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Meniscal Dominant Loaders During Simulated Gait: A Cadaveric Study in Human Knees
Tony Chen1, Kalle Chastain1, Megh Prajapati2
1Hospital for Special Surgery, New York, New York, USA.
Background:
Changes in joint contact force distribution after injury are 1 factor driving tissue degeneration. Although clinical interventions aim to restore forces to their uninjured state, inconsistent outcomes suggest that patient variability in joint contact mechanics remains poorly understood, despite the use of patient-specific computational models that are too labor-intensive to be widely adopted. A more practical solution may involve grouping knees by commonalities in force distribution, enabling recognition of heterogeneity without requiring fully individualized models.
Hypothesis/Purpose:
The objective of this study was to determine whether human cadaveric knees can be grouped based on differences in joint contact force distribution across the tibial plateau during the stance phase of simulated gait. We hypothesized that a subset of knees would heavily rely on the meniscus ("meniscal-dominant loaders") and another subset of knees would distribute more force through cartilage-to-cartilage contact ("cartilage-dominant loaders"). Our secondary hypothesis was that cartilage-dominant loaders would have their peak contact stress in the cartilage-cartilage contact region, and those with meniscal-dominant loading would have peak contact stress primarily located in the meniscus footprint.
Study Design:
Descriptive laboratory study.
Methods:
Cartilage-cartilage and meniscal footprints were identified on contact force data across the tibial plateaus of cadaveric knees (n = 44) subjected to simulated gait. Knees were grouped based on force distribution on the medial or lateral plateaus using K-means clustering. They were characterized as meniscal dominant loaders if >50% of the compartment load was acting through the meniscus for >50% of the simulated gait cycle. Knees were characterized as cartilage-dominant loaders if >50% of the compartment load was acting through the cartilage-to-cartilage contact zone for most of the gait cycle.
Results:
On the medial plateau, 4 clusters were identified. These clusters ranged from cartilage-dominant loaders (Cluster 1 [7% of knees]) to meniscal loaders (Cluster 4 [48% of knees]). Knees in Cluster 2 (20% of knees) and 3 (25% of knees) were meniscal-dominant loaders in early stance and switched to cartilage-dominant loading in late stance. The peak contact stress shifted from the cartilage-cartilage region in cartilage-dominant loaders to the meniscus footprint in meniscal-dominant loaders. On the lateral plateau, 3 clusters were identified. These clusters again ranged from cartilage-dominant loaders (Cluster 1 [11% of knees]) to meniscal-dominant loaders (Cluster 3 [72% of knees]). Knees in Cluster 2 (17% of knees) equally shared load between the cartilage and meniscus. No differences were found in peak stress between cartilage-dominant loaders and meniscal-dominant loaders on the lateral plateau.
Conclusion:
We confirmed that human cadaveric knees can be stratified based on the distribution of load through menisci and that peak pressures were higher in the cartilage-dominant loading knees.
Clinical Relevance:
This study identifies heterogeneity in how human cadaveric knees distribute forces during simulated gait. This information is fundamental to understanding and improving upon the biomechanical variability in the knee's response to injury and repair.

