Abstract
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 using XVR as a tool to help early diagnosis of bone diseases, such as osteoporosis.
Highlights
Besides the overall mass density, strength of trabecular bone depends significantly on its microstructure
In analogy to conventional absorption-based imaging, which is governed by the Lambert-Beer-Law, the visibility signal recorded during an X-ray vector radiography (XVR) scan, V, can be described with an exponential function
The degree of anisotropy (DAXVR) of the XVR signal can be defined as the amplitude of the oscillating part (a1) to the constant part (a0), which by this definition assumes values between 0 and 1: DAXVR
Summary
Besides the overall mass density, strength of trabecular bone depends significantly on its microstructure. A model is presented which proves that XVR imaging yields information directly correlated with the trabecular microstructure. This opens up possibilities of using XVR as a tool to help early diagnosis of bone diseases, such as osteoporosis. The recorded small angle scattering (SAS) signal often varies under rotation of the sample and we have previously called this direction-dependent dark-field imaging X-ray vector radiography (XVR)[12]. While it is possible to obtain information about this trabecular structure ex-vivo using mCT, this method is not suitable for diagnostics due to the very high dose required to directly resolve the individual trabeculae in great detail. By using an elaborate numerical analysis, we correlate the XVR signal to the present trabecular microstructure within the sample
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