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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Cheetah : software for high-throughput reduction and analysis of serial femtosecond X-ray diffraction data

The emerging technique of serial X-ray diffraction, in which diffraction data are collected from samples flowing across a pulsed X-ray source at repetition rates of 100 Hz or higher, has necessitated the development of new software in order to handle the large data volumes produced. Sorting of data according to different criteria and rapid filtering of events to retain only diffraction patterns of interest results in significant reductions in data volume, thereby simplifying subsequent data analysis and management tasks. Meanwhile the generation of reduced data in the form of virtual powder patterns, radial stacks, histograms and other meta data creates data set summaries for analysis and overall experiment evaluation. Rapid data reduction early in the analysis pipeline is proving to be an essential first step in serial imaging experiments, prompting the authors to make the tool described in this article available to the general community. Originally developed for experiments at X-ray free-electron lasers, the software is based on a modular facility-independent library to promote portability between different experiments and is available under version 3 or later of the GNU General Public License.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Diffraction pattern simulation of cellulose fibrils using distributed and quantized pair distances

Intensity simulation of X-ray scattering from large twisted cellulose molecular fibrils is important in understanding the impact of chemical or physical treatments on structural properties such as twisting or coiling. This paper describes a highly efficient method for the simulation of X-ray diffraction patterns from complex fibrils using atom-type-specific pair-distance quantization. Pair distances are sorted into arrays which are labelled by atom type. Histograms of pair distances in each array are computed and binned and the resulting population distributions are used to represent the whole pair-distance data set. These quantized pair-distance arrays are used with a modified and vectorized Debye formula to simulate diffraction patterns. This approach utilizes fewer pair distances in each iteration, and atomic scattering factors are moved outside the iteration since the arrays are labelled by atom type. As a result, this algorithm significantly reduces the computation time while maintaining the accuracy of diffraction pattern simulation, making possible the simulation of diffraction patterns from large twisted fibrils in a relatively short period of time, as is required for model testing and refinement.

09 BIOMASS FUELS↗
DOE OSTI2022

Efficient data reduction for time-of-flight neutron scattering experiments on single crystals

Event-mode data collection presents remarkable new opportunities for time-of-flight neutron scattering studies of collective excitations, diffuse scattering from short-range atomic and magnetic structures, and neutron crystallography. In these experiments, large volumes of the reciprocal space are surveyed, often using different wavelengths and counting times. These data then have to be added together, with accurate propagation of the counting errors. This paper presents a statistically correct way of adding and histogramming the data for single-crystal time-of-flight neutron scattering measurements. In order to gain a broader community acceptance, particular attention is given to improving the efficiency of calculations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Hard X-ray self-seeding commissioning at PAL-XFEL

A wake monochromator based on a large-area diamond single crystal for hard X-ray self-seeding has been successfully installed and commissioned in the hard X-ray free-electron laser (FEL) at the Pohang Accelerator Laboratory with international collaboration. For this commissioning, the self-seeding was demonstrated with a low bunch charge (40 pC) and the nominal bunch charge (180 pC) of self-amplified spontaneous emission (SASE) operation. The FEL pulse lengths were estimated as 7 fs and 29.5 fs, respectively. In both cases, the average spectral brightness increased by more than three times compared with the SASE mode. The self-seeding experiment was demonstrated for the first time using a crystal with a thickness of 30 µm, and a narrow bandwidth of 0.22 eV (full width at half-maximum) was obtained at 8.3 keV, which confirmed the functionality of a crystal with such a small thickness. In the nominal bunch-charge self-seeding experiment, the histogram of the intensity integrated over a 1 eV bandwidth showed a well defined Gaussian profile, which is evidence of the saturated FEL and a minimal electron-energy jitter (~1.2 × 10 –4 ) effect. Here, the corresponding low photon-energy jitter (~2.4 × 10 –4 ) of the SASE FEL pulse, which is two times lower than the Pierce parameter, enabled the seeding power to be maximized by maintaining the spectral overlap between SASE FEL gain and the monochromator.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

MemGaze: Rapid and Effective Load-Level Memory Trace Analysis

A major challenge of memory analysis tools is combining high-resolution analysis and low overhead measurement. Currently, hardware/software-based analysis of load-level sequences incurs time slowdowns of O(100×). We present MemGaze, a tool for low-overhead, high-resolution memory analysis. MemGaze uses Intel’s Processor Tracing (PT) instruction ptwrite to collect sampled and compressed memory address traces for load-level, sequence-aware analysis of data reuse. We describe multi-resolution analysis for locations vs. operations, accesses vs. spatio-temporal reuse, and reuse (distance, rate, volume) vs. access patterns. Both trace size and resolution are controllable. We use MemGaze to elucidate the memory effects of different data structures and algorithms. For sampled traces that are ˜1% of a full one, analysis metrics have 1-25% MAPE for histograms of varying dynamic sequence lengths. With current suboptimal kernel support (PT runs continuously), MemGaze’s time overhead is typically 10–95%; 7× at worst. However, when PT runs only during samples, overhead is 10–35% on memory intensive regions and correlates with executed ptwrites.

Kilic, Ozgur O.↗
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 OSTI2014

Toward adaptive radiotherapy for head and neck patients: Feasibility study on using CT-to-CBCT deformable registration for “dose of the day” calculations

Purpose: The aim of this study was to evaluate the appropriateness of using computed tomography (CT) to cone-beam CT (CBCT) deformable image registration (DIR) for the application of calculating the “dose of the day” received by a head and neck patient. Methods: NiftyReg is an open-source registration package implemented in our institution. The affine registration uses a Block Matching-based approach, while the deformable registration is a GPU implementation of the popular B-spline Free Form Deformation algorithm. Two independent tests were performed to assess the suitability of our registrations methodology for “dose of the day” calculations in a deformed CT. A geometric evaluation was performed to assess the ability of the DIR method to map identical structures between the CT and CBCT datasets. Features delineated in the planning CT were warped and compared with features manually drawn on the CBCT. The authors computed the dice similarity coefficient (DSC), distance transformation, and centre of mass distance between features. A dosimetric evaluation was performed to evaluate the clinical significance of the registrations errors in the application proposed and to identify the limitations of the approximations used. Dose calculations for the same intensity-modulated radiation therapy plan on the deformed CT and replan CT were compared. Dose distributions were compared in terms of dose differences (DD), gamma analysis, target coverage, and dose volume histograms (DVHs). Doses calculated in a rigidly aligned CT and directly in an extended CBCT were also evaluated. Results: A mean value of 0.850 in DSC was achieved in overlap between manually delineated and warped features, with the distance between surfaces being less than 2 mm on over 90% of the pixels. Deformable registration was clearly superior to rigid registration in mapping identical structures between the two datasets. The dose recalculated in the deformed CT is a good match to the dose calculated on a replan CT. The DD is smaller than 2% of the prescribed dose on 90% of the body's voxels and it passes a 2% and 2 mm gamma-test on over 95% of the voxels. Target coverage similarity was assessed in terms of the 95%-isodose volumes. A mean value of 0.962 was obtained for the DSC, while the distance between surfaces is less than 2 mm in 95.4% of the pixels. The method proposed provided adequate dose estimation, closer to the gold standard than the other two approaches. Differences in DVH curves were mainly due to differences in the OARs definition (manual vs warped) and not due to differences in dose estimation (dose calculated in replan CT vs dose calculated in deformed CT). Conclusions: Deforming a planning CT to match a daily CBCT provides the tools needed for the calculation of the “dose of the day” without the need to acquire a new CT. The initial clinical application of our method will be weekly offline calculations of the “dose of the day,” and use this information to inform adaptive radiotherapy (ART). The work here presented is a first step into a full implementation of a “dose-driven” online ART.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Dosimetric comparison of flattened and unflattened beams for stereotactic ablative radiotherapy of stage I non-small cell lung cancer

Purpose: To compare contribution and accuracy of delivery for two flattening filter free (FFF) beams of the nominal energy 6 and 10 MV and a 6 MV flattened beam for early stage lung cancer. Methods: For each of 11 patients with stage I nonsmall cell lung cancer three volumetric modulated arc therapy plans were prepared utilizing a 6 MV flattened photon beam (X6FF) and two nonflattened beams of nominal energy 6 and 10 MV (X6FFF, X10FFF). Optimization constraints were set to produce dose distributions that meet the criteria of the RTOG-0915 protocol. The radiation schedule used for plan comparison in all patients was 50 Gy in five fractions. Dosimetric parameters of planning target volume (PTV) and organs-at-risk and delivery times were assessed and compared. All plans were subject to verification using Delta{sup 4} unit (Scandidos, Sweden) and absolutely calibrated gafchromic films in a thorax phantom. Results: All plans had a qualitatively comparable outcome. Obtained dose distributions were conformal (CI < 1.17) and exhibited a steep dose fall-off outside the PTV. The ratio of monitor units for FFF versus FF plans in the authors' study ranged from 0.95 to 1.21 and from 0.93 to 1.25 for X6FFF/X6FF and X10FFF/X6FF comparisons, respectively. The ratio systematically increased with increasing size of the PTV (up to +25% for 150 cm{sup 3} PTV). Yet the integral dose to healthy tissue did not follow this trend. Comparison of cumulative dose volume histograms for a patient's body showed that X6FFF plans exhibit improved conformity and reduced the volume of tissue that received more than 50% of the prescription dose. Parameters related to dose gradient showed statistically significant improvement. CI{sub 50%}, CI{sub 60%}, CI{sub 80%}, and CI{sub 100%} were on average reduced by 4.6% (p < 0.001), 4.6% (p = 0.002), 3.1% (p = 0.002), and 1.2% (p = 0.039), respectively. Gradient measure was on average reduced by 4.2% (p < 0.001). Due to dose reduction in the surrounding lung tissue, the V{sub 20} {sub Gy} and V{sub 12.5} {sub Gy} were reduced by 5.5% (p = 0.002) and 4.5% (p < 0.001). These dosimetric improvements in the fall-off were not observed for the X10FFF plans. Differences in sparing of normal tissues were not found to be statistically significant for either of the two FFF beams. Mean beam-on times were 111 s (2SD = 11 s) for X10FFF, 128 s (2SD = 19 s) for X6FFF, and X6FF plans required on average 269 s (2SD = 71 s). While the mean dose rate was 1555 ± 264 and 1368 ± 63 MU/min, for X10FFF and X6FFF, plans using the conventional X6FF were delivered with the constant maximum dose rate of 600 MU/min. Verification of all plans showed acceptable and comparable results for all plans in homogeneous as well as heterogeneous phantoms. Mean GS (3%, 2 mm) using the Delta{sup 4} phantom were 98.9% (2SD = 3.2%), 99.2% (2SD = 2.3%), and 99.2% (2SD = 2.3%) for X6FFF, X6FF, and X10FFF modalities. Verification using a thorax phantom showed GS > 98% in all cases. Conclusions: The use of FFF beams for stereotactic radiation therapy of nonsmall cell lung cancer patients yielded dose distributions qualitatively comparable to flattened beams and significantly reduced treatment delivery time. Utilizing the X6FFF beam improved conformity of dose distribution. On the other hand, X10FFF beam offered a slight improvement in treatment efficiency, and lower skin and peripheral dose. All effects were relatively small.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Beam geometry selection using sequential beam addition

Purpose: The selection of optimal beam geometry has been of interest since the inception of conformal radiotherapy. The authors report on sequential beam addition, a simple beam geometry selection method, for intensity modulated radiation therapy. Methods: The sequential beam addition algorithm (SBA) requires definition of an objective function (score) and a set of candidate beam geometries (pool). In the first iteration, the optimal score is determined for each beam in the pool and the beam with the best score selected. In the next iteration, the optimal score is calculated for each beam remaining in the pool combined with the beam selected in the first iteration, and the best scoring beam is selected. The process is repeated until the desired number of beams is reached. The authors selected three treatment sites, breast, lung, and brain, and determined beam arrangements for up to 11 beams from a pool comprised of 25 equiangular transverse beams. For the brain, arrangements were additionally selected from a pool of 22 noncoplanar beams. Scores were determined for geometries comprised equiangular transverse beams (EQA), as well as two tangential beams for the breast case. Results: In all cases, SBA resulted in scores superior to EQA. The breast case had the strongest dependence on beam geometry, for which only the 7-beam EQA geometry had a score better than the two tangential beams, whereas all SBA geometries with more than two beams were superior. In the lung case, EQA and SBA scores monotonically improved with increasing number of beams; however, SBA required fewer beams to achieve scores equivalent to EQA. For the brain case, SBA with a coplanar pool was equivalent to EQA, while the noncoplanar pool resulted in slightly better scores; however, the dose-volume histograms demonstrated that the differences were not clinically significant. Conclusions: For situations in which beam geometry has a significant effect on the objective function, SBA can identify arrangements equivalent to equiangular geometries but using fewer beams. Furthermore, SBA provides the value of the objective function as the number of beams is increased, allowing the planner to select the minimal beam number that achieves the clinical goals. The method is simple to implement and could readily be incorporated into an existing optimization system.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Helical tomotherapy with dynamic running-start-stop delivery compared to conventional tomotherapy delivery

Purpose: Despite superior target dose uniformity, helical tomotherapy{sup ®} (HT) may involve a trade-off between longitudinal dose conformity and beam-on time (BOT), due to the limitation of only three available jaw sizes with the conventional HT (1.0, 2.5, and 5.0 cm). The recently introduced dynamic running-start-stop (RSS) delivery allows smaller jaw opening at the superior and inferior ends of the target when a sharp penumbra is needed. This study compared the dosimetric performance of RSS delivery with the fixed jaw HT delivery. Methods: Twenty patient cases were selected and deidentified prior to treatment planning, including 16 common clinical cases (brain, head and neck (HN), lung, and prostate) and four special cases of whole brain with hippocampus avoidance (WBHA) that require a high degree of dose modulation. HT plans were generated for common clinical cases using the fixed 2.5 cm jaw width (HT2.5) and WBHA cases using 1.0 cm (HT1.0). The jaw widths for RSS were preset with a larger size (RSS5.0 vs HT2.5 and RSS2.5 vs HT1.0). Both delivery techniques were planned based on identical contours, prescriptions, and planning objectives. Dose indices for targets and critical organs were compared using dose-volume histograms, BOT, and monitor units. Results: The average BOT was reduced from 4.8 min with HT2.5 to 2.5 min with RSS5.0. Target dose homogeneity with RSS5.0 was shown comparable to HT2.5 for common clinical sites. Superior normal tissue sparing was observed in RSS5.0 for optic nerves and optic chiasm in brain and HN cases. RSS5.0 demonstrated improved dose sparing for cord and esophagus in lung cases, as well as penile bulb in prostate cases. The mean body dose was comparable for both techniques. For the WBHA cases, the target homogeneity was significantly degraded in RSS2.5 without distinct dose sparing for hippocampus, compared to HT1.0. Conclusions: Compared to the fixed jaw HT delivery, RSS combined with a larger jaw width provides faster treatment delivery and improved cranial-caudal target dose conformity. The target coverage achieved by RSS with a large jaw width is comparable to the fixed jaw HT delivery for common cancer sites, but may deteriorate for cases where complex geometry is present in the middle part of the target.

62 RADIOLOGY AND NUCLEAR MEDICINE↗