Abstract
The development of predictive mathematical models can contribute to a deeper understanding of the specific stages of bone mechanobiology and the process by which bone adapts to mechanical forces. The objective of this work was to predict, with spatial accuracy, cortical bone adaptation to mechanical load, in order to better understand the mechanical cues that might be driving adaptation. The axial tibial loading model was used to trigger cortical bone adaptation in C57BL/6 mice and provide relevant biological and biomechanical information. A method for mapping cortical thickness in the mouse tibia diaphysis was developed, allowing for a thorough spatial description of where bone adaptation occurs. Poroelastic finite-element (FE) models were used to determine the structural response of the tibia upon axial loading and interstitial fluid velocity as the mechanical stimulus. FE models were coupled with mechanobiological governing equations, which accounted for non-static loads and assumed that bone responds instantly to local mechanical cues in an on–off manner. The presented formulation was able to simulate the areas of adaptation and accurately reproduce the distributions of cortical thickening observed in the experimental data with a statistically significant positive correlation (Kendall's τ rank coefficient τ = 0.51, p < 0.001). This work demonstrates that computational models can spatially predict cortical bone mechanoadaptation to a time variant stimulus. Such models could be used in the design of more efficient loading protocols and drug therapies that target the relevant physiological mechanisms.
Highlights
Bone is a dynamic tissue, responding to changes in mechanical demands by adapting its shape and material properties
The mechanostat hypothesis by Frost [1] relies upon a quantitatively matched adaptive response of bone as a function of loading, considering that there are mechanical stimulus thresholds at which bone tissue responds. This conceptual model delineates the foundations of most of the mathematical models developed to simulate bone adaptation [5,6,7,8,9,10,11,12,13]. Such predictive mathematical models usually rely on numerical methods, namely finite-element analysis (FEA), to calculate mechanical fields in bone that result from external loading
We modelled permeability through the periosteal and endosteal membranes by including a layer of poroelastic elements, similar to Steck et al [32], and considered each surface to have an isotropic permeability of k 1⁄4 10217 m2 [36]
Summary
Bone is a dynamic tissue, responding to changes in mechanical demands by adapting its shape and material properties. The mechanostat hypothesis by Frost [1] relies upon a quantitatively matched adaptive response of bone as a function of loading, considering that there are mechanical stimulus thresholds at which bone tissue responds This conceptual model delineates the foundations of most of the mathematical models developed to simulate bone adaptation [5,6,7,8,9,10,11,12,13]. Such predictive mathematical models usually rely on numerical methods, namely finite-element analysis (FEA), to calculate mechanical fields in bone that result from external loading. These help to find correlations between the mechanical environment and biological response
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have