A patient-specific finite element methodology to predict damage accumulation in vertebral bodies under axial compression, sagittal flexion and combined loads

Chevalier, Y; Charlebois, M; Pahra, D; Varga, P; Heini, P; Schneider, E; Zysset, P (2008). A patient-specific finite element methodology to predict damage accumulation in vertebral bodies under axial compression, sagittal flexion and combined loads. Computer methods in biomechanics and biomedical engineering, 11(5), pp. 477-87. Abingdon, UK: Taylor & Francis 10.1080/10255840802078022

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Due to the inherent limitations of DXA, assessment of the biomechanical properties of vertebral bodies relies increasingly on CT-based finite element (FE) models, but these often use simplistic material behaviour and/or single loading cases. In this study, we applied a novel constitutive law for bone elasticity, plasticity and damage to FE models created from coarsened pQCT images of human vertebrae, and compared vertebral stiffness, strength and damage accumulation for axial compression, anterior flexion and a combination of these two cases. FE axial stiffness and strength correlated with experiments and were linearly related to flexion properties. In all loading modes, damage localised preferentially in the trabecular compartment. Damage for the combined loading was higher than cumulated damage produced by individual compression and flexion. In conclusion, this FE method predicts stiffness and strength of vertebral bodies from CT images with clinical resolution and provides insight into damage accumulation in various loading modes.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Department of Orthopaedic, Plastic and Hand Surgery (DOPH) > Clinic of Orthopaedic Surgery

UniBE Contributor:

Heini, Paul Ferdinand

ISSN:

1025-5842

ISBN:

18608338

Publisher:

Taylor & Francis

Language:

English

Submitter:

Factscience Import

Date Deposited:

04 Oct 2013 15:03

Last Modified:

04 May 2014 23:19

Publisher DOI:

10.1080/10255840802078022

PubMed ID:

18608338

Web of Science ID:

000260457900006

URI:

https://boris.unibe.ch/id/eprint/27491 (FactScience: 107893)

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