Abstract
A dynamic model regulated by both biphasic poroelastic finite element analysis and fuzzy logic control was established. Fuzzy logic control was an easy and comprehensive way to simulate the tissue differentiation process, and it is convenient for researchers and medical experts to communicate with one another to change the fuzzy logic rules and improve the simulation of the tissue differentiation process. In this study, a three-dimensional fracture healing model with two different interfragmentary movements (case A: 0.25 mm and case B: 1.25 mm) was analysed with the new set-up computational model. As the healing process proceeded, both simulated interfragmentary movements predicted a decrease and the time that the decrease started for case B was later than that for case A. Compared with experimental results, both cases corresponded with experimental data well. The newly established dynamic model can simulate the healing process under different mechanical environments and has the potential to extend to the multiscale healing model, which is essential for reducing the animal experiments and helping to characterise the complex dynamic interaction between tissue differentiations within the callus region.
Highlights
In single finite element models[3,4,5,6,7,8,9], tissue differentiation pathways were regulated by mechanical stimuli (Fig. 1a) based on the work of Claes and Heigele[10] and fuzzy logic control was used to simulate the process of tissue differentiation within the callus region, which is an easy way to establish the healing process as linguistic principles
We analyzed fracture healing with two different interfragmentary movement (IFM) with our computational models, which corresponded to two experimental fracture healing cases in sheep[29]
To make the tissue differentiation taking place with the callus region, the max diameter of the callus was 16 mm, which was according to the work of Claes and Heigele[10]
Summary
For bioregulatory and coupled mechanobioregulatory models, the healing process was simulated with the activities (migration, proliferation, differentiation and death) of different cells participating in the process within the callus region. These cell activities were regulated by the corresponding growth factors[21,22,23,24] and mechanical stimuli[25,26]. Partial differential equations were used to simulate different cell populations during the healing process, and finite element analysis was used to calculate the local mechanical stimuli Carlier and her colleagues made a step further in this field, they simulated the healing process with a multiscale modelling method[27,28] from the intracellular level to the tissue level, which was a more mechanistic modelling method. Bioregulatory and coupled mechanobioregulatory healing models simulated fracture healing in a more mechanistic way, there are still challenges in this field, such as the transduction of mechanical stimuli from the intracellular level to the tissue level and the influence of mechanical stimuli on growth factors
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