Statistical modelling of the whole human femur incorporating geometric and material properties

Abstract When analysing the performance of orthopaedic implants the vast majority of computational studies use either a single or limited number of bone models. The results are then extrapolated to the population as a whole, overlooking the inherent and large interpatient variability in bone quality...

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Bibliographic Details
Published in:Medical engineering & physics 2010-01, Vol.32 (1), p.57-65
Main Authors: Bryan, Rebecca, Surya Mohan, P, Hopkins, Andrew, Galloway, Francis, Taylor, Mark, Nair, Prasanth B
Format: Article
Language:English
Subjects:
Adrenals. Interrenals
Adult
Aged
Aged, 80 and over
Automation
Biological and medical sciences
Elasticity
Female
Femur
Femur - anatomy & histology
Femur - physiology
Finite Element Analysis
Fundamental and applied biological sciences. Psychology
Humans
Male
Material property
Middle Aged
Models, Anatomic
Models, Statistical
Principal Component Analysis
Radiology
Registration
Reproducibility of Results
Statistical model
Surface Properties
Vertebrates: endocrinology
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Summary:Abstract When analysing the performance of orthopaedic implants the vast majority of computational studies use either a single or limited number of bone models. The results are then extrapolated to the population as a whole, overlooking the inherent and large interpatient variability in bone quality and geometry. This paper describes the creation of a three dimensional, statistical, finite element analysis (FEA) ready model of the femur using principal component analysis. To achieve this a registration scheme based on elastic surface matching and a mesh morphing algorithm has been developed. This method is fully automated enabling registration and generation of high resolution models. The variation in both geometry and material properties was extracted from 46 computer tomography scans and captured by the statistical model. Analysis of mesh quality showed this was maintained throughout the model generation and sampling process. Reconstruction of the training femurs showed 35 eigenmodes were required for accurate reproduction. A set of unique, anatomically realistic femur models were generated using the statistical model, with a variation comparable to that seen in the population. This study illustrates a methodology with the potential to generate femur models incorporating material properties for large scale multi-femur finite element studies.
ISSN:1350-4533
1873-4030
DOI:10.1016/j.medengphy.2009.10.008