Hewett, Timothy E.

Background: Knee abduction moment during landing has been associated with anterior cruciate ligament (ACL) injury. However, accurately capturing this measurement is expensive and technically rigorous. Less complex variables that lend themselves to easier clinical integration are desirable. Purpose: To corroborate in vitro cadaveric simulation and in vivo knee abduction angles from landing tasks to allow for estimation of ACL strain in live participants during a landing task. Study Design: Descriptive laboratory study. Methods: A total of 205 female high school athletes previously underwent prospective 3-dimensional motion analysis and subsequent injury tracking. Differences in knee abduction angle between those who went on to develop ACL injury and healthy controls were assessed using Student t tests and receiver operating characteristic analysis. A total of 11 cadaveric specimens underwent mechanical impact simulation while instrumented to record ACL strain and knee abduction angle. Pearson correlation coefficients were calculated between these variables. The resultant linear regression model was used to estimate ACL strain in the 205 high school athletes based on their knee abduction angles. Results: Knee abduction angle was greater for athletes who went on to develop injury than for healthy controls ( P < .01). Knee abduction angle at initial contact predicted ACL injury status with 78% sensitivity and 83% specificity, with a threshold of 4.6° of knee abduction. ACL strain was significantly correlated with knee abduction angle during cadaveric simulation ( P < .01). Subsequent estimates of peak ACL strain in the high school athletes were greater for those who went on to injury (7.7-8.1% ± 1.5%) than for healthy controls (4.1-4.5% ± 3.6%) ( P < .01). Conclusion: Knee abduction angle exhibited comparable reliability with knee abduction moment for ACL injury risk identification. Cadaveric simulation data can be extrapolated to estimate in vivo ACL strain. Athletes who went on to ACL injury exhibited greater knee abduction and greater ACL strain than did healthy controls during landing. Clinical Relevance: These important associations between the in vivo and cadaveric environments allow clinicians to estimate peak ACL strain from observed knee abduction angles. Neuromuscular control of knee abduction angle during dynamic tasks is imperative for knee joint health. The present associations are an important step toward the establishment of a minimal clinically important difference value for ACL strain during landing.

Background: The most commonly damaged structures of the knee are the anterior cruciate ligament (ACL), medial collateral ligament (MCL), and menisci. Given that these injuries present as either isolated or concomitant, it follows that these events are driven by specific mechanics versus coincidence. This study was designed to investigate the multiplanar mechanisms and determine the important biomechanical and demographic factors that contribute to classification of the injury outcome. Hypothesis: Linear discriminant analysis (LDA) would accurately classify each injury type generated by the mechanical impact simulator based on biomechanical input variables (ie, ligament strain and knee kinetics). Study Design: Controlled laboratory study. Methods: In vivo kinetics and kinematics of 42 healthy, athletic participants were measured to determine stratification of injury risk (ie, low, medium, and high) in 3 degrees of knee forces/moments (knee abduction moment, anterior tibial shear, and internal tibial rotation). These stratified kinetic values were input into a cadaveric impact simulator to assess ligamentous strain and knee kinetics during a simulated landing task. Uniaxial and multiaxial load cells and implanted strain sensors were used to collect mechanical data for analysis. LDA was used to determine the ability to classify injury outcome by demographic and biomechanical input variables. Results: From LDA, a 5-factor model (Entropy R 2 = 0.26) demonstrated an area under the receiver operating characteristic curve (AUC) for all 5 injury outcomes (ACL, MCL, ACL+MCL, ACL+MCL+meniscus, ACL+meniscus) of 0.74 or higher, with “good” prediction for 4 of 5 injury classifications. A 10-factor model (Entropy R 2 = 0.66) improved the AUC to 0.86 or higher, with “excellent” prediction for 5 injury classifications. The 15-factor model (Entropy R 2 = 0.85), produced 94.1% accuracy with the AUC 0.98 or higher for all 5 injury classifications. Conclusion: Use of LDA accurately predicted the outcome of knee injury from kinetic data from cadaveric simulations with the use of a mechanical impact simulator at 25° of knee flexion. Thus, with clinically relevant kinetics, it is possible to determine clinical risk of injury and also the likely presentation of singular or concomitant knee injury. Clinical Relevance: LDA demonstrates that injury outcomes are largely characterized by specific mechanics that can distinguish ACL, MCL, and medial meniscal injury. Furthermore, as the mechanics of injury are better understood, improved interventional prehabilitation can be designed to reduce these injuries.

Anterior cruciate ligament (ACL) injury videos estimate that rupture occurs within 50 milliseconds of initial contact, but are limited by imprecise timing and nondirect data acquisition. The objective of this study was to precisely quantify the timing associated with ligament strain during simulated landing and injury events. The hypotheses tested were that the timing of peak strain following initial contact would differ between ligaments and that peak strain timing would be independent of the injury-risk profile emulated during simulated landing. A mechanical impact simulator was used to perform landing simulations based on various injury-risk profiles that were applied to each specimen in a block-randomized order. The ACL and medial collateral ligament were instrumented with strain gauges that recorded continuously. The data from 35 lower-extremity specimens were included for analysis. Analysis of variance and Kruskal–Wallis tests were used to determine the differences between timing and profiles. The mean time to peak strain was 53 (24) milliseconds for the ACL and 58 (35) milliseconds for the medial collateral ligament. The time to peak ACL strain ranged from 48 to 61 milliseconds, but the timing differences were not significant between profiles. Strain timing was independent of injury-risk profile. Noncontact ACL injuries are expected to occur between 0 and 61 milliseconds after initial contact. Both ligaments reached peak strain within the same time frame.

Context Neck pain (NP), neck injuries, and concussions are more prevalent in female athletes than in their male counterparts. Females exhibit less neck girth, strength, and stiffness against a perturbation. As part of the clinical examination for individuals with NP, ultrasound (US)–based imaging of the cervical muscles has become common. Muscle size or thickness and stiffness can be measured with US-based B-mode and shear-wave elastography (SWE), respectively. Information on reliability, normative values, and sex differences based on US-based muscle size or thickness and stiffness in young and athletic individuals is limited. Objective To evaluate sex differences in US-based muscle size or thickness and biomechanical properties of the cervical-flexor and -extensor muscles. Design Cross-sectional study. Setting Laboratory. Patients or Other Participants A total of 13 women (age = 23.7 ± 1.9 years, height = 167.1 ± 6.1 cm, mass = 63.8 ± 5.6 kg) and 11 men (age = 25.6 ± 4.9 years, height = 178.7 ± 8.3 cm, mass = 78.9 ± 12.0 kg). Main Outcome Measure(s) The same examiner collected all measures, using US B-mode to scan the cross-sectional area and thickness of the longus colli (LC), sternocleidomastoid (SCM), cervical-extensor muscles, and upper trapezius (UT) muscle. The US SWE-mode was used to measure the stiffness of the SCM and UT. Independent t tests or Mann-Whitney U tests were calculated to determine sex differences. The intraclass correlation coefficient (ICC) measured intrarater test-retest reliability. Results Men had thicker SCMs than women (P = .01). No sex differences were present for longus colli cross-sectional area, cervical-extensor muscle thickness, or UT thickness (P &gt; .05). In addition, no sex differences were evident for SCM (P = .302) or UT (P = .703) SWE stiffness. Reliability was good to excellent (ICC = 0.715–0.890) except for SCM SWE stiffness (ICC = 0.554). Conclusions The only sex difference was in SCM thickness. However, smaller SCMs in women did not result in less SCM SWE stiffness. We provided normative values for US-based imaging of the cervical-flexor and -extensor muscles in young and athletic men and women.

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.

Objective: Faulty neuromuscular and biomechanical deficits of the knee are nearly ubiquitous in athletes after anterior cruciate ligament (ACL) reconstruction (ACLR). Knee biomechanical deficits are directly associated with an increased risk of second ACL injury, which typically occurs during a sports-related movement on a single limb. To date, the biomechanical effects of a neuromuscular training (NMT) program on knee biomechanics during a single-leg landing task have not been investigated. Design: Prospective Cohort Study. Setting: Controlled laboratory setting. Participants: Eighteen ACLR and 10 control athletes. Interventions: Neuromuscular training. Main Outcome Measures: Knee kinematics and kinetics. Results: There were no significant interactions of session and limb (P > 0.05) for the athletes with ACLR after training. However, there were several significant main effects of session (P < 0.05) for knee kinematics and kinetics during the single-leg landing task. After training, the athletes with ACLR landed with greater knee flexion angles, decreased knee abduction angles, increased knee flexion range of motion, and decreased knee excursion. Also, the ACLR athletes landed with lower knee flexion moments, greater knee adduction moments, and lower peak vertical ground reaction force. Post-training comparison of the ACLR and control cohorts found no significant interactions of group and limb (P > 0.05) and only a significant main effect of group (P < 0.05) for frontal plane knee angle at initial contact. The athletes with ACLR landed with greater knee adduction angles than the control group. Conclusions: Deficits in knee biomechanics that are associated with an increased risk of ACL injury are attenuated after completion of this NMT program.