Optimal Implant Positioning Following Total Knee Arthroplasty Using Predictive Dynamic Simulation.

In this paper, a novel method is proposed for the determination of the optimal subject-specific placement of knee implants based on predictive dynamic simulations of human movement following total knee arthroplasty (TKA). Two knee implant models are introduced. The first model is a comprehensive 12-degree-of-freedom (DoF) representation that incorporates volumetric contact between femoral and tibial implants, as well as patellofemoral contact. The second model employs a single-degree-of-freedom equivalent kinematic (SEK) approach for the knee joint. A cosimulation framework is proposed to leverage both knee models in our simulations. The knee model is calibrated and validated using patient-specific data, including knee kinematics and ground reaction forces. Additionally, quantitative indices are introduced to evaluate the optimality of implant positioning based on three criteria: balancing medial and lateral load distributions, ligament balancing, and varus/valgus alignment. The knee implant placement is optimized by minimizing the deviation of the indices from their user-defined desired values during predicted sit-to-stand motion. The method presented in this paper has the potential to enhance the results of knee arthroplasty and serve as a valuable instrument for surgeons when planning and performing this procedure.

Model-Based Acetabular Cup Orientation Optimization Based on Minimizing the Risk of Edge-Loading and Implant Impingement Following Total Hip Arthroplasty.

In this paper, a computationally efficient model-based method for determining patient-specific optimal acetabular cup alignment for total hip arthroplasty (THA) is presented. The proposed algorithm minimizes the risk of implant impingement and edge-loading, which are reported as the major causes of hip dislocation following THA. First, by using motion capture data recorded from the patient performing different daily activities, the hip contact force and the relative orientation of the femur and pelvis are calculated by a musculoskeletal model. Then, by defining two quantitative indices, i.e., angular impingement distance and angular edge-loading distance (AED), the risk of impingement and edge-loading are assessed for a wide range of cup alignments. Finally, three optimization criteria are introduced to estimate the optimal cup alignment with a tradeoff between the risk of impingement and edge loading. The results show that patient-specific characteristics such as pelvic tilt could significantly change the optimal cup alignment, especially the value of cup anteversion. Therefore, in some cases, the well-known Lewinnek safe zone may not be optimal, or even safe. Unlike other dynamic model-based methods, in this work, the need for force plate measurements is eliminated by estimating the ground reaction forces and moments, which makes this method more practical and cost-efficient. Furthermore, the low computational complexity due to analytical formulas makes this method suitable for both pre-operative and intra-operative planning.