Computational Modeling of Bone-Implant Construct Osseointegration: Advantages and Shortcomings
Abstract
Background: Osseointegration (OI), the direct structural and functional connection between living bone and implants, remains poorly understood despite being critical for implant success. Current bone implant designs lack optimization due to limited understanding of the multifactorial mechanical, chemical, and biological processes which govern the OI process.
Methods: This systematic review analyzed studies published in English using numerical/mathematical methods to model OI. A PubMed search was conducted up to July 2025, and full-text articles were screened for keywords including "osseointegration," "healing," "bone generation," "computer simulations," "finite element models," and "mechanobiological model." The selected studies encompassed various species, tissue types, and computational procedures. Articles were categorized by modeling approach: mechanical, biological, and compound models.
Results: Seventeen articles met the inclusion criteria. Ten studies had employed mechanobiological algorithms simulating bone formation around implants, focusing on mechanical factors. Four studies had developed bioregulatory algorithms, targeting biological aspects. Three studies had created compound models integrating both mechanical and biological factors. Current models successfully predicted key mechanical influences but showed limitations in capturing complete biological complexity.
Conclusion: Mathematical models of OI face significant challenges in accurately considering both biological and mechanical factors simultaneously, often oversimplifying one aspect, while focusing on the other. Their key limitations include unrealistic boundary conditions, computational constraints, and incomplete understanding of biophysical signal translation. Moreover, most models rely on animal studies with interspecies differences and adapt bone healing algorithms rather than developing OI-specific approaches. Despite these challenges, mechanobiological models offer promising insights for optimizing implant design, though developing comprehensive models requires substantial experimental investment and computational resources.
1. Brånemark PI, Adell R, Albrektsson T, Lekholm U, Lundkvist S, Rockler B. Osseointegrated titanium fixtures in the treatment of edentulousness. Biomaterials. 1983;4(1):25-8. doi: 10.1016/0142-9612(83)90065-0. [PubMed: 6838955].
2. Pandey C, Rokaya D, Bhattarai BP. Contemporary Concepts in Osseointegration of Dental Implants: A Review. Biomed Res Int. 2022;2022:6170452. doi: 10.1155/2022/6170452. [PubMed: 35747499]. [PubMed Central: PMC9213185].
3. Abrahamsson I, Carcuac O, Berglundh T. Influence of implant geometry and osteotomy design on early bone healing: A pre- clinical in vivo study. Clin Oral Implants Res. 2021;32(10):1190-9. doi: 10.1111/clr.13816. [PubMed: 34352142].
4. Geris L, Gerisch A, Sloten JV, Weiner R, Oosterwyck HV. Angiogenesis in bone fracture healing: a bioregulatory model. J Theor Biol. 2008;251(1):137-58. doi: 10.1016/j.jtbi.2007.11.008. [PubMed: 18155732].
5. Mirzaie T, Rouhi G, Mehdi Dehghan M, Farzad-Mohajeri S, Barikani H. Dental implants' stability dependence on rotational speed and feed-rate of drilling: In-vivo and ex-vivo investigations. J Biomech. 2021;127:110696. doi: 10.1016/j.jbiomech.2021.110696. [PubMed: 34419826].
6. Mavrogenis AF, Dimitriou R, Parvizi J, Babis GC. Biology of implant osseointegration. J Musculoskelet Neuronal Interact. 2009;9(2):61-71. [PubMed: 19516081].
7. Sasaki K, Suzuki O, Takahashi N, Editors. Interface Oral Health Science 2016. Singapore: Springer Singapore; 2017.
8. Bailón-Plaza A, Van Der Meulen MC. A mathematical framework to study the effects of growth factor influences on fracture healing. J Theor Biol. 2001;212(2):191-209. doi: 10.1006/jtbi.2001.2372. [PubMed: 11531385].
9. Davies JE. Understanding peri-implant endosseous healing. J Dent Educ. 2003;67(8):932-49. [PubMed: 12959168].
10. Kondo T, Yamada M, Egusa H. Innate immune regulation in dental implant osseointegration. J Prosthodont Res. 2024;68(4):511-21. doi: 10.2186/jpr.JPR_D_23_00198. [PubMed: 38346728].
11. Soto-Peñaloza D, Martín-de-Llano JJ, Carda-Batalla C, Peñarrocha-Diago M, Peñarrocha-Oltra D. Basic Bone Biology Healing During Osseointegration of Titanium Dental Implants. In: Peñarrocha-Diago M, Covani U, Cuadrado L, Editors. Atlas of Immediate Dental Implant Loading. Cham, Switzerland: Springer International Publishing; 2019. p. 17-28.
12. Salvi GE, Bosshardt DD, Lang NP, Abrahamsson I, Berglundh T, Lindhe J, et al. Temporal sequence of hard and soft tissue healing around titanium dental implants. Periodontol 2000. 2015;68(1):135-52. doi: 10.1111/prd.12054. [PubMed: 25867984].
13. García-Aznar JM, Nasello G, Hervas-Raluy S, Pérez M, Gómez- Benito MJ. Multiscale modeling of bone tissue mechanobiology. Bone. 2021;151:116032. doi: 10.1016/j.bone.2021.116032. [PubMed: 34118446].
14. Overmann AL, Forsberg JA. The state of the art of osseointegration for limb prosthesis. Biomed Eng Lett. 2020;10(1):5-16. doi: 10.1007/s13534-019-00133-9. [PubMed: 32175127]. [PubMed Central: PMC7046912].
15. Hoellwarth JS, Tetsworth K, Rozbruch SR, Handal MB, Coughlan A, Al Muderis M. Osseointegration for amputees: current implants, techniques, and future directions. JBJS Rev. 2020;8(3):e0043. doi: 10.2106/jbjs.Rvw.19.00043. [PubMed: 32224634]. [PubMed Central: PMC7161721].
16. Mohandes Y, Tahani M, Rouhi G, Tahami M. A mechanobiological approach to find the optimal thickness for the locking compression plate: Finite element investigations. Proc Inst Mech Eng H. 2021;235(4):408-18. doi: 10.1177/0954411920985757. [PubMed: 33427059].
17. Colnot C, Romero DM, Huang S, Rahman J, Currey JA, Nanci A, et al. Molecular analysis of healing at a bone-implant interface. J Dent Res. 2007;86(9):862-7. doi: 10.1177/154405910708600911. [PubMed: 17720856].
18. Rea M, Botticelli D, Ricci S, Soldini C, González GG, Lang NP. Influence of immediate loading on healing of implants installed with different insertion torques--an experimental study in dogs. Clin Oral Implants Res. 2015;26(1):90-5. doi: 10.1111/clr.12305. [PubMed: 24313303].
19. Prendergast PJ, Huiskes R, Søballe K. ESB Research Award 1996.
Biophysical stimuli on cells during tissue differentiation at implant interfaces. J Biomech. 1997;30(6):539-48. doi: 10.1016/s0021-9290(96)00140-6. [PubMed: 9165386].
20. Chou HY, Müftü S. Simulation of peri-implant bone healing due to immediate loading in dental implant treatments. J Biomech. 2013;46(5):871-8. doi: 10.1016/j.jbiomech.2012.12.023. [PubMed: 23351367].
21. Irandoust S, Müftü S. The interplay between bone healing and remodeling around dental implants. Sci Rep. 2020;10(1):4335. doi: 10.1038/s41598-020-60735-7. [PubMed: 32152332]. [PubMed Central: PMC7063044].
22. Geris L, Andreykiv A, Van Oosterwyck H, Sloten JV, Van Keulen F, Duyck J, et al. Numerical simulation of tissue differentiation around loaded titanium implants in a bone chamber. J Biomech. 2004;37(5):763-9. doi: 10.1016/j.jbiomech.2003.09.026. [PubMed: 15047006].
23. Claes LE, Heigele CA. Magnitudes of local stress and strain along bony surfaces predict the course and type of fracture healing. J Biomech. 1999;32(3):255-66. doi: 10.1016/s0021- 9290(98)00153-5. [PubMed: 10093025].
24. Andreykiv A, Prendergast PJ, van Keulen F, Swieszkowski W, Rozing PM. Bone ingrowth simulation for a concept glenoid component design. J Biomech. 2005;38(5):1023-33. doi: 10.1016/j.jbiomech.2004.05.044. [PubMed: 15797584].
25. Geris L, Van Oosterwyck H, Vander Sloten J, Duyck J, Naert I. Assessment of mechanobiological models for the numerical simulation of tissue differentiation around immediately loaded implants. Comput Methods Biomech Biomed Engin. 2003;6(5-6):277-88. doi: 10.1080/10255840310001634412. [PubMed: 14675948].
26. Liu X, Niebur GL. Bone ingrowth into a porous coated implant predicted by a mechano-regulatory tissue differentiation algorithm. Biomech Model Mechanobiol. 2008;7(4):335-44. doi: 10.1007/s10237-007-0100-3. [PubMed: 17701434].
27. Babayi M, Ashtiani MN, Emamian A, Ramezanpour H, Yousefi H, Mahdavi M. Peri-implant cell differentiation in delayed and immediately-loaded dental implant: A mechanobiological simulation. Arch Oral Biol. 2023;151:105702. doi: 10.1016/j.archoralbio.2023.105702. [PubMed: 37086495].
28. Moreo P, Pérez MA, García-Aznar JM, Doblaré M. Modelling the mechanical behaviour of living bony interfaces. Comput Methods Appl Mech Eng. 2007;196(35):3300-14. doi: 10.1016/j.cma.2007.03.020.
29. Ambard D, Swider P. A predictive mechano-biological model of the bone-implant healing. Eur J Mech A/Solids. 2006;25(6): 927-37. doi: 10.1016/j.euromechsol.2006.02.006.
30. Amor N, Geris L, Vander Sloten J, Van Oosterwyck H. Modelling the early phases of bone regeneration around an endosseous oral implant. Comput Methods Biomech Biomed Engin. 2009;12(4):459-68. doi: 10.1080/10255840802687392. [PubMed: 19199168].
31. Amor N, Geris L, Vander Sloten J, Van Oosterwyck H. Computational modelling of biomaterial surface interactions with blood platelets and osteoblastic cells for the prediction of contact osteogenesis. Acta Biomater. 2011;7(2):779-90. doi: 10.1016/j.actbio.2010.09.025. [PubMed: 20883839].
32. Moreo P, García-Aznar JM, Doblaré M. Bone ingrowth on the surface of endosseous implants. Part 1: Mathematical model. J Theor Biol. 2009;260(1):1-12. doi: 10.1016/j.jtbi.2008.07.040. [PubMed: 18762197].
33. Vanegas-Acosta JC, Landinez PN, Garzón-Alvarado DA, Casale RM. A finite element method approach for the mechanobiological modeling of the osseointegration of a dental implant. Comput Methods Programs Biomed. 2011;101(3):297-314. doi: 10.1016/j.cmpb.2010.11.007. [PubMed: 21183241].
34. Prokharau PA, Vermolen FJ, García-Aznar JM. A mathematical model for cell differentiation, as an evolutionary and regulated process. Comput Methods Biomech Biomed Engin. 2014;17(10):1051-70. doi: 10.1080/10255842.2012.736503. [PubMed: 23113617].
35. Prokharau PA, Vermolen FJ, García-Aznar JM. Model for direct bone apposition on pre-existing surfaces, during peri-implant osseointegration. J Theor Biol. 2012;304:131-42. doi: 10.1016/j.jtbi.2012.03.025. [PubMed: 22554950].
36. Lacroix D, Prendergast PJ. A mechano-regulation model for tissue differentiation during fracture healing: analysis of gap size and loading. J Biomech. 2002;35(9):1163-71. doi: 10.1016/s0021-9290(02)00086-6. [PubMed: 12163306].
37. Haase K, Rouhi G. Prediction of stress shielding around an orthopedic screw: using stress and strain energy density as mechanical stimuli. Comput Biol Med. 2013;43(11):1748-57. doi: 10.1016/j.compbiomed.2013.07.032. [PubMed: 24209921].
38. Vahdati A, Rouhi G. A model for mechanical adaptation of trabecular bone incorporating cellular accommodation and effects of microdamage and disuse. Mech Res Commun. 2009;36(3):284-93. doi: 10.1016/j.mechrescom.2008.10.004.
39. Rouhi G, Epstein M, Sudak L, Herzog W. Free surface density and microdamage in the bone remodeling equation: Theoretical considerations. Int J Eng Sci. 2006;44(7):456-69. doi: 10.1016/j.ijengsci.2006.02.001.
40. Chou H-Y, Müftü S. Corrigendum to “Simulation of peri- implant bone healing due to immediate loading in dental implant treatments” [J. Biomech. 46/5 (2013) 871–878]. J Biomech. 2016;49(9):2000-5. doi: 10.1016/j.jbiomech.2016.04.014.
41. Moreo P, García-Aznar JM, Doblaré M. Bone ingrowth on the surface of endosseous implants. Part 2: Theoretical and numerical analysis. J Theor Biol. 2009;260(1):13-26. doi: 10.1016/j.jtbi.2009.05.036. [PubMed: 19524597].
42. Roeder I, Loeffler M. A novel dynamic model of hematopoietic stem cell organization based on the concept of within-tissue plasticity. Exp Hematol. 2002;30(8):853-61. doi: 10.1016/s0301-472x(02)00832-9. [PubMed: 12160836].
43. Dorogoy A, Rittel D, Shemtov-Yona K, Korabi R. Modeling dental implant insertion. J Mech Behav Biomed Mater. 2017;68:42-50. doi: 10.1016/j.jmbbm.2017.01.021. [PubMed: 28142072].
44. Christen P, Ito K, Ellouz R, Boutroy S, Sornay-Rendu E, Chapurlat RD, et al. Bone remodelling in humans is load- driven but not lazy. Nat Commun. 2014;5:4855. doi: 10.1038/ncomms5855. [PubMed: 25209333].
45. Roberts WE. Bone tissue interface. J Dent Educ. 1988;52(12): 804-9. [PubMed: 3057027].
46. Prados-Privado M, Martínez-Martínez C, Gehrke SA, Prados- Frutos JC. Influence of bone definition and finite element parameters in bone and dental implants stress: A Literature Review. Biology (Basel). 2020;9(8):224. doi: 10.3390/biology9080224. [PubMed: 32823884]. [PubMed Central: PMC7464638].
47. Isaksson H, Van Donkelaar CC, Huiskes R, Ito K. A mechano- regulatory bone-healing model incorporating cell-phenotype specific activity. J Theor Biol. 2008;252(2):230-46. doi: 10.1016/j.jtbi.2008.01.030. [PubMed: 18353374].
48. Jacobs CR, Kelly DJ. Cell mechanics: The role of simulation. In: Fernandes PR, Bártolo PJ, Editors. Advances on Modeling in Tissue Engineering. Dordrecht, Netherlands: Springer Netherlands; 2011. p. 1-14.
2. Pandey C, Rokaya D, Bhattarai BP. Contemporary Concepts in Osseointegration of Dental Implants: A Review. Biomed Res Int. 2022;2022:6170452. doi: 10.1155/2022/6170452. [PubMed: 35747499]. [PubMed Central: PMC9213185].
3. Abrahamsson I, Carcuac O, Berglundh T. Influence of implant geometry and osteotomy design on early bone healing: A pre- clinical in vivo study. Clin Oral Implants Res. 2021;32(10):1190-9. doi: 10.1111/clr.13816. [PubMed: 34352142].
4. Geris L, Gerisch A, Sloten JV, Weiner R, Oosterwyck HV. Angiogenesis in bone fracture healing: a bioregulatory model. J Theor Biol. 2008;251(1):137-58. doi: 10.1016/j.jtbi.2007.11.008. [PubMed: 18155732].
5. Mirzaie T, Rouhi G, Mehdi Dehghan M, Farzad-Mohajeri S, Barikani H. Dental implants' stability dependence on rotational speed and feed-rate of drilling: In-vivo and ex-vivo investigations. J Biomech. 2021;127:110696. doi: 10.1016/j.jbiomech.2021.110696. [PubMed: 34419826].
6. Mavrogenis AF, Dimitriou R, Parvizi J, Babis GC. Biology of implant osseointegration. J Musculoskelet Neuronal Interact. 2009;9(2):61-71. [PubMed: 19516081].
7. Sasaki K, Suzuki O, Takahashi N, Editors. Interface Oral Health Science 2016. Singapore: Springer Singapore; 2017.
8. Bailón-Plaza A, Van Der Meulen MC. A mathematical framework to study the effects of growth factor influences on fracture healing. J Theor Biol. 2001;212(2):191-209. doi: 10.1006/jtbi.2001.2372. [PubMed: 11531385].
9. Davies JE. Understanding peri-implant endosseous healing. J Dent Educ. 2003;67(8):932-49. [PubMed: 12959168].
10. Kondo T, Yamada M, Egusa H. Innate immune regulation in dental implant osseointegration. J Prosthodont Res. 2024;68(4):511-21. doi: 10.2186/jpr.JPR_D_23_00198. [PubMed: 38346728].
11. Soto-Peñaloza D, Martín-de-Llano JJ, Carda-Batalla C, Peñarrocha-Diago M, Peñarrocha-Oltra D. Basic Bone Biology Healing During Osseointegration of Titanium Dental Implants. In: Peñarrocha-Diago M, Covani U, Cuadrado L, Editors. Atlas of Immediate Dental Implant Loading. Cham, Switzerland: Springer International Publishing; 2019. p. 17-28.
12. Salvi GE, Bosshardt DD, Lang NP, Abrahamsson I, Berglundh T, Lindhe J, et al. Temporal sequence of hard and soft tissue healing around titanium dental implants. Periodontol 2000. 2015;68(1):135-52. doi: 10.1111/prd.12054. [PubMed: 25867984].
13. García-Aznar JM, Nasello G, Hervas-Raluy S, Pérez M, Gómez- Benito MJ. Multiscale modeling of bone tissue mechanobiology. Bone. 2021;151:116032. doi: 10.1016/j.bone.2021.116032. [PubMed: 34118446].
14. Overmann AL, Forsberg JA. The state of the art of osseointegration for limb prosthesis. Biomed Eng Lett. 2020;10(1):5-16. doi: 10.1007/s13534-019-00133-9. [PubMed: 32175127]. [PubMed Central: PMC7046912].
15. Hoellwarth JS, Tetsworth K, Rozbruch SR, Handal MB, Coughlan A, Al Muderis M. Osseointegration for amputees: current implants, techniques, and future directions. JBJS Rev. 2020;8(3):e0043. doi: 10.2106/jbjs.Rvw.19.00043. [PubMed: 32224634]. [PubMed Central: PMC7161721].
16. Mohandes Y, Tahani M, Rouhi G, Tahami M. A mechanobiological approach to find the optimal thickness for the locking compression plate: Finite element investigations. Proc Inst Mech Eng H. 2021;235(4):408-18. doi: 10.1177/0954411920985757. [PubMed: 33427059].
17. Colnot C, Romero DM, Huang S, Rahman J, Currey JA, Nanci A, et al. Molecular analysis of healing at a bone-implant interface. J Dent Res. 2007;86(9):862-7. doi: 10.1177/154405910708600911. [PubMed: 17720856].
18. Rea M, Botticelli D, Ricci S, Soldini C, González GG, Lang NP. Influence of immediate loading on healing of implants installed with different insertion torques--an experimental study in dogs. Clin Oral Implants Res. 2015;26(1):90-5. doi: 10.1111/clr.12305. [PubMed: 24313303].
19. Prendergast PJ, Huiskes R, Søballe K. ESB Research Award 1996.
Biophysical stimuli on cells during tissue differentiation at implant interfaces. J Biomech. 1997;30(6):539-48. doi: 10.1016/s0021-9290(96)00140-6. [PubMed: 9165386].
20. Chou HY, Müftü S. Simulation of peri-implant bone healing due to immediate loading in dental implant treatments. J Biomech. 2013;46(5):871-8. doi: 10.1016/j.jbiomech.2012.12.023. [PubMed: 23351367].
21. Irandoust S, Müftü S. The interplay between bone healing and remodeling around dental implants. Sci Rep. 2020;10(1):4335. doi: 10.1038/s41598-020-60735-7. [PubMed: 32152332]. [PubMed Central: PMC7063044].
22. Geris L, Andreykiv A, Van Oosterwyck H, Sloten JV, Van Keulen F, Duyck J, et al. Numerical simulation of tissue differentiation around loaded titanium implants in a bone chamber. J Biomech. 2004;37(5):763-9. doi: 10.1016/j.jbiomech.2003.09.026. [PubMed: 15047006].
23. Claes LE, Heigele CA. Magnitudes of local stress and strain along bony surfaces predict the course and type of fracture healing. J Biomech. 1999;32(3):255-66. doi: 10.1016/s0021- 9290(98)00153-5. [PubMed: 10093025].
24. Andreykiv A, Prendergast PJ, van Keulen F, Swieszkowski W, Rozing PM. Bone ingrowth simulation for a concept glenoid component design. J Biomech. 2005;38(5):1023-33. doi: 10.1016/j.jbiomech.2004.05.044. [PubMed: 15797584].
25. Geris L, Van Oosterwyck H, Vander Sloten J, Duyck J, Naert I. Assessment of mechanobiological models for the numerical simulation of tissue differentiation around immediately loaded implants. Comput Methods Biomech Biomed Engin. 2003;6(5-6):277-88. doi: 10.1080/10255840310001634412. [PubMed: 14675948].
26. Liu X, Niebur GL. Bone ingrowth into a porous coated implant predicted by a mechano-regulatory tissue differentiation algorithm. Biomech Model Mechanobiol. 2008;7(4):335-44. doi: 10.1007/s10237-007-0100-3. [PubMed: 17701434].
27. Babayi M, Ashtiani MN, Emamian A, Ramezanpour H, Yousefi H, Mahdavi M. Peri-implant cell differentiation in delayed and immediately-loaded dental implant: A mechanobiological simulation. Arch Oral Biol. 2023;151:105702. doi: 10.1016/j.archoralbio.2023.105702. [PubMed: 37086495].
28. Moreo P, Pérez MA, García-Aznar JM, Doblaré M. Modelling the mechanical behaviour of living bony interfaces. Comput Methods Appl Mech Eng. 2007;196(35):3300-14. doi: 10.1016/j.cma.2007.03.020.
29. Ambard D, Swider P. A predictive mechano-biological model of the bone-implant healing. Eur J Mech A/Solids. 2006;25(6): 927-37. doi: 10.1016/j.euromechsol.2006.02.006.
30. Amor N, Geris L, Vander Sloten J, Van Oosterwyck H. Modelling the early phases of bone regeneration around an endosseous oral implant. Comput Methods Biomech Biomed Engin. 2009;12(4):459-68. doi: 10.1080/10255840802687392. [PubMed: 19199168].
31. Amor N, Geris L, Vander Sloten J, Van Oosterwyck H. Computational modelling of biomaterial surface interactions with blood platelets and osteoblastic cells for the prediction of contact osteogenesis. Acta Biomater. 2011;7(2):779-90. doi: 10.1016/j.actbio.2010.09.025. [PubMed: 20883839].
32. Moreo P, García-Aznar JM, Doblaré M. Bone ingrowth on the surface of endosseous implants. Part 1: Mathematical model. J Theor Biol. 2009;260(1):1-12. doi: 10.1016/j.jtbi.2008.07.040. [PubMed: 18762197].
33. Vanegas-Acosta JC, Landinez PN, Garzón-Alvarado DA, Casale RM. A finite element method approach for the mechanobiological modeling of the osseointegration of a dental implant. Comput Methods Programs Biomed. 2011;101(3):297-314. doi: 10.1016/j.cmpb.2010.11.007. [PubMed: 21183241].
34. Prokharau PA, Vermolen FJ, García-Aznar JM. A mathematical model for cell differentiation, as an evolutionary and regulated process. Comput Methods Biomech Biomed Engin. 2014;17(10):1051-70. doi: 10.1080/10255842.2012.736503. [PubMed: 23113617].
35. Prokharau PA, Vermolen FJ, García-Aznar JM. Model for direct bone apposition on pre-existing surfaces, during peri-implant osseointegration. J Theor Biol. 2012;304:131-42. doi: 10.1016/j.jtbi.2012.03.025. [PubMed: 22554950].
36. Lacroix D, Prendergast PJ. A mechano-regulation model for tissue differentiation during fracture healing: analysis of gap size and loading. J Biomech. 2002;35(9):1163-71. doi: 10.1016/s0021-9290(02)00086-6. [PubMed: 12163306].
37. Haase K, Rouhi G. Prediction of stress shielding around an orthopedic screw: using stress and strain energy density as mechanical stimuli. Comput Biol Med. 2013;43(11):1748-57. doi: 10.1016/j.compbiomed.2013.07.032. [PubMed: 24209921].
38. Vahdati A, Rouhi G. A model for mechanical adaptation of trabecular bone incorporating cellular accommodation and effects of microdamage and disuse. Mech Res Commun. 2009;36(3):284-93. doi: 10.1016/j.mechrescom.2008.10.004.
39. Rouhi G, Epstein M, Sudak L, Herzog W. Free surface density and microdamage in the bone remodeling equation: Theoretical considerations. Int J Eng Sci. 2006;44(7):456-69. doi: 10.1016/j.ijengsci.2006.02.001.
40. Chou H-Y, Müftü S. Corrigendum to “Simulation of peri- implant bone healing due to immediate loading in dental implant treatments” [J. Biomech. 46/5 (2013) 871–878]. J Biomech. 2016;49(9):2000-5. doi: 10.1016/j.jbiomech.2016.04.014.
41. Moreo P, García-Aznar JM, Doblaré M. Bone ingrowth on the surface of endosseous implants. Part 2: Theoretical and numerical analysis. J Theor Biol. 2009;260(1):13-26. doi: 10.1016/j.jtbi.2009.05.036. [PubMed: 19524597].
42. Roeder I, Loeffler M. A novel dynamic model of hematopoietic stem cell organization based on the concept of within-tissue plasticity. Exp Hematol. 2002;30(8):853-61. doi: 10.1016/s0301-472x(02)00832-9. [PubMed: 12160836].
43. Dorogoy A, Rittel D, Shemtov-Yona K, Korabi R. Modeling dental implant insertion. J Mech Behav Biomed Mater. 2017;68:42-50. doi: 10.1016/j.jmbbm.2017.01.021. [PubMed: 28142072].
44. Christen P, Ito K, Ellouz R, Boutroy S, Sornay-Rendu E, Chapurlat RD, et al. Bone remodelling in humans is load- driven but not lazy. Nat Commun. 2014;5:4855. doi: 10.1038/ncomms5855. [PubMed: 25209333].
45. Roberts WE. Bone tissue interface. J Dent Educ. 1988;52(12): 804-9. [PubMed: 3057027].
46. Prados-Privado M, Martínez-Martínez C, Gehrke SA, Prados- Frutos JC. Influence of bone definition and finite element parameters in bone and dental implants stress: A Literature Review. Biology (Basel). 2020;9(8):224. doi: 10.3390/biology9080224. [PubMed: 32823884]. [PubMed Central: PMC7464638].
47. Isaksson H, Van Donkelaar CC, Huiskes R, Ito K. A mechano- regulatory bone-healing model incorporating cell-phenotype specific activity. J Theor Biol. 2008;252(2):230-46. doi: 10.1016/j.jtbi.2008.01.030. [PubMed: 18353374].
48. Jacobs CR, Kelly DJ. Cell mechanics: The role of simulation. In: Fernandes PR, Bártolo PJ, Editors. Advances on Modeling in Tissue Engineering. Dordrecht, Netherlands: Springer Netherlands; 2011. p. 1-14.
| Files | ||
| Issue | Vol 12 No 1 (2026) | |
| Section | Research Articles | |
| Keywords | ||
| Osseointegration Prostheses and Implants Bone-Implant Interface Fracture Healing Computer Simulation Finite Element Analysis | ||
| Rights and permissions | |
|
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
How to Cite
1.
Rezvanifar Y, Najafi Ashtiani M, Rouhi G. Computational Modeling of Bone-Implant Construct Osseointegration: Advantages and Shortcomings. J Orthop Spine Trauma. 2026;12(1):29-36.
