Factors driving the change of household CO2 emissions through 2040 in China: based on decomposition and scenario analyses

With China's economic transformation into a consumption-driven model, household CO₂ emissions (HCEs) become an increasingly essential part of China's CO₂ emissions. However, how will the HCEs change in urban and rural areas and what are the driving forces of HCEs through 2040 are not clear. In this paper, we project nation-level HCEs up to 2040 by the scenario analysis, and analyze the drivers of HCEs during 1997-2040 by the decomposition analysis. We find that the HCEs kept a persistent growth during 1997-2017 as energy intensity reduction and energy structure optimization cannot offset the rapid growth of consumption and population. During 2017-2040, in the current policy scenario, the rural HCEs will decrease, while the peaking of the total HCEs and urban HCEs would not be achieved. In the sustainable development scenario, the total HCEs, urban HCEs and rural HCEs will peak before 2030 and afterward decrease, because the energy intensity will induce a 51% and 76% reduction in the total HCEs and urban HCEs, respectively. Moreover, the decrease in the share of coal consumption due to the development of non-fossil fuels and natural gas will cause a more than 25% reduction in HCEs in the sustainable development scenario.

Dose-response of deformable radiochromic dosimeters for spot scanning proton therapy

Intrafractional motion and deformation influence proton therapy delivery for tumours in the thorax, abdomen and pelvis. This study aimed to test the dose-response of a compressively strained three-dimensional silicone-based radiochromic dosimeter during proton beam delivery. The dosimeter was read-out in its relaxed state using optical computed tomography and calibrated for the linear energy transfer, based on Monte Carlo simulations. A three-dimensional gamma analysis showed a 99.3% pass rate for 3%/3 mm and 93.9% for 2%/2 mm, for five superimposed measurements using deformation-including Monte Carlo dose calculations as reference. We conclude that the dosimeter's dose-response is unaffected by deformations.

Influence of beam quality on reference dosimetry correction factors in magnetic resonance guided radiation therapy

Correction factors for reference dosimetry in magnetic resonance (MR) imaging-guided radiation therapy (k B → , M , Q ) are often determined in setups that combine a conventional 6 MV linac with an electromagnet. This study investigated whether results based on these measurements were applicable for a 7 MV MR-linac using Monte Carlo simulations. For a Farmer-type ionization chamber,k B → , M , Q was assessed for different tissue-phantom ratios (TPR 20 , 10 ).k B → , M , Q differed by 0.0029 ( 43 ) betweenTPR 20 , 10 = 0.6790 ( 23 ) (6 MV linac) andTPR 20 , 10 = 0.7028 ( 14 ) (7 MV MR-linac) at 1.5 T . The agreement was best in an orientation in which the secondary electrons were deflected to the stem of the ionization chamber.

Challenges in the quantification approach to a radiation relevant adverse outcome pathway for lung cancer

PURPOSE

Adverse outcome pathways (AOPs) provide a modular framework for describing sequences of biological key events (KEs) and key event relationships (KERs) across levels of biological organization. Empirical evidence across KERs can support construction of quantified AOPs (qAOPs). Using an example AOP of energy deposition from ionizing radiation onto DNA leading to lung cancer incidence, we investigate the feasibility of quantifying data from KERs supported by all types of stressors. The merits and challenges of this process in the context of AOP construction are discussed.

MATERIALS AND METHODS

Empirical evidence across studies of dose-response from four KERs of the AOP were compiled independently for quantification. Three upstream KERs comprised of evidence from various radiation types in line with AOP guidelines. For these three KERs, a focused analysis of data from alpha-particle studies was undertaken to better characterize the process to the adverse outcome (AO) for a radon gas stressor. Numerical information was extracted from tables and graphs to plot and tabulate the response of KEs. To complement areas of the AOP quantification process, Monte Carlo (MC) simulations in TOPAS-nBio were performed to model exposure conditions relevant to the AO for an example bronchial compartment of the lung with secretory cell nuclei targets.

RESULTS

Quantification of AOP KERs highlighted the relevance of radiation types under the stressor-agnostic intent of AOP design, motivating a focus on specific types. For a given type, significant differences of KE response indicate meaningful data to derive linkages from the MIE to the AO is lacking and that better response-response focused studies are required. The MC study estimates the linear energy transfer (LET) of alpha-particles emitted by radon-222 and its progeny in the secretory cell nuclei of the example lung compartment to range from 94 - 5 + 5 to 192 - 18 + 15 keV/µm.

CONCLUSION

Quantifying AOP components provides a means to assemble empirical evidence across different studies. This highlights challenges in the context of studies examining similar endpoints using different radiation types. Data linking KERs to a MIE of 'deposition of energy' is shown to be non-compatible with the stressor-agnostic principles of AOP design. Limiting data to that describing response-response relationships between adjacent KERs may better delineate studies relevant to the damage that drives a pathway to the next KE and still support an 'all hazards' approach. Such data remains limited and future investigations in the radiation field may consider this approach when designing experiments and reporting their results and outcomes.

Achievable dose reductions with gonadal shielding for children and adults during abdominal/pelvic radiographic examinations: A Monte Carlo simulation

PURPOSE

Recently, medical professionals have reconsidered the practice of routine gonadal shielding for radiographic examinations. The objective of this study was to evaluate the gonadal dose reduction achievable with gonadal shields in the primary beam during abdominal/pelvic radiographic examinations under ideal and non-ideal shielding placement.

METHODS

CT scans of CIRS anthropomorphic phantoms were used to perform voxelized Monte Carlo simulations of the photon transport during abdominal/pelvic radiographic examinations with standard filtration and 0.1 mm Cu + 1 mm Al added filtration to estimate gonadal doses for an adult, 5 yr old, and newborn phantom with and without gonadal shields. The reduction in dose when the shields were not placed at the ideal locations was also evaluated. The ratio of the number of scattered-to-primary photons (SPR) across the anteroposterior (AP) dimension of the phantoms was also reported.

RESULTS

The simulated dose reduction with ideal shielding placement for the testes and ovaries ranged from 80% to 90% and 55% to 70% respectively. For children, a misalignment of the shield to the gonad of 4 cm reduced the measured dose reduction to the gonads to <10%. For adults, this effect did not occur until the misalignment increased to ~6 cm. Effects of dose reduction with and without the gonadal shields properly placed were similar for standard filtration and added filtration. SPR at the level of the testes was consistently <1 for all phantoms. SPR for ovaries was ~1.5 for the adult and 5-yr old, and ~1 for the newborn phantom.

CONCLUSION

Dose reduction with ideal alignment of the simulated gonadal shield to the gonads in this study was greater for the testes than the ovaries; both reductions were substantial. However, the dose reductions were greatly reduced (to <10%) for both sexes with misalignment of the gonads to the shields by 4 cm for children and 6 cm for adults.

Quantitative Monte Carlo-based brain dopamine transporter SPECT imaging

OBJECTIVE

Brain dopamine transporter imaging with I-123-labeled radioligands is technically demanding due to the small size of the imaging target relative to the spatial resolution of most SPECT systems. In addition, I-123 has high-energy peaks which can penetrate or scatter in the collimator and be detected in the imaging energy window. The aim of this study was to implement Monte Carlo (MC)-based full collimator-detector response (CDR) compensation algorithm for I-123 into a third-party commercial SPECT reconstruction software package and to evaluate its effect on the quantitative accuracy of dopaminergic-image analysis compared to a method where only the geometric component of the CDR is compensated.

METHODS

In this work, we utilized a full Monte Carlo collimator-detector model and incorporated it into an iterative SPECT reconstruction algorithm. The full Monte Carlo model reconstruction was compared to standard reconstruction using an anthropomorphic striatal phantom filled with different I-123 striatal/cortex uptake ratios and with clinical I-123 Ioflupane DaTScan studies.

RESULTS

Reconstruction with the full model yielded higher (13-25%) striatal uptake ratios than the conventional reconstruction, but the uptake ratios were still much lower than the true ratios due to partial volume effect. Visually, images reconstructed with the full Monte Carlo model had better contrast and resolution than the conventional images, with both phantom and patient studies.

CONCLUSIONS

Reconstruction with full Monte Carlo collimator-detector model yields higher quantitative accuracy than conventional reconstruction. Additional work to reduce the partial volume effect related errors would improve the accuracy further.

Evaluation of GATE-RTion (GATE/Geant4) Monte Carlo simulation settings for proton pencil beam scanning quality assurance

PURPOSE

Geant4 is a multi-purpose Monte Carlo simulation tool for modeling particle transport in matter. It provides a wide range of settings, which the user may optimize for their specific application. This study investigates GATE/Geant4 parameter settings for proton pencil beam scanning therapy.

METHODS

GATE8.1/Geant4.10.3.p03 (matching the versions used in GATE-RTion1.0) simulations were performed with a set of prebuilt Geant4 physics lists (QGSP_BIC, QGSP_BIC_EMY, QGSP_BIC_EMZ, QGSP_BIC_HP_EMZ), using 0.1mm-10mm as production cuts on secondary particles (electrons, photons, positrons) and varying the maximum step size of protons (0.1mm, 1mm, none). The results of the simulations were compared to measurement data taken during clinical patient specific quality assurance at The Christie NHS Foundation Trust pencil beam scanning proton therapy facility. Additionally, the influence of simulation settings was quantified in a realistic patient anatomy based on computer tomography (CT) scans.

RESULTS

When comparing the different physics lists, only the results (ranges in water) obtained with QGSP_BIC (G4EMStandardPhysics_Option0) depend on the maximum step size. There is clinically negligible difference in the target region when using High Precision neutron models (HP) for dose calculations. The EMZ electromagnetic constructor provides a closer agreement (within 0.35 mm) to measured beam sizes in air, but yields up to 20% longer execution times compared to the EMY electromagnetic constructor (maximum beam size difference 0.79 mm). The impact of this on patient-specific quality assurance simulations is clinically negligible, with a 97% average 2%/2 mm gamma pass rate for both physics lists. However, when considering the CT-based patient model, dose deviations up to 2.4% are observed. Production cuts do not substantially influence dosimetric results in solid water, but lead to dose differences of up to 4.1% in the patient CT. Small (compared to voxel size) production cuts increase execution times by factors of 5 (solid water) and 2 (patient CT).

CONCLUSIONS

Taking both efficiency and dose accuracy into account and considering voxel sizes with 2 mm linear size, the authors recommend the following Geant4 settings to simulate patient specific quality assurance measurements: No step limiter on proton tracks; production cuts of 1 mm for electrons, photons and positrons (in the phantom and range-shifter) and 10 mm (world); best agreement to measurement data was found for QGSP_BIC_EMZ reference physics list at the cost of 20% increased execution times compared to QGSP_BIC_EMY. For simulations considering the patient CT model, the following settings are recommended: No step limiter on proton tracks; production cuts of 1 mm for electrons, photons and positrons (phantom/range-shifter) and 10 mm (world) if the goal is to achieve sufficient dosimetric accuracy to ensure that a plan is clinically safe; or 0.1 mm (phantom/range-shifter) and 1 mm (world) if higher dosimetric accuracy is needed (increasing execution times by a factor of 2); most accurate results expected for QGSP_BIC_EMZ reference physics list, at the cost of 10-20% increased execution times compared to QGSP_BIC_EMY.

The HARMONIC project: study design for the assessment of radiation doses and associated cancer risks following cardiac fluoroscopy in childhood

The HARMONIC project (Health Effects of Cardiac Fluoroscopy and Modern Radiotherapy in Paediatrics) is a European study aiming to improve our understanding of the long-term health risks from radiation exposures in childhood and early adulthood. Here, we present the study design for the cardiac fluoroscopy component of HARMONIC. A pooled cohort of approximately 100 000 patients who underwent cardiac fluoroscopy procedures in Belgium, France, Germany, Italy, Norway, Spain or the UK, while aged under 22 years, will be established from hospital records and/or insurance claims data. Doses to individual organs will be estimated from dose indicators recorded at the time of examination, using a lookup-table-based dosimetry system produced using Monte Carlo radiation transport simulations and anatomically realistic computational phantom models. Information on beam geometry and x-ray energy spectra will be obtained from a representative sample of radiation dose structured reports. Uncertainties in dose estimates will be modelled using 2D Monte Carlo methods. The cohort will be followed up using national registries and insurance records to determine vital status and cancer incidence. Information on organ transplantation (a major risk factor for cancer development in this patient group) and/or other conditions predisposing to cancer will be obtained from national or local registries and health insurance data, depending on country. The relationship between estimated radiation dose and cancer risk will be investigated using regression modelling. Results will improve information for patients and parents and aid clinicians in managing and implementing changes to reduce radiation risks without compromising medical benefits.

Random cancers as supported by registry data

There has been considerable interest in recent years in quantifying the rate of unavoidable or so-called random cancers, as opposed to cancers linked to environmental, genetic or other factors. We propose a data-based approach to estimate an upper limit to this probability, based on an analysis of multiple registry data. The argument is that the cumulative hazards for random cancers cannot exceed the minimum reliable cumulative hazard observed across the registries. We propose a Monte Carlo method to identify this upper limit and apply the method to data on nine different cancers recorded by 423 registries. We compare our values with estimates obtained from a random mutations argument.

Experimental validation of Monte Carlo based treatment planning system in bone density equivalent media

Introduction Advanced, Monte Carlo (MC) based dose calculation algorithms, determine absorbed dose as dose to medium-in-medium (Dm,m) or dose to water-in-medium (Dw,m). Some earlier studies identified the differences in the absorbed doses related to the calculation mode, especially in the bone density equivalent (BDE) media. Since the calculation algorithms built in the treatment planning systems (TPS) should be dosimetrically verified before their use, we analyzed dose differences between two calculation modes for the Elekta Monaco TPS. We compared them with experimentally determined values, aiming to define a supplement to the existing TPS verification methodology. Materials and methods In our study, we used a 6 MV photon beam from a linear accelerator. To evaluate the accuracy of the TPS calculation approaches, measurements with a Farmer type chamber in a semi-anthropomorphic phantom were compared to those obtained by two calculation options. The comparison was made for three parts of the phantom having different densities, with a focus on the BDE part. Results Measured and calculated doses were in agreement for water and lung equivalent density materials, regardless of the calculation mode. However, in the BDE part of the phantom, mean dose differences between the calculation options ranged from 5.7 to 8.3%, depending on the method used. In the BDE part of the phantom, neither of the two calculation options were consistent with experimentally determined absorbed doses. Conclusions Based on our findings, we proposed a supplement to the current methodology for the verification of commercial MC based TPS by performing additional measurements in BDE material.

Machine Learning Guidance for Connection Tableaux

Connection calculi allow for very compact implementations of goal-directed proof search. We give an overview of our work related to connection tableaux calculi: first, we show optimised functional implementations of connection tableaux proof search, including a consistent Skolemisation procedure for machine learning. Then, we show two guidance methods based on machine learning, namely reordering of proof steps with Naive Bayesian probabilities, and expansion of a proof search tree with Monte Carlo Tree Search.

An on-lattice agent-based Monte Carlo model simulating the growth kinetics of multicellular tumor spheroids

PURPOSE

To develop an on-lattice agent-based model describing the growth of multicellular tumor spheroids using simple Monte Carlo tools.

METHODS

Cells are situated on the vertices of a cubic grid. Different cell states (proliferative, hypoxic or dead) and cell evolution rules, driven by 10 parameters, and the effects of the culture medium are included. About twenty spheroids of MCF-7 human breast cancer were cultivated and the experimental data were used for tuning the model parameters.

RESULTS

Simulated spheroids showed adequate sizes of the necrotic nuclei and of the hypoxic and proliferative cell phases as a function of the growth time, mimicking the overall characteristics of the experimental spheroids. The relation between the radii of the necrotic nucleus and the whole spheroid obtained in the simulations was similar to the experimental one and the number of cells, as a function of the spheroid volume, was well reproduced. The statistical variability of the Monte Carlo model described the whole volume range observed for the experimental spheroids. Assuming that the model parameters vary within Gaussian distributions it was obtained a sample of spheroids that reproduced much better the experimental findings.

CONCLUSIONS

The model developed allows describing the growth of in vitro multicellular spheroids and the experimental variability can be well reproduced. Its flexibility permits to vary both the agents involved and the rules that govern the spheroid growth. More general situations, such as, e. g., tumor vascularization, radiotherapy effects on solid tumors, or the validity of the tumor growth mathematical models can be studied.

Quantification of internal dosimetry in PET patients: individualized Monte Carlo vs generic phantom-based calculations

PURPOSE

The purpose of this work is to calculate individualized dose distributions in patients undergoing 18 F-FDG PET/CT studies through a methodology based on full Monte Carlo (MC) simulations and PET/CT patient images, and to compare such values with those obtained by employing nonindividualized phantom-based methods.

METHODS

We developed a MC-based methodology for individualized internal dose calculations, which relies on CT images (for organ segmentation and dose deposition), PET images (for organ segmentation and distributions of activities), and a biokinetic model (which works with information provided by PET and CT images) to obtain cumulated activities. The software vGATE version 8.1. was employed to carry out the Monte Carlo calculations. We also calculated deposited doses with nonindividualized phantom-based methods (Cristy-Eckerman, Stabin, and ICRP-133).

RESULTS

Median MC-calculated dose/activity values are within 0.01-0.03 mGy/MBq for most organs, with higher doses delivered especially to the bladder wall, major vessels, and brain (medians of 0.058, 0.060, 0.066 mGy/MBq, respectively). Comparison with values obtained with nonindividualized phantom-based methods has shown important differences in many cases (ranging from -80% to + 260%). These differences are significant (p < 0.05) for several organs/tissues, namely, remaining tissues, adrenals, bladder wall, bones, upper large intestine, heart, pancreas, skin, and stomach wall.

CONCLUSIONS

The methodology presented in this work is a viable and useful method to calculate internal dose distributions in patients undergoing medical procedures involving radiopharmaceuticals, individually, with higher accuracy than phantom-based methods, fulfilling the guidelines provided by the European Council directive 2013/59/Euratom.

Monte Carlo commissioning of radiotherapy LINAC-Introducing an improved methodology

Purpose

Monte Carlo (MC) commissioning of medical linear accelerator (LINAC) is a time-consuming process involving a comparison between measured and simulated cross beam/lateral profiles and percentage depth doses (PDDs) for various field sizes. An agreement between these two data sets is sought by trial and error method while varying the incident electron beam parameters, such as electron beam energy or width, etc. This study aims to improve the efficiency of MC commissioning of a LINAC by assessing the feasibility of using a limited number of simulated PDDs.

Materials and methods

Using EGSnrc codes, a Varian Clinac 2100 unit has been commissioned for 6 MV photon beam, and a methodology has been proposed to identify the incident electron beam parameters in a speedier fashion. Impact of voxel size in 3-dimensions and cost functions used for comparison of the measured and simulated data have been investigated along with the role of interpolation.

Results

A voxel size of 1 × 1×0.5 cm³ has been identified as suitable for accurate and fast commissioning of the LIANC. The optimum number of simulated PDDs (required for further interpolation) has been found to be five.

Conclusion

The present study suggests that PDDs alone at times can be insufficient for an unambiguous commissioning process and should be supported by including the lateral beam profiles in the process.

Phantom dosimetry and cancer risks estimation undergoing 6 MV photon beam by an Elekta SL-25 linac

The High-energy linear accelerator (linac) is a valuable tool and the most commonly used devices for external beam radiation treatments in subjects suffer from cancer. To estimate the dose deposited in several organs of a female patient due to pelvic irradiation by an Elekta SL-25 linac in 6 MV photon beam mode, the MCNPX code is used considering the most details of linac. The equivalent dose in different organs is computed according to the face down position (prone) of MIRD and UFRO phantoms. The data obtained using MCNPX show that the received dose in all commons organs of MIRD and UFRO phantoms is 535.73 and 433.09 mSv/Gy_x, respectively. The risks of second cancer incidence and mortality during radiotherapy treatment are compared between MIRD and UFRO phantoms. The results indicated that bladder has the maximum risk of secondary cancer incidence risk of 142.85 and 135.34 per 10⁵ persons based on MIRD and UFRO phantoms, respectively; while the total risk is about 1 in 163 and about 1 in 101 in these phantoms.

Whole-body voxel-based internal dosimetry using deep learning

Purpose

In the era of precision medicine, patient-specific dose calculation using Monte Carlo (MC) simulations is deemed the gold standard technique for risk-benefit analysis of radiation hazards and correlation with patient outcome. Hence, we propose a novel method to perform whole-body personalized organ-level dosimetry taking into account the heterogeneity of activity distribution, non-uniformity of surrounding medium, and patient-specific anatomy using deep learning algorithms.

Methods

We extended the voxel-scale MIRD approach from single S-value kernel to specific S-value kernels corresponding to patient-specific anatomy to construct 3D dose maps using hybrid emission/transmission image sets. In this context, we employed a Deep Neural Network (DNN) to predict the distribution of deposited energy, representing specific S-values, from a single source in the center of a 3D kernel composed of human body geometry. The training dataset consists of density maps obtained from CT images and the reference voxelwise S-values generated using Monte Carlo simulations. Accordingly, specific S-value kernels are inferred from the trained model and whole-body dose maps constructed in a manner analogous to the voxel-based MIRD formalism, i.e., convolving specific voxel S-values with the activity map. The dose map predicted using the DNN was compared with the reference generated using MC simulations and two MIRD-based methods, including Single and Multiple S-Values (SSV and MSV) and Olinda/EXM software package.

Results

The predicted specific voxel S-value kernels exhibited good agreement with the MC-based kernels serving as reference with a mean relative absolute error (MRAE) of 4.5 ± 1.8 (%). Bland and Altman analysis showed the lowest dose bias (2.6%) and smallest variance (CI: − 6.6, + 1.3) for DNN. The MRAE of estimated absorbed dose between DNN, MSV, and SSV with respect to the MC simulation reference were 2.6%, 3%, and 49%, respectively. In organ-level dosimetry, the MRAE between the proposed method and MSV, SSV, and Olinda/EXM were 5.1%, 21.8%, and 23.5%, respectively.

Conclusion

The proposed DNN-based WB internal dosimetry exhibited comparable performance to the direct Monte Carlo approach while overcoming the limitations of conventional dosimetry techniques in nuclear medicine.

Evaluation of Fluence Correction Algorithms in Multispectral Photoacoustic Imaging

Multispectral photoacoustic imaging (MPAI) is a promising emerging diagnostic technology, but fluence artifacts can degrade device performance. Our goal was to develop well-validated phantom-based test methods for evaluating and comparing MPAI fluence correction algorithms, including a heuristic diffusion approximation, Monte Carlo simulations, and an algorithm we developed based on novel application of the diffusion dipole model (DDM). Phantoms simulated a range of breast-mimicking optical properties and contained channels filled with chromophore solutions (ink, hemoglobin, or copper sulfate) or connected to a previously developed blood flow circuit providing tunable oxygen saturation (SO₂). The DDM algorithm achieved similar spectral recovery and SO₂ measurement accuracy to Monte Carlo-based corrections with lower computational cost, potentially providing an accurate, real-time correction approach. Algorithms were sensitive to optical property uncertainty, but error was minimized by matching phantom albedo. The developed test methods may provide a foundation for standardized assessment of MPAI fluence correction algorithm performance.

Monte Carlo Modeling of the Agility MLC for IMRT and VMAT Calculations

BACKGROUND/AIM

The Purpose of this study was to develop a Monte Carlo (MC) model for the Agility multileaf collimator (MLC) mounted and to validate its accuracy.

MATERIALS AND METHODS

To describe the Agility MLC in the BEAMnrc MC code, an existing component module code was modified to include its characteristics. The leaf characterization of the MC model was validated by comparing the calculated interleaf transmission and tongue-and-groove effect with EBT2 film and diode measurements and IMRT and VMAT calculations with film measurements.

RESULTS

Agreement between mean calculated and measured leaf transmissions was within 0.1%. The discrepancy between MC calculation and measurement in a static irregular field was less than 2%/2 mm. Gamma analysis of the comparison of MC and EBT2 film measurements in IMRT and VMAT fields yielded pass rates of 99.1% and 99.5% with 3%/3 mm criteria, respectively.

CONCLUSION

Our findings demonstrate the accuracy of the MC model using an adapted BEAMnrc component module for the Agility MLC.

The use of a CZT detector with robotic systems

This work is focused on the use of a CZT detector for a radiation mapping with an industrial robotic arm. Measurements were carried out within the RadioRoSo experiment (Radioactive Waste Robotic Sorter), under the umbrella of EU FP7 project ECHORD++. In tests with a dual-arm robot and standard point sources of ¹³⁷Cs and ⁶⁰Co, a Magnox waste was mimicked. Thereafter, for relevant measurement geometries and selected shielding materials, full energy peak efficiencies were calculated using the MCNP transport code. Simulated FEP efficiency values were used for minimum detectable activity assessments for expected measurement conditions. Obtained results would be also applicable for cases of shielded lost/orphan point-like sources.

EGSnrc-based depth-dependent photon energy response and phantom scatter corrections for low-energy brachytherapy sources

In the present study, beam quality correction, [Formula: see text], and phantom scatter correction, k_phan(r), for low-energy brachytherapy sources, ¹³¹Cs, ¹²⁵I, and ¹⁰³Pd, are calculated using the Monte Carlo-based EGSnrc code system as a function of the distance along the transverse axis of the source. The solid-state detectors investigated are diamond, LiF, Li₂B₄O₇, Al₂O₃, and radiochromic films, such as HS, EBT, EBT2, EBT3, RTQA, XRT, and XRQA. The solid phantoms investigated are polystyrene, PMMA, virtual water, solid water, plastic water (LR), A150, RW1, RW3, and WE210. For a given detector and brachytherapy source, [Formula: see text] is independent of distance in the water phantom. Meanwhile, for a given detector, k_phan(r) depends on the distance from the source for the investigated solid phantoms. Moreover, the k_phan(r) values do not change with the detector type for sources ¹³¹Cs, ¹²⁵I, and ¹⁰³Pd at all distances. The LR and A150 phantoms are water equivalent for the investigated distances of 1-5 cm. The phantoms including solid water, virtual water, and WE210 are not water-equivalent for distances beyond 1 cm. Furthermore, PMMA, polystyrene, RW1, and RW3 are not water equivalent.

Comparison between codes MCNPX and Gate/Geant4 in volume fraction studies

Knowing the volume fraction in a multiphase flow is of fundamental importance in predicting the performance of many systems and processes, it has been possible to model an experimental apparatus for volume fraction studies using Monte Carlo codes. Artificial neural networks have been applied for the recognition of the pulse height distributions in order to obtain the prediction of the volume fractions of the flow. In this sense, some researchers are unsure of which Monte Carlo code to use for volume fractions studies in two-phase flows. This work aims to model a biphasic flow (water and air) experiment in a stratified regime in two Monte Carlo-based codes (MCNP-X and Gate/Geant4), and to verify which one has the greatest benefits for researchers, focusing on volume fractions studies.

Comparison of different methods for the shielding analysis of an AB-BNCT facility based on the Be(p,xn) reaction with 30-MeV protons

Five shielding calculation methods were employed to estimate the dose rate distribution around an accelerator-based boron neutron capture therapy facility. Their performances were compared in terms of accuracy and efficiency. The results indicate that the hybrid deterministic/Monte Carlo method is the most efficient in the context of accurate modeling and simulation, whereas the analytical approximation with pre-generated source terms and attenuation lengths is preferable in the design phase because of its simplicity and ease of verification while retaining a reasonable accuracy.

In silico exploration of the fingerprints triggering modulation of glutaminyl cyclase inhibition for the treatment of Alzheimer's disease using SMILES based attributes in Monte Carlo optimization

Alzheimer's disease is the most common neurodegenerative disorder and being a social burden Alzheimer's has become an economic liability on developing countries. With limited understanding regarding the cause of disease, it is commonly identified by extracellular deposit of amyloid β (Aβ) peptides as senile plaques. Pyroglutamated Aβ is identified from the brain of AD patients and constituted the majority of total Aβ present. The formation of Pyroglutamated Aβ could be hindered by the use of Glutaminyl cyclase inhibitors and could efficiently improve the symptoms of Alzheimer's. The literature revealed the competence of quantitative structure activity/property relationship studies in drug discovery. The present work explores the efficiency of Monte Carlo based QSAR modelling studies on a dataset of 125 Glutaminyl cyclase inhibitors with pKi taken as the endpoint for QSAR analysis. The dataset is divided into training, subtraining, calibration and validation sets resulting in the generation of five random splits. The validation is performed in accordance with the Organization of Economic Corporation and Development principles. The values of R², Q², index of ideality of correlation, concordance correlation coefficient, av. rm2 and delta rm2 of calibration set of the best split are found to be 0.9012, 0.8775, 0.9479, 0.9435, 0.8347 and 0.0847, respectively. The structural features responsible for increasing the inhibitory activity are identified. These structural features are added to a base compound from the dataset to design six novel molecules. These new molecules possess improved inhibitory activity as compare to the base compound. The results are further supported by docking studies.Communicated by Vsevolod Makeev.

Clinical implementation of a Monte Carlo based independent TPS dose checking system

The increase in complexity of treatment plans over time through modalities such as intensity modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT) has often not been met with an increase in capability of the secondary dose calculation checking systems typically used to verify the treatment planning system. Monte Carlo (MC) codes such as EGSnrc have become easily available and are capable of performing calculations of highly complex radiotherapy treatments. This educational note demonstrates a method for implementing and using a fully automated system for performing and analysing full MC calculations of conformal, IMRT and VMAT radiotherapy plans. Example calculations were based on BEAMnrc/DOSXYZnrc and are performed automatically after either uploading exported plan DICOM data through a Python-based web interface, or exporting DICOM data to a monitored network location. This note demonstrates how completed MC calculations can then be analysed using an automatically generated dose point comparison report, or easily re-imported back into the treatment planning system. Agreement between the TPS and MC calculation was an improvement on agreement between RadCalc and the TPS, with differences ranging from 1.2 to 5.5% between RadCalc and the treatment planning system (TPS), and 0.1-1.7% between MC and TPS. Comparison of the dose-volume histogram (DVH) parameters [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text] for the example VMAT plans showed agreement for the mean planning target volume dose within [Formula: see text], [Formula: see text] and [Formula: see text] generally within [Formula: see text] with the exception of a brain case, and [Formula: see text] within [Formula: see text]. Overall, this note provides a demonstration of a system that has been integrated well into existing clinical workflow, and has been shown to be a valuable additional tool in the secondary checking of treatment plan calculations.

A Monte Carlo model of synchrotron radiotherapy shows good agreement with experimental dosimetry measurements: Data from the imaging and medical beamline at the Australian Synchrotron

Experimental measurement of Synchrotron Radiotherapy (SyncRT) doses is challenging, especially for Microbeam Radiotherapy (MRT), which is characterised by very high dynamic ranges with spatial resolutions on the micrometer scale. Monte Carlo (MC) simulation is considered a gold standard for accurate dose calculation in radiotherapy, and is therefore routinely relied upon to produce verification data. We present a MC model for Australian Synchrotron's Imaging and Medical Beamline (IMBL), which is capable of generating accurate dosimetry data to inform and/or verify SyncRT experiments. Our MC model showed excellent agreement with dosimetric measurement for Synchrotron Broadbeam Radiotherapy (SBBR). Our MC model is also the first to achieve validation for MRT, using two methods of dosimetry, to within clinical tolerances of 5% for a 20×20 mm² field size, except for surface measurements at 5 mm depth, which remained to within good agreement of 7.5%. Our experimental methodology has allowed us to control measurement uncertainties for MRT doses to within 5-6%, which has also not been previously achieved, and provides a confidence which until now has been lacking in MRT validation studies. The MC model is suitable for SyncRT dose calculation of clinically relevant field sizes at the IMBL, and can be extended to include medical beamlines at other Synchrotron facilities as well. The presented MC model will be used as a validation tool for treatment planning dose calculation algorithms, and is an important step towards veterinary SyncRT trials at the Australian Synchrotron.