The study objective was to construct and validate a subject-specific knee model that can simulate full six degree of freedom tibiofemoral and patellofemoral joint behavior in the context of full body movement. Segmented MR images were used to reconstruct the geometry of 14 ligament bundles and articular cartilage surfaces. The knee was incorporated into a lower extremity musculoskeletal model, which was then used to simulate laxity tests, passive knee flexion, active knee flexion, and human walking. Simulated passive and active knee kinematics were shown to be consistent with subject-specific measures obtained via dynamic MRI. Anterior tibial translation and internal tibial rotation exhibited the greatest variability when uncertainties in ligament properties were considered. When used to simulate walking, the model predicted knee kinematic patterns that differed substantially from passive joint behavior. Predictions of mean knee cartilage contact pressures during normal gait reached 6.2 and 2.8 MPa on the medial tibial plateau and patellar facets, respectively. Thus, the dynamic modeling framework can be used to simulate the interaction of soft tissue loads and cartilage contact during locomotion activities, and therefore provides a basis to simulate the effects of soft tissue injury and surgical treatment on functional knee mechanics.

The study objective was to investigate the influence of coronal plane alignment and ligament properties on total knee replacement (TKR) contact loads during walking. We created a subject-specific knee model of an 83-year-old male who had an instrumented TKR. The knee model was incorporated into a lower extremity musculoskeletal model and included deformable contact, ligamentous structures, and six degrees-of-freedom (DOF) tibiofemoral and patellofemoral joints. A novel numerical optimization technique was used to simultaneously predict muscle forces, secondary knee kinematics, ligament forces, and joint contact pressures from standard gait analysis data collected on the subject. The nominal knee model predictions of medial, lateral, and total contact forces during gait agreed well with TKR measures, with root-mean-square (rms) errors of 0.23, 0.22, and 0.33 body weight (BW), respectively. Coronal plane component alignment did not affect total knee contact loads, but did alter the medial-lateral load distribution, with 4 deg varus and 4 deg valgus rotations in component alignment inducing þ17% and À23% changes in the first peak medial tibiofemoral contact forces, respectively. A Monte Carlo analysis showed that uncertainties in ligament stiffness and reference strains induce 60.2 BW uncertainty in tibiofemoral force estimates over the gait cycle. Ligament properties had substantial influence on the TKR load distributions, with the medial collateral ligament and iliotibial band (ITB) properties having the largest effects on medial and lateral compartment loading, respectively. The computational framework provides a viable approach for virtually designing TKR components, considering parametric uncertainty and predicting the effects of joint alignment and soft tissue balancing procedures on TKR function during movement.

This study investigated the use of dynamic, volumetric MRI to measure 3D skeletal motion. Ten healthy subjects were positioned on a MR-compatible knee loading device and instructed to harmonically flex and extend their knee at 0.5 Hz. The device induced active quadriceps loading with knee flexion, similar to the load acceptance phase of gait. Volumetric images were continuously acquired for five minutes using a 3D cine SPGR sequence in conjunction with vastly under-sampled isotropic projections (SPGR-VIPR). Knee angle was simultaneously monitored and used retrospectively to sort images into 60 frames over the motion cycle. High resolution static knee images were acquired and segmented to create subject-specific models of the femur and tibia. At each time frame, bone positions and orientations were determined by automatically registering the skeletal models to the dynamic images. Three-dimensional tibiofemoral translations and rotations were consistent across healthy subjects. Internal tibia rotations of 7.8 ± 3.5° were present with 35.8 ± 3.8° of knee flexion, a pattern consistent with knee kinematic measures during walking. We conclude that VIPR volumetric imaging is a promising approach for non-invasively measuring 3D joint kinematics, which may be useful for assessing cartilage contact and investigating the causes and treatment of joint abnormalities. Keywords: dynamic imaging; knee mechanics; joint motion

Computational knee models provide a powerful platform to investigate the effects of injury and surgery on functional knee behavior. The objective of this study was to use a multibody knee model to investigate the influence of ligament properties on tibiofemoral kinematics and cartilage contact pressures in the stance phase of walking. The knee model included 14 ligament bundles and articular cartilage contact acting across the tibiofemoral and patellofemoral joints. The knee was incorporated into a lower extremity musculoskeletal model and used to simulate knee mechanics during the stance phase of normal walking. A Monte Carlo approach was employed to assess the influence ligament stiffness and reference strains on knee mechanics. The ACL, MCL and posterior capsule properties exhibited significant influence on anterior tibial translation at heel strike, with the ACL acting as the primary restraint to anterior translation in mid-stance. The MCL and LCL exhibited the greatest influence on tibial rotation from heel strike through mid-stance. Simulated tibial plateau contact location was dependent on the ACL, MCL and LCL properties, while pressure magnitudes were most dependent on the ACL. A decrease in ACL stiffness or reference strain significantly increased average contact pressure in mid-stance, with the pressure migrating posteriorly on the medial tibial plateau. These ligament-dependent shifts in tibiofemoral cartilage contact during walking are potentially relevant to consider when investigating the causes of early onset osteoarthritis following knee ligament injury and surgical treatment.

Interventions used to treat patellofemoral pain in runners are often designed to alter patellofemoral mechanics. This study used a computational model to investigate the influence of two interventions, step rate manipulation and quadriceps strengthening, on patellofemoral contact pressures during running. Running mechanics were analyzed using a lower extremity musculoskeletal model that included a knee with six degree-of-freedom tibiofemoral and patellofemoral joints. An elastic foundation model was used to compute articular contact pressures. The lower extremity model was scaled to anthropometric dimensions of 22 healthy adults, who ran on an instrumented treadmill at 90%, 100% and 110% of their preferred step rate. Numerical optimization was then used to predict the muscle forces, secondary tibiofemoral kinematics and all patellofemoral kinematics that would generate the measured hip, knee and ankle joint accelerations. Mean and peak patella contact pressures reached 5.0 and 9.7 MPa during the midstance phase of running. Increasing step rate by 10% significantly reduced mean contact pressures by 10.4% and contact area by 7.4%, but had small effects on lateral patella translation and tilt. Enhancing vastus medialis strength did not substantially affect pressure magnitudes or lateral patella translation, but did shift contact pressure medially toward the patellar median ridge. Thus, the model suggests that step rate tends to primarily modulate the magnitude of contact pressure and contact area, while vastus medialis strengthening has the potential to alter mediolateral pressure locations. These results are relevant to consider in the design of interventions used to prevent or treat patellofemoral pain in runners.