Abstract
Background:
Anterior cruciate ligament (ACL) injuries are catastrophic events that affect athletic careers and lead to long-term degenerative knee changes. As injuries are believed to occur within the first 50 milliseconds after initial contact during a rapid deceleration task, impact simulators that rapidly deliver impulse loads to cadaveric specimens have been developed. However, no impactor has reproducibly and reliably created ACL injures in a distribution that mimics clinical observation.
Purpose:
To better understand ACL injury patterns through a cadaveric investigation that applied in vivo–measured external loads to the knee during simulated landings.
Study Design:
Controlled laboratory study.
Methods:
A novel mechanical impact simulator reproduced kinetics from in vivo–recorded drop landing tasks on 45 cadaveric knees. Specimens were exposed to a randomized order of variable knee abduction moment, anterior tibial shear, and internal tibial rotation loads before the introduction of an impulse load at the foot. This process was repeated until a hard or soft tissue injury was induced on the joint. Injuries were assessed by an orthopaedic surgeon, and ligament strain was recorded by implanted strain gauges.
Results:
The mechanical impact simulator induced ACL injuries in 87% of specimens, with medial collateral ligament (MCL) injuries in 31%. ACL tear locations were 71% femoral side, 21% midsubstance, and 9% tibial side. Peak strain before failure for ACL-injured specimens was 15.3% ± 8.7% for the ACL and 5.1% ± 5.6% for the MCL (P < .001).
Conclusion:
The ACL injuries induced by the mechanical impact simulator in the present study have provided clinically relevant in vitro representations of in vivo ACL injury patterns as cited in the literature. Additionally, current ligament strains corroborate the literature to support disproportionate loading of the ACL relative to the MCL during athletic tasks.
Clinical Relevance:
These findings indicate that the mechanical impact simulator is an appropriate model for examining independent mechanical variables, treatment techniques, and preventive interventions during athletic tasks leading up to and including an ACL injury. Accordingly, this system can be utilized to further parse out contributing factors to an ACL injury as well as assess the shortcomings of ACL reconstruction techniques in a dynamic, simulated environment that is better representative of in vivo injury scenarios.
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