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DOE OSTI2017

TUNABLE IRRADIATION TESTBED

PNNL has developed and continues to develop innovative methods for characterizing irradiated materials from nuclear reactors and particle accelerators for various clients and collaborators around the world. The continued development of these methods, in addition to the ability to perform unique scientific investigations of the effects of radiation on materials could be greatly enhanced with easy access to irradiation facilities. A Tunable Irradiation Testbed with customized targets (a 30 MeV, 1mA cyclotron or similar coupled to a unique target system) is shown to provide a much more flexible and cost-effective source of irradiating particles than a test reactor or isotopic source. The configuration investigated was a single shielded building with multiple beam lines from a small, flexible, high flux irradiation source. Potential applications investigated were the characterization of radiation damage to materials applicable to advanced reactors, fusion reactor, legacy waste, (via neutron spectra tailored to HTGR, molten salt, LWR, LMR, fusion environments); 252Cf replacement; characterization of radiation damage to materials of interest to High Energy Physics to enable the neutrino program; and research into production of short lived isotopes for potential medical and other applications.

Wootan, David W.↗

DOE OSTI2017

TUNABLE IRRADIATION TESTBED

Wootan, David W.↗

DOE OSTI2021

Accelerating phase-field-based microstructure evolution predictions via surrogate models trained by machine learning methods

Abstract The phase-field method is a powerful and versatile computational approach for modeling the evolution of microstructures and associated properties for a wide variety of physical, chemical, and biological systems. However, existing high-fidelity phase-field models are inherently computationally expensive, requiring high-performance computing resources and sophisticated numerical integration schemes to achieve a useful degree of accuracy. In this paper, we present a computationally inexpensive, accurate, data-driven surrogate model that directly learns the microstructural evolution of targeted systems by combining phase-field and history-dependent machine-learning techniques. We integrate a statistically representative, low-dimensional description of the microstructure, obtained directly from phase-field simulations, with either a time-series multivariate adaptive regression splines autoregressive algorithm or a long short-term memory neural network. The neural-network-trained surrogate model shows the best performance and accurately predicts the nonlinear microstructure evolution of a two-phase mixture during spinodal decomposition in seconds, without the need for “on-the-fly” solutions of the phase-field equations of motion. We also show that the predictions from our machine-learned surrogate model can be fed directly as an input into a classical high-fidelity phase-field model in order to accelerate the high-fidelity phase-field simulations by leaping in time. Such machine-learned phase-field framework opens a promising path forward to use accelerated phase-field simulations for discovering, understanding, and predicting processing–microstructure–performance relationships.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Multipoint-BAX: a new approach for efficiently tuning particle accelerator emittance via virtual objectives

Abstract Although beam emittance is critical for the performance of high-brightness accelerators, optimization is often time limited as emittance calculations, commonly done via quadrupole scans, are typically slow. Such calculations are a type of multipoint query , i.e. each query requires multiple secondary measurements. Traditional black-box optimizers such as Bayesian optimization are slow and inefficient when dealing with such objectives as they must acquire the full series of measurements, but return only the emittance, with each query. We propose a new information-theoretic algorithm, Multipoint-BAX , for black-box optimization on multipoint queries, which queries and models individual beam-size measurements using techniques from Bayesian Algorithm Execution (BAX). Our method avoids the slow multipoint query on the accelerator by acquiring points through a virtual objective , i.e. calculating the emittance objective from a fast learned model rather than directly from the accelerator. We use Multipoint-BAX to minimize emittance at the Linac Coherent Light Source (LCLS) and the Facility for Advanced Accelerator Experimental Tests II (FACET-II). In simulation, our method is 20× faster and more robust to noise compared to existing methods. In live tests, it matched the hand-tuned emittance at FACET-II and achieved a 24% lower emittance than hand-tuning at LCLS. Our method represents a conceptual shift for optimizing multipoint queries, and we anticipate that it can be readily adapted to similar problems in particle accelerators and other scientific instruments.

43 PARTICLE ACCELERATORS↗

DOE OSTI2016

TU-AB-BRC-11: Moving a GPU-OpenCL-Based Monte Carlo (MC) Dose Engine Towards Routine Clinical Use: Automatic Beam Commissioning and Efficient Source Sampling

Purpose: We have previously developed a GPU-OpenCL-based MC dose engine named goMC with built-in analytical linac beam model. To move goMC towards routine clinical use, we have developed an automatic beam-commissioning method, and an efficient source sampling strategy to facilitate dose calculations for real treatment plans. Methods: Our commissioning method is to automatically adjust the relative weights among the sub-sources, through an optimization process minimizing the discrepancies between calculated dose and measurements. Six models built for Varian Truebeam linac photon beams (6MV, 10MV, 15MV, 18MV, 6MVFFF, 10MVFFF) were commissioned using measurement data acquired at our institution. To facilitate dose calculations for real treatment plans, we employed inverse sampling method to efficiently incorporate MLC leaf-sequencing into source sampling. Specifically, instead of sampling source particles control-point by control-point and rejecting the particles blocked by MLC, we assigned a control-point index to each sampled source particle, according to MLC leaf-open duration of each control-point at the pixel where the particle intersects the iso-center plane. Results: Our auto-commissioning method decreased distance-to-agreement (DTA) of depth dose at build-up regions by 36.2% averagely, making it within 1mm. Lateral profiles were better matched for all beams, with biggest improvement found at 15MV for which root-mean-square difference was reduced from 1.44% to 0.50%. Maximum differences of output factors were reduced to less than 0.7% for all beams, with largest decrease being from1.70% to 0.37% found at 10FFF. Our new sampling strategy was tested on a Head&Neck VMAT patient case. Achieving clinically acceptable accuracy, the new strategy could reduce the required history number by a factor of ∼2.8 given a statistical uncertainty level and hence achieve a similar speed-up factor. Conclusion: Our studies have demonstrated the feasibility and effectiveness of our auto-commissioning approach and new efficient source sampling strategy, implying the potential of our GPU-based MC dose engine goMC for routine clinical use.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2023

Distributed Optimal Power Management for Battery Energy Storage Systems: A Novel Accelerated Tracking ADMM Approach

Optimal power management (OPM) is critical for large-scale battery energy storage systems. Today’s methods often require formidable computational effort due to the design based on centralized numerical optimization. Thus, this paper investigates computationally distributed OPM where the agents based on the cells communicate over a network to cooperatively solve the OPM problem. We propose an accelerated tracking alternating direction method of multipliers (ADMM) algorithm to solve the distributed OPM. The proposed algorithm embeds dynamic average consensus and Nesterov’s acceleration technique in the ADMM algorithm. Not only is the proposed algorithm fully distributed without a need for fusion or aggregating nodes, but it also accelerates convergence. The paper formulates the OPM in a model predictive control framework where it seeks to regulate the charging/discharging power of each battery cell to minimize the total power losses and promote balanced use of the constituent cells while complying with the safety constraints. The paper provides ample simulation results to demonstrate the effectiveness and advantages of the proposed distributed OPM in terms of computation and convergence.

Farakhor, Amir↗

DOE OSTI2024

Promoting regulatory acceptance of combined ion and neutron irradiation testing of nuclear reactor materials: Modeling and software considerations

As the needs for the nuclear energy industry continue to evolve in the 21st century, timely adoption of new technological solutions acceptable to regulatory agencies is critical. Quantitative prediction of radiation damage in materials and its impact on mechanical properties is a key component of licensing and regulatory decisions regarding nuclear power plants. Accelerated testing methodologies such as combined ion and neutron irradiation data sets are crucial for the development and deployment of new materials and new manufacturing methods (e.g., additive manufacturing). However, regulatory acceptance of accelerated testing methodologies is necessary for their adoption. Further, the present work discusses the fundamental basis for comparing ion- and neutron-induced material microstructures, the theory behind interpreting radiation damage across length and time scales and radiation types, and the codes, standards, and quality assurance concerns surrounding different modeling methods and software. In particular, recommendations are given as to the path forward that will enable national laboratories, academia, and industry to develop the modeling and software basis for regulatory acceptance of the combined use of ion and neutron irradiation for material performance evaluation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2016

SU-F-T-366: Dosimetric Parameters Enhancement of 120-Leaf Millennium MLC Using EGSnrc and IAEA Phase-Space Data

Purpose: Recently, the multileaf collimators (MLC) have become an important part of any LINAC collimation systems because they reduce the treatment planning time and improves the conformity. Important factors that affects the MLCs collimation performance are leaves material composition and their thickness. In this study, we investigate the main dosimetric parameters of 120-leaf Millennium MLC including dose in the buildup point, physical penumbra as well as average and end leaf leakages. Effects of the leaves geometry and density on these parameters are evaluated Methods: From EGSnrc Monte Carlo code, BEAMnrc and DOSXYZnrc modules are used to evaluate the dosimetric parameters of a water phantom exposed to a Varian xi for 100cm SSD. Using IAEA phasespace data just above MLC (Z=46cm) and BEAMnrc, for the modified 120-leaf Millennium MLC a new phase space data at Z=52cm is produces. The MLC is modified both in leaf thickness and material composition. EGSgui code generates 521ICRU library for tungsten alloys. DOSXYZnrc with the new phase space evaluates the dose distribution in a water phantom of 60×60×20 cm3 with voxel size of 4×4×2 mm3. Using DOSXYZnrc dose distributions for open beam and closed beam as well as the leakages definition, end leakage, average leakage and physical penumbra are evaluated. Results: A new MLC with improved dosimetric parameters is proposed. The physical penumbra for proposed MLC is 4.7mm compared to 5.16 mm for Millennium. Average leakage in our design is reduced to 1.16% compared to 1.73% for Millennium, the end leaf leakage suggested design is also reduced to 4.86% compared to 7.26% of Millennium. Conclusion: The results show that the proposed MLC with enhanced dosimetric parameters could improve the conformity of treatment planning.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-D-201-03: During-Treatment Delivery Monitoring System for TomoTherapy

Purpose: Multiple error pathways can lead to delivery errors during the treatment course that cannot be caught with pre-treatment QA. While in vivo solutions are being developed for linacs, no such solution exists for tomotherapy. The purpose of this study is to develop a near real-time system for tomotherapy that can monitor the delivery and dose accumulation process during the treatment-delivery, which enable the user to assess the impact of delivery variations and/or errors and to interrupt the treatment if necessary. Methods: A program running on a tomotherapy planning station fetches the raw DAS data during treatment. Exit detector data is extracted as well as output, gantry angle, and other machine parameters. For each sample, the MLC open-close state is determined. The delivered plan is compared with the original plan via a Monte Carlo dose engine which transports fluence deviations from a pre-treatment Monte Carlo run. A report containing the difference in fluence, dose and DVH statistics is created in html format. This process is repeated until the treatment is completed. Results: Since we only need to compute the dose for the difference in fluence for a few projections each time, dose with 2% statistical uncertainty can be computed in less than 1 second on a 4-core cpu. However, the current bottleneck in this near real-time system is the repeated fetching and processing the growing DAS data file throughout the delivery. The frame rate drops from 10Hz at the beginning of treatment to 5Hz after 3 minutes and to 2Hz after 10 minutes. Conclusion: A during-treatment delivery monitor system has been built to monitor tomotherapy treatments. The system improves patient safety by allowing operators to assess the delivery variations and errors during treatment delivery and adopt appropriate actions.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

A pencil beam dose calculation model for CyberKnife system

Purpose: CyberKnife system is initially equipped with fixed circular cones for stereotactic radiosurgery. Two dose calculation algorithms, Ray-Tracing and Monte Carlo, are available in the supplied treatment planning system. A multileaf collimator system was recently introduced in the latest generation of system, capable of arbitrarily shaped treatment field. The purpose of this study is to develop a model based dose calculation algorithm to better handle the lateral scatter in an irregularly shaped small field for the CyberKnife system. Methods: A pencil beam dose calculation algorithm widely used in linac based treatment planning system was modified. The kernel parameters and intensity profile were systematically determined by fitting to the commissioning data. The model was tuned using only a subset of measured data (4 out of 12 cones) and applied to all fixed circular cones for evaluation. The root mean square (RMS) of the difference between the measured and calculated tissue-phantom-ratios (TPRs) and off-center-ratio (OCR) was compared. Three cone size correction techniques were developed to better fit the OCRs at the penumbra region, which are further evaluated by the output factors (OFs). The pencil beam model was further validated against measurement data on the variable dodecagon-shaped Iris collimators and a half-beam blocked field. Comparison with Ray-Tracing and Monte Carlo methods was also performed on a lung SBRT case. Results: The RMS between the measured and calculated TPRs is 0.7% averaged for all cones, with the descending region at 0.5%. The RMSs of OCR at infield and outfield regions are both at 0.5%. The distance to agreement (DTA) at the OCR penumbra region is 0.2 mm. All three cone size correction models achieve the same improvement in OCR agreement, with the effective source shift model (SSM) preferred, due to their ability to predict more accurately the OF variations with the source to axis distance (SAD). In noncircular field validation, the pencil beam calculated results agreed well with the film measurement of both Iris collimators and the half-beam blocked field, fared much better than the Ray-Tracing calculation. Conclusions: The authors have developed a pencil beam dose calculation model for the CyberKnife system. The dose calculation accuracy is better than the standard linac based system because the model parameters were specifically tuned to the CyberKnife system and geometry correction factors. The model handles better the lateral scatter and has the potential to be used for the irregularly shaped fields. Comprehensive validations on MLC equipped system are necessary for its clinical implementation. It is reasonably fast enough to be used during plan optimization.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2017

Multi-scale calculation based on dual domain material point method combined with molecular dynamics

This dissertation combines the dual domain material point method (DDMP) with molecular dynamics (MD) in an attempt to create a multi-scale numerical method to simulate materials undergoing large deformations with high strain rates. In these types of problems, the material is often in a thermodynamically non-equilibrium state, and conventional constitutive relations are often not available. In this method, the closure quantities, such as stress, at each material point are calculated from a MD simulation of a group of atoms surrounding the material point. Rather than restricting the multi-scale simulation in a small spatial region, such as phase interfaces, or crack tips, this multi-scale method can be used to consider non-equilibrium thermodynamic e ects in a macroscopic domain. This method takes advantage that the material points only communicate with mesh nodes, not among themselves; therefore MD simulations for material points can be performed independently in parallel. First, using a one-dimensional shock problem as an example, the numerical properties of the original material point method (MPM), the generalized interpolation material point (GIMP) method, the convected particle domain interpolation (CPDI) method, and the DDMP method are investigated. Among these methods, only the DDMP method converges as the number of particles increases, but the large number of particles needed for convergence makes the method very expensive especially in our multi-scale method where we calculate stress in each material point using MD simulation. To improve DDMP, the sub-point method is introduced in this dissertation, which provides high quality numerical solutions with a very small number of particles. The multi-scale method based on DDMP with sub-points is successfully implemented for a one dimensional problem of shock wave propagation in a cerium crystal. The MD simulation to calculate stress in each material point is performed in GPU using CUDA to accelerate the computation. The numerical properties of the multiscale method are investigated as well as the results from this multi-scale calculation are compared of particles needed for convergence makes the method very expensive especially in our multi-scale method where we calculate stress in each material point using MD simulation. To improve DDMP, the sub-point method is introduced in this dissertation, which provides high quality numerical solutions with a very small number of particles. The multi-scale method based on DDMP with sub-points is successfully implemented for a one dimensional problem of shock wave propagation in a cerium crystal. The MD simulation to calculate stress in each material point is performed in GPU using CUDA to accelerate the computation. The numerical properties of the multiscale method are investigated as well as the results from this multi-scale calculation are compared with direct MD simulation results to demonstrate the feasibility of the method. Also, the multi-scale method is applied for a two dimensional problem of jet formation around copper notch under a strong impact.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2019

Multi-architecture Monte-Carlo (MC) simulation of soft coarse-grained polymeric materials: SOft coarse grained Monte-Carlo Acceleration (SOMA)

Not Available

Schneider, L. (ORCID:0000000239108217)↗

DOE OSTI2016

TH-CD-201-05: Characterization of a Novel Light-Collimating Tank Optical-CT System for 3D Dosimetry

Purpose: Comprehensive 3D dosimetry is highly desirable for advanced clinical QA, but costly optical readout techniques have hindered widespread implementation. Here, we present the first results from a cost-effective Integrated-lens Dry-tank Optical Scanner (IDOS), designed for convenient 3D dosimetry readout of radiochromic plastic dosimeters (e.g. PRESAGE). Methods: The scanner incorporates a novel transparent light-collimating tank, which collimates a point light source into parallel-ray CT geometry. The tank was designed using an in-house Monte-Carlo optical ray-tracing simulation, and was cast in polyurethane using a 3D printed mould. IDOS spatial accuracy was evaluated by imaging a set of custom optical phantoms, with comparison to x-ray CT images. IDOS dose measurement performance was assessed by imaging PRESAGE dosimeters irradiated with simple known dose distributions (e.g., 4 field box 6MV treatment with Varian Linac). Direct comparisons were made to images from our gold standard DLOS scanner and calculated dose distributions from a commissioned Eclipse planning system. Results: All optical CT images were reconstructed at 1mm isotropic resolution. Comparison of IDOS and x-ray CT images of the geometric phantom demonstrated excellent IDOS geometric accuracy (sub-mm) throughout the dosimeter. IDOS measured 3D dose distribution agreed well with prediction from Eclipse, with 95% gamma pass rate at 3%/3mm. Cross-scanner dose measurement gamma analysis shows >90% of pixels passing at 3%/3mm. Conclusion: The first prototype of the IDOS system has demonstrated promising performance, with accurate dosimeter readout and negligible spatial distortion. The use of optical simulations and 3D printing to create a light collimating-tank has dramatically increased convenience and reduced costs by removing the need for expensive lenses and large volumes of refractive matching fluids.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-T-673: Effects of Cardiac Induced Brain Pulsations On Proton Minibeams

Purpose: To quantify the dosimetric impact of internal motion within the brain on spatially modulated proton minibeam radiation therapy (pMRT) for small animal research. Methods: The peak-to-valley dose ratio (PVDR) is an essential dosimetric factor for pMRT. Motion of an animal brain caused by cardiac-induced pulsations (CIP) can impact dose deposition. For synchrotron generated high dose rate X-ray microbeams this effect is evaded due to the quasi-instantaneous delivery. By comparison, pMRT potentially suffers increased spread due to lower dose rates. However, for a given dose rate it is less susceptible to beam spread than microbeams, due to the spatial modulation being an order of magnitude larger. Monte Carlo simulations in TOPAS were used to model the beam spread for a 50.5MeV pMRT beam. Motion effects were simulated for a 50mm thick brass collimator with 0.3mm slit width and 1.0mm center-to-center spacing in a water phantom. The maximum motion in a rat brain due to CIP has been reported to be 0.06mm. Motion was simulated with a peak amplitude in the range 0–0.2mm. Results: The impact of 0.06mm peak motion was minimal and reduced the PVDR by about 1% at a depth of 10mm. For 0.2mm peak motion the PVDR was reduced by 16% at a depth of 10mm. Conclusion: For the pMRT beam the magnitude of cardiac-induced brain motion has minimal impact on the PVDR for the investigated collimator geometry. For more narrow beams the effect is likely to be larger. This indicates that delivery of pMRT to small animal brains should not be affected considerably by beamlines with linac compatible dose rates.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Cu–Ni Oxidation Mechanism Unveiled: A Machine Learning-Accelerated First-Principles and in Situ TEM Study

Here, the development of accurate methods for determining how alloy surfaces spontaneously restructure under reactive and corrosive environments is a key, long-standing, grand challenge in materials science. Using machine learning-accelerated density functional theory and rare-event methods, in conjunction with in situ environmental transmission electron microscopy (ETEM), we examine the interplay between surface reconstructions and preferential segregation tendencies of CuNi(100) surfaces under oxidation conditions. Our modeling approach predicts that oxygen-induced Ni segregation in CuNi alloys favors Cu(100)-O c(2 × 2) reconstruction and destabilizes the Cu(100)-O (2√2 × √2)R45° missing row reconstruction (MRR). In situ ETEM experiments validate these predictions and show Ni segregation followed by NiO nucleation and growth in regions without MRR, with secondary nucleation and growth of Cu 2 O in MRR regions. Our approach based on combining disparate computational components and in situ ETEM provides a holistic description of the oxidation mechanism in CuNi, which applies to other alloy systems.

36 MATERIALS SCIENCE↗

DOE OSTI2016

SU-F-T-371: Development of a Linac Monte Carlo Model to Calculate Surface Dose

Purpose: To generate and validate a linac Monte Carlo (MC) model for surface dose prediction. Methods: BEAMnrc V4-2.4.0 was used to model 6 and 18 MV photon beams for a commercially available linac. DOSXYZnrc V4-2.4.0 calculated 3D dose distributions in water. Percent depth dose (PDD) and beam profiles were extracted for comparison to measured data. Surface dose and at depths in the buildup region was measured with radiochromic film at 100 cm SSD for 4 × 4 cm{sup 2} and 10 × 10 cm{sup 2} collimator settings for open and MLC collimated fields. For the 6 MV beam, films were placed at depths ranging from 0.015 cm to 2 cm and for 18 MV, 0.015 cm to 3.5 cm in Solid Water™. Films were calibrated for both photon energies at their respective dmax. PDDs and profiles were extracted from the film and compared to the MC data. The MC model was adjusted to match measured PDD and profiles. Results: For the 6 MV beam, the mean error(ME) in PDD between film and MC for open fields was 1.9%, whereas it was 2.4% for MLC. For the 18 MV beam, the ME in PDD for open fields was 2% and was 3.5% for MLC. For the 6 MV beam, the average root mean square(RMS) deviation for the central 80% of the beam profile for open fields was 1.5%, whereas it was 1.6% for MLC. For the 18 MV beam, the maximum RMS for open fields was 3%, and was 3.1% for MLC. Conclusion: The MC model of a linac agreed to within 4% of film measurements for depths ranging from the surface to dmax. Therefore, the MC linac model can predict surface dose for clinical applications. Future work will focus on adjusting the linac MC model to reduce RMS error and improve accuracy.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2016

SU-G-BRB-10: New Generation of High Frame-Rate and High Spatial-Resolution EPID QA System for Full-Body MLC-Based Robotic Radiosurgery

Purpose: To systematically investigate an ultra-high spatial-resolution amorphous silicon flat-panel electronic portal imaging device (EPID) for MLC-based full-body robotic radiosurgery geometric and dosimetric quality assurance (QA). Methods: The high frame-rate and ultra-high spatial resolution EPID is an outstanding detector for measuring profiles, MLC-shaped radiosurgery field aperture verification, and small field dosimetry. A Monte Carlo based technique with a robotic linac specific response and calibration is developed to convert a raw EPID-measured image of a radiosurgery field into water-based dose distribution. The technique is applied to measure output factors and profiles for 6MV MLC-defined radiosurgery fields with various sizes ranging from 7.6mm×7.7mm to 100mm×100.1mm and the results are compared with the radiosurgery diode scan measurements in water tank. The EPID measured field sizes and the penumbra regions are analyzed to evaluate the MLC positioning accuracy. Results: For all MLC fields, the EPID measured output factors of MLC-shaped fields are in good agreement with the diode measurements. The mean output difference between the EPID and diode measurement is 0.05±0.87%. The max difference is −1.33% for 7.6mm×7.7mm field. The MLC field size derived from the EPID measurements are in good agreement comparing to the diode scan result. For crossline field sizes, the mean difference is −0.17mm±0.14mm with a maximum of −0.35mm for the 30.8mm×30.8mm field. For inline field sizes, the mean difference is +0.08mm±0.18mm with a maximum of +0.45mm for the 100mm×100.1mm field. The high resolution EPID is able to measure the whole radiation field, without the need to align the detector center perfectly at field center as diode or ion chamber measurement. The setup time is greatly reduced so that the whole process is possible for machine and patient-specific QA. Conclusion: The high spatial-resolution EPID is proved to be an accurate and efficient tool for QA of MLC-equipped robotic radiosurgery system.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-G-JeP2-09: Minimal Skin Dose Increase in Longitudinal Rotating Biplanar Linac-MR Systems: Examination of Radiation Energy and Flattening Filter Design

Purpose: To quantify increase in entrance skin-dose due to magnetic fields of the Alberta longitudinal linac-MR by examining the effect of radiation energy and flattening filter, using Monte Carlo calculations and accurate 3-D models of the magnetic field. Methods: The 3-D magnetic fields generated by the bi-planar Linac-MR are calculated with FEM using Opera-3D. BEAMnrc simulates the particle phase-space in the presence of the rapidly decaying fringe field of 0.5T MRI assembled with a Varian 600C linac with an isocentre distance of 130 cm for 6 MV and 10 MV beams. Skin doses are calculated at an average depth of 70 µm using DOSXYZnrc with varying SSDs and field sizes. Furthermore, flattening filters are reshaped to compensate for the significant drop in dose rate due to increased SAD of 130 cm and skin-doses are evaluated. Results: The confinement effect of the MRI fringe field on the contaminant electrons is minimal. For SSDs of 100 – 120 cm the increase in skin dose is ∼6% – 19% and ∼1% – 9% for the 6 and 10 MV beams, respectively. For 6MV, skin dose increases from ∼10.5% to 1.5%. for field-size increases of 5×5 cm2 to 20×20 cm2. For 10 MV, skin dose increases by ∼6% for a 5×5 cm2 field, and decreases by ∼1.5% for a 20×20 cm2 field. The reshaped flattening filter increases the dose rate from 355 MU/min to 529 MU/min (6 MV) or 604 MU/min (10 MV), while the skin-dose increases by only an additional ∼2.6% (all percent increases in skin dose are relative to Dmax). Conclusion: There is minimal increase in the entrance skin dose and minimal/no decrease in the dose rate of the Alberta longitudinal linac-MR system. There is even lower skin-dose increase at 10 MV. Funding: Alberta Innovates - Health Solutions (AIHS) Conflict of Interest: Fallone is a co-founder and CEO of MagnetTx Oncology Solutions (under discussions to license Alberta bi-planar linac MR for commercialization)

60 APPLIED LIFE SCIENCES↗