[en] Osteoarthritis is a whole joint disease with cartilage degeneration being an important manifestation. Tissue engineering treatment is a solution for repairing cartilage defects by implantation of chondrocyte-laden hydrogel constructs within the defect. In silico models have recently been introduced to simulate and optimize the design of these constructs. These models require accurate knowledge on the mechanical properties of the hydrogel constructs and cartilage explants, which are challenging to obtain due to their anisotropic structure and time-dependent behaviour. We performed a systematic in silico parameter sensitivity analysis to find the most efficient unconfined compression testing protocols for mechanical characterization of hydrogel constructs and cartilage explants, with a minimum number of tests but maximum identifiability of the material parameters. The construct and explant were thereby modelled as porohyperelastic and fibril-reinforced poroelastic materials, respectively. Three commonly used loading regimes were simulated in Abaqus (ramp, relaxation and dynamic loading) with varying compressive strain magnitudes and rates. From these virtual experiments, the resulting material parameters were obtained for each combination using a numerical inverse identification scheme. For hydrogels, maximum sensitivity to the different material parameters was found when using a single step ramp loading (20% compression with 10%/s rate) followed by 15 min relaxation. For cartilage explants, a two-stepped ramp loading (10% compression with 10%/s rate and 10% compression with 1%/s rate), each step followed by 15 min relaxation, yielded the maximum sensitivity to the different material parameters. With these protocols, the material parameters could be retrieved with the lowest amount of uncertainty (hydrogel: < 2% and cartilage: < 6%). These specific results and the overall methodology can be used to optimize mechanical testing protocols to yield reliable material parameters for in silico models of cartilage and hydrogel constructs.
Disciplines :
Engineering, computing & technology: Multidisciplinary, general & others
Author, co-author :
Elahi, Seyed Ali; Human Movement Biomechanics Research Group, Department of Movement Sciences, KU
Tanska, Petri; Department of Applied Physics, University of Eastern Finland, Kuopio, Finland.
Mukherjee, Satanik; Prometheus, Division of Skeletal Tissue Engineering, KU Leuven, Leuven, Belgium,
Korhonen, Rami K; Department of Applied Physics, University of Eastern Finland, Kuopio, Finland.
Geris, Liesbet ; Université de Liège - ULiège > GIGA > GIGA In silico medecine - Biomechanics Research Unit ; Prometheus, Division of Skeletal Tissue Engineering, KU Leuven, Leuven, Belgium,
Jonkers, Ilse; Human Movement Biomechanics Research Group, Department of Movement Sciences, KU
Ateshian, G.A., Hung, C.T., Functional properties of native articular cartilage. Guilak, F., Butler, D.L., Goldstein, S.A., Mooney, D.J., (eds.) Functional Tissue Engineering, 2003, Springer, New York, 46–68.
Ateshian, G.A., Rajan, V., Chahine, N.O., Canal, C.E., Hung, C.T., Modeling the matrix of articular cartilage using a continuous fiber angular distribution predicts many observed phenomena. J. Biomech. Eng.-T. Asme., 131, 2009, 061003.
Babalola, O.M., Bonassar, L.J., Parametric finite element analysis of physical stimuli resulting from mechanical stimulation of tissue engineered cartilage. J. Biomech. Eng.-T. Asme., 131, 2009, 061014.
Bandeiras, C., Completo, A., A mathematical model of tissue-engineered cartilage development under cyclic compressive loading. Biomech. Model. Mechanobiol. 16 (2017), 651–656 66.
Beynnon, B.D., Fleming, B.C., Labovitch, R., Parsons, B., Chronic anterior cruciate ligament deficiency is associated with increased anterior translation of the tibia during the transition from non-weightbearing to weightbearing. J. Orthop. Res. 20 (2002), 332–337.
Brittberg, M., Lindahl, A., Nilsson, A., Ohlsson, C., Isaksson, O., Peterson, L., Treatment of deep cartilage defects in the knee with autologous chondrocyte transplantation. N. Engl. J. Med. 331 (1994), 889–895.
Danso, E.K., Julkunen, P., Korhonen, R.K., Poisson's ratio of bovine meniscus determined combining unconfined and confined compression. J. Biomech. 77 (2018), 233–237.
DiSilvestro, M.R., Suh, J.K., A cross-validation of the biphasic poroviscoelastic model of articular cartilage in unconfined compression, indentation, and confined compression. J. Biomech. 34 (2001), 519–525.
DiSilvestro, M.R., Zhu, Q., Wong, M., Jurvelin, J.S., Suh, J.K., Biphasic poroviscoelastic simulation of the unconfined compression of articular cartilage: I—simultaneous prediction of reaction force and lateral displacement. J. Biomech. Eng.-T. Asme. 123 (2001), 191–197.
Drury, J.L., Mooney, D.J., Hydrogels for tissue engineering: scaffold design variables and applications. Biomaterials 24 (2003), 4337–4351.
Ebrahimi, M., Ojanen, S., Mohammadi, A., Finnilä, M.A., Joukainen, A., Kröger, H., Saarakkala, S., Korhonen, R.K., Tanska, P., Elastic, viscoelastic and fibril-reinforced poroelastic material properties of healthy and osteoarthritic human tibial cartilage. Ann. Biomed. Eng. 47 (2019), 953–966.
Elahi, S.A., Towards In-Vivo and In-Situ Mechanical Characterization of Soft Living Tissues. PhD thesis, 2018, Grenoble Alpes University, Grenoble.
Elahi, S.A., Connesson, N., Payan, Y., Disposable system for in-vivo mechanical characterization of soft tissues based on volume measurement. J. Mech. Med. Biol., 18, 2018, 1850037.
Elahi, S.A., Fehervary, H., Famaey, N., Tanska, P., Korhonen, R.K., Jonker, I., Optimized multi-axial loading to enhance chondrogenesis and limit proteoglycan loss in cartilage explants during bioreactor experimentation. Osteoarthritis Cartilage, 28, 2020, S519.
Eskelinen, A.S., Mononen, M.E., Venäläinen, M.S., Korhonen, R.K., Tanska P, P., Maximum shear strain-based algorithm can predict proteoglycan loss in damaged articular cartilage. Biomech. Model. Mechanobiol. 18 (2019), 753–778.
Evans, S., How can we measure the mechanical properties of soft tissues?. Material Parameter Identification and Inverse Problems in Soft Tissue Biomechanics, 2017, Springer Cham, 67–83.
Farokhi, M., Jonidi Shariatzadeh, F., Solouk, A., Mirzadeh, H., Alginate based scaffolds for cartilage tissue engineering: a review. Int. J. Polym. Mater. 69 (2020), 230–247.
Frauziols, F., Chassagne, F., Badel, P., Navarro, L., Molimard, J., Curt, N., Avril, S., In vivo identification of the passive mechanical properties of deep soft tissues in the human leg. Strain 52 (2016), 400–411.
Hendrikson, W.J., Deegan, A.J., Yang, Y., Van Blitterswijk, C.A., Verdonschot, N., Moroni, L., Rouwkema, J., Influence of additive manufactured scaffold architecture on the distribution of surface strains and fluid flow shear stresses and expected osteochondral cell differentiation. Front. Bioeng. Biotech., 10, 2017, 6.
Holmes, M.H., Mow, V.C., The nonlinear characteristics of soft gels and hydrated connective tissues in ultrafiltration. J. Biomech. 23 (1990), 1145–1156.
Hosseini, S.M., Wilson, W., Ito, K., Van Donkelaar, C.C., A numerical model to study mechanically induced initiation and progression of damage in articular cartilage. Osteoarthritis Cartilage 22 (2014), 95–103.
Hosseini, S.A., Mohammadi, R., Noruzi, S., Ganji, R., Oroojalian, F., Sahebkar, A., Evolution of hydrogels for cartilage tissue engineering of the knee: a systematic review and meta-analysis of clinical studies. Joint Bone Spine, 88, 2021, 105096.
Jacobi, M., Villa, V., Magnussen, R.A., Neyret, P., MACI-a new era?. Sports Med. Arthrosc. Rehabil. Ther. Technol., 3, 2011.
Jones, B., Hung, C.T., Ateshian, G., Biphasic analysis of cartilage stresses in the patellofemoral joint. J. Knee Surg. 29 (2016), 92–98.
Julian, T.N., Radebaugh, G.W., Wisniewski, S.J., Permeability characteristics of calcium alginate films. J. Contr. Release 7 (1988), 165–169.
Kaklamani, G., Cheneler, D., Grover, L.M., Adams, M.J., Bowen, J., Mechanical properties of alginate hydrogels manufactured using external gelation. J. Mech. Behav. Biomed. 36 (2014), 135–142.
Kazemi, M., Li, L.P., A viscoelastic poromechanical model of the knee joint in large compression. Med. Eng. Phys. 36 (2014), 998–1006.
Kazemi, M., Dabiri, Y., Li, L.P., Recent advances in computational mechanics of the human knee joint. Comput. Math. Method M. 19 (2013), 1–27.
Kelly, D.J., Prendergast, P.J., Prediction of the optimal mechanical properties for a scaffold used in osteochondral defect repair. Tissue Eng. 12 (2006), 2509–2519.
Kisiday, D.J., Jin, M., DiMicco, M.A., Kurz, B., Grodzinsky, A.J., Effects of dynamic compressive loading on chondrocyte biosynthesis in self-assembling peptide scaffolds. J. Biomech. 37 (2004), 595–604.
Kundu, J., Shim, J.H., Jang, J., Kim, S.W., Cho, D.W., An additive manufacturing‐based PCL–alginate–chondrocyte bioprinted scaffold for cartilage tissue engineering. J. Tissue Eng. Regen. M. 9 (2015), 1286–1297.
Li, L.P., Soulhat, J., Buschmann, M.D., Shirazi-Adl, A., Nonlinear analysis of cartilage in unconfined ramp compression using a fibril reinforced poroelastic model. Clin. Biomech. 14 (1999), 673–682.
Li, L., Yang, L., Zhang, K., Zhu, L., Wang, X., Jiang, Q., Three-dimensional finite-element analysis of aggravating medial meniscus tears on knee osteoarthritis. J. Orthop. Transl. 20 (2020), 47–55.
Matyash, M., Despang, F., Ikonomidou, C., Gelinsky, M., Swelling and mechanical properties of alginate hydrogels with respect to promotion of neural growth. Tissue Eng. C Methods 20 (2014), 401–411.
Mohammadi, H., Mequanint, K., Herzog, W., Computational aspects in mechanical modeling of the articular cartilage tissue. Proc. Inst. Mech. Eng. H. 227 (2013), 402–420.
Mononen, M.E., Tanska, P., Isaksson, H., Korhonen, R.K., A novel method to simulate the progression of collagen degeneration of cartilage in the knee: data from the osteoarthritis initiative. Sci. Rep., 6, 2016, 21415.
Mononen, M.E., Tanska, P., Isaksson, H., Korhonen, R.K., New algorithm for simulation of proteoglycan loss and collagen degeneration in the knee joint: data from the osteoarthritis initiative. J. Orthop. Res. 36 (2018), 1673–1683.
Mukherjee, S., Nazemi, M., Jonkers, I., Geris, L., Use of computational modeling to study joint degeneration: a review. Front. Bioeng. Biotech., 8, 2020, 93.
Nelder, J.A., Mead R, R., A simplex method for function minimization. Comput. J. 7 (1965), 308–313.
Nguyen, V.B., Wang, C.X., Thomas, C.R., Zhang, Z., Mechanical properties of single alginate microspheres determined by microcompression and finite element modelling. Chem. Eng. Sci. 64 (2009), 821–829.
Nguyen, V.B., Wang, C.X., Thomas, C.R., Zhang, Z., Mechanical properties of single alginate microspheres determined by microcompression and finite element modelling. Chem. Eng. Sci. 64 (2009), 821–829.
Novaretti, J.V., João, Lian, J., Patel, N.K., Chan, C.K., Cohen, M., Musah, V., Debski, R.E., Partial lateral meniscectomy affects knee stability even in anterior cruciate ligament-intact knees. J. Bone Joint Surg. 102 (2020), 567–573.
Olvera, D., Daly, A., Kelly, D.J., Mechanical testing of cartilage constructs. Doran, P., (eds.) Cartilage Tissue Engineering, 2015, Humana Press, New York, 279–287.
Orozco, G.A., Tanska, P., Florea, C., Grodzinsky, A.J., Korhonen, R.K., A novel mechanobiological model can predict how physiologically relevant dynamic loading causes proteoglycan loss in mechanically injured articular cartilage. Sci. Rep. 8 (2018), 1–6.
Patel, J.M., Wise, B.C., Bonnevie, E.D., Mauck, R.L., A systematic review and guide to mechanical testing for articular cartilage tissue engineering. Tissue Eng. C Methods 25 (2019), 593–608.
Quiroga, J.P., Wilson, W., Ito, K., C Van Donkelaar, C., Relative contribution of articular cartilage's constitutive components to load support depending on strain rate. Biomech. Model. Mechanobiol. 16 (2017), 151–158.
Shefelbine, S.J., Ma, C.B., Lee, K.Y., Schrumpf, M.A., Patel, P., Safran, M.R., Slavinsky, J.P., Majumdar, S., MRI analysis of in vivo meniscal and tibiofemoral kinematics in ACL‐deficient and normal knees. J. Orthop. Res. 24 (2006), 1208–1217.
Walter, S.G., Ossendorff, R., Schildberg, F.A., Articular cartilage regeneration and tissue engineering models: a systematic review. Arch. Orthop. Trauma Surg. 139 (2019), 305–316.
Wilson, W., Van Donkelaar, C.C., Van Rietbergen, B., Ito, K., Huiskes, R., Stresses in the local collagen network of articular cartilage: a poroviscoelastic fibril-reinforced finite element study. J. Biomech. 37 (2004), 357–366.
Wilson, W., van Donkelaar, C.C., van Rietbergen, B., Huiskes, R., A fibril-reinforced poroviscoelastic swelling model for articular cartilage. J. Biomech. 38 (2005), 1195–1204.
Wilson, W., Van Donkelaar, C.C., Van Rietbergen, B., Huiskes, R., A fibril-reinforced poroviscoelastic swelling model for articular cartilage. J. Biomech. 38 (2005), 1195–1204.
Zahedmanesh, H., Stoddart, M., Lezuo, P., Forkmann, C., Wimmmer, M.A., Alini, M., Van Oosterwyck, H., Deciphering mechanical regulation of chondrogenesis in fibrin–polyurethane composite scaffolds enriched with human mesenchymal stem cells: a dual computational and experimental approach. Tissue Eng. 20 (2014), 1197–1212.