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Sample records for optimal treatment planning

  1. MO-B-BRB-00: Optimizing the Treatment Planning Process

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2015-06-15

    The radiotherapy treatment planning process has evolved over the years with innovations in treatment planning, treatment delivery and imaging systems. Treatment modality and simulation technologies are also rapidly improving and affecting the planning process. For example, Image-guided-radiation-therapy has been widely adopted for patient setup, leading to margin reduction and isocenter repositioning after simulation. Stereotactic Body radiation therapy (SBRT) and Radiosurgery (SRS) have gradually become the standard of care for many treatment sites, which demand a higher throughput for the treatment plans even if the number of treatments per day remains the same. Finally, simulation, planning and treatment are traditionally sequential events. However, with emerging adaptive radiotherapy, they are becoming more tightly intertwined, leading to iterative processes. Enhanced efficiency of planning is therefore becoming more critical and poses serious challenge to the treatment planning process; Lean Six Sigma approaches are being utilized increasingly to balance the competing needs for speed and quality. In this symposium we will discuss the treatment planning process and illustrate effective techniques for managing workflow. Topics will include: Planning techniques: (a) beam placement, (b) dose optimization, (c) plan evaluation (d) export to RVS. Planning workflow: (a) import images, (b) Image fusion, (c) contouring, (d) plan approval (e) plan check (f) chart check, (g) sequential and iterative process Influence of upstream and downstream operations: (a) simulation, (b) immobilization, (c) motion management, (d) QA, (e) IGRT, (f) Treatment delivery, (g) SBRT/SRS (h) adaptive planning Reduction of delay between planning steps with Lean systems due to (a) communication, (b) limited resource, (b) contour, (c) plan approval, (d) treatment. Optimizing planning processes: (a) contour validation (b) consistent planning protocol, (c) protocol/template sharing, (d) semi

  2. Optimal partial-arcs in VMAT treatment planning

    CERN Document Server

    Wala, Jeremiah; Chen, Wei; Craft, David

    2012-01-01

    Purpose: To improve the delivery efficiency of VMAT by extending the recently published VMAT treatment planning algorithm vmerge to automatically generate optimal partial-arc plans. Methods and materials: A high-quality initial plan is created by solving a convex multicriteria optimization problem using 180 equi-spaced beams. This initial plan is used to form a set of dose constraints, and a set of partial-arc plans is created by searching the space of all possible partial-arc plans that satisfy these constraints. For each partial-arc, an iterative fluence map merging and sequencing algorithm (vmerge) is used to improve the delivery efficiency. Merging continues as long as the dose quality is maintained above a user-defined threshold. The final plan is selected as the partial arc with the lowest treatment time. The complete algorithm is called pmerge. Results: Partial-arc plans are created using pmerge for a lung, liver and prostate case, with final treatment times of 127, 245 and 147 seconds. Treatment times...

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

    Science.gov (United States)

    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.

  4. Optimizing global liver function in radiation therapy treatment planning

    Science.gov (United States)

    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

  5. Optimizing global liver function in radiation therapy treatment planning

    Science.gov (United States)

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

    2017-01-01

    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 (ℓEUD) (conventional ‘ℓEUD model’), the so-called perfusion-weighted ℓEUD (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 ℓEUD, fEUD, and GLF plans delivering the same target ℓEUD 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%(7.5%) more liver function than the fEUD (ℓEUD) plan does in 2D cases, and up to 4.5%(5.6%) in 3D cases. The GLF and fEUD plans worsen in ℓEUD 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 ℓEUD model optimization does, the GLF model directly optimizes a more clinically

  6. Speed optimized influence matrix processing in inverse treatment planning tools

    Energy Technology Data Exchange (ETDEWEB)

    Ziegenhein, Peter; Wilkens, Jan J; Nill, Simeon; Oelfke, Uwe [German Cancer Research Center (DKFZ), Department of Medical Physics in Radiation Oncology, Im Neuenheimer Feld 280, 69120 Heidelberg (Germany); Ludwig, Thomas [University of Heidelberg, Institute of Computer Science, Research Group Parallel and Distributed Systems, Im Neuenheimer Feld 348, 69120 Heidelberg (Germany)], E-mail: p.ziegenhein@dkfz.de, E-mail: u.oelfke@dkfz.de

    2008-05-07

    An optimal plan in modern treatment planning tools is found through the use of an iterative optimization algorithm, which deals with a high amount of patient-related data and number of treatment parameters to be optimized. Thus, calculating a good plan is a very time-consuming process which limits the application for patients in clinics and for research activities aiming for more accuracy. A common technique to handle the vast amount of radiation dose data is the concept of the influence matrix (DIJ), which stores the dose contribution of each bixel to the patient in the main memory of the computer. This study revealed that a bottleneck for the optimization time arises from the data transfer of the dose data between the memory and the CPU. In this note, we introduce a new method which speeds up the data transportation from stored dose data to the CPU. As an example we used the DIJ approach as is implemented in our treatment planning tool KonRad, developed at the German Cancer Research Center (DKFZ) in Heidelberg. A data cycle reordering method is proposed to take the advantage of modern memory hardware. This induces a minimal eviction policy which results in a memory behaviour exhibiting a 2.6 times faster algorithm compared to the naive implementation. Although our method is described for the DIJ approach implemented in KonRad, we believe that any other planning tool which uses a similar approach to store the dose data will also benefit from the described methods. (note)

  7. Optimization of stereotactic body radiotherapy treatment planning using a multicriteria optimization algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Ghandour, Sarah; Cosinschi, Adrien; Mazouni, Zohra; Pachoud, Marc; Matzinger, Oscar [Riviera-Chablais Hospital, Vevey (Switzerland). Cancer Center, Radiotherapy Dept.

    2016-07-01

    To provide high-quality and efficient dosimetric planning for various types of stereotactic body radiotherapy (SBRT) for tumor treatment using a multicriteria optimization (MCO) technique fine-tuned with direct machine parameter optimization (DMPO). Eighteen patients with lung (n = 11), liver (n = 5) or adrenal cell cancer (n = 2) were treated using SBRT in our clinic between December 2014 and June 2015. Plans were generated using the RayStation trademark Treatment Planning System (TPS) with the VMAT technique. Optimal deliverable SBRT plans were first generated using an MCO algorithm to find a well-balanced tradeoff between tumor control and normal tissue sparing in an efficient treatment planning time. Then, the deliverable plan was post-processed using the MCO solution as the starting point for the DMPO algorithm to improve the dose gradient around the planning target volume (PTV) while maintaining the clinician's priorities. The dosimetric quality of the plans was evaluated using dose-volume histogram (DVH) parameters, which account for target coverage and the sparing of healthy tissue, as well as the CI100 and CI50 conformity indexes. Using a combination of the MCO and DMPO algorithms showed that the treatment plans were clinically optimal and conformed to all organ risk dose volume constraints reported in the literature, with a computation time of approximately one hour. The coverage of the PTV (D99% and D95%) and sparing of organs at risk (OAR) were similar between the MCO and MCO + DMPO plans, with no significant differences (p > 0.05) for all the SBRT plans. The average CI100 and CI50 values using MCO + DMPO were significantly better than those with MCO alone (p < 0.05). The MCO technique allows for convergence on an optimal solution for SBRT within an efficient planning time. The combination of the MCO and DMPO techniques yields a better dose gradient, especially for lung tumors.

  8. Novel tools for stepping source brachytherapy treatment planning: Enhanced geometrical optimization and interactive inverse planning

    Energy Technology Data Exchange (ETDEWEB)

    Dinkla, Anna M., E-mail: a.m.dinkla@amc.uva.nl; Laarse, Rob van der; Koedooder, Kees; Petra Kok, H.; Wieringen, Niek van; Pieters, Bradley R.; Bel, Arjan [Department of Radiation Oncology, Academic Medical Center Amsterdam, Meibergdreef 9, Amsterdam 1105 AZ (Netherlands)

    2015-01-15

    Purpose: Dose optimization for stepping source brachytherapy can nowadays be performed using automated inverse algorithms. Although much quicker than graphical optimization, an experienced treatment planner is required for both methods. With automated inverse algorithms, the procedure to achieve the desired dose distribution is often based on trial-and-error. Methods: A new approach for stepping source prostate brachytherapy treatment planning was developed as a quick and user-friendly alternative. This approach consists of the combined use of two novel tools: Enhanced geometrical optimization (EGO) and interactive inverse planning (IIP). EGO is an extended version of the common geometrical optimization method and is applied to create a dose distribution as homogeneous as possible. With the second tool, IIP, this dose distribution is tailored to a specific patient anatomy by interactively changing the highest and lowest dose on the contours. Results: The combined use of EGO–IIP was evaluated on 24 prostate cancer patients, by having an inexperienced user create treatment plans, compliant to clinical dose objectives. This user was able to create dose plans of 24 patients in an average time of 4.4 min/patient. An experienced treatment planner without extensive training in EGO–IIP also created 24 plans. The resulting dose-volume histogram parameters were comparable to the clinical plans and showed high conformance to clinical standards. Conclusions: Even for an inexperienced user, treatment planning with EGO–IIP for stepping source prostate brachytherapy is feasible as an alternative to current optimization algorithms, offering speed, simplicity for the user, and local control of the dose levels.

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

    CERN Document Server

    Engberg, Lovisa; Forsgren, Anders; Hårdemark, Björn

    2016-01-01

    Given the widespread agreement that doses-at-volume play important roles in quality assessment of radiation therapy treatment plans, planning objectives that correlate well with explicit dose-at-volume optimization are likely to correlate well with plan quality. In this study, planning objectives are formulated to explicitly either minimize or maximize convex approximations of dose-at-volume, namely, mean-tail-doses. This is in contrast to the conventionally used planning objectives, which are used to maximize clinical goal fulfilment by relating to deviations from dose-at-volume thresholds. Advantages of the proposed planning objectives are investigated through juxtaposition with conventional objectives in a computational study of two patient cases, each with three doses-at-volume to be minimized subject to PTV coverage. With proposed planning objectives, this is translated into minimizing three mean-tail-doses. Comparison with conventional objectives is carried out in the dose-at-volume domain and in the no...

  10. A treatment planning code for inverse planning and 3D optimization in hadrontherapy.

    Science.gov (United States)

    Bourhaleb, F; Marchetto, F; Attili, A; Pittà, G; Cirio, R; Donetti, M; Giordanengo, S; Givehchi, N; Iliescu, S; Krengli, M; La Rosa, A; Massai, D; Pecka, A; Pardo, J; Peroni, C

    2008-09-01

    The therapeutic use of protons and ions, especially carbon ions, is a new technique and a challenge to conform the dose to the target due to the energy deposition characteristics of hadron beams. An appropriate treatment planning system (TPS) is strictly necessary to take full advantage. We developed a TPS software, ANCOD++, for the evaluation of the optimal conformal dose. ANCOD++ is an analytical code using the voxel-scan technique as an active method to deliver the dose to the patient, and provides treatment plans with both proton and carbon ion beams. The iterative algorithm, coded in C++ and running on Unix/Linux platform, allows the determination of the best fluences of the individual beams to obtain an optimal physical dose distribution, delivering a maximum dose to the target volume and a minimum dose to critical structures. The TPS is supported by Monte Carlo simulations with the package GEANT3 to provide the necessary physical lookup tables and verify the optimized treatment plans. Dose verifications done by means of full Monte Carlo simulations show an overall good agreement with the treatment planning calculations. We stress the fact that the purpose of this work is the verification of the physical dose and a next work will be dedicated to the radiobiological evaluation of the equivalent biological dose.

  11. On the selection of optimization parameters for an inverse treatment planning replacement of a forward planning technique for prostate cancer.

    Science.gov (United States)

    Hristov, Dimitre H; Moftah, Belal A; Charrois, Colette; Parker, William; Souhami, Luis; Podgorsak, Ervin B

    2002-01-01

    The influence of organ volume sampling, lateral scatter inclusion, and the selection of objectives and constraints on the inverse treatment planning process with a commercial treatment planning system is investigated and suitable parameters are identified for an inverse treatment planning replacement of a clinical forward planning technique for prostate cancer. For the beam geometries of the forward technique, a variable set of parameters is used for the calculation of dose from pencil beams. An optimal set is identified after the evaluation of optimized plans that correspond to different sets of pencil-beam parameters. This set along with a single, optimized set of objectives and constraints is used to perform inverse planning on ten randomly selected patients. The acceptability of the resulting plans is verified by comparisons to the clinical ones calculated with the forward techniques. For the particular commercial treatment planning system, the default values of the pencil beam parameters are found adequate for inverse treatment planning. For all ten patients, the optimized, single set of objectives and constraints results in plans with target coverage comparable to that of the forward plans. Furthermore inverse treatment planning reduces the overall mean rectal and bladder doses by 4.8% and 5.8% of the prescription dose respectively. The study indicates that (i) inverse treatment planning results depend implicitly on the sampling of the dose distribution, (ii) inverse treatment planning results depend on the method used by the dose calculation model to account for scatter, and (iii) for certain sites, a single set of optimization parameters can be used for all patient plans.

  12. IMRT treatment planning for prostate cancer using prioritized prescription optimization and mean-tail-dose functions

    OpenAIRE

    2008-01-01

    Treatment planning for intensity modulated radiation therapy (IMRT) is challenging due to both the size of the computational problems (thousands of variables and constraints) and the multi-objective, imprecise nature of the goals. We apply hierarchical programming to IMRT treatment planning. In this formulation, treatment planning goals/objectives are ordered in an absolute hierarchy, and the problem is solved from the top-down such that more important goals are optimized in turn. After each ...

  13. A Multi-Criteria Framework with Voxel-Dependent Parameters for Radiotherapy Treatment Plan Optimization

    CERN Document Server

    Zarepisheh, Masoud; Li, Nan; Jia, Xun; Jiang, Steve B

    2012-01-01

    In a treatment plan optimization problem for radiotherapy, a clinically acceptable plan is usually generated by an optimization process with weighting factors or reference doses adjusted for organs. Recent discoveries indicate that adjusting parameters associated with each voxel may lead to better plan quality. However, it is still unclear regarding the mathematical reasons behind it. To answer questions related to this problem, we establish in this work a new mathematical framework equipped with two theorems. The new framework clarifies the different consequences of adjusting organ-dependent and voxel-dependent parameters for the treatment plan optimization of radiation therapy, as well as the different effects of adjusting weighting factors versus reference doses in the optimization process. The main discoveries are threefold: 1) While in the organ-based model the selection of the objective function has an impact on the quality of the optimized plans, this is no longer an issue for the voxel-based model sin...

  14. MO-B-BRB-01: Optimize Treatment Planning Process in Clinical Environment

    Energy Technology Data Exchange (ETDEWEB)

    Feng, W. [New York Presbyterian Hospital (United States)

    2015-06-15

    The radiotherapy treatment planning process has evolved over the years with innovations in treatment planning, treatment delivery and imaging systems. Treatment modality and simulation technologies are also rapidly improving and affecting the planning process. For example, Image-guided-radiation-therapy has been widely adopted for patient setup, leading to margin reduction and isocenter repositioning after simulation. Stereotactic Body radiation therapy (SBRT) and Radiosurgery (SRS) have gradually become the standard of care for many treatment sites, which demand a higher throughput for the treatment plans even if the number of treatments per day remains the same. Finally, simulation, planning and treatment are traditionally sequential events. However, with emerging adaptive radiotherapy, they are becoming more tightly intertwined, leading to iterative processes. Enhanced efficiency of planning is therefore becoming more critical and poses serious challenge to the treatment planning process; Lean Six Sigma approaches are being utilized increasingly to balance the competing needs for speed and quality. In this symposium we will discuss the treatment planning process and illustrate effective techniques for managing workflow. Topics will include: Planning techniques: (a) beam placement, (b) dose optimization, (c) plan evaluation (d) export to RVS. Planning workflow: (a) import images, (b) Image fusion, (c) contouring, (d) plan approval (e) plan check (f) chart check, (g) sequential and iterative process Influence of upstream and downstream operations: (a) simulation, (b) immobilization, (c) motion management, (d) QA, (e) IGRT, (f) Treatment delivery, (g) SBRT/SRS (h) adaptive planning Reduction of delay between planning steps with Lean systems due to (a) communication, (b) limited resource, (b) contour, (c) plan approval, (d) treatment. Optimizing planning processes: (a) contour validation (b) consistent planning protocol, (c) protocol/template sharing, (d) semi

  15. MO-B-BRB-03: Systems Engineering Tools for Treatment Planning Process Optimization in Radiation Medicine

    Energy Technology Data Exchange (ETDEWEB)

    Kapur, A. [Long Island Jewish Medical Center (United States)

    2015-06-15

    The radiotherapy treatment planning process has evolved over the years with innovations in treatment planning, treatment delivery and imaging systems. Treatment modality and simulation technologies are also rapidly improving and affecting the planning process. For example, Image-guided-radiation-therapy has been widely adopted for patient setup, leading to margin reduction and isocenter repositioning after simulation. Stereotactic Body radiation therapy (SBRT) and Radiosurgery (SRS) have gradually become the standard of care for many treatment sites, which demand a higher throughput for the treatment plans even if the number of treatments per day remains the same. Finally, simulation, planning and treatment are traditionally sequential events. However, with emerging adaptive radiotherapy, they are becoming more tightly intertwined, leading to iterative processes. Enhanced efficiency of planning is therefore becoming more critical and poses serious challenge to the treatment planning process; Lean Six Sigma approaches are being utilized increasingly to balance the competing needs for speed and quality. In this symposium we will discuss the treatment planning process and illustrate effective techniques for managing workflow. Topics will include: Planning techniques: (a) beam placement, (b) dose optimization, (c) plan evaluation (d) export to RVS. Planning workflow: (a) import images, (b) Image fusion, (c) contouring, (d) plan approval (e) plan check (f) chart check, (g) sequential and iterative process Influence of upstream and downstream operations: (a) simulation, (b) immobilization, (c) motion management, (d) QA, (e) IGRT, (f) Treatment delivery, (g) SBRT/SRS (h) adaptive planning Reduction of delay between planning steps with Lean systems due to (a) communication, (b) limited resource, (b) contour, (c) plan approval, (d) treatment. Optimizing planning processes: (a) contour validation (b) consistent planning protocol, (c) protocol/template sharing, (d) semi

  16. A moment-based approach for DVH-guided radiotherapy treatment plan optimization

    Science.gov (United States)

    Zarepisheh, M.; Shakourifar, M.; Trigila, G.; Ghomi, P. S.; Couzens, S.; Abebe, A.; Noreña, L.; Shang, W.; Jiang, Steve B.; Zinchenko, Y.

    2013-03-01

    The dose-volume histogram (DVH) is a clinically relevant criterion to evaluate the quality of a treatment plan. It is hence desirable to incorporate DVH constraints into treatment plan optimization for intensity modulated radiation therapy. Yet, the direct inclusion of the DVH constraints into a treatment plan optimization model typically leads to great computational difficulties due to the non-convex nature of these constraints. To overcome this critical limitation, we propose a new convex-moment-based optimization approach. Our main idea is to replace the non-convex DVH constraints by a set of convex moment constraints. In turn, the proposed approach is able to generate a Pareto-optimal plan whose DVHs are close to, or if possible even outperform, the desired DVHs. In particular, our experiment on a prostate cancer patient case demonstrates the effectiveness of this approach by employing two and three moment formulations to approximate the desired DVHs.

  17. Three-Dimensional Dose Optimization for Noncoplanar Treatment Planning with Conformal Fields.

    Science.gov (United States)

    Ma, Ying-Chang L.

    1990-01-01

    Recent advances in imaging techniques, especially three dimensional reconstruction of CT images, have made precision tumor localization feasible. These imaging techniques along with developments in computer controlled radiation treatment machines have provided an important thrust in developing better techniques for cancer treatment. This often requires a complex noncoplanar beam arrangements and elaborate treatment planning, which, unfortunately, are time consuming, costly and dependent on operator expertise and experience. A reliable operator-independent dose optimization tool is therefore desirable, especially for 3D treatment planning. In this dissertation, several approaches (linear programming, quadratic programming, and direct search methods) of computer optimization using various criteria including least sire fitting on the 90% isodose to target periphery, dose uniformity, and integral dose are presented. All of these methods are subject to restrictions on the upper limit of the dose to critical organs. In the quadratic programming approach, Kuhn-Tucker theory was employed to convert the quadratic problem into one which permits application of the very powerful, revised simplex method. Several examples are used to analyze the effectiveness of these dose optimization approaches. The studies show that the quadratic programming approach with the criteria of least square fitting and critical organ constraints is superior in efficiency for dose optimization in 3D treatment planning, particularly for cases with a large number of beams. Use of least square fitting allows one to deduce optimized plans for irregularly shaped targets by employing a multi-isocentric technique. Our studies also illustrate the advantages of using irregular conformal fields, optimized beam energy, and noncoplanar beam arrangements in contrast to the conventional treatment which uses a symmetrical rectangular collimator, fixed beam energy, and coplanar beam arrangements. Optimized plans can

  18. A comparison of inverse optimization algorithms for HDR/PDR prostate brachytherapy treatment planning.

    Science.gov (United States)

    Dinkla, Anna M; van der Laarse, Rob; Kaljouw, Emmie; Pieters, Bradley R; Koedooder, Kees; van Wieringen, Niek; Bel, Arjan

    2015-01-01

    Graphical optimization (GrO) is a common method for high-dose-rate/pulsed-dose-rate (PDR) prostate brachytherapy treatment planning. New methods performing inverse optimization of the dose distribution have been developed over the past years. The purpose is to compare GrO and two established inverse methods, inverse planning simulated annealing (IPSA) and hybrid inverse treatment planning and optimization (HIPO), and one new method, enhanced geometric optimization-interactive inverse planning (EGO-IIP), in terms of speed and dose-volume histogram (DVH) parameters. For 26 prostate cancer patients treated with a PDR brachytherapy boost, an experienced treatment planner optimized the dose distributions using four different methods: GrO, IPSA, HIPO, and EGO-IIP. Relevant DVH parameters (prostate-V100%, D90%, V150%; urethra-D(0.1cm3) and D(1.0cm3); rectum-D(0.1cm3) and D(2.0cm3); bladder-D(2.0cm3)) were evaluated and their compliance to the constraints. Treatment planning time was also recorded. All inverse methods resulted in shorter planning time (mean, 4-6.7 min), as compared with GrO (mean, 7.6 min). In terms of DVH parameters, none of the inverse methods outperformed the others. However, all inverse methods improved on compliance to the planning constraints as compared with GrO. On average, EGO-IIP and GrO resulted in highest D90%, and the IPSA plans resulted in lowest bladder D2.0cm3 and urethra D(1.0cm3). Inverse planning methods decrease planning time as compared with GrO for PDR/high-dose-rate prostate brachytherapy. DVH parameters are comparable for all methods. Copyright © 2015 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.

  19. Evaluation of plan quality assurance models for prostate cancer patients based on fully automatically generated Pareto-optimal treatment plans

    Science.gov (United States)

    Wang, Yibing; Breedveld, Sebastiaan; Heijmen, Ben; Petit, Steven F.

    2016-06-01

    IMRT planning with commercial Treatment Planning Systems (TPSs) is a trial-and-error process. Consequently, the quality of treatment plans may not be consistent among patients, planners and institutions. Recently, different plan quality assurance (QA) models have been proposed, that could flag and guide improvement of suboptimal treatment plans. However, the performance of these models was validated using plans that were created using the conventional trail-and-error treatment planning process. Consequently, it is challenging to assess and compare quantitatively the accuracy of different treatment planning QA models. Therefore, we created a golden standard dataset of consistently planned Pareto-optimal IMRT plans for 115 prostate patients. Next, the dataset was used to assess the performance of a treatment planning QA model that uses the overlap volume histogram (OVH). 115 prostate IMRT plans were fully automatically planned using our in-house developed TPS Erasmus-iCycle. An existing OVH model was trained on the plans of 58 of the patients. Next it was applied to predict DVHs of the rectum, bladder and anus of the remaining 57 patients. The predictions were compared with the achieved values of the golden standard plans for the rectum D mean, V 65, and V 75, and D mean of the anus and the bladder. For the rectum, the prediction errors (predicted-achieved) were only  -0.2  ±  0.9 Gy (mean  ±  1 SD) for D mean,-1.0  ±  1.6% for V 65, and  -0.4  ±  1.1% for V 75. For D mean of the anus and the bladder, the prediction error was 0.1  ±  1.6 Gy and 4.8  ±  4.1 Gy, respectively. Increasing the training cohort to 114 patients only led to minor improvements. A dataset of consistently planned Pareto-optimal prostate IMRT plans was generated. This dataset can be used to train new, and validate and compare existing treatment planning QA models, and has been made publicly available. The OVH model was highly accurate

  20. SU-D-BRD-01: Cloud-Based Radiation Treatment Planning: Performance Evaluation of Dose Calculation and Plan Optimization

    Energy Technology Data Exchange (ETDEWEB)

    Na, Y; Kapp, D; Kim, Y; Xing, L [Stanford University School of Medicine, Stanford, CA (United States); Suh, T [Catholic UniversityMedical College, Seoul, Seoul (Korea, Republic of)

    2014-06-01

    Purpose: To report the first experience on the development of a cloud-based treatment planning system and investigate the performance improvement of dose calculation and treatment plan optimization of the cloud computing platform. Methods: A cloud computing-based radiation treatment planning system (cc-TPS) was developed for clinical treatment planning. Three de-identified clinical head and neck, lung, and prostate cases were used to evaluate the cloud computing platform. The de-identified clinical data were encrypted with 256-bit Advanced Encryption Standard (AES) algorithm. VMAT and IMRT plans were generated for the three de-identified clinical cases to determine the quality of the treatment plans and computational efficiency. All plans generated from the cc-TPS were compared to those obtained with the PC-based TPS (pc-TPS). The performance evaluation of the cc-TPS was quantified as the speedup factors for Monte Carlo (MC) dose calculations and large-scale plan optimizations, as well as the performance ratios (PRs) of the amount of performance improvement compared to the pc-TPS. Results: Speedup factors were improved up to 14.0-fold dependent on the clinical cases and plan types. The computation times for VMAT and IMRT plans with the cc-TPS were reduced by 91.1% and 89.4%, respectively, on average of the clinical cases compared to those with pc-TPS. The PRs were mostly better for VMAT plans (1.0 ≤ PRs ≤ 10.6 for the head and neck case, 1.2 ≤ PRs ≤ 13.3 for lung case, and 1.0 ≤ PRs ≤ 10.3 for prostate cancer cases) than for IMRT plans. The isodose curves of plans on both cc-TPS and pc-TPS were identical for each of the clinical cases. Conclusion: A cloud-based treatment planning has been setup and our results demonstrate the computation efficiency of treatment planning with the cc-TPS can be dramatically improved while maintaining the same plan quality to that obtained with the pc-TPS. This work was supported in part by the National Cancer Institute (1

  1. Maximizing dosimetric benefits of IMRT in the treatment of localized prostate cancer through multicriteria optimization planning

    Energy Technology Data Exchange (ETDEWEB)

    Wala, Jeremiah; Craft, David [Harvard Medical School, Boston, MA (United States); Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA (United States); Paly, Jon [Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA (United States); Zietman, Anthony [Harvard Medical School, Boston, MA (United States); Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA (United States); Efstathiou, Jason, E-mail: jefstathiou@partners.org [Harvard Medical School, Boston, MA (United States); Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA (United States)

    2013-10-01

    We examine the quality of plans created using multicriteria optimization (MCO) treatment planning in intensity-modulated radiation therapy (IMRT) in treatment of localized prostate cancer. Nine random cases of patients receiving IMRT to the prostate were selected. Each case was associated with a clinically approved plan created using Corvus. The cases were replanned using MCO-based planning in RayStation. Dose-volume histogram data from both planning systems were presented to 2 radiation oncologists in a blinded evaluation, and were compared at a number of dose-volume points. Both physicians rated all 9 MCO plans as superior to the clinically approved plans (p<10{sup −5}). Target coverage was equivalent (p = 0.81). Maximum doses to the prostate and bladder and the V50 and V70 to the anterior rectum were reduced in all MCO plans (p<0.05). Treatment planning time with MCO took approximately 60 minutes per case. MCO-based planning for prostate IMRT is efficient and produces high-quality plans with good target homogeneity and sparing of the anterior rectum, bladder, and femoral heads, without sacrificing target coverage.

  2. Robustness of IPSA optimized high-dose-rate prostate brachytherapy treatment plans to catheter displacements

    Science.gov (United States)

    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

  3. Robustness of IPSA optimized high-dose-rate prostate brachytherapy treatment plans to catheter displacements.

    Science.gov (United States)

    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.

  4. Patient specific optimization-based treatment planning for catheter-based ultrasound hyperthermia and thermal ablation

    Science.gov (United States)

    Prakash, Punit; Chen, Xin; Wootton, Jeffery; Pouliot, Jean; Hsu, I.-Chow; Diederich, Chris J.

    2009-02-01

    A 3D optimization-based thermal treatment planning platform has been developed for the application of catheter-based ultrasound hyperthermia in conjunction with high dose rate (HDR) brachytherapy for treating advanced pelvic tumors. Optimal selection of applied power levels to each independently controlled transducer segment can be used to conform and maximize therapeutic heating and thermal dose coverage to the target region, providing significant advantages over current hyperthermia technology and improving treatment response. Critical anatomic structures, clinical target outlines, and implant/applicator geometries were acquired from sequential multi-slice 2D images obtained from HDR treatment planning and used to reconstruct patient specific 3D biothermal models. A constrained optimization algorithm was devised and integrated within a finite element thermal solver to determine a priori the optimal applied power levels and the resulting 3D temperature distributions such that therapeutic heating is maximized within the target, while placing constraints on maximum tissue temperature and thermal exposure of surrounding non-targeted tissue. This optimizationbased treatment planning and modeling system was applied on representative cases of clinical implants for HDR treatment of cervix and prostate to evaluate the utility of this planning approach. The planning provided significant improvement in achievable temperature distributions for all cases, with substantial increase in T90 and thermal dose (CEM43T90) coverage to the hyperthermia target volume while decreasing maximum treatment temperature and reducing thermal dose exposure to surrounding non-targeted tissues and thermally sensitive rectum and bladder. This optimization based treatment planning platform with catheter-based ultrasound applicators is a useful tool that has potential to significantly improve the delivery of hyperthermia in conjunction with HDR brachytherapy. The planning platform has been extended

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

    CERN Document Server

    Yarmand, Hamed

    2013-01-01

    Stereotactic body radiotherapy (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 since 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 simultaneously, 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 m...

  6. Radiobiological effect based treatment plan optimization with the linear quadratic model

    Energy Technology Data Exchange (ETDEWEB)

    Schell, Stefan; Wilkens, Jan J.; Oelfke, Uwe [German Cancer Research Center, Heidelberg (Germany). Dept. of Medical Physics in Radiation Oncology

    2010-07-01

    As an approach towards more biology-oriented treatment planning for external beam radiation therapy, we present the incorporation of local radiation damage models into three dimensional treatment planning. This allows effect based instead of dose based plan optimization which could potentially better match the biologically relevant tradeoff between target and normal tissues. In particular, our approach facilitates an effective comparison of different fractionation schemes. It is based on the linear quadratic model to describe the biological radiation effect. Effect based optimization was integrated into our inverse treatment planning software KonRad, and we demonstrate the resulting differences between conventional and biological treatment planning. Radiation damage can be analyzed both qualitatively and quantitatively in dependence of the fractionation scheme and tissue specific parameters in a three dimensional voxel based system. As an example the potential advantages as well as the associated risks of hypofractionation for prostate cancer are analyzed and visualized with the help of effective dose volume histograms. Our results suggest a very conservative view regarding alternative fractionation schemes since uncertainties in biological parameters are still too big to make reliable clinical predictions. (orig.)

  7. An exact approach to direct aperture optimization in IMRT treatment planning

    Energy Technology Data Exchange (ETDEWEB)

    Men Chunhua [Department of Industrial and Systems Engineering, University of Florida, Gainesville, Florida 32611-6595 (United States); Romeijn, H Edwin [Department of Industrial and Systems Engineering, University of Florida, Gainesville, Florida 32611-6595 (United States); Taskin, Z Caner [Department of Industrial and Systems Engineering, University of Florida, Gainesville, Florida 32611-6595 (United States); Dempsey, James F [Department of Radiation Oncology, University of Florida, Gainesville, Florida 32610-0385 (United States)

    2007-12-21

    We consider the problem of intensity-modulated radiation therapy (IMRT) treatment planning using direct aperture optimization. While this problem has been relatively well studied in recent years, most approaches employ a heuristic approach to the generation of apertures. In contrast, we use an exact approach that explicitly formulates the fluence map optimization (FMO) problem as a convex optimization problem in terms of all multileaf collimator (MLC) deliverable apertures and their associated intensities. However, the number of deliverable apertures, and therefore the number of decision variables and constraints in the new problem formulation, is typically enormous. To overcome this, we use an iterative approach that employs a subproblem whose optimal solution either provides a suitable aperture to add to a given pool of allowable apertures or concludes that the current solution is optimal. We are able to handle standard consecutiveness, interdigitation and connectedness constraints that may be imposed by the particular MLC system used, as well as jaws-only delivery. Our approach has the additional advantage that it can explicitly account for transmission of dose through the part of an aperture that is blocked by the MLC system, yielding a more precise assessment of the treatment plan than what is possible using a traditional beamlet-based FMO problem. Finally, we develop and test two stopping rules that can be used to identify treatment plans of high clinical quality that are deliverable very efficiently. Tests on clinical head-and-neck cancer cases showed the efficacy of our approach, yielding treatment plans comparable in quality to plans obtained by the traditional method with a reduction of more than 75% in the number of apertures and a reduction of more than 50% in beam-on time, with only a modest increase in computational effort. The results also show that delivery efficiency is very insensitive to the addition of traditional MLC constraints; however, jaws

  8. Comment on genetic and global algorithms for optimization of three-dimensional conformal radiotherapy treatment planning

    Energy Technology Data Exchange (ETDEWEB)

    Vaarkamp, Jaap [Joint Department of Physics, Royal Marsden NHS Trust, Sutton, Surrey (United Kingdom). E-mail: jaap@icr.ac.uk

    2001-06-01

    Full text: I would like to make four comments on three papers by two authors (Wu and Zhu 2000, 2001, Wu et al 2000) on one topic: optimization of 3D conformal radiotherapy treatment planning. In the papers, genetic and global algorithms are proposed for this optimization, and the authors claim to be able to generate better treatment plans than those produced manually and used for patient treatment (Wu and Zhu 2000). However, the data in the papers do not warrant such a conclusion and the work contains such serious methodological flaws that only the opposite can have been true. First, in the papers a few treatment plans for patients with different brain tumours are discussed. Dose volume histograms (DVHs) are presented for the target, sometimes the planning target volume, sometimes the clinical target volume, and the organs at risk (OARs): left and right eye, and thyroid or spinal cord. However, other OARs limit dose more in clinical treatment planning, and it is those OARs to which the planner must direct all effort when optimizing the treatment plan. One such important OAR when treating children is the temporal lobes because the dose to the temporal lobes has been associated with a reduction in IQ points (Fuss et al 2000). Also particularly important when treating children are the hypothalamus and pituitary, because they influence growth and the further hormonal development (Schmiegelow et al 1999, 2000). Furthermore, rather than the eyes themselves, the optic chiasm usually gets more serious attention (Fuss et al 1999) and is considered so important that it is often blocked from the treatment fields during the final fractions, thus compromising dose homogeneity in the target. Finally, irradiating the auditory apparatus can lead to a loss of hearing (Lin et al 2000), and, in particular when one side receives a high dose, every effort is made to at least spare the other side. Hence, it is not surprising to find a treatment plan that is superior in some of the

  9. Treatment planning, optimization, and beam delivery technqiues for intensity modulated proton therapy

    Science.gov (United States)

    Sengbusch, Evan R.

    Physical properties of proton interactions in matter give them a theoretical advantage over photons in radiation therapy for cancer treatment, but they are seldom used relative to photons. The primary barriers to wider acceptance of proton therapy are the technical feasibility, size, and price of proton therapy systems. Several aspects of the proton therapy landscape are investigated, and new techniques for treatment planning, optimization, and beam delivery are presented. The results of these investigations suggest a means by which proton therapy can be delivered more efficiently, effectively, and to a much larger proportion of eligible patients. An analysis of the existing proton therapy market was performed. Personal interviews with over 30 radiation oncology leaders were conducted with regard to the current and future use of proton therapy. In addition, global proton therapy market projections are presented. The results of these investigations serve as motivation and guidance for the subsequent development of treatment system designs and treatment planning, optimization, and beam delivery methods. A major factor impacting the size and cost of proton treatment systems is the maximum energy of the accelerator. Historically, 250 MeV has been the accepted value, but there is minimal quantitative evidence in the literature that supports this standard. A retrospective study of 100 patients is presented that quantifies the maximum proton kinetic energy requirements for cancer treatment, and the impact of those results with regard to treatment system size, cost, and neutron production is discussed. This study is subsequently expanded to include 100 cranial stereotactic radiosurgery (SRS) patients, and the results are discussed in the context of a proposed dedicated proton SRS treatment system. Finally, novel proton therapy optimization and delivery techniques are presented. Algorithms are developed that optimize treatment plans over beam angle, spot size, spot spacing

  10. Fast thermal simulations and temperature optimization for hyperthermia treatment planning, including realistic 3D vessel networks.

    Science.gov (United States)

    Kok, H P; van den Berg, C A T; Bel, A; Crezee, J

    2013-10-01

    Accurate thermal simulations in hyperthermia treatment planning require discrete modeling of large blood vessels. The very long computation time of the finite difference based DIscrete VAsculature model (DIVA) developed for this purpose is impractical for clinical applications. In this work, a fast steady-state thermal solver was developed for simulations with realistic 3D vessel networks. Additionally, an efficient temperature-based optimization method including the thermal effect of discrete vasculature was developed. The steady-state energy balance for vasculature and tissue was described by a linear system, which was solved with an iterative method on the graphical processing unit. Temperature calculations during optimization were performed by superposition of several precomputed temperature distributions, calculated with the developed thermal solver. The thermal solver and optimization were applied to a human anatomy, with the prostate being the target region, heated with the eight waveguide 70 MHz AMC-8 system. Realistic 3D pelvic vasculature was obtained from angiography. Both the arterial and venous vessel networks consisted of 174 segments and 93 endpoints with a diameter of 1.2 mm. Calculation of the steady-state temperature distribution lasted about 3.3 h with the original DIVA model, while the newly developed method took only ≈ 1-1.5 min. Temperature-based optimization with and without taking the vasculature into account showed differences in optimized waveguide power of more than a factor 2 and optimized tumor T90 differed up to ≈ 0.5°C. This shows the necessity to take discrete vasculature into account during optimization. A very fast method was developed for thermal simulations with realistic 3D vessel networks. The short simulation time allows online calculations and makes temperature optimization with realistic vasculature feasible, which is an important step forward in hyperthermia treatment planning.

  11. Single versus multichannel applicator in high-dose-rate vaginal brachytherapy optimized by inverse treatment planning.

    Science.gov (United States)

    Bahadur, Yasir A; Constantinescu, Camelia; Hassouna, Ashraf H; Eltaher, Maha M; Ghassal, Noor M; Awad, Nesreen A

    2015-01-01

    To retrospectively compare the potential dosimetric advantages of a multichannel vaginal applicator vs. a single channel one in intracavitary vaginal high-dose-rate (HDR) brachytherapy after hysterectomy, and evaluate the dosimetric advantage of fractional re-planning. We randomly selected 12 patients with endometrial carcinoma, who received adjuvant vaginal cuff HDR brachytherapy using a multichannel applicator. For each brachytherapy fraction, two inverse treatment plans (for central channel and multichannel loadings) were performed and compared. The advantage of fractional re-planning was also investigated. Dose-volume-histogram (DVH) analysis showed limited, but statistically significant difference (p = 0.007) regarding clinical-target-volume dose coverage between single and multichannel approaches. For the organs-at-risk rectum and bladder, the use of multichannel applicator demonstrated a noticeable dose reduction, when compared to single channel, but statistically significant for rectum only (p = 0.0001). For D2cc of rectum, an average fractional dose of 6.1 ± 0.7 Gy resulted for single channel vs. 5.1 ± 0.6 Gy for multichannel. For D2cc of bladder, an average fractional dose of 5 ± 0.9 Gy occurred for single channel vs. 4.9 ± 0.8 Gy for multichannel. The dosimetric benefit of fractional re-planning was demonstrated: DVH analysis showed large, but not statistically significant differences between first fraction plan and fractional re-planning, due to large inter-fraction variations for rectum and bladder positioning and filling. Vaginal HDR brachytherapy using a multichannel vaginal applicator and inverse planning provides dosimetric advantages over single channel cylinder, by reducing the dose to organs at risk without compromising the target volume coverage, but at the expense of an increased vaginal mucosa dose. Due to large inter-fraction dose variations, we recommend individual fraction treatment plan optimization.

  12. [Impact of optimization algorithms on the intensity map in IMRT treatment planning.].

    Science.gov (United States)

    Shimada, Mari; Nakamura, Mitsuhiro; Miyabe, Yuki; Yamamoto, Tokihiro; Teshima, Teruki; Narita, Yuichiro; Mizowaki, Takashi; Nagata, Yasushi; Hiraoka, Masahiro

    2006-01-01

    In inverse planning of IMRT, optimum intensity maps are generated using an optimization algorithm. In this paper, impacts of two different optimization algorithms on the intensity map in IMRT treatment planning were evaluated. These were from the steepest descent (SD) and simulated annealing (SA) methods. The following five patterns were compared: [1] SD with calculation time of 5 min; [2] SD with the terminal criterion based on cost function; [3] SA with calculation time of 5 min; [4] SA with the terminal criterion; and [5] SA with the terminal criterion using a smoothing filter. Differences of D(95%) for the planning target volume, V(70Gy) for the rectum wall and the bladder wall were up to 0.5, 1.8 and 3.2 %, respectively in all patterns. The dosimetric impact was negligible. In contrast, generated intensity maps were sensitive to the algorithms. Intensity maps generated by SA tended to have much fluctuation due to numerical artifacts compared to those generated by SD. The difference in the profile was over 7 % between the algorithms. The smoothing filter decreased the fluctuation in intensity maps of SA. In conclusion, it is important to understand impacts of optimization algorithms on the intensity map and the dose distribution.

  13. Optimization of prostate cancer treatment plans using the adjoint transport method and discrete ordinates codes

    Energy Technology Data Exchange (ETDEWEB)

    Yoo, S.; Henderson, D.L. [Dept. of Medical Physics, Madison, WI (United States); Thomadsen, B.R. [Dept. of Medical Physics and Dept. of Human Oncology, Madison (United States)

    2001-07-01

    Interstitial brachytherapy is a type of radiation in which radioactive sources are implanted directly into cancerous tissue. Determination of dose delivered to tissue by photons emitted from implanted seeds is an important step in the treatment plan process. In this paper we will investigate the use of the discrete ordinates method and the adjoint method to calculate absorbed dose in the regions of interest. MIP (mixed-integer programming) is used to determine the optimal seed distribution that conforms the prescribed dose to the tumor and delivers minimal dose to the sensitive structures. The patient treatment procedure consists of three steps: (1) image acquisition with the transrectal ultrasound (TRUS) and assessing the region of interest, (2) adjoint flux computation with discrete ordinate code for inverse dose calculation, and (3) optimization with the MIP branch-and-bound method.

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

    Energy Technology Data Exchange (ETDEWEB)

    Yan Di; Liang Jian [Department of Radiation Oncology, Beaumont Health System, Royal Oak, Michigan 48073 (United States)

    2013-02-15

    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 to 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

  15. Ultra-fast treatment plan optimization for volumetric modulated arc therapy (VMAT)

    CERN Document Server

    Men, Chunhua; Jia, Xun; Jiang, Steve B

    2010-01-01

    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. We consider a cost function consisting two terms, the first which enforces a desired dose distribution while the second guarantees a smooth dose rate variation between successive gantry angles. At each iteration of the column generation method, a subproblem is first solved to generate one more deliverable MLC aperture which potentially decreases the cost function most effectively. A subsequent master problem is then solved to determine the dose rate at all currently generated apertures by minimizing the cost function. The iteration of such an algorithm yields a set of deliverable apertures, as well as dose rates, at all gantry angles. Results: The algorithm was preliminarily tested on five prostate and five head-a...

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

    Science.gov (United States)

    Yarmand, Hamed; Winey, Brian; Craft, David

    2013-09-07

    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.

  17. WE-B-304-02: Treatment Planning Evaluation and Optimization Should Be Biologically and Not Dose/volume Based

    Energy Technology Data Exchange (ETDEWEB)

    Deasy, J. [Memorial Sloan Kettering Cancer Center, New York, NY (United States)

    2015-06-15

    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 by 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.

  18. WE-B-304-01: Treatment Planning Evaluation and Optimization Should Be Dose/volume and Not Biologically Based

    Energy Technology Data Exchange (ETDEWEB)

    Mayo, C. [Mayo Clinic (United States)

    2015-06-15

    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 by 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.

  19. Evaluation of the generalized gamma as a tool for treatment planning optimization

    Directory of Open Access Journals (Sweden)

    Emmanouil I Petrou

    2014-12-01

    independent software. Furthermore, it was proved that after a small change in dose, the organ that is being affected most is the organ with the highest Generalized Gamma. Apart from that, the validity of the theoretical expressions that describe the change in response and the associated Generalized Gamma was verified but only for the case of small change in dose. Especially for the case of 50% TCP and NTCP, the theoretical values (ΔPapprox. and those calculated by the RayStation show close agreement, which proves the high importance of the D50 parameter in specifying clinical response levels. Finally, the presented findings show that the behavior of ΔPapprox. looks sensible because, for both of the models that were used (Poisson and Probit, it significantly approaches the real ΔP around the region of 37% and 50% response. The present study managed to evaluate the mathematical expression of Generalized Gamma for the case of non-uniform dose delivery and the accuracy of the RayStation to calculate its values for different organs. Conclusion: A very important finding of this work is the establishment of the usefulness and clinical relevance of Generalized Gamma. That is because it gives the planner the opportunity to precisely determine which organ will be affected most after a small increase in dose and as a result an optimal treatment plan regarding tumor control and normal tissue complications can be found.

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

    Energy Technology Data Exchange (ETDEWEB)

    Chi, Y; Li, Y; Tian, Z; Gu, X; Jiang, S; Jia, X [UT Southwestern Medical Center, Dallas, TX (United States)

    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 was 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.

  1. The Adjoint Method for The Optimization of Brachytherapy and Radiotherapy Patient Treatment Planning Procedures Using Monte Carlo Calculations

    Energy Technology Data Exchange (ETDEWEB)

    D.L. Henderson; S. Yoo; M. Kowalok; T.R. Mackie; B.R. Thomadsen

    2001-10-30

    The goal of this project is to investigate the use of the adjoint method, commonly used in the reactor physics community, for the optimization of radiation therapy patient treatment plans. Two different types of radiation therapy are being examined, interstitial brachytherapy and radiotherapy. In brachytherapy radioactive sources are surgically implanted within the diseased organ such as the prostate to treat the cancerous tissue. With radiotherapy, the x-ray source is usually located at a distance of about 1-metere from the patient and focused on the treatment area. For brachytherapy the optimization phase of the treatment plan consists of determining the optimal placement of the radioactive sources, which delivers the prescribed dose to the disease tissue while simultaneously sparing (reducing) the dose to sensitive tissue and organs. For external beam radiation therapy the optimization phase of the treatment plan consists of determining the optimal direction and intensity of beam, which provides complete coverage of the tumor region with the prescribed dose while simultaneously avoiding sensitive tissue areas. For both therapy methods, the optimal treatment plan is one in which the diseased tissue has been treated with the prescribed dose and dose to the sensitive tissue and organs has been kept to a minimum.

  2. Organ sample generator for expected treatment dose construction and adaptive inverse planning optimization

    Energy Technology Data Exchange (ETDEWEB)

    Nie Xiaobo; Liang Jian; Yan Di [Department of Radiation Oncology, Beaumont Health System, Royal Oak, Michigan 48073 (United States)

    2012-12-15

    Purpose: To create an organ sample generator (OSG) for expected treatment dose construction and adaptive inverse planning optimization. The OSG generates random samples of organs of interest from a distribution obeying the patient specific organ variation probability density function (PDF) during the course of adaptive radiotherapy. Methods: Principle component analysis (PCA) and a time-varying least-squares regression (LSR) method were used on patient specific geometric variations of organs of interest manifested on multiple daily volumetric images obtained during the treatment course. The construction of the OSG includes the determination of eigenvectors of the organ variation using PCA, and the determination of the corresponding coefficients using time-varying LSR. The coefficients can be either random variables or random functions of the elapsed treatment days depending on the characteristics of organ variation as a stationary or a nonstationary random process. The LSR method with time-varying weighting parameters was applied to the precollected daily volumetric images to determine the function form of the coefficients. Eleven h and n cancer patients with 30 daily cone beam CT images each were included in the evaluation of the OSG. The evaluation was performed using a total of 18 organs of interest, including 15 organs at risk and 3 targets. Results: Geometric variations of organs of interest during h and n cancer radiotherapy can be represented using the first 3 {approx} 4 eigenvectors. These eigenvectors were variable during treatment, and need to be updated using new daily images obtained during the treatment course. The OSG generates random samples of organs of interest from the estimated organ variation PDF of the individual. The accuracy of the estimated PDF can be improved recursively using extra daily image feedback during the treatment course. The average deviations in the estimation of the mean and standard deviation of the organ variation PDF for h

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

    Science.gov (United States)

    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.

  4. Optimization of beam angles for intensity modulated radiation therapy treatment planning using genetic algorithm on a distributed computing platform.

    Science.gov (United States)

    Nazareth, Daryl P; Brunner, Stephen; Jones, Matthew D; Malhotra, Harish K; Bakhtiari, Mohammad

    2009-07-01

    Planning intensity modulated radiation therapy (IMRT) treatment involves selection of several angle parameters as well as specification of structures and constraints employed in the optimization process. Including these parameters in the combinatorial search space vastly increases the computational burden, and therefore the parameter selection is normally performed manually by a clinician, based on clinical experience. We have investigated the use of a genetic algorithm (GA) and distributed-computing platform to optimize the gantry angle parameters and provide insight into additional structures, which may be necessary, in the dose optimization process to produce optimal IMRT treatment plans. For an IMRT prostate patient, we produced the first generation of 40 samples, each of five gantry angles, by selecting from a uniform random distribution, subject to certain adjacency and opposition constraints. Dose optimization was performed by distributing the 40-plan workload over several machines running a commercial treatment planning system. A score was assigned to each resulting plan, based on how well it satisfied clinically-relevant constraints. The second generation of 40 samples was produced by combining the highest-scoring samples using techniques of crossover and mutation. The process was repeated until the sixth generation, and the results compared with a clinical (equally-spaced) gantry angle configuration. In the sixth generation, 34 of the 40 GA samples achieved better scores than the clinical plan, with the best plan showing an improvement of 84%. Moreover, the resulting configuration of beam angles tended to cluster toward the patient's sides, indicating where the inclusion of additional structures in the dose optimization process may avoid dose hot spots. Additional parameter selection in IMRT leads to a large-scale computational problem. We have demonstrated that the GA combined with a distributed-computing platform can be applied to optimize gantry angle

  5. Multicriteria optimization informed VMAT planning

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Huixiao; Craft, David L.; Gierga, David P., E-mail: dgierga@partners.org

    2014-04-01

    We developed a patient-specific volumetric-modulated arc therapy (VMAT) optimization procedure using dose-volume histogram (DVH) information from multicriteria optimization (MCO) of intensity-modulated radiotherapy (IMRT) plans. The study included 10 patients with prostate cancer undergoing standard fractionation treatment, 10 patients with prostate cancer undergoing hypofractionation treatment, and 5 patients with head/neck cancer. MCO-IMRT plans using 20 and 7 treatment fields were generated for each patient on the RayStation treatment planning system (clinical version 2.5, RaySearch Laboratories, Stockholm, Sweden). The resulting DVH of the 20-field MCO-IMRT plan for each patient was used as the reference DVH, and the extracted point values of the resulting DVH of the MCO-IMRT plan were used as objectives and constraints for VMAT optimization. Weights of objectives or constraints of VMAT optimization or both were further tuned to generate the best match with the reference DVH of the MCO-IMRT plan. The final optimal VMAT plan quality was evaluated by comparison with MCO-IMRT plans based on homogeneity index, conformity number of planning target volume, and organ at risk sparing. The influence of gantry spacing, arc number, and delivery time on VMAT plan quality for different tumor sites was also evaluated. The resulting VMAT plan quality essentially matched the 20-field MCO-IMRT plan but with a shorter delivery time and less monitor units. VMAT plan quality of head/neck cancer cases improved using dual arcs whereas prostate cases did not. VMAT plan quality was improved by fine gantry spacing of 2 for the head/neck cancer cases and the hypofractionation-treated prostate cancer cases but not for the standard fractionation–treated prostate cancer cases. MCO-informed VMAT optimization is a useful and valuable way to generate patient-specific optimal VMAT plans, though modification of the weights of objectives or constraints extracted from resulting DVH of MCO

  6. Multicriteria optimization informed VMAT planning.

    Science.gov (United States)

    Chen, Huixiao; Craft, David L; Gierga, David P

    2014-01-01

    We developed a patient-specific volumetric-modulated arc therapy (VMAT) optimization procedure using dose-volume histogram (DVH) information from multicriteria optimization (MCO) of intensity-modulated radiotherapy (IMRT) plans. The study included 10 patients with prostate cancer undergoing standard fractionation treatment, 10 patients with prostate cancer undergoing hypofractionation treatment, and 5 patients with head/neck cancer. MCO-IMRT plans using 20 and 7 treatment fields were generated for each patient on the RayStation treatment planning system (clinical version 2.5, RaySearch Laboratories, Stockholm, Sweden). The resulting DVH of the 20-field MCO-IMRT plan for each patient was used as the reference DVH, and the extracted point values of the resulting DVH of the MCO-IMRT plan were used as objectives and constraints for VMAT optimization. Weights of objectives or constraints of VMAT optimization or both were further tuned to generate the best match with the reference DVH of the MCO-IMRT plan. The final optimal VMAT plan quality was evaluated by comparison with MCO-IMRT plans based on homogeneity index, conformity number of planning target volume, and organ at risk sparing. The influence of gantry spacing, arc number, and delivery time on VMAT plan quality for different tumor sites was also evaluated. The resulting VMAT plan quality essentially matched the 20-field MCO-IMRT plan but with a shorter delivery time and less monitor units. VMAT plan quality of head/neck cancer cases improved using dual arcs whereas prostate cases did not. VMAT plan quality was improved by fine gantry spacing of 2 for the head/neck cancer cases and the hypofractionation-treated prostate cancer cases but not for the standard fractionation-treated prostate cancer cases. MCO-informed VMAT optimization is a useful and valuable way to generate patient-specific optimal VMAT plans, though modification of the weights of objectives or constraints extracted from resulting DVH of MCO-IMRT or

  7. SU-E-T-555: A Protontherapy Inverse Treatment Planning System Prototype with Linear Energy Transfer (LET) Optimization

    Energy Technology Data Exchange (ETDEWEB)

    Sanchez-Parcerisa, D; Carabe-Fernandez, A [Department of Radiation Oncology, Hospital of the University of Pennsylvania, Philadelphia, PA (United States)

    2014-06-01

    Purpose: Develop and benchmark an inverse treatment planning system (TPS) for proton radiotherapy integrating fast analytical dose and LET calculations in patient geometries and a dual objective function with both dose and LET components, enabling us to apply optimization techniques to improve the predicted outcome of treatments based on radiobiological models. Methods: The software package was developed in MATLAB and implements a fluence-dose calculation technique based on a pencil beam model for dose calculations and a 3D LET model based on the extension of the LET in the radial direction as a function of the predicted radiological pathway. Both models were benchmarked against commissioning data from our institution, dose calculations performed with a commercial treatment planning system and Monte Carlo simulations. The optimization is based on the adaptive simulated annealing approach . Results: The dose and LET calculations were tested in a water phantom and several real patient treatments. The pass rate for the gamma index analysis (3%/3mm) test was above 90% for all test cases analyzed, and the calculation time was of the order of seconds. The inverse planning module produced plans with a significantly higher mean LET in the target compared to traditional plans, without any loss of target coverage. The clinical relevance of this improvement is under consideration . Conclusion: The developed treatment planning system is a valuable clinical and research tool that enables us to incorporate LET effects into proton radiotherapy planning in a streamlined fashion.

  8. Treatment planning considerations in contrast-enhanced radiotherapy: energy and beam aperture optimization

    Energy Technology Data Exchange (ETDEWEB)

    Garnica-Garza, H M, E-mail: hgarnica@cinvestav.mx [Centro de Investigacion y de Estudios Avanzados del Instituto Politecnico Nacional Unidad Monterrey, Via del Conocimiento 201 Parque de Investigacion e Innovacion Tecnologica, Apodaca NL CP 66600 (Mexico)

    2011-01-21

    It has been shown that the use of kilovoltage x-rays in conjunction with a contrast agent incorporated into the tumor can lead to acceptable treatment plans with regard to the absorbed dose distribution produced in the target as well as in the tissue and organs at risk surrounding it. In this work, several key aspects related to the technology and irradiation techniques necessary to clinically implement this treatment modality are addressed by means of Monte Carlo simulation. The Zubal phantom was used to model a prostate radiotherapy treatment, a challenging site due to the depth of the prostate and the presence of bony structures that must be traversed by the x-ray beam on its way to the target. It is assumed that the concentration levels of the enhancing agent present in the tumor are at or below 10 mg per 1 g of tissue. The Monte Carlo code PENELOPE was used to model a commercial x-ray tube having a tungsten target. X-ray energy spectra for several combinations of peak electron energy and added filtration were obtained. For each energy spectrum, a treatment plan was calculated, with the PENELOPE Monte Carlo code, by modeling the irradiation of the patient as 72 independent conformal beams distributed at intervals of 5{sup 0} around the phantom in order to model a full x-ray source rotation. The Cimmino optimization algorithm was then used to find the optimum beam weight and energy for different treatment strategies. It is shown that for a target dose prescription of 72 Gy covering the whole tumor, the maximum rectal wall and bladder doses are kept below 52 Gy for the largest concentration of contrast agent of 10 mg per 1 g of tissue. It is also shown that concentrations of as little as 5 mg per 1 g of tissue also render dose distributions with excellent sparing of the organs at risk. A treatment strategy to address the presence of non-uniform distributions of the contrast agent in the target is also modeled and discussed.

  9. Optimizing electrode placement using finite-element models in radiofrequency ablation treatment planning.

    Science.gov (United States)

    Chen, Chun-Cheng R; Miga, Michael I; Galloway, Robert L

    2009-02-01

    Conventional radiofrequency ablation (RFA) planning methods for identifying suitable electrode placements typically use geometric shapes to model ablation outcomes. A method is presented for searching electrode placements that couples finite-element models (FEMs) of RFA together with a novel optimization strategy. The method was designed to reduce the need for model solutions per local search step. The optimization strategy was tested against scenarios requiring single and multiple ablations. In particular, for a scenario requiring multiple ablations, a domain decomposition strategy was described to minimize the complexity of simultaneously searching multiple electrode placements. The effects of nearby vasculature on optimal electrode placement were also studied. Compared with geometric planning approaches, FEMs could potentially deliver electrode placement plans that provide more physically meaningful predictions of therapeutic outcomes.

  10. Heat Transfer Simulation for Optimization and Treatment Planning of Magnetic Hyperthermia Using Magnetic Particle Imaging

    CERN Document Server

    Banura, Natsuo; Nishimoto, Kohei; Murase, Kenya

    2016-01-01

    This study was undertaken to develop a system for heat transfer simulation for optimization and treatment planning of magnetic hyperthermia treatment (MHT) using magnetic particle imaging (MPI). First, we performed phantom experiments to obtain the regression equation between the MPI pixel value and the specific absorption rate (SAR) of magnetic nanoparticles (MNPs), from which the MPI pixel value was converted to the SAR value in the simulation. Second, we generated the geometries for use in the simulation by processing X-ray computed tomography (CT) and MPI images of tumor-bearing mice injected intratumorally with MNPs (Resovist). The geometries and MPI images were then imported into software based on a finite element method (COMSOL Multiphysics) to compute the time-dependent temperature distribution for 20 min after the start of MHT. There was an excellent correlation between the MPI pixel value and the SAR value (r = 0.956). There was good agreement between the time course of the temperature rise in the t...

  11. Optimization Model for Land Treatment Planning, Design and Operation. Part 3. Model Description and User’s Guide.

    Science.gov (United States)

    1983-04-01

    land treatment equations is necessary to develop the user -supplied PARAM and INPUT files and to interpret the model results. A schematic of the system...land treatment equations and is supplied and named by the user . A total of 160 parameter values must be specified. The file must consist of 26 lines...7 AD-A134 461 OPTIMIZATION MODEL FOR LAND TREATMENT PLANNING DESIN 1/AND OPERATION PART 3..U) COLD REGIONS RESEARCH ANDENGINEERING LAB HANOVER NH J A

  12. Analysis of Various Multi-Objective Optimization Evolutionary Algorithms for Monte Carlo Treatment Planning System

    CERN Document Server

    Tydrichova, Magdalena

    2017-01-01

    In this project, various available multi-objective optimization evolutionary algorithms were compared considering their performance and distribution of solutions. The main goal was to select the most suitable algorithms for applications in cancer hadron therapy planning. For our purposes, a complex testing and analysis software was developed. Also, many conclusions and hypothesis have been done for the further research.

  13. A new optimization method using a compressed sensing inspired solver for real-time LDR-brachytherapy treatment planning

    Science.gov (United States)

    Guthier, C.; Aschenbrenner, K. P.; Buergy, D.; Ehmann, M.; Wenz, F.; Hesser, J. W.

    2015-03-01

    This work discusses a novel strategy for inverse planning in low dose rate brachytherapy. It applies the idea of compressed sensing to the problem of inverse treatment planning and a new solver for this formulation is developed. An inverse planning algorithm was developed incorporating brachytherapy dose calculation methods as recommended by AAPM TG-43. For optimization of the functional a new variant of a matching pursuit type solver is presented. The results are compared with current state-of-the-art inverse treatment planning algorithms by means of real prostate cancer patient data. The novel strategy outperforms the best state-of-the-art methods in speed, while achieving comparable quality. It is able to find solutions with comparable values for the objective function and it achieves these results within a few microseconds, being up to 542 times faster than competing state-of-the-art strategies, allowing real-time treatment planning. The sparse solution of inverse brachytherapy planning achieved with methods from compressed sensing is a new paradigm for optimization in medical physics. Through the sparsity of required needles and seeds identified by this method, the cost of intervention may be reduced.

  14. Treatment planning of intensity modulated composite particle therapy with dose and linear energy transfer optimization

    Science.gov (United States)

    Inaniwa, Taku; Kanematsu, Nobuyuki; Noda, Koji; Kamada, Tadashi

    2017-06-01

    The biological effect of charged-particle beams depends on both dose and particle spectrum. As one of the physical quantities describing the particle spectrum of charged-particle beams, we considered the linear energy transfer (LET) throughout this study. We investigated a new therapeutic technique using two or more ion species in one treatment session, which we call an intensity modulated composite particle therapy (IMPACT), for optimizing the physical dose and dose-averaged LET distributions in a patient as its proof of principle. Protons and helium, carbon, and oxygen ions were considered as ion species for IMPACT. For three cubic targets of 4  ×  4  ×  4, 8  ×  8  ×  8, and 12  ×  12  ×  12 cm3, defined at the center of the water phantom of 20  ×  20  ×  20 cm3, we made IMPACT plans of two composite fields with opposing and orthogonal geometries. The prescribed dose to the target was fixed at 1 Gy, while the prescribed LET to the target was varied from 1 keV µm-1 to 120 keV µm-1 to investigate the range of LET valid for prescription. The minimum and maximum prescribed LETs, (L T_min, L T_max), by the opposing-field geometry, were (3 keV µm-1, 115 keV µm-1), (2 keV µm-1, 84 keV µm-1),and (2 keV µm-1, 66 keV µm-1), while those by the orthogonal-field geometry were (8 keV µm-1, 98 keV µm-1), (7 keV µm-1, 72 keV µm-1), and (8 keV µm-1, 57 keV µm-1) for the three targets, respectively. To show the proof of principle of IMPACT in a clinical situation, we made IMPACT plans for a prostate case. In accordance with the prescriptions, the LETs in prostate, planning target volume (PTV), and rectum could be adjusted at 80 keV µm-1, at 50 keV µm-1, and below 30 keV µm-1, respectively, while keeping the dose to the PTV at 2 Gy uniformly. IMPACT enables the optimization of the dose and the LET distributions in a patient, which will maximize the

  15. A role for biological optimization within the current treatment planning paradigm

    Energy Technology Data Exchange (ETDEWEB)

    Das, Shiva [Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina 27710 (United States)

    2009-10-15

    Purpose: Biological optimization using complication probability models in intensity modulated radiotherapy (IMRT) planning has tremendous potential for reducing radiation-induced toxicity. Nevertheless, biological optimization is almost never clinically utilized, probably because of clinician confidence in, and familiarity with, physical dose-volume constraints. The method proposed here incorporates biological optimization after dose-volume constrained optimization so as to improve the dose distribution without detrimentally affecting the important reductions achieved by dose-volume optimization (DVO). Methods: Following DVO, the clinician/planner first identifies ''fixed points'' on the target and organ-at-risk (OAR) dose-volume histograms. These points represent important DVO plan qualities that are not to be violated within a specified tolerance. Biological optimization then maximally reduces a biological metric (illustrated with equivalent uniform dose (EUD) in this work) while keeping the fixed dose-volume points within tolerance limits, as follows. Incremental fluence adjustments are computed and applied to incrementally reduce the OAR EUDs while approximately maintaining the fixed points. This process of incremental fluence adjustment is iterated until the fixed points exceed tolerance. At this juncture, remedial fluence adjustments are computed and iteratively applied to bring the fixed points back within tolerance, without increasing OAR EUDs. This process of EUD reduction followed by fixed-point correction is repeated until no further EUD reduction is possible. The method is demonstrated in the context of a prostate cancer case and olfactory neuroblastoma case. The efficacy of EUD reduction after DVO is evaluated by comparison to an optimizer with purely biological (EUD) OAR objectives. Results: For both cases, EUD reduction after DVO additionally reduced doses, especially high doses, to normal organs. For the prostate case, bladder

  16. Brachytherapy optimization using radiobiological-based planning for high dose rate and permanent implants for prostate cancer treatment

    Science.gov (United States)

    Seeley, Kaelyn; Cunha, J. Adam; Hong, Tae Min

    2017-01-01

    We discuss an improvement in brachytherapy--a prostate cancer treatment method that directly places radioactive seeds inside target cancerous regions--by optimizing the current standard for delivering dose. Currently, the seeds' spatiotemporal placement is determined by optimizing the dose based on a set of physical, user-defined constraints. One particular approach is the ``inverse planning'' algorithms that allow for tightly fit isodose lines around the target volumes in order to reduce dose to the patient's organs at risk. However, these dose distributions are typically computed assuming the same biological response to radiation for different types of tissues. In our work, we consider radiobiological parameters to account for the differences in the individual sensitivities and responses to radiation for tissues surrounding the target. Among the benefits are a more accurate toxicity rate and more coverage to target regions for planning high-dose-rate treatments as well as permanent implants.

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

    Energy Technology Data Exchange (ETDEWEB)

    Tian, Zhen, E-mail: Zhen.Tian@UTSouthwestern.edu, E-mail: Xun.Jia@UTSouthwestern.edu, E-mail: Steve.Jiang@UTSouthwestern.edu; Folkerts, Michael; Tan, Jun; Jia, Xun, E-mail: Zhen.Tian@UTSouthwestern.edu, E-mail: Xun.Jia@UTSouthwestern.edu, E-mail: Steve.Jiang@UTSouthwestern.edu; Jiang, Steve B., E-mail: Zhen.Tian@UTSouthwestern.edu, E-mail: Xun.Jia@UTSouthwestern.edu, E-mail: Steve.Jiang@UTSouthwestern.edu [Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas 75390 (United States); Peng, Fei [Computer Science Department, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213 (United States)

    2015-06-15

    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.

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

    Science.gov (United States)

    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.

  19. Geographic information system-based healthcare waste management planning for treatment site location and optimal transportation routeing.

    Science.gov (United States)

    Shanmugasundaram, Jothiganesh; Soulalay, Vongdeuane; Chettiyappan, Visvanathan

    2012-06-01

    In Lao People's Democratic Republic (Lao PDR), a growth of healthcare centres, and the environmental hazards and public health risks typically accompanying them, increased the need for healthcare waste (HCW) management planning. An effective planning of an HCW management system including components such as the treatment plant siting and an optimized routeing system for collection and transportation of waste is deemed important. National government offices at developing countries often lack the proper tools and methodologies because of the high costs usually associated with them. However, this study attempts to demonstrate the use of an inexpensive GIS modelling tool for healthcare waste management in the country. Two areas were designed for this study on HCW management, including: (a) locating centralized treatment plants and designing optimum travel routes for waste collection from nearby healthcare facilities; and (b) utilizing existing hospital incinerators and designing optimum routes for collecting waste from nearby healthcare facilities. Spatial analysis paved the way to understand the spatial distribution of healthcare wastes and to identify hotspots of higher waste generating locations. Optimal route models were designed for collecting and transporting HCW to treatment plants, which also highlights constraints in collecting and transporting waste for treatment and disposal. The proposed model can be used as a decision support tool for the efficient management of hospital wastes by government healthcare waste management authorities and hospitals.

  20. Simultaneous delivery time and aperture shape optimization for the volumetric-modulated arc therapy (VMAT) treatment planning problem

    Science.gov (United States)

    Mahnam, Mehdi; Gendreau, Michel; Lahrichi, Nadia; Rousseau, Louis-Martin

    2017-07-01

    In this paper, we propose a novel heuristic algorithm for the volumetric-modulated arc therapy treatment planning problem, optimizing the trade-off between delivery time and treatment quality. We present a new mixed integer programming model in which the multi-leaf collimator leaf positions, gantry speed, and dose rate are determined simultaneously. Our heuristic is based on column generation; the aperture configuration is modeled in the columns and the dose distribution and time restriction in the rows. To reduce the number of voxels and increase the efficiency of the master model, we aggregate similar voxels using a clustering technique. The efficiency of the algorithm and the treatment quality are evaluated on a benchmark clinical prostate cancer case. The computational results show that a high-quality treatment is achievable using a four-thread CPU. Finally, we analyze the effects of the various parameters and two leaf-motion strategies.

  1. Shortening Delivery Times of Intensity Modulated Proton Therapy by Reducing Proton Energy Layers During Treatment Plan Optimization

    Energy Technology Data Exchange (ETDEWEB)

    Water, Steven van de, E-mail: s.vandewater@erasmusmc.nl [Department of Radiation Oncology, Erasmus MC Cancer Institute, Rotterdam (Netherlands); Kooy, Hanne M. [F. H. Burr Proton Therapy Center, Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts (United States); Heijmen, Ben J.M.; Hoogeman, Mischa S. [Department of Radiation Oncology, Erasmus MC Cancer Institute, Rotterdam (Netherlands)

    2015-06-01

    Purpose: To shorten delivery times of intensity modulated proton therapy by reducing the number of energy layers in the treatment plan. Methods and Materials: We have developed an energy layer reduction method, which was implemented into our in-house-developed multicriteria treatment planning system “Erasmus-iCycle.” The method consisted of 2 components: (1) minimizing the logarithm of the total spot weight per energy layer; and (2) iteratively excluding low-weighted energy layers. The method was benchmarked by comparing a robust “time-efficient plan” (with energy layer reduction) with a robust “standard clinical plan” (without energy layer reduction) for 5 oropharyngeal cases and 5 prostate cases. Both plans of each patient had equal robust plan quality, because the worst-case dose parameters of the standard clinical plan were used as dose constraints for the time-efficient plan. Worst-case robust optimization was performed, accounting for setup errors of 3 mm and range errors of 3% + 1 mm. We evaluated the number of energy layers and the expected delivery time per fraction, assuming 30 seconds per beam direction, 10 ms per spot, and 400 Giga-protons per minute. The energy switching time was varied from 0.1 to 5 seconds. Results: The number of energy layers was on average reduced by 45% (range, 30%-56%) for the oropharyngeal cases and by 28% (range, 25%-32%) for the prostate cases. When assuming 1, 2, or 5 seconds energy switching time, the average delivery time was shortened from 3.9 to 3.0 minutes (25%), 6.0 to 4.2 minutes (32%), or 12.3 to 7.7 minutes (38%) for the oropharyngeal cases, and from 3.4 to 2.9 minutes (16%), 5.2 to 4.2 minutes (20%), or 10.6 to 8.0 minutes (24%) for the prostate cases. Conclusions: Delivery times of intensity modulated proton therapy can be reduced substantially without compromising robust plan quality. Shorter delivery times are likely to reduce treatment uncertainties and costs.

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

    Science.gov (United States)

    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

  3. Acceleration of high resolution temperature based optimization for hyperthermia treatment planning using element grouping.

    Science.gov (United States)

    Kok, H P; de Greef, M; Bel, A; Crezee, J

    2009-08-01

    In regional hyperthermia, optimization is useful to obtain adequate applicator settings. A speed-up of the previously published method for high resolution temperature based optimization is proposed. Element grouping as described in literature uses selected voxel sets instead of single voxels to reduce computation time. Elements which achieve their maximum heating potential for approximately the same phase/amplitude setting are grouped. To form groups, eigenvalues and eigenvectors of precomputed temperature matrices are used. At high resolution temperature matrices are unknown and temperatures are estimated using low resolution (1 cm) computations and the high resolution (2 mm) temperature distribution computed for low resolution optimized settings using zooming. This technique can be applied to estimate an upper bound for high resolution eigenvalues. The heating potential of elements was estimated using these upper bounds. Correlations between elements were estimated with low resolution eigenvalues and eigenvectors, since high resolution eigenvectors remain unknown. Four different grouping criteria were applied. Constraints were set to the average group temperatures. Element grouping was applied for five patients and optimal settings for the AMC-8 system were determined. Without element grouping the average computation times for five and ten runs were 7.1 and 14.4 h, respectively. Strict grouping criteria were necessary to prevent an unacceptable exceeding of the normal tissue constraints (up to approximately 2 degrees C), caused by constraining average instead of maximum temperatures. When strict criteria were applied, speed-up factors of 1.8-2.1 and 2.6-3.5 were achieved for five and ten runs, respectively, depending on the grouping criteria. When many runs are performed, the speed-up factor will converge to 4.3-8.5, which is the average reduction factor of the constraints and depends on the grouping criteria. Tumor temperatures were comparable. Maximum exceeding

  4. Implant treatment planning considerations.

    Science.gov (United States)

    Kao, Richard T

    2008-04-01

    As dental implants become a more accepted treatment modality, there is a need for all parties involved with implant dentistry to be familiar with various treatment planning issues. Though the success can be highly rewarding, failure to forecast treatment planning issues can result in an increase of surgical needs, surgical cost, and even case failure. In this issue, the focus is on implant treatment planning considerations.

  5. Automatic planning of head and neck treatment plans

    DEFF Research Database (Denmark)

    Hazell, Irene; Bzdusek, Karl; Kumar, Prashant;

    2016-01-01

    treatment plans were reoptimized with the Auto-Planning module. Comparison of the two types of treatment plans were performed using DVH metrics and a blinded clinical evaluation by two senior radiation oncologists using a scale from one to six. Both evaluations investigated dose coverage of target and dose......Treatment planning is time-consuming and the outcome depends on the person performing the optimization. A system that automates treatment planning could potentially reduce the manual time required for optimization and could also pro-vide a method to reduce the variation between persons performing...... radiation dose planning (dosimetrist) and potentially improve the overall plan quality. This study evaluates the performance of the Auto-Planning module that has recently become clinically available in the Pinnacle3 radiation therapy treatment planning system. Twenty-six clinically delivered head and neck...

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

    CERN Document Server

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

    2015-01-01

    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 have been used to speed up the computations. However, its small memory size cannot handle cases with a large dose-deposition coefficient (DDC) matrix. This paper is to report an implementation of our column-generation based VMAT algorithm on a multi-GPU platform to solve the memory limitation problem. The column-generation approach generates apertures sequentially by solving a pricing problem (PP) and a master problem (MP) iteratively. The DDC matrix is split into four sub-matrices according to beam angles, stored on four GPUs in compressed sparse row format. Computation of beamlet price is accomplished using multi-GPU. While the remaining steps of PP and MP problems are implemented on a single GPU due to their modest computational loads. A H&N patient case was used to validate our method. We compare our multi-GPU implemen...

  7. SU-E-T-583: Optimizing the MLC Model Parameters for IMRT in the RayStation Treatment Planning System

    Energy Technology Data Exchange (ETDEWEB)

    Chen, S; Yi, B; Xu, H; Yang, X; Prado, K; D' Souza, W [University of Maryland School of Medicine, Baltimore, MD (United States)

    2014-06-01

    Purpose: To optimize the MLC model parameters for IMRT in the RayStation v.4.0 planning system and for a Varian C-series Linac with a 120-leaf Millennium MLC. Methods: The RayStation treatment planning system models rounded leaf-end MLC with the following parameters: average transmission, leaf-tip width, tongue-and-groove, and position offset. The position offset was provided by Varian. The leaf-tip width was iteratively evaluated by comparing computed and measured transverse dose profiles of MLC-defined fields at dmax in water. The profile comparison was also used to verify the MLC position offset. The transmission factor and leaf tongue width were derived iteratively by optimizing five clinical patient IMRT QA Results: brain, lung, pancreas, head-and-neck (HN), and prostate. The HN and prostate cases involved splitting fields. Verifications were performed with Mapcheck2 measurements and Monte Carlo calculations. Finally, the MLC model was validated using five test IMRT cases from the AAPM TG119 report. Absolute gamma analyses (3mm/3% and 2mm/2%) were applied. In addition, computed output factors for MLC-defined small fields (2×2, 3×3, 4×4, 6×6cm) of both 6MV and 18MV were compared to those measured by the Radiological Physics Center (RPC). Results: Both 6MV and 18MV models were determined to have the same MLC parameters: 2.5% transmission, tongue-and-groove 0.05cm, and leaftip 0.3cm. IMRT QA analysis for five cases in TG119 resulted in a 100% passing rate with 3mm/3% gamma analysis for 6MV, and >97.5% for 18MV. With 2mm/2% gamma analysis, the passing rate was >94.6% for 6MV and >90.9% for 18MV. The difference between computed output factors in RayStation and RPC measurements was less than 2% for all MLCdefined fields, which meets the RPC's acceptance criterion. Conclusion: The rounded leaf-end MLC model in RayStation 4.0 planning system was verified and IMRT commissioning was clinically acceptable. The IMRT commissioning was well validated using guidance

  8. Temperature simulations in hyperthermia treatment planning of the head and neck region. Rigorous optimization of tissue properties

    Energy Technology Data Exchange (ETDEWEB)

    Verhaart, Rene F.; Rijnen, Zef; Verduijn, Gerda M.; Paulides, Margarethus M. [Erasmus MC - Cancer Institute, Department of Radiation Oncology, Hyperthermia Unit, Rotterdam (Netherlands); Fortunati, Valerio; Walsum, Theo van; Veenland, Jifke F. [Erasmus MC, Departments of Medical Informatics and Radiology, Biomedical Imaging Group Rotterdam, Rotterdam (Netherlands)

    2014-12-15

    Hyperthermia treatment planning (HTP) is used in the head and neck region (H and N) for pretreatment optimization, decision making, and real-time HTP-guided adaptive application of hyperthermia. In current clinical practice, HTP is based on power-absorption predictions, but thermal dose-effect relationships advocate its extension to temperature predictions. Exploitation of temperature simulations requires region- and temperature-specific thermal tissue properties due to the strong thermoregulatory response of H and N tissues. The purpose of our work was to develop a technique for patient group-specific optimization of thermal tissue properties based on invasively measured temperatures, and to evaluate the accuracy achievable. Data from 17 treated patients were used to optimize the perfusion and thermal conductivity values for the Pennes bioheat equation-based thermal model. A leave-one-out approach was applied to accurately assess the difference between measured and simulated temperature (∇T). The improvement in ∇T for optimized thermal property values was assessed by comparison with the ∇T for values from the literature, i.e., baseline and under thermal stress. The optimized perfusion and conductivity values of tumor, muscle, and fat led to an improvement in simulation accuracy (∇T: 2.1 ± 1.2 C) compared with the accuracy for baseline (∇T: 12.7 ± 11.1 C) or thermal stress (∇T: 4.4 ± 3.5 C) property values. The presented technique leads to patient group-specific temperature property values that effectively improve simulation accuracy for the challenging H and N region, thereby making simulations an elegant addition to invasive measurements. The rigorous leave-one-out assessment indicates that improvements in accuracy are required to rely only on temperature-based HTP in the clinic. (orig.) [German] Die Hyperthermiebehandlungsplanung (HTP, ''hyperthermia treatment planning'') wird in der Kopf- und Halsregion zur Optimierung der

  9. Design and development of a new micro-beam treatment planning system: effectiveness of algorithms of optimization and dose calculations and potential of micro-beam treatment.

    Science.gov (United States)

    Tachibana, Hidenobu; Kojima, Hiroyuki; Yusa, Noritaka; Miyajima, Satoshi; Tsuda, Akihisa; Yamashita, Takashi

    2012-07-01

    A new treatment planning system (TPS) was designed and developed for a new treatment system, which consisted of a micro-beam-enabled linac with robotics and a real-time tracking system. We also evaluated the effectiveness of the implemented algorithms of optimization and dose calculations in the TPS for the new treatment system. In the TPS, the optimization procedure consisted of the pseudo Beam's-Eye-View method for finding the optimized beam directions and the steepest-descent method for determination of beam intensities. We used the superposition-/convolution-based (SC-based) algorithm and Monte Carlo-based (MC-based) algorithm to calculate dose distributions using CT image data sets. In the SC-based algorithm, dose density scaling was applied for the calculation of inhomogeneous corrections. The MC-based algorithm was implemented with Geant4 toolkit and a phase-based approach using a network-parallel computing. From the evaluation of the TPS, the system can optimize the direction and intensity of individual beams. The accuracy of the dose calculated by the SC-based algorithm was less than 1% on average with the calculation time of 15 s for one beam. However, the MC-based algorithm needed 72 min for one beam using the phase-based approach, even though the MC-based algorithm with the parallel computing could decrease multiple beam calculations and had 18.4 times faster calculation speed using the parallel computing. The SC-based algorithm could be practically acceptable for the dose calculation in terms of the accuracy and computation time. Additionally, we have found a dosimetric advantage of proton Bragg peak-like dose distribution in micro-beam treatment.

  10. MO-G-304-04: Generating Well-Dispersed Representations of the Pareto Front for Multi-Criteria Optimization in Radiation Treatment Planning

    Energy Technology Data Exchange (ETDEWEB)

    Kirlik, G; Zhang, H [University of Maryland School of Medicine, Baltimore, MD (United States)

    2015-06-15

    Purpose: To present a novel multi-criteria optimization (MCO) solution approach that generates well-dispersed representation of the Pareto front for radiation treatment planning. Methods: Different algorithms have been proposed and implemented in commercial planning software to generate MCO plans for external-beam radiation therapy. These algorithms consider convex optimization problems. We propose a grid-based algorithm to generate well-dispersed treatment plans over Pareto front. Our method is able to handle nonconvexity in the problem to deal with dose-volume objectives/constraints, biological objectives, such as equivalent uniform dose (EUD), tumor control probability (TCP), normal tissue complication probability (NTCP), etc. In addition, our algorithm is able to provide single MCO plan when clinicians are targeting narrow bounds of objectives for patients. In this situation, usually none of the generated plans were within the bounds and a solution is difficult to identify via manual navigation. We use the subproblem formulation utilized in the grid-based algorithm to obtain a plan within the specified bounds. The subproblem aims to generate a solution that maps into the rectangle defined by the bounds. If such a solution does not exist, it generates the solution closest to the rectangle. We tested our method with 10 locally advanced head and neck cancer cases. Results: 8 objectives were used including 3 different objectives for primary target volume, high-risk and low-risk target volumes, and 5 objectives for each of the organs-at-risk (OARs) (two parotids, spinal cord, brain stem and oral cavity). Given tight bounds, uniform dose was achieved for all targets while as much as 26% improvement was achieved in OAR sparing comparing to clinical plans without MCO and previously proposed MCO method. Conclusion: Our method is able to obtain well-dispersed treatment plans to attain better approximation for convex and nonconvex Pareto fronts. Single treatment plan can

  11. Automatic planning of head and neck treatment plans.

    Science.gov (United States)

    Hazell, Irene; Bzdusek, Karl; Kumar, Prashant; Hansen, Christian R; Bertelsen, Anders; Eriksen, Jesper G; Johansen, Jørgen; Brink, Carsten

    2016-01-01

    Treatment planning is time-consuming and the outcome depends on the person performing the optimization. A system that automates treatment planning could potentially reduce the manual time required for optimization and could also provide a method to reduce the variation between persons performing radiation dose planning (dosimetrist) and potentially improve the overall plan quality. This study evaluates the performance of the Auto-Planning module that has recently become clinically available in the Pinnacle3 radiation therapy treatment planning system. Twenty-six clinically delivered head and neck treatment plans were reoptimized with the Auto-Planning module. Comparison of the two types of treatment plans were performed using DVH metrics and a blinded clinical evaluation by two senior radiation oncologists using a scale from one to six. Both evaluations investigated dose coverage of target and dose to healthy tissues. Auto-Planning was able to produce clinically acceptable treatment plans in all 26 cases. Target coverages in the two types of plans were similar, but automatically generated plans had less irradiation of healthy tissue. In 94% of the evaluations, the autoplans scored at least as high as the previously delivered clinical plans. For all patients, the Auto-Planning tool produced clinically acceptable head and neck treatment plans without any manual intervention, except for the initial target and OAR delineations. The main benefit of the method is the likely improvement in the overall treatment quality since consistent, high-quality plans are generated which even can be further optimized, if necessary. This makes it possible for the dosimetrist to focus more time on difficult dose planning goals and to spend less time on the more tedious parts of the planning process.

  12. Shortening delivery times of intensity modulated proton therapy by reducing proton energy layers during treatment plan optimization

    NARCIS (Netherlands)

    S. van de Water (Steven); H.M. Kooy; B.J.M. Heijmen (Ben); M.S. Hoogeman (Mischa)

    2015-01-01

    textabstractPurpose To shorten delivery times of intensity modulated proton therapy by reducing the number of energy layers in the treatment plan. Methods and Materials We have developed an energy layer reduction method, which was implemented into our in-house-developed multicriteria treatment

  13. Shortening delivery times of intensity modulated proton therapy by reducing proton energy layers during treatment plan optimization

    NARCIS (Netherlands)

    S. van de Water (Steven); H.M. Kooy; B.J.M. Heijmen (Ben); M.S. Hoogeman (Mischa)

    2015-01-01

    textabstractPurpose To shorten delivery times of intensity modulated proton therapy by reducing the number of energy layers in the treatment plan. Methods and Materials We have developed an energy layer reduction method, which was implemented into our in-house-developed multicriteria treatment plann

  14. SU-E-T-549: A Combinatorial Optimization Approach to Treatment Planning with Non-Uniform Fractions in Intensity Modulated Proton Therapy

    Energy Technology Data Exchange (ETDEWEB)

    Papp, D; Unkelbach, J [Massachusetts General Hospital, Boston, MA (United States)

    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 delivers 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.

  15. Optimization approaches to volumetric modulated arc therapy planning

    Energy Technology Data Exchange (ETDEWEB)

    Unkelbach, Jan, E-mail: junkelbach@mgh.harvard.edu; Bortfeld, Thomas; Craft, David [Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114 (United States); Alber, Markus [Department of Medical Physics and Department of Radiation Oncology, Aarhus University Hospital, Aarhus C DK-8000 (Denmark); Bangert, Mark [Department of Medical Physics in Radiation Oncology, German Cancer Research Center, Heidelberg D-69120 (Germany); Bokrantz, Rasmus [RaySearch Laboratories, Stockholm SE-111 34 (Sweden); Chen, Danny [Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, Indiana 46556 (United States); Li, Ruijiang; Xing, Lei [Department of Radiation Oncology, Stanford University, Stanford, California 94305 (United States); Men, Chunhua [Department of Research, Elekta, Maryland Heights, Missouri 63043 (United States); Nill, Simeon [Joint Department of Physics at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London SM2 5NG (United Kingdom); Papp, Dávid [Department of Mathematics, North Carolina State University, Raleigh, North Carolina 27695 (United States); Romeijn, Edwin [H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332 (United States); Salari, Ehsan [Department of Industrial and Manufacturing Engineering, Wichita State University, Wichita, Kansas 67260 (United States)

    2015-03-15

    Volumetric modulated arc therapy (VMAT) has found widespread clinical application in recent years. A large number of treatment planning studies have evaluated the potential for VMAT for different disease sites based on the currently available commercial implementations of VMAT planning. In contrast, literature on the underlying mathematical optimization methods used in treatment planning is scarce. VMAT planning represents a challenging large scale optimization problem. In contrast to fluence map optimization in intensity-modulated radiotherapy planning for static beams, VMAT planning represents a nonconvex optimization problem. In this paper, the authors review the state-of-the-art in VMAT planning from an algorithmic perspective. Different approaches to VMAT optimization, including arc sequencing methods, extensions of direct aperture optimization, and direct optimization of leaf trajectories are reviewed. Their advantages and limitations are outlined and recommendations for improvements are discussed.

  16. Optimization approaches for planning external beam radiotherapy

    Science.gov (United States)

    Gozbasi, Halil Ozan

    Cancer begins when cells grow out of control as a result of damage to their DNA. These abnormal cells can invade healthy tissue and form tumors in various parts of the body. Chemotherapy, immunotherapy, surgery and radiotherapy are the most common treatment methods for cancer. According to American Cancer Society about half of the cancer patients receive a form of radiation therapy at some stage. External beam radiotherapy is delivered from outside the body and aimed at cancer cells to damage their DNA making them unable to divide and reproduce. The beams travel through the body and may damage nearby healthy tissue unless carefully planned. Therefore, the goal of treatment plan optimization is to find the best system parameters to deliver sufficient dose to target structures while avoiding damage to healthy tissue. This thesis investigates optimization approaches for two external beam radiation therapy techniques: Intensity-Modulated Radiation Therapy (IMRT) and Volumetric-Modulated Arc Therapy (VMAT). We develop automated treatment planning technology for IMRT that produces several high-quality treatment plans satisfying provided clinical requirements in a single invocation and without human guidance. A novel bi-criteria scoring based beam selection algorithm is part of the planning system and produces better plans compared to those produced using a well-known scoring-based algorithm. Our algorithm is very efficient and finds the beam configuration at least ten times faster than an exact integer programming approach. Solution times range from 2 minutes to 15 minutes which is clinically acceptable. With certain cancers, especially lung cancer, a patient's anatomy changes during treatment. These anatomical changes need to be considered in treatment planning. Fortunately, recent advances in imaging technology can provide multiple images of the treatment region taken at different points of the breathing cycle, and deformable image registration algorithms can

  17. Preliminary evaluation of multifield and single-field optimization for the treatment planning of spot-scanning proton therapy of head and neck cancer

    Energy Technology Data Exchange (ETDEWEB)

    Quan, Enzhuo M.; Liu, Wei; Wu, Richard; Zhang, Xiaodong; Zhu, X. Ronald; Mohan, Radhe [Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030 (United States); Li, Yupeng [Varian Medical Systems, Inc., Palo Alto, California 94304 (United States); Frank, Steven J. [Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030 (United States)

    2013-08-15

    Purpose: Spot-scanning proton therapy (SSPT) using multifield optimization (MFO) can generate highly conformal dose distributions, but it is more sensitive to setup and range uncertainties than SSPT using single-field optimization (SFO). The authors compared the two optimization methods for the treatment of head and neck cancer with bilateral targets and determined the superior method on the basis of both the plan quality and the plan robustness in the face of setup and range uncertainties.Methods: Four patients with head and neck cancer with bilateral targets who received SSPT treatment in the authors' institution were studied. The patients had each been treated with a MFO plan using three fields. A three-field SFO plan (3F-SFO) and a two-field SFO plan (2F-SFO) with the use of a range shifter in the beam line were retrospectively generated for each patient. The authors compared the plan quality and robustness to uncertainties of the SFO plans with the MFO plans. Robustness analysis of each plan was performed to generate the two dose distributions consisting of the highest and the lowest possible doses (worst-case doses) from the spatial and range perturbations at every voxel. Dosimetric indices from the nominal and worst-case plans were compared.Results: The 3F-SFO plans generally yielded D95 and D5 values in the targets that were similar to those of the MFO plans. 3F-SFO resulted in a lower dose to the oral cavity than MFO in all four patients by an average of 9.9 Gy, but the dose to the two parotids was on average 6.7 Gy higher for 3F-SFO than for MFO. 3F-SFO plans reduced the variations of dosimetric indices under uncertainties in the targets by 22.8% compared to the MFO plans. Variations of dosimetric indices under uncertainties in the organs at risk (OARs) varied between organs and between patients, although they were on average 9.2% less for the 3F-SFO plans than for the MFO plans. Compared with the MFO plans, the 2F-SFO plans showed a reduced dose to

  18. Multi-objective optimization of inverse planning for accurate radiotherapy

    Institute of Scientific and Technical Information of China (English)

    曹瑞芬; 吴宜灿; 裴曦; 景佳; 李国丽; 程梦云; 李贵; 胡丽琴

    2011-01-01

    The multi-objective optimization of inverse planning based on the Pareto solution set, according to the multi-objective character of inverse planning in accurate radiotherapy, was studied in this paper. Firstly, the clinical requirements of a treatment pl

  19. SU-E-T-222: Computational Optimization of Monte Carlo Simulation On 4D Treatment Planning Using the Cloud Computing Technology

    Energy Technology Data Exchange (ETDEWEB)

    Chow, J [Princess Margaret Cancer Center, Toronto, ON (Canada)

    2015-06-15

    Purpose: This study evaluated the efficiency of 4D lung radiation treatment planning using Monte Carlo simulation on the cloud. The EGSnrc Monte Carlo code was used in dose calculation on the 4D-CT image set. Methods: 4D lung radiation treatment plan was created by the DOSCTP linked to the cloud, based on the Amazon elastic compute cloud platform. Dose calculation was carried out by Monte Carlo simulation on the 4D-CT image set on the cloud, and results were sent to the FFD4D image deformation program for dose reconstruction. The dependence of computing time for treatment plan on the number of compute node was optimized with variations of the number of CT image set in the breathing cycle and dose reconstruction time of the FFD4D. Results: It is found that the dependence of computing time on the number of compute node was affected by the diminishing return of the number of node used in Monte Carlo simulation. Moreover, the performance of the 4D treatment planning could be optimized by using smaller than 10 compute nodes on the cloud. The effects of the number of image set and dose reconstruction time on the dependence of computing time on the number of node were not significant, as more than 15 compute nodes were used in Monte Carlo simulations. Conclusion: The issue of long computing time in 4D treatment plan, requiring Monte Carlo dose calculations in all CT image sets in the breathing cycle, can be solved using the cloud computing technology. It is concluded that the optimized number of compute node selected in simulation should be between 5 and 15, as the dependence of computing time on the number of node is significant.

  20. Optimizing clozapine treatment

    DEFF Research Database (Denmark)

    Damkier, P; Lublin, H; Taylor, D

    2011-01-01

    Clozapine treatment remains the gold standard for treatment-resistant schizophrenia, but treatment with clozapine is associated with several side-effects that complicate the use of the drug. This clinical overview aims to provide psychiatrists with knowledge about how to optimize clozapine...... treatment. Relevant strategies for reducing side-effects and increasing the likelihood of response are discussed....

  1. Biocapacity optimization in regional planning

    Science.gov (United States)

    Guo, Jianjun; Yue, Dongxia; Li, Kai; Hui, Cang

    2017-01-01

    Ecological overshoot has been accelerating across the globe. Optimizing biocapacity has become a key to resolve the overshoot of ecological demand in regional sustainable development. However, most literature has focused on reducing ecological footprint but ignores the potential of spatial optimization of biocapacity through regional planning of land use. Here we develop a spatial probability model and present four scenarios for optimizing biocapacity of a river basin in Northwest China. The potential of enhanced biocapacity and its effects on ecological overshoot and water consumption in the region were explored. Two scenarios with no restrictions on croplands and water use reduced the overshoot by 29 to 53%, and another two scenarios which do not allow croplands and water use to increase worsened the overshoot by 11 to 15%. More spatially flexible transition rules of land use led to higher magnitude of change after optimization. However, biocapacity optimization required a large amount of additional water resources, casting considerable pressure on the already water-scarce socio-ecological system. Our results highlight the potential for policy makers to manage/optimize regional land use which addresses ecological overshoot. Investigation on the feasibility of such spatial optimization complies with the forward-looking policies for sustainable development and deserves further attention.

  2. SU-E-T-587: Optimal Volumetric Modulated Arc Radiotherapy Treatment Planning Technique for Multiple Brain Metastases with Increasing Number of Arcs

    Energy Technology Data Exchange (ETDEWEB)

    Keeling, V; Hossain, S; Hildebrand, K; Ahmad, S [University of Oklahoma Health Sciences Center, Oklahoma City, OK (United States); Larson, D; Ma, L [University of California San Francisco, San Francisco, CA (United States); Sahgal, A [University of Toronto, Toronto, ON (Canada)

    2015-06-15

    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 (OPT 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.

  3. Risk Analysis for Resource Planning Optimization

    Science.gov (United States)

    Cheung, Kar-Ming

    2008-01-01

    This paper describes a systems engineering approach to resource planning by integrating mathematical modeling and constrained optimization, empirical simulation, and theoretical analysis techniques to generate an optimal task plan in the presence of uncertainties.

  4. Combined MV + kV inverse treatment planning for optimal kV dose incorporation in IGRT

    Science.gov (United States)

    Grelewicz, Zachary; Wiersma, Rodney D.

    2014-04-01

    Despite the existence of real-time kV intra-fractional tumor tracking strategies for many years, clinical adoption has been held back by concern over the excess kV imaging dose cost to the patient when imaging in continuous fluoroscopic mode. This work aims to solve this problem by investigating, for the first time, the use of convex optimization tools to optimally integrate this excess kV imaging dose into the MV therapeutic dose in order to make real-time kV tracking clinically feasible. Phase space files modeling both a 6 MV treatment beam and a kV on-board-imaging beam of a commercial LINAC were generated with BEAMnrc, and used to generate dose influence matrices in DOSXYZnrc for ten previously treated lung cancer patients. The dose optimization problem for IMRT, formulated as a quadratic problem, was modified to include additional constraints as required for real-time kV intra-fractional tracking. An interior point optimizer was used to solve the modified optimization problem. It was found that when using large kV imaging apertures during fluoroscopic tracking, combined MV + kV optimization lead to a 0.5%-5.17% reduction in the total number of monitor units assigned to the MV beam due to inclusion of the kV dose over the ten patients. This was accompanied by a reduction of up to 42% of the excess kV dose compared to standard MV IMRT with kV tracking. For all kV field sizes considered, combined MV + kV optimization provided prescription dose to the treatment volume coverage equal to the no-imaging case, yet superior to standard MV IMRT with non-optimized kV fluoroscopic tracking. With combined MV + kV optimization, it is possible to quantify in a patient specific way the dosimetric effect of real-time imaging on the patient. Such information is necessary when substantial kV imaging is performed.

  5. Computational optimization techniques applied to microgrids planning

    DEFF Research Database (Denmark)

    Gamarra, Carlos; Guerrero, Josep M.

    2015-01-01

    appear along the planning process. In this context, technical literature about optimization techniques applied to microgrid planning have been reviewed and the guidelines for innovative planning methodologies focused on economic feasibility can be defined. Finally, some trending techniques and new...

  6. TU-EF-304-02: 4D Optimized Treatment Planning for Actively Scanned Proton Therapy Delivered to Moving Target Volume

    Energy Technology Data Exchange (ETDEWEB)

    Bernatowicz, K; Zhang, Y; Weber, D; Lomax, A [Paul Scherrer Institut, Villigen-psi, Aargau (Switzerland)

    2015-06-15

    Purpose: To develop a 4D treatment optimization approach for Pencil Beam Scanned (PBS) proton therapy that includes breathing variability. Method: PBS proton therapy delivers a pattern of proton pencil beams (PBs), distributed to cover the target volume and optimized such as to achieve a homogenous dose distribution across the target. In this work, this optimization step has been enhanced to include advanced 4D dose calculations of liver tumors based on motion extracted from either 4D-CT (representing a single and averaged respiratory cycle) or 4D-CT(MRI) (including breathing variability). The 4D dose calculation is performed per PB on deforming dose grid, and according to the timestamp of each PB, a displacement due to patient’s motion and a change in radiological depth.Three different treatment fields have been optimized in 3D on the end-exhale phase of a 4D-CT liver data set (3D-opt) and then in 4D using the motion extracted from either 4D-CT or 4D-CT(MRI) using deformable image registration. All plans were calculated directly on the PTV without the use of an ITV. The delivery characteristics of the PSI Gantry 2 have been assumed for all calculations. Results: Dose inhomogeneities (D5-D95) in the CTV for the 3D optimized plans recalculated under conditions of variable motion were increased by on average 19.8% compared to the static case. These differences could be reduced by 4D-CT based 4D optimization to 10.5% and by 4D-CT(MRI) based optimization to only 2.3% of the static value. Liver V25 increased by less than 1% using 4D optimization. Conclusion: 4D optimized PBS treatment plans taking into account breathing variability provide for significantly improved robustness against motion and motion variability than those based on 4D-CT alone, and may negate the need of motion specific target expansions. Swiss National Fund Grant (320030-1493942-1)

  7. Personalized treatment planning.

    Science.gov (United States)

    Pitts, N B; Richards, D

    2009-01-01

    This chapter aims to outline a flexible framework which the dental team can use to bring together key elements of information about their patients and their patients' teeth in order to plan appropriate, patient-centred, caries management based on the application of best current evidence and practice. This framework can be enabled by the use of the International Caries Detection and Assessment System (ICDAS) clinical visual scoring systems for caries detection and activity, but also needs additional information about lesions and the patient to plan and then monitor the effectiveness of personalized caries care. The treatment planning process has evolved from restorative treatment decisions being largely made during clinical assessment as an examination of wet teeth proceeds, with limited charting and a minor role for patient factors. Best practice now involves a comprehensive examination being made systematically of clean dry teeth using sharp eyes and blunt probes. The ICDAS-enabled framework provides for information to be collected at the tooth/surface level (clinical visual lesion detection, lesion detection aids and lesion activity assessment) and at the patient level (patient caries risk assessment, dentition and lesion history and patient behavioural assessment). This information is then synthesized to inform integrated, personalized treatment planning which involves the choice of appropriate treatment options (background level care, preventive treatment options, operative treatment options) and then recall, reassessment and monitoring. Examples of international moves towards using integrated, personalized treatment planning for caries control are given, drawing on experiences in the UK, the USA and from the ICDAS Committee. Copyright 2009 S. Karger AG, Basel

  8. [Postoperative patient. Treatment plan].

    Science.gov (United States)

    López Medina, I M; Sánchez Criado, V

    2001-03-01

    In order to prevent problems and complications which patients who have undergone surgery tend to suffer, it is fundamental to utilize a generic standardized treatment plan due to the preventive dimension which nursing care may then acquire. So that this treatment plan provide greater effectiveness, it should include standardized nursing interventions such as those listed in the Classification of Nursing Interventions since by this method, a common terminology is built up among professionals which provides continuity to treatment and facilitates the selection of adequate interventions for each situation. This report establishes the most frequent nursing diagnoses among post-surgical patients and adapts these to the nursing treatments in the Classification of Nursing Interventions.

  9. Improved planning time and plan quality through multicriteria optimization for intensity-modulated radiotherapy.

    Science.gov (United States)

    Craft, David L; Hong, Theodore S; Shih, Helen A; Bortfeld, Thomas R

    2012-01-01

    To test whether multicriteria optimization (MCO) can reduce treatment planning time and improve plan quality in intensity-modulated radiotherapy (IMRT). Ten IMRT patients (5 with glioblastoma and 5 with locally advanced pancreatic cancers) were logged during the standard treatment planning procedure currently in use at Massachusetts General Hospital (MGH). Planning durations and other relevant planning information were recorded. In parallel, the patients were planned using an MCO planning system, and similar planning time data were collected. The patients were treated with the standard plan, but each MCO plan was also approved by the physicians. Plans were then blindly reviewed 3 weeks after planning by the treating physician. In all cases, the treatment planning time was vastly shorter for the MCO planning (average MCO treatment planning time was 12 min; average standard planning time was 135 min). The physician involvement time in the planning process increased from an average of 4.8 min for the standard process to 8.6 min for the MCO process. In all cases, the MCO plan was blindly identified as the superior plan. This provides the first concrete evidence that MCO-based planning is superior in terms of both planning efficiency and dose distribution quality compared with the current trial and error-based IMRT planning approach. Copyright © 2012 Elsevier Inc. All rights reserved.

  10. An optimization framework for interdependent planning goals

    Science.gov (United States)

    Estlin, T. A.; Gaines, D. M.

    2002-01-01

    This paper describes an approach for optimizing over interdependent planning goals. We have implemented a methodology for representing and utilizing information about interdependent goals and their related utilities using the ASPEN planning and scheduling system.

  11. GPU-based ultrafast IMRT plan optimization

    Science.gov (United States)

    Men, Chunhua; Gu, Xuejun; Choi, Dongju; Majumdar, Amitava; Zheng, Ziyi; Mueller, Klaus; Jiang, Steve B.

    2009-11-01

    The widespread adoption of on-board volumetric imaging in cancer radiotherapy has stimulated research efforts to develop online adaptive radiotherapy techniques to handle the inter-fraction variation of the patient's geometry. Such efforts face major technical challenges to perform treatment planning in real time. To overcome this challenge, we are developing a supercomputing online re-planning environment (SCORE) at the University of California, San Diego (UCSD). As part of the SCORE project, this paper presents our work on the implementation of an intensity-modulated radiation therapy (IMRT) optimization algorithm on graphics processing units (GPUs). We adopt a penalty-based quadratic optimization model, which is solved by using a gradient projection method with Armijo's line search rule. Our optimization algorithm has been implemented in CUDA for parallel GPU computing as well as in C for serial CPU computing for comparison purpose. A prostate IMRT case with various beamlet and voxel sizes was used to evaluate our implementation. On an NVIDIA Tesla C1060 GPU card, we have achieved speedup factors of 20-40 without losing accuracy, compared to the results from an Intel Xeon 2.27 GHz CPU. For a specific nine-field prostate IMRT case with 5 × 5 mm2 beamlet size and 2.5 × 2.5 × 2.5 mm3 voxel size, our GPU implementation takes only 2.8 s to generate an optimal IMRT plan. Our work has therefore solved a major problem in developing online re-planning technologies for adaptive radiotherapy.

  12. Angelic Hierarchical Planning: Optimal and Online Algorithms

    Science.gov (United States)

    2008-12-06

    restrict our attention to plans in I∗(Act, s0). Definition 2. ( Parr and Russell , 1998) A plan ah∗ is hierarchically optimal iff ah∗ = argmina∈I∗(Act,s0):T...Murdock, Dan Wu, and Fusun Yaman. SHOP2: An HTN planning system. JAIR, 20:379–404, 2003. Ronald Parr and Stuart Russell . Reinforcement Learning with...Angelic Hierarchical Planning: Optimal and Online Algorithms Bhaskara Marthi Stuart J. Russell Jason Wolfe Electrical Engineering and Computer

  13. Automatic treatment planning facilitates fast generation of high-quality treatment plans for esophageal cancer

    DEFF Research Database (Denmark)

    Hansen, Christian Rønn; Nielsen, Morten; Bertelsen, Anders Smedegaard

    2017-01-01

    BACKGROUND: 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...... to the lungs. The automation of the planning process generated esophageal cancer treatment plans quickly and with high quality....... cancer patients. MATERIAL AND METHODS: 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...

  14. Automatic Planning of External Search Engine Optimization

    Directory of Open Access Journals (Sweden)

    Vita Jasevičiūtė

    2015-07-01

    Full Text Available This paper describes an investigation of the external search engine optimization (SEO action planning tool, dedicated to automatically extract a small set of most important keywords for each month during whole year period. The keywords in the set are extracted accordingly to external measured parameters, such as average number of searches during the year and for every month individually. Additionally the position of the optimized web site for each keyword is taken into account. The generated optimization plan is similar to the optimization plans prepared manually by the SEO professionals and can be successfully used as a support tool for web site search engine optimization.

  15. Strategies for automatic online treatment plan reoptimization using clinical treatment planning system: a planning parameters study.

    Science.gov (United States)

    Li, Taoran; Wu, Qiuwen; Zhang, You; Vergalasova, Irina; Lee, W Robert; Yin, Fang-Fang; Wu, Q Jackie

    2013-11-01

    Adaptive radiation therapy for prostate cancer using online reoptimization provides an improved control of interfractional anatomy variations. However, the clinical implementation of online reoptimization is currently limited by the low efficiency of current strategies and the difficulties associated with integration into the current treatment planning system. This study investigates the strategies for performing fast (~2 min) automatic online reoptimization with a clinical fluence-map-based treatment planning system; and explores the performance with different input parameters settings: dose-volume histogram (DVH) objective settings, starting stage, and iteration number (in the context of real time planning). Simulated treatments of 10 patients were reoptimized daily for the first week of treatment (5 fractions) using 12 different combinations of optimization strategies. Options for objective settings included guideline-based RTOG objectives, patient-specific objectives based on anatomy on the planning CT, and daily-CBCT anatomy-based objectives adapted from planning CT objectives. Options for starting stages involved starting reoptimization with and without the original plan's fluence map. Options for iteration numbers were 50 and 100. The adapted plans were then analyzed by statistical modeling, and compared both in terms of dosimetry and delivery efficiency. All online reoptimized plans were finished within ~2 min with excellent coverage and conformity to the daily target. The three input parameters, i.e., DVH objectives, starting stage, and iteration number, contributed to the outcome of optimization nearly independently. Patient-specific objectives generally provided better OAR sparing compared to guideline-based objectives. The benefit in high-dose sparing from incorporating daily anatomy into objective settings was positively correlated with the relative change in OAR volumes from planning CT to daily CBCT. The use of the original plan fluence map as the

  16. Strategies for automatic online treatment plan reoptimization using clinical treatment planning system: A planning parameters study

    Energy Technology Data Exchange (ETDEWEB)

    Li, Taoran; Wu, Qiuwen; Zhang, You; Vergalasova, Irina; Lee, W. Robert; Yin, Fang-Fang; Wu, Q. Jackie [Duke Medical Physics Graduate Program, Duke University, Durham, North Carolina 27705 and Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina 27710 (United States)

    2013-11-15

    Purpose: Adaptive radiation therapy for prostate cancer using online reoptimization provides an improved control of interfractional anatomy variations. However, the clinical implementation of online reoptimization is currently limited by the low efficiency of current strategies and the difficulties associated with integration into the current treatment planning system. This study investigates the strategies for performing fast (∼2 min) automatic online reoptimization with a clinical fluence-map-based treatment planning system; and explores the performance with different input parameters settings: dose-volume histogram (DVH) objective settings, starting stage, and iteration number (in the context of real time planning).Methods: Simulated treatments of 10 patients were reoptimized daily for the first week of treatment (5 fractions) using 12 different combinations of optimization strategies. Options for objective settings included guideline-based RTOG objectives, patient-specific objectives based on anatomy on the planning CT, and daily-CBCT anatomy-based objectives adapted from planning CT objectives. Options for starting stages involved starting reoptimization with and without the original plan's fluence map. Options for iteration numbers were 50 and 100. The adapted plans were then analyzed by statistical modeling, and compared both in terms of dosimetry and delivery efficiency.Results: All online reoptimized plans were finished within ∼2 min with excellent coverage and conformity to the daily target. The three input parameters, i.e., DVH objectives, starting stage, and iteration number, contributed to the outcome of optimization nearly independently. Patient-specific objectives generally provided better OAR sparing compared to guideline-based objectives. The benefit in high-dose sparing from incorporating daily anatomy into objective settings was positively correlated with the relative change in OAR volumes from planning CT to daily CBCT. The use of the

  17. Reply to 'Comment on genetic and global algorithms for optimization of three-dimensional conformal radiotherapy treatment planning'

    Energy Technology Data Exchange (ETDEWEB)

    Wu Xingen; Zhu Yunping [Department of Radiation Oncology, St. Jude Children' s Research Hospital, Memphis, TN (United States)

    2001-06-01

    In reply to the letter by Dr. Vaarkamp, we would like first to offer him our thank for pointing out some issues in the complex problem of radiotherapy planning optimization that will require our closer attention in the future. We certainly can add any organs at risk (OARs) to help improve the overall radiotherapy ratio. We can objectively judge the merit of our planning on the basis of the resulting dose volume histogram (DVH) information for certain OARs chosen on the basis of the tumour location and clinical decision. In addition, any treatment planning, regardless of the method used, must still be approved by the radiation oncologist. Response to the first comment: Different plans may select different OARs for different clinical considerations and patient outcomes. Our selection of OARs (left or right eye, thyroid or spinal cord) is based mainly on clinical judgement about the specific case under investigation. For example, the first case (Wu et al 2000) used three OARs (left eye, right eye and thyroid). In this clinical case, the radiation oncologist did not specify the volumes for hypothalamus, pituitary, optic chiasm an any auditory apparatus. That is not to say that these organs are not important. We think it is reasonable to choose the OARs according to clinical judgement, since it is very convenient for us to make a comparison with the manual plans where those DVHs are available. In the case of the right temporal lobe, for example, we look at it closely when we want to treat the right eye. But when the parotid gland is treated, the hypothalamus and pituitary are normally no problem, because few beams go directly through them. We are aware of all the OARs mentioned by Dr. Vaarkamp and can take any or all of them into consideration in our planning optimization. We can also apply relative weighting to them. We are working on a model that will not only limit the maximum dose in OARs but also take the DVHs of these OARs into consideration in our optimization

  18. Optimization and control in deep hyperthermia: Clinical implementation of hyperthermia treatment planning in cervical cancer treatment to obtain a higher treatment quality

    NARCIS (Netherlands)

    R.A.M. Canters (Richard)

    2013-01-01

    textabstractDeep hyperthermia is a treatment used in concurrence with radiation therapy or chemotherapy in the treatment of deep seated tumors. In hyperthermia, tumor temperatures are elevated 3 to 7oC above normal body temperature, up to a temperature of 44oC. In a randomized trial, the 3 year over

  19. Optimization and control in deep hyperthermia: Clinical implementation of hyperthermia treatment planning in cervical cancer treatment to obtain a higher treatment quality

    NARCIS (Netherlands)

    R.A.M. Canters (Richard)

    2013-01-01

    textabstractDeep hyperthermia is a treatment used in concurrence with radiation therapy or chemotherapy in the treatment of deep seated tumors. In hyperthermia, tumor temperatures are elevated 3 to 7oC above normal body temperature, up to a temperature of 44oC. In a randomized trial, the 3 year

  20. [Oligodontia: treatment plan and therapy].

    Science.gov (United States)

    Reitsma, J H; Meijer, H J A; van Oort, R P

    2005-09-01

    The aim of this retrospective study was to gain insight in treatment planning and therapy for patients with oligodontia. Records of 58 treated patients with oligodontia were screened using several parameters: gender, year and age of registration, symptoms, case history, treatment plan and therapy. Treatment plans were sorted into the following categories: tooth-supported overdentures, fixed or removable partial dentures and implant-supported restorations. Dependent on the complexity of oligodontia, it is advocated to make a treatment plan before the age of 12 years old and to follow the provided treatment conscientiously until the final prosthetic treatment. After analyzing the 58 treatment plans, the following conclusions could be made: the treatment plan was not in all cases made before the age of 12 years, it was not clear in all cases who was the coordinator of the treatment and dental implants are becoming more and more important in treating patients with oligodontia.

  1. Production Planning Based on BOM Optimization

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    According to a prototype enterprise, a rulebased Bill of Materials (BOM) structure is designed in order to get optimal design and management of product BOM. The constraint rules and optional objects for product data structure optimization are considered by associating customer demands with product BOM. Furthermore, the functional model of production planning system for assembling enterprise is given based on customization and BOM optimization.

  2. PARETO: A novel evolutionary optimization approach to multiobjective IMRT planning.

    Science.gov (United States)

    Fiege, Jason; McCurdy, Boyd; Potrebko, Peter; Champion, Heather; Cull, Andrew

    2011-09-01

    In radiation therapy treatment planning, the clinical objectives of uniform high dose to the planning target volume (PTV) and low dose to the organs-at-risk (OARs) are invariably in conflict, often requiring compromises to be made between them when selecting the best treatment plan for a particular patient. In this work, the authors introduce Pareto-Aware Radiotherapy Evolutionary Treatment Optimization (pareto), a multiobjective optimization tool to solve for beam angles and fluence patterns in intensity-modulated radiation therapy (IMRT) treatment planning. pareto is built around a powerful multiobjective genetic algorithm (GA), which allows us to treat the problem of IMRT treatment plan optimization as a combined monolithic problem, where all beam fluence and angle parameters are treated equally during the optimization. We have employed a simple parameterized beam fluence representation with a realistic dose calculation approach, incorporating patient scatter effects, to demonstrate feasibility of the proposed approach on two phantoms. The first phantom is a simple cylindrical phantom containing a target surrounded by three OARs, while the second phantom is more complex and represents a paraspinal patient. pareto results in a large database of Pareto nondominated solutions that represent the necessary trade-offs between objectives. The solution quality was examined for several PTV and OAR fitness functions. The combination of a conformity-based PTV fitness function and a dose-volume histogram (DVH) or equivalent uniform dose (EUD) -based fitness function for the OAR produced relatively uniform and conformal PTV doses, with well-spaced beams. A penalty function added to the fitness functions eliminates hotspots. Comparison of resulting DVHs to those from treatment plans developed with a single-objective fluence optimizer (from a commercial treatment planning system) showed good correlation. Results also indicated that pareto shows promise in optimizing the number

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

    Energy Technology Data Exchange (ETDEWEB)

    Wild, Esther, E-mail: e.wild@dkfz.de; Bangert, Mark [Department of Medical Physics in Radiation Oncology, German Cancer Research Center, Im Neuenheimer Feld 280, D-69120 Heidelberg (Germany); Nill, Simeon [Joint Department of Physics at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London SM2 5NG (United Kingdom); Oelfke, Uwe [Joint Department of Physics at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London SM2 5NG, United Kingdom and Department of Medical Physics in Radiation Oncology, German Cancer Research Center, Im Neuenheimer Feld 280, D-69120 Heidelberg (Germany)

    2015-05-15

    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 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. 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

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

    Science.gov (United States)

    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

  5. Software for Optimizing Plans Involving Interdependent Goals

    Science.gov (United States)

    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.

  6. Derivative-free generation and interpolation of convex Pareto optimal IMRT plans.

    NARCIS (Netherlands)

    Hoffmann, A.L.; Siem, A.Y.; Hertog, D. den; Kaanders, J.H.A.M.; Huizenga, H.

    2006-01-01

    In inverse treatment planning for intensity-modulated radiation therapy (IMRT), beamlet intensity levels in fluence maps of high-energy photon beams are optimized. Treatment plan evaluation criteria are used as objective functions to steer the optimization process. Fluence map optimization can be co

  7. OPTIMAL TRAJECTORY PLANNING OF MANIPULATORS: A REVIEW

    Directory of Open Access Journals (Sweden)

    ATEF A. ATA

    2007-04-01

    Full Text Available Optimal motion planning is very important to the operation of robot manipulators. Its main target is the generation of a trajectory from start to goal that satisfies objectives, such as minimizing path traveling distance or time interval, lowest energy consumption or obstacle avoidance and satisfying the robot’s kinematics and dynamics. Review, discussion and analysis of optimization techniques to find the optimal trajectory either in Cartesian space or joint space are presented and investigated. Optimal trajectory selection approaches such as kinematics and dynamics techniques with various constraints are presented and explained. Although the kinematics approach is simple and straight forward, it will experience some problems in implementation because of lack of Inertia and torque constraints. The application of Genetic Algorithms to find the optimal trajectory of manipulators especially in the obstacle avoidance is also highlighted. Combining the Genetic Algorithms with other classical optimization methods proves to have better performance as a hybrid optimization technique.

  8. Automatic treatment planning facilitates fast generation of high-quality treatment plans for esophageal cancer.

    Science.gov (United States)

    Hansen, Christian Rønn; Nielsen, Morten; Bertelsen, Anders Smedegaard; Hazell, Irene; Holtved, Eva; Zukauskaite, Ruta; Bjerregaard, Jon Kroll; Brink, Carsten; Bernchou, Uffe

    2017-08-25

    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 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.

  9. Enterprise resource planning implementation decision & optimization models

    Institute of Scientific and Technical Information of China (English)

    Wang Shaojun; Wang Gang; Lü Min; Gao Guoan

    2008-01-01

    To study the uncertain optimization problems on implementation schedule, time-cost trade-off and quality in enterprise resource planning (ERP) implementation, combined with program evaluation and review technique (PERT), some optimization models are proposed, which include the implementation schedule model, the timecost trade-off model, the quality model, and the implementation time-cost-quality synthetic optimization model. A PERT-embedded genetic algorithm (GA) based on stochastic simulation technique is introduced to the optimization models solution. Finally, an example is presented to show that the models and algorithm are reasonable and effective, which can offer a reliable quantitative decision method for ERP implementation.

  10. Experiments Planning, Analysis, and Optimization

    CERN Document Server

    Wu, C F Jeff

    2011-01-01

    Praise for the First Edition: "If you . . . want an up-to-date, definitive reference written by authors who have contributed much to this field, then this book is an essential addition to your library."-Journal of the American Statistical Association Fully updated to reflect the major progress in the use of statistically designed experiments for product and process improvement, Experiments, Second Edition introduces some of the newest discoveries-and sheds further light on existing ones-on the design and analysis of experiments and their applications in system optimization, robustness, and tre

  11. Plan optimization for stereotactic radiotherapy

    NARCIS (Netherlands)

    J.A. de Pooter (Jacobus Abraham)

    2008-01-01

    textabstractCancer is one of the leading causes of death in the world. Next to surgery and chemotherapy, radiotherapy is one of the most used treatment modalities for cancer. About 50% of the patients with cancer will be treated with radiotherapy during the management of their disease. In radiothera

  12. Helicopter trajectory planning using optimal control theory

    Science.gov (United States)

    Menon, P. K. A.; Cheng, V. H. L.; Kim, E.

    1988-01-01

    A methodology for optimal trajectory planning, useful in the nap-of-the-earth guidance of helicopters, is presented. This approach uses an adjoint-control transformation along with a one-dimensional search scheme for generating the optimal trajectories. In addition to being useful for helicopter nap-of-the-earth guidance, the trajectory planning solution is of interest in several other contexts, such as robotic vehicle guidance and terrain-following guidance for cruise missiles and aircraft. A distinguishing feature of the present research is that the terrain constraint and the threat envelopes are incorporated in the equations of motion. Second-order necessary conditions are examined.

  13. SURFACE MINE PLANNING OPTIMIZATION BY GOAL PROGRAMMING

    Institute of Scientific and Technical Information of China (English)

    陈意平; 张幼蒂

    1991-01-01

    This paper introduced an approach to surface mine planning optimization-Goal Programming.The multiobjective[0-1] model has been built and the software has been developed.The method has been applied to a huge surface coal mine,the result of which shows that it is effective and feasible.

  14. Temporal Optimization Planning for Fleet Repositioning

    DEFF Research Database (Denmark)

    Tierney, Kevin; Jensen, Rune Møller

    2011-01-01

    Fleet repositioning problems pose a high financial bur- den on shipping firms, but have received little attention in the literature, despite their high importance to the shipping industry. Fleet repositioning problems are characterized by chains of interacting activities, but state-of-the-art pla......Fleet repositioning problems pose a high financial bur- den on shipping firms, but have received little attention in the literature, despite their high importance to the shipping industry. Fleet repositioning problems are characterized by chains of interacting activities, but state......-of-the-art planning and scheduling techniques do not offer cost models that are rich enough to represent essential objectives of these problems. To this end, we introduce a novel framework called Temporal Optimization Planning (TOP). TOP uses partial order planning to build optimization models associated...

  15. Treatment planning in conservative dentistry.

    Science.gov (United States)

    Sivakumar, Andamuthu; Thangaswamy, Vinod; Ravi, Vaiyapuri

    2012-08-01

    A patient attending for treatment of a restorative nature may present for a variety of reasons. The success is built upon careful history taking coupled with a logical progression to diagnosis of the problem that has been presented. Each stage follows on from the preceding one. A fitting treatment plan should be formulated and should involve a holistic approach to what is required.

  16. Optimal planning of high voltage distribution substations

    Institute of Scientific and Technical Information of China (English)

    YU Yixin; YAN Xuefei; ZHANG Yongwu

    2007-01-01

    Aimed at solving the problem of optimal planning for high voltage distribution substations,an efficient method is put forward.The method divides the problem into two sub-problems:source locating and combinational optimization.The algorithm of allocating and locating alternatively (ALA) is widely used to deal with the source locating problem,but it is dependent on the initial location to a large degree.Thus,some modifications were made to the ALA algorithm,which could greatly improve the quality of solutions.In addition,considering the non-convex and nonconcave nature of the sub-problem of combinational optimization,the branch-and-bound technique was adopted to obtain or approximate a global optimal solution.To improve the efficiency of the branch-and-bound technique,some heuristic principles were proposed to cut those branches that may generate a global optimization solution with low probability.Examples show that the proposed algorithm meets the requirement of engineering and it is an effective approach to rapidly solve the problem of optimal planning for high voltage distribution substations.

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

    Energy Technology Data Exchange (ETDEWEB)

    Cruz, W [University of Texas Health Science Center at San Antonio, San Antonio, TX (United States); Cancer Therapy and Research Center, San Antonio, TX (United States); Papanikolaou, P [University of Texas Health Science Center at San Antonio, San Antonio, TX (United States); Mavroidis, P [University of North Carolina, Chapel Hill, NC (United States); Stathakis, S [Cancer Therapy and Research Center, San Antonio, TX (United States)

    2015-06-15

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

  18. Optimal Antihypertensive Combination Treatments

    Directory of Open Access Journals (Sweden)

    Massimo Volpe

    2012-03-01

    Full Text Available Over the past three decades it has been consistently shown that optimal blood pressure (BP control significantly reduced cardiovascular (CV morbidity and mortality [1]. Despite solid evidence in favour of benefits derived from BP reductions, however, hypertension control in treated hypertensive patients remains suboptimal worldwide [2, 3]. In addition, proportions of diagnosed and treated hypertensive patients remain largely unchanged over the last two decades[4]. Multiple factors may be advocated to explain this observation, including variation in healthcare access and availability [5, 6], attitudes amongst clinicians towards hypertension [7, 8], inaccuracy in BP measurements [9] and underuse or under dosage of antihypertensive drugs in both monotherapy and in combination therapy [10, 11].On the basis of these considerations, it is beyond the aim of this article to discuss the socioeconomic impact on healthcare and BP measurement techniques. Instead it will seek to explain the importance of attaining early optimal BP control and the use of combination therapy as a new paradigm for the modern clinical management of hypertension.

  19. Discrepancies between selected Pareto optimal plans and final deliverable plans in radiotherapy multi-criteria optimization.

    Science.gov (United States)

    Kyroudi, Archonteia; Petersson, Kristoffer; Ghandour, Sarah; Pachoud, Marc; Matzinger, Oscar; Ozsahin, Mahmut; Bourhis, Jean; Bochud, François; Moeckli, Raphaël

    2016-08-01

    Multi-criteria optimization provides decision makers with a range of clinical choices through Pareto plans that can be explored during real time navigation and then converted into deliverable plans. Our study shows that dosimetric differences can arise between the two steps, which could compromise the clinical choices made during navigation.

  20. Resampling: an optimization method for inverse planning in robotic radiosurgery.

    Science.gov (United States)

    Schweikard, Achim; Schlaefer, Alexander; Adler, John R

    2006-11-01

    By design, the range of beam directions in conventional radiosurgery are constrained to an isocentric array. However, the recent introduction of robotic radiosurgery dramatically increases the flexibility of targeting, and as a consequence, beams need be neither coplanar nor isocentric. Such a nonisocentric design permits a large number of distinct beam directions to be used in one single treatment. These major technical differences provide an opportunity to improve upon the well-established principles for treatment planning used with GammaKnife or LINAC radiosurgery. With this objective in mind, our group has developed over the past decade an inverse planning tool for robotic radiosurgery. This system first computes a set of beam directions, and then during an optimization step, weights each individual beam. Optimization begins with a feasibility query, the answer to which is derived through linear programming. This approach offers the advantage of completeness and avoids local optima. Final beam selection is based on heuristics. In this report we present and evaluate a new strategy for utilizing the advantages of linear programming to improve beam selection. Starting from an initial solution, a heuristically determined set of beams is added to the optimization problem, while beams with zero weight are removed. This process is repeated to sample a set of beams much larger compared with typical optimization. Experimental results indicate that the planning approach efficiently finds acceptable plans and that resampling can further improve its efficiency.

  1. SU-F-BRD-10: Improving Plan Delivery Efficiency of Intensity Modulated Proton Plans with Prioritized Optimization

    Energy Technology Data Exchange (ETDEWEB)

    Müller, BS; Wilkens, JJ [Department of Radiation Oncology, Technische Universität München, Klinikum rechts der Isar, Munich (Germany); Physik-Department, Technische Universität München, Munich, DE (Germany)

    2015-06-15

    Purpose: To integrate treatment delivery time into plan optimization in spot scanning intensity modulated proton therapy. Utilizing a dedicated research treatment planning system we present an optimization approach to explore the trade-off between the correlated parameters treatment time and plan quality on an astrocytoma patient case. Methods: The planning system is based on prioritized optimization, a stepwise approach of implementing clinical goals. After each optimization step, dosimetric achievements are turned into hard constraints to maintain the achieved plan quality. Prior achievements can be violated by a so-called slip-factor which allows to study possible trade-offs of conflicting goals. Plan quality is obtained in the first two steps, while the third step optimizes delivery efficiency by working on the spot weight distribution via four alternative Methods: elimination of low weighted spots (1), elimination of spots hardly contributing to PTV dose, followed by reoptimization of the resulting smaller optimization problem (2), reduction of spot weights variance within each energy layer (3), and reduction of the overall spot weight sum (4). Treatment times were calculated assuming either constant or variable beam current depending on the lowest spot weight. Results: Delivery efficiency can be improved remarkably without influencing the plan quality. Absolute time savings depend on the utilized method and facility properties. By varying slip-factor and spot reduction limits, a border of worsening quality is detectable for all methods.Deleting low weighted spots by 10% results in a noticeable decrease in minimum target dose. Further reduction results in more heterogeneous dose distributions and insufficient coverage. Option 2 showed constant plan quality for spot reductions of more than 10%. Conclusion: Including treatment time optimization as a final step into prioritized optimization allows for more efficient treatment plans by redistributing the spot

  2. Improving IMRT-plan quality with MLC leaf position refinement post plan optimization.

    Science.gov (United States)

    Niu, Ying; Zhang, Guowei; Berman, Barry L; Parke, William C; Yi, Byongyong; Yu, Cedric X

    2012-08-01

    In intensity-modulated radiation therapy (IMRT) planning, reducing the pencil-beam size may lead to a significant improvement in dose conformity, but also increase the time needed for the dose calculation and plan optimization. The authors develop and evaluate a postoptimization refinement (POpR) method, which makes fine adjustments to the multileaf collimator (MLC) leaf positions after plan optimization, enhancing the spatial precision and improving the plan quality without a significant impact on the computational burden. The authors' POpR method is implemented using a commercial treatment planning system based on direct aperture optimization. After an IMRT plan is optimized using pencil beams with regular pencil-beam step size, a greedy search is conducted by looping through all of the involved MLC leaves to see if moving the MLC leaf in or out by half of a pencil-beam step size will improve the objective function value. The half-sized pencil beams, which are used for updating dose distribution in the greedy search, are derived from the existing full-sized pencil beams without need for further pencil-beam dose calculations. A benchmark phantom case and a head-and-neck (HN) case are studied for testing the authors' POpR method. Using a benchmark phantom and a HN case, the authors have verified that their POpR method can be an efficient technique in the IMRT planning process. Effectiveness of POpR is confirmed by noting significant improvements in objective function values. Dosimetric benefits of POpR are comparable to those of using a finer pencil-beam size from the optimization start, but with far less computation and time. The POpR is a feasible and practical method to significantly improve IMRT-plan quality without compromising the planning efficiency.

  3. GPU-based ultra fast IMRT plan optimization

    CERN Document Server

    Men, Chunhua; Choi, Dongju; Majumdar, Amitava; Zheng, Ziyi; Mueller, Klaus; Jiang, Steve B

    2009-01-01

    The widespread adoption of on-board volumetric imaging in cancer radiotherapy has stimulated research efforts to develop online adaptive radiotherapy techniques to handle the inter-fraction variation of the patient's geometry. Such efforts face major technical challenges to perform treatment planning in real-time. To overcome this challenge, we are developing a supercomputing online re-planning environment (SCORE) at the University of California San Diego (UCSD). As part of the SCORE project, this paper presents our work on the implementation of an intensity modulated radiation therapy (IMRT) optimization algorithm on graphics processing units (GPUs). We adopt a penalty-based quadratic optimization model, which is solved by using a gradient projection method with Armijo's line search rule. Our optimization algorithm has been implemented in CUDA for parallel GPU computing as well as in C for serial CPU computing for comparison purpose. A prostate IMRT case with various beamlet and voxel sizes was used to evalu...

  4. Derivative-free generation and interpolation of convex Pareto optimal IMRT plans.

    Science.gov (United States)

    Hoffmann, Aswin L; Siem, Alex Y D; den Hertog, Dick; Kaanders, Johannes H A M; Huizenga, Henk

    2006-12-21

    In inverse treatment planning for intensity-modulated radiation therapy (IMRT), beamlet intensity levels in fluence maps of high-energy photon beams are optimized. Treatment plan evaluation criteria are used as objective functions to steer the optimization process. Fluence map optimization can be considered a multi-objective optimization problem, for which a set of Pareto optimal solutions exists: the Pareto efficient frontier (PEF). In this paper, a constrained optimization method is pursued to iteratively estimate the PEF up to some predefined error. We use the property that the PEF is convex for a convex optimization problem to construct piecewise-linear upper and lower bounds to approximate the PEF from a small initial set of Pareto optimal plans. A derivative-free Sandwich algorithm is presented in which these bounds are used with three strategies to determine the location of the next Pareto optimal solution such that the uncertainty in the estimated PEF is maximally reduced. We show that an intelligent initial solution for a new Pareto optimal plan can be obtained by interpolation of fluence maps from neighbouring Pareto optimal plans. The method has been applied to a simplified clinical test case using two convex objective functions to map the trade-off between tumour dose heterogeneity and critical organ sparing. All three strategies produce representative estimates of the PEF. The new algorithm is particularly suitable for dynamic generation of Pareto optimal plans in interactive treatment planning.

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

    Science.gov (United States)

    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.

  6. Treatment planning for volumetric modulated arc therapy

    Energy Technology Data Exchange (ETDEWEB)

    Bedford, James L. [Joint Department of Physics, Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, Downs Road, Sutton, Surrey SM2 5PT (United Kingdom)

    2009-11-15

    Purpose: Volumetric modulated arc therapy (VMAT) is a specific type of intensity-modulated radiation therapy (IMRT) in which the gantry speed, multileaf collimator (MLC) leaf position, and dose rate vary continuously during delivery. A treatment planning system for VMAT is presented. Methods: Arc control points are created uniformly throughout one or more arcs. An iterative least-squares algorithm is used to generate a fluence profile at every control point. The control points are then grouped and all of the control points in a given group are used to approximate the fluence profiles. A direct-aperture optimization is then used to improve the solution, taking into account the allowed range of leaf motion of the MLC. Dose is calculated using a fast convolution algorithm and the motion between control points is approximated by 100 interpolated dose calculation points. The method has been applied to five cases, consisting of lung, rectum, prostate and seminal vesicles, prostate and pelvic lymph nodes, and head and neck. The resulting plans have been compared with segmental (step-and-shoot) IMRT and delivered and verified on an Elekta Synergy to ensure practicality. Results: For the lung, prostate and seminal vesicles, and rectum cases, VMAT provides a plan of similar quality to segmental IMRT but with faster delivery by up to a factor of 4. For the prostate and pelvic nodes and head-and-neck cases, the critical structure doses are reduced with VMAT, both of these cases having a longer delivery time than IMRT. The plans in general verify successfully, although the agreement between planned and measured doses is not very close for the more complex cases, particularly the head-and-neck case. Conclusions: Depending upon the emphasis in the treatment planning, VMAT provides treatment plans which are higher in quality and/or faster to deliver than IMRT. The scheme described has been successfully introduced into clinical use.

  7. Automated radiotherapy treatment plan integrity verification

    Energy Technology Data Exchange (ETDEWEB)

    Yang Deshan; Moore, Kevin L. [Department of Radiation Oncology, School of Medicine, Washington University in Saint Louis, St. Louis, Missouri 63110 (United States)

    2012-03-15

    Purpose: In our clinic, physicists spend from 15 to 60 min to verify the physical and dosimetric integrity of radiotherapy plans before presentation to radiation oncology physicians for approval. The purpose of this study was to design and implement a framework to automate as many elements of this quality control (QC) step as possible. Methods: A comprehensive computer application was developed to carry out a majority of these verification tasks in the Philips PINNACLE treatment planning system (TPS). This QC tool functions based on both PINNACLE scripting elements and PERL sub-routines. The core of this technique is the method of dynamic scripting, which involves a PERL programming module that is flexible and powerful for treatment plan data handling. Run-time plan data are collected, saved into temporary files, and analyzed against standard values and predefined logical rules. The results were summarized in a hypertext markup language (HTML) report that is displayed to the user. Results: This tool has been in clinical use for over a year. The occurrence frequency of technical problems, which would cause delays and suboptimal plans, has been reduced since clinical implementation. Conclusions: In addition to drastically reducing the set of human-driven logical comparisons, this QC tool also accomplished some tasks that are otherwise either quite laborious or impractical for humans to verify, e.g., identifying conflicts amongst IMRT optimization objectives.

  8. Optimal Planning and Problem-Solving

    Science.gov (United States)

    Clemet, Bradley; Schaffer, Steven; Rabideau, Gregg

    2008-01-01

    CTAEMS MDP Optimal Planner is a problem-solving software designed to command a single spacecraft/rover, or a team of spacecraft/rovers, to perform the best action possible at all times according to an abstract model of the spacecraft/rover and its environment. It also may be useful in solving logistical problems encountered in commercial applications such as shipping and manufacturing. The planner reasons around uncertainty according to specified probabilities of outcomes using a plan hierarchy to avoid exploring certain kinds of suboptimal actions. Also, planned actions are calculated as the state-action space is expanded, rather than afterward, to reduce by an order of magnitude the processing time and memory used. The software solves planning problems with actions that can execute concurrently, that have uncertain duration and quality, and that have functional dependencies on others that affect quality. These problems are modeled in a hierarchical planning language called C_TAEMS, a derivative of the TAEMS language for specifying domains for the DARPA Coordinators program. In realistic environments, actions often have uncertain outcomes and can have complex relationships with other tasks. The planner approaches problems by considering all possible actions that may be taken from any state reachable from a given, initial state, and from within the constraints of a given task hierarchy that specifies what tasks may be performed by which team member.

  9. GPU-Monte Carlo based fast IMRT plan optimization

    Directory of Open Access Journals (Sweden)

    Yongbao Li

    2014-03-01

    Full Text Available Purpose: Intensity-modulated radiation treatment (IMRT plan optimization needs pre-calculated beamlet dose distribution. Pencil-beam or superposition/convolution type algorithms are typically used because of high computation speed. However, inaccurate beamlet dose distributions, particularly in cases with high levels of inhomogeneity, may mislead optimization, hindering the resulting plan quality. It is desire to use Monte Carlo (MC methods for beamlet dose calculations. Yet, the long computational time from repeated dose calculations for a number of beamlets prevents this application. It is our objective to integrate a GPU-based MC dose engine in lung IMRT optimization using a novel two-steps workflow.Methods: A GPU-based MC code gDPM is used. Each particle is tagged with an index of a beamlet where the source particle is from. Deposit dose are stored separately for beamlets based on the index. Due to limited GPU memory size, a pyramid space is allocated for each beamlet, and dose outside the space is neglected. A two-steps optimization workflow is proposed for fast MC-based optimization. At first step, a rough dose calculation is conducted with only a few number of particle per beamlet. Plan optimization is followed to get an approximated fluence map. In the second step, more accurate beamlet doses are calculated, where sampled number of particles for a beamlet is proportional to the intensity determined previously. A second-round optimization is conducted, yielding the final result.Results: For a lung case with 5317 beamlets, 105 particles per beamlet in the first round, and 108 particles per beam in the second round are enough to get a good plan quality. The total simulation time is 96.4 sec.Conclusion: A fast GPU-based MC dose calculation method along with a novel two-step optimization workflow are developed. The high efficiency allows the use of MC for IMRT optimizations.--------------------------------Cite this article as: Li Y, Tian Z

  10. WiMax network planning and optimization

    CERN Document Server

    Zhang, Yan

    2009-01-01

    This book offers a comprehensive explanation on how to dimension, plan, and optimize WiMAX networks. The first part of the text introduces WiMAX networks architecture, physical layer, standard, protocols, security mechanisms, and highly related radio access technologies. It covers system framework, topology, capacity, mobility management, handoff management, congestion control, medium access control (MAC), scheduling, Quality of Service (QoS), and WiMAX mesh networks and security. Enabling easy understanding of key concepts and technologies, the second part presents practical examples and illu

  11. WE-B-304-03: Biological Treatment Planning

    Energy Technology Data Exchange (ETDEWEB)

    Orton, C. [Wayne State University, Detroit, MI (United States)

    2015-06-15

    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 by 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.

  12. Evolutionary optimization technique for site layout planning

    KAUST Repository

    El Ansary, Ayman M.

    2014-02-01

    Solving the site layout planning problem is a challenging task. It requires an iterative approach to satisfy design requirements (e.g. energy efficiency, skyview, daylight, roads network, visual privacy, and clear access to favorite views). These design requirements vary from one project to another based on location and client preferences. In the Gulf region, the most important socio-cultural factor is the visual privacy in indoor space. Hence, most of the residential houses in this region are surrounded by high fences to provide privacy, which has a direct impact on other requirements (e.g. daylight and direction to a favorite view). This paper introduces a novel technique to optimally locate and orient residential buildings to satisfy a set of design requirements. The developed technique is based on genetic algorithm which explores the search space for possible solutions. This study considers two dimensional site planning problems. However, it can be extended to solve three dimensional cases. A case study is presented to demonstrate the efficiency of this technique in solving the site layout planning of simple residential dwellings. © 2013 Elsevier B.V. All rights reserved.

  13. Transmission network expansion planning with simulation optimization

    Energy Technology Data Exchange (ETDEWEB)

    Bent, Russell W [Los Alamos National Laboratory; Berscheid, Alan [Los Alamos National Laboratory; Toole, G. Loren [Los Alamos National Laboratory

    2010-01-01

    Within the electric power literatW''e the transmi ssion expansion planning problem (TNEP) refers to the problem of how to upgrade an electric power network to meet future demands. As this problem is a complex, non-linear, and non-convex optimization problem, researchers have traditionally focused on approximate models. Often, their approaches are tightly coupled to the approximation choice. Until recently, these approximations have produced results that are straight-forward to adapt to the more complex (real) problem. However, the power grid is evolving towards a state where the adaptations are no longer easy (i.e. large amounts of limited control, renewable generation) that necessitates new optimization techniques. In this paper, we propose a generalization of the powerful Limited Discrepancy Search (LDS) that encapsulates the complexity in a black box that may be queJied for information about the quality of a proposed expansion. This allows the development of a new optimization algOlitlun that is independent of the underlying power model.

  14. Advanced Treatment Planning in Cancer Thermal Therapies

    Institute of Scientific and Technical Information of China (English)

    Theodoros SAMARAS; Esra NEUFELD; Niels KUSTER

    2016-01-01

    CEM43 thermal dose is a very common concept in thermal oncology. Thermal dose is the maximum amount of energy that can be transmitted during hyperthermia therapy conducted on temperature-sensitive tissue. Thermal dose is also the maximum value of local energy accumulation in human bodies, which can lead to tissue injury and pain. Thermal dose can also decrease the ifnishing temperature and reduce the energy to the tolerable range. There are two functions of the individualized hyperthermia treatment plan: it determines the setting and location that can realize the best tumor hyperthermia therapy; at the same time, it can decrease the effect of hyperthermia therapy on healthy tissues. There are four steps in the treatment plan of hyperthermia therapy for tumors: the ifrst step is to establish a three dimensional human body model and its corresponding an atomical structure that can be used in numerical algorithmvia medical imaging resources; the second step is to determine the volume of the electromagnetic energy accumulation. Based on the peculiarity of frequency and materials, even full-wave electromagnetic wave or quasi-static technique can be used to determine the tissue distribution. Evaluation of the therapy can be conducted based on thermal dose and the corresponding tissue damage model; the third step is to use Arrhenius model to provide direct evaluation of tissues in the thermal ablation zone, solidiifcation zone, as well as the necrotic area; the last step is the optimization of the treatment plan.

  15. Sub-optimality analysis of mobile robot rolling path planning

    Institute of Scientific and Technical Information of China (English)

    张纯刚; 席裕庚

    2003-01-01

    Rolling planning is an efficient method for path planning in uncertain environment. In this paper, the general principle and algorithm of mobile robot path planning based on rolling windows are studied. The sub-optimality of rolling path planning is analyzed in details and explained with a concrete example.

  16. Optimization of verification pretreatment of plans of radiotherapy treatment with the technique of arcoterapia with RapidArc VMAT intensity-modulated; Optimizacion de la verificacion pretratamiento de los planes de tratamiento radioterapico con la tecnica de arcoterapia con intensidad modulada RapidArc VMAT

    Energy Technology Data Exchange (ETDEWEB)

    Serna Berna, A.; Puchades Puchades, V.; Mata Cologro, F.; Ramos Amores, D.

    2013-07-01

    The pretreatment verification of plans arcoterapia intensity modulated (VMAT) increases the workload on the services of radio physics. These checks focus with two objectives: First, check the dose calculation system for treatment planning; and second verify that the accelerator is able to administer treatment as has been planned. There are different commercial solutions to facilitate this procedure. The purpose of this paper is to compare the efficiency of four sets of independent verification to establish an optimal protocol. (Author)

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

    Energy Technology Data Exchange (ETDEWEB)

    Tiwari, P; Chen, Y [Memorial Sloan Kettering Cancer Center, New York, NY (United States); Hong, L; Apte, A; Yang, J; Mechalakos, J; Mageras, G; Hunt, M; Deasy, J [Washington University in St. Louis (United States)

    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, while sparing key sensitive organs from radiation. In the second step, the algorithm finds the best beamlet weight to reduce toxicity risks to normal tissue while holding the objective function achieved in the first step as a constraint, with a small amount of allowed slip. Likewise, the third and fourth steps introduce lower priority normal tissue goals and beam smoothing. We compared with prostate treatment plans from Memorial Sloan Kettering Cancer Center developed using Eclipse, with a prescription dose of 72 Gy. A combination of liear, quadratic, and gEUD objective functions were used with a modified open source solver code (IPOPT). Results Initial plan results on 3 different cases show that the automated planning system is capable of competing or improving on expert-driven eclipse plans. Compared to the Eclipse planning system, the automated system produced up to 26% less mean dose to rectum and 24% less mean dose to bladder while having the same D95 (after matching) to the target. Conclusion We have demonstrated that Pareto optimal treatment plans can be generated automatically without a trial-and-error process. The solver finds an optimal plan for the given patient, as opposed to database-driven approaches that set parameters based on geometry and population modeling.

  18. SU-E-T-572: A Plan Quality Metric for Evaluating Knowledge-Based Treatment Plans.

    Science.gov (United States)

    Chanyavanich, V; Lo, J; Das, S

    2012-06-01

    In prostate IMRT treatment planning, the variation in patient anatomy makes it difficult to estimate a priori the potentially achievable extent of dose reduction possible to the rectum and bladder. We developed a mutual information-based framework to estimate the achievable plan quality for a new patient, prior to any treatment planning or optimization. The knowledge-base consists of 250 retrospective prostate IMRT plans. Using these prior plans, twenty query cases were each matched with five cases from the database. We propose a simple DVH plan quality metric (PQ) based on the weighted-sum of the areas under the curve (AUC) of the PTV, rectum and bladder. We evaluate the plan quality of knowledge-based generated plans, and established a correlation between the plan quality and case similarity. The introduced plan quality metric correlates well (r2 = 0.8) with the mutual similarity between cases. A matched case with high anatomical similarity can be used to produce a new high quality plan. Not surprisingly, a poorly matched case with low degree of anatomical similarity tends to produce a low quality plan, since the adapted fluences from a dissimilar case cannot be modified sufficiently to yield acceptable PTV coverage. The plan quality metric is well-correlated to the degree of anatomical similarity between a new query case and matched cases. Further work will investigate how to apply this metric to further stratify and select cases for knowledge-based planning. © 2012 American Association of Physicists in Medicine.

  19. Evolving strategies for optimal care management and plan benefit designs.

    Science.gov (United States)

    Cruickshank, John M

    2012-11-01

    As a prevalent, complex disease, diabetes presents a challenge to managed care. Strategies to optimize type 2 diabetes care management and treatment outcomes have been evolving over the past several years. Novel economic incentive programs (eg, those outlined in the Patient Protection and Affordable Care Act of 2010 that tie revenue from Medicare Advantage plans to the quality of healthcare delivered) are being implemented, as are evidence-based interventions designed to optimize treatment, reduce clinical complications, and lower the total financial burden of the disease. Another step that can improve outcomes is to align managed care diabetes treatment algorithms with national treatment guidelines. In addition, designing the pharmacy benefit to emphasize the overall value of treatment and minimize out-of-pocket expenses for patients can be an effective approach to reducing prescription abandonment. The implementation of emerging models of care that encourage collaboration between providers, support lifestyle changes, and engage patients to become partners in their own treatment also appears to be effective.

  20. Optimal Reliability-Based Planning of Experiments for POD Curves

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard; Faber, M. H.; Kroon, I. B.

    Optimal planning of the crack detection test is considered. The test are used to update the information on the reliability of the inspection techniques modelled by probability of detection (P.O.D.) curves. It is shown how cost-optimal and reliability based test plans can be obtained using First...

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

    Science.gov (United States)

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

    2013-07-01

    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. 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. When considering tradeoffs, the optimal number of intensity levels depends on the treatment site and on the stage in the process

  2. The effect of gantry spacing resolution on plan quality in a single modulated arc optimization.

    Science.gov (United States)

    Mihaylov, Ivaylo B; Curran, Bruce; Sternick, Edward

    2011-11-15

    Volumetric-modulated arc technique (VMAT) is an efficient form of IMRT delivery. It is advantageous over conventional IMRT in terms of treatment delivery time. This study investigates the relation between the number of segments and plan quality in VMAT optimization for a single modulated arc. Five prostate, five lung, and five head-and-neck (HN) patient plans were studied retrospectively. For each case, four VMAT plans were generated. The plans differed only in the number of control points used in the optimization process. The control points were spaced 2°, 3°, 4°, and 6° apart, respectively. All of the optimization parameters were the same among the four schemes. The 2° spacing plan was used as a reference to which the other three plans were compared. The plan quality was assessed by comparison of dose indices (DIs) and generalized equivalent uniform doses (gEUDs) for targets and critical structures. All optimization schemes generated clinically acceptable plans. The differences between the majority of reference and compared DIs and gEUDs were within 3%. DIs and gEUDs which differed in excess of 3% corresponded to dose levels well below the organ tolerances. The DI and the gEUD differences increased with an increase in plan complexity from prostates to HNs. Optimization with gantry spacing resolution of 4° seems to be a very balanced alternative between plan quality and plan complexity.

  3. Optimal Reliability-Based Planning of Experiments for POD Curves

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard; Faber, M. H.; Kroon, I. B.

    Optimal planning of the crack detection test is considered. The test are used to update the information on the reliability of the inspection techniques modelled by probability of detection (P.O.D.) curves. It is shown how cost-optimal and reliability based test plans can be obtained using First O...... Order Reliability Methods in combination with life-cycle cost-optimal inspection and maintenance planning. The methodology is based on preposterior analyses from Bayesian decision theory. An illustrative example is shown.......Optimal planning of the crack detection test is considered. The test are used to update the information on the reliability of the inspection techniques modelled by probability of detection (P.O.D.) curves. It is shown how cost-optimal and reliability based test plans can be obtained using First...

  4. Optimal Road Capacity Building : Road Planning by Marginal Cost Pricing

    OpenAIRE

    NEMOTO, Toshinori; Misui, Yuki; Kajiwara, Akira

    2009-01-01

    The purpose of this study is to propose a new road planning and financing scheme based on short-term social marginal cost pricing that facilitates the establishment of optimal road standards in the long term. We conducted a simulation analysis based on the proposed planning scheme and observed that the simulation calculated the optimal road capacity in the future, and thus proved that the new planning scheme is feasible.

  5. A broad scope knowledge based model for optimization of VMAT in esophageal cancer: validation and assessment of plan quality among different treatment centers.

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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

  7. Volume visualization in radiation treatment planning.

    Science.gov (United States)

    Pelizzari, C A; Chen, G T

    2000-12-01

    Radiation treatment planning (RTP), historically an image-intensive discipline and one of the first areas in which 3D information from imaging was clinically applied, has become even more critically dependent on accurate 3D definition of target and non-target structures in recent years with the advent of conformal radiation therapy. In addition to the interactive display of wireframe or shaded surface models of anatomic objects, proposed radiation beams, beam modifying devices, and calculated dose distributions, recently significant use has been made of direct visualization of relevant anatomy from image data. Dedicated systems are commercially available for the purpose of geometrically optimizing beam placement, implementing in virtual reality the functionality of standard radiation therapy simulators. Such "CT simulation" systems rely heavily on 3D visualization and on reprojection of image data to produce simulated radiographs for comparison with either diagnostic-quality radiographs made on a simulator or megavoltage images made using the therapeutic beams themselves. Although calculation and analysis of dose distributions is an important component of radiation treatment design, geometric targeting with optimization based on 3D anatomic information is frequently performed as a separate step independent of dose calculations.

  8. Optimism and Planning for Future Care Needs among Older Adults

    Science.gov (United States)

    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

  9. Methodology for commissioning a brachytherapy treatment planning system in the era of 3D planning.

    Science.gov (United States)

    Dempsey, Claire

    2010-12-01

    To describe the steps undertaken to commission a 3D high dose rate (HDR) brachytherapy treatment planning system (TPS). Emphasis was placed on validating previously published recommendations, in addition to checking 3D parameters such as treatment optimization and dose volume histogram (DVH) analysis. Commissioning was performed of the brachytherapy module of the Nucletron Oncentra MasterPlan treatment planning system (version 3.2). Commissioning test results were compared to an independent external beam TPS (Varian Eclipse v 8.6) and the previously commissioned Nucletron Plato (v 14.3.7) brachytherapy treatment planning system, with point doses also independently verified using the brachytherapy module in RadCalc (v 6.0) independent point dose calculation software. Tests were divided into eight categories: (i) Image import accuracy, (ii) Reconstruction accuracy, (iii) Source configuration data check, (iv) Dose calculation accuracy, (v) Treatment optimization validation, (vi) DVH reproducibility, (vii) Treatment export check and (viii) Printout consistency. Point dose agreement between Oncentra, Plato and RadCalc was better than 5% with source data and dose calculation protocols following the American Association of Physicists in Medicine (AAPM) guidelines. Testing of image accuracy (import and reconstruction), along with validation of automated treatment optimization and DVH analysis generated a more comprehensive set of testing procedures than previously listed in published recommendations.

  10. The Comparison Study of Quadratic Infinite Beam Program on Optimization Instensity Modulated Radiation Therapy Treatment Planning (IMRTP) between Threshold and Exponential Scatter Method with CERR® In The Case of Lung Cancer

    Science.gov (United States)

    Hardiyanti, Y.; Haekal, M.; Waris, A.; Haryanto, F.

    2016-08-01

    This research compares the quadratic optimization program on Intensity Modulated Radiation Therapy Treatment Planning (IMRTP) with the Computational Environment for Radiotherapy Research (CERR) software. We assumed that the number of beams used for the treatment planner was about 9 and 13 beams. The case used the energy of 6 MV with Source Skin Distance (SSD) of 100 cm from target volume. Dose calculation used Quadratic Infinite beam (QIB) from CERR. CERR was used in the comparison study between Gauss Primary threshold method and Gauss Primary exponential method. In the case of lung cancer, the threshold variation of 0.01, and 0.004 was used. The output of the dose was distributed using an analysis in the form of DVH from CERR. The maximum dose distributions obtained were on the target volume (PTV) Planning Target Volume, (CTV) Clinical Target Volume, (GTV) Gross Tumor Volume, liver, and skin. It was obtained that if the dose calculation method used exponential and the number of beam 9. When the dose calculation method used the threshold and the number of beam 13, the maximum dose distributions obtained were on the target volume PTV, GTV, heart, and skin.

  11. Brachytherapy treatment planning algorithm applied to prostate cancer

    Science.gov (United States)

    Herrera-Rodríguez, M. R.; Martínez-Dávalos, A.

    2000-10-01

    An application of Genetic Algorithms (GAs) for treatment planning optimization in prostate brachytherapy is presented. The importance of multi-objective selection criteria based on the contour of the volume of interest and radiosensitive structures such as the rectum and urethra is discussed. First results are obtained for a simple test case which presents radial symmetry.

  12. Impact of dose calculation accuracy during optimization on lung IMRT plan quality.

    Science.gov (United States)

    Li, Ying; Rodrigues, Anna; Li, Taoran; Yuan, Lulin; Yin, Fang-Fang; Wu, Q Jackie

    2015-01-08

    The purpose of this study was to evaluate the effect of dose calculation accuracy and the use of an intermediate dose calculation step during the optimization of intensity-modulated radiation therapy (IMRT) planning on the final plan quality for lung cancer patients. This study included replanning for 11 randomly selected free-breathing lung IMRT plans. The original plans were optimized using a fast pencil beam convolution algorithm. After optimization, the final dose calculation was performed using the analytical anisotropic algorithm (AAA). The Varian Treatment Planning System (TPS) Eclipse v11, includes an option to perform intermediate dose calculation during optimization using the AAA. The new plans were created using this intermediate dose calculation during optimization with the same planning objectives and dose constraints as in the original plan. Differences in dosimetric parameters for the planning target volume (PTV) dose coverage, organs-at-risk (OARs) dose sparing, and the number of monitor units (MU) between the original and new plans were analyzed. Statistical significance was determined with a p-value of less than 0.05. All plans were normalized to cover 95% of the PTV with the prescription dose. Compared with the original plans, the PTV in the new plans had on average a lower maximum dose (69.45 vs. 71.96Gy, p = 0.005), a better homogeneity index (HI) (0.08 vs. 0.12, p = 0.002), and a better conformity index (CI) (0.69 vs. 0.59, p = 0.003). In the new plans, lung sparing was increased as the volumes receiving 5, 10, and 30 Gy were reduced when compared to the original plans (40.39% vs. 42.73%, p = 0.005; 28.93% vs. 30.40%, p = 0.001; 14.11%vs. 14.84%, p = 0.031). The volume receiving 20 Gy was not significantly lower (19.60% vs. 20.38%, p = 0.052). Further, the mean dose to the lung was reduced in the new plans (11.55 vs. 12.12 Gy, p = 0.024). For the esophagus, the mean dose, the maximum dose, and the volumes receiving 20 and 60 Gy were lower in

  13. Integrating robust timetabling in line plan optimization for railway systems

    DEFF Research Database (Denmark)

    Burggraeve, Sofie; Bull, Simon Henry; Vansteenwegen, Pieter

    2017-01-01

    We propose a heuristic algorithm to build a railway line plan from scratch that minimizes passenger travel time and operator cost and for which a feasible and robust timetable exists. A line planning module and a timetabling module work iteratively and interactively. The line planning module...... creates an initial line plan. The timetabling module evaluates the line plan and identifies a critical line based on minimum buffer times between train pairs. The line planning module proposes a new line plan in which the time length of the critical line is modified in order to provide more flexibility......, but is constrained by limited shunt capacity. While the operator and passenger cost remain close to those of the initially and (for these costs) optimally built line plan, the timetable corresponding to the finally developed robust line plan significantly improves the minimum buffer time, and thus the robustness...

  14. Comparison of step and shoot IMRT treatment plans generated by three inverse treatment planning systems; Comparacion de tratamientos de IMRT estatica generados por tres sistemas de planificacion inversa

    Energy Technology Data Exchange (ETDEWEB)

    Perez Moreno, J. M.; Zucca Aparicio, D.; Fernandez leton, P.; Garcia Ruiz-Zorrilla, J.; Minambres Moro, A.

    2011-07-01

    One of the most important issues of intensity modulated radiation therapy (IMRT) treatments using the step-and-shoot technique is the number of segments and monitor units (MU) for treatment delivery. These parameters depend heavily on the inverse optimization module of the treatment planning system (TPS) used. Three commercial treatment planning systems: CMS XiO, iPlan and Prowess Panther have been evaluated. With each of them we have generated a treatment plan for the same group of patients, corresponding to clinical cases. Dosimetric results, MU calculated and number of segments were compared. Prowess treatment planning system generates plans with a number of segments significantly lower than other systems, while MU are less than a half. It implies important reductions in leakage radiation and delivery time. Degradation in the final dose calculation of dose is very small, because it directly optimizes positions of multileaf collimator (MLC). (Author) 13 refs.

  15. UMTS network planning, optimization, and inter-operation with GSM

    CERN Document Server

    Rahnema, Moe

    2008-01-01

    UMTS Network Planning, Optimization, and Inter-Operation with GSM is an accessible, one-stop reference to help engineers effectively reduce the time and costs involved in UMTS deployment and optimization. Rahnema includes detailed coverage from both a theoretical and practical perspective on the planning and optimization aspects of UMTS, and a number of other new techniques to help operators get the most out of their networks. Provides an end-to-end perspective, from network design to optimizationIncorporates the hands-on experiences of numerous researchersSingle

  16. Disregarding RBE variation in treatment plan comparison may lead to bias in favor of proton plans.

    Science.gov (United States)

    Wedenberg, Minna; Toma-Dasu, Iuliana

    2014-09-01

    Currently in proton radiation therapy, a constant relative biological effectiveness (RBE) equal to 1.1 is assumed. The purpose of this study is to evaluate the impact of disregarding variations in RBE on the comparison of proton and photon treatment plans. Intensity modulated treatment plans using photons and protons were created for three brain tumor cases with the target situated close to organs at risk. The proton plans were optimized assuming a standard RBE equal to 1.1, and the resulting linear energy transfer (LET) distribution for the plans was calculated. In the plan evaluation, the effect of a variable RBE was studied. The RBE model used considers the RBE variation with dose, LET, and the tissue specific parameter α/β of photons. The plan comparison was based on dose distributions, DVHs and normal tissue complication probabilities (NTCPs). Under the assumption of RBE=1.1, higher doses to the tumor and lower doses to the normal tissues were obtained for the proton plans compared to the photon plans. In contrast, when accounting for RBE variations, the comparison showed lower doses to the tumor and hot spots in organs at risk in the proton plans. These hot spots resulted in higher estimated NTCPs in the proton plans compared to the photon plans. Disregarding RBE variations might lead to suboptimal proton plans giving lower effect in the tumor and higher effect in normal tissues than expected. For cases where the target is situated close to structures sensitive to hot spot doses, this trend may lead to bias in favor of proton plans in treatment plan comparisons.

  17. Modeling to Optimize Hospital Evacuation Planning in EMS Systems.

    Science.gov (United States)

    Bish, Douglas R; Tarhini, Hussein; Amara, Roel; Zoraster, Richard; Bosson, Nichole; Gausche-Hill, Marianne

    2017-01-01

    To develop optimal hospital evacuation plans within a large urban EMS system using a novel evacuation planning model and a realistic hospital evacuation scenario, and to illustrate the ways in which a decision support model may be useful in evacuation planning. An optimization model was used to produce detailed evacuation plans given the number and type of patients in the evacuating hospital, resource levels (teams to move patients, vehicles, and beds at other hospitals), and evacuation rules. Optimal evacuation plans under various resource levels and rules were developed and high-level metrics were calculated, including evacuation duration and the utilization of resources. Using this model we were able to determine the limiting resources and demonstrate how strategically augmenting the resource levels can improve the performance of the evacuation plan. The model allowed the planner to test various evacuation conditions and resource levels to demonstrate the effect on performance of the evacuation plan. We present a hospital evacuation planning analysis for a hospital in a large urban EMS system using an optimization model. This model can be used by EMS administrators and medical directors to guide planning decisions and provide a better understanding of various resource allocation decisions and rules that govern a hospital evacuation.

  18. Model-based Optimal Evacuation Planning anticipating Traveler Compliance Behavior

    NARCIS (Netherlands)

    Pel, A.J.; Huibregtse, O.L.; Hoogendoorn, S.P.; Bliemer, M.C.J.

    2010-01-01

    Instructing evacuees on their departure time, destination, and route can lead to more efficient evacuation traffic operations. While current evacuation plan optimization techniques are limited to assessing mandatory evacuation where travelers strictly follow the instructions, in reality a share of

  19. Optimization of energy planning strategies in municipalities

    DEFF Research Database (Denmark)

    Petersen, Jens-Phillip

    The paper evaluates the current status of community energy planning in northern Europe via a review of literature, practice and the performance of a barrier analysis for successful community energy planning. Main findings of the paper are that current community energy planning lacks a systematic...... approach, suffers from insufficient information, tools and resources. Municipalities are often unable to take on a steering role in community energy planning. To overcome these barriers and guide municipalities in the pre-project phase, a decision-support methodology, based on community energy profiles...... (CEP), is presented. The methodology was applied in a case study in Germany. With CEPs, a possibility to merge qualitative data from local settings into generic energy modelling is shown, which could contribute to improved community energy strategies....

  20. Data Center Optimization Initiative Strategic Plans

    Data.gov (United States)

    Social Security Administration — On August 1, 2016, the Office of Management and Budget issued memorandum M-16-19, establishing the Data Center Optimization Initiative (DCOI). The DCOI, as described...

  1. Optimal production planning for PCB assembly

    CERN Document Server

    Ho, William

    2006-01-01

    Focuses on the optimization of the Printed circuit board (PCB) assembly lines' efficiency. This book integrates the component sequencing and the feeder arrangement problems together for the pick-and-place machine and the chip shooter machines.

  2. Optimizing Rank of Landscape Planning Works of Urban Wetland Park

    Institute of Scientific and Technical Information of China (English)

    Qiao Li-fang; Zhang Yi-chuan; Qi An-guo; Li Xin-zheng

    2012-01-01

    Classifying and ranking the huge amounts of landscape planning works of urban wetland park is always difficult due to the multi-functions (ecological, leisure, educational and disaster prevention) of the urban wetland park. Therefore, an optimizing rank system is urgently needed. Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) models were used to rank the planning works of 30 urban wetland park based on four mainly factors, which included landscape ecological planning, landscape planning, ecological planning and economic planning. The study indicated that the AHP- TOPSIS model had good discrimination in the classification and ranking of landscape planning works of urban wetland park and it was also applicable to the planning works of other urban greenbelts.

  3. Direct leaf trajectory optimization for volumetric modulated arc therapy planning with sliding window delivery

    CERN Document Server

    Papp, Dávid

    2013-01-01

    We propose a novel optimization model for volumetric modulated arc therapy (VMAT) planning that directly optimizes deliverable leaf trajectories in the treatment plan optimization problem, and eliminates the need for a separate arc-sequencing step. In this model, a 360-degree arc is divided into a given number of arc segments in which the leaves move unidirectionally. This facilitates an algorithm that determines the optimal piecewise linear leaf trajectories for each arc segment, which are deliverable in a given treatment time. Multi-leaf collimator (MLC) constraints, including maximum leaf speed and interdigitation, are accounted for explicitly. The algorithm is customized to allow for VMAT delivery using constant gantry speed and dose rate, however, the algorithm generalizes to variable gantry speed if beneficial. We demonstrate the method for three different tumor sites: a head-and-neck case, a prostate case, and a paraspinal case. For that purpose, we first obtain a reference plan for intensity modulated...

  4. Brachytherapy optimal planning with application to intravascular radiation therapy

    DEFF Research Database (Denmark)

    Sadegh, Payman; Mourtada, Firas A.; Taylor, Russell H.;

    1999-01-01

    . Dose rate calculations are based on the sosimetry formulation of the American Association of Physicists in Medicine, Task Group 43. We apply the technique to optimal planning for intravascular brachytherapy of intimal hyperplasia using ultrasound data and 192Ir seeds. The planning includes...

  5. The study of cuckoo optimization algorithm for production planning problem

    OpenAIRE

    Akbarzadeh, Afsane; Shadkam, Elham

    2015-01-01

    Constrained Nonlinear programming problems are hard problems, and one of the most widely used and common problems for production planning problem to optimize. In this study, one of the mathematical models of production planning is survey and the problem solved by cuckoo algorithm. Cuckoo Algorithm is efficient method to solve continues non linear problem. Moreover, mentioned models of production planning solved with Genetic algorithm and Lingo software and the results will compared. The Cucko...

  6. Optimizing nursing human resource planning in British Columbia.

    Science.gov (United States)

    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.

  7. Optimizing Long-Term Capital Planning for Special Operations Forces

    Science.gov (United States)

    2015-06-01

    TERM CAPITAL PLANNING FOR SPECIAL OPERATIONS FORCES by Gretchen M. Radke June 2015 Thesis Advisor: Emily Craparo Co-Advisor: Jonathan Alt...REPORT TYPE AND DATES COVERED Master’s Thesis 4. TITLE AND SUBTITLE OPTIMIZING LONG-TERM CAPITAL PLANNING FOR SPECIAL OPERATIONS FORCES 5...words) The United States Special Operations Command (USSOCOM) J8 directorate is responsible for planning long-range capital expenditure for Special

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

    Science.gov (United States)

    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  cancer.

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

    Energy Technology Data Exchange (ETDEWEB)

    Chen, S; Zhang, H; Zhang, B; D’Souza, W [University of Maryland School of Medicine, Baltimore, MD (United States)

    2015-06-15

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

  10. Prior-knowledge treatment planning for volumetric arc therapy using feature-based database mining.

    Science.gov (United States)

    Schreibmann, Eduard; Fox, Tim

    2014-03-06

    Treatment planning for volumetric arc therapy (VMAT) is a lengthy process that requires many rounds of optimizations to obtain the best treatment settings and optimization constraints for a given patient's geometry. We propose a feature-selection search engine that explores previously treated cases of similar anatomy, returning the optimal plan configurations and attainable DVH constraints. Using an institutional database of 83 previously treated cases of prostate carcinoma treated with volumetric-modulated arc therapy, the search procedure first finds the optimal isocenter position with an optimization procedure, then ranks the anatomical similarity as the mean distance between targets. For the best matching plan, the planning information is reformatted to the DICOM format and imported into the treatment planning system to suggest isocenter, arc directions, MLC patterns, and optimization constraints that can be used as starting points in the optimization process. The approach was tested to create prospective treatment plans based on anatomical features that match previously treated cases from the institution database. By starting from a near-optimal solution and using previous optimization constraints, the best matching test only required simple optimization steps to further decrease target inhomogeneity, ultimately reducing time spend by the therapist in planning arcs' directions and lengths.

  11. Monitoring Hazardous Fuels Treatments: Southeast Regional Plan

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — The purpose of this document is to provide technical guidance on monitoring activities to refuge staff involved in planning and conducting hazardous fuel treatments....

  12. Multi-criteria optimization methods in radiation therapy planning: a review of technologies and directions

    CERN Document Server

    Craft, David

    2013-01-01

    We review the field of multi-criteria optimization for radiation therapy treatment planning. Special attention is given to the technique known as Pareto surface navigation, which allows physicians and treatment planners to interactively navigate through treatment planning options to get an understanding of the tradeoffs (dose to the target versus over-dosing of important nearby organs) involved in each patient's plan. We also describe goal programming and prioritized optimization, two other methods designed to handle multiple conflicting objectives. Issues related to nonconvexities, both in terms of dosimetric goals and the fact that the mapping from controllable hardware parameters to patient doses is usually nonconvex, are discussed at length since nonconvexities have a large impact on practical solution techniques for Pareto surface construction and navigation. A general planning strategy is recommended which handles the issue of nonconvexity by first finding an ideal Pareto surface with radiation delivere...

  13. Evolving treatment plan quality criteria from institution-specific experience.

    Science.gov (United States)

    Ruan, D; Shao, W; Demarco, J; Tenn, S; King, C; Low, D; Kupelian, P; Steinberg, M

    2012-05-01

    The dosimetric aspects of radiation therapy treatment plan quality are usually evaluated and reported with dose volume histogram (DVH) endpoints. For clinical practicality, a small number of representative quantities derived from the DVH are often used as dose endpoints to summarize the plan quality. National guidelines on reference values for such quantities for some standard treatment approaches are often used as acceptance criteria to trigger treatment plan review. On the other hand, treatment prescription and planning approaches specific to each institution warrants the need to report plan quality in terms of practice consistency and with respect to institution-specific experience. The purpose of this study is to investigate and develop a systematic approach to record and characterize the institution-specific plan experience and use such information to guide the design of plan quality criteria. In the clinical setting, this approach will assist in (1) improving overall plan quality and consistency and (2) detecting abnormal plan behavior for retrospective analysis. The authors propose a self-evolving methodology and have developed an in-house prototype software suite that (1) extracts the dose endpoints from a treatment plan and evaluates them against both national standard and institution-specific criteria and (2) evolves the statistics for the dose endpoints and updates institution-specific criteria. The validity of the proposed methodology was demonstrated with a database of prostate stereotactic body radiotherapy cases. As more data sets are accumulated, the evolving institution-specific criteria can serve as a reliable and stable consistency measure for plan quality and reveals the potential use of the "tighter" criteria than national standards or projected criteria, leading to practice that may push to shrink the gap between plans deemed acceptable and the underlying unknown optimality. The authors have developed a rationale to improve plan quality and

  14. OPTIMIZED AGRICULTURAL PLANNING OF SUGARCANE USING LINEAR PROGRAMMING

    Directory of Open Access Journals (Sweden)

    Maximiliano Salles Scarpari* and Edgar Gomes Ferreira de Beauclair**

    2010-03-01

    Full Text Available Optimized agricultural planning is a fundamental activity in business profitability because it can increase the returns from an operation with low additional costs. Nonetheless, the use of operations research adapted to sugarcane plantation management is still limited, resulting in decision-making at management level being primarily empirical. The goal of this work was to develop an optimized planning model for sugarcane farming using a linear programming tool. The program language used was General Algebraic Modelling System (GAMS as this system was seen to be an excellent tool to allow profit maximization and harvesting time schedule optimization in the sugar mill studied. The results presented support this optimized planning model as being a very useful tool for sugarcane management.

  15. Optimal Planning of Maintenance of Concrete Structures

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard; Engelund, S.

    1997-01-01

    of initiation of cerrosion in reinforced concrete structures as function of time. Further clifferent strategies for maintenance and repairs are formulated and it is shown how the probabilistic models can be used to estimate the expected costs for different strategies and how to select the optimal strategy....

  16. SERA - An Advanced Treatment Planning System for Neutron Therapy

    Energy Technology Data Exchange (ETDEWEB)

    C. A. Wemple; C. L. Albright; D. W. Nigg; D. W. Wessol; F. J. Wheeler; G. J. Harkin; M. B. Rossmeirer; M. T. Cohen; M. W. Frandsen

    1999-06-01

    The technology for computational dosimetry and treatment planning for Boron Neutron Capture Therapy (BNCT) has advanced significantly over the past few years. Because of the more complex nature of the problem, the computational methods that work well for treatment planning in photon radiotherapy are not applicable to BNCT. The necessary methods have, however, been developed and have been successfully employed both for research applications as well as human trials. Computational geometry for BNCT applications can be constructed directly from tomographic medical imagery and computed radiation dose distributions can be readily displayed in formats that are familiar to the radiotherapy community. The SERA system represents a significant advance in several areas for treatment planning. However further improvements in speed and results presentation are still needed for routine clinical applications, particularly when optimizations of dose pattern is required.

  17. Optimal Planning of Communication System of CPS for Distribution Network

    Directory of Open Access Journals (Sweden)

    Ting Yang

    2017-01-01

    Full Text Available IoT is the technical basis to realize the CPS (Cyber Physical System for distribution networks, with which the complex system becomes more intelligent and controllable. Because of the multihop and self-organization characteristics, the large-scale heterogeneous CPS network becomes more difficult to plan. Using topological potential theory, one of typical big data analysis technologies, this paper proposed a novel optimal CPS planning model. Topological potential equalization is considered as the optimization objective function in heterogeneous CPS network with the constraints of communication requirements, physical infrastructures, and network reliability. An improved binary particle swarm optimization algorithm is proposed to solve this complex optimal problem. Two IEEE classic examples are adopted in the simulation, and the results show that, compared with benchmark algorithms, our proposed method can provide an effective topology optimization scheme to improve the network reliability and transmitting performance.

  18. Improving treatment plan evaluation with automation.

    Science.gov (United States)

    Covington, Elizabeth L; Chen, Xiaoping; Younge, Kelly C; Lee, Choonik; Matuszak, Martha M; Kessler, Marc L; Keranen, Wayne; Acosta, Eduardo; Dougherty, Ashley M; Filpansick, Stephanie E; Moran, Jean M

    2016-11-01

    The goal of this work is to evaluate the effectiveness of Plan-Checker Tool (PCT) which was created to improve first-time plan quality, reduce patient delays, increase the efficiency of our electronic workflow, and standardize and automate the physics plan review in the treatment planning system (TPS). PCT uses an application programming interface to check and compare data from the TPS and treatment management system (TMS). PCT includes a comprehensive checklist of automated and manual checks that are documented when performed by the user as part of a plan readiness check for treatment. Prior to and during PCT development, errors identified during the physics review and causes of patient treatment start delays were tracked to prioritize which checks should be automated. Nineteen of 33 checklist items were automated, with data extracted with PCT. There was a 60% reduction in the number of patient delays in the six months after PCT release. PCT was successfully implemented for use on all external beam treatment plans in our clinic. While the number of errors found during the physics check did not decrease, automation of checks increased visibility of errors during the physics check, which led to decreased patient delays. The methods used here can be applied to any TMS and TPS that allows queries of the database. PACS number(s): 87.55.-x, 87.55.N-, 87.55.Qr, 87.55.tm, 89.20.Bb.

  19. Feasibility of identification of gamma knife planning strategies by identification of pareto optimal gamma knife plans.

    Science.gov (United States)

    Giller, C A

    2011-12-01

    The use of conformity indices to optimize Gamma Knife planning is common, but does not address important tradeoffs between dose to tumor and normal tissue. Pareto analysis has been used for this purpose in other applications, but not for Gamma Knife (GK) planning. The goal of this work is to use computer models to show that Pareto analysis may be feasible for GK planning to identify dosimetric tradeoffs. We define a GK plan A to be Pareto dominant to B if the prescription isodose volume of A covers more tumor but not more normal tissue than B, or if A covers less normal tissue but not less tumor than B. A plan is Pareto optimal if it is not dominated by any other plan. Two different Pareto optimal plans represent different tradeoffs between dose to tumor and normal tissue, because neither plan dominates the other. 'GK simulator' software calculated dose distributions for GK plans, and was called repetitively by a genetic algorithm to calculate Pareto dominant plans. Three irregular tumor shapes were tested in 17 trials using various combinations of shots. The mean number of Pareto dominant plans/trial was 59 ± 17 (sd). Different planning strategies were identified by large differences in shot positions, and 70 of the 153 coordinate plots (46%) showed differences of 5mm or more. The Pareto dominant plans dominated other nearby plans. Pareto dominant plans represent different dosimetric tradeoffs and can be systematically calculated using genetic algorithms. Automatic identification of non-intuitive planning strategies may be feasible with these methods.

  20. Planning for mARC treatments with the Eclipse treatment planning system.

    Science.gov (United States)

    Sarkar, Vikren; Huang, Long; Rassiah-Szegedi, Prema; Zhao, Hui; Huang, Jessica; Szegedi, Martin; Salter, Bill J

    2015-03-08

    While modulated arc (mARC) capabilities have been available on Siemens linear accelerators for almost two years now, there was, until recently, only one treatment planning system capable of planning these treatments. The Eclipse treatment planning system now offers a module that can plan for mARC treatments. The purpose of this work was to test the module to determine whether it is capable of creating clinically acceptable plans. A total of 23 plans were created for various clinical sites and all plans delivered without anomaly. The average 3%/3 mm gamma pass rate for the plans was 98.0%, with a standard deviation of 1.7%. For a total of 14 plans, an equivalent static gantry IMRT plan was also created to compare delivery time. In all but two cases, the mARC plans delivered significantly faster than the static gantry plan. We have confirmed the successful creation of mARC plans that are deliverable with high fidelity on an ARTISTE linear accelerator, thus demonstrating the successful implementation of the Eclipse mARC module.

  1. Pediatric radiotherapy planning and treatment

    CERN Document Server

    Olch, Arthur J

    2013-01-01

    "This is a very well-written and -organized book covering the planning and delivery aspects unique to pediatric radiotherapy. The author is a respected and well-known medical physicist with extensive pediatric radiotherapy experience. … a very useful book for any clinical physicist treating pediatric cases and seeking contextual and historical perspective. … a great reference for medical physicists who may not see many pediatric cases and can look to this text as a one-stop shop for not only a comprehensive overview, but detailed explanation for specific pediatric disease sites. Overall, it is a great addition to the reference library of any radiation therapy physicist."-Medical Physics, April 2014.

  2. Distribution System Optimization Planning Based on Plant Growth Simulation Algorithm

    Institute of Scientific and Technical Information of China (English)

    WANG Chun; CHENG Hao-zhong; HU Ze-chun; WANG Yi

    2008-01-01

    An approach for the integrated optimization of the construction/expansion capacity of high-voltage/medium-voltage (HV/MV) substations and the configuration of MV radial distribution network was presented using plant growth simulation algorithm (PGSA). In the optimization process, fixed costs correspondent to the investment in lines and substations and the variable costs associated to the operation of the system were considered under the constraints of branch capacity, substation capacity and bus voltage. The optimization variables considerably reduce the dimension of variables and speed up the process of optimizing. The effectiveness of the proposed approach was tested by a distribution system planning.

  3. TECHNIQUE OF OPTIMAL AUDIT PLANNING FOR INFORMATION SECURITY MANAGEMENT SYSTEM

    Directory of Open Access Journals (Sweden)

    F. N. Shago

    2014-03-01

    Full Text Available Complication of information security management systems leads to the necessity of improving the scientific and methodological apparatus for these systems auditing. Planning is an important and determining part of information security management systems auditing. Efficiency of audit will be defined by the relation of the reached quality indicators to the spent resources. Thus, there is an important and urgent task of developing methods and techniques for optimization of the audit planning, making it possible to increase its effectiveness. The proposed technique gives the possibility to implement optimal distribution for planning time and material resources on audit stages on the basis of dynamics model for the ISMS quality. Special feature of the proposed approach is the usage of a priori data as well as a posteriori data for the initial audit planning, and also the plan adjustment after each audit event. This gives the possibility to optimize the usage of audit resources in accordance with the selected criteria. Application examples of the technique are given while planning audit information security management system of the organization. The result of computational experiment based on the proposed technique showed that the time (cost audit costs can be reduced by 10-15% and, consequently, quality assessments obtained through audit resources allocation can be improved with respect to well-known methods of audit planning.

  4. Optimal Planning of Maintenance of Concrete Structures

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard; Engelund, S.

    1997-01-01

    Chloride ingress and progress of the carbonation front into concrete are considered. Probabilistic models are formulated and it is shown how the parameters in the models can be estimated on the basis of measurements using Bayesian statistics. The stochastic model is used to estimate the probability...... of initiation of cerrosion in reinforced concrete structures as function of time. Further clifferent strategies for maintenance and repairs are formulated and it is shown how the probabilistic models can be used to estimate the expected costs for different strategies and how to select the optimal strategy....

  5. 3D conformal planning using low segment multi-criteria IMRT optimization

    CERN Document Server

    Khan, Fazal

    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 treatment (3D-CRT) plans. Methods: Ten patients previously planned with 3D-CRT were replanned with a low-segment inverse multicriteria optimized technique. The MCO-3D plans used the same number of beams, beam geometry and machine parameters of the corresponding 3D plans, but were limited to an energy of 6 MV. The MCO-3D plans were optimized using a fluence-based MCO IMRT algorithm and then, after MCO navigation, segmented with a low number of segments. The 3D and MCO-3D plans were compared by evaluating mean doses to individual organs at risk (OARs), mean doses to combined OARs, homogeneity indexes (HI), monitor units (MUs), physician preference, and qualitative assessments of planning time and plan customizability. Results: The MCO-3D plans significantly reduced the OAR mean doses and monitor unit...

  6. On-line re-optimization of prostate IMRT plans for adaptive radiation therapy.

    Science.gov (United States)

    Wu, Q Jackie; Thongphiew, Danthai; Wang, Zhiheng; Mathayomchan, Boonyanit; Chankong, Vira; Yoo, Sua; Lee, W Robert; Yin, Fang-Fang

    2008-02-01

    For intermediate and high risk prostate cancer, both the prostate gland and seminal vesicles are included in the clinical target volume. Internal motion patterns of these two organs vary, presenting a challenge for adaptive treatment. Adaptive techniques such as isocenter repositioning and soft tissue alignment are effective when tumor volumes only exhibit translational shift, while direct re-optimization of the intensity-modulated radiation therapy (IMRT) plan maybe more desirable when extreme deformation or differential positioning changes of the organs occur. Currently, direct re-optimization of the IMRT plan using beamlet (or fluence map) has not been reported. In this study, we report a novel on-line re-optimization technique that can accomplish plan adjustment on-line. Deformable image registration is used to provide position variation information on each voxel along the three dimensions. The original planned dose distribution is used as the 'goal' dose distribution for adaptation and to ensure planning quality. Fluence maps are re-optimized via linear programming, and a plan solution can be achieved within 2 min. The feasibility of this technique is demonstrated with a clinical case with large deformation. Such on-line ART process can be highly valuable with hypo-fractionated prostate IMRT treatment.

  7. On-line re-optimization of prostate IMRT plans for adaptive radiation therapy

    Energy Technology Data Exchange (ETDEWEB)

    Wu, Q Jackie [Department of Radiation Oncology, Duke University Medical Center Durham, NC (United States); Thongphiew, Danthai [Department of Radiation Oncology, Duke University Medical Center Durham, NC (United States); Wang, Zhiheng [Department of Radiation Oncology, Duke University Medical Center Durham, NC (United States); Mathayomchan, Boonyanit [Department of Electrical Engineering and Computer Science, Case Western Reserve University Cleveland, OH (United States); Chankong, Vira [Department of Electrical Engineering and Computer Science, Case Western Reserve University Cleveland, OH (United States); Yoo, Sua [Department of Radiation Oncology, Duke University Medical Center Durham, NC (United States); Lee, W Robert [Department of Radiation Oncology, Duke University Medical Center Durham, NC (United States); Yin, Fang-Fang [Department of Radiation Oncology, Duke University Medical Center Durham, NC (United States)

    2008-02-07

    For intermediate and high risk prostate cancer, both the prostate gland and seminal vesicles are included in the clinical target volume. Internal motion patterns of these two organs vary, presenting a challenge for adaptive treatment. Adaptive techniques such as isocenter repositioning and soft tissue alignment are effective when tumor volumes only exhibit translational shift, while direct re-optimization of the intensity-modulated radiation therapy (IMRT) plan maybe more desirable when extreme deformation or differential positioning changes of the organs occur. Currently, direct re-optimization of the IMRT plan using beamlet (or fluence map) has not been reported. In this study, we report a novel on-line re-optimization technique that can accomplish plan adjustment on-line. Deformable image registration is used to provide position variation information on each voxel along the three dimensions. The original planned dose distribution is used as the 'goal' dose distribution for adaptation and to ensure planning quality. Fluence maps are re-optimized via linear programming, and a plan solution can be achieved within 2 min. The feasibility of this technique is demonstrated with a clinical case with large deformation. Such on-line ART process can be highly valuable with hypo-fractionated prostate IMRT treatment.

  8. On-line re-optimization of prostate IMRT plans for adaptive radiation therapy

    Science.gov (United States)

    Wu, Q. Jackie; Thongphiew, Danthai; Wang, Zhiheng; Mathayomchan, Boonyanit; Chankong, Vira; Yoo, Sua; Lee, W. Robert; Yin, Fang-Fang

    2008-02-01

    For intermediate and high risk prostate cancer, both the prostate gland and seminal vesicles are included in the clinical target volume. Internal motion patterns of these two organs vary, presenting a challenge for adaptive treatment. Adaptive techniques such as isocenter repositioning and soft tissue alignment are effective when tumor volumes only exhibit translational shift, while direct re-optimization of the intensity-modulated radiation therapy (IMRT) plan maybe more desirable when extreme deformation or differential positioning changes of the organs occur. Currently, direct re-optimization of the IMRT plan using beamlet (or fluence map) has not been reported. In this study, we report a novel on-line re-optimization technique that can accomplish plan adjustment on-line. Deformable image registration is used to provide position variation information on each voxel along the three dimensions. The original planned dose distribution is used as the 'goal' dose distribution for adaptation and to ensure planning quality. Fluence maps are re-optimized via linear programming, and a plan solution can be achieved within 2 min. The feasibility of this technique is demonstrated with a clinical case with large deformation. Such on-line ART process can be highly valuable with hypo-fractionated prostate IMRT treatment. Abstract and preliminary data presented at 49th AAPM Annual Meeting, Minneapolis, MN, USA, July 2007.

  9. Optimal quality reporting in markets for health plans.

    Science.gov (United States)

    Glazer, Jacob; McGuire, Thomas G

    2006-03-01

    Quality reports about health plans and providers are becoming more prevalent in health care markets. This paper casts the decision about what information to report to consumers about health plans as a policy decision. In a market with adverse selection, complete information about quality leads to inefficient outcomes. In a Rothschild-Stiglitz model, we show that averaging quality information into a summary report can enforce pooling in health insurance, and by choice of the right weights in the averaged report, a payer or regulator can induce first-best quality choices. The optimal quality report is as powerful as optimal risk adjustment in correcting adverse selection inefficiencies.

  10. Practice-Oriented Optimization of Distribution Network Planning Using Metaheuristic Algorithms

    NARCIS (Netherlands)

    Grond, M.O.W.; Luong, N.H.; Morren, J.; Bosman, P.A.N.; Slootweg, J.G.; La Poutré, J.A.

    2014-01-01

    Distribution network operators require more advanced planning tools to deal with the challenges of future network planning. An appropriate planning and optimization tool can identify which option for network extension should be selected from available alternatives. However, many optimization approac

  11. Optimal trajectory planning for natural biped walking locomotion

    Institute of Scientific and Technical Information of China (English)

    刘荣强; 焦映厚; 陈照波

    2003-01-01

    An optimal trajectory planning method has been proposed for the walking locomotion of a biped me-c hanical system with thighs, shanks and small feet, which is modelled as a 3-DOF link system consisting of aninverted pendulum and a 2-DOF swing leg. The locomotion of swing and supporting legs is solved by the optimaltrajectory planning based on function approximation. The optimal trajectory planning based on function approxi-mation. The optimal walking locomotion solution with minimum square of input torque exhibits a natural walkinggait with one step period of 0.64 s similar to the human walking gait by using the link parameters of an adult'sleg. It is concluded from the computation results that the method proposed in this paper has been proved to bean effective tool for solving the optimal walking locomotion and joint control torque problems for a 3-DOF bipedmechanism; when the ankle joint of the supporting leg is a passive joint, a nearly, optimal walking solution canbe obtained at t1 = 0. 49 s and t2 = 10 s, and however, when the knee is a passive joint, it is impossible to ob-tain a solution which satisfies the constraint condition; for the link parameters used in this paper, the length ofan optimal stride is 0.3 m.

  12. Monte Carlo Treatment Planning for Advanced Radiotherapy

    DEFF Research Database (Denmark)

    Cronholm, Rickard

    and validation of a Monte Carlo model of a medical linear accelerator (i), converting a CT scan of a patient to a Monte Carlo compliant phantom (ii) and translating the treatment plan parameters (including beam energy, angles of incidence, collimator settings etc) to a Monte Carlo input file (iii). A protocol...... previous algorithms since it uses delineations of structures in order to include and/or exclude certain media in various anatomical regions. This method has the potential to reduce anatomically irrelevant media assignment. In house MATLAB scripts translating the treatment plan parameters to Monte Carlo...

  13. Tolerance doses for treatment planning

    Energy Technology Data Exchange (ETDEWEB)

    Lyman, J.T.

    1985-10-01

    Data for the tolerance of normal tissues or organs to (low-LET) radiation has been compiled from a number of sources which are referenced at the end of this document. This tolerance dose data are ostensibly for uniform irradiation of all or part of an organ, and are for either 5% (TD/sub 5/) or 50% (TD/sub 50/) complication probability. The ''size'' of the irradiated organ is variously stated in terms of the absolute volume or the fraction of the organ volume irradiated, or the area or the length of the treatment field. The accuracy of these data is questionable. Much of the data represents doses that one or several experienced therapists have estimated could be safely given rather than quantitative analyses of clinical observations. Because these data have been obtained from multiple sources with possible different criteria for the definition of a complication, there are sometimes different values for what is apparently the same endpoint. The data from some sources shows a tendancy to be quantized in 5 Gy increments. This reflects the size of possible round off errors. It is believed that all these data have been accumulated without the benefit of 3-D dose distributions and therefore the estimates of the size of the volume and/or the uniformity of the irradiation may be less accurate than is now possible. 19 refs., 4 figs.

  14. Strategies for microwave thermal treatment planning, navigation, and assessment

    Science.gov (United States)

    Ryan, Thomas P.

    2011-03-01

    Thermal treatment is commonly performed interstitially in either surgical or percutaneous procedures, using microwave antenna sources at 915 or 2540 MHz. There are a number of tools or aids as well as challenges for clinicians performing these procedures in the course of patient treatment. These challenges will be present whether the procedure is surgical, laparoscopic, or percutaneous, and include treatment planning, image guidance, navigation, coregistration in 3D, and treatment assessment. Treatment planning has been used historically in hyperthermia for microwave antenna arrays, but has yet to be properly applied in thermal ablation. Image assessment of thermal treatment is not typically performed in real time, although these tools will provide the clinician with further information to understand the extent of treatment and whether further treatment is needed. 3D imaging is available, but not coregistered to patient space. Navigation has been used in many medical specialties, but is also not in the clinician's toolbox in thermal treatment. Although treatment planning will lay out the skin entry and trajectory for each antenna placed, subsequently, each antenna needs to be tracked to accurately show placement in the patient and overlaid in patient space, along with the tumor target location. Some patient treatments may consist of multiple, but sequential single placements of an antenna, and guidance is even more critical to track positions and plan for the next insertion. Lastly, real-time image assessment will show the extent and shape of the coagulated lesion and which targets may have been undertreated. If used synchronously in arrays, MW power steering may also aid in filling in the ablation as the treatment progresses. This paper will analyze the present state-of-the art as well as a strategy to incorporate the various facets of planning, guidance, and assessment of treatment. The integration of thermal treatment planning, navigation and guidance, robotics

  15. Optimal vehicle planning and the search tour problem

    Science.gov (United States)

    Wettergren, Thomas A.; Bays, Matthew J.

    2016-05-01

    We describe a problem of optimal planning for unmanned vehicles and illustrate two distinct procedures for its solution. The problem under consideration, which we refer to as the search tour problem, involves the determination of multi-stage plans for unmanned vehicles conducting search operations. These types of problems are important in situations where the searcher has varying performance in different regions throughout the domain due to environmental complexity. The ability to provide robust planning for unmanned systems under difficult environmental conditions is critical for their use in search operations. The problem we consider consists of searches with variable times for each of the stages, as well as an additional degree of freedom for each stage to select from one of a finite set of operational configurations. As each combination of configuration and stage time leads to a different performance level, there is a need to determine the optimal configuration of these stages. When the complexity of constraints on total time, as well as resources expended at each stage for a given configuration, are added, the problem becomes one of non-trivial search effort allocation and numerical methods of optimization are required. We show two solution approaches for this numerical optimization problem. The first solution technique is to use a mixed-integer linear programming formulation, for which commercially available solvers can find optimal solutions in a reasonable amount of time. We use this solution as a baseline and compare against a new inner/outer optimization formulation. This inner/outer optimization compares favorably to the baseline solution, but is also amenable to adaptation as the search operation progresses. Numerical examples illustrate the utility of the approach for unmanned vehicle search planning.

  16. Model-based Optimal Evacuation Planning anticipating Traveler Compliance Behavior

    NARCIS (Netherlands)

    Pel, A.J.; Huibregtse, O.L.; Hoogendoorn, S.P.; Bliemer, M.C.J.

    2010-01-01

    Instructing evacuees on their departure time, destination, and route can lead to more efficient evacuation traffic operations. While current evacuation plan optimization techniques are limited to assessing mandatory evacuation where travelers strictly follow the instructions, in reality a share of t

  17. SU-E-T-580: Comparison of Cervical Carcinoma IMRT Plans From Four Commercial Treatment Planning Systems (TPS)

    Energy Technology Data Exchange (ETDEWEB)

    Cao, Y; Li, R; Chi, Z; Zhu, S [The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei (China)

    2014-06-01

    Purpose: Different treatment planning systems (TPS) use different treatment optimization and leaf sequencing algorithms. This work compares cervical carcinoma IMRT plans optimized with four commercial TPSs to investigate the plan quality in terms of target conformity and delivery efficiency. Methods: Five cervical carcinoma cases were planned with the Corvus, Monaco, Pinnacle and Xio TPSs by experienced planners using appropriate optimization parameters and dose constraints to meet the clinical acceptance criteria. Plans were normalized for at least 95% of PTV to receive the prescription dose (Dp). Dose-volume histograms and isodose distributions were compared. Other quantities such as Dmin(the minimum dose received by 99% of GTV/PTV), Dmax(the maximum dose received by 1% of GTV/PTV), D100, D95, D90, V110%, V105%, V100% (the volume of GTV/PTV receiving 110%, 105%, 100% of Dp), conformity index(CI), homogeneity index (HI), the volume of receiving 40Gy and 50 Gy to rectum (V40,V50) ; the volume of receiving 30Gy and 50 Gy to bladder (V30,V50) were evaluated. Total segments and MUs were also compared. Results: While all plans meet target dose specifications and normal tissue constraints, the maximum GTVCI of Pinnacle plans was up to 0.74 and the minimum of Corvus plans was only 0.21, these four TPSs PTVCI had significant difference. The GTVHI and PTVHI of Pinnacle plans are all very low and show a very good dose distribution. Corvus plans received the higer dose of normal tissue. The Monaco plans require significantly less segments and MUs to deliver than the other plans. Conclusion: To deliver on a Varian linear-accelerator, the Pinnacle plans show a very good dose distribution. Corvus plans received the higer dose of normal tissue. The Monaco plans have faster beam delivery.

  18. Operations planning for agricultural harvesters using ant colony optimization

    Directory of Open Access Journals (Sweden)

    A. Bakhtiari

    2013-07-01

    Full Text Available An approach based on ant colony optimization for the generation for optimal field coverage plans for the harvesting operations using the optimal track sequence principle B-patterns was presented. The case where the harvester unloads to a stationary facility located out of the field area, or in the field boundary, was examined. In this operation type there are capacity constraints to the load that a primary unit, or a harvester in this specific case, can carry and consequently, it is not able to complete the task of harvesting a field area and therefore it has to leave the field area, to unload, and return to continue the task one or more times. Results from comparing the optimal plans with conventional plans generated by operators show reductions in the in-field nonworking distance in the range of 19.3-42.1% while the savings in the total non-working distance were in the range of 18-43.8%. These savings provide a high potential for the implementation of the ant colony optimization approach for the case of harvesting operations that are not supported by transport carts for the out-of-the-field removal of the crops, a practice case that is normally followed in developing countries, due to lack of resources.

  19. Treatment Planning Systems for BNCT Requirements and Peculiarities

    CERN Document Server

    Daquino, G G

    2003-01-01

    The main requirements and peculiarities expected from the BNCT-oriented treatment planning system (TPS) are summarized in this paper. The TPS is a software, which can be integrated or composed by several auxiliary programs. It plays important roles inside the whole treatment planning of the patient's organ in BNCT. However, the main goal is the simulation of the irradiation, in order to obtain the optimal configuration, in terms of neutron spectrum, patient positioning and dose distribution in the tumour and healthy tissues. The presence of neutrons increases the level of complexity, because much more nuclear reactions need to be monitored and properly calculated during the simulation of the patient's treatment. To this purposes several 3D geometry reconstruction techniques, generally based on the CT scanning data, are implemented and Monte Carlo codes are normally used. The TPSs are expected to show also the results (basically doses and fluences) in a proper format, such as isocurves (or isosurfaces) along t...

  20. Treatment planning for multicatheter interstitial brachytherapy of breast cancer - from Paris system to anatomy-based inverse planning.

    Science.gov (United States)

    Major, Tibor; Polgár, Csaba

    2017-02-01

    In the last decades, treatment planning for multicatheter interstitial breast brachytherapy has evolved considerably from fluoroscopy-based 2D to anatomy-based 3D planning. To plan the right positions of the catheters, ultrasound or computed tomography (CT) imaging can be used, but the treatment plan is always based on postimplant CT images. With CT imaging, the 3D target volume can be defined more precisely and delineation of the organs at risk volumes is also possible. Consequently, parameters calculated from dose-volume histogram can be used for quantitative plan evaluation. The catheter reconstruction is also easier and faster on CT images compared to X-ray films. In high dose rate brachytherapy, using a stepping source, a number of forward dose optimization methods (manual, geometrical, on dose points, graphical) are available to shape the dose distribution to the target volume, and these influence dose homogeneities to different extent. Currently, inverse optimization algorithms offer new possibilities to improve dose distributions further considering the requirements for dose coverage, dose homogeneity, and dose to organs at risk simultaneously and automatically. In this article, the evolvement of treatment planning for interstitial breast implants is reviewed, different forward optimization methods are discussed, and dose-volume parameters used for quantitative plan evaluation are described. Finally, some questions of the inverse optimization method are investigated and initial experiences of the authors are presented.

  1. Treatment planning for multicatheter interstitial brachytherapy of breast cancer – from Paris system to anatomy-based inverse planning

    Directory of Open Access Journals (Sweden)

    Tibor Major

    2017-02-01

    Full Text Available In the last decades, treatment planning for multicatheter interstitial breast brachytherapy has evolved considerably from fluoroscopy-based 2D to anatomy-based 3D planning. To plan the right positions of the catheters, ultrasound or computed tomography (CT imaging can be used, but the treatment plan is always based on postimplant CT images. With CT imaging, the 3D target volume can be defined more precisely and delineation of the organs at risk volumes is also possible. Consequently, parameters calculated from dose-volume histogram can be used for quantitative plan evaluation. The catheter reconstruction is also easier and faster on CT images compared to X-ray films. In high dose rate brachytherapy, using a stepping source, a number of forward dose optimization methods (manual, geometrical, on dose points, graphical are available to shape the dose distribution to the target volume, and these influence dose homogeneities to different extent. Currently, inverse optimization algorithms offer new possibilities to improve dose distributions further considering the requirements for dose coverage, dose homogeneity, and dose to organs at risk simultaneously and automatically. In this article, the evolvement of treatment planning for interstitial breast implants is reviewed, different forward optimization methods are discussed, and dose-volume parameters used for quantitative plan evaluation are described. Finally, some questions of the inverse optimization method are investigated and initial experiences of the authors are presented.

  2. Inverse treatment planning for spinal robotic radiosurgery: an international multi-institutional benchmark trial.

    Science.gov (United States)

    Blanck, Oliver; Wang, Lei; Baus, Wolfgang; Grimm, Jimm; Lacornerie, Thomas; Nilsson, Joakim; Luchkovskyi, Sergii; Palazon Cano, Isabel; Shou, Zhenyu; Ayadi, Myriam; Treuer, Harald; Viard, Romain; Siebert, Frank-Andre; Chan, Mark K H; Hildebrandt, Guido; Dunst, Jürgen; Imhoff, Detlef; Wurster, Stefan; Wolff, Robert; Romanelli, Pantaleo; Lartigau, Eric; Semrau, Robert; Soltys, Scott G; Schweikard, Achim

    2016-01-01

    Stereotactic radiosurgery (SRS) is the accurate, conformal delivery of high-dose radiation to well-defined targets while minimizing normal structure doses via steep dose gradients. While inverse treatment planning (ITP) with computerized optimization algorithms are routine, many aspects of the planning process remain user-dependent. We performed an international, multi-institutional benchmark trial to study planning variability and to analyze preferable ITP practice for spinal robotic radiosurgery. 10 SRS treatment plans were generated for a complex-shaped spinal metastasis with 21 Gy in 3 fractions and tight constraints for spinal cord (V14Gy 95%). The resulting plans were rated on a scale from 1 to 4 (excellent-poor) in five categories (constraint compliance, optimization goals, low-dose regions, ITP complexity, and clinical acceptability) by a blinded review panel. Additionally, the plans were mathemati-cally rated based on plan indices (critical structure and target doses, conformity, monitor units, normal tissue complication probability, and treatment time) and compared to the human rankings. The treatment plans and the reviewers' rankings varied substantially among the participating centers. The average mean overall rank was 2.4 (1.2-4.0) and 8/10 plans were rated excellent in at least one category by at least one reviewer. The mathematical rankings agreed with the mean overall human rankings in 9/10 cases pointing toward the possibility for sole mathematical plan quality comparison. The final rankings revealed that a plan with a well-balanced trade-off among all planning objectives was preferred for treatment by most par-ticipants, reviewers, and the mathematical ranking system. Furthermore, this plan was generated with simple planning techniques. Our multi-institutional planning study found wide variability in ITP approaches for spinal robotic radiosurgery. The participants', reviewers', and mathematical match on preferable treatment plans and ITP

  3. Inverse treatment planning for spinal robotic radiosurgery: an international multi-institutional benchmark trial.

    Science.gov (United States)

    Blanck, Oliver; Wang, Lei; Baus, Wolfgang; Grimm, Jimm; Lacornerie, Thomas; Nilsson, Joakim; Luchkovskyi, Sergii; Cano, Isabel Palazon; Shou, Zhenyu; Ayadi, Myriam; Treuer, Harald; Viard, Romain; Siebert, Frank-Andre; Chan, Mark K H; Hildebrandt, Guido; Dunst, Jürgen; Imhoff, Detlef; Wurster, Stefan; Wolff, Robert; Romanelli, Pantaleo; Lartigau, Eric; Semrau, Robert; Soltys, Scott G; Schweikard, Achim

    2016-05-01

    Stereotactic radiosurgery (SRS) is the accurate, conformal delivery of high-dose radiation to well-defined targets while minimizing normal structure doses via steep dose gradients. While inverse treatment planning (ITP) with computerized optimization algorithms are routine, many aspects of the planning process remain user-dependent. We performed an international, multi-institutional benchmark trial to study planning variability and to analyze preferable ITP practice for spinal robotic radiosurgery. 10 SRS treatment plans were generated for a complex-shaped spinal metastasis with 21 Gy in 3 fractions and tight constraints for spinal cord (V14Gy95%). The resulting plans were rated on a scale from 1 to 4 (excellent-poor) in five categories (constraint compliance, optimization goals, low-dose regions, ITP complexity, and clinical acceptability) by a blinded review panel. Additionally, the plans were mathematically rated based on plan indices (critical structure and target doses, conformity, monitor units, normal tissue complication probability, and treatment time) and compared to the human rankings. The treatment plans and the reviewers' rankings varied substantially among the participating centers. The average mean overall rank was 2.4 (1.2-4.0) and 8/10 plans were rated excellent in at least one category by at least one reviewer. The mathematical rankings agreed with the mean overall human rankings in 9/10 cases pointing toward the possibility for sole mathematical plan quality comparison. The final rankings revealed that a plan with a well-balanced trade-off among all planning objectives was preferred for treatment by most participants, reviewers, and the mathematical ranking system. Furthermore, this plan was generated with simple planning techniques. Our multi-institutional planning study found wide variability in ITP approaches for spinal robotic radiosurgery. The participants', reviewers', and mathematical match on preferable treatment plans and ITP techniques

  4. Sci—Thur PM: Planning and Delivery — 06: Real-Time Interactive Treatment Planning

    Energy Technology Data Exchange (ETDEWEB)

    Matthews, Q; Mestrovic, A [BC Cancer Agency - Vancouver Island Centre (Canada); Otto, K [Physics and Astronomy, University of British Columbia (Canada)

    2014-08-15

    Purpose: To describe and evaluate a novel system for generalized Real-Time Interactive Planning (RTIP) applied to head and neck (H and N) VMAT. Methods: The clinician interactively manipulates dose distributions using DVHs, isodoses, or rate of dose fall-off, which may be subjected to user-defined constraints. Dose is calculated using a fast Achievable Dose Estimate (ADE) algorithm, which simulates the limits of what can be achieved during treatment. After each manipulation contributing fluence elements are modified and the dose distribution updates in effectively real-time. For H and N VMAT planning, structure sets for 11 patients were imported into RTIP. Each dose distribution was interactively modified to minimize OAR dose while constraining target DVHs. The resulting RTIP DVHs were transferred to the Eclipse™ VMAT optimizer, and conventional VMAT optimization was performed. Results: Dose calculation and update times for the ADE algorithm ranged from 2.4 to 22.6 milliseconds, thus facilitating effectively real-time manipulation of dose distributions. For each of the 11 H and N VMAT cases, the RTIP process took ∼2–10 minutes. All RTIP plans exhibited acceptable PTV coverage, mean dose, and max dose. 10 of 11 RTIP plans achieved substantially improved sparing of one or more OARs without compromising dose to targets or other OARs. Importantly, 10 of the 11 RTIP plans required only one or two post-RTIP optimizations. Conclusions: RTIP is a novel system for manipulating and updating achievable dose distributions in real-time. H and N VMAT plans generated using RTIP demonstrate improved OAR sparing and planning efficiency. Disclosures: One author has a commercial interest in the presented materials.

  5. Radiotherapy treatment planning linear-quadratic radiobiology

    CERN Document Server

    Chapman, J Donald

    2015-01-01

    Understand Quantitative Radiobiology from a Radiation Biophysics PerspectiveIn the field of radiobiology, the linear-quadratic (LQ) equation has become the standard for defining radiation-induced cell killing. Radiotherapy Treatment Planning: Linear-Quadratic Radiobiology describes tumor cell inactivation from a radiation physics perspective and offers appropriate LQ parameters for modeling tumor and normal tissue responses.Explore the Latest Cell Killing Numbers for Defining Iso-Effective Cancer TreatmentsThe book compil

  6. Multiple Space Debris Collecting Mission -- Optimal Mission Planning

    CERN Document Server

    Cerf, Max

    2014-01-01

    This paper addresses the problem of planning successive Space Debris Collecting missions so that they can be achieved at minimal cost by a generic vehicle. The problem mixes combinatorial optimization to select and order the debris among a list of candidates, and continuous optimization to fix the rendezvous dates and to define the minimum fuel orbital maneuvers. The solution method proposed consists in three stages. Firstly the orbital transfer problem is simplified by considering a generic transfer strategy suited either to a high thrust or a low thrust vehicle. A response surface modelling is built by solving the reduced problem for all pairs of debris and for discretized dates, and storing the results in cost matrices. Secondly a simulated annealing algorithm is applied to find the optimal mission planning. The cost function is assessed by interpolation on the response surface based on the cost matrices. This allows the convergence of the simulated algorithm in a limited computation time, yielding an opti...

  7. TRACON Aircraft Arrival Planning and Optimization Through Spatial Constraint Satisfaction

    Science.gov (United States)

    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.

  8. Spatial Coverage Planning and Optimization for Planetary Exploration

    Science.gov (United States)

    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.

  9. MO-B-BRB-02: Maintain the Quality of Treatment Planning for Time-Constraint Cases

    Energy Technology Data Exchange (ETDEWEB)

    Chang, J. [New York Weill Cornell Medical Ctr (United States)

    2015-06-15

    The radiotherapy treatment planning process has evolved over the years with innovations in treatment planning, treatment delivery and imaging systems. Treatment modality and simulation technologies are also rapidly improving and affecting the planning process. For example, Image-guided-radiation-therapy has been widely adopted for patient setup, leading to margin reduction and isocenter repositioning after simulation. Stereotactic Body radiation therapy (SBRT) and Radiosurgery (SRS) have gradually become the standard of care for many treatment sites, which demand a higher throughput for the treatment plans even if the number of treatments per day remains the same. Finally, simulation, planning and treatment are traditionally sequential events. However, with emerging adaptive radiotherapy, they are becoming more tightly intertwined, leading to iterative processes. Enhanced efficiency of planning is therefore becoming more critical and poses serious challenge to the treatment planning process; Lean Six Sigma approaches are being utilized increasingly to balance the competing needs for speed and quality. In this symposium we will discuss the treatment planning process and illustrate effective techniques for managing workflow. Topics will include: Planning techniques: (a) beam placement, (b) dose optimization, (c) plan evaluation (d) export to RVS. Planning workflow: (a) import images, (b) Image fusion, (c) contouring, (d) plan approval (e) plan check (f) chart check, (g) sequential and iterative process Influence of upstream and downstream operations: (a) simulation, (b) immobilization, (c) motion management, (d) QA, (e) IGRT, (f) Treatment delivery, (g) SBRT/SRS (h) adaptive planning Reduction of delay between planning steps with Lean systems due to (a) communication, (b) limited resource, (b) contour, (c) plan approval, (d) treatment. Optimizing planning processes: (a) contour validation (b) consistent planning protocol, (c) protocol/template sharing, (d) semi

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

    Energy Technology Data Exchange (ETDEWEB)

    Breedveld, Sebastiaan; Storchi, Pascal R. M.; Voet, Peter W. J.; Heijmen, Ben J. M. [Department of Radiation Oncology, Erasmus MC Rotterdam, Groene Hilledijk 301, 3075 EA Rotterdam (Netherlands)

    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 between 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

  11. Mixed integer programming improves comprehensibility and plan quality in inverse optimization of prostate HDR-brachytherapy

    CERN Document Server

    Gorissen, Bram L; Hoffmann, Aswin L

    2014-01-01

    Current inverse treatment planning methods that optimize both catheter positions and dwell times in prostate HDR brachytherapy use surrogate linear or quadratic objective functions that have no direct interpretation in terms of dose-volume histogram (DVH) criteria, do not result in an optimum or have long solution times. We decrease the solution time of existing linear and quadratic dose-based programming models (LP and QP, respectively) to allow optimizing over potential catheter positions using mixed integer programming. An additional average speed-up of 75% can be obtained by stopping the solver at an early stage, without deterioration of the plan quality. For a fixed catheter configuration, the dwell time optimization model LP solves to optimality in less than 15 seconds, which confirms earlier results. We propose an iterative procedure for QP that allows to prescribe the target dose as an interval, while retaining independence between the solution time and the number of dose calculation points. This iter...

  12. Planning Framework for Mesolevel Optimization of Urban Runoff Control Schemes

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, Qianqian; Blohm, Andrew J.; Liu, Bo

    2017-04-01

    A planning framework is developed to optimize runoff control schemes at scales relevant for regional planning at an early stage. The framework employs less sophisticated modeling approaches to allow a practical application in developing regions with limited data sources and computing capability. The methodology contains three interrelated modules: (1)the geographic information system (GIS)-based hydrological module, which aims at assessing local hydrological constraints and potential for runoff control according to regional land-use descriptions; (2)the grading module, which is built upon the method of fuzzy comprehensive evaluation. It is used to establish a priority ranking system to assist the allocation of runoff control targets at the subdivision level; and (3)the genetic algorithm-based optimization module, which is included to derive Pareto-based optimal solutions for mesolevel allocation with multiple competing objectives. The optimization approach describes the trade-off between different allocation plans and simultaneously ensures that all allocation schemes satisfy the minimum requirement on runoff control. Our results highlight the importance of considering the mesolevel allocation strategy in addition to measures at macrolevels and microlevels in urban runoff management. (C) 2016 American Society of Civil Engineers.

  13. Cost-Effective Fuel Treatment Planning

    Science.gov (United States)

    Kreitler, J.; Thompson, M.; Vaillant, N.

    2014-12-01

    The cost of fighting large wildland fires in the western United States has grown dramatically over the past decade. This trend will likely continue with growth of the WUI into fire prone ecosystems, dangerous fuel conditions from decades of fire suppression, and a potentially increasing effect from prolonged drought and climate change. Fuel treatments are often considered the primary pre-fire mechanism to reduce the exposure of values at risk to wildland fire, and a growing suite of fire models and tools are employed to prioritize where treatments could mitigate wildland fire damages. Assessments using the likelihood and consequence of fire are critical because funds are insufficient to reduce risk on all lands needing treatment, therefore prioritization is required to maximize the effectiveness of fuel treatment budgets. Cost-effectiveness, doing the most good per dollar, would seem to be an important fuel treatment metric, yet studies or plans that prioritize fuel treatments using costs or cost-effectiveness measures are absent from the literature. Therefore, to explore the effect of using costs in fuel treatment planning we test four prioritization algorithms designed to reduce risk in a case study examining fuel treatments on the Sisters Ranger District of central Oregon. For benefits we model sediment retention and standing biomass, and measure the effectiveness of each algorithm by comparing the differences among treatment and no treat alternative scenarios. Our objective is to maximize the averted loss of net benefits subject to a representative fuel treatment budget. We model costs across the study landscape using the My Fuel Treatment Planner software, tree list data, local mill prices, and GIS-measured site characteristics. We use fire simulations to generate burn probabilities, and estimate fire intensity as conditional flame length at each pixel. Two prioritization algorithms target treatments based on cost-effectiveness and show improvements over those

  14. Optimality of Profit-Including Prices Under Ideal Planning

    Science.gov (United States)

    Samuelson, Paul A.

    1973-01-01

    Although prices calculated by a constant percentage markup on all costs (nonlabor as well as direct-labor) are usually admitted to be more realistic for a competitive capitalistic model, the view is often expressed that, for optimal planning purposes, the “values” model of Marx's Capital, Volume I, is to be preferred. It is shown here that an optimal-control model that maximizes discounted social utility of consumption per capita and that ultimately approaches a steady state must ultimately have optimal pricing that involves equal rates of steady-state profit in all industries; and such optimal pricing will necessarily deviate from Marx's model of equal rates of surplus value (markups on direct-labor only) in all industries. PMID:16592102

  15. SU-E-T-627: Optimal Partial Arcs in VMAT Planning.

    Science.gov (United States)

    Wala, J; Chen, W; Salari, E; Craft, D

    2012-06-01

    To describe a method for producing minimal delivery time partial arc VMAT plans. We begin with the assumption that dose quality is the primary treatment planning goal. Therefore the first step in the partial arc computation is a 180 beam equi-spaced IMRT multi-criteria optimized treatment plan, which serves as an ideal plan, along with a set of user- specified allowable deviations from this plan. This defines a set of target coverage and healthy organ sparing constraints. We then seek a partial arc plan which recovers this ideal plan but is minimal in delivery time. The search for the optimal partial arc which fulfills the hard constraints is done by wrapping a VMAT fluence map optimization/merging/simplification algorithm called VMERGE. The search is performed over all possible partial arcs, with start and end locations discretized to 20 degree increments, and respecting that the gantry cannot pass underneath the couch. This results in 169 partial arcs. For the ones that yield feasible plans, the complete VMERGE algorithm is run, which minimizes the delivery time for that arc. The minimal delivery time plan that fulfills the dosimetric requirements is returned. We apply the method to a lung and liver case. The time savings are as follows: (full arc time, optimal partial arc time): lung (185 s, 94 s), liver (263 s, 165 s). The optimal arc for the lung lesion, a left anterior target, is 140 degrees centered at 50 degrees. The optimal arc for the liver lesion is 160 degrees centered at -90 degrees. By wrapping a fast VMAT optimization/sequencing routine by an exhaustive search over 169 possible partial arcs, we are able to determine the fastest delivery partial arc. The use of partial arcs can significantly shorten delivery time in VMAT delivery. The project described was supported by Award Number R01CA103904 from the National Cancer Institute. The content is solely the responsibility of the authors and does not necessarily represent the ocial views of the National

  16. Economic and environmental optimization of waste treatment

    Energy Technology Data Exchange (ETDEWEB)

    Münster, M. [System Analysis Department, DTU Management Engineering, Technical University of Denmark, Frederiksborgvej 399, 4000 Roskilde (Denmark); Ravn, H. [RAM-løse edb, Æblevangen 55, 2765 Smørum (Denmark); Hedegaard, K.; Juul, N. [System Analysis Department, DTU Management Engineering, Technical University of Denmark, Frederiksborgvej 399, 4000 Roskilde (Denmark); Ljunggren Söderman, M. [IVL Swedish Environmental Research Institute, Box 53021, SE-40014 Gothenburg (Sweden); Chalmers University of Technology, SE-412 96 Gothenburg (Sweden)

    2015-04-15

    Highlights: • Optimizing waste treatment by incorporating LCA methodology. • Applying different objectives (minimizing costs or GHG emissions). • Prioritizing multiple objectives given different weights. • Optimum depends on objective and assumed displaced electricity production. - Abstract: This article presents the new systems engineering optimization model, OptiWaste, which incorporates a life cycle assessment (LCA) methodology and captures important characteristics of waste management systems. As part of the optimization, the model identifies the most attractive waste management options. The model renders it possible to apply different optimization objectives such as minimizing costs or greenhouse gas emissions or to prioritize several objectives given different weights. A simple illustrative case is analysed, covering alternative treatments of one tonne of residual household waste: incineration of the full amount or sorting out organic waste for biogas production for either combined heat and power generation or as fuel in vehicles. The case study illustrates that the optimal solution depends on the objective and assumptions regarding the background system – illustrated with different assumptions regarding displaced electricity production. The article shows that it is feasible to combine LCA methodology with optimization. Furthermore, it highlights the need for including the integrated waste and energy system into the model.

  17. Triangular Geometrized Sampling Heuristics for Fast Optimal Motion Planning

    Directory of Open Access Journals (Sweden)

    Ahmed Hussain Qureshi

    2015-02-01

    Full Text Available Rapidly-exploring Random Tree (RRT-based algorithms have become increasingly popular due to their lower computational complexity as compared with other path planning algorithms. The recently presented RRT* motion planning algorithm improves upon the original RRT algorithm by providing optimal path solutions. While RRT determines an initial collision-free path fairly quickly, RRT* guarantees almost certain convergence to an optimal, obstacle-free path from the start to the goal points for any given geometrical environment. However, the main limitations of RRT* include its slow processing rate and high memory consumption, due to the large number of iterations required for calculating the optimal path. In order to overcome these limitations, we present another improvement, i.e, the Triangular Geometerized-RRT* (TGRRT* algorithm, which utilizes triangular geometrical methods to improve the performance of the RRT* algorithm in terms of the processing time and a decreased number of iterations required for an optimal path solution. Simulations comparing the performance results of the improved TG-RRT* with RRT* are presented to demonstrate the overall improvement in performance and optimal path detection.

  18. Triangular Geometrized Sampling Heuristics for Fast Optimal Motion Planning

    Directory of Open Access Journals (Sweden)

    Ahmed Hussain Qureshi

    2015-02-01

    Full Text Available Rapidly-exploring Random Tree (RRT-based algorithms have become increasingly popular due to their lower computational complexity as compared with other path planning algorithms. The recently presented RRT* motion planning algorithm improves upon the original RRT algorithm by providing optimal path solutions. While RRT determines an initial collision-free path fairly quickly, RRT* guarantees almost certain convergence to an optimal, obstacle-free path from the start to the goal points for any given geometrical environment. However, the main limitations of RRT* include its slow processing rate and high memory consumption, due to the large number of iterations required for calculating the optimal path. In order to overcome these limitations, we present another improvement, i.e, the Triangular Geometerized-RRT* (TG-RRT* algorithm, which utilizes triangular geometrical methods to improve the performance of the RRT* algorithm in terms of the processing time and a decreased number of iterations required for an optimal path solution. Simulations comparing the performance results of the improved TG-RRT* with RRT* are presented to demonstrate the overall improvement in performance and optimal path detection.

  19. Optimal Path Planning for Mobile Robot Using Tailored Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Dong Xiao Xian

    2013-07-01

    Full Text Available During routine inspecting, mobile robot may be requested to visit multiple locations to execute special tasks occasionally. This study aims at optimal path planning for multiple goals visiting task based on tailored genetic algorithm. The proposed algorithm will generate an optimal path that has the least idle time, which is proven to be more effective on evaluating a path in our previous work. In proposed algorithm, customized chromosome representing a path and genetic operators including repair and cut are developed and implemented. Afterwards, simulations are carried out to verify the effectiveness and applicability. Finally, analysis of simulation results is conducted and future work is addressed.

  20. Optimal savings management for individuals with defined contribution pension plans

    DEFF Research Database (Denmark)

    Konicz, Agnieszka Karolina; Mulvey, John M.

    2015-01-01

    The paper provides some guidelines to individuals with defined contribution (DC) pension plans on how to manage pension savings both before and after retirement. We argue that decisions regarding investment, annuity payments, and the size of death sum should not only depend on the individual’s age...... characterizing the individual. The problem is solved via a model that combines two optimization approaches: stochastic optimal control and multi-stage stochastic programming. The first method is common in financial and actuarial literature, but produces theoretical results. However, the latter, which...

  1. A novel implementation of mARC treatment for non-dedicated planning systems using converted IMRT plans.

    Science.gov (United States)

    Dzierma, Yvonne; Nuesken, Frank; Licht, Norbert; Ruebe, Christian

    2013-08-03

    The modulated arc (mARC) technique has recently been introduced by Siemens as an analogue to VMAT treatment. However, up to now only one certified treatment planning system supports mARC planning. We therefore present a conversion algorithm capable of converting IMRT plans created by any treatment planning system into mARC plans, with the hope of expanding the availability of mARC to a larger range of clinical users and researchers. As additional advantages, our implementation offers improved functionality for planning hybrid arcs and provides an equivalent step-and-shoot plan for each mARC plan, which can be used as a back-up concept in institutions where only one linac is equipped with mARC. We present a feasibility study to outline a practical implementation of mARC plan conversion using Philips Pinnacle and Prowess Panther. We present examples for three different kinds of prostate and head-and-neck plans, for 6 MV and flattening-filter-free (FFF) 7 MV photon energies, which are dosimetrically verified. It is generally more difficult to create good quality IMRT plans in Pinnacle using a large number of beams and few segments. We present different ways of optimization as examples. By careful choosing the beam and segment arrangement and inversion objectives, we achieve plan qualities similar to our usual IMRT plans. The conversion of the plans to mARC format yields functional plans, which can be irradiated without incidences. Absolute dosimetric verification of both the step-and-shoot and mARC plans by point dose measurements showed deviations below 5% local dose, mARC plans deviated from step-and-shoot plans by no more than 1%. The agreement between GafChromic film measurements of planar dose before and after mARC conversion is excellent. The comparison of the 3D dose distribution measured by PTW Octavius 729 2D-Array with the step-and-shoot plans and with the TPS is well above the pass criteria of 90% of the points falling within 5% local dose and 3

  2. Automatic liver contouring for radiotherapy treatment planning

    Science.gov (United States)

    Li, Dengwang; Liu, Li; Kapp, Daniel S.; Xing, Lei

    2015-09-01

    To develop automatic and efficient liver contouring software for planning 3D-CT and four-dimensional computed tomography (4D-CT) for application in clinical radiation therapy treatment planning systems. The algorithm comprises three steps for overcoming the challenge of similar intensities between the liver region and its surrounding tissues. First, the total variation model with the L1 norm (TV-L1), which has the characteristic of multi-scale decomposition and an edge-preserving property, is used for removing the surrounding muscles and tissues. Second, an improved level set model that contains both global and local energy functions is utilized to extract liver contour information sequentially. In the global energy function, the local correlation coefficient (LCC) is constructed based on the gray level co-occurrence matrix both of the initial liver region and the background region. The LCC can calculate the correlation of a pixel with the foreground and background regions, respectively. The LCC is combined with intensity distribution models to classify pixels during the evolutionary process of the level set based method. The obtained liver contour is used as the candidate liver region for the following step. In the third step, voxel-based texture characterization is employed for refining the liver region and obtaining the final liver contours. The proposed method was validated based on the planning CT images of a group of 25 patients undergoing radiation therapy treatment planning. These included ten lung cancer patients with normal appearing livers and ten patients with hepatocellular carcinoma or liver metastases. The method was also tested on abdominal 4D-CT images of a group of five patients with hepatocellular carcinoma or liver metastases. The false positive volume percentage, the false negative volume percentage, and the dice similarity coefficient between liver contours obtained by a developed algorithm and a current standard delineated by the expert group

  3. Automation and Intensity Modulated Radiation Therapy for Individualized High-Quality Tangent Breast Treatment Plans

    Energy Technology Data Exchange (ETDEWEB)

    Purdie, Thomas G., E-mail: Tom.Purdie@rmp.uhn.on.ca [Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario (Canada); Department of Radiation Oncology, University of Toronto, Toronto, Ontario (Canada); Techna Institute, University Health Network, Toronto, Ontario (Canada); Dinniwell, Robert E.; Fyles, Anthony [Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario (Canada); Department of Radiation Oncology, University of Toronto, Toronto, Ontario (Canada); Sharpe, Michael B. [Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario (Canada); Department of Radiation Oncology, University of Toronto, Toronto, Ontario (Canada); Techna Institute, University Health Network, Toronto, Ontario (Canada)

    2014-11-01

    Purpose: To demonstrate the large-scale clinical implementation and performance of an automated treatment planning methodology for tangential breast intensity modulated radiation therapy (IMRT). Methods and Materials: Automated planning was used to prospectively plan tangential breast IMRT treatment for 1661 patients between June 2009 and November 2012. The automated planning method emulates the manual steps performed by the user during treatment planning, including anatomical segmentation, beam placement, optimization, dose calculation, and plan documentation. The user specifies clinical requirements of the plan to be generated through a user interface embedded in the planning system. The automated method uses heuristic algorithms to define and simplify the technical aspects of the treatment planning process. Results: Automated planning was used in 1661 of 1708 patients receiving tangential breast IMRT during the time interval studied. Therefore, automated planning was applicable in greater than 97% of cases. The time for treatment planning using the automated process is routinely 5 to 6 minutes on standard commercially available planning hardware. We have shown a consistent reduction in plan rejections from plan reviews through the standard quality control process or weekly quality review multidisciplinary breast rounds as we have automated the planning process for tangential breast IMRT. Clinical plan acceptance increased from 97.3% using our previous semiautomated inverse method to 98.9% using the fully automated method. Conclusions: Automation has become the routine standard method for treatment planning of tangential breast IMRT at our institution and is clinically feasible on a large scale. The method has wide clinical applicability and can add tremendous efficiency, standardization, and quality to the current treatment planning process. The use of automated methods can allow centers to more rapidly adopt IMRT and enhance access to the documented

  4. Comparison of IPSA and HIPO inverse planning optimization algorithms for prostate HDR brachytherapy.

    Science.gov (United States)

    Panettieri, Vanessa; Smith, Ryan L; Mason, Natasha J; Millar, Jeremy L

    2014-11-08

    Publications have reported the benefits of using high-dose-rate brachytherapy (HDRB) for the treatment of prostate cancer, since it provides similar biochemical control as other treatments while showing lowest long-term complications to the organs at risk (OAR). With the inclusion of anatomy-based inverse planning opti- mizers, HDRB has the advantage of potentially allowing dose escalation. Among the algorithms used, the Inverse Planning Simulated Annealing (IPSA) optimizer is widely employed since it provides adequate dose coverage, minimizing dose to the OAR, but it is known to generate large dwell times in particular positions of the catheter. As an alternative, the Hybrid Inverse treatment Planning Optimization (HIPO) algorithm was recently implemented in Oncentra Brachytherapy V. 4.3. The aim of this work was to compare, with the aid of radiobiological models, plans obtained with IPSA and HIPO to assess their use in our clinical practice. Thirty patients were calculated with IPSA and HIPO to achieve our department's clinical constraints. To evaluate their performance, dosimetric data were collected: Prostate PTV D90(%), V100(%), V150(%), and V200(%), Urethra D10(%), Rectum D2cc(%), and conformity indices. Additionally tumor control probability (TCP) and normal tissue complication probability (NTCP) were calculated with the BioSuite software. The HIPO optimization was performed firstly with Prostate PTV (HIPOPTV) and then with Urethra as priority 1 (HIPOurethra). Initial optimization constraints were then modified to see the effects on dosimetric parameters, TCPs, and NTCPs. HIPO optimizations could reduce TCPs up to 10%-20% for all PTVs lower than 74 cm3. For the urethra, IPSA and HIPOurethra provided similar NTCPs for the majority of volume sizes, whereas HIPOPTV resulted in large NTCP values. These findings were in agreement with dosimetric values. By increasing the PTV maximum dose constraints for HIPOurethra plans, TCPs were found to be in agreement with

  5. The optimization of operating parameters on microalgae upscaling process planning.

    Science.gov (United States)

    Ma, Yu-An; Huang, Hsin-Fu; Yu, Chung-Chyi

    2016-03-01

    The upscaling process planning developed in this study primarily involved optimizing operating parameters, i.e., dilution ratios, during process designs. Minimal variable cost was used as an indicator for selecting the optimal combination of dilution ratios. The upper and lower mean confidence intervals obtained from the actual cultured cell density data were used as the final cell density stability indicator after the operating parameters or dilution ratios were selected. The process planning method and results were demonstrated through three case studies of batch culture simulation. They are (1) final objective cell densities were adjusted, (2) high and low light intensities were used for intermediate-scale cultures, and (3) the number of culture days was expressed as integers for the intermediate-scale culture.

  6. Using Optimization Models for Scheduling in Enterprise Resource Planning Systems

    Directory of Open Access Journals (Sweden)

    Frank Herrmann

    2016-03-01

    Full Text Available Companies often use specially-designed production systems and change them from time to time. They produce small batches in order to satisfy specific demands with the least tardiness. This imposes high demands on high-performance scheduling algorithms which can be rapidly adapted to changes in the production system. As a solution, this paper proposes a generic approach: solutions were obtained using a widely-used commercially-available tool for solving linear optimization models, which is available in an Enterprise Resource Planning System (in the SAP system for example or can be connected to it. In a real-world application of a flow shop with special restrictions this approach is successfully used on a standard personal computer. Thus, the main implication is that optimal scheduling with a commercially-available tool, incorporated in an Enterprise Resource Planning System, may be the best approach.

  7. Resource-Optimal Planning For An Autonomous Planetary Vehicle

    Directory of Open Access Journals (Sweden)

    Giuseppe Della Penna

    2010-07-01

    Full Text Available Autonomous planetary vehicles, also known as rovers, are small autonomous vehicles equipped with a variety of sensors used to perform exploration and experiments on a planet’s surface. Rovers work in a partially unknown environment, with narrow energy/time/movement constraints and, typically, small computational resources that limit the complexity of on-line planning and scheduling, thus they represent a great challenge in the field of autonomous vehicles. Indeed, formal models for such vehicles usually involve hybrid systems with nonlinear dynamics, which are difficult to handle by most of the current planning algorithms and tools. Therefore, when offline planning of the vehicle activities is required, for example for rovers that operate without a continuous Earth supervision, such planning is often performed on simplified models that are not completely realistic. In this paper we show how the UPMurphi model checking based planning tool can be used to generate resource-optimal plans to control the engine of an autonomous planetary vehicle, working directly on its hybrid model and taking into account several safety constraints, thus achieving very accurate results.

  8. Optimal passive optical network planning under demand uncertainty

    OpenAIRE

    2014-01-01

    As a result of ever-increasing demand for access level bandwidth, long deployment cycles and the popularisation of more economically viable Point-to-Multipoint (P2MP) networks, service providers are moving to extensively future-proof fibre technologies to connect consumers. Of these, the Passive Optical Network (PON) is the most prevalent. Though the optimal planning of these networks have been studied by a number of authors recently, the typical situation where consumer ...

  9. Ant colony optimized planning for unmanned surface marine vehicles

    OpenAIRE

    Benítez, J.M.; Jiménez, Juan F.; Jose M. Girón-Sierra

    2010-01-01

    This paper presents some results achieved from a preliminary study on the use of the Ant Colony Algorithm to plan feasible optimal or suboptimal trajectories for an autonomous ship manoeuvring. The scenario, for this preliminary work, comprises only open sea manoeuvres. The goal involves obtaining the least time consuming ship trajectory between to points, departing from the start point with arbitrary initial speed and attitude values and arriving to the end point with prede...

  10. Path Planning Optimization for Teaching and Playback Welding Robot

    Directory of Open Access Journals (Sweden)

    Yuehai Wang

    2013-02-01

    Full Text Available Path planning for the industrial robot plays an important role in the intelligent control of robot. Tradition strategies, including model-based methods and human taught based methods, find it is difficult to control manipulator intelligently and optically. Thus, it is hard to ensure the better performance and lower energy consumption even if the same welding task was executed repeatedly. A path planning optimization method was proposed to add learning ability to teaching and playback welding robot. The optimization was divided into the welding points sequence improvement and trajectory improvement, which was done both on-line and off-line. Points sequence optimization was modeled as TSP and was continuously improved by genetic algorithm based strategy, while the trajectory between two welding points was on-line improved by an try-and-error strategy where the robot try different trajectory from time to time so as to search a better plan. Simulation results verified that this control strategy reduced the time and energy cost as compared with the man-made fix-order sequence. Our method prevents the robot from the computation-intensive model-based control, and offers a convenient way for self-improvement on the basis of human teaching.

  11. Optimal planning of integrated multi-energy systems

    DEFF Research Database (Denmark)

    van Beuzekom, I.; Gibescu, M.; Pinson, Pierre

    2017-01-01

    In this paper, a mathematical approach for the optimal planning of integrated energy systems is proposed. In order to address the challenges of future, RES-dominated energy systems, the model deliberates between the expansion of traditional energy infrastructures, the integration of these infrast......In this paper, a mathematical approach for the optimal planning of integrated energy systems is proposed. In order to address the challenges of future, RES-dominated energy systems, the model deliberates between the expansion of traditional energy infrastructures, the integration...... of these infrastructures using conversion technologies (e.g. gas-to-electricity-and-heat, power-to-heat, power-to-gas), and the placement of energy storage. The model is demonstrated using a representative case study from the city of Eindhoven. Current energy data from 2015 is combined with city development scenarios...... and sustainability goals for 2030 and 2045. Optimal green- and brownfield designs for a district's future integrated energy system are compared using a one-step, as well as a two-step planning approach. As expected, the greenfield designs are more cost efficient, as their results are not constrained by the existing...

  12. TAX PLANNING: OPTIMIZATION TOOL OF DEBTS TOWARDS THE BUDGET

    Directory of Open Access Journals (Sweden)

    Anatol GRAUR

    2017-06-01

    Full Text Available Tax planning is complex of measures,consisting in the reduction of tax payments under the law. Tax planning at the enterprise starts from the initial structuring of businesses and activities and can be carried out both at entity level (corporate and the individual (individual. Compared to tax evasion, tax planning is performed only under the law by avoiding taxes. Avoiding or reducing taxes is possible by organizing activities in such a way that the law allows reducing the tax base or tax rate. Optimization of tax payments is possible by organizing the work in such a way, so as the legislation avoids or reduces the tax base,tax rates and tax incentives application.

  13. Open source Modeling and optimization tools for Planning

    Energy Technology Data Exchange (ETDEWEB)

    Peles, S. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2017-02-10

    Open source modeling and optimization tools for planning The existing tools and software used for planning and analysis in California are either expensive, difficult to use, or not generally accessible to a large number of participants. These limitations restrict the availability of participants for larger scale energy and grid studies in the state. The proposed initiative would build upon federal and state investments in open source software, and create and improve open source tools for use in the state planning and analysis activities. Computational analysis and simulation frameworks in development at national labs and universities can be brought forward to complement existing tools. An open source platform would provide a path for novel techniques and strategies to be brought into the larger community and reviewed by a broad set of stakeholders.

  14. Treatment planning system for carbon ion radiotherapy

    Energy Technology Data Exchange (ETDEWEB)

    Koyama-Ito, Hiroko [National Inst. of Radiological Sciences, Chiba (Japan)

    2002-06-01

    This paper describes the treatment planning (TP) and its peripheral system for carbon ion therapy that has been developed and in clinical use in recent two years at our institution. A new treatment planning system which is FOCUS customized to our irradiation system will be launched in clinical use soon. A new DICOM based PACS has been developed and in use. Now MRI, PET images are ready to be utilized for patient definition with image fusion functionality of radiotherapy TP. We implemented the exchange functionality of TP data specified by RTOG 3D QA Center in FOCUS, Pinnacle3 and heavy ion TP. Target volume and normal structure contours and dose distributions are exchangeable. A database system of carbon ion therapy dedicated to analysis of therapy data has been designed and implemented. All accessible planning data and treatment records of more than 1000 patients treated for seven and half years have been archived. The system has a DICOM RT sever and a database for miscellaneous text data. Limited numbers of private attributes were introduced for ion therapy specific objects. On-line as well as manual registration along with edit functionalities is prepared. Standard web browser is used to search and retrieve information. A DICOM RT viewer has been developed to view and retrieve RT images, dose distributions and structure set. These system described above are all designed to conform to the up-to-date standards of radiation therapy so as to be bases of the future development of the therapy at our institution. (author)

  15. Optimal needle arrangement for intraoperative planning in permanent I-125 prostate implants

    Energy Technology Data Exchange (ETDEWEB)

    Thompson, S.A. [Department of Medical Physics, North Shore-Long Island Jewish Health System, Manhassett, NY (United States); Fung, A.Y.C.; Zaider, M. [Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, NY (United States)

    2002-08-21

    One limitation of intraoperative planning of permanent prostate implants is that needles must already be in the gland before planning images are acquired. Improperly placed needles often restrict the capability of generating optimal seed placement. We developed guiding principles for the proper layout of needles within the treatment volume. The Memorial Sloan-Kettering Cancer Center planning system employs a genetic algorithm to find the optimal seed implantation pattern consistent with pre-assigned constraints (needle geometry, uniformity, conformity and the avoidance of high doses to urethra and rectum). Ultrasound volumes for twelve patients with I-125 implants were used to generate six plans per patient (total 72 plans) with different needle arrangements. The plans were evaluated in terms of V100 (percentage prostate volume receiving at least the prescription dose), U135 (percentage urethra volume receiving at least 135% of prescription dose), and CI (conformity index, the ratio of treatment volume to prescription dose volume.) The method termed POSTCTR, in which needles were placed on the periphery of the largest ultrasound slice and posterior central needles were placed as needed, consistently gave superior results for all prostate sizes. Another arrangement, labelled POSTLAT, where the needles were placed peripherally with additional needles in the posterior lateral lobes, also gave satisfactory results. We advocate two needle arrangements, POSTCTR and POSTLAT, with the former giving better results. (author)

  16. NOTE: Optimal needle arrangement for intraoperative planning in permanent I-125 prostate implants

    Science.gov (United States)

    Thompson, S. A.; Fung, A. Y. C.; Zaider, M.

    2002-08-01

    One limitation of intraoperative planning of permanent prostate implants is that needles must already be in the gland before planning images are acquired. Improperly placed needles often restrict the capability of generating optimal seed placement. We developed guiding principles for the proper layout of needles within the treatment volume. The Memorial Sloan-Kettering Cancer Center planning system employs a genetic algorithm to find the optimal seed implantation pattern consistent with pre-assigned constraints (needle geometry, uniformity, conformity and the avoidance of high doses to urethra and rectum). Ultrasound volumes for twelve patients with I-125 implants were used to generate six plans per patient (total 72 plans) with different needle arrangements. The plans were evaluated in terms of V100 (percentage prostate volume receiving at least the prescription dose), U135 (percentage urethra volume receiving at least 135% of prescription dose), and CI (conformity index, the ratio of treatment volume to prescription dose volume.) The method termed POSTCTR, in which needles were placed on the periphery of the largest ultrasound slice and posterior central needles were placed as needed, consistently gave superior results for all prostate sizes. Another arrangement, labelled POSTLAT, where the needles were placed peripherally with additional needles in the posterior lateral lobes, also gave satisfactory results. We advocate two needle arrangements, POSTCTR and POSTLAT, with the former giving better results.

  17. A stochastic optimization approach for integrated urban water resource planning.

    Science.gov (United States)

    Huang, Y; Chen, J; Zeng, S; Sun, F; Dong, X

    2013-01-01

    Urban water is facing the challenges of both scarcity and water quality deterioration. Consideration of nonconventional water resources has increasingly become essential over the last decade in urban water resource planning. In addition, rapid urbanization and economic development has led to an increasing uncertain water demand and fragile water infrastructures. Planning of urban water resources is thus in need of not only an integrated consideration of both conventional and nonconventional urban water resources including reclaimed wastewater and harvested rainwater, but also the ability to design under gross future uncertainties for better reliability. This paper developed an integrated nonlinear stochastic optimization model for urban water resource evaluation and planning in order to optimize urban water flows. It accounted for not only water quantity but also water quality from different sources and for different uses with different costs. The model successfully applied to a case study in Beijing, which is facing a significant water shortage. The results reveal how various urban water resources could be cost-effectively allocated by different planning alternatives and how their reliabilities would change.

  18. Study of Multi-objective Fuzzy Optimization for Path Planning

    Institute of Scientific and Technical Information of China (English)

    WANG Yanyang; WEI Tietao; QU Xiangju

    2012-01-01

    During path planning,it is necessary to satisfy the requirements of multiple objectives.Multi-objective synthesis is based on the need of flight mission and subjectivity inclination of decision-maker.The decision-maker,however,has illegibility for understanding the requirements of multiple objectives and the subjectivity inclination.It is important to develop a reasonable cost performance index for describing the illegibility of the decision-maker in multi-objective path planning.Based on Voronoi diagram method for the path planning,this paper studies the synthesis method of the multi-objective cost performance index.According to the application of the cost performance index to the path planning based on Voronoi diagram method,this paper analyzes the cost performance index which has been referred to at present.The analysis shows the insufficiency of the cost performance index at present,i.e.,it is difficult to synthesize sub-objective functions because of the great disparity of the sub-objective functions.Thus,a new approach is developed to optimize the cost performance index with the multi-objective fuzzy optimization strategy,and an improved performance index is established,which could coordinate the weight conflict of the sub-objective functions.Finally,the experimental result shows the effectiveness of the proposed approach.

  19. Bi-objective optimization for multi-modal transportation routing planning problem based on Pareto optimality

    Directory of Open Access Journals (Sweden)

    Yan Sun

    2015-09-01

    Full Text Available Purpose: The purpose of study is to solve the multi-modal transportation routing planning problem that aims to select an optimal route to move a consignment of goods from its origin to its destination through the multi-modal transportation network. And the optimization is from two viewpoints including cost and time. Design/methodology/approach: In this study, a bi-objective mixed integer linear programming model is proposed to optimize the multi-modal transportation routing planning problem. Minimizing the total transportation cost and the total transportation time are set as the optimization objectives of the model. In order to balance the benefit between the two objectives, Pareto optimality is utilized to solve the model by gaining its Pareto frontier. The Pareto frontier of the model can provide the multi-modal transportation operator (MTO and customers with better decision support and it is gained by the normalized normal constraint method. Then, an experimental case study is designed to verify the feasibility of the model and Pareto optimality by using the mathematical programming software Lingo. Finally, the sensitivity analysis of the demand and supply in the multi-modal transportation organization is performed based on the designed case. Findings: The calculation results indicate that the proposed model and Pareto optimality have good performance in dealing with the bi-objective optimization. The sensitivity analysis also shows the influence of the variation of the demand and supply on the multi-modal transportation organization clearly. Therefore, this method can be further promoted to the practice. Originality/value: A bi-objective mixed integer linear programming model is proposed to optimize the multi-modal transportation routing planning problem. The Pareto frontier based sensitivity analysis of the demand and supply in the multi-modal transportation organization is performed based on the designed case.

  20. Real-time inverse high-dose-rate brachytherapy planning with catheter optimization by compressed sensing-inspired optimization strategies.

    Science.gov (United States)

    Guthier, C V; Aschenbrenner, K P; Müller, R; Polster, L; Cormack, R A; Hesser, J W

    2016-08-21

    This paper demonstrates that optimization strategies derived from the field of compressed sensing (CS) improve computational performance in inverse treatment planning (ITP) for high-dose-rate (HDR) brachytherapy. Following an approach applied to low-dose-rate brachytherapy, we developed a reformulation of the ITP problem with the same mathematical structure as standard CS problems. Two greedy methods, derived from hard thresholding and subspace pursuit are presented and their performance is compared to state-of-the-art ITP solvers. Applied to clinical prostate brachytherapy plans speed-up by a factor of 56-350 compared to state-of-the-art methods. Based on a Wilcoxon signed rank-test the novel method statistically significantly decreases the final objective function value (p  plans are either clinically equivalent or show a better performance with respect to dosimetric measures.

  1. Epilepsy Treatment Simplified through Mobile Ketogenic Diet Planning.

    Science.gov (United States)

    Li, Hanzhou; Jauregui, Jeffrey L; Fenton, Cagla; Chee, Claire M; Bergqvist, A G Christina

    2014-07-01

    The Ketogenic Diet (KD) is an effective, alternative treatment for refractory epilepsy. This high fat, low protein and carbohydrate diet mimics the metabolic and hormonal changes that are associated with fasting. To maximize the effectiveness of the KD, each meal is precisely planned, calculated, and weighed to within 0.1 gram for the average three-year duration of treatment. Managing the KD is time-consuming and may deter caretakers and patients from pursuing or continuing this treatment. Thus, we investigated methods of planning KD faster and making the process more portable through mobile applications. Nutritional data was gathered from the United States Department of Agriculture (USDA) Nutrient Database. User selected foods are converted into linear equations with n variables and three constraints: prescribed fat content, prescribed protein content, and prescribed carbohydrate content. Techniques are applied to derive the solutions to the underdetermined system depending on the number of foods chosen. The method was implemented on an iOS device and tested with varieties of foods and different number of foods selected. With each case, the application's constructed meal plan was within 95% precision of the KD requirements. In this study, we attempt to reduce the time needed to calculate a meal by automating the computation of the KD via a linear algebra model. We improve upon previous KD calculators by offering optimal suggestions and incorporating the USDA database. We believe this mobile application will help make the KD and other dietary treatment preparations less time consuming and more convenient.

  2. Wind farm operation planning using optimal pitch angle pattern (OPAP)

    Energy Technology Data Exchange (ETDEWEB)

    Moskalenko, Natalia S.; Rudion, K. [Magdeburg Univ. (Germany). Chair for Electric Power Networks and Renewable Energy Sources

    2011-07-01

    This paper presents the possibilities of optimal operation planning to maximize the energy production from a wind farm based on optimal pitch angle pattern (OPAP). The current status of this work is to investigate the influence of the pitch angle adaptation of single wind turbines (WTs) on the overall energy yield of the farm. The approach proposed in this paper assumes a selective change of the pitch angle of the chosen WTs from the optimal value, which corresponds to the maximal utilization of kinetic energy from the wind flow, in order to minimize wake effect influence on the overall energy yield of the farm. In this paper the fundamental assumptions of the proposed approach will be specified and the calculation algorithm will be presented. Furthermore, an exemplary test system will be defined and chosen scenarios will be calculated in order to show the potentials of the OPAP method. (orig.)

  3. Optimal pricing and marketing planning for deteriorating items

    Science.gov (United States)

    Moosavi Tabatabaei, Seyed Reza; Sadjadi, Seyed Jafar; Makui, Ahmad

    2017-01-01

    Optimal pricing and marketing planning plays an essential role in production decisions on deteriorating items. This paper presents a mathematical model for a three-level supply chain, which includes one producer, one distributor and one retailer. The proposed study considers the production of a deteriorating item where demand is influenced by price, marketing expenditure, quality of product and after-sales service expenditures. The proposed model is formulated as a geometric programming with 5 degrees of difficulty and the problem is solved using the recent advances in optimization techniques. The study is supported by several numerical examples and sensitivity analysis is performed to analyze the effects of the changes in different parameters on the optimal solution. The preliminary results indicate that with the change in parameters influencing on demand, inventory holding, inventory deteriorating and set-up costs change and also significantly affect total revenue. PMID:28306750

  4. A novel adaptive Cuckoo search for optimal query plan generation.

    Science.gov (United States)

    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.

  5. A Novel Adaptive Cuckoo Search for Optimal Query Plan Generation

    Directory of Open Access Journals (Sweden)

    Ramalingam Gomathi

    2014-01-01

    Full Text Available 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.

  6. Optimal pricing and marketing planning for deteriorating items.

    Science.gov (United States)

    Moosavi Tabatabaei, Seyed Reza; Sadjadi, Seyed Jafar; Makui, Ahmad

    2017-01-01

    Optimal pricing and marketing planning plays an essential role in production decisions on deteriorating items. This paper presents a mathematical model for a three-level supply chain, which includes one producer, one distributor and one retailer. The proposed study considers the production of a deteriorating item where demand is influenced by price, marketing expenditure, quality of product and after-sales service expenditures. The proposed model is formulated as a geometric programming with 5 degrees of difficulty and the problem is solved using the recent advances in optimization techniques. The study is supported by several numerical examples and sensitivity analysis is performed to analyze the effects of the changes in different parameters on the optimal solution. The preliminary results indicate that with the change in parameters influencing on demand, inventory holding, inventory deteriorating and set-up costs change and also significantly affect total revenue.

  7. Visibility-based optimal path and motion planning

    CERN Document Server

    Wang, Paul Keng-Chieh

    2015-01-01

    This monograph deals with various visibility-based path and motion planning problems motivated by real-world applications such as exploration and mapping planetary surfaces, environmental surveillance using stationary or mobile robots, and imaging of global air/pollutant circulation. The formulation and solution of these problems call for concepts and methods from many areas of applied mathematics including computational geometry, set-covering, non-smooth optimization, combinatorial optimization and optimal control. Emphasis is placed on the formulation of new problems and methods of approach to these problems. Since geometry and visualization play important roles in the understanding of these problems, intuitive interpretations of the basic concepts are presented before detailed mathematical development. The development of a particular topic begins with simple cases illustrated by specific examples, and then progresses forward to more complex cases. The intended readers of this monograph are primarily studen...

  8. A key to success: optimizing the planning process

    Science.gov (United States)

    Turk, Huseyin; Karakaya, Kamil

    2014-05-01

    operation planning process is analyzed according to a comprehensive approach. The difficulties of planning are identified. Consequently, for optimizing a decisionmaking process of an air operation, a planning process is identified in a virtual command and control structure.

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

    Energy Technology Data Exchange (ETDEWEB)

    Bazalova-Carter, Magdalena; Qu, Bradley; Palma, Bianey; Jensen, Christopher; Maxim, Peter G., E-mail: Peter.Maxim@Stanford.edu, E-mail: BWLoo@Stanford.edu; Loo, Billy W., E-mail: Peter.Maxim@Stanford.edu, E-mail: BWLoo@Stanford.edu [Department of Radiation Oncology, Stanford University, Stanford, California 94305 (United States); Hårdemark, Björn; Hynning, Elin [RaySearch Laboratories AB, Stockholm SE-103 65 (Sweden)

    2015-05-15

    Purpose: The aim of this work was to develop a treatment planning workflow for rapid radiotherapy delivered with very high-energy electron (VHEE) scanning pencil beams of 60–120 MeV and to study VHEE plans as a function of VHEE treatment parameters. Additionally, VHEE plans were compared to clinical state-of-the-art volumetric modulated arc therapy (VMAT) photon plans for three cases. Methods: VHEE radiotherapy treatment planning was performed by linking EGSnrc Monte Carlo (MC) dose calculations with inverse treatment planning in a research version of RayStation. In order to study the effect of VHEE treatment parameters on VHEE dose distributions, a MATLAB graphical user interface (GUI) for calculation of VHEE MC pencil beam doses was developed. Through the GUI, pediatric case MC simulations were run for a number of beam energies (60, 80, 100, and 120 MeV), number of beams (13, 17, and 36), pencil beam spot (0.1, 1.0, and 3.0 mm) and grid (2.0, 2.5, and 3.5 mm) sizes, and source-to-axis distance, SAD (40 and 50 cm). VHEE plans for the pediatric case calculated with the different treatment parameters were optimized and compared. Furthermore, 100 MeV VHEE plans for the pediatric case, a lung, and a prostate case were calculated and compared to the clinically delivered VMAT plans. All plans were normalized such that the 100% isodose line covered 95% of the target volume. Results: VHEE beam energy had the largest effect on the quality of dose distributions of the pediatric case. For the same target dose, the mean doses to organs at risk (OARs) decreased by 5%–16% when planned with 100 MeV compared to 60 MeV, but there was no further improvement in the 120 MeV plan. VHEE plans calculated with 36 beams outperformed plans calculated with 13 and 17 beams, but to a more modest degree (<8%). While pencil beam spacing and SAD had a small effect on VHEE dose distributions, 0.1–3 mm pencil beam sizes resulted in identical dose distributions. For the 100 MeV VHEE pediatric

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

    Science.gov (United States)

    Bazalova-Carter, Magdalena; Qu, Bradley; Palma, Bianey; Hårdemark, Björn; Hynning, Elin; Jensen, Christopher; Maxim, Peter G; Loo, Billy W

    2015-05-01

    The aim of this work was to develop a treatment planning workflow for rapid radiotherapy delivered with very high-energy electron (VHEE) scanning pencil beams of 60-120 MeV and to study VHEE plans as a function of VHEE treatment parameters. Additionally, VHEE plans were compared to clinical state-of-the-art volumetric modulated arc therapy (VMAT) photon plans for three cases. VHEE radiotherapy treatment planning was performed by linking EGSnrc Monte Carlo (MC) dose calculations with inverse treatment planning in a research version of RayStation. In order to study the effect of VHEE treatment parameters on VHEE dose distributions, a matlab graphical user interface (GUI) for calculation of VHEE MC pencil beam doses was developed. Through the GUI, pediatric case MC simulations were run for a number of beam energies (60, 80, 100, and 120 MeV), number of beams (13, 17, and 36), pencil beam spot (0.1, 1.0, and 3.0 mm) and grid (2.0, 2.5, and 3.5 mm) sizes, and source-to-axis distance, SAD (40 and 50 cm). VHEE plans for the pediatric case calculated with the different treatment parameters were optimized and compared. Furthermore, 100 MeV VHEE plans for the pediatric case, a lung, and a prostate case were calculated and compared to the clinically delivered VMAT plans. All plans were normalized such that the 100% isodose line covered 95% of the target volume. VHEE beam energy had the largest effect on the quality of dose distributions of the pediatric case. For the same target dose, the mean doses to organs at risk (OARs) decreased by 5%-16% when planned with 100 MeV compared to 60 MeV, but there was no further improvement in the 120 MeV plan. VHEE plans calculated with 36 beams outperformed plans calculated with 13 and 17 beams, but to a more modest degree (plan, OAR doses were up to 70% lower and the integral dose was 33% lower for VHEE compared to 6 MV VMAT. Additionally, VHEE conformity indices (CI100 = 1.09 and CI50 = 4.07) were better than VMAT conformity indices (CI

  11. Resource-Optimal Planning For An Autonomous Planetary Vehicle

    Directory of Open Access Journals (Sweden)

    Giuseppe Della Penna

    2010-07-01

    Full Text Available Autonomous planetary vehicles, also known as rovers, are small autonomous vehicles equipped with avariety of sensors used to perform exploration and experiments on a planet’s surface. Rovers work in apartially unknown environment, with narrow energy/time/movement constraints and, typically, smallcomputational resources that limit the complexity of on-line planning and scheduling, thus they representa great challenge in the field of autonomous vehicles. Indeed, formal models for such vehicles usuallyinvolve hybrid systems with nonlinear dynamics, which are difficult to handle by most of the currentplanning algorithms and tools. Therefore, when offline planning of the vehicle activities is required, forexample for rovers that operate without a continuous Earth supervision, such planning is often performedon simplified models that are not completely realistic. In this paper we show how the UPMurphi modelchecking based planning tool can be used to generate resource-optimal plans to control the engine of anautonomous planetary vehicle, working directly on its hybrid model and taking into account severalsafety constraints, thus achieving very accurate results.

  12. Current state of the art brachytherapy treatment planning dosimetry algorithms.

    Science.gov (United States)

    Papagiannis, P; Pantelis, E; Karaiskos, P

    2014-09-01

    Following literature contributions delineating the deficiencies introduced by the approximations of conventional brachytherapy dosimetry, different model-based dosimetry algorithms have been incorporated into commercial systems for (192)Ir brachytherapy treatment planning. The calculation settings of these algorithms are pre-configured according to criteria established by their developers for optimizing computation speed vs accuracy. Their clinical use is hence straightforward. A basic understanding of these algorithms and their limitations is essential, however, for commissioning; detecting differences from conventional algorithms; explaining their origin; assessing their impact; and maintaining global uniformity of clinical practice.

  13. Conformal Radiotherapy: Physics, Treatment Planning and Verification. Proceedings book

    Energy Technology Data Exchange (ETDEWEB)

    De Wagter, C. [ed.

    1995-12-01

    The goal of conformal radiotherapy is to establish radiation dose distributions that conform tightly to the target volume in view of limiting radiation to normal tissues. Conformal radiotherapy significantly improves both local control and palliation and thus contributes to increase survival and to improve the quality of life. The subjects covered by the symposium include : (1) conformal radiotherapy and multi-leaf collimation; (2) three dimensional imaging; (3) treatment simulation, planning and optimization; (4) quality assurance; and (5) dosimetry. The book of proceedings contains the abstracts of the invited lectures, papers and poster presentations as well as the full papers of these contributions.

  14. Development of an autonomous treatment planning strategy for radiation therapy with effective use of population-based prior data.

    Science.gov (United States)

    Wang, Huan; Dong, Peng; Liu, Hongcheng; Xing, Lei

    2017-02-01

    Current treatment planning remains a costly and labor intensive procedure and requires multiple trial-and-error adjustments of system parameters such as the weighting factors and prescriptions. The purpose of this work is to develop an autonomous treatment planning strategy with effective use of prior knowledge and in a clinically realistic treatment planning platform to facilitate radiation therapy workflow. Our technique consists of three major components: (i) a clinical treatment planning system (TPS); (ii) a formulation of decision-function constructed using an assemble of prior treatment plans; (iii) a plan evaluator or decision-function and an outer-loop optimization independent of the clinical TPS to assess the TPS-generated plan and to drive the search toward a solution optimizing the decision-function. Microsoft (MS) Visual Studio Coded UI is applied to record some common planner-TPS interactions as subroutines for querying and interacting with the TPS. These subroutines are called back in the outer-loop optimization program to navigate the plan selection process through the solution space iteratively. The utility of the approach is demonstrated by using clinical prostate and head-and-neck cases. An autonomous treatment planning technique with effective use of an assemble of prior treatment plans is developed to automatically maneuver the clinical treatment planning process in the platform of a commercial TPS. The process mimics the decision-making process of a human planner and provides a clinically sensible treatment plan automatically, thus reducing/eliminating the tedious manual trial-and-errors of treatment planning. It is found that the prostate and head-and-neck treatment plans generated using the approach compare favorably with that used for the patients' actual treatments. Clinical inverse treatment planning process can be automated effectively with the guidance of an assemble of prior treatment plans. The approach has the potential to

  15. Robust, Optimal Water Infrastructure Planning Under Deep Uncertainty Using Metamodels

    Science.gov (United States)

    Maier, H. R.; Beh, E. H. Y.; Zheng, F.; Dandy, G. C.; Kapelan, Z.

    2015-12-01

    Optimal long-term planning plays an important role in many water infrastructure problems. However, this task is complicated by deep uncertainty about future conditions, such as the impact of population dynamics and climate change. One way to deal with this uncertainty is by means of robustness, which aims to ensure that water infrastructure performs adequately under a range of plausible future conditions. However, as robustness calculations require computationally expensive system models to be run for a large number of scenarios, it is generally computationally intractable to include robustness as an objective in the development of optimal long-term infrastructure plans. In order to overcome this shortcoming, an approach is developed that uses metamodels instead of computationally expensive simulation models in robustness calculations. The approach is demonstrated for the optimal sequencing of water supply augmentation options for the southern portion of the water supply for Adelaide, South Australia. A 100-year planning horizon is subdivided into ten equal decision stages for the purpose of sequencing various water supply augmentation options, including desalination, stormwater harvesting and household rainwater tanks. The objectives include the minimization of average present value of supply augmentation costs, the minimization of average present value of greenhouse gas emissions and the maximization of supply robustness. The uncertain variables are rainfall, per capita water consumption and population. Decision variables are the implementation stages of the different water supply augmentation options. Artificial neural networks are used as metamodels to enable all objectives to be calculated in a computationally efficient manner at each of the decision stages. The results illustrate the importance of identifying optimal staged solutions to ensure robustness and sustainability of water supply into an uncertain long-term future.

  16. Real-time inverse high-dose-rate brachytherapy planning with catheter optimization by compressed sensing-inspired optimization strategies

    Science.gov (United States)

    Guthier, C. V.; Aschenbrenner, K. P.; Müller, R.; Polster, L.; Cormack, R. A.; Hesser, J. W.

    2016-08-01

    This paper demonstrates that optimization strategies derived from the field of compressed sensing (CS) improve computational performance in inverse treatment planning (ITP) for high-dose-rate (HDR) brachytherapy. Following an approach applied to low-dose-rate brachytherapy, we developed a reformulation of the ITP problem with the same mathematical structure as standard CS problems. Two greedy methods, derived from hard thresholding and subspace pursuit are presented and their performance is compared to state-of-the-art ITP solvers. Applied to clinical prostate brachytherapy plans speed-up by a factor of 56-350 compared to state-of-the-art methods. Based on a Wilcoxon signed rank-test the novel method statistically significantly decreases the final objective function value (p  <  0.01). The optimization times were below one second and thus planing can be considered as real-time capable. The novel CS inspired strategy enables real-time ITP for HDR brachytherapy including catheter optimization. The generated plans are either clinically equivalent or show a better performance with respect to dosimetric measures.

  17. Essential components of written behavior treatment plans.

    Science.gov (United States)

    Williams, Don E; Vollmer, Timothy R

    2014-11-12

    For the last 25 years, the only empirically determined system to evaluate the content of written behavior analysis plans was developed by Vollmer et al. (1992). For the current study, the content of that earlier system was revised by the first author and submitted to 48 members of the editorial board of the Journal of Applied Behavior Analysis and seven (7) other acknowledged experts on the editorial boards of Behavioral Interventions and Research in Developmental Disabilities. Of 55 recipients, 36 responded. The thirty-six (36) respondents rated each of 28 items from essential to non-essential using a five-point Likert scale. After reviewing the expert panel members' evaluations, we reduced the 28 items to 20 essential components of written behavior treatment plans. The implications of the results were discussed.

  18. Generalized Tumor Dose for Treatment Planning Decision Support

    Science.gov (United States)

    Zuniga, Areli A.

    Modern radiation therapy techniques allow for improved target conformity and normal tissue sparing. These highly conformal treatment plans have allowed dose escalation techniques increasing the probability of tumor control. At the same time this conformation has introduced inhomogeneous dose distributions, making delivered dose characterizations more difficult. The concept of equivalent uniform dose (EUD) characterizes a heterogeneous dose distribution within irradiated structures as a single value and has been used in biologically based treatment planning (BBTP); however, there are no substantial validation studies on clinical outcome data supporting EUD's use and therefore has not been widely adopted as decision-making support. These highly conformal treatment plans have also introduced the need for safety margins around the target volume. These margins are designed to minimize geometrical misses, and to compensate for dosimetric and treatment delivery uncertainties. The margin's purpose is to reduce the chance of tumor recurrence. This dissertation introduces a new EUD formulation designed especially for tumor volumes, called generalized Tumor Dose (gTD). It also investigates, as a second objective, margins extensions for potential improvements in local control while maintaining or minimizing toxicity. The suitability of gTD to rank LC was assessed by means of retrospective studies in a head and neck (HN) squamous cell carcinoma (SCC) and non-small cell lung cancer (NSCLC) cohorts. The formulation was optimized based on two datasets (one of each type) and then, model validation was assessed on independent cohorts. The second objective of this dissertation was investigated by ranking the probability of LC of the primary disease adding different margin sizes. In order to do so, an already published EUD formula was used retrospectively in a HN and a NSCLC datasets. Finally, recommendations for the viability to implement this new formulation into a routine treatment

  19. Aircraft path planning for optimal imaging using dynamic cost functions

    Science.gov (United States)

    Christie, Gordon; Chaudhry, Haseeb; Kochersberger, Kevin

    2015-05-01

    Unmanned aircraft development has accelerated with recent technological improvements in sensing and communications, which has resulted in an "applications lag" for how these aircraft can best be utilized. The aircraft are becoming smaller, more maneuverable and have longer endurance to perform sensing and sampling missions, but operating them aggressively to exploit these capabilities has not been a primary focus in unmanned systems development. This paper addresses a means of aerial vehicle path planning to provide a realistic optimal path in acquiring imagery for structure from motion (SfM) reconstructions and performing radiation surveys. This method will allow SfM reconstructions to occur accurately and with minimal flight time so that the reconstructions can be executed efficiently. An assumption is made that we have 3D point cloud data available prior to the flight. A discrete set of scan lines are proposed for the given area that are scored based on visibility of the scene. Our approach finds a time-efficient path and calculates trajectories between scan lines and over obstacles encountered along those scan lines. Aircraft dynamics are incorporated into the path planning algorithm as dynamic cost functions to create optimal imaging paths in minimum time. Simulations of the path planning algorithm are shown for an urban environment. We also present our approach for image-based terrain mapping, which is able to efficiently perform a 3D reconstruction of a large area without the use of GPS data.

  20. Optimal Path Planning for Minimizing Base Disturbance of Space Robot

    Directory of Open Access Journals (Sweden)

    Xiao-Peng Wei

    2016-03-01

    Full Text Available The path planning of free-floating space robot in space on-orbit service has been paid more and more attention. The problem is more complicated because of the interaction between the space robot and base. Therefore, it is necessary to minimize the base position and attitude disturbance to improve the path planning of free-floating space robot, reducing the fuel consumption for the position and attitude maintenance. In this paper, a reasonable path planning method to solve the problem is presented, which is feasible and relatively simple. First, the kinematic model of 6 degrees of freedom free-floating space robot is established. And then the joint angles are parameterized using the 7th order polynomial sine functions. The fitness function is defined according to the position and attitude of minimizing base disturbance and constraints of space robot. Furthermore, an improved chaotic particle swarm optimization (ICPSO is presented. The proposed algorithm is compared with the standard PSO and CPSO algorithm in the literature by the experimental simulation. The simulation results demonstrate that the proposed algorithm is more effective than the two other approaches, such as easy to find the optimal solution, and this method could provide a satisfactory path for the free-floating space robot.

  1. Optimal Path Planning for Minimizing Base Disturbance of Space Robot

    Directory of Open Access Journals (Sweden)

    Xiao-Peng Wei

    2016-03-01

    Full Text Available The path planning of free-floating space robot in space on-orbit service has been paid more and more attention. The problem is more complicated because of the interaction between the space robot and base. Therefore, it is necessary to minimize the base position and attitude disturbance to improve the path planning of free-floating space robot, reducing the fuel consumption for the position and attitude maintenance. In this paper, a reasonable path planning method to solve the problem is presented, which is feasible and relatively simple. First, the kinematic model of 6 degrees of freedom free-floating space robot is established. And then the joint angles are parameterized using the 7th order polynomial sine functions. The fitness function is defined according to the position and attitude of minimizing base disturbance and constraints of space robot. Furthermore, an improved chaotic particle swarm optimization (ICPSO is presented. The proposed algorithm is compared with the standard PSO and CPSO algorithm in the literature by the experimental simulation. The simulation results demonstrate that the proposed algorithm is more effective than the two other approaches, such as easy to find the optimal solution, and this method could provide a satisfactory path for the free-floating space robot.

  2. Optimal Motion Planning for Differentially Flat Underactuated Mechanical Systems

    Institute of Scientific and Technical Information of China (English)

    HE Guangping; GENG Zhiyong

    2009-01-01

    Underactuated mechanical system has less independent inputs than the degrees of freedom(DOF) of the mechanism. The energy efficiency of this class of mechanical systems is an essential problem in practice. On the basis of the sufficient and necessary condition that concludes a single input nonlinear system is differentially flat, it is shown that the flat output of the single input tmderactuated mechanical system can be obtained by finding a smooth output function such that the relative degree of the system equals to the dimension of the state space. If the fiat output of the underactuated system can be solved explicitly, and by constructing a smooth curve with satisfying given boundary conditions in flat output space, an energy efficiency optimization method is proposed for the motion planning of the differentially fiat underactuated mechanical systems. The inertia wheel pendulum is used to verify the proposed optimization method, and some numerical simulations show that the presented optimal motion planning method can efficaciously reduce the energy cost for given control tasks.

  3. Nevada Test Site Treatment Plan. Revision 2

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1996-03-01

    Treatment Plans (STPS) are required for facilities at which the US Department of Energy (DOE) or stores mixed waste, defined by the Federal Facility Compliance Act (FFCAct) as waste containing both a hazardous waste subject to the Resource Conservation and Recovery Act and a radioactive material subject to the Atomic Energy Act. On April 6, 1993, DOE published a Federal Register notice (58 FR 17875) describing its proposed process for developing the STPs in three phases including a Conceptual, a Draft, and a Proposed Site Treatment Plan (PSTP). All of the DOE Nevada Operations Office STP iterations have been developed with the state of Nevada`s input. The options and schedules reflect a ``bottoms-up`` approach and have been evaluated for impacts on other DOE sites, as well as impacts to the overall DOE program. Changes may have occurred in the preferred option and associated schedules between the PSTP, which was submitted to the state of Nevada and US Environmental Protection Agency April 1995, and the Final STP (hereafter referred to as the STP) as treatment evaluations progressed. The STP includes changes that have occurred since the submittal of the PSTP as a result of state-to-state and DOE-to-state discussions.

  4. A single-field integrated boost treatment planning technique for spot scanning proton therapy

    OpenAIRE

    Zhu, Xiaorong Ronald; Poenisch, Falk; LI, Heng; Zhang, Xiaodong; Sahoo, Narayan; Richard Y. Wu; Li, Xiaoqiang; Lee, Andrew K.; Chang, Eric L.; Choi, Seungtaek; Pugh, Thomas; Steven J. Frank; Gillin, Michael T.; Mahajan, Anita; Grosshans, David R.

    2014-01-01

    Purpose Intensity modulated proton therapy (IMPT) plans are normally generated utilizing multiple field optimization (MFO) techniques. Similar to photon based IMRT, MFO allows for the utilization of a simultaneous integrated boost in which multiple target volumes are treated to discrete doses simultaneously, potentially improving plan quality and streamlining quality assurance and treatment delivery. However, MFO may render plans more sensitive to the physical uncertainties inherent to partic...

  5. Photographic-assisted diagnosis and treatment planning.

    Science.gov (United States)

    Goodlin, Ron

    2011-04-01

    The advent of digital photography allows the practitioner to show the patient the photographs immediately, to co-diagnose, and to work with the patient chairside or in a consult room while showing the patient some simple imaging techniques, such as whitening the teeth, making the teeth look longer, and showing the effects of orthodontics or veneers to get better alignment and other factors of smile design and esthetic dentistry. This article describes recommended digital dental photographic equipment, how to produce the standard series of diagnostic dental photographs, photographic assisted diagnosis and treatment planning including a discussion of anthropometrics and cephalometrics, and digital imaging techniques.

  6. How to study optimal timing of PET/CT for monitoring of cancer treatment

    DEFF Research Database (Denmark)

    Vach, Werner; Høilund-Carlsen, Poul Flemming; Fischer, Barbara Malene Bjerregaard

    2011-01-01

    Purpose: The use of PET/CT for monitoring treatment response in cancer patients after chemo- or radiotherapy is a very promising approach to optimize cancer treatment. However, the timing of the PET/CT-based evaluation of reduction in viable tumor tissue is a crucial question. We investigated how...... to plan and analyze studies to optimize this timing. Methods: General considerations about studying the optimal timing are given and four fundamental steps are illustrated using data from a published study. Results: The optimal timing should be examined by optimizing the schedule with respect...... to predicting the overall individual time course we can observe in the case of dense measurements. The optimal timing needs not to and should not be studied by optimizing the association with the prognosis of the patient. Conclusions: The optimal timing should be examined in specific ‘schedule optimizing...

  7. Collaborative mission planning for UAV cluster to optimize relay distance

    Science.gov (United States)

    Tanil, Cagatay; Warty, Chirag; Obiedat, Esam

    Unmanned Aerial Vehicles (UAVs) coordinated path planning and intercommunication for visual exploration of a geographical region has recently become crucial. Multiple UAVs cover larger area than a single UAV and eliminate blind spots. To improve the surveillance, survivability and quality of the communication, we propose two algorithms for the route planning of UAV cluster operated in obstacle rich environment: (i) Multiple Population Genetic Algorithm (MPGA) (ii) Relay Selection Criteria (RSC). The main objective of MPGA is to minimize the total mission time while maintaining an optimal distance for communication between the neighboring nodes. MPGA utilizes evolutionary speciation techniques with a novel Feasible Population Creation Method (FPCM) and enhanced Inter-species Crossover Mechanism (ISCM) to obtain diversified routes in remarkably short time. In obtaining collision-free optimum paths, UAVs are subjected to constraints such as limited communication range, maximum maneuverability and fuel capacity. In addition to the path planning, RSC is developed for selection of UAVs relay nodes that is based on the location of the relay relative to source and destination. It is crucial since the Bit Error Rate (BER) performance of the link significantly depends on the location of the selected relay. In this paper, path planning and relay allocation algorithms are combined to have a seamless high quality monitoring of the region and to provide superior Quality of Service (QoS) for audio-video applications. Also, simulations in different operation zones with a cluster of up to six UAVs are performed to verify the feasibility of the proposed algorithms both in optimality and computation time.

  8. An Optimal Capacity Planning Model for General Cargo Seaport

    Directory of Open Access Journals (Sweden)

    Čedomir Dundović

    2012-10-01

    Full Text Available In this paper the application of the queuing the01y in optimalcapacity planning for general cargo seaport is presented.The seaport as a queuing syslem is defined and tlws, on the basisof the arrival and serviced number of ships in an obsen•edtime unit, the appropriate operating indicators of a port systemare calculated. Using the model of total port costs, the munberof berths and cranes on the berth can be determined wherebythe optimal port system functioning is achieved.

  9. Optimal compensation for temporal uncertainty in movement planning.

    Directory of Open Access Journals (Sweden)

    Todd E Hudson

    2008-07-01

    Full Text Available Motor control requires the generation of a precise temporal sequence of control signals sent to the skeletal musculature. We describe an experiment that, for good performance, requires human subjects to plan movements taking into account uncertainty in their movement duration and the increase in that uncertainty with increasing movement duration. We do this by rewarding movements performed within a specified time window, and penalizing slower movements in some conditions and faster movements in others. Our results indicate that subjects compensated for their natural duration-dependent temporal uncertainty as well as an overall increase in temporal uncertainty that was imposed experimentally. Their compensation for temporal uncertainty, both the natural duration-dependent and imposed overall components, was nearly optimal in the sense of maximizing expected gain in the task. The motor system is able to model its temporal uncertainty and compensate for that uncertainty so as to optimize the consequences of movement.

  10. Autonomous guided vehicles methods and models for optimal path planning

    CERN Document Server

    Fazlollahtabar, Hamed

    2015-01-01

      This book provides readers with extensive information on path planning optimization for both single and multiple Autonomous Guided Vehicles (AGVs), and discusses practical issues involved in advanced industrial applications of AGVs. After discussing previously published research in the field and highlighting the current gaps, it introduces new models developed by the authors with the goal of reducing costs and increasing productivity and effectiveness in the manufacturing industry. The new models address the increasing complexity of manufacturing networks, due for example to the adoption of flexible manufacturing systems that involve automated material handling systems, robots, numerically controlled machine tools, and automated inspection stations, while also considering the uncertainty and stochastic nature of automated equipment such as AGVs. The book discusses and provides solutions to important issues concerning the use of AGVs in the manufacturing industry, including material flow optimization with A...

  11. Hierarchical Artificial Bee Colony Algorithm for RFID Network Planning Optimization

    Directory of Open Access Journals (Sweden)

    Lianbo Ma

    2014-01-01

    Full Text Available This paper presents a novel optimization algorithm, namely, hierarchical artificial bee colony optimization, called HABC, to tackle the radio frequency identification network planning (RNP problem. In the proposed multilevel model, the higher-level species can be aggregated by the subpopulations from lower level. In the bottom level, each subpopulation employing the canonical ABC method searches the part-dimensional optimum in parallel, which can be constructed into a complete solution for the upper level. At the same time, the comprehensive learning method with crossover and mutation operators is applied to enhance the global search ability between species. Experiments are conducted on a set of 10 benchmark optimization problems. The results demonstrate that the proposed HABC obtains remarkable performance on most chosen benchmark functions when compared to several successful swarm intelligence and evolutionary algorithms. Then HABC is used for solving the real-world RNP problem on two instances with different scales. Simulation results show that the proposed algorithm is superior for solving RNP, in terms of optimization accuracy and computation robustness.

  12. The feasibility of using Pareto fronts for comparison of treatment planning systems and delivery techniques

    DEFF Research Database (Denmark)

    Ottosson, Rickard O; Engstrom, Per E; Sjöström, David

    2008-01-01

    of a treatment planning system (TPS), treatment strategy or delivery technique, Pareto fronts for a given case are likely to differ. The aim of this study was to investigate the feasibility of using Pareto fronts as a comparative tool for TPSs, treatment strategies and delivery techniques. In order to sample...... Pareto fronts, multiple treatment plans with varying target conformity and dose sparing of OAR were created for a number of prostate and head & neck IMRT cases. The DVHs of each plan were evaluated with respect to target coverage and dose to relevant OAR. Pareto fronts were successfully created for all...... may be used to evaluate a number of parameters within radiotherapy. Examples are TPS optimization algorithms, the variation between accelerators or delivery techniques and the degradation of a plan during the treatment planning process. The issue of designing a model for unbiased comparison...

  13. Rational design of antibiotic treatment plans: a treatment strategy for managing evolution and reversing resistance.

    Science.gov (United States)

    Mira, Portia M; Crona, Kristina; Greene, Devin; Meza, Juan C; Sturmfels, Bernd; Barlow, Miriam

    2015-01-01

    The development of reliable methods for restoring susceptibility after antibiotic resistance arises has proven elusive. A greater understanding of the relationship between antibiotic administration and the evolution of resistance is key to overcoming this challenge. Here we present a data-driven mathematical approach for developing antibiotic treatment plans that can reverse the evolution of antibiotic resistance determinants. We have generated adaptive landscapes for 16 genotypes of the TEM β-lactamase that vary from the wild type genotype "TEM-1" through all combinations of four amino acid substitutions. We determined the growth rate of each genotype when treated with each of 15 β-lactam antibiotics. By using growth rates as a measure of fitness, we computed the probability of each amino acid substitution in each β-lactam treatment using two different models named the Correlated Probability Model (CPM) and the Equal Probability Model (EPM). We then performed an exhaustive search through the 15 treatments for substitution paths leading from each of the 16 genotypes back to the wild type TEM-1. We identified optimized treatment paths that returned the highest probabilities of selecting for reversions of amino acid substitutions and returning TEM to the wild type state. For the CPM model, the optimized probabilities ranged between 0.6 and 1.0. For the EPM model, the optimized probabilities ranged between 0.38 and 1.0. For cyclical CPM treatment plans in which the starting and ending genotype was the wild type, the probabilities were between 0.62 and 0.7. Overall this study shows that there is promise for reversing the evolution of resistance through antibiotic treatment plans.

  14. Rational design of antibiotic treatment plans: a treatment strategy for managing evolution and reversing resistance.

    Directory of Open Access Journals (Sweden)

    Portia M Mira

    Full Text Available The development of reliable methods for restoring susceptibility after antibiotic resistance arises has proven elusive. A greater understanding of the relationship between antibiotic administration and the evolution of resistance is key to overcoming this challenge. Here we present a data-driven mathematical approach for developing antibiotic treatment plans that can reverse the evolution of antibiotic resistance determinants. We have generated adaptive landscapes for 16 genotypes of the TEM β-lactamase that vary from the wild type genotype "TEM-1" through all combinations of four amino acid substitutions. We determined the growth rate of each genotype when treated with each of 15 β-lactam antibiotics. By using growth rates as a measure of fitness, we computed the probability of each amino acid substitution in each β-lactam treatment using two different models named the Correlated Probability Model (CPM and the Equal Probability Model (EPM. We then performed an exhaustive search through the 15 treatments for substitution paths leading from each of the 16 genotypes back to the wild type TEM-1. We identified optimized treatment paths that returned the highest probabilities of selecting for reversions of amino acid substitutions and returning TEM to the wild type state. For the CPM model, the optimized probabilities ranged between 0.6 and 1.0. For the EPM model, the optimized probabilities ranged between 0.38 and 1.0. For cyclical CPM treatment plans in which the starting and ending genotype was the wild type, the probabilities were between 0.62 and 0.7. Overall this study shows that there is promise for reversing the evolution of resistance through antibiotic treatment plans.

  15. Rational Design of Antibiotic Treatment Plans: A Treatment Strategy for Managing Evolution and Reversing Resistance

    Science.gov (United States)

    Mira, Portia M.; Crona, Kristina; Greene, Devin; Meza, Juan C.; Sturmfels, Bernd; Barlow, Miriam

    2015-01-01

    The development of reliable methods for restoring susceptibility after antibiotic resistance arises has proven elusive. A greater understanding of the relationship between antibiotic administration and the evolution of resistance is key to overcoming this challenge. Here we present a data-driven mathematical approach for developing antibiotic treatment plans that can reverse the evolution of antibiotic resistance determinants. We have generated adaptive landscapes for 16 genotypes of the TEM β-lactamase that vary from the wild type genotype “TEM-1” through all combinations of four amino acid substitutions. We determined the growth rate of each genotype when treated with each of 15 β-lactam antibiotics. By using growth rates as a measure of fitness, we computed the probability of each amino acid substitution in each β-lactam treatment using two different models named the Correlated Probability Model (CPM) and the Equal Probability Model (EPM). We then performed an exhaustive search through the 15 treatments for substitution paths leading from each of the 16 genotypes back to the wild type TEM-1. We identified optimized treatment paths that returned the highest probabilities of selecting for reversions of amino acid substitutions and returning TEM to the wild type state. For the CPM model, the optimized probabilities ranged between 0.6 and 1.0. For the EPM model, the optimized probabilities ranged between 0.38 and 1.0. For cyclical CPM treatment plans in which the starting and ending genotype was the wild type, the probabilities were between 0.62 and 0.7. Overall this study shows that there is promise for reversing the evolution of resistance through antibiotic treatment plans. PMID:25946134

  16. Recovery post treatment: plans, barriers and motivators

    Directory of Open Access Journals (Sweden)

    Duffy Paul

    2013-01-01

    Full Text Available Abstract Background The increasing focus on achieving a sustained recovery from substance use brings with it a need to better understand the factors (recovery capital that contribute to recovery following treatment. This work examined the factors those in recovery perceive to be barriers to (lack of capital or facilitators of (presence of capital sustained recovery post treatment. Methods A purposive sample of 45 participants was recruited from 11 drug treatment services in northern England. Semi-structured qualitative interviews lasting between 30 and 90 minutes were conducted one to three months after participants completed treatment. Interviews examined key themes identified through previous literature but focused on allowing participants to explore their unique recovery journey. Interviews were transcribed and analysed thematically using a combination of deductive and inductive approaches. Results Participants generally reported high levels of confidence in maintaining their recovery with most planning to remain abstinent. There were indications of high levels of recovery capital. Aftercare engagement was high, often through self referral, with non substance use related activity felt to be particularly positive. Supported housing was critical and concerns were raised about the ability to afford to live independently with financial stability and welfare availability a key concern in general. Employment, often in the substance use treatment field, was a desire. However, it was a long term goal, with substantial risks associated with pursuing this too early. Positive social support was almost exclusively from within the recovery community although the re-building of relationships with family (children in particular was a key motivator post treatment. Conclusions Addressing internal factors and underlying issues i.e. ‘human capital’, provided confidence for continued recovery whilst motivators focused on external factors such as family and

  17. Prescribing and evaluating target dose in dose-painting treatment plans.

    Science.gov (United States)

    Håkansson, Katrin; Specht, Lena; Aznar, Marianne C; Rasmussen, Jacob H; Bentzen, Søren M; Vogelius, Ivan R

    2014-09-01

    Assessment of target dose conformity in multi-dose-level treatment plans is challenging due to inevitable over/underdosage at the border zone between dose levels. Here, we evaluate different target dose prescription planning aims and approaches to evaluate the relative merit of such plans. A quality volume histogram (QVH) tool for history-based evaluation is proposed. Twenty head and neck cancer dose-painting plans with five prescription levels were evaluated, as well as clinically delivered simultaneous integrated boost (SIB) plans from 2010 and 2012. The QVH tool was used for target dose comparison between groups of plans, and to identify and improve a suboptimal dose-painting plan. Comparison of 2010 and 2012 treatment plans with the QVH tool demonstrated that 2012 plans have decreased underdosed volume at the expense of increased overdosed volume relative to the 2010 plans. This shift had not been detected previously. One suboptimal dose-painting plan was compared to the 'normal zone' of the QVH tool and could be improved by re-optimization. The QVH tool provides a method to assess target dose conformity in dose-painting and multi-dose-level plans. The tool can be useful for quality assurance of multi-center trials, and for visualizing the development of treatment planning in routine clinical practice.

  18. Treatment planning capability assessment of a beam shaping assembly for accelerator-based BNCT

    Energy Technology Data Exchange (ETDEWEB)

    Herrera, M.S., E-mail: herrera@tandar.cnea.gov.ar [Comision Nacional de Energia Atomica, CNEA, Av. Gral. Paz 1499, San Martin (Argentina)] [Consejo Nacional de Investigaciones Cientificas y Tecnicas, CONICET, Av. Rivadavia 191, Buenos Aires (Argentina)] [Universidad Nacional de San Martin, UNSAM, Av. 25 de Mayo y Francia Buenos Aires (Argentina); Gonzalez, S.J. [Comision Nacional de Energia Atomica, CNEA, Av. Gral. Paz 1499, San Martin (Argentina)] [Consejo Nacional de Investigaciones Cientificas y Tecnicas, CONICET, Av. Rivadavia 191, Buenos Aires (Argentina); Burlon, A.A. [Comision Nacional de Energia Atomica, CNEA, Av. Gral. Paz 1499, San Martin (Argentina)] [Universidad Nacional de San Martin, UNSAM, Av. 25 de Mayo y Francia Buenos Aires (Argentina); Minsky, D.M.; Kreiner, A.J. [Comision Nacional de Energia Atomica, CNEA, Av. Gral. Paz 1499, San Martin (Argentina)] [Consejo Nacional de Investigaciones Cientificas y Tecnicas, CONICET, Av. Rivadavia 191, Buenos Aires (Argentina)] [Universidad Nacional de San Martin, UNSAM, Av. 25 de Mayo y Francia Buenos Aires (Argentina)

    2011-12-15

    Within the frame of an ongoing project to develop a folded Tandem-Electrostatic-Quadrupole accelerator facility for Accelerator-Based Boron Neutron Capture Therapy (AB-BNCT) a theoretical study was performed to assess the treatment planning capability of different configurations of an optimized beam shaping assembly for such a facility. In particular this study aims at evaluating treatment plans for a clinical case of Glioblastoma.

  19. Oral diagnosis and treatment planning: part 6. Preventive and treatment planning for periodontal disease.

    Science.gov (United States)

    Corbet, E; Smales, R

    2012-09-01

    A high level of sustained personal plaque control is fundamental for successful treatment outcomes in patients with active periodontal disease and, hence, oral hygiene instructions are the cornerstone of periodontal treatment planning. Other risk factors for periodontal disease also should be identified and modified where possible. Many restorative dental treatments in particular require the establishment of healthy periodontal tissues for their clinical success. Failure by patients to control dental plaque because of inappropriate designs and materials for restorations and prostheses will result in the long-term failure of the restorations and the loss of supporting tissues. Periodontal treatment planning considerations are also very relevant to endodontic, orthodontic and osseointegrated dental implant conditions and proposed therapies.

  20. Treatment Planning and Image Guidance for Radiofrequency Ablations of Large Tumors

    Science.gov (United States)

    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

  1. Vanpool trip planning based on evolutionary multiple objective optimization

    Science.gov (United States)

    Zhao, Ming; Yang, Disheng; Feng, Shibing; Liu, Hengchang

    2017-08-01

    Carpool and vanpool draw a lot of researchers’ attention, which is the emphasis of this paper. A concrete vanpool operation definition is given, based on the given definition, this paper tackles vanpool operation optimization using user experience decline index(UEDI). This paper is focused on making each user having identical UEDI and the system having minimum sum of all users’ UEDI. Three contributions are made, the first contribution is a vanpool operation scheme diagram, each component of the scheme is explained in detail. The second contribution is getting all customer’s UEDI as a set, standard deviation and sum of all users’ UEDI set are used as objectives in multiple objective optimization to decide trip start address, trip start time and trip destination address. The third contribution is a trip planning algorithm, which tries to minimize the sum of all users’ UEDI. Geographical distribution of the charging stations and utilization rate of the charging stations are considered in the trip planning process.

  2. Optimal planning for the sustainable utilization of municipal solid waste

    Energy Technology Data Exchange (ETDEWEB)

    Santibañez-Aguilar, José Ezequiel [Chemical Engineering Department, Universidad Michoacana de San Nicolás de Hidalgo, Morelia, Michoacán 58060 (Mexico); Ponce-Ortega, José María, E-mail: jmponce@umich.mx [Chemical Engineering Department, Universidad Michoacana de San Nicolás de Hidalgo, Morelia, Michoacán 58060 (Mexico); Betzabe González-Campos, J. [Institute of Chemical and Biological Researches, Universidad Michoacana de San Nicolás de Hidalgo, Morelia, Michoacán 58060 (Mexico); Serna-González, Medardo [Chemical Engineering Department, Universidad Michoacana de San Nicolás de Hidalgo, Morelia, Michoacán 58060 (Mexico); El-Halwagi, Mahmoud M. [Chemical Engineering Department, Texas A and M University, College Station, TX 77843 (United States); Adjunct Faculty at the Chemical and Materials Engineering Department, Faculty of Engineering, King Abdulaziz University, P.O. Box 80204, Jeddah 21589 (Saudi Arabia)

    2013-12-15

    Highlights: • An optimization approach for the sustainable management of municipal solid waste is proposed. • The proposed model optimizes the entire supply chain network of a distributed system. • A case study for the sustainable waste management in the central-west part of Mexico is presented. • Results shows different interesting solutions for the case study presented. - Abstract: The increasing generation of municipal solid waste (MSW) is a major problem particularly for large urban areas with insufficient landfill capacities and inefficient waste management systems. Several options associated to the supply chain for implementing a MSW management system are available, however to determine the optimal solution several technical, economic, environmental and social aspects must be considered. Therefore, this paper proposes a mathematical programming model for the optimal planning of the supply chain associated to the MSW management system to maximize the economic benefit while accounting for technical and environmental issues. The optimization model simultaneously selects the processing technologies and their location, the distribution of wastes from cities as well as the distribution of products to markets. The problem was formulated as a multi-objective mixed-integer linear programing problem to maximize the profit of the supply chain and the amount of recycled wastes, where the results are showed through Pareto curves that tradeoff economic and environmental aspects. The proposed approach is applied to a case study for the west-central part of Mexico to consider the integration of MSW from several cities to yield useful products. The results show that an integrated utilization of MSW can provide economic, environmental and social benefits.

  3. Imaging TMS: antidepressant mechanisms and treatment optimization.

    Science.gov (United States)

    Dubin, Marc

    2017-04-01

    With the antidepressant efficacy of Transcranial Magnetic Stimulation well-established by several meta-analyses, there is growing interest in its mechanism of action. TMS has been shown to engage, and in some cases, normalize functional connectivity and neurotransmitter levels within networks dysfunctional in the depressed state. In this review, I will suggest candidate biomarkers, based on neuroimaging, that may be predictive of response to TMS. I will then review the effects of TMS on networks and neurotransmitter systems involved in depression. Throughout, I will also discuss how our current understanding of response predication and network engagement may be used to personalize treatment and optimize its efficacy.

  4. Influence of optimizing protocol choice on the integral dose value in prostate radiotherapy planning by dynamic techniques - Pilot study.

    Science.gov (United States)

    Zaleska, Anna; Bogaczyk, Krzysztof; Piotrowski, Tomasz

    2017-01-01

    The purpose of this study was to compare the values of integral dose, calculated for treatment plans of dynamic radiotherapy techniques prepared with two different optimization protocols. Delivering radiation by IMRT, VMAT and also HT techniques has an influence on the low dose deposition of large areas of the patient body. Delivery of low dose can induce injury of healthy cells. In this situation, a good solution would be to reduce the area, which receives a low dose, but with appropriate dose level for the target volume. To calculate integral dose values of plans structures, we used 90 external beam radiotherapy plans prepared for three techniques (intensity modulated radiotherapy, volumetric modulated arc therapy and helical tomotherapy). One technique includes three different geometry combinations. 45 plans were prepared with classic optimization protocol and 45 with rings optimization protocol which should reduce the low doses in the normal tissue. Differences in values of the integral dose depend on the geometry and technique of irradiation, as well as optimization protocol used in preparing treatment plans. The application of the rings optimization caused the value of normal tissue integral dose (NTID) to decrease. It is possible to limit the area of low dose irradiation and reduce NTID in dynamic techniques with the same clinical constraints for OAR and PTV volumes by using an optimization protocol other than the classic one.

  5. Comparisons of treatment optimization directly incorporating random patient setup uncertainty with a margin-based approach.

    Science.gov (United States)

    Moore, Joseph A; Gordon, John J; Anscher, Mitchell S; Siebers, Jeffrey V

    2009-09-01

    The purpose of this study is to incorporate the dosimetric effect of random patient positioning uncertainties directly into a commercial treatment planning system's IMRT plan optimization algorithm through probabilistic treatment planning (PTP) and compare coverage of this method with margin-based planning. In this work, PTP eliminates explicit margins and optimizes directly on the estimated integral treatment dose to determine optimal patient dose in the presence of setup uncertainties. Twenty-eight prostate patient plans adhering to the RTOG-0126 criteria are optimized using both margin-based and PTP methods. Only random errors are considered. For margin-based plans, the planning target volume is created by expanding the clinical target volume (CTV) by 2.1 mm to accommodate the simulated 3 mm random setup uncertainty. Random setup uncertainties are incorporated into IMRT dose evaluation by convolving each beam's incident fluence with a sigma = 3 mm Gaussian prior to dose calculation. PTP optimization uses the convolved fluence to estimate dose to ensure CTV coverage during plan optimization. PTP-based plans are compared to margin-based plans with equal CTV coverage in the presence of setup errors based on dose-volume metrics. The sensitivity of the optimized plans to patient-specific setup uncertainty variations is assessed by evaluating dose metrics for dose distributions corresponding to halving and doubling of the random setup uncertainty used in the optimization. Margin-based and PTP-based plans show similar target coverage. A physician review shows that PTP is preferred for 21 patients, margin-based plans are preferred in 2 patients, no preference is expressed for 1 patient, and both autogenerated plans are rejected for 4 patients. For the PTP-based plans, the average CTV receiving the prescription dose decreases by 0.5%, while the mean dose to the CTV increases by 0.7%. The CTV tumor control probability (TCP) is the same for both methods with the exception

  6. Dynamic path planning for mobile robot based on particle swarm optimization

    Science.gov (United States)

    Wang, Yong; Cai, Feng; Wang, Ying

    2017-08-01

    In the contemporary, robots are used in many fields, such as cleaning, medical treatment, space exploration, disaster relief and so on. The dynamic path planning of robot without collision is becoming more and more the focus of people's attention. A new method of path planning is proposed in this paper. Firstly, the motion space model of the robot is established by using the MAKLINK graph method. Then the A* algorithm is used to get the shortest path from the start point to the end point. Secondly, this paper proposes an effective method to detect and avoid obstacles. When an obstacle is detected on the shortest path, the robot will choose the nearest safety point to move. Moreover, calculate the next point which is nearest to the target. Finally, the particle swarm optimization algorithm is used to optimize the path. The experimental results can prove that the proposed method is more effective.

  7. Improved VMAT planning for head and neck tumors with an advanced optimization algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Klippel, Norbert; Schmuecking, Michael; Terribilini, Dario; Geretschlaeger, Andreas; Aebersold, Daniel M.; Manser, Peter [Bern University Hospital - Inselspital (Switzerland). Div. of Medical Radiation Physics and Dept. of Radiation Oncology

    2015-07-01

    In this study, the ''Progressive Resolution Optimizer PRO3'' (Varian Medical Systems) is compared to the previous version PRO2'' with respect to its potential to improve dose sparing to the organs at risk (OAR) and dose coverage of the PTV for head and neck cancer patients. Materials and Methods For eight head and neck cancer patients, volumetric modulated arc therapy (VMAT) treatment plans were generated in this study. All cases have 2-3 phases and the total prescribed dose (PD) was 60-72 Gy in the PTV. The study is mainly focused on the phase 1 plans, which all have an identical PD of 54 Gy, and complex PTV structures with an overlap to the parotids. Optimization was performed based on planning objectives for the PTV according to ICRU83, and with minimal dose to spinal cord, and parotids outside PTV. In order to assess the quality of the optimization algorithms, an identical set of constraints was used for both, PRO2 and PRO3. The resulting treatment plans were investigated with respect to dose distribution based on the analysis of the dose volume histograms. Results For the phase 1 plans (PD = 54 Gy) the near maximum dose D{sub 2%} of the spinal cord, could be minimized to 22±5 Gy with PRO3, as compared to 32±12 Gy with PRO2, averaged for all patients. The mean dose to the parotids was also lower in PRO3 plans compared to PRO2, but the differences were less pronounced. A PTV coverage of V{sub 95%} = 97±1% could be reached with PRO3, as compared to 86±5% with PRO2. In clinical routine, these PRO2 plans would require modifications to obtain better PTV coverage at the cost of higher OAR doses. Conclusion A comparison between PRO3 and PRO2 optimization algorithms was performed for eight head and neck cancer patients. In general, the quality of VMAT plans for head and neck patients are improved with PRO3 as compared to PRO2. The dose to OARs can be reduced significantly, especially for the spinal cord. These reductions are achieved

  8. Optimal planning of LEO active debris removal based on hybrid optimal control theory

    Science.gov (United States)

    Yu, Jing; Chen, Xiao-qian; Chen, Li-hu

    2015-06-01

    The mission planning of Low Earth Orbit (LEO) active debris removal problem is studied in this paper. Specifically, the Servicing Spacecraft (SSc) and several debris exist on near-circular near-coplanar LEOs. The SSc should repeatedly rendezvous with the debris, and de-orbit them until all debris are removed. Considering the long-duration effect of J2 perturbation, a linear dynamics model is used for each rendezvous. The purpose of this paper is to find the optimal service sequence and rendezvous path with minimum total rendezvous cost (Δv) for the whole mission, and some complex constraints (communication time window constraint, terminal state constraint, and time distribution constraint) should be satisfied meanwhile. Considering this mission as a hybrid optimal control problem, a mathematical model is proposed, as well as the solution method. The proposed approach is demonstrated by a typical active debris removal problem. Numerical experiments show that (1) the model and solution method proposed in this paper can effectively address the planning problem of LEO debris removal; (2) the communication time window constraint and the J2 perturbation have considerable influences on the optimization results; and (3) under the same configuration, some suboptimal sequences are equivalent to the optimal one since their difference in Δv cost is very small.

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

    Energy Technology Data Exchange (ETDEWEB)

    Barragán, A. M., E-mail: ana.barragan@uclouvain.be; Differding, S.; Lee, J. A.; Sterpin, E. [Center of Molecular Imaging, Radiotherapy and Oncology, Institut de Recherche Expérimentale et Clinique, Université catholique de Louvain, Brussels B-1200 (Belgium); Janssens, G. [Ion Beam Applications S.A., Louvain-la-Neuve 1348 (Belgium)

    2015-04-15

    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 of 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

  10. Optimal planning for the sustainable utilization of municipal solid waste.

    Science.gov (United States)

    Santibañez-Aguilar, José Ezequiel; Ponce-Ortega, José María; Betzabe González-Campos, J; Serna-González, Medardo; El-Halwagi, Mahmoud M

    2013-12-01

    The increasing generation of municipal solid waste (MSW) is a major problem particularly for large urban areas with insufficient landfill capacities and inefficient waste management systems. Several options associated to the supply chain for implementing a MSW management system are available, however to determine the optimal solution several technical, economic, environmental and social aspects must be considered. Therefore, this paper proposes a mathematical programming model for the optimal planning of the supply chain associated to the MSW management system to maximize the economic benefit while accounting for technical and environmental issues. The optimization model simultaneously selects the processing technologies and their location, the distribution of wastes from cities as well as the distribution of products to markets. The problem was formulated as a multi-objective mixed-integer linear programing problem to maximize the profit of the supply chain and the amount of recycled wastes, where the results are showed through Pareto curves that tradeoff economic and environmental aspects. The proposed approach is applied to a case study for the west-central part of Mexico to consider the integration of MSW from several cities to yield useful products. The results show that an integrated utilization of MSW can provide economic, environmental and social benefits.

  11. Optimizing the treatment of rhegmatogenous retinal detachment

    DEFF Research Database (Denmark)

    Hajari, Javad Nouri

    2016-01-01

    within one year after initial surgery with pneumatic retinopexy, scleral buckling and VTX with gas, and one and a half years after surgery with VTX with oil. Also lack of oil removal within the first year is a failed operation. It is widely accepted that RRD is an acute disease but when should surgery...... as an acute eye disease that needs immediate treatment. With the increasing number of cataract surgeries and an increased elderly population, the numbers of RRD occurrences are increasing. The aim of this thesis is to create knowledge on how treatment and care of RRD patients can be optimized. In the first...... of cataract surgeries and an increased elderly population. Using data from the NPR, we estimated that the risk of a RRD occurring on the fellow eye is 100 times larger than on the first eye and that middle aged men have the highest risk. Having an increase in the incidence of RRD we need to ensure...

  12. A Knowledge-Based Approach to Improving and Homogenizing Intensity Modulated Radiation Therapy Planning Quality Among Treatment Centers: An Example Application to Prostate Cancer Planning

    Energy Technology Data Exchange (ETDEWEB)

    Good, David [Medical Physics Graduate Program, Duke University, Durham, North Carolina (United States); Lo, Joseph [Medical Physics Graduate Program, Duke University, Durham, North Carolina (United States); Department of Radiology and Departments of Biomedical Engineering and Electrical and Computer Engineering, Duke University, Durham, North Carolina (United States); Lee, W. Robert [Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina (United States); Wu, Q. Jackie; Yin, Fang-Fang [Medical Physics Graduate Program, Duke University, Durham, North Carolina (United States); Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina (United States); Das, Shiva K., E-mail: shiva.das@duke.edu [Medical Physics Graduate Program, Duke University, Durham, North Carolina (United States); Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina (United States)

    2013-09-01

    Purpose: Intensity modulated radiation therapy (IMRT) treatment planning can have wide variation among different treatment centers. We propose a system to leverage the IMRT planning experience of larger institutions to automatically create high-quality plans for outside clinics. We explore feasibility by generating plans for patient datasets from an outside institution by adapting plans from our institution. Methods and Materials: A knowledge database was created from 132 IMRT treatment plans for prostate cancer at our institution. The outside institution, a community hospital, provided the datasets for 55 prostate cancer cases, including their original treatment plans. For each “query” case from the outside institution, a similar “match” case was identified in the knowledge database, and the match case’s plan parameters were then adapted and optimized to the query case by use of a semiautomated approach that required no expert planning knowledge. The plans generated with this knowledge-based approach were compared with the original treatment plans at several dose cutpoints. Results: Compared with the original plan, the knowledge-based plan had a significantly more homogeneous dose to the planning target volume and a significantly lower maximum dose. The volumes of the rectum, bladder, and femoral heads above all cutpoints were nominally lower for the knowledge-based plan; the reductions were significantly lower for the rectum. In 40% of cases, the knowledge-based plan had overall superior (lower) dose–volume histograms for rectum and bladder; in 54% of cases, the comparison was equivocal; in 6% of cases, the knowledge-based plan was inferior for both bladder and rectum. Conclusions: Knowledge-based planning was superior or equivalent to the original plan in 95% of cases. The knowledge-based approach shows promise for homogenizing plan quality by transferring planning expertise from more experienced to less experienced institutions.

  13. A Monte Carlo-based treatment planning tool for proton therapy

    Science.gov (United States)

    Mairani, A.; Böhlen, T. T.; Schiavi, A.; Tessonnier, T.; Molinelli, S.; Brons, S.; Battistoni, G.; Parodi, K.; Patera, V.

    2013-04-01

    In the field of radiotherapy, Monte Carlo (MC) particle transport calculations are recognized for their superior accuracy in predicting dose and fluence distributions in patient geometries compared to analytical algorithms which are generally used for treatment planning due to their shorter execution times. In this work, a newly developed MC-based treatment planning (MCTP) tool for proton therapy is proposed to support treatment planning studies and research applications. It allows for single-field and simultaneous multiple-field optimization in realistic treatment scenarios and is based on the MC code FLUKA. Relative biological effectiveness (RBE)-weighted dose is optimized either with the common approach using a constant RBE of 1.1 or using a variable RBE according to radiobiological input tables. A validated reimplementation of the local effect model was used in this work to generate radiobiological input tables. Examples of treatment plans in water phantoms and in patient-CT geometries together with an experimental dosimetric validation of the plans are presented for clinical treatment parameters as used at the Italian National Center for Oncological Hadron Therapy. To conclude, a versatile MCTP tool for proton therapy was developed and validated for realistic patient treatment scenarios against dosimetric measurements and commercial analytical TP calculations. It is aimed to be used in future for research and to support treatment planning at state-of-the-art ion beam therapy facilities.

  14. Averaging VMAT treatment plans for multi-criteria navigation

    CERN Document Server

    Craft, David; Unkelbach, Jan

    2013-01-01

    The main approach to smooth Pareto surface navigation for radiation therapy multi-criteria treatment planning involves taking real-time averages of pre-computed treatment plans. In fluence-based treatment planning, fluence maps themselves can be averaged, which leads to the dose distributions being averaged due to the linear relationship between fluence and dose. This works for fluence-based photon plans and proton spot scanning plans. In this technical note, we show that two or more sliding window volumetric modulated arc therapy (VMAT) plans can be combined by averaging leaf positions in a certain way, and we demonstrate that the resulting dose distribution for the averaged plan is approximately the average of the dose distributions of the original plans. This leads to the ability to do Pareto surface navigation, i.e. interactive multi-criteria exploration of VMAT plan dosimetric tradeoffs.

  15. Development of a regional hyperthermia treatment planning system.

    Science.gov (United States)

    Van de Kamer, J B; De Leeuw, A A; Hornsleth, S N; Kroeze, H; Kotte, A N; Lagendijk, J J

    2001-01-01

    A flexible and fast regional hyperthermia treatment planning system for the Coaxial TEM System has been devised and is presented. Using Hounsfield Unit based thresholding and manually outlining of the tumour, a 40 cm CT data set (slice thickness 5 mm) is segmented and down scaled to a resolution of 1 cm, requiring only 30 min. The SAR model is based on the finite-difference time-domain (FDTD) method. The number of time steps to achieve numerical stability has been determined and was found to be 7000. Various optimizations of the SAR model have been applied, resulting in a relatively short computation time of 3.7 h (memory requirements 121 MB) on a Pentium III, 450 MHz standard personal computer, running GNU/Linux. The model has been validated using absolute value(Ez) measurements in a standard phantom inserted in the Coaxial TEM Applicator under different conditions and a good agreement was found. Hyperthermia treatment planning in combination with the homemade visualization tools have provided much insight in the regional hyperthermia treatment with the Coaxial TEM Applicator.

  16. Comparison of treatment plans: a retrospective study by the method of radiobiological evaluation

    Science.gov (United States)

    Puzhakkal, Niyas; Kallikuzhiyil Kochunny, Abdullah; Manthala Padannayil, Noufal; Singh, Navin; Elavan Chalil, Jumanath; Kulangarakath Umer, Jamshad

    2016-09-01

    There are many situations in radiotherapy where multiple treatment plans need to be compared for selection of an optimal plan. In this study we performed the radiobiological method of plan evaluation to verify the treatment plan comparison procedure of our clinical practice. We estimated and correlated various radiobiological dose indices with physical dose metrics for a total of 30 patients representing typical cases of head and neck, prostate and brain tumors. Three sets of plans along with a clinically approved plan (final plan) treated by either Intensity Modulated Radiation Therapy (IMRT) or Rapid Arc (RA) techniques were considered. The study yielded improved target coverage for final plans, however, no appreciable differences in doses and the complication probabilities of organs at risk were noticed. Even though all four plans showed adequate dose distributions, from dosimetric point of view, the final plan had more acceptable dose distribution. The estimated biological outcome and dose volume histogram data showed least differences between plans for IMRT when compared to RA. Our retrospective study based on 120 plans, validated the radiobiological method of plan evaluation. The tumor cure or normal tissue complication probabilities were found to be correlated with the corresponding physical dose indices.

  17. Investigating the robustness of ion beam therapy treatment plans to uncertainties in biological treatment parameters

    CERN Document Server

    Boehlen, T T; Dosanjh, M; Ferrari, A; Fossati, P; Haberer, T; Mairani, A; Patera, V

    2012-01-01

    Uncertainties in determining clinically used relative biological effectiveness (RBE) values for ion beam therapy carry the risk of absolute and relative misestimations of RBE-weighted doses for clinical scenarios. This study assesses the consequences of hypothetical misestimations of input parameters to the RBE modelling for carbon ion treatment plans by a variational approach. The impact of the variations on resulting cell survival and RBE values is evaluated as a function of the remaining ion range. In addition, the sensitivity to misestimations in RBE modelling is compared for single fields and two opposed fields using differing optimization criteria. It is demonstrated for single treatment fields that moderate variations (up to +/-50\\%) of representative nominal input parameters for four tumours result mainly in a misestimation of the RBE-weighted dose in the planning target volume (PTV) by a constant factor and only smaller RBE-weighted dose gradients. Ensuring a more uniform radiation quality in the PTV...

  18. PLANNED LEAD TIME OPTIMIZATION IN MATERIAL REQUIREMENT PLANNING ENVIRONMENT FOR MULTILEVEL PRODUCTION SYSTEMS

    Institute of Scientific and Technical Information of China (English)

    Faicel HNAIEN; Alexandre DOLGUI; Mohamed-Aly OULD LOULY

    2008-01-01

    This paper deals with the problem of planned lead time calculation in a Material Requirement Planning (MRP) environment under stochastic lead times. The objective is to minimize the sum of holding and backlogging costs. The proposed approach is based on discrete time inventory control where the decision variables are integer. Two types of systems are considered: multi-level serial-production and assembly systems. For the serial production systems (one type of component at each level), a mathematical model is suggested. Then, it is proven that this model is equivalent to the well known discrete Newsboy Model. This directly provides the optimal values for the planned lead times. For multilevel assembly systems, a dedicated model is proposed and some properties of the decision variables and objective function are proven. These properties are used to calculate lower and upper limits on the decision variables and lower and upper bounds on the objective function. The obtained limits and bounds open the possibility to develop an efficient optimization algorithm using, for example, a Branch and Bound approach. The paper presents the proposed models in detail with corresponding proofs and several numerical examples. Some advantages of the suggested models and perspectives of this research are discussed.

  19. An improved ant colony optimization approach for optimization of process planning.

    Science.gov (United States)

    Wang, JinFeng; Fan, XiaoLiang; Ding, Haimin

    2014-01-01

    Computer-aided process planning (CAPP) is an important interface between computer-aided design (CAD) and computer-aided manufacturing (CAM) in computer-integrated manufacturing environments (CIMs). In this paper, process planning problem is described based on a weighted graph, and an ant colony optimization (ACO) approach is improved to deal with it effectively. The weighted graph consists of nodes, directed arcs, and undirected arcs, which denote operations, precedence constraints among operation, and the possible visited path among operations, respectively. Ant colony goes through the necessary nodes on the graph to achieve the optimal solution with the objective of minimizing total production costs (TPCs). A pheromone updating strategy proposed in this paper is incorporated in the standard ACO, which includes Global Update Rule and Local Update Rule. A simple method by controlling the repeated number of the same process plans is designed to avoid the local convergence. A case has been carried out to study the influence of various parameters of ACO on the system performance. Extensive comparative experiments have been carried out to validate the feasibility and efficiency of the proposed approach.

  20. Simulation and optimization models for emergency medical systems planning.

    Science.gov (United States)

    Bettinelli, Andrea; Cordone, Roberto; Ficarelli, Federico; Righini, Giovanni

    2014-01-01

    The authors address strategic planning problems for emergency medical systems (EMS). In particular, the three following critical decisions are considered: i) how many ambulances to deploy in a given territory at any given point in time, to meet the forecasted demand, yielding an appropriate response time; ii) when ambulances should be used for serving nonurgent requests and when they should better be kept idle for possible incoming urgent requests; iii) how to define an optimal mix of contracts for renting ambulances from private associations to meet the forecasted demand at minimum cost. In particular, analytical models for decision support, based on queuing theory, discrete-event simulation, and integer linear programming were presented. Computational experiments have been done on real data from the city of Milan, Italy.

  1. Dose prescription and treatment planning based on FMISO-PET hypoxia

    Energy Technology Data Exchange (ETDEWEB)

    Toma-Dasu, Iuliana; Antonovic, Laura (Medical Radiation Physics, Stockholm Univ. and Karolinska Institutet, Stockholm (Sweden)), E-mail: iuliana.livia.dasu@ki.se; Uhrdin, Johan (RaySearch Laboratories AB, Stockholm (Sweden)); Dasu, Alexandru (Dept. of Radiation Physics UHL, County Council of Oestergoetland, Linkoeping (Sweden); Radiation Physics, Dept. of Medical and Health Sciences, Faculty of Health Sciences, Linkoeping Univ., Linkoeping (Sweden)); Nuyts, Sandra; Dirix, Piet; Haustermans, Karin (Leuven Univ. Hospitals, Gasthuisberg, Dept. of Radiotherapy, Leuven (Belgium)); Brahme, Anders (Dept. of Oncology and Pathology, Karolinska Institutet, Stockholm (Sweden))

    2012-02-15

    Purpose. The study presents the implementation of a novel method for incorporating hypoxia information from PET-CT imaging into treatment planning and estimates the efficiency of various optimization approaches. Its focuses on the feasibility of optimizing treatment plans based on the non-linear conversion of PET hypoxia images into radiosensitivity maps from the uptake properties of the tracers used. Material and methods. PET hypoxia images of seven head-and-neck cancer patients were used to determine optimal dose distributions needed to counteract the radiation resistance associated with tumor hypoxia assuming various scenarios regarding the evolution of the hypoxic compartment during the treatment. A research planning system for advanced studies has been used to optimize IMRT plans based on hypoxia information from patient PET images. These resulting plans were compared in terms of target coverage for the same fulfilled constraints regarding the organs at risk. Results. The results of a planning study indicated the clinical feasibility of the proposed method for treatment planning based on PET hypoxia. Antihypoxic strategies would lead to small improvements in all the patients, but higher effects are expected for the fraction of patients with hypoxic tumors. For these, individualization of the treatment based on hypoxia PET imaging could lead to improved treatment outcome while creating the premises for limiting the irradiation of the surrounding normal tissues. Conclusions. The proposed approach offers the possibility of improved treatment results as it takes into consideration the heterogeneity and the dynamics of the hypoxic regions. It also provides early identification of the clinical cases that might benefit from dose escalation as well as the cases that could benefit from other counter-hypoxic measures

  2. Dosimetric comparison of RapidPlan and manually optimized plans in volumetric modulated arc therapy for prostate cancer.

    Science.gov (United States)

    Kubo, Kazuki; Monzen, Hajime; Ishii, Kentaro; Tamura, Mikoto; Kawamorita, Ryu; Sumida, Iori; Mizuno, Hirokazu; Nishimura, Yasumasa

    2017-07-10

    This study evaluated whether RapidPlan based plans (RP plans) created by a single optimization, are usable in volumetric modulated arc therapy (VMAT) for patients with prostate cancer. We used 51 previously administered VMAT plans to train a RP model. Thirty RP plans were created by a single optimization without planner intervention during optimization. Differences between RP plans and clinical manual optimization (CMO) plans created by an experienced planner for the same patients were analyzed (Wilcoxon tests) in terms of homogeneity index (HI), conformation number (CN), D95%, and D2% to planning target volume (PTV), mean dose, V50Gy, V70Gy, V75Gy, and V78Gy to rectum and bladder, monitor unit (MU), and multi-leaf collimator (MLC) sequence complexity. RP and CMO values for PTV D95%, PTV D2%, HI, and CN were significantly similar (pplans (pplans (pplans created by a single optimization were clinically acceptable in VMAT for patient with prostate cancer. Our simple model could reduce optimization time, independently of planner's skill and knowledge. Copyright © 2017. Published by Elsevier Ltd.

  3. Optimal Control Approaches to the Aggregate Production Planning Problem

    Directory of Open Access Journals (Sweden)

    Yasser A. Davizón

    2015-12-01

    Full Text Available In the area of production planning and control, the aggregate production planning (APP problem represents a great challenge for decision makers in production-inventory systems. Tradeoff between inventory-capacity is known as the APP problem. To address it, static and dynamic models have been proposed, which in general have several shortcomings. It is the premise of this paper that the main drawback of these proposals is, that they do not take into account the dynamic nature of the APP. For this reason, we propose the use of an Optimal Control (OC formulation via the approach of energy-based and Hamiltonian-present value. The main contribution of this paper is the mathematical model which integrates a second order dynamical system coupled with a first order system, incorporating production rate, inventory level, and capacity as well with the associated cost by work force in the same formulation. Also, a novel result in relation with the Hamiltonian-present value in the OC formulation is that it reduces the inventory level compared with the pure energy based approach for APP. A set of simulations are provided which verifies the theoretical contribution of this work.

  4. Efficient Configuration Space Construction and Optimization for Motion Planning

    Directory of Open Access Journals (Sweden)

    Jia Pan

    2015-03-01

    Full Text Available The configuration space is a fundamental concept that is widely used in algorithmic robotics. Many applications in robotics, computer-aided design, and related areas can be reduced to computational problems in terms of configuration spaces. In this paper, we survey some of our recent work on solving two important challenges related to configuration spaces: how to efficiently compute an approximate representation of high-dimensional configuration spaces; and how to efficiently perform geometric proximity and motion planning queries in high-dimensional configuration spaces. We present new configuration space construction algorithms based on machine learning and geometric approximation techniques. These algorithms perform collision queries on many configuration samples. The collision query results are used to compute an approximate representation for the configuration space, which quickly converges to the exact configuration space. We also present parallel GPU-based algorithms to accelerate the performance of optimization and search computations in configuration spaces. In particular, we design efficient GPU-based parallel k-nearest neighbor and parallel collision detection algorithms and use these algorithms to accelerate motion planning.

  5. Radiotherapy Treatment Planning for Testicular Seminoma

    Energy Technology Data Exchange (ETDEWEB)

    Wilder, Richard B., E-mail: richardbwilder@yahoo.com [Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL (United States); Buyyounouski, Mark K. [Department of Radiation Oncology, Fox Chase Cancer Center, Philadelphia, PA (United States); Efstathiou, Jason A. [Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA (United States); Beard, Clair J. [Department of Radiation Oncology, Dana-Farber/Brigham and Women' s Cancer Center, Boston, MA (United States)

    2012-07-15

    Virtually all patients with Stage I testicular seminoma are cured regardless of postorchiectomy management. For patients treated with adjuvant radiotherapy, late toxicity is a major concern. However, toxicity may be limited by radiotherapy techniques that minimize radiation exposure of healthy normal tissues. This article is an evidence-based review that provides radiotherapy treatment planning recommendations for testicular seminoma. The minority of Stage I patients who choose adjuvant treatment over surveillance may be considered for (1) para-aortic irradiation to 20 Gy in 10 fractions, or (2) carboplatin chemotherapy consisting of area under the curve, AUC = 7 Multiplication-Sign 1-2 cycles. Two-dimensional radiotherapy based on bony anatomy is a simple and effective treatment for Stage IIA or IIB testicular seminoma. Centers with expertise in vascular and nodal anatomy may consider use of anteroposterior-posteroanterior fields based on three-dimensional conformal radiotherapy instead. For modified dog-leg fields delivering 20 Gy in 10 fractions, clinical studies support placement of the inferior border at the top of the acetabulum. Clinical and nodal mapping studies support placement of the superior border of all radiotherapy fields at the top of the T12 vertebral body. For Stage IIA and IIB patients, an anteroposterior-posteroanterior boost is then delivered to the adenopathy with a 2-cm margin to the block edge. The boost dose consists of 10 Gy in 5 fractions for Stage IIA and 16 Gy in 8 fractions for Stage IIB. Alternatively, bleomycin, etoposide, and cisplatin chemotherapy for 3 cycles or etoposide and cisplatin chemotherapy for 4 cycles may be delivered to Stage IIA or IIB patients (e.g., if they have a horseshoe kidney, inflammatory bowel disease, or a history of radiotherapy).

  6. A comprehensive comparison of IMRT and VMAT plan quality for prostate cancer treatment.

    Science.gov (United States)

    Quan, Enzhuo M; Li, Xiaoqiang; Li, Yupeng; Wang, Xiaochun; Kudchadker, Rajat J; Johnson, Jennifer L; Kuban, Deborah A; Lee, Andrew K; Zhang, Xiaodong

    2012-07-15

    We performed a comprehensive comparative study of the plan quality between volumetric-modulated arc therapy (VMAT) and intensity-modulated radiation therapy (IMRT) for the treatment of prostate cancer. Eleven patients with prostate cancer treated at our institution were randomly selected for this study. For each patient, a VMAT plan and a series of IMRT plans using an increasing number of beams (8, 12, 16, 20, and 24 beams) were examined. All plans were generated using our in-house-developed automatic inverse planning (AIP) algorithm. An existing eight-beam clinical IMRT plan, which was used to treat the patient, was used as the reference plan. For each patient, all AIP-generated plans were optimized to achieve the same level of planning target volume (PTV) coverage as the reference plan. Plan quality was evaluated by measuring mean dose to and dose-volume statistics of the organs at risk, especially the rectum, from each type of plan. For the same PTV coverage, the AIP-generated VMAT plans had significantly better plan quality in terms of rectum sparing than the eight-beam clinical and AIP-generated IMRT plans (p plans in all the dosimetric indices decreased as the number of beams used in IMRT increased. IMRT plan quality was similar or superior to that of VMAT when the number of beams in IMRT was increased to a certain number, which ranged from 12 to 24 for the set of patients studied. The superior VMAT plan quality resulted in approximately 30% more monitor units than the eight-beam IMRT plans, but the delivery time was still less than 3 min. Considering the superior plan quality as well as the delivery efficiency of VMAT compared with that of IMRT, VMAT may be the preferred modality for treating prostate cancer. Copyright © 2012 Elsevier Inc. All rights reserved.

  7. Federal Facilities Compliance Act, Conceptual Site Treatment Plan. Part 1

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1993-10-29

    This Conceptual Site Treatment Plan was prepared by Ames Laboratory to meet the requirements of the Federal Facilities Compliance Act. Topics discussed in this document include: general discussion of the plan, including the purpose and scope; technical aspects of preparing plans, including the rationale behind the treatability groupings and a discussion of characterization issues; treatment technology needs and treatment options for specific waste streams; low-level mixed waste options; TRU waste options; and future waste generation from restoration activities.

  8. Three dimensional intensity modulated brachytherapy (IMBT): Dosimetry algorithm and inverse treatment planning

    Energy Technology Data Exchange (ETDEWEB)

    Shi Chengyu; Guo Bingqi; Cheng, Chih-Yao; Esquivel, Carlos; Eng, Tony; Papanikolaou, Niko [Cancer Therapy and Research Center, University of Texas Health Science Center at San Antonio, San Antonio, Texas 78229 (United States); Department of Radiation Oncology, Oklahoma University Health Science Center, Oklahoma City, Oklahoma 73104 (United States); Cancer Therapy and Research Center, University of Texas Health Science Center at San Antonio, San Antonio, Texas 78229 (United States)

    2010-07-15

    Purpose: 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. Methods: 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. Results: IMBT approaches showed superior plan quality compared to the original plans and the 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 V{sub 200} by 16.1% and 4.8%, respectively, compared to the original and the

  9. Formal-language-theoretic Optimal Path Planning For Accommodation of Amortized Uncertainties and Dynamic Effects

    CERN Document Server

    Chattopadhyay, Ishanu; Ray, Asok

    2010-01-01

    We report a globally-optimal approach to robotic path planning under uncertainty, based on the theory of quantitative measures of formal languages. A significant generalization to the language-measure-theoretic path planning algorithm $\

  10. Optimal mechanical harvester route planning for sugarcane f ield operations using particle swarm optimization

    Directory of Open Access Journals (Sweden)

    Woraya Neungmatcha

    2015-06-01

    Full Text Available Since current agricultural production systems such as the sugarcane supply system in the sugar industry are developing towards larger and more complicated systems, there is consequently increasing use of agricultural machinery. Even though mechanization can help to increase the sugarcane yield, if the mechanical operation efficiency is low, then higher harvest costs and machinery shortages will occur. Global route planning for mechanical harvesters is one of the most important problems in the field of sugarcane harvesting and transporting operations. Improved efficiency and realistic implementation can be achieved by applying advanced planning methods for the execution of field operations, especially considering the field accessibility aspect. To address this issue, participative research was undertaken with a sugar milling company to produce and implement a mixed integer programming model that represents the mechanical harvester route plan. Particle swarm optimization was applied to find a solution to the model, leading to potential cost savings versus schedules produced manually by the mill officer. The model was also applied to explore regional planning options for a more integrated harvesting and transport system.

  11. Mathematical Optimization Techniques for Multi-Phase Radiation Treatment Design

    OpenAIRE

    Sonderman, David

    1983-01-01

    A mathematical model for optimal external beam radiotherapy treatment design over multiple treatment phases is presented. The solution procedure is discussed and illustrated on a case of boost treatment for lung cancer. The models are integrated with current radiobiological software to produce an optimal design over both phases of treatment displayed by means of computer graphics.

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

    Science.gov (United States)

    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

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

    Energy Technology Data Exchange (ETDEWEB)

    Ghobadi, Kimia; Ghaffari, Hamid R.; Aleman, Dionne M.; Jaffray, David A.; Ruschin, Mark [Department of Mechanical and Industrial Engineering, University of Toronto, 5 King' s College Road, Toronto, Ontario M5S 3G8 (Canada); Department of Radiation Oncology, University of Toronto, Radiation Medicine Program, Princess Margaret Hospital, 610 University Avenue, Toronto, Ontario M5G 2M9 (Canada)

    2012-06-15

    Purpose: The purpose of this work is to develop a framework to the inverse problem for radiosurgery treatment planning on the Gamma Knife{sup Registered-Sign} Perfexion Trade-Mark-Sign (PFX) for intracranial targets. Methods: 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. Results: 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{sub 100}) between forward and inverse plans was 0.2% (range: -2.4% to +2.0%). After plan renormalization for equivalent coverage (i.e., V{sub 100}), the mean difference in dose to 1 mm{sup 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

  14. Automated high-dose rate brachytherapy treatment planning for a single-channel vaginal cylinder applicator

    Science.gov (United States)

    Zhou, Yuhong; Klages, Peter; Tan, Jun; Chi, Yujie; Stojadinovic, Strahinja; Yang, Ming; Hrycushko, Brian; Medin, Paul; Pompos, Arnold; Jiang, Steve; Albuquerque, Kevin; Jia, Xun

    2017-06-01

    High dose rate (HDR) brachytherapy treatment planning is conventionally performed manually and/or with aids of preplanned templates. In general, the standard of care would be elevated by conducting an automated process to improve treatment planning efficiency, eliminate human error, and reduce plan quality variations. Thus, our group is developing AutoBrachy, an automated HDR brachytherapy planning suite of modules used to augment a clinical treatment planning system. This paper describes our proof-of-concept module for vaginal cylinder HDR planning that has been fully developed. After a patient CT scan is acquired, the cylinder applicator is automatically segmented using image-processing techniques. The target CTV is generated based on physician-specified treatment depth and length. Locations of the dose calculation point, apex point and vaginal surface point, as well as the central applicator channel coordinates, and the corresponding dwell positions are determined according to their geometric relationship with the applicator and written to a structure file. Dwell times are computed through iterative quadratic optimization techniques. The planning information is then transferred to the treatment planning system through a DICOM-RT interface. The entire process was tested for nine patients. The AutoBrachy cylindrical applicator module was able to generate treatment plans for these cases with clinical grade quality. Computation times varied between 1 and 3 min on an Intel Xeon CPU E3-1226 v3 processor. All geometric components in the automated treatment plans were generated accurately. The applicator channel tip positions agreed with the manually identified positions with submillimeter deviations and the channel orientations between the plans agreed within less than 1 degree. The automatically generated plans obtained clinically acceptable quality.

  15. Optimal control of HIV/AIDS dynamic: Education and treatment

    Science.gov (United States)

    Sule, Amiru; Abdullah, Farah Aini

    2014-07-01

    A mathematical model which describes the transmission dynamics of HIV/AIDS is developed. The optimal control representing education and treatment for this model is explored. The existence of optimal Control is established analytically by the use of optimal control theory. Numerical simulations suggest that education and treatment for the infected has a positive impact on HIV/AIDS control.

  16. Childhood cancer treatment optimization: In rhabdomyosarcoma and supportive care

    NARCIS (Netherlands)

    Schoot, R.A.

    2015-01-01

    This thesis covers two subjects investigating optimization of cancer cure: prevention and treatment of central venous catheter related complications and improvement of local treatment in head and neck rhabdomyosarcoma survivors. Central venous catheters are indispensable in the modern day treatment

  17. Childhood cancer treatment optimization: In rhabdomyosarcoma and supportive care

    NARCIS (Netherlands)

    Schoot, R.A.

    2015-01-01

    This thesis covers two subjects investigating optimization of cancer cure: prevention and treatment of central venous catheter related complications and improvement of local treatment in head and neck rhabdomyosarcoma survivors. Central venous catheters are indispensable in the modern day treatment

  18. Photon Optimizer (PO) prevails over Progressive Resolution Optimizer (PRO) for VMAT planning with or without knowledge-based solution.

    Science.gov (United States)

    Jiang, Fan; Wu, Hao; Yue, Haizhen; Jia, Fei; Zhang, Yibao

    2017-03-01

    The enhanced dosimetric performance of knowledge-based volumetric modulated arc therapy (VMAT) planning might be jointly contributed by the patient-specific optimization objectives, as estimated by the RapidPlan model, and by the potentially improved Photon Optimizer (PO) algorithm than the previous Progressive Resolution Optimizer (PRO) engine. As PO is mandatory for RapidPlan estimation but optional for conventional manual planning, appreciating the two optimizers may provide practical guidelines for the algorithm selection because knowledge-based planning may not replace the current method completely in a short run. Using a previously validated dose-volume histogram (DVH) estimation model which can produce clinically acceptable plans automatically for rectal cancer patients without interactive manual adjustment, this study reoptimized 30 historically approved plans (referred as clinical plans that were created manually with PRO) with RapidPlan solution (PO plans). Then the PRO algorithm was utilized to optimize the plans again using the same dose-volume constraints as PO plans, where the line objectives were converted as a series of point objectives automatically (PRO plans). On the basis of comparable target dose coverage, the combined applications of new objectives and PO algorithm have significantly reduced the organs-at-risk (OAR) exposure by 23.49-32.72% than the clinical plans. These discrepancies have been largely preserved after substituting PRO for PO, indicating the dosimetric improvements were mostly attributable to the refined objectives. Therefore, Eclipse users of earlier versions may instantly benefit from adopting the model-generated objectives from other RapidPlan-equipped centers, even with PRO algorithm. However, the additional contribution made by the PO relative to PRO accounted for 1.54-3.74%, suggesting PO should be selected with priority whenever available, with or without RapidPlan solution as a purchasable package. Significantly

  19. Automatic treatment planning implementation using a database of previously treated patients

    Science.gov (United States)

    Moore, J. A.; Evans, K.; Yang, W.; Herman, J.; McNutt, T.

    2014-03-01

    Purpose: Using a database of prior treated patients, it is possible to predict the dose to critical structures for future patients. Automatic treatment planning speeds the planning process by generating a good initial plan from predicted dose values. Methods: A SQL relational database of previously approved treatment plans is populated via an automated export from Pinnacle3. This script outputs dose and machine information and selected Regions of Interests as well as its associated Dose-Volume Histogram (DVH) and Overlap Volume Histograms (OVHs) with respect to the target structures. Toxicity information is exported from Mosaiq and added to the database for each patient. The SQL query is designed to ask the system for the lowest achievable dose for a specified region of interest (ROI) for each patient with a given volume of that ROI being as close or closer to the target than the current patient. Results: The additional time needed to calculate OVHs is approximately 1.5 minutes for a typical patient. Database lookup of planning objectives takes approximately 4 seconds. The combined additional time is less than that of a typical single plan optimization (2.5 mins). Conclusions: An automatic treatment planning interface has been successfully used by dosimetrists to quickly produce a number of SBRT pancreas treatment plans. The database can be used to compare dose to individual structures with the toxicity experienced and predict toxicities before planning for future patients.

  20. Treatment plan comparison between helical tomotherapy and MLC-based IMRT using radiobiological measures

    Energy Technology Data Exchange (ETDEWEB)

    Mavroidis, Panayiotis [Department of Medical Radiation Physics, Karolinska Institutet and Stockholm University (Sweden); Ferreira, Brigida Costa [Department of Medical Radiation Physics, Karolinska Institutet and Stockholm University (Sweden); Shi, Chengyu [Department of Radiation Oncology, University of Texas Health Science Center, San Antonio, TX (United States); Lind, Bengt K [Department of Medical Radiation Physics, Karolinska Institutet and Stockholm University (Sweden); Papanikolaou, Nikos [Department of Radiation Oncology, University of Texas Health Science Center, San Antonio, TX (United States)

    2007-07-07

    The rapid implementation of advanced treatment planning and delivery technologies for radiation therapy has brought new challenges in evaluating the most effective treatment modality. Intensity-modulated radiotherapy (IMRT) using multi-leaf collimators (MLC) and helical tomotherapy (HT) are becoming popular modes of treatment delivery and their application and effectiveness continues to be investigated. Presently, there are several treatment planning systems (TPS) that can generate and optimize IMRT plans based on user-defined objective functions for the internal target volume (ITV) and organs at risk (OAR). However, the radiobiological parameters of the different tumours and normal tissues are typically not taken into account during dose prescription and optimization of a treatment plan or during plan evaluation. The suitability of a treatment plan is typically decided based on dosimetric criteria such as dose-volume histograms (DVH), maximum, minimum, mean and standard deviation of the dose distribution. For a more comprehensive treatment plan evaluation, the biologically effective uniform dose D-bar is applied together with the complication-free tumour control probability (P{sub +}). Its utilization is demonstrated using three clinical cases that were planned with two different forms of IMRT. In this study, three different cancer types at different anatomical sites were investigated: head and neck, lung and prostate cancers. For each cancer type, a linac MLC-based step-and-shoot IMRT plan and a HT plan were developed. The MLC-based IMRT treatment plans were developed on the Philips treatment-planning platform, using the Pinnacle 7.6 software release. For the tomotherapy HiArt plans, the dedicated tomotherapy treatment planning station was used, running version 2.1.2. By using D-bar as the common prescription point of the treatment plans and plotting the tissue response probabilities versus D-bar for a range of prescription doses, a number of plan trials can be

  1. Interactive dose shaping part 1: a new paradigm for IMRT treatment planning.

    Science.gov (United States)

    Ziegenhein, Peter; Ph Kamerling, Cornelis; Oelfke, Uwe

    2016-03-21

    In this work we present a novel treatment planning technique called interactive dose shaping (IDS) to be employed for the optimization of intensity modulated radiation therapy (IMRT). IDS does not rely on a Newton-based optimization algorithm which is driven by an objective function formed of dose volume constraints on pre-segmented volumes of interest (VOIs). Our new planning technique allows for direct, interactive adaptation of localized planning features. This is realized by a dose modification and recovery (DMR) planning engine which implements a two-step approach: firstly, the desired localized plan adaptation is imposed on the current plan (modification) while secondly inevitable, undesired disturbances of the dose pattern elsewhere are compensated for automatically by the recovery module. Together with an ultra-fast dose update calculation method the DMR engine has been implemented in a newly designed 3D therapy planning system Dynaplan enabling true real-time interactive therapy planning. Here we present the underlying strategy and algorithms of the DMR based planning concept. The functionality of the IDS planning approach is demonstrated for a phantom geometry of clinical resolution and size.

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

    Energy Technology Data Exchange (ETDEWEB)

    Gopan, O; Yang, F; Ford, E [University of Washington, Seattle, WA (United States)

    2015-06-15

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

  3. A study of the plan dosimetric evaluation on the rectal cancer treatment

    Energy Technology Data Exchange (ETDEWEB)

    Jeong, Hyun Hak; An, Beom Seok; Kim, Dae Il; Lee, Yang Hoon; Lee, Je Hee [Dept. of Radiation Oncology, Seoul National University Hospital, Seoul (Korea, Republic of)

    2016-12-15

    In order to minimize the dose of femoral head as an appropriate treatment plan for rectal cancer radiation therapy, we compare and evaluate the usefulness of 3-field 3D conformal radiation therapy(below 3fCRT), which is a universal treatment method, and 5-field 3D conformal radiation therapy(below 5fCRT), and Volumetric Modulated Arc Therapy (VMAT). The 10 cases of rectal cancer that treated with 21EX were enrolled. Those cases were planned by Eclipse(Ver. 10.0.42, Varian, USA), PRO3(Progressive Resolution Optimizer 10.0.28) and AAA(Anisotropic Analytic Algorithm Ver. 10.0.28). 3fCRT and 5fCRT plan has 0 degrees, 270 degrees, 90 degrees and 0 degrees, 95 degrees, 45 degrees, 315 degrees, 265 degrees gantry angle, respectively. VMAT plan parameters consisted of 15MV coplanar 360 degrees 1 arac. Treatment prescription was employed delivering 54Gy to recum in 30 fractions. To minimize the dose difference that shows up randomly on optimizing, VMAT plans were optimized and calculated twice, and normalized to the target V100%=95%. The indexes of evaluation are D of Both femoral head and aceta fossa, total MU, H.I.(Homogeneity index) and C.I.(Conformity index) of the PTV. All VMAT plans were verified by gamma test with portal dosimetry using EPID. D of Rt. femoral head was 53.08 Gy, 50.27 Gy, and 30.92 Gy, respectively, in the order of 3fCRT, 5fCRT, and VMAT treatment plan. Likewise, Lt. Femoral head showed average 53.68 Gy, 51.01 Gy and 29.23 Gy in the same order. D of Rt. aceta fossa was 54.86 Gy, 52.40 Gy, 30.37 Gy, respectively, in the order of 3fCRT, 5fCRT, and VMAT treatment plan. Likewise, Lt. Femoral head showed average 53.68 Gy, 51.01 Gy and 29.23 Gy in the same order. The maximum dose of both femoral head and aceta fossa was higher in the order of 3fCRT, 5fCRT, and VMAT treatment plan. C.I. showed the lowest VMAT treatment plan with an average of 1.64, 1.48, and 0.99 in the order of 3fCRT, 5fCRT, and VMAT treatment plan. There was no significant difference on H

  4. MINERVA - A Multi-Modal Radiation Treatment Planning System

    Energy Technology Data Exchange (ETDEWEB)

    D. E. Wessol; C. A. Wemple; D. W. Nigg; J. J. Cogliati; M. L. Milvich; C. Frederickson; M. Perkins; G. A. Harkin

    2004-10-01

    Recently, research efforts have begun to examine the combination of BNCT with external beam photon radiotherapy (Barth et al. 2004). In order to properly prepare treatment plans for patients being treated with combinations of radiation modalities, appropriate planning tools must be available. To facilitiate this, researchers at the Idaho National Engineering and Environmental Laboratory (INEEL)and Montana State University (MSU) have undertaken development of a fully multi-modal radiation treatment planning system.

  5. The feasibility of using Pareto fronts for comparison of treatment planning systems and delivery techniques.

    Science.gov (United States)

    Ottosson, Rickard O; Engstrom, Per E; Sjöström, David; Behrens, Claus F; Karlsson, Anna; Knöös, Tommy; Ceberg, Crister

    2009-01-01

    Pareto optimality is a concept that formalises the trade-off between a given set of mutually contradicting objectives. A solution is said to be Pareto optimal when it is not possible to improve one objective without deteriorating at least one of the other. A set of Pareto optimal solutions constitute the Pareto front. The Pareto concept applies well to the inverse planning process, which involves inherently contradictory objectives, high and uniform target dose on one hand, and sparing of surrounding tissue and nearby organs at risk (OAR) on the other. Due to the specific characteristics of a treatment planning system (TPS), treatment strategy or delivery technique, Pareto fronts for a given case are likely to differ. The aim of this study was to investigate the feasibility of using Pareto fronts as a comparative tool for TPSs, treatment strategies and delivery techniques. In order to sample Pareto fronts, multiple treatment plans with varying target conformity and dose sparing of OAR were created for a number of prostate and head & neck IMRT cases. The DVHs of each plan were evaluated with respect to target coverage and dose to relevant OAR. Pareto fronts were successfully created for all studied cases. The results did indeed follow the definition of the Pareto concept, i.e. dose sparing of the OAR could not be improved without target coverage being impaired or vice versa. Furthermore, various treatment techniques resulted in distinguished and well separated Pareto fronts. Pareto fronts may be used to evaluate a number of parameters within radiotherapy. Examples are TPS optimization algorithms, the variation between accelerators or delivery techniques and the degradation of a plan during the treatment planning process. The issue of designing a model for unbiased comparison of parameters with such large inherent discrepancies, e.g. different TPSs, is problematic and should be carefully considered.

  6. Optimization of intensity modulated beams in inverse planning by norm minimization

    Science.gov (United States)

    Ringor, Michael Randall

    There are two general paradigms for treatment planning: forward planning and inverse planning. In forward planning, an initial set of treatment parameter values are refined by trial and error until a desired dose distribution is produced. In inverse planning the problem is to determine the appropriate parameter values directly from the desired dose distribution. In this thesis the inverse planning problem (IPP) is posed mathematically as an inverse problem and as an optimization problem. In the case where scatter and attenuation are ignored (the NS-NA model) the inverse problem reduces to the inversion of the Dual Radon operator; if rotational symmetry is assumed, the problem simplifies to the solution of the Abel integral equation. The inverse solutions exhibit negative components and are therefore nonphysical. By formulating the IPP as a constrained optimization problem, the occurrence of negative components can be eliminated using non-negativity constraints. Additional constraints, such as dose limits, can be easily incorporated. The optimality criteria are based on minimizing the L1 and the L2 norms: the former is formulated as a linear program and the latter is formulated as a quadratic program. The numerical solutions of these mathematical programs are obtained in the NS-NA model and in the case where attenuation and scatter are present (SCAT models). In the case of the symmetric NS-NA model, analytical solutions are found using the variational calculus. Since linear and quadratic programs are convex programs, the solutions are global solutions (but not necessarily unique). Comparisons are made between the L1 and the L2 solutions in both the SCAT and the NS-NA dose models for various phantom geometries. The results indicate that norm minimization is a viable approach in the resolution of the IPP; furthermore, the underlying algorithms are sufficiently fast for use in an interactive environment. On a PC running Window NT 4.0 with 192MB RAM, solving the L1

  7. Sampling-based Algorithms for Optimal Motion Planning

    CERN Document Server

    Karaman, Sertac

    2011-01-01

    During the last decade, sampling-based path planning algorithms, such as Probabilistic RoadMaps (PRM) and Rapidly-exploring Random Trees (RRT), have been shown to work well in practice and possess theoretical guarantees such as probabilistic completeness. However, little effort has been devoted to the formal analysis of the quality of the solution returned by such algorithms, e.g., as a function of the number of samples. The purpose of this paper is to fill this gap, by rigorously analyzing the asymptotic behavior of the cost of the solution returned by stochastic sampling-based algorithms as the number of samples increases. A number of negative results are provided, characterizing existing algorithms, e.g., showing that, under mild technical conditions, the cost of the solution returned by broadly used sampling-based algorithms converges almost surely to a non-optimal value. The main contribution of the paper is the introduction of new algorithms, namely, PRM* and RRT*, which are provably asymptotically opti...

  8. Knowledge-based treatment planning: An inter-technique and inter-system feasibility study for prostate cancer.

    Science.gov (United States)

    Cagni, Elisabetta; Botti, Andrea; Micera, Renato; Galeandro, Maria; Sghedoni, Roberto; Orlandi, Matteo; Iotti, Cinzia; Cozzi, Luca; Iori, Mauro

    2017-04-01

    Helical Tomotherapy (HT) plans were used to create two RapidPlan knowledge-based (KB) models to generate plans with different techniques and to guide the optimization in a different treatment planning system for prostate plans. Feasibility and performance of these models were evaluated. two sets of 35 low risk (LR) and 30 intermediate risk (IR) prostate cancer cases who underwent HT treatments were selected to train RapidPlan models. The KB predicted constraints were used to perform new 20KB plans using RapidArc technique (KB-RA) (inter-technique validation), and to optimise 20 new HT (KB-HT) plans in the Tomoplan (inter-system validation). For each validation modality, KB plans were benchmarked with the manual plans created by an expert planner (EP). RapidPlan was successfully configured using HT plans. The KB-RA plans fulfilled the clinical dose-volume requirements in 100% and 92% of cases for planning target volumes (PTVs) and organs at risk (OARs), respectively. For KB-HT plans these percentages were found to be a bit lower: 90% for PTVs and 86% for OARs. In comparison to EP plans, the KB-RA plans produced higher bladder doses for both LR and IR, and higher rectum doses for LR. KB-HT and EP plans produced similar results. RapidPlan can be trained to create models by using plans of a different treatment modality. These models were suitable for generating clinically acceptable plans for inter-technique and inter-system applications. The use of KB models based on plans of consolidated technique could be useful with a new treatment modality. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

  9. Nitrate Waste Treatment Sampling and Analysis Plan

    Energy Technology Data Exchange (ETDEWEB)

    Vigil-Holterman, Luciana R. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Martinez, Patrick Thomas [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Garcia, Terrence Kerwin [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-07-05

    This plan is designed to outline the collection and analysis of nitrate salt-bearing waste samples required by the New Mexico Environment Department- Hazardous Waste Bureau in the Los Alamos National Laboratory (LANL) Hazardous Waste Facility Permit (Permit).

  10. A dose homogeneity and conformity evaluation between ViewRay and pinnacle-based linear accelerator IMRT treatment plans.

    Science.gov (United States)

    Saenz, Daniel L; Paliwal, Bhudatt R; Bayouth, John E

    2014-04-01

    ViewRay, a novel technology providing soft-tissue imaging during radiotherapy is investigated for treatment planning capabilities assessing treatment plan dose homogeneity and conformity compared with linear accelerator plans. ViewRay offers both adaptive radiotherapy and image guidance. The combination of cobalt-60 (Co-60) with 0.35 Tesla magnetic resonance imaging (MRI) allows for magnetic resonance (MR)-guided intensity-modulated radiation therapy (IMRT) delivery with multiple beams. This study investigated head and neck, lung, and prostate treatment plans to understand what is possible on ViewRay to narrow focus toward sites with optimal dosimetry. The goal is not to provide a rigorous assessment of planning capabilities, but rather a first order demonstration of ViewRay planning abilities. Images, structure sets, points, and dose from treatment plans created in Pinnacle for patients in our clinic were imported into ViewRay. The same objectives were used to assess plan quality and all critical structures were treated as similarly as possible. Homogeneity index (HI), conformity index (CI), and volume receiving conformity increase for lung. The volume receiving 20% of the prescription dose increased 2-8% for head and neck and up to 4% for lung and prostate. Overall, for head and neck Co-60 ViewRay treatments planned with its Monte Carlo treatment planning software were comparable with 6 MV plans computed with convolution superposition algorithm on Pinnacle treatment planning system.

  11. Particle Swarm Optimization and Its Application in Transmission Network Expansion Planning

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    The author introduced particle swarm optimization as a new method for power transmission network expansion planning. A new discrete method for particle swarm optimization, was developed, which is suitable for power transmission network expansion planning, and requires less computer s memory. The optimization fitness function construction, parameter selection, convergence judgement, and their characters were analyzed. Numerical simulation demonstrated the effectiveness and correctness of the method, This paper provides an academic and practical basis of particle swarm optimization in application of transmission network expansion planning for further investigation.

  12. CDIO Based Optimization of Urban Planning Personnel Training Courses in Forestry Universities

    Institute of Scientific and Technical Information of China (English)

    Ming; SUN; Jun; ZHANG; Jun; DONG; Bing; CHANG

    2014-01-01

    On the basis of analyzing existing course system of urban planning discipline,this paper came up with a framework for optimization of urban planning personnel training mode and course system,oriented towards training practical engineering personnel and based on CDIO engineering education and teaching platform. Then it made empirical study on setting of the urban planning discipline in Northeast Forestry University. It proposed changing the original "3 + 2" course system,exploring and optimizing the course system,improving teaching effect of urban planning personnel training courses,and raising planning and design ability of students.

  13. Voxel-Based Dose Prediction with Multi-Patient Atlas Selection for Automated Radiotherapy Treatment Planning

    CERN Document Server

    McIntosh, Chris

    2016-01-01

    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 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 (CT) 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 do...

  14. Using Optimization to Improve NASA Extravehicular Activity Planning

    Science.gov (United States)

    2012-09-01

    planning process is required to prepare for each highly choreographed EVA operation. The current planning process relies heavily upon time-consuming...process is required to prepare for each highly choreographed EVA operation. The current planning process relies heavily upon time-consuming heuristic...multitude of sources. As a result, EVA plans must be highly choreographed to achieve the maximum value from each operation. Since the advent of EVA

  15. Integrated modeling of ozonation for optimization of drinking water treatment

    NARCIS (Netherlands)

    van der Helm, A.W.C.

    2007-01-01

    Drinking water treatment plants automation becomes more sophisticated, more on-line monitoring systems become available and integration of modeling environments with control systems becomes easier. This gives possibilities for model-based optimization. In operation of drinking water treatment

  16. Aortic stenosis: From diagnosis to optimal treatment

    Directory of Open Access Journals (Sweden)

    Tavčiovski Dragan

    2008-01-01

    Full Text Available Aortic stenosis is the most frequent valvular heart disease. Aortic sclerosis is the first characteristic lesion of the cusps, which is considered today as the process similar to atherosclerosis. Progression of the disease is an active process leading to forming of bone matrix and heavily calcified stiff cusps by inflammatory cells and osteopontin. It is a chronic, progressive disease which can remain asymptomatic for a long time even in the presence of severe aortic stenosis. Proper physical examination remains an essential diagnostic tool in aortic stenosis. Recognition of characteristic systolic murmur draws attention and guides further diagnosis in the right direction. Doppler echocardiography is an ideal tool to confirm diagnosis. It is well known that exercise tests help in stratification risk of asymptomatic aortic stenosis. Serial measurements of brain natriuretic peptide during a follow-up period may help to identify the optimal time for surgery. Heart catheterization is mostly restricted to preoperative evaluation of coronary arteries rather than to evaluation of the valve lesion itself. Currently, there is no ideal medical treatment for slowing down the disease progression. The first results about the effect of ACE inhibitors and statins in aortic sclerosis and stenosis are encouraging, but there is still not enough evidence. Onset symptoms based on current ACC/AHA/ESC recommendations are I class indication for aortic valve replacement. Aortic valve can be replaced with a biological or prosthetic valve. There is a possibility of percutaneous aortic valve implantation and transapical operation for patients that are contraindicated for standard cardiac surgery.

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

    Science.gov (United States)

    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.

  18. Optimizing municipal wastewater treatment plants using an improved multi-objective optimization method.

    Science.gov (United States)

    Zhang, Rui; Xie, Wen-Ming; Yu, Han-Qing; Li, Wen-Wei

    2014-04-01

    An improved multi-objective optimization (MOO) model was established and used for simultaneously optimizing the treatment cost and multiple effluent quality indexes (including effluent COD, NH4(+)-N, NO3(-)-N) of a municipal wastewater treatment plant (WWTP). Compared with previous models that were mainly based on the use of fixed decision factors and did not taken into account the treatment cost, this model introduces a relationship model based on back propagation algorithm to determine the set of decision factors according to the expected optimization targets. Thus, a more flexible and precise optimization of the treatment process was allowed. Moreover, a MOO of conflicting objectives (i.e., treatment cost and effluent quality) was achieved. Applying this method, an optimal balance between operating cost and effluent quality of a WWTP can be found. This model may offer a useful tool for optimized design and control of practical WWTPs.

  19. An Optimization Model and Modified Harmony Search Algorithm for Microgrid Planning with ESS

    Directory of Open Access Journals (Sweden)

    Yang Jiao

    2017-01-01

    Full Text Available To solve problems such as the high cost of microgrids (MGs, balance between supply and demand, stability of system operation, and optimizing the MG planning model, the energy storage system (ESS and harmony search algorithm (HSA are proposed. First, the conventional MG planning optimization model is constructed and the constraint conditions are defined: the supply and demand balance and reserve requirements. Second, an ESS is integrated into the optimal model of MG planning. The model with an ESS can solve and identify parameters such as the optimal power, optimal capacity, and optimal installation year. Third, the convergence speed and robustness of the ESS are optimized and improved. A case study comprising three different cases concludes the paper. The results show that the modified HSA (MHSA can effectively improve the stability and economy of MG operation with an ESS.

  20. An overview of Monte Carlo treatment planning for radiotherapy.

    Science.gov (United States)

    Spezi, Emiliano; Lewis, Geraint

    2008-01-01

    The implementation of Monte Carlo dose calculation algorithms in clinical radiotherapy treatment planning systems has been anticipated for many years. Despite a continuous increase of interest in Monte Carlo Treatment Planning (MCTP), its introduction into clinical practice has been delayed by the extent of calculation time required. The development of newer and faster MC codes is behind the commercialisation of the first MC-based treatment planning systems. The intended scope of this article is to provide the reader with a compact 'primer' on different approaches to MCTP with particular attention to the latest developments in the field.

  1. Proposed Site Treatment Plan (PSTP). STP reference document

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1995-02-22

    The Department of Energy (DOE) is required by Section 3021(b) of the Resource Conservation and Recovery Act (RCRA), as amended by the Federal Facility Compliance Act (FFCAct), to prepare a plan describing the development of treatment capacities and technologies for treating mixed waste (hazardous/radioactive waste). DOE decided to prepare its site treatment plan in a three phased approach. The first phase, called the Conceptual Site Treatment Plan (CSTP), was issued in October 1993. At the Savannah River Site (SRS) the CSTP described mixed waste streams generated at SRS and listed treatment scenarios for each waste stream utilizing an onsite, offsite DOE, and offsite or onsite commercial or vendor treatment option. The CSTP is followed by the Draft Site Treatment Plan (DSTP), due to be issued in August 1994. The DSTP, the current activity., will narrow the options discussed in the CSTP to a preferred treatment option, if possible, and will include waste streams proposed to be shipped to SRS from other DOE facilities as well as waste streams SRS may send offsite for treatment. The SRS DSTP process has been designed to address treatment options for each of the site`s mixed waste streams. The SRS Proposed Site Treatment Plan (PSTP) is due to be issued in February 1995. The compliance order would be derived from the PSTP.

  2. Manpower Planning for Wastewater Treatment Plants.

    Science.gov (United States)

    Davies, J. Kenneth; And Others

    This document discusses the components necessary in the development of a forecasting process by which manpower needs can be determined and the development of action programs by which the projected needs may be satisfied. The primary focus of this manual is directed at that person in a state agency who has the responsibility for planning the…

  3. TH-A-9A-02: BEST IN PHYSICS (THERAPY) - 4D IMRT Planning Using Highly- Parallelizable Particle Swarm Optimization

    Energy Technology Data Exchange (ETDEWEB)

    Modiri, A; Gu, X; Sawant, A [UT Southwestern Medical Center, Dallas, TX (United States)

    2014-06-15

    Purpose: We present a particle swarm optimization (PSO)-based 4D IMRT planning technique designed for dynamic MLC tracking delivery to lung tumors. The key idea is to utilize the temporal dimension as an additional degree of freedom rather than a constraint in order to achieve improved sparing of organs at risk (OARs). Methods: The target and normal structures were manually contoured on each of the ten phases of a 4DCT scan acquired from a lung SBRT patient who exhibited 1.5cm tumor motion despite the use of abdominal compression. Corresponding ten IMRT plans were generated using the Eclipse treatment planning system. These plans served as initial guess solutions for the PSO algorithm. Fluence weights were optimized over the entire solution space i.e., 10 phases × 12 beams × 166 control points. The size of the solution space motivated our choice of PSO, which is a highly parallelizable stochastic global optimization technique that is well-suited for such large problems. A summed fluence map was created using an in-house B-spline deformable image registration. Each plan was compared with a corresponding, internal target volume (ITV)-based IMRT plan. Results: The PSO 4D IMRT plan yielded comparable PTV coverage and significantly higher dose—sparing for parallel and serial OARs compared to the ITV-based plan. The dose-sparing achieved via PSO-4DIMRT was: lung Dmean = 28%; lung V20 = 90%; spinal cord Dmax = 23%; esophagus Dmax = 31%; heart Dmax = 51%; heart Dmean = 64%. Conclusion: Truly 4D IMRT that uses the temporal dimension as an additional degree of freedom can achieve significant dose sparing of serial and parallel OARs. Given the large solution space, PSO represents an attractive, parallelizable tool to achieve globally optimal solutions for such problems. This work was supported through funding from the National Institutes of Health and Varian Medical Systems. Amit Sawant has research funding from Varian Medical Systems, VisionRT Ltd. and Elekta.

  4. Automated generation of IMRT treatment plans for prostate cancer patients with metal hip prostheses: comparison of different planning strategies.

    Science.gov (United States)

    Voet, Peter W J; Dirkx, Maarten L P; Breedveld, Sebastiaan; Heijmen, Ben J M

    2013-07-01

    To compare IMRT planning strategies for prostate cancer patients with metal hip prostheses. All plans were generated fully automatically (i.e., no human trial-and-error interactions) using iCycle, the authors' in-house developed algorithm for multicriterial selection of beam angles and optimization of fluence profiles, allowing objective comparison of planning strategies. For 18 prostate cancer patients (eight with bilateral hip prostheses, ten with a right-sided unilateral prosthesis), two planning strategies were evaluated: (i) full exclusion of beams containing beamlets that would deliver dose to the target after passing a prosthesis (IMRT remove) and (ii) exclusion of those beamlets only (IMRT cut). Plans with optimized coplanar and noncoplanar beam arrangements were generated. Differences in PTV coverage and sparing of organs at risk (OARs) were quantified. The impact of beam number on plan quality was evaluated. Especially for patients with bilateral hip prostheses, IMRT cut significantly improved rectum and bladder sparing compared to IMRT remove. For 9-beam coplanar plans, rectum V60 Gy reduced by 17.5% ± 15.0% (maximum 37.4%, p = 0.036) and rectum D mean by 9.4% ± 7.8% (maximum 19.8%, p = 0.036). Further improvements in OAR sparing were achievable by using noncoplanar beam setups, reducing rectum V 60Gy by another 4.6% ± 4.9% (p = 0.012) for noncoplanar 9-beam IMRT cut plans. Large reductions in rectum dose delivery were also observed when increasing the number of beam directions in the plans. For bilateral implants, the rectum V 60Gy was 37.3% ± 12.1% for coplanar 7-beam plans and reduced on average by 13.5% (maximum 30.1%, p = 0.012) for 15 directions. iCycle was able to automatically generate high quality plans for prostate cancer patients with prostheses. Excluding only beamlets that passed through the prostheses (IMRTcut strategy) significantly improved OAR sparing. Noncoplanar beam arrangements and, to a larger extent, increasing the number of

  5. Automated generation of IMRT treatment plans for prostate cancer patients with metal hip prostheses: Comparison of different planning strategies

    Energy Technology Data Exchange (ETDEWEB)

    Voet, Peter W. J.; Dirkx, Maarten L. P.; Breedveld, Sebastiaan; Heijmen, Ben J. M. [Erasmus MC - Daniel den Hoed Cancer Center, Department of Radiation Oncology, Groene Hilledijk 301, 3075EA Rotterdam (Netherlands)

    2013-07-15

    Purpose: To compare IMRT planning strategies for prostate cancer patients with metal hip prostheses.Methods: All plans were generated fully automatically (i.e., no human trial-and-error interactions) using iCycle, the authors' in-house developed algorithm for multicriterial selection of beam angles and optimization of fluence profiles, allowing objective comparison of planning strategies. For 18 prostate cancer patients (eight with bilateral hip prostheses, ten with a right-sided unilateral prosthesis), two planning strategies were evaluated: (i) full exclusion of beams containing beamlets that would deliver dose to the target after passing a prosthesis (IMRT{sub remove}) and (ii) exclusion of those beamlets only (IMRT{sub cut}). Plans with optimized coplanar and noncoplanar beam arrangements were generated. Differences in PTV coverage and sparing of organs at risk (OARs) were quantified. The impact of beam number on plan quality was evaluated.Results: Especially for patients with bilateral hip prostheses, IMRT{sub cut} significantly improved rectum and bladder sparing compared to IMRT{sub remove}. For 9-beam coplanar plans, rectum V{sub 60Gy} reduced by 17.5%{+-} 15.0% (maximum 37.4%, p= 0.036) and rectum D{sub mean} by 9.4%{+-} 7.8% (maximum 19.8%, p= 0.036). Further improvements in OAR sparing were achievable by using noncoplanar beam setups, reducing rectum V{sub 60Gy} by another 4.6%{+-} 4.9% (p= 0.012) for noncoplanar 9-beam IMRT{sub cut} plans. Large reductions in rectum dose delivery were also observed when increasing the number of beam directions in the plans. For bilateral implants, the rectum V{sub 60Gy} was 37.3%{+-} 12.1% for coplanar 7-beam plans and reduced on average by 13.5% (maximum 30.1%, p= 0.012) for 15 directions.Conclusions: iCycle was able to automatically generate high quality plans for prostate cancer patients with prostheses. Excluding only beamlets that passed through the prostheses (IMRT{sub cut} strategy) significantly improved

  6. Economic and environmental optimization of waste treatment

    DEFF Research Database (Denmark)

    Münster, Marie; Ravn, Hans; Hedegaard, Karsten;

    2015-01-01

    waste: incineration of the full amount or sorting out organic waste for biogas production for either combined heat and power generation or as fuel in vehicles. The case study illustrates that the optimal solution depends on the objective and assumptions regarding the background system - illustrated......This article presents the new systems engineering optimization model, OptiWaste, which incorporates a life cycle assessment (LCA) methodology and captures important characteristics of waste management systems. As part of the optimization, the model identifies the most attractive waste management...... with different assumptions regarding displaced electricity production. The article shows that it is feasible to combine LCA methodology with optimization. Furthermore, it highlights the need for including the integrated waste and energy system into the model. © 2014 Elsevier Ltd. All rights reserved....

  7. Economic and environmental optimization of waste treatment

    DEFF Research Database (Denmark)

    Münster, Marie; Ravn, Hans; Hedegaard, Karsten

    2015-01-01

    with different assumptions regarding displaced electricity production. The article shows that it is feasible to combine LCA methodology with optimization. Furthermore, it highlights the need for including the integrated waste and energy system into the model. © 2014 Elsevier Ltd. All rights reserved.......This article presents the new systems engineering optimization model, OptiWaste, which incorporates a life cycle assessment (LCA) methodology and captures important characteristics of waste management systems. As part of the optimization, the model identifies the most attractive waste management...... waste: incineration of the full amount or sorting out organic waste for biogas production for either combined heat and power generation or as fuel in vehicles. The case study illustrates that the optimal solution depends on the objective and assumptions regarding the background system - illustrated...

  8. Optimization model for the design of distributed wastewater treatment networks

    Directory of Open Access Journals (Sweden)

    Ibrić Nidret

    2012-01-01

    Full Text Available In this paper we address the synthesis problem of distributed wastewater networks using mathematical programming approach based on the superstructure optimization. We present a generalized superstructure and optimization model for the design of the distributed wastewater treatment networks. The superstructure includes splitters, treatment units, mixers, with all feasible interconnections including water recirculation. Based on the superstructure the optimization model is presented. The optimization model is given as a nonlinear programming (NLP problem where the objective function can be defined to minimize the total amount of wastewater treated in treatment operations or to minimize the total treatment costs. The NLP model is extended to a mixed integer nonlinear programming (MINLP problem where binary variables are used for the selection of the wastewater treatment technologies. The bounds for all flowrates and concentrations in the wastewater network are specified as general equations. The proposed models are solved using the global optimization solvers (BARON and LINDOGlobal. The application of the proposed models is illustrated on the two wastewater network problems of different complexity. First one is formulated as the NLP and the second one as the MINLP. For the second one the parametric and structural optimization is performed at the same time where optimal flowrates, concentrations as well as optimal technologies for the wastewater treatment are selected. Using the proposed model both problems are solved to global optimality.

  9. A graph-based ant colony optimization approach for process planning.

    Science.gov (United States)

    Wang, JinFeng; Fan, XiaoLiang; Wan, Shuting

    2014-01-01

    The complex process planning problem is modeled as a combinatorial optimization problem with constraints in this paper. An ant colony optimization (ACO) approach has been developed to deal with process planning problem by simultaneously considering activities such as sequencing operations, selecting manufacturing resources, and determining setup plans to achieve the optimal process plan. A weighted directed graph is conducted to describe the operations, precedence constraints between operations, and the possible visited path between operation nodes. A representation of process plan is described based on the weighted directed graph. Ant colony goes through the necessary nodes on the graph to achieve the optimal solution with the objective of minimizing total production costs (TPC). Two cases have been carried out to study the influence of various parameters of ACO on the system performance. Extensive comparative experiments have been conducted to demonstrate the feasibility and efficiency of the proposed approach.

  10. The Trimeric Model: A New Model of Periodontal Treatment Planning

    OpenAIRE

    Azouni, Khalid G; Tarakji, Bassel

    2014-01-01

    Treatment of periodontal disease is a complex and multidisciplinary procedure, requiring periodontal, surgical, restorative, and orthodontic treatment modalities. Several authors attempted to formulate models for periodontal treatment that orders the treatment steps in a logical and easy to remember manner. In this article, we discuss two models of periodontal treatment planning from two of the most well-known textbook in the specialty of periodontics internationally. Then modify them to arri...

  11. OPTIMAL MOTION PLANNING FOR A RIGID SPACECRAFT WITH TWO MOMENTUM WHEELS USING QUASI-NEWTON METHOD

    Institute of Scientific and Technical Information of China (English)

    Ge Xinsheng; Zhang Qizhi; Chen LiQun

    2006-01-01

    An optimal motion planning scheme based on the quasi-Newton method is proposed for a rigid spacecraft with two momentum wheels. A cost functional is introduced to incorporate the control energy, the final state errors and the constraints on states. The motion planning for determining control inputs to minimize the cost functional is formulated as a nonlinear optimal control problem. Using the control parametrization, one can transform the infinite dimensional optimal control problem to a finite dimensional one that is solved via the quasi-Newton methods for a feasible trajectory which satisfies the nonholonomic constraint. The optimal motion planning scheme was applied to a rigid spacecraft with two momentum wheels. The simulation results show the effectiveness of the proposed optimal motion planning scheme.

  12. Quality assurance procedures during commissioning of a treatment planning system as a tool to establish new standards before migration.

    Science.gov (United States)

    Bielęda, Grzegorz; Zwierzchowski, Grzegorz; Błasiak, Barbara; Skowronek, Janusz

    2010-06-01

    Treatment planning system commissioning is one of the most important parts of the quality assurance system in a working brachytherapy department. Migration to a more sophisticated system is always a step forward for the planning team but careful verification of the workflow and obtained results is mandatory. The question is not only whether the quality and safety of the previous standards can be preserved, but also about the possibility of reaching a higher level. The general objective of this study was to compare and verify calculation algorithms implemented in the treatment planning systems Plato Brachytherapy v.14.3.7 and Oncentra Masterplan (Brachy) V.3.1 SP 3. In order to revise the optimization algorithms implemented in the compared treatment systems, a series of 20 interstitial breast cancer applications were used. Treatment plans were optimized using geometric optimization with distance option. The parameters V, D90, D100, V100, V150, V200 and DNR were gained for target volume. On the basis of the value of Student's t-test parameters (α = 0.05) plans prepared using optimization algorithms implemented in the two treatment planning systems were compared. For the treatment plans prepared using Oncentra Masterplan a lower value of DNR (p = 0.018) was obtained. Uniformity of the dose distribution does not collide with comparable D90 values for both treatment planning systems (p = 0.109). Dose throughout the target volume (D100) was also proved to be higher in plans prepared using Oncentra Masterplan (p = 0.012). For interstitial applications Oncentra Masterplan planning system enables one to prepare a more homogeneous dose distribution but also a higher dose in the whole treated volume, while the volume covered with the therapeutic dose does not statistically differ.

  13. Role of the parameters involved in the plan optimization based on the generalized equivalent uniform dose and radiobiological implications

    Science.gov (United States)

    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.

  14. An optimization model of UAV route planning for road segment surveillance

    Institute of Scientific and Technical Information of China (English)

    刘晓锋; 关志伟; 宋裕庆; 陈大山

    2014-01-01

    Unmanned aerial vehicle (UAV) was introduced to take road segment traffic surveillance. Considering the limited UAV maximum flight distance, UAV route planning problem was studied. First, a multi-objective optimization model of planning UAV route for road segment surveillance was proposed, which aimed to minimize UAV cruise distance and minimize the number of UAVs used. Then, an evolutionary algorithm based on Pareto optimality technique was proposed to solve multi-objective UAV route planning problem. At last, a UAV flight experiment was conducted to test UAV route planning effect, and a case with three scenarios was studied to analyze the impact of different road segment lengths on UAV route planning. The case results show that the optimized cruise distance and the number of UAVs used decrease by an average of 38.43% and 33.33%, respectively. Additionally, shortening or extending the length of road segments has different impacts on UAV route planning.

  15. A dosimetric comparison between CyberKnife and tomotherapy treatment plans for single brain metastasis.

    Science.gov (United States)

    Greto, Daniela; Pallotta, Stefania; Masi, Laura; Talamonti, Cinzia; Marrazzo, Livia; Doro, Raffaella; Saieva, Calogero; Scoccianti, Silvia; Desideri, Isacco; Livi, Lorenzo

    2017-05-01

    Radiosurgery (RS) is a well-established treatment in selected patients with brain metastasis. The aim of this study is to compare the differences between CyberKnife (CK) and TomoTherapy (HT) treatment plans of RS of single brain metastasis (BM) to define when HT should be used in cases beyond Cyberknife-when both systems are readily available for the radiation oncologist. Nineteen patients with single brain metastasis treated with CK were re-planned for radiosurgery using TomoTherapy Hi-ART system. Two planning approaches have been used for TomoTherapy plans: the classical one (HT) and the improved conformity (icHT) that produces dose distributions more similar to those of RS plans. PTV coverage, Conformity Index (CI), Paddick Conformity Index (nCI), Homogeneity Index (HI), Gradient Index (GI), and beam on time of CK, HT, and icHT plans were evaluated and compared. A good coverage was found for CK, HT, and icHT plans. A difference between mean HI of CK and icHT plans was observed (p = 0.007). Better dose gradients compared to both icHT and HT modalities were observed in CK plans. icHT modality showed improved mean CI respect to HT modality, similar to that obtained in CK plans. CK plans show higher conformity and lower GI than icHT and HT plans. TomoTherapy demonstrates the advantage of being a device capable to reach different clinical objectives depending on the different planning modality employed. CyberKnife and TomoTherapy are both optimal RS devices, the choice to use one over another has to be clinically guided.

  16. 300 Area waste acid treatment system closure plan. Revision 1

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1996-03-01

    This section provides a description of the Hanford Site, identifies the proposed method of 300 Area Waste Acid Treatment System (WATS) closure, and briefly summarizes the contents of each chapter of this plan.

  17. Optimisation of beam-orientations in conformal radiotherapy treatment planning

    Energy Technology Data Exchange (ETDEWEB)

    Rowbottom, C.G

    1999-07-01

    Many synergistic advances have led to the beginnings of the routine use of conformal radiotherapy. These include advances in diagnostic imaging, in 3D treatment planning, in the technology for complex treatment delivery and in computer assessment of rival treatment plans. A conformal radiotherapy treatment plan more closely conforms the high-dose volume to the target volume, reducing the dose to normal healthy tissue. Traditionally, human planners have devised the treatment parameters used in radiotherapy treatment plans via a manually iterative process. Computer 'optimisation' algorithms have been shown to improve treatment plans as they can explore much more of the search space in a relatively short time. This thesis examines beam-orientation computer 'optimisation' in radiotherapy treatment planning and several new techniques were developed. Using these techniques a comparison was performed between treatment plans with 'standard', fixed beam-orientations and treatment plans with 'optimised' beam-orientations for patients with cancer of the prostate, oesophagus and brain. Plans were compared on the basis of dose-distributions and in some cases biological models for the probability of damage to the target volume and the major organs-at-risk (OARs) in each patient group. A cohort of patients was considered in each group to avoid bias from a specific patient geometry. In the case of the patient cohort with cancer of the prostate, a coplanar beam-orientation 'optimisation' scheme led to an average increase in the TCP of (5.7{+-}1.4)% compared to the standard plans after the dose to the isocentre had been scaled to produce a rectal NTCP of 1%. For the patient cohort with cancer of the oesophagus, the beam-orientation 'optimisation' scheme reduced the average lung NTCP by (0.7{+-}0.2)% at the expense of a modest increase in the average spinal cord NTCP of (0.1{+-}0.2)%. A non-coplanar beam-orientation &apos

  18. Dose optimization based on linear programming implemented in a system for treatment planning in Monte Carlo; Optimizacion de dosis basada en programacion lineal implemenetada en un un sistema para la planificacion de tratamiento en Monte Carlo

    Energy Technology Data Exchange (ETDEWEB)

    Ureba, A.; Palma, B. A.; Leal, A.

    2011-07-01

    Develop a more efficient method of optimization in relation to time, based on linear programming designed to implement a multi objective penalty function which also permits a simultaneous solution integrated boost situations considering two white volumes simultaneously.

  19. The path planning of UAV based on orthogonal particle swarm optimization

    Science.gov (United States)

    Liu, Xin; Wei, Haiguang; Zhou, Chengping; Li, Shujing

    2013-10-01

    To ensure the attack mission success rate, a trajectory with high survivability and accepted path length and multiple paths with different attack angles must be planned. This paper proposes a novel path planning algorithm based on orthogonal particle swarm optimization, which divides population individual and speed vector into independent orthogonal parts, velocity and individual part update independently, this improvement advances optimization effect of traditional particle swarm optimization in the field of path planning, multiple paths are produced by setting different attacking angles, this method is simulated on electronic chart, the simulation result shows the effect of this method.

  20. A Monte Carlo-based treatment-planning tool for ion beam therapy

    CERN Document Server

    Böhlen, T T; Dosanjh, M; Ferrari, A; Haberer, T; Parodi, K; Patera, V; Mairan, A

    2013-01-01

    Ion beam therapy, as an emerging radiation therapy modality, requires continuous efforts to develop and improve tools for patient treatment planning (TP) and research applications. Dose and fluence computation algorithms using the Monte Carlo (MC) technique have served for decades as reference tools for accurate dose computations for radiotherapy. In this work, a novel MC-based treatment-planning (MCTP) tool for ion beam therapy using the pencil beam scanning technique is presented. It allows single-field and simultaneous multiple-fields optimization for realistic patient treatment conditions and for dosimetric quality assurance for irradiation conditions at state-of-the-art ion beam therapy facilities. It employs iterative procedures that allow for the optimization of absorbed dose and relative biological effectiveness (RBE)-weighted dose using radiobiological input tables generated by external RBE models. Using a re-implementation of the local effect model (LEM), theMCTP tool is able to perform TP studies u...

  1. A minimally invasive approach for a compromised treatment plan.

    Science.gov (United States)

    Maibaum, Wayne W

    2016-01-01

    A primary goal in dentistry is the execution of appropriate treatment plans that are minimally invasive and maintainable. However, it is sometimes necessary to repair existing dental restorations or revise treatment plans to accommodate changes in a patient's condition. In the present case, a patient who was satisfied with a removable partial overdenture lost a critical abutment tooth. A creative, minimally invasive approach enabled the patient to keep his existing partial prosthesis and avoid the need for a full reconstruction or complete denture.

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

    Energy Technology Data Exchange (ETDEWEB)

    Hosini, M [King Saud University Hospitals, Riyadh (Saudi Arabia); GALAL, M [Hermitage Medical Clinic, Dublin (Ireland); Emam, I [Ain Shams University, Cairo (France); Kamal, G; Algohary, M [Al Azhar University, Cairo (Egypt)

    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 Direct 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.

  3. Optimal Model and Solution of Railway Hub Shift Working Plan

    Institute of Scientific and Technical Information of China (English)

    He Shiwei; Zhu Songnian; Lin Boliang

    1996-01-01

    Aiming at decreasing the hub transportation costs, a railway hub shift working plan in terms of multicommodity network flow model is set up for considering the coordination of freight working, train working and locomotive working plans. The solution and the calculating results are also introduced.

  4. Methods to model and predict the ViewRay treatment deliveries to aid patient scheduling and treatment planning.

    Science.gov (United States)

    Liu, Shi; Wu, Yu; Wooten, H Omar; Green, Olga; Archer, Brent; Li, Harold; Yang, Deshan

    2016-03-08

    A software tool is developed, given a new treatment plan, to predict treatment delivery time for radiation therapy (RT) treatments of patients on ViewRay magnetic resonance image-guided radiation therapy (MR-IGRT) delivery system. This tool is necessary for managing patient treatment scheduling in our clinic. The predicted treatment delivery time and the assessment of plan complexities could also be useful to aid treatment planning. A patient's total treatment delivery time, not including time required for localization, is modeled as the sum of four components: 1) the treatment initialization time; 2) the total beam-on time; 3) the gantry rotation time; and 4) the multileaf collimator (MLC) motion time. Each of the four components is predicted separately. The total beam-on time can be calculated using both the planned beam-on time and the decay-corrected dose rate. To predict the remain-ing components, we retrospectively analyzed the patient treatment delivery record files. The initialization time is demonstrated to be random since it depends on the final gantry angle of the previous treatment. Based on modeling the relationships between the gantry rotation angles and the corresponding rotation time, linear regression is applied to predict the gantry rotation time. The MLC motion time is calculated using the leaves delay modeling method and the leaf motion speed. A quantitative analysis was performed to understand the correlation between the total treatment time and the plan complexity. The proposed algorithm is able to predict the ViewRay treatment delivery time with the average prediction error 0.22min or 1.82%, and the maximal prediction error 0.89 min or 7.88%. The analysis has shown the correlation between the plan modulation (PM) factor and the total treatment delivery time, as well as the treatment delivery duty cycle. A possibility has been identified to significantly reduce MLC motion time by optimizing the positions of closed MLC pairs. The accuracy of

  5. Procedures for Dealing with Optimism Bias in Transport Planning

    DEFF Research Database (Denmark)

    Flyvbjerg, Bent; Glenting, Carsten; Rønnest, Arne Kvist

    of the document are to provide empirically based optimism bias up-lifts for selected reference classes of transport infrastructure projects and provide guidance on using the established uplifts to produce more realistic forecasts for the individual project's capital expenditures. Furthermore, the underlying...... causes and institutional context for optimism bias in British transport projects are discussed and some possibilities for reducing optimism bias in project preparation and decision-making are identified....

  6. Quality assurance procedures during commissioning of a treatment planning system as a tool to establish new standards before migration

    Directory of Open Access Journals (Sweden)

    Barbara Błasiak

    2010-07-01

    Full Text Available Purpose: Treatment planning system commissioning is one of the most important parts of the quality assurance system in a working brachytherapy department. Migration to a more sophisticated system is always a step forward for the planning team but careful verification of the workflow and obtained results is mandatory. The question is not only whether the quality and safety of the previous standards can be preserved, but also about the possibility of reaching a higher level. The general objective of this study was to compare and verify calculation algorithms implemented in thetreatment planning systems Plato Brachytherapy v.14.3.7 and Oncentra Masterplan (Brachy V.3.1 SP 3.Material and methods: In order to revise the optimization algorithms implemented in the compared treatment systems, a series of 20 interstitial breast cancer applications were used. Treatment plans were optimized using geometric optimization with distance option. The parameters V, D90, D100, V100, V150, V200 and DNR were gained for target volume. On the basis of the value of Student’s t-test parameters (α = 0.05 plans prepared using optimization algorithmsimplemented in the two treatment planning systems were compared.Results: For the treatment plans prepared using Oncentra Masterplan a lower value of DNR (p = 0.018 was obtained.Uniformity of the dose distribution does not collide with comparable D90 values for both treatment planning systems (p = 0.109. Dose throughout the target volume (D100 was also proved to be higher in plans prepared using Oncentra Masterplan (p = 0.012.Conclusions: For interstitial applications Oncentra Masterplan planning system enables one to prepare a more homogeneous dose distribution but also a higher dose in the whole treated volume, while the volume covered with the therapeutic dose does not statistically differ.

  7. Planning Optimal Paths for Multi-agent Systems on Graphs

    CERN Document Server

    Yu, Jingjin

    2012-01-01

    For the problem of moving a set of agents on a connected graph with unit edge distance to agent-specific goal locations, free of collisions, we propose two multiflow based integer linear programming (ILP) models that find time optimal and distance optimal solutions, respectively. The resulting algorithms from our ILP models are complete and guaranteed to yield true optimal solutions. Focusing on the time optimal formulation, we evaluate its performance, both as a stand alone algorithm and as a generic heuristic for quickly solving large problem instances. The computational results confirm the effectiveness of our method.

  8. IMRT treatment planning based on prioritizing prescription goals.

    Science.gov (United States)

    Wilkens, Jan J; Alaly, James R; Zakarian, Konstantin; Thorstad, Wade L; Deasy, Joseph O

    2007-03-21

    Determining the 'best' optimization parameters in IMRT planning is typically a time-consuming trial-and-error process with no unambiguous termination point. Recently we and others proposed a goal-programming approach which better captures the desired prioritization of dosimetric goals. Here, individual prescription goals are addressed stepwise in their order of priority. In the first step, only the highest order goals are considered (target coverage and dose-limiting normal structures). In subsequent steps, the achievements of the previous steps are turned into hard constraints and lower priority goals are optimized, in turn, subject to higher priority constraints. So-called 'slip' factors were introduced to allow for slight, clinically acceptable violations of the constraints. Focusing on head and neck cases, we present several examples for this planning technique. The main advantages of the new optimization method are (i) its ability to generate plans that meet the clinical goals, as well as possible, without tuning any weighting factors or dose-volume constraints, and (ii) the ability to conveniently include more terms such as fluence map smoothness. Lower level goals can be optimized to the achievable limit without compromising higher order goals. The prioritized prescription-goal planning method allows for a more intuitive and human-time-efficient way of dealing with conflicting goals compared to the conventional trial-and-error method of varying weighting factors and dose-volume constraints.

  9. IMRT treatment planning based on prioritizing prescription goals

    Science.gov (United States)

    Wilkens, Jan J.; Alaly, James R.; Zakarian, Konstantin; Thorstad, Wade L.; Deasy, Joseph O.

    2007-03-01

    Determining the 'best' optimization parameters in IMRT planning is typically a time-consuming trial-and-error process with no unambiguous termination point. Recently we and others proposed a goal-programming approach which better captures the desired prioritization of dosimetric goals. Here, individual prescription goals are addressed stepwise in their order of priority. In the first step, only the highest order goals are considered (target coverage and dose-limiting normal structures). In subsequent steps, the achievements of the previous steps are turned into hard constraints and lower priority goals are optimized, in turn, subject to higher priority constraints. So-called 'slip' factors were introduced to allow for slight, clinically acceptable violations of the constraints. Focusing on head and neck cases, we present several examples for this planning technique. The main advantages of the new optimization method are (i) its ability to generate plans that meet the clinical goals, as well as possible, without tuning any weighting factors or dose-volume constraints, and (ii) the ability to conveniently include more terms such as fluence map smoothness. Lower level goals can be optimized to the achievable limit without compromising higher order goals. The prioritized prescription-goal planning method allows for a more intuitive and human-time-efficient way of dealing with conflicting goals compared to the conventional trial-and-error method of varying weighting factors and dose-volume constraints.

  10. IMRT treatment planning based on prioritizing prescription goals

    Energy Technology Data Exchange (ETDEWEB)

    Wilkens, Jan J [Department of Radiation Oncology, Washington University School of Medicine, and Siteman Cancer Center, Saint Louis, MO (United States); Alaly, James R [Department of Radiation Oncology, Washington University School of Medicine, and Siteman Cancer Center, Saint Louis, MO (United States); Zakarian, Konstantin [Department of Radiation Oncology, Washington University School of Medicine, and Siteman Cancer Center, Saint Louis, MO (United States); Thorstad, Wade L [Department of Radiation Oncology, Washington University School of Medicine, and Siteman Cancer Center, Saint Louis, MO (United States); Deasy, Joseph O [Department of Radiation Oncology, Washington University School of Medicine, and Siteman Cancer Center, Saint Louis, MO (United States)

    2007-03-21

    Determining the 'best' optimization parameters in IMRT planning is typically a time-consuming trial-and-error process with no unambiguous termination point. Recently we and others proposed a goal-programming approach which better captures the desired prioritization of dosimetric goals. Here, individual prescription goals are addressed stepwise in their order of priority. In the first step, only the highest order goals are considered (target coverage and dose-limiting normal structures). In subsequent steps, the achievements of the previous steps are turned into hard constraints and lower priority goals are optimized, in turn, subject to higher priority constraints. So-called 'slip' factors were introduced to allow for slight, clinically acceptable violations of the constraints. Focusing on head and neck cases, we present several examples for this planning technique. The main advantages of the new optimization method are (i) its ability to generate plans that meet the clinical goals, as well as possible, without tuning any weighting factors or dose-volume constraints, and (ii) the ability to conveniently include more terms such as fluence map smoothness. Lower level goals can be optimized to the achievable limit without compromising higher order goals. The prioritized prescription-goal planning method allows for a more intuitive and human-time-efficient way of dealing with conflicting goals compared to the conventional trial-and-error method of varying weighting factors and dose-volume constraints.

  11. Developing a treatment planning process and software for improved translation of photodynamic therapy

    Science.gov (United States)

    Cassidy, J.; Zheng, Z.; Xu, Y.; Betz, V.; Lilge, L.

    2017-04-01

    Background: The majority of de novo cancers are diagnosed in low and middle-income countries, which often lack the resources to provide adequate therapeutic options. None or minimally invasive therapies such as Photodynamic Therapy (PDT) or photothermal therapies could become part of the overall treatment options in these countries. However, widespread acceptance is hindered by the current empirical training of surgeons in these optical techniques and a lack of easily usable treatment optimizing tools. Methods: Based on image processing programs, ITK-SNAP, and the publicly available FullMonte light propagation software, a work plan is proposed that allows for personalized PDT treatment planning. Starting with, contoured clinical CT or MRI images, the generation of 3D tetrahedral models in silico, execution of the Monte Carlo simulation and presentation of the 3D fluence rate, Φ, [mWcm-2] distribution a treatment plan optimizing photon source placement is developed. Results: Permitting 1-2 days for the installation of the required programs, novices can generate their first fluence, H [Jcm-2] or Φ distribution in a matter of hours. This is reduced to 10th of minutes with some training. Executing the photon simulation calculations is rapid and not the performance limiting process. Largest sources of errors are uncertainties in the contouring and unknown tissue optical properties. Conclusions: The presented FullMonte simulation is the fastest tetrahedral based photon propagation program and provides the basis for PDT treatment planning processes, enabling a faster proliferation of low cost, minimal invasive personalized cancer therapies.

  12. Physics aspects of prostate tomotherapy: Planning optimization and image-guidance issues

    Energy Technology Data Exchange (ETDEWEB)

    Fiorino, Claudio; Alongi, Filippo; Broggi, Sara (Medical Physics, S. Raffaele Inst., Milano (Italy)) (and others)

    2008-08-15

    Purpose. To review planning and image-guidance aspects of more than 3 years experience in the treatment of prostate cancer with Helical Tomotherapy (HT). Methods and materials. Planning issues concerning two Phase I-II clinical studies were addressed: in the first one, 58 Gy in 20 fractions were delivered to the prostatic bed for post-prostatectomy patients: in the second one, a simultaneous integrated boost (SIB) approach was applied for radical treatment, delivering 71.4-74.2 Gy to the prostate in 28 fractions. On-line daily MVCT image guidance was applied: bone match was used for post-operative patients while prostate match was applied for radically treated patients. MVCT data of a large sample of both categories of patients were reviewed. Results. At now, more than 250 patients were treated. Planning data show the ability of HT in creating highly homogeneous dose distributions within PTVs. Organs at risk (OAR) sparing also showed to be excellent. HT was also found to favorably compare to inversely-optimized IMAT in terms of PTVs coverage and dose distribution homogeneity. In the case of pelvic nodes irradiation, a large sparing of bowel was evident compared to 3DCRT and conventional 5-fields IMRT. The analysis of MVCT data showed a limited motion of the prostate (about 5% of the fractions show a deviation =3 mm in posterior-anterior direction), due to the careful application of rectal emptying procedures. Based on phantom measurements and on the comparison with intra-prostatic calcification-based match, direct visualization prostate match seems to be sufficiently reliable in assessing shifts =3 mm. Conclusions. HT offers excellent planning solutions for prostate cancer, showing to be highly efficient in a SIB scenario. Daily MVCT information showed evidence of a limited motion of the prostate in the context of rectal filling control obtained by instructing patients in self-administrating a rectal enema

  13. Assessment tool for planning fallback Tomotherapy treatment plans; Evaluacion de la herramienta fallback planning para planes de tratamiento de tomoterapia

    Energy Technology Data Exchange (ETDEWEB)

    Sanchez Rubio, P.; Rodriguez Romero, R.; Montes Uruen, A.

    2015-07-01

    Interruption of radiotherapy treatments in an increase the total time of the same to the detriment of tumour control. In centers that have a unique special unit as the TomoTherapy, is emphasized the difficulty to resume treatment at another unit, since the technique of helical TomoTherapy is not portable to conventional accelerators and therefore requires the planning of new dosimetry distributions emulating the initially obtained and accepted. This work evaluates the ability of an automatic planning tool to mimic TomoTherapy plans. (Author)

  14. Novel methods for treatment planning in Ion Beam Therapy

    OpenAIRE

    Cabal Arango, Gonzalo Alfonso

    2012-01-01

    One of the biggest challenges in ion beam therapy is the mitigation of the impact of uncertainties in the quality of treatment plans. Some of the strategies used to reduce this impact are based on concepts developed decades ago for photon therapy. In this thesis novel methods and concepts, tailored to the specifi c needs of ion beam therapy, are proposed which reduce the effect of uncertainties on treatment plans. This is done in two steps: First, we revisit the concept of the Planning Target...

  15. Novel integrated optimization algorithm for trajectory planning of robot manipulators based on integrated evolutionary programming

    Institute of Scientific and Technical Information of China (English)

    Xiong LUO; Xiaoping FAN; Heng ZHANG; Tefang CHEN

    2004-01-01

    Optimal trajectory planning for robot manipulators plays an important role in implementing the high productivity for robots.The performance indexes used in optimal trajectory planning are classified into two main categories:optimum traveling time and optimum mechanical energy of the actuators.The current trajectory planning algorithms are designed based on one of the above two performance indexes.So far,there have been few planning algorithms designed to satisfy two performance indexes simultaneously.On the other hand,some deficiencies arise in the existing integrated optimization algorithms of trajectory planning.In order to overcome those deficiencies,the integrated optimization algorithms of trajectory planning are presented based on the complete analysis for trajectory planning of robot manipulators.In the algorithm,two object functions are designed based on the specific weight coefficient method and "ideal point" strategy.Moreover,based on the features of optimization problem,the intensified evolutionary programming is proposed to solve the corresponding optimization model.Especially,for the Stanford Robot,the high-quality solutions are found at a lower cost.

  16. Application of particle swarm optimization in path planning of mobile robot

    Science.gov (United States)

    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.

  17. New ways to optimize breast cancer treatment

    NARCIS (Netherlands)

    Schröder, Carolina Pia

    2001-01-01

    Breast cancer patients without apparent distant metastases at the time of primary tumor removal, may later suffer from a distant relapse, indicating the presence of occult micrometastases at the time of diagnosis. Sensitive methods to detect micrometastatic breast cancer may be helpful in optimizing

  18. 300 Area waste acid treatment system closure plan

    Energy Technology Data Exchange (ETDEWEB)

    LUKE, S.N.

    1999-05-17

    The Hanford Facility Dangerous Waste Permit Application is considered to be a single application organized into a General Information Portion (document number DOERL-91-28) and a Unit-Specific Portion. The scope of the Unit-Specific Portion includes closure plan documentation submitted for individual, treatment, storage, and/or disposal units undergoing closure, such as the 300 Area Waste Acid Treatment System. Documentation contained in the General Information Portion is broader in nature and could be used by multiple treatment, storage, and/or disposal units (e.g., the glossary provided in the General Information Portion). Whenever appropriate, 300 Area Waste Acid Treatment System documentation makes cross-reference to the General Information Portion, rather than duplicating text. This 300 Area Waste Acid Treatment System Closure Plan (Revision 2) includes a Hanford Facility Dangerous Waste Permit Application, Part A, Form 3. Information provided in this closure plan is current as of April 1999.

  19. Globally Optimal Path Planning with Anisotropic Running Costs

    Science.gov (United States)

    2013-03-01

    Proceedings of the American Control Conference , pp...Jacques, D. R. & Pachter, M. (2002) Air vehicle optimal trajectories between two radars, in Proceedings of the American Control Conference . Pachter...M. & Hebert, J. (2001) Optimal aircraft trajectories for radar exposure mini- mization, in Proceedings of the American Control Conference .

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

    Science.gov (United States)

    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) CPU plan. The average number of voxels meeting the Γ 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

  1. Treatment planning for brachytherapy: an integer programming model, two computational approaches and experiments with permanent prostate implant planning.

    Science.gov (United States)

    Lee, E K; Gallagher, R J; Silvern, D; Wuu, C S; Zaider, M

    1999-01-01

    An integer linear programming model is proposed as a framework for optimizing seed placement and dose distribution in brachytherapy treatment planning. The basic model involves using 0/1 indicator variables to describe the placement or non-placement of seeds in a prespecified three-dimensional grid of potential locations. The dose delivered to each point in a discretized representation of the diseased organ and neighbouring healthy tissue can then be modelled as a linear combination of the indicator variables. A system of linear constraints is imposed to attempt to keep the dose level at each point to within specified target bounds. Since it is physically impossible to satisfy all constraints simultaneously, each constraint uses a variable to either record when the target dose level is achieved, or to record the deviation from the desired level. These additional variables are embedded into an objective function to be optimized. Variations on this model are discussed and two computational approaches--a branch-and-bound algorithm and a genetic algorithm--for finding 'optimal' seed placements are described. Results of computational experiments on a collection of prostate cancer cases are reported. The results indicate that both optimization algorithms are capable of producing good solutions within 5 to 15 min, and that small variations in model parameters can have a measurable effect on the dose distribution of the resulting plans.

  2. Cost Optimal Reliability Based Inspection and Replacement Planning of Piping Subjected to CO2 Corrosion

    DEFF Research Database (Denmark)

    Hellevik, S. G.; Langen, I.; Sørensen, John Dalsgaard

    1999-01-01

    A methodology for cost optimal reliability based inspection and replacement planning of piping subjected to CO2 corrosion is described. Both initial (design phase) and in-service planning are dealt with. The methodology is based on the application of methods for structural reliability analysis...... within the framework of Bayesian decision theory. The planning problem is formulated as an optimization problem where the expected lifetime costs are minimized with a constraint on the minimum acceptable reliability level. The optimization parameters are the number of inspections in the expected lifetime......, the inspection times and methods. In the design phase the nominal design wall thickness is also treated as an optimization parameter. The most important benefits gained through the application of the methodology are consistent evaluation of the consequences of different inspection and replacement plans...

  3. Incorporating High-Speed, Optimizing, Interleaving, Configurable/Composable Scheduling into NASA's EUROPA Planning Architecture Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Advanced, robust, autonomous planning systems have not focused on the scheduling decisions made by the planner. And high quality, optimizing schedulers have rarely...

  4. Double global optimum genetic algorithm-particle swarm optimization-based welding robot path planning

    Science.gov (United States)

    Wang, Xuewu; Shi, Yingpan; Ding, Dongyan; Gu, Xingsheng

    2016-02-01

    Spot-welding robots have a wide range of applications in manufacturing industries. There are usually many weld joints in a welding task, and a reasonable welding path to traverse these weld joints has a significant impact on welding efficiency. Traditional manual path planning techniques can handle a few weld joints effectively, but when the number of weld joints is large, it is difficult to obtain the optimal path. The traditional manual path planning method is also time consuming and inefficient, and cannot guarantee optimality. Double global optimum genetic algorithm-particle swarm optimization (GA-PSO) based on the GA and PSO algorithms is proposed to solve the welding robot path planning problem, where the shortest collision-free paths are used as the criteria to optimize the welding path. Besides algorithm effectiveness analysis and verification, the simulation results indicate that the algorithm has strong searching ability and practicality, and is suitable for welding robot path planning.

  5. Optimal, Generic Planning of Maintenance and Inspection of Steel Bridges

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard; Faber, M.H.

    2002-01-01

    Fatigue damage is an important deterioration mechanism for steel bridges. This paper describes a simplified and generic approach for reliability and risk based inspection planning of fatigue sensitive structural details. Fatigue sensitive details are categorized according to their loading...

  6. Machine Learning for Earth Observation Flight Planning Optimization

    Data.gov (United States)

    National Aeronautics and Space Administration — This paper is a progress report of an effort whose goal is to demonstrate the effectiveness of automated data mining and planning for the daily management of Earth...

  7. Treatment Planning Considerations for Robotic Guided Cardiac Radiosurgery for Atrial Fibrillation

    Science.gov (United States)

    Ipsen, Svenja; Chan, Mark K; Bauer, Ralf; Kerl, Matthias; Hunold, Peter; Jacobi, Volkmar; Bruder, Ralf; Schweikard, Achim; Rades, Dirk; Vogl, Thomas J; Kleine, Peter; Bode, Frank; Dunst, Jürgen

    2016-01-01

    Purpose Robotic guided stereotactic radiosurgery has recently been investigated for the treatment of atrial fibrillation (AF). Before moving into human treatments, multiple implications for treatment planning given a potential target tracking approach have to be considered.    Materials & Methods Theoretical AF radiosurgery treatment plans for twenty-four patients were generated for baseline comparison. Eighteen patients were investigated under ideal tracking conditions, twelve patients under regional dose rate (RDR = applied dose over a certain time window) optimized conditions (beam delivery sequence sorting according to regional beam targeting), four patients under ultrasound tracking conditions (beam block of the ultrasound probe) and four patients with temporary single fiducial tracking conditions (differential surrogate-to-target respiratory and cardiac motion).   Results With currently known guidelines on dose limitations of critical structures, treatment planning for AF radiosurgery with 25 Gy under ideal tracking conditions with a 3 mm safety margin may only be feasible in less than 40% of the patients due to the unfavorable esophagus and bronchial tree location relative to the left atrial antrum (target area). Beam delivery sequence sorting showed a large increase in RDR coverage (% of voxels having a larger dose rate for a given time window) of 10.8-92.4% (median, 38.0%) for a 40-50 min time window, which may be significant for non-malignant targets. For ultrasound tracking, blocking beams through the ultrasound probe was found to have no visible impact on plan quality given previous optimal ultrasound window estimation for the planning CT. For fiducial tracking in the right atrial septum, the differential motion may reduce target coverage by up to -24.9% which could be reduced to a median of -0.8% (maximum, -12.0%) by using 4D dose optimization. The cardiac motion was also found to have an impact on the dose distribution, at the anterior left atrial

  8. Treatment optimization with concurrent SBRT and intracavitary brachytherapy for locally advanced cervical cancer.

    Science.gov (United States)

    Wan, Bin; Lang, Jinyi; Wang, Pei; Ma, C-M

    2016-01-01

    This work is aimed at investigating treatment planning strategies to optimally combine stereotactic body radiation therapy (SBRT) with intracavitary brachytherapy (ICBT) for the treatment of locally advanced cervical cancer. Forty patients (stage IIB - IIIB) previously treated with combined SBRT and ICBT were randomly selected for this retrospective study. All patients were CT- and MR-scanned with a ring applicator in situ. HR-CTV and OARs were contoured according to fused CT and MR images. Several ICBT plans were generated for each patient based on different dose prescription points, and then a matching SBRT plan was generated for each ICBT plan. The dose distribution of each composite plan was analyzed with a focus on the doses received by 90% and 100% of the target volume (D90 and D100), the target volume receiving 100% of the prescription dose (V100%), and the doses received by 2 cc and 40% of the OARs (D2cc and D40). As the distance, d, between the prescription point and the tandem varied within 1.0 and 1.9 cm, the D90, D100 and V100% for the target, as well as D2cc and D40 for the bladder and rectum approached their optimal values for d value between 1.0 and 1.4 cm. When designing a combined ICBT+SBRT plan, one should measure the size of the cervix and set the prescription isodose line 1.0 to 1.4 cm away from the tandem for the ICBT plan first and then optimize the SBRT plan based on the ICBT dose distribution to achieve the best target coverage and critical structures sparing. PACS number: 87.53.jw; 87.55.D. © 2016 The Authors.

  9. Optimization of Map Compilation for County-level Land Consolidation Planning

    Institute of Scientific and Technical Information of China (English)

    2012-01-01

    Based on practice of the land consolidation planning in Changfeng County of Hefei City,taking full account of reality of land consolidation and its significance as livelihood project,we analyzed map compilation procedure.In combination with actual effect of land consolidation,we carried out consolidation assessment of same elements by overall planning method,and optimized the map compilation for county-level land consolidation planning.Results show that planning map of land consolidation potential is to be improved and legends should be merged.After consolidation of legends,it is convenient to apply in potential planning map and solve complicated problem of reading maps.

  10. submitter Biologically optimized helium ion plans: calculation approach and its in vitro validation

    CERN Document Server

    Mairani, A; Magro, G; Tessonnier, T; Kamp, F; Carlson, D J; Ciocca, M; Cerutti, F; Sala, P R; Ferrari, A; Böhlen, T T; Jäkel, O; Parodi, K; Debus, J; Abdollahi, A; Haberer, T

    2016-01-01

    Treatment planning studies on the biological effect of raster-scanned helium ion beams should be performed, together with their experimental verification, before their clinical application at the Heidelberg Ion Beam Therapy Center (HIT). For this purpose, we introduce a novel calculation approach based on integrating data-driven biological models in our Monte Carlo treatment planning (MCTP) tool. Dealing with a mixed radiation field, the biological effect of the primary $^4$He ion beams, of the secondary $^3$He and $^4$He (Z  =  2) fragments and of the produced protons, deuterons and tritons (Z  =  1) has to be taken into account. A spread-out Bragg peak (SOBP) in water, representative of a clinically-relevant scenario, has been biologically optimized with the MCTP and then delivered at HIT. Predictions of cell survival and RBE for a tumor cell line, characterized by ${{(\\alpha /\\beta )}_{\\text{ph}}}=5.4$ Gy, have been successfully compared against measured clonogenic survival data. The mean ...

  11. FoCa: a modular treatment planning system for proton radiotherapy with research and educational purposes.

    Science.gov (United States)

    Sánchez-Parcerisa, D; Kondrla, M; Shaindlin, A; Carabe, A

    2014-12-07

    FoCa is an in-house modular treatment planning system, developed entirely in MATLAB, which includes forward dose calculation of proton radiotherapy plans in both active and passive modalities as well as a generic optimization suite for inverse treatment planning. The software has a dual education and research purpose. From the educational point of view, it can be an invaluable teaching tool for educating medical physicists, showing the insights of a treatment planning system from a well-known and widely accessible software platform. From the research point of view, its current and potential uses range from the fast calculation of any physical, radiobiological or clinical quantity in a patient CT geometry, to the development of new treatment modalities not yet available in commercial treatment planning systems. The physical models in FoCa were compared with the commissioning data from our institution and show an excellent agreement in depth dose distributions and longitudinal and transversal fluence profiles for both passive scattering and active scanning modalities. 3D dose distributions in phantom and patient geometries were compared with a commercial treatment planning system, yielding a gamma-index pass rate of above 94% (using FoCa's most accurate algorithm) for all cases considered. Finally, the inverse treatment planning suite was used to produce the first prototype of intensity-modulated, passive-scattered proton therapy, using 13 passive scattering proton fields and multi-leaf modulation to produce a concave dose distribution on a cylindrical solid water phantom without any field-specific compensator.

  12. Incorrect dosimetric leaf separation in IMRT and VMAT treatment planning

    DEFF Research Database (Denmark)

    Sjölin, Maria; Edmund, Jens Morgenthaler

    2016-01-01

    PURPOSE: Dynamic treatment planning algorithms use a dosimetric leaf separation (DLS) parameter to model the multi-leaf collimator (MLC) characteristics. Here, we quantify the dosimetric impact of an incorrect DLS parameter and investigate whether common pretreatment quality assurance (QA) methods...... can detect this effect. METHODS: 16 treatment plans with intensity modulated radiation therapy (IMRT) or volumetric modulated arc therapy (VMAT) technique for multiple treatment sites were calculated with a correct and incorrect setting of the DLS, corresponding to a MLC gap difference of 0.5mm...

  13. METROSIM: Metroplex-Wide Flight Planning and Optimization Project

    Data.gov (United States)

    National Aeronautics and Space Administration — The key innovation of this effort is the development of a Metroplex-based arrival, departure, and surface optimization system which we call MetroSim. Linking with...

  14. METROSIM: Metroplex-Wide Flight Planning and Optimization Project

    Data.gov (United States)

    National Aeronautics and Space Administration — MetroSim is a Metroplex-based arrival, departure, and surface optimization. Linking with both the NASA-developed Traffic Management Advisor (TMA) tool as well as the...

  15. Optimization-based decision support systems for planning problems in processing industries

    NARCIS (Netherlands)

    Claassen, G.D.H.

    2014-01-01

    Summary Optimization-based decision support systems for planning problems in processing industries Nowadays, efficient planning of material flows within and between supply chains is of vital importance and has become one of the most challenging problems for decision support in practice. The

  16. Optimization-based decision support systems for planning problems in processing industries

    NARCIS (Netherlands)

    Claassen, G.D.H.

    2014-01-01

    Summary Optimization-based decision support systems for planning problems in processing industries Nowadays, efficient planning of material flows within and between supply chains is of vital importance and has become one of the most challenging problems for decision support in practice. The tremendo

  17. Optimization-based decision support systems for planning problems in processing industries

    NARCIS (Netherlands)

    Claassen, G.D.H.

    2014-01-01

    Summary Optimization-based decision support systems for planning problems in processing industries Nowadays, efficient planning of material flows within and between supply chains is of vital importance and has become one of the most challenging problems for decision support in practice. The tremendo

  18. Reliability-Based Optimal Design of Experiment Plans for Offshore Structures

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard; Faber, M. H.; Kroon, I. B.

    1993-01-01

    Design of cost optimal experiment plans on the basis of a preposterior analysis is discussed. In particular the planning of on-site response measurements on offshore structures in order to update probabilistic models for fatigue life estimation is addressed. Special emphasis is given to modelling...

  19. [Clinical laboratory approaches to parodontitis treatment optimization].

    Science.gov (United States)

    Soboleva, L A; Shul'diakov, A A; Oseeva, A O; Aleksandrova, E A

    2010-01-01

    In order to determine cycloferon liniment clinical-pathogenetic efficacy in comprehensive parodontitis therapy examination and treatment of 80 patients was done. It was determined that the cycloferon liniment use in comprehensive treatment of patients with parodontitis let to reduce infectious load in parodontal pockets and local inflammation intensity, to normalize the secretory immunoglobulin level and immune status indices that provided speed up of healing process and reduction relapse frequency.

  20. Plan quality and treatment planning technique for single isocenter cranial radiosurgery with volumetric modulated arc therapy.

    Science.gov (United States)

    Clark, Grant M; Popple, Richard A; Prendergast, Brendan M; Spencer, Sharon A; Thomas, Evan M; Stewart, John G; Guthrie, Barton L; Markert, James M; Fiveash, John B

    2012-01-01

    To demonstrate plan quality and provide a practical, systematic approach to the treatment planning technique for single isocenter cranial radiosurgery with volumetric modulated arc therapy (VMAT; RapidArc, Varian Medical systems, Palo Alto, CA). Fifteen patients with 1 or more brain metastases underwent single isocenter VMAT radiosurgery. All plans were normalized to deliver 100% of the prescription dose to 99%-100% of the target volume. All targets per plan were treated to the same dose. Plans were created with dose control tuning structures surrounding targets to maximize conformity and dose gradient. Plan quality was evaluated by calculation of conformity index (CI = 100% isodose volume/target volume) and homogeneity index (HI = maximum dose/prescription dose) scores for each target and a Paddick gradient index (GI = 50% isodose volume/100% isodose volume) score for each plan. The median number of targets per patient was 2 (range, 1-5). The median number of non-coplanar arcs utilized per plan was 2 (range, 1- 4). Single target plans were created with 1 or 2 non-coplanar arcs while multitarget plans utilized 2 to 4 non-coplanar arcs. Prescription doses ranged from 5-16 Gy in 1-5 fractions. The mean conformity index was 1.12 (± SD, 0.13) and the mean HI was 1.44 (± SD, 0.11) for all targets. The mean GI per plan was 3.34 (± SD, 0.42). We have outlined a practical approach to cranial radiosurgery treatment planning using the single isocenter VMAT platform. One or 2 arc single isocenter plans are often adequate for treatment of single targets, while 2-4 arcs may be more advantageous for multiple targets. Given the high plan quality and extreme clinical efficiency, this single isocenter VMAT approach will continue to become more prevalent for linac-based radiosurgical treatment of 1 or more intracranial targets and will likely replace multiple isocenter techniques. Copyright © 2012 American Society for Radiation Oncology. Published by Elsevier Inc. All rights

  1. Orthovoltage radiation therapy treatment planning using Monte Carlo simulation: treatment of neuroendocrine carcinoma of the maxillary sinus

    Science.gov (United States)

    Gao, Wanbao; Raeside, David E.

    1997-12-01

    Dose distributions that result from treating a patient with orthovoltage beams are best determined with a treatment planning system that uses the Monte Carlo method, and such systems are not readily available. In the present work, the Monte Carlo method was used to develop a computer code for determining absorbed dose distributions in orthovoltage radiation therapy. The code was used in planning treatment of a patient with a neuroendocrine carcinoma of the maxillary sinus. Two lateral high-energy photon beams supplemented by an anterior orthovoltage photon beam were utilized in the treatment plan. For the clinical case and radiation beams considered, a reasonably uniform dose distribution TOP"/> is achieved within the target volume, while the dose to the lens of each eye is 4 - 8% of the prescribed dose. Therefore, an orthovoltage photon beam, when properly filtered and optimally combined with megavoltage beams, can be effective in the treatment of cancers below the skin, providing that accurate treatment planning is carried out to establish with accuracy and precision the doses to critical structures.

  2. A Hybrid Analytical/Simulation Modeling Approach for Planning and Optimizing Mass Tactical Airborne Operations

    Science.gov (United States)

    1995-05-01

    A HYBRID ANALYTICAL/ SIMULATION MODELING APPROACH FOR PLANNING AND OPTIMIZING MASS TACTICAL AIRBORNE OPERATIONS by DAVID DOUGLAS BRIGGS M.S.B.A...COVERED MAY 1995 TECHNICAL REPORT THESIS 4. TITLE AND SUBTITLE 5. FUNDING NUMBERS A HYBRID ANALYTICAL SIMULATION MODELING APPROACH FOR PLANNING AND...are present. Thus, simulation modeling presents itself as an excellent alternate tool for planning because it allows for the modeling of highly complex

  3. WE-F-BRB-00: New Developments in Knowledge-Based Treatment Planning and Automation

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2015-06-15

    Advancements in informatics in radiotherapy are opening up opportunities to improve our ability to assess treatment plans. Models on individualizing patient dose constraints from prior patient data and shape relationships have been extensively researched and are now making their way into commercial products. New developments in knowledge based treatment planning involve understanding the impact of the radiation dosimetry on the patient. Akin to radiobiology models that have driven intensity modulated radiotherapy optimization, toxicity and outcome predictions based on treatment plans and prior patient experiences may be the next step in knowledge based planning. In order to realize these predictions, it is necessary to understand how the clinical information can be captured, structured and organized with ontologies and databases designed for recall. Large databases containing radiation dosimetry and outcomes present the opportunity to evaluate treatment plans against predictions of toxicity and disease response. Such evaluations can be based on dose volume histogram or even the full 3-dimensional dose distribution and its relation to the critical anatomy. This session will provide an understanding of ontologies and standard terminologies used to capture clinical knowledge into structured databases; How data can be organized and accessed to utilize the knowledge in planning; and examples of research and clinical efforts to incorporate that clinical knowledge into planning for improved care for our patients. Learning Objectives: Understand the role of standard terminologies, ontologies and data organization in oncology Understand methods to capture clinical toxicity and outcomes in a clinical setting Understand opportunities to learn from clinical data and its application to treatment planning Todd McNutt receives funding from Philips, Elekta and Toshiba for some of the work presented.

  4. SU-D-BRD-03: Improving Plan Quality with Automation of Treatment Plan Checks

    Energy Technology Data Exchange (ETDEWEB)

    Covington, E; Younge, K; Chen, X; Lee, C; Matuszak, M; Kessler, M; Acosta, E; Orow, A; Filpansick, S; Moran, J [University of Michigan Hospital and Health System, Ann Arbor, MI (United States); Keranen, W [Varian Medical Systems, Palo Alto, CA (United States)

    2015-06-15

    Purpose: To evaluate the effectiveness of an automated plan check tool to improve first-time plan quality as well as standardize and document performance of physics plan checks. Methods: The Plan Checker Tool (PCT) uses the Eclipse Scripting API to check and compare data from the treatment planning system (TPS) and treatment management system (TMS). PCT was created to improve first-time plan quality, reduce patient delays, increase efficiency of our electronic workflow, and to standardize and partially automate plan checks in the TPS. A framework was developed which can be configured with different reference values and types of checks. One example is the prescribed dose check where PCT flags the user when the planned dose and the prescribed dose disagree. PCT includes a comprehensive checklist of automated and manual checks that are documented when performed by the user. A PDF report is created and automatically uploaded into the TMS. Prior to and during PCT development, errors caught during plan checks and also patient delays were tracked in order to prioritize which checks should be automated. The most common and significant errors were determined. Results: Nineteen of 33 checklist items were automated with data extracted with the PCT. These include checks for prescription, reference point and machine scheduling errors which are three of the top six causes of patient delays related to physics and dosimetry. Since the clinical roll-out, no delays have been due to errors that are automatically flagged by the PCT. Development continues to automate the remaining checks. Conclusion: With PCT, 57% of the physics plan checklist has been partially or fully automated. Treatment delays have declined since release of the PCT for clinical use. By tracking delays and errors, we have been able to measure the effectiveness of automating checks and are using this information to prioritize future development. This project was supported in part by P01CA059827.

  5. Solid Mesh Registration for Radiotherapy Treatment Planning

    DEFF Research Database (Denmark)

    Noe, Karsten Østergaard; Sørensen, Thomas Sangild

    2010-01-01

    We present an algorithm for solid organ registration of pre-segmented data represented as tetrahedral meshes. Registration of the organ surface is driven by force terms based on a distance field representation of the source and reference shapes. Registration of internal morphology is achieved usi...... to complete. The proposed method has many potential uses in image guided radiotherapy (IGRT) which relies on registration to account for organ deformation between treatment sessions....

  6. A planning study investigating dual-gated volumetric arc stereotactic treatment of primary renal cell carcinoma

    Energy Technology Data Exchange (ETDEWEB)

    Devereux, Thomas, E-mail: thomas.devereux@petermac.org [Radiation Therapy Services, Peter MacCallum Cancer Centre, Melbourne (Australia); Pham, Daniel [Radiation Therapy Services, Peter MacCallum Cancer Centre, Melbourne (Australia); Kron, Tomas [Department of Physical Sciences, Peter MacCallum Cancer Centre, Melbourne (Australia); Sir Peter MacCallum Department of Oncology, Melbourne University, Melbourne (Australia); Foroudi, Farshad [Sir Peter MacCallum Department of Oncology, Melbourne University, Melbourne (Australia); Radiation Oncology and Cancer Imaging, Peter MacCallum Cancer Centre, Melbourne (Australia); Supple, Jeremy [School of Applied Sciences, Royal Melbourne Institute of Technology, Melbourne (Australia); Siva, Shankar [Sir Peter MacCallum Department of Oncology, Melbourne University, Melbourne (Australia); Radiation Oncology and Cancer Imaging, Peter MacCallum Cancer Centre, Melbourne (Australia)

    2015-04-01

    This is a planning study investigating the dosimetric advantages of gated volumetric-modulated arc therapy (VMAT) to the end-exhale and end-inhale breathing phases for patients undergoing stereotactic treatment of primary renal cell carcinoma. VMAT plans were developed from the end-inhale (VMATinh) and the end-exhale (VMATexh) phases of the breathing cycle as well as a VMAT plan and 3-dimensional conformal radiation therapy plan based on an internal target volume (ITV) (VMATitv). An additional VMAT plan was created by giving the respective gated VMAT plan a 50% weighting and summing the inhale and exhale plans together to create a summed gated plan. Dose to organs at risk (OARs) as well as comparison of intermediate and low-dose conformity was evaluated. There was no difference in the volume of healthy tissue receiving the prescribed dose for the planned target volume (PTV) (CI100%) for all the VMAT plans; however, the mean volume of healthy tissue receiving 50% of the prescribed dose for the PTV (CI50%) values were 4.7 (± 0.2), 4.6 (± 0.2), and 4.7 (± 0.6) for the VMATitv, VMATinh, and VMATexh plans, respectively. The VMAT plans based on the exhale and inhale breathing phases showed a 4.8% and 2.4% reduction in dose to 30 cm{sup 3} of the small bowel, respectively, compared with that of the ITV-based VMAT plan. The summed gated VMAT plans showed a 6.2% reduction in dose to 30 cm{sup 3} of the small bowel compared with that of the VMAT plans based on the ITV. Additionally, when compared with the inhale and the exhale VMAT plans, a 4% and 1.5%, respectively, reduction was observed. Gating VMAT was able to reduce the amount of prescribed, intermediate, and integral dose to healthy tissue when compared with VMAT plans based on an ITV. When summing the inhale and exhale plans together, dose to healthy tissue and OARs was optimized. However, gating VMAT plans would take longer to treat and is a factor that needs to be considered.

  7. INDUSTRIAL ENTERPRISE TAX PLANNING AS PART OF EXPENSE OPTIMIZATION STRATEGY

    Directory of Open Access Journals (Sweden)

    A. P. Garnov

    2012-01-01

    Full Text Available Tax liability planning is vital for industrial enterprises to reduce their tax burden and thus reduce expenses of the organization for a certain period. Industrial enterprises are among main taxpayers in the Russian Federation, and recommendations given in the article on topical issues related to planning of tax obligations will help top managers of the enterprises to avoid unnecessary financial losses and to ensure further growth and development of their organizations. Attention is focused on specifics of the industrial enterprises’ activities under present conditions due to the nature and particular features of their operation.

  8. INDUSTRIAL ENTERPRISE TAX PLANNING AS PART OF EXPENSE OPTIMIZATION STRATEGY

    Directory of Open Access Journals (Sweden)

    A. P. Garnov

    2012-01-01

    Full Text Available Tax liability planning is vital for industrial enterprises to reduce their tax burden and thus reduce expenses of the organization for a certain period. Industrial enterprises are among main taxpayers in the Russian Federation, and recommendations given in the article on topical issues relatedto planning of tax obligations will help top managers of the enterprises to avoid unnecessary financial losses and to ensure further growth and development of their organizations. Attention is focused on specifics of the industrial enterprises’ activities under present conditions due to thenature and particular features of their operation.

  9. Optimization of the Actuarial Model of Defined Contribution Pension Plan

    Directory of Open Access Journals (Sweden)

    Yan Li

    2014-01-01

    Full Text Available The paper focuses on the actuarial models of defined contribution pension plan. Through assumptions and calculations, the expected replacement ratios of three different defined contribution pension plans are compared. Specially, more significant considerable factors are put forward in the further cost and risk analyses. In order to get an assessment of current status, the paper finds a relationship between the replacement ratio and the pension investment rate using econometrics method. Based on an appropriate investment rate of 6%, an expected replacement ratio of 20% is reached.

  10. Optimal Risk-Based Inspection Planning for Offshore Wind Turbines

    DEFF Research Database (Denmark)

    Rangel-Ramirez, Jose G.; Sørensen, John Dalsgaard

    2008-01-01

    Wind turbines for electricity production have increased significantly the last years both in production capability and size. This development is expected to continue also in the coining years. The Support structure for offshore wind turbines is typically a steel structure consisting of a tower......, inspection and maintenance activities are developed. This paper considers aspects of inspection and maintenance planning of fatigue prone details in jacket and tripod types of wind turbine support structures. Based oil risk-based inspection planning methods used for oil & gas installations, a framework...

  11. Optimal Risk-Based Inspection Planning for Offshore Wind Turbines

    DEFF Research Database (Denmark)

    Ramírez, José G. Rangel; Sørensen, John Dalsgaard

    2008-01-01

    Wind turbines for electricity production have increased significantly the last years both in production capability and size. This development is expected to continue also in the coming years. The support structure for offshore wind turbines is typically a steel structure consisting of a tower......, inspection and maintenance activities are developed. This paper considers aspects of inspection and maintenance planning of fatigue prone details in jacket and tripod types of wind turbine support structures. Based on risk-based inspection planning methods used for oil & gas installations, a framework...

  12. Optimal Risk-Based Inspection Planning for Offshore Wind Turbines

    DEFF Research Database (Denmark)

    Ramírez, José G. Rangel; Sørensen, John Dalsgaard

    2008-01-01

    and monopile, tripod or jacket type foundation. Monopiles are at present the most typical foundation, but tripods and jackets are expected to be used in the future at larger water depths. The support structures are facing deterioration processes such as fatigue and corrosion. To ‘control' this deterioration......, inspection and maintenance activities are developed. This paper considers aspects of inspection and maintenance planning of fatigue prone details in jacket and tripod types of wind turbine support structures. Based on risk-based inspection planning methods used for oil & gas installations, a framework...

  13. Initial application of digital tomosynthesis to improve brachytherapy treatment planning

    Science.gov (United States)

    Baydush, Alan H.; Mirzaei McKee, Mahta; King, June; Godfrey, Devon J.

    2007-03-01

    We present preliminary investigations that examine the feasibility of incorporating volumetric images generated using digital tomosynthesis into brachytherapy treatment planning. The Integrated Brachytherapy Unit (IBU) at our facility consists of an L-arm, C-arm isocentric motion system with an x-ray tube and fluoroscopic imager attached. Clinically, this unit is used to generate oblique, anterior-posterior, and lateral images for simple treatment planning and dose prescriptions. Oncologists would strongly prefer to have volumetric data to better determine three dimensional dose distributions (dose-volume histograms) to the target area and organs at risk. Moving the patient back and forth to CT causes undo stress on the patient, allows extensive motion of organs and treatment applicators, and adds additional time to patient treatment. We propose to use the IBU imaging system with digital tomosynthesis to generate volumetric patient data, which can be used for improving treatment planning and overall reducing treatment time. Initial image data sets will be acquired over a limited arc of a human-like phantom composed of real bones and tissue equivalent material. A brachytherapy applicator will be incorporated into one of the phantoms for visualization purposes. Digital tomosynthesis will be used to generate a volumetric image of this phantom setup. This volumetric image set will be visually inspected to determine the feasibility of future incorporation of these types of images into brachytherapy treatment planning. We conclude that initial images using the tomosynthesis reconstruction technique show much promise and bode well for future work.

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

    Science.gov (United States)

    2015-09-30

    Optimal Planning Systems (NASCar-OPS) Dr. Pierre F.J. Lermusiaux Department of Mechanical Engineering Center for Ocean Science and Engineering... system design and for adaptive sampling during sea operations , using advanced Bayesian information theoretic approaches - Improve the understanding of...modeling, both for real-time sea operations and for optimized re-analyses - Collaborate and transfer data, expertise, approaches, algorithms and

  15. Integrated production-distribution planning optimization models: A review in collaborative networks context

    Directory of Open Access Journals (Sweden)

    Beatriz Andres

    2017-01-01

    Full Text Available Researchers in the area of collaborative networks are more and more aware of proposing collaborative approaches to address planning processes, due to the advantages associated when enterprises perform integrated planning models. Collaborative production-distribution planning, among the supply network actors, is considered a proper mechanism to support enterprises on dealing with uncertainties and dynamicity associated to the current markets. Enterprises, and especially SMEs, should be able to overcome the continuous changes of the market by increasing their agility. Carrying out collaborative planning allows enterprises to enhance their readiness and agility for facing the market turbulences. However, SMEs have limited access when incorporating optimization tools to deal with collaborative planning, reducing their ability to respond to the competition. The problem to solve is to provide SMEs affordable solutions to support collaborative planning. In this regard, new optimisation algorithms are required in order to improve the collaboration within the supply network partners. As part of the H2020 Cloud Collaborative Manufacturing Networks (C2NET research project, this paper presents a study on integrated production and distribution plans. The main objective of the research is to identify gaps in current optimization models, proposed to address integrated planning, taking into account the requirements and needs of the industry. Thus, the needs of the companies belonging to the industrial pilots, defined in the C2NET project, are identified; analysing how these needs are covered by the optimization models proposed in the literature, to deal with the integrated production-distribution planning.

  16. An optimal setup planning selection approach in a complex product machining process

    Science.gov (United States)

    Zhu, Fang

    2011-10-01

    Setup planning has very important influence on the product quality in a Complex Product Machining Process (CPMP). Part production in a CPMP involves multiple setup plans, which will lead into variation propagation and lead to extreme complexity in final product quality. Current approaches of setup planning in a CPMP are experience-based that lead to adopt higher machining process cost to ensure the final product quality, and most approaches are used for a single machining process. This work attempts to solve those challenging problems and aims to develop a method to obtain an optimal setup planning in a CPMP, which can satisfies the quality specifications and minimizes the expected value of the sum of machining costs. To this end, a machining process model is established to describe the variation propagation effect of setup plan throughout all stages in a CPMP firstly and then a quantitative setup plan evaluation methods driven by cost constraint is proposed to clarify what is optimality of setup plans. Based on the above procedures, an optimal setup planning is obtained through a dynamic programming solver. At last, a case study is provided to illustrate the validity and the significance of the proposed setup planning selective method.

  17. Global optimal path planning for mobile robot based on improved Dijkstra algorithm and ant system algorithm

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    A novel method of global optimal path planning for mobile robot was proposed based on the improved Dijkstra algorithm and ant system algorithm. This method includes three steps: the first step is adopting the MAKLINK graph theory to establish the free space model of the mobile robot, the second step is adopting the improved Dijkstra algorithm to find out a sub-optimal collision-free path, and the third step is using the ant system algorithm to adjust and optimize the location of the sub-optimal path so as to generate the global optimal path for the mobile robot. The computer simulation experiment was carried out and the results show that this method is correct and effective. The comparison of the results confirms that the proposed method is better than the hybrid genetic algorithm in the global optimal path planning.

  18. Fast Generation of Near-Optimal Plans for Eco-Efficient Stowage of Large Container Vessels

    DEFF Research Database (Denmark)

    Pacino, Dario; Delgado, Alberto; Jensen, Rune Møller

    2011-01-01

    Eco-efficient stowage plans that are both competitive and sustainable have become a priority for the shipping industry. Stowage planning is NP-hard and is a challenging optimization problem in practice. We propose a new 2-phase approach that generates near-optimal stowage plans and fulfills indus...... industrial time and quality requirements. Our approach combines an integer programming model for assigning groups of containers to storage areas of the vessel over multiple ports, and a constraint programming and local search procedure for stowing individual containers....

  19. Application of Taboo Search and Genetic Algorithm in planning and optimization of UMTS radio networks

    OpenAIRE

    Jalili, B; Dianati, M.

    2010-01-01

    Planning and optimization of 3G networks is more than just frequency allocation and coverage planning, due to the nature of WCDMA coding. It usually involves solution of an NP-Hard problem. In this paper we propose an effective method for optimizing the Common Pilot Channel (CPICH) transmit power, along with maximizing the number of served users and minimizing the number of cell sites and compare use of two meta-heuristic methods: Taboo Search (TS) and Genetic Algorithm (GA) in planning and o...

  20. Fast Generation of Near-Optimal Plans for Eco-Efficient Stowage of Large Container Vessels

    DEFF Research Database (Denmark)

    Pacino, Dario; Jensen, Rune Møller; Delgado-Ortegon, Alberto

    2011-01-01

    Eco-Efficient stowage plans that are both competitive and sustainable have become a priority for the shipping industry. Stowage planning is NP-hard and is a challenging optimization problem in practice. We propose a new 2-phase approach that generates near-optimal stowage plans and fulfills indus...... industrial time and quality requirements. Our approach combines an integer programming model for assigning groups of containers to storage areas of the vessel over multiple ports, and a constraint programming and local search procedure for stowing individual containers....

  1. Economic optimization of waste treatment and energy production in Denmark

    DEFF Research Database (Denmark)

    Münster, Marie; Ravn, Hans; Hedegaard, Karsten

    2013-01-01

    This article presents an optimization model that incorporates LCA methodology and captures important characteristics of waste management systems. The most attractive waste management options are in the model identified as part the optimization. The model renders it possible to apply different...... optimization objectives such as minimizing costs or greenhouse gas emissions or to prioritise several objectives given different weights. An illustrative case is analyzed, covering alternative treatments of 1 tonne residual household waste: incineration of the full amount or sorting out organic waste...... shows that it is feasible to combine LCA approaches with optimization and highlights the need for including the integrated waste and energy system into the model....

  2. Integrated Multidisciplinary Optimization of Rotorcraft: A Plan for Development

    Science.gov (United States)

    1989-05-01

    that of thickness noise, strongest in the rotor plane. Although observed experimentally, due to nonlinear transonic effects, this source is not as well...frequencies. The plan for validating the components of the design process was described and the strategy for overall validation of the design methology was

  3. Wildlife Conservation Planning Using Stochastic Optimization and Importance Sampling

    Science.gov (United States)

    Robert G. Haight; Laurel E. Travis

    1997-01-01

    Formulations for determining conservation plans for sensitive wildlife species must account for economic costs of habitat protection and uncertainties about how wildlife populations will respond. This paper describes such a formulation and addresses the computational challenge of solving it. The problem is to determine the cost-efficient level of habitat protection...

  4. Sampling and Analysis Plan - Waste Treatment Plant Seismic Boreholes Project

    Energy Technology Data Exchange (ETDEWEB)

    Reidel, Steve P.

    2006-05-26

    This sampling and analysis plan (SAP) describes planned data collection activities for four entry boreholes through the sediment overlying the basalt, up to three new deep rotary boreholes through the basalt and sedimentary interbeds, and one corehole through the basalt and sedimentary interbeds at the Waste Treatment Plant (WTP) site. The SAP will be used in concert with the quality assurance plan for the project to guide the procedure development and data collection activities needed to support borehole drilling, geophysical measurements, and sampling. This SAP identifies the American Society of Testing Materials standards, Hanford Site procedures, and other guidance to be followed for data collection activities.

  5. Optimal vaccination and treatment of an epidemic network model

    Science.gov (United States)

    Chen, Lijuan; Sun, Jitao

    2014-08-01

    In this Letter, we firstly propose an epidemic network model incorporating two controls which are vaccination and treatment. For the constant controls, by using Lyapunov function, global stability of the disease-free equilibrium and the endemic equilibrium of the model is investigated. For the non-constant controls, by using the optimal control strategy, we discuss an optimal strategy to minimize the total number of the infected and the cost associated with vaccination and treatment. Table 1 and Figs. 1-5 are presented to show the global stability and the efficiency of this optimal control.

  6. Optimization and Robustness in Planning and Scheduling Problems. Application to Container Terminals

    OpenAIRE

    Rodríguez Molins, Mario

    2015-01-01

    Despite the continuous evolution in computers and information technology, real-world combinatorial optimization problems are NP-problems, in particular in the domain of planning and scheduling. Thus, although exact techniques from the Operations Research (OR) field, such as Linear Programming, could be applied to solve optimization problems, they are difficult to apply in real-world scenarios since they usually require too much computational time, i.e: an optimized solution is ...

  7. Optimal planning of electric vehicle charging station at the distribution system using hybrid optimization algorithm

    DEFF Research Database (Denmark)

    Awasthi, Abhishek; Venkitusamy, Karthikeyan; Padmanaban, Sanjeevikumar

    2017-01-01

    , a hybrid algorithm based on genetic algorithm and improved version of conventional particle swarm optimization is utilized for finding optimal placement of charging station in the Allahabad distribution system. The particle swarm optimization algorithm re-optimizes the received sub-optimal solution (site...... and the size of the station) which leads to an improvement in the algorithm functionality and enhances quality of solution. The genetic algorithm and improved version of conventional particle swarm optimization algorithm will also be compared with a conventional genetic algorithm and particle swarm...... optimization. Through simulation studies on a real time system of Allahabad city, the superior performance of the aforementioned technique with respect to genetic algorithm and particle swarm optimization in terms of improvement in voltage profile and quality....

  8. Optimal treatment of anaphylaxis: antihistamines versus epinephrine.

    Science.gov (United States)

    Fineman, Stanley M

    2014-07-01

    Anaphylaxis is a rapid, systemic, often unanticipated, and potentially life-threatening immune reaction occurring after exposure to certain foreign substances. The main immunologic triggers include food, insect venom, and medications. Multiple immunologic pathways underlie anaphylaxis, but most involve immune activation and release of immunomodulators. Anaphylaxis can be difficult to recognize clinically, making differential diagnosis key. The incidence of anaphylaxis has at least doubled during the past few decades, and in the United States alone, an estimated 1500 fatalities are attributed to anaphylaxis annually. The increasing incidence and potentially life-threatening nature of anaphylaxis coupled with diagnostic challenges make appropriate and timely treatment critical. Epinephrine is universally recommended as the first-line therapy for anaphylaxis, and early treatment is critical to prevent a potentially fatal outcome. Despite the evidence and guideline recommendations supporting its use for anaphylaxis, epinephrine remains underused. Data indicate that antihistamines are more commonly used to treat patients with anaphylaxis. Although histamine is involved in anaphylaxis, treatment with antihistamines does not relieve or prevent all of the pathophysiological symptoms of anaphylaxis, including the more serious complications such as airway obstruction, hypotension, and shock. Additionally, antihistamines do not act as rapidly as epinephrine; maximal plasma concentrations are reached between 1 and 3 hours for antihistamines compared with < 10 minutes for intramuscular epinephrine injection. This demonstrates the need for improved approaches to educate physicians and patients regarding the appropriate treatment of anaphylaxis.

  9. Optimal Inspection Planning for Fatigue Damage of Offshore Structures

    DEFF Research Database (Denmark)

    Madsen, H.O.; Sørensen, John Dalsgaard; Olesen, R.

    1990-01-01

    A formulation of optimal design, inspection and maintenance against damage caused by fatigue crack growth is formulated. A stochastic model for fatigue crack growth based on linear elastic fracture mechanics Is applied. Failure is defined by crack growth beyond a critical crack size. The failure...... probability and associated sensitivity factors are computed by first-order reliability methods. Inspection reliability is included through a pod (probability of detection) curve. Optimization variables are structural design parameters, inspection times and qualities. The total expected cost of design......, inspection, repair and failure is minimized with a constraint on the life time reliability....

  10. Optimal vaccination and treatment of an epidemic network model

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Lijuan [Department of Mathematics, Tongji University, Shanghai 200092 (China); College of Mathematics and Computer Science, Fuzhou University, Fuzhou, Fujian 350002 (China); Sun, Jitao, E-mail: sunjt@sh163.net [Department of Mathematics, Tongji University, Shanghai 200092 (China)

    2014-08-22

    In this Letter, we firstly propose an epidemic network model incorporating two controls which are vaccination and treatment. For the constant controls, by using Lyapunov function, global stability of the disease-free equilibrium and the endemic equilibrium of the model is investigated. For the non-constant controls, by using the optimal control strategy, we discuss an optimal strategy to minimize the total number of the infected and the cost associated with vaccination and treatment. Table 1 and Figs. 1–5 are presented to show the global stability and the efficiency of this optimal control. - Highlights: • Propose an optimally controlled SIRS epidemic model on heterogeneous networks. • Obtain criteria of global stability of the disease-free equilibrium and the endemic equilibrium. • Investigate existence of optimal control for the control problem. • The results be illustrated by some numerical simulations.

  11. Solving complex maintenance planning optimization problems using stochastic simulation and multi-criteria fuzzy decision making

    Energy Technology Data Exchange (ETDEWEB)

    Tahvili, Sahar [Mälardalen University (Sweden); Österberg, Jonas; Silvestrov, Sergei [Division of Applied Mathematics, Mälardalen University (Sweden); Biteus, Jonas [Scania CV (Sweden)

    2014-12-10

    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 of a suggested framework model based on discrete event simulation.

  12. The impact of direct aperture optimization on plan quality and efficiency in complex head and neck IMRT

    Directory of Open Access Journals (Sweden)

    Sabatino Marcello

    2012-01-01

    Full Text Available Abstract Background Conventional step&shoot intensity modulated radio therapy (IMRT approaches potentially lead to treatment plans with high numbers of segments and monitor units (MU and, therefore, could be time consuming at the linear accelerator. Direct optimization methods are able to reduce the complexity without degrading the quality of the plan. The aim of this study is the evaluation of different IMRT approaches at standardized conditions for head and neck tumors. Method For 27 patients with carcinomas in the head and neck region a planning study with a 2-step-IMRT system (KonRad, a direct optimization system (Panther DAO and a mixture of both approaches (MasterPlan DSS was created. In order to avoid different prescription doses for boost volumes a simple standardization was realized. The dose was downscaled to 50 Gy to the planning target volume (PTV which included the primary tumor as well as the bilateral lymphatic drainage (cervical and supraclavicular. Dose restrictions for the organs at risk (OAR were downscaled to this prescription from high dose concepts up to 72 Gy. Those limits were defined as planning objectives while reaching definable PTV coverage with a standardized field setup. The parameters were evaluated from the corresponding dose volume histogram (DVH. Special attention was paid to the efficiency of the method, measured by means of calculated MU and required segments. Statistical tests of significance were applied to quantify the differences between the evaluated systems. Results PTV coverage for all systems in terms of V90% and V95% fell short of the requested 100% and 95%, respectively, but were still acceptable (range: 98.7% to 99.1% and 94.2% to 94.7%. Overall for OAR sparing and the burden of healthy tissue with low doses no technique was superior for all evaluated parameters. Differences were found for the number of segments where the direct optimization systems generated less segments. Lowest average numbers of

  13. Periodontal risk assessment, diagnosis and treatment planning.

    Science.gov (United States)

    Pihlstrom, B L

    2001-01-01

    The prevention and treatment of the periodontal diseases is based on accurate diagnosis, reduction or elimination of causative agents, risk management and correction of the harmful effects of disease. Prominent and confirmed risk factors or risk predictors for periodontitis in adults include smoking, diabetes, race, P. gingivalis, P. intermedia, low education, infrequent dental attendance and genetic influences. Several other specific periodontal bacteria, herpesviruses, increased age, male, sex, depression, race, traumatic occlusion and female osteoporosis in the presence of heavy dental calculus have been shown to be associated with loss of periodontal support and can be considered to be risk indicators of periodontitis. The presence of furcation involvement, tooth mobility, and a parafunctional habit without the use of a biteguard are associated with a poorer periodontal prognosis following periodontal therapy. An accurate diagnosis can only be made by a thorough evaluation of data that have been systematically collected by: 1) patient interview, 2) medical consultation as indicated, 3) clinical periodontal examination, 4) radiographic examination, and 5) laboratory tests as needed. Clinical signs of periodontal disease such as pocket depth, loss of clinical attachment and bone loss are cumulative measures of past disease. They do not provide the dentist with a current assessment of disease activity. In an attempt to improve the ability to predict future disease progression, several types of diagnostic tests have been studied, including host inflammatory products and mediators, enzymes, tissue breakdown products and subgingival temperature. In general, the usefulness of these tests for predicting future disease activity remains to be established in terms of sensitivity, specificity and predictive value. Although microbiological analysis of subgingival plaque is not necessary to diagnose and treat most patients with periodontitis, it is helpful when treating

  14. A Multi-pipe Path Planning by Modified Ant Colony Optimization

    Institute of Scientific and Technical Information of China (English)

    QU Yan-feng; JIANG Dan; LIU Bin

    2011-01-01

    Path planning in 3D geometry space is used to find an optimal path in the restricted environment, according to a certain evaluation criteria. To solve the problem of long searching time and slow solving speed in 3D path planning, a modified ant colony optimization is proposed in this paper. Firstly, the grid method for environment modeling is adopted. Heuristic information is connected with the planning space. A semi-iterative global pheromone update mechanism is proposed. Secondly, the optimal ants mutate the paths to improve the diversity of the algorithm after a defined iterative number. Thirdly, co-evolutionary algorithm is used. Finally, the simulation result shows the effectiveness of the proposed algorithm in solving the problem of 3D pipe path planning.

  15. Optimal Trajectory Planning and Coordinated Tracking Control Method of Tethered Space Robot Based on Velocity Impulse

    Directory of Open Access Journals (Sweden)

    Panfeng Huang

    2014-09-01

    Full Text Available The tethered space robot (TSR is a new concept of space robot which consists of a robot platform, space tether and operation robot. This paper presents a multi-objective optimal trajectory planning and a coordinated tracking control scheme for TSR based on velocity impulse in the approaching phase. Both total velocity impulse and flight time are included in this optimization. The non-dominated sorting genetic algorithm is employed to obtain the optimal trajectory Pareto solution using the TSR dynamic model and optimal trajectory planning model. The coordinated tracking control scheme utilizes optimal velocity impulse. Furthermore, the PID controller is designed in order to compensate for the distance measurement errors. The PID control force is optimized and distributed to thrusters and the space tether using a simulated annealing algorithm. The attitude interferential torque of the space tether is compensated a using time-delay algorithm through reaction wheels. The simulation results show that the multi-objective optimal trajectory planning method can reveal the relationships among flight time, fuel consumption, planar view angle and velocity impulse number. This method can provide a series of optimal trajectory according to a number of special tasks. The coordinated control scheme can significantly save thruster fuel for tracking the optimal trajectory, restrain the attitude interferential torque produced by space tether and maintain the relative attitude stability of the operation robot.

  16. MINERVA - a multi-modal radiation treatment planning system

    Energy Technology Data Exchange (ETDEWEB)

    Wemple, C.A. E-mail: cew@enel.gov; Wessol, D.E.; Nigg, D.W.; Cogliati, J.J.; Milvich, M.L.; Frederickson, C.; Perkins, M.; Harkin, G.J

    2004-11-01

    Researchers at the Idaho National Engineering and Environmental Laboratory and Montana State University have undertaken development of MINERVA, a patient-centric, multi-modal, radiation treatment planning system. This system can be used for planning and analyzing several radiotherapy modalities, either singly or combined, using common modality independent image and geometry construction and dose reporting and guiding. It employs an integrated, lightweight plugin architecture to accommodate multi-modal treatment planning using standard interface components. The MINERVA design also facilitates the future integration of improved planning technologies. The code is being developed with the Java Virtual Machine for interoperability. A full computation path has been established for molecular targeted radiotherapy treatment planning, with the associated transport plugin developed by researchers at the Lawrence Livermore National Laboratory. Development of the neutron transport plugin module is proceeding rapidly, with completion expected later this year. Future development efforts will include development of deformable registration methods, improved segmentation methods for patient model definition, and three-dimensional visualization of the patient images, geometry, and dose data. Transport and source plugins will be created for additional treatment modalities, including brachytherapy, external beam proton radiotherapy, and the EGSnrc/BEAMnrc codes for external beam photon and electron radiotherapy.

  17. Maximizing the probability of satisfying the clinical goals in radiation therapy treatment planning under setup uncertainty

    Energy Technology Data Exchange (ETDEWEB)

    Fredriksson, Albin, E-mail: albin.fredriksson@raysearchlabs.com; Hårdemark, Björn [RaySearch Laboratories, Sveavägen 44, Stockholm SE-111 34 (Sweden); Forsgren, Anders [Optimization and Systems Theory, Department of Mathematics, KTH Royal Institute of Technology, Stockholm SE-100 44 (Sweden)

    2015-07-15

    Purpose: This paper introduces a method that maximizes the probability of satisfying the clinical goals in intensity-modulated radiation therapy treatments subject to setup uncertainty. Methods: The authors perform robust optimization in which the clinical goals are constrained to be satisfied whenever the setup error falls within an uncertainty set. The shape of the uncertainty set is included as a variable in the optimization. The goal of the optimization is to modify the shape of the uncertainty set in order to maximize the probability that the setup error will fall within the modified set. Because the constraints enforce the clinical goals to be satisfied under all setup errors within the uncertainty set, this is equivalent to maximizing the probability of satisfying the clinical goals. This type of robust optimization is studied with respect to photon and proton therapy applied to a prostate case and compared to robust optimization using an a priori defined uncertainty set. Results: Slight reductions of the uncertainty sets resulted in plans that satisfied a larger number of clinical goals than optimization with respect to a priori defined uncertainty sets, both within the reduced uncertainty sets and within the a priori, nonreduced, uncertainty sets. For the prostate case, the plans taking reduced uncertainty sets into account satisfied 1.4 (photons) and 1.5 (protons) times as many clinical goals over the scenarios as the method taking a priori uncertainty sets into account. Conclusions: Reducing the uncertainty sets enabled the optimization to find better solutions with respect to the errors within the reduced as well as the nonreduced uncertainty sets and thereby achieve higher probability of satisfying the clinical goals. This shows that asking for a little less in the optimization sometimes leads to better overall plan quality.

  18. SU-E-T-437: Four-Dimensional Treatment Planning for Lung VMAT-SBRT

    Energy Technology Data Exchange (ETDEWEB)

    Hashimoto, M; Takashina, M; Koizumi, M [Osaka University, Suita, Osaka (Japan); Oohira, S; Ueda, Y; Miyazaki, M; Isono, M; Masaoka, A; Teshima, T [Osaka Medical Center for Cancer and Cardiovascular Diseases, Osaka-shi, Osaka (Japan)

    2015-06-15

    Purpose: To assess optimal treatment planning approach of Volumetric Modulated Arc Therapy for lung Stereotactic Body Radiation Therapy (VMAT-SBRT). Methods: Subjects were 10 patients with lung cancer who had undergone 4DCT. The internal target volume (ITV) volume ranged from 2.6 to 16.5cm{sup 3} and the tumor motion ranged from 0 to 2cm. From 4DCT, which was binned into 10 respiratory phases, 4 image data sets were created; maximum intensity projection (MIP), average intensity projection (AIP), AIP with the ITV replaced by 0HU (RITV-AIP) and RITV-AIP with the planning target volume (PTV) minus the internal target volume was set to −200 HU (HR-AIP). VMAT-SBRT plans were generated on each image set for a patient. 48Gy was prescribed to 95% of PTV. The plans were recalculated on all phase images of 4DCT and the dose distributions were accumulated using a deformable image registration software MIM Maestro™ as the 4D calculated dose to the gross tumor volume (GTV). The planned dose to the ITV and 4D calculated dose to the GTV were compared. Results: In AIP plan, 10 patients average of all dose parameters (D1%, D-mean, and D99%) discrepancy were 1Gy or smaller. MIP and RITV-AIP plans resulted in having common tendency and larger discrepancy than AIP plan. The 4D dose was lower than the planned dose, and 10 patients average of all dose parameters discrepancy were in range 1.3 to 2.6Gy. HR-AIP plan had the largest discrepancy in our trials. 4D calculated D1%, D-mean, and D99% were resulted in 3.0, 4.1, and 6.1Gy lower than the expected in plan, respectively. Conclusion: For all patients, the dose parameters expected in AIP plan approximated to 4D calculated. Using AIP image set seems optimal treatment planning approach of VMAT-SBRT for a mobile tumor. Funding Support: This work was supported by the Japan Society for the Promotion of Science Core-to-Core program (No. 23003)

  19. Optimal motion planning of an underactuated spacecraft using wavelet approximate method

    Institute of Scientific and Technical Information of China (English)

    GE Xinsheng; CHEN Liqun; LIU Yanzhu

    2006-01-01

    An optimal motion planning scheme using wavelet approximation is proposed for an underactuated spacecraft. The motion planning of an underactuated spacecraft can be formulated as an optimal control of a drift-free system. A cost functional is used to incorporate the control energy and the final state errors. The motion planning is to determine control inputs to minimize the cost functional.Using the method of wavelet, one can transform an infinite-dimensional optimal control problem to a finite-dimensional one and use GaussNewton algorithm to solve it for a feasible trajectory which satisfies nonholonomic constraints. The proposed scheme has been applied to a rigid spacecraft with two momentum wheels. The numerical simulation results indicate that optimal control with wavelet approximation is an effective approach to steering an underactuated spacecraft system from the initial configuration to the final configuration.

  20. Optimization of wastewater treatment plant operation for greenhouse gas mitigation.

    Science.gov (United States)

    Kim, Dongwook; Bowen, James D; Ozelkan, Ertunga C

    2015-11-01

    This study deals with the determination of optimal operation of a wastewater treatment system for minimizing greenhouse gas emissions, operating costs, and pollution loads in the effluent. To do this, an integrated performance index that includes three objectives was established to assess system performance. The ASMN_G model was used to perform system optimization aimed at determining a set of operational parameters that can satisfy three different objectives. The complex nonlinear optimization problem was simulated using the Nelder-Mead Simplex optimization algorithm. A sensitivity analysis was performed to identify influential operational parameters on system performance. The results obtained from the optimization simulations for six scenarios demonstrated that there are apparent trade-offs among the three conflicting objectives. The best optimized system simultaneously reduced greenhouse gas emissions by 31%, reduced operating cost by 11%, and improved effluent quality by 2% compared to the base case operation.

  1. TH-A-9A-04: Incorporating Liver Functionality in Radiation Therapy Treatment Planning

    Energy Technology Data Exchange (ETDEWEB)

    Wu, V; Epelman, M; Feng, M; Cao, Y; Wang, H; Romeijn, E; Matuszak, M [University of Michigan, Ann Arbor, MI (United States)

    2014-06-15

    Purpose: Liver SBRT patients have both variable pretreatment liver function (e.g., due to degree of cirrhosis and/or prior treatments) and sensitivity to radiation, leading to high variability in potential liver toxicity with similar doses. This work aims to explicitly incorporate liver perfusion into treatment planning to redistribute dose to preserve well-functioning areas without compromising target coverage. Methods: Voxel-based liver perfusion, a measure of functionality, was computed from dynamic contrast-enhanced MRI. Two optimization models with different cost functions subject to the same dose constraints (e.g., minimum target EUD and maximum critical structure EUDs) were compared. The cost functions minimized were EUD (standard model) and functionality-weighted EUD (functional model) to the liver. The resulting treatment plans delivering the same target EUD were compared with respect to their DVHs, their dose wash difference, the average dose delivered to voxels of a particular perfusion level, and change in number of high-/low-functioning voxels receiving a particular dose. Two-dimensional synthetic and three-dimensional clinical examples were studied. Results: The DVHs of all structures of plans from each model were comparable. In contrast, in plans obtained with the functional model, the average dose delivered to high-/low-functioning voxels was lower/higher than in plans obtained with its standard counterpart. The number of high-/low-functioning voxels receiving high/low dose was lower in the plans that considered perfusion in the cost function than in the plans that did not. Redistribution of dose can be observed in the dose wash differences. Conclusion: Liver perfusion can be used during treatment planning potentially to minimize the risk of toxicity during liver SBRT, resulting in better global liver function. The functional model redistributes dose in the standard model from higher to lower functioning voxels, while achieving the same target EUD

  2. A Graphical Exposition of the Inconsistency of Optimal Monetary Plans

    Science.gov (United States)

    Steindl, Frank G.

    2007-01-01

    The author presents a geometrical framework in which the inability of discretionary policy (consistent policy in the sense of Kydland and Prescott) to be socially optimal is demonstrated. Policy based on a rule results in a higher level of utility. The author extends the model to demonstrate that policy of a Rogoff conservative central banker…

  3. Generating Optimal Stowage Plans for Container Vessel Bays

    DEFF Research Database (Denmark)

    Delgado-Ortegon, Alberto; Jensen, Rune Møller; Schulte, Christian

    2009-01-01

    Millions of containers are stowed every week with goods worth billions of dollars, but container vessel stowage is an all but ne- glected combinatorial optimization problem. In this paper, we introduce a model for stowing containers in a vessel bay which is the result of prob- ably the longest...

  4. SU-E-T-521: Feasibility Study of a Rotational Step-And-Shoot IMRT Treatment Planning Approach

    Energy Technology Data Exchange (ETDEWEB)

    Zhu, X [Univ. of North Carolina at Chapel Hill, Chapel Hill, NC (United States); Chang, S [UNC School of Medicine, Chapel Hill, NC (United States); Cullip, T [UNC Hospitals, Chapel Hill, NC (United States); Yuan, L; Zhang, X [Duke University, Durham, NC (United States); Lian, J; Tang, X [UniversityNorth Carolina, Chapel Hill, NC (United States); Tracton, G; Dooley, J [University of North Carolina, Chapel Hill, NC (United States)

    2014-06-01

    Purpose: Rotational step-and-shot IMRT (r-IMRT) could improve delivery efficiency with good dose conformity, especially if it can leverage the burst mode of the accelerator where radiation is turned on/off momentarily while the gantry rotates continuously. The challenge for the r-IMRT planning is to minimize the number of beams to achieve a fast and smooth rotational delivery. Methods: Treatment plans for r-IMRT were created using an in-house treatment planning system. To generate the plan using a very few beams, gantry angle was optimized by weighting the beam monitoring unit (MU), and beam shape optimization was a combination of column search with k-means clustering. A prostate case and a head and neck case were planned using r-IMRT. The dosimetry is compared to s-IMRT planned with Varian Eclipse treatment planning system. Results: With the same PTV dose coverage D95=100%, the r-IMRT plans shows comparable sparing as the s-IMRT plans in the prostate for the rectum D10cc and the bladder Dmean, and in the head and neck for the spinal cord Dmax, the brain stem Dmax, the left/right parotid Dmean, the larynx Dmean, and the mandible Dmean. Both plans meet the established institutional clinical dosimetric criteria. The r-IMRT plan uses 19 beam/405 MU for the prostate, and 68 beam/880 MU for the head and neck, while the s-IMRT uses 7 beam/724 MU and 9 beam/1812 MU, respectively. Compared to the corresponding s-IMRT, r-IMRT has a reduction of MUs of 44% for the prostate case and 41% for the head and neck case. Conclusions: We have demonstrated the feasibility of a rotational step and shoot IMRT treatment planning approach that significantly shortens the conventional IMRT treatment beam-on time without degrading the dose comformity.

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

    Science.gov (United States)

    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

  6. Artificial immune system for diabetes meal plans optimization

    Science.gov (United States)

    Prilianti, K. R.; Callista, P. B.; Setiawan, H.

    2017-03-01

    Type 2 diabetes mellitus is a disease that occurs because the body lacks of insulin or the insulin produced by the pancreas cannot work effectively such that the glucose level in the blood cannot well controlled. One of the most common causes of diabetes mellitus type 2 is obesity, therefore this disease can be controlled with the appropriate diet regarding to the daily calorie requirement. Hence, the level of blood glucose is maintained. Unfortunately, because the lack of proper diet education and facility, many people cannot work on proper daily healthy diet by their own. In this research Artificial Immune System algorithm was applied to build a model that help diabetes mellitus patient arrange their meal plans. The model can calculate the amount of daily calorie needed and arrange the appropriate daily meal plans based on it. The meal plans vary according to the patient calorie needs. The required input data are age, gender, weight, height, and type of patient daily main activity. The experiments show that this model has a good result. The result is already approaching the patients' daily calorie need, i.e. 97.6% (actual need is not less than 80% and not greater than 100%). Carbohydrate of the meal plan is 55-57% (actual need is not less than 45% and not greater than 60%) whereas the protein approximate 15-18% (actual need is not less than 15% and not greater than 20%) and fat of approximate 22-24% (actual need is not less than 20% and not greater than 25%).

  7. An optimal antenna motion generation using shortest path planning

    Science.gov (United States)

    Jeon, Moon-Jin; Kwon, Dong-Soo

    2017-03-01

    This paper considers an angular velocity minimization method for a satellite antenna. For high speed transmission of science data, a directional antenna with a two-axis gimbal is generally used. When a satellite passes over a ground station while pointing directly at it, the angular velocity of the satellite antenna can increase rapidly due to the gimbal kinematics. The high angular velocity could exceed the dynamic constraint of the antenna. Furthermore, micro vibration induced by high speed antenna rotation during an imaging operation might cause jitter, which can degrade the satellite image quality. To solve this problem, a minimum-velocity antenna motion generation method is proposed. Boundaries of the azimuth and elevation angles of the antenna within an effective beam width are derived using antenna geometry. A minimum-velocity azimuth profile and elevation profile within the boundaries are generated sequentially using a shortest path planning method. For fast and correct generation of the shortest path, a new algorithm called a string nailing algorithm is proposed. A numerical simulation shows that the antenna profile generated by the shortest path planning has a much lower angular velocity than the profiles generated by previous methods. The proposed string nailing algorithm also spends much less computation time than a search-based shortest path planning algorithm to generate almost the same antenna profiles.