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Sensitivity of tissue differentiation and bone healing predictions to tissue properties

Isaksson, Hanna LU orcid ; van Donkelaar, Corrinus C and Ito, Keita (2009) In Journal of Biomechanics 42(5). p.555-564
Abstract
Computational models are employed as tools to investigate possible mechano-regulation pathways for tissue differentiation and bone healing. However, current models do not account for the uncertainty in input parameters, and often include assumptions about parameter values that are not yet established. The aim was to clarify the importance of the assumed tissue material properties in a computational model of tissue differentiation during bone healing. An established mechano-biological model was employed together with a statistical approach. The model included an adaptive 2D finite element model of a fractured long bone. Four outcome criteria were quantified: (1) ability to predict sequential healing events, (2) amount of bone formation at... (More)
Computational models are employed as tools to investigate possible mechano-regulation pathways for tissue differentiation and bone healing. However, current models do not account for the uncertainty in input parameters, and often include assumptions about parameter values that are not yet established. The aim was to clarify the importance of the assumed tissue material properties in a computational model of tissue differentiation during bone healing. An established mechano-biological model was employed together with a statistical approach. The model included an adaptive 2D finite element model of a fractured long bone. Four outcome criteria were quantified: (1) ability to predict sequential healing events, (2) amount of bone formation at specific time points, (3) total time until healing, and (4) mechanical stability at specific time points. Statistical analysis based on fractional factorial designs first involved a screening experiment to identify the most significant tissue material properties. These seven properties were studied further with response surface methodology in a three-level Box–Behnken design. Generally, the sequential events were not significantly influenced by any properties, whereas rate-dependent outcome criteria and mechanical stability were significantly influenced by Young's modulus and permeability. Poisson's ratio and porosity had minor effects. The amount of bone formation at early, mid and late phases of healing, the time until complete healing and the mechanical stability were all mostly dependent on three material properties; permeability of granulation tissue, Young's modulus of cartilage and permeability of immature bone. The consistency between effects of the most influential parameters was high. To increase accuracy and predictive capacity of computational models of bone healing, the most influential tissue mechanical properties should be accurately quantified. (Less)
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author
; and
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Fracture healing, Mechanobiology, Material properties Fractional factorial design, Design of experiments, Orthogonal array
in
Journal of Biomechanics
volume
42
issue
5
pages
555 - 564
publisher
Elsevier
external identifiers
  • scopus:61849084684
ISSN
1873-2380
DOI
10.1016/j.jbiomech.2009.01.001
language
English
LU publication?
no
id
6b23d407-ac8f-4f5c-98c8-5dcb02851021 (old id 2275385)
date added to LUP
2016-04-04 13:23:02
date last changed
2023-09-20 16:57:42
@article{6b23d407-ac8f-4f5c-98c8-5dcb02851021,
  abstract     = {{Computational models are employed as tools to investigate possible mechano-regulation pathways for tissue differentiation and bone healing. However, current models do not account for the uncertainty in input parameters, and often include assumptions about parameter values that are not yet established. The aim was to clarify the importance of the assumed tissue material properties in a computational model of tissue differentiation during bone healing. An established mechano-biological model was employed together with a statistical approach. The model included an adaptive 2D finite element model of a fractured long bone. Four outcome criteria were quantified: (1) ability to predict sequential healing events, (2) amount of bone formation at specific time points, (3) total time until healing, and (4) mechanical stability at specific time points. Statistical analysis based on fractional factorial designs first involved a screening experiment to identify the most significant tissue material properties. These seven properties were studied further with response surface methodology in a three-level Box–Behnken design. Generally, the sequential events were not significantly influenced by any properties, whereas rate-dependent outcome criteria and mechanical stability were significantly influenced by Young's modulus and permeability. Poisson's ratio and porosity had minor effects. The amount of bone formation at early, mid and late phases of healing, the time until complete healing and the mechanical stability were all mostly dependent on three material properties; permeability of granulation tissue, Young's modulus of cartilage and permeability of immature bone. The consistency between effects of the most influential parameters was high. To increase accuracy and predictive capacity of computational models of bone healing, the most influential tissue mechanical properties should be accurately quantified.}},
  author       = {{Isaksson, Hanna and van Donkelaar, Corrinus C and Ito, Keita}},
  issn         = {{1873-2380}},
  keywords     = {{Fracture healing; Mechanobiology; Material properties Fractional factorial design; Design of experiments; Orthogonal array}},
  language     = {{eng}},
  number       = {{5}},
  pages        = {{555--564}},
  publisher    = {{Elsevier}},
  series       = {{Journal of Biomechanics}},
  title        = {{Sensitivity of tissue differentiation and bone healing predictions to tissue properties}},
  url          = {{http://dx.doi.org/10.1016/j.jbiomech.2009.01.001}},
  doi          = {{10.1016/j.jbiomech.2009.01.001}},
  volume       = {{42}},
  year         = {{2009}},
}