A wear model to predict damage of reconstructed ACL. (December 2022) - Maeztu Redin, Deyo; Caroux, Julien; Rohan, Pierre-Yves; Pillet, Hélène; Cermolacce, Alexia; Trnka, Julien; Manassero, Mathieu; Viateau, Véronique; Corté, Laurent
Abstract: Impingement with surrounding tissues is a major cause of failure of anterior cruciate ligament reconstruction. However, the complexity of the knee kinematics and anatomical variations make it difficult to predict the occurrence of contact and the extent of the resulting damage. Here we hypothesise that a description of wear between the reconstructed ligament and adjacent structures captures the in vivo damage produced with physiological loadings. To test this, we performed an in vivo study on a sheep model and investigated the role of different sources of damage: overstretching, excessive twist, excessive compression, and wear. Seven sheep underwent cranial cruciate ligament reconstruction using a tendon autograft. Necropsy observations and pull-out force measurements performed postoperatively at three months showed high variability across specimens of the extent and location of graft damage. Using 3D digital models of each stifle based on X-ray imaging and kinematics measurements, we determined the relative displacements between the graft and the surrounding bones and computed a wear index describing the work of friction forces underwent by the graft during a full flexion-extension movement. While tensile strain, angle of twist and impingement volume showed no correlation with pull-out force (ρ = −0.321, p = 0.498), the wear index showed a strong negative correlation (r = −0.902, p = 0.006). Moreover, contour maps showing the distribution of wear on the graft were consistent with the observations of damage during the necropsy. These results demonstrate that wear is a good proxy of graft damage. The proposed wear index could be used in implant design and surgery planning to minimise the risk of implant failure. Its application to sheep can provide a way to increase preclinical testing efficiency.