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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 1,711 records · Page 95
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

GQLink: an implementation of Quantized State Systems (QSS) methods in Geant4

Simulations in high energy physics (HEP) often require the numerical solution of ordinary differential equations (ODE) to determine the trajectories of charged particles in a magnetic field when particles move throughout detector volumes. Each crossing of a volume interrupts the underlying numerical method that solves the equations of motion, triggering iterative algorithms to estimate the intersection point within a given accuracy. The computational cost of this procedure can grow significantly depending on the application at hand. Quantized State System (QSS) is a recent family of discrete-event driven numerical methods exhibiting attractive features for this type of problems, such as native dense output (sequences of polynomial segments updated only by accuracy-driven events) and lightweight detection and handling of volume crossings. In this work we present GQLink, a proof-of-concept integration of QSS with the Geant4 simulation toolkit which stands as an interface for co-simulation that orchestrates robustly and transparently the interaction between the QSS simulation engine and aspects such as geometry definition and physics processes controlled by Geant4. In conclusion, we validate the accuracy and study the performance of the method in simple geometries (subject to intense volume crossing activity) and then in a realistic HEP application using a full CMS detector configuration.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Enhancing photoionization rate calculations in low-temperature plasmas using spectral methods

Photoionization plays a central role in the development of streamer discharges and other non-equilibrium plasma phenomena. It creates seed electrons, which are essential for positive streamer propagation, allowing the ionization front to move forward. Because of this, accurate modeling of photoionization is very important for predicting streamer behavior and plasma evolution. The photoionization process in air (N 2 – O 2 mixture) is often described by the Zheleznyak model (1982). This model is usually solved through Helmholtz-type equations that approximate the Zheleznyak photoionization model (Zheleznyak et al. 1982) as Partial Differential Equations (PDEs). Conventional numerical methods, such as the Finite Difference Method (FDM) or Finite Volume Method (FVM), are widely used to solve these equations. Although they are prevalent, the computational cost of these methods due to their need for matrix operations and iterative solver is demanding. To address this challenge, this work develops a spectral solver based on the Fast Fourier Transform (FFT) combined with Discrete Cosine Transform (DCT) and Discrete Sine Transform (DST) to calculate the photoionization rate efficiently in an axisymmetric cylindrical domain. This method naturally satisfies the boundary conditions used in the model and converts the PDE into algebraic ones in spectral space. Thus, avoids the need for iterative matrix solvers. When compared with FDM results, it is demonstrated that the new solver not only maintains accuracy, but also reduces the computational cost, showing a performance increase of approximately 100 compared to FDM over a wide range of problem sizes. The method is parallelized using Message Passing Interface (MPI) and has been integrated into a fluid plasma model for streamer simulation. Here, this FFT-based approach provides a fast and reliable alternative for calculating photoionization in fluid models, helping large-scale plasma simulations run faster and efficiently, and allows higher-resolution simulation without extra computational cost.

Axisymmetric system↗
DOE OSTI2023

Symmetry breaking/symmetry preserving circuits and symmetry restoration on quantum computers

In this article, we discuss some aspects related to the symmetries of a quantum many-body problem when trying to treat it on a quantum computer. Several features related to symmetry conservation, symmetry breaking, and possible symmetry restoration are reviewed. After briefly discussing some of the standard symmetries relevant for many-particle systems, we discuss the advantage of encoding some symmetries directly in quantum ansätze, especially to reduce the quantum register size. It is, however, well-known that the use of symmetry-breaking states can also be a unique way to incorporate specific internal correlations when a spontaneous symmetry breaking occurs. These aspects are discussed in the quantum computing context. Ultimately, an accurate description of quantum systems can be achieved only when the initially broken symmetries are properly restored. We review several methods explored previously to perform symmetry restoration on a quantum computer, for instance, the ones based on symmetry filtering by quantum phase estimation and by an iterative independent set of Hadamard tests. We propose novel methods that pave the new directions to perform symmetry restoration, like those based on the purification of the state employing the linear combination of unitaries (LCU) approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2010

Computerized method for evaluating diagnostic image quality of calcified plaque images in cardiac CT: Validation on a physical dynamic cardiac phantom

Purpose: In cardiac computed tomography (CT), important clinical indices, such as the coronary calcium score and the percentage of coronary artery stenosis, are often adversely affected by motion artifacts. As a result, the expert observer must decide whether or not to use these indices during image interpretation. Computerized methods potentially can be used to assist in these decisions. In a previous study, an artificial neural network (ANN) regression model provided assessability (image quality) indices of calcified plaque images from the software NCAT phantom that were highly agreeable with those provided by expert observers. The method predicted assessability indices based on computer-extracted features of the plaque. In the current study, the ANN-predicted assessability indices were used to identify calcified plaque images with diagnostic calcium scores (based on mass) from a physical dynamic cardiac phantom. The basic assumption was that better quality images were associated with more accurate calcium scores. Methods: A 64-channel CT scanner was used to obtain 500 calcified plaque images from a physical dynamic cardiac phantom at different heart rates, cardiac phases, and plaque locations. Two expert observers independently provided separate sets of assessability indices for each of these images. Separate sets of ANN-predicted assessability indices tailored to each observer were then generated within the framework of a bootstrap resampling scheme. For each resampling iteration, the absolute calcium score error between the calcium scores of the motion-contaminated plaque image and its corresponding stationary image served as the ground truth in terms of indicating images with diagnostic calcium scores. The performances of the ANN-predicted and observer-assigned indices in identifying images with diagnostic calcium scores were then evaluated using ROC analysis. Results: Assessability indices provided by the first observer and the corresponding ANN performed similarly (AUC{sub OBS1}=0.80 [0.73,0.86] vs AUC{sub ANN1}=0.88 [0.82,0.92]) as that of the second observer and the corresponding ANN (AUC{sub OBS2}=0.87 [0.83,0.91] vs AUC{sub ANN2}=0.90 [0.85,0.94]). Moreover, the ANN-predicted indices were generated in a fraction of the time required to obtain the observer-assigned indices. Conclusions: ANN-predicted assessability indices performed similar to observer-assigned assessability indices in identifying images with diagnostic calcium scores from the physical dynamic cardiac phantom. The results of this study demonstrate the potential of using computerized methods for identifying images with diagnostic clinical indices in cardiac CT images.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

MO-FG-CAMPUS-TeP1-05: Rapid and Efficient 3D Dosimetry for End-To-End Patient-Specific QA of Rotational SBRT Deliveries Using a High-Resolution EPID

Purpose: EPID-based patient-specific quality assurance provides verification of the planning setup and delivery process that phantomless QA and log-file based virtual dosimetry methods cannot achieve. We present a method for EPID-based QA utilizing spatially-variant EPID response kernels that allows for direct calculation of the entrance fluence and 3D phantom dose. Methods: An EPID dosimetry system was utilized for 3D dose reconstruction in a cylindrical phantom for the purposes of end-to-end QA. Monte Carlo (MC) methods were used to generate pixel-specific point-spread functions (PSFs) characterizing the spatially non-uniform EPID portal response in the presence of phantom scatter. The spatially-variant PSFs were decomposed into spatially-invariant basis PSFs with the symmetric central-axis kernel as the primary basis kernel and off-axis representing orthogonal perturbations in pixel-space. This compact and accurate characterization enables the use of a modified Richardson-Lucy deconvolution algorithm to directly reconstruct entrance fluence from EPID images without iterative scatter subtraction. High-resolution phantom dose kernels were cogenerated in MC with the PSFs enabling direct recalculation of the resulting phantom dose by rapid forward convolution once the entrance fluence was calculated. A Delta4 QA phantom was used to validate the dose reconstructed in this approach. Results: The spatially-invariant representation of the EPID response accurately reproduced the entrance fluence with >99.5% fidelity with a simultaneous reduction of >60% in computational overhead. 3D dose for 10{sub 6} voxels was reconstructed for the entire phantom geometry. A 3D global gamma analysis demonstrated a >95% pass rate at 3%/3mm. Conclusion: Our approach demonstrates the capabilities of an EPID-based end-to-end QA methodology that is more efficient than traditional EPID dosimetry methods. Displacing the point of measurement external to the QA phantom reduces the necessary complexity of the phantom itself while offering a method that is highly scalable and inherently generalizable to rotational and trajectory based deliveries. This research was partially supported by Varian.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Overview of Nuclear Integration Activities for Mitigation of Radiation Loads to ITER Superconducting Magnets

The Nuclear Integration Unit (NIU) is a trans-departmental team from the ITER Organization and Domestic Agencies, responsible for all nuclear integration aspects of the facility and for ensuring that systems and components are suitable for their radiation environment and satisfy all related performance requirements. This is a very challenging task namely due to the large number of systems, their still evolving designs, the intricate and far-reaching impacts of these in nuclear responses everywhere, and the complex world-wide distribution of procurement responsibilities. A sound systems engineering approach that involves all relevant experts and stakeholders, and trades-off between different performance requirements in an optimum way, needs to be taken and sustained during design evolution and construction, always with the objective of final overall project success. One of the most important current occupations of the NIU is the evaluation of, and protection from, radiation conditions to superconducting magnets during plasma operations, and particularly nuclear heating. This requires neutronic analyses in massive computer resources, with state-of-the-art methods and complex, extensive computer models. The main ITER superconducting magnet systems subject to significant nuclear loads are the toroidal field coils (TFCs) and the poloidal field coils (PFCs). These are illustrated in Fig. 1. Nuclear responses in these depend mostly on the design of all in-vessel (blankets, manifolds, divertor, in-vessel coils, port plugs), vessel and thermal shield components. Sources to consider are the 500 MW DT burning plasma (14.1 MeV neutrons) and the activated water in the in-vessel cooling system (photons up to 7 MeV from N-16 and neutrons up to 3.5 MeV from N-17). This paper discusses a snapshot of the present understanding of nuclear heat conditions in both the TFC and PFC magnets. This includes integral values and distributions, as well as best estimates from computations and conservative upper estimates by consideration of systematic effects and random uncertainties. The computer models, methods and assumptions used for evaluation of these responses are described. Nuclear integration aspects and ongoing efforts to study and implement additional shielding and other mitigating measures are also discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

Characterization of a commercial hybrid iterative and model-based reconstruction algorithm in radiation oncology

Purpose: Iterative reconstruction (IR) reduces noise, thereby allowing dose reduction in computed tomography (CT) while maintaining comparable image quality to filtered back-projection (FBP). This study sought to characterize image quality metrics, delineation, dosimetric assessment, and other aspects necessary to integrate IR into treatment planning. Methods: CT images (Brilliance Big Bore v3.6, Philips Healthcare) were acquired of several phantoms using 120 kVp and 25–800 mAs. IR was applied at levels corresponding to noise reduction of 0.89–0.55 with respect to FBP. Noise power spectrum (NPS) analysis was used to characterize noise magnitude and texture. CT to electron density (CT-ED) curves were generated over all IR levels. Uniformity as well as spatial and low contrast resolution were quantified using a CATPHAN phantom. Task specific modulation transfer functions (MTF{sub task}) were developed to characterize spatial frequency across objects of varied contrast. A prospective dose reduction study was conducted for 14 patients undergoing interfraction CT scans for high-dose rate brachytherapy. Three physicians performed image quality assessment using a six-point grading scale between the normal-dose FBP (reference), low-dose FBP, and low-dose IR scans for the following metrics: image noise, detectability of the vaginal cuff/bladder interface, spatial resolution, texture, segmentation confidence, and overall image quality. Contouring differences between FBP and IR were quantified for the bladder and rectum via overlap indices (OI) and Dice similarity coefficients (DSC). Line profile and region of interest analyses quantified noise and boundary changes. For two subjects, the impact of IR on external beam dose calculation was assessed via gamma analysis and changes in digitally reconstructed radiographs (DRRs) were quantified. Results: NPS showed large reduction in noise magnitude (50%), and a slight spatial frequency shift (∼0.1 mm{sup −1}) with application of IR at L6. No appreciable changes were observed for CT-ED curves between FBP and IR levels [maximum difference ∼13 HU for bone (∼1% difference)]. For uniformity, differences were ∼1 HU between FBP and IR. Spatial resolution was well conserved; the largest MTF{sub task} decrease between FBP and IR levels was 0.08 A.U. No notable changes in low-contrast detectability were observed and CNR increased substantially with IR. For the patient study, qualitative image grading showed low-dose IR was equivalent to or slightly worse than normal dose FBP, and is superior to low-dose FBP (p < 0.001 for noise), although these did not translate to differences in CT number, contouring ability, or dose calculation. The largest CT number discrepancy from FBP occurred at a bone/tissue interface using the most aggressive IR level [−1.2 ± 4.9 HU (range: −17.6–12.5 HU)]. No clinically significant contour differences were found between IR and FBP, with OIs and DSCs ranging from 0.85 to 0.95. Negligible changes in dose calculation were observed. DRRs preserved anatomical detail with <2% difference in intensity from FBP combined with aggressive IRL6. Conclusions: These results support integrating IR into treatment planning. While slight degradation in edges and shift in texture were observed in phantom, patient results show qualitative image grading, contouring ability, and dosimetric parameters were not adversely affected.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Resolution enhancement of lung 4D-CT data using multiscale interphase iterative nonlocal means

Purpose: Four-dimensional computer tomography (4D-CT) has been widely used in lung cancer radiotherapy due to its capability in providing important tumor motion information. However, the prolonged scanning duration required by 4D-CT causes considerable increase in radiation dose. To minimize the radiation-related health risk, radiation dose is often reduced at the expense of interslice spatial resolution. However, inadequate resolution in 4D-CT causes artifacts and increases uncertainty in tumor localization, which eventually results in extra damages of healthy tissues during radiotherapy. In this paper, the authors propose a novel postprocessing algorithm to enhance the resolution of lung 4D-CT data. Methods: The authors' premise is that anatomical information missing in one phase can be recovered from the complementary information embedded in other phases. The authors employ a patch-based mechanism to propagate information across phases for the reconstruction of intermediate slices in the longitudinal direction, where resolution is normally the lowest. Specifically, the structurally matching and spatially nearby patches are combined for reconstruction of each patch. For greater sensitivity to anatomical details, the authors employ a quad-tree technique to adaptively partition the image for more fine-grained refinement. The authors further devise an iterative strategy for significant enhancement of anatomical details. Results: The authors evaluated their algorithm using a publicly available lung data that consist of 10 4D-CT cases. The authors' algorithm gives very promising results with significantly enhanced image structures and much less artifacts. Quantitative analysis shows that the authors' algorithm increases peak signal-to-noise ratio by 3-4 dB and the structural similarity index by 3%-5% when compared with the standard interpolation-based algorithms. Conclusions: The authors have developed a new algorithm to improve the resolution of 4D-CT. It outperforms the conventional interpolation-based approaches by producing images with the markedly improved structural clarity and greatly reduced artifacts.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

A new accelerated algorithm for ill-conditioned ridge regression problems

In this work, we study the primal and dual formulations of the regularized least squares problem, in special norm L{sub 2}, named ridge regression. We state the Gradient method for the corresponding primal-dual problem through a fixed point approach. For this formulation, we present an original convergence analysis involving the spectral radius of a suitable iteration matrix. The main contribution of this work is to accelerate the studied method by means of a memory-like strategy. Some connections with the spectral properties of the associated iteration matrices were established to prove the convergence of the accelerated method. Preliminary experiments showed the good performance of the proposed algorithm when applied to solve ill-conditioned problems, providing better results than the conjugate gradient method for this class of problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

TU-A-9A-03: Development and Verification of a Forward Model That Assists in Iterative Post-Processing Algorithms Used to Reduce Blur in Compton Backscatter Imaging Systems

Purpose: In Compton Backscatter Imaging (CBI), the source and detector reside on the same side of the patient. We previously demonstrated the applicability of CBI systems for medical purposes using an industrial system. To assist in post-processing images from a CBI system, a forward model based on radiation absorption and scatter principles has been developed. Methods: The forward model was developed in C++ using raytracing to track particles. The algorithm accepts phantoms of any size and resolution to calculate the fraction of incident photons scattered back to the detector, and can perform these calculations for any detector geometry and source specification. To validate the model, results were compared to MCNP-X, which is a Monte Carlo based simulation software, for various combinations of source specifications, detector geometries, and phantom compositions. Results: The model verified that the backscatter signal to the detector was based on three interaction probabilities: a) attenuation of photons going into the phantom, b) Compton scatter of photons toward the detector, and c) attenuation of photons coming out of the phantom. The results from the MCNP-X simulations and the forward model varied from 1 to 5%. This difference was less than 1% for energies higher than 30 keV, but was up to 4% for lower energies. At 50 keV, the difference was less than 1% for multiple detector widths and for both homogeneous and heterogeneous phantoms. Conclusion: As part of the optimization of a medical CBI system, an efficient and accurate forward model was constructed in C++ to estimate the output of CBI system. The model characterized individual components contributing to CBI output and increased computational efficiency over Monte Carlo simulations. It is now used in the development of novel post-processing algorithms that reduce image blur by reversing undesired contribution from outside the region of interest.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2015

TU-G-BRA-05: Predicting Volume Change of the Tumor and Critical Structures Throughout Radiation Therapy by CT-CBCT Registration with Local Intensity Correction

Purpose: The purpose of this study is to develop an accurate and effective technique to predict and monitor volume changes of the tumor and organs at risk (OARs) from daily cone-beam CTs (CBCTs). Methods: While CBCT is typically used to minimize the patient setup error, its poor image quality impedes accurate monitoring of daily anatomical changes in radiotherapy. Reconstruction artifacts in CBCT often cause undesirable errors in registration-based contour propagation from the planning CT, a conventional way to estimate anatomical changes. To improve the registration and segmentation accuracy, we developed a new deformable image registration (DIR) that iteratively corrects CBCT intensities using slice-based histogram matching during the registration process. Three popular DIR algorithms (hierarchical B-spline, demons, optical flow) augmented by the intensity correction were implemented on a graphics processing unit for efficient computation, and their performances were evaluated on six head and neck (HN) cancer cases. Four trained scientists manually contoured nodal gross tumor volume (GTV) on the planning CT and every other fraction CBCTs for each case, to which the propagated GTV contours by DIR were compared. The performance was also compared with commercial software, VelocityAI (Varian Medical Systems Inc.). Results: Manual contouring showed significant variations, [-76, +141]% from the mean of all four sets of contours. The volume differences (mean±std in cc) between the average manual segmentation and four automatic segmentations are 3.70±2.30(B-spline), 1.25±1.78(demons), 0.93±1.14(optical flow), and 4.39±3.86 (VelocityAI). In comparison to the average volume of the manual segmentations, the proposed approach significantly reduced the estimation error by 9%(B-spline), 38%(demons), and 51%(optical flow) over the conventional mutual information based method (VelocityAI). Conclusion: The proposed CT-CBCT registration with local CBCT intensity correction can accurately predict the tumor volume change with reduced errors. Although demonstrated only on HN nodal GTVs, the results imply improved accuracy for other critical structures. This work was supported by NIH/NCI under grant R42CA137886.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-DE-201-02: A Statistical Analysis Tool for Plan Quality Verification in HDR Brachytherapy Forward Planning for Cervix Cancer

Purpose: High Dose Rate (HDR) brachytherapy forward planning is principally an iterative process; hence, plan quality is affected by planners’ experiences and limited planning time. Thus, this may lead to sporadic errors and inconsistencies in planning. A statistical tool based on previous approved clinical treatment plans would help to maintain the consistency of planning quality and improve the efficiency of second checking. Methods: An independent dose calculation tool was developed from commercial software. Thirty-three previously approved cervical HDR plans with the same prescription dose (550cGy), applicator type, and treatment protocol were examined, and ICRU defined reference point doses (bladder, vaginal mucosa, rectum, and points A/B) along with dwell times were collected. Dose calculation tool then calculated appropriate range with a 95% confidence interval for each parameter obtained, which would be used as the benchmark for evaluation of those parameters in future HDR treatment plans. Model quality was verified using five randomly selected approved plans from the same dataset. Results: Dose variations appears to be larger at the reference point of bladder and mucosa as compared with rectum. Most reference point doses from verification plans fell between the predicted range, except the doses of two points of rectum and two points of reference position A (owing to rectal anatomical variations & clinical adjustment in prescription points, respectively). Similar results were obtained for tandem and ring dwell times despite relatively larger uncertainties. Conclusion: This statistical tool provides an insight into clinically acceptable range of cervical HDR plans, which could be useful in plan checking and identifying potential planning errors, thus improving the consistency of plan quality.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

A spectral scheme for Kohn–Sham density functional theory of clusters

Starting from the observation that one of the most successful methods for solving the Kohn–Sham equations for periodic systems – the plane-wave method – is a spectral method based on eigenfunction expansion, we formulate a spectral method designed towards solving the Kohn–Sham equations for clusters. This allows for efficient calculation of the electronic structure of clusters (and molecules) with high accuracy and systematic convergence properties without the need for any artificial periodicity. The basis functions in this method form a complete orthonormal set and are expressible in terms of spherical harmonics and spherical Bessel functions. Computation of the occupied eigenstates of the discretized Kohn–Sham Hamiltonian is carried out using a combination of preconditioned block eigensolvers and Chebyshev polynomial filter accelerated subspace iterations. Several algorithmic and computational aspects of the method, including computation of the electrostatics terms and parallelization are discussed. We have implemented these methods and algorithms into an efficient and reliable package called ClusterES (Cluster Electronic Structure). A variety of benchmark calculations employing local and non-local pseudopotentials are carried out using our package and the results are compared to the literature. Convergence properties of the basis set are discussed through numerical examples. Computations involving large systems that contain thousands of electrons are demonstrated to highlight the efficacy of our methodology. The use of our method to study clusters with arbitrary point group symmetries is briefly discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2011

3D automatic anatomy segmentation based on iterative graph-cut-ASM

Purpose: This paper studies the feasibility of developing an automatic anatomy segmentation (AAS) system in clinical radiology and demonstrates its operation on clinical 3D images. Methods: The AAS system, the authors are developing consists of two main parts: object recognition and object delineation. As for recognition, a hierarchical 3D scale-based multiobject method is used for the multiobject recognition task, which incorporates intensity weighted ball-scale (b-scale) information into the active shape model (ASM). For object delineation, an iterative graph-cut-ASM (IGCASM) algorithm is proposed, which effectively combines the rich statistical shape information embodied in ASM with the globally optimal delineation capability of the GC method. The presented IGCASM algorithm is a 3D generalization of the 2D GC-ASM method that they proposed previously in Chen et al.[Proc. SPIE, 7259, 72590C1-72590C-8 (2009)]. The proposed methods are tested on two datasets comprised of images obtained from 20 patients (10 male and 10 female) of clinical abdominal CT scans, and 11 foot magnetic resonance imaging (MRI) scans. The test is for four organs (liver, left and right kidneys, and spleen) segmentation, five foot bones (calcaneus, tibia, cuboid, talus, and navicular). The recognition and delineation accuracies were evaluated separately. The recognition accuracy was evaluated in terms of translation, rotation, and scale (size) error. The delineation accuracy was evaluated in terms of true and false positive volume fractions (TPVF, FPVF). The efficiency of the delineation method was also evaluated on an Intel Pentium IV PC with a 3.4 GHZ CPU machine. Results: The recognition accuracies in terms of translation, rotation, and scale error over all organs are about 8 mm, 10 deg. and 0.03, and over all foot bones are about 3.5709 mm, 0.35 deg. and 0.025, respectively. The accuracy of delineation over all organs for all subjects as expressed in TPVF and FPVF is 93.01% and 0.22%, and all foot bones for all subjects are 93.75% and 0.28%, respectively. While the delineations for the four organs can be accomplished quite rapidly with average of 78 s, the delineations for the five foot bones can be accomplished with average of 70 s. Conclusions: The experimental results showed the feasibility and efficacy of the proposed automatic anatomy segmentation system: (a) the incorporation of shape priors into the GC framework is feasible in 3D as demonstrated previously for 2D images; (b) our results in 3D confirm the accuracy behavior observed in 2D. The hybrid strategy IGCASM seems to be more robust and accurate than ASM and GC individually; and (c) delineations within body regions and foot bones of clinical importance can be accomplished quite rapidly within 1.5 min.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

SU-E-T-531: Large--Scale DVH Quality Study: Correlated Aims Lead Relaxations

Purpose: Intensity modulated radiation therapy plans are designed to optimally target a tumor while sparing surrounding tissue. Desired dose distributions are iteratively approached via inverse planning. This leads to tradeoffs between clinical objectives for the planning target volume (PTV), organs at risk, and normal tissues. Dose volume histogram (DVHs) related aims are followed that are either institutional or internationally recommended. We analyze common goals and identify potential reasons that often lead to tradeoffs. Methods: 524 IMRT plans for various tumor sites were analyzed based on the main institutional DVH goal for PTV (D95) and the recommendations by ICRU-83 (D2, D50, and D98). Robust statistical tools are developed and applied to ensure that the results are immune to data uncertainties. The probability of violation was measured for each of the DVH goals based on the frequency of not meeting recommended doses. Conditional probabilities for satisfying and/or violating DVH aims were computed to test the hypothesized pair-wise relations between DVH aims. For example, for plans that satisfied D50, the probability of violating D98 was computed via P(D98 < 95% | 98% ≤ D50 ≤ 102%). The equality constraint D50 = 100% was relaxed to encompass the range [98,102]%. Results: A large majority of cases (88%) satisfied the institutional goal for PTV of D95 ≤ 95%. Similar consensus existed for D98. 51% of cases satisfied D2 ≥ 107%. However, only 18% of cases satisfied D50. The conditional probability showed correlations amongst the studied DVH goals. In fact, a negative correlation was revealed between D50 and D95 (and D98), suggesting that these competing goals cannot be satisfied concurrently. Conclusion: The majority of plans followed the institutional guidelines. The reason for their deviation from international recommendations seems to be that the latter goals are competing and cannot be satisfied concurrently in clinical practice.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Directed combinatorial mutagenesis of Escherichia coli for complex phenotype engineering

Strain engineering for industrial production requires a targeted improvement of multiple complex traits, which range from pathway flux to tolerance to mixed sugar utilization. Here, we report the use of an iterative CRISPR EnAbled Trackable genome Engineering (iCREATE) method to engineer rapid glucose and xylose co-consumption and tolerance to hydrolysate inhibitors in E. coli. Deep mutagenesis libraries were rationally designed, constructed, and screened to target ~40,000 mutations across 30 genes. These libraries included global and high-level regulators that regulate global gene expression, transcription factors that play important roles in genome-level transcription, enzymes that function in the sugar transport system, NAD(P)H metabolism, and the aldehyde reduction system. Specific mutants that conferred increased growth in mixed sugars and hydrolysate tolerance conditions were isolated, confirmed, and evaluated for changes in genome-wide expression levels. As a result, we tested the strain with positive combinatorial mutations for 3-hydroxypropionic acid (3HP) production under high furfural and high acetate hydrolysate fermentation, which demonstrated a 7- and 8-fold increase in 3HP productivity relative to the parent strain, respectively.

09 BIOMASS FUELS↗
DOE OSTI2015

Learning Delayed Influences of Biological Systems

Boolean networks are widely used model to represent gene interactions and global dynamical behavior of gene regulatory networks. To understand the memory effect involved in some interactions between biological components, it is necessary to include delayed influences in the model. In this paper, we present a logical method to learn such models from sequences of gene expression data. This method analyzes each sequence one by one to iteratively construct a Boolean network that captures the dynamics of these observations. To illustrate the merits of this approach, we apply it to learning real data from bioinformatic literature. Using data from the yeast cell cycle, we give experimental results and show the scalability of the method. We show empirically that using this method we can handle millions of observations and successfully capture delayed influences of Boolean networks.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Computational and human observer image quality evaluation of low dose, knowledge-based CT iterative reconstruction

Purpose: Aims in this study are to (1) develop a computational model observer which reliably tracks the detectability of human observers in low dose computed tomography (CT) images reconstructed with knowledge-based iterative reconstruction (IMR™, Philips Healthcare) and filtered back projection (FBP) across a range of independent variables, (2) use the model to evaluate detectability trends across reconstructions and make predictions of human observer detectability, and (3) perform human observer studies based on model predictions to demonstrate applications of the model in CT imaging. Methods: Detectability (d′) was evaluated in phantom studies across a range of conditions. Images were generated using a numerical CT simulator. Trained observers performed 4-alternative forced choice (4-AFC) experiments across dose (1.3, 2.7, 4.0 mGy), pin size (4, 6, 8 mm), contrast (0.3%, 0.5%, 1.0%), and reconstruction (FBP, IMR), at fixed display window. A five-channel Laguerre–Gauss channelized Hotelling observer (CHO) was developed with internal noise added to the decision variable and/or to channel outputs, creating six different internal noise models. Semianalytic internal noise computation was tested against Monte Carlo and used to accelerate internal noise parameter optimization. Model parameters were estimated from all experiments at once using maximum likelihood on the probability correct, P{sub C}. Akaike information criterion (AIC) was used to compare models of different orders. The best model was selected according to AIC and used to predict detectability in blended FBP-IMR images, analyze trends in IMR detectability improvements, and predict dose savings with IMR. Predicted dose savings were compared against 4-AFC study results using physical CT phantom images. Results: Detection in IMR was greater than FBP in all tested conditions. The CHO with internal noise proportional to channel output standard deviations, Model-k4, showed the best trade-off between fit and model complexity according to AIC{sub c}. With parameters fixed, the model reasonably predicted detectability of human observers in blended FBP-IMR images. Semianalytic internal noise computation gave results equivalent to Monte Carlo, greatly speeding parameter estimation. Using Model-k4, the authors found an average detectability improvement of 2.7 ± 0.4 times that of FBP. IMR showed greater improvements in detectability with larger signals and relatively consistent improvements across signal contrast and x-ray dose. In the phantom tested, Model-k4 predicted an 82% dose reduction compared to FBP, verified with physical CT scans at 80% reduced dose. Conclusions: IMR improves detectability over FBP and may enable significant dose reductions. A channelized Hotelling observer with internal noise proportional to channel output standard deviation agreed well with human observers across a wide range of variables, even across reconstructions with drastically different image characteristics. Utility of the model observer was demonstrated by predicting the effect of image processing (blending), analyzing detectability improvements with IMR across dose, size, and contrast, and in guiding real CT scan dose reduction experiments. Such a model observer can be applied in optimizing parameters in advanced iterative reconstruction algorithms as well as guiding dose reduction protocols in physical CT experiments.

60 APPLIED LIFE SCIENCES↗