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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Evidence Report: Risk of Radiation Carcinogenesis

As noted by Durante and Cucinotta (2008), cancer risk caused by exposure to space radiation is now generally considered a main hindrance to interplanetary travel for the following reasons: large uncertainties are associated with the projected cancer risk estimates; no simple and effective countermeasures are available, and significant uncertainties prevent scientists from determining the effectiveness of countermeasures. Optimizing operational parameters such as the length of space missions, crew selection for age and sex, or applying mitigation measures such as radiation shielding or use of biological countermeasures can be used to reduce risk, but these procedures have inherent limitations and are clouded by uncertainties. Space radiation is comprised of high energy protons, neutrons and high charge (Z) and energy (E) nuclei (HZE). The ionization patterns and resulting biological insults of these particles in molecules, cells, and tissues are distinct from typical terrestrial radiation, which is largely X-rays and gamma-rays, and generally characterized as low linear energy transfer (LET) radiation. Galactic cosmic rays (GCR) are comprised mostly of highly energetic protons with a small component of high charge and energy (HZE) nuclei. Prominent HZE nuclei include He, C, O, Ne, Mg, Si, and Fe. GCR ions have median energies near 1 GeV/n, and energies as high as 10 GeV/n make important contributions to the total exposure. Ionizing radiation is a well known carcinogen on Earth (BEIR 2006). The risks of cancer from X-rays and gamma-rays have been established at doses above 50 mSv (5 rem), although there are important uncertainties and on-going scientific debate about cancer risk at lower doses and at low dose rates (<50 mSv/h). The relationship between the early biological effects of HZE nuclei and the probability of cancer in humans is poorly understood, and it is this missing knowledge that leads to significant uncertainties in projecting cancer risks during space exploration (Cucinotta and Durante 2006; Durante and Cucinotta 2008).

Huff, Janice↗
DOE OSTI2023

Lithium-Ion Battery Diagnostics Using Electrochemical Impedance via Machine-Learning

Diagnosing battery states such as health, state-of-charge, or temperature is crucial for ensuring the safety and reliability of electrochemical energy storage systems. While some states, such as temperature, may be measured using cheap sensors, accurate diagnosis of battery health metrics usually requires time-consuming performance measurements, making them infeasible for use in real-world operation. These health metrics can be measured during lab-testing and then estimated on-line using predictive life models or via state observer algorithms such as Kalman filters, but these predictive methods should be supplemented by actual measurement of battery health whenever possible to ensure reliability. Rapid measurement of battery health may be done by various types of fast diagnostic techniques such as electrochemical impedance spectroscopy (EIS), which can be performed in only a few minutes and require only a fraction of the energy and power needed for a full charge and discharge measurement. But there is a substantial challenge for estimating battery health using EIS data, as EIS is sensitive to cell temperature, state-of-charge, current, and resting time in addition to health. Thus, utilizing EIS data to predict battery capacity requires correcting for all these additional variables, a task that is extremely difficult to handle analytically. This talk utilizes machine-learning methods to estimate the effectiveness of battery capacity prediction from EIS data, leveraging a data set of hundreds of EIS measurements recorded at varying temperature and state-of-charge throughout a 500-day aging study of 32 commercial, large-format NMC-Graphite lithium-ion batteries. Using EIS as input to machine-learning models is complicated by the nonlinear response of impedance to battery health, temperature, and state-of-charge, as well as the collinearity between the impedance response at neighboring frequencies, which can easily lead to overfit models. To train robust models, features from EIS data need to be extracted from the data or some subset of critical frequencies selected. Many approaches for extracting and selecting features from EIS data from electrochemical analysis and machine-learning fields were identified for analysis: using the entire raw spectra; selection of one, two, or many frequencies from the entire spectra; selecting interesting points from the EIS measurement using domain knowledge; fitting EIS with an equivalent-circuit model; calculating statistics on the raw impedance values; and reducing the dimensionality of the data using unsupervised linear (principal component analysis) and non-linear (uniform manifold approximation and projection) methods. These approaches were rigorously compared using a machine-learning pipeline approach, training linear, Gaussian process, and random forest regression models and quantifying performance using cross-validation as well as a held-out test set. An artificial neural network model trained on the raw spectra was also tested. Promising pipelines were fine-tuned via Bayesian hyperparameter optimization using cross-validation loss and training with class-specific weights to counter data set imbalance. The most reliable method for utilizing impedance in this work was the selection of two optimal frequencies through an exhaustive search, resulting in about 2% mean absolute error on test data for both Gaussian process and random forest model architectures. Interrogation of a variety of models reveals critical frequencies of 100 Hz and 103 Hz for this data set, though the optimal set of frequencies is not necessarily intuitive, i.e., the best performing models are not simply those that use impedance at frequencies that have the highest correlation to the relative discharge capacity. The best performing model is an ensemble model, which is able to predict battery capacity with 1.9% mean absolute error for unseen cells using impedance recorded at a variety of temperatures and states-of-charge.

battery↗
DOE OSTI2024

Detecting Important Drivers of Gridded Population Modeling With Machine Learning

High-resolution population datasets have been lever-aged across a broad swath of domains, such as climate change, public policy, humanitarian aid, and rescue operations, among others. Machine learning methods were adopted to generate high-resolution or gridded population estimates by using various geospatial input features such as buildings, roads, and nighttime lights. In this study, we evaluate the importance of population features using Random Forest models across three levels of analysis, utilizing permutation measures. Our research aims to address key questions to enhance our understanding of high-resolution population modeling, such as: Are certain features globally (10 countries collectively) more important than others? Do optimal features vary by country? Within each country, do feature importance differ across administrative units? What similarities exist in feature importance at the global, country, and administrative unit levels? To answer these questions, we leverage the Kneedle algorithm to automate the selection of optimum features. We find that there are patterns displayed by features across spatial boundaries, evidenced by the same feature being the most important indicator of population across 7 of the 10 countries modeled. Our findings indicate that while important features may vary across geographies, certain features consistently hold greater importance than others agnostic of geography.

Lebakula, Viswadeep [ORNL] (ORCID:0000000152935914↗
DOE OSTI2019

DCIS with Microinvasion: Is It In Situ or Invasive Disease?

Background: Ductal carcinoma in situ (DCIS) with microinvasion (DCISM) can be challenging in balancing the risks of overtreatment versus undertreatment. We compared DCISM, pure DCIS, and small volume (T1a) invasive ductal carcinoma (IDC) as related to histopathology, treatment patterns, and survival outcomes. Methods: Women ages 18–90 years who underwent breast surgery for DCIS, DCISM, or T1a IDC were selected from the SEER Database (2004–2015). Multivariate logistic regression and Cox proportional hazards models were used to estimate the association of diagnosis with treatment and survival, respectively. Results: A total of 134,569 women were identified: 3.2% DCISM, 70.9% DCIS, and 25.9% with T1a IDC. Compared with invasive disease, DCISM was less likely to be ER+ or PR+ and more likely to be HER2+. After adjustment, DCIS and invasive patients were less likely to undergo mastectomy than DCISM patients (DCIS: OR 0.53, 95% CI 0.49–0.56; invasive: OR 0.86, CI 0.81–0.92). For those undergoing lumpectomy, the likelihood of receiving radiation was similar for DCISM and invasive patients but lower for DCIS patients (OR 0.57, CI 0.52–0.63). After adjustment, breast-cancer-specific survival was significantly different between DCISM and the other two groups (DCIS: HR 0.59, CI 0.43–0.8; invasive: HR 1.43, CI 1.04–1.96). However, overall survival was not significantly different between DCISM and invasive disease, whereas patients with DCIS had improved OS (HR 0.83, CI 0.75–0.93). Conclusions: Although DCISM is a distinct entity, current treatment patterns and prognosis are comparable to those with small volume IDC. These findings may help providers counsel patients and determine appropriate treatment plans.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Gulf of Mexico Miocene CO2 Site Characterization Mega Transect

The project Gulf of Mexico Miocene CO2 Site Characterization Mega Transect is one of 9 site characterization projects that were implemented as part of ARRA (American Recovery and Reinvestment Act). Data from this project was used to improve resolution of data in NATCARB in the area of study. Data related to this study has already been incorporated in NATCARB Atlas. The University of Texas at Austin study focused on (1) collecting high-resolution, 3-D (HR3D) seismic datasets of the shallow geologic section to evaluate the capacity of potential reservoirs and the sealing capacity of the confining system, and (2) producing a regional CO2 atlas of Miocene age units of the upper Texas coast submerged lands (southeast Texas). The goal of the study was to evaluate the capability of the Miocene age geologic section of Texas submerged lands to permanently store large volumes of anthropogenic CO2. The geographic locations of three HR3D, “P-Cable” seismic surveys collected in the near-shore waters of southeast Texas offers a vertical and horizontal view (data “cube”) example from the second survey. The dataset's high quality allowed for defining recognizable geologic morphologies (shapes) and possible fluid content, which are important for determining an area’s prospects for geologic storage. The regional CO2 atlas of Miocene age units highlights several topics, including: (1) a regional analyses of petroleum systems as analogs for CO2 storage; (2) petrography, petrology, and extent of confining systems of the Miocene section; (3) static capacity estimate; and (4) examples of characterization methodologies of prospect areas. The HR3D datasets and regional analyses within the CO2 atlas of the offshore Texas Miocene provide a sound basis for a future generation of specific CO2 prospects in the study area.

.las↗
DOE OSTI2018

Status Report - Fiberboard Properties and Degradation Rates for Storage of the 9975 Shipping Package in KAC

Thermal, mechanical and physical properties have been measured on fiberboard samples following accelerated aging for up to approximately 12 years. The aging environments include elevated temperature up to 250 ºF (the maximum allowed service temperature for fiberboard in 9975 packages) and elevated humidity. The results from this testing have been analyzed, and aging models fit to the data. Correlations relating several properties (thermal conductivity, energy absorption, weight, dimensions and density) to their rate of change in potential storage environments have been developed. Combined with an estimate of the actual conditions the fiberboard experiences in KAC, these models allow development of service life predictions.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

SAVY-4000 Corrosion Evaluation Plan

Nuclear material packages, with few exceptions, outside of an approved engineered contamination barrier must meet packaging, surveillance, and testing requirements designed to protect workers from airborne contamination per Department of Energy (DOE) Manual 441.1-1, Nuclear Material Packaging. The SAVY-4000 containers were developed at Los Alamos National Laboratory (LANL) in conjunction with Nuclear Filter Technology Inc. (NFT Inc.) as a general purpose vented manually-compliant container system for staging and storage of plutonium for LANL and the DOE complex. The SAVY-4000 containers have a 316L stainless steel containment barrier, which was selected based on its corrosion resistant properties. These containers were approved for use in 2014 with a five-year design life; LANL requested and DOE has approved lifetime extension from 5 to 15 years. The 10-year lifetime extension was proposed as a conservative recommendation based on the corrosion observations for the metal components in surveillance and results from laboratory studies. Extensive accelerated aging studies have been done on the SAVY-4000 O-ring with very little evidence of significant degradation when subjected to aggressive elevated temperature and radiation conditions. Therefore, our current conservative lifetime estimate for the O-ring and the filter is 40 years at 80°C. Additional work is ongoing in a phased approach to further extend the design life of the Manual compliant SAVY-4000 storage container; the limiting component for further life extension is still the 316L containment barrier.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Epidemiologic Factors Supporting Triage of Infected Dog Patients Admitted to a Veterinary Hospital Biological Isolation and Containment Unit

The teaching hospital of the Faculty of Veterinary Medicine at the University of Lisbon hosts a Biological Isolation and Containment Unit (BICU) for the hospitalization of both confirmed and suspected animals of an infectious disease. This study targets the BICU dog population to identify and characterize the most frequent infectious diseases recorded in a 7-year period. Several epidemiologic factors were analyzed for their significance to triage infected cases. During the study period, 534 dogs were admitted, of which 263 (49.3%) had a confirmed infectious disease diagnosis: parvovirosis (49.4%; n = 130); leptospirosis (21.7%; n = 57); multidrug-resistant (MDR) bacterial infection; (10.6%; n = 28), and canine distemper (9.9%; n = 26). Several potential risk factors for these diseases were identified: age under 2 years old (p < 0.001), incomplete vaccination for parvovirosis (p < 0.001), age ≥ 10 years old (p < 0.001), and the presence of concomitant disorders for MDR-infected cases (p = 0.03). Logistic regression models were constructed to classify cases and controls. The sensitivity and specificity estimates were very high (>0.83) for parvovirosis, MDR, and distemper infections. A lower sensitivity (0.77) was obtained for identifying cases with leptospirosis. In conclusion, infectious diseases are frequent, hence, it is essential to decrease their occurrence through effective preventive measures such as vaccination. The constructed logistic models can also help in triaging admitted dogs with a potential infectious disease.

Machado, Inês Cunha (ORCID:0000000238151125)↗
DOE OSTI2016

THE ISLANDS PROJECT. I. ANDROMEDA XVI, AN EXTREMELY LOW MASS GALAXY NOT QUENCHED BY REIONIZATION

Based on data aquired in 13 orbits of Hubble Space Telescope time, we present a detailed evolutionary history of the M31 dSph satellite Andromeda XVI, including its lifetime star formation history (SFH), the spatial distribution of its stellar populations, and the properties of its variable stars. And XVI is characterized by prolonged star formation activity from the oldest epochs until star formation was quenched ∼6 Gyr ago, and, notably, only half of the mass in stars of And XVI was in place 10 Gyr ago. And XVI appears to be a low-mass galaxy for which the early quenching by either reionization or starburst feedback seems highly unlikely, and thus it is most likely due to an environmental effect (e.g., an interaction), possibly connected to a late infall in the densest regions of the Local Group. Studying the SFH as a function of galactocentric radius, we detect a mild gradient in the SFH: the star formation activity between 6 and 8 Gyr ago is significantly stronger in the central regions than in the external regions, although the quenching age appears to be the same, within 1 Gyr. We also report the discovery of nine RR Lyrae (RRL) stars, eight of which belong to And XVI. The RRL stars allow a new estimate of the distance, (m − M){sub 0} = 23.72 ± 0.09 mag, which is marginally larger than previous estimates based on the tip of the red giant branch.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1977

Relative crater production rates on planets

The relative numbers of impacts on different planets, estimated from the dynamical histories of planetesimals in specified orbits (Wetherill, 1975), are converted by a described procedure to crater production rates. Conversions are dependent on impact velocity and surface gravity. Crater retention ages can then be derived from the ratio of the crater density to the crater production rate. The data indicate that the terrestrial planets have crater production rates within a factor ten of each other. As an example, for the case of Mars, least-squares fits to crater-count data suggest an average age of 0.3 to 3 billion years for two types of channels. The age of Olympus Mons is discussed, and the effect of Tharsis volcanism on channel formation is considered.

Hartmann, W. K.↗
NASA NTRS1984

Thermomechanical evolution of oceanic fracture zones

To explain the topographic and gravitational signals of fracture zones (FZs), a realistic model is developed and compared with Seasat altimeter data across three major FZs. The model is based on the thermal, subsidence, and mechanical models of the oceanic lithosphere. The model is used to calculate the FZ topography and the evolution of the geoid signature across a FZ. When lithospheric flexure is included, the model explains the persistence of sharp FZ geoid steps on old seafloor as well as the asymmetry of the geoid steps across major FZs. The model does not explain the disappearance of the thermal part of the FZ geoid signature. The model profiles are used to access the various techniques for estimating the overall geoid offsets across FZs. It is shown that steps may be underestimated by as much as 50 percent. These predictions, if correct, will force reinterpretation of published geoid height versus age data derived from altimeter profiles across FZs.

Sandwell, D. T.↗
NASA NTRS2021

Improved Constraints for the XUV Luminosity Evolution of Trappist-1

We re-examine the XUV luminosity evolution of TRAPPIST-1 utilizing new observational constraints of the current stellar parameters (XUV and bolometric luminosity) from multi-epoch X-ray/UV photometry. Following the formalism presented on Fleming et al. (2020), we infer that TRAPPIST-1maintained a saturated XUV luminosity, relative to the bolometric luminosity, of log10(LXUV/Lbol)=−3.03+0.25−0.23at early times for a period of tsat= 3.14+2.22−1.46Gyr. After the saturation phase, we find LXUV decayed over time by an exponential rate ofβXUV=−1.17+0.27−0.28. Compared to our inferred age of the system, age = 7.96+1.78−1.87Gyr, our result for tsat suggests that there is only a∼4% chance thatTRAPPIST-1 still remains in the saturated phase today, which is significantly lower than the previous estimate of 40%. Despite this reduction in tsat, our results remain consistent in the conclusion that the TRAPPIST-1 planets likely received an extreme amount XUV energy—an estimated integrated XUV energy of∼1030−1032erg over the star’s lifetime—that is∼15% lower than the original result.

Stellar evolution↗
DOE OSTI2017

Power Plant Retirements: Trends and Possible Drivers

This paper synthesizes available data on historical and planned power plant retirements. Specifically, we present data on historical generation capacity additions and retirements over time, and the types of plants recently retired and planned for retirement. We then present data on the age of plants that have recently retired or that have plans to retire. We also review the characteristics of plants that recently retired or plan to retire vs. those that continue to operate, focusing on plant size, age, heat rate, and SO 2 emissions. Finally, we show the level of recent thermal plant retirements on a regional basis and correlate those data with a subset of possible factors that may be contributing to retirement decisions. This basic data synthesis cannot be used to precisely estimate the relative magnitude of retirement drivers. Nor do we explore every possible driver for retirement decisions. Moreover, future retirement decisions may be influenced by different factors than those that have affected past decisions. Nonetheless, it is clear that recently retired plants are relatively old, and that plants with stated planned retirement dates are—on average—no younger. We observe that retired plants are smaller, older, less efficient, and more polluting than operating plants. Based on simple correlation graphics, the strongest predictors of regional retirement differences appear to include SO 2 emissions rates (for coal), planning reserve margins (for all thermal units), variations in load growth or contraction (for all thermal units), and the age of older thermal plans (for all thermal units). Additional apparent predictors of regional retirements include the ratio of coal to gas prices and delivered natural gas prices. Other factors appear to have played lesser roles, including the penetration variable renewable energy (VRE), recent non-VRE capacity additions, and whether the region hosts an ISO/RTO.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Lung Cancer in the Mayak Workers Cohort: Risk Estimation and Uncertainty Analysis

The workers at the Mayak nuclear facility near Ozyorsk, Russia are a primary source of information about exposure to radiation at low-dose rates, since they were subject to protracted exposures to external gamma rays and to internal exposures from plutonium inhalation. Here we re-examine lung cancer mortality rates and assess the effects of external gamma and internal plutonium exposures using recently developed Monte Carlo dosimetry systems. Using individual lagged mean annual lung doses computed from the dose realizations, we fit excess relative risk (ERR) models to the lung cancer mortality data for the Mayak Workers Cohort using risk-modeling software. We then used the corrected information matrix (CIM) approach to widen the confidence intervals of ERR by taking into account the uncertainty in doses represented by multiple realizations from the Monte Carlo dosimetry systems. Findings of this work revealed that there were 930 lung cancer deaths during follow-up. Plutonium lung doses (but not gamma doses) were generally higher in the new dosimetry systems than those used in the previous analysis. This led to a reduction in the risk per unit dose compared to prior estimates. The estimated ERR/Gy for external gamma-ray exposure was 0.19 (95% CI: 0.07 to 0.31) for both sexes combined, while the ERR/Gy for internal exposures based on mean plutonium doses were 3.5 (95% CI: 2.3 to 4.6) and 8.9 (95% CI: 3.4 to 14) for males and females at attained age 60. Accounting for uncertainty in dose had little effect on the confidence intervals for the ERR associated with gamma-ray exposure, but had a marked impact on confidence intervals, particularly the upper bounds, for the effect of plutonium exposure [adjusted 95% CIs: 1.5 to 8.9 for males and 2.7 to 28 for females]. In conclusion, lung cancer rates increased significantly with both external gamma-ray and internal plutonium exposures. Accounting for the effects of dose uncertainty markedly increased the width of the confidence intervals for the plutonium dose response but had little impact on the external gamma dose effect estimate. Adjusting risk estimate confidence intervals using CIM provides a solution to the important problem of dose uncertainty. This work demonstrates, for the first time, that it is possible and practical to use our recently developed CIM method to make such adjustments in a large cohort study.

uncertainty, radiation risk estimation, Mayak Prod↗
DOE OSTI2018

Expected condition of concrete exposed to radiation at age 80 years of reactor operation

This report is intended to provide access to information generated by LPI, Inc. on behalf of the US Department of Energy (DOE), Office of Nuclear Energy, Light Water Reactor Sustainability (LWRS) Program and the Electric Power Research Institute (EPRI) in 2013. Specifically, estimates of the fast neutron fluence at 80 years of operation on the outer surface of the concrete biological shield (CBS) of US Nuclear Power Plants (NPPs) operating in 2013 and an estimate of the effects of gamma radiation on the temperature on the biological shield were determined.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

THE LEECH EXOPLANET IMAGING SURVEY: ORBIT AND COMPONENT MASSES OF THE INTERMEDIATE-AGE, LATE-TYPE BINARY NO UMa

We present high-resolution Large Binocular Telescope LBTI/LMIRcam images of the spectroscopic and astrometric binary NO UMa obtained as part of the LBT Interferometer Exozodi Exoplanet Common Hunt exoplanet imaging survey. Our H-, K{sub s}-, and L′-band observations resolve the system at angular separations <0.″09. The components exhibit significant orbital motion over a span of ∼7 months. We combine our imaging data with archival images, published speckle interferometry measurements, and existing spectroscopic velocity data to solve the full orbital solution and estimate component masses. The masses of the K2.0 ± 0.5 primary and K6.5 ± 0.5 secondary are 0.83 ± 0.02 M{sub ⊙} and 0.64 ± 0.02 M{sub ⊙}, respectively. We also derive a system distance of d = 25.87 ± 0.02 pc and revise the Galactic kinematics of NO UMa. Our revised Galactic kinematics confirm NO UMa as a nuclear member of the ∼500 Myr old Ursa Major moving group, and it is thus a mass and age benchmark. We compare the masses of the NO UMa binary components to those predicted by five sets of stellar evolution models at the age of the Ursa Major group. We find excellent agreement between our measured masses and model predictions with little systematic scatter between the models. NO UMa joins the short list of nearby, bright, late-type binaries having known ages and fully characterized orbits.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Radiation-Related Risk of Cancers of the Upper Digestive Tract among Japanese Atomic Bomb Survivors

As a follow-up to the comprehensive work on solid cancer incidence in the Life Span Study (LSS) cohort of atomic bomb survivors between 1958 and 1998, we report here on updated radiation risk estimates for upper digestive tract cancers. In this study, we added 11 years of follow-up (1958–2009), used improved radiation dose estimates, considered effects of smoking and alcohol consumption and performed dose-response analyses by anatomical sub-site. In examining 52 years'worth of data, we ascertained the occurrence of 394 oral cavity/pharyngeal cancers, 486 esophageal cancers and 5,661 stomach cancers among 105,444 subjects. The radiation risk for oral cavity/pharyngeal cancer, other than salivary gland, was elevated but not significantly so. In contrast, salivary gland cancer exhibited a strong linear dose response with excess relative risk (ERR) of 2.54 per Gy [95% confidence interval (CI): 0.69 to 6.1]. Radiation risk decreased considerably with increasing age at time of exposure (–66% per decade, 95% CI: –88% to –32%). The dose response for esophageal cancer was statistically significant under a simple linear, linear-quadratic and quadratic model. Both linear-quadratic and quadratic models described the data better than a simple linear model and, of the two, the quadratic model showed a marginally better fit based on the Akaike Information Criteria. Sex difference in linear ERRs was not statistically significant; however, when the dose-response shape was allowed to vary by sex, statistically significant curvature was found among males, with no evidence of quadratic departure from linearity among females. The risk for stomach cancer increased significantly with dose and there was little evidence for quadratic departure from linearity among either males or females. The sex-averaged ERR at age 70 was 0.33 per Gy (95% CI: 0.20 to 0.47). The ERR decreased significantly (–1.93 power of attained age, 95% CI: –2.94 to –0.82) with increasing attained age, but not with age at exposure, and was higher in females than males (P = 0.02). Our results are largely consistent with the results of prior LSS analyses. Salivary gland, esophageal and stomach cancers continue to show significant increases in risk with radiation dose. Adjustment for lifestyle factors had almost no impact on the radiation effect estimates. Further follow-up of the LSS cohort is important to clarify the nature of radiation effects for upper digestive tract cancers, especially for oral cavity/pharyngeal and esophageal cancers, for which detailed investigation for dose-response shape could not be conducted due to the small number of cases.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Long-Term Update of NRG Oncology RTOG 0319: A Phase 1 and 2 Trial to Evaluate 3-Dimensional Conformal Radiation Therapy Confined to the Region of the Lumpectomy Cavity for Stage I and II Breast Carcinoma

Purpose: NRG Oncology RTOG 0319 was the first cooperative group trial in the United States to evaluate 3-dimensional conformal radiation therapy (3D-CRT) accelerated partial breast irradiation (APBI). This report updates secondary endpoints of toxicity and efficacy. Methods and Materials: Patients with stage I or II invasive breast cancer (tumor size ≤3 cm, ≤3 positive lymph nodes, negative margins) were eligible for 3D-CRT APBI: 38.5 Gy in 10 twice-daily fractions. Patient characteristics and treatment details have previously been reported. Adverse events were graded with CTCAE v3.0 (National Cancer Institute Common Terminology Criteria for Adverse Events version 3.0). This analysis updates the rates of ipsilateral breast recurrence (IBR), contralateral breast recurrence, ipsilateral node recurrence (INR), metastatic sites (distant metastases [DM]), mastectomy, disease-free survival, mastectomy-free survival, and overall survival. Results: Of 58 enrolled patients, 52 were eligible, with a median age of 61 years; 94% had stage I cancer and 83% had estrogen receptor positive disease. The median follow-up period was 8 years (minimum-maximum, 1.7-9.0 years). The 7-year estimate of isolated IBR (no DM) was 5.9%. The 7-year estimates of all IBRs, INR, mastectomy rate, and DM were 7.7%, 5.8%, 7.7%, and 7.7%, respectively. All 4 IBRs were invasive, of which 3 had a component within the planning target volume. The patterns of failure were as follows: 3 IBRs, 1 INR, 2 DM, 1 INR plus DM, and 1 IBR plus INR plus DM. The 7-year estimates of mastectomy-free survival, disease-free survival, and overall survival were 71.2%, 71.2%, and 78.8%, respectively. Thirteen patients died: 3 of breast cancer and 10 of other causes. Grade 3 (G3) treatment-related adverse events were reported by 4 patients (7.7%). No G3 pain or pulmonary or cardiac toxicities were reported. Conclusions: This phase 1 and 2 trial of 3D-CRT APBI continues to show durable tumor control and minimal G3 toxicity, comparable to other APBI techniques. Mature phase 3 results will determine the appropriateness and limitations of this noninvasive APBI technique.

62 RADIOLOGY AND NUCLEAR MEDICINE↗