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      Effect of size and location of simulated lytic lesions on the structural properties of human vertebral bodies, a micro-finite element study

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          Abstract

          Currently, the Spinal Instability Neoplastic Score system is used in clinics to evaluate the risk of fracture in patients with spinal metastases. This method, however, does not always provide a clear guideline due to the complexity in accounting for the effect of metastatic lesions on vertebral stability. The aim of this study was to use a validated micro Finite Element (microFE) modelling approach to analyse the effect of the size and location of lytic metastases on the mechanical properties of human vertebral bodies. Micro Computed Tomography based microFE models were generated with and without lytic lesions simulated as holes within a human vertebral body. Single and multiple lytic lesions were simulated with four different sizes and in five different locations. Bone was assumed homogenous, isotropic and linear elastic, and each vertebra was loaded in axial compression. It was observed that the size of lytic lesions was linearly related with the reduction in structural properties of the vertebral body (reduction of stiffness between 3% and 30% for lesion volume between 4% and 35%). The location of lytic lesions did not show a clear effect on predicted structural properties. Single or multiple lesions with the same volume provided similar results. Locally, there was a homogeneous distribution of axial principal strains among the models with and without lytic lesions. This study highlights the potential of microFE models to study the effect of lesions on the mechanical properties of the human vertebral body.

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          Highlights

          • MicroFE models can show the effect of lytic lesions on vertebral properties.

          • The size of the lesions was more critical than the location of the lesions.

          • Lesions affecting the cortical shell had a larger effect on the local strains.

          • Multiple lesions showed a similar effect to single lesions.

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          Micro-CT based finite element models of cancellous bone predict accurately displacement once the boundary condition is well replicated: A validation study.

          Non-destructive 3D micro-computed tomography (microCT) based finite element (microFE) models are used to estimate bone mechanical properties at tissue level. However, their validation remains challenging. Recent improvements in the quantification of displacements in bone tissue biopsies subjected to staged compression, using refined Digital Volume Correlation (DVC) techniques, now provide a full field displacement information accurate enough to be used for microFE validation. In this study, three specimens (two humans and one bovine) were tested with two different experimental set-ups, and the resulting data processed with the same DVC algorithm. The resulting displacement vector field was compared to that predicted by microFE models solved with three different boundary conditions (BC): nominal force resultant, nominal displacement resultant, distributed displacement. The first two conditions were obtained directly from the measurements provided by the experimental jigs, whereas in the third case the displacement field measured by the DVC in the top and bottom layer of the specimen was applied. Results show excellent relationship between the numerical predictions (x) and the experiments (y) when using BC derived from the DVC measurements (UX: y=1.07x-0.002, RMSE: 0.001mm; UY: y=1.03x-0.001, RMSE: 0.001mm; UZ: y=x+0.0002, RMSE: 0.001 mm for bovine specimen), whereas only poor correlation was found using BCs according to experiment set-ups. In conclusion, microFE models were found to predict accurately the vectorial displacement field using interpolated displacement boundary condition from DVC measurement.
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            Validation of finite element models of the mouse tibia using digital volume correlation

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

              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 (R2 = 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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                Author and article information

                Contributors
                Journal
                Bone Rep
                Bone Rep
                Bone Reports
                Elsevier
                2352-1872
                09 March 2020
                June 2020
                09 March 2020
                : 12
                : 100257
                Affiliations
                [a ]Department of Oncology and Metabolism, Mellanby Centre for bone Research, University of Sheffield, UK
                [b ]INSIGNEO Institute for in silico Medicine, University of Sheffield, UK
                [c ]Academic Unit of Medical Education, Medical School, University of Sheffield, UK
                [d ]Department of Industrial Engineering, Alma Mater Studiorum - University of Bologna, Italy
                [e ]Medical Technology Lab, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
                Author notes
                [* ]Corresponding author at: The Pam Liversidge Building, Sir Robert Hadfield Building, Mappin Street, Sheffield S1 3JD, UK. e.dallara@ 123456sheffield.ac.uk
                Article
                S2352-1872(20)30017-6 100257
                10.1016/j.bonr.2020.100257
                7292861
                32551335
                3a5894b4-fc14-48c0-8b48-97e66bfde183
                © 2020 The Authors

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 21 October 2019
                : 7 January 2020
                : 6 March 2020
                Categories
                Articles from the Special Issue on Computational Methods in Bone Research; Edited by Dr Penny Atkins and Dr Patrik Christen

                spinal metastases,lytic lesions,biomechanics,vertebral strength,finite element,microfe,parametric analysis,mechanical properties

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