Planar biaxial extension of the lumbar facet capsular ligament reveals significant in-plane shear forces

Amy A. Claeson, Victor H. Barocas

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

The lumbar facet capsular ligament (FCL) articulates with six degrees of freedom during spinal motions of flexion/extension, lateral bending, and axial rotation. The lumbar FCL is composed of highly aligned collagen fiber bundles on the posterior surface (oriented primarily laterally between the rigid articular facets) and irregularly oriented elastin on the anterior surface. Because the FCL is a capsule, it has multiple insertion sites across the lumbar facet joint, which, along with its material structure, give rise to complicated deformations in vivo. We performed planar equibiaxial mechanical tests on excised healthy cadaveric lumbar FCLs (n=6) to extract normal and shear reaction forces, and fit sample-specific two-fiber-family finite element models to the experimental force data. An eight-parameter anisotropic, hyperelastic model was used. Shear forces at maximum extension (mean values of 1.68 N and 3.01 N in the two directions) were of comparable magnitude to the normal forces perpendicular to the aligned collagen fiber bundles (4.67 N) but smaller than normal forces in the fiber direction (16.11 N). Inclusion of the experimental shear forces in the model optimization yielded fits with highly aligned fibers oriented at a specific angle across all samples, typically with one fiber population aligned nearly horizontally and the other at an oblique angle. Conversely, models fit to only the normal force data resulted in a broad range of fiber angles with low specificity. We found that shear forces generated through planar equibiaxial extension aided the model fit in describing the anisotropic nature of the FCL surface.

Original languageEnglish (US)
Pages (from-to)127-136
Number of pages10
JournalJournal of the Mechanical Behavior of Biomedical Materials
Volume65
DOIs
StatePublished - Jan 1 2017

Bibliographical note

Funding Information:
This work was supported by the National Institutes of Health ( U01 EB016638 and T32 AR050938 ). The authors acknowledge the Minnesota Supercomputing Institute (MSI) at the University of Minnesota for providing resources that contributed to the research results reported within this paper. The assistance of the FEBio staff is gratefully acknowledged.

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