Estimation of local anisotropy of plexiform bone: Comparison between depth sensing micro-indentation and Reference Point Indentation.

The recently developed Reference Point Indentation (RPI) allows the measurements of bone properties at the tissue level in vivo. The goal of this study was to compare the local anisotropic behaviour of bovine plexiform bone measured with depth sensing micro-indentation tests and with RPI. Fifteen plexiform bone specimens were extracted from a bovine femur and polished down to 0.05µm alumina paste for indentations along the axial, radial and circumferential directions (N=5 per group). Twenty-four micro-indentations (2.5µm in depth, 10% of them were excluded for testing problems) and four RPI-indentations (~50µm in depth) were performed on each sample. The local indentation modulus Eind was found to be highest for the axial direction (24.3±2.5GPa) compared to the one for the circumferential indentations (19% less stiff) and for the radial direction (30% less stiff). RPI measurements were also found to be dependent on indentation direction (p0.157). In conclusion some of the RPI measurements can provide information about local anisotropy but IDI cannot. Moreover, there is a linear relationship between most local mechanical properties measured with RPI and with micro-indentations, but IDI does not correlate with any micro-indentation measurements

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: 0.001 mm; UY: y=1.03x-0.001, RMSE: 0.001 mm; UZ: y=x+0.0002, RMSE: 0.001 mm for bovine specimen), whereas only poor correlation was found using BCs according to experiment setups. In conclusion, microFE models were found to predict accurately the vectorial displacement field using interpolated displacement boundary condition from DVC measurement

Digital volume correlation can be used to estimate local strains in natural and augmented vertebrae: An organ-level study

Digital Volume Correlation (DVC) has become popular for measuring the strain distribution inside bone structures. A number of methodological questions are still open: the reliability of DVC to investigate augmented bone tissue, the variability of the errors between different specimens of the same type, the distribution of measurement errors inside a bone, and the possible presence of preferential directions. To address these issues, five augmented and five natural porcine vertebrae were subjected to repeated zero-strain micro-CT scan (39 μm voxel size). The acquired images were processed with two independent DVC approaches (a local and a global one), considering different computation sub-volume sizes, in order to assess the strain measurement uncertainties. The systematic errors generally ranged within ±100 microstrain and did not depend on the computational sub-volume. The random error was higher than 1000 microstrain for the smallest sub-volume and rapidly decreased: with a sub-volume of 48 voxels the random errors were typically within 200 microstrain for both DVC approaches. While these trends were rather consistent within the sample, two individual specimens had unpredictably larger errors. For this reason, a zero-strain check on each specimen should always be performed before any in-situ micro-CT testing campaign. This study clearly shows that, when sufficient care is dedicated to preliminary methodological work, different DVC computation approaches allow measuring the strain with a reduced overall error (approximately 200 microstrain). Therefore, DVC is a viable technique to investigate strain in the elastic regime in natural and augmented bones