NUI Galway – UL Alliance First Annual ENGINEERING AND - ARAN ...

Multi-Scale Computational Modelling of
Physiological Loading on Bone Cells
Verbruggen, S., McNamara, L.M.
Department of Mechanical & Biomedical Engineering, NUI, Galway, Ireland
email: s.verbruggen1@nuigalway.ie
Abstract
Bone is an adaptive material that can alter its structure
in response to changes in the mechanical environment.
It is possible to enhance bone regeneration in vitro by
manipulating the mechanical environment. However the
mechanical environment necessary to regulate bone
growth is not fully understood. The objective of this
research is to use computational methods to predict the
mechanical micro-environment of bone cells in healthy,
structured bone and thereby inform tissue regeneration
approaches that can mimic the native mechanical
environment to optimise bone regeneration in vitro..
1. Introduction
Bone is an adaptive material, which is particularly
responsive to mechanical loading. [1] Mechanobiology
refers to the ability of biological cells to sense and
respond to extracellular mechanical stimuli. It is
believed that the pathogenesis of diseases such as
osteoporosis, arthritis and diabetes may be correlated to
the mechanobiology of bone cells. [2] Additionally it has
been demonstrated that it is possible to manipulate
cellular responses using mechanical loading regimes,
with such advances paving the way for developing
clinical treatments to address many diseases. [3] However
the precise mechanical environment that regulates
normal bone growth in the body are not fully
understood, because experimental studies to quantify
this are unfeasible.
2. Materials and Methods
Computational models were generated using
ABAQUS® finite element software, with three
complimentary levels of analysis of stimuli in vivo:
Organ-Level: The geometry was generated from CT
(256µm resolution) scans of a femur bone, with material
properties obtained from literature (E=17GPa,
ν=0.38). [3] Loading conditions were applied at the
femoral head, imitating forces generated during normal
walking. The bone was constrained at the distal end.
Tissue-Level: A trabecular and cortical bone tissue
model was generated from µCT (5µm resolution) scans
of a tibia bone using a custom-designed voxel-meshing
software (FEEBE) [4] developed at NUIG. The material
properties and mechanical loading was defined from the
organ-level model to simulate stress during normal
walking.
Cellular-Level: An idealised geometry of the lacunarcanalicular
system was generated, with mechanical
loading defined from the tissue-level to represent stress
and strain in the bone matrix surrounding the bone cell.
A model of the osteocyte cell membrane (E=100kPa,
67
ν=0.5) [5] and the surrounding interstitial matrix has also
been developed, allowing the mechanical stimulation of
the cell by its environment to be quantified.
3. Preliminary Results
A preliminary computational analysis of
mechanical loading has been carried out using a multiscale
approach (see Figure 1) to explore the boundary
conditions at the cellular level using homogenised
loading from higher levels. We have been able to
calculate the loading conditions from the organ scale, to
define the conditions at the tissue and cellular level.
ORGAN
TISSUE
CELL
Figure 1: Multi-scale computational models of bone, at organlevel,
tissue-level & cellular level respectively
4. Discussion and Future Work
Multi-scale modelling allows homogenisation
between different length scales, and this approach
allows us to converge on physiological loading at the
cellular level, based on organ-level loading experienced
by a femur bone. Future studies will incorporate
confocal microscopy scans and TEM images to generate
more accurate FE models at the cellular-level. These
models will include the cell membrane and the
cytoskeleton, as these are crucial for accurate
understanding of cell mechanics in vitro. These models
will allow us to predict the mechanical environment
surrounding osteocyte cells in vivo. Using the
information derived from these studies tissue
differentiation algorithms will be developed to predict
bone formation on tissue engineering scaffolds in
response to various regimes of mechanical stimulation.
5. References
[1] Jan-Hung, C. et al., J Biomech 43:108-118, 2010
[2] Martin, I., et al., J Biomech 40:750-765, 2007
[3] McMahon, L.A. et al., Ann. Biomed. Eng. 36:185, 2008
[4]Harrison, N.M. et al., J Biomech, 41:2589-2596, 2008
[5]Sugitate T. et al., Curr. App. Phys., 9:e291-293, 2009