Development of subject specific finite element models of the mouse knee joint for preclinical applications

Osteoarthritis is the most common musculoskeletal disabling disease worldwide. Preclinical studies on mice are commonly performed to test new interventions. Finite element (FE) models can be used to study joint mechanics, but usually simplified geometries are used. The aim of this project was to create a realistic subject specific FE model of the mouse knee joint for the assessment of joint mechanical properties. Four different FE models of a C57Bl/6 female mouse knee joint were created based on micro-computed tomography images of specimens stained with phosphotungstic acid in order to include different features: individual cartilage layers with meniscus, individual cartilage layers without meniscus, homogeneous cartilage layers with two different thickness values, and homogeneous cartilage with same thickness for both condyles. They were all analyzed under compressive displacement and the cartilage contact pressure was compared at 0.3 N reaction force. Peak contact pressure in the femur cartilage was 25% lower in the model with subject specific cartilage compared to the simpler model with homogeneous cartilage. A much more homogeneous pressure distribution across the joint was observed in the model with meniscus, with cartilage peak pressure 5–34% lower in the two condyles compared to that with individual cartilage layers. In conclusion, modeling the meniscus and individual cartilage was found to affect the pressure distribution in the mouse knee joint under compressive load and should be included in realistic models for assessing the effect of interventions preclinically

Effect of integration time on the morphometric, densitometric and mechanical properties of the mouse tibia

Micro-Computed Tomography (microCT) images are used to measure morphometric and densitometric properties of bone, and to develop finite element (FE) models to estimate mechanical properties. However, there are concerns about the invasiveness of microCT imaging due to the X-rays ionising radiation induced by the repeated scans on the same animal. Therefore, the best compromise between radiation dose and image quality should be chosen for each preclinical application. In this study, we investigated the effect of integration time (time the bone is exposed to radiation at each rotation step during microCT imaging) on measurements performed on the mouse tibia. Four tibiae were scanned at 10.4 µm voxel size using four different procedures, characterized by decreasing integration time (from 200 ms to 50 ms) and therefore decreasing nominal radiation dose (from 513 mGy to 128 mGy). From each image, trabecular and cortical morphometric parameters, spatial distribution of bone mineral content (BMC) in the whole tibia and FE-based estimations of stiffness and strength were obtained. A high-resolution scan (4.3 µm voxel size) was used to quantify measurement errors. Integration time had the largest effect on trabecular morphometric parameters (7-28%). Lower effects were observed on cortical parameters (1-3%), BMC (1-10%) distribution, and FE-based estimations of mechanical properties (1-3%). In conclusion, the effect of integration time on image-based measurements has been quantified. This data should be considered when defining the in vivo microCT scanning protocols in order to find the best compromise between nominal radiation exposure and accuracy in the estimation of bone parameters

Research model for farm building design: General structure and physiognomic characterization phase

The design of contemporary farm buildings often subordinates architectural quality and aesthetic features to economic aspects, thus leading to poor landscape consistency and compatibility.  The research presented in this paper is based on the theoretical principle that historic rural buildings, being expression of an accumulation of empirical knowledge broadly associated with high architectural quality, have remarkable potentials to contribute with useful elements to the design of contemporary buildings, and on the awareness that the design process is also necessarily and substantially determined by technological, economic and functional variables.  The paper presents the FarmBuiLD model (Farm Building Landscape Design), a research model proposed by the authors as a tool for the analysis of the architectural characteristics of both historical and contemporary rural buildings, as well as the meta-design of new construction and transformation of contemporary rural buildings.  In particular, the work focuses on the general structure of this model and a synthesis of the main results of the critical analysis of the scientific literature aimed at identifying a set of synthetic architectural parameters suitable for its implementation, through the interpretation of the main physiognomical characteristics of rural buildings.  These parameters are not meant as a tool to obtain quantitative data to be translated into design constraints automatically; on the contrary, they are mainly considered as an interpretive-analytical tool, part of a broader knowledge framework aimed at supporting, stimulating and suggesting the design choices.Keywords: Rural building design, historical-typological consistency, landscape compatibility, architectural quality, analytical and meta-design criteria, Italian rural building heritage Citation: Tassinari P, D. Torreggiani, S. Benni, and E. Dall’Ara.  Research model for farm building design: General structure and physiognomic characterization phase.  Agric Eng Int: CIGR Journal, 2010; 12(1): 47-54

Regional nanoindentation properties in different locations on the mouse tibia from C57BL/6 and Balb/C female mice

The local spatial heterogeneity of the material properties of the cortical and trabecular bone extracted from the mouse tibia is not well-known. Nevertheless, its characterization is fundamental to be able to study comprehensively the effect of interventions and to generate computational models to predict the bone strength preclinically. The goal of this study was to evaluate the nanoindentation properties of bone tissue extracted from two different mouse strains across the tibia length and in different sectors. Left tibiae were collected from four female mice, two C57BL/6, and two Balb/C mice. Nanoindentations with maximum 6 mN load were performed on different microstructures, regions along the axis of the tibiae, and sectors (379 in total). Reduced modulus (Er) and hardness (H) were computed for each indentation. Trabecular bone of Balb/C mice was 21% stiffer than that of C57BL/6 mice (20.8 ± 4.1 GPa vs. 16.5 ± 7.1 GPa). Moreover, the proximal regions of the bones were 13–36% less stiff than the mid-shaft and distal regions of the same bones. No significant differences were found for the different sectors for Er and H for Balb/C mice. The bone in the medial sector was found to be 8–14% harder and stiffer than the bone in the anterior or posterior sectors for C57BL/6 mice. In conclusion, this study showed that the nanoindentation properties of the mouse tibia are heterogeneous across the tibia length and the trabecular bone properties are different between Balb/C and C57BL/6 mice. These results will help the research community to identify regions where to characterize the mechanical properties of the bone during preclinical optimisation of treatments for skeletal diseases

Uncertainties of synchrotron microCT-based digital volume correlation bone strain measurements under simulated deformation

Digital Volume Correlation (DVC) is used to measure internal displacements and strains in bone. Recent studies have shown that synchrotron radiation micro-computed tomography (SR-microCT) can improve the accuracy and precision of DVC. However, only zero-strain or virtually-moved test have been used to quantify the DVC uncertainties, leading to potential underestimation of the measurement errors. In this study, for the first time, the uncertainties of a global DVC approach have been evaluated on repeated SR-microCT scans of bovine cortical bone (voxel size: 1.6μm), which were virtually deformed for different magnitudes and along different directions. The results showed that systematic and random errors of the normal strain components along the deformation direction were higher than the errors along unstrained directions. The systematic percentage errors were smaller for larger virtual deformations. The random percentage error was in the order of 10% of the virtual deformation. However, higher errors were localized at the boundary of the volumes of interest, perpendicular to the deformation direction. When only the central region of the samples was considered (100 micrometers layers removed from the borders where the deformation was applied), the errors in the direction of virtual deformation were comparable to the errors in the unstrained directions. In conclusion, the method presented to estimate the uncertainties of DVC is suitable for testing anisotropic specimens as cortical bone. The good agreement between the uncertainties in measurements of strain components obtained with this approach and with the simpler zero-strain-test suggests that the latter is adequate in the tested deformation scenarios

Bone remodelling in the mouse tibia is spatio-temporally modulated by oestrogen deficiency and external mechanical loading: A combined in vivo/in silico study

Osteoporosis disrupts the healthy remodelling process in bone and affects its mechanical properties. Mechanical loading has been shown to be effective in stimulating bone formation to mitigate initial bone loss. However, no study has investigated the effects of repeated mechanical loading, with a pause of one week in between, in the mouse tibia with oestrogen deficiency. This study uses a combined experimental and computational approach, through longitudinal monitoring with micro-computed tomography, to evaluate the effects of loading on bone adaptation in the tibiae of ovariectomised (OVX) C57BL/6 mice from 14 to 22 weeks of age. Micro-FE models coupled with bone adaptation algorithms were used to estimate changes in local tissue strains due to OVX and mechanical loading, and to quantify the relationship between local strain and remodelling. The first in vivo mechanical loading increased apposition, by 50–150%, while resorption decreased by 50–60%. Both endosteal and periosteal resorption increased despite the second mechanical loading, and periosteal resorption was up to 70% higher than that after the first loading. This was found to correlate with an initial decrease in average strain energy density after the first loading, which was lower and more localised after the second loading. Predictions of bone adaptation showed that between 50 and 90% of the load-induced bone apposition is linearly strain driven at the organ-level, but resorption is more biologically driven at the local level. The results imply that a systematic increase in peak load or loading rate may be required to achieve a similar bone adaptation rate in specific regions of interests

Variability in strain distribution in the mice tibia loading model: A preliminary study using digital volume correlation

It is well known that bone has an enormous adaptive capacity to mechanical loadings, and to this extent, several in vivo studies on mouse tibia use established cyclic compressive loading protocols to investigate the effects of mechanical stimuli. In these experiments, the applied axial load is well controlled but the positioning of the hind-limb between the loading endcaps may dramatically affect the strain distribution induced on the tibia. In this study, the full field strain distribution induced by a typical in vivo setup on mouse tibiae was investigated through a combination of in situ compressive testing, µCT scanning and a global digital volume correlation (DVC) approach. The precision of the DVC method and the effect of repositioning on the strain distributions were evaluated. Acceptable uncertainties of the DVC approach for the analysis of loaded tibiae (411 ± 58µɛ) were found for nodal spacing of approximately 50 voxels (520 µm). When pairs of in situ preloaded and loaded images were registered, low variability of the strain distributions within the tibia were seen (range of mean differences in principal strains: 585-1800µɛ). On contrary, larger differences were seen after repositioning (range of mean differences in principal strains: 2500-5500µɛ). To conclude, these preliminary results on thee specimens showed that the DVC approach applied to the mouse tibia can be precise enough to evaluate local strain distributions under loads, and that repositioning of the hind-limb within the testing machine can induce large differences in the strain distributions that should be accounted for when modelling this system

Experimental Validation of DXA-based Finite Element models for prediction of femoral strength

Osteoporotic fractures are a major clinical problem and current diagnostic tools have an accuracy of only 50%. The aim of this study was to validate dual energy x-rays absorptiometry (DXA)-based Finite Element (FE) models to predict femoral strength in two loading configurations. Thirty-six pairs of fresh frozen human proximal femora were scanned with DXA and quantitative computed tomography (QCT). For each pair one femur was tested until failure in a one-legged standing configuration (STANCE) and one by replicating the positon of the femur in a fall onto the greater trochanter (SIDE). Subject-specific 2D DXA-based linear FE models and 3D QCT-based nonlinear FE models were generated for each specimen and used to predict the measured femoral strength. The outcomes of the models were compared to standard DXA-based areal bone mineral density (aBMD) measurements. For the STANCE configuration the DXA-based FE models (R²=0.74, SEE=1473N) outperformed the best densitometric predictor (Neck_aBMD, R²=0.66, SEE=1687N) but not the QCT-based FE models (R²=0.80, SEE=1314N). For the SIDE configuration both QCT-based FE models (R²=0.85, SEE=455N) and DXA neck aBMD (R²=0.80, SEE=502N) outperformed DXA-based FE models (R²=0.77, SEE=529N). In both configurations the DXA-based FE model provided a good 1:1 agreement with the experimental data (CC=0.87 for SIDE and CC=0.86 for STANCE), with proper optimization of the failure criteria. In conclusion we found that the DXA-based FE models are a good predictor of femoral strength as compared with experimental data ex vivo. However, it remains to be investigated whether this novel approach can provide good predictions of the risk of fracture in vivo

Development of a protocol to quantify local bone adaptation over space and time: quantification of reproducibility

In vivo micro-computed tomography (μCT) scanning of small rodents is a powerful method for longitudinal monitoring of bone adaptation. However, the life-time bone growth in small rodents makes it a challenge to quantify local bone adaptation. Therefore, the aim of this study was to develop a protocol, which can take into account large bone growth, to quantify local bone adaptations over space and time. The entire right tibiae of eight 14-week-old C57BL/6J female mice were consecutively scanned four times in an in vivo μCT scanner using a nominal isotropic image voxel size of 10.4 μm. The repeated scan image datasets were aligned to the corresponding baseline (first) scan image dataset using rigid registration. 80% of tibia length (starting from the endpoint of the proximal growth plate) was selected as the volume of interest and partitioned into 40 regions along the tibial long axis (10 divisions) and in the cross-section (4 sectors). The bone mineral content (BMC) was used to quantify bone adaptation and was calculated in each region. All local BMCs have precision errors (PE%CV) of less than 3.5% (24 out of 40 regions have PE%CV of less than 2%), least significant changes (LSCs) of less than 3.8%, and 38 out of 40 regions have intraclass correlation coefficients (ICCs) of over 0.8. The proposed protocol allows to quantify local bone adaptations over an entire tibia in longitudinal studies, with a high reproducibility, an essential requirement to reduce the number of animals to achieve the necessary statistical power

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