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At least 19 records

Radiation Dose Modeling for Niowave’s Accelerator Driven Uranium Target Assembly 3

Molybdenum-99 is a high-value radionuclide commonly used for medical purposes within the United States. The National Nuclear Security Administration (NNSA) seeks to reliably produce the radioisotope 99 Mo without the use of highly enriched uranium. NNSA’s Office of Material Management and Minimization (M3) provides funding and government laboratory expertise to private companies to expedite the production process domestically and currently funds designs that use low-enriched uranium or other 99 Mo production pathways. Several production designs are being explored across the industry, including uranium fission and photonuclear conversion of 100 Mo targets. Niowave Inc. seeks to produce 99 Mo via a high-energy electron accelerator that strikes a lead-bismuth eutectic target that ultimately produces a consistent neutron flux. The neutron flux then interacts in a subcritical reactor core configuration to produce fission in low-enriched or natural uranium targets. These fissionable targets are then processed to extract 99 Mo. The purpose of this work is to estimate the neutron and photon dose response across Niowave’s proposed facility for worker safety during operation. Owing to the size of the proposed Niowave facility and necessary shielding, unbiased Monte Carlo radiation transport is impractical, and variance reduction methods are required. This work focuses on the weight window variance reduction method to produce high confidence dose response results within a Monte Carlo radiation transport code. Specifically, an adjoint-informed weight window methodology was created to improve the dose response estimates for accelerator-driven subcritical reactor designs. This adjoint-informed methodology was implemented for Niowave’s proposed design and improved dose results at far-field locations across the facility. Acceptable dose rate contours for the proposed facility were generated across the facility and are presented in this work.

07 ISOTOPE AND RADIATION SOURCES↗

Ultraviolet radiation therapy and UVR dose models

Ultraviolet radiation (UVR) has been an effective treatment for a number of chronic skin disorders, and its ability to alleviate these conditions has been well documented. Although nonionizing, exposure to ultraviolet (UV) radiation is still damaging to deoxyribonucleic acid integrity, and has a number of unpleasant side effects ranging from erythema (sunburn) to carcinogenesis. As the conditions treated with this therapy tend to be chronic, exposures are repeated and can be high, increasing the lifetime probability of an adverse event or mutagenic effect. Despite the potential detrimental effects, quantitative ultraviolet dosimetry for phototherapy is an underdeveloped area and better dosimetry would allow clinicians to maximize biological effect whilst minimizing the repercussions of overexposure. This review gives a history and insight into the current state of UVR phototherapy, including an overview of biological effects of UVR, a discussion of UVR production, illness treated by this modality, cabin design and the clinical implementation of phototherapy, as well as clinical dose estimation techniques. Several dose models for ultraviolet phototherapy are also examined, and the need for an accurate computational dose estimation method in ultraviolet phototherapy is discussed.

60 APPLIED LIFE SCIENCES↗

SU-D-16A-03: A Radiation Pneumonitis Dose-Response Model Incorporating Non- Local Radiation-Induced Bystander Effect

Purpose: Dose-response models that can reliably predict radiation pneumonitis (RP) to guide radiation therapy (RT) for lung cancer presently do not exist. A model is proposed that incorporates non-local radiationinduced bystander effect (RIBE). Methods: A single sigmoid response function, derived from published data for whole lung irradiation, relates RP probability to cumulative lung damage, regardless of fractionation scheme. Lung damage is assumed to be caused by direct local radiation damage, quantified via the linear-quadratic (LQ) model, and RIBE. Based on published data, RIBE is assumed to be activated when per-fraction dose rises above ∼0.6 Gy, but is constant with dose above that threshold. Integral RIBE damage is assumed proportional to lung volume irradiated above ∼0.6 Gy per fraction. Key model parameters include LQ α and β, and two RIBE parameters: the single-fraction probability δ of damage, and a proportionality parameter κ that relates the potential for RIBE damage to irradiated lung volume. All parameters are tentatively fitted from published data, the RIBE parameters from published RP rates for conventionally fractionated RT (CFRT) and stereotactic body RT (SBRT). Results: The model predicts dose-response curves that are consistent with clinical experience. It provides a tentative explanation for why V20 (33 fractions), V13 (20 fractions) and V5 (<10 fractions) are observed to be correlated with RP. It also provides a plausible explanation for the success of SBRT — RIBE damage increases with the number of fractions, so penalizes CFRT relative to SBRT. Conclusion: The proposed model is relatively simple, extrapolates from published data, plausibly explains several clinical observations, and produces dose-response curves that are consistent with clinical experience. While capable of elaboration, its ability to explain doseresponse experience with different fractionation schemes using a small number of assumptions and parameters is an advantage.

60 APPLIED LIFE SCIENCES↗

Validating a Dynamic PWR Safety and Security Model?

Nuclear power plants (NPPs) are assessed for safety and security using separate models that cannot capture how an attacker's decisions and a plant's response unfold together in real time, leaving regulators and operators without a complete picture of true plant vulnerability. Traditional probabilistic risk assessment (PRA) methods treat adversarial events as fixed initiators with predetermined outcomes, and are structurally incapable of representing the time-dependent interplay between physical security events, safety system response, and operator mitigative actions. At Idaho National Laboratory (INL), I contributed to the development and validation of Modeling and Analysis for Safety and Security using the Dynamic EMRALD Framework (MASS-DEF). Where static PRA relies on event-tree logic that cannot evolve mid-scenario, MASS-DEF couples a time-dependent dynamic PRA tool EMRALD (Event Modeling Risk Assessment using Linked Diagrams) with attack simulation software, allowing attacker behavior, plant system states, and operator actions to interact across time. My work focused on validating a general Pressurized Water Reactor (PWR) model. I traced model logic against PWR plant to identified errors in logic and confirm accuracy. I then built and tested attack scenarios against a general PWR model to verify that the model produced expected outcomes across all logical pathways. I also contributed a section to a related technical paper applying the same EMRALD platform to radiation dose modeling. Results show that MASS-DEF can quantitatively demonstrate that many plants exceed their regulatory security thresholds. This demonstrated margin provides a technically defensible basis for reducing the number of guards without compromising regulatory compliance. Physical security costs represent roughly 10% of annual operating budgets, making such reductions directly meaningful to INL's mission of sustaining existing commercial NPPs. This internship strengthened my understanding of nuclear systems, probabilistic modeling, and technical writing, and has solidified my pursuit of a career at a national laboratory.

98 - NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL↗

Radiation-Induced Leukemia at Doses Relevant to Radiation Therapy: Modeling Mechanisms and Estimating Risks

Because many cancer patients are diagnosed earlier and live longer than in the past, second cancers induced by radiation therapy have become a clinically significant issue. An earlier biologically based model that was designed to estimate risks of high-dose radiation induced solid cancers included initiation of stem cells to a premalignant state, inactivation of stem cells at high radiation doses, and proliferation of stem cells during cellular repopulation after inactivation. This earlier model predicted the risks of solid tumors induced by radiation therapy but overestimated the corresponding leukemia risks. Methods: To extend the model to radiation-induced leukemias, we analyzed in addition to cellular initiation, inactivation, and proliferation a repopulation mechanism specific to the hematopoietic system: long-range migration through the blood stream of hematopoietic stem cells (HSCs) from distant locations. Parameters for the model were derived from HSC biologic data in the literature and from leukemia risks among atomic bomb survivors v^ ho were subjected to much lower radiation doses. Results: Proliferating HSCs that migrate from sites distant from the high-dose region include few preleukemic HSCs, thus decreasing the high-dose leukemia risk. The extended model for leukemia provides risk estimates that are consistent with epidemiologic data for leukemia risk associated with radiation therapy over a wide dose range. For example, when applied to an earlier case-control study of 110000 women undergoing radiotherapy for uterine cancer, the model predicted an excess relative risk (ERR) of 1.9 for leukemia among women who received a large inhomogeneous fractionated external beam dose to the bone marrow (mean = 14.9 Gy), consistent with the measured ERR (2.0, 95% confidence interval [CI] = 0.2 to 6.4; from 3.6 cases expected and 11 cases observed). As a corresponding example for brachytherapy, the predicted ERR of 0.80 among women who received an inhomogeneous low-dose-rate dose to the bone marrow (mean = 2.5 Gy) was consistent with the measured ERR (0.62, 95% Cl =-0.2 to 1.9). Conclusions: An extended, biologically based model for leukemia that includes HSC initiation, inactivation, proliferation, and, uniquely for leukemia, long-range HSC migration predicts, %Kith reasonable accuracy, risks for radiationinduced leukemia associated with exposure to therapeutic doses of radiation.

Shuryak, Igor↗

Department of Energy Air Emissions Annual Report Oak Ridge Reservation, Oak Ridge, Tennessee 40 Code of Federal Regulations (CFR) 61, Subpart H Calendar Year 2016

As defined in the preamble of the final rule, the entire DOE facility on the Oak Ridge Reservation (ORR) must meet the 10 mrem/yr ED standard.1 In other words, the combined ED from all radiological air emission sources from Y-12 National Security Complex (Y-12 Complex), Oak Ridge National Laboratory (ORNL), East Tennessee Technology Park (ETTP), Oak Ridge Institute for Science and Education (ORISE) and any other DOE operation on the reservation must meet the 10 mrem/yr standard. Compliance with the standard is demonstrated through emission sampling, monitoring, calculations and radiation dose modeling in accordance with approved EPA methodologies and procedures. DOE estimates the ED to many individuals or receptor points in the vicinity of ORR, but it is the dose to the maximally exposed individual (MEI) that determines compliance with the standard.

54 ENVIRONMENTAL SCIENCES↗

Effect of Anatomical Modeling on Space Radiation Dose Estimates: A Comparison of Doses for NASA Phantoms and 5th, 50th, and 95th Percentile UF Hybrid Phantoms

The estimate of absorbed dose to individual organs of a space crewmember is affected by the geometry of the anatomical model of the astronaut used in the radiation transport calculation. For astronaut dosimetry, NASA currently uses the computerized anatomical male (CAM) and computerized anatomical female (CAF) stylized phantoms to represent astronauts in its operational radiation dose analyses. These phantoms are available in one size and in two body positions. In contrast, the UF Hybrid Adult Male and Female (UFHADM and UFHADF) phantoms have organ shapes based on actual CT data. The surfaces of these phantoms are defined by non-uniform rational B-spline surfaces, and are thus flexible in terms of body morphometry and extremity positioning. In this study, UFHADM and UFHADF are scaled to dimensions corresponding to 5th, 50th, and 95th percentile (PCTL) male and female astronauts. A ray-tracing program is written in Visual Basic 2008, which is then used to create areal density maps for dose points corresponding to various organs within the phantoms. The areal density maps, along with appropriate space radiation spectra, are input into the NASA program couplet HZETRN/BRYNTRN, and organ doses are calculated. The areal density maps selected tissues and organs of the 5th, 50th, and 95th PCTL male and female phantoms are presented and compared. In addition, the organ doses for the 5th, 50th, and 95th PCTL male and female phantoms are presented and compared to organ doses for CAM and CAF.

Bahadori, A.↗

TU-C-18A-01: Models of Risk From Low-Dose Radiation Exposures: What Does the Evidence Say?

At dose levels of (approximately) 500 mSv or more, increased cancer incidence and mortality have been clearly demonstrated. However, at the low doses of radiation used in medical imaging, the relationship between dose and cancer risk is not well established. As such, assumptions about the shape of the dose-response curve are made. These assumptions, or risk models, are used to estimate potential long term effects. Common models include 1) the linear non-threshold (LNT) model, 2) threshold models with either a linear or curvilinear dose response above the threshold, and 3) a hormetic model, where the risk is initially decreased below background levels before increasing. The choice of model used when making radiation risk or protection calculations and decisions can have significant implications on public policy and health care decisions. However, the ongoing debate about which risk model best describes the dose-response relationship at low doses of radiation makes informed decision making difficult. This symposium will review the two fundamental approaches to determining the risk associated with low doses of ionizing radiation, namely radiation epidemiology and radiation biology. The strengths and limitations of each approach will be reviewed, the results of recent studies presented, and the appropriateness of different risk models for various real world scenarios discussed. Examples of well-designed and poorly-designed studies will be provided to assist medical physicists in 1) critically evaluating publications in the field and 2) communicating accurate information to medical professionals, patients, and members of the general public. Equipped with the best information that radiation epidemiology and radiation biology can currently provide, and an understanding of the limitations of such information, individuals and organizations will be able to make more informed decisions regarding questions such as 1) how much shielding to install at medical facilities, 2) at what dose level are risk vs. benefit discussions with patients appropriate, 3) at what dose level should we tell a pregnant woman that the baby’s health risk from a prenatal radiation exposure is “significant”, 4) is informed consent needed for patients undergoing medical imaging, and 5) at what dose level is evacuation appropriate after a radiological accident. Examples of the tremendous impact that choosing different risks models can have on the answers to these types of questions will be given.A moderated panel discussion will allow audience members to pose questions to the faculty members, each of whom is an established expert in his respective discipline. Learning Objectives: Understand the fundamental principles, strengths and limitations of radiation epidemiology and radiation biology for determining the risk from exposures to low doses of ionizing radiation Become familiar with common models of risk used to describe the dose-response relationship at low dose levels Learn to identify strengths and weaknesses in studies designed to measure the effect of low doses of ionizing radiation Understand the implications of different risk models on public policy and health care decisions.

60 APPLIED LIFE SCIENCES↗

Low-dose radiation cancer susceptibility models

These and studies including CC and DO genetically diverse mouse resources are crucial for identifying genes that drive radiation-induced health effects and individual susceptibilities. This information together with fundamental mechanistic studies will permit more biologically realistic mathematical models to be developed to extend risk evaluation to dose levels below which direct human data are unavailable and will provide regulatory agencies, such as DOE, with the necessary data to develop accurate regulatory standards for exposure to low dose radiation.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Models for Total-Dose Radiation Effects in Non-Volatile Memory

The objective of this work is to develop models to predict radiation effects in non- volatile memory: flash memory and ferroelectric RAM. In flash memory experiments have found that the internal high-voltage generators (charge pumps) are the most sensitive to radiation damage. Models are presented for radiation effects in charge pumps that demonstrate the experimental results. Floating gate models are developed for the memory cell in two types of flash memory devices by Intel and Samsung. These models utilize Fowler-Nordheim tunneling and hot electron injection to charge and erase the floating gate. Erase times are calculated from the models and compared with experimental results for different radiation doses. FRAM is less sensitive to radiation than flash memory, but measurements show that above 100 Krad FRAM suffers from a large increase in leakage current. A model for this effect is developed which compares closely with the measurements.

97 MATHEMATICS AND COMPUTING↗

Model calculations of the radiation dose and LET spectra on LDEF and comparisons with flight data

Ionizing radiation environment models, a 3-D spacecraft mass model, and radiation transport codes have been used to predict the radiation dose and linear energy transfer (LET) spectra measured at various locations on the LDEF satellite. The predictions are compared with thermoluminescent dosimeter measurements of the trapped proton and electron doses and with LET spectra measured by plastic nuclear track detectors. The predicted vs observed comparisons indicate some of the uncertainties of present ionizing radiation environment models for low Earth-orbit missions.

LDEF Project↗

A Primer on Dose-Response Data Modeling in Radiation Therapy

An overview of common approaches used to assess a dose response for radiation therapy–associated endpoints is presented, using lung toxicity data sets analyzed as a part of the High Dose per Fraction, Hypofractionated Treatment Effects in the Clinic effort as an example. Each component presented (eg, data-driven analysis, dose-response analysis, and calculating uncertainties on model prediction) is addressed using established approaches. Specifically, the maximum likelihood method was used to calculate best parameter values of the commonly used logistic model, the profile-likelihood to calculate confidence intervals on model parameters, and the likelihood ratio to determine whether the observed data fit is statistically significant. The bootstrap method was used to calculate confidence intervals for model predictions. Correlated behavior of model parameters and implication for interpreting dose response are discussed.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Modular and Stochastic Approaches to Molecular Pathway Models of ATM, TGF beta, and WNT Signaling

Deterministic pathway models that describe the biochemical interactions of a group of related proteins, their complexes, activation through kinase, etc. are often the basis for many systems biology models. Low dose radiation effects present a unique set of challenges to these models including the importance of stochastic effects due to the nature of radiation tracks and small number of molecules activated, and the search for infrequent events that contribute to cancer risks. We have been studying models of the ATM, TGF -Smad and WNT signaling pathways with the goal of applying pathway models to the investigation of low dose radiation cancer risks. Modeling challenges include introduction of stochastic models of radiation tracks, their relationships to more than one substrate species that perturb pathways, and the identification of a representative set of enzymes that act on the dominant substrates. Because several pathways are activated concurrently by radiation the development of modular pathway approach is of interest.

Cucinotta, Francis A.↗

Can the Equivalent Sphere Model Approximate Organ Doses in Space Radiation Environments?

In space radiation calculations it is often useful to calculate the dose or dose equivalent in blood-forming organs (BFO). the skin or the eye. It has been customary to use a 5cm equivalent sphere to approximate the BFO dose. However previous studies have shown that a 5cm sphere gives conservative dose values for BFO. In this study we use a deterministic radiation transport with the Computerized Anatomical Man model to investigate whether the equivalent sphere model can approximate organ doses in space radiation environments. We find that for galactic cosmic rays environments the equivalent sphere model with an organ-specific constant radius parameter works well for the BFO dose equivalent and marginally well for the BFO dose and the dose equivalent of the eye or the skin. For solar particle events the radius parameters for the organ dose equivalent increase with the shielding thickness, and the model works marginally for BFO but is unacceptable for the eye or the skin The ranges of the radius parameters are also shown and the BFO radius parameters are found to be significantly larger than 5 cm in all eases.

Zi-Wei, Lin↗

Impact of Fractionation and Dose in a Multivariate Model for Radiation-Induced Chest Wall Pain

Purpose: To determine the role of patient/tumor characteristics, radiation dose, and fractionation using the linear-quadratic (LQ) model to predict stereotactic body radiation therapy–induced grade ≥2 chest wall pain (CWP2) in a larger series and develop clinically useful constraints for patients treated with different fraction numbers. Methods and Materials: A total of 316 lung tumors in 295 patients were treated with stereotactic body radiation therapy in 3 to 5 fractions to 39 to 60 Gy. Absolute dose–absolute volume chest wall (CW) histograms were acquired. The raw dose-volume histograms (α/β = ∞ Gy) were converted via the LQ model to equivalent doses in 2-Gy fractions (normalized total dose, NTD) with α/β from 0 to 25 Gy in 0.1-Gy steps. The Cox proportional hazards (CPH) model was used in univariate and multivariate models to identify and assess CWP2 exposed to a given physical and NTD. Results: The median follow-up was 15.4 months, and the median time to development of CWP2 was 7.4 months. On a univariate CPH model, prescription dose, prescription dose per fraction, number of fractions, D83cc, distance of tumor to CW, and body mass index were all statistically significant for the development of CWP2. Linear-quadratic correction improved the CPH model significance over the physical dose. The best-fit α/β was 2.1 Gy, and the physical dose (α/β = ∞ Gy) was outside the upper 95% confidence limit. With α/β = 2.1 Gy, V{sub NTD99Gy} was most significant, with median V{sub NTD99Gy} = 31.5 cm{sup 3} (hazard ratio 3.87, P<.001). Conclusion: There were several predictive factors for the development of CWP2. The LQ-adjusted doses using the best-fit α/β = 2.1 Gy is a better predictor of CWP2 than the physical dose. To aid dosimetrists, we have calculated the physical dose equivalent corresponding to V{sub NTD99Gy} = 31.5 cm{sup 3} for the 3- to 5-fraction groups.

62 RADIOLOGY AND NUCLEAR MEDICINE↗