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All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Generating Performance Models for Irregular Applications

Many applications have irregular behavior --- non-uniform input data, input-dependent solvers, irregular memory accesses, unbiased branches --- that cannot be captured using today's automated performance modeling techniques. We describe new hierarchical critical path analyses for the \Palm model generation tool. To create a model's structure, we capture tasks along representative MPI critical paths. We create a histogram of critical tasks with parameterized task arguments and instance counts. To model each task, we identify hot instruction-level sub-paths and model each sub-path based on data flow, instruction scheduling, and data locality. We describe application models that generate accurate predictions for strong scaling when varying CPU speed, cache speed, memory speed, and architecture. We present results for the Sweep3D neutron transport benchmark; Page Rank on multiple graphs; Support Vector Machine with pruning; and PFLOTRAN's reactive flow/transport solver with domain-induced load imbalance.

analytical performance models↗
DOE OSTI2017

Real-Time Fine Grained Occupancy Estimation Using Depth Sensors on ARM Embedded Platforms

Occupancy estimation is an important primitive for a wide range of applications including building energy efficiency, safety, and security. In this paper, we explore the potential of using depth sensors to detect, estimate, identify, and track occupants in buildings. While depth sensors have been widely used for human detection and gesture recognition, computer vision algorithms are typically run on a powerful computer like XBOX or Intel R CoreTM i7 processor. In this work, we develop a prototype system called FORK using off-the-shelf components that performs the entire depth data processing on a cheaper and low power ARM processor in real-time. As ARM processors are extremely weak in running computer vision algorithms, FORK is designed to detect humans and track them in a very efficient way by leveraging a novel lightweight model based approach instead of traditional approaches based on histogram of oriented gradients (HOG) features. Unlike other camera based approaches, FORK is much less privacy invasive (even if the sensor is compromised). Based on a complete implementation, real-world deployment, and extensive evaluation at realistic scenarios, we observe that FORK achieves over 99% accuracy in real-time (4-9 FPS) in occupancy estimation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Spatiotemporal Learning in Power Modules: Wavelet-Enhanced Forecasting of Thermomechanical Degradation

Detecting internal defects in power electronics packages is critical for their performance and reliability, especially under extreme operating conditions, as these defects can lead to catastrophic failure if not properly addressed. Confocal scanning acoustic microscopy (C-SAM) plays a key role in the nondestructive evaluation of bond layer degradation within a power electronics package by detecting defects such as delamination, voids, and cracks. However, accurately quantifying and predicting these defects from C-SAM images remains a significant challenge due to the low noise-to-signal ratio, which typically arises from both imaging process and bond patterns itself. In this paper, we explore machine learning strategies for processing C-SAM images and providing predictive models of defect growth. We use C-SAM images of sintered copper and sintered silver samples, which are obtained under accelerated thermal experiments, as the representative dataset for our study. We investigate the effect of Fourier transforms and wavelet transforms on these datasets to remove high-frequency noise and address noise across multiple scales with histogram equalization to enhance the contrast and improve the visibility of defects. As a result, defect boundaries can be clearly distinguished, enabling more accurate tracking of their growth over time. We then employ different time-series forecasting algorithms on the denoised images to formulate an image-based lifetime prediction model. Statistical models and deep-learning techniques are trained on images obtained in the early stages of thermal shock, and defect growth in the later stages is predicted. Our work serves as a preliminary attempt to improve the accuracy of lifetime prediction models of power electronics packages, which is critical under extreme operating environments.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Sparse Coding for N-Gram Feature Extraction and Training for File Fragment Classification

File fragment classification is an important step in the task of file carving in digital forensics. In file carving, files must be reconstructed based on their content as a result of their fragmented storage on disk or in memory. Existing methods for classification of file fragments typically use hand-engineered features such as byte histograms or entropy measures. In this paper, we propose an approach using sparse coding that enables automated feature extraction. Sparse coding, or sparse dictionary learning, is an unsupervised learning algorithm, and is capable of extracting features based simply on how well those features can be used to reconstruct the original data. With respect to file fragments, we learn sparse dictionaries for n-grams, continuous sequences of bytes, of different sizes. These dictionaries may then be used to estimate n-gram frequencies for a given file fragment, but for significantly larger n-gram sizes than are typically found in existing methods which suffer from combinatorial explosion. To demonstrate the capability of our sparse coding approach, we used the resulting features to train standard classifiers such as support vector machines (SVMs) over multiple file types. Experimentally, we achieved significantly better classification results with respect to existing methods, especially when the features were used in supplement to existing hand-engineered features.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Fiber Uncertainty Visualization for Bivariate Data With Parametric and Nonparametric Noise Models

Visualization and analysis of multivariate data and their uncertainty are top research challenges in data visualization. Constructing fiber surfaces is a popular technique for multivariate data visualization that generalizes the idea of level-set visualization for univariate data to multivariate data. Here, in this paper, we present a statistical framework to quantify positional probabilities of fibers extracted from uncertain bivariate fields. Specifically, we extend the state-of-the-art Gaussian models of uncertainty for bivariate data to other parametric distributions (e.g., uniform and Epanechnikov) and more general nonparametric probability distributions (e.g., histograms and kernel density estimation) and derive corresponding spatial probabilities of fibers. In our proposed framework, we leverage Green's theorem for closed-form computation of fiber probabilities when bivariate data are assumed to have independent parametric and nonparametric noise. Additionally, we present a nonparametric approach combined with numerical integration to study the positional probability of fibers when bivariate data are assumed to have correlated noise. For uncertainty analysis, we visualize the derived probability volumes for fibers via volume rendering and extracting level sets based on probability thresholds. We present the utility of our proposed techniques via experiments on synthetic and simulation datasets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Uncertainty Visualization of Critical Points of 2D Scalar Fields for Parametric and Nonparametric Probabilistic Models

This paper presents a novel end-to-end framework for closed-form computation and visualization of critical point uncertainty in 2D uncertain scalar fields. Critical points are fundamental topological descriptors used in the visualization and analysis of scalar fields. The uncertainty inherent in data (e.g., observational and experimental data, approximations in simulations, and compression), however, creates uncertainty regarding critical point positions. Uncertainty in critical point positions, therefore, cannot be ignored, given their impact on downstream data analysis tasks. Here, in this work, we study uncertainty in critical points as a function of uncertainty in data modeled with probability distributions. Although Monte Carlo (MC) sampling techniques have been used in prior studies to quantify critical point uncertainty, they are often expensive and are infrequently used in production-quality visualization software. We, therefore, propose a new end-to-end framework to address these challenges that comprises a threefold contribution. First, we derive the critical point uncertainty in closed form, which is more accurate and efficient than the conventional MC sampling methods. Specifically, we provide the closed-form and semianalytical (a mix of closed-form and MC methods) solutions for parametric (e.g., uniform, Epanechnikov) and nonparametric models (e.g., histograms) with finite support. Second, we accelerate critical point probability computations using a parallel implementation with the VTK-m library, which is platform portable. Finally, we demonstrate the integration of our implementation with the ParaView software system to demonstrate near-real-time results for real datasets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Completeness and coverage of open-access freshwater fish distribution data in the United States

Aim: Primary biodiversity data constitute observations of particular species at given points in space and time. Open-access databases provide unprecedented access to these data, but their utility depends on how complete species inventories are at a given surveying resolution and how uniformly distributed surveys are in space and time. Our aim was to characterize the completeness of freshwater fish data across spatial scales and among habitat types (lotic stream reaches and lentic waterbodies), and assess coverage bias in space and time. Location: Freshwater habitats of the contiguous United States. Methods: We compiled fish occurrence records from the Global Biodiversity Information Facility (GBIF), the Multi-state Aquatic Resources Information Server (MARIS), and three federally-administered surveys (EMAP, NAQWA, NRS). Next, we evaluated survey completeness across seven spatial resolutions representing nested stream catchments, and separately for lotic and lentic habitats. Lastly, we tested for bias in survey coverage along environmental and temporal gradients for each habitat type. Results: A total of 39,855,157 records representing 1925 species were available from 1800 to 2014. The percent of catchments surveyed increased as spatial resolution decreased while the density of occurrence records within surveyed catchments decreased. Species richness also increased with catchment size consistent with putative species–area relationships. Occurrence records were distributed among 72,114 lotic reaches and 3,325 lentic waterbodies throughout the contiguous US. Seven percent (N=5,055) of surveyed lotic reaches and 23% (N=771) of surveyed lentic waterbodies were well-surveyed based on the most conservative thresholds for two completeness indices. Most well-surveyed lotic reaches (95%) and undammed lentic waterbodies (97%) were completed since 1980, and most were surveyed during only one 20-year time interval (83% and 56% for lotic and lentic waterbodies, respectively). Coverage analyses indicated that contemporary and future climates corresponding to regions along the west coast and gulf coast are the most under-represented for both lotic and lentic habitats. Small lentic waterbodies (surface area < 0.1 km2) are also under-represented. Main Conclusions: Contemporary surveys of lotic reaches and, to a lesser extent, lentic waterbodies are plentiful and generally representative of climatic and landscape characteristics. Data compilation efforts should focus on adding historical data to public repositories. Clustering of well-surveyed waterbodies in MARIS-participating states highlights the value of state-agency data and demonstrates the need for dissemination of these data by more state agencies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Direct current response of a thin scCVD diamond detector under increased applied field to 14.1 MeV neutrons

An avalanche effect yielding inherent gain can be exploited in thin, single-crystal chemical vapor deposition (scCVD) diamond. It occurs when a high enough bias is applied across the diamond thickness while avoiding breakdown. This charge multiplication effect was studied previously with alpha particles and heavy ions either by using the transient current technique or by measuring the energy spectrum. The measurements we obtained to evaluate the charge multiplication performance of a 10 μm thick scCVD diamond detector used a novel approach—we employed an electrometer to characterize the response of the detector by performing directly coupled current measurements (time-averaged charge, at 1 Hz sampling) when exposed to 14.1 MeV neutrons from deuterium-tritium fusion. We measured both the dark and irradiated currents from the detector over a range of applied displacement field values from 2 to 75 V/μm. A histogram method with central mean and standard deviation width was used to determine the current over each measurement duration typically from 100 to 300 seconds. The dark-subtracted irradiated current (i.e., contrast) was used to evaluate the gain of the detector at each applied displacement field. The contrast at an applied displacement field between 15 and 20 V/μm was higher than the expected linear increase in contrast proportional to the increased applied bias, indicating the possible presence of avalanche events in the diamond. The detector response also indicated possible polarization and charge depletion effects. These results provide an opportunity to further explore the use of thin scCVD diamond as a fast neutron current mode detector with inherent gain.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2012

Development of a pixelated GSO gamma camera system with tungsten parallel hole collimator for single photon imaging

Purpose: In small animal imaging using a single photon emitting radionuclide, a high resolution gamma camera is required. Recently, position sensitive photomultiplier tubes (PSPMTs) with high quantum efficiency have been developed. By combining these with nonhygroscopic scintillators with a relatively low light output, a high resolution gamma camera can become useful for low energy gamma photons. Therefore, the authors developed a gamma camera by combining a pixelated Ce-doped Gd{sub 2}SiO{sub 5} (GSO) block with a high quantum efficiency PSPMT. Methods: GSO was selected for the scintillator, because it is not hygroscopic and does not contain any natural radioactivity. An array of 1.9 mm x 1.9 mm x 7 mm individual GSO crystal elements was constructed. These GSOs were combined with a 0.1-mm thick reflector to form a 22 x 22 matrix and optically coupled to a high quantum efficiency PSPMT (H8500C-100 MOD8). The GSO gamma camera was encased in a tungsten gamma-ray shield with tungsten pixelated parallel hole collimator, and the basic performance was measured for Co-57 gamma photons (122 keV). Results: In a two-dimensional position histogram, all pixels were clearly resolved. The energy resolution was {approx}15% FWHM. With the 20-mm thick tungsten pixelated collimator, the spatial resolution was 4.4-mm FWHM 40 mm from the collimator surface, and the sensitivity was {approx}0.05%. Phantom and small animal images were successfully obtained with our developed gamma camera. Conclusions: These results confirmed that the developed pixelated GSO gamma camera has potential as an effective instrument for low energy gamma photon imaging.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2012

Tomotherapy dose distribution verification using MAGIC-f polymer gel dosimetry

Purpose: This paper presents the application of MAGIC-f gel in a three-dimensional dose distribution measurement and its ability to accurately measure the dose distribution from a tomotherapy unit. Methods: A prostate intensity-modulated radiation therapy (IMRT) irradiation was simulated in the gel phantom and the treatment was delivered by a TomoTherapy equipment. Dose distribution was evaluated by the R2 distribution measured in magnetic resonance imaging. Results: A high similarity was found by overlapping of isodoses of the dose distribution measured with the gel and expected by the treatment planning system (TPS). Another analysis was done by comparing the relative absorbed dose profiles in the measured and in the expected dose distributions extracted along indicated lines of the volume and the results were also in agreement. The gamma index analysis was also applied to the data and a high pass rate was achieved (88.4% for analysis using 3%/3 mm and of 96.5% using 4%/4 mm). The real three-dimensional analysis compared the dose-volume histograms measured for the planning volumes and expected by the treatment planning, being the results also in good agreement by the overlapping of the curves. Conclusions: These results show that MAGIC-f gel is a promise for tridimensional dose distribution measurements.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2012

Evolving treatment plan quality criteria from institution-specific experience

Purpose: The dosimetric aspects of radiation therapy treatment plan quality are usually evaluated and reported with dose volume histogram (DVH) endpoints. For clinical practicality, a small number of representative quantities derived from the DVH are often used as dose endpoints to summarize the plan quality. National guidelines on reference values for such quantities for some standard treatment approaches are often used as acceptance criteria to trigger treatment plan review. On the other hand, treatment prescription and planning approaches specific to each institution warrants the need to report plan quality in terms of practice consistency and with respect to institution-specific experience. The purpose of this study is to investigate and develop a systematic approach to record and characterize the institution-specific plan experience and use such information to guide the design of plan quality criteria. In the clinical setting, this approach will assist in (1) improving overall plan quality and consistency and (2) detecting abnormal plan behavior for retrospective analysis. Methods: The authors propose a self-evolving methodology and have developed an in-house prototype software suite that (1) extracts the dose endpoints from a treatment plan and evaluates them against both national standard and institution-specific criteria and (2) evolves the statistics for the dose endpoints and updates institution-specific criteria. Results: The validity of the proposed methodology was demonstrated with a database of prostate stereotactic body radiotherapy cases. As more data sets are accumulated, the evolving institution-specific criteria can serve as a reliable and stable consistency measure for plan quality and reveals the potential use of the ''tighter'' criteria than national standards or projected criteria, leading to practice that may push to shrink the gap between plans deemed acceptable and the underlying unknown optimality. Conclusions: The authors have developed a rationale to improve plan quality and consistency, by evolving the plan quality criteria from institution-specific experience, complementary to national standards. The validity of the proposed method was demonstrated with a prototype system on prostate stereotactic body radiotherapy (SBRT) cases. The current study uses direct and indirect DVH endpoints for plan quality evaluation, but the infrastructure proposed here applies to general outcome data as well. The authors expect forward evaluation together with intelligent update based on evidence-based learning, which will evolve the clinical practice for improved efficiency, consistency, and ultimately better treatment outcome.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2012

Dosimetric and deformation effects of image-guided interventions during stereotactic body radiation therapy of the prostate using an endorectal balloon

Purpose: During stereotactic body radiation therapy (SBRT) for the treatment of prostate cancer, an inflatable endorectal balloon (ERB) may be used to reduce motion of the target and reduce the dose to the posterior rectal wall. This work assessed the dosimetric impact of manual interventions on ERB position in patients receiving prostate SBRT and investigated the impact of ERB interventions on prostate shape. Methods: The data of seven consecutive patients receiving SBRT for the treatment of clinical stage T1cN0M0 prostate cancer enrolled in a multi-institutional, IRB-approved trial were analyzed. The SBRT dose was 50 Gy in five fractions to a planning target volume (PTV) that included the prostate (implanted with three fiducial markers) with a 3-5 mm margin. All plans were based on simulation images that included an ERB inflated with 60 cm{sup 3} of air. Daily kilovoltage cone-beam computed tomography (CBCT) imaging was performed to localize the PTV, and an automated fusion with the planning images yielded displacements required for PTV relocalization. When the ERB volume and/or position were judged to yield inaccurate repositioning, manual adjustment (ERB reinflation and/or repositioning) was performed. Based on all 59 CBCT image sets acquired, a deformable registration algorithm was used to determine the dose received by, displacement of, and deformation of the prostate, bladder (BLA), and anterior rectal wall (ARW). This dose tracking methodology was applied to images taken before and after manual adjustment of the ERB (intervention), and the delivered dose was compared to that which would have been delivered in the absence of intervention. Results: Interventions occurred in 24 out of 35 (69%) of the treated fractions. The direct effect of these interventions was an increase in the prostate radiation dose that included 95% of the PTV (D95) from 9.6 {+-} 1.0 to 10.0 {+-} 0.2 Gy (p = 0.06) and an increase in prostate coverage from 94.0% {+-} 8.5% to 97.8% {+-} 1.9% (p = 0.03). Additionally, ERB interventions reduced prostate deformation in the anterior-posterior (AP) direction, reduced errors in the sagittal rotation of the prostate, and increased the similarity in shape of the prostate to the radiotherapy plan (increased Dice coefficient from 0.76 {+-} 0.06 to 0.80 {+-} 0.04, p = 0.01). Postintervention decreases in prostate volume receiving less than the prescribed dose and decreases in the voxel-wise displacement of the prostate, bladder, and anterior rectal wall were observed, which resulted in improved dose-volume histogram (DVH) characteristics. Conclusions: Image-guided interventions in ERB volume and/or position during prostate SBRT were necessary to ensure the delivery of the dose distribution as planned. ERB interventions resulted in reductions in prostate deformations that would have prevented accurate localization of patient anatomy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

Quantifying the margin sharpness of lesions on radiological images for content-based image retrieval

Purpose: To develop a method to quantify the margin sharpness of lesions on CT and to evaluate it in simulations and CT scans of liver and lung lesions. Methods: The authors computed two attributes of margin sharpness: the intensity difference between a lesion and its surroundings, and the sharpness of the intensity transition across the lesion boundary. These two attributes were extracted from sigmoid curves fitted along lines automatically drawn orthogonal to the lesion margin. The authors then represented the margin characteristics for each lesion by a feature vector containing histograms of these parameters. The authors created 100 simulated CT scans of lesions over a range of intensity difference and margin sharpness, and used the concordance correlation between the known parameter and the corresponding computed feature as a measure of performance. The authors also evaluated their method in 79 liver lesions (44 patients: 23 M, 21 F, mean age 61) and 58 lung nodules (57 patients: 24 M, 33 F, mean age 66). The methodology presented takes into consideration the boundary of the liver and lung during feature extraction in clinical images to ensure that the margin feature do not get contaminated by anatomy other than the normal organ surrounding the lesions. For evaluation in these clinical images, the authors created subjective independent reference standards for pairwise margin sharpness similarity in the liver and lung cohorts, and compared rank orderings of similarity used using our sharpness feature to that expected from the reference standards using mean normalized discounted cumulative gain (NDCG) over all query images. In addition, the authors compared their proposed feature with two existing techniques for lesion margin characterization using the simulated and clinical datasets. The authors also evaluated the robustness of their features against variations in delineation of the lesion margin by simulating five types of deformations of the lesion margin. Equivalence across deformations was assessed using Schuirmann's paired two one-sided tests. Results: In simulated images, the concordance correlation between measured gradient and actual gradient was 0.994. The mean (s.d.) and standard deviation NDCG score for the retrieval of K images, K = 5, 10, and 15, were 84% (8%), 85% (7%), and 85% (7%) for CT images containing liver lesions, and 82% (7%), 84% (6%), and 85% (4%) for CT images containing lung nodules, respectively. The authors' proposed method outperformed the two existing margin characterization methods in average NDCG scores over all K, by 1.5% and 3% in datasets containing liver lesion, and 4.5% and 5% in datasets containing lung nodules. Equivalence testing showed that the authors' feature is more robust across all margin deformations (p < 0.05) than the two existing methods for margin sharpness characterization in both simulated and clinical datasets. Conclusions: The authors have described a new image feature to quantify the margin sharpness of lesions. It has strong correlation with known margin sharpness in simulated images and in clinical CT images containing liver lesions and lung nodules. This image feature has excellent performance for retrieving images with similar margin characteristics, suggesting potential utility, in conjunction with other lesion features, for content-based image retrieval applications.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

Reduction of prostate intrafraction motion using gas-release rectal balloons

Purpose: To analyze prostate intrafraction motion using both non-gas-release (NGR) and gas-release (GR) rectal balloons and to evaluate the ability of GR rectal balloons to reduce prostate intrafraction motion. Methods: Twenty-nine patients with NGR rectal balloons and 29 patients with GR balloons were randomly selected from prostate patients treated with proton therapy at University of Florida Proton Therapy Institute (Jacksonville, FL). Their pretreatment and post-treatment orthogonal radiographs were analyzed, and both pretreatment setup residual error and intrafraction-motion data were obtained. Population histograms of intrafraction motion were plotted for both types of balloons. Population planning target-volume (PTV) margins were calculated with the van Herk formula of 2.5{Sigma}+ 0.7{sigma} to account for setup residual errors and intrafraction motion errors. Results: Pretreatment and post-treatment radiographs indicated that the use of gas-release rectal balloons reduced prostate intrafraction motion along superior-inferior (SI) and anterior-posterior (AP) directions. Similar patient setup residual errors were exhibited for both types of balloons. Gas-release rectal balloons resulted in PTV margin reductions from 3.9 to 2.8 mm in the SI direction, 3.1 to 1.8 mm in the AP direction, and an increase from 1.9 to 2.1 mm in the left-right direction. Conclusions: Prostate intrafraction motion is an important uncertainty source in radiotherapy after image-guided patient setup with online corrections. Compared to non-gas-release rectal balloons, gas-release balloons can reduce prostate intrafraction motion in the SI and AP directions caused by gas buildup.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2012

Three-dimensional radiobiological dosimetry of kidneys for treatment planning in peptide receptor radionuclide therapy

Purpose: Peptide receptor radionuclide therapy (PRRT) delivers high absorbed doses to kidneys and may lead to permanent nephropathy. Reliable dosimetry of kidneys is thus critical for safe and effective PRRT. The aim of this work was to assess the feasibility of planning PRRT based on 3D radiobiological dosimetry (3D-RD) in order to optimize both the amount of activity to administer and the fractionation scheme, while limiting the absorbed dose and the biological effective dose (BED) to the renal cortex. Methods: Planar and SPECT data were available for a patient examined with {sup 111}In-DTPA-octreotide at 0.5 (planar only), 4, 24, and 48 h post-injection. Absorbed dose and BED distributions were calculated for common therapeutic radionuclides, i.e., {sup 111}In, {sup 90}Y and {sup 177}Lu, using the 3D-RD methodology. Dose-volume histograms were computed and mean absorbed doses to kidneys, renal cortices, and medullae were compared with results obtained using the MIRD schema (S-values) with the multiregion kidney dosimetry model. Two different treatment planning approaches based on (1) the fixed absorbed dose to the cortex and (2) the fixed BED to the cortex were then considered to optimize the activity to administer by varying the number of fractions. Results: Mean absorbed doses calculated with 3D-RD were in good agreement with those obtained with S-value-based SPECT dosimetry for {sup 90}Y and {sup 177}Lu. Nevertheless, for {sup 111}In, differences of 14% and 22% were found for the whole kidneys and the cortex, respectively. Moreover, the authors found that planar-based dosimetry systematically underestimates the absorbed dose in comparison with SPECT-based methods, up to 32%. Regarding the 3D-RD-based treatment planning using a fixed BED constraint to the renal cortex, the optimal number of fractions was found to be 3 or 4, depending on the radionuclide administered and the value of the fixed BED. Cumulative activities obtained using the proposed simulated treatment planning are compatible with real activities administered to patients in PRRT. Conclusions: The 3D-RD treatment planning approach based on the fixed BED was found to be the method of choice for clinical implementation in PRRT by providing realistic activity to administer and number of cycles. While dividing the activity in several cycles is important to reduce renal toxicity, the clinical outcome of fractionated PRRT should be investigated in the future.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

A digitally reconstructed radiograph algorithm calculated from first principles

Purpose: To develop an algorithm for computing realistic digitally reconstructed radiographs (DRRs) that match real cone-beam CT (CBCT) projections with no artificial adjustments. Methods: The authors used measured attenuation data from cone-beam CT projection radiographs of different materials to obtain a function to convert CT number to linear attenuation coefficient (LAC). The effects of scatter, beam hardening, and veiling glare were first removed from the attenuation data. Using this conversion function the authors calculated the line integral of LAC through a CT along rays connecting the radiation source and detector pixels with a ray-tracing algorithm, producing raw DRRs. The effects of scatter, beam hardening, and veiling glare were then included in the DRRs through postprocessing. Results: The authors compared actual CBCT projections to DRRs produced with all corrections (scatter, beam hardening, and veiling glare) and to uncorrected DRRs. Algorithm accuracy was assessed through visual comparison of projections and DRRs, pixel intensity comparisons, intensity histogram comparisons, and correlation plots of DRR-to-projection pixel intensities. In general, the fully corrected algorithm provided a small but nontrivial improvement in accuracy over the uncorrected algorithm. The authors also investigated both measurement- and computation-based methods for determining the beam hardening correction, and found the computation-based method to be superior, as it accounted for nonuniform bowtie filter thickness. The authors benchmarked the algorithm for speed and found that it produced DRRs in about 0.35 s for full detector and CT resolution at a ray step-size of 0.5 mm. Conclusions: The authors have demonstrated a DRR algorithm calculated from first principles that accounts for scatter, beam hardening, and veiling glare in order to produce accurate DRRs. The algorithm is computationally efficient, making it a good candidate for iterative CT reconstruction techniques that require a data fidelity term based on the matching of DRRs and projections.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Dosimetric accuracy of a deterministic radiation transport based {sup 192}Ir brachytherapy treatment planning system. Part III. Comparison to Monte Carlo simulation in voxelized anatomical computational models

Purpose: To compare TG43-based and Acuros deterministic radiation transport-based calculations of the BrachyVision treatment planning system (TPS) with corresponding Monte Carlo (MC) simulation results in heterogeneous patient geometries, in order to validate Acuros and quantify the accuracy improvement it marks relative to TG43. Methods: Dosimetric comparisons in the form of isodose lines, percentage dose difference maps, and dose volume histogram results were performed for two voxelized mathematical models resembling an esophageal and a breast brachytherapy patient, as well as an actual breast brachytherapy patient model. The mathematical models were converted to digital imaging and communications in medicine (DICOM) image series for input to the TPS. The MCNP5 v.1.40 general-purpose simulation code input files for each model were prepared using information derived from the corresponding DICOM RT exports from the TPS. Results: Comparisons of MC and TG43 results in all models showed significant differences, as reported previously in the literature and expected from the inability of the TG43 based algorithm to account for heterogeneities and model specific scatter conditions. A close agreement was observed between MC and Acuros results in all models except for a limited number of points that lay in the penumbra of perfectly shaped structures in the esophageal model, or at distances very close to the catheters in all models. Conclusions: Acuros marks a significant dosimetry improvement relative to TG43. The assessment of the clinical significance of this accuracy improvement requires further work. Mathematical patient equivalent models and models prepared from actual patient CT series are useful complementary tools in the methodology outlined in this series of works for the benchmarking of any advanced dose calculation algorithm beyond TG43.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

PTV-based IMPT optimization incorporating planning risk volumes vs robust optimization

Purpose: Robust optimization leads to intensity-modulated proton therapy (IMPT) plans that are less sensitive to uncertainties and superior in terms of organs-at-risk (OARs) sparing, target dose coverage, and homogeneity compared to planning target volume (PTV)-based optimized plans. Robust optimization incorporates setup and range uncertainties, which implicitly adds margins to both targets and OARs and is also able to compensate for perturbations in dose distributions within targets and OARs caused by uncertainties. In contrast, the traditional PTV-based optimization considers only setup uncertainties and adds a margin only to targets but no margins to the OARs. It also ignores range uncertainty. The purpose of this work is to determine if robustly optimized plans are superior to PTV-based plans simply because the latter do not assign margins to OARs during optimization. Methods: The authors retrospectively selected from their institutional database five patients with head and neck (H and N) cancer and one with prostate cancer for this analysis. Using their original images and prescriptions, the authors created new IMPT plans using three methods: PTV-based optimization, optimization based on the PTV and planning risk volumes (PRVs) (i.e., 'PTV+PRV-based optimization'), and robust optimization using the 'worst-case' dose distribution. The PRVs were generated by uniformly expanding OARs by 3 mm for the H and N cases and 5 mm for the prostate case. The dose-volume histograms (DVHs) from the worst-case dose distributions were used to assess and compare plan quality. Families of DVHs for each uncertainty for all structures of interest were plotted along with the nominal DVHs. The width of the 'bands' of DVHs was used to quantify the plan sensitivity to uncertainty. Results: Compared with conventional PTV-based and PTV+PRV-based planning, robust optimization led to a smaller bandwidth for the targets in the face of uncertainties {l_brace}clinical target volume [CTV] bandwidth: 0.59 [robust], 3.53 [PTV+PRV], and 3.53 [PTV] Gy (RBE){r_brace}. It also resulted in higher doses to 95% of the CTV {l_brace}D{sub 95%}: 60.8 [robust] vs 59.3 [PTV+PRV] vs 59.6 [PTV] Gy (RBE){r_brace}, smaller D{sub 5%} (doses to 5% of the CTV) minus D{sub 95%} {l_brace}D{sub 5%}- D{sub 95%}: 13.2 [robust] vs 17.5 [PTV+PRV] vs 17.2 [PTV] Gy (RBE){r_brace}. At the same time, the robust optimization method irradiated OARs less {l_brace}maximum dose to 1 cm{sup 3} of the brainstem: 48.3 [robust] vs 48.8 [PTV+PRV] vs 51.2 [PTV] Gy (RBE); mean dose to the oral cavity: 22.3 [robust] vs 22.9 [PTV+PRV] vs 26.1 [PTV] Gy (RBE); maximum dose to 1% of the normal brain: 66.0 [robust] vs 68.0 [PTV+PRV] vs 69.3 [PTV] Gy (RBE){r_brace}. Conclusions: For H and N cases studied, OAR sparing in PTV+PRV-based optimization was inferior compared to robust optimization but was superior compared to PTV-based optimization; however, target dose robustness and homogeneity were comparable in the PTV+PRV-based and PTV-based optimizations. The same pattern held for the prostate case. The authors' data suggest that the superiority of robust optimization is not due simply to its inclusion of margins for OARs, but that this is due mainly to the ability of robust optimization to compensate for perturbations in dose distributions within target volumes and normal tissues caused by uncertainties.

60 APPLIED LIFE SCIENCES↗