Research Highlights

Quantitative X-ray phase contrast computed tomography with grating interferometry : Biomedical applications of quantitative X-ray grating-based phase contrast computed tomography

Research Highlights |


Birnbacher, L., Braig, E. M., Pfeiffer, D., Pfeiffer, F., & Herzen, J. (2021). Quantitative X-ray phase contrast computed tomography with grating interferometry : Biomedical applications of quantitative X-ray grating-based phase contrast computed tomography. European journal of nuclear medicine and molecular imaging, 48(13), 4171–4188. https://doi.org/10.1007/s00259-021-05259-6

Purpose: While many imaging applications including phase contrast methods have been focusing mainly on revealing subtle relative signal differences, quantitative imaging is gaining more and more interest. In general, relative contrast signals like the relaxation times in magnetic resonance imaging (MRI) can be sufficient for the desired information. However, absolute signals of physical nature like e.g. the electron density—this is what we describe in this work with quantitativeness—are in theory independent of the method of contrast formation. This does not only increase the comparability and reproducibility of the results but absolute quantitative signals can also be used for standardized diagnostics or for data science on a larger scale 

Figure: A papillary renal cell carcinoma (RCC) sample imaged with a GBPC-CT setup is shown by way of example. The corresponding histological slice (a) is presented next to the tomographic slice of the attenuation contrast (b) and phase contrast (c) signal. A clear discrimination between healthy (*) and tumorous (**) renal cortex is visualized in the phase contrast signal, which is not the case for the attenuation signal. The arrowhead points to a pseudo-capsule around the tumor which was also not revealed in the attenuation signal. In subfigure (d), the HUp values of different RCC types (ccRCC: clear cell, pRCC: papillary, chrRCC chromophobe RCC) as well as cortex and medulla are shown. Subfigure (e) depicts quantitatively different RCC features. Figure adapted from Braunagel et al. [63]. This figure is licensed under the Creative Commons Attribution (CC BY)