X-ray Phase Contrast 3D virtual histology: evaluation of lung alterations after micro-beam irradiation

3D imaging of SARS-CoV-2 infected hamster lungs by X-ray phase contrast tomography enables drug testing

X-ray Phase Contrast Tomography (XPCT) based on wavefield propagation has been established as a high resolution three-dimensional (3D) imaging modality, suitable to reconstruct the intricate structure of soft tissues, and the corresponding pathological alterations. However, for biomedical research, more is needed than 3D visualisation and rendering of the cytoarchitecture in a few selected cases. First, the throughput needs to be increased to cover a statistically relevant number of samples. Second, the cytoarchitecture has to be quantified in terms of morphometric parameters, independent of visual impression. Third, dimensionality reduction and classification are required for identification of effects and interpretation of results. To address these challenges, we here design and implement a novel integrated and high throughput XPCT imaging and analysis workflow for 3D histology, pathohistology and drug testing. Our approach uses semi-automated data acquisition, reconstruction and statistical quantification. We demonstrate its capability for the example of lung pathohistology in Covid-19. Using a small animal model, different Covid-19 drug candidates are administered after infection and tested in view of restoration of the physiological cytoarchitecture, specifically the alveolar morphology. To this end, we then use morphometric parameter determination followed by a dimensionality reduction and classification based on optimal transport. This approach allows efficient discrimination between physiological and pathological lung structure, thereby providing quantitative insights into the pathological progression and partial recovery due to drug treatment. Finally, we stress that the XPCT image chain implemented here only used synchrotron radiation for validation, while the data used for analysis was recorded with laboratory μ CT radiation, more easily accessible for pre-clinical research.

Multi-Modal X-ray Imaging and Analysis for Characterization of Urinary Stones

Backgound: The composition of stones formed in the urinary tract plays an important role in their management over time. The most common imaging method for the non-invasive evaluation of urinary stones is radiography and computed tomography (CT). However, CT is not very sensitive, and cannot differentiate between all critical stone types. In this study, we propose the application, and evaluate the potential, of a multi-modal (or multi-contrast) X-ray imaging technique called speckle-based imaging (SBI) to differentiate between various types of urinary stones. Methods: Three different stone samples were extracted from animal and human urinary tracts and examined in a laboratory-based speckle tracking setup. The results were discussed based on an X-ray diffraction analysis and a comparison with X-ray microtomography and grating-based interferometry. Results: The stones were classified through compositional analysis by X-ray diffraction. The multi-contrast images obtained using the SBI method provided detailed information about the composition of various urinary stone types, and could differentiate between them. X-ray SBI could provide highly sensitive and high-resolution characterizations of different urinary stones in the radiography mode, comparable to those by grating interferometry. Conclusions: This investigation demonstrated the capability of the SBI technique for the non-invasive classification of urinary stones through radiography in a simple and cost-effective laboratory setting. This opens the possibility for further studies concerning full-field in vivo SBI for the clinical imaging of urinary stones.