The effects of posterior cruciate ligament deficiency on posterolateral corner structures under gait- and squat-loading conditions: A computational knee model.

Abstract

ObjectivesThe aim of the current study was to analyse the effects of posterior cruciate ligament (PCL) deficiency on forces of the posterolateral corner structure and on tibiofemoral (TF) and patellofemoral (PF) contact force under dynamic-loading conditions.MethodsA subject-specific knee model was validated using a passive flexion experiment, electromyography data, muscle activation, and previous experimental studies. The simulation was performed on the musculoskeletal models with and without PCL deficiency using a novel force-dependent kinematics method under gait- and squat-loading conditions, followed by probabilistic analysis for material uncertain to be considered.ResultsComparison of predicted passive flexion, posterior drawer kinematics and muscle activation with experimental measurements showed good agreement. Forces of the posterolateral corner structure, and TF and PF contact forces increased with PCL deficiency under gait- and squat-loading conditions. The rate of increase in PF contact force was the greatest during the squat-loading condition. The TF contact forces increased on both medial and lateral compartments during gait-loading conditions. However, during the squat-loading condition, the medial TF contact force tended to increase, while the lateral TF contact forces decreased. The posterolateral corner structure, which showed the greatest increase in force with deficiency of PCL under both gait- and squat-loading conditions, was the popliteus tendon (PT).ConclusionPCL deficiency is a factor affecting the variability of force on the PT in dynamic-loading conditions, and it could lead to degeneration of the PF joint.Cite this article: K-T. Kang, Y-G. Koh, M. Jung, J-H. Nam, J. Son, Y.H. Lee, S-J. Kim, S-H. Kim. The effects of posterior cruciate ligament deficiency on posterolateral corner structures under gait- and squat-loading conditions: A computational knee model. Bone Joint Res 2017;6:31–42. DOI: 10.1302/2046-3758.61.BJR-2016-0184.R1.