evaluating tissue damage which is often related to failure of the fibre architecture and mechanical injury to the cells. This knowledge also has significant implications for understanding the mechanobiological response in healthy and diseased cartilage and can drive the development of intervention strategies, ranging from the design of tissue-engineered constructs to the establishment of rehabilitation protocols. Spanning multiple spatial scales, a wide range of biomechanical factors dictate this mechanical environment. Computational modelling and simulation provide descriptive and predictive tools to identify multiscale interactions, and can lead towards a greater comprehension of healthy and diseased cartilage function, possibly in an individualized manner. Cartilage and chondrocyte mechanics can be examined in silico, through post-processing or feed-forward approaches. First, joint-tissue level simulations, typically using the finite-element method, solve boundary value problems representing the joint articulation and underlying tissue, which can differentiate the role of compartmental joint loading in cartilage contact mechanics and macroscale cartilage field mechanics. Subsequently, tissue-cell scale simulations, driven by the macroscale cartilage mechanical field information, can predict chondrocyte deformation metrics along with the mechanics of the surrounding pericellular and extracellular matrices. A high-throughput modelling and simulation framework is necessary to develop models representative of regional and population-wide variations in cartilage and chondrocyte anatomy and mechanical properties, and to conduct large-scale analysis accommodating a multitude of loading scenarios. However, realization of such a framework is a daunting task, with technical difficulties hindering the processes of model development, scale coupling, simulation and interpretation of the results. This study aims to summarize various strategies to address the technical challenges of post-processing-based simulations of cartilage and chondrocyte mechanics with the ultimate goal of establishing the foundations of a high-throughput multiscale analysis framework. At the joint-tissue scale, rapid development of regional models of articular contact is possible by automating the process of generating parametric representations of cartilage boundaries and depth-dependent zonal delineation with associated constitutive relationships. At the tissue-cell scale, models descriptive of multicellular and fibrillar architecture of cartilage zones can also be generated in an automated fashion. Through post-processing, scripts can extract biphasic mechanical metrics at a desired point in the cartilage to assign loading and boundary conditions to models at the lower spatial scale of cells. Cell deformation metrics can be extracted from simulation results to provide a simplified description of individual chondrocyte responses. Simulations at the tissue-cell scale can be parallelized owing to the loosely coupled nature of the feed-forward approach. Verification studies illustrated the necessity of a second-order data passing scheme between scales and evaluated the role that the microscale representative volume size plays in appropriately predicting the mechanical response of the chondrocytes. The tools summarized in this study collectively provide a framework for high-throughput exploration of cartilage biomechanics, which includes minimally supervised model generation, and prediction of multiscale biomechanical metrics across a range of spatial scales, from joint regions and cartilage zones, down to that of the chondrocytes.

Indexed as

cartilagechondrocyteextracellularfinite-element analysispericellularpost-processing

Identifiers

PMID25844153
PMCPMC4342949
OpenAlexW2080809170

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.