Development and validation of a kinematically-driven discrete element model of the patellofemoral joint

Abstract Quantifying the complex loads at the patellofemoral joint (PFJ) is vital to understanding the development of PFJ pain and osteoarthritis. Discrete element analysis (DEA) is a computationally efficient method to estimate cartilage contact stresses with potential application at the PFJ to better understand PFJ mechanics. The current study validated a DEA modeling framework driven by PFJ kinematics to predict experimentally-measured PFJ contact stress distributions. Two cadaveric knee specimens underwent quadriceps muscle [215 N] and joint compression [350 N] forces at ten discrete knee positions representing PFJ positions during early gait while measured PFJ kinematics were used to drive specimen-specific DEA models. DEA-computed contact stress and area were compared to experimentally-measured data. There was good agreement between computed and measured mean and peak stress across the specimens and positions (r = 0.63–0.85). DEA-computed mean stress was within an average of 12% (range: 1–47%) of the experimentally-measured mean stress while DEA-computed peak stress was within an average of 22% (range: 1–40%). Stress magnitudes were within the ranges measured (0.17–1.26 MPa computationally vs 0.12–1.13 MPa experimentally). DEA-computed areas overestimated measured areas (average error = 60%; range: 4–117%) with magnitudes ranging from 139 to 307 mm 2 computationally vs 74–194 mm 2 experimentally. DEA estimates of the ratio of lateral to medial patellofemoral stress distribution predicted the experimental data well (mean error = 15%) with minimal measurement bias. These results indicate that kinematically-driven DEA models can provide good estimates of relative changes in PFJ contact stress.