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Bone's ability to adapt is governed by the network of embedded osteocytes, which inhabit individual pores called lacunae. The morphology of these lacunae and their resident osteocytes are known to change with age and diseases such as postmenopausal osteoporosis. However, it is unclear whether alterations in lacunar morphology are present in younger populations with osteoporosis. To investigate this, we implemented a previously validated methodology to image and quantify the three-dimensional morphometries of lacunae on a large scale with ultra-high-resolution micro-computed tomography (microCT) in transiliac bone biopsies from three groups of premenopausal women: control n = 39; idiopathic osteoporosis (IOP) n = 45; idiopathic low BMD (ILBMD) n = 19. Lacunar morphometric parameters were measured in both trabecular and cortical bone such as lacunar density (Lc.N/BV), lacunar volume (Lc.V), and lacunar sphericity (Lc.Sr). These were then compared against each other and also with previously measured tissue morphometries such as bone volume density (BV/TV), trabecular separation (Tb.Sp), trabecular number (Tb.N), and others. We detected no differences in lacunar morphology between the IOP, ILBMD and healthy premenopausal women. In contrast, we did find significant differences between lacunar morphologies including Lc.N/BV, Lc. V, and Lc. Sr in cortical and trabecular regions within all three groups (p < 0.001), which was consistent with our previous findings on a subgroup of the healthy group. Furthermore, we discovered strong correlations between Lc. Sr from trabecular regions with the measured BV/TV (R = -0.90, p < 0.05). The findings and comprehensive lacunar dataset we present here will be a crucial foundation for future investigations of the relationship between osteocyte lacunar morphology and disease., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Ultra-high-resolution imaging of the osteocyte lacuno-canalicular network (LCN) three-dimensionally (3D) in a high-throughput fashion has greatly improved the morphological knowledge about the constituent structures - positioning them as potential biomarkers. Technologies such as serial focused ion beam/scanning electron microscopy (FIB/SEM) and confocal scanning laser microscopy (CLSM) can image in extremely high resolution, yet only capture a small number of lacunae. Synchrotron radiation computed tomography (SR-CT) can image with both high resolution and high throughput but has a limited availability. Desktop micro-computed tomography (micro-CT) provides an attractive balance: high-throughput imaging on the micron level without the restrictions of SR-CT availability. In this study, accuracy, reproducibility, and sensitivity of large-scale quantification of human osteocyte lacunar morphometries were assessed by ultra-high-resolution desktop micro-computed tomography. For this purpose, thirty-one transiliac human bone biopsies containing trabecular and cortical regions were imaged using ultra-high-resolution desktop micro-CT at a nominal isotropic voxel resolution of 1.2 µm. The resulting 3D images were segmented, component labeled, and the following morphometric parameters of 7.71 million lacunae were measured: Lacunar number (Lc.N), density (Lc.N/BV), porosity (Lc.TV/BV), volume (Lc.V), surface area (Lc.S), surface area to volume ratio (Lc.S/Lc.V), stretch (Lc.St), oblateness (Lc.Ob), sphericity (Lc.Sr), equancy (Lc.Eq), and angle (Lc.θ). Accuracy was quantified by comparing automated lacunar identification to manual identification. Mean true positive rate (TPR), false positive rate (FPR), and false negative rate (FNR) were 89.0%, 3.4%, and 11.0%, respectively. Regarding the reproducibility of lacunar morphometry from repeated measurements, precision errors were low (0.2-3.0%) and intraclass correlation coefficients were high (0.960-0.999). Significant differences between cortical and trabecular regions (p<0.001) existed for Lc.N/BV, Lc.TV/BV, local lacunar surface area (), and local lacunar volume (), all of which demonstrate the sensitivity of the method and are possible biomarker candidates. This study provides the foundation required for future large-scale morphometric studies using ultra-high-resolution desktop micro-CT and high-throughput analysis of millions of osteocyte lacunae in human bone samples., (Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.)

The mechanical integrity of the bone-implant system is maintained by the process of bone remodeling. Specifically, the interplay between bone resorption and bone formation is of paramount importance to fully understand the net changes in bone structure occurring in the peri-implant bone, which are eventually responsible for the mechanical stability of the bone-implant system. Using time-lapsed in vivo micro-computed tomography combined with new composite material implants, we were able to characterize the spatio-temporal changes of bone architecture and bone remodeling following implantation in living mice. After insertion, implant stability was attained by a quick and substantial thickening of the cortical shell which counteracted the observed loss of trabecular bone, probably due to the disruption of the trabecular network. Within the trabecular compartment, the rate of bone formation close to the implant was transiently higher than far from the implant mainly due to an increased mineral apposition rate which indicated a higher osteoblastic activity. Conversely, in cortical bone, the higher rate of bone formation close to the implant compared to far away was mostly related to the recruitment of new osteoblasts as indicated by a prevailing mineralizing surface. The behavior of bone resorption also showed dissimilarities between trabecular and cortical bone. In the former, the rate of bone resorption was higher in the peri-implant region and remained elevated during the entire monitoring period. In the latter, bone resorption rate had a bigger value away from the implant and decreased with time. Our approach may help to tune the development of smart implants that can attain a better long-term stability by a local and targeted manipulation of the remodeling process within the cortical and the trabecular compartments and, particularly, in bone of poor health., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Trabecular bone is a highly dynamic tissue due to bone remodeling, mineralization and demineralization. The mineral content and its spatial heterogeneity are main contributors to bone quality. Using time-lapsed in vivo micro-computed tomography (micro-CT), it is now possible to resolve in three dimensions where bone gets resorbed and deposited over several weeks. In addition, the gray values in the micro-CT images contain quantitative information about the local tissue mineral density (TMD). The aim of this study was to measure how TMD increases with time after new bone formation and how this mineralization kinetics is influenced by mechanical stimulation. Our analysis of changes in TMD was based on an already reported experiment on 15-week-old female mice (C57BL/6), where in one group the sixth caudal vertebra was mechanically loaded with 8N, while in the control group no loading was applied. Comparison of two consecutive images allows the categorization of bone into newly formed, resorbed, and quiescent bone for different time points. Gray values of bone in these categories were compared layer-wise to minimize the effects of beam hardening artifacts. Quiescent bone in the control group was found to mineralize with a rate of 8 ± 1 mgHA/cm(3) per week, which is about half as fast as observed for newly formed bone. Mechanical loading increased the rate of mineral incorporation by 63% in quiescent bone. The week before bone resorption, demineralization could be observed with a drop of TMD by 36 ± 4 mgHA/cm(3) in the control and 34 ± 3 mgHA/cm(3) in the loaded group. In conclusion, this study shows how time-lapsed in vivo micro-CT can be used to assess changes in TMD of bone with high spatial and temporal resolution. This will allow a quantification of how bone diseases and pharmaceutical interventions influence not only microarchitecture of trabecular bone, but also its material quality., (Copyright © 2013. Published by Elsevier Inc.)

Bone has the ability to adapt to external loading conditions. Especially the beneficial effect of short-term cyclic loading has been investigated in a number of in vivo animal studies. The aim of this study was to assess the long-term effect (>10 weeks) of cyclic mechanical loading on the bone microstructure, bone stiffness, and bone remodeling rates. Mice were subjected to cyclic mechanical loading at the sixth caudal vertebra with 8N or 0N (control) three times per week for a total period of 14 weeks. Structural bone parameters were determined from in vivo micro-computed tomography (micro-CT) scans performed at week 0, 4, 6, 8, 10, 12, and 14. Mechanical parameters were derived from micro-finite element analysis. Dynamic bone morphometry was calculated using registration of serial micro-CT scans. Bone volume fraction and trabecular thickness increased significantly more for the loaded group than for the control group (p = 0.006 and p = 0.002 respectively). The trabecular bone microstructure adapted to the load of 8N in approximately ten weeks, indicated by the trabecular bone volume fraction, which increased from 16.7% at 0 weeks to 21.6% at week 10 and only showed little change afterwards (bone volume fraction of 21.5% at 14 weeks). Similarly bone stiffness - (at the start of the experiment 649N/mm) - reached 846N/mm at 10 weeks in the loaded group and was maintained to the end of the experiment (850N/mm). At 4 weeks the bone formation rate was 32% greater and the bone resorption rate 22% less for 8N compared to 0N. This difference was significantly reduced as the bone adapted to 8N, with 8N remodeling rates returning to the values of the 0N group at approximately 10 weeks. Together these data suggest that once bone has adapted to a new loading state, the remodeling rates reduce gradually while maintaining bone volume fraction and stiffness., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Osteocytes are considered the skeletal mechanosensors. However, because osteocytes, particularly trabecular, are barely accessible to in vivo molecular analyses, very little is known on the signals transmitted by these cells to the extra-trabecular milieu. To investigate so called "osteocytic genes" involved in extracellular signaling, we have used a recently developed model whereby a single caudal mouse vertebra (C5) is subjected to controlled compression loading and further devised a method for the isolation of high quality RNA from trabecular osteocytes. RNA samples from loaded and sham-loaded individual vertebrae where then subjected to gene array analysis following the administration of a single or repetitive loading doses (thrice weekly for 4 weeks). Focusing on extracellular genes potentially involved in mediating osteocyte-derived signals to the trabecular surface, we identified sets of genes differentially regulated by either single or multiple loading bouts as well as genes affected by both loading protocols. A comparison with published studies on load-regulated genes in cortical osteocytes revealed that the majority of these genes are specifically activated/silenced in the trabecular bone. Many of these genes could be clustered according to processes directly relevant to the life cycle and activity of osteoblasts and osteoclasts and their progenitors. The present findings are consistent with an osteocytic role in the control of trabecular bone remodeling and mass and provide a comprehensive database of load-regulated genes in trabecular osteocytes that is potentially useful in further mouse genetic studies and identification of drug targets to combat osteoporosis., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Computational models are an invaluable tool to test different mechanobiological theories and, if validated properly, for predicting changes in individuals over time. Concise validation of in silico models, however, has been a bottleneck in the past due to a lack of appropriate reference data. Here, we present a strain-adaptive in silico algorithm which is validated by means of experimental in vivo loading data as well as by an in vivo ovariectomy experiment in the mouse. The maximum prediction error following four weeks of loading resulted in 2.4% in bone volume fraction (BV/TV) and 8.4% in other bone structural parameters. Bone formation and resorption rate did not differ significantly between experiment and simulation. The spatial distribution of formation and resorption sites matched in 55.4% of the surface voxels. Bone loss was simulated with a maximum prediction error of 12.1% in BV/TV and other bone morphometric indices, including a saturation level after a few weeks. Dynamic rates were more difficult to be accurately predicted, showing evidence for significant differences between simulation and experiment (p<0.05). The spatial agreement still amounted to 47.6%. In conclusion, we propose a computational model which was validated by means of experimental in vivo data. The predictive value of an in silico model may become of major importance if the computational model should be applied in clinical settings to predict bone changes due to disease and test the efficacy of potential pharmacological interventions., (Copyright © 2012 Elsevier Inc. All rights reserved.)

It is known that mechanical loading leads to an increase in bone mass through a positive shift in the balance between bone formation and bone resorption. How the remodeling sites change over time as an effect of loading remains, however, to be clarified. The purpose of this paper was to investigate how bone formation and resorption sites are modulated by mechanical loading over time by using a new imaging technique that extracts three dimensional formation and resorption parameters from time-lapsed in vivo micro-computed tomography images. To induce load adaptation, the sixth caudal vertebra of C57BL/6 mice was cyclically loaded through pins in the adjacent vertebrae at either 8 N or 0 N (control) three times a week for 5 min (3000 cycles) over a total of 4 weeks. The results showed that mechanical loading significantly increased trabecular bone volume fraction by 20% (p<0.001) and cortical area fraction by 6% (p<0.001). The bone formation rate was on average 23% greater (p<0.001) and the bone resorption rate was on average 25% smaller (p<0.001) for the 8 N group than for the 0 N group. The increase in bone formation rate for the 8 N group was mostly an effect of a significantly increased surface of bone formation sites (on average 16%, p<0.001), while the thickness of bone formation packages was less affected (on average 5% greater, p<0.05). At the same time the surface of bone resorption sites was significantly reduced (on average 15%, p<0.001), while the depth of resorption pits remained the same. For the 8 N group, the strength of the whole bone increased significantly by 24% (p<0.001) over the loading period, while the strain energy density in the trabecular bone decreased significantly by 24% (p<0.001). In conclusion, mouse tail vertebrae adapt to mechanical loading by increasing the surface of formation sites and decreasing the surface of resorption sites, leading to an overall increase in bone strength. This new imaging technique will provide opportunities to investigate in vivo bone remodeling in the context of disease and treatment options, with the added value that both bone formation and bone resorption parameters can be nondestructively calculated over time., (Copyright © 2011 Elsevier Inc. All rights reserved.)

Cyclic mechanical loading augments trabecular bone mass, mainly by increasing trabecular thickness. For this reason, we hypothesized that an in silico thickening algorithm using open-loop control would be sufficient to reliably predict the response of trabecular bone to cyclic mechanical loading. This would also mean that trabecular bone adaptation could be modeled as a system responding to an input signal at the onset of the process in a predefined manner, without feedback from the outputs. Here, time-lapsed in vivo micro-computed tomography scans of mice cyclically loaded at the sixth caudal vertebra were used to validate the in silico model. When comparing in silico and in vivo data sets after a period of four weeks, a maximum prediction error of 2.4% in bone volume fraction and 5.4% in other bone morphometric indices was calculated. Superimposition of sequentially acquired experimental images and simulated structures revealed that in silico simulations deposited thin and homogeneous layers of bone whilst the experiment was characterized by local areas of strong thickening, as well as considerable volumes of bone resorption. From the results, we concluded that the proposed computational algorithm predicted changes in bone volume fraction and global parameters of bone structure very well over a period of four weeks while it was unable to reproduce accurate spatial patterns of local bone formation and resorption. This study demonstrates the importance of validation of computational models through the use of experimental in vivo data, including the local comparison of simulated and experimental remodeling sites. It is assumed that the ability to accurately predict changes in bone micro-architecture will facilitate a deeper understanding of the cellular mechanisms underlying bone remodeling and adaptation due to mechanical loading., (Copyright © 2011 Elsevier Inc. All rights reserved.)

Bone is a living tissue able to adapt its structure to external influences such as altered mechanical loading. This adaptation process is governed by two distinct cell types: bone-forming cells called osteoblasts and bone-resorbing cells called osteoclasts. It is therefore of particular interest to have quantitative access to the outcomes of bone formation and resorption separately. This article presents a non-invasive three-dimensional technique to directly extract bone formation and resorption parameters from time-lapsed in vivo micro-computed tomography scans. This includes parameters such as Mineralizing Surface (MS), Mineral Apposition Rate (MAR), and Bone Formation Rate (BFR), which were defined in accordance to the current nomenclature of dynamic histomorphometry. Due to the time-lapsed and non-destructive nature of in vivo micro-computed tomography, not only formation but also resorption can now be assessed quantitatively and time-dependent parameters Eroded Surface (ES) as well as newly defined indices Mineral Resorption Rate (MRR) and Bone Resorption Rate (BRR) are introduced. For validation purposes, dynamic formation parameters were compared to the traditional quantitative measures of dynamic histomorphometry, where MAR correlated with R = 0.68 and MS with R = 0.78 (p < 0.05). Reproducibility was assessed in 8 samples that were scanned 5 times and errors ranged from 0.9% (MRR) to 6.6% (BRR). Furthermore, the new parameters were applied to a murine in vivo loading model. A comparison of directly extracted parameters between formation and resorption within each animal revealed that in the control group, i.e., during normal remodeling, MAR was significantly lower than MRR (p < 0.01), whereas MS compared to ES was significantly higher (p < 0.0001). This implies that normal remodeling seems to take place by many small formation packets and few but large resorption volumes. After 4 weeks of mechanical loading, newly extracted trabecular BFR and MS were significantly higher (p < 0.01) in the loading compared to the control group. At the same time, ES was significantly decreased (p < 0.01). This indicates that modeling induced by mechanical loading takes place primarily by increased area, not width of formation packets. With these results, we conclude that the non-invasive direct technique is well suited to extract dynamic bone morphometry parameters and eventually gain more insight into the processes of bone adaptation not only for formation but also resorption., (Copyright © 2010 Elsevier Inc. All rights reserved.)