Small-angle scattering tensor tomography algorithm for robust reconstruction of complex textures

Texture tomography, a versatile framework to study crystalline texture in 3D

Crystallographic texture is a key organization feature of many technical and biological materials. In these materials, especially hierarchically structured ones, the preferential alignment of the nano constituents heavily influences the macroscopic behavior of the material. To study local crystallographic texture with both high spatial and angular resolution, we developed Texture Tomography (TexTOM). This approach allows the user to model the diffraction data of polycrystalline materials using the full reciprocal space of the crystal ensemble and describe the texture in each voxel via an orientation distribution function, hence it provides 3D reconstructions of the local texture by measuring the probabilities of all crystal orientations. The TexTOM approach addresses limitations associated with existing models: it correlates the intensities from several Bragg reflections, thus reducing ambiguities resulting from symmetry. Further, it yields quantitative probability distributions of local real space crystal orientations without further assumptions about the sample structure. Finally, its efficient mathematical formulation enables reconstructions faster than the time scale of the experiment. This manuscript presents the mathematical model, the inversion strategy and its current experimental implementation. We show characterizations of simulated data as well as experimental data obtained from a synthetic, inorganic model sample: the silica-witherite biomorph. TexTOM provides a versatile framework to reconstruct 3D quantitative texture information for polycrystalline samples; it opens the door for unprecedented insights into the nanostructural makeup of natural and technical materials.

Crossing length scales: X-ray approaches to studying the structure of biological materials

Biological materials have outstanding properties. With ease, challenging mechanical, optical or electrical properties are realised from comparatively `humble' building blocks. The key strategy to realise these properties is through extensive hierarchical structuring of the material from the millimetre to the nanometre scale in 3D. Though hierarchical structuring in biological materials has long been recognized, the 3D characterization of such structures remains a challenge. To understand the behaviour of materials, multimodal and multi-scale characterization approaches are needed. In this review, we outline current X-ray analysis approaches using the structures of bone and shells as examples. We show how recent advances have aided our understanding of hierarchical structures and their functions, and how these could be exploited for future research directions. We also discuss current roadblocks including radiation damage, data quantity and sample preparation, as well as strategies to address them.

Investigating the missing-wedge problem in small-angle X-ray scattering tensor tomography across real and reciprocal space

Small-angle-scattering tensor tomography is a technique for studying anisotropic nanostructures of millimetre-sized samples in a volume-resolved manner. It requires the acquisition of data through repeated tomographic rotations about an axis which is subjected to a series of tilts. The tilt that can be achieved with a typical setup is geometrically constrained, which leads to limits in the set of directions from which the different parts of the reciprocal space map can be probed. Here, we characterize the impact of this limitation on reconstructions in terms of the missing wedge problem of tomography, by treating the problem of tensor tomography as the reconstruction of a three-dimensional field of functions on the unit sphere, represented by a grid of Gaussian radial basis functions. We then devise an acquisition scheme to obtain complete data by remounting the sample, which we apply to a sample of human trabecular bone. Performing tensor tomographic reconstructions of limited data sets as well as the complete data set, we further investigate and validate the missing wedge problem by investigating reconstruction errors due to data incompleteness across both real and reciprocal space. Finally, we carry out an analysis of orientations and derived scalar quantities, to quantify the impact of this missing wedge problem on a typical tensor tomographic analysis. We conclude that the effects of data incompleteness are consistent with the predicted impact of the missing wedge problem, and that the impact on tensor tomographic analysis is appreciable but limited, especially if precautions are taken. In particular, there is only limited impact on the means and relative anisotropies of the reconstructed reciprocal space maps.

A step towards 6D WAXD tensor tomography

X-ray scattering/diffraction tensor tomography techniques are promising methods to acquire the 3D texture information of heterogeneous biological tissues at micrometre resolution. However, the methods suffer from a long overall acquisition time due to multi-dimensional scanning across real and reciprocal space. Here, a new approach is introduced to obtain 3D reciprocal information of each illuminated scanning volume using mathematic modeling, which is equivalent to a physical scanning procedure for collecting the full reciprocal information required for voxel reconstruction. The virtual reciprocal scanning scheme was validated by a simulated 6D wide-angle X-ray diffraction tomography experiment. The theoretical validation of the method represents an important technological advancement for 6D diffraction tensor tomography and a crucial step towards pervasive applications in the characterization of heterogeneous materials.

ForMAX - a beamline for multiscale and multimodal structural characterization of hierarchical materials

The ForMAX beamline at the MAX IV Laboratory provides multiscale and multimodal structural characterization of hierarchical materials in the nanometre to millimetre range by combining small- and wide-angle X-ray scattering with full-field microtomography. The modular design of the beamline is optimized for easy switching between different experimental modalities. The beamline has a special focus on the development of novel fibrous materials from forest resources, but it is also well suited for studies within, for example, food science and biomedical research.

Unveiling breast cancer metastasis through an advanced X-ray imaging approach

Breast cancer is a significant global health burden, causing a substantial number of deaths. Systemic metastatic tumour cell dissemination is a major cause of poor outcomes. Understanding the mechanisms underlying metastasis is crucial for effective interventions. Changes in the extracellular matrix play a pivotal role in breast cancer metastasis. In this work, we present an advanced multimodal X-ray computed tomography, by combining Small-angle X-ray Scattering Tensor Tomography (SAXS-TT) and X-ray Fluorescence Computed Tomography (XRF-CT). This approach likely brings out valuable information about the breast cancer metastasis cascade. Initial results from its application on a breast cancer specimen reveal the collective influence of key molecules in the metastatic mechanism, identifying a strong correlation between zinc accumulation (associated with matrix metalloproteinases MMPs) and highly oriented collagen. MMPs trigger collagen alignment, facilitating breast cancer cell intravasation, while iron accumulation, linked to angiogenesis and vascular endothelial growth factor VEGF, supports cell proliferation and metastasis. Therefore, these findings highlight the potential of the advanced multimodal X-ray computed tomography approach and pave the way for in-depth investigation of breast cancer metastasis, which may guide the development of novel therapeutic approaches and enable personalised treatment strategies, ultimately improving patient outcomes in breast cancer management.

Micro- and nanostructure specific X-ray tomography reveals less matrix formation and altered collagen organization following reduced loading during Achilles tendon healing

Recovery of the collagen structure following Achilles tendon rupture is poor, resulting in a high risk for re-ruptures. The loading environment during healing affects the mechanical properties of the tendon, but the relation between loading regime and healing outcome remains unclear. This is partially due to our limited understanding regarding the effects of loading on the micro- and nanostructure of the healing tissue. We addressed this through a combination of synchrotron phase-contrast X-ray microtomography and small-angle X-ray scattering tensor tomography (SASTT) to visualize the 3D organization of microscale fibers and nanoscale fibrils, respectively. The effect of in vivo loading on these structures was characterized in early healing of rat Achilles tendons by comparing full activity with immobilization. Unloading resulted in structural changes that can explain the reported impaired mechanical performance. In particular, unloading led to slower tissue regeneration and maturation, with less and more disorganized collagen, as well as an increased presence of adipose tissue. This study provides the first application of SASTT on soft musculoskeletal tissues and clearly demonstrates its potential to investigate a variety of other collagenous tissues. STATEMENT OF SIGNIFICANCE: Currently our understanding of the mechanobiological effects on the recovery of the structural hierarchical organization of injured Achilles tendons is limited. We provide insight into how loading affects the healing process by using a cutting-edge approach to for the first time characterize the 3D micro- and nanostructure of the regenerating collagen. We uncovered that, during early healing, unloading results in a delayed and more disorganized regeneration of both fibers (microscale) and fibrils (nanoscale), as well as increased presence of adipose tissue. The results set the ground for the development of further specialized protocols for tendon recovery.