Can lateral tenodesis improve the rotational stability of the ACL reconstruction? A finite element analysis.

One of the most common knee injuries is the Anterior Cruciate Ligament (ACL) rupture with severe implications on knee stability. The usual treatment is the ACL Reconstruction (ACLR) surgery where the surgeon replaces the torn ligament with a graft in an effort to restore knee kinematics. In case of excessive rotatory instability, Lateral Extra-Articular Tenodesis (LET) can be performed in combination with ACLR. Additionally, LET appears to reduce ACLR graft forces minimizing graft failure chances. However, there are concerns about overconstraining physiological rotation. To gain insight in this controversial topic, we developed an automatic, open-source tool to create a series of Finite Element (FE) models attempting to investigate the interactions of ACLR and LET through simulation. We started by creating a validated model of the healthy knee joint that served as reference for subsequent FE simulations. Then, we created FE models of standalone ACLR and combined ACLR-LET. Each model was assessed by applying a loading profile that resembles the reduction phase of the Pivot-Shift clinical exam. We measured the External Tibia Rotation (ETR), the Posterior Tibia Translation (PTT) of the lateral tibial compartment, and the ACLR graft stress developed around the femoral tunnel insertion site. We observed the following: a) LET reduces ETR and PTT compared to isolated ACLR, b) combined ACLR-LET is more sensitive to LET graft pretension with lower values showcasing performance closer to the healthy joint, c) LET reduces ACLR graft forces for the same pretension values, d) LET exhibits significant overconstraint for higher pretension values. In general, these findings are in agreement with relevant clinical studies and accentuate the potential of the developed framework as a tool that can assist orthopaedists during surgery planning. We provide open access for the FE models of this study to enhance research transparency, reproducibility and extensibility.

Predictive simulation of single-leg landing scenarios for ACL injury risk factors evaluation.

The Anterior Cruciate Ligament (ACL) rupture is a very common knee injury during sport activities. Landing after jump is one of the most prominent human body movements that can lead to such an injury. The landing-related ACL injury risk factors have been in the spotlight of research interest. Over the years, researchers and clinicians acquire knowledge about human movement during daily-life activities by organizing complex in vivo studies that feature high complexity, costs and technical and most importantly physical challenges. In an attempt to overcome these limitations, this paper introduces a computational modeling and simulation pipeline that aims to predict and identify key parameters of interest that are related to ACL injury during single-leg landings. We examined the following conditions: a) landing height, b) hip internal and external rotation, c) lumbar forward and backward leaning, d) lumbar medial and lateral bending, e) muscle forces permutations and f) effort goal weight. Identified on related research studies, we evaluated the following risk factors: vertical Ground Reaction Force (vGRF), knee joint Anterior force (AF), Medial force (MF), Compressive force (CF), Abduction moment (AbdM), Internal rotation moment (IRM), quadricep and hamstring muscle forces and Quadriceps/Hamstrings force ratio (Q/H force ratio). Our study clearly demonstrated that ACL injury is a rather complicated mechanism with many associated risk factors which are evidently correlated. Nevertheless, the results were mostly in agreement with other research studies regarding the ACL risk factors. The presented pipeline showcased promising potential of predictive simulations to evaluate different aspects of complicated phenomena, such as the ACL injury.

Evaluation of anterior cruciate ligament surgical reconstruction through finite element analysis.

Anterior cruciate ligament (ACL) tear is one of the most common knee injuries. The ACL reconstruction surgery aims to restore healthy knee function by replacing the injured ligament with a graft. Proper selection of the optimal surgery parameters is a complex task. To this end, we developed an automated modeling framework that accepts subject-specific geometries and produces finite element knee models incorporating different surgical techniques. Initially, we developed a reference model of the intact knee, validated with data provided by the Open Knee(s) project. This helped us evaluate the effectiveness of estimating ligament stiffness directly from MRI. Next, we performed a plethora of "what-if" simulations, comparing responses with the reference model. We found that (a) increasing graft pretension and radius reduces relative knee displacement, (b) the correlation of graft radius and tension should not be neglected, (c) graft fixation angle of 20[Formula: see text] can reduce knee laxity, and (d) single-versus double-bundle techniques demonstrate comparable performance in restraining knee translation. In most cases, these findings confirm reported values from comparative clinical studies. The numerical models are made publicly available, allowing for experimental reuse and lowering the barriers for meta-studies. The modeling approach proposed here can complement orthopedic surgeons in their decision-making.