NDLI: A subject-specific finite element model of the anterior cruciate ligament

Content Provider	IEEE Xplore Digital Library
Author	Zhang, Xiaoyan Jiang, Guotai Wu, Changfu Woo, Savio L-Y.
Copyright Year	2008
Description	Author affiliation: Musculoskeletal Research Center, Department of Bioengineering, University of Pittsburgh, PA 15219, USA (Wu, Changfu; Woo, Savio L-Y.) \|\| School of Life Science and Technology, Tongji University, Shanghai, 200092 China (Zhang, Xiaoyan; Jiang, Guotai)
Abstract	The anterior cruciate ligament (ACL) is commonly injured. The stress distribution in the ACL is the key for understanding its function and injury mechanism, as well as for developing optimal surgical reconstruction protocols. In this study, a three-dimensional subject-specific finite element model of human ACL was developed. Bony geometries were reconstructed from CT scan images, while the geometry of the ACL and the orientation of its fiber bundles were measured via a mechanical digitizer. A transversely isotropic, hyperelastic, and nearly incompressible constitutive model was implemented to describe the mechanical properties of the ACL. A 134N anterior tibial load were applied to a cadaveric knee specimen at full extension, 30°, and 60° of flexion by a 6-DOF Robotic/Universal Force-moment Sensor (UFS) system, which was also used to measure the ACL resultant force. Knee kinematics was collected by digitizing two registration blocks attached to the femur and the tibia, respectively, and was input into the FE model as boundary conditions. The resultant force of the ACL calculated by the FE model was comparable to the experimental data, with the error within 10%, thus validated the model. The FE results showed that the average stress in the ACL was between the range 4.7–5.0MPa, with a peak stress between the range 9.8–10.9MPa, which shifted from the posterior lateral (PL) bundle to the anterior medial (AM) bundle as the knee flexed.
Starting Page	891
Ending Page	894
File Size	444709
Page Count	4
File Format	PDF
ISBN	9781424418145
ISSN	1557170X
DOI	10.1109/IEMBS.2008.4649297
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-08-20
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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