Abstract
Introduction
The human wrist is a highly complex joint, offering extensive motion across various planes. This study investigates scapholunate ligament (SLL) injuries’ impact on wrist stability and arthritis risks using cadaveric experiments and the finite element (FE) method. It aims to validate experimental findings with FE analysis results.
Method
The study utilized eight wrist specimens on a custom rig to investigate Scapho-Lunate dissociation. Contact pressure and flexion were measured using sensors. A CT-based 3D geometry reconstruction approach was used to create the geometries needed for the FE analysis. The study used the Friedman test with pairwise comparisons to assess if differences between testing conditions were statistically significant.
Result
The study found significant variations in scaphoid and lunate bone movement based on ligament condition. Full tears increased scapholunate distance in the distal-proximal direction and decreased in the medial-lateral direction. Lunate angles shifted from flexion to extension with fully torn ligaments. Conversely, the scaphoid shifted significantly from extension to flexion with full tears. A proximal movement was observed in the distal-proximal direction in all groups, with significant differences in the partial tear group. Lateral deviation of the scaphoid and lunate occurred with ligament damage, being more pronounced in the partial tear group. All groups exhibited statistically significant movement in the volar direction, with the full tear group showing the least movement. Also, radiocarpal joint and finger contact pressure and contact area were studied. Whereas the differences in contact area were not significant, scapholunate ligament tears resulted in significantly decreased finger contact pressures. FEA confirmed these findings, showing notable peak radiocarpal contact pressure differences between intact and fully torn ligaments.
Conclusion
Our study found that SLL damage alters wrist stability, potentially leading to early arthritis. The FEA model confirmed these findings, indicating the potential for the clinical use of computer models from CT scans for treatment planning.
