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Enhancing the Biofidelity of an Upper Cervical Spine Finite Element Model Within the Physiologic Range of Motion and Its Effect on the Full Ligamentous Neck Model Response. | LitMetric

Enhancing the Biofidelity of an Upper Cervical Spine Finite Element Model Within the Physiologic Range of Motion and Its Effect on the Full Ligamentous Neck Model Response.

J Biomech Eng

Department of Mechanical and Mechatronics Engineering, University of Waterloo, 200 University Avenue West, Waterloo, ON N2 L 3G1, Canada.

Published: January 2023

Contemporary finite element (FE) neck models are developed in a neutral posture; however, evaluation of injury risk for out-of-position impacts requires neck model repositioning to non-neutral postures, with much of the motion occurring in the upper cervical spine (UCS). Current neck models demonstrate a limitation in predicting the intervertebral motions within the UCS within the range of motion, while recent studies have highlighted the importance of including the tissue strains resulting from repositioning FE neck models to predict injury risk. In the current study, the ligamentous cervical spine from a contemporary neck model (GHBMC M50 v4.5) was evaluated in flexion, extension, and axial rotation by applying moments from 0 to 1.5 N·m in 0.5 N·m increments, as reported in experimental studies and corresponding to the physiologic loading of the UCS. Enhancements to the UCS model were identified, including the C0-C1 joint-space and alar ligament orientation. Following geometric enhancements, an analysis was undertaken to determine the UCS ligament laxities, using a sensitivity study followed by an optimization study. The ligament laxities were optimized to UCS-level experimental data from the literature. The mean percent difference between UCS model response and experimental data improved from 55% to 23% with enhancements. The enhanced UCS model was integrated with a ligamentous cervical spine (LS) model and assessed with independent experimental data. The mean percent difference between the LS model and the experimental data improved from 46% to 35% with the integration of the enhanced UCS model.

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Source
http://dx.doi.org/10.1115/1.4055037DOI Listing

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