Imaging intact human organs with local resolution of cellular structures using hierarchical phase-contrast tomography

Endothelial cell supplementation promotes xenograft revascularization during short-term ovarian tissue transplantation

The ischemic/hypoxic window after Ovarian Tissue Transplantation (OTT) can be responsible for the loss of more than 60 % of follicles. The implantation of the tissue supplemented with endothelial cells (ECs) inside dermal substitutes represents a promising strategy for improving graft revascularization. Ovarian biopsies were partly cryopreserved and partly digested to isolate ovarian ECs (OVECs). Four dermal substitutes (Integra®, made of bovine collagen enriched with chondroitin 6-sulfate; PELNAC®, composed of porcine collagen; Myriad Matrix®, derived from decellularized ovine forestomach; and NovoSorb® BMT, a foam of polyurethane) were compared for their angiogenic bioactive properties. OVECs cultured onto the scaffolds upregulated the expression of angiogenic factors, supporting their use in boosting revascularization. Adhesion and proliferation assays suggested that the most suitable scaffold was the bovine collagen one, which was chosen for further in vivo experiments. Cryopreserved tissue was transplanted onto the 3D scaffold in immunodeficient mice with or without cell supplementation, and after 14 days, it was analyzed by immunofluorescence (IF) and X-ray phase contrast microtomography. The revascularization area of OVECs-supplemented tissue was doubled (7.14 %) compared to the scaffold transplanted alone (3.67 %). Furthermore, tissue viability, evaluated by nuclear counting, was significantly higher (mean of 169.6 nuclei/field) in the tissue grafted with OVECs than in the tissue grafted alone (mean of 87.2 nuclei/field). Overall, our findings suggest that the OVECs-supplementation shortens the ischemic interval and may significantly improve fertility preservation procedures.

Considerations and recommendations from the ISMRM Diffusion Study Group for preclinical diffusion MRI: Part 3-Ex vivo imaging: Data processing, comparisons with microscopy, and tractography

Preclinical diffusion MRI (dMRI) has proven value in methods development and validation, characterizing the biological basis of diffusion phenomena, and comparative anatomy. While dMRI enables in vivo non-invasive characterization of tissue, ex vivo dMRI is increasingly being used to probe tissue microstructure and brain connectivity. Ex vivo dMRI has several experimental advantages that facilitate high spatial resolution and high SNR images, cutting-edge diffusion contrasts, and direct comparison with histological data as a methodological validation. However, there are a number of considerations that must be made when performing ex vivo experiments. The steps from tissue preparation, image acquisition and processing, and interpretation of results are complex, with many decisions that not only differ dramatically from in vivo imaging of small animals, but ultimately affect what questions can be answered using the data. This work concludes a three-part series of recommendations and considerations for preclinical dMRI. Herein, we describe best practices for dMRI of ex vivo tissue, with a focus on image pre-processing, data processing, and comparisons with microscopy. In each section, we attempt to provide guidelines and recommendations but also highlight areas for which no guidelines exist (and why), and where future work should lie. We end by providing guidelines on code sharing and data sharing and point toward open-source software and databases specific to small animal and ex vivo imaging.

Visualization of Unhatched Brine Shrimp Eggs in Zebrafish Intestines Using Synchrotron Radiation Phase-Contrast CT

Brine shrimp are an ideal bait for zebrafish with high protein content. In laboratory settings, brine shrimp eggs (BSEs) are commonly used to hatch for acquiring brine shrimp. However, not all BSEs are able to successfully hatch into brine shrimp. Actually, some unhatched BSEs (UBSEs) retain and are collected along with the brine shrimp as bait. The digestibility of UBSEs and their potential impact on the digestive system of zebrafish have not been demonstrated. In this study, high-resolution synchrotron radiation phase-contrast CT (PCCT) was used to show the internal structures of UBSEs. Morphological changes of UBSEs were investigated after digestion in zebrafish intestines. The visualization of shell rupturing, collapsing, and shattering of UBSEs reveals that zebrafish intestines exerted much extra useless effort to digest the UBSEs. The results indicate that UBSEs should be completely discarded from the bait of brine shrimp before feeding zebrafish.

Harnessing Advanced Machine Learning Techniques for Microscopic Vessel Segmentation in Pulmonary Fibrosis Using Novel Hierarchical Phase-Contrast Tomography Images

BACKGROUND

 Fibrotic lung disease is a progressive illness that causes scarring and ultimately respiratory failure, with irreversible damage by the time it is diagnosed on computed tomography imaging. Recent research postulates the role of the lung vasculature on the pathogenesis of the disease. With the recent development of high-resolution hierarchical phase-contrast tomography (HiP-CT), we have the potential to understand and detect changes in the lungs long before conventional imaging. However, to gain quantitative insight into vascular changes you first need to be able to segment the vessels before further downstream analysis can be conducted. Aside from this, HiP-CT generates large-volume, high-resolution data which is time-consuming and expensive to label.

OBJECTIVES

 This project aims to qualitatively assess the latest machine learning methods for vessel segmentation in HiP-CT data to enable label propagation as the first step for imaging biomarker discovery, with the goal to identify early-stage interstitial lung disease amenable to treatment, before fibrosis begins.

METHODS

 Semisupervised learning (SSL) has become a growing method to tackle sparsely labeled datasets due to its leveraging of unlabeled data. In this study, we will compare two SSL methods; Seg PL, based on pseudo-labeling, and MisMatch, using consistency regularization against state-of-the-art supervised learning method, nnU-Net, on vessel segmentation in sparsely labeled lung HiP-CT data.

RESULTS

 On initial experimentation, both MisMatch and SegPL showed promising performance on qualitative review. In comparison with supervised learning, both MisMatch and SegPL showed better out-of-distribution performance within the same sample (different vessel morphology and texture vessels), though supervised learning provided more consistent segmentations for well-represented labels in the limited annotations.

CONCLUSION

 Further quantitative research is required to better assess the generalizability of these findings, though they show promising first steps toward leveraging this novel data to tackle fibrotic lung disease.

Determining the optimal choice of attenuation filters and propagation distance for polychromatic phase-contrast micro-computed tomography of a multi-material electromotor using synchrotron radiation

Optimizing phase-contrast micro-computed tomography (µCT) for a given object is not trivial if the radiation is polychromatic and the object multi-material. This study demonstrates how an optimal combination of propagation distance and mean energy (set by attenuation filters) may be derived for such an object (an electromotor scanned on beamline BM18 at ESRF in Grenoble, France). In addition to appropriate image quality metrics, it is mandatory to define a task. In that respect, raising Emean from 100 keV to 164 keV mitigates beam hardening by metal parts, yet raising Emean further to 230 keV deteriorates CNR2 (where CNR is contrast-to-noise ratio) due to higher image noise. Propagation distances between d = 2 m and 25.3 m are evaluated crosswise with energy. While longer propagation distances generally yield higher CNR2, shorter distances appear favorable when discerning plastic near metal parts. SNR2 (where SNR is signal-to-noise ratio) power spectra and modulation transfer (MTF) are evaluated independently from two-dimensional projections supporting volume image analysis for which image sharpness depends strongly on the digital filters (Paganin and Wiener) which are applied along with filtered back-projection. In summary, optimizing synchrotron µCT scans remains a very complex task which differs from object to object. A physically accurate model of the complete imaging process may not only allow for optimization by simulation but also ideally improve CT image reconstruction in the near future.

Air artifact suppression in phase contrast micro-CT using conditional generative adversarial networks

3D virtual histology of formalin-fixed and paraffin-embedded (FFPE) tissue by means of phase contrast micro-computed tomography (micro-CT) is an increasingly popular technique, as it allows the 3D architecture of the tissue to be addressed without the need of additional heavy ion based staining approaches. Therefore, it can be applied on archived standard FFPE tissue blocks. However, one of the major concerns of using phase contrast micro-CT in combination with FFPE tissue blocks is the trapped air within the tissue. While air inclusion within the FFPE tissue block does not strongly impact the workflow and quality of classical histology, it creates serious obstacles in 3D visualization of detailed morphology. In particular, the 3D analysis of structural features is challenging, due to a strong edge effect caused by the phase shift at the air-tissue/paraffin interface. Despite certain improvements in sample preparation to eliminate air inclusion, such as the use of negative pressure, it is not always possible to remove all trapped air, for example in soft tissues such as lung. Here, we present a novel workflow based on conditional generative adversarial networks (cGANs) to effectively replace these air artifact regions with generated tissue, which are influenced by the surrounding content. Our results show that this approach not only improves the visualization of the lung tissue but also eases the use of structural analysis on the air artifact-suppressed phase contrast micro-CT scans. In addition, we demonstrate the transferability of the generative model to FFPE specimens of porcine lung tissue.

Three-dimensional fiber orientation mapping of ex vivo human brain at micrometer resolution

The accurate measurement of three-dimensional (3D) fiber orientation in the brain is crucial for reconstructing fiber pathways and studying their involvement in neurological diseases. Comprehensive reconstruction of axonal tracts and small fascicles requires high-resolution technology beyond the ability of current in vivo imaging (e.g., diffusion magnetic resonance imaging). Optical imaging methods such as polarization-sensitive optical coherence tomography (PS-OCT) can quantify fiber orientation at micrometer resolution but have been limited to two-dimensional in-plane orientation, preventing the comprehensive study of connectivity in 3D. In this work we present a novel method to quantify volumetric 3D orientation in full angular space with PS-OCT in postmortem human brain tissues. We measure the polarization contrasts of the brain sample from two illumination angles of 0 and 15° and apply a computational method that yields the 3D optic axis orientation and true birefringence. We further present 3D fiber orientation maps of entire coronal cerebrum sections and brainstem with 10 μm in-plane resolution, revealing unprecedented details of fiber configurations. We envision that our method will open a promising avenue towards large-scale 3D fiber axis mapping in the human brain as well as other complex fibrous tissues at microscopic level.

Superimposed Wavefront Imaging of Diffraction-enhanced X-rays: sparsity-aware CT reconstruction from limited-view projections

PURPOSE

In this paper, we describe an algebraic reconstruction algorithm with a total variation regularization (ART + TV) based on the Superimposed Wavefront Imaging of Diffraction-enhanced X-rays (SWIDeX) method to effectively reduce the number of projections required for differential phase-contrast CT reconstruction.

METHODS

SWIDeX is a technique that uses a Laue-case Si analyzer with closely spaced scintillator to generate second derivative phase-contrast images with high contrast of a subject. When the projections obtained by this technique are reconstructed, a Laplacian phase-contrast tomographic image with higher sparsity than the original physical distribution of the subject can be obtained. In the proposed method, the Laplacian image is first obtained by applying ART + TV, which is expected to reduce the projection with higher sparsity, to the projection obtained from SWIDeX with a limited number of views. Then, by solving Poisson's equation for the Laplacian image, a tomographic image representing the refractive index distribution is obtained.

RESULTS

Simulations and actual X-ray experiments were conducted to demonstrate the effectiveness of the proposed method in projection reduction. In the simulation, image quality was maintained even when the number of projections was reduced to about 1/10 of the originally required views, and in the actual experiment, biological tissue structure was maintained even when the number of projections was reduced to about 1/30.

CONCLUSION

SWIDeX can visualize the internal structures of biological tissues with very high contrast, and the proposed method will be useful for CT reconstruction from large projection data with a wide field of view and high spatial resolution.

Chest computed tomography and plain radiographs demonstrate vascular distribution and characteristics in COVID-19 lung disease - a pulmonary vasculopathy

Introduction

Early in the COVID-19 pandemic, CT was demonstrated as a sensitive tool for diagnosing COVID-19. We undertook a detailed study of CT scans in COVID-19 patients to characterise disease distribution within lung parenchyma, respiratory airways, and pulmonary vasculature, aiming to delineate underlying disease processes.

Methods

We characterised acute phase chest CT of 40 participants with COVID-19 from the REACT study, 31 with CT pulmonary angiography (CTPA), 4 with intravenous contrast enhanced CT and 5 with non-intravenous contrast enhanced CT. Participants had neither been vaccinated nor received systemic steroids. We further correlated the distribution of lung parenchymal damage on CT with contemporaneous chest radiographs.

Results

Parenchymal lung damage was found in all subjects. However, airways inflammation was present in only 23% (9) and limited to small areas. Notably, vascular abnormalities were dominant and characterised by dilated peripheral pulmonary vessels supplying areas of lung damage in a gravity-dependent distribution bilaterally in 95% (38), basally in 90% (36), peripherally in 92.5% (37), and posteriorly in 90% (36). Macrothrombosis was demonstrated in 23% (7) of CTPAs. Wedge-shaped peripheral lung damage, resembling areas of pulmonary vascular congestion, were distinct in 53% (21) with or without visible macrothrombosis. Pleural effusions were seen in 28% (11). Notably, lung opacification distribution in 98% of the plain radiographs matched distribution on CT (39).

Conclusion

Our study frames COVID-19 as a pulmonary vasculopathy rather than a more conventional pneumonia which may be important not only for guiding mechanistic study design but also for the development of novel targeted therapeutics.

3D Histological Analysis of Soft Tissues by Contrast-Enhanced X-Ray Microfocus Computed Tomography: Screening and Staining Optimization of Contrast-Enhancing Staining Agents

The gold standard for studying biological soft tissues at the microscale (i.e., histology) is tissue sectioning with subsequent colorimetric or fluorescent staining and visual inspection under the microscope. When tissue integrity must be maintained for 3D histological assessment, contrast-enhanced microfocus X-ray computed tomography (CECT) is a promising solution, but there is still a lack of staining protocol optimization of contrast-enhancing staining agents (CESAs). Therefore, in this study, mouse auricles were incubated with Hafnium-substituted Wells-Dawson polyoxometalate, cationic iodinated contrast agent, or Lugol's iodine and were imaged with high-resolution CECT. Alignment with corresponding H&E-stained sections enabled the identification and segmentation of different tissue types. Contrast differences between tissue types were increased by washing the samples after staining or by combining CESAs. Finally, we proved that the latter could be used to quantitatively assess the 3D thickness distribution of the epidermis in the ears of a mouse model of psoriasis-like dermatitis. In conclusion, CECT and bright-field microscopy are complementary and not mutually exclusive techniques for the histological assessment of biological tissues. While bright-field microscopy gives detailed information about the cellular composition of tissues, CECT provides a better insight into the spatial interrelationship of tissues and is a powerful tool for performing 3D structural quantification.

Quantification of 3D microstructures in Achilles tendons during in situ loading reveals anisotropic fiber response

While the number of studies investigating Achilles tendon pathologies has grown exponentially, more research is needed to gain a better understanding of the complex relation between its hierarchical structure, mechanical response, and failure. At the microscale, collagen fibers are, with some degree of dispersion, primarily aligned along the principal loading direction. However, during tension, rearrangements and reorientations of these fibers are believed to occur. As 3D micro-movements are hard to capture, the precise nature of this fiber reorganization remains unknown. This study aimed to visualize and quantify the intricate fiber changes occurring within rat Achilles tendons under tension. Rat tendons were in situ loaded with concurrent synchrotron phase contrast microCT imaging. The results are heterogenous and show that collagen fibers' response to loading is nonuniform and depends on anatomical orientation. Furthermore, damage propagation could be visualized, revealing that in the presence of heterotopic ossification, damage proceeds within the ossified deposits rather than at the interface between hard and soft tissues. Our approach could effectively capture the microstructural changes occurring during loading and shows promise in understanding the relation between microstructure and mechanical response for ex-vivo Achilles tendons and other biological tissues. STATEMENT OF SIGNIFICANCE: Achilles tendons endure high mechanical loads during daily motion and physical activities. Understanding the structural and mechanical responses of Achilles tendons to such loads is vital for elucidating their function in health and pathology. We have combined the use of synchrotron phase contrast microCT with in situ mechanical loading to contribute to a better understanding of the relation between microstructural response and organ scale mechanical properties. The proposed methodology will be valuable for future research into the interplay between structure, mechanics, and pathology of tendons, and for the development of more effective strategies to preserve tendon function and possibly mitigating musculoskeletal disorders.

Visualization of the hatching of brine shrimp eggs using ultrafast and high-resolution phase-contrast CTs

Micro and small organisms (MSOs) are essential components of the ecosystem. Many MSOs reproduce by hatching eggs, making it crucial to study the morphology of these eggs and their incubation products (IPs) in related research. Phase-contrast CT (PCCT) is a powerful imaging modality known for its high resolution and sensitivity to soft tissues. In this study, an ultrafast PCCT system was used to scan brine shrimp eggs (BSEs) before hatching to determine their viability. High-resolution PCCT was used to reveal the microstructures of BSEs and IPs. We found that normal BSEs have an exclusively regular structure, making them easily identifiable. The use of ultrafast PCCT not only allowed for quick determination of BSE viability but also significantly reduced the amount of irradiation exposure to the eggs. All of the normal BSEs that were tested successfully hatched into brine shrimp, demonstrating the high safety of ultrafast PCCT. The high-resolution PCCT images clearly showed the formation of hatching membranes, cracks, and deformable bodies during the hatching process. The results suggest that ultrafast PCCT has the potential to assess the viability of MSO eggs, while high-resolution PCCT can provide valuable insight into the morphological changes that occur during the hatching process.

Bridging the 3D geometrical organisation of white matter pathways across anatomical length scales and species

We used diffusion MRI and x-ray synchrotron imaging on monkey and mice brains to examine the organisation of fibre pathways in white matter across anatomical scales. We compared the structure in the corpus callosum and crossing fibre regions and investigated the differences in cuprizone-induced demyelination in mouse brains versus healthy controls. Our findings revealed common principles of fibre organisation that apply despite the varying patterns observed across species; small axonal fasciculi and major bundles formed laminar structures with varying angles, according to the characteristics of major pathways. Fasciculi exhibited non-straight paths around obstacles like blood vessels, comparable across the samples of varying fibre complexity and demyelination. Quantifications of fibre orientation distributions were consistent across anatomical length scales and modalities, whereas tissue anisotropy had a more complex relationship, both dependent on the field-of-view. Our study emphasises the need to balance field-of-view and voxel size when characterising white matter features across length scales.

Design, Construction, and Test of Compact, Distributed-Charge, X-Band Accelerator Systems that Enable Image-Guided, VHEE FLASH Radiotherapy

The design and optimization of laser-Compton x-ray systems based on compact distributed charge accelerator structures can enable micron-scale imaging of disease and the concomitant production of beams of Very High Energy Electrons (VHEEs) capable of producing FLASH-relevant dose rates. The physics of laser-Compton x-ray scattering ensures that the scattered x-rays follow exactly the trajectory of the incident electrons, thus providing a route to image-guided, VHEE FLASH radiotherapy. The keys to a compact architecture capable of producing both laser-Compton x-rays and VHEEs are the use of X-band RF accelerator structures which have been demonstrated to operate with over 100 MeV/m acceleration gradients. The operation of these structures in a distributed charge mode in which each radiofrequency (RF) cycle of the drive RF pulse is filled with a low-charge, high-brightness electron bunch is enabled by the illumination of a high-brightness photogun with a train of UV laser pulses synchronized to the frequency of the underlying accelerator system. The UV pulse trains are created by a patented pulse synthesis approach which utilizes the RF clock of the accelerator to phase and amplitude modulate a narrow band continuous wave (CW) seed laser. In this way it is possible to produce up to 10 μA of average beam current from the accelerator. Such high current from a compact accelerator enables production of sufficient x-rays via laser-Compton scattering for clinical imaging and does so from a machine of "clinical" footprint. At the same time, the production of 1000 or greater individual micro-bunches per RF pulse enables > 10 nC of charge to be produced in a macrobunch of < 100 ns. The design, construction, and test of the 100-MeV class prototype system in Irvine, CA is also presented.

3D multiscale characterization of the human placenta: Bridging anatomy and histology by X-ray phase-contrast tomography

The human placenta exhibits a complex three-dimensional (3D) structure with a interpenetrating vascular tree and large internal interfacial area. In a unique and yet insufficiently explored way, this parenchymal structure enables its multiple functions as a respiratory, renal, and gastrointestinal multiorgan. The histopathological states are highly correlated with complications and health issues of mother, and fetus or newborn. Macroscopic and microscopic examination has so far been challenging to reconcile on the entire organ. Here we show that anatomical and histological scales can be bridged with the advent of hierarchical phase-contrast tomography and highly brilliant synchrotron radiation. To this end, we are exploiting the new capabilities offered by the BM18 beamline at ESRF, Grenoble for whole organ as well as the coherence beamline P10 at DESY, Hamburg for high-resolution, creating unique multiscale datasets. We also show that within certain limits, translation to μCT instrumentation for 3D placenta examination becomes possible based on advanced preparation and CT protocols, while segmentation of the datasets by machine learning now remains the biggest challenge.

The Human Cell Atlas from a cell census to a unified foundation model

With the convergence of notable advances in molecular and spatial profiling methods and new computational approaches taking advantage of artificial intelligence and machine learning, the construction of cell atlases is progressing from data collection to atlas integration and beyond. Here, we explore five ways in which cell atlases, including the Human Cell Atlas, are already revealing valuable biological insights, and how they are poised to provide even greater benefits in the coming years. In particular, we discuss cell atlases as censuses of cells; as 3D maps of cells in the body, across modalities and scales; as maps connecting genotype causes to phenotype effects; as 4D maps of development; and, ultimately, as foundation models of biology unifying all of these aspects and helping to transform medicine.

Hybrid dark-field and attenuation contrast retrieval for laboratory-based X-ray tomography

X-ray dark-field imaging highlights sample structures through contrast generated by sub-resolution features within the inspected volume. Quantifying dark-field signals generally involves multiple exposures for phase retrieval, separating contributions from scattering, refraction, and attenuation. Here, we introduce an approach for non-interferometric X-ray dark-field imaging that presents a single-parameter representation of the sample. This fuses attenuation and dark-field signals, enabling the reconstruction of a unified three-dimensional volume. Notably, our method can obtain dark-field contrast from a single exposure and employs conventional back projection algorithms for reconstruction. Our approach is based on the assumption of a macroscopically homogeneous material, which we validate through experiments on phantoms and on biological tissue samples. The methodology is implemented on a laboratory-based, rotating anode X-ray tube system without the need for coherent radiation or a high-resolution detector. Utilizing this system with streamlined data acquisition enables expedited scanning while maximizing dose efficiency. These attributes are crucial in time- and dose-sensitive medical imaging applications and unlock the ability of dark-field contrast with high-throughput lab-based tomography. We believe that the proposed approach can be extended across X-ray dark-field imaging implementations beyond tomography, spanning fast radiography, directional dark-field imaging, and compatibility with pulsed X-ray sources.

The Sensory Shark: High-quality Morphological, Genomic and Transcriptomic Data for the Small-spotted Catshark Scyliorhinus Canicula Reveal the Molecular Bases of Sensory Organ Evolution in Jawed Vertebrates

Cartilaginous fishes (chondrichthyans: chimeras and elasmobranchs -sharks, skates, and rays) hold a key phylogenetic position to explore the origin and diversifications of jawed vertebrates. Here, we report and integrate reference genomic, transcriptomic, and morphological data in the small-spotted catshark Scyliorhinus canicula to shed light on the evolution of sensory organs. We first characterize general aspects of the catshark genome, confirming the high conservation of genome organization across cartilaginous fishes, and investigate population genomic signatures. Taking advantage of a dense sampling of transcriptomic data, we also identify gene signatures for all major organs, including chondrichthyan specializations, and evaluate expression diversifications between paralogs within major gene families involved in sensory functions. Finally, we combine these data with 3D synchrotron imaging and in situ gene expression analyses to explore chondrichthyan-specific traits and more general evolutionary trends of sensory systems. This approach brings to light, among others, novel markers of the ampullae of Lorenzini electrosensory cells, a duplication hotspot for crystallin genes conserved in jawed vertebrates, and a new metazoan clade of the transient-receptor potential (TRP) family. These resources and results, obtained in an experimentally tractable chondrichthyan model, open new avenues to integrate multiomics analyses for the study of elasmobranchs and jawed vertebrates.

A new dimension in cardiac imaging: Three-dimensional exploration of the atrioventricular conduction axis with hierarchical phase-contrast tomography

Much of our understanding of the atrioventricular conduction axis has been derived from early 20th-century histologic investigations. These studies, although foundational, are constrained by their 2-dimensional representation of complex 3-dimensional anatomy. The variability in the course of the atrioventricular conduction axis, and its relationship to surrounding cardiac structures, necessitates a more advanced imaging approach. Using hierarchical phase-contrast tomography of an autopsied heart specimen with cellular resolution, this review provides a contemporary understanding of the atrioventricular conduction axis. By correlating these findings with 3-dimensional computed tomographic reconstructions in living patients, we offer clinicians the insights needed accurately to predict the location of the atrioventricular conduction axis. This novel approach overcomes the inherent limitations of 2-dimensional histology, enhancing our ability to understand and visualize the intricate relationships of the conduction axis within the heart.

Fabrication and X-ray microtomography of sandwich-structured PEEK implants for skull defect repair

Bone defects pose a significant risk to human health. Medical polyetheretherketone (PEEK) is an excellent implant material for bone defect repair, but it faces the challenge of bone osteoconduction and osseointegration. Osteoconduction describes the process by which bone grows on the surface of the implant, while osseointegration is the stable anchoring of the implant achieved by direct contact between the bone and the implant. Bone defects repair depends on the implant's three-dimensional spatial structure, including pore size, porosity, and interconnections to a great extent. However, it is challenging to fabricate the porous structures to meet specific requirements and to characterize them without causing damage. In this study, we designed and fabricated sandwich-like PEEK implants mimicking the three-layer structures of the skull, whose defects imposes a significant burden on young adulthood and paediatric populations, and performed in-line phase-contrast synchrotron X-ray microtomography to non-destructively investigate the internal porous microstructures. The sandwich-like three-layer microstructure, comprising a dense layer, a loose layer and a dense layer in succession, exhibits structural similarity to that in a natural skull. This work demonstrated the fabrication of the sandwich-like PEEK implant that could potentially enhance osteoconduction and osseointegration. Furthermore, the interior structures and residual porogen sodium chloride particles were observed within the PEEK implant, which cannot be realized by other microscopic methods without destroying the sample. It highlights the advantages and potential of using synchrotron X-ray microtomography to analyze the structure of biomedical materials. This study provides theoretical guidance for the further design and fabrication of PEEK bone repair materials and will advance the clinical application of innovative bioactive bone repair materials.

Deep learning for 3D vascular segmentation in hierarchical phase contrast tomography: a case study on kidney

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 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 a resolution of around 20 μm/voxel and enabling highly detailed localised zooms up to 1-2 μm/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 similarity coefficient (DSC) scores of 0.9523, 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 DSC ranging from 0.82 to 0.88, certain errors persisted. Specifically, large vessels that collapsed due to the lack of hydrostatic 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. Our study establishes the benchmark across various evaluation metrics, for vascular segmentation of HiP-CT imaging data, an imaging technology that has the potential to substantively shift our understanding of human vascular networks.

Micro to macro scale anatomical analysis of the human hippocampal arteries with synchrotron hierarchical phase-contrast tomography

PURPOSE

To date, no non-invasive imaging modality has been employed to profile the structural intricacies of the hippocampal arterial microvasculature in humans. We hypothesised that synchrotron-based imaging of the human hippocampus would enable precise characterisation of the arterial microvasculature.

METHODS

Two preserved human brains from, a 69-year-old female and a 63-year-old male body donors were imaged using hierarchical phase-contrast tomography (HiP-CT) with synchrotron radiation at multiple voxel resolutions from 25.08 μm down to 2.45 μm. Subsequent manual and semi-automatic artery segmentation were performed followed by morphometric analyses. These data were compared to published data from alternative methodologies.

RESULTS

HiP-CT made it possible to segment in context the arterial architecture of the human hippocampus. Our analysis identified anterior, medial and posterior hippocampal arteries arising from the P2 segment of the posterior cerebral artery on the image slices. We mapped arterial branches with external diameters greater than 50 μm in the hippocampal region. We visualised vascular asymmetry and quantified arterial structures with diameters as small as 7 μm.

CONCLUSIONS

Through the application of HiP-CT, we have provided the first imaging visualisation and quantification of the arterial system of the human hippocampus at high resolution in the context of whole brain imaging. Our results bridge the gap between anatomical and histological scales.

Synchrotron X-ray imaging of soft biological tissues - principles, applications and future prospects

Synchrotron-based tomographic phase-contrast X-ray imaging (SRµCT or SRnCT) is a versatile isotropic three-dimensional imaging technique that can be used to study biological samples spanning from single cells to human-sized specimens. SRµCT and SRnCT take advantage of the highly brilliant and coherent X-rays produced by a synchrotron light source. This enables fast data acquisition and enhanced image contrast for soft biological samples owing to the exploitation of phase contrast. In this Review, we provide an overview of the basics behind the technique, discuss its applications for biologists and provide an outlook on the future of this emerging technique for biology. We introduce the latest advances in the field, such as whole human organs imaged with micron resolution, using X-rays as a tool for virtual histology and resolving neuronal connections in the brain.

Development of a nanometre scale X-ray speckle-based CT technique through the 3-D histological assessment of an acute respiratory distress syndrome model

The study of biological soft tissue structures at the micron scale details the function of healthy and pathological tissues, which is vital in the diagnosis and treatment of diseases. Speckle based X-ray phase contrast tomographic scans at a nanometer scale have the potential to thoroughly analyse such tissues in a quantitative and qualitative manner. Diamond light source, the UKs national synchrotron facility developed and refined a 1-D X-ray speckle-based imaging technique, referred to as Fly scan mode. This novel image acquisition technique was used to perform a rapid structural composition scan of rodent lung histology samples. The rodent samples were taken from healthy and Staphylococcus aureus induced acute respiratory distress syndrome models. The analysis and cross comparison of the fly scan method, absorption-based tomography and conventional histopathology H&E staining microscopy are discussed in this paper. This analysis and cross comparison outline the ways the speckle-based technique can be of benefit. These advantages include improved soft tissue contrast, 3-D volumetric rendering, segmentation of specific gross tissue structures, quantitative analysis of gross tissue volume. A further advantage is the analysis of cellular distribution throughout the volumetric rendering of the tissue sample. The study also details the current limitations of this technique and points to ways in which future work on this imaging modality may progress.

Synchrotron-Based Phase-Contrast Micro-CT Combined With Histology to Decipher Differences Between Hereditary and Sporadic Pediatric Pulmonary Veno-Occlusive Disease

Pulmonary veno-occlusive disease (PVOD) is a lethal variant of pulmonary hypertension. The degree of pulmonary arterial involvement varies. Here, we compare two PVOD patients who were transplanted at 8 years of age, whereof one is a homozygous EIF2AK4 mutation carrier. Tissue was imaged with synchrotron-based micro-CT and the results were compared with clinical data and sectioned tissue was analyzed with histology, immunohistochemistry, immunofluorescence, and in situ hybridization. Chest CT of the noncarrier exhibited scattered poorly defined ground-glass opacities and marked septal lines, whereas the mutation carrier showed numerous nodular centrilobular ground-glass opacities and sparse septal lines. The noncarrier developed pulmonary edema with vasodilators and 3D imaging combined with histology showed severe obstruction of interlobular septal veins and medial hypertrophy of pulmonary arteries, but no arterial or arteriolar intimal fibrosis. In contrast, the mutation carrier exhibited only mild intimal fibrosis in interlobular septal veins but severe arterial and arteriolar remodeling, including intimal fibrosis, tortuous course of arterioles, muscularization extending to the alveolar duct level and multiple vascular lumens within the same pulmonary arterial adventitia. Both patients had focally thickened alveolar septa with areas of pulmonary capillary hemangiomatosis (PCH) which colocalized with increased capillary muscularization, tenascin C expression, and deposition, as well as with matrix metalloproteinase-9 (MMP9)/CD45 positive cells. In conclusion, synchrotron-based phase-contrast micro-CT is valuable for understanding vascular remodeling. Significant differences were observed between heritable and sporadic PVOD, which may influence management strategies.

On human nanoscale synaptome: Morphology modeling and storage estimation

One of the key challenges in neuroscience is to generate the human nanoscale connectome which requires comprehensive knowledge of synaptome forming the neural microcircuits. The synaptic architecture determines limits of individual mental capacity and provides the framework for understanding neurologic disorders. Here, I address morphology modeling and storage estimation for the human synaptome at the nanoscale. A synapse is defined as a pair of pairs [(presynaptic_neuron),(presynaptic_axonal_terminal);(postsynaptic_neuron),(postsynaptic_dendritic_terminal)]. Center coordinates, radius, and identifier characterize a dendritic or axonal terminal. A synapse comprises topology with the paired neuron and terminal identifiers, location with terminal coordinates, and geometry with terminal radii. The storage required for the synaptome depends on the number of synapses and storage necessary for a single synapse determined by a synaptic model. I introduce three synaptic models: topologic with topology, point with topology and location, and geometric with topology, location, and geometry. To accommodate for a wide range of variations in the numbers of neurons and synapses reported in the literature, four cases of neurons (30;86;100;138 billion) and three cases of synapses per neuron (1,000;10,000;30,000) are considered with three full and simplified (to reduce storage) synaptic models resulting in total 72 cases of storage estimation. The full(simplified) synaptic model of the entire human brain requires from 0.21(0.14) petabytes (PB) to 28.98(18.63) PB for the topologic model, from 0.57(0.32) PB to 78.66(43.47) PB for the point model, and from 0.69(0.38) PB to 95.22(51.75) PB for the geometric model. The full(simplified) synaptic model of the cortex needs from 86.80(55.80) TB to 2.60(1.67) PB for the topologic model, from 235.60(130.02) TB to 7.07(3.91) PB for the point model, and from 285.20(155.00) TB to 8.56(4.65) PB for the geometric model. The topologic model is sufficient to compute the connectome's topology, but it is still too big to be stored on today's top supercomputers related to neuroscience. Frontier, the world's most powerful supercomputer for 86 billion neurons can handle the nanoscale synaptome in the range of 1,000-10,000 synapses per neuron. To my best knowledge, this is the first big data work attempting to provide storage estimation for the human nanoscale synaptome.

Phase retrieval in propagation-based X-ray imaging beyond the limits of transport of intensity and contrast transfer function approaches

We derive a phase retrieval formula for propagation-based phase contrast X-ray imaging that does not require weakly attenuating objects or short propagation distances. It is directly applicable to both single- and multiple-distance scenarios. We show the validity conditions and study the error of the underlying mutual intensity approximation, which uses the common assumptions of weak phase shift variations and phase-attenuation duality. The approximation generalizes those behind the transport of intensity (TIE) and contrast transfer function (CTF) models, and it approaches them when their respective additional assumptions are satisfied. When they are not, it clearly outperforms them, which we show both theoretically and practically on synthetic and measured data.

A next-generation, histological atlas of the human brain and its application to automated brain MRI segmentation

Magnetic resonance imaging (MRI) is the standard tool to image the human brain in vivo. In this domain, digital brain atlases are essential for subject-specific segmentation of anatomical regions of interest (ROIs) and spatial comparison of neuroanatomy from different subjects in a common coordinate frame. High-resolution, digital atlases derived from histology (e.g., Allen atlas [7], BigBrain [13], Julich [15]), are currently the state of the art and provide exquisite 3D cytoarchitectural maps, but lack probabilistic labels throughout the whole brain. Here we present NextBrain, a next-generation probabilistic atlas of human brain anatomy built from serial 3D histology and corresponding highly granular delineations of five whole brain hemispheres. We developed AI techniques to align and reconstruct ~10,000 histological sections into coherent 3D volumes with joint geometric constraints (no overlap or gaps between sections), as well as to semi-automatically trace the boundaries of 333 distinct anatomical ROIs on all these sections. Comprehensive delineation on multiple cases enabled us to build the first probabilistic histological atlas of the whole human brain. Further, we created a companion Bayesian tool for automated segmentation of the 333 ROIs in any in vivo or ex vivo brain MRI scan using the NextBrain atlas. We showcase two applications of the atlas: automated segmentation of ultra-high-resolution ex vivo MRI and volumetric analysis of Alzheimer's disease and healthy brain ageing based on ~4,000 publicly available in vivo MRI scans. We publicly release: the raw and aligned data (including an online visualisation tool); the probabilistic atlas; the segmentation tool; and ground truth delineations for a 100 μm isotropic ex vivo hemisphere (that we use for quantitative evaluation of our segmentation method in this paper). By enabling researchers worldwide to analyse brain MRI scans at a superior level of granularity without manual effort or highly specific neuroanatomical knowledge, NextBrain holds promise to increase the specificity of MRI findings and ultimately accelerate our quest to understand the human brain in health and disease.

High-angular-sensitivity X-ray phase-contrast microtomography of soft tissue through a two-directional beam-tracking synchrotron set-up

Two-directional beam-tracking (2DBT) is a method for phase-contrast imaging and tomography that uses an intensity modulator to structure the X-ray beam into an array of independent circular beamlets that are resolved by a high-resolution detector. It features isotropic spatial resolution, provides two-dimensional phase sensitivity, and enables the three-dimensional reconstructions of the refractive index decrement, δ, and the attenuation coefficient, μ. In this work, the angular sensitivity and the spatial resolution of 2DBT images in a synchrotron-based implementation is reported. In its best configuration, angular sensitivities of ∼20 nrad and spatial resolution of at least 6.25 µm in phase-contrast images were obtained. Exemplar application to the three-dimensional imaging of soft tissue samples, including a mouse liver and a decellularized porcine dermis, is also demonstrated.

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.

Boundarics in Biomedicine

"Boundarics in Biomedicine" is a cutting-edge interdisciplinary discipline, which is of great significance for understanding the origin of life, the interaction between internal and external environments, and the mechanism of disease occurrence and evolution. Here, the definition of Boundarics in Biomedicine is first described, including its connotation, research object, research method, challenges, and future perspectives. "Boundarics in Biomedicine" is a cutting-edge interdisciplinary discipline involving multiple fields (e.g., bioscience, medicine, chemistry, materials science, and information science) dedicated to investigating and solving key scientific questions in the formation, identification, and evolution of living organism boundaries. Specifically, it encompasses 3 levels: (a) the boundary between the living organism and the external environment, (b) internal boundary within living organism, and (c) the boundary related to disease in living organism. The advancement of research in Boundarics in Biomedicine is of great scientific significance for understanding the origin of life, the interaction between internal and external environments, and the mechanism of disease occurrence and evolution, thus providing novel principles, technologies, and methods for early diagnosis and prevention of major diseases, personalized drug development, and prognosis assessment (Fig. 1).

Molecular connectomics: Placing cells into morphological tissue context

Here we propose "molecular connectomics" to link molecular and morphological cell features in three dimensions across scales, using machine learning and artificial intelligence to reveal emergent properties of complex biological systems.

The role of vasculature and angiogenesis in respiratory diseases

In European countries, nearly 10% of all hospital admissions are related to respiratory diseases, mainly chronic life-threatening diseases such as COPD, pulmonary hypertension, IPF or lung cancer. The contribution of blood vessels and angiogenesis to lung regeneration, remodeling and disease progression has been increasingly appreciated. The vascular supply of the lung shows the peculiarity of dual perfusion of the pulmonary circulation (vasa publica), which maintains a functional blood-gas barrier, and the bronchial circulation (vasa privata), which reveals a profiled capacity for angiogenesis (namely intussusceptive and sprouting angiogenesis) and alveolar-vascular remodeling by the recruitment of endothelial precursor cells. The aim of this review is to outline the importance of vascular remodeling and angiogenesis in a variety of non-neoplastic and neoplastic acute and chronic respiratory diseases such as lung infection, COPD, lung fibrosis, pulmonary hypertension and lung cancer.

High-Resolution Iodine-Enhanced Micro-Computed Tomography of Intact Human Hearts for Detailed Coronary Microvasculature Analyses

Identifying the detailed anatomies of the coronary microvasculature remains an area of research; one needs to develop methods for non-destructive, high-resolution, three-dimensional imaging of these vessels for computational modeling. Currently employed Micro-Computed Tomography (Micro-CT) protocols for vasa vasorum analyses require organ dissection and, in most cases, non-clearable contrast agents. Here, we describe a method developed for a non-destructive, economical means to achieve high-resolution images of the human coronary microvasculature without organ dissection. Formalin-fixed human hearts were cannulated using venogram balloon catheters, which were then fixed into the specimen's aortic root. The canulated hearts, protected by a polyethylene bag, were placed in radiolucent containers filled with insulating polyurethane foam to reduce movement. For vasculature staining, iodine potassium iodide (IKI, Lugol's solution; 6.3% Potassium Iodide, 4.1% Iodide) was injected. Contrast distributions were monitored using a North Star Imaging X3000 micro-CT scanner with low-radiation settings, followed by high-radiation scanning (3600 rad, 60 kV, 900 mA) for the final high-resolution imaging. We successfully imaged four intact human hearts presenting with chronic total coronary occlusions of the right coronary artery. This imaging enabled detailed analyses of the vasa vasorum surrounding stenosed and occluded segments. After imaging, the hearts were cleared of iodine and excess polyurethane foam and returned to their initial formalin-fixed state for indefinite storage. Conclusions: the described methodologies allow for the non-destructive, high-resolution micro-CT imaging of coronary microvasculature in intact human hearts, paving the way for detailed computational 3D microvascular reconstructions with a macrovascular context.

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.

Sharing massive biomedical data at magnitudes lower bandwidth using implicit neural function

Efficient storage and sharing of massive biomedical data would open up their wide accessibility to different institutions and disciplines. However, compressors tailored for natural photos/videos are rapidly limited for biomedical data, while emerging deep learning-based methods demand huge training data and are difficult to generalize. Here, we propose to conduct Biomedical data compRession with Implicit nEural Function (BRIEF) by representing the target data with compact neural networks, which are data specific and thus have no generalization issues. Benefiting from the strong representation capability of implicit neural function, BRIEF achieves 2[Formula: see text]3 orders of magnitude compression on diverse biomedical data at significantly higher fidelity than existing techniques. Besides, BRIEF is of consistent performance across the whole data volume, and supports customized spatially varying fidelity. BRIEF's multifold advantageous features also serve reliable downstream tasks at low bandwidth. Our approach will facilitate low-bandwidth data sharing and promote collaboration and progress in the biomedical field.

Mapping the blood vasculature in an intact human kidney using hierarchical phase-contrast tomography

The architecture of the kidney vasculature is essential for its function. Although structural profiling of the intact rodent kidney vasculature has been performed, it is challenging to map vascular architecture of larger human organs. We hypothesised that hierarchical phase-contrast tomography (HiP-CT) would enable quantitative analysis of the entire human kidney vasculature. Combining label-free HiP-CT imaging of an intact kidney from a 63-year-old male with topology network analysis, we quantitated vasculature architecture in the human kidney down to the scale of arterioles. Although human and rat kidney vascular topologies are comparable, vascular radius decreases at a significantly faster rate in humans as vessels branch from artery towards the cortex. At branching points of large vessels, radii are theoretically optimised to minimise flow resistance, an observation not found for smaller arterioles. Structural differences in the vasculature were found in different spatial zones of the kidney reflecting their unique functional roles. Overall, this represents the first time the entire arterial vasculature of a human kidney has been mapped providing essential inputs for computational models of kidney vascular flow and synthetic vascular architectures, with implications for understanding how the structure of individual blood vessels collectively scales to facilitate organ function.

The sensory shark: high-quality morphological, genomic and transcriptomic data for the small-spotted catshark Scyliorhinus canicula reveal the molecular bases of sensory organ evolution in jawed vertebrates

Cartilaginous fishes (chimaeras and elasmobranchs -sharks, skates and rays) hold a key phylogenetic position to explore the origin and diversifications of jawed vertebrates. Here, we report and integrate reference genomic, transcriptomic and morphological data in the small-spotted catshark Scyliorhinus canicula to shed light on the evolution of sensory organs. We first characterise general aspects of the catshark genome, confirming the high conservation of genome organisation across cartilaginous fishes, and investigate population genomic signatures. Taking advantage of a dense sampling of transcriptomic data, we also identify gene signatures for all major organs, including chondrichthyan specializations, and evaluate expression diversifications between paralogs within major gene families involved in sensory functions. Finally, we combine these data with 3D synchrotron imaging and in situ gene expression analyses to explore chondrichthyan-specific traits and more general evolutionary trends of sensory systems. This approach brings to light, among others, novel markers of the ampullae of Lorenzini electro-sensory cells, a duplication hotspot for crystallin genes conserved in jawed vertebrates, and a new metazoan clade of the Transient-receptor potential (TRP) family. These resources and results, obtained in an experimentally tractable chondrichthyan model, open new avenues to integrate multiomics analyses for the study of elasmobranchs and jawed vertebrates.

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.

Investigating the three-dimensional myocardial micro-architecture in the laminar structure using X-ray phase-contrast microtomography

A comprehensive grasp of the myocardial micro-architecture is essential for understanding diverse heart functions. This study aimed to investigate three-dimensional (3D) cardiomyocyte arrangement in the laminar structure using X-ray phase-contrast microtomography. Using the ID-19 beamline at the European Synchrotron Radiation Facility, we imaged human left ventricular (LV) wall transparietal samples and reconstructed them with an isotropic voxel edge length of 3.5 μm. From the reconstructed volumes, we extracted different regions to analyze the orientation distribution of local cardiomyocyte aggregates, presenting findings in terms of helix and intrusion angles. In regions containing one sheetlet population, we observed cardiomyocyte aggregates running along the local LV wall's radial direction at the border of sheetlets, branching and merging into a complex network around connecting points of different sheetlets, and bending to accommodate vessel passages. In regions with two sheetlet populations, the helix angle of local cardiomyocyte aggregates experiences a nonmonotonic change, and some cardiomyocyte aggregates run along the local radial direction. X-ray phase-contrast microtomography is a valuable technique for investigating the 3D local myocardial architecture at microscopic level. The arrangement of local cardiomyocyte aggregates in the LV wall proves to be both regional and complex, intricately linked to the local laminar structure.

A scalable and modular computational pipeline for axonal connectomics: automated tracing and assembly of axons across serial sections

Progress in histological methods and in microscope technology has enabled dense staining and imaging of axons over large brain volumes, but tracing axons over such volumes requires new computational tools for 3D reconstruction of data acquired from serial sections. We have developed a computational pipeline for automated tracing and volume assembly of densely stained axons imaged over serial sections, which leverages machine learning-based segmentation to enable stitching and alignment with the axon traces themselves. We validated this segmentation-driven approach to volume assembly and alignment of individual axons over centimeter-scale serial sections and show the application of the output traces for analysis of local orientation and for proofreading over aligned volumes. The pipeline is scalable, and combined with recent advances in experimental approaches, should enable new studies of mesoscale connectivity and function over the whole human brain.

Animal models to study cognitive impairment of chronic kidney disease

Mild cognitive impairment (MCI) is common in people with chronic kidney disease (CKD), and its prevalence increases with progressive loss of kidney function. MCI is characterized by a decline in cognitive performance greater than expected for an individual age and education level but with minimal impairment of instrumental activities of daily living. Deterioration can affect one or several cognitive domains (attention, memory, executive functions, language, and perceptual motor or social cognition). Given the increasing prevalence of kidney disease, more and more people with CKD will also develop MCI causing an enormous disease burden for these individuals, their relatives, and society. However, the underlying pathomechanisms are poorly understood, and current therapies mostly aim at supporting patients in their daily lives. This illustrates the urgent need to elucidate the pathogenesis and potential therapeutic targets and test novel therapies in appropriate preclinical models. Here, we will outline the necessary criteria for experimental modeling of cognitive disorders in CKD. We discuss the use of mice, rats, and zebrafish as model systems and present valuable techniques through which kidney function and cognitive impairment can be assessed in this setting. Our objective is to enable researchers to overcome hurdles and accelerate preclinical research aimed at improving the therapy of people with CKD and MCI.

Obliteration of portal venules contributes to portal hypertension in biliary cirrhosis

The effects of the obliteration of portal venules (OPV) in cirrhotic portal hypertension are poorly understood. To investigate its contribution to portal hypertension in biliary cirrhosis and its underlying mechanism, we evaluated OPV using two-dimensional (2D) histopathology in liver explants from patients with biliary atresia (BA, n = 63), primary biliary cholangitis (PBC, n = 18), and hepatitis B-related cirrhosis (Hep-B-cirrhosis, n = 35). Then, three-dimensional (3D) OPV was measured by X-ray phase-contrast CT in two parallel models in rats following bile duct ligation (BDL) or carbon tetrachloride (CCl4) administration, representing biliary cirrhosis and post-necrotic cirrhosis, respectively. The portal pressure was also measured in the two models. Finally, the effects of proliferative bile ducts on OPV were investigated. We found that OPV was significantly more frequent in patients with biliary cirrhosis, including BA (78.57 ± 16.45%) and PBC (60.00 ± 17.15%), than that in Hep-B-cirrhotic patients (29.43 ± 14.94%, p < 0.001). OPV occurred earlier, evidenced by the paired liver biopsy at a Kasai procedure (KP), and was irreversible even after a successful KP in the patients with BA. OPV was also significantly more frequent in the BDL models than in the CCl4 models, as shown by 2D and 3D quantitative analysis. Portal pressure was significantly higher in the BDL model than that in the CCl4 model. With the proliferation of bile ducts, portal venules were compressed and irreversibly occluded, contributing to the earlier and higher portal pressure in biliary cirrhosis. OPV, as a pre-sinusoidal component, plays a key role in the pathogenesis of portal hypertension in biliary cirrhosis. The proliferated bile ducts and ductules gradually take up the 'territory' originally attributed to portal venules and compress the portal venules, which may lead to OPV in biliary cirrhosis. © 2024 The Pathological Society of Great Britain and Ireland.

Analysis of 3D pathology samples using weakly supervised AI

Human tissue, which is inherently three-dimensional (3D), is traditionally examined through standard-of-care histopathology as limited two-dimensional (2D) cross-sections that can insufficiently represent the tissue due to sampling bias. To holistically characterize histomorphology, 3D imaging modalities have been developed, but clinical translation is hampered by complex manual evaluation and lack of computational platforms to distill clinical insights from large, high-resolution datasets. We present TriPath, a deep-learning platform for processing tissue volumes and efficiently predicting clinical outcomes based on 3D morphological features. Recurrence risk-stratification models were trained on prostate cancer specimens imaged with open-top light-sheet microscopy or microcomputed tomography. By comprehensively capturing 3D morphologies, 3D volume-based prognostication achieves superior performance to traditional 2D slice-based approaches, including clinical/histopathological baselines from six certified genitourinary pathologists. Incorporating greater tissue volume improves prognostic performance and mitigates risk prediction variability from sampling bias, further emphasizing the value of capturing larger extents of heterogeneous morphology.

Multiscale and multimodal imaging for three-dimensional vascular and histomorphological organ structure analysis of the pancreas

Exocrine and endocrine pancreas are interconnected anatomically and functionally, with vasculature facilitating bidirectional communication. Our understanding of this network remains limited, largely due to two-dimensional histology and missing combination with three-dimensional imaging. In this study, a multiscale 3D-imaging process was used to analyze a porcine pancreas. Clinical computed tomography, digital volume tomography, micro-computed tomography and Synchrotron-based propagation-based imaging were applied consecutively. Fields of view correlated inversely with attainable resolution from a whole organism level down to capillary structures with a voxel edge length of 2.0 µm. Segmented vascular networks from 3D-imaging data were correlated with tissue sections stained by immunohistochemistry and revealed highly vascularized regions to be intra-islet capillaries of islets of Langerhans. Generated 3D-datasets allowed for three-dimensional qualitative and quantitative organ and vessel structure analysis. Beyond this study, the method shows potential for application across a wide range of patho-morphology analyses and might possibly provide microstructural blueprints for biotissue engineering.

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.

X-Ray-Based 3D Histopathology of the Kidney Using Cryogenic Contrast-Enhanced MicroCT

The kidney's microstructure, which comprises a highly convoluted tubular and vascular network, can only be partially revealed using classical 2D histology. Considering that the kidney's microstructure is closely related to its function and is often affected by pathologies, there is a need for powerful and high-resolution 3D imaging techniques to visualize the microstructure. Here, we present how cryogenic contrast-enhanced microCT (cryo-CECT) allowed 3D visualization of glomeruli, tubuli, and vasculature. By comparing different contrast-enhancing staining agents and freezing protocols, we found that the preferred sample preparation protocol was the combination of staining with 1:2 hafnium(IV)-substituted Wells-Dawson polyoxometalate and freezing by submersion in isopentane at -78°C. This optimized protocol showed to be highly sensitive, allowing to detect small pathology-induced microstructural changes in a mouse model of mild trauma-related acute kidney injury after thorax trauma and hemorrhagic shock. In summary, we demonstrated that cryo-CECT is an effective 3D histopathological tool that allows to enhance our understanding of kidney tissue microstructure and their related function.

Review of Hyperpolarized Pulmonary Functional 129 Xe MR for Long-COVID

The respiratory consequences of acute COVID-19 infection and related symptoms tend to resolve 4 weeks post-infection. However, for some patients, new, recurrent, or persisting symptoms remain beyond the acute phase and persist for months, post-infection. The symptoms that remain have been referred to as long-COVID. A number of research sites employed 129 Xe magnetic resonance imaging (MRI) during the pandemic and evaluated patients post-infection, months after hospitalization or home-based care as a way to better understand the consequences of infection on 129 Xe MR gas-exchange and ventilation imaging. A systematic review and comprehensive search were employed using MEDLINE via PubMed (April 2023) using the National Library of Medicine's Medical Subject Headings and key words: post-COVID-19, MRI, 129 Xe, long-COVID, COVID pneumonia, and post-acute COVID-19 syndrome. Fifteen peer-reviewed manuscripts were identified including four editorials, a single letter to the editor, one review article, and nine original research manuscripts (2020-2023). MRI and MR spectroscopy results are summarized from these prospective, controlled studies, which involved small sample sizes ranging from 9 to 76 participants. Key findings included: 1) 129 Xe MRI gas-exchange and ventilation abnormalities, 3 months post-COVID-19 infection, and 2) a combination of MRI gas-exchange and ventilation abnormalities alongside persistent symptoms in patients hospitalized and not hospitalized for COVID-19, 1-year post-infection. The persistence of respiratory symptoms and 129 Xe MRI abnormalities in the context of normal or nearly normal pulmonary function test results and chest computed tomography (CT) was consistent. Longitudinal improvements were observed in long-term follow-up of long-COVID patients but mean 129 Xe gas-exchange, ventilation heterogeneity values and symptoms remained abnormal, 1-year post-infection. Pulmonary functional MRI using inhaled hyperpolarized 129 Xe gas has played a role in detecting gas-exchange and ventilation abnormalities providing complementary information that may help develop our understanding of the root causes of long-COVID. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 5.