Background: Analyzing sports injuries is essential to mitigate risk for injury, but inherently challenging using in vivo approaches. Computational modeling is a powerful engineering tool used to access biomechanical information on tissue failure that cannot be obtained otherwise using traditional motion capture techniques.
Methods: We extrapolated high-risk kinematics associated with ACL strain and cartilage load and stress from a previous motion analysis of 14 uninjured participants. Computational simulations were used to induce ACL failure strain and cartilage failure load, stress, and contact pressure in two age- and BMI-matched participants, one of each biological sex, during single-leg cross drop and single-leg drop tasks. The high-risk kinematics were exaggerated in 20% intervals, within their physiological range of motion, to determine if injury occurred in the models. Where injury occurred, we reported the kinematic profiles that led to tissue failure.
Findings: Our findings revealed ACL strains up to 9.99%, consistent with reported failure values in existing literature. Cartilage failure was observed in all eight analyzed conditions when increasing each high-risk kinematic parameter by 2.61 ± 0.67 times the participants' natural landing values. The kinematics associated with tissue failure included peak hip internal rotation of 22.48 ± 19.04°, peak hip abduction of 22.51 ± 9.09°, and peak lumbar rotation away from the stance limb of 11.56 ± 9.78°.
Interpretation: Our results support the ability of previously reported high-risk kinematics in the literature to induce injury and add to the literature by reporting extreme motion limits leading to injurious cases. Therefore, training programs able to modify these motions during single-leg landings may reduce the risk of ACL injury and cartilage trauma.
Keywords: ACL injury; Finite element analysis; Knee; Neuromuscular intervention; Single-leg cross drop; What-if study.
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