Fatigue-driven compliance increase and collagen unravelling in mechanically tested anterior cruciate ligament

Regenerative Anterior Cruciate Ligament Healing in Youth and Adolescent Athletes: The Emerging Age of Recovery Science

Anterior cruciate ligament (ACL) injuries mainly arise from non-contact mechanisms during sport performance, with most injuries occurring among youth or adolescent-age athletes, particularly females. The growing popularity of elite-level sport training has increased the total volume, intensity and frequency of exercise and competition loading to levels that may exceed natural healing capacity. Growing evidence suggests that the prevailing mechanism that leads to non-contact ACL injury from sudden mechanical fatigue failure may be accumulated microtrauma. Given the consequences of primary ACL injury on the future health and quality of life of youth and adolescent athletes, the objective of this review is to identify key "recovery science" factors that can help prevent these injuries. Recovery science is any aspect of sports training (type, volume, intensity, frequency), nutrition, and sleep/rest or other therapeutic modalities that may prevent the accumulated microtrauma that precedes non-contact ACL injury from sudden mechanical fatigue failure. This review discusses ACL injury epidemiology, current surgical efficacy, the native ACL vascular network, regional ACL histological complexities such as the entheses and crimp patterns, extracellular matrix remodeling, the concept of causal histogenesis, exercise dosage and ligament metabolism, central nervous system reorganization post-ACL rupture, homeostasis regulation, nutrition, sleep and the autonomic nervous system. Based on this information, now may be a good time to re-think primary ACL injury prevention strategies with greater use of modified sport training, improved active recovery that includes well-planned nutrition, and healthy sleep patterns. The scientific rationale behind the efficacy of regenerative orthobiologics and concomitant therapies for primary ACL injury prevention in youth and adolescent athletes are also discussed.

Plastic and elastic biomechanical properties of anterior cruciate ligament autografts

BACKGROUND

Anterior cruciate ligament (ACL) rupture is a common orthopedic injury, occurring in roughly 68.6 per 100,000 persons annually, with the primary treatment option being ACL reconstruction. However, debate remains about the appropriate graft type for restoring the native biomechanical properties of the knee. Furthermore, plastic graft elongation may promote increased knee laxity and instability without rupture. This study aims to investigate the plastic properties of common ACL-R graft options.

METHODS

Patellar tendon (PT), hamstring tendon (HT), and quadriceps tendon (QT) grafts were harvested from 11 cadaveric knees (6 male and 5 female) with a mean age of 71(range 55-81). All grafts were mechanically tested under uniaxial tension until failure to determine each graft's elastic and plastic biomechanical properties.

RESULTS

Mechanically, the QT graft was the weakest, exhibiting the lowest failure force and the lowest failure stress (QT < HT, p = 0.032). The PT was the stiffest of the grafts, having a significantly higher stiffness (PT > QT, p = 0.0002) and Young's modulus (PT > QT, p = 0.001; PT > HT, p = 0.041). The HT graft had the highest plastic elongation at 4.01 ± 1.32 mm (HT > PT, p = 0.002). The post-yield behavior of the HT tendon shows increased energy storage capabilities with the highest plastic energy storage (HT > QT, p = 0.012) and the highest toughness (HT > QT, p = 0.032).

CONCLUSION

Our study agrees with prior studies indicating that the failure load of all grafts is above the requirements for everyday activities. However, grafts may be susceptible to yielding before failure during daily activities. This may result in the eventual loss of functionality for the neo-ACL, resulting in increased knee laxity and instability.

Predicting Leg Forces and Knee Moments Using Inertial Measurement Units: An In Vitro Study

We compared the ability of seven machine learning algorithms to use wearable inertial measurement unit (IMU) data to identify the severe knee loading cycles known to induce microdamage associated with anterior cruciate ligament rupture. Sixteen cadaveric knee specimens, dissected free of skin and muscle, were mounted in a rig simulating standardized jump landings. One IMU was located above and the other below the knee, the applied three-dimensional action and reaction loads were measured via six-axis load cells, and the three-dimensional knee kinematics were also recorded by a laboratory motion capture system. Machine learning algorithms were used to predict the knee moments and the tibial and femur vertical forces; 13 knees were utilized for training each model, while three were used for testing its accuracy (i.e., normalized root-mean-square error) and reliability (Bland-Altman limits of agreement). The results showed the models predicted force and knee moment values with acceptable levels of error and, although several models exhibited some form of bias, acceptable reliability. Further research will be needed to determine whether these types of models can be modified to attenuate the inevitable in vivo soft tissue motion artifact associated with highly dynamic activities like jump landings.