Literature DB >> 27825602

Comparison of different material models of articular cartilage in 3D computational modeling of the knee: Data from the Osteoarthritis Initiative (OAI).

Olesya Klets1, Mika E Mononen2, Petri Tanska2, Miika T Nieminen3, Rami K Korhonen4, Simo Saarakkala3.   

Abstract

The intricate properties of articular cartilage and the complexity of the loading environment are some of the key challenges in developing models for biomechanical analysis of the knee joint. Fibril-reinforced poroelastic (FRPE) material models have been reported to accurately capture characteristic responses of cartilage during dynamic and static loadings. However, high computational and time costs associated with such advanced models limit applicability of FRPE models when multiple subjects need to be analyzed. If choosing simpler material models, it is important to show that they can still produce truthful predictions. Therefore, the aim of this study was to compare depth-dependent maximum principal stresses and strains within articular cartilage in the 3D knee joint between FRPE material models and simpler isotropic elastic (IE), isotropic poroelastic (IPE) and transversely isotropic poroelastic (TIPE) material models during simulated gait cycle. When cartilage-cartilage contact pressures were matched between the models (15% allowed difference), maximum principal stresses in the IE, IPE and TIPE models were substantially lower than those in the FRPE model (by more than 50%, TIPE model being closest to the FRPE model), and stresses occurred only in compression in the IE model. Additional simulations were performed to find material parameters for the TIPE model (due to its anisotropic nature) that would yield maximum principal stresses similar to the FRPE model. The modified homogeneous TIPE model was in a better agreement with the homogeneous FRPE model, and the average and maximum differences in maximum principal stresses throughout the depth of cartilage were 7% and 9%, respectively, in the lateral compartment and 9% and 11% in the medial compartment. This study revealed that it is possible to match simultaneously maximum principal stresses and strains of cartilage between non-fibril-reinforced and fibril-reinforced knee joint models during gait. Depending on the research question (such as analysis of fibril strain necessitates the use of fibril-reinforced material models) or clinical demand (fast simulations with simpler material models), the choice of the material model should be done carefully.
Copyright © 2016 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Articular cartilage; Finite element analysis; Gait cycle; Knee joint; Magnetic resonance imaging; Material parameters

Mesh:

Year:  2016        PMID: 27825602      PMCID: PMC5653924          DOI: 10.1016/j.jbiomech.2016.10.025

Source DB:  PubMed          Journal:  J Biomech        ISSN: 0021-9290            Impact factor:   2.712


  51 in total

1.  Biphasic poroviscoelastic simulation of the unconfined compression of articular cartilage: II--Effect of variable strain rates.

Authors:  M R DiSilvestro; Q Zhu; J K Suh
Journal:  J Biomech Eng       Date:  2001-04       Impact factor: 2.097

2.  Methodology and apparatus to determine material properties of the knee joint meniscus.

Authors:  D J Goertzen; D R Budney; J G Cinats
Journal:  Med Eng Phys       Date:  1997-07       Impact factor: 2.242

3.  Characterization of site-specific biomechanical properties of human meniscus-Importance of collagen and fluid on mechanical nonlinearities.

Authors:  E K Danso; J T A Mäkelä; P Tanska; M E Mononen; J T J Honkanen; J S Jurvelin; J Töyräs; P Julkunen; R K Korhonen
Journal:  J Biomech       Date:  2015-02-07       Impact factor: 2.712

4.  Direct measurement of the Poisson's ratio of human patella cartilage in tension.

Authors:  Dawn M Elliott; Daria A Narmoneva; Lori A Setton
Journal:  J Biomech Eng       Date:  2002-04       Impact factor: 2.097

5.  A modeling framework to estimate patellofemoral joint cartilage stress in vivo.

Authors:  Thor F Besier; Garry E Gold; Gary S Beaupré; Scott L Delp
Journal:  Med Sci Sports Exerc       Date:  2005-11       Impact factor: 5.411

6.  Effect of bone inhomogeneity on tibiofemoral contact mechanics during physiological loading.

Authors:  M S Venäläinen; M E Mononen; S P Väänänen; J S Jurvelin; J Töyräs; T Virén; R K Korhonen
Journal:  J Biomech       Date:  2016-02-24       Impact factor: 2.712

7.  Pathways of load-induced cartilage damage causing cartilage degeneration in the knee after meniscectomy.

Authors:  W Wilson; B van Rietbergen; C C van Donkelaar; R Huiskes
Journal:  J Biomech       Date:  2003-06       Impact factor: 2.712

8.  A composition-based cartilage model for the assessment of compositional changes during cartilage damage and adaptation.

Authors:  W Wilson; J M Huyghe; C C van Donkelaar
Journal:  Osteoarthritis Cartilage       Date:  2006-02-13       Impact factor: 6.576

9.  Depth-dependent analysis of the role of collagen fibrils, fixed charges and fluid in the pericellular matrix of articular cartilage on chondrocyte mechanics.

Authors:  Rami K Korhonen; Walter Herzog
Journal:  J Biomech       Date:  2007-10-22       Impact factor: 2.712

10.  Standardized loads acting in knee implants.

Authors:  Georg Bergmann; Alwina Bender; Friedmar Graichen; Jörn Dymke; Antonius Rohlmann; Adam Trepczynski; Markus O Heller; Ines Kutzner
Journal:  PLoS One       Date:  2014-01-23       Impact factor: 3.240

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  11 in total

1.  Estimation of the Effect of Body Weight on the Development of Osteoarthritis Based on Cumulative Stresses in Cartilage: Data from the Osteoarthritis Initiative.

Authors:  Olesya Klets; Mika E Mononen; Mimmi K Liukkonen; Mika T Nevalainen; Miika T Nieminen; Simo Saarakkala; Rami K Korhonen
Journal:  Ann Biomed Eng       Date:  2017-12-26       Impact factor: 3.934

2.  Low-level cyclic tibial compression attenuates early osteoarthritis progression after joint injury in mice.

Authors:  D T Holyoak; C Chlebek; M J Kim; T M Wright; M Otero; M C H van der Meulen
Journal:  Osteoarthritis Cartilage       Date:  2019-06-29       Impact factor: 6.576

3.  The effect of modelling parameters in the development and validation of knee joint models on ligament mechanics: A systematic review.

Authors:  Sara Sadat Farshidfar; Joseph Cadman; Danny Deng; Richard Appleyard; Danè Dabirrahmani
Journal:  PLoS One       Date:  2022-01-27       Impact factor: 3.240

4.  Subject-specific biomechanical analysis to estimate locations susceptible to osteoarthritis-Finite element modeling and MRI follow-up of ACL reconstructed patients.

Authors:  Paul O Bolcos; Mika E Mononen; Koren E Roach; Matthew S Tanaka; Juha-Sampo Suomalainen; Santtu Mikkonen; Mikko J Nissi; Juha Töyräs; Thomas M Link; Richard B Souza; Sharmila Majumdar; C Benjamin Ma; Xiaojuan Li; Rami K Korhonen
Journal:  J Orthop Res       Date:  2021-11-24       Impact factor: 3.102

5.  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

6.  Comparison between kinetic and kinetic-kinematic driven knee joint finite element models.

Authors:  Paul O Bolcos; Mika E Mononen; Ali Mohammadi; Mohammadhossein Ebrahimi; Matthew S Tanaka; Michael A Samaan; Richard B Souza; Xiaojuan Li; Juha-Sampo Suomalainen; Jukka S Jurvelin; Juha Töyräs; Rami K Korhonen
Journal:  Sci Rep       Date:  2018-11-26       Impact factor: 4.379

7.  Evaluation of Patellar Contact Pressure Changes after Static versus Dynamic Medial Patellofemoral Ligament Reconstructions Using a Finite Element Model.

Authors:  Vicente Sanchis-Alfonso; Gerard Ginovart; Diego Alastruey-López; Erik Montesinos-Berry; Joan Carles Monllau; Angel Alberich-Bayarri; María Angeles Pérez
Journal:  J Clin Med       Date:  2019-12-01       Impact factor: 4.241

8.  Model for in-vivo estimation of stiffness of tibiofemoral joint using MR imaging and FEM analysis.

Authors:  Sandeep Panwar Jogi; Rafeek Thaha; Sriram Rajan; Vidur Mahajan; Vasantha Kumar Venugopal; Anup Singh; Amit Mehndiratta
Journal:  J Transl Med       Date:  2021-07-19       Impact factor: 5.531

9.  The effect of constitutive representations and structural constituents of ligaments on knee joint mechanics.

Authors:  Gustavo A Orozco; Petri Tanska; Mika E Mononen; Kimmo S Halonen; Rami K Korhonen
Journal:  Sci Rep       Date:  2018-02-02       Impact factor: 4.379

10.  Numerical Modeling of Shockwave Treatment of Knee Joint.

Authors:  Galina Eremina; Alexey Smolin
Journal:  Materials (Basel)       Date:  2021-12-13       Impact factor: 3.623

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