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Research

APPLICATION OF A COMPREHENSIVE STATISTICAL APPROACH FOR ASSESSING IMPLANT PERFORMANCE TO THR

European Orthopaedic Research Society (EORS) 24th Annual Meeting, 14–16 September 2016. Part 2.



Abstract

There is a critical need for safe innovation in total joint replacements to address the demands of an ageing yet increasingly active population. The development of robust implant designs requires consideration of uncertainties including patient related factors such as bone morphology but also activity related loads and the variability in the surgical procedure itself. Here we present an integrated framework considering these sources of variability and its application to assess the performance of the femoral component of a total hip replacement (THR).

The framework offers four key features. To consider variability in bone properties, an automated workflow for establishing statistical shape and intensity models (SSIM) was developed. Here, the inherent relationship between shape and bone density is captured and new meshes of the target bone structures are generated with specific morphology and density distributions. The second key feature is a virtual implantation capability including implant positioning, and bone resection. Implant positioning is performed using automatically identified bone features and flexibly defined rules reflecting surgical variability. Bone resection is performed according to manufacturer guidelines. Virtual implantation then occurs through Boolean operations to remove bone elements contained within the implant's volume. The third feature is the automatic application of loads at muscle attachment points or on the joint contact surfaces defined on the SSIM. The magnitude and orientation of the forces are derived from models of similar morphology for a range of activities from a database of musculoskeletal (MS) loads. The connection to this MS loading model allows the intricate link between morphology and muscle forces to be captured. Importantly, this model of the internal forces provides access to the spectrum of loading conditions across a patient population rather than just typical or average values. The final feature is an environment that allows finite element simulations to be run to assess the mechanics of the bone-implant construct and extract results for e.g. bone strains, interface mechanics and implant stresses. Results are automatically processed and mapped in an anatomically consistent manner and can be further exploited to establish surrogate models for efficient subsequent design optimization. To demonstrate the capability of the framework, it has been applied to the femoral component of a THR.

An SSIM was created from 102 segmented femurs capturing the heterogeneous bone density distributions. Cementless femoral stems were positioned such that for the optimal implantation the proximal shaft axis of the femurs coincided with the distal stem axis and the position of the native femoral head centre was restored. Here, the resection did not affect the greater trochanter and the implantations were clinically acceptable for 10000 virtual implantations performed to simulate variability in patient morphology and surgical variation. The MS database was established from musculoskeletal analyses run for a cohort of 17 THR subjects obtaining over 100,000 individual samples of 3D muscle and joint forces. An initial analysis of the mechanical performance in 7 bone-implant constructs showed levels of bone strains and implant stresses in general agreement with the literature.