Journal article
Bone mineral density and donor age are not predictive of femoral ring allograft bone mechanical strength
Journal of orthopaedic research, Vol.32(10), pp.1271-1276
10/2014
Handle:
https://hdl.handle.net/2376/106459
PMID: 25041905
Abstract
While metal or plastic interbody spinal fusion devices are manufactured to appropriate mechanical standards, mechanical properties of commercially prepared structural allograft bone remain relatively unassessed. Robust models predicting compressive load to failure of structural allograft bone based on easily measured variables would be useful. Three hundred twenty seven femoral rings from 34 cadaver femora were tested to failure in axial compression. Predictive variables included age, gender, bone mineral density (BMD), position along femoral shaft, maximum/minimum wall thickness, outer/inner diameter, and area. We used support vector regression and 10-fold cross-validation to develop robust nonlinear predictive models for load to failure. Model performance was measured by the root-mean-squared-deviation (RMSD) and correlation coefficients (r). A polynomial model using all variables had RMSD = 7.92, r = 0.84, indicating excellent performance. A model using all variables except BMD was essentially unchanged (RMSD = 8.12, r = 0.83). Eliminating both age and BMD produced a model with RMSD = 8.41, r = 0.82, again essentially unchanged. Compressive strength of structural allograft bone can be estimated using easily measured geometric parameters, without including BMD or age. As DEXA is costly and cumbersome, and setting upper age-limits for potential donors reduces the supply, our results may prove helpful to increase the quality and availability of structural allograft.
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Details
- Title
- Bone mineral density and donor age are not predictive of femoral ring allograft bone mechanical strength
- Creators
- Bala Krishnamoorthy - Department of Mathematics, Washington State University, Pullman, WashingtonBrian K BayRobert A Hart
- Publication Details
- Journal of orthopaedic research, Vol.32(10), pp.1271-1276
- Academic Unit
- Mathematics and Statistics, Department of
- Publisher
- United States
- Identifiers
- 99900546897101842
- Language
- English
- Resource Type
- Journal article