Editorial Computational Models of Articular Cartilage

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Hindawi Publishing CorporationComputational and Mathematical Methods in MedicineVolume 2013, Article ID 254507, 2 pageshttp://dx.doi.org/10.1155/2013/254507

EditorialComputational Models of Articular Cartilage

Rami K. Korhonen,1 Petro Julkunen,2 LePing Li,3 and Corrinus C. van Donkelaar4

1 Department of Applied Physics, University of Eastern Finland, P.O. Box 1627, 70211 Kuopio, Finland2Department of Clinical Neurophysiology, Kuopio University Hospital, P.O. Box 1777, 70211, Kuopio, Finland3Department of Mechanical and Manufacturing Engineering, University of Calgary, Calgary, AB, Canada T2N 1N44Department of Biomedical Engineering, Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven, The Netherlands

Correspondence should be addressed to Rami K. Korhonen; rami.korhonen@uef.fi

Received 19 March 2013; Accepted 19 March 2013

Copyright © 2013 Rami K. Korhonen et al. This is an open access article distributed under the Creative Commons AttributionLicense, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properlycited.

In osteoarthritis, articular cartilage degenerates and eventu-ally wears out, resulting in pain and disability. It is a majorchallenge in health care to prevent osteoarthritis or slowdown the progression of the disease.The onset of osteoarthri-tis may result from an altered stress and strain state in carti-lage, for example, due to an injury of ligament, cartilage, ormeniscus. However, the disease progression is patient specificand can hardly be predicted. In order to assess the articularcartilage function and possible failure sites in joints, and toevaluate the onset and progression of osteoarthritis patient-specifically, computational models may become useful tools.Although there has been significant progress over the lastyears, these models need to be further developed before theymay eventually become of direct clinical value.

For clinical, patient-specific application of a computermodel, a realistic description of joint geometry, joint kine-matics, and tissue loading is ultimately required. Geometricaldata can be obtained from imaging modalities, such as MRI,which become increasingly more detailed. Still, meshingof such information and running computational simula-tions of such meshes is challenging. Simulation analysis ofjoint kinematics is computationally expensive and requiresknowledge of the kinematic constraints as a consequence ofmuscles and ligaments, including, for instance, pre stressesand attachment sites of ligaments. In many cases, 3D and/orkinematic simulations are still more feasible in combinationwith simpler material models for cartilage. More advancedmaterial descriptions are required for a more detailed inves-tigation of mechanical conditions inside cartilage. However,

these are essential to move forward in our understandingof the relationship between mechanical loading, cartilagedamage, and osteoarthritis.

A wide variety of cartilage models have been developedand employed to evaluate the mechanical behavior at thecell, tissue, and joint level. They have been used to evaluatestatic and dynamic tissue behavior, to explore effects ofmechanical and biochemical loading, and even to predicttissue adaptation at the long time scale.The expectation is thatsuch models may be taken to the next level, where patient-specific characteristics are incorporated in 3D kinematic jointmodels.

Given the composite structure of cartilage with thecollagen fibril network, proteoglycan matrix, and fluid, thisspecial issue has a focus on the development and applicationof fibril-reinforced models at different scales. A review of thefibril-reinforced tissuemodels and their application in the celllevel is presented (P. Julkunen et al.). Practical considerationsin modeling applications and model limitations are furtherdiscussed. A thorough review of recent advances in com-putational modeling of human knee joints is also presented(M. Kazemi et al.). Creation of knee joint models startingfrom imaging data (such as MRI) is summarized, clinicalapplications of the models are discussed, and examples aregiven for patient-specific evaluation of knee joint mechanics.Furthermore, influence of the altered depth-dependent prop-erties of cartilage in osteoarthritis on fluid pressurization ina knee joint is demonstrated (Y. Dabiri and L. P. Li). Sincegeneration of computational finite element models of knee

2 Computational and Mathematical Methods in Medicine

joints is time-consuming and model simulation times canbe relatively long, a semiautomated method is presented tostudy tibiofemoral contact stresses of adult subjects (D. D.Anderson et al.).

Combination of experimental measurements and model-ing is reviewed and model validation in cell, tissue, and jointlevel is discussed (P. Julkunen et al. and M. Kazemi et al.).Specifically, experimental results on the depth-dependentmicrostructural response of cartilage under directly loadedand unloaded regions are presented (A. Thambyah and N.Broom). Loading-related changes in chondron aspect ratiosat different zones are also shown. These results can beused for the validation and development of computationalmodels incorporating higher degrees of structural realism.Further, experimentally measured chondrocyte deformationbehavior under mechanical loading of the tissue is presentedfor normal and osteoarthritic cartilage (P. Tanska et al.).Computational multiscale modeling is applied to explaindifferences in the cell behavior between the aforementionedgroups. Finally, potential future directions in the applicationof multiscale models for the evaluation of cell responses anddisease progression in knee joints are addressed (P. Julkunenet al.).

Recent advances in the development of computationalmodels of articular cartilage, as partially demonstrated inthis special issue, and models of joints with realistic patient-specific material descriptions and joint kinematics havebrought clinical application closer.More advanced adaptationmodels, likely combinations of models addressing differentlength scales, should ultimately lead to the prediction ofaltered tissue properties and wear, which strongly correlateto the development of osteoarthritis. Ultimately, computa-tional modeling may become a clinical tool for identifyingor optimizing patient-specific treatment strategies, such asrehabilitation and surgical interventions.

Rami K. KorhonenPetro Julkunen

LePing LiCorrinus C. van Donkelaar

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