Literature DB >> 27255452

Mechanobiological simulations of peri-acetabular bone ingrowth: a comparative analysis of cell-phenotype specific and phenomenological algorithms.

Kaushik Mukherjee1, Sanjay Gupta2.   

Abstract

Several mechanobiology algorithms have been employed to simulate bone ingrowth around porous coated implants. However, there is a scarcity of quantitative comparison between the efficacies of commonly used mechanoregulatory algorithms. The objectives of this study are: (1) to predict peri-acetabular bone ingrowth using cell-phenotype specific algorithm and to compare these predictions with those obtained using phenomenological algorithm and (2) to investigate the influences of cellular parameters on bone ingrowth. The variation in host bone material property and interfacial micromotion of the implanted pelvis were mapped onto the microscale model of implant-bone interface. An overall variation of 17-88 % in peri-acetabular bone ingrowth was observed. Despite differences in predicted tissue differentiation patterns during the initial period, both the algorithms predicted similar spatial distribution of neo-tissue layer, after attainment of equilibrium. Results indicated that phenomenological algorithm, being computationally faster than the cell-phenotype specific algorithm, might be used to predict peri-prosthetic bone ingrowth. The cell-phenotype specific algorithm, however, was found to be useful in numerically investigating the influence of alterations in cellular activities on bone ingrowth, owing to biologically related factors. Amongst the host of cellular activities, matrix production rate of bone tissue was found to have predominant influence on peri-acetabular bone ingrowth.

Keywords:  Finite element analysis; Implant–bone interface modelling; Mechanical stimuli; Mechanoregulatory algorithms; Micromotion

Mesh:

Year:  2016        PMID: 27255452     DOI: 10.1007/s11517-016-1528-3

Source DB:  PubMed          Journal:  Med Biol Eng Comput        ISSN: 0140-0118            Impact factor:   2.602


  51 in total

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Journal:  J Biomech       Date:  2011-03-05       Impact factor: 2.712

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Journal:  Biomech Model Mechanobiol       Date:  2007-10-31

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10.  Determining the most important cellular characteristics for fracture healing using design of experiments methods.

Authors:  Hanna Isaksson; Corrinus C van Donkelaar; Rik Huiskes; Jiang Yao; Keita Ito
Journal:  J Theor Biol       Date:  2008-08-03       Impact factor: 2.691

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