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At least 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

WE-DE-201-11: Sensitivity and Specificity of Verification Methods Based On Total Reference Air Kerma (TRAK) Or On User Provided Dose Points for Graphically Planned Skin HDR Brachytherapy

Purpose: To investigate the sensitivity and specificity of a novel verification methodology for image-guided skin HDR brachytherapy plans using a TRAK-based reasonableness test, compared to a typical manual verification methodology. Methods: Two methodologies were used to flag treatment plans necessitating additional review due to a potential discrepancy of 3 mm between planned dose and clinical target in the skin. Manual verification was used to calculate the discrepancy between the average dose to points positioned at time of planning representative of the prescribed depth and the expected prescription dose. Automatic verification was used to calculate the discrepancy between TRAK of the clinical plan and its expected value, which was calculated using standard plans with varying curvatures, ranging from flat to cylindrically circumferential. A plan was flagged if a discrepancy >10% was observed. Sensitivity and specificity were calculated using as a criteria for true positive that >10% of plan dwells had a distance to prescription dose >1 mm different than prescription depth (3 mm + size of applicator). All HDR image-based skin brachytherapy plans treated at our institution in 2013 were analyzed. Results: 108 surface applicator plans to treat skin of the face, scalp, limbs, feet, hands or abdomen were analyzed. Median number of catheters was 19 (range, 4 to 71) and median number of dwells was 257 (range, 20 to 1100). Sensitivity/specificity were 57%/78% for manual and 70%/89% for automatic verification. Conclusion: A check based on expected TRAK value is feasible for irregularly shaped, image-guided skin HDR brachytherapy. This test yielded higher sensitivity and specificity than a test based on the identification of representative points, and can be implemented with a dedicated calculation code or with pre-calculated lookup tables of ideally shaped, uniform surface applicators.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

The Future of Electricity Resource Planning

Electricity resource planning is the process of identifying longer-term investments to meet electricity reliability requirements and public policy goals at a reasonable cost. Resource planning processes provide a forum for regulators, electric utilities, and electricity industry stakeholders to evaluate the economic, environmental, and social benefits and costs of different investment options. By facilitating a discussion on future goals, challenges and strategies, resource planning processes often play an important role in shaping utility business decisions. Resource planning emerged more than three decades ago in an era of transition, where declining electricity demand and rising costs spurred fundamental changes in electricity industry regulation and structure. Despite significant changes in the industry, resource planning continues to play an important role in supporting investment decision making. Over the next two decades, the electricity industry will again undergo a period of transition, driven by technological change, shifting customer preferences and public policy goals. This transition will bring about a gradual paradigm shift in resource planning, requiring changes in scope, approaches and methods. Even as it changes, resource planning will continue to be a central feature of the electricity industry. Its functions — ensuring the reliability of high voltage (“bulk”) power systems, enabling oversight of regulated utilities and facilitating low-cost compliance with public policy goals — are likely to grow in importance as the electricity industry enters a new period of technological, economic and regulatory change. This report examines the future of electricity resource planning in the context of a changing electricity industry. The report examines emerging issues and evolving practices in five key areas that will shape the future of resource planning: (1) central-scale generation, (2) distributed generation, (3) demand-side resources, (4) transmission and (5) uncertainty and risk management. The analysis draws on a review of recent resource plans for 10 utilities that reflect some of the U.S. electricity industry’s extensive diversity.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Best Practices in Integrated Resource Planning: A guide for planners developing the electricity resource mix of the future

Most states today require regulated electric utilities to file an IRP every 1 to 5 years, and some utilities voluntarily prepare these plans. Planning needs have changed in recent years due to emerging load growth, plant retirements, rising costs, and more extreme weather events – among other factors. In response, Synapse Energy Economics and Lawrence Berkeley National Laboratory produced a joint report, Best Practices in Integrated Resource Planning: A guide for planners developing the electricity resource mix of the future. The guide offers best planning practices for electricity systems undergoing a major transition, but also contains a wealth of practical guidance to develop technically sophisticated, clearer, more effective, and state-of-the-art electric utility resource plans. The guide is for resource planning professionals and stakeholders involved in resource planning processes. This diverse group includes utility personnel tasked with conducting resource planning and making investment decisions, state regulatory commissions that develop planning guidance and oversee the resource planning process, and stakeholders that represent a wide range of interests—utility consumer advocates, environmental groups, industrial customers, local governments, independent power producers, and many other

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

State Requirements for Electric Distribution System Planning

Utilities have conducted distribution planning since they first began building and operating electricity systems. But filing these plans for regulatory and stakeholder review is a relatively recent phenomenon. This report summarizes legislative and regulatory requirements for regulated electric utilities to file some type of distribution system plan in 20 U.S. jurisdictions. Some plans focus on expedited cost recovery for certain types of distribution system improvements; other plans focus on investments for grid modernization or distributed energy resources. Increasingly, states are adopting requirements for Integrated Distribution Plans. Such plans provide holistic grid investment strategies that address state and local policies and increasing complexity at the grid edge. The report covers the following topics for distribution system plans, highlighting advanced practices: -State goals and objectives -Procedural requirements -Forecasting loads and distributed energy resources -Hosting capacity analysis -Baseline information requirements -Grid modernization strategy -Grid needs assessment -Non-wires solutions -Reliability and resilience analyses -Stakeholder engagement -Equity -Pilots -Coordination with other planning processes The report includes links to legislation; regulatory requirements, proceedings, and orders; and filed utility plans. The U.S. Department of Energy’s Office of Electricity provided funding support.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1994

Abstraction Planning in Real Time

When a planning agent works in a complex, real-world domain, it is unable to plan for and store all possible contingencies and problem situations ahead of time. This thesis presents a method for planning a run time that incrementally builds up plans at multiple levels of abstraction. The plans are continually updated by information from the world, allowing the planner to adjust its plan to a changing world during the planning process. All the information is represented over intervals of time, allowing the planner to reason about durations, deadlines, and delays within its plan. In addition to the method, the thesis presents a formal model of the planning process and uses the model to investigate planning strategies.

COMPUTER PROGRAMMING↗
NASA NTRSDate not supplied

COCPIT: Collaborative Activity Planning Software for Mars Perseverance Rover

Since landing on the Martian surface, the Perseverance rover has relied on a distributed team to generate commands for exploring its new environment each sol(Martian day). The team uses a complex suite of software tools to accomplish this challenging task in time for the next window of opportunity to send commands to the rover. A key piece of this software ecosystem is COCPIT (Component-based Campaign Planning, Implementation, and Tactical). COCPIT is part of the next generation of planning and scheduling software tools developed by NASA's Jet Propulsion Laboratory in partnership with NASA's Ames Research Center. COCPIT is a web-based application that allows users to collaboratively view and update the Perseverance rover's activity plans, continuously verify that the plan satisfies constraints, assign targets for directing scientific instruments, document science intent, and model power and data resources. Mars Surface Operations requires diverse expertise from team members within the Engineering, Science, Robotic, and Instrument Operations groups, distributed across North America and Europe. In order to improve efficiency and reduce risk, all teams are able to review and edit their activities simultaneously and see the effects on the plan in its entirety. As part of the Ground Data System (GDS) tool suite, COCPIT is responsible for the activity plan. It provides specialized views that allow operators to understand where there may be room for additional observations, see whether any planning constraints are being violated, and confirm that energy usage and data generation are within the defined limits. It contains details such as which filters a camera will use for a given observation, what the resolution of the images should be, where to store the data onboard, and how long the observation is expected to take. It predicts when specific data will be downlinked from the rover to a passing orbiter, so that the team knows when to expect that data on Earth for evaluation in future planning. Ultimately the information from the COCPIT plan is translated to sequences that will be bundled and radiated to Perseverance for execution. The COCPIT tool is used throughout all planning phases.

activity planning↗
NASA NTRSDate not supplied

COCPIT: Collaborative Activity Planning Software for Mars Perseverance Rover

Since landing on the Martian surface, the Perseverance rover has relied on a distributed team to generate commands for exploring its new environment each sol(Martian day). The team uses a complex suite of software tools to accomplish this challenging task in time for the next window of opportunity to send commands to the rover. A key piece of this software ecosystem is COCPIT (Component-based Campaign Planning, Implementation, and Tactical). COCPIT is part of the next generation of planning and scheduling software tools developed by NASA's Jet Propulsion Laboratory in partnership with NASA's Ames Research Center. COCPIT is a web-based application that allows users to collaboratively view and update the Perseverance rover's activity plans, continuously verify that the plan satisfies constraints, assign targets for directing scientific instruments, document science intent, and model power and data resources. Mars Surface Operations requires diverse expertise from team members within the Engineering, Science, Robotic, and Instrument Operations groups, distributed across North America and Europe. In order to improve efficiency and reduce risk, all teams are able to review and edit their activities simultaneously and see the effects on the plan in its entirety. As part of the Ground Data System (GDS) tool suite, COCPIT is responsible for the activity plan. It provides specialized views that allow operators to understand where there may be room for additional observations, see whether any planning constraints are being violated, and confirm that energy usage and data generation are within the defined limits. It contains details such as which filters a camera will use for a given observation, what the resolution of the images should be, where to store the data onboard, and how long the observation is expected to take. It predicts when specific data will be downlinked from the rover to a passing orbiter, so that the team knows when to expect that data on Earth for evaluation in future planning. Ultimately the information from the COCPIT plan is translated to sequences that will be bundled and radiated to Perseverance for execution. The COCPIT tool is used throughout all planning phases.

activity planning↗
DOE OSTI2011

Shot Planning and Analysis Tools

Shot planning and analysis tools (SPLAT) integrate components necessary to help achieve a high over-all operational efficiency of the National Ignition Facility (NIF) by combining near and long-term shot planning, final optics demand and supply loops, target diagnostics planning, and target fabrication requirements. Currently, the SPLAT project is comprised of two primary tool suites for shot planning and optics demand. The shot planning component provides a web-based interface to selecting and building a sequence of proposed shots for the NIF. These shot sequences, or 'lanes' as they are referred to by shot planners, provide for planning both near-term shots in the Facility and long-term 'campaigns' in the months and years to come. The shot planning capabilities integrate with the Configuration Management Tool (CMT) for experiment details and the NIF calendar for availability. Future enhancements will additionally integrate with target diagnostics planning and target fabrication requirements tools. The optics demand component is built upon predictive modelling of maintenance requirements on the final optics as a result of the proposed shots assembled during shot planning. The predictive models integrate energetics from a Laser Performance Operations Model (LPOM), the status of the deployed optics as provided by the online Final Optics Inspection system, and physics-based mathematical 'rules' that predict optic flaw growth and new flaw initiations. These models are then run on an analytical cluster comprised of forty-eight Linux-based compute nodes. Results from the predictive models are used to produce decision-support reports in the areas of optics inspection planning, optics maintenance exchanges, and optics beam blocker placement advisories. Over time, the SPLAT project will evolve to provide a variety of decision-support and operation optimization tools.

42 ENGINEERING↗
DOE OSTI2024

Advanced Guide to Understanding Power System Model Results for Long-Term Resource Plans

This guide is for public utility commission staff, state energy office staff, and other stakeholders who review model results for utility integrated resource plans (IRPs). It builds on the "Beginner's Guide to Understanding Power System Model Results for Long-Term Resource Plans," and delves into more advanced topics that were not included or not fully covered in the beginner's guide. The topics included here are evolving and may or may not be important to the resource plan you are evaluating. Due to limitations in resources, it's also not possible to give the highest level of detail or attention to every topic within a plan. An important part of planning for an uncertain future involves deciding which topics deserve the most focus and resources. It's all about prioritizing efforts where they will have the most impact or be most beneficial despite uncertainties ahead. As with the beginner's guide, we intend for this guide to help improve decision-making in the electricity planning process by strengthening understanding and dialogue between electricity system planners and relevant stakeholders. The following information is designed to allow you to better engage in the planning process by evaluating results, asking questions, and thinking through what is most important. We allocate significant discussion in the guide to electricity demand evolution, demand-side resources, and resource adequacy. These topics have garnered increasing attention, hence their prominence in this guide. Other topics are also presented, but their incorporation into the planning process might vary based on interest and relevance. The absence of certain topics doesn't diminish their importance; rather, it reflects the reality that in planning, trade-offs necessitate prioritizing certain aspects over others.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Methods for Reducing Normal Tissue Complication Probabilities in Oropharyngeal Cancer: Dose Reduction or Planning Target Volume Elimination

Purpose: Strategies to reduce the toxicities of head and neck radiation (ie, dysphagia [difficulty swallowing] and xerostomia [dry mouth]) are currently underway. However, the predicted benefit of dose and planning target volume (PTV) reduction strategies is unknown. The purpose of the present study was to compare the normal tissue complication probabilities (NTCP) for swallowing and salivary structures in standard plans (70 Gy [P70]), dose-reduced plans (60 Gy [P60]), and plans eliminating the PTV margin. Methods and Materials: A total of 38 oropharyngeal cancer (OPC) plans were analyzed. Standard organ-sparing volumetric modulated arc therapy plans (P70) were created and then modified by eliminating the PTVs and treating the clinical tumor volumes (CTVs) only (C70) or maintaining the PTV but reducing the dose to 60 Gy (P60). NTCP dose models for the pharyngeal constrictors, glottis/supraglottic larynx, parotid glands (PGs), and submandibular glands (SMGs) were analyzed. The minimal clinically important benefit was defined as a mean change in NTCP of >5%. The P70 NTCP thresholds and overlap percentages of the organs at risk with the PTVs (56-59 Gy, vPTV{sub 56}) were evaluated to identify the predictors for NTCP improvement. Results: With the P60 plans, only the ipsilateral PG (iPG) benefited (23.9% vs 16.2%; P<.01). With the C70 plans, only the iPG (23.9% vs 17.5%; P<.01) and contralateral SMG (cSMG) (NTCP 32.1% vs 22.9%; P<.01) benefited. An iPG NTCP threshold of 20% and 30% predicted NTCP benefits for the P60 and C70 plans, respectively (P<.001). A cSMG NTCP threshold of 30% predicted for an NTCP benefit with the C70 plans (P<.001). Furthermore, for the iPG, a vPTV{sub 56} >13% predicted benefit with P60 (P<.001) and C70 (P=.002). For the cSMG, a vPTV{sub 56} >22% predicted benefit with C70 (P<.01). Conclusions: PTV elimination and dose-reduction lowered the NTCP of the iPG, and PTV elimination lowered the NTCP of the cSMG. NTCP thresholds and the percentage of overlap of the PTV with organs at risk can predict which patients will benefit and inform future clinical trial design.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

SU-E-T-39: Analyses of Plan Quality Using Different Gantry Rotation Time On Volumetric Modulated Arc Therapy in Rectal Carcinoma

Purpose: To compare plan quality of volumetric modulated arc radiotherapy (VMAT) using different gantry rotation times. Methods: In ten rectal carcinoma patients, plans with different gantry rotation times were designed by Oncentra4.3 planning system, each of them was optimized by experienced planners using almost similar parameters and dose constraints except the different gantry rotation time. The gantry rotation time was increased from 30s to 150s by step of 30(30s, 60s, 90s, 120s, and 150s). Plans (VMAT30s, VMAT60s, VMAT90s, VMAT120s and VMAT150s) were normalized so that at least 95% of PTV would receive the prescription dose 50 Gray in 25 fractions. Dose-volume histograms and isodose distributions were evaluated. Conformity indices (CI), homogeneous indices (HI), monitor units (MUs), delivery time were also compared. Results: As the increasing of gantry rotation time, VMAT150s provided comparable organs at risk sparing and better target coverage and conformity than VMAT30s. In the normal tissue such as bladder and femurs, the VMAT plans show almost the same V30 and Dmean for them compared with IMRT plans, meanwhile the conformity indices (CI) was better than IMRT plans(p=0.021). However, there was no significant different among the VMAT60s, VMAT90s, VMAT120s and VMAT150s (p=0.054). VMAT150s increased delivery time and monitor units in plans without improving plan quality compared to VMAT60s, VMAT90s and VMAT120s. Conclusion: VMAT60s, VMAT90s, VMAT120s and VMAT150s achieved comparable treatment plans in rectal carcinoma. Slower gantry movement in VMAT150s only improves slight improvement than the others.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-T-199: How Number of Control Points Influences the Dynamic IMRT Plan Quality and Deliverability

Purpose: To study the influence of number of control points on plan quality and deliverability. Methods: Five previously treated patients of carcinoma of rectum were selected. Planning target volume (PTV) and organs at risk (OARs) i.e. bladder and bowel were contoured. Dynamic IMRT plans (6MV, 7-fields, 45Gy/25 fractions and prescribed at 95% isodose) were created in Eclipse (Varian medical system, Palo Alto, CA) treatment planning system (TPS) for Varian CL2300C/D linear-accelerator. Base plan was calculated with 166 control points, variable mode (Eclipse Default). For generating other plans, all parameters were kept constant, only number of control points (Fixed mode) was varied as follows: 100, 166 and 200. Then, plan quality was analyzed in terms of maximum and mean dose received by the PTV and OARs. For plan deliverability, TPS calculated fluence was verified with I’matriXX (IBA Dosimetry, Germany) array and compared with TPS dose-plane using gamma index criteria of 3% dose difference and 3mm distance to agreement (DTA). Total number of monitor units (MU) required to deliver a plan was also noted. Results: The maximum variation for the PTV maximum with respect to eclipse default control point (166) was 0.28% (0.14Gy). Similarly, PTV mean varied only up to 0.22 %( 0.11Gy). Bladder maximum and bladder mean varied up to 0.51% (0.24Gy) and 0.16% (0.06Gy). The variation for the bowel maximum and bowel mean was also only 0.39% (0.19Gy) and 0.33% (0.04Gy). Total MU was within 0.32 % (4MU). Average gamma pass rate using different control points for five patients are 98.75±0.33%, 99.37±0.09%, 99.29±0.12%, 98.14±0.13% and 99.25±0.14% respectively. Conclusion: Slight variation (<1%) in PTV and OARs maximum and mean doses was observed with varying number of control points. Monitor unit was also not varied much. Reducing number of control points did not showed any comprise in plan deliverability in terms of gamma index pass rate.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-T-552: Minimum Monitor Unit Effects On Plan Quality for Multi-Field Optimized Spot Scanning Proton Therapy

Purpose: To investigate the influence of the minimum monitor unit (MU) on the quality of clinical treatment plans for scanned proton therapy. Methods: Delivery system characteristics limit the minimum number of protons that can be delivered per spot, resulting in a min-MU limit. Plan quality can be impacted by the min-MU limit. Two sites were used to investigate the impact of min-MU on treatment plans: pediatric brain tumor at a depth of 5-10 cm; a head and neck tumor at a depth of 1-20 cm. Three field intensity modulated spot scanning proton plans were created for each site with the following parameter variations: min-MU limit range of 0.0000-0.0060; and spot spacing range of 0.5-2.0σ of the nominal spot size at isocenter in water (σ=4mm in this work). Comparisons were based on target homogeneity and normal tissue sparing. Results: The increase of the min-MU with a fixed spot spacing decreases plan quality both in homogeneous target coverage and in the avoidance of critical structures. Both head and neck and pediatric brain plans show a 20% increase in relative dose for the hot spot in the CTV and 10% increase in key critical structures when comparing min-MU limits of 0.0000 and 0.0060 with a fixed spot spacing of 1σ. The DVHs of CTVs show min-MU limits of 0.0000 and 0.0010 produce similar plan quality and quality decreases as the min-MU limit increases beyond 0.0020. As spot spacing approaches 2σ, degradation in plan quality is observed when no min-MU limit is imposed. Conclusion: Given a fixed spot spacing of ≤ 1σ of the spot size in water, plan quality decreases as min- MU increases greater than 0.0020. The effect of min-MU should be taken into consideration while planning spot scanning proton therapy treatments to realize its full potential.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-T-616: Comparison of Plan Dose Accuracy for Anterior Vs. Lateral Fields in Proton Therapy of Prostate Cancer

Purpose: With the anticipated introduction of in vivo range verification methods, the use of anterior fields for proton therapy of prostate cancer may become an attractive treatment option, and improve upon the dose distributions achievable with conventional lateral-opposed fields. This study aimed to evaluate and compare the planned dose accuracy for lateral versus anterior oblique field arrangements. Methods: Four patients with low/intermediate risk prostate cancer, participating in a clinical trial at our institution, were selected for this study. All patients were treated using lateral-opposed fields (LAT). The clinical target volume (CTV) received a total dose of 79.2 Gy in 44 fractions. Anterior oblique research plans (ANT) were created using the clinical planning system, and featured beams with ±35-degree gantry angle, 1.2 cm aperture margins, 3-mm range compensator smearing and no range uncertainty margins. Monte Carlo (MC) simulations were performed for both beam arrangements using TOPAS. Dose volume histograms were analyzed and compared for planned and MC dose distributions. Differences between MC and planned DVH parameters were computed as a percentage of the total prescribed dose. Results: For all patients, CTV dose was systematically lower (∼2–2.5%) for MC than the plan. This discrepancy was slightly larger (∼0.5%) for LAT compared to ANT plans for all cases. Although the dose differences for bladder and anterior rectal wall remained within 0.7% for all LAT cases, they were slightly larger for ANT plans, especially for case 3 due to larger patient size and MC-plan range difference. The EUD difference for femoral heads was within 0.6% for both LAT and ANT cases. Conclusion: The dose calculated by the treatment planning system using pencil beam algorithm agrees with MC to within 2.5% and is comparable for lateral and anterior scenarios. The dose agreement in the anterior rectal wall is range- and hence, patient-dependent for ANT treatments.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-T-622: Identification and Improvement of Patients Eligible for Dose Escalation with Matched Plans

Purpose: Radiation-therapy dose-escalation beyond 80Gy may improve tumor control rates for patients with localized prostate cancer. Since toxicity remains a concern, treatment planners must achieve dose-escalation while still adhering to dose-constraints for surrounding structures. Patientmatching is a machine-learning technique that identifies prior patients that dosimetrically match DVH parameters of target volumes and critical structures prior to actual treatment planning. We evaluated the feasibility of patient-matching in (1)identifying candidates for safe dose-escalation; and (2)improving DVH parameters for critical structures in actual dose-escalated plans. Methods: We analyzed DVH parameters from 319 historical treatment plans to determine which plans could achieve dose-escalation (8640cGy) without exceeding Zelefsky dose-constraints (rectal and bladder V47Gy<53%, and V75.6Gy<30%, max-point dose to rectum of 8550cGy, max dose to PTV< 9504cGy). We then estimated the percentage of cases that could achieve safe dose-escalation using software that enables patient matching (QuickMatch, Siris Medical, Mountain View, CA). We then replanned a case that had violated DVH constraints with DVH parameters from patient matching, in order to determine whether this previously unacceptable plan could be made eligible with this automated technique. Results: Patient-matching improved the percentage of patients eligible for dose-escalation from 40% to 63% (p=4.7e-4, t-test). Using a commercial optimizer augmented with patient-matching, we demonstrated a case where patient-matching improved the toxicity-profile such that dose-escalation would have been possible; this plan was rapidly achieved using patientmatching software. In this patient, all lower-dose constraints were met with both the denovo and patient-matching plan. In the patient-matching plan, maximum dose to the rectum was 8385cGy, while the denovo plan failed to meet the maximum rectal constraint at 8571cGy. Conclusion: Patientmatching is a promising method to identify eligible patients, and to assist in creating acceptable plans for dose-escalation. Further study will investigate other disease states. Additionally, the time-savings provided by patientmatching warrants further investigation. The following authors have equity ownership in Siris Medical, Inc: K Bush, TF Atwood.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-618: Plan Robustness Study of Volumetric-Modulated Arc Therapy Vs. Intensity-Modulated Radiation Therapy for Head and Neck Cancer

Purpose: Lack of plan robustness may contribute to local failure in volumetric-modulated arc therapy (VMAT) to treat head and neck (H&N) cancer. Thus we compared plan robustness of VMAT with intensity-modulated radiation therapy (IMRT). Methods: VMAT and IMRT plans were created for 9 H&N cancer patients. For each plan, six new perturbed dose distributions were computed — one each for ± 3mm setup deviations along the S-I, A-P and L-R directions. We used three robustness quantification tools: (1) worst-case analysis (WCA); (2) dose-volume histograms (DVHs) band (DVHB); and (3) root-mean-square-dose deviation (RMSD) volume histogram (DDVH). DDVH represents the relative volume (y) on the vertical axis and the RMSD (x) on the horizontal axis. Similar to DVH, this means that y% of the volume of the indicated structure has the RMSD at least x Gy[RBE].The width from the first two methods at different target DVH indices (such as D95 and D5) and the area under the DDVH curves (AUC) for the target were used to indicate plan robustness. In these robustness quantification tools, the smaller the value, the more robust the plan is. Plan robustness evaluation metrics were compared using Wilcoxon test. Results: DVHB showed the width at D95 from IMRT to be larger than from VMAT (unit Gy) [1.59 vs 1.18 (p=0.49)], while the width at D5 from IMRT was found to be slightly larger than from VMAT [0.59 vs 0.54 (p=0.84)]. WCA showed similar results [D95: 3.28 vs 3.00 (p=0.56); D5: 1.68 vs 1.95 (p=0.23)]. DDVH showed the AUC from IMRT to be slightly smaller than from VMAT [1.13 vs 1.15 (p=0.43)]. Conclusion: VMAT plan robustness is comparable to IMRT plan robustness. The plan robustness conclusions from WCA and DVHB are DVH parameter dependent. On the other hand DDVH captures the overall effect of uncertainties on the dose to a volume of interest. NIH/NCI K25CA168984; Eagles Cancer Research Career Development; The Lawrence W. and Marilyn W. Matteson Fund for Cancer Research Mayo ASU Seed Grant; The Kemper Marley Foundation.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

TU-FG-201-03: Automatic Pre-Delivery Verification Using Statistical Analysis of Consistencies in Treatment Plan Parameters by the Treatment Site and Modality

Purpose: A novel computer software system, namely APDV (Automatic Pre-Delivery Verification), has been developed for verifying patient treatment plan parameters right prior to treatment deliveries in order to automatically detect and prevent catastrophic errors. Methods: APDV is designed to continuously monitor new DICOM plan files on the TMS computer at the treatment console. When new plans to be delivered are detected, APDV checks the consistencies of plan parameters and high-level plan statistics using underlying rules and statistical properties based on given treatment site, technique and modality. These rules were quantitatively derived by retrospectively analyzing all the EBRT treatment plans of the past 8 years at authors’ institution. Therapists and physicists will be notified with a warning message displayed on the TMS computer if any critical errors are detected, and check results, confirmation, together with dismissal actions will be saved into database for further review. Results: APDV was implemented as a stand-alone program using C# to ensure required real time performance. Mean values and standard deviations were quantitatively derived for various plan parameters including MLC usage, MU/cGy radio, beam SSD, beam weighting, and the beam gantry angles (only for lateral targets) per treatment site, technique and modality. 2D-based rules of combined MU/cGy ratio and averaged SSD values were also derived using joint probabilities of confidence error ellipses. The statistics of these major treatment plan parameters quantitatively evaluate the consistency of any treatment plans which facilitates automatic APDV checking procedures. Conclusion: APDV could be useful in detecting and preventing catastrophic errors immediately before treatment deliveries. Future plan including automatic patient identify and patient setup checks after patient daily images are acquired by the machine and become available on the TMS computer. This project is supported by the Agency for Healthcare Research and Quality (AHRQ) under award 1R01HS0222888. The senior author received research grants from ViewRay Inc. and Varian Medical System.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Los Alamos National Laboratory SAVY-4000 Field Surveillance Plan Update for 2016

The Packaging Surveillance Program section of the Department of Energy (DOE) Manual 441.1-1, Nuclear Material Packaging Manual (DOE 2008), requires DOE contractors to “ensure that a surveillance program is established and implemented to ensure the nuclear material storage package continues to meet its design criteria.” The Los Alamos National Laboratory (LANL) SAVY-4000 Field Surveillance Plan was first issued in FY 2013 (Kelly et al. 2013). The surveillance plan is reviewed annually and updated as necessary based on SAVY-4000 surveillance and other surveillance findings, as well as results of the lifetime extension studies (Blair et al. 2012, Weis et al. 2015a). The LANL SAVY-4000 Field Surveillance Plan Update was issued in 2014 (Kelly et al. 2014). This 2016 update reflects changes to the surveillance plan resulting from restrictions on handling residue materials greater than 500 g, the addition of specific engineering judgment containers, and 2015 surveillance findings. The SAVY-4000 container has a design life of five years, which was chosen as a conservative estimate of the functional properties of the materials used in the construction of the SAVY 4000 when exposed to the potential insults including temperature, corrosive materials and gases, and radiation. The SAVY-4000 container design basis is described in a safety analysis report (Anderson et al. 2013). In the National Nuclear Security Administration's (NNSA’s) approval of the safety analysis report, it was recommended that the design life clock begin on March 2014 (Nez et al. 2014). However, it is expected that a technical basis can be developed to extend the design life of the SAVY-4000 containers to approximately 40 years (Blair et al. 2012, Weis et al. 2015a). This surveillance plan update covers five years (2015–2019) and is developed to ensure SAVY-4000 containers meet their design criteria over the current five-year design life and to gather data that can be used in developing the technical basis for a 40-year design life. The technical basis for the longer design life will be developed based on the results of this surveillance plan and the concurrent lifetime extension studies (Blair et al. 2012, Weis et al. 2015a). A long-term surveillance plan will be developed by the completion of this plan and will be based on the results of the first several years of this five-year surveillance plan and the lifetime extension studies. In addition, the current Hagan container population is so large (approximately 3,500 LANL-wide, approximately 3,000 in PF-4) that it is anticipated Hagan containers will be in use for many years to come. Therefore, this plan includes surveillance activities for the Hagan container system during the time it takes to replace the Hagan containers with manually-compliant containers such as the SAVY 4000. These Hagan examinations not only provide information to determine if additional Hagan surveillance is needed, but also support SAVY lifetime-extension studies because some of the container components are made from similar material (e.g., stainless steel and Viton).

42 ENGINEERING↗