Molecular Dynamics and Other HPC Simulations for Drug Discovery

High performance computing (HPC) is taking an increasingly important place in drug discovery. It makes possible the simulation of complex biochemical systems with high precision in a short time, thanks to the use of sophisticated algorithms. It promotes the advancement of knowledge in fields that are inaccessible or difficult to access through experimentation and it contributes to accelerating the discovery of drugs for unmet medical needs while reducing costs. Herein, we report how computational performance has evolved over the past years, and then we detail three domains where HPC is essential. Molecular dynamics (MD) is commonly used to explore the flexibility of proteins, thus generating a better understanding of different possible approaches to modulate their activity. Modeling and simulation of biopolymer complexes enables the study of protein-protein interactions (PPI) in healthy and disease states, thus helping the identification of targets of pharmacological interest. Virtual screening (VS) also benefits from HPC to predict in a short time, among millions or billions of virtual chemical compounds, the best potential ligands that will be tested in relevant assays to start a rational drug design process.

Generation and comparison of 3D dosimetric reference datasets for COMS eye plaque brachytherapy using model-based dose calculations

PURPOSE

A joint Working Group of the American Association of Physicists in Medicine (AAPM), the European Society for Radiotherapy and Oncology (ESTRO), and the Australasian Brachytherapy Group (ABG) was created to aid in the transition from the AAPM TG-43 dose calculation formalism, the current standard, to model-based dose calculations. This work establishes the first test cases for low-energy photon-emitting brachytherapy using model-based dose calculation algorithms (MBDCAs).

ACQUISITION AND VALIDATION METHODS

Five test cases are developed: (1) a single model 6711 125 I brachytherapy seed in water, 13 seeds (2) individually and (3) in combination in water, (4) the full Collaborative Ocular Melanoma Study (COMS) 16 mm eye plaque in water, and (5) the full plaque in a realistic eye phantom. Calculations are done with four Monte Carlo (MC) codes and a research version of a commercial treatment planning system (TPS). For all test cases, local agreement of MC codes was within ∼2.5% and global agreement was ∼2% (4% for test case 5). MC agreement was within expected uncertainties. Local agreement of TPS with MC was within 5% for test case 1 and ∼20% for test cases 4 and 5, and global agreement was within 0.4% for test case 1 and 10% for test cases 4 and 5.

DATA FORMAT AND USAGE NOTES

Dose distributions for each set of MC and TPS calculations are available online (https://doi.org/10.52519/00005) along with input files and all other information necessary to repeat the calculations.

POTENTIAL APPLICATIONS

These data can be used to support commissioning of MBDCAs for low-energy brachytherapy as recommended by TGs 186 and 221 and AAPM Report 372. This work additionally lays out a sample framework for the development of test cases that can be extended to other applications beyond eye plaque brachytherapy.

A GPU-based fast Monte Carlo code that supports proton transport in magnetic field for radiation therapy

This paper presents the effort to extend a previously reported code ARCHER, a GPU-based Monte Carlo (MC) code for coupled photon and electron transport, into protons including the consideration of magnetic fields. The proton transport is modeled using a Class-II condensed-history algorithm with continuous slowing-down approximation. The model includes ionization, multiple scattering, energy straggling, elastic and inelastic nuclear interactions, as well as deflection due to the Lorentz force in magnetic fields. An additional direction change is added for protons at the end of each step in the presence of the magnetic field. Secondary charge particles, except for protons, are terminated depositing kinetic energies locally, whereas secondary neutral particles are ignored. Each proton is transported step by step until its energy drops to below 0.5 MeV or when the proton leaves the phantom. The code is implemented using the compute unified device architecture (CUDA) platform for optimized GPU thread-level parallelism and efficiency. The code is validated by comparing it against TOPAS. Comparisons of dose distributions between our code and TOPAS for several exposure scenarios, ranging from single square beams in water to patient plan with magnetic fields, show good agreement. The 3D-gamma pass rate with a 2 mm/2% criterion in the region with dose greater than 10% of the maximum dose is computed to be over 99% for all tested cases. Using a single NVIDIA TITAN V GPU card, the computational time of ARCHER is found to range from 0.82 to 4.54 seconds for 1 × 107 proton histories. Compared to a few hours running on TOPAS, this speed improvement is significant. This work presents, for the first time, the performance of a GPU-based MC code to simulate proton transportation magnetic fields, demonstrating the feasibility of accurate and efficient dose calculations in potential magnetic resonance imaging (MRI)-guided proton therapy.

Artificial Neural Network (ANN)-Based Determination of Fractional Contributions from Mixed Fluorophores using Fluorescence Lifetime Measurements

Here we present an artificial neural network (ANN)-approach to determine the fractional contributions Pi from fluorophores to a multi-exponential fluorescence decay in time-resolved lifetime measurements. Conventionally, Pi are determined by extracting two parameters (amplitude and lifetime) for each underlying mono-exponential decay using non-linear fitting. However, in this case parameter estimation is highly sensitive to initial guesses and weighting. In contrast, the ANN-based approach robustly gives the Pi without knowledge of amplitudes and lifetimes. By experimental measurements and Monte-Carlo simulations, we comprehensively show that accuracy and precision of Pi determination with ANNs and hence the number of distinguishable fluorophores depend on the fluorescence lifetimes' differences. For mixtures of up to five fluorophores, we determined the minimum uniform spacing Δτmin between lifetimes to obtain fractional contributions with a standard deviation of 5%. In example, five lifetimes can be distinguished with a respective minimum uniform spacing of approx. 10 ns even when the fluorophores' emission spectra are overlapping. This study underlines the enormous potential of ANN-based analysis for multi-fluorophore applications in fluorescence lifetime measurements.

ZAFG Method for Quantitative Characterization of Spherical Particles: Deriving a Universal Equation for Geometrical Correction

This study introduces a universal equation to calculate the geometrical correction factor (G) as the fourth factor in the conventional ZAF method for quantifying spherical particles (specifically, NIST-K411 glass microspheres mounted on bulk carbon substrate). Note that the fluorescence correction factor (F) is not considered in this study. Our findings demonstrate that the G factor, as a function of the particle diameter (D) and the range of emitted X-rays in a bulk sample (Xe), provides the best model. Xe depends on the chemical composition and accelerating voltage. We observed excellent agreement between the G factor predicted by our model and experimental data obtained from NIST-K411 standard particles. Our results show that when Xe is greater than D, the G factor decays exponentially, independent of the incident electron energy, X-ray lines, and chemical composition of the particles. We also found that when DXe > 1, the particle behaves as a bulk sample, and G = 1. Notably, our data indicate that the G factor depends only on DXe, not on the chemical composition or beam energy.

Investigating the correlation between chemical parameters, risk assessment, and sensitivity analysis of fluoride and nitrate in regional groundwater sources using Monte Carlo

Groundwater is one of the most important sources of drinking and irrigation water in arid and semi-arid areas. This study aimed to investigate the chemical quality of groundwater for drinking and irrigation, assess the non-carcinogenic risk factors resulting from the concentration of fluoride and nitrate ions, and analyze the sensitivity among children, teenagers, and adults using Monte Carlo method. A total of 171 samples were obtained from confined groundwater in Arsanjan. Among other hydrological parameters of water, EC had the highest average (1135.97). TDS ranged from 67.90 to 1878.30 mg/L, with the lowest and highest total hardness values being 2.90 and 680.8, respectively. The water quality index (WQI) results indicated that 33% of the samples were at the poor water level and the irrigation (IWQI) was less than 25 in 96.36% of the samples, which were categorized as excellent. Thus, the majority of the samples were suitable for irrigation purposes. Additionally, the oral and dermal health risks of fluoride and nitrate were less than 1 in all age groups. Concentration factor was the main indicator in the assessment of the non-carcinogenic risk factors of nitrate and fluoride. The results of sensitivity analysis revealed a reverse relationship with body weight. Further, the results of principal component analysis (PCA) showed a negative relationship between fluoride concentration and pH. Hierarchical cluster analysis also showed that the study variables belonged to three main clusters. Some elements in C1 were also found in the first factor in PCA. The elements in C2 were among the dominant compounds of the groundwater resources of the study area, which may be caused by earth cations or human activities. C3 variables may also be one of the consequences of fertilizer use in areas around groundwater sources.

Effects of tissue heterogeneity and comparisons of collapsed cone and Monte Carlo fast neutron patient dosimetry using the University of Washington clinical neutron therapy system (CNTS)

Fast neutron therapy is a high linear energy transfer (LET) radiation treatment modality offering advantages over low LET radiations. Multileaf collimator technology reduces normal-tissue dose (toxicity) and makes neutron therapy more comparable to MV x-ray treatments. Published clinical-trial and other experiences with fast neutron therapy are reported. Early comparative studies failed to consider differences in target-dose spatial conformality between x-ray and neutron treatments, which is especially important for organs-at-risk close to tumor targets. Treatments planning systems (TPS) for high-energy neutrons lag behind TPS tools for MV x-rays, creating challenges for comparative studies of clinical outcomes. A previously published Monte Carlo model of the University of Washington (UW) Clinical Neutron Therapy System (CNTS) is refined and integrated with the RayStation TPS as an external dose planning/verification tool. The collapsed cone (CC) dose calculations in the TPS are based on measured dose profiles and output factors in water, with the absolute dose determined using a tissue-equivalent ionization chamber. For comparison, independent (external) Monte Carlo simulation computes dose on a voxel-by-voxel basis using an atlas that maps Hounsfield Unit (HU) numbers to elemental composition and density. Although the CC algorithm in the TPS accurately computes neutron dose to water compared to Monte Carlo calculations, calculated dose to water differs from bone or tissue depending largely on hydrogen content. Therefore, the elemental composition of tissue and bone, rather than the material or electron density, affects fast neutron dose. While the CC algorithm suffices for reproducible patient dosimetry in fast neutron therapy, adopting methods that consider tissue heterogeneity would enhance patient-specific neutron dose accuracy relative to national standards for other types of ionizing radiation. Corrections for tissue composition have a significant impact on absolute dose and the relative biological effectiveness (RBE) of neutron treatments compared to other radiation types (MV x-rays, protons, and carbon ions).

The influence of different versions of FLUKA and GEANT4 on the calculation of response functions of ionization chambers in clinical proton beams

Objective.To investigate the influence of different versions of the Monte Carlo codesgeant4 andflukaon the calculation of overall response functionsfQof air-filled ionization chambers in clinical proton beams.Approach. fQfactors were calculated for six plane-parallel and four cylindrical ionization chambers withgeant4 andfluka. These factors were compared to already published values that were derived using older versions of these codes.Main results.Differences infQfactors calculated with different versions of the same Monte Carlo code can be up to ∼1%. Especially forgeant4, the updated version leads to a more pronounced dependence offQon proton energy and to smallerfQfactors for high energies.Significance.Different versions of the same Monte Carlo code can lead to differences in the calculation offQfactors of up to ∼1% without changing the simulation setup, transport parameters, ionization chamber geometry modeling, or employed physics lists. These findings support the statement that the dominant contributor to the overall uncertainty of Monte Carlo calculatedfQfactors are type-B uncertainties.

[Pollution Level and Risk Assessment of OPEs in Typical River Basins of China]

Organophosphate esters(OPEs), as a substitute for brominated flame retardants, are widely used in production and life, and their environmental pollution and toxic effects have attracted widespread attention. In this study, the concentrations and distribution characteristics of OPEs in seven major drainage basins of China were sorted out. The average daily dose of OPEs in Chinese adults, adolescents, and children was calculated to assess the health risks, and the reliability of the results was evaluated using Monte Carlo simulation. The toxic effect concentrations of 12 OPEs on aquatic organisms were investigated, and the species sensitivity distribution(SSD) curve was constructed to assess the ecological risk. The results showed that the 5th percentile concentration of ΣOPEs in the seven drainage basins was 52.61 ng·L-1 under the low exposure scenario. The median concentration of ΣOPEs in the seven basins was 499.74 ng·L-1, with trichloroethyl phosphate(TCEP), triethyl phosphate(TEP), and triethyl phosphate(1,3-dichloro-2-propyl) esters(TDCP) as the main contaminants. Under the high exposure scenario, the 95th percentile concentration of ΣOPEs in the seven basins was 1904.4 ng·L-1, 3.8 times that of the intermediate exposure scenario, and the Yangtze River Basin had the highest ΣOPEs concentration under the high exposure scenario. The health risk assessment showed that the non-carcinogenic risk of OPEs exposure through drinking water was within acceptable limits for different populations. Trimethyl phosphate(TMP), triisobutyl phosphate(TiBP), and TCEP were the main contributors to cancer risk. The results of ecological risk assessment showed that TCEP had medium ecological risk at the high exposure level, tributyl phosphate(TnBP) had medium ecological risk under the intermediate exposure scenario, and there was higher ecological risk under the high exposure scenario. Triphenyl phosphate(TPhP) had a risk quotient greater than 1 under the low, intermediate, and high exposure scenarios, and there was a high ecological risk, which requires special attention.

Monte Carlo Approach to the Evaluation of Nanoparticles Size Distribution from the Analysis of UV-Vis-NIR Spectra

How nice would it be to obtain the size distribution of a nanoparticle dispersion fast and without electron microscope measurements? UV-Vis-NIR spectrophotometry offers a very rapid solution; however, the spectra interpretation can be very challenging and needs to take into account the size distribution of the nanoparticles and agglomeration. This work suggests a Monte Carlo method for rapid fitting UV-Vis-NIR spectra using one or two size distributions starting from a dataset of precomputed spectra based on Mie theory. The proposed algorithm is tested on copper nanoparticles produced with Pulsed Laser Ablation in Liquid and on gold nanoparticles from the literature. The fitted distribution results are comparable with Transmission Electron Microscope results and, in some cases, reflect the presence of agglomeration.

Two- and Three-Dimensional Modeling and Simulations of Grain Growth Behavior in Dual-Phase Steel Using Monte Carlo and Machine Learning

Dual-phase (DP) steel has been widely used in automotive steel plates with a balance of excellent strength and ductility. Grain refinement in DP steel is important to improve the properties further; however, the factors affecting grain growth need to be well understood. The remaining problem is that acquiring data through experiments is still time-consuming and difficult to evaluate quantitatively. With the development of materials informatics in recent years, material development time and costs are expected to be significantly reduced through experimentation, simulation, and machine learning. In this study, grain growth behavior in DP steel was studied using two-dimensional (2D) and three-dimensional (3D) Monte Carlo modeling and simulation to estimate the effect of some key parameters. Grain growth can be suppressed when the grain boundary energy is greater than the phase boundary energy. When the volume fractions of the matrix and the second phase were equal, the suppression of grain growth became obvious. The long-distance diffuse frequency can promote grain growth significantly. The simulation results allow us to better understand the factors affecting grain growth behavior in DP steel. Machine learning was performed to conduct a sensitivity analysis of the affecting parameters and estimate the magnitude of each parameter's effects on grain growth in the model. Combining MC simulation and machine learning will provide one promising research strategy to gain deeper insights into grain growth behaviors in metallic materials and accelerate the research process.

A torus source and its application for non-primary radiation evaluation

Objective. Non-primary radiation doses to normal tissues from proton therapy may be associated with an increased risk of secondary malignancies, particularly in long-term survivors. Thus, a systematic method to evaluate if the dose level of non-primary radiation meets the IEC standard requirements is needed.Approach. Different from the traditional photon radiation therapy system, proton therapy systems are composed of several subsystems in a thick bunker. These subsystems are all possible sources of non-primary radiation threatening the patient. As a case study, 7 sources in the P-Cure synchrotron-based proton therapy system are modeled in Monte Carlo (MC) code: tandem injector, injection, synchrotron ring, extraction, beam transport line, scanning nozzle and concrete reflection/scattering. To accurately evaluate the synchrotron beam loss and non-primary dose, a new model called the torus source model is developed. Its parametric equations define the position and direction of the off-orbit particle bombardment on the torus pipe shell in the Cartesian coordinate system. Non-primary doses are finally calculated by several FLUKA simulations.Main results. The ratios of summarized non-primary doses from different sources to the planned dose of 2 Gy are all much smaller than the IEC requirements in both the 15-50 cm and 50-200 cm regions. Thus, the P-Cure synchrotron-based proton therapy system is clean and patient-friendly, and there is no need an inner shielding concrete between the accelerator and patient.Significance. Non-primary radiation dose level is a very important indicator to evaluate the quality of a PT system. This manuscript provides a feasible MC procedure for synchrotron-based proton therapy with new beam loss model. Which could help people figure out precisely whether this level complies with the IEC standard before the system put into clinical treatment. What' more, the torus source model could be widely used for bending magnets in gantries and synchrotrons to evaluate non-primary doses or other radiation doses.

Commissioning of Aktina SRS cones and dosimetric validation of the RayStation photon Monte Carlo dose calculation algorithm

Clinical implementation of SRS cones demands particular experimental care and dosimetric considerations in order to deliver precise and safe radiotherapy to patients. The purpose of this work was to present the commissioning data of recent Aktina cones combined with a 6MV flattened beam produced by an Elekta VersaHD linear accelerator. Additionally, the modelling process, and an assessment of dosimetric accuracy of the RayStation Monte Carlo dose calculation algorithm for cone based SRS was performed. There are currently no studies presenting beam data for this equipment and none that outlines the modelling parameters and validation of dose calculation using RayStation's photon Monte Carlo dose engine with cones. Beam data was measured using an SFD and a microDiamond and benchmarked against EBT3 film for cones of diameter 5-39 mm. Modelling was completed and validated within homogeneous and heterogeneous phantoms. End-to-end image-guided validation was performed using a StereoPHAN™ housing, an SRS MapCHECK and EBT3 film, and calculation time was investigated as a function of statistical uncertainty and field diameter. The TPS calculations agreed with measured data within their estimated uncertainties and clinical treatment plans could be calculated in under a minute. The data presented serves as a reference for others commissioning Aktina stereotactic cones and the modelling parameters serve similarly, while providing a starting point for those commissioning the same TPS algorithm for use with cones. It has been shown in this work that RayStation's Monte Carlo photon dose algorithm performs satisfactorily in the presence of SRS cones.

Hydrochemistry, quality, and integrated health risk assessments of groundwater in the Huaibei Plain, China

Groundwater is an essential freshwater resource utilized in industry, agriculture, and daily life. In the Huaibei Plain (HBP), where groundwater significantly influences socio-economic development, information about its quality, hydrochemistry, and related health risks remains limited. We conducted a comprehensive groundwater sampling in the HBP and examined its rock characteristics, water quality index (WQI), and potential health risks. The results revealed that the primary factors shaping groundwater hydrochemistry were rock dissolution and weathering, cation exchange, and anthropogenic activities. WQI assessment indicated that only 73% of the groundwaters is potable, as Fe2+, Mn2+, NO3-, and F- contents in the water could pose non-carcinogenic hazards to humans. Children were more susceptible to these health risks through oral ingestion than adults. Uncertainty analysis indicated that the probabilities of non-carcinogenic risk were approximately 57% and 31% for children and adults, respectively. Sensitivity analysis further identified fluoride as the primary factor influencing non-carcinogenic risks, indicating that reducing fluoride contamination should be prioritized in future groundwater management in the HBP.

AgeSpectraAnalyst: A MATLAB based package to model zircon age distributions in silicic magmatic systems

In the last decade, improvements in the analytical precision achievable by zircon U-Pb geochronological techniques have allowed to resolve complexities of zircon crystallization histories in magmatic rocks to an unprecedented level. A number of studies have strived to link resolvable dispersion in zircon age spectra of samples from fossil magmatic systems to the physical parameters of their parent magma bodies. However, the methodologies developed have so far been limited to reproduce the effect of simple thermal histories on the final distribution of zircon ages. In this work we take a more nuanced approach, fine-tuning a thermodynamics-based zircon saturation model to predict the relative distribution of zircon ages in samples from silicic magma reservoirs experiencing open-system processes (e.g. heat/mass addition, mechanical mixing). Employing the MATLAB package (AgeSpectraAnalyst) presented in this contribution:•Users can forward model the effect that diverse thermal histories and mechanical mixing processes characteristic of silicic magma bodies have on zircon age distributions as measured by high-precision, chemical abrasion thermal ionization mass spectrometry (CA-ID-TIMS) U-Pb geochronology.•Zircon CA-ID-TIMS datasets from silicic magmatic systems can be easily compared with model output to gain semi-quantitative information on thermo-mechanical history of the system of interest.•We demonstrated (Tavazzani et al., in press) that distribution of high-precision zircon ages in crystallized remnants of shallow (∼ 250 MPa), silicic magma reservoirs can discriminate between systems that experienced catastrophic, caldera-forming eruptions and systems that underwent monotonic cooling histories.

Monte Carlo dosimetry of a novel Yttrium-90 disc source for episcleral brachytherapy

PURPOSE

To calculate the dose distribution using Monte Carlo simulations for a novel high-dose-rate Yttrium-90 (Y-90) disc source recently developed for episcleral brachytherapy and provide a lookup table for treatment planning.

METHODS

Monte Carlo simulations were performed to calculate the in-water dose distribution of the Y-90 disc source using the "GATE", a software based on the "Geant4" Monte Carlo simulation toolkit developed by the international OpenGATE collaboration. The geometry of this novel beta source, its capsule, and the surrounding water medium were accurately modeled in the simulation input files. The standard Y-90 element beta spectrum from ICRU 72 was used, and the physics processes for beta and photon interactions with matters were all included. The dose distribution of this Y-90 disc source was measured in a separate study using Gafchromic EBT-3 films and the results were reported elsewhere. To match the setup of the experiment, a Gafchromic EBT-3 film was also included in the simulation geometry. The simulated dose profiles were exported from the 3D dose distribution results and compared with the measured dose profiles. Transverse dose profiles at different distances from the seed surface were also obtained to study the lateral coverage of the source.

RESULTS

The measured percent depth dose (PDD) curves along the central axis perpendicular to the surface of the Y-90 disc were constructed from the experimental and simulated data, and normalized to the reference point at 1 mm from the source capsule. Both PDD curves agreed well up to 4 mm from the source surface (maximum difference ± 10%) but deviated from each other beyond 4 mm. The deviation might be caused by the increased measurement uncertainty in the low-dose region. The dose rate at the reference point calculated from the Monte Carlo simulation was 1.09 cGy/mCi-s and agreed very well with the measured dose rate of 1.05 cGy/mCi-s. If the 80% isodose line is selected as the lateral coverage, the lateral dose coverage is maximal (∼4.5 mm) at the plane next to the source surface, and gradually decreases with the increasing distance, approaching 3.5 mm when the plane is 5 mm from the 6-mm diameter source surface.

CONCLUSION

Monte Carlo simulations were successfully performed to confirm the measured PDD curve of the novel Y-90 disc source. This simulation work laid a solid foundation for characterizing the full dosimetry parameters of this source for episcleral brachytherapy applications.

Comparison of calibration coefficients for a vinten ionization chamber simulated using four Monte Carlo methods

The Vinten 671 ionization chamber (VIC) was modelled using Monte Carlo (MC) programs EGSnrc, Penelope, and TOPAS. Several national measurement institutes have VICs with well-characterized response relationships and have measured calibration coefficients for many radionuclides. Twelve radionuclides with various decay emissions were assessed as well as 14 monoenergetic photon sources and 10 monoenergetic electron sources. Calibration coefficients were calculated based on the energy deposited in the simulated VIC nitrogen gas volume and compared to experimental values from the literature.

Radiation-Driven Polymerisation of Methacrylic Acid in Aqueous Solution: A Chemical Events Monte Carlo Study

This study employed a coarse-grained Monte Carlo (MC) simulation to investigate the radiation-induced polymerisation of methacrylic acid (MAA) in an aqueous solution. This method provides an alternative to traditional kinetic models, enabling a detailed examination of the micro-structure and growth patterns of MAA polymers, which are often not captured in other approaches. In this work, we generated multiple clones of a simulation box, each containing a specific chemical composition. In these simulations, every coarse-grained (CG) bead represents an entire monomer. The growth function, defined by the chemical behaviour of interacting substances, was determined through repeated random sampling. This approach allowed us to simulate the complex process of radiation-induced polymerisation, enhancing our understanding of the formation of poly(methacrylic acid) hydrogels at a microscopic level; while Monte Carlo simulations have been applied in various contexts of polymerisation, this study's specific approach to modelling the radiation-induced polymerisation of MAA in an aqueous environment, utilising the data obtained by quantum chemistry modelling, with an emphasis on micro-structural growth, has not been extensively explored in existing studies. This understanding is important for advancing the synthesis of these hydrogels, which have potential applications in diverse fields such as materials science and medicine.

Monte Carlo simulations and phantom modeling for spatial frequency domain imaging of surgical wound monitoring

Significance

Postoperative surgical wound infection is a serious problem around the globe, including in countries with advanced healthcare systems, and a method for early detection of infection is urgently required.

Aim

We explore spatial frequency domain imaging (SFDI) for distinguishing changes in surgical wound healing based on the tissue scattering properties and surgical wound width measurements.

Approach

A comprehensive numerical method is developed by applying a three-dimensional Monte Carlo simulation to a vertical heterogeneous wound model. The Monte Carlo simulation results are validated using resin phantom imaging experiments.

Results

We report on the SFDI lateral resolution with varying reduced scattering value and wound width and discuss the partial volume effect at the sharp vertical boundaries present in a surgical incision. The detection sensitivity of this method is dependent on spatial frequency, wound reduced scattering coefficient, and wound width.

Conclusions

We provide guidelines for future SFDI instrument design and explanation for the expected error in SFDI measurements.

Comparison of the accuracy of Monte Carlo and Ray Tracing dose calculation algorithms for multiple target brain treatments on CyberKnife

Single plan multiple brain targets (MBT) stereotactic radiosurgery dose difference between Monte Carlo (MC) and Ray Tracing (RT) algorithms has not been studied. A retrospective study and dose measurements were performed to access factors influencing dose differences. Fifty-three RT treatment plans with a total of 209 brain metastases were extracted from Precision Treatment Planning System (TPS). These plans were generated using fixed cones and were delivered using the CyberKnife M6 system. The same treatment plans were recalculated using MC algorithm and keeping the beam parameters unchanged. MC calculated plan parameters were extracted and dose differences were normalised to MC calculated dose. Correlations were investigated. RT and MC calculated off-centre-ratio (OCR) and tissue-phantom-ratio (TPRs) were exported from the TPS and compared with measured. Plans with 5 gross tumour volumes (GTVs) were created on a phantom and dose measured using a CC04 ionisation chamber and microdiamond detector for comparison with calculated doses. Calculated and measured TPR agreed within ± 1% beyond depth of maximum dose. The OCR showed differences up to 4.3% in the penumbra and out-of-field (OOF) regions. Largest RT and MC calculated GTV mean dose difference was - 5.7%. An increase in the number of GTVs and reduction in the geometric separation of metastases were associated with increased differences between RT and MC calculated doses. In conclusion, calculated dose disagreement in MBT depends on the number of GTVs per plan, number of GTVs within a certain separation distance and plan complexity. MC dose calculation is recommended for complex CyberKnife SRS of MBT.

A Monte Carlo dose recalculation pipeline for durable datasets: an I-125 LDR prostate brachytherapy use case

Monte Carlo (MC) dose datasets are valuable for large-scale dosimetric studies. This work aims to build and validate a DICOM-compliant automated MC dose recalculation pipeline with an application to the production of I-125 low dose-rate prostate brachytherapy MC datasets. Built as a self-contained application, the recalculation pipeline ingested clinical DICOM-RT studies, reproduced the treatment into the Monte Carlo simulation, and outputted a traceable and durable dose distribution in the DICOM dose format. MC simulations with TG43-equivalent conditions using both TOPAS andegs_brachyMC codes were compared to TG43 calculations to validate the pipeline. The consistency of the pipeline when generating TG186 simulations was measured by comparing simulations made with both MC codes. Finally,egs_brachysimulations were run on a 240-patient cohort to simulate a large-scale application of the pipeline. Compared to line source TG43 calculations, simulations with both MC codes had more than 90% of voxels with a global difference under ±1%. Differences of 2.1% and less were seen in dosimetric indices when comparing TG186 simulations from both MC codes. The large-scale comparison ofegs_brachysimulations with treatment planning system dose calculation seen the same dose overestimation of TG43 calculations showed in previous studies. The MC dose recalculation pipeline built and validated against TG43 calculations in this work efficiently produced durable MC dose datasets. Since the dataset could reproduce previous dosimetric studies within 15 h at a rate of 20 cases per 25 min, the pipeline is a promising tool for future large-scale dosimetric studies.

Developing of Lead/Polyurethane Micro/Nano Composite for Nuclear Shielding Novel Supplies: γ-Spectroscopy and FLUKA Simulation Techniques

In this work, the effect of adding Pb nano/microparticles in polyurethane foams to improve thermo-physical and mechanical properties were investigated. Moreover, an attempt has been made to modify the micron-sized lead metal powder into nanostructured Pb powder using a high-energy ball mill. Two types of fillers were used, the first is Pb in micro scale and the second is Pb in nano scale. A lead/polyurethane nanocomposite is made using the in-situ polymerization process. The different characterization techniques describe the state of the dispersion of fillers in foam. The effects of these additions in the foam were evaluated, Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), transmission electron microscopy (TEM), and X-ray diffraction (XRD) have all been used to analyze the morphology and dispersion of lead in polyurethane. The findings demonstrate that lead is uniformly distributed throughout the polyurethane matrix. The compression test demonstrates that the inclusion of lead weakens the compression strength of the nanocomposites in comparison to that of pure polyurethane. The TGA study shows that the enhanced thermal stability is a result of the inclusion of fillers, especially nanofillers. The shielding efficiency has been studied, MAC, LAC, HVL, MFP and Zeff were determined either experimentally or by Monte Carlo calculations. The nuclear radiation shielding properties were simulated by the FLUKA code for the photon energy range of 0.0001-100 MeV.

A systematic approach for calibrating a Monte Carlo code to a treatment planning system for obtaining dose, LET, variable proton RBE and out-of-field dose

Objective. While integration of variable relative biological effectiveness (RBE) has not reached full clinical implementation, the importance of having the ability to recalculate proton treatment plans in a flexible, dedicated Monte Carlo (MC) code cannot be understated . Here we provide a step-wise method for calibrating dose from a MC code to a treatment planning system (TPS), to obtain required parameters for calculating linear energy transfer (LET), variable RBE and in general enabling clinical realistic research studies beyond the capabilities of a TPS.Approach. Initially, Pristine Bragg peaks (PBP) were calculated in both the Eclipse TPS and the FLUKA MC code. A rearranged Bortfeld energy-range relation was applied to the initial energy of the beam to fine-tune the range of the MC code at 80% dose level distal to the PBP. The energy spread was adapted by dividing the TPS range by the MC range for dose level 80%-20% distal to the PBP. Density and relative proton stopping power were adjusted by comparing the TPS and MC for different Hounsfield units. To find the relationship of dose per primary particle from the MC to dose per monitor unit in the TPS, integration was applied to the area of the Bragg curve. The calibration was validated for spread-out Bragg peaks (SOBP) in water and patient treatment plans. Following the validation, variable RBE were calculated using established models.Main results.The PBPs ranges were within ±0.3mm threshold, and a maximum of 5.5% difference for the SOBPs was observed. The patient validation showed excellent dose agreement between the TPS and MC, with the greatest differences for the lung tumor patient.Significance. Aprocedure for calibrating a MC code to a TPS was developed and validated. The procedure enables MC-based calculation of dose, LET, variable RBE, advanced (secondary) particle tracking and more from treatment plans.

[Accumulation Characteristics, Sources, and Health Risks of Soil Lead of Urban Parks in Beijing]

Urban parks have multiple functions such as social culture, economy, and environmental services during urban development. The rapid development of cities and economy may lead to the accumulation of heavy metals in the soil of urban parks, which may threaten human health. A total of 140 soil samples were collected in 32 typical parks in Beijing. The accumulation characteristics of Pb in the soil of urban parks were analyzed using the single-factor pollution and geo-accumulation indices. The sources of Pb pollution in soils were quantitatively analyzed using the stable isotope of Pb, and the health risk was assessed using the probabilistic risk assessment method based on Monte Carlo simulation. The results showed that the geometric mean of Pb in soils of urban parks in Beijing was 38.63 mg·kg-1, which was 1.48 times the background value. However, it did not exceed the risk screening value(GB 36600-2018). The accumulation of soil Pb in urban parks increased with the increase in the proximity between the park and the central urban area and the increase in the establishment time. The soil Pb pollution index of 2 ring, 2-4 ring, and 4-6 ring parks were 0.16, 0.10, and 0.09, which did not reach the pollution level, and the geo-accumulation indices were 0.80, 0.07, and -0.31, respectively. Except for the no-moderate pollution level in ring 2 and ring 2 to ring 4, the other rings did not reach the pollution level. The sources of Pb pollution in urban parks were coal combustion, road dust, and paint, with the contributions of 45.4%, 19.6%, and 13.9%, respectively. The 95% quantiles of hazard index(HI) of soil Pb in the park for different age groups were 1.11E-01, 8.57E-02, 6.39E-02, 1.64E-02, 1.36E-02, 1.26E-02, 1.64E-02, and 1.78E-02, respectively, which indicated that there was no potential non-carcinogenic risk(HI<1). Exposure duration was the most sensitive to non-carcinogenic risks in people aged 0-18 years, and soil Pb concentration was the most sensitive to non-carcinogenic risks in people aged 18-80 years. The increase in body weight often reduced the non-carcinogenic risks. These results can provide theoretical basis for soil environmental risk control in urban parks.

Microdosimetry-based investigation of biological effectiveness of252Cf brachytherapy source: TOPAS Monte Carlo study

Objective.To investigate biological effectiveness of252Cf brachytherapy source using Monte Carlo-calculated microdosimetric distributions.Approach.252Cf source capsule was placed at the center of the spherical water phantom and phase-space data were scored as a function of radial distance in water (R= 1-5 cm) using TOPAS Monte Carlo code. The phase-space data were used to calculate microdosimetric distributions at 1μm site size. Using these distributions, Relative Biological Effectiveness (RBE), mean quality factor (Q̅) and Oxygen Enhancement Ratio (OER) were calculated as a function ofR.Main results.The overall shapes of the microdosimetric distributions are comparable at all the radial distances in water. However, slight variation in the bin-wise yield is observed withR. RBE,Q̅and OER are insensitive to R over the range 1-5 cm. Microdosimetric kinetic model based RBE values are about 2.3 and 2.8 for HSG tumour cells and V79 cells, respectively, whereas biological weighting function-based RBE is about 2.8. ICRP 60 and ICRU 40 recommendation-basedQ̅values are about 14.5 and 16, respectively. Theory of dual radiation action based RBE is 11.4. The calculated value of OER is 1.6.Significance.This study demonstrates the relative insensitivity of RBE,Q̅and OER radially away from the252Cf source along the distances of 1-5 cm in water.