bone healing; computer modeling; multiscale modeling; systems biology; tissue regeneration; Physiology; Physiology (medical)
Abstract :
[en] Bone is a living part of the body that can, in most situations, heal itself after fracture. However, in some situations, healing may fail. Compromised conditions, such as large bone defects, aging, immuno-deficiency, or genetic disorders, might lead to delayed or non-unions. Treatment strategies for those conditions remain a clinical challenge, emphasizing the need to better understand the mechanisms behind endogenous bone regeneration. Bone healing is a complex process that involves the coordination of multiple events at different length and time scales. Computer models have been able to provide great insights into the interactions occurring within and across the different scales (organ, tissue, cellular, intracellular) using different modeling approaches [partial differential equations (PDEs), agent-based models, and finite element techniques]. In this review, we summarize the latest advances in computer models of bone healing with a focus on multiscale approaches and how they have contributed to understand the emergence of tissue formation patterns as a result of processes taking place at the lower length scales.
Precision for document type :
Review article
Disciplines :
Engineering, computing & technology: Multidisciplinary, general & others
Author, co-author :
Borgiani, Edoardo ; Julius Wolff Institute, Charité-Universitätsmedizin BerlinBerlin, Germany ; Berlin-Brandenburg School for Regenerative Therapies, Charité-Universitätsmedizin BerlinBerlin, Germany
Duda, Georg N; Julius Wolff Institute, Charité-Universitätsmedizin BerlinBerlin, Germany ; Berlin-Brandenburg School for Regenerative Therapies, Charité-Universitätsmedizin BerlinBerlin, Germany
Checa, Sara; Julius Wolff Institute, Charité-Universitätsmedizin BerlinBerlin, Germany ; Berlin-Brandenburg School for Regenerative Therapies, Charité-Universitätsmedizin BerlinBerlin, Germany
Language :
English
Title :
Multiscale Modeling of Bone Healing: Toward a Systems Biology Approach.
Bailon-Plaza, A., and van der Meulen, M. C. (2001). A mathematical framework to study the effects of growth factor influences on fracture healing. J. Theor. Biol. 212, 191-209. doi: 10.1006/jtbi.2001.2372
Bailon-Plaza, A., and van der Meulen, M. C. (2003). Beneficial effects of moderate, early loading and adverse effects of delayed or excessive loading on bone healing. J. Biomech. 36, 1069-1077. doi: 10.1016/S0021-9290(03)00117-9
Bak, B., and Andreassen, T. T. (1989). The effect of aging on fracture-healing in the rat. Calcif. Tissue Int. 45, 292-297. doi: 10.1007/BF02556022
Bell, B. J., Nauman, E., and Voytik-Harbin, S. L. (2012). Multiscale strain analysis of tissue equivalents using a custom-designed biaxial testing device. Biophys. J. 102, 1303-1312. doi: 10.1016/j.bpj.2012.02.007
Borgiani, E. D. G., Willie, B., and Checa, S. (2015). Bone Healing in Mice: Does It Follow Generic Mechano-Regulation Rules? Series: Mechanical Engineering, Facta Universitatis. 13, 217-227
Burke, D., Dishowitz, M., Sweetwyne, M., Miedel, E., Hankenson, K. D., and Kelly, D. J. (2013). The role of oxygen as a regulator of stem cell fate during fracture repair in TSP2-null mice. J. Orthop. Res. 31, 1585-1596. doi: 10.1002/jor.22396
Burke, D. P., and Kelly, D. J. (2012). Substrate stiffness and oxygen as regulators of stem cell differentiation during skeletal tissue regeneration: a mechanobiological model. PLoS ONE 7:e40737. doi: 10.1371/journal.pone.0040737
Byrne, D. P., Lacroix, D., and Prendergast, P. J. (2011). Simulation of fracture healing in the tibia: mechanoregulation of cell activity using a lattice modeling approach. J. Orthop. Res. 29, 1496-1503. doi: 10.1002/jor.21362
Carlier, A., Brems, H., Ashbourn, J. M., Nica, I., Legius, E., and Geris, L. (2016). Capturing the wide variety of impaired fracture healing phenotypes in Neurofibromatosis Type 1 with eight key factors: a computational study. Sci. Rep. 7:20010. doi: 10.1038/srep20010
Carlier, A., Geris, L., Bentley, K., Carmeliet, G., Carmeliet, P., and Van Oosterwyck, H. (2012). MOSAIC: a multiscale model of osteogenesis and sprouting angiogenesis with lateral inhibition of endothelial cells. PLoS Comput. Biol. 8:e1002724. doi: 10.1371/journal.pcbi.1002724
Carlier, A., Geris, L., van Gastel, N., Carmeliet, G., and Van Oosterwyck, H. (2015). Oxygen as a critical determinant of bone fracture healing-A multiscale model. J. Theor. Biol. 365, 247-264. doi: 10.1016/j.jtbi.2014.10.012
Carlier, A., van Gastel, N., Geris, L., Carmeliet, G., and Van Oosterwyck, H. (2014). Size does matter: an integrative in vivo-in silico approach for the treatment of critical size bone defects. PLoS Comput. Biol. 10:e1003888. doi: 10.1371/journal.pcbi.1003888
Carter, D. R., Blenman, P. R., and Beaupre, G. S. (1988). Correlations between mechanical-stress history and tissue differentiation in initial fracture-healing. J. Orthop. Res. 6, 736-748. doi: 10.1002/jor.1100060517
Checa, S., Prendergast, P. J., and Duda, G. N. (2011). Inter-species investigation of the mechano-regulation of bone healing: comparison of secondary bone healing in sheep and rat. J. Biomech. 44, 1237-1245. doi: 10.1016/j.jbiomech.2011.02.074
Checa, S., Rausch, M. K., Petersen, A., Kuhl, E., and Duda, G. N. (2015). The emergence of extracellular matrix mechanics and cell traction forces as important regulators of cellular self-organization. Biomech. Model. Mechanobiol. 14, 1-13. doi: 10.1007/s10237-014-0581-9
Chen, G., Niemeyer, F., Wehner, T., Simon, U., Schuetz, M. A., Pearcy, M. J., et al. (2009). Simulation of the nutrient supply in fracture healing. J. Biomech. 42, 2575-2583. doi: 10.1016/j.jbiomech.2009.07.010
Claes, L., Augat, P., Suger, G., and Wilke, H. J. (1997). Influence of size and stability of the osteotomy gap on the success of fracture healing. J. Orthop. Res. 15, 577-584. doi: 10.1002/jor.1100150414
Claes, L. E., and Heigele, C. A. (1999). Magnitudes of local stress and strain along bony surfaces predict the course and type of fracture healing. J. Biomech. 32, 255-266. doi: 10.1016/S0021-9290(98)00153-5
Claes, L., Recknagel, S., and Ignatius, A. (2012). Fracture healing under healthy and inflammatory conditions. Nat. Rev. Rheumatol. 8, 133-143. doi: 10.1038/nrrheum.2012.1
El Khassawna, T., Toben, D., Kolanczyk, M., Schmidt-Bleek, K., Koennecke, I., Schell, H., et al. (2012). Deterioration of fracture healing in the mouse model of NF1 long bone dysplasia. Bone 51, 651-660. doi: 10.1016/j.bone.2012.07.011
Engler, A. J., Sen, S., Sweeney, H. L., and Discher, D. E. (2006). Matrix elasticity directs stem cell lineage specification. Cell 126, 677-689. doi: 10.1016/j.cell.2006.06.044
Garcia-Aznar, J. M., Kuiper, J. H., Gomez-Benito, M. J., Doblare, M., and Richardson, J. B. (2007). Computational simulation of fracture healing: influence of interfragmentary movement on the callus growth. J. Biomech. 40, 1467-1476. doi: 10.1016/j.jbiomech.2006.06.013
Geris, L., Gerisch, A., Sloten, J. V., Weiner, R., and Oosterwyck, H. V. (2008). Angiogenesis in bone fracture healing: a bioregulatory model. J. Theor. Biol. 251, 137-158. doi: 10.1016/j.jtbi.2007.11.008
Geris, L., Reed, A. A., Vander Sloten, J., Simpson, A. H., and Van Oosterwyck, H. (2010a). Occurrence and treatment of bone atrophic non-unions investigated by an integrative approach. PLoS Comput. Biol. 6:e1000915. doi: 10.1371/journal.pcbi.1000915
Geris, L., Vander Sloten, J., and Van Oosterwyck, H. (2010b). Connecting biology and mechanics in fracture healing: an integrated mathematical modeling framework for the study of nonunions. Biomech. Model. Mechanobiol. 9, 713-724. doi: 10.1007/s10237-010-0208-8
Gilbert, D., Fuss, H., Gu, X., Orton, R., Robinson, S., Vyshemirsky, V., et al. (2006). Computational methodologies for modelling, analysis and simulation of signalling networks. Brief. Bioinformatics 7, 339-353. doi: 10.1093/bib/bbl043
Gomez-Benito, M. J., Garcia-Aznar, J. M., Kuiper, J. H., and Doblare, M. (2005). Influence of fracture gap size on the pattern of long bone healing: a computational study. J. Theor. Biol. 235, 105-119. doi: 10.1016/j.jtbi.2004.12.023
Hadjipanayi, E., Mudera, V., and Brown, R. A. (2009). Close dependence of fibroblast proliferation on collagen scaffold matrix stiffness. J. Tissue Eng. Regen. Med. 3, 77-84. doi: 10.1002/term.136
Hayrapetyan, A., Jansen, J. A., and van den Beucken, J. J. (2015). Signaling pathways involved in osteogenesis and their application for bone regenerative medicine. Tissue Eng. Part B Rev. 21, 75-87. doi: 10.1089/ten.teb.2014.0119
Isaksson, H., van Donkelaar, C. C., Huiskes, R., and Ito, K. (2006). Corroboration of mechanoregulatory algorithms for tissue differentiation during fracture healing: comparison with in vivo results. J. Orthop. Res. 24, 898-907. doi: 10.1002/jor.20118
Isaksson, H., van Donkelaar, C. C., Huiskes, R., Yao, J., and Ito, K. (2008). Determining the most important cellular characteristics for fracture healing using design of experiments methods. J. Theor. Biol. 255, 26-39. doi: 10.1016/j.jtbi.2008.07.037
Klein, P., Schell, H., Streitparth, F., Heller, M., Kassi, J. P., Kandziora, F., et al. (2003). The initial phase of fracture healing is specifically sensitive to mechanical conditions. J. Orthop. Res. 21, 662-669. doi: 10.1016/S0736-0266(02)00259-0
Konnecke, I., Serra, A., El Khassawna, T., Schlundt, C., Schell, H., Hauser, A., et al. (2014). T and B cells participate in bone repair by infiltrating the fracture callus in a two-wave fashion. Bone 64, 155-165. doi: 10.1016/j.bone.2014.03.052
Lacroix, D., Prendergast, P. J., Li, G., and Marsh, D. (2002). Biomechanical model to simulate tissue differentiation and bone regeneration: application to fracture healing. Med. Biol. Eng. Comput. 40, 14-21. doi: 10.1007/BF02347690
Liu, Y. F., Manjubala, I., Schell, H., Epari, D. R., Roschger, P., Duda, G. N., et al. (2010). Size and habit of mineral particles in bone and mineralized callus during bone healing in sheep. J. Bone Miner. Res. 25, 2029-2038. doi: 10.1002/jbmr.84
Lo, C. M., Wang, H. B., Dembo, M., and Wang, Y. L. (2000). Cell movement is guided by the rigidity of the substrate. Biophys. J. 79, 144-152. doi: 10.1016/S0006-3495(00)76279-5
Moore, S. R., Saidel, G. M., Knothe, U., and Knothe Tate, M. L. (2014). Mechanistic, mathematical model to predict the dynamics of tissue genesis in bone defects via mechanical feedback and mediation of biochemical factors. PLoS Comput. Biol. 10:e1003604. doi: 10.1371/journal.pcbi.1003604
Nagel, T., and Kelly, D. J. (2010). Mechano-regulation of mesenchymal stem cell differentiation and collagen organisation during skeletal tissue repair. Biomech. Model. Mechanobiol. 9, 359-372. doi: 10.1007/s10237-009-0182-1
O'Reilly, A., Hankenson, K. D., Kelly, D. J. (2016). A computational model to explore the role of angiogenic impairment on endochondral ossification during fracture healing. Biomech. Model. Mechanobiol. 15, 1279-1294. doi: 10.1007/s10237-016-0759-4
Peiffer, V., Gerisch, A., Vandepitte, D., Van Oosterwyck, H., and Geris, L. (2011). A hybrid bioregulatory model of angiogenesis during bone fracture healing. Biomech. Model. Mechanobiol. 10, 383-395. doi: 10.1007/s10237-010-0241-7
Preininger, B., Checa, S., Molnar, F. L., Fratzl, P., Duda, G. N., and Raum, K. (2011). Spatial-temporal mapping of bone structural and elastic properties in a sheep model following osteotomy. Ultrasound Med. Biol. 37, 474-483. doi: 10.1016/j.ultrasmedbio.2010.12.007
Ribeiro, F. O., Gomez-Benito, M. J., Folgado, J., Fernandes, P. R., and Garcia-Aznar, J. (2015). In silico mechano-chemical model of bone healing for the regeneration of critical defects: the effect of BMP-2. PLoS ONE 10:e0127722. doi: 10.1371/journal.pone.0127722
Schell, H., Epari, D. R., Kassi, J. P., Bragulla, H., Bail, H. J., and Duda, G. N. (2005). The course of bone healing is influenced by the initial shear fixation stability. J. Orthop. Res. 23, 1022-1028. doi: 10.1016/j.orthres.2005.03.005
Schlundt, C., Schell, H., Goodman, S. B., Vunjak-Novakovic, G., Duda, G. N., and Schmidt-Bleek, K. (2015). Immune modulation as a therapeutic strategy in bone regeneration. J. Exp. Orthop. 2:1. doi: 10.1186/s40634-014-0017-6
Schmidt-Bleek, K., Petersen, A., Dienelt, A., Schwarz, C., and Duda, G. N. (2014). Initiation and early control of tissue regeneration-bone healing as a model system for tissue regeneration. Expert Opin. Biol. Ther. 14, 247-259. doi: 10.1517/14712598.2014.857653
Schmidt-Bleek, K., Willie, B. M., Schwabe, P., Seemann, P., and Duda, G. N. (2016). BMPs in bone regeneration: less is more effective, a paradigm-shift. Cytokine Growth Factor Rev. 27, 141-148. doi: 10.1016/j.cytogfr.2015.11.006
Secreto, F. J., Hoeppner, L. H., and Westendorf, J. J. (2009). Wnt signaling during fracture repair. Curr. Osteoporos. Rep. 7, 64-69. doi: 10.1007/s11914-009-0012-5
Shoham, N., and Gefen, A. (2012). Deformations, mechanical strains and stresses across the different hierarchical scales in weight-bearing soft tissues. J. Tissue Viabil. 21, 39-46. doi: 10.1016/j.jtv.2012.03.001
Simon, U., Augat, P., Utz, M., and Claes, L. (2011). A numerical model of the fracture healing process that describes tissue development and revascularisation. Comput. Methods Biomech. Biomed. Eng. 14, 79-93. doi: 10.1080/10255842.2010.499865
Steiner, M., Claes, L., Ignatius, A., Niemeyer, F., Simon, U., and Wehner, T. (2013). Prediction of fracture healing under axial loading, shear loading and bending is possible using distortional and dilatational strains as determining mechanical stimuli. J. R. Soc. Interface 10:20130389. doi: 10.1098/rsif.2013.0389
Strube, P., Sentuerk, U., Riha, T., Kaspar, K., Mueller, M., Kasper, G., et al. (2008). Influence of age and mechanical stability on bone defect healing: age reverses mechanical effects. Bone 42, 758-764. doi: 10.1016/j.bone.2007.12.223
Su, F. C., Wu, C. C., and Chien, S. (2011). Review: roles of microenvironment and mechanical forces in cell and tissue remodeling. J. Med. Biol. Eng. 31, 233-244. doi: 10.5405/jmbe.944
Vetter, A., Witt, F., Sander, O., Duda, G. N., and Weinkamer, R. (2012). The spatio-temporal arrangement of different tissues during bone healing as a result of simple mechanobiological rules. Biomech. Model. Mechanobiol. 11, 147-160. doi: 10.1007/s10237-011-0299-x
Waltemath, D., and Wolkenhauer, O. (2016). How modeling standards, software, and initiatives support reproducibility in systems biology and systems medicine. IEEE Trans. Biomed. Eng. 63, 1999-2006. doi: 10.1109/TBME.2016.2555481
Wehner, T., Claes, L., Niemeyer, F., Nolte, D., and Simon, U. (2010). Influence of the fixation stability on the healing time-a numerical study of a patient-specific fracture healing process. Clin. Biomech. 25, 606-612. doi: 10.1016/j.clinbiomech.2010.03.003
