Abstract
Long-term biological fixation and stability of uncemented acetabular implant are influenced by peri-prosthetic bone ingrowth which is known to follow the principle of mechanoregulatory tissue differentiation algorithm. A tissue differentiation is a complex set of cellular events which are largely influenced by various mechanical stimuli. Over the last decade, a number of cell-phenotype specific algorithms have been developed in order to simulate these complex cellular events during bone ingrowth. Higher bone ingrowth results in better implant fixation. It is hypothesized that these cellular events might influence the peri-prosthetic bone ingrowth and thereby implant fixation. Using a three-dimensional (3D) microscale FE model representing an implant-bone interface and a cell-phenotype specific algorithm, the objective of the study is to evaluate the influences of various cellular activities on peri-prosthetic tissue differentiation. Consequently the study aims at identifying those cellular activities that may enhance implant fixation.
The 3D microscale implant-bone interface model, comprising of Porocast Bead of BHR implant, granulation tissue and bone, was developed and meshed in ANSYS (Fig. 1b). Frictional contact (µ=0.5) was simulated at all interfaces. The displacement fields were transferred and prescribed at the top and bottom boundaries of the microscale model from a previously investigated macroscale implanted pelvis model (Fig. 1a) [4]. Periodic boundary conditions were imposed on the lateral surfaces. Linear elastic, isotropic material properties were assumed for all materials. Young's modulus and Poisson's ratios of bone and implant were mapped from the macroscale implanted pelvis [4]. A cell-phenotype specific mechanoregulatory algorithm was developed where various cellular activities and tissue formation were modeled with seven coupled differential equations [1, 2]. In order to evaluate the influence of various cellular activities, a Plackett-Burman DOE scheme was adopted. In the present study each of the cellular activity was assumed to be an independent factor. A total of 20 independent two-level factors were considered in this study which resulted in altogether 24 different combinations to be investigated. All these cellular activities were in turn assumed to be regulated by local mechanical stimulus [3]. The mechano-biological simulation was run until a convergence in tissue formation was attained.
The cell-phenotype specific algorithm predicted a progressive transformation of granulation tissue into bone, cartilage and fibrous tissue (Fig. 1c). Various cellular activities were found to influence the time to reach equilibrium in tissue differentiation and, thereby, attainment of sufficient implant fixation (Fig. 2, Table 1). Negative regression coefficients were predicted for the significant factors, differentiation rate of MSCs and bone matrix formation rate, indicating that these cellular activities favor peri-prosthetic bone ingrowth by facilitating rapid peri-prosthetic bone ingrowth. Osteoblast differentiation rate, on the contrary, was found to have the highest positive regression coefficient among the other cellular activities, indicating that an increase in this cellular activity delays the attainment of equilibrium in bone ingrowth prohibiting rapid implant fixation.
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