Influence of Clinically Relevant Factors on the Immediate Biomechanical Surrounding for a Series of Dental Implant Designs

The objective of the present study was to assess the influence of various clinically relevant scenarios on the strain distribution in the biomechanical surrounding of five different dental implant macrogeometries. The biomechanical environment surrounding an implant, i.e., the cortical and trabecular bone, was modeled along with the implant. These models included two different values of the study parameters including loading conditions, trabecular bone elastic modulus, cortical/trabecular bone thickness ratio, and bone loss for five implant designs. Finite element analysis was conducted on the models and strain in the bones surrounding the implant was calculated. Bone volumes having strains in four different windows of 0–200 με, 200–1000 με, 1000–3000 με, and >3000 με were measured and the effect of each biomechanical variable and their two-way interactions were statistically analyzed using the analysis of variance method. This study showed that all the parameters included in this study had an effect on the volume of bones in all strain windows, except the implant design, which affected only the 0–200 με and >3000 με windows. The two-way interaction results showed that interactions existed between implant design and bone loss, and loading condition, bone loss in the 200–1000 με window, and between implant design and loading condition in the 0–200 με window. Within the limitations of the present methodology, it can be concluded that although some unfavorable clinical scenarios demonstrated a higher volume of bone in deleterious strain levels, a tendency toward the biomechanical equilibrium was evidenced regardless of the implant design.

Design and Analysis of Robust Total Joint Replacements: Finite Element Model Experiments With Environmental Variables

Computer simulations of orthopaedic devices can be prohibitively time consuming, particularly when assessing multiple design and environmental factors. Chang et al. (1999) address these computational challenges using an efficient statistical predictor to optimize a flexible hip implant, defined by a midstem reduction, subjected to multiple environmental conditions. Here, we extend this methodology by: (1) explicitly considering constraint equations in the optimization formulation, (2) showing that the optimal design for one environmental distribution is robust to alternate distributions, and (3) illustrating a sensitivity analysis technique to determine influential design and environmental factors. A thin midstem diameter with a short stabilizing distal tip minimized the bone remodeling signal while maintaining satisfactory stability. Hip joint force orientation was more influential than the effect of the controllable design variables on bone remodeling and the cancellous bone elastic modulus had the most influence on relative motion, both results indicating the importance of including uncontrollable environmental factors. The optimal search indicated that only 16 to 22 computer simulations were necessary to predict the optimal design, a significant savings over traditional search techniques.