Full-field strain measurement during mechanical testing of the human femur at physiologically relevant strain rates.

Understanding the mechanical properties of human femora is of great importance for the development of a reliable fracture criterion aimed at assessing fracture risk. Earlier ex vivo studies have been conducted by measuring strains on a limited set of locations using strain gauges (SGs). Digital image correlation (DIC) could instead be used to reconstruct the full-field strain pattern over the surface of the femur. The objective of this study was to measure the full-field strain response of cadaver femora tested at a physiological strain rate up to fracture in a configuration resembling single stance. The three cadaver femora were cleaned from soft tissues, and a white background paint was applied with a random black speckle pattern over the anterior surface. The mechanical tests were conducted up to fracture at a constant displacement rate of 15 mm/s, and two cameras recorded the event at 3000 frames per second. DIC was performed to retrieve the full-field displacement map, from which strains were derived. A low-pass filter was applied over the measured displacements before the crack opened in order to reduce the noise level. The noise levels were assessed using a dedicated control plate. Conversely, no filtering was applied at the frames close to fracture to get the maximum resolution. The specimens showed a linear behavior of the principal strains with respect to the applied force up to fracture. The strain rate was comparable to the values available in literature from in vivo measurements during daily activities. The cracks opened and fully propagated in less than 1 ms, and small regions with high values of the major principal strains could be spotted just a few frames before the crack opened. This corroborates the hypothesis of a strain-driven fracture mechanism in human bone. The data represent a comprehensive collection of full-field strains, both at physiological load levels and up to fracture. About 10,000 points were tracked on each bone, providing superior spatial resolution compared to ∼15 measurements typically collected using SGs. These experimental data collection can be further used for validation of numerical models, and for experimental verification of bone constitutive laws and fracture criteria.

[1]  S. Lekamwasam Application of FRAX model to Sri Lankan postmenopausal women. , 2010, Journal of clinical densitometry : the official journal of the International Society for Clinical Densitometry.

[2]  T. Therneau,et al.  Association of hip strength estimates by finite‐element analysis with fractures in women and men , 2011, Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research.

[3]  P. Delmas,et al.  Structural determinants of hip fracture in elderly women: re-analysis of the data from the EPIDOS study , 2006, Osteoporosis International.

[4]  Dan Dragomir-Daescu,et al.  Validated finite element models of the proximal femur using two-dimensional projected geometry and bone density , 2011, Comput. Methods Programs Biomed..

[5]  M. Viceconti,et al.  Strain distribution in the proximal human femoral metaphysis , 2009, Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine.

[6]  F Eckstein,et al.  Mechanical strength of the proximal femur as predicted from geometric and densitometric bone properties at the lower limb versus the distal radius. , 2002, Bone.

[7]  Marco Viceconti,et al.  Mechanical testing of bones: the positive synergy of finite–element models and in vitro experiments , 2010, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[8]  Hubert W. Schreier,et al.  Image Correlation for Shape, Motion and Deformation Measurements: Basic Concepts,Theory and Applications , 2009 .

[9]  P. Cripton,et al.  Development of an inertia-driven model of sideways fall for detailed study of femur fracture mechanics. , 2013, Journal of biomechanical engineering.

[10]  J. Johnston,et al.  Direct in vivo strain measurements in human bone-a systematic literature review. , 2012, Journal of biomechanics.

[11]  Amir A Zadpoor,et al.  Patient-specific finite element modeling of bones , 2013, Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine.

[12]  A. A. Zadpoor,et al.  Repeatability of digital image correlation for measurement of surface strains in composite long bones. , 2013, Journal of biomechanics.

[13]  Niklas Zethraeus,et al.  Assessment of fracture risk , 2005, Osteoporosis International.

[14]  S. Silverman,et al.  The Utility and Limitations of FRAX: A US Perspective , 2010, Current osteoporosis reports.

[15]  Hanna Isaksson,et al.  Experimental validation of finite element model for proximal composite femur using optical measurements. , 2013, Journal of the mechanical behavior of biomedical materials.

[16]  Marcelo Coca-Perraillon,et al.  Incidence and mortality of hip fractures in the United States. , 2009, JAMA.

[17]  Alberto Leardini,et al.  Multimod Data Manager: A tool for data fusion , 2007, Comput. Methods Programs Biomed..

[18]  M. Viceconti,et al.  The human proximal femur behaves linearly elastic up to failure under physiological loading conditions. , 2011, Journal of biomechanics.

[19]  M. Blauth,et al.  Outcome in geriatric fracture patients and how it can be improved , 2010, Osteoporosis International.

[20]  T San Antonio,et al.  Orientation of orthotropic material properties in a femur FE model: a method based on the principal stresses directions. , 2012, Medical engineering & physics.

[21]  John Currey,et al.  Measurement of the Mechanical Properties of Bone: A Recent History , 2009, Clinical orthopaedics and related research.

[22]  A. A. Zadpoor,et al.  Full-field strain measurement and fracture analysis of rat femora in compression test. , 2013, Journal of biomechanics.

[23]  A. C. Taylor,et al.  Experimental validation of a finite element model of the proximal femur using digital image correlation and a composite bone model. , 2011, Journal of biomechanical engineering.

[24]  M. Grédiac,et al.  Assessment of Digital Image Correlation Measurement Errors: Methodology and Results , 2009 .

[25]  D B Burr,et al.  In vivo measurement of human tibial strains during vigorous activity. , 1996, Bone.

[26]  David Larsson,et al.  Measurement of structural anisotropy in femoral trabecular bone using clinical-resolution CT images. , 2013, Journal of biomechanics.

[27]  Marco Viceconti,et al.  Subject-specific finite element models implementing a maximum principal strain criterion are able to estimate failure risk and fracture location on human femurs tested in vitro. , 2008, Journal of biomechanics.

[28]  J. Cauley,et al.  Public health impact of osteoporosis. , 2013, The journals of gerontology. Series A, Biological sciences and medical sciences.

[29]  Marco Viceconti,et al.  Structural behaviour and strain distribution of the long bones of the human lower limbs. , 2010, Journal of biomechanics.

[30]  D. Rohrbach,et al.  Longitudinal elastic properties and porosity of cortical bone tissue vary with age in human proximal femur. , 2013, Bone.

[31]  C. C. Perry Strain-Gage Reinforcement Effects on Orthotropic Materials , 1986 .