Software for Optimizing Plans Involving Interdependent Goals

NASA Technical Reports Server (NTRS)

Estlin, Tara; Gaines, Daniel; Rabideau, Gregg

2005-01-01

A computer program enables construction and optimization of plans for activities that are directed toward achievement of goals that are interdependent. Goal interdependence is defined as the achievement of one or more goals affecting the desirability or priority of achieving one or more other goals. This program is overlaid on the Automated Scheduling and Planning Environment (ASPEN) software system, aspects of which have been described in a number of prior NASA Tech Briefs articles. Unlike other known or related planning programs, this program considers interdependences among goals that can change between problems and provides a language for easily specifying such dependences. Specifications of the interdependences can be formulated dynamically and provided to the associated planning software as part of the goal input. Then an optimization algorithm provided by this program enables the planning software to reason about the interdependences and incorporate them into an overall objective function that it uses to rate the quality of a plan under construction and to direct its optimization search. In tests on a series of problems of planning geological experiments by a team of instrumented robotic vehicles (rovers) on new terrain, this program was found to enhance plan quality.

MHK Hydrofoils Design, Wind Tunnel Optimization and CFD Analysis Report for the Aquantis 2.5MW Ocean Current Generation Device

DOE Data Explorer

Shiu, Henry; Swales, Henry; Van Damn, Case

2015-06-03

Dataset contains MHK Hydrofoils Design and Optimization and CFD Analysis Report for the Aquantis 2.5 MW Ocean Current Generation Device, as well as MHK Hydrofoils Wind Tunnel Test Plan and Checkout Test Report.

A reliability as an independent variable (RAIV) methodology for optimizing test planning for liquid rocket engines

NASA Astrophysics Data System (ADS)

Strunz, Richard; Herrmann, Jeffrey W.

2011-12-01

The hot fire test strategy for liquid rocket engines has always been a concern of space industry and agency alike because no recognized standard exists. Previous hot fire test plans focused on the verification of performance requirements but did not explicitly include reliability as a dimensioning variable. The stakeholders are, however, concerned about a hot fire test strategy that balances reliability, schedule, and affordability. A multiple criteria test planning model is presented that provides a framework to optimize the hot fire test strategy with respect to stakeholder concerns. The Staged Combustion Rocket Engine Demonstrator, a program of the European Space Agency, is used as example to provide the quantitative answer to the claim that a reduced thrust scale demonstrator is cost beneficial for a subsequent flight engine development. Scalability aspects of major subsystems are considered in the prior information definition inside the Bayesian framework. The model is also applied to assess the impact of an increase of the demonstrated reliability level on schedule and affordability.

SU-E-T-175: Clinical Evaluations of Monte Carlo-Based Inverse Treatment Plan Optimization for Intensity Modulated Radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chi, Y; Li, Y; Tian, Z

2015-06-15

Purpose: Pencil-beam or superposition-convolution type dose calculation algorithms are routinely used in inverse plan optimization for intensity modulated radiation therapy (IMRT). However, due to their limited accuracy in some challenging cases, e.g. lung, the resulting dose may lose its optimality after being recomputed using an accurate algorithm, e.g. Monte Carlo (MC). It is the objective of this study to evaluate the feasibility and advantages of a new method to include MC in the treatment planning process. Methods: We developed a scheme to iteratively perform MC-based beamlet dose calculations and plan optimization. In the MC stage, a GPU-based dose engine wasmore » used and the particle number sampled from a beamlet was proportional to its optimized fluence from the previous step. We tested this scheme in four lung cancer IMRT cases. For each case, the original plan dose, plan dose re-computed by MC, and dose optimized by our scheme were obtained. Clinically relevant dosimetric quantities in these three plans were compared. Results: Although the original plan achieved a satisfactory PDV dose coverage, after re-computing doses using MC method, it was found that the PTV D95% were reduced by 4.60%–6.67%. After re-optimizing these cases with our scheme, the PTV coverage was improved to the same level as in the original plan, while the critical OAR coverages were maintained to clinically acceptable levels. Regarding the computation time, it took on average 144 sec per case using only one GPU card, including both MC-based beamlet dose calculation and treatment plan optimization. Conclusion: The achieved dosimetric gains and high computational efficiency indicate the feasibility and advantages of the proposed MC-based IMRT optimization method. Comprehensive validations in more patient cases are in progress.« less

Optimal allocation model of construction land based on two-level system optimization theory

NASA Astrophysics Data System (ADS)

Liu, Min; Liu, Yanfang; Xia, Yuping; Lei, Qihong

2007-06-01

The allocation of construction land is an important task in land-use planning. Whether implementation of planning decisions is a success or not, usually depends on a reasonable and scientific distribution method. Considering the constitution of land-use planning system and planning process in China, multiple levels and multiple objective decision problems is its essence. Also, planning quantity decomposition is a two-level system optimization problem and an optimal resource allocation decision problem between a decision-maker in the topper and a number of parallel decision-makers in the lower. According the characteristics of the decision-making process of two-level decision-making system, this paper develops an optimal allocation model of construction land based on two-level linear planning. In order to verify the rationality and the validity of our model, Baoan district of Shenzhen City has been taken as a test case. Under the assistance of the allocation model, construction land is allocated to ten townships of Baoan district. The result obtained from our model is compared to that of traditional method, and results show that our model is reasonable and usable. In the end, the paper points out the shortcomings of the model and further research directions.

Computer-aided resource planning and scheduling for radiological services

NASA Astrophysics Data System (ADS)

Garcia, Hong-Mei C.; Yun, David Y.; Ge, Yiqun; Khan, Javed I.

1996-05-01

There exists tremendous opportunity in hospital-wide resource optimization based on system integration. This paper defines the resource planning and scheduling requirements integral to PACS, RIS and HIS integration. An multi-site case study is conducted to define the requirements. A well-tested planning and scheduling methodology, called Constrained Resource Planning model, has been applied to the chosen problem of radiological service optimization. This investigation focuses on resource optimization issues for minimizing the turnaround time to increase clinical efficiency and customer satisfaction, particularly in cases where the scheduling of multiple exams are required for a patient. How best to combine the information system efficiency and human intelligence in improving radiological services is described. Finally, an architecture for interfacing a computer-aided resource planning and scheduling tool with the existing PACS, HIS and RIS implementation is presented.

On the role of the optimization algorithm of RapidArc(®) volumetric modulated arc therapy on plan quality and efficiency.

PubMed

Vanetti, Eugenio; Nicolini, Giorgia; Nord, Janne; Peltola, Jarkko; Clivio, Alessandro; Fogliata, Antonella; Cozzi, Luca

2011-11-01

The RapidArc volumetric modulated arc therapy (VMAT) planning process is based on a core engine, the so-called progressive resolution optimizer (PRO). This is the optimization algorithm used to determine the combination of field shapes, segment weights (with dose rate and gantry speed variations), which best approximate the desired dose distribution in the inverse planning problem. A study was performed to assess the behavior of two versions of PRO. These two versions mostly differ in the way continuous variables describing the modulated arc are sampled into discrete control points, in the planning efficiency and in the presence of some new features. The analysis aimed to assess (i) plan quality, (ii) technical delivery aspects, (iii) agreement between delivery and calculations, and (iv) planning efficiency of the two versions. RapidArc plans were generated for four groups of patients (five patients each): anal canal, advanced lung, head and neck, and multiple brain metastases and were designed to test different levels of planning complexity and anatomical features. Plans from optimization with PRO2 (first generation of RapidArc optimizer) were compared against PRO3 (second generation of the algorithm). Additional plans were optimized with PRO3 using new features: the jaw tracking, the intermediate dose and the air cavity correction options. Results showed that (i) plan quality was generally improved with PRO3 and, although not for all parameters, some of the scored indices showed a macroscopic improvement with PRO3. (ii) PRO3 optimization leads to simpler patterns of the dynamic parameters particularly for dose rate. (iii) No differences were observed between the two algorithms in terms of pretreatment quality assurance measurements and (iv) PRO3 optimization was generally faster, with a time reduction of a factor approximately 3.5 with respect to PRO2. These results indicate that PRO3 is either clinically beneficial or neutral in terms of dosimetric quality while it showed significant advantages in speed and technical aspects.

MO-FG-CAMPUS-TeP2-05: Optimizing Stereotactic Radiosurgery Treatment of Multiple Brain Metastasis Lesions with Individualized Rotational Arc Trajectories

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dong, P; Xing, L; Ma, L

Purpose: Radiosurgery of multiple (n>4) brain metastasis lesions requires 3–4 noncoplanar VMAT arcs with excessively high monitor units and long delivery time. We investigated whether an improved optimization technique would decrease the needed arc numbers and increase the delivery efficiency, while improving or maintaining the plan quality. Methods: The proposed 4pi arc space optimization algorithm consists of two steps: automatic couch angle selection followed by aperture generation for each arc with optimized control points distribution. We use a greedy algorithm to select the couch angles. Starting from a single coplanar arc plan we search through the candidate noncoplanar arcs tomore » pick a single noncoplanar arc that will bring the best plan quality when added into the existing treatment plan. Each time, only one additional noncoplanar arc is considered making the calculation time tractable. This process repeats itself until desired number of arc is reached. The technique is first evaluated in coplanar arc delivery scheme with testing cases and then applied to noncoplanar treatments of a case with 12 brain metastasis lesions. Results: Clinically acceptable plans are created within minutes. For the coplanar testing cases the algorithm yields singlearc plans with better dose distributions than that of two-arc VMAT, simultaneously with a 12–17% reduction in the delivery time and a 14–21% reduction in MUs. For the treatment of 12 brain mets while Paddick conformity indexes of the two plans were comparable the SCG-optimization with 2 arcs (1 noncoplanar and 1 coplanar) significantly improved the conventional VMAT with 3 arcs (2 noncoplanar and 1 coplanar). Specifically V16 V10 and V5 of the brain were reduced by 11%, 11% and 12% respectively. The beam delivery time was shortened by approximately 30%. Conclusion: The proposed 4pi arc space optimization technique promises to significantly reduce the brain toxicity while greatly improving the treatment efficiency.« less

Development of a protocol to optimize electric power consumption and life cycle environmental impacts for operation of wastewater treatment plant.

PubMed

Piao, Wenhua; Kim, Changwon; Cho, Sunja; Kim, Hyosoo; Kim, Minsoo; Kim, Yejin

2016-12-01

In wastewater treatment plants (WWTPs), the portion of operating costs related to electric power consumption is increasing. If the electric power consumption decreased, however, it would be difficult to comply with the effluent water quality requirements. A protocol was proposed to minimize the environmental impacts as well as to optimize the electric power consumption under the conditions needed to meet the effluent water quality standards in this study. This protocol was comprised of six phases of procedure and was tested using operating data from S-WWTP to prove its applicability. The 11 major operating variables were categorized into three groups using principal component analysis and K-mean cluster analysis. Life cycle assessment (LCA) was conducted for each group to deduce the optimal operating conditions for each operating state. Then, employing mathematical modeling, six improvement plans to reduce electric power consumption were deduced. The electric power consumptions for suggested plans were estimated using an artificial neural network. This was followed by a second round of LCA conducted on the plans. As a result, a set of optimized improvement plans were derived for each group that were able to optimize the electric power consumption and life cycle environmental impact, at the same time. Based on these test results, the WWTP operating management protocol presented in this study is deemed able to suggest optimal operating conditions under which power consumption can be optimized with minimal life cycle environmental impact, while allowing the plant to meet water quality requirements.

SU-E-T-488: An Iso-Dose Curve Based Interactive IMRT Optimization System for Physician-Driven Plan Tuning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shi, F; Tian, Z; Jia, X

Purpose: In treatment plan optimization for Intensity Modulated Radiation Therapy (IMRT), after a plan is initially developed by a dosimetrist, the attending physician evaluates its quality and often would like to improve it. As opposed to having the dosimetrist implement the improvements, it is desirable to have the physician directly and efficiently modify the plan for a more streamlined and effective workflow. In this project, we developed an interactive optimization system for physicians to conveniently and efficiently fine-tune iso-dose curves. Methods: An interactive interface is developed under C++/Qt. The physician first examines iso-dose lines. S/he then picks an iso-dose curvemore » to be improved and drags it to a more desired configuration using a computer mouse or touchpad. Once the mouse is released, a voxel-based optimization engine is launched. The weighting factors corresponding to voxels between the iso-dose lines before and after the dragging are modified. The underlying algorithm then takes these factors as input to re-optimize the plan in near real-time on a GPU platform, yielding a new plan best matching the physician's desire. The re-optimized DVHs and iso-dose curves are then updated for the next iteration of modifications. This process is repeated until a physician satisfactory plan is achieved. Results: We have tested this system for a series of IMRT plans. Results indicate that our system provides the physicians an intuitive and efficient tool to edit the iso-dose curves according to their preference. The input information is used to guide plan re-optimization, which is achieved in near real-time using our GPU-based optimization engine. Typically, a satisfactory plan can be developed by a physician in a few minutes using this tool. Conclusion: With our system, physicians are able to manipulate iso-dose curves according to their preferences. Preliminary results demonstrate the feasibility and effectiveness of this tool.« less

Fuel efficient traffic signal operation and evaluation: Garden Grove Demonstration Project

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1983-02-01

The procedures and results of a case study of fuel efficient traffic signal operation and evaluation in the City of Garden Grove, California are documented. Improved traffic signal timing was developed for a 70-intersection test network in Garden Grove using an optimization tool called the TRANSYT Version 8 computer program. Full-scale field testing of five alternative timing plans was conducted using two instrumented vehicles equipped to measure traffic performance characteristics and fuel consumption. The field tests indicated that significant improvements in traffic flow and fuel consumption result from the use of timing plans generated by the TRANSYT optimization model. Changingmore » from pre-existing to an optimized timing plan yields a networkwide 5 percent reduction in total travel time, more than 10 percent reduction in both the number of stops and stopped delay time, and 6 percent reduction in fuel consumption. Projections are made of the benefits and costs of implementing such a program at the 20,000 traffic signals in networks throughout the State of California.« less

Comparison of IMRT planning with two-step and one-step optimization: a strategy for improving therapeutic gain and reducing the integral dose

NASA Astrophysics Data System (ADS)

Abate, A.; Pressello, M. C.; Benassi, M.; Strigari, L.

2009-12-01

The aim of this study was to evaluate the effectiveness and efficiency in inverse IMRT planning of one-step optimization with the step-and-shoot (SS) technique as compared to traditional two-step optimization using the sliding windows (SW) technique. The Pinnacle IMRT TPS allows both one-step and two-step approaches. The same beam setup for five head-and-neck tumor patients and dose-volume constraints were applied for all optimization methods. Two-step plans were produced converting the ideal fluence with or without a smoothing filter into the SW sequence. One-step plans, based on direct machine parameter optimization (DMPO), had the maximum number of segments per beam set at 8, 10, 12, producing a directly deliverable sequence. Moreover, the plans were generated whether a split-beam was used or not. Total monitor units (MUs), overall treatment time, cost function and dose-volume histograms (DVHs) were estimated for each plan. PTV conformality and homogeneity indexes and normal tissue complication probability (NTCP) that are the basis for improving therapeutic gain, as well as non-tumor integral dose (NTID), were evaluated. A two-sided t-test was used to compare quantitative variables. All plans showed similar target coverage. Compared to two-step SW optimization, the DMPO-SS plans resulted in lower MUs (20%), NTID (4%) as well as NTCP values. Differences of about 15-20% in the treatment delivery time were registered. DMPO generates less complex plans with identical PTV coverage, providing lower NTCP and NTID, which is expected to reduce the risk of secondary cancer. It is an effective and efficient method and, if available, it should be favored over the two-step IMRT planning.

An evolutionary algorithm technique for intelligence, surveillance, and reconnaissance plan optimization

NASA Astrophysics Data System (ADS)

Langton, John T.; Caroli, Joseph A.; Rosenberg, Brad

2008-04-01

To support an Effects Based Approach to Operations (EBAO), Intelligence, Surveillance, and Reconnaissance (ISR) planners must optimize collection plans within an evolving battlespace. A need exists for a decision support tool that allows ISR planners to rapidly generate and rehearse high-performing ISR plans that balance multiple objectives and constraints to address dynamic collection requirements for assessment. To meet this need we have designed an evolutionary algorithm (EA)-based "Integrated ISR Plan Analysis and Rehearsal System" (I2PARS) to support Effects-based Assessment (EBA). I2PARS supports ISR mission planning and dynamic replanning to coordinate assets and optimize their routes, allocation and tasking. It uses an evolutionary algorithm to address the large parametric space of route-finding problems which is sometimes discontinuous in the ISR domain because of conflicting objectives such as minimizing asset utilization yet maximizing ISR coverage. EAs are uniquely suited for generating solutions in dynamic environments and also allow user feedback. They are therefore ideal for "streaming optimization" and dynamic replanning of ISR mission plans. I2PARS uses the Non-dominated Sorting Genetic Algorithm (NSGA-II) to automatically generate a diverse set of high performing collection plans given multiple objectives, constraints, and assets. Intended end users of I2PARS include ISR planners in the Combined Air Operations Centers and Joint Intelligence Centers. Here we show the feasibility of applying the NSGA-II algorithm and EAs in general to the ISR planning domain. Unique genetic representations and operators for optimization within the ISR domain are presented along with multi-objective optimization criteria for ISR planning. Promising results of the I2PARS architecture design, early software prototype, and limited domain testing of the new algorithm are discussed. We also present plans for future research and development, as well as technology transition goals.

A new Monte Carlo-based treatment plan optimization approach for intensity modulated radiation therapy.

PubMed

Li, Yongbao; Tian, Zhen; Shi, Feng; Song, Ting; Wu, Zhaoxia; Liu, Yaqiang; Jiang, Steve; Jia, Xun

2015-04-07

Intensity-modulated radiation treatment (IMRT) plan optimization needs beamlet dose distributions. Pencil-beam or superposition/convolution type algorithms are typically used because of their high computational speed. However, inaccurate beamlet dose distributions may mislead the optimization process and hinder the resulting plan quality. To solve this problem, the Monte Carlo (MC) simulation method has been used to compute all beamlet doses prior to the optimization step. The conventional approach samples the same number of particles from each beamlet. Yet this is not the optimal use of MC in this problem. In fact, there are beamlets that have very small intensities after solving the plan optimization problem. For those beamlets, it may be possible to use fewer particles in dose calculations to increase efficiency. Based on this idea, we have developed a new MC-based IMRT plan optimization framework that iteratively performs MC dose calculation and plan optimization. At each dose calculation step, the particle numbers for beamlets were adjusted based on the beamlet intensities obtained through solving the plan optimization problem in the last iteration step. We modified a GPU-based MC dose engine to allow simultaneous computations of a large number of beamlet doses. To test the accuracy of our modified dose engine, we compared the dose from a broad beam and the summed beamlet doses in this beam in an inhomogeneous phantom. Agreement within 1% for the maximum difference and 0.55% for the average difference was observed. We then validated the proposed MC-based optimization schemes in one lung IMRT case. It was found that the conventional scheme required 10(6) particles from each beamlet to achieve an optimization result that was 3% difference in fluence map and 1% difference in dose from the ground truth. In contrast, the proposed scheme achieved the same level of accuracy with on average 1.2 × 10(5) particles per beamlet. Correspondingly, the computation time including both MC dose calculations and plan optimizations was reduced by a factor of 4.4, from 494 to 113 s, using only one GPU card.

Direct aperture optimization using an inverse form of back-projection.

PubMed

Zhu, Xiaofeng; Cullip, Timothy; Tracton, Gregg; Tang, Xiaoli; Lian, Jun; Dooley, John; Chang, Sha X

2014-03-06

Direct aperture optimization (DAO) has been used to produce high dosimetric quality intensity-modulated radiotherapy (IMRT) treatment plans with fast treatment delivery by directly modeling the multileaf collimator segment shapes and weights. To improve plan quality and reduce treatment time for our in-house treatment planning system, we implemented a new DAO approach without using a global objective function (GFO). An index concept is introduced as an inverse form of back-projection used in the CT multiplicative algebraic reconstruction technique (MART). The index, introduced for IMRT optimization in this work, is analogous to the multiplicand in MART. The index is defined as the ratio of the optima over the current. It is assigned to each voxel and beamlet to optimize the fluence map. The indices for beamlets and segments are used to optimize multileaf collimator (MLC) segment shapes and segment weights, respectively. Preliminary data show that without sacrificing dosimetric quality, the implementation of the DAO reduced average IMRT treatment time from 13 min to 8 min for the prostate, and from 15 min to 9 min for the head and neck using our in-house treatment planning system PlanUNC. The DAO approach has also shown promise in optimizing rotational IMRT with burst mode in a head and neck test case.

SU-F-T-187: Quantifying Normal Tissue Sparing with 4D Robust Optimization of Intensity Modulated Proton Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Newpower, M; Ge, S; Mohan, R

Purpose: To report an approach to quantify the normal tissue sparing for 4D robustly-optimized versus PTV-optimized IMPT plans. Methods: We generated two sets of 90 DVHs from a patient’s 10-phase 4D CT set; one by conventional PTV-based optimization done in the Eclipse treatment planning system, and the other by an in-house robust optimization algorithm. The 90 DVHs were created for the following scenarios in each of the ten phases of the 4DCT: ± 5mm shift along x, y, z; ± 3.5% range uncertainty and a nominal scenario. A Matlab function written by Gay and Niemierko was modified to calculate EUDmore » for each DVH for the following structures: esophagus, heart, ipsilateral lung and spinal cord. An F-test determined whether or not the variances of each structure’s DVHs were statistically different. Then a t-test determined if the average EUDs for each optimization algorithm were statistically significantly different. Results: T-test results showed each structure had a statistically significant difference in average EUD when comparing robust optimization versus PTV-based optimization. Under robust optimization all structures except the spinal cord received lower EUDs than PTV-based optimization. Using robust optimization the average EUDs decreased 1.45% for the esophagus, 1.54% for the heart and 5.45% for the ipsilateral lung. The average EUD to the spinal cord increased 24.86% but was still well below tolerance. Conclusion: This work has helped quantify a qualitative relationship noted earlier in our work: that robust optimization leads to plans with greater normal tissue sparing compared to PTV-based optimization. Except in the case of the spinal cord all structures received a lower EUD under robust optimization and these results are statistically significant. While the average EUD to the spinal cord increased to 25.06 Gy under robust optimization it is still well under the TD50 value of 66.5 Gy from Emami et al. Supported in part by the NCI U19 CA021239.« less

Decision Models for Determining the Optimal Life Test Sampling Plans

NASA Astrophysics Data System (ADS)

Nechval, Nicholas A.; Nechval, Konstantin N.; Purgailis, Maris; Berzins, Gundars; Strelchonok, Vladimir F.

2010-11-01

Life test sampling plan is a technique, which consists of sampling, inspection, and decision making in determining the acceptance or rejection of a batch of products by experiments for examining the continuous usage time of the products. In life testing studies, the lifetime is usually assumed to be distributed as either a one-parameter exponential distribution, or a two-parameter Weibull distribution with the assumption that the shape parameter is known. Such oversimplified assumptions can facilitate the follow-up analyses, but may overlook the fact that the lifetime distribution can significantly affect the estimation of the failure rate of a product. Moreover, sampling costs, inspection costs, warranty costs, and rejection costs are all essential, and ought to be considered in choosing an appropriate sampling plan. The choice of an appropriate life test sampling plan is a crucial decision problem because a good plan not only can help producers save testing time, and reduce testing cost; but it also can positively affect the image of the product, and thus attract more consumers to buy it. This paper develops the frequentist (non-Bayesian) decision models for determining the optimal life test sampling plans with an aim of cost minimization by identifying the appropriate number of product failures in a sample that should be used as a threshold in judging the rejection of a batch. The two-parameter exponential and Weibull distributions with two unknown parameters are assumed to be appropriate for modelling the lifetime of a product. A practical numerical application is employed to demonstrate the proposed approach.

SU-G-TeP3-11: Radiobiological-Cum-Dosimetric Quality Assurance of Complex Radiotherapy Plans

DOE Office of Scientific and Technical Information (OSTI.GOV)

Paudel, N; Narayanasamy, G; Zhang, X

2016-06-15

Purpose: Dosimetric gamma-analysis used for QA of complex radiotherapy plans tests the dosimetric equivalence of a delivered plan with the treatment planning system (TPS) optimized plan. It does not examine whether a dosimetric difference results in any radiobiological difference. This study introduces a method to test the radiobiological and dosimetric equivalence between a delivered and the TPS optimized plan. Methods: Six head and neck and seven lung cancer VMAT or IMRT plans optimized for patient treatment were calculated and delivered to an ArcCheck phantom. ArcCheck measured dose distributions were compared with the TPS calculated dose distributions using a 2-D gamma-analysis.more » Dose volume histograms (DVHs) for various patient structures were obtained by using measured data in 3DVH software and compared against the TPS calculated DVHs using 3-D gamma analysis. DVH data were used in the Poisson model to calculate tumor control probability (TCP) for the treatment targets and in the sigmoid dose response model to calculate normal tissue complication probability (NTCP) for the normal structures. Results: Two-D and three-D gamma passing rates among six H&N patient plans differed by 0 to 2.7% and among seven lung plans by 0.1 to 4.5%. Average ± SD TCPs based on measurement and TPS were 0.665±0.018 and 0.674±0.044 for H&N, and 0.791±0.027 and 0.733±0.031 for lung plans, respectively. Differences in NTCPs were usually negligible. The differences in dosimetric results, TCPs and NTCPs were insignificant. Conclusion: The 2-D and 3-D gamma-analysis based agreement between measured and planned dose distributions may indicate their dosimetric equivalence. Small and insignificant differences in TCPs and NTCPs based on measured and planned dose distributions indicate the radiobiological equivalence between the measured and optimized plans. However, patient plans showing larger differences between 2-D and 3-D gamma-analysis can help us make a more definite conclusion through our ongoing research with a larger number of patients.« less

SU-E-T-654: Quantifying Plan Quality Can Effectively Distinguish Between Competing Equivocal IMRT Prostate Plans

DOE Office of Scientific and Technical Information (OSTI.GOV)

Price, A; Lo, J; Department of Radiology, Duke University Medical Center, Durham, NC

2015-06-15

Purpose: The purpose of this study was to create a prostate IMRT plan quality index (PQI) that may be used to quantitatively compare competing plans using a methodology that mimics physician preference. This methodology allows planners to choose between plans with equivocal characteristics, prior to physician scrutiny. Methods: An observer study was conducted to gather data from 3 radiation oncology physicians who ranked a set of 20 patients (each with 5 plans). The rankings were used to optimize a PQI that combined weighted portions of the rectum, bladder, and planning target volume DVHs, such that the relative PQI mimicked physicianmore » rankings as best as possible. Once optimized, a test study assessed the PQI by comparison to physician rankings in a new set of 25 patients (each with 4 plans). The physician group in the test study included 6 physicians, 5 of whom were not included in the modeling study. PQI scores were evaluated against the physicians’ rank list using Spearman rank correlation. Results: The optimized plan quality index combined the following DVH features: high dose regions above 40Gy/60Gy (rectum/bladder), organ weightings, and PTV shoulder coverage. Mean correlation of the PQI vs. physicians’ rankings in the modeling study was 0.507 (range: 0.345–0.706). By comparison, the mean correlation between physicians was 0.301 (range: 0.242–0.334). The mean correlation of the PQI vs. physician rankings in test study was 0.726 (range: 0.416–0.936), indicating robustness of the PQI by virtue of producing similar results to the modeling study. Intra-physician correlation was 0.564 (range: 0.398–0.689). Conclusion: The correlation coefficients of the PQI vs. physicians were similar to the correlation coefficients of the physicians with each other, implying that the PQI developed in this work shows promise in reflecting physician clinical preference when selecting between competing, dosimetrically equivocal plans.« less

Improved approach for electric vehicle rapid charging station placement and sizing using Google maps and binary lightning search algorithm

PubMed Central

Shareef, Hussain; Mohamed, Azah

2017-01-01

The electric vehicle (EV) is considered a premium solution to global warming and various types of pollution. Nonetheless, a key concern is the recharging of EV batteries. Therefore, this study proposes a novel approach that considers the costs of transportation loss, buildup, and substation energy loss and that incorporates harmonic power loss into optimal rapid charging station (RCS) planning. A novel optimization technique, called binary lightning search algorithm (BLSA), is proposed to solve the optimization problem. BLSA is also applied to a conventional RCS planning method. A comprehensive analysis is conducted to assess the performance of the two RCS planning methods by using the IEEE 34-bus test system as the power grid. The comparative studies show that the proposed BLSA is better than other optimization techniques. The daily total cost in RCS planning of the proposed method, including harmonic power loss, decreases by 10% compared with that of the conventional method. PMID:29220396

Improved approach for electric vehicle rapid charging station placement and sizing using Google maps and binary lightning search algorithm.

PubMed

Islam, Md Mainul; Shareef, Hussain; Mohamed, Azah

2017-01-01

The electric vehicle (EV) is considered a premium solution to global warming and various types of pollution. Nonetheless, a key concern is the recharging of EV batteries. Therefore, this study proposes a novel approach that considers the costs of transportation loss, buildup, and substation energy loss and that incorporates harmonic power loss into optimal rapid charging station (RCS) planning. A novel optimization technique, called binary lightning search algorithm (BLSA), is proposed to solve the optimization problem. BLSA is also applied to a conventional RCS planning method. A comprehensive analysis is conducted to assess the performance of the two RCS planning methods by using the IEEE 34-bus test system as the power grid. The comparative studies show that the proposed BLSA is better than other optimization techniques. The daily total cost in RCS planning of the proposed method, including harmonic power loss, decreases by 10% compared with that of the conventional method.

A comprehensive formulation for volumetric modulated arc therapy planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nguyen, Dan; Lyu, Qihui; Ruan, Dan

2016-07-15

Purpose: Volumetric modulated arc therapy (VMAT) is a widely employed radiation therapy technique, showing comparable dosimetry to static beam intensity modulated radiation therapy (IMRT) with reduced monitor units and treatment time. However, the current VMAT optimization has various greedy heuristics employed for an empirical solution, which jeopardizes plan consistency and quality. The authors introduce a novel direct aperture optimization method for VMAT to overcome these limitations. Methods: The comprehensive VMAT (comVMAT) planning was formulated as an optimization problem with an L2-norm fidelity term to penalize the difference between the optimized dose and the prescribed dose, as well as an anisotropicmore » total variation term to promote piecewise continuity in the fluence maps, preparing it for direct aperture optimization. A level set function was used to describe the aperture shapes and the difference between aperture shapes at adjacent angles was penalized to control MLC motion range. A proximal-class optimization solver was adopted to solve the large scale optimization problem, and an alternating optimization strategy was implemented to solve the fluence intensity and aperture shapes simultaneously. Single arc comVMAT plans, utilizing 180 beams with 2° angular resolution, were generated for a glioblastoma multiforme case, a lung (LNG) case, and two head and neck cases—one with three PTVs (H&N{sub 3PTV}) and one with foue PTVs (H&N{sub 4PTV})—to test the efficacy. The plans were optimized using an alternating optimization strategy. The plans were compared against the clinical VMAT (clnVMAT) plans utilizing two overlapping coplanar arcs for treatment. Results: The optimization of the comVMAT plans had converged within 600 iterations of the block minimization algorithm. comVMAT plans were able to consistently reduce the dose to all organs-at-risk (OARs) as compared to the clnVMAT plans. On average, comVMAT plans reduced the max and mean OAR dose by 6.59% and 7.45%, respectively, of the prescription dose. Reductions in max dose and mean dose were as high as 14.5 Gy in the LNG case and 15.3 Gy in the H&N{sub 3PTV} case. PTV coverages measured by D95, D98, and D99 were within 0.25% of the prescription dose. By comprehensively optimizing all beams, the comVMAT optimizer gained the freedom to allow some selected beams to deliver higher intensities, yielding a dose distribution that resembles a static beam IMRT plan with beam orientation optimization. Conclusions: The novel nongreedy VMAT approach simultaneously optimizes all beams in an arc and then directly generates deliverable apertures. The single arc VMAT approach thus fully utilizes the digital Linac’s capability in dose rate and gantry rotation speed modulation. In practice, the new single VMAT algorithm generates plans superior to existing VMAT algorithms utilizing two arcs.« less

Planning Image-Based Measurements in Wind Tunnels by Virtual Imaging

NASA Technical Reports Server (NTRS)

Kushner, Laura Kathryn; Schairer, Edward T.

2011-01-01

Virtual imaging is routinely used at NASA Ames Research Center to plan the placement of cameras and light sources for image-based measurements in production wind tunnel tests. Virtual imaging allows users to quickly and comprehensively model a given test situation, well before the test occurs, in order to verify that all optical testing requirements will be met. It allows optimization of the placement of cameras and light sources and leads to faster set-up times, thereby decreasing tunnel occupancy costs. This paper describes how virtual imaging was used to plan optical measurements for three tests in production wind tunnels at NASA Ames.

SU-F-P-61: Does It Matter Not to Use Optimization Points at the Apex for Vaginal Cylinder HDR Brachytherapy Planning?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Y

2016-06-15

Purpose: To test the impact of the use of apex optimization points for new vaginal cylinder (VC) applicators. Methods: New “ClickFit” single channel VC applicators (Varian) that have a different top thicknesses but the same diameters as the old VC applicators (2.3 cm diameter, 2.6 cm, 3.0 cm, and 3.5 cm) were compared using phantom studies. Old VC applicator plans without apex optimization points were also compared to the plans with the optimization points. The apex doses were monitored at 5 mm depth doses (8 points) where a prescription dose (Rx) of 6Gy was prescribed. VC surface doses (8 points)more » were also analyzed. Results: The new VC applicator plans without apex optimization points presented significantly lower 5mm depth doses than Rx (on average −31 ± 7%, p <0.00001) due to their thicker VC tops (3.4 ± 1.1 mm thicker with the range of 1.2 to 4.4 mm) than the old VC applicators. Old VC applicator plans also showed a statistically significant reduction (p <0.00001) due to Ir-192 source anisotropic effect at the apex region but the % reduction over Rx was only −7 ± 9%. However, by adding apex optimization points to the new VC applicator plans, the plans improved 5 mm depth doses (−7 ± 9% over Rx) that were not statistically different from old VC plans (p = 0.923), along with apex VC surface doses (−22 ± 10% over old VC versus −46 ± 7% without using apex optimization points). Conclusion: The use of apex optimization points are important in order to avoid significant additional cold doses (−24 ± 2%) at the prescription depth (5 mm) of apex, especially for the new VC applicators that have thicker tops.« less

Commissioning of a 3D image‐based treatment planning system for high‐dose‐rate brachytherapy of cervical cancer

PubMed Central

Kim, Yongbok; Modrick, Joseph M.; Pennington, Edward C.

2016-01-01

The objective of this work is to present commissioning procedures to clinically implement a three‐dimensional (3D), image‐based, treatment‐planning system (TPS) for high‐dose‐rate (HDR) brachytherapy (BT) for gynecological (GYN) cancer. The physical dimensions of the GYN applicators and their values in the virtual applicator library were varied by 0.4 mm of their nominal values. Reconstruction uncertainties of the titanium tandem and ovoids (T&O) were less than 0.4 mm on CT phantom studies and on average between 0.8‐1.0 mm on MRI when compared with X‐rays. In‐house software, HDRCalculator, was developed to check HDR plan parameters such as independently verifying active tandem or cylinder probe length and ovoid or cylinder size, source calibration and treatment date, and differences between average Point A dose and prescription dose. Dose‐volume histograms were validated using another independent TPS. Comprehensive procedures to commission volume optimization algorithms and process in 3D image‐based planning were presented. For the difference between line and volume optimizations, the average absolute differences as a percentage were 1.4% for total reference air KERMA (TRAK) and 1.1% for Point A dose. Volume optimization consistency tests between versions resulted in average absolute differences in 0.2% for TRAK and 0.9 s (0.2%) for total treatment time. The data revealed that the optimizer should run for at least 1 min in order to avoid more than 0.6% dwell time changes. For clinical GYN T&O cases, three different volume optimization techniques (graphical optimization, pure inverse planning, and hybrid inverse optimization) were investigated by comparing them against a conventional Point A technique. End‐to‐end testing was performed using a T&O phantom to ensure no errors or inconsistencies occurred from imaging through to planning and delivery. The proposed commissioning procedures provide a clinically safe implementation technique for 3D image‐based TPS for HDR BT for GYN cancer. PACS number(s): 87.55.D‐ PMID:27074463

Exploratory Study of 4D Versus 3D Robust Optimization in Intensity-Modulated Proton Therapy for Lung Cancer

PubMed Central

Liu, Wei; Schild, Steven E.; Chang, Joe Y.; Liao, Zhongxing; Chang, Yu-Hui; Wen, Zhifei; Shen, Jiajian; Stoker, Joshua B.; Ding, Xiaoning; Hu, Yanle; Sahoo, Narayan; Herman, Michael G.; Vargas, Carlos; Keole, Sameer; Wong, William; Bues, Martin

2015-01-01

Background To compare the impact of uncertainties and interplay effect on 3D and 4D robustly optimized intensity-modulated proton therapy (IMPT) plans for lung cancer in an exploratory methodology study. Methods IMPT plans were created for 11 non-randomly selected non-small-cell lung cancer (NSCLC) cases: 3D robustly optimized plans on average CTs with internal gross tumor volume density overridden to irradiate internal target volume, and 4D robustly optimized plans on 4D CTs to irradiate clinical target volume (CTV). Regular fractionation (66 Gy[RBE] in 33 fractions) were considered. In 4D optimization, the CTV of individual phases received non-uniform doses to achieve a uniform cumulative dose. The root-mean-square-dose volume histograms (RVH) measured the sensitivity of the dose to uncertainties, and the areas under the RVH curve (AUCs) were used to evaluate plan robustness. Dose evaluation software modeled time-dependent spot delivery to incorporate interplay effect with randomized starting phases of each field per fraction. Dose-volume histogram indices comparing CTV coverage, homogeneity, and normal tissue sparing were evaluated using Wilcoxon signed-rank test. Results 4D robust optimization plans led to smaller AUC for CTV (14.26 vs. 18.61 (p=0.001), better CTV coverage (Gy[RBE]) [D95% CTV: 60.6 vs 55.2 (p=0.001)], and better CTV homogeneity [D5%–D95% CTV: 10.3 vs 17.7 (p=0.002)] in the face of uncertainties. With interplay effect considered, 4D robust optimization produced plans with better target coverage [D95% CTV: 64.5 vs 63.8 (p=0.0068)], comparable target homogeneity, and comparable normal tissue protection. The benefits from 4D robust optimization were most obvious for the 2 typical stage III lung cancer patients. Conclusions Our exploratory methodology study showed that, compared to 3D robust optimization, 4D robust optimization produced significantly more robust and interplay-effect-resistant plans for targets with comparable dose distributions for normal tissues. A further study with a larger and more realistic patient population is warranted to generalize the conclusions. PMID:26725727

Noncoplanar Beam Angle Class Solutions to Replace Time-Consuming Patient-Specific Beam Angle Optimization in Robotic Prostate Stereotactic Body Radiation Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rossi, Linda, E-mail: l.rossi@erasmusmc.nl; Breedveld, Sebastiaan; Aluwini, Shafak

Purpose: To investigate development of a recipe for the creation of a beam angle class solution (CS) for noncoplanar prostate stereotactic body radiation therapy to replace time-consuming individualized beam angle selection (iBAS) without significant loss in plan quality, using the in-house “Erasmus-iCycle” optimizer for fully automated beam profile optimization and iBAS. Methods and Materials: For 30 patients, Erasmus-iCycle was first used to generate 15-, 20-, and 25-beam iBAS plans for a CyberKnife equipped with a multileaf collimator. With these plans, 6 recipes for creation of beam angle CSs were investigated. Plans of 10 patients were used to create CSs based on themore » recipes, and the other 20 to independently test them. For these tests, Erasmus-iCycle was also used to generate intensity modulated radiation therapy plans for the fixed CS beam setups. Results: Of the tested recipes for CS creation, only 1 resulted in 15-, 20-, and 25-beam noncoplanar CSs without plan deterioration compared with iBAS. For the patient group, mean differences in rectum D{sub 1cc}, V{sub 60GyEq}, V{sub 40GyEq}, and D{sub mean} between 25-beam CS plans and 25-beam plans generated with iBAS were 0.2 ± 0.4 Gy, 0.1% ± 0.2%, 0.2% ± 0.3%, and 0.1 ± 0.2 Gy, respectively. Differences between 15- and 20-beam CS and iBAS plans were also negligible. Plan quality for CS plans relative to iBAS plans was also preserved when narrower planning target volume margins were arranged and when planning target volume dose inhomogeneity was decreased. Using a CS instead of iBAS reduced the computation time by a factor of 14 to 25, mainly depending on beam number, without loss in plan quality. Conclusions: A recipe for creation of robust beam angle CSs for robotic prostate stereotactic body radiation therapy has been developed. Compared with iBAS, computation times decreased by a factor 14 to 25. The use of a CS may avoid long planning times without losses in plan quality.« less

Design of Quiet Rotorcraft Approach Trajectories: Verification Phase

NASA Technical Reports Server (NTRS)

Padula, Sharon L.

2010-01-01

Flight testing that is planned for October 2010 will provide an opportunity to evaluate rotorcraft trajectory optimization techniques. The flight test will involve a fully instrumented MD-902 helicopter, which will be flown over an array of microphones. In this work, the helicopter approach trajectory is optimized via a multiobjective genetic algorithm to improve community noise, passenger comfort, and pilot acceptance. Previously developed optimization strategies are modified to accommodate new helicopter data and to increase pilot acceptance. This paper describes the MD-902 trajectory optimization plus general optimization strategies and modifications that are needed to reduce the uncertainty in noise predictions. The constraints that are imposed by the flight test conditions and characteristics of the MD-902 helicopter limit the testing possibilities. However, the insights that will be gained through this research will prove highly valuable.

Development and flight testing of UV optimized Photon Counting CCDs

NASA Astrophysics Data System (ADS)

Hamden, Erika T.

2018-06-01

I will discuss the latest results from the Hamden UV/Vis Detector Lab and our ongoing work using a UV optimized EMCCD in flight. Our lab is currently testing efficiency and performance of delta-doped, anti-reflection coated EMCCDs, in collaboration with JPL. The lab has been set-up to test quantum efficiency, dark current, clock-induced-charge, and read noise. I will describe our improvements to our circuit boards for lower noise, updates from a new, more flexible NUVU controller, and the integration of an EMCCD in the FIREBall-2 UV spectrograph. I will also briefly describe future plans to conduct radiation testing on delta-doped EMCCDs (both warm, unbiased and cold, biased configurations) thus summer and longer term plans for testing newer photon counting CCDs as I move the HUVD Lab to the University of Arizona in the Fall of 2018.

Development of Autonomous Optimal Cooperative Control in Relay Rover Configured Small Unmanned Aerial Systems

DTIC Science & Technology

2013-03-01

Unmanned Aircraft Systems Flight Plan that identified small unmanned aerial systems ( SUAS ) as “a profound technological...advances in small unmanned aerial systems ( SUAS ) cooperative control. The end state objective of the research effort was to flight test an autonomous...requirements were captured in the Unmanned Aircraft Systems Flight Plan . The flight plan

Spatiotemporal radiotherapy planning using a global optimization approach

NASA Astrophysics Data System (ADS)

Adibi, Ali; Salari, Ehsan

2018-02-01

This paper aims at quantifying the extent of potential therapeutic gain, measured using biologically effective dose (BED), that can be achieved by altering the radiation dose distribution over treatment sessions in fractionated radiotherapy. To that end, a spatiotemporally integrated planning approach is developed, where the spatial and temporal dose modulations are optimized simultaneously. The concept of equivalent uniform BED (EUBED) is used to quantify and compare the clinical quality of spatiotemporally heterogeneous dose distributions in target and critical structures. This gives rise to a large-scale non-convex treatment-plan optimization problem, which is solved using global optimization techniques. The proposed spatiotemporal planning approach is tested on two stylized cancer cases resembling two different tumor sites and sensitivity analysis is performed for radio-biological and EUBED parameters. Numerical results validate that spatiotemporal plans are capable of delivering a larger BED to the target volume without increasing the BED in critical structures compared to conventional time-invariant plans. In particular, this additional gain is attributed to the irradiation of different regions of the target volume at different treatment sessions. Additionally, the trade-off between the potential therapeutic gain and the number of distinct dose distributions is quantified, which suggests a diminishing marginal gain as the number of dose distributions increases.

SU-F-T-419: Evaluation of PlanIQ Feasibility DVH as Planning Objectives for Skull Base SBRT Patients

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiang, W; Wang, H; Chi, P

2016-06-15

Purpose: PlanIQ(Sun Nuclear Corporation) can provide feasibility measures on organs-at-risk(OARs) around the target based on depth, local anatomy density and energy of radiation beam used. This study is to test and evaluate PlanIQ feasibility DVHs as optimization objectives in the treatment planning process, and to investigate the potential to use them in routine clinical cases to improve planning efficiency. Methods: Two to three arcs VMAT Treatment plans were generated in Pinnacle based on PlanIQ feasibility DVH for six skull base patients who previously treated with SBRT. The PlanIQ feasibility DVH for each OAR consists of four zones – impossible (atmore » 100% target coverage), difficult, challenging and probable. Constrains to achieve DVH in difficult zone were used to start plan optimization. Further adjustment was made to improve coverage. The plan DVHs were compared to PlanIQ feasibility DVH to assess the dose received by 0%(D0), 5%(D5), 10%(D10) and 50%(D50) of the OAR volumes. Results: A total of 90 OARs were evaluated for 6 patients (mean 15 OARs, range 11–18 OARs). We used >98% PTV coverage as planning goal since it’s difficult to achieve 100% target coverage. For the generated plans, 96.7% of the OARs achieved D0 or D5 within difficult zone or impossible zone (ipsilateral OARs 93.5%, contralateral OARs 100%), while 90% and 65.6% of the OARs achieved D10 and D50 within difficult zone, respectively. Seventeen of the contralateral and out of field OARs achieved DVHs in impossible zone. For OARs adjacent or overlapped with target volume, the D0 and D5 are challenging to be optimized into difficult zone. All plans were completed within 2–4 adjustments to improve target coverage and uniformity. Conclusion: PlanIQ feasibility tool has the potential to provide difficult but achievable initial optimization objectives and therefore reduce the planning time to obtain a well optimized plan.« less

Feasibility and robustness of dose painting by numbers in proton therapy with contour-driven plan optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barragán, A. M., E-mail: ana.barragan@uclouvain.be; Differding, S.; Lee, J. A.

Purpose: To prove the ability of protons to reproduce a dose gradient that matches a dose painting by numbers (DPBN) prescription in the presence of setup and range errors, by using contours and structure-based optimization in a commercial treatment planning system. Methods: For two patients with head and neck cancer, voxel-by-voxel prescription to the target volume (GTV{sub PET}) was calculated from {sup 18}FDG-PET images and approximated with several discrete prescription subcontours. Treatments were planned with proton pencil beam scanning. In order to determine the optimal plan parameters to approach the DPBN prescription, the effects of the scanning pattern, number ofmore » fields, number of subcontours, and use of range shifter were separately tested on each patient. Different constant scanning grids (i.e., spot spacing = Δx = Δy = 3.5, 4, and 5 mm) and uniform energy layer separation [4 and 5 mm WED (water equivalent distance)] were analyzed versus a dynamic and automatic selection of the spots grid. The number of subcontours was increased from 3 to 11 while the number of beams was set to 3, 5, or 7. Conventional PTV-based and robust clinical target volumes (CTV)-based optimization strategies were considered and their robustness against range and setup errors assessed. Because of the nonuniform prescription, ensuring robustness for coverage of GTV{sub PET} inevitably leads to overdosing, which was compared for both optimization schemes. Results: The optimal number of subcontours ranged from 5 to 7 for both patients. All considered scanning grids achieved accurate dose painting (1% average difference between the prescribed and planned doses). PTV-based plans led to nonrobust target coverage while robust-optimized plans improved it considerably (differences between worst-case CTV dose and the clinical constraint was up to 3 Gy for PTV-based plans and did not exceed 1 Gy for robust CTV-based plans). Also, only 15% of the points in the GTV{sub PET} (worst case) were above 5% of DPBN prescription for robust-optimized plans, while they were more than 50% for PTV plans. Low dose to organs at risk (OARs) could be achieved for both PTV and robust-optimized plans. Conclusions: DPBN in proton therapy is feasible with the use of a sufficient number subcontours, automatically generated scanning patterns, and no more than three beams are needed. Robust optimization ensured the required target coverage and minimal overdosing, while PTV-approach led to nonrobust plans with excessive overdose. Low dose to OARs can be achieved even in the presence of a high-dose escalation as in DPBN.« less

Coverage-based constraints for IMRT optimization

NASA Astrophysics Data System (ADS)

Mescher, H.; Ulrich, S.; Bangert, M.

2017-09-01

Radiation therapy treatment planning requires an incorporation of uncertainties in order to guarantee an adequate irradiation of the tumor volumes. In current clinical practice, uncertainties are accounted for implicitly with an expansion of the target volume according to generic margin recipes. Alternatively, it is possible to account for uncertainties by explicit minimization of objectives that describe worst-case treatment scenarios, the expectation value of the treatment or the coverage probability of the target volumes during treatment planning. In this note we show that approaches relying on objectives to induce a specific coverage of the clinical target volumes are inevitably sensitive to variation of the relative weighting of the objectives. To address this issue, we introduce coverage-based constraints for intensity-modulated radiation therapy (IMRT) treatment planning. Our implementation follows the concept of coverage-optimized planning that considers explicit error scenarios to calculate and optimize patient-specific probabilities q(\\hat{d}, \\hat{v}) of covering a specific target volume fraction \\hat{v} with a certain dose \\hat{d} . Using a constraint-based reformulation of coverage-based objectives we eliminate the trade-off between coverage and competing objectives during treatment planning. In-depth convergence tests including 324 treatment plan optimizations demonstrate the reliability of coverage-based constraints for varying levels of probability, dose and volume. General clinical applicability of coverage-based constraints is demonstrated for two cases. A sensitivity analysis regarding penalty variations within this planing study based on IMRT treatment planning using (1) coverage-based constraints, (2) coverage-based objectives, (3) probabilistic optimization, (4) robust optimization and (5) conventional margins illustrates the potential benefit of coverage-based constraints that do not require tedious adjustment of target volume objectives.

WE-DE-201-01: BEST IN PHYSICS (THERAPY): A Fast Multi-Target Inverse Treatment Planning Strategy Optimizing Dosimetric Measures for High-Dose-Rate (HDR) Brachytherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Guthier, C; University Medical Center Mannheim, Mannheim; Harvard Medical School, Boston, MA

Purpose: Inverse treatment planning (ITP) for interstitial HDR brachytherapy of gynecologic cancers seeks to maximize coverage of the clinical target volumes (tumor and vagina) while respecting dose-volume-histogram related dosimetric measures (DMs) for organs at risk (OARs). Commercially available ITP tools do not support DM-based planning because it is computationally too expensive to solve. In this study we present a novel approach that allows fast ITP for gynecologic cancers based on DMs for the first time. Methods: This novel strategy is an optimization model based on a smooth DM-based objective function. The smooth approximation is achieved by utilizing a logistic functionmore » for the evaluation of DMs. The resulting nonconvex and constrained optimization problem is then optimized with a BFGS algorithm. The model was evaluated using the implant geometry extracted from 20 patient treatment plans under an IRB-approved retrospective study. For each plan, the final DMs were evaluated and compared to the original clinical plans. The CTVs were the contoured tumor volume and the contoured surface of the vagina. Statistical significance was evaluated with a one-sided paired Wilcoxon signed-rank test. Results: As did the clinical plans, all generated plans fulfilled the defined DMs for OARs. The proposed strategy showed a statistically significant improvement (p<0.001) in coverage of the tumor and vagina, with absolute improvements of related DMs of (6.9 +/− 7.9)% and (28.2 +/− 12.0)%, respectively. This was achieved with a statistically significant (p<0.01) decrease of the high-dose-related DM for the tumor. The runtime of the optimization was (2.3 +/− 2.0) seconds. Conclusion: We demonstrated using clinical data that our novel approach allows rapid DM-based optimization with improved coverage of CTVs with fewer hot spots. Being up to three orders of magnitude faster than the current clinical practice, the method dramatically shortens planning time.« less

Full Monte Carlo-Based Biologic Treatment Plan Optimization System for Intensity Modulated Carbon Ion Therapy on Graphics Processing Unit.

PubMed

Qin, Nan; Shen, Chenyang; Tsai, Min-Yu; Pinto, Marco; Tian, Zhen; Dedes, Georgios; Pompos, Arnold; Jiang, Steve B; Parodi, Katia; Jia, Xun

2018-01-01

One of the major benefits of carbon ion therapy is enhanced biological effectiveness at the Bragg peak region. For intensity modulated carbon ion therapy (IMCT), it is desirable to use Monte Carlo (MC) methods to compute the properties of each pencil beam spot for treatment planning, because of their accuracy in modeling physics processes and estimating biological effects. We previously developed goCMC, a graphics processing unit (GPU)-oriented MC engine for carbon ion therapy. The purpose of the present study was to build a biological treatment plan optimization system using goCMC. The repair-misrepair-fixation model was implemented to compute the spatial distribution of linear-quadratic model parameters for each spot. A treatment plan optimization module was developed to minimize the difference between the prescribed and actual biological effect. We used a gradient-based algorithm to solve the optimization problem. The system was embedded in the Varian Eclipse treatment planning system under a client-server architecture to achieve a user-friendly planning environment. We tested the system with a 1-dimensional homogeneous water case and 3 3-dimensional patient cases. Our system generated treatment plans with biological spread-out Bragg peaks covering the targeted regions and sparing critical structures. Using 4 NVidia GTX 1080 GPUs, the total computation time, including spot simulation, optimization, and final dose calculation, was 0.6 hour for the prostate case (8282 spots), 0.2 hour for the pancreas case (3795 spots), and 0.3 hour for the brain case (6724 spots). The computation time was dominated by MC spot simulation. We built a biological treatment plan optimization system for IMCT that performs simulations using a fast MC engine, goCMC. To the best of our knowledge, this is the first time that full MC-based IMCT inverse planning has been achieved in a clinically viable time frame. Copyright © 2017 Elsevier Inc. All rights reserved.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kontaxis, C; Bol, G; Lagendijk, J

2016-06-15

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 certainmore » 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.« less

TU-EF-304-03: 4D Monte Carlo Robustness Test for Proton Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Souris, K; Sterpin, E; Lee, J

Purpose: Breathing motion and approximate dose calculation engines may increase proton range uncertainties. We address these two issues using a comprehensive 4D robustness evaluation tool based on an efficient Monte Carlo (MC) engine, which can simulate breathing with no significant increase in computation time. Methods: To assess the robustness of the treatment plan, multiple scenarios of uncertainties are simulated, taking into account the systematic and random setup errors, range uncertainties, and organ motion. Our fast MC dose engine, called MCsquare, implements optimized models on a massively-parallel computation architecture and allows us to accurately simulate a scenario in less than onemore » minute. The deviations of the uncertainty scenarios are then reported on a DVH-band and compared to the nominal plan.The robustness evaluation tool is illustrated in a lung case by comparing three 60Gy treatment plans. First, a plan is optimized on a PTV obtained by extending the CTV with an 8mm margin, in order to take into account systematic geometrical uncertainties, like in our current practice in radiotherapy. No specific strategy is employed to correct for tumor and organ motions. The second plan involves a PTV generated from the ITV, which encompasses the tumor volume in all breathing phases. The last plan results from robust optimization performed on the ITV, with robustness parameters of 3% for tissue density and 8 mm for positioning errors. Results: The robustness test revealed that the first two plans could not properly cover the target in the presence of uncertainties. CTV-coverage (D95) in the three plans ranged respectively between 39.4–55.5Gy, 50.2–57.5Gy, and 55.1–58.6Gy. Conclusion: A realistic robustness verification tool based on a fast MC dose engine has been developed. This test is essential to assess the quality of proton therapy plan and very useful to study various planning strategies for mobile tumors. This work is partly funded by IBA (Louvain-la-Neuve, Belgium)« less

Uncertainty reduction in intensity modulated proton therapy by inverse Monte Carlo treatment planning

NASA Astrophysics Data System (ADS)

Morávek, Zdenek; Rickhey, Mark; Hartmann, Matthias; Bogner, Ludwig

2009-08-01

Treatment plans for intensity-modulated proton therapy may be sensitive to some sources of uncertainty. One source is correlated with approximations of the algorithms applied in the treatment planning system and another one depends on how robust the optimization is with regard to intra-fractional tissue movements. The irradiated dose distribution may substantially deteriorate from the planning when systematic errors occur in the dose algorithm. This can influence proton ranges and lead to improper modeling of the Braggpeak degradation in heterogeneous structures or particle scatter or the nuclear interaction part. Additionally, systematic errors influence the optimization process, which leads to the convergence error. Uncertainties with regard to organ movements are related to the robustness of a chosen beam setup to tissue movements on irradiation. We present the inverse Monte Carlo treatment planning system IKO for protons (IKO-P), which tries to minimize the errors described above to a large extent. Additionally, robust planning is introduced by beam angle optimization according to an objective function penalizing paths representing strongly longitudinal and transversal tissue heterogeneities. The same score function is applied to optimize spot planning by the selection of a robust choice of spots. As spots can be positioned on different energy grids or on geometric grids with different space filling factors, a variety of grids were used to investigate the influence on the spot-weight distribution as a result of optimization. A tighter distribution of spot weights was assumed to result in a more robust plan with respect to movements. IKO-P is described in detail and demonstrated on a test case and a lung cancer case as well. Different options of spot planning and grid types are evaluated, yielding a superior plan quality with dose delivery to the spots from all beam directions over optimized beam directions. This option shows a tighter spot-weight distribution and should therefore be less sensitive to movements compared to optimized directions. But accepting a slight loss in plan quality, the latter choice could potentially improve robustness even further by accepting only spots from the most proper direction. The choice of a geometric grid instead of an energy grid for spot positioning has only a minor influence on the plan quality, at least for the investigated lung case.

Optimization and Performance Analysis of a Supersonic Conical-Flow Waverider for a Deck-Launched Intercept Mission

DTIC Science & Technology

1993-06-01

radius aid 20 minutes of comibat follovcu by retum to the carrer . A conical-flow waweider served as the starting pount for the aircraft configuration. A...design, test meia adj p teat paramieter siekction were studied for planned low speed wind and water tunnel tests as well as performance predictions fir die... planned win~d tunnel tests. 14. SUBJECT TERMS 15. NUMBER OF PAGES Waveniders, Hypersonics, Aircraft Design 82 `16. PRICE CODE 17. SECURITY

Exploratory Study of 4D versus 3D Robust Optimization in Intensity Modulated Proton Therapy for Lung Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Wei, E-mail: Liu.Wei@mayo.edu; Schild, Steven E.; Chang, Joe Y.

Purpose: The purpose of this study was to compare the impact of uncertainties and interplay on 3-dimensional (3D) and 4D robustly optimized intensity modulated proton therapy (IMPT) plans for lung cancer in an exploratory methodology study. Methods and Materials: IMPT plans were created for 11 nonrandomly selected non-small cell lung cancer (NSCLC) cases: 3D robustly optimized plans on average CTs with internal gross tumor volume density overridden to irradiate internal target volume, and 4D robustly optimized plans on 4D computed tomography (CT) to irradiate clinical target volume (CTV). Regular fractionation (66 Gy [relative biological effectiveness; RBE] in 33 fractions) was considered.more » In 4D optimization, the CTV of individual phases received nonuniform doses to achieve a uniform cumulative dose. The root-mean-square dose-volume histograms (RVH) measured the sensitivity of the dose to uncertainties, and the areas under the RVH curve (AUCs) were used to evaluate plan robustness. Dose evaluation software modeled time-dependent spot delivery to incorporate interplay effect with randomized starting phases of each field per fraction. Dose-volume histogram (DVH) indices comparing CTV coverage, homogeneity, and normal tissue sparing were evaluated using Wilcoxon signed rank test. Results: 4D robust optimization plans led to smaller AUC for CTV (14.26 vs 18.61, respectively; P=.001), better CTV coverage (Gy [RBE]) (D{sub 95%} CTV: 60.6 vs 55.2, respectively; P=.001), and better CTV homogeneity (D{sub 5%}-D{sub 95%} CTV: 10.3 vs 17.7, resspectively; P=.002) in the face of uncertainties. With interplay effect considered, 4D robust optimization produced plans with better target coverage (D{sub 95%} CTV: 64.5 vs 63.8, respectively; P=.0068), comparable target homogeneity, and comparable normal tissue protection. The benefits from 4D robust optimization were most obvious for the 2 typical stage III lung cancer patients. Conclusions: Our exploratory methodology study showed that, compared to 3D robust optimization, 4D robust optimization produced significantly more robust and interplay-effect-resistant plans for targets with comparable dose distributions for normal tissues. A further study with a larger and more realistic patient population is warranted to generalize the conclusions.« less

Dose-mass inverse optimization for minimally moving thoracic lesions

NASA Astrophysics Data System (ADS)

Mihaylov, I. B.; Moros, E. G.

2015-05-01

In the past decade, several different radiotherapy treatment plan evaluation and optimization schemes have been proposed as viable approaches, aiming for dose escalation or an increase of healthy tissue sparing. In particular, it has been argued that dose-mass plan evaluation and treatment plan optimization might be viable alternatives to the standard of care, which is realized through dose-volume evaluation and optimization. The purpose of this investigation is to apply dose-mass optimization to a cohort of lung cancer patients and compare the achievable healthy tissue sparing to that one achievable through dose-volume optimization. Fourteen non-small cell lung cancer (NSCLC) patient plans were studied retrospectively. The range of tumor motion was less than 0.5 cm and motion management in the treatment planning process was not considered. For each case, dose-volume (DV)-based and dose-mass (DM)-based optimization was performed. Nine-field step-and-shoot IMRT was used, with all of the optimization parameters kept the same between DV and DM optimizations. Commonly used dosimetric indices (DIs) such as dose to 1% the spinal cord volume, dose to 50% of the esophageal volume, and doses to 20 and 30% of healthy lung volumes were used for cross-comparison. Similarly, mass-based indices (MIs), such as doses to 20 and 30% of healthy lung masses, 1% of spinal cord mass, and 33% of heart mass, were also tallied. Statistical equivalence tests were performed to quantify the findings for the entire patient cohort. Both DV and DM plans for each case were normalized such that 95% of the planning target volume received the prescribed dose. DM optimization resulted in more organs at risk (OAR) sparing than DV optimization. The average sparing of cord, heart, and esophagus was 23, 4, and 6%, respectively. For the majority of the DIs, DM optimization resulted in lower lung doses. On average, the doses to 20 and 30% of healthy lung were lower by approximately 3 and 4%, whereas lung volumes receiving 2000 and 3000 cGy were lower by 3 and 2%, respectively. The behavior of MIs was very similar. The statistical analyses of the results again indicated better healthy anatomical structure sparing with DM optimization. The presented findings indicate that dose-mass-based optimization results in statistically significant OAR sparing as compared to dose-volume-based optimization for NSCLC. However, the sparing is case-dependent and it is not observed for all tallied dosimetric endpoints.

SU-E-T-625: Robustness Evaluation and Robust Optimization of IMPT Plans Based on Per-Voxel Standard Deviation of Dose Distributions.

PubMed

Liu, W; Mohan, R

2012-06-01

Proton dose distributions, IMPT in particular, are highly sensitive to setup and range uncertainties. We report a novel method, based on per-voxel standard deviation (SD) of dose distributions, to evaluate the robustness of proton plans and to robustly optimize IMPT plans to render them less sensitive to uncertainties. For each optimization iteration, nine dose distributions are computed - the nominal one, and one each for ± setup uncertainties along x, y and z axes and for ± range uncertainty. SD of dose in each voxel is used to create SD-volume histogram (SVH) for each structure. SVH may be considered a quantitative representation of the robustness of the dose distribution. For optimization, the desired robustness may be specified in terms of an SD-volume (SV) constraint on the CTV and incorporated as a term in the objective function. Results of optimization with and without this constraint were compared in terms of plan optimality and robustness using the so called'worst case' dose distributions; which are obtained by assigning the lowest among the nine doses to each voxel in the clinical target volume (CTV) and the highest to normal tissue voxels outside the CTV. The SVH curve and the area under it for each structure were used as quantitative measures of robustness. Penalty parameter of SV constraint may be varied to control the tradeoff between robustness and plan optimality. We applied these methods to one case each of H&N and lung. In both cases, we found that imposing SV constraint improved plan robustness but at the cost of normal tissue sparing. SVH-based optimization and evaluation is an effective tool for robustness evaluation and robust optimization of IMPT plans. Studies need to be conducted to test the methods for larger cohorts of patients and for other sites. This research is supported by National Cancer Institute (NCI) grant P01CA021239, the University Cancer Foundation via the Institutional Research Grant program at the University of Texas MD Anderson Cancer Center, and MD Anderson’s cancer center support grant CA016672. © 2012 American Association of Physicists in Medicine.

SU-F-T-344: Commissioning Constant Dose Rate VMAT in the Raystation Treatment Planning System for a Varian Clinac IX

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pursley, J; Gueorguiev, G; Prichard, H

Purpose: To demonstrate the commissioning of constant dose rate volumetric modulated arc therapy (VMAT) in the Raystation treatment planning system for a Varian Clinac iX with Exact couch. Methods: Constant dose rate (CDR) VMAT is an option in the Raystation treatment planning system, enabling VMAT delivery on Varian linacs without a RapidArc upgrade. Raystation 4.7 was used to commission CDR-VMAT for a Varian Clinac iX. Raystation arc model parameters were selected to match machine deliverability characteristics. A Varian Exact couch model was added to Raystation 4.7 and commissioned for use in VMAT optimization. CDR-VMAT commissioning checks were performed on themore » linac, including patient-specific QA measurements for 10 test patients using both the ArcCHECK from Sun Nuclear Corporation and COMPASS from IBA Dosimetry. Multi-criteria optimization (MCO) in Raystation was used for CDR-VMAT planning. Results: Raystation 4.7 generated clinically acceptable and deliverable CDR-VMAT plans for the Varian Clinac. VMAT plans were optimized including a model of the Exact couch with both rails in the out positions. CDR-VMAT plans generated with MCO in Raystation were dosimetrically comparable to Raystation MCO-generated IMRT plans. Patient-specific QA measurements with the ArcCHECK on the couch showed good agreement with the treatment planning system prediction. Patient-specific, structure-specific, multi-statistical parameter 3D QA measurements with gantry-mounted COMPASS also showed good agreement. Conclusion: Constant dose rate VMAT was successfully modeled in Raystation 4.7 for a Varian Clinac iX, and Raystation’s multicriteria optimization generated constant dose rate VMAT plans which were deliverable and dosimetrically comparable to IMRT plans.« less

Renewable energy in electric utility capacity planning: a decomposition approach with application to a Mexican utility

DOE Office of Scientific and Technical Information (OSTI.GOV)

Staschus, K.

1985-01-01

In this dissertation, efficient algorithms for electric-utility capacity expansion planning with renewable energy are developed. The algorithms include a deterministic phase that quickly finds a near-optimal expansion plan using derating and a linearized approximation to the time-dependent availability of nondispatchable energy sources. A probabilistic second phase needs comparatively few computer-time consuming probabilistic simulation iterations to modify this solution towards the optimal expansion plan. For the deterministic first phase, two algorithms, based on a Lagrangian Dual decomposition and a Generalized Benders Decomposition, are developed. The probabilistic second phase uses a Generalized Benders Decomposition approach. Extensive computational tests of the algorithms aremore » reported. Among the deterministic algorithms, the one based on Lagrangian Duality proves fastest. The two-phase approach is shown to save up to 80% in computing time as compared to a purely probabilistic algorithm. The algorithms are applied to determine the optimal expansion plan for the Tijuana-Mexicali subsystem of the Mexican electric utility system. A strong recommendation to push conservation programs in the desert city of Mexicali results from this implementation.« less

Real-time maneuver optimization of space-based robots in a dynamic environment: Theory and on-orbit experiments

NASA Astrophysics Data System (ADS)

Chamitoff, Gregory E.; Saenz-Otero, Alvar; Katz, Jacob G.; Ulrich, Steve; Morrell, Benjamin J.; Gibbens, Peter W.

2018-01-01

This paper presents the development of a real-time path-planning optimization approach to controlling the motion of space-based robots. The algorithm is capable of planning three dimensional trajectories for a robot to navigate within complex surroundings that include numerous static and dynamic obstacles, path constraints and performance limitations. The methodology employs a unique transformation that enables rapid generation of feasible solutions for complex geometries, making it suitable for application to real-time operations and dynamic environments. This strategy was implemented on the Synchronized Position Hold Engage Reorient Experimental Satellite (SPHERES) test-bed on the International Space Station (ISS), and experimental testing was conducted onboard the ISS during Expedition 17 by the first author. Lessons learned from the on-orbit tests were used to further refine the algorithm for future implementations.

Multiple objective optimization in reliability demonstration test

DOE PAGES

Lu, Lu; Anderson-Cook, Christine Michaela; Li, Mingyang

2016-10-01

Reliability demonstration tests are usually performed in product design or validation processes to demonstrate whether a product meets specified requirements on reliability. For binomial demonstration tests, the zero-failure test has been most commonly used due to its simplicity and use of minimum sample size to achieve an acceptable consumer’s risk level. However, this test can often result in unacceptably high risk for producers as well as a low probability of passing the test even when the product has good reliability. This paper explicitly explores the interrelationship between multiple objectives that are commonly of interest when planning a demonstration test andmore » proposes structured decision-making procedures using a Pareto front approach for selecting an optimal test plan based on simultaneously balancing multiple criteria. Different strategies are suggested for scenarios with different user priorities and graphical tools are developed to help quantify the trade-offs between choices and to facilitate informed decision making. As a result, potential impacts of some subjective user inputs on the final decision are studied to offer insights and useful guidance for general applications.« less

Optimization and planning of operating theatre activities: an original definition of pathways and process modeling.

PubMed

Barbagallo, Simone; Corradi, Luca; de Ville de Goyet, Jean; Iannucci, Marina; Porro, Ivan; Rosso, Nicola; Tanfani, Elena; Testi, Angela

2015-05-17

The Operating Room (OR) is a key resource of all major hospitals, but it also accounts for up 40% of resource costs. Improving cost effectiveness, while maintaining a quality of care, is a universal objective. These goals imply an optimization of planning and a scheduling of the activities involved. This is highly challenging due to the inherent variable and unpredictable nature of surgery. A Business Process Modeling Notation (BPMN 2.0) was used for the representation of the "OR Process" (being defined as the sequence of all of the elementary steps between "patient ready for surgery" to "patient operated upon") as a general pathway ("path"). The path was then both further standardized as much as possible and, at the same time, keeping all of the key-elements that would allow one to address or define the other steps of planning, and the inherent and wide variability in terms of patient specificity. The path was used to schedule OR activity, room-by-room, and day-by-day, feeding the process from a "waiting list database" and using a mathematical optimization model with the objective of ending up in an optimized planning. The OR process was defined with special attention paid to flows, timing and resource involvement. Standardization involved a dynamics operation and defined an expected operating time for each operation. The optimization model has been implemented and tested on real clinical data. The comparison of the results reported with the real data, shows that by using the optimization model, allows for the scheduling of about 30% more patients than in actual practice, as well as to better exploit the OR efficiency, increasing the average operating room utilization rate up to 20%. The optimization of OR activity planning is essential in order to manage the hospital's waiting list. Optimal planning is facilitated by defining the operation as a standard pathway where all variables are taken into account. By allowing a precise scheduling, it feeds the process of planning and, further up-stream, the management of a waiting list in an interactive and bi-directional dynamic process.

An adequacy-constrained integrated planning method for effective accommodation of DG and electric vehicles in smart distribution systems

NASA Astrophysics Data System (ADS)

Tan, Zhukui; Xie, Baiming; Zhao, Yuanliang; Dou, Jinyue; Yan, Tong; Liu, Bin; Zeng, Ming

2018-06-01

This paper presents a new integrated planning framework for effective accommodating electric vehicles in smart distribution systems (SDS). The proposed method incorporates various investment options available for the utility collectively, including distributed generation (DG), capacitors and network reinforcement. Using a back-propagation algorithm combined with cost-benefit analysis, the optimal network upgrade plan, allocation and sizing of the selected components are determined, with the purpose of minimizing the total system capital and operating costs of DG and EV accommodation. Furthermore, a new iterative reliability test method is proposed. It can check the optimization results by subsequently simulating the reliability level of the planning scheme, and modify the generation reserve margin to guarantee acceptable adequacy levels for each year of the planning horizon. Numerical results based on a 32-bus distribution system verify the effectiveness of the proposed method.

Direct aperture optimization: a turnkey solution for step-and-shoot IMRT.

PubMed

Shepard, D M; Earl, M A; Li, X A; Naqvi, S; Yu, C

2002-06-01

IMRT treatment plans for step-and-shoot delivery have traditionally been produced through the optimization of intensity distributions (or maps) for each beam angle. The optimization step is followed by the application of a leaf-sequencing algorithm that translates each intensity map into a set of deliverable aperture shapes. In this article, we introduce an automated planning system in which we bypass the traditional intensity optimization, and instead directly optimize the shapes and the weights of the apertures. We call this approach "direct aperture optimization." This technique allows the user to specify the maximum number of apertures per beam direction, and hence provides significant control over the complexity of the treatment delivery. This is possible because the machine dependent delivery constraints imposed by the MLC are enforced within the aperture optimization algorithm rather than in a separate leaf-sequencing step. The leaf settings and the aperture intensities are optimized simultaneously using a simulated annealing algorithm. We have tested direct aperture optimization on a variety of patient cases using the EGS4/BEAM Monte Carlo package for our dose calculation engine. The results demonstrate that direct aperture optimization can produce highly conformal step-and-shoot treatment plans using only three to five apertures per beam direction. As compared with traditional optimization strategies, our studies demonstrate that direct aperture optimization can result in a significant reduction in both the number of beam segments and the number of monitor units. Direct aperture optimization therefore produces highly efficient treatment deliveries that maintain the full dosimetric benefits of IMRT.

Inverse-optimized 3D conformal planning: Minimizing complexity while achieving equivalence with beamlet IMRT in multiple clinical sites

PubMed Central

Fraass, Benedick A.; Steers, Jennifer M.; Matuszak, Martha M.; McShan, Daniel L.

2012-01-01

Purpose: Inverse planned intensity modulated radiation therapy (IMRT) has helped many centers implement highly conformal treatment planning with beamlet-based techniques. The many comparisons between IMRT and 3D conformal (3DCRT) plans, however, have been limited because most 3DCRT plans are forward-planned while IMRT plans utilize inverse planning, meaning both optimization and delivery techniques are different. This work avoids that problem by comparing 3D plans generated with a unique inverse planning method for 3DCRT called inverse-optimized 3D (IO-3D) conformal planning. Since IO-3D and the beamlet IMRT to which it is compared use the same optimization techniques, cost functions, and plan evaluation tools, direct comparisons between IMRT and simple, optimized IO-3D plans are possible. Though IO-3D has some similarity to direct aperture optimization (DAO), since it directly optimizes the apertures used, IO-3D is specifically designed for 3DCRT fields (i.e., 1–2 apertures per beam) rather than starting with IMRT-like modulation and then optimizing aperture shapes. The two algorithms are very different in design, implementation, and use. The goals of this work include using IO-3D to evaluate how close simple but optimized IO-3D plans come to nonconstrained beamlet IMRT, showing that optimization, rather than modulation, may be the most important aspect of IMRT (for some sites). Methods: The IO-3D dose calculation and optimization functionality is integrated in the in-house 3D planning/optimization system. New features include random point dose calculation distributions, costlet and cost function capabilities, fast dose volume histogram (DVH) and plan evaluation tools, optimization search strategies designed for IO-3D, and an improved, reimplemented edge/octree calculation algorithm. The IO-3D optimization, in distinction to DAO, is designed to optimize 3D conformal plans (one to two segments per beam) and optimizes MLC segment shapes and weights with various user-controllable search strategies which optimize plans without beamlet or pencil beam approximations. IO-3D allows comparisons of beamlet, multisegment, and conformal plans optimized using the same cost functions, dose points, and plan evaluation metrics, so quantitative comparisons are straightforward. Here, comparisons of IO-3D and beamlet IMRT techniques are presented for breast, brain, liver, and lung plans. Results: IO-3D achieves high quality results comparable to beamlet IMRT, for many situations. Though the IO-3D plans have many fewer degrees of freedom for the optimization, this work finds that IO-3D plans with only one to two segments per beam are dosimetrically equivalent (or nearly so) to the beamlet IMRT plans, for several sites. IO-3D also reduces plan complexity significantly. Here, monitor units per fraction (MU/Fx) for IO-3D plans were 22%–68% less than that for the 1 cm × 1 cm beamlet IMRT plans and 72%–84% than the 0.5 cm × 0.5 cm beamlet IMRT plans. Conclusions: The unique IO-3D algorithm illustrates that inverse planning can achieve high quality 3D conformal plans equivalent (or nearly so) to unconstrained beamlet IMRT plans, for many sites. IO-3D thus provides the potential to optimize flat or few-segment 3DCRT plans, creating less complex optimized plans which are efficient and simple to deliver. The less complex IO-3D plans have operational advantages for scenarios including adaptive replanning, cases with interfraction and intrafraction motion, and pediatric patients. PMID:22755717

The Advantages of Collimator Optimization for Intensity Modulated Radiation Therapy

NASA Astrophysics Data System (ADS)

Doozan, Brian

The goal of this study was to improve dosimetry for pelvic, lung, head and neck, and other cancers sites with aspherical planning target volumes (PTV) using a new algorithm for collimator optimization for intensity modulated radiation therapy (IMRT) that minimizes the x-jaw gap (CAX) and the area of the jaws (CAA) for each treatment field. A retroactive study on the effects of collimator optimization of 20 patients was performed by comparing metric results for new collimator optimization techniques in Eclipse version 11.0. Keeping all other parameters equal, multiple plans are created using four collimator techniques: CA 0, all fields have collimators set to 0°, CAE, using the Eclipse collimator optimization, CAA, minimizing the area of the jaws around the PTV, and CAX, minimizing the x-jaw gap. The minimum area and the minimum x-jaw angles are found by evaluating each field beam's eye view of the PTV with ImageJ and finding the desired parameters with a custom script. The evaluation of the plans included the monitor units (MU), the maximum dose of the plan, the maximum dose to organs at risk (OAR), the conformity index (CI) and the number of fields that are calculated to split. Compared to the CA0 plans, the monitor units decreased on average by 6% for the CAX method with a p-value of 0.01 from an ANOVA test. The average maximum dose remained within 1.1% difference between all four methods with the lowest given by CAX. The maximum dose to the most at risk organ was best spared by the CAA method, which decreased by 0.62% compared to the CA0. Minimizing the x-jaws significantly reduced the number of split fields from 61 to 37. In every metric tested the CAX optimization produced comparable or superior results compared to the other three techniques. For aspherical PTVs, CAX on average reduced the number of split fields, lowered the maximum dose, minimized the dose to the surrounding OAR, and decreased the monitor units. This is achieved while maintaining the same control of the PTV.

Beam orientation optimization for intensity-modulated radiation therapy using mixed integer programming

NASA Astrophysics Data System (ADS)

Yang, Ruijie; Dai, Jianrong; Yang, Yong; Hu, Yimin

2006-08-01

The purpose of this study is to extend an algorithm proposed for beam orientation optimization in classical conformal radiotherapy to intensity-modulated radiation therapy (IMRT) and to evaluate the algorithm's performance in IMRT scenarios. In addition, the effect of the candidate pool of beam orientations, in terms of beam orientation resolution and starting orientation, on the optimized beam configuration, plan quality and optimization time is also explored. The algorithm is based on the technique of mixed integer linear programming in which binary and positive float variables are employed to represent candidates for beam orientation and beamlet weights in beam intensity maps. Both beam orientations and beam intensity maps are simultaneously optimized in the algorithm with a deterministic method. Several different clinical cases were used to test the algorithm and the results show that both target coverage and critical structures sparing were significantly improved for the plans with optimized beam orientations compared to those with equi-spaced beam orientations. The calculation time was less than an hour for the cases with 36 binary variables on a PC with a Pentium IV 2.66 GHz processor. It is also found that decreasing beam orientation resolution to 10° greatly reduced the size of the candidate pool of beam orientations without significant influence on the optimized beam configuration and plan quality, while selecting different starting orientations had large influence. Our study demonstrates that the algorithm can be applied to IMRT scenarios, and better beam orientation configurations can be obtained using this algorithm. Furthermore, the optimization efficiency can be greatly increased through proper selection of beam orientation resolution and starting beam orientation while guaranteeing the optimized beam configurations and plan quality.

Real-time inverse planning for Gamma Knife radiosurgery.

PubMed

Wu, Q Jackie; Chankong, Vira; Jitprapaikulsarn, Suradet; Wessels, Barry W; Einstein, Douglas B; Mathayomchan, Boonyanit; Kinsella, Timothy J

2003-11-01

The challenges of real-time Gamma Knife inverse planning are the large number of variables involved and the unknown search space a priori. With limited collimator sizes, shots have to be heavily overlapped to form a smooth prescription isodose line that conforms to the irregular target shape. Such overlaps greatly influence the total number of shots per plan, making pre-determination of the total number of shots impractical. However, this total number of shots usually defines the search space, a pre-requisite for most of the optimization methods. Since each shot only covers part of the target, a collection of shots in different locations and various collimator sizes selected makes up the global dose distribution that conforms to the target. Hence, planning or placing these shots is a combinatorial optimization process that is computationally expensive by nature. We have previously developed a theory of shot placement and optimization based on skeletonization. The real-time inverse planning process, reported in this paper, is an expansion and the clinical implementation of this theory. The complete planning process consists of two steps. The first step is to determine an optimal number of shots including locations and sizes and to assign initial collimator size to each of the shots. The second step is to fine-tune the weights using a linear-programming technique. The objective function is to minimize the total dose to the target boundary (i.e., maximize the dose conformity). Results of an ellipsoid test target and ten clinical cases are presented. The clinical cases are also compared with physician's manual plans. The target coverage is more than 99% for manual plans and 97% for all the inverse plans. The RTOG PITV conformity indices for the manual plans are between 1.16 and 3.46, compared to 1.36 to 2.4 for the inverse plans. All the inverse plans are generated in less than 2 min, making real-time inverse planning a reality.

SU-E-T-395: Multi-GPU-Based VMAT Treatment Plan Optimization Using a Column-Generation Approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tian, Z; Shi, F; Jia, X

Purpose: GPU has been employed to speed up VMAT optimizations from hours to minutes. However, its limited memory capacity makes it difficult to handle cases with a huge dose-deposition-coefficient (DDC) matrix, e.g. those with a large target size, multiple arcs, small beam angle intervals and/or small beamlet size. We propose multi-GPU-based VMAT optimization to solve this memory issue to make GPU-based VMAT more practical for clinical use. Methods: Our column-generation-based method generates apertures sequentially by iteratively searching for an optimal feasible aperture (referred as pricing problem, PP) and optimizing aperture intensities (referred as master problem, MP). The PP requires accessmore » to the large DDC matrix, which is implemented on a multi-GPU system. Each GPU stores a DDC sub-matrix corresponding to one fraction of beam angles and is only responsible for calculation related to those angles. Broadcast and parallel reduction schemes are adopted for inter-GPU data transfer. MP is a relatively small-scale problem and is implemented on one GPU. One headand- neck cancer case was used for test. Three different strategies for VMAT optimization on single GPU were also implemented for comparison: (S1) truncating DDC matrix to ignore its small value entries for optimization; (S2) transferring DDC matrix part by part to GPU during optimizations whenever needed; (S3) moving DDC matrix related calculation onto CPU. Results: Our multi-GPU-based implementation reaches a good plan within 1 minute. Although S1 was 10 seconds faster than our method, the obtained plan quality is worse. Both S2 and S3 handle the full DDC matrix and hence yield the same plan as in our method. However, the computation time is longer, namely 4 minutes and 30 minutes, respectively. Conclusion: Our multi-GPU-based VMAT optimization can effectively solve the limited memory issue with good plan quality and high efficiency, making GPUbased ultra-fast VMAT planning practical for real clinical use.« less

Impact of Spot Size and Spacing on the Quality of Robustly Optimized Intensity Modulated Proton Therapy Plans for Lung Cancer.

PubMed

Liu, Chenbin; Schild, Steven E; Chang, Joe Y; Liao, Zhongxing; Korte, Shawn; Shen, Jiajian; Ding, Xiaoning; Hu, Yanle; Kang, Yixiu; Keole, Sameer R; Sio, Terence T; Wong, William W; Sahoo, Narayan; Bues, Martin; Liu, Wei

2018-06-01

To investigate how spot size and spacing affect plan quality, robustness, and interplay effects of robustly optimized intensity modulated proton therapy (IMPT) for lung cancer. Two robustly optimized IMPT plans were created for 10 lung cancer patients: first by a large-spot machine with in-air energy-dependent large spot size at isocenter (σ: 6-15 mm) and spacing (1.3 σ), and second by a small-spot machine with in-air energy-dependent small spot size (σ: 2-6 mm) and spacing (5 mm). Both plans were generated by optimizing radiation dose to internal target volume on averaged 4-dimensional computed tomography scans using an in-house-developed IMPT planning system. The dose-volume histograms band method was used to evaluate plan robustness. Dose evaluation software was developed to model time-dependent spot delivery to incorporate interplay effects with randomized starting phases for each field per fraction. Patient anatomy voxels were mapped phase-to-phase via deformable image registration, and doses were scored using in-house-developed software. Dose-volume histogram indices, including internal target volume dose coverage, homogeneity, and organs at risk (OARs) sparing, were compared using the Wilcoxon signed-rank test. Compared with the large-spot machine, the small-spot machine resulted in significantly lower heart and esophagus mean doses, with comparable target dose coverage, homogeneity, and protection of other OARs. Plan robustness was comparable for targets and most OARs. With interplay effects considered, significantly lower heart and esophagus mean doses with comparable target dose coverage and homogeneity were observed using smaller spots. Robust optimization with a small spot-machine significantly improves heart and esophagus sparing, with comparable plan robustness and interplay effects compared with robust optimization with a large-spot machine. A small-spot machine uses a larger number of spots to cover the same tumors compared with a large-spot machine, which gives the planning system more freedom to compensate for the higher sensitivity to uncertainties and interplay effects for lung cancer treatments. Copyright © 2018 Elsevier Inc. All rights reserved.

Evaluation of Big Data Containers for Popular Storage, Retrieval, and Computation Primitives in Earth Science Analysis

NASA Astrophysics Data System (ADS)

Das, K.; Clune, T.; Kuo, K. S.; Mattmann, C. A.; Huang, T.; Duffy, D.; Yang, C. P.; Habermann, T.

2015-12-01

Data containers are infrastructures that facilitate storage, retrieval, and analysis of data sets. Big data applications in Earth Science require a mix of processing techniques, data sources and storage formats that are supported by different data containers. Some of the most popular data containers used in Earth Science studies are Hadoop, Spark, SciDB, AsterixDB, and RasDaMan. These containers optimize different aspects of the data processing pipeline and are, therefore, suitable for different types of applications. These containers are expected to undergo rapid evolution and the ability to re-test, as they evolve, is very important to ensure the containers are up to date and ready to be deployed to handle large volumes of observational data and model output. Our goal is to develop an evaluation plan for these containers to assess their suitability for Earth Science data processing needs. We have identified a selection of test cases that are relevant to most data processing exercises in Earth Science applications and we aim to evaluate these systems for optimal performance against each of these test cases. The use cases identified as part of this study are (i) data fetching, (ii) data preparation for multivariate analysis, (iii) data normalization, (iv) distance (kernel) computation, and (v) optimization. In this study we develop a set of metrics for performance evaluation, define the specifics of governance, and test the plan on current versions of the data containers. The test plan and the design mechanism are expandable to allow repeated testing with both new containers and upgraded versions of the ones mentioned above, so that we can gauge their utility as they evolve.

Active distribution network planning considering linearized system loss

NASA Astrophysics Data System (ADS)

Li, Xiao; Wang, Mingqiang; Xu, Hao

2018-02-01

In this paper, various distribution network planning techniques with DGs are reviewed, and a new distribution network planning method is proposed. It assumes that the location of DGs and the topology of the network are fixed. The proposed model optimizes the capacities of DG and the optimal distribution line capacity simultaneously by a cost/benefit analysis and the benefit is quantified by the reduction of the expected interruption cost. Besides, the network loss is explicitly analyzed in the paper. For simplicity, the network loss is appropriately simplified as a quadratic function of difference of voltage phase angle. Then it is further piecewise linearized. In this paper, a piecewise linearization technique with different segment lengths is proposed. To validate its effectiveness and superiority, the proposed distribution network planning model with elaborate linearization technique is tested on the IEEE 33-bus distribution network system.

Test plan for the soils facility demonstration: A petroleum contaminated soil bioremediation facility

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lombard, K.H.

1994-08-01

The objectives of this test plan are to show the value added by using bioremediation as an effective and environmentally sound method to remediate petroleum contaminated soils (PCS) by: demonstrating bioremediation as a permanent method for remediating soils contaminated with petroleum products; establishing the best operating conditions for maximizing bioremediation and minimizing volatilization for SRS PCS during different seasons; determining the minimum set of analyses and sampling frequency to allow efficient and cost-effective operation; determining best use of existing site equipment and personnel to optimize facility operations and conserve SRS resources; and as an ancillary objective, demonstrating and optimizing newmore » and innovative analytical techniques that will lower cost, decrease time, and decrease secondary waste streams for required PCS assays.« less

Maximizing the potential of direct aperture optimization through collimator rotation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Milette, Marie-Pierre; Otto, Karl; Medical Physics, BC Cancer Agency-Vancouver Centre, Vancouver, British Columbia

Intensity-modulated radiation therapy (IMRT) treatment plans are conventionally produced by the optimization of fluence maps followed by a leaf sequencing step. An alternative to fluence based inverse planning is to optimize directly the leaf positions and field weights of multileaf collimator (MLC) apertures. This approach is typically referred to as direct aperture optimization (DAO). It has been shown that equivalent dose distributions may be generated that have substantially fewer monitor units (MU) and number of apertures compared to fluence based optimization techniques. Here we introduce a DAO technique with rotated apertures that we call rotating aperture optimization (RAO). The advantagesmore » of collimator rotation in IMRT have been shown previously and include higher fluence spatial resolution, increased flexibility in the generation of aperture shapes and less interleaf effects. We have tested our RAO algorithm on a complex C-shaped target, seven nasopharynx cancer recurrences, and one multitarget nasopharynx carcinoma patient. A study was performed in order to assess the capabilities of RAO as compared to fixed collimator angle DAO. The accuracy of fixed and rotated collimator aperture delivery was also verified. An analysis of the optimized treatment plans indicates that plans generated with RAO are as good as or better than DAO while maintaining a smaller number of apertures and MU than fluence based IMRT. Delivery verification results show that RAO is less sensitive to tongue and groove effects than DAO. Delivery time is currently increased due to the collimator rotation speed although this is a mechanical limitation that can be eliminated in the future.« less

Fast approximate delivery of fluence maps for IMRT and VMAT

NASA Astrophysics Data System (ADS)

Balvert, Marleen; Craft, David

2017-02-01

In this article we provide a method to generate the trade-off between delivery time and fluence map matching quality for dynamically delivered fluence maps. At the heart of our method lies a mathematical programming model that, for a given duration of delivery, optimizes leaf trajectories and dose rates such that the desired fluence map is reproduced as well as possible. We begin with the single fluence map case and then generalize the model and the solution technique to the delivery of sequential fluence maps. The resulting large-scale, non-convex optimization problem was solved using a heuristic approach. We test our method using a prostate case and a head and neck case, and present the resulting trade-off curves. Analysis of the leaf trajectories reveals that short time plans have larger leaf openings in general than longer delivery time plans. Our method allows one to explore the continuum of possibilities between coarse, large segment plans characteristic of direct aperture approaches and narrow field plans produced by sliding window approaches. Exposing this trade-off will allow for an informed choice between plan quality and solution time. Further research is required to speed up the optimization process to make this method clinically implementable.

Convergent evolution of vascular optimization in kelp (Laminariales).

PubMed

Drobnitch, Sarah Tepler; Jensen, Kaare H; Prentice, Paige; Pittermann, Jarmila

2015-10-07

Terrestrial plants and mammals, although separated by a great evolutionary distance, have each arrived at a highly conserved body plan in which universal allometric scaling relationships govern the anatomy of vascular networks and key functional metabolic traits. The universality of allometric scaling suggests that these phyla have each evolved an 'optimal' transport strategy that has been overwhelmingly adopted by extant species. To truly evaluate the dominance and universality of vascular optimization, however, it is critical to examine other, lesser-known, vascularized phyla. The brown algae (Phaeophyceae) are one such group--as distantly related to plants as mammals, they have convergently evolved a plant-like body plan and a specialized phloem-like transport network. To evaluate possible scaling and optimization in the kelp vascular system, we developed a model of optimized transport anatomy and tested it with measurements of the giant kelp, Macrocystis pyrifera, which is among the largest and most successful of macroalgae. We also evaluated three classical allometric relationships pertaining to plant vascular tissues with a diverse sampling of kelp species. Macrocystis pyrifera displays strong scaling relationships between all tested vascular parameters and agrees with our model; other species within the Laminariales display weak or inconsistent vascular allometries. The lack of universal scaling in the kelps and the presence of optimized transport anatomy in M. pyrifera raises important questions about the evolution of optimization and the possible competitive advantage conferred by optimized vascular systems to multicellular phyla. © 2015 The Author(s).

Phase averaging method for the modeling of the multiprobe and cutaneous cryosurgery

NASA Astrophysics Data System (ADS)

E Shilnikov, K.; Kudryashov, N. A.; Y Gaiur, I.

2017-12-01

In this paper we consider the problem of planning and optimization of the cutaneous and multiprobe cryosurgery operations. An explicit scheme based on the finite volume approximation of phase averaged Pennes bioheat transfer model is applied. The flux relaxation method is used for the stability improvement of scheme. Skin tissue is considered as strongly inhomogeneous media. Computerized planning tool is tested on model cryotip-based and cutaneous cryosurgery problems. For the case of cutaneous cryosurgery the method of an additional freezing element mounting is studied as an approach to optimize the cellular necrosis front propagation.

Ultrafast treatment plan optimization for volumetric modulated arc therapy (VMAT)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Men Chunhua; Romeijn, H. Edwin; Jia Xun

2010-11-15

Purpose: To develop a novel aperture-based algorithm for volumetric modulated arc therapy (VMAT) treatment plan optimization with high quality and high efficiency. Methods: The VMAT optimization problem is formulated as a large-scale convex programming problem solved by a column generation approach. The authors consider a cost function consisting two terms, the first enforcing a desired dose distribution and the second guaranteeing a smooth dose rate variation between successive gantry angles. A gantry rotation is discretized into 180 beam angles and for each beam angle, only one MLC aperture is allowed. The apertures are generated one by one in a sequentialmore » way. At each iteration of the column generation method, a deliverable MLC aperture is generated for one of the unoccupied beam angles by solving a subproblem with the consideration of MLC mechanic constraints. A subsequent master problem is then solved to determine the dose rate at all currently generated apertures by minimizing the cost function. When all 180 beam angles are occupied, the optimization completes, yielding a set of deliverable apertures and associated dose rates that produce a high quality plan. Results: The algorithm was preliminarily tested on five prostate and five head-and-neck clinical cases, each with one full gantry rotation without any couch/collimator rotations. High quality VMAT plans have been generated for all ten cases with extremely high efficiency. It takes only 5-8 min on CPU (MATLAB code on an Intel Xeon 2.27 GHz CPU) and 18-31 s on GPU (CUDA code on an NVIDIA Tesla C1060 GPU card) to generate such plans. Conclusions: The authors have developed an aperture-based VMAT optimization algorithm which can generate clinically deliverable high quality treatment plans at very high efficiency.« less

Ultrafast treatment plan optimization for volumetric modulated arc therapy (VMAT).

PubMed

Men, Chunhua; Romeijn, H Edwin; Jia, Xun; Jiang, Steve B

2010-11-01

To develop a novel aperture-based algorithm for volumetric modulated are therapy (VMAT) treatment plan optimization with high quality and high efficiency. The VMAT optimization problem is formulated as a large-scale convex programming problem solved by a column generation approach. The authors consider a cost function consisting two terms, the first enforcing a desired dose distribution and the second guaranteeing a smooth dose rate variation between successive gantry angles. A gantry rotation is discretized into 180 beam angles and for each beam angle, only one MLC aperture is allowed. The apertures are generated one by one in a sequential way. At each iteration of the column generation method, a deliverable MLC aperture is generated for one of the unoccupied beam angles by solving a subproblem with the consideration of MLC mechanic constraints. A subsequent master problem is then solved to determine the dose rate at all currently generated apertures by minimizing the cost function. When all 180 beam angles are occupied, the optimization completes, yielding a set of deliverable apertures and associated dose rates that produce a high quality plan. The algorithm was preliminarily tested on five prostate and five head-and-neck clinical cases, each with one full gantry rotation without any couch/collimator rotations. High quality VMAT plans have been generated for all ten cases with extremely high efficiency. It takes only 5-8 min on CPU (MATLAB code on an Intel Xeon 2.27 GHz CPU) and 18-31 s on GPU (CUDA code on an NVIDIA Tesla C1060 GPU card) to generate such plans. The authors have developed an aperture-based VMAT optimization algorithm which can generate clinically deliverable high quality treatment plans at very high efficiency.

A method to incorporate leakage and head scatter corrections into a tomotherapy inverse treatment planning algorithm

NASA Astrophysics Data System (ADS)

Holmes, Timothy W.

2001-01-01

A detailed tomotherapy inverse treatment planning method is described which incorporates leakage and head scatter corrections during each iteration of the optimization process, allowing these effects to be directly accounted for in the optimized dose distribution. It is shown that the conventional inverse planning method for optimizing incident intensity can be extended to include a `concurrent' leaf sequencing operation from which the leakage and head scatter corrections are determined. The method is demonstrated using the steepest-descent optimization technique with constant step size and a least-squared error objective. The method was implemented using the MATLAB scientific programming environment and its feasibility demonstrated for 2D test cases simulating treatment delivery using a single coplanar rotation. The results indicate that this modification does not significantly affect convergence of the intensity optimization method when exposure times of individual leaves are stratified to a large number of levels (>100) during leaf sequencing. In general, the addition of aperture dependent corrections, especially `head scatter', reduces incident fluence in local regions of the modulated fan beam, resulting in increased exposure times for individual collimator leaves. These local variations can result in 5% or greater local variation in the optimized dose distribution compared to the uncorrected case. The overall efficiency of the modified intensity optimization algorithm is comparable to that of the original unmodified case.

SU-E-T-197: Helical Cranial-Spinal Treatments with a Linear Accelerator

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anderson, J; Bernard, D; Liao, Y

2014-06-01

Purpose: Craniospinal irradiation (CSI) of systemic disease requires a high level of beam intensity modulation to reduce dose to bone marrow and other critical structures. Current helical delivery machines can take 30 minutes or more of beam-on time to complete these treatments. This pilot study aims to test the feasibility of performing helical treatments with a conventional linear accelerator using longitudinal couch travel during multiple gantry revolutions. Methods: The VMAT optimization package of the Eclipse 10.0 treatment planning system was used to optimize pseudo-helical CSI plans of 5 clinical patient scans. Each gantry revolution was divided into three 120° arcsmore » with each isocenter shifted longitudinally. Treatments requiring more than the maximum 10 arcs used multiple plans with each plan after the first being optimized including the dose of the others (Figure 1). The beam pitch was varied between 0.2 and 0.9 (couch speed 5- 20cm/revolution and field width of 22cm) and dose-volume histograms of critical organs were compared to tomotherapy plans. Results: Viable pseudo-helical plans were achieved using Eclipse. Decreasing the pitch from 0.9 to 0.2 lowered the maximum lens dose by 40%, the mean bone marrow dose by 2.1% and the maximum esophagus dose by 17.5%. (Figure 2). Linac-based helical plans showed dose results comparable to tomotherapy delivery for both target coverage and critical organ sparing, with the D50 of bone marrow and esophagus respectively 12% and 31% lower in the helical linear accelerator plan (Figure 3). Total mean beam-on time for the linear accelerator plan was 8.3 minutes, 54% faster than the tomotherapy average for the same plans. Conclusions: This pilot study has demonstrated the feasibility of planning pseudo-helical treatments for CSI targets using a conventional linac and dynamic couch movement, and supports the ongoing development of true helical optimization and delivery.« less

Robust plan optimization for electromagnetic transponder guided hypo-fractionated prostate treatment using volumetric modulated arc therapy

NASA Astrophysics Data System (ADS)

Zhang, Pengpeng; Hunt, Margie; Happersett, Laura; Yang, Jie; Zelefsky, Michael; Mageras, Gig

2013-11-01

To develop an optimization algorithm for volumetric modulated arc therapy which incorporates an electromagnetic tracking (EMT) guided gating strategy and is robust to residual intra-fractional motion uncertainties. In a computer simulation, intra-fractional motion traces from prior treatments with EMT were converted to a probability distribution function (PDF), truncated using a patient specific action volume that encloses allowed deviations from the planned position, and renormalized to yield a new PDF with EMT-gated interventions. In lieu of a conventional planning target volume (PTV), multiple instances of clinical target volume (CTV) and organs at risk (OARs) were replicated and displaced to extreme positions inside the action volume representing possible delivery scenarios. When optimizing the volumetric modulated arc therapy plan, doses to the CTV and OARs were calculated as a sum of doses to the replicas weighted by the PDF to account for motion. A treatment plan meeting the clinical constraints was produced and compared to the counterpart conventional margin (PTV) plan. EMT traces from a separate testing database served to simulate motion during gated delivery. Dosimetric end points extracted from dose accumulations for each motion trace were utilized to evaluate potential clinical benefit. Five prostate cases from a hypofractionated protocol (42.5 Gy in 5 fractions) were retrospectively investigated. The patient specific gating window resulted in tight anterior and inferior action levels (∼1 mm) to protect rectal wall and bladder wall, and resulted in an average of four beam interruptions per fraction in the simulation. The robust-optimized plans achieved the same average CTV D95 coverage of 40.5 Gy as the PTV-optimized plans, but with reduced patient-averaged rectum wall D1cc by 2.2 Gy (range 0.7 to 4.7 Gy) and bladder wall mean dose by 2.9 Gy (range 2.0 to 3.4 Gy). Integration of an intra-fractional motion management strategy into the robust optimization process is feasible and may yield improved OAR sparing compared to the standard margin approach.

Robust plan optimization for electromagnetic transponder guided hypo-fractionated prostate treatment using volumetric modulated arc therapy.

PubMed

Zhang, Pengpeng; Hunt, Margie; Happersett, Laura; Yang, Jie; Zelefsky, Michael; Mageras, Gig

2013-11-07

To develop an optimization algorithm for volumetric modulated arc therapy which incorporates an electromagnetic tracking (EMT) guided gating strategy and is robust to residual intra-fractional motion uncertainties. In a computer simulation, intra-fractional motion traces from prior treatments with EMT were converted to a probability distribution function (PDF), truncated using a patient specific action volume that encloses allowed deviations from the planned position, and renormalized to yield a new PDF with EMT-gated interventions. In lieu of a conventional planning target volume (PTV), multiple instances of clinical target volume (CTV) and organs at risk (OARs) were replicated and displaced to extreme positions inside the action volume representing possible delivery scenarios. When optimizing the volumetric modulated arc therapy plan, doses to the CTV and OARs were calculated as a sum of doses to the replicas weighted by the PDF to account for motion. A treatment plan meeting the clinical constraints was produced and compared to the counterpart conventional margin (PTV) plan. EMT traces from a separate testing database served to simulate motion during gated delivery. Dosimetric end points extracted from dose accumulations for each motion trace were utilized to evaluate potential clinical benefit. Five prostate cases from a hypofractionated protocol (42.5 Gy in 5 fractions) were retrospectively investigated. The patient specific gating window resulted in tight anterior and inferior action levels (~1 mm) to protect rectal wall and bladder wall, and resulted in an average of four beam interruptions per fraction in the simulation. The robust-optimized plans achieved the same average CTV D95 coverage of 40.5 Gy as the PTV-optimized plans, but with reduced patient-averaged rectum wall D1cc by 2.2 Gy (range 0.7 to 4.7 Gy) and bladder wall mean dose by 2.9 Gy (range 2.0 to 3.4 Gy). Integration of an intra-fractional motion management strategy into the robust optimization process is feasible and may yield improved OAR sparing compared to the standard margin approach.

Optimizing global liver function in radiation therapy treatment planning

NASA Astrophysics Data System (ADS)

Wu, Victor W.; Epelman, Marina A.; Wang, Hesheng; Romeijn, H. Edwin; Feng, Mary; Cao, Yue; Ten Haken, Randall K.; Matuszak, Martha M.

2016-09-01

Liver stereotactic body radiation therapy (SBRT) patients differ in both pre-treatment liver function (e.g. due to degree of cirrhosis and/or prior treatment) and radiosensitivity, leading to high variability in potential liver toxicity with similar doses. This work investigates three treatment planning optimization models that minimize risk of toxicity: two consider both voxel-based pre-treatment liver function and local-function-based radiosensitivity with dose; one considers only dose. Each model optimizes different objective functions (varying in complexity of capturing the influence of dose on liver function) subject to the same dose constraints and are tested on 2D synthesized and 3D clinical cases. The normal-liver-based objective functions are the linearized equivalent uniform dose (\\ell \\text{EUD} ) (conventional ‘\\ell \\text{EUD} model’), the so-called perfusion-weighted \\ell \\text{EUD} (\\text{fEUD} ) (proposed ‘fEUD model’), and post-treatment global liver function (GLF) (proposed ‘GLF model’), predicted by a new liver-perfusion-based dose-response model. The resulting \\ell \\text{EUD} , fEUD, and GLF plans delivering the same target \\ell \\text{EUD} are compared with respect to their post-treatment function and various dose-based metrics. Voxel-based portal venous liver perfusion, used as a measure of local function, is computed using DCE-MRI. In cases used in our experiments, the GLF plan preserves up to 4.6 % ≤ft(7.5 % \\right) more liver function than the fEUD (\\ell \\text{EUD} ) plan does in 2D cases, and up to 4.5 % ≤ft(5.6 % \\right) in 3D cases. The GLF and fEUD plans worsen in \\ell \\text{EUD} of functional liver on average by 1.0 Gy and 0.5 Gy in 2D and 3D cases, respectively. Liver perfusion information can be used during treatment planning to minimize the risk of toxicity by improving expected GLF; the degree of benefit varies with perfusion pattern. Although fEUD model optimization is computationally inexpensive and often achieves better GLF than \\ell \\text{EUD} model optimization does, the GLF model directly optimizes a more clinically relevant metric and can further improve fEUD plan quality.

TRACON Aircraft Arrival Planning and Optimization Through Spatial Constraint Satisfaction

NASA Technical Reports Server (NTRS)

Bergh, Christopher P.; Krzeczowski, Kenneth J.; Davis, Thomas J.; Denery, Dallas G. (Technical Monitor)

1995-01-01

A new aircraft arrival planning and optimization algorithm has been incorporated into the Final Approach Spacing Tool (FAST) in the Center-TRACON Automation System (CTAS) developed at NASA-Ames Research Center. FAST simulations have been conducted over three years involving full-proficiency, level five air traffic controllers from around the United States. From these simulations an algorithm, called Spatial Constraint Satisfaction, has been designed, coded, undergone testing, and soon will begin field evaluation at the Dallas-Fort Worth and Denver International airport facilities. The purpose of this new design is an attempt to show that the generation of efficient and conflict free aircraft arrival plans at the runway does not guarantee an operationally acceptable arrival plan upstream from the runway -information encompassing the entire arrival airspace must be used in order to create an acceptable aircraft arrival plan. This new design includes functions available previously but additionally includes necessary representations of controller preferences and workload, operationally required amounts of extra separation, and integrates aircraft conflict resolution. As a result, the Spatial Constraint Satisfaction algorithm produces an optimized aircraft arrival plan that is more acceptable in terms of arrival procedures and air traffic controller workload. This paper discusses the current Air Traffic Control arrival planning procedures, previous work in this field, the design of the Spatial Constraint Satisfaction algorithm, and the results of recent evaluations of the algorithm.

Patient-specific dosimetric endpoints based treatment plan quality control in radiotherapy.

PubMed

Song, Ting; Staub, David; Chen, Mingli; Lu, Weiguo; Tian, Zhen; Jia, Xun; Li, Yongbao; Zhou, Linghong; Jiang, Steve B; Gu, Xuejun

2015-11-07

In intensity modulated radiotherapy (IMRT), the optimal plan for each patient is specific due to unique patient anatomy. To achieve such a plan, patient-specific dosimetric goals reflecting each patient's unique anatomy should be defined and adopted in the treatment planning procedure for plan quality control. This study is to develop such a personalized treatment plan quality control tool by predicting patient-specific dosimetric endpoints (DEs). The incorporation of patient specific DEs is realized by a multi-OAR geometry-dosimetry model, capable of predicting optimal DEs based on the individual patient's geometry. The overall quality of a treatment plan is then judged with a numerical treatment plan quality indicator and characterized as optimal or suboptimal. Taking advantage of clinically available prostate volumetric modulated arc therapy (VMAT) treatment plans, we built and evaluated our proposed plan quality control tool. Using our developed tool, six of twenty evaluated plans were identified as sub-optimal plans. After plan re-optimization, these suboptimal plans achieved better OAR dose sparing without sacrificing the PTV coverage, and the dosimetric endpoints of the re-optimized plans agreed well with the model predicted values, which validate the predictability of the proposed tool. In conclusion, the developed tool is able to accurately predict optimally achievable DEs of multiple OARs, identify suboptimal plans, and guide plan optimization. It is a useful tool for achieving patient-specific treatment plan quality control.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, R; Liu, A; Poenisch, F

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 33more » 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.« less

SU-E-T-182: Feasibility of Dose Painting by Numbers in Proton Therapy with Contour-Driven Plan Optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Montero, A Barragan; Differding, S; Lee, J

Purpose: The work aims to 1) prove the feasibility of dose painting by numbers (DPBN) in proton therapy with usual contour-driven plan optimization and 2) compare the achieved plan quality to that of rotational IMRT. Methods: For two patients with head and neck cancers, voxel-by-voxel prescription to the target volume (PTV-PET) was calculated from {sup 18} FDG-PET images and converted to contour-based prescription by defining several sub-contours. Treatments were planned with RayStation (RaySearch Laboratories, Sweden) and proton pencil beam scanning modality. In order to determine the optimal plan parameters to approach the DPBN prescription, the effect of the number ofmore » fields, number of sub-contours and use of range shifter were tested separately on each patient. The number of sub-contours were increased from 3 to 11 while the number of fields were set to 3, 5, 7 and 9. Treatment plans were also optimized on two rotational IMRT systems (TomoTherapy and Varian RapidArc) using previously published guidelines. Results: For both patients, more than 99% of the PTV-PET received at least 95% of the prescribed dose while less than 1% of the PTV-PET received more than 105%, which demonstrates the feasibility of the treatment. Neither the use of a range shifter nor the increase of the number of fields had a significant influence on PTV coverage. Plan quality increased when increasing number of fields up to 7 or 9 and slightly decreased for a bigger number of sub-contours. Good OAR sparing is achieved while keeping high plan quality. Finally, proton therapy achieved significantly better plan quality than rotational IMRT. Conclusion: Voxel-by-voxel prescriptions can be approximated accurately in proton therapy using a contour-driven optimization. Target coverage is nearly insensitive to the number of fields and the use of a range shifter. Finally, plan quality assessment confirmed the superiority of proton therapy compared to rotational IMRT.« less

A novel adaptive Cuckoo search for optimal query plan generation.

PubMed

Gomathi, Ramalingam; Sharmila, Dhandapani

2014-01-01

The emergence of multiple web pages day by day leads to the development of the semantic web technology. A World Wide Web Consortium (W3C) standard for storing semantic web data is the resource description framework (RDF). To enhance the efficiency in the execution time for querying large RDF graphs, the evolving metaheuristic algorithms become an alternate to the traditional query optimization methods. This paper focuses on the problem of query optimization of semantic web data. An efficient algorithm called adaptive Cuckoo search (ACS) for querying and generating optimal query plan for large RDF graphs is designed in this research. Experiments were conducted on different datasets with varying number of predicates. The experimental results have exposed that the proposed approach has provided significant results in terms of query execution time. The extent to which the algorithm is efficient is tested and the results are documented.

Pre-implementation studies of a workforce planning tool for nurse staffing and human resource management in university hospitals.

PubMed

van Oostveen, Catharina J; Ubbink, Dirk T; Mens, Marian A; Pompe, Edwin A; Vermeulen, Hester

2016-03-01

To investigate the reliability, validity and feasibility of the RAFAELA workforce planning system (including the Oulu patient classification system - OPCq), before deciding on implementation in Dutch hospitals. The complexity of care, budgetary restraints and demand for high-quality patient care have ignited the need for transparent hospital workforce planning. Nurses from 12 wards of two university hospitals were trained to test the reliability of the OPCq by investigating the absolute agreement of nursing care intensity (NCI) measurements among nurses. Validity was tested by assessing whether optimal NCI/nurse ratio, as calculated by a regression analysis in RAFAELA, was realistic. System feasibility was investigated through a questionnaire among all nurses involved. Almost 67 000 NCI measurements were performed between December 2013 and June 2014. Agreement using the OPCq varied between 38% and 91%. For only 1 in 12 wards was the optimal NCI area calculated judged as valid. Although the majority of respondents was positive about the applicability and user-friendliness, RAFAELA was not accepted as useful workforce planning system. Nurses' performance using the RAFAELA system did not warrant its implementation. Hospital managers should first focus on enlarging the readiness of nurses regarding the implementation of a workforce planning system. © 2015 John Wiley & Sons Ltd.

Formulation of a parametric systems design framework for disaster response planning

NASA Astrophysics Data System (ADS)

Mma, Stephanie Weiya

The occurrence of devastating natural disasters in the past several years have prompted communities, responding organizations, and governments to seek ways to improve disaster preparedness capabilities locally, regionally, nationally, and internationally. A holistic approach to design used in the aerospace and industrial engineering fields enables efficient allocation of resources through applied parametric changes within a particular design to improve performance metrics to selected standards. In this research, this methodology is applied to disaster preparedness, using a community's time to restoration after a disaster as the response metric. A review of the responses from Hurricane Katrina and the 2010 Haiti earthquake, among other prominent disasters, provides observations leading to some current capability benchmarking. A need for holistic assessment and planning exists for communities but the current response planning infrastructure lacks a standardized framework and standardized assessment metrics. Within the humanitarian logistics community, several different metrics exist, enabling quantification and measurement of a particular area's vulnerability. These metrics, combined with design and planning methodologies from related fields, such as engineering product design, military response planning, and business process redesign, provide insight and a framework from which to begin developing a methodology to enable holistic disaster response planning. The developed methodology was applied to the communities of Shelby County, TN and pre-Hurricane-Katrina Orleans Parish, LA. Available literature and reliable media sources provide information about the different values of system parameters within the decomposition of the community aspects and also about relationships among the parameters. The community was modeled as a system dynamics model and was tested in the implementation of two, five, and ten year improvement plans for Preparedness, Response, and Development capabilities, and combinations of these capabilities. For Shelby County and for Orleans Parish, the Response improvement plan reduced restoration time the most. For the combined capabilities, Shelby County experienced the greatest reduction in restoration time with the implementation of Development and Response capability improvements, and for Orleans Parish it was the Preparedness and Response capability improvements. Optimization of restoration time with community parameters was tested by using a Particle Swarm Optimization algorithm. Fifty different optimized restoration times were generated using the Particle Swarm Optimization algorithm and ranked using the Technique for Order Preference by Similarity to Ideal Solution. The optimization results indicate that the greatest reduction in restoration time for a community is achieved with a particular combination of different parameter values instead of the maximization of each parameter.

Motor planning flexibly optimizes performance under uncertainty about task goals.

PubMed

Wong, Aaron L; Haith, Adrian M

2017-03-03

In an environment full of potential goals, how does the brain determine which movement to execute? Existing theories posit that the motor system prepares for all potential goals by generating several motor plans in parallel. One major line of evidence for such theories is that presenting two competing goals often results in a movement intermediate between them. These intermediate movements are thought to reflect an unintentional averaging of the competing plans. However, normative theories suggest instead that intermediate movements might actually be deliberate, generated because they improve task performance over a random guessing strategy. To test this hypothesis, we vary the benefit of making an intermediate movement by changing movement speed. We find that participants generate intermediate movements only at (slower) speeds where they measurably improve performance. Our findings support the normative view that the motor system selects only a single, flexible motor plan, optimized for uncertain goals.

Incorporating deliverable monitor unit constraints into spot intensity optimization in intensity modulated proton therapy treatment planning

PubMed Central

Cao, Wenhua; Lim, Gino; Li, Xiaoqiang; Li, Yupeng; Zhu, X. Ronald; Zhang, Xiaodong

2014-01-01

The purpose of this study is to investigate the feasibility and impact of incorporating deliverable monitor unit (MU) constraints into spot intensity optimization in intensity modulated proton therapy (IMPT) treatment planning. The current treatment planning system (TPS) for IMPT disregards deliverable MU constraints in the spot intensity optimization (SIO) routine. It performs a post-processing procedure on an optimized plan to enforce deliverable MU values that are required by the spot scanning proton delivery system. This procedure can create a significant dose distribution deviation between the optimized and post-processed deliverable plans, especially when small spot spacings are used. In this study, we introduce a two-stage linear programming (LP) approach to optimize spot intensities and constrain deliverable MU values simultaneously, i.e., a deliverable spot intensity optimization (DSIO) model. Thus, the post-processing procedure is eliminated and the associated optimized plan deterioration can be avoided. Four prostate cancer cases at our institution were selected for study and two parallel opposed beam angles were planned for all cases. A quadratic programming (QP) based model without MU constraints, i.e., a conventional spot intensity optimization (CSIO) model, was also implemented to emulate the commercial TPS. Plans optimized by both the DSIO and CSIO models were evaluated for five different settings of spot spacing from 3 mm to 7 mm. For all spot spacings, the DSIO-optimized plans yielded better uniformity for the target dose coverage and critical structure sparing than did the CSIO-optimized plans. With reduced spot spacings, more significant improvements in target dose uniformity and critical structure sparing were observed in the DSIO- than in the CSIO-optimized plans. Additionally, better sparing of the rectum and bladder was achieved when reduced spacings were used for the DSIO-optimized plans. The proposed DSIO approach ensures the deliverability of optimized IMPT plans that take into account MU constraints. This eliminates the post-processing procedure required by the TPS as well as the resultant deteriorating effect on ultimate dose distributions. This approach therefore allows IMPT plans to adopt all possible spot spacings optimally. Moreover, dosimetric benefits can be achieved using smaller spot spacings. PMID:23835656

Behavioural and psychophysiological correlates of athletic performance: a test of the multi-action plan model.

PubMed

Bertollo, Maurizio; Bortoli, Laura; Gramaccioni, Gianfranco; Hanin, Yuri; Comani, Silvia; Robazza, Claudio

2013-06-01

The main purposes of the present study were to substantiate the existence of the four types of performance categories (i.e., optimal-automatic, optimal-controlled, suboptimal-controlled, and suboptimal-automatic) as hypothesised in the multi-action plan (MAP) model, and to investigate whether some specific affective, behavioural, psychophysiological, and postural trends may typify each type of performance. A 20-year-old athlete of the Italian shooting team, and a 46-year-old athlete of the Italian dart-throwing team participated in the study. Athletes were asked to identify the core components of the action and then to execute a large number of shots/flights. A 2 × 2 (optimal/suboptimal × automated/controlled) within subjects multivariate analysis of variance was performed to test the differences among the four types of performance. Findings provided preliminary evidence of psychophysiological and postural differences among four performance categories as conceptualized within the MAP model. Monitoring the entire spectrum of psychophysiological and behavioural features related to the different types of performance is important to develop and implement biofeedback and neurofeedback techniques aimed at helping athletes to identify individual zones of optimal functioning and to enhance their performance.

A non-voxel-based broad-beam (NVBB) framework for IMRT treatment planning.

PubMed

Lu, Weiguo

2010-12-07

We present a novel framework that enables very large scale intensity-modulated radiation therapy (IMRT) planning in limited computation resources with improvements in cost, plan quality and planning throughput. Current IMRT optimization uses a voxel-based beamlet superposition (VBS) framework that requires pre-calculation and storage of a large amount of beamlet data, resulting in large temporal and spatial complexity. We developed a non-voxel-based broad-beam (NVBB) framework for IMRT capable of direct treatment parameter optimization (DTPO). In this framework, both objective function and derivative are evaluated based on the continuous viewpoint, abandoning 'voxel' and 'beamlet' representations. Thus pre-calculation and storage of beamlets are no longer needed. The NVBB framework has linear complexities (O(N(3))) in both space and time. The low memory, full computation and data parallelization nature of the framework render its efficient implementation on the graphic processing unit (GPU). We implemented the NVBB framework and incorporated it with the TomoTherapy treatment planning system (TPS). The new TPS runs on a single workstation with one GPU card (NVBB-GPU). Extensive verification/validation tests were performed in house and via third parties. Benchmarks on dose accuracy, plan quality and throughput were compared with the commercial TomoTherapy TPS that is based on the VBS framework and uses a computer cluster with 14 nodes (VBS-cluster). For all tests, the dose accuracy of these two TPSs is comparable (within 1%). Plan qualities were comparable with no clinically significant difference for most cases except that superior target uniformity was seen in the NVBB-GPU for some cases. However, the planning time using the NVBB-GPU was reduced many folds over the VBS-cluster. In conclusion, we developed a novel NVBB framework for IMRT optimization. The continuous viewpoint and DTPO nature of the algorithm eliminate the need for beamlets and lead to better plan quality. The computation parallelization on a GPU instead of a computer cluster significantly reduces hardware and service costs. Compared with using the current VBS framework on a computer cluster, the planning time is significantly reduced using the NVBB framework on a single workstation with a GPU card.

A Study on Linear Programming Applications for the Optimization of School Lunch Menus. Summation Report.

ERIC Educational Resources Information Center

Findorff, Irene K.

This document summarizes the results of a project at Tulane University that was designed to adapt, test, and evaluate a computerized information and menu planning system utilizing linear programing techniques for use in school lunch food service operations. The objectives of the menu planning were to formulate menu items into a palatable,…

Interval linear programming model for long-term planning of vehicle recycling in the Republic of Serbia under uncertainty.

PubMed

Simic, Vladimir; Dimitrijevic, Branka

2015-02-01

An interval linear programming approach is used to formulate and comprehensively test a model for optimal long-term planning of vehicle recycling in the Republic of Serbia. The proposed model is applied to a numerical case study: a 4-year planning horizon (2013-2016) is considered, three legislative cases and three scrap metal price trends are analysed, availability of final destinations for sorted waste flows is explored. Potential and applicability of the developed model are fully illustrated. Detailed insights on profitability and eco-efficiency of the projected contemporary equipped vehicle recycling factory are presented. The influences of the ordinance on the management of end-of-life vehicles in the Republic of Serbia on the vehicle hulks procuring, sorting generated material fractions, sorted waste allocation and sorted metals allocation decisions are thoroughly examined. The validity of the waste management strategy for the period 2010-2019 is tested. The formulated model can create optimal plans for procuring vehicle hulks, sorting generated material fractions, allocating sorted waste flows and allocating sorted metals. Obtained results are valuable for supporting the construction and/or modernisation process of a vehicle recycling system in the Republic of Serbia. © The Author(s) 2015.

A mathematical tool to generate complex whole body motor tasks and test hypotheses on underlying motor planning.

PubMed

Tagliabue, Michele; Pedrocchi, Alessandra; Pozzo, Thierry; Ferrigno, Giancarlo

2008-01-01

In spite of the complexity of human motor behavior, difficulties in mathematical modeling have restricted to rather simple movements attempts to identify the motor planning criterion used by the central nervous system. This paper presents a novel-simulation technique able to predict the "desired trajectory" corresponding to a wide range of kinematic and kinetic optimality criteria for tasks involving many degrees of freedom and the coordination between goal achievement and balance maintenance. Employment of proper time discretization, inverse dynamic methods and constrained optimization technique are combined. The application of this simulator to a planar whole body pointing movement shows its effectiveness in managing system nonlinearities and instability as well as in ensuring the anatomo-physiological feasibility of predicted motor plans. In addition, the simulator's capability to simultaneously optimize competing movement aspects represents an interesting opportunity for the motor control community, in which the coexistence of several controlled variables has been hypothesized.

Learning stochastic reward distributions in a speeded pointing task.

PubMed

Seydell, Anna; McCann, Brian C; Trommershäuser, Julia; Knill, David C

2008-04-23

Recent studies have shown that humans effectively take into account task variance caused by intrinsic motor noise when planning fast hand movements. However, previous evidence suggests that humans have greater difficulty accounting for arbitrary forms of stochasticity in their environment, both in economic decision making and sensorimotor tasks. We hypothesized that humans can learn to optimize movement strategies when environmental randomness can be experienced and thus implicitly learned over several trials, especially if it mimics the kinds of randomness for which subjects might have generative models. We tested the hypothesis using a task in which subjects had to rapidly point at a target region partly covered by three stochastic penalty regions introduced as "defenders." At movement completion, each defender jumped to a new position drawn randomly from fixed probability distributions. Subjects earned points when they hit the target, unblocked by a defender, and lost points otherwise. Results indicate that after approximately 600 trials, subjects approached optimal behavior. We further tested whether subjects simply learned a set of stimulus-contingent motor plans or the statistics of defenders' movements by training subjects with one penalty distribution and then testing them on a new penalty distribution. Subjects immediately changed their strategy to achieve the same average reward as subjects who had trained with the second penalty distribution. These results indicate that subjects learned the parameters of the defenders' jump distributions and used this knowledge to optimally plan their hand movements under conditions involving stochastic rewards and penalties.

Planning intensive care unit design using computer simulation modeling: optimizing integration of clinical, operational, and architectural requirements.

PubMed

OʼHara, Susan

2014-01-01

Nurses have increasingly been regarded as critical members of the planning team as architects recognize their knowledge and value. But the nurses' role as knowledge experts can be expanded to leading efforts to integrate the clinical, operational, and architectural expertise through simulation modeling. Simulation modeling allows for the optimal merge of multifactorial data to understand the current state of the intensive care unit and predict future states. Nurses can champion the simulation modeling process and reap the benefits of a cost-effective way to test new designs, processes, staffing models, and future programming trends prior to implementation. Simulation modeling is an evidence-based planning approach, a standard, for integrating the sciences with real client data, to offer solutions for improving patient care.

Integrated beam orientation and scanning-spot optimization in intensity-modulated proton therapy for brain and unilateral head and neck tumors.

PubMed

Gu, Wenbo; O'Connor, Daniel; Nguyen, Dan; Yu, Victoria Y; Ruan, Dan; Dong, Lei; Sheng, Ke

2018-04-01

Intensity-Modulated Proton Therapy (IMPT) is the state-of-the-art method of delivering proton radiotherapy. Previous research has been mainly focused on optimization of scanning spots with manually selected beam angles. Due to the computational complexity, the potential benefit of simultaneously optimizing beam orientations and spot pattern could not be realized. In this study, we developed a novel integrated beam orientation optimization (BOO) and scanning-spot optimization algorithm for intensity-modulated proton therapy (IMPT). A brain chordoma and three unilateral head-and-neck patients with a maximal target size of 112.49 cm 3 were included in this study. A total number of 1162 noncoplanar candidate beams evenly distributed across 4π steradians were included in the optimization. For each candidate beam, the pencil-beam doses of all scanning spots covering the PTV and a margin were calculated. The beam angle selection and spot intensity optimization problem was formulated to include three terms: a dose fidelity term to penalize the deviation of PTV and OAR doses from ideal dose distribution; an L1-norm sparsity term to reduce the number of active spots and improve delivery efficiency; a group sparsity term to control the number of active beams between 2 and 4. For the group sparsity term, convex L2,1-norm and nonconvex L2,1/2-norm were tested. For the dose fidelity term, both quadratic function and linearized equivalent uniform dose (LEUD) cost function were implemented. The optimization problem was solved using the Fast Iterative Shrinkage-Thresholding Algorithm (FISTA). The IMPT BOO method was tested on three head-and-neck patients and one skull base chordoma patient. The results were compared with IMPT plans created using column generation selected beams or manually selected beams. The L2,1-norm plan selected spatially aggregated beams, indicating potential degeneracy using this norm. L2,1/2-norm was able to select spatially separated beams and achieve smaller deviation from the ideal dose. In the L2,1/2-norm plans, the [mean dose, maximum dose] of OAR were reduced by an average of [2.38%, 4.24%] and[2.32%, 3.76%] of the prescription dose for the quadratic and LEUD cost function, respectively, compared with the IMPT plan using manual beam selection while maintaining the same PTV coverage. The L2,1/2 group sparsity plans were dosimetrically superior to the column generation plans as well. Besides beam orientation selection, spot sparsification was observed. Generally, with the quadratic cost function, 30%~60% spots in the selected beams remained active. With the LEUD cost function, the percentages of active spots were in the range of 35%~85%.The BOO-IMPT run time was approximately 20 min. This work shows the first IMPT approach integrating noncoplanar BOO and scanning-spot optimization in a single mathematical framework. This method is computationally efficient, dosimetrically superior and produces delivery-friendly IMPT plans. © 2018 American Association of Physicists in Medicine.

Adaptation of the CVT algorithm for catheter optimization in high dose rate brachytherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Poulin, Eric; Fekete, Charles-Antoine Collins; Beaulieu, Luc

2013-11-15

Purpose: An innovative, simple, and fast method to optimize the number and position of catheters is presented for prostate and breast high dose rate (HDR) brachytherapy, both for arbitrary templates or template-free implants (such as robotic templates).Methods: Eight clinical cases were chosen randomly from a bank of patients, previously treated in our clinic to test our method. The 2D Centroidal Voronoi Tessellations (CVT) algorithm was adapted to distribute catheters uniformly in space, within the maximum external contour of the planning target volume. The catheters optimization procedure includes the inverse planning simulated annealing algorithm (IPSA). Complete treatment plans can then bemore » generated from the algorithm for different number of catheters. The best plan is chosen from different dosimetry criteria and will automatically provide the number of catheters and their positions. After the CVT algorithm parameters were optimized for speed and dosimetric results, it was validated against prostate clinical cases, using clinically relevant dose parameters. The robustness to implantation error was also evaluated. Finally, the efficiency of the method was tested in breast interstitial HDR brachytherapy cases.Results: The effect of the number and locations of the catheters on prostate cancer patients was studied. Treatment plans with a better or equivalent dose distributions could be obtained with fewer catheters. A better or equal prostate V100 was obtained down to 12 catheters. Plans with nine or less catheters would not be clinically acceptable in terms of prostate V100 and D90. Implantation errors up to 3 mm were acceptable since no statistical difference was found when compared to 0 mm error (p > 0.05). No significant difference in dosimetric indices was observed for the different combination of parameters within the CVT algorithm. A linear relation was found between the number of random points and the optimization time of the CVT algorithm. Because the computation time decrease with the number of points and that no effects were observed on the dosimetric indices when varying the number of sampling points and the number of iterations, they were respectively fixed to 2500 and to 100. The computation time to obtain ten complete treatments plans ranging from 9 to 18 catheters, with the corresponding dosimetric indices, was 90 s. However, 93% of the computation time is used by a research version of IPSA. For the breast, on average, the Radiation Therapy Oncology Group recommendations would be satisfied down to 12 catheters. Plans with nine or less catheters would not be clinically acceptable in terms of V100, dose homogeneity index, and D90.Conclusions: The authors have devised a simple, fast and efficient method to optimize the number and position of catheters in interstitial HDR brachytherapy. The method was shown to be robust for both prostate and breast HDR brachytherapy. More importantly, the computation time of the algorithm is acceptable for clinical use. Ultimately, this catheter optimization algorithm could be coupled with a 3D ultrasound system to allow real-time guidance and planning in HDR brachytherapy.« less

TH-CD-209-05: Impact of Spot Size and Spacing On the Quality of Robustly-Optimized Intensity-Modulated Proton Therapy Plans for Lung Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, W; Ding, X; Hu, Y

Purpose: To investigate how spot size and spacing affect plan quality, especially, plan robustness and the impact of interplay effect, of robustly-optimized intensity-modulated proton therapy (IMPT) plans for lung cancer. Methods: Two robustly-optimized IMPT plans were created for 10 lung cancer patients: (1) one for a proton beam with in-air energy dependent large spot size at isocenter (σ: 5–15 mm) and spacing (1.53σ); (2) the other for a proton beam with small spot size (σ: 2–6 mm) and spacing (5 mm). Both plans were generated on the average CTs with internal-gross-tumor-volume density overridden to irradiate internal target volume (ITV). Themore » root-mean-square-dose volume histograms (RVH) measured the sensitivity of the dose to uncertainties, and the areas under RVH curves were used to evaluate plan robustness. Dose evaluation software was developed to model time-dependent spot delivery to incorporate interplay effect with randomized starting phases of each field per fraction. Patient anatomy voxels were mapped from phase to phase via deformable image registration to score doses. Dose-volume-histogram indices including ITV coverage, homogeneity, and organs-at-risk (OAR) sparing were compared using Student-t test. Results: Compared to large spots, small spots resulted in significantly better OAR sparing with comparable ITV coverage and homogeneity in the nominal plan. Plan robustness was comparable for ITV and most OARs. With interplay effect considered, significantly better OAR sparing with comparable ITV coverage and homogeneity is observed using smaller spots. Conclusion: Robust optimization with smaller spots significantly improves OAR sparing with comparable plan robustness and similar impact of interplay effect compare to larger spots. Small spot size requires the use of larger number of spots, which gives optimizer more freedom to render a plan more robust. The ratio between spot size and spacing was found to be more relevant to determine plan robustness and the impact of interplay effect than spot size alone. This research was supported by the National Cancer Institute Career Developmental Award K25CA168984, by the Fraternal Order of Eagles Cancer Research Fund Career Development Award, by The Lawrence W. and Marilyn W. Matteson Fund for Cancer Research, by Mayo Arizona State University Seed Grant, and by The Kemper Marley Foundation.« less

A new Gamma Knife radiosurgery paradigm: Tomosurgery

NASA Astrophysics Data System (ADS)

Hu, Xiaoliang

The Leksell (Elekta, Stockholm, Sweden) Gamma Knife(TM) (LGK) is the worldwide standard-of-care for the radiosurgical treatment of a wide variety of intracranial lesions. The current LGK utilizes a step-and-shoot dose delivery mechanism where the centroid of each conformal radiation dose (i.e., the shot isocenter) requires repositioning the patient outside of the irradiation field. Perhaps the greatest challenge the LGK treatment team faces is planning the treatment of large and/or complexly shaped lesions that may be in close proximity to critical neural or vascular structures. The standard manual treatment planning approach is a time consuming procedure where additional time spent does not guarantee the identification of an increasingly optimal treatment plan. I propose a new radiosurgery paradigm which I refer to as "Tomosurgery". The Tomosurgery paradigm begins with the division of the target volume into a series of adjacent treatment slices, each with a carefully determined optimal thickness. The use of a continuously moving disk-shaped radiation shot that moves through the lesion in a raster-scanning pattern is expected to improve overall radiation dose conformality and homogeneity. The Tomosurgery treatment planning algorithm recruits a two-stage optimization strategy, which first plans each treatment slice as a simplified 2D problem and secondly optimally assembles the 2D treatment plans into the final 3D treatment plan. Tested on 11 clinical LGK cases, the automated inversely-generated Tomosurgery treatment plans performed as well or better than the neurosurgeon's manually created treatment plans across all criteria: (a) dose volume histograms, (b) dose homogeneity, (c) dose conformality, and (d) critical structure damage, where applicable. LGK Tomosurgery inverse treatment planning required much less time than standard of care, manual (i.e., forward) LGK treatment planning procedures. These results suggest that Tomosurgery might provide an improvement over the current LGK radiosurgery treatment planning software. As regards treatment delivery, a Tomosurgery Investigational Platform (TIP) is proposed to perform the physical validation of radiation dose delivery. The TIP should facilitate translation of the Tomosurgery paradigm to several other radiosurgery and/or radiotherapy devices without the need for expensive modification of commercial devices until the feasibility of delivering Tomosurgical treatment plans has been well established.

Field Scale Optimization for Long-Term Sustainability of Best Management Practices in Watersheds

NASA Astrophysics Data System (ADS)

Samuels, A.; Babbar-Sebens, M.

2012-12-01

Agricultural and urban land use changes have led to disruption of natural hydrologic processes and impairment of streams and rivers. Multiple previous studies have evaluated Best Management Practices (BMPs) as means for restoring existing hydrologic conditions and reducing impairment of water resources. However, planning of these practices have relied on watershed scale hydrologic models for identifying locations and types of practices at scales much coarser than the actual field scale, where landowners have to plan, design and implement the practices. Field scale hydrologic modeling provides means for identifying relationships between BMP type, spatial location, and the interaction between BMPs at a finer farm/field scale that is usually more relevant to the decision maker (i.e. the landowner). This study focuses on development of a simulation-optimization approach for field-scale planning of BMPs in the School Branch stream system of Eagle Creek Watershed, Indiana, USA. The Agricultural Policy Environmental Extender (APEX) tool is used as the field scale hydrologic model, and a multi-objective optimization algorithm is used to search for optimal alternatives. Multiple climate scenarios downscaled to the watershed-scale are used to test the long term performance of these alternatives and under extreme weather conditions. The effectiveness of these BMPs under multiple weather conditions are included within the simulation-optimization approach as a criteria/goal to assist landowners in identifying sustainable design of practices. The results from these scenarios will further enable efficient BMP planning for current and future usage.

Optimal Paths in Gliding Flight

NASA Astrophysics Data System (ADS)

Wolek, Artur

Underwater gliders are robust and long endurance ocean sampling platforms that are increasingly being deployed in coastal regions. This new environment is characterized by shallow waters and significant currents that can challenge the mobility of these efficient (but traditionally slow moving) vehicles. This dissertation aims to improve the performance of shallow water underwater gliders through path planning. The path planning problem is formulated for a dynamic particle (or "kinematic car") model. The objective is to identify the path which satisfies specified boundary conditions and minimizes a particular cost. Several cost functions are considered. The problem is addressed using optimal control theory. The length scales of interest for path planning are within a few turn radii. First, an approach is developed for planning minimum-time paths, for a fixed speed glider, that are sub-optimal but are guaranteed to be feasible in the presence of unknown time-varying currents. Next the minimum-time problem for a glider with speed controls, that may vary between the stall speed and the maximum speed, is solved. Last, optimal paths that minimize change in depth (equivalently, maximize range) are investigated. Recognizing that path planning alone cannot overcome all of the challenges associated with significant currents and shallow waters, the design of a novel underwater glider with improved capabilities is explored. A glider with a pneumatic buoyancy engine (allowing large, rapid buoyancy changes) and a cylindrical moving mass mechanism (generating large pitch and roll moments) is designed, manufactured, and tested to demonstrate potential improvements in speed and maneuverability.

Motor planning under temporal uncertainty is suboptimal when the gain function is asymmetric

PubMed Central

Ota, Keiji; Shinya, Masahiro; Kudo, Kazutoshi

2015-01-01

For optimal action planning, the gain/loss associated with actions and the variability in motor output should both be considered. A number of studies make conflicting claims about the optimality of human action planning but cannot be reconciled due to their use of different movements and gain/loss functions. The disagreement is possibly because of differences in the experimental design and differences in the energetic cost of participant motor effort. We used a coincident timing task, which requires decision making with constant energetic cost, to test the optimality of participant's timing strategies under four configurations of the gain function. We compared participant strategies to an optimal timing strategy calculated from a Bayesian model that maximizes the expected gain. We found suboptimal timing strategies under two configurations of the gain function characterized by asymmetry, in which higher gain is associated with higher risk of zero gain. Participants showed a risk-seeking strategy by responding closer than optimal to the time of onset/offset of zero gain. Meanwhile, there was good agreement of the model with actual performance under two configurations of the gain function characterized by symmetry. Our findings show that human ability to make decisions that must reflect uncertainty in one's own motor output has limits that depend on the configuration of the gain function. PMID:26236227

Design and development of bio-inspired framework for reservoir operation optimization

NASA Astrophysics Data System (ADS)

Asvini, M. Sakthi; Amudha, T.

2017-12-01

Frameworks for optimal reservoir operation play an important role in the management of water resources and delivery of economic benefits. Effective utilization and conservation of water from reservoirs helps to manage water deficit periods. The main challenge in reservoir optimization is to design operating rules that can be used to inform real-time decisions on reservoir release. We develop a bio-inspired framework for the optimization of reservoir release to satisfy the diverse needs of various stakeholders. In this work, single-objective optimization and multiobjective optimization problems are formulated using an algorithm known as "strawberry optimization" and tested with actual reservoir data. Results indicate that well planned reservoir operations lead to efficient deployment of the reservoir water with the help of optimal release patterns.

Implementation of a software for REmote COMparison of PARticlE and photon treatment plans: ReCompare.

PubMed

Löck, Steffen; Roth, Klaus; Skripcak, Tomas; Worbs, Mario; Helmbrecht, Stephan; Jakobi, Annika; Just, Uwe; Krause, Mechthild; Baumann, Michael; Enghardt, Wolfgang; Lühr, Armin

2015-09-01

To guarantee equal access to optimal radiotherapy, a concept of patient assignment to photon or particle radiotherapy using remote treatment plan exchange and comparison - ReCompare - was proposed. We demonstrate the implementation of this concept and present its clinical applicability. The ReCompare concept was implemented using a client-server based software solution. A clinical workflow for the remote treatment plan exchange and comparison was defined. The steps required by the user and performed by the software for a complete plan transfer were described and an additional module for dose-response modeling was added. The ReCompare software was successfully tested in cooperation with three external partner clinics and worked meeting all required specifications. It was compatible with several standard treatment planning systems, ensured patient data protection, and integrated in the clinical workflow. The ReCompare software can be applied to support non-particle radiotherapy institutions with the patient-specific treatment decision on the optimal irradiation modality by remote treatment plan exchange and comparison. Copyright © 2015. Published by Elsevier GmbH.

Intensity modulated neutron radiotherapy optimization by photon proxy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Snyder, Michael; Hammoud, Ahmad; Bossenberger, Todd

2012-08-15

Purpose: Introducing intensity modulation into neutron radiotherapy (IMNRT) planning has the potential to mitigate some normal tissue complications seen in past neutron trials. While the hardware to deliver IMNRT plans has been in use for several years, until recently the IMNRT planning process has been cumbersome and of lower fidelity than conventional photon plans. Our in-house planning system used to calculate neutron therapy plans allows beam weight optimization of forward planned segments, but does not provide inverse optimization capabilities. Commercial treatment planning systems provide inverse optimization capabilities, but currently cannot model our neutron beam. Methods: We have developed a methodologymore » and software suite to make use of the robust optimization in our commercial planning system while still using our in-house planning system to calculate final neutron dose distributions. Optimized multileaf collimator (MLC) leaf positions for segments designed in the commercial system using a 4 MV photon proxy beam are translated into static neutron ports that can be represented within our in-house treatment planning system. The true neutron dose distribution is calculated in the in-house system and then exported back through the MATLAB software into the commercial treatment planning system for evaluation. Results: The planning process produces optimized IMNRT plans that reduce dose to normal tissue structures as compared to 3D conformal plans using static MLC apertures. The process involves standard planning techniques using a commercially available treatment planning system, and is not significantly more complex than conventional IMRT planning. Using a photon proxy in a commercial optimization algorithm produces IMNRT plans that are more conformal than those previously designed at our center and take much less time to create. Conclusions: The planning process presented here allows for the optimization of IMNRT plans by a commercial treatment planning optimization algorithm, potentially allowing IMNRT to achieve similar conformality in treatment as photon IMRT. The only remaining requirements for the delivery of very highly modulated neutron treatments are incremental improvements upon already implemented hardware systems that should be readily achievable.« less

Automated treatment planning for a dedicated multi-source intracranial radiosurgery treatment unit using projected gradient and grassfire algorithms.

PubMed

Ghobadi, Kimia; Ghaffari, Hamid R; Aleman, Dionne M; Jaffray, David A; Ruschin, Mark

2012-06-01

The purpose of this work is to develop a framework to the inverse problem for radiosurgery treatment planning on the Gamma Knife(®) Perfexion™ (PFX) for intracranial targets. The approach taken in the present study consists of two parts. First, a hybrid grassfire and sphere-packing algorithm is used to obtain shot positions (isocenters) based on the geometry of the target to be treated. For the selected isocenters, a sector duration optimization (SDO) model is used to optimize the duration of radiation delivery from each collimator size from each individual source bank. The SDO model is solved using a projected gradient algorithm. This approach has been retrospectively tested on seven manually planned clinical cases (comprising 11 lesions) including acoustic neuromas and brain metastases. In terms of conformity and organ-at-risk (OAR) sparing, the quality of plans achieved with the inverse planning approach were, on average, improved compared to the manually generated plans. The mean difference in conformity index between inverse and forward plans was -0.12 (range: -0.27 to +0.03) and +0.08 (range: 0.00-0.17) for classic and Paddick definitions, respectively, favoring the inverse plans. The mean difference in volume receiving the prescribed dose (V(100)) between forward and inverse plans was 0.2% (range: -2.4% to +2.0%). After plan renormalization for equivalent coverage (i.e., V(100)), the mean difference in dose to 1 mm(3) of brainstem between forward and inverse plans was -0.24 Gy (range: -2.40 to +2.02 Gy) favoring the inverse plans. Beam-on time varied with the number of isocenters but for the most optimal plans was on average 33 min longer than manual plans (range: -17 to +91 min) when normalized to a calibration dose rate of 3.5 Gy/min. In terms of algorithm performance, the isocenter selection for all the presented plans was performed in less than 3 s, while the SDO was performed in an average of 215 min. PFX inverse planning can be performed using geometric isocenter selection and mathematical modeling and optimization techniques. The obtained treatment plans all meet or exceed clinical guidelines while displaying high conformity. © 2012 American Association of Physicists in Medicine.

Cost Minimization for Joint Energy Management and Production Scheduling Using Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

Shah, Rahul H.

Production costs account for the largest share of the overall cost of manufacturing facilities. With the U.S. industrial sector becoming more and more competitive, manufacturers are looking for more cost and resource efficient working practices. Operations management and production planning have shown their capability to dramatically reduce manufacturing costs and increase system robustness. When implementing operations related decision making and planning, two fields that have shown to be most effective are maintenance and energy. Unfortunately, the current research that integrates both is limited. Additionally, these studies fail to consider parameter domains and optimization on joint energy and maintenance driven production planning. Accordingly, production planning methodology that considers maintenance and energy is investigated. Two models are presented to achieve well-rounded operating strategy. The first is a joint energy and maintenance production scheduling model. The second is a cost per part model considering maintenance, energy, and production. The proposed methodology will involve a Time-of-Use electricity demand response program, buffer and holding capacity, station reliability, production rate, station rated power, and more. In practice, the scheduling problem can be used to determine a joint energy, maintenance, and production schedule. Meanwhile, the cost per part model can be used to: (1) test the sensitivity of the obtained optimal production schedule and its corresponding savings by varying key production system parameters; and (2) to determine optimal system parameter combinations when using the joint energy, maintenance, and production planning model. Additionally, a factor analysis on the system parameters is conducted and the corresponding performance of the production schedule under variable parameter conditions, is evaluated. Also, parameter optimization guidelines that incorporate maintenance and energy parameter decision making in the production planning framework are discussed. A modified Particle Swarm Optimization solution technique is adopted to solve the proposed scheduling problem. The algorithm is described in detail and compared to Genetic Algorithm. Case studies are presented to illustrate the benefits of using the proposed model and the effectiveness of the Particle Swarm Optimization approach. Numerical Experiments are implemented and analyzed to test the effectiveness of the proposed model. The proposed scheduling strategy can achieve savings of around 19 to 27 % in cost per part when compared to the baseline scheduling scenarios. By optimizing key production system parameters from the cost per part model, the baseline scenarios can obtain around 20 to 35 % in savings for the cost per part. These savings further increase by 42 to 55 % when system parameter optimization is integrated with the proposed scheduling problem. Using this method, the most influential parameters on the cost per part are the rated power from production, the production rate, and the initial machine reliabilities. The modified Particle Swarm Optimization algorithm adopted allows greater diversity and exploration compared to Genetic Algorithm for the proposed joint model which results in it being more computationally efficient in determining the optimal scheduling. While Genetic Algorithm could achieve a solution quality of 2,279.63 at an expense of 2,300 seconds in computational effort. In comparison, the proposed Particle Swarm Optimization algorithm achieved a solution quality of 2,167.26 in less than half the computation effort which is required by Genetic Algorithm.

Explicit optimization of plan quality measures in intensity-modulated radiation therapy treatment planning.

PubMed

Engberg, Lovisa; Forsgren, Anders; Eriksson, Kjell; Hårdemark, Björn

2017-06-01

To formulate convex planning objectives of treatment plan multicriteria optimization with explicit relationships to the dose-volume histogram (DVH) statistics used in plan quality evaluation. Conventional planning objectives are designed to minimize the violation of DVH statistics thresholds using penalty functions. Although successful in guiding the DVH curve towards these thresholds, conventional planning objectives offer limited control of the individual points on the DVH curve (doses-at-volume) used to evaluate plan quality. In this study, we abandon the usual penalty-function framework and propose planning objectives that more closely relate to DVH statistics. The proposed planning objectives are based on mean-tail-dose, resulting in convex optimization. We also demonstrate how to adapt a standard optimization method to the proposed formulation in order to obtain a substantial reduction in computational cost. We investigated the potential of the proposed planning objectives as tools for optimizing DVH statistics through juxtaposition with the conventional planning objectives on two patient cases. Sets of treatment plans with differently balanced planning objectives were generated using either the proposed or the conventional approach. Dominance in the sense of better distributed doses-at-volume was observed in plans optimized within the proposed framework. The initial computational study indicates that the DVH statistics are better optimized and more efficiently balanced using the proposed planning objectives than using the conventional approach. © 2017 American Association of Physicists in Medicine.

Using Partially Observed Markov Decision Processes (POMDPs) to Implement a Response to Intervention (RTI) Framework for Early Reading

ERIC Educational Resources Information Center

Tokac, Umit

2016-01-01

The dissertation explored the efficacy of using a POMDP to select and apply appropriate instruction. POMDPs are a tool for planning: selecting a sequence of actions that will lead to an optimal outcome. RTI is an approach to instruction, where teachers craft individual plans for students based on the results of screening test. The goal is to…

SU-F-T-352: Development of a Knowledge Based Automatic Lung IMRT Planning Algorithm with Non-Coplanar Beams

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhu, W; Wu, Q; Yuan, L

Purpose: To improve the robustness of a knowledge based automatic lung IMRT planning method and to further validate the reliability of this algorithm by utilizing for the planning of clinical cases with non-coplanar beams. Methods: A lung IMRT planning method which automatically determines both plan optimization objectives and beam configurations with non-coplanar beams has been reported previously. A beam efficiency index map is constructed to guide beam angle selection in this algorithm. This index takes into account both the dose contributions from individual beams and the combined effect of multiple beams which is represented by a beam separation score. Wemore » studied the effect of this beam separation score on plan quality and determined the optimal weight for this score.14 clinical plans were re-planned with the knowledge-based algorithm. Significant dosimetric metrics for the PTV and OARs in the automatic plans are compared with those in the clinical plans by the two-sample t-test. In addition, a composite dosimetric quality index was defined to obtain the relationship between the plan quality and the beam separation score. Results: On average, we observed more than 15% reduction on conformity index and homogeneity index for PTV and V{sub 40}, V{sub 60} for heart while an 8% and 3% increase on V{sub 5}, V{sub 20} for lungs, respectively. The variation curve of the composite index as a function of angle spread score shows that 0.6 is the best value for the weight of the beam separation score. Conclusion: Optimal value for beam angle spread score in automatic lung IMRT planning is obtained. With this value, model can result in statistically the “best” achievable plans. This method can potentially improve the quality and planning efficiency for IMRT plans with no-coplanar angles.« less

Water-resources optimization model for Santa Barbara, California

USGS Publications Warehouse

Nishikawa, Tracy

1998-01-01

A simulation-optimization model has been developed for the optimal management of the city of Santa Barbara's water resources during a drought. The model, which links groundwater simulation with linear programming, has a planning horizon of 5 years. The objective is to minimize the cost of water supply subject to: water demand constraints, hydraulic head constraints to control seawater intrusion, and water capacity constraints. The decision variables are montly water deliveries from surface water and groundwater. The state variables are hydraulic heads. The drought of 1947-51 is the city's worst drought on record, and simulated surface-water supplies for this period were used as a basis for testing optimal management of current water resources under drought conditions. The simulation-optimization model was applied using three reservoir operation rules. In addition, the model's sensitivity to demand, carry over [the storage of water in one year for use in the later year(s)], head constraints, and capacity constraints was tested.

Research in Satellite-Fiber Network Interoperability

NASA Technical Reports Server (NTRS)

Edelson, Burt

1997-01-01

This four part report evaluated the performance of high data rate transmission links using the ACTS satellite, and to provide a preparatory test framework for two of the space science applications that have been approved for tests and demonstrations as part of the overall ACTS program. The test plan will provide guidance and information necessary to find the optimal values of the transmission parameters and then apply these parameters to specific applications. The first part will focus on the satellite-to-earth link. The second part is a set of tests to study the performance of ATM on the ACTS channel. The third and fourth parts of the test plan will cover the space science applications, Global Climate Modeling and Keck Telescope Acquisition Modeling and Control.

Use of plan quality degradation to evaluate tradeoffs in delivery efficiency and clinical plan metrics arising from IMRT optimizer and sequencer compromises

PubMed Central

Wilkie, Joel R.; Matuszak, Martha M.; Feng, Mary; Moran, Jean M.; Fraass, Benedick A.

2013-01-01

Purpose: Plan degradation resulting from compromises made to enhance delivery efficiency is an important consideration for intensity modulated radiation therapy (IMRT) treatment plans. IMRT optimization and/or multileaf collimator (MLC) sequencing schemes can be modified to generate more efficient treatment delivery, but the effect those modifications have on plan quality is often difficult to quantify. In this work, the authors present a method for quantitative assessment of overall plan quality degradation due to tradeoffs between delivery efficiency and treatment plan quality, illustrated using comparisons between plans developed allowing different numbers of intensity levels in IMRT optimization and/or MLC sequencing for static segmental MLC IMRT plans. Methods: A plan quality degradation method to evaluate delivery efficiency and plan quality tradeoffs was developed and used to assess planning for 14 prostate and 12 head and neck patients treated with static IMRT. Plan quality was evaluated using a physician's predetermined “quality degradation” factors for relevant clinical plan metrics associated with the plan optimization strategy. Delivery efficiency and plan quality were assessed for a range of optimization and sequencing limitations. The “optimal” (baseline) plan for each case was derived using a clinical cost function with an unlimited number of intensity levels. These plans were sequenced with a clinical MLC leaf sequencer which uses >100 segments, assuring delivered intensities to be within 1% of the optimized intensity pattern. Each patient's optimal plan was also sequenced limiting the number of intensity levels (20, 10, and 5), and then separately optimized with these same numbers of intensity levels. Delivery time was measured for all plans, and direct evaluation of the tradeoffs between delivery time and plan degradation was performed. Results: When considering tradeoffs, the optimal number of intensity levels depends on the treatment site and on the stage in the process at which the levels are limited. The cost of improved delivery efficiency, in terms of plan quality degradation, increased as the number of intensity levels in the sequencer or optimizer decreased. The degradation was more substantial for the head and neck cases relative to the prostate cases, particularly when fewer than 20 intensity levels were used. Plan quality degradation was less severe when the number of intensity levels was limited in the optimizer rather than the sequencer. Conclusions: Analysis of plan quality degradation allows for a quantitative assessment of the compromises in clinical plan quality as delivery efficiency is improved, in order to determine the optimal delivery settings. The technique is based on physician-determined quality degradation factors and can be extended to other clinical situations where investigation of various tradeoffs is warranted. PMID:23822412

Optimization process planning using hybrid genetic algorithm and intelligent search for job shop machining.

PubMed

Salehi, Mojtaba; Bahreininejad, Ardeshir

2011-08-01

Optimization of process planning is considered as the key technology for computer-aided process planning which is a rather complex and difficult procedure. A good process plan of a part is built up based on two elements: (1) the optimized sequence of the operations of the part; and (2) the optimized selection of the machine, cutting tool and Tool Access Direction (TAD) for each operation. In the present work, the process planning is divided into preliminary planning, and secondary/detailed planning. In the preliminary stage, based on the analysis of order and clustering constraints as a compulsive constraint aggregation in operation sequencing and using an intelligent searching strategy, the feasible sequences are generated. Then, in the detailed planning stage, using the genetic algorithm which prunes the initial feasible sequences, the optimized operation sequence and the optimized selection of the machine, cutting tool and TAD for each operation based on optimization constraints as an additive constraint aggregation are obtained. The main contribution of this work is the optimization of sequence of the operations of the part, and optimization of machine selection, cutting tool and TAD for each operation using the intelligent search and genetic algorithm simultaneously.

Optimization process planning using hybrid genetic algorithm and intelligent search for job shop machining

PubMed Central

Salehi, Mojtaba

2010-01-01

Optimization of process planning is considered as the key technology for computer-aided process planning which is a rather complex and difficult procedure. A good process plan of a part is built up based on two elements: (1) the optimized sequence of the operations of the part; and (2) the optimized selection of the machine, cutting tool and Tool Access Direction (TAD) for each operation. In the present work, the process planning is divided into preliminary planning, and secondary/detailed planning. In the preliminary stage, based on the analysis of order and clustering constraints as a compulsive constraint aggregation in operation sequencing and using an intelligent searching strategy, the feasible sequences are generated. Then, in the detailed planning stage, using the genetic algorithm which prunes the initial feasible sequences, the optimized operation sequence and the optimized selection of the machine, cutting tool and TAD for each operation based on optimization constraints as an additive constraint aggregation are obtained. The main contribution of this work is the optimization of sequence of the operations of the part, and optimization of machine selection, cutting tool and TAD for each operation using the intelligent search and genetic algorithm simultaneously. PMID:21845020

A fast optimization algorithm for multicriteria intensity modulated proton therapy planning.

PubMed

Chen, Wei; Craft, David; Madden, Thomas M; Zhang, Kewu; Kooy, Hanne M; Herman, Gabor T

2010-09-01

To describe a fast projection algorithm for optimizing intensity modulated proton therapy (IMPT) plans and to describe and demonstrate the use of this algorithm in multicriteria IMPT planning. The authors develop a projection-based solver for a class of convex optimization problems and apply it to IMPT treatment planning. The speed of the solver permits its use in multicriteria optimization, where several optimizations are performed which span the space of possible treatment plans. The authors describe a plan database generation procedure which is customized to the requirements of the solver. The optimality precision of the solver can be specified by the user. The authors apply the algorithm to three clinical cases: A pancreas case, an esophagus case, and a tumor along the rib cage case. Detailed analysis of the pancreas case shows that the algorithm is orders of magnitude faster than industry-standard general purpose algorithms (MOSEK'S interior point optimizer, primal simplex optimizer, and dual simplex optimizer). Additionally, the projection solver has almost no memory overhead. The speed and guaranteed accuracy of the algorithm make it suitable for use in multicriteria treatment planning, which requires the computation of several diverse treatment plans. Additionally, given the low memory overhead of the algorithm, the method can be extended to include multiple geometric instances and proton range possibilities, for robust optimization.

An automated optimization tool for high-dose-rate (HDR) prostate brachytherapy with divergent needle pattern

NASA Astrophysics Data System (ADS)

Borot de Battisti, M.; Maenhout, M.; de Senneville, B. Denis; Hautvast, G.; Binnekamp, D.; Lagendijk, J. J. W.; van Vulpen, M.; Moerland, M. A.

2015-10-01

Focal high-dose-rate (HDR) for prostate cancer has gained increasing interest as an alternative to whole gland therapy as it may contribute to the reduction of treatment related toxicity. For focal treatment, optimal needle guidance and placement is warranted. This can be achieved under MR guidance. However, MR-guided needle placement is currently not possible due to space restrictions in the closed MR bore. To overcome this problem, a MR-compatible, single-divergent needle-implant robotic device is under development at the University Medical Centre, Utrecht: placed between the legs of the patient inside the MR bore, this robot will tap the needle in a divergent pattern from a single rotation point into the tissue. This rotation point is just beneath the perineal skin to have access to the focal prostate tumor lesion. Currently, there is no treatment planning system commercially available which allows optimization of the dose distribution with such needle arrangement. The aim of this work is to develop an automatic inverse dose planning optimization tool for focal HDR prostate brachytherapy with needle insertions in a divergent configuration. A complete optimizer workflow is proposed which includes the determination of (1) the position of the center of rotation, (2) the needle angulations and (3) the dwell times. Unlike most currently used optimizers, no prior selection or adjustment of input parameters such as minimum or maximum dose or weight coefficients for treatment region and organs at risk is required. To test this optimizer, a planning study was performed on ten patients (treatment volumes ranged from 8.5 cm3to 23.3 cm3) by using 2-14 needle insertions. The total computation time of the optimizer workflow was below 20 min and a clinically acceptable plan was reached on average using only four needle insertions.

A new approach to integrate GPU-based Monte Carlo simulation into inverse treatment plan optimization for proton therapy.

PubMed

Li, Yongbao; Tian, Zhen; Song, Ting; Wu, Zhaoxia; Liu, Yaqiang; Jiang, Steve; Jia, Xun

2017-01-07

Monte Carlo (MC)-based spot dose calculation is highly desired for inverse treatment planning in proton therapy because of its accuracy. Recent studies on biological optimization have also indicated the use of MC methods to compute relevant quantities of interest, e.g. linear energy transfer. Although GPU-based MC engines have been developed to address inverse optimization problems, their efficiency still needs to be improved. Also, the use of a large number of GPUs in MC calculation is not favorable for clinical applications. The previously proposed adaptive particle sampling (APS) method can improve the efficiency of MC-based inverse optimization by using the computationally expensive MC simulation more effectively. This method is more efficient than the conventional approach that performs spot dose calculation and optimization in two sequential steps. In this paper, we propose a computational library to perform MC-based spot dose calculation on GPU with the APS scheme. The implemented APS method performs a non-uniform sampling of the particles from pencil beam spots during the optimization process, favoring those from the high intensity spots. The library also conducts two computationally intensive matrix-vector operations frequently used when solving an optimization problem. This library design allows a streamlined integration of the MC-based spot dose calculation into an existing proton therapy inverse planning process. We tested the developed library in a typical inverse optimization system with four patient cases. The library achieved the targeted functions by supporting inverse planning in various proton therapy schemes, e.g. single field uniform dose, 3D intensity modulated proton therapy, and distal edge tracking. The efficiency was 41.6  ±  15.3% higher than the use of a GPU-based MC package in a conventional calculation scheme. The total computation time ranged between 2 and 50 min on a single GPU card depending on the problem size.

A new approach to integrate GPU-based Monte Carlo simulation into inverse treatment plan optimization for proton therapy

NASA Astrophysics Data System (ADS)

Li, Yongbao; Tian, Zhen; Song, Ting; Wu, Zhaoxia; Liu, Yaqiang; Jiang, Steve; Jia, Xun

2017-01-01

Monte Carlo (MC)-based spot dose calculation is highly desired for inverse treatment planning in proton therapy because of its accuracy. Recent studies on biological optimization have also indicated the use of MC methods to compute relevant quantities of interest, e.g. linear energy transfer. Although GPU-based MC engines have been developed to address inverse optimization problems, their efficiency still needs to be improved. Also, the use of a large number of GPUs in MC calculation is not favorable for clinical applications. The previously proposed adaptive particle sampling (APS) method can improve the efficiency of MC-based inverse optimization by using the computationally expensive MC simulation more effectively. This method is more efficient than the conventional approach that performs spot dose calculation and optimization in two sequential steps. In this paper, we propose a computational library to perform MC-based spot dose calculation on GPU with the APS scheme. The implemented APS method performs a non-uniform sampling of the particles from pencil beam spots during the optimization process, favoring those from the high intensity spots. The library also conducts two computationally intensive matrix-vector operations frequently used when solving an optimization problem. This library design allows a streamlined integration of the MC-based spot dose calculation into an existing proton therapy inverse planning process. We tested the developed library in a typical inverse optimization system with four patient cases. The library achieved the targeted functions by supporting inverse planning in various proton therapy schemes, e.g. single field uniform dose, 3D intensity modulated proton therapy, and distal edge tracking. The efficiency was 41.6  ±  15.3% higher than the use of a GPU-based MC package in a conventional calculation scheme. The total computation time ranged between 2 and 50 min on a single GPU card depending on the problem size.

A New Approach to Integrate GPU-based Monte Carlo Simulation into Inverse Treatment Plan Optimization for Proton Therapy

PubMed Central

Li, Yongbao; Tian, Zhen; Song, Ting; Wu, Zhaoxia; Liu, Yaqiang; Jiang, Steve; Jia, Xun

2016-01-01

Monte Carlo (MC)-based spot dose calculation is highly desired for inverse treatment planning in proton therapy because of its accuracy. Recent studies on biological optimization have also indicated the use of MC methods to compute relevant quantities of interest, e.g. linear energy transfer. Although GPU-based MC engines have been developed to address inverse optimization problems, their efficiency still needs to be improved. Also, the use of a large number of GPUs in MC calculation is not favorable for clinical applications. The previously proposed adaptive particle sampling (APS) method can improve the efficiency of MC-based inverse optimization by using the computationally expensive MC simulation more effectively. This method is more efficient than the conventional approach that performs spot dose calculation and optimization in two sequential steps. In this paper, we propose a computational library to perform MC-based spot dose calculation on GPU with the APS scheme. The implemented APS method performs a non-uniform sampling of the particles from pencil beam spots during the optimization process, favoring those from the high intensity spots. The library also conducts two computationally intensive matrix-vector operations frequently used when solving an optimization problem. This library design allows a streamlined integration of the MC-based spot dose calculation into an existing proton therapy inverse planning process. We tested the developed library in a typical inverse optimization system with four patient cases. The library achieved the targeted functions by supporting inverse planning in various proton therapy schemes, e.g. single field uniform dose, 3D intensity modulated proton therapy, and distal edge tracking. The efficiency was 41.6±15.3% higher than the use of a GPU-based MC package in a conventional calculation scheme. The total computation time ranged between 2 and 50 min on a single GPU card depending on the problem size. PMID:27991456

Optimal integration of gravity in trajectory planning of vertical pointing movements.

PubMed

Crevecoeur, Frédéric; Thonnard, Jean-Louis; Lefèvre, Philippe

2009-08-01

The planning and control of motor actions requires knowledge of the dynamics of the controlled limb to generate the appropriate muscular commands and achieve the desired goal. Such planning and control imply that the CNS must be able to deal with forces and constraints acting on the limb, such as the omnipresent force of gravity. The present study investigates the effect of hypergravity induced by parabolic flights on the trajectory of vertical pointing movements to test the hypothesis that motor commands are optimized with respect to the effect of gravity on the limb. Subjects performed vertical pointing movements in normal gravity and hypergravity. We use a model based on optimal control to identify the role played by gravity in the optimal arm trajectory with minimal motor costs. First, the simulations in normal gravity reproduce the asymmetry in the velocity profiles (the velocity reaches its maximum before half of the movement duration), which typically characterizes the vertical pointing movements performed on Earth, whereas the horizontal movements present symmetrical velocity profiles. Second, according to the simulations, the optimal trajectory in hypergravity should present an increase in the peak acceleration and peak velocity despite the increase in the arm weight. In agreement with these predictions, the subjects performed faster movements in hypergravity with significant increases in the peak acceleration and peak velocity, which were accompanied by a significant decrease in the movement duration. This suggests that movement kinematics change in response to an increase in gravity, which is consistent with the hypothesis that motor commands are optimized and the action of gravity on the limb is taken into account. The results provide evidence for an internal representation of gravity in the central planning process and further suggest that an adaptation to altered dynamics can be understood as a reoptimization process.

Optimization of spatiotemporally fractionated radiotherapy treatments with bounds on the achievable benefit

NASA Astrophysics Data System (ADS)

Gaddy, Melissa R.; Yıldız, Sercan; Unkelbach, Jan; Papp, Dávid

2018-01-01

Spatiotemporal fractionation schemes, that is, treatments delivering different dose distributions in different fractions, can potentially lower treatment side effects without compromising tumor control. This can be achieved by hypofractionating parts of the tumor while delivering approximately uniformly fractionated doses to the surrounding tissue. Plan optimization for such treatments is based on biologically effective dose (BED); however, this leads to computationally challenging nonconvex optimization problems. Optimization methods that are in current use yield only locally optimal solutions, and it has hitherto been unclear whether these plans are close to the global optimum. We present an optimization framework to compute rigorous bounds on the maximum achievable normal tissue BED reduction for spatiotemporal plans. The approach is demonstrated on liver tumors, where the primary goal is to reduce mean liver BED without compromising any other treatment objective. The BED-based treatment plan optimization problems are formulated as quadratically constrained quadratic programming (QCQP) problems. First, a conventional, uniformly fractionated reference plan is computed using convex optimization. Then, a second, nonconvex, QCQP model is solved to local optimality to compute a spatiotemporally fractionated plan that minimizes mean liver BED, subject to the constraints that the plan is no worse than the reference plan with respect to all other planning goals. Finally, we derive a convex relaxation of the second model in the form of a semidefinite programming problem, which provides a rigorous lower bound on the lowest achievable mean liver BED. The method is presented on five cases with distinct geometries. The computed spatiotemporal plans achieve 12-35% mean liver BED reduction over the optimal uniformly fractionated plans. This reduction corresponds to 79-97% of the gap between the mean liver BED of the uniform reference plans and our lower bounds on the lowest achievable mean liver BED. The results indicate that spatiotemporal treatments can achieve substantial reductions in normal tissue dose and BED, and that local optimization techniques provide high-quality plans that are close to realizing the maximum potential normal tissue dose reduction.

Feasibility of online IMPT adaptation using fast, automatic and robust dose restoration

NASA Astrophysics Data System (ADS)

Bernatowicz, Kinga; Geets, Xavier; Barragan, Ana; Janssens, Guillaume; Souris, Kevin; Sterpin, Edmond

2018-04-01

Intensity-modulated proton therapy (IMPT) offers excellent dose conformity and healthy tissue sparing, but it can be substantially compromised in the presence of anatomical changes. A major dosimetric effect is caused by density changes, which alter the planned proton range in the patient. Three different methods, which automatically restore an IMPT plan dose on a daily CT image were implemented and compared: (1) simple dose restoration (DR) using optimization objectives of the initial plan, (2) voxel-wise dose restoration (vDR), and (3) isodose volume dose restoration (iDR). Dose restorations were calculated for three different clinical cases, selected to test different capabilities of the restoration methods: large range adaptation, complex dose distributions and robust re-optimization. All dose restorations were obtained in less than 5 min, without manual adjustments of the optimization settings. The evaluation of initial plans on repeated CTs showed large dose distortions, which were substantially reduced after restoration. In general, all dose restoration methods improved DVH-based scores in propagated target volumes and OARs. Analysis of local dose differences showed that, although all dose restorations performed similarly in high dose regions, iDR restored the initial dose with higher precision and accuracy in the whole patient anatomy. Median dose errors decreased from 13.55 Gy in distorted plan to 9.75 Gy (vDR), 6.2 Gy (DR) and 4.3 Gy (iDR). High quality dose restoration is essential to minimize or eventually by-pass the physician approval of the restored plan, as long as dose stability can be assumed. Motion (as well as setup and range uncertainties) can be taken into account by including robust optimization in the dose restoration. Restoring clinically-approved dose distribution on repeated CTs does not require new ROI segmentation and is compatible with an online adaptive workflow.

Hydraulische Optimierung des Reaktionsraumes um einen Infiltrationsbrunnen zur unterirdischen Enteisenung. Feldversuche und numerische Simulation zur Planung der optimalen Verfahrensergiebigkeit (Teil 1/2) Hydraulic optimization of the reaction zone around an injection well during subsurface iron removal

NASA Astrophysics Data System (ADS)

Ahrns, Johannes; Bartak, Rico; Grischek, Thomas; Pörschke, Richard

2017-11-01

In subsurface iron removal (SIR), oxygen-enriched water is injected into an aquifer to create a reaction zone. Aside from the hydraulic properties of the aquifer, groundwater quality often varies with depth so that in vertical wells the dissolved oxygen distribution (reaction zone) may not correspond to the dissolved iron concentration which may result in a lower efficiency coefficient. Therefore, measures to hydraulically optimize the formation of the reaction zone through a non-conventional injection were investigated. A high-resolution groundwater flow model was calibrated based on tracer and pump tests and used to plan the optimized injection for a SIR-pilot well with two screen segments. An optimized injection appears to be possible through the inactivation of well screen sections using packers. A doubling of the efficiency coefficient in comparison to a conventional injection was predicted when a packer, which remains evacuated inside the well while pumping, was used to seal 4/5 of the upper well screen length during injection. This scenario was used to plan the operating regime for a SIR field test, which is presented in Part 2.

Iterative dataset optimization in automated planning: Implementation for breast and rectal cancer radiotherapy.

PubMed

Fan, Jiawei; Wang, Jiazhou; Zhang, Zhen; Hu, Weigang

2017-06-01

To develop a new automated treatment planning solution for breast and rectal cancer radiotherapy. The automated treatment planning solution developed in this study includes selection of the iterative optimized training dataset, dose volume histogram (DVH) prediction for the organs at risk (OARs), and automatic generation of clinically acceptable treatment plans. The iterative optimized training dataset is selected by an iterative optimization from 40 treatment plans for left-breast and rectal cancer patients who received radiation therapy. A two-dimensional kernel density estimation algorithm (noted as two parameters KDE) which incorporated two predictive features was implemented to produce the predicted DVHs. Finally, 10 additional new left-breast treatment plans are re-planned using the Pinnacle 3 Auto-Planning (AP) module (version 9.10, Philips Medical Systems) with the objective functions derived from the predicted DVH curves. Automatically generated re-optimized treatment plans are compared with the original manually optimized plans. By combining the iterative optimized training dataset methodology and two parameters KDE prediction algorithm, our proposed automated planning strategy improves the accuracy of the DVH prediction. The automatically generated treatment plans using the dose derived from the predicted DVHs can achieve better dose sparing for some OARs without compromising other metrics of plan quality. The proposed new automated treatment planning solution can be used to efficiently evaluate and improve the quality and consistency of the treatment plans for intensity-modulated breast and rectal cancer radiation therapy. © 2017 American Association of Physicists in Medicine.

Multivariable normal tissue complication probability model-based treatment plan optimization for grade 2-4 dysphagia and tube feeding dependence in head and neck radiotherapy.

PubMed

Kierkels, Roel G J; Wopken, Kim; Visser, Ruurd; Korevaar, Erik W; van der Schaaf, Arjen; Bijl, Hendrik P; Langendijk, Johannes A

2016-12-01

Radiotherapy of the head and neck is challenged by the relatively large number of organs-at-risk close to the tumor. Biologically-oriented objective functions (OF) could optimally distribute the dose among the organs-at-risk. We aimed to explore OFs based on multivariable normal tissue complication probability (NTCP) models for grade 2-4 dysphagia (DYS) and tube feeding dependence (TFD). One hundred head and neck cancer patients were studied. Additional to the clinical plan, two more plans (an OF DYS and OF TFD -plan) were optimized per patient. The NTCP models included up to four dose-volume parameters and other non-dosimetric factors. A fully automatic plan optimization framework was used to optimize the OF NTCP -based plans. All OF NTCP -based plans were reviewed and classified as clinically acceptable. On average, the Δdose and ΔNTCP were small comparing the OF DYS -plan, OF TFD -plan, and clinical plan. For 5% of patients NTCP TFD reduced >5% using OF TFD -based planning compared to the OF DYS -plans. Plan optimization using NTCP DYS - and NTCP TFD -based objective functions resulted in clinically acceptable plans. For patients with considerable risk factors of TFD, the OF TFD steered the optimizer to dose distributions which directly led to slightly lower predicted NTCP TFD values as compared to the other studied plans. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

A fast optimization approach for treatment planning of volumetric modulated arc therapy.

PubMed

Yan, Hui; Dai, Jian-Rong; Li, Ye-Xiong

2018-05-30

Volumetric modulated arc therapy (VMAT) is widely used in clinical practice. It not only significantly reduces treatment time, but also produces high-quality treatment plans. Current optimization approaches heavily rely on stochastic algorithms which are time-consuming and less repeatable. In this study, a novel approach is proposed to provide a high-efficient optimization algorithm for VMAT treatment planning. A progressive sampling strategy is employed for beam arrangement of VMAT planning. The initial beams with equal-space are added to the plan in a coarse sampling resolution. Fluence-map optimization and leaf-sequencing are performed for these beams. Then, the coefficients of fluence-maps optimization algorithm are adjusted according to the known fluence maps of these beams. In the next round the sampling resolution is doubled and more beams are added. This process continues until the total number of beams arrived. The performance of VMAT optimization algorithm was evaluated using three clinical cases and compared to those of a commercial planning system. The dosimetric quality of VMAT plans is equal to or better than the corresponding IMRT plans for three clinical cases. The maximum dose to critical organs is reduced considerably for VMAT plans comparing to those of IMRT plans, especially in the head and neck case. The total number of segments and monitor units are reduced for VMAT plans. For three clinical cases, VMAT optimization takes < 5 min accomplished using proposed approach and is 3-4 times less than that of the commercial system. The proposed VMAT optimization algorithm is able to produce high-quality VMAT plans efficiently and consistently. It presents a new way to accelerate current optimization process of VMAT planning.

Improving Navy Recruiting with the New Planned Resource Optimization Model With Experimental Design (PROM-WED)

DTIC Science & Technology

2017-03-01

RECRUITING WITH THE NEW PLANNED RESOURCE OPTIMIZATION MODEL WITH EXPERIMENTAL DESIGN (PROM-WED) by Allison R. Hogarth March 2017 Thesis...with the New Planned Resource Optimization Model With Experimental Design (PROM-WED) 5. FUNDING NUMBERS 6. AUTHOR(S) Allison R. Hogarth 7. PERFORMING...has historically used a non -linear optimization model, the Planned Resource Optimization (PRO) model, to help inform decisions on the allocation of

GPU-based ultra-fast dose calculation using a finite size pencil beam model.

PubMed

Gu, Xuejun; Choi, Dongju; Men, Chunhua; Pan, Hubert; Majumdar, Amitava; Jiang, Steve B

2009-10-21

Online adaptive radiation therapy (ART) is an attractive concept that promises the ability to deliver an optimal treatment in response to the inter-fraction variability in patient anatomy. However, it has yet to be realized due to technical limitations. Fast dose deposit coefficient calculation is a critical component of the online planning process that is required for plan optimization of intensity-modulated radiation therapy (IMRT). Computer graphics processing units (GPUs) are well suited to provide the requisite fast performance for the data-parallel nature of dose calculation. In this work, we develop a dose calculation engine based on a finite-size pencil beam (FSPB) algorithm and a GPU parallel computing framework. The developed framework can accommodate any FSPB model. We test our implementation in the case of a water phantom and the case of a prostate cancer patient with varying beamlet and voxel sizes. All testing scenarios achieved speedup ranging from 200 to 400 times when using a NVIDIA Tesla C1060 card in comparison with a 2.27 GHz Intel Xeon CPU. The computational time for calculating dose deposition coefficients for a nine-field prostate IMRT plan with this new framework is less than 1 s. This indicates that the GPU-based FSPB algorithm is well suited for online re-planning for adaptive radiotherapy.

SU-F-J-66: Anatomy Deformation Based Comparison Between One-Step and Two-Step Optimization for Online ART

DOE Office of Scientific and Technical Information (OSTI.GOV)

Feng, Z; Yu, G; Qin, S

Purpose: This study investigated that how the quality of adapted plan was affected by inter-fractional anatomy deformation by using one-step and two-step optimization for on line adaptive radiotherapy (ART) procedure. Methods: 10 lung carcinoma patients were chosen randomly to produce IMRT plan by one-step and two-step algorithms respectively, and the prescribed dose was set as 60 Gy on the planning target volume (PTV) for all patients. To simulate inter-fractional target deformation, four specific cases were created by systematic anatomy variation; including target superior shift 0.5 cm, 0.3cm contraction, 0.3 cm expansion and 45-degree rotation. Based on these four anatomy deformation,more » adapted plan, regenerated plan and non-adapted plan were created to evaluate quality of adaptation. Adapted plans were generated automatically by using one-step and two-step algorithms respectively to optimize original plans, and regenerated plans were manually created by experience physicists. Non-adapted plans were produced by recalculating the dose distribution based on corresponding original plans. The deviations among these three plans were statistically analyzed by paired T-test. Results: In PTV superior shift case, adapted plans had significantly better PTV coverage by using two-step algorithm compared with one-step one, and meanwhile there was a significant difference of V95 by comparison with adapted and non-adapted plans (p=0.0025). In target contraction deformation, with almost same PTV coverage, the total lung received lower dose using one-step algorithm than two-step algorithm (p=0.0143,0.0126 for V20, Dmean respectively). In other two deformation cases, there were no significant differences observed by both two optimized algorithms. Conclusion: In geometry deformation such as target contraction, with comparable PTV coverage, one-step algorithm gave better OAR sparing than two-step algorithm. Reversely, the adaptation by using two-step algorithm had higher efficiency and accuracy as target occurred position displacement. We want to thank Dr. Lei Xing and Dr. Yong Yang in the Stanford University School of Medicine for this work. This work was jointly supported by NSFC (61471226), Natural Science Foundation for Distinguished Young Scholars of Shandong Province (JQ201516), and China Postdoctoral Science Foundation (2015T80739, 2014M551949).« less

Dynamic path planning for autonomous driving on various roads with avoidance of static and moving obstacles

NASA Astrophysics Data System (ADS)

Hu, Xuemin; Chen, Long; Tang, Bo; Cao, Dongpu; He, Haibo

2018-02-01

This paper presents a real-time dynamic path planning method for autonomous driving that avoids both static and moving obstacles. The proposed path planning method determines not only an optimal path, but also the appropriate acceleration and speed for a vehicle. In this method, we first construct a center line from a set of predefined waypoints, which are usually obtained from a lane-level map. A series of path candidates are generated by the arc length and offset to the center line in the s - ρ coordinate system. Then, all of these candidates are converted into Cartesian coordinates. The optimal path is selected considering the total cost of static safety, comfortability, and dynamic safety; meanwhile, the appropriate acceleration and speed for the optimal path are also identified. Various types of roads, including single-lane roads and multi-lane roads with static and moving obstacles, are designed to test the proposed method. The simulation results demonstrate the effectiveness of the proposed method, and indicate its wide practical application to autonomous driving.

Noncoplanar VMAT for nasopharyngeal tumors: Plan quality versus treatment time.

PubMed

Wild, Esther; Bangert, Mark; Nill, Simeon; Oelfke, Uwe

2015-05-01

The authors investigated the potential of optimized noncoplanar irradiation trajectories for volumetric modulated arc therapy (VMAT) treatments of nasopharyngeal patients and studied the trade-off between treatment plan quality and delivery time in radiation therapy. For three nasopharyngeal patients, the authors generated treatment plans for nine different delivery scenarios using dedicated optimization methods. They compared these scenarios according to dose characteristics, number of beam directions, and estimated delivery times. In particular, the authors generated the following treatment plans: (1) a 4π plan, which is a not sequenced, fluence optimized plan that uses beam directions from approximately 1400 noncoplanar directions and marks a theoretical upper limit of the treatment plan quality, (2) a coplanar 2π plan with 72 coplanar beam directions as pendant to the noncoplanar 4π plan, (3) a coplanar VMAT plan, (4) a coplanar step and shoot (SnS) plan, (5) a beam angle optimized (BAO) coplanar SnS IMRT plan, (6) a noncoplanar BAO SnS plan, (7) a VMAT plan with rotated treatment couch, (8) a noncoplanar VMAT plan with an optimized great circle around the patient, and (9) a noncoplanar BAO VMAT plan with an arbitrary trajectory around the patient. VMAT using optimized noncoplanar irradiation trajectories reduced the mean and maximum doses in organs at risk compared to coplanar VMAT plans by 19% on average while the target coverage remains constant. A coplanar BAO SnS plan was superior to coplanar SnS or VMAT; however, noncoplanar plans like a noncoplanar BAO SnS plan or noncoplanar VMAT yielded a better plan quality than the best coplanar 2π plan. The treatment plan quality of VMAT plans depended on the length of the trajectory. The delivery times of noncoplanar VMAT plans were estimated to be 6.5 min in average; 1.6 min longer than a coplanar plan but on average 2.8 min faster than a noncoplanar SnS plan with comparable treatment plan quality. The authors' study reconfirms the dosimetric benefits of noncoplanar irradiation of nasopharyngeal tumors. Both SnS using optimized noncoplanar beam ensembles and VMAT using an optimized, arbitrary, noncoplanar trajectory enabled dose reductions in organs at risk compared to coplanar SnS and VMAT. Using great circles or simple couch rotations to implement noncoplanar VMAT, however, was not sufficient to yield meaningful improvements in treatment plan quality. The authors estimate that noncoplanar VMAT using arbitrary optimized irradiation trajectories comes at an increased delivery time compared to coplanar VMAT yet at a decreased delivery time compared to noncoplanar SnS IMRT.

SU-F-BRD-01: A Novel 4D Robust Optimization Mitigates Interplay Effect in Intensity-Modulated Proton Therapy for Lung Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, W; Shen, J; Stoker, J

2015-06-15

Purpose: To compare the impact of interplay effect on 3D and 4D robustly optimized intensity-modulated proton therapy (IMPT) plans to treat lung cancer. Methods: Two IMPT plans were created for 11 non-small-cell-lung-cancer cases with 6–14 mm spots. 3D robust optimization generated plans on average CTs with the internal gross tumor volume density overridden to deliver 66 CGyE in 33 fractions to the internal target volume (ITV). 4D robust optimization generated plans on 4D CTs with the delivery of prescribed dose to the clinical target volume (CTV). In 4D optimization, the CTV of individual 4D CT phases received non-uniform doses tomore » achieve a uniform cumulative dose. Dose evaluation software was developed to model time-dependent spot delivery to incorporate interplay effect with randomized starting phases of each field per fraction. Patient anatomy voxels were mapped from phase to phase via deformable image registration to score doses. Indices from dose-volume histograms were used to compare target coverage, dose homogeneity, and normal-tissue sparing. DVH indices were compared using Wilcoxon test. Results: Given the presence of interplay effect, 4D robust optimization produced IMPT plans with better target coverage and homogeneity, but slightly worse normal tissue sparing compared to 3D robust optimization (unit: Gy) [D95% ITV: 63.5 vs 62.0 (p=0.014), D5% - D95% ITV: 6.2 vs 7.3 (p=0.37), D1% spinal cord: 29.0 vs 29.5 (p=0.52), Dmean total lung: 14.8 vs 14.5 (p=0.12), D33% esophagus: 33.6 vs 33.1 (p=0.28)]. The improvement of target coverage (D95%,4D – D95%,3D) was related to the ratio RMA3/(TVx10−4), with RMA and TV being respiratory motion amplitude (RMA) and tumor volume (TV), respectively. Peak benefit was observed at ratios between 2 and 10. This corresponds to 125 – 625 cm3 TV with 0.5-cm RMA. Conclusion: 4D optimization produced more interplay-effect-resistant plans compared to 3D optimization. It is most effective when respiratory motion is modest compared to TV. 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.« less

Twin Cities ramp meter evaluation : evaluation plan

DOT National Transportation Integrated Search

2000-09-25

The Minnesota Department of Transportation (Mn/DOT) uses ramp meters to manage freeway access on approximately 210 miles of freeways in the Twin Cities metropolitan area. Mn/DOT first tested ramp meters in 1969 as a method to optimize freeway safety ...

Robust optimization in lung treatment plans accounting for geometric uncertainty.

PubMed

Zhang, Xin; Rong, Yi; Morrill, Steven; Fang, Jian; Narayanasamy, Ganesh; Galhardo, Edvaldo; Maraboyina, Sanjay; Croft, Christopher; Xia, Fen; Penagaricano, Jose

2018-05-01

Robust optimization generates scenario-based plans by a minimax optimization method to find optimal scenario for the trade-off between target coverage robustness and organ-at-risk (OAR) sparing. In this study, 20 lung cancer patients with tumors located at various anatomical regions within the lungs were selected and robust optimization photon treatment plans including intensity modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT) plans were generated. The plan robustness was analyzed using perturbed doses with setup error boundary of ±3 mm in anterior/posterior (AP), ±3 mm in left/right (LR), and ±5 mm in inferior/superior (IS) directions from isocenter. Perturbed doses for D 99 , D 98 , and D 95 were computed from six shifted isocenter plans to evaluate plan robustness. Dosimetric study was performed to compare the internal target volume-based robust optimization plans (ITV-IMRT and ITV-VMAT) and conventional PTV margin-based plans (PTV-IMRT and PTV-VMAT). The dosimetric comparison parameters were: ITV target mean dose (D mean ), R 95 (D 95 /D prescription ), Paddick's conformity index (CI), homogeneity index (HI), monitor unit (MU), and OAR doses including lung (D mean , V 20 Gy and V 15 Gy ), chest wall, heart, esophagus, and maximum cord doses. A comparison of optimization results showed the robust optimization plan had better ITV dose coverage, better CI, worse HI, and lower OAR doses than conventional PTV margin-based plans. Plan robustness evaluation showed that the perturbed doses of D 99 , D 98 , and D 95 were all satisfied at least 99% of the ITV to received 95% of prescription doses. It was also observed that PTV margin-based plans had higher MU than robust optimization plans. The results also showed robust optimization can generate plans that offer increased OAR sparing, especially for normal lungs and OARs near or abutting the target. Weak correlation was found between normal lung dose and target size, and no other correlation was observed in this study. © 2018 University of Arkansas for Medical Sciences. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

A two‐point scheme for optimal breast IMRT treatment planning

PubMed Central

2013-01-01

We propose an approach to determining optimal beam weights in breast/chest wall IMRT treatment plans. The goal is to decrease breathing effect and to maximize skin dose if the skin is included in the target or, otherwise, to minimize the skin dose. Two points in the target are utilized to calculate the optimal weights. The optimal plan (i.e., the plan with optimal beam weights) consists of high energy unblocked beams, low energy unblocked beams, and IMRT beams. Six breast and five chest wall cases were retrospectively planned with this scheme in Eclipse, including one breast case where CTV was contoured by the physician. Compared with 3D CRT plans composed of unblocked and field‐in‐field beams, the optimal plans demonstrated comparable or better dose uniformity, homogeneity, and conformity to the target, especially at beam junction when supraclavicular nodes are involved. Compared with nonoptimal plans (i.e., plans with nonoptimized weights), the optimal plans had better dose distributions at shallow depths close to the skin, especially in cases where breathing effect was taken into account. This was verified with experiments using a MapCHECK device attached to a motion simulation table (to mimic motion caused by breathing). PACS number: 87.55 de PMID:24257291

Anatomical robust optimization to account for nasal cavity filling variation during intensity-modulated proton therapy: a comparison with conventional and adaptive planning strategies

NASA Astrophysics Data System (ADS)

van de Water, Steven; Albertini, Francesca; Weber, Damien C.; Heijmen, Ben J. M.; Hoogeman, Mischa S.; Lomax, Antony J.

2018-01-01

The aim of this study is to develop an anatomical robust optimization method for intensity-modulated proton therapy (IMPT) that accounts for interfraction variations in nasal cavity filling, and to compare it with conventional single-field uniform dose (SFUD) optimization and online plan adaptation. We included CT data of five patients with tumors in the sinonasal region. Using the planning CT, we generated for each patient 25 ‘synthetic’ CTs with varying nasal cavity filling. The robust optimization method available in our treatment planning system ‘Erasmus-iCycle’ was extended to also account for anatomical uncertainties by including (synthetic) CTs with varying patient anatomy as error scenarios in the inverse optimization. For each patient, we generated treatment plans using anatomical robust optimization and, for benchmarking, using SFUD optimization and online plan adaptation. Clinical target volume (CTV) and organ-at-risk (OAR) doses were assessed by recalculating the treatment plans on the synthetic CTs, evaluating dose distributions individually and accumulated over an entire fractionated 50 GyRBE treatment, assuming each synthetic CT to correspond to a 2 GyRBE fraction. Treatment plans were also evaluated using actual repeat CTs. Anatomical robust optimization resulted in adequate CTV doses (V95%  ⩾  98% and V107%  ⩽  2%) if at least three synthetic CTs were included in addition to the planning CT. These CTV requirements were also fulfilled for online plan adaptation, but not for the SFUD approach, even when applying a margin of 5 mm. Compared with anatomical robust optimization, OAR dose parameters for the accumulated dose distributions were on average 5.9 GyRBE (20%) higher when using SFUD optimization and on average 3.6 GyRBE (18%) lower for online plan adaptation. In conclusion, anatomical robust optimization effectively accounted for changes in nasal cavity filling during IMPT, providing substantially improved CTV and OAR doses compared with conventional SFUD optimization. OAR doses can be further reduced by using online plan adaptation.

Optimal Capacity Proportion and Distribution Planning of Wind, Photovoltaic and Hydro Power in Bundled Transmission System

NASA Astrophysics Data System (ADS)

Ye, X.; Tang, Q.; Li, T.; Wang, Y. L.; Zhang, X.; Ye, S. Y.

2017-05-01

The wind, photovoltaic and hydro power bundled transmission system attends to become common in Northwest and Southwest of China. To make better use of the power complementary characteristic of different power sources, the installed capacity proportion of wind, photovoltaic and hydro power, and their capacity distribution for each integration node is a significant issue to be solved in power system planning stage. An optimal capacity proportion and capacity distribution model for wind, photovoltaic and hydro power bundled transmission system is proposed here, which considers the power out characteristic of power resources with different type and in different area based on real operation data. The transmission capacity limit of power grid is also considered in this paper. Simulation cases are tested referring to one real regional system in Southwest China for planning level year 2020. The results verify the effectiveness of the model in this paper.

A Comparison of Probabilistic and Deterministic Campaign Analysis for Human Space Exploration

NASA Technical Reports Server (NTRS)

Merrill, R. Gabe; Andraschko, Mark; Stromgren, Chel; Cirillo, Bill; Earle, Kevin; Goodliff, Kandyce

2008-01-01

Human space exploration is by its very nature an uncertain endeavor. Vehicle reliability, technology development risk, budgetary uncertainty, and launch uncertainty all contribute to stochasticity in an exploration scenario. However, traditional strategic analysis has been done in a deterministic manner, analyzing and optimizing the performance of a series of planned missions. History has shown that exploration scenarios rarely follow such a planned schedule. This paper describes a methodology to integrate deterministic and probabilistic analysis of scenarios in support of human space exploration. Probabilistic strategic analysis is used to simulate "possible" scenario outcomes, based upon the likelihood of occurrence of certain events and a set of pre-determined contingency rules. The results of the probabilistic analysis are compared to the nominal results from the deterministic analysis to evaluate the robustness of the scenario to adverse events and to test and optimize contingency planning.

iCycle: Integrated, multicriterial beam angle, and profile optimization for generation of coplanar and noncoplanar IMRT plans

DOE Office of Scientific and Technical Information (OSTI.GOV)

Breedveld, Sebastiaan; Storchi, Pascal R. M.; Voet, Peter W. J.

2012-02-15

Purpose: To introduce iCycle, a novel algorithm for integrated, multicriterial optimization of beam angles, and intensity modulated radiotherapy (IMRT) profiles. Methods: A multicriterial plan optimization with iCycle is based on a prescription called wish-list, containing hard constraints and objectives with ascribed priorities. Priorities are ordinal parameters used for relative importance ranking of the objectives. The higher an objective priority is, the higher the probability that the corresponding objective will be met. Beam directions are selected from an input set of candidate directions. Input sets can be restricted, e.g., to allow only generation of coplanar plans, or to avoid collisions betweenmore » patient/couch and the gantry in a noncoplanar setup. Obtaining clinically feasible calculation times was an important design criterium for development of iCycle. This could be realized by sequentially adding beams to the treatment plan in an iterative procedure. Each iteration loop starts with selection of the optimal direction to be added. Then, a Pareto-optimal IMRT plan is generated for the (fixed) beam setup that includes all so far selected directions, using a previously published algorithm for multicriterial optimization of fluence profiles for a fixed beam arrangement Breedveld et al.[Phys. Med. Biol. 54, 7199-7209 (2009)]. To select the next direction, each not yet selected candidate direction is temporarily added to the plan and an optimization problem, derived from the Lagrangian obtained from the just performed optimization for establishing the Pareto-optimal plan, is solved. For each patient, a single one-beam, two-beam, three-beam, etc. Pareto-optimal plan is generated until addition of beams does no longer result in significant plan quality improvement. Plan generation with iCycle is fully automated. Results: Performance and characteristics of iCycle are demonstrated by generating plans for a maxillary sinus case, a cervical cancer patient, and a liver patient treated with SBRT. Plans generated with beam angle optimization did better meet the clinical goals than equiangular or manually selected configurations. For the maxillary sinus and liver cases, significant improvements for noncoplanar setups were seen. The cervix case showed that also in IMRT with coplanar setups, beam angle optimization with iCycle may improve plan quality. Computation times for coplanar plans were around 1-2 h and for noncoplanar plans 4-7 h, depending on the number of beams and the complexity of the site. Conclusions: Integrated beam angle and profile optimization with iCycle may result in significant improvements in treatment plan quality. Due to automation, the plan generation workload is minimal. Clinical application has started.« less

SU-E-T-618: Dosimetric Comparison of Manual and Beam Angle Optimization of Gantry Angles in IMRT for Cervical Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lin, X; Sun, T; Liu, T

2014-06-01

Purpose: To evaluate the dosimetric characteristics of intensity-modulated radiotherapy (IMRT) treatment plan with beam angle optimization. Methods: Ten post-operation patients with cervical cancer were included in this analysis. Two IMRT plans using seven beams were designed in each patient. A standard coplanar equi-space beam angles were used in the first plan (plan 1), whereas the selection of beam angle was optimized by beam angle optimization algorithm in Varian Eclipse treatment planning system for the same number of beams in the second plan (plan 2). Two plans were designed for each patient with the same dose-volume constraints and prescription dose. Allmore » plans were normalized to the mean dose to PTV. The dose distribution in the target, the dose to the organs at risk and total MU were compared. Results: For conformity and homogeneity in PTV, no statistically differences were observed in the two plans. For the mean dose in bladder, plan 2 were significantly lower than plan 1(p<0.05). No statistically significant differences were observed between two plans for the mean doses in rectum, left and right femur heads. Compared with plan1, the average monitor units reduced 16% in plan 2. Conclusion: The IMRT plan based on beam angle optimization for cervical cancer could reduce the dose delivered to bladder and also reduce MU. Therefore there were some dosimetric advantages in the IMRT plan with beam angle optimization for cervical cancer.« less

MO-FG-CAMPUS-TeP2-01: A Graph Form ADMM Algorithm for Constrained Quadratic Radiation Treatment Planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, X; Belcher, AH; Wiersma, R

Purpose: In radiation therapy optimization the constraints can be either hard constraints which must be satisfied or soft constraints which are included but do not need to be satisfied exactly. Currently the voxel dose constraints are viewed as soft constraints and included as a part of the objective function and approximated as an unconstrained problem. However in some treatment planning cases the constraints should be specified as hard constraints and solved by constrained optimization. The goal of this work is to present a computation efficiency graph form alternating direction method of multipliers (ADMM) algorithm for constrained quadratic treatment planning optimizationmore » and compare it with several commonly used algorithms/toolbox. Method: ADMM can be viewed as an attempt to blend the benefits of dual decomposition and augmented Lagrangian methods for constrained optimization. Various proximal operators were first constructed as applicable to quadratic IMRT constrained optimization and the problem was formulated in a graph form of ADMM. A pre-iteration operation for the projection of a point to a graph was also proposed to further accelerate the computation. Result: The graph form ADMM algorithm was tested by the Common Optimization for Radiation Therapy (CORT) dataset including TG119, prostate, liver, and head & neck cases. Both unconstrained and constrained optimization problems were formulated for comparison purposes. All optimizations were solved by LBFGS, IPOPT, Matlab built-in toolbox, CVX (implementing SeDuMi) and Mosek solvers. For unconstrained optimization, it was found that LBFGS performs the best, and it was 3–5 times faster than graph form ADMM. However, for constrained optimization, graph form ADMM was 8 – 100 times faster than the other solvers. Conclusion: A graph form ADMM can be applied to constrained quadratic IMRT optimization. It is more computationally efficient than several other commercial and noncommercial optimizers and it also used significantly less computer memory.« less

Optimization for high-dose-rate brachytherapy of cervical cancer with adaptive simulated annealing and gradient descent.

PubMed

Yao, Rui; Templeton, Alistair K; Liao, Yixiang; Turian, Julius V; Kiel, Krystyna D; Chu, James C H

2014-01-01

To validate an in-house optimization program that uses adaptive simulated annealing (ASA) and gradient descent (GD) algorithms and investigate features of physical dose and generalized equivalent uniform dose (gEUD)-based objective functions in high-dose-rate (HDR) brachytherapy for cervical cancer. Eight Syed/Neblett template-based cervical cancer HDR interstitial brachytherapy cases were used for this study. Brachytherapy treatment plans were first generated using inverse planning simulated annealing (IPSA). Using the same dwell positions designated in IPSA, plans were then optimized with both physical dose and gEUD-based objective functions, using both ASA and GD algorithms. Comparisons were made between plans both qualitatively and based on dose-volume parameters, evaluating each optimization method and objective function. A hybrid objective function was also designed and implemented in the in-house program. The ASA plans are higher on bladder V75% and D2cc (p=0.034) and lower on rectum V75% and D2cc (p=0.034) than the IPSA plans. The ASA and GD plans are not significantly different. The gEUD-based plans have higher homogeneity index (p=0.034), lower overdose index (p=0.005), and lower rectum gEUD and normal tissue complication probability (p=0.005) than the physical dose-based plans. The hybrid function can produce a plan with dosimetric parameters between the physical dose-based and gEUD-based plans. The optimized plans with the same objective value and dose-volume histogram could have different dose distributions. Our optimization program based on ASA and GD algorithms is flexible on objective functions, optimization parameters, and can generate optimized plans comparable with IPSA. Copyright © 2014 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.

Efficacy of robust optimization plan with partial-arc VMAT for photon volumetric-modulated arc therapy: A phantom study.

PubMed

Miura, Hideharu; Ozawa, Shuichi; Nagata, Yasushi

2017-09-01

This study investigated position dependence in planning target volume (PTV)-based and robust optimization plans using full-arc and partial-arc volumetric modulated arc therapy (VMAT). The gantry angles at the periphery, intermediate, and center CTV positions were 181°-180° (full-arc VMAT) and 181°-360° (partial-arc VMAT). A PTV-based optimization plan was defined by 5 mm margin expansion of the CTV to a PTV volume, on which the dose constraints were applied. The robust optimization plan consisted of a directly optimized dose to the CTV under a maximum-uncertainties setup of 5 mm. The prescription dose was normalized to the CTV D 99% (the minimum relative dose that covers 99% of the volume of the CTV) as an original plan. The isocenter was rigidly shifted at 1 mm intervals in the anterior-posterior (A-P), superior-inferior (S-I), and right-left (R-L) directions from the original position to the maximum-uncertainties setup of 5 mm in the original plan, yielding recalculated dose distributions. It was found that for the intermediate and center positions, the uncertainties in the D 99% doses to the CTV for all directions did not significantly differ when comparing the PTV-based and robust optimization plans (P > 0.05). For the periphery position, uncertainties in the D 99% doses to the CTV in the R-L direction for the robust optimization plan were found to be lower than those in the PTV-based optimization plan (P < 0.05). Our study demonstrated that a robust optimization plan's efficacy using partial-arc VMAT depends on the periphery CTV position. © 2017 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Automated medial axis seeding and guided evolutionary simulated annealing for optimization of gamma knife radiosurgery treatment plans

NASA Astrophysics Data System (ADS)

Zhang, Pengpeng

The Leksell Gamma KnifeRTM (LGK) is a tool for providing accurate stereotactic radiosurgical treatment of brain lesions, especially tumors. Currently, the treatment planning team "forward" plans radiation treatment parameters while viewing a series of 2D MR scans. This primarily manual process is cumbersome and time consuming because the difficulty in visualizing the large search space for the radiation parameters (i.e., shot overlap, number, location, size, and weight). I hypothesize that a computer-aided "inverse" planning procedure that utilizes tumor geometry and treatment goals could significantly improve the planning process and therapeutic outcome of LGK radiosurgery. My basic observation is that the treatment team is best at identification of the location of the lesion and prescribing a lethal, yet safe, radiation dose. The treatment planning computer is best at determining both the 3D tumor geometry and optimal LGK shot parameters necessary to deliver a desirable dose pattern to the tumor while sparing adjacent normal tissue. My treatment planning procedure asks the neurosurgeon to identify the tumor and critical structures in MR images and the oncologist to prescribe a tumoricidal radiation dose. Computer-assistance begins with geometric modeling of the 3D tumor's medial axis properties. This begins with a new algorithm, a Gradient-Phase Plot (G-P Plot) decomposition of the tumor object's medial axis. I have found that medial axis seeding, while insufficient in most cases to produce an acceptable treatment plan, greatly reduces the solution space for Guided Evolutionary Simulated Annealing (GESA) treatment plan optimization by specifying an initial estimate for shot number, size, and location, but not weight. They are used to generate multiple initial plans which become initial seed plans for GESA. The shot location and weight parameters evolve and compete in the GESA procedure. The GESA objective function optimizes tumor irradiation (i.e., as close to the prescribed dose as possible) and minimizes normal tissue and critical structure damage. In tests of five patient data sets (4 acoustic neuromas and 1 meningioma), the G-P Plot/GESA-generated treatment plans improved conformality of the lethal dose to the tumor, required no human interaction, improved dose homogeneity, suggested use of fewer shots, and reduced treatment administration time.

TH-EF-BRB-10: Dosimetric Validation of a Trajectory Based Cranial SRS Treatment Technique On a Varian TrueBeam Linac

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wilson, B; Vancouver Cancer Centre, Vancouver, BC; Gete, E

2016-06-15

Purpose: This work investigates the dosimetric accuracy of a trajectory based delivery technique in which an optimized radiation beam is delivered along a Couch-Gantry trajectory that is formed by simultaneous rotation of the linac gantry and the treatment couch. Methods: Nine trajectory based cranial SRS treatment plans were created using in-house optimization software. The plans were calculated for delivery on the TrueBeam STx linac with 6MV photon beam. Dose optimization was performed along a user-defined trajectory using MLC modulation, dose rate modulation and jaw tracking. The pre-defined trajectory chosen for this study is formed by a couch rotation through itsmore » full range of 180 degrees while the gantry makes four partial arc sweeps which are 170 degrees each. For final dose calculation, the trajectory based plans were exported to the Varian Eclipse Treatment Planning System. The plans were calculated on a homogeneous cube phantom measuring 18.2×18.2×18.2 cm3 with the analytical anisotropic algorithm (AAA) using a 1mm3 calculation voxel. The plans were delivered on the TrueBeam linac via the developer’s mode. Point dose measurements were performed on 9 patients with the IBA CC01 mini-chamber with a sensitive volume of 0.01 cc. Gafchromic film measurements along the sagittal and coronal planes were performed on three of the 9 treatment plans. Point dose values were compared with ion chamber measurements. Gamma analysis comparing film measurement and AAA calculations was performed using FilmQA Pro. Results: The AAA calculations and measurements were in good agreement. The point dose difference between AAA and ion chamber measurements were within 2.2%. Gamma analysis test pass rates (2%, 2mm passing criteria) for the Gafchromic film measurements were >95%. Conclusion: We have successfully tested TrueBeam’s ability to deliver accurate trajectory based treatments involving simultaneous gantry and couch rotation with MLC and dose rate modulation along the trajectory.« less

The use of TCP based EUD to rank and compare lung radiotherapy plans: in-silico study to evaluate the correlation between TCP with physical quality indices.

PubMed

Chaikh, Abdulhamid; Balosso, Jacques

2017-06-01

To apply the equivalent uniform dose (EUD) radiobiological model to estimate the tumor control probability (TCP) scores for treatment plans using different radiobiological parameter settings, and to evaluate the correlation between TCP and physical quality indices of the treatment plans. Ten radiotherapy treatment plans for lung cancer were generated. The dose distributions were calculated using anisotropic analytical algorithm (AAA). Dose parameters and quality indices derived from dose volume histograms (DVH) for target volumes were evaluated. The predicted TCP was computed using EUD model with tissue-specific parameter (a=-10). The assumed radiobiological parameter setting for adjuvant therapy [tumor dose to control 50% of the tumor (TCD 50 ) =36.5 Gy and γ 50 =0.72] and curative intent (TCD 50 =51.24 Gy and γ 50 =0.83) were used. The bootstrap method was used to estimate the 95% confidence interval (95% CI). The coefficients (ρ) from Spearman's rank test were calculated to assess the correlation between quality indices with TCP. Wilcoxon paired test was used to calculate P value. The 95% CI of TCP were 70.6-81.5 and 46.6-64.7, respectively, for adjuvant radiotherapy and curative intent. The TCP outcome showed a positive and good correlation with calculated dose to 95% of the target volume (D95%) and minimum dose (Dmin). Consistently, TCP correlate negatively with heterogeneity indices. This study confirms that more relevant and robust radiobiological parameters setting should be integrated according to cancer type. The positive correlation with quality indices gives chance to improve the clinical out-come by optimizing the treatment plans to maximize the Dmin and D95%. This attempt to increase the TCP should be carried out with the respect of dose constraints for organs at risks. However, the negative correlation with heterogeneity indices shows that the optimization of beam arrangements could be also useful. Attention should be paid to obtain an appropriate optimization of initial plans, when comparing and ranking radiotherapy plans using TCP models, to avoid over or underestimated for TCP outcome.

Optimism and Planning for Future Care Needs among Older Adults

PubMed Central

Sörensen, Silvia; Hirsch, Jameson K.; Lyness, Jeffrey M.

2015-01-01

Aging is associated with an increase in need for assistance. Preparation for future care (PFC) is related to improved coping ability as well as better mental and physical health outcomes among older adults. We examined the association of optimism with components of PFC among older adults. We also explored race differences in the relationship between optimism and PFC. In Study 1, multiple regression showed that optimism was positively related to concrete planning. In Study 2, optimism was related to gathering information. An exploratory analysis combining the samples yielded a race interaction: For Whites higher optimism, but for Blacks lower optimism was associated with more planning. High optimism may be a barrier to future planning in certain social and cultural contexts. PMID:26045699

Noncoplanar VMAT for nasopharyngeal tumors: Plan quality versus treatment time

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wild, Esther, E-mail: e.wild@dkfz.de; Bangert, Mark; Nill, Simeon

Purpose: The authors investigated the potential of optimized noncoplanar irradiation trajectories for volumetric modulated arc therapy (VMAT) treatments of nasopharyngeal patients and studied the trade-off between treatment plan quality and delivery time in radiation therapy. Methods: For three nasopharyngeal patients, the authors generated treatment plans for nine different delivery scenarios using dedicated optimization methods. They compared these scenarios according to dose characteristics, number of beam directions, and estimated delivery times. In particular, the authors generated the following treatment plans: (1) a 4π plan, which is a not sequenced, fluence optimized plan that uses beam directions from approximately 1400 noncoplanar directionsmore » and marks a theoretical upper limit of the treatment plan quality, (2) a coplanar 2π plan with 72 coplanar beam directions as pendant to the noncoplanar 4π plan, (3) a coplanar VMAT plan, (4) a coplanar step and shoot (SnS) plan, (5) a beam angle optimized (BAO) coplanar SnS IMRT plan, (6) a noncoplanar BAO SnS plan, (7) a VMAT plan with rotated treatment couch, (8) a noncoplanar VMAT plan with an optimized great circle around the patient, and (9) a noncoplanar BAO VMAT plan with an arbitrary trajectory around the patient. Results: VMAT using optimized noncoplanar irradiation trajectories reduced the mean and maximum doses in organs at risk compared to coplanar VMAT plans by 19% on average while the target coverage remains constant. A coplanar BAO SnS plan was superior to coplanar SnS or VMAT; however, noncoplanar plans like a noncoplanar BAO SnS plan or noncoplanar VMAT yielded a better plan quality than the best coplanar 2π plan. The treatment plan quality of VMAT plans depended on the length of the trajectory. The delivery times of noncoplanar VMAT plans were estimated to be 6.5 min in average; 1.6 min longer than a coplanar plan but on average 2.8 min faster than a noncoplanar SnS plan with comparable treatment plan quality. Conclusions: The authors’ study reconfirms the dosimetric benefits of noncoplanar irradiation of nasopharyngeal tumors. Both SnS using optimized noncoplanar beam ensembles and VMAT using an optimized, arbitrary, noncoplanar trajectory enabled dose reductions in organs at risk compared to coplanar SnS and VMAT. Using great circles or simple couch rotations to implement noncoplanar VMAT, however, was not sufficient to yield meaningful improvements in treatment plan quality. The authors estimate that noncoplanar VMAT using arbitrary optimized irradiation trajectories comes at an increased delivery time compared to coplanar VMAT yet at a decreased delivery time compared to noncoplanar SnS IMRT.« less

Lean and Efficient Software: Whole-Program Optimization of Executables

DTIC Science & Technology

2013-01-03

staffing for the project  Implementing the necessary infrastructure ( testing, performance evaluation, needed support software, bug and issue...in the SOW The result of the planning discussions is shown in the milestone table (section 6). In addition, we selected appropriate engineering

Development and clinical introduction of automated radiotherapy treatment planning for prostate cancer

NASA Astrophysics Data System (ADS)

Winkel, D.; Bol, G. H.; van Asselen, B.; Hes, J.; Scholten, V.; Kerkmeijer, L. G. W.; Raaymakers, B. W.

2016-12-01

To develop an automated radiotherapy treatment planning and optimization workflow to efficiently create patient specifically optimized clinical grade treatment plans for prostate cancer and to implement it in clinical practice. A two-phased planning and optimization workflow was developed to automatically generate 77Gy 5-field simultaneously integrated boost intensity modulated radiation therapy (SIB-IMRT) plans for prostate cancer treatment. A retrospective planning study (n  =  100) was performed in which automatically and manually generated treatment plans were compared. A clinical pilot (n  =  21) was performed to investigate the usability of our method. Operator time for the planning process was reduced to  <5 min. The retrospective planning study showed that 98 plans met all clinical constraints. Significant improvements were made in the volume receiving 72Gy (V72Gy) for the bladder and rectum and the mean dose of the bladder and the body. A reduced plan variance was observed. During the clinical pilot 20 automatically generated plans met all constraints and 17 plans were selected for treatment. The automated radiotherapy treatment planning and optimization workflow is capable of efficiently generating patient specifically optimized and improved clinical grade plans. It has now been adopted as the current standard workflow in our clinic to generate treatment plans for prostate cancer.

Systems Engineering Management Plan NASA Traffic Aware Planner Integration Into P-180 Airborne Test-Bed

NASA Technical Reports Server (NTRS)

Maris, John

2015-01-01

NASA's Traffic Aware Planner (TAP) is a cockpit decision support tool that provides aircrew with vertical and lateral flight-path optimizations with the intent of achieving significant fuel and time savings, while automatically avoiding traffic, weather, and restricted airspace conflicts. A key step towards the maturation and deployment of TAP concerned its operational evaluation in a representative flight environment. This Systems Engineering Management Plan (SEMP) addresses the test-vehicle design, systems integration, and flight-test planning for the first TAP operational flight evaluations, which were successfully completed in November 2013. The trial outcomes are documented in the Traffic Aware Planner (TAP) flight evaluation paper presented at the 14th AIAA Aviation Technology, Integration, and Operations Conference, Atlanta, GA. (AIAA-2014-2166, Maris, J. M., Haynes, M. A., Wing, D. J., Burke, K. A., Henderson, J., & Woods, S. E., 2014).

SU-E-T-110: An Investigation On Monitor Unit Threshold and Effects On IMPT Delivery in Proton Pencil Beam Planning System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Syh, J; Ding, X; Syh, J

2015-06-15

Purpose: An approved proton pencil beam scanning (PBS) treatment plan might not be able to deliver because of existed extremely low monitor unit per beam spot. A dual hybrid plan with higher efficiency of higher spot monitor unit and the efficacy of less number of energy layers were searched and optimized. The range of monitor unit threshold setting was investigated and the plan quality was evaluated by target dose conformity. Methods: Certain limitations and requirements need to be checks and tested before a nominal proton PBS treatment plan can be delivered. The plan needs to be met the machine characterization,more » specification in record and verification to deliver the beams. Minimal threshold of monitor unit, e.g. 0.02, per spot was set to filter the low counts and plan was re-computed. Further MU threshold increment was tested in sequence without sacrificing the plan quality. The number of energy layer was also alternated due to elimination of low count layer(s). Results: Minimal MU/spot threshold, spot spacing in each energy layer and total number of energy layer and the MU weighting of beam spots of each beam were evaluated. Plan optimization between increases of the spot MU (efficiency) and less energy layers of delivery (efficacy) was adjusted. 5% weighting limit of total monitor unit per beam was feasible. Scarce spreading of beam spots was not discouraging as long as target dose conformity within 3% criteria. Conclusion: Each spot size is equivalent to the relative dose in the beam delivery system. The energy layer is associated with the depth of the targeting tumor. Our work is crucial to maintain the best possible quality plan. To keep integrity of all intrinsic elements such as spot size, spot number, layer number and the carried weighting of spots in each layer is important in this study.« less

Drilling and Production Testing the Methane Hydrate Resource Potential Associated with the Barrow Gas Fields

DOE Office of Scientific and Technical Information (OSTI.GOV)

Steve McRae; Thomas Walsh; Michael Dunn

2010-02-22

In November of 2008, the Department of Energy (DOE) and the North Slope Borough (NSB) committed funding to develop a drilling plan to test the presence of hydrates in the producing formation of at least one of the Barrow Gas Fields, and to develop a production surveillance plan to monitor the behavior of hydrates as dissociation occurs. This drilling and surveillance plan was supported by earlier studies in Phase 1 of the project, including hydrate stability zone modeling, material balance modeling, and full-field history-matched reservoir simulation, all of which support the presence of methane hydrate in association with the Barrowmore » Gas Fields. This Phase 2 of the project, conducted over the past twelve months focused on selecting an optimal location for a hydrate test well; design of a logistics, drilling, completion and testing plan; and estimating costs for the activities. As originally proposed, the project was anticipated to benefit from industry activity in northwest Alaska, with opportunities to share equipment, personnel, services and mobilization and demobilization costs with one of the then-active exploration operators. The activity level dropped off, and this benefit evaporated, although plans for drilling of development wells in the BGF's matured, offering significant synergies and cost savings over a remote stand-alone drilling project. An optimal well location was chosen at the East Barrow No.18 well pad, and a vertical pilot/monitoring well and horizontal production test/surveillance well were engineered for drilling from this location. Both wells were designed with Distributed Temperature Survey (DTS) apparatus for monitoring of the hydrate-free gas interface. Once project scope was developed, a procurement process was implemented to engage the necessary service and equipment providers, and finalize project cost estimates. Based on cost proposals from vendors, total project estimated cost is $17.88 million dollars, inclusive of design work, permitting, barging, ice road/pad construction, drilling, completion, tie-in, long-term production testing and surveillance, data analysis and technology transfer. The PRA project team and North Slope have recommended moving forward to the execution phase of this project.« less

Optimizing spacecraft design - optimization engine development : progress and plans

NASA Technical Reports Server (NTRS)

Cornford, Steven L.; Feather, Martin S.; Dunphy, Julia R; Salcedo, Jose; Menzies, Tim

2003-01-01

At JPL and NASA, a process has been developed to perform life cycle risk management. This process requires users to identify: goals and objectives to be achieved (and their relative priorities), the various risks to achieving those goals and objectives, and options for risk mitigation (prevention, detection ahead of time, and alleviation). Risks are broadly defined to include the risk of failing to design a system with adequate performance, compatibility and robustness in addition to more traditional implementation and operational risks. The options for mitigating these different kinds of risks can include architectural and design choices, technology plans and technology back-up options, test-bed and simulation options, engineering models and hardware/software development techniques and other more traditional risk reduction techniques.

SU-F-J-133: Adaptive Radiation Therapy with a Four-Dimensional Dose Calculation Algorithm That Optimizes Dose Distribution Considering Breathing Motion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ali, I; Algan, O; Ahmad, S

Purpose: To model patient motion and produce four-dimensional (4D) optimized dose distributions that consider motion-artifacts in the dose calculation during the treatment planning process. Methods: An algorithm for dose calculation is developed where patient motion is considered in dose calculation at the stage of the treatment planning. First, optimal dose distributions are calculated for the stationary target volume where the dose distributions are optimized considering intensity-modulated radiation therapy (IMRT). Second, a convolution-kernel is produced from the best-fitting curve which matches the motion trajectory of the patient. Third, the motion kernel is deconvolved with the initial dose distribution optimized for themore » stationary target to produce a dose distribution that is optimized in four-dimensions. This algorithm is tested with measured doses using a mobile phantom that moves with controlled motion patterns. Results: A motion-optimized dose distribution is obtained from the initial dose distribution of the stationary target by deconvolution with the motion-kernel of the mobile target. This motion-optimized dose distribution is equivalent to that optimized for the stationary target using IMRT. The motion-optimized and measured dose distributions are tested with the gamma index with a passing rate of >95% considering 3% dose-difference and 3mm distance-to-agreement. If the dose delivery per beam takes place over several respiratory cycles, then the spread-out of the dose distributions is only dependent on the motion amplitude and not affected by motion frequency and phase. This algorithm is limited to motion amplitudes that are smaller than the length of the target along the direction of motion. Conclusion: An algorithm is developed to optimize dose in 4D. Besides IMRT that provides optimal dose coverage for a stationary target, it extends dose optimization to 4D considering target motion. This algorithm provides alternative to motion management techniques such as beam-gating or breath-holding and has potential applications in adaptive radiation therapy.« less

Dose-shaping using targeted sparse optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sayre, George A.; Ruan, Dan

2013-07-15

Purpose: Dose volume histograms (DVHs) are common tools in radiation therapy treatment planning to characterize plan quality. As statistical metrics, DVHs provide a compact summary of the underlying plan at the cost of losing spatial information: the same or similar dose-volume histograms can arise from substantially different spatial dose maps. This is exactly the reason why physicians and physicists scrutinize dose maps even after they satisfy all DVH endpoints numerically. However, up to this point, little has been done to control spatial phenomena, such as the spatial distribution of hot spots, which has significant clinical implications. To this end, themore » authors propose a novel objective function that enables a more direct tradeoff between target coverage, organ-sparing, and planning target volume (PTV) homogeneity, and presents our findings from four prostate cases, a pancreas case, and a head-and-neck case to illustrate the advantages and general applicability of our method.Methods: In designing the energy minimization objective (E{sub tot}{sup sparse}), the authors utilized the following robust cost functions: (1) an asymmetric linear well function to allow differential penalties for underdose, relaxation of prescription dose, and overdose in the PTV; (2) a two-piece linear function to heavily penalize high dose and mildly penalize low and intermediate dose in organs-at risk (OARs); and (3) a total variation energy, i.e., the L{sub 1} norm applied to the first-order approximation of the dose gradient in the PTV. By minimizing a weighted sum of these robust costs, general conformity to dose prescription and dose-gradient prescription is achieved while encouraging prescription violations to follow a Laplace distribution. In contrast, conventional quadratic objectives are associated with a Gaussian distribution of violations, which is less forgiving to large violations of prescription than the Laplace distribution. As a result, the proposed objective E{sub tot}{sup sparse} improves tradeoff between planning goals by 'sacrificing' voxels that have already been violated to improve PTV coverage, PTV homogeneity, and/or OAR-sparing. In doing so, overall plan quality is increased since these large violations only arise if a net reduction in E{sub tot}{sup sparse} occurs as a result. For example, large violations to dose prescription in the PTV in E{sub tot}{sup sparse}-optimized plans will naturally localize to voxels in and around PTV-OAR overlaps where OAR-sparing may be increased without compromising target coverage. The authors compared the results of our method and the corresponding clinical plans using analyses of DVH plots, dose maps, and two quantitative metrics that quantify PTV homogeneity and overdose. These metrics do not penalize underdose since E{sub tot}{sup sparse}-optimized plans were planned such that their target coverage was similar or better than that of the clinical plans. Finally, plan deliverability was assessed with the 2D modulation index.Results: The proposed method was implemented using IBM's CPLEX optimization package (ILOG CPLEX, Sunnyvale, CA) and required 1-4 min to solve with a 12-core Intel i7 processor. In the testing procedure, the authors optimized for several points on the Pareto surface of four 7-field 6MV prostate cases that were optimized for different levels of PTV homogeneity and OAR-sparing. The generated results were compared against each other and the clinical plan by analyzing their DVH plots and dose maps. After developing intuition by planning the four prostate cases, which had relatively few tradeoffs, the authors applied our method to a 7-field 6 MV pancreas case and a 9-field 6MV head-and-neck case to test the potential impact of our method on more challenging cases. The authors found that our formulation: (1) provided excellent flexibility for balancing OAR-sparing with PTV homogeneity; and (2) permitted the dose planner more control over the evolution of the PTV's spatial dose distribution than conventional objective functions. In particular, E{sub tot}{sup sparse}-optimized plans for the pancreas case and head-and-neck case exhibited substantially improved sparing of the spinal cord and parotid glands, respectively, while maintaining or improving sparing for other OARs and markedly improving PTV homogeneity. Plan deliverability for E{sub tot}{sup sparse}-optimized plans was shown to be better than their associated clinical plans, according to the two-dimensional modulation index.Conclusions: These results suggest that our formulation may be used to improve dose-shaping and OAR-sparing for complicated disease sites, such as the pancreas or head and neck. Furthermore, our objective function and constraints are linear and constitute a linear program, which converges to the global minimum quickly, and can be easily implemented in treatment planning software. Thus, the authors expect fast translation of our method to the clinic where it may have a positive impact on plan quality for challenging disease sites.« less

Planning multi-arm screening studies within the context of a drug development program

PubMed Central

Wason, James M S; Jaki, Thomas; Stallard, Nigel

2013-01-01

Screening trials are small trials used to decide whether an intervention is sufficiently promising to warrant a large confirmatory trial. Previous literature examined the situation where treatments are tested sequentially until one is considered sufficiently promising to take forward to a confirmatory trial. An important consideration for sponsors of clinical trials is how screening trials should be planned to maximize the efficiency of the drug development process. It has been found previously that small screening trials are generally the most efficient. In this paper we consider the design of screening trials in which multiple new treatments are tested simultaneously. We derive analytic formulae for the expected number of patients until a successful treatment is found, and propose methodology to search for the optimal number of treatments, and optimal sample size per treatment. We compare designs in which only the best treatment proceeds to a confirmatory trial and designs in which multiple treatments may proceed to a multi-arm confirmatory trial. We find that inclusion of a large number of treatments in the screening trial is optimal when only one treatment can proceed, and a smaller number of treatments is optimal when more than one can proceed. The designs we investigate are compared on a real-life set of screening designs. Copyright © 2013 John Wiley & Sons, Ltd. PMID:23529936

Advanced proton beam dosimetry part II: Monte Carlo vs. pencil beam-based planning for lung cancer.

PubMed

Maes, Dominic; Saini, Jatinder; Zeng, Jing; Rengan, Ramesh; Wong, Tony; Bowen, Stephen R

2018-04-01

Proton pencil beam (PB) dose calculation algorithms have limited accuracy within heterogeneous tissues of lung cancer patients, which may be addressed by modern commercial Monte Carlo (MC) algorithms. We investigated clinical pencil beam scanning (PBS) dose differences between PB and MC-based treatment planning for lung cancer patients. With IRB approval, a comparative dosimetric analysis between RayStation MC and PB dose engines was performed on ten patient plans. PBS gantry plans were generated using single-field optimization technique to maintain target coverage under range and setup uncertainties. Dose differences between PB-optimized (PBopt), MC-recalculated (MCrecalc), and MC-optimized (MCopt) plans were recorded for the following region-of-interest metrics: clinical target volume (CTV) V95, CTV homogeneity index (HI), total lung V20, total lung V RX (relative lung volume receiving prescribed dose or higher), and global maximum dose. The impact of PB-based and MC-based planning on robustness to systematic perturbation of range (±3% density) and setup (±3 mm isotropic) was assessed. Pairwise differences in dose parameters were evaluated through non-parametric Friedman and Wilcoxon sign-rank testing. In this ten-patient sample, CTV V95 decreased significantly from 99-100% for PBopt to 77-94% for MCrecalc and recovered to 99-100% for MCopt (P<10 -5 ). The median CTV HI (D95/D5) decreased from 0.98 for PBopt to 0.91 for MCrecalc and increased to 0.95 for MCopt (P<10 -3 ). CTV D95 robustness to range and setup errors improved under MCopt (ΔD95 =-1%) compared to MCrecalc (ΔD95 =-6%, P=0.006). No changes in lung dosimetry were observed for large volumes receiving low to intermediate doses (e.g., V20), while differences between PB-based and MC-based planning were noted for small volumes receiving high doses (e.g., V RX ). Global maximum patient dose increased from 106% for PBopt to 109% for MCrecalc and 112% for MCopt (P<10 -3 ). MC dosimetry revealed a reduction in target dose coverage under PB-based planning that was regained under MC-based planning along with improved plan robustness. MC-based optimization and dose calculation should be integrated into clinical planning workflows of lung cancer patients receiving actively scanned proton therapy.

Advanced proton beam dosimetry part II: Monte Carlo vs. pencil beam-based planning for lung cancer

PubMed Central

Maes, Dominic; Saini, Jatinder; Zeng, Jing; Rengan, Ramesh; Wong, Tony

2018-01-01

Background Proton pencil beam (PB) dose calculation algorithms have limited accuracy within heterogeneous tissues of lung cancer patients, which may be addressed by modern commercial Monte Carlo (MC) algorithms. We investigated clinical pencil beam scanning (PBS) dose differences between PB and MC-based treatment planning for lung cancer patients. Methods With IRB approval, a comparative dosimetric analysis between RayStation MC and PB dose engines was performed on ten patient plans. PBS gantry plans were generated using single-field optimization technique to maintain target coverage under range and setup uncertainties. Dose differences between PB-optimized (PBopt), MC-recalculated (MCrecalc), and MC-optimized (MCopt) plans were recorded for the following region-of-interest metrics: clinical target volume (CTV) V95, CTV homogeneity index (HI), total lung V20, total lung VRX (relative lung volume receiving prescribed dose or higher), and global maximum dose. The impact of PB-based and MC-based planning on robustness to systematic perturbation of range (±3% density) and setup (±3 mm isotropic) was assessed. Pairwise differences in dose parameters were evaluated through non-parametric Friedman and Wilcoxon sign-rank testing. Results In this ten-patient sample, CTV V95 decreased significantly from 99–100% for PBopt to 77–94% for MCrecalc and recovered to 99–100% for MCopt (P<10−5). The median CTV HI (D95/D5) decreased from 0.98 for PBopt to 0.91 for MCrecalc and increased to 0.95 for MCopt (P<10−3). CTV D95 robustness to range and setup errors improved under MCopt (ΔD95 =−1%) compared to MCrecalc (ΔD95 =−6%, P=0.006). No changes in lung dosimetry were observed for large volumes receiving low to intermediate doses (e.g., V20), while differences between PB-based and MC-based planning were noted for small volumes receiving high doses (e.g., VRX). Global maximum patient dose increased from 106% for PBopt to 109% for MCrecalc and 112% for MCopt (P<10−3). Conclusions MC dosimetry revealed a reduction in target dose coverage under PB-based planning that was regained under MC-based planning along with improved plan robustness. MC-based optimization and dose calculation should be integrated into clinical planning workflows of lung cancer patients receiving actively scanned proton therapy. PMID:29876310

Residential solar-heating/cooling system

NASA Technical Reports Server (NTRS)

1980-01-01

Report documents progress of residential solar-heating and cooling system development program at 5-month mark of anticipated 17-month program. System design has been completed, and development and component testing has been initiated. Report includes diagrams, operation overview, optimization studies of subcomponents, and marketing plans for system.

Verification of dosimetric accuracy on the TrueBeam STx: rounded leaf effect of the high definition MLC.

PubMed

Kielar, Kayla N; Mok, Ed; Hsu, Annie; Wang, Lei; Luxton, Gary

2012-10-01

The dosimetric leaf gap (DLG) in the Varian Eclipse treatment planning system is determined during commissioning and is used to model the effect of the rounded leaf-end of the multileaf collimator (MLC). This parameter attempts to model the physical difference between the radiation and light field and account for inherent leakage between leaf tips. With the increased use of single fraction high dose treatments requiring larger monitor units comes an enhanced concern in the accuracy of leakage calculations, as it accounts for much of the patient dose. This study serves to verify the dosimetric accuracy of the algorithm used to model the rounded leaf effect for the TrueBeam STx, and describes a methodology for determining best-practice parameter values, given the novel capabilities of the linear accelerator such as flattening filter free (FFF) treatments and a high definition MLC (HDMLC). During commissioning, the nominal MLC position was verified and the DLG parameter was determined using MLC-defined field sizes and moving gap tests, as is common in clinical testing. Treatment plans were created, and the DLG was optimized to achieve less than 1% difference between measured and calculated dose. The DLG value found was tested on treatment plans for all energies (6 MV, 10 MV, 15 MV, 6 MV FFF, 10 MV FFF) and modalities (3D conventional, IMRT, conformal arc, VMAT) available on the TrueBeam STx. The DLG parameter found during the initial MLC testing did not match the leaf gap modeling parameter that provided the most accurate dose delivery in clinical treatment plans. Using the physical leaf gap size as the DLG for the HDMLC can lead to 5% differences in measured and calculated doses. Separate optimization of the DLG parameter using end-to-end tests must be performed to ensure dosimetric accuracy in the modeling of the rounded leaf ends for the Eclipse treatment planning system. The difference in leaf gap modeling versus physical leaf gap dimensions is more pronounced in the more recent versions of Eclipse for both the HDMLC and the Millennium MLC. Once properly commissioned and tested using a methodology based on treatment plan verification, Eclipse is able to accurately model radiation dose delivered for SBRT treatments using the TrueBeam STx.

Preparing GMAT for Operational Maneuver Planning of the Advanced Composition Explorer (ACE)

NASA Technical Reports Server (NTRS)

Qureshi, Rizwan Hamid; Hughes, Steven P.

2014-01-01

The General Mission Analysis Tool (GMAT) is an open-source space mission design, analysis and trajectory optimization tool. GMAT is developed by a team of NASA, private industry, public and private contributors. GMAT is designed to model, optimize and estimate spacecraft trajectories in flight regimes ranging from low Earth orbit to lunar applications, interplanetary trajectories and other deep space missions. GMAT has also been flight qualified to support operational maneuver planning for the Advanced Composition Explorer (ACE) mission. ACE was launched in August, 1997 and is orbiting the Sun-Earth L1 libration point. The primary science objective of ACE is to study the composition of both the solar wind and the galactic cosmic rays. Operational orbit determination, maneuver operations and product generation for ACE are conducted by NASA Goddard Space Flight Center (GSFC) Flight Dynamics Facility (FDF). This paper discusses the entire engineering lifecycle and major operational certification milestones that GMAT successfully completed to obtain operational certification for the ACE mission. Operational certification milestones such as gathering of the requirements for ACE operational maneuver planning, gap analysis, test plans and procedures development, system design, pre-shadow operations, training to FDF ACE maneuver planners, shadow operations, Test Readiness Review (TRR) and finally Operational Readiness Review (ORR) are discussed. These efforts have demonstrated that GMAT is flight quality software ready to support ACE mission operations in the FDF.

TU-AB-303-12: Towards Inter and Intra Fraction Plan Adaptation for the MR-Linac

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kontaxis, C; Bol, G; Lagendijk, J

Purpose: To develop a new sequencer for IMRT that during treatment can account for anatomy changes provided by online and real-time MRI. This sequencer employs a novel inter and intra fraction scheme that converges to the prescribed dose without a final segment weight optimization (SWO) and enables immediate optimization and delivery of radiation adapted to the deformed anatomy. Methods: The sequencer is initially supplied with a voxel-based dose prescription and during the optimization iteratively generates segments that provide this prescribed dose. Every iteration selects the best segment for the current anatomy state, calculates the dose it will deliver, warps itmore » back to the reference prescription grid and subtracts it from the remaining prescribed dose. This process continues until a certain percentage of dose or a number of segments has been delivered. The anatomy changes that occur during treatment require that convergence is achieved without a final SWO. This is resolved by adding the difference between the prescribed and delivered dose up to this fraction to the prescription of the subsequent fraction. This process is repeated for all fractions of the treatment. Results: Two breast cases were selected to stress test the pipeline by producing artificial inter and intra fraction anatomy deformations using a combination of incrementally applied rigid transformations. The dose convergence of the adaptive scheme over the entire treatment, relative to the prescribed dose, was on average 8.6% higher than the static plans delivered to the respective deformed anatomies and only 1.6% less than the static segment weighted plans on the static anatomy. Conclusion: This new adaptive sequencing strategy enables dose convergence without the need of SWO while adapting the plan to intermediate anatomies, which is a prerequisite for online plan adaptation. We are now testing our pipeline on prostate cases using clinical anatomy deformation data from our department. This work is financially supported by Elekta AB, Stockholm, Sweden.« less

OPTIMIZATION OF MUD HAMMER DRILLING PERFORMANCE - A PROGRAM TO BENCHMARK THE VIABILITY OF ADVANCED MUD HAMMER DRILLING

DOE Office of Scientific and Technical Information (OSTI.GOV)

Arnis Judzis

2002-10-01

This document details the progress to date on the OPTIMIZATION OF MUD HAMMER DRILLING PERFORMANCE -- A PROGRAM TO BENCHMARK THE VIABILITY OF ADVANCED MUD HAMMER DRILLING contract for the quarter starting July 2002 through September 2002. Even though we are awaiting the optimization portion of the testing program, accomplishments include the following: (1) Smith International agreed to participate in the DOE Mud Hammer program. (2) Smith International chromed collars for upcoming benchmark tests at TerraTek, now scheduled for 4Q 2002. (3) ConocoPhillips had a field trial of the Smith fluid hammer offshore Vietnam. The hammer functioned properly, though themore » well encountered hole conditions and reaming problems. ConocoPhillips plan another field trial as a result. (4) DOE/NETL extended the contract for the fluid hammer program to allow Novatek to ''optimize'' their much delayed tool to 2003 and to allow Smith International to add ''benchmarking'' tests in light of SDS Digger Tools' current financial inability to participate. (5) ConocoPhillips joined the Industry Advisors for the mud hammer program. (6) TerraTek acknowledges Smith International, BP America, PDVSA, and ConocoPhillips for cost-sharing the Smith benchmarking tests allowing extension of the contract to complete the optimizations.« less

The method of planning the energy consumption for electricity market

NASA Astrophysics Data System (ADS)

Russkov, O. V.; Saradgishvili, S. E.

2017-10-01

The limitations of existing forecast models are defined. The offered method is based on game theory, probabilities theory and forecasting the energy prices relations. New method is the basis for planning the uneven energy consumption of industrial enterprise. Ecological side of the offered method is disclosed. The program module performed the algorithm of the method is described. Positive method tests at the industrial enterprise are shown. The offered method allows optimizing the difference between planned and factual consumption of energy every hour of a day. The conclusion about applicability of the method for addressing economic and ecological challenges is made.

Influence of tumor location on the intensity-modulated radiation therapy plan of helical tomotherapy.

PubMed

Xu, Yingjie; Yan, Hui; Hu, Zhihui; Ma, Pan; Men, Kuo; Huang, Peng; Ren, Wenting; Dai, Jianrong; Li, Yexiong

2017-01-01

Given the design of the Helical TomoTherapy device, the patient's central axis is routinely aligned with the machine's rotational axis to prevent the patient's body from colliding with the machine walls. However, for treatment of tumors located away from the patient's central axis, this position may not be optimal as the adequate radiation dose may not reach the affected site. Our study aimed to investigate the influence of tumor location on dose quality and delivery efficiency of tomotherapy plans. A phantom and 15 patients were selected for this study. Two plans, A and B, were implemented for each case. In plan A, the patient's central axis was aligned with the machine's rotational axis, whereas in plan B, the center of the planning target volume (PTV) was aligned with the machine's rotational axis. Both plans were optimized with the same planning parameters, and the dose quality of the plans was evaluated using dosimetrics. The delivery efficiency was determined from delivery time and monitor units (MUs). A paired t-test or nonparametric Wilcoxon signed-rank test was performed for statistical comparison. In the phantom study, the median delivery times were 358 and 336 seconds for plans A and B, respectively, and this difference was significant (p = 0.005). In the patient study, the median delivery times were 348 and 317 seconds for plans A and B, respectively, and this difference was also significant (p = 0.001). The dose qualities of both plans for each patient were nearly identical. No significant differences were found in the conformal index, heterogeneity index, and mean dose delivered to normal tissue between the plans. Both phantom and patient studies showed that for normal-sized patients, the delivery time reduced as the distance between the PTV and the patient's central axis increased when the PTV center was aligned with the machine axis. In conclusion, aligning the PTV center with the machine's rotational axis by shifting the patient during tomotherapy reduces the delivery time without compromising the dose quality of intensity-modulated radiation therapy. Copyright © 2017 American Association of Medical Dosimetrists. Published by Elsevier Inc. All rights reserved.

Optimization of Deep Drilling Performance--Development and Benchmark Testing of Advanced Diamond Product Drill Bits & HP/HT Fluids to Significantly Improve Rates of Penetration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alan Black; Arnis Judzis

2003-10-01

This document details the progress to date on the OPTIMIZATION OF DEEP DRILLING PERFORMANCE--DEVELOPMENT AND BENCHMARK TESTING OF ADVANCED DIAMOND PRODUCT DRILL BITS AND HP/HT FLUIDS TO SIGNIFICANTLY IMPROVE RATES OF PENETRATION contract for the year starting October 2002 through September 2002. The industry cost shared program aims to benchmark drilling rates of penetration in selected simulated deep formations and to significantly improve ROP through a team development of aggressive diamond product drill bit--fluid system technologies. Overall the objectives are as follows: Phase 1--Benchmark ''best in class'' diamond and other product drilling bits and fluids and develop concepts for amore » next level of deep drilling performance; Phase 2--Develop advanced smart bit--fluid prototypes and test at large scale; and Phase 3--Field trial smart bit--fluid concepts, modify as necessary and commercialize products. Accomplishments to date include the following: 4Q 2002--Project started; Industry Team was assembled; Kick-off meeting was held at DOE Morgantown; 1Q 2003--Engineering meeting was held at Hughes Christensen, The Woodlands Texas to prepare preliminary plans for development and testing and review equipment needs; Operators started sending information regarding their needs for deep drilling challenges and priorities for large-scale testing experimental matrix; Aramco joined the Industry Team as DEA 148 objectives paralleled the DOE project; 2Q 2003--Engineering and planning for high pressure drilling at TerraTek commenced; 3Q 2003--Continuation of engineering and design work for high pressure drilling at TerraTek; Baker Hughes INTEQ drilling Fluids and Hughes Christensen commence planning for Phase 1 testing--recommendations for bits and fluids.« less

Can persuasive messages encourage individuals to create action plans for physical activity?

PubMed

Sweet, Shane N; Brawley, Lawrence R; Hatchell, Alexandra; Gainforth, Heather L; Latimer-Cheung, Amy E

2014-08-01

Given the positive influence of action planning on physical activity, persuasive messages could be designed to promote action planning. The purpose of this paper was to test action planning messages in two studies. Participants were allocated to one of two message groups, reading either a physical activity only or physical activity plus action planning message (Study 1) and either a gain-framed or loss-framed action planning message (Study 2). The percent of individuals who created an action plan and the quality of the plans were evaluated. In Study 1, individuals in the physical activity plus action planning group created as many action plans as the physical activity only group, but their plans were higher quality. In Study 2, Week 2 differences between the gain- and loss-framed message groups were found for action planning. To our knowledge, these studies were the first to investigate message-induced action planning as a behavior. More research is needed to optimize these messages.

SU-F-BRD-07: Fast Monte Carlo-Based Biological Optimization of Proton Therapy Treatment Plans for Thyroid Tumors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wan Chan Tseung, H; Ma, J; Ma, D

2015-06-15

Purpose: To demonstrate the feasibility of fast Monte Carlo (MC) based biological planning for the treatment of thyroid tumors in spot-scanning proton therapy. Methods: Recently, we developed a fast and accurate GPU-based MC simulation of proton transport that was benchmarked against Geant4.9.6 and used as the dose calculation engine in a clinically-applicable GPU-accelerated IMPT optimizer. Besides dose, it can simultaneously score the dose-averaged LET (LETd), which makes fast biological dose (BD) estimates possible. To convert from LETd to BD, we used a linear relation based on cellular irradiation data. Given a thyroid patient with a 93cc tumor volume, we createdmore » a 2-field IMPT plan in Eclipse (Varian Medical Systems). This plan was re-calculated with our MC to obtain the BD distribution. A second 5-field plan was made with our in-house optimizer, using pre-generated MC dose and LETd maps. Constraints were placed to maintain the target dose to within 25% of the prescription, while maximizing the BD. The plan optimization and calculation of dose and LETd maps were performed on a GPU cluster. The conventional IMPT and biologically-optimized plans were compared. Results: The mean target physical and biological doses from our biologically-optimized plan were, respectively, 5% and 14% higher than those from the MC re-calculation of the IMPT plan. Dose sparing to critical structures in our plan was also improved. The biological optimization, including the initial dose and LETd map calculations, can be completed in a clinically viable time (∼30 minutes) on a cluster of 25 GPUs. Conclusion: Taking advantage of GPU acceleration, we created a MC-based, biologically optimized treatment plan for a thyroid patient. Compared to a standard IMPT plan, a 5% increase in the target’s physical dose resulted in ∼3 times as much increase in the BD. Biological planning was thus effective in escalating the target BD.« less

OPTIMIZATION OF MUD HAMMER DRILLING PERFORMANCE - A PROGRAM TO BENCHMARK THE VIABILITY OF ADVANCED MUD HAMMER DRILLING

DOE Office of Scientific and Technical Information (OSTI.GOV)

Arnis Judzis

2003-07-01

This document details the progress to date on the ''OPTIMIZATION OF MUD HAMMER DRILLING PERFORMANCE--A PROGRAM TO BENCHMARK THE VIABILITY OF ADVANCED MUD HAMMER DRILLING'' contract for the quarter starting April 2003 through June 2003. The DOE and TerraTek continue to wait for Novatek on the optimization portion of the testing program (they are completely rebuilding their fluid hammer). Accomplishments included the following: (1) Hughes Christensen has recently expressed interest in the possibility of a program to examine cutter impact testing, which would be useful in a better understanding of the physics of rock impact. Their interest however is notmore » necessarily fluid hammers, but to use the information for drilling bit development. (2) Novatek (cost sharing supplier of tools) has informed the DOE project manager that their tool may not be ready for ''optimization'' testing late summer 2003 (August-September timeframe) as originally anticipated. During 3Q Novatek plans to meet with TerraTek to discuss progress with their tool for 4Q 2003 testing. (3) A task for an addendum to the hammer project related to cutter impact studies was written during 2Q 2003. (4) Smith International internally is upgrading their hammer for the optimization testing phase. One currently known area of improvement is their development program to significantly increase the hammer blow energy.« less

Combined Inter- and Intrafractional Plan Adaptation Using Fraction Partitioning in Magnetic Resonance-guided Radiotherapy Delivery.

PubMed

Lagerwaard, Frank; Bohoudi, Omar; Tetar, Shyama; Admiraal, Marjan A; Rosario, Tezontl S; Bruynzeel, Anna

2018-04-05

Magnetic resonance-guided radiation therapy (MRgRT) not only allows for superior soft-tissue setup and online MR-guidance during delivery but also for inter-fractional plan re-optimization or adaptation. This plan adaptation involves repeat MR imaging, organs at risk (OARs) re-contouring, plan prediction (i.e., recalculating the baseline plan on the anatomy of that moment), plan re-optimization, and plan quality assurance. In contrast, intrafractional plan adaptation cannot be simply performed by pausing delivery at any given moment, adjusting contours, and re-optimization because of the complex and composite nature of deformable dose accumulation. To overcome this limitation, we applied a practical workaround by partitioning treatment fractions, each with half the original fraction dose. In between successive deliveries, the patient remained in the treatment position and all steps of the initial plan adaptation were repeated. Thus, this second re-optimization served as an intrafractional plan adaptation at 50% of the total delivery. The practical feasibility of this partitioning approach was evaluated in a patient treated with MRgRT for locally advanced pancreatic cancer (LAPC). MRgRT was delivered in 40Gy in 10 fractions, with two fractions scheduled successively on each treatment day. The contoured gross tumor volume (GTV) was expanded by 3 mm, excluding parts of the OARs within this expansion to derive the planning target volume for daily re-optimization (PTV OPT ). The baseline GTVV 95%  achieved in this patient was 80.0% to adhere to the high-dose constraints for the duodenum, stomach, and bowel (V 33 Gy <1 cc and V 36 Gy <0.1 cc). Treatment was performed on the MRIdian (ViewRay Inc, Mountain View, USA) using video-assisted breath-hold in shallow inspiration. The dual plan adaptation resulted, for each partitioned fraction, in the generation of Plan PREDICTED1 , Plan RE-OPTIMIZED1  (inter-fractional adaptation), Plan PREDICTED2 , and Plan RE-OPTIMIZED2  (intrafractional adaptation). An offline analysis was performed to evaluate the benefit of inter-fractional versus intrafractional plan adaptation with respect to GTV coverage and high-dose OARs sparing for all five partitioned fractions. Interfractional changes in adjacent OARs were substantially larger than intrafractional changes. Mean GTV V 95% was 76.8 ± 1.8% (Plan PREDICTED1 ), 83.4 ± 5.7% (Plan RE-OPTIMIZED1 ), 82.5 ± 4.3% (Plan PREDICTED2 ),and 84.4 ± 4.4% (Plan RE-OPTIMIZED2 ). Both plan re-optimizations appeared important for correcting the inappropriately high duodenal V 33 Gy values of 3.6 cc (Plan PREDICTED1 ) and 3.9 cc (Plan PREDICTED2 ) to 0.2 cc for both re-optimizations. To a smaller extent, this improvement was also observed for V 25 Gy values. For the stomach, bowel, and all other OARs, high and intermediate doses were well below preset constraints, even without re-optimization. The mean delivery time of each daily treatment was 90 minutes. This study presents the clinical application of combined inter-fractional and intrafractional plan adaptation during MRgRT for LAPC using fraction partitioning with successive re-optimization. Whereas, in this study, interfractional plan adaptation appeared to benefit both GTV coverage and OARs sparing, intrafractional adaptation was particularly useful for high-dose OARs sparing. Although all necessary steps lead to a prolonged treatment duration, this may be applied in selected cases where high doses to adjacent OARs are regarded as critical.

Combined Inter- and Intrafractional Plan Adaptation Using Fraction Partitioning in Magnetic Resonance-guided Radiotherapy Delivery

PubMed Central

Bohoudi, Omar; Tetar, Shyama; Admiraal, Marjan A; Rosario, Tezontl S; Bruynzeel, Anna

2018-01-01

Magnetic resonance-guided radiation therapy (MRgRT) not only allows for superior soft-tissue setup and online MR-guidance during delivery but also for inter-fractional plan re-optimization or adaptation. This plan adaptation involves repeat MR imaging, organs at risk (OARs) re-contouring, plan prediction (i.e., recalculating the baseline plan on the anatomy of that moment), plan re-optimization, and plan quality assurance. In contrast, intrafractional plan adaptation cannot be simply performed by pausing delivery at any given moment, adjusting contours, and re-optimization because of the complex and composite nature of deformable dose accumulation. To overcome this limitation, we applied a practical workaround by partitioning treatment fractions, each with half the original fraction dose. In between successive deliveries, the patient remained in the treatment position and all steps of the initial plan adaptation were repeated. Thus, this second re-optimization served as an intrafractional plan adaptation at 50% of the total delivery. The practical feasibility of this partitioning approach was evaluated in a patient treated with MRgRT for locally advanced pancreatic cancer (LAPC). MRgRT was delivered in 40Gy in 10 fractions, with two fractions scheduled successively on each treatment day. The contoured gross tumor volume (GTV) was expanded by 3 mm, excluding parts of the OARs within this expansion to derive the planning target volume for daily re-optimization (PTVOPT). The baseline GTVV95% achieved in this patient was 80.0% to adhere to the high-dose constraints for the duodenum, stomach, and bowel (V33 Gy <1 cc and V36 Gy <0.1 cc). Treatment was performed on the MRIdian (ViewRay Inc, Mountain View, USA) using video-assisted breath-hold in shallow inspiration. The dual plan adaptation resulted, for each partitioned fraction, in the generation of PlanPREDICTED1, PlanRE-OPTIMIZED1 (inter-fractional adaptation), PlanPREDICTED2, and PlanRE-OPTIMIZED2 (intrafractional adaptation). An offline analysis was performed to evaluate the benefit of inter-fractional versus intrafractional plan adaptation with respect to GTV coverage and high-dose OARs sparing for all five partitioned fractions. Interfractional changes in adjacent OARs were substantially larger than intrafractional changes. Mean GTV V95% was 76.8 ± 1.8% (PlanPREDICTED1), 83.4 ± 5.7% (PlanRE-OPTIMIZED1), 82.5 ± 4.3% (PlanPREDICTED2),and 84.4 ± 4.4% (PlanRE-OPTIMIZED2). Both plan re-optimizations appeared important for correcting the inappropriately high duodenal V33 Gy values of 3.6 cc (PlanPREDICTED1) and 3.9 cc (PlanPREDICTED2) to 0.2 cc for both re-optimizations. To a smaller extent, this improvement was also observed for V25 Gy values. For the stomach, bowel, and all other OARs, high and intermediate doses were well below preset constraints, even without re-optimization. The mean delivery time of each daily treatment was 90 minutes. This study presents the clinical application of combined inter-fractional and intrafractional plan adaptation during MRgRT for LAPC using fraction partitioning with successive re-optimization. Whereas, in this study, interfractional plan adaptation appeared to benefit both GTV coverage and OARs sparing, intrafractional adaptation was particularly useful for high-dose OARs sparing. Although all necessary steps lead to a prolonged treatment duration, this may be applied in selected cases where high doses to adjacent OARs are regarded as critical. PMID:29876156

The use and QA of biologically related models for treatment planning: short report of the TG-166 of the therapy physics committee of the AAPM.

PubMed

Allen Li, X; Alber, Markus; Deasy, Joseph O; Jackson, Andrew; Ken Jee, Kyung-Wook; Marks, Lawrence B; Martel, Mary K; Mayo, Charles; Moiseenko, Vitali; Nahum, Alan E; Niemierko, Andrzej; Semenenko, Vladimir A; Yorke, Ellen D

2012-03-01

Treatment planning tools that use biologically related models for plan optimization and/or evaluation are being introduced for clinical use. A variety of dose-response models and quantities along with a series of organ-specific model parameters are included in these tools. However, due to various limitations, such as the limitations of models and available model parameters, the incomplete understanding of dose responses, and the inadequate clinical data, the use of biologically based treatment planning system (BBTPS) represents a paradigm shift and can be potentially dangerous. There will be a steep learning curve for most planners. The purpose of this task group is to address some of these relevant issues before the use of BBTPS becomes widely spread. In this report, the authors (1) discuss strategies, limitations, conditions, and cautions for using biologically based models and parameters in clinical treatment planning; (2) demonstrate the practical use of the three most commonly used commercially available BBTPS and potential dosimetric differences between biologically model based and dose-volume based treatment plan optimization and evaluation; (3) identify the desirable features and future directions in developing BBTPS; and (4) provide general guidelines and methodology for the acceptance testing, commissioning, and routine quality assurance (QA) of BBTPS.

Assessment of the Monitor Unit Objective tool for VMAT in the Eclipse treatment planning system.

PubMed

Jiménez-Puertas, Sara; Sánchez-Artuñedo, David; Hermida-López, Marcelino

2018-01-01

This work aims to achieve the highest possible monitor units (MU) reduction using the MU Objective tool included in the Eclipse treatment planning system, while preserving the plan quality. The treatment planning system Eclipse (Varian Medical Systems, Palo Alto, CA) includes a control mechanism for the number of monitor units of volumetric modulated arc therapy (VMAT) plans, named the MU Objective tool. Forty prostate plans, 20 gynecological plans and 20 head and neck plans designed with VMAT were retrospectively studied. Each plan ( base plan ) was optimized without using the MU Objective tool, and it was re-optimized with different values of the Maximum MU ( MaxMU ) parameter of the MU Objective tool. MU differences were analyzed with a paired samples t -test and changes in plan quality were assessed with a set of parameters for OARs and PTVs. The average relative MU difference [Formula: see text] considering all treatment sites, was the highest when MaxMU  = 400 (-4.2%, p  < 0.001). For prostate plans, the lowest [Formula: see text] was obtained (-3.7%, p  < 0.001). For head and neck plans [Formula: see text] was -7.3% ( p  < 0.001) and for gynecological plans [Formula: see text] was 7.0% ( p  = 0.002). Although similar MU reductions were observed for both sites, for some gynecological plans maximum differences were greater than 10%. All the assessed parameters for PTVs and OARs sparing showed average differences below 2%. For the three studied clinical sites, establishing MaxMU  = 400 led to the optimum MU reduction, maintaining the original dose distribution and dosimetric parameters practically unaltered.

Automated IMRT planning with regional optimization using planning scripts

PubMed Central

Wong, Eugene; Bzdusek, Karl; Lock, Michael; Chen, Jeff Z.

2013-01-01

Intensity‐modulated radiation therapy (IMRT) has become a standard technique in radiation therapy for treating different types of cancers. Various class solutions have been developed for simple cases (e.g., localized prostate, whole breast) to generate IMRT plans efficiently. However, for more complex cases (e.g., head and neck, pelvic nodes), it can be time‐consuming for a planner to generate optimized IMRT plans. To generate optimal plans in these more complex cases which generally have multiple target volumes and organs at risk, it is often required to have additional IMRT optimization structures such as dose limiting ring structures, adjust beam geometry, select inverse planning objectives and associated weights, and additional IMRT objectives to reduce cold and hot spots in the dose distribution. These parameters are generally manually adjusted with a repeated trial and error approach during the optimization process. To improve IMRT planning efficiency in these more complex cases, an iterative method that incorporates some of these adjustment processes automatically in a planning script is designed, implemented, and validated. In particular, regional optimization has been implemented in an iterative way to reduce various hot or cold spots during the optimization process that begins with defining and automatic segmentation of hot and cold spots, introducing new objectives and their relative weights into inverse planning, and turn this into an iterative process with termination criteria. The method has been applied to three clinical sites: prostate with pelvic nodes, head and neck, and anal canal cancers, and has shown to reduce IMRT planning time significantly for clinical applications with improved plan quality. The IMRT planning scripts have been used for more than 500 clinical cases. PACS numbers: 87.55.D, 87.55.de PMID:23318393

Multi-AUV autonomous task planning based on the scroll time domain quantum bee colony optimization algorithm in uncertain environment

PubMed Central

Zhang, Rubo; Yang, Yu

2017-01-01

Research on distributed task planning model for multi-autonomous underwater vehicle (MAUV). A scroll time domain quantum artificial bee colony (STDQABC) optimization algorithm is proposed to solve the multi-AUV optimal task planning scheme. In the uncertain marine environment, the rolling time domain control technique is used to realize a numerical optimization in a narrowed time range. Rolling time domain control is one of the better task planning techniques, which can greatly reduce the computational workload and realize the tradeoff between AUV dynamics, environment and cost. Finally, a simulation experiment was performed to evaluate the distributed task planning performance of the scroll time domain quantum bee colony optimization algorithm. The simulation results demonstrate that the STDQABC algorithm converges faster than the QABC and ABC algorithms in terms of both iterations and running time. The STDQABC algorithm can effectively improve MAUV distributed tasking planning performance, complete the task goal and get the approximate optimal solution. PMID:29186166

Multi-AUV autonomous task planning based on the scroll time domain quantum bee colony optimization algorithm in uncertain environment.

PubMed

Li, Jianjun; Zhang, Rubo; Yang, Yu

2017-01-01

Research on distributed task planning model for multi-autonomous underwater vehicle (MAUV). A scroll time domain quantum artificial bee colony (STDQABC) optimization algorithm is proposed to solve the multi-AUV optimal task planning scheme. In the uncertain marine environment, the rolling time domain control technique is used to realize a numerical optimization in a narrowed time range. Rolling time domain control is one of the better task planning techniques, which can greatly reduce the computational workload and realize the tradeoff between AUV dynamics, environment and cost. Finally, a simulation experiment was performed to evaluate the distributed task planning performance of the scroll time domain quantum bee colony optimization algorithm. The simulation results demonstrate that the STDQABC algorithm converges faster than the QABC and ABC algorithms in terms of both iterations and running time. The STDQABC algorithm can effectively improve MAUV distributed tasking planning performance, complete the task goal and get the approximate optimal solution.

Proceedings of the Aircraft Wake Vortices Conference Held in Washington, DC on October 29 - 31, 1991. Volume 1, Papers 1-29.

DTIC Science & Technology

1992-06-01

Large scale data collection activities began with the installation of several sensor systems at the John F. Kennedy International Airport ( JFK ) in June... airport in 1989 (Figure 2). It assists the controllers in the management of the arrival traffic by the provision of an optimized plan for the incoming...Vzf t GOAL ---- > MINIMIZE jVref -Vesti BY OPTIMIZING SENSOR PARAMETERS AND TAKING IN ACCOUNT CUMBERNESS AND ENVIRONMENTAL CONSTRAINTS AIRPORT TESTS

A fast inverse treatment planning strategy facilitating optimized catheter selection in image-guided high-dose-rate interstitial gynecologic brachytherapy.

PubMed

Guthier, Christian V; Damato, Antonio L; Hesser, Juergen W; Viswanathan, Akila N; Cormack, Robert A

2017-12-01

Interstitial high-dose rate (HDR) brachytherapy is an important therapeutic strategy for the treatment of locally advanced gynecologic (GYN) cancers. The outcome of this therapy is determined by the quality of dose distribution achieved. This paper focuses on a novel yet simple heuristic for catheter selection for GYN HDR brachytherapy and their comparison against state of the art optimization strategies. The proposed technique is intended to act as a decision-supporting tool to select a favorable needle configuration. The presented heuristic for catheter optimization is based on a shrinkage-type algorithm (SACO). It is compared against state of the art planning in a retrospective study of 20 patients who previously received image-guided interstitial HDR brachytherapy using a Syed Neblett template. From those plans, template orientation and position are estimated via a rigid registration of the template with the actual catheter trajectories. All potential straight trajectories intersecting the contoured clinical target volume (CTV) are considered for catheter optimization. Retrospectively generated plans and clinical plans are compared with respect to dosimetric performance and optimization time. All plans were generated with one single run of the optimizer lasting 0.6-97.4 s. Compared to manual optimization, SACO yields a statistically significant (P ≤ 0.05) improved target coverage while at the same time fulfilling all dosimetric constraints for organs at risk (OARs). Comparing inverse planning strategies, dosimetric evaluation for SACO and "hybrid inverse planning and optimization" (HIPO), as gold standard, shows no statistically significant difference (P > 0.05). However, SACO provides the potential to reduce the number of used catheters without compromising plan quality. The proposed heuristic for needle selection provides fast catheter selection with optimization times suited for intraoperative treatment planning. Compared to manual optimization, the proposed methodology results in fewer catheters without a clinically significant loss in plan quality. The proposed approach can be used as a decision support tool that guides the user to find the ideal number and configuration of catheters. © 2017 American Association of Physicists in Medicine.

Guaranteed epsilon-optimal treatment plans with the minimum number of beams for stereotactic body radiation therapy

NASA Astrophysics Data System (ADS)

Yarmand, Hamed; Winey, Brian; Craft, David

2013-09-01

Stereotactic body radiation therapy (SBRT) is characterized by delivering a high amount of dose in a short period of time. In SBRT the dose is delivered using open fields (e.g., beam’s-eye-view) known as ‘apertures’. Mathematical methods can be used for optimizing treatment planning for delivery of sufficient dose to the cancerous cells while keeping the dose to surrounding organs at risk (OARs) minimal. Two important elements of a treatment plan are quality and delivery time. Quality of a plan is measured based on the target coverage and dose to OARs. Delivery time heavily depends on the number of beams used in the plan as the setup times for different beam directions constitute a large portion of the delivery time. Therefore the ideal plan, in which all potential beams can be used, will be associated with a long impractical delivery time. We use the dose to OARs in the ideal plan to find the plan with the minimum number of beams which is guaranteed to be epsilon-optimal (i.e., a predetermined maximum deviation from the ideal plan is guaranteed). Since the treatment plan optimization is inherently a multi-criteria-optimization problem, the planner can navigate the ideal dose distribution Pareto surface and select a plan of desired target coverage versus OARs sparing, and then use the proposed technique to reduce the number of beams while guaranteeing epsilon-optimality. We use mixed integer programming (MIP) for optimization. To reduce the computation time for the resultant MIP, we use two heuristics: a beam elimination scheme and a family of heuristic cuts, known as ‘neighbor cuts’, based on the concept of ‘adjacent beams’. We show the effectiveness of the proposed technique on two clinical cases, a liver and a lung case. Based on our technique we propose an algorithm for fast generation of epsilon-optimal plans.

Optimal Operation and Dispatch of Voltage Regulation Devices Considering High Penetrations of Distributed Photovoltaic Generation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mather, Barry A; Hodge, Brian S; Cho, Gyu-Jung

Voltage regulation devices have been traditionally installed and utilized to support distribution voltages. Installations of distributed energy resources (DERs) in distribution systems are rapidly increasing, and many of these generation resources have variable and uncertain power output. These generators can significantly change the voltage profile for a feeder; therefore, in the distribution system planning stage of the optimal operation and dispatch of voltage regulation devices, possible high penetrations of DERs should be considered. In this paper, we model the IEEE 34-bus test feeder, including all essential equipment. An optimization method is adopted to determine the optimal siting and operation ofmore » the voltage regulation devices in the presence of distributed solar power generation. Finally, we verify the optimal configuration of the entire system through the optimization and simulation results.« less

Lockheed L-1011 Test Station on-board in support of the Adaptive Performance Optimization flight res

NASA Technical Reports Server (NTRS)

1997-01-01

This console and its compliment of computers, monitors and commmunications equipment make up the Research Engineering Test Station, the nerve center for a new aerodynamics experiment being conducted by NASA's Dryden Flight Research Center, Edwards, California. The equipment is installed on a modified Lockheed L-1011 Tristar jetliner operated by Orbital Sciences Corp., of Dulles, Va., for Dryden's Adaptive Performance Optimization project. The experiment seeks to improve the efficiency of long-range jetliners by using small movements of the ailerons to improve the aerodynamics of the wing at cruise conditions. About a dozen research flights in the Adaptive Performance Optimization project are planned over the next two to three years. Improving the aerodynamic efficiency should result in equivalent reductions in fuel usage and costs for airlines operating large, wide-bodied jetliners.

A Multi-Year Plan for Research, Development, and Prototype Testing of Standard Modular Hydropower Technology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, Brennan T.; Welch, Tim; Witt, Adam M.

The Multi-Year Plan for Research, Development, and Prototype Testing of Standard Modular Hydropower Technology (MYRP) presents a strategy for specifying, designing, testing, and demonstrating the efficacy of standard modular hydropower (SMH) as an environmentally compatible and cost-optimized renewable electricity generation technology. The MYRP provides the context, background, and vision for testing the SMH hypothesis: if standardization, modularity, and preservation of stream functionality become essential and fully realized features of hydropower technology, project design, and regulatory processes, they will enable previously unrealized levels of new project development with increased acceptance, reduced costs, increased predictability of outcomes, and increased value to stakeholders.more » To achieve success in this effort, the MYRP outlines a framework of stakeholder-validated criteria, models, design tools, testing facilities, and assessment protocols that will facilitate the development of next-generation hydropower technologies.« less

Hybrid General Pattern Search and Simulated Annealing for Industrail Production Planning Problems

NASA Astrophysics Data System (ADS)

Vasant, P.; Barsoum, N.

2010-06-01

In this paper, the hybridization of GPS (General Pattern Search) method and SA (Simulated Annealing) incorporated in the optimization process in order to look for the global optimal solution for the fitness function and decision variables as well as minimum computational CPU time. The real strength of SA approach been tested in this case study problem of industrial production planning. This is due to the great advantage of SA for being easily escaping from trapped in local minima by accepting up-hill move through a probabilistic procedure in the final stages of optimization process. Vasant [1] in his Ph. D thesis has provided 16 different techniques of heuristic and meta-heuristic in solving industrial production problems with non-linear cubic objective functions, eight decision variables and 29 constraints. In this paper, fuzzy technological problems have been solved using hybrid techniques of general pattern search and simulated annealing. The simulated and computational results are compared to other various evolutionary techniques.

Cooperative optimization of reconfigurable machine tool configurations and production process plan

NASA Astrophysics Data System (ADS)

Xie, Nan; Li, Aiping; Xue, Wei

2012-09-01

The production process plan design and configurations of reconfigurable machine tool (RMT) interact with each other. Reasonable process plans with suitable configurations of RMT help to improve product quality and reduce production cost. Therefore, a cooperative strategy is needed to concurrently solve the above issue. In this paper, the cooperative optimization model for RMT configurations and production process plan is presented. Its objectives take into account both impacts of process and configuration. Moreover, a novel genetic algorithm is also developed to provide optimal or near-optimal solutions: firstly, its chromosome is redesigned which is composed of three parts, operations, process plan and configurations of RMTs, respectively; secondly, its new selection, crossover and mutation operators are also developed to deal with the process constraints from operation processes (OP) graph, otherwise these operators could generate illegal solutions violating the limits; eventually the optimal configurations for RMT under optimal process plan design can be obtained. At last, a manufacturing line case is applied which is composed of three RMTs. It is shown from the case that the optimal process plan and configurations of RMT are concurrently obtained, and the production cost decreases 6.28% and nonmonetary performance increases 22%. The proposed method can figure out both RMT configurations and production process, improve production capacity, functions and equipment utilization for RMT.

The combination of simulation and response methodology and its application in an aggregate production plan

NASA Astrophysics Data System (ADS)

Chen, Zhiming; Feng, Yuncheng

1988-08-01

This paper describes an algorithmic structure for combining simulation and optimization techniques both in theory and practice. Response surface methodology is used to optimize the decision variables in the simulation environment. A simulation-optimization software has been developed and successfully implemented, and its application to an aggregate production planning simulation-optimization model is reported. The model's objective is to minimize the production cost and to generate an optimal production plan and inventory control strategy for an aircraft factory.

Optimization of the scheme for natural ecology planning of urban rivers based on ANP (analytic network process) model.

PubMed

Zhang, Yichuan; Wang, Jiangping

2015-07-01

Rivers serve as a highly valued component in ecosystem and urban infrastructures. River planning should follow basic principles of maintaining or reconstructing the natural landscape and ecological functions of rivers. Optimization of planning scheme is a prerequisite for successful construction of urban rivers. Therefore, relevant studies on optimization of scheme for natural ecology planning of rivers is crucial. In the present study, four planning schemes for Zhaodingpal River in Xinxiang City, Henan Province were included as the objects for optimization. Fourteen factors that influenced the natural ecology planning of urban rivers were selected from five aspects so as to establish the ANP model. The data processing was done using Super Decisions software. The results showed that important degree of scheme 3 was highest. A scientific, reasonable and accurate evaluation of schemes could be made by ANP method on natural ecology planning of urban rivers. This method could be used to provide references for sustainable development and construction of urban rivers. ANP method is also suitable for optimization of schemes for urban green space planning and design.

Development of a new integrated local trajectory planning and tracking control framework for autonomous ground vehicles

NASA Astrophysics Data System (ADS)

Li, Xiaohui; Sun, Zhenping; Cao, Dongpu; Liu, Daxue; He, Hangen

2017-03-01

This study proposes a novel integrated local trajectory planning and tracking control (ILTPTC) framework for autonomous vehicles driving along a reference path with obstacles avoidance. For this ILTPTC framework, an efficient state-space sampling-based trajectory planning scheme is employed to smoothly follow the reference path. A model-based predictive path generation algorithm is applied to produce a set of smooth and kinematically-feasible paths connecting the initial state with the sampling terminal states. A velocity control law is then designed to assign a speed value at each of the points along the generated paths. An objective function considering both safety and comfort performance is carefully formulated for assessing the generated trajectories and selecting the optimal one. For accurately tracking the optimal trajectory while overcoming external disturbances and model uncertainties, a combined feedforward and feedback controller is developed. Both simulation analyses and vehicle testing are performed to verify the effectiveness of the proposed ILTPTC framework, and future research is also briefly discussed.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beltran, C; Kamal, H

Purpose: To provide a multicriteria optimization algorithm for intensity modulated radiation therapy using pencil proton beam scanning. Methods: Intensity modulated radiation therapy using pencil proton beam scanning requires efficient optimization algorithms to overcome the uncertainties in the Bragg peaks locations. This work is focused on optimization algorithms that are based on Monte Carlo simulation of the treatment planning and use the weights and the dose volume histogram (DVH) control points to steer toward desired plans. The proton beam treatment planning process based on single objective optimization (representing a weighted sum of multiple objectives) usually leads to time-consuming iterations involving treatmentmore » planning team members. We proved a time efficient multicriteria optimization algorithm that is developed to run on NVIDIA GPU (Graphical Processing Units) cluster. The multicriteria optimization algorithm running time benefits from up-sampling of the CT voxel size of the calculations without loss of fidelity. Results: We will present preliminary results of Multicriteria optimization for intensity modulated proton therapy based on DVH control points. The results will show optimization results of a phantom case and a brain tumor case. Conclusion: The multicriteria optimization of the intensity modulated radiation therapy using pencil proton beam scanning provides a novel tool for treatment planning. Work support by a grant from Varian Inc.« less

Bee Inspired Novel Optimization Algorithm and Mathematical Model for Effective and Efficient Route Planning in Railway System

PubMed Central

Leong, Kah Huo; Abdul-Rahman, Hamzah; Wang, Chen; Onn, Chiu Chuen

2016-01-01

Railway and metro transport systems (RS) are becoming one of the popular choices of transportation among people, especially those who live in urban cities. Urbanization and increasing population due to rapid development of economy in many cities are leading to a bigger demand for urban rail transit. Despite being a popular variant of Traveling Salesman Problem (TSP), it appears that the universal formula or techniques to solve the problem are yet to be found. This paper aims to develop an optimization algorithm for optimum route selection to multiple destinations in RS before returning to the starting point. Bee foraging behaviour is examined to generate a reliable algorithm in railway TSP. The algorithm is then verified by comparing the results with the exact solutions in 10 test cases, and a numerical case study is designed to demonstrate the application with large size sample. It is tested to be efficient and effective in railway route planning as the tour can be completed within a certain period of time by using minimal resources. The findings further support the reliability of the algorithm and capability to solve the problems with different complexity. This algorithm can be used as a method to assist business practitioners making better decision in route planning. PMID:27930659

Bee Inspired Novel Optimization Algorithm and Mathematical Model for Effective and Efficient Route Planning in Railway System.

PubMed

Leong, Kah Huo; Abdul-Rahman, Hamzah; Wang, Chen; Onn, Chiu Chuen; Loo, Siaw-Chuing

2016-01-01

Railway and metro transport systems (RS) are becoming one of the popular choices of transportation among people, especially those who live in urban cities. Urbanization and increasing population due to rapid development of economy in many cities are leading to a bigger demand for urban rail transit. Despite being a popular variant of Traveling Salesman Problem (TSP), it appears that the universal formula or techniques to solve the problem are yet to be found. This paper aims to develop an optimization algorithm for optimum route selection to multiple destinations in RS before returning to the starting point. Bee foraging behaviour is examined to generate a reliable algorithm in railway TSP. The algorithm is then verified by comparing the results with the exact solutions in 10 test cases, and a numerical case study is designed to demonstrate the application with large size sample. It is tested to be efficient and effective in railway route planning as the tour can be completed within a certain period of time by using minimal resources. The findings further support the reliability of the algorithm and capability to solve the problems with different complexity. This algorithm can be used as a method to assist business practitioners making better decision in route planning.

SU-E-J-193: Feasibility of MRI-Only Based IMRT Planning for Pancreatic Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Prior, P; Botros, M; Chen, X

2014-06-01

Purpose: With the increasing use of MRI simulation and the advent of MRI-guided delivery, it is desirable to use MRI only for treatment planning. In this study, we assess the dosimetric difference between MRI- and CTbased IMRT planning for pancreatic cancer. Methods: Planning CTs and MRIs acquired for a representative pancreatic cancer patient were used. MRI-based planning utilized forced relative electron density (rED) assignment of organ specific values from IRCU report 46, where rED = 1.029 for PTV and a rED = 1.036 for non-specified tissue (NST). Six IMRT plans were generated with clinical dose-volume (DV) constraints using a researchmore » Monaco planning system employing Monte Carlo dose calculation with optional perpendicular magnetic field (MF) of 1.5T. The following five plans were generated and compared with the planning CT: 1.) CT plan with MF and dose recalculation without optimization; 2.) MRI (T2) plan with target and OARs redrawn based on MRI, forced rED, no MF, and recalculation without optimization; 3.) Similar as in 2 but with MF; 4.) MRI plan with MF but without optimization; and 5.) Similar as in 4 but with optimization. Results: Generally, noticeable differences in PTV point doses and DV parameters (DVPs) between the CT-and MRI-based plans with and without the MF were observed. These differences between the optimized plans were generally small, mostly within 2%. Larger differences were observed in point doses and mean doses for certain OARs between the CT and MRI plan, mostly due to differences between image acquisition times. Conclusion: MRI only based IMRT planning for pancreatic cancer is feasible. The differences observed between the optimized CT and MRI plans with or without the MF were practically negligible if excluding the differences between MRI and CT defined structures.« less

Assessment of multi-criteria optimization (MCO) for volumetric modulated arc therapy (VMAT) in hippocampal avoidance whole brain radiation therapy (HA-WBRT).

PubMed

Zieminski, Stephen; Khandekar, Melin; Wang, Yi

2018-03-01

This study compared the dosimetric performance of (a) volumetric modulated arc therapy (VMAT) with standard optimization (STD) and (b) multi-criteria optimization (MCO) to (c) intensity modulated radiation therapy (IMRT) with MCO for hippocampal avoidance whole brain radiation therapy (HA-WBRT) in RayStation treatment planning system (TPS). Ten HA-WBRT patients previously treated with MCO-IMRT or MCO-VMAT on an Elekta Infinity accelerator with Agility multileaf collimators (5-mm leaves) were re-planned for the other two modalities. All patients received 30 Gy in 15 fractions to the planning target volume (PTV), namely, PTV30 expanded with a 2-mm margin from the whole brain excluding hippocampus with margin. The patients all had metastatic lesions (up to 12) of variable sizes and proximity to the hippocampus, treated with an additional 7.5 Gy from a simultaneous integrated boost (SIB) to PTV37.5. The IMRT plans used eight to eleven non-coplanar fields, whereas the VMAT plans used two coplanar full arcs and a vertex half arc. The averaged target coverage, dose to organs-at-risk (OARs) and monitor unit provided by the three modalities were compared, and a Wilcoxon signed-rank test was performed. MCO-VMAT provided statistically significant reduction of D100 of hippocampus compared to STD-VMAT, and Dmax of cochleas compared to MCO-IMRT. With statistical significance, MCO-VMAT improved V30 of PTV30 by 14.2% and 4.8%, respectively, compared to MCO-IMRT and STD-VMAT. It also raised D95 of PTV37.5 by 0.4 Gy compared to both MCO-IMRT and STD-VMAT. Improved plan quality parameters such as a decrease in overall plan Dmax and total monitor units (MU) were also observed for MCO-VMAT. MCO-VMAT is found to be the optimal modality for HA-WBRT in terms of PTV coverage, OAR sparing and delivery efficiency, compared to MCO-IMRT or STD-VMAT. © 2018 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Automated treatment planning for a dedicated multi-source intra-cranial radiosurgery treatment unit accounting for overlapping structures and dose homogeneity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ghobadi, Kimia; Ghaffari, Hamid R.; Aleman, Dionne M.

2013-09-15

Purpose: The purpose of this work is to advance the two-step approach for Gamma Knife{sup ®} Perfexion™ (PFX) optimization to account for dose homogeneity and overlap between the planning target volume (PTV) and organs-at-risk (OARs).Methods: In the first step, a geometry-based algorithm is used to quickly select isocentre locations while explicitly accounting for PTV-OARs overlaps. In this approach, the PTV is divided into subvolumes based on the PTV-OARs overlaps and the distance of voxels to the overlaps. Only a few isocentres are selected in the overlap volume, and a higher number of isocentres are carefully selected among voxels that aremore » immediately close to the overlap volume. In the second step, a convex optimization is solved to find the optimal combination of collimator sizes and their radiation duration for each isocentre location.Results: This two-step approach is tested on seven clinical cases (comprising 11 targets) for which the authors assess coverage, OARs dose, and homogeneity index and relate these parameters to the overlap fraction for each case. In terms of coverage, the mean V{sub 99} for the gross target volume (GTV) was 99.8% while the V{sub 95} for the PTV averaged at 94.6%, thus satisfying the clinical objectives of 99% for GTV and 95% for PTV, respectively. The mean relative dose to the brainstem was 87.7% of the prescription dose (with maximum 108%), while on average, 11.3% of the PTV overlapped with the brainstem. The mean beam-on time per fraction per dose was 8.6 min with calibration dose rate of 3.5 Gy/min, and the computational time averaged at 205 min. Compared with previous work involving single-fraction radiosurgery, the resulting plans were more homogeneous with average homogeneity index of 1.18 compared to 1.47.Conclusions: PFX treatment plans with homogeneous dose distribution can be achieved by inverse planning using geometric isocentre selection and mathematical modeling and optimization techniques. The quality of the obtained treatment plans are clinically satisfactory while the homogeneity index is improved compared to conventional PFX plans.« less

Advantages and limitations of navigation-based multicriteria optimization (MCO) for localized prostate cancer IMRT planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

McGarry, Conor K., E-mail: conor.mcgarry@belfasttrust.hscni.net; Bokrantz, Rasmus; RaySearch Laboratories, Stockholm

2014-10-01

Efficacy of inverse planning is becoming increasingly important for advanced radiotherapy techniques. This study’s aims were to validate multicriteria optimization (MCO) in RayStation (v2.4, RaySearch Laboratories, Sweden) against standard intensity-modulated radiation therapy (IMRT) optimization in Oncentra (v4.1, Nucletron BV, the Netherlands) and characterize dose differences due to conversion of navigated MCO plans into deliverable multileaf collimator apertures. Step-and-shoot IMRT plans were created for 10 patients with localized prostate cancer using both standard optimization and MCO. Acceptable standard IMRT plans with minimal average rectal dose were chosen for comparison with deliverable MCO plans. The trade-off was, for the MCO plans, managedmore » through a user interface that permits continuous navigation between fluence-based plans. Navigated MCO plans were made deliverable at incremental steps along a trajectory between maximal target homogeneity and maximal rectal sparing. Dosimetric differences between navigated and deliverable MCO plans were also quantified. MCO plans, chosen as acceptable under navigated and deliverable conditions resulted in similar rectal sparing compared with standard optimization (33.7 ± 1.8 Gy vs 35.5 ± 4.2 Gy, p = 0.117). The dose differences between navigated and deliverable MCO plans increased as higher priority was placed on rectal avoidance. If the best possible deliverable MCO was chosen, a significant reduction in rectal dose was observed in comparison with standard optimization (30.6 ± 1.4 Gy vs 35.5 ± 4.2 Gy, p = 0.047). Improvements were, however, to some extent, at the expense of less conformal dose distributions, which resulted in significantly higher doses to the bladder for 2 of the 3 tolerance levels. In conclusion, similar IMRT plans can be created for patients with prostate cancer using MCO compared with standard optimization. Limitations exist within MCO regarding conversion of navigated plans to deliverable apertures, particularly for plans that emphasize avoidance of critical structures. Minimizing these differences would result in better quality treatments for patients with prostate cancer who were treated with radiotherapy using MCO plans.« less

Probabilistic cross-link analysis and experiment planning for high-throughput elucidation of protein structure.

PubMed

Ye, Xiaoduan; O'Neil, Patrick K; Foster, Adrienne N; Gajda, Michal J; Kosinski, Jan; Kurowski, Michal A; Bujnicki, Janusz M; Friedman, Alan M; Bailey-Kellogg, Chris

2004-12-01

Emerging high-throughput techniques for the characterization of protein and protein-complex structures yield noisy data with sparse information content, placing a significant burden on computation to properly interpret the experimental data. One such technique uses cross-linking (chemical or by cysteine oxidation) to confirm or select among proposed structural models (e.g., from fold recognition, ab initio prediction, or docking) by testing the consistency between cross-linking data and model geometry. This paper develops a probabilistic framework for analyzing the information content in cross-linking experiments, accounting for anticipated experimental error. This framework supports a mechanism for planning experiments to optimize the information gained. We evaluate potential experiment plans using explicit trade-offs among key properties of practical importance: discriminability, coverage, balance, ambiguity, and cost. We devise a greedy algorithm that considers those properties and, from a large number of combinatorial possibilities, rapidly selects sets of experiments expected to discriminate pairs of models efficiently. In an application to residue-specific chemical cross-linking, we demonstrate the ability of our approach to plan experiments effectively involving combinations of cross-linkers and introduced mutations. We also describe an experiment plan for the bacteriophage lambda Tfa chaperone protein in which we plan dicysteine mutants for discriminating threading models by disulfide formation. Preliminary results from a subset of the planned experiments are consistent and demonstrate the practicality of planning. Our methods provide the experimenter with a valuable tool (available from the authors) for understanding and optimizing cross-linking experiments.

SU-F-T-387: A Novel Optimization Technique for Field in Field (FIF) Chestwall Radiation Therapy Using a Single Plan to Improve Delivery Safety and Treatment Planning Efficiency

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tabibian, A; Kim, A; Rose, J

Purpose: A novel optimization technique was developed for field-in-field (FIF) chestwall radiotherapy using bolus every other day. The dosimetry was compared to currently used optimization. Methods: The prior five patients treated at our clinic to the chestwall and supraclavicular nodes with a mono-isocentric four-field arrangement were selected for this study. The prescription was 5040 cGy in 28 fractions, 5 mm bolus every other day on the tangent fields, 6 and/or 10 MV x-rays, and multileaf collimation.Novelly, tangents FIF segments were forward planned optimized based on the composite bolus and non-bolus dose distribution simultaneously. The prescription was spilt into 14 fractionsmore » for both bolus and non-bolus tangents. The same segments and monitor units were used for the bolus and non-bolus treatment. The plan was optimized until the desired coverage was achieved, minimized 105% hotspots, and a maximum dose of less than 108%. Each tangential field had less than 5 segments.Comparison plans were generated using FIF optimization with the same dosimetric goals, but using only the non-bolus calculation for FIF optimization. The non-bolus fields were then copied and bolus was applied. The same segments and monitor units were used for the bolus and non-bolus segments. Results: The prescription coverage of the chestwall, as defined by RTOG guidelines, was on average 51.8% for the plans that optimized bolus and non-bolus treatments simultaneous (SB) and 43.8% for the plans optimized to the non-bolus treatments (NB). Chestwall coverage of 90% prescription averaged to 80.4% for SB and 79.6% for NB plans. The volume receiving 105% of the prescription was 1.9% for SB and 0.8% for NB plans on average. Conclusion: Simultaneously optimizing for bolus and non-bolus treatments noticeably improves prescription coverage of the chestwall while maintaining similar hotspots and 90% prescription coverage in comparison to optimizing only to non-bolus treatments.« less

SU-F-BRD-08: Guaranteed Epsilon-Optimal Treatment Plans with Minimum Number of Beams for SBRT Using RayStation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yarmand, H; Winey, B; Craft, D

2014-06-15

Purpose: To efficiently find quality-guaranteed treatment plans with the minimum number of beams for stereotactic body radiation therapy using RayStation. Methods: For a pre-specified pool of candidate beams we use RayStation (a treatment planning software for clinical use) to identify the deliverable plan which uses all the beams with the minimum dose to organs at risk (OARs) and dose to the tumor and other structures in specified ranges. Then use the dose matrix information for the generated apertures from RayStation to solve a linear program to find the ideal plan with the same objective and constraints allowing use of allmore » beams. Finally we solve a mixed integer programming formulation of the beam angle optimization problem (BAO) with the objective of minimizing the number of beams while remaining in a predetermined epsilon-optimality of the ideal plan with respect to the dose to OARs. Since the treatment plan optimization is a multicriteria optimization problem, the planner can exploit the multicriteria optimization capability of RayStation to navigate the ideal dose distribution Pareto surface and select a plan of desired target coverage versus OARs sparing, and then use the proposed technique to reduce the number of beams while guaranteeing quality. For the numerical experiments two liver cases and one lung case with 33 non-coplanar beams are considered. Results: The ideal plan uses an impractically large number of beams. The proposed technique reduces the number of beams to the range of practical application (5 to 9 beams) while remaining in the epsilon-optimal range of 1% to 5% optimality gap. Conclusion: The proposed method can be integrated into a general algorithm for fast navigation of the ideal dose distribution Pareto surface and finding the treatment plan with the minimum number of beams, which corresponds to the delivery time, in epsilon-optimality range of the desired ideal plan. The project was supported by the Federal Share of program income earned by Massachusetts General Hospital on C06 CA059267, Proton Therapy Research and Treatment Center and partially by RaySearch Laboratories.« less

Automatic learning-based beam angle selection for thoracic IMRT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Amit, Guy; Marshall, Andrea; Purdie, Thomas G., E-mail: tom.purdie@rmp.uhn.ca

Purpose: The treatment of thoracic cancer using external beam radiation requires an optimal selection of the radiation beam directions to ensure effective coverage of the target volume and to avoid unnecessary treatment of normal healthy tissues. Intensity modulated radiation therapy (IMRT) planning is a lengthy process, which requires the planner to iterate between choosing beam angles, specifying dose–volume objectives and executing IMRT optimization. In thorax treatment planning, where there are no class solutions for beam placement, beam angle selection is performed manually, based on the planner’s clinical experience. The purpose of this work is to propose and study a computationallymore » efficient framework that utilizes machine learning to automatically select treatment beam angles. Such a framework may be helpful for reducing the overall planning workload. Methods: The authors introduce an automated beam selection method, based on learning the relationships between beam angles and anatomical features. Using a large set of clinically approved IMRT plans, a random forest regression algorithm is trained to map a multitude of anatomical features into an individual beam score. An optimization scheme is then built to select and adjust the beam angles, considering the learned interbeam dependencies. The validity and quality of the automatically selected beams evaluated using the manually selected beams from the corresponding clinical plans as the ground truth. Results: The analysis included 149 clinically approved thoracic IMRT plans. For a randomly selected test subset of 27 plans, IMRT plans were generated using automatically selected beams and compared to the clinical plans. The comparison of the predicted and the clinical beam angles demonstrated a good average correspondence between the two (angular distance 16.8° ± 10°, correlation 0.75 ± 0.2). The dose distributions of the semiautomatic and clinical plans were equivalent in terms of primary target volume coverage and organ at risk sparing and were superior over plans produced with fixed sets of common beam angles. The great majority of the automatic plans (93%) were approved as clinically acceptable by three radiation therapy specialists. Conclusions: The results demonstrated the feasibility of utilizing a learning-based approach for automatic selection of beam angles in thoracic IMRT planning. The proposed method may assist in reducing the manual planning workload, while sustaining plan quality.« less

Evaluation of the low-temperature heat-exchanger fouling problem. Phase I report. Literature review and work plan

DOE Office of Scientific and Technical Information (OSTI.GOV)

Butcher, T.A.

1983-05-01

This report describes Phase I of a study of the fouling of condensing heat exchangers in residential oil-fired boiler and furnaces. The first phase consists of a review of available information on soot information in residential systems and the preparation of a work plan for Phase II. In the literature review the effects of burner type, startup and shutdown, time from tuning, fuel quality, combustion chambers, nozzles, and fuel additives are discussed. While data are available on soot emissions with current burners and fuels there are limited data available on advanced burners and degraded fuels with modern burners. The Phasemore » II work will provide an evaluation of the need for the development of advanced burner concepts for oil-fired condensing systems. Planned experimental work includes a furnace draft optimization study, extended fouling tests, a blue flame/yellow flame comparative test, and some degraded fuel teste.« less

Thermal Stability of Al2O3/Silicone Composites as High-Temperature Encapsulants

NASA Astrophysics Data System (ADS)

Yao, Yiying

Underwater gliders are robust and long endurance ocean sampling platforms that are increasingly being deployed in coastal regions. This new environment is characterized by shallow waters and significant currents that can challenge the mobility of these efficient (but traditionally slow moving) vehicles. This dissertation aims to improve the performance of shallow water underwater gliders through path planning. The path planning problem is formulated for a dynamic particle (or "kinematic car") model. The objective is to identify the path which satisfies specified boundary conditions and minimizes a particular cost. Several cost functions are considered. The problem is addressed using optimal control theory. The length scales of interest for path planning are within a few turn radii. First, an approach is developed for planning minimum-time paths, for a fixed speed glider, that are sub-optimal but are guaranteed to be feasible in the presence of unknown time-varying currents. Next the minimum-time problem for a glider with speed controls, that may vary between the stall speed and the maximum speed, is solved. Last, optimal paths that minimize change in depth (equivalently, maximize range) are investigated. Recognizing that path planning alone cannot overcome all of the challenges associated with significant currents and shallow waters, the design of a novel underwater glider with improved capabilities is explored. A glider with a pneumatic buoyancy engine (allowing large, rapid buoyancy changes) and a cylindrical moving mass mechanism (generating large pitch and roll moments) is designed, manufactured, and tested to demonstrate potential improvements in speed and maneuverability.

Electric Grid Expansion Planning with High Levels of Variable Generation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hadley, Stanton W.; You, Shutang; Shankar, Mallikarjun

2016-02-01

Renewables are taking a large proportion of generation capacity in U.S. power grids. As their randomness has increasing influence on power system operation, it is necessary to consider their impact on system expansion planning. To this end, this project studies the generation and transmission expansion co-optimization problem of the US Eastern Interconnection (EI) power grid with a high wind power penetration rate. In this project, the generation and transmission expansion problem for the EI system is modeled as a mixed-integer programming (MIP) problem. This study analyzed a time series creation method to capture the diversity of load and wind powermore » across balancing regions in the EI system. The obtained time series can be easily introduced into the MIP co-optimization problem and then solved robustly through available MIP solvers. Simulation results show that the proposed time series generation method and the expansion co-optimization model and can improve the expansion result significantly after considering the diversity of wind and load across EI regions. The improved expansion plan that combines generation and transmission will aid system planners and policy makers to maximize the social welfare. This study shows that modelling load and wind variations and diversities across balancing regions will produce significantly different expansion result compared with former studies. For example, if wind is modeled in more details (by increasing the number of wind output levels) so that more wind blocks are considered in expansion planning, transmission expansion will be larger and the expansion timing will be earlier. Regarding generation expansion, more wind scenarios will slightly reduce wind generation expansion in the EI system and increase the expansion of other generation such as gas. Also, adopting detailed wind scenarios will reveal that it may be uneconomic to expand transmission networks for transmitting a large amount of wind power through a long distance in the EI system. Incorporating more details of renewables in expansion planning will inevitably increase the computational burden. Therefore, high performance computing (HPC) techniques are urgently needed for power system operation and planning optimization. As a scoping study task, this project tested some preliminary parallel computation techniques such as breaking down the simulation task into several sub-tasks based on chronology splitting or sample splitting, and then assigning these sub-tasks to different cores. Testing results show significant time reduction when a simulation task is split into several sub-tasks for parallel execution.« less

Power Distribution System Planning with GIS Consideration

NASA Astrophysics Data System (ADS)

Wattanasophon, Sirichai; Eua-Arporn, Bundhit

This paper proposes a method for solving radial distribution system planning problems taking into account geographical information. The proposed method can automatically determine appropriate location and size of a substation, routing of feeders, and sizes of conductors while satisfying all constraints, i.e. technical constraints (voltage drop and thermal limit) and geographical constraints (obstacle, existing infrastructure, and high-cost passages). Sequential quadratic programming (SQP) and minimum path algorithm (MPA) are applied to solve the planning problem based on net price value (NPV) consideration. In addition this method integrates planner's experience and optimization process to achieve an appropriate practical solution. The proposed method has been tested with an actual distribution system, from which the results indicate that it can provide satisfactory plans.

Treatment Optimization Using Computed Tomography-Delineated Targets Should be Used for Supraclavicular Irradiation for Breast Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liengsawangwong, Raweewan; Yu, T.-K.; Sun, T.-L.

2007-11-01

Background: The purpose of this study was to determine whether the use of optimized CT treatment planning offered better coverage of axillary level III (LIII)/supraclavicular (SC) targets than the empirically derived dose prescription that are commonly used. Materials/Methods: Thirty-two consecutive breast cancer patients who underwent CT treatment planning of a SC field were evaluated. Each patient was categorized according to body mass index (BMI) classes: normal, overweight, or obese. The SC and LIII nodal beds were contoured, and four treatment plans for each patient were generated. Three of the plans used empiric dose prescriptions, and these were compared with amore » CT-optimized plan. Each plan was evaluated by two criteria: whether 98% of target volume receive >90% of prescribed dose and whether < 5% of the irradiated volume received 105% of prescribed dose. Results: The mean depth of SC and LIII were 3.2 cm (range, 1.4-6.7 cm) and 3.1 (range, 1.7-5.8 cm). The depth of these targets varied according across BMI classes (p = 0.01). Among the four sets of plans, the CT-optimized plans were the most successful at achieving both of the dosimetry objectives for every BMI class (normal BMI, p = .003; overweight BMI, p < .0001; obese BMI, p < .001). Conclusions: Across all BMI classes, routine radiation prescriptions did not optimally cover intended targets for every patient. Optimized CT-based treatment planning generated the most successful plans; therefore, we recommend the use of routine CT simulation and treatment planning of SC fields in breast cancer.« less

Game theory and risk-based leveed river system planning with noncooperation

NASA Astrophysics Data System (ADS)

Hui, Rui; Lund, Jay R.; Madani, Kaveh

2016-01-01

Optimal risk-based levee designs are usually developed for economic efficiency. However, in river systems with multiple levees, the planning and maintenance of different levees are controlled by different agencies or groups. For example, along many rivers, levees on opposite riverbanks constitute a simple leveed river system with each levee designed and controlled separately. Collaborative planning of the two levees can be economically optimal for the whole system. Independent and self-interested landholders on opposite riversides often are willing to separately determine their individual optimal levee plans, resulting in a less efficient leveed river system from an overall society-wide perspective (the tragedy of commons). We apply game theory to simple leveed river system planning where landholders on each riverside independently determine their optimal risk-based levee plans. Outcomes from noncooperative games are analyzed and compared with the overall economically optimal outcome, which minimizes net flood cost system-wide. The system-wide economically optimal solution generally transfers residual flood risk to the lower-valued side of the river, but is often impractical without compensating for flood risk transfer to improve outcomes for all individuals involved. Such compensation can be determined and implemented with landholders' agreements on collaboration to develop an economically optimal plan. By examining iterative multiple-shot noncooperative games with reversible and irreversible decisions, the costs of myopia for the future in making levee planning decisions show the significance of considering the externalities and evolution path of dynamic water resource problems to improve decision-making.

SPIDERplan: A tool to support decision-making in radiation therapy treatment plan assessment.

PubMed

Ventura, Tiago; Lopes, Maria do Carmo; Ferreira, Brigida Costa; Khouri, Leila

2016-01-01

In this work, a graphical method for radiotherapy treatment plan assessment and comparison, named SPIDERplan, is proposed. It aims to support plan approval allowing independent and consistent comparisons of different treatment techniques, algorithms or treatment planning systems. Optimized plans from modern radiotherapy are not easy to evaluate and compare because of their inherent multicriterial nature. The clinical decision on the best treatment plan is mostly based on subjective options. SPIDERplan combines a graphical analysis with a scoring index. Customized radar plots based on the categorization of structures into groups and on the determination of individual structures scores are generated. To each group and structure, an angular amplitude is assigned expressing the clinical importance defined by the radiation oncologist. Completing the graphical evaluation, a global plan score, based on the structures score and their clinical weights, is determined. After a necessary clinical validation of the group weights, SPIDERplan efficacy, to compare and rank different plans, was tested through a planning exercise where plans had been generated for a nasal cavity case using different treatment planning systems. SPIDERplan method was applied to the dose metrics achieved by the nasal cavity test plans. The generated diagrams and scores successfully ranked the plans according to the prescribed dose objectives and constraints and the radiation oncologist priorities, after a necessary clinical validation process. SPIDERplan enables a fast and consistent evaluation of plan quality considering all targets and organs at risk.

The PNC-CAT insertion device beamline at the Advanced Photon Source

NASA Astrophysics Data System (ADS)

Heald, S. M.; Stern, E. A.; Brown, F. C.; Kim, K. H.; Barg, B.; Crozier, E. D.

1996-09-01

The PNC-CAT is a consortium of Pacific Northwest institutions formed to instrument a sector (number 20) at the Advanced Photon Source (APS). Research is planned in a variety of areas, with an emphasis on environmentally based problems. The insertion device beamline is based on the APS undulator A and will be optimized for producing microbeams as well as for applications requiring energy scanning capabilities. This paper describes the basic layout and some special features of the beamline. Two experimental stations are planned: one general purpose and one dedicated to MBE and surface science problems. Both tapered capillaries and Kirkpatrick-Baez optics will be used for producing microbeams, and a large optical bench is planned for the main station to allow for easy accommodation of new optics developments. Design calculations and initial capillary tests indicate that flux densities exceeding 1011 photons/sec/mm2 should be achievable. All major components are under construction or in procurement, and initial testing is planned for late 1996.

Investigating multi-objective fluence and beam orientation IMRT optimization

NASA Astrophysics Data System (ADS)

Potrebko, Peter S.; Fiege, Jason; Biagioli, Matthew; Poleszczuk, Jan

2017-07-01

Radiation Oncology treatment planning requires compromises to be made between clinical objectives that are invariably in conflict. It would be beneficial to have a ‘bird’s-eye-view’ perspective of the full spectrum of treatment plans that represent the possible trade-offs between delivering the intended dose to the planning target volume (PTV) while optimally sparing the organs-at-risk (OARs). In this work, the authors demonstrate Pareto-aware radiotherapy evolutionary treatment optimization (PARETO), a multi-objective tool featuring such bird’s-eye-view functionality, which optimizes fluence patterns and beam angles for intensity-modulated radiation therapy (IMRT) treatment planning. The problem of IMRT treatment plan optimization is managed as a combined monolithic problem, where all beam fluence and angle parameters are treated equally during the optimization. To achieve this, PARETO is built around a powerful multi-objective evolutionary algorithm, called Ferret, which simultaneously optimizes multiple fitness functions that encode the attributes of the desired dose distribution for the PTV and OARs. The graphical interfaces within PARETO provide useful information such as: the convergence behavior during optimization, trade-off plots between the competing objectives, and a graphical representation of the optimal solution database allowing for the rapid exploration of treatment plan quality through the evaluation of dose-volume histograms and isodose distributions. PARETO was evaluated for two relatively complex clinical cases, a paranasal sinus and a pancreas case. The end result of each PARETO run was a database of optimal (non-dominated) treatment plans that demonstrated trade-offs between the OAR and PTV fitness functions, which were all equally good in the Pareto-optimal sense (where no one objective can be improved without worsening at least one other). Ferret was able to produce high quality solutions even though a large number of parameters, such as beam fluence and beam angles, were included in the optimization.

Impact of database quality in knowledge-based treatment planning for prostate cancer.

PubMed

Wall, Phillip D H; Carver, Robert L; Fontenot, Jonas D

2018-03-13

This article investigates dose-volume prediction improvements in a common knowledge-based planning (KBP) method using a Pareto plan database compared with using a conventional, clinical plan database. Two plan databases were created using retrospective, anonymized data of 124 volumetric modulated arc therapy (VMAT) prostate cancer patients. The clinical plan database (CPD) contained planning data from each patient's clinically treated VMAT plan, which were manually optimized by various planners. The multicriteria optimization database (MCOD) contained Pareto-optimal plan data from VMAT plans created using a standardized multicriteria optimization protocol. Overlap volume histograms, incorporating fractional organ at risk volumes only within the treatment fields, were computed for each patient and used to match new patient anatomy to similar database patients. For each database patient, CPD and MCOD KBP predictions were generated for D 10 , D 30 , D 50 , D 65 , and D 80 of the bladder and rectum in a leave-one-out manner. Prediction achievability was evaluated through a replanning study on a subset of 31 randomly selected database patients using the best KBP predictions, regardless of plan database origin, as planning goals. MCOD predictions were significantly lower than CPD predictions for all 5 bladder dose-volumes and rectum D 50 (P = .004) and D 65 (P < .001), whereas CPD predictions for rectum D 10 (P = .005) and D 30 (P < .001) were significantly less than MCOD predictions. KBP predictions were statistically achievable in the replans for all predicted dose-volumes, excluding D 10 of bladder (P = .03) and rectum (P = .04). Compared with clinical plans, replans showed significant average reductions in D mean for bladder (7.8 Gy; P < .001) and rectum (9.4 Gy; P < .001), while maintaining statistically similar planning target volume, femoral head, and penile bulb dose. KBP dose-volume predictions derived from Pareto plans were more optimal overall than those resulting from manually optimized clinical plans, which significantly improved KBP-assisted plan quality. This work investigates how the plan quality of knowledge databases affects the performance and achievability of dose-volume predictions from a common knowledge-based planning approach for prostate cancer. Bladder and rectum dose-volume predictions derived from a database of standardized Pareto-optimal plans were compared with those derived from clinical plans manually designed by various planners. Dose-volume predictions from the Pareto plan database were significantly lower overall than those from the clinical plan database, without compromising achievability. Copyright © 2018 Elsevier Inc. All rights reserved.

SU-E-T-593: Clinical Evaluation of Direct Aperture Optimization in Head/Neck and Prostate IMRT Treatment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hosini, M; GALAL, M; Emam, I

2014-06-01

Purpose: To investigate the planning and dosimetric advantages of direct aperture optimization (DAO) over beam-let optimization in IMRT treatment of head and neck (H/N) and prostate cancers. Methods: Five Head and Neck as well as five prostate patients were planned using the beamlet optimizer in Elekta-Xio ver 4.6 IMRT treatment planning system. Based on our experience in beamlet IMRT optimization, PTVs in H/N plans were prescribed to 70 Gy delivered by 7 fields. While prostate PTVs were prescribed to 76 Gy with 9 fields. In all plans, fields were set to be equally spaced. All cases were re-planed using Directmore » Aperture optimizer in Prowess Panther ver 5.01 IMRT planning system at same configurations and dose constraints. Plans were evaluated according to ICRU criteria, number of segments, number of monitor units and planning time. Results: For H/N plans, the near maximum dose (D2) and the dose that covers 95% D95 of PTV has improved by 4% in DAO. For organs at risk (OAR), DAO reduced the volume covered by 30% (V30) in spinal cord, right parotid, and left parotid by 60%, 54%, and 53% respectively. This considerable dosimetric quality improvement achieved using 25% less planning time and lower number of segments and monitor units by 46% and 51% respectively. In DAO prostate plans, Both D2 and D95 for the PTV were improved by only 2%. The V30 of the right femur, left femur and bladder were improved by 35%, 15% and 3% respectively. On the contrary, the rectum V30 got even worse by 9%. However, number of monitor units, and number of segments decreased by 20% and 25% respectively. Moreover the planning time reduced significantly too. Conclusion: DAO introduces considerable advantages over the beamlet optimization in regards to organs at risk sparing. However, no significant improvement occurred in most studied PTVs.« less

"SABER": A new software tool for radiotherapy treatment plan evaluation.

PubMed

Zhao, Bo; Joiner, Michael C; Orton, Colin G; Burmeister, Jay

2010-11-01

Both spatial and biological information are necessary in order to perform true optimization of a treatment plan and for predicting clinical outcome. The goal of this work is to develop an enhanced treatment plan evaluation tool which incorporates biological parameters and retains spatial dose information. A software system is developed which provides biological plan evaluation with a novel combination of features. It incorporates hyper-radiosensitivity using the induced-repair model and applies the new concept of dose convolution filter (DCF) to simulate dose wash-out effects due to cell migration, bystander effect, and/or tissue motion during treatment. Further, the concept of spatial DVH (sDVH) is introduced to evaluate and potentially optimize the spatial dose distribution in the target volume. Finally, generalized equivalent uniform dose is derived from both the physical dose distribution (gEUD) and the distribution of equivalent dose in 2 Gy fractions (gEUD2) and the software provides three separate models for calculation of tumor control probability (TCP), normal tissue complication probability (NTCP), and probability of uncomplicated tumor control (P+). TCP, NTCP, and P+ are provided as a function of prescribed dose and multivariable TCP, NTCP, and P+ plots are provided to illustrate the dependence on individual parameters used to calculate these quantities. Ten plans from two clinical treatment sites are selected to test the three calculation models provided by this software. By retaining both spatial and biological information about the dose distribution, the software is able to distinguish features of radiotherapy treatment plans not discernible using commercial systems. Plans that have similar DVHs may have different spatial and biological characteristics and the application of novel tools such as sDVH and DCF within the software may substantially change the apparent plan quality or predicted plan metrics such as TCP and NTCP. For the cases examined, both the calculation method and the application of DCF can change the ranking order of competing plans. The voxel-by-voxel TCP model makes it feasible to incorporate spatial variations of clonogen densities (n), radiosensitivities (SF2), and fractionation sensitivities (alpha/beta) as those data become available. The new software incorporates both spatial and biological information into the treatment planning process. The application of multiple methods for the incorporation of biological and spatial information has demonstrated that the order of application of biological models can change the order of plan ranking. Thus, the results of plan evaluation and optimization are dependent not only on the models used but also on the order in which they are applied. This software can help the planner choose more biologically optimal treatment plans and potentially predict treatment outcome more accurately.

Conduct overall test operations and evaluate two Doppler systems to detect, track and measure velocities in aircraft wake vortices

NASA Technical Reports Server (NTRS)

Wilson, D. J.; Krause, M. C.; Craven, C. E.; Edwards, B. B.; Coffey, E. W.; Huang, C. C.; Jetton, J. L.; Morrison, L. K.

1974-01-01

A program plan for system evaluation of the two-dimensional Scanning Laser Doppler System (SLDS) is presented. In order to meet system evaluation and optimization objectives the following tests were conducted: (1) noise tests; (2) wind tests; (3) blower flowfield tests; (4) single unit (1-D) flyby tests; and (5) dual unit (2-D) flyby tests. Test results are reported. The final phase of the program included logistics preparation, equipment interface checkouts, and data processing. It is concluded that the SLDS is capable of accurately tracking aircraft wake vortices from small or large aircraft, and in any type of weather.

Real-time Collision Avoidance and Path Optimizer for Semi-autonomous UAVs.

NASA Astrophysics Data System (ADS)

Hawary, A. F.; Razak, N. A.

2018-05-01

Whilst UAV offers a potentially cheaper and more localized observation platform than current satellite or land-based approaches, it requires an advance path planner to reveal its true potential, particularly in real-time missions. Manual control by human will have limited line-of-sights and prone to errors due to careless and fatigue. A good alternative solution is to equip the UAV with semi-autonomous capabilities that able to navigate via a pre-planned route in real-time fashion. In this paper, we propose an easy-and-practical path optimizer based on the classical Travelling Salesman Problem and adopts a brute force search method to re-optimize the route in the event of collisions using range finder sensor. The former utilizes a Simple Genetic Algorithm and the latter uses Nearest Neighbour algorithm. Both algorithms are combined to optimize the route and avoid collision at once. Although many researchers proposed various path planning algorithms, we find that it is difficult to integrate on a basic UAV model and often lacks of real-time collision detection optimizer. Therefore, we explore a practical benefit from this approach using on-board Arduino and Ardupilot controllers by manually emulating the motion of an actual UAV model prior to test on the flying site. The result showed that the range finder sensor provides a real-time data to the algorithm to find a collision-free path and eventually optimized the route successfully.

SU-E-T-230: Creating a Large Number of Focused Beams with Variable Patient Head Tilt to Improve Dose Fall-Off for Brain Radiosurgery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chiu, J; Ma, L

2015-06-15

Purpose: To develop a treatment delivery and planning strategy by increasing the number of beams to minimize dose to brain tissue surrounding a target, while maximizing dose coverage to the target. Methods: We analyzed 14 different treatment plans via Leksell PFX and 4C. For standardization, single tumor cases were chosen. Original treatment plans were compared with two optimized plans. The number of beams was increased in treatment plans by varying tilt angles of the patient head, while maintaining original isocenter and the beam positions in the x-, y- and z-axes, collimator size, and beam blocking. PFX optimized plans increased beammore » numbers with three pre-set tilt angles, 70, 90, 110, and 4C optimized plans increased beam numbers with tilt angles increasing arbitrarily from range of 30 to 150 degrees. Optimized treatment plans were compared dosimetrically with original treatment plans. Results: Comparing total normal tissue isodose volumes between original and optimized plans, the low-level percentage isodose volumes decreased in all plans. Despite the addition of multiple beams up to a factor of 25, beam-on times for 1 tilt angle versus 3 or more tilt angles were comparable (<1 min.). In 64% (9/14) of the studied cases, the volume percentage decrease by >5%, with the highest value reaching 19%. The addition of more tilt angles correlates to a greater decrease in normal brain irradiated volume. Selectivity and coverage for original and optimized plans remained comparable. Conclusion: Adding large number of additional focused beams with variable patient head tilt shows improvement for dose fall-off for brain radiosurgery. The study demonstrates technical feasibility of adding beams to decrease target volume.« less

Three-Dimensional Path Planning for Uninhabited Combat Aerial Vehicle Based on Predator-Prey Pigeon-Inspired Optimization in Dynamic Environment.

PubMed

Zhang, Bo; Duan, Haibin

2017-01-01

Three-dimension path planning of uninhabited combat aerial vehicle (UCAV) is a complicated optimal problem, which mainly focused on optimizing the flight route considering the different types of constrains under complex combating environment. A novel predator-prey pigeon-inspired optimization (PPPIO) is proposed to solve the UCAV three-dimension path planning problem in dynamic environment. Pigeon-inspired optimization (PIO) is a new bio-inspired optimization algorithm. In this algorithm, map and compass operator model and landmark operator model are used to search the best result of a function. The prey-predator concept is adopted to improve global best properties and enhance the convergence speed. The characteristics of the optimal path are presented in the form of a cost function. The comparative simulation results show that our proposed PPPIO algorithm is more efficient than the basic PIO, particle swarm optimization (PSO), and different evolution (DE) in solving UCAV three-dimensional path planning problems.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ranganathan, V; Kumar, P; Bzdusek, K

Purpose: We propose a novel data-driven method to predict the achievability of clinical objectives upfront before invoking the IMRT optimization. Methods: A new metric called “Geometric Complexity (GC)” is used to estimate the achievability of clinical objectives. Here, GC is the measure of the number of “unmodulated” beamlets or rays that intersect the Region-of-interest (ROI) and the target volume. We first compute the geometric complexity ratio (GCratio) between the GC of a ROI (say, parotid) in a reference plan and the GC of the same ROI in a given plan. The GCratio of a ROI indicates the relative geometric complexitymore » of the ROI as compared to the same ROI in the reference plan. Hence GCratio can be used to predict if a defined clinical objective associated with the ROI can be met by the optimizer for a given case. Basically a higher GCratio indicates a lesser likelihood for the optimizer to achieve the clinical objective defined for a given ROI. Similarly, a lower GCratio indicates a higher likelihood for the optimizer to achieve the clinical objective defined for the given ROI. We have evaluated the proposed method on four Head and Neck cases using Pinnacle3 (version 9.10.0) Treatment Planning System (TPS). Results: Out of the total of 28 clinical objectives from four head and neck cases included in the study, 25 were in agreement with the prediction, which implies an agreement of about 85% between predicted and obtained results. The Pearson correlation test shows a positive correlation between predicted and obtained results (Correlation = 0.82, r2 = 0.64, p < 0.005). Conclusion: The study demonstrates the feasibility of the proposed method in head and neck cases for predicting the achievability of clinical objectives with reasonable accuracy.« less

Social Planning for Small Cities.

ERIC Educational Resources Information Center

Meyers, James

Derived mainly from publications by the League of California Cities, this guide to social planning for small cities presents the following: (1) social planning definitions; (2) a checklist of social planning concerns (provision for: adequate income and economic opportunity; optimal environmental conditions for basic material needs; optimal health…

An Automated Treatment Plan Quality Control Tool for Intensity-Modulated Radiation Therapy Using a Voxel-Weighting Factor-Based Re-Optimization Algorithm.

PubMed

Song, Ting; Li, Nan; Zarepisheh, Masoud; Li, Yongbao; Gautier, Quentin; Zhou, Linghong; Mell, Loren; Jiang, Steve; Cerviño, Laura

2016-01-01

Intensity-modulated radiation therapy (IMRT) currently plays an important role in radiotherapy, but its treatment plan quality can vary significantly among institutions and planners. Treatment plan quality control (QC) is a necessary component for individual clinics to ensure that patients receive treatments with high therapeutic gain ratios. The voxel-weighting factor-based plan re-optimization mechanism has been proved able to explore a larger Pareto surface (solution domain) and therefore increase the possibility of finding an optimal treatment plan. In this study, we incorporated additional modules into an in-house developed voxel weighting factor-based re-optimization algorithm, which was enhanced as a highly automated and accurate IMRT plan QC tool (TPS-QC tool). After importing an under-assessment plan, the TPS-QC tool was able to generate a QC report within 2 minutes. This QC report contains the plan quality determination as well as information supporting the determination. Finally, the IMRT plan quality can be controlled by approving quality-passed plans and replacing quality-failed plans using the TPS-QC tool. The feasibility and accuracy of the proposed TPS-QC tool were evaluated using 25 clinically approved cervical cancer patient IMRT plans and 5 manually created poor-quality IMRT plans. The results showed high consistency between the QC report quality determinations and the actual plan quality. In the 25 clinically approved cases that the TPS-QC tool identified as passed, a greater difference could be observed for dosimetric endpoints for organs at risk (OAR) than for planning target volume (PTV), implying that better dose sparing could be achieved in OAR than in PTV. In addition, the dose-volume histogram (DVH) curves of the TPS-QC tool re-optimized plans satisfied the dosimetric criteria more frequently than did the under-assessment plans. In addition, the criteria for unsatisfied dosimetric endpoints in the 5 poor-quality plans could typically be satisfied when the TPS-QC tool generated re-optimized plans without sacrificing other dosimetric endpoints. In addition to its feasibility and accuracy, the proposed TPS-QC tool is also user-friendly and easy to operate, both of which are necessary characteristics for clinical use.

A study of optimization techniques in HDR brachytherapy for the prostate

NASA Astrophysics Data System (ADS)

Pokharel, Ghana Shyam

Several studies carried out thus far are in favor of dose escalation to the prostate gland to have better local control of the disease. But optimal way of delivery of higher doses of radiation therapy to the prostate without hurting neighboring critical structures is still debatable. In this study, we proposed that real time high dose rate (HDR) brachytherapy with highly efficient and effective optimization could be an alternative means of precise delivery of such higher doses. This approach of delivery eliminates the critical issues such as treatment setup uncertainties and target localization as in external beam radiation therapy. Likewise, dosimetry in HDR brachytherapy is not influenced by organ edema and potential source migration as in permanent interstitial implants. Moreover, the recent report of radiobiological parameters further strengthen the argument of using hypofractionated HDR brachytherapy for the management of prostate cancer. Firstly, we studied the essential features and requirements of real time HDR brachytherapy treatment planning system. Automating catheter reconstruction with fast editing tools, fast yet accurate dose engine, robust and fast optimization and evaluation engine are some of the essential requirements for such procedures. Moreover, in most of the cases we performed, treatment plan optimization took significant amount of time of overall procedure. So, making treatment plan optimization automatic or semi-automatic with sufficient speed and accuracy was the goal of the remaining part of the project. Secondly, we studied the role of optimization function and constraints in overall quality of optimized plan. We have studied the gradient based deterministic algorithm with dose volume histogram (DVH) and more conventional variance based objective functions for optimization. In this optimization strategy, the relative weight of particular objective in aggregate objective function signifies its importance with respect to other objectives. Based on our study, DVH based objective function performed better than traditional variance based objective function in creating a clinically acceptable plan when executed under identical conditions. Thirdly, we studied the multiobjective optimization strategy using both DVH and variance based objective functions. The optimization strategy was to create several Pareto optimal solutions by scanning the clinically relevant part of the Pareto front. This strategy was adopted to decouple optimization from decision such that user could select final solution from the pool of alternative solutions based on his/her clinical goals. The overall quality of treatment plan improved using this approach compared to traditional class solution approach. In fact, the final optimized plan selected using decision engine with DVH based objective was comparable to typical clinical plan created by an experienced physicist. Next, we studied the hybrid technique comprising both stochastic and deterministic algorithm to optimize both dwell positions and dwell times. The simulated annealing algorithm was used to find optimal catheter distribution and the DVH based algorithm was used to optimize 3D dose distribution for given catheter distribution. This unique treatment planning and optimization tool was capable of producing clinically acceptable highly reproducible treatment plans in clinically reasonable time. As this algorithm was able to create clinically acceptable plans within clinically reasonable time automatically, it is really appealing for real time procedures. Next, we studied the feasibility of multiobjective optimization using evolutionary algorithm for real time HDR brachytherapy for the prostate. The algorithm with properly tuned algorithm specific parameters was able to create clinically acceptable plans within clinically reasonable time. However, the algorithm was let to run just for limited number of generations not considered optimal, in general, for such algorithms. This was done to keep time window desirable for real time procedures. Therefore, it requires further study with improved conditions to realize the full potential of the algorithm.

Mod-2 wind turbine project assessment and cluster test plans

NASA Technical Reports Server (NTRS)

Gordon, L. H.

1982-01-01

An assessment of the Mod-2 Wind Turbine project is presented based on initial goals and present results. Specifically, the Mod-2 background, project flow, and a chronology of events/results leading to Mod-2 acceptance is presented. After checkout/acceptance of the three operating turbines, NASA/LeRC will continue management of a two year test program performed at the DOE Goodnoe Hills test site. This test program is expected to yield data necessary for the continued development and optimization of wind energy systems. These test activities, the implementation of, and the results to date are also presented.

The economics of personalized medicine: commercialization as a driver of return on investment.

PubMed

Keeling, Peter; Roth, Mollie; Zietlow, Tom

2012-09-15

Optimizing commercialization of drugs is the sine qua non of the pharmaceutical industry and intensive work has been done to characterize fully the drivers of drug adoption and understand the resources required to optimize those drivers for full adoption of drugs. Conversely, while the pharmaceutical industry is actively embracing the new personalized medicine (PM) paradigm, much work remains to be done to understand fully what drives adoption of targeted therapies and how to resource those drivers appropriately. While the industry is slowly learning from its early missteps, progress is still inhibited by a lack of understanding of the specific hurdles that individual development teams face in developing and commercializing targeted therapies and the requirement for budgets specifically aimed at driving test adoption. This article considers the benefits of optimizing commercial planning in the PM space and the potential negative impact in potentially failing to optimize that planning. Real world insights are used to illustrate that a far broader commercial lens is required in the PM space and will touch on functional areas not usually included in the context of 'commercial' decisions. Copyright © 2012 Elsevier B.V. All rights reserved.

Comparison of linear and nonlinear programming approaches for "worst case dose" and "minmax" robust optimization of intensity-modulated proton therapy dose distributions.

PubMed

Zaghian, Maryam; Cao, Wenhua; Liu, Wei; Kardar, Laleh; Randeniya, Sharmalee; Mohan, Radhe; Lim, Gino

2017-03-01

Robust optimization of intensity-modulated proton therapy (IMPT) takes uncertainties into account during spot weight optimization and leads to dose distributions that are resilient to uncertainties. Previous studies demonstrated benefits of linear programming (LP) for IMPT in terms of delivery efficiency by considerably reducing the number of spots required for the same quality of plans. However, a reduction in the number of spots may lead to loss of robustness. The purpose of this study was to evaluate and compare the performance in terms of plan quality and robustness of two robust optimization approaches using LP and nonlinear programming (NLP) models. The so-called "worst case dose" and "minmax" robust optimization approaches and conventional planning target volume (PTV)-based optimization approach were applied to designing IMPT plans for five patients: two with prostate cancer, one with skull-based cancer, and two with head and neck cancer. For each approach, both LP and NLP models were used. Thus, for each case, six sets of IMPT plans were generated and assessed: LP-PTV-based, NLP-PTV-based, LP-worst case dose, NLP-worst case dose, LP-minmax, and NLP-minmax. The four robust optimization methods behaved differently from patient to patient, and no method emerged as superior to the others in terms of nominal plan quality and robustness against uncertainties. The plans generated using LP-based robust optimization were more robust regarding patient setup and range uncertainties than were those generated using NLP-based robust optimization for the prostate cancer patients. However, the robustness of plans generated using NLP-based methods was superior for the skull-based and head and neck cancer patients. Overall, LP-based methods were suitable for the less challenging cancer cases in which all uncertainty scenarios were able to satisfy tight dose constraints, while NLP performed better in more difficult cases in which most uncertainty scenarios were hard to meet tight dose limits. For robust optimization, the worst case dose approach was less sensitive to uncertainties than was the minmax approach for the prostate and skull-based cancer patients, whereas the minmax approach was superior for the head and neck cancer patients. The robustness of the IMPT plans was remarkably better after robust optimization than after PTV-based optimization, and the NLP-PTV-based optimization outperformed the LP-PTV-based optimization regarding robustness of clinical target volume coverage. In addition, plans generated using LP-based methods had notably fewer scanning spots than did those generated using NLP-based methods. © 2017 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Optimal slew path planning for the Sino-French Space-based multiband astronomical Variable Objects Monitor mission

NASA Astrophysics Data System (ADS)

She, Yuchen; Li, Shuang

2018-01-01

The planning algorithm to calculate a satellite's optimal slew trajectory with a given keep-out constraint is proposed. An energy-optimal formulation is proposed for the Space-based multiband astronomical Variable Objects Monitor Mission Analysis and Planning (MAP) system. The innovative point of the proposed planning algorithm lies in that the satellite structure and control limitation are not considered as optimization constraints but are formulated into the cost function. This modification is able to relieve the burden of the optimizer and increases the optimization efficiency, which is the major challenge for designing the MAP system. Mathematical analysis is given to prove that there is a proportional mapping between the formulation and the satellite controller output. Simulations with different scenarios are given to demonstrate the efficiency of the developed algorithm.

Desaturation Patterns Detected by Oximetry in a Large Population of Athletes

ERIC Educational Resources Information Center

Garrido-Chamorro, Raul P.; Gonzalez-Lorenzo, Marta; Sirvent-Belando, Jose; Blasco-Lafarga, Cristina; Roche, Enrique

2009-01-01

Optimal exercise performance in well trained athletes can be affected by arterial oxygen saturation failure. Noninvasive detection of this phenomenon when performing a routine ergometric test can be a valuable tool for subsequent planning of the athlete's training, recovery, and nutrition. Oximetry has been used to this end. The authors studied…

Optimizing Preseason Training Loads in Australian Football.

PubMed

Carey, David L; Crow, Justin; Ong, Kok-Leong; Blanch, Peter; Morris, Meg E; Dascombe, Ben J; Crossley, Kay M

2018-02-01

To investigate whether preseason training plans for Australian football can be computer generated using current training-load guidelines to optimize injury-risk reduction and performance improvement. A constrained optimization problem was defined for daily total and sprint distance, using the preseason schedule of an elite Australian football team as a template. Maximizing total training volume and maximizing Banister-model-projected performance were both considered optimization objectives. Cumulative workload and acute:chronic workload-ratio constraints were placed on training programs to reflect current guidelines on relative and absolute training loads for injury-risk reduction. Optimization software was then used to generate preseason training plans. The optimization framework was able to generate training plans that satisfied relative and absolute workload constraints. Increasing the off-season chronic training loads enabled the optimization algorithm to prescribe higher amounts of "safe" training and attain higher projected performance levels. Simulations showed that using a Banister-model objective led to plans that included a taper in training load prior to competition to minimize fatigue and maximize projected performance. In contrast, when the objective was to maximize total training volume, more frequent training was prescribed to accumulate as much load as possible. Feasible training plans that maximize projected performance and satisfy injury-risk constraints can be automatically generated by an optimization problem for Australian football. The optimization methods allow for individualized training-plan design and the ability to adapt to changing training objectives and different training-load metrics.

A surrogate-based metaheuristic global search method for beam angle selection in radiation treatment planning.

PubMed

Zhang, H H; Gao, S; Chen, W; Shi, L; D'Souza, W D; Meyer, R R

2013-03-21

An important element of radiation treatment planning for cancer therapy is the selection of beam angles (out of all possible coplanar and non-coplanar angles in relation to the patient) in order to maximize the delivery of radiation to the tumor site and minimize radiation damage to nearby organs-at-risk. This category of combinatorial optimization problem is particularly difficult because direct evaluation of the quality of treatment corresponding to any proposed selection of beams requires the solution of a large-scale dose optimization problem involving many thousands of variables that represent doses delivered to volume elements (voxels) in the patient. However, if the quality of angle sets can be accurately estimated without expensive computation, a large number of angle sets can be considered, increasing the likelihood of identifying a very high quality set. Using a computationally efficient surrogate beam set evaluation procedure based on single-beam data extracted from plans employing equallyspaced beams (eplans), we have developed a global search metaheuristic process based on the nested partitions framework for this combinatorial optimization problem. The surrogate scoring mechanism allows us to assess thousands of beam set samples within a clinically acceptable time frame. Tests on difficult clinical cases demonstrate that the beam sets obtained via our method are of superior quality.

A surrogate-based metaheuristic global search method for beam angle selection in radiation treatment planning

PubMed Central

Zhang, H H; Gao, S; Chen, W; Shi, L; D’Souza, W D; Meyer, R R

2013-01-01

An important element of radiation treatment planning for cancer therapy is the selection of beam angles (out of all possible coplanar and non-coplanar angles in relation to the patient) in order to maximize the delivery of radiation to the tumor site and minimize radiation damage to nearby organs-at-risk. This category of combinatorial optimization problem is particularly difficult because direct evaluation of the quality of treatment corresponding to any proposed selection of beams requires the solution of a large-scale dose optimization problem involving many thousands of variables that represent doses delivered to volume elements (voxels) in the patient. However, if the quality of angle sets can be accurately estimated without expensive computation, a large number of angle sets can be considered, increasing the likelihood of identifying a very high quality set. Using a computationally efficient surrogate beam set evaluation procedure based on single-beam data extracted from plans employing equally-spaced beams (eplans), we have developed a global search metaheuristic process based on the Nested Partitions framework for this combinatorial optimization problem. The surrogate scoring mechanism allows us to assess thousands of beam set samples within a clinically acceptable time frame. Tests on difficult clinical cases demonstrate that the beam sets obtained via our method are superior quality. PMID:23459411

Expected treatment dose construction and adaptive inverse planning optimization: Implementation for offline head and neck cancer adaptive radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yan Di; Liang Jian

Purpose: To construct expected treatment dose for adaptive inverse planning optimization, and evaluate it on head and neck (h and n) cancer adaptive treatment modification. Methods: Adaptive inverse planning engine was developed and integrated in our in-house adaptive treatment control system. The adaptive inverse planning engine includes an expected treatment dose constructed using the daily cone beam (CB) CT images in its objective and constrains. Feasibility of the adaptive inverse planning optimization was evaluated retrospectively using daily CBCT images obtained from the image guided IMRT treatment of 19 h and n cancer patients. Adaptive treatment modification strategies with respect tomore » the time and the number of adaptive inverse planning optimization during the treatment course were evaluated using the cumulative treatment dose in organs of interest constructed using all daily CBCT images. Results: Expected treatment dose was constructed to include both the delivered dose, to date, and the estimated dose for the remaining treatment during the adaptive treatment course. It was used in treatment evaluation, as well as in constructing the objective and constraints for adaptive inverse planning optimization. The optimization engine is feasible to perform planning optimization based on preassigned treatment modification schedule. Compared to the conventional IMRT, the adaptive treatment for h and n cancer illustrated clear dose-volume improvement for all critical normal organs. The dose-volume reductions of right and left parotid glands, spine cord, brain stem and mandible were (17 {+-} 6)%, (14 {+-} 6)%, (11 {+-} 6)%, (12 {+-} 8)%, and (5 {+-} 3)% respectively with the single adaptive modification performed after the second treatment week; (24 {+-} 6)%, (22 {+-} 8)%, (21 {+-} 5)%, (19 {+-} 8)%, and (10 {+-} 6)% with three weekly modifications; and (28 {+-} 5)%, (25 {+-} 9)%, (26 {+-} 5)%, (24 {+-} 8)%, and (15 {+-} 9)% with five weekly modifications. Conclusions: Adaptive treatment modification can be implemented including the expected treatment dose in the adaptive inverse planning optimization. The retrospective evaluation results demonstrate that utilizing the weekly adaptive inverse planning optimization, the dose distribution of h and n cancer treatment can be largely improved.« less

OPTIMIZATION OF MUD HAMMER DRILLING PERFORMANCE--A PROGRAM TO BENCHMARK THE VIABILITY OF ADVANCED MUD HAMMER DRILLING

DOE Office of Scientific and Technical Information (OSTI.GOV)

Arnis Judzis

2004-04-01

This document details the progress to date on the OPTIMIZATION OF MUD HAMMER DRILLING PERFORMANCE--A PROGRAM TO BENCHMARK THE VIABILITY OF ADVANCED MUD HAMMER DRILLING contract for the quarter starting January 2004 through March 2004. The DOE and TerraTek continue to wait for Novatek on the optimization portion of the testing program (they are completely rebuilding their fluid hammer). The latest indication is that the Novatek tool would be ready for retesting only 3Q 2004. Smith International's hammer will be tested in April of 2004 (2Q 2004 report). Accomplishments included the following: (1) TerraTek presented a paper for publication inmore » conjunction with a peer review at the GTI Natural Gas Technologies Conference February 10, 2004. Manuscripts and associated presentation material were delivered on schedule. The paper was entitled ''Mud Hammer Performance Optimization''. (2) Shell Exploration and Production continued to express high interest in the ''cutter impact'' testing program Task 8. Hughes Christensen supplied inserts for this testing program. (3) TerraTek hosted an Industry/DOE planning meeting to finalize a testing program for ''Cutter Impact Testing--Understanding Rock Breakage with Bits'' on February 13, 2004. (4) Formal dialogue with Terralog was initiated. Terralog has recently been awarded a DOE contract to model hammer mechanics with TerraTek as a sub-contractor. (5) Novatek provided the DOE with a schedule to complete their new fluid hammer and test it at TerraTek.« less

Plant growth using EMCS hardware on the ISS.

PubMed

Iversen, Tor-Henning; Fossum, Knut R; Svare, Hakon; Johnsson, Anders; Schiller, Peter

2002-07-01

Under separate contracts with ESA (FUMO and ERM Study) and as a link in the development of the European Modular Cultivation System's (EMCS) functionality and biocompatibility, plant studies have been performed at The Plant Biocentre in Trondheim, Norway. The main goal was to test whether the breadboards containing the major components planned for use in the EMCS would be optimal for space experiments with plant material. The test plans and the experimental set-up for the verification of biocompatibility and biological functionality included the use of a few model plant species including cress (Lepidium sativum L.) and Arabidopsis thaliana. The plants were tested at different developmental levels of morphological and physiological complexity (illumination, life support, humidity control, water supply, observation, short- and long-term plant growth experiments and contamination prevention). Results from the tests show that the EMCS concept is useful for long duration plant growth on the ISS.

Clinical implementation of a knowledge based planning tool for prostate VMAT.

PubMed

Powis, Richard; Bird, Andrew; Brennan, Matthew; Hinks, Susan; Newman, Hannah; Reed, Katie; Sage, John; Webster, Gareth

2017-05-08

A knowledge based planning tool has been developed and implemented for prostate VMAT radiotherapy plans providing a target average rectum dose value based on previously achievable values for similar rectum/PTV overlap. The purpose of this planning tool is to highlight sub-optimal clinical plans and to improve plan quality and consistency. A historical cohort of 97 VMAT prostate plans was interrogated using a RayStation script and used to develop a local model for predicting optimum average rectum dose based on individual anatomy. A preliminary validation study was performed whereby historical plans identified as "optimal" and "sub-optimal" by the local model were replanned in a blinded study by four experienced planners and compared to the original clinical plan to assess whether any improvement in rectum dose was observed. The predictive model was then incorporated into a RayStation script and used as part of the clinical planning process. Planners were asked to use the script during planning to provide a patient specific prediction for optimum average rectum dose and to optimise the plan accordingly. Plans identified as "sub-optimal" in the validation study observed a statistically significant improvement in average rectum dose compared to the clinical plan when replanned whereas plans that were identified as "optimal" observed no improvement when replanned. This provided confidence that the local model can identify plans that were suboptimal in terms of rectal sparing. Clinical implementation of the knowledge based planning tool reduced the population-averaged mean rectum dose by 5.6Gy. There was a small but statistically significant increase in total MU and femoral head dose and a reduction in conformity index. These did not affect the clinical acceptability of the plans and no significant changes to other plan quality metrics were observed. The knowledge-based planning tool has enabled substantial reductions in population-averaged mean rectum dose for prostate VMAT patients. This suggests plans are improved when planners receive quantitative feedback on plan quality against historical data.

Multicriteria plan optimization in the hands of physicians: a pilot study in prostate cancer and brain tumors.

PubMed

Müller, Birgit S; Shih, Helen A; Efstathiou, Jason A; Bortfeld, Thomas; Craft, David

2017-11-06

The purpose of this study was to demonstrate the feasibility of physician driven planning in intensity modulated radiotherapy (IMRT) with a multicriteria optimization (MCO) treatment planning system and template based plan optimization. Exploiting the full planning potential of MCO navigation, this alternative planning approach intends to improve planning efficiency and individual plan quality. Planning was retrospectively performed on 12 brain tumor and 10 post-prostatectomy prostate patients previously treated with MCO-IMRT. For each patient, physicians were provided with a template-based generated Pareto surface of optimal plans to navigate, using the beam angles from the original clinical plans. We compared physician generated plans to clinically delivered plans (created by dosimetrists) in terms of dosimetric differences, physician preferences and planning times. Plan qualities were similar, however physician generated and clinical plans differed in the prioritization of clinical goals. Physician derived prostate plans showed significantly better sparing of the high dose rectum and bladder regions (p(D1) < 0.05; D1: dose received by 1% of the corresponding structure). Physicians' brain tumor plans indicated higher doses for targets and brainstem (p(D1) < 0.05). Within blinded plan comparisons physicians preferred the clinical plans more often (brain: 6:3 out of 12, prostate: 2:6 out of 10) (not statistically significant). While times of physician involvement were comparable for prostate planning, the new workflow reduced the average involved time for brain cases by 30%. Planner times were reduced for all cases. Subjective benefits, such as a better understanding of planning situations, were observed by clinicians through the insight into plan optimization and experiencing dosimetric trade-offs. We introduce physician driven planning with MCO for brain and prostate tumors as a feasible planning workflow. The proposed approach standardizes the planning process by utilizing site specific templates and integrates physicians more tightly into treatment planning. Physicians' navigated plan qualities were comparable to the clinical plans. Given the reduction of planning time of the planner and the equal or lower planning time of physicians, this approach has the potential to improve departmental efficiencies.

3D conformal planning using low segment multi-criteria IMRT optimization

PubMed Central

Khan, Fazal; Craft, David

2014-01-01

Purpose To evaluate automated multicriteria optimization (MCO) – designed for intensity modulated radiation therapy (IMRT), but invoked with limited segmentation – to efficiently produce high quality 3D conformal radiation therapy (3D-CRT) plans. Methods Ten patients previously planned with 3D-CRT to various disease sites (brain, breast, lung, abdomen, pelvis), were replanned with a low-segment inverse multicriteria optimized technique. The MCO-3D plans used the same beam geometry of the original 3D plans, but were limited to an energy of 6 MV. The MCO-3D plans were optimized using fluence-based MCO IMRT and then, after MCO navigation, segmented with a low number of segments. The 3D and MCO-3D plans were compared by evaluating mean dose for all structures, D95 (dose that 95% of the structure receives) and homogeneity indexes for targets, D1 and clinically appropriate dose volume objectives for individual organs at risk (OARs), monitor units (MUs), and physician preference. Results The MCO-3D plans reduced the OAR mean doses (41 out of a total of 45 OARs had a mean dose reduction, p<<0.01) and monitor units (seven out of ten plans have reduced MUs; the average reduction is 17%, p=0.08) while maintaining clinical standards on coverage and homogeneity of target volumes. All MCO-3D plans were preferred by physicians over their corresponding 3D plans. Conclusion High quality 3D plans can be produced using MCO-IMRT optimization, resulting in automated field-in-field type plans with good monitor unit efficiency. Adopting this technology in a clinic could improve plan quality, and streamline treatment plan production by utilizing a single system applicable to both IMRT and 3D planning. PMID:25413405

TH-EF-BRB-02: Feasibility of Optimization for Dynamic Trajectory Radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fix, MK; Frei, D; Volken, W

2016-06-15

Purpose: Over the last years, volumetric modulated arc therapy (VMAT) has been widely introduced into clinical routine using a coplanar delivery technique. However, VMAT might be improved by including dynamic couch and collimator rotations, leading to dynamic trajectory radiotherapy (DTRT). In this work the feasibility and the potential benefit of DTRT was investigated. Methods: A general framework for the optimization was developed using the Eclipse Scripting Research Application Programming Interface (ESRAPI). Based on contoured target and organs at risk (OARs), the structures are extracted using the ESRAPI. Sampling potential beam directions, regularly distributed on a sphere using a Fibanocci-lattice, themore » fractional volume-overlap of each OAR and the target is determined and used to establish dynamic gantry-couch movements. Then, for each gantry-couch track the most suitable collimator angle is determined for each control point by optimizing the area between the MLC leaves and the target contour. The resulting dynamic trajectories are used as input to perform the optimization using a research version of the VMAT optimization algorithm and the ESRAPI. The feasibility of this procedure was tested for a clinically motivated head and neck case. Resulting dose distributions for the VMAT plan and for the dynamic trajectory treatment plan were compared based on DVH-parameters. Results: While the DVH for the target is virtually preserved, improvements in maximum dose for the DTRT plan were achieved for all OARs except for the inner-ear, where maximum dose remains the same. The major improvements in maximum dose were 6.5% of the prescribed dose (66 Gy) for the parotid and 5.5% for the myelon and the eye. Conclusion: The result of this work suggests that DTRT has a great potential to reduce dose to OARs with similar target coverage when compared to conventional VMAT treatment plans. This work was supported by Varian Medical Systems. This work was supported by Varian Medical Systems.« less

Complaint-adaptive power density optimization as a tool for HTP-guided steering in deep hyperthermia treatment of pelvic tumors

NASA Astrophysics Data System (ADS)

Canters, R. A. M.; Franckena, M.; van der Zee, J.; Van Rhoon, G. C.

2008-12-01

For an efficient clinical use of HTP (hyperthermia treatment planning), optimization methods are needed. In this study, a complaint-adaptive PD (power density) optimization as a tool for HTP-guided steering in deep hyperthermia of pelvic tumors is developed and tested. PD distribution in patients is predicted using FE-models. Two goal functions, Opt1 and Opt2, are applied to optimize PD distributions. Optimization consists of three steps: initial optimization, adaptive optimization after a first complaint and increasing the weight of a region after recurring complaints. Opt1 initially considers only target PD whereas Opt2 also takes into account hot spots. After patient complaints though, both limit PD in a region. Opt1 and Opt2 are evaluated in a phantom test, using patient models and during hyperthermia treatment. The phantom test and a sensitivity study in ten patient models, show that HTP-guided steering is most effective in peripheral complaint regions. Clinical evaluation in two groups of five patients shows that time between complaints is longer using Opt2 (p = 0.007). However, this does not lead to significantly different temperatures (T50s of 40.3 (Opt1) versus 40.1 °C (Opt2) (p = 0.898)). HTP-guided steering is feasible in terms of PD reduction in complaint regions and in time consumption. Opt2 is preferable in future use, because of better complaint reduction and control.

SU-E-T-562: Motion Tracking Optimization for Conformal Arc Radiotherapy Plans: A QUASAR Phantom Based Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, Z; Wang, I; Yao, R

Purpose: This study is to use plan parameters optimization (Dose rate, collimator angle, couch angle, initial starting phase) to improve the performance of conformal arc radiotherapy plans with motion tracking by increasing the plan performance score (PPS). Methods: Two types of 3D conformal arc plans were created based on QUASAR respiratory motion phantom with spherical and cylindrical targets. Sinusoidal model was applied to the MLC leaves to generate motion tracking plans. A MATLAB program was developed to calculate PPS of each plan (ranges from 0–1) and optimize plan parameters. We first selected the dose rate for motion tracking plans andmore » then used simulated annealing algorithm to search for the combination of the other parameters that resulted in the plan of the maximal PPS. The optimized motion tracking plan was delivered by Varian Truebeam Linac. In-room cameras and stopwatch were used for starting phase selection and synchronization between phantom motion and plan delivery. Gaf-EBT2 dosimetry films were used to measure the dose delivered to the target in QUASAR phantom. Dose profiles and Truebeam trajectory log files were used for plan delivery performance evaluation. Results: For spherical target, the maximal PPS (PPSsph) of the optimized plan was 0.79: (Dose rate: 500MU/min, Collimator: 90°, Couch: +10°, starting phase: 0.83π). For cylindrical target, the maximal PPScyl was 0.75 (Dose rate: 300MU/min, Collimator: 87°, starting phase: 0.97π) with couch at 0°. Differences of dose profiles between motion tracking plans (with the maximal and the minimal PPS) and 3D conformal plans were as follows: PPSsph=0.79: %ΔFWHM: 8.9%, %Dmax: 3.1%; PPSsph=0.52: %ΔFWHM: 10.4%, %Dmax: 6.1%. PPScyl=0.75: %ΔFWHM: 4.7%, %Dmax: 3.6%; PPScyl=0.42: %ΔFWHM: 12.5%, %Dmax: 9.6%. Conclusion: By achieving high plan performance score through parameters optimization, we can improve target dose conformity of motion tracking plan by decreasing total MLC leaf travel distance and leaf speed.« less

SU-F-T-337: Accounting for Patient Motion During Volumetric Modulated Ac Therapy (VMAT) Planning for Post Mastectomy Chest Wall Irradiation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hernandez, M; Fontenot, J; Heins, D

2016-06-15

Purpose: To evaluate two dose optimization strategies for maintaining target volume coverage of inversely-planned post mastectomy radiotherapy (PMRT) plans during patient motion. Methods: Five patients previously treated with VMAT for PMRT at our clinical were randomly selected for this study. For each patient, two plan optimization strategies were compared. Plan 1 was optimized to a volume that included the physician’s planning target volume (PTV) plus an expansion up to 0.3 cm from the bolus surface. Plan 2 was optimized to the PTV plus an expansion up to 0.3 cm from the patient surface (i.e., not extending into the bolus). VMATmore » plans were optimized to deliver 95% of the prescription to 95% of the PTV while sparing organs at risk based on clinical dose limits. PTV coverage was then evaluated following the simulation of patient shifts by 1.0 cm in the anterior and posterior directions using the treatment planning system. Results: Posterior patient shifts produced a difference in D95% of around 11% in both planning approaches from the non-shifted dose distributions. Coverage of the medial and lateral borders of the evaluation volume was reduced in both the posteriorly shifted plans (Plan 1 and Plan 2). Anterior patient shifts affected Plan 2 more than Plan 1 with a difference in D95% of 1% for Plan 1 versus 6% for Plan 2 from the non-shifted dose distributions. The least variation in PTV dose homogeneity for both shifts was obtained with Plan 1. However, all posteriorly shifted plans failed to deliver 95% of the prescription to 95% of the PTV. Whereas, only a few anteriorly shifted plans failed this criteria. Conclusion: The results of this study suggest both planning volume methods are sensitive to patient motion, but that a PTV extended into a bolus volume is slightly more robust for anterior patient shifts.« less

SU-E-T-628: A Cloud Computing Based Multi-Objective Optimization Method for Inverse Treatment Planning.

PubMed

Na, Y; Suh, T; Xing, L

2012-06-01

Multi-objective (MO) plan optimization entails generation of an enormous number of IMRT or VMAT plans constituting the Pareto surface, which presents a computationally challenging task. The purpose of this work is to overcome the hurdle by developing an efficient MO method using emerging cloud computing platform. As a backbone of cloud computing for optimizing inverse treatment planning, Amazon Elastic Compute Cloud with a master node (17.1 GB memory, 2 virtual cores, 420 GB instance storage, 64-bit platform) is used. The master node is able to scale seamlessly a number of working group instances, called workers, based on the user-defined setting account for MO functions in clinical setting. Each worker solved the objective function with an efficient sparse decomposition method. The workers are automatically terminated if there are finished tasks. The optimized plans are archived to the master node to generate the Pareto solution set. Three clinical cases have been planned using the developed MO IMRT and VMAT planning tools to demonstrate the advantages of the proposed method. The target dose coverage and critical structure sparing of plans are comparable obtained using the cloud computing platform are identical to that obtained using desktop PC (Intel Xeon® CPU 2.33GHz, 8GB memory). It is found that the MO planning speeds up the processing of obtaining the Pareto set substantially for both types of plans. The speedup scales approximately linearly with the number of nodes used for computing. With the use of N nodes, the computational time is reduced by the fitting model, 0.2+2.3/N, with r̂2>0.99, on average of the cases making real-time MO planning possible. A cloud computing infrastructure is developed for MO optimization. The algorithm substantially improves the speed of inverse plan optimization. The platform is valuable for both MO planning and future off- or on-line adaptive re-planning. © 2012 American Association of Physicists in Medicine.

SU-F-T-336: A Quick Auto-Planning (QAP) Method for Patient Intensity Modulated Radiotherapy (IMRT)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peng, J; Zhang, Z; Wang, J

2016-06-15

Purpose: The aim of this study is to develop a quick auto-planning system that permits fast patient IMRT planning with conformal dose to the target without manual field alignment and time-consuming dose distribution optimization. Methods: The planning target volume (PTV) of the source and the target patient were projected to the iso-center plane in certain beameye- view directions to derive the 2D projected shapes. Assuming the target interior was isotropic for each beam direction boundary analysis under polar coordinate was performed to map the source shape boundary to the target shape boundary to derive the source-to-target shape mapping function. Themore » derived shape mapping function was used to morph the source beam aperture to the target beam aperture over all segments in each beam direction. The target beam weights were re-calculated to deliver the same dose to the reference point (iso-center) as the source beam did in the source plan. The approach was tested on two rectum patients (one source patient and one target patient). Results: The IMRT planning time by QAP was 5 seconds on a laptop computer. The dose volume histograms and the dose distribution showed the target patient had the similar PTV dose coverage and OAR dose sparing with the source patient. Conclusion: The QAP system can instantly and automatically finish the IMRT planning without dose optimization.« less

WE-AB-303-06: Combining DAO with MV + KV Optimization to Improve Skin Dose Sparing with Real-Time Fluoroscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grelewicz, Z; Wiersma, R

Purpose: Real-time fluoroscopy may allow for improved patient positioning and tumor tracking, particularly in the treatment of lung tumors. In order to mitigate the effects of the imaging dose, previous studies have demonstrated the effect of including both imaging dose and imaging constraints into the inverse treatment planning object function. That method of combined MV+kV optimization may Result in plans with treatment beams chosen to allow for more gentle imaging beam-on times. Direct-aperture optimization (DAO) is also known to produce treatment plans with fluence maps more conducive to lower beam-on times. Therefore, in this work we demonstrate the feasibility ofmore » a combination of DAO and MV+kV optimization for further optimized real-time kV imaging. Methods: Therapeutic and imaging beams were modeled in the EGSnrc Monte Carlo environment, and applied to a patient model for a previously treated lung patient to provide dose influence matrices from DOSXYZnrc. An MV + kV IMRT DAO treatment planning system was developed to compare DAO treatment plans with and without MV+kV optimization. The objective function was optimized using simulated annealing. In order to allow for comparisons between different cases of the stochastically optimized plans, the optimization was repeated twenty times. Results: Across twenty optimizations, combined MV+kV IMRT resulted in an average of 12.8% reduction in peak skin dose. Both non-optimized and MV+kV optimized imaging beams delivered, on average, mean dose of approximately 1 cGy per fraction to the target, with peak doses to target of approximately 6 cGy per fraction. Conclusion: When using DAO, MV+kV optimization is shown to Result in improvements to plan quality in terms of skin dose, when compared to the case of MV optimization with non-optimized kV imaging. The combination of DAO and MV+kV optimization may allow for real-time imaging without excessive imaging dose. Financial support for the work has been provided in part by NIH Grant T32 EB002103, ACS RSG-13-313-01-CCE, and NIH S10 RR021039 and P30 CA14599 grants. The contents of this submission do not necessarily represent the official views of any of the supporting organizations.« less

Backward assembly planning with DFA analysis

NASA Technical Reports Server (NTRS)

Lee, Sukhan (Inventor)

1995-01-01

An assembly planning system that operates based on a recursive decomposition of assembly into subassemblies, and analyzes assembly cost in terms of stability, directionality, and manipulability to guide the generation of preferred assembly plans is presented. The planning in this system incorporates the special processes, such as cleaning, testing, labeling, etc. that must occur during the assembly, and handles nonreversible as well as reversible assembly tasks through backward assembly planning. In order to increase the planning efficiency, the system avoids the analysis of decompositions that do not correspond to feasible assembly tasks. This is achieved by grouping and merging those parts that can not be decomposable at the current stage of backward assembly planning due to the requirement of special processes and the constraint of interconnection feasibility. The invention includes methods of evaluating assembly cost in terms of the number of fixtures (or holding devices) and reorientations required for assembly, through the analysis of stability, directionality, and manipulability. All these factors are used in defining cost and heuristic functions for an AO* search for an optimal plan.

Comparison of DVH parameters and loading patterns of standard loading, manual and inverse optimization for intracavitary brachytherapy on a subset of tandem/ovoid cases.

PubMed

Jamema, Swamidas V; Kirisits, Christian; Mahantshetty, Umesh; Trnkova, Petra; Deshpande, Deepak D; Shrivastava, Shyam K; Pötter, Richard

2010-12-01

Comparison of inverse planning with the standard clinical plan and with the manually optimized plan based on dose-volume parameters and loading patterns. Twenty-eight patients who underwent MRI based HDR brachytherapy for cervix cancer were selected for this study. Three plans were calculated for each patient: (1) standard loading, (2) manual optimized, and (3) inverse optimized. Dosimetric outcomes from these plans were compared based on dose-volume parameters. The ratio of Total Reference Air Kerma of ovoid to tandem (TRAK(O/T)) was used to compare the loading patterns. The volume of HR CTV ranged from 9-68 cc with a mean of 41(±16.2) cc. Mean V100 for standard, manual optimized and inverse plans was found to be not significant (p=0.35, 0.38, 0.4). Dose to bladder (7.8±1.6 Gy) and sigmoid (5.6±1.4 Gy) was high for standard plans; Manual optimization reduced the dose to bladder (7.1±1.7 Gy p=0.006) and sigmoid (4.5±1.0 Gy p=0.005) without compromising the HR CTV coverage. The inverse plan resulted in a significant reduction to bladder dose (6.5±1.4 Gy, p=0.002). TRAK was found to be 0.49(±0.02), 0.44(±0.04) and 0.40(±0.04) cGy m(-2) for the standard loading, manual optimized and inverse plans, respectively. It was observed that TRAK(O/T) was 0.82(±0.05), 1.7(±1.04) and 1.41(±0.93) for standard loading, manual optimized and inverse plans, respectively, while this ratio was 1 for the traditional loading pattern. Inverse planning offers good sparing of critical structures without compromising the target coverage. The average loading pattern of the whole patient cohort deviates from the standard Fletcher loading pattern. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Particle swarm optimizer for weighting factor selection in intensity-modulated radiation therapy optimization algorithms.

PubMed

Yang, Jie; Zhang, Pengcheng; Zhang, Liyuan; Shu, Huazhong; Li, Baosheng; Gui, Zhiguo

2017-01-01

In inverse treatment planning of intensity-modulated radiation therapy (IMRT), the objective function is typically the sum of the weighted sub-scores, where the weights indicate the importance of the sub-scores. To obtain a high-quality treatment plan, the planner manually adjusts the objective weights using a trial-and-error procedure until an acceptable plan is reached. In this work, a new particle swarm optimization (PSO) method which can adjust the weighting factors automatically was investigated to overcome the requirement of manual adjustment, thereby reducing the workload of the human planner and contributing to the development of a fully automated planning process. The proposed optimization method consists of three steps. (i) First, a swarm of weighting factors (i.e., particles) is initialized randomly in the search space, where each particle corresponds to a global objective function. (ii) Then, a plan optimization solver is employed to obtain the optimal solution for each particle, and the values of the evaluation functions used to determine the particle's location and the population global location for the PSO are calculated based on these results. (iii) Next, the weighting factors are updated based on the particle's location and the population global location. Step (ii) is performed alternately with step (iii) until the termination condition is reached. In this method, the evaluation function is a combination of several key points on the dose volume histograms. Furthermore, a perturbation strategy - the crossover and mutation operator hybrid approach - is employed to enhance the population diversity, and two arguments are applied to the evaluation function to improve the flexibility of the algorithm. In this study, the proposed method was used to develop IMRT treatment plans involving five unequally spaced 6MV photon beams for 10 prostate cancer cases. The proposed optimization algorithm yielded high-quality plans for all of the cases, without human planner intervention. A comparison of the results with the optimized solution obtained using a similar optimization model but with human planner intervention revealed that the proposed algorithm produced optimized plans superior to that developed using the manual plan. The proposed algorithm can generate admissible solutions within reasonable computational times and can be used to develop fully automated IMRT treatment planning methods, thus reducing human planners' workloads during iterative processes. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Planning 4D intensity-modulated arc therapy for tumor tracking with a multileaf collimator

NASA Astrophysics Data System (ADS)

Niu, Ying; Betzel, Gregory T.; Yang, Xiaocheng; Gui, Minzhi; Parke, William C.; Yi, Byongyong; Yu, Cedric X.

2017-02-01

This study introduces a practical four-dimensional (4D) planning scheme of IMAT using 4D computed tomography (4D CT) for planning tumor tracking with dynamic multileaf beam collimation. We assume that patients can breathe regularly, i.e. the same way as during 4D CT with an unchanged period and amplitude, and that the start of 4D-IMAT delivery can be synchronized with a designated respiratory phase. Each control point of the IMAT-delivery process can be associated with an image set of 4D CT at a specified respiratory phase. Target is contoured at each respiratory phase without a motion-induced margin. A 3D-IMAT plan is first optimized on a reference-phase image set of 4D CT. Then, based on the projections of the planning target volume in the beam’s eye view at different respiratory phases, a 4D-IMAT plan is generated by transforming the segments of the optimized 3D plan by using a direct aperture deformation method. Compensation for both translational and deformable tumor motion is accomplished, and the smooth delivery of the transformed plan is ensured by forcing connectivity between adjacent angles (control points). It is envisioned that the resultant plans can be delivered accurately using the dose rate regulated tracking method which handles breathing irregularities (Yi et al 2008 Med. Phys. 35 3955-62).This planning process is straightforward and only adds a small step to current clinical 3D planning practice. Our 4D planning scheme was tested on three cases to evaluate dosimetric benefits. The created 4D-IMAT plans showed similar dose distributions as compared with the 3D-IMAT plans on a single static phase, indicating that our method is capable of eliminating the dosimetric effects of breathing induced target motion. Compared to the 3D-IMAT plans with large treatment margins encompassing respiratory motion, our 4D-IMAT plans reduced radiation doses to surrounding normal organs and tissues.

Evaluation of an artificial intelligence guided inverse planning system: clinical case study.

PubMed

Yan, Hui; Yin, Fang-Fang; Willett, Christopher

2007-04-01

An artificial intelligence (AI) guided method for parameter adjustment of inverse planning was implemented on a commercial inverse treatment planning system. For evaluation purpose, four typical clinical cases were tested and the results from both plans achieved by automated and manual methods were compared. The procedure of parameter adjustment mainly consists of three major loops. Each loop is in charge of modifying parameters of one category, which is carried out by a specially customized fuzzy inference system. A physician prescribed multiple constraints for a selected volume were adopted to account for the tradeoff between prescription dose to the PTV and dose-volume constraints for critical organs. The searching process for an optimal parameter combination began with the first constraint, and proceeds to the next until a plan with acceptable dose was achieved. The initial setup of the plan parameters was the same for each case and was adjusted independently by both manual and automated methods. After the parameters of one category were updated, the intensity maps of all fields were re-optimized and the plan dose was subsequently re-calculated. When final plan arrived, the dose statistics were calculated from both plans and compared. For planned target volume (PTV), the dose for 95% volume is up to 10% higher in plans using the automated method than those using the manual method. For critical organs, an average decrease of the plan dose was achieved. However, the automated method cannot improve the plan dose for some critical organs due to limitations of the inference rules currently employed. For normal tissue, there was no significant difference between plan doses achieved by either automated or manual method. With the application of AI-guided method, the basic parameter adjustment task can be accomplished automatically and a comparable plan dose was achieved in comparison with that achieved by the manual method. Future improvements to incorporate case-specific inference rules are essential to fully automate the inverse planning process.

Selective robust optimization: A new intensity-modulated proton therapy optimization strategy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Yupeng; Niemela, Perttu; Siljamaki, Sami

2015-08-15

Purpose: To develop a new robust optimization strategy for intensity-modulated proton therapy as an important step in translating robust proton treatment planning from research to clinical applications. Methods: In selective robust optimization, a worst-case-based robust optimization algorithm is extended, and terms of the objective function are selectively computed from either the worst-case dose or the nominal dose. Two lung cancer cases and one head and neck cancer case were used to demonstrate the practical significance of the proposed robust planning strategy. The lung cancer cases had minimal tumor motion less than 5 mm, and, for the demonstration of the methodology,more » are assumed to be static. Results: Selective robust optimization achieved robust clinical target volume (CTV) coverage and at the same time increased nominal planning target volume coverage to 95.8%, compared to the 84.6% coverage achieved with CTV-based robust optimization in one of the lung cases. In the other lung case, the maximum dose in selective robust optimization was lowered from a dose of 131.3% in the CTV-based robust optimization to 113.6%. Selective robust optimization provided robust CTV coverage in the head and neck case, and at the same time improved controls over isodose distribution so that clinical requirements may be readily met. Conclusions: Selective robust optimization may provide the flexibility and capability necessary for meeting various clinical requirements in addition to achieving the required plan robustness in practical proton treatment planning settings.« less

Exact and explicit optimal solutions for trajectory planning and control of single-link flexible-joint manipulators

NASA Technical Reports Server (NTRS)

Chen, Guanrong

1991-01-01

An optimal trajectory planning problem for a single-link, flexible joint manipulator is studied. A global feedback-linearization is first applied to formulate the nonlinear inequality-constrained optimization problem in a suitable way. Then, an exact and explicit structural formula for the optimal solution of the problem is derived and the solution is shown to be unique. It turns out that the optimal trajectory planning and control can be done off-line, so that the proposed method is applicable to both theoretical analysis and real time tele-robotics control engineering.

Multi-GPU implementation of a VMAT treatment plan optimization algorithm.

PubMed

Tian, Zhen; Peng, Fei; Folkerts, Michael; Tan, Jun; Jia, Xun; Jiang, Steve B

2015-06-01

Volumetric modulated arc therapy (VMAT) optimization is a computationally challenging problem due to its large data size, high degrees of freedom, and many hardware constraints. High-performance graphics processing units (GPUs) have been used to speed up the computations. However, GPU's relatively small memory size cannot handle cases with a large dose-deposition coefficient (DDC) matrix in cases of, e.g., those with a large target size, multiple targets, multiple arcs, and/or small beamlet size. The main purpose of this paper is to report an implementation of a column-generation-based VMAT algorithm, previously developed in the authors' group, on a multi-GPU platform to solve the memory limitation problem. While the column-generation-based VMAT algorithm has been previously developed, the GPU implementation details have not been reported. Hence, another purpose is to present detailed techniques employed for GPU implementation. The authors also would like to utilize this particular problem as an example problem to study the feasibility of using a multi-GPU platform to solve large-scale problems in medical physics. The column-generation approach generates VMAT apertures sequentially by solving a pricing problem (PP) and a master problem (MP) iteratively. In the authors' method, the sparse DDC matrix is first stored on a CPU in coordinate list format (COO). On the GPU side, this matrix is split into four submatrices according to beam angles, which are stored on four GPUs in compressed sparse row format. Computation of beamlet price, the first step in PP, is accomplished using multi-GPUs. A fast inter-GPU data transfer scheme is accomplished using peer-to-peer access. The remaining steps of PP and MP problems are implemented on CPU or a single GPU due to their modest problem scale and computational loads. Barzilai and Borwein algorithm with a subspace step scheme is adopted here to solve the MP problem. A head and neck (H&N) cancer case is then used to validate the authors' method. The authors also compare their multi-GPU implementation with three different single GPU implementation strategies, i.e., truncating DDC matrix (S1), repeatedly transferring DDC matrix between CPU and GPU (S2), and porting computations involving DDC matrix to CPU (S3), in terms of both plan quality and computational efficiency. Two more H&N patient cases and three prostate cases are used to demonstrate the advantages of the authors' method. The authors' multi-GPU implementation can finish the optimization process within ∼ 1 min for the H&N patient case. S1 leads to an inferior plan quality although its total time was 10 s shorter than the multi-GPU implementation due to the reduced matrix size. S2 and S3 yield the same plan quality as the multi-GPU implementation but take ∼4 and ∼6 min, respectively. High computational efficiency was consistently achieved for the other five patient cases tested, with VMAT plans of clinically acceptable quality obtained within 23-46 s. Conversely, to obtain clinically comparable or acceptable plans for all six of these VMAT cases that the authors have tested in this paper, the optimization time needed in a commercial TPS system on CPU was found to be in an order of several minutes. The results demonstrate that the multi-GPU implementation of the authors' column-generation-based VMAT optimization can handle the large-scale VMAT optimization problem efficiently without sacrificing plan quality. The authors' study may serve as an example to shed some light on other large-scale medical physics problems that require multi-GPU techniques.

EUD-based biological optimization for carbon ion therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brüningk, Sarah C., E-mail: sarah.brueningk@icr.ac.uk; Kamp, Florian; Wilkens, Jan J.

2015-11-15

Purpose: Treatment planning for carbon ion therapy requires an accurate modeling of the biological response of each tissue to estimate the clinical outcome of a treatment. The relative biological effectiveness (RBE) accounts for this biological response on a cellular level but does not refer to the actual impact on the organ as a whole. For photon therapy, the concept of equivalent uniform dose (EUD) represents a simple model to take the organ response into account, yet so far no formulation of EUD has been reported that is suitable to carbon ion therapy. The authors introduce the concept of an equivalentmore » uniform effect (EUE) that is directly applicable to both ion and photon therapies and exemplarily implemented it as a basis for biological treatment plan optimization for carbon ion therapy. Methods: In addition to a classical EUD concept, which calculates a generalized mean over the RBE-weighted dose distribution, the authors propose the EUE to simplify the optimization process of carbon ion therapy plans. The EUE is defined as the biologically equivalent uniform effect that yields the same probability of injury as the inhomogeneous effect distribution in an organ. Its mathematical formulation is based on the generalized mean effect using an effect-volume parameter to account for different organ architectures and is thus independent of a reference radiation. For both EUD concepts, quadratic and logistic objective functions are implemented into a research treatment planning system. A flexible implementation allows choosing for each structure between biological effect constraints per voxel and EUD constraints per structure. Exemplary treatment plans are calculated for a head-and-neck patient for multiple combinations of objective functions and optimization parameters. Results: Treatment plans optimized using an EUE-based objective function were comparable to those optimized with an RBE-weighted EUD-based approach. In agreement with previous results from photon therapy, the optimization by biological objective functions resulted in slightly superior treatment plans in terms of final EUD for the organs at risk (OARs) compared to voxel-based optimization approaches. This observation was made independent of the underlying objective function metric. An absolute gain in OAR sparing was observed for quadratic objective functions, whereas intersecting DVHs were found for logistic approaches. Even for considerable under- or overestimations of the used effect- or dose–volume parameters during the optimization, treatment plans were obtained that were of similar quality as the results of a voxel-based optimization. Conclusions: EUD-based optimization with either of the presented concepts can successfully be applied to treatment plan optimization. This makes EUE-based optimization for carbon ion therapy a useful tool to optimize more specifically in the sense of biological outcome while voxel-to-voxel variations of the biological effectiveness are still properly accounted for. This may be advantageous in terms of computational cost during treatment plan optimization but also enables a straight forward comparison of different fractionation schemes or treatment modalities.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wan Chan Tseung, Hok Seum, E-mail: wanchantseung.hok@mayo.edu; Ma, Jiasen; Kreofsky, Cole R.

Purpose: Our aim is to demonstrate the feasibility of fast Monte Carlo (MC)–based inverse biological planning for the treatment of head and neck tumors in spot-scanning proton therapy. Methods and Materials: Recently, a fast and accurate graphics processor unit (GPU)–based MC simulation of proton transport was developed and used as the dose-calculation engine in a GPU-accelerated intensity modulated proton therapy (IMPT) optimizer. Besides dose, the MC can simultaneously score the dose-averaged linear energy transfer (LET{sub d}), which makes biological dose (BD) optimization possible. To convert from LET{sub d} to BD, a simple linear relation was assumed. By use of thismore » novel optimizer, inverse biological planning was applied to 4 patients, including 2 small and 1 large thyroid tumor targets, as well as 1 glioma case. To create these plans, constraints were placed to maintain the physical dose (PD) within 1.25 times the prescription while maximizing target BD. For comparison, conventional intensity modulated radiation therapy (IMRT) and IMPT plans were also created using Eclipse (Varian Medical Systems) in each case. The same critical-structure PD constraints were used for the IMRT, IMPT, and biologically optimized plans. The BD distributions for the IMPT plans were obtained through MC recalculations. Results: Compared with standard IMPT, the biologically optimal plans for patients with small tumor targets displayed a BD escalation that was around twice the PD increase. Dose sparing to critical structures was improved compared with both IMRT and IMPT. No significant BD increase could be achieved for the large thyroid tumor case and when the presence of critical structures mitigated the contribution of additional fields. The calculation of the biologically optimized plans can be completed in a clinically viable time (<30 minutes) on a small 24-GPU system. Conclusions: By exploiting GPU acceleration, MC-based, biologically optimized plans were created for small–tumor target patients. This optimizer will be used in an upcoming feasibility trial on LET{sub d} painting for radioresistant tumors.« less

Dosimetric comparison of helical tomotherapy treatment plans for total marrow irradiation created using GPU and CPU dose calculation engines.

PubMed

Nalichowski, Adrian; Burmeister, Jay

2013-07-01

To compare optimization characteristics, plan quality, and treatment delivery efficiency between total marrow irradiation (TMI) plans using the new TomoTherapy graphic processing unit (GPU) based dose engine and CPU/cluster based dose engine. Five TMI plans created on an anthropomorphic phantom were optimized and calculated with both dose engines. The planning treatment volume (PTV) included all the bones from head to mid femur except for upper extremities. Evaluated organs at risk (OAR) consisted of lung, liver, heart, kidneys, and brain. The following treatment parameters were used to generate the TMI plans: field widths of 2.5 and 5 cm, modulation factors of 2 and 2.5, and pitch of either 0.287 or 0.43. The optimization parameters were chosen based on the PTV and OAR priorities and the plans were optimized with a fixed number of iterations. The PTV constraint was selected to ensure that at least 95% of the PTV received the prescription dose. The plans were evaluated based on D80 and D50 (dose to 80% and 50% of the OAR volume, respectively) and hotspot volumes within the PTVs. Gamma indices (Γ) were also used to compare planar dose distributions between the two modalities. The optimization and dose calculation times were compared between the two systems. The treatment delivery times were also evaluated. The results showed very good dosimetric agreement between the GPU and CPU calculated plans for any of the evaluated planning parameters indicating that both systems converge on nearly identical plans. All D80 and D50 parameters varied by less than 3% of the prescription dose with an average difference of 0.8%. A gamma analysis Γ(3%, 3 mm) < 1 of the GPU plan resulted in over 90% of calculated voxels satisfying Γ < 1 criterion as compared to baseline CPU plan. The average number of voxels meeting the Γ < 1 criterion for all the plans was 97%. In terms of dose optimization/calculation efficiency, there was a 20-fold reduction in planning time with the new GPU system. The average optimization/dose calculation time utilizing the traditional CPU/cluster based system was 579 vs 26.8 min for the GPU based system. There was no difference in the calculated treatment delivery time per fraction. Beam-on time varied based on field width and pitch and ranged between 15 and 28 min. The TomoTherapy GPU based dose engine is capable of calculating TMI treatment plans with plan quality nearly identical to plans calculated using the traditional CPU/cluster based system, while significantly reducing the time required for optimization and dose calculation.

SU-E-T-07: 4DCT Robust Optimization for Esophageal Cancer Using Intensity Modulated Proton Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liao, L; Department of Industrial Engineering, University of Houston, Houston, TX; Yu, J

2015-06-15

Purpose: To develop a 4DCT robust optimization method to reduce the dosimetric impact from respiratory motion in intensity modulated proton therapy (IMPT) for esophageal cancer. Methods: Four esophageal cancer patients were selected for this study. The different phases of CT from a set of 4DCT were incorporated into the worst-case dose distribution robust optimization algorithm. 4DCT robust treatment plans were designed and compared with the conventional non-robust plans. Result doses were calculated on the average and maximum inhale/exhale phases of 4DCT. Dose volume histogram (DVH) band graphic and ΔD95%, ΔD98%, ΔD5%, ΔD2% of CTV between different phases were used tomore » evaluate the robustness of the plans. Results: Compare to the IMPT plans optimized using conventional methods, the 4DCT robust IMPT plans can achieve the same quality in nominal cases, while yield a better robustness to breathing motion. The mean ΔD95%, ΔD98%, ΔD5% and ΔD2% of CTV are 6%, 3.2%, 0.9% and 1% for the robustly optimized plans vs. 16.2%, 11.8%, 1.6% and 3.3% from the conventional non-robust plans. Conclusion: A 4DCT robust optimization method was proposed for esophageal cancer using IMPT. We demonstrate that the 4DCT robust optimization can mitigate the dose deviation caused by the diaphragm motion.« less

SU-E-T-332: Dosimetric Impact of Photon Energy and Treatment Technique When Knowledge Based Auto-Planning Is Implemented in Radiotherapy of Localized Prostate Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Z; Kennedy, A; Larsen, E

2015-06-15

Purpose: The aim of this study was to investigate the dosimetric impact of the combination of photon energy and treatment technique on radiotherapy of localized prostate cancer when knowledge based planning was used. Methods: A total of 16 patients with localized prostate cancer were retrospectively retrieved from database and used for this study. For each patient, four types of treatment plans with different combinations of photon energy (6X and 10X) and treatment techniques (7-field IMRT and 2-arc VMAT) were created using a prostate DVH estimation model in RapidPlan™ and Eclipse treatment planning system (Varian Medical System). For any beam arrangement,more » DVH objectives and weighting priorities were generated based on the geometric relationship between the OAR and PTV. Photon optimization algorithm was used for plan optimization and AAA algorithm was used for final dose calculation. Plans were evaluated in terms of the pre-defined dosimetric endpoints for PTV, rectum, bladder, penile bulb, and femur heads. A Student’s paired t-test was used for statistical analysis and p > 0.05 was considered statistically significant. Results: For PTV, V95 was statistically similar among all four types of plans, though the mean dose of 10X plans was higher than that of 6X plans. VMAT plans showed higher heterogeneity index than IMRT plans. No statistically significant difference in dosimetry metrics was observed for rectum, bladder, and penile bulb among plan types. For left and right femur, VMAT plans had a higher mean dose than IMRT plans regardless of photon energy, whereas the maximum dose was similar. Conclusion: Overall, the dosimetric endpoints were similar regardless of photon energy and treatment techniques when knowledge based auto planning was used. Given the similarity in dosimetry metrics of rectum, bladder, and penile bulb, the genitourinary and gastrointestinal toxicities should be comparable among the selections of photon energy and treatment techniques.« less

Nanodosimetry-Based Plan Optimization for Particle Therapy

PubMed Central

Schulte, Reinhard W.

2015-01-01

Treatment planning for particle therapy is currently an active field of research due uncertainty in how to modify physical dose in order to create a uniform biological dose response in the target. A novel treatment plan optimization strategy based on measurable nanodosimetric quantities rather than biophysical models is proposed in this work. Simplified proton and carbon treatment plans were simulated in a water phantom to investigate the optimization feasibility. Track structures of the mixed radiation field produced at different depths in the target volume were simulated with Geant4-DNA and nanodosimetric descriptors were calculated. The fluences of the treatment field pencil beams were optimized in order to create a mixed field with equal nanodosimetric descriptors at each of the multiple positions in spread-out particle Bragg peaks. For both proton and carbon ion plans, a uniform spatial distribution of nanodosimetric descriptors could be obtained by optimizing opposing-field but not single-field plans. The results obtained indicate that uniform nanodosimetrically weighted plans, which may also be radiobiologically uniform, can be obtained with this approach. Future investigations need to demonstrate that this approach is also feasible for more complicated beam arrangements and that it leads to biologically uniform response in tumor cells and tissues. PMID:26167202

XML technology planning database : lessons learned

NASA Technical Reports Server (NTRS)

Some, Raphael R.; Neff, Jon M.

2005-01-01

A hierarchical Extensible Markup Language(XML) database called XCALIBR (XML Analysis LIBRary) has been developed by Millennium Program to assist in technology investment (ROI) analysis and technology Language Capability the New return on portfolio optimization. The database contains mission requirements and technology capabilities, which are related by use of an XML dictionary. The XML dictionary codifies a standardized taxonomy for space missions, systems, subsystems and technologies. In addition to being used for ROI analysis, the database is being examined for use in project planning, tracking and documentation. During the past year, the database has moved from development into alpha testing. This paper describes the lessons learned during construction and testing of the prototype database and the motivation for moving from an XML taxonomy to a standard XML-based ontology.

Using 3D printed models for planning and guidance during endovascular intervention: a technical advance.

PubMed

Itagaki, Michael W

2015-01-01

Three-dimensional (3D) printing applications in medicine have been limited due to high cost and technical difficulty of creating 3D printed objects. It is not known whether patient-specific, hollow, small-caliber vascular models can be manufactured with 3D printing, and used for small vessel endoluminal testing of devices. Manufacture of anatomically accurate, patient-specific, small-caliber arterial models was attempted using data from a patient's CT scan, free open-source software, and low-cost Internet 3D printing services. Prior to endovascular treatment of a patient with multiple splenic artery aneurysms, a 3D printed model was used preoperatively to test catheter equipment and practice the procedure. A second model was used intraoperatively as a reference. Full-scale plastic models were successfully produced. Testing determined the optimal puncture site for catheter positioning. A guide catheter, base catheter, and microcatheter combination selected during testing was used intraoperatively with success, and the need for repeat angiograms to optimize image orientation was minimized. A difficult and unconventional procedure was successful in treating the aneurysms while preserving splenic function. We conclude that creation of small-caliber vascular models with 3D printing is possible. Free software and low-cost printing services make creation of these models affordable and practical. Models are useful in preoperative planning and intraoperative guidance.

Interactive multiobjective optimization for anatomy-based three-dimensional HDR brachytherapy

NASA Astrophysics Data System (ADS)

Ruotsalainen, Henri; Miettinen, Kaisa; Palmgren, Jan-Erik; Lahtinen, Tapani

2010-08-01

In this paper, we present an anatomy-based three-dimensional dose optimization approach for HDR brachytherapy using interactive multiobjective optimization (IMOO). In brachytherapy, the goals are to irradiate a tumor without causing damage to healthy tissue. These goals are often conflicting, i.e. when one target is optimized the other will suffer, and the solution is a compromise between them. IMOO is capable of handling multiple and strongly conflicting objectives in a convenient way. With the IMOO approach, a treatment planner's knowledge is used to direct the optimization process. Thus, the weaknesses of widely used optimization techniques (e.g. defining weights, computational burden and trial-and-error planning) can be avoided, planning times can be shortened and the number of solutions to be calculated is small. Further, plan quality can be improved by finding advantageous trade-offs between the solutions. In addition, our approach offers an easy way to navigate among the obtained Pareto optimal solutions (i.e. different treatment plans). When considering a simulation model of clinical 3D HDR brachytherapy, the number of variables is significantly smaller compared to IMRT, for example. Thus, when solving the model, the CPU time is relatively short. This makes it possible to exploit IMOO to solve a 3D HDR brachytherapy optimization problem. To demonstrate the advantages of IMOO, two clinical examples of optimizing a gynecologic cervix cancer treatment plan are presented.

Enabling Incremental Query Re-Optimization.

PubMed

Liu, Mengmeng; Ives, Zachary G; Loo, Boon Thau

2016-01-01

As declarative query processing techniques expand to the Web, data streams, network routers, and cloud platforms, there is an increasing need to re-plan execution in the presence of unanticipated performance changes. New runtime information may affect which query plan we prefer to run. Adaptive techniques require innovation both in terms of the algorithms used to estimate costs , and in terms of the search algorithm that finds the best plan. We investigate how to build a cost-based optimizer that recomputes the optimal plan incrementally given new cost information, much as a stream engine constantly updates its outputs given new data. Our implementation especially shows benefits for stream processing workloads. It lays the foundations upon which a variety of novel adaptive optimization algorithms can be built. We start by leveraging the recently proposed approach of formulating query plan enumeration as a set of recursive datalog queries ; we develop a variety of novel optimization approaches to ensure effective pruning in both static and incremental cases. We further show that the lessons learned in the declarative implementation can be equally applied to more traditional optimizer implementations.

Enabling Incremental Query Re-Optimization

PubMed Central

Liu, Mengmeng; Ives, Zachary G.; Loo, Boon Thau

2017-01-01

As declarative query processing techniques expand to the Web, data streams, network routers, and cloud platforms, there is an increasing need to re-plan execution in the presence of unanticipated performance changes. New runtime information may affect which query plan we prefer to run. Adaptive techniques require innovation both in terms of the algorithms used to estimate costs, and in terms of the search algorithm that finds the best plan. We investigate how to build a cost-based optimizer that recomputes the optimal plan incrementally given new cost information, much as a stream engine constantly updates its outputs given new data. Our implementation especially shows benefits for stream processing workloads. It lays the foundations upon which a variety of novel adaptive optimization algorithms can be built. We start by leveraging the recently proposed approach of formulating query plan enumeration as a set of recursive datalog queries; we develop a variety of novel optimization approaches to ensure effective pruning in both static and incremental cases. We further show that the lessons learned in the declarative implementation can be equally applied to more traditional optimizer implementations. PMID:28659658

Geometric Reasoning for Automated Planning

NASA Technical Reports Server (NTRS)

Clement, Bradley J.; Knight, Russell L.; Broderick, Daniel

2012-01-01

An important aspect of mission planning for NASA s operation of the International Space Station is the allocation and management of space for supplies and equipment. The Stowage, Configuration Analysis, and Operations Planning teams collaborate to perform the bulk of that planning. A Geometric Reasoning Engine is developed in a way that can be shared by the teams to optimize item placement in the context of crew planning. The ISS crew spends (at the time of this writing) a third or more of their time moving supplies and equipment around. Better logistical support and optimized packing could make a significant impact on operational efficiency of the ISS. Currently, computational geometry and motion planning do not focus specifically on the optimized orientation and placement of 3D objects based on multiple distance and containment preferences and constraints. The software performs reasoning about the manipulation of 3D solid models in order to maximize an objective function based on distance. It optimizes for 3D orientation and placement. Spatial placement optimization is a general problem and can be applied to object packing or asset relocation.

An Investigation of Generalized Differential Evolution Metaheuristic for Multiobjective Optimal Crop-Mix Planning Decision

PubMed Central

Olugbara, Oludayo

2014-01-01

This paper presents an annual multiobjective crop-mix planning as a problem of concurrent maximization of net profit and maximization of crop production to determine an optimal cropping pattern. The optimal crop production in a particular planting season is a crucial decision making task from the perspectives of economic management and sustainable agriculture. A multiobjective optimal crop-mix problem is formulated and solved using the generalized differential evolution 3 (GDE3) metaheuristic to generate a globally optimal solution. The performance of the GDE3 metaheuristic is investigated by comparing its results with the results obtained using epsilon constrained and nondominated sorting genetic algorithms—being two representatives of state-of-the-art in evolutionary optimization. The performance metrics of additive epsilon, generational distance, inverted generational distance, and spacing are considered to establish the comparability. In addition, a graphical comparison with respect to the true Pareto front for the multiobjective optimal crop-mix planning problem is presented. Empirical results generally show GDE3 to be a viable alternative tool for solving a multiobjective optimal crop-mix planning problem. PMID:24883369

An investigation of generalized differential evolution metaheuristic for multiobjective optimal crop-mix planning decision.

PubMed

Adekanmbi, Oluwole; Olugbara, Oludayo; Adeyemo, Josiah

2014-01-01

This paper presents an annual multiobjective crop-mix planning as a problem of concurrent maximization of net profit and maximization of crop production to determine an optimal cropping pattern. The optimal crop production in a particular planting season is a crucial decision making task from the perspectives of economic management and sustainable agriculture. A multiobjective optimal crop-mix problem is formulated and solved using the generalized differential evolution 3 (GDE3) metaheuristic to generate a globally optimal solution. The performance of the GDE3 metaheuristic is investigated by comparing its results with the results obtained using epsilon constrained and nondominated sorting genetic algorithms-being two representatives of state-of-the-art in evolutionary optimization. The performance metrics of additive epsilon, generational distance, inverted generational distance, and spacing are considered to establish the comparability. In addition, a graphical comparison with respect to the true Pareto front for the multiobjective optimal crop-mix planning problem is presented. Empirical results generally show GDE3 to be a viable alternative tool for solving a multiobjective optimal crop-mix planning problem.

Simultaneous optimization of photons and electrons for mixed beam radiotherapy

NASA Astrophysics Data System (ADS)

Mueller, S.; Fix, M. K.; Joosten, A.; Henzen, D.; Frei, D.; Volken, W.; Kueng, R.; Aebersold, D. M.; Stampanoni, M. F. M.; Manser, P.

2017-07-01

The aim of this work is to develop and investigate an inverse treatment planning process (TPP) for mixed beam radiotherapy (MBRT) capable of performing simultaneous optimization of photon and electron apertures. A simulated annealing based direct aperture optimization (DAO) is implemented to perform simultaneous optimization of photon and electron apertures, both shaped with the photon multileaf collimator (pMLC). Validated beam models are used as input for Monte Carlo dose calculations. Consideration of photon pMLC transmission during DAO and a weight re-optimization of the apertures after deliverable dose calculation are utilized to efficiently reduce the differences between optimized and deliverable dose distributions. The TPP for MBRT is evaluated for an academic situation with a superficial and an enlarged PTV in the depth, a left chest wall case including the internal mammary chain and a squamous cell carcinoma case. Deliverable dose distributions of MBRT plans are compared to those of modulated electron radiotherapy (MERT), photon IMRT and if available to those of clinical VMAT plans. The generated MBRT plans dosimetrically outperform the MERT, photon IMRT and VMAT plans for all investigated situations. For the clinical cases of the left chest wall and the squamous cell carcinoma, the MBRT plans cover the PTV similarly or more homogeneously than the VMAT plans, while OARs are spared considerably better with average reductions of the mean dose to parallel OARs and D 2% to serial OARs by 54% and 26%, respectively. Moreover, the low dose bath expressed as V 10% to normal tissue is substantially reduced by up to 45% compared to the VMAT plans. A TPP for MBRT including simultaneous optimization is successfully implemented and the dosimetric superiority of MBRT plans over MERT, photon IMRT and VMAT plans is demonstrated for academic and clinical situations including superficial targets with and without deep-seated part.

Simultaneous optimization of photons and electrons for mixed beam radiotherapy.

PubMed

Mueller, S; Fix, M K; Joosten, A; Henzen, D; Frei, D; Volken, W; Kueng, R; Aebersold, D M; Stampanoni, M F M; Manser, P

2017-06-26

The aim of this work is to develop and investigate an inverse treatment planning process (TPP) for mixed beam radiotherapy (MBRT) capable of performing simultaneous optimization of photon and electron apertures. A simulated annealing based direct aperture optimization (DAO) is implemented to perform simultaneous optimization of photon and electron apertures, both shaped with the photon multileaf collimator (pMLC). Validated beam models are used as input for Monte Carlo dose calculations. Consideration of photon pMLC transmission during DAO and a weight re-optimization of the apertures after deliverable dose calculation are utilized to efficiently reduce the differences between optimized and deliverable dose distributions. The TPP for MBRT is evaluated for an academic situation with a superficial and an enlarged PTV in the depth, a left chest wall case including the internal mammary chain and a squamous cell carcinoma case. Deliverable dose distributions of MBRT plans are compared to those of modulated electron radiotherapy (MERT), photon IMRT and if available to those of clinical VMAT plans. The generated MBRT plans dosimetrically outperform the MERT, photon IMRT and VMAT plans for all investigated situations. For the clinical cases of the left chest wall and the squamous cell carcinoma, the MBRT plans cover the PTV similarly or more homogeneously than the VMAT plans, while OARs are spared considerably better with average reductions of the mean dose to parallel OARs and D 2% to serial OARs by 54% and 26%, respectively. Moreover, the low dose bath expressed as V 10% to normal tissue is substantially reduced by up to 45% compared to the VMAT plans. A TPP for MBRT including simultaneous optimization is successfully implemented and the dosimetric superiority of MBRT plans over MERT, photon IMRT and VMAT plans is demonstrated for academic and clinical situations including superficial targets with and without deep-seated part.

Including robustness in multi-criteria optimization for intensity-modulated proton therapy

NASA Astrophysics Data System (ADS)

Chen, Wei; Unkelbach, Jan; Trofimov, Alexei; Madden, Thomas; Kooy, Hanne; Bortfeld, Thomas; Craft, David

2012-02-01

We present a method to include robustness in a multi-criteria optimization (MCO) framework for intensity-modulated proton therapy (IMPT). The approach allows one to simultaneously explore the trade-off between different objectives as well as the trade-off between robustness and nominal plan quality. In MCO, a database of plans each emphasizing different treatment planning objectives, is pre-computed to approximate the Pareto surface. An IMPT treatment plan that strikes the best balance between the different objectives can be selected by navigating on the Pareto surface. In our approach, robustness is integrated into MCO by adding robustified objectives and constraints to the MCO problem. Uncertainties (or errors) of the robust problem are modeled by pre-calculated dose-influence matrices for a nominal scenario and a number of pre-defined error scenarios (shifted patient positions, proton beam undershoot and overshoot). Objectives and constraints can be defined for the nominal scenario, thus characterizing nominal plan quality. A robustified objective represents the worst objective function value that can be realized for any of the error scenarios and thus provides a measure of plan robustness. The optimization method is based on a linear projection solver and is capable of handling large problem sizes resulting from a fine dose grid resolution, many scenarios, and a large number of proton pencil beams. A base-of-skull case is used to demonstrate the robust optimization method. It is demonstrated that the robust optimization method reduces the sensitivity of the treatment plan to setup and range errors to a degree that is not achieved by a safety margin approach. A chordoma case is analyzed in more detail to demonstrate the involved trade-offs between target underdose and brainstem sparing as well as robustness and nominal plan quality. The latter illustrates the advantage of MCO in the context of robust planning. For all cases examined, the robust optimization for each Pareto optimal plan takes less than 5 min on a standard computer, making a computationally friendly interface possible to the planner. In conclusion, the uncertainty pertinent to the IMPT procedure can be reduced during treatment planning by optimizing plans that emphasize different treatment objectives, including robustness, and then interactively seeking for a most-preferred one from the solution Pareto surface.

New Polyazine-Bridged RuII,RhIII and RuII,RhI Supramolecular Photocatalysts for Water Reduction to Hydrogen Applicable for Solar Energy Conversion and Mechanistic Investigation of the Photocatalytic Cycle

NASA Astrophysics Data System (ADS)

Zhou, Rongwei

Underwater gliders are robust and long endurance ocean sampling platforms that are increasingly being deployed in coastal regions. This new environment is characterized by shallow waters and significant currents that can challenge the mobility of these efficient (but traditionally slow moving) vehicles. This dissertation aims to improve the performance of shallow water underwater gliders through path planning. The path planning problem is formulated for a dynamic particle (or "kinematic car") model. The objective is to identify the path which satisfies specified boundary conditions and minimizes a particular cost. Several cost functions are considered. The problem is addressed using optimal control theory. The length scales of interest for path planning are within a few turn radii. First, an approach is developed for planning minimum-time paths, for a fixed speed glider, that are sub-optimal but are guaranteed to be feasible in the presence of unknown time-varying currents. Next the minimum-time problem for a glider with speed controls, that may vary between the stall speed and the maximum speed, is solved. Last, optimal paths that minimize change in depth (equivalently, maximize range) are investigated. Recognizing that path planning alone cannot overcome all of the challenges associated with significant currents and shallow waters, the design of a novel underwater glider with improved capabilities is explored. A glider with a pneumatic buoyancy engine (allowing large, rapid buoyancy changes) and a cylindrical moving mass mechanism (generating large pitch and roll moments) is designed, manufactured, and tested to demonstrate potential improvements in speed and maneuverability.

Robustness of mission plans for unmanned aircraft

NASA Astrophysics Data System (ADS)

Niendorf, Moritz

This thesis studies the robustness of optimal mission plans for unmanned aircraft. Mission planning typically involves tactical planning and path planning. Tactical planning refers to task scheduling and in multi aircraft scenarios also includes establishing a communication topology. Path planning refers to computing a feasible and collision-free trajectory. For a prototypical mission planning problem, the traveling salesman problem on a weighted graph, the robustness of an optimal tour is analyzed with respect to changes to the edge costs. Specifically, the stability region of an optimal tour is obtained, i.e., the set of all edge cost perturbations for which that tour is optimal. The exact stability region of solutions to variants of the traveling salesman problems is obtained from a linear programming relaxation of an auxiliary problem. Edge cost tolerances and edge criticalities are derived from the stability region. For Euclidean traveling salesman problems, robustness with respect to perturbations to vertex locations is considered and safe radii and vertex criticalities are introduced. For weighted-sum multi-objective problems, stability regions with respect to changes in the objectives, weights, and simultaneous changes are given. Most critical weight perturbations are derived. Computing exact stability regions is intractable for large instances. Therefore, tractable approximations are desirable. The stability region of solutions to relaxations of the traveling salesman problem give under approximations and sets of tours give over approximations. The application of these results to the two-neighborhood and the minimum 1-tree relaxation are discussed. Bounds on edge cost tolerances and approximate criticalities are obtainable likewise. A minimum spanning tree is an optimal communication topology for minimizing the cumulative transmission power in multi aircraft missions. The stability region of a minimum spanning tree is given and tolerances, stability balls, and criticalities are derived. This analysis is extended to Euclidean minimum spanning trees. This thesis aims at enabling increased mission performance by providing means of assessing the robustness and optimality of a mission and methods for identifying critical elements. Examples of the application to mission planning in contested environments, cargo aircraft mission planning, multi-objective mission planning, and planning optimal communication topologies for teams of unmanned aircraft are given.

Backward assembly planning with DFA analysis

NASA Technical Reports Server (NTRS)

Lee, Sukhan (Inventor)

1992-01-01

An assembly planning system that operates based on a recursive decomposition of assembly into subassemblies is presented. The planning system analyzes assembly cost in terms of stability, directionality, and manipulability to guide the generation of preferred assembly plans. The planning in this system incorporates the special processes, such as cleaning, testing, labeling, etc., that must occur during the assembly. Additionally, the planning handles nonreversible, as well as reversible, assembly tasks through backward assembly planning. In order to decrease the planning efficiency, the system avoids the analysis of decompositions that do not correspond to feasible assembly tasks. This is achieved by grouping and merging those parts that can not be decomposable at the current stage of backward assembly planning due to the requirement of special processes and the constraint of interconnection feasibility. The invention includes methods of evaluating assembly cost in terms of the number of fixtures (or holding devices) and reorientations required for assembly, through the analysis of stability, directionality, and manipulability. All these factors are used in defining cost and heuristic functions for an AO* search for an optimal plan.

AllAboard: Visual Exploration of Cellphone Mobility Data to Optimise Public Transport.

PubMed

Di Lorenzo, G; Sbodio, M; Calabrese, F; Berlingerio, M; Pinelli, F; Nair, R

2016-02-01

The deep penetration of mobile phones offers cities the ability to opportunistically monitor citizens' mobility and use data-driven insights to better plan and manage services. With large scale data on mobility patterns, operators can move away from the costly, mostly survey based, transportation planning processes, to a more data-centric view, that places the instrumented user at the center of development. In this framework, using mobile phone data to perform transit analysis and optimization represents a new frontier with significant societal impact, especially in developing countries. In this paper we present AllAboard, an intelligent tool that analyses cellphone data to help city authorities in visually exploring urban mobility and optimizing public transport. This is performed within a self contained tool, as opposed to the current solutions which rely on a combination of several distinct tools for analysis, reporting, optimisation and planning. An interactive user interface allows transit operators to visually explore the travel demand in both space and time, correlate it with the transit network, and evaluate the quality of service that a transit network provides to the citizens at very fine grain. Operators can visually test scenarios for transit network improvements, and compare the expected impact on the travellers' experience. The system has been tested using real telecommunication data for the city of Abidjan, Ivory Coast, and evaluated from a data mining, optimisation and user prospective.

SU-E-T-355: A Comparative Study of Robotic and Linac-Based Stereotactitc Body Radiation Therapy for Lumbar Spinal Tumors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bossart, E; Monterroso, M; Couto, M

Purpose: Dosimetrically compare CyberKnife (CK) and linac-based (LB) stereotactic body radiotherapy (SBRT) plans for lumbar spine. Methods: Ten patient plans with lumbar spine tumors treated with CK were selected and retrospectively optimized using three techniques: CK, volumetric modulated arc (VMAT, three arcs), and 9-field-intensity modulated radiotherapy (IMRT). For the LB plans, the target volume was expanded by 1mm to accommodate additional uncertainty in patient positioning. All plans were optimized to a prescription dose of 27Gy in 3 fractions covering 90% of the PTV. If the dose constraints to the cauda equina (cauda) were not met, the prescription dose was loweredmore » to 24Gy. Parameters evaluated included Paddick Conformity-Index (CI) and Gradient-Index (GI). A two-tailed paired t-test was used to establish statistically significant differences in cauda doses. Results: Target volumes for LB plans were on average 38% larger. In terms of the indices, the closer the index values to unity the steeper the dose falloff and the higher the dose conformity to the target. The results showed that LB plans were in general statistically superior to CK plans. The IMRT plan showed the best average gradient index of 2.995, with VMAT and CK GI values of 3.699 and 5.476, respectively. Similarly, the same trend occurs with the average CI results: 0.821, 0.814, and 0.758, corresponding to IMRT, VMAT, and CK. Notably, in one CK plan the target dose was reduced to 24Gy to meet cauda constraints. Additionally, there was a statistically significant dose difference for the cauda between the CK and LB plans. Conclusion: This study demonstrates that LB plans for lumbar spine SBRT can be as effective or even better than CK plans. Despite the expansion of the target volume, the LB plans did not demonstrate dosimetric inferiority. The LB plans Resultin 2-to-3 fold decrease of treatment time.« less

An Automated Treatment Plan Quality Control Tool for Intensity-Modulated Radiation Therapy Using a Voxel-Weighting Factor-Based Re-Optimization Algorithm

PubMed Central

Song, Ting; Li, Nan; Zarepisheh, Masoud; Li, Yongbao; Gautier, Quentin; Zhou, Linghong; Mell, Loren; Jiang, Steve; Cerviño, Laura

2016-01-01

Intensity-modulated radiation therapy (IMRT) currently plays an important role in radiotherapy, but its treatment plan quality can vary significantly among institutions and planners. Treatment plan quality control (QC) is a necessary component for individual clinics to ensure that patients receive treatments with high therapeutic gain ratios. The voxel-weighting factor-based plan re-optimization mechanism has been proved able to explore a larger Pareto surface (solution domain) and therefore increase the possibility of finding an optimal treatment plan. In this study, we incorporated additional modules into an in-house developed voxel weighting factor-based re-optimization algorithm, which was enhanced as a highly automated and accurate IMRT plan QC tool (TPS-QC tool). After importing an under-assessment plan, the TPS-QC tool was able to generate a QC report within 2 minutes. This QC report contains the plan quality determination as well as information supporting the determination. Finally, the IMRT plan quality can be controlled by approving quality-passed plans and replacing quality-failed plans using the TPS-QC tool. The feasibility and accuracy of the proposed TPS-QC tool were evaluated using 25 clinically approved cervical cancer patient IMRT plans and 5 manually created poor-quality IMRT plans. The results showed high consistency between the QC report quality determinations and the actual plan quality. In the 25 clinically approved cases that the TPS-QC tool identified as passed, a greater difference could be observed for dosimetric endpoints for organs at risk (OAR) than for planning target volume (PTV), implying that better dose sparing could be achieved in OAR than in PTV. In addition, the dose-volume histogram (DVH) curves of the TPS-QC tool re-optimized plans satisfied the dosimetric criteria more frequently than did the under-assessment plans. In addition, the criteria for unsatisfied dosimetric endpoints in the 5 poor-quality plans could typically be satisfied when the TPS-QC tool generated re-optimized plans without sacrificing other dosimetric endpoints. In addition to its feasibility and accuracy, the proposed TPS-QC tool is also user-friendly and easy to operate, both of which are necessary characteristics for clinical use. PMID:26930204

A knowledge-based approach to improving optimization techniques in system planning

NASA Technical Reports Server (NTRS)

Momoh, J. A.; Zhang, Z. Z.

1990-01-01

A knowledge-based (KB) approach to improve mathematical programming techniques used in the system planning environment is presented. The KB system assists in selecting appropriate optimization algorithms, objective functions, constraints and parameters. The scheme is implemented by integrating symbolic computation of rules derived from operator and planner's experience and is used for generalized optimization packages. The KB optimization software package is capable of improving the overall planning process which includes correction of given violations. The method was demonstrated on a large scale power system discussed in the paper.

SU-E-T-109: Development of An End-To-End Test for the Varian TrueBeamtm with a Novel Multiple-Dosimetric Modality H and N Phantom

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zakjevskii, V; Knill, C; Rakowski, J

2014-06-01

Purpose: To develop a comprehensive end-to-end test for Varian's TrueBeam linear accelerator for head and neck IMRT using a custom phantom designed to utilize multiple dosimetry devices. Methods: The initial end-to-end test and custom H and N phantom were designed to yield maximum information in anatomical regions significant to H and N plans with respect to: i) geometric accuracy, ii) dosimetric accuracy, and iii) treatment reproducibility. The phantom was designed in collaboration with Integrated Medical Technologies. A CT image was taken with a 1mm slice thickness. The CT was imported into Varian's Eclipse treatment planning system, where OARs and themore » PTV were contoured. A clinical template was used to create an eight field static gantry angle IMRT plan. After optimization, dose was calculated using the Analytic Anisotropic Algorithm with inhomogeneity correction. Plans were delivered with a TrueBeam equipped with a high definition MLC. Preliminary end-to-end results were measured using film and ion chambers. Ion chamber dose measurements were compared to the TPS. Films were analyzed with FilmQAPro using composite gamma index. Results: Film analysis for the initial end-to-end plan with a geometrically simple PTV showed average gamma pass rates >99% with a passing criterion of 3% / 3mm. Film analysis of a plan with a more realistic, ie. complex, PTV yielded pass rates >99% in clinically important regions containing the PTV, spinal cord and parotid glands. Ion chamber measurements were on average within 1.21% of calculated dose for both plans. Conclusion: trials have demonstrated that our end-to-end testing methods provide baseline values for the dosimetric and geometric accuracy of Varian's TrueBeam system.« less

Optimal rail container shipment planning problem in multimodal transportation

NASA Astrophysics Data System (ADS)

Cao, Chengxuan; Gao, Ziyou; Li, Keping

2012-09-01

The optimal rail container shipment planning problem in multimodal transportation is studied in this article. The characteristics of the multi-period planning problem is presented and the problem is formulated as a large-scale 0-1 integer programming model, which maximizes the total profit generated by all freight bookings accepted in a multi-period planning horizon subject to the limited capacities. Two heuristic algorithms are proposed to obtain an approximate optimal solution of the problem. Finally, numerical experiments are conducted to demonstrate the proposed formulation and heuristic algorithms.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, X; Wang, J; Hu, W

Purpose: The Varian RapidPlan™ is a commercial knowledge-based optimization process which uses a set of clinically used treatment plans to train a model that can predict individualized dose-volume objectives. The purpose of this study is to evaluate the performance of RapidPlan to generate intensity modulated radiation therapy (IMRT) plans for cervical cancer. Methods: Totally 70 IMRT plans for cervical cancer with varying clinical and physiological indications were enrolled in this study. These patients were all previously treated in our institution. There were two prescription levels usually used in our institution: 45Gy/25 fractions and 50.4Gy/28 fractions. 50 of these plans weremore » selected to train the RapidPlan model for predicting dose-volume constraints. After model training, this model was validated with 10 plans from training pool(internal validation) and additional other 20 new plans(external validation). All plans used for the validation were re-optimized with the original beam configuration and the generated priorities from RapidPlan were manually adjusted to ensure that re-optimized DVH located in the range of the model prediction. DVH quantitative analysis was performed to compare the RapidPlan generated and the original manual optimized plans. Results: For all the validation cases, RapidPlan based plans (RapidPlan) showed similar or superior results compared to the manual optimized ones. RapidPlan increased the result of D98% and homogeneity in both two validations. For organs at risk, the RapidPlan decreased mean doses of bladder by 1.25Gy/1.13Gy (internal/external validation) on average, with p=0.12/p<0.01. The mean dose of rectum and bowel were also decreased by an average of 2.64Gy/0.83Gy and 0.66Gy/1.05Gy,with p<0.01/ p<0.01and p=0.04/<0.01 for the internal/external validation, respectively. Conclusion: The RapidPlan model based cervical cancer plans shows ability to systematically improve the IMRT plan quality. It suggests that RapidPlan has great potential to make the treatment planning process more efficient.« less

Northern Arabian Sea Circulation - Autonomous Research: Optimal Planning Systems (NASCar-OPS)

DTIC Science & Technology

2015-09-30

vehicles ( gliders , drifters, floats, and/or wave- gliders ) - Provide guidance for persistent optimal sampling, including for long-duration observation...headings and relative operating speeds will be provided to the operational fleets of instruments and vehicles (e.g. gliders , drifters, floats or wave... gliders ). We plan to use models specific to vehicle types (floats, wave- gliders , etc.). We also plan to further parallelize and optimize our codes

Assessing the shelf life of cost-efficient conservation plans for species at risk across gradients of agricultural land use.

PubMed

Robillard, Cassandra M; Kerr, Jeremy T

2017-08-01

High costs of land in agricultural regions warrant spatial prioritization approaches to conservation that explicitly consider land prices to produce protected-area networks that accomplish targets efficiently. However, land-use changes in such regions and delays between plan design and implementation may render optimized plans obsolete before implementation occurs. To measure the shelf life of cost-efficient conservation plans, we simulated a land-acquisition and restoration initiative aimed at conserving species at risk in Canada's farmlands. We accounted for observed changes in land-acquisition costs and in agricultural intensity based on censuses of agriculture taken from 1986 to 2011. For each year of data, we mapped costs and areas of conservation priority designated using Marxan. We compared plans to test for changes through time in the arrangement of high-priority sites and in the total cost of each plan. For acquisition costs, we measured the savings from accounting for prices during site selection. Land-acquisition costs and land-use intensity generally rose over time independent of inflation (24-78%), although rates of change were heterogeneous through space and decreased in some areas. Accounting for spatial variation in land price lowered the cost of conservation plans by 1.73-13.9%, decreased the range of costs by 19-82%, and created unique solutions from which to choose. Despite the rise in plan costs over time, the high conservation priority of particular areas remained consistent. Delaying conservation in these critical areas may compromise what optimized conservation plans can achieve. In the case of Canadian farmland, rapid conservation action is cost-effective, even with moderate levels of uncertainty in how to implement restoration goals. © 2016 Society for Conservation Biology.

Robotic path-finding in inverse treatment planning for stereotactic radiosurgery with continuous dose delivery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vandewouw, Marlee M., E-mail: marleev@mie.utoronto

Purpose: Continuous dose delivery in radiation therapy treatments has been shown to decrease total treatment time while improving the dose conformity and distribution homogeneity over the conventional step-and-shoot approach. The authors develop an inverse treatment planning method for Gamma Knife® Perfexion™ that continuously delivers dose along a path in the target. Methods: The authors’ method is comprised of two steps: find a path within the target, then solve a mixed integer optimization model to find the optimal collimator configurations and durations along the selected path. Robotic path-finding techniques, specifically, simultaneous localization and mapping (SLAM) using an extended Kalman filter, aremore » used to obtain a path that travels sufficiently close to selected isocentre locations. SLAM is novelly extended to explore a 3D, discrete environment, which is the target discretized into voxels. Further novel extensions are incorporated into the steering mechanism to account for target geometry. Results: The SLAM method was tested on seven clinical cases and compared to clinical, Hamiltonian path continuous delivery, and inverse step-and-shoot treatment plans. The SLAM approach improved dose metrics compared to the clinical plans and Hamiltonian path continuous delivery plans. Beam-on times improved over clinical plans, and had mixed performance compared to Hamiltonian path continuous plans. The SLAM method is also shown to be robust to path selection inaccuracies, isocentre selection, and dose distribution. Conclusions: The SLAM method for continuous delivery provides decreased total treatment time and increased treatment quality compared to both clinical and inverse step-and-shoot plans, and outperforms existing path methods in treatment quality. It also accounts for uncertainty in treatment planning by accommodating inaccuracies.« less

Simple tool for prediction of parotid gland sparing in intensity-modulated radiation therapy.

PubMed

Gensheimer, Michael F; Hummel-Kramer, Sharon M; Cain, David; Quang, Tony S

2015-01-01

Sparing one or both parotid glands is a key goal when planning head and neck cancer radiation treatment. If the planning target volume (PTV) overlaps one or both parotid glands substantially, it may not be possible to achieve adequate gland sparing. This finding results in physicians revising their PTV contours after an intensity-modulated radiation therapy (IMRT) plan has been run and reduces workflow efficiency. We devised a simple formula for predicting mean parotid gland dose from the overlap of the parotid gland and isotropically expanded PTV contours. We tested the tool using 44 patients from 2 institutions and found agreement between predicted and actual parotid gland doses (mean absolute error = 5.3 Gy). This simple method could increase treatment planning efficiency by improving the chance that the first plan presented to the physician will have optimal parotid gland sparing. Published by Elsevier Inc.

Simple tool for prediction of parotid gland sparing in intensity-modulated radiation therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gensheimer, Michael F.; Hummel-Kramer, Sharon M., E-mail: sharonhummel@comcast.net; Cain, David

Sparing one or both parotid glands is a key goal when planning head and neck cancer radiation treatment. If the planning target volume (PTV) overlaps one or both parotid glands substantially, it may not be possible to achieve adequate gland sparing. This finding results in physicians revising their PTV contours after an intensity-modulated radiation therapy (IMRT) plan has been run and reduces workflow efficiency. We devised a simple formula for predicting mean parotid gland dose from the overlap of the parotid gland and isotropically expanded PTV contours. We tested the tool using 44 patients from 2 institutions and found agreementmore » between predicted and actual parotid gland doses (mean absolute error = 5.3 Gy). This simple method could increase treatment planning efficiency by improving the chance that the first plan presented to the physician will have optimal parotid gland sparing.« less

VMAT optimization with dynamic collimator rotation.

PubMed

Lyu, Qihui; O'Connor, Daniel; Ruan, Dan; Yu, Victoria; Nguyen, Dan; Sheng, Ke

2018-04-16

Although collimator rotation is an optimization variable that can be exploited for dosimetric advantages, existing Volumetric Modulated Arc Therapy (VMAT) optimization uses a fixed collimator angle in each arc and only rotates the collimator between arcs. In this study, we develop a novel integrated optimization method for VMAT, accounting for dynamic collimator angles during the arc motion. Direct Aperture Optimization (DAO) for Dynamic Collimator in VMAT (DC-VMAT) was achieved by adding to the existing dose fidelity objective an anisotropic total variation term for regulating the fluence smoothness, a binary variable for forming simple apertures, and a group sparsity term for controlling collimator rotation. The optimal collimator angle for each beam angle was selected using the Dijkstra's algorithm, where the node costs depend on the estimated fluence map at the current iteration and the edge costs account for the mechanical constraints of multi-leaf collimator (MLC). An alternating optimization strategy was implemented to solve the DAO and collimator angle selection (CAS). Feasibility of DC-VMAT using one full-arc with dynamic collimator rotation was tested on a phantom with two small spherical targets, a brain, a lung and a prostate cancer patient. The plan was compared against a static collimator VMAT (SC-VMAT) plan using three full arcs with 60 degrees of collimator angle separation in patient studies. With the same target coverage, DC-VMAT achieved 20.3% reduction of R50 in the phantom study, and reduced the average max and mean OAR dose by 4.49% and 2.53% of the prescription dose in patient studies, as compared with SC-VMAT. The collimator rotation co-ordinated with the gantry rotation in DC-VMAT plans for deliverability. There were 13 beam angles in the single-arc DC-VMAT plan in patient studies that requires slower gantry rotation to accommodate multiple collimator angles. The novel DC-VMAT approach utilizes the dynamic collimator rotation during arc delivery. In doing so, DC-VMAT affords more sophisticated intensity modulation, alleviating the limitation previously imposed by the square beamlet from the MLC leaf thickness and achieves higher effective modulation resolution. Consequently, DC-VMAT with a single arc manages to achieve superior dosimetry than SC-VMAT with three full arcs. © 2018 American Association of Physicists in Medicine.

Optimization of light source parameters in the photodynamic therapy of heterogeneous prostate

NASA Astrophysics Data System (ADS)

Li, Jun; Altschuler, Martin D.; Hahn, Stephen M.; Zhu, Timothy C.

2008-08-01

The three-dimensional (3D) heterogeneous distributions of optical properties in a patient prostate can now be measured in vivo. Such data can be used to obtain a more accurate light-fluence kernel. (For specified sources and points, the kernel gives the fluence delivered to a point by a source of unit strength.) In turn, the kernel can be used to solve the inverse problem that determines the source strengths needed to deliver a prescribed photodynamic therapy (PDT) dose (or light-fluence) distribution within the prostate (assuming uniform drug concentration). We have developed and tested computational procedures to use the new heterogeneous data to optimize delivered light-fluence. New problems arise, however, in quickly obtaining an accurate kernel following the insertion of interstitial light sources and data acquisition. (1) The light-fluence kernel must be calculated in 3D and separately for each light source, which increases kernel size. (2) An accurate kernel for light scattering in a heterogeneous medium requires ray tracing and volume partitioning, thus significant calculation time. To address these problems, two different kernels were examined and compared for speed of creation and accuracy of dose. Kernels derived more quickly involve simpler algorithms. Our goal is to achieve optimal dose planning with patient-specific heterogeneous optical data applied through accurate kernels, all within clinical times. The optimization process is restricted to accepting the given (interstitially inserted) sources, and determining the best source strengths with which to obtain a prescribed dose. The Cimmino feasibility algorithm is used for this purpose. The dose distribution and source weights obtained for each kernel are analyzed. In clinical use, optimization will also be performed prior to source insertion to obtain initial source positions, source lengths and source weights, but with the assumption of homogeneous optical properties. For this reason, we compare the results from heterogeneous optical data with those obtained from average homogeneous optical properties. The optimized treatment plans are also compared with the reference clinical plan, defined as the plan with sources of equal strength, distributed regularly in space, which delivers a mean value of prescribed fluence at detector locations within the treatment region. The study suggests that comprehensive optimization of source parameters (i.e. strengths, lengths and locations) is feasible, thus allowing acceptable dose coverage in a heterogeneous prostate PDT within the time constraints of the PDT procedure.

Dosimetric effect of limited aperture multileaf collimator on VMAT plan quality: A study of prostate and head-and-neck cancers.

PubMed

Murtaza, Ghulam; Mehmood, Shahid; Rasul, Shahid; Murtaza, Imran; Khan, Ehsan Ullah

2018-01-01

The aim of study was to evaluate the dosimetric effect of collimator-rotation on VMAT plan quality, when using limited aperture multileaf collimator of Elekta Beam Modulator™ providing a maximum aperture of 21 cm × 16 cm. The increased use of VMAT technique to deliver IMRT from conventional to very specialized treatments present a challenge in plan optimization. In this study VMAT plans were optimized for prostate and head and neck cancers using Elekta Beam-Modulator TM , whereas previous studies were reported for conventional Linac aperture. VMAT plans for nine of each prostate and head-and-neck cancer patients were produced using the 6 MV photon beam for Elekta-SynergyS ® Linac using Pinnacle 3 treatment planning system. Single arc, dual arc and two combined independent-single arcs were optimized for collimator angles (C) 0°, 90° and 0°-90° (0°-90°; i.e. the first-arc was assigned C0° and second-arc was assigned C90°). A treatment plan comparison was performed among C0°, C90° and C(0°-90°) for single-arc dual-arc and two independent-single-arcs VMAT techniques to evaluate the influence of extreme collimator rotations (C0° and 90°) on VMAT plan quality. Plan evaluation criteria included the target coverage, conformity index, homogeneity index and doses to organs at risk. A 'two-sided student t -test' ( p  ≤ 0.05) was used to determine if there was a significant difference in dose volume indices of plans. For both prostate and head-and-neck, plan quality at collimator angles C0° and C(0°-90°) was clinically acceptable for all VMAT-techniques, except SA for head-and-neck. Poorer target coverage, higher normal tissue doses and significant p -values were observed for collimator angle 90° when compared with C0° and C(0°-90°). A collimator rotation of 0° provided significantly better target coverage and sparing of organs-at-risk than a collimator rotation of 90° for all VMAT techniques.

SU-E-T-109: An Investigation of Including Variable Relative Biological Effectiveness in Intensity Modulated Proton Therapy Planning Optimization for Head and Neck Cancer Patients

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cao, W; Zaghian, M; Lim, G

2015-06-15

Purpose: The current practice of considering the relative biological effectiveness (RBE) of protons in intensity modulated proton therapy (IMPT) planning is to use a generic RBE value of 1.1. However, RBE is indeed a variable depending on the dose per fraction, the linear energy transfer, tissue parameters, etc. In this study, we investigate the impact of using variable RBE based optimization (vRBE-OPT) on IMPT dose distributions compared by conventional fixed RBE based optimization (fRBE-OPT). Methods: Proton plans of three head and neck cancer patients were included for our study. In order to calculate variable RBE, tissue specific parameters were obtainedmore » from the literature and dose averaged LET values were calculated by Monte Carlo simulations. Biological effects were calculated using the linear quadratic model and they were utilized in the variable RBE based optimization. We used a Polak-Ribiere conjugate gradient algorithm to solve the model. In fixed RBE based optimization, we used conventional physical dose optimization to optimize doses weighted by 1.1. IMPT plans for each patient were optimized by both methods (vRBE-OPT and fRBE-OPT). Both variable and fixed RBE weighted dose distributions were calculated for both methods and compared by dosimetric measures. Results: The variable RBE weighted dose distributions were more homogenous within the targets, compared with the fixed RBE weighted dose distributions for the plans created by vRBE-OPT. We observed that there were noticeable deviations between variable and fixed RBE weighted dose distributions if the plan were optimized by fRBE-OPT. For organs at risk sparing, dose distributions from both methods were comparable. Conclusion: Biological dose based optimization rather than conventional physical dose based optimization in IMPT planning may bring benefit in improved tumor control when evaluating biologically equivalent dose, without sacrificing OAR sparing, for head and neck cancer patients. The research is supported in part by National Institutes of Health Grant No. 2U19CA021239-35.« less

SU-F-T-342: Dosimetric Constraint Prediction Guided Automatic Mulit-Objective Optimization for Intensity Modulated Radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Song, T; Zhou, L; Li, Y

Purpose: For intensity modulated radiotherapy, the plan optimization is time consuming with difficulties of selecting objectives and constraints, and their relative weights. A fast and automatic multi-objective optimization algorithm with abilities to predict optimal constraints and manager their trade-offs can help to solve this problem. Our purpose is to develop such a framework and algorithm for a general inverse planning. Methods: There are three main components contained in this proposed multi-objective optimization framework: prediction of initial dosimetric constraints, further adjustment of constraints and plan optimization. We firstly use our previously developed in-house geometry-dosimetry correlation model to predict the optimal patient-specificmore » dosimetric endpoints, and treat them as initial dosimetric constraints. Secondly, we build an endpoint(organ) priority list and a constraint adjustment rule to repeatedly tune these constraints from their initial values, until every single endpoint has no room for further improvement. Lastly, we implement a voxel-independent based FMO algorithm for optimization. During the optimization, a model for tuning these voxel weighting factors respecting to constraints is created. For framework and algorithm evaluation, we randomly selected 20 IMRT prostate cases from the clinic and compared them with our automatic generated plans, in both the efficiency and plan quality. Results: For each evaluated plan, the proposed multi-objective framework could run fluently and automatically. The voxel weighting factor iteration time varied from 10 to 30 under an updated constraint, and the constraint tuning time varied from 20 to 30 for every case until no more stricter constraint is allowed. The average total costing time for the whole optimization procedure is ∼30mins. By comparing the DVHs, better OAR dose sparing could be observed in automatic generated plan, for 13 out of the 20 cases, while others are with competitive results. Conclusion: We have successfully developed a fast and automatic multi-objective optimization for intensity modulated radiotherapy. This work is supported by the National Natural Science Foundation of China (No: 81571771)« less

A novel two-step optimization method for tandem and ovoid high-dose-rate brachytherapy treatment for locally advanced cervical cancer.

PubMed

Sharma, Manju; Fields, Emma C; Todor, Dorin A

2015-01-01

To present a novel method allowing fast volumetric optimization of tandem and ovoid high-dose-rate treatments and to quantify its benefits. Twenty-seven CT-based treatment plans from 6 consecutive cervical cancer patients treated with four to five intracavitary tandem and ovoid insertions were used. Initial single-step optimized plans were manually optimized, approved, and delivered plans created with a goal to cover high-risk clinical target volume (HR-CTV) with D90 >90% and minimize rectum, bladder, and sigmoid D2cc. For the two-step optimized (TSO) plan, each single-step optimized plan was replanned adding a structure created from prescription isodose line to the existent physician delineated HR-CTV, rectum, bladder, and sigmoid. New, more rigorous dose-volume histogram constraints for the critical organs at risks (OARs) were used for the optimization. HR-CTV D90 and OAR D2ccs were evaluated in both plans. TSO plans had consistently smaller D2ccs for all three OARs while preserving HR-CTV D90. On plans with "excellent" CTV coverage, average D90 of 96% (91-102%), sigmoid, bladder, and rectum D2cc, respectively, reduced on average by 37% (16-73%), 28% (20-47%), and 27% (15-45%). Similar reductions were obtained on plans with "good" coverage, average D90 of 93% (90-99%). For plans with "inferior" coverage, average D90 of 81%, the coverage increased to 87% with concurrent D2cc reductions of 31%, 18%, and 11% for sigmoid, bladder, and rectum, respectively. The TSO can be added with minimal planning time increase but with the potential of dramatic and systematic reductions in OAR D2ccs and in some cases with concurrent increase in target dose coverage. These single-fraction modifications would be magnified over the course of four to five intracavitary insertions and may have real clinical implications in terms of decreasing both acute and late toxicities. Copyright © 2015 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.

Evaluation of the optimal combinations of modulation factor and pitch for Helical TomoTherapy plans made with TomoEdge using Pareto optimal fronts.

PubMed

De Kerf, Geert; Van Gestel, Dirk; Mommaerts, Lobke; Van den Weyngaert, Danielle; Verellen, Dirk

2015-09-17

Modulation factor (MF) and pitch have an impact on Helical TomoTherapy (HT) plan quality and HT users mostly use vendor-recommended settings. This study analyses the effect of these two parameters on both plan quality and treatment time for plans made with TomoEdge planning software by using the concept of Pareto optimal fronts. More than 450 plans with different combinations of pitch [0.10-0.50] and MF [1.2-3.0] were produced. These HT plans, with a field width (FW) of 5 cm, were created for five head and neck patients and homogeneity index, conformity index, dose-near-maximum (D2), and dose-near-minimum (D98) were analysed for the planning target volumes, as well as the mean dose and D2 for most critical organs at risk. For every dose metric the median value will be plotted against treatment time. A Pareto-like method is used in the analysis which will show how pitch and MF influence both treatment time and plan quality. For small pitches (≤0.20), MF does not influence treatment time. The contrary is true for larger pitches (≥0.25) as lowering MF will both decrease treatment time and plan quality until maximum gantry speed is reached. At this moment, treatment time is saturated and only plan quality will further decrease. The Pareto front analysis showed optimal combinations of pitch [0.23-0.45] and MF > 2.0 for a FW of 5 cm. Outside this range, plans will become less optimal. As the vendor-recommended settings fall within this range, the use of these settings is validated.

Tools of the Future: How Decision Tree Analysis Will Impact Mission Planning

NASA Technical Reports Server (NTRS)

Otterstatter, Matthew R.

2005-01-01

The universe is infinitely complex; however, the human mind has a finite capacity. The multitude of possible variables, metrics, and procedures in mission planning are far too many to address exhaustively. This is unfortunate because, in general, considering more possibilities leads to more accurate and more powerful results. To compensate, we can get more insightful results by employing our greatest tool, the computer. The power of the computer will be utilized through a technology that considers every possibility, decision tree analysis. Although decision trees have been used in many other fields, this is innovative for space mission planning. Because this is a new strategy, no existing software is able to completely accommodate all of the requirements. This was determined through extensive research and testing of current technologies. It was necessary to create original software, for which a short-term model was finished this summer. The model was built into Microsoft Excel to take advantage of the familiar graphical interface for user input, computation, and viewing output. Macros were written to automate the process of tree construction, optimization, and presentation. The results are useful and promising. If this tool is successfully implemented in mission planning, our reliance on old-fashioned heuristics, an error-prone shortcut for handling complexity, will be reduced. The computer algorithms involved in decision trees will revolutionize mission planning. The planning will be faster and smarter, leading to optimized missions with the potential for more valuable data.

On the use of genetic algorithm to optimize industrial assets lifecycle management under safety and budget constraints

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lonchampt, J.; Fessart, K.

2013-07-01

The purpose of this paper is to describe the method and tool dedicated to optimize investments planning for industrial assets. These investments may either be preventive maintenance tasks, asset enhancements or logistic investments such as spare parts purchases. The two methodological points to investigate in such an issue are: 1. The measure of the profitability of a portfolio of investments 2. The selection and planning of an optimal set of investments 3. The measure of the risk of a portfolio of investments The measure of the profitability of a set of investments in the IPOP tool is synthesised in themore » Net Present Value indicator. The NPV is the sum of the differences of discounted cash flows (direct costs, forced outages...) between the situations with and without a given investment. These cash flows are calculated through a pseudo-Markov reliability model representing independently the components of the industrial asset and the spare parts inventories. The component model has been widely discussed over the years but the spare part model is a new one based on some approximations that will be discussed. This model, referred as the NPV function, takes for input an investments portfolio and gives its NPV. The second issue is to optimize the NPV. If all investments were independent, this optimization would be an easy calculation, unfortunately there are two sources of dependency. The first one is introduced by the spare part model, as if components are indeed independent in their reliability model, the fact that several components use the same inventory induces a dependency. The second dependency comes from economic, technical or logistic constraints, such as a global maintenance budget limit or a safety requirement limiting the residual risk of failure of a component or group of component, making the aggregation of individual optimum not necessary feasible. The algorithm used to solve such a difficult optimization problem is a genetic algorithm. After a description of the features of the software a test case is presented showing the influence of the optimization algorithm parameters on its efficiency to find an optimal investments planning. (authors)« less

Inspection logistics planning for multi-stage production systems with applications to semiconductor fabrication lines

NASA Astrophysics Data System (ADS)

Chen, Kyle Dakai

Since the market for semiconductor products has become more lucrative and competitive, research into improving yields for semiconductor fabrication lines has lately received a tremendous amount of attention. One of the most critical tasks in achieving such yield improvements is to plan the in-line inspection sampling efficiently so that any potential yield problems can be detected early and eliminated quickly. We formulate a multi-stage inspection planning model based on configurations in actual semiconductor fabrication lines, specifically taking into account both the capacity constraint and the congestion effects at the inspection station. We propose a new mixed First-Come-First-Serve (FCFS) and Last-Come-First-Serve (LCFS) discipline for serving the inspection samples to expedite the detection of potential yield problems. Employing this mixed FCFS and LCFS discipline, we derive approximate expressions for the queueing delays in yield problem detection time and develop near-optimal algorithms to obtain the inspection logistics planning policies. We also investigate the queueing performance with this mixed type of service discipline under different assumptions and configurations. In addition, we conduct numerical tests and generate managerial insights based on input data from actual semiconductor fabrication lines. To the best of our knowledge, this research is novel in developing, for the first time in the literature, near-optimal results for inspection logistics planning in multi-stage production systems with congestion effects explicitly considered.

Optimizing Perioperative Decision Making: Improved Information for Clinical Workflow Planning

PubMed Central

Doebbeling, Bradley N.; Burton, Matthew M.; Wiebke, Eric A.; Miller, Spencer; Baxter, Laurence; Miller, Donald; Alvarez, Jorge; Pekny, Joseph

2012-01-01

Perioperative care is complex and involves multiple interconnected subsystems. Delayed starts, prolonged cases and overtime are common. Surgical procedures account for 40–70% of hospital revenues and 30–40% of total costs. Most planning and scheduling in healthcare is done without modern planning tools, which have potential for improving access by assisting in operations planning support. We identified key planning scenarios of interest to perioperative leaders, in order to examine the feasibility of applying combinatorial optimization software solving some of those planning issues in the operative setting. Perioperative leaders desire a broad range of tools for planning and assessing alternate solutions. Our modeled solutions generated feasible solutions that varied as expected, based on resource and policy assumptions and found better utilization of scarce resources. Combinatorial optimization modeling can effectively evaluate alternatives to support key decisions for planning clinical workflow and improving care efficiency and satisfaction. PMID:23304284

Optimizing perioperative decision making: improved information for clinical workflow planning.

PubMed

Doebbeling, Bradley N; Burton, Matthew M; Wiebke, Eric A; Miller, Spencer; Baxter, Laurence; Miller, Donald; Alvarez, Jorge; Pekny, Joseph

2012-01-01

Perioperative care is complex and involves multiple interconnected subsystems. Delayed starts, prolonged cases and overtime are common. Surgical procedures account for 40-70% of hospital revenues and 30-40% of total costs. Most planning and scheduling in healthcare is done without modern planning tools, which have potential for improving access by assisting in operations planning support. We identified key planning scenarios of interest to perioperative leaders, in order to examine the feasibility of applying combinatorial optimization software solving some of those planning issues in the operative setting. Perioperative leaders desire a broad range of tools for planning and assessing alternate solutions. Our modeled solutions generated feasible solutions that varied as expected, based on resource and policy assumptions and found better utilization of scarce resources. Combinatorial optimization modeling can effectively evaluate alternatives to support key decisions for planning clinical workflow and improving care efficiency and satisfaction.

Visualization of logistic algorithm in Wilson model

NASA Astrophysics Data System (ADS)

Glushchenko, A. S.; Rodin, V. A.; Sinegubov, S. V.

2018-05-01

Economic order quantity (EOQ), defined by the Wilson's model, is widely used at different stages of production and distribution of different products. It is useful for making decisions in the management of inventories, providing a more efficient business operation and thus bringing more economic benefits. There is a large amount of reference material and extensive computer shells that help solving various logistics problems. However, the use of large computer environments is not always justified and requires special user training. A tense supply schedule in a logistics model is optimal, if, and only if, the planning horizon coincides with the beginning of the next possible delivery. For all other possible planning horizons, this plan is not optimal. It is significant that when the planning horizon changes, the plan changes immediately throughout the entire supply chain. In this paper, an algorithm and a program for visualizing models of the optimal value of supplies and their number, depending on the magnitude of the planned horizon, have been obtained. The program allows one to trace (visually and quickly) all main parameters of the optimal plan on the charts. The results of the paper represent a part of the authors’ research work in the field of optimization of protection and support services of ports in the Russian North.

Affordable Development and Optimization of CERMET Fuels for NTP Ground Testing

NASA Technical Reports Server (NTRS)

Hickman, Robert R.; Broadway, Jeramie W.; Mireles, Omar R.

2014-01-01

CERMET fuel materials for Nuclear Thermal Propulsion (NTP) are currently being developed at NASA's Marshall Space Flight Center. The work is part of NASA's Advanced Space Exploration Systems Nuclear Cryogenic Propulsion Stage (NCPS) Project. The goal of the FY12-14 project is to address critical NTP technology challenges and programmatic issues to establish confidence in the affordability and viability of an NTP system. A key enabling technology for an NCPS system is the fabrication of a stable high temperature nuclear fuel form. Although much of the technology was demonstrated during previous programs, there are currently no qualified fuel materials or processes. The work at MSFC is focused on developing critical materials and process technologies for manufacturing robust, full-scale CERMET fuels. Prototypical samples are being fabricated and tested in flowing hot hydrogen to understand processing and performance relationships. As part of this initial demonstration task, a final full scale element test will be performed to validate robust designs. The next phase of the project will focus on continued development and optimization of the fuel materials to enable future ground testing. The purpose of this paper is to provide a detailed overview of the CERMET fuel materials development plan. The overall CERMET fuel development path is shown in Figure 2. The activities begin prior to ATP for a ground reactor or engine system test and include materials and process optimization, hot hydrogen screening, material property testing, and irradiation testing. The goal of the development is to increase the maturity of the fuel form and reduce risk. One of the main accomplishmens of the current AES FY12-14 project was to develop dedicated laboratories at MSFC for the fabrication and testing of full length fuel elements. This capability will enable affordable, near term development and optimization of the CERMET fuels for future ground testing. Figure 2 provides a timeline of the development and optimization tasks for the AES FY15-17 follow on program.

Poster — Thur Eve — 61: A new framework for MPERT plan optimization using MC-DAO

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baker, M; Lloyd, S AM; Townson, R

2014-08-15

This work combines the inverse planning technique known as Direct Aperture Optimization (DAO) with Intensity Modulated Radiation Therapy (IMRT) and combined electron and photon therapy plans. In particular, determining conditions under which Modulated Photon/Electron Radiation Therapy (MPERT) produces better dose conformality and sparing of organs at risk than traditional IMRT plans is central to the project. Presented here are the materials and methods used to generate and manipulate the DAO procedure. Included is the introduction of a powerful Java-based toolkit, the Aperture-based Monte Carlo (MC) MPERT Optimizer (AMMO), that serves as a framework for optimization and provides streamlined access tomore » underlying particle transport packages. Comparison of the toolkit's dose calculations to those produced by the Eclipse TPS and the demonstration of a preliminary optimization are presented as first benchmarks. Excellent agreement is illustrated between the Eclipse TPS and AMMO for a 6MV photon field. The results of a simple optimization shows the functioning of the optimization framework, while significant research remains to characterize appropriate constraints.« less

Automatic treatment plan re-optimization for adaptive radiotherapy guided with the initial plan DVHs.

PubMed

Li, Nan; Zarepisheh, Masoud; Uribe-Sanchez, Andres; Moore, Kevin; Tian, Zhen; Zhen, Xin; Graves, Yan Jiang; Gautier, Quentin; Mell, Loren; Zhou, Linghong; Jia, Xun; Jiang, Steve

2013-12-21

Adaptive radiation therapy (ART) can reduce normal tissue toxicity and/or improve tumor control through treatment adaptations based on the current patient anatomy. Developing an efficient and effective re-planning algorithm is an important step toward the clinical realization of ART. For the re-planning process, manual trial-and-error approach to fine-tune planning parameters is time-consuming and is usually considered unpractical, especially for online ART. It is desirable to automate this step to yield a plan of acceptable quality with minimal interventions. In ART, prior information in the original plan is available, such as dose-volume histogram (DVH), which can be employed to facilitate the automatic re-planning process. The goal of this work is to develop an automatic re-planning algorithm to generate a plan with similar, or possibly better, DVH curves compared with the clinically delivered original plan. Specifically, our algorithm iterates the following two loops. An inner loop is the traditional fluence map optimization, in which we optimize a quadratic objective function penalizing the deviation of the dose received by each voxel from its prescribed or threshold dose with a set of fixed voxel weighting factors. In outer loop, the voxel weighting factors in the objective function are adjusted according to the deviation of the current DVH curves from those in the original plan. The process is repeated until the DVH curves are acceptable or maximum iteration step is reached. The whole algorithm is implemented on GPU for high efficiency. The feasibility of our algorithm has been demonstrated with three head-and-neck cancer IMRT cases, each having an initial planning CT scan and another treatment CT scan acquired in the middle of treatment course. Compared with the DVH curves in the original plan, the DVH curves in the resulting plan using our algorithm with 30 iterations are better for almost all structures. The re-optimization process takes about 30 s using our in-house optimization engine.

Underestimation of Project Costs

NASA Technical Reports Server (NTRS)

Jones, Harry W.

2015-01-01

Large projects almost always exceed their budgets. Estimating cost is difficult and estimated costs are usually too low. Three different reasons are suggested: bad luck, overoptimism, and deliberate underestimation. Project management can usually point to project difficulty and complexity, technical uncertainty, stakeholder conflicts, scope changes, unforeseen events, and other not really unpredictable bad luck. Project planning is usually over-optimistic, so the likelihood and impact of bad luck is systematically underestimated. Project plans reflect optimism and hope for success in a supposedly unique new effort rather than rational expectations based on historical data. Past project problems are claimed to be irrelevant because "This time it's different." Some bad luck is inevitable and reasonable optimism is understandable, but deliberate deception must be condemned. In a competitive environment, project planners and advocates often deliberately underestimate costs to help gain project approval and funding. Project benefits, cost savings, and probability of success are exaggerated and key risks ignored. Project advocates have incentives to distort information and conceal difficulties from project approvers. One naively suggested cure is more openness, honesty, and group adherence to shared overall goals. A more realistic alternative is threatening overrun projects with cancellation. Neither approach seems to solve the problem. A better method to avoid the delusions of over-optimism and the deceptions of biased advocacy is to base the project cost estimate on the actual costs of a large group of similar projects. Over optimism and deception can continue beyond the planning phase and into project execution. Hard milestones based on verified tests and demonstrations can provide a reality check.

Configuration evaluation and criteria plan. Volume 1: System trades study and design methodology plan (preliminary). Space Transportation Main Engine (STME) configuration study

NASA Technical Reports Server (NTRS)

Bair, E. K.

1986-01-01

The System Trades Study and Design Methodology Plan is used to conduct trade studies to define the combination of Space Shuttle Main Engine features that will optimize candidate engine configurations. This is accomplished by using vehicle sensitivities and engine parametric data to establish engine chamber pressure and area ratio design points for candidate engine configurations. Engineering analyses are to be conducted to refine and optimize the candidate configurations at their design points. The optimized engine data and characteristics are then evaluated and compared against other candidates being considered. The Evaluation Criteria Plan is then used to compare and rank the optimized engine configurations on the basis of cost.

Optimal motion planning for collision avoidance of mobile robots in non-stationary environments

NASA Technical Reports Server (NTRS)

Kyriakopoulos, K. J.; Saridis, G. N.

1992-01-01

An optimal control formulation of the problem of collision avoidance of mobile robots moving in general terrains containing moving obstacles is presented. A dynamic model of the mobile robot and the dynamic constraints are derived. Collision avoidance is guaranteed if the minimum distance between the robot and the object is nonzero. A nominal trajectory is assumed to be known from off-line planning. The main idea is to change the velocity along the nominal trajectory so that collisions are avoided. Time consistency with the nominal plan is desirable. A numerical solution of the optimization problem is obtained. A perturbation control type of approach is used to update the optimal plan. Simulation results verify the value of the proposed strategy.

A methodology for optimal MSW management, with an application in the waste transportation of Attica Region, Greece

DOE Office of Scientific and Technical Information (OSTI.GOV)

Economopoulou, M.A.; Economopoulou, A.A.; Economopoulos, A.P., E-mail: eco@otenet.gr

2013-11-15

Highlights: • A two-step (strategic and detailed optimal planning) methodology is used for solving complex MSW management problems. • A software package is outlined, which can be used for generating detailed optimal plans. • Sensitivity analysis compares alternative scenarios that address objections and/or wishes of local communities. • A case study shows the application of the above procedure in practice and demonstrates the results and benefits obtained. - Abstract: The paper describes a software system capable of formulating alternative optimal Municipal Solid Wastes (MSWs) management plans, each of which meets a set of constraints that may reflect selected objections and/ormore » wishes of local communities. The objective function to be minimized in each plan is the sum of the annualized capital investment and annual operating cost of all transportation, treatment and final disposal operations involved, taking into consideration the possible income from the sale of products and any other financial incentives or disincentives that may exist. For each plan formulated, the system generates several reports that define the plan, analyze its cost elements and yield an indicative profile of selected types of installations, as well as data files that facilitate the geographic representation of the optimal solution in maps through the use of GIS. A number of these reports compare the technical and economic data from all scenarios considered at the study area, municipality and installation level constituting in effect sensitivity analysis. The generation of alternative plans offers local authorities the opportunity of choice and the results of the sensitivity analysis allow them to choose wisely and with consensus. The paper presents also an application of this software system in the capital Region of Attica in Greece, for the purpose of developing an optimal waste transportation system in line with its approved waste management plan. The formulated plan was able to: (a) serve 113 Municipalities and Communities that generate nearly 2 million t/y of comingled MSW with distinctly different waste collection patterns, (b) take into consideration several existing waste transfer stations (WTS) and optimize their use within the overall plan, (c) select the most appropriate sites among the potentially suitable (new and in use) ones, (d) generate the optimal profile of each WTS proposed, and (e) perform sensitivity analysis so as to define the impact of selected sets of constraints (limitations in the availability of sites and in the capacity of their installations) on the design and cost of the ensuing optimal waste transfer system. The results show that optimal planning offers significant economic savings to municipalities, while reducing at the same time the present levels of traffic, fuel consumptions and air emissions in the congested Athens basin.« less

TH-EF-BRB-05: 4pi Non-Coplanar IMRT Beam Angle Selection by Convex Optimization with Group Sparsity Penalty

DOE Office of Scientific and Technical Information (OSTI.GOV)

O’Connor, D; Nguyen, D; Voronenko, Y

Purpose: Integrated beam orientation and fluence map optimization is expected to be the foundation of robust automated planning but existing heuristic methods do not promise global optimality. We aim to develop a new method for beam angle selection in 4π non-coplanar IMRT systems based on solving (globally) a single convex optimization problem, and to demonstrate the effectiveness of the method by comparison with a state of the art column generation method for 4π beam angle selection. Methods: The beam angle selection problem is formulated as a large scale convex fluence map optimization problem with an additional group sparsity term thatmore » encourages most candidate beams to be inactive. The optimization problem is solved using an accelerated first-order method, the Fast Iterative Shrinkage-Thresholding Algorithm (FISTA). The beam angle selection and fluence map optimization algorithm is used to create non-coplanar 4π treatment plans for several cases (including head and neck, lung, and prostate cases) and the resulting treatment plans are compared with 4π treatment plans created using the column generation algorithm. Results: In our experiments the treatment plans created using the group sparsity method meet or exceed the dosimetric quality of plans created using the column generation algorithm, which was shown superior to clinical plans. Moreover, the group sparsity approach converges in about 3 minutes in these cases, as compared with runtimes of a few hours for the column generation method. Conclusion: This work demonstrates the first non-greedy approach to non-coplanar beam angle selection, based on convex optimization, for 4π IMRT systems. The method given here improves both treatment plan quality and runtime as compared with a state of the art column generation algorithm. When the group sparsity term is set to zero, we obtain an excellent method for fluence map optimization, useful when beam angles have already been selected. NIH R43CA183390, NIH R01CA188300, Varian Medical Systems; Part of this research took place while D. O’Connor was a summer intern at RefleXion Medical.« less

Advanced Free Flight Planner and Dispatcher's Workstation: Preliminary Design Specification

NASA Technical Reports Server (NTRS)

Wilson, J.; Wright, C.; Couluris, G. J.

1997-01-01

The National Aeronautics and Space Administration (NASA) has implemented the Advanced Air Transportation Technology (AATT) program to investigate future improvements to the national and international air traffic management systems. This research, as part of the AATT program, developed preliminary design requirements for an advanced Airline Operations Control (AOC) dispatcher's workstation, with emphasis on flight planning. This design will support the implementation of an experimental workstation in NASA laboratories that would emulate AOC dispatch operations. The work developed an airline flight plan data base and specified requirements for: a computer tool for generation and evaluation of free flight, user preferred trajectories (UPT); the kernel of an advanced flight planning system to be incorporated into the UPT-generation tool; and an AOC workstation to house the UPT-generation tool and to provide a real-time testing environment. A prototype for the advanced flight plan optimization kernel was developed and demonstrated. The flight planner uses dynamic programming to search a four-dimensional wind and temperature grid to identify the optimal route, altitude and speed for successive segments of a flight. An iterative process is employed in which a series of trajectories are successively refined until the LTPT is identified. The flight planner is designed to function in the current operational environment as well as in free flight. The free flight environment would enable greater flexibility in UPT selection based on alleviation of current procedural constraints. The prototype also takes advantage of advanced computer processing capabilities to implement more powerful optimization routines than would be possible with older computer systems.

WE-AB-BRA-09: Sensitivity of Plan Re-Optimization to Errors in Deformable Image Registration in Online Adaptive Image-Guided Radiation Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

McClain, B; Olsen, J; Green, O

2015-06-15

Purpose: Online adaptive therapy (ART) relies on auto-contouring using deformable image registration (DIR). DIR’s inherent uncertainties require user intervention and manual edits while the patient is on the table. We investigated the dosimetric impact of DIR errors on the quality of re-optimized plans, and used the findings to establish regions for focusing manual edits to where DIR errors can Result in clinically relevant dose differences. Methods: Our clinical implementation of online adaptive MR-IGRT involves using DIR to transfer contours from CT to daily MR, followed by a physicians’ edits. The plan is then re-optimized to meet the organs at riskmore » (OARs) constraints. Re-optimized abdomen and pelvis plans generated based on physician edited OARs were selected as the baseline for evaluation. Plans were then re-optimized on auto-deformed contours with manual edits limited to pre-defined uniform rings (0 to 5cm) around the PTV. A 0cm ring indicates that the auto-deformed OARs were used without editing. The magnitude of the variations caused by the non-deterministic optimizer was quantified by repeat re-optimizations on the same geometry to determine the mean and standard deviation (STD). For each re-optimized plan, various volumetric parameters for the PTV, the OARs were extracted along with DVH and isodose evaluation. A plan was deemed acceptable if the variation from the baseline plan was within one STD. Results: Initial results show that for abdomen and pancreas cases, a minimum of 5cm margin around the PTV is required for contour corrections, while for pelvic and liver cases a 2–3 cm margin is sufficient. Conclusion: Focusing manual contour edits to regions of dosimetric relevance can reduce contouring time in the online ART process while maintaining a clinically comparable plan. Future work will further refine the contouring region by evaluating the path along the beams, dose gradients near the target and OAR dose metrics.« less

Network planning under uncertainties

NASA Astrophysics Data System (ADS)

Ho, Kwok Shing; Cheung, Kwok Wai

2008-11-01

One of the main focuses for network planning is on the optimization of network resources required to build a network under certain traffic demand projection. Traditionally, the inputs to this type of network planning problems are treated as deterministic. In reality, the varying traffic requirements and fluctuations in network resources can cause uncertainties in the decision models. The failure to include the uncertainties in the network design process can severely affect the feasibility and economics of the network. Therefore, it is essential to find a solution that can be insensitive to the uncertain conditions during the network planning process. As early as in the 1960's, a network planning problem with varying traffic requirements over time had been studied. Up to now, this kind of network planning problems is still being active researched, especially for the VPN network design. Another kind of network planning problems under uncertainties that has been studied actively in the past decade addresses the fluctuations in network resources. One such hotly pursued research topic is survivable network planning. It considers the design of a network under uncertainties brought by the fluctuations in topology to meet the requirement that the network remains intact up to a certain number of faults occurring anywhere in the network. Recently, the authors proposed a new planning methodology called Generalized Survivable Network that tackles the network design problem under both varying traffic requirements and fluctuations of topology. Although all the above network planning problems handle various kinds of uncertainties, it is hard to find a generic framework under more general uncertainty conditions that allows a more systematic way to solve the problems. With a unified framework, the seemingly diverse models and algorithms can be intimately related and possibly more insights and improvements can be brought out for solving the problem. This motivates us to seek a generic framework for solving the network planning problem under uncertainties. In addition to reviewing the various network planning problems involving uncertainties, we also propose that a unified framework based on robust optimization can be used to solve a rather large segment of network planning problem under uncertainties. Robust optimization is first introduced in the operations research literature and is a framework that incorporates information about the uncertainty sets for the parameters in the optimization model. Even though robust optimization is originated from tackling the uncertainty in the optimization process, it can serve as a comprehensive and suitable framework for tackling generic network planning problems under uncertainties. In this paper, we begin by explaining the main ideas behind the robust optimization approach. Then we demonstrate the capabilities of the proposed framework by giving out some examples of how the robust optimization framework can be applied to the current common network planning problems under uncertain environments. Next, we list some practical considerations for solving the network planning problem under uncertainties with the proposed framework. Finally, we conclude this article with some thoughts on the future directions for applying this framework to solve other network planning problems.

Electric power market agent design

NASA Astrophysics Data System (ADS)

Oh, Hyungseon

The electric power industry in many countries has been restructured in the hope of a more economically efficient system. In the restructured system, traditional operating and planning tools based on true marginal cost do not perform well since information required is strictly confidential. For developing a new tool, it is necessary to understand offer behavior. The main objective of this study is to create a new tool for power system planning. For the purpose, this dissertation develops models for a market and market participants. A new model is developed in this work for explaining a supply-side offer curve, and several variables are introduced to characterize the curve. Demand is estimated using a neural network, and a numerical optimization process is used to determine the values of the variables that maximize the profit of the agent. The amount of data required for the optimization is chosen with the aid of nonlinear dynamics. To suggest an optimal demand-side bidding function, two optimization problems are constructed and solved for maximizing consumer satisfaction based on the properties of two different types of demands: price-based demand and must-be-served demand. Several different simulations are performed to test how an agent reacts in various situations. The offer behavior depends on locational benefit as well as the offer strategies of competitors.

A gEUD-based inverse planning technique for HDR prostate brachytherapy: Feasibility study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Giantsoudi, D.; Department of Radiation Oncology, Francis H. Burr Proton Therapy Center, Boston, Massachusetts 02114; Baltas, D.

2013-04-15

Purpose: The purpose of this work was to study the feasibility of a new inverse planning technique based on the generalized equivalent uniform dose for image-guided high dose rate (HDR) prostate cancer brachytherapy in comparison to conventional dose-volume based optimization. Methods: The quality of 12 clinical HDR brachytherapy implants for prostate utilizing HIPO (Hybrid Inverse Planning Optimization) is compared with alternative plans, which were produced through inverse planning using the generalized equivalent uniform dose (gEUD). All the common dose-volume indices for the prostate and the organs at risk were considered together with radiobiological measures. The clinical effectiveness of the differentmore » dose distributions was investigated by comparing dose volume histogram and gEUD evaluators. Results: Our results demonstrate the feasibility of gEUD-based inverse planning in HDR brachytherapy implants for prostate. A statistically significant decrease in D{sub 10} or/and final gEUD values for the organs at risk (urethra, bladder, and rectum) was found while improving dose homogeneity or dose conformity of the target volume. Conclusions: Following the promising results of gEUD-based optimization in intensity modulated radiation therapy treatment optimization, as reported in the literature, the implementation of a similar model in HDR brachytherapy treatment plan optimization is suggested by this study. The potential of improved sparing of organs at risk was shown for various gEUD-based optimization parameter protocols, which indicates the ability of this method to adapt to the user's preferences.« less

Planning hybrid intensity modulated radiation therapy for whole-breast irradiation.

PubMed

Farace, Paolo; Zucca, Sergio; Solla, Ignazio; Fadda, Giuseppina; Durzu, Silvia; Porru, Sergio; Meleddu, Gianfranco; Deidda, Maria Assunta; Possanzini, Marco; Orrù, Sivia; Lay, Giancarlo

2012-09-01

To test tangential and not-tangential hybrid intensity modulated radiation therapy (IMRT) for whole-breast irradiation. Seventy-eight (36 right-, 42 left-) breast patients were randomly selected. Hybrid IMRT was performed by direct aperture optimization. A semiautomated method for planning hybrid IMRT was implemented using Pinnacle scripts. A plan optimization volume (POV), defined as the portion of the planning target volume covered by the open beams, was used as the target objective during inverse planning. Treatment goals were to prescribe a minimum dose of 47.5 Gy to greater than 90% of the POV and to minimize the POV and/or normal tissue receiving a dose greater than 107%. When treatment goals were not achieved by using a 4-field technique (2 conventional open plus 2 IMRT tangents), a 6-field technique was applied, adding 2 non tangential (anterior-oblique) IMRT beams. Using scripts, manual procedures were minimized (choice of optimal beam angle, setting monitor units for open tangentials, and POV definition). Treatment goals were achieved by using the 4-field technique in 61 of 78 (78%) patients. The 6-field technique was applied in the remaining 17 of 78 (22%) patients, allowing for significantly better achievement of goals, at the expense of an increase of low-dose (∼5 Gy) distribution in the contralateral tissue, heart, and lungs but with no significant increase of higher doses (∼20 Gy) in heart and lungs. The mean monitor unit contribution to IMRT beams was significantly greater (18.7% vs 9.9%) in the group of patients who required 6-field procedure. Because hybrid IMRT can be performed semiautomatically, it can be planned for a large number of patients with little impact on human or departmental resources, promoting it as the standard practice for whole-breast irradiation. Copyright © 2012 Elsevier Inc. All rights reserved.

SU-F-J-94: Development of a Plug-in Based Image Analysis Tool for Integration Into Treatment Planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Owen, D; Anderson, C; Mayo, C

Purpose: To extend the functionality of a commercial treatment planning system (TPS) to support (i) direct use of quantitative image-based metrics within treatment plan optimization and (ii) evaluation of dose-functional volume relationships to assist in functional image adaptive radiotherapy. Methods: A script was written that interfaces with a commercial TPS via an Application Programming Interface (API). The script executes a program that performs dose-functional volume analyses. Written in C#, the script reads the dose grid and correlates it with image data on a voxel-by-voxel basis through API extensions that can access registration transforms. A user interface was designed through WinFormsmore » to input parameters and display results. To test the performance of this program, image- and dose-based metrics computed from perfusion SPECT images aligned to the treatment planning CT were generated, validated, and compared. Results: The integration of image analysis information was successfully implemented as a plug-in to a commercial TPS. Perfusion SPECT images were used to validate the calculation and display of image-based metrics as well as dose-intensity metrics and histograms for defined structures on the treatment planning CT. Various biological dose correction models, custom image-based metrics, dose-intensity computations, and dose-intensity histograms were applied to analyze the image-dose profile. Conclusion: It is possible to add image analysis features to commercial TPSs through custom scripting applications. A tool was developed to enable the evaluation of image-intensity-based metrics in the context of functional targeting and avoidance. In addition to providing dose-intensity metrics and histograms that can be easily extracted from a plan database and correlated with outcomes, the system can also be extended to a plug-in optimization system, which can directly use the computed metrics for optimization of post-treatment tumor or normal tissue response models. Supported by NIH - P01 - CA059827.« less

Avionic Architecture for Model Predictive Control Application in Mars Sample & Return Rendezvous Scenario

NASA Astrophysics Data System (ADS)

Saponara, M.; Tramutola, A.; Creten, P.; Hardy, J.; Philippe, C.

2013-08-01

Optimization-based control techniques such as Model Predictive Control (MPC) are considered extremely attractive for space rendezvous, proximity operations and capture applications that require high level of autonomy, optimal path planning and dynamic safety margins. Such control techniques require high-performance computational needs for solving large optimization problems. The development and implementation in a flight representative avionic architecture of a MPC based Guidance, Navigation and Control system has been investigated in the ESA R&T study “On-line Reconfiguration Control System and Avionics Architecture” (ORCSAT) of the Aurora programme. The paper presents the baseline HW and SW avionic architectures, and verification test results obtained with a customised RASTA spacecraft avionics development platform from Aeroflex Gaisler.

Advanced Intelligent System Application to Load Forecasting and Control for Hybrid Electric Bus

NASA Technical Reports Server (NTRS)

Momoh, James; Chattopadhyay, Deb; Elfayoumy, Mahmoud

1996-01-01

The primary motivation for this research emanates from providing a decision support system to the electric bus operators in the municipal and urban localities which will guide the operators to maintain an optimal compromise among the noise level, pollution level, fuel usage etc. This study is backed up by our previous studies on study of battery characteristics, permanent magnet DC motor studies and electric traction motor size studies completed in the first year. The operator of the Hybrid Electric Car must determine optimal power management schedule to meet a given load demand for different weather and road conditions. The decision support system for the bus operator comprises three sub-tasks viz. forecast of the electrical load for the route to be traversed divided into specified time periods (few minutes); deriving an optimal 'plan' or 'preschedule' based on the load forecast for the entire time-horizon (i.e., for all time periods) ahead of time; and finally employing corrective control action to monitor and modify the optimal plan in real-time. A fully connected artificial neural network (ANN) model is developed for forecasting the kW requirement for hybrid electric bus based on inputs like climatic conditions, passenger load, road inclination, etc. The ANN model is trained using back-propagation algorithm employing improved optimization techniques like projected Lagrangian technique. The pre-scheduler is based on a Goal-Programming (GP) optimization model with noise, pollution and fuel usage as the three objectives. GP has the capability of analyzing the trade-off among the conflicting objectives and arriving at the optimal activity levels, e.g., throttle settings. The corrective control action or the third sub-task is formulated as an optimal control model with inputs from the real-time data base as well as the GP model to minimize the error (or deviation) from the optimal plan. These three activities linked with the ANN forecaster proving the output to the GP model which in turn produces the pre-schedule of the optimal control model. Some preliminary results based on a hypothetical test case will be presented for the load forecasting module. The computer codes for the three modules will be made available fe adoption by bus operating agencies. Sample results will be provided using these models. The software will be a useful tool for supporting the control systems for the Electric Bus project of NASA.

The ITER bolometer diagnostic: Status and plansa)

NASA Astrophysics Data System (ADS)

Meister, H.; Giannone, L.; Horton, L. D.; Raupp, G.; Zeidner, W.; Grunda, G.; Kalvin, S.; Fischer, U.; Serikov, A.; Stickel, S.; Reichle, R.

2008-10-01

A consortium consisting of four EURATOM Associations has been set up to develop the project plan for the full development of the ITER bolometer diagnostic and to continue urgent R&D activities. An overview of the current status is given, including detector development, line-of-sight optimization, performance analysis as well as the design of the diagnostic components and their integration in ITER. This is complemented by the presentation of plans for future activities required to successfully implement the bolometer diagnostic, ranging from the detector development over diagnostic design and prototype testing to RH tools for calibration.

Comparison of optimization algorithms in intensity-modulated radiation therapy planning

NASA Astrophysics Data System (ADS)

Kendrick, Rachel

Intensity-modulated radiation therapy is used to better conform the radiation dose to the target, which includes avoiding healthy tissue. Planning programs employ optimization methods to search for the best fluence of each photon beam, and therefore to create the best treatment plan. The Computational Environment for Radiotherapy Research (CERR), a program written in MATLAB, was used to examine some commonly-used algorithms for one 5-beam plan. Algorithms include the genetic algorithm, quadratic programming, pattern search, constrained nonlinear optimization, simulated annealing, the optimization method used in Varian EclipseTM, and some hybrids of these. Quadratic programing, simulated annealing, and a quadratic/simulated annealing hybrid were also separately compared using different prescription doses. The results of each dose-volume histogram as well as the visual dose color wash were used to compare the plans. CERR's built-in quadratic programming provided the best overall plan, but avoidance of the organ-at-risk was rivaled by other programs. Hybrids of quadratic programming with some of these algorithms seems to suggest the possibility of better planning programs, as shown by the improved quadratic/simulated annealing plan when compared to the simulated annealing algorithm alone. Further experimentation will be done to improve cost functions and computational time.

Application of Particle Swarm Optimization in Computer Aided Setup Planning

NASA Astrophysics Data System (ADS)

Kafashi, Sajad; Shakeri, Mohsen; Abedini, Vahid

2011-01-01

New researches are trying to integrate computer aided design (CAD) and computer aided manufacturing (CAM) environments. The role of process planning is to convert the design specification into manufacturing instructions. Setup planning has a basic role in computer aided process planning (CAPP) and significantly affects the overall cost and quality of machined part. This research focuses on the development for automatic generation of setups and finding the best setup plan in feasible condition. In order to computerize the setup planning process, three major steps are performed in the proposed system: a) Extraction of machining data of the part. b) Analyzing and generation of all possible setups c) Optimization to reach the best setup plan based on cost functions. Considering workshop resources such as machine tool, cutter and fixture, all feasible setups could be generated. Then the problem is adopted with technological constraints such as TAD (tool approach direction), tolerance relationship and feature precedence relationship to have a completely real and practical approach. The optimal setup plan is the result of applying the PSO (particle swarm optimization) algorithm into the system using cost functions. A real sample part is illustrated to demonstrate the performance and productivity of the system.

High velocity penetration into fibre-reinforced concrete materials - protection of buildings

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anderson, W.F.; Watson, A.J.; Armstrong, P.J.

1983-05-01

Fibre reinforced concrete suitable for spraying onto existing structures is being examined to assess its resistance to penetration by 7.62mm diameter armour piercing projectiles. A major test programme is being carried out to examine the influence of aggregate type and fibre type. For each aggregate/fibre combination a statistical method is being used to plan test series which will lead to optimization of the concrete in terms of water/cement ratio, fibre content and aggregate/cement ratio. The minimum thickness of optimized concretes to resist penetration by the projectile and minimise spall and scabbing, will be determined. The mechanics of the impact andmore » penetration event are being studied and a possible method of deflecting the projectile within the concrete is suggested.« less

Flight Testing of Terrain-Relative Navigation and Large-Divert Guidance on a VTVL Rocket

NASA Technical Reports Server (NTRS)

Trawny, Nikolas; Benito, Joel; Tweddle, Brent; Bergh, Charles F.; Khanoyan, Garen; Vaughan, Geoffrey M.; Zheng, Jason X.; Villalpando, Carlos Y.; Cheng, Yang; Scharf, Daniel P.;

An approach to multiobjective optimization of rotational therapy. II. Pareto optimal surfaces and linear combinations of modulated blocked arcs for a prostate geometry.

PubMed

Pardo-Montero, Juan; Fenwick, John D

2010-06-01

The purpose of this work is twofold: To further develop an approach to multiobjective optimization of rotational therapy treatments recently introduced by the authors [J. Pardo-Montero and J. D. Fenwick, "An approach to multiobjective optimization of rotational therapy," Med. Phys. 36, 3292-3303 (2009)], especially regarding its application to realistic geometries, and to study the quality (Pareto optimality) of plans obtained using such an approach by comparing them with Pareto optimal plans obtained through inverse planning. In the previous work of the authors, a methodology is proposed for constructing a large number of plans, with different compromises between the objectives involved, from a small number of geometrically based arcs, each arc prioritizing different objectives. Here, this method has been further developed and studied. Two different techniques for constructing these arcs are investigated, one based on image-reconstruction algorithms and the other based on more common gradient-descent algorithms. The difficulty of dealing with organs abutting the target, briefly reported in previous work of the authors, has been investigated using partial OAR unblocking. Optimality of the solutions has been investigated by comparison with a Pareto front obtained from inverse planning. A relative Euclidean distance has been used to measure the distance of these plans to the Pareto front, and dose volume histogram comparisons have been used to gauge the clinical impact of these distances. A prostate geometry has been used for the study. For geometries where a blocked OAR abuts the target, moderate OAR unblocking can substantially improve target dose distribution and minimize hot spots while not overly compromising dose sparing of the organ. Image-reconstruction type and gradient-descent blocked-arc computations generate similar results. The Pareto front for the prostate geometry, reconstructed using a large number of inverse plans, presents a hockey-stick shape comprising two regions: One where the dose to the target is close to prescription and trade-offs can be made between doses to the organs at risk and (small) changes in target dose, and one where very substantial rectal sparing is achieved at the cost of large target underdosage. Plans computed following the approach using a conformal arc and four blocked arcs generally lie close to the Pareto front, although distances of some plans from high gradient regions of the Pareto front can be greater. Only around 12% of plans lie a relative Euclidean distance of 0.15 or greater from the Pareto front. Using the alternative distance measure of Craft ["Calculating and controlling the error of discrete representations of Pareto surfaces in convex multi-criteria optimization," Phys. Medica (to be published)], around 2/5 of plans lie more than 0.05 from the front. Computation of blocked arcs is quite fast, the algorithms requiring 35%-80% of the running time per iteration needed for conventional inverse plan computation. The geometry-based arc approach to multicriteria optimization of rotational therapy allows solutions to be obtained that lie close to the Pareto front. Both the image-reconstruction type and gradient-descent algorithms produce similar modulated arcs, the latter one perhaps being preferred because it is more easily implementable in standard treatment planning systems. Moderate unblocking provides a good way of dealing with OARs which abut the PTV. Optimization of geometry-based arcs is faster than usual inverse optimization of treatment plans, making this approach more rapid than an inverse-based Pareto front reconstruction.

Highly Efficient Training, Refinement, and Validation of a Knowledge-based Planning Quality-Control System for Radiation Therapy Clinical Trials

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Nan; Carmona, Ruben; Sirak, Igor

Purpose: To demonstrate an efficient method for training and validation of a knowledge-based planning (KBP) system as a radiation therapy clinical trial plan quality-control system. Methods and Materials: We analyzed 86 patients with stage IB through IVA cervical cancer treated with intensity modulated radiation therapy at 2 institutions according to the standards of the INTERTECC (International Evaluation of Radiotherapy Technology Effectiveness in Cervical Cancer, National Clinical Trials Network identifier: 01554397) protocol. The protocol used a planning target volume and 2 primary organs at risk: pelvic bone marrow (PBM) and bowel. Secondary organs at risk were rectum and bladder. Initial unfiltered dose-volumemore » histogram (DVH) estimation models were trained using all 86 plans. Refined training sets were created by removing sub-optimal plans from the unfiltered sample, and DVH estimation models… and DVH estimation models were constructed by identifying 30 of 86 plans emphasizing PBM sparing (comparing protocol-specified dosimetric cutpoints V{sub 10} (percentage volume of PBM receiving at least 10 Gy dose) and V{sub 20} (percentage volume of PBM receiving at least 20 Gy dose) with unfiltered predictions) and another 30 of 86 plans emphasizing bowel sparing (comparing V{sub 40} (absolute volume of bowel receiving at least 40 Gy dose) and V{sub 45} (absolute volume of bowel receiving at least 45 Gy dose), 9 in common with the PBM set). To obtain deliverable KBP plans, refined models must inform patient-specific optimization objectives and/or priorities (an auto-planning “routine”). Four candidate routines emphasizing different tradeoffs were composed, and a script was developed to automatically re-plan multiple patients with each routine. After selection of the routine that best met protocol objectives in the 51-patient training sample (KBP{sub FINAL}), protocol-specific DVH metrics and normal tissue complication probability were compared for original versus KBP{sub FINAL} plans across the 35-patient validation set. Paired t tests were used to test differences between planning sets. Results: KBP{sub FINAL} plans outperformed manual planning across the validation set in all protocol-specific DVH cutpoints. The mean normal tissue complication probability for gastrointestinal toxicity was lower for KBP{sub FINAL} versus validation-set plans (48.7% vs 53.8%, P<.001). Similarly, the estimated mean white blood cell count nadir was higher (2.77 vs 2.49 k/mL, P<.001) with KBP{sub FINAL} plans, indicating lowered probability of hematologic toxicity. Conclusions: This work demonstrates that a KBP system can be efficiently trained and refined for use in radiation therapy clinical trials with minimal effort. This patient-specific plan quality control resulted in improvements on protocol-specific dosimetric endpoints.« less

Choosing a reliability inspection plan for interval censored data

DOE PAGES

Lu, Lu; Anderson-Cook, Christine Michaela

2017-04-19

Reliability test plans are important for producing precise and accurate assessment of reliability characteristics. This paper explores different strategies for choosing between possible inspection plans for interval censored data given a fixed testing timeframe and budget. A new general cost structure is proposed for guiding precise quantification of total cost in inspection test plan. Multiple summaries of reliability are considered and compared as the criteria for choosing the best plans using an easily adapted method. Different cost structures and representative true underlying reliability curves demonstrate how to assess different strategies given the logistical constraints and nature of the problem. Resultsmore » show several general patterns exist across a wide variety of scenarios. Given the fixed total cost, plans that inspect more units with less frequency based on equally spaced time points are favored due to the ease of implementation and consistent good performance across a large number of case study scenarios. Plans with inspection times chosen based on equally spaced probabilities offer improved reliability estimates for the shape of the distribution, mean lifetime, and failure time for a small fraction of population only for applications with high infant mortality rates. The paper uses a Monte Carlo simulation based approach in addition to the common evaluation based on the asymptotic variance and offers comparison and recommendation for different applications with different objectives. Additionally, the paper outlines a variety of different reliability metrics to use as criteria for optimization, presents a general method for evaluating different alternatives, as well as provides case study results for different common scenarios.« less

Choosing a reliability inspection plan for interval censored data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lu, Lu; Anderson-Cook, Christine Michaela

Reliability test plans are important for producing precise and accurate assessment of reliability characteristics. This paper explores different strategies for choosing between possible inspection plans for interval censored data given a fixed testing timeframe and budget. A new general cost structure is proposed for guiding precise quantification of total cost in inspection test plan. Multiple summaries of reliability are considered and compared as the criteria for choosing the best plans using an easily adapted method. Different cost structures and representative true underlying reliability curves demonstrate how to assess different strategies given the logistical constraints and nature of the problem. Resultsmore » show several general patterns exist across a wide variety of scenarios. Given the fixed total cost, plans that inspect more units with less frequency based on equally spaced time points are favored due to the ease of implementation and consistent good performance across a large number of case study scenarios. Plans with inspection times chosen based on equally spaced probabilities offer improved reliability estimates for the shape of the distribution, mean lifetime, and failure time for a small fraction of population only for applications with high infant mortality rates. The paper uses a Monte Carlo simulation based approach in addition to the common evaluation based on the asymptotic variance and offers comparison and recommendation for different applications with different objectives. Additionally, the paper outlines a variety of different reliability metrics to use as criteria for optimization, presents a general method for evaluating different alternatives, as well as provides case study results for different common scenarios.« less

A case management tool for occupational health nurses: development, testing, and application.

PubMed

Mannon, J A; Conrad, K M; Blue, C L; Muran, S

1994-08-01

1. Case management is a process of coordinating an individual client's health care services to achieve optimal, quality care delivered in a cost effective manner. The case manager establishes a provider network, recommends treatment plans that assure quality and efficacy while controlling costs, monitors outcomes, and maintains a strong communication link among all the parties. 2. Through development of audit tools such as the one presented in this article, occupational health nurses can document case management activities and provide employers with measurable outcomes. 3. The Case Management Activity Checklist was tested using data from 61 firefighters' musculoskeletal injury cases. 4. The activities on the checklist are a step by step process: case identification/case disposition; assessment; return to work plan; resource identification; collaborative communication; and evaluation.

Treatment Planning and Image Guidance for Radiofrequency Ablations of Large Tumors

PubMed Central

Ren, Hongliang; Campos-Nanez, Enrique; Yaniv, Ziv; Banovac, Filip; Abeledo, Hernan; Hata, Nobuhiko; Cleary, Kevin

2014-01-01

This article addresses the two key challenges in computer-assisted percutaneous tumor ablation: planning multiple overlapping ablations for large tumors while avoiding critical structures, and executing the prescribed plan. Towards semi-automatic treatment planning for image-guided surgical interventions, we develop a systematic approach to the needle-based ablation placement task, ranging from pre-operative planning algorithms to an intra-operative execution platform. The planning system incorporates clinical constraints on ablations and trajectories using a multiple objective optimization formulation, which consists of optimal path selection and ablation coverage optimization based on integer programming. The system implementation is presented and validated in phantom studies and on an animal model. The presented system can potentially be further extended for other ablation techniques such as cryotherapy. PMID:24235279

Compiling quantum circuits to realistic hardware architectures using temporal planners

NASA Astrophysics Data System (ADS)

Venturelli, Davide; Do, Minh; Rieffel, Eleanor; Frank, Jeremy

2018-04-01

To run quantum algorithms on emerging gate-model quantum hardware, quantum circuits must be compiled to take into account constraints on the hardware. For near-term hardware, with only limited means to mitigate decoherence, it is critical to minimize the duration of the circuit. We investigate the application of temporal planners to the problem of compiling quantum circuits to newly emerging quantum hardware. While our approach is general, we focus on compiling to superconducting hardware architectures with nearest neighbor constraints. Our initial experiments focus on compiling Quantum Alternating Operator Ansatz (QAOA) circuits whose high number of commuting gates allow great flexibility in the order in which the gates can be applied. That freedom makes it more challenging to find optimal compilations but also means there is a greater potential win from more optimized compilation than for less flexible circuits. We map this quantum circuit compilation problem to a temporal planning problem, and generated a test suite of compilation problems for QAOA circuits of various sizes to a realistic hardware architecture. We report compilation results from several state-of-the-art temporal planners on this test set. This early empirical evaluation demonstrates that temporal planning is a viable approach to quantum circuit compilation.

Technology Implementation Plan: Irradiation Testing and Qualification for Nuclear Thermal Propulsion Fuel

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harrison, Thomas J.; Howard, Richard H.; Rader, Jordan D.

This document is a notional technology implementation plan (TIP) for the development, testing, and qualification of a prototypic fuel element to support design and construction of a nuclear thermal propulsion (NTP) engine, specifically its pre-flight ground test. This TIP outlines a generic methodology for the progression from non-nuclear out-of-pile (OOP) testing through nuclear in-pile (IP) testing, at operational temperatures, flows, and specific powers, of an NTP fuel element in an existing test reactor. Subsequent post-irradiation examination (PIE) will occur in existing radiological facilities. Further, the methodology is intended to be nonspecific with respect to fuel types and irradiation or examinationmore » facilities. The goals of OOP and IP testing are to provide confidence in the operational performance of fuel system concepts and provide data to program leadership for system optimization and fuel down-selection. The test methodology, parameters, collected data, and analytical results from OOP, IP, and PIE will be documented for reference by the NTP operator and the appropriate regulatory and oversight authorities. Final full-scale integrated testing would be performed separately by the reactor operator as part of the preflight ground test.« less

TU-AB-BRB-01: Coverage Evaluation and Probabilistic Treatment Planning as a Margin Alternative

DOE Office of Scientific and Technical Information (OSTI.GOV)

Siebers, J.

The accepted clinical method to accommodate targeting uncertainties inherent in fractionated external beam radiation therapy is to utilize GTV-to-CTV and CTV-to-PTV margins during the planning process to design a PTV-conformal static dose distribution on the planning image set. Ideally, margins are selected to ensure a high (e.g. >95%) target coverage probability (CP) in spite of inherent inter- and intra-fractional positional variations, tissue motions, and initial contouring uncertainties. Robust optimization techniques, also known as probabilistic treatment planning techniques, explicitly incorporate the dosimetric consequences of targeting uncertainties by including CP evaluation into the planning optimization process along with coverage-based planning objectives. Themore » treatment planner no longer needs to use PTV and/or PRV margins; instead robust optimization utilizes probability distributions of the underlying uncertainties in conjunction with CP-evaluation for the underlying CTVs and OARs to design an optimal treated volume. This symposium will describe CP-evaluation methods as well as various robust planning techniques including use of probability-weighted dose distributions, probability-weighted objective functions, and coverage optimized planning. Methods to compute and display the effect of uncertainties on dose distributions will be presented. The use of robust planning to accommodate inter-fractional setup uncertainties, organ deformation, and contouring uncertainties will be examined as will its use to accommodate intra-fractional organ motion. Clinical examples will be used to inter-compare robust and margin-based planning, highlighting advantages of robust-plans in terms of target and normal tissue coverage. Robust-planning limitations as uncertainties approach zero and as the number of treatment fractions becomes small will be presented, as well as the factors limiting clinical implementation of robust planning. Learning Objectives: To understand robust-planning as a clinical alternative to using margin-based planning. To understand conceptual differences between uncertainty and predictable motion. To understand fundamental limitations of the PTV concept that probabilistic planning can overcome. To understand the major contributing factors to target and normal tissue coverage probability. To understand the similarities and differences of various robust planning techniques To understand the benefits and limitations of robust planning techniques.« less

TU-AB-BRB-03: Coverage-Based Treatment Planning to Accommodate Organ Deformable Motions and Contouring Uncertainties for Prostate Treatment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, H.

The accepted clinical method to accommodate targeting uncertainties inherent in fractionated external beam radiation therapy is to utilize GTV-to-CTV and CTV-to-PTV margins during the planning process to design a PTV-conformal static dose distribution on the planning image set. Ideally, margins are selected to ensure a high (e.g. >95%) target coverage probability (CP) in spite of inherent inter- and intra-fractional positional variations, tissue motions, and initial contouring uncertainties. Robust optimization techniques, also known as probabilistic treatment planning techniques, explicitly incorporate the dosimetric consequences of targeting uncertainties by including CP evaluation into the planning optimization process along with coverage-based planning objectives. Themore » treatment planner no longer needs to use PTV and/or PRV margins; instead robust optimization utilizes probability distributions of the underlying uncertainties in conjunction with CP-evaluation for the underlying CTVs and OARs to design an optimal treated volume. This symposium will describe CP-evaluation methods as well as various robust planning techniques including use of probability-weighted dose distributions, probability-weighted objective functions, and coverage optimized planning. Methods to compute and display the effect of uncertainties on dose distributions will be presented. The use of robust planning to accommodate inter-fractional setup uncertainties, organ deformation, and contouring uncertainties will be examined as will its use to accommodate intra-fractional organ motion. Clinical examples will be used to inter-compare robust and margin-based planning, highlighting advantages of robust-plans in terms of target and normal tissue coverage. Robust-planning limitations as uncertainties approach zero and as the number of treatment fractions becomes small will be presented, as well as the factors limiting clinical implementation of robust planning. Learning Objectives: To understand robust-planning as a clinical alternative to using margin-based planning. To understand conceptual differences between uncertainty and predictable motion. To understand fundamental limitations of the PTV concept that probabilistic planning can overcome. To understand the major contributing factors to target and normal tissue coverage probability. To understand the similarities and differences of various robust planning techniques To understand the benefits and limitations of robust planning techniques.« less

TU-AB-BRB-02: Stochastic Programming Methods for Handling Uncertainty and Motion in IMRT Planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Unkelbach, J.

The accepted clinical method to accommodate targeting uncertainties inherent in fractionated external beam radiation therapy is to utilize GTV-to-CTV and CTV-to-PTV margins during the planning process to design a PTV-conformal static dose distribution on the planning image set. Ideally, margins are selected to ensure a high (e.g. >95%) target coverage probability (CP) in spite of inherent inter- and intra-fractional positional variations, tissue motions, and initial contouring uncertainties. Robust optimization techniques, also known as probabilistic treatment planning techniques, explicitly incorporate the dosimetric consequences of targeting uncertainties by including CP evaluation into the planning optimization process along with coverage-based planning objectives. Themore » treatment planner no longer needs to use PTV and/or PRV margins; instead robust optimization utilizes probability distributions of the underlying uncertainties in conjunction with CP-evaluation for the underlying CTVs and OARs to design an optimal treated volume. This symposium will describe CP-evaluation methods as well as various robust planning techniques including use of probability-weighted dose distributions, probability-weighted objective functions, and coverage optimized planning. Methods to compute and display the effect of uncertainties on dose distributions will be presented. The use of robust planning to accommodate inter-fractional setup uncertainties, organ deformation, and contouring uncertainties will be examined as will its use to accommodate intra-fractional organ motion. Clinical examples will be used to inter-compare robust and margin-based planning, highlighting advantages of robust-plans in terms of target and normal tissue coverage. Robust-planning limitations as uncertainties approach zero and as the number of treatment fractions becomes small will be presented, as well as the factors limiting clinical implementation of robust planning. Learning Objectives: To understand robust-planning as a clinical alternative to using margin-based planning. To understand conceptual differences between uncertainty and predictable motion. To understand fundamental limitations of the PTV concept that probabilistic planning can overcome. To understand the major contributing factors to target and normal tissue coverage probability. To understand the similarities and differences of various robust planning techniques To understand the benefits and limitations of robust planning techniques.« less

Development of an adjoint sensitivity field-based treatment-planning technique for the use of newly designed directional LDR sources in brachytherapy.

PubMed

Chaswal, V; Thomadsen, B R; Henderson, D L

2012-02-21

The development and application of an automated 3D greedy heuristic (GH) optimization algorithm utilizing the adjoint sensitivity fields for treatment planning to assess the advantage of directional interstitial prostate brachytherapy is presented. Directional and isotropic dose kernels generated using Monte Carlo simulations based on Best Industries model 2301 I-125 source are utilized for treatment planning. The newly developed GH algorithm is employed for optimization of the treatment plans for seven interstitial prostate brachytherapy cases using mixed sources (directional brachytherapy) and using only isotropic sources (conventional brachytherapy). All treatment plans resulted in V100 > 98% and D90 > 45 Gy for the target prostate region. For the urethra region, the D10(Ur), D90(Ur) and V150(Ur) and for the rectum region the V100cc, D2cc, D90(Re) and V90(Re) all are reduced significantly when mixed sources brachytherapy is used employing directional sources. The simulations demonstrated that the use of directional sources in the low dose-rate (LDR) brachytherapy of the prostate clearly benefits in sparing the urethra and the rectum sensitive structures from overdose. The time taken for a conventional treatment plan is less than three seconds, while the time taken for a mixed source treatment plan is less than nine seconds, as tested on an Intel Core2 Duo 2.2 GHz processor with 1GB RAM. The new 3D GH algorithm is successful in generating a feasible LDR brachytherapy treatment planning solution with an extra degree of freedom, i.e. directionality in very little time.

Development of an adjoint sensitivity field-based treatment-planning technique for the use of newly designed directional LDR sources in brachytherapy

NASA Astrophysics Data System (ADS)

Chaswal, V.; Thomadsen, B. R.; Henderson, D. L.

2012-02-01

The development and application of an automated 3D greedy heuristic (GH) optimization algorithm utilizing the adjoint sensitivity fields for treatment planning to assess the advantage of directional interstitial prostate brachytherapy is presented. Directional and isotropic dose kernels generated using Monte Carlo simulations based on Best Industries model 2301 I-125 source are utilized for treatment planning. The newly developed GH algorithm is employed for optimization of the treatment plans for seven interstitial prostate brachytherapy cases using mixed sources (directional brachytherapy) and using only isotropic sources (conventional brachytherapy). All treatment plans resulted in V100 > 98% and D90 > 45 Gy for the target prostate region. For the urethra region, the D10Ur, D90Ur and V150Ur and for the rectum region the V100cc, D2cc, D90Re and V90Re all are reduced significantly when mixed sources brachytherapy is used employing directional sources. The simulations demonstrated that the use of directional sources in the low dose-rate (LDR) brachytherapy of the prostate clearly benefits in sparing the urethra and the rectum sensitive structures from overdose. The time taken for a conventional treatment plan is less than three seconds, while the time taken for a mixed source treatment plan is less than nine seconds, as tested on an Intel Core2 Duo 2.2 GHz processor with 1GB RAM. The new 3D GH algorithm is successful in generating a feasible LDR brachytherapy treatment planning solution with an extra degree of freedom, i.e. directionality in very little time.

Recent Progress on High-Current SRF Cavities at Jlab

DOE Office of Scientific and Technical Information (OSTI.GOV)

Robert Rimmer, William Clemens, James Henry, Peter Kneisel, Kurt Macha, Frank Marhauser, Larry Turlington, Haipeng Wang, Daniel Forehand

2010-05-01

JLab has designed and fabricated several prototype SRF cavities with cell shapes optimized for high current beams and with strong damping of unwanted higher order modes. We report on the latest test results of these cavities and on developments of concepts for new variants optimized for particular applications such as light sources and high-power proton accelerators, including betas less than one. We also report on progress towards a first beam test of this design in the recirculation loop of the JLab ERL based FEL. With growing interest worldwide in applications of SRF for high-average power electron and hadron machines, amore » practical test of these concepts is highly desirable. We plan to package two prototype cavities in a de-mountable cryomodule for temporary installation into the JLab FEL for testing with RF and beam. This will allow verification of all critical design and operational parameters paving the way to a full-scale prototype cryomodule.« less

SU-E-T-574: Novel Chance-Constrained Optimization in Intensity-Modulated Proton Therapy Planning to Account for Range and Patient Setup Uncertainties

DOE Office of Scientific and Technical Information (OSTI.GOV)

An, Y; Liang, J; Liu, W

2015-06-15

Purpose: We propose to apply a probabilistic framework, namely chanceconstrained optimization, in the intensity-modulated proton therapy (IMPT) planning subject to range and patient setup uncertainties. The purpose is to hedge against the influence of uncertainties and improve robustness of treatment plans. Methods: IMPT plans were generated for a typical prostate patient. Nine dose distributions are computed — the nominal one and one each for ±5mm setup uncertainties along three cardinal axes and for ±3.5% range uncertainty. These nine dose distributions are supplied to the solver CPLEX as chance constraints to explicitly control plan robustness under these representative uncertainty scenarios withmore » certain probability. This probability is determined by the tolerance level. We make the chance-constrained model tractable by converting it to a mixed integer optimization problem. The quality of plans derived from this method is evaluated using dose-volume histogram (DVH) indices such as tumor dose homogeneity (D5% – D95%) and coverage (D95%) and normal tissue sparing like V70 of rectum, V65, and V40 of bladder. We also compare the results from this novel method with the conventional PTV-based method to further demonstrate its effectiveness Results: Our model can yield clinically acceptable plans within 50 seconds. The chance-constrained optimization produces IMPT plans with comparable target coverage, better target dose homogeneity, and better normal tissue sparing compared to the PTV-based optimization [D95% CTV: 67.9 vs 68.7 (Gy), D5% – D95% CTV: 11.9 vs 18 (Gy), V70 rectum: 0.0 % vs 0.33%, V65 bladder: 2.17% vs 9.33%, V40 bladder: 8.83% vs 21.83%]. It also simultaneously makes the plan more robust [Width of DVH band at D50%: 2.0 vs 10.0 (Gy)]. The tolerance level may be varied to control the tradeoff between plan robustness and quality. Conclusion: The chance-constrained optimization generates superior IMPT plan compared to the PTV-based optimization with explicit control of plan robustness. NIH/NCI K25CA168984, Eagles Cancer Research Career Development, The Lawrence W. and Marilyn W. Matteson Fund for Cancer Research, Mayo ASU Seed Grant, and The Kemper Marley Foundation.« less

A broad scope knowledge based model for optimization of VMAT in esophageal cancer: validation and assessment of plan quality among different treatment centers.

PubMed

Fogliata, Antonella; Nicolini, Giorgia; Clivio, Alessandro; Vanetti, Eugenio; Laksar, Sarbani; Tozzi, Angelo; Scorsetti, Marta; Cozzi, Luca

2015-10-31

To evaluate the performance of a broad scope model-based optimisation process for volumetric modulated arc therapy applied to esophageal cancer. A set of 70 previously treated patients in two different institutions, were selected to train a model for the prediction of dose-volume constraints. The model was built with a broad-scope purpose, aiming to be effective for different dose prescriptions and tumour localisations. It was validated on three groups of patients from the same institution and from another clinic not providing patients for the training phase. Comparison of the automated plans was done against reference cases given by the clinically accepted plans. Quantitative improvements (statistically significant for the majority of the analysed dose-volume parameters) were observed between the benchmark and the test plans. Of 624 dose-volume objectives assessed for plan evaluation, in 21 cases (3.3 %) the reference plans failed to respect the constraints while the model-based plans succeeded. Only in 3 cases (<0.5 %) the reference plans passed the criteria while the model-based failed. In 5.3 % of the cases both groups of plans failed and in the remaining cases both passed the tests. Plans were optimised using a broad scope knowledge-based model to determine the dose-volume constraints. The results showed dosimetric improvements when compared to the benchmark data. Particularly the plans optimised for patients from the third centre, not participating to the training, resulted in superior quality. The data suggests that the new engine is reliable and could encourage its application to clinical practice.

A detailed dosimetric comparison between manual and inverse plans in HDR intracavitary/interstitial cervical cancer brachytherapy.

PubMed

Trnková, Petra; Baltas, Dimos; Karabis, Andreas; Stock, Markus; Dimopoulos, Johannes; Georg, Dietmar; Pötter, Richard; Kirisits, Christian

2010-12-01

The purpose of this study was to compare two inverse planning algorithms for cervical cancer brachytherapy and a conventional manual treatment planning according to the MUW (Medical University of Vienna) protocol. For 20 patients, manually optimized, and, inversely optimized treatment plans with Hybrid Inverse treatment Planning and Optimization (HIPO) and with Inverse Planning Simulated Annealing (IPSA) were created. Dosimetric parameters, absolute volumes of normal tissue receiving reference doses, absolute loading times of tandem, ring and interstitial needles, Paddick and COIN conformity indices were evaluated. HIPO was able to achieve a similar dose distribution to manual planning with the restriction of high dose regions. It reduced the loading time of needles and the overall treatment time. The values of both conformity indices were the lowest. IPSA was able to achieve acceptable dosimetric results. However, it overloaded the needles. This resulted in high dose regions located in the normal tissue. The Paddick index for the volume of two times prescribed dose was outstandingly low. HIPO can produce clinically acceptable treatment plans with the elimination of high dose regions in normal tissue. Compared to IPSA, it is an inverse optimization method which takes into account current clinical experience gained from manual treatment planning.

A detailed dosimetric comparison between manual and inverse plans in HDR intracavitary/interstitial cervical cancer brachytherapy

PubMed Central

Baltas, Dimos; Karabis, Andreas; Stock, Markus; Dimopoulos, Johannes; Georg, Dietmar; Pötter, Richard; Kirisits, Christian

2011-01-01

Purpose The purpose of this study was to compare two inverse planning algorithms for cervical cancer brachytherapy and a conventional manual treatment planning according to the MUW (Medical University of Vienna) protocol. Material and methods For 20 patients, manually optimized, and, inversely optimized treatment plans with Hybrid Inverse treatment Planning and Optimization (HIPO) and with Inverse Planning Simulated Annealing (IPSA) were created. Dosimetric parameters, absolute volumes of normal tissue receiving reference doses, absolute loading times of tandem, ring and interstitial needles, Paddick and COIN conformity indices were evaluated. Results HIPO was able to achieve a similar dose distribution to manual planning with the restriction of high dose regions. It reduced the loading time of needles and the overall treatment time. The values of both conformity indices were the lowest. IPSA was able to achieve acceptable dosimetric results. However, it overloaded the needles. This resulted in high dose regions located in the normal tissue. The Paddick index for the volume of two times prescribed dose was outstandingly low. Conclusions HIPO can produce clinically acceptable treatment plans with the elimination of high dose regions in normal tissue. Compared to IPSA, it is an inverse optimization method which takes into account current clinical experience gained from manual treatment planning. PMID:27853479

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, E; Yuan, F; Templeton, A

Purpose: The ultimate goal of radiotherapy treatment planning is to find a treatment that will yield a high tumor-control-probability(TCP) with an acceptable normal-tissue-complication probability(NTCP). Yet most treatment planning today is not based upon optimization of TCPs and NTCPs, but rather upon meeting physical dose and volume constraints defined by the planner. We design treatment plans that optimize TCP directly and contrast them with the clinical dose-based plans. PET image is incorporated to evaluate gain in TCP for dose escalation. Methods: We build a nonlinear mixed integer programming optimization model that maximizes TCP directly while satisfying the dose requirements on themore » targeted organ and healthy tissues. The solution strategy first fits the TCP function with a piecewise-linear approximation, then solves the problem that maximizes the piecewise linear approximation of TCP, and finally performs a local neighborhood search to improve the TCP value. To gauge the feasibility, characteristics, and potential benefit of PET-image guided dose escalation, initial validation consists of fifteen cervical cancer HDR patient cases. These patients have all received prior 45Gy of external radiation dose. For both escalated strategies, we consider 35Gy PTV-dose, and two variations (37Gy-boost to BTV vs 40Gy-boost) to PET-image-pockets. Results: TCP for standard clinical plans range from 59.4% - 63.6%. TCP for dose-based PET-guided escalated-dose-plan ranges from 63.8%–98.6% for all patients; whereas TCP-optimized plans achieves over 91% for all patients. There is marginal difference in TCP among those with 37Gy-boosted vs 40Gy-boosted. There is no increase in rectum and bladder dose among all plans. Conclusion: Optimizing TCP directly results in highly conformed treatment plans. The TCP-optimized plan is individualized based on the biological PET-image of the patients. The TCP-optimization framework is generalizable and has been applied successfully to other external-beam delivery modalities. A clinical trial is on-going to gauge the clinical significance. Partially supported by the National Science Foundation.« less

SU-F-T-199: A New Strategy for Integrating Photon with Proton and Carbon Ion in the Treatment Planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Z; Wang, J; Hu, W

2016-06-15

Purpose: The aim of this study was to develop a viable strategy to integrate photon plan and proton/carbon ion plan based on deformable registration. Methods: Two prostate cancer patients were enrolled in this study. Each patient has 2 CTs, which were input in the Raystation radiotherapy treatment planning system (TPS). CT1 was deformed to the second CT2 using the Hybrid deformation method. The dice similarity coefficient (DSC) parameter was used to evaluate the difference between the actual structures (bladder, rectum and CTV) and the corresponding deformed structures on CT2. The prescription dose was 63.02GyE to CTV, which included 49.32GyE formore » CTV1 with carbon and boost 13.7Gy for CTV2 with photon. The carbon plan was made first in Syngo TPS (Syngo PT Planning system, version VB10. Siemens, Germany) on CT1 and transferred to Raystation TPS. Selected Isodoses (23.5Gy, 36.8Gy, 39.1Gy, 47.0Gy and 49.3Gy) of carbon plan were converted to contours and then deformed to CT2, which was used as normal tissues for photon plan optimization on CT2. The final plan was the combination of photon plan and the carbon deformation plan on the CT2. The plan from this strategy was compared with direct optimization of the photon plan on CT2 added some clinical endpoints from carbon plan on CT1. Results: The new strategy with deformable registration is tested and combined plans were successfully obtained for the 2 patients. This strategy obtained both integrated DVH and dose distribution information. For patient 1, the rectum V30, V60 and bladder V63 were 45.8, 10.3 and 9.7 for the combined plan with deformation and 48.1, 11.0 and 12.0 for the direct photon plan. Conclusion: The new strategy for combining photon and carbon/proton is feasible. However, the clinical accuracy is still need more evaluation.« less

Optimal helicopter trajectory planning for terrain following flight

NASA Technical Reports Server (NTRS)

Menon, P. K. A.

1990-01-01

Helicopters operating in high threat areas have to fly close to the earth surface to minimize the risk of being detected by the adversaries. Techniques are presented for low altitude helicopter trajectory planning. These methods are based on optimal control theory and appear to be implementable onboard in realtime. Second order necessary conditions are obtained to provide a criterion for finding the optimal trajectory when more than one extremal passes through a given point. A second trajectory planning method incorporating a quadratic performance index is also discussed. Trajectory planning problem is formulated as a differential game. The objective is to synthesize optimal trajectories in the presence of an actively maneuvering adversary. Numerical methods for obtaining solutions to these problems are outlined. As an alternative to numerical method, feedback linearizing transformations are combined with the linear quadratic game results to synthesize explicit nonlinear feedback strategies for helicopter pursuit-evasion. Some of the trajectories generated from this research are evaluated on a six-degree-of-freedom helicopter simulation incorporating an advanced autopilot. The optimal trajectory planning methods presented are also useful for autonomous land vehicle guidance.

Poster — Thur Eve — 69: Computational Study of DVH-guided Cancer Treatment Planning Optimization Methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ghomi, Pooyan Shirvani; Zinchenko, Yuriy

2014-08-15

Purpose: To compare methods to incorporate the Dose Volume Histogram (DVH) curves into the treatment planning optimization. Method: The performance of three methods, namely, the conventional Mixed Integer Programming (MIP) model, a convex moment-based constrained optimization approach, and an unconstrained convex moment-based penalty approach, is compared using anonymized data of a prostate cancer patient. Three plans we generated using the corresponding optimization models. Four Organs at Risk (OARs) and one Tumor were involved in the treatment planning. The OARs and Tumor were discretized into total of 50,221 voxels. The number of beamlets was 943. We used commercially available optimization softwaremore » Gurobi and Matlab to solve the models. Plan comparison was done by recording the model runtime followed by visual inspection of the resulting dose volume histograms. Conclusion: We demonstrate the effectiveness of the moment-based approaches to replicate the set of prescribed DVH curves. The unconstrained convex moment-based penalty approach is concluded to have the greatest potential to reduce the computational effort and holds a promise of substantial computational speed up.« less

Development of the trickle roof cooling and heating system: Experimental plan

NASA Astrophysics Data System (ADS)

Haves, P.; Jankovic, T.; Doderer, E.

1982-07-01

A passive system applicable both to retrofit and new construction was developed. This system (the trickle roof system) dissipates heat from a thin film of water flowing over the roof. A small scale trickle roof system dissipator was tested at Trinity University under a range of ambient conditions and operating configurations. The results suggest that trickle roof systems should have comparable performance to roof pond systems. Provided is a review of the trickle roof system concept, several possible configurations, and the benefits the systems can provide. Test module experiments And results are presented in detail. The requirements for full scale testing are discussed and a plan is outlined using the two identical residential scale passive test facility buildings at Trinity University, San Antonio, Texas. Full scale experimental results would be used to validate computer algorithms, provide system optimization, and produce a nationwide performance assessment and design guidelines. This would provide industry with the information necessary to determine the commerical potential of the trickle roof system.

TU-AB-BRB-00: New Methods to Ensure Target Coverage

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

2015-06-15

The accepted clinical method to accommodate targeting uncertainties inherent in fractionated external beam radiation therapy is to utilize GTV-to-CTV and CTV-to-PTV margins during the planning process to design a PTV-conformal static dose distribution on the planning image set. Ideally, margins are selected to ensure a high (e.g. >95%) target coverage probability (CP) in spite of inherent inter- and intra-fractional positional variations, tissue motions, and initial contouring uncertainties. Robust optimization techniques, also known as probabilistic treatment planning techniques, explicitly incorporate the dosimetric consequences of targeting uncertainties by including CP evaluation into the planning optimization process along with coverage-based planning objectives. Themore » treatment planner no longer needs to use PTV and/or PRV margins; instead robust optimization utilizes probability distributions of the underlying uncertainties in conjunction with CP-evaluation for the underlying CTVs and OARs to design an optimal treated volume. This symposium will describe CP-evaluation methods as well as various robust planning techniques including use of probability-weighted dose distributions, probability-weighted objective functions, and coverage optimized planning. Methods to compute and display the effect of uncertainties on dose distributions will be presented. The use of robust planning to accommodate inter-fractional setup uncertainties, organ deformation, and contouring uncertainties will be examined as will its use to accommodate intra-fractional organ motion. Clinical examples will be used to inter-compare robust and margin-based planning, highlighting advantages of robust-plans in terms of target and normal tissue coverage. Robust-planning limitations as uncertainties approach zero and as the number of treatment fractions becomes small will be presented, as well as the factors limiting clinical implementation of robust planning. Learning Objectives: To understand robust-planning as a clinical alternative to using margin-based planning. To understand conceptual differences between uncertainty and predictable motion. To understand fundamental limitations of the PTV concept that probabilistic planning can overcome. To understand the major contributing factors to target and normal tissue coverage probability. To understand the similarities and differences of various robust planning techniques To understand the benefits and limitations of robust planning techniques.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Guida, K; Qamar, K; Thompson, M

Purpose: The RTOG 1005 trial offered a hypofractionated arm in delivering WBRT+SIB. Traditionally, treatments were planned at our institution using field-in-field (FiF) tangents with a concurrent 3D conformal boost. With the availability of VMAT, it is possible that a hybrid VMAT-3D planning technique could provide another avenue in treating WBRT+SIB. Methods: A retrospective study of nine patients previously treated using RTOG 1005 guidelines was performed to compare FiF+3D plans with the hybrid technique. A combination of static tangents and partial VMAT arcs were used in base-dose optimization. The hybrid plans were optimized to deliver 4005cGy to the breast PTVeval andmore » 4800cGy to the lumpectomy PTVeval over 15 fractions. Plans were optimized to meet the planning goals dictated by RTOG 1005. Results: Hybrid plans yielded similar coverage of breast and lumpectomy PTVs (average D95 of 4013cGy compared to 3990cGy for conventional), while reducing the volume of high dose within the breast; the average D30 and D50 for the hybrid technique were 4517cGy and 4288cGy, compared to 4704cGy and 4377cGy for conventional planning. Hybrid plans increased conformity as well, yielding CI95% values of 1.22 and 1.54 for breast and lumpectomy PTVeval volumes; in contrast, conventional plans averaged 1.49 and 2.27, respectively. The nearby organs at risk (OARs) received more low dose with the hybrid plans due to low dose spray from the partial arcs, but all hybrid plans did meet the acceptable constraints, at a minimum, from the protocol. Treatment planning time was also reduced, as plans were inversely optimized (VMAT) rather than forward optimized. Conclusion: Hybrid-VMAT could be a solution in delivering WB+SIB, as plans yield very conformal treatment plans and maintain clinical standards in OAR sparing. For treating breast cancer patients with a simultaneously-integrated boost, Hybrid-VMAT offers superiority in dosimetric conformity and planning time as compared to FIF techniques.« less

Improving IMRT delivery efficiency using intensity limits during inverse planning.

PubMed

Coselmon, Martha M; Moran, Jean M; Radawski, Jeffrey D; Fraass, Benedick A

2005-05-01

Inverse planned intensity modulated radiotherapy (IMRT) fields can be highly modulated due to the large number of degrees of freedom involved in the inverse planning process. Additional modulation typically results in a more optimal plan, although the clinical rewards may be small or offset by additional delivery complexity and/or increased dose from transmission and leakage. Increasing modulation decreases delivery efficiency, and may lead to plans that are more sensitive to geometrical uncertainties. The purpose of this work is to assess the use of maximum intensity limits in inverse IMRT planning as a simple way to increase delivery efficiency without significantly affecting plan quality. Nine clinical cases (three each for brain, prostate, and head/neck) were used to evaluate advantages and disadvantages of limiting maximum intensity to increase delivery efficiency. IMRT plans were generated using in-house protocol-based constraints and objectives for the brain and head/neck, and RTOG 9406 dose volume objectives in the prostate. Each case was optimized at a series of maximum intensity ratios (the product of the maximum intensity and the number of beams divided by the prescribed dose to the target volume), and evaluated in terms of clinical metrics, dose-volume histograms, monitor units (MU) required per fraction (SMLC and DMLC delivery), and intensity map variation (a measure of the beam modulation). In each site tested, it was possible to reduce total monitor units by constraining the maximum allowed intensity without compromising the clinical acceptability of the plan. Monitor unit reductions up to 38% were observed for SMLC delivery, while reductions up to 29% were achieved for DMLC delivery. In general, complicated geometries saw a smaller reduction in monitor units for both delivery types, although DMLC delivery required significantly more monitor units in all cases. Constraining the maximum intensity in an inverse IMRT plan is a simple way to improve delivery efficiency without compromising plan objectives.

A modular approach to intensity-modulated arc therapy optimization with noncoplanar trajectories

NASA Astrophysics Data System (ADS)

Papp, Dávid; Bortfeld, Thomas; Unkelbach, Jan

2015-07-01

Utilizing noncoplanar beam angles in volumetric modulated arc therapy (VMAT) has the potential to combine the benefits of arc therapy, such as short treatment times, with the benefits of noncoplanar intensity modulated radiotherapy (IMRT) plans, such as improved organ sparing. Recently, vendors introduced treatment machines that allow for simultaneous couch and gantry motion during beam delivery to make noncoplanar VMAT treatments possible. Our aim is to provide a reliable optimization method for noncoplanar isocentric arc therapy plan optimization. The proposed solution is modular in the sense that it can incorporate different existing beam angle selection and coplanar arc therapy optimization methods. Treatment planning is performed in three steps. First, a number of promising noncoplanar beam directions are selected using an iterative beam selection heuristic; these beams serve as anchor points of the arc therapy trajectory. In the second step, continuous gantry/couch angle trajectories are optimized using a simple combinatorial optimization model to define a beam trajectory that efficiently visits each of the anchor points. Treatment time is controlled by limiting the time the beam needs to trace the prescribed trajectory. In the third and final step, an optimal arc therapy plan is found along the prescribed beam trajectory. In principle any existing arc therapy optimization method could be incorporated into this step; for this work we use a sliding window VMAT algorithm. The approach is demonstrated using two particularly challenging cases. The first one is a lung SBRT patient whose planning goals could not be satisfied with fewer than nine noncoplanar IMRT fields when the patient was treated in the clinic. The second one is a brain tumor patient, where the target volume overlaps with the optic nerves and the chiasm and it is directly adjacent to the brainstem. Both cases illustrate that the large number of angles utilized by isocentric noncoplanar VMAT plans can help improve dose conformity, homogeneity, and organ sparing simultaneously using the same beam trajectory length and delivery time as a coplanar VMAT plan.

TH-AB-202-09: Direct-Aperture Optimization for Combined MV+kV Dose Planning in Fluoroscopic Real-Time Tumor-Tracking Radiation Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, X; Belcher, AH; Grelewicz, Z

Purpose: Real-time kV fluoroscopic tumor tracking has the benefit of direct tumor position monitoring. However, there is clinical concern over the excess kV imaging dose cost to the patient when imaging in continuous fluoroscopic mode. This work addresses this specific issue by proposing a combined MV+kV direct-aperture optimization (DAO) approach to integrate the kV imaging beam into a treatment planning such that the kV radiation is considered as a contributor to the overall dose delivery. Methods: The combined MV+kV DAO approach includes three algorithms. First, a projected Quasi-Newton algorithm (L-BFGS) is used to find optimized fluence with MV+kV dose formore » the best possible dose distribution. Then, Engel’s algorithm is applied to optimize the total number of monitor units and heuristically optimize the number of apertures. Finally, an aperture shape optimization (ASO) algorithm is applied to locally optimize the leaf positions of MLC. Results: Compared to conventional DAO MV plans with continuous kV fluoroscopic tracking, combined MV+kV DAO plan leads to a reduction in the total number of MV monitor units due to inclusion of kV dose as part of the PTV, and was also found to reduce the mean and maximum doses on the organs at risk (OAR). Compared to conventional DAO MV plan without kV tracking, the OAR dose in the combined MV+kV DAO plan was only slightly higher. DVH curves show that combined MV+kV DAO plan provided about the same PTV coverage as that in the conventional DAO plans without kV imaging. Conclusion: We report a combined MV+kV DAO approach that allows real time kV imager tumor tracking with only a trivial increasing on the OAR doses while providing the same coverage to PTV. The approach is suitable for clinic implementation.« less

Application of particle swarm optimization in path planning of mobile robot

NASA Astrophysics Data System (ADS)

Wang, Yong; Cai, Feng; Wang, Ying

2017-08-01

In order to realize the optimal path planning of mobile robot in unknown environment, a particle swarm optimization algorithm based on path length as fitness function is proposed. The location of the global optimal particle is determined by the minimum fitness value, and the robot moves along the points of the optimal particles to the target position. The process of moving to the target point is done with MATLAB R2014a. Compared with the standard particle swarm optimization algorithm, the simulation results show that this method can effectively avoid all obstacles and get the optimal path.

An online replanning method using warm start optimization and aperture morphing for flattening-filter-free beams

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ahunbay, Ergun E., E-mail: eahunbay@mcw.edu; Ates,

Purpose: In a situation where a couch shift for patient positioning is not preferred or prohibited (e.g., MR-linac), segment aperture morphing (SAM) can address target dislocation and deformation. For IMRT/VMAT with flattening-filter-free (FFF) beams, however, SAM method would lead to an adverse translational dose effect due to the beam unflattening. Here the authors propose a new two-step process to address both the translational effect of FFF beams and the target deformation. Methods: The replanning method consists of an offline and an online step. The offline step is to create a series of preshifted-plans (PSPs) obtained by a so-called “warm start”more » optimization (starting optimization from the original plan, rather than from scratch) at a series of isocenter shifts. The PSPs all have the same number of segments with very similar shapes, since the warm start optimization only adjusts the MLC positions instead of regenerating them. In the online step, a new plan is obtained by picking the closest PSP or linearly interpolating the MLC positions and the monitor units of the closest PSPs for the shift determined from the image of the day. This two-step process is completely automated and almost instantaneous (no optimization or dose calculation needed). The previously developed SAM algorithm is then applied for daily deformation. The authors tested the method on sample prostate and pancreas cases. Results: The two-step interpolation method can account for the adverse dose effects from FFF beams, while SAM corrects for the target deformation. Plan interpolation method is effective in diminishing the unflat beam effect and may allow reducing the required number of PSPs. The whole process takes the same time as the previously reported SAM process (5–10 min). Conclusions: The new two-step method plus SAM can address both the translation effects of FFF beams and target deformation, and can be executed in full automation except the delineation of target contour required by the SAM process.« less

SU-E-T-250: New IMRT Sequencing Strategy: Towards Intra-Fraction Plan Adaptation for the MR-Linac

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kontaxis, C; Bol, G; Lagendijk, J

2014-06-01

Purpose: To develop a new sequencer for IMRT planning that during treatment makes the inclusion of external factors possible and by doing so accounts for intra-fraction anatomy changes. Given a real-time imaging modality that will provide the updated patient anatomy during delivery, this sequencer is able to take these changes into account during the calculation of subsequent segments. Methods: Pencil beams are generated for each beam angle of the treatment and a fluence optimization is performed. The pencil beams, together with the patient anatomy and the above optimal fluence form the input of our algorithm. During each iteration the followingmore » steps are performed: A fluence optimization is done and each beam's fluence is then split to discrete intensity levels. Deliverable segments are calculated for each one of these. Each segment's area multiplied by its intensity describes its efficiency. The most efficient segment among all beams is then chosen to deliver a part of the calculated fluence and the dose that will be delivered by this segment is calculated. This delivered dose is then subtracted from the remaining dose. This loop is repeated until 90% of the dose has been delivered and a final segment weight optimization is performed to reach full convergence. Results: This algorithm was tested in several prostate cases yielding results that meet all clinical constraints. Quality assurance was performed on Delta4 and film phantoms for one of these prostate cases and received clinical acceptance after passing both gamma analyses with the 3%/3mm criteria. Conclusion: A new sequencing algorithm was developed to facilitate the needs of intensity modulated treatment. The first results on static anatomy confirm that it can calculate clinical plans equivalent to those of the commercially available planning systems. We are now working towards 100% dose convergence which will allow us to handle anatomy deformations. This work is financially supported by Elekta AB, Stockholm, Sweden.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Swanson, K; Corwin, D; Rockne, R

Purpose: To demonstrate a method of generating patient-specific, biologically-guided radiation therapy (RT) plans and to quantify and predict response to RT in glioblastoma. We investigate the biological correlates and imaging physics driving T2-MRI based response to radiation therapy using an MRI simulator. Methods: We have integrated a patient-specific biomathematical model of glioblastoma proliferation, invasion and radiotherapy with a multiobjective evolutionary algorithm for intensity-modulated RT optimization to construct individualized, biologically-guided plans. Patient-individualized simulations of the standard-of-care and optimized plans are compared in terms of several biological metrics quantified on MRI. An extension of the PI model is used to investigate themore » role of angiogenesis and its correlates in glioma response to therapy with the Proliferation-Invasion-Hypoxia- Necrosis-Angiogenesis model (PIHNA). The PIHNA model is used with a brain tissue phantom to predict tumor-induced vasogenic edema, tumor and tissue density that is used in a multi-compartmental MRI signal equation for generation of simulated T2- weighted MRIs. Results: Applying a novel metric of treatment response (Days Gained) to the patient-individualized simulation results predicted that the optimized RT plans would have a significant impact on delaying tumor progression, with Days Gained increases from 21% to 105%. For the T2- MRI simulations, initial validation tests compared average simulated T2 values for white matter, tumor, and peripheral edema to values cited in the literature. Simulated results closely match the characteristic T2 value for each tissue. Conclusion: Patient-individualized simulations using the combination of a biomathematical model with an optimization algorithm for RT generated biologically-guided doses that decreased normal tissue dose and increased therapeutic ratio with the potential to improve survival outcomes for treatment of glioblastoma. Simulated T2-MRI is shown to be consistent with known physics of MRI and can be used to further investigate biological drivers of imaging-based response to RT.« less

Flight Planning

NASA Technical Reports Server (NTRS)

1991-01-01

Seagull Technology, Inc., Sunnyvale, CA, produced a computer program under a Langley Research Center Small Business Innovation Research (SBIR) grant called STAFPLAN (Seagull Technology Advanced Flight Plan) that plans optimal trajectory routes for small to medium sized airlines to minimize direct operating costs while complying with various airline operating constraints. STAFPLAN incorporates four input databases, weather, route data, aircraft performance, and flight-specific information (times, payload, crew, fuel cost) to provide the correct amount of fuel optimal cruise altitude, climb and descent points, optimal cruise speed, and flight path.

Universal field matching in craniospinal irradiation by a background-dose gradient-optimized method.

PubMed

Traneus, Erik; Bizzocchi, Nicola; Fellin, Francesco; Rombi, Barbara; Farace, Paolo

2018-01-01

The gradient-optimized methods are overcoming the traditional feathering methods to plan field junctions in craniospinal irradiation. In this note, a new gradient-optimized technique, based on the use of a background dose, is described. Treatment planning was performed by RayStation (RaySearch Laboratories, Stockholm, Sweden) on the CT scans of a pediatric patient. Both proton (by pencil beam scanning) and photon (by volumetric modulated arc therapy) treatments were planned with three isocenters. An 'in silico' ideal background dose was created first to cover the upper-spinal target and to produce a perfect dose gradient along the upper and lower junction regions. Using it as background, the cranial and the lower-spinal beams were planned by inverse optimization to obtain dose coverage of their relevant targets and of the junction volumes. Finally, the upper-spinal beam was inversely planned after removal of the background dose and with the previously optimized beams switched on. In both proton and photon plans, the optimized cranial and the lower-spinal beams produced a perfect linear gradient in the junction regions, complementary to that produced by the optimized upper-spinal beam. The final dose distributions showed a homogeneous coverage of the targets. Our simple technique allowed to obtain high-quality gradients in the junction region. Such technique universally works for photons as well as protons and could be applicable to the TPSs that allow to manage a background dose. © 2017 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

“A System for Automatically Maintaining Pressure in a Commercial Truck Tire”

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maloney, John

2017-07-07

Under-inflated tires significantly reduce a vehicle’s fuel efficiency by increasing rolling resistance (drag force). The Air Maintenance Technology (“AMT”) system developed through this project replenishes lost air and maintains optimal tire cavity pressure whenever the tire is rolling in service, thus improving overall fuel economy by reducing the tire’s rolling resistance. The system consists of an inlet air filter, an air pump driven by tire deformation during rotation, and a pressure regulating device. Pressurized air in the tire cavity naturally escapes by diffusion through the tire and wheel, leaks in tire seating, and through the filler valve and its seating.more » As a result, tires require constant maintenance to replenish lost air. Since manual tire inflation maintenance is both labor intensive and time consuming, it is frequently overlooked or ignored. By automating the maintenance of optimal tire pressure, the tire’s contribution to the vehicle’s overall fuel economy can be maximized. The work was divided into three phases. The objectives of Phase 1, Planning and Initial Design, resulted in an effective project plan and to create a baseline design. The objectives for Phase 2, Design and Process Optimization, were: to identify finalized design for the pump, regulator and filter components; identify a process to build prototype tires; assemble prototype tires; test prototype tires and document results. The objectives of Phase 3, Design Release and Industrialization, were to finalize system tire assembly, perform release testing and industrialize the assembly process.« less

Contingency Contractor Optimization Phase 3 Sustainment Software Design Document - Contingency Contractor Optimization Tool - Prototype

DOE Office of Scientific and Technical Information (OSTI.GOV)

Durfee, Justin David; Frazier, Christopher Rawls; Bandlow, Alisa

This document describes the final software design of the Contingency Contractor Optimization Tool - Prototype. Its purpose is to provide the overall architecture of the software and the logic behind this architecture. Documentation for the individual classes is provided in the application Javadoc. The Contingency Contractor Optimization project is intended to address Department of Defense mandates by delivering a centralized strategic planning tool that allows senior decision makers to quickly and accurately assess the impacts, risks, and mitigation strategies associated with utilizing contract support. The Contingency Contractor Optimization Tool - Prototype was developed in Phase 3 of the OSD ATLmore » Contingency Contractor Optimization project to support strategic planning for contingency contractors. The planning tool uses a model to optimize the Total Force mix by minimizing the combined total costs for selected mission scenarios. The model optimizes the match of personnel types (military, DoD civilian, and contractors) and capabilities to meet mission requirements as effectively as possible, based on risk, cost, and other requirements.« less

Trajectory planning of mobile robots using indirect solution of optimal control method in generalized point-to-point task

NASA Astrophysics Data System (ADS)

Nazemizadeh, M.; Rahimi, H. N.; Amini Khoiy, K.

2012-03-01

This paper presents an optimal control strategy for optimal trajectory planning of mobile robots by considering nonlinear dynamic model and nonholonomic constraints of the system. The nonholonomic constraints of the system are introduced by a nonintegrable set of differential equations which represent kinematic restriction on the motion. The Lagrange's principle is employed to derive the nonlinear equations of the system. Then, the optimal path planning of the mobile robot is formulated as an optimal control problem. To set up the problem, the nonlinear equations of the system are assumed as constraints, and a minimum energy objective function is defined. To solve the problem, an indirect solution of the optimal control method is employed, and conditions of the optimality derived as a set of coupled nonlinear differential equations. The optimality equations are solved numerically, and various simulations are performed for a nonholonomic mobile robot to illustrate effectiveness of the proposed method.

Robustness of IPSA optimized high-dose-rate prostate brachytherapy treatment plans to catheter displacements

PubMed Central

Whitaker, May

2016-01-01

Purpose Inverse planning simulated annealing (IPSA) optimized brachytherapy treatment plans are characterized with large isolated dwell times at the first or last dwell position of each catheter. The potential of catheter shifts relative to the target and organs at risk in these plans may lead to a more significant change in delivered dose to the volumes of interest relative to plans with more uniform dwell times. Material and methods This study aims to determine if the Nucletron Oncentra dwell time deviation constraint (DTDC) parameter can be optimized to improve the robustness of high-dose-rate (HDR) prostate brachytherapy plans to catheter displacements. A set of 10 clinically acceptable prostate plans were re-optimized with a DTDC parameter of 0 and 0.4. For each plan, catheter displacements of 3, 7, and 14 mm were retrospectively applied and the change in dose volume histogram (DVH) indices and conformity indices analyzed. Results The robustness of clinically acceptable prostate plans to catheter displacements in the caudal direction was found to be dependent on the DTDC parameter. A DTDC value of 0 improves the robustness of planning target volume (PTV) coverage to catheter displacements, whereas a DTDC value of 0.4 improves the robustness of the plans to changes in hotspots. Conclusions The results indicate that if used in conjunction with a pre-treatment catheter displacement correction protocol and a tolerance of 3 mm, a DTDC value of 0.4 may produce clinically superior plans. However, the effect of the DTDC parameter in plan robustness was not observed to be as strong as initially suspected. PMID:27504129

Robustness of IPSA optimized high-dose-rate prostate brachytherapy treatment plans to catheter displacements.

PubMed

Poder, Joel; Whitaker, May

2016-06-01

Inverse planning simulated annealing (IPSA) optimized brachytherapy treatment plans are characterized with large isolated dwell times at the first or last dwell position of each catheter. The potential of catheter shifts relative to the target and organs at risk in these plans may lead to a more significant change in delivered dose to the volumes of interest relative to plans with more uniform dwell times. This study aims to determine if the Nucletron Oncentra dwell time deviation constraint (DTDC) parameter can be optimized to improve the robustness of high-dose-rate (HDR) prostate brachytherapy plans to catheter displacements. A set of 10 clinically acceptable prostate plans were re-optimized with a DTDC parameter of 0 and 0.4. For each plan, catheter displacements of 3, 7, and 14 mm were retrospectively applied and the change in dose volume histogram (DVH) indices and conformity indices analyzed. The robustness of clinically acceptable prostate plans to catheter displacements in the caudal direction was found to be dependent on the DTDC parameter. A DTDC value of 0 improves the robustness of planning target volume (PTV) coverage to catheter displacements, whereas a DTDC value of 0.4 improves the robustness of the plans to changes in hotspots. The results indicate that if used in conjunction with a pre-treatment catheter displacement correction protocol and a tolerance of 3 mm, a DTDC value of 0.4 may produce clinically superior plans. However, the effect of the DTDC parameter in plan robustness was not observed to be as strong as initially suspected.

Designing a multiple dependent state sampling plan based on the coefficient of variation.

PubMed

Yan, Aijun; Liu, Sanyang; Dong, Xiaojuan

2016-01-01

A multiple dependent state (MDS) sampling plan is developed based on the coefficient of variation of the quality characteristic which follows a normal distribution with unknown mean and variance. The optimal plan parameters of the proposed plan are solved by a nonlinear optimization model, which satisfies the given producer's risk and consumer's risk at the same time and minimizes the sample size required for inspection. The advantages of the proposed MDS sampling plan over the existing single sampling plan are discussed. Finally an example is given to illustrate the proposed plan.

American BRCA Outcomes and Utilization of Testing (ABOUT) study: a pragmatic research model that incorporates personalized medicine/patient-centered outcomes in a real world setting.

PubMed

Armstrong, Joanne; Toscano, Michele; Kotchko, Nancy; Friedman, Sue; Schwartz, Marc D; Virgo, Katherine S; Lynch, Kristian; Andrews, James E; Aguado Loi, Claudia X; Bauer, Joseph E; Casares, Carolina; Teten, Rachel Threet; Kondoff, Matthew R; Molina, Ashley D; Abdollahian, Mehrnaz; Brand, Lana; Walker, Gregory S; Sutphen, Rebecca

2015-02-01

Research to date regarding identification and management of hereditary breast and ovarian cancer syndrome (HBOC) in the U.S. has been confined primarily to academic center-based studies with limited patient engagement. To begin to understand and address the current gaps and disparities in delivery of services for the appropriate identification and optimal risk management of individuals with HBOC, we designed and have initiated the American BRCA Outcomes and Utilization of Testing (ABOUT) Study. ABOUT relies on a collaborative patient advocacy, academic and industry partnership to recruit and engage U.S. individuals who are at increased risk for HBOC and investigate their experiences, decisions and outcomes. It utilizes an extensive research infrastructure, including an interactive web-based data system and electronic interfaces for secure online participation and automated data exchange. We describe the novel recruitment approach that was designed for collaboration with a national commercial health plan partner to identify all individuals for whom a healthcare provider orders a BRCA test and mail to each individual an invitation to participate and study packet. The study packet contains detailed information about the study, a baseline questionnaire and informed consent for participation in the study, for release of relevant medical and health plan records and for ongoing research engagement. This approach employs patient-reported, laboratory-reported and health plan-reported outcomes and facilitates longitudinal engagement. We believe that the type of innovative methodology and collaborative framework we have developed for ABOUT is an ideal foundation for a patient-powered research network. This approach can make substantial contributions to identifying current and best practices in HBOC, leading to improved strategies for clinical care and optimal health outcomes among individuals with high inherited risk for cancer.

MO-AB-BRA-01: A Global Level Set Based Formulation for Volumetric Modulated Arc Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nguyen, D; Lyu, Q; Ruan, D

2016-06-15

Purpose: The current clinical Volumetric Modulated Arc Therapy (VMAT) optimization is formulated as a non-convex problem and various greedy heuristics have been employed for an empirical solution, jeopardizing plan consistency and quality. We introduce a novel global direct aperture optimization method for VMAT to overcome these limitations. Methods: The global VMAT (gVMAT) planning was formulated as an optimization problem with an L2-norm fidelity term and an anisotropic total variation term. A level set function was used to describe the aperture shapes and adjacent aperture shapes were penalized to control MLC motion range. An alternating optimization strategy was implemented to solvemore » the fluence intensity and aperture shapes simultaneously. Single arc gVMAT plans, utilizing 180 beams with 2° angular resolution, were generated for a glioblastoma multiforme (GBM), lung (LNG), and 2 head and neck cases—one with 3 PTVs (H&N3PTV) and one with 4 PTVs (H&N4PTV). The plans were compared against the clinical VMAT (cVMAT) plans utilizing two overlapping coplanar arcs. Results: The optimization of the gVMAT plans had converged within 600 iterations. gVMAT reduced the average max and mean OAR dose by 6.59% and 7.45% of the prescription dose. Reductions in max dose and mean dose were as high as 14.5 Gy in the LNG case and 15.3 Gy in the H&N3PTV case. PTV coverages (D95, D98, D99) were within 0.25% of the prescription dose. By globally considering all beams, the gVMAT optimizer allowed some beams to deliver higher intensities, yielding a dose distribution that resembles a static beam IMRT plan with beam orientation optimization. Conclusions: The novel VMAT approach allows for the search of an optimal plan in the global solution space and generates deliverable apertures directly. The single arc VMAT approach fully utilizes the digital linacs’ capability in dose rate and gantry rotation speed modulation. Varian Medical Systems, NIH grant R01CA188300, NIH grant R43CA183390.« less

Accounting for range uncertainties in the optimization of intensity modulated proton therapy.

PubMed

Unkelbach, Jan; Chan, Timothy C Y; Bortfeld, Thomas

2007-05-21

Treatment plans optimized for intensity modulated proton therapy (IMPT) may be sensitive to range variations. The dose distribution may deteriorate substantially when the actual range of a pencil beam does not match the assumed range. We present two treatment planning concepts for IMPT which incorporate range uncertainties into the optimization. The first method is a probabilistic approach. The range of a pencil beam is assumed to be a random variable, which makes the delivered dose and the value of the objective function a random variable too. We then propose to optimize the expectation value of the objective function. The second approach is a robust formulation that applies methods developed in the field of robust linear programming. This approach optimizes the worst case dose distribution that may occur, assuming that the ranges of the pencil beams may vary within some interval. Both methods yield treatment plans that are considerably less sensitive to range variations compared to conventional treatment plans optimized without accounting for range uncertainties. In addition, both approaches--although conceptually different--yield very similar results on a qualitative level.

A trajectory planning scheme for spacecraft in the space station environment. M.S. Thesis - University of California

NASA Technical Reports Server (NTRS)

Soller, Jeffrey Alan; Grunwald, Arthur J.; Ellis, Stephen R.

1991-01-01

Simulated annealing is used to solve a minimum fuel trajectory problem in the space station environment. The environment is special because the space station will define a multivehicle environment in space. The optimization surface is a complex nonlinear function of the initial conditions of the chase and target crafts. Small permutations in the input conditions can result in abrupt changes to the optimization surface. Since no prior knowledge about the number or location of local minima on the surface is available, the optimization must be capable of functioning on a multimodal surface. It was reported in the literature that the simulated annealing algorithm is more effective on such surfaces than descent techniques using random starting points. The simulated annealing optimization was found to be capable of identifying a minimum fuel, two-burn trajectory subject to four constraints which are integrated into the optimization using a barrier method. The computations required to solve the optimization are fast enough that missions could be planned on board the space station. Potential applications for on board planning of missions are numerous. Future research topics may include optimal planning of multi-waypoint maneuvers using a knowledge base to guide the optimization, and a study aimed at developing robust annealing schedules for potential on board missions.

Agility and change of direction in soccer: differences according to the player ages.

PubMed

Fiorilli, Giovanni; Mitrotasios, Michalis; Iuliano, Enzo; Pistone, Eugenio M; Aquino, Giovanna; Calcagno, Giuseppe; DI Cagno, Alessandra

2017-12-01

The goal of this study was to compare the changes of direction speed (CODS) and reactive agility (RA) in soccer players of different ages, in order to optimize the best training of these skills. One hundred eighty-seven players, divided into bi-annual age-groups, U12, U14, U16 and U18, performed two tests: Y-Agility Test, carried out in planned and reactive mode (Y-PLAN and Y-REAC) and Illinois for Change of Direction Test (ICODT). Difference between Y-REAC minus Y-PLAN represents the index of reactivity (REAC-INDEX). MANOVA showed significant differences among groups (F3,182=14.591; P<0.01; η2p=0.244). Y-PLAN showed significant differences only between U12 and the other groups (P<0.01). ICODT results were significantly different between the groups U12 and U14 and the other groups (P<0.01). Significant Pearson's correlations between Y-TEST and ICODT, for the three categories of young players (0.398 P<0.05; 0.615 P<0.01; 0.608 P<0.01 respectively), were found, whereas no significant correlation was found in U18 group. The best performance of Y-PLAN and ICODT, through age, depends on physical skill level, whereas the best RA results depend on technique and experience that help the players to use anticipatory skill. The high correlations between CODS and RA performances, differently than adult athletes, suggest that an effective work program for young players may include RA and CODS training at the same time.

Inverse 4D conformal planning for lung SBRT using particle swarm optimization

NASA Astrophysics Data System (ADS)

Modiri, A.; Gu, X.; Hagan, A.; Bland, R.; Iyengar, P.; Timmerman, R.; Sawant, A.

2016-08-01

A critical aspect of highly potent regimens such as lung stereotactic body radiation therapy (SBRT) is to avoid collateral toxicity while achieving planning target volume (PTV) coverage. In this work, we describe four dimensional conformal radiotherapy using a highly parallelizable swarm intelligence-based stochastic optimization technique. Conventional lung CRT-SBRT uses a 4DCT to create an internal target volume and then, using forward-planning, generates a 3D conformal plan. In contrast, we investigate an inverse-planning strategy that uses 4DCT data to create a 4D conformal plan, which is optimized across the three spatial dimensions (3D) as well as time, as represented by the respiratory phase. The key idea is to use respiratory motion as an additional degree of freedom. We iteratively adjust fluence weights for all beam apertures across all respiratory phases considering OAR sparing, PTV coverage and delivery efficiency. To demonstrate proof-of-concept, five non-small-cell lung cancer SBRT patients were retrospectively studied. The 4D optimized plans achieved PTV coverage comparable to the corresponding clinically delivered plans while showing significantly superior OAR sparing ranging from 26% to 83% for D max heart, 10%-41% for D max esophagus, 31%-68% for D max spinal cord and 7%-32% for V 13 lung.

Inverse 4D conformal planning for lung SBRT using particle swarm optimization

PubMed Central

Modiri, A; Gu, X; Hagan, A; Bland, R; Iyengar, P; Timmerman, R; Sawant, A

2016-01-01

A critical aspect of highly potent regimens such as lung stereotactic body radiation therapy (SBRT) is to avoid collateral toxicity while achieving planning target volume (PTV) coverage. In this work, we describe four dimensional conformal radiotherapy (4D CRT) using a highly parallelizable swarm intelligence-based stochastic optimization technique. Conventional lung CRT-SBRT uses a 4DCT to create an internal target volume (ITV) and then, using forward-planning, generates a 3D conformal plan. In contrast, we investigate an inverse-planning strategy that uses 4DCT data to create a 4D conformal plan, which is optimized across the three spatial dimensions (3D) as well as time, as represented by the respiratory phase. The key idea is to use respiratory motion as an additional degree of freedom. We iteratively adjust fluence weights for all beam apertures across all respiratory phases considering OAR sparing, PTV coverage and delivery efficiency. To demonstrate proof-of-concept, five non-small-cell lung cancer SBRT patients were retrospectively studied. The 4D optimized plans achieved PTV coverage comparable to the corresponding clinically delivered plans while showing significantly superior OAR sparing ranging from 26% to 83% for Dmax heart, 10% to 41% for Dmax esophagus, 31% to 68% for Dmax spinal cord and 7% to 32% for V13 lung. PMID:27476472

Dose to mass for evaluation and optimization of lung cancer radiation therapy.

PubMed

Tyler Watkins, William; Moore, Joseph A; Hugo, Geoffrey D; Siebers, Jeffrey V

2017-11-01

To evaluate potential organ at risk dose-sparing by using dose-mass-histogram (DMH) objective functions compared with dose-volume-histogram (DVH) objective functions. Treatment plans were retrospectively optimized for 10 locally advanced non-small cell lung cancer patients based on DVH and DMH objectives. DMH-objectives were the same as DVH objectives, but with mass replacing volume. Plans were normalized to dose to 95% of the PTV volume (PTV-D95v) or mass (PTV-D95m). For a given optimized dose, DVH and DMH were intercompared to ascertain dose-to-volume vs. dose-to-mass differences. Additionally, the optimized doses were intercompared using DVH and DMH metrics to ascertain differences in optimized plans. Mean dose to volume, D v ‾, mean dose to mass, D M ‾, and fluence maps were intercompared. For a given dose distribution, DVH and DMH differ by >5% in heterogeneous structures. In homogeneous structures including heart and spinal cord, DVH and DMH are nearly equivalent. At fixed PTV-D95v, DMH-optimization did not significantly reduce dose to OARs but reduced PTV-D v ‾ by 0.20±0.2Gy (p=0.02) and PTV-D M ‾ by 0.23±0.3Gy (p=0.02). Plans normalized to PTV-D95m also result in minor PTV dose reductions and esophageal dose sparing (D v ‾ reduced 0.45±0.5Gy, p=0.02 and D M ‾ reduced 0.44±0.5Gy, p=0.02) compared to DVH-optimized plans. Optimized fluence map comparisons indicate that DMH optimization reduces dose in the periphery of lung PTVs. DVH- and DMH-dose indices differ by >5% in lung and lung target volumes for fixed dose distributions, but optimizing DMH did not reduce dose to OARs. The primary difference observed in DVH- and DMH-optimized plans were variations in fluence to the periphery of lung target PTVs, where low density lung surrounds tumor. Copyright © 2017 Elsevier B.V. All rights reserved.

Multiple anatomy optimization of accumulated dose

DOE Office of Scientific and Technical Information (OSTI.GOV)

Watkins, W. Tyler, E-mail: watkinswt@virginia.edu; Siebers, Jeffrey V.; Moore, Joseph A.

Purpose: To investigate the potential advantages of multiple anatomy optimization (MAO) for lung cancer radiation therapy compared to the internal target volume (ITV) approach. Methods: MAO aims to optimize a single fluence to be delivered under free-breathing conditions such that the accumulated dose meets the plan objectives, where accumulated dose is defined as the sum of deformably mapped doses computed on each phase of a single four dimensional computed tomography (4DCT) dataset. Phantom and patient simulation studies were carried out to investigate potential advantages of MAO compared to ITV planning. Through simulated delivery of the ITV- and MAO-plans, target dosemore » variations were also investigated. Results: By optimizing the accumulated dose, MAO shows the potential to ensure dose to the moving target meets plan objectives while simultaneously reducing dose to organs at risk (OARs) compared with ITV planning. While consistently superior to the ITV approach, MAO resulted in equivalent OAR dosimetry at planning objective dose levels to within 2% volume in 14/30 plans and to within 3% volume in 19/30 plans for each lung V20, esophagus V25, and heart V30. Despite large variations in per-fraction respiratory phase weights in simulated deliveries at high dose rates (e.g., treating 4/10 phases during single fraction beams) the cumulative clinical target volume (CTV) dose after 30 fractions and per-fraction dose were constant independent of planning technique. In one case considered, however, per-phase CTV dose varied from 74% to 117% of prescription implying the level of ITV-dose heterogeneity may not be appropriate with conventional, free-breathing delivery. Conclusions: MAO incorporates 4DCT information in an optimized dose distribution and can achieve a superior plan in terms of accumulated dose to the moving target and OAR sparing compared to ITV-plans. An appropriate level of dose heterogeneity in MAO plans must be further investigated.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ju, N; Chen, C; Gans, S

Purpose: A fixed-beam room could be underutilized in a multi-room proton center. We investigated the use of proton pencil beam scanning (PBS) on a fixed-beam as an alternative for posterior fossa tumor bed (PF-TB) boost treatments which were usually treating on a gantry with uniform scanning. Methods: Five patients were treated with craniospinal irradiation (CSI, 23.4 or 36.0 Gy(RBE)) followed by a PF-TB boost to 54 Gy(RBE) with proton beams. Three PF-TB boost plans were generated for each patient: (1) a uniform scanning (US) gantry plan with 4–7 posterior fields shaped with apertures and compensators (2) a PBS plan usingmore » bi-lateral and vertex fields with a 3-mm planning organ-at-risk volume (PRV) expansion around the brainstem and (3) PBS fields using same beam arrangement but replacing the PRV with robust optimization considering a 3-mm setup uncertainty. Results: A concave 54-Gy(RBE) isodose line surrounding the brainstem could be achieved using all three techniques. The mean V95% of the PTV was 99.7% (range: 97.6% to 100%) while the V100% of the PTV ranged from 56.3% to 93.1% depending on the involvement of the brainstem with the PTV. The mean doses received by 0.05 cm{sup 3} of the brainstem were effectively identical: 54.0 Gy(RBE), 53.4 Gy(RBE) and 53.3 Gy(RBE) for US, PBS optimized with PRV, and PBS optimized with robustness plans respectively. The cochlea mean dose increased by 23% of the prescribed boost dose in average from the bi-lateral fields used in the PBS plan. Planning time for the PBS plan with PRV was 5–10 times less than the US plan and the robustly optimized PBS plan. Conclusion: We have demonstrated that a fixed-beam with PBS can deliver a dose distribution comparable to a gantry plan using uniform scanning. Planning time can be reduced substantially using a PRV around the brainstem instead of robust optimization.« less

Dosimetric evaluation of total marrow irradiation using 2 different planning systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nalichowski, Adrian, E-mail: nalichoa@karmanos.org; Eagle, Don G.; Burmeister, Jay

This study compared 2 different treatment planning systems (TPSs) for quality and efficiency of total marrow irradiation (TMI) plans. The TPSs used in this study were VOxel-Less Optimization (VoLO) (Accuray Inc, Sunnyvale, CA) using helical dose delivery on a Tomotherapy Hi-Art treatment unit and Eclipse (Varian Medical Systems Inc, Palo Alto, CA) using volumetric modulated arc therapy (VMAT) dose delivery on a Varian iX treatment unit. A total dose of 1200 cGy was prescribed to cover 95% of the planning target volume (PTV). The plans were optimized and calculated based on a single CT data and structure set using themore » Alderson Rando phantom (The Phantom Laboratory, Salem, NY) and physician contoured target and organ at risk (OAR) volumes. The OARs were lungs, heart, liver, kidneys, brain, and small bowel. The plans were evaluated based on plan quality, time to optimize the plan and calculate the dose, and beam on time. The resulting mean and maximum doses to the PTV were 1268 and 1465 cGy for VoLO and 1284 and 1541 cGy for Eclipse, respectively. For 5 of 6 OAR structures the VoLO system achieved lower mean and D10 doses ranging from 22% to 52% and 3% to 44%, respectively. Total computational time including only optimization and dose calculation were 0.9 hours for VoLO and 3.8 hours for Eclipse. These times do not include user-dependent target delineation and field setup. Both planning systems are capable of creating high-quality plans for total marrow irradiation. The VoLO planning system was able to achieve more uniform dose distribution throughout the target volume and steeper dose fall off, resulting in superior OAR sparing. VoLO's graphics processing unit (GPU)–based optimization and dose calculation algorithm also allowed much faster creation of TMI plans.« less

Artificial intelligence for the CTA Observatory scheduler

NASA Astrophysics Data System (ADS)

Colomé, Josep; Colomer, Pau; Campreciós, Jordi; Coiffard, Thierry; de Oña, Emma; Pedaletti, Giovanna; Torres, Diego F.; Garcia-Piquer, Alvaro

2014-08-01

The Cherenkov Telescope Array (CTA) project will be the next generation ground-based very high energy gamma-ray instrument. The success of the precursor projects (i.e., HESS, MAGIC, VERITAS) motivated the construction of this large infrastructure that is included in the roadmap of the ESFRI projects since 2008. CTA is planned to start the construction phase in 2015 and will consist of two arrays of Cherenkov telescopes operated as a proposal-driven open observatory. Two sites are foreseen at the southern and northern hemispheres. The CTA observatory will handle several observation modes and will have to operate tens of telescopes with a highly efficient and reliable control. Thus, the CTA planning tool is a key element in the control layer for the optimization of the observatory time. The main purpose of the scheduler for CTA is the allocation of multiple tasks to one single array or to multiple sub-arrays of telescopes, while maximizing the scientific return of the facility and minimizing the operational costs. The scheduler considers long- and short-term varying conditions to optimize the prioritization of tasks. A short-term scheduler provides the system with the capability to adapt, in almost real-time, the selected task to the varying execution constraints (i.e., Targets of Opportunity, health or status of the system components, environment conditions). The scheduling procedure ensures that long-term planning decisions are correctly transferred to the short-term prioritization process for a suitable selection of the next task to execute on the array. In this contribution we present the constraints to CTA task scheduling that helped classifying it as a Flexible Job-Shop Problem case and finding its optimal solution based on Artificial Intelligence techniques. We describe the scheduler prototype that uses a Guarded Discrete Stochastic Neural Network (GDSN), for an easy representation of the possible long- and short-term planning solutions, and Constraint Propagation techniques. A simulation platform, an analysis tool and different test case scenarios for CTA were developed to test the performance of the scheduler and are also described.

Automatic treatment plan re-optimization for adaptive radiotherapy guided with the initial plan DVHs

NASA Astrophysics Data System (ADS)

Li, Nan; Zarepisheh, Masoud; Uribe-Sanchez, Andres; Moore, Kevin; Tian, Zhen; Zhen, Xin; Jiang Graves, Yan; Gautier, Quentin; Mell, Loren; Zhou, Linghong; Jia, Xun; Jiang, Steve

2013-12-01

Adaptive radiation therapy (ART) can reduce normal tissue toxicity and/or improve tumor control through treatment adaptations based on the current patient anatomy. Developing an efficient and effective re-planning algorithm is an important step toward the clinical realization of ART. For the re-planning process, manual trial-and-error approach to fine-tune planning parameters is time-consuming and is usually considered unpractical, especially for online ART. It is desirable to automate this step to yield a plan of acceptable quality with minimal interventions. In ART, prior information in the original plan is available, such as dose-volume histogram (DVH), which can be employed to facilitate the automatic re-planning process. The goal of this work is to develop an automatic re-planning algorithm to generate a plan with similar, or possibly better, DVH curves compared with the clinically delivered original plan. Specifically, our algorithm iterates the following two loops. An inner loop is the traditional fluence map optimization, in which we optimize a quadratic objective function penalizing the deviation of the dose received by each voxel from its prescribed or threshold dose with a set of fixed voxel weighting factors. In outer loop, the voxel weighting factors in the objective function are adjusted according to the deviation of the current DVH curves from those in the original plan. The process is repeated until the DVH curves are acceptable or maximum iteration step is reached. The whole algorithm is implemented on GPU for high efficiency. The feasibility of our algorithm has been demonstrated with three head-and-neck cancer IMRT cases, each having an initial planning CT scan and another treatment CT scan acquired in the middle of treatment course. Compared with the DVH curves in the original plan, the DVH curves in the resulting plan using our algorithm with 30 iterations are better for almost all structures. The re-optimization process takes about 30 s using our in-house optimization engine. This work was originally presented at the 54th AAPM annual meeting in Charlotte, NC, July 29-August 2, 2012.

Integrated platform for optimized solar PV system design and engineering plan set generation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Adeyemo, Samuel

2015-12-30

The Aurora team has developed software that allows users to quickly generate a three-dimensional model for a building, with a corresponding irradiance map, from any two-dimensional image with associated geo-coordinates. The purpose of this project is to build upon that technology by developing and distributing to solar installers a software platform that automatically retrieves engineering, financial and geographic data for a specific site, and quickly generates an optimal customer proposal and corresponding engineering plans for that site. At the end of the project, Aurora’s optimization platform would have been used to make at least one thousand proposals from at leastmore » ten unique solar installation companies, two of whom would sign economically viable contracts to use the software. Furthermore, Aurora’s algorithms would be tested to show that in at least seventy percent of cases, Aurora automatically generated a design equivalent to or better than what a human could have done manually. A ‘better’ design is one that generates more energy for the same cost, or that generates a higher return on investment, while complying with all site-specific aesthetic, electrical and spatial requirements.« less

Clinical applications of advanced rotational radiation therapy

NASA Astrophysics Data System (ADS)

Nalichowski, Adrian

Purpose: With a fast adoption of emerging technologies, it is critical to fully test and understand its limits and capabilities. In this work we investigate new graphic processing unit (GPU) based treatment planning algorithm and its applications in helical tomotherapy dose delivery. We explore the limits of the system by applying it to challenging clinical cases of total marrow irradiation (TMI) and stereotactic radiosurgery (SRS). We also analyze the feasibility of alternative fractionation schemes for total body irradiation (TBI) and TMI based on reported historical data on lung dose and interstitial pneumonitis (IP) incidence rates. Methods and Materials: An anthropomorphic phantom was used to create TMI plans using the new GPU based treatment planning system and the existing CPU cluster based system. Optimization parameters were selected based on clinically used values for field width, modulation factor and pitch. Treatment plans were also created on Eclipse treatment planning system (Varian Medical Systems Inc, Palo Alto, CA) using volumetric modulated arc therapy (VMAT) for dose delivery on IX treatment unit. A retrospective review was performed of 42 publications that reported IP rates along with lung dose, fractionation regimen, dose rate and chemotherapy. The analysis consisted of nearly thirty two hundred patients and 34 unique radiation regimens. Multivariate logistic regression was performed to determine parameters associated with IP and establish does response function. Results: The results showed very good dosimetric agreement between the GPU and CPU calculated plans. The results from SBRT study show that GPU planning system can maintain 90% target coverage while meeting all the constraints of RTOG 0631 protocol. Beam on time for Tomotherapy and flattening filter free RapidArc was much faster than for Vero or Cyberknife. Retrospective data analysis showed that lung dose and Cyclophosphomide (Cy) are both predictors of IP in TBI/TMI treatments. The dose rate was not found to be an independent risk factor for IP. The model failed to establish accurate dose response function, but the discrete data indicated a radiation dose threshold of 7.6Gy (EQD2_repair) and 120 mg/kg of Cy below which no IP cases were reported. Conclusion: The TomoTherapy GPU based dose engine is capable of calculating TMI treatment plans with plan quality nearly identical to plans calculated using the traditional CPU/cluster based system, while significantly reducing the time required for optimization and dose calculation. The new system was able to achieve more uniform dose distribution throughout the target volume and steeper dose fall off, resulting in superior OAR sparing when compared to Eclipse treatment planning system for VMAT delivery. The machine optimization parameters tested for TMI cases provide a comprehensive overview of the capabilities of the treatment planning station and associated helical delivery system. The new system also proved to be dosimetrically compatible with other leading modalities for treatments of small and complicated target volumes and was even superior when treatment delivery times were compared. These finding demonstrate that the advanced treatment planning and delivery system from TomoTherapy is well suitable for treatments of complicated cases such as TMI and SRS and it's often dosimetrically and/or logistically superior to other modalities. The new planning system can easily meet the constraint of threshold lung dose established in this study. The results presented here on the capabilities of Tomotherapy and on the identified lung dose threshold provide an opportunity to explore alternative fractionation schemes without sacrificing target coverage or lung toxicity. (Abstract shortened by ProQuest.).

The dosimetric impact of inversely optimized arc radiotherapy plan modulation for real-time dynamic MLC tracking delivery.

PubMed

Falk, Marianne; Larsson, Tobias; Keall, Paul; Chul Cho, Byung; Aznar, Marianne; Korreman, Stine; Poulsen, Per; Munck Af Rosenschold, Per

2012-03-01

Real-time dynamic multileaf collimator (MLC) tracking for management of intrafraction tumor motion can be challenging for highly modulated beams, as the leaves need to travel far to adjust for target motion perpendicular to the leaf travel direction. The plan modulation can be reduced by using a leaf position constraint (LPC) that reduces the difference in the position of adjacent MLC leaves in the plan. The purpose of this study was to investigate the impact of the LPC on the quality of inversely optimized arc radiotherapy plans and the effect of the MLC motion pattern on the dosimetric accuracy of MLC tracking delivery. Specifically, the possibility of predicting the accuracy of MLC tracking delivery based on the plan modulation was investigated. Inversely optimized arc radiotherapy plans were created on CT-data of three lung cancer patients. For each case, five plans with a single 358° arc were generated with LPC priorities of 0 (no LPC), 0.25, 0.5, 0.75, and 1 (highest possible LPC), respectively. All the plans had a prescribed dose of 2 Gy × 30, used 6 MV, a maximum dose rate of 600 MU/min and a collimator angle of 45° or 315°. To quantify the plan modulation, an average adjacent leaf distance (ALD) was calculated by averaging the mean adjacent leaf distance for each control point. The linear relationship between the plan quality [i.e., the calculated dose distributions and the number of monitor units (MU)] and the LPC was investigated, and the linear regression coefficient as well as a two tailed confidence level of 95% was used in the evaluation. The effect of the plan modulation on the performance of MLC tracking was tested by delivering the plans to a cylindrical diode array phantom moving with sinusoidal motion in the superior-inferior direction with a peak-to-peak displacement of 2 cm and a cycle time of 6 s. The delivery was adjusted to the target motion using MLC tracking, guided in real-time by an infrared optical system. The dosimetric results were evaluated using gamma index evaluation with static target measurements as reference. The plan quality parameters did not depend significantly on the LPC (p ≥ 0.066), whereas the ALD depended significantly on the LPC (p < 0.001). The gamma index failure rate depended significantly on the ALD, weighted to the percentage of the beam delivered in each control point of the plan (ALD(w)) when MLC tracking was used (p < 0.001), but not for delivery without MLC tracking (p ≥ 0.342). The gamma index failure rate with the criteria of 2% and 2 mm was decreased from > 33.9% without MLC tracking to <31.4% (LPC 0) and <2.2% (LPC 1) with MLC tracking. The results indicate that the dosimetric robustness of MLC tracking delivery of an inversely optimized arc radiotherapy plan can be improved by incorporating leaf position constraints in the objective function without otherwise affecting the plan quality. The dosimetric robustness may be estimated prior to delivery by evaluating the ALD(w) of the plan.

A methodology for optimal MSW management, with an application in the waste transportation of Attica Region, Greece.

PubMed

Economopoulou, M A; Economopoulou, A A; Economopoulos, A P

2013-11-01

The paper describes a software system capable of formulating alternative optimal Municipal Solid Wastes (MSWs) management plans, each of which meets a set of constraints that may reflect selected objections and/or wishes of local communities. The objective function to be minimized in each plan is the sum of the annualized capital investment and annual operating cost of all transportation, treatment and final disposal operations involved, taking into consideration the possible income from the sale of products and any other financial incentives or disincentives that may exist. For each plan formulated, the system generates several reports that define the plan, analyze its cost elements and yield an indicative profile of selected types of installations, as well as data files that facilitate the geographic representation of the optimal solution in maps through the use of GIS. A number of these reports compare the technical and economic data from all scenarios considered at the study area, municipality and installation level constituting in effect sensitivity analysis. The generation of alternative plans offers local authorities the opportunity of choice and the results of the sensitivity analysis allow them to choose wisely and with consensus. The paper presents also an application of this software system in the capital Region of Attica in Greece, for the purpose of developing an optimal waste transportation system in line with its approved waste management plan. The formulated plan was able to: (a) serve 113 Municipalities and Communities that generate nearly 2 milliont/y of comingled MSW with distinctly different waste collection patterns, (b) take into consideration several existing waste transfer stations (WTS) and optimize their use within the overall plan, (c) select the most appropriate sites among the potentially suitable (new and in use) ones, (d) generate the optimal profile of each WTS proposed, and (e) perform sensitivity analysis so as to define the impact of selected sets of constraints (limitations in the availability of sites and in the capacity of their installations) on the design and cost of the ensuing optimal waste transfer system. The results show that optimal planning offers significant economic savings to municipalities, while reducing at the same time the present levels of traffic, fuel consumptions and air emissions in the congested Athens basin. Copyright © 2013 Elsevier Ltd. All rights reserved.

Three dimensional intensity modulated brachytherapy (IMBT): dosimetry algorithm and inverse treatment planning.

PubMed

Shi, Chengyu; Guo, Bingqi; Cheng, Chih-Yao; Esquivel, Carlos; Eng, Tony; Papanikolaou, Niko

2010-07-01

The feasibility of intensity modulated brachytherapy (IMBT) to improve dose conformity for irregularly shaped targets has been previously investigated by researchers by means of using partially shielded sources. However, partial shielding does not fully explore the potential of IMBT. The goal of this study is to introduce the concept of three dimensional (3D) intensity modulated brachytherapy and solve two fundamental issues regarding the application of 3D IMBT treatment planning: The dose calculation algorithm and the inverse treatment planning method. A 3D IMBT treatment planning system prototype was developed using the MATLAB platform. This system consists of three major components: (1) A comprehensive IMBT source calibration method with dosimetric inputs from Monte Carlo (EGSnrc) simulations; (2) a "modified TG-43" (mTG-43) dose calculation formalism for IMBT dosimetry; and (3) a physical constraint based inverse IMBT treatment planning platform utilizing a simulated annealing optimization algorithm. The model S700 Axxent electronic brachytherapy source developed by Xoft, Inc. (Fremont, CA), was simulated in this application. Ten intracavitary accelerated partial breast irradiation (APBI) cases were studied. For each case, an "isotropic plan" with only optimized source dwell time and a fully optimized IMBT plan were generated and compared to the original plan in various dosimetric aspects, such as the plan quality, planning, and delivery time. The issue of the mechanical complexity of the IMBT applicator is not addressed in this study. IMBT approaches showed superior plan quality compared to the original plans and tht isotropic plans to different extents in all studied cases. An extremely difficult case with a small breast and a small distance to the ribs and skin, the IMBT plan minimized the high dose volume V200 by 16.1% and 4.8%, respectively, compared to the original and the isotropic plans. The conformity index for the target was increased by 0.13 and 0.04, respectively. The maximum dose to the skin was reduced by 56 and 28 cGy, respectively, per fraction. Also, the maximum dose to the ribs was reduced by 104 and 96 cGy, respectively, per fraction. The mean dose to the ipsilateral and contralateral breasts and lungs were also slightly reduced by the IMBT plan. The limitations of IMBT are the longer planning and delivery time. The IMBT plan took around 2 h to optimize, while the isotropic plan optimization could reach the global minimum within 5 min. The delivery time for the IMBT plan is typically four to six times longer than the corresponding isotropic plan. In this study, a dosimetry method for IMBT sources was proposed and an inverse treatment planning system prototype for IMBT was developed. The improvement of plan quality by 3D IMBT was demonstrated using ten APBI case studies. Faster computers and higher output of the source can further reduce plan optimization and delivery time, respectively.

A difference-matrix metaheuristic for intensity map segmentation in step-and-shoot IMRT delivery.

PubMed

Gunawardena, Athula D A; D'Souza, Warren D; Goadrich, Laura D; Meyer, Robert R; Sorensen, Kelly J; Naqvi, Shahid A; Shi, Leyuan

2006-05-21

At an intermediate stage of radiation treatment planning for IMRT, most commercial treatment planning systems for IMRT generate intensity maps that describe the grid of beamlet intensities for each beam angle. Intensity map segmentation of the matrix of individual beamlet intensities into a set of MLC apertures and corresponding intensities is then required in order to produce an actual radiation delivery plan for clinical use. Mathematically, this is a very difficult combinatorial optimization problem, especially when mechanical limitations of the MLC lead to many constraints on aperture shape, and setup times for apertures make the number of apertures an important factor in overall treatment time. We have developed, implemented and tested on clinical cases a metaheuristic (that is, a method that provides a framework to guide the repeated application of another heuristic) that efficiently generates very high-quality (low aperture number) segmentations. Our computational results demonstrate that the number of beam apertures and monitor units in the treatment plans resulting from our approach is significantly smaller than the corresponding values for treatment plans generated by the heuristics embedded in a widely use commercial system. We also contrast the excellent results of our fast and robust metaheuristic with results from an 'exact' method, branch-and-cut, which attempts to construct optimal solutions, but, within clinically acceptable time limits, generally fails to produce good solutions, especially for intensity maps with more than five intensity levels. Finally, we show that in no instance is there a clinically significant change of quality associated with our more efficient plans.

Converging on the optimal attainment of requirements

NASA Technical Reports Server (NTRS)

Feather, M. S.; Menzies, T.

2002-01-01

Planning for the optimal attainment of requirements is an important early lifecycle activity. However, such planning is difficult when dealing with competing requirements, limited resources, and the incompleteness of information available at requirements time.

Fast online Monte Carlo-based IMRT planning for the MRI linear accelerator

NASA Astrophysics Data System (ADS)

Bol, G. H.; Hissoiny, S.; Lagendijk, J. J. W.; Raaymakers, B. W.

2012-03-01

The MRI accelerator, a combination of a 6 MV linear accelerator with a 1.5 T MRI, facilitates continuous patient anatomy updates regarding translations, rotations and deformations of targets and organs at risk. Accounting for these demands high speed, online intensity-modulated radiotherapy (IMRT) re-optimization. In this paper, a fast IMRT optimization system is described which combines a GPU-based Monte Carlo dose calculation engine for online beamlet generation and a fast inverse dose optimization algorithm. Tightly conformal IMRT plans are generated for four phantom cases and two clinical cases (cervix and kidney) in the presence of the magnetic fields of 0 and 1.5 T. We show that for the presented cases the beamlet generation and optimization routines are fast enough for online IMRT planning. Furthermore, there is no influence of the magnetic field on plan quality and complexity, and equal optimization constraints at 0 and 1.5 T lead to almost identical dose distributions.

A modeling framework for optimal long-term care insurance purchase decisions in retirement planning.

PubMed

Gupta, Aparna; Li, Lepeng

2004-05-01

The level of need and costs of obtaining long-term care (LTC) during retired life require that planning for it is an integral part of retirement planning. In this paper, we divide retirement planning into two phases, pre-retirement and post-retirement. On the basis of four interrelated models for health evolution, wealth evolution, LTC insurance premium and coverage, and LTC cost structure, a framework for optimal LTC insurance purchase decisions in the pre-retirement phase is developed. Optimal decisions are obtained by developing a trade-off between post-retirement LTC costs and LTC insurance premiums and coverage. Two-way branching models are used to model stochastic health events and asset returns. The resulting optimization problem is formulated as a dynamic programming problem. We compare the optimal decision under two insurance purchase scenarios: one assumes that insurance is purchased for good and other assumes it may be purchased, relinquished and re-purchased. Sensitivity analysis is performed for the retirement age.

A systematic approach to designing statistically powerful heteroscedastic 2 × 2 factorial studies while minimizing financial costs.

PubMed

Jan, Show-Li; Shieh, Gwowen

2016-08-31

The 2 × 2 factorial design is widely used for assessing the existence of interaction and the extent of generalizability of two factors where each factor had only two levels. Accordingly, research problems associated with the main effects and interaction effects can be analyzed with the selected linear contrasts. To correct for the potential heterogeneity of variance structure, the Welch-Satterthwaite test is commonly used as an alternative to the t test for detecting the substantive significance of a linear combination of mean effects. This study concerns the optimal allocation of group sizes for the Welch-Satterthwaite test in order to minimize the total cost while maintaining adequate power. The existing method suggests that the optimal ratio of sample sizes is proportional to the ratio of the population standard deviations divided by the square root of the ratio of the unit sampling costs. Instead, a systematic approach using optimization technique and screening search is presented to find the optimal solution. Numerical assessments revealed that the current allocation scheme generally does not give the optimal solution. Alternatively, the suggested approaches to power and sample size calculations give accurate and superior results under various treatment and cost configurations. The proposed approach improves upon the current method in both its methodological soundness and overall performance. Supplementary algorithms are also developed to aid the usefulness and implementation of the recommended technique in planning 2 × 2 factorial designs.

SU-F-T-194: Analyzing the Effect of Range Shifter Air Gap On TPS Dose Modeling Accuracy in Superficial PBS Proton Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shirey, R; Wu, H

2016-06-15

Purpose: Treatment planning systems (TPS) may not accurately model superficial dose distributions of range shifted proton pencil beam scanning (PBS) treatments. Numerous patient-specific QA tests performed on superficially treated PBS plans have shown a consistent overestimate of dose by the TPS. This study quantifies variations between TPS planned dose and measured dose as a function of range shifter air gap and treatment depths up to 5 cm. Methods: PBS treatment plans were created in the TPS to uniformly irradiate a volume of solid water. One plan was created for each range shifter position analyzed, and all plans utilized identical dosemore » optimization parameters. Each optimized plan was analyzed in the TPS to determine the planned dose at varying depths. A PBS proton therapy system with a 3.5 cm lucite range shifter delivered the treatment plans, and a parallel plate chamber embedded in RW3 solid water measured dose at shallow depths for each air gap. Differences between measured and planned doses were plotted and analyzed. Results: The data show that the TPS more accurately models superficial dose as the air gap between the range shifter and patient surface decreases. Air gaps less than 10 cm have an average dose difference of only 1.6%, whereas air gaps between 10 and 20 cm differ by 3.0% and gaps greater than 20 cm differ by 4.4%. Conclusion: This study has shown that the TPS is unable to accurately model superficial dose with a large range shifter air gap. Dose differences greater than 3% will likely cause QA failure, as many institutions analyze patient QA with a 3%/3mm gamma analysis. For superficial PBS therapy, range shifter positions should be chosen to keep the air gap less then 10 cm when patient setup and gantry geometry allow.« less

Threshold-driven optimization for reference-based auto-planning

NASA Astrophysics Data System (ADS)

Long, Troy; Chen, Mingli; Jiang, Steve; Lu, Weiguo

2018-02-01

We study threshold-driven optimization methodology for automatically generating a treatment plan that is motivated by a reference DVH for IMRT treatment planning. We present a framework for threshold-driven optimization for reference-based auto-planning (TORA). Commonly used voxel-based quadratic penalties have two components for penalizing under- and over-dosing of voxels: a reference dose threshold and associated penalty weight. Conventional manual- and auto-planning using such a function involves iteratively updating the preference weights while keeping the thresholds constant, an unintuitive and often inconsistent method for planning toward some reference DVH. However, driving a dose distribution by threshold values instead of preference weights can achieve similar plans with less computational effort. The proposed methodology spatially assigns reference DVH information to threshold values, and iteratively improves the quality of that assignment. The methodology effectively handles both sub-optimal and infeasible DVHs. TORA was applied to a prostate case and a liver case as a proof-of-concept. Reference DVHs were generated using a conventional voxel-based objective, then altered to be either infeasible or easy-to-achieve. TORA was able to closely recreate reference DVHs in 5-15 iterations of solving a simple convex sub-problem. TORA has the potential to be effective for auto-planning based on reference DVHs. As dose prediction and knowledge-based planning becomes more prevalent in the clinical setting, incorporating such data into the treatment planning model in a clear, efficient way will be crucial for automated planning. A threshold-focused objective tuning should be explored over conventional methods of updating preference weights for DVH-guided treatment planning.

TU-AB-201-02: An Automated Treatment Plan Quality Assurance Program for Tandem and Ovoid High Dose-Rate Brachytherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tan, J; Shi, F; Hrycushko, B

2015-06-15

Purpose: For tandem and ovoid (T&O) HDR brachytherapy in our clinic, it is required that the planning physicist manually capture ∼10 images during planning, perform a secondary dose calculation and generate a report, combine them into a single PDF document, and upload it to a record- and-verify system to prove to an independent plan checker that the case was planned correctly. Not only does this slow down the already time-consuming clinical workflow, the PDF document also limits the number of parameters that can be checked. To solve these problems, we have developed a web-based automatic quality assurance (QA) program. Methods:more » We set up a QA server accessible through a web- interface. A T&O plan and CT images are exported as DICOMRT files and uploaded to the server. The software checks 13 geometric features, e.g. if the dwell positions are reasonable, and 10 dosimetric features, e.g. secondary dose calculations via TG43 formalism and D2cc to critical structures. A PDF report is automatically generated with errors and potential issues highlighted. It also contains images showing important geometric and dosimetric aspects to prove the plan was created following standard guidelines. Results: The program has been clinically implemented in our clinic. In each of the 58 T&O plans we tested, a 14- page QA report was automatically generated. It took ∼45 sec to export the plan and CT images and ∼30 sec to perform the QA tests and generate the report. In contrast, our manual QA document preparation tooks on average ∼7 minutes under optimal conditions and up to 20 minutes when mistakes were made during the document assembly. Conclusion: We have tested the efficiency and effectiveness of an automated process for treatment plan QA of HDR T&O cases. This software was shown to improve the workflow compared to our conventional manual approach.« less

An optimization model for the US Air-Traffic System

NASA Technical Reports Server (NTRS)

Mulvey, J. M.

1986-01-01

A systematic approach for monitoring U.S. air traffic was developed in the context of system-wide planning and control. Towards this end, a network optimization model with nonlinear objectives was chosen as the central element in the planning/control system. The network representation was selected because: (1) it provides a comprehensive structure for depicting essential aspects of the air traffic system, (2) it can be solved efficiently for large scale problems, and (3) the design can be easily communicated to non-technical users through computer graphics. Briefly, the network planning models consider the flow of traffic through a graph as the basic structure. Nodes depict locations and time periods for either individual planes or for aggregated groups of airplanes. Arcs define variables as actual airplanes flying through space or as delays across time periods. As such, a special case of the network can be used to model the so called flow control problem. Due to the large number of interacting variables and the difficulty in subdividing the problem into relatively independent subproblems, an integrated model was designed which will depict the entire high level (above 29000 feet) jet route system for the 48 contiguous states in the U.S. As a first step in demonstrating the concept's feasibility a nonlinear risk/cost model was developed for the Indianapolis Airspace. The nonlinear network program --NLPNETG-- was employed in solving the resulting test cases. This optimization program uses the Truncated-Newton method (quadratic approximation) for determining the search direction at each iteration in the nonlinear algorithm. It was shown that aircraft could be re-routed in an optimal fashion whenever traffic congestion increased beyond an acceptable level, as measured by the nonlinear risk function.

Optimization of the prescription isodose line for Gamma Knife radiosurgery using the shot within shot technique.

PubMed

Johnson, Perry B; Monterroso, Maria I; Yang, Fei; Mellon, Eric

2017-11-25

This work explores how the choice of prescription isodose line (IDL) affects the dose gradient, target coverage, and treatment time for Gamma Knife radiosurgery when a smaller shot is encompassed within a larger shot at the same stereotactic coordinates (shot within shot technique). Beam profiles for the 4, 8, and 16 mm collimator settings were extracted from the treatment planning system and characterized using Gaussian fits. The characterized data were used to create over 10,000 shot within shot configurations by systematically changing collimator weighting and choice of prescription IDL. Each configuration was quantified in terms of the dose gradient, target coverage, and beam-on time. By analyzing these configurations, it was found that there are regions of overlap in target size where a higher prescription IDL provides equivalent dose fall-off to a plan prescribed at the 50% IDL. Furthermore, the data indicate that treatment times within these regions can be reduced by up to 40%. An optimization strategy was devised to realize these gains. The strategy was tested for seven patients treated for 1-4 brain metastases (20 lesions total). For a single collimator setting, the gradient in the axial plane was steepest when prescribed to the 56-63% (4 mm), 62-70% (8 mm), and 77-84% (16 mm) IDL, respectively. Through utilization of the optimization technique, beam-on time was reduced by more than 15% in 16/20 lesions. The volume of normal brain receiving 12 Gy or above also decreased in many cases, and in only one instance increased by more than 0.5 cm 3 . This work demonstrates that IDL optimization using the shot within shot technique can reduce treatment times without degrading treatment plan quality.

Linear energy transfer incorporated intensity modulated proton therapy optimization

NASA Astrophysics Data System (ADS)

Cao, Wenhua; Khabazian, Azin; Yepes, Pablo P.; Lim, Gino; Poenisch, Falk; Grosshans, David R.; Mohan, Radhe

2018-01-01

The purpose of this study was to investigate the feasibility of incorporating linear energy transfer (LET) into the optimization of intensity modulated proton therapy (IMPT) plans. Because increased LET correlates with increased biological effectiveness of protons, high LETs in target volumes and low LETs in critical structures and normal tissues are preferred in an IMPT plan. However, if not explicitly incorporated into the optimization criteria, different IMPT plans may yield similar physical dose distributions but greatly different LET, specifically dose-averaged LET, distributions. Conventionally, the IMPT optimization criteria (or cost function) only includes dose-based objectives in which the relative biological effectiveness (RBE) is assumed to have a constant value of 1.1. In this study, we added LET-based objectives for maximizing LET in target volumes and minimizing LET in critical structures and normal tissues. Due to the fractional programming nature of the resulting model, we used a variable reformulation approach so that the optimization process is computationally equivalent to conventional IMPT optimization. In this study, five brain tumor patients who had been treated with proton therapy at our institution were selected. Two plans were created for each patient based on the proposed LET-incorporated optimization (LETOpt) and the conventional dose-based optimization (DoseOpt). The optimized plans were compared in terms of both dose (assuming a constant RBE of 1.1 as adopted in clinical practice) and LET. Both optimization approaches were able to generate comparable dose distributions. The LET-incorporated optimization achieved not only pronounced reduction of LET values in critical organs, such as brainstem and optic chiasm, but also increased LET in target volumes, compared to the conventional dose-based optimization. However, on occasion, there was a need to tradeoff the acceptability of dose and LET distributions. Our conclusion is that the inclusion of LET-dependent criteria in the IMPT optimization could lead to similar dose distributions as the conventional optimization but superior LET distributions in target volumes and normal tissues. This may have substantial advantages in improving tumor control and reducing normal tissue toxicities.

Falcon: automated optimization method for arbitrary assessment criteria

DOEpatents

Yang, Tser-Yuan; Moses, Edward I.; Hartmann-Siantar, Christine

2001-01-01

FALCON is a method for automatic multivariable optimization for arbitrary assessment criteria that can be applied to numerous fields where outcome simulation is combined with optimization and assessment criteria. A specific implementation of FALCON is for automatic radiation therapy treatment planning. In this application, FALCON implements dose calculations into the planning process and optimizes available beam delivery modifier parameters to determine the treatment plan that best meets clinical decision-making criteria. FALCON is described in the context of the optimization of external-beam radiation therapy and intensity modulated radiation therapy (IMRT), but the concepts could also be applied to internal (brachytherapy) radiotherapy. The radiation beams could consist of photons or any charged or uncharged particles. The concept of optimizing source distributions can be applied to complex radiography (e.g. flash x-ray or proton) to improve the imaging capabilities of facilities proposed for science-based stockpile stewardship.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zaks, D; Fletcher, R; Salamon, S

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, wemore » 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.« less

A new sparse optimization scheme for simultaneous beam angle and fluence map optimization in radiotherapy planning

NASA Astrophysics Data System (ADS)

Liu, Hongcheng; Dong, Peng; Xing, Lei

2017-08-01

{{\\ell }2,1} -minimization-based sparse optimization was employed to solve the beam angle optimization (BAO) in intensity-modulated radiation therapy (IMRT) planning. The technique approximates the exact BAO formulation with efficiently computable convex surrogates, leading to plans that are inferior to those attainable with recently proposed gradient-based greedy schemes. In this paper, we alleviate/reduce the nontrivial inconsistencies between the {{\\ell }2,1} -based formulations and the exact BAO model by proposing a new sparse optimization framework based on the most recent developments in group variable selection. We propose the incorporation of the group-folded concave penalty (gFCP) as a substitution to the {{\\ell }2,1} -minimization framework. The new formulation is then solved by a variation of an existing gradient method. The performance of the proposed scheme is evaluated by both plan quality and the computational efficiency using three IMRT cases: a coplanar prostate case, a coplanar head-and-neck case, and a noncoplanar liver case. Involved in the evaluation are two alternative schemes: the {{\\ell }2,1} -minimization approach and the gradient norm method (GNM). The gFCP-based scheme outperforms both counterpart approaches. In particular, gFCP generates better plans than those obtained using the {{\\ell }2,1} -minimization for all three cases with a comparable computation time. As compared to the GNM, the gFCP improves both the plan quality and computational efficiency. The proposed gFCP-based scheme provides a promising framework for BAO and promises to improve both planning time and plan quality.

A new sparse optimization scheme for simultaneous beam angle and fluence map optimization in radiotherapy planning.

PubMed

Liu, Hongcheng; Dong, Peng; Xing, Lei

2017-07-20

[Formula: see text]-minimization-based sparse optimization was employed to solve the beam angle optimization (BAO) in intensity-modulated radiation therapy (IMRT) planning. The technique approximates the exact BAO formulation with efficiently computable convex surrogates, leading to plans that are inferior to those attainable with recently proposed gradient-based greedy schemes. In this paper, we alleviate/reduce the nontrivial inconsistencies between the [Formula: see text]-based formulations and the exact BAO model by proposing a new sparse optimization framework based on the most recent developments in group variable selection. We propose the incorporation of the group-folded concave penalty (gFCP) as a substitution to the [Formula: see text]-minimization framework. The new formulation is then solved by a variation of an existing gradient method. The performance of the proposed scheme is evaluated by both plan quality and the computational efficiency using three IMRT cases: a coplanar prostate case, a coplanar head-and-neck case, and a noncoplanar liver case. Involved in the evaluation are two alternative schemes: the [Formula: see text]-minimization approach and the gradient norm method (GNM). The gFCP-based scheme outperforms both counterpart approaches. In particular, gFCP generates better plans than those obtained using the [Formula: see text]-minimization for all three cases with a comparable computation time. As compared to the GNM, the gFCP improves both the plan quality and computational efficiency. The proposed gFCP-based scheme provides a promising framework for BAO and promises to improve both planning time and plan quality.

Optimizing the Long-Term Operating Plan of Railway Marshalling Station for Capacity Utilization Analysis

PubMed Central

Zhou, Wenliang; Yang, Xia; Deng, Lianbo

2014-01-01

Not only is the operating plan the basis of organizing marshalling station's operation, but it is also used to analyze in detail the capacity utilization of each facility in marshalling station. In this paper, a long-term operating plan is optimized mainly for capacity utilization analysis. Firstly, a model is developed to minimize railcars' average staying time with the constraints of minimum time intervals, marshalling track capacity, and so forth. Secondly, an algorithm is designed to solve this model based on genetic algorithm (GA) and simulation method. It divides the plan of whole planning horizon into many subplans, and optimizes them with GA one by one in order to obtain a satisfactory plan with less computing time. Finally, some numeric examples are constructed to analyze (1) the convergence of the algorithm, (2) the effect of some algorithm parameters, and (3) the influence of arrival train flow on the algorithm. PMID:25525614

Next-generation simulation and optimization platform for forest management and analysis

Treesearch

Antti Makinen; Jouni Kalliovirta; Jussi Rasinmaki

2009-01-01

Late developments in the objectives and the data collection methods of forestry create new challenges and possibilities in forest management planning. Tools in forest management and forest planning systems must be able to make good use of novel data sources, use new models, and solve complex forest planning tasks at different scales. The SIMulation and Optimization (...

Surface Modeling of Workpiece and Tool Trajectory Planning for Spray Painting Robot

PubMed Central

Tang, Yang; Chen, Wei

2015-01-01

Automated tool trajectory planning for spray-painting robots is still a challenging problem, especially for a large free-form surface. A grid approximation of a free-form surface is adopted in CAD modeling in this paper. A free-form surface model is approximated by a set of flat patches. We describe here an efficient and flexible tool trajectory optimization scheme using T-Bézier curves calculated in a new way from trigonometrical bases. The distance between the spray gun and the free-form surface along the normal vector is varied. Automotive body parts, which are large free-form surfaces, are used to test the scheme. The experimental results show that the trajectory planning algorithm achieves satisfactory performance. This algorithm can also be extended to other applications. PMID:25993663

Surface modeling of workpiece and tool trajectory planning for spray painting robot.

PubMed

Tang, Yang; Chen, Wei

2015-01-01

Automated tool trajectory planning for spray-painting robots is still a challenging problem, especially for a large free-form surface. A grid approximation of a free-form surface is adopted in CAD modeling in this paper. A free-form surface model is approximated by a set of flat patches. We describe here an efficient and flexible tool trajectory optimization scheme using T-Bézier curves calculated in a new way from trigonometrical bases. The distance between the spray gun and the free-form surface along the normal vector is varied. Automotive body parts, which are large free-form surfaces, are used to test the scheme. The experimental results show that the trajectory planning algorithm achieves satisfactory performance. This algorithm can also be extended to other applications.

Recommendations for the evaluation of specimen stability for flow cytometric testing during drug development.

PubMed

Brown, Lynette; Green, Cherie L; Jones, Nicholas; Stewart, Jennifer J; Fraser, Stephanie; Howell, Kathy; Xu, Yuanxin; Hill, Carla G; Wiwi, Christopher A; White, Wendy I; O'Brien, Peter J; Litwin, Virginia

2015-03-01

The objective of this manuscript is to present an approach for evaluating specimen stability for flow cytometric methods used during drug development. While this approach specifically addresses stability assessment for assays to be used in clinical trials with centralized testing facilities, the concepts can be applied to any stability assessment for flow cytometric methods. The proposed approach is implemented during assay development and optimization, and includes suggestions for designing a stability assessment plan, data evaluation and acceptance criteria. Given that no single solution will be applicable in all scenarios, this manuscript offers the reader a roadmap for stability assessment and is intended to guide the investigator during both the method development phase and in the experimental design of the validation plan. Copyright © 2015 Elsevier B.V. All rights reserved.

Plan averaging for multicriteria navigation of sliding window IMRT and VMAT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Craft, David, E-mail: dcraft@partners.org; Papp, Dávid; Unkelbach, Jan

2014-02-15

Purpose: To describe a method for combining sliding window plans [intensity modulated radiation therapy (IMRT) or volumetric modulated arc therapy (VMAT)] for use in treatment plan averaging, which is needed for Pareto surface navigation based multicriteria treatment planning. Methods: The authors show that by taking an appropriately defined average of leaf trajectories of sliding window plans, the authors obtain a sliding window plan whose fluence map is the exact average of the fluence maps corresponding to the initial plans. In the case of static-beam IMRT, this also implies that the dose distribution of the averaged plan is the exact dosimetricmore » average of the initial plans. In VMAT delivery, the dose distribution of the averaged plan is a close approximation of the dosimetric average of the initial plans. Results: The authors demonstrate the method on three Pareto optimal VMAT plans created for a demanding paraspinal case, where the tumor surrounds the spinal cord. The results show that the leaf averaged plans yield dose distributions that approximate the dosimetric averages of the precomputed Pareto optimal plans well. Conclusions: The proposed method enables the navigation of deliverable Pareto optimal plans directly, i.e., interactive multicriteria exploration of deliverable sliding window IMRT and VMAT plans, eliminating the need for a sequencing step after navigation and hence the dose degradation that is caused by such a sequencing step.« less

Influence of robust optimization in intensity-modulated proton therapy with different dose delivery techniques

PubMed Central

Liu, Wei; Li, Yupeng; Li, Xiaoqiang; Cao, Wenhua; Zhang, Xiaodong

2012-01-01

Purpose: The distal edge tracking (DET) technique in intensity-modulated proton therapy (IMPT) allows for high energy efficiency, fast and simple delivery, and simple inverse treatment planning; however, it is highly sensitive to uncertainties. In this study, the authors explored the application of DET in IMPT (IMPT-DET) and conducted robust optimization of IMPT-DET to see if the planning technique’s sensitivity to uncertainties was reduced. They also compared conventional and robust optimization of IMPT-DET with three-dimensional IMPT (IMPT-3D) to gain understanding about how plan robustness is achieved. Methods: They compared the robustness of IMPT-DET and IMPT-3D plans to uncertainties by analyzing plans created for a typical prostate cancer case and a base of skull (BOS) cancer case (using data for patients who had undergone proton therapy at our institution). Spots with the highest and second highest energy layers were chosen so that the Bragg peak would be at the distal edge of the targets in IMPT-DET using 36 equally spaced angle beams; in IMPT-3D, 3 beams with angles chosen by a beam angle optimization algorithm were planned. Dose contributions for a number of range and setup uncertainties were calculated, and a worst-case robust optimization was performed. A robust quantification technique was used to evaluate the plans’ sensitivity to uncertainties. Results: With no uncertainties considered, the DET is less robust to uncertainties than is the 3D method but offers better normal tissue protection. With robust optimization to account for range and setup uncertainties, robust optimization can improve the robustness of IMPT plans to uncertainties; however, our findings show the extent of improvement varies. Conclusions: IMPT’s sensitivity to uncertainties can be improved by using robust optimization. They found two possible mechanisms that made improvements possible: (1) a localized single-field uniform dose distribution (LSFUD) mechanism, in which the optimization algorithm attempts to produce a single-field uniform dose distribution while minimizing the patching field as much as possible; and (2) perturbed dose distribution, which follows the change in anatomical geometry. Multiple-instance optimization has more knowledge of the influence matrices; this greater knowledge improves IMPT plans’ ability to retain robustness despite the presence of uncertainties. PMID:22755694

SU-F-T-256: 4D IMRT Planning Using An Early Prototype GPU-Enabled Eclipse Workstation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hagan, A; Modiri, A; Sawant, A

Purpose: True 4D IMRT planning, based on simultaneous spatiotemporal optimization has been shown to significantly improve plan quality in lung radiotherapy. However, the high computational complexity associated with such planning represents a significant barrier to widespread clinical deployment. We introduce an early prototype GPU-enabled Eclipse workstation for inverse planning. To our knowledge, this is the first GPUintegrated Eclipse system demonstrating the potential for clinical translation of GPU computing on a major commercially-available TPS. Methods: The prototype system comprised of four NVIDIA Tesla K80 GPUs, with a maximum processing capability of 8.5 Tflops per K80 card. The system architecture consisted ofmore » three key modules: (i) a GPU-based inverse planning module using a highly-parallelizable, swarm intelligence-based global optimization algorithm, (ii) a GPU-based open-source b-spline deformable image registration module, Elastix, and (iii) a CUDA-based data management module. For evaluation, aperture fluence weights in an IMRT plan were optimized over 9 beams,166 apertures and 10 respiratory phases (14940 variables) for a lung cancer case (GTV = 95 cc, right lower lobe, 15 mm cranio-caudal motion). Sensitivity of the planning time and memory expense to parameter variations was quantified. Results: GPU-based inverse planning was significantly accelerated compared to its CPU counterpart (36 vs 488 min, for 10 phases, 10 search agents and 10 iterations). The optimized IMRT plan significantly improved OAR sparing compared to the original internal target volume (ITV)-based clinical plan, while maintaining prescribed tumor coverage. The dose-sparing improvements were: Esophagus Dmax 50%, Heart Dmax 42% and Spinal cord Dmax 25%. Conclusion: Our early prototype system demonstrates that through massive parallelization, computationally intense tasks such as 4D treatment planning can be accomplished in clinically feasible timeframes. With further optimization, such systems are expected to enable the eventual clinical translation of higher-dimensional and complex treatment planning strategies to significantly improve plan quality. This work was partially supported through research funding from National Institutes of Health (R01CA169102) and Varian Medical Systems, Palo Alto, CA, USA.« less

Comparison of different treatment planning optimization methods for vaginal HDR brachytherapy with multichannel applicators: A reduction of the high doses to the vaginal mucosa is possible.

PubMed

Carrara, Mauro; Cusumano, Davide; Giandini, Tommaso; Tenconi, Chiara; Mazzarella, Ester; Grisotto, Simone; Massari, Eleonora; Mazzeo, Davide; Cerrotta, Annamaria; Pappalardi, Brigida; Fallai, Carlo; Pignoli, Emanuele

2017-12-01

A direct planning approach with multi-channel vaginal cylinders (MVCs) used for HDR brachytherapy of vaginal cancers is particularly challenging. Purpose of this study was to compare the dosimetric performances of different forward and inverse methods used for the optimization of MVC-based vaginal treatments for endometrial cancer, with a particular attention to the definition of strategies useful to limit the high doses to the vaginal mucosa. Twelve postoperative vaginal HDR brachytherapy treatments performed with MVCs were considered. Plans were retrospectively optimized with three different methods: Dose Point Optimization followed by Graphical Optimization (DPO + GrO), Inverse Planning Simulated Annealing with two different class solutions as starting conditions (surflPSA and homogIPSA) and Hybrid Inverse Planning Optimization (HIPO). Several dosimetric parameters related to target coverage, hot spot extensions and sparing of organs at risk were analyzed to evaluate the quality of the achieved treatment plans. Dose homogeneity index (DHI), conformal index (COIN) and a further parameter quantifying the proportion of the central catheter loading with respect to the overall loading (i.e., the central catheter loading index: CCLI) were also quantified. The achieved PTV coverage parameters were highly correlated with each other but uncorrelated with the hot spot quantifiers. HomogIPSA and HIPO achieved higher DHIs and CCLIs and lower volumes of high doses than DPO + GrO and surflPSA. Within the investigated optimization methods, HIPO and homoglPSA showed the highest dose homogeneity to the target. In particular, homogIPSA resulted also the most effective in reducing hot spots to the vaginal mucosa. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Development of an Experiment High Performance Nozzle Research Program

NASA Technical Reports Server (NTRS)

2004-01-01

As proposed in the above OAI/NASA Glenn Research Center (GRC) Co-Operative Agreement the objective of the work was to provide consultation and assistance to the NASA GRC GTX Rocket Based Combined Cycle (RBCC) Program Team in planning and developing requirements, scale model concepts, and plans for an experimental nozzle research program. The GTX was one of the launch vehicle concepts being studied as a possible future replacement for the aging NASA Space Shuttle, and was one RBCC element in the ongoing NASA Access to Space R&D Program (Reference 1). The ultimate program objective was the development of an appropriate experimental research program to evaluate and validate proposed nozzle concepts, and thereby result in the optimization of a high performance nozzle for the GTX launch vehicle. Included in this task were the identification of appropriate existing test facilities, development of requirements for new non-existent test rigs and fixtures, develop scale nozzle model concepts, and propose corresponding test plans. Also included were the evaluation of originally proposed and alternate nozzle designs (in-house and contractor), evaluation of Computational Fluid Dynamics (CFD) study results, and make recommendations for geometric changes to result in improved nozzle thrust coefficient performance (Cfg).

SU-C-204-02: Improved Patient-Specific Optimization of the Stopping Power Calibration for Proton Therapy Planning Using a Single Proton Radiography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rinaldi, I; Ludwig Maximilian University, Garching, DE; Heidelberg University Hospital, Heidelberg, DE

2015-06-15

Purpose: We present an improved method to calculate patient-specific calibration curves to convert X-ray computed tomography (CT) Hounsfield Unit (HU) to relative stopping powers (RSP) for proton therapy treatment planning. Methods: By optimizing the HU-RSP calibration curve, the difference between a proton radiographic image and a digitally reconstructed X-ray radiography (DRR) is minimized. The feasibility of this approach has previously been demonstrated. This scenario assumes that all discrepancies between proton radiography and DRR originate from uncertainties in the HU-RSP curve. In reality, external factors cause imperfections in the proton radiography, such as misalignment compared to the DRR and unfaithful representationmore » of geometric structures (“blurring”). We analyze these effects based on synthetic datasets of anthropomorphic phantoms and suggest an extended optimization scheme which explicitly accounts for these effects. Performance of the method is been tested for various simulated irradiation parameters. The ultimate purpose of the optimization is to minimize uncertainties in the HU-RSP calibration curve. We therefore suggest and perform a thorough statistical treatment to quantify the accuracy of the optimized HU-RSP curve. Results: We demonstrate that without extending the optimization scheme, spatial blurring (equivalent to FWHM=3mm convolution) in the proton radiographies can cause up to 10% deviation between the optimized and the ground truth HU-RSP calibration curve. Instead, results obtained with our extended method reach 1% or better correspondence. We have further calculated gamma index maps for different acceptance levels. With DTA=0.5mm and RD=0.5%, a passing ratio of 100% is obtained with the extended method, while an optimization neglecting effects of spatial blurring only reach ∼90%. Conclusion: Our contribution underlines the potential of a single proton radiography to generate a patient-specific calibration curve and to improve dose delivery by optimizing the HU-RSP calibration curve as long as all sources of systematic incongruence are properly modeled.« less

Spatial Coverage Planning and Optimization for Planetary Exploration

NASA Technical Reports Server (NTRS)

Gaines, Daniel M.; Estlin, Tara; Chouinard, Caroline

2008-01-01

We are developing onboard planning and scheduling technology to enable in situ robotic explorers, such as rovers and aerobots, to more effectively assist scientists in planetary exploration. In our current work, we are focusing on situations in which the robot is exploring large geographical features such as craters, channels or regional boundaries. In to develop valid and high quality plans, the robot must take into account a range of scientific and engineering constraints and preferences. We have developed a system that incorporates multiobjective optimization and planning allowing the robot to generate high quality mission operations plans that respect resource limitations and mission constraints while attempting to maximize science and engineering objectives. An important scientific objective for the exploration of geological features is selecting observations that spatially cover an area of interest. We have developed a metric to enable an in situ explorer to reason about and track the spatial coverage quality of a plan. We describe this technique and show how it is combined in the overall multiobjective optimization and planning algorithm.

Application of genetic algorithm in integrated setup planning and operation sequencing

NASA Astrophysics Data System (ADS)

Kafashi, Sajad; Shakeri, Mohsen

2011-01-01

Process planning is an essential component for linking design and manufacturing process. Setup planning and operation sequencing is two main tasks in process planning. Many researches solved these two problems separately. Considering the fact that the two functions are complementary, it is necessary to integrate them more tightly so that performance of a manufacturing system can be improved economically and competitively. This paper present a generative system and genetic algorithm (GA) approach to process plan the given part. The proposed approach and optimization methodology analyses the TAD (tool approach direction), tolerance relation between features and feature precedence relations to generate all possible setups and operations using workshop resource database. Based on these technological constraints the GA algorithm approach, which adopts the feature-based representation, optimizes the setup plan and sequence of operations using cost indices. Case study show that the developed system can generate satisfactory results in optimizing the setup planning and operation sequencing simultaneously in feasible condition.

Comparative effectiveness research methodology using secondary data: A starting user's guide.

PubMed

Sun, Maxine; Lipsitz, Stuart R

2018-04-01

The use of secondary data, such as claims or administrative data, in comparative effectiveness research has grown tremendously in recent years. We believe that the current review can help investigators relying on secondary data to (1) gain insight into both the methodologies and statistical methods, (2) better understand the necessity of a rigorous planning before initiating a comparative effectiveness investigation, and (3) optimize the quality of their investigations. Specifically, we review concepts of adjusted analyses and confounders, methods of propensity score analyses, and instrumental variable analyses, risk prediction models (logistic and time-to-event), decision-curve analysis, as well as the interpretation of the P value and hypothesis testing. Overall, we hope that the current review article can help research investigators relying on secondary data to perform comparative effectiveness research better understand the necessity of a rigorous planning before study start, and gain better insight in the choice of statistical methods so as to optimize the quality of the research study. Copyright © 2017 Elsevier Inc. All rights reserved.

The CPAT 2.0.2 Domain Model - How CPAT 2.0.2 "Thinks" From an Analyst Perspective.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Waddell, Lucas; Muldoon, Frank; Melander, Darryl J.

To help effectively plan the management and modernization of their large and diverse fleets of vehicles, the Program Executive Office Ground Combat Systems (PEO GCS) and the Program Executive Office Combat Support and Combat Service Support (PEO CS &CSS) commissioned the development of a large - scale portfolio planning optimization tool. This software, the Capability Portfolio Analysis Tool (CPAT), creates a detailed schedule that optimally prioritizes the modernization or replacement of vehicles within the fleet - respecting numerous business rules associated with fleet structure, budgets, industrial base, research and testing, etc., while maximizing overall fleet performance through time. This reportmore » contains a description of the organizational fleet structure and a thorough explanation of the business rules that the CPAT formulation follows involving performance, scheduling, production, and budgets. This report, which is an update to the original CPAT domain model published in 2015 (SAND2015 - 4009), covers important new CPAT features. This page intentionally left blank« less

The Capability Portfolio Analysis Tool (CPAT): A Mixed Integer Linear Programming Formulation for Fleet Modernization Analysis (Version 2.0.2).

DOE Office of Scientific and Technical Information (OSTI.GOV)

Waddell, Lucas; Muldoon, Frank; Henry, Stephen Michael

In order to effectively plan the management and modernization of their large and diverse fleets of vehicles, Program Executive Office Ground Combat Systems (PEO GCS) and Program Executive Office Combat Support and Combat Service Support (PEO CS&CSS) commis- sioned the development of a large-scale portfolio planning optimization tool. This software, the Capability Portfolio Analysis Tool (CPAT), creates a detailed schedule that optimally prioritizes the modernization or replacement of vehicles within the fleet - respecting numerous business rules associated with fleet structure, budgets, industrial base, research and testing, etc., while maximizing overall fleet performance through time. This paper contains a thor-more » ough documentation of the terminology, parameters, variables, and constraints that comprise the fleet management mixed integer linear programming (MILP) mathematical formulation. This paper, which is an update to the original CPAT formulation document published in 2015 (SAND2015-3487), covers the formulation of important new CPAT features.« less

SU-D-BRB-02: Combining a Commercial Autoplanning Engine with Database Dose Predictions to Further Improve Plan Quality

DOE Office of Scientific and Technical Information (OSTI.GOV)

Robertson, SP; Moore, JA; Hui, X

Purpose: Database dose predictions and a commercial autoplanning engine both improve treatment plan quality in different but complimentary ways. The combination of these planning techniques is hypothesized to further improve plan quality. Methods: Four treatment plans were generated for each of 10 head and neck (HN) and 10 prostate cancer patients, including Plan-A: traditional IMRT optimization using clinically relevant default objectives; Plan-B: traditional IMRT optimization using database dose predictions; Plan-C: autoplanning using default objectives; and Plan-D: autoplanning using database dose predictions. One optimization was used for each planning method. Dose distributions were normalized to 95% of the planning target volumemore » (prostate: 8000 cGy; HN: 7000 cGy). Objectives used in plan optimization and analysis were the larynx (25%, 50%, 90%), left and right parotid glands (50%, 85%), spinal cord (0%, 50%), rectum and bladder (0%, 20%, 50%, 80%), and left and right femoral heads (0%, 70%). Results: All objectives except larynx 25% and 50% resulted in statistically significant differences between plans (Friedman’s χ{sup 2} ≥ 11.2; p ≤ 0.011). Maximum dose to the rectum (Plans A-D: 8328, 8395, 8489, 8537 cGy) and bladder (Plans A-D: 8403, 8448, 8527, 8569 cGy) were significantly increased. All other significant differences reflected a decrease in dose. Plans B-D were significantly different from Plan-A for 3, 17, and 19 objectives, respectively. Plans C-D were also significantly different from Plan-B for 8 and 13 objectives, respectively. In one case (cord 50%), Plan-D provided significantly lower dose than plan C (p = 0.003). Conclusion: Combining database dose predictions with a commercial autoplanning engine resulted in significant plan quality differences for the greatest number of objectives. This translated to plan quality improvements in most cases, although special care may be needed for maximum dose constraints. Further evaluation is warranted in a larger cohort across HN, prostate, and other treatment sites. This work is supported by Philips Radiation Oncology Systems.« less

Multi-GPU implementation of a VMAT treatment plan optimization algorithm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tian, Zhen, E-mail: Zhen.Tian@UTSouthwestern.edu, E-mail: Xun.Jia@UTSouthwestern.edu, E-mail: Steve.Jiang@UTSouthwestern.edu; Folkerts, Michael; Tan, Jun

Purpose: Volumetric modulated arc therapy (VMAT) optimization is a computationally challenging problem due to its large data size, high degrees of freedom, and many hardware constraints. High-performance graphics processing units (GPUs) have been used to speed up the computations. However, GPU’s relatively small memory size cannot handle cases with a large dose-deposition coefficient (DDC) matrix in cases of, e.g., those with a large target size, multiple targets, multiple arcs, and/or small beamlet size. The main purpose of this paper is to report an implementation of a column-generation-based VMAT algorithm, previously developed in the authors’ group, on a multi-GPU platform tomore » solve the memory limitation problem. While the column-generation-based VMAT algorithm has been previously developed, the GPU implementation details have not been reported. Hence, another purpose is to present detailed techniques employed for GPU implementation. The authors also would like to utilize this particular problem as an example problem to study the feasibility of using a multi-GPU platform to solve large-scale problems in medical physics. Methods: The column-generation approach generates VMAT apertures sequentially by solving a pricing problem (PP) and a master problem (MP) iteratively. In the authors’ method, the sparse DDC matrix is first stored on a CPU in coordinate list format (COO). On the GPU side, this matrix is split into four submatrices according to beam angles, which are stored on four GPUs in compressed sparse row format. Computation of beamlet price, the first step in PP, is accomplished using multi-GPUs. A fast inter-GPU data transfer scheme is accomplished using peer-to-peer access. The remaining steps of PP and MP problems are implemented on CPU or a single GPU due to their modest problem scale and computational loads. Barzilai and Borwein algorithm with a subspace step scheme is adopted here to solve the MP problem. A head and neck (H and N) cancer case is then used to validate the authors’ method. The authors also compare their multi-GPU implementation with three different single GPU implementation strategies, i.e., truncating DDC matrix (S1), repeatedly transferring DDC matrix between CPU and GPU (S2), and porting computations involving DDC matrix to CPU (S3), in terms of both plan quality and computational efficiency. Two more H and N patient cases and three prostate cases are used to demonstrate the advantages of the authors’ method. Results: The authors’ multi-GPU implementation can finish the optimization process within ∼1 min for the H and N patient case. S1 leads to an inferior plan quality although its total time was 10 s shorter than the multi-GPU implementation due to the reduced matrix size. S2 and S3 yield the same plan quality as the multi-GPU implementation but take ∼4 and ∼6 min, respectively. High computational efficiency was consistently achieved for the other five patient cases tested, with VMAT plans of clinically acceptable quality obtained within 23–46 s. Conversely, to obtain clinically comparable or acceptable plans for all six of these VMAT cases that the authors have tested in this paper, the optimization time needed in a commercial TPS system on CPU was found to be in an order of several minutes. Conclusions: The results demonstrate that the multi-GPU implementation of the authors’ column-generation-based VMAT optimization can handle the large-scale VMAT optimization problem efficiently without sacrificing plan quality. The authors’ study may serve as an example to shed some light on other large-scale medical physics problems that require multi-GPU techniques.« less

Voxel-based dose prediction with multi-patient atlas selection for automated radiotherapy treatment planning

NASA Astrophysics Data System (ADS)

McIntosh, Chris; Purdie, Thomas G.

2017-01-01

Automating the radiotherapy treatment planning process is a technically challenging problem. The majority of automated approaches have focused on customizing and inferring dose volume objectives to be used in plan optimization. In this work we outline a multi-patient atlas-based dose prediction approach that learns to predict the dose-per-voxel for a novel patient directly from the computed tomography planning scan without the requirement of specifying any objectives. Our method learns to automatically select the most effective atlases for a novel patient, and then map the dose from those atlases onto the novel patient. We extend our previous work to include a conditional random field for the optimization of a joint distribution prior that matches the complementary goals of an accurately spatially distributed dose distribution while still adhering to the desired dose volume histograms. The resulting distribution can then be used for inverse-planning with a new spatial dose objective, or to create typical dose volume objectives for the canonical optimization pipeline. We investigated six treatment sites (633 patients for training and 113 patients for testing) and evaluated the mean absolute difference in all DVHs for the clinical and predicted dose distribution. The results on average are favorable in comparison to our previous approach (1.91 versus 2.57). Comparing our method with and without atlas-selection further validates that atlas-selection improved dose prediction on average in whole breast (0.64 versus 1.59), prostate (2.13 versus 4.07), and rectum (1.46 versus 3.29) while it is less important in breast cavity (0.79 versus 0.92) and lung (1.33 versus 1.27) for which there is high conformity and minimal dose shaping. In CNS brain, atlas-selection has the potential to be impactful (3.65 versus 5.09), but selecting the ideal atlas is the most challenging.

Large-scale linear programs in planning and prediction.

DOT National Transportation Integrated Search

2017-06-01

Large-scale linear programs are at the core of many traffic-related optimization problems in both planning and prediction. Moreover, many of these involve significant uncertainty, and hence are modeled using either chance constraints, or robust optim...

OPTIMIZATION OF MUD HAMMER DRILLING PERFORMANCE - A PROGRAM TO BENCHMARK THE VIABILITY OF ADVANCED MUD HAMMER DRILLING

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gordon Tibbitts; Arnis Judzis

2001-10-01

This document details the progress to date on the OPTIMIZATION OF MUD HAMMER DRILLING PERFORMANCE -- A PROGRAM TO BENCHMARK THE VIABILITY OF ADVANCED MUD HAMMER DRILLING contract for the quarter starting July 2001 through September 2001. Accomplishments to date include the following: TerraTek highlighted DOE's National Energy Technology Laboratory effort on Mud Hammer Optimization at the recent Annual Conference and Exhibition for the Society of Petroleum Engineers. The original exhibit scheduled by NETL was canceled due to events surrounding the September tragedies in the US. TerraTek has completed analysis of drilling performance (rates of penetration, hydraulics, etc.) for themore » Phase One testing which was completed at the beginning of July. TerraTek jointly with the Industry Advisory Board for this project and DOE/NETL conducted a lessons learned meeting to transfer technology vital for the next series of performance tests. Both hammer suppliers benefited from the testing program and are committed to pursue equipment improvements and ''optimization'' in accordance with the scope of work. An abstract for a proposed publication by the society of Petroleum Engineers/International Association of Drilling Contractors jointly sponsored Drilling Conference was accepted as an alternate paper. Technology transfer is encouraged by the DOE in this program, thus plans are underway to prepare the paper for this prestigious venue.« less

Methodology, status and plans for development and assessment of Cathare code

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bestion, D.; Barre, F.; Faydide, B.

1997-07-01

This paper presents the methodology, status and plans for the development, assessment and uncertainty evaluation of the Cathare code. Cathare is a thermalhydraulic code developed by CEA (DRN), IPSN, EDF and FRAMATOME for PWR safety analysis. First, the status of the code development and assessment is presented. The general strategy used for the development and the assessment of the code is presented. Analytical experiments with separate effect tests, and component tests are used for the development and the validation of closure laws. Successive Revisions of constitutive laws are implemented in successive Versions of the code and assessed. System tests ormore » integral tests are used to validate the general consistency of the Revision. Each delivery of a code Version + Revision is fully assessed and documented. A methodology is being developed to determine the uncertainty on all constitutive laws of the code using calculations of many analytical tests and applying the Discrete Adjoint Sensitivity Method (DASM). At last, the plans for the future developments of the code are presented. They concern the optimization of the code performance through parallel computing - the code will be used for real time full scope plant simulators - the coupling with many other codes (neutronic codes, severe accident codes), the application of the code for containment thermalhydraulics. Also, physical improvements are required in the field of low pressure transients and in the modeling for the 3-D model.« less

Risk-based planning analysis for a single levee

NASA Astrophysics Data System (ADS)

Hui, Rui; Jachens, Elizabeth; Lund, Jay

2016-04-01

Traditional risk-based analysis for levee planning focuses primarily on overtopping failure. Although many levees fail before overtopping, few planning studies explicitly include intermediate geotechnical failures in flood risk analysis. This study develops a risk-based model for two simplified levee failure modes: overtopping failure and overall intermediate geotechnical failure from through-seepage, determined by the levee cross section represented by levee height and crown width. Overtopping failure is based only on water level and levee height, while through-seepage failure depends on many geotechnical factors as well, mathematically represented here as a function of levee crown width using levee fragility curves developed from professional judgment or analysis. These levee planning decisions are optimized to minimize the annual expected total cost, which sums expected (residual) annual flood damage and annualized construction costs. Applicability of this optimization approach to planning new levees or upgrading existing levees is demonstrated preliminarily for a levee on a small river protecting agricultural land, and a major levee on a large river protecting a more valuable urban area. Optimized results show higher likelihood of intermediate geotechnical failure than overtopping failure. The effects of uncertainty in levee fragility curves, economic damage potential, construction costs, and hydrology (changing climate) are explored. Optimal levee crown width is more sensitive to these uncertainties than height, while the derived general principles and guidelines for risk-based optimal levee planning remain the same.

On-line Adaptive Radiation Treatment of Prostate Cancer

DTIC Science & Technology

2009-01-01

12]. For intensity modulated radiation therapy (IMRT) plans , the beamlet weight can be re-optimized on a daily basis to mini- mize the dose to the OAR...Thongphiew D, Wang Z, Mathayomchan B, Chankong V, Yoo S, et al. On-line re-optimization of prostate IMRT plans for adaptive radiation therapy . Phys Med Biol...time. The treatment planning method for VMAT however is not mature. We are developing a robust VMAT treatment planning method which incorporates

MO-FG-CAMPUS-TeP3-04: Deliverable Robust Optimization in IMPT Using Quadratic Objective Function

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shan, J; Liu, W; Bues, M

Purpose: To find and evaluate the way of applying deliverable MU constraints into robust spot intensity optimization in Intensity-Modulated- Proton-Therapy (IMPT) to prevent plan quality and robustness from degrading due to machine deliverable MU-constraints. Methods: Currently, the influence of the deliverable MU-constraints is retrospectively evaluated by post-processing immediately following optimization. In this study, we propose a new method based on the quasi-Newton-like L-BFGS-B algorithm with which we turn deliverable MU-constraints on and off alternatively during optimization. Seven patients with two different machine settings (small and large spot size) were planned with both conventional and new methods. For each patient, threemore » kinds of plans were generated — conventional non-deliverable plan (plan A), conventional deliverable plan with post-processing (plan B), and new deliverable plan (plan C). We performed this study with both realistic (small) and artificial (large) deliverable MU-constraints. Results: With small minimum MU-constraints considered, new method achieved a slightly better plan quality than conventional method (D95% CTV normalized to the prescription dose: 0.994[0.992∼0.996] (Plan C) vs 0.992[0.986∼0.996] (Plan B)). With large minimum MU constraints considered, results show that the new method maintains plan quality while plan quality from the conventional method is degraded greatly (D95% CTV normalized to the prescription dose: 0.987[0.978∼0.994] (Plan C) vs 0.797[0.641∼1.000] (Plan B)). Meanwhile, plan robustness of these two method’s results is comparable. (For all 7 patients, CTV DVH band gap at D95% normalized to the prescription dose: 0.015[0.005∼0.043] (Plan C) vs 0.012[0.006∼0.038] (Plan B) with small MU-constraints and 0.019[0.009∼0.039] (Plan C) vs 0.030[0.015∼0.041] (Plan B) with large MU-constraints) Conclusion: Positive correlation has been found between plan quality degeneration and magnitude of deliverable minimal MU. Compared to conventional post-processing method, our new method of incorporating deliverable minimal MU-constraints directly into plan optimization, can produce machine-deliverable plans with better plan qualities and non-compromised plan robustness. This research was supported by the National Cancer Institute Career Developmental Award K25CA168984, by the Fraternal Order of Eagles Cancer Research Fund Career Development Award, by The Lawrence W. and Marilyn W. Matteson Fund for Cancer Research, by Mayo Arizona State University Seed Grant and by The Kemper Marley Foundation.« less

Hybrid Motion Planning with Multiple Destinations

NASA Technical Reports Server (NTRS)

Clouse, Jeffery

1998-01-01

In our initial proposal, we laid plans for developing a hybrid motion planning system that combines the concepts of visibility-based motion planning, artificial potential field based motion planning, evolutionary constrained optimization, and reinforcement learning. Our goal was, and still is, to produce a hybrid motion planning system that outperforms the best traditional motion planning systems on problems with dynamic environments. The proposed hybrid system will be in two parts the first is a global motion planning system and the second is a local motion planning system. The global system will take global information about the environment, such as the placement of the obstacles and goals, and produce feasible paths through those obstacles. We envision a system that combines the evolutionary-based optimization and visibility-based motion planning to achieve this end.

SU-E-T-549: A Combinatorial Optimization Approach to Treatment Planning with Non-Uniform Fractions in Intensity Modulated Proton Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Papp, D; Unkelbach, J

2014-06-01

Purpose: Non-uniform fractionation, i.e. delivering distinct dose distributions in two subsequent fractions, can potentially improve outcomes by increasing biological dose to the target without increasing dose to healthy tissues. This is possible if both fractions deliver a similar dose to normal tissues (exploit the fractionation effect) but high single fraction doses to subvolumes of the target (hypofractionation). Optimization of such treatment plans can be formulated using biological equivalent dose (BED), but leads to intractable nonconvex optimization problems. We introduce a novel optimization approach to address this challenge. Methods: We first optimize a reference IMPT plan using standard techniques that deliversmore » a homogeneous target dose in both fractions. The method then divides the pencil beams into two sets, which are assigned to either fraction one or fraction two. The total intensity of each pencil beam, and therefore the physical dose, remains unchanged compared to the reference plan. The objectives are to maximize the mean BED in the target and to minimize the mean BED in normal tissues, which is a quadratic function of the pencil beam weights. The optimal reassignment of pencil beams to one of the two fractions is formulated as a binary quadratic optimization problem. A near-optimal solution to this problem can be obtained by convex relaxation and randomized rounding. Results: The method is demonstrated for a large arteriovenous malformation (AVM) case treated in two fractions. The algorithm yields a treatment plan, which delivers a high dose to parts of the AVM in one of the fractions, but similar doses in both fractions to the normal brain tissue adjacent to the AVM. Using the approach, the mean BED in the target was increased by approximately 10% compared to what would have been possible with a uniform reference plan for the same normal tissue mean BED.« less

Multi-GPU configuration of 4D intensity modulated radiation therapy inverse planning using global optimization

NASA Astrophysics Data System (ADS)

Hagan, Aaron; Sawant, Amit; Folkerts, Michael; Modiri, Arezoo

2018-01-01

We report on the design, implementation and characterization of a multi-graphic processing unit (GPU) computational platform for higher-order optimization in radiotherapy treatment planning. In collaboration with a commercial vendor (Varian Medical Systems, Palo Alto, CA), a research prototype GPU-enabled Eclipse (V13.6) workstation was configured. The hardware consisted of dual 8-core Xeon processors, 256 GB RAM and four NVIDIA Tesla K80 general purpose GPUs. We demonstrate the utility of this platform for large radiotherapy optimization problems through the development and characterization of a parallelized particle swarm optimization (PSO) four dimensional (4D) intensity modulated radiation therapy (IMRT) technique. The PSO engine was coupled to the Eclipse treatment planning system via a vendor-provided scripting interface. Specific challenges addressed in this implementation were (i) data management and (ii) non-uniform memory access (NUMA). For the former, we alternated between parameters over which the computation process was parallelized. For the latter, we reduced the amount of data required to be transferred over the NUMA bridge. The datasets examined in this study were approximately 300 GB in size, including 4D computed tomography images, anatomical structure contours and dose deposition matrices. For evaluation, we created a 4D-IMRT treatment plan for one lung cancer patient and analyzed computation speed while varying several parameters (number of respiratory phases, GPUs, PSO particles, and data matrix sizes). The optimized 4D-IMRT plan enhanced sparing of organs at risk by an average reduction of 26% in maximum dose, compared to the clinical optimized IMRT plan, where the internal target volume was used. We validated our computation time analyses in two additional cases. The computation speed in our implementation did not monotonically increase with the number of GPUs. The optimal number of GPUs (five, in our study) is directly related to the hardware specifications. The optimization process took 35 min using 50 PSO particles, 25 iterations and 5 GPUs.

Multi-GPU configuration of 4D intensity modulated radiation therapy inverse planning using global optimization.

PubMed

Hagan, Aaron; Sawant, Amit; Folkerts, Michael; Modiri, Arezoo

2018-01-16

We report on the design, implementation and characterization of a multi-graphic processing unit (GPU) computational platform for higher-order optimization in radiotherapy treatment planning. In collaboration with a commercial vendor (Varian Medical Systems, Palo Alto, CA), a research prototype GPU-enabled Eclipse (V13.6) workstation was configured. The hardware consisted of dual 8-core Xeon processors, 256 GB RAM and four NVIDIA Tesla K80 general purpose GPUs. We demonstrate the utility of this platform for large radiotherapy optimization problems through the development and characterization of a parallelized particle swarm optimization (PSO) four dimensional (4D) intensity modulated radiation therapy (IMRT) technique. The PSO engine was coupled to the Eclipse treatment planning system via a vendor-provided scripting interface. Specific challenges addressed in this implementation were (i) data management and (ii) non-uniform memory access (NUMA). For the former, we alternated between parameters over which the computation process was parallelized. For the latter, we reduced the amount of data required to be transferred over the NUMA bridge. The datasets examined in this study were approximately 300 GB in size, including 4D computed tomography images, anatomical structure contours and dose deposition matrices. For evaluation, we created a 4D-IMRT treatment plan for one lung cancer patient and analyzed computation speed while varying several parameters (number of respiratory phases, GPUs, PSO particles, and data matrix sizes). The optimized 4D-IMRT plan enhanced sparing of organs at risk by an average reduction of [Formula: see text] in maximum dose, compared to the clinical optimized IMRT plan, where the internal target volume was used. We validated our computation time analyses in two additional cases. The computation speed in our implementation did not monotonically increase with the number of GPUs. The optimal number of GPUs (five, in our study) is directly related to the hardware specifications. The optimization process took 35 min using 50 PSO particles, 25 iterations and 5 GPUs.

Risk Analysis for Resource Planning Optimization

NASA Technical Reports Server (NTRS)

Chueng, Kar-Ming

2008-01-01

The main purpose of this paper is to introduce a risk management approach that allows planners to quantify the risk and efficiency tradeoff in the presence of uncertainties, and to make forward-looking choices in the development and execution of the plan. Demonstrate a planning and risk analysis framework that tightly integrates mathematical optimization, empirical simulation, and theoretical analysis techniques to solve complex problems.

Simulated annealing in orbital flight planning

NASA Technical Reports Server (NTRS)

Soller, Jeffrey

1990-01-01

Simulated annealing is used to solve a minimum fuel trajectory problem in the space station environment. The environment is unique because the space station will define the first true multivehicle environment in space. The optimization yields surfaces which are potentially complex, with multiple local minima. Because of the likelihood of these local minima, descent techniques are unable to offer robust solutions. Other deterministic optimization techniques were explored without success. The simulated annealing optimization is capable of identifying a minimum-fuel, two-burn trajectory subject to four constraints. Furthermore, the computational efforts involved in the optimization are such that missions could be planned on board the space station. Potential applications could include the on-site planning of rendezvous with a target craft of the emergency rescue of an astronaut. Future research will include multiwaypoint maneuvers, using a knowledge base to guide the optimization.

Study of Double-Weighted Graph Model and Optimal Path Planning for Tourist Scenic Area Oriented Intelligent Tour Guide

NASA Astrophysics Data System (ADS)

Shi, Y.; Long, Y.; Wi, X. L.

2014-04-01

When tourists visiting multiple tourist scenic spots, the travel line is usually the most effective road network according to the actual tour process, and maybe the travel line is different from planned travel line. For in the field of navigation, a proposed travel line is normally generated automatically by path planning algorithm, considering the scenic spots' positions and road networks. But when a scenic spot have a certain area and have multiple entrances or exits, the traditional described mechanism of single point coordinates is difficult to reflect these own structural features. In order to solve this problem, this paper focuses on the influence on the process of path planning caused by scenic spots' own structural features such as multiple entrances or exits, and then proposes a doubleweighted Graph Model, for the weight of both vertexes and edges of proposed Model can be selected dynamically. And then discusses the model building method, and the optimal path planning algorithm based on Dijkstra algorithm and Prim algorithm. Experimental results show that the optimal planned travel line derived from the proposed model and algorithm is more reasonable, and the travelling order and distance would be further optimized.

A Generalized Decision Framework Using Multi-objective Optimization for Water Resources Planning

NASA Astrophysics Data System (ADS)

Basdekas, L.; Stewart, N.; Triana, E.

2013-12-01

Colorado Springs Utilities (CSU) is currently engaged in an Integrated Water Resource Plan (IWRP) to address the complex planning scenarios, across multiple time scales, currently faced by CSU. The modeling framework developed for the IWRP uses a flexible data-centered Decision Support System (DSS) with a MODSIM-based modeling system to represent the operation of the current CSU raw water system coupled with a state-of-the-art multi-objective optimization algorithm. Three basic components are required for the framework, which can be implemented for planning horizons ranging from seasonal to interdecadal. First, a water resources system model is required that is capable of reasonable system simulation to resolve performance metrics at the appropriate temporal and spatial scales of interest. The system model should be an existing simulation model, or one developed during the planning process with stakeholders, so that 'buy-in' has already been achieved. Second, a hydrologic scenario tool(s) capable of generating a range of plausible inflows for the planning period of interest is required. This may include paleo informed or climate change informed sequences. Third, a multi-objective optimization model that can be wrapped around the system simulation model is required. The new generation of multi-objective optimization models do not require parameterization which greatly reduces problem complexity. Bridging the gap between research and practice will be evident as we use a case study from CSU's planning process to demonstrate this framework with specific competing water management objectives. Careful formulation of objective functions, choice of decision variables, and system constraints will be discussed. Rather than treating results as theoretically Pareto optimal in a planning process, we use the powerful multi-objective optimization models as tools to more efficiently and effectively move out of the inferior decision space. The use of this framework will help CSU evaluate tradeoffs in a continually changing world.

An Optimized Trajectory Planning for Welding Robot

NASA Astrophysics Data System (ADS)

Chen, Zhilong; Wang, Jun; Li, Shuting; Ren, Jun; Wang, Quan; Cheng, Qunchao; Li, Wentao

2018-03-01

In order to improve the welding efficiency and quality, this paper studies the combined planning between welding parameters and space trajectory for welding robot and proposes a trajectory planning method with high real-time performance, strong controllability and small welding error. By adding the virtual joint at the end-effector, the appropriate virtual joint model is established and the welding process parameters are represented by the virtual joint variables. The trajectory planning is carried out in the robot joint space, which makes the control of the welding process parameters more intuitive and convenient. By using the virtual joint model combined with the B-spline curve affine invariant, the welding process parameters are indirectly controlled by controlling the motion curve of the real joint. To solve the optimal time solution as the goal, the welding process parameters and joint space trajectory joint planning are optimized.

SU-E-T-436: Fluence-Based Trajectory Optimization for Non-Coplanar VMAT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smyth, G; Bamber, JC; Bedford, JL

2015-06-15

Purpose: To investigate a fluence-based trajectory optimization technique for non-coplanar VMAT for brain cancer. Methods: Single-arc non-coplanar VMAT trajectories were determined using a heuristic technique for five patients. Organ at risk (OAR) volume intersected during raytracing was minimized for two cases: absolute volume and the sum of relative volumes weighted by OAR importance. These trajectories and coplanar VMAT formed starting points for the fluence-based optimization method. Iterative least squares optimization was performed on control points 24° apart in gantry rotation. Optimization minimized the root-mean-square (RMS) deviation of PTV dose from the prescription (relative importance 100), maximum dose to the brainstemmore » (10), optic chiasm (5), globes (5) and optic nerves (5), plus mean dose to the lenses (5), hippocampi (3), temporal lobes (2), cochleae (1) and brain excluding other regions of interest (1). Control point couch rotations were varied in steps of up to 10° and accepted if the cost function improved. Final treatment plans were optimized with the same objectives in an in-house planning system and evaluated using a composite metric - the sum of optimization metrics weighted by importance. Results: The composite metric decreased with fluence-based optimization in 14 of the 15 plans. In the remaining case its overall value, and the PTV and OAR components, were unchanged but the balance of OAR sparing differed. PTV RMS deviation was improved in 13 cases and unchanged in two. The OAR component was reduced in 13 plans. In one case the OAR component increased but the composite metric decreased - a 4 Gy increase in OAR metrics was balanced by a reduction in PTV RMS deviation from 2.8% to 2.6%. Conclusion: Fluence-based trajectory optimization improved plan quality as defined by the composite metric. While dose differences were case specific, fluence-based optimization improved both PTV and OAR dosimetry in 80% of cases.« less

VT-136 Market Research and Sourcing Case Exercise

DTIC Science & Technology

2006-04-30

Josh Parsons (USAF), Army AL&T Magazine, January-February 2005 Web Edition. “The Yoder Three-tier Model for Optimal Planning and Execution of...relevant to pricing and ability to determine “fair and reasonable” price2 Identification of suitable substitutes and alternative products or...Tests for Determining Fair and Reasonable Price By far, the best methodology for making the determination that a product or service cost or price

Specific recommendations for accurate and direct use of PET-CT in PET guided radiotherapy for head and neck sites

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thomas, C. M., E-mail: christopher.thomas@gstt.nhs.uk; Convery, D. J.; Greener, A. G.

2014-04-15

Purpose: To provide specific experience-based guidance and recommendations for centers wishing to develop, validate, and implement an accurate and efficient process for directly using positron emission tomography-computed tomography (PET-CT) for the radiotherapy planning of head and neck cancer patients. Methods: A PET-CT system was modified with hard-top couch, external lasers and radiotherapy immobilization and indexing devices and was subject to a commissioning and quality assurance program. PET-CT imaging protocols were developed specifically for radiotherapy planning and the image quality and pathway tested using phantoms and five patients recruited into an in-house study. Security and accuracy of data transfer was testedmore » throughout the whole data pathway. The patient pathway was fully established and tested ready for implementation in a PET-guided dose-escalation trial for head and neck cancer patients. Results: Couch deflection was greater than for departmental CT simulator machines. An area of high attenuation in the couch generated image artifacts and adjustments were made accordingly. Using newly developed protocols CT image quality was suitable to maintain delineation and treatment accuracy. Upon transfer of data to the treatment planning system a half pixel offset between PET and CT was observed and corrected. By taking this into account, PET to CT alignment accuracy was maintained below 1 mm in all systems in the data pathway. Transfer of structures delineated in the PET fusion software to the radiotherapy treatment planning system was validated. Conclusions: A method to perform direct PET-guided radiotherapy planning was successfully validated and specific recommendations were developed to assist other centers. Of major concern is ensuring that the quality of PET and CT data is appropriate for radiotherapy treatment planning and on-treatment verification. Couch movements can be compromised, bore-size can be a limitation for certain immobilization techniques, laser positioning may affect setup accuracy and couch deflection may be greater than scanners dedicated to radiotherapy. The full set of departmental commissioning and routine quality assurance tests applied to radiotherapy CT simulators must be carried out on the PET-CT scanner. CT image quality must be optimized for radiotherapy planning whilst understanding that the appearance will differ between scanners and may affect delineation. PET-CT quality assurance schedules will need to be added to and modified to incorporate radiotherapy quality assurance. Methods of working for radiotherapy and PET staff will change to take into account considerations of both parties. PET to CT alignment must be subject to quality control on a loaded and unloaded couch preferably using a suitable emission phantom, and tested throughout the whole data pathway. Data integrity must be tested throughout the whole pathway and a system included to verify that delineated structures are transferred correctly. Excellent multidisciplinary team communication and working is vital, and key staff members on both sides should be specifically dedicated to the project. Patient pathway should be clearly devised to optimize patient care and the resources of all departments. Recruitment of a cohort of patients into a methodology study is valuable to test the quality assurance methods and pathway.« less

Automatic CT simulation optimization for radiation therapy: A general strategy.

PubMed

Li, Hua; Yu, Lifeng; Anastasio, Mark A; Chen, Hsin-Chen; Tan, Jun; Gay, Hiram; Michalski, Jeff M; Low, Daniel A; Mutic, Sasa

2014-03-01

In radiation therapy, x-ray computed tomography (CT) simulation protocol specifications should be driven by the treatment planning requirements in lieu of duplicating diagnostic CT screening protocols. The purpose of this study was to develop a general strategy that allows for automatically, prospectively, and objectively determining the optimal patient-specific CT simulation protocols based on radiation-therapy goals, namely, maintenance of contouring quality and integrity while minimizing patient CT simulation dose. The authors proposed a general prediction strategy that provides automatic optimal CT simulation protocol selection as a function of patient size and treatment planning task. The optimal protocol is the one that delivers the minimum dose required to provide a CT simulation scan that yields accurate contours. Accurate treatment plans depend on accurate contours in order to conform the dose to actual tumor and normal organ positions. An image quality index, defined to characterize how simulation scan quality affects contour delineation, was developed and used to benchmark the contouring accuracy and treatment plan quality within the predication strategy. A clinical workflow was developed to select the optimal CT simulation protocols incorporating patient size, target delineation, and radiation dose efficiency. An experimental study using an anthropomorphic pelvis phantom with added-bolus layers was used to demonstrate how the proposed prediction strategy could be implemented and how the optimal CT simulation protocols could be selected for prostate cancer patients based on patient size and treatment planning task. Clinical IMRT prostate treatment plans for seven CT scans with varied image quality indices were separately optimized and compared to verify the trace of target and organ dosimetry coverage. Based on the phantom study, the optimal image quality index for accurate manual prostate contouring was 4.4. The optimal tube potentials for patient sizes of 38, 43, 48, 53, and 58 cm were 120, 140, 140, 140, and 140 kVp, respectively, and the corresponding minimum CTDIvol for achieving the optimal image quality index 4.4 were 9.8, 32.2, 100.9, 241.4, and 274.1 mGy, respectively. For patients with lateral sizes of 43-58 cm, 120-kVp scan protocols yielded up to 165% greater radiation dose relative to 140-kVp protocols, and 140-kVp protocols always yielded a greater image quality index compared to the same dose-level 120-kVp protocols. The trace of target and organ dosimetry coverage and the γ passing rates of seven IMRT dose distribution pairs indicated the feasibility of the proposed image quality index for the predication strategy. A general strategy to predict the optimal CT simulation protocols in a flexible and quantitative way was developed that takes into account patient size, treatment planning task, and radiation dose. The experimental study indicated that the optimal CT simulation protocol and the corresponding radiation dose varied significantly for different patient sizes, contouring accuracy, and radiation treatment planning tasks.

Braided Composite Technologies for Rotorcraft Structures

NASA Technical Reports Server (NTRS)

Jessie, Nathan

2015-01-01

A&P Technology has developed a braided material approach for fabricating lightweight, high-strength hybrid gears for aerospace drive systems. The conventional metallic web was replaced with a composite element made from A&P's quasi-isotropic braid. The 0deg, +/-60deg braid architecture was chosen so that inplane stiffness properties and strength would be nearly equal in all directions. The test results from the Phase I Small Spur Gear program demonstrated satisfactory endurance and strength while providing a 20 percent weight savings. (Greater weight savings is anticipated with structural optimization.) The hybrid gears were subjected to a proof-of-concept test of 1 billion cycles in a gearbox at 10,000 revolutions per minute and 490 in-lb torque with no detectable damage to the gears. After this test the maximum torque capability was also tested, and the static strength capability of the gears was 7x the maximum operating condition. Additional proof-of-concept tests are in progress using a higher oil temperature, and a loss-of-oil test is planned. The success of Phase I led to a Phase II program to develop, fabricate, and optimize full-scale gears, specifically Bull Gears. The design of these Bull Gears will be refined using topology optimization, and the full-scale Bull Gears will be tested in a full-scale gear rig. The testing will quantify benefits of weight savings, as well as noise and vibration reduction. The expectation is that vibration and noise will be reduced through the introduction of composite material in the vibration transmission path between the contacting gear teeth and the shaft-and-bearing system.

Braided Composite Technologies for Rotorcraft Structures

NASA Technical Reports Server (NTRS)

Jessie, Nathan

2014-01-01

A&P Technology has developed a braided material approach for fabricating lightweight, high-strength hybrid gears for aerospace drive systems. The conventional metallic web was replaced with a composite element made from A&P's quasi-isotropic braid. The 0deg, plus or minus 60 deg braid architecture was chosen so that inplane stiffness properties and strength would be nearly equal in all directions. The test results from the Phase I Small Spur Gear program demonstrated satisfactory endurance and strength while providing a 20 percent weight savings. (Greater weight savings is anticipated with structural optimization.) The hybrid gears were subjected to a proof-of-concept test of 1 billion cycles in a gearbox at 10,000 revolutions per minute and 490 in-lb torque with no detectable damage to the gears. After this test the maximum torque capability was also tested, and the static strength capability of the gears was 7x the maximum operating condition. Additional proof-of-concept tests are in progress using a higher oil temperature, and a loss-of-oil test is planned. The success of Phase I led to a Phase II program to develop, fabricate, and optimize full-scale gears, specifically Bull Gears. The design of these Bull Gears will be refined using topology optimization, and the full-scale Bull Gears will be tested in a full-scale gear rig. The testing will quantify benefits of weight savings, as well as noise and vibration reduction. The expectation is that vibration and noise will be reduced through the introduction of composite material in the vibration transmission path between the contacting gear teeth and the shaft-and-bearing system.

Protons Offer Reduced Normal-Tissue Exposure for Patients Receiving Postoperative Radiotherapy for Resected Pancreatic Head Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nichols, Romaine C., E-mail: rnichols@floridaproton.org; Huh, Soon N.; Prado, Karl L.

2012-05-01

Purpose: To determine the potential role for adjuvant proton-based radiotherapy (PT) for resected pancreatic head cancer. Methods and Materials: Between June 2008 and November 2008, 8 consecutive patients with resected pancreatic head cancers underwent optimized intensity-modulated radiotherapy (IMRT) treatment planning. IMRT plans used between 10 and 18 fields and delivered 45 Gy to the initial planning target volume (PTV) and a 5.4 Gy boost to a reduced PTV. PTVs were defined according to the Radiation Therapy Oncology Group 9704 radiotherapy guidelines. Ninety-five percent of PTVs received 100% of the target dose and 100% of the PTVs received 95% of themore » target dose. Normal tissue constraints were as follows: right kidney V18 Gy to <70%; left kidney V18 Gy to <30%; small bowel/stomach V20 Gy to <50%, V45 Gy to <15%, V50 Gy to <10%, and V54 Gy to <5%; liver V30 Gy to <60%; and spinal cord maximum to 46 Gy. Optimized two- to three-field three-dimensional conformal proton plans were retrospectively generated on the same patients. The team generating the proton plans was blinded to the dose distributions achieved by the IMRT plans. The IMRT and proton plans were then compared. A Wilcoxon paired t-test was performed to compare various dosimetric points between the two plans for each patient. Results: All proton plans met all normal tissue constraints and were isoeffective with the corresponding IMRT plans in terms of PTV coverage. The proton plans offered significantly reduced normal-tissue exposure over the IMRT plans with respect to the following: median small bowel V20 Gy, 15.4% with protons versus 47.0% with IMRT (p = 0.0156); median gastric V20 Gy, 2.3% with protons versus 20.0% with IMRT (p = 0.0313); and median right kidney V18 Gy, 27.3% with protons versus 50.5% with IMRT (p = 0.0156). Conclusions: By reducing small bowel and stomach exposure, protons have the potential to reduce the acute and late toxicities of postoperative chemoradiation in this setting.« less

Protons offer reduced normal-tissue exposure for patients receiving postoperative radiotherapy for resected pancreatic head cancer.

PubMed

Nichols, Romaine C; Huh, Soon N; Prado, Karl L; Yi, Byong Y; Sharma, Navesh K; Ho, Meng W; Hoppe, Bradford S; Mendenhall, Nancy P; Li, Zuofeng; Regine, William F

2012-05-01

To determine the potential role for adjuvant proton-based radiotherapy (PT) for resected pancreatic head cancer. Between June 2008 and November 2008, 8 consecutive patients with resected pancreatic head cancers underwent optimized intensity-modulated radiotherapy (IMRT) treatment planning. IMRT plans used between 10 and 18 fields and delivered 45 Gy to the initial planning target volume (PTV) and a 5.4 Gy boost to a reduced PTV. PTVs were defined according to the Radiation Therapy Oncology Group 9704 radiotherapy guidelines. Ninety-five percent of PTVs received 100% of the target dose and 100% of the PTVs received 95% of the target dose. Normal tissue constraints were as follows: right kidney V18 Gy to <70%; left kidney V18 Gy to <30%; small bowel/stomach V20 Gy to <50%, V45 Gy to <15%, V50 Gy to <10%, and V54 Gy to <5%; liver V30 Gy to <60%; and spinal cord maximum to 46 Gy. Optimized two- to three-field three-dimensional conformal proton plans were retrospectively generated on the same patients. The team generating the proton plans was blinded to the dose distributions achieved by the IMRT plans. The IMRT and proton plans were then compared. A Wilcoxon paired t-test was performed to compare various dosimetric points between the two plans for each patient. All proton plans met all normal tissue constraints and were isoeffective with the corresponding IMRT plans in terms of PTV coverage. The proton plans offered significantly reduced normal-tissue exposure over the IMRT plans with respect to the following: median small bowel V20 Gy, 15.4% with protons versus 47.0% with IMRT (p = 0.0156); median gastric V20 Gy, 2.3% with protons versus 20.0% with IMRT (p = 0.0313); and median right kidney V18 Gy, 27.3% with protons versus 50.5% with IMRT (p = 0.0156). By reducing small bowel and stomach exposure, protons have the potential to reduce the acute and late toxicities of postoperative chemoradiation in this setting. Copyright © 2012 Elsevier Inc. All rights reserved.

Strategic Air Traffic Planning Using Eulerian Route Based Modeling and Optimization

NASA Astrophysics Data System (ADS)

Bombelli, Alessandro

Due to a soaring air travel growth in the last decades, air traffic management has become increasingly challenging. As a consequence, planning tools are being devised to help human decision-makers achieve a better management of air traffic. Planning tools are divided into two categories, strategic and tactical. Strategic planning generally addresses a larger planning domain and is performed days to hours in advance. Tactical planning is more localized and is performed hours to minutes in advance. An aggregate route model for strategic air traffic flow management is presented. It is an Eulerian model, describing the flow between cells of unidirectional point-to-point routes. Aggregate routes are created from flight trajectory data based on similarity measures. Spatial similarity is determined using the Frechet distance. The aggregate routes approximate actual well-traveled traffic patterns. By specifying the model resolution, an appropriate balance between model accuracy and model dimension can be achieved. For a particular planning horizon, during which weather is expected to restrict the flow, a procedure for designing airborne reroutes and augmenting the traffic flow model is developed. The dynamics of the traffic flow on the resulting network take the form of a discrete-time, linear time-invariant system. The traffic flow controls are ground holding, pre-departure rerouting and airborne rerouting. Strategic planning--determining how the controls should be used to modify the future traffic flow when local capacity violations are anticipated--is posed as an integer programming problem of minimizing a weighted sum of flight delays subject to control and capacity constraints. Several tests indicate the effectiveness of the modeling and strategic planning approach. In the final, most challenging, test, strategic planning is demonstrated for the six western-most Centers of the 22-Center national airspace. The planning time horizon is four hours long, and there is weather predicted that causes significant delays to the scheduled flights. Airborne reroute options are computed and added to the route model, and it is shown that the predicted delays can be significantly reduced. The test results also indicate the computational feasibility of the approach for a planning problem of this size.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tiwari, P; Chen, Y; Hong, L

2015-06-15

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, whilemore » 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.« less

Verification of Dosimetric Commissioning Accuracy of Intensity Modulated Radiation Therapy and Volumetric Modulated Arc Therapy Delivery using Task Group-119 Guidelines.

PubMed

Kaviarasu, Karunakaran; Nambi Raj, N Arunai; Hamid, Misba; Giri Babu, A Ananda; Sreenivas, Lingampally; Murthy, Kammari Krishna

2017-01-01

The purpose of this study is to verify the accuracy of the commissioning of intensity-modulated radiation therapy (IMRT) and volumetric-modulated arc therapy (VMAT) based on the recommendation of the American Association of Physicists in Medicine Task Group 119 (TG-119). TG-119 proposes a set of clinical test cases to verify the accuracy of IMRT planning and delivery system. For these test cases, we generated two sets of treatment plans, the first plan using 7-9 IMRT fields and a second plan utilizing two-arc VMAT technique for both 6 MV and 15 MV photon beams. The template plans of TG-119 were optimized and calculated by Varian Eclipse Treatment Planning System (version 13.5). Dose prescription and planning objectives were set according to the TG-119 goals. The point dose (mean dose to the contoured chamber volume) at the specified positions/locations was measured using compact (CC-13) ion chamber. The composite planar dose was measured with IMatriXX Evaluation 2D array with OmniPro IMRT Software (version 1.7b). The per-field relative gamma was measured using electronic portal imaging device in a way similar to the routine pretreatment patient-specific quality assurance. Our planning results are compared with the TG-119 data. Point dose and fluence comparison data where within the acceptable confident limit. From the obtained data in this study, we conclude that the commissioning of IMRT and VMAT delivery were found within the limits of TG-119.

Verification of Dosimetric Commissioning Accuracy of Intensity Modulated Radiation Therapy and Volumetric Modulated Arc Therapy Delivery using Task Group-119 Guidelines

PubMed Central

Kaviarasu, Karunakaran; Nambi Raj, N. Arunai; Hamid, Misba; Giri Babu, A. Ananda; Sreenivas, Lingampally; Murthy, Kammari Krishna

2017-01-01

Aim: The purpose of this study is to verify the accuracy of the commissioning of intensity-modulated radiation therapy (IMRT) and volumetric-modulated arc therapy (VMAT) based on the recommendation of the American Association of Physicists in Medicine Task Group 119 (TG-119). Materials and Methods: TG-119 proposes a set of clinical test cases to verify the accuracy of IMRT planning and delivery system. For these test cases, we generated two sets of treatment plans, the first plan using 7–9 IMRT fields and a second plan utilizing two-arc VMAT technique for both 6 MV and 15 MV photon beams. The template plans of TG-119 were optimized and calculated by Varian Eclipse Treatment Planning System (version 13.5). Dose prescription and planning objectives were set according to the TG-119 goals. The point dose (mean dose to the contoured chamber volume) at the specified positions/locations was measured using compact (CC-13) ion chamber. The composite planar dose was measured with IMatriXX Evaluation 2D array with OmniPro IMRT Software (version 1.7b). The per-field relative gamma was measured using electronic portal imaging device in a way similar to the routine pretreatment patient-specific quality assurance. Results: Our planning results are compared with the TG-119 data. Point dose and fluence comparison data where within the acceptable confident limit. Conclusion: From the obtained data in this study, we conclude that the commissioning of IMRT and VMAT delivery were found within the limits of TG-119. PMID:29296041

HURON (HUman and Robotic Optimization Network) Multi-Agent Temporal Activity Planner/Scheduler

NASA Technical Reports Server (NTRS)

Hua, Hook; Mrozinski, Joseph J.; Elfes, Alberto; Adumitroaie, Virgil; Shelton, Kacie E.; Smith, Jeffrey H.; Lincoln, William P.; Weisbin, Charles R.

2012-01-01

HURON solves the problem of how to optimize a plan and schedule for assigning multiple agents to a temporal sequence of actions (e.g., science tasks). Developed as a generic planning and scheduling tool, HURON has been used to optimize space mission surface operations. The tool has also been used to analyze lunar architectures for a variety of surface operational scenarios in order to maximize return on investment and productivity. These scenarios include numerous science activities performed by a diverse set of agents: humans, teleoperated rovers, and autonomous rovers. Once given a set of agents, activities, resources, resource constraints, temporal constraints, and de pendencies, HURON computes an optimal schedule that meets a specified goal (e.g., maximum productivity or minimum time), subject to the constraints. HURON performs planning and scheduling optimization as a graph search in state-space with forward progression. Each node in the graph contains a state instance. Starting with the initial node, a graph is automatically constructed with new successive nodes of each new state to explore. The optimization uses a set of pre-conditions and post-conditions to create the children states. The Python language was adopted to not only enable more agile development, but to also allow the domain experts to easily define their optimization models. A graphical user interface was also developed to facilitate real-time search information feedback and interaction by the operator in the search optimization process. The HURON package has many potential uses in the fields of Operations Research and Management Science where this technology applies to many commercial domains requiring optimization to reduce costs. For example, optimizing a fleet of transportation truck routes, aircraft flight scheduling, and other route-planning scenarios involving multiple agent task optimization would all benefit by using HURON.

Optimization of Deep Drilling Performance - Development and Benchmark Testing of Advanced Diamond Product Drill Bits & HP/HT Fluids to Significantly Improve Rates of Penetration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alan Black; Arnis Judzis

2005-09-30

This document details the progress to date on the OPTIMIZATION OF DEEP DRILLING PERFORMANCE--DEVELOPMENT AND BENCHMARK TESTING OF ADVANCED DIAMOND PRODUCT DRILL BITS AND HP/HT FLUIDS TO SIGNIFICANTLY IMPROVE RATES OF PENETRATION contract for the year starting October 2004 through September 2005. The industry cost shared program aims to benchmark drilling rates of penetration in selected simulated deep formations and to significantly improve ROP through a team development of aggressive diamond product drill bit--fluid system technologies. Overall the objectives are as follows: Phase 1--Benchmark ''best in class'' diamond and other product drilling bits and fluids and develop concepts for amore » next level of deep drilling performance; Phase 2--Develop advanced smart bit-fluid prototypes and test at large scale; and Phase 3--Field trial smart bit--fluid concepts, modify as necessary and commercialize products. As of report date, TerraTek has concluded all Phase 1 testing and is planning Phase 2 development.« less

Mission Operations Planning with Preferences: An Empirical Study

NASA Technical Reports Server (NTRS)

Bresina, John L.; Khatib, Lina; McGann, Conor

2006-01-01

This paper presents an empirical study of some nonexhaustive approaches to optimizing preferences within the context of constraint-based, mixed-initiative planning for mission operations. This work is motivated by the experience of deploying and operating the MAPGEN (Mixed-initiative Activity Plan GENerator) system for the Mars Exploration Rover Mission. Responsiveness to the user is one of the important requirements for MAPGEN, hence, the additional computation time needed to optimize preferences must be kept within reasonabble bounds. This was the primary motivation for studying non-exhaustive optimization approaches. The specific goals of rhe empirical study are to assess the impact on solution quality of two greedy heuristics used in MAPGEN and to assess the improvement gained by applying a linear programming optimization technique to the final solution.

Solving complex maintenance planning optimization problems using stochastic simulation and multi-criteria fuzzy decision making

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tahvili, Sahar; Österberg, Jonas; Silvestrov, Sergei

One of the most important factors in the operations of many cooperations today is to maximize profit and one important tool to that effect is the optimization of maintenance activities. Maintenance activities is at the largest level divided into two major areas, corrective maintenance (CM) and preventive maintenance (PM). When optimizing maintenance activities, by a maintenance plan or policy, we seek to find the best activities to perform at each point in time, be it PM or CM. We explore the use of stochastic simulation, genetic algorithms and other tools for solving complex maintenance planning optimization problems in terms ofmore » a suggested framework model based on discrete event simulation.« less

A new multi-objective optimization model for preventive maintenance and replacement scheduling of multi-component systems

NASA Astrophysics Data System (ADS)

Moghaddam, Kamran S.; Usher, John S.

2011-07-01

In this article, a new multi-objective optimization model is developed to determine the optimal preventive maintenance and replacement schedules in a repairable and maintainable multi-component system. In this model, the planning horizon is divided into discrete and equally-sized periods in which three possible actions must be planned for each component, namely maintenance, replacement, or do nothing. The objective is to determine a plan of actions for each component in the system while minimizing the total cost and maximizing overall system reliability simultaneously over the planning horizon. Because of the complexity, combinatorial and highly nonlinear structure of the mathematical model, two metaheuristic solution methods, generational genetic algorithm, and a simulated annealing are applied to tackle the problem. The Pareto optimal solutions that provide good tradeoffs between the total cost and the overall reliability of the system can be obtained by the solution approach. Such a modeling approach should be useful for maintenance planners and engineers tasked with the problem of developing recommended maintenance plans for complex systems of components.

Stochastic Evolutionary Algorithms for Planning Robot Paths

NASA Technical Reports Server (NTRS)

Fink, Wolfgang; Aghazarian, Hrand; Huntsberger, Terrance; Terrile, Richard

2006-01-01

A computer program implements stochastic evolutionary algorithms for planning and optimizing collision-free paths for robots and their jointed limbs. Stochastic evolutionary algorithms can be made to produce acceptably close approximations to exact, optimal solutions for path-planning problems while often demanding much less computation than do exhaustive-search and deterministic inverse-kinematics algorithms that have been used previously for this purpose. Hence, the present software is better suited for application aboard robots having limited computing capabilities (see figure). The stochastic aspect lies in the use of simulated annealing to (1) prevent trapping of an optimization algorithm in local minima of an energy-like error measure by which the fitness of a trial solution is evaluated while (2) ensuring that the entire multidimensional configuration and parameter space of the path-planning problem is sampled efficiently with respect to both robot joint angles and computation time. Simulated annealing is an established technique for avoiding local minima in multidimensional optimization problems, but has not, until now, been applied to planning collision-free robot paths by use of low-power computers.

Beam angle optimization for intensity-modulated radiation therapy using a guided pattern search method

NASA Astrophysics Data System (ADS)

Rocha, Humberto; Dias, Joana M.; Ferreira, Brígida C.; Lopes, Maria C.

2013-05-01

Generally, the inverse planning of radiation therapy consists mainly of the fluence optimization. The beam angle optimization (BAO) in intensity-modulated radiation therapy (IMRT) consists of selecting appropriate radiation incidence directions and may influence the quality of the IMRT plans, both to enhance better organ sparing and to improve tumor coverage. However, in clinical practice, most of the time, beam directions continue to be manually selected by the treatment planner without objective and rigorous criteria. The goal of this paper is to introduce a novel approach that uses beam’s-eye-view dose ray tracing metrics within a pattern search method framework in the optimization of the highly non-convex BAO problem. Pattern search methods are derivative-free optimization methods that require a few function evaluations to progress and converge and have the ability to better avoid local entrapment. The pattern search method framework is composed of a search step and a poll step at each iteration. The poll step performs a local search in a mesh neighborhood and ensures the convergence to a local minimizer or stationary point. The search step provides the flexibility for a global search since it allows searches away from the neighborhood of the current iterate. Beam’s-eye-view dose metrics assign a score to each radiation beam direction and can be used within the pattern search framework furnishing a priori knowledge of the problem so that directions with larger dosimetric scores are tested first. A set of clinical cases of head-and-neck tumors treated at the Portuguese Institute of Oncology of Coimbra is used to discuss the potential of this approach in the optimization of the BAO problem.

Optimizing nursing human resource planning in British Columbia.

PubMed

Lavieri, Mariel S; Puterman, Martin L

2009-06-01

This paper describes a linear programming hierarchical planning model that determines the optimal number of nurses to train, promote to management and recruit over a 20 year planning horizon to achieve specified workforce levels. Age dynamics and attrition rates of the nursing workforce are key model components. The model was developed to help policy makers plan a sustainable nursing workforce for British Columbia, Canada. An easy to use interface and considerable flexibility makes it ideal for scenario and "What-If?" analyses.

Virtual Factory Framework for Supporting Production Planning and Control.

PubMed

Kibira, Deogratias; Shao, Guodong

2017-01-01

Developing optimal production plans for smart manufacturing systems is challenging because shop floor events change dynamically. A virtual factory incorporating engineering tools, simulation, and optimization generates and communicates performance data to guide wise decision making for different control levels. This paper describes such a platform specifically for production planning. We also discuss verification and validation of the constituent models. A case study of a machine shop is used to demonstrate data generation for production planning in a virtual factory.

SU-E-T-587: Optimal Volumetric Modulated Arc Radiotherapy Treatment Planning Technique for Multiple Brain Metastases with Increasing Number of Arcs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Keeling, V; Hossain, S; Hildebrand, K

Purpose: To show improvements in dose conformity and normal brain tissue sparing using an optimal planning technique (OPT) against clinically acceptable planning technique (CAP) in the treatment of multiple brain metastases. Methods: A standardized international benchmark case with12 intracranial tumors was planned using two different VMAT optimization methods. Plans were split into four groups with 3, 6, 9, and 12 targets each planned with 3, 5, and 7 arcs using Eclipse TPS. The beam geometries were 1 full coplanar and half non-coplanar arcs. A prescription dose of 20Gy was used for all targets. The following optimization criteria was used (OPTmore » vs. CAP): (No upper limit vs.108% upper limit for target volume), (priority 140–150 vs. 75–85 for normal-brain-tissue), and (selection of automatic sparing Normal-Tissue-Objective (NTO) vs. Manual NTO). Both had priority 50 to critical structures such as brainstem and optic-chiasm, and both had an NTO priority 150. Normal-brain-tissue doses along with Paddick Conformity Index (PCI) were evaluated. Results: In all cases PCI was higher for OPT plans. The average PCI (OPT,CAP) for all targets was (0.81,0.64), (0.81,0.63), (0.79,0.57), and (0.72,0.55) for 3, 6, 9, and 12 target plans respectively. The percent decrease in normal brain tissue volume (OPT/CAP*100) achieved by OPT plans was (reported as follows: V4, V8, V12, V16, V20) (184, 343, 350, 294, 371%), (192, 417, 380, 299, 360%), and (235, 390, 299, 281, 502%) for the 3, 5, 7 arc 12 target plans, respectively. The maximum brainstem dose decreased for the OPT plan by 4.93, 4.89, and 5.30 Gy for 3, 5, 7 arc 12 target plans, respectively. Conclusion: Substantial increases in PCI, critical structure sparing, and decreases in normal brain tissue dose were achieved by eliminating upper limits from optimization, using automatic sparing of normal tissue function with high priority, and a high priority to normal brain tissue.« less

An efficient inverse radiotherapy planning method for VMAT using quadratic programming optimization.

PubMed

Hoegele, W; Loeschel, R; Merkle, N; Zygmanski, P

2012-01-01

The purpose of this study is to investigate the feasibility of an inverse planning optimization approach for the Volumetric Modulated Arc Therapy (VMAT) based on quadratic programming and the projection method. The performance of this method is evaluated against a reference commercial planning system (eclipse(TM) for rapidarc(TM)) for clinically relevant cases. The inverse problem is posed in terms of a linear combination of basis functions representing arclet dose contributions and their respective linear coefficients as degrees of freedom. MLC motion is decomposed into basic motion patterns in an intuitive manner leading to a system of equations with a relatively small number of equations and unknowns. These equations are solved using quadratic programming under certain limiting physical conditions for the solution, such as the avoidance of negative dose during optimization and Monitor Unit reduction. The modeling by the projection method assures a unique treatment plan with beneficial properties, such as the explicit relation between organ weightings and the final dose distribution. Clinical cases studied include prostate and spine treatments. The optimized plans are evaluated by comparing isodose lines, DVH profiles for target and normal organs, and Monitor Units to those obtained by the clinical treatment planning system eclipse(TM). The resulting dose distributions for a prostate (with rectum and bladder as organs at risk), and for a spine case (with kidneys, liver, lung and heart as organs at risk) are presented. Overall, the results indicate that similar plan qualities for quadratic programming (QP) and rapidarc(TM) could be achieved at significantly more efficient computational and planning effort using QP. Additionally, results for the quasimodo phantom [Bohsung et al., "IMRT treatment planning: A comparative inter-system and inter-centre planning exercise of the estro quasimodo group," Radiother. Oncol. 76(3), 354-361 (2005)] are presented as an example for an extreme concave case. Quadratic programming is an alternative approach for inverse planning which generates clinically satisfying plans in comparison to the clinical system and constitutes an efficient optimization process characterized by uniqueness and reproducibility of the solution.

A stochastic multi-agent optimization model for energy infrastructure planning under uncertainty and competition.

DOT National Transportation Integrated Search

2017-07-04

This paper presents a stochastic multi-agent optimization model that supports energy infrastruc- : ture planning under uncertainty. The interdependence between dierent decision entities in the : system is captured in an energy supply chain network, w...

Manpower Planning Models. 5. Optimization Models

DTIC Science & Technology

1975-10-01

aide 11 neceaaary and Identity by block number) Manpower Planning \\ \\ X Modelling Optimization 20. ABS emry and Identity by block number...notation resulting from the previous maximum M. We exploit the probabilistic interpretation of the flow process whenever it eases the exposi - tion

Automatic treatment planning facilitates fast generation of high-quality treatment plans for esophageal cancer.

PubMed

Hansen, Christian Rønn; Nielsen, Morten; Bertelsen, Anders Smedegaard; Hazell, Irene; Holtved, Eva; Zukauskaite, Ruta; Bjerregaard, Jon Kroll; Brink, Carsten; Bernchou, Uffe

2017-11-01

The quality of radiotherapy planning has improved substantially in the last decade with the introduction of intensity modulated radiotherapy. The purpose of this study was to analyze the plan quality and efficacy of automatically (AU) generated VMAT plans for inoperable esophageal cancer patients. Thirty-two consecutive inoperable patients with esophageal cancer originally treated with manually (MA) generated volumetric modulated arc therapy (VMAT) plans were retrospectively replanned using an auto-planning engine. All plans were optimized with one full 6MV VMAT arc giving 60 Gy to the primary target and 50 Gy to the elective target. The planning techniques were blinded before clinical evaluation by three specialized oncologists. To supplement the clinical evaluation, the optimization time for the AU plan was recorded along with DVH parameters for all plans. Upon clinical evaluation, the AU plan was preferred for 31/32 patients, and for one patient, there was no difference in the plans. In terms of DVH parameters, similar target coverage was obtained between the two planning methods. The mean dose for the spinal cord increased by 1.8 Gy using AU (p = .002), whereas the mean lung dose decreased by 1.9 Gy (p < .001). The AU plans were more modulated as seen by the increase of 12% in mean MUs (p = .001). The median optimization time for AU plans was 117 min. The AU plans were in general preferred and showed a lower mean dose to the lungs. The automation of the planning process generated esophageal cancer treatment plans quickly and with high quality.

A novel software and conceptual design of the hardware platform for intensity modulated radiation therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nguyen, Dan; Ruan, Dan; O’Connor, Daniel

Purpose: To deliver high quality intensity modulated radiotherapy (IMRT) using a novel generalized sparse orthogonal collimators (SOCs), the authors introduce a novel direct aperture optimization (DAO) approach based on discrete rectangular representation. Methods: A total of seven patients—two glioblastoma multiforme, three head & neck (including one with three prescription doses), and two lung—were included. 20 noncoplanar beams were selected using a column generation and pricing optimization method. The SOC is a generalized conventional orthogonal collimators with N leaves in each collimator bank, where N = 1, 2, or 4. SOC degenerates to conventional jaws when N = 1. For SOC-basedmore » IMRT, rectangular aperture optimization (RAO) was performed to optimize the fluence maps using rectangular representation, producing fluence maps that can be directly converted into a set of deliverable rectangular apertures. In order to optimize the dose distribution and minimize the number of apertures used, the overall objective was formulated to incorporate an L2 penalty reflecting the difference between the prescription and the projected doses, and an L1 sparsity regularization term to encourage a low number of nonzero rectangular basis coefficients. The optimization problem was solved using the Chambolle–Pock algorithm, a first-order primal–dual algorithm. Performance of RAO was compared to conventional two-step IMRT optimization including fluence map optimization and direct stratification for multileaf collimator (MLC) segmentation (DMS) using the same number of segments. For the RAO plans, segment travel time for SOC delivery was evaluated for the N = 1, N = 2, and N = 4 SOC designs to characterize the improvement in delivery efficiency as a function of N. Results: Comparable PTV dose homogeneity and coverage were observed between the RAO and the DMS plans. The RAO plans were slightly superior to the DMS plans in sparing critical structures. On average, the maximum and mean critical organ doses were reduced by 1.94% and 1.44% of the prescription dose. The average number of delivery segments was 12.68 segments per beam for both the RAO and DMS plans. The N = 2 and N = 4 SOC designs were, on average, 1.56 and 1.80 times more efficient than the N = 1 SOC design to deliver. The mean aperture size produced by the RAO plans was 3.9 times larger than that of the DMS plans. Conclusions: The DAO and dose domain optimization approach enabled high quality IMRT plans using a low-complexity collimator setup. The dosimetric quality is comparable or slightly superior to conventional MLC-based IMRT plans using the same number of delivery segments. The SOC IMRT delivery efficiency can be significantly improved by increasing the leaf numbers, but the number is still significantly lower than the number of leaves in a typical MLC.« less

A novel software and conceptual design of the hardware platform for intensity modulated radiation therapy.

PubMed

Nguyen, Dan; Ruan, Dan; O'Connor, Daniel; Woods, Kaley; Low, Daniel A; Boucher, Salime; Sheng, Ke

2016-02-01

To deliver high quality intensity modulated radiotherapy (IMRT) using a novel generalized sparse orthogonal collimators (SOCs), the authors introduce a novel direct aperture optimization (DAO) approach based on discrete rectangular representation. A total of seven patients-two glioblastoma multiforme, three head & neck (including one with three prescription doses), and two lung-were included. 20 noncoplanar beams were selected using a column generation and pricing optimization method. The SOC is a generalized conventional orthogonal collimators with N leaves in each collimator bank, where N = 1, 2, or 4. SOC degenerates to conventional jaws when N = 1. For SOC-based IMRT, rectangular aperture optimization (RAO) was performed to optimize the fluence maps using rectangular representation, producing fluence maps that can be directly converted into a set of deliverable rectangular apertures. In order to optimize the dose distribution and minimize the number of apertures used, the overall objective was formulated to incorporate an L2 penalty reflecting the difference between the prescription and the projected doses, and an L1 sparsity regularization term to encourage a low number of nonzero rectangular basis coefficients. The optimization problem was solved using the Chambolle-Pock algorithm, a first-order primal-dual algorithm. Performance of RAO was compared to conventional two-step IMRT optimization including fluence map optimization and direct stratification for multileaf collimator (MLC) segmentation (DMS) using the same number of segments. For the RAO plans, segment travel time for SOC delivery was evaluated for the N = 1, N = 2, and N = 4 SOC designs to characterize the improvement in delivery efficiency as a function of N. Comparable PTV dose homogeneity and coverage were observed between the RAO and the DMS plans. The RAO plans were slightly superior to the DMS plans in sparing critical structures. On average, the maximum and mean critical organ doses were reduced by 1.94% and 1.44% of the prescription dose. The average number of delivery segments was 12.68 segments per beam for both the RAO and DMS plans. The N = 2 and N = 4 SOC designs were, on average, 1.56 and 1.80 times more efficient than the N = 1 SOC design to deliver. The mean aperture size produced by the RAO plans was 3.9 times larger than that of the DMS plans. The DAO and dose domain optimization approach enabled high quality IMRT plans using a low-complexity collimator setup. The dosimetric quality is comparable or slightly superior to conventional MLC-based IMRT plans using the same number of delivery segments. The SOC IMRT delivery efficiency can be significantly improved by increasing the leaf numbers, but the number is still significantly lower than the number of leaves in a typical MLC.

Assessing the Dosimetric Accuracy of Magnetic Resonance-Generated Synthetic CT Images for Focal Brain VMAT Radiation Therapy.

PubMed

Paradis, Eric; Cao, Yue; Lawrence, Theodore S; Tsien, Christina; Feng, Mary; Vineberg, Karen; Balter, James M

2015-12-01

The purpose of this study was to assess the dosimetric accuracy of synthetic CT (MRCT) volumes generated from magnetic resonance imaging (MRI) data for focal brain radiation therapy. A study was conducted in 12 patients with gliomas who underwent both MR and CT imaging as part of their simulation for external beam treatment planning. MRCT volumes were generated from MR images. Patients' clinical treatment planning directives were used to create 12 individual volumetric modulated arc therapy (VMAT) plans, which were then optimized 10 times on each of their respective CT and MRCT-derived electron density maps. Dose metrics derived from optimization criteria, as well as monitor units and gamma analyses, were evaluated to quantify differences between the imaging modalities. Mean differences between planning target volume (PTV) doses on MRCT and CT plans across all patients were 0.0% (range: -0.1 to 0.2%) for D(95%); 0.0% (-0.7 to 0.6%) for D(5%); and -0.2% (-1.0 to 0.2%) for D(max). MRCT plans showed no significant changes in monitor units (-0.4%) compared to CT plans. Organs at risk (OARs) had average D(max) differences of 0.0 Gy (-2.2 to 1.9 Gy) over 85 structures across all 12 patients, with no significant differences when calculated doses approached planning constraints. Focal brain VMAT plans optimized on MRCT images show excellent dosimetric agreement with standard CT-optimized plans. PTVs show equivalent coverage, and OARs do not show any overdose. These results indicate that MRI-derived synthetic CT volumes can be used to support treatment planning of most patients treated for intracranial lesions. Copyright © 2015 Elsevier Inc. All rights reserved.

Assessing the Dosimetric Accuracy of Magnetic Resonance-Generated Synthetic CT Images for Focal Brain VMAT Radiation Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Paradis, Eric, E-mail: eparadis@umich.edu; Cao, Yue; Department of Radiology, University of Michigan Hospital and Health Systems, Ann Arbor, Michigan

2015-12-01

Purpose: The purpose of this study was to assess the dosimetric accuracy of synthetic CT (MRCT) volumes generated from magnetic resonance imaging (MRI) data for focal brain radiation therapy. Methods and Materials: A study was conducted in 12 patients with gliomas who underwent both MR and CT imaging as part of their simulation for external beam treatment planning. MRCT volumes were generated from MR images. Patients' clinical treatment planning directives were used to create 12 individual volumetric modulated arc therapy (VMAT) plans, which were then optimized 10 times on each of their respective CT and MRCT-derived electron density maps. Dosemore » metrics derived from optimization criteria, as well as monitor units and gamma analyses, were evaluated to quantify differences between the imaging modalities. Results: Mean differences between planning target volume (PTV) doses on MRCT and CT plans across all patients were 0.0% (range: −0.1 to 0.2%) for D{sub 95%}; 0.0% (−0.7 to 0.6%) for D{sub 5%}; and −0.2% (−1.0 to 0.2%) for D{sub max}. MRCT plans showed no significant changes in monitor units (−0.4%) compared to CT plans. Organs at risk (OARs) had average D{sub max} differences of 0.0 Gy (−2.2 to 1.9 Gy) over 85 structures across all 12 patients, with no significant differences when calculated doses approached planning constraints. Conclusions: Focal brain VMAT plans optimized on MRCT images show excellent dosimetric agreement with standard CT-optimized plans. PTVs show equivalent coverage, and OARs do not show any overdose. These results indicate that MRI-derived synthetic CT volumes can be used to support treatment planning of most patients treated for intracranial lesions.« less

Validation of the relative insensitivity of volumetric-modulated arc therapy (VMAT) plan quality to gantry space resolution

PubMed Central

Cora, Stefania; Khan, Ehsan Ullah

2017-01-01

Abstract Volumetric-modulated arc therapy (VMAT) is an efficient form of radiotherapy used to deliver intensity-modulated radiotherapy beams. The aim of this study was to investigate the relative insensitivity of VMAT plan quality to gantry angle spacing (GS). Most previous VMAT planning and dosimetric work for GS resolution has been conducted for single arc VMAT. In this work, a quantitative comparison of dose–volume indices (DIs) was made for partial-, single- and double-arc VMAT plans optimized at 2°, 3° and 4° GS, representing a large variation in deliverable multileaf collimator segments. VMAT plans of six prostate cancer and six head-and-neck cancer patients were simulated for an Elekta SynergyS® Linac (Elekta Ltd, Crawley, UK), using the SmartArc™ module of Pinnacle³ TPS, (version 9.2, Philips Healthcare). All optimization techniques generated clinically acceptable VMAT plans, except for the single-arc for the head-and-neck cancer patients. Plan quality was assessed by comparing the DIs for the planning target volume, organs at risk and normal tissue. A GS of 2°, with finest resolution and consequently highest intensity modulation, was considered to be the reference, and this was compared with GS 3° and 4°. The differences between the majority of reference DIs and compared DIs were <2%. The metrics, such as treatment plan optimization time and pretreatment (phantom) dosimetric calculation time, supported the use of a GS of 4°. The ArcCHECK™ phantom–measured dosimetric agreement verifications resulted in a >95.0% passing rate, using the criteria for γ (3%, 3 mm). In conclusion, a GS of 4° is an optimal choice for minimal usage of planning resources without compromise of plan quality. PMID:27974507

BSA Delta Qualification 2, volume 3, book 1

NASA Technical Reports Server (NTRS)

1994-01-01

This report, presented in three volumes, provides the results of a two-motor Delta Qualification 2 program conducted in 1993 to certify the following enhancements for incorporation into booster separation motor (BSM) flight hardware: vulcanized-in-place nozzle aft closure insulation; new iso-static ATJ bulk graphite throat insert material; adhesive EA 9394 for bonding the nozzle throat, igniter grain rod/centering insert/igniter case; deletion of the igniter adapter insulator ring; deletion of the igniter adapter/igniter case interface RTV; and deletion of Loctite from igniter retainer plate threads. The enhancements above directly resulted from (1) the BSM total quality management (TQM) team initiatives to enhance the BSM producibility, and (2) the necessity to qualify new throat insert and adhesive systems to replace existing materials that will not be available. Testing was completed at both the component and motor levels. Component testing was accomplished to screen candidate materials (e.g., throat materials, adhesive systems) and to optimize processes (e.g., aft closure insulator vulcanization approach) prior to their incorporation into the test motors. Motor tests -- consisting of two motors, randomly selected by USBI's on-site quality personnel from production lot AAY, which were modified to accept the enhancements -- were completed to provide the final qualification of the enhancements for incorporation into flight hardware. Volume 3 book 1 provides supporting documentation to the analyses and plans of testing the two Delta Qualification units including thermal cycling planning/data acceptance records, environmental test procedures and pretest temperature conditioning history, Delta Qualification test plan, and specification SE0837 -- mix acceptance test specification.

Statistical considerations in monitoring birds over large areas

USGS Publications Warehouse

Johnson, D.H.

2000-01-01

The proper design of a monitoring effort depends primarily on the objectives desired, constrained by the resources available to conduct the work. Typically, managers have numerous objectives, such as determining abundance of the species, detecting changes in population size, evaluating responses to management activities, and assessing habitat associations. A design that is optimal for one objective will likely not be optimal for others. Careful consideration of the importance of the competing objectives may lead to a design that adequately addresses the priority concerns, although it may not be optimal for any individual objective. Poor design or inadequate sample sizes may result in such weak conclusions that the effort is wasted. Statistical expertise can be used at several stages, such as estimating power of certain hypothesis tests, but is perhaps most useful in fundamental considerations of describing objectives and designing sampling plans.

Renewable Energy Resources Portfolio Optimization in the Presence of Demand Response

DOE Office of Scientific and Technical Information (OSTI.GOV)

Behboodi, Sahand; Chassin, David P.; Crawford, Curran

In this paper we introduce a simple cost model of renewable integration and demand response that can be used to determine the optimal mix of generation and demand response resources. The model includes production cost, demand elasticity, uncertainty costs, capacity expansion costs, retirement and mothballing costs, and wind variability impacts to determine the hourly cost and revenue of electricity delivery. The model is tested on the 2024 planning case for British Columbia and we find that cost is minimized with about 31% renewable generation. We also find that demand responsive does not have a significant impact on cost at themore » hourly level. The results suggest that the optimal level of renewable resource is not sensitive to a carbon tax or demand elasticity, but it is highly sensitive to the renewable resource installation cost.« less

A quantitative study of IMRT delivery effects in commercial planning systems for the case of oesophagus and prostate tumours.

PubMed

Seco, J; Clark, C H; Evans, P M; Webb, S

2006-05-01

This study focuses on understanding the impact of intensity-modulated radiotherapy (IMRT) delivery effects when applied to plans generated by commercial treatment-planning systems such as Pinnacle (ADAC Laboratories Inc.) and CadPlan/Helios (Varian Medical Systems). These commercial planning systems have had several version upgrades (with improvements in the optimization algorithm), but the IMRT delivery effects have not been incorporated into the optimization process. IMRT delivery effects include head-scatter fluence from IMRT fields, transmission through leaves and the effect of the rounded shape of the leaf ends. They are usually accounted for after optimization when leaf sequencing the "optimal" fluence profiles, to derive the delivered fluence profile. The study was divided into two main parts: (a) analysing the dose distribution within the planning-target volume (PTV), produced by each of the commercial treatment-planning systems, after the delivered fluence had been renormalized to deliver the correct dose to the PTV; and (b) studying the impact of the IMRT delivery technique on the surrounding critical organs such as the spinal cord, lungs, rectum, bladder etc. The study was performed for tumours of (i) the oesophagus and (ii) the prostate and pelvic nodes. An oesophagus case was planned with the Pinnacle planning system for IMRT delivery, via multiple-static fields (MSF) and compensators, using the Elekta SL25 with a multileaf collimator (MLC) component. A prostate and pelvic nodes IMRT plan was performed with the Cadplan/Helios system for a dynamic delivery (DMLC) using the Varian 120-leaf Millennium MLC. In these commercial planning systems, since IMRT delivery effects are not included into the optimization process, fluence renormalization is required such that the median delivered PTV dose equals the initial prescribed PTV dose. In preparing the optimum fluence profile for delivery, the PTV dose has been "smeared" by the IMRT delivery techniques. In the case of the oesophagus, the critical organ, spinal cord, received a greater dose than initially planned, due to the delivery effects. The increase in the spinal cord dose is of the order of 2-3 Gy. In the case of the prostate and pelvic nodes, the IMRT delivery effects led to an increase of approximately 2 Gy in the dose delivered to the secondary PTV, the pelvic nodes. In addition to this, the small bowel, rectum and bladder received an increased dose of the order of 2-3 Gy to 50% of their total volume. IMRT delivery techniques strongly influence the delivered dose distributions for the oesophagus and prostate/pelvic nodes tumour sites and these effects are not yet accounted for in the Pinnacle and the CadPlan/Helios planning systems. Currently, they must be taken into account during the optimization stage by altering the dose limits accepted during optimization so that the final (sequenced) dose is within the constraints.

The Federal Aviation Administration Plan for Research, Engineering and Development, 1994

DTIC Science & Technology

1994-05-01

Aeronautical Data Link Communications and (COTS) runway incursion system software will Applications, and 051-130 Airport Safety be demonstrated as a... airport departure and ar- efforts rival scheduling plans that optimize daily traffic flows for long-range flights between major city- * OTFP System to...Expanded HARS planning capabilities to in- aviation dispatchers to develop optimized high clude enhanced communications software for altitude flight

A Computational/Experimental Study of Two Optimized Supersonic Transport Designs and the Reference H Baseline

NASA Technical Reports Server (NTRS)

Cliff, Susan E.; Baker, Timothy J.; Hicks, Raymond M.; Reuther, James J.

1999-01-01

Two supersonic transport configurations designed by use of non-linear aerodynamic optimization methods are compared with a linearly designed baseline configuration. One optimized configuration, designated Ames 7-04, was designed at NASA Ames Research Center using an Euler flow solver, and the other, designated Boeing W27, was designed at Boeing using a full-potential method. The two optimized configurations and the baseline were tested in the NASA Langley Unitary Plan Supersonic Wind Tunnel to evaluate the non-linear design optimization methodologies. In addition, the experimental results are compared with computational predictions for each of the three configurations from the Enter flow solver, AIRPLANE. The computational and experimental results both indicate moderate to substantial performance gains for the optimized configurations over the baseline configuration. The computed performance changes with and without diverters and nacelles were in excellent agreement with experiment for all three models. Comparisons of the computational and experimental cruise drag increments for the optimized configurations relative to the baseline show excellent agreement for the model designed by the Euler method, but poorer comparisons were found for the configuration designed by the full-potential code.

Technical Note: Dose effects of 1.5 T transverse magnetic field on tissue interfaces in MRI-guided radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Xinfeng; Prior, Phil; Chen, Guang-Pei

Purpose: The integration of MRI with a linear accelerator (MR-linac) offers great potential for high-precision delivery of radiation therapy (RT). However, the electron deflection resulting from the presence of a transverse magnetic field (TMF) can affect the dose distribution, particularly the electron return effect (ERE) at tissue interfaces. The purpose of the study is to investigate the dose effects of ERE at air-tissue and lung-tissue interfaces during intensity-modulated radiation therapy (IMRT) planning. Methods: IMRT and volumetric modulated arc therapy (VMAT) plans for representative pancreas, lung, breast, and head and neck (HN) cases were generated following commonly used clinical dose volumemore » (DV) criteria. In each case, three types of plans were generated: (1) the original plan generated without a TMF; (2) the reconstructed plan generated by recalculating the original plan with the presence of a TMF of 1.5 T (no optimization); and (3) the optimized plan generated by a full optimization with TMF = 1.5 T. These plans were compared using a variety of DV parameters, including V{sub 100%}, D{sub 95%}, DHI [dose heterogeneity index: (D{sub 20%}–D{sub 80%})/D{sub prescription}], D{sub max}, and D{sub 1cc} in OARs (organs at risk) and tissue interface. All the optimizations and calculations in this work were performed on static data. Results: The dose recalculation under TMF showed the presence of the 1.5 T TMF can slightly reduce V{sub 100%} and D{sub 95%} for PTV, with the differences being less than 4% for all but one lung case studied. The TMF results in considerable increases in D{sub max} and D{sub 1cc} on the skin in all cases, mostly between 10% and 35%. The changes in D{sub max} and D{sub 1cc} on air cavity walls are dependent upon site, geometry, and size, with changes ranging up to 15%. The VMAT plans lead to much smaller dose effects from ERE compared to fixed-beam IMRT in pancreas case. When the TMF is considered in the plan optimization, the dose effects of the TMF at tissue interfaces (e.g., air-cavity wall, lung-tissue interfaces, skin) are significantly reduced in most cases. Conclusions: The doses on tissue interfaces can be significantly changed by the presence of a TMF during MR-guided RT when the magnetic field is not included in plan optimization. These changes can be substantially reduced or even eliminated during VMAT/IMRT optimization that specifically considers the TMF, without deteriorating overall plan quality.« less

Continuous intensity map optimization (CIMO): A novel approach to leaf sequencing in step and shoot IMRT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cao Daliang; Earl, Matthew A.; Luan, Shuang

2006-04-15

A new leaf-sequencing approach has been developed that is designed to reduce the number of required beam segments for step-and-shoot intensity modulated radiation therapy (IMRT). This approach to leaf sequencing is called continuous-intensity-map-optimization (CIMO). Using a simulated annealing algorithm, CIMO seeks to minimize differences between the optimized and sequenced intensity maps. Two distinguishing features of the CIMO algorithm are (1) CIMO does not require that each optimized intensity map be clustered into discrete levels and (2) CIMO is not rule-based but rather simultaneously optimizes both the aperture shapes and weights. To test the CIMO algorithm, ten IMRT patient cases weremore » selected (four head-and-neck, two pancreas, two prostate, one brain, and one pelvis). For each case, the optimized intensity maps were extracted from the Pinnacle{sup 3} treatment planning system. The CIMO algorithm was applied, and the optimized aperture shapes and weights were loaded back into Pinnacle. A final dose calculation was performed using Pinnacle's convolution/superposition based dose calculation. On average, the CIMO algorithm provided a 54% reduction in the number of beam segments as compared with Pinnacle's leaf sequencer. The plans sequenced using the CIMO algorithm also provided improved target dose uniformity and a reduced discrepancy between the optimized and sequenced intensity maps. For ten clinical intensity maps, comparisons were performed between the CIMO algorithm and the power-of-two reduction algorithm of Xia and Verhey [Med. Phys. 25(8), 1424-1434 (1998)]. When the constraints of a Varian Millennium multileaf collimator were applied, the CIMO algorithm resulted in a 26% reduction in the number of segments. For an Elekta multileaf collimator, the CIMO algorithm resulted in a 67% reduction in the number of segments. An average leaf sequencing time of less than one minute per beam was observed.« less

A new optimization tool path planning for 3-axis end milling of free-form surfaces based on efficient machining intervals

NASA Astrophysics Data System (ADS)

Vu, Duy-Duc; Monies, Frédéric; Rubio, Walter

2018-05-01

A large number of studies, based on 3-axis end milling of free-form surfaces, seek to optimize tool path planning. Approaches try to optimize the machining time by reducing the total tool path length while respecting the criterion of the maximum scallop height. Theoretically, the tool path trajectories that remove the most material follow the directions in which the machined width is the largest. The free-form surface is often considered as a single machining area. Therefore, the optimization on the entire surface is limited. Indeed, it is difficult to define tool trajectories with optimal feed directions which generate largest machined widths. Another limiting point of previous approaches for effectively reduce machining time is the inadequate choice of the tool. Researchers use generally a spherical tool on the entire surface. However, the gains proposed by these different methods developed with these tools lead to relatively small time savings. Therefore, this study proposes a new method, using toroidal milling tools, for generating toolpaths in different regions on the machining surface. The surface is divided into several regions based on machining intervals. These intervals ensure that the effective radius of the tool, at each cutter-contact points on the surface, is always greater than the radius of the tool in an optimized feed direction. A parallel plane strategy is then used on the sub-surfaces with an optimal specific feed direction for each sub-surface. This method allows one to mill the entire surface with efficiency greater than with the use of a spherical tool. The proposed method is calculated and modeled using Maple software to find optimal regions and feed directions in each region. This new method is tested on a free-form surface. A comparison is made with a spherical cutter to show the significant gains obtained with a toroidal milling cutter. Comparisons with CAM software and experimental validations are also done. The results show the efficiency of the method.

Toward a Multi-Decadal Record of Satellite CO from MOPITT to Suomi NPP/CrIS: Overview and Initial Results

NASA Astrophysics Data System (ADS)

Francis, G. L.; Cady-Pereira, K.; Worden, H. M.; Shephard, M.; Fu, D.

2016-12-01

A prototype optimal estimation CO retrieval framework using CrIS thermal-IR spectra is being developed and undergoing initial testing and evaluation. The goal is construction of a multi- decadal climate-quality data record, consistent with MOPITT, extending into the post-EOS/Terra era, given the planned JPSS mission schedule. The EOS/MOPITT instrument has an ongoing and unprecedented record of CO retrievals since early 2000. CrIS CO offers the potential to significantly extend the MOPITT thermal-IR retrieval record, as well as providing expanded spatial coverage. We describe the prototype CrIS CO optimal estimation retrieval system. Test CO retrievals include data for the California Central Valley and the fires near Fort McMurray, Canada. We compare our results to other satellite datasets as well as available in-situ data. Directions for future work will be discussed.

Improving plan quality for prostate volumetric-modulated arc therapy.

PubMed

Wright, Katrina; Ferrari-Anderson, Janet; Barry, Tamara; Bernard, Anne; Brown, Elizabeth; Lehman, Margot; Pryor, David

2017-01-01

We critically evaluated the quality and consistency of volumetric-modulated arc therapy (VMAT) prostate planning at a single institution to quantify objective measures for plan quality and establish clear guidelines for plan evaluation and quality assurance. A retrospective analysis was conducted on 34 plans generated on the Pinnacle 3 version 9.4 and 9.8 treatment planning system to deliver 78 Gy in 39 fractions to the prostate only using VMAT. Data were collected on contoured structure volumes, overlaps and expansions, planning target volume (PTV) and organs at risk volumes and relationship, dose volume histogram, plan conformity, plan homogeneity, low-dose wash, and beam parameters. Standard descriptive statistics were used to describe the data. Despite a standardized planning protocol, we found variability was present in all steps of the planning process. Deviations from protocol contours by radiation oncologists and radiation therapists occurred in 12% and 50% of cases, respectively, and the number of optimization parameters ranged from 12 to 27 (median 17). This contributed to conflicts within the optimization process reflected by the mean composite objective value of 0.07 (range 0.01 to 0.44). Methods used to control low-intermediate dose wash were inconsistent. At the PTV rectum interface, the dose-gradient distance from the 74.1 Gy to 40 Gy isodose ranged from 0.6 cm to 2.0 cm (median 1.0 cm). Increasing collimator angle was associated with a decrease in monitor units and a single full 6 MV arc was sufficient for the majority of plans. A significant relationship was found between clinical target volume-rectum distance and rectal tolerances achieved. A linear relationship was determined between the PTV volume and volume of 40 Gy isodose. Objective values and composite objective values were useful in determining plan quality. Anatomic geometry and overlap of structures has a measurable impact on the plan quality achieved for prostate patients being treated with VMAT. By evaluating multiple planning variables, we have been able to determine important factors influencing plan quality and develop predictive models for quality metrics that have been incorporated into our new protocol and will be tested and refined in future studies. Crown Copyright © 2017. Published by Elsevier Inc. All rights reserved.

WE-B-304-02: Treatment Planning Evaluation and Optimization Should Be Biologically and Not Dose/volume Based

DOE Office of Scientific and Technical Information (OSTI.GOV)

Deasy, J.

The ultimate goal of radiotherapy treatment planning is to find a treatment that will yield a high tumor control probability (TCP) with an acceptable normal tissue complication probability (NTCP). Yet most treatment planning today is not based upon optimization of TCPs and NTCPs, but rather upon meeting physical dose and volume constraints defined by the planner. It has been suggested that treatment planning evaluation and optimization would be more effective if they were biologically and not dose/volume based, and this is the claim debated in this month’s Point/Counterpoint. After a brief overview of biologically and DVH based treatment planning bymore » the Moderator Colin Orton, Joseph Deasy (for biological planning) and Charles Mayo (against biological planning) will begin the debate. Some of the arguments in support of biological planning include: this will result in more effective dose distributions for many patients DVH-based measures of plan quality are known to have little predictive value there is little evidence that either D95 or D98 of the PTV is a good predictor of tumor control sufficient validated outcome prediction models are now becoming available and should be used to drive planning and optimization Some of the arguments against biological planning include: several decades of experience with DVH-based planning should not be discarded we do not know enough about the reliability and errors associated with biological models the radiotherapy community in general has little direct experience with side by side comparisons of DVH vs biological metrics and outcomes it is unlikely that a clinician would accept extremely cold regions in a CTV or hot regions in a PTV, despite having acceptable TCP values Learning Objectives: To understand dose/volume based treatment planning and its potential limitations To understand biological metrics such as EUD, TCP, and NTCP To understand biologically based treatment planning and its potential limitations.« less

WE-B-304-01: Treatment Planning Evaluation and Optimization Should Be Dose/volume and Not Biologically Based

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mayo, C.

The ultimate goal of radiotherapy treatment planning is to find a treatment that will yield a high tumor control probability (TCP) with an acceptable normal tissue complication probability (NTCP). Yet most treatment planning today is not based upon optimization of TCPs and NTCPs, but rather upon meeting physical dose and volume constraints defined by the planner. It has been suggested that treatment planning evaluation and optimization would be more effective if they were biologically and not dose/volume based, and this is the claim debated in this month’s Point/Counterpoint. After a brief overview of biologically and DVH based treatment planning bymore » the Moderator Colin Orton, Joseph Deasy (for biological planning) and Charles Mayo (against biological planning) will begin the debate. Some of the arguments in support of biological planning include: this will result in more effective dose distributions for many patients DVH-based measures of plan quality are known to have little predictive value there is little evidence that either D95 or D98 of the PTV is a good predictor of tumor control sufficient validated outcome prediction models are now becoming available and should be used to drive planning and optimization Some of the arguments against biological planning include: several decades of experience with DVH-based planning should not be discarded we do not know enough about the reliability and errors associated with biological models the radiotherapy community in general has little direct experience with side by side comparisons of DVH vs biological metrics and outcomes it is unlikely that a clinician would accept extremely cold regions in a CTV or hot regions in a PTV, despite having acceptable TCP values Learning Objectives: To understand dose/volume based treatment planning and its potential limitations To understand biological metrics such as EUD, TCP, and NTCP To understand biologically based treatment planning and its potential limitations.« less

Application of Particle Swarm Optimization Algorithm in the Heating System Planning Problem

PubMed Central

Ma, Rong-Jiang; Yu, Nan-Yang; Hu, Jun-Yi

2013-01-01

Based on the life cycle cost (LCC) approach, this paper presents an integral mathematical model and particle swarm optimization (PSO) algorithm for the heating system planning (HSP) problem. The proposed mathematical model minimizes the cost of heating system as the objective for a given life cycle time. For the particularity of HSP problem, the general particle swarm optimization algorithm was improved. An actual case study was calculated to check its feasibility in practical use. The results show that the improved particle swarm optimization (IPSO) algorithm can more preferably solve the HSP problem than PSO algorithm. Moreover, the results also present the potential to provide useful information when making decisions in the practical planning process. Therefore, it is believed that if this approach is applied correctly and in combination with other elements, it can become a powerful and effective optimization tool for HSP problem. PMID:23935429

New Insights into Dialysis Vascular Access: What Is the Optimal Vascular Access Type and Timing of Access Creation in CKD and Dialysis Patients?

PubMed

Woo, Karen; Lok, Charmaine E

2016-08-08

Optimal vascular access planning begins when the patient is in the predialysis stages of CKD. The choice of optimal vascular access for an individual patient and determining timing of access creation are dependent on a multitude of factors that can vary widely with each patient, including demographics, comorbidities, anatomy, and personal preferences. It is important to consider every patient's ESRD life plan (hence, their overall dialysis access life plan for every vascular access creation or placement). Optimal access type and timing of access creation are also influenced by factors external to the patient, such as surgeon experience and processes of care. In this review, we will discuss the key determinants in optimal access type and timing of access creation for upper extremity arteriovenous fistulas and grafts. Copyright © 2016 by the American Society of Nephrology.

Real-Time Monitoring of Results During First Year of Dutch Colorectal Cancer Screening Program and Optimization by Altering Fecal Immunochemical Test Cut-Off Levels.

PubMed

Toes-Zoutendijk, Esther; van Leerdam, Monique E; Dekker, Evelien; van Hees, Frank; Penning, Corine; Nagtegaal, Iris; van der Meulen, Miriam P; van Vuuren, Anneke J; Kuipers, Ernst J; Bonfrer, Johannes M G; Biermann, Katharina; Thomeer, Maarten G J; van Veldhuizen, Harriët; Kroep, Sonja; van Ballegooijen, Marjolein; Meijer, Gerrit A; de Koning, Harry J; Spaander, Manon C W; Lansdorp-Vogelaar, Iris

2017-03-01

After careful pilot studies and planning, the national screening program for colorectal cancer (CRC), with biennial fecal immunochemical tests (FITs), was initiated in The Netherlands in 2014. A national information system for real-time monitoring was developed to allow for timely evaluation. Data were collected from the first year of this screening program to determine the importance of planning and monitoring for optimal screening program performance. The national information system of the CRC screening program kept track of the number of invitations sent in 2014, FIT kits returned, and colonoscopies performed. Age-adjusted rates of participation, the number of positive test results, and positive predictive values (PPVs) for advanced neoplasia were determined weekly, quarterly, and yearly. In 2014, there were 741,914 persons invited for FIT; of these, 529,056 (71.3%; 95% CI, 71.2%-71.4%) participated. A few months into the program, real-time monitoring showed that rates of participation and positive test results (10.6%; 95% CI, 10.5%-10.8%) were higher than predicted and the PPV was lower (42.1%; 95% CI, 41.3%-42.9%) than predicted based on pilot studies. To reduce the burden of unnecessary colonoscopies and alleviate colonoscopy capacity, the cut-off level for a positive FIT result was increased from 15 to 47 μg Hb/g feces halfway through 2014. This adjustment decreased the percentage of positive test results to 6.7% (95% CI, 6.6%-6.8%) and increased the PPV to 49.1% (95% CI, 48.3%-49.9%). In total, the first year of the Dutch screening program resulted in the detection of 2483 cancers and 12,030 advanced adenomas. Close monitoring of the implementation of the Dutch national CRC screening program allowed for instant adjustment of the FIT cut-off levels to optimize program performance. Copyright © 2017 AGA Institute. Published by Elsevier Inc. All rights reserved.

VirSSPA- a virtual reality tool for surgical planning workflow.

PubMed

Suárez, C; Acha, B; Serrano, C; Parra, C; Gómez, T

2009-03-01

A virtual reality tool, called VirSSPA, was developed to optimize the planning of surgical processes. Segmentation algorithms for Computed Tomography (CT) images: a region growing procedure was used for soft tissues and a thresholding algorithm was implemented to segment bones. The algorithms operate semiautomati- cally since they only need seed selection with the mouse on each tissue segmented by the user. The novelty of the paper is the adaptation of an enhancement method based on histogram thresholding applied to CT images for surgical planning, which simplifies subsequent segmentation. A substantial improvement of the virtual reality tool VirSSPA was obtained with these algorithms. VirSSPA was used to optimize surgical planning, to decrease the time spent on surgical planning and to improve operative results. The success rate increases due to surgeons being able to see the exact extent of the patient's ailment. This tool can decrease operating room time, thus resulting in reduced costs. Virtual simulation was effective for optimizing surgical planning, which could, consequently, result in improved outcomes with reduced costs.

Resilient off-grid microgrids: Capacity planning and N-1 security

DOE PAGES

Madathil, Sreenath Chalil; Yamangil, Emre; Nagarajan, Harsha; ...

2017-06-13

Over the past century the electric power industry has evolved to support the delivery of power over long distances with highly interconnected transmission systems. Despite this evolution, some remote communities are not connected to these systems. These communities rely on small, disconnected distribution systems, i.e., microgrids to deliver power. However, as microgrids often are not held to the same reliability standards as transmission grids, remote communities can be at risk for extended blackouts. To address this issue, we develop an optimization model and an algorithm for capacity planning and operations of microgrids that include N-1 security and other practical modelingmore » features like AC power flow physics, component efficiencies and thermal limits. Lastly, we demonstrate the computational effectiveness of our approach on two test systems; a modified version of the IEEE 13 node test feeder and a model of a distribution system in a remote community in Alaska.« less

Resilient off-grid microgrids: Capacity planning and N-1 security

DOE Office of Scientific and Technical Information (OSTI.GOV)

Madathil, Sreenath Chalil; Yamangil, Emre; Nagarajan, Harsha

Over the past century the electric power industry has evolved to support the delivery of power over long distances with highly interconnected transmission systems. Despite this evolution, some remote communities are not connected to these systems. These communities rely on small, disconnected distribution systems, i.e., microgrids to deliver power. However, as microgrids often are not held to the same reliability standards as transmission grids, remote communities can be at risk for extended blackouts. To address this issue, we develop an optimization model and an algorithm for capacity planning and operations of microgrids that include N-1 security and other practical modelingmore » features like AC power flow physics, component efficiencies and thermal limits. Lastly, we demonstrate the computational effectiveness of our approach on two test systems; a modified version of the IEEE 13 node test feeder and a model of a distribution system in a remote community in Alaska.« less

An Interval Type-2 Fuzzy Multiple Echelon Supply Chain Model

NASA Astrophysics Data System (ADS)

Miller, Simon; John, Robert

Planning resources for a supply chain is a major factor determining its success or failure. In this paper we build on previous work introducing an Interval Type-2 Fuzzy Logic model of a multiple echelon supply chain. It is believed that the additional degree of uncertainty provided by Interval Type-2 Fuzzy Logic will allow for better representation of the uncertainty and vagueness present in resource planning models. First, the subject of Supply Chain Management is introduced, then some background is given on related work using Type-1 Fuzzy Logic. A description of the Interval Type-2 Fuzzy model is given, and a test scenario detailed. A Genetic Algorithm uses the model to search for a near-optimal plan for the scenario. A discussion of the results follows, along with conclusions and details of intended further work.

Simulation-optimization model for production planning in the blood supply chain.

PubMed

Osorio, Andres F; Brailsford, Sally C; Smith, Honora K; Forero-Matiz, Sonia P; Camacho-Rodríguez, Bernardo A

2017-12-01

Production planning in the blood supply chain is a challenging task. Many complex factors such as uncertain supply and demand, blood group proportions, shelf life constraints and different collection and production methods have to be taken into account, and thus advanced methodologies are required for decision making. This paper presents an integrated simulation-optimization model to support both strategic and operational decisions in production planning. Discrete-event simulation is used to represent the flows through the supply chain, incorporating collection, production, storing and distribution. On the other hand, an integer linear optimization model running over a rolling planning horizon is used to support daily decisions, such as the required number of donors, collection methods and production planning. This approach is evaluated using real data from a blood center in Colombia. The results show that, using the proposed model, key indicators such as shortages, outdated units, donors required and cost are improved.

An optimization design for evacuation planning based on fuzzy credibility theory and genetic algorithm

NASA Astrophysics Data System (ADS)

Zhang, D.; Zhang, W. Y.

2017-08-01

Evacuation planning is an important activity in disaster management. It has to be planned in advance due to the unpredictable occurrence of disasters. It is necessary that the evacuation plans are as close as possible to the real evacuation work. However, the evacuation plan is extremely challenging because of the inherent uncertainty of the required information. There is a kind of vehicle routing problem based on the public traffic evacuation. In this paper, the demand for each evacuation set point is a fuzzy number, and each routing selection of the point is based on the fuzzy credibility preference index. This paper proposes an approximate optimal solution for this problem by the genetic algorithm based on the fuzzy reliability theory. Finally, the algorithm is applied to an optimization model, and the experiment result shows that the algorithm is effective.

New problem with sales, inventories, and operations planning in a supply chain environment

NASA Astrophysics Data System (ADS)

Thomas, Andre; Lamouri, Samir

2000-10-01

The highest level of planning and control system is necessary, because production and logistics systems are not so flexible to follow, from day to day, sales evolutions. The companies are therefore held to standardize the good practices concerning the elaboration of their Sales, Inventories and Operations Planning (SIOP). The SIOP makes it possible to implement the strategic objectives defined by Top Management at the time of the Business Plan. It is the link between sales and manufacturing planning. The objectives of each of those depend on the specificity of their trade: the Sales Department will go for a maximum sales whereas Production will endeavor to keep industrial cost prices as low as possible while the Finance Department will try to optimize the use of available funds. There are several tools for this optimization: Graphical method and linear programming. Today, the economic context requires robust optimization.

Link Design and Planning for Mars Reconnaissance Orbiter (MRO) Ka-band (32 GHz) Telecom Demonstration

NASA Technical Reports Server (NTRS)

Shambayati, Shervin; Davarian, Faramaz; Morabito, David

2004-01-01

NASA is planning an engineering telemetry demonstration with Mars Reconnaissance Orbiter (MRO). Capabilities of Ka-band (32 GHz) for use with deep space mission are demonstrated using the link optimization algorithms and weather forecasting. Furthermore, based on the performance of previous deep space missions with Ka-band downlink capabilities, experiment plans are developed for telemetry operations during superior solar conjunction. A general overview of the demonstration is given followed by a description of the mission planning during cruise, the primary science mission and superior conjunction. As part of the primary science mission planning the expected data return for various data optimization methods is calculated. These results indicate that, given MRO's data rates, a link optimized to use of at most two data rates, subject to a minimum availability of 90%, performs almost as well as a link with no limits on the number of data rates subject to the same minimum availability.

Cache-Aware Asymptotically-Optimal Sampling-Based Motion Planning

PubMed Central

Ichnowski, Jeffrey; Prins, Jan F.; Alterovitz, Ron

2014-01-01

We present CARRT* (Cache-Aware Rapidly Exploring Random Tree*), an asymptotically optimal sampling-based motion planner that significantly reduces motion planning computation time by effectively utilizing the cache memory hierarchy of modern central processing units (CPUs). CARRT* can account for the CPU’s cache size in a manner that keeps its working dataset in the cache. The motion planner progressively subdivides the robot’s configuration space into smaller regions as the number of configuration samples rises. By focusing configuration exploration in a region for periods of time, nearest neighbor searching is accelerated since the working dataset is small enough to fit in the cache. CARRT* also rewires the motion planning graph in a manner that complements the cache-aware subdivision strategy to more quickly refine the motion planning graph toward optimality. We demonstrate the performance benefit of our cache-aware motion planning approach for scenarios involving a point robot as well as the Rethink Robotics Baxter robot. PMID:25419474

Cache-Aware Asymptotically-Optimal Sampling-Based Motion Planning.

PubMed

Ichnowski, Jeffrey; Prins, Jan F; Alterovitz, Ron

2014-05-01

We present CARRT* (Cache-Aware Rapidly Exploring Random Tree*), an asymptotically optimal sampling-based motion planner that significantly reduces motion planning computation time by effectively utilizing the cache memory hierarchy of modern central processing units (CPUs). CARRT* can account for the CPU's cache size in a manner that keeps its working dataset in the cache. The motion planner progressively subdivides the robot's configuration space into smaller regions as the number of configuration samples rises. By focusing configuration exploration in a region for periods of time, nearest neighbor searching is accelerated since the working dataset is small enough to fit in the cache. CARRT* also rewires the motion planning graph in a manner that complements the cache-aware subdivision strategy to more quickly refine the motion planning graph toward optimality. We demonstrate the performance benefit of our cache-aware motion planning approach for scenarios involving a point robot as well as the Rethink Robotics Baxter robot.

Role of the parameters involved in the plan optimization based on the generalized equivalent uniform dose and radiobiological implications

NASA Astrophysics Data System (ADS)

Widesott, L.; Strigari, L.; Pressello, M. C.; Benassi, M.; Landoni, V.

2008-03-01

We investigated the role and the weight of the parameters involved in the intensity modulated radiation therapy (IMRT) optimization based on the generalized equivalent uniform dose (gEUD) method, for prostate and head-and-neck plans. We systematically varied the parameters (gEUDmax and weight) involved in the gEUD-based optimization of rectal wall and parotid glands. We found that the proper value of weight factor, still guaranteeing planning treatment volumes coverage, produced similar organs at risks dose-volume (DV) histograms for different gEUDmax with fixed a = 1. Most of all, we formulated a simple relation that links the reference gEUDmax and the associated weight factor. As secondary objective, we evaluated plans obtained with the gEUD-based optimization and ones based on DV criteria, using the normal tissue complication probability (NTCP) models. gEUD criteria seemed to improve sparing of rectum and parotid glands with respect to DV-based optimization: the mean dose, the V40 and V50 values to the rectal wall were decreased of about 10%, the mean dose to parotids decreased of about 20-30%. But more than the OARs sparing, we underlined the halving of the OARs optimization time with the implementation of the gEUD-based cost function. Using NTCP models we enhanced differences between the two optimization criteria for parotid glands, but no for rectum wall.

SU-F-T-527: A Novel Dynamic Multileaf Collimator Leaf-Sequencing Algorithm in Radiation Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jing, J; Lin, H; Chow, J

Purpose: A novel leaf-sequencing algorithm is developed for generating arbitrary beam intensity profiles in discrete levels using dynamic multileaf collimator (MLC). The efficiency of this dynamic MLC leaf-sequencing method was evaluated using external beam treatment plans delivered by intensity modulated radiation therapy technique. Methods: To qualify and validate this algorithm, integral test for the beam segment of MLC generated by the CORVUS treatment planning system was performed with clinical intensity map experiments. The treatment plans were optimized and the fluence maps for all photon beams were determined. This algorithm started with the algebraic expression for the area under the beammore » profile. The coefficients in the expression can be transformed into the specifications for the leaf-setting sequence. The leaf optimization procedure was then applied and analyzed for clinical relevant intensity profiles in cancer treatment. Results: The macrophysical effect of this method can be described by volumetric plan evaluation tools such as dose-volume histograms (DVHs). The DVH results are in good agreement compared to those from the CORVUS treatment planning system. Conclusion: We developed a dynamic MLC method to examine the stability of leaf speed including effects of acceleration and deceleration of leaf motion in order to make sure the stability of leaf speed did not affect the intensity profile generated. It was found that the mechanical requirements were better satisfied using this method. The Project is sponsored by the Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry.« less

Patient-specific Monte Carlo-based dose-kernel approach for inverse planning in afterloading brachytherapy.

PubMed

D'Amours, Michel; Pouliot, Jean; Dagnault, Anne; Verhaegen, Frank; Beaulieu, Luc

2011-12-01

Brachytherapy planning software relies on the Task Group report 43 dosimetry formalism. This formalism, based on a water approximation, neglects various heterogeneous materials present during treatment. Various studies have suggested that these heterogeneities should be taken into account to improve the treatment quality. The present study sought to demonstrate the feasibility of incorporating Monte Carlo (MC) dosimetry within an inverse planning algorithm to improve the dose conformity and increase the treatment quality. The method was based on precalculated dose kernels in full patient geometries, representing the dose distribution of a brachytherapy source at a single dwell position using MC simulations and the Geant4 toolkit. These dose kernels are used by the inverse planning by simulated annealing tool to produce a fast MC-based plan. A test was performed for an interstitial brachytherapy breast treatment using two different high-dose-rate brachytherapy sources: the microSelectron iridium-192 source and the electronic brachytherapy source Axxent operating at 50 kVp. A research version of the inverse planning by simulated annealing algorithm was combined with MC to provide a method to fully account for the heterogeneities in dose optimization, using the MC method. The effect of the water approximation was found to depend on photon energy, with greater dose attenuation for the lower energies of the Axxent source compared with iridium-192. For the latter, an underdosage of 5.1% for the dose received by 90% of the clinical target volume was found. A new method to optimize afterloading brachytherapy plans that uses MC dosimetric information was developed. Including computed tomography-based information in MC dosimetry in the inverse planning process was shown to take into account the full range of scatter and heterogeneity conditions. This led to significant dose differences compared with the Task Group report 43 approach for the Axxent source. Copyright © 2011 Elsevier Inc. All rights reserved.

Research on global path planning based on ant colony optimization for AUV

NASA Astrophysics Data System (ADS)

Wang, Hong-Jian; Xiong, Wei

2009-03-01

Path planning is an important issue for autonomous underwater vehicles (AUVs) traversing an unknown environment such as a sea floor, a jungle, or the outer celestial planets. For this paper, global path planning using large-scale chart data was studied, and the principles of ant colony optimization (ACO) were applied. This paper introduced the idea of a visibility graph based on the grid workspace model. It also brought a series of pheromone updating rules for the ACO planning algorithm. The operational steps of the ACO algorithm are proposed as a model for a global path planning method for AUV. To mimic the process of smoothing a planned path, a cutting operator and an insertion-point operator were designed. Simulation results demonstrated that the ACO algorithm is suitable for global path planning. The system has many advantages, including that the operating path of the AUV can be quickly optimized, and it is shorter, safer, and smoother. The prototype system successfully demonstrated the feasibility of the concept, proving it can be applied to surveys of unstructured unmanned environments.

UAV path planning using artificial potential field method updated by optimal control theory

NASA Astrophysics Data System (ADS)

Chen, Yong-bo; Luo, Guan-chen; Mei, Yue-song; Yu, Jian-qiao; Su, Xiao-long

2016-04-01

The unmanned aerial vehicle (UAV) path planning problem is an important assignment in the UAV mission planning. Based on the artificial potential field (APF) UAV path planning method, it is reconstructed into the constrained optimisation problem by introducing an additional control force. The constrained optimisation problem is translated into the unconstrained optimisation problem with the help of slack variables in this paper. The functional optimisation method is applied to reform this problem into an optimal control problem. The whole transformation process is deduced in detail, based on a discrete UAV dynamic model. Then, the path planning problem is solved with the help of the optimal control method. The path following process based on the six degrees of freedom simulation model of the quadrotor helicopters is introduced to verify the practicability of this method. Finally, the simulation results show that the improved method is more effective in planning path. In the planning space, the length of the calculated path is shorter and smoother than that using traditional APF method. In addition, the improved method can solve the dead point problem effectively.

Co-Optimization of Electricity Transmission and Generation Resources for Planning and Policy Analysis: Review of Concepts and Modeling Approaches

DOE Office of Scientific and Technical Information (OSTI.GOV)

Krishnan, Venkat; Ho, Jonathan; Hobbs, Benjamin F.

2016-05-01

The recognition of transmission's interaction with other resources has motivated the development of co-optimization methods to optimize transmission investment while simultaneously considering tradeoffs with investments in electricity supply, demand, and storage resources. For a given set of constraints, co-optimized planning models provide solutions that have lower costs than solutions obtained from decoupled optimization (transmission-only, generation-only, or iterations between them). This paper describes co-optimization and provides an overview of approaches to co-optimizing transmission options, supply-side resources, demand-side resources, and natural gas pipelines. In particular, the paper provides an up-to-date assessment of the present and potential capabilities of existing co-optimization tools, andmore » it discusses needs and challenges for developing advanced co-optimization models.« less

Front end optimization for the monolithic active pixel sensor of the ALICE Inner Tracking System upgrade

NASA Astrophysics Data System (ADS)

Kim, D.; Aglieri Rinella, G.; Cavicchioli, C.; Chanlek, N.; Collu, A.; Degerli, Y.; Dorokhov, A.; Flouzat, C.; Gajanana, D.; Gao, C.; Guilloux, F.; Hillemanns, H.; Hristozkov, S.; Junique, A.; Keil, M.; Kofarago, M.; Kugathasan, T.; Kwon, Y.; Lattuca, A.; Mager, M.; Sielewicz, K. M.; Marin Tobon, C. A.; Marras, D.; Martinengo, P.; Mazza, G.; Mugnier, H.; Musa, L.; Pham, T. H.; Puggioni, C.; Reidt, F.; Riedler, P.; Rousset, J.; Siddhanta, S.; Snoeys, W.; Song, M.; Usai, G.; Van Hoorne, J. W.; Yang, P.

2016-02-01

ALICE plans to replace its Inner Tracking System during the second long shut down of the LHC in 2019 with a new 10 m2 tracker constructed entirely with monolithic active pixel sensors. The TowerJazz 180 nm CMOS imaging Sensor process has been selected to produce the sensor as it offers a deep pwell allowing full CMOS in-pixel circuitry and different starting materials. First full-scale prototypes have been fabricated and tested. Radiation tolerance has also been verified. In this paper the development of the charge sensitive front end and in particular its optimization for uniformity of charge threshold and time response will be presented.

Review: Optimization methods for groundwater modeling and management

NASA Astrophysics Data System (ADS)

Yeh, William W.-G.

2015-09-01

Optimization methods have been used in groundwater modeling as well as for the planning and management of groundwater systems. This paper reviews and evaluates the various optimization methods that have been used for solving the inverse problem of parameter identification (estimation), experimental design, and groundwater planning and management. Various model selection criteria are discussed, as well as criteria used for model discrimination. The inverse problem of parameter identification concerns the optimal determination of model parameters using water-level observations. In general, the optimal experimental design seeks to find sampling strategies for the purpose of estimating the unknown model parameters. A typical objective of optimal conjunctive-use planning of surface water and groundwater is to minimize the operational costs of meeting water demand. The optimization methods include mathematical programming techniques such as linear programming, quadratic programming, dynamic programming, stochastic programming, nonlinear programming, and the global search algorithms such as genetic algorithms, simulated annealing, and tabu search. Emphasis is placed on groundwater flow problems as opposed to contaminant transport problems. A typical two-dimensional groundwater flow problem is used to explain the basic formulations and algorithms that have been used to solve the formulated optimization problems.

Role of step size and max dwell time in anatomy based inverse optimization for prostate implants

PubMed Central

Manikandan, Arjunan; Sarkar, Biplab; Rajendran, Vivek Thirupathur; King, Paul R.; Sresty, N.V. Madhusudhana; Holla, Ragavendra; Kotur, Sachin; Nadendla, Sujatha

2013-01-01

In high dose rate (HDR) brachytherapy, the source dwell times and dwell positions are vital parameters in achieving a desirable implant dose distribution. Inverse treatment planning requires an optimal choice of these parameters to achieve the desired target coverage with the lowest achievable dose to the organs at risk (OAR). This study was designed to evaluate the optimum source step size and maximum source dwell time for prostate brachytherapy implants using an Ir-192 source. In total, one hundred inverse treatment plans were generated for the four patients included in this study. Twenty-five treatment plans were created for each patient by varying the step size and maximum source dwell time during anatomy-based, inverse-planned optimization. Other relevant treatment planning parameters were kept constant, including the dose constraints and source dwell positions. Each plan was evaluated for target coverage, urethral and rectal dose sparing, treatment time, relative target dose homogeneity, and nonuniformity ratio. The plans with 0.5 cm step size were seen to have clinically acceptable tumor coverage, minimal normal structure doses, and minimum treatment time as compared with the other step sizes. The target coverage for this step size is 87% of the prescription dose, while the urethral and maximum rectal doses were 107.3 and 68.7%, respectively. No appreciable difference in plan quality was observed with variation in maximum source dwell time. The step size plays a significant role in plan optimization for prostate implants. Our study supports use of a 0.5 cm step size for prostate implants. PMID:24049323