Virtual dosimetry study with three cone-beam breast computed tomography scanners using a fast GPU-based Monte Carlo code.

Objective. To compare the dosimetric performance of three cone-beam breast computed tomography (BCT) scanners, using real-time Monte Carlo-based dose estimates obtained with the virtual clinical trials (VCT)-BREAST graphical processing unit (GPU)-accelerated platform dedicated to VCT in breast imaging. Approach. A GPU-based Monte Carlo (MC) code was developed for replicatingin silicothe geometric, x-ray spectra and detector setups adopted, respectively, in two research scanners and one commercial BCT scanner, adopting 80 kV, 60 kV and 49 kV tube voltage, respectively. Our cohort of virtual breasts included 16 anthropomorphic voxelized breast phantoms from a publicly available dataset. For each virtual patient, we simulated exams on the three scanners, up to a nominal simulated mean glandular dose of 5 mGy (primary photons launched, in the order of 1011-1012per scan). Simulated 3D dose maps (recorded for skin, adipose and glandular tissues) were compared for the same phantom, on the three scanners. MC simulations were implemented on a single NVIDIA GeForce RTX 3090 graphics card.Main results.Using the spread of the dose distribution as a figure of merit, we showed that, in the investigated phantoms, the glandular dose is more uniform within less dense breasts, and it is more uniformly distributed for scans at 80 kV and 60 kV, than at 49 kV. A realistic virtual study of each breast phantom was completed in about 3.0 h with less than 1% statistical uncertainty, with 109primary photons processed in 3.6 s computing time.Significance. We reported the first dosimetric study of the VCT-BREAST platform, a fast MC simulation tool for real-time virtual dosimetry and imaging trials in BCT, investigating the dose delivery performance of three clinical BCT scanners. This tool can be adopted to investigate also the effects on the 3D dose distribution produced by changes in the geometrical and spectrum characteristics of a cone-beam BCT scanner.

ART2Dose: A comprehensive dose verification platform for online adaptive radiotherapy.

BACKGROUND: Online adaptive radiotherapy (ART) involves the development of adaptable treatment plans that consider patient anatomical data obtained right prior to treatment administration, facilitated by cone-beam computed tomography guided adaptive radiotherapy (CTgART) and magnetic resonance image-guided adaptive radiotherapy (MRgART). To ensure accuracy of these adaptive plans, it is crucial to conduct calculation-based checks and independent verification of volumetric dose distribution, as measurement-based checks are not practical within online workflows. However, the absence of comprehensive, efficient, and highly integrated commercial software for secondary dose verification can impede the time-sensitive nature of online ART procedures. PURPOSE: The main aim of this study is to introduce an efficient online quality assurance (QA) platform for online ART, and subsequently evaluate it on Ethos and Unity treatment delivery systems in our clinic. METHODS: To enhance efficiency and ensure compliance with safety standards in online ART, ART2Dose, a secondary dose verification software, has been developed and integrated into our online QA workflow. This implementation spans all online ART treatments at our institution. The ART2Dose infrastructure comprises four key components: an SQLite database, a dose calculation server, a report generator, and a web portal. Through this infrastructure, file transfer, dose calculation, report generation, and report approval/archival are seamlessly managed, minimizing the need for user input when exporting RT DICOM files and approving the generated QA report. ART2Dose was compared with Mobius3D in pre-clinical evaluations on secondary dose verification for 40 adaptive plans. Additionally, a retrospective investigation was conducted utilizing 1302 CTgART fractions from ten treatment sites and 1278 MRgART fractions from seven treatment sites to evaluate the practical accuracy and efficiency of ART2Dose in routine clinical use. RESULTS: With dedicated infrastructure and an integrated workflow, ART2Dose achieved gamma passing rates that were comparable to or higher than those of Mobius3D. Additionally, it significantly reduced the time required to complete pre-treatment checks by 3-4 min for each plan. In the retrospective analysis of clinical CTgART and MRgART fractions, ART2Dose demonstrated average gamma passing rates of 99.61 ± 0.83% and 97.75 ± 2.54%, respectively, using the 3%/2 mm criteria for region greater than 10% of prescription dose. The average calculation times for CTgART and MRgART were approximately 1 and 2 min, respectively. CONCLUSION: Overall, the streamlined implementation of ART2Dose notably enhances the online ART workflow, offering reliable and efficient online QA while reducing time pressure in the clinic and minimizing labor-intensive work.

Mechanistic modelling of relative biological effectiveness of carbon ion beams and comparison with experiments.

Objective.Relative biological effectiveness (RBE) plays a vital role in carbon ion radiotherapy, which is a promising treatment method for reducing toxic effects on normal tissues and improving treatment efficacy. It is important to have an effective and precise way of obtaining RBE values to support clinical decisions. A method of calculating RBE from a mechanistic perspective is reported.Approach.Ratio of dose to obtain the same number of double strand breaks (DSBs) between different radiation types was used to evaluate RBE. Package gMicroMC was used to simulate DSB yields. The DSB inductions were then analyzed to calculate RBE. The RBE values were compared with experimental results.Main results.Furusawa's experiment yielded RBE values of 1.27, 2.22, 3.00 and 3.37 for carbon ion beam with dose-averaged LET of 30.3 keVµm-1, 54.5 keVµm-1, 88 keVµm-1and 137 keVµm-1, respectively. RBE values computed from gMicroMC simulations were 1.75, 2.22, 2.87 and 2.97. When it came to a more sophisticated carbon ion beam with 6 cm spread-out Bragg peak, RBE values were 1.61, 1.63, 2.19 and 2.36 for proximal, middle, distal and distal end part, respectively. Values simulated by gMicroMC were 1.50, 1.87, 2.19 and 2.34. The simulated results were in reasonable agreement with the experimental data.Significance.As a mechanistic way for the evaluation of RBE for carbon ion radiotherapy by combining the macroscopic simulation of energy spectrum and microscopic simulation of DNA damages, this work provides a promising tool for RBE calculation supporting clinical applications such as treatment planning.

Development and implementation of a metaphase DNA model for ionizing radiation induced DNA damage calculation.

Objective. To develop a metaphase chromosome model representing the complete genome of a human lymphocyte cell to support microscopic Monte Carlo (MMC) simulation-based radiation-induced DNA damage studies.Approach. We first employed coarse-grained polymer physics simulation to obtain a rod-shaped chromatid segment of 730 nm in diameter and 460 nm in height to match Hi-C data. We then voxelized the segment with a voxel size of 11 nm per side and connected the chromatid with 30 types of pre-constructed nucleosomes and 6 types of linker DNAs in base pair (bp) resolutions. Afterward, we piled different numbers of voxelized chromatid segments to create 23 pairs of chromosomes of 1-5µm long. Finally, we arranged the chromosomes at the cell metaphase plate of 5.5µm in radius to create the complete set of metaphase chromosomes. We implemented the model in gMicroMC simulation by denoting the DNA structure in a four-level hierarchical tree: nucleotide pairs, nucleosomes and linker DNAs, chromatid segments, and chromosomes. We applied the model to compute DNA damage under different radiation conditions and compared the results to those obtained with G0/G1 model and experimental measurements. We also performed uncertainty analysis for relevant simulation parameters.Main results. The chromatid segment was successfully voxelized and connected in bps resolution, containing 26.8 mega bps (Mbps) of DNA. With 466 segments, we obtained the metaphase chromosome containing 12.5 Gbps of DNA. Applying it to compute the radiation-induced DNA damage, the obtained results were self-consistent and agreed with experimental measurements. Through the parameter uncertainty study, we found that the DNA damage ratio between metaphase and G0/G1 phase models was not sensitive to the chemical simulation time. The damage was also not sensitive to the specific parameter settings in the polymer physics simulation, as long as the produced metaphase model followed a similar contact map distribution.Significance. Experimental data reveal that ionizing radiation induced DNA damage is cell cycle dependent. Yet, DNA chromosome models, except for the G0/G1 phase, are not available in the state-of-the-art MMC simulation. For the first time, we successfully built a metaphase chromosome model and implemented it into MMC simulation for radiation-induced DNA damage computation.

Small animal photon counting cone-beam CT on a preclinical radiation research platform to improve radiation dose calculation accuracy.

Objective.Cone beam CT (CBCT) in preclinical small animal irradiation platforms provides essential information for image guidance and radiation dose calculation for experiment planning. This project developed a photon-counting detector (PCD)-based multi(3)-energy (ME-)CBCT on a small animal irradiator to improve the accuracy of material differentiation and hence dose calculation, and compared to conventional flat panel detector (FPD)-based CBCT.Approach.We constructed a mechanical structure to mount a PCD to an existing preclinical irradiator platform and built a data acquisition pipeline to acquire x-ray projection data with a 100 kVp x-ray beam using three different energy thresholds in a single gantry rotation. We implemented an energy threshold optimization scheme to determine optimal thresholds to balance signal-to-noise ratios (SNRs) among energy channels. Pixel-based detector response calibration was performed to remove ring artifacts in reconstructed CBCT images. Feldkamp-Davis-Kress method was employed to reconstruct CBCT images and a total-variance regularization-based optimization model was used to decompose CBCT images into bone and water material images. We compared dose calculation results using PCD-based ME-CBCT with that of FPD-based CBCT.Main results.The optimal nominal energy thresholds were determined as 26, 56, and 90 keV, under which SNRs in a selected region-of-interest in the water region were 6.11, 5.91 and 5.93 in the three energy channels, respectively. Compared with dose calculation results using FPD-based CBCT, using PCD-based ME-CBCT reduced the mean relative error from 49.5% to 16.4% in bone regions and from 7.5% to 6.9% in soft tissue regions.Significance.PCD-based ME-CBCT is beneficial in improving radiation dose calculation accuracy in experiment planning of preclinical small animal irradiation researches.

Mechanistic modelling of oxygen enhancement ratio of radiation via Monte Carlo simulation-based DNA damage calculation.

Objective.Oxygen plays an important role in affecting the cellular radio-sensitivity to ionizing radiation. The objective of this study is to build a mechanistic model to compute oxygen enhancement ratio (OER) using a GPU-based Monte Carlo (MC) simulation package gMicroMC for microscopic radiation transport simulation and DNA damage calculation.Approach.We first simulated the water radiolysis process in the presence of DNA and oxygen for 1 ns and recorded the produced DNA damages. In this process, chemical reactions among oxygen, water radiolysis free radicals and DNA molecules were considered. We then applied a probabilistic approach to model the reactions between oxygen and indirect DNA damages for a maximal reaction time oft0. Finally, we defined two parametersP0andP1, representing probabilities for DNA damages without and with oxygen fixation effect not being restored in the repair process, to compute the final DNA double strand breaks (DSBs). As cell survival fraction is mainly determined by the number of DSBs, we assumed that the same numbers of DSBs resulted in the same cell survival rates, which enabled us to compute the OER as the ratio of doses producing the same number of DSBs without and with oxygen. We determined the three parameters (t0,P0andP1) by fitting the OERs obtained in our computation to a set of published experimental data under x-ray irradiation. We then validated the model by performing OER studies under proton irradiation and studied model sensitivity to parameter values.Main results.We obtained the model parameters ast0= 3.8 ms,P0= 0.08, andP1= 0.28 with a mean difference of 3.8% between the OERs computed by our model and that obtained from experimental measurements under x-ray irradiation. Applying the established model to proton irradiation, we obtained OERs as functions of oxygen concentration, LET, and dose values, which generally agreed with published experimental data. The parameter sensitivity analysis revealed that the absolute magnitude of the OER curve relied on the values ofP0andP1, while the curve was subject to a horizontal shift when adjustingt0.Significance.This study developed a mechanistic model that fully relies on microscopic MC simulations to compute OER.

Virtual Clinical Trials in 2D and 3D X-ray Breast Imaging and Dosimetry: Comparison of CPU-Based and GPU-Based Monte Carlo Codes.

Computational reproductions of medical imaging tests, a form of virtual clinical trials (VCTs), are increasingly being used, particularly in breast imaging research. The accuracy of the computational platform that is used for the imaging and dosimetry simulation processes is a fundamental requirement. Moreover, for practical usage, the imaging simulation computation time should be compatible with the clinical workflow. We compared three different platforms for in-silico X-ray 3D breast imaging: the Agata (University & INFN Napoli) that was based on the Geant4 toolkit and running on a CPU-based server architecture; the XRMC Monte Carlo (University of Cagliari) that was based on the use of variance reduction techniques, running on a CPU hardware; and the Monte Carlo code gCTD (University of Texas Southwestern Medical Center) running on a single GPU platform with CUDA environment. The tests simulated the irradiation of cylindrical objects as well as anthropomorphic breast phantoms and produced 2D and 3D images and 3D maps of absorbed dose. All the codes showed compatible results in terms of simulated dose maps and imaging values within a maximum discrepancy of 3%. The GPU-based code produced a reduction of the computation time up to factor 104, and so permits real-time VCT studies for X-ray breast imaging.

Improving dose calculation accuracy in preclinical radiation experiments using multi-energy element resolved cone-beam CT.

Objective.Cone-beam CT (CBCT) in modern pre-clinical small-animal radiation research platforms provides volumetric images for image guidance and experiment planning purposes. In this work, we implemented multi-energy element-resolved (MEER) CBCT using three scans with different kVps on a SmART platform (Precision x-ray Inc.) to determine images of relative electron density (rED) and elemental composition (EC) that are needed for Monte Carlo-based radiation dose calculation.Approach.We performed comprehensive calibration tasks to achieve sufficient accuracy for this quantitative imaging purpose. For geometry calibration, we scanned a ball bearing phantom and used an analytical method together with an optimization approach to derive gantry angle specific geometry parameters. Intensity calibration and correction included the corrections for detector lag, glare, and beam hardening. The corrected CBCT projection images acquired at 30, 40, and 60 kVp in multiple scans were used to reconstruct CBCT images using the Feldkamp-Davis-Kress reconstruction algorithm. After that, an optimization problem was solved to determine images of rED and EC. We demonstrated the effectiveness of our CBCT calibration steps by showing improvements in image quality and successful material decomposition in cases with a small animal CT calibration phantom and a plastinated mouse phantom.Main results.It was found that artifacts induced by geometry inaccuracy, detector lag, glare, and beam hardening were visually reduced. CT number mean errors were reduced from 19% to 5%. In the CT calibration phantom case, median errors in H, O, and Ca fractions for all the inserts were below 1%, 2%, and 4% respectively, and median error in rED was less than 5%. Compared to the standard approach deriving material type and rED via CT number conversion, our approach improved Monte Carlo simulation-based dose calculation accuracy in bone regions. Mean dose error was reduced from 47.5% to 10.9%.Significance.The MEER-CBCT implemented on an existing CBCT system of a small animal irradiation platform achieved accurate material decomposition and significantly improved Monte Carlo dose calculation accuracy.

Recent Developments on gMicroMC: Transport Simulations of Proton and Heavy Ions and Concurrent Transport of Radicals and DNA.

Mechanistic Monte Carlo (MC) simulation of radiation interaction with water and DNA is important for the understanding of biological responses induced by ionizing radiation. In our previous work, we employed the Graphical Processing Unit (GPU)-based parallel computing technique to develop a novel, highly efficient, and open-source MC simulation tool, gMicroMC, for simulating electron-induced DNA damages. In this work, we reported two new developments in gMicroMC: the transport simulation of protons and heavy ions and the concurrent transport of radicals in the presence of DNA. We modeled these transports based on electromagnetic interactions between charged particles and water molecules and the chemical reactions between radicals and DNA molecules. Various physical properties, such as Linear Energy Transfer (LET) and particle range, from our simulation agreed with data published by NIST or simulation results from other CPU-based MC packages. The simulation results of DNA damage under the concurrent transport of radicals and DNA agreed with those from nBio-Topas simulation in a comprehensive testing case. GPU parallel computing enabled high computational efficiency. It took 41 s to simultaneously transport 100 protons with an initial kinetic energy of 10 MeV in water and 470 s to transport 105 radicals up to 1 µs in the presence of DNA.

H2RSPET: a 0.5 mm resolution high-sensitivity small-animal PET scanner, a simulation study.

With the goal of developing a total-body small-animal PET system with a high spatial resolution of ∼0.5 mm and a high sensitivity >10% for mouse/rat studies, we simulated four scanners using the graphical processing unit-based Monte Carlo simulation package (gPET) and compared their performance in terms of spatial resolution and sensitivity. We also investigated the effect of depth-of-interaction (DOI) resolution on the spatial resolution. All the scanners are built upon 128 DOI encoding dual-ended readout detectors with lutetium yttrium oxyorthosilicate (LYSO) arrays arranged in 8 detector rings. The solid angle coverages of the four scanners are all ∼0.85 steradians. Each LYSO element has a cross-section of 0.44 × 0.44 mm2 and the pitch size of the LYSO arrays are all 0.5 mm. The four scanners can be divided into two groups: (1) H2RS110-C10 and H2RS110-C20 with 40 × 40 LYSO arrays, a ring diameter of 110 mm and axial length of 167 mm, and (2) H2RS160-C10 and H2RS160-C20 with 60 × 60 LYSO arrays, a diameter of 160 mm and axial length of 254 mm. C10 and C20 denote the crystal thickness of 10 and 20 mm, respectively. The simulation results show that all scanners have a spatial resolution better than 0.5 mm at the center of the field-of-view (FOV). The radial resolution strongly depends on the DOI resolution and radial offset, but not the axial resolution and tangential resolution. Comparing the C10 and C20 designs, the former provides better resolution, especially at positions away from the center of the FOV, whereas the latter has 2× higher sensitivity (∼10% versus ∼20%). This simulation study provides evidence that the 110 mm systems are a good choice for total-body mouse studies at a lower cost, whereas the 160 mm systems are suited for both total-body mouse and rat studies.

Experimental and numerical studies on kV scattered x-ray imaging for real-time image guidance in radiation therapy.

Motion management is a critical component of image guided radiotherapy for lung cancer. We previously proposed a scheme using kV scattered x-ray photons for marker-less real-time image guidance in lung cancer radiotherapy. This study reports our recent progress using the photon counting detection technique to demonstrate potential feasibility of this method and using Monte Carlo (MC) simulations and ray-tracing calculations to characterize the performance. In our scheme, a thin slice of x-ray beam was directed to the target and we measured the outgoing scattered photons using a photon counting detector with a parallel-hole collimator to establish the correspondence between detector pixels and scatter positions. Image corrections of geometry, beam attenuation and scattering angle were performed to convert the raw image to the actual image of Compton attenuation coefficient. We set up a MC simulation system using an in-house developed GPU-based MC package modeling the image formation process. We also performed ray-tracing calculations to investigate the impacts of imaging system geometry on resulting image resolution. The experiment demonstrated feasibility of using a photon counting detector to measure scattered x-ray photons and generate the proposed scattered x-ray image. After correction, x-ray scattering image intensity and Compton scattering attenuation coefficient were linearly related, with R 2 greater than 0.9. Contrast to noise ratios of different objects were improved and the values in experimental results and MC simulation results agreed with each other. Ray-tracing calculations revealed the dependence of image resolution on imaging geometry. The image resolution increases with reduced source to object distance and increased collimator height. The study demonstrated potential feasibility of using scattered x-ray imaging as a real-time image guidance method in radiation therapy.

Modeling the effect of oxygen on the chemical stage of water radiolysis using GPU-based microscopic Monte Carlo simulations, with an application in FLASH radiotherapy.

Oxygen plays a critical role in determining the initial DNA damages induced by ionizing radiation. It is important to mechanistically model the oxygen effect in the water radiolysis process. However, due to the computational costs from the many body interaction problem, oxygen is often ignored or treated as a constant continuum radiolysis-scavenger background in the simulations using common microscopic Monte Carlo tools. In this work, we reported our recent progress on the modeling of the chemical stage of the water radiolysis with an explicit consideration of the oxygen effect, based upon our initial development of an open-source graphical processing unit (GPU)-based MC simulation tool, gMicroMC. The inclusion of oxygen mainly reduces the yields of [Formula: see text] and [Formula: see text] chemical radicals, turning them into highly toxic [Formula: see text] and [Formula: see text] species. To demonstrate the practical value of gMicroMC in large scale simulation problems, we applied the oxygen-simulation-enabled gMicroMC to compute the yields of chemical radicals under a high instantaneous dose rate [Formula: see text] to study the oxygen depletion hypothesis in FLASH radiotherapy. A decreased oxygen consumption rate (OCR) was found associated with a reduced initial oxygen concentration level due to reduced probabilities of reactions. With respect to dose rate, for the oxygen concentration of 21% and electron energy of 4.5 [Formula: see text], OCR remained approximately constant (∼0.22 [Formula: see text]) for [Formula: see text]'s of [Formula: see text], [Formula: see text] and reduced to 0.19 [Formula: see text] at [Formula: see text], because the increased dose rate improved the mutual reaction frequencies among radicals, hence reducing their reactions with oxygen. We computed the time evolution of oxygen concentration under the FLASH irradiation setups. At the dose rate of [Formula: see text] and initial oxygen concentrations from 0.01% to 21%, the oxygen is unlikely to be fully depleted with an accumulative dose of 30 Gy, which is a typical dose used in FLASH experiments. The computational efficiency of gMicroMC when considering oxygen molecules in the chemical stage was evaluated through benchmark work to GEANT4-DNA with simulating an equivalent number of radicals. With an initial oxygen concentration of 3% (∼105 molecules), a speedup factor of 1228 was achieved for gMicroMC on a single GPU card when comparing with GEANT4-DNA on a single CPU.

Dose rate determination for preclinical total body irradiation.

The accuracy of delivered radiation dose and the reproducibility of employed radiotherapy methods are key factors for preclinical radiobiology applications and research studies. In this work, ionization chamber (IC) measurements and Monte Carlo (MC) simulations were used to accurately determine the dose rate for total body irradiation (TBI), a classic radiobiologic and immunologic experimental method. Several phantom configurations, including large solid water slab, small water box and rodentomorphic mouse and rat phantoms were simulated and measured for TBI setup utilizing a preclinical irradiator XRad320. The irradiator calibration and the phantom measurements were performed using an ADCL calibrated IC N31010 following the AAPM TG-61 protocol. The MC simulations were carried out using Geant4/GATE to compute absorbed dose distributions for all phantom configurations. All simulated and measured geometries had favorable agreement. On average, the relative dose rate difference was 2.3%. However, the study indicated large dose rate deviations, if calibration conditions are assumed for a given experimental setup as commonly done for a quick determination of irradiation times utilizing lookup tables and hand calculations. In a TBI setting, the reference calibration geometry at an extended source-to-surface distance and a large reference field size is likely to overestimate true photon scatter. Consequently, the measured and hand calculated dose rates, for TBI geometries in this study, had large discrepancies: 16% for a large solid water slab, 27% for a small water box, and 31%, 36%, and 30% for mouse phantom, rat phantom, and mouse phantom in a pie cage, respectively. Small changes in TBI experimental setup could result in large dose rate variations. MC simulations and the corresponding measurements specific to a designed experimental setup are vital for accurate preclinical dosimetry and reproducibility of radiobiological findings. This study supports the well-recognized need for physics consultation for all radiobiological investigations.

A new open-source GPU-based microscopic Monte Carlo simulation tool for the calculations of DNA damages caused by ionizing radiation --- Part I: Core algorithm and validation.

PURPOSE: Monte Carlo (MC) simulation of radiation interactions with water medium at physical, physicochemical, and chemical stages, as well as the computation of biologically relevant quantities such as DNA damages, are of critical importance for the understanding of microscopic basis of radiation effects. Due to the large problem size and many-body simulation problem in the chemical stage, existing CPU-based computational packages encounter the problem of low computational efficiency. This paper reports our development on a GPU-based microscopic Monte Carlo simulation tool gMicroMC using advanced GPU-acceleration techniques. METHODS: gMicroMC simulated electron transport in the physical stage using an interaction-by-interaction scheme to calculate the initial events generating radicals in water. After the physicochemical stage, initial positions of all radicals were determined. Simulation of radicals' diffusion and reactions in the chemical stage was achieved using a step-by-step model using GPU-accelerated parallelization together with a GPU-enabled box-sorting algorithm to reduce the computations of searching for interaction pairs and therefore improve efficiency. A multi-scale DNA model of the whole lymphocyte cell nucleus containing ~6.2 Gbp of DNA was built. RESULTS: Accuracy of physical stage simulation was demonstrated by computing stopping power and track length. The results agreed with published data and the data produced by GEANT4-DNA (version 10.3.3) simulations with 10 -20% difference in most cases. Difference of yield values of major radiolytic species from GEANT4-DNA results was within 10%. We computed DNA damages caused by monoenergetic 662 keV photons, approximately representing 137 Cs decay. Single-strand break (SSB) and double-strand break (DSB) yields were 196 ± 8 SSB/Gy/Gbp and 7.3 ± 0.7 DSB/Gy/Gbp, respectively, which agreed with the result of 188 SSB/Gy/Gbp and 8.4 DSB/Gy/Gbp computed by Hsiao et al. Compared to computation using a single CPU, gMicroMC achieved a speedup factor of ~540x using an NVidia TITAN Xp GPU card. CONCLUSIONS: The achieved accuracy and efficiency demonstrated that gMicroMC can facilitate research on microscopic radiation transport simulation and DNA damage calculation. gMicroMC is an open-source package available to the research community.

A new open-source GPU-based microscopic Monte Carlo simulation tool for the calculations of DNA damages caused by ionizing radiation - Part II: sensitivity and uncertainty analysis.

PURPOSE: Calculations of deoxyribonucleic acid (DNA) damages involve many parameters in the computation process. As these parameters are often subject to uncertainties, it is of central importance to comprehensively quantify their impacts on DNA single-strand break (SSB) and double-strand break (DSB) yields. This has been a challenging task due to the required large number of simulations and the relatively low computational efficiency using CPU-based MC packages. In this study, we present comprehensive evaluations on sensitivities and uncertainties of DNA SSB and DSB yields on 12 parameters using our GPU-based MC tool, gMicroMC. METHODS: We sampled one electron at a time in a water sphere containing a human lymphocyte nucleus and transport the electrons and generated radicals until 2 Gy dose was accumulated in the nucleus. We computed DNA damages caused by electron energy deposition events in the physical stage and the hydroxyl radicals at the end of the chemical stage. We repeated the computations by varying 12 parameters: (a) physics cross section, (b) cutoff energy for electron transport, (c)-(e) three branching ratios of hydroxyl radicals in the de-excitation of excited water molecules, (f) temporal length of the chemical stage, (g)-(h) reaction radii for direct and indirect damages, (i) threshold energy defining the threshold damage model to generate a physics damage, (j)-(k) minimum and maximum energy values defining the linear-probability damage model to generate a physics damage, and (l) probability to generate a damage by a radical. We quantified sensitivity of SSB and DSB yields with respect to these parameters for cases with 1.0 and 4.5 keV electrons. We further estimated uncertainty of SSB and DSB yields caused by uncertainties of these parameters. RESULTS: Using a threshold of 10% uncertainty as a criterion, threshold energy in the threshold damage model, maximum energy in the linear-probability damage model, and probability for a radical to generate a damage were found to cause large uncertainties in both SSB and DSB yields. The scaling factor of the cross section, cutoff energy, physics reaction radius, and minimum energy in the linear-probability damage model were found to generate large uncertainties in DSB yields. CONCLUSIONS: We identified parameters that can generate large uncertainties in the calculations of SSB and DSB yields. Our study could serve as a guidance to reduce uncertainties of parameters and hence uncertainties of the simulation results.

Carbon-11 and Carbon-12 beam range verifications through prompt gamma and annihilation gamma measurements: Monte Carlo simulations.

Range uncertainty remains a big concern in particle therapy, as it may cause target dose degradation and normal tissue overdosing. Positron emission tomography (PET) and prompt gamma imaging (PGI) are two promising modalities for range verification. However, the relatively long acquisition time of PET and the relatively low yield of PGI pose challenges for real-time range verification. In this paper, we explore using the primary Carbon-11 (C-11) ion beams to enhance the gamma yield compared to the primary C-12 ion beams to improve PET and PGI by using Monte Carlo simulations of water and PMMA phantoms at four incident energies (95, 200, 300, and 430 MeV u-1). Prompt gammas (PGs) and annihilation gammas (AGs) were recorded for post-processing to mimic PGI and PET imaging, respectively. We used both time-of-flight (TOF) and energy selections for PGI, which boosted the ratio of PGs to background neutrons to 2.44, up from 0.87 without the selections. At the lowest incident energy (100 MeVu-1), PG yield from C-11 was 0.82 times of that from C-12, while AG yield from C-11 was 6 ∼ 11 folds higher than from C-12 in PMMA. At higher energies, PG differences between C-11 and C-12 were much smaller, while AG yield from C-11 was 30%∼90% higher than from C-12 using minute-acquisition. With minute-acquisition, the AG depth distribution of C-11 showed a sharp peak coincident with the Bragg peak due to the decay of the primary C-11 ions, but that of C-12 had no such one. The high AG yield and distinct peaks could lead to more precise range verification of C-11 than C-12. These results demonstrate that using C-11 ion beams for potentially combined PGI and PET has great potential to improve online single-spot range verification accuracy and precision.

gPET: a GPU-based, accurate and efficient Monte Carlo simulation tool for PET.

Monte Carlo (MC) simulation method plays an essential role in the refinement and development of positron emission tomography (PET) systems. However, most existing MC simulation packages suffer from long execution time for practical PET simulations. To fully address this issue, we developed and validated gPET, a graphics processing unit (GPU)-based MC simulation tool for PET. gPET was built on the NVidia CUDA platform. The simulation process was modularized into three functional parts and carried out by the GPU parallel threads: (1) source management, including positron decay, transport and annihilation; (2) gamma transport inside the phantom; and (3) signal detection and processing inside the detector. A hybrid of voxelized (for patient phantoms) and parametrized (for detectors) geometries were employed to sufficiently support particle navigations. Multiple inputs and outputs were available. Hence, a user can flexibly examine different aspects of a PET simulation. We evaluated the performance of gPET in three test cases with benchmark work from GATE8.0, in terms of the testing of the functional modules, the physics models used for gamma transport inside the detector, and the geometric configuration of an irregularly shaped PET detector. Both accuracy and efficiency were quantified. In all test cases, the differences between gPET and GATE for the coincidences with respect to the energy and crystal index distributions are below 3.18% and 2.54%, respectively. The speedup factor is 500 for gPET on a single Titan Xp GPU (1.58 GHz) over GATE8.0 on a single core of Intel i7-6850K CPU (3.6 GHz) for all test cases. In summary, gPET is an accurate and efficient MC simulation tool for PET.

Two-dimensional ferromagnetism and driven ferroelectricity in van der Waals CuCrP2S6.

Multiferroic materials have the potential to be applied in novel magnetoelectric devices, for example, high-density non-volatile storage devices. During the last decades, research on multiferroic materials was focused on three-dimensional (3D) materials. However, 3D materials suffer from dangling bonds and quantum tunneling in nano-scale thin films. Two-dimensional (2D) materials might provide an elegant solution to these problems, and thus are highly in demand. Using first-principles calculations, we predicted ferromagnetism and electric-field-driving ferroelectricity in the monolayer and even in the few-layers of CuCrP2S6. Although the total energy of the ferroelectric phase of the monolayer is higher than that of the antiferroelectric phase, the ferroelectric phases can be realized by applying a large electric field. Besides the degrees of freedom in the common multiferroic materials, the valley degree of freedom is also polarized, according to our calculations. The spins, electric dipoles and valleys are coupled with each other as shown in the computational results. In our experiment, we observed the out-of-plane ferroelectricity in few-layer CuCrP2S6 (approximately 13 nm thick) at room temperature. 2D ferromagnetism of few-layers is inferred from the magnetic hysteresis loops of the massively stacked nanosheets at 10 K. The experimental observations support our calculations very well. Our findings may provide a series of 2D materials for further device applications.