Thermal neutron dose measurements using TLD-100 detectors in the IPEN/MB-01 reactor core

Considerable experimental effort has been aimed at uncovering a reliable way to perform a dosimetric assessment in mixed radiation fields. In fields composed by gammas and neutrons, TLD dosimeters are usually applied to execute such measurements, although there is no consensus on the most favorable strategy to employ them. In this context, TLD-100 measurements within two different core configurations of the IPEN/MB-01 research reactor and Monte Carlo simulations have been used to investigate the behavior of those detectors in multiple mixed radiation fields, deriving a methodology to evaluate the dose deposition in the dosimeter by different gamma and neutron energy spectra and intensities. A surprising outcome is the linear neutron dose response shown by TLD-100 even irradiated by so distinct irradiation fields.

On the significance of the measurement evaluation method in decision making: A synthesis of JCGM 101 and JCGM 106 applied to gross alpha and gross beta measurements using LSC

In decision making, e.g. conformity to a specification like a reference value or a requirement, the decision rule applied shall be documented. Furthermore, if the measurement uncertainty is considered in the decision process the associated probability, or risk, that a measurement result is above (or below) a reference value shall be taken into account. In this work it is shown that for gross alpha and gross beta measurements the evaluation method, GUMUF (GUM Uncertainty Framework) or MC (Monte Carlo), may also be important and influence the decisions taken when measurement results are very close to the reference value. Therefore the evaluation method and assumptions of the input quantities may also be important to document. Moreover, decision makers or users of measurement results should be aware of possible differences and/or consequences due to the evaluation method regardless of the decision rule and the choice of evaluation method.

Efficient optimization of an accelerator neutron source for neutron capture therapy using genetic algorithms

BACKGROUND

In recent years, genetic algorithms have been applied in the field of nuclear technology design, producing superior optimization results compared to traditional methods. They can be employed in the design and optimization of beam shaping assemblies (BSA) BSA to obtain the desired neutron beams. But it should be noted that the direct combination of Monte Carlo methods with genetic algorithms requires a significant amount of computational resources and time.

PURPOSE

Design and optimize BSA more efficiently to achieve neutron beams that meet specified recommendations.

METHODS

We propose an approach of NSGA II with crucial variables which are identified by multivariate statistical techniques. This approach significantly reduces the problem sizes, thus reducing the time required for optimization. We illustrate this methodology using the example of BSA design for AB-BNCT.

RESULTS

The computational efficiency has tripled with crucial variables. By using NSGA II, we obtained optimized models conforming to both the new and old version IAEA BNCT guidelines through a single optimization process and subjected them to phantom analysis. The results demonstrate that models obtained through this method can meet the IAEA recommendations with deep advantage depth (AD) and high absorbed ratio (AR).

CONCLUSION

The genetic algorithm with crucial variables displays tremendous potential in addressing BSA optimization challenges.

Polyurethane reinforced with micro/nano waste slag as a shielding panel for photons (experimental and theoretical study)

This study not only provides an innovative technique for producing rigid polyurethane foam (RPUF) composites, but it also offers a way to reuse metallurgical solid waste. Rigid polyurethane (RPUF) composite samples have been prepared with different proportions of iron slag as additives, with a range of 0-25% mass by weight. The process of grinding iron slag microparticles into iron slag nanoparticles powder was accomplished with the use of a high-energy ball mill. The synthesized samples have been characterized using Fourier Transform Infrared Spectroscopy, and Scanning Electron Microscope. Then, their radiation shielding properties were measured by using A hyper-pure germanium detector using point sources 241Am, 133 BA, 152 EU, 137Cs, and 60Co, with an energy range of 0.059-1.408 MeV. Then using Fluka simulation code to validate the results in the energy range of photon energies of 0.0001-100 MeV. The linear attenuation coefficient, mass attenuation coefficient, mean free path, half-value layer and tenth-value layer, were calculated to determine the radiation shielding characteristics of the composite samples. The calculated values are in good agreement with the calculated values. The results of this study showed that the gamma-ray and neutron attenuation parameters of the studied polyurethane composite samples have improved. Moreover, the effect of iron slag not only increases the gamma-ray attenuation shielding properties but also enhances compressive strength and the thermal stability. Which encourages us to use polyurethane iron-slag composite foam in sandwich panel manufacturing as walls to provide protection from radiation and also heat insulation.

[Health Risk Assessment of Heavy Metals in Soils of a City in Guangdong Province Based on Source Oriented and Monte Carlo Models]

Taking a city in Guangdong Province as the research area, the concentration and spatial distribution characteristics of heavy metals in the surface soil were studied to clarify the situation of soil heavy metal pollution and priority control factors, providing basic data for the prevention and control of soil heavy metal pollution in the city. The content characteristics of heavy metals in 221 soil samples in the city were analyzed, and the potential health risk assessment and source analysis were carried out through the Monte Carlo model, the potential health risk assessment (HRA) model, and the PMF receptor model. It was found that heavy metals ω(As), ω(Hg), ω(Cd), ω(Pb), ω(Cr), ω(Cu), ω(Ni), and ω(Zn) in the soil of the city were 18.16, 0.43, 1.46, 68.57, 98.34, 64.19, 26.53, and 257.32 mg·kg-1, respectively, with a moderate to high degree of variation. Except for Ni concentration, the soil concentrations of other heavy metal elements exceeded the background values of soil in Guangdong Province to a certain extent, and the concentrations of Cd and Zn exceeded the national secondary standards, resulting in severe heavy metal pollution; the main sources of heavy metals were industrial sources, and natural parent materials, lead battery manufacturing, transportation, artificial cultivation, and pesticide and fertilizer inputs also had an undeniable impact on the accumulation of heavy metals in the soil. Heavy metals in the soil had a certain degree of tolerable carcinogenic health risk for both children and adults, whereas non-carcinogenic risks could be ignored. The potential health risk of children was greater than that of adults, and the main exposure route was through oral intake. The input sources of pesticides and fertilizers and As should be the main controlling factors for the health risks of heavy metals in the city's soil, followed by mixed sources and Cr. There were differences in the spatial distribution characteristics and relative pollution levels of heavy metals, and it is necessary to deepen zoning monitoring and control, strengthen soil pollution prevention and control, and reduce human input of heavy metals in soil.

IOeRT conventional and FLASH treatment planning system implementation exploiting fast GPU Monte Carlo: The case of breast cancer

Partial breast irradiation for the treatment of early-stage breast cancer patients can be performed by means of Intra Operative electron Radiation Therapy (IOeRT). One of the main limitations of this technique is the absence of a treatment planning system (TPS) that could greatly help in ensuring a proper coverage of the target volume during irradiation. An IOeRT TPS has been developed using a fast Monte Carlo (MC) and an ultrasound imaging system to provide the best irradiation strategy (electron beam energy, applicator position and bevel angle) and to facilitate the optimisation of dose prescription and delivery to the target volume while maximising the organs at risk sparing. The study has been performed in silico, exploiting MC simulations of a breast cancer treatment. Ultrasound-based input has been used to compute the absorbed dose maps in different irradiation strategies and a quantitative comparison between the different options was carried out using Dose Volume Histograms. The system was capable of exploring different beam energies and applicator positions in few minutes, identifying the best strategy with an overall computation time that was found to be completely compatible with clinical implementation. The systematic uncertainty related to tissue deformation during treatment delivery with respect to imaging acquisition was taken into account. The potential and feasibility of a GPU based full MC TPS implementation of IOeRT breast cancer treatments has been demonstrated in-silico. This long awaited tool will greatly improve the treatment safety and efficacy, overcoming the limits identified within the clinical trials carried out so far.

Dosimetric evaluation in Helical TomoTherapy for lung SBRT using Monte Carlo-based independent dose verification software

PURPOSE

To elucidate the dosimetric errors caused by a model-based algorithm in lung stereotactic body radiation therapy (SBRT) with Helical TomoTherapy (HT) using Monte Carlo (MC)-based dose verification software.

METHODS

For 38 plans of lung SBRT, the dose calculation accuracy of a treatment planning system (TPS) of HT was compared with the results of DoseCHECK, the commercial MC-based independent verification software. The following indices were extracted to evaluate the correlation of dosimetric errors: (1) target volume, (2) average computed tomography (CT) value of the planning target volume (PTV) margin, and (3) average CT value of surrounding 2-mm area of the PTV (PTV ring). Receiver operating characteristic (ROC) analyses determined the threshold for 5% of differences in PTV D95%. Then, the 38 plans were classified into two groups using the cutoff values of ROC analysis for these three indices. Dosimetric differences between groups were statistically compared using the Mann-Whitney U test.

RESULTS

TPS of HT overestimated by more than 5% in the PTV D95% in 16 of 38 plans. The PTV ring showed the strongest correlation with dosimetric differences. The cutoff value for the target volume, the PTV margin, and the PTV ring was 14.7 cc, -754 HU, and -708 HU, respectively. The area under the curve (AUC) for the target volume, the PTV margin, and the PTV ring were 0.835, 0.878, and 0.932, respectively. Dosimetric errors more than 5% were observed when the PTV volume was less than 15 cc or when the CT value around the target was less than -700 HU.

CONCLUSION

The TPS of HT might overestimate the PTV dose by more than 5% if any the three indices in this study were below threshold. Therefore, independent verification with an MC-based algorithm should be strongly recommended for lung SBRT in HT.

Hepatic steatosis modeling and MRI signal simulations for comparison of single- and dual-R2* models and estimation of fat fraction at 1.5T and 3T

BACKGROUND AND OBJECTIVE

Magnetic resonance imaging (MRI) has emerged as a noninvasive clinical tool for assessment of hepatic steatosis. Multi-spectral fat-water MRI models, incorporating single or dual transverse relaxation decay rate(s) (R2*) have been proposed for accurate fat fraction (FF) estimation. However, it is still unclear whether single- or dual-R2* model accurately mimics in vivo signal decay for precise FF estimation and the impact of signal-to-noise ratio (SNR) on each model performance. Hence, this study aims to construct virtual steatosis models and synthesize MRI signals with different SNRs to systematically evaluate the accuracy of single- and dual-R2* models for FF and R2* estimations at 1.5T and 3.0T.

METHODS

Realistic hepatic steatosis models encompassing clinical FF range (0-60 %) were created using morphological features of fat droplets (FDs) extracted from human liver biopsy samples. MRI signals were synthesized using Monte Carlo simulations for noise-free (SNRideal) and varying SNR conditions (5-100). Fat-water phantoms were scanned with different SNRs to validate simulation results. Fat water toolbox was used to calculate R2* and FF for both single- and dual-R2* models. The model accuracies in R2* and FF estimates were analyzed using linear regression, bias plot and heatmap analysis.

RESULTS

The virtual steatosis model closely mimicked in vivo fat morphology and Monte Carlo simulation produced realistic MRI signals. For SNRideal and moderate-high SNRs, water R2* (R2*W) by dual-R2* and common R2* (R2*com) by single-R2* model showed an excellent agreement with slope close to unity (0.95-1.01) and R2 > 0.98 at both 1.5T and 3.0T. In simulations, the R2*com-FF and R2*W-FF relationships exhibited slopes similar to in vivo calibrations, confirming the accuracy of our virtual models. For SNRideal, fat R2* (R2*F) was similar to R2*W and dual-R2* model showed slightly higher accuracy in FF estimation. However, in the presence of noise, dual-R2* produced higher FF bias with decreasing SNR, while leading to only marginal improvement for high SNRs and in regions dominated by fat and water. In contrast, single-R2* model was robust and produced accurate FF estimations in simulations and phantom scans with clinical SNRs.

CONCLUSION

Our study demonstrates the feasibility of creating virtual steatosis models and generating MRI signals that mimic in vivo morphology and signal behavior. The single-R2* model consistently produced lower FF bias for clinical SNRs across entire FF range compared to dual-R2* model, hence signifying that single-R2* model is optimal for assessing hepatic steatosis.

RapidBrachyTG43: A Geant4-based TG-43 parameter and dose calculation module for brachytherapy dosimetry

BACKGROUND

The AAPM TG-43U1 formalism remains the clinical standard for dosimetry of low- and high-energy γ $\gamma$ -emitting brachytherapy sources. TG-43U1 and related reports provide consensus datasets of TG-43 parameters derived from various published measured data and Monte Carlo simulations. These data are used to perform standardized and fast dose calculations for brachytherapy treatment planning.

PURPOSE

Monte Carlo TG-43 dosimetry parameters are commonly derived to characterize novel brachytherapy sources. RapidBrachyTG43 is a module of RapidBrachyMCTPS, a Monte Carlo-based treatment planning system, designed to automate this process, requiring minimal user input to prepare Geant4-based Monte Carlo simulations for a source. RapidBrachyTG43 may also perform a TG-43 dose to water-in-water calculation for a plan, substantially accelerating the same calculation performed using RapidBrachyMCTPS's Monte Carlo dose calculation engine.

METHODS

TG-43 parametersS K / A $S_K/A$ , Λ $\Lambda$ ,g L ( r ) $g_L(r)$ , andF ( r , θ ) $F(r,\theta)$ were calculated using three commercial source models, one each of125 $^{125}$ I,192 $^{192}$ Ir, and60 $^{60}$ Co, and were benchmarked to published data. TG-43 dose to water was calculated for a clinical breast brachytherapy plan and was compared to a Monte Carlo dose calculation with all patient tissues, air, and catheters set to water.

RESULTS

TG-43 parameters for the three simulated sources agreed with benchmark datasets within tolerances specified by the High Energy Brachytherapy Dosimetry working group. A gamma index comparison between the TG-43 and Monte Carlo dose-to-water calculations with a dose difference and difference to agreement criterion of 1%/1 mm yielded a 98.9% pass rate, with all relevant dose volume histogram metrics for the plan agreeing within 1%. Performing a TG-43-based dose calculation provided an acceleration of dose-to-water calculation by a factor of 165.

CONCLUSIONS

Determination of TG-43 parameter data for novel brachytherapy sources may now be facilitated by RapidBrachyMCTPS. These parameter datasets and existing consensus or published datasets may also be used to determine the TG-43 dose for a plan in RapidBrachyMCTPS.

Exploring the evolution of circular polarized light backscattered from turbid tissue-like disperse medium utilizing generalized Monte Carlo modeling approach with a combined use of Jones and Stokes-Mueller formalisms

Significance

Phase retardation of circularly polarized light (CPL), backscattered by biological tissue, is used extensively for quantitative evaluation of cervical intraepithelial neoplasia, presence of senile Alzheimer's plaques, and characterization of biotissues with optical anisotropy. The Stokes polarimetry and Mueller matrix approaches demonstrate high potential in definitive non-invasive cancer diagnosis and tissue characterization. The ultimate understanding of CPL interaction with tissues is essential for advancing medical diagnostics, optical imaging, therapeutic applications, and the development of optical instruments and devices.

Aim

We investigate propagation of CPL within turbid tissue-like scattering medium utilizing a combination of Jones and Stokes-Mueller formalisms in a Monte Carlo (MC) modeling approach. We explore the fundamentals of CPL memory effect and depolarization formation.

Approach

The generalized MC computational approach developed for polarization tracking within turbid tissue-like scattering medium is based on the iterative solution of the Bethe-Salpeter equation. The approach handles helicity response of CPL scattered in turbid medium and provides explicit expressions for assessment of its polarization state.

Results

Evolution of CPL backscattered by tissue-like medium at different conditions of observation in terms of source-detector configuration is assessed quantitatively. The depolarization of light is presented in terms of the coherence matrix and Stokes-Mueller formalism. The obtained results reveal the origins of the helicity flip of CPL depending on the source-detector configuration and the properties of the medium and are in a good agreement with the experiment.

Conclusions

By integrating Jones and Stokes-Mueller formalisms, the combined MC approach allows for a more complete representation of polarization effects in complex optical systems. The developed model is suitable to imitate propagation of the light beams of different shape and profile, including Gaussian, Bessel, Hermite-Gaussian, and Laguerre-Gaussian beams, within tissue-like medium. Diverse configuration of the experimental conditions, coherent properties of light, and peculiarities of polarization can be also taken into account.

Spatial sensitivity distribution assessment and Monte Carlo simulations for needle-based bioimpedance imaging during venipuncture using the finite element method

Despite being among the most common medical procedures, needle insertions suffer from a high error rate. Impedance measurements using electrode-equipped needles offer promise for improved tissue targeting and reduced errors. Impedance visualization usually requires an extensive pre-measured impedance dataset for tissue differentiation and knowledge of the electric fields contributing to the resulting impedances. This work presents two finite element simulation approaches for both problems. The first approach describes the generation of a multitude of impedances with Monte Carlo simulations for both, homogeneous and inhomogeneous tissue to circumvent the need to rely on previously measured data. These datasets could be used for tissue discrimination. The second method describes the simulation of the spatial sensitivity distribution of an electrode layout. Two singularity analysis methods were employed to determine the bulk of the sensitivity within a finite volume, which in turn enables consistent 3D visualization. The modeled electrode layout consists of 12 electrodes radially placed around a hypodermic needle. Electrical excitation was simulated using two neighboring electrodes for current carriage and voltage pickup, which resulted in 12 distinct bipolar excitation states. Both, the impedance simulations and the respective singularity analysis methods were compared with each other. The results show that the statistical spread of impedances is highly dependent on the tissue type and its inhomogeneities. The bounded bulk of sensitivities of both methods are of similar extent and symmetry. Future models should incorporate more detailed tissue properties such as anisotropy or changing material properties due to tissue deformation to gain more accurate predictions.

A Monte Carlo simulation-based decision support system for radiation oncologists in the treatment of glioblastoma multiforme

In the present research, we have developed a model-based crisp logic function statistical classifier decision support system supplemented with treatment planning systems for radiation oncologists in the treatment of glioblastoma multiforme (GBM). This system is based on Monte Carlo radiation transport simulation and it recreates visualization of treatment environments on mathematical anthropomorphic brain (MAB) phantoms. Energy deposition within tumour tissue and normal tissues are graded by quality audit factors which ensure planned dose delivery to tumour site thereby minimising damages to healthy tissues. The proposed novel methodology predicts tumour growth response to radiation therapy from a patient-specific medicine quality audit perspective. Validation of the study was achieved by recreating thirty-eight patient-specific mathematical anthropomorphic brain phantoms of treatment environments by taking into consideration density variation and composition of brain tissues. Dose computations accomplished through water phantom, tissue-equivalent head phantoms are neither cost-effective, nor patient-specific customized and is often less accurate. The above-highlighted drawbacks can be overcome by using open-source Electron Gamma Shower (EGSnrc) software and clinical case reports for MAB phantom synthesis which would result in accurate dosimetry with due consideration to the time factors. Considerable dose deviations occur at the tumour site for environments with intraventricular glioblastoma, haematoma, abscess, trapped air and cranial flaps leading to quality factors with a lower logic value of 0. Logic value of 1 depicts higher dose deposition within healthy tissues and also leptomeninges for majority of the environments which results in radiation-induced laceration.

Deep learning for high-resolution dose prediction in high dose rate brachytherapy for breast cancer treatment

Objective.Monte Carlo (MC) simulations are the benchmark for accurate radiotherapy dose calculations, notably in patient-specific high dose rate brachytherapy (HDR BT), in cases where considering tissue heterogeneities is critical. However, the lengthy computational time limits the practical application of MC simulations. Prior research used deep learning (DL) for dose prediction as an alternative to MC simulations. While accurate dose predictions akin to MC were attained, graphics processing unit limitations constrained these predictions to large voxels of 3 mm × 3 mm × 3 mm. This study aimed to enable dose predictions as accurate as MC simulations in 1 mm × 1 mm × 1 mm voxels within a clinically acceptable timeframe.Approach.Computed tomography scans of 98 breast cancer patients treated with Iridium-192-based HDR BT were used: 70 for training, 14 for validation, and 14 for testing. A new cropping strategy based on the distance to the seed was devised to reduce the volume size, enabling efficient training of 3D DL models using 1 mm × 1 mm × 1 mm dose grids. Additionally, novel DL architecture with layer-level fusion were proposed to predict MC simulated dose to medium-in-medium (Dm,m). These architectures fuse information from TG-43 dose to water-in-water (Dw,w) with patient tissue composition at the layer-level. Different inputs describing patient body composition were investigated.Main results.The proposed approach demonstrated state-of-the-art performance, on par with the MCDm,mmaps, but 300 times faster. The mean absolute percent error for dosimetric indices between the MC and DL-predicted complete treatment plans was 0.17% ± 0.15% for the planning target volumeV100, 0.30% ± 0.32% for the skinD2cc, 0.82% ± 0.79% for the lungD2cc, 0.34% ± 0.29% for the chest wallD2ccand 1.08% ± 0.98% for the heartD2cc.Significance.Unlike the time-consuming MC simulations, the proposed novel strategy efficiently converts TG-43Dw,wmaps into preciseDm,mmaps at high resolution, enabling clinical integration.

Active and passive dosimetry for beta-emitting radiopharmaceutical therapy agents in a custom SPECT/CT compatible phantom

OBJECTIVE

This work introduces a novel approach to performing active and passive dosimetry for beta-emitting radionuclides in solution using common dosimeters. The measurements are compared to absorbed dose to water (Dw) estimates from Monte Carlo (MC) simulations. We present a method for obtaining absorbed dose to water, measured with dosimeters, from beta-emitting radiopharmaceutical agents using a custom SPECT/CT compatible phantom for validation of Monte Carlo based absorbed dose to water estimates. APPROACH: A cylindrical, acrylic SPECT/CT compatible phantom capable of housing an IBA EFD diode, IBA RAZOR diode, Exradin A20-375 parallel plate ion chamber, unlaminated EBT3 film, and thin TLD100 microcubes was constructed for the purpose of measuring absorbed dose to water from solutions of common beta-emitting radiopharmaceutical therapy agents. The phantom is equipped with removable detector inserts that allow for multiple configurations and is designed to be used for validation of image-based absorbed dose estimates with detector measurements. Two experiments with 131I and one experiment with 177Lu were conducted over extended measurement intervals with starting activities of approximately 150 - 350 MBq. Measurement data was compared to Monte Carlo simulations using the egs_chamber user code in EGSnrc 2019. MAIN RESULTS: Agreement within k = 1 uncertainty between measured and MC predicted Dwwas observed for all dosimeters, except the IBA RAZOR diode and the A20-375 ion chamber during the second 131I experiment. Despite the agreement, the measured values generally lower than predicted values by 5 - 15 %. The uncertainties at k=1 remain large (5 - 30 % depending on the dosimeter) relative to other forms of radiation therapy. SIGNIFICANCE: Despite high uncertainties, the overall agreement between measured and simulated absorbed doses is promising for the use of dosimeter-based RPT measurements in the validation of MC predicted Dw. .

Minimum phantom size for megavoltage photon beam reference dosimetry

BACKGROUND

Water phantoms are required to perform reference dosimetry and beam quality measurements but there are no published studies about the size requirements for such phantoms.

PURPOSE

To investigate, using Monte Carlo techniques, the size requirements for water phantoms used in reference dosimetry and/or to measure the beam quality specifiers% d d ( 10 ) x $\%dd(10)_{\sf x}$ andT P R 10 20 $TPR^{20}_{10}$ .

METHODS

The EGSnrc application DOSXYZnrc is used to calculateD ( 10 ) $D(10)$ , the dose per incident fluence at 10 cm depth in a water phantom irradiated by incident10 × 10 cm 2 $10\,\times \,10 \, {\rm {cm}}^{2}$   beams of60 Co $^{60}{\rm {Co}}$   or 6 MV photons. The water phantom dimensions are varied from30 × 30 × 40 cm 3 $30 \,\times \, 30 \,\times \, 40 \, {\rm {cm}}^3$ to15 × 15 × 22 cm 3 $15 \,\times \, 15 \,\times \, 22 \, {\rm {cm}}^3$ and occasionally smaller. The% d d ( 10 ) x $\%dd(10)_{\sf x}$ andT P R 10 20 $TPR^{20}_{10}$ values are also calculated with care being taken to distinguishT P R 10 20 $TPR^{20}_{10}$ results when using Method A (changing depth of water in phantom) and Method B (moving entire phantom). Typical statistical uncertainties are 0.03%.

RESULTS

Phantom dimensions have only minor effects for phantoms larger than20 × 20 × 25 cm 3 $20 \,\times \, 20 \,\times \, 25 \, {\rm {cm}}^3$ . A table of corrections to the dose at 10 cm depth in10 × 10 cm 2 $10 \,\times \, 10 \, {\rm {cm}}^{2}$   beams of60 Co $^{60}{\rm {Co}}$   or 6 MV photons are provided and range from no correction to 0.75% for a60 Co $^{60}{\rm {Co}}$  beam incident on a20 × 20 × 15 cm 3 $20 \,\times \, 20 \,\times \, 15 \, {\rm {cm}}^3$ phantom. There can be distinct differences in theT P R 10 20 $TPR^{20}_{10}$ values measured using Method A or Method B, especially for smaller phantoms. It is explicitly demonstrated that, within ± $\pm$ 0.15%,T P R 10 20 $TPR^{20}_{10}$ values for a30 × 30 × 30 cm 3 $30 \,\times \, 30 \,\times \, 30 \, {\rm {cm}}^3$ phantom measured using Method A or B are independent of source detector distance between 40 and 200 cm.

CONCLUSIONS

The phantom sizes recommended in the TG-51 and IAEA TRS-398 reference dosimetry protocols are adequate for accurate reference dosimetry and in some cases are even conservative. Correction factors are necessary for accurate measurement of the dose at 10 cm depth in smaller phantoms and these factors are provided. Very accurate beam quality specifiers are not required for reference dosimetry itself, but for specifying beam stability and characteristics it is important to specify phantom sizes and also the method used forT P R 10 20 $TPR^{20}_{10}$  measurements.

TOPAS simulation of photoneutrons in radiotherapy: accuracy and speed with variance reduction

We provide optimal particle split numbers for speeding up TOPAS Monte Carlo simulations of linear accelerator (linac) treatment heads while maintaining accuracy. In addition, we provide a new TOPAS physics module for simulating photoneutron production and transport. TOPAS simulation of a Siemens Oncor linac was used to determine the optimal number of splits for directional bremsstrahlung splitting as a function of the field size for 6MV and 18MV x-ray beams. The linac simulation was validated against published data of lateral dose profiles and percentage depth-dose curves (PDD) for the largest square field (40cm side). In separate simulations, neutron particle split and the custom TOPAS physics module was used to generate and transport photoneutrons, called "TsPhotoNeutron". Verification of accuracy was performed by comparing simulations with published measurements of: 1) neutron yields as a function of beam energy for thick targets of Al, Cu, Ta, W, Pb and concrete; and 2) photoneutron energy spectrum at 40cm laterally from the isocenter of the linac from an 18MV beam with closed jaws and MLC. The optimal number of splits obtained for directional bremsstrahlung splitting enhanced the computational efficiency by two orders of magnitude. The efficiency decreased with increasing beam energy and field size. Calculated lateral profiles in the central region agreed within 1mm/2% from measured data, PDD curves within 1 mm/1%. For the TOPAS physics module, at a split number of 146, the efficiency of computing photoneutron yields was enhanced by a 27.6 factor, whereas it improved the accuracy over existing Geant4 physics modules. This work provides simulation parameters and a new TOPAS physics module to improve the efficiency and accuracy of TOPAS simulations that involve photonuclear processes occurring in high-Z materials found in linac components, patient devices, and treatment rooms, as well as to explore new therapeutic modalities such as very-high-energy electron therapy.

Implementation of a new EGSnrc particle source class for computed tomography: validation and uncertainty quantification

Objective. Personalized dose monitoring and risk management are of increasing significance with the growing number of computer tomography (CT) examinations. These require high-quality Monte Carlo (MC) simulations that are of the utmost importance for the new developments in personalized CT dosimetry. This work aims to extend the MC framework EGSnrc source code with a new particle source. This, in turn, allows CT-scanner-specific dose and image calculations for any CT scanner. The novel method can be used with all modern EGSnrc user codes, particularly for the simulation of the effective dose based on DICOM images and the calculation of CT images.Approach. The new particle source can be used with input data derived by the user. The input data can be generated by the user based on a previously developed method for the experimental characterization of any CT scanner (doi.org/10.1016/j.ejmp.2015.09.006). Furthermore, the new particle source was benchmarked by air kerma measurements in an ionization chamber at a clinical CT scanner. For this, the simulated angular distribution and attenuation characteristics were compared to measurements to verify the source output free in air. In a second validation step, simulations of air kerma in a homogenous cylindrical and an anthropomorphic thorax phantom were performed and validated against experimentally determined results. A detailed uncertainty evaluation of the simulated air kerma values was developed.Main results. We successfully implemented a new particle source class for the simulation of realistic CT scans. This method can be adapted to any CT scanner. For the attenuation characteristics, there was a maximal deviation of 6.86% between the measurement and the simulation. The mean deviation for all tube voltages was 2.36% (σ= 1.6%). For the phantom measurements and simulations, all the values agreed within 5.0%. The uncertainty evaluation resulted in an uncertainty of 5.5% (k=1).

Joint EURADOS-EANM initiative for an advanced computational framework for the assessment of external dose rates from nuclear medicine patients

BACKGROUND

In order to ensure adequate radiation protection of critical groups such as staff, caregivers and the general public coming into proximity of nuclear medicine (NM) patients, it is necessary to consider the impact of the radiation emitted by the patients during their stay at the hospital or after leaving the hospital. Current risk assessments are based on ambient dose rate measurements in a single position at a specified distance from the patient and carried out at several time points after administration of the radiopharmaceutical to estimate the whole-body retention. The limitations of such an approach are addressed in this study by developing and validating a more advanced computational dosimetry approach using Monte Carlo (MC) simulations in combination with flexible and realistic computational phantoms and time activity distribution curves from reference biokinetic models.

RESULTS

Measurements of the ambient dose rate equivalent Ḣ*(10) at 1 m from the NM patient have been successfully compared against MC simulations with 5 different codes using the ICRP adult reference computational voxel phantoms, for typical clinical procedures with 99mTc-HDP/MDP, 18FDG and Na131I. All measurement data fall in the 95% confidence intervals, determined for the average simulated results. Moreover, the different MC codes (MCNP-X, PHITS, GATE, GEANT4, TRIPOLI-4®) have been compared for a more realistic scenario where the effective dose rate Ė of an exposed individual was determined in positions facing and aside the patient model at 30 cm, 50 cm and 100 cm. The variation between codes was lower than 8% for all the radiopharmaceuticals at 1 m, and varied from 5 to 16% for the face-to face and side-by-side configuration at 30 cm and 50 cm. A sensitivity study on the influence of patient model morphology demonstrated that the relative standard deviation of Ḣ*(10) at 1 m for the range of included patient models remained under 16% for time points up to 120 min post administration.

CONCLUSIONS

The validated computational approach will be further used for the evaluation of effective dose rates per unit administered activity for a variety of close-contact configurations and a range of radiopharmaceuticals as part of risk assessment studies. Together with the choice of appropriate dose constraints this would facilitate the setting of release criteria and patient restrictions.

Development and characterization of the first proton minibeam system for single-gantry proton facility

BACKGROUND

Minibeam represents a preclinical spatially fractionated radiotherapy modality with great translational potential. The advantage lies in its high therapeutic index (compared to GRID and LATTICE) and ability to treat at greater depth (compared to microbeam). Proton minibeam radiotherapy (pMBRT) is a synergy of proton and minibeam. While the single-gantry proton facility has gained popularity due to its affordability and compact design, it often has limited beam time available for research purposes. Conversely, given the current requirement of pMBRT on specific minibeam hardware collimators, necessitates a reproducible and fast setup to minimize pMBRT treatment time and streamline the switching time between pMBRT and conventional treatment for clinically translation.

PURPOSE

The contribution of this work is the development and characterization of the first pMBRT system tailored for single-gantry proton facility. The system allows for efficient and reproducible plug-and-play setup, achievable within minutes.

METHODS

The single room pMBRT system is constructed based on IBA ProteusONE proton machine. The end of nozzle is attached with beam modifying accessories though an accessory drawer. A small snout is attached to the accessory drawer and used to hold apertures and range shifters. The minibeam aperture consists of two components: a fitting ring and an aperture body. Three minibeam apertures were manufactured. The first-generation apertures underwent qualitatively analysis with film, and the second generation aperture underwent more comprehensive quantitative measurement. The reproducibility of the setup is accessed, and the film measurements are performed to characterize the pMBRT system in cross validation with Monte Carlo (MC) simulations.

RESULTS

We presented initial results of large field pMBRT aperture and the film measurements indicates the effect of source-to-isocenter distance = 930 cm in Y proton scanning direction. Consistent with TOPAS MC simulation, the dose uniformity of pMBRT field <2 cm is demonstrated to be better than 2%, rendering its suitability for pre-clinical studies. Subsequently, we developed the second generation of aperture with five slits and characterized the aperture with film dosimetry studies and compared the results to the benchmark MC. Comprehensive film measurements were also performed to evaluate the effect of divergence, air gap and gantry-angle dependency and repeatability and revealing a consistent performance within 5%. Furthermore, the 2D gamma analysis indicated a passing rate exceeding 99% using 3% dose difference and 0.2 mm distance agreement criteria. We also establish the peak valley dose ratio and the depth dose profile measurements, and the results are within 10% from MC simulation.

CONCLUSIONS

We have developed the first pMBRT system tailored for a single-gantry proton facility, which has demonstrated accuracy in benchmark with MC simulations, and allows for efficient plug-and-play setup, emphasizing efficiency.

Dosimetric validation of SmART-RAD Monte Carlo modelling for x-ray cabinet radiobiology irradiators

Objective. Accuracy and reproducibility in the measurement of radiation dose and associated reporting are critically important for the validity of basic and preclinical radiobiological studies performed with kilovolt x-ray radiation cabinets. This is essential to enable results of radiobiological studies to be repeated, as well as enable valid comparisons between laboratories. In addition, the commonly used single point dose value hides the 3D dose heterogeneity across the irradiated sample. This is particularly true for preclinical rodent models, and is generally difficult to measure directly. Radiation transport simulations integrated in an easy to use application could help researchers improve quality of dosimetry and reporting.Approach. This paper describes the use and dosimetric validation of a newly-developed Monte Carlo (MC) tool, SmART-RAD, to simulate the x-ray field in a range of standard commercial x-ray cabinet irradiators used for preclinical irradiations. Comparisons are made between simulated and experimentally determined dose distributions for a range of configurations to assess the potential use of this tool in determining dose distributions through samples, based on more readily available air-kerma calibration point measurements.Main results. Simulations gave very good dosimetric agreement with measured depth dose distributions in phantoms containing both water and bone equivalent materials. Good spatial and dosimetric agreement between simulated and measured dose distributions was obtained when using beam-shaping shielding.Significance. The MC simulations provided by SmART-RAD provide a useful tool to go from a limited number of dosimetry measurements to detailed 3D dose distributions through a non-homogeneous irradiated sample. This is particularly important when trying to determine the dose distribution in more complex geometries. The use of such a tool can improve reproducibility and dosimetry reporting in preclinical radiobiological research.

Accuracy of patient-specific CT organ doses from Monte Carlo simulations: influence of CT-based voxel models

Monte Carlo simulations using patient CT images as input are the gold standard to perform patient-specific dosimetry. However, in standard clinical practice patient's CT images are limited to the reconstructed CT scan range. In this study, organ dose calculations were performed with ImpactMC for chest and cardiac CT using whole-body and anatomy-specific voxel models to estimate the accuracy of CT organ doses based on the latter model. When the 3D patient model is limited to the CT scan range, CT organ doses from Monte Carlo simulations are the most accurate for organs entirely in the field of view. For these organs only the radiation dose related to scatter from the rest of the body is not incorporated. For organs lying partially outside the field of view organ doses are overestimated by not accounting for the non-irradiated tissue mass. This overestimation depends strongly on the amount of the organ volume located outside the field of view. To get a more accurate estimation of the radiation dose to these organs, the ICRP reference organ masses and densities could form a solution. Except for the breast, good agreement in dose was found for most organs. Voxel models generated from clinical CT examinations do not include the overscan in the z-direction. The availability of whole-body voxel models allowed to study this influence as well. As expected, overscan induces slightly higher organ doses.

Optimal fibre length and maximum isometric force are the most influential parameters when modelling muscular adaptations to unloading using Hill-type muscle models

Introduction: Spaceflight is associated with severe muscular adaptations with substantial inter-individual variability. A Hill-type muscle model is a common method to replicate muscle physiology in musculoskeletal simulations, but little is known about how the underlying parameters should be adjusted to model adaptations to unloading. The aim of this study was to determine how Hill-type muscle model parameters should be adjusted to model disuse muscular adaptations. Methods: Isokinetic dynamometer data were taken from a bed rest campaign and used to perform tracking simulations at two knee extension angular velocities (30°·s-1 and 180°·s-1). The activation and contraction dynamics were solved using an optimal control approach and direct collocation method. A Monte Carlo sampling technique was used to perturb muscle model parameters within physiological boundaries to create a range of theoretical and feasible parameters to model muscle adaptations. Results: Optimal fibre length could not be shortened by more than 67% and 61% for the knee flexors and non-knee muscles, respectively. Discussion: The Hill-type muscle model successfully replicated muscular adaptations due to unloading, and recreated salient features of muscle behaviour associated with spaceflight, such as altered force-length behaviour. Future researchers should carefully adjust the optimal fibre lengths of their muscle-models when trying to model adaptations to unloading, particularly muscles that primarily operate on the ascending and descending limbs of the force-length relationship.

Reinforcement Learning Algorithms and Applications in Healthcare and Robotics: A Comprehensive and Systematic Review

Reinforcement learning (RL) has emerged as a dynamic and transformative paradigm in artificial intelligence, offering the promise of intelligent decision-making in complex and dynamic environments. This unique feature enables RL to address sequential decision-making problems with simultaneous sampling, evaluation, and feedback. As a result, RL techniques have become suitable candidates for developing powerful solutions in various domains. In this study, we present a comprehensive and systematic review of RL algorithms and applications. This review commences with an exploration of the foundations of RL and proceeds to examine each algorithm in detail, concluding with a comparative analysis of RL algorithms based on several criteria. This review then extends to two key applications of RL: robotics and healthcare. In robotics manipulation, RL enhances precision and adaptability in tasks such as object grasping and autonomous learning. In healthcare, this review turns its focus to the realm of cell growth problems, clarifying how RL has provided a data-driven approach for optimizing the growth of cell cultures and the development of therapeutic solutions. This review offers a comprehensive overview, shedding light on the evolving landscape of RL and its potential in two diverse yet interconnected fields.

Aleatoric and epistemic uncertainty extraction of patient-specific deep learning-based dose predictions in LDR prostate brachytherapy

Objective.In brachytherapy, deep learning (DL) algorithms have shown the capability of predicting 3D dose volumes. The reliability and accuracy of such methodologies remain under scrutiny for prospective clinical applications. This study aims to establish fast DL-based predictive dose algorithms for low-dose rate (LDR) prostate brachytherapy and to evaluate their uncertainty and stability.Approach.Data from 200 prostate patients, treated with125I sources, was collected. The Monte Carlo (MC) ground truth dose volumes were calculated with TOPAS considering the interseed effects and an organ-based material assignment. Two 3D convolutional neural networks, UNet and ResUNet TSE, were trained using the patient geometry and the seed positions as the input data. The dataset was randomly split into training (150), validation (25) and test (25) sets. The aleatoric (associated with the input data) and epistemic (associated with the model) uncertainties of the DL models were assessed.Main results.For the full test set, with respect to the MC reference, the predicted prostateD90metric had mean differences of -0.64% and 0.08% for the UNet and ResUNet TSE models, respectively. In voxel-by-voxel comparisons, the average global dose difference ratio in the [-1%, 1%] range included 91.0% and 93.0% of voxels for the UNet and the ResUNet TSE, respectively. One forward pass or prediction took 4 ms for a 3D dose volume of 2.56 M voxels (128 × 160 × 128). The ResUNet TSE model closely encoded the well-known physics of the problem as seen in a set of uncertainty maps. The ResUNet TSE rectum D2cchad the largest uncertainty metric of 0.0042.Significance.The proposed DL models serve as rapid dose predictors that consider the patient anatomy and interseed attenuation effects. The derived uncertainty is interpretable, highlighting areas where DL models may struggle to provide accurate estimations. The uncertainty analysis offers a comprehensive evaluation tool for dose predictor model assessment.

Characterizing Microheterogeneity in Liquid Mixtures via Local Density Fluctuations

We present a novel approach to characterize and quantify microheterogeneity and microphase separation in computer simulations of complex liquid mixtures. Our post-processing method is based on local density fluctuations of the different constituents in sampling spheres of varying size. It can be easily applied to both molecular dynamics (MD) and Monte Carlo (MC) simulations, including periodic boundary conditions. Multidimensional correlation of the density distributions yields a clear picture of the domain formation due to the subtle balance of different interactions. We apply our approach to the example of force field molecular dynamics simulations of imidazolium-based ionic liquids with different side chain lengths at different temperatures, namely 1-ethyl-3-methylimidazolium chloride, 1-hexyl-3-methylimidazolium chloride, and 1-decyl-3-methylimidazolium chloride, which are known to form distinct liquid domains. We put the results into the context of existing microheterogeneity analyses and demonstrate the advantages and sensitivity of our novel method. Furthermore, we show how to estimate the configuration entropy from our analysis, and we investigate voids in the system. The analysis has been implemented into our program package TRAVIS and is thus available as free software.

Numerical optimization of longitudinal collimator geometry for novel x-ray field

OBJECTIVE

A novel X-ray field produced by an ultrathin conical target is described in the literature. However, the optimal design for an associated collimator remains ambiguous. Current optimization methods using Monte Carlo calculations restrict the efficiency and robustness of the design process. A more generic optimization method that reduces parameter constraints while minimizing computational load is necessary. A numerical method for optimizing the longitudinal collimator hole geometry for a cylindrically-symmetrical X-ray tube is demonstrated and compared to Monte Carlo calculations. Approach: The X-ray phase space was modelled as a four-dimensional histogram differential in photon initial position, final position, and photon energy. The collimator was modelled as a stack of thin washers with varying inner radii. Simulated annealing was employed to optimize this set of inner radii according to various objective functions calculated on the photon flux at a specified plane. Main results: The analytical transport model used for optimization was validated against Monte Carlo calculations using Geant4 via its wrapper, TOPAS. Optimized collimators and the resulting photon flux profiles are presented for three focal spot sizes and five positions of the source. Optimizations were performed with multiple objective functions based on various weightings of precision, intensity, and field flatness metrics. Finally, a select set of these optimized collimators, plus a parallel-hole collimator for comparison, were modelled in TOPAS. The evolution of the radiation field profiles are presented for various positions of the source for each collimator. Significance: This novel optimization strategy proved consistent and robust across the range of X-ray tube settings regardless of the optimization starting point. Common collimator geometries were re-derived using this algorithm while simultaneously optimizing geometry-specific parameters. The advantages of this strategy over iterative Monte Carlo-based techniques, including computational efficiency, radiation source-specificity, and solution flexibility, make it a desirable optimization method for complex irradiation geometries. .

Evaluation of monolithic crystal detector with dual-ended readout utilizing multiplexing method

Objective.Monolithic crystal detectors are increasingly being applied in positron emission tomography (PET) devices owing to their excellent depth-of-interaction (DOI) resolution capabilities and high detection efficiency. In this study, we constructed and evaluated a dual-ended readout monolithic crystal detector based on a multiplexing method.Approach.We employed two 12 × 12 silicon photomultiplier (SiPM) arrays for readout, and the signals from the 12 × 12 array were merged into 12 X and 12 Y channels using channel multiplexing. In 2D reconstruction, three methods based on the centre of gravity (COG) were compared, and the concept of thresholds was introduced. Furthermore, a light convolutional neural network (CNN) was employed for testing. To enhance depth localization resolution, we proposed a method by utilizing the mutual information from both ends of the SiPMs. The source width and collimation effect were simulated using GEANT4, and the intrinsic spatial resolution was separated from the measured values.Main results.At an operational voltage of 29 V for the SiPM, an energy resolution of approximately 12.5 % was achieved. By subtracting a 0.8 % threshold from the total energy in every channel, a 2D spatial resolution of approximately 0.90 mm full width at half maximum (FWHM) can be obtained. Furthermore, a higher level of resolution, approximately 0.80 mm FWHM, was achieved using a CNN, with some alleviation of edge effects. With the proposed DOI method, a significant 1.36 mm FWHM average DOI resolution can be achieved. Additionally, it was found that polishing and black coating on the crystal surface yielded smaller edge effects compared to a rough surface with a black coating.Significance.The introduction of a threshold in COG method and a dual-ended readout scheme can lead to excellent spatial resolution for monolithic crystal detectors, which can help to develop PET systems with both high sensitivity and high spatial resolution.

Fano cavity test and investigation of the response of the Roos chamber irradiated by proton beams in perpendicular magnetic fields up to 1 T

Objective. The aim of this work is to investigate the response of the Roos chamber (type 34001) irradiated by clinical proton beams in magnetic fields.Approach. At first, a Fano test was implemented in Monte Carlo software package GATE version 9.2 (based on Geant4 version 11.0.2) using a cylindrical slab geometry in a magnetic field up to 1 T. In accordance to an experimental setup (Fuchset al2021), the magnetic field correction factorskQB⃗of the Roos chamber were determined at different energies up to 252 MeV and magnetic field strengths up to 1 T, by separately simulating the ratios of chamber signalsMQ/MQB⃗,without and with magnetic field, and the dose-conversion factorsDw,QB⃗/Dw,Qin a small cylinder of water, with and without magnetic field. Additionally, detailed simulations were carried out to understand the observed magnetic field dependence.Main results. The Fano test was passed with deviations smaller than 0.25% between 0 and 1 T. The ratios of the chamber signals show both energy and magnetic field dependence. The maximum deviation of the dose-conversion factors from unity of 0.22% was observed at the lowest investigated proton energy of 97.4 MeV andB⃗= 1 T. The resultingkQB⃗factors increase initially with the applied magnetic field and decrease again after reaching a maximum at around 0.5 T; except for the lowest 97.4 MeV beam that show no observable magnetic field dependence. The deviation from unity of the factors is also larger for higher proton energies, where the maximum lies at 1.0035(5), 1.0054(7) and 1.0069(7) for initial energies ofE0= 152, 223.4 and 252 MeV, respectively.Significance. Detailed Monte Carlo studies showed that the observed effect can be mainly attributed to the differences in the transport of electrons produced both outside and inside of the air cavity in the presence of a magnetic field.

Uncertainty-aware image classification on 3D CT lung

Early detection is crucial for lung cancer to prolong the patient's survival. Existing model architectures used in such systems have shown promising results. However, they lack reliability and robustness in their predictions and the models are typically evaluated on a single dataset, making them overconfident when a new class is present. With the existence of uncertainty, uncertain images can be referred to medical experts for a second opinion. Thus, we propose an uncertainty-aware framework that includes three phases: data preprocessing and model selection and evaluation, uncertainty quantification (UQ), and uncertainty measurement and data referral for the classification of benign and malignant nodules using 3D CT images. To quantify the uncertainty, we employed three approaches; Monte Carlo Dropout (MCD), Deep Ensemble (DE), and Ensemble Monte Carlo Dropout (EMCD). We evaluated eight different deep learning models consisting of ResNet, DenseNet, and the Inception network family, all of which achieved average F1 scores above 0.832, and the highest average value of 0.845 was obtained using InceptionResNetV2. Furthermore, incorporating the UQ demonstrated significant improvement in the overall model performance. Upon evaluation of the uncertainty estimate, MCD outperforms the other UQ models except for the metric, URecall, where DE and EMCD excel, implying that they are better at identifying incorrect predictions with higher uncertainty levels, which is vital in the medical field. Finally, we show that using a threshold for data referral can greatly improve the performance further, increasing the accuracy up to 0.959.

Monte-Carlo study of contrast-enhanced spectral mammography with cadmium telluride photon-counting x-ray detectors

BACKGROUND

Contrast-enhanced spectral mammography (CESM) with photon-counting x-ray detectors (PCDs) can be used to improve the classification of breast cancers as benign or malignant. Commercially-available PCD-based mammography systems use silicon-based PCDs. Cadmium-telluride (CdTe) PCDs may provide a practical advantage over silicon-based PCDs because they can be implemented as large-area detectors that are more easily adaptable to existing mammography systems.

PURPOSE

The purpose of this work is to optimize CESM implemented with CdTe PCDs and to investigate the influence of the number of energy bins, electronic noise level, pixel size, and anode material on image quality.

METHODS

We developed a Monte Carlo model of the energy-bin-dependent modulation transfer functions (MTFs) and noise power spectra, including spatioenergetic noise correlations. We validated model predictions using a CdTe PCD with analog charge summing for charge-sharing suppression. Using the ideal-observer detectability, we optimized CESM for the task of detecting a 7-mm-diameter iodine nodule embedded in a breast with 50% glandularity. We optimized the tube voltage, beam filtration, and the location of energy thresholds for 50 and 100- μ $\mu$ m pixels, tungsten and molybdenum anodes, and two electronic noise levels. One of the electronic noise levels was that of the experimental system; the other was half that of the experimental system. Optimization was performed for CdTe PCDs with two or three energy bins. We also estimated the impact of anatomic noise due to background parenchymal enhancement and computed the minimum detectable iodine area density in the presence of quantum and anatomic noise.

RESULTS

Model predictions of the MTFs and noise power spectra agreed well with experiment. For optimized systems, adding a third energy bin increased quantum noise levels and reduced detectability by ∼55% compared to two-bin approaches that simply suppress contrast between fibroglandular and adipose tissue. Decreasing the electronic noise standard deviation from 3.4 to 1.7 keV increased iodine detectability by ∼5% and ∼30% for two-bin imaging and three-bin imaging, respectively. After optimizing for tube voltage, beam filtration, and the location of energy thresholds, there was ∼a 3% difference in iodine detectability between molybdenum and tungsten anodes for two-bin imaging, but for three-bin imaging, molybdenum anodes provided up to 14% increase in detectability relative to tungsten anodes. Anatomic noise decreased iodine detectability by 15% to 40%, with greater impact for lower electronic noise settings and larger pixel sizes.

CONCLUSIONS

For CESM implemented with CdTe PCDs, (1) quantitatively-accurate three-material decompositions using three energy bins are associated with substantial increases in quantum noise relative to two-energy-bin approaches that simply suppress contrast between fibroglandular and adipose tissues; (2) tungsten and molybdenum anodes can provide nearly equal iodine detectability for two-bin imaging, but molybdenum provides a modest detectability advantage for three-bin imaging provided that all other technique parameters are optimized; (3) reducing pixel sizes from 100 to 50  μ $\mu$ m can reduce detectability by up to 20% due to charge sharing; (4) anatomic noise due to background parenchymal enhancement is estimated to have a substantial impact on lesion visibility, reducing detectability by approximately 30%.

Forecast of the number of nursing beds per 1000 older people from 2023 to 2025: Empirical quantitative research

AIM

This research aims to offer a reference point for relevant departments to enhance the allocation of ageing resources and formulate policies accordingly.

DESIGN

This study is designed as empirical quantitative research.

METHODS

Data from the National Bureau of Statistics and the Ministry of Civil Affairs regarding older adults (aged≥60) from 2000 to 2022 and nursing beds from 1978 to 2022 were analysed. The differential autoregressive integrated moving averages model and Monte Carlo simulation were used to predict the growth of nursing beds per 1000 older people in China for the Years 2023-2025.

RESULTS

It is projected that from 2023 to 2025, China will experience a further increase in its ageing population, with an average annual growth rate of 3.1%. By 2025, the number of older people in China is expected to surpass 300 million. Additionally, there will be a rise in the number of nursing beds, with an average annual growth rate of 1.9%, leading to a total of 8.79 million nursing beds by 2025. However, due to the rapid growth of the older population, there will be a slight decline in the number of nursing beds per 1000 older people in China, with an average annual growth rate of -1.00%.

History and future of water footprint in the Yangtze River Delta of China

Quantifying the drivers of water footprint evolution in the Yangtze River Delta is vital for the optimization of China's total water consumption. The article aims to decompose and predict the water footprint of the Yangtze River Delta and provide policy recommendations for optimizing water use in the Yangtze River Delta. The paper applies the LMDI method to decompose the water footprint of the Yangtze River Delta and its provinces into five major drivers: water footprint structure, water use intensity, R&D scale, R&D efficiency, and population size. Furthermore, this paper combines scenario analysis and Monte Carlo simulation methods to predict the potential evolution trends of water footprint under the basic, general, and enhanced water conservation scenario, respectively. The results show that (1) the expansion of R&D scale is the main factor promoting the growth of water footprint, the improvement of R&D efficiency, and the reduction of water intensity are the main factors inhibiting the increase of water footprint, and the water footprint structure and population size have less influence on water footprint. (2) The evolution trend of water footprint of each province under three scenarios is different. Compared to the basic scenario, the water footprint decreases more in Shanghai, Zhejiang, and Anhui under the general and enhanced water conservation scenario. The increase in water footprint in Jiangsu under the enhanced scenario is smaller than that of the general water conservation scenario.

New optically stimulated luminescence dosimetry film optimized for energy dependence guided by Monte Carlo simulations

Optically stimulated luminescence (OSL) film dosimeters, based on BaFBr:Eu2+phosphor material, have major dosimetric advantages such as dose linearity, high spatial resolution, film re-usability, and immediate film readout. However, they exhibit an energy-dependent over-response at low photon energies because they are not made of tissue-equivalent materials. In this work, the OSL energy-dependent response was optimized by lowering the phosphor grain size and seeking an optimal choice of phosphor concentration and film thickness to achieve sufficient signal sensitivity. This optimization process combines measurement-based assessments of energy response in narrow x-ray beams with various energy response calculation methods applied to different film metrics. Theoretical approaches and MC dose simulations were used for homogeneous phosphor distributions and for isolated phosphor grains of different dimensions, where the dose in the phosphor grain was calculated. In total 8 OSL films were manufactured with different BaFBr:Eu2+median particle diameters (D50): 3.2μm, 1.5μm and 230 nm and different phosphor concentrations (1.6%, 5.3% and 21.3 %) and thicknesses (from 5.2 to 49μm). Films were irradiated in narrow x-ray spectra (N60, N80, N-150 and N-300) and the signal intensity relative to the nominal dose-to-water value was normalized to Co-60. Finally, we experimentally tested the response of several films in Varian 6MV TrueBeam STx linear accelerator using the following settings: 10 × 10 cm2field, 0deggantry angle, 90 cm SSD, 10 cm depth. The x-ray irradiation experiment reported a reduced energy response for the smallest grain size with an inverse correlation between response and grain size. The N-60 irradiation showed a 43% reduction in the energy over-response when going from 3μm to 230 nm grain size for the 5% phosphor concentration. Energy response calculation using a homogeneous dispersion of the phosphor underestimated the experimental response and was not able to obtain the experimental correlation between grain size and energy response. Isolated grain size modeling combined with MC dose simulations allowed to establish a good agreement with experimental data, and enabled steering the production of optimized OSL-films. The clinical 6 MV beam test confirmed a reduction in energy dependence, which is visible in small-grain films where a decrease in out-of-field over-response was observed.

Surface Segregation Studies in Ternary Noble Metal Alloys: Comparing DFT and Machine Learning with Experimental Data

Surface segregation, whereby the surface composition of an alloy differs systematically from the bulk, has historically been hard to study, because it requires experimental and modeling methods that span alloy composition space. In this work, we study surface segregation in catalytically relevant noble and platinum-group metal alloys with a focus on three ternary systems: AgAuCu, AuCuPd, and CuPdPt. We develop a data set of 2478 slabs with those compositions including all three low-index crystallographic orientations relaxed with Density Functional Theory using the PBEsol functional with D3 dispersion corrections. We fine-tune a machine learning model on this data and use the model in a series of 1800 Monte Carlo simulations spanning ternary composition space for each surface orientation and ternary chemical system. The results of these simulations are validated against prior experimental surface segregation data collected using composition spread alloy films for AgAuCu and AuCuPd. Our findings reveal that simulations conducted using the (110) orientation most closely match experimentally observed surface segregation trends, and while predicted trends qualitatively match observation, biases in the PBEsol functional limit numeric accuracy. This study advances understanding of surface segregation and the utility of computational studies and highlights the need for further improvements in simulation accuracy.

Effect of bolus materials on dose deposition in deep tissues during electron beam radiotherapy

Several materials are utilized in the production of bolus, which is essential for superficial tumor radiotherapy. This research aimed to compare the variations in dose deposition in deep tissues during electron beam radiotherapy when employing different bolus materials. Specifically, the study developed general superficial tumor models (S-T models) and postoperative breast cancer models (P-B models). Each model comprised a bolus made of water, polylactic acid (PLA), polystyrene, silica-gel or glycerol. Geant4 was employed to simulate the transportation of electron beams within the studied models, enabling the acquisition of dose distributions along the central axis of the field. A comparison was conducted to assess the dose distributions in deep tissues. In regions where the percentage depth dose (PDD) decreases rapidly, the relative doses (RDs) in the S-T models with silica-gel bolus exhibited the highest values. Subsequently, RDs for PLA, glycerol and polystyrene boluses followed in descending order. Notably, the RDs for glycerol and polystyrene boluses were consistently below 1. Within the P-B models, RDs for all four bolus materials are consistently below 1. Among them, the smallest RDs are observed with the glycerol bolus, followed by silica-gel, PLA and polystyrene bolus in ascending order. As PDDs are ~1-3% or smaller, the differences in RDs diminish rapidly until are only around 10%. For the S-T and P-B models, polystyrene and glycerol are the most suitable bolus materials, respectively. The choice of appropriate bolus materials, tailored to the specific treatment scenario, holds significant importance in safeguarding deep tissues during radiotherapy.

Dosimetry of Large Field Valencia applicators for Cobalt-60-based brachytherapy

BACKGROUND

Non-melanoma skin cancer is one of the most common types of cancer and one of the main approaches is brachytherapy. For small lesions, the treatment of this cancer with brachytherapy can be done with two commercial applicators, one of these is the Large Field Valencia Applicators (LFVA).

PURPOSE

The aim of this study is to test the capabilities of the LFVA to use clinically 60Co sources instead of the 192Ir ones. This study was designed for the same dwell positions and weights for both sources.

METHODS

The Penelope Monte Carlo code was used to evaluate dose distribution in a water phantom when a 60Co source is considered. The LFVA design and the optimized dwell weights reported for the case of 192Ir are maintained with the only exception of the dwell weight of the central position, that was increased. 2D dose distributions, field flatness, symmetry and the leakage dose distribution around the applicator were calculated.

RESULTS

When comparing the dose distributions of both sources, field flatness and symmetry remain unchanged. The only evident difference is an increase of the penumbra regions for all depths when using the 60Co source. Regarding leakage, the maximum dose within the air volume surrounding the applicator is in the order of 20% of the prescription dose for the 60Co source, but it decreases to less than 5% at about 1 cm distance.

CONCLUSIONS

Flatness and symmetry remains unaltered as compared with 192Ir sources, while an increase in leakage has been observed. This proves the feasibility of using the LFVA in a larger range of clinical applications.

Quantifying accuracy on distance estimation tasks: A Monte Carlo study

An important aspect of perceptual learning involves understanding how well individuals can perceive distances, sizes, and time-to-contact. Oftentimes, the primary goal in these experiments is to assess participants' errors (i.e., how accurately participants perform these tasks). However, the manner in which researchers have quantified error, or task accuracy, has varied. The use of different measures of task accuracy, to include error scores, ratios, and raw estimates, indicates that the interpretation of findings depends on the measure of task accuracy utilized. In an effort to better understand this issue, we used a Monte Carlo simulation to evaluate five dependent measures of accuracy: raw distance judgments, a ratio of true to estimated distance judgments, relative error, signed error, and absolute error. We simulated data consistent with prior findings in the distance perception literature and evaluated how findings and interpretations vary as a function of the measure of accuracy used. We found there to be differences in both statistical findings (e.g., overall model fit, mean square error, Type I error rate) and the interpretations of those findings. The costs and benefits of utilizing each accuracy measure for quantifying accuracy in distance estimation studies are discussed.

First Monte Carlo beam model for ultra-high dose rate radiotherapy with a compact electron LINAC

BACKGROUND

FLASH radiotherapy based on ultra-high dose rate (UHDR) is actively being studied by the radiotherapy community. Dedicated UHDR electron devices are currently a mainstay for FLASH studies.

PURPOSE

To present the first Monte Carlo (MC) electron beam model for the UHDR capable Mobetron (FLASH-IQ) as a dose calculation and treatment planning platform for preclinical research and FLASH-radiotherapy (RT) clinical trials.

METHODS

The initial beamline geometry of the Mobetron was provided by the manufacturer, with the first-principal implementation realized in the Geant4-based GAMOS MC toolkit. The geometry and electron source characteristics, such as energy spectrum and beamline parameters, were tuned to match the central-axis percentage depth dose (PDD) and lateral profiles for the pristine beam measured during machine commissioning. The thickness of the small foil in secondary scatter affected the beam model dominantly and was fine tuned to achieve the best agreement with commissioning data. Validation of the MC beam modeling was performed by comparing the calculated PDDs and profiles with EBT-XD radiochromic film measurements for various combinations of applicators and inserts.

RESULTS

The nominal 9 MeV electron FLASH beams were best represented by a Gaussian energy spectrum with mean energy of 9.9 MeV and variance (σ) of 0.2 MeV. Good agreement between the MC beam model and commissioning data were demonstrated with maximal discrepancy < 3% for PDDs and profiles. Hundred percent gamma pass rate was achieved for all PDDs and profiles with the criteria of 2 mm/3%. With the criteria of 2 mm/2%, maximum, minimum and mean gamma pass rates were (100.0%, 93.8%, 98.7%) for PDDs and (100.0%, 96.7%, 99.4%) for profiles, respectively.

CONCLUSIONS

A validated MC beam model for the UHDR capable Mobetron is presented for the first time. The MC model can be utilized for direct dose calculation or to generate beam modeling input required for treatment planning systems for FLASH-RT planning. The beam model presented in this work should facilitate translational and clinical FLASH-RT for trials conducted on the Mobetron FLASH-IQ platform.

Health risk assessment of heavy metals based on source analysis and Monte Carlo in the downstream basin of the Zishui

In this study, stone coal mines in the lower reaches of the Zijiang River were adopted as the research object. To analyze the spatial distribution, sources, and health risks of heavy metals in the surrounding soil of stone coal mines, 82 topsoil samples were collected in the study area, and the contents of 8 heavy metals including Cd, Hg, As, Cr, Pb, Cu, Ni, and Zn were determined. The spatial distribution of heavy metals was analyzed using ArcGIS, and the pollution sources of heavy metals were identified using Positive matrix factorization (PMF). Then, Monte Carlo and health risk assessment models were used to evaluate the health risks of different populations. The results showed that the average content of heavy metals followed the order of Zn > Cr > Pb > Cu > Ni > As > Cd > Hg, and the contents of all heavy metals were higher than the soil background values of Hunan Province. The high-value areas of heavy metals content were mostly concentrated in the central region close to areas with a notable concentration of stone coal mines. PMF identified four pollution sources, namely, mining activities (26.9%), atmospheric deposition (18.8%), natural sources (32.8%) and agricultural sources (21.5%). The carcinogenic and non-carcinogenic risks for children were higher than those for adults, with As and Cd posing higher carcinogenic risks to children. Based on the source of health risks, it was determined that the health risks could be primarily attributed to agricultural sources, and As was the main heavy metal causing health risks. This study provides theoretical support for treating heavy metal pollution in mining basins.

Shape-Interaction Dualism: Unraveling Complex Phase Behavior in Triangular Particle Monolayers

This paper examines the effect of finite attractive and repulsive interactions on the self-assembly of triangular-shaped particles on a triangular lattice. The ground state analysis of the lattice model has revealed an infinite sequence of ordered structures, a phenomenon referred to as the "devil's staircase" of phase transitions. The model has been studied at finite temperatures using both the transfer-matrix and tensor renormalization group methods. The concurrent use of these two methods lends credibility to the obtained results. It has been demonstrated that the initial ordered structures of the "devil's staircase" persist at non-zero temperatures. Further increase of the attraction between particles or a decrease of the temperature induces the appearance of subsequent ordered structures of the "devil's staircase". The corresponding phase diagram of the model has been calculated. The phase behavior of our model agrees qualitatively with the phase behavior of trimesic acid adsorption layer on single crystal surfaces. .

Angle-dependent light scattering in tissue phantoms for the case of thin bone layers with predominant forward scattering

The cochlea forms a key element of the human auditory system in the temporal bone. Damage to the cochlea continues to produce significant impairment for sensory reception of environmental stimuli. To improve this impairment, the optical cochlear implant forms a new research approach. A prerequisite for this method is to understand how light propagation, as well as scattering, reflection, and absorption, takes place within the cochlea. We offer a method to study the light distribution in the human cochlea through phantom materials which have the objective to mimic the optical behavior of bone and Monte-Carlo simulations. The calculation of an angular distribution after scattering requires a phase function. Often approximate functions like Henyey-Greenstein, two-term Henyey-Greenstein or Legendre polynomial decompositions are used as phase function. An alternative is to exactly calculate a Mie distribution for each scattering event. This method provides a better fit to the data measured in this work.

Beam quality correction factors for ionization chambers in a 0.35 T magnetic resonance (MR)-linac - A Monte Carlo study

PURPOSE

The purpose of this study was to directly calculate [Formula: see text] correction factors for four cylindrical ICs for a 0.35 T MR-linac using the Monte Carlo (MC) method.

METHODS

A previously-validated TOPAS/GEANT4 MC head model of the 0.35 T MR-linac was employed. The MR-compatible Exradin A12, A1SL, A26, and A28 cylindrical ICs were modeled considering the dead volume in the air cavity. The [Formula: see text] correction factor was determined for initial electron energies of 5-7 MeV. The correction factor was calculated for all four angular orientations in the lateral plane. The impact of the 0.35 T magnetic field on the IC response was also investigated.

RESULTS

The maximum beam quality dependence in the [Formula: see text] exhibited by the A12, A1SL, A26, and A28 ICs was 1.10 %, 2.17 %, 0.81 %, and 1.75 %, respectively, considering all angular orientations. The magnetic field dependence was < 1 % and the maximum [Formula: see text] correction was < 2 % when the detector was aligned along the direction of the magnetic field at 0° and 180° angles. The A12 IC over-responded up to 5.40 % for the orthogonal orientation. An asymmetry in the response of up to 8.30 % was noted for the A28 IC aligned at 90° and 270° angles.

CONCLUSIONS

A parallel orientation for the IC, with respect to the magnetic field, is recommended for reference dosimetry in MRgRT. Both over and under-response in the IC signal was noted for the orthogonal orientations, which is highly dependent on the cavity diameter, cavity length, and the dead volume.

MCGPU-PET: An Open-Source Real-Time Monte Carlo PET Simulator

Monte Carlo (MC) simulations are commonly used to model the emission, transmission, and/or detection of radiation in Positron Emission Tomography (PET). In this work, we introduce a new open-source MC software for PET simulation, MCGPU-PET, which has been designed to fully exploit the computing capabilities of modern GPUs to simulate the acquisition of more than 100 million coincidences per second from voxelized sources and material distributions. The new simulator is an extension of the PENELOPE-based MCGPU code previously used in cone-beam CT and mammography applications. We validated the accuracy of the accelerated code by comparing it to GATE and PeneloPET simulations achieving an agreement within 10 percent approximately. As an example application of the code for fast estimation of PET coincidences, a scan of the NEMA IQ phantom was simulated. A fully 3D sinogram with 6382 million true coincidences and 731 million scatter coincidences was generated in 54 seconds in one GPU. MCGPU-PET provides an estimation of true and scatter coincidences and spurious background (for positron-gamma emitters such as 124I) at a rate 3 orders of magnitude faster than CPU-based MC simulators. This significant speed-up enables the use of the code for accurate scatter and prompt-gamma background estimations within an iterative image reconstruction process.

Possible improvements in effective fill factor using X-ray fluorescent interpixel reflectors

BACKGROUND

The spatial resolution of energy-integrating diagnostic CT scanners is limited by interpixel reflectors on the detector, which optically isolate pixels but create dead space. Because the width of the reflector cannot easily be decreased, fill factor diminishes as resolution increases.

PURPOSE

We propose loading (or mixing) a high-Z element into the reflectors, causing the reflectors to be X-ray fluorescent. Re-emitted characteristic X-rays could be detected in adjacent pixels, increasing the effective fill factor and compensating for fill factor loss with higher-resolution detectors. The purpose of this work is to understand the physical principles of this approach and to analyze its effectiveness using Monte Carlo simulations.

METHODS

Detector pixels were modeled using the GEANT4 Monte Carlo package. The width of the reflector was kept constant at 0.1 mm throughout, and we considered pixel pitches between 0.5 and 1 mm. The pixelated scintillator material was gadolinium oxysulfide, 3 mm thick. The baseline reflector material was chosen to be acrylic, and varying concentrations of a high-Z element were loaded into the material. We assumed that the optical characteristics of pixels were ideal (no absorption within pixels, perfect reflection at boundaries). The detector was irradiated uniformly with 10,000 X-ray photons to estimate its spectral response. The figure of merit was the variance of the detector signal at zero frequency normalized to that of an ideal single-bin photon-counting detector with 100% fill factor. Sensitivity analyses were conducted to understand the effect of varying the high-Z element concentration and the spectrum.

RESULTS

Initial simulations suggested that a k-edge near 50 keV would be ideal. Gd was therefore selected as the high-Z material. The relative variances for a conventional energy integrating detector without Gd at 1 mm pixel pitch (81% fill factor) and 0.5 mm pixel pitch (64% fill factor) were 1.38 and 1.74, compared to 1.00 for an ideal photon counting detector, implying a 26% variance penalty for 0.5 mm pitch. When 1 g/cm3 Gd was loaded into the interpixel reflector, the relative variance improved to 1.27 and 1.43, respectively, implying that the variance penalty for including Gd together with 0.5 mm pitch is only 4%. Performance was nearly maximized at 1.0 g/cm3 of Gd, but a concentration of 0.5 g/cm3 of Gd showed most of the benefit. Improvements depend weakly on kV, with lower kV associated with higher improvements. An external anti-scatter grid was not modeled in our simulations and would reduce the expected benefit, depending greatly on the pitch and dimensionality of the anti-scatter grid.

CONCLUSIONS

The losses in fill factor associated with smaller pixel pitch can be reduced if Gd or a similar element could be loaded into the interpixel reflector. These improvements in noise efficiency are yet to be verified experimentally.

Comparison of CBCT radiation doses with conventional radiographs in TMJ imaging using Monte Carlo simulations

Three-dimensional imaging methods are widely used for evaluation of bony changes of temporomandibular joint (TMJ). Besides, lateral and posterio-anterior TMJ projections in both closed- and open-jaw positions for each temporomandibular joint are used as two-dimensional diagnostic tools. The purpose of the present study was to compare effective and mean organ absorbed doses of plain radiography techniques with those of different modalities of cone beam computed tomography (CBCT) scanning of an adult's temporomandibular joint. PCXMC 2.0 software was used to calculate mean organ and effective doses. A NewTom CBCT device (Newtom 5G XL; QR systems; Verona, Italy) was simulated at 360° rotation using a 6 × 6 cm2 FOV in standard and high-resolution modes. Lateral and posterio-anterior TMJ plain projections were simulated according to recommendations of the manufacturer of the Planmeca ProMax® 2D S3 device. Doses for both projections were simulated with Monte Carlo methods and the International Commission on radiological protection adult reference computational phantoms. The highest mean organ absorbed doses occurred in bone surfaces, salivary glands, and skull for posterio-anterior TMJ and lateral TMJ, and for CBCT scanning in all examinations. The effective doses of posterio-anterior and lateral TMJ plain radiographs were found to be higher than those of the Standard Mode-Eco Scan CBCT. Therefore, the lowest effective dose was calculated in Standard Mode-Eco Scan CBCT. It is concluded that NewTom 5G XL Standard Mode-Eco Scan CBCT can be used instead of plain radiographs (lateral and posterio-anterior TMJ) in temporomandibular joint imaging as it allows visualizing the three-dimensional structure of the temporomandibular joint as an advantage.

Beam quality and the mystery behind the lower percentage depth dose in grid radiation therapy

Grid therapy recently has been picking momentum due to favorable outcomes in bulky tumors. This is being termed as Spatially Fractionated Radiation Therapy (SFRT) and lattice therapy. SFRT can be performed with specially designed blocks made with brass or cerrobend with repeated holes or using multi-leaf collimators where dosimetry is uncertain. The dosimetric challenge in grid therapy is the mystery behind the lower percentage depth dose (PDD) in grid fields. The knowledge about the beam quality, indexed by TPR20/10 (Tissue Phantom Ratio), is also necessary for absolute dosimetry of grid fields. Since the grid may change the quality of the primary photons, a new [Formula: see text] should be evaluated for absolute dosimetry of grid fields. A Monte Carlo (MC) approach is provided to resolving the dosimetric issues. Using 6 MV beam from a linear accelerator, MC simulation was performed using MCNPX code. Additionally, a commercial grid therapy device was used to simulate the grid fields. Beam parameters were validated with MC model for output factor, depth of maximum dose, PDDs, dose profiles, and TPR20/10. The electron and photon spectra were also compared between open and grid fields. The dmax is the same for open and grid fields. The PDD with grid is lower (~ 10%) than the open field. The difference in TPR20/10 of open and grid fields is observable (~ 5%). Accordingly, TPR20/10 is still a good index for the beam quality in grid fields and consequently choose the correct [Formula: see text] in measurements. The output factors for grid fields are 0.2 lower compared to open fields. The lower depth dose with grid therapy is due to lower depth fluence with scatter radiation but it does not impact the dosimetry as the calibration parameters are insensitive to the effective beam energies. Thus, standard dosimetry in open beam based on international protocol could be used.

The Influence of B4C Film Density on Damage Threshold Based on Monte Carlo Method for X-ray Mirror

The uniformity and consistency of X-ray mirror film materials prepared by experimental methods are difficult to guarantee completely. These factors directly affect the service life of free electron laser devices in addition to its own optical properties. Therefore, the quality of the film material, especially the density, has a critical effect on its application. Boron carbide film and monocrystalline silicon substrate were suitable examples to explore their influence of density on the damage threshold based on Monte Carlo and heat-conduction methods. Through simulation results, it was found that the change in film density could affect the energy deposition depth and damage threshold. When the film density was 2.48 g/cm3, it had relatively high damage threshold in all energy ranges. And then the specific incident parameter for practical application was investigated. It was found that the damage mechanism of the B4C/Si was the melting of the interface. And the damage threshold was also higher with the film density of 2.48 g/cm3. Therefore, it was recommended to maintain the density at this value as far as possible when preparing the film, and to ensure the uniformity and consistency of the film material.

The Effect of Polymer-Solvent Interaction on the Swelling of Polymer Matrix Tablets: A Magnetic Resonance Microscopy Study Complemented by Bond Fluctuation Model Simulations

Polymer matrix tablets are an important drug-delivery system widely used for oral drug administration. Understanding the tablet hydration process, both experimentally and theoretically, is, thus, very important for the development of drug delivery systems that exhibit high drug loading capacity and controlled release potential. In this study, we used magnetic resonance microscopy (MRM) to nondestructively and dynamically analyze the water hydration process of xanthan-based tablets. The swelling process was characterized by well-resolved fronts of erosion, swelling, and penetration. The experimental results were complemented by numerical simulations of the polymer matrix hydration process. In the simulations, the polymer tablet matrix was modeled as an assembly of interacting chains with embedded drug particles, while its hydration process was mediated by interaction with solvent particles. The swelling dynamics were modeled within a Monte Carlo-based bond fluctuation model (BFM) that elegantly accounted for steric and nearest-neighbor interactions. This study provides an efficient experimental-theoretical approach for the study of polymer matrix swelling processes.

Creating uniform cluster dose spread-out Bragg peaks for proton and carbon beams

BACKGROUND

Preliminary data have shown a close association of the generalized ionization cluster size dose (in short, cluster dose) with cell survival, independent of particle type, and energy, when cluster dose is derived from an ionization detail parameter preferred for its association with cell survival. Such results suggest cluster dose has the potential to replace RBE-weighted dose in proton and ion beam radiotherapy treatment plan optimization, should a uniform cluster dose lead to comparable biological effects. However, further preclinical investigations are warranted to confirm this premise.

PURPOSE

To present an analytical approach to create uniform cluster dose spread-out Bragg peaks (SOBP) for evaluation of the potential of cluster dose to result in uniform biological effect.

METHODS

We modified the coefficients of the Bortfeld and Schlegel weight formula, an analytical method typically used for the creation of radiation dose SOBP in particle therapy, to produce uniform cluster dose SOBP of different widths (1-5 cm) at relevant clinical proton and carbon beam energies. Optimum parameters were found by minimization of the ratio between the maximum and minimum cluster dose in the SOBP region using the Nelder-Mead method.

RESULTS

The coefficients of the Bortfeld and Schlegel weight formula leading to uniform cluster dose SOBPs were determined for each combination of beam energy and SOBP width studied. The uniformity of the resulting cluster dose SOBPs, calculated as the relative difference between the maximum and minimum cluster dose within the SOBP, was within 0.3%-3.5% for the evaluated proton beams and 1.3%-3.4% for the evaluated carbon beams.

CONCLUSIONS

The modifications to the analytical approach to create radiation dose SOBPs resulted in uniform cluster dose proton and carbon SOBPs over a wide range of beam energies and SOBP widths. Such SOBPs should prove valuable in preclinical investigations for the selection of nanodosimetric quantities to be used in proton and ion therapy treatment planning.

Assessing the impact of PV panel climate-based degradation rates on inverter reliability in grid-connected solar energy systems

This paper provides an evaluation of a 4-kW grid-connected full-bridge PV inverter under three different scenarios to assess its reliability with a fixed PV degradation rate, with a climate-based degradation rate, and without considering PV degradation. The climate-based degradation rates are estimated using a physics-based model that considers the different parameters influencing the PV reliability. Three different locations representing three different climate zones (hot and dry, hot and humid, and moderate climates) have been chosen in this study. The estimated lifetime of the IGBT, the switching device in the PV inverter, varies depending on the location, with the inclusion of fixed and climate-based degradation rates extending the lifespan of the PV inverter in the examined locations. The results demonstrate the significant impact of PV climate-based degradation rates on power electronics' reliability assessment and the importance of considering various factors in predicting device failures. To ensure the PV inverter's lifespan over the desired period in areas with high solar irradiation rates and extremely hot climates, the design parameters should be slightly elevated above the standard value.