For a proper assessment of osteoporotic fragility fracture prediction, all aspects regarding bone mineral density, bone texture, geometry and information about strength are necessary, particularly in endocrinological and rheumatological diseases, where bone quality impairment is relevant. Data regarding bone quantity (density) and, partially, bone quality (structure and geometry) are obtained by the gold standard method of dual X-ray absorptiometry (DXA). Data about bone strength are not yet readily available. To evaluate bone resistance to strain, a new DXA-derived index based on the Finite Element Analysis (FEA) of a greyscale of density distribution measured on spine and femoral scan, namely Bone Strain Index (BSI), has recently been developed. Bone Strain Index includes local information on density distribution, bone geometry and loadings and it differs from bone mineral density (BMD) and other variables of bone quality like trabecular bone score (TBS), which are all based on the quantification of bone mass and distribution averaged over the scanned region. This state of the art review illustrates the methodology of BSI calculation, the findings of its in reproducibility and the preliminary data about its capability to predict fragility fracture and to monitor the follow up of the pharmacological treatment for osteoporosis.

Bone’s resistance to fracture depends on several factors, such as bone mass, microarchitecture, and tissue material properties. The clinical assessment of bone strength is generally performed by Dual-X Ray Photon Absorptiometry (DXA), measuring bone mineral density (BMD) and trabecular bone score (TBS). Although it is considered the major predictor of bone strength, BMD only accounts for about 70% of fragility fractures, while the remaining 30% could be described by bone “quality” impairment parameters, mainly related to tissue microarchitecture. The assessment of bone microarchitecture generally requires more invasive techniques, which are not applicable in routine clinical practice, or X-Ray based imaging techniques, requiring a longer post-processing. Another important aspect is the presence of local damage in the bony tissue that may also affect the prediction of bone strength and fracture risk. To provide a more comprehensive analysis of bone quality and quantity, and to assess the effect of damage, here we adopt a framework that includes clinical, morphological, and mechanical analyses, carried out by means of DXA, μCT and mechanical compressive testing, respectively. This study has been carried out on trabecular bones, taken from porcine trabecular vertebrae, for the similarity with human lumbar spine. This study confirms that no single method can provide a complete characterization of bone tissue, and the combination of complementary characterization techniques is required for an accurate and exhaustive description of bone status. BMD and TBS have shown to be complementary parameters to assess bone strength, the former assessing the bone quantity and resistance to damage, and the latter the bone quality and the presence of damage accumulation without being able to predict the risk of fracture.

The consolidated way of diagnosing and treating osteoporosis in order to prevent fragility fractures has recently been questioned by some papers, which complained of overdiagnosis and consequent overtreatment of this pathology with underestimating other causes of the fragility fractures, like falls. A new clinical approach is proposed for identifying the subgroup of patients prone to fragility fractures.This retrospective observational study was conducted from January to June 2015 at the Nuclear Medicine-Bone Metabolic Unit of the of the Fondazione IRCCS Ca' Granda, Milan, Italy. An Italian population of 125 consecutive postmenopausal women was investigated for bone quantity and bone quality. Patients with neurological diseases regarding balance and vestibular dysfunction, sarcopenia, past or current history of diseases and use of drugs known to affect bone metabolism were excluded. Dual X-ray absorptiometry was used to assess bone quantity (bone mineral density) and bone quality (trabecular bone score and bone strain). Biochemical markers of bone turnover (type I collagen carboxy-terminal telopeptide, alkaline phosphatase, vitamin D) have been measured. Morphometric fractures have been searched by spine radiography. Balance was evaluated by the Romberg test. The data were evaluated with the neural network analysis using the Auto Contractive Map algorithm. The resulting semantic map shows the Minimal Spanning Tree and the Maximally Regular Graph of the interrelations between bone status parameters, balance conditions and fractures of the studied population. A low fracture risk seems to be related to a low carboxy-terminal cross-linking telopeptide of type I collagen level, whereas a positive Romberg test, together with compromised bone trabecular microarchitecture DXA parameters, appears to be strictly connected with fragility fractures. A simple assessment of the risk of fragility fracture is proposed in order to identify those frail patients at risk for osteoporotic fractures, who may have the best benefit from a pharmacological and physiotherapeutic approach.

Dual Energy X-Ray Absorptiometry (DXA) is currently the most widely adopted non-invasive clinical technique to assess bone mineral density and bone mineral content in human research and represents the primary tool for the diagnosis of osteoporosis. DXA measures areal bone mineral density, BMD, which does not account for the three-dimensional structure of the vertebrae and for the distribution of bone mass. The result is that longitudinal DXA can only predict about 70% of vertebral fractures. This study proposes a complementary tool, based on Finite Element (FE) models, to improve the DXA accuracy. Bone is simulated as elastic and inhomogeneous material, with stiffness distribution derived from DXA greyscale images of density. The numerical procedure simulates a compressive load on each vertebra to evaluate the local minimum principal strain values. From these values, both the local average and the maximum strains are computed over the cross sections and along the height of the analysed bone region, to provide a parameter, named Strain Index of Bone (SIB), which could be considered as a bone fragility index. The procedure is initially validated on 33 cylindrical trabecular bone samples obtained from porcine lumbar vertebrae, experimentally tested under static compressive loading. Comparing the experimental mechanical parameters with the SIB, we could find a higher correlation of the ultimate stress, σULT, with the SIB values (R2adj = 0.63) than that observed with the conventional DXA-based clinical parameters, i.e. Bone Mineral Density, BMD (R2adj = 0.34) and Trabecular Bone Score, TBS (R2adj = -0.03). The paper finally presents a few case studies of numerical simulations carried out on human lumbar vertebrae. If our results are confirmed in prospective studies, SIB could be used—together with BMD and TBS—to improve the fracture risk assessment and support the clinical decision to assume specific drugs for metabolic bone diseases.

Osteoporotic fracture incidence represents a major social and economic concern in the modern society, where the progressive graying of the population involves an highly increased fracture occurrence. Although the gold standard to diagnose osteoporosis is represented by the T-score measurement, estimated from the Bone Mineral Density (BMD) using Dual-energy X-ray Absorptiometry (DXA), the identification of the subjects at high risk of fracture still remains an issue. From this perspective, the purpose of this work is to investigate the role that DXA-based two-dimensional patient-specific finite element (FE) models of the proximal femur, in combination with T-score, could play in enhancing the risk of fracture estimation. With this aim, 2D FE models were built from DXA images of the 28 post-menopausal female subjects involved. A sideways fall condition was reproduced and a Risk of Fracture (trueRF^) was computed on the basis of principal strains criteria. The identified trueRF^ was then compared to that derived from the CT-based models developed in a previous study. The 2D and 3D trueRF^ turned out to be significantly correlated (Spearman's ρ = 0.66, p < 0.001), highlighting the same patients as those at higher risk. Moreover, the 2D trueRF^ resulted significantly correlated with the T-score (Spearman's ρ = −0.69, p < 0.001), and managed to better differentiate osteopenic patients, drawing the attention to some of them. The Hip Structural Analysis (HSA) variables explaining the majority of the variance of the 2D and 3D fracture risk were the same as well, i.e., neck-shaft angle and narrow neck buckling ratio. In conclusion, DXA-based FE models, developable from currently available clinical data, appear promising in supporting and integrating the present diagnostic procedure.