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Section 180(c) Policy Implementation Exercise: Multiple Views - 17383

The Department of Energy (DOE) Office of Nuclear Energy's Office of Integrated Waste Management (formerly the Nuclear Fuels Storage and Transportation Planning Project) recently completed a two-year Section 180(c) Proposed Policy Implementation Exercise (the Exercise) with volunteers from eight states and one Native American Tribe. Under Section 180(c) of the Nuclear Waste Policy Act of 1982, as amended (NWPA), DOE is responsible for providing technical and financial assistance to states and Tribes for training of local public safety officials through whose jurisdictions the Secretary of Energy plans to transport spent nuclear fuel (SNF) or high-level radioactive waste to a NWPA-authorized facility. In the 2000's, DOE staff worked closely with state and tribal representatives to develop a revised proposed policy to implement Section 180(c), including grants for assessment and planning activities, as well as grants for training public safety officials. This revised proposed policy was published in a Federal Register Notice in 2008 (2008 FRN) (73 Federal Register 64933, Oct. 31, 2008). The purpose of the Exercise was to evaluate the efficacy of DOE's 2008 revised proposed policy for implementing Section 180(c), and identify outstanding issues to be resolved. DOE presented an interim update on the Exercise at the 2016 Waste Management Symposium and the Exercise concluded in June 2016. This paper describes the remaining activities of the Exercise that occurred since the 2016 Waste Management Symposium, and presents the perspectives of one state and one Tribal participant in the Exercise as well as DOE's perspective. The paper concludes with a discussion of the lessons learned from the Exercise, what steps are next, and how the Exercise may inform and improve future consultations between DOE and state, tribal, and local public safety officials. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

SU-E-T-267: Proton Pencil Beam Scanning for Mediastinal Lymphoma: 4-Dimensional Feasibility Study

Purpose: To assess the feasibility of proton pencil beam scanning (PBS) for the treatment of mediastinal lymphoma. Methods: A group of 6 patients were planned using an anterior field with PBS. Spots with ∼5 mm σ were used for all patients, while large spots (∼10 mm σ) were employed for patients with motion perpendicular to the beam (≥5 mm). We considered volumetric repainting such that, in each fraction, the same field would be delivered twice. Four-dimensional dose was calculated on initial and verification 4-dimensional computed tomography (4D-CT) scans (2—3) based on respiratory trace and beam delivery sequence. This was implemented by binning the spots into separate plans on each 4D-CT phase respectively. Four starting phases were sampled for each painting and 4 energy switching times (0.5 s, 1 s, 3 s, and 5 s) were tested, resulting in 2560 dose distributions for the cohort. Plan robustness was measured for target and critical structures in terms of the percentage difference between delivered dose and planned dose. Results: For 5 of the 6 patients, the ITV (internal target volume) D 98% was degraded by <3% (standard deviations ∼ 0.1%) when averaged over the whole course (up to 5% per fraction). Deviations of mean lung dose, heart maximum dose, and cord maximum dose were within 5% of prescribed dose. For one patient with motion perpendicular to the beam (up to 5 mm), the degradation of ITV D 98% was 9% over the whole course (12% per fraction), which was mitigated to 1% (3% per fraction) by employing large spots and repainting. No significant difference in coverage was observed for different energy switching times. Conclusion: This feasibility study demonstrates that, for mediastinal lymphoma, the PBS plan robustness can be maintained during delivery when target motion is measured and volumetric repainting and/or large spots are employed. This work was supported by Ion Beam Application.

60 APPLIED LIFE SCIENCES↗

Fast Biological Modeling for Voxel-based Heavy Ion Treatment Planning Using the Mechanistic Repair-Misrepair-Fixation Model and Nuclear Fragment Spectra

Purpose: The physical and biological differences between heavy ions and photons have not been fully exploited and could improve treatment outcomes. In carbon ion therapy, treatment planning must account for physical properties, such as the absorbed dose and nuclear fragmentation, and for differences in the relative biological effectiveness (RBE) of ions compared with photons. We combined the mechanistic repair-misrepair-fixation (RMF) model with Monte Carlo-generated fragmentation spectra for biological optimization of carbon ion treatment plans. Methods and Materials: Relative changes in double-strand break yields and radiosensitivity parameters with particle type and energy were determined using the independently benchmarked Monte Carlo damage simulation and the RMF model to estimate the RBE values for primary carbon ions and secondary fragments. Depth-dependent energy spectra were generated with the Monte Carlo code FLUKA for clinically relevant initial carbon ion energies. The predicted trends in RBE were compared with the published experimental data. Biological optimization for carbon ions was implemented in a 3-dimensional research treatment planning tool. Results: We compared the RBE and RBE-weighted dose (RWD) distributions of different carbon ion treatment scenarios with and without nuclear fragments. The inclusion of fragments in the simulations led to smaller RBE predictions. A validation of RMF against measured cell survival data reported in published studies showed reasonable agreement. We calculated and optimized the RWD distributions on patient data and compared the RMF predictions with those from other biological models. The RBE values in an astrocytoma tumor ranged from 2.2 to 4.9 (mean 2.8) for a RWD of 3 Gy(RBE) assuming (α/β){sub X} = 2 Gy. Conclusions: These studies provide new information to quantify and assess uncertainties in the clinically relevant RBE values for carbon ion therapy based on biophysical mechanisms. We present results from the first biological optimization of carbon ion radiation therapy beams on patient data using a combined RMF and Monte Carlo damage simulation modeling approach. The presented method is advantageous for fast biological optimization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Safety, reliability, maintainability and quality provisions for the Space Shuttle program

This publication establishes common safety, reliability, maintainability and quality provisions for the Space Shuttle Program. NASA Centers shall use this publication both as the basis for negotiating safety, reliability, maintainability and quality requirements with Shuttle Program contractors and as the guideline for conduct of program safety, reliability, maintainability and quality activities at the Centers. Centers shall assure that applicable provisions of the publication are imposed in lower tier contracts. Centers shall give due regard to other Space Shuttle Program planning in order to provide an integrated total Space Shuttle Program activity. In the implementation of safety, reliability, maintainability and quality activities, consideration shall be given to hardware complexity, supplier experience, state of hardware development, unit cost, and hardware use. The approach and methods for contractor implementation shall be described in the contractors safety, reliability, maintainability and quality plans. This publication incorporates provisions of NASA documents: NHB 1700.1 'NASA Safety Manual, Vol. 1'; NHB 5300.4(IA), 'Reliability Program Provisions for Aeronautical and Space System Contractors'; and NHB 5300.4(1B), 'Quality Program Provisions for Aeronautical and Space System Contractors'. It has been tailored from the above documents based on experience in other programs. It is intended that this publication be reviewed and revised, as appropriate, to reflect new experience and to assure continuing viability.

M S Malkin↗

Floorspace.js

Floorspace.js is a 2D geometry editor. Users can define an explicit floor plan for each story of a building. A story-by-story interface makes it easy to develop space geometry and assign properties. Referencing satellite imagery or floor plan images, when available, speeds up geometry entry. Conversion of 2D to 3D geometry is currently out of scope for Floorspace.js, a reference implementation is available in the OpenStudio® SDK. Explicit floor plans allow more building-specific information than parameterized shoe-boxes but less information than a full 3D BIM model. Sloped walls, complex roofs, detailed shading structures, and other complex 3D structures are out of FloorspaceJS's scope. In general, if users have a 3D BIM model in a tool that can export a useful BEM representation then it is better to use that export than to recreate a new model using FloorspaceJS. Re-usability and minimal dependencies were key design considerations for software developers. Web technologies can be used in both online and desktop applications. The editor was written in pure JavaScript for maximum portability and re-usability. A custom JavaScript Object Notation (JSON) file format was developed to ease integration with other applications. Custom JSON schema design was a key part of FloorspaceJS development.

Noland, Katie↗

SU-G-BRA-15: Dosimetric Evaluation of Dynamic Tumor Tracking Radiation Therapy Using Digital Phantom: A Study On Margin and Desired Accuracy of Tracking

Purpose: Dynamic tumor tracking radiation therapy can potentially reduce internal margin without prolongation of irradiation time. However, dynamic tumor tracking technique requires an extra margin (tracking margin, TM) for the uncertainty of tumor localization, prediction, and beam repositioning. The purpose of this study was to evaluate a dosimetric impact caused by TM. Methods: We used 4D XCAT to create 9 digital phantom datasets of different tumor size and motion range: tumor diameter TD=(1, 3, 5) cm and motion range MR=(1, 2, 3) cm. For each dataset, respiratory gating (30%–70% phase) and tumor tracking treatment plans were created using 8-field 3D-CRT by 4D dose calculation implemented in RayStation. The dose constraint was based on RTOG0618. For the tracking plan, TMs of (0, 2.5, 5) mm were considered by surrounding a normal setup margin: SM=5 mm. We calculated V20 of normal lung to evaluate the dosimetric impact for each case, and estimated an equivalent TM that affects the same impact on V20 obtained by the gated plan. Results: The equivalent TMs for (TD=1 cm, MR=2 cm), (TD=1 cm, MR=3 cm), (TD=5 cm, MR=2 cm), and (TD=5 cm, MR=3 cm) were estimated as 1.47 mm, 3.95 mm, 1.04 mm, and 2.13 mm, respectively. The larger the tumor size, the equivalent TM became smaller. On the other hand, the larger the motion range, the equivalent TM was found to be increased. Conclusion: Our results showed the equivalent TM changes depending on tumor size and motion range. The tracking plan with TM less than the equivalent TM achieves a dosimetric impact better than the gated plan in less treatment time. This study was partially supported by JSPS Kakenhi and Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗

Sewer System Management Plan

The Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC (NTESS), a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration (DOE/NNSA) under contract DE-NA0003525. In 2008, a Notice of Intent (NOI) was filed for the Sandia National Laboratories, California (SNL/CA) facility to be covered under the State Water Resources Control Board (SWRCB) Order No. 2006-0003-DWQ Statewide General Waste Discharge Requirements (WDR) for Sanitary Sewer Systems (General Permit) and was issued the WDID No. 2SSO11605. The General Permit requires a proactive approach to reduce the number and frequency of sanitary sewer overflows (SSOs) within the State. Provision D.11 of the General Permit requires the development and implementation of a written Sewer System Management Plan (SSMP). This SSMP is prepared according to the mandatory elements required by Provision D.13 and D.14, as well as the schedule for a population less than 2,500 as outlined in Provision D.15.

42 ENGINEERING↗

Research and applications: Artificial intelligence

Research in the field of artificial intelligence is discussed. The focus of recent work has been the design, implementation, and integration of a completely new system for the control of a robot that plans, learns, and carries out tasks autonomously in a real laboratory environment. The computer implementation of low-level and intermediate-level actions; routines for automated vision; and the planning, generalization, and execution mechanisms are reported. A scenario that demonstrates the approximate capabilities of the current version of the entire robot system is presented.

Raphael, B.↗

SU-F-T-340: Direct Editing of Dose Volume Histograms: Algorithms and a Unified Convex Formulation for Treatment Planning with Dose Constraints

Purpose: To develop a procedure for including dose constraints in convex programming-based approaches to treatment planning, and to support dynamic modification of such constraints during planning. Methods: We present a mathematical approach that allows mean dose, maximum dose, minimum dose and dose volume (i.e., percentile) constraints to be appended to any convex formulation of an inverse planning problem. The first three constraint types are convex and readily incorporated. Dose volume constraints are not convex, however, so we introduce a convex restriction that is related to CVaR-based approaches previously proposed in the literature. To compensate for the conservatism of this restriction, we propose a new two-pass algorithm that solves the restricted problem on a first pass and uses this solution to form exact constraints on a second pass. In another variant, we introduce slack variables for each dose constraint to prevent the problem from becoming infeasible when the user specifies an incompatible set of constraints. We implement the proposed methods in Python using the convex programming package cvxpy in conjunction with the open source convex solvers SCS and ECOS. Results: We show, for several cases taken from the clinic, that our proposed method meets specified constraints (often with margin) when they are feasible. Constraints are met exactly when we use the two-pass method, and infeasible constraints are replaced with the nearest feasible constraint when slacks are used. Finally, we introduce ConRad, a Python-embedded free software package for convex radiation therapy planning. ConRad implements the methods described above and offers a simple interface for specifying prescriptions and dose constraints. Conclusion: This work demonstrates the feasibility of using modifiable dose constraints in a convex formulation, making it practical to guide the treatment planning process with interactively specified dose constraints. This work was supported by the Stanford BioX Graduate Fellowship and NIH Grant 5R01CA176553.

60 APPLIED LIFE SCIENCES↗

Subject Matter Expert Evaluation of Multi-Flight Common Route Advisories

Traffic flow management seeks to balance the demand for National Airspace System (NAS) flight resources, such as airspace and airports, with the available supply. When forecasted weather blocks nominal air traffic routes, traffic managers must re-route affected flights for weather avoidance. Depending on the nature and scope of the weather, traffic managers may use pre-coordinated re-routes such as Playbook Routes or Coded Departure Routes, or may design ad hoc local re-routes. The routes of affected flights are modified accordingly. These weather avoidance routes will, of course, be less efficient than the nominal routes due to increased flight time and fuel burn. In current traffic management operations, the transition into a weather avoidance re-routing initiative is typically implemented more aggressively than the transition out of that initiative after the weather has dissipated or moved away. For example, strategic large-scale Playbook re-routes are sometimes left in place (as initially implemented) for many hours before being lifted entirely when the weather dissipates. There is an opportunity to periodically modify the re-routing plan as weather evolves, thereby attenuating its adverse impact on flight time and fuel consumption; this is called delay recovery. Multi-Flight Common Routes (MFCR) is a NASA-developed operational concept and associated decision support tool for delay recovery, designed to assist traffic managers to efficiently update weather avoidance traffic routes after the original re-routes have become stale due to subsequent evolution of the convective weather system. MFCR groups multiple flights to reduce the number of advisories that the traffic manager needs to evaluate, and also merges these flights on a common route segment to provide an orderly flow of re-routed traffic. The advisory is presented to the appropriate traffic manager who evaluates it and has the option to modify it using MFCRs graphical user interface. If the traffic manager finds the advisory to be operationally appropriate, he or she would coordinate with the Area Supervisor(s) of the sectors that currently control the flights in the advisory. When the traffic manager accepts the MFCR advisory via the user interface, the corresponding flight plan amendments would be sent to the displays of the appropriate sector controllers, using the Airborne Re-Routing (ABRR) capability which is scheduled for nationwide operation in 2017. The sector controllers would then offer this time-saving route modification to the pilots of the affected flights via datalink (or voice), and implement the corresponding flight plan amendment if the pilots accept it. MFCR is implemented as an application in the software environment of the Future Air traffic management Concepts Evaluation Tool (FACET). This paper focuses on an initial subject matter expert (SME) evaluation of MFCR. The evaluation covers MFCRs operational concept, algorithm, and user interface.

Human-in-the-loop Evaluation↗

Subject Matter Expert Evaluation of Multi-Flight Common Route Advisories

Traffic flow management seeks to balance the demand for National Airspace System (NAS) flight resources, such as airspace and airports, with the available supply. When forecasted weather blocks nominal air traffic routes, traffic managers must re-route affected flights for weather avoidance. Depending on the nature and scope of the weather, traffic managers may use pre-coordinated re-routes such as Playbook Routes or Coded Departure Routes, or may design ad hoc local re-routes. The routes of affected flights are modified accordingly. These weather avoidance routes will, of course, be less efficient than the nominal routes due to increased flight time and fuel burn. In current traffic management operations, the transition into a weather avoidance re-routing initiative is typically implemented more aggressively than the transition out of that initiative after the weather has dissipated or moved away. For example, strategic large-scale Playbook re-routes are sometimes left in place (as initially implemented) for many hours before being lifted entirely when the weather dissipates. There is an opportunity to periodically modify the re-routing plan as weather evolves, thereby attenuating its adverse impact on flight time and fuel consumption; this is called delay recovery. Multi-Flight Common Routes (MFCR) is a NASA-developed operational concept and associated decision support tool for delay recovery, designed to assist traffic managers to efficiently update weather avoidance traffic routes after the original re-routes have become stale due to subsequent evolution of the convective weather system. MFCR groups multiple flights to reduce the number of advisories that the traffic manager needs to evaluate, and also merges these flights on a common route segment to provide an orderly flow of re-routed traffic. The advisory is presented to the appropriate traffic manager who evaluates it and has the option to modify it using MFCRs graphical user interface. If the traffic manager finds the advisory to be operationally appropriate, he or she would coordinate with the Area Supervisor(s) of the sectors that currently control the flights in the advisory. When the traffic manager accepts the MFCR advisory via the user interface, the corresponding flight plan amendments would be sent to the displays of the appropriate sector controllers, using the Airborne Re-Routing (ABRR) capability which is scheduled for nationwide operation in 2017. The sector controllers would then offer this time-saving route modification to the pilots of the affected flights via datalink (or voice), and implement the corresponding flight plan amendment if the pilots accept it. MFCR is implemented as an application in the software environment of the Future Air traffic management Concepts Evaluation Tool (FACET). This paper focuses on an initial subject matter expert (SME) evaluation of MFCR. The evaluation covers MFCRs operational concept, algorithm, and user interface.

Traffic flow management↗

Laying the groundwork for a large-scale spent nuclear fuel transportation system - 15408

The US Department of Energy Office of Nuclear Energy established the Nuclear Fuels Storage and Transportation Planning Project to lay the groundwork for implementing an interim storage facility, including associated transportation activities. Efforts include the development of a system for the large-scale transport of spent nuclear fuel that will be necessary in an integrated waste management system. Progress is being made on long lead time, destination-independent aspects of the transportation infrastructure. The large-scale transportation system for spent nuclear fuel is divided into three elements: institutional, operational, and hardware. The institutional element refers to the various forms of stakeholder interaction that must occur for this type of transportation system to be successful. It includes activities like development of a national transportation plan, work on policy development for Section 180(c) of the Nuclear Waste Policy Act, and identification of a preliminary suite of national transportation routes that reflect the interests of a broad cross section of stakeholders while meeting regulatory requirements. The operational element refers to the activities that must be undertaken to run a large-scale transportation system. This element is currently focused on development of a new SNF transportation routing analysis tool, study of the infrastructure near SNF storage sites that may be de-inventoried first, and development of tools for modeling transportation activities. The hardware element refers to the casks, railcars, and other items necessary to operate the system. This element currently focuses on development of railcars compliant with Association of American Railroads Standard S-2043, as well as studies related to the use of rail casks and their ancillary equipment. The Nuclear Fuels Storage and Transportation Planning Project is making significant progress in all three of these areas along the path forward to a fully operational transportation system. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Risk-informed Graded Approach for Reliability and Performance Assessment of Machine Learning and Artificial Intelligence for Advanced Condition Monitoring Techniques

With the shift away from time-based maintenance and toward condition-based maintenance, and to reduce overall maintenance costs, there has been an upsurge in the usage and development of advanced condition monitoring (ACM) techniques for real-time monitoring of nuclear power plant (NPP) components. ACM is particularly useful in the development of digital twins, which are designed to predict the failure or degradation of plant components. Successful implementation of ACM requires an assessment to inform the development of a risk-informed approach to evaluate the use of ACM to meet Nuclear Regulatory Committee (NRC) regulations for in-service testing (IST) programs. This includes the monitoring and diagnostics of reactor components and systems in current, new, and advanced reactors. A key component in ACM is the usage of machine learning (ML) and artificial intelligence (AI) algorithms that can employ real-time data from instrumentation and sensors to detect and predict reactor component degradations. Such predictive capabilities enable early detection of component degradation so as to help plant personnel plan and execute necessary maintenance. For successful implementation of ML/AI in ACM such that regulatory requirements are met, a risk-informed graded approach is needed to assess the reliability and performance of ML/AI for ACM. The American Society for Mechanical Engineers (ASME) developed their Operations and Maintenance (O&M) Code to provide guidance on safe, reliable O&M of NPPs. The IST section of the O&M Code specifically establishes requirements for IST and examination to gauge operational readiness of components in water-cooled NPPs. This paper presents a state-of-the-art review of how reliability and risk assessment can be integrated with ACM to assess component performance by non-nuclear industries. This is followed by different methodologies and approaches for conducting performance and reliability assessments so as to meet IST requirements for NPP components.

97 - MATHEMATICS AND COMPUTING↗

Risk-informed Graded Approach for Reliability and Performance Assessment for Advanced Condition Monitoring Techniques

With the shift away from time-based maintenance and toward condition-based maintenance, and to reduce overall maintenance costs, there has been an upsurge in the usage and development of advanced condition monitoring (ACM) techniques for real-time monitoring of nuclear power plant (NPP) components. ACM is particularly useful in the development of digital twins, which are designed to predict the failure or degradation of plant components. Successful implementation of ACM requires an assessment to inform the development of a risk-informed approach to evaluate the use of ACM to meet Nuclear Regulatory Committee (NRC) regulations for in-service testing (IST) programs. This includes the monitoring and diagnostics of reactor components and systems in current, new, and advanced reactors. A key component in ACM is the usage of machine learning (ML) and artificial intelligence (AI) algorithms that can employ real-time data from instrumentation and sensors to detect and predict reactor component degradations. Such predictive capabilities enable early detection of component degradation so as to help plant personnel plan and execute necessary maintenance. For successful implementation of ML/AI in ACM such that regulatory requirements are met, a risk-informed graded approach is needed to assess the reliability and performance of ML/AI for ACM. The American Society for Mechanical Engineers (ASME) developed their Operations and Maintenance (O&M) Code to provide guidance on safe, reliable O&M of NPPs. The IST section of the O&M Code specifically establishes requirements for IST and examination to gauge operational readiness of components in water-cooled NPPs. This paper presents a state-of-the-art review of how reliability and risk assessment can be integrated with ACM to assess component performance by non-nuclear industries. This is followed by different methodologies and approaches for conducting performance and reliability assessments so as to meet IST requirements for NPP components.

99 - GENERAL AND MISCELLANEOUS↗

Intermediate Scale Testing Recommendation Report

A summary of recommendations for near-term intermediate-scale testing pertaining to a salt repository is provided in this report. Each proposal was asked to implement a phased progression, initiating with test plan production in FY 2017 and early-stage testing, if possible. Beyond 2017, testing is anticipated to progress to an underground setting and involve intermediate-scale field activities. Each test concept was presented at the June 6th 2016 meeting in Las Vegas NV and a team of DOE-NE, DOE-EM, and National Laboratory staff discussed the rnerits of each proposal. Discussions among managers and researchers in the weeks following the meeting led to selection of a path forward for phased testing that includes a series of small diarneter borehole tests designed to illuminate thermomechanical processes and potential vapor and brine transport. These tests are intended to be implemented at the WIPP facility and involve collaboration between SNL, LANL, and LBL. This document summarizes the test concepts generated by the te s of researchers and decisions made subsequent to the June 6th meeting.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

A Framework for Intelligent Rocket Test Facilities with Smart Sensors

A long-term center goal at the John C. Stennis Space Center (SSC) is the formulation and implementation of a framework for an Intelligent Rocket Test Facility (IRTF), which incorporates distributed smart sensor elements. The IRTF is to provide reliable, high-confident measurements. Specific objectives include: 1. Definition of a framework and architecture that supports implementation of highly autonomous methodologies founded on basic physical principles and embedded knowledge. 2. Modeling of autonomous sensors and processes as self-sufficient, evolutionary elements. 3. Development of appropriate communications protocols to enable the complex interactions that must take place to allow timely and high-quality flow of of information among all the autonomous elements of the system. 4. Development of lab-scale prototypes of key system elements. Though our application is next-generation rocket test facilities, applications for the approach are much wider and include monitoring of shuttle launch operations, air and spacecraft operations and health monitoring, and other large-scale industrial system operations such as found in processing and manufacturing plans. Elements of prototype IRTF have been implemented in preparation for advanced development and validation using rocket test stand facilities as SSC. This work has identified issues that are important to further development of complex network and should be of interest to other working with sensor networks.

Figueroa, Fernando↗

SU-D-BRD-05: Online Framework for Plan Tracking and Automatic Checks in Radiation Therapy

Purpose: To develop an online framework that tracks a patient’s plan from initial simulation to treatment and that helps automate elements of the physics plan checks usually performed in the record and verify (RV) system and treatment planning system. Methods: We have developed PlanTracker, an online plan tracking system that automatically imports new patients tasks and follows it through treatment planning, physics checks, therapy check, and chart rounds. A survey was designed to collect information about the amount of time spent by medical physicists in non-physics related tasks. We then assessed these non-physics tasks for automation. Using these surveys, we directed our PlanTracker software development towards the automation of intra-plan physics review. We then conducted a systematic evaluation of PlanTracker’s accuracy by generating test plans in the RV system software designed to mimic real plans, in order to test its efficacy in catching errors both real and theoretical. Results: PlanTracker has proven to be an effective improvement to the clinical workflow in a radiotherapy clinic. We present data indicating that roughly 1/3 of the physics plan check can be automated, and the workflow optimized, and show the functionality of PlanTracker. When the full system is in clinical use we will present data on improvement of time use in comparison to survey data prior to PlanTracker implementation. Conclusion: We have developed a framework for plan tracking and automatic checks in radiation therapy. We anticipate using PlanTracker as a basis for further development in clinical/research software. We hope that by eliminating the most simple and time consuming checks, medical physicists may be able to spend their time on plan quality and other physics tasks rather than in arithmetic and logic checks. We see this development as part of a broader initiative to advance the clinical/research informatics infrastructure surrounding the radiotherapy clinic. This research project has been financially supported by Varian Medical Systems, Palo Alto, CA, through a Varian MRA.

60 APPLIED LIFE SCIENCES↗

SU-F-T-195: Systematic Constraining of Contralateral Parotid Gland Led to Improved Dosimetric Outcomes for Multi-Field Optimization with Scanning Beam Proton Therapy: Promising Results From a Pilot Study in Patients with Base of Tongue Carcinoma

Purpose: Treatment planning for Intensity Modulated Proton Therapy (IMPT) for head and neck cancer is time-consuming due to the large number of organs-at-risk (OAR) to be considered. As there are many competing objectives and also wide range of acceptable OAR constraints, the final approved plan may not be most optimal for the given structures. We evaluated the dose reduction to the contralateral parotid by implementing standardized constraints during optimization for scanning beam proton therapy planning. Methods: Twenty-four (24) consecutive patients previously treated for base of tongue carcinoma were retrospectively selected. The doses were 70Gy, 63Gy and 57Gy (SIB in 33 fractions) for high-, intermediate-, and standard-risk clinical target volumes (CTV), respectively; the treatment included bilateral neck. Scanning beams using MFO with standardized bilateral anterior oblique and PA fields were applied. New plans where then developed and optimized by employing additional contralateral parotid constraints at multiple defined dose levels. Using a step-wise iterative process, the volume-based constraints at each level were then further reduced until known target coverages were compromised. The newly developed plans were then compared to the original clinically approved plans using paired student t-testing. Results: All 24 newly optimized treatment plans maintained initial plan quality as compared to the approved plans, and the 98% prescription dose coverage to the CTV’s were not compromised. Representative DVH comparison is shown in FIGURE 1. The contralateral parotid doses were reduced at all levels of interest when systematic constraints were applied to V10, V20, V30 and V40Gy (All P<0.0001; TABLE 1). Overall, the mean contralateral parotid doses were reduced by 2.26 Gy on average, a ∼13% relative improvement. Conclusion: Applying systematic and volume-based contralateral parotid constraints for IMPT planning significantly reduced the dose at all dosimetric levels for patients with base of tongue cancer.

60 APPLIED LIFE SCIENCES↗