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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

TU-H-CAMPUS-JeP3-02: Automated Dose Accumulation and Dose Accuracy Assessment for Online Or Offline Adaptive Replanning

Purpose: With introduction of high-quality treatment imaging during radiation therapy (RT) delivery, e.g., MR-Linac, adaptive replanning of either online or offline becomes appealing. Dose accumulation of delivered fractions, a prerequisite for the adaptive replanning, can be cumbersome and inaccurate. The purpose of this work is to develop an automated process to accumulate daily doses and to assess the dose accumulation accuracy voxel-by-voxel for adaptive replanning. Methods: The process includes the following main steps: 1) reconstructing daily dose for each delivered fraction with a treatment planning system (Monaco, Elekta) based on the daily images using machine delivery log file and considering patient repositioning if applicable, 2) overlaying the daily dose to the planning image based on deformable image registering (DIR) (ADMIRE, Elekta), 3) assessing voxel dose deformation accuracy based on deformation field using predetermined criteria, and 4) outputting accumulated dose and dose-accuracy volume histograms and parameters. Daily CTs acquired using a CT-on-rails during routine CT-guided RT for sample patients with head and neck and prostate cancers were used to test the process. Results: Daily and accumulated doses (dose-volume histograms, etc) along with their accuracies (dose-accuracy volume histogram) can be robustly generated using the proposed process. The test data for a head and neck cancer case shows that the gross tumor volume decreased by 20% towards the end of treatment course, and the parotid gland mean dose increased by 10%. Such information would trigger adaptive replanning for the subsequent fractions. The voxel-based accuracy in the accumulated dose showed that errors in accumulated dose near rigid structures were small. Conclusion: A procedure as well as necessary tools to automatically accumulate daily dose and assess dose accumulation accuracy is developed and is useful for adaptive replanning. Partially supported by Elekta, Inc.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

The Poisson tensor completion parametric estimator

We introduce the Poisson tensor completion (PTC) estimator that exploits inter-sample relationships to compute a low-rank Poisson tensor decomposition of the frequency histogram for samples of a multivariate distribution. Our crucial observation is that the histogram bins are an instance of a space partitioning of counts and thus can be identified with a spatial non-homogeneous Poisson process. The Poisson tensor decomposition leads to a completion of the mean measure over all bins—including those containing few to no samples—and leads to our proposed estimator. A Poisson tensor decomposition models the underlying distribution of the count data and guarantees non-negative estimated values obviating the need for additional constraints to ensure non-negativity. Furthermore, we demonstrate that our PTC estimator is a substantial improvement over standard histogram-based estimators for sub-Gaussian probability distributions because of the concentration of norm phenomenon.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Laser-Induced Fluorescence for Monitoring Environmental Contamination and Stress in the Moss Thuidium plicatile

The ability to detect, measure, and locate the source of contaminants, especially heavy metals and radionuclides, is of ongoing interest. A common tool for contaminant identification and bioremediation is vegetation that can accumulate and indicate recent and historic pollution. However, large-scale sampling can be costly and labor-intensive. Hence, non-invasive in-situ techniques such as laser-induced fluorescence (LIF) are becoming useful and effective ways to observe the health of plants through the excitation of organic molecules, e.g., chlorophyll. The technique presented utilizes images collected of LIF in moss to identify different metals and environmental stressors. Analysis through image processing of LIF response was key to identifying Cu, Zn, Pb, and a mixture of the metals at nmol/cm 2 levels. Specifically, the RGB values from each image were used to create density histograms of each color channel’s relative pixel abundance at each decimal code value. These histograms were then used to compare color shifts linked to the successful identification of contaminated moss samples. Photoperiod and extraneous environmental stressors had minimal impact on the histogram color shift compared to metals and presented with a response that differentiated them from metal contamination.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

The Herschel Orion Protostar Survey: Luminosity and Envelope Evolution

The Herschel Orion Protostar Survey obtained well-sampled 1.2–870 μm spectral energy distributions (SEDs) of over 300 protostars in the Orion molecular clouds, home to most of the young stellar objects (YSOs) in the nearest 500 pc. We plot the bolometric luminosities and temperatures for 330 Orion YSOs, 315 of which have bolometric temperatures characteristic of protostars. The histogram of the bolometric temperature is roughly flat; 29% of the protostars are in Class 0. The median luminosity decreases by a factor of four with increasing bolometric temperature; consequently, the Class 0 protostars are systematically brighter than the Class I protostars, with a median luminosity of 2.3 L{sub ⊙} as opposed to 0.87 L{sub ⊙}. At a given bolometric temperature, the scatter in luminosities is three orders of magnitude. Using fits to the SEDs, we analyze how the luminosities corrected for inclination and foreground reddening relate to the mass in the inner 2500 au of the best-fit model envelopes. The histogram of the envelope mass is roughly flat, while the median-corrected luminosity peaks at 15 L{sub ⊙} for young envelopes and falls to 1.7 L{sub ⊙} for late-stage protostars with remnant envelopes. The spread in luminosity at each envelope mass is three orders of magnitude. Envelope masses that decline exponentially with time explain the flat mass histogram and the decrease in luminosity, while the formation of a range of stellar masses explains the dispersion in luminosity.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

The Gaia-ESO survey: metal-rich bananas in the bulge

We analyze the kinematics of ∼2000 giant stars in the direction of the Galactic bulge, extracted from the Gaia-ESO survey in the region −10{sup ∘}≲ℓ≲10{sup ∘} and −11{sup ∘}≲b≲−3{sup ∘}. We find distinct kinematic trends in the metal-rich ([M/H]>0) and metal-poor ([M/H]<0) stars in the data. The velocity dispersion of the metal-rich stars drops steeply with latitude, compared to a flat profile in the metal-poor stars, as has been seen previously. We argue that the metal-rich stars in this region are mostly on orbits that support the boxy–peanut shape of the bulge, which naturally explains the drop in their velocity dispersion profile with latitude. The metal-rich stars also exhibit peaky features in their line of sight velocity histograms, particularly along the minor axis of the bulge. We propose that these features are due to stars on resonant orbits supporting the boxy–peanut bulge. This conjecture is strengthened through the comparison of the minor axis data with the velocity histograms of resonant orbits generated in simulations of buckled bars. The “banana” or 2:1:2 orbits provide strongly bimodal histograms with narrow velocity peaks that resemble the Gaia-ESO metal-rich data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Reconstruction of Six-Dimensional Phase Space

A phase space is a mathematical representation of all possible physical states of a system. Particle beams at Fermilab exist within a six-dimensional (6D) phase space defined by three positional components, (x, y, z) and three momentum components, (px, py, pz). To reconstruct this space implies taking measurement data from detectors and mapping out particle behavior using computational methods. The beam detectors, however, are only able to detect spatial distribution among the events of the beam, therefore being limited to positional data. Also, due to the vast number of events in a particle beam, it is extremely difficult to analyze and differentiate every single one’s behavior. However, with Machine Learning (ML), which can distinguish between patterns and map out particle behavior more efficiently. We first used the particle beam software, G4beamline, to simulate a 10,000-event muon beam, adjusting parameters such as initial momentum magnitude (p¬0) and virtual detector position. Using ten virtual detectors, we analyzed p0 values such that minimum 9,990 events were analyzed by every detector. We then input the data from these beam simulations to a C++ program, that randomly selects 100 events, and creates a 2D histogram based on spatial distribution, detector position, and event intensity. This process is repeated 100 times to create 100 histograms per p0 value. These images were then input to a modified ResNet18 Convolutional Neural Network (CNN) for training, and to predict p0 from some unseen set of histograms. The model was accurate when trained on momentum increments of 5 MeV/c and provided with denser training samples around highly variable test values. These results displayed machine learning being able to accurately predict p0 from being trained on different particle behaviors.

Shirlee, Jermain [Fermilab]↗
DOE OSTI2020

Binary Analysis with Architecture and Code Section Detection using Supervised Machine Learning

When presented with an unknown binary, which may or may not be complete, having the ability to determine information about it is critical to future reverse engineering, particularly in discovering the binary’s intended use and potentially malicious nature. This paper details techniques to both identify the machine architecture of the binary, as well as to locate the important code segments within the file. This identification of unknown binaries makes use of a technique called byte histogram in addition to various machine learning (ML) techniques, which we call “What is it Binary” or WiiBin. Benefits of byte histograms reflect the simplicity of calculation and do not rely on file headers or metadata, allowing for acceptable results when only a small portion of the original file is available. Utilizing WiiBin, we were able to accurately (>80%) determine the architecture of test binaries with as little as a 20% contagious portion of the file present. We were also able to determine the location of code sections within a binary by utilizing the WiiBin framework. Ultimately, the more information that can be gleaned from a binary file, the easier it is to successfully reverse engineer.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2015

Factorization-based texture segmentation

This study introduces a factorization-based approach that efficiently segments textured images. We use local spectral histograms as features, and construct an M × N feature matrix using M-dimensional feature vectors in an N-pixel image. Based on the observation that each feature can be approximated by a linear combination of several representative features, we factor the feature matrix into two matrices-one consisting of the representative features and the other containing the weights of representative features at each pixel used for linear combination. The factorization method is based on singular value decomposition and nonnegative matrix factorization. The method uses local spectral histograms to discriminate region appearances in a computationally efficient way and at the same time accurately localizes region boundaries. Finally, the experiments conducted on public segmentation data sets show the promise of this simple yet powerful approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Simulations of cloud‐radiation interaction using large‐scale forcing derived from the CINDY/DYNAMO northern sounding array

Abstract The recently completed CINDY/DYNAMO field campaign observed two Madden‐Julian oscillation (MJO) events in the equatorial Indian Ocean from October to December 2011. Prior work has indicated that the moist static energy anomalies in these events grew and were sustained to a significant extent by radiative feedbacks. We present here a study of radiative fluxes and clouds in a set of cloud‐resolving simulations of these MJO events. The simulations are driven by the large‐scale forcing data set derived from the DYNAMO northern sounding array observations, and carried out in a doubly periodic domain using the Weather Research and Forecasting (WRF) model. Simulated cloud properties and radiative fluxes are compared to those derived from the S‐PolKa radar and satellite observations. To accommodate the uncertainty in simulated cloud microphysics, a number of single‐moment (1M) and double‐moment (2M) microphysical schemes in the WRF model are tested. The 1M schemes tend to underestimate radiative flux anomalies in the active phases of the MJO events, while the 2M schemes perform better, but can overestimate radiative flux anomalies. All the tested microphysics schemes exhibit biases in the shapes of the histograms of radiative fluxes and radar reflectivity. Histograms of radiative fluxes and brightness temperature indicate that radiative biases are not evenly distributed; the most significant bias occurs in rainy areas with OLR less than 150 W/m 2 in the 2M schemes. Analysis of simulated radar reflectivities indicates that this radiative flux uncertainty is closely related to the simulated stratiform cloud coverage. Single‐moment schemes underestimate stratiform cloudiness by a factor of 2, whereas 2M schemes simulate much more stratiform cloud.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Using the apparent diffusion coefficient to identifying MGMT promoter methylation status early in glioblastoma: importance of analytical method

Accurate knowledge of O{sup 6}-methylguanine methyltransferase (MGMT) gene promoter subtype in patients with glioblastoma (GBM) is important for treatment. However, this test is not always available. Pre-operative diffusion MRI (dMRI) can be used to probe tumour biology using the apparent diffusion coefficient (ADC); however, its ability to act as a surrogate to predict MGMT status has shown mixed results. We investigated whether this was due to variations in the method used to analyse ADC. We undertook a retrospective study of 32 patients with GBM who had MGMT status measured. Matching pre-operative MRI data were used to calculate the ADC within contrast enhancing regions of tumour. The relationship between ADC and MGMT was examined using two published ADC methods. A strong trend between a measure of ‘minimum ADC’ and methylation status was seen. An elevated minimum ADC was more likely in the methylated compared to the unmethylated MGMT group (U = 56, P = 0.0561). In contrast, utilising a two-mixture model histogram approach, a significant reduction in mean measure of the ‘low ADC’ component within the histogram was associated with an MGMT promoter methylation subtype (P < 0.0246). This study shows that within the same patient cohort, the method selected to analyse ADC measures has a significant bearing on the use of that metric as a surrogate marker of MGMT status. Thus for dMRI data to be clinically useful, consistent methods of data analysis need to be established prior to establishing any relationship with genetic or epigenetic profiling.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Juxtatumoral perinephric fat analysis in clear cell renal cell carcinoma

Purpose: The purpose of the study was to evaluate the feasibility of using contrast-enhanced computed tomography (CECT)-based texture analysis (CTTA) metrics to differentiate between juxtatumoral perinephric fat (JPF) surrounding low-grade (ISUP 1–2) versus high-grade (ISUP 3–4) clear cell renal cell carcinoma (ccRCC). Methods: In this IRB-approved study, we retrospectively queried the surgical database between June 2009 and April 2016 and identified 83 patients with pathologically confirmed ccRCC (low grade: n = 54, mean age = 61.5 years, 18F/35M; high grade n = 30, mean age = 61.7 years, 8F/22M) who also had pre-operative multiphase CT acquisitions. CT images were transferred to a 3D workstation, and nephrographic phase JPF regions were manually segmented. Using an in-house developed Matlab program, a CTTA panel comprising of texture metrics extracted using six different methods, histogram, 2D- and 3D-Gray-level co-occurrence matrix (GLCM) and Gray-level difference matrix (GLDM), and 2D-Fast Fourier Transform (FFT) analyses, was applied to the segmented images to assess JPF textural heterogeneity in low- versus high-grade ccRCC. Univariate analysis and receiver-operator characteristics (ROC) analysis were used to assess interclass differences in texture metrics and their prediction accuracy, respectively. Results: All methods except GLCM consistently revealed increased heterogeneity in the JPF surrounding high- versus low-grade ccRCC. FFT showed increased complexity index (p < 0.01). Histogram analysis showed increased kurtosis and positive skewness in (p < 0.03), and GLDM analysis showed decreased measure of correlation coefficient (MCC) (p < 0.04). Several of the GLCM metrics showed statistically significant (p < 0.04) textural differences between the two groups, but with no consistent trend. ROC analysis showed that MCC in GLCM analysis had an area under the curve of 0.75. Conclusions: Our study suggests that CTTA of ccRCC shows statistically significant textural differences in JPF surrounding high- versus low-grade ccRCC.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

Measurement uncertainty of rossi-alpha neutron experiments

Rossi-alpha neutron experiments are used to estimate the prompt neutron decay constant of a fissile assembly, a quantity of widespread interest in applications including in nuclear nonproliferation and criticality safety. This work develops a mathematical model to efficiently estimate measurement uncertainty of Rossi-alpha neutron experiments inferred from a two-exponential fit model with histogram binning. The derived uncertainty estimates were validated using repeated Rossi-alpha measurements of a subcritical, 4.5-kg sphere of weapons-grade, alpha-phase plutonium with nickel, copper, tungsten, and polyethylene reflectors. The estimates of uncertainty for the histogram data produced by the model were conservative and agree with the reference uncertainties within noise. The estimates of the prompt neutron decay constant uncertainty agreed with the reference uncertainties within one standard deviation. In conclusion, the proposed model will reduce total measurement times, ultimately reducing operational and procedural costs in application.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Probability Density Function Control for Stochastic Nonlinear Systems using Monte Carlo Simulation

This paper presents a fast implementation framework of output probability density function (PDF) control for a class of stochastic nonlinear systems which are subjected to non-Gaussian noises. The statistical properties of the system outputs can be adjusted by shaping the dynamic output probability density function to track the reference stochastic distribution. However, the dynamic probability density function evolution is very difficult to obtain analytically even if the system model and the stochastic distributions of the noises are known. Motivated by Monte Carlo simulation, the dynamic probability density function can be estimated by sampling data which forms the contribution of this paper. In particular, the sampling points are generated following the stochastic distribution of the noise for each instant. These points go through the system would generate the histogram for system outputs, then the dynamic model can be established based on the dynamic histogram which reflects the randomness and the nonlinear dynamics of the investigated system. Based on the established model, the output probability density function tracking can be achieved and the simulation results and discussions show the effectiveness and benefits of the presented framework.

Zhang, Qichun↗
DOE OSTI2023

A direct numerical simulation study for confined non-isothermal jet impingement at moderate nozzle-to-plate distances: Capturing jet-to-ambient density effects

A direct numerical simulation (DNS) campaign is deployed for a series of confined downward oriented, non-isothermal turbulent impinging jet configurations. A baseline Reynolds number of 9960 is obtained through a precursor DNS pipe flow simulation (Re τ = 505). Three jet temperature configurations (confinement height to nozzle diameter of three) enter a cylindrical domain that share ambient and impingement plate temperatures (298.15 K). The range of jet temperatures are crafted such that the ratio of inlet to ambient density varies from unity to 0.52, showcasing the effect of density disparity on flow characteristics such as core collapse, radial mixing of momentum and energy, near-wall stagnation behavior, wall-jet profiles, and large-scale vortical structures. Surface quantities provided include mean radial heat flux and wall-shear stress profiles, and heat flux histograms at select radial stations. Results showcase increased radial normal stresses for higher temperature jets that support increased mixing, resulting in large-scale recirculation structures that are smaller, while retaining similar normalized radial wall profiles for shear stress, heat flux and pressure. Furthermore, radial plots for wall shear stress and Nusselt number showcase strong radial decay as compared to previous configurations that share similar jet and ambient temperatures. For the 373.15 K case, a Gaussian-like histogram for heat fluxes at the impingement plate transitions to a log-normal profile as radial distances increase. In contrast, the 573.15 K configuration displays a bi-modal heat flux characteristic at the impingement plate, and in similar manner to the moderate temperature counterpart, transitions to a log-normal profile at larger radial distances.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2013

Risk Factors for Neovascular Glaucoma After Proton Beam Therapy of Uveal Melanoma: A Detailed Analysis of Tumor and Dose–Volume Parameters

Purpose: To determine neovascular glaucoma (NVG) incidence and identify contributing tumor and dosing factors in uveal melanoma patients treated with proton beam radiation therapy (PBRT). Methods and Materials: A total of 704 PBRT patients treated by a single surgeon (DHC) for uveal melanoma (1996-2010) were reviewed for NVG in our prospectively maintained database. All patients received 56 GyE in 4 fractions. Median follow-up was 58.3 months. Analyses included the Kaplan-Meier method to estimate NVG distributions, univariate log–rank tests, and Cox's proportional hazards multivariate analysis using likelihood ratio tests to identify independent risk factors of NVG among patient, tumor, and dose–volume histogram parameters. Results: The 5-year PBRT NVG rate was 12.7% (95% confidence interval [CI] 10.2%-15.9%). The 5-year rate of enucleation due to NVG was 4.9% (95% CI 3.4%-7.2%). Univariately, the NVG rate increased significantly with larger tumor diameter (P<.0001), greater height (P<.0001), higher T stage (P<.0001), and closer proximity to the disc (P=.002). Dose–volume histogram analysis revealed that if >30% of the lens or ciliary body received ≥50% dose (≥28 GyE), there was a higher probability of NVG (P<.0001 for both). Furthermore, if 100% of the disc or macula received ≥28 GyE, the NVG rate was higher (P<.0001 and P=.03, respectively). If both anterior and posterior doses were above specified cut points, NVG risk was highest (P<.0001). Multivariate analysis confirmed significant independent risk factors to include tumor height (P<.0001), age (P<.0001), %disc treated to ≥50% Dose (<100% vs 100%) (P=.0007), larger tumor diameter (P=.01), %lens treated to ≥90% Dose (0 vs >0%-30% vs >30%) (P=.01), and optic nerve length treated to ≥90% Dose (≤1 mm vs >1 mm) (P=.02). Conclusions: Our current PBRT patients experience a low rate of NVG and resultant enucleation compared with historical data. The present analysis shows that tumor height, diameter, and anterior as well as posterior critical structure dose–volume parameters may be used to predict NVG risk.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

Effects of Respiratory Motion on Passively Scattered Proton Therapy Versus Intensity Modulated Photon Therapy for Stage III Lung Cancer: Are Proton Plans More Sensitive to Breathing Motion?

Purpose: To quantify and compare the effects of respiratory motion on paired passively scattered proton therapy (PSPT) and intensity modulated photon therapy (IMRT) plans; and to establish the relationship between the magnitude of tumor motion and the respiratory-induced dose difference for both modalities. Methods and Materials: In a randomized clinical trial comparing PSPT and IMRT, radiation therapy plans have been designed according to common planning protocols. Four-dimensional (4D) dose was computed for PSPT and IMRT plans for a patient cohort with respiratory motion ranging from 3 to 17 mm. Image registration and dose accumulation were performed using grayscale-based deformable image registration algorithms. The dose–volume histogram (DVH) differences (4D-3D [3D = 3-dimensional]) were compared for PSPT and IMRT. Changes in 4D-3D dose were correlated to the magnitude of tumor respiratory motion. Results: The average 4D-3D dose to 95% of the internal target volume was close to zero, with 19 of 20 patients within 1% of prescribed dose for both modalities. The mean 4D-3D between the 2 modalities was not statistically significant (P<.05) for all dose–volume histogram indices (mean ± SD) except the lung V5 (PSPT: +1.1% ± 0.9%; IMRT: +0.4% ± 1.2%) and maximum cord dose (PSPT: +1.5 ± 2.9 Gy; IMRT: 0.0 ± 0.2 Gy). Changes in 4D-3D dose were correlated to tumor motion for only 2 indices: dose to 95% planning target volume, and heterogeneity index. Conclusions: With our current margin formalisms, target coverage was maintained in the presence of respiratory motion up to 17 mm for both PSPT and IMRT. Only 2 of 11 4D-3D indices (lung V5 and spinal cord maximum) were statistically distinguishable between PSPT and IMRT, contrary to the notion that proton therapy will be more susceptible to respiratory motion. Because of the lack of strong correlations with 4D-3D dose differences in PSPT and IMRT, the extent of tumor motion was not an adequate predictor of potential dosimetric error caused by breathing motion.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Functional Data Analysis in NTCP Modeling: A New Method to Explore the Radiation Dose-Volume Effects

Purpose/Objective(s): To describe a novel method to explore radiation dose-volume effects. Functional data analysis is used to investigate the information contained in differential dose-volume histograms. The method is applied to the normal tissue complication probability modeling of rectal bleeding (RB) for patients irradiated in the prostatic bed by 3-dimensional conformal radiation therapy. Methods and Materials: Kernel density estimation was used to estimate the individual probability density functions from each of the 141 rectum differential dose-volume histograms. Functional principal component analysis was performed on the estimated probability density functions to explore the variation modes in the dose distribution. The functional principal components were then tested for association with RB using logistic regression adapted to functional covariates (FLR). For comparison, 3 other normal tissue complication probability models were considered: the Lyman-Kutcher-Burman model, logistic model based on standard dosimetric parameters (LM), and logistic model based on multivariate principal component analysis (PCA). Results: The incidence rate of grade ≥2 RB was 14%. V{sub 65Gy} was the most predictive factor for the LM (P=.058). The best fit for the Lyman-Kutcher-Burman model was obtained with n=0.12, m = 0.17, and TD50 = 72.6 Gy. In PCA and FLR, the components that describe the interdependence between the relative volumes exposed at intermediate and high doses were the most correlated to the complication. The FLR parameter function leads to a better understanding of the volume effect by including the treatment specificity in the delivered mechanistic information. For RB grade ≥2, patients with advanced age are significantly at risk (odds ratio, 1.123; 95% confidence interval, 1.03-1.22), and the fits of the LM, PCA, and functional principal component analysis models are significantly improved by including this clinical factor. Conclusion: Functional data analysis provides an attractive method for flexibly estimating the dose-volume effect for normal tissues in external radiation therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

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↗