Quantifying trabecular bone material anisotropy and orientation using low resolution clinical CT images: A feasibility study.
Accounting for spatial variation of trabecular material anisotropy and orientation can improve the accuracy of quantitative computed tomography based finite element (FE) modeling of bone. The objective of this study was to investigate the feasibility of quantifying trabecular material anisotropy and orientation using clinical computed tomography (CT) Forty four cubic volumes of interest were obtained from micro CT images of the human radius. Micro FE modeling was performed on the samples to obtain orthotropic stiffness entries as well as trabecular orientation. Simulated computed tomography images (0.32, 0.37, and 0.5mm isotropic voxel sizes) were created by resampling micro CT images with added image noise. The gray level structure tensor was used to derive fabric eigenvalues and eigenvectors in simulated CT images. For 'best case' comparison purposes, Mean Intercept Length was used to define fabric from micro CT images. Regression was used in combination with eigenvalues, imaged density and FE to inversely derive the constants used in Cowin and Zysset Curnier fabric elasticity equations, and for comparing image derived fabric elasticity stiffness entries to those obtained using micro FE. Image derived eigenvectors (which indicated trabecular orientation) were then compared to orientation derived using micro FE. When using clinically available voxel sizes, gray level structure tensor derived fabric combined with Cowin's equations was able to explain 94 97% of the variance in orthotropic stiffness entries while Zysset Curnier equations explained 82 88% of the variance in stiffness. Image derived orientation deviated by 4.4 10.8deg from micro FE derived orientation. Our results indicate potential to account for spatial variation of trabecular material anisotropy and orientation in subject specific finite element modeling of bone using clinically available CT.
Medical engineering physics