Multidimensional Analysis of the Adult Human Heart in Health and Disease Using Hierarchical Phase-Contrast Tomography.

Background Current clinical imaging modalities such as CT and MRI provide resolution adequate to diagnose cardiovascular diseases but cannot depict detailed structural features in the heart across length scales. Hierarchical phase-contrast tomography (HiP-CT) uses fourth-generation synchrotron sources with improved x-ray brilliance and high energies to provide micron-resolution imaging of intact adult organs with unprecedented detail. Purpose To evaluate the capability of HiP-CT to depict the macro- to microanatomy of structurally normal and abnormal adult human hearts ex vivo. Materials and Methods Between February 2021 and September 2023, two adult human donor hearts were obtained, fixed in formalin, and prepared using a mixture of crushed agar in a 70% ethanol solution. One heart was from a 63-year-old White male without known cardiac disease, and the other was from an 87-year-old White female with a history of multiple known cardiovascular pathologies including ischemic heart disease, hypertension, and atrial fibrillation. Nondestructive ex vivo imaging of these hearts without exogenous contrast agent was performed using HiP-CT at the European Synchrotron Radiation Facility. Results HiP-CT demonstrated the capacity for high-spatial-resolution, multiscale cardiac imaging ex vivo, revealing histologic-level detail of the myocardium, valves, coronary arteries, and cardiac conduction system across length scales. Virtual sectioning of the cardiac conduction system provided information on fatty infiltration, vascular supply, and pathways between the cardiac nodes and adjacent structures. HiP-CT achieved resolutions ranging from gross (isotropic voxels of approximately 20 µm) to microscopic (approximately 6.4-µm voxel size) to cellular (approximately 2.3-µm voxel size) in scale. The potential for quantitative assessment of features in health and disease was demonstrated. Conclusion HiP-CT provided high-spatial-resolution, three-dimensional images of structurally normal and diseased ex vivo adult human hearts. Whole-heart image volumes were obtained with isotropic voxels of approximately 20 µm, and local regions of interest were obtained with resolution down to 2.3-6.4 µm without the need for sectioning, destructive techniques, or exogenous contrast agents. Published under a CC BY 4.0 license Supplemental material is available for this article. See also the editorial by Bluemke and Pourmorteza in this issue.

A closer look at high-energy X-ray-induced bubble formation during soft tissue imaging.

Improving the scalability of tissue imaging throughput with bright, coherent X-rays requires identifying and mitigating artifacts resulting from the interactions between X-rays and matter. At synchrotron sources, long-term imaging of soft tissues in solution can result in gas bubble formation or cavitation, which dramatically compromises image quality and integrity of the samples. By combining in-line phase-contrast imaging with gas chromatography in real time, we were able to track the onset and evolution of high-energy X-ray-induced gas bubbles in ethanol-embedded soft tissue samples for tens of minutes (two to three times the typical scan times). We demonstrate quantitatively that vacuum degassing of the sample during preparation can significantly delay bubble formation, offering up to a twofold improvement in dose tolerance, depending on the tissue type. However, once nucleated, bubble growth is faster in degassed than undegassed samples, indicating their distinct metastable states at bubble onset. Gas chromatography analysis shows increased solvent vaporization concurrent with bubble formation, yet the quantities of dissolved gasses remain unchanged. By coupling features extracted from the radiographs with computational analysis of bubble characteristics, we uncover dose-controlled kinetics and nucleation site-specific growth. These hallmark signatures provide quantitative constraints on the driving mechanisms of bubble formation and growth. Overall, the observations highlight bubble formation as a critical yet often overlooked hurdle in upscaling X-ray imaging for biological tissues and soft materials and we offer an empirical foundation for their understanding and imaging protocol optimization. More importantly, our approaches establish a top-down scheme to decipher the complex, multiscale radiation-matter interactions in these applications.

In situ 4D tomography image analysis framework to follow sintering within 3D-printed glass scaffolds.

We propose a novel image analysis framework to automate analysis of X-ray microtomography images of sintering ceramics and glasses, using open-source toolkits and machine learning. Additive manufacturing (AM) of glasses and ceramics usually requires sintering of green bodies. Sintering causes shrinkage, which presents a challenge for controlling the metrology of the final architecture. Therefore, being able to monitor sintering in 3D over time (termed 4D) is important when developing new porous ceramics or glasses. Synchrotron X-ray tomographic imaging allows in situ, real-time capture of the sintering process at both micro and macro scales using a furnace rig, facilitating 4D quantitative analysis of the process. The proposed image analysis framework is capable of tracking and quantifying the densification of glass or ceramic particles within multiple volumes of interest (VOIs) along with structural changes over time using 4D image data. The framework is demonstrated by 4D quantitative analysis of bioactive glass ICIE16 within a 3D-printed scaffold. Here, densification of glass particles within 3 VOIs were tracked and quantified along with diameter change of struts and interstrut pore size over the 3D image series, delivering new insights on the sintering mechanism of ICIE16 bioactive glass particles in both micro and macro scales.

Observation of microstructure evolution during inertia friction welding using in-situ synchrotron X-ray diffraction.

The widespread use and development of inertia friction welding is currently restricted by an incomplete understanding of the deformation mechanisms and microstructure evolution during the process. Understanding phase transformations and lattice strains during inertia friction welding is essential for the development of robust numerical models capable of determining optimized process parameters and reducing the requirement for costly experimental trials. A unique compact rig has been designed and used in-situ with a high-speed synchrotron X-ray diffraction instrument to investigate the microstructure evolution during inertia friction welding of a high-carbon steel (BS1407). At the contact interface, the transformation from ferrite to austenite was captured in great detail, allowing for analysis of the phase fractions during the process. Measurement of the thermal response of the weld reveals that the transformation to austenite occurs 230 °C below the equilibrium start temperature of 725 °C. It is concluded that the localization of large strains around the contact interface produced as the specimens deform assists this non-equilibrium phase transformation.

Dynamic Multicontrast X-Ray Imaging Method Applied to Additive Manufacturing.

We present a dynamic implementation of the beam-tracking x-ray imaging method providing absorption, phase, and ultrasmall angle scattering signals with microscopic resolution and high frame rate. We demonstrate the method's ability to capture dynamic processes with 22-ms time resolution by investigating the melting of metals in laser additive manufacturing, which has so far been limited to single-modality synchrotron radiography. The simultaneous availability of three contrast channels enables earlier segmentation of droplets, tracking of powder dynamic, and estimation of unfused powder amounts, demonstrating that the method can provide additional information on melting processes.

High-Density Protein Loading on Hierarchically Porous Layered Double Hydroxide Composites with a Rational Mesostructure.

Hierarchically porous biocompatible Mg-Al-Cl-type layered double hydroxide (LDH) composites containing aluminum hydroxide (Alhy) have been prepared using a phase-separation process. The sol-gel synthesis allows for the hierarchical pores of the LDH-Alhy composites to be tuned, leading to a high specific solid surface area per unit volume available for high-molecular-weight protein adsorptions. A linear relationship between the effective surface area, SEFF, and loading capacity of a model protein, bovine serum albumin (BSA), is established following successful control of the structure of the LDH-Alhy composite. The threshold of the mean pore diameter, Dpm, above which BSA is effectively adsorbed on the surface of LDH-Alhy composites, is deduced as 20 nm. In particular, LDH-Alhy composite aerogels obtained via supercritical drying exhibit an extremely high capacity for protein loading (996 mg/g) as a result of a large mean mesopore diameter (>30 nm). The protein loading on LDH-Alhy is >14 times that of a reference LDH material (70 mg/g) prepared via a standard procedure. Importantly, BSA molecules pre-adsorbed on porous composites were successfully released on soaking in ionic solutions (HPO4(2-) and Cl(-) aqueous). The superior capability of the biocompatible LDH materials for loading, encapsulation, and releasing large quantities of proteins was clearly demonstrated.

Comparison of three-dimensional analysis and stereological techniques for quantifying lithium-ion battery electrode microstructures.

Lithium-ion battery performance is intrinsically linked to electrode microstructure. Quantitative measurement of key structural parameters of lithium-ion battery electrode microstructures will enable optimization as well as motivate systematic numerical studies for the improvement of battery performance. With the rapid development of 3-D imaging techniques, quantitative assessment of 3-D microstructures from 2-D image sections by stereological methods appears outmoded; however, in spite of the proliferation of tomographic imaging techniques, it remains significantly easier to obtain two-dimensional (2-D) data sets. In this study, stereological prediction and three-dimensional (3-D) analysis techniques for quantitative assessment of key geometric parameters for characterizing battery electrode microstructures are examined and compared. Lithium-ion battery electrodes were imaged using synchrotron-based X-ray tomographic microscopy. For each electrode sample investigated, stereological analysis was performed on reconstructed 2-D image sections generated from tomographic imaging, whereas direct 3-D analysis was performed on reconstructed image volumes. The analysis showed that geometric parameter estimation using 2-D image sections is bound to be associated with ambiguity and that volume-based 3-D characterization of nonconvex, irregular and interconnected particles can be used to more accurately quantify spatially-dependent parameters, such as tortuosity and pore-phase connectivity.

A correlative imaging based methodology for accurate quantitative assessment of bone formation in additive manufactured implants.

A correlative imaging methodology was developed to accurately quantify bone formation in the complex lattice structure of additive manufactured implants. Micro computed tomography (µCT) and histomorphometry were combined, integrating the best features from both, while demonstrating the limitations of each imaging modality. This semi-automatic methodology registered each modality using a coarse graining technique to speed the registration of 2D histology sections to high resolution 3D µCT datasets. Once registered, histomorphometric qualitative and quantitative bone descriptors were directly correlated to 3D quantitative bone descriptors, such as bone ingrowth and bone contact. The correlative imaging allowed the significant volumetric shrinkage of histology sections to be quantified for the first time (~15 %). This technique demonstrated the importance of location of the histological section, demonstrating that up to a 30 % offset can be introduced. The results were used to quantitatively demonstrate the effectiveness of 3D printed titanium lattice implants.

Temporal sparsity exploiting nonlocal regularization for 4D computed tomography reconstruction.

X-ray imaging applications in medical and material sciences are frequently limited by the number of tomographic projections collected. The inversion of the limited projection data is an ill-posed problem and needs regularization. Traditional spatial regularization is not well adapted to the dynamic nature of time-lapse tomography since it discards the redundancy of the temporal information. In this paper, we propose a novel iterative reconstruction algorithm with a nonlocal regularization term to account for time-evolving datasets. The aim of the proposed nonlocal penalty is to collect the maximum relevant information in the spatial and temporal domains. With the proposed sparsity seeking approach in the temporal space, the computational complexity of the classical nonlocal regularizer is substantially reduced (at least by one order of magnitude). The presented reconstruction method can be directly applied to various big data 4D (x, y, z+time) tomographic experiments in many fields. We apply the proposed technique to modelled data and to real dynamic X-ray microtomography (XMT) data of high resolution. Compared to the classical spatio-temporal nonlocal regularization approach, the proposed method delivers reconstructed images of improved resolution and higher contrast while remaining significantly less computationally demanding.

A novel high-temperature furnace for combined in situ synchrotron X-ray diffraction and infrared thermal imaging to investigate the effects of thermal gradients upon the structure of ceramic materials.

A new technique combining in situ X-ray diffraction using synchrotron radiation and infrared thermal imaging is reported. The technique enables the application, generation and measurement of significant thermal gradients, and furthermore allows the direct spatial correlation of thermal and crystallographic measurements. The design and implementation of a novel furnace enabling the simultaneous thermal and X-ray measurements is described. The technique is expected to have wide applicability in material science and engineering; here it has been applied to the study of solid oxide fuel cells at high temperature.

Deep Learning for 3D Vascular Segmentation in Phase Contrast Tomography.

Automated blood vessel segmentation is critical for biomedical image analysis, as vessel morphology changes are associated with numerous pathologies. Still, precise segmentation is difficult due to the complexity of vascular structures, anatomical variations across patients, the scarcity of annotated public datasets, and the quality of images. Our goal is to provide a foundation on the topic and identify a robust baseline model for application to vascular segmentation using a new imaging modality, Hierarchical Phase-Contrast Tomography (HiP-CT). We begin with an extensive review of current machine learning approaches for vascular segmentation across various organs. Our work introduces a meticulously curated training dataset, verified by double annotators, consisting of vascular data from three kidneys imaged using Hierarchical Phase-Contrast Tomography (HiP-CT) as part of the Human Organ Atlas Project. HiP-CT, pioneered at the European Synchrotron Radiation Facility in 2020, revolutionizes 3D organ imaging by offering resolution around 20µm/voxel, and enabling highly detailed localized zooms up to 1µm/voxel without physical sectioning. We leverage the nnU-Net framework to evaluate model performance on this high-resolution dataset, using both known and novel samples, and implementing metrics tailored for vascular structures. Our comprehensive review and empirical analysis on HiP-CT data sets a new standard for evaluating machine learning models in high-resolution organ imaging. Our three experiments yielded Dice scores of 0.9523 and 0.9410, and 0.8585, respectively. Nevertheless, DSC primarily assesses voxel-to-voxel concordance, overlooking several crucial characteristics of the vessels and should not be the sole metric for deciding the performance of vascular segmentation. Our results show that while segmentations yielded reasonably high scores-such as centerline Dice values ranging from 0.82 to 0.88, certain errors persisted. Specifically, large vessels that collapsed due to the lack of hydro-static pressure (HiP-CT is an ex vivo technique) were segmented poorly. Moreover, decreased connectivity in finer vessels and higher segmentation errors at vessel boundaries were observed. Such errors, particularly in significant vessels, obstruct the understanding of the structures by interrupting vascular tree connectivity. Through our review and outputs, we aim to set a benchmark for subsequent model evaluations using various modalities, especially with the HiP-CT imaging database.

Vasculature segmentation in 3D hierarchical phase-contrast tomography images of human kidneys.

Efficient algorithms are needed to segment vasculature in new three-dimensional (3D) medical imaging datasets at scale for a wide range of research and clinical applications. Manual segmentation of vessels in images is time-consuming and expensive. Computational approaches are more scalable but have limitations in accuracy. We organized a global machine learning competition, engaging 1,401 participants, to help develop new deep learning methods for 3D blood vessel segmentation. This paper presents a detailed analysis of the top-performing solutions using manually curated 3D Hierarchical Phase-Contrast Tomography datasets of the human kidney, focusing on the segmentation accuracy and morphological analysis, thereby establishing a benchmark for future studies in blood vessel segmentation within phase-contrast tomography imaging.

Direct observation of degassing during decompression of basaltic magma.

Transitions in eruptive style during volcanic eruptions strongly depend on how easily gas and magma decouple during ascent. Stronger gas-melt coupling favors highly explosive eruptions, whereas weaker coupling promotes lava fountaining and lava flows. The mechanisms producing these transitions are still poorly understood because of a lack of direct observations of bubble dynamics under natural magmatic conditions. Here, we combine x-ray radiography with a novel high-pressure/high-temperature apparatus to observe and quantify in real-time bubble growth and coalescence in basaltic magmas from 100 megapascals to surface. For low-viscosity magmas, bubbles coalesce and recover a spherical shape within 3 seconds, implying that, for lava fountaining activity, gas and melt remain coupled during the ascent up to the last hundred meters of the conduit. For higher-viscosity magmas, recovery times become longer, promoting connected bubble pathways. This apparatus opens frontiers in unraveling magmatic/volcanic processes, leading to improved hazard assessment and risk mitigation.

Pore evolution mechanisms during directed energy deposition additive manufacturing.

Porosity in directed energy deposition (DED) deteriorates mechanical performances of components, limiting safety-critical applications. However, how pores arise and evolve in DED remains unclear. Here, we reveal pore evolution mechanisms during DED using in situ X-ray imaging and multi-physics modelling. We quantify five mechanisms contributing to pore formation, migration, pushing, growth, removal and entrapment: (i) bubbles from gas atomised powder enter the melt pool, and then migrate circularly or laterally; (ii) small bubbles can escape from the pool surface, or coalesce into larger bubbles, or be entrapped by solidification fronts; (iii) larger coalesced bubbles can remain in the pool for long periods, pushed by the solid/liquid interface; (iv) Marangoni surface shear flow overcomes buoyancy, keeping larger bubbles from popping out; and (v) once large bubbles reach critical sizes they escape from the pool surface or are trapped in DED tracks. These mechanisms can guide the development of pore minimisation strategies.

3D printed hybrid scaffolds for bone regeneration using calcium methoxyethoxide as a calcium source.

Introduction: Hybrids consist of inorganic and organic co-networks that are indistinguishable above the nanoscale, which can lead to unprecedented combinations of properties, such as high toughness and controlled degradation. Methods: We present 3D printed bioactive hybrid scaffolds for bone regeneration, produced by incorporating calcium into our "Bouncy Bioglass", using calcium methoxyethoxide (CME) as the calcium precursor. SiO2-CaOCME/PTHF/PCL-diCOOH hybrid "inks" for additive manufacturing (Direct Ink Writing) were optimised for synergy of mechanical properties and open interconnected pore channels. Results and Discussion: Adding calcium improved printability. Changing calcium content (5, 10, 20, 30, and 40 mol.%) of the SiO2-CaOCME/PTHF/PCL-diCOOH hybrids affected printability and mechanical properties of the lattice-like scaffolds. Hybrids containing 30 mol.% calcium in the inorganic network (70S30CCME-CL) printed with 500 µm channels and 100 µm strut size achieved the highest strength (0.90 ± 0.23 MPa) and modulus of toughness (0.22 ± 0.04 MPa). These values were higher than Ca-free SiO2/PTHF/PCL-diCOOH hybrids (0.36 ± 0.14 MPa strength and 0.06 ± 0.01 MPa toughness modulus). Over a period of 90 days of immersion in simulated body fluid (SBF), the 70S30CCME-CL hybrids also kept a stable strain to failure (~30 %) and formed hydroxycarbonate apatite within three days. The extracts released by the 70S30CCME-CL hybrids in growth medium did not cause cytotoxic effects on human bone marrow stromal cells over 24 h of culture.

Preparation of large biological samples for high-resolution, hierarchical, synchrotron phase-contrast tomography with multimodal imaging compatibility.

Imaging across different scales is essential for understanding healthy organ morphology and pathophysiological changes. The macro- and microscale three-dimensional morphology of large samples, including intact human organs, is possible with X-ray microtomography (using laboratory or synchrotron sources). Preparation of large samples for high-resolution imaging, however, is challenging due to limitations such as sample shrinkage, insufficient contrast, movement of the sample and bubble formation during mounting or scanning. Here, we describe the preparation, stabilization, dehydration and mounting of large soft-tissue samples for X-ray microtomography. We detail the protocol applied to whole human organs and hierarchical phase-contrast tomography at the European Synchrotron Radiation Facility, yet it is applicable to a range of biological samples, including complete organisms. The protocol enhances the contrast when using X-ray imaging, while preventing sample motion during the scan, even with different sample orientations. Bubbles trapped during mounting and those formed during scanning (in the case of synchrotron X-ray imaging) are mitigated by multiple degassing steps. The sample preparation is also compatible with magnetic resonance imaging, computed tomography and histological observation. The sample preparation and mounting require 24-36 d for a large organ such as a whole human brain or heart. The preparation time varies depending on the composition, size and fragility of the tissue. Use of the protocol enables scanning of intact organs with a diameter of 150 mm with a local voxel size of 1 µm. The protocol requires users with expertise in handling human or animal organs, laboratory operation and X-ray imaging.