Predicting patellar kinematics and contact forces after TKA: a simulation study on quadriceps malalignment.

Area of Science:

• Biomechanics
• Computational modeling
• Orthopedic surgery

Background:

• Patellofemoral complications are a common cause of dissatisfaction after total knee arthroplasty (TKA).
• Abnormal patellar tracking, often due to preoperative quadriceps malalignment, can lead to pain and instability.
• Subject-specific assessment tools are crucial for optimizing TKA surgical planning and outcomes.

Purpose of the Study:

• To develop and validate a subject-specific multibody dynamics (MBD) framework for simulating patellofemoral mechanics after TKA.
• To evaluate the impact of component positioning on patellar tracking and contact forces in a patient with quadriceps malalignment.
• To assess the computational efficiency and predictive accuracy of the MBD framework.

Main Methods:

• A subject-specific MBD framework was created to simulate TKA patellofemoral mechanics.
• A representative patient with significant quadriceps malalignment was modeled for detailed analysis.
• The influence of femoral and tibial component alignment (rotation, varus/valgus) was systematically investigated.
• Numerical predictions were validated against experimental data from a sensorized 3D-printed knee rig.

Main Results:

• Quadriceps malalignment was identified as the primary driver of patellar instability, causing increased lateralization and contact forces.
• Valgus alignment and internal rotation of components exacerbated lateral patellar shift and increased contact forces.
• Varus alignment and external rotation showed potential for moderate reductions in contact forces and improved patellar alignment.
• The simulation demonstrated strong agreement with experimental measurements, with an average computation time of 48 seconds.

Conclusions:

• The developed computational framework allows for rapid, subject-specific evaluation of patellofemoral mechanics in TKA.
• The model incorporates individual patient anatomy and alignment for personalized surgical planning.
• This efficient and predictive tool has potential for intraoperative assessment and surgical optimization in TKA.