Contribution of Shape Features to Intradiscal Pressure and Facets Contact Pressure in L4/L5 FSUs: An In-Silico Study

• Published in: Annals of biomedical engineering 2023-01, Vol.51 (1), p.174-188
• Main Authors: Kassab-Bachi, Amin, Ravikumar, Nishant, Wilcox, Ruth K., Frangi, Alejandro F., Taylor, Zeike A.
• Format: Article
• Language: English
• Subjects: Axial compression; Biochemistry; Bioengineering; Biological and Medical Physics; Biomechanical Phenomena; Biomechanics; Biomedical and Life Sciences; Biomedical engineering; Biomedical Engineering and Bioengineering; Biomedicine; Biophysics; Classical Mechanics; Compression; Contact pressure; Finite Element Analysis; Finite element method; Geometry; Humans; Influence; Intervertebral Disc - physiology; Investigations; Lumbar Vertebrae; Mathematical models; Mechanical engineering; Models, Statistical; Parameterization; Pressure; Principal components analysis; Range of Motion, Articular; S.I. : Modeling for Advancing Regulatory Science; Spine
• ISSN: 0090-6964; 1573-9686
• DOI: 10.1007/s10439-022-03072-2

Finite element models (FEMs) of the spine commonly use a limited number of simplified geometries. Nevertheless, the geometric features of the spine are important in determining its FEM outcomes. The link between a spinal segment’s shape and its biomechanical response has been studied, but the co-variances of the shape features have been omitted. We used a principal component (PCA)-based statistical shape modelling (SSM) approach to investigate the contribution of shape features to the intradiscal pressure (IDP) and the facets contact pressure (FCP) in a cohort of synthetic L4/L5 functional spinal units under axial compression. We quantified the uncertainty in the FEM results, and the contribution of individual shape modes to these results. This parameterisation approach is able to capture the variability in the correlated anatomical features in a real population and sample plausible synthetic geometries. The first shape mode ( ϕ 1 ) explained 22.6% of the shape variation in the subject-specific cohort used to train the SSM, and had the largest correlation with, and contribution to IDP (17%) and FCP (11%). The largest geometric variation in ( ϕ 1 ) was in the annulus-nucleus ratio.