Fifty years of Monte Carlo simulations for medical physics

An automated commissioning method based on virtual source models: Customizing Monte Carlo dose verification models for individual accelerators

BACKGROUND

In pursuit of precise dose calculation and verification, the importance of beam modelling cannot be overstated, as it ensures an accurate distribution of particles incident upon the human body. The virtual source model, as one of the beam modelling methods, offers the advantage of not requiring detailed accelerator information. Although various virtual source models exist, manual adjustment to these models demands a substantial investment of time and computational resources. There has long been a desire to develop an efficient and automated approach for model commissioning.

PURPOSE

To develop an automatic commissioning method for the virtual source model to customize the accelerator model for independent Monte Carlo dose verification.

METHODS

Initially, the accelerator model is established using the virtual source model and self-developed Jaw and MLC models. Then, a fully automated iteration process is employed to adjust the parameters of the virtual source model. Three types of objective functions are designed to represent differences from water tank measurements. Each objective function is paired with a specific parameter for adjustment, and their effectiveness is demonstrated through physical evidence. In each iteration, parameters with the highest objective function percentage are chosen for adjustment, and step length is determined based on current objective function values. Iteration is terminated when changes in any direction from the optimal solution no longer produce an improvement. Dose verification model for nine accelerators has been accomplished using this method. Additionally, under the same initial conditions, verification models for Versa HD accelerator (FF and FFF modes) are established using this method, Nelder-Mead Simplex optimization method, and the Bayesian optimization method to compare the efficiency and quality of these three iterative approaches.

RESULTS

Iterations for all nine accelerators are completed within 30 iterations. The relative dose differences in dose fall-off region compared to water tank measurements are all less than 2%, and the average gamma passing rates (3%/2 mm) for ArcCHECK measurements in QA plans are all higher than 97%. For Versa HD accelerator in FFF and FF modes, the proposed method achieves an average relative dose difference below 1% within 11 and 13 iterations, respectively. In contrast, the Simplex optimization reached 1% within 78 iterations in FFF mode. Furthermore, the Simplex optimization in FF mode and Bayesian optimization in both modes failed to achieve a 1% difference within 100 iterations.

CONCLUSIONS

The proposed iterative method achieves fast and automated commissioning of dose verification models, contributing to accurate and reliable clinical dose verification.

Technical note: A GPU-based shared Monte Carlo method for fast photon transport in multi-energy x-ray exposures

BACKGROUND

The Monte Carlo (MC) method is an accurate technique for particle transport calculation due to the precise modeling of physical interactions. Nevertheless, the MC method still suffers from the problem of expensive computational cost, even with graphics processing unit (GPU) acceleration. Our previous works have investigated the acceleration strategies of photon transport simulation for single-energy CT. But for multi-energy CT, conventional individual simulation leads to unnecessary redundant calculation, consuming more time.

PURPOSE

This work proposes a novel GPU-based shared MC scheme (gSMC) to reduce unnecessary repeated simulations of similar photons between different spectra, thereby enhancing the efficiency of scatter estimation in multi-energy x-ray exposures.

METHODS

The shared MC method selects shared photons between different spectra using two strategies. Specifically, we introduce spectral region classification strategy to select photons with the same initial energy from different spectra, thus generating energy-shared photon groups. Subsequently, the multi-directional sampling strategy is utilized to select energy-and-direction-shared photons, which have the same initial direction, from energy-shared photon groups. Energy-and-direction-shared photons perform shared simulations, while others are simulated individually. Finally, all results are integrated to obtain scatter distribution estimations for different spectral cases.

RESULTS

The efficiency and accuracy of the proposed gSMC are evaluated on the digital phantom and clinical case. The experimental results demonstrate that gSMC can speed up the simulation in the digital case by ∼37.8% and the one in the clinical case by ∼20.6%, while keeping the differences in total scatter results within 0.09%, compared to the conventional MC package, which performs an individual simulation.

CONCLUSIONS

The proposed GPU-based shared MC simulation method can achieve fast photon transport calculation for multi-energy x-ray exposures.

Radiation Detectors and Sensors in Medical Imaging

Medical imaging instrumentation design and construction is based on radiation sources and radiation detectors/sensors. This review focuses on the detectors and sensors of medical imaging systems. These systems are subdivided into various categories depending on their structure, the type of radiation they capture, how the radiation is measured, how the images are formed, and the medical goals they serve. Related to medical goals, detectors fall into two major areas: (i) anatomical imaging, which mainly concerns the techniques of diagnostic radiology, and (ii) functional-molecular imaging, which mainly concerns nuclear medicine. An important parameter in the evaluation of the detectors is the combination of the quality of the diagnostic result they offer and the burden of the patient with radiation dose. The latter has to be minimized; thus, the input signal (radiation photon flux) must be kept at low levels. For this reason, the detective quantum efficiency (DQE), expressing signal-to-noise ratio transfer through an imaging system, is of primary importance. In diagnostic radiology, image quality is better than in nuclear medicine; however, in most cases, the dose is higher. On the other hand, nuclear medicine focuses on the detection of functional findings and not on the accurate spatial determination of anatomical data. Detectors are integrated into projection or tomographic imaging systems and are based on the use of scintillators with optical sensors, photoconductors, or semiconductors. Analysis and modeling of such systems can be performed employing theoretical models developed in the framework of cascaded linear systems analysis (LCSA), as well as within the signal detection theory (SDT) and information theory.

Monte Carlo Model Validation of 6MV Beam of OMID, the First Iranian Linear Accelerator

Monte Carlo (MC) techniques are regarded as an accurate method to simulate the dose calculation in radiotherapy for many years. The present paper aims to validate the simulated model of the 6-MV beam of OMID linear accelerator (BEHYAAR Company) by EGSnrc codes system and also investigate the effects of initial electron beam parameters (energy, radial full width at half maximum, and mean angular spread) on dose distributions. For this purpose, the comparison between the calculated and measured percentage depth dose (PDD) and lateral dose profiles was done by gamma index (GI) with 1%-1 mm acceptance criteria. MC model validating was done for 3 cm × 3 cm, 5 cm × 5 cm, 8 cm × 8 cm, 10 cm × 10 cm, and 20 cm × 20 cm field sizes. To study the sensitivity of model to beam parameters, the field size was selected as 10 cm × 10 cm and 30 cm × 30 cm. All lateral dose profiles were obtained at 10 cm. Excellent agreement was achieved with a 99.2% GI passing percentage for PDD curves and at least 93.8% GI for lateral dose profiles for investigated field sizes. Our investigation confirmed that the lateral dose profile severely depends on the considered source parameters in this study. PDD only considerably depends on the initial electron beam energy. Therefore, source parameters should not be specified independently. These results indicate that the current model of OMID 6-MV Linac is well established, and the accuracy of the simulation is high enough to be used in various applications.

Computational Polarization Imaging In Vivo through Surgical Smoke Using Refined Polarization Difference

In surgery, the surgical smoke generated during tissue dissection and hemostasis can degrade the image quality, affecting tissue visibility and interfering with the further image processing. Developing reliable and interpretable computational imaging methods for restoring smoke-affected surgical images is crucial, as typical image restoration methods relying on color-texture information are insufficient. Here a computational polarization imaging method through surgical smoke is demonstrated, including a refined polarization difference estimation based on the discrete electric field direction, and a corresponding prior-based estimation method, for better parameter estimation and image restoration performance. Results and analyses for ex vivo, the first in vivo animal experiments, and human oral cavity tests show that the proposed method achieves visibility restoration and color recovery of higher quality, and exhibits good generalization across diverse imaging scenarios with interpretability. The method is expected to enhance the precision, safety, and efficiency of advanced image-guided and robotic surgery.

Effect of model-based dose-calculation algorithms in high dose rate brachytherapy of cervical carcinoma

Background

Task Group 43 (TG-43) formalism does not consider the tissue and applicator heterogeneities. This study is to compare the effect of model-based dose calculation algorithms, like Advanced Collapsed Cone Engine (ACE), on dose calculation with the TG-43 dose calculation formalism in patients with cervical carcinoma.

Materials and methods

20 patients of cervical carcinoma treated with a high dose rate of intracavitary brachytherapy were prospectively studied. The target volume and organs at risk (OARs) were contoured in the Oncentra treatment planning system (Elekta, Veenendaal, The Netherlands). All patients were planned with cobalt-60 (Co-60) and iridium-192 (Ir-192) sources with doses of 21 Gy in 3 fractions. These plans were calculated with TG-43 formalism and a model-based dose calculation algorithm ACE. The dosimetric parameters of TG-43 and ACE-based plans were compared in terms of target coverage and OAR doses.

Results

For Co-60-based plans, the percentage differences in the D90 and V100 values for high-risk clinical target volume (HR-CTV) were 0.36 ± 0.43% and 0.17 ± 0.31%, respectively. For the bladder, rectum and sigmoid, the percentage differences for D2cc volumes were -0.50 ± 0.51%, -0.16 ± 0.53% and -0.37 ± 1.21%, respectively. For Ir-192-based plans, the percentage difference in the D90 for HR-CTV was 0.54 ± 0.79%, while V100 was 0.24 ± 0.29%. For the bladder, rectum and sigmoid, the doses to 2cc volume were 0.35 ± 1.06%, 0.99 ± 0.74% and 0.74 ± 1.92%, respectively. No significant differences were found in the dosimetric parameters calculated with ACE and TG-43.

Conclusion

The ACE algorithm reduced doses to OARs and targets. However, ACE and TG-43 did not show significant differences in the dosimetric parameters of the target and OARs with both sources.

Dose, dose, dose, but where is the patient dose?

The article reviews the historical developments in radiation dose metrices in medical imaging. It identifies the good, the bad, and the ugly aspects of current-day metrices. The actions on shifting focus from International Commission on Radiological Protection (ICRP) Reference-Man-based population-average phantoms to patient-specific computational phantoms have been proposed and discussed. Technological developments in recent years involving AI-based automatic organ segmentation and 'near real-time' Monte Carlo dose calculations suggest the feasibility and advantage of obtaining patient-specific organ doses. It appears that the time for ICRP and other international organizations to embrace 'patient-specific' dose quantity representing risk may have finally come. While the existing dose metrices meet specific demands, emphasis needs to be also placed on making radiation units understandable to the medical community.

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.

Simulating photodynamic therapy for the treatment of glioblastoma using Monte Carlo radiative transport

Significance

Glioblastoma (GBM) is a rare but deadly form of brain tumor with a low median survival rate of 14.6 months, due to its resistance to treatment. An independent simulation of the INtraoperative photoDYnamic therapy for GliOblastoma (INDYGO) trial, a clinical trial aiming to treat the GBM resection cavity with photodynamic therapy (PDT) via a laser coupled balloon device, is demonstrated.

Aim

To develop a framework providing increased understanding for the PDT treatment, its parameters, and their impact on the clinical outcome.

Approach

We use Monte Carlo radiative transport techniques within a computational brain model containing a GBM to simulate light path and PDT effects. Treatment parameters (laser power, photosensitizer concentration, and irradiation time) are considered, as well as PDT's impact on brain tissue temperature.

Results

The simulation suggests that 39% of post-resection GBM cells are killed at the end of treatment when using the standard INDYGO trial protocol (light fluence = 200    J / cm 2 at balloon wall) and assuming an initial photosensitizer concentration of 5    μ M . Increases in treatment time and light power (light fluence = 400    J / cm 2 at balloon wall) result in further cell kill but increase brain cell temperature, which potentially affects treatment safety. Increasing the p hotosensitizer concentration produces the most significant increase in cell kill, with 61% of GBM cells killed when doubling concentration to 10    μ M and keeping the treatment time and power the same. According to these simulations, the standard trial protocol is reasonably well optimized with improvements in cell kill difficult to achieve without potentially dangerous increases in temperature. To improve treatment outcome, focus should be placed on improving the photosensitizer.

Conclusions

With further development and optimization, the simulation could have potential clinical benefit and be used to help plan and optimize intraoperative PDT treatment for GBM.

Validation of a discovery MI 4-ring model according to the NEMA NU 2-2018 standards: from Monte Carlo simulations to clinical-like reconstructions

BACKGROUND

We propose a comprehensive evaluation of a Discovery MI 4-ring (DMI) model, using a Monte Carlo simulator (GATE) and a clinical reconstruction software package (PET toolbox). The following performance characteristics were compared with actual measurements according to NEMA NU 2-2018 guidelines: system sensitivity, count losses and scatter fraction (SF), coincidence time resolution (CTR), spatial resolution (SR), and image quality (IQ). For SR and IQ tests, reconstruction of time-of-flight (TOF) simulated data was performed using the manufacturer's reconstruction software.

RESULTS

Simulated prompt, random, true, scatter and noise equivalent count rates closely matched the experimental rates with maximum relative differences of 1.6%, 5.3%, 7.8%, 6.6%, and 16.5%, respectively, in a clinical range of less than 10 kBq/mL. A 3.6% maximum relative difference was found between experimental and simulated sensitivities. The simulated spatial resolution was better than the experimental one. Simulated image quality metrics were relatively close to the experimental results.

CONCLUSIONS

The current model is able to reproduce the behaviour of the DMI count rates in the clinical range and generate clinical-like images with a reasonable match in terms of contrast and noise.

UMC-PET: a fast and flexible Monte Carlo PET simulator

Objective.The GPU-based Ultra-fast Monte Carlo positron emission tomography simulator (UMC-PET) incorporates the physics of the emission, transport and detection of radiation in PET scanners. It includes positron range, non-colinearity, scatter and attenuation, as well as detector response. The objective of this work is to present and validate UMC-PET as a a multi-purpose, accurate, fast and flexible PET simulator.Approach.We compared UMC-PET against PeneloPET, a well-validated MC PET simulator, both in preclinical and clinical scenarios. Different phantoms for scatter fraction (SF) assessment following NEMA protocols were simulated in a 6R-SuperArgus and a Biograph mMR scanner, comparing energy histograms, NEMA SF, and sensitivity for different energy windows. A comparison with real data reported in the literature on the Biograph scanner is also shown.Main results.NEMA SF and sensitivity estimated by UMC-PET where within few percent of PeneloPET predictions. The discrepancies can be attributed to small differences in the physics modeling. Running in a 11 GB GeForce RTX 2080 Ti GPU, UMC-PET is ∼1500 to ∼2000 times faster than PeneloPET executing in a single core Intel(R) Xeon(R) CPU W-2155 @ 3.30 GHz.Significance.UMC-PET employs a voxelized scheme for the scanner, patient adjacent objects (such as shieldings or the patient bed), and the activity distribution. This makes UMC-PET extremely flexible. Its high simulation speed allows applications such as MC scatter correction, faster SRM estimation for complex scanners, or even MC iterative image reconstruction.

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.

A simple method to import CAD mesh format models in FLUKA

BACKGROUND

Monte Carlo (MC) code FLUKA possesses widespread usage and accuracy in the simulation of particle beam radiotherapy. However, the conversion from computer-aided design (CAD) mesh format models to FLUKA readable geometries could not be implemented directly and conveniently. A simple method was required to be developed.

PURPOSE

The present study proposed a simple method to voxelize CAD mesh format files by using a Python-based script and establishing geometric models in FLUKA.

METHODS

Five geometric models including cube, sphere, cone, ridge filter (RGF), and 1D-Ripple Filter (1D-RiFi) were created and exported as CAD mesh format files (.stl). An open-source Python-based script was used to convert them into voxels by endowing X, Y, and Z (following the Cartesian coordinates system) of solid materials in the three-dimensional (3D) grid. A FLUKA (4-2.2, CERN) predefined routine was used to establish the voxelized geometry model (VGM), while Flair (3.2-1, CERN) was used to build the direct geometry model (DGM) in FLUKA for comparison purposes. Uniform carbon ion radiation fields 8×8 cm3 and 4×4 cm3 were generated to transport through the five pairs of models, 2D and 3D dose distributions were compared. The integral depth dose (IDD) in water of three different energy levels of carbon ion beams transported through 1D-RiFis were also simulated and compared. Moreover, the volume between CAD mesh and VGMs, as well as the computing speed between FLUKA DGMs and VGMs were simultaneously recorded.

RESULTS

The volume differences between VGMs and CAD mesh models were not more than 0.6%. The maximum mean point-to-point deviation of IDD distribution was 0.7% ± 0.51% (mean ± standard deviation). The 3D dose Gamma-index passing rates were never lower than 97% with criteria of 1%-1 mm. The difference in computing CPU time was 2.89% ± 0.22 on average.

CONCLUSIONS

The present study proposed and verified a Python-based method for converting CAD mesh format files into VGMs and establishing them in FLUKA simply as well as accurately.

Investigation of Monte Carlo simulations of the electron transport in external magnetic fields using Fano cavity test

PURPOSE

Monte Carlo simulations are crucial for calculating magnetic field correction factors kB for the dosimetry in external magnetic fields. As in Monte Carlo codes the charged particle transport is performed in straight condensed history (CH) steps, the curved trajectories of these particles in the presence of external magnetic fields can only be approximated. In this study, the charged particle transport in presence of a strong magnetic field B→ was investigated using the Fano cavity test. The test was performed in an ionization chamber and a diode detector, showing how the step size restrictions must be adjusted to perform a consistent charged particle transport within all geometrical regions.

METHODS

Monte Carlo simulations of the charged particle transport in a magnetic field of 1.5 T were performed using the EGSnrc code system including an additional EMF-macro for the transport of charged particle in electro-magnetic fields. Detailed models of an ionization chamber and a diode detector were placed in a water phantom and irradiated with a so called Fano source, which is a monoenergetic, isotropic electron source, where the number of emitted particles is proportional to the local density.

RESULTS

The results of the Fano cavity test strongly depend on the energy of charged particles and the density within the given geometry. By adjusting the maximal length of the charged particle steps, it was possible to calculate the deposited dose in the investigated regions with high accuracy (<0.1%). The Fano cavity test was performed in all regions of the detailed detector models. Using the default value for the step size in the external magnetic field, the maximal deviation between Monte Carlo based and analytical dose value in the sensitive volume of the ion chamber and diode detector was 8% and 0.1%, respectively.

CONCLUSIONS

The Fano cavity test is a crucial validation method for the modeled detectors and the transport algorithms when performing Monte Carlo simulations in a strong external magnetic field. Special care should be given, when calculating dose in volumes of low density. This study has shown that the Fano cavity test is a useful method to adapt particle transport parameters for a given simulation geometry.

Measuring dose in lung identifies peripheral tumour dose inaccuracy in SBRT audit

PURPOSE

Stereotactic Body Radiotherapy (SBRT) for lung tumours has become a mainstay of clinical practice worldwide. Measurements in anthropomorphic phantoms enable verification of patient dose in clinically realistic scenarios. Correction factors for reporting dose to the tissue equivalent materials in a lung phantom are presented in the context of a national dosimetry audit for SBRT. Analysis of dosimetry audit results is performed showing inaccuracies of common dose calculation algorithms in soft tissue lung target, inhale lung material and at tissue interfaces.

METHODS

Monte Carlo based simulation of correction factors for detectors in non-water tissue was performed for the soft tissue lung target and inhale lung materials of a modified CIRS SBRT thorax phantom. The corrections were determined for Gafchromic EBT3 Film and PTW 60019 microDiamond detectors used for measurements of 168 SBRT lung plans in an end-to-end dosimetry audit. Corrections were derived for dose to medium (Dm,m) and dose to water (Dw,w) scenarios.

RESULTS

Correction factors were up to -3.4% and 9.2% for in field and out of field lung respectively. Overall, application of the correction factors improved the measurement-to-plan dose discrepancy. For the soft tissue lung target, agreement between planned and measured dose was within average of 3% for both film and microDiamond measurements.

CONCLUSIONS

The correction factors developed for this work are provided for clinical users to apply to commissioning measurements using a commercially available thorax phantom where inhomogeneity is present. The end-to-end dosimetry audit demonstrates dose calculation algorithms can underestimate dose at lung tumour/lung tissue interfaces by an average of 2-5%.

Influence on voxel-based dosimetry: noise effect on absorbed dose dosimetry at single time-point versus sequential single-photon emission computed tomography

OBJECTIVE

The purpose of this study was to evaluate how statistical fluctuation in single-photon emission computed tomography (SPECT) images propagate to absorbed dose maps.

METHODS

SPECT/computed tomography (CT) images of iodine-131 filled phantoms, using different acquisition and processing protocols, were evaluated using STRATOS software to assess the absorbed dose distribution at the voxel level. Absorbed dose values and coefficient of variation (COV) were analyzed for dosimetry based on single time-point SPECT images and time-integrated activities of SPECT sequences with low and high counts.

RESULTS

Considering dosimetry based on a single time-point, the mean absorbed dose was not significantly affected by total counts or reconstruction parameters, but the uniformity of the absorbed dose maps had an almost linear correlation with SPECT noise. When high- and low-count SPECT sequences were used to generate an absorbed dose map, the absorbed dose COV for each of the temporal sequences was slightly lower than the absorbed dose COV based on the single SPECT image with the highest count included in the sequence.

CONCLUSION

The impact of changes in SPECT counts and reconstruction parameters is almost linear when dosimetry is based on isolated SPECT images, but less pronounced when dosimetry is based on sequential SPECTs.

Depth Dose Enhancement in Orthovoltage Nanoparticle-Enhanced Radiotherapy: A Monte Carlo Phantom Study

BACKGROUND

This study was to examine the depth dose enhancement in orthovoltage nanoparticle-enhanced radiotherapy for skin treatment by investigating the impact of various photon beam energies, nanoparticle materials, and nanoparticle concentrations.

METHODS

A water phantom was utilized, and different nanoparticle materials (gold, platinum, iodine, silver, iron oxide) were added to determine the depth doses through Monte Carlo simulation. The clinical 105 kVp and 220 kVp photon beams were used to compute the depth doses of the phantom at different nanoparticle concentrations (ranging from 3 mg/mL to 40 mg/mL). The dose enhancement ratio (DER), which represents the ratio of the dose with nanoparticles to the dose without nanoparticles at the same depth in the phantom, was calculated to determine the dose enhancement.

RESULTS

The study found that gold nanoparticles outperformed the other nanoparticle materials, with a maximum DER value of 3.77 at a concentration of 40 mg/mL. Iron oxide nanoparticles exhibited the lowest DER value, equal to 1, when compared to other nanoparticles. Additionally, the DER value increased with higher nanoparticle concentrations and lower photon beam energy.

CONCLUSIONS

It is concluded in this study that gold nanoparticles are the most effective in enhancing the depth dose in orthovoltage nanoparticle-enhanced skin therapy. Furthermore, the results suggest that increasing nanoparticle concentration and decreasing photon beam energy lead to increased dose enhancement.

Mesh modeling of system geometry and anatomy phantoms for realistic GATE simulations and their inclusion in SPECT reconstruction

Objective.Monte-Carlo simulation studies have been essential for advancing various developments in single photon emission computed tomography (SPECT) imaging, such as system design and accurate image reconstruction. Among the simulation software available, Geant4 application for tomographic emission (GATE) is one of the most used simulation toolkits in nuclear medicine, which allows building systems and attenuation phantom geometries based on the combination of idealized volumes. However, these idealized volumes are inadequate for modeling free-form shape components of such geometries. Recent GATE versions alleviate these major limitations by allowing users to import triangulated surface meshes.Approach.In this study, we describe our mesh-based simulations of a next-generation multi-pinhole SPECT system dedicated to clinical brain imaging, called AdaptiSPECT-C. To simulate realistic imaging data, we incorporated in our simulation the XCAT phantom, which provides an advanced anatomical description of the human body. An additional challenge with the AdaptiSPECT-C geometry is that the default voxelized XCAT attenuation phantom was not usable in our simulation due to intersection of objects of dissimilar materials caused by overlap of the air containing regions of the XCAT beyond the surface of the phantom and the components of the imaging system.Main results.We validated our mesh-based modeling against the one constructed by idealized volumes for a simplified single vertex configuration of AdaptiSPECT-C through simulated projection data of123I-activity distributions. We resolved the overlap conflict by creating and incorporating a mesh-based attenuation phantom following a volume hierarchy. We then evaluated our reconstructions with attenuation and scatter correction for projections obtained from simulation consisting of mesh-based modeling of the system and the attenuation phantom for brain imaging. Our approach demonstrated similar performance as the reference scheme simulated in air for uniform and clinical-like123I-IMP brain perfusion source distributions.Significance.This work enables the simulation of complex SPECT acquisitions and reconstructions for emulating realistic imaging data close to those of actual patients.

Validation of the TOPAS Monte Carlo toolkit for LDR brachytherapy simulations

PURPOSE

This work has the purpose of validating the Monte Carlo toolkit TOol for PArticle Simulation (TOPAS) for low-dose-rate (LDR) brachytherapy uses.

METHODS AND MATERIALS

Simulations of 12 LDR sources and 2 COMS eye plaques (10 mm and 20 mm in diameter) and comparisons with published reference data from the Carleton Laboratory for Radiotherapy Physics (CLRP), the TG-43 consensus data and the TG-129 consensus data were performed. Sources from the IROC Houston Source Registry were modeled. The OncoSeed 6711 and the SelectSeed 130.002 were also modeled for historical reasons. For each source, the dose rate constant, the radial dose function and the anisotropy functions at 0.5, 1 and 5 cm were extracted. For the eye plaques (loaded with ¹²⁵I sources), dose distribution maps, dose profiles along the central axis and transverse axis were calculated.

RESULTS

Dose rate constants for 11 of the 12 sources are within 4% of the consensus data and within 2% of the CLRP data. The radial dose functions and anisotropy functions are mostly within 2% of the CLRP data. In average, 92% of all voxels are within 1% of the CLRP data for the eye plaques dose distributions. The dose profiles are within 0.5% (central axis) and 1% (transverse axis) of the reference data.

CONCLUSION

The TOPAS MC toolkit was validated for LDR brachytherapy applications. Single-seed and multi-seed results agree with the published reference data. TOPAS has several benefits such as a simplified approach to MC simulations and an accessible brachytherapy package including comprehensive learning resources.

Monte Carlo modeling of Halcyon and Ethos radiotherapy beam using CAD geometry: validation and IAEA-compliant phase space

Objective.A Monte Carlo (MC) model of a Halcyon and Ethos (Varian Medical Systems, a Siemens Healthineers Company) radiotherapy beam was validated and field-independent phase space (PHSP) files were recorded above the dual-layer multileaf collimators (MLC).Approach.The treatment head geometry was modeled according to engineering drawings and the dual-layer MLC was imported from CAD (computer-aided design) files. The information for the incident electron beam was achieved from an iterative electromagnetic solver. The validation of the model was performed by comparing the dose delivered by the square MLC fields as well as complex field measurements.Main results.An electron phase space was generated from linac simulations and achieved improved MC results. The output factors for square fields were within 1% and the largest differences of 5% were found in the build-up region of PDDs and the penumbra region of profiles. With the more complicated MLC-shaped field (Fishbone), the largest differences of up to 8% were found in the MLC leaf tip region due to the uncertainty of the MLC positioning and the mechanical leaf gap value. The impact of the collimator rotation on the PHSP solution has been assessed with both small and large fields, confirming negligible effects on in-field and out-of-field dose distributions.Significance.A computational model of the Halcyon and Ethos radiotherapy beam with a high accuracy implementation of the MLC was shown to be able to reproduce the radiation beam characteristics with square fields and more complex MLC-shaped fields. The field-independent PHSP files that were produced can be used as an accurate treatment head model above the MLC, and reduce the time to simulate particle transport through treatment head components.

Dual- and multi-energy CT for particle stopping-power estimation: current state, challenges and potential

Range uncertainty has been a key factor preventing particle radiotherapy from reaching its full physical potential. One of the main contributing sources is the uncertainty in estimating particle stopping power (ρ_s) within patients. Currently, theρ_sdistribution in a patient is derived from a single-energy CT (SECT) scan acquired for treatment planning by converting CT number expressed in Hounsfield units (HU) of each voxel toρ_susing a Hounsfield look-up table (HLUT), also known as the CT calibration curve. HU andρ_sshare a linear relationship with electron density but differ in their additional dependence on elemental composition through different physical properties, i.e. effective atomic number and mean excitation energy, respectively. Because of that, the HLUT approach is particularly sensitive to differences in elemental composition between real human tissues and tissue surrogates as well as tissue variations within and among individual patients. The use of dual-energy CT (DECT) forρ_sprediction has been shown to be effective in reducing the uncertainty inρ_sestimation compared to SECT. The acquisition of CT data over different x-ray spectra yields additional information on the material elemental composition. Recently, multi-energy CT (MECT) has been explored to deduct material-specific information with higher dimensionality, which has the potential to further improve the accuracy ofρ_sestimation. Even though various DECT and MECT methods have been proposed and evaluated over the years, these approaches are still only scarcely implemented in routine clinical practice. In this topical review, we aim at accelerating this translation process by providing: (1) a comprehensive review of the existing DECT/MECT methods forρ_sestimation with their respective strengths and weaknesses; (2) a general review of uncertainties associated with DECT/MECT methods; (3) a general review of different aspects related to clinical implementation of DECT/MECT methods; (4) other potential advanced DECT/MECT applications beyondρ_sestimation.

On the field size definition and field output factors in small field dosimetry

BACKGROUND

There is a major conceptual difference between small-field and large field dosimetry that is, different definition of the field size. The dosimetry protocol IAEA TRS-483 recommends the use of the field size defined by measured dose profiles (full-width half maximum, FWHM) that is significantly different from conventional field size definition by the geometric field opening of MLC/Jaw at the isocenter. The application of the effective field size concept, S_clin , was introduced by Cranmer-Sargison et al. (DOI:10.1016/j.radonc.2013.10.002) as a reporting mechanism for field output factors of rectangular fields. The study by Das et al. (DOI:10.1002/mp.15624) indicated the limitations of obtaining the field size by experimentally measuring FWHM, for example, the measured FWHM is smaller than beam geometric size, which is contradictory to what is expected as a result of partial occlusion of the primary photon source by the collimating devices. Cranmer-Sargison et al. and Das et al suggested that additional investigations are needed to evaluate its limitations.

PURPOSE

This study investigates the validity of the field size definition by FWHM and by MLC/Jaw opening and finds the pros and cons between these two methods to resolve the controversial issue.

METHODS

The FWHM can be obtained by measuring or calculating dose profiles. Using Monte Carlo simulations this study compares the field size obtained by FWHM and by field geometric field opening. The EGSnrc system is used to simulate 6 MV beam to generate square and rectangular fields from 5-30 mm with every possible permutation (keeping one jaw fixed and varying other jaw from 5 to 30 mm). The calculated FWHM and output factors are compared with measurements obtained by a microSilicon detector.

RESULTS

The results show that field width (FWHM) derived from MC calculations generally agrees with machine geometric field width within 0.5 mm for square or rectangular fields with a minimum field width of ≥8 mm. For the extremely small fields with a minimum field width of 5 mm the discrepancies are up to 1.6 mm. The field width (FWHM) obtained by measuring dose profiles are unreliable for small fields due to the measurement uncertainties for an extremely small field. The effect of partial occlusion of the primary photon source by the jaws on the beam axis is clearly observed in the calculated dose profiles. For the extremely small field width of 5 mm, Monte Carlo predicted up to 10% exchange factor differences which are confirmed by the measurements.

CONCLUSION

The field size defined by the geometric opening of the beam-defining system, is still valid for small fields. The field size defined by geometric opening is independent of measurement uncertainties, independent of machine design, and highly reproducible. It is feasible to accurately tabulate the output factors as a function of geometric field opening thus eliminating user and detector choice for FWHM measurements. The field output factor of a small rectangular field cannot be related to an equivalent field size without considering the exchange factor due to partial occlusion of the photon source.

TopasOpt: An open-source library for optimization with Topas Monte Carlo

PURPOSE

To describe and test TopasOpt: a free, open-source and extensible library for performing mathematical optimization of Monte Carlo simulations in Topas.

METHODS

TopasOpt enables any Topas model to be transformed into an optimization problem, and any parameter within the model to be treated as an optimization variable. Three case studies are presented. The starting model consists of a 10 MeV electron beam striking a tungsten target. The resulting bremsstrahlung X-ray spectrum is collimated by a primary and secondary collimator before being scored in a water tank. In the first case study (electron phase space optimization), five parameters describing the electron beam were treated as optimization variables and assigned a random starting value. An objective function was defined based on differences of depth-dose and profiles in water between the original (ground truth) model and a given model generated by TopasOpt. The problem was solved using Bayesian Optimization and the Nelder-Mead method. One hundred iterations were run in each case. In the second case study, (collimator geometry optimization), this process was repeated, but three geometric parameters defining the secondary collimator were treated as optimization variables and assigned random starting values, and forty iterations were run. In the third case study, the optimization was repeated with different number of primary particles to study the effect of noise on convergence.

RESULTS

For case 1 (phase space optimization), both optimization algorithms successfully minimized the objective function, with absolute mean differences in profile dose of 0.4% (Bayesian) and 0.3% (Nelder-Mead) and 0.2% in depth-dose for both algorithms. The beam energy was recovered to within 1%, however some parameters had relative errors of up to 171% - a result consistent with the known X-ray dose is insensitivity to many electron beam parameters. For case 2 (geometry optimization), absolute mean differences in profile dose were 0.6% (Bayesian) and 0.9% (Nelder-Mead), and 0.5% and 0.9% in depth-dose. The maximum percentage error in any parameter was 9% with Bayesian Optimization and 28% with Nelder-Mead. Finally, the Bayesian Optimization algorithm was demonstrated to be robust to moderate levels of noise; when the standard deviation of the objective function was 16% of the mean, the maximum error in any parameter value was 16%, and the absolute mean difference in dose was 0.9% (profile) and 0.8% (depth-dose).

CONCLUSIONS

An open-source library for optimization with Topas Monte Carlo has been developed, tested, and released. This tool will improve accuracy and efficiency in any situation in which the optimal value of a parameter in a Monte Carlo simulation is unknown. Applications for this tool include (1) The design of new components (2) Reverse engineering of models based on limited experimental or published data, and (3) Tuning of Monte Carlo "hyper parameters" such as variance reduction, physics settings, or scoring parameters.

Monte-Carlo techniques for radiotherapy applications II: equipment and source modelling, dose calculations and radiobiology

Introduction:

This is the second of two papers giving an overview of the use of Monte-Carlo techniques for radiotherapy applications.

Methods:

The first paper gave an introduction and introduced some of the codes that are available to the user wishing to model the different aspects of radiotherapy treatment. It also aims to serve as a useful companion to a curated collection of papers on Monte-Carlo that have been published in this journal.

Results and Conclusions:

This paper focuses on the application of Monte-Carlo to specific problems in radiotherapy. These include radiotherapy and imaging beam production, brachytherapy, phantom and patient dosimetry, detector modelling and track structure calculations for micro-dosimetry, nano-dosimetry and radiobiology.

Grain Size Distribution Analysis of Different Activator Doped Gd2O2S Powder Phosphors for Use in Medical Image Sensors

The structural properties of phosphor materials, such as their grain size distribution (GSD), affect their overall optical emission performance. In the widely used gadolinium oxysulfide (Gd₂O₂S) host material, the type of activator is one significant parameter that also changes the GSD of the powder phosphor. For this reason, in this study, different phosphors samples of Gd₂O₂S:Tb, Gd₂O₂S:Eu, and Gd₂O₂S:Pr,Ce,F, were analyzed, their GSDs were experimentally determined using the scanning electron microscopy (SEM) technique, and thereafter, their optical emission profiles were investigated using the LIGHTAWE Monte Carlo simulation package. Two sets of GSDs were examined corresponding to approximately equal mean particle size, such as: (i) 1.232 μm, 1.769 μm and 1.784 μm, and (ii) 2.377 μm, 3.644 μm and 3.677 μm, for Tb, Eu and Pr,Ce,F, respectively. The results showed that light absorption was almost similar, for instance, 25.45% and 8.17% for both cases of Eu dopant utilizing a thin layer (100 μm), however, given a thicker layer (200 μm), the difference was more obvious, 22.82%. On the other hand, a high amount of light loss within the phosphor affects the laterally directed light quanta, which lead to sharper distributions and therefore to higher resolution properties of the samples.

Dosimetric Impact on the Flattening Filter and Addition of Gold Nanoparticles in Radiotherapy: A Monte Carlo Study on Depth Dose Using the 6 and 10 MV FFF Photon Beams

PURPOSE

This phantom study investigated through Monte Carlo simulation how the dose enhancement varied with depth, when gold nanoparticles (NPs) were added using the flattening filter-free (FFF) photon beams in gold NP-enhanced radiotherapy.

METHOD

A phantom with materials varying from pure water to a mixture of water and gold NPs at different concentrations (3-40 mg/mL) were irradiated by the 6 and 10 MV flattening filter (FF) and FFF photon beams. Monte Carlo simulations were carried out to determine the depth doses along the central beam axis of the phantom up to a depth of 40 cm. The dose enhancement ratio (DER) and FFF enhancement ratio (FFFER) were calculated based on the Monte Carlo results.

RESULTS

The DER values were found decreased with an increase of depth and increase of NP concentration in the phantom. For the maximum NP concentration of 40 mg/mL, the DER values decreased 6.9, 12, 4.6 and 7.2% at a phantom depth from 2 to 40 cm, using the 6 MV FF, 6 MV FFF, 10 MV FF and 10 MV FFF photon beams, respectively. The maximum DER values for the 6 MV beams were 1.08 (FF) and 1.14 (FFF), while those for the 10 MV beams were 1.04 (FF) and 1.07 (FFF). When the FF was removed from the linear accelerator head, the FFFER showed a more significant increase of dose enhancement for the 6 MV beams (1.057) than the 10 MV (1.031).

CONCLUSION

From the DER and FFFER values based on the Monte Carlo results, it is concluded that the dose enhancement with depth was dependent on the NP and beam variables, namely, NP concentration, presence of FF in the beam and beam energy. Dose enhancement was more significant when using the lower photon beam energy (i.e., 6 MV), FFF photon beam and higher NP concentration in the study.

Evaluation of Dosimetric Effect of Bone Scatter on Nanoparticle-Enhanced Orthovoltage Radiotherapy: A Monte Carlo Phantom Study

In nanoparticle (NP)-enhanced orthovoltage radiotherapy, bone scatter affected dose enhancement at the skin lesion in areas such as the forehead, chest wall, and knee. Since each of these treatment sites have a bone, such as the frontal bone, rib, or patella, underneath the skin lesion and this bone is not considered in dose delivery calculations, uncertainty arises in the evaluation of dose enhancement with the addition of NPs in radiotherapy. To investigate the impact of neglecting the effect of bone scatter, Monte Carlo simulations based on heterogeneous phantoms were carried out to determine and compare the dose enhancement ratio (DER), when a bone was and was not present underneath the skin lesion. For skin lesions with added NPs, Monte Carlo simulations were used to calculate the DER values using different elemental NPs (gold, platinum, silver, iodine, as well as iron oxide), in varying NP concentrations (3−40 mg/mL), at two different photon beam energies (105 and 220 kVp). It was found that DER values at the skin lesion increased with the presence of bone when there was a higher atomic number of NPs, a higher NP concentration, and a lower photon beam energy. When comparing DER values with and without bone, using the same NP elements, NP concentration, and beam energy, differences were found in the range 0.04−3.55%, and a higher difference was found when the NP concentration increased. By considering the uncertainty in the DER calculation, the effect of bone scatter became significant to the dose enhancement (>2%) when the NP concentration was higher than 18 mg/mL. This resulted in an underestimation of dose enhancement at the skin lesion, when the bone underneath the tumour was neglected during orthovoltage radiotherapy.

Toolkit implementation to exchange phase-space files between IAEA and MCNP6 monte Carlo code format

PURPOSE

Some Monte Carlo simulation codes can read and write phase space files in IAEA format, which are used to characterize accelerators, brachytherapy seeds and other radiation sources. Moreover, as the format has been standardized, these files can be used with different simulation codes. However, MCNP6 has not still implemented this capability, which complicate the studies involving this kind of sources and the reproducibility of results among independent researchers. Therefore, the purpose of this work is to develop a tool to perform conversions between IAEA and MCNP6 phase space files formats, to be used for Monte Carlo simulations.

MATERIALS AND METHODS

This paper presents a toolkit written in C language that uses the IAEA libraries to convert phase space files between IAEA and MCNP6 format and vice versa. To test the functionality of the provided tool, a set of verification tests has been carried out. In addition, a linear accelerator treatment has been simulated with the PENELOPE library using the PenEasy framework, which is already capable to read and write IAEA phase space files, and MCNP6 using the developed tools.

RESULTS

Both codes show compatible depth dose curves and profiles in a water tank, demonstrating that the conversion tools work properly. Moreover, the phase space file formats have been converted from IAEA to MCNP6 format and back again to IAEA format, reproducing the very same results.

CONCLUSION

The toolkit developed in this work offers MCNP6 scientific community an external and validated program able to convert phase space files in IAEA format to MCNP6 internal format and use them for Monte Carlo applications. Furthermore, the developed tools provide also the reverse conversion, which allow sharing MCNP6 results with users of other Monte Carlo codes. This capability in the MCNP6 ecosystem provides to the scientific community the ability not only to share radiation sources, but also to facilitate the reproducibility among different groups using different codes via the standard format specified by the IAEA.

TransDose: a transformer-based UNet model for fast and accurate dose calculation for MR-LINACs

Objective. To present a transformer-based UNet model (TransDose) for fast and accurate dose calculation for magnetic resonance-linear accelerators (MR-LINACs). Approach. A 2D fluence map from each beam was first projected into a 3D fluence volume and then fed into the TransDose model together with patient density volume and output predicted beam dose. The proposed TransDose model combined a 3D residual UNet with a transformer encoder, where convolutional layers extracted the volumetric spatial features, and the transformer encoder processed the long-range dependencies in a global space. Ninety-eight cases with four tumor sites (brain, nasopharynx, lung, and rectum) treated with fixed-beam intensity-modulated radiotherapy were included in the dataset; 78 cases were used for model training and validation; and 20 cases were used for testing. The ground-truth beam doses were calculated with Monte Carlo (MC) simulations within 1% statistical uncertainty and magnetic field strength B = 1.5 T in the superior and inferior direction. Beam angles from the training and validation datasets were rotated 2–5 times, and doses were recalculated to augment the datasets. Results. The dose-volume histograms and indices between the predicted and MC doses showed good consistency. The average 3D γ-passing rates (3%/2 mm, for dose regions above 10% of maximum dose) were 99.13 ± 0.89% (brain), 98.31 ± 1.92% (nasopharynx), 98.74 ± 0.70% (lung), and 99.28 ± 0.25% (rectum). The average dose calculation time, which included the fluence projection and model prediction, was less than 310 ms for each beam. Significance. We successfully developed a transformer-based UNet dose calculation model—TransDose in magnetic fields. Its accuracy and efficiency indicated its potential for use in online adaptive plan optimization for MR-LINACs.

A probabilistic approach for determining Monte Carlo beam source parameters: II. Impact of beam modeling uncertainties on dosimetric functions and treatment plans

Objective. The Monte Carlo method is recognized as a valid approach for the evaluation of dosimetric functions for clinical use. This procedure requires the accurate modeling of the considered linear accelerator. In Part I, we propose a new method to extract the probability density function of the beam model physical parameters. The aim of this work is to evaluate the impact of beam modeling uncertainties on Monte Carlo evaluated dosimetric functions and treatment plans in the context of small fields. Approach. Simulations of output factors, output correction factors, dose profiles, percent-depth doses and treatment plans are performed using the CyberKnife M6 model developed in Part I. The optimized pair of electron beam energy and spot size, and eight additional pairs of beam parameters representing a 95% confidence region are used to propagate the uncertainties associated to the source parameters to the dosimetric functions. Main results. For output factors, the impact of beam modeling uncertainties increases with the reduction of the field size and confidence interval half widths reach 1.8% for the 5 mm collimator. The impact on output correction factors cancels in part, leading to a maximum confidence interval half width of 0.44%. The impact is less significant for percent-depth doses in comparison to dose profiles. For these types of measurement, in absolute terms and in comparison to the reference dose, confidence interval half widths less than or equal to 1.4% are observed. For simulated treatment plans, the impact is more significant for the treatment delivered with a smaller field size with confidence interval half widths reaching 2.5% and 1.4% for the 5 and 20 mm collimators, respectively. Significance. Results confirm that AAPM TG-157's tolerances cannot apply to the field sizes studied. This study provides an insight on the reachable dose calculation accuracy in a clinical setup.

Review of high energy x-ray computed tomography for non-destructive dimensional metrology of large metallic advanced manufactured components

Advanced manufacturing technologies, led by additive manufacturing, have undergone significant growth in recent years. These technologies enable engineers to design parts with reduced weight while maintaining structural and functional integrity. In particular, metal additive manufacturing parts are increasingly used in application areas such as aerospace, where a failure of a mission-critical part can have dire safety consequences. Therefore, the quality of these components is extremely important. A critical aspect of quality control is dimensional evaluation, where measurements provide quantitative results that are traceable to the standard unit of length, the metre. Dimensional measurements allow designers, manufacturers and users to check product conformity against engineering drawings and enable the same quality standard to be used across the supply chain nationally and internationally. However, there is a lack of development of measurement techniques that provide non-destructive dimensional measurements beyond common non-destructive evaluation focused on defect detection. X-ray computed tomography (XCT) technology has great potential to be used as a non-destructive dimensional evaluation technology. However, technology development is behind the demand and growth for advanced manufactured parts. Both the size and the value of advanced manufactured parts have grown significantly in recent years, leading to new requirements of dimensional measurement technologies. This paper is a cross-disciplinary review of state-of-the-art non-destructive dimensional measuring techniques relevant to advanced manufacturing of metallic parts at larger length scales, especially the use of high energy XCT with source energy of greater than 400 kV to address the need in measuring large advanced manufactured parts. Technologies considered as potential high energy x-ray generators include both conventional x-ray tubes, linear accelerators, and alternative technologies such as inverse Compton scattering sources, synchrotron sources and laser-driven plasma sources. Their technology advances and challenges are elaborated on. The paper also outlines the development of XCT for dimensional metrology and future needs.

Can Agents Model Hydrocarbon Migration for Petroleum System Analysis? A Fast Screening Tool to De-Risk Hydrocarbon Prospects

Understanding subsurface hydrocarbon migration is a crucial task for petroleum geoscientists. Hydrocarbons are released from deeply buried and heated source rocks, such as shales with a high organic content. They then migrate upwards through the overlying lithologies. Some hydrocarbon becomes trapped in suitable geological structures that, over a geological timescale, produce viable hydrocarbon reservoirs. This work investigates how intelligent agent models can mimic these complex natural subsurface processes and account for geological uncertainty. Physics-based approaches are commonly used in petroleum system modelling and flow simulation software to identify migration pathways from source rocks to traps. However, the problem with these simulations is that they are computationally demanding, making them infeasible for extensive uncertainty quantification. In this work, we present a novel dynamic screening tool for secondary hydrocarbon migration that relies on agent-based modelling. It is fast and is therefore suitable for uncertainty quantification, before using petroleum system modelling software for a more accurate evaluation of migration scenarios. We first illustrate how interacting but independent agents can mimic the movement of hydrocarbon molecules using a few simple rules by focusing on the main drivers of migration: buoyancy and capillary forces. Then, using a synthetic case study, we validate the usefulness of the agent modelling approach to quantify the impact of geological parameter uncertainty (e.g., fault transmissibility, source rock location, expulsion rate) on potential hydrocarbon accumulations and migrations pathways, an essential task to enable quick de-risking of a likely prospect.

Absorbed dose distribution in human eye simulated by FOTELP-VOX code and verified by volumetric modulated arc therapy treatment plan

This paper illustrates the potential of the FOTELP-VOX code, a modification of the general-purpose FOTELP code, combining Monte Carlo techniques to simulate particle transportation from an external source through the internal organs, resulting in a 3-D absorbed dose distribution. The study shows the comparison of results obtained by FOTELP software and the volumetric modulated arc therapy technique. This planning technique with two full arcs was applied, and the plan was created to destroy the diseased tissue in the eye tumor bed and avoid damage to surrounding healthy tissue, for one patient. The dose coverage, homogeneity index, conformity index of the target, and the dose volumes of critical structures were calculated. Good agreement of the results for absorbed dose in the human eye was obtained using these two techniques.

Technical Note: Bremsstrahlung dose in the electron beam at extended distances in total skin electron therapy

PURPOSE

Electron beam from a linear accelerator is commonly used in total skin electron Therapy (TSET) at extended distances. Since Das et al (Med Phys 21, p.1733, 1994) reported 5% bremsstrahlung dose for a 6 MeV electron beam at extended distance of 500 cm it has been accepted as common knowledge. However, measurements by Chen et al (Int J. Rad Onc Biol Phys 59 p.872, 2004) and Monte Carlo simulations by Ding et al (Phys. Med. Biol. 66, 075010, 2021) were unable to reproduce such high bremsstrahlung dose. As bremsstrahlung dose contributes to whole-body dose which could produce bone marrow toxicity with serious complications for the outcome of the TSET, it is important to re-evaluate the magnitude of bremsstrahlung dose accurately.

METHODS

The EGSnrc Monte Carlo system is used to investigate bremsstrahlung doses from 6 MeV high dose rate total skin electron (HDTSe) beams from Varian TrueBeam and Clinac Accelerators. The measurements were carried out at depth of d_max and 5 cm in solid water and Acrylic phantoms at extended distances using a parallel-plate chamber and a cylindrical ion chamber.

RESULTS

We were able to reproduce previously reported high bremsstrahlung dose at extended distances by using a parallel plate ionization chamber. However, both the measurements by using a cylindrical chamber and Monte Carlo simulations showed an insignificant bremsstrahlung dose (∼1%) even at SSD = 500 cm.

CONCLUSION

The bremsstrahlung doses of a 6 MeV electron beam are 0.5% to 1% for SSD from 100 to 700 cm, although it increases with the increasing extended distance. The common belief of up to 5% bremsstrahlung dose at large extended distances is incorrect. Previously reported high bremsstrahlung doses might be due to poor signal-to-noise ratio of using parallel plate chamber for measuring very low dose or particular set-up. This article is protected by copyright. All rights reserved.

Voxel model of a rabbit: assessment of absorbed doses in organs after CT examination performed by two different protocols

The objective of this work was to assess absorbed doses in organs and tissues of a rabbit, following computed tomography (CT) examinations, using a dedicated 3D voxel model. Absorbed doses in relevant organs were calculated using the MCNP5 Monte Carlo software. Calculations were perfomed for two standard CT protocols, using tube voltages of 110 kVp and 130 kVp. Absorbed doses were calculated in 11 organs and tissues, i.e., skin, bones, brain, muscles, heart, lungs, liver, spleen, kidney, testicles, and fat tissue. The doses ranged from 15.3 to 28.3 mGy, and from 40.2 to 74.3 mGy, in the two investigated protocols. The organs that received the highest dose were bones and kidneys. In contrast, brain and spleen were organs that received the smallest doses. Doses in organs which are stretched along the body did not change significantly with distance. On the other hand, doses in organs which are localized in the body showed maximums and minimums. Using the voxel model, it is possible to calculate the dose distribution in the rabbit's body after CT scans, and study the potential biological effects of CT doses in certain organs. The voxel model presented in this work can be used to calculated doses in all radiation experiments in which rabbits are used as experimental animals.

Monte Carlo methods for device simulations in radiation therapy

Monte Carlo (MC) simulations play an important role in radiotherapy, especially as a method to evaluate physical properties that are either impossible or difficult to measure. For example, MC simulations (MCSs) are used to aid in the design of radiotherapy devices or to understand their properties. The aim of this article is to review the MC method for device simulations in radiation therapy. After a brief history of the MC method and popular codes in medical physics, we review applications of the MC method to model treatment heads for neutral and charged particle radiation therapy as well as specific in-room devices for imaging and therapy purposes. We conclude by discussing the impact that MCSs had in this field and the role of MC in future device design.

Investigating the feasibility of TOPAS-nBio for Monte Carlo track structure simulations by adapting GEANT4-DNA examples application

Purpose.The purpose of this work is to investigate the feasibility of TOPAS-nBio for track structure simulations using tuple scoring and ROOT/Python-based post-processing.Materials and methods.There are several example applications implemented in GEANT4-DNA demonstrating track structure simulations. These examples are not implemented by default in TOPAS-nBio. In this study, the tuple scorer was used to re-simulate these examples. The simulations contained investigations of different physics lists, calculation of energy-dependent range, stopping power, mean free path andW-value. Additionally, further applications of the TOPAS-nBio tool were investigated, focusing on physical interactions and deposited energies of electrons with initial energies in the range of 10-60 eV, not covered in the recently published GEANT4-DNA simulations. Low-energetic electrons are currently of great interest in the radiobiology research community due to their high effectiveness towards the induction of biological damage.Results.The quantities calculated with TOPAS-nBio show a good agreement with the simulations of GEANT4-DNA with deviations of 5% at maximum. Thus, we have presented a feasible way to implement the example applications included in GEANT4-DNA in TOPAS-nBio. With the extended simulations, an insight could be given, which further tracking information can be gained with the track structure code and how cross sections and physics models influence a particle's fate.Conclusion.With our results, we could show the potentials of applying the tuple scorer in TOPAS-nBio Monte Carlo track structure simulations. Using this scorer, a large amount of information about the track structure can be accessed, which can be analyzed as preferred after the simulation.

Technical note: GAMMORA, a free, open-source, and validated GATE-based model for Monte-Carlo simulations of the Varian TrueBeam

PURPOSE

Monte Carlo (MC) is the reference computation method for medical physics. In radiotherapy, MC computations are necessary for some issues (such as assessing figures of merit, double checks, and dose conversions). A tool based on GATE is proposed to easily create full MC simulations of the Varian TrueBeam STx.

METHODS

GAMMORA is a package that contains photon phase spaces as a pre-trained generative adversarial network (GAN) and the TrueBeam's full geometry. It allows users to easily create MC simulations for simple or complex radiotherapy plans such as VMAT. To validate the model, the characteristics of generated photons are first compared to those provided by Varian (IAEA format). Simulated data are also compared to measurements in water and heterogeneous media. Simulations of 8 SBRT plans are compared to measurements (in a phantom). Two examples of applications (a second check and interplay effect assessment) are presented.

RESULTS

The simulated photons generated by the GAN have the same characteristics (energy, position, and direction) as the IAEA data. Computed dose distributions of simple cases (in water) and complex plans delivered in a phantom are compared to measurements, and the Gamma index (3%/3mm) was always superior to 98%. The feasibility of both clinical applications is shown.

CONCLUSIONS

This model is now shared as a free and open-source tool that generates radiotherapy MC simulations. It has been validated and used for five years. Several applications can be envisaged for research and clinical purposes.

Personalized brachytherapy dose reconstruction using deep learning

BACKGROUND AND PURPOSE

Accurate calculation of the absorbed dose delivered to the tumor and normal tissues improves treatment gain factor, which is the major advantage of brachytherapy over external radiation therapy. To address the simplifications of TG-43 assumptions that ignore the dosimetric impact of medium heterogeneities, we proposed a deep learning (DL)-based approach, which improves the accuracy while requiring a reasonable computation time.

MATERIALS AND METHODS

We developed a Monte Carlo (MC)-based personalized brachytherapy dosimetry simulator (PBrDoseSim), deployed to generate patient-specific dose distributions. A deep neural network (DNN) was trained to predict personalized dose distributions derived from MC simulations, serving as ground truth. The paired channel input used for the training is composed of dose distribution kernel in water medium along with the full-volumetric density maps obtained from CT images reflecting medium heterogeneity.

RESULTS

The predicted single-dwell dose kernels were in good agreement with MC-based kernels serving as reference, achieving a mean relative absolute error (MRAE) and mean absolute error (MAE) of 1.16 ± 0.42% and 4.2 ± 2.7 × 10^-4 (Gy.sec^-1/voxel), respectively. The MRAE of the dose volume histograms (DVHs) between the DNN and MC calculations in the clinical target volume were 1.8 ± 0.86%, 0.56 ± 0.56%, and 1.48 ± 0.72% for D90, V150, and V100, respectively. For bladder, sigmoid, and rectum, the MRAE of D5cc between the DNN and MC calculations were 2.7 ± 1.7%, 1.9 ± 1.3%, and 2.1 ± 1.7%, respectively.

CONCLUSION

The proposed DNN-based personalized brachytherapy dosimetry approach exhibited comparable performance to the MC method while overcoming the computational burden of MC calculations and oversimplifications of TG-43.

Calculation algorithms and penumbra: Underestimation of dose in organs at risk in dosimetry audits

PURPOSE

The aim of this study is to investigate overdose to organs at risk (OARs) observed in dosimetry audits in Monte Carlo (MC) algorithms and Linear Boltzmann Transport Equation (LBTE) algorithms. The impact of penumbra modeling on OAR dose was assessed with the adjustment of MC modeling parameters and the clinical relevance of the audit cases was explored with a planning study of spine and head and neck (H&N) patient cases.

METHODS

Dosimetric audits performed by the Australian Clinical Dosimetry Service (ACDS) of 43 anthropomorphic spine plans and 1318 C-shaped target plans compared the planned dose to doses measured with ion chamber, microdiamond, film, and ion chamber array. An MC EGSnrc model was created to simulate the C-shape target case. The electron cut-off energy E_cut(kinetic) was set at 500, 200, and 10 keV, and differences between 1 and 3 mm voxel were calculated. A planning study with 10 patient stereotactic body radiotherapy (SBRT) spine plans and 10 patient H&N plans was calculated in both Acuros XB (AXB) v15.6.06 and Anisotropic Analytical Algorithm (AAA) v15.6.06. The patient contour was overridden to water as only the penumbral differences between the two different algorithms were under investigation.

RESULTS

The dosimetry audit results show that for the SBRT spine case, plans calculated in AXB are colder than what is measured in the spinal cord by 5%-10%. This was also observed for other audit cases where a C-shape target is wrapped around an OAR where the plans were colder by 3%-10%. Plans calculated with Monaco MC were colder than measurements by approximately 7% with the OAR surround by a C-shape target, but these differences were not noted in the SBRT spine case. Results from the clinical patient plans showed that the AXB was on average 7.4% colder than AAA when comparing the minimum dose in the spinal cord OAR. This average difference between AXB and AAA reduced to 4.5% when using the more clinically relevant metric of maximum dose in the spinal cord. For the H&N plans, AXB was cooler on average than AAA in the spinal cord OAR (1.1%), left parotid (1.7%), and right parotid (2.3%). The EGSnrc investigation also noted similar, but smaller differences. The beam penumbra modeled by E_cut(kinetic)  = 500 keV was steeper than the beam penumbra modeled by E_cut(kinetic)  = 10 keV as the full scatter is not accounted for, which resulted in less dose being calculated in a central OAR region where the penumbra contributes much of the dose. The dose difference when using 2.5 mm voxels of the center of the OAR between 500 and 10 keV was 3%, reducing to 1% between 200 and 10 keV.

CONCLUSIONS

Lack of full penumbral modeling due to approximations in the algorithms in MC based or LBTE algorithms are a contributing factor as to why these algorithms under-predict the dose to OAR when the treatment volume is wrapped around the OAR. The penumbra modeling approximations also contribute to AXB plans predicting colder doses than AAA in areas that are in the vicinity of beam penumbra. This effect is magnified in regions where there are many beam penumbras, for example in the spinal cord for spine SBRT cases.

Gold Nanoparticle DNA Damage by Photon Beam in a Magnetic Field: A Monte Carlo Study

Ever since the emergence of magnetic resonance (MR)-guided radiotherapy, it is important to investigate the impact of the magnetic field on the dose enhancement in deoxyribonucleic acid (DNA), when gold nanoparticles are used as radiosensitizers during radiotherapy. Gold nanoparticle-enhanced radiotherapy is known to enhance the dose deposition in the DNA, resulting in a double-strand break. In this study, the effects of the magnetic field on the dose enhancement factor (DER) for varying gold nanoparticle sizes, photon beam energies and magnetic field strengths and orientations were investigated using Geant4-DNA Monte Carlo simulations. Using a Monte Carlo model including a single gold nanoparticle with a photon beam source and DNA molecule on the left and right, it is demonstrated that as the gold nanoparticle size increased, the DER increased. However, as the photon beam energy decreased, an increase in the DER was detected. When a magnetic field was added to the simulation model, the DER was found to increase by 2.5-5% as different field strengths (0-2 T) and orientations (x-, y- and z-axis) were used for a 100 nm gold nanoparticle using a 50 keV photon beam. The DNA damage reflected by the DER increased slightly with the presence of the magnetic field. However, variations in the magnetic field strength and orientation did not change the DER significantly.

Validation of the TOPAS Monte Carlo toolkit for HDR brachytherapy simulations

PURPOSE

The goal of this work is to validate the user-friendly Geant4-based Monte Carlo toolkit TOol for PArticle Simulation (TOPAS) for brachytherapy applications.

METHODS AND MATERIALS

Brachytherapy simulations performed with TOPAS were systematically compared with published TG-186 reference data. The photon emission energy spectrum, the air-kerma strength, and the dose-rate constant of the model-based dose calculation algorithm (MBDCA)-WG generic Ir-192 source were extracted. For dose calculations, a track-length estimator was implemented. The four Joint AAPM/ESTRO/ABG MBDCA-WG test cases were evaluated through histograms of the local and global dose difference volumes. A prostate, a palliative lung, and a breast case were simulated. For each case, the dose ratio map, the histogram of the global dose difference volume, and cumulative dose-volume histograms were calculated.

RESULTS

The air-kerma strength was (9.772 ± 0.001) × 10-8 U Bq-1 (within 0.3% of the reference value). The dose-rate constant was 1.1107 ± 0.0005 cGy h-1 U-1 (within 0.01% of the reference value). For all cases, at least 96.9% of voxels had a local dose difference within [-1%, 1%] and at least 99.9% of voxels had a global dose difference within [-0.1%, 0.1%]. The implemented track-length estimator scorer was more efficient than the default analog dose scorer by a factor of 237. For all clinical cases, at least 97.5% of voxels had a global dose difference within [-1%, 1%]. Dose-volume histograms were consistent with the reference data.

CONCLUSIONS

TOPAS was validated for high-dose-rate brachytherapy simulations following the TG-186 recommended approach for MBDCAs. Built on top of Geant4, TOPAS provides broad access to a state-of-the-art Monte Carlo code for brachytherapy simulations.