The anterior cruciate ligament (ACL) is one of the most common sites of the injury in the knee joint. Over 120,000 ACL injuries occur annually in the United States, mainly affecting the young athletic population with females at a reported 2-8 fold greater risk than males. Non-contact injuries constitute the predominant mechanism of ACL injury (in over 70% of ACL injuries) occur mainly during landing following a jump and lateral cutting maneuvers. Due to long term disabilities associated with ACL injury (i.e. joint instability, pain and early development of osteoarthritis), potential loss of sports participation and high costs associated with surgical reconstruction, prevention is an appealing option to avoid the complications associated with ACL injury. While many advances have been made in terms of surgical and rehabilitation interventions, patients who have suffered ACL injury face long-term consequences that include lowered activity levels, 10-25 % incidence of re-injury 5 years after return to sport and 50-100 % incidence of osteoarthritis within 10-15 years of injury, regardless of the treatment.

Despite the substantial effort conducted on investigation of the non-contact ACL injuries, the mechanism of these injuries is not well understood. Many proposed risk factors can be categorized as anatomic, neuromuscular or biomechanical. However, just biomechanical and neuromuscular risk factors can be defined as modifiable factors, which can be modified through targeted intervention strategies in an effort to reduce the risk of injury. Identification of modifiable risk factors for ACL injury represents a major step in the reduction of the incidence of injury. A better understanding of the mechanisms underlying non-contact ACL injuries and associated risk factors, might serve to improve current prevention strategies and decrease the risk of early-onset knee osteoarthritis. This proposal aims to employ a unique combination of established ex vivo and in silico methods in order to gain an in depth understanding of knee joint biomechanics during dynamic landing (as an identified high-risk task) with a specific focus on ACL injury. The objectives of this dissertation were to investigate the non-contact ACL injury during landing in an effort to identify the potential biomechanical and neuromuscular risk factors and determine the mechanisms that lead to these injuries.

Cadaveric experiments were conducted on 20 normal, relatively young instrumented lower extremities. Following knee arthrometry, specimens were tested under a wide range of quasi-static single- and multi-axial loading conditions in order to quantify the global the biomechanical response of the tibiofemoral joint with regards to joint kinematics, ACL and MCL strains, and intra-articular cartilage pressure distribution. Subsequently, multiple bi-pedal and uni-pedal landing scenarios were simulated using a custom designed novel drop-stand. An extensive physiologic loading protocol was designed based on the identified high-risk loading factors from quasi-static characterization to simulated a wide range of landing scenarios. The findings of these cadaveric experiments were suggested the anterior tibial shear force, knee abduction moment and internal tibial rotation moment as the most critical biomechanical risk factors for the non-contact ACL injury during landing. Results further suggested the multi-planar loading condition consists of all three identified biomechanical risk factors as the most probable mechanism for non-contact ACL injuries. Findings finally highlighted the importance of dynamic knee valgus collapse as a primary factor contributing to these injuries (Specific Aim I).

In addition to cadaveric experiments, a detailed anatomic non-linear finite element (FE) model of the lower extremity was developed from imaging data of a healthy, young female athlete. The developed model includes bony and soft tissue structures of the knee joint such as major ligaments, trans-knee muscles, articular cartilage and menisci. The model was then extensively validated against cadaveric measurements of joint kinematics, ligament strains and cartilage pressure distribution under a wide range of static, quasi-static and dynamic loading conditions. A comprehensive FE parametric study was conducted in order to investigate the effect of trans-knee muscle loads on knee joint biomechanics and risk of ACL injury. The findings in combination with ex vivo data resulted in identification of the anterior-posterior and medial-lateral muscle force imbalances as the potential neuromuscular risk factors lead to high ACL strains and high risk of ACL injury (Specific Aim II). The developed FE model was further used to help better interpret the experimental findings in an effort to identify ACL injury biomechanical risk factors and associated mechanism (Specific Aim I).

Finally a novel framework was developed in order to customize the validated generalized FE model based on the structural properties of ACL and critical tibiofermoral anatomic factors. The customized models were then validated based subject-specific ACL strain data obtained ex vivo. It was shown that the customized models using the proposed approach lead to more realistic FE-predicted ACL strain compared to the generalized FE model. Findings suggested that this novel, validated framework can be used as a critical risk-screening tool in the large-scale clinical assessment of ACL injury risk among individuals (Specific Aim III).