Correction for Mechanical Inaccuracies in a Scanning Talbot-Lau Interferometer.

Grating-based X-ray phase-contrast and in particular dark-field radiography are promising new imaging modalities for medical applications. Currently, the potential advantage of dark-field imaging in early-stage diagnosis of pulmonary diseases in humans is being investigated. These studies make use of a comparatively large scanning interferometer at short acquisition times, which comes at the expense of a significantly reduced mechanical stability as compared to tabletop laboratory setups. Vibrations create random fluctuations of the grating alignment, causing artifacts in the resulting images. Here, we describe a novel maximum likelihood method for estimating this motion, thereby preventing these artifacts. It is tailored to scanning setups and does not require any sample-free areas. Unlike any previously described method, it accounts for motion in between as well as during exposures.

Nanoscopic X-ray tomography for correlative microscopy of a small meiofaunal sea-cucumber.

In the field of correlative microscopy, light and electron microscopy form a powerful combination for morphological analyses in zoology. Due to sample thickness limitations, these imaging techniques often require sectioning to investigate small animals and thereby suffer from various artefacts. A recently introduced nanoscopic X-ray computed tomography (NanoCT) setup has been used to image several biological objects, none that were, however, embedded into resin, which is prerequisite for a multitude of correlative applications. In this study, we assess the value of this NanoCT for correlative microscopy. For this purpose, we imaged a resin-embedded, meiofaunal sea cucumber with an approximate length of 1 mm, where microCT would yield only little information about the internal anatomy. The resulting NanoCT data exhibits isotropic 3D resolution, offers deeper insights into the 3D microstructure, and thereby allows for a complete morphological characterization. For comparative purposes, the specimen was sectioned subsequently to evaluate the NanoCT data versus serial sectioning light microscopy (ss-LM). To correct for mechanical instabilities and drift artefacts, we applied an alternative alignment procedure for CT reconstruction. We thereby achieve a level of detail on the subcellular scale comparable to ss-LM images in the sectioning plane.

Model-Based Iterative Reconstruction for Propagation-Based Phase-Contrast X-Ray CT including Models for the Source and the Detector.

Propagation-based phase-contrast X-ray computed tomography is a valuable tool for high-resolution visualization of biological samples, giving distinct improvements in terms of contrast and dose requirements compared to conventional attenuation-based computed tomography. Due to its ease of implementation and advances in laboratory X-ray sources, this imaging technique is increasingly being transferred from synchrotron facilities to laboratory environments. This however poses additional challenges, such as the limited spatial coherence and flux of laboratory sources, resulting in worse resolution and higher noise levels. Here we extend a previously developed iterative reconstruction algorithm for this imaging technique to include models for the reduced spatial coherence and the signal spreading of efficient scintillator-based detectors directly into the physical forward model. Furthermore, we employ a noise model which accounts for the full covariance statistics of the image formation process. In addition, we extend the model describing the interference effects such that it now matches the formalism of the widely-used single-material phase-retrieval algorithm, which is based on the sample-homogeneity assumption. We perform a simulation study as well as an experimental study at a laboratory inverse Compton source and compare our approach to the conventional analytical approaches. We find that the modeling of the source and the detector inside the physical forward model can tremendously improve the resolution at matched noise levels and that the modeling of the covariance statistics reduces overshoots (i.e. incorrect increase / decrease in sample properties) at the sample edges significantly.

Multimodal Precision Imaging of Pulmonary Nanoparticle Delivery in Mice: Dynamics of Application, Spatial Distribution, and Dosimetry.

Targeted delivery of nanomedicine/nanoparticles (NM/NPs) to the site of disease (e.g., the tumor or lung injury) is of vital importance for improved therapeutic efficacy. Multimodal imaging platforms provide powerful tools for monitoring delivery and tissue distribution of drugs and NM/NPs. This study introduces a preclinical imaging platform combining X-ray (two modes) and fluorescence imaging (three modes) techniques for time-resolved in vivo and spatially resolved ex vivo visualization of mouse lungs during pulmonary NP delivery. Liquid mixtures of iodine (contrast agent for X-ray) and/or (nano)particles (X-ray absorbing and/or fluorescent) are delivered to different regions of the lung via intratracheal instillation, nasal aspiration, and ventilator-assisted aerosol inhalation. It is demonstrated that in vivo propagation-based phase-contrast X-ray imaging elucidates the dynamic process of pulmonary NP delivery, while ex vivo fluorescence imaging (e.g., tissue-cleared light sheet fluorescence microscopy) reveals the quantitative 3D drug/particle distribution throughout the entire lung with cellular resolution. The novel and complementary information from this imaging platform unveils the dynamics and mechanisms of pulmonary NM/NP delivery and deposition for each of the delivery routes, which provides guidance on optimizing pulmonary delivery techniques and novel-designed NM for targeting and efficacy.

Blind deconvolution in model-based iterative reconstruction for CT using a normalized sparsity measure.

Model-based iterative reconstruction techniques for CT that include a description of the noise statistics and a physical forward model of the image formation process have proven to increase image quality for many applications. Specifically, including models of the system blur into the physical forward model and thus implicitly performing a deconvolution of the projections during tomographic reconstruction, could demonstrate distinct improvements, especially in terms of resolution. However, the results strongly rely on an exact characterization of all components contributing to the system blur. Such characterizations can be laborious and even a slight mismatch can diminish image quality significantly. Therefore, we introduce a novel objective function, which enables us to jointly estimate system blur parameters during tomographic reconstruction. Conventional objective functions are biased in terms of blur and can yield lowest cost to blurred reconstructions with low noise levels. A key feature of our objective function is a new normalized sparsity measure for CT based on total-variation regularization, constructed to be less biased in terms of blur. We outline a solving strategy for jointly recovering low-dimensional blur parameters during tomographic reconstruction. We perform an extensive simulation study, evaluating the performance of the regularization and the dependency of the different parts of the objective function on the blur parameters. Scenarios with different regularization strengths and system blurs are investigated, demonstrating that we can recover the blur parameter used for the simulations. The proposed strategy is validated and the dependency of the objective function with the number of iterations is analyzed. Finally, our approach is experimentally validated on test-bench data of a human wrist phantom, where the estimated blur parameter coincides well with visual inspection. Our findings are not restricted to attenuation-based CT and may facilitate the recovery of more complex imaging model parameters.

Full-field structured-illumination super-resolution X-ray transmission microscopy.

Modern transmission X-ray microscopy techniques provide very high resolution at low and medium X-ray energies, but suffer from a limited field-of-view. If sub-micrometre resolution is desired, their field-of-view is typically limited to less than one millimetre. Although the field-of-view increases through combining multiple images from adjacent regions of the specimen, so does the required data acquisition time. Here, we present a method for fast full-field super-resolution transmission microscopy by structured illumination of the specimen. This technique is well-suited even for hard X-ray energies above 30 keV, where efficient optics are hard to obtain. Accordingly, investigation of optically thick specimen becomes possible with our method combining a wide field-of-view spanning multiple millimetres, or even centimetres, with sub-micron resolution and hard X-ray energies.

Visualizing treatment delivery and deposition in mouse lungs using in vivo x-ray imaging.

The complexity of lung diseases makes pre-clinical in vivo respiratory research in mouse lungs of great importance for a better understanding of physiology and therapeutic effects. Synchrotron-based imaging has been successfully applied to lung research studies, however longitudinal studies can be difficult to perform due to limited facility access. Laboratory-based x-ray sources, such as inverse Compton x-ray sources, remove this access limitation and opens up new possibilities for pre-clinical small-animal lung research at high spatial and temporal resolution. The in vivo visualization of drug deposition in mouse lungs is of interest, particularly in longitudinal research, because the therapeutic outcome is not only dependent on the delivered dose of the drug, but also on the spatial distribution of the drug. An additional advantage of this approach, when compared to other imaging techniques, is that anatomic and dynamic information is collected simultaneously. Here we report the use of dynamic x-ray phase-contrast imaging to observe pulmonary drug delivery via liquid instillation, and by inhalation of micro-droplets. Different liquid volumes (4 µl, 20 µl, 50 µl) were tested and a range of localized and global distributions were observed with a temporal resolution of up to 1.5 fps. The in vivo imaging results were confirmed by ex vivo x-ray and fluorescence imaging. This ability to visualize pulmonary substance deposition in live small animals has provided a better understanding of the two key methods of delivery; instillation and nebulization.

X-ray imaging of a water bear offers a new look at tardigrade internal anatomy.

BACKGROUND: Tardigrades (water bears) are microscopic invertebrates of which the anatomy has been well studied using traditional techniques, but a comprehensive three-dimensional reconstruction has never been performed. In order to close this gap, we employed X-ray computed tomography (CT), a technique that is becoming increasingly popular in zoology for producing high-resolution, three-dimensional (3D) scans of whole specimens. While CT has long been used to scan larger samples, its use in some microscopic animals can be problematic, as they are often too small for conventional CT yet too large for high-resolution, optics-based soft X-ray microscopy. This size gap continues to be narrowed with advancements in technology, with high-resolution imaging now being possible using both large synchrotron devices and, more recently, laboratory-based instruments. RESULTS: Here we use a recently developed prototype lab-based nano-computed tomography device to image a 152 µm-long tardigrade at high resolution (200-270 nm pixel size). The resulting dataset allowed us to visualize the anatomy of the tardigrade in 3D and analyze the spatial relationships of the internal structures. Segmentation of the major structures of the body enabled the direct measurement of their respective volumes. Furthermore, we segmented every storage cell individually and quantified their volume distribution. We compare our measurements to those from published studies in which other techniques were used. CONCLUSIONS: The data presented herein demonstrate the utility of CT imaging as a powerful supplementary tool for studies of tardigrade anatomy, especially for quantitative volume measurements. This nanoCT study represents the smallest complete animal ever imaged using CT, and offers new 3D insights into the spatial relationships of the internal organs of water bears.

Propagation-based phase-contrast tomography of a guinea pig inner ear with cochlear implant using a model-based iterative reconstruction algorithm.

Propagation-based phase-contrast computed tomography has become a valuable tool for visualization of three-dimensional biological samples, due to its high contrast between materials with similar attenuation properties. However, one of the most-widely used phase-retrieval algorithms imposes a homogeneity assumption onto the sample, which leads to artifacts for numerous applications where this assumption is violated. Prominent examples are biological samples with highly-absorbing implants. Using synchrotron radiation, we demonstrate by the example of a guinea pig inner ear with a cochlear implant electrode, how a recently developed model-based iterative algorithm for propagation-based phase-contrast computed tomography yields distinct benefits for such a task. We find that the model-based approach improves the overall image quality, removes the detrimental influence of the implant and accurately visualizes the cochlea.

In vivo Dynamic Phase-Contrast X-ray Imaging using a Compact Light Source.

We describe the first dynamic and the first in vivo X-ray imaging studies successfully performed at a laser-undulator-based compact synchrotron light source. The X-ray properties of this source enable time-sequence propagation-based X-ray phase-contrast imaging. We focus here on non-invasive imaging for respiratory treatment development and physiological understanding. In small animals, we capture the regional delivery of respiratory treatment, and two measures of respiratory health that can reveal the effectiveness of a treatment; lung motion and mucociliary clearance. The results demonstrate the ability of this set-up to perform laboratory-based dynamic imaging, specifically in small animal models, and with the possibility of longitudinal studies.

Nonlinear statistical iterative reconstruction for propagation-based phase-contrast tomography.

Propagation-based phase-contrast tomography has become a valuable tool for visualization of three-dimensional biological samples, due to its high sensitivity and its potential in providing increased contrast between materials with similar absorption properties. We present a statistical iterative reconstruction algorithm for this imaging technique in the near-field regime. Under the assumption of a single material, the propagation of the x-ray wavefield-relying on the transport-of-intensity equation-is made an integral part of the tomographic reconstruction problem. With a statistical approach acting directly on the measured intensities, we find an unconstrained nonlinear optimization formulation whose solution yields the three-dimensional distribution of the sample. This formulation not only omits the intermediate step of retrieving the projected thicknesses but also takes the statistical properties of the measurements into account and incorporates prior knowledge about the sample in the form of regularization techniques. We show some advantages of this integrated approach compared to two-step approaches on data obtained using a commercially available x-ray micro-tomography system. In particular, we address one of the most considerable challenges of the imaging technique, namely, the artifacts arising from samples containing highly absorbing features. With the use of statistical weights in our noise model, we can account for these materials and recover features in the vicinity of the highly absorbing features that are lost in the conventional two-step approaches. In addition, the statistical modeling of our reconstruction approach will prove particularly beneficial in the ongoing transition of this imaging technique from synchrotron facilities to laboratory setups.

Myoanatomy of the velvet worm leg revealed by laboratory-based nanofocus X-ray source tomography.

X-ray computed tomography (CT) is a powerful noninvasive technique for investigating the inner structure of objects and organisms. However, the resolution of laboratory CT systems is typically limited to the micrometer range. In this paper, we present a table-top nanoCT system in conjunction with standard processing tools that is able to routinely reach resolutions down to 100 nm without using X-ray optics. We demonstrate its potential for biological investigations by imaging a walking appendage of Euperipatoides rowelli, a representative of Onychophora-an invertebrate group pivotal for understanding animal evolution. Comparative analyses proved that the nanoCT can depict the external morphology of the limb with an image quality similar to scanning electron microscopy, while simultaneously visualizing internal muscular structures at higher resolutions than confocal laser scanning microscopy. The obtained nanoCT data revealed hitherto unknown aspects of the onychophoran limb musculature, enabling the 3D reconstruction of individual muscle fibers, which was previously impossible using any laboratory-based imaging technique.

Propagation-based Phase-Contrast X-ray Imaging at a Compact Light Source.

We demonstrate the applicability of propagation-based X-ray phase-contrast imaging at a laser-assisted compact light source with known phantoms and the lungs and airways of a mouse. The Munich Compact Light Source provides a quasi-monochromatic beam with partial spatial coherence, and high flux relative to other non-synchrotron sources (up to 1010 ph/s). In our study we observe significant edge-enhancement and quantitative phase-retrieval is successfully performed on the known phantom. Furthermore the images of a small animal show the potential for live bio-imaging research studies that capture biological function using short exposures.