Purpose: To evaluate the performance of an experimental X-ray dark-field radiography system for chest imaging in humans and to compare with conventional diagnostic imaging. Materials and Methods: The study was institutional review board (IRB) approved. A single human cadaver (52 years, female, height: 173 cm, weight: 84 kg, chest circumference: 97 cm) was imaged within 24 hours post mortem on the experimental x-ray dark-field system. In addition, the cadaver was imaged on a clinical CT system to obtain a reference scan. The grating-based dark-field radiography setup was equipped with a set of three gratings to enable grating-based dark-field contrast x-ray imaging. The prototype operates at an acceleration voltage of up to 70 kVp and with a field-of-view large enough for clinical chest x-ray (>35 x 35 cm2). Results: It was feasible to extract x-ray dark-field signal of the whole human thorax, clearly demonstrating that human x-ray dark-field chest radiography is feasible. Lung tissue produced strong scattering, reflected in a pronounced x-ray dark-field signal. The ribcage and the backbone are less prominent than the lung but are also distinguishable. Finally, the soft tissue is not present in the dark-field radiography. The regions of the lungs affected by edema, as verified by CT, showed less dark-field signal compared to healthy lung tissue. Conclusion: Our results reveal the current status of translating dark-field imaging from a micro (small animal) scale to a macro (patient) scale. The performance of the experimental x-ray dark-field radiography setup offers, for the first time, obtaining multi-contrast chest x-ray images (attenuation and dark-field signal) from a human cadaver.
Grating-based X-ray phase-contrast (gbPC) is known to provide significant benefits for biomedical imaging. To investigate these benefits, a high-sensitivity gbPC micro-CT setup for small (≈ 5 cm) biological samples has been constructed. Unfortunately, high differential-phase sensitivity leads to an increased magnitude of data processing artifacts, limiting the quality of tomographic reconstructions. Most importantly, processing of phase-stepping data with incorrect stepping positions can introduce artifacts resembling Moiré fringes to the projections. Additionally, the focal spot size of the X-ray source limits resolution of tomograms. Here we present a set of algorithms to minimize artifacts, increase resolution and improve visual impression of projections and tomograms from the examined setup. We assessed two algorithms for artifact reduction: Firstly, a correction algorithm exploiting correlations of the artifacts and differential-phase data was developed and tested. Artifacts were reliably removed without compromising image data. Secondly, we implemented a new algorithm for flatfield selection, which was shown to exclude flat-fields with strong artifacts. Both procedures successfully improved image quality of projections and tomograms. Deconvolution of all projections of a CT scan can minimize blurring introduced by the finite size of the X-ray source focal spot. Application of the Richardson-Lucy deconvolution algorithm to gbPC-CT projections resulted in an improved resolution of phase-contrast tomograms. Additionally, we found that nearest-neighbor interpolation of projections can improve the visual impression of very small features in phase-contrast tomograms. In conclusion, we achieved an increase in image resolution and quality for the investigated setup, which may lead to an improved detection of very small sample features, thereby maximizing the setup's utility.
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