Abstract
Computer simulation is a cornerstone of engineering design of high performance mechanical engineering equipment. However computer simulation is not so much used in the design of medical devices. The reasons for this are multifactorial and have their origin in the scepticism that biologists (and therefore clinicians) have regarding the plausibility of actually including all relevant factors in a computational model. In this work we have set out to model the response of tissues to changes in their mechanical environment, which could be caused by the presence of an implant or by damage of the tissue. We have used a lattice modelling approach, where the domain under analysis is discretized using both a finite element grid to compute biophysical stimuli and a ‘lattice’ to model cell activities. We applied the approach to two problems: (i) healing after bone fracture, and (ii) tissue regeneration inside a scaffold implanted into the body.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
van der Meulen, M.C.H., Huiskes, R.: Why mechanobiology? A survey article. Journal of Biomechanics 35, 401–414 (2002)
Pauwels, F.: A new theory on the influence of mechanical stimuli on the differentiation of supporting tissue. The tenth contribution to the functional anatomy and causal morphology of the supporting structure. Z. Anat. Entwickl. Gesch. 121, 478–515 (1960)
Carter, D., Blenman, P., Beaupré, G.: Correlations between mechanical stress history and tissue differentiation in initial fracture healing. J Ortho. Res. 6, 736–748 (1988)
Claes, L., Heigele, C.: Magnitudes of local stress and strain along bony surfaces predicts the course and type of fracture healing. Journal of Biomechanics 32, 255–266 (1999)
Prendergast, P.J., Huiskes, R., Søballe, K.: Biophysical stimuli on cells during tissue differentiation at implant interfaces. Journal of Biomechanics 30, 539–548 (1997)
Andreykiv, A., van Keulen, F., Prendergast, P.J.: Simulation of fracture healing incorporating mechano-regulation of tissue differentiation and dispersal/proliferation of cells. Biomech. Model. Mechanobiol. 7, 443–461 (2008)
Isaksson, H., Wilson, W., van Donkellaar, C.C., Huiskes, R., Ito, K.: Comparison of biophysical stimuli for mechano-regulation of tissue differentiation during fracture healing. Journal of Biomechanics 39, 1507–1516 (2006)
Lacroix, D., Prendergast, P.J.: A mechano-regulation model for tissue differentiation during fracture healing: analysis of gap size and loading. Journal of Biomechanics 35, 1163–1171 (2002)
Hayward, L.N.M., Morgan, E.F.: Assessment of a mechano-regulation theory of skeletal tissue differentiation in an in vivo model of mechanically induced cartilage formation. Biomech. Model Mechanobio (2009), doi:10.1007/s10237-009-0148-3
Kelly, D.J., Prendergast, P.J.: Mechano-regulation of stem cell differentiation and tissue regeneration in osteochondral defects. Journal of Biomechanics 38, 1413–1422 (2005)
Isaksson, H., Comas, O., van Donkelaar, C.C., Mediavilla, J., Wilson, W., Huiskes, R., Ito, K.: Bone regeneration during distraction osteogenesis: mechano-regulation by shear strain and fluid velocity. Journal of Biomechanics 40, 2002–2011 (2006)
Morgan, E.F., Longaker, M.T., Carter, D.R.: Relationships between tissue dilatation and differentiation in distraction osteogenesis. Matrix Biol. 25(2), 94–103 (2006)
Byrne, D.P., Lacroix, D., Planell, J.A., Kelly, D.J., Prendergast, P.J.: Simulation of tissue differentiation in a scaffold as a function of porosity, Young’s modulus and dissolution rate: application of mechanobiological models in tissue engineering. Biomaterials 28, 5544–5554 (2007)
Kelly, D.J., Prendergast, P.J.: Prediction of optimal mechanical properties for a scaffold used in osteochondral defect repair. Tissue Engineering 12, 2509–2519 (2006)
Geris, L., Andreykiv, A., van Oosterwyck, H., van der Sloten, J., van Keulen, F., Duyck, J., Naert, I.: Numerical simulation of tissue differentiation around loaded titanium implants in a bone chamber. Journal of Biomechanics 37, 763–769 (2008)
Huiskes, R., van Driel, W.D., Prendergast, P.J., Søballe, K.: A biomechanical regulatory model for periprosthetic fibrous tissue differentiation. J. Mater. Sci.: Mater. Med. 8, 785–788 (1997)
Liu, X., Niebur, G.L.: Bone ingrowth into a porous coated implant predicted by a mechano-regulatory tissue differentiation algorithm. Biomech. Model. Mechanobiol. 7, 335–344 (2008)
Simpson, M.J., Merrifield, A., Landman, K.A., Hughes, B.D.: Simulating invasion with cellular automata: Connecting cell-scale and population-scale properties. Physical Review E76 (2007)
Isaksson, H., van Donkelaar, C., Huiskes, R., Ito, K.: A mechano-regulatory bone-healing model incorporating cell-phenotype specific activity. Journal of Theoretical Biology 252, 230–246 (2008)
Pérez, M., Prendergast, P.J.: Random-walk model of cell-dispersal included in mechanobiological simulation of tissue differentiation. Journal of Biomechanics 40, 2244–2253 (2007)
Claes, L., Eckert-Hubner, K., Augat, P.: The fracture gap size influences the local vascularisation and tissue differentiation in callus healing. Langenbecks Arch. Surg. 388, 316–322 (2003)
Checa, S., Prendergast, P.J.: A Mechanobiological Model for Tissue Differentiation that Includes Angiogenesis: A Lattice-Based Modeling Approach. Annals of Biomed Eng. 37, 129–145 (2009)
Kanichai, M., Ferguson, D., Prendergast, P.J., Campbell, V.A.: Hypoxia promotes chondrogenesis in rat mesenchymal stem cells: a role for AKT and Hypoxia-Inducible Factor (HIF)-1α. Journal of Cellular Physiology 216, 708–715 (2008)
Carmeliet, P., Jain, M.K.: Angiogenesis in cancer and other diseases. Nature 407, 249–257 (2008)
Byrne, D.P.: Computational modelling of bone regeneration using a three-dimensional lattice approach, PhD thesis, University of Dublin (2008)
Duda, G.N., Mandruzzato, F., Heller, M., Kassi, J.P., Khodadadyan, C., Haas, N.P.: Mechanical conditions in the internal stabilization of proximal tibial defects. Clinical Bio-mechanics 17(1), 64–72 (2002)
Kneser, U., Stangenberg, L., Ohnolz, J., Buettner, O., Stern-Strater, J., Möbest, D., Horch, R.E., Stark, G.B., Schaefer, D.J.: Evaluation of processed bovine cancellous bone matrix seeded with syngenic osteoblasts in a critical size calvarial defect rat model. J. Cell. Mol. Med. 10, 695–707 (2006)
Prendergast, P.J., Checa, S., Lacroix, D.: Computational models for tissue differentiation. In: De, S., Guilak, F., Mofrad, M. (eds.) Computational Methods in Biomechanics, Springer, New York (in press, 2009)
Geris, L., Vandamme, K., Naert, I., van der Sloten, J., Duyck, J.: Application of mechanoregulatory models to simulate periimplant tissue formation in an in vivo bone chamber. Journal of Biomechanics 41, 145–154 (2008)
Khayyeri, H., Checa, S., Tagil, M., Prendergast, P.J.: Corroboration of mechanobiological simulations of tissue differentiation in an in vivo bone chamber using a lattice-modeling approach. J. Orthop. Res. (in press) (2009)
Clapworthy, G., Viceconti, M., Coveney, P.V., Kohl, P.: The virtual physiological human: building a framework for computational biomedicine. Phil. Trans. R. Soc. 366, 2975–2978 (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer Berlin Heidelberg
About this chapter
Cite this chapter
Checa, S., Byrne, D.P., Prendergast, P.J. (2010). Predictive Modelling in Mechanobiology: Combining Algorithms for Cell Activities in Response to Physical Stimuli Using a Lattice-Modelling Approach. In: Kuczma, M., Wilmanski, K. (eds) Computer Methods in Mechanics. Advanced Structured Materials, vol 1. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05241-5_22
Download citation
DOI: https://doi.org/10.1007/978-3-642-05241-5_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-05240-8
Online ISBN: 978-3-642-05241-5
eBook Packages: Chemistry and Materials ScienceChemistry and Material Science (R0)