Objective In rodent osteoarthritis models, behavioral changes are often subtle and require highly sensitive methods to detect these changes. Gait analysis is one assay that may provide sensitive, quantitative measurement of these behavioral changes1. To increase detection sensitivity of gait assessments relative to spatiotemporal gait collection alone, we combined our spatiotemporal and dynamic gait collection systems. Using this combined system, gait was assessed in the rat medial meniscus transection model and monoiodoacetate injection model of knee osteoarthritis. Design 36 male Lewis rats were separated into medial meniscus transection (n=8), medial collateral ligament transection (n=8), skin incision (n=4), monoiodoacetate injection (n=8), and saline injection (n=8) groups. After initiation of osteoarthritis, gait data were collected weekly in each group out to 4 weeks. Results The medial meniscus transection and monoiodoacetate injection models produced unique pathologic gait profiles, with medial meniscus transection animals developing a shuffling gait and monoiodoacetate injection animals exhibiting antalgic gait. Spatiotemporal changes were also observed in the medial meniscus transection model at week 1 (p<0.01), but were not observed in the monoiodoacetate injection model until week 3 (p<0.01). Dynamic gait changes were observed in both models as early as 1 week post-surgery (p<0.01). Conclusion Combined analysis of spatiotemporal and dynamic gait data increased detection sensitivity for gait modification in two rat osteoarthritis models. Analyzing the combined gait data provided a robust characterization of the pathologic gait produced by each model. Furthermore, this characterization revealed different patterns of gait compensations in two common rat models of knee osteoarthritis.

Conclusions:The results of this study support the hypothesis that side to side differences in mean full thickness UTE-T2* qMRI correlate with side to side differences in knee kinematics at 2 years after ACLR. The finding that a more lateral KCOR in the ACLR knee correlates with UTE T2* values in the medial tibia that were higher than the contralateral side suggests that this kinematic change, which has been previously shown to result in more relative motion between the femur and tibia in the medial compartment, could be affecting subsurface matrix integrity, inducing changes detectable by UTE-T2* mapping. Additionally, the finding that a more posterior KCOR in the ACLR knee correlated with UTE-T2* values in the lateral tibia that were lower than the contralateral knee further suggests that the UTE-T2* metric may reflect early changes in cartilage health. When interpreted within the context of prior work showing that a posterior shift in KCOR from 2 to 4 years post-surgery correlated with improved clinical outcomes at 8 years, the observed lower UTE-T2* with a more posterior KCOR, which is reflective of improved quadriceps recruitment, suggests positive cartilage matrix properties. In spite of the limitations of this cross-sectional and exploratory study, and the difficulty accounting for changes in the contralateral knee, these results support future studies of the relationship between UTE-T2* and KCOR to provide new insight into predicting the risk for OA after ACLR.