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Maintaining normal knee biomechanics is crucial for preserving joint health after anterior cruciate ligament reconstruction (ACLR), particularly in paediatric patients who face a higher risk of long-term complications from suboptimal surgeries. This study employed a neuromusculoskeletal-finite element (NMSK-FE) modelling pipeline to generate subject-specific loading and boundary conditions for finite element (FE) models of three paediatric participants; each assessed eight months post-ACLR. For each participant, three FE models were developed: intact, actual post-surgery, and 135 simulated ACLR models systematically representing variations in surgical parameters (graft type, graft size, femoral tunnel placement, and pretension). Knee kinematics and tibial cartilage stresses were simulated during the stance phase of walking and compared to intact knee models using root-mean-square error (RMSE) and coefficient of determination (R 2 ). The 10 best and 10 worst surgical parameter sets were identified based on summed normalized RMSE (nRMSE) across four kinematic and two cartilage stress metrics. Applying the optimal surgical parameters from one participant to others produced clear biomechanical deviations, with average RMSE increases of ∼28% in anteroposterior translation, ∼48% in internal/external rotation, and ∼24–28% in tibial cartilage stresses, underscoring strong subject-specific variability. Notably, actual surgical choices did not align with the top 10 simulated scenarios, suggesting that conventional approaches may not yield optimal biomechanical outcomes. This study demonstrates the limitations of conventional techniques and advocates for patient-specific NMSK-FE modelling to enhance surgical decision-making, with the potential to better restore knee biomechanics and reduce the risk of long-term complications.
Dastgerdi et al. (Fri,) studied this question.