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Updated: Jun 28, 2026

Athymic Rat Model for Evaluation of Engineered Anterior Cruciate Ligament Grafts
Published on: March 26, 2015
In Vitro Assessment of Knee Joint Biomechanics Using a Virtual Anterior Cruciate Ligament Reconstruction
Samira Vakili1, Thiago Vivacqua2,3, Alan Getgood4
1School of Biomedical Engineering, Western University, 1151 Richmond Street N, London, ON N6A 5B9, Canada;Western's Bone and Joint Institute, Western University, London, ON N6A 5B9, Canada.
Abstract:
Understanding the biomechanical impact of injuries and reconstruction of the anterior cruciate ligament (ACL) is vital for improving surgical treatments that restore normal knee function. The purpose of this study was to develop a technique that enables parametric analysis of the effect of the ACL reconstruction (ACLR) in cadaver knees, by replacing its contributions with that of a specimen-specific virtual ACLR that can be enabled, disabled, or modified. Twelve ACLR reconstructed knees were mounted onto a motion simulator. In situ ACLR graft forces were measured using superposition, and these data were used to design specimen-specific virtual ACLRs that would yield the same ligament force-elongation behaviors. Tests were then repeated using the virtual ACLR in place of the real ACLR and following that in ACL deficient knee by disabling the virtual ACLR. In comparison to the ACL deficient state, the virtual ACLRs were able to restore knee stability to the same extent as real ACLRs. The average differences between the anterior tibial translation (ATT) of the virtual ACLR versus the real ACLR were +1.6 ± 0.9 mm (p = 0.4), +2.1 ± 0.4 mm (p = 0.4), and +1.0 ± 0.9 mm (p = 0.4) during Anterior drawer, Lachman and Pivot-shift tests, respectively, which is small in comparison to the full ATT range of motion (ROM) of these knees. Therefore, we conclude that a virtual ACLR can be used in place of real ACLR during biomechanical testing of cadaveric knees. This capability opens the door for future studies that can leverage parameterization of the ACLR for surgical design optimization.
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