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Respiratory X-ray imaging enhanced by phase contrast has shown improved airway visualization in animal models. Limitations in current X-ray technology have nevertheless hindered clinical translation, leaving the potential clinical impact an open question. Here, we explore phase-contrast chest radiography in a realistic in silico framework. Specifically, we use preprocessed virtual patients to generate in silico chest radiographs by Fresnel-diffraction simulations of X-ray wave propagation. Following a reader study conducted with clinical radiologists, we predict that phase-contrast edge enhancement will have a negligible impact on improving solitary pulmonary nodule detection (6 to 20 mm). However, edge enhancement of bronchial walls visualizes small airways (<2 mm), which are invisible in conventional radiography. Our results show that phase-contrast chest radiography could play a future role in observing small-airway obstruction (e.g., relevant for asthma or early-stage chronic obstructive pulmonary disease), which cannot be directly visualized using current clinical methods, thereby motivating the experimental development needed for clinical translation. Finally, we discuss quantitative requirements on distances and X-ray source/detector specifications for clinical implementation of phase-contrast chest radiography.

Phase-contrast X-ray lung imaging has broken new ground in preclinical respiratory research by improving contrast at air/tissue interfaces. To minimize blur from respiratory motion, intubation and mechanical ventilation is commonly employed for end-inspiration gated imaging at synchrotrons and in the laboratory. Inevitably, the prospect of ventilation induced lung injury (VILI) renders mechanical ventilation a confounding factor in respiratory studies of animal models. Here we demonstrate proof-of-principle 3D imaging of the tracheobronchial tree in free-breathing mice without mechanical ventilation at radiation levels compatible with longitudinal studies. We use a prospective gating approach for end-expiration propagation-based phase-contrast X-ray imaging where the natural breathing of the mouse dictates the acquisition flow. We achieve intrapulmonary spatial resolution in the 30-μm-range, sufficient for resolving terminal bronchioles in the 60-μm-range distinguished from the surrounding lung parenchyma. These results should enable non-invasive longitudinal studies of native state murine airways for translational lung disease research in the laboratory. Mechanical ventilation of living animals is routinely used to achieve high-resolution pulmonary imaging, but this can damage the subject. Here, an alternative, free-breathing method enables X-ray tomography with 30 μm resolution.

Radiation workers need accurate monitoring of X-ray exposure, but existing solutions are either inaccessible, expensive, or provide delayed feedback. We present OpenDosimeter ( www.opendosimeter.org ), an open hardware solution for real-time personal X-ray dose monitoring. Using a scintillator-based X-ray sensor on a custom board powered by a Raspberry Pi Pico, OpenDosimeter provides real-time feedback (1 Hz), data logging (10 hours), and battery-powered operation. A core innovation is that we calibrate the device using 241 Am found in ionization smoke detectors. Specifically, we use the γ -emissions to spectrally calibrate the dosimeter, then calculate the effective dose from X-ray exposure using the scintillator absorption efficiency and energy-to-dose coefficients derived from public tabulated data. We demonstrate that this transparent approach enables dose rate readings with linear response between 0.1–1000 μ Sv/h at  ± 25% accuracy, tested for energies up to 120 keV. The maximum dose rate readings are limited by pile-up effects when approaching count rate saturation (~77,000 counts per second at  ~13 μ s average pulse-processing time). The total cost for making an OpenDosimeter is <$100, which, combined with its open design, enables cost-effective local reproducibility on a global scale. This paper complements the open-source documentation by explaining the underlying technology, algorithms, and areas for future improvement. Radiation workers need accurate monitoring of X-ray exposure, but existing solutions are either inaccessible, expensive, or provide delayed feedback. This paper presents OpenDosimeter, a low-cost and open design solution to the problem.

X-Ray fluorescence computed tomography (XFCT) is an emerging biomedical imaging technique, which demands the development of new contrast agents. Ruthenium (Ru) and rhodium (Rh) have spectrally attractive Kα edge energies, qualifying them as new XFCT bio-imaging probes. Metallic Ru and Rh nanoparticles are synthesized by polyol method, in the presence of a stabilizer. The effect of several reaction parameters, including reaction temperature time, precursor and stabilizer concentration, and stabilizer molecular weight, on the size of particles, were studied. Resultant materials were characterized in detail using XRD, TEM, FT-IR, DLS-zeta potential and TGA techniques. Ru particles in the size range of 1–3 nm, and Rh particles of 6–9 nm were obtained. At physiological pH, both material systems showed agglomeration into larger assemblies ranging from 12–104 nm for Ru and 25–50 nm for Rh. Cytotoxicity of the nanoparticles (NPs) was evaluated on macrophages and ovarian cancer cells, showing minimal toxicity in doses up to 50 μg/mL. XFCT performance was evaluated on a small-animal-sized phantom model, demonstrating the possibility of quantitative evaluation of the measured dose with an expected linear response. This work provides a detailed route for the synthesis, size control and characterization of two materials systems as viable contrast agents for XFCT bio-imaging.

Nanoparticles (NPs) have been used as contrast agents for several bioimaging modalities. X-ray fluorescence (XRF) tomography can provide sensitive and quantitative 3D detection of NPs. With spectrally matched NPs as contrast agents, we demonstrated earlier in a laboratory system that XRF tomography could achieve high-spatial-resolution tumor imaging in mice. Here, we present the synthesis, characterization, and evaluation of a library of NPs containing Y, Zr, Nb, Rh, and Ru that have spectrally matched K-shell absorption for the laboratory scale X-ray source. The K-shell emissions of these NPs are spectrally well separated from the X-ray probe and the Compton background, making them suitable for the lab-scale XRF tomography system. Their potential as XRF contrast agents is demonstrated successfully in a small-animal equivalent phantom, confirming the simulation results. The diversity in the NP composition provides a flexible platform for a better design and biological optimization of XRF tomography nanoprobes.

Morphologically controllable synthesis of Rh nanoparticles (NPs) was achieved by the use of additives during polyol synthesis. The effect of salts and surfactant additives including PVP, sodium acetate, sodium citrate, CTAB, CTAC, and potassium bromide on Rh NPs morphology was investigated. When PVP was used as the only additive, trigonal NPs were obtained. Additives containing Br− ions (CTAB and KBr) resulted in NPs with a cubic morphology, while those with carboxyl groups (sodium citrate and acetate) formed spheroid NPs. The use of Cl− ions (CTAC) resulted in a mixture of polygon morphologies. Cytotoxicity of these NPs was evaluated on macrophages and ovarian cancer cell lines. Membrane integrity and cellular activity are both influenced to a similar extent, for both the cell lines, with respect to the morphology of Rh NPs. The cells exposed to trigonal Rh NPs showed the highest viability, among the NP series. Particles with a mixed polygon morphology had the highest cytotoxic impact, followed by cubic and spherical NPs. The Rh NPs were further demonstrated as contrast agents for X-ray fluorescence computed tomography (XFCT) in a small-animal imaging setting. This work provides a detailed route for the synthesis, morphology control, and characterization of Rh NPs as viable contrast agents for XFCT bio-imaging.

Stacked prism lenses (SPLs) are a type of refractive X-ray optics currently under development with the potential to greatly improve on current X-ray telescope optics in terms of focal length, angular resolution, efficiency and scalability. For this work, SPLs are manufactured using two-photon polymerization (2PP), with production being significantly faster and with higher geometric fidelity than previous methods. Preliminary laboratory tests show improved efficiency compared to previous manufacturing methods and promising optical capabilities. Two-photon polymerization is shown to be a reliable method for producing SPLs, and when challenges around printing time and assembly are addressed, the path towards an SPL X-ray telescope lies open.

Human exposure to lead (Pb) is a global health concern, yet existing technologies for detecting lead in our environment remain prohibitively expensive for widespread deployment. Here we present a new concept towards lead screening using X-ray fluorescence (XRF) in an unconventional geometry we coin transmission XRF in which the sample is placed between the source and detector. For cost reduction, we then show that \\(^241\\)Am found in ionizing smoke detectors is spectrally suitable for Pb L-shell XRF generation and can thus replace X-ray tubes used in conventional XRF devices. Exploring soil screening as the first application, we demonstrate with Monte Carlo simulations that a configuration with 7\\(\\) \\(^241\\)Am sources and a standard silicon drift detector can enable screening-relevant detection limits (100 ppm Pb) in soil within practical measurement times (<30 min). We believe this concept opens a route toward low-cost and scalable XRF instrumentation for democratizing lead screening across a wide range of samples.

We present OpenDosimeter (www.opendosimeter.org), an open hardware solution for real-time personal X-ray dose monitoring based on a scintillation counter. Using an X-ray sensor assembly (LYSO + SiPM) on a custom board powered by a Raspberry Pi Pico, OpenDosimeter provides real-time feedback (1 Hz), data logging (10 hours), and battery-powered operation. One of the core innovations is that we calibrate the device using \\(^241\\)Am found in ionization smoke detectors. Specifically, we use the \\(\\)-emissions to spectrally calibrate the dosimeter, then calculate the effective dose from X-ray exposure by compensating for the scintillator absorption efficiency and applying energy-to-dose coefficients derived from tabulated data in the ICRP 116 publication. We demonstrate that this transparent approach enables real-time dose rate readings with a linear response between 0.1-1000 \\(\\)Sv/h at \\(\\)25% accuracy, tested for energies up to 120 keV. The maximum dose rate readings are limited by pile-up effects when approaching count rate saturation (\\(\\)77 kcps at \\(\\)13 \\(\\)s average pulse processing time). The total component cost for making an OpenDosimeter is <\\$100, which, combined with its open design (both hardware and software), enables cost-effective local reproducibility on a global scale. Through a student workshop, we also demonstrate its effectiveness as an educational and capacity-building tool. This paper complements the open-source documentation by explaining the underlying technology, the algorithm for dose calculation, and areas for future improvement.