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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Semiautomated head-and-neck IMRT planning using dose warping and scaling to robustly adapt plans in a knowledge database containing potentially suboptimal plans

Purpose: Prior work by the authors and other groups has studied the creation of automated intensity modulated radiotherapy (IMRT) plans of equivalent quality to those in a patient database of manually created clinical plans; those database plans provided guidance on the achievable sparing to organs-at-risk (OARs). However, in certain sites, such as head-and-neck, the clinical plans may not be sufficiently optimized because of anatomical complexity and clinical time constraints. This could lead to automated plans that suboptimally exploit OAR sparing. This work investigates a novel dose warping and scaling scheme that attempts to reduce effects of suboptimal sparing in clinical database plans, thus improving the quality of semiautomated head-and-neck cancer (HNC) plans. Methods: Knowledge-based radiotherapy (KBRT) plans for each of ten “query” patients were semiautomatically generated by identifying the most similar “match” patient in a database of 103 clinical manually created patient plans. The match patient’s plans were adapted to the query case by: (1) deforming the match beam fluences to suit the query target volume and (2) warping the match primary/boost dose distribution to suit the query geometry and using the warped distribution to generate query primary/boost optimization dose-volume constraints. Item (2) included a distance scaling factor to improve query OAR dose sparing with respect to the possibly suboptimal clinical match plan. To further compensate for a component plan of the match case (primary/boost) not optimally sparing OARs, the query dose volume constraints were reduced using a dose scaling factor to be the minimum from either (a) the warped component plan (primary or boost) dose distribution or (b) the warped total plan dose distribution (primary + boost) scaled in proportion to the ratio of component prescription dose to total prescription dose. The dose-volume constraints were used to plan the query case with no human intervention to adjust constraints during plan optimization. Results: KBRT and original clinical plans were dosimetrically equivalent for parotid glands (mean/median doses), spinal cord, and brainstem (maximum doses). KBRT plans significantly reduced larynx median doses (21.5 ± 6.6 Gy to 17.9 ± 3.9 Gy), and oral cavity mean (32.3 ± 6.2 Gy to 28.9 ± 5.4 Gy) and median (28.7 ± 5.7 Gy to 23.2 ± 5.3 Gy) doses. Doses to ipsilateral parotid gland, larynx, oral cavity, and brainstem were lower or equivalent in the KBRT plans for the majority of cases. By contrast, KBRT plans generated without the dose warping and dose scaling steps were not significantly different from the clinical plans. Conclusions: Fast, semiautomatically generated HNC IMRT plans adapted from existing plans in a clinical database can be of equivalent or better quality than manually created plans. The reductions in OAR doses in the semiautomated plans, compared to the clinical plans, indicate that the proposed dose warping and scaling method shows promise in mitigating the impact of suboptimal clinical plans.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-502: Initial Results of a Comparison of Treatment Plans Produced From Automated Prioritized Planning Method and a Commercial Treatment Planning System

Purpose We developed an automated treatment planning system based on a hierarchical goal programming approach. To demonstrate the feasibility of our method, we report the comparison of prostate treatment plans produced from the automated treatment planning system with those produced by a commercial treatment planning system. Methods In our approach, we prioritized the goals of the optimization, and solved one goal at a time. The purpose of prioritization is to ensure that higher priority dose-volume planning goals are not sacrificed to improve lower priority goals. The algorithm has four steps. The first step optimizes dose to the target structures, while sparing key sensitive organs from radiation. In the second step, the algorithm finds the best beamlet weight to reduce toxicity risks to normal tissue while holding the objective function achieved in the first step as a constraint, with a small amount of allowed slip. Likewise, the third and fourth steps introduce lower priority normal tissue goals and beam smoothing. We compared with prostate treatment plans from Memorial Sloan Kettering Cancer Center developed using Eclipse, with a prescription dose of 72 Gy. A combination of liear, quadratic, and gEUD objective functions were used with a modified open source solver code (IPOPT). Results Initial plan results on 3 different cases show that the automated planning system is capable of competing or improving on expert-driven eclipse plans. Compared to the Eclipse planning system, the automated system produced up to 26% less mean dose to rectum and 24% less mean dose to bladder while having the same D95 (after matching) to the target. Conclusion We have demonstrated that Pareto optimal treatment plans can be generated automatically without a trial-and-error process. The solver finds an optimal plan for the given patient, as opposed to database-driven approaches that set parameters based on geometry and population modeling.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

An Analysis of Plan Robustness for Esophageal Tumors: Comparing Volumetric Modulated Arc Therapy Plans and Spot Scanning Proton Planning

Purpose: Planning studies to compare x-ray and proton techniques and to select the most suitable technique for each patient have been hampered by the nonequivalence of several aspects of treatment planning and delivery. A fair comparison should compare similarly advanced delivery techniques from current clinical practice and also assess the robustness of each technique. The present study therefore compared volumetric modulated arc therapy (VMAT) and single-field optimization (SFO) spot scanning proton therapy plans created using a simultaneous integrated boost (SIB) for dose escalation in midesophageal cancer and analyzed the effect of setup and range uncertainties on these plans. Methods and Materials: For 21 patients, SIB plans with a physical dose prescription of 2 Gy or 2.5 Gy/fraction in 25 fractions to planning target volume (PTV){sub 50Gy} or PTV{sub 62.5Gy} (primary tumor with 0.5 cm margins) were created and evaluated for robustness to random setup errors and proton range errors. Dose–volume metrics were compared for the optimal and uncertainty plans, with P<.05 (Wilcoxon) considered significant. Results: SFO reduced the mean lung dose by 51.4% (range 35.1%-76.1%) and the mean heart dose by 40.9% (range 15.0%-57.4%) compared with VMAT. Proton plan robustness to a 3.5% range error was acceptable. For all patients, the clinical target volume D{sub 98} was 95.0% to 100.4% of the prescribed dose and gross tumor volume (GTV) D{sub 98} was 98.8% to 101%. Setup error robustness was patient anatomy dependent, and the potential minimum dose per fraction was always lower with SFO than with VMAT. The clinical target volume D{sub 98} was lower by 0.6% to 7.8% of the prescribed dose, and the GTV D{sub 98} was lower by 0.3% to 2.2% of the prescribed GTV dose. Conclusions: The SFO plans achieved significant sparing of normal tissue compared with the VMAT plans for midesophageal cancer. The target dose coverage in the SIB proton plans was less robust to random setup errors and might be unacceptable for certain patients. Robust optimization to ensure adequate target coverage of SIB proton plans might be beneficial.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

SU-F-J-105: Towards a Novel Treatment Planning Pipeline Delivering Pareto- Optimal Plans While Enabling Inter- and Intrafraction Plan Adaptation

Purpose: To develop a new IMRT treatment planning methodology suitable for the new generation of MR-linear accelerator machines. The pipeline is able to deliver Pareto-optimal plans and can be utilized for conventional treatments as well as for inter- and intrafraction plan adaptation based on real-time MR-data. Methods: A Pareto-optimal plan is generated using the automated multicriterial optimization approach Erasmus-iCycle. The resulting dose distribution is used as input to the second part of the pipeline, an iterative process which generates deliverable segments that target the latest anatomical state and gradually converges to the prescribed dose. This process continues until a certain percentage of the dose has been delivered. Under a conventional treatment, a Segment Weight Optimization (SWO) is then performed to ensure convergence to the prescribed dose. In the case of inter- and intrafraction adaptation, post-processing steps like SWO cannot be employed due to the changing anatomy. This is instead addressed by transferring the missing/excess dose to the input of the subsequent fraction. In this work, the resulting plans were delivered on a Delta4 phantom as a final Quality Assurance test. Results: A conventional static SWO IMRT plan was generated for two prostate cases. The sequencer faithfully reproduced the input dose for all volumes of interest. For the two cases the mean relative dose difference of the PTV between the ideal input and sequenced dose was 0.1% and −0.02% respectively. Both plans were delivered on a Delta4 phantom and passed the clinical Quality Assurance procedures by achieving 100% pass rate at a 3%/3mm gamma analysis. Conclusion: We have developed a new sequencing methodology capable of online plan adaptation. In this work, we extended the pipeline to support Pareto-optimal input and clinically validated that it can accurately achieve these ideal distributions, while its flexible design enables inter- and intrafraction plan adaptation. This research is financially supported by Elekta AB, Stockholm, Sweden.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Commercial Building Planning and Retrofitting Strategy for Grid Services

The increasing integration of distributed energy resources (DERs) plays an important role in improving energy consumption efficiency. In September 2020, the Federal Energy Regulatory Commission (FERC) approved Order 2222 which opens wholesale electricity markets to small capacity DERs. The benefit of this new FERC Order 2222 is that DERs, such as rooftop solar panels and batteries, will be able to participate in regional electricity markets and provide grid services. Meanwhile, the planning and operation strategies of DERs are facing new challenges to account for the impact of the wholesale market with numerous uncertainty factors. Therefore, in this paper, we propose a new planning and retrofitting model for long-term commercial buildings that considers both DER investment and market participation. Specifically, we explore the capability of implementing DERs for grid services. The effectiveness of the proposed model is validated using real-world data. Simulation results also validate that participating in grid services can significantly increase revenues through appropriate building energy management and shorten the payback period of DER investments.

building energy management↗
DOE OSTI2015

SU-E-T-43: A Methodology for Quality Control of IMPT Treatment Plan Based On VMAT Plan

Purpose: IMPT plan design is highly dependent on planner’s experiences. VMAT plan design is relatively mature and can even be automated. The quality of IMPT plan designed by in-experienced planner could be inferior to that of VMAT plan designed by experienced planner or automatic planning software. Here we introduce a method for designing IMPT plan based on VMAT plan to ensure the IMPT plan be superior to IMRT/VMAT plan for majority clinical scenario. Methods: To design a new IMPT plan, a VMAT plan is first generated either by experienced planner or by in-house developed automatic planning system. An in-house developed tool is used to generate the dose volume constrains for the IMPT plan as plan template to Eclipse TPS. The beam angles for IMPT plan are selected based on the preferred angles in the VMAT plan. IMPT plan is designed by importing the plan objectives generated from VMAT plan. Majority thoracic IMPT plans are designed using this plan approach in our center. In this work, a thoracic IMPT plan under RTOG 1308 protocol is selected to demonstrate the effectiveness and efficiency of this approach. The dosimetric indices of IMPT are compared with VMAT plan. Results: The PTV D95, lung V20, MLD, mean heart dose, esophagus D1, cord D1 are 70Gy, 31%, 17.8Gy, 25.5Gy, 73Gy, 45Gy for IMPT plan and 65.3Gy, 34%, 21.6Gy, 35Gy, 74Gy, 48Gy for VMAT plan. For majority cases, the high dose region of the normal tissue which is in proximity of PTV is comparable between IMPT and VMAT plan. The low dose region of the IMPT plan is significantly better than VMAT plan. Conclusion: Using the knowledge gained in VMAT plan design can help efficiently and effectively design high quality IMPT plan. The quality of IMPT plan can be controlled to ensure the superiority of IMPT plan compared to VMAT/IMRT plan.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Treatment planning for radiotherapy with very high-energy electron beams and comparison of VHEE and VMAT plans

Purpose: The aim of this work was to develop a treatment planning workflow for rapid radiotherapy delivered with very high-energy electron (VHEE) scanning pencil beams of 60–120 MeV and to study VHEE plans as a function of VHEE treatment parameters. Additionally, VHEE plans were compared to clinical state-of-the-art volumetric modulated arc therapy (VMAT) photon plans for three cases. Methods: VHEE radiotherapy treatment planning was performed by linking EGSnrc Monte Carlo (MC) dose calculations with inverse treatment planning in a research version of RayStation. In order to study the effect of VHEE treatment parameters on VHEE dose distributions, a MATLAB graphical user interface (GUI) for calculation of VHEE MC pencil beam doses was developed. Through the GUI, pediatric case MC simulations were run for a number of beam energies (60, 80, 100, and 120 MeV), number of beams (13, 17, and 36), pencil beam spot (0.1, 1.0, and 3.0 mm) and grid (2.0, 2.5, and 3.5 mm) sizes, and source-to-axis distance, SAD (40 and 50 cm). VHEE plans for the pediatric case calculated with the different treatment parameters were optimized and compared. Furthermore, 100 MeV VHEE plans for the pediatric case, a lung, and a prostate case were calculated and compared to the clinically delivered VMAT plans. All plans were normalized such that the 100% isodose line covered 95% of the target volume. Results: VHEE beam energy had the largest effect on the quality of dose distributions of the pediatric case. For the same target dose, the mean doses to organs at risk (OARs) decreased by 5%–16% when planned with 100 MeV compared to 60 MeV, but there was no further improvement in the 120 MeV plan. VHEE plans calculated with 36 beams outperformed plans calculated with 13 and 17 beams, but to a more modest degree (<8%). While pencil beam spacing and SAD had a small effect on VHEE dose distributions, 0.1–3 mm pencil beam sizes resulted in identical dose distributions. For the 100 MeV VHEE pediatric plan, OAR doses were up to 70% lower and the integral dose was 33% lower for VHEE compared to 6 MV VMAT. Additionally, VHEE conformity indices (CI{sub 100} = 1.09 and CI{sub 50} = 4.07) were better than VMAT conformity indices (CI{sub 100} = 1.30 and CI{sub 50} = 6.81). The 100 MeV VHEE lung plan resulted in mean dose decrease to all OARs by up to 27% for the same target coverage compared to the clinical 6 MV flattening filter-free (FFF) VMAT plan. The 100 MeV prostate plan resulted in 3% mean dose increase to the penile bulb and the urethra, but all other OAR mean doses were lower compared to the 15 MV VMAT plan. The lung case CI{sub 100} and CI{sub 50} conformity indices were 3% and 8% lower, respectively, in the VHEE plan compared to the VMAT plan. The prostate case CI{sub 100} and CI{sub 50} conformity indices were 1% higher and 8% lower, respectively, in the VHEE plan compared to the VMAT plan. Conclusions: The authors have developed a treatment planning workflow for MC dose calculation of pencil beams and optimization for treatment planning of VHEE radiotherapy. The authors have demonstrated that VHEE plans resulted in similar or superior dose distributions for pediatric, lung, and prostate cases compared to clinical VMAT plans.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-P-37: Helical Tomotherapy to LINAC Plan Conversion Utilizing RayStation Fallback Planning

Purpose: RayStation Fallback (RSF) plan was developed to switch patient’s treatment from Helical Tomotherapy (HT) to Varian TrueBeam. Helical Tomotherapy plans were compared with the corresponding RSF plans by looking at the following dosimetric parameters: PTV coverage (Dmean and D95), Paddick conformity index (CI), uniformity index (UI=(D98-D2)/Drx) and organ-at-risk (OAR) doses. Methods: Five patients with five tumor sites including larynx, head and neck, esophagus, lung, and prostate previously treated with HT were re-planned using RSF treatment planning station(TPS) to best match the HT treatment plans. IMRT technique with nine fields 6 MV X-ray beams and a static multi-leaf collimator (MLC) were used for RSF plans without any additional attempt to further optimize the RSF plans. Results: A physician evaluated and confirmed the clinical acceptability of the RSF plans. Both HT and RSF plans gave comparable PTV coverage with a maximum percentage difference for D95 of 0.7%. HT plans had a better CIs ranging from 2%–15% higher conformity compared to RSF plans. HT plans also had better UIs for all tumor sites except the esophagus. The UIs were 1.6% to 8.9% lower for HT plans compared to RSF plans. Both HT and RSF plans gave comparable and acceptable OAR doses. However, the integral dose was 1%–15% higher for HT plans compared to RSF plans. Conclusion: RSF plans were simple and fast to generate. In the study cases of 5 various tumor sites, RSF efficiently created clinically acceptable plans without further optimization. However, further optimization for any IMRT plan can be done if clinically warranted. The absolute differences in CI and UI were small between RSF and HT plans.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-173: Clinical Comparison of Treatment Plans and Fallback Plans for Machine Downtime

Purpose: The purpose of this study was to determine the clinical effectiveness and dosimetric quality of fallback planning in relation to machine downtime. Methods: Plans for a Varian Novalis TX were mimicked, and fallback plans using an Elekta VersaHD machine were generated using a dual arc template. Plans for thirty (n=30) patients of various treatment sites optimized and calculated using RayStation treatment planning system. For each plan, a fall back plan was created and compared to the original plan. A dosimetric evaluation was conducted using the homogeneity index, conformity index, as well as DVH analysis to determine the quality of the fallback plan on a different treatment machine. Fallback plans were optimized for 60 iterations using the imported dose constraints from the original plan DVH to give fallback plans enough opportunity to achieve the dose objectives. Results: The average conformity index and homogeneity index for the NovalisTX plans were 0.76 and 10.3, respectively, while fallback plan values were 0.73 and 11.4. (Homogeneity =1 and conformity=0 for ideal plan) The values to various organs at risk were lower in the fallback plans as compared to the imported plans across most organs at risk. Isodose difference comparisons between plans were also compared and the average dose difference across all plans was 0.12%. Conclusion: The clinical impact of fallback planning is an important aspect to effective treatment of patients. With the complexity of LINACS increasing every year, an option to continue treating during machine downtime remains an essential tool in streamlined treatment execution. Fallback planning allows the clinic to continue to run efficiently should a treatment machine become offline due to maintenance or repair without degrading the quality of the plan all while reducing strain on members of the radiation oncology team.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Knowledge-based treatment planning and its potential role in the transition between treatment planning systems

Commissioning a new treatment planning system (TPS) involves many time-consuming tasks. We investigated the role that knowledge-based planning (KBP) can play in aiding a clinic's transition to a new TPS. Sixty clinically treated prostate/prostate bed intensity-modulated radiation therapy (IMRT) plans were exported from an in-house TPS and were used to create a KBP model in a newly implemented commercial application. To determine the benefit that KBP may have in a TPS transition, the model was tested on 2 groups of patients. Group 1 consisted of the first 10 prostate/prostate bed patients treated in the commercial TPS after the transition from the in-house TPS. Group 2 consisted of 10 patients planned in the commercial TPS after 8 months of clinical use. The KBP-generated plan was compared with the clinically used plan in terms of plan quality (ability to meet planning objectives and overall dose metrics) and planning efficiency (time required to generate clinically acceptable plans). The KBP-generated plans provided a significantly improved target coverage (p = 0.01) compared with the clinically used plans for Group 1, but yielded plans of comparable target coverage to the clinically used plans for Group 2. For the organs at risk, the KBP-generated plans produced lower doses, on average, for every normal-tissue objective except for the maximum dose to 0.1 cc of rectum. The time needed for the KBP-generated plans ranged from 6 to 15 minutes compared to 30 to 150 and 15 to 60 minutes for manual planning in Groups 1 and 2, respectively. KBP is a promising tool to aid in the transition to a new TPS. Our study indicates that high-quality treatment plans could have been generated in the newly implemented TPS more efficiently compared with not using KBP. Even after 8 months of the clinical use, KBP still showed an increase in plan quality and planning efficiency compared with manual planning.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

SU-F-T-358: Is Auto-Planning Useful for Volumetric-Modulated Arc Therapy Planning in Rectal Cancer Radiotherapy?

Purpose: To evaluate whether Auto-Planning based volumetric-modulated radiotherapy (auto-VMAT) can reduce manual interaction time during treatment planning and improve plan quality for rectal cancer radiotherapy. Methods: Ten rectal cancer patients (stage II and III) after radical resection using Dixon surgery were enrolled. All patients were treated with VMAT technique. The manual VMAT plans (man-VMAT) were designed in the Pinnacle treatment planning system (Version 9.10) following the standard treatment planning procedure developed in our department. Clinical plans were manually designed by our experienced dosimetrists. Additionally, an auto-VMAT plan was created for each patient using Auto-Planning module. However, manual interaction was still applied to meet the clinical requirements. The treatment planning time and plan quality surrogated by the DVH parameters were compared between manual and automated plans. Results: The total planning time and manual interaction time were 50.38 and 4.47 min for the auto-VMAT and 36.81 and 16.94 min for the man-VMAT (t=60.14,−23.86; p=0.000, 0.000). In terms of plan quality, both plans meet the clinical requirements. The PTV homogeneity index (HI) and conformity index (CI) were 0.054 and 0.822 for the auto-VMAT and 0.059 and 0.815 for the man-VMAT (t=−1.72, 0.36;p=0.119,0.730).Compared to the man-VMAT, the auto-VMAT showed reduction of 11.9% and 0.7% in V40 and V50 of the bladder, respectively.The V30 and D mean were reduced by 14.0% and 5.1Gy in the left femur and 12.2% and 3.8Gy in the right femur. Conclusion: The Auto-Planning based VMAT plans not only shows similar or superior plan quality to the manual ones in the rectal cancer radiotherapy, but also improve the planning efficiency significantly. However, manual interactions are still required to achieve a clinically acceptable plan based on our experiences.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Plan evaluation for heat resilience: complementary methods to comprehensively assess heat planning in Tempe and Tucson, Arizona

Abstract Escalating impacts from climate change and urban heat are increasing the urgency for communities to equitably plan for heat resilience. Cities in the desert Southwest are among the hottest and fastest warming in the U.S., placing them on the front lines of heat planning. Urban heat resilience requires an integrated planning approach that coordinates strategies across the network of plans that shape the built environment and risk patterns. To date, few studies have assessed cities’ progress on heat planning. This research is the first to combine two emerging plan evaluation approaches to examine how networks of plans shape urban heat resilience through case studies of Tempe and Tucson, Arizona. The first methodology, Plan Quality Evaluation for Heat Resilience, adapts existing plan quality assessment approaches to heat. We assess whether plans meet 56 criteria across seven principles of high-quality planning and the types of heat strategies included in the plans. The second methodology, the Plan Integration for Resilience Scorecard™ (PIRS™) for Heat, focuses on plan policies that could influence urban heat hazards. We categorize policies by policy tool and heat mitigation strategy and score them based on their heat impact. Scored policies are then mapped to evaluate their spatial distribution and the net effect of the plan network. The resulting PIRS™ for Heat scorecard is compared with heat vulnerability indicators to assess policy alignment with risks. We find that both cities are proactively planning for heat resilience using similar plan and strategy types, however, there are clear and consistent opportunities for improvement. Combining these complementary plan evaluation methods provides a more comprehensive understanding of how plans address heat and a generalizable approach that communities everywhere could use to identify opportunities for improved heat resilience planning.

Environmental Sciences & Ecology↗
DOE OSTI2016

SU-F-T-312: Identifying Distinct Radiation Therapy Plan Classes Through Multi-Dimensional Analysis of Plan Complexity Metrics

Purpose: To determine whether body site-specific treatment plans form unique “plan class” clusters in a multi-dimensional analysis of plan complexity metrics such that a single beam quality correction determined for a representative plan could be universally applied within the “plan class”, thereby increasing the dosimetric accuracy of a detector’s response within a subset of similarly modulated nonstandard deliveries. Methods: We collected 95 clinical volumetric modulated arc therapy (VMAT) plans from four body sites (brain, lung, prostate, and spine). The lung data was further subdivided into SBRT and non-SBRT data for a total of five plan classes. For each control point in each plan, a variety of aperture-based complexity metrics were calculated and stored as unique characteristics of each patient plan. A multiple comparison of means analysis was performed such that every plan class was compared to every other plan class for every complexity metric in order to determine which groups could be considered different from one another. Statistical significance was assessed after correcting for multiple hypothesis testing. Results: Six out of a possible 10 pairwise plan class comparisons were uniquely distinguished based on at least nine out of 14 of the proposed metrics (Brain/Lung, Brain/SBRT lung, Lung/Prostate, Lung/SBRT Lung, Lung/Spine, Prostate/SBRT Lung). Eight out of 14 of the complexity metrics could distinguish at least six out of the possible 10 pairwise plan class comparisons. Conclusion: Aperture-based complexity metrics could prove to be useful tools to quantitatively describe a distinct class of treatment plans. Certain plan-averaged complexity metrics could be considered unique characteristics of a particular plan. A new approach to generating plan-class specific reference (pcsr) fields could be established through a targeted preservation of select complexity metrics or a clustering algorithm that identifies plans exhibiting similar modulation characteristics. Measurements and simulations will better elucidate potential plan-class specific dosimetry correction factors.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-D-BRD-04: The Impact of Automatic Radiation Therapy Plan Checks in Treatment Planning

Purpose: The physics plan check verifies various aspects of a treatment plan after dosimetrists have finished creating the plan. Some errors in the plan which are caught by the physics check could be caught earlier in the departmental workflow. The purpose of this project was to evaluate a plan checking script that can be run within the treatment planning system (TPS) by the dosimetrists prior to plan approval and export to the record and verify system. Methods: A script was created in the Pinnacle TPS to automatically check 15 aspects of a plan for clinical practice conformity. The script outputs a list of checks which the plan has passed and a list of checks which the plan has failed so that appropriate adjustments can be made. For this study, the script was run on a total of 108 plans: IMRT (46/108), VMAT (35/108) and SBRT (27/108). Results: Of the plans checked by the script, 77/108 (71%) failed at least one of the fifteen checks. IMRT plans resulted in more failed checks (91%) than VMAT (51%) or SBRT (63%), due to the high failure rate of an IMRT-specific check, which checks that no IMRT segment < 5 MU. The dose grid size and couch removal checks caught errors in 10% and 14% of all plans – errors that ultimately may have resulted in harm to the patient. Conclusion: Approximately three-fourths of the plans being examined contain errors that could be caught by dosimetrists running an automated script embedded in the TPS. The results of this study will improve the departmental workflow by cutting down on the number of plans that, due to these types of errors, necessitate re-planning and re-approval of plans, increase dosimetrist and physician workload and, in urgent cases, inconvenience patients by causing treatment delays.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-G-TeP4-14: Quality Control of Treatment Planning Using Knowledge-Based Planning Across a System of Radiation Oncology Practices

Purpose: There is potentially a wide variation in plan quality for a certain disease site, even for clinics located in the same system of hospitals. We have used a prostate-specific knowledge-based planning (KBP) model as a quality control tool to investigate the variation in prostate treatment planning across a network of affiliated radiation oncology departments. Methods: A previously created KBP model was applied to 10 patients each from 4 community-based clinics (Clinics A, B, C, and D). The KBP model was developed using RapidPlan (Eclipse v13.5, Varian Medical Systems) from 60 prostate/prostate bed IMRT plans that were originally planned using an in-house treatment planning system at the central institution of the community-based clinics. The dosimetric plan quality (target coverage and normal-tissue sparing) of each model-generated plan was compared to the respective clinically-used plan. Each community-based clinic utilized the same planning goals to develop the clinically-used plans that were used at the main institution. Results: Across all 4 clinics, the model-generated plans decreased the mean dose to the rectum by varying amounts (on average, 12.5, 2.6, 4.5, and 2.7 Gy for Clinics A, B, C, and D, respectively). The mean dose to the bladder also decreased with the model-generated plans (5.4, 2.3, 3.0, and 4.1 Gy, respectively). The KBP model also identified that target coverage (D95%) improvements were possible for for Clinics A, B, and D (0.12, 1.65, and 2.75%) while target coverage decreased by 0.72% for Clinic C, demonstrating potentially different trade-offs made in clinical plans at different institutions. Conclusion: Quality control of dosimetric plan quality across a system of radiation oncology practices is possible with knowledge-based planning. By using a quality KBP model, smaller community-based clinics can potentially identify the areas of their treatment plans that may be improved, whether it be in normal-tissue sparing or improved target coverage. M. Matuszak has research funding for KBP from Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Community Planning for Solar: Compiling a Community Solar Action Plan

This document provides an annotated outline for a Community Solar Action Plan. This document is designed to assist community officials, volunteers, and regional planning agency staff in preparing a draft Community Solar Action Plan for a municipality, community, or other jurisdiction. Preparing a Community Solar Action Plan is the fifth step in the Community Planning for Solar process (ag.umass.edu/solarplanning). The plan is intended to be the culmination of the planning process. The contents of the plan will include summaries of information gathered as part of foregoing steps in the process, including completion of a Solar Resource and Infrastructure Assessment, administering of a Community Solar Survey, interpretation of survey results, and review of Solar Financing and Ownership Options and tools. Once the Community Solar Action Plan has been drafted, it should be reviewed by municipal board and commission members and presented at an open community forum. Any important comments or revisions can be incorporated before the final Community Solar Action Plan is approved and implemented. The approved Community Solar Action Plan is a living document that guides community solar planning action over time. As conditions change, new information becomes available, or actions progress over the life of the plan, adjustments may be necessary to maintain the plan's relevance. The Monitoring, Evaluating, and Updating Your Community Solar Action Plan fact sheet (Step 6, Item a) describes some things to consider when updating the Community Solar Action Plan over time.

14 SOLAR ENERGY↗
DOE OSTI2015

SU-E-T-268: Differences in Treatment Plan Quality and Delivery Between Two Commercial Treatment Planning Systems for Volumetric Arc-Based Radiation Therapy

Purpose: To clinically evaluate the differences in volumetric modulated arc therapy (VMAT) treatment plan and delivery between two commercial treatment planning systems. Methods: Two commercial VMAT treatment planning systems with different VMAT optimization algorithms and delivery approaches were evaluated. This study included 16 clinical VMAT plans performed with the first system: 2 spine, 4 head and neck (HN), 2 brain, 4 pancreas, and 4 pelvis plans. These 16 plans were then re-optimized with the same number of arcs using the second treatment planning system. Planning goals were invariant between the two systems. Gantry speed, dose rate modulation, MLC modulation, plan quality, number of monitor units (MUs), VMAT quality assurance (QA) results, and treatment delivery time were compared between the 2 systems. VMAT QA results were performed using Mapcheck2 and analyzed with gamma analysis (3mm/3% and 2mm/2%). Results: Similar plan quality was achieved with each VMAT optimization algorithm, and the difference in delivery time was minimal. Algorithm 1 achieved planning goals by highly modulating the MLC (total distance traveled by leaves (TL) = 193 cm average over control points per plan), while maintaining a relatively constant dose rate (dose-rate change <100 MU/min). Algorithm 2 involved less MLC modulation (TL = 143 cm per plan), but greater dose-rate modulation (range = 0-600 MU/min). The average number of MUs was 20% less for algorithm 2 (ratio of MUs for algorithms 2 and 1 ranged from 0.5-1). VMAT QA results were similar for all disease sites except HN plans. For HN plans, the average gamma passing rates were 88.5% (2mm/2%) and 96.9% (3mm/3%) for algorithm 1 and 97.9% (2mm/2%) and 99.6% (3mm/3%) for algorithm 2. Conclusion: Both VMAT optimization algorithms achieved comparable plan quality; however, fewer MUs were needed and QA results were more robust for Algorithm 2, which more highly modulated dose rate.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-P-64: The Impact of Plan Complexity Parameters On the Plan Quality and Deliverability of Volumetric Modulated Arc Therapy with Canonical Correlation Analysis

Purpose: To evaluate the impact of complexity indices on the plan quality and deliverability of volumetric modulated arc therapy (VMAT), and to determine the most significant parameters in the generation of an ideal VMAT plan. Methods: A multi-dimensional exploratory statistical method, canonical correlation analysis (CCA) was adopted to study the correlations between VMAT parameters of complexity, quality and deliverability, as well as their contribution weights with 32 two-arc VMAT nasopharyngeal cancer (NPC) patients and 31 one-arc VMAT prostate cancer patients. Results: The MU per arc (MU/Arc) and MU per control point (MU/CP) of NPC were 337.8±25.2 and 3.7±0.3, respectively, which were significantly lower than those of prostate cancer patients (MU/Arc : 506.9±95.4, MU/CP : 5.6±1.1). The plan complexity indices indicated that two-arc VMAT plans were more complex than one-arc VMAT plans. Plan quality comparison confirmed that one-arc VMAT plans had a high quality than two-arc VMAT plans. CCA results implied that plan complexity parameters were highly correlated with plan quality with the first two canonical correlations of 0.96, 0.88 (both p<0.001) and significantly correlated with deliverability with the first canonical correlation of 0.79 (p<0.001), plan quality and deliverability was also correlated with the first canonical correlation of 0.71 (p=0.02). Complexity parameters of MU/CP, segment area (SA) per CP, percent of MU/CP less 3 and planning target volume (PTV) were weighted heavily in correlation with plan quality and deliveability . Similar results obtained from individual NPC and prostate CCA analysis. Conclusion: Relationship between complexity, quality, and deliverability parameters were investigated with CCA. MU, SA related parameters and PTV volume were found to have strong effect on the plan quality and deliverability. The presented correlation among different quantified parameters could be used to improve the plan quality and the efficiency of the radiotherapy process when creating a complex VMAT plan.

60 APPLIED LIFE SCIENCES↗