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

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.

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.

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.

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.

Renal-clearable nanoprobes for optical imaging and early diagnosis of diseases

Optical imaging has played an indispensable role in clinical diagnostics and fundamental biomedical research due to its high sensitivity, high spatiotemporal resolution, cost-effectiveness, and easy accessibility. However, the issues of light scattering and low tissue penetration make them effective only for superficial imaging. To overcome these issues, renal-clearable optical nanoprobes have recently emerged, which are activated by abnormal disease-associated biomarkers and initiate a pharmacokinetic switch by undergoing degradation and eventually releasing signal reporters into urine, for simple imaging and sensitive optical in vitro urinalysis. In this review, we focus on the advancements of renal-clearable organic nanoprobes for optical imaging and remote urinalysis. The versatile design strategies of these nanoprobes are discussed along with their sensing mechanisms toward biomolecules of interest as well as their unique biological applications. Finally, challenges and perspectives are discussed to further advance the next-generation renal-clearable nanoprobes for in vivo imaging and in vitro urinalysis.

[Advances in computational quantitative nephropathology]

BACKGROUND

Semiquantitative histological scoring systems are frequently used in nephropathology. In computational nephropathology, the focus is on generating quantitative data from histology (so-called pathomics). Several recent studies have collected such data using next-generation morphometry (NGM) based on segmentations by artificial neural networks and investigated their usability for various clinical or diagnostic purposes.

AIM

To present an overview of the current state of studies regarding renal pathomics and to identify current challenges and potential solutions.

MATERIALS AND METHODS

Due to the literature restriction (maximum of 30 references), studies were selected based on a database search that processed as much data as possible, used innovative methodologies, and/or were ideally multicentric in design.

RESULTS AND DISCUSSION

Pathomics studies in the kidney have impressively demonstrated that morphometric data are useful clinically (for example, for prognosis assessment) and translationally. Further development of NGM requires overcoming some challenges, including better standardization and generation of prospective evidence.

Pulmonary phase contrast CT imaging: a novel setup at the Italian synchrotron for the study of fresh lungs at human scale

High-resolution computed tomography (HRCT) remains the current gold standard for detailed morphological assessment of the human lung, but is intrinsically limited in spatial resolution to about 0.5 mm, because an increase in spatial resolution is accompanied by a significant increase in the required radiation dose.

Propagation-based imaging generates at clinical x-ray dose pulmonary CT images of unprecedented image detail for which the diagnostic value is to be explored. To this end, a dedicated imaging setup was developed that can be assessed via EuroBioImaging. https://bit.ly/491S0FH

Reconstructing microvascular network skeletons from 3D images: What is the ground truth?

Structural changes to microvascular networks are increasingly highlighted as markers of pathogenesis in a wide range of disease, e.g. Alzheimer's disease, vascular dementia and tumour growth. This has motivated the development of dedicated 3D imaging techniques, alongside the creation of computational modelling frameworks capable of using 3D reconstructed networks to simulate functional behaviours such as blood flow or transport processes. Extraction of 3D networks from imaging data broadly consists of two image processing steps: segmentation followed by skeletonisation. Much research effort has been devoted to segmentation field, and there are standard and widely-applied methodologies for creating and assessing gold standards or ground truths produced by manual annotation or automated algorithms. The Skeletonisation field, however, lacks widely applied, simple to compute metrics for the validation or optimisation of the numerous algorithms that exist to extract skeletons from binary images. This is particularly problematic as 3D imaging datasets increase in size and visual inspection becomes an insufficient validation approach. In this work, we first demonstrate the extent of the problem by applying 4 widely-used skeletonisation algorithms to 3 different imaging datasets. In doing so we show significant variability between reconstructed skeletons of the same segmented imaging dataset. Moreover, we show that such a structural variability propagates to simulated metrics such as blood flow. To mitigate this variability we introduce a new, fast and easy to compute super metric that compares the volume, connectivity, medialness, bifurcation point identification and homology of the reconstructed skeletons to the original segmented data. We then show that such a metric can be used to select the best performing skeletonisation algorithm for a given dataset, as well as to optimise its parameters. Finally, we demonstrate that the super metric can also be used to quickly identify how a particular skeletonisation algorithm could be improved, becoming a powerful tool in understanding the complex implication of small structural changes in a network.

Between neurons and networks: investigating mesoscale brain connectivity in neurological and psychiatric disorders

The study of brain connectivity has been a cornerstone in understanding the complexities of neurological and psychiatric disorders. It has provided invaluable insights into the functional architecture of the brain and how it is perturbed in disorders. However, a persistent challenge has been achieving the proper spatial resolution, and developing computational algorithms to address biological questions at the multi-cellular level, a scale often referred to as the mesoscale. Historically, neuroimaging studies of brain connectivity have predominantly focused on the macroscale, providing insights into inter-regional brain connections but often falling short of resolving the intricacies of neural circuitry at the cellular or mesoscale level. This limitation has hindered our ability to fully comprehend the underlying mechanisms of neurological and psychiatric disorders and to develop targeted interventions. In light of this issue, our review manuscript seeks to bridge this critical gap by delving into the domain of mesoscale neuroimaging. We aim to provide a comprehensive overview of conditions affected by aberrant neural connections, image acquisition techniques, feature extraction, and data analysis methods that are specifically tailored to the mesoscale. We further delineate the potential of brain connectivity research to elucidate complex biological questions, with a particular focus on schizophrenia and epilepsy. This review encompasses topics such as dendritic spine quantification, single neuron morphology, and brain region connectivity. We aim to showcase the applicability and significance of mesoscale neuroimaging techniques in the field of neuroscience, highlighting their potential for gaining insights into the complexities of neurological and psychiatric disorders.

Synchrotron Radiation Refraction-Contrast Computed Tomography Based on X-ray Dark-Field Imaging Optics of Pulmonary Malignancy: Comparison with Pathologic Examination

Refraction-contrast computed tomography based on X-ray dark-field imaging (XDFI) using synchrotron radiation (SR) has shown superior resolution compared to conventional absorption-based methods and is often comparable to pathologic examination under light microscopy. This study aimed to investigate the potential of the XDFI technique for clinical application in lung cancer diagnosis. Two types of lung specimens, primary and secondary malignancies, were investigated using an XDFI optic system at beamline BL14B of the High-Energy Accelerator Research Organization Photon Factory, Tsukuba, Japan. Three-dimensional reconstruction and segmentation were performed on each specimen. Refraction-contrast computed tomographic images were compared with those obtained from pathological examinations. Pulmonary microstructures including arterioles, venules, bronchioles, alveolar sacs, and interalveolar septa were identified in SR images. Malignant lesions could be distinguished from the borders of normal structures. The lepidic pattern was defined as the invasive component of the same primary lung adenocarcinoma. The SR images of secondary lung adenocarcinomas of colorectal origin were distinct from those of primary lung adenocarcinomas. Refraction-contrast images based on XDFI optics of lung tissues correlated well with those of pathological examinations under light microscopy. This imaging method may have the potential for use in lung cancer diagnosis without tissue damage. Considerable equipment modifications are crucial before implementing them from the lab to the hospital in the near future.

The role of cardiac pericytes in health and disease: therapeutic targets for myocardial infarction

Millions of cardiomyocytes die immediately after myocardial infarction, regardless of whether the culprit coronary artery undergoes prompt revascularization. Residual ischaemia in the peri-infarct border zone causes further cardiomyocyte damage, resulting in a progressive decline in contractile function. To date, no treatment has succeeded in increasing the vascularization of the infarcted heart. In the past decade, new approaches that can target the heart's highly plastic perivascular niche have been proposed. The perivascular environment is populated by mesenchymal progenitor cells, fibroblasts, myofibroblasts and pericytes, which can together mount a healing response to the ischaemic damage. In the infarcted heart, pericytes have crucial roles in angiogenesis, scar formation and stabilization, and control of the inflammatory response. Persistent ischaemia and accrual of age-related risk factors can lead to pericyte depletion and dysfunction. In this Review, we describe the phenotypic changes that characterize the response of cardiac pericytes to ischaemia and the potential of pericyte-based therapy for restoring the perivascular niche after myocardial infarction. Pericyte-related therapies that can salvage the area at risk of an ischaemic injury include exogenously administered pericytes, pericyte-derived exosomes, pericyte-engineered biomaterials, and pharmacological approaches that can stimulate the differentiation of constitutively resident pericytes towards an arteriogenic phenotype. Promising preclinical results from in vitro and in vivo studies indicate that pericytes have crucial roles in the treatment of coronary artery disease and the prevention of post-ischaemic heart failure.

Image restoration of degraded time-lapse microscopy data mediated by near-infrared imaging

Time-lapse fluorescence microscopy is key to unraveling biological development and function; however, living systems, by their nature, permit only limited interrogation and contain untapped information that can only be captured by more invasive methods. Deep-tissue live imaging presents a particular challenge owing to the spectral range of live-cell imaging probes/fluorescent proteins, which offer only modest optical penetration into scattering tissues. Herein, we employ convolutional neural networks to augment live-imaging data with deep-tissue images taken on fixed samples. We demonstrate that convolutional neural networks may be used to restore deep-tissue contrast in GFP-based time-lapse imaging using paired final-state datasets acquired using near-infrared dyes, an approach termed InfraRed-mediated Image Restoration (IR2). Notably, the networks are remarkably robust over a wide range of developmental times. We employ IR2 to enhance the information content of green fluorescent protein time-lapse images of zebrafish and Drosophila embryo/larval development and demonstrate its quantitative potential in increasing the fidelity of cell tracking/lineaging in developing pescoids. Thus, IR2 is poised to extend live imaging to depths otherwise inaccessible.

Photon-level single-pixel 3D tomography with masked attention network

Tomography plays an important role in characterizing the three-dimensional structure of samples within specialized scenarios. In the paper, a masked attention network is presented to eliminate interference from different layers of the sample, substantially enhancing the resolution for photon-level single-pixel tomographic imaging. The simulation and experimental results have demonstrated that the axial resolution and lateral resolution of the imaging system can be improved by about 3 and 2 times respectively, with a sampling rate of 3.0 %. The scheme is expected to be seamlessly integrated into various tomography systems, which is conducive to promoting the tomographic imaging for biology, medicine, and materials science.

Multi-resolution X-ray phase-contrast and dark-field tomography of human cerebellum with near-field speckles

In this study, we use synchrotron-based multi-modal X-ray tomography to examine human cerebellar tissue in three dimensions at two levels of spatial resolution (2.3 µm and 11.9 µm). We show that speckle-based imaging (SBI) produces results that are comparable to propagation-based imaging (PBI), a well-established phase-sensitive imaging method. The different SBI signals provide complementary information, which improves tissue differentiation. In particular, the dark-field signal aids in distinguishing tissues with similar average electron density but different microstructural variations. The setup's high resolution and the imaging technique's excellent phase sensitivity enabled the identification of different cellular layers and additionally, different cell types within these layers. We also correlated this high-resolution phase-contrast information with measured dark-field signal levels. These findings demonstrate the viability of SBI and the potential benefit of the dark-field modality for virtual histology of brain tissue.

Operational greenhouse-gas emissions of deep learning in digital pathology: a modelling study

BACKGROUND

Deep learning is a promising way to improve health care. Image-processing medical disciplines, such as pathology, are expected to be transformed by deep learning. The first clinically applicable deep-learning diagnostic support tools are already available in cancer pathology, and their number is increasing. However, data on the environmental sustainability of these tools are scarce. We aimed to conduct an environmental-sustainability analysis of a theoretical implementation of deep learning in patient-care pathology.

METHODS

For this modelling study, we first assembled and calculated relevant data and parameters of a digital-pathology workflow. Data were breast and prostate specimens from the university clinic at the Institute of Pathology of the Rheinisch-Westfälische Technische Hochschule Aachen (Aachen, Germany), for which commercially available deep learning was already available. Only specimens collected between Jan 1 and Dec 31, 2019 were used, to omit potential biases due to the COVID-19 pandemic. Our final selection was based on 2 representative weeks outside holidays, covering different types of specimens. To calculate carbon dioxide (CO2) or CO2 equivalent (CO2 eq) emissions of deep learning in pathology, we gathered relevant data for exact numbers and sizes of whole-slide images (WSIs), which were generated by scanning histopathology samples of prostate and breast specimens. We also evaluated different data input scenarios (including all slide tiles, only tiles containing tissue, or only tiles containing regions of interest). To convert estimated energy consumption from kWh to CO2 eq, we used the internet protocol address of the computational server and the Electricity Maps database to obtain information on the sources of the local electricity grid (ie, renewable vs non-renewable), and estimated the number of trees and proportion of the local and world's forests needed to sequester the CO2 eq emissions. We calculated the computational requirements and CO2 eq emissions of 30 deep-learning models that varied in task and size. The first scenario represented the use of one commercially available deep-learning model for one task in one case (1-task), the second scenario considered two deep-learning models for two tasks per case (2-task), the third scenario represented a future, potentially automated workflow that could handle 7 tasks per case (7-task), and the fourth scenario represented the use of a single potential, large, computer-vision model that could conduct multiple tasks (multitask). We also compared the performance (ie, accuracy) and CO2 eq emissions of different deep-learning models for the classification of renal cell carcinoma on WSIs, also from Rheinisch-Westfälische Technische Hochschule Aachen. We also tested other approaches to reducing CO2 eq emissions, including model pruning and an alternative method for histopathology analysis (pathomics).

FINDINGS

The pathology database contained 35 552 specimens (237 179 slides), 6420 of which were prostate specimens (10 115 slides) and 11 801 of which were breast specimens (19 763 slides). We selected and subsequently digitised 140 slides from eight breast-cancer cases and 223 slides from five prostate-cancer cases. Applying large deep-learning models on all WSI tiles of prostate and breast pathology cases would result in yearly CO2 eq emissions of 7·65 metric tons (t; 95% CI 7·62-7·68) with the use of a single deep-learning model per case; yearly CO2 eq emissions were up to 100·56 t (100·21-100·99) with the use of seven deep-learning models per case. CO2 eq emissions for different deep-learning model scenarios, data inputs, and deep-learning model sizes for all slides varied from 3·61 t (3·59-3·63) to 2795·30 t (1177·51-6482·13. For the estimated number of overall pathology cases worldwide, the yearly CO2 eq emissions varied, reaching up to 16 megatons (Mt) of CO2 eq, requiring up to 86 590 km2 (0·22%) of world forest to sequester the CO2 eq emissions. Use of the 7-task scenario and small deep-learning models on slides containing tissue only could substantially reduce CO2 eq emissions worldwide by up to 141 times (0·1 Mt, 95% CI 0·1-0·1). Considering the local environment in Aachen, Germany, the maximum CO2 eq emission from the use of deep learning in digital pathology only would require 32·8% (95% CI 13·8-76·6) of the local forest to sequester the CO2 eq emissions. A single pathomics run on a tissue could provide information that was comparable to or even better than the output of multitask deep-learning models, but with 147 times reduced CO2 eq emissions.

INTERPRETATION

Our findings suggest that widespread use of deep learning in pathology might have considerable global-warming potential. The medical community, policy decision makers, and the public should be aware of this potential and encourage the use of CO2 eq emissions reduction strategies where possible.

FUNDING

German Research Foundation, European Research Council, German Federal Ministry of Education and Research, Health, Economic Affairs and Climate Action, and the Innovation Fund of the Federal Joint Committee.

Imaging and spatial omics of kidney injury: significance, challenges, advances and perspectives

The kidneys are susceptible to a range of insults that can cause damage to them. Early diagnosis, timely prevention, and proper treatment are crucial for improving the outcome of kidney injury. However, the complexity of renal structure and function makes it difficult to reach the demand of early detection and comprehensive evaluation of kidney injury. No successful drug therapy caused by the elaborate pathogenesis mechanism network of kidney injury calls for a systematical interpretation in mechanism researches. Recent advances in renal imaging and omics studies have provided novel views and deeper insights into kidney injury, but also raise challenges in reaching a comprehensive cellular and molecular atlas of kidney injury. Progresses in imaging and omics of kidney injury are being made in various directions, with the initiative of construction a high-resolution structural atlas of kidney, dynamic and non-invasive evaluation of renal function, and systematic establishment of spatially resolved molecular atlas by transcriptomics and metabolomics. With the limitations of a single modality, novel multimodal integration technologies of imaging and omics are being attempted to achieve a systematic description of nephropathy mechanisms. Further extensive efforts in renal multimodal imaging and omics studies are extremely required to deepen our understanding on kidney injury in the context of diagnostic, mechanistic and therapeutic perspectives.

High-Resolution Phase-Contrast Tomography on Human Collagenous Tissues: A Comprehensive Review

Phase-contrast X-ray imaging is becoming increasingly considered since its first applications, which occurred almost 30 years ago. Particular emphasis was placed on studies that use this technique to investigate soft tissues, which cannot otherwise be investigated at a high resolution and in a three-dimensional manner, using conventional absorption-based settings. Indeed, its consistency and discrimination power in low absorbing samples, unified to being a not destructive analysis, are pushing interests on its utilization from researchers of different specializations, from botany, through zoology, to human physio-pathology research. In this regard, a challenging method for 3D imaging and quantitative analysis of collagenous tissues has spread in recent years: it is based on the unique characteristics of synchrotron radiation phase-contrast microTomography (PhC-microCT). In this review, the focus has been placed on the research based on the exploitation of synchrotron PhC-microCT for the investigation of collagenous tissue physio-pathologies from solely human samples. Collagen tissues' elasto-mechanic role bonds it to the morphology of the site it is extracted from, which could weaken the results coming from animal experimentations. Encouraging outcomes proved this technique to be suitable to access and quantify human collagenous tissues and persuaded different researchers to approach it. A brief mention was also dedicated to the results obtained on collagenous tissues using new and promising high-resolution phase-contrast tomographic laboratory-based setups, which will certainly represent the real step forward in the diffusion of this relatively young imaging technique.

Feasibility and safety of synchrotron-based X-ray phase contrast imaging as a technique complementary to histopathology analysis

X-ray phase contrast imaging (X-PCI) is a powerful technique for high-resolution, three-dimensional imaging of soft tissue samples in a non-destructive manner. In this technical report, we assess the quality of standard histopathological techniques performed on formalin-fixed, paraffin-embedded (FFPE) human tissue samples that have been irradiated with different doses of X-rays in the context of an X-PCI experiment. The data from this study demonstrate that routine histochemical and immunohistochemical staining quality as well as DNA and RNA analyses are not affected by previous X-PCI on human FFPE samples. From these data we conclude it is feasible and acceptable to perform X-PCI on FFPE human biopsies.

Virtual histology of Alzheimer's disease: Biometal entrapment within amyloid-β plaques allows for detection via X-ray phase-contrast imaging

Amyloid-β (Aβ) plaques from Alzheimer's Disease (AD) can be visualized ex vivo in label-free brain samples using synchrotron X-ray phase-contrast tomography (XPCT). However, for XPCT to be useful as a screening method for amyloid pathology, it is essential to understand which factors drive the detection of Aβ plaques. The current study was designed to test the hypothesis that Aβ-related contrast in XPCT could be caused by Aβ fibrils and/or by metals trapped in the plaques. Fibrillar and elemental compositions of Aβ plaques were probed in brain samples from different types of AD patients and AD models to establish a relationship between XPCT contrast and Aβ plaque characteristics. XPCT, micro-Fourier-Transform Infrared spectroscopy and micro-X-Ray Fluorescence spectroscopy were conducted on human samples (one genetic and one sporadic case) and on four transgenic rodent strains (mouse: APPPS1, ArcAβ, J20; rat: TgF344). Aβ plaques from the genetic AD patient were visible using XPCT, and had higher β-sheet content and higher metal levels than those from the sporadic AD patient, which remained undetected by XPCT. Aβ plaques in J20 mice and TgF344 rats appeared hyperdense on XPCT images, while they were hypodense with a hyperdense core in the case of APPPS1 and ArcAβ mice. In all four transgenic strains, β-sheet content was similar, while metal levels were highly variable: J20 (zinc and iron) and TgF344 (copper) strains showed greater metal accumulation than APPPS1 and ArcAβ mice. Hence, a hyperdense contrast formation of Aβ plaques in XPCT images was associated with biometal entrapment within plaques. STATEMENT OF SIGNIFICANCE: The role of metals in Alzheimer's disease (AD) has been a subject of continuous interest. It was already known that amyloid-β plaques (Aβ), the earliest hallmark of AD, tend to trap endogenous biometals like zinc, iron and copper. Here we show that this metal accumulation is the main reason why Aβ plaques are detected with a new technique called X-ray phase contrast tomography (XPCT). XPCT enables to map the distribution of Aβ plaques in the whole excised brain without labeling. In this work we describe a unique collection of four transgenic models of AD, together with a human sporadic and a rare genetic case of AD, thus exploring the full spectrum of amyloid contrast in XPCT.

Distribution of corpora amylacea in the human midbrain: using synchrotron radiation phase-contrast microtomography, high-field magnetic resonance imaging, and histology

Corpora amylacea (CA) are polyglucosan aggregated granules that accumulate in the human body throughout aging. In the cerebrum, CA have been found in proximity to ventricular walls, pial surfaces, and blood vessels. However, studies showing their three-dimensional spatial distribution are sparse. In this study, volumetric images of four human brain stems were obtained with MRI and phase-contrast X-ray microtomography, followed up by Periodic acid Schiff stain for validation. CA appeared as hyperintense spheroid structures with diameters up to 30 μm. An automatic pipeline was developed to segment the CA, and the spatial distribution of over 200,000 individual corpora amylacea could be investigated. A threefold-or higher-density of CA was detected in the dorsomedial column of the periaqueductal gray (860-4,200 CA count/mm3) than in the superior colliculus (150-340 CA count/mm3). We estimated that about 2% of the CA were located in the immediate vicinity of the vessels or in the peri-vascular space. While CA in the ependymal lining of the cerebral aqueduct was rare, the sub-pial tissue of the anterior and posterior midbrain contained several CA. In the sample with the highest CA density, quantitative maps obtained with MRI revealed high R2* values and a diamagnetic shift in a region which spatially coincided with the CA dense region.

Multielement Z-tag imaging by X-ray fluorescence microscopy for next-generation multiplex imaging

Rapid, highly multiplexed, nondestructive imaging that spans the molecular to the supra-cellular scale would be a powerful tool for tissue analysis. However, the physical constraints of established imaging methods limit the simultaneous improvement of these parameters. Whole-organism to atomic-level imaging is possible with tissue-penetrant, picometer-wavelength X-rays. To enable highly multiplexed X-ray imaging, we developed multielement Z-tag X-ray fluorescence (MEZ-XRF) that can operate at kHz speeds when combined with signal amplification by exchange reaction (SABER)-amplified Z-tag reagents. We demonstrated parallel imaging of 20 Z-tag or SABER Z-tag reagents at subcellular resolution in cell lines and multiple human tissues. We benchmarked MEZ-XRF against imaging mass cytometry and demonstrated the nondestructive multiscale repeat imaging capabilities of MEZ-XRF with rapid tissue overview scans, followed by slower, more sensitive imaging of low-abundance markers such as immune checkpoint proteins. The unique multiscale, nondestructive nature of MEZ-XRF, combined with SABER Z-tags for high sensitivity or enhanced speed, enables highly multiplexed bioimaging across biological scales.

Neodymium acetate as a contrast agent for X-ray phase-contrast tomography

Purpose

X-ray phase-contrast tomography (XPCT) is a non-destructive, three-dimensional imaging modality that provides higher contrast in soft tissue than absorption-based CT and allows one to cover the cytoarchitecture from the centi- and millimeter scale down to the nanoscale. To further increase contrast and resolution of XPCT, for example, in view of addressing connectivity issues in the central nervous system (CNS), metal staining is indispensable. However, currently used protocols, for example, based on osmium and/or uranium are less suited for XPCT, due to an excessive β / δ -ratio. In this work, we explore the suitability of different staining agents for XPCT. Particularly, neodymium(III)-acetate (NdAc), which has recently been proposed as a non-toxic, non-radioactive easy to use alternative contrast agent for uranyl acetate (UAc) in electron microscopy, is investigated. Due to its vertical proximity to UAc in the periodic table, similar chemical but better suited optical properties for phase contrast can be expected.

Approach

Differently stained whole eye samples of wild type mouse and tissues of the CNS are embedded into EPON epoxy resin and scanned using synchrotron as well as with laboratory radiation. Phase retrieval is performed on the projection images, followed by tomographic reconstruction, which enables a quantitative analysis based on the reconstructed electron densities. Segmentation techniques and rendering software is used to visualize structures of interest in the sample.

Results

We show that staining neuronal samples with NdAc enhances contrast, in particular for laboratory scans, allowing high-resolution imaging of biological soft tissue in-house. For the example of murine retina, specifically rods and cones as well as the sclera and the Ganglion cell layer seem to be targeted by the stain. A comparison of electron density by the evaluation of histograms allowed to determine quantitative measures to describe the difference between the examined stains.

Conclusion

The results suggest NdAc to be an effective stain for XPCT, with a preferential binding to anionic groups, such as phosphate and carboxyl groups at cell surfaces, targeting certain layers of the retina with a stronger selectivity compared to other staining agents. Due to the advantageous X-ray optical properties, the stain seems particularly well-suited for phase contrast, with a comparably small number density and an overall superior image quality at laboratory sources.

Multiscale X-ray phase-contrast tomography: From breast CT to micro-CT for virtual histology

Phase-contrast imaging techniques address the issue of poor soft-tissue contrast encountered in traditional X-ray imaging. This can be accomplished with the propagation-based phase-contrast technique by employing a coherent photon beam, which is available at synchrotron facilities, as well as long sample-to-detector distances. This study demonstrates the optimization of propagation-based phase-contrast computed tomography (CT) techniques for multiscale X-ray imaging of the breast at the Elettra synchrotron facility (Trieste, Italy). Two whole breast mastectomy samples were acquired with propagation-based breast-CT using a monochromatic synchrotron beam at a pixel size of 60 µm. Paraffin-embedded blocks sampled from the same tissues were scanned with propagation-based micro-CT imaging using a polychromatic synchrotron beam at a pixel size of 4 µm. Images of both methodologies and of the same sample were spatially registered. The resulting images showed the transition from whole breast imaging with propagation-based breast-CT methodology to virtual histology with propagation-based micro-CT imaging of the same sample. Additionally, conventional histological images were matched to virtual histology images. Phase-contrast images offer a high resolution with low noise, which allows for a highly precise match between virtual and conventional histology. Furthermore, those techniques allow a clear discernment of breast structures, lesions, and microcalcifications, being a promising clinically-compatible tool for breast imaging in a multiscale approach, to either assist in the detection of cancer in full volume breast samples or to complement structure identification in paraffin-embedded breast tissue samples.

3D-imaging and quantitative assessment for size-related penetration of HfO2 nanoparticles in breast cancer tumor by synchrotron radiation microcomputed tomography

The development of quantitative analytical methods to assess the heterogeneous distribution and penetration of nanodrugs in solid tumors is of great importance for anticancer nanomedicine. Herein, Expectation-Maximization (EM) iterate algorithm and threshold segmentation methods were used to visualize and quantify the spatial distribution patterns, penetration depth and diffusion features of two-sized hafnium oxide nanoparticles (s-HfO₂ NPs in 2 nm and l-HfO₂ NPs in 50 nm sizes) in mouse models of breast cancer using synchrotron radiation micro-computed tomography (SR-μCT) imaging technique. The three-dimensional (3D) SR-μCT images were reconstructed based on the EM iterate algorithm thus clearly displayed the size-related penetration and distribution within the tumors after intra-tumoral injection of HfO₂ NPs and X-ray irradiation treatment. The obtained 3D animations clearly show that a considerable amount of s-HfO₂ and l-HfO₂ NPs diffused into tumor tissues at 2 h post-injection and displayed the obvious increase in the tumor penetration and distribution area within the tumors at day 7 after combination with low-dose X-ray irradiation treatment. A thresholding segmentation for 3D SR-μCT image was developed to assess the penetration depth and quantity of HfO₂ NPs along the injection sites in tumors. The developed 3D-imaging techniques revealed that the s-HfO₂ NPs presented more homogeneous distribution pattern, diffused more quickly and penetrated more deeply within tumor tissues than the l-HfO₂ NPs did. Whereas, the low-dose X-ray irradiation treatment greatly enhanced the wide distribution and deep penetration of both s-HfO₂ and l-HfO₂ NPs. This developed method may provide quantitative distribution and penetration information for the X-ray sensitive high-Z metal nanodrugs in the cancer imaging and therapy.

DiI-CT-A bimodal neural tracer for X-ray and fluorescence imaging

Here, we present an X-ray-visible neural tracer, referred to as DiI-CT, which is based on the well-established lipophilic indocarbocyanine dye DiI, to which we conjugated two iodine atoms. The tracer is visible with microfocus computed tomography (microCT) imaging and shares the excellent fluorescent tracing properties of DiI. We document the discovery potential of DiI-CT by analyzing the vibrissa follicle-sinus complex, a structure where visual access is poor and 3D tissue structure matters and reveal innervation patterns of the intact follicle in unprecedented detail. In the brain, DiI-CT tracing holds promise for verification evaluation of indirect connectivity measures, such as diffusion tensor imaging. We conclude that the bimodal dye DiI-CT opens new avenues for neuroanatomy.

Towards virtual histology with X-ray grating interferometry

Breast cancer is the most common type of cancer worldwide. Diagnosing breast cancer relies on clinical examination, imaging and biopsy. A core-needle biopsy enables a morphological and biochemical characterization of the cancer and is considered the gold standard for breast cancer diagnosis. A histopathological examination uses high-resolution microscopes with outstanding contrast in the 2D plane, but the spatial resolution in the third, Z-direction, is reduced. In the present paper, we propose two high-resolution table-top systems for phase-contrast X-ray tomography of soft-tissue samples. The first system implements a classical Talbot-Lau interferometer and allows to perform ex-vivo imaging of human breast samples with a voxel size of 5.57 μm. The second system with a comparable voxel size relies on a Sigray MAAST X-ray source with structured anode. For the first time, we demonstrate the applicability of the latter to perform X-ray imaging of human breast specimens with ductal carcinoma in-situ. We assessed image quality of both setups and compared it to histology. We showed that both setups made it possible to target internal features of breast specimens with better resolution and contrast than previously achieved, demonstrating that grating-based phase-contrast X-ray CT could be a complementary tool for clinical histopathology.

Novel setup for rapid phase contrast CT imaging of heavy and bulky specimens

This work introduces a novel setup for computed tomography of heavy and bulky specimens at the SYRMEP beamline of the Italian synchrotron Elettra. All the key features of the setup are described and the first application to off-center computed tomography scanning of a human chest phantom (approximately 45 kg) as well as the first results for vertical helical acquisitions are discussed.

Flexible design in the stomatopod dactyl club

The stomatopod is a fascinating animal that uses its weaponized appendage dactyl clubs for breaking mollusc shells. Dactyl clubs are a well studied example of biomineralized hierarchical structures. Most research has focused on the regions close to the action, namely the impact region and surface composed of chitin and apatite crystallites. Further away from the site of impact, the club has lower mineralization and more amorphous phases; these areas have not been as actively studied as their highly mineralized counterparts. This work focuses on the side of the club, in what is known as the periodic and striated regions. A combination of laboratory micro-computed tomography, synchrotron X-ray diffraction mapping and synchrotron X-ray fluorescence mapping has shown that the mineral in this region undergoes the transition from an amorphous to a crystalline phase in some, but not all, clubs. This means that this side region can be mineralized by either an amorphous phase, calcite crystallites or a mixture of both. It was found that when larger calcite crystallites form, they are organized (textured) with respect to the chitin present in this biocomposite. This suggests that chitin may serve as a template for crystallization when the side of the club is fully mineralized. Further, calcite crystallites were found to form as early as 1 week after moulting of the club. This suggests that the side of the club is designed with a significant safety margin that allows for a variety of phases, i.e. the club can function independently of whether the side region has a crystalline or amorphous mineral phase.

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.

Micro to macro scale analysis of the intact human renal arterial tree with Synchrotron Tomography

Background

The kidney vasculature is exquisitely structured to orchestrate renal function. Structural profiling of the vasculature in intact rodent kidneys, has provided insights into renal haemodynamics and oxygenation, but has never been extended to the human kidney beyond a few vascular generations. We hypothesised that synchrotron-based imaging of a human kidney would enable assessment of vasculature across the whole organ.

Methods

An intact kidney from a 63-year-old male was scanned using hierarchical phase-contrast tomography (HiP-CT), followed by semi-automated vessel segmentation and quantitative analysis. These data were compared to published micro-CT data of whole rat kidney.

Results

The intact human kidney vascular network was imaged with HiP-CT at 25 μm voxels, representing a 20-fold increase in resolution compared to clinical CT scanners. Our comparative quantitative analysis revealed the number of vessel generations, vascular asymmetry and a structural organisation optimised for minimal resistance to flow, are conserved between species, whereas the normalised radii are not. We further demonstrate regional heterogeneity in vessel geometry between renal cortex, medulla, and hilum, showing how the distance between vessels provides a structural basis for renal oxygenation and hypoxia.

Conclusions

Through the application of HiP-CT, we have provided the first quantification of the human renal arterial network, with a resolution comparable to that of light microscopy yet at a scale several orders of magnitude larger than that of a renal punch biopsy. Our findings bridge anatomical scales, profiling blood vessels across the intact human kidney, with implications for renal physiology, biophysical modelling, and tissue engineering.

Enhanced contrast synchrotron X-ray microtomography for describing skeleton-associated soft tissue defects in zebrafish mutants

Detailed histological analyses are desirable for zebrafish mutants that are models for human skeletal diseases, but traditional histological techniques are limited to two-dimensional thin sections with orientations highly dependent on careful sample preparation. On the other hand, techniques that provide three-dimensional (3D) datasets including µCT scanning are typically limited to visualizing the bony skeleton and lack histological resolution. We combined diffusible iodine-based contrast enhancement (DICE) and propagation phase-contrast synchrotron radiation micro-computed tomography (PPC-SRµCT) to image late larval and juvenile zebrafish, obtaining high-quality 3D virtual histology datasets of the mineralized skeleton and surrounding soft tissues. To demonstrate this technique, we used virtual histological thin sections and 3D segmentation to qualitatively and quantitatively compare wild-type zebrafish and nkx3.2 -/- mutants to characterize novel soft-tissue phenotypes in the muscles and tendons of the jaw and ligaments of the Weberian apparatus, as well as the sinus perilymphaticus associated with the inner ear. We could observe disrupted fiber organization and tendons of the adductor mandibulae and protractor hyoideus muscles associated with the jaws, and show that despite this, the overall muscle volumes appeared unaffected. Ligaments associated with the malformed Weberian ossicles were mostly absent in nkx3.2 -/- mutants, and the sinus perilymphaticus was severely constricted or absent as a result of the fused exoccipital and basioccipital elements. These soft-tissue phenotypes have implications for the physiology of nkx3.2 -/- zebrafish, and demonstrate the promise of DICE-PPC-SRµCT for histopathological investigations of bone-associated soft tissues in small-fish skeletal disease models and developmental studies more broadly.

Tissue clearing and 3D reconstruction of digitized, serially sectioned slides provide novel insights into pancreatic cancer

Pancreatic cancer is currently the third leading cause of cancer death in the United States. The clinical hallmarks of this disease include abdominal pain that radiates to the back, the presence of a hypoenhancing intrapancreatic lesion on imaging, and widespread liver metastases. Technologies such as tissue clearing and three-dimensional (3D) reconstruction of digitized serially sectioned hematoxylin and eosin-stained slides can be used to visualize large (up to 2- to 3-centimeter cube) tissues at cellular resolution. When applied to human pancreatic cancers, these 3D visualization techniques have provided novel insights into the basis of a number of the clinical characteristics of this disease. Here, we describe the clinical features of pancreatic cancer, review techniques for clearing and the 3D reconstruction of digitized microscope slides, and provide examples that illustrate how 3D visualization of human pancreatic cancer at the microscopic level has revealed features not apparent in 2D microscopy and, in so doing, has closed the gap between bench and bedside. Compared with animal models and 2D microscopy, studies of human tissues in 3D can reveal the difference between what can happen and what does happen in human cancers.

Morphological and Chemical Investigation of Ovarian Structures in a Bovine Model by Contrast-Enhanced X-ray Imaging and Microscopy

An improved understanding of an ovary's structures is highly desirable to support advances in folliculogenesis knowledge and reproductive medicine, with particular attention to fertility preservation options for prepubertal girls with malignant tumors. Although currently the golden standard for structural analysis is provided by combining histological sections, staining, and visible 2D microscopic inspection, synchrotron radiation phase-contrast microtomography is becoming a new challenge for three-dimensional studies at micrometric resolution. To this aim, the proper use of contrast agents can improve the visualization of internal structures in ovary tissues, which normally present a low radiopacity. In this study, we report a comparison of four staining protocols, based on iodine or tungsten containing agents, applied to bovine ovarian tissues fixed in Bouin's solution. The microtomography (microCT) analyses at two synchrotron facilities under different set-ups were performed at different energies in order to maximize the image contrast. While tungsten-based agents allow large structures to be well identified, Iodine ones better highlight smaller features, especially when acquired above the K-edge energy of the specific metal. Further scans performed at lower energy where the setup was optimized for overall quality and sensitivity from phase-contrast still provided highly resolved visualization of follicular and intrafollicular structures at different maturation stages, independent of the staining protocol. The analyses were complemented by X-ray Fluorescence mapping on 2D sections, showing that the tungsten-based agent has a higher penetration in this type of tissues.

Image quality and scan time optimisation for in situ phase contrast x-ray tomography of the intervertebral disc

In-line phase contrast synchrotron tomography combined with in situ mechanical loading enables the characterisation of soft tissue micromechanics via digital volume correlation (DVC) within whole organs. Optimising scan time is important for reducing radiation dose from multiple scans and to limit sample movement during acquisition. Also, although contrasted edges provided by in-line phase contrast tomography of soft tissues are useful for DVC, the effect of phase contrast imaging on its accuracy has yet to be investigated. Due to limited time at synchrotron facilities, scan parameters are often decided during imaging and their effect on DVC accuracy is not fully understood. Here, we used previously published data of intervertebral disc phase contrast tomography to evaluate the influence of i) fibrous image texture, ii) number of projections, iii) tomographic reconstruction method, and iv) phase contrast propagation distance on DVC results. A greater understanding of how image texture influences optimal DVC tracking was obtained by visualising objective function mapping, enabling tracking inaccuracies to be identified. When reducing the number of projections, DVC was minimally affected by image high frequency noise but with a compromise in accuracy. Iterative reconstruction methods improved image signal-to-noise and consequently significantly lowered DVC displacement uncertainty. Propagation distance was shown to affect DVC accuracy. Consistent DVC results were achieved within a propagation distance range which provided contrast to the smallest scale features, where; too short a distance provided insufficient features to track, whereas too long led to edge effect inconsistencies, particularly at greater deformations. Although limited to a single sample type and image setup, this study provides general guidelines for future investigations when optimising image quality and scan times for in situ phase contrast x-ray tomography of fibrous connective tissues.

Comment on: Intrapulmonary shunt and alveolar dead space in a cohort of patients with acute COVID-19 pneumonitis and early recovery

With the greatest interest we read the paper by Harbut et al. [1] describing the role of intrapulmonary shunting and alveolar dead space in patients with acute COVID-19 pneumonitis. We are grateful for them sharing their valuable functional blood and alveolar gas exchange data, pointing out a significant alveolar dead space of nearly 30% in recovered COVID-19 patients, suggesting a persistent pulmonary vascular pathology. Although COVID-19 related hypoxaemia is characterised by preserved oxygen saturation, a ventilation–perfusion mismatch and increased alveolar ventilation/perfusion ratio heterogeneity, the underlying morphological evidence of this physiological enigma has not been fully understood.

A compelling explanation for mosaic-like micro-ischaemia in the severe pathology of COVID-19 pneumonitis, which reflects the vasculopathy affecting the secondary lobule and the interlobular septae http://bit.ly/3GwMkII

The Extremely Brilliant Source storage ring of the European Synchrotron Radiation Facility

The Extremely Brilliant Source (EBS) is the experimental implementation of the novel Hybrid Multi Bend Achromat (HMBA) storage ring magnetic lattice concept, which has been realised at European Synchrotron Radiation Facility. We present its successful commissioning and first operation. We highlight the strengths of the HMBA design and compare them to the previous designs, on which most operational synchrotron X-ray sources are based. We report on the EBS storage ring's significantly improved horizontal electron beam emittance and other key beam parameters. EBS extends the reach of synchrotron X-ray science confirming the HMBA concept for future facility upgrades and new constructions.

A tomographic microscopy-compatible Langendorff system for the dynamic structural characterization of the cardiac cycle

Introduction

Cardiac architecture has been extensively investigated ex vivo using a broad spectrum of imaging techniques. Nevertheless, the heart is a dynamic system and the structural mechanisms governing the cardiac cycle can only be unveiled when investigating it as such.

Methods

This work presents the customization of an isolated, perfused heart system compatible with synchrotron-based X-ray phase contrast imaging (X-PCI).

Results

Thanks to the capabilities of the developed setup, it was possible to visualize a beating isolated, perfused rat heart for the very first time in 4D at an unprecedented 2.75 μm pixel size (10.6 μm spatial resolution), and 1 ms temporal resolution.

Discussion

The customized setup allows high-spatial resolution studies of heart architecture along the cardiac cycle and has thus the potential to serve as a tool for the characterization of the structural dynamics of the heart, including the effects of drugs and other substances able to modify the cardiac cycle.

Imaging in translational cancer research

This review is aimed at presenting some of the recent developments in translational cancer imaging research, with a focus on novel, recently established, or soon to be established cross-sectional imaging techniques for computed tomography (CT), magnetic resonance imaging (MRI), and positron-emission tomography (PET) imaging, including computational investigations based on machine-learning techniques.

A high-resolution 3D atlas of the spectrum of tuberculous and COVID-19 lung lesions

Our current understanding of the spectrum of TB and COVID-19 lesions in the human lung is limited by a reliance on low-resolution imaging platforms that cannot provide accurate 3D representations of lesion types within the context of the whole lung. To characterize TB and COVID-19 lesions in 3D, we applied micro/nanocomputed tomography to surgically resected, postmortem, and paraffin-embedded human lung tissue. We define a spectrum of TB pathologies, including cavitary lesions, calcium deposits outside and inside necrotic granulomas and mycetomas, and vascular rearrangement. We identified an unusual spatial arrangement of vasculature within an entire COVID-19 lobe, and 3D segmentation of blood vessels revealed microangiopathy associated with hemorrhage. Notably, segmentation of pathological anomalies reveals hidden pathological structures that might otherwise be disregarded, demonstrating a powerful method to visualize pathologies in 3D in TB lung tissue and whole COVID-19 lobes. These findings provide unexpected new insight into the spatial organization of the spectrum of TB and COVID-19 lesions within the framework of the entire lung.