Biomedical Engineering Reference
In-Depth Information
spectrum of scientific areas—the focus shifts from parameter identification to
explanation. In essence, the modeller tries to ask the system of interest a specific
question and seeks to approach a possible answer by conducting in silico exper-
iments. In mechanobiology, where the central question is how cells and tissues
respond and adapt to mechanical forces, these simulations can provide a valuable
extension of classical experimental methods. Even under very defined and
simplified experimental conditions the inherent heterogeneity and adaptivity of
biological tissues presents a major hurdle in evaluating and quantifying the stimuli
and mechanisms responsible for an observed response. The role of computer
simulations in this quest has been defined by van der Meulen and Huiskes [ 111 ]as
follows:
''Computational mechanobiologists hypothesize a potential rule and determine if the
outcome of this hypothesis produces realistic tissue structures and morphologies, hence
trial-and-error. If the results correspond well, they might be an explanation for the
mechanism being modeled. This method of research is common practice and productive in
physics, less common in biology (Huiskes, 1995); although theoretical biology is based on
this type of approach.''
In other words, due to the complexity of mechanobiological systems simple
answers are often unlikely from experiments alone and alterations to the experi-
mental system tend to introduce other unknowns. In such cases, simulation
environments can help unravel part of the mysteries by approaching a problem in a
more systematic and quantitative way. For that purpose, computational engi-
neering methods have been introduced into the field and aim to tackle the multi-
physics problem by linking mechanics and various branches of biology.
As the opening quote stated and our short introduction outlined, the approaches,
intentions and philosophies behind theoretical models differ between the various
fields of science and engineering. In this review, we focus on hypothesis driven
simulations that try to explain certain experimental phenomena, the assumptions
made in them and the conceptual ideas relevant for the understanding of both their
potentials and limitations. For this reason we have excluded purely quantitative
analyses of biomechanical behaviour. For computer aided tissue engineering with
a focus on CAD, image processing and various computer aided scaffold manu-
facturing techniques we further refer the reader to the review articles by Sun et al.
[ 109 , 110 ]. Since the field of computational mechanobiology is growing rapidly
and the wealth of publications is significant, we narrowed our focus on studies that
have relevance to cartilage and bone tissue engineering applications. In particular,
our interest lies with the mechanoregulation of mesenchymal stem cell differen-
tiation and the incorporation of tissue architecture into simulations of tissue
engineering and regeneration. This chapter is organised into several sections that
are intended to highlight different conceptual modelling aspects relevant to tissue
engineering applications and as such are often very selective in the literature cited:
Section 2 introduces some examples of mechanobiological single cell models
and exemplary questions currently under investigation, namely the interaction
of cells with their substrate. This is done for the purpose of showing how
Search WWH ::




Custom Search