X-ray phase-contrast tomography (XPCT) offers a highly sensitive 3D imaging approach to investigate different disease-relevant networks from the single cell to the whole organ. We present here a concomitant study of the evolution of tissue damage and inflammation in potential target organs of the disease in the murine model of multiple sclerosis. XPCT identifies and monitors structural and cellular alterations throughout the central nervous system, but also in the gut and eye, of mice induced to develop multiple sclerosis-like disease and sacrificed at pre-symptomatic and symptomatic time points. This approach rests on a multiscale analysis to detect early appearance of imaging indicators potentially acting as biomarkers predictive of the disease. The longitudinal data permit an original evaluation of the sequential evolution of multi-organ damage in the mouse model, shedding light on the role of the gut-brain axis in the disease initiation and progression, of relevance for the human case.
The human olfactory bulb (OB), an important part of the brain responsible for the sense of smell, is a complex structure composed of multiple layers and cell types. Studying the OB morphological structure is essential for understanding the decline in olfactory function related to aging, neurodegenerative disorders, and other pathologies. Traditional microscopy methods in which slices are stained with solutions to contrast individual elements of the morphological structure are destructive. Non-destructive high-resolution technique is the X-ray phase-contrast tomography. However, manual segmentation of the reconstructed images are time-consuming due to large amount of data and prone to errors. U-Net-based model to optimize the segmentation of OB morphological structures, focusing specifically on glomeruli, in tomographic images of the human OB is proposed. The strategy to address overfitting and enhance the model's accuracy is described. This method addresses the challenges posed by complex limited data containing abundant details, similar grayscale levels between soft tissues, and blurry image details. Additionally, it successfully overcomes the limitations of a small dataset containing images with extremely dense point clouds, preventing the models from overfitting.
To date there have been only indirect indications of the presence of bound sodium accumulation in muscle and skin tissues. Despite their osmotic inactivity, such sodium deposits can effect on mechanical properties of the heart muscle impairing its elasticity and leading to serious heart dysfunctions. In this work an accurate study of the chemical composition of the heart muscle tissue at the cellular level was carried out using the methods of X-ray absorption and fluorescence microscopy. The experiments were carried out on a TwinMic X-ray scanning microscope [3] at ELETTRA synchrotron (Italy) with a resolution of about 1 μm. Comparison of the obtained maps of intra- and extracellular sodium distribution in heart tissues of different laboratory animals has resulted in the first experimental confirmation of the hypotheses about the existence of deposited sodium states in the intercellular space. The paper demonstrates an example of the state-of-the-art medical applications of high spectral brilliance X-ray sources.
Despite significant progress in computer vision, pattern recognition, and image analysis, artifacts in imaging still hampers the progress in many scientific fields relying on the results of image analysis. We here present an advanced image-based artifacts suppression algorithm for high-resolution tomography. The algorithm is based on guided filtering of a reconstructed image mapped from the Cartesian to the polar coordinates space. This postprocessing method efficiently reduces both ring- and radial streak artifacts in a reconstructed image. Radial streak artifacts can appear in tomography with an off-center rotation of a large object over 360 degrees used to increase the reconstruction field of view. We successfully applied the developed algorithm for improving x-ray phase-contrast images of human post-mortem pineal gland and olfactory bulbs.
Computer vision for biomedical imaging applications is fast developing and at once demanding field of computer science. In particular, computer vision technique provides excellent results for detection and segmentation problems in tomographic imaging. X-ray phase contrast Tomography (XPCT) is a noninvasive 3D imaging technique with high sensitivity for soft tissues. Despite a considerable progress in XPCT data acquisition and data processing methods, the problem in degradation of image quality due to artifacts remains a widespread and often critical issue for computer vision applications. One of the main problems originates from a sample alteration during a long tomographic scan. We proposed and tested Simultaneous Iterative Reconstruction algorithm with Total Variation regularization to reduce the number of projections in high resolution XPCT scans of ex-vivo mouse spinal cord. We have shown that the proposed algorithm allows tenfold reducing the number of projections and, therefore, the exposure time, with conservation of the important morphological information in 3D image with quality acceptable for computer graphics and computer vision applications. Our research paves a way for more effective implementation of advanced computer technologies in phase contrast tomographic research.
Theranostics is an innovative research field that aims to develop high target specificity cancer treatments by administering small metal-based nanoparticles (NPs). This new generation of compounds exhibits diagnostic and therapeutic properties due to the high atomic number of their metal component. In the framework of a combined research program on low dose X-ray imaging and theranostic NPs, X-ray Phase Contrast Tomography (XPCT) was performed at ESRF using a 3 μm pixel optical system on two samples: a mouse brain bearing melanoma metastases injected with gadolinium NPs and, a mouse liver injected with gold NPs. XPCT is a non-destructive technique suitable to achieve the 3D reconstruction of a specimen and, widely used at micro-scale to detect abnormalities of the vessels, which are associated to the tumor growth or to the development of neurodegenerative diseases. Moreover, XPCT represents a promising and complementary tool to study the biodistribution of theranostic NPs in biological materials, thanks to the strong contrast with respect to soft tissues that metal-based NPs provide in radiological images. This work is relied on an original imaging approach based on the evaluation of the contrast differences between the images acquired below and above K-edge energies, as a proof of the certain localization of NPs. We will present different methods aiming to enhance the localization of NPs and a 3D map of their distribution in large volume of tissues.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.