Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “algorithm”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,765 records · Page 98
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Leveraging Qubit Loss Detection in Fault-Tolerant Quantum Algorithms

Qubit loss errors constitute a dominant source of noise in many quantum hardware systems, particularly in neutral-atom quantum computers. We develop a theoretical framework to effectively detect and correct loss errors in logical algorithms and leverage such loss information in decoding. Considering general quantum error correction codes and logical circuits, we introduce a delayed-erasure decoder for experimentally motivated error models which leverages information from delayed loss detection to accurately correct loss errors, even when the precise moment of the error is unknown. Using this decoder, we identify strategies for detecting and correcting loss errors based on the logical circuit structure. For deep circuits prior to logical measurement, we explore methods to integrate loss detection into syndrome extraction with minimal overhead, identifying optimal strategies depending on the qubit loss fraction in the noise and hardware capabilities. In contrast, we find that many key algorithmic subroutines involve frequent gate teleportation, shortening the circuit depth before logical measurement and naturally replacing qubits with no additional experimental overhead. We simulate this setting using a toy model algorithm for small-angle synthesis and find a significant performance improvement as the loss fraction increases. These results provide a path forward for advancing large-scale fault-tolerant quantum computation in systems with loss error detection.

atoms↗
DOE OSTI2020

K-space algorithmic reconstruction (KAREN): a robust statistical methodology to separate Bragg and diffuse scattering

Diffuse scattering occurring in the Bragg diffraction pattern of a long-range-ordered structure represents local deviation from the governing regular lattice. However, interpreting the real-space structure from the diffraction pattern presents a significant challenge because of the dramatic difference in intensity between the Bragg and diffuse components of the total scattering function. In contrast to the sharp Bragg diffraction, the diffuse signal has generally been considered to be a weak expansive or continuous background signal. In this paper, using 1D and 2D models, it is demonstrated that diffuse scattering in fact consists of a complex array of high-frequency features that must not be averaged into a low-frequency background signal. To evaluate the actual diffuse scattering effectively, an algorithm has been developed that uses robust statistics and traditional signal processing techniques to identify Bragg peaks as signal outliers which can be removed from the overall scattering data and then replaced by statistically valid fill values. This method, described as a 'K-space algorithmic reconstruction' (KAREN), can identify Bragg reflections independent of prior knowledge of a system's unit cell. KAREN does not alter any data other than that in the immediate vicinity of the Bragg reflections, and reconstructs the diffuse component surrounding the Bragg peaks without introducing discontinuities which induce Fourier ripples or artifacts from underfilling `punched' voids. The KAREN algorithm for reconstructing diffuse scattering provides demonstrably better resolution than can be obtained from previously described punch-and-fill methods. The superior structural resolution obtained using the KAREN method is demonstrated by evaluating the complex ordered diffuse scattering observed from the neutron diffraction of a single plastic crystal of CBr 4 using pair distribution function analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A ray-tracing algorithm for ab-initio calculation of thermal load in undulator-based synchrotron beamlines

The OASYS suite and its powerful integration features are used to implement a ray-tracing algorithm to accurately calculate the thermal load in any component of an undulator-based synchrotron beamline. This is achieved by sampling and converting the SRW source of a given energy into a Shadow source and using the latter code to ray trace the full beamline. The accuracy of the algorithm is proved by reconstructing the full undulator radiation distribution through an aperture and comparing the result with direct calculaton of the total power using SRW. The algorithm is particularly suited to analyze cases with complex beamline layouts and optical elements, such as crystals, multilayers, and compound refractive lenses. Examples of its use to calculate the power load on elements of two of the feature beamlines at the Advanced Photon Source Upgrade Project and a comparison of the results with analytical calculations are presented.

43 PARTICLE ACCELERATORS↗
DOE OSTI2016

Algorithm and Architecture Independent Benchmarking with SEAK

Many applications of high performance embedded computing are limited by performance or power bottlenecks. We have designed the Suite for Embedded Applications & Kernels (SEAK), a new benchmark suite, (a) to capture these bottlenecks in a way that encourages creative solutions; and (b) to facilitate rigorous, objective, end-user evaluation for their solutions. To avoid biasing solutions toward existing algorithms, SEAK benchmarks use a mission-centric (abstracted from a particular algorithm) and goal-oriented (functional) specification. To encourage solutions that are any combination of software or hardware, we use an end-user black-box evaluation that can capture tradeoffs between performance, power, accuracy, size, and weight. The tradeoffs are especially informative for procurement decisions. We call our benchmarks future proof because each mission-centric interface and evaluation remains useful despite shifting algorithmic preferences. It is challenging to create both concise and precise goal-oriented specifications for mission-centric problems. This paper describes the SEAK benchmark suite and presents an evaluation of sample solutions that highlights power and performance tradeoffs.

algorithms and kernels↗
DOE OSTI2020

An Approximation Algorithm for a Task Allocation, Sequencing and Scheduling Problem Involving a Human-Robot Team

Here we present an approximation algorithm for a Task Allocation, Sequencing and Scheduling Problem (TASSP) involving a team of human operators and robots. The robots have to travel to a given set of targets and collaboratively work on the tasks at the targets with the human operators. The problem aims to find a sequence of targets for each robot to visit and schedule the tasks at the targets with the human operators such that each target is visited exactly once by some robot, the scheduling constraints are satisfied and the maximum mission time of any robot is minimum. This problem is a generalization of the single Traveling Salesman Problem and is NP-Hard. Given k robots and m human operators, an algorithm is developed for solving the TASSP with an approximation ratio equal to 5/2- 1/k when m ≥ k and equal to 7/2 -1/k otherwise. Computational results are also presented to corroborate the performance of the proposed algorithm.

42 ENGINEERING↗
DOE OSTI2020

Generation of Synthetic Data for a Radiation Detection Algorithm Competition

This paper details the generation of synthetic radiation data using large-scale Monte Carlo transport models to evaluate radiation search detection algorithms. Modular 3-D Monte Carlo models spanning multiple city blocks were constructed, loosely based on downtown Knoxville, TN, containing buildings composed of multiple materials (brick, granite, and concrete), sidewalks, a four-lane road, side streets, parking lots, and grassy fields. Background and simulated source detector response calculations from these models were used to create synthetic list mode data sets for a 2"×4"×16" NaI(Tl) detector moving through a city street at a constant speed. For the background simulations, major isotopes were computed individually so that background composition and variability could be computed efficiently outside Monte Carlo. The source detector response included six simulated sources placed at 15 source locations. Detector response was developed to be periodic through the city street so that a detector path could begin at one end of the model and wrap around to the other. This framework allowed for the creation of diverse data sets, each with its own unique background and simulated source detector response. Synthetic data allows for high-quality labels, which are useful in developing data-driven radiation detection algorithms. This methodology was used to create synthetic data sets which were released as part of a public data competition to spur the development of new radiation detection algorithms for radiological search applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Controller-Based Energy-Aware Wireless Sensor Network Routing Using Quantum Algorithms

Energy-efficient routing in wireless sensor networks has attracted attention from researchers in both academia and industry, most recently motivated by the opportunity to use software-defined network-inspired approaches. These problems are NP-hard, with algorithms needing computation time that scales faster than polynomials in the problem size. Consequently, heuristic algorithms are used in practice, which are unable to guarantee optimally. In this article, we show proof-of-principle for the use of a quantum annealing processor instead of a classical processor, to find optimal or nearly optimal solutions very quickly. Our preliminary results for small networks show that this approach using quantum computing has great promise and may open the door for other significant improvements in the efficacy of network algorithms.

42 ENGINEERING↗
DOE OSTI2025

Analog In-Memory Computing for the Synthetic Aperture Radar Polar Format Algorithm

As the utility of synthetic aperture radar (SAR) systems increases in autonomous vehicles, satellites, and other power- and space-constrained edge applications, there is a growing need for processors that can form SAR images at low power. In recent years, analog in-memory compute (AIMC) has shown immense promise for accelerating neural networks and other matrix-vector multiplication (MVM) heavy workloads at the edge. Here, in this work, we examine how the polar format algorithm (PFA), a popular SAR image formation algorithm, can be mapped to these AIMC systems. The PFA maps readily onto analog MVMs because it primarily consists of two linear operations: interpolation of frequency-domain data to a Cartesian grid, followed by a 2-D Fourier transform. This work presents two approaches to map the interpolation operation onto MVMs in analog hardware: a chirp transform and a modified form of sinc interpolation. These mappings introduce algorithmic errors, and their effect on the quality of SAR image formation is examined, both quantitatively and qualitatively. In addition, the impact of errors introduced by the analog hardware is explored to determine which approach is optimal under varying assumptions about the underlying analog memory devices and circuits.

Analog computing↗
DOE OSTI2020

Accurate Consensus-based Distributed Averaging with Variable Time Delay in Support of Distributed Secondary Control Algorithms

We report that distributed secondary control has been widely used in hierarchical control structures, where multiple distributed generators (DGs) need to coordinate to regulate system voltage and frequency. In these systems, consensus algorithms determine the average of a group of dynamic states (e.g. voltages measured by a group of DGs). To be useful, consensus algorithms must be computationally efficient, stable and accurate. In practice, numerous practical implementation challenges significantly affect the consensus equilibrium. In this paper, we quantify the accuracy deviations of the distributed average observer algorithms proposed in the literature to demonstrate the problems with the state-of-the-art distributed averaging techniques. A novel approach is proposed that achieves accurate average tracking in the presence of time-varying communication delays among agents. In our implementation, time synchronization of all distributed controllers is enabled by a novel software platform, called Resilient Information Architecture Platform for the Smart Grid (RIAPS). The proposed distributed average observer is implemented on hardware controllers and its effectiveness is validated in a controller hardware-in-the-loop testbed.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Description of reaction and vibrational energetics of CO 2 –NH 3 interaction using quantum computing algorithms

CO 2 capture is critical to solving global warming. Amine-based solvents are extensively used to chemically absorb CO 2 . Thus, it is crucial to study the chemical absorption of CO 2 by amine-based solvents to better understand and optimize CO 2 capture processes. Here, we use quantum computing algorithms to quantify molecular vibrational energies and reaction pathways between CO 2 and a simplified amine-based solvent model—NH 3 . Molecular vibrational properties are important to understanding kinetics of reactions. However, the molecule size correlates with the strength of anharmonicity effect on vibrational properties, which can be challenging to address using classical computing. Quantum computing can help enhance molecular vibrational calculations by including anharmonicity. We implement a variational quantum eigensolver (VQE) algorithm in a quantum simulator to calculate ground state vibrational energies of reactants and products of the CO 2 and NH 3 reaction. The VQE calculations yield ground vibrational energies of CO 2 and NH 3 with similar accuracy to classical computing. In the presence of hardware noise, Compact Heuristic for Chemistry (CHC) ansatz with shallower circuit depth performs better than Unitary Vibrational Coupled Cluster. The “Zero Noise Extrapolation” error-mitigation approach in combination with CHC ansatz improves the vibrational calculation accuracy. Excited vibrational states are accessed with quantum equation of motion method for CO 2 and NH 3 . Using quantum Hartree–Fock (HF) embedding algorithm to calculate electronic energies, the corresponding reaction profile compares favorably with Coupled Cluster Singles and Doubles while being more accurate than HF. Our research showcases quantum computing applications in the study of CO 2 capture reactions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

A generalized 2D pencil beam scaling algorithm for proton dose calculation in heterogeneous slab geometries

Purpose: Pencil beam algorithms are commonly used for proton therapy dose calculations. Szymanowski and Oelfke ['Two-dimensional pencil beam scaling: An improved proton dose algorithm for heterogeneous media,' Phys. Med. Biol. 47, 3313-3330 (2002)] developed a two-dimensional (2D) scaling algorithm which accurately models the radial pencil beam width as a function of depth in heterogeneous slab geometries using a scaled expression for the radial kernel width in water as a function of depth and kinetic energy. However, an assumption made in the derivation of the technique limits its range of validity to cases where the input expression for the radial kernel width in water is derived from a local scattering power model. The goal of this work is to derive a generalized form of 2D pencil beam scaling that is independent of the scattering power model and appropriate for use with any expression for the radial kernel width in water as a function of depth. Methods: Using Fermi-Eyges transport theory, the authors derive an expression for the radial pencil beam width in heterogeneous slab geometries which is independent of the proton scattering power and related quantities. The authors then perform test calculations in homogeneous and heterogeneous slab phantoms using both the original 2D scaling model and the new model with expressions for the radial kernel width in water computed from both local and nonlocal scattering power models, as well as a nonlocal parameterization of Moliere scattering theory. In addition to kernel width calculations, dose calculations are also performed for a narrow Gaussian proton beam. Results: Pencil beam width calculations indicate that both 2D scaling formalisms perform well when the radial kernel width in water is derived from a local scattering power model. Computing the radial kernel width from a nonlocal scattering model results in the local 2D scaling formula under-predicting the pencil beam width by as much as 1.4 mm (21%) at the depth of the Bragg peak for a 220 MeV proton beam in homogeneous water. This translates into a 32% dose discrepancy for a 5 mm Gaussian proton beam. Similar trends were observed for calculations made in heterogeneous slab phantoms where it was also noted that errors tend to increase with greater beam penetration. The generalized 2D scaling model performs well in all situations, with a maximum dose error of 0.3% at the Bragg peak in a heterogeneous phantom containing 3 cm of hard bone. Conclusions: The authors have derived a generalized form of 2D pencil beam scaling which is independent of the proton scattering power model and robust to the functional form of the radial kernel width in water used for the calculations. Sample calculations made with this model show excellent agreement with expected values in both homogeneous water and heterogeneous phantoms.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2013

Accuracy of pencil-beam redefinition algorithm dose calculations in patient-like cylindrical phantoms for bolus electron conformal therapy

Purpose: The purpose of this study was to document the improved accuracy of the pencil beam redefinition algorithm (PBRA) compared to the pencil beam algorithm (PBA) for bolus electron conformal therapy using cylindrical patient phantoms based on patient computed tomography (CT) scans of retromolar trigone and nose cancer.Methods: PBRA and PBA electron dose calculations were compared with measured dose in retromolar trigone and nose phantoms both with and without bolus. For the bolus treatment plans, a radiation oncologist outlined a planning target volume (PTV) on the central axis slice of the CT scan for each phantom. A bolus was designed using the planning.decimal{sup Registered-Sign} (p.d) software (.decimal, Inc., Sanford, FL) to conform the 90% dose line to the distal surface of the PTV. Dose measurements were taken with thermoluminescent dosimeters placed into predrilled holes. The Pinnacle{sup 3} (Philips Healthcare, Andover, MD) treatment planning system was used to calculate PBA dose distributions. The PBRA dose distributions were calculated with an in-house C++ program. In order to accurately account for the phantom materials a table correlating CT number to relative electron stopping and scattering powers was compiled and used for both PBA and PBRA dose calculations. Accuracy was determined by comparing differences in measured and calculated dose, as well as distance to agreement for each measurement point.Results: The measured doses had an average precision of 0.9%. For the retromolar trigone phantom, the PBRA dose calculations had an average {+-}1{sigma} dose difference (calculated - measured) of -0.65%{+-} 1.62% without the bolus and -0.20%{+-} 1.54% with the bolus. The PBA dose calculation had an average dose difference of 0.19%{+-} 3.27% without the bolus and -0.05%{+-} 3.14% with the bolus. For the nose phantom, the PBRA dose calculations had an average dose difference of 0.50%{+-} 3.06% without bolus and -0.18%{+-} 1.22% with the bolus. The PBA dose calculations had an average dose difference of 0.65%{+-} 6.21% without bolus and 1.75%{+-} 5.94% with the bolus. From a clinical perspective an agreement of 5% or better between planned (calculated) and delivered (measured) dose is desired. Statistically, this was true for 99% ({+-}2{sigma}) of the dose points for three of the four cases for the PBRA dose calculations, the exception being the nose without bolus for which this was true for 89% ({+-}1.6{sigma}) of the dose points. For the retromolar trigone, with and without bolus, the PBA showed agreement of 5% or better for approximately 86% ({+-}1.5{sigma}) of the dose points. For the nose, with and without bolus, the PBA showed agreement of 5% or better for only approximately 58% ({+-}0.8{sigma}) of the dose points.Conclusions: The measured data, whose high precision makes them useful for evaluation of the accuracy of electron dose algorithms, will be made publicly available. Based on the spread in dose differences, the PBRA has at least twice the accuracy of the PBA. From a clinical perspective the PBRA accuracy is acceptable in the retromolar trigone and nose for electron therapy with and without bolus.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2014

A block matching-based registration algorithm for localization of locally advanced lung tumors

Purpose: To implement and evaluate a block matching-based registration (BMR) algorithm for locally advanced lung tumor localization during image-guided radiotherapy. Methods: Small (1 cm{sup 3}), nonoverlapping image subvolumes (“blocks”) were automatically identified on the planning image to cover the tumor surface using a measure of the local intensity gradient. Blocks were independently and automatically registered to the on-treatment image using a rigid transform. To improve speed and robustness, registrations were performed iteratively from coarse to fine image resolution. At each resolution, all block displacements having a near-maximum similarity score were stored. From this list, a single displacement vector for each block was iteratively selected which maximized the consistency of displacement vectors across immediately neighboring blocks. These selected displacements were regularized using a median filter before proceeding to registrations at finer image resolutions. After evaluating all image resolutions, the global rigid transform of the on-treatment image was computed using a Procrustes analysis, providing the couch shift for patient setup correction. This algorithm was evaluated for 18 locally advanced lung cancer patients, each with 4–7 weekly on-treatment computed tomography scans having physician-delineated gross tumor volumes. Volume overlap (VO) and border displacement errors (BDE) were calculated relative to the nominal physician-identified targets to establish residual error after registration. Results: Implementation of multiresolution registration improved block matching accuracy by 39% compared to registration using only the full resolution images. By also considering multiple potential displacements per block, initial errors were reduced by 65%. Using the final implementation of the BMR algorithm, VO was significantly improved from 77% ± 21% (range: 0%–100%) in the initial bony alignment to 91% ± 8% (range: 56%–100%;p < 0.001). Left-right, anterior-posterior, and superior-inferior systematic BDE were 3.2, 2.4, and 4.4 mm, respectively, with random BDE of 2.4, 2.1, and 2.7 mm. Margins required to include both localization and delineation uncertainties ranged from 5.0 to 11.7 mm, an average of 40% less than required for bony alignment. Conclusions: BMR is a promising approach for automatic lung tumor localization. Further evaluation is warranted to assess the accuracy and robustness of BMR against other potential localization strategies.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

SU-E-T-21: A Novel Sampling Algorithm to Reduce Intensity-Modulated Radiation Therapy (IMRT) Optimization Time

Purpose: The IMRT optimization problem requires substantial computer time to find optimal dose distributions because of the large number of variables and constraints. Voxel sampling reduces the number of constraints and accelerates the optimization process, but usually deteriorates the quality of the dose distributions to the organs. We propose a novel sampling algorithm that accelerates the IMRT optimization process without significantly deteriorating the quality of the dose distribution. Methods: We included all boundary voxels, as well as a sampled fraction of interior voxels of organs in the optimization. We selected a fraction of interior voxels using a clustering algorithm, that creates clusters of voxels that have similar influence matrix signatures. A few voxels are selected from each cluster based on the pre-set sampling rate. Results: We ran sampling and no-sampling IMRT plans for de-identified head and neck treatment plans. Testing with the different sampling rates, we found that including 10% of inner voxels produced the good dose distributions. For this optimal sampling rate, the algorithm accelerated IMRT optimization by a factor of 2–3 times with a negligible loss of accuracy that was, on average, 0.3% for common dosimetric planning criteria. Conclusion: We demonstrated that a sampling could be developed that reduces optimization time by more than a factor of 2, without significantly degrading the dose quality.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-T-202: Impact of Monte Carlo Dose Calculation Algorithm On Prostate SBRT Treatments

Purpose: The purpose of this work was to quantify the dosimetric impact of using Monte Carlo algorithm on pre calculated SBRT prostate treatment with pencil beam dose calculation algorithm. Methods: A 6MV photon beam produced by a Novalis TX (BrainLAB-Varian) linear accelerator equipped with HDMLC was used. Treatment plans were done using 9 fields with Iplanv4.5 (BrainLAB) and dynamic IMRT modality. Institutional SBRT protocol uses a total dose to the prostate of 40Gy in 5 fractions, every other day. Dose calculation is done by pencil beam (2mm dose resolution), heterogeneity correction and dose volume constraint (UCLA) for PTV D95%=40Gy and D98%>39.2Gy, Rectum V20Gy<50%, V32Gy<20%, V36Gy<10% and V40Gy<5%, Bladder V20Gy<40% and V40Gy<10%, femoral heads V16Gy<5%, penile bulb V25Gy<3cc, urethra and overlap region between PTV and PRV Rectum Dmax<42Gy. 10 SBRT treatments plans were selected and recalculated using Monte Carlo with 2mm spatial resolution and mean variance of 2%. DVH comparisons between plans were done. Results: The average difference between PTV doses constraints were within 2%. However 3 plans have differences higher than 3% which does not meet the D98% criteria (>39.2Gy) and should have been renormalized. Dose volume constraint differences for rectum, bladder, femoral heads and penile bulb were les than 2% and within tolerances. Urethra region and overlapping between PTV and PRV Rectum shows increment of dose in all plans. The average difference for urethra region was 2.1% with a maximum of 7.8% and for the overlapping region 2.5% with a maximum of 8.7%. Conclusion: Monte Carlo dose calculation on dynamic IMRT treatments could affects on plan normalization. Dose increment in critical region of urethra and PTV overlapping region with PTV could have clinical consequences which need to be studied. The use of Monte Carlo dose calculation algorithm is limited because inverse planning dose optimization use only pencil beam.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

SU-E-T-347: Validation of the Condensed History Algorithm of Geant4 Using the Fano Test

Purpose: To validate the condensed history algorithm and physics of the Geant4 Monte Carlo toolkit for simulations of ionization chambers (ICs). This study is the first step to validate Geant4 for calculations of photon beam quality correction factors under the presence of a strong magnetic field for magnetic resonance guided linac system applications. Methods: The electron transport and boundary crossing algorithms of Geant4 version 9.6.p02 were tested under Fano conditions using the Geant4 example/application FanoCavity. User-defined parameters of the condensed history and multiple scattering algorithms were investigated under Fano test conditions for three scattering models (physics lists): G4UrbanMscModel95 (PhysListEmStandard-option3), G4GoudsmitSaundersonMsc (PhysListEmStandard-GS), and G4WentzelVIModel/G4CoulombScattering (PhysListEmStandard-WVI). Simulations were conducted using monoenergetic photon beams, ranging from 0.5 to 7 MeV and emphasizing energies from 0.8 to 3 MeV. Results: The GS and WVI physics lists provided consistent Fano test results (within ±0.5%) for maximum step sizes under 0.01 mm at 1.25 MeV, with improved performance at 3 MeV (within ±0.25%). The option3 physics list provided consistent Fano test results (within ±0.5%) for maximum step sizes above 1 mm. Optimal parameters for the option3 physics list were 10 km maximum step size with default values for other user-defined parameters: 0.2 dRoverRange, 0.01 mm final range, 0.04 range factor, 2.5 geometrical factor, and 1 skin. Simulations using the option3 physics list were ∼70 – 100 times faster compared to GS and WVI under optimal parameters. Conclusion: This work indicated that the option3 physics list passes the Fano test within ±0.5% when using a maximum step size of 10 km for energies suitable for IC calculations in a 6 MV spectrum without extensive computational times. Optimal user-defined parameters using the option3 physics list will be used in future IC simulations to calculate beam quality correction factors under the presence of a magnetic field. Elekta-MD Anderson Research Agreement.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

SU-E-T-496: A Study of Two Commercial Dose Calculation Algorithms in Low Density Phantom

Purpose: Some lung cancer patients have very low lung density due to comorbidities. We investigate calculation accuracy of Eclipse AAA and Acuros(AXB) using a phantom that simulates this situation. Methods: A 2.5 x 5.0 x 5 cm (long) solid water inhomogeneity positioned 10 cm deep in a Balsa lung phantom (density 0.099 gm/cc) was irradiated with an off-center field such that the central axis was parallel to one side of the inhomogeneity. Radiochromic films were placed at 2.5cm(S1) and 5cm(S2) depths. After CT scanning, Hounsfield Units(HU) were converted to electron(ρe) and mass(ρm) density using in-house(IH) and vendor-supplied(V) calibration curves. IH electron densities were generated using a commercial electron density phantom. The phantom was exposed to 6 MV 3x3 and 20x20 fields. Dose distributions were calculated using the AAA and AXB algorithms. Results: The HU of BW is -910±40 which translates to ρe of 0.088±0.050(IH) and 0.090±0.050(V), and ρm of 0.101±0.045(IH) and 0.103±0.039(V). Both ρe(V) and ρm(V) are higher than ρe(IH) and ρm(IH) respectively by 1.4-5.3% and 0.5-12.3%. The average calculated dose inside the solid water ‘tumor’ are within 3.7% and 2.4% of measurements for both calibrations and field sizes using AAA and AXB. Within 10mm outside the ‘tumor’, AAA on average underestimates by 18.3% and 17.0% respectively for 3x3 using IH and V. AXB underestimates by 5.9%(S1)-6.6%(S2) and 13.1%(S1)-16.0%(S2) respectively using IH and V. For 20x20, AAA and AXB underestimate by 2.8%(S1)-4.4%(S2) and 0.3%(S1)-1.4%(S2) respectively with either calibration. Conclusion: The difference in the HU calibration between V and IH is not of clinical significance in normal field sizes. In the low density region of small fields, the calculations from both algorithms differ significantly from measurements. This may be attributed to the insufficient lateral electron transport modeled by two algorithms resulting in the over-estimation in penumbra expansion.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

MO-G-17A-07: Improved Image Quality in Brain F-18 FDG PET Using Penalized-Likelihood Image Reconstruction Via a Generalized Preconditioned Alternating Projection Algorithm: The First Patient Results

Purpose: To investigate the performance of a new penalized-likelihood PET image reconstruction algorithm using the 1{sub 1}-norm total-variation (TV) sum of the 1st through 4th-order gradients as the penalty. Simulated and brain patient data sets were analyzed. Methods: This work represents an extension of the preconditioned alternating projection algorithm (PAPA) for emission-computed tomography. In this new generalized algorithm (GPAPA), the penalty term is expanded to allow multiple components, in this case the sum of the 1st to 4th order gradients, to reduce artificial piece-wise constant regions (“staircase” artifacts typical for TV) seen in PAPA images penalized with only the 1st order gradient. Simulated data were used to test for “staircase” artifacts and to optimize the penalty hyper-parameter in the root-mean-squared error (RMSE) sense. Patient FDG brain scans were acquired on a GE D690 PET/CT (370 MBq at 1-hour post-injection for 10 minutes) in time-of-flight mode and in all cases were reconstructed using resolution recovery projectors. GPAPA images were compared PAPA and RMSE-optimally filtered OSEM (fully converged) in simulations and to clinical OSEM reconstructions (3 iterations, 32 subsets) with 2.6 mm XYGaussian and standard 3-point axial smoothing post-filters. Results: The results from the simulated data show a significant reduction in the 'staircase' artifact for GPAPA compared to PAPA and lower RMSE (up to 35%) compared to optimally filtered OSEM. A simple power-law relationship between the RMSE-optimal hyper-parameters and the noise equivalent counts (NEC) per voxel is revealed. Qualitatively, the patient images appear much sharper and with less noise than standard clinical images. The convergence rate is similar to OSEM. Conclusions: GPAPA reconstructions using the 1{sub 1}-norm total-variation sum of the 1st through 4th-order gradients as the penalty show great promise for the improvement of image quality over that currently achieved with clinical OSEM reconstructions.

60 APPLIED LIFE SCIENCES↗