Superlative mechanical energy absorbing efficiency discovered through self-driving lab-human partnership.

Energy absorbing efficiency is a key determinant of a structure's ability to provide mechanical protection and is defined by the amount of energy that can be absorbed prior to stresses increasing to a level that damages the system to be protected. Here, we explore the energy absorbing efficiency of additively manufactured polymer structures by using a self-driving lab (SDL) to perform >25,000 physical experiments on generalized cylindrical shells. We use a human-SDL collaborative approach where experiments are selected from over trillions of candidates in an 11-dimensional parameter space using Bayesian optimization and then automatically performed while the human team monitors progress to periodically modify aspects of the system. The result of this human-SDL campaign is the discovery of a structure with a 75.2% energy absorbing efficiency and a library of experimental data that reveals transferable principles for designing tough structures.

Geometric determinants of the mechanical behavior of image-based finite element models of the intervertebral disc.

The intervertebral disc is an important structure for load transfer through the spine. Its injury and degeneration have been linked to pain and spinal fractures. Disc injury and spine fractures are associated with high stresses; however, these stresses cannot be measured, necessitating the use of finite element (FE) models. These models should include the disc's complex structure, as changes in disc geometry have been linked to altered mechanical behavior. However, image-based models using disc-specific structures have yet to be established. This study describes a multiphasic FE modeling approach for noninvasive estimates of subject-specific intervertebral disc mechanical behavior based on medical imaging. The models (n = 22) were used to study the influence of disc geometry on the predicted global mechanical response (moments and forces), internal local disc stresses, and tractions at the interface between the disc and the bone. Disc geometry was found to have a strong influence on the predicted moments and forces on the disc (R2 = 0.69-0.93), while assumptions regarding the side curvature (bulge) of the disc had only a minor effect. Strong variability in the predicted internal disc stresses and tractions was observed between the models (mean absolute differences of 5.1%-27.7%). Disc height had a systematic influence on the internal disc stresses and tractions at the disc-to-bone interface. The influence of disc geometry on mechanics highlights the importance of disc-specific modeling to estimate disc injury risk, loading on the adjacent vertebral bodies, and the mechanical environment present in disc tissues.

Harnessing mechanical cues in the cellular microenvironment for bone regeneration.

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.

Multiscale theoretical model shows that aging-related mechanical degradation of cortical bone is driven by microstructural changes in addition to porosity.

This study aims to gain mechanistic understanding of how aging-related changes in the microstructure of cortical bone drive mechanical consequences at the macroscale. To that end, cortical bone was modeled as a bundle of elastic-plastic, parallel fibers, which represented osteons and interstitial tissue, loaded in uniaxial tension. Distinct material properties were assigned to each fiber in either the osteon or interstitial fiber "families." Models representative of mature (20-60 yrs.) bone, and elderly (60+) bone were created by modeling aging via the following changes to the input parameters: (i) increasing porosity from 5% to 15%, (ii) increasing the ratio of the number of osteon fibers relative to interstitial fibers from 40% to 50%, and (iii) changing the fiber material properties from representing mature bone samples to representing elderly bone samples (i.e., increased strength and decreased toughness of interstitial fibers together with decreased toughness of osteon fibers). To understand the respective contributions of these changes, additional models isolating one or two of each of these were also created. From the computed stress-strain curve for the fiber bundle, the yield point (ϵy, σy), ultimate point (ϵu, σu), and toughness (UT) for the bundle as a whole were measured. We found that changes to all three input parameters were required for the model to capture the aging-related decline in cortical bone mechanical properties consistent with those previously reported in the literature. In both mature and elderly bundles, rupture of the interstitial fibers drove the initial loss of strength following the ultimate point. Plasticity and more gradual rupture of the osteons drove the remainder of the response. Both the onset and completion of interstitial fiber rupture occurred at lower strains in the elderly vs. mature case. These findings point to the importance of studying microstructural changes beyond porosity, such as the area fraction of osteons and the material properties of osteon and interstitial tissue, in order to further understanding of aging-related changes in bone.

Biomechanical structure-function relations for human trabecular bone - comparison of calcaneus, femoral neck, greater trochanter, proximal tibia, and vertebra.

MicroCT-based finite element models were used to compute power law relations for uniaxial compressive yield stress versus bone volume fraction for 78 cores of human trabecular bone from five anatomic sites. The leading coefficient of the power law for calcaneus differed from those for most of the other sites (p < 0.05). However, after normalizing by site-specific mean values, neither the leading coefficient (p > 0.5) nor exponent (p > 0.5) differed among sites, suggesting that a given percentage deviation from mean bone volume fraction has the same mechanical consequence for all sites investigated. These findings help explain the success of calcaneal x-ray and ultrasound measurements for predicting hip fracture risk.

An in silico micro-multiphysics agent-based approach for simulating bone regeneration in a mouse femur defect model.

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.

A Review of CT-Based Fracture Risk Assessment with Finite Element Modeling and Machine Learning.

PURPOSE OF REVIEW: We reviewed advances over the past 3 years in assessment of fracture risk based on CT scans, considering methods that use finite element models, machine learning, or a combination of both. RECENT FINDINGS: Several studies have demonstrated that CT-based assessment of fracture risk, using finite element modeling or biomarkers derived from machine learning, is equivalent to currently used clinical tools. Phantomless calibration of CT scans for bone mineral density enables accurate measurements from routinely taken scans. This opportunistic use of CT scans for fracture risk assessment is facilitated by high-quality automated segmentation with deep learning, enabling workflows that do not require user intervention. Modeling of more realistic and diverse loading conditions, as well as improved modeling of fracture mechanisms, has shown promise to enhance our understanding of fracture processes and improve the assessment of fracture risk beyond the performance of current clinical tools. CT-based screening for fracture risk is effective and, by analyzing scans that were taken for other indications, could be used to expand the pool of people screened, therefore improving fracture prevention. Finite element modeling and machine learning both provide valuable tools for fracture risk assessment. Future approaches should focus on including more loading-related aspects of fracture risk.

Identification of Known and Novel Long Noncoding RNAs Potentially Responsible for the Effects of Bone Mineral Density (BMD) Genomewide Association Study (GWAS) Loci.

Osteoporosis, characterized by low bone mineral density (BMD), is the most common complex disease affecting bone and constitutes a major societal health problem. Genome-wide association studies (GWASs) have identified over 1100 associations influencing BMD. It has been shown that perturbations to long noncoding RNAs (lncRNAs) influence BMD and the activities of bone cells; however, the extent to which lncRNAs are involved in the genetic regulation of BMD is unknown. Here, we combined the analysis of allelic imbalance (AI) in human acetabular bone fragments with a transcriptome-wide association study (TWAS) and expression quantitative trait loci (eQTL) colocalization analysis using data from the Genotype-Tissue Expression (GTEx) project to identify lncRNAs potentially responsible for GWAS associations. We identified 27 lncRNAs in bone that are located in proximity to a BMD GWAS association and harbor single-nucleotide polymorphisms (SNPs) demonstrating AI. Using GTEx data we identified an additional 31 lncRNAs whose expression was associated (false discovery rate [FDR] correction < 0.05) with BMD through TWAS and had a colocalizing eQTL (regional colocalization probability [RCP] > 0.1). The 58 lncRNAs are located in 43 BMD associations. To further support a causal role for the identified lncRNAs, we show that 23 of the 58 lncRNAs are differentially expressed as a function of osteoblast differentiation. Our approach identifies lncRNAs that are potentially responsible for BMD GWAS associations and suggest that lncRNAs play a role in the genetics of osteoporosis. © 2022 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

Identification and Characterization of a Novel Long Noncoding RNA that Regulates Osteogenesis in Diet-Induced Obesity Mice.

As a precursor to type 2 diabetes mellitus (T2D), obesity adversely alters bone cell functions, causing decreased bone quality. Currently, the mechanisms leading to alterations in bone quality in obesity and subsequently T2D are largely unclear. Emerging evidence suggests that long noncoding RNAs (lncRNAs) participate in a vast repertoire of biological processes and play essential roles in gene expression and posttranscriptional processes. Mechanistically, the expression of lncRNAs is implicated in pathogenesis surrounding the aggregation or alleviation of human diseases. To investigate the functional link between specific lncRNA and obesity-associated poor bone quality and elucidate the molecular mechanisms underlying the interaction between the two, we first assessed the structure of the bones in a diet-induced obese (DIO) mouse model. We found that bone microarchitecture markedly deteriorated in the DIO mice, mainly because of aberrant remodeling in the bone structure. The results of in vitro mechanistic experiments supported these observations. We then screened mRNAs and lncRNAs from DIO bones and functionally identified a specific lncRNA, Gm15222. Further analyses demonstrated that Gm15222 promotes osteogenesis and inhibits the expression of adipogenesis-related genes in DIO via recruitment of lysine demethylases KDM6B and KDM4B, respectively. Through this epigenetic pathway, Gm15222 modulates histone methylation of osteogenic genes. In addition, Gm15222 showed a positive correlation with the expression of a neighboring gene, BMP4. Together, the results of this study identified and provided initial characterization of Gm15222 as a critical epigenetic modifier that regulates osteogenesis and has potential roles in targeting the pathophysiology of bone disease in obesity and potential T2D.

Temporal and Quantitative Transcriptomic Differences Define Sexual Dimorphism in Murine Postnatal Bone Aging.

Time is a central element of the sexual dimorphic patterns of development, pathology, and aging of the skeleton. Because the transcriptome is a representation of the phenome, we hypothesized that both sex and sex-specific temporal, transcriptomic differences in bone tissues over an 18-month period would be informative to the underlying molecular processes that lead to postnatal sexual dimorphism. Regardless of age, sex-associated changes of the whole bone transcriptomes were primarily associated not only with bone but also vascular and connective tissue ontologies. A pattern-based approach used to screen the entire Gene Expression Omnibus (GEO) database against those that were sex-specific in bone identified two coordinately regulated gene sets: one related to high phosphate-induced aortic calcification and one induced by mechanical stimulation in bone. Temporal clustering of the transcriptome identified two skeletal tissue-associated, sex-specific patterns of gene expression. One set of genes, associated with skeletal patterning and morphology, showed peak expression earlier in females. The second set of genes, associated with coupled remodeling, had quantitatively higher expression in females and exhibited a broad peak between 3 to 12 months, concurrent with the animals' reproductive period. Results of phenome-level structural assessments of the tibia and vertebrae, and in vivo and in vitro analysis of cells having osteogenic potential, were consistent with the existence of functionally unique, skeletogenic cell populations that are separately responsible for appositional growth and intramedullary functions. These data suggest that skeletal sexual dimorphism arises through sex-specific, temporally different processes controlling morphometric growth and later coupled remodeling of the skeleton during the reproductive period of the animal. © 2021 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

Spatial assessment of femoral neck bone density and microstructure in hip osteoarthritis.

Osteoarthritis (OA) is known to involve profound changes in bone density and microstructure near to, and even distal to, the joint. Critically, however, a full, spatial picture of these abnormalities has not been well documented in a quantitative fashion in hip OA. Here, micro-computed tomography (44.8 µm/voxel) and data-driven computational anatomy were used to generate 3-D maps of the distribution of bone density and microstructure in human femoral neck samples with early (6F/4M, mean age = 51.3 years), moderate (14F/8M, mean age = 60 years), and severe (16F/6M, mean age = 63.3 years) radiographic OA. With increasing severity of radiographic OA, there was decreased cortical bone mineral density (BMD) (p=0.003), increased cortical thickness (p=0.001), increased cortical porosity (p=0.0028), and increased cortical cross-sectional area (p=0.0012, due to an increase in periosteal radius (p=0.018)), with no differences detected in the total femoral neck or trabecular compartment measures. No OA-related region-specific differences were detected through Statistical Parametric Mapping, but there were trends towards decreased tissue mineral density (TMD) in the inferior femoral neck with increasing OA severity (0.050 < p ≤ 0.091), possibly due to osteophytes. Overall, the lack of differences in cortical TMD among radiographic OA groups indicated that the decrease in cortical BMD with increasing OA severity was largely due to the increased cortical porosity rather than decreased tissue mineralization. As porosity is inversely associated with stiffness and strength in cortical bone, increased porosity may offset the effect that increased cortical cross-sectional area would be expected to have on reducing stresses within the femoral neck. The use of high-resolution imaging and quantitative spatial assessment in this study provide insight into the heterogeneous and multi-faceted changes in density and microstructure in hip OA, which have implications for OA progression and fracture risk.

Roles and Mechanisms of Irisin in Attenuating Pathological Features of Osteoarthritis.

To investigate the effects and mechanisms of irisin, a newly discovered myokine, in cartilage development, osteoarthritis (OA) pathophysiology and its therapeutic potential for treating OA we applied the following five strategical analyses using (1) murine joint tissues at different developmental stages; (2) human normal and OA pathological tissue samples; (3) experimental OA mouse model; (4) irisin gene knockout (KO) and knock in (KI) mouse lines and their cartilage cells; (5) in vitro mechanistic experiments. We found that Irisin was involved in all stages of cartilage development. Both human and mouse OA tissues showed a decreased expression of irisin. Intra-articular injection of irisin attenuated ACLT-induced OA progression. Irisin knockout mice developed severe OA while irisin overexpression in both irisin KI mice and intraarticular injection of irisin protein attenuated OA progression. Irisin inhibited inflammation and promoted anabolism in chondrogenic ADTC5 cells. Proliferative potential of primary chondrocytes from KI mice was found to be enhanced, while KO mice showed an inhibition under normal or inflammatory conditions. The primary chondrocytes from irisin KI mice showed reduced expression of inflammatory factors and the chondrocytes isolated from KO mice showed an opposite pattern. In conclusion, it is the first time to show that irisin is involved in cartilage development and OA pathogenesis. Irisin has the potential to ameliorate OA progression by decreasing cartilage degradation and inhibiting inflammation, which could lead to the development of a novel therapeutic target for treating bone and cartilage disorders including osteoarthritis.

Using simulation to accelerate autonomous experimentation: A case study using mechanics.

Autonomous experimentation (AE) accelerates research by combining automation and machine learning to perform experiments intelligently and rapidly in a sequential fashion. While AE systems are most needed to study properties that cannot be predicted analytically or computationally, even imperfect predictions can in principle be useful. Here, we investigate whether imperfect data from simulation can accelerate AE using a case study on the mechanics of additively manufactured structures. Initially, we study resilience, a property that is well-predicted by finite element analysis (FEA), and find that FEA can be used to build a Bayesian prior and experimental data can be integrated using discrepancy modeling to reduce the number of needed experiments ten-fold. Next, we study toughness, a property not well-predicted by FEA and find that FEA can still improve learning by transforming experimental data and guiding experiment selection. These results highlight multiple ways that simulation can improve AE through transfer learning.

Overview of Skeletal Repair (Fracture Healing and Its Assessment).

The study of postnatal skeletal repair is of immense clinical interest. Optimal repair of skeletal tissue is necessary in all varieties of elective and reparative orthopedic surgical treatments. However, the repair of fractures is unique in this context in that fractures are one of the most common traumas that humans experience and are the end-point manifestation of osteoporosis, the most common chronic disease of aging. In the first part of this introduction the basic biology of fracture healing is presented. The second part discusses the primary methodological approaches that are used to examine repair of skeletal hard tissue and specific considerations for choosing among and implementing these approaches.

Generation of Closed Transverse Fractures in Small Animals.

The most common procedure that has been developed for use in rats and mice to model fracture healing is described. The nature of the regenerative processes that may be assessed and the types of research questions that may be addressed with this model are briefly outlined. The detailed surgical protocol to generate closed simple transverse fractures is presented and general considerations when setting up an experiment using this model are described.

Trabecular Architecture and Mechanical Heterogeneity Effects on Vertebral Body Strength.

PURPOSE OF REVIEW: We aimed to synthesize the recent work on the intra-vertebral heterogeneity in density, trabecular architecture and mechanical properties, its implications for fracture risk, its association with degeneration of the intervertebral discs, and its implications for implant design. RECENT FINDINGS: As compared to the peripheral regions of the centrum, the central region of the vertebral body exhibits lower density and more sparse microstructure. As compared to the anterior region, the posterior region shows higher density. These variations are more pronounced in vertebrae from older persons and in those adjacent to degenerated discs. Mixed results have been reported in regard to variation along the superior-inferior axis and to relationships between the heterogeneity in density and vertebral strength and fracture risk. These discrepancies highlight that, first, despite the large amount of study of the intra-vertebral heterogeneity in microstructure, direct study of that in mechanical properties has lagged, and second, more measurements of vertebral loading are needed to understand how the heterogeneity affects distributions of stress and strain in the vertebra. These future areas of study are relevant not only to the question of spine fractures but also to the design and selection of implants for spine fusion and disc replacement. The intra-vertebral heterogeneity in microstructure and mechanical properties may be a product of mechanical adaptation as well as a key determinant of the ability of the vertebral body to withstand a given type of loading.

A Bayesian experimental autonomous researcher for mechanical design.

While additive manufacturing (AM) has facilitated the production of complex structures, it has also highlighted the immense challenge inherent in identifying the optimum AM structure for a given application. Numerical methods are important tools for optimization, but experiment remains the gold standard for studying nonlinear, but critical, mechanical properties such as toughness. To address the vastness of AM design space and the need for experiment, we develop a Bayesian experimental autonomous researcher (BEAR) that combines Bayesian optimization and high-throughput automated experimentation. In addition to rapidly performing experiments, the BEAR leverages iterative experimentation by selecting experiments based on all available results. Using the BEAR, we explore the toughness of a parametric family of structures and observe an almost 60-fold reduction in the number of experiments needed to identify high-performing structures relative to a grid-based search. These results show the value of machine learning in experimental fields where data are sparse.

Effect of fabric on the accuracy of computed tomography-based finite element analyses of the vertebra.

Quantitative computed tomography (QCT)-based finite element (FE) models of the vertebra are widely used in studying spine biomechanics and mechanobiology, but their accuracy has not been fully established. Although the models typically assign material properties based only on local bone mineral density (BMD), the mechanical behavior of trabecular bone also depends on fabric. The goal of this study was to determine the effect of incorporating measurements of fabric on the accuracy of FE predictions of vertebral deformation. Accuracy was assessed by using displacement fields measured via digital volume correlation-applied to time-lapse microcomputed tomography (µCT)-as the gold standard. Two QCT-based FE models were generated from human L1 vertebrae (n = 11): the entire vertebral body and a cuboid-shaped portion of the trabecular centrum [dimensions: (20-30) × (15-20) × (15-20) mm3]. For axial compression boundary conditions, there was no difference (p = 0.40) in the accuracy of the FE-computed displacements for models using material properties based on local values of BMD versus those using material properties based on local values of fabric and volume fraction. However, when using BMD-based material properties, errors were higher for the vertebral-body models (8.4-50.1%) than cuboid models (1.5-19.6%), suggesting that these properties are inaccurate in the peripheral regions of the centrum. Errors also increased when assuming that the cuboid region experienced uniaxial loading during axial compression of the vertebra. These findings indicate that a BMD-based constitutive model is not sufficient for the peripheral region of the vertebral body when seeking accurate QCT-based FE modeling of the vertebra.

Heterogeneity and Spatial Distribution of Intravertebral Trabecular Bone Mineral Density in the Lumbar Spine Is Associated With Prevalent Vertebral Fracture.

The spatial heterogeneity in trabecular bone density within the vertebral centrum is associated with vertebral strength and could explain why volumetric bone mineral density (vBMD) exhibits low sensitivity in identifying fracture risk. This study evaluated whether the heterogeneity and spatial distribution of trabecular vBMD are associated with prevalent vertebral fracture. We examined the volumetric quantitative computed tomography (QCT) scans of the L3 vertebra in 148 participants in the Framingham Heart Study Multidetector CT study. Of these individuals, 37 were identified as cases of prevalent fracture, and 111 were controls, matched on sex and age with three controls per case. vBMD was calculated within 5-mm contiguous cubic regions of the centrum. Two measures of heterogeneity were calculated: (i) interquartile range (IQR); and (ii) quartile coefficient of variation (QCV). Ratios in the spatial distributions of the trabecular vBMD were also calculated: anterior/posterior, central/outer, superior/mid-transverse, and inferior/mid-transverse. Heterogeneity and spatial distributions were compared between cases and controls using Wilcoxon rank sum tests and t tests and tested for association with prevalent fractures with conditional logistic regressions independent of integral vBMD. Prevalent fracture cases had lower mean ± SD integral vBMD (134 ± 38 versus165 ± 42 mg/cm3 , p < .001), higher QCV (0.22 ± 0.13 versus 0.17 ± 0.09, p = .003), and lower anterior/posterior rBMD (0.65 ± 0.13 versus 0.78 ± 0.16, p < .001) than controls. QCV was positively associated with increased odds of prevalent fracture (OR 1.61; 95% CI, 1.04 to 2.49; p = .034), but this association was not independent of integral vBMD (p = .598). Increased anterior/posterior trabecular vBMD ratio was associated with decreased odds of prevalent fracture independent of integral vBMD (OR 0.38; 95% CI, 0.20 to 0.71; p = .003). In conclusion, increased trabecular vBMD in the anterior versus posterior centrum, but not trabecular vBMD heterogeneity, was associated with decreased risk of prevalent fracture independent of integral vBMD. Regional measurements of trabecular vBMD could aid in determining the risk and underlying mechanisms of vertebral fracture. © 2019 American Society for Bone and Mineral Research.

Association of vertebral endplate microstructure with bone strength in men and women.

Epidemiological and biomechanical evidence indicates that the risk of vertebral fracture differs between men and women, and that vertebral fracture frequently involves failure of the endplate region. The goal of this study was to compare the bone microstructure of the endplate region-defined as the (bony) vertebral endplate and underlying subchondral trabecular bone-between sexes and to determine whether any such sex differences are associated with vertebral strength. The bone density (volume fraction, apparent density and tissue mineral density) of the superior-most 2 mm of the vertebra, and the bone density and trabecular architecture of the next 5 mm were quantified using micro-computed tomography in human T8 (12 female, 16 male) and L1 (13 female, 12 male) vertebrae. Average density of the vertebra (integral bone mineral density (BMD)) was determined by quantitative computed tomography and compressive strength by mechanical testing. Few differences were found between male and female vertebrae in the density of the endplate region; none were found in trabecular architecture. However, whereas endplate volume fraction was positively correlated with integral BMD in male vertebrae (r = 0.654, p < .001), no correlation was found in the female vertebrae (r = 0.157, p = .455). Accounting for the density of the endplate region improved predictions of vertebral strength (p < .034) and eliminated sex-specificity in the strength prediction that was based on integral BMD alone. These results suggest that the density of the endplate region influences vertebral fracture and that non-invasive assessment of this region's density can contribute to predictions of vertebral strength in men and women.