Prediction of micro-scale bone adaptation of human trabecular bone under different implanted conditions

Different bone remodeling algorithms are used to predict bone adaptation and to understand how bones respond to the mechanical stimuli altered by implants. This paper introduces a novel micro-scale bone remodeling algorithm, which deviates from conventional methods by focusing on structure-based bone adaptation instead of density-based approaches.

The proposed model simulated cellular activities such as bone resorption, new bone formation, and maturation of newly formed bone. These activities were assumed to be triggered by mechanical stimuli. Model parameters were evaluated for the 3D geometries of trabecular bone from intact femur developed from micro computed tomography (CT) scan data. Two different hip implants, solid and porous were used, and two different bone remodeling methods were performed using the proposed and conventional methods.

Results showed that micro CT scan-based finite element (FE) models accurately captured the microarchitecture and anisotropy of trabecular bone. The predicted bone resorption rate at the peri-prosthetic regions for the solid and porous implants was in the range of 17-27% and 4.5-7.3%, respectively, for a simulated period of four years.

The results obtained from FE analysis strongly align with clinical findings, confirming the effectiveness of the proposed algorithm. By emphasizing the structural aspect of bone adaptation, the proposed algorithm brings a fresh perspective on bone adaptation at the peri-prosthetic bone. This method can help researchers and clinicians to improve implant designs for better clinical outcomes.