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We investigated the effects of low-dose multi detector computed tomography (MDCT) in combination with statistical iterative reconstruction algorithms on trabecular bone microstructure parameters. Twelve donated vertebrae were scanned with the routine radiation exposure used in our department (standard-dose) and a low-dose protocol. Reconstructions were performed with filtered backprojection (FBP) and maximum-likelihood based statistical iterative reconstruction (SIR). Trabecular bone microstructure parameters were assessed and statistically compared for each reconstruction. Moreover, fracture loads of the vertebrae were biomechanically determined and correlated to the assessed microstructure parameters. Trabecular bone microstructure parameters based on low-dose MDCT and SIR significantly correlated with vertebral bone strength. There was no significant difference between microstructure parameters calculated on low-dose SIR and standard-dose FBP images. However, the results revealed a strong dependency on the regularization strength applied during SIR. It was observed that stronger regularization might corrupt the microstructure analysis, because the trabecular structure is a very small detail that might get lost during the regularization process. As a consequence, the introduction of SIR for trabecular bone microstructure analysis requires a specific optimization of the regularization parameters. Moreover, in comparison to other approaches, superior noise-resolution trade-offs can be found with the proposed methods. [ABSTRACT FROM AUTHOR]

Besides the overall mass density, strength of trabecular bone depends significantly on its microstructure. However, due to dose constraints in medical CT imaging, it is impossible to gain sufficient information about very fine bone structures in vivo on the micrometer scale. Here we show that a recently developed method of X-ray vector radiography (XVR), an imaging method which uses X-ray scattering information to form an image, allows predictions on the bone microstructure without the explicit need to spatially resolve even individual trabeculae in the bone. We investigated thick human femoral bone samples and compared state-of-the-art μCT data with XVR imaging. A model is presented which proves that XVR imaging yields information directly correlated with the trabecular microstructure. This opens up possibilities of usingXVR as a tool to help early diagnosis of bone diseases, such as osteoporosis. [ABSTRACT FROM AUTHOR]

X-ray dark-field scatter imaging allows to gain information on the average local direction and anisotropy of micro-structural features in a sample well below the actual detector resolution. For thin samples the morphological interpretation of the signal is straight forward, provided that only one average orientation of sub-pixel features is present in the specimen. For thick samples, however, where the x-ray beam may pass structures of many different orientations and dimensions, this simple assumption in general does not hold and a quantitative description of the resulting directional dark-field signal is required to draw deductions on the morphology. Here we present a description of the signal formation for thick samples with many overlying structures and show its validity in experiment. In contrast to existing experimental work this description follows from theoretical predictions of a numerical study using a Fourier optics approach. One can easily extend this description and perform a quantitative structural analysis of clinical or materials science samples with directional dark-field imaging or even direction-dependent dark-field CT. [ABSTRACT FROM AUTHOR]