Analysis of Internal Knee Forces Allows for the Prediction of Rupture Events in a Clinically Relevant Model of Anterior Cruciate Ligament Injuries. Issue 1 (10th January 2020)

• Record Type: Journal Article
• Authors: Ueno, Ryo; Navacchia, Alessandro; Bates, Nathaniel A.; Schilaty, Nathan D.; Krych, Aaron J.; Hewett, Timothy E.
• Is Part Of: Orthopaedic journal of sports medicine. Volume 8:Issue 1(2020)
• Publication Date: 2020-01-10
• Subjects: ACL -- landing -- injury mechanism -- principal component analysis; Sports medicine -- Periodicals; Orthopedics -- Periodicals; Arthroscopy -- Periodicals; Arthroplasty -- Periodicals; Knee -- Surgery -- Periodicals; 616.7
• DOI: 10.1177/2325967119893758
• Languages: English
• ISSNs: 2325-9671

Abstract

Background: A recently developed mechanical impact simulator induced an anterior cruciate ligament (ACL) rupture via the application of a combination of inverse dynamics–based knee abduction moment (KAM), anterior tibial shear force (ATS), and internal tibial rotation moment with impulsive compression in a cohort of cadaveric limbs. However, there remains an opportunity to further define the interaction of internal forces and moments at the knee and their respective influence on injury events. Purpose: To identify the influence of internal knee loads on an ACL injury event using a cadaveric impact simulator. Study Design: Controlled laboratory study. Methods: Drop-landing simulations were performed and analyzed on 30 fresh-frozen cadaveric knees with a validated mechanical impact simulator. Internal forces and moments at the knee joint center were calculated using data from a 6-axis load cell recorded on the femur during testing. Kinetic data from a total of 1083 trials that included 30 ACL injury trials were used as inputs for principal component (PC) analysis to identify the most critical features of loading waveforms. Logistic regression analysis with a stepwise selection was used to select the PCs that predicted an ACL injury. Injurious waveforms were reconstructed with selected PCs in logistic regression analysis. Results: A total of 3 PCs were selected in logistic regression analysis that developed a significant model ( P < .001). The external loading of KAM was highly correlated with PC1 (ρ < –0.8; P < .001), which explained the majority (>69%) of the injurious waveforms reconstructed with the 3 selected PCs. The injurious waveforms demonstrated a larger internal knee adduction moment and lateral tibial force. After the ACL was ruptured, decreased posterior tibial force was observed in injury trials. Conclusion: These findings give us a better understanding of ACL injury mechanisms using 6-axis kinetics from an in vitro simulator. An ACL rupture was correlated with an internal knee adduction moment (external KAM) and was augmented by ATS and lateral tibial force induced by an impact, which distorted the ACL insertion orientation. Clinical Relevance: The ACL injury mechanism explained in this study may help target injury prevention programs to decrease injurious knee loading (KAM, ATS, and lateral tibial force) during landing tasks.