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(A) Three-dimensional trabecular bone formation and resorption sites measured with in vivo micro-CT over 4 weeks. The inset shows a magnified view of formation and resorption locations in individual trabeculae. (B) Corresponding SED computed with micro-FE in the basal scan. The same regions as in (A) are enlarged. A visual comparison reveals that high SED (red) matches with sites of bone formation (yellow), while low SED (blue) is found at locations of bone resorption (violet).
Source publication
Bone is able to react to changing mechanical demands by adapting its internal microstructure through bone forming and resorbing cells. This process is called bone modeling and remodeling. It is evident that changes in mechanical demands at the organ level must be interpreted at the tissue level where bone (re)modeling takes place. Although assumed...
Citations
... Though beyond the scope of this study, investigators could then use image analysis to quantify typically evaluated size factors such as tissue length, diameter, and cross-sectional area, as well as relative density, and relationships between adjacent tissues (distances, location of insertion sites, etc.). Micro-CT is commonly used to evaluate changes in bone with respect to mechanical stimuli, genotype, age, and many others [59][60][61] . This method provides a new option to include soft tissues into these investigations of the bony anatomy when conducting ex vivo analysis. ...
... This intricate process of bone remodeling involves highly coordinated activity of bone-resorbing osteoclasts and bone-forming osteoblasts both of which are influenced by mechanical strains in the mechanical in vivo environment of these cells [4]. Bone formation has been associated with regions subjected to high strains, while bone resorption was more frequently observed in regions with low strains [5][6][7][8]. Notably, this effect is more evident in trabecular bone, that is more sensitive to mechanical loading due to its higher metabolic activity and (caption on next page) D. Yılmaz et al. mechanical heterogeneity compared to cortical bone [9]. Furthermore, bone resorption was shown to be more tightly regulated by mechanical loading in comparison to bone formation, thus highlighting the key role of osteoclasts in bone remodeling and mediating bone loss [10]. ...
... Particularly, in-depth characterization of mechanical in vivo environment during bone remodeling by correlating time-lapsed in vivo micro-computed tomography (micro-CT) measurements with micro-finite element simulations (micro-FE). By registering consecutive micro-CT time points, remodeling sites can be accurately identified and associated with local mechanical signals computed with micro-FE [8,26]. In this regard, the role of TRAP in bone mechanoregulation, when considering the influence of supraphysiological mechanical loading on trabecular bone adaptation, is yet to be elucidated. ...
... In contrast, sham-loaded mice exhibited a negative remodeling (− 0.2 % per day in BCR Ibsp/Acp5 and -0.3 % in WT), that was associated with bone loss (Fig. 5B). For simplicity reasons, we are assuming that both remodeling and modeling events, also referred to as (re)modeling [8,9], contribute to the measurement of the net remodeling rate. ...
... Mean effective strain of formation volumes was calculated and compared to mean effective strain on the quiescent surface. Additionally, conditional probability curves for tissue formation were calculated as described elsewhere (40,63). AUC for tissue formation was computed based on formation associated effective strain and effective strain on the scaffold surface, resulting in a value between 0.5 and 1, indicating the level of mechanoregulation present in tissue formation (64,65). ...
Osteogenesis imperfecta (OI) is a heterogeneous group of rare genetic diseases characterized by increased bone fragility and deformities. The pathomechanisms of OI are poorly understood, hindering the development of disease-specific therapy. Addressing the limited understanding of OI and the lack of targeted treatments remains a challenge, given its varied symptoms and large clinical spectrum. Animal models have greatly advanced the understanding of the disease; however, the heterogeneity and subtype-specific symptoms are difficult to translate to humans. In vitro models offer a promising tool for translational medicine, as they have the potential to yield patient-specific insights in a controlled environment using patient derived-cells. We used mechanically loaded 3D-bioprinted patient-specific organotypic bone models and time-lapsed micro-computed tomography to demonstrate dysregulation of mineralization in FKBP10 -related OI compared to healthy controls. In contrast to healthy controls, tissue mineral density and stiffness were decoupled, such that hypermineralization observed in OI samples did not lead to increased stiffness. Additionally, we were able to replicate experimental stiffness using sample specific micro-finite element analysis. This allowed us to show mineral formation in regions of high local strain, suggesting mechanoregulation in FKBP10 -related OI organotypic bone models is comparable to healthy controls. Regional analysis of mineralization showed increased heterogeneous mineralization, microarchitectural inhomogeneities and scaffold microporosity of OI samples compared to healthy controls. Our results suggest that the observed dysregulation of mineralization is the main driver for the altered mineral-mechanics properties observed in FKBP10 -related organotypic bone models.
One Sentence Summary
Organotypic bone models demonstrate dysregulated mineralization in osteogenesis imperfecta samples compared to healthy controls.
... Mice have been used to study bone adaptation under mechanical loading on the tissue level, by combining in-vivo loading [17] with in-vivo microCT [19][20][21] and fluorescence labelling [18,22]. Local bone formation and resorption were quantified to link with the local mechanical signals [23,24]. It was found that mechanical loading has a stronger effect on enhancing bone formation than inhibiting resorption [20], and that the periosteal surface is less mechano-responsive than the endocortical surface of the tibia [25]. ...
Osteocyte lacuno-canalicular network (LCN) is comprised of micrometre-sized pores and submicrometric wide channels in bone. Accumulating evidence suggests multiple functions of this network in material transportation, mechanobiological signalling, mineral homeostasis and bone remodelling. Combining rhodamine staining and confocal laser scanning microscopy, the longitudinal cross-sections of six mouse tibiae were imaged, and the connectome of the network was quantified with a focus on the spatial heterogeneities of network density, connectivity and length of canaliculi. In-vivo loading and double calcein labelling on these tibiae allowed differentiating the newly formed bone from the pre-existing regions. The canalicular density of the murine cortical bone varied between 0.174 and 0.243 μm/μm³, and therefore is three times larger than the corresponding value for human femoral midshaft osteons. The spatial heterogeneity of the network was found distinctly more pronounced across the cortex than along the cortex. We found that in regions with a dense network, the LCN conserves its largely tree-like character, but increases the density by including shorter canaliculi. The current study on healthy mice should serve as a motivating starting point to study the connectome of genetically modified mice, including models of bone diseases and of reduced mechanoresponse.
... The micro-FE models were solved across 2 nodes on Piz Daint, a Cray XC30/ 40 system at the Swiss National Supercomputing Centre (CSCS), using ParOSol, a parallel solver optimised for micro-CT images (Flaig and Arbenz, 2011). The mechanical stimulus used for the cells within the soft tissue was effective strain (EFF), calculated as described by Pistoia et al. (2002), whereas the mechanical stimulus for the osteocytes within the mineralised tissue was strain-energy density (SED) (Schulte et al., 2013a). Both mechanical signals were Gaussian-filtered (sigma = 1.0, support = 0.8) to mitigate partial volume effects following the standard approach when evaluating micro-CT images (Bouxsein et al., 2010;Ohs et al., 2020). ...
Bone defects represent a challenging clinical problem as they can lead to non-union. In silico models are well suited to study bone regeneration under varying conditions by linking both cellular and systems scales. This paper presents an in silico micro-multiphysics agent-based (micro-MPA) model for bone regeneration following an osteotomy. The model includes vasculature, bone, and immune cells, as well as their interaction with the local environment. The model was calibrated by time-lapsed micro-computed tomography data of femoral osteotomies in C57Bl/6J mice, and the differences between predicted bone volume fractions and the longitudinal in vivo measurements were quantitatively evaluated using root mean square error (RMSE). The model performed well in simulating bone regeneration across the osteotomy gap, with no difference (5.5% RMSE, p = 0.68) between the in silico and in vivo groups for the 5-week healing period – from the inflammatory phase to the remodelling phase – in the volume spanning the osteotomy gap. Overall, the proposed micro-MPA model was able to simulate the influence of the local mechanical environment on bone regeneration, and both this environment and cytokine concentrations were found to be key factors in promoting bone regeneration. Further, the validated model matched clinical observations that larger gap sizes correlate with worse healing outcomes and ultimately simulated non-union. This model could help design and guide future experimental studies in bone repair, by identifying which are the most critical in vivo experiments to perform.
... Several mechanical quantities (i.e., stimuli) were proposed as driving force of BA based on stress [14,15], strain [16] and strain energy density [17][18][19], with many efforts made to compare these stimuli and select the most suitable candidate [11,20,21]. Furthermore, dependence of a BA rate on a specific mechanical stimulus was formulated using piecewise linear [17,22,23], bilinear [24,25], quadratic [26,27] and step [14,28] functions. ...
Bone is a living material that, unlike man-made ones, demonstrates continuous adaptation of its structure and mechanical properties to resist the imposed mechanical loading. Adaptation in trabecular bone is characterised by improvement of its stiffness in the loading direction and respective realignment of trabecular load-bearing architecture. Considerable experimental and simulation evidence of trabecular bone adaptation to its mechanical environment at the tissue- and organ-levels was obtained, while little attention was given to the trabecula-level of this process. This study aims to describe and classify load-driven morphological changes at the level of individual trabeculae and to propose their drivers.
For this purpose, a well-established mechanoregulation-based numerical model of bone adaptation was implemented in a user-defined subroutine that changed the structural and mechanical properties of trabeculae based on the magnitude of a mechanical stimulus. This subroutine was used in conjunction with finite-element models of variously shaped structures representing trabeculae loaded in compression or shear.
In all analysed cases, trabeculae underwent morphological evolution under applied compressive or shear loading. Among twelve cases analysed, six main mechanisms of morphological evolution were established: reorientation, splitting, merging, full resorption, thinning, and thickening. Moreover, all simulated cases presented the ability to reduce the mean value of von Mises stress while increasing their ability to resist compressive/shear loading during adaptation.
This study evaluated morphological and mechanical changes in trabeculae of different shapes in response to compressive or shear loadings and compared them based on the analysis of von Mises stress distribution as well as profiles of normal and shear stresses in the trabeculae at different stages of their adaptation.
... As such, a single formation threshold was selected per surface ( E hom = 1100 , P hom = 2785 ). In line with previous studies of mechano-adaptation, our mechanostat model uses a linear relationship between longitudinal strain and the adaptive response Sugiyama et al. 2012;Miller et al. 2021;Schulte et al. 2013;Huiskes et al. 1987;Razi et al. 2015). Adaptation rates k S sd were calculated per mechanostat model through an optimisation process, discussed in the next section. ...
The two major aims of the present study were: (i) quantify localised cortical bone adaptation at the surface level using contralateral endpoint imaging data and image analysis techniques, and (ii) investigate whether cortical bone adaptation responses are universal or region specific and dependent on the respective peak load. For this purpose, we re-analyse previously published μ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mu$$\end{document}CT data of the mouse tibia loading model that investigated bone adaptation in response to sciatic neurectomy and various peak load magnitudes (F = 0, 2, 4, 6, 8, 10, 12 N). A beam theory-based approach was developed to simulate cortical bone adaptation in different sections of the tibia, using longitudinal strains as the adaptive stimuli. We developed four mechanostat models: universal, surface-based, strain directional-based, and combined surface and strain direction-based. Rates of bone adaptation in these mechanostat models were computed using an optimisation procedure (131,606 total simulations), performed on a single load case (F = 10 N). Subsequently, the models were validated against the remaining six peak loads. Our findings indicate that local bone adaptation responses are quasi-linear and bone region specific. The mechanostat model which accounted for differences in endosteal and periosteal regions and strain directions (i.e. tensile versus compressive) produced the lowest root mean squared error between simulated and experimental data for all loads, with a combined prediction accuracy of 76.6, 55.0 and 80.7% for periosteal, endosteal, and cortical thickness measurements (in the midshaft of the tibia). The largest root mean squared errors were observed in the transitional loads, i.e. F = 2 to 6 N, where inter-animal variability was highest. Finally, while endpoint imaging studies provide great insights into organ level bone adaptation responses, the between animal and loaded versus control limb variability make simulations of local surface-based adaptation responses challenging.
... Additionally, efforts should be made to account for stimuli beyond those being directly investigated, for example, compression-induced fluid flow. To this end, computational simulation offers a powerful tool for analysis of microenvironments (Figure 1) that can be paired with experimental results (Schulte et al., 2013). Another step to improving the robustness and generalizability of studies examining the effect of microenvironmental stimuli on osteogenesis is to examine multiple markers of osteogenic differentiation, with an eye towards developing a minimum standard set of readouts. ...
At the macroscale, bones experience a variety of compressive and tensile loads, and these loads cause deformations of the cortical and trabecular microstructure. These deformations produce a variety of stimuli in the cellular microenvironment that can influence the differentiation of marrow stromal cells (MSCs) and the activity of cells of the MSC lineage, including osteoblasts, osteocytes, and chondrocytes. Mechanotransduction, or conversion of mechanical stimuli to biochemical and biological signals, is thus part of a multiscale mechanobiological process that drives bone modeling, remodeling, fracture healing, and implant osseointegration. Despite strong evidence of the influence of a variety of mechanical cues, and multiple paradigms proposed to explain the influence of these cues on tissue growth and differentiation, even a working understanding of how skeletal cells respond to the complex combinations of stimuli in their microenvironments remains elusive. This review covers the current understanding of what types of microenvironmental mechanical cues MSCs respond to and what is known about how they respond in the presence of multiple such cues. We argue that in order to realize the vast potential for harnessing the cellular microenvironment for the enhancement of bone regeneration, additional investigations of how combinations of mechanical cues influence bone regeneration are needed.
... The upper regions of the condyle were fully fixed, and two bitting forces ( 1 = 60 and 2 = 110 ) measured from a clinical experiments were applied at the front tooth region [48]. The target equivalent strain ̅ was set to be 0.001, which was recommended by several clinical studies for promoting bone growth [50][51][52][53]. The initial design of the scaffold is composed of uniform iso-truss lattices with a bar size of 0.35 mm. ...
... 41 The animal experiment study demonstrated that significantly higher pressure promoted the bone formation compared to quiescent areas. 42 Theoretically, multidimensional fixation related to 4 screws allows stronger pressure in the intervertebral space and pressure dispersion to avoid internal fixation failure due to excessive stress concentration compared with anterolateral single screw-rod fixation, but these data need to be determined by finite element analysis or biomechanical analysis in further study. Alternatively, bone marrow enrichment procedure had a catalytic effect on osteogenesis 16 and Shen et al. 43 demonstrated that this technique has a faster healing time than conventional bone grafts in children with infectious bone defects. ...
Objective
To evaluate the clinical and radiological efficacy of a combine of lateral single screw-rod and unilateral percutaneous pedicle screw fixation (LSUP) for lateral lumbar interbody fusion (LLIF) in the treatment of spondylolisthesis.
Methods
Sixty-two consecutive patients with lumbar spondylolisthesis who underwent minimally invasive (MIS)-TLIF with bilateral pedicle screw (BPS) or LLIF-LSUP were retrospectively studied. Segmental lordosis angle (SLA), lumbar lordosis angle (LLA), disc height (DH), slipping percentage, the cross-sectional areas (CSA) of the thecal sac, screw placement accuracy, fusion rate and foraminal height (FH) were used to evaluate radiographic changes postoperatively. Visual analogue scale (VAS) and Oswestry Disability Index (ODI) were used to evaluate the clinical efficacy.
Results
Patients who underwent LLIF-LSUP showed shorter operating time, less length of hospital stay and lower blood loss than MIS-TLIF. No statistical difference was found between the 2 groups in screw placement accuracy, overall complications, VAS, and ODI. Compared with MIS-TLIF-BPS, LLIF-LSUP had a significant improvement in sagittal parameters including DH, FH, LLA, and SLA. The CSA of MIS-TLIF-BPS was significantly increased than that of LLIF-LSUP. The fusion rate of LLIF-LSUP was significantly higher than that of MIS-TLIF-BPS at the follow-up of 3 months postoperatively, but there was no statistical difference between the 2 groups at the follow-up of 6 months, 9 months, and 12 months.
Conclusion
The overall clinical outcomes and complications of LLIF-LSUP were comparable to that of MIS-TLIF-BPS in this series. Compared with MIS-TLIF-BPS, LLIF-LSUP for lumbar spondylolisthesis represents a significantly shorter operating time, hospital stay and lower blood loss, and demonstrates better radiological outcomes to maintain lumbar lordosis, and reveal an overwhelming superiority in the early fusion rate.
