A stochastic biomechanical model for risk and risk factors of non-contact anterior cruciate ligament injuries.

Gender has been identified as a risk factor for non-contact anterior cruciate ligament (ACL) injuries. Although some possible biomechanical risk factors underlying the gender differences in the risk for non-contact ACL injuries have been identified, they have not been quantitatively confirmed yet because of the descriptive nature of the traditional epidemiological methods. The purpose of this study was to validate a stochastic biomechanical model for the risk and risk factors for non-contact ACL injuries. An ACL loading model was developed and instrumented to a Monte Carlo simulation to estimate the ACL injury rate for a stop-jump task in which non-contact ACL injuries frequently occur. Density distributions of independent variables of the ACL loading model were determined from in-vivo data of 40 male and 40 female athletes when performing the stop-jump task. A non-contact ACL injury was defined as the peak ACL loading being greater than 2250N for males and 1800N for females. The female-to-male non-contact ACL injury rate ratio was determined as the ratio of the probability of ACL ruptures of females to that of males. The female-to-male non-contact ACL injury rate ratio predicted by the stochastic biomechanical model was 4.96 (SD=0.22). The predicted knee flexion angle at the peak ACL loading in the simulated injury trials was 22.0 (SD=8.0) degrees for males and 24.9 (SD=5.6) degrees for females. The stochastic biomechanical model for non-contact ACL injuries developed in the present study accurately predicted the female-to-male injury rate ratio for non-contact ACL injuries and one of the kinematic characteristics of the injury.