Periacetabular osteolysis is a potentially difficult surgical challenge, which can often drive the choice of reconstruction methods used in revision hip replacement. For smaller defects, impaction of bone grafts may be sufficient, but larger defects can require filler materials that provide structural support in addition to filling a void. This study utilized finite element analysis (FEA) to examine the state of stress in periprosthetic pelvic bone when subjected to a stair-climbing load and in the presence of two simulated defects, to show the effect of implanting a defect repair implant fabricated from Trabecular Metal. Even a small medial bone defect showed a local stress elevation of 4x compared with that seen with an acetabular implant supported by intact periacetabular bone. Local bone stress was much greater (8x the baseline level) for a defect case in which the loss of bone superior to the acetabular implant permitted significant migration. FEA results showed that a repair of the small defect with a Trabecular Metal restrictor lowered periprosthetic bone stress to a level comparable to that in the case of a primary implant. For the larger defect case, the use of a Trabecular Metal augment provides structural stabilization and helps to restore the THR head center. However, stress in the adjacent periprosthetic bone is lower than that observed in the defect-free acetabulum. In the augment case, the load path between the femoral head and the pelvis now passes through the augment as the superior rim of the acetabulum has been replaced. Contact-induced stress in the augment is similar in magnitude to that seen in the superior rim of the baseline case, although the stress pattern in the augment is noticeably different from that in intact bone.
Specimen-specific modeling of the knee can be an effective tool for understanding knee mechanics [1–2]. It can also serve as a design tool for orthopaedic implant design through enhancing understanding of mechanics in the reconstructed knee [3], particularly when used in conjunction with instrumented components that record in vivo joint forces [4]. Techniques for developing specimen-specific computational geometric models of hard tissue and soft tissue are fairly commonplace, using imaging tools such as computed tomography (CT) and magnetic resonance (MR) in conjunction with software tools for image processing. Determination of specimen-specific material properties relies on measuring kinematics of the tissue associated with a defined load, either in vivo or in vitro, selecting an appropriate material model, and estimating values of the parameters of the model that closely match the experimental data. The goal of this work was to utilize inverse finite element (FE) analysis to determine material parameters of ligaments in a specimen-specific model of the knee, using both local and global optimization algorithms.
Passive knee kinematics and kinetics following total knee replacement (TKR) are dependent on the topology of the component joint surfaces as well as the properties of the passive soft tissue structures (ligaments and capsule). Recently, explicit computer models have been used for the prediction of knee joint kinematics based on experimental investigations [1]. However, most of these models replicate experimental knee simulators [2], which simulate soft tissue structures using springs or elastomeric structures. New generations of experimental setups deploy industrial robots for measuring kinematics and kinetics in six degrees of freedom as well as the contribution of soft tissue structures. Based on these experiments, accurate soft tissue properties are available for use in computer models to aid more realistic predictions of kinematics. Final evidence of the quality of the kinematic predictions from these computer models can be provided by direct validation of the models against experimental data. Therefore, the objective of this study was to use in vitro robotic test data to develop, verify, and validate specimen specific virtual models suitable for predicting laxity and kinematics of the reconstructed knee.
Advances in medical imaging techniques and computing power have allowed for the creation of sophisticated joint models that include anatomical soft tissue geometries. However the models still require experimental data of the joint’s mechanical response in order to validate the model and accurately predict joint biomechanics. Experimental methods to acquire data of the joint’s mechanical response have a long history in biomechanics [1], but it has been found that the validation of models [2] based on previously collected experimental data has been difficult because of the large inter-specimen variability. A shift, therefore, has taken place emphasizing the development of specimen specific models. Our aim was to develop a method by which the mechanical response of the knee could be measured and used as input and validation data for a specimen specific computational model.
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