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Biomedical Engineering / Biomedizinische Technik, 58 (Supplement 1), ISSN:0013-5585, ISSN:1862-278X

More accurate techniques to estimate fracture risk could help reduce the burden of fractures in postmenopausal women. Although micro-finite element (µFE) simulations allow a direct assessment of bone mechanical performance, in this first clinical study we investigated whether the additional information obtained using geometrically and materially nonlinear µFE simulations allows a better discrimination between fracture cases and controls. We used patient data and high-resolution peripheral quantitative computed tomography (HRpQCT) measurements from our previous clinical study on fracture risk, which compared 100 postmenopausal women with a distal forearm fracture to 105 controls. Analyzing these data with the nonlinear µFE simulations, the odds ratio (OR) for the factor-of-risk (yield load divided by the expected fall load) was marginally higher (1.99; 95% confidence interval [CI], 1.41–2.77) than for the factor-of-risk computed from linear µFE (1.89; 95% CI, 1.37–2.69). The yield load and the energy absorbed up to the yield point as computed from nonlinear µFE were highly correlated with the initial stiffness (R2 = 0.97 and 0.94, respectively) and could therefore be derived from linear simulations with little loss in precision. However, yield deformation was not related to any other measurement performed and was itself a good predictor of fracture risk (OR, 1.89; 95% CI, 1.39–2.63). Moreover, a combined risk score integrating information on relative bone strength (yield load-based factor-of-risk), bone ductility (yield deformation), and the structural integrity of the bone under critical loads (cortical plastic volume) improved the separation of cases and controls by one-third (OR, 2.66; 95% CI, 1.84–4.02). We therefore conclude that nonlinear µFE simulations provide important additional information on the risk of distal forearm fractures not accessible from linear µFE nor from other techniques assessing bone microstructure, density, or mass. © 2013 American Society for Bone and Mineral Research.

Bone strength at the ultradistal radius, quantified by micro-finite element modeling, can be predicted by variables obtained from high-resolution peripheral quantitative computed tomography scans. The specific formula for this bone strength surrogate (-555.2 + 8.1 × [trabecular vBMD] + 19.6 × [cortical area] + 4.2 × [total cross-sectional area]) should be validated and tested in fracture risk assessment.The purpose of this study was to identify key determinants of ultradistal radius (UDR) strength and evaluate their relationships with age, sex steroid levels, and measures of habitual skeletal loading.UDR failure load (~strength) was assessed by micro-finite element (μFE) modeling in 105 postmenopausal controls from an earlier forearm fracture case-control study. Predictors of bone strength obtained by high-resolution peripheral quantitative computed tomography (HRpQCT) in this group were then evaluated in a population-based cohort of 214 postmenopausal women. Sex steroids were measured by mass spectrometry.A surrogate variable (-555.2 + 8.1 × [trabecular vBMD] + 19.6 × [cortical area] + 4.2 × [total cross-sectional area]) predicted UDR strength modeled by μFE (R(2) = 0.81), and all parameters except total cross-sectional area declined with age. Evaluated cross-sectionally, the 21% fall in predicted bone strength between ages 40-49 years and 80+ years more resembled the change in trabecular volumetric bone mineral density (vBMD) (-15%) than that in cortical area (-41%). In multivariable analyses, measures of body composition and physical activity were stronger predictors of UDR trabecular vBMD, cortical area, total cross-sectional area, and predicted bone strength than were sex steroid levels, but bio-available estradiol and testosterone were correlated with body mass.Bone strength at the UDR, as quantified by μFE, can be predicted from variables obtained by HRpQCT. Predicted bone strength declines with age with changes in UDR trabecular vBMD and cortical area, related in turn to reduced skeletal loading and sex steroid levels. The predicted bone strength formula should be validated and tested in fracture risk assessment.

The risk of osteoporotic fractures is currently estimated based on an assessment of bone mass as measured by dual-energy X-ray absorptiometry. However, patient-specific finite element (FE) simulations that include information from multiple scales have the potential to allow more accurate prognosis. In the past, FE models of bone were limited either in resolution or to the linearization of the mechanical behaviour. Now, nonlinear, high-resolution simulations including the bone microstructure have been made possible by recent advances in simulation methods, computer infrastructure and imaging, allowing the implementation of multiscale modelling schemes. For example, the mechanical loads generated in the musculoskeletal system define the boundary conditions for organ-level, continuum-based FE models, whose nonlinear material properties are derived from microstructural information. Similarly microstructure models include tissue-level information such as the dynamic behaviour of collagen by modifying the model's constitutive law. This multiscale approach to modelling the mechanics of bone allows a more accurate characterization of bone fracture behaviour. Furthermore, such models could also include the effects of ageing, osteoporosis and drug treatment. Here we present the current state of the art for multiscale modelling and assess its potential to better predict an individual's risk of fracture in a clinical setting.

The incidence of distal forearm fractures peaks during the adolescent growth spurt, but the structural basis for this is unclear. Thus, we studied healthy 6- to 21-yr-old girls (n = 66) and boys (n = 61) using high-resolution pQCT (voxel size, 82 microm) at the distal radius. Subjects were classified into five groups by bone-age: group I (prepuberty, 6-8 yr), group II (early puberty, 9-11 yr), group III (midpuberty, 12-14 yr), group IV (late puberty, 15-17 yr), and group V (postpuberty, 18-21 yr). Compared with group I, trabecular parameters (bone volume fraction, trabecular number, and thickness) did not change in girls but increased in boys from late puberty onward. Cortical thickness and density decreased from pre- to midpuberty in girls but were unchanged in boys, before rising to higher levels at the end of puberty in both sexes. Total bone strength, assessed using microfinite element models, increased linearly across bone age groups in both sexes, with boys showing greater bone strength than girls after midpuberty. The proportion of load borne by cortical bone, and the ratio of cortical to trabecular bone volume, decreased transiently during mid- to late puberty in both sexes, with apparent cortical porosity peaking during this time. This mirrors the incidence of distal forearm fractures in prior studies. We conclude that regional deficits in cortical bone may underlie the adolescent peak in forearm fractures. Whether these deficits are more severe in children who sustain forearm fractures or persist into later life warrants further study.