Contribution of the intra-specimen variations in tissue mineralization to PTH- and raloxifene-induced changes in stiffness of rat vertebrae

Easley, Sarah K.; Jekir, Michael; Burghardt, Andrew J.; Li, Mei; Keaveny, Tony M.

doi:10.1016/j.bone.2009.12.009

Cited by 30 publications

(32 citation statements)

References 47 publications

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“…The mFEAs derived from the 12-mm isotropic voxel scan under predicted strength by 2 N, but the strength predictions were highly correlated with those from the high mesh density model (threshold ¼ 421.8 mg HA cm À 3 ). Figure 7 Of the published relationships to convert mCT-derived volumetric density to elastic modulus, this study used those derived by Wagner et al 32 , Easley et al 28 and Renders et al 35 The typical TMD range for this study is highlighted with the darker colors. A linear regression equation derived from the Wagner relationship (dashed white line) was used to calculate element-specific E t in the inhomogeneous mFEAs.…”

Section: Methodsmentioning

confidence: 99%

“…In doing so, TMD distribution was binned into 43-47 materials starting at 401.21 mg HA cm À 3 and incrementing by 22.96 mg HA cm À 3 until reaching the maximum TMD for the given scan ( Figure 7). The mean material density of each bin was converted to E t using either a first-order approximation of the relationship from Wagner et al 34 in the typical TMD range (420.1-1298.2 mg HA cm À 3 ; E t ¼ À 6034.6 þ 23.4 Â TMD; MPa from mgHA cm À 3 ) or using the relationship from Easley et al 28 Figure 7). Initially, the failure criteria of the Base Model were used in the inhomogeneous mFEAs, and then near optimal values were sought.…”

Section: Methodsmentioning

confidence: 99%

“…This typically involves converting the TMD of each element to E t using a theoretical relationship between TMD and E t . We investigated three published conversions: Wagner et al 34 (equation 1), Easley et al 28 and Renders et al 35 The use of an elementspecific E t to generate mFEA models improved the R 2 , regardless of whether the Wagner et al, 34 the Easley et al 28 or the Renders et al 35 relationship was used to convert TMD to E t (Table 1 and Figure 2). Keeping failure strain and failure volume set to 0.007 and 2%, respectively, results in an under-prediction of the peak force.…”

Section: Effect Of Varying Failure Volume For Homogenous Materials Promentioning

confidence: 99%

“…24 Moreover, mFEA of excised bones is non-destructive allowing for subsequent histological analysis. Although a number of studies involving rodents have used mFEA to determine the effect of drug treatment on bone strength, [25][26][27][28][29][30] there is little evidence in the literature establishing that mFEA can accurately predict the mechanical properties of rodent bone, and especially murine bones. Of the few studies comparing FEA predictions to experimental measurements of strength in rodent tissues, long bones were tested with limited examination of material definitions.…”

Section: Introductionmentioning

confidence: 99%

“…Avoiding the difficulties of sample preparation for material testing of rodent bone tissue, a few FEA studies of rodent bone developed constitutive relationships using available experimental data. One study fit a nonlinear equation to a compilation of E t and tissue mineral density (TMD) data acquired from different species and anatomical sites and using different modalities (for example, nanoindentation, tensile tests, scanning acoustic microscopy), 28 whereas another developed a linear scaling factor to determine tissue modulus from TMD based on the ratio of whole bone stiffness (determined experimentally by threepoint bending of a mouse femur) to the predicted stiffness derived from a mFEA of the same bone under similar boundary conditions. 31 In addition to the uncertainty regarding material behavior assumptions and directional dependence of rodent bone, failure criteria used in mFEA have also not been rigorously tested.…”

Section: Introductionmentioning

confidence: 99%

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Predicting mouse vertebra strength with micro-computed tomography-derived finite element analysis

Nyman¹,

Uppuganti²,

Makowski³

et al. 2015

BoneKEy Reports

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As in clinical studies, finite element analysis (FEA) developed from computed tomography (CT) images of bones are useful in pre-clinical rodent studies assessing treatment effects on vertebral body (VB) strength. Since strength predictions from microCT-derived FEAs (mFEA) have not been validated against experimental measurements of mouse VB strength, a parametric analysis exploring material and failure definitions was performed to determine whether elastic mFEAs with linear failure criteria could reasonably assess VB strength in two studies, treatment and genetic, with differences in bone volume fraction between the control and the experimental groups. VBs were scanned with a 12-mm voxel size, and voxels were directly converted to 8-node, hexahedral elements. The coefficient of determination or R 2 between predicted VB strength and experimental VB strength, as determined from compression tests, was 62.3% for the treatment study and 85.3% for the genetic study when using a homogenous tissue modulus (E t ) of 18 GPa for all elements, a failure volume of 2%, and an equivalent failure strain of 0.007. The difference between prediction and measurement (that is, error) increased when lowering the failure volume to 0.1% or increasing it to 4%. Using inhomogeneous tissue density-specific moduli improved the R 2 between predicted and experimental strength when compared with uniform E t ¼ 18 GPa. Also, the optimum failure volume is higher for the inhomogeneous than for the homogeneous material definition. Regardless of model assumptions, mFEA can assess differences in murine VB strength between experimental groups when the expected difference in strength is at least 20%.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Effect Of Varying Failure Volume For Homogenous Materials Promentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Predicting mouse vertebra strength with micro-computed tomography-derived finite element analysis

Nyman¹,

Uppuganti²,

Makowski³

et al. 2015

BoneKEy Reports

View full text Add to dashboard Cite

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Contributions of Material Properties and Structure to Increased Bone Fragility for a Given Bone Mass in the UCD-T2DM Rat Model of Type 2 Diabetes

Acevedo

Sylvia

Schaible³

et al. 2018

Journal of Bone and Mineral Research

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Adults with type 2 diabetes (T2D) have a higher fracture risk for a given bone quantity, but the mechanisms remain unclear. Using a rat model of polygenic obese T2D, we demonstrate that diabetes significantly reduces whole-bone strength for a given bone mass (μCT-derived BMC), and we quantify the roles of T2D-induced deficits in material properties versus bone structure; ie, geometry and microarchitecture. Lumbar vertebrae and ulnae were harvested from 6-month-old lean Sprague-Dawley rats, obese Sprague-Dawley rats, and diabetic obese UCD-T2DM rats (diabetic for 69 ± 7 days; blood glucose >200 mg/dL). Both obese rats and those with diabetes had reduced whole-bone strength for a given BMC. In obese rats, this was attributable to structural deficits, whereas in UCD-T2DM rats, this was attributable to structural deficits and to deficits in tissue material properties. For the vertebra, deficits in bone structure included thinner and more rod-like trabeculae; for the ulnae, these deficits included inefficient distribution of bone mass to resist bending. Deficits in ulnar material properties in UCD-T2DM rats were associated with increased non-enzymatic crosslinking and impaired collagen fibril deformation. Specifically, small-angle X-ray scattering revealed that diabetes reduced collagen fibril ultimate strain by 40%, and those changes coincided with significant reductions in the elastic, yield, and ultimate tensile properties of the bone tissue. Importantly, the biomechanical effects of these material property deficits were substantial. Prescribing diabetes-specific tissue yield strains in high-resolution finite element models reduced whole-bone strength by a similar amount (and in some cases a 3.4-fold greater amount) as the structural deficits. These findings provide insight into factors that increase bone fragility for a given bone mass in T2D; not only does diabetes associate with less biomechanically efficient bone structure, but diabetes also reduces tissue ductility by limiting collagen fibril deformation, and in doing so, reduces the maximum load capacity of the bone. © 2018 American Society for Bone and Mineral Research.

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Age Dependence of Systemic Bone Loss and Recovery Following Femur Fracture in Mice

Emami

Toupadakis

Telek

et al. 2018

Journal of Bone and Mineral Research

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The most reliable predictor of future fracture risk is a previous fracture of any kind. The etiology of this increased fracture risk is not fully known, but it is possible that fracture initiates systemic bone loss, leading to greater fracture risk at all skeletal sites. In this study, we investigated systemic bone loss and recovery after femoral fracture in young (3-month-old) and middle-aged (12-month-old) mice. Transverse femur fractures were created using a controlled impact, and whole-body bone mineral density (BMD), trabecular and cortical microstructure, bone mechanical properties, bone formation and resorption rates, mouse voluntary movement, and systemic inflammation were quantified at multiple time points post-fracture. We found that fracture led to decreased whole-body BMD in both young and middle-aged mice 2 weeks post-fracture; this bone loss was recovered by 6 weeks in young but not middle-aged mice. Similarly, trabecular bone volume fraction (BV/TV) of the L5 vertebral body was significantly reduced in fractured mice relative to control mice 2 weeks post-fracture (-11% for young mice, -18% for middle-aged mice); no significant differences were observed 6 weeks post-fracture. At 3 days post-fracture, we observed significant increases in serum levels of interleukin-6 and significant decreases in voluntary movement in fractured mice compared with control mice, with considerably greater changes in middle-aged mice than in young mice. At this time point, we also observed increased osteoclast number on L5 vertebral body trabecular bone of fractured mice compared with control mice. These data show that systemic bone loss occurs after fracture in both young and middle-aged mice, and recovery from this bone loss may vary with age. This systemic response could contribute to increased future fracture risk after fracture; these data may inform clinical treatment of fractures with respect to improving long-term skeletal health. © 2018 American Society for Bone and Mineral Research.

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Contribution of the intra-specimen variations in tissue mineralization to PTH- and raloxifene-induced changes in stiffness of rat vertebrae

Cited by 30 publications

References 47 publications

Predicting mouse vertebra strength with micro-computed tomography-derived finite element analysis

Predicting mouse vertebra strength with micro-computed tomography-derived finite element analysis

Contributions of Material Properties and Structure to Increased Bone Fragility for a Given Bone Mass in the UCD-T2DM Rat Model of Type 2 Diabetes

Age Dependence of Systemic Bone Loss and Recovery Following Femur Fracture in Mice

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