Beyond MAP: A guide to dimensions of rainfall variability for tropical ecology
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Environmental Sciences & Ecology↗
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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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Soils' dirty little secret: Depth–based comparisons can be inadequate for quantifying changes in soil organic carbon and other mineral soil properties
Quantifying changes in soil organic carbon (SOC) stocks and other soil properties is essential for understanding how soils will respond to land management practices and global change. Although they are widely used, comparisons of SOC stocks at fixed depth (FD) intervals are subject to errors when changes in bulk density or soil organic matter occur. The equivalent soil mass (ESM) method has been recommended in lieu of FD for assessing changes in SOC stocks in mineral soils, but ESM remains underutilized for SOC stocks and has rarely been used for other soil properties. In this paper, we draw attention to the limitations of the FD method and demonstrate the advantages of the ESM approach. We provide illustrations to show that the FD approach is susceptible to errors not only for quantifying SOC stocks but also for soil mass-based properties such as SOC mass percent, C:N mass ratio, and δ 13 C. Here we describe the ESM approach and show how it mitigates the FD method limitations. Using bulk density change simulations applied to an empirical dataset from bioenergy cropping systems, we show that the ESM method provides consistently lower errors than FD when quantifying changes in SOC stocks and other soil properties. To simplify the use of ESM, we detail how the method can be integrated into sampling schemes, and we provide an example R computer script that can perform ESM calculations on large datasets. We encourage future studies, whether temporal or comparative, to utilize sampling methods that are amenable to the ESM approach. Overall, we agree with previous recommendations that ESM should be the standard method for evaluating SOC stock changes in mineral soils, but we further suggest that ESM may also be preferred for comparisons of other soil properties including mass percentages, elemental mass ratios, and stable isotope composition.
59 BASIC BIOLOGICAL SCIENCES↗
Tundra Trait Team: A database of plant traits spanning the tundra biome
Motivation: The Tundra Trait Team (TTT) database includes field-based measurements of key traits related to plant form and function at multiple sites across the tundra biome. This dataset can be used to address theoretical questions about plant strategy and trade-offs, trait-environment relationships and environmental filtering, and trait variation across spatial scales, to validate satellite data, and to inform earth system model parameters. Main types of variable contained: The database contains 81,537 measurements of 18 plant traits. The most frequently measured traits (>1,000 observations each) include plant height, leaf area, specific leaf area, leaf fresh and dry mass, leaf dry matter content, leaf nitrogen content, leaf carbon content, leaf phosphorus content, seed mass, and stem specific density. Spatial location and grain: Measurements were collected in tundra habitats in both the northern and southern hemispheres, including Arctic sites in Alaska, Canada, Greenland, Fennoscandia, and Siberia and alpine sites in the European Alps, Colorado Rockies, Caucasus, Ural Mountains, Pyrenees, Australian Alps, and Central Otago Mountains (New Zealand). More than 99% of observations are georeferenced. Time period and grain: All data were collected between 1964 and 2016. A small number of sites have repeated trait measurements at two or more time periods. Major taxa and level of measurement: Trait measurements were made on 858 terrestrial vascular plant species growing in tundra habitats. Most observations are on individuals (87%), while a small number represent plot or site means or maximums per species. Software format: csv file and GitHub repository with data cleaning scripts in R; contribution to TRY plant trait database (www.try-db.org) to be included in the next version release.
59 BASIC BIOLOGICAL SCIENCES↗
Global root traits (GRooT) database
Motivation: Trait data are fundamental to the quantitative description of plant form and function. Although root traits capture key dimensions related to plant responses to changing environmental conditions and effects on ecosystem processes, they have rarely been included in large-scale comparative studies and global models. For instance, root traits remain absent from nearly all studies that define the global spectrum of plant form and function. Thus, to overcome conceptual and methodological roadblocks preventing a widespread integration of root trait data into large-scale analyses we created the Global Root Trait (GRooT) Database. GRooT provides readyto- use data by combining the expertise of root ecologists with data mobilization and curation. Specifically, we (a) determined a set of core root traits relevant to the description of plant form and function based on an assessment by experts, (b) maximized species coverage through data standardization within and among traits, and (c) implemented data quality checks. Main types of variables contained: GRooT contains 114,222 trait records on 38 continuous root traits. Spatial location and grain: Global coverage with data from arid, continental, polar, temperate and tropical biomes. Data on root traits were derived from experimental studies and field studies. Time period and grain: Data were recorded between 1911 and 2019. Major taxa and level of measurement: GRooT includes root trait data for which taxonomic information is available. Trait records vary in their taxonomic resolution, with subspecies or varieties being the highest and genera the lowest taxonomic resolution available. It contains information for 184 subspecies or varieties, 6,214 species, 1,967 genera and 254 families. Owing to variation in data sources, trait records in the database include both individual observations and mean values. Software format: GRooT includes two csv files. A GitHub repository contains the csv files and a script in R to query the database.
59 BASIC BIOLOGICAL SCIENCES↗
High-throughput sequencing of the chloroplast and mitochondrion of Chlamydomonas reinhardtii to generate improved de novo assemblies, analyze expression patterns and transcript speciation, and evaluate diversity among laboratory strains and wild isolates
Chlamydomonas reinhardtii is a unicellular chlorophyte alga that is widely studied as a reference organism for understanding photosynthesis, sensory and motile cilia, and for development of an algal-based platform for producing biofuels and bio-products. Its highly repetitive, ~205-kbp circular chloroplast genome and ~15.8-kbp linear mitochondrial genome were sequenced prior to the advent of high-throughput sequencing technologies. Here, high coverage shotgun sequencing was used to assemble both organellar genomes de novo. These new genomes correct dozens of errors in the prior genome sequences and annotations. Gen-ome sequencing coverage indicates that each cell contains on average 83 copies of the chloroplast genome and 130 copies of the mitochondrial genome. Using protocols and analyses optimized for organellar tran-scripts, RNA-Seq was used to quantify their relative abundances across 12 different growth conditions. Forty-six percent of total cellular mRNA is attributable to high expression from a few dozen chloroplast genes. RNA-Seq data were used to guide gene annotation, to demonstrate polycistronic gene expression, and to quantify splicing of psaA and psbA introns. In contrast to a conclusion from a recent study, we found that chloroplast transcripts are not edited. Unexpectedly, cytosine-rich polynucleotide tails were observed at the 3’-end of all mitochondrial transcripts. A comparative genomics analysis of eight laboratory strains and 11 wild isolates of C. reinhardtii identified 2658 variants in the organellargenomes, which is 1/10th as much genetic diversity as is found in the nucleus.
ftsH↗
Demonstrating solarpilot ’s Python Application Programmable Interface Through Heliostat Optimal Aimpoint Strategy Use Case
solarpilot is a software package that generates solar field layouts and characterizes the optical performance of concentrating solar power (CSP) tower systems. solarpilot was developed by the National Renewable Energy Laboratory (NREL) as a stand-alone desktop application but has also been incorporated into NREL’s System Advisor Model (SAM) in a simplified format. Prior means for user interaction with solarpilot have included the application’s graphical interface, the SAM routines with limited configurability, and through a built-in scripting language called “LK.” This article presents a new, full-featured, python-based application programmable interface (API) for solarpilot, which we hereafter refer to as CoPylot. CoPylot enables python users to perform detailed CSP tower analysis utilizing either the Hermite expansion technique (analytical) or the SolTrace ray-tracing engine. CoPylot’s enables CSP researchers to perform analysis that was previously not possible through solarpilot’s existing interfaces. This article discusses the capabilities of CoPylot and presents a use case wherein we populate a model that obtains optimal solar field aiming strategies.
14 SOLAR ENERGY↗
Demonstrating SolarPILOT’s Python API Through Heliostat Optimal Aimpoint Strategy Use Case
SolarPILOT is a software package that generates solar field layouts and characterizes the optical performance of concentrating solar power (CSP) tower systems. SolarPILOT was developed by the National Renewable Energy Laboratory (NREL) as a stand-alone desktop application but has also been incorporated into NREL’s1 System Advisor Model (SAM) in a simplified format. Prior means for user interaction with SolarPILOT have included the application’s graphical interface, the SAM routines with limited configurability, and through a built-in scripting language called “LK.” This paper presents a new, full-featured, Python-based application programmable interface (API) for SolarPILOT, which we hereafter refer to as CoPylot. CoPylot provides access to all SolarPILOT’s capabilities to generate and characterize power tower CSP systems seamlessly through Python. Supported capabilities include (i) creating and destroying a model instance with message reporting tools; (ii) accessing and setting any SolarPILOT variable including custom land boundaries for field layouts; (iii) programmatically managing receiver and heliostat objects with varied attributes for systems with multiple receiver or heliostat types; (iv) generating, assigning, and modifying solar field layouts including the ability to set individual heliostat locations, aimpoints, soiling rates, and reflectivity levels; (v) simulating solar field performance; (vi) returning detailed results describing performance of individual heliostats, the aggregate field, and receiver flux distribution; and, (vii) exporting Python-based model instances to multiple file formats. CoPylot enables Python users to perform detailed CSP tower analysis utilizing either the Hermite expansion technique (analytical) or the SolTrace ray-tracing engine. In addition to CoPylot’s functionality, Python users have access to the over 100,000 open-source libraries to develop, analyze, optimize, and visualize power tower CSP research. This enables CSP researchers to perform analysis that was previously not possible through SolarPILOT’s existing interfaces. This paper discusses the capabilities of CoPylot and presents a use case wherein we demonstrate optimal solar field aiming strategies.
41 EE - Solar Energy Technologies Office (EE-4S)↗
New Developments and Capabilities Within WEC-Sim
WEC-Sim is an open-source software for simulating wave energy converters and has been actively developed and applied since its initial release in 2014 to simulate a wide variety of device archetypes. WEC-Sim is developed jointly by the National Renewable Energy Laboratory and Sandia National Laboratories within the MATLAB/SIMULINK environment. A general wave-to-wire model begins with a deployment site resource characterization, which is used to complete the hydrodynamic simulation of wave energy converters (WEC), with the power generation profile imported to a grid simulator to understand the influence on the local electrical network. While modeling the entire wave-to-wire is difficult and encompasses multiple time scales and physics, WEC-Sim is focused on the hydrodynamics simulation to predict, analyze, and optimize WEC dynamics and power performance. WEC-Sim simulations are performed in the time domain based on the radiation and diffraction method using hydrodynamics coefficients derived from boundary element method (BEM)-based frequency-domain potential flow solvers (e.g., WAMIT, NEMOH, Capytaine, or ANSYS-AQWA). With this level of modeling fidelity, WEC-Sim can handle floating body hydrodynamics, mechanical and electrical power generation methods, advanced control implementation, mooring systems, and other unique applications such as desalination. Additional WEC-Sim functionalities include pre-built Simulink blocks and MATLAB scripts that can simulate a wide range of floating systems and the corresponding auxiliary subsystems. The developers of WEC-Sim continue to release new versions of the software, at least annually, with the latest release in September 2022. These releases include bug fixes, updates to software documentation, as well as new features to expand WEC-Sim's capabilities to model a wide range of WEC concepts. This publication will highlight the new features added to WEC-Sim between versions 4.1.0 to 5.0.1, which spans a 2-year period from June 2020 to September 2022. New features described here include topics such as continuous integration checks, revised Morison Element and nonlinear hydro implementations, run directly from Simulink (required for hardware-in-the-loop execution), BEMIO updates to import Capytaine BEM hydrodynamics, addition of cable blocks, and new wave visualization features.
TIDAL AND WAVE POWER↗
A generalized reconstruction framework for unconventional PET systems
Purpose: Quantitative estimation of the radionuclide activity concentration in positron emission tomography (PET) requires precise modeling of PET physics. The authors are focused on designing unconventional PET geometries for specific applications. This work reports the creation of a generalized reconstruction framework, capable of reconstructing tomographic PET data for systems that use right cuboidal detector elements positioned at arbitrary geometry using a regular Cartesian grid of image voxels. Methods: The authors report on a variety of design choices and optimization for the creation of the generalized framework. The image reconstruction algorithm is maximum likelihood-expectation–maximization. System geometry can be specified using a simple script. Given the geometry, a symmetry seeking algorithm finds existing symmetry in the geometry with respect to the image grid to improve the memory usage/speed. Normalization is approached from a geometry independent perspective. The system matrix is computed using the Siddon’s algorithm and subcrystal approach. The program is parallelized through open multiprocessing and message passing interface libraries. A wide variety of systems can be modeled using the framework. This is made possible by modeling the underlying physics and data correction, while generalizing the geometry dependent features. Results: Application of the framework for three novel PET systems, each designed for a specific application, is presented to demonstrate the robustness of the framework in modeling PET systems of unconventional geometry. Three PET systems of unconventional geometry are studied. (1) Virtual-pinhole half-ring insert integrated into Biograph-40: although the insert device improves image quality over conventional whole-body scanner, the image quality varies depending on the position of the insert and the object. (2) Virtual-pinhole flat-panel insert integrated into Biograph-40: preliminary results from an investigation into a modular flat-panel insert are presented. (3) Plant PET system: a reconfigurable PET system for imaging plants, with resolution of greater than 3.3 mm, is shown. Using the automated symmetry seeking algorithm, the authors achieved a compression ratio of the storage and memory requirement by a factor of approximately 50 for the half-ring and flat-panel systems. For plant PET system, the compression ratio is approximately five. The ratio depends on the level of symmetry that exists in different geometries. Conclusions: This work brings the field closer to arbitrary geometry reconstruction. A generalized reconstruction framework can be used to validate multiple hypotheses and the effort required to investigate each system is reduced. Memory usage/speed can be improved with certain optimizations.
60 APPLIED LIFE SCIENCES↗
SU-C-304-01: Investigation of Various Detector Response Functions and Their Geometry Dependence in a Novel Method to Address Ion Chamber Volume Averaging Effect
Purpose: A novel convolution-based approach has been proposed to address ion chamber (IC) volume averaging effect (VAE) for the commissioning of commercial treatment planning systems (TPS). We investigate the use of various convolution kernels and its impact on the accuracy of beam models. Methods: Our approach simulates the VAE by iteratively convolving the calculated beam profiles with a detector response function (DRF) while optimizing the beam model. At convergence, the convolved profiles match the measured profiles, indicating the calculated profiles match the “true” beam profiles. To validate the approach, beam profiles of an Elekta LINAC were repeatedly collected with ICs of various volumes (CC04, CC13 and SNC 125) to obtain clinically acceptable beam models. The TPS-calculated profiles were convolved externally with the DRF of respective IC. The beam model parameters were reoptimized using Nelder-Mead method by forcing the convolved profiles to match the measured profiles. We evaluated three types of DRFs (Gaussian, Lorentzian, and parabolic) and the impact of kernel dependence on field geometry (depth and field size). The profiles calculated with beam models were compared with SNC EDGE diode-measured profiles. Results: The method was successfully implemented with Pinnacle Scripting and Matlab. The reoptimization converged in ∼10 minutes. For all tested ICs and DRFs, penumbra widths of the TPS-calculated profiles and diode-measured profiles were within 1.0 mm. Gaussian function had the best performance with mean penumbra width difference within 0.5 mm. The use of geometry dependent DRFs showed marginal improvement, reducing the penumbra width differences to less than 0.3 mm. Significant increase in IMRT QA passing rates was achieved with the optimized beam model. Conclusion: The proposed approach significantly improved the accuracy of the TPS beam model. Gaussian functions as the convolution kernel performed consistently better than Lorentzian and parabolic functions. Further improvement of using geometry-dependent kernels was marginal.
60 APPLIED LIFE SCIENCES↗
SU-D-BRD-03: Improving Plan Quality with Automation of Treatment Plan Checks
Purpose: To evaluate the effectiveness of an automated plan check tool to improve first-time plan quality as well as standardize and document performance of physics plan checks. Methods: The Plan Checker Tool (PCT) uses the Eclipse Scripting API to check and compare data from the treatment planning system (TPS) and treatment management system (TMS). PCT was created to improve first-time plan quality, reduce patient delays, increase efficiency of our electronic workflow, and to standardize and partially automate plan checks in the TPS. A framework was developed which can be configured with different reference values and types of checks. One example is the prescribed dose check where PCT flags the user when the planned dose and the prescribed dose disagree. PCT includes a comprehensive checklist of automated and manual checks that are documented when performed by the user. A PDF report is created and automatically uploaded into the TMS. Prior to and during PCT development, errors caught during plan checks and also patient delays were tracked in order to prioritize which checks should be automated. The most common and significant errors were determined. Results: Nineteen of 33 checklist items were automated with data extracted with the PCT. These include checks for prescription, reference point and machine scheduling errors which are three of the top six causes of patient delays related to physics and dosimetry. Since the clinical roll-out, no delays have been due to errors that are automatically flagged by the PCT. Development continues to automate the remaining checks. Conclusion: With PCT, 57% of the physics plan checklist has been partially or fully automated. Treatment delays have declined since release of the PCT for clinical use. By tracking delays and errors, we have been able to measure the effectiveness of automating checks and are using this information to prioritize future development. This project was supported in part by P01CA059827.
60 APPLIED LIFE SCIENCES↗
SU-E-J-73: Extension of a Clinical OIS/EMR/R&V System to Deliver Safe and Efficient Adaptive Plan-Of-The-Day Treatments Using a Fully Customizable Plan-Library-Based Workflow
Purpose: To extend a clinical Record and Verify (R&V) system to enable a safe and fast workflow for Plan-of-the-Day (PotD) adaptive treatments based on patient-specific plan libraries. Methods: Plan libraries for PotD adaptive treatments contain for each patient several pre-treatment generated treatment plans. They may be generated for various patient anatomies or CTV-PTV margins. For each fraction, a Cone Beam CT scan is acquired to support the selection of the plan that best fits the patient’s anatomy-of-the-day. To date, there are no commercial R&V systems that support PotD delivery strategies. Consequently, the clinical workflow requires many manual interventions. Moreover, multiple scheduled plans have a high risk of excessive dose delivery. In this work we extended a commercial R&V system (MOSAIQ) to support PotD workflows using IQ-scripting. The PotD workflow was designed after extensive risk analysis of the manual procedure, and all identified risks were incorporated as logical checks. Results: All manual PotD activities were automated. The workflow first identifies if the patient is scheduled for PotD, then performs safety checks, and continues to treatment plan selection only if no issues were found. The user selects the plan to deliver from a list of candidate plans. After plan selection, the workflow makes the treatment fields of the selected plan available for delivery by adding them to the treatment calendar. Finally, control is returned to the R&V system to commence treatment. Additional logic was added to incorporate off-line changes such as updating the plan library. After extensive testing including treatment fraction interrupts and plan-library updates during the treatment course, the workflow is running successfully in a clinical pilot, in which 35 patients have been treated since October 2014. Conclusion: We have extended a commercial R&V system for improved safety and efficiency in library-based adaptive strategies enabling a wide-spread implementation of those strategies. This work was in part funded by a research grant of Elekta AB, Stockholm, Sweden.
60 APPLIED LIFE SCIENCES↗
SU-E-J-164: Estimation of DVH Variation for PTV Due to Interfraction Organ Motion in Prostate VMAT Using Gaussian Error Function
Purpose: We developed a method to predict the change of DVH for PTV due to interfraction organ motion in prostate VMAT without repeating the CT scan and treatment planning. The method is based on a pre-calculated patient database with DVH curves of PTV modelled by the Gaussian error function (GEF). Methods: For a group of 30 patients with different prostate sizes, their VMAT plans were recalculated by shifting their PTVs 1 cm with 10 increments in the anterior-posterior, left-right and superior-inferior directions. The DVH curve of PTV in each replan was then fitted by the GEF to determine parameters describing the shape of curve. Information of parameters, varying with the DVH change due to prostate motion for different prostate sizes, was analyzed and stored in a database of a program written by MATLAB. Results: To predict a new DVH for PTV due to prostate interfraction motion, prostate size and shift distance with direction were input to the program. Parameters modelling the DVH for PTV were determined based on the pre-calculated patient dataset. From the new parameters, DVH curves of PTVs with and without considering the prostate motion were plotted for comparison. The program was verified with different prostate cases involving interfraction prostate shifts and replans. Conclusion: Variation of DVH for PTV in prostate VMAT can be predicted using a pre-calculated patient database with DVH curve fitting. The computing time is fast because CT rescan and replan are not required. This quick DVH estimation can help radiation staff to determine if the changed PTV coverage due to prostate shift is tolerable in the treatment. However, it should be noted that the program can only consider prostate interfraction motions along three axes, and is restricted to prostate VMAT plan using the same plan script in the treatment planning system.
60 APPLIED LIFE SCIENCES↗
SU-E-T-143: Automatic PBS Treatment Planning for Prostate Cancer
Purpose: This study presents a novel idea of using automated planning technique for parallel-opposed prostate plans with pencil beam scanning proton therapy. Methods: A random 5 clinical prostate patients treated with parallel-opposed modulated-scanning proton beam in our proton center were selected in this study. All of the 5 cases were re-planned with in-house developed python scripts integrated into RayStation 4.0 clinical version. This automatic tool was designed to perform patient DICOM data import, external structure contours, CT density assignment, prescription to PTV assignment, beam placement, optimization, and dose calculation. Results: The mean time to generate a complete treatment plan was 1 minute per plan. For the automatically generated plans, 5 out of 5 plans (100%) were deemed clinically acceptable by one experienced radiation oncologist. In addition, the automated plans were overall dosimetrically equivalent to the clinical plans when scored for target coverage, rectum and bladder dose. Mann-Whitney U tests did not show significant dosimetric differences for normal tissue structures between the clinical and automated plans. Conclusion: We have developed a robust and automated method for fully inversed planned paralleled-opposed prostate proton treatment planning. This efficient method can be readily integrated into clinical practice. The tool produces clinically acceptable plans using only manually contoured anatomic structures and simulation CT data set. We anticipate that this tool will not only improve patient access to high-quality proton treatment by simplifying the planning process and will also reduce the effort and cost of incorporating more advanced planning into clinical practice in the near future.
60 APPLIED LIFE SCIENCES↗
SU-E-T-465: Implementation of An Automated Collision Detection Program Using Open Source Software for the Pinnacle Treatment Planning System
Purpose: Potential collisions between the gantry head and the patient or table assembly are difficult to detect in most treatment planning systems. We have developed and implemented a novel software package for the representation of potential gantry collisions with the couch assembly at the time of treatment planning. Methods: Physical dimensions of the Varian Edge linear accelerator treatment head were measured and reproduced using the Visual Python display package. A script was developed for the Pinnacle treatment planning system to generate a file with the relevant couch, gantry, and isocenter positions for each beam in a planning trial. A python program was developed to parse the information from the TPS and produce a representative model of the couch/gantry system. Using the model and the Visual Python libraries, a rendering window is generated for each beam that allows the planner to evaluate the possibility of a collision. Results: Comparison against heuristic methods and direct verification on the machine validated the collision model generated by the software. Encounters of <1 cm between the gantry treatment head and table were visualized as collisions in our virtual model. Visual windows were created depicting the angle of collision for each beam, including the anticipated table coordinates. Visual rendering of a 6 arc trial with multiple couch positions was completed in under 1 minute, with network bandwidth being the primary bottleneck. Conclusion: The developed software allows for quick examination of possible collisions during the treatment planning process and helps to prevent major collisions prior to plan approval. The software can easily be implemented on future planning systems due to the versatility and platform independence of the Python programming language. Further integration of the software with the treatment planning system will allow the possibility of patient-gantry collision detection for a range of treatment machines.
60 APPLIED LIFE SCIENCES↗
SU-E-T-500: Initial Implementation of GPU-Based Particle Swarm Optimization for 4D IMRT Planning in Lung SBRT
Purpose 4D-IMRT planning, combined with dynamic MLC tracking delivery, utilizes the temporal dimension as an additional degree of freedom to achieve improved OAR-sparing. The computational complexity for such optimization increases exponentially with increase in dimensionality. In order to accomplish this task in a clinically-feasible time frame, we present an initial implementation of GPU-based 4D-IMRT planning based on particle swarm optimization (PSO). Methods The target and normal structures were manually contoured on ten phases of a 4DCT scan of a NSCLC patient with a 54cm3 right-lower-lobe tumor (1.5cm motion). Corresponding ten 3D-IMRT plans were created in the Eclipse treatment planning system (Ver-13.6). A vendor-provided scripting interface was used to export 3D-dose matrices corresponding to each control point (10 phases × 9 beams × 166 control points = 14,940), which served as input to PSO. The optimization task was to iteratively adjust the weights of each control point and scale the corresponding dose matrices. In order to handle the large amount of data in GPU memory, dose matrices were sparsified and placed in contiguous memory blocks with the 14,940 weight-variables. PSO was implemented on CPU (dual-Xeon, 3.1GHz) and GPU (dual-K20 Tesla, 2496 cores, 3.52Tflops, each) platforms. NiftyReg, an open-source deformable image registration package, was used to calculate the summed dose. Results The 4D-PSO plan yielded PTV coverage comparable to the clinical ITV-based plan and significantly higher OAR-sparing, as follows: lung Dmean=33%; lung V20=27%; spinal cord Dmax=26%; esophagus Dmax=42%; heart Dmax=0%; heart Dmean=47%. The GPU-PSO processing time for 14940 variables and 7 PSO-particles was 41% that of CPU-PSO (199 vs. 488 minutes). Conclusion Truly 4D-IMRT planning can yield significant OAR dose-sparing while preserving PTV coverage. The corresponding optimization problem is large-scale, non-convex and computationally rigorous. Our initial results indicate that GPU-based PSO with further software optimization can make such planning clinically feasible. This work was supported through funding from the National Institutes of Health and Varian Medical Systems.
60 APPLIED LIFE SCIENCES↗
SU-E-T-567: Neutron Dose Equivalent Evaluation for Pencil Beam Scanning Proton Therapy with Apertures
Purpose: To determine the neutron contamination from the aperture in pencil beam scanning during proton therapy. Methods: A Monte Carlo based proton therapy research platform TOPAS and the UF-series hybrid pediatric phantoms were used to perform this study. First, pencil beam scanning (PBS) treatment pediatric plans with average spot size of 10 mm at iso-center were created and optimized for three patients with and without apertures. Then, the plans were imported into TOPAS. A scripting method was developed to automatically replace the patient CT with a whole body phantom positioned according to the original plan iso-center. The neutron dose equivalent was calculated using organ specific quality factors for two phantoms resembling a 4- and 14-years old patient. Results: The neutron dose equivalent generated by the apertures in PBS is 4–10% of the total neutron dose equivalent for organs near the target, while roughly 40% for organs far from the target. Compared to the neutron dose equivalent caused by PBS without aperture, the results show that the neutron dose equivalent with aperture is reduced in the organs near the target, and moderately increased for those organs located further from the target. This is due to the reduction of the proton dose around the edge of the CTV, which causes fewer neutrons generated in the patient. Conclusion: Clinically, for pediatric patients, one might consider adding an aperture to get a more conformal treatment plan if the spot size is too large. This work shows the somewhat surprising fact that adding an aperture for beam scanning for facilities with large spot sizes reduces instead of increases a potential neutron background in regions near target. Changran Geng is supported by the Chinese Scholarship Council (CSC) and the National Natural Science Foundation of China (Grant No. 11475087)
61 RADIATION PROTECTION AND DOSIMETRY↗
SU-E-T-603: PBS Prostate Plan Robustness: A Tool for Patient Specific Setup Tolerance
Purpose: Fiducial markers are commonly used for setup of prostate patients using orthogonal radiographs. After aligned with the markers, the displacement of the bony anatomy relative to the planned DRR can be up to 10 mm. Such offset can potentially have significant dosimetric effects because it changes the radiological path length of protons in differing amounts of bone. It is imperative to develop a method to evaluate its impact on target coverage and hence establish patient specific setup tolerance for prostate proton PBS treatment. Methods: Prostate patients were planned in RayStation according to the PCG protocol with bi-lateral beams. The primary planning objectives are: (1) 100% of CTV receives full prescription dose; (2) 98% of the prescription dose covers at least 98% of the PTV; (3) OARs meet criteria per protocol. For each patient 108 dose perturbations were automatically generated using an in-house script, which considered the isocenter shifting in S-I and A-P directions (up to ±15 mm with an interval of 6mm) as well as the range uncertainty (±3.5%). The target coverage was evaluated on the contour shifted along with prostate to mimic the daily treatment. Results: The minimum CTV coverage as a function of offsets in S-I and A-P directions is presented in a 2D contour map. The offsets along A-P direction generally have greater impact than along S-I direction. Both the CTV D98%>98% or CTV V98%>98% are achievable for most patients if the offset is <10 mm in either direction despite of range uncertainties. Conclusion: We developed a method to evaluate the plan robustness for proton PBS prostate treatment. It can provide patient specific setup tolerance of bony structure offset. For our current planning approach, a 1 cm displacement is acceptable. This approach can be generalized to other target structures that move relative to bony anatomy.
61 RADIATION PROTECTION AND DOSIMETRY↗