Knee extension moment arm variations relate to mechanical function in walking and running

Morphology and transverse alignment of the patella have no effect on knee gait characteristics in healthy Chinese adults over the age of 40 years

Background: The influence of patella morphology and horizontal alignment on knee joint kinematics and kinetics remains uncertain. This study aimed to assess patella morphology and transverse alignment in relation to knee kinetics and kinematics in individuals without knee conditions. A secondary objective was to investigate the impact of femur and tibia alignment and shape on knee gait within this population. Patients and methods: We conducted a prospective collection of data, including full-leg anteroposterior and skyline X-ray views and three-dimensional gait data, from a cohort comprising 54 healthy individuals aged 40 years and older. Our study involved correlation and logistic regression analyses to examine the influence of patella, femur, and tibia morphology and alignment on knee gait. Results: The patellar tilt angle or the patella index did not show any significant relationships with different aspects of gait in the knee joint, such as velocity, angle, or moment (p > 0.05, respectively). Using multivariate logistic regression analysis, we found that the tibiofemoral angle and the Q angle both had a significant effect on the adduction angle (OR = 1.330, 95%CI 1.033-1.711, p = 0.027; OR = 0.475, 95%CI 0.285-0.792, p = 0.04; respectively). The primary variable influencing the knee adduction moment was the tibiofemoral angle (OR = 1.526, 95% CI 1.125-2.069, p = 0.007). Conclusion: In healthy Chinese individuals aged over 40, patella morphology and transverse alignment do not impact knee gait. However, the femoral-tibial angle has a big impact on the knee adduction moment.

Prediction of Model Generated Patellofemoral Joint Contact Forces Using Principal Component Prediction and Reconstruction

It is not currently possible to directly and noninvasively measure in vivo patellofemoral joint contact force during dynamic movement; therefore, indirect methods are required. Simple models may be inaccurate because patellofemoral contact forces vary for the same knee flexion angle, and the patellofemoral joint has substantial out-of-plane motion. More sophisticated models use 3-dimensional kinematics and kinetics coupled to a subject-specific anatomical model to predict contact forces; however, these models are time consuming and expensive. We applied a principal component analysis prediction and regression method to predict patellofemoral joint contact forces derived from a robust musculoskeletal model using exclusively optical motion capture kinematics (external approach), and with both patellofemoral and optical motion capture kinematics (internal approach). We tested this on a heterogeneous population of asymptomatic subjects (n = 8) during ground-level walking (n = 12). We developed equations that successfully capture subject-specific gait characteristics with the internal approach outperforming the external. These approaches were compared with a knee-flexion based model in literature (Brechter model). Both outperformed the Brechter model in interquartile range, limits of agreement, and the coefficient of determination. The equations generated by these approaches are less computationally demanding than a musculoskeletal model and may act as an effective tool in future rapid gait analysis and biofeedback applications.

Anterior-cruciate-ligament reconstruction does not alter the knee-extensor moment arm during gait

BACKGROUND

The ability of the quadriceps muscles to extend the knee depends on the moment arm of the knee-extensor mechanism, which is described by the moment arm of the patellar tendon at the knee. The knee-extensor moment may be altered by a change in quadriceps force, a change in the patellar tendon moment arm (PTMA), or both. A change in quadriceps muscle strength after anterior-cruciate-ligament-reconstruction (ACLR) surgery is well documented, however, there is limited knowledge about how this procedure affects the PTMA.

RESEARCH QUESTION

Does ACLR surgery alter the moment arm of the knee-extensor mechanism during gait?

METHODS

We measured the PTMA in both the ACLR knee and the uninjured contralateral knee in 10 young active individuals after unilateral ACLR surgery. Mobile biplane X-ray imaging was used to measure the three-dimensional positions of the femur, tibia and patella during level walking and downhill walking over ground. The PTMA was found from the location of the instantaneous axis of rotation at the knee and the line-of-action of the patellar tendon.

RESULTS

There was a small but statistically significant difference in the mean PTMA calculated over one cycle of level walking between the ACLR knee and the contralateral knee, with the mean PTMA in the ACLR knee being 1.5 mm larger (p < 0.01). In downhill walking, statistically significant differences were found in the range 15°- 25° of knee flexion, where the PTMA was 4.7 mm larger in the ACLR knee compared to the contralateral knee (p < 0.01).

SIGNIFICANCE

Significant differences were evident in the mean PTMA between the ACLR knee and the contralateral knee in both activities, however, the magnitudes of these differences were relatively small (range: 3-10%), indicating that ACLR surgery successfully restores the moment arm of the knee-extensor mechanism during dynamic activity.

A Guide to Inverse Kinematic Marker-Guided Rotoscoping using IK Solvers

X-ray Reconstruction of Moving Morphology (XROMM) permits researchers to see beneath the skin, usually to see musculoskeletal movements. These movements can be tracked and later used to provide information regarding the mechanics of movement. Here, we discuss “IK marker-guided rotoscoping”—a method that combines inverse kinematic solvers with that of traditional scientific rotoscoping methods to quickly and efficiently overlay 3D bone geometries with the X-ray shadows from XROMM data. We use a case study of three Nile crocodiles’ (Crocodylus niloticus) forelimbs and hindlimbs to evaluate this method. Within these limbs, different marker configurations were used: some configurations had six markers, others had five markers, and all forelimb data only had three markers. To evaluate IK marker-guided rotoscoping, we systematically remove markers in the six-marker configuration and then test the magnitudes of deviation in translations and rotations of the rigged setup with fewer markers versus those of the six-marker configuration. We establish that IK marker-guided rotoscoping is a suitable method for “salvaging” data that may have too few markers.