The relation between meniscal dynamics and tibiofemoral kinematics.

Over the past 30 years, research on meniscal kinematics has been limited by challenges such as low-resolution imaging and capturing continuous motion from static data. This study aimed to develop a computational knee model that overcomes these limitations and enables the continuous assessment of meniscal dynamics. A high-resolution MRI dataset (n = 11) was acquired in 4 configurations of knee flexion. In each configuration, the menisci were modeled based on the underlying osseous anatomy. Principal Polynomial Shape Analysis (PPSA) was employed for continuous meniscal modeling. Maximal medial anterior horn displacement occurred in 60° of flexion, equaling 6.24 mm posteromedial, while the posterior horn remained relatively stable. At 90° of flexion, the lateral anterior and posterior horn displaced posteromedially, amounting 5.70 mm and 6.51 mm respectively. The maximal observed Average Surface Distance (ASD) equaled 0.70 mm for lateral meniscal modeling in 90° of flexion. Based on our results, a strong relation between meniscal dynamics and tibiofemoral kinematics was confirmed. Expanding on static meniscal modeling and employing PPSA, we derived and validated a standardized and systematic methodological workflow.

Quantifying walking speeds in relation to ankle biomechanics on a real-time interactive gait platform: a musculoskeletal modeling approach in healthy adults.

Background: Given the inherent variability in walking speeds encountered in day-to-day activities, understanding the corresponding alterations in ankle biomechanics would provide valuable clinical insights. Therefore, the objective of this study was to examine the influence of different walking speeds on biomechanical parameters, utilizing gait analysis and musculoskeletal modelling. Methods: Twenty healthy volunteers without any lower limb medical history were included in this study. Treadmill-assisted gait-analysis with walking speeds of 0.8 m/s and 1.1 m/s was performed using the Gait Real-time Analysis Interactive Lab (GRAIL®). Collected kinematic data and ground reaction forces were processed via the AnyBody® modeling system to determine ankle kinetics and muscle forces of the lower leg. Data were statistically analyzed using statistical parametric mapping to reveal both spatiotemporal and magnitude significant differences. Results: Significant differences were found for both magnitude and spatiotemporal curves between 0.8 m/s and 1.1 m/s for the ankle flexion (p < 0.001), subtalar force (p < 0.001), ankle joint reaction force and muscles forces of the M. gastrocnemius, M. soleus and M. peroneus longus (α = 0.05). No significant spatiotemporal differences were found between 0.8 m/s and 1.1 m/s for the M. tibialis anterior and posterior. Discussion: A significant impact on ankle joint kinematics and kinetics was observed when comparing walking speeds of 0.8 m/s and 1.1 m/s. The findings of this study underscore the influence of walking speed on the biomechanics of the ankle. Such insights may provide a biomechanical rationale for several therapeutic and preventative strategies for ankle conditions.