Accurate Monte Carlo Simulations Research Articles

Implementation and validation of a very-high-energy electron model in the matRad treatment planning system.

While electron beams of up to 20 MeV are commonly used in radiotherapy, the use of very-high-energy electrons (VHEEs) in the range of 100-200 MeV is now becoming a realistic option thanks to the recent advancements in accelerator technology. Indeed, VHEE offers several clinically attractive features and can be delivered using various conformation methods (including scanning, collimation, and focussing) at ultra-high dose rates. To date, there is a lack of research tools for fast simulation of treatment plans using VHEE beams. This work aims to implement and validate a simple and fast dose calculation algorithm based on the Fermi-Eyges theory of multiple Coulomb scattering for VHEE radiation therapy, with energies up to 200 MeV. A treatment planning system (TPS) toolkit with VHEE modality would indeed allow for further preclinical investigations, including treatment plan optimization and evaluation, and thus contribute to the gradual introduction of VHEE radiotherapy in clinical practice. A VHEE pencil beam scanning double Gaussian model was introduced into the open-source TPS matRad environment along with new functions and options dedicated to VHEE dose calculations. Various geometries and field configurations were then calculated in matRad (up to 200 MeV and 15×15 cm2, with complex bone or lung heterogeneities) and the results were compared to Monte Carlo simulations in the TOPAS/Geant4 toolkit. Two types of beam model (divergent or focused) were also tested. Examples of clinical treatment plans were computed, and the results were compared between the two codes. VHEE modality was fully implemented in matRad with GUI capabilities while preserving all original TPS features. New relevant options such as the importation of specific spot-lists or adjustment of the lateral dose calculation cutoff to optimize the calculation speed were validated. Single spot and square field dose distributions were validated in water alone as well as in clinically relevant inhomogeneities. Dose maps from the VHEE model in matRad were in good agreement with TOPAS (2D gamma index [2%/1mm] with passing rates superior to 90%, <6% mean dose differences), except for large interface heterogeneities. This work describes the implementation of a simple but efficient VHEE simulation model in matRad. A few configurations were studied in order to validate the model against accurate Monte Carlo simulations, demonstrating its usefulness for carrying out preliminary studies involving VHEE radiotherapy.

Analysis of neutron time-of-flight spectra with a Bayesian unfolding methodology

We have developed an innovative methodology for obtaining the neutron energy distribution from a time-of-flight (TOF) measurement based on the iterative Bayesian unfolding method and accurate Monte Carlo simulations. This methodology has been validated through the analysis of a realistic virtual β-decay experiment, including the most relevant systematic effects in a real experiment. The proposed methodology allowed for obtaining accurate results over the energy range above the neutron detection threshold.

Analysis of carbon peak achievement at the provincial level in China: Construction of ensemble prediction models and Monte Carlo simulation

As China advances toward its carbon peaking goals, many regions face the challenge of balancing rapid economic growth with sustainable development. Evaluating carbon emissions at the provincial level is crucial for formulating effective strategies to achieve China's carbon peak targets. This study aims to construct an accurate model for predicting carbon emissions and to explore the evolution of these emissions across Chinese provinces, as well as their contributions to national carbon peak targets. Using the Environmental Kuznets Curve (EKC) theory, the 30 provinces were categorized into groups. An ensemble carbon emissions forecasting model was developed by integrating time-series models with multifactor models. Three scenarios were established within the framework of Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs). Monte Carlo simulations were employed to explore potential pathways to achieve carbon peaks. The results indicate that China will reach its carbon emission peak between 2030 and 2031, with peak values expected to range between 11,499.65 and 11,629.51 Mt. Significant differences were observed among the provincial groups in their contributions to carbon peaking. Groups II and III are projected to peak in 2030 and 2022, respectively, while Groups I and IV face greater challenges, with peak years projected between 2032–2035 and 2031–2034, respectively. Four tiers with different emission reduction responsibilities were identified by comparing the peak times of the 30 provinces under the three scenarios, and optimal recommendations for achieving carbon peaks were proposed for each province. The accurate prediction models and Monte Carlo simulations provide reliable results for achieving carbon peak targets across Chinese provinces, offering a scientific basis for optimizing national carbon emission reduction policies.

Virial coefficients of the uniform electron gas from path-integral Monte Carlo simulations.

The properties of plasmas in the low-density limit are described by virial expansions. Analytical expressions are known from Green's function approaches only for the first three virial coefficients. Accurate path-integral Monte Carlo (PIMC) simulations have recently been performed for the uniform electron gas, allowing the virial expansions to be analyzed and interpolation formulas to be derived. The exact expression for the second virial coefficient is used to test the accuracy of the PIMC simulations and the range of validity of the interpolation formula of Groth etal. [Phys. Rev. Lett. 119, 135001 (2017)0031-900710.1103/PhysRevLett.119.135001], and we discuss the fourth virial coefficient, which is not exactly known yet. Combining PIMC simulations with benchmarks from exact virial expansion results would allow us to obtain more accurate representations of the equationof state for parameter ranges of conditions which are of interest, e.g., for helioseismology.

New Advantage in Stereotactic Treatment of Lung and Pancreatic Cancer. Performance of Ultra-High Energy Electron (VHEE) Therapy Adjuvanted to the FLASH Effect: Clinical Implications and Treatment Plans Analysis

Very High-Energy Electron (VHEE) beams delivered at ultra-high dose rates and hence profiting from the FLASH effect, may be a viable alternative to conventional treatment plans for the treatment of deep-seated tumors. Experimental data support the evidence of a considerable normal tissue sparing effect when treatments are delivered with dose rates much larger (100 times or more) compared to the conventional ones. Lung cancer and pancreatic cancer are considered the two biggest cancer killers. We urgently need more research in these areas, more awareness that support improvement in treatment strategies. To evaluate the potential of FLASH VHEE irradiation in these two clinical situations, we investigated the achievable sparing of healthy tissues and critical dose-limiting structures, with the goal of performing a higher dose prescription. The study on the potential of VHEE for the stereotactic treatment of pancreatic and lung lesions was carried out on two clinical cases treated with Volumetric Modulated Arc Therapy (VMAT) techniques at University Hospital Campus Bio-Medico of Rome. The Planning Target Volume (PTV) was identified and the constraints on the Organs at Risk (OAR) and details on the irradiation approach were defined. The VHEE plan was designed to optimize the dose delivery to best activate the modelled FLASH effect based on the current experimental knowledge. In particular the impact on a dose threshold to activate the effect was studied. The VHEE treatment plan was based on an accurate Monte Carlo simulation of the electrons interactions and the results achievable with different FLASH effect models were studied. The simulation allowed the estimation of dose maps, which were used as input to an optimization algorithm that modified the fluence of each beam to meet treatment prescriptions in terms of dose to PTV. At the end the VHEE DVH plans were compared to VMAT plans. The results demonstrated that FLASH therapy with VHEE beams of 70-130 MeV, could represent a promising alternative to standard radiotherapy allowing a comparable sparing of the healthy tissues. In the case of pancreatic cancer, the Dose Volume Histograms (DVH) showed how such a technique can be effective in sparing the duodenum. In case of lung cancers, the result showed how pulmonary tissue sparing can lead to a substantial reduction of pulmonary toxicity in comparison with the VMAT technique. In the case of pancreatic cancer and assuming a non-negligible contribution from the FLASH effect, the DVH showed how the duodenum healthy tissue sparing could allow a higher dose to be prescribed at the target while keeping the constraints respected, improving the therapeutic ratio. In the case of lung cancer, the advantages of the technique are additionally increased by the significant benefit that could be related to the treatment delivery time reduction (<1s) and to the corresponding advantage coming from a reduced organ movement that translates in a lower risk of lung toxicity.

Proton Bragg peak imaging by colour centre radiophotoluminescence in lithium fluoride thin film radiation detectors on silicon

Optically transparent lithium fluoride (LiF) thin films, thermally evaporated on Si(100) substrates, are under investigation as novel radiation detectors based on radiophotoluminescence for imaging of the full Bragg curves of proton beams produced by a linear accelerator for proton therapy under development at ENEA C.R. Frascati. Proton irradiation induces the formation of stable colour centres in LiF, amongst which the broadband light-emitting F2 and F3+ aggregate defects, whose concentrations are locally proportional to the energy deposited in the material. Their spatial distributions in the irradiated LiF thin films and crystals are carefully measured by acquiring the latent two-dimensional visible fluorescence images with an optical microscope under blue lamp excitation. Several LiF films grown on silicon substrate were irradiated in air at increasing proton energies up to 35 MeV with their surface parallel to the particle beam and a cleaved edge perpendicularly facing it; for each sample, the fluorescence image acquired from the top surface side of the film allows to obtain the depth profile of the energy released by protons. Differences in colour centre distributions detected in LiF films with respect to LiF crystals are presented and discussed. Accurate Monte Carlo simulations allow to fully explain their experimental behaviours, paving the way towards using LiF film radiation detectors on silicon for the advanced diagnostics of proton beams at typical particle energies used for proton therapy.

β-delayed neutron spectroscopy of 85,86As with MONSTER

The β-delayed neutron emission in the 85,86As β-decays has been measured at the IGISOL facility of the Accelerator Laboratory of the University of Jyväskylä (JYFL-ACCLAB). The complete β-decays have been studied with a complex setup that consists of a plastic scintillator, the MOdular Neutron time-of-flight SpectromeTER (MONSTER), and two types of γ-ray detectors—an HPGe clover and four LaBr3 crystals. The β-delayed neutron energy distributions have been determined by unfolding the TOF spectra with an innovative methodology based on the iterative Bayesian unfolding method and accurate Monte Carlo simulations.

Feasibility Study on the nIORT® Adjuvant Treatment of Glioblastoma Multiforme through the Irradiation Field of Fast Neutrons Produced by a Compact Generator

The glioblastoma multiforme (GBM) is the most malignant glial brain tumour with average survival time of 6÷18 months. Emerging evidence suggests that GBM cells appears to reprogram their tumour microenvironment, which is a highly heterogeneous and complex system, so that an efficient GBM radiotherapy (RT) should cover both the cells of the GBM and those of its microenvironment. Relying on a 5-year collaborative research study on the intra-operative radiotherapy (IORT) with fast neutrons - the so-called neutron-IORT (nIORT®) technique - the authors think that this objective could be achieved by using an ionizing radiation field of fast neutrons that behave in the biological tissues as a “foam field” hitting both the GBM cancer cells and the neighbouring microenvironment. The nIORT® research activities - conducted by TheranostiCentre Srl, Berkion Technology LLC and ENEA - led to the fabrication of the first prototype of a compact neutron generator (CNG) that, through the deuterium-deuterium fusion reaction, produces neutrons of 2.45 MeV energy having: i) high linear energy transfer; ii) very high relative biological effectiveness (RBE), about 16 times higher than X-rays (and electrons) used in standard RT and IORT treatments; iii) reduced oxygen enhancement ratio, and hence resulting be very effective in cancer cells necrosis and apoptosis. The CNG is self-shielded, limited in size and weight (~120 kg) and manageable remotely by a robotic arm. A new prototype equipped by a cylindrical applicator to be inserted in the surgical cavities is currently under construction, with some technical advancements making possible its installation in an operating room dedicated to nIORT® treatments without posing any safety and environmental concern. In this article the nIORT® potentiality was investigated in the view of the GBM treatment, but the study is however generalisable for the neutron irradiation of other brain cancer pathologies. Accurate Monte Carlo simulations, modelling the CNG equipped with a couple of cylindrical applicators of 4 and 6 cm in diameter inserted in the brain surgical cavity after craniotomy, demonstrated that the nIORT® device operated at 100 kV-10 mA DC supplies a neutron flux ~108 cm-2 s-1 and can deliver equivalent dose rates ~5 Gy (RBE)/min in the centre of the tumour bed. Thus, it could administer the clinical endpoints foreseen by the standard IORT protocols (~10-20 Gy (RBE)) in treatment times of few minutes, by providing a sort of “switching on and off neutron brachytherapy tool” without using needles of radioisotopes (e.g., 252Cf). The near isotropic neutron emission allows to irradiate the tumour bed margins, normally filled by potential quiescent cancer cells, with lower (but still significant) dose levels. This should improve the local control of the tumour through the reduction of local recurrences and metastasis in the tumour microenvironment, and at the same time to avoid adverse effects of the administered neutron radiation field on the surrounding brain central nervous system. Also, the rapid decrease in tissue depth of the dose gradient (within few centimetres) should avoid any adverse effect on normal brain tissues and the neighbouring organs.

A COMPACT NEUTRON GENERATOR FOR THE NIORT® TREATMENT OF SEVERE SOLID CANCERS

In the last four years, TheranostiCentre S.r.l., Berkion Technology LLC and ENEA have patented and fabricated a first prototype of a Compact Neutron Generator (CNG) currently under testing in the ENEA laboratories. Besides the usual applications in the field of materials irradiation, this CNG - producing neutrons of 2.45 MeV energy by using the DD fusion reaction - was conceived for the neutron irradiation of the solid cancer’s tumour bed by means of the Intra-Operative Radiotherapy (IORT) technique, the so-called neutron-IORT (nIORT®). The CNG is self-shielded and light-weight (~120 kg) making possible its remote handling by a robotic arm. Accurate Monte Carlo simulations, modelling the CNG and the “open wound” biological tissues near its irradiation window, demonstrated that the apparatus - operated at 100 kV-10 mA - supplies a neutron flux ~108 cm-2 s-1 and can deliver equivalent dose rates ~2 Gy (RBE)/min. Hence, it can administer very high dose levels in limited treatment times. This article briefly summarizes the main findings of this collaborative research study, the clinical rationales underpinning the nIORT® idea and the potential performances of the CNG for the treatment of solid cancer pathologies. Indeed, the CNG can be installed in an operating room dedicated to nIORT® treatments, without posing any environmental and safety issues. Monte Carlo simulations have been carried out by envisioning the CNG equipped with an IORT applicator, that is an applicator pipe with a tuneable diameter to be inserted in the surgical cavity. By foreseeing the clinical endpoints of the standard IORT protocols, the irradiation performances for potential nIORT® treatments - obtained with an applicator pipe of 6 cm diameter - are here reported for different regimes: from 10 up to 75 Gy (RBE), that can be administered in a single session of about 4 to 30 minutes. Besides the dose peak in the centre of the tumour bed, the almost isotropic neutrons emission allows to irradiate the surroundings side-walls of the tumour bed – usually filled by potential quiescent cancer cells (QCCs) – and therefore reducing the chances of local recurrences by improving the local control of the tumour. The rapid decrease in tissues depth of the dose profile (in few centimetres) will spare the neighbouring organs at risk from harmful radiations. Thus, the CNG apparatus developed for nIORT® applications can potentially improve the resectability rate of a given neoadjuvant cancer treatment and, generally, could satisfy all five R’s criteria of radiotherapy. Furthermore, in comparing with the current IORT techniques with electrons or low-keV X-rays, the nIORT® exploiting a high-flux neutrons beam of 2.45 MeV energy could lead to some significant clinical advantages due to its larger Linear Energy Transfer (LET, ~ 40 keV/m as average) and significantly higher Relative Biological Effectiveness (RBE 16) than all other forms of ionizing radiation.

Measured and GATE predicted PET-image-based activity range verification for carbon therapy: a phantom study

In-beam PET is one of the imaging-based methods for monitoring carbon therapy by reconstruction of positron-emitters produced by incident particles. The accurate Monte Carlo simulation is necessary for range verification and therapeutic dose monitoring by means of the in-beam PET. GATE is capable of performing in-beam PET imaging but very few studies assess the accuracy of activity range measured from PET imaging with GATE simulated results. In this work, we present both experimental and GATE simulation studies of in-beam PET imaging of a phantom, which is irradiated by carbon ion beam, for range verification. The experiment data is acquired at Wuwei Heavy Ion Cancer Treatment Center in Gansu, China, with a dual-head plate PET prototype. The PET prototype consists of 2 panels, each arranged in 2 × 2 matrix. Each detector block is composed of 20 × 20 LYSO crystal array coupled with the position-sensitive photomultiplier tube (HAMAMATSU H8500). A homogeneous plastic phantom is irradiated with monoenergetic 131.05 MeV and 190.19 MeV 12C ion pencil beams. The irradiation and full response of PET prototype are simulated with GATE macros. A novel mathematical model is established, which is capable of calculating and revealing the variation of the positron activity. Our focus is on the reconstructed activity ranges obtained by the experimental measurement and GATE MC prediction combined with the positron activity distribution calculation mathematical model. Results show that the reconstructed activity distribution of experimental data and GATE MC prediction are in good agreement. The measured and simulated 1D activity peak and falling edge positions are within 1.0 mm in all cases. The 20%, 50% and 80% PET peak positions predicted by GATE are close to measurements. These results indicated that it is feasible to assess the accuracy of activity range measured from the dual-head plate PET system with the modeled GATE hadron-PET simulation.

I2S-LWR Activation Analysis of Heat Exchangers Using Hybrid Shielding Methodology With SCALE6.1

The Integral Inherently Safe Light Water Reactor (I2S-LWR) concept developed by a team lead by Georgia Tech is a novel PWR reactor delivering electric power of 1000 MWe while implementing inherent safety features typically reserved for Generation III+ small modular reactors. The main safety feature is based on an integral primary circuit configuration, bringing together a compact core design with 121 fuel assemblies (FA), control rod drive mechanism (CRDM), 8 primary heat exchangers (PHE), 4 passive decay heat removal systems (DHRS), 8 pumps, and other integral components. A high power density core based on uranium silicide fuel (U3Si2) is selected to achieve high thermal power which is extracted with PHEs placed in the annular region between the barrel and the vessel. The compact and integrated design of I2S-LWR leads to activation of integral components, mainly made from stainless steel, so accurate and precise Monte Carlo (MC) simulations are needed to quantify potential dose rates to personnel during routine maintenance operation. This shielding problem is therefore very challenging, posing a non-trivial neutron flux solution in a phase space. This paper presents the performance of the hybrid shielding methodologies CADIS/FW-CADIS implemented in the MAVRIC sequence of the SCALE6.1 code package. The main objective was to develop a detailed MC shielding model of the I2S-LWR reactor along with effective variance reduction (VR) parameters and to calculate neutron fluence rates inside PHEs. Such results are then utilized to find the neutron activation rate distribution via 60Co generation inside of a stack of microchannel heat exchangers (MCHX), which will be periodically withdrawn for the maintenance. 59Co impurities are the main cause of (n,γ) radiative gamma dose to personnel via neutron activation since 60Co has half-life of 5.27 years and is emitting high energy gamma rays (1.17 MeV and 1.33 MeV). The developed MC model was successfully used to find converged fluxes inside all 8 stacks of PHEs with respect to MC statistics using the FW-CADIS methodology. For that purpose the SN module Denovo, based on forward-adjoint transport theory, was used to find VR parameters (importance map and biased source) to effectively bias MC simulation. Further research is required to account for other activation pathways, i.e. isotopes of iron which may generate 59Co through neutron activation and beta decay.

Learning the Physics of Particle Transport via Transformers

Particle physics simulations are the cornerstone of nuclear engineering applications. Among them radiotherapy (RT) is crucial for society, with 50% of cancer patients receiving radiation treatments. For the most precise targeting of tumors, next generation RT treatments aim for real-time correction during radiation delivery, necessitating particle transport algorithms that yield precise dose distributions in sub-second times even in highly heterogeneous patient geometries. This is infeasible with currently available, purely physics based simulations. In this study, we present a data-driven dose calculation algorithm predicting the dose deposited by mono-energetic proton beams for arbitrary energies and patient geometries. Our approach frames particle transport as sequence modeling, where convolutional layers extract important spatial features into tokens and the transformer self-attention mechanism routes information between such tokens in the sequence and a beam energy token. We train our network and evaluate prediction accuracy using computationally expensive but accurate Monte Carlo (MC) simulations, considered the gold standard in particle physics. Our proposed model is 33 times faster than current clinical analytic pencil beam algorithms, improving upon their accuracy in the most heterogeneous and challenging geometries. With a relative error of 0.34±0.2% and very high gamma pass rate of 99.59±0.7% (1%, 3 mm), it also greatly outperforms the only published similar data-driven proton dose algorithm, even at a finer grid resolution. Offering MC precision 4000 times faster, our model could overcome a major obstacle that has so far prohibited real-time adaptive proton treatments and significantly increase cancer treatment efficacy. Its potential to model physics interactions of other particles could also boost heavy ion treatment planning procedures limited by the speed of traditional methods.

The Accuracy of Cerenkov Photons Simulation in Geant4/Gate Depends on the Parameterization of Primary Electron Propagation.

Energetic electrons traveling in a dispersive medium can produce Cerenkov radiation. Cerenkov photons' prompt emission, combined with their predominantly forward emission direction with respect to the parent electron, makes them extremely promising to improve radiation detector timing resolution. Triggering gamma detections based on Cerenkov photons to achieve superior timing resolution is challenging due to the low number of photons produced per interaction. Monte Carlo simulations are fundamental to understanding their behavior and optimizing their pathway to detection. Therefore, accurately modeling the electron propagation and Cerenkov photons emission is crucial for reliable simulation results. In this work, we investigated the physics characteristics of the primary electrons (velocity, energy) and those of all emitted Cerenkov photons (spatial and timing distributions) generated by 511 keV photoelectric interactions in a bismuth germanate crystal using simulations with Geant4/GATE. Geant4 uses a stepwise particle tracking approach, and users can limit the electron velocity change per step. Without limiting it (default Geant4 settings), an electron mean step length of ~250 μm was obtained, providing only macroscopic modeling of electron transport, with all Cerenkov photons emitted in the forward direction with respect to the incident gamma direction. Limiting the electron velocity change per step reduced the electron mean step length (~0.200 μm), leading to a microscopic approach to its transport which more accurately modeled the electron physical properties in BGO at 511 keV. The electron and Cerenkov photons rapidly lost directionality, affecting Cerenkov photons' transport and, ultimately, their detection. Results suggested that a deep understanding of low energy physics is crucial to perform accurate optical Monte Carlo simulations and ultimately use them in TOF PET detectors.

Proton therapy monitoring: spatiotemporal emission reconstruction with prompt gamma timing and implementation with PET detectors

Objective. In this study we introduce spatiotemporal emission reconstruction prompt gamma timing (SER-PGT), a new method to directly reconstruct the prompt photon emission in the space and time domains inside the patient in proton therapy. Approach. SER-PGT is based on the numerical optimisation of a multidimensional likelihood function, followed by a post-processing of the results. The current approach relies on a specific implementation of the maximum-likelihood expectation maximisation algorithm. The robustness of the method is guaranteed by the complete absence of any information about the target composition in the algorithm. Main results. Accurate Monte Carlo simulations indicate a range resolution of about 0.5 cm (standard deviation) when considering 107 primary protons impinging on an homogeneous phantom. Preliminary results on an anthropomorphic phantom are also reported. Significance. By showing the feasibility for the reconstruction of the primary particle range using PET detectors, this study provides significant basis for the development of an hybrid in-beam PET and prompt photon device.

Band selection for oxygenation estimation with multispectral/hyperspectral imaging.

Multispectral imaging provides valuable information on tissue composition such as hemoglobin oxygen saturation. However, the real-time application of this technique in interventional medicine can be challenging due to the long acquisition times needed for large amounts of hyperspectral data with hundreds of bands. While this challenge can partially be addressed by choosing a discriminative subset of bands, the band selection methods proposed to date are mainly restricted by the availability of often hard to obtain reference measurements. We address this bottleneck with a new approach to band selection that leverages highly accurate Monte Carlo (MC) simulations. We hypothesize that a so chosen small subset of bands can reproduce or even improve upon the results of a quasi continuous spectral measurement. We further investigate whether novel domain adaptation techniques can address the inevitable domain shift stemming from the use of simulations. Initial results based on in silico and in vivo experiments suggest that 10-20 bands are sufficient to closely reproduce results from spectral measurements with 101 bands in the 500-700 nm range. The investigated domain adaptation technique, which only requires unlabeled in vivo measurements, yielded better results than the pure in silico band selection method. Overall, our method could guide development of fast multispectral imaging systems suited for interventional use without relying on complex hardware setups or manually labeled data.

Deep Seated Tumour Treatments With Electrons of High Energy Delivered at FLASH Rates: The Example of Prostate Cancer.

Different therapies are adopted for the treatment of deep seated tumours in combination or as an alternative to surgical removal or chemotherapy: radiotherapy with photons (RT), particle therapy (PT) with protons or even heavier ions like 12C, are now available in clinical centres. In addition to these irradiation modalities, the use of Very High Energy Electron (VHEE) beams (100–200 MeV) has been suggested in the past, but the diffusion of that technique was delayed due to the needed space and budget, with respect to standard photon devices. These disadvantages were not paired by an increased therapeutic efficacy, at least when comparing to proton or carbon ion beams. In this contribution we investigate how recent developments in electron beam therapy could reshape the treatments of deep seated tumours. In this respect we carefully explored the application of VHEE beams to the prostate cancer, a well-known and studied example of deep seated tumour currently treated with high efficacy both using RT and PT. The VHEE Treatment Planning System was obtained by means of an accurate Monte Carlo (MC) simulation of the electrons interactions with the patient body. A simple model of the FLASH effect (healthy tissues sparing at ultra-high dose rates), has been introduced and the results have been compared with conventional RT. The study demonstrates that VHEE beams, even in absence of a significant FLASH effect and with a reduced energy range (70–130 MeV) with respect to implementations already explored in literature, could be a good alternative to standard RT, even in the framework of technological developments that are nowadays affordable.

Efficient uncertainty quantification for Monte Carlo dose calculations using importance (re-)weighting

Objective. To present an efficient uncertainty quantification method for range and set-up errors in Monte Carlo (MC) dose calculations. Further, we show that uncertainty induced by interplay and other dynamic influences may be approximated using suitable error correlation models. Approach. We introduce an importance (re-)weighting method in MC history scoring to concurrently construct estimates for error scenarios, the expected dose and its variance from a single set of MC simulated particle histories. The approach relies on a multivariate Gaussian input and uncertainty model, which assigns probabilities to the initial phase space sample, enabling the use of different correlation models. Through modification of the phase space parameterization, accuracy can be traded between that of the uncertainty or the nominal dose estimate. Main results. The method was implemented using the MC code TOPAS and validated for proton intensity-modulated particle therapy (IMPT) with reference scenario estimates. We achieve accurate results for set-up uncertainties (γ 2 mm/2% ≥ 99.01% (E[ d ]), γ 2 mm/2% ≥ 98.04% (σ( d ))) and expectedly lower but still sufficient agreement for range uncertainties, which are approximated with uncertainty over the energy distribution. Here pass rates of 99.39% (E[ d ])/ 93.70% (σ( d )) (range errors) and 99.86% (E[ d ])/ 96.64% (σ( d )) (range and set-up errors) can be achieved. Initial evaluations on a water phantom, a prostate and a liver case from the public CORT dataset show that the CPU time decreases by more than an order of magnitude. Significance. The high precision and conformity of IMPT comes at the cost of susceptibility to treatment uncertainties in particle range and patient set-up. Yet, dose uncertainty quantification and mitigation, which is usually based on sampled error scenarios, becomes challenging when computing the dose with computationally expensive but accurate MC simulations. As the results indicate, the proposed method could reduce computational effort while also facilitating the use of high-dimensional uncertainty models.

High-throughput, accurate Monte Carlo simulation on CPU hardware for PET applications

Monte Carlo simulations (MCS) represent a fundamental approach to modelling the photon interactions in positron emission tomography (PET). A variety of PET-dedicated MCS tools are available to assist and improve PET imaging applications. Of these, GATE has evolved into one of the most popular software for PET MCS because of its accuracy and flexibility. However, simulations are extremely time-consuming. The use of graphics processing units (GPU) has been proposed as a solution to this, with reported acceleration factors about 400–800. These factors refer to GATE benchmarks performed on a single CPU core. Consequently, CPU-based MCS can also be easily accelerated by one order of magnitude or beyond when exploiting multi-threading on powerful CPUs. Thus, CPU-based implementations become competitive when further optimisations can be achieved. In this context, we have developed a novel, CPU-based software called the PET physics simulator (PPS), which combines several efficient methods to significantly boost the performance. PPS flexibly applies GEANT4 cross-sections as a pre-calculated database, thus obtaining results equivalent to GATE. This is demonstrated for an elaborated PET scanner with 3-layer block detectors. All code optimisations yield an acceleration factor of ≈20 (single core). Multi-threading on a high-end CPU workstation (96 cores) further accelerates the PPS by a factor of 80. This results in a total speed-up factor of ≈1600, which outperforms comparable GPU-based MCS by a factor of ≳2. Optionally, the proposed method of coincidence multiplexing can further enhance the throughput by an additional factor of ≈15. The combination of all optimisations corresponds to an acceleration factor of ≈24 000. In this way, the PPS can simulate complex PET detector systems with an effective throughput of 106 photon pairs in less than 10 milliseconds.

Correlations and structure of interfaces in the Ising model: theory and numerics

We consider phase separation on the strip for the two-dimensional Ising model in the near-critical region. Within the framework of field theory, we find exact analytic results for certain two- and three-point correlation functions of the order parameter field. The analytic results for order parameter correlations, energy density profile, subleading corrections and passage probability density of the interface are confirmed by accurate Monte Carlo simulations we performed.

Efficient, High-Fidelity Modeling and Simulation of Global Navigation Satellite System Constellations

This paper presents a method for modeling and simulation of Global Navigation Satellite System (GNSS) constellations by the use of Chebyshev polynomials fit to publicly available precision data. The Global Positioning System (GPS) is used to demonstrate the method, but the method applies to all GNSS with precise ephemeris data including Galileo and GLONASS. The method facilitates highly accurate satellite orbit and clock modeling, including relativistic effects, with mean fit differences of the order in position, in velocity, and microseconds in clock offset. The method also improves simulation run time by using a fast technique for evaluating the Chebyshev polynomials. Runtime comparisons demonstrate the polynomial method reduces runtime by up to 72% of more traditional methods. The speed of the method makes it well suited for practical, accurate Monte Carlo simulation techniques. The method can be used in simulations for the verification and validation of GNSS receivers embedded in autonomous aerospace navigation systems, for uncertainty analysis, and for other purposes. Details for validating the precision data are given. Pseudocode algorithms are provided for fitting and evaluating Chebyshev polynomials. Also provided are high-level concepts of one approach for integrating the method into larger, multisystem aerospace simulations, including the effects of signal propagation delay and Earth blockage.