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Use of a statistical model of the whole femur in a large scale, multi-model study of femoral neck fracture risk

Use of a statistical model of the whole femur in a large scale, multi-model study of femoral neck fracture risk
Use of a statistical model of the whole femur in a large scale, multi-model study of femoral neck fracture risk
Interpatient variability is often overlooked in orthopaedic computational studies due to the substantial challenges involved in sourcing and generating large numbers of bone models. A statistical model of the whole femur incorporating both geometric and material property variation was developed as a potential solution to this problem. The statistical model was constructed using principal component analysis, applied to 21 individual computer tomography scans. To test the ability of the statistical model to generate realistic, unique, finite element (FE) femur models it was used as a source of 1000 femurs to drive a study on femoral neck fracture risk. The study simulated the impact of an oblique fall to the side, a scenario known to account for a large proportion of hip fractures in the elderly and have a lower fracture load than alternative loading approaches. FE model generation, application of subject specific loading and boundary conditions, FE processing and post processing of the solutions were completed automatically. The generated models were within the bounds of the training data used to create the statistical model with a high mesh quality, able to be used directly by the FE solver without remeshing. The results indicated that 28 of the 1000 femurs were at highest risk of fracture. Closer analysis revealed the percentage of cortical bone in the proximal femur to be a crucial differentiator between the failed and non-failed groups. The likely fracture location was indicated to be intertrochantic. Comparison to previous computational, clinical and experimental work revealed support for these findings.
0021-9290
2171-2176
Bryan, Rebecca
58870a3c-49f9-4473-8ba6-6518e4fa5328
Nair, Prasanth B.
d4d61705-bc97-478e-9e11-bcef6683afe7
Taylor, Mark
e368bda3-6ca5-4178-80e9-41a689badeeb
Bryan, Rebecca
58870a3c-49f9-4473-8ba6-6518e4fa5328
Nair, Prasanth B.
d4d61705-bc97-478e-9e11-bcef6683afe7
Taylor, Mark
e368bda3-6ca5-4178-80e9-41a689badeeb

Bryan, Rebecca, Nair, Prasanth B. and Taylor, Mark (2009) Use of a statistical model of the whole femur in a large scale, multi-model study of femoral neck fracture risk. Journal of Biomechanics, 42 (13), 2171-2176. (doi:10.1016/j.jbiomech.2009.05.038).

Record type: Article

Abstract

Interpatient variability is often overlooked in orthopaedic computational studies due to the substantial challenges involved in sourcing and generating large numbers of bone models. A statistical model of the whole femur incorporating both geometric and material property variation was developed as a potential solution to this problem. The statistical model was constructed using principal component analysis, applied to 21 individual computer tomography scans. To test the ability of the statistical model to generate realistic, unique, finite element (FE) femur models it was used as a source of 1000 femurs to drive a study on femoral neck fracture risk. The study simulated the impact of an oblique fall to the side, a scenario known to account for a large proportion of hip fractures in the elderly and have a lower fracture load than alternative loading approaches. FE model generation, application of subject specific loading and boundary conditions, FE processing and post processing of the solutions were completed automatically. The generated models were within the bounds of the training data used to create the statistical model with a high mesh quality, able to be used directly by the FE solver without remeshing. The results indicated that 28 of the 1000 femurs were at highest risk of fracture. Closer analysis revealed the percentage of cortical bone in the proximal femur to be a crucial differentiator between the failed and non-failed groups. The likely fracture location was indicated to be intertrochantic. Comparison to previous computational, clinical and experimental work revealed support for these findings.

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Published date: 18 September 2009

Identifiers

Local EPrints ID: 71603
URI: https://eprints.soton.ac.uk/id/eprint/71603
ISSN: 0021-9290
PURE UUID: e6ab5f2c-fcdb-4b89-a705-07a5e80475e4

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Date deposited: 16 Dec 2009
Last modified: 19 Jul 2019 23:44

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Contributors

Author: Rebecca Bryan
Author: Prasanth B. Nair
Author: Mark Taylor

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