Literature DB >> 25844153

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

Ahmet Erdemir1, Craig Bennetts1, Sean Davis2, Akhil Reddy3, Scott Sibole4.   

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.

Entities:  

Keywords:  cartilage; chondrocyte; extracellular; finite-element analysis; pericellular; post-processing

Year:  2015        PMID: 25844153      PMCID: PMC4342949          DOI: 10.1098/rsfs.2014.0081

Source DB:  PubMed          Journal:  Interface Focus        ISSN: 2042-8898            Impact factor:   3.906


  50 in total

Review 1.  Multiscale mechanics of articular cartilage: potentials and challenges of coupling musculoskeletal, joint, and microscale computational models.

Authors:  J P Halloran; S Sibole; C C van Donkelaar; M C van Turnhout; C W J Oomens; J A Weiss; F Guilak; A Erdemir
Journal:  Ann Biomed Eng       Date:  2012-05-31       Impact factor: 3.934

Review 2.  Structure and biology of cartilage and bone matrix noncollagenous macromolecules.

Authors:  D Heinegård; A Oldberg
Journal:  FASEB J       Date:  1989-07       Impact factor: 5.191

3.  Cell and matrix morphology in articular cartilage from adult human knee and ankle joints suggests depth-associated adaptations to biomechanical and anatomical roles.

Authors:  T M Quinn; H-J Häuselmann; N Shintani; E B Hunziker
Journal:  Osteoarthritis Cartilage       Date:  2013-12       Impact factor: 6.576

4.  Age-related changes in the morphology and deformational behavior of knee joint cartilage.

Authors:  M Hudelmaier; C Glaser; J Hohe; K H Englmeier; M Reiser; R Putz; F Eckstein
Journal:  Arthritis Rheum       Date:  2001-11

5.  Effect of compressive strain on cell viability in statically loaded articular cartilage.

Authors:  P A Torzilli; X-H Deng; M Ramcharan
Journal:  Biomech Model Mechanobiol       Date:  2006-02-28

6.  Adaptive surrogate modeling for expedited estimation of nonlinear tissue properties through inverse finite element analysis.

Authors:  Jason P Halloran; Ahmet Erdemir
Journal:  Ann Biomed Eng       Date:  2011-05-05       Impact factor: 3.934

7.  Quantitative structural organization of normal adult human articular cartilage.

Authors:  E B Hunziker; T M Quinn; H-J Häuselmann
Journal:  Osteoarthritis Cartilage       Date:  2002-07       Impact factor: 6.576

8.  Composition of the pericellular matrix modulates the deformation behaviour of chondrocytes in articular cartilage under static loading.

Authors:  Petro Julkunen; Wouter Wilson; Jukka S Jurvelin; Rami K Korhonen
Journal:  Med Biol Eng Comput       Date:  2009-11-07       Impact factor: 2.602

9.  Importance of collagen orientation and depth-dependent fixed charge densities of cartilage on mechanical behavior of chondrocytes.

Authors:  Rami K Korhonen; Petro Julkunen; Wouter Wilson; Walter Herzog
Journal:  J Biomech Eng       Date:  2008-04       Impact factor: 2.097

10.  The influence of size, clearance, cartilage properties, thickness and hemiarthroplasty on the contact mechanics of the hip joint with biphasic layers.

Authors:  Junyan Li; Todd D Stewart; Zhongmin Jin; Ruth K Wilcox; John Fisher
Journal:  J Biomech       Date:  2013-05-09       Impact factor: 2.712

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  11 in total

Review 1.  Osteoarthritis year in review 2015: mechanics.

Authors:  N H Varady; A J Grodzinsky
Journal:  Osteoarthritis Cartilage       Date:  2016-01       Impact factor: 6.576

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

Authors:  Ahmet Erdemir; Craig Bennetts; Sean Davis; Akhil Reddy; Scott Sibole
Journal:  Interface Focus       Date:  2015-04-06       Impact factor: 3.906

3.  Multiscale mechanics of the cervical facet capsular ligament, with particular emphasis on anomalous fiber realignment prior to tissue failure.

Authors:  Sijia Zhang; Vahhab Zarei; Beth A Winkelstein; Victor H Barocas
Journal:  Biomech Model Mechanobiol       Date:  2017-08-18

4.  The potential for intercellular mechanical interaction: simulations of single chondrocyte versus anatomically based distribution.

Authors:  Jason P Halloran; Scott C Sibole; Ahmet Erdemir
Journal:  Biomech Model Mechanobiol       Date:  2017-08-24

Review 5.  Numerical Study on Electromechanics in Cartilage Tissue with Respect to Its Electrical Properties.

Authors:  Abdul Razzaq Farooqi; Rainer Bader; Ursula van Rienen
Journal:  Tissue Eng Part B Rev       Date:  2018-12-31       Impact factor: 6.389

6.  Prediction of patellofemoral joint kinematics and contact through co-simulation of rigid body dynamics and nonlinear finite element analysis.

Authors:  Jacobus H Müller; Swithin Razu; Ahmet Erdemir; Trent M Guess
Journal:  Comput Methods Biomech Biomed Engin       Date:  2020-05-07       Impact factor: 1.763

7.  Comparison of the effects of exercise with chondroitin sulfate on knee osteoarthritis in rabbits.

Authors:  Ning Ma; Tingting Wang; Lianyu Bie; Yang Zhao; Lidong Zhao; Shai Zhang; Li Gao; Jianhua Xiao
Journal:  J Orthop Surg Res       Date:  2018-01-22       Impact factor: 2.359

Review 8.  Bioinspired Technologies to Connect Musculoskeletal Mechanobiology to the Person for Training and Rehabilitation.

Authors:  Claudio Pizzolato; David G Lloyd; Rod S Barrett; Jill L Cook; Ming H Zheng; Thor F Besier; David J Saxby
Journal:  Front Comput Neurosci       Date:  2017-10-18       Impact factor: 2.380

9.  In Vivo Multiscale and Spatially-Dependent Biomechanics Reveals Differential Strain Transfer Hierarchy in Skeletal Muscle.

Authors:  Soham Ghosh; James G Cimino; Adrienne K Scott; Frederick W Damen; Evan H Phillips; Alexander I Veress; Corey P Neu; Craig J Goergen
Journal:  ACS Biomater Sci Eng       Date:  2017-02-17

10.  Study of the Mechanical Environment of Chondrocytes in Articular Cartilage Defects Repaired Area under Cyclic Compressive Loading.

Authors:  Hai-Ying Liu; Hang-Tian Duan; Chun-Qiu Zhang; Wei Wang
Journal:  J Healthc Eng       Date:  2017-07-09       Impact factor: 2.682

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