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

Journal of Theoretical Biology
Hanna IsakssonKeita Ito

Abstract

Computational models are employed as tools to investigate possible mechanoregulation 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 objective of this study was to determine the most important cellular characteristics of a mechanoregulatory model describing both cell phenotype-specific and mechanobiological processes that are active during bone healing using a statistical approach. The computational model included an adaptive two-dimensional finite element model of a fractured long bone. Three different outcome criteria were quantified: (1) ability to predict sequential healing events, (2) amount of bone formation at early, mid and late stages of healing and (3) the total time until complete healing. For the statistical analysis, first a resolution IV fractional factorial design (L(64)) was used to identify the most significant factors. Thereafter, a three-level Taguchi orthogonal array (L(27)) was employed to study the curvature (non-linearity) of the 10 identified most important parameters. The results show that the ability of the model to predict the sequ...Continue Reading

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