Biofidelic finite element models for accurately classifying hip fracture in a retrospective clinical study of elderly women from the AGES Reykjavik cohort.

Clinical retrospective studies have only reported limited improvements in hip fracture classification accuracy using finite element (FE) models compared to conventional areal bone mineral density (aBMD) measurements. A possible explanation is that state-of-the-art quasi-static models do not estimate patient-specific loads. A novel FE modeling technique was developed to improve the biofidelity of simulated impact loading from sideways falling. This included surrogate models of the pelvis, lower extremities, and soft tissue that were morphed based on subject anthropometrics. Hip fracture prediction models based on aBMD and FE measurements were compared in a retrospective study of 254 elderly female subjects from the AGES-Reykjavik study. Subject fragility ratio (FR) was defined as the ratio between the ultimate forces of paired biofidelic models, one with linear elastic and the other with non-linear stress-strain relationships in the proximal femur. The expected end-point value (EEV) was defined as the FR weighted by the probability of one sideways fall over five years, based on self-reported fall frequency at baseline. The change in maximum volumetric strain (ΔMVS) on the surface of the femoral neck was calculated between time of ultimate femur force and 90% post-ultimate force in order to assess the extent of tensile tissue damage present in non-linear models. After age-adjusted logistic regression, the area under the receiver-operator curve (AUC) was highest for ΔMVS (0.72), followed by FR (0.71), aBMD (0.70), and EEV (0.67), however the differences between FEA and aBMD based prediction models were not deemed statistically significant. When subjects with no history of falling were excluded from the analysis, thus artificially assuming that falls were known a priori with no uncertainty, a statistically significant difference in AUC was detected between ΔMVS (0.85), and aBMD (0.74). Multivariable linear regression suggested that the variance in maximum elastic femur force was best explained by femoral head radius, pelvis width, and soft tissue thickness (R2 = 0.79; RMSE = 0.46 kN; p < 0.005). Weighting the hip fracture prediction models based on self-reported fall frequency did not improve the models' sensitivity, however excluding non-fallers lead to significant differences between aBMD and FE based models. These findings suggest that an accurate assessment of fall probability is necessary for accurately identifying individuals predisposed to hip fracture.

Larger vertebral endplate concavities cause higher failure load and work at failure under high-rate impact loading of rabbit spinal explants.

Vertebral fractures are among the most common of all osteoporosis related fracture types and its risk assessment is largely based on bone quality measures. Morphometric parameters are not yet considered, although endplate thickness and concavity shape were found to be important in fracture prediction in low-rate tests. We hypothesized that, under high-rate impact loading, the shape and size of the central endplate concavity are of key importance for fracture prediction. Therefore, we tested rabbit spinal segment explants in vitro under high-rate impact loading. With a combination of microCT to describe endplate morphometry, high-speed video imaging, and impact force measurement, endplate morphometry was correlated to the mechanical response. We found that endplate concavity shape and volume were important in describing the mechanical response: larger concavities caused higher failure load. We suggest a model for the fracture mechanism under high-rate impact loading, considering the morphometry of the endplates: wider and more voluminous concavities are protective whereas steeper slopes of the concavity edges and increasing bone volume fraction of the central endplate moiety are disadvantageous. Therefore, the shape and size of endplate morphometry are important in vertebral fracture prediction and should be considered included in vertebral fracture risk assessment.

The influence of the modulus-density relationship and the material mapping method on the simulated mechanical response of the proximal femur in side-ways fall loading configuration.

Contributing to slow advance of finite element (FE) simulations for hip fracture risk prediction, into clinical practice, could be a lack of consensus in the biomechanics community on how to map properties to the models. Thus, the aim of the present study was first, to systematically quantify the influence of the modulus-density relationship (E-ρ) and the material mapping method (MMM) on the predicted mechanical response of the proximal femur in a side-ways fall (SWF) loading configuration and second, to perform a model-to-model comparison of the predicted mechanical response within the femoral neck for all the specimens tested in the present study, using three different modelling techniques that have yielded good validation outcome in terms of surface strain prediction and whole bone response according to the literature. We found the outcome to be highly dependent on both the E-ρ relationship and the MMM. In addition, we found that the three modelling techniques that have resulted in good validation outcome in the literature yielded different principal strain prediction both on the surface as well as internally in the femoral neck region of the specimens modelled in the present study. We conclude that there exists a need to carry out a more comprehensive validation study for the SWF loading mode to identify which combination of MMMs and E-ρ relationship leads to the best match for whole bone and local mechanical response. The MMMs tested in the present study have been made publicly available at https://simtk.org/home/mitk-gem.

Modeling susceptibility difference artifacts produced by metallic implants in magnetic resonance imaging with point-based thin-plate spline image registration.

Magnetic resonance imaging (MRI) suffers from geometric distortions arising from various sources. One such source are the non-linearities associated with the presence of metallic implants, which can profoundly distort the obtained images. These non-linearities result in pixel shifts and intensity changes in the vicinity of the implant, often precluding any meaningful assessment of the entire image. This paper presents a method for correcting these distortions based on non-rigid image registration techniques. Two images from a modelled three-dimensional (3D) grid phantom were subjected to point-based thin-plate spline registration. The reference image (without distortions) was obtained from a grid model including a spherical implant, and the corresponding test image containing the distortions was obtained using previously reported technique for spatial modelling of magnetic susceptibility artifacts. After identifying the nonrecoverable area in the distorted image, the calculated spline model was able to quantitatively account for the distortions, thus facilitating their compensation. Upon the completion of the compensation procedure, the non-recoverable area was removed from the reference image and the latter was compared to the compensated image. Quantitative assessment of the goodness of the proposed compensation technique is presented.