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DOE OSTI2021

Distributed Fiber Sensors With High Spatial Resolution in Extreme Radiation Environments in Nuclear Reactor Cores

This paper is a comprehensive experimental report on the neutron radiation effects of distributed optical fiber sensors with enhanced Rayleigh scattering profiles in an in-pile environment. Femtosecond laser direct writing was used to inscribe Type-II modifications in standard telecom fibers and radiation-hardened fibers with fluorine-doped cores. Rayleigh backscattering signals were enhanced for continuous 1.5 m. In-pile lead-out sensors tests were carried out at the MIT Research Reactor for two months, which was operated at a nominal power of 5.7 MW with fast neutron (>0.1 MeV) flux of 1.29 × 1014 n/cm2/s and an in-core temperature of up to 560°C. Using the Optical Frequency Domain Reflectometry technique, the backscattering profiles of fiber sensors were interrogated with a 3-cm spatial resolution to monitor the temperature profile of the reactor. Results show that laser inscribed Type-II modifications in the form of nanogratings are highly stable against extreme temperature and ionizing radiation. Both standard telecom fibers and radiation-hardened fibers with laser-enhanced Rayleigh profiles can continuously perform distributed temperature measurements over the entire duration of the in-pile testing. Temperature coefficients of sensors and spectral shift quality were studied as functions of total radiation fluence. To the best of our knowledge, we present for the first time, the temperature profile of an operating nuclear reactor core with 3-cm spatial resolution, enabled by distributed fiber sensors with laser-enhanced Rayleigh scattering profiles. The high spatial resolution measurements can provide valuable data for the design and validation of digital twin and virtual reality of nuclear energy systems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2013

A lightweight I/O scheme to facilitate spatial and temporal queries of scientific data analytics

In the era of petascale computing, more scientific applications are being deployed on leadership scale computing platforms to enhance the scientific productivity. Many I/O techniques have been designed to address the growing I/O bottleneck on large-scale systems by handling massive scientific data in a holistic manner. While such techniques have been leveraged in a wide range of applications, they have not been shown as adequate for many mission critical applications, particularly in data postprocessing stage. One of the examples is that some scientific applications generate datasets composed of a vast amount of small data elements that are organized along many spatial and temporal dimensions but require sophisticated data analytics on one or more dimensions. Including such dimensional knowledge into data organization can be beneficial to the efficiency of data post-processing, which is often missing from exiting I/O techniques. In this study, we propose a novel I/O scheme named STAR (Spatial and Temporal AggRegation) to enable high performance data queries for scientific analytics. STAR is able to dive into the massive data, identify the spatial and temporal relationships among data variables, and accordingly organize them into an optimized multi-dimensional data structure before storing to the storage. This technique not only facilitates the common access patterns of data analytics, but also further reduces the application turnaround time. In particular, STAR is able to enable efficient data queries along the time dimension, a practice common in scientific analytics but not yet supported by existing I/O techniques. In our case study with a critical climate modeling application GEOS-5, the experimental results on Jaguar supercomputer demonstrate an improvement up to 73 times for the read performance compared to the original I/O method.

Tian, Yuan↗

DOE OSTI2015

Spectral and Spatial Classification of Hyperspectral Images Based on ICA and Reduced Morphological Attribute Profiles

The availability of hyperspectral images with improved spectral and spatial resolutions provides the opportunity to obtain accurate land-cover classification. In this paper, a novel methodology that combines spectral and spatial information for supervised hyperspectral image classification is proposed. A feature reduction strategy based on independent component analysis is the main core of the spectral analysis, where the exploitation of prior information coupled to the evaluation of the reconstruction error assures the identification of the best class-informative subset of independent components. Reduced attribute profiles (APs), which are designed to address well-known issues related to information redundancy that affect the common morphological APs, are then employed for the modeling and fusion of the contextual information. Four real hyperspectral data sets, which are characterized by different spectral and spatial resolutions with a variety of scene typologies (urban, agriculture areas), have been used for assessing the accuracy and generalization capabilities of the proposed methodology. The obtained results demonstrate the classification effectiveness of the proposed approach in all different scene typologies, with respect to other state-of-the-art techniques.

42 ENGINEERING↗

DOE OSTI2026

Secure Wireless Communication Using Distributed Coherent Transmission and Spatial Signal Decomposition

We present a new approach to secure wireless communications using coherent distributed transmission of signals that are spatially decomposed between a two-element distributed antenna array. High-accuracy distributed coordination of microwave wireless systems supports the ability to transmit different parts of a signal from separate transmitters such that they combine coherently at a designated destination. In this article, we explore this concept using a two-element coherent distributed phased array where each of the two transmitters sends a separate component of a communication signal, where each symbol is decomposed into a sum of two pseudorandom signal vectors, the coherent summation of which yields the intended symbol. By directing the transmission to an intended receiver using distributed beamforming, the summation of the two vector components is largely confined to a spatial region at the destination receiver. We implement the technique in a $50−λ$ array operating at 3 GHz. We evaluate the symbol error rate (SER) in 2-D space through simulation and measurement, showing that the approach yields a spatially confined secure region where the information is recoverable (i.e., the received signal has low SER), and outside of which the information is unrecoverable (high SER). The proposed system is also compared against a traditional beamforming system where each node sends the same data. We validate experimentally that our approach achieves a low SER of 0.0082 at broadside and an SER above 0.25 at all other locations compared to a traditional beamforming approach that achieves a SER of 0 at all locations measured.

Engineering - Electronic and electrical engineerin↗

DOE OSTI2021

Deep Cellular Recurrent Network for Efficient Analysis of Time-Series Data With Spatial Information

Efficient processing of large-scale time series data is an intricate problem in machine learning. Conventional sensor signal processing pipelines with hand engineered feature extraction often involve huge computational cost with high dimensional data. Deep recurrent neural networks have shown promise in automated feature learning for improved time-series processing. However, generic deep recurrent models grow in scale and depth with increased complexity of the data. This is particularly challenging in presence of high dimensional data with temporal and spatial characteristics. Consequently, this work proposes a novel deep cellular recurrent neural network (DCRNN) architecture to efficiently process complex multi-dimensional time series data with spatial information. Here, the cellular recurrent architecture in the proposed model allows for location-aware synchronous processing of time series data from spatially distributed sensor signal sources. Extensive trainable parameter sharing due to cellularity in the proposed architecture ensures efficiency in the use of recurrent processing units with high-dimensional inputs. This study also investigates the versatility of the proposed DCRNN model for classification of multi-class time series data from different application domains. Consequently, the proposed DCRNN architecture is evaluated using two time-series datasets: a multichannel scalp EEG dataset for seizure detection, and a machine fault detection dataset obtained in-house. The results suggest that the proposed architecture achieves state-of-the-art performance while utilizing substantially less trainable parameters when compared to comparable methods in the literature.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

Spatial-Temporal Synchrophasor Data Characterization and Analytics in Smart Grid Fault Detection, Identification, and Impact Causal Analysis

An approach of big data characterization for smart grids (SGs) and its applications in fault detection, identification, and causal impact analysis is proposed in this paper, which aims to provide substantial data volume reduction while keeping comprehensive information from synchrophasor measurements in spatial and temporal domains. Especially, based on secondary voltage control (SVC) and local SG observation algorithm, a two-layer dynamic optimal synchrophasor measurement devices selection algorithm (OSMDSA) is proposed to determine SVC zones, their corresponding pilot buses, and the optimal synchrophasor measurement devices. Combining the two-layer dynamic OSMDSA and matching pursuit decomposition, the synchrophasor data is completely characterized in the spatial-temporal domain. To demonstrate the effectiveness of the proposed characterization approach, SG situational awareness is investigated based on hidden Markov model based fault detection and identification using the spatial-temporal characteristics generated from the reduced data. To identify the major impact buses, the weighted Granger causality for SGs is proposed to investigate the causal relationship of buses during system disturbance. The IEEE 39-bus system and IEEE 118-bus system are employed to validate and evaluate the proposed approach.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

MAGIC: M arching Cubes Isosurface Uncertainty Visualization for G auss i an Uncertain Data With Spatial C orrelation

Here, in this paper, we study the propagation of data uncertainty through the marching cubes algorithm for isosurface visualization for correlated uncertain data. Consideration of correlation has been shown paramount for avoiding errors in uncertainty quantification and visualization in multiple prior studies. Although the problem of isosurface uncertainty with spatial data correlation has been previously addressed, there are two major limitations to prior treatments. First, there are no analytical formulations for uncertainty quantification of isosurfaces when the data uncertainty is characterized by a Gaussian distribution with spatial correlation. Second, as a consequence of the lack of analytical formulations,existing techniques resort to a Monte Carlo sampling approach, which is expensive and difficult to integrate into visualization tools. To address these limitations, we present a closed-form framework to efficiently derive uncertainty in marching cubes level-sets for Gaussian uncertain data with spatial correlation (MAGIC). To derive closed-form solutions, we leverage the Hinkley's derivation on the ratio of Gaussian distributions. With our analytical framework, we achieve a significant speed-up and enhanced accuracy of uncertainty quantification over classical Monte Carlo methods. We further accelerate our analytical solutions using many-core processors to achieve speed-ups up to 585× and integrability with production visualization tools for broader impact. We demonstrate the effectiveness of our correlation-aware uncertainty framework through experiments on meteorology, urban flow, and astrophysics simulation datasets.

Gaussian↗

DOE OSTI2022

Genotype–environment associations across spatial scales reveal the importance of putative adaptive genetic variation in divergence

Abstract Identifying areas of high evolutionary potential is a judicious strategy for developing conservation priorities in the face of environmental change. For wide‐ranging species occupying heterogeneous environments, the evolutionary forces that shape distinct populations can vary spatially. Here, we investigate patterns of genomic variation and genotype–environment associations in the hermit thrush ( Catharus guttatus ), a North American songbird, at broad (across the breeding range) and narrow spatial scales (at a hybrid zone). We begin by building a genoscape or map of genetic variation across the breeding range and find five distinct genetic clusters within the species, with the greatest variation occurring in the western portion of the range. Genotype–environment association analyses indicate higher allelic turnover in the west than in the east, with measures of temperature surfacing as key predictors of putative adaptive genomic variation rangewide. Since broad patterns detected across a species' range represent the aggregate of many locally adapted populations, we investigate whether our broadscale analysis is consistent with a finer scale analysis. We find that top rangewide temperature‐associated loci vary in their clinal patterns (e.g., steep clines vs. fixed allele frequencies) across a hybrid zone in British Columbia, suggesting that the environmental predictors and the associated candidate loci identified in the rangewide analysis are of variable importance in this particular region. However, two candidate loci exhibit strong concordance with the temperature gradient in British Columbia, suggesting a potential role for temperature‐related barriers to gene flow and/or temperature‐driven ecological selection in maintaining putative local adaptation. This study demonstrates how patterns identified at the broad (macrogeographic) scale can be validated by investigating genotype–environment correlations at the local (microgeographic) scale. Furthermore, our results highlight the importance of considering the spatial distribution of putative adaptive variation when assessing population‐level sensitivity to climate change and other stressors.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Spatially Resolved Characterisation of Low Mass Fraction Uranium Glass Working Reference Materials

Here, we present the results of a study to generate reference glasses that reflect an environment analogous to historic nuclear fallout samples of interest for post-detonation nuclear forensics. The glasses were generated by melting and then quenching SiO 2 , Al 2 O 3 and CaCO 3 powders. Two suites of glasses with three distinct U isotopic ratios were successfully made with enrichments in the 235 U isotope (~ natural [0.72%], ~ 53% and 94%), but the bulk elemental data showed heterogeneity (~ 10% RSD) with U mass fractions ranging from 331.47 to 373.63 μg g -1 . Spatially resolved U isotopic measurements were performed using three mass spectrometry techniques (secondary ion mass spectrometry-single stage accelerator mass spectrometry [SIMS-SSAMS], large geometry [LG] - SIMS, and laser ablation-inductively coupled plasma-mass spectrometry [LA-ICP-MS]) across five National Laboratories. The results showed good agreement with the bulk U isotopic data for the low, medium, and high U mass fractions. We conclude that despite elemental heterogeneity, these samples can serve as useful working reference materials for spatially resolved nuclear fallout analyses, as well as for other related spatially resolved analyses.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Relationship between surface μ‐roughness and interface slurry particle spatial distribution during glass polishing

Abstract During optical glass polishing, a number of interactions between the workpiece (i.e., glass), polishing slurry, and pad can influence the resulting workpiece roughness at different spatial scale lengths. In our previous studies, the particle size distribution of the slurry, the pad topography, and the amount of material removed by a single particle on the workpiece were shown to strongly correlate with roughness at AFM scale lengths (nm‐μm) and weakly at μ‐roughness scale lengths (μm‐mm). In this study, the polishing slurry pH and the generation of glass removal products are shown to influence the slurry particle spatial and height distribution at the polishing interface and the resulting μ‐roughness of the glass workpiece. A series of fused silica and phosphate glass samples were polished with various ceria and colloidal silica slurries over a range of slurry pH , and the resulting AFM roughness and μ‐roughness were measured. The AFM roughness was largely invariant with pH , suggesting that the removal function of a single particle is unchanged with pH . However, the μ‐roughness changed significantly, increasing linearly with pH for phosphate glass and having a maximum at an intermediate pH for fused silica. In addition, the spatial and height distribution of slurry particles on the pad (as measured by laser confocal microscopy) was determined to be distinctly different at low and high pH during phosphate glass polishing. Also, the zeta potential as a function of pH was measured for the workpiece, slurry, and pad with and without surrogate glass products (K 3 PO 4 for phosphate glass and Si( OH ) 4 for silica) to assess the role of interfacial charge during polishing. The addition of K 3 PO 4 significantly raised the zeta potential, whereas addition of Si( OH ) 4 had little effect on the zeta potential. An electrostatic DLVO three‐body force model, using the measured zeta potentials, was used to calculate the particle–particle, particle–workpiece, and particle–pad attractive and repulsive forces as a function of pH and the incorporation of glass products at the interface. The model predicted an increase in particle–pad attraction with an increase in pH and phosphate glass products consistent with the measured slurry distribution on the pads during phosphate glass polishing. Finally, a slurry “island” distribution gap ( IDG ) model has been formulated which utilizes the measured interface slurry distributions and a load balance to determine the interface gap, the contact area fraction, and the load on each slurry “island”. The IDG model was then used to simulate the workpiece surface topography and μ‐roughness; the results show an increase in roughness with pH similar to that observed experimentally.

Suratwala, Tayyab↗

DOE OSTI2017

The strain-dependent spatial evolution of garnet in a high- P ductile shear zone from the Western Gneiss Region (Norway): a synchrotron X-ray microtomography study

Reaction and deformation microfabrics provide key information to understand the thermodynamic and kinetic controls of tectono-metamorphic processes, however they are usually analysed in two dimensions, omitting important information regarding the third spatial dimension. We applied synchrotron-based X-ray microtomography to document the evolution of a pristine olivine gabbro into a deformed omphacite-garnet eclogite in four dimensions, where the 4th dimension is represented by the degree of strain. In the investigated samples, which cover a strain gradient into a shear zone from the Western Gneiss Region (Norway), we focused on the spatial transformation of garnet coronas into elongated clusters of garnets with increasing strain. Our microtomographic data allowed quantification of garnet volume, shape and spatial arrangement evolution with increasing strain. We combined microtomographic observations with light microscope- and backscatter electron images as well as electron microprobe- (EMPA) and electron backscatter diffraction (EBSD) analysis to correlate mineral composition and orientation data with the X-ray absorption signal of the same mineral grains. With increasing deformation, the garnet volume almost triples. In the low strain domain, garnets form a well interconnected large garnet aggregate that develops throughout the entire Page 1 of 52 sample. We also observed that garnet coronas in the gabbros never completely encapsulate olivine grains. In the most highly deformed eclogites, the oblate shapes of garnet clusters reflect a deformational origin of the microfabrics. We interpret the aligned garnet aggregates to direct synkinematic fluid flow and consequently influence the transport of dissolved chemical components. EBSD analyses reveal that garnet show a near-random crystal preferred orientation that testifies no evidence for crystal plasticity. There is, however evidence for minor fracturing, neo-nucleation and overgrowth. Microprobe chemical analysis revealed that garnet compositions progressively equilibrate to eclogite facies, becoming more almandine-rich. We interpret these observations as pointing to a mechanical disintegration of the garnet coronas during strain localisation, and their rearrangement into individual garnet clusters through a combination of garnet coalescence and overgrowth while the rock was deforming.

garnet↗

DOE OSTI2015

Kinship, inbreeding and fine‐scale spatial structure influence gut microbiota in a hindgut‐fermenting tortoise

Abstract Herbivorous vertebrates rely on complex communities of mutualistic gut bacteria to facilitate the digestion of celluloses and hemicelluloses. Gut microbes are often convergent based on diet and gut morphology across a phylogenetically diverse group of mammals. However, little is known about microbial communities of herbivorous hindgut‐fermenting reptiles. Here, we investigate how factors at the individual level might constrain the composition of gut microbes in an obligate herbivorous reptile. Using multiplexed 16S rRNA gene sequencing, we characterized the faecal microbial community of a population of gopher tortoises ( Gopherus polyphemus ) and examined how age, genetic diversity, spatial structure and kinship influence differences among individuals. We recovered phylotypes associated with known cellulolytic function, including candidate phylum Termite Group 3, suggesting their importance for gopher tortoise digestion. Although host genetic structure did not explain variation in microbial composition and community structure, we found that fine‐scale spatial structure, inbreeding, degree of relatedness and possibly ontogeny shaped patterns of diversity in faecal microbiomes of gopher tortoises. Our findings corroborate widespread convergence of faecal‐associated microbes based on gut morphology and diet and demonstrate the role of spatial and demographic structure in driving differentiation of gut microbiota in natural populations.

Yuan, Michael L.↗

DOE OSTI2013

Spatial frequency spectrum of the x-ray scatter distribution in CBCT projections

Purpose: X-ray scatter is a source of significant image quality loss in cone-beam computed tomography (CBCT). The use of Monte Carlo (MC) simulations separating primary and scattered photons has allowed the structure and nature of the scatter distribution in CBCT to become better elucidated. This work seeks to quantify the structure and determine a suitable basis function for the scatter distribution by examining its spectral components using Fourier analysis.Methods: The scatter distribution projection data were simulated using a CBCT MC model based on the EGSnrc code. CBCT projection data, with separated primary and scatter signal, were generated for a 30.6 cm diameter water cylinder [single angle projection with varying axis-to-detector distance (ADD) and bowtie filters] and two anthropomorphic phantoms (head and pelvis, 360 projections sampled every 1°, with and without a compensator). The Fourier transform of the resulting scatter distributions was computed and analyzed both qualitatively and quantitatively. A novel metric called the scatter frequency width (SFW) is introduced to determine the scatter distribution's frequency content. The frequency content results are used to determine a set basis functions, consisting of low-frequency sine and cosine functions, to fit and denoise the scatter distribution generated from MC simulations using a reduced number of photons and projections. The signal recovery is implemented using Fourier filtering (low-pass Butterworth filter) and interpolation. Estimates of the scatter distribution are used to correct and reconstruct simulated projections.Results: The spatial and angular frequencies are contained within a maximum frequency of 0.1 cm{sup −1} and 7/(2π) rad{sup −1} for the imaging scenarios examined, with these values varying depending on the object and imaging setup (e.g., ADD and compensator). These data indicate spatial and angular sampling every 5 cm and π/7 rad (∼25°) can be used to properly capture the scatter distribution, with reduced sampling possible depending on the imaging scenario. Using a low-pass Butterworth filter, tuned with the SFW values, to denoise the scatter projection data generated from MC simulations using 10{sup 6} photons resulted in an error reduction of greater than 85% for the estimating scatter in single and multiple projections. Analysis showed that the use of a compensator helped reduce the error in estimating the scatter distribution from limited photon simulations by more than 37% when compared to the case without a compensator for the head and pelvis phantoms. Reconstructions of simulated head phantom projections corrected by the filtered and interpolated scatter estimates showed improvements in overall image quality.Conclusions: The spatial frequency content of the scatter distribution in CBCT is found to be contained within the low frequency domain. The frequency content is modulated both by object and imaging parameters (ADD and compensator). The low-frequency nature of the scatter distribution allows for a limited set of sine and cosine basis functions to be used to accurately represent the scatter signal in the presence of noise and reduced data sampling decreasing MC based scatter estimation time. Compensator induced modulation of the scatter distribution reduces the frequency content and improves the fitting results.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2014

SU-E-T-300: Spatial Variations of Multiple Off-Axial Targets for a Single Isocenter SRS Treatment Plan in ExacTrac 6D Robotic Couch System

Purpose: To evaluate the spatial variations of multiple off-axial targets for a single isocenter stereotactic radiosurgery (SRS) treatment plan in ExacTrac 6D robotic couch system (BrainLab AG). Methods: Five metallic ball bearing (BB) markers were placed sparsely in 3D off-axial locations (non-coplanar) inside a skull phantom as the representatives of multiple targets mimicking multiple brain metastases. The locations of the BB markers were carefully chosen to minimize overlapping of each other in a port imaging detector plane. The skull phantom was immobilized by a frameless mask and CT scanned with a BrainLab Head and Neck Localizer using a GE Optima MDCT scanner. The CT images were exported to iPlan software (BrainLab AG) and a multiple target PTV was drawn by combining all the contours of the BBs. The margin of the MLC opening was selected as 3 mm expansion outward. Two coplanar arc beams were placed to generate a single isocenter SRS plan to treat the PTV. The arc beams were delivered using Novalis Tx system with portal imaging acquisition mode per 10% temporal resolution. The locations of the BBs were visualized and analyzed with respect to the MLC aperture in the treatment plan similar to the Winston-Lutz test. Results: All the BBs were clearly identified inside the MLC openings. The positional errors for the BBs were overall less than 1 mm along the rotational path of the two arcs. Conclusion: This study verified that the spatial deviations of multiple off-axial targets for a single isocenter SRS treatment plan is within sub-millimeter range in ExacTrac 6D robotic couch system. Accompanied with the Winston-Lutz test, this test will quality-assure the spatial accuracies of the isocenter as well as the positions of multiple off-axial targets for the SRS treatment using a single isocenter multiple target treatment plan.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-E-J-71: Spatially Preserving Prior Knowledge-Based Treatment Planning

Purpose: Prior knowledge-based treatment planning is impeded by the use of a single dose volume histogram (DVH) curve. Critical spatial information is lost from collapsing the dose distribution into a histogram. Even similar patients possess geometric variations that becomes inaccessible in the form of a single DVH. We propose a simple prior knowledge-based planning scheme that extracts features from prior dose distribution while still preserving the spatial information. Methods: A prior patient plan is not used as a mere starting point for a new patient but rather stopping criteria are constructed. Each structure from the prior patient is partitioned into multiple shells. For instance, the PTV is partitioned into an inner, middle, and outer shell. Prior dose statistics are then extracted for each shell and translated into the appropriate Dmin and Dmax parameters for the new patient. Results: The partitioned dose information from a prior case has been applied onto 14 2-D prostate cases. Using prior case yielded final DVHs that was comparable to manual planning, even though the DVH for the prior case was different from the DVH for the 14 cases. Solely using a single DVH for the entire organ was also performed for comparison but showed a much poorer performance. Different ways of translating the prior dose statistics into parameters for the new patient was also tested. Conclusion: Prior knowledge-based treatment planning need to salvage the spatial information without transforming the patients on a voxel to voxel basis. An efficient balance between the anatomy and dose domain is gained through partitioning the organs into multiple shells. The use of prior knowledge not only serves as a starting point for a new case but the information extracted from the partitioned shells are also translated into stopping criteria for the optimization problem at hand.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

TU-CD-304-08: Feasibility of a VMAT-Based Spatially Fractionated Grid Therapy Technique

Purpose: Grid therapy (GT) uses spatially modulated radiation doses to treat large tumors without significant toxicities. Incorporating 3D conformal-RT or IMRT improved single-field GT by reducing dose to normal tissues spatially through the use of multiple fields. The feasibility of a MLC-based, inverse-planned multi-field GT technique has been demonstrated. Volumetric modulated arc therapy (VMAT) provides conformal dose distributions with the additional potential advantage of reduced treatment times. In this study, we characterize a new VMAT-based GT (VMAT-GT) technique with respect to its deliverability and dosimetric accuracy. Methods: A lattice of 5mm-diameter spheres was created as the boost volume within a large treatment target. A simultaneous boost VMAT (RapidArc) plan with 8Gy to the target and 20Gy to the boost volume was generated using the Eclipse treatment planning system (AAA-v11). The linac utilized HD120 MLC and 6MV flattening-filter free beam. Four non-coplanar arcs, with couch angles at 0, 45, 90 and 317° were used. Collimator angles were at 45 and 315°. The plan was mapped to a phantom. Calibrated Gafchromic EBT3 films were used to measure the delivered dose. Results: The VMAT plan generated a highly spatially modulated dose distribution in the target. D95%, D50%, D5% for the spheres and the targets in Gy were 18.9, 20.6, 23 and 8.0, 9.6, 14.8, respectively. D50% for a 1cm ring 1cm outside the target was 3.0Gy. The peak-to-valley ratio of this technique is comparable to previously proposed techniques, but the MUs were reduced by almost 50%. Film dosimetry showed good agreement between calculated and delivered dose, with an overall gamma passing rate of >98% (3% and 1mm). The point dose differences at sphere centers varied from 2–8%. Conclusion: The deliverability and dose calculation accuracy of the proposed VMAT-GT technique demonstrates that ablative radiation doses are deliverable to large tumors safely and efficiently.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

Evaluation of MRI and cannabinoid type 1 receptor PET templates constructed using DARTEL for spatial normalization of rat brains

Purpose: Image registration is one prerequisite for the analysis of brain regions in magnetic-resonance-imaging (MRI) or positron-emission-tomography (PET) studies. Diffeomorphic anatomical registration through exponentiated Lie algebra (DARTEL) is a nonlinear, diffeomorphic algorithm for image registration and construction of image templates. The goal of this small animal study was (1) the evaluation of a MRI and calculation of several cannabinoid type 1 (CB1) receptor PET templates constructed using DARTEL and (2) the analysis of the image registration accuracy of MR and PET images to their DARTEL templates with reference to analytical and iterative PET reconstruction algorithms. Methods: Five male Sprague Dawley rats were investigated for template construction using MRI and [{sup 18}F]MK-9470 PET for CB1 receptor representation. PET images were reconstructed using the algorithms filtered back-projection, ordered subset expectation maximization in 2D, and maximum a posteriori in 3D. Landmarks were defined on each MR image, and templates were constructed under different settings, i.e., based on different tissue class images [gray matter (GM), white matter (WM), and GM + WM] and regularization forms (“linear elastic energy,” “membrane energy,” and “bending energy”). Registration accuracy for MRI and PET templates was evaluated by means of the distance between landmark coordinates. Results: The best MRI template was constructed based on gray and white matter images and the regularization form linear elastic energy. In this case, most distances between landmark coordinates were <1 mm. Accordingly, MRI-based spatial normalization was most accurate, but results of the PET-based spatial normalization were quite comparable. Conclusions: Image registration using DARTEL provides a standardized and automatic framework for small animal brain data analysis. The authors were able to show that this method works with high reliability and validity. Using DARTEL templates together with nonlinear registration algorithms allows for accurate spatial normalization of combined MRI/PET or PET-only studies.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

Characterization of a synthetic single crystal diamond detector for dosimetry in spatially fractionated synchrotron x-ray fields

Purpose: Modern radiotherapy modalities often use small or nonstandard fields to ensure highly localized and precise dose delivery, challenging conventional clinical dosimetry protocols. The emergence of preclinical spatially fractionated synchrotron radiotherapies with high dose-rate, sub-millimetric parallel kilovoltage x-ray beams, has pushed clinical dosimetry to its limit. A commercially available synthetic single crystal diamond detector designed for small field dosimetry has been characterized to assess its potential as a dosimeter for synchrotron microbeam and minibeam radiotherapy. Methods: Experiments were carried out using a synthetic diamond detector on the imaging and medical beamline (IMBL) at the Australian Synchrotron. The energy dependence of the detector was characterized by cross-referencing with a calibrated ionization chamber in monoenergetic beams in the energy range 30–120 keV. The dose-rate dependence was measured in the range 1–700 Gy/s. Dosimetric quantities were measured in filtered white beams, with a weighted mean energy of 95 keV, in broadbeam and spatially fractionated geometries, and compared to reference dosimeters. Results: The detector exhibits an energy dependence; however, beam quality correction factors (k{sub Q}) have been measured for energies in the range 30–120 keV. The k{sub Q} factor for the weighted mean energy of the IMBL radiotherapy spectrum, 95 keV, is 1.05 ± 0.09. The detector response is independent of dose-rate in the range 1–700 Gy/s. The percentage depth dose curves measured by the diamond detector were compared to ionization chambers and agreed to within 2%. Profile measurements of microbeam and minibeam arrays were performed. The beams are well resolved and the full width at halfmaximum agrees with the nominal width of the beams. The peak to valley dose ratio (PVDR) calculated from the profiles at various depths in water agrees within experimental error with PVDR calculations from Gafchromic film data. Conclusions: The synthetic diamond detector is now well characterized and will be used to develop an experimental dosimetry protocol for spatially fractionated synchrotron radiotherapy.

60 APPLIED LIFE SCIENCES↗