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DOE OSTI2022

2021 NIRT Mini Drill (After Action Report)

During the summer and fall of 2021, several functional area drills were held that focused on exercising Consequence Management’s (CM) ability to extract and use data from RadResponder for the purpose of answering intermediate-phase questions presented as technical inject requests for information (RFI) in Sandia National Laboratories (SNL) Consequence Management Operational System (COSMOS) software. The scenario chosen was that of Northern Lights 2016 (NL16) which was a large-scale nuclear power plant (NPP) release exercise in the state of Minnesota. The NL16 data was extracted from the Radiological Assessment and Monitoring System (RAMS) event where it was created and was reformatted for implanting to a new RadResponder event. Next, the beta-version of a laboratory sample data simulator was used to generate more sample data that was injected to the event. Five “mini-drills” were devised with each prompt defined by a data-based need. For each drill, a team of assessment and NARAC scientists worked the problem using the drill prompt and the available data in RadResponder. The teams held a kickoff meeting, had several days to work the problem, and then reported their results as well as observations in a hotwash. Several areas for improvement in both the software and process were identified during the course of these drills. This report will document the process of addressing each RFI and the discovered gaps in both software capability and methodology so that they can be considered for future development and investment by the CM and NIRT programs.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2019

Radiological Performance Modeling: Platform Comparison

Zapadnoe Uranium Mill Tailings Site, Pridneprovsky Chemical Plant Ukraine: Two exposure scenarios were utilized to develop performance assessment models in GoldSim and NORMALYSA. The first scenario is an onsite worker exposed to radioactivity through external ground irradiation as well as radon and radioactive dust inhalation. The second being an offsite Resident 300 years after institutional control exposed through the ingestion of garden vegetables irrigated by contaminated ground water, ingestion of fish from Konoplyanka River, and agricultural activities in contaminated garden. NORMALYSA utilizes a modular interface to connect extensive pre-created modules to develop contaminant transport and risk assessment models for safety assessments and performance assessments at NORM and legacy sites. Developed by Facilia AB, the program was tested with the creation of the Zapadnoe model under the International Atomic Energy Agency MODARIA Il Working Group 1 (WG1). Default values are provided for input parameters where site specific data and distributions lack. Probabilistic simulations and inputs are limited to parameters with assigned Gaussian probability functions. Similar results for transient worker inhalation dose were found in comparison with the Zapadnoe GoldSim model. However, the NORMALYSA model has results larger by an order of magnitude for external radiation in the transient worker and for aquatic food ingestion, inhalation, and garden food ingestion to the resident. Performance Assessment Modeling: Radiological performance models promote good management and support in remediation and environmental decision making by optimizing radioactive waste disposal site performance. a performance assessment model of the Zapadnoe uranium mill tailings site and a model for calculating authorized limits at Los Alamos National Laboratory are created to demonstrate and highlight the respective capabilities of three modeling platforms: GoldSim, NORMALYSA, and RESRAD-Onsite. GoldSim is a general-purpose modeling platform with the ability to simulate site-specific FT radionuclide transport and risk assessment using a graphical interface to create and link elements that act as indivisible building blocks of the model. The Zapadnoe performance assessment model created in GoldSim is composed of input parameters collected from site specific parameters from WG1 as well as standard assumptions seen in the Generic PA Model from Neptune and Company. The multivariate Zapadnoe simulation contains both deterministic and probabilistic simulation capabilities with the ability to quantitatively represent the uncertainty and associated risks of the site via the Monte Carlo simulation method. Model parameters, documentation, and assumptions are built directly into the model creating a transparent, reproducible, and more purposeful site specific model. To demonstrate this, an ingestion of water pathway was included in addition to the exposure pathways included in the NORMALYSA model. GoldSim offers a wide variety of probability distributions to choose from as well as many tools to visualize the uncertainty of the models and explore which pathways and radionuclides dominate dose. In contrast to the NORMALYSA model, the GoldSim model uses dynamic simulation to calculate tritium concentrations. Authorized limits support the evaluation of radiological health effects from radionuclides present in bulk contaminated soil in order to assist in the process of clearing land for release under different uses. Calculations of authorized limits in RESRAD-Onsite and GoldSim models support the evaluation for 15 radionuclides using a residential exposure scenario, indoor and outdoor inhalation of dust and vapor phase radionuclides (tritium), incidental soil ingestion, and ingestion grown fruits and Vegetables. RESRAD-Onsite, developed by Argonne National Laboratory is a dedicated computer code for calculating radiation doses and cancer risks to an individual located on top of radioactively contaminated soils. It can also be used to provide guidelines for deriving radionuclide soil levels corresponding to a specific dose criterion. The menu driven user interface facilitates selection of radionuclides and soil concentrations, as well as defines parameter values related to materials, environmental factors, and exposure pathways. The program contains radionuclide-specific data such as dose conversion factors and risk coefficients, as well as soil-water partition coefficients and transfer factors for biotic media. The GoldSim model successfully emulates the RESRAD-Onsite code using identical radiological decay and ingrowth factors, radiation dose conversion factors, and other input parameters. DE EEDE ETS Each model supports dynamic modeling of radionuclide ingrowth and decay over time, and integrate this capability with the transport of radionuclides in the environment via processes such as advection and/or diffusion in fluids, or within porous solid media, The applicability of each program is heavily dependent on project context. In the context of developing Authorized Limits, RESRAD-Onsite may be a more desirable option as it was developed for this particular application. For simple disposal or legacy sites or sites that do not need site-specific model structure, NORMALYSA may be a desirable modeling platform, GoldSim can be used to model any problem for which RESRAD or NORMALYSA is applicable, but its strength lies in its flexibility, analytical, and probabilistic capabilities.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

4D ML reconstruction as a tool for volumetric PET-based treatment verification in ion beam radiotherapy

Purpose: An innovative strategy to improve the sensitivity of positron emission tomography (PET)-based treatment verification in ion beam radiotherapy is proposed. Methods: Low counting statistics PET images acquired during or shortly after the treatment (Measured PET) and a Monte Carlo estimate of the same PET images derived from the treatment plan (Expected PET) are considered as two frames of a 4D dataset. A 4D maximum likelihood reconstruction strategy was adapted to iteratively estimate the annihilation events distribution in a reference frame and the deformation motion fields that map it in the Expected PET and Measured PET frames. The outputs generated by the proposed strategy are as follows: (1) an estimate of the Measured PET with an image quality comparable to the Expected PET and (2) an estimate of the motion field mapping Expected PET to Measured PET. The details of the algorithm are presented and the strategy is preliminarily tested on analytically simulated datasets. Results: The algorithm demonstrates (1) robustness against noise, even in the worst conditions where 1.5 × 10{sup 4} true coincidences and a random fraction of 73% are simulated; (2) a proper sensitivity to different kind and grade of mismatches ranging between 1 and 10 mm; (3) robustness against bias due to incorrect washout modeling in the Monte Carlo simulation up to 1/3 of the original signal amplitude; and (4) an ability to describe the mismatch even in presence of complex annihilation distributions such as those induced by two perpendicular superimposed ion fields. Conclusions: The promising results obtained in this work suggest the applicability of the method as a quantification tool for PET-based treatment verification in ion beam radiotherapy. An extensive assessment of the proposed strategy on real treatment verification data is planned.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2023

Python Urban Deployment Model (PyUDM) v1.0.0

The Python Urban Deployment Model (PyUDM) is a simulation tool used to investigate networks of static radiation detectors in urban environments. PyUDM simulates traffic, stationary NaI gamma-ray detectors, and moving radioactive sources on simulated vehicles. The analyzed output of the simulations contain valuable insights into the performance of different configurations of urban radiological detector configurations such as their ability to detect sources moving through the environment. To accurately simulate radioactive material moving through urban environments, PyUDM combines Monte Carlo simulation tools, publicly available map and traffic data, and measured gamma-ray spectra from urban environments.

Rofors, Emil↗
DOE OSTI2018

Using EPA's Risk Assessment Tools for Superfund When Addressing Removal Actions and Late-Phase Response to Terrorist Attacks - 18228

EPA's Office of Superfund Remediation and Technology Innovation (OSRTI) has three internet based calculators, or risk assessment models, for developing risk based Preliminary Remediation Goals (PRGs) for radioactively contaminated CERCLA sites. These PRG calculators are EPA's recommended methodology for developing risk-based concentrations for remedial actions for soil and water (PRG), inside buildings (BPRG), and outside hard surfaces (SPRG). EPA has three equivalent calculators for dose assessment, which are the Dose Compliance Concentration (DCC) calculator for soil and water, inside buildings (BDCC), and outside hard surfaces (SDCC). The three PRG calculators also include default PRG tables provided for each of the calculators showing concentrations corresponding to 1 x 10-6 when the calculators are run using all of their default parameters. This presentation will provide information on how users may employ these tools beyond their original intended uses in the remedial program, to develop risk based cleanup levels during the late-phase portion of an actual response after a Radiological Dispersal Device (RDD) or Improvised Nuclear Device (IND) terrorist attack or a major accident at a Nuclear Power Plant (NPP), or a simulation during an exercise of an RDD/IND/NPP event, they may want to run the calculator using more site-specific data. This presentation will provide information on how users may employ these tools beyond their original intended uses in the remedial program, and focus on some of the more conservative default parameters that are likely candidates for replacement by site-specific information. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

SU-E-I-49: Simulation Study for Removing Scatter Radiation in Cesium-Iodine Based Flat Panel Detector System

Purpose: This study aims to identify the feasibility of a novel cesium-iodine (CsI)-based flat-panel detector (FPD) for removing scatter radiation in diagnostic radiology. Methods: The indirect FPD comprises three layers: a substrate, scintillation, and thin-film-transistor (TFT) layer. The TFT layer has a matrix structure with pixels. There are ineffective dimensions on the TFT layer, such as the voltage and data lines; therefore, we devised a new FPD system having net-like lead in the substrate layer, matching the ineffective area, to block the scatter radiation so that only primary X-rays could reach the effective dimension.To evaluate the performance of this new FPD system, we conducted a Monte Carlo simulation using MCNPX 2.6.0 software. Scatter fractions (SFs) were acquired using no grid, a parallel grid (8:1 grid ratio), and the new system, and the performances were compared.Two systems having different thicknesses of lead in the substrate layer—10 and 20μm—were simulated. Additionally, we examined the effects of different pixel sizes (153×153 and 163×163μm) on the image quality, while keeping the effective area of pixels constant (143×143μm). Results: In case of 10μm lead, the SFs of the new system (∼11%) were lower than those of the other system (∼27% with no grid, ∼16% with parallel grid) at 40kV. However, as the tube voltage increased, the SF of new system (∼19%) was higher than that of parallel grid (∼18%) at 120kV. In the case of 20μm lead, the SFs of the new system were lower than those of the other systems at all ranges of the tube voltage (40–120kV). Conclusion: The novel CsI-based FPD system for removing scatter radiation is feasible for improving the image contrast but must be optimized with respect to the lead thickness, considering the system’s purposes and the ranges of the tube voltage in diagnostic radiology. This study was supported by a grant(K1422651) from Institute of Health Science, Korea University.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Sensitivity of the diagnostic radiological index of protection to procedural factors in fluoroscopy

Purpose: To evaluate the sensitivity of the diagnostic radiological index of protection (DRIP), used to quantify the protective value of radioprotective garments, to procedural factors in fluoroscopy in an effort to determine an appropriate set of scatter-mimicking primary beams to be used in measuring the DRIP. Methods: Monte Carlo simulations were performed to determine the shape of the scattered x-ray spectra incident on the operator in different clinical fluoroscopy scenarios, including interventional radiology and interventional cardiology (IC). Two clinical simulations studied the sensitivity of the scattered spectrum to gantry angle and patient size, while technical factors were varied according to measured automatic dose rate control (ADRC) data. Factorial simulations studied the sensitivity of the scattered spectrum to gantry angle, field of view, patient size, and beam quality for constant technical factors. Average energy (E{sub avg}) was the figure of merit used to condense fluence in each energy bin to a single numerical index. Results: Beam quality had the strongest influence on the scattered spectrum in fluoroscopy. Many procedural factors affect the scattered spectrum indirectly through their effect on primary beam quality through ADRC, e.g., gantry angle and patient size. Lateral C-arm rotation, common in IC, increased the energy of the scattered spectrum, regardless of the direction of rotation. The effect of patient size on scattered radiation depended on ADRC characteristics, patient size, and procedure type. Conclusions: The scattered spectrum striking the operator in fluoroscopy is most strongly influenced by primary beam quality, particularly kV. Use cases for protective garments should be classified by typical procedural primary beam qualities, which are governed by the ADRC according to the impacts of patient size, anatomical location, and gantry angle.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Validation of numerical simulations of activation by neutron flux - 15038

The knowledge of the radionuclide content of radioactive waste is of utmost importance for safety and waste management reasons. Numerical simulations are used at EDF-CIDEN to anticipate the dismantling and the radioactive waste management. The activation scheme by neutron flux developed at EDF-CIDEN comprises four steps. First of all, a 3 dimensional description of the reactor, the chemical composition of each structure, and the neutron sources at nominal power rating conditions are used as the input data to simulate the neutron propagation and to generate a 3 dimensional multi energy group neutron flux distribution in nominal power rating conditions. Secondly, this output data is used with the chemical compositions (including impurities) and the history of the operating conditions to calculate the radiological inventory for each structure. Thirdly, according to the radioactive inventory of each component or sub-component, a waste classification can be made; the classification criteria are based on the levels of radioactivity and radiotoxicity of 143 radionuclides. Finally, comparisons between the calculated radioactive inventories and the results of radio-chemical analyses can be made. These comparisons are made with regards to the activation of 'standard' chemical elements (meaning radionuclides being perfectly modeled with no uncertainty about the chemical concentrations). The results, linked with 'standard' chemical elements, can be used to validate the calculation scheme, including the neutron propagation, the neutron activation and all the other associated simplified assumptions (geometry, history of irradiation, etc). For steel, activation of 'Fe' is retained, and for stainless steel, activation of 'Fe' 'Ni' are retained. Overall, the feedback from Chooz A (Pressurized Water Reactor) shows that numerical simulations produce a slight overestimation of 'Fe-55' and 'Ni-63'. The results linked with minor chemical elements or impurities allowed us to validate the use of the average measured compositions. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Method for Real-Time Salt Aerosol Concentration and Size Measurements for Molten Salt Reactor Safety Assessments

Licensing a new nuclear reactor involves evaluating credible accident scenarios by developing models that simulate accident progression to predict possible outcomes and their impact on safety. The formation of radionuclide-bearing aerosols in the respirable size range can significantly affect dose consequence and threaten human health and is therefore a focus of nuclear reactor safety assessments. Recent reviews of the literature identified a lack of existing experimental data describing the mechanisms of formation and properties (size, concentration, and composition) of radionuclide-bearing aerosols that may be produced from molten salt reactor (MSR) facilities during postulated accident scenarios. Experiments on aerosol formation from molten salt systems are a high priority need that will support MSR licensing by indicating the radiological consequences of aerosol formation and providing the data required for model development and validation. The evolving conditions that occur during a MSR accident, such as a spill of molten fuel salt, may affect aerosol formation mechanisms and aerosol properties over time. There is a need to conduct experiments that simulate credible MSR accidents in a laboratory to generate aerosols with realistic characteristics and behaviors and a need to measure these aerosols in real time under accident-relevant conditions. This report describes the development of a method that can be used to quantify the size and concentration of salt aerosol particles that form from molten salt systems in real time. This method will be employed in future integral effects tests that are conducted at an engineering scale to simulate realistic MSR accidents and in future separate effects tests that will provide mechanistic insight into aerosol formation and properties to support process model development.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Multiscale Modeling Meets Machine Learning: What Can We Learn?

Machine learning is increasingly recognized as a promising technology in the biological, biomedical, and behavioral sciences. There can be no argument that this technique is incredibly successful in image recognition with immediate applications in diagnostics including electrophysiology, radiology, or pathology, where we have access to massive amounts of annotated data. However, machine learning often performs poorly in prognosis, especially when dealing with sparse data. This is a field where classical physics-based simulation seems to remain irreplaceable. In this review, we identify areas in the biomedical sciences where machine learning and multiscale modeling can mutually benefit from one another: Machine learning can integrate physics-based knowledge in the form of governing equations, boundary conditions, or constraints to manage ill-posted problems and robustly handle sparse and noisy data; multiscale modeling can integrate machine learn- ing to create surrogate models, identify system dynamics and parameters, analyze sensitivities, and quantify uncertainty to bridge the scales and understand the emergence of function. With a view towards applications in the life sciences, we discuss the state of the art of combining machine learning and multiscale modeling, identify applications and opportunities, raise open questions, and address potential challenges and limitations. We anticipate that it will stimulate discussion within the community of computational mechanics and reach out to other disciplines including mathematics, statistics, computer science, artificial intelligence, biomedicine, systems biology, and precision medicine to join forces towards creating robust and efficient models for biological systems.

machine learning, multiscale modeling, physics-bas↗
DOE OSTI2016

Parameterization of photon beam dosimetry for a linear accelerator

Purpose: In radiation therapy, accurate data acquisition of photon beam dosimetric quantities is important for (1) beam modeling data input into a treatment planning system (TPS), (2) comparing measured and TPS modeled data, (3) the quality assurance process of a linear accelerator’s (Linac) beam characteristics, (4) the establishment of a standard data set for comparison with other data, etcetera. Parameterization of the photon beam dosimetry creates a data set that is portable and easy to implement for different applications such as those previously mentioned. The aim of this study is to develop methods to parameterize photon beam dosimetric quantities, including percentage depth doses (PDDs), profiles, and total scatter output factors (S{sub cp}). Methods: S{sub cp}, PDDs, and profiles for different field sizes, depths, and energies were measured for a Linac using a cylindrical 3D water scanning system. All data were smoothed for the analysis and profile data were also centered, symmetrized, and geometrically scaled. The S{sub cp} data were analyzed using an exponential function. The inverse square factor was removed from the PDD data before modeling and the data were subsequently analyzed using exponential functions. For profile modeling, one halfside of the profile was divided into three regions described by exponential, sigmoid, and Gaussian equations. All of the analytical functions are field size, energy, depth, and, in the case of profiles, scan direction specific. The model’s parameters were determined using the minimal amount of measured data necessary. The model’s accuracy was evaluated via the calculation of absolute differences between the measured (processed) and calculated data in low gradient regions and distance-to-agreement analysis in high gradient regions. Finally, the results of dosimetric quantities obtained by the fitted models for a different machine were also assessed. Results: All of the differences in the PDDs’ buildup and the profiles’ penumbra regions were less than 2 and 0.5 mm, respectively. The differences in the low gradient regions were 0.20% ± 0.20% (<1% for all) and 0.50% ± 0.35% (<1% for all) for PDDs and profiles, respectively. For S{sub cp} data, all of the absolute differences were less than 0.5%. Conclusions: This novel analytical model with minimum measurement requirements was proved to accurately calculate PDDs, profiles, and S{sub cp} for different field sizes, depths, and energies.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2015

SU-E-T-560: Monte Carlo Simulation of the Neutron Radiation Field Around a Medical 18 MV Linac

Purpose: Today the majority of radiation therapy treatments are performed at medical electron linear accelerators (linacs). The accelerated electrons are used for the generation of bremsstrahlung photons. The use of higher electron respectively photon energies has some advantages over lower energies such as the longer dose build-up. However photons with energies higher than ∼7 MeV can additionally to the interaction with bound electrons undergo inelastic reactions with nuclei. These photonuclear reactions lead to the emission of fast neutrons which contaminate the primary photon field. The neutrons might penetrate through the collimators and deliver out-of-field dose to the patient. Furthermore the materials inside the linac head as well as the air inside the treatment room get activated which might deliver dose to the medical employees even when the linac is not in operation. A detailed knowledge of these effects is essential for adequate radiation protection of the employees and an optimal patient treatment. Methods: It is a common method to study the radiation fields of such linacs by means of Monte Carlo simulations. For the investigation of the effects caused by photonuclear reactions a typical linac in high energy mode (Varian Clinac 18 MV-X) as well as the surrounding bunker were modelled and simulated using the Monte Carlo code FLUKA which includes extensive nuclear reaction and neutron transport models additional to electron-photon transport as well as capabilities for a detailed study of effective dose distributions and activation yields. Results: Neutron spectra as well as neutron effective dose distributions within the bunker were obtained, reaching up to some mSv/Gy in the patient’s plane. The results are normalized per Gy in the depth dose maximum at 10×10 cm{sup 2} field size. Therefore an absolute interpretation is possible. Conclusion: The obtained data gives a better understanding of the photonuclear reaction caused effects.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2022

Detection of Marine Borne Radioactive Sources Report

This report describes a preliminary analysis on the utility of modern capabilities to localize radiological sources in marine environment. This study analyzed expected background sources and identified possible approaches based on modeling and simulation analyses. The effort culminated in the design and fabrication of validation experiments which provided favorable supporting data. The conclusions of this effort are not conclusive as to the viability of the approach nor is the underlining hypothesis discounted. Continuation of the experimental approach is recommended with a focus on open-water experimentation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

E-Area Low-Level Waste Facility GoldSim System Model

This report documents the development of the E-Area Low-Level Waste Facility (ELLWF) trench system model. The GoldSim® Monte Carlo simulation software is utilized to model the release and transport of radiological inventory disposed (both currently and in the future) within Engineered and Slit Trenches. This model is in support of the sensitivity and uncertainty analysis for the ELLWF Performance Assessment. The ELLWF system model utilizes a hybrid-approach to accurately describe the disposal system. The Hydrologic Evaluation of Landfill Performance model provides the infiltration data to both PORFLOW and GoldSim. PORFLOW is used to calibrate the GoldSim model to ensure confidence in the stochastic results. Finally, the concentrations from GoldSim transport simulations are fed into the SRNL Dose Toolkit to calculate dose impacts and assess plume interaction

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

Nuclear aircraft carrier inactivation - Execution of waste management initiatives - 15565

After 6 years of planning efforts, in June 2013, Newport News Shipbuilding (NNS) began the execution phase of the inactivation of the USS Enterprise. The USS Enterprise decommissioning involves implementation of a new approach to defueling aircraft carriers, utilizing new processes for defueling and shipment of spent nuclear fuel and waste. During planning for this complex endeavor, NNS developed several process improvement initiatives including streamlining waste management processes and technology insertion using modeling and simulation (M and S) capabilities. One of the new approaches involves the establishment of a Waste Packaging Area (WPA) onboard the ship. The process assists with maximizing waste loading and shipments directly from the ship. Another waste management initiative includes the NNS/ Waste Vendor teaming effort to facilitate more efficient loading and shipment of inactivation waste. With execution underway, these initiatives are being put to the test to see if they can withstand the rigors of day-to-day production. NNS has implemented the use of the Modeling and Simulation (M and S) technology. During the planning phase, the M and S 3D Spatial Arrangement Tool was utilized to determine the optimal equipment layout within the new M-290 facility used for spent fuel packaging and ship-out and to determine the appropriate shipping container placement on the ship to maximize waste loading. The M and S technology proved to be a beneficial application resulting in continued utilization through the execution phase of the carrier inactivation. NNS is currently expanding the M-290 Facility Model to provide a visual representation of the facility, its processes, resources, and variable parameters that can be utilized as a decision support tool through simulation of the spent fuel packaging and ship-out process through the facility's life-cycle. NNS is also expanding the application of the waste management model to effectively predict waste forecast. The simulation model is linked with the defueling schedule which captures the operational elements of the waste flow process. The model extrapolates the data to provide waste generation output to assess the most efficient and cost effective path for radiological waste shipments offsite. The ability to conduct waste forecasting allows streamlining of the waste management process in support of complex defueling operations. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

An evaluation of nearest neighbor averaging's improvements to the measurement sensitivity of wide-area radiological scanning instruments - 15560

Through the Sandia National Laboratories (SNL) New Mexico Small Business Assistance (NMSBA) program, Sandia worked with the Environmental Restoration Group (ERG) Inc. to verify and validate a novel algorithm used to determine the scanning Critical Level (Lc) and Minimum Detectable Concentration (MDC) (or Minimum Detectable Areal Activity) for the 102F scanning system. Through the use of Monte Carlo statistical simulations the algorithm mathematically demonstrates accuracy in determining the Lc and MDC when a nearest-neighbor averaging (NNA) technique was used. To empirically validate this approach, SNL prepared several spiked sources and ran a test with the ERG 102F instrument on a bare concrete floor known to have no radiological contamination other than background naturally occurring radioactive material (NORM). The tests conclude that the NNA technique increases the sensitivity (decreases the Lc and MDC) for high-density data maps that are obtained by scanning radiological survey instruments. It is further described in Sandia Laboratories document number SAND2014-16522. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Functional Data Analysis Applied to Modeling of Severe Acute Mucositis and Dysphagia Resulting From Head and Neck Radiation Therapy

Purpose: Current normal tissue complication probability modeling using logistic regression suffers from bias and high uncertainty in the presence of highly correlated radiation therapy (RT) dose data. This hinders robust estimates of dose-response associations and, hence, optimal normal tissue–sparing strategies from being elucidated. Using functional data analysis (FDA) to reduce the dimensionality of the dose data could overcome this limitation. Methods and Materials: FDA was applied to modeling of severe acute mucositis and dysphagia resulting from head and neck RT. Functional partial least squares regression (FPLS) and functional principal component analysis were used for dimensionality reduction of the dose-volume histogram data. The reduced dose data were input into functional logistic regression models (functional partial least squares–logistic regression [FPLS-LR] and functional principal component–logistic regression [FPC-LR]) along with clinical data. This approach was compared with penalized logistic regression (PLR) in terms of predictive performance and the significance of treatment covariate–response associations, assessed using bootstrapping. Results: The area under the receiver operating characteristic curve for the PLR, FPC-LR, and FPLS-LR models was 0.65, 0.69, and 0.67, respectively, for mucositis (internal validation) and 0.81, 0.83, and 0.83, respectively, for dysphagia (external validation). The calibration slopes/intercepts for the PLR, FPC-LR, and FPLS-LR models were 1.6/−0.67, 0.45/0.47, and 0.40/0.49, respectively, for mucositis (internal validation) and 2.5/−0.96, 0.79/−0.04, and 0.79/0.00, respectively, for dysphagia (external validation). The bootstrapped odds ratios indicated significant associations between RT dose and severe toxicity in the mucositis and dysphagia FDA models. Cisplatin was significantly associated with severe dysphagia in the FDA models. None of the covariates was significantly associated with severe toxicity in the PLR models. Dose levels greater than approximately 1.0 Gy/fraction were most strongly associated with severe acute mucositis and dysphagia in the FDA models. Conclusions: FPLS and functional principal component analysis marginally improved predictive performance compared with PLR and provided robust dose-response associations. FDA is recommended for use in normal tissue complication probability modeling.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

TU-E-201-03: Eye Lens Dosimetry in Radiotherapy Using Contact Lens-Shaped Applicator

Madan M. Rehani, Massachusetts General Hospital and Harvard Medical School, Boston Methods for Eye Lens Dosimetry and Studies On Lens Opacities with Interventionalists Radiation induced cataract is a major threat among staff working in interventional suites. Nearly 16 million interventional procedures are performed annually in USA. Recent studies by the principal investigator’s group, primarily among interventional cardiologists, on behalf of the International Atomic Energy Agency, show posterior subcapsular (PSC) changes in the eye lens in 38–53% of main operators and 21–45% of support staff. These changes have potential to lead to cataract in future years, as per information from A-Bomb survivors. The International Commission on Radiological Protection has reduced dose limit for staff by a factor of 7.5 (from 150 mSv/y to 20 mSv/y). With increasing emphasis on radiation induced cataracts and reduction in threshold dose for eye lens, there is a need to implement strategies for estimating eye lens dose. Unfortunately eye lens dosimetry is at infancy when it comes to routine application. Various approaches are being tried namely direct measurement using active or passive dosimeters kept close to eyes, retrospective estimations and lastly correlating patient dose in interventional procedures with staff eye dose. The talk will review all approaches available and ongoing active research in this area, as well as data from surveys done in Europe on status of eye dose monitoring in interventional radiology and nuclear medicine. The talk will provide update on how good is Hp(10) against Hp(3), estimations from CTDI values, Monte Carlo based simulations and current status of eye lens dosimetry in USA and Europe. The cataract risk among patients is in CT examinations of the head. Since radiation induced cataract predominantly occurs in posterior sub-capsular (PSC) region and is thus distinguishable from age or drug related cataracts and is also preventable, actions on awareness can lead to avoidance or even prevention. Learning Objectives: To understand recent changes in eye lens dose limits and thresholds for tissue reactions To understand different approaches to dose estimation for eye lens To learn about challenges in eye lens opacities among staff in interventional fluoroscopy Di Zhang, Toshiba America Medical Systems, Tustin, CA, USA Eye lens radiation dose from brain perfusion CT exams CT perfusion imaging requires repeatedly exposing one location of the head to monitor the uptake and washout of iodinated contrast. The accumulated radiation dose to the eye lens can be high, leading to concerns about potential radiation injury from these scans. CTDIvol assumes continuous z coverage and can overestimate eye lens dose in CT perfusion scans where the table do not increment. The radiation dose to the eye lens from clinical CT brain perfusion studies can be estimated using Monte Carlo simulation methods on voxelized patient models. MDCT scanners from four major manufacturers were simulated and the eye lens doses were estimated using the AAPM posted clinical protocols. They were also compared to CTDIvol values to evaluate the overestimation from CTDIvol. The efficacy of eye lens dose reduction techniques such as tilting the gantry and moving the scan location away from the eyelens were also investigated. Eye lens dose ranged from 81 mGy to 279 mGy, depending on the scanner and protocol used. It is between 59% and 63% of the CTDIvol values reported by the scanners. The eye lens dose is significantly reduced when the eye lenses were not directly irradiated. CTDIvol should not be interpreted as patient dose; this study has shown it to overestimate dose to the eye lens. These results may be used to provide more accurate estimates of actual dose to ensure that protocols are operated safely below thresholds. Tilting the gantry or moving the scanning region further away from the eyes are effective for reducing lens dose in clinical practice. These actions should be considered when they are consistent with the clinical task and patient anatomy. Learning Objectives: To become familiar with method of eye dose estimation for patient in specific situation of brain perfusion CT To become familiar with level of eye lens radiation doses in patients undergoing brain perfusion MDCT To understand methods for reducing eye lens dose to patient Jong Min Park, Department of Radiation Oncology, Seoul National University Hospital, Seoul, Korea Eye lens dosimetry in radiotherapy using contact lens-shaped applicator Dose calculation accuracy of commercial treatment planning systems is relatively low at shallow depths. Therefore, in-vivo measurements are often performed in the clinic to verify delivered doses to eye lens which are located at shallow depth. Current in-vivo dosimetry for eye lens during radiotherapy is generally performed with small in-vivo dosimeters on the surface of patient eyelid. Since this procedure potentially contains considerable uncertainty, a contact lens-shaped applicator made of acrylic (lens applicator) was developed for in-vivo measurements of eye lens dose during radiotherapy to reduce uncertainty. The lens applicator allows the insertion of commercially available metal oxide semiconductor field effect transistor (MOSFET) dosimeters. Computed tomography (CT) images of an anthropomorphic phantom with and without the lens applicator were acquired. A total of 20 VMAT plans were delivered to an anthropomorphic phantom and the doses with the lens applicator and the doses at the surface of the eyelid were measured using both micro and standard MOSFET dosimeters. The differences in measured dose at the surface of the eyelid from the calculated lens dose were acquired. The differences between the measured and the calculated doses at the lens applicator, as well as the differences between the measured and the calculated doses at the surface of the eyelid were acquired. The statistical significance of the differences was analyzed. The average difference between the measured and the calculated dose with the lens applicator was 16.8 % ± 10.4 % with a micro MOSFET dosimeter and 16.6 % ± 10.9% with a standard MOSFET dosimeter. The average difference without the lens applicator was 35.9% ± 41.5% with micro MOSFET dosimeter and 42.9% ± 52.2% with standard MOSFET dosimeter. The maximum difference with micro MOSFET dosimeter was 46% with the applicator and 188.4% without the applicator. For the standard MOSFET dosimeter, the maximum difference was 44.4% with the applicator and 246.4% without the applicator. The lens applicator allowed reduction of the differences between the calculated and the measured dose during in-vivo measurement for the eye lens as compared to in-vivo measurement at the surface of the eyelid. Learning Objectives: To understand limitations of dose calculation with commercial treatment planning system for eye lens during radiotherapy To learn about current in-vivo dosimetry methods for eye lens in the clinic To understand limitations of in-vivo dosimetry for eye lens during radiotherapy Di Zhang is an employee of Toshiba America Medical Systems.

60 APPLIED LIFE SCIENCES↗