Patient-Specific Simulated Dynamics After Total Knee Arthroplasty Correlate With Patient-Reported Outcomes

Abstract

Background: Component alignment variation following total knee arthroplasty (TKA) does not fully explain the instance of long-term postoperative pain. Joint dynamics following TKA vary with component alignment and patient-specific musculoskeletal anatomy. Computational simulations allow joint dynamics outcomes to be studied across populations. This study aims to determine if simulated postoperative TKA joint dynamics correlate with patient-reported outcomes.

Methods: Landmarking and 3D registration of implants was performed on 96 segmented postoperative computed tomography scans of TKAs. A cadaver rig-validated platform for generating patient-specific simulation of deep knee bend kinematics was run for each patient. Resultant dynamic outcomes were correlated with a 12-month postoperative Knee Injury and Osteoarthritis Outcome Score (KOOS). A Classification and Regression Tree (CART) was used for determining nonlinear relationships.

Results: Nonlinear relationships between the KOOS pain score and rollback and dynamic coronal alignment were found to be significant. Combining a dynamic coronal angular change from extension to full flexion between 0° and 4° varus (long leg axis) and measured rollback of no more than 6 mm without rollforward formed a "kinematic safe zone" of outcomes in which the postoperative KOOS score is 10.5 points higher (P = .013).

Conclusion: The study showed statistically significant correlations between kinematic factors in a simulation of postoperative TKA and postoperative KOOS scores. The presence of a dynamic safe zone in the data suggests a potential optimal target for any given individual patient's joint dynamics and the opportunity to preoperatively determine a patient-specific alignment target to achieve those joint dynamics.

Keywords: computational simulation; joint dynamics; kinematics; rollback; segmentation; total knee arthroplasty (TKA).