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      Micro Finite Element models of the vertebral body: Validation of local displacement predictions

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          Abstract

          The estimation of local and structural mechanical properties of bones with micro Finite Element (microFE) models based on Micro Computed Tomography images depends on the quality bone geometry is captured, reconstructed and modelled. The aim of this study was to validate microFE models predictions of local displacements for vertebral bodies and to evaluate the effect of the elastic tissue modulus on model’s predictions of axial forces. Four porcine thoracic vertebrae were axially compressed in situ, in a step-wise fashion and scanned at approximately 39μm resolution in preloaded and loaded conditions. A global digital volume correlation (DVC) approach was used to compute the full-field displacements. Homogeneous, isotropic and linear elastic microFE models were generated with boundary conditions assigned from the interpolated displacement field measured from the DVC. Measured and predicted local displacements were compared for the cortical and trabecular compartments in the middle of the specimens. Models were run with two different tissue moduli defined from microindentation data (12.0GPa) and a back-calculation procedure (4.6GPa). The predicted sum of axial reaction forces was compared to the experimental values for each specimen. MicroFE models predicted more than 87% of the variation in the displacement measurements (R 2 = 0.87–0.99). However, model predictions of axial forces were largely overestimated (80–369%) for a tissue modulus of 12.0GPa, whereas differences in the range 10–80% were found for a back-calculated tissue modulus. The specimen with the lowest density showed a large number of elements strained beyond yield and the highest predictive errors. This study shows that the simplest microFE models can accurately predict quantitatively the local displacements and qualitatively the strain distribution within the vertebral body, independently from the considered bone types.

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          A concordance correlation coefficient to evaluate reproducibility.

          L Lin (1989)
          A new reproducibility index is developed and studied. This index is the correlation between the two readings that fall on the 45 degree line through the origin. It is simple to use and possesses desirable properties. The statistical properties of this estimate can be satisfactorily evaluated using an inverse hyperbolic tangent transformation. A Monte Carlo experiment with 5,000 runs was performed to confirm the estimate's validity. An application using actual data is given.
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            Comparison of the elastic and yield properties of human femoral trabecular and cortical bone tissue.

            The ability to determine trabecular bone tissue elastic and failure properties has biological and clinical importance. To date, trabecular tissue yield strains remain unknown due to experimental difficulties, and elastic moduli studies have reported controversial results. We hypothesized that the elastic and tensile and compressive yield properties of trabecular tissue are similar to those of cortical tissue. Effective tissue modulus and yield strains were calibrated for cadaveric human femoral neck specimens taken from 11 donors, using a combination of apparent-level mechanical testing and specimen-specific, high-resolution, nonlinear finite element modeling. The trabecular tissue properties were then compared to measured elastic modulus and tensile yield strain of human femoral diaphyseal cortical bone specimens obtained from a similar cohort of 34 donors. Cortical tissue properties were obtained by statistically eliminating the effects of vascular porosity. Results indicated that mean elastic modulus was 10% lower (p<0.05) for the trabecular tissue (18.0+/-2.8 GPa) than for the cortical tissue (19.9+/-1.8 GPa), and the 0.2% offset tensile yield strain was 15% lower for the trabecular tissue (0.62+/-0.04% vs. 0.73+/-0.05%, p<0.001). The tensile-compressive yield strength asymmetry for the trabecular tissue, 0.62 on average, was similar to values reported in the literature for cortical bone. We conclude that while the elastic modulus and yield strains for trabecular tissue are just slightly lower than those of cortical tissue, because of the cumulative effect of these differences, tissue strength is about 25% greater for cortical bone.
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              Mechanical properties of cortical bone and their relationships with age, gender, composition and microindentation properties in the elderly.

              The growing incidence of skeletal fractures poses a significant challenge to ageing societies. Since a major part of physiological loading in the lower limbs is carried by cortical bone, it would be desirable to better understand the structure-mechanical property relationships and scale effects in this tissue. This study aimed at assessing whether microindentation properties combined with chemical and morphological information are usable to predict macroscopic elastic and strength properties in a donor- and site-matched manner. Specimens for quasi-static macroscopic tests in tension, compression, and torsion and microindentation were prepared from a cohort of 19 male and 20 female donors (46 to 99 years). All tests were performed under fully hydrated conditions. The chemical composition of the extra-cellular matrix was investigated with Raman spectroscopy. The results of the micro-mechanical tests were combined with morphological and compositional properties using a power law relationship to predict the macro-mechanical results. Microindentation properties were not gender dependent, remarkably constant over age, and showed an overall small variation with standard deviations of approximately 10 %. Similar results were obtained for chemical tissue composition. Macro-mechanical stiffness and strength were significantly related to porosity for all load cases (p<0.05). In case of macroscopic yield strain and work-to-failure this was only true in torsion and compression, respectively. The correlations of macro-mechanical with micro-mechanical, morphological, and chemical properties showed no significance for cement line density, mineralisation, or variations in the microindentation results and were dominated by porosity with a moderate explanatory power of predominately less than 50 %. The results confirm that age, with minor exceptions gender, and small variations in average mineralisation have negligible effect on the tissue microindentation properties of human lamellar bone in the elderly. Furthermore, our findings suggest that microindentation experiments are suitable to predict macroscopic mechanical properties in the elderly only on average and not on a one to one basis. The presented data may help to form a better understanding of the mechanisms of ageing in bone tissue and of the length scale at which they are active. This may be used for future prediction of fracture risk in the elderly.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                11 July 2017
                2017
                : 12
                : 7
                : e0180151
                Affiliations
                [1 ] Department of Oncology and Metabolism, University of Sheffield, Sheffield, United Kingdom
                [2 ] INSIGNEO Institute for In Silico Medicine, University of Sheffield, Sheffield, United Kingdom
                [3 ] Zeiss Global Centre, School of Engineering, University of Portsmouth, Portsmouth, United Kingdom
                [4 ] School of Engineering and Architecture, Alma Mater Studiorum–Università di Bologna, Bologna, Italy
                [5 ] Department of Mechanical Engineering, University of Sheffield, Sheffield, United Kingdom
                University of Zaragoza, SPAIN
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                • Conceptualization: MCC GT MV ED.

                • Data curation: MCC ED.

                • Formal analysis: MCC.

                • Funding acquisition: GT MV ED.

                • Investigation: MCC GT ED.

                • Methodology: MCC GT ED.

                • Project administration: MCC MV ED.

                • Resources: GT LC MV ED.

                • Software: MCC.

                • Supervision: GT MV ED.

                • Validation: MCC GT LC VD MV ED.

                • Visualization: MCC.

                • Writing – original draft: MCC.

                • Writing – review & editing: MCC GT LC VD MV ED.

                Author information
                http://orcid.org/0000-0003-1471-5077
                Article
                PONE-D-17-08175
                10.1371/journal.pone.0180151
                5507408
                28700618
                5cb90bff-ac63-42c3-9de0-74987dfb741b
                © 2017 Costa et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 1 March 2017
                : 10 June 2017
                Page count
                Figures: 5, Tables: 4, Pages: 18
                Funding
                Funded by: Sheffield Hospitals Charity (GB)
                Award ID: 141515-1
                Award Recipient :
                Funded by: Engineering and Physical Sciences Research Council (GB)
                Award ID: EP/K03877X/1
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100000288, Royal Society;
                Award ID: RG130831
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100000288, Royal Society;
                Award ID: RG150012
                Award Recipient :
                This study was partially supported by Sheffield Hospital Charity (grant number: 141515-1; ED, MV; http://www.sheffieldhospitalscharity.org.uk/), the Engineering and Physical Sciences Research Council (MultiSim project, grant number: EP/K03877X/1; MV; https://www.epsrc.ac.uk/), the Royal Society (grant number: RG130831, GT; grant number: RG150012, ED; https://royalsociety.org/), and the European Society of Biomechanics (ESB mobility award 2014; VD; https://esbiomech.org/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and Health Sciences
                Diagnostic Medicine
                Diagnostic Radiology
                Bone Imaging
                Research and Analysis Methods
                Imaging Techniques
                Diagnostic Radiology
                Bone Imaging
                Medicine and Health Sciences
                Radiology and Imaging
                Diagnostic Radiology
                Bone Imaging
                Biology and Life Sciences
                Biomechanics
                Bone and Joint Mechanics
                Biology and Life Sciences
                Anatomy
                Musculoskeletal System
                Spine
                Vertebrae
                Medicine and Health Sciences
                Anatomy
                Musculoskeletal System
                Spine
                Vertebrae
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Regression Analysis
                Linear Regression Analysis
                Physical Sciences
                Mathematics
                Statistics (Mathematics)
                Statistical Methods
                Regression Analysis
                Linear Regression Analysis
                Physical Sciences
                Mathematics
                Applied Mathematics
                Finite Element Analysis
                Medicine and Health Sciences
                Surgical and Invasive Medical Procedures
                Biopsy
                Physical Sciences
                Materials Science
                Material Properties
                Mechanical Properties
                Stiffness
                People and Places
                Population Groupings
                Age Groups
                Adults
                Custom metadata
                Data are available from https://doi.org/10.15131/shef.data.5121871.

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