Cortical Bone Thickness Estimation in CT Images: A Model-Based Approach Without Profile Fitting

Museyko, Oleg; Gerner, Bastian; Engelke, Klaus

doi:10.1007/978-3-319-41827-8_6

Cited by 2 publications

(1 citation statement)

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“…Third, the cortex surrounding the proximal femur cannot be properly represented by 3 mm voxels. This limitation could be circumvented by using methods that were proposed to extract cortical thickness from QCT images [64,65]. For accurate modelling of the cortical shell, smooth wedge elements may be used [13].…”

Section: Discussionmentioning

confidence: 99%

Mapping anisotropy improves QCT-based finite element estimation of hip strength in pooled stance and side-fall load configurations

Panyasantisuk

Dall’Ara

Pretterklieber

et al. 2018

Medical Engineering & Physics

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Hip fractures are one of the most severe consequences of osteoporosis. Compared to the clinical standard of DXA-based aBMD at the femoral neck, QCT-based FEA delivers a better surrogate of femoral strength and gains acceptance for the calculation of hip fracture risk when a CT reconstruction is available. Isotropic, homogenised voxel-based, finite element (hvFE) models are widely used to estimate femoral strength in cross-sectional and longitudinal clinical studies. However, fabric anisotropy is a classical feature of the architecture of the proximal femur and the second determinant of the homogenised mechanical properties of trabecular bone. Due to the limited resolution, fabric anisotropy cannot be derived from clinical CT reconstructions. Alternatively, fabric anisotropy can be extracted from HR-pQCT images of cadaveric femora. In this study, fabric anisotropy from HR-pQCT images was mapped onto QCT-based hvFE models of 71 human proximal femora for which both HR-pQCT and QCT images were available. Stiffness and ultimate load computed from anisotropic hvFE models were compared with previous biomechanical tests in both stance and side-fall configurations. The influence of using the femur-specific versus a mean fabric distribution on the hvFE predictions was assessed. Femur-specific and mean fabric enhance the prediction of experimental ultimate force for the pooled, i.e. stance and side-fall, (isotropic: r=0.81, femur-specific fabric: r=0.88, mean fabric: r=0.86,p<0.001) but not for the individual configurations. Fabric anisotropy significantly improves bone strength prediction for the pooled configurations, and mapped fabric provides a comparable prediction to true fabric. The mapping of fabric anisotropy is therefore expected to help generate more accurate QCT-based hvFE models of the proximal femur for personalised or multiple load configurations.

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Section: Discussionmentioning

confidence: 99%