Introduction

Early in the design-phase of new implant design, numerous in vitro tests would be desirable to assess the influence of design parameters or component alignment on the performance of the device. However, cadaveric testing of knee replacement devices is a costly and time-consuming procedure, requiring manufacture of parts, preparation of cadaveric specimens, and personnel to carry of the experiments. Validated computational models are ideally suited for pre-clinical, high-volume design evaluation. Initial development of these models requires substantial time and expertise; once developed, however, computational simulations may be applied for comparative evaluation of devices in an extremely efficient manner [Baldwin et al. 2012]. Still, computational models are complementary of experimental testing and for this reason, computational models tuned with subject-specific experimental data, e.g. soft tissue parameters, could bring even more efficiency in the design phase. The objective of the current study was to develop a platform of tools that easily allows for subject-specific knee simulations. The system integrates with commercially available medical imaging and finite element software to allow for direct, efficient comparison of designs and surgical alignment under a host of different boundary conditions.