Advanced porous hip implants: A comprehensive review

Biomechanical Impact of Cementation Technique Variations on Femoral Stem Stability: An In Vitro Polyurethane Model Study

Background/Objectives: Achieving optimal primary stability in cemented total hip arthroplasty remains a critical factor influencing long-term implant success. Variability in cementation techniques can significantly affect biomechanical performance, yet consensus on best practices is lacking. This study investigates the influence of cementation parameters on femoral stem fixation. Methods: This in vitro comparative study evaluated four cementation techniques-Classic (line-to-line), Press-Fit (undersized reaming), Overreaming (oversized reaming), and Valgus Malpositioning (15° deviation). An experimental model using standardized Polyurethane (PU) bone surrogates was developed. Mechanical testing assessed axial deformation and ultimate load capacity to failure. Results: The Press-Fit technique demonstrated significantly greater deformation (17.10 ± 0.89 mm) but a reduced load capacity (6317.47 ± 518.34 N) compared to the Classic approach. Overreaming and Valgus techniques both showed reduced mechanical performance, with Overreaming yielding the lowest structural integrity. Conclusions: Cement mantle thickness emerged as the primary determinant of biomechanical stability, surpassing the impact of implant positioning. While increased mantle thickness improves energy absorption, it may compromise ultimate strength. These findings underscore the importance of optimizing the cementation technique to balance flexibility and mechanical resistance, guiding surgical protocols toward improved implant longevity. This study introduces a novel integrative approach combining fluoroscopic assessment of cement mantle morphology with mechanical testing in a standardized model, providing new evidence on the relative influence of mantle thickness and implant malposition on femoral stem stability.

A Neural Network-Accelerated Approach for Orthopedic Implant Design and Evaluation Through Strain Shielding Analysis

The design of orthopedic implants is a complex challenge, requiring the careful balance of mechanical performance and biological integration to ensure long-term success. This study focuses on the development of a porous femoral stem implant aimed at reducing stiffness and mitigating stress shielding effects. To accelerate the design process, neural networks were trained to predict the optimal density distribution of the implant, enabling rapid optimization. Two initial design spaces were evaluated, revealing the necessity of incorporating the femur's anatomical features into the design process. The trained models achieved a median error near 0 for both conventional and extended design spaces, producing optimized designs in a fraction of the computational time typically required. Finite element analysis (FEA) was employed to assess the mechanical performance of the neural network-generated implants. The results demonstrated that the neural network predictions effectively reduced stress shielding compared to a solid model in 50% of the test cases. While the graded porosity implant design did not show significant differences in stress shielding prevention compared to a uniform porosity design, it was found to be significantly stronger, highlighting its potential for enhanced durability. This work underscores the efficacy of neural network-accelerated design in improving implant development efficiency and performance.

Developing porous hip implants implementing topology optimization based on the bone remodelling model and fatigue failure

In contemporary orthopaedic practice, total hip arthroplasty (THA) is a reliable surgical technique for hip joint replacement. However, introducing solid implants into human bone tissue can lead to complications, notably stress shielding and cortical hypertrophy. These issues often stem from mechanical mismatches, particularly stiffness disparities, between the solid implants and the bone tissue. A potential solution lies in adopting porous implant structures with lower stiffness and tuneable mechanical properties based on morphological parameters such as porosity, relative density, and unit cell sizes. This study, which is of significant importance to orthopaedic implant development, aims to develop porous implants that meet biological and manufacturing requirements, employing topology optimization methods to address the challenges associated with conventional solid implants. To achieve this objective, we conducted finite element analyses to compare the stress distribution within healthy bones with solid and newly developed porous implants under real-life loading conditions. The porous implants were designed with triply periodic minimal surface structures, featuring uniform relative density and gradient relative density mapping derived from topology optimization results considering additive manufacturing capabilities and biological constraints. Our findings provide critical insights into the impact on the bone's mechanical environment about the choice of implant. Specifically, solid implants significantly decrease applied stress within the cortical bone, leading to stress shielding and subsequent bone resorption, consistent with bone remodelling principles and Wolff's law. However, replacing the solid implant with uniform porosity with maximum compliance and employing gradient porous implants based on topology optimization methods significantly increases the strain energy density ratio. Specifically, the uniform gyroid, uniform diamond, gradient gyroid, and gradient diamond stems exhibited increases of 43%, 39%, 27%, and 25%, respectively, compared to the solid stem, effectively mitigating the stress shielding effect. However, amongst porous stems, only gradient designs could meet the mechanical strength requirements with a safety factor greater than one, rendering them suitable replacements for solid implants aimed at addressing associated complications. These results hold promise, particularly with the advancements in additive manufacturing methods capable of fabricating these porous implants with acceptable precision.