Experimental and finite element analysis of the mouse caudal vertebrae loading model: prediction of cortical and trabecular bone adaptation

Positive interactions of mechanical loading and PTH treatments on spatio-temporal bone remodelling

Osteoporosis is one of the most common skeletal diseases, but current therapies are limited to generalized antiresorptive or anabolic interventions, which do not target regions that would benefit from improvements to skeletal health. To improve the evaluation of treatment plans, we used a spatio-temporal multiscale approach that combines longitudinal in vivo micro-computed tomography (micro-CT) and in silico subject-specific finite element modeling to quantitatively map bone adaptation changes due to disease and treatment at high resolution. Our findings show time and region-dependent modifications in bone remodelling following one and two sets of mechanical loading and/or pharmacological interventions. The multiscale results highlighted that the distal section was unaffected by mechanical loading alone but the proximal tibia had the greatest gain from positive interactions of combined therapies. Mechanical loading abated the catabolic effect of PTH, but the main benefit of combined treatments occurred from the additive interactions of the two therapies in periosteal apposition. These results provide detailed insight into the efficacy of combined treatments, facilitating the optimisation of dosage and treatment duration in preclinical mouse studies, and the development of novel interventions for skeletal diseases. STATEMENT OF SIGNIFICANCE: Combined mechanical loading and pharmacotherapy have the potential to slow osteoporosis-induced bone loss but current therapies do not target the regions in need of strengthening. We show for the first time spatial region-dependant interactions between PTH and mechanical loading treatment in OVX mouse tibiae, highlighting local regions in the tibia that benefitted from separate and combined treatments. Combined experimental-computational analysis also detailed the lasting period of each treatment per location in the tibia, the extent of positive (or negative) interactions of the combined therapies, and the impact of each treatment on the regulation of bone adaptation spatio-temporally. This approach can be used to create hypothesis about the interactions of different treatments to optimise the design of biomaterials and medical interventions.

Cortical Thickness Adaptive Response to Mechanical Loading Depends on Periosteal Position and Varies Linearly With Loading Magnitude

The aim of the current study was to quantify the local effect of mechanical loading on cortical bone formation response at the periosteal surface using previously obtained μCT data from a mouse tibia mechanical loading study. A novel image analysis algorithm was developed to quantify local cortical thickness changes (ΔCt.Th) along the periosteal surface due to different peak loads (0N ≤ F ≤ 12N) applied to right-neurectomised mature female C57BL/6 mice. Furthermore, beam analysis was performed to analyse the local strain distribution including regions of tensile, compressive, and low strain magnitudes. Student's paired t-test showed that ΔCt.Th in the proximal (25%), proximal/middle (37%), and middle (50%) cross-sections (along the z-axis of tibia) is strongly associated with the peak applied loads. These changes are significant in a majority of periosteal positions, in particular those experiencing high compressive or tensile strains. No association between F and ΔCt.Th was found in regions around the neutral axis. For the most distal cross-section (75%), the association of loading magnitude and ΔCt.Th was not as pronounced as the more proximal cross-sections. Also, bone formation responses along the periosteum did not occur in regions of highest compressive and tensile strains predicted by beam theory. This could be due to complex experimental loading conditions which were not explicitly accounted for in the mechanical analysis. Our results show that the bone formation response depends on the load magnitude and the periosteal position. Bone resorption due to the neurectomy of the loaded tibia occurs throughout the entire cross-sectional region for all investigated cortical sections 25, 37, 50, and 75%. For peak applied loads higher than 4 N, compressive and tensile regions show bone formation; however, regions around the neutral axis show constant resorption. The 50% cross-section showed the most regular ΔCt.Th response with increased loading when compared to 25 and 37% cross-sections. Relative thickness gains of approximately 70, 60, and 55% were observed for F = 12 N in the 25, 37, and 50% cross-sections. ΔCt.Th at selected points of the periosteum follow a linear response with increased peak load; no lazy zone was observed at these positions.

The Role of the Loading Condition in Predictions of Bone Adaptation in a Mouse Tibial Loading Model

The in vivo mouse tibial loading model is used to evaluate the effectiveness of mechanical loading treatment against skeletal diseases. Although studies have correlated bone adaptation with the induced mechanical stimulus, predictions of bone remodeling remained poor, and the interaction between external and physiological loading in engendering bone changes have not been determined. The aim of this study was to determine the effect of passive mechanical loading on the strain distribution in the mouse tibia and its predictions of bone adaptation. Longitudinal micro-computed tomography (micro-CT) imaging was performed over 2 weeks of cyclic loading from weeks 18 to 22 of age, to quantify the shape change, remodeling, and changes in densitometric properties. Micro-CT based finite element analysis coupled with an optimization algorithm for bone remodeling was used to predict bone adaptation under physiological loads, nominal 12N axial load and combined nominal 12N axial load superimposed to the physiological load. The results showed that despite large differences in the strain energy density magnitudes and distributions across the tibial length, the overall accuracy of the model and the spatial match were similar for all evaluated loading conditions. Predictions of densitometric properties were most similar to the experimental data for combined loading, followed closely by physiological loading conditions, despite no significant difference between these two predicted groups. However, all predicted densitometric properties were significantly different for the 12N and the combined loading conditions. The results suggest that computational modeling of bone's adaptive response to passive mechanical loading should include the contribution of daily physiological load.

Dominant and nondominant distal radius microstructure: Predictors of asymmetry and effects of a unilateral mechanical loading intervention

Most information about distal radius microstructure is based on the non-dominant forearm, with little known about the factors that contribute to bilateral asymmetries in the general population, or what factors may influence bilateral changes over time. Here, we analyzed bilateral high resolution peripheral quantitative computed tomography (HRpQCT) data collected over a 12-month period as part of a clinical trial that prescribed a well-controlled, compressive loading task to the nondominant forearm. Baseline data from 102 women age 21–40, and longitudinal data from 66 women who completed the 12-month trial, were examined to determine factors responsible for side-to-side asymmetries in bone structure and change in structure over time. Cross-sectionally, the dominant radius had 2.4%–2.7% larger cross-sectional area, trabecular area, and bone mineral content than the nondominant radius, but no other differences were noted. Those who more strongly favored their dominant arm had significantly more, thinner, closely spaced trabecular struts in their dominant versus nondominant radius. Individuals assigned to a loading intervention had significant bilateral gains in total bone mineral density (2.0% and 1.2% in the nondominant versus dominant sides), and unilateral gains in the nondominant (loaded) cortical area (3.1%), thickness (3.0%), bone mineral density (1.7%) and inner trabecular density (1.3%). Each of these gains were significantly predicted by loading dose, a metric that included bone strain, number of cycles, and strain rate. Within individuals, change was negatively associated with age, meaning that women closer to age 40 experienced less of a gain in bone versus those closer to age 21. We believe that dominant/nondominant asymmetries in bone structure reflect differences in habitual loads during growth and past ability to adapt, while response to loading reflects current individual physiologic capacity to adapt.

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We examined relationships between physical activity, handedness, demographics, and asymmetries in distal radius structure.

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Trabecular and cross-sectional area were 2.4-2.7% larger in the dominant side.

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We examined factors that predicted 12-month change after a unilateral loading intervention on the nondominant side.

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The intervention caused unilateral (nondominant) increases in most variables, which scaled with loading dose.

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The results also suggest that greater dietary calcium is associated with endosteal bone apposition following loading.

Application of subject-specific adaptive mechanical loading for bone healing in a mouse tail vertebral defect

Methods to repair bone defects arising from trauma, resection, or disease, continue to be sought after. Cyclic mechanical loading is well established to influence bone (re)modelling activity, in which bone formation and resorption are correlated to micro-scale strain. Based on this, the application of mechanical stimulation across a bone defect could improve healing. However, if ignoring the mechanical integrity of defected bone, loading regimes have a high potential to either cause damage or be ineffective. This study explores real-time finite element (rtFE) methods that use three-dimensional structural analyses from micro-computed tomography images to estimate effective peak cyclic loads in a subject-specific and time-dependent manner. It demonstrates the concept in a cyclically loaded mouse caudal vertebral bone defect model. Using rtFE analysis combined with adaptive mechanical loading, mouse bone healing was significantly improved over non-loaded controls, with no incidence of vertebral fractures. Such rtFE-driven adaptive loading regimes demonstrated here could be relevant to clinical bone defect healing scenarios, where mechanical loading can become patient-specific and more efficacious. This is achieved by accounting for initial bone defect conditions and spatio-temporal healing, both being factors that are always unique to the patient.

Multiscale finite element modeling of mechanical strains and fluid flow in osteocyte lacunocanalicular system

Osteocytes form over 90% of the bone cells and are postulated to be mechanosensors responsible for regulating the function of osteoclasts and osteoblasts in bone modeling and remodeling. Physical activity results in mechanical loading on the bones. Osteocytes are thought to be the main mechanosensory cells in bone. Upon load osteocytes secrete key factors initiating downstream signaling pathways that regulate skeletal metabolism including the Wnt/β-catenin signaling pathway. Osteocytes have dendritic structures and are housed in the lacunae and canaliculi within the bone matrix. Mechanical loading is known to have two primary effects, namely a mechanical strain (membrane disruption by stretching) on the lacunae/cells, and fluid flow, in the form of fluid flow shear stress (FFSS), in the space between the cell membranes and the lacuna-canalicular walls. In response, osteocytes get activated via a process called mechanotransduction in which mechanical signals are transduced to biological responses. The study of mechanotransduction is a complex subject involving principles of engineering mechanics as well as biological signaling pathway studies. Several length scales are involved as the mechanical loading on macro sized bones are converted to strain and FFSS responses at the micro-cellular level. Experimental measurements of strain and FFSS at the cellular level are very difficult and correlating them to specific biological activity makes this a very challenging task. One of the methods commonly adopted is a multi-scale approach that combines biological and mechanical experimentation with in silico numerical modeling of the engineering aspects of the problem. Finite element analysis along with fluid-structure interaction methodologies are used to compute the mechanical strain and FFSS. These types of analyses often involve a multi-length scale approach where models of both the macro bone structure and micro structure at the cellular length scale are used. Imaging modalities play a crucial role in the development of the models and present their own challenges. This paper reviews the efforts of various research groups in addressing this problem and presents the work in our research group. A clear understanding of how mechanical stimuli affect the lacunae and perilacunar tissue strains and shear stresses on the cellular membranes may ultimately lead to a better understanding of the process of osteocyte activation.

A novel algorithm to predict bone changes in the mouse tibia properties under physiological conditions

Understanding how bone adapts to mechanical stimuli is fundamental for optimising treatments against musculoskeletal diseases in preclinical studies, but the contribution of physiological loading to bone adaptation in mouse tibia has not been quantified so far. In this study, a novel mechanistic model to predict bone adaptation based on physiological loading was developed and its outputs were compared with longitudinal scans of the mouse tibia. Bone remodelling was driven by the mechanical stimuli estimated from micro-FEA models constructed from micro-CT scans of C57BL/6 female mice (N = 5) from weeks 14 and 20 of age, to predict bone changes in week 16 or 22. Parametric analysis was conducted to evaluate the sensitivity of the models to subject-specific or averaged parameters, parameters from week 14 or week 20, and to strain energy density (SED) or maximum principal strain (ε_maxprinc). The results at week 20 showed no significant difference in bone densitometric properties between experimental and predicted images across the tibia for both stimuli, and 59% and 47% of the predicted voxels matched with the experimental sites in apposition and resorption, respectively. The model was able to reproduce regions of bone apposition in both periosteal and endosteal surfaces (70% and 40% for SED and ε_maxprinc, respectively), but it under-predicted the experimental sites of resorption by over 85%. This study shows for the first time the potential of a subject-specific mechanoregulation algorithm to predict bone changes in a mouse model under physiological loading. Nevertheless, the weak predictions of resorption suggest that a combined stimulus or biological stimuli should be accounted for in the model.

Stochastic analysis of a heterogeneous micro-finite element model of a mouse tibia

Finite element (FE) analysis can be used to predict bone mechanical environments that can be used for many important applications, such as the understanding of bone mechano-regulation mechanisms. However, when defining the FE models, uncertainty in bone material properties may lead to marked variations in the predicted mechanical environment. The aim of this study is to investigate the influence of uncertainty in bone material property on the mechanical environment of bone. A heterogeneous FE model of a mouse tibia was created from micro computed tomography images. Axial compression loading was applied, and all possible bone density-modulus relationships were considered through stochastic analysis. The 1st and 3rd principal strains (ε₁ and ε₃) and the strain energy density (SED) were quantified in the tibial volume of interest (VOI). The bounds of ε₁, ε₃, and SED were determined by the bounds of the density-modulus relationship; the bone mechanical environment (ε₁, ε₃, and SED) and the bone density-modulus relationship exhibit the same trend of change; the relative percentage differences caused by bone material uncertainty are up to 28%, 28%, and 21% for ε₁, ε₃, and SED, respectively. These data provide guidelines on the adoption of bone density-modulus relationship in heterogeneous FE models.

Spatial relationship between bone formation and mechanical stimulus within cortical bone: Combining 3D fluorochrome mapping and poroelastic finite element modelling

Bone is a dynamic tissue and adapts its architecture in response to biological and mechanical factors. Here we investigate how cortical bone formation is spatially controlled by the local mechanical environment in the murine tibia axial loading model (C57BL/6). We obtained 3D locations of new bone formation by performing ‘slice and view’ 3D fluorochrome mapping of the entire bone and compared these sites with the regions of high fluid velocity or strain energy density estimated using a finite element model, validated with ex-vivo bone surface strain map acquired ex-vivo using digital image correlation. For the comparison, 2D maps of the average bone formation and peak mechanical stimulus on the tibial endosteal and periosteal surface across the entire cortical surface were created. Results showed that bone formed on the periosteal and endosteal surface in regions of high fluid flow. Peak strain energy density predicted only the formation of bone periosteally. Understanding how the mechanical stimuli spatially relates with regions of cortical bone formation in response to loading will eventually guide loading regime therapies to maintain or restore bone mass in specific sites in skeletal pathologies.

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3D spatial representation of new bone formation after loading is shown by fluorochrome mapping of the entire mouse tibia

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Regions of new bone formation spatially associate with regions of high strain and fluid mechanical stimulus in a FE model

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The FE model was validated with the strains on the bone surface determined ex-vivo using digital image correlation

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Regions of new bone formation co-localize in sites of peak fluid flow, both endosteally and periosteally

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Peak strain energy density was able to predict only periosteal bone formation

A novel use of 3D printing model demonstrates the effects of deteriorated trabecular bone structure on bone stiffness and strength

Trabecular bone structure is crucial to normal mechanical behavior of bones. Studies have shown that osteoporosis negatively affects trabecular bone structure, mainly by reducing bone volume fraction (BV/TV) and thus increasing fracture risk. One major limitation in assessing and quantifying the effect of this structural deterioration is that no two trabecular structures are identical. Thus, when we compare a group of healthy bones against a different group of bones that experienced resorption (i.e. decreased BV/TV) we only discover an "average" mechanical effect. It is impossible to quantify the mechanical effect of individual structural deterioration for each sample, simply because we never have the same sample in both states (intact and deteriorated structure). 3D printing is a new technology that can assist in overcoming this issue. Here we report a preliminary study that compares a healthy 3D printed trabecular bone model with the same model after bone resorption was simulated. Since the deteriorated structural bone model is derived from the healthy one, it is possible to directly estimate (percentage wise) the decrease of tissue stiffness and strength as a result of bone resorption for this specific structure. Our results demonstrate that a relatively small decrease in BV/TV (about 8%) leads to a dramatic decrease in structural strength (24%) and structural stiffness (17%), (P < 0.01). Structural strength decreased from an average of 9.14 ± 2.85MPa to 6.97 ± 2.44MPa, while structural stiffness decreased from an average of 282.5 ± 63.4N/mm to 233.8 ± 51.2N/mm. This study demonstrates that 3D printing is a novel and valuable tool for quantifying the effect of structural deterioration on the mechanical properties of trabecular bone. In the future, this approach may help us attain better personal fracture risk assessments by CT scanning, 3D printing and mechanically testing individual bone replicas from patients suffering excessive bone resorption.

Mechanically induced bone formation is not sensitive to local osteocyte density in rat vertebral cancellous bone

Osteocytes play an integral role in bone by sensing mechanical stimuli and releasing signaling factors that direct bone formation. The importance of osteocytes in mechanotransduction suggests that regions of bone tissue with greater osteocyte populations are more responsive to mechanical stimuli. To determine the effects of osteocyte population on bone functional adaptation we applied mechanical loads to the 8th caudal vertebra of skeletally mature female Sprague Dawley rats (6 months of age, n = 8 loaded, n = 8 sham controls). The distribution of tissue stress/strain within cancellous bone was determined using high-resolution finite element models, osteocyte distribution was determined using nano-computed tomography, and locations of bone formation were determined using three-dimensional images of fluorescent bone formation markers. Loading increased bone formation (3D MS/BS 10.82 ± 2.09% in loaded v. 3.17 ± 2.05% in sham control, mean ± SD). Bone formation occurred at regions of cancellous bone experiencing greater tissue stress/strain, however stress/strain was only a modest predictor of bone formation; even at locations of greatest stress/strain the probability of observing bone formation did not exceed 41%. The local osteocyte population was not correlated with locations of new bone formation. The findings support the idea that local tissue stress/strain influence the locations of bone formation in cancellous bone, but suggest that the size of the osteocyte population itself is not influential. We conclude that other aspects of osteocytes such as osteocyte connectivity, lacunocanilicular nano-geometry, and/or fluid pressure/shear distributions within the marrow space may be more influential in regulating bone mechanotransduction than the number of osteocytes. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:672-681, 2018.

Cortical Bony Thickening of the Lateral Intercondylar Wall: The Functional Attachment of the Anterior Cruciate Ligament

BACKGROUND

The anatomy of the anterior cruciate ligament (ACL) has become the subject of much debate. There has been extensive study into attachment points of the native ligament, especially regarding the femoral attachment. Some of these studies have suggested that fibers in the ACL are of differing functional importance. Fibers with higher functional importance would be expected to exert larger mechanical stress on the bone. According to Wolff's law, cortical thickening would be expected in these areas.

PURPOSE

To examine cortical thickening in the region of the ACL footprint (ie, the functional footprint of the ACL).

STUDY DESIGN

Descriptive laboratory study.

METHODS

Using micro-computed tomography with resolutions ranging from 71 to 91 μm, the cortical thickness of the lateral wall of the intercondylar notch in 17 cadaveric knees was examined, along with surface topography. After image processing, the relationship between the cortical thickening and surface topology was visually compared.

RESULTS

A pattern of cortical thickening consistent with the functional footprint of the ACL was found. On average, this area was 3 times thicker than the surrounding bone and significantly thicker than the remaining lateral wall ( P < .0001). This thickening was roughly elliptical in shape (with a mean centroid at 23.5 h:31 t on a Bernard and Hertel grid) and had areas higher on the wall where greater thickness was present. The relationship to previously reported osseous landmarks was variable, although the patterns were broadly consistent with those reported in previous studies describing direct and indirect fibers of the ACL.

CONCLUSION

The findings of this study are consistent with those of recent studies describing fibers in the ACL of differing functional importance. The area in which the thickening was found has been defined and is likely to represent the functional footprint of the ACL.

CLINICAL RELEVANCE

This information is of value to surgeons when determining the optimal place to position the femoral attachment site of the reconstructed ACL.

Predicting cortical bone adaptation to axial loading in the mouse tibia

The development of predictive mathematical models can contribute to a deeper understanding of the specific stages of bone mechanobiology and the process by which bone adapts to mechanical forces. The objective of this work was to predict, with spatial accuracy, cortical bone adaptation to mechanical load, in order to better understand the mechanical cues that might be driving adaptation. The axial tibial loading model was used to trigger cortical bone adaptation in C57BL/6 mice and provide relevant biological and biomechanical information. A method for mapping cortical thickness in the mouse tibia diaphysis was developed, allowing for a thorough spatial description of where bone adaptation occurs. Poroelastic finite-element (FE) models were used to determine the structural response of the tibia upon axial loading and interstitial fluid velocity as the mechanical stimulus. FE models were coupled with mechanobiological governing equations, which accounted for non-static loads and assumed that bone responds instantly to local mechanical cues in an on–off manner. The presented formulation was able to simulate the areas of adaptation and accurately reproduce the distributions of cortical thickening observed in the experimental data with a statistically significant positive correlation (Kendall's τ rank coefficient τ = 0.51, p < 0.001). This work demonstrates that computational models can spatially predict cortical bone mechanoadaptation to a time variant stimulus. Such models could be used in the design of more efficient loading protocols and drug therapies that target the relevant physiological mechanisms.

A computational model to describe the regional interlamellar shear of the annulus fibrosus

Interlamellar shear may play an important role in the homeostasis and degeneration of the intervertebral disk. Accurately modeling the shear behavior of the interlamellar compartment would enhance the study of its mechanobiology. In this study, physical experiments were utilized to describe interlamellar shear and define a constitutive model, which was implemented into a finite element analysis. Ovine annulus fibrosus (AF) specimens from three locations within the intervertebral disk (lateral, outer anterior, and inner anterior) were subjected to in vitro mechanical shear testing. The local shear stress-stretch relationship was described for the lamellae and across the interlamellar layer of the AF. A hyperelastic constitutive model was defined for interlamellar and lamellar materials at each location tested. The constitutive models were incorporated into a finite element model of a block of AF, which modeled the interlamellar and lamellar layers using a continuum description. The global shear behavior of the AF was compared between the finite element model and physical experiments. The shear moduli at the initial and final regions of the stress-strain curve were greater within the lamellae than across the interlamellar layer. The difference between interlamellar and lamellar shear was greater at the outer anterior AF than at the inner anterior region. The finite element model was shown to accurately predict the global shear behavior or the AF. Future studies incorporating finite element analysis of the interlamellar compartment may be useful for predicting its physiological mechanical behavior to inform the study of its mechanobiology.

Strain energy density gradients in bone marrow predict osteoblast and osteoclast activity: a finite element study

Huiskes et al. hypothesized that mechanical strains sensed by osteocytes residing in trabecular bone dictate the magnitude of load-induced bone formation. More recently, the mechanical environment in bone marrow has also been implicated in bone׳s response to mechanical stimulation. In this study, we hypothesize that trabecular load-induced bone formation can be predicted by mechanical signals derived from an integrative µFE model, incorporating a description of both the bone and marrow phase. Using the mouse tail loading model in combination with in vivo micro-computed tomography (µCT) we tracked load induced changes in the sixth caudal vertebrae of C57BL/6 mice to quantify the amount of newly mineralized and eroded bone volumes. To identify the mechanical signals responsible for adaptation, local morphometric changes were compared to micro-finite element (µFE) models of vertebrae prior to loading. The mechanical parameters calculated were strain energy density (SED) on trabeculae at bone forming and resorbing surfaces, SED in the marrow at the boundary between bone forming and resorbing surfaces, along with SED in the trabecular bone and marrow volumes. The gradients of each parameter were also calculated. Simple regression analysis showed mean SED gradients in the trabecular bone matrix to significantly correlate with newly mineralized and eroded bone volumes R(2)=0.57 and 0.41, respectively, p<0.001). Nevertheless, SED gradients in the marrow were shown to be the best predictor of osteoblastic and osteoclastic activity (R(2)=0.83 and 0.60, respectively, p<0.001). These data suggest that the mechanical environment of the bone marrow plays a significant role in determining osteoblast and osteoclast activity.

The effects of misalignment during in vivo loading of bone: techniques to detect the proximity of objects in three-dimensional models

Theories of mechanical adaptation of bone suggest that mechanical loading causes bone formation at discrete locations within bone microstructure experiencing the greatest mechanical stress/strain. Experimental testing of such theories requires in vivo loading experiments and high-resolution finite element models to determine the distribution of mechanical stresses. Finite element models of in vivo loading experiments typically assume idealized boundary conditions with applied load perfectly oriented on the bone, however small misalignments in load orientation during an in vivo experiment are unavoidable, and potentially confound the ability of finite element models to predict locations of bone formation at the scale of micrometers. Here we demonstrate two different three-dimensional spatial correlation methods to determine the effects of misalignment in load orientation on the locations of high mechanical stress/strain in the rodent tail loading model. We find that, in cancellous bone, the locations of tissue with high stress are maintained under reasonable misalignments in load orientation (p<0.01). In cortical bone, however, angular misalignments in the dorsal direction can alter the locations of high mechanical stress, but the locations of tissue with high stress are maintained under other misalignments (p<0.01). We conclude that, when using finite element models of the rodent tail loading model, small misalignments in loading orientation do not affect the predicted locations of high mechanical stress within cancellous bone.

EXPERIMENTAL METHODS FOR THE BIOMECHANICAL INVESTIGATION OF THE HUMAN SPINE: A REVIEW

In vitro mechanical testing of spinal specimens is extremely important to better understand the biomechanics of the healthy and diseased spine, fracture, and to test/optimize surgical treatment. While spinal testing has extensively been carried out in the past four decades, testing methods are quite diverse. This paper aims to provide a critical overview of the in vitro methods for mechanical testing the human spine at different scales. Specimens of different type are used, according to the aim of the study: spine segments (two or more adjacent vertebrae) are used both to investigate the spine kinematics, and the mechanical properties of the spine components (vertebrae, ligaments, discs); single vertebrae (whole vertebra, isolated vertebral body, or vertebral body without endplates) are used to investigate the structural properties of the vertebra itself; core specimens are extracted to test the mechanical properties of the trabecular bone at the tissue-level; mechanical properties of spine soft tissue (discs, ligaments, spinal cord) are measured on isolated elements, or on tissue specimens. Identification of consistent reference frames is still a debated issue. Testing conditions feature different pre-conditioning and loading rates, depending on the simulated action. Tissue specimen preservation is a very critical issue, affecting test results. Animal models are often used as a surrogate. However, because of different structure and anatomy, extreme caution is required when extrapolating to the human spine. In vitro loading conditions should be based on reliable in vivo data. Because of the high complexity of the spine, such information (either through instrumented implants or through numerical modeling) is currently unsatisfactory. Because of the increasing ability of computational models in predicting biomechanical properties of musculoskeletal structures, a synergy is possible (and desirable) between in vitro experiments and numerical modeling. Future perspectives in spine testing include integration of mechanical and structural properties at different dimensional scales (from the whole-body-level down to the tissue-level) so that organ-level models (which are used to predict the most relevant phenomena such as fracture) include information from all dimensional scales.

Studying osteocytes within their environment

It is widely hypothesized that osteocytes are the mechano-sensors residing in the bone's mineralized matrix which control load induced bone adaptation. Owing to their inaccessibility it has proved challenging to generate quantitative in vivo experimental data which supports this hypothesis. Recent advances in in situ imaging, both in non-living and living specimens, have provided new insights into the role of osteocytes in the skeleton. Combined with the retrieval of biochemical information from mechanically stimulated osteocytes using in vivo models, quantitative experimental data is now becoming available which is leading to a more accurate understanding of osteocyte function. With this in mind, here we review i) state of the art ex vivo imaging modalities which are able to precisely capture osteocyte structure in 3D, ii) live cell imaging techniques which are able to track structural morphology and cellular differentiation in both space and time, and iii) in vivo models which when combined with the latest biochemical assays and microfluidic imaging techniques can provide further insight on the biological function of osteocytes.