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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

SU-F-T-638: Is There A Need For Immobilization in SRS?

Purpose: Frameless Stereotactic radiosurgery (SRS) is increasingly used in the clinic. Cone-Beam CT (CBCT) to simulation-CT match has replaced the 3-dimensional coordinate based set up using a stereotactic localizing frame. The SRS frame however served as both a localizing and immobilizing device. We seek to measure the quality of frameless (mask based) and frame based immobilization and evaluate its impact on target dose. Methods: Each SRS patient was set up by kV on-board imaging (OBI) and then fine-tuned with CBCT. A second CBCT was done at treatment-end to ascertain intrafraction motion. We compared pre- vs post-treatment CBCT shifts for both frameless and frame based SRS patients. CBCT to sim-CT fusion was repeated for each patient off-line to assess systematic residual image registration error. Each patient was re-planned with measured shifts to assess effects on target dose. Results: We analyzed 11 patients (12 lesions) treated with frameless SRS and 6 patients (11 lesions) with a fixed frame system. Average intra-fraction iso-center positioning errors for frameless and frame-based treatments were 1.24 ± 0.57 mm and 0.28 ± 0.08 mm (mean ± s.d.) respectively. Residual error in CBCT registration was 0.24 mm. The frameless positioning uncertainties led to target dose errors in Dmin and D95 of 15.5 ± 18.4% and 6.6 ± 9.1% respectively. The corresponding errors in fixed frame SRS were much lower with Dmin and D95 reduced by 4.2 ± 6.5% and D95 2.5 ± 3.8% respectively. Conclusion: Frameless mask provides good immobilization with average patient motion of 1.2 mm during treatment. This exceeds MRI voxel dimensions (∼0.43mm) used for target delineation. Frame-based SRS provides superior patient immobilization with measureable movement no greater than the background noise of the CBCT registration. Small lesions requiring submm precision are better served with a frame based SRS.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-T-640: Feasibility of Using a Commercially Available Surface Guided Radiotherapy System with An Open-Face SRS Immobilization System

Purpose: To evaluate the inherent accuracy of using a surface guided radiotherapy system (SGRT) in the setup and monitoring of patients receiving stereotactic radiosurgery with an open-face SRS immobilization system. Methods: An anthropomorphic head phantom was set up using the Qfix Encompass SRS Immobilization System on a Varian Edge with OSMS and Varian TrueBeam with AlignRT. The phantom was positioned at 0° gantry and couch. A reference image was acquired using the SGRT system and an ROI was created over the mask opening. The couch and gantry were rotated to different combinations focusing on clinically used SRS gantry/couch combinations and those blocking the SGRT cameras. Perceived surface deviation by the SGRT system from the reference image was recorded. A Winston-Lutz test was performed on couch angles tested and used to exclude couch walkout. The deviation magnitude was calculated using translational values and rotational raw values were recorded. Results: The maximum couch walkouts were: 0.4mm (Edge) and 0.5mm (TB). Solely rotating the gantry resulted in a median couch deviation of 0.2mm and range of 0.1–0.3mm for both linacs. Only rotating the couch (0° gantry) resulted in median deviations of 0.6mm and 0.5mm with ranges of 0.3–1.0mm and 0.3–0.7mm for the Edge and TB, respectively. Combining gantry and couch rotations, the median deviations were 0.7mm and 0.9mm with ranges of 0.3–1.1mm and 0.2–1.9mm for the Edge and TB, respectively. Including all combinations, rotation, roll, and pitch median deviations ranged from 0.1–0.3° with pitch demonstrating consistently higher values and a maximum deviation of 1.0° (both linacs). Conclusion: SGRT is a reliable monitoring tool, though taking into account system fluctuations, 1mm is too restrictive a site tolerance to use with the Qfix Encompass mask. Gantry rotation has little effect on system fluctuation even with camera blockage, whereas couch rotation has a larger effect.

43 PARTICLE ACCELERATORS↗
DOE OSTI2016

SU-G-JeP1-01: A Combination of Real Time Electromagnetic Localization and Tracking with Cone Beam Computed Tomography in Stereotactic Radiosurgery for Brain Tumors

Purpose: 1. online verification of patient position during treatment using calypso electromagnetic localization and tracking system. 2. Verification and comparison of positional accuracy between cone beam computed tomography and calypso system. 3. Presenting the advantage of continuation localization in Stereotactic radiosurgery treatments. Methods: Ten brain tumor cases were taken for this study. Patients with head mask were under gone Computed Tomography (CT). Before scanning, mask was cut on the fore head area to keep surface beacons on the skin. Slice thickness of 0.65 mm were taken for this study. x, y, z coordinates of these beacons in TPS were entered into tracking station. Varian True Beam accelerator, equipped with On Board Imager was used to take Cone beam Computed Tomography (CBCT) to localize the patient. Simultaneously Surface beacons were used to localize and track the patient throughout the treatment. The localization values were compared in both systems. For localization CBCT considered as reference. Tracking was done throughout the treatment using Calypso tracking system using electromagnetic array. This array was in tracking position during imaging and treatment. Flattening Filter free beams of 6MV photons along with Volumetric Modulated Arc Therapy was used for the treatment. The patient movement was observed throughout the treatment ranging from 2 min to 4 min. Results: The average variation observed between calypso system and CBCT localization was less than 0.5 mm. These variations were due to manual errors while keeping beacon on the patient. Less than 0.05 cm intra-fraction motion was observed throughout the treatment with the help of continuous tracking. Conclusion: Calypso target localization system is one of the finest tools to perform radiosurgery in combination with CBCT. This non radiographic method of tracking is a real beneficial method to treat patients confidently while observing real-time motion information of the patient.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Poster - 30: Use of a Hazard-Risk Analysis for development of a new eye immobilization tool for treatment of choroidal melanoma

Purpose: Our treatment for choroidal melanoma utilizes the GTC frame. The patient looks at a small LED to stabilize target position. The LED is attached to a metal arm attached to the GTC frame. A camera on the arm allows therapists to monitor patient compliance. To move to mask-based immobilization we need a new LED/camera attachment mechanism. We used a Hazard-Risk Analysis (HRA) to guide the design of the new tool. Method: A pre-clinical model was built with input from therapy and machine shop personnel. It consisted of an aluminum frame placed in aluminum guide posts attached to the couch top. Further development was guided by the Department of Defense Standard Practice - System Safety hazard risk analysis technique. Results: An Orfit mask was selected because it allowed access to indexes on the couch top which assist with setup reproducibility. The first HRA table was created considering mechanical failure modes of the device. Discussions with operators and manufacturers identified other failure modes and solutions. HRA directed the design towards a safe clinical device. Conclusion: A new immobilization tool has been designed using hazard-risk analysis which resulted in an easier-to-use and safer tool compared to the initial design. The remaining risks are all low probability events and not dissimilar from those currently faced with the GTC setup. Given the gains in ease of use for therapists and patients as well as the lower costs for the hospital, we will implement this new tool.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Fabrication of a terahertz quantum-cascade laser with a double metal waveguide based on multilayer GaAs/AlGaAs heterostructures

The Postgrowth processing of GaAs/AlGaAs multilayer heterostructures for terahertz quantumcascade lasers (QCLs) are studied. This procedure includes the thermocompression bonding of In–Au multilayer heterostructures with a doped n{sup +}-GaAs substrate, mechanical grinding, and selective wet etching of the substrate, and dry etching of QCL ridge mesastripes through a Ti/Au metallization mask 50 and 100 μm wide. Reactive-ion-etching modes with an inductively coupled plasma source in a BCl{sub 3}/Ar gas mixture are selected to obtain vertical walls of the QCL ridge mesastripes with minimum Ti/Au mask sputtering.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Surface nanostructuring in the carbon–silicon(100) system upon microwave plasma treatment

The study is concerned with the physical and chemical processes and the mechanisms of the effect of plasma preparation of a surface on the systematic features of condensation and surface phase transformations during the formation of Si–C mask domains on p-Si(100) crystals by the deposition of submonolayer C coatings in the microwave plasma of low-pressure ethanol vapors. It is shown that, at short durations of the deposition of carbon onto silicon wafers with a natural-oxide coating at a temperature of 100°C, the formation of domains is observed. The lateral dimensions of the domains lie in the range from 10–15 to 200 nm, and the heights of ridges produced by the plasma chemical etching of silicon through the mask domain coatings vary in the range from 40 to 80 nm.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Maskman

SAND2025-04369O Maskman is a user-friendly tool designed to create hex masks, which are essential for optimizing application performance in high-performance computing environments. By converting a list of integers into binary and then hex masks, Maskman simplifies the process of setting application affinity. This ensures that software runs efficiently on specific nodes within a computing cluster. Ideal for researchers and developers, Maskman streamlines the preparation of inputs for HPC schedulers, enhancing resource management and improving overall system performance. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Pase, Douglas [Sandia National Lab. (SNL-CA), Live↗
DOE OSTI2026

WFSUITE: A PYTHON SOFTWARE SUITE FOR X-RAY WAVEFRONT SENDING AND AT-WAVELENGTH METROLOGY

SF-26-025 WFSuite is a graphical and command-line toolkit for coded-mask-based X-ray wavefront sensing and phase reconstruction at synchrotron beamlines. It integrates analysis tools for both relative and absolute speckle-based measurements. In the relative metrology module, WFSuite implements Wavelet-transform-based X-ray Speckle Tracking (WXST) and Wavelet-transform-based Speckle Vector Tracking (WSVT) methods to retrieve differential phase and wavefront distortions by comparing speckle patterns recorded with and without the test sample. In the absolute phase module, WFSuite uses coded-mask speckle patterns and replaces the measured reference with a numerically simulated one, enablingsingle-shot wavefront reconstruction using either WXST or a neural-network-based method (SPINNet).

Rebuffi, Luca [Argonne National Laboratory (ANL), ↗
DOE OSTI2026

PRISMA: PARALLEL REFINEMENT AND INTEGRATION SYSTEM FOR MULTI-AZIMUTHAL ANALYSIS

The Parallel Refinement and Integration System for Multi-azimuthal Analysis (PRISMA, version 1.1.0) is a Python application for processing X-ray diffraction (XRD) image data. PRISMA wraps GSAS-II to perform azimuthally-binned peak refinement, computes per-frame strain and d-spacing from those fits, and provides three PyQt5 graphical interfaces: (1) a Recipe Builder for selecting GSAS-II control (.imctrl) files, optional mask (.immask) files or threshold-ased masking, reference and experiment image sets, peaks, zimuthal range and bin size, and an optional ceria-based auto-calibration; (2) a Batch Processor that uses Dask on local workstations and pure MPI (mpi4py.futures.MPICommExecutor) on HPC to distribute GSAS-II refinement across cores or compute nodes and write results to a 4-dimensional (peaks x frames x azimuths x measurements) Zarr dataset; and (3) a Data Analyzer that renders heatmaps of fit parameters, strain, frame-to-frame deltas, and percent-change-vs-reference, and exports user-defined subsections to CSV or Excel. The peak-refinement algorithm is deterministic. Benchmark on ALCF Crux: a 20,000-image set, single-peak fit in frame mode with 44 azimuthal bins on 128 nodes x 128 workers, 48 seconds total wall time.

Lorenzo Martin, Maria De La Cinta [Argonne Nationa↗
DOE OSTI2020

Quantification of the Radiative Effect of Aerosol–Cloud Interactions in Shallow Continental Cumulus Clouds

The indirect radiative effect of aerosol variability on shallow cumulus clouds is realized in nature with considerable concurrent meteorological variability. Large-eddy simulations constrained by observations at a continental site in Oklahoma are performed to represent the variability of different meteorological states on days with different aerosol conditions. The total radiative effect of this natural covariation between aerosol and other meteorological drivers of total cloud amount and albedo is quantified. The changes to these bulk quantities are used to understand the response of the cloud radiative effect to aerosol–cloud interactions (ACI) in the context of concurrent processes, as opposed to attempting to untangle the effect of individual processes on a case-by-case basis. Mutual information (MI) analysis suggests that meteorological variability masks the strength of the relationship between cloud drop number concentration and the cloud radiative effect. This is shown to be mostly due to variation in solar zenith angle and cloud field horizontal heterogeneity masking the relationship between cloud drop number and cloud albedo. By combining MI and more traditional differential analyses, a framework to identify important modes of covariation between aerosol, clouds, and meteorological conditions is developed. This shows that accounting for solar zenith angle variation and implementing an albedo bias correction increases the detectability of the radiative effects of ACI in simulations of shallow cumulus.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Improving Satellite Quantitative Precipitation Estimation Using GOES-Retrieved Cloud Optical Depth

To address significant gaps in ground-based radar coverage and rain gauge networks in the U.S., geostationary satellite quantitative precipitation estimates (QPEs) such as the Self-Calibrating Multivariate Precipitation Retrievals (SCaMPR) can be used to fill in both the spatial and temporal gaps of ground-based measurements. Additionally, with the launch of GOES-R, the temporal resolution of satellite QPEs may be comparable to that of Weather Service Radar-1988 Doppler (WSR-88D) volume scans as GOES images will be available every five minutes. However, while satellite QPEs have strengths in spatial coverage and temporal resolution, they face limitations particularly during convective events. Deep Convective Systems (DCSs) have large cloud shields with similar brightness temperatures (BTs) over nearly the entire system, but widely varying precipitation rates beneath these clouds. Geostationary satellite QPEs relying on the indirect relationship between BTs and precipitation rates often suffer from large errors because anvil regions (little/no precipitation) cannot be distinguished from rain-cores (heavy precipitation) using only BTs. However, a combination of BTs and optical depth (τ) has been found to reduce overestimates of precipitation in anvil regions. A new rain mask algorithm incorporating both τ and BTs has been developed, and its application to the existing SCaMPR algorithm was evaluated. Here, the performance of the modified SCaMPR was evaluated using traditional skill scores and a more detailed analysis of performance in individual DCS components by utilizing the Feng et al. (2012) classification algorithm. SCaMPR estimates with the new rain mask applied benefited from significantly reduced overestimates of precipitation in anvil regions and overall improvements in skill scores.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Automated retrieval of cloud and aerosol properties from the ARM Raman lidar, part 1: feature detection

A Feature detection and EXtinction retrieval (FEX) algorithm for the Atmospheric Radiation Measurement (ARM) program’s Raman lidar (RL) has been developed. Presented here is part 1 of the FEX algorithm: the detection of features including both clouds and aerosols. The approach of FEX is to use multiple quantities— scattering ratios derived using elastic and nitro-gen channel signals from two fields of view, the scattering ratio derived using only the elastic channel, and the total volume depolarization ratio— to identify features using range-dependent detection thresholds. FEX is designed to be context-sensitive with thresholds determined for each profile by calculating the expected clear-sky signal and noise. The use of multiple quantities pro-vides complementary depictions of cloud and aerosol locations and allows for consistency checks to improve the accuracy of the feature mask. The depolarization ratio is shown to be particularly effective at detecting optically-thin features containing non-spherical particles such as cirrus clouds. Improve-ments over the existing ARM RL cloud mask are shown. The performance of FEX is validated against a collocated micropulse lidar and observations from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite over the ARM Darwin, Australia site. While we focus on a specific lidar system, the FEX framework presented here is suitable for other Raman or high spectral resolution lidars.

Thorsen, Tyler J.↗
DOE OSTI2014

Growth of arrays of oriented epitaxial platinum nanoparticles with controlled size and shape by natural colloidal lithography

Here, we developed a method for production of arrays of platinum nanocrystals of controlled size and shape using templates from ordered silica bead monolayers. Silica beads with nominal sizes of 150 and 450 nm were self-assembl into monolayers over strontium titanate single crystal substrates. The monolayers were used as shadow masks for platinum metal deposition on the substrate using the three-step evaporation technique. Produced arrays of epitaxial platinum islands were transformed into nanocrystals by annealing in a quartz tube in nitrogen flow. The shape of particles is determined by the substrate crystallography, while the size of the particles and their spacing are controlled by the size of the silica beads in the mono- layer mask. As a proof of concept, arrays of platinum nanocrystals of cubooctahedral shape were prepared on (100) strontium titanate substrates. We also characterized the nanocrystal arrays by atomic force microscopy, scanning electron microscopy, and synchrotron X-ray diffraction techniques.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Summit Darshan Archival Dataset

Summit Darshan Archival Dataset contains 2021 Summit Darshan log data for 25 applications and is grouped into science domains. The dataset is processed, and all the propriety fields are anonymized. The resultant data is converted into a tabular structure and saved in parquet file format. In this notebook, we demonstrate how to access the data. Data Organization: The data is organized into two directories: Darshan total (`darshan_total`): List all the high levels generated by the `darshan-parser --total` command on `.darshan` files. There is one parquet file for each application. Note: `uid` and `exe` field are masked Darshan detail (`darshan_detail`): This data contains detailed job level log information extracted by command `darshan-parser` on the raw `.darshan` files. The data is sorted by directory hierarchy in the order of `year/month/day (2021/12/07)`. For instance, to get the data for a `job_id` 3819766 of application `App11`, which was executed on `2021-12-07`can be accessed as follows. Note:`uid` and `filename` fields are masked

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Layer-wise Imaging Dataset from Powder Bed Additive Manufacturing Processes for Machine Learning Applications (Peregrine v2022-10)

This release consists of six datasets which together include multi-modal layer-wise powder bed images from two different powder bed printing technologies. These datasets are designed primarily to facilitate the development and testing of new computer vision and machine learning based anomaly and defect detection algorithms. The authors provide both training data with corresponding ground truth pixel masks and evaluation data with corresponding baseline prediction pixel masks made by a trained neural network. The laser powder bed fusion (L-PBF) datasets are sourced from EOS M290 and AddUp FormUp 350 printers and the binder jet (BJ) dataset is sourced from an ExOne M-Flex printer. The materials represented in these datasets include 17-4 PH Stainless Steel, DMREF, Inconel 718, Maraging Steel, and H13 Steel. The sensor imaging modalities represented include visible-light (VL), temporally-integrated (i.e., long duration exposure) near-infrared (TI-NIR), and wide-band infrared (IR).

36 MATERIALS SCIENCE↗
DOE OSTI2023

Supporting information for Few-Shot Learning Enables Population-Scale Analysis of Leaf Traits in Populus trichocarpa

In this work, we use few-shot learning to segment the body and vein architecture of P. trichocarpa leaves from high-resolution scans obtained in the UC Davis common garden. Leaf and vein segmentation are formulated as separate tasks, in which convolutional neural networks (CNNs) are used to iteratively expand partial segmentations until reaching stopping criteria. Our leaf and vein segmentation approaches use just 50 and 8 manually traced images for training, respectively, and are applied to a set of 2,634 top and bottom leaf scans. We show that both methods achieve high segmentation accuracy, in some cases exceeding even human-level segmentation. The leaf and vein segmentations are subsequently used to extract 68 morphological traits using traditional open-source image processing tools, which are validated using real-world physical measurements. For a biological perspective, we perform a genome-wide association study using the vein density trait to discover novel genetic architectures associated with multiple physiological processes relating to leaf development and function. In addition to sharing all of the few-shot learning code (see https://github.com/jlager/few-shot-leaf-segmentation), we are releasing all images, manual segmentations, model predictions, 68 extracted leaf phenotypes, and a new set of SNPs called against the v4 P. trichocarpa genome for 1,419 genotypes. The data folder includes all images, ground truth segmentations, predicted segmentations, and extracted leaf traits. All images encode the sample ID in the file name by indicating the treatment, block, row, position, and leaf side, respectively. For example, the file, C_1_1_2_bot.jpeg, indicates the control treatment, block 1, row 1, position 2, and the bottom side of the leaf. Tabulated results include position IDs as well as the corresponding genotype IDs. The images folder includes the 2,906 high-resolution leaf scans taken in the field. The leaf_masks folder includes 50 ground truth segmentations used for training the leaf tracing algorithm. The leaf_preds folder includes the 2,906 predicted segmentations from the leaf tracing algorithm. The vein_masks folder includes 8 ground truth segmentations used for training the vein growing algorithm. The vein_preds folder includes the 1,453 predicted segmentations from the vein growing algorithm. The vein_probs folder includes the 1,453 predicted probability maps from the vein growing algorithm before thresholding. The genomes folder includes the set of SNPs called against the v4 P. trichocarpa genome for 1,419 genotypes with a README file detailing the steps taken. The results folder includes: (i) raw values of the 68 predicted leaf traits in digital_traits.tsv, (ii) manually measured values of petiole length and width in manual_traits.tsv, (iii) thin plate spline (TPS) adjusted values of the vein density trait in vein_density_tps_adj.tsv, (iv) best linear unbiased prediction (BLUP) adjusted values of the vein density trait in vein_density_blups.tsv, and (v) GWAS results for the vein density trait, including chromosome positions and corresponding P values, in gwas_results.csv.

09 BIOMASS FUELS↗
DOE OSTI2023

Layer-wise Imaging Dataset from Powder Bed Additive Manufacturing Processes for Machine Learning Applications (Peregrine v2022-10.1)

This release consists of six datasets which together include multi-modal layer-wise powder bed images from two different powder bed printing technologies. These datasets are designed primarily to facilitate the development and testing of new computer vision and machine learning based anomaly and defect detection algorithms. The authors provide both training data with corresponding ground truth pixel masks and evaluation data with corresponding baseline prediction pixel masks made by a trained neural network. The laser powder bed fusion (L-PBF) datasets are sourced from EOS M290 and AddUp FormUp 350 printers and the binder jet (BJ) dataset is sourced from an ExOne M-Flex printer. The materials represented in these datasets include 17-4 PH Stainless Steel, GammaPrint-700, Inconel 718, Maraging Steel, and H13 Steel. The sensor imaging modalities represented include visible-light (VL), temporally-integrated (i.e., long duration exposure) near-infrared (TI-NIR), and wide-band infrared (IR). To download the dataset: (1) Create a Globus account. (2) Create a Globus Endpoint on your computer. (3) Transfer the dataset from the OLCF DOI-DOWNLOADS Collection to your Collection. Common troubleshooting steps: (a) Confirm that the transfer is going from OLCF DOI-DOWNLOADS to your Collection. (b) Create an exception for Globus in your antivirus software so that it can create an Endpoint. (c) Manually create a Globus access directory (where the data will be downloaded) by going to the Preferences > Access tab.

36 MATERIALS SCIENCE↗