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• Pub. Date : 2025
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Lung ultrasound is increasingly used in neonatal intensive care units. We summarized the ultrasonographic patterns, features of most neonatal respiratory morbidities, and clinical application in neonates. Lung ultrasound is a non-invasive, radiation-free, and reproducible adjunct tool that can guide the clinical management of neonates presenting with respiratory distress.

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• Pub. Date : 2025
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The supermassive black hole Sgr A* at the center of our galaxy produces repeating near-infrared flares that are observed by ground- and space-based instruments. This activity has been simulated in the past with magnetically arrested disk models that include stable jet formations. We used a different approach, considering a standard and normal evolution (SANE) multi-loop model that lacks a stable jet structure. The main objective of this research is to identify regions that contain current sheets and high magnetic turbulence, and to subsequently generate a 2.2 μm light curve from nonthermal particles. These aims required the identification of areas that contain current sheets and high magnetic turbulence, and the averaging of the magnetization in the regions surrounding these areas. Subsequently, particle-in-cell fitting formulas were applied to determine the nonthermal particle distribution and to obtain the sought-after light curve. Additionally, we investigated the properties of the flares, in particular their evolution during flare events, and the similarity of flare characteristics between the generated and observed light curves. We employed 2D general relativistic magnetohydrodynamic simulation data from a SANE multi-loop model and introduced thermal radiation to generate a 230 GHz light curve. Physical variables were calibrated to align with the 230 GHz observations. We identified current sheets by analyzing toroidal currents, magnetization, plasma β, density, and dimensionless temperatures. We studied the evolution of current sheets during flare events and calculated higher-energy nonthermal light curves, focusing on the 2.2 μm near-infrared range. We obtain promising $2.2 μ$m light curves whose flare duration and spectral index behavior align well with observations. Our findings support the association of flares with particle acceleration and nonthermal emission in current sheet plasmoid chains and at the boundary of the disk inside the funnel above and below the central black hole.

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• Pub. Date : 2025
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AbstractTransarterial radioembolization (TARE) is an established clinical therapy for treating patients with intermediate to advanced hepatocellular carcinoma (HCC) or those who cannot undergo radical treatment. However, the delivery of a high radiation dose is associated with several adverse effects, such as radiation pneumonitis. Additionally, the available radioactive microspheres (MSs) are dense and unsuitable for interventional delivery. This study proposes the use of commercial CalliSpheres polyvinyl alcohol (PVA) gel MSs coated with polydopamine (PDA) as a carrier for radioactive iodine (131I) labeled using the iodogen method, denoted as 131I‐PDA@PVA MSs, which can be for radioembolization combined photothermal therapy (PTT) of HCC. In vitro experiments have demonstrated that 131I‐PDA@PVA MSs have high radiolabeling stability and photothermal properties. Single photon emission computed tomography (SPECT)/computed tomography (CT) imaging and biodistribution experiments have shown that 131I‐PDA@PVA MSs remain stable in vivo without any radioactive leakage. The results of the antitumor study suggest that 131I‐PDA@PVA MSs are an effective treatment for inhibiting tumor growth through a combination of radioembolization and PTT while avoiding significant side effects. These multifunctional MSs have great potential for clinical application in the treatment of HCC.

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• Pub. Date : 2025
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• Pub. Date : 2025
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Abstract For successfully heating plasma with waves in the Ion Cyclotron Range of Frequencies (ICRF), mitigating impurity production is just as crucial as maximizing power coupling, especially in high-Z environments [Urbanczyk 2021]. Only when the power is coupled with limited influence on impurity production, can ICRF truly become a powerful tool to directly deposit energy on ions, modify turbulence-driven transport and enhance the efficiency of fusion reactions. 
To do so, one must rely on a toroidal array of at least three active elements excited with appropriate phasing and power ratio to reduce the currents induced on the antenna frame below levels critical for physical sputtering. In contrast with classic 2-strap antennas which work best when operated in dipole phasing with same power on both straps, 3-strap antennas in ASDEX Upgrade (AUG) – but also 4-strap antennas in JET, Alcator C-Mod, SPARC and ITER – offer the possibility to also act on the power ratio between central and outer straps. With optimal settings, impurity production can be reduced substantially, making ICRF compatible with high-Z wall [Bobkov 2017]. 
This paper explores the characteristics of the AUG 3-strap antennas in terms of impurity production, as well as the key role of plasma composition in this process. It is shown that the experimentally measured energies of ions falling on antenna limiters can well be predicted with at least two different numerical tools: SSWICH and Petra-M. These tools are further used to describe the source of impurity, namely the gross erosion of tungsten from an ICRF antenna for different plasma mixtures, and results of the calculations are compared to experiments. We finally show that deleterious effects of ICRF on plasma surface interactions will be weaker in plasmas containing larger fractions of highly ionized heavier low-Z impurity, which is typically relevant for experiments relying on impurity seeding.

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• Pub. Date : 2025
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• Pub. Date : 2025
• Page : pp.1-14
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Abstract Background This work aimed to develop deep learning (DL) models for CT-free attenuation and Monte Carlo-based scatter correction (AC, SC) in quantitative 90Y SPECT imaging for improved dose calculation. Methods Data of 190 patients who underwent 90Y selective internal radiation therapy (SIRT) with glass microspheres was studied. Voxel-level dosimetry was performed on uncorrected and corrected SPECT images using the local energy deposition method. Three deep learning models were trained individually for AC, SC, and joint ASC using a modified 3D shifted-window UNet Transformer (Swin UNETR) architecture. Corrected and unorrected dose maps served as reference and as inputs, respectively. The data was split into train set (~ 80%) and unseen test set (~ 20%). Training was conducted in a five-fold cross-validation scheme. The trained models were tested on the unseen test set. The model’s performance was thoroughly evaluated by comparing organ- and voxel-level dosimetry results between the reference and DL-generated dose maps on the unseen test dataset. The voxel and organ-level evaluations also included Gamma analysis with three different distances to agreement (DTA (mm)) and dose difference (DD (%)) criteria to explore suitable criteria in SIRT dosimetry using SPECT. Results The average ± SD of the voxel-level quantitative metrics for AC task, are mean error (ME (Gy)): -0.026 ± 0.06, structural similarity index (SSIM (%)): 99.5 ± 0.25, and peak signal to noise ratio (PSNR (dB)): 47.28 ± 3.31. These values for SC task are − 0.014 ± 0.05, 99.88 ± 0.099, 55.9 ± 4, respectively. For ASC task, these values are as follows: -0.04 ± 0.06, 99.57 ± 0.33, 47.97 ± 3.6, respectively. The results of voxel level gamma evaluations with three different criteria, namely “DTA: 4.79, DD: 1%”, “DTA:10 mm, DD: 5%”, and “DTA: 15 mm, DD:10%” were around 98%. The mean absolute error (MAE (Gy)) for tumor and whole normal liver across tasks are as follows: 7.22 ± 5.9 and 1.09 ± 0.86 for AC, 8 ± 9.3 and 0.9 ± 0.8 for SC, and 11.8 ± 12.02 and 1.3 ± 0.98 for ASC, respectively. Conclusion We developed multiple models for three different clinically scenarios, namely AC, SC, and ASC using the patient-specific Monte Carlo scatter corrected and CT-based attenuation corrected images. These task-specific models could be beneficial to perform the essential corrections where the CT images are either not available or not reliable due to misalignment, after training with a larger dataset.

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• Pub. Date : 2025
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