Ultra-high-resolution propagation-based synchrotron phase-contrast CT is an emerging technique for lung imaging. However, its feasibility and diagnostic potential at radiation doses comparable to those used in standard clinical procedures has yet to be established. This study aims to evaluate the performance of phase-contrast CT in comparison with state-of-the-art high-resolution multislice CT and bronchoscopy, and to validate its diagnostic accuracy histologically using porcine and, for the first time, human lung specimens. Phase-contrast CT experiments were conducted at the Italian synchrotron using lung specimens mounted in a custom-made anthropomorphic chest phantom. Imaging utilized two photon-counting detectors under various acquisition settings, followed by artificial intelligence-based denoising. Sequential imaging by phase-contrast CT, multislice CT, and bronchoscopy was performed prior to formaldehyde vapor fixation and histological dissection. Image quality was assessed quantitatively (contrast-to-noise ratio, edge sharpness, power spectra) and qualitatively via radiological scoring across 14 criteria. Phase-contrast CT achieved effective pixel sizes of 0.067 mm (Hydra detector) and 0.038 mm (LAMBDA detector), at radiation doses near full-dose multislice CT (≈ 12 mGy). Denoising improved contrast without major loss of edge sharpness. Radiological scoring showed phase-contrast CT outperformed multislice CT in visualizing peripheral airways and fine parenchymal structures. Histological validation confirmed imaging accuracy. Limitations from source spot size (≈ 200 μm) were noted but did not prevent significant diagnostic improvements. Phase-contrast CT, combined with artificial intelligence-based denoising, offers detailed, non-invasive imaging of lung microstructures at clinically relevant radiation doses. It complements multislice CT, holds potential for clinical adoption in advanced pulmonary diagnostics, and may reduce reliance on invasive biopsies.

PURPOSE:Free-space phase contrast propagation coupled with a photon-counting detector enables CT imaging with improved contrast in soft tissues at lower radiation dose. In addition, photon-counting detectors enable inherent spectral separation that can be used to capture tissue contrast at different energy levels. The objective of this study was to (i) develop a novel split-beam method for spectral synchrotron-based imaging considering limitations of photon-counting technology and clinical requirements, and (ii) propose a redefined mathematical model to calculate contrast-to-noise ratio in spectral imaging applications. METHODS:Our novel approach was applied in a CT imaging setup using a custom-made breast phantom with tissue-equivalent inserts and compared to the more common setup utilizing monochromatic beams. To complement the traditional contrast-to-noise ratio metric, a new mathematical framework for spectral contrast-to-noise ratio was introduced as a composite metric that integrates the signal-to-noise performance across spectral channels. RESULTS:The results show that the split-beam method proposed in this study obtains a comparable spectral contrast-to-noise ratio at the same radiation dose. Relative spectral contrast-to-noise differences were 0.12 (polyethylene), 1.92 (polyamide), 1.19 (polymethylmethacrylate), -0.29 (polyoxymethylene), and -0.17 (polytetrafluoroethylene) when comparing spectral imaging with two monochromatic beams at energies of 24 keV and 38 keV against the split-beam method. CONCLUSION:The potential advantages of the split-beam method for spectral CT imaging are numerous - it avoids non-rigid deformations, is fast to implement, and enables optimization in the post-processing step. The model for contrast-to-noise ratio redefined in this study applies to new generation spectral CT scanners beyond synchrotron setups.

Accurate diagnosis and characterization of lung disease increasingly rely on advanced imaging modalities capable of resolving fine microstructural details while minimizing radiation exposure. Phase-sensitive computed tomography (CT), particularly propagation-based imaging (PBI), offers superior soft tissue contrast but has historically been limited by the lack of compatible fixation techniques that preserve lung architecture post-excision. We present an adapted formaldehyde (FA) vapour fixation protocol designed to maintain human-sized lungs in a physiologically inflated and morphologically stable state. This approach prevents collapse of the delicate air–tissue interfaces, a major barrier to high-fidelity phase-contrast imaging and histological correlation. Our method enables high-resolution, multiscale imaging from whole-organ PBI at 67 µm voxel size to localized subcellular synchrotron PBI at 650 nm voxel size on the same specimen, with preserved spatial relationships critical for accurate validation of imaging findings. In porcine models, FA vapour fixation maintained alveolar integrity and radiological contrast without compromising histological detail, while also avoiding the artifacts associated with liquid fixation. Crucially, the protocol allows regulation of inflation and fixation dynamics, addressing longstanding challenges in ex vivo lung imaging and enabling consistent specimen preparation across studies. This fixation technique supports biosafe stabilization of freshly explanted human lungs–such as those from transplant procedures creating new opportunities for translational research on pathological tissue. By bridging high-resolution radiology and histopathology, our scalable fixation protocol establishes a standardized foundation for multimodal lung imaging and offers a critical tool for advancing both fundamental lung research and clinical diagnostics.

Previous evidence has shown that high-frequency transcranial random noise stimulation (hf-tRNS) reduces motion coherence thresholds when applied with a cephalic montage (i.e., return electrode over Cz). Extracephalic montages, which avoid stimulating regions under the return electrode, have also been used to modulate behavioral performance. In this study, we investigated the effects of different transcranial electrical stimulation (tES) protocols on visual motion discrimination, placing the return electrode on the ipsilateral arm. We assessed the impact of electrode positioning using hf-tRNS, anodal, cathodal transcranial direct current stimulation (tDCS), and Sham stimulation over hMT+, a brain region involved in global motion perception. Motion direction discrimination was measured using random dot kinematograms (RDKs). Given the increased distance between the stimulation and return electrodes in this montage, we expected a smaller reduction in motion discrimination thresholds compared to our previous study. Our results suggest that increasing interelectrode distance alters current flow characteristics - such as current distribution and focality - within the cortical areas under the target electrode, producing different effects. Additionally, no significant effects were observed with the other tES protocols tested. Our findings suggest that change in the interelectrode distance influences current flow characteristics, such as current distribution and focality, within the cortical areas under the target electrode, resulting in differential neuromodulatory effects. These results highlight the importance of stimulation configuration on performance, particularly a potential electric field shift due to the change in the interelectrode distance. Given the widespread application of brain stimulation techniques in clinical and cognitive research, our results can guide future studies carefully considering this further aspect of stimulation montage configurations.

Lung diseases such as chronic obstructive pulmonary disease are a major health burden to society for which early detection plays a crucial role for treatment success. For detection, as well as diagnosis and serial evaluation, imaging plays a major role, but lung diseases are often still diagnosed in progressed states for which effective causal therapies do not presently exist. Recently, dark-field lung imaging has been introduced as a promising technique for early stage detection of alterations in lung micro-structures. This work presents an analyzer-free, full-scale lung imaging system based on a dual-phase interferometer, which allows tuning and direct resolution of grating induced intensity fringes. It provides the classical absorption chest image with additional dark-field information without significant attenuation of the patient-exposed photon-flux or the cost of large area absorption gratings. The detailed system achieves a dark-field sensitivity adequate for lung imaging, governed by system autocorrelation lengths of up to 0.6 [Formula: see text]. The computed tomography (CT) reconstructions show further evidence of the emergence of the dark-field in the parenchyma.

SYRMEP is the hard X-ray imaging beamline of Elettra synchrotron offering X-ray full-field techniques, micro-computed tomography (microCT) and phase-contrast modality in the energy range 10–40 keV. The beamline operates in a multidisciplinary research context spanning from biomedical applications to botany, from zoology to food technology and cultural heritage, from materials engineering to geology and earth science. Thanks to the flexibility of SYRMEP setup, in situ experiments can be performed as well, novel imaging methods can be developed and implemented in a synergical manner with interested users and collaborators. SYRMEP peculiar wide beam together with the long sample-to-detector distance enables multiscale phase-contrast studies with optimized contrast and spatial resolution on rather large specimens, such as human lung phantoms. This is particularly relevant in view of future clinical lung imaging foreseen in the framework of Elettra 2.0 program. Here, the current beamline features and recent upgrades are illustrated, an overview of the imaging methods routinely offered to SYRMEP users’ community is presented, and the outlook for the new beamline SYRMEP-Life Science (SYRMEP-LS) is reported.

Background: Visual perceptual learning plays a crucial role in shaping our understanding of how the human brain integrates visual cues to construct coherent perceptual experiences. The visual system is continually challenged to integrate a multitude of visual cues, including form and motion, to create a unified representation of the surrounding visual scene. This process involves both the processing of local signals and their integration into a coherent global percept. Over the past several decades, researchers have explored the mechanisms underlying this integration, focusing on concepts such as internal noise and sampling efficiency, which pertain to local and global processing, respectively. Objectives and Methods: In this study, we investigated the influence of visual perceptual learning on non-directional motion processing using dynamic Glass patterns (GPs) and modified Random-Dot Kinematograms (mRDKs). We also explored the mechanisms of learning transfer to different stimuli and tasks. Specifically, we aimed to assess whether visual perceptual learning based on illusory directional motion, triggered by form and motion cues (dynamic GPs), transfers to stimuli that elicit comparable illusory motion, such as mRDKs. Additionally, we examined whether training on form and motion coherence thresholds improves internal noise filtering and sampling efficiency. Results: Our results revealed significant learning effects on the trained task, enhancing the perception of dynamic GPs. Furthermore, there was a substantial learning transfer to the non-trained stimulus (mRDKs) and partial transfer to a different task. The data also showed differences in coherence thresholds between dynamic GPs and mRDKs, with GPs showing lower coherence thresholds than mRDKs. Finally, an interaction between visual stimulus type and session for sampling efficiency revealed that the effect of training session on participants’ performance varied depending on the type of visual stimulus, with dynamic GPs being influenced differently than mRDKs. Conclusion: These findings highlight the complexity of perceptual learning and suggest that the transfer of learning effects may be influenced by the specific characteristics of both the training stimuli and tasks, providing valuable insights for future research in visual processing.

Lung diseases continue to present a major burden on public health. Therefore, improving the process of diagnosis by the development of novel imaging techniques is of great importance. In this perspective, phase sensitive CT imaging techniques such as propagation based imaging (PBI) might play an important role as they allow increasing the spatial resolution at very low x-ray dose levels that are comparable to clinical CT. However, the development of such methods is not only hindered by technological problems but also by the lack of precise validation strategies. We adapted formaldehyde (FA) vapor fixation to demonstrate that fresh porcine lungs that have been investigated by PBI can be fixed in their physiological shape and studied by multi-scale microCT imaging as well as classical histology. In addition, we show that FA vapor fixed pig lungs can be scanned by PBI without visible deterioration of image quality compared to fresh tissue. This opens the possibility of fixing and storing, for instance, human lung tissue before performing a PBI experiment, which in turn allows to study pathological changes in human lungs without questioning the translate-ability of findings in pig lung. The setup can be used by any interested researchers. ### Competing Interest Statement The authors have declared no competing interest.

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.

Objective.Differentiation of breast tissues is challenging in X-ray imaging because tissues might share similar or even the same linear attenuation coefficientsμ. Spectral computed tomography (CT) allows for more quantitative characterization in terms of tissue density (ρ) and effective atomic number (Zeff) by exploiting the energy dependence ofμ. The objective of this study was to examine the potential ofρ/Zeffdecomposition in spectral breast CT so as to explore the benefits of tissue characterization and improve the diagnostic accuracy of this emerging 3D imaging technique.Approach.In this work, 5 mastectomy samples and a phantom with inserts mimicking breast soft tissues were evaluated in a retrospective study. The samples were imaged at three monochromatic energy levels in the range of 24-38 keV at 5 mGy per scan using a propagation-based phase-contrast setup at SYRMEP beamline at the Italian national synchrotron Elettra.Main results.A custom-made algorithm incorporating CT reconstructions of an arbitrary number of spectral energy channels was developed to extract the density and effective atomic number of adipose, fibro-glandular, pure glandular, tumor, and skin from regions selected by a radiologist.Significance.Preliminary results suggest that, via spectral CT, it is possible to enhance tissue differentiation. It was found that adipose, fibro-glandular and tumorous tissues have average effective atomic numbers (5.94 ± 0.09, 7.03 ± 0.012, and 7.40 ± 0.10) and densities (0.90 ± 0.02, 0.96 ± 0.02, and 1.07 ± 0.03 g cm-3) and can be better distinguished if both quantitative values are observed together.

Objective: Our goal is to evaluate the effects of heat and ultraviolet (UV) irradiation on P3 facial respirator microstructure. Intervention: P3 facial filters were exposed to dry heat and UV sterilization procedures. Methods: P3 facial filter samples underwent a standardized sterilization process based on dry heat and UV irradiation techniques. We analyzed critical parameters of internal microstructure, such as fiber thickness and porosity, before and after sterilization, using 3D data obtained with synchrotron radiation-based X-ray computed microtomography (micro-CT). The analyzed filter has two inner layers called the “finer” and “coarser” layers. The “finer” layer consists of a dense fiber network, while the “coarser” layer has a less compact fiber network. Results: Analysis of 3D images showed no statistically significant differences between the P3 filter of the controls and the dry heat/UV sterilized samples. In particular, averages fiber thickness in the finer layer of the control and the 60° dry heated and UV-irradiated sample groups was almost identical. Average fiber thickness for the coarser layer of the control and the 60° dry heated and UV-irradiated sample groups was very similar, measuring 19.33 µm (±0.47), 18.33 µm (±0.47), and 18.66 µm (±0.47), respectively. There was no substantial difference in maximum fiber thickness in the finer layers and coarser layers. For the control group samples, maximum thickness was on average 11.43 µm (±1.24) in the finer layer and 59.33 µm (±6.79) in the coarser layer. Similarly, the 60° dry heated group samples were thickened 12.2 µm (±0.21) in the finer layer and 57.33 µm (±1.24) in the coarser layer, while for the UV-irradiated group, the mean max thickness was 12.23 µm (±0.90) in the finer layer and 58.00 µm (±6.68) in the coarser layer. Theoretical porosity analysis resulted in 74% and 88% for the finer and coarser layers. The finer layers’ theoretical porosity tended to decrease in dry heat and UV-irradiated samples compared with the respective control samples. Conclusions: Dry heat and UV sterilization processes do not substantially alter the morphometry of the P3 filter samples’ internal microstructure, as studied with micro-CT. The current study suggests that safe P3 filter facepiece reusability is theoretically feasible and should be further investigated.

In this work, we propose the software library PyPore3D, an open source solution for data processing of large 3D/4D tomographic data sets. PyPore3D is based on the Pore3D core library, developed thanks to the collaboration between Elettra Sincrotrone (Trieste) and the University of Trieste (Italy). The Pore3D core library is built with a distinction between the User Interface and the backend filtering, segmentation, morphological processing, skeletonisation and analysis functions. The current Pore3D version relies on the closed source IDL framework to call the backend functions and enables simple scripting procedures for streamlined data processing. PyPore3D addresses this limitation by proposing a full open source solution which provides Python wrappers to the the Pore3D C library functions. The PyPore3D library allows the users to fully use the Pore3D Core Library as an open source solution under Python and Jupyter Notebooks PyPore3D is both getting rid of all the intrinsic limitations of licensed platforms (e.g., closed source and export restrictions) and adding, when needed, the flexibility of being able to integrate scientific libraries available for Python (SciPy, TensorFlow, etc.).

The implementation of organic semiconductor (OSC) materials in X‐ray detectors provides exciting new opportunities for developing a new generation of biocompatible devices with high potential for the fabrication of sensitive and low‐cost X‐ray imaging systems. Here, the fabrication of high performance organic field‐effect transistors (OFETs) based on blends of 1,4,8,11‐tetramethyl‐6,13‐triethylsilylethynyl pentacene (TMTES) with polystyrene is reported. The films are printed employing a low cost and high‐throughput deposition technique. The devices exhibit excellent electrical characteristics with a high mobility and low density of hole traps, which is ascribed to the favorable herringbone packing (different from most pentacene derivatives) and the vertical phase separation in the blend films. As a consequence, an exceptional high sensitivity of (4.10 ± 0.05) × 10 10 µC Gy –1 cm –3 for X‐ray detection is achieved, which is the highest reported so far for a direct X‐ray detector based on a tissue equivalent full organic active layer, and is higher than most perovskite film‐based X‐ray detectors. As a proof of concept to demonstrate the high potential of these devices, an X‐ray image with sub‐millimeter pixel size is recorded employing a 4‐pixel array. This work highlights the potential exploitation of high performance OFETs for future innovative large‐area and highly sensitive X‐ray detectors for medical dosimetry and diagnostic applications.

Static and dynamic cues within certain spatiotemporal proximity are used to evoke respective global percepts of form and motion. The limiting factors in this process are, first, internal noise, which indexes local orientation/direction detection, and, second, sampling efficiency, which relates to the processing and the representation of global orientation/direction. These parameters are quantified using the equivalent noise (EN) paradigm. EN has been implemented with just two levels: high and low noise. However, when using this simplified version, one must assume the shape of the overall noise dependence, as the intermediate points are missing. Here, we investigated whether two distinct EN methods, the 8-point and the simplified 2-point version, reveal comparable parameter estimates. This was performed for three different types of stimuli: random dot kinematograms, and static and dynamic translational Glass patterns, to investigate how constant internal noise estimates are, and how sampling efficiency might vary over tasks. The results indicated substantial compatibility between estimates over a wide range of external noise levels sampled with eight data points, and a simplified version producing two highly informative data points. Our findings support the use of a simplified procedure to estimate essential form-motion integration parameters, paving the way for rapid and critical applications to populations that cannot tolerate protracted measurements.

Photon-counting CT (PCCT) is an emerging CT technology that uses photon-counting detectors (PCDs) to offer better spatial resolution, higher contrast, lower noise, and material-specific imaging as compared to conventional energy-integrating CT. To study the efficiency and performance of PCCT technologies in clinical use, virtual imaging trials (VITs) can be used. VITs use computational human phantoms to generate scanner-specific CT images. The integration of PCCT into VITs requires modeling the signal generation and signal processing in the detector and electronics, which includes incorporating the effects of non-idealities in PCDs such as crosstalk, charge sharing, and pulse pileup. These non-idealities adversely affect the image quality of PCCT systems, and their inclusion is important in accurate and realistic modeling of the PCDs. The existing scanner simulators model either charge sharing or pulse pileup but not their combined effects. The purpose of this study was to develop an experimentally validated modular detector response model that accounted for the combined effects of crosstalk, charge sharing, and pulse pileup in CdTe- and Si-based PCDs. It can be used to simulate variety of PCCT designs, including different detector materials and geometry, facilitating the evaluation and study of present and future PCCTs. The validation showed a close agreement with the experimental data acquired using Pixirad-1/Pixie-III PCDs. The platform was used to generate spatio-energetic covariance correlation matrices that integrated with a VIT framework called DukeSim to simulate scanner specific PCCT images.

In this work, we applied the singular value decomposition (SVD) method to a set of monochromatic images to extract the dominant physical contributions to image formation. We showed that the first two principal components can be related to an arbitrary pair of basis material in mathematically enclosed expression. The later principal components are assumed to carry mostly sub-leading image formation effects, noise, and reconstruction artifact contribution. The proof of concept is shown on numerical (linear) images and later confirmed on physical spectral CT phantom images obtained with monochromatic x-ray radiation at Elettra synchrotron in Trieste, Italy. Following material decomposition, we also performed a quantitative description of tissue-equivalent phantom materials in terms of material density and effective atomic number.

The scope of this paper is to outline the main marks and performances of the MagneDyn beamline, which was designed and built to perform ultrafast magnetodynamic studies in solids. Open to users since 2019, MagneDyn operates with variable circular and linear polarized femtosecond pulses delivered by the externally laser-seeded FERMI free-electron laser (FEL). The very high degree of polarization, the high pulse-to-pulse stability, and the photon energy tunability in the 50-300 eV range allow performing advanced time-resolved magnetic dichroic experiments at the K-edge of light elements, e.g., carbon and at the M- and N-edge of the 3d-transition-metals and rare earth elements, respectively. To this end, two experimental end-stations are available. The first is equipped with an in situ dedicated electromagnet, a cryostat, and an extreme ultraviolet Wollaston-like polarimeter. The second, designed for carry-in user instruments, hosts also a spectrometer for pump-probe resonant x-ray emission and inelastic spectroscopy experiments with a sub-eV energy resolution. A Kirkpatrick-Baez active optics system provides a minimum focus of ∼20×20μm2 FWHM at the sample. A pump laser setup, synchronized with the FEL-laser seeding system, delivers sub-picosecond pulses with photon energies ranging from the mid-IR to near-UV for optical pump-FEL probe experiments with a minimal pump-probe jitter of few femtoseconds. The overall combination of these features renders MagneDyn a unique state-of-the-art tool for studying ultrafast magnetic and resonant emission phenomena in solids.

Objective.To introduce the optimization of a customized GPU-based simultaneous algebraic reconstruction technique (cSART) in the field of phase-contrast breast computed tomography (bCT). The presented algorithm features a 3D bilateral regularization filter that can be tuned to yield optimal performance for clinical image visualization and tissues segmentation.Approach.Acquisitions of a dedicated test object and a breast specimen were performed at Elettra, the Italian synchrotron radiation (SR) facility (Trieste, Italy) using a large area CdTe single-photon counting detector. Tomographic images were obtained at 5 mGy of mean glandular dose, with a 32 keV monochromatic x-ray beam in the free-space propagation mode. Three independent algorithms parameters were optimized by using contrast-to-noise ratio (CNR), spatial resolution, and noise texture metrics. The results obtained with the cSART algorithm were compared with conventional SART and filtered back projection (FBP) reconstructions. Image segmentation was performed both with gray scale-based and supervised machine-learning approaches.Main results.Compared to conventional FBP reconstructions, results indicate that the proposed algorithm can yield images with a higher CNR (by 35% or more), retaining a high spatial resolution while preserving their textural properties. Alternatively, at the cost of an increased image 'patchiness', the cSART can be tuned to achieve a high-quality tissue segmentation, suggesting the possibility of performing an accurate glandularity estimation potentially of use in the realization of realistic 3D breast models starting from low radiation dose images.Significance.The study indicates that dedicated iterative reconstruction techniques could provide significant advantages in phase-contrast bCT imaging. The proposed algorithm offers great flexibility in terms of image reconstruction optimization, either toward diagnostic evaluation or image segmentation.

A single-energy CT provides a map of gray levels simply related to X-rays linear attenuation coefficients, which could be very similar for different materials at a given energy. Images acquired at multiple energies allows for a quantitative description of an object. In this work, phantom images were acquired using synchrotron radiation CT at precisely defined energies. A successful attempt was made to differentiate the phantom materials with respect to their decomposition into basis materials.