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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Probabilistic Forecasting of Generators Startups and Shutdowns in the MISO System Based on Random Forest

Solving security constrained unit commitment (SCUC) problems to plan an economical generation schedule for day-head electricity market has been an important research topic in recent years. Mixed integer programming method (MIP), the-state-of-art approach for solving SCUC problem, is known computationally hard when the number of binary status variables is large. In this paper, a machine learning-based algorithm - random forest (RF), was applied to forecast the startups (SU) and shutdowns (SD) hours of generators, based on historical hourly system condition observations in the Midcontinent Independent System Operator (MISO) system. The main purpose is to reduce the number of binary status variables, by fixing the SU/SD hours to a narrow range of high confidence. This would significantly reduce the size of the decision space, and therefore speed up SCUC solutions with reduced uncertainty.

Lin, Xinming↗
DOE OSTI2015

Phase transitions of macromolecular microsphere composite hydrogels based on the stochastic Cahn–Hilliard equation

We use the stochastic Cahn–Hilliard equation to simulate the phase transitions of the macromolecular microsphere composite (MMC) hydrogels under a random disturbance. Based on the Flory–Huggins lattice model and the Boltzmann entropy theorem, we develop a reticular free energy suit for the network structure of MMC hydrogels. Taking the random factor into account, with the time-dependent Ginzburg-Landau (TDGL) mesoscopic simulation method, we set up a stochastic Cahn–Hilliard equation, designated herein as the MMC-TDGL equation. The stochastic term in the equation is constructed appropriately to satisfy the fluctuation-dissipation theorem and is discretized on a spatial grid for the simulation. A semi-implicit difference scheme is adopted to numerically solve the MMC-TDGL equation. Some numerical experiments are performed with different parameters. The results are consistent with the physical phenomenon, which verifies the good simulation of the stochastic term.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Quantum walk computation

Quantum versions of random walks have diverse applications that are motivating experimental implementations as well as theoretical studies. Recent results showing quantum walks are “universal for quantum computation” relate to algorithms, to be run on quantum computers. We consider whether an experimental implementation of a quantum walk could provide useful computation before we have a universal quantum computer.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Stochastic behavior of nanoscale dielectric wall buckling

The random buckling patterns of nanoscale dielectric walls are analyzed using a nonlinear multi-scale stochastic method that combines experimental measurements with simulations. The dielectric walls, approximately 200 nm tall and 20 nm wide, consist of compliant, low dielectric constant (low-k) fins capped with stiff, compressively stressed TiN lines that provide the driving force for buckling. The deflections of the buckled lines exhibit sinusoidal pseudoperiodicity with amplitude fluctuation and phase decorrelation arising from stochastic variations in wall geometry, properties, and stress state at length scales shorter than the characteristic deflection wavelength of about 1000 nm. The buckling patterns are analyzed and modeled at two length scales: a longer scale (up to 5000 nm) that treats randomness as a longer-scale measurable quantity, and a shorter-scale (down to 20 nm) that treats buckling as a deterministic phenomenon. Statistical simulation is used to join the two length scales. Through this approach, the buckling model is validated and material properties and stress states are inferred. In particular, the stress state of TiN lines in three different systems is determined, along with the elastic moduli of low-k fins and the amplitudes of the small-scale random fluctuations in wall properties—all in the as-processed state. The important case of stochastic effects giving rise to buckling in a deterministically sub-critical buckling state is demonstrated. The nonlinear multiscale stochastic analysis provides guidance for design of low-k structures with acceptable buckling behavior and serves as a template for how randomness that is common to nanoscale phenomena might be measured and analyzed in other contexts.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Improved Sampling Algorithms in the Risk-Informed Safety Margin Characterization Toolkit

The RISMC approach is developing advanced set of methodologies and algorithms in order to perform Probabilistic Risk Analyses (PRAs). In contrast to classical PRA methods, which are based on Event-Tree and Fault-Tree methods, the RISMC approach largely employs system simulator codes applied to stochastic analysis tools. The basic idea is to randomly perturb (by employing sampling algorithms) timing and sequencing of events and internal parameters of the system codes (i.e., uncertain parameters) in order to estimate stochastic parameters such as core damage probability. This approach applied to complex systems such as nuclear power plants requires to perform a series of computationally expensive simulation runs given a large set of uncertain parameters. These types of analysis are affected by two issues. Firstly, the space of the possible solutions (a.k.a., the issue space or the response surface) can be sampled only very sparsely, and this precludes the ability to fully analyze the impact of uncertainties on the system dynamics. Secondly, large amounts of data are generated and tools to generate knowledge from such data sets are not yet available. This report focuses on the first issue and in particular employs novel methods that optimize the information generated by the sampling process by sampling unexplored and risk-significant regions of the issue space: adaptive (smart) sampling algorithms. They infer system response from surrogate models constructed from existing samples and predict the most relevant location of the next sample. It is therefore possible to understand features of the issue space with a small number of carefully selected samples. In this report, we will present how it is possible to perform adaptive sampling using the RISMC toolkit and highlight the advantages compared to more classical sampling approaches such Monte-Carlo. We will employ RAVEN to perform such statistical analyses using both analytical cases but also another RISMC code: RELAP-7.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

Noise Is Not Error: Detecting Parametric Heterogeneity Between Epidemiologic Time Series

Mathematical models play a central role in epidemiology. For example, models unify heterogeneous data into a single framework, suggest experimental designs, and generate hypotheses. Traditional methods based on deterministic assumptions, such as ordinary differential equations (ODE), have been successful in those scenarios. However, noise caused by random variations rather than true differences is an intrinsic feature of the cellular/molecular/social world. Time series data from patients (in the case of clinical science) or number of infections (in the case of epidemics) can vary due to both intrinsic differences or incidental fluctuations. The use of traditional fitting methods for ODEs applied to noisy problems implies that deviation from some trend can only be due to error or parametric heterogeneity, that is noise can be wrongly classified as parametric heterogeneity. This leads to unstable predictions and potentially misguided policies or research programs. In this paper, we quantify the ability of ODEs under different hypotheses (fixed or random effects) to capture individual differences in the underlying data. We explore a simple (exactly solvable) example displaying an initial exponential growth by comparing state-of-the-art stochastic fitting and traditional least squares approximations. We also provide a potential approach for determining the limitations and risks of traditional fitting methodologies. Finally, we discuss the implications of our results for the interpretation of data from the 2014-2015 Ebola epidemic in Africa.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A survey of unsupervised learning methods for high-dimensional uncertainty quantification in black-box-type problems

Constructing surrogate models for uncertainty quantification (UQ) on complex partial differential equations (PDEs) having inherently high-dimensional O(10 n ), n ≥ 2, stochastic inputs (e.g., forcing terms, boundary conditions, initial conditions) poses tremendous challenges. The “curse of dimensionality” can be addressed with suitable unsupervised learning techniques used as a pre-processing tool to encode inputs onto lower-dimensional subspaces while retaining its structural information and meaningful properties. In this work, we review and investigate thirteen dimension reduction methods including linear and nonlinear, spectral, blind source separation, convex and non-convex methods and utilize the resulting embeddings to construct a mapping to quantities of interest via polynomial chaos expansions (PCE). Here, we refer to the general proposed approach as manifold PCE (m-PCE), where manifold corresponds to the latent space resulting from any of the studied dimension reduction methods. To investigate the capabilities and limitations of these methods we conduct numerical tests for three physics-based systems (treated as black-boxes) having high-dimensional stochastic inputs of varying complexity modeled as both Gaussian and non-Gaussian random fields to investigate the effect of the intrinsic dimensionality of input data. We demonstrate both the advantages and limitations of the unsupervised learning methods and we conclude that a suitable m-PCE model provides a cost-effective approach compared to alternative algorithms proposed in the literature, including recently proposed expensive deep neural network-based surrogates and can be readily applied for high-dimensional UQ in stochastic PDEs.

42 ENGINEERING↗
DOE OSTI2013

Early Clinical Outcomes and Toxicity of Intensity Modulated Versus Conventional Pelvic Radiation Therapy for Locally Advanced Cervix Carcinoma: A Prospective Randomized Study

Purpose: To evaluate the toxicity and clinical outcome in patients with locally advanced cervical cancer (LACC) treated with whole pelvic conventional radiation therapy (WP-CRT) versus intensity modulated radiation therapy (WP-IMRT). Methods and Materials: Between January 2010 and January 2012, 44 patients with International Federation of Gynecology and Obstetrics (FIGO 2009) stage IIB-IIIB squamous cell carcinoma of the cervix were randomized to receive 50.4 Gy in 28 fractions delivered via either WP-CRT or WP-IMRT with concurrent weekly cisplatin 40 mg/m{sup 2}. Acute toxicity was graded according to the Common Terminology Criteria for Adverse Events, version 3.0, and late toxicity was graded according to the Radiation Therapy Oncology Group system. The primary and secondary endpoints were acute gastrointestinal toxicity and disease-free survival, respectively. Results: Of 44 patients, 22 patients received WP-CRT and 22 received WP-IMRT. In the WP-CRT arm, 13 patients had stage IIB disease and 9 had stage IIIB disease; in the IMRT arm, 12 patients had stage IIB disease and 10 had stage IIIB disease. The median follow-up time in the WP-CRT arm was 21.7 months (range, 10.7-37.4 months), and in the WP-IMRT arm it was 21.6 months (range, 7.7-34.4 months). At 27 months, disease-free survival was 79.4% in the WP-CRT group versus 60% in the WP-IMRT group (P=.651), and overall survival was 76% in the WP-CRT group versus 85.7% in the WP-IMRT group (P=.645). Patients in the WP-IMRT arm experienced significantly fewer grade ≥2 acute gastrointestinal toxicities (31.8% vs 63.6%, P=.034) and grade ≥3 gastrointestinal toxicities (4.5% vs 27.3%, P=.047) than did patients receiving WP-CRT and had less chronic gastrointestinal toxicity (13.6% vs 50%, P=.011). Conclusion: WP-IMRT is associated with significantly less toxicity compared with WP-CRT and has a comparable clinical outcome. Further studies with larger sample sizes and longer follow-up times are warranted to justify its use in routine clinical practice.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

A Quick Overview of the Extended Feynman Project

The low natural background rates and the penetrating nature of neutron radiation makes neutron detection a good method for quantifying and accounting for large amounts of special nuclear material capable of neutron induced fission and fission chains. Fission is one of the few natural processes that produces time-correlated neutrons, the others are spallation-type processes (e.g. (n,Xn), cosmic induced background, etc) which have low but measurable rates in common terrestrial material. The high rates of most transuranic spontaneous fission sources of even a gram or less usually swamp any cosmic induced background rate but even Kilogram quantities of natural uranium produce neutrons only on the same order as that of the cosmic generated background flux. However the primary characteristic of special nuclear material is its ability to fission and to support fission chains through neutron induced fission. This means that neutrons produced from fission are not produced randomly singly but rather in time-correlated bursts. Almost from the beginning of the atomic age, the measurement of time-correlated neutrons has been used to detect and quantify fission and fission processes. Feynman himself proposed a method, the grandfather of what is used today, to compare correlation rates of neutron flux in a fixed time to that which would be expected of a random neutron source. The larger variance (broader distribution) as compared to a random distribution is a tell-tale sign of correlated production and commonly used as signature of fission and more importantly fission chains, the broader the distribution (and its departure from a random distribution) the higher the multiplication. Feynman’s original method was used to determine the criticality of the first reactor and other critical or near critical systems. We at LLNL have been developing this concept over the past decade and a half and have employed it for the detection and assessment of nuclear materials. Our method for doing this involved generating a theoretical prediction of what we might expect to see, given a neutron source (spontaneous fission with a nubar, or alpha-n) and a possibly multiplying material (Plutonium or Uranium) and comparing it to a measured result and deducing from this what it is we are measuring. We first developed these methods for portable (low efficiency) thermal neutron detectors that were used predominantly for emergency response situations and we have applied some of these techniques with thermal neutron detectors to arms control verification and authentication, for example verifying that there are multiplying quantities of plutonium in an unknown object. In recent years we have been exploring the use of fast neutrons using liquid scintillator cells with Pulse Shape Discrimination (PSD) and in this project we developing both the theory of fast particle production from fission and fission chains and the use of fast particle detection methods primarily for arms control verification and authentication, but for other uses. We have found that fast detection has many advantages, primarily because the speed of the detection (nanoseconds) preserves the original time scale of the particles produced by fission (and more importantly from induced fission) but also because the fast time scales allow for considering much shorter measurement times (binning) that greatly reduce the pollution of random correlations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Statistical ensemble analysis for simulating extrinsic noise-driven response in NF-κB signaling networks

Background: Gene expression profiles and protein dynamics in single cells have a large cell-to-cell variability due to intracellular noise. Intracellular fluctuations originate from two sources: intrinsic noise due to the probabilistic nature of biochemical reactions and extrinsic noise due to randomized interactions of the cell with other cellular systems or its environment. Presently, there is no systematic parameterization and modeling scheme to simulate cellular response at the single cell level in the presence of extrinsic noise. Results: In this paper, we propose a novel statistical ensemble method to simulate the distribution of heterogeneous cellular responses in single cells. We capture the effects of extrinsic noise by randomizing values of the model parameters. In this context, a statistical ensemble is a large number of system replicates, each with randomly sampled model parameters from biologically feasible intervals. We apply this statistical ensemble approach to the well-studied NF-κB signaling system. We predict several characteristic dynamic features of NF-κB response distributions; one of them is the dosage-dependent distribution of the first translocation time of NF-κB. Conclusion: The distributions of heterogeneous cellular responses that our statistical ensemble formulation generates reveal the effect of different cellular conditions, e.g., effects due to wild type versus mutant cells or between different dosages of external stimulants. Distributions generated in the presence of extrinsic noise yield valuable insight into underlying regulatory mechanisms, which are sometimes otherwise hidden.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Determination of grain boundary mobility during recrystallization by statistical evaluation of electron backscatter diffraction measurements

One of the key aspects influencing microstructural design pathways in metallic systems is grain boundary motion. The present work introduces a method by means of which direct measurement of grain boundary mobility vs. misorientation dependence is made possible. The technique utilizes datasets acquired by means of serial electron backscatter diffraction (EBSD) measurements. The experimental EBSD measurements are collectively analyzed, whereby datasets were used to obtain grain boundary mobility and grain aspect ratio with respect to grain boundary misorientation. The proposed method is further validated using cellular automata (CA) simulations. Single crystal aluminium was cold rolled and scratched in order to nucleate random orientations. Subsequent annealing at 300 °C resulted in grains growing, in the direction normal to the scratch, into a single deformed orientation. Growth selection was observed, wherein the boundaries with misorientations close to Σ7 CSL orientation relationship (38° 〈111〉) migrated considerably faster. The obtained boundary mobility distribution exhibited a non-monotonic behavior with a maximum corresponding to misorientation of 38° ± 2° about 〈111〉 axes ± 4°, which was 10–100 times higher than the mobility values of random high angle boundaries. Correlation with the grain aspect ratio values indicated a strong growth anisotropy displayed by the fast growing grains. The observations have been discussed in terms of the influence of grain boundary character on grain boundary motion during recrystallization. - Highlights: • Statistical microstructure method to measure grain boundary mobility during recrystallization • Method implementation independent of material or crystal structure • Mobility of the Σ7 boundaries in 5N Al was calculated as 4.7 × 10{sup –8} m{sup 4}/J ⋅ s. • Pronounced growth selection in the recrystallizing nuclei in Al • Boundary mobility values during recrystallization 2–3 orders of magnitude larger vis-à-vis curvature driven motion.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Study of Particle Rotation Effect in Gas-Solid Flows using Direct Numerical Simulation with a Lattice Boltzmann Method

A new and efficient direct numerical method with second-order convergence accuracy was developed for fully resolved simulations of incompressible viscous flows laden with rigid particles. The method combines the state-of-the-art immersed boundary method (IBM), the multi-direct forcing method, and the lattice Boltzmann method (LBM). First, the multi-direct forcing method is adopted in the improved IBM to better approximate the no-slip/no-penetration (ns/np) condition on the surface of particles. Second, a slight retraction of the Lagrangian grid from the surface towards the interior of particles with a fraction of the Eulerian grid spacing helps increase the convergence accuracy of the method. An over-relaxation technique in the procedure of multi-direct forcing method and the classical fourth order Runge-Kutta scheme in the coupled fluid-particle interaction were applied. The use of the classical fourth order Runge-Kutta scheme helps the overall IB-LBM achieve the second order accuracy and provides more accurate predictions of the translational and rotational motion of particles. The preexistent code with the first-order convergence rate is updated so that the updated new code can resolve the translational and rotational motion of particles with the second-order convergence rate. The updated code has been validated with several benchmark applications. The efficiency of IBM and thus the efficiency of IB-LBM were improved by reducing the number of the Lagragian markers on particles by using a new formula for the number of Lagrangian markers on particle surfaces. The immersed boundary-lattice Boltzmann method (IBLBM) has been shown to predict correctly the angular velocity of a particle. Prior to examining drag force exerted on a cluster of particles, the updated IB-LBM code along with the new formula for the number of Lagrangian markers has been further validated by solving several theoretical problems. Moreover, the unsteadiness of the drag force is examined when a fluid is accelerated from rest by a constant average pressure gradient toward a steady Stokes flow. The simulation results agree well with the theories for the short- and long-time behavior of the drag force. Flows through non-rotational and rotational spheres in simple cubic arrays and random arrays are simulated over the entire range of packing fractions, and both low and moderate particle Reynolds numbers to compare the simulated results with the literature results and develop a new drag force formula, a new lift force formula, and a new torque formula. Random arrays of solid particles in fluids are generated with Monte Carlo procedure and Zinchenko's method to avoid crystallization of solid particles over high solid volume fractions. A new drag force formula was developed with extensive simulated results to be closely applicable to real processes over the entire range of packing fractions and both low and moderate particle Reynolds numbers. The simulation results indicate that the drag force is barely affected by rotational Reynolds numbers. Drag force is basically unchanged as the angle of the rotating axis varies.

36 MATERIALS SCIENCE↗
DOE OSTI2016

SU-G-IeP4-03: Cone Beam X-Ray Luminescence Computed Tomography Based On Generalized Gaussian Markov Random Field

Purpose: Cone beam X-ray luminescence computed tomography (CB-XLCT), which aims to achieve molecular and functional imaging by X-rays, has recently been proposed as a new imaging modality. However, the inverse problem of CB-XLCT is seriously ill-conditioned, hindering us to achieve good image quality. In this work, a novel reconstruction method based on Bayesian theory is proposed to tackle this problem Methods: Bayesian theory provides a natural framework for utilizing various kinds of available prior information to improve the reconstruction image quality. A generalized Gaussian Markov random field (GGMRF) model is proposed here to construct the prior model of the Bayesian theory. The most important feature of GGMRF model is the adjustable shape parameter p, which can be continuously adjusted from 1 to 2. The reconstruction image tends to have more edge-preserving property when p is slide to 1, while having more noise tolerance property when p is slide to 2, just like the behavior of L1 and L2 regularization methods, respectively. The proposed method provides a flexible regularization framework to adapt to a wide range of applications. Results: Numerical simulations were implemented to test the performance of the proposed method. The Digimouse atlas were employed to construct a three-dimensional mouse model, and two small cylinders were placed inside to serve as the targets. Reconstruction results show that the proposed method tends to obtain better spatial resolution with a smaller shape parameter, while better signal-to-noise image with a larger shape parameter. Quantitative indexes, contrast-to-noise ratio (CNR) and full-width at half-maximum (FWHM), were used to assess the performance of the proposed method, and confirmed its effectiveness in CB-XLCT reconstruction. Conclusion: A novel reconstruction method for CB-XLCT is proposed based on GGMRF model, which enables an adjustable performance tradeoff between L1 and L2 regularization methods. Numerical simulations were conducted to demonstrate its performance.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Percutaneous Vertebroplasty for Pain Management in Patients with Multiple Myeloma: Is Radiofrequency Ablation Necessary?

Purpose: This study was designed to investigate the added role of radiofrequency ablation (RFA) to vertebroplasty on the pain management of patients with multiple myeloma (MM). Methods: Thirty-six patients (51–82 years) with vertebral localization of MM were randomly divided into two groups: 18 patients (group A) who underwent RFA and then vertebroplasty, and 18 patients (group B) who underwent only vertebroplasty. Primary endpoints were technical success and pain relief score rate measured by the visual analogue pain scores (VAS) and Roland–Morris Questionnaire (RMQ); secondary endpoint was the amount of administered analgesia. Survival and complications were compared. Results: Technical success was 100 % in both groups. The VAS score (at 24 h and 6 weeks postprocedure) decreased in equal manner for both groups from a mean of 9.1–3.4 and 2.0 for group A and from a mean of 9.3–3.0 and 2.3 for group B; RMQ mean score was 19.8 for group A and 19.9 for group B and decreased to a mean of 9.6 and 8.2 for group A and 9.5 and 8.7 for group B. The amount of medication was equally decreased in the two groups. No statistically significant difference was noted. No major complication occurred and two patients died from other causes. Conclusions: The use of percutaneous vertebroplasty alone appears to be effective for the pain management of the patients with vertebral involvement of multiple myeloma. The use of RFA that includes cost and time does not offer any clear added benefit on the midterm pain management of such patients.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

Universality for 1d Random Band Matrices: Sigma-Model Approximation

The paper continues the development of the rigorous supersymmetric transfer matrix approach to the random band matrices started in (J Stat Phys 164:1233–1260, 2016; Commun Math Phys 351:1009–1044, 2017). We consider random Hermitian block band matrices consisting of W×W random Gaussian blocks (parametrized by j,k∈Λ=[1,n]{sup d}∩ℤ{sup d}) with a fixed entry’s variance J{sub jk}=δ{sub j,k}W{sup −1}+βΔ{sub j,k}W{sup −2}, β>0 in each block. Taking the limit W→∞ with fixed n and β, we derive the sigma-model approximation of the second correlation function similar to Efetov’s one. Then, considering the limit β,n→∞, we prove that in the dimension d=1 the behaviour of the sigma-model approximation in the bulk of the spectrum, as β≫n, is determined by the classical Wigner–Dyson statistics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Dimension-adaptive machine learning-based quantum state reconstruction

Here, we introduce an approach for performing quantum state reconstruction on systems of n qubits using a machine learning-based reconstruction system trained exclusively on m qubits, where m ≥ n. This approach removes the necessity of exactly matching the dimensionality of a system under consideration with the dimension of a model used for training. We demonstrate our technique by performing quantum state reconstruction on randomly sampled systems of one, two, and three qubits using machine learning-based methods trained exclusively on systems containing at least one additional qubit. The reconstruction time required for machine learning-based methods scales significantly more favorably than the training time; hence this technique can offer an overall saving of resources by leveraging a single neural network for dimension-variable state reconstruction, obviating the need to train dedicated machine learning systems for each Hilbert space.

42 ENGINEERING↗
DOE OSTI2012

Mitigation of Late Renal and Pulmonary Injury After Hematopoietic Stem Cell Transplantation

Purpose: To update the results of a clinical trial that assessed whether the angiotensin-converting enzyme inhibitor captopril was effective in mitigating chronic renal failure and pulmonary-related mortality in subjects undergoing total body irradiation (TBI) in preparation for hematopoietic stem cell transplantation (HSCT). Methods and Materials: Updated records of the 55 subjects who were enrolled in this randomized controlled trial were analyzed. Twenty-eight patients received captopril, and 27 patients received placebo. Definitions of TBI-HSCT-related chronic renal failure (and relapse) were the same as those in the 2007 analysis. Pulmonary-related mortality was based on clinical or autopsy findings of pulmonary failure or infection as the primary cause of death. Follow-up data for overall and pulmonary-related mortality were supplemented by use of the National Death Index. Results: The risk of TBI-HSCT-related chronic renal failure was lower in the captopril group (11% at 4 years) than in the placebo group (17% at 4 years), but this was not statistically significant (p > 0.2). Analysis of mortality was greatly extended by use of the National Death Index, and no patients were lost to follow-up for reasons other than death prior to 67 months. Patient survival was higher in the captopril group than in the placebo group, but this was not statistically significant (p > 0.2). The improvement in survival was influenced more by a decrease in pulmonary mortality (11% risk at 4 years in the captopril group vs. 26% in the placebo group, p = 0.15) than by a decrease in chronic renal failure. There was no adverse effect on relapse risk (p = 0.4). Conclusions: Captopril therapy produces no detectable adverse effects when given after TBI. Captopril therapy reduces overall and pulmonary-related mortality after radiation-based HSCT, and there is a trend toward mitigation of chronic renal failure.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2012

Automated Volumetric Modulated Arc Therapy Treatment Planning for Stage III Lung Cancer: How Does It Compare With Intensity-Modulated Radio Therapy?

Purpose: To compare the quality of volumetric modulated arc therapy (VMAT) or intensity-modulated radiation therapy (IMRT) plans generated by an automated inverse planning system with that of dosimetrist-generated IMRT treatment plans for patients with stage III lung cancer. Methods and Materials: Two groups of 8 patients with stage III lung cancer were randomly selected. For group 1, the dosimetrists spent their best effort in designing IMRT plans to compete with the automated inverse planning system (mdaccAutoPlan); for group 2, the dosimetrists were not in competition and spent their regular effort. Five experienced radiation oncologists independently blind-reviewed and ranked the three plans for each patient: a rank of 1 was the best and 3 was the worst. Dosimetric measures were also performed to quantitatively evaluate the three types of plans. Results: Blind rankings from different oncologists were generally consistent. For group 1, the auto-VMAT, auto-IMRT, and manual IMRT plans received average ranks of 1.6, 2.13, and 2.18, respectively. The auto-VMAT plans in group 1 had 10% higher planning tumor volume (PTV) conformality and 24% lower esophagus V70 (the volume receiving 70 Gy or more) than the manual IMRT plans; they also resulted in more than 20% higher complication-free tumor control probability (P+) than either type of IMRT plans. The auto- and manual IMRT plans in this group yielded generally comparable dosimetric measures. For group 2, the auto-VMAT, auto-IMRT, and manual IMRT plans received average ranks of 1.55, 1.75, and 2.75, respectively. Compared to the manual IMRT plans in this group, the auto-VMAT plans and auto-IMRT plans showed, respectively, 17% and 14% higher PTV dose conformality, 8% and 17% lower mean lung dose, 17% and 26% lower mean heart dose, and 36% and 23% higher P+. Conclusions: mdaccAutoPlan is capable of generating high-quality VMAT and IMRT treatment plans for stage III lung cancer. Manual IMRT plans could achieve quality similar to auto-IMRT plans if best effort was spent.

62 RADIOLOGY AND NUCLEAR MEDICINE↗