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Purpose: The primary fluence of a proton pencil beam exiting the accelerator is enveloped by a region of secondaries, commonly called "spray". Although small in magnitude, this spray may affect dose distributions in pencil beam scanning mode e.g., in the calculation of the small field output, if not modelled properly in a treatment planning system (TPS). The purpose of this study was to dosimetrically benchmark the Monte Carlo (MC) dose engine of the RayStation TPS (v.10A) in small proton fields and systematically compare single Gaussian (SG) and double Gaussian (DG) modeling of initial proton fluence providing a more accurate representation of the nozzle spray.
Methods: The initial proton fluence distribution for SG/DG beam modeling was deduced from two-dimensional measurements in air with a scintillation screen with electronic readout. The DG model was either based on direct fits of the two Gaussians to the measured profiles, or by an iterative optimization procedure, which uses the measured profiles to mimic in-air scan-field factor (SF) measurements. To validate the DG beam models SFs, i.e. relative doses to a 10 × 10 cm field, were measured in water for three different initial proton energies (100MeV, 160MeV, 226.7MeV) and square field sizes from 1×1cm to 10×10cm using a small field ionization chamber (IBA CC01) and an IBA ProteusPlus system (universal nozzle). Furthermore, the dose to the center of spherical target volumes (diameters: 1cm to 10cm) was determined using the same small volume ionization chamber (IC). A comprehensive uncertainty analysis was performed, including estimates of influence factors typical for small field dosimetry deduced from a simple two-dimensional analytical model of the relative fluence distribution. Measurements were compared to the predictions of the RayStation TPS.
Results: SFs deviated by more than 2% from TPS predictions in all fields <4×4cm with a maximum deviation of 5.8% for SG modeling. In contrast, deviations were smaller than 2% for all field-sizes and proton energies when using the directly fitted DG model. The optimized DG model performed similarly except for slightly larger deviations in the 1×1cm scan-fields. The uncertainty estimates showed a significant impact of pencil beam size variations (±5%) resulting in up to 5.0% standard uncertainty. The point doses within spherical irradiation volumes deviated from calculations by up to 3.3% for the SG model and 2.0% for the DG model.
Conclusion: Properly representing nozzle spray in RayStation's MC-based dose engine using a DG beam model was found to reduce the deviation to measurements in small spherical targets to below 2%. A thorough uncertainty analysis shows a similar magnitude for the combined standard uncertainty of such measurements.
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http://dx.doi.org/10.1016/j.zemedi.2022.11.011 | DOI Listing |
J Phys Chem A
September 2025
Department of Chemistry, Institute for Quantum Information Research and Engineering, and Center for Molecular Quantum Transduction, Northwestern University, Evanston, Illinois 60208-3113, United States.
Light-driven formation of radical ion pairs that occurs much faster than their electron spin dynamics results in correlated spins whose coherence properties can be used as a quantum-based electric field sensor. This results from the radical ion pair having charge and spin distributions that track one another. Thus, electric field induced changes in the distance between the two charges are reflected in the spin-spin distance that can be measured directly using out-of-phase electron spin echo envelope modulation (OOP-ESEEM), a pulse-EPR technique.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
September 2025
Molecular Imaging Program at Stanford, Department of Radiology, School of Medicine, Stanford University, Palo Alto, CA 94304.
The biophysical properties of single cells are crucial for understanding cellular function and behavior in biology and medicine. However, precise manipulation of cells in 3-D microfluidic environments remains challenging, particularly for heterogeneous populations. Here, we present "Electro-LEV," a unique platform integrating electromagnetic and magnetic levitation principles for dynamic 3-D control of cell position during separation.
View Article and Find Full Text PDFPLoS One
September 2025
School of Medical Engineering, Xinxiang Medical University, Xinxiang, China.
Computer-aided diagnostic (CAD) systems for color fundus images play a critical role in the early detection of fundus diseases, including diabetes, hypertension, and cerebrovascular disorders. Although deep learning has substantially advanced automatic segmentation techniques in this field, several challenges persist, such as limited labeled datasets, significant structural variations in blood vessels, and persistent dataset discrepancies, which continue to hinder progress. These challenges lead to inconsistent segmentation performance, particularly for small vessels and branch regions.
View Article and Find Full Text PDFElife
September 2025
Department of Chemistry, University of Massachusetts, Amherst, United States.
Voltage-dependence gating of ion channels underlies numerous physiological and pathophysiological processes, and disruption of normal voltage gating is the cause of many channelopathies. Here, long timescale atomistic simulations were performed to directly probe voltage-induced gating transitions of the big potassium (BK) channels, where the voltage sensor domain (VSD) movement has been suggested to be distinct from that of canonical Kv channels but remains poorly understood. Using a Core-MT construct without the gating ring, multiple voltage activation transitions were observed at 750 mV, allowing detailed analysis of the activated state of BK VSD and key mechanistic features.
View Article and Find Full Text PDFNutr Health
September 2025
Department of Nursing, Faculty of Health Sciences, John Paul II University in Biała Podlaska, Biala Podlaska, Poland.
Healthy plant-based diets, such as vegan and vegetarian diets, as well as planetary health diets, meet the recommendations of sustainable dietary patterns and are healthier for both the planet and humans. The adoption of these dietary patterns may depend on socio-demographic factors and individual motivations. This study aimed to analyse the association between socio-demographic factors and knowledge and attitudes towards vegan and vegetarian diets amongst university students.
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