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Sample records for optimal treatment planning

  1. Interactively exploring optimized treatment plans

    International Nuclear Information System (INIS)

    Rosen, Isaac; Liu, H. Helen; Childress, Nathan; Liao Zhongxing

    2005-01-01

    Purpose: A new paradigm for treatment planning is proposed that embodies the concept of interactively exploring the space of optimized plans. In this approach, treatment planning ignores the details of individual plans and instead presents the physician with clinical summaries of sets of solutions to well-defined clinical goals in which every solution has been optimized in advance by computer algorithms. Methods and materials: Before interactive planning, sets of optimized plans are created for a variety of treatment delivery options and critical structure dose-volume constraints. Then, the dose-volume parameters of the optimized plans are fit to linear functions. These linear functions are used to show in real time how the target dose-volume histogram (DVH) changes as the DVHs of the critical structures are changed interactively. A bitmap of the space of optimized plans is used to restrict the feasible solutions. The physician selects the critical structure dose-volume constraints that give the desired dose to the planning target volume (PTV) and then those constraints are used to create the corresponding optimized plan. Results: The method is demonstrated using prototype software, Treatment Plan Explorer (TPEx), and a clinical example of a patient with a tumor in the right lung. For this example, the delivery options included 4 open beams, 12 open beams, 4 wedged beams, and 12 wedged beams. Beam directions and relative weights were optimized for a range of critical structure dose-volume constraints for the lungs and esophagus. Cord dose was restricted to 45 Gy. Using the interactive interface, the physician explored how the tumor dose changed as critical structure dose-volume constraints were tightened or relaxed and selected the best compromise for each delivery option. The corresponding treatment plans were calculated and compared with the linear parameterization presented to the physician in TPEx. The linear fits were best for the maximum PTV dose and worst

  2. Treatment planning optimization for linear accelerator radiosurgery

    International Nuclear Information System (INIS)

    Meeks, Sanford L.; Buatti, John M.; Bova, Francis J.; Friedman, William A.; Mendenhall, William M.

    1998-01-01

    Purpose: Linear accelerator radiosurgery uses multiple arcs delivered through circular collimators to produce a nominally spherical dose distribution. Production of dose distributions that conform to irregular lesions or conformally avoid critical neural structures requires a detailed understanding of the available treatment planning parameters. Methods and Materials: Treatment planning parameters that may be manipulated within a single isocenter to provide conformal avoidance and dose conformation to ellipsoidal lesions include differential arc weighting and gantry start/stop angles. More irregular lesions require the use of multiple isocenters. Iterative manipulation of treatment planning variables can be difficult and computationally expensive, especially if the effects of these manipulations are not well defined. Effects of treatment parameter manipulation are explained and illustrated. This is followed by description of the University of Florida Stereotactic Radiosurgery Treatment Planning Algorithm. This algorithm organizes the manipulations into a practical approach for radiosurgery treatment planning. Results: Iterative treatment planning parameters may be efficiently manipulated to achieve optimal treatment plans by following the University of Florida Treatment Planning Algorithm. The ability to produce conformal stereotactic treatment plans using the algorithm is demonstrated for a variety of clinical presentations. Conclusion: The standard dose distribution produced in linear accelerator radiosurgery is spherical, but manipulation of available treatment planning parameters may result in optimal dose conformation. The University of Florida Treatment Planning Algorithm organizes available treatment parameters to efficiently produce conformal radiosurgery treatment plans

  3. 94: Treatment plan optimization for conformal therapy

    International Nuclear Information System (INIS)

    Rosen, I.I.; Lane, R.G.

    1987-01-01

    Computer-controlled conformal radiation therapy techniques can deliver complex treatments utilizing large numbers of beams, gantry angles and beam shapes. Linear programming is well-suited for planning conformal treatments. Given a list of available treatment beams, linear programming calculates the relative weights of the beams such that the objective function is optimized and doses to constraint points are within the prescribed limits. 5 refs.; 3 figs

  4. Conventional treatment planning optimization using simulated annealing

    International Nuclear Information System (INIS)

    Morrill, S.M.; Langer, M.; Lane, R.G.

    1995-01-01

    Purpose: Simulated annealing (SA) allows for the implementation of realistic biological and clinical cost functions into treatment plan optimization. However, a drawback to the clinical implementation of SA optimization is that large numbers of beams appear in the final solution, some with insignificant weights, preventing the delivery of these optimized plans using conventional (limited to a few coplanar beams) radiation therapy. A preliminary study suggested two promising algorithms for restricting the number of beam weights. The purpose of this investigation was to compare these two algorithms using our current SA algorithm with the aim of producing a algorithm to allow clinically useful radiation therapy treatment planning optimization. Method: Our current SA algorithm, Variable Stepsize Generalized Simulated Annealing (VSGSA) was modified with two algorithms to restrict the number of beam weights in the final solution. The first algorithm selected combinations of a fixed number of beams from the complete solution space at each iterative step of the optimization process. The second reduced the allowed number of beams by a factor of two at periodic steps during the optimization process until only the specified number of beams remained. Results of optimization of beam weights and angles using these algorithms were compared using a standard cadre of abdominal cases. The solution space was defined as a set of 36 custom-shaped open and wedged-filtered fields at 10 deg. increments with a target constant target volume margin of 1.2 cm. For each case a clinically-accepted cost function, minimum tumor dose was maximized subject to a set of normal tissue binary dose-volume constraints. For this study, the optimized plan was restricted to four (4) fields suitable for delivery with conventional therapy equipment. Results: The table gives the mean value of the minimum target dose obtained for each algorithm averaged over 5 different runs and the comparable manual treatment

  5. When does treatment plan optimization require inverse planning?

    International Nuclear Information System (INIS)

    Sherouse, George W.

    1995-01-01

    Increasing maturity of image-based computer-aided design of three-dimensional conformal radiotherapy has recently sparked a great deal of work in the area of treatment plan optimization. Optimization of a conformal photon beam treatment plan is that exercise through which a set of intensity-modulated static beams or arcs is specified such that, when the plan is executed, 1) a region of homogeneous dose is produced in the patient with a shape which geometrically conforms (within a specified tolerance) to the three-dimensional shape of a designated target volume and 2) acceptably low incidental dose is delivered to non-target tissues. Interest in conformal radiotherapy arise from a fundamental assumption that there is significant value to be gained from aggressive customization of the treatment for each individual patient In our efforts to design optimal treatments, however, it is important to remember that, given the biological and economic realities of clinical radiotherapy, mathematical optimization of dose distribution metrics with respect to some minimal constraint set is not a necessary or even sufficient condition for design of a clinically optimal treatment. There is wide variation in the complexity of the clinical situations encountered in practice and there are a number of non-physical criteria to be considered in planning. There is also a complementary variety of computational and engineering means for achieving optimization. To date, the scientific dialogue regarding these techniques has concentrated on development of solutions to worst-case scenarios, largely in the absence of consideration of appropriate matching of solution complexity to problem complexity. It is the aim of this presentation to propose a provisional stratification of treatment planning problems, stratified by relative complexity, and to identify a corresponding stratification of necessary treatment planning techniques. It is asserted that the subset of clinical radiotherapy cases for

  6. Optimization of rotational radiotherapy treatment planning

    International Nuclear Information System (INIS)

    Tulovsky, Vladimir; Ringor, Michael; Papiez, Lech

    1995-01-01

    Purpose: Rotational therapy treatment planning for rotationally symmetric geometry of tumor and healthy tissue provides an important example of testing various approaches to optimizing dose distributions for therapeutic x-ray irradiations. In this article, dose distribution optimization is formulated as a variational problem. This problem is solved analytically and numerically. Methods and Materials: The classical Lagrange method is used to derive equations and inequalities that give necessary conditions for minimizing the mean-square deviation between the ideal dose distribution and the achievable dose distribution. The solution of the resulting integral equation with Cauchy kernel is used to derive analytical formulas for the minimizing irradiation intensity function. Results: The solutions are evaluated numerically and the graphs of the minimizing intensity functions and the corresponding dose distributions are presented. Conclusions: The optimal solutions obtained using the mean-square criterion lead to significant underdosage in some areas of the tumor volume. Possible solutions to this shortcoming are investigated and medically more appropriate criteria for optimization are proposed for future investigations

  7. Normalisation: ROI optimal treatment planning - SNDH pattern

    International Nuclear Information System (INIS)

    Shilvat, D.V.; Bhandari, Virendra; Tamane, Chandrashekhar; Pangam, Suresh

    2001-01-01

    Dose precision maximally to the target / ROI (Region of Interest), taking care of tolerance dose of normal tissue is the aim of ideal treatment planning. This goal is achieved with advanced modalities such as, micro MLC, simulator and 3-dimensional treatment planning system. But SNDH PATTERN uses minimum available resources as, ALCYON II Telecobalt unit, CT Scan, MULTIDATA 2-dimensional treatment planning system to their maximum utility and reaches to the required precision, same as that with advance modalities. Among the number of parameters used, 'NORMALISATION TO THE ROI' will achieve the aim of the treatment planning effectively. This is dealing with an example of canal of esophagus modified treatment planning based on SNDH pattern. Results are attractive and self explanatory. By implementing SNDH pattern, the QUALITY INDEX of treatment plan will reach to greater than 90%, with substantial reduction in dose to the vital organs. Aim is to utilize the minimum available resources efficiently to achieve highest possible precision for delivering homogenous dose to ROI while taking care of tolerance dose to vital organs

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

    International Nuclear Information System (INIS)

    2015-01-01

    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

  9. 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

  10. Optimal partial-arcs in VMAT treatment planning

    International Nuclear Information System (INIS)

    Wala, Jeremiah; Salari, Ehsan; Chen Wei; Craft, David

    2012-01-01

    We present a method for improving the delivery efficiency of VMAT by extending the recently published VMAT treatment planning algorithm vmerge to automatically generate optimal partial-arc plans. 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. Partial-arc plans are created using pmerge for a lung, liver and prostate case, with final treatment times of 127, 245 and 147 s. Treatment times using full arcs with vmerge are 211, 357 and 178 s. The mean doses to the critical structures for the vmerge and pmerge plans are kept within 5% of those in the initial plan, and the target volume covered by the prescription isodose is maintained above 98% for the pmerge and vmerge plans. Additionally, we find that the angular distribution of fluence in the initial plans is predictive of the start and end angles of the optimal partial-arc. We conclude that VMAT delivery efficiency can be improved by employing partial-arcs without compromising dose quality, and that partial-arcs are most applicable to cases with non-centralized targets. (paper)

  11. Plug pattern optimization for gamma knife radiosurgery treatment planning

    International Nuclear Information System (INIS)

    Zhang Pengpeng; Wu, Jackie; Dean, David; Xing Lei; Xue Jinyue; Maciunas, Robert; Sibata, Claudio

    2003-01-01

    Purpose: To develop a novel dose optimization algorithm for improving the sparing of critical structures during gamma knife radiosurgery by shaping the plug pattern of each individual shot. Method and Materials: We first use a geometric information (medial axis) aided guided evolutionary simulated annealing (GESA) optimization algorithm to determine the number of shots and isocenter location, size, and weight of each shot. Then we create a plug quality score system that checks the dose contribution to the volume of interest by each plug in the treatment plan. A positive score implies that the corresponding source could be open to improve tumor coverage, whereas a negative score means the source could be blocked for the purpose of sparing normal and critical structures. The plug pattern is then optimized via the GESA algorithm that is integrated with this score system. Weight and position of each shot are also tuned in this procedure. Results: An acoustic tumor case is used to evaluate our algorithm. Compared to the treatment plan generated without plug patterns, adding an optimized plug pattern into the treatment planning process boosts tumor coverage index from 95.1% to 97.2%, reduces RTOG conformity index from 1.279 to 1.167, lowers Paddick's index from 1.34 to 1.20, and trims the critical structure receiving more than 30% maximum dose from 16 mm 3 to 6 mm 3 . Conclusions: Automated GESA-based plug pattern optimization of gamma knife radiosurgery frees the treatment planning team from the manual forward planning procedure and provides an optimal treatment plan

  12. 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.

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

    Science.gov (United States)

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

    2010-11-01

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

  14. 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.

  15. Quality assurance for high dose rate brachytherapy treatment planning optimization: using a simple optimization to verify a complex optimization

    International Nuclear Information System (INIS)

    Deufel, Christopher L; Furutani, Keith M

    2014-01-01

    As dose optimization for high dose rate brachytherapy becomes more complex, it becomes increasingly important to have a means of verifying that optimization results are reasonable. A method is presented for using a simple optimization as quality assurance for the more complex optimization algorithms typically found in commercial brachytherapy treatment planning systems. Quality assurance tests may be performed during commissioning, at regular intervals, and/or on a patient specific basis. A simple optimization method is provided that optimizes conformal target coverage using an exact, variance-based, algebraic approach. Metrics such as dose volume histogram, conformality index, and total reference air kerma agree closely between simple and complex optimizations for breast, cervix, prostate, and planar applicators. The simple optimization is shown to be a sensitive measure for identifying failures in a commercial treatment planning system that are possibly due to operator error or weaknesses in planning system optimization algorithms. Results from the simple optimization are surprisingly similar to the results from a more complex, commercial optimization for several clinical applications. This suggests that there are only modest gains to be made from making brachytherapy optimization more complex. The improvements expected from sophisticated linear optimizations, such as PARETO methods, will largely be in making systems more user friendly and efficient, rather than in finding dramatically better source strength distributions. (paper)

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

    International Nuclear Information System (INIS)

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

    2013-01-01

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

  17. Clinical treatment planning optimization by Powell's method for gamma unit treatment system

    International Nuclear Information System (INIS)

    Yan Yulong; Shu Huazhong; Bao Xudong; Luo Limin; Bai Yi

    1997-01-01

    Purpose: This article presents a new optimization method for stereotactic radiosurgery treatment planning for gamma unit treatment system. Methods and Materials: The gamma unit has been utilized in stereotactic radiosurgery for about 30 years, but the usual procedure for a physician-physicist team to design a treatment plan is a trial-and-error approach. Isodose curves are viewed on two-dimensional computed tomography (CT) or magnetic resonance (MR) image planes, which is not only time consuming but also seldom achieves the optimal treatment plan, especially when the isocenter weights are regarded. We developed a treatment-planning system on a computer workstation in which Powell's optimization method is realized. The optimization process starts with the initial parameters (the number of iso centers as well as corresponding 3D iso centers' coordinates, collimator sizes, and weight factors) roughly determined by the physician-physicist team. The objective function can be changed to consider protection of sensitive tissues. Results: We use the plan parameters given by a well-trained physician-physicist team, or ones that the author give roughly as the initial parameters for the optimization procedure. Dosimetric results of optimization show a better high dose-volume conformation to the target volume compared to the doctor's plan. Conclusion: This method converges quickly and is not sensitive to the initial parameters. It achieves an excellent conformation of the estimated isodose curves with the contours of the target volume. If the initial parameters are varied, there will be a little difference in parameters' configuration, but the dosimetric results proved almost to be the same

  18. Development of a fast optimization preview in radiation treatment planning

    International Nuclear Information System (INIS)

    Hoeffner, J.; Decker, P.; Schmidt, E.L.; Herbig, W.; Rittler, J.; Weiss, P.

    1996-01-01

    Usually, the speed of convergence of some iterative algorithms is restricted to a bounded relaxation parameter. Exploiting the special altering behavior of the weighting factors at each step, many iteration steps are avoided by overrelaxing this relaxation parameter. Therefore, the relaxation parameter is increased as long as the optimization result is improved. This can be performed without loss of accuracy. Our optimization technique is demonstrated by the case of a right lung carcinoma. The solution space for this case is 36 isocentric X-ray beams evenly spaced at 10 . Each beam is restricted to 23 MV X-ray fields with a planning target volume matched by irregular field shapes, similar to that produced by a multileaf collimator. Four organs at risk plus the planning target volume are considered in the optimization process. The convergence behavior of the optimization algorithm is shown by overrelaxing the relaxation parameter in comparison to conventional relaxation parameter control. The new approach offers the ability to get a fast preview of the expected final result. If the clinician is in agreement with the preview, the algorithm is continued and achieves the result proven by the Cimmino optimization algorithm. In the other case, if the clinician doesn't agree with the preview, he will be able to change the optimization parameters (e.g. field entry points) and to restart the algorithm. (orig./MG) [de

  19. AI-guided parameter optimization in inverse treatment planning

    International Nuclear Information System (INIS)

    Yan Hui; Yin Fangfang; Guan Huaiqun; Kim, Jae Ho

    2003-01-01

    An artificial intelligence (AI)-guided inverse planning system was developed to optimize the combination of parameters in the objective function for intensity-modulated radiation therapy (IMRT). In this system, the empirical knowledge of inverse planning was formulated with fuzzy if-then rules, which then guide the parameter modification based on the on-line calculated dose. Three kinds of parameters (weighting factor, dose specification, and dose prescription) were automatically modified using the fuzzy inference system (FIS). The performance of the AI-guided inverse planning system (AIGIPS) was examined using the simulated and clinical examples. Preliminary results indicate that the expected dose distribution was automatically achieved using the AI-guided inverse planning system, with the complicated compromising between different parameters accomplished by the fuzzy inference technique. The AIGIPS provides a highly promising method to replace the current trial-and-error approach

  20. A DVH-guided IMRT optimization algorithm for automatic treatment planning and adaptive radiotherapy replanning

    International Nuclear Information System (INIS)

    Zarepisheh, Masoud; Li, Nan; Long, Troy; Romeijn, H. Edwin; Tian, Zhen; Jia, Xun; Jiang, Steve B.

    2014-01-01

    Purpose: To develop a novel algorithm that incorporates prior treatment knowledge into intensity modulated radiation therapy optimization to facilitate automatic treatment planning and adaptive radiotherapy (ART) replanning. Methods: The algorithm automatically creates a treatment plan guided by the DVH curves of a reference plan that contains information on the clinician-approved dose-volume trade-offs among different targets/organs and among different portions of a DVH curve for an organ. In ART, the reference plan is the initial plan for the same patient, while for automatic treatment planning the reference plan is selected from a library of clinically approved and delivered plans of previously treated patients with similar medical conditions and geometry. The proposed algorithm employs a voxel-based optimization model and navigates the large voxel-based Pareto surface. The voxel weights are iteratively adjusted to approach a plan that is similar to the reference plan in terms of the DVHs. If the reference plan is feasible but not Pareto optimal, the algorithm generates a Pareto optimal plan with the DVHs better than the reference ones. If the reference plan is too restricting for the new geometry, the algorithm generates a Pareto plan with DVHs close to the reference ones. In both cases, the new plans have similar DVH trade-offs as the reference plans. Results: The algorithm was tested using three patient cases and found to be able to automatically adjust the voxel-weighting factors in order to generate a Pareto plan with similar DVH trade-offs as the reference plan. The algorithm has also been implemented on a GPU for high efficiency. Conclusions: A novel prior-knowledge-based optimization algorithm has been developed that automatically adjust the voxel weights and generate a clinical optimal plan at high efficiency. It is found that the new algorithm can significantly improve the plan quality and planning efficiency in ART replanning and automatic treatment

  1. Analysis of Radiation Treatment Planning by Dose Calculation and Optimization Algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Dae Sup; Yoon, In Ha; Lee, Woo Seok; Baek, Geum Mun [Dept. of Radiation Oncology, Asan Medical Center, Seoul (Korea, Republic of)

    2012-09-15

    Analyze the Effectiveness of Radiation Treatment Planning by dose calculation and optimization algorithm, apply consideration of actual treatment planning, and then suggest the best way to treatment planning protocol. The treatment planning system use Eclipse 10.0. (Varian, USA). PBC (Pencil Beam Convolution) and AAA (Anisotropic Analytical Algorithm) Apply to Dose calculation, DVO (Dose Volume Optimizer 10.0.28) used for optimized algorithm of Intensity Modulated Radiation Therapy (IMRT), PRO II (Progressive Resolution Optimizer V 8.9.17) and PRO III (Progressive Resolution Optimizer V 10.0.28) used for optimized algorithm of VAMT. A phantom for experiment virtually created at treatment planning system, 30x30x30 cm sized, homogeneous density (HU: 0) and heterogeneous density that inserted air assumed material (HU: -1,000). Apply to clinical treatment planning on the basis of general treatment planning feature analyzed with Phantom planning. In homogeneous density phantom, PBC and AAA show 65.2% PDD (6 MV, 10 cm) both, In heterogeneous density phantom, also show similar PDD value before meet with low density material, but they show different dose curve in air territory, PDD 10 cm showed 75%, 73% each after penetrate phantom. 3D treatment plan in same MU, AAA treatment planning shows low dose at Lung included area. 2D POP treatment plan with 15 MV of cervical vertebral region include trachea and lung area, Conformity Index (ICRU 62) is 0.95 in PBC calculation and 0.93 in AAA. DVO DVH and Dose calculation DVH are showed equal value in IMRT treatment plan. But AAA calculation shows lack of dose compared with DVO result which is satisfactory condition. Optimizing VMAT treatment plans using PRO II obtained results were satisfactory, but lower density area showed lack of dose in dose calculations. PRO III, but optimizing the dose calculation results were similar with optimized the same conditions once more. In this study, do not judge the rightness of the dose

  2. Analysis of Radiation Treatment Planning by Dose Calculation and Optimization Algorithm

    International Nuclear Information System (INIS)

    Kim, Dae Sup; Yoon, In Ha; Lee, Woo Seok; Baek, Geum Mun

    2012-01-01

    Analyze the Effectiveness of Radiation Treatment Planning by dose calculation and optimization algorithm, apply consideration of actual treatment planning, and then suggest the best way to treatment planning protocol. The treatment planning system use Eclipse 10.0. (Varian, USA). PBC (Pencil Beam Convolution) and AAA (Anisotropic Analytical Algorithm) Apply to Dose calculation, DVO (Dose Volume Optimizer 10.0.28) used for optimized algorithm of Intensity Modulated Radiation Therapy (IMRT), PRO II (Progressive Resolution Optimizer V 8.9.17) and PRO III (Progressive Resolution Optimizer V 10.0.28) used for optimized algorithm of VAMT. A phantom for experiment virtually created at treatment planning system, 30x30x30 cm sized, homogeneous density (HU: 0) and heterogeneous density that inserted air assumed material (HU: -1,000). Apply to clinical treatment planning on the basis of general treatment planning feature analyzed with Phantom planning. In homogeneous density phantom, PBC and AAA show 65.2% PDD (6 MV, 10 cm) both, In heterogeneous density phantom, also show similar PDD value before meet with low density material, but they show different dose curve in air territory, PDD 10 cm showed 75%, 73% each after penetrate phantom. 3D treatment plan in same MU, AAA treatment planning shows low dose at Lung included area. 2D POP treatment plan with 15 MV of cervical vertebral region include trachea and lung area, Conformity Index (ICRU 62) is 0.95 in PBC calculation and 0.93 in AAA. DVO DVH and Dose calculation DVH are showed equal value in IMRT treatment plan. But AAA calculation shows lack of dose compared with DVO result which is satisfactory condition. Optimizing VMAT treatment plans using PRO II obtained results were satisfactory, but lower density area showed lack of dose in dose calculations. PRO III, but optimizing the dose calculation results were similar with optimized the same conditions once more. In this study, do not judge the rightness of the dose

  3. Optimization of Gamma Knife treatment planning via guided evolutionary simulated annealing

    International Nuclear Information System (INIS)

    Zhang Pengpeng; Dean, David; Metzger, Andrew; Sibata, Claudio

    2001-01-01

    We present a method for generating optimized Gamma Knife trade mark sign (Elekta, Stockholm, Sweden) radiosurgery treatment plans. This semiautomatic method produces a highly conformal shot packing plan for the irradiation of an intracranial tumor. We simulate optimal treatment planning criteria with a probability function that is linked to every voxel in a volumetric (MR or CT) region of interest. This sigmoidal P + parameter models the requirement of conformality (i.e., tumor ablation and normal tissue sparing). After determination of initial radiosurgery treatment parameters, a guided evolutionary simulated annealing (GESA) algorithm is used to find the optimal size, position, and weight for each shot. The three-dimensional GESA algorithm searches the shot parameter space more thoroughly than is possible during manual shot packing and provides one plan that is suitable to the treatment criteria of the attending neurosurgeon and radiation oncologist. The result is a more conformal plan, which also reduces redundancy, and saves treatment administration time

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

    International Nuclear Information System (INIS)

    Kapur, A.

    2015-01-01

    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

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

    International Nuclear Information System (INIS)

    Feng, W.

    2015-01-01

    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

  6. 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

  7. 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

  8. Optimization in radiotherapy treatment planning thanks to a fast dose calculation method

    International Nuclear Information System (INIS)

    Yang, Mingchao

    2014-01-01

    This thesis deals with the radiotherapy treatments planning issue which need a fast and reliable treatment planning system (TPS). The TPS is composed of a dose calculation algorithm and an optimization method. The objective is to design a plan to deliver the dose to the tumor while preserving the surrounding healthy and sensitive tissues. The treatment planning aims to determine the best suited radiation parameters for each patient's treatment. In this thesis, the parameters of treatment with IMRT (Intensity modulated radiation therapy) are the beam angle and the beam intensity. The objective function is multi-criteria with linear constraints. The main objective of this thesis is to demonstrate the feasibility of a treatment planning optimization method based on a fast dose-calculation technique developed by (Blanpain, 2009). This technique proposes to compute the dose by segmenting the patient's phantom into homogeneous meshes. The dose computation is divided into two steps. The first step impacts the meshes: projections and weights are set according to physical and geometrical criteria. The second step impacts the voxels: the dose is computed by evaluating the functions previously associated to their mesh. A reformulation of this technique makes possible to solve the optimization problem by the gradient descent algorithm. The main advantage of this method is that the beam angle parameters could be optimized continuously in 3 dimensions. The obtained results in this thesis offer many opportunities in the field of radiotherapy treatment planning optimization. (author) [fr

  9. Pre-optimization of radiotherapy treatment planning: an artificial neural network classification aided technique

    International Nuclear Information System (INIS)

    Hosseini-Ashrafi, M.E.; Bagherebadian, H.; Yahaqi, E.

    1999-01-01

    A method has been developed which, by using the geometric information from treatment sample cases, selects from a given data set an initial treatment plan as a step for treatment plan optimization. The method uses an artificial neural network (ANN) classification technique to select a best matching plan from the 'optimized' ANN database. Separate back-propagation ANN classifiers were trained using 50, 60 and 77 examples for three groups of treatment case classes (up to 21 examples from each class were used). The performance of the classifiers in selecting the correct treatment class was tested using the leave-one-out method; the networks were optimized with respect their architecture. For the three groups used in this study, successful classification fractions of 0.83, 0.98 and 0.93 were achieved by the optimized ANN classifiers. The automated response of the ANN may be used to arrive at a pre-plan where many treatment parameters may be identified and therefore a significant reduction in the steps required to arrive at the optimum plan may be achieved. Treatment planning 'experience' and also results from lengthy calculations may be used for training the ANN. (author)

  10. Comparison of various online IGRT strategies: The benefits of online treatment plan re-optimization

    International Nuclear Information System (INIS)

    Schulze, Derek; Liang, Jian; Yan, Di; Zhang Tiezhi

    2009-01-01

    Purpose: To compare the dosimetric differences of various online IGRT strategies and to predict potential benefits of online re-optimization techniques in prostate cancer radiation treatments. Materials and methods: Nine prostate patients were recruited in this study. Each patient has one treatment planning CT images and 10-treatment day CT images. Five different online IGRT strategies were evaluated which include 3D conformal with bone alignment, 3D conformal re-planning via aperture changes, intensity modulated radiation treatment (IMRT) with bone alignment, IMRT with target alignment and IMRT daily re-optimization. Treatment planning and virtual treatment delivery were performed. The delivered doses were obtained using in-house deformable dose mapping software. The results were analyzed using equivalent uniform dose (EUD). Results: With the same margin, rectum and bladder doses in IMRT plans were about 10% and 5% less than those in CRT plans, respectively. Rectum and bladder doses were reduced as much as 20% if motion margin is reduced by 1 cm. IMRT is more sensitive to organ motion. Large discrepancies of bladder and rectum doses were observed compared to the actual delivered dose with treatment plan predication. The therapeutic ratio can be improved by 14% and 25% for rectum and bladder, respectively, if IMRT online re-planning is employed compared to the IMRT bone alignment approach. The improvement of target alignment approach is similar with 11% and 21% dose reduction to rectum and bladder, respectively. However, underdosing in seminal vesicles was observed on certain patients. Conclusions: Online treatment plan re-optimization may significantly improve therapeutic ratio in prostate cancer treatments mostly due to the reduction of PTV margin. However, for low risk patient with only prostate involved, online target alignment IMRT treatment would achieve similar results as online re-planning. For all IGRT approaches, the delivered organ-at-risk doses may be

  11. Inverse optimization of objective function weights for treatment planning using clinical dose-volume histograms

    Science.gov (United States)

    Babier, Aaron; Boutilier, Justin J.; Sharpe, Michael B.; McNiven, Andrea L.; Chan, Timothy C. Y.

    2018-05-01

    We developed and evaluated a novel inverse optimization (IO) model to estimate objective function weights from clinical dose-volume histograms (DVHs). These weights were used to solve a treatment planning problem to generate ‘inverse plans’ that had similar DVHs to the original clinical DVHs. Our methodology was applied to 217 clinical head and neck cancer treatment plans that were previously delivered at Princess Margaret Cancer Centre in Canada. Inverse plan DVHs were compared to the clinical DVHs using objective function values, dose-volume differences, and frequency of clinical planning criteria satisfaction. Median differences between the clinical and inverse DVHs were within 1.1 Gy. For most structures, the difference in clinical planning criteria satisfaction between the clinical and inverse plans was at most 1.4%. For structures where the two plans differed by more than 1.4% in planning criteria satisfaction, the difference in average criterion violation was less than 0.5 Gy. Overall, the inverse plans were very similar to the clinical plans. Compared with a previous inverse optimization method from the literature, our new inverse plans typically satisfied the same or more clinical criteria, and had consistently lower fluence heterogeneity. Overall, this paper demonstrates that DVHs, which are essentially summary statistics, provide sufficient information to estimate objective function weights that result in high quality treatment plans. However, as with any summary statistic that compresses three-dimensional dose information, care must be taken to avoid generating plans with undesirable features such as hotspots; our computational results suggest that such undesirable spatial features were uncommon. Our IO-based approach can be integrated into the current clinical planning paradigm to better initialize the planning process and improve planning efficiency. It could also be embedded in a knowledge-based planning or adaptive radiation therapy framework to

  12. Study on hybrid multi-objective optimization algorithm for inverse treatment planning of radiation therapy

    International Nuclear Information System (INIS)

    Li Guoli; Song Gang; Wu Yican

    2007-01-01

    Inverse treatment planning for radiation therapy is a multi-objective optimization process. The hybrid multi-objective optimization algorithm is studied by combining the simulated annealing(SA) and genetic algorithm(GA). Test functions are used to analyze the efficiency of algorithms. The hybrid multi-objective optimization SA algorithm, which displacement is based on the evolutionary strategy of GA: crossover and mutation, is implemented in inverse planning of external beam radiation therapy by using two kinds of objective functions, namely the average dose distribution based and the hybrid dose-volume constraints based objective functions. The test calculations demonstrate that excellent converge speed can be achieved. (authors)

  13. A new column-generation-based algorithm for VMAT treatment plan optimization

    International Nuclear Information System (INIS)

    Peng Fei; Epelman, Marina A; Romeijn, H Edwin; Jia Xun; Gu Xuejun; Jiang, Steve B

    2012-01-01

    We study the treatment plan optimization problem for volumetric modulated arc therapy (VMAT). We propose a new column-generation-based algorithm that takes into account bounds on the gantry speed and dose rate, as well as an upper bound on the rate of change of the gantry speed, in addition to MLC constraints. The algorithm iteratively adds one aperture at each control point along the treatment arc. In each iteration, a restricted problem optimizing intensities at previously selected apertures is solved, and its solution is used to formulate a pricing problem, which selects an aperture at another control point that is compatible with previously selected apertures and leads to the largest rate of improvement in the objective function value of the restricted problem. Once a complete set of apertures is obtained, their intensities are optimized and the gantry speeds and dose rates are adjusted to minimize treatment time while satisfying all machine restrictions. Comparisons of treatment plans obtained by our algorithm to idealized IMRT plans of 177 beams on five clinical prostate cancer cases demonstrate high quality with respect to clinical dose–volume criteria. For all cases, our algorithm yields treatment plans that can be delivered in around 2 min. Implementation on a graphic processing unit enables us to finish the optimization of a VMAT plan in 25–55 s. (paper)

  14. Treatment planning for heavy ion radiotherapy: calculation and optimization of biologically effective dose

    International Nuclear Information System (INIS)

    Kraemer, M.; Scholz, M.

    2000-09-01

    We describe a novel approach to treatment planning for heavy ion radiotherapy based on the local effect model (LEM) which allows to calculate the biologically effective dose not only for the target region but for the entire irradiation volume. LEM is ideally suited to be used as an integral part of treatment planning code systems for active dose shaping devices like the GSI raster scan system. Thus, it has been incorporated into our standard treatment planning system for ion therapy (TRiP). Single intensity modulated fields can be optimized with respect to homogeneous biologically effective dose. The relative biological effectiveness (RBE) is calculated separately for each voxel of the patient CT. Our radiobiologically oriented code system is in use since 1995 for the planning of irradiation experiments with cell cultures and animals such as rats and minipigs. Since 1997 it is in regular and successful use for patient treatment planning. (orig.)

  15. 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

    2016-06-07

    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

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

    International Nuclear Information System (INIS)

    Na, Y; Kapp, D; Kim, Y; Xing, L; Suh, T

    2014-01-01

    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

  17. 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

  18. Development of a Whole Body Atlas for Radiation Therapy Planning and Treatment Optimization

    International Nuclear Information System (INIS)

    Qatarneh, Sharif

    2006-01-01

    The main objective of radiation therapy is to obtain the highest possible probability of tumor cure while minimizing adverse reactions in healthy tissues. A crucial step in the treatment process is to determine the location and extent of the primary tumor and its loco regional lymphatic spread in relation to adjacent radiosensitive anatomical structures and organs at risk. These volumes must also be accurately delineated with respect to external anatomic reference points, preferably on surrounding bony structures. At the same time, it is essential to have the best possible physical and radiobiological knowledge about the radiation responsiveness of the target tissues and organs at risk in order to achieve a more accurate optimization of the treatment outcome. A computerized whole body Atlas has therefore been developed to serve as a dynamic database, with systematically integrated knowledge, comprising all necessary physical and radiobiological information about common target volumes and normal tissues. The Atlas also contains a database of segmented organs and a lymph node topography, which was based on the Visible Human dataset, to form standard reference geometry of organ systems. The reference knowledge base and the standard organ dataset can be utilized for Atlas-based image processing and analysis in radiation therapy planning and for biological optimization of the treatment outcome. Atlas-based segmentation procedures were utilized to transform the reference organ dataset of the Atlas into the geometry of individual patients. The anatomic organs and target volumes of the database can be converted by elastic transformation into those of the individual patient for final treatment planning. Furthermore, a database of reference treatment plans was started by implementing state-of-the-art biologically based radiation therapy planning techniques such as conformal, intensity modulated, and radio biologically optimized treatment planning. The computerized Atlas can

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

    International Nuclear Information System (INIS)

    Wala, Jeremiah; Craft, David; Paly, Jon; Zietman, Anthony; Efstathiou, Jason

    2013-01-01

    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 −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

  20. 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.

  1. Geometric moments and artificial neural network in per optimization of radiotherapy treatment planning

    International Nuclear Information System (INIS)

    Yahaqi, E.; Movafeghi, A.; Hosseini- Ashrafi, M.E.

    2004-01-01

    Given the number of possible combinations of different setting in radiotherapy such as the number of fields etc., arriving at an optimum treatment plan with a completely conventional solution would require an unacceptable number of interaction. Using a priori information whether of a qualitative or quantitative nature has the potential of greatly reducing amount of calculation required in any optimization procedure. Having extracted the outline of the body counter line the treatment area, the sensitive organ and any in- homogeneity present in the given cross section quantitative information in the form of moments is calculated for each treatment case. An artificial neural network classifier is then developed using group of sample treatment case and applied to arrive at initial treatment plan for any new case. The approach has been shown to have strong potential for greatly reducing the number of choices in selecting the optimum answer in treatment planning

  2. A multicriteria framework with voxel-dependent parameters for radiotherapy treatment plan optimization

    International Nuclear Information System (INIS)

    Zarepisheh, Masoud; Uribe-Sanchez, Andres F.; Li, Nan; Jia, Xun; Jiang, Steve B.

    2014-01-01

    Purpose: To establish a new mathematical framework for radiotherapy treatment optimization with voxel-dependent optimization parameters. Methods: In the 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 a set of the objective functions associated to the 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. Furthermore, questions about the objective function selection and parameter adjustment to assure Pareto optimality as well as the relationship between the optimal solutions obtained from the organ-based and voxel-based models remain unanswered. To answer these questions, the authors establish in this work a new mathematical framework equipped with two theorems. Results: 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 impact of using different objective functions on plan qualities and Pareto surfaces. 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 since the Pareto surface is independent of the objective function selection and the entire Pareto surface could be generated as long as the objective function satisfies certain mathematical conditions; (2) All Pareto solutions generated by the organ-based model with different objective functions are parts of a unique Pareto surface generated by the voxel-based model with any appropriate objective function; (3) A much larger Pareto surface is explored by adjusting voxel-dependent parameters than by adjusting organ-dependent parameters, possibly

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

    Science.gov (United States)

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

    2015-04-07

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

  5. Therapeutic treatment plan optimization with probability density-based dose prescription

    International Nuclear Information System (INIS)

    Lian Jun; Cotrutz, Cristian; Xing Lei

    2003-01-01

    The dose optimization in inverse planning is realized under the guidance of an objective function. The prescription doses in a conventional approach are usually rigid values, defining in most instances an ill-conditioned optimization problem. In this work, we propose a more general dose optimization scheme based on a statistical formalism [Xing et al., Med. Phys. 21, 2348-2358 (1999)]. Instead of a rigid dose, the prescription to a structure is specified by a preference function, which describes the user's preference over other doses in case the most desired dose is not attainable. The variation range of the prescription dose and the shape of the preference function are predesigned by the user based on prior clinical experience. Consequently, during the iterative optimization process, the prescription dose is allowed to deviate, with a certain preference level, from the most desired dose. By not restricting the prescription dose to a fixed value, the optimization problem becomes less ill-defined. The conventional inverse planning algorithm represents a special case of the new formalism. An iterative dose optimization algorithm is used to optimize the system. The performance of the proposed technique is systematically studied using a hypothetical C-shaped tumor with an abutting circular critical structure and a prostate case. It is shown that the final dose distribution can be manipulated flexibly by tuning the shape of the preference function and that using a preference function can lead to optimized dose distributions in accordance with the planner's specification. The proposed framework offers an effective mechanism to formalize the planner's priorities over different possible clinical scenarios and incorporate them into dose optimization. The enhanced control over the final plan may greatly facilitate the IMRT treatment planning process

  6. An interactive beam-weight optimization tool for three-dimensional radiotherapy treatment planning

    International Nuclear Information System (INIS)

    Burba, S.; Gardey, K.; Nadobny, J.; Stalling, D.; Seebass, M.; Beier, J.; Wust, P.; Budach, V.; Felix, R.

    1997-01-01

    Purpose: A computer software tool has been developed to aid the treatment planner in selecting beam weights for three-dimensional radiotherapy treatment planning. An approach to plan optimization has been made that is based on the use of an iterative feasibility search algorithm combined with a quadratic convergence method that seeks a set of beam weights which satisfies all the dose constraints set by the planner. Materials and Methods: A FORTRAN module for dose calculation for radiotherapy (a VOXELPLAN modification) has been integrated into an object-oriented Silicon Graphics TM platform in an IRIS Inventor environment on basis of the OpenGL which up to now has been exclusively used for the calculation of E-field distributions in hyperthermia (HyperPlan TM ). After the successful calculation and representation of the dose distribution in the Silicon Graphics TM platform, an algorithm involving the minimization method according to the principle of quadratic convergence was developed for optimizing beam weights of a number of pre-calculated fields. The verification of the algorithms for dose calculation and dose optimization has been realized by use of a standardized interface to the program VIRTUOS as well as by the collapsed cone algorithm implemented in the commercial treatment planning system Helax TMS TM . Results: The search algorithm allows the planner to incorporate relative importance weightings to target volumes and anatomical structures, specifying, for example, that a dose constraint to the spinal cord is much more crucial to the overall evaluation of a treatment plan than a dose constraint to otherwise uninvolved soft tissue. In most cases the applied minimization method according to the model of Davidon-Fletcher-Powell showed ultimate fast convergence for a general function f(x) with continuous second derivatives and fast convergence for a positive definite quadratic function. In other cases, however, the absence of an acceptable solution may indicate

  7. Role of functional imaging in treatment plan optimization of stereotactic body radiation therapy for liver cancer.

    Science.gov (United States)

    De Bari, Berardino; Jumeau, Raphael; Deantonio, Letizia; Adib, Salim; Godin, Sarah; Zeverino, Michele; Moeckli, Raphael; Bourhis, Jean; Prior, John O; Ozsahin, Mahmut

    2016-10-13

    We report the first known instance of the clinical use of 99mTc-mebrofenin hepatobiliary scintigraphy (HBS) for the optimization of radiotherapy treatment planning and for the follow-up of acute toxicity in a patient undergoing stereotactic body radiation therapy for hepatocellular carcinoma. In our experience, HBS allowed the identification and the sparing of more functioning liver areas, thus potentially reducing the risk of radiation-induced liver toxicity.

  8. Penalized likelihood fluence optimization with evolutionary components for intensity modulated radiation therapy treatment planning

    International Nuclear Information System (INIS)

    Baydush, Alan H.; Marks, Lawrence B.; Das, Shiva K.

    2004-01-01

    A novel iterative penalized likelihood algorithm with evolutionary components for the optimization of beamlet fluences for intensity modulated radiation therapy (IMRT) is presented. This algorithm is designed to be flexible in terms of the objective function and automatically escalates dose, as long as the objective function increases and all constraints are met. For this study, the objective function employed was the product of target equivalent uniform dose (EUD) and fraction of target tissue within set homogeneity constraints. The likelihood component of the algorithm iteratively attempts to minimize the mean squared error between a homogeneous dose prescription and the actual target dose distribution. The updated beamlet fluences are then adjusted via a quadratic penalty function that is based on the dose-volume histogram (DVH) constraints of the organs at risk. The evolutionary components were included to prevent the algorithm from converging to a local maximum. The algorithm was applied to a prostate cancer dataset, with especially difficult DVH constraints on bladder, rectum, and femoral heads. Dose distributions were generated for manually selected sets of three-, four-, five-, and seven-field treatment plans. Additionally, a global search was performed to find the optimal orientations for an axial three-beam plan. The results from this optimal orientation set were compared to results for manually selected orientation (gantry angle) sets of 3- (0 deg., 90 deg., 270 deg. ), 4- (0 deg., 90 deg., 180 deg., 270 deg. ), 5- (0 deg., 50 deg., 130 deg., 230 deg., 310 deg.), and 7- (0 deg., 40 deg., 90 deg., 140 deg., 230 deg., 270 deg., 320 deg. ) field axial treatment plans. For all the plans generated, all DVH constraints were met and average optimization computation time was approximately 30 seconds. For the manually selected orientations, the algorithm was successful in providing a relatively homogeneous target dose distribution, while simultaneously satisfying

  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. High-resolution temperature-based optimization for hyperthermia treatment planning

    International Nuclear Information System (INIS)

    Kok, H P; Haaren, P M A van; Kamer, J B Van de; Wiersma, J; Dijk, J D P Van; Crezee, J

    2005-01-01

    In regional hyperthermia, optimization techniques are valuable in order to obtain amplitude/phase settings for the applicators to achieve maximal tumour heating without toxicity to normal tissue. We implemented a temperature-based optimization technique and maximized tumour temperature with constraints on normal tissue temperature to prevent hot spots. E-field distributions are the primary input for the optimization method. Due to computer limitations we are restricted to a resolution of 1 x 1 x 1 cm 3 for E-field calculations, too low for reliable treatment planning. A major problem is the fact that hot spots at low-resolution (LR) do not always correspond to hot spots at high-resolution (HR), and vice versa. Thus, HR temperature-based optimization is necessary for adequate treatment planning and satisfactory results cannot be obtained with LR strategies. To obtain HR power density (PD) distributions from LR E-field calculations, a quasi-static zooming technique has been developed earlier at the UMC Utrecht. However, quasi-static zooming does not preserve phase information and therefore it does not provide the HR E-field information required for direct HR optimization. We combined quasi-static zooming with the optimization method to obtain a millimetre resolution temperature-based optimization strategy. First we performed a LR (1 cm) optimization and used the obtained settings to calculate the HR (2 mm) PD and corresponding HR temperature distribution. Next, we performed a HR optimization using an estimation of the new HR temperature distribution based on previous calculations. This estimation is based on the assumption that the HR and LR temperature distributions, though strongly different, respond in a similar way to amplitude/phase steering. To verify the newly obtained settings, we calculate the corresponding HR temperature distribution. This method was applied to several clinical situations and found to work very well. Deviations of this estimation method for

  11. Automated gamma knife radiosurgery treatment planning with image registration, data-mining, and Nelder-Mead simplex optimization

    International Nuclear Information System (INIS)

    Lee, Kuan J.; Barber, David C.; Walton, Lee

    2006-01-01

    Gamma knife treatments are usually planned manually, requiring much expertise and time. We describe a new, fully automatic method of treatment planning. The treatment volume to be planned is first compared with a database of past treatments to find volumes closely matching in size and shape. The treatment parameters of the closest matches are used as starting points for the new treatment plan. Further optimization is performed with the Nelder-Mead simplex method: the coordinates and weight of the isocenters are allowed to vary until a maximally conformal plan specific to the new treatment volume is found. The method was tested on a randomly selected set of 10 acoustic neuromas and 10 meningiomas. Typically, matching a new volume took under 30 seconds. The time for simplex optimization, on a 3 GHz Xeon processor, ranged from under a minute for small volumes ( 30 000 cubic mm,>20 isocenters). In 8/10 acoustic neuromas and 8/10 meningiomas, the automatic method found plans with conformation number equal or better than that of the manual plan. In 4/10 acoustic neuromas and 5/10 meningiomas, both overtreatment and undertreatment ratios were equal or better in automated plans. In conclusion, data-mining of past treatments can be used to derive starting parameters for treatment planning. These parameters can then be computer optimized to give good plans automatically

  12. 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

  13. Development of a neuro-fuzzy technique for automated parameter optimization of inverse treatment planning

    International Nuclear Information System (INIS)

    Stieler, Florian; Yan, Hui; Lohr, Frank; Wenz, Frederik; Yin, Fang-Fang

    2009-01-01

    Parameter optimization in the process of inverse treatment planning for intensity modulated radiation therapy (IMRT) is mainly conducted by human planners in order to create a plan with the desired dose distribution. To automate this tedious process, an artificial intelligence (AI) guided system was developed and examined. The AI system can automatically accomplish the optimization process based on prior knowledge operated by several fuzzy inference systems (FIS). Prior knowledge, which was collected from human planners during their routine trial-and-error process of inverse planning, has first to be 'translated' to a set of 'if-then rules' for driving the FISs. To minimize subjective error which could be costly during this knowledge acquisition process, it is necessary to find a quantitative method to automatically accomplish this task. A well-developed machine learning technique, based on an adaptive neuro fuzzy inference system (ANFIS), was introduced in this study. Based on this approach, prior knowledge of a fuzzy inference system can be quickly collected from observation data (clinically used constraints). The learning capability and the accuracy of such a system were analyzed by generating multiple FIS from data collected from an AI system with known settings and rules. Multiple analyses showed good agreements of FIS and ANFIS according to rules (error of the output values of ANFIS based on the training data from FIS of 7.77 ± 0.02%) and membership functions (3.9%), thus suggesting that the 'behavior' of an FIS can be propagated to another, based on this process. The initial experimental results on a clinical case showed that ANFIS is an effective way to build FIS from practical data, and analysis of ANFIS and FIS with clinical cases showed good planning results provided by ANFIS. OAR volumes encompassed by characteristic percentages of isodoses were reduced by a mean of between 0 and 28%. The study demonstrated a feasible way

  14. Development of a neuro-fuzzy technique for automated parameter optimization of inverse treatment planning

    Directory of Open Access Journals (Sweden)

    Wenz Frederik

    2009-09-01

    Full Text Available Abstract Background Parameter optimization in the process of inverse treatment planning for intensity modulated radiation therapy (IMRT is mainly conducted by human planners in order to create a plan with the desired dose distribution. To automate this tedious process, an artificial intelligence (AI guided system was developed and examined. Methods The AI system can automatically accomplish the optimization process based on prior knowledge operated by several fuzzy inference systems (FIS. Prior knowledge, which was collected from human planners during their routine trial-and-error process of inverse planning, has first to be "translated" to a set of "if-then rules" for driving the FISs. To minimize subjective error which could be costly during this knowledge acquisition process, it is necessary to find a quantitative method to automatically accomplish this task. A well-developed machine learning technique, based on an adaptive neuro fuzzy inference system (ANFIS, was introduced in this study. Based on this approach, prior knowledge of a fuzzy inference system can be quickly collected from observation data (clinically used constraints. The learning capability and the accuracy of such a system were analyzed by generating multiple FIS from data collected from an AI system with known settings and rules. Results Multiple analyses showed good agreements of FIS and ANFIS according to rules (error of the output values of ANFIS based on the training data from FIS of 7.77 ± 0.02% and membership functions (3.9%, thus suggesting that the "behavior" of an FIS can be propagated to another, based on this process. The initial experimental results on a clinical case showed that ANFIS is an effective way to build FIS from practical data, and analysis of ANFIS and FIS with clinical cases showed good planning results provided by ANFIS. OAR volumes encompassed by characteristic percentages of isodoses were reduced by a mean of between 0 and 28%. Conclusion The

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

    Energy Technology Data Exchange (ETDEWEB)

    Kontaxis, C; Bol, G; Lagendijk, J; Raaymakers, B [University Medical Center Utrecht, Utrecht (Netherlands); Breedveld, S; Sharfo, A; Heijmen, B [Erasmus University Medical Center Rotterdam, Rotterdam (Netherlands)

    2016-06-15

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

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

    International Nuclear Information System (INIS)

    Kontaxis, C; Bol, G; Lagendijk, J; Raaymakers, B; Breedveld, S; Sharfo, A; Heijmen, B

    2016-01-01

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

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

    International Nuclear Information System (INIS)

    Yarmand, Hamed; Winey, Brian; Craft, David

    2013-01-01

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

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

    International Nuclear Information System (INIS)

    Deasy, J.

    2015-01-01

    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. Optimal 3-D conformal treatment planning of posterior lateral supratentorial tumors

    International Nuclear Information System (INIS)

    Gius, David; Klein, Eric; Oehmke, Fred

    1995-01-01

    Purpose/Objective: The ability to treat the brain to greater doses is limited by normal brain tissue tolerance. With the use of 3-dimensional treatment planning dose escalation will result in increased target dose while sparing normal tissue. Treatment of the supratentorial region of the brain presents several unique difficulties due to the changing contour of the calvarium, which are especially noticeable with treatment to the posterior lateral quadrant. The use of a single wedge beam is sub-optimal and a more appropriate solution would employ a two tier wedge arrangement to better conform the isodoses around the target volume. In the past it has only been possible to use a single wedge during treatment with a single port, however, the dynamic wedge presents the opportunity to employ a two tier wedge system by simultaneously using conventional and dynamic wedging. Methods and Materials: An anthropomorphic phantom with a lesion located in the posterior lateral aspect of the brain where the external surface slopes at a maximum was configured. CT generated contours outlined the external surface, normal anatomy, gross tumor, and target volumes. We used the beam's-eye-view projection from the 3D planning system to derive the conformal beams. A standard opposed lateral and posterior oblique wedge pair beam arrangements, were compared to a three field technique (PA, lateral, and vertex) which used both a single wedge arrangement and a two-tier wedge plan. Treatment plans were evaluated by calculating isodose distribution, DVH, TCP, and NTCP. Each beam arrangement was used to treat our phantom with film placed in between the phantom layers at the tumor levels to confirm the accuracy of the 3-D system calculations. Results: The three field, two-tier wedge technique isodose distribution was significantly superior when compared to the standard 2-D plans, and a moderate improvement over the three field, single wedge technique in terms of conforming dose to the tumor and

  1. 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.

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

    International Nuclear Information System (INIS)

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

    2001-01-01

    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-meter 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

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

    Science.gov (United States)

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

    2018-01-01

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

  4. 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.

  5. 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.

  6. Multiobjective optimization with a modified simulated annealing algorithm for external beam radiotherapy treatment planning

    International Nuclear Information System (INIS)

    Aubry, Jean-Francois; Beaulieu, Frederic; Sevigny, Caroline; Beaulieu, Luc; Tremblay, Daniel

    2006-01-01

    Inverse planning in external beam radiotherapy often requires a scalar objective function that incorporates importance factors to mimic the planner's preferences between conflicting objectives. Defining those importance factors is not straightforward, and frequently leads to an iterative process in which the importance factors become variables of the optimization problem. In order to avoid this drawback of inverse planning, optimization using algorithms more suited to multiobjective optimization, such as evolutionary algorithms, has been suggested. However, much inverse planning software, including one based on simulated annealing developed at our institution, does not include multiobjective-oriented algorithms. This work investigates the performance of a modified simulated annealing algorithm used to drive aperture-based intensity-modulated radiotherapy inverse planning software in a multiobjective optimization framework. For a few test cases involving gastric cancer patients, the use of this new algorithm leads to an increase in optimization speed of a little more than a factor of 2 over a conventional simulated annealing algorithm, while giving a close approximation of the solutions produced by a standard simulated annealing. A simple graphical user interface designed to facilitate the decision-making process that follows an optimization is also presented

  7. Evaluation of treatment plan quality of IMRT and VMAT with and without flattening filter using Pareto optimal fronts.

    Science.gov (United States)

    Lechner, Wolfgang; Kragl, Gabriele; Georg, Dietmar

    2013-12-01

    To investigate the differences in treatment plan quality of IMRT and VMAT with and without flattening filter using Pareto optimal fronts, for two treatment sites of different anatomic complexity. Pareto optimal fronts (POFs) were generated for six prostate and head-and-neck cancer patients by stepwise reduction of the constraint (during the optimization process) of the primary organ-at-risk (OAR). 9-static field IMRT and 360°-single-arc VMAT plans with flattening filter (FF) and without flattening filter (FFF) were compared. The volume receiving 5 Gy or more (V5 Gy) was used to estimate the low dose exposure. Furthermore, the number of monitor units (MUs) and measurements of the delivery time (T) were used to assess the efficiency of the treatment plans. A significant increase in MUs was found when using FFF-beams while the treatment plan quality was at least equivalent to the FF-beams. T was decreased by 18% for prostate for IMRT with FFF-beams and by 4% for head-and-neck cases, but increased by 22% and 16% for VMAT. A reduction of up to 5% of V5 Gy was found for IMRT prostate cases with FFF-beams. The evaluation of the POFs showed an at least comparable treatment plan quality of FFF-beams compared to FF-beams for both treatment sites and modalities. For smaller targets the advantageous characteristics of FFF-beams could be better exploited. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  8. Optimization of a novel large field of view distortion phantom for MR-only treatment planning.

    Science.gov (United States)

    Price, Ryan G; Knight, Robert A; Hwang, Ken-Pin; Bayram, Ersin; Nejad-Davarani, Siamak P; Glide-Hurst, Carri K

    2017-07-01

    MR-only treatment planning requires images of high geometric fidelity, particularly for large fields of view (FOV). However, the availability of large FOV distortion phantoms with analysis software is currently limited. This work sought to optimize a modular distortion phantom to accommodate multiple bore configurations and implement distortion characterization in a widely implementable solution. To determine candidate materials, 1.0 T MR and CT images were acquired of twelve urethane foam samples of various densities and strengths. Samples were precision-machined to accommodate 6 mm diameter paintballs used as landmarks. Final material candidates were selected by balancing strength, machinability, weight, and cost. Bore sizes and minimum aperture width resulting from couch position were tabulated from the literature (14 systems, 5 vendors). Bore geometry and couch position were simulated using MATLAB to generate machine-specific models to optimize the phantom build. Previously developed software for distortion characterization was modified for several magnet geometries (1.0 T, 1.5 T, 3.0 T), compared against previously published 1.0 T results, and integrated into the 3D Slicer application platform. All foam samples provided sufficient MR image contrast with paintball landmarks. Urethane foam (compressive strength ∼1000 psi, density ~20 lb/ft 3 ) was selected for its accurate machinability and weight characteristics. For smaller bores, a phantom version with the following parameters was used: 15 foam plates, 55 × 55 × 37.5 cm 3 (L×W×H), 5,082 landmarks, and weight ~30 kg. To accommodate > 70 cm wide bores, an extended build used 20 plates spanning 55 × 55 × 50 cm 3 with 7,497 landmarks and weight ~44 kg. Distortion characterization software was implemented as an external module into 3D Slicer's plugin framework and results agreed with the literature. The design and implementation of a modular, extendable distortion phantom was optimized for several bore

  9. Hyperthermia treatment planning

    International Nuclear Information System (INIS)

    Lagendijk, J.J.W.

    2000-01-01

    The development of hyperthermia, the treatment of tumours with elevated temperatures in the range of 40-44 deg. C with treatment times over 30 min, greatly benefits from the development of hyperthermia treatment planning. This review briefly describes the state of the art in hyperthermia technology, followed by an overview of the developments in hyperthermia treatment planning. It particularly highlights the significant problems encountered with heating realistic tissue volumes and shows how treatment planning can help in designing better heating technology. Hyperthermia treatment planning will ultimately provide information about the actual temperature distributions obtained and thus the tumour control probabilities to be expected. This will improve our understanding of the present clinical results of thermoradiotherapy and thermochemotherapy, and will greatly help both in optimizing clinical heating technology and in designing optimal clinical trials. (author)

  10. 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

  11. 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.

  12. Optimization of tomotherapy treatment planning for patients with bilateral hip prostheses.

    Science.gov (United States)

    Chapman, David; Smith, Shaun; Barnett, Rob; Bauman, Glenn; Yartsev, Slav

    2014-02-04

    To determine the effect of different imaging options and the most efficient imaging strategy for treatment planning of patients with hip prostheses. The planning kilovoltage CT (kVCT) and daily megavoltage CT (MVCT) studies for three prostate cancer patients with bilateral hip prostheses were used for creating hybrid kVCT/MVCT image sets. Treatment plans were created for kVCT images alone, hybrid kVCT/MVCT images, and MVCT images alone using the same dose prescription and planning parameters. The resulting dose volume histograms were compared. The orthopedic metal artifact reduction (O-MAR) reconstruction tool for kVCT images and different MVCT options were investigated with a water tank fit with double hip prostheses. Treatment plans were created for all imaging options and calculated dose was compared with the one measured by a pin-point ion chamber. On average for three patients, the D35% for the bladder was 8% higher in plans based on MVCT images and 7% higher in plans based on hybrid images, compared to the plans based on kVCT images alone. Likewise, the D35% for the rectum was 3% higher than the kVCT based plan for both hybrid and MVCT plans. The average difference in planned D99% in the PTV compared to kVCT plans was 0.9% and 0.1% for MVCT and hybrid plans, respectively. For the water tank with hip prostheses phantom, the kVCT plan with O-MAR correction applied showed better agreement between the measured and calculated dose than the original image set, with a difference of -1.9% compared to 3.3%. The measured doses for the MVCT plans were lower than the calculated dose due to image size limitations. The best agreement was for the kVCT/MVCT hybrid plans with the difference between calculated and measured dose around 1%. MVCT image provides better visualization of patient anatomy and hybrid kVCT/MVCT study enables more accurate calculations using updated MVCT relative electron density calibration.

  13. Optimization of tomotherapy treatment planning for patients with bilateral hip prostheses

    International Nuclear Information System (INIS)

    Chapman, David; Smith, Shaun; Barnett, Rob; Bauman, Glenn; Yartsev, Slav

    2014-01-01

    To determine the effect of different imaging options and the most efficient imaging strategy for treatment planning of patients with hip prostheses. The planning kilovoltage CT (kVCT) and daily megavoltage CT (MVCT) studies for three prostate cancer patients with bilateral hip prostheses were used for creating hybrid kVCT/MVCT image sets. Treatment plans were created for kVCT images alone, hybrid kVCT/MVCT images, and MVCT images alone using the same dose prescription and planning parameters. The resulting dose volume histograms were compared. The orthopedic metal artifact reduction (O-MAR) reconstruction tool for kVCT images and different MVCT options were investigated with a water tank fit with double hip prostheses. Treatment plans were created for all imaging options and calculated dose was compared with the one measured by a pin-point ion chamber. On average for three patients, the D 35% for the bladder was 8% higher in plans based on MVCT images and 7% higher in plans based on hybrid images, compared to the plans based on kVCT images alone. Likewise, the D 35% for the rectum was 3% higher than the kVCT based plan for both hybrid and MVCT plans. The average difference in planned D99% in the PTV compared to kVCT plans was 0.9% and 0.1% for MVCT and hybrid plans, respectively. For the water tank with hip prostheses phantom, the kVCT plan with O-MAR correction applied showed better agreement between the measured and calculated dose than the original image set, with a difference of -1.9% compared to 3.3%. The measured doses for the MVCT plans were lower than the calculated dose due to image size limitations. The best agreement was for the kVCT/MVCT hybrid plans with the difference between calculated and measured dose around 1%. MVCT image provides better visualization of patient anatomy and hybrid kVCT/MVCT study enables more accurate calculations using updated MVCT relative electron density calibration

  14. Multicriteria Optimization in Intensity-Modulated Radiation Therapy Treatment Planning for Locally Advanced Cancer of the Pancreatic Head

    International Nuclear Information System (INIS)

    Hong, Theodore S.; Craft, David L.; Carlsson, Fredrik; Bortfeld, Thomas R.

    2008-01-01

    Purpose: Intensity-modulated radiation therapy (IMRT) affords the potential to decrease radiation therapy-associated toxicity by creating highly conformal dose distributions. However, the inverse planning process can create a suboptimal plan despite meeting all constraints. Multicriteria optimization (MCO) may reduce the time-consuming iteration loop necessary to develop a satisfactory plan while providing information regarding trade-offs between different treatment planning goals. In this exploratory study, we examine the feasibility and utility of MCO in physician plan selection in patients with locally advanced pancreatic cancer (LAPC). Methods and Materials: The first 10 consecutive patients with LAPC treated with IMRT were evaluated. A database of plans (Pareto surface) was created that met the inverse planning goals. The physician then navigated to an 'optimal' plan from the point on the Pareto surface at which kidney dose was minimized. Results: Pareto surfaces were created for all 10 patients. A physician was able to select a plan from the Pareto surface within 10 minutes for all cases. Compared with the original (treated) IMRT plans, the plan selected from the Pareto surface had a lower stomach mean dose in 9 of 10 patients, although often at the expense of higher kidney dose than with the treated plan. Conclusion: The MCO is feasible in patients with LAPC and allows the physician to choose a satisfactory plan quickly. Generally, when given the opportunity, the physician will choose a plan with a lower stomach dose. The MCO enables a physician to provide greater active clinical input into the IMRT planning process

  15. 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.

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

    International Nuclear Information System (INIS)

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

    2015-01-01

    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. (paper)

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

    International Nuclear Information System (INIS)

    Das, Shiva

    2009-01-01

    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/rectum EUDs were

  18. Poster — Thur Eve — 69: Computational Study of DVH-guided Cancer Treatment Planning Optimization Methods

    Energy Technology Data Exchange (ETDEWEB)

    Ghomi, Pooyan Shirvani; Zinchenko, Yuriy [University of Calgary, Department of Mathematics and Statistics (Canada)

    2014-08-15

    Purpose: To compare methods to incorporate the Dose Volume Histogram (DVH) curves into the treatment planning optimization. Method: The performance of three methods, namely, the conventional Mixed Integer Programming (MIP) model, a convex moment-based constrained optimization approach, and an unconstrained convex moment-based penalty approach, is compared using anonymized data of a prostate cancer patient. Three plans we generated using the corresponding optimization models. Four Organs at Risk (OARs) and one Tumor were involved in the treatment planning. The OARs and Tumor were discretized into total of 50,221 voxels. The number of beamlets was 943. We used commercially available optimization software Gurobi and Matlab to solve the models. Plan comparison was done by recording the model runtime followed by visual inspection of the resulting dose volume histograms. Conclusion: We demonstrate the effectiveness of the moment-based approaches to replicate the set of prescribed DVH curves. The unconstrained convex moment-based penalty approach is concluded to have the greatest potential to reduce the computational effort and holds a promise of substantial computational speed up.

  19. WE-D-BRB-02: Proton Treatment Planning and Beam Optimization

    Energy Technology Data Exchange (ETDEWEB)

    Pankuch, M. [Northwestern Medicine Proton Center (United States)

    2016-06-15

    The goal of this session is to review the physics of proton therapy, treatment planning techniques, and the use of volumetric imaging in proton therapy. The course material covers the physics of proton interaction with matter and physical characteristics of clinical proton beams. It will provide information on proton delivery systems and beam delivery techniques for double scattering (DS), uniform scanning (US), and pencil beam scanning (PBS). The session covers the treatment planning strategies used in DS, US, and PBS for various anatomical sites, methods to address uncertainties in proton therapy and uncertainty mitigation to generate robust treatment plans. It introduces the audience to the current status of image guided proton therapy and clinical applications of CBCT for proton therapy. It outlines the importance of volumetric imaging in proton therapy. Learning Objectives: Gain knowledge in proton therapy physics, and treatment planning for proton therapy including intensity modulated proton therapy. The current state of volumetric image guidance equipment in proton therapy. Clinical applications of CBCT and its advantage over orthogonal imaging for proton therapy. B. Teo, B.K Teo had received travel funds from IBA in 2015.

  20. Improving CT quality with optimized image parameters for radiation treatment planning and delivery guidance

    Directory of Open Access Journals (Sweden)

    Guang-Pei Chen

    2017-10-01

    Conclusion: CT image quality can be improved with the IQE protocols created in this study, to provide better soft tissue contrast, which would be beneficial for use in radiation therapy, e.g., for planning data acquisition or for IGRT for hypo-fractionated treatments.

  1. Flight plan optimization

    Science.gov (United States)

    Dharmaseelan, Anoop; Adistambha, Keyne D.

    2015-05-01

    Fuel cost accounts for 40 percent of the operating cost of an airline. Fuel cost can be minimized by planning a flight on optimized routes. The routes can be optimized by searching best connections based on the cost function defined by the airline. The most common algorithm that used to optimize route search is Dijkstra's. Dijkstra's algorithm produces a static result and the time taken for the search is relatively long. This paper experiments a new algorithm to optimize route search which combines the principle of simulated annealing and genetic algorithm. The experimental results of route search, presented are shown to be computationally fast and accurate compared with timings from generic algorithm. The new algorithm is optimal for random routing feature that is highly sought by many regional operators.

  2. Dose-volume histograms for optimization of treatment plans illustrated by the example of oesophagus carcinoma

    International Nuclear Information System (INIS)

    Roth, J.; Huenig, R.; Huegli, C.

    1995-01-01

    Using the example of oesophagus carcinoma, dose-volume histograms for diverse treatment techniques are calculated and judged by means of multiplanar isodose representations. The selected treatment plans are ranked with the aid of the dose-volume histograms. We distinguish the tissue inside and outside of the target volume. The description of the spatial dose distribution in dependence of the different volumes and the respective fractions of the tumor dose therein with the help of dose-volume histograms brings about a correlation between the physical parameters and the biological effects. In addition one has to bear in mind the consequences of measures that influence the reaction and the side-effects of radiotherapy (e.g. chemotherapy), i.e. the recuperation of the tissues that were irradiated intentionally or inevitably. Taking all that into account it is evident that the dose-volume histograms are a powerful tool for assessing the quality of treatment plans. (orig./MG) [de

  3. The relationship between the bladder volume and optimal treatment planning in definitive radiotherapy for localized prostate cancer

    International Nuclear Information System (INIS)

    Nakamura, Naoki; Sekiguchi, Kenji; Akahane, Keiko; Shikama, Naoto; Takahashi, Osamu; Hama, Yukihiro; Nakagawa, Keiichi

    2012-01-01

    Background and purpose: There is no current consensus regarding the optimal bladder volumes in definitive radiotherapy for localized prostate cancer. The aim of this study was to clarify the relationship between the bladder volume and optimal treatment planning in radiotherapy for localized prostate cancer. Material and methods: Two hundred and forty-three patients underwent definitive radiotherapy with helical tomotherapy for intermediate- and high-risk localized prostate cancer. The prescribed dose defined as 95 % of the planning target volume (PTV) receiving 100 % of the prescription dose was 76 Gy in 38 fractions. The clinical target volume (CTV) was defined as the prostate with a 5-mm margin and 2 cm of the proximal seminal vesicle. The PTV was defined as the CTV with a 5-mm margin. Treatment plans were optimized to satisfy the dose constraints defined by in-house protocols for PTV and organs at risk (rectum wall, bladder wall, sigmoid colon and small intestine). If all dose constraints were satisfied, the plan was defined as an optimal plan (OP). Results: An OP was achieved with 203 patients (84%). Mean bladder volume (± 1 SD) was 266 ml (± 130 ml) among those with an OP and 214 ml (±130 ml) among those without an OP (p = 0.02). Logistic regression analysis also showed that bladder volumes below 150 ml decreased the possibility of achieving an OP. However, the percentage of patients with an OP showed a plateau effect at bladder volumes above 150 ml. Conclusions. Bladder volume is a significant factor affecting OP rates. However, our results suggest that bladder volumes exceeding 150 ml may not help meet planning dose constraints

  4. 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.

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

    International Nuclear Information System (INIS)

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

    2015-01-01

    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

  6. 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.

  7. Treatment planning for heavy ion radiotherapy: physical beam model and dose optimization

    International Nuclear Information System (INIS)

    Kraemer, M.; Haberer, T.; Kraft, G.; Schardt, D.; Weber, U.

    2000-09-01

    We describe a novel code system, TRiP, dedicated to the planning of radiotherapy with energetic ions, in particular 12 C. The software is designed to cooperate with three-dimensional active dose shaping devices like the GSI raster scan system. This unique beam delivery system allows to select any combination from a list of 253 individual beam energies, 7 different beam spot sizes and 15 intensity levels. The software includes a beam model adapted to and verified for carbon ions. Inverse planning techniques are implemented in order to obtain a uniform target dose distribution from clinical input data, i.e. CT images and patient contours. This implies the automatic generation of intensity modulated fields of heavy ions with as many as 40000 raster points, where each point corresponds to a specific beam position, energy and particle fluence. This set of data is directly passed to the beam delivery and control system. The treatment planning code is in clinical use since the start of the GSI pilot project in December 1997. To this end 48 patients have been successfully planned and treated. (orig.)

  8. Treatment planning for heavy-ion radiotherapy: physical beam model and dose optimization

    Science.gov (United States)

    Krämer, M.; Jäkel, O.; Haberer, T.; Kraft, G.; Schardt, D.; Weber, U.

    2000-11-01

    We describe a novel code system, TRiP, dedicated to the planning of radiotherapy with energetic ions, in particular 12C. The software is designed to cooperate with three-dimensional active dose shaping devices like the GSI raster scan system. This unique beam delivery system allows us to select any combination from a list of 253 individual beam energies, 7 different beam spot sizes and 15 intensity levels. The software includes a beam model adapted to and verified for carbon ions. Inverse planning techniques are implemented in order to obtain a uniform target dose distribution from clinical input data, i.e. CT images and patient contours. This implies the automatic generation of intensity modulated fields of heavy ions with as many as 40 000 raster points, where each point corresponds to a specific beam position, energy and particle fluence. This set of data is directly passed to the beam delivery and control system. The treatment planning code has been in clinical use since the start of the GSI pilot project in December 1997. Forty-eight patients have been successfully planned and treated.

  9. 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.

  10. Computerized radiation treatment planning

    International Nuclear Information System (INIS)

    Laarse, R. van der.

    1981-01-01

    Following a general introduction, a chain consisting of three computer programs which has been developed for treatment planning of external beam radiotherapy without manual intervention is described. New score functions used for determination of optimal incidence directions are presented and the calculation of the position of the isocentre for each optimum combination of incidence directions is explained. A description of how a set of applicators, covering fields with dimensions of 4 to 20 cm, for the 6 to 20 MeV electron beams of a MEL SL75-20 linear accelerator was developed, is given. A computer program for three dimensional electron beam treatment planning is presented. A microprocessor based treatment planning system for the Selectron remote controlled afterloading system for intracavitary radiotherapy is described. The main differences in treatment planning procedures for external beam therapy with neutrons instead of photons is discussed. A microprocessor based densitometer for plotting isodensity lines in film dosimetry is described. A computer program for dose planning of brachytherapy is presented. Finally a general discussion about the different aspects of computerized treatment planning as presented in this thesis is given. (Auth.)

  11. WE-AB-209-12: Quasi Constrained Multi-Criteria Optimization for Automated Radiation Therapy Treatment Planning

    Energy Technology Data Exchange (ETDEWEB)

    Watkins, W.T.; Siebers, J.V. [University of Virginia, Charlottesville, VA (United States)

    2016-06-15

    Purpose: To introduce quasi-constrained Multi-Criteria Optimization (qcMCO) for unsupervised radiation therapy optimization which generates alternative patient-specific plans emphasizing dosimetric tradeoffs and conformance to clinical constraints for multiple delivery techniques. Methods: For N Organs At Risk (OARs) and M delivery techniques, qcMCO generates M(N+1) alternative treatment plans per patient. Objective weight variations for OARs and targets are used to generate alternative qcMCO plans. For 30 locally advanced lung cancer patients, qcMCO plans were generated for dosimetric tradeoffs to four OARs: each lung, heart, and esophagus (N=4) and 4 delivery techniques (simple 4-field arrangements, 9-field coplanar IMRT, 27-field non-coplanar IMRT, and non-coplanar Arc IMRT). Quasi-constrained objectives included target prescription isodose to 95% (PTV-D95), maximum PTV dose (PTV-Dmax)< 110% of prescription, and spinal cord Dmax<45 Gy. The algorithm’s ability to meet these constraints while simultaneously revealing dosimetric tradeoffs was investigated. Statistically significant dosimetric tradeoffs were defined such that the coefficient of determination between dosimetric indices which varied by at least 5 Gy between different plans was >0.8. Results: The qcMCO plans varied mean dose by >5 Gy to ipsilateral lung for 24/30 patients, contralateral lung for 29/30 patients, esophagus for 29/30 patients, and heart for 19/30 patients. In the 600 plans computed without human interaction, average PTV-D95=67.4±3.3 Gy, PTV-Dmax=79.2±5.3 Gy, and spinal cord Dmax was >45 Gy in 93 plans (>50 Gy in 2/600 plans). Statistically significant dosimetric tradeoffs were evident in 19/30 plans, including multiple tradeoffs of at least 5 Gy between multiple OARs in 7/30 cases. The most common statistically significant tradeoff was increasing PTV-Dmax to reduce OAR dose (15/30 patients). Conclusion: The qcMCO method can conform to quasi-constrained objectives while revealing

  12. WE-AB-209-12: Quasi Constrained Multi-Criteria Optimization for Automated Radiation Therapy Treatment Planning

    International Nuclear Information System (INIS)

    Watkins, W.T.; Siebers, J.V.

    2016-01-01

    Purpose: To introduce quasi-constrained Multi-Criteria Optimization (qcMCO) for unsupervised radiation therapy optimization which generates alternative patient-specific plans emphasizing dosimetric tradeoffs and conformance to clinical constraints for multiple delivery techniques. Methods: For N Organs At Risk (OARs) and M delivery techniques, qcMCO generates M(N+1) alternative treatment plans per patient. Objective weight variations for OARs and targets are used to generate alternative qcMCO plans. For 30 locally advanced lung cancer patients, qcMCO plans were generated for dosimetric tradeoffs to four OARs: each lung, heart, and esophagus (N=4) and 4 delivery techniques (simple 4-field arrangements, 9-field coplanar IMRT, 27-field non-coplanar IMRT, and non-coplanar Arc IMRT). Quasi-constrained objectives included target prescription isodose to 95% (PTV-D95), maximum PTV dose (PTV-Dmax)< 110% of prescription, and spinal cord Dmax<45 Gy. The algorithm’s ability to meet these constraints while simultaneously revealing dosimetric tradeoffs was investigated. Statistically significant dosimetric tradeoffs were defined such that the coefficient of determination between dosimetric indices which varied by at least 5 Gy between different plans was >0.8. Results: The qcMCO plans varied mean dose by >5 Gy to ipsilateral lung for 24/30 patients, contralateral lung for 29/30 patients, esophagus for 29/30 patients, and heart for 19/30 patients. In the 600 plans computed without human interaction, average PTV-D95=67.4±3.3 Gy, PTV-Dmax=79.2±5.3 Gy, and spinal cord Dmax was >45 Gy in 93 plans (>50 Gy in 2/600 plans). Statistically significant dosimetric tradeoffs were evident in 19/30 plans, including multiple tradeoffs of at least 5 Gy between multiple OARs in 7/30 cases. The most common statistically significant tradeoff was increasing PTV-Dmax to reduce OAR dose (15/30 patients). Conclusion: The qcMCO method can conform to quasi-constrained objectives while revealing

  13. Teaching Treatment Planning.

    Science.gov (United States)

    Seligman, Linda

    1993-01-01

    Describes approach to teaching treatment planning that author has used successfully in both seminars and graduate courses. Clarifies nature and importance of systematic treatment planning, then describes context in which treatment planning seems more effectively taught, and concludes with step-by-step plan for teaching treatment planning.…

  14. Simultaneous optimization of sequential IMRT plans

    International Nuclear Information System (INIS)

    Popple, Richard A.; Prellop, Perri B.; Spencer, Sharon A.; Santos, Jennifer F. de los; Duan, Jun; Fiveash, John B.; Brezovich, Ivan A.

    2005-01-01

    Radiotherapy often comprises two phases, in which irradiation of a volume at risk for microscopic disease is followed by a sequential dose escalation to a smaller volume either at a higher risk for microscopic disease or containing only gross disease. This technique is difficult to implement with intensity modulated radiotherapy, as the tolerance doses of critical structures must be respected over the sum of the two plans. Techniques that include an integrated boost have been proposed to address this problem. However, clinical experience with such techniques is limited, and many clinicians are uncomfortable prescribing nonconventional fractionation schemes. To solve this problem, we developed an optimization technique that simultaneously generates sequential initial and boost IMRT plans. We have developed an optimization tool that uses a commercial treatment planning system (TPS) and a high level programming language for technical computing. The tool uses the TPS to calculate the dose deposition coefficients (DDCs) for optimization. The DDCs were imported into external software and the treatment ports duplicated to create the boost plan. The initial, boost, and tolerance doses were specified and used to construct cost functions. The initial and boost plans were optimized simultaneously using a gradient search technique. Following optimization, the fluence maps were exported to the TPS for dose calculation. Seven patients treated using sequential techniques were selected from our clinical database. The initial and boost plans used to treat these patients were developed independently of each other by dividing the tolerance doses proportionally between the initial and boost plans and then iteratively optimizing the plans until a summation that met the treatment goals was obtained. We used the simultaneous optimization technique to generate plans that met the original planning goals. The coverage of the initial and boost target volumes in the simultaneously optimized

  15. An improved fast and elitist multi-objective genetic algorithm-ANSGA-II for multi-objective optimization of inverse radiotherapy treatment planning

    International Nuclear Information System (INIS)

    Cao Ruifen; Li Guoli; Song Gang; Zhao Pan; Lin Hui; Wu Aidong; Huang Chenyu; Wu Yican

    2007-01-01

    Objective: To provide a fast and effective multi-objective optimization algorithm for inverse radiotherapy treatment planning system. Methods: Non-dominated Sorting Genetic Algorithm-NSGA-II is a representative of multi-objective evolutionary optimization algorithms and excels the others. The paper produces ANSGA-II that makes use of advantage of NSGA-II, and uses adaptive crossover and mutation to improve its flexibility; according the character of inverse radiotherapy treatment planning, the paper uses the pre-known knowledge to generate individuals of every generation in the course of optimization, which enhances the convergent speed and improves efficiency. Results: The example of optimizing average dose of a sheet of CT, including PTV, OAR, NT, proves the algorithm could find satisfied solutions in several minutes. Conclusions: The algorithm could provide clinic inverse radiotherapy treatment planning system with selection of optimization algorithms. (authors)

  16. Optimization of stereotactically-guided conformal treatment planning of sellar and parasellar tumors, based on normal brain dose volume histograms

    International Nuclear Information System (INIS)

    Perks, Julian R.; Jalali, Rakesh; Cosgrove, Vivian P.; Adams, Elizabeth J.; Shepherd, Stephen F.; Warrington, Alan P.; Brada, Michael

    1999-01-01

    Purpose: To investigate the optimal treatment plan for stereo tactically-guided conformal radiotherapy (SCRT) of sellar and parasellar lesions, with respect to sparing normal brain tissue, in the context of routine treatment delivery, based on dose volume histogram analysis. Methods and Materials: Computed tomography (CT) data sets for 8 patients with sellar- and parasellar-based tumors (6 pituitary adenomas and 2 meningiomas) have been used in this study. Treatment plans were prepared for 3-coplanar and 3-, 4-, 6-, and 30-noncoplanar-field arrangements to obtain 95% isodose coverage of the planning target volume (PTV) for each plan. Conformal shaping was achieved by customized blocks generated with the beams eye view (BEV) facility. Dose volume histograms (DVH) were calculated for the normal brain (excluding the PTV), and comparisons made for normal tissue sparing for all treatment plans at ≥80%, ≥60%, and ≥40% of the prescribed dose. Results: The mean volume of normal brain receiving ≥80% and ≥60% of the prescribed dose decreased by 22.3% (range 14.8-35.1%, standard deviation σ = 7.5%) and 47.6% (range 25.8-69.1%, σ 13.2%), respectively, with a 4-field noncoplanar technique when compared with a conventional 3-field coplanar technique. Adding 2 further fields, from 4-noncoplanar to 6-noncoplanar fields reduced the mean normal brain volume receiving ≥80% of the prescribed dose by a further 4.1% (range -6.5-11.8%, σ = 6.4%), and the volume receiving ≥60% by 3.3% (range -5.5-12.2%, σ = 5.4%), neither of which were statistically significant. Each case must be considered individually however, as a wide range is seen in the volume spared when increasing the number of fields from 4 to 6. Comparing the 4- and 6-field noncoplanar techniques to a 30-field conformal field approach (simulating a dynamic arc plan) revealed near-equivalent normal tissue sparing. Conclusion: Four to six widely spaced, fixed-conformal fields provide the optimum class solution

  17. New Techniques for Optimal Treatment Planning for LINAC-based Sterotactic Radiosurgery

    International Nuclear Information System (INIS)

    Suh, Tae Suk

    1992-01-01

    Since LINAC-based stereotactic radiosurgery uses multiple noncoplanar arcs, three-dimensional dose evaluation and many beam parameters, a lengthy computation time is required to optimize even the simplest case by a trial and error. The basic approach presented in this paper is to show promising methods using an experimental optimization and an analytic optimization. The purpose of this paper is not to describe the detailed methods, but introduce briefly, proceeding research done currently or in near future. A more detailed description will be shown in ongoing published papers. Experimental optimization is based on two approaches. One is shaping the target volumes through the use of multiple isocenters determined from dose experience and testing. The other method is conformal therapy using a beam eye view technique and field shaping. The analytic approach is to adapt computer-aided design optimization in finding optimum irradiation parameters automatically

  18. 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.

  19. Optimization of the dose level for a given treatment plan to maximize the complication-free tumor cure

    International Nuclear Information System (INIS)

    Lind, B.K.; Mavroidis, P.; Hyoedynmaa, S.; Kappas, C.

    1999-01-01

    During the past decade, tumor and normal tissue reactions after radiotherapy have been increasingly quantified in radiobiological terms. For this purpose, response models describing the dependence of tumor and normal tissue reactions on the irradiated volume, heterogeneity of the delivered dose distribution and cell sensitivity variations can be taken into account. The probability of achieving a good treatment outcome can be increased by using an objective function such as P + , the probability of complication-free tumor control. A new procedure is presented, which quantifies P + from the dose delivery on 2D surfaces and 3D volumes and helps the user of any treatment planning system (TPS) to select the best beam orientations, the best beam modalities and the most suitable beam energies. The final step of selecting the prescribed dose level is made by a renormalization of the entire dose plan until the value of P + is maximized. The index P + makes use of clinically established dose-response parameters, for tumors and normal tissues of interest, in order to improve its clinical relevance. The results, using P + , are compared against the assessments of experienced medical physicists and radiation oncologists for two clinical cases. It is observed that when the absorbed dose level for a given treatment plan is increased, the treatment outcome first improves rapidly. As the dose approaches the tolerance of normal tissues the complication-free curve begins to drop. The optimal dose level is often just below this point and it depends on the geometry of each patient and target volume. Furthermore, a more conformal dose delivery to the target results in a higher control rate for the same complication level. This effect can be quantified by the increased value of the P + parameter. (orig.)

  20. The availability of the step optimization in Monaco planning system

    International Nuclear Information System (INIS)

    Kim, Dae Sup

    2014-01-01

    We present a method to reduce this gap and complete the treatment plan, to be made by the re-optimization is performed in the same conditions as the initial treatment plan different from Monaco treatment planning system. The optimization is carried in two steps when performing the inverse calculation for volumetric modulated radiation therapy or intensity modulated radiation therapy in Monaco treatment planning system. This study was the first plan with a complete optimization in two steps by performing all of the treatment plan, without changing the optimized condition from Step 1 to Step 2, a typical sequential optimization performed. At this time, the experiment was carried out with a pencil beam and Monte Carlo algorithm is applied In step 2. We compared initial plan and re-optimized plan with the same optimized conditions. And then evaluated the planning dose by measurement. When performing a re-optimization for the initial treatment plan, the second plan applied the step optimization. When the common optimization again carried out in the same conditions in the initial treatment plan was completed, the result is not the same. From a comparison of the treatment planning system, similar to the dose-volume the histogram showed a similar trend, but exhibit different values that do not satisfy the conditions best optimized dose, dose homogeneity and dose limits. Also showed more than 20% different in comparison dosimetry. If different dose algorithms, this measure is not the same out. The process of performing a number of trial and error, and you get to the ultimate goal of treatment planning optimization process. If carried out to optimize the completion of the initial trust only the treatment plan, we could be made of another treatment plan. The similar treatment plan could not satisfy to optimization results. When you perform re-optimization process, you will need to apply the step optimized conditions, making sure the dose distribution through the optimization

  1. Dose optimization based on linear programming implemented in a system for treatment planning in Monte Carlo

    International Nuclear Information System (INIS)

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

    2011-01-01

    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.

  2. WE-AB-207B-07: Dose Cloud: Generating “Big Data” for Radiation Therapy Treatment Plan Optimization Research

    Energy Technology Data Exchange (ETDEWEB)

    Folkerts, MM [University of Texas Southwestern Medical Center, Dallas, TX (United States); University of California San Diego, La Jolla, California (United States); Long, T; Tian, Z; Jia, X; Chen, M; Lu, W; Jiang, SB [University of Texas Southwestern Medical Center, Dallas, TX (United States); Radke, RJ [Rensselaer Polytechnic Institute, Troy, NY (United States)

    2016-06-15

    Purpose: To provide a tool to generate large sets of realistic virtual patient geometries and beamlet doses for treatment optimization research. This tool enables countless studies exploring the fundamental interplay between patient geometry, objective functions, weight selections, and achievable dose distributions for various algorithms and modalities. Methods: Generating realistic virtual patient geometries requires a small set of real patient data. We developed a normalized patient shape model (PSM) which captures organ and target contours in a correspondence-preserving manner. Using PSM-processed data, we perform principal component analysis (PCA) to extract major modes of variation from the population. These PCA modes can be shared without exposing patient information. The modes are re-combined with different weights to produce sets of realistic virtual patient contours. Because virtual patients lack imaging information, we developed a shape-based dose calculation (SBD) relying on the assumption that the region inside the body contour is water. SBD utilizes a 2D fluence-convolved scatter kernel, derived from Monte Carlo simulations, and can compute both full dose for a given set of fluence maps, or produce a dose matrix (dose per fluence pixel) for many modalities. Combining the shape model with SBD provides the data needed for treatment plan optimization research. Results: We used PSM to capture organ and target contours for 96 prostate cases, extracted the first 20 PCA modes, and generated 2048 virtual patient shapes by randomly sampling mode scores. Nearly half of the shapes were thrown out for failing anatomical checks, the remaining 1124 were used in computing dose matrices via SBD and a standard 7-beam protocol. As a proof of concept, and to generate data for later study, we performed fluence map optimization emphasizing PTV coverage. Conclusions: We successfully developed and tested a tool for creating customizable sets of virtual patients suitable for

  3. WE-AB-207B-07: Dose Cloud: Generating “Big Data” for Radiation Therapy Treatment Plan Optimization Research

    International Nuclear Information System (INIS)

    Folkerts, MM; Long, T; Tian, Z; Jia, X; Chen, M; Lu, W; Jiang, SB; Radke, RJ

    2016-01-01

    Purpose: To provide a tool to generate large sets of realistic virtual patient geometries and beamlet doses for treatment optimization research. This tool enables countless studies exploring the fundamental interplay between patient geometry, objective functions, weight selections, and achievable dose distributions for various algorithms and modalities. Methods: Generating realistic virtual patient geometries requires a small set of real patient data. We developed a normalized patient shape model (PSM) which captures organ and target contours in a correspondence-preserving manner. Using PSM-processed data, we perform principal component analysis (PCA) to extract major modes of variation from the population. These PCA modes can be shared without exposing patient information. The modes are re-combined with different weights to produce sets of realistic virtual patient contours. Because virtual patients lack imaging information, we developed a shape-based dose calculation (SBD) relying on the assumption that the region inside the body contour is water. SBD utilizes a 2D fluence-convolved scatter kernel, derived from Monte Carlo simulations, and can compute both full dose for a given set of fluence maps, or produce a dose matrix (dose per fluence pixel) for many modalities. Combining the shape model with SBD provides the data needed for treatment plan optimization research. Results: We used PSM to capture organ and target contours for 96 prostate cases, extracted the first 20 PCA modes, and generated 2048 virtual patient shapes by randomly sampling mode scores. Nearly half of the shapes were thrown out for failing anatomical checks, the remaining 1124 were used in computing dose matrices via SBD and a standard 7-beam protocol. As a proof of concept, and to generate data for later study, we performed fluence map optimization emphasizing PTV coverage. Conclusions: We successfully developed and tested a tool for creating customizable sets of virtual patients suitable for

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

    International Nuclear Information System (INIS)

    Verhaart, Rene F.; Rijnen, Zef; Verduijn, Gerda M.; Paulides, Margarethus M.; Fortunati, Valerio; Walsum, Theo van; Veenland, Jifke F.

    2014-01-01

    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.) [de

  5. A novel linear programming approach to fluence map optimization for intensity modulated radiation therapy treatment planning

    International Nuclear Information System (INIS)

    Romeijn, H Edwin; Ahuja, Ravindra K; Dempsey, James F; Kumar, Arvind; Li, Jonathan G

    2003-01-01

    We present a novel linear programming (LP) based approach for efficiently solving the intensity modulated radiation therapy (IMRT) fluence-map optimization (FMO) problem to global optimality. Our model overcomes the apparent limitations of a linear-programming approach by approximating any convex objective function by a piecewise linear convex function. This approach allows us to retain the flexibility offered by general convex objective functions, while allowing us to formulate the FMO problem as a LP problem. In addition, a novel type of partial-volume constraint that bounds the tail averages of the differential dose-volume histograms of structures is imposed while retaining linearity as an alternative approach to improve dose homogeneity in the target volumes, and to attempt to spare as many critical structures as possible. The goal of this work is to develop a very rapid global optimization approach that finds high quality dose distributions. Implementation of this model has demonstrated excellent results. We found globally optimal solutions for eight 7-beam head-and-neck cases in less than 3 min of computational time on a single processor personal computer without the use of partial-volume constraints. Adding such constraints increased the running times by a factor of 2-3, but improved the sparing of critical structures. All cases demonstrated excellent target coverage (>95%), target homogeneity (<10% overdosing and <7% underdosing) and organ sparing using at least one of the two models

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

    International Nuclear Information System (INIS)

    Yarmand, H; Winey, B; Craft, D

    2014-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

    Yarmand, H; Winey, B; Craft, D [Massachusetts General Hospital, Boston, MA (United States)

    2014-06-15

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

  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. Monte Carlo simulation for treatment planning optimization of the COMS and USC eye plaques using the MCNP4C code

    International Nuclear Information System (INIS)

    Jannati Isfahani, A.; Shokrani, P.; Raisali, Gh.

    2010-01-01

    Ophthalmic plaque radiotherapy using I-125 radioactive seeds in removable episcleral plaques is often used in management of ophthalmic tumors. Radioactive seeds are fixed in a gold bowl-shaped plaque and the plaque is sutured to the scleral surface corresponding to the base of the intraocular tumor. This treatment allows for a localized radiation dose delivery to the tumor with a minimum target dose of 85 Gy. The goal of this study was to develop a Monte Carlo simulation method for treatment planning optimization of the COMS and USC eye plaques. Material and Methods: The MCNP4C code was used to simulate three plaques: COMS-12mm, COMS-20mm, and USC ≠9 with I-125 seeds. Calculation of dose was performed in a spherical water phantom (radius 12 mm) using a 3D matrix with a size of 12 voxels in each dimension. Each voxel contained a sphere of radius 1 mm. Results: Dose profiles were calculated for each plaque. Isodose lines were created in 2 planes normal to the axes of the plaque, at the base of the tumor and at the level of the 85 Gy isodose in a 7 day treatment. Discussion and Conclusion: This study shows that it is necessary to consider the following tumor properties in design or selection of an eye plaque: the diameter of tumor base, its thickness and geometric shape, and the tumor location with respect to normal critical structures. The plaque diameter is selected by considering the tumor diameter. Tumor thickness is considered when selecting the seed parameters such as their number, activity and distribution. Finally, tumor shape and its location control the design of following parameters: the shape and material of the plaque and the need for collimation.

  10. TU-EF-304-07: Monte Carlo-Based Inverse Treatment Plan Optimization for Intensity Modulated Proton Therapy

    International Nuclear Information System (INIS)

    Li, Y; Tian, Z; Jiang, S; Jia, X; Song, T; Wu, Z; Liu, Y

    2015-01-01

    Purpose: Intensity-modulated proton therapy (IMPT) is increasingly used in proton therapy. For IMPT optimization, Monte Carlo (MC) is desired for spots dose calculations because of its high accuracy, especially in cases with a high level of heterogeneity. It is also preferred in biological optimization problems due to the capability of computing quantities related to biological effects. However, MC simulation is typically too slow to be used for this purpose. Although GPU-based MC engines have become available, the achieved efficiency is still not ideal. The purpose of this work is to develop a new optimization scheme to include GPU-based MC into IMPT. Methods: A conventional approach using MC in IMPT simply calls the MC dose engine repeatedly for each spot dose calculations. However, this is not the optimal approach, because of the unnecessary computations on some spots that turned out to have very small weights after solving the optimization problem. GPU-memory writing conflict occurring at a small beam size also reduces computational efficiency. To solve these problems, we developed a new framework that iteratively performs MC dose calculations and plan optimizations. At each dose calculation step, the particles were sampled from different spots altogether with Metropolis algorithm, such that the particle number is proportional to the latest optimized spot intensity. Simultaneously transporting particles from multiple spots also mitigated the memory writing conflict problem. Results: We have validated the proposed MC-based optimization schemes in one prostate case. The total computation time of our method was ∼5–6 min on one NVIDIA GPU card, including both spot dose calculation and plan optimization, whereas a conventional method naively using the same GPU-based MC engine were ∼3 times slower. Conclusion: A fast GPU-based MC dose calculation method along with a novel optimization workflow is developed. The high efficiency makes it attractive for clinical

  11. TU-EF-304-07: Monte Carlo-Based Inverse Treatment Plan Optimization for Intensity Modulated Proton Therapy

    Energy Technology Data Exchange (ETDEWEB)

    Li, Y [Tsinghua University, Beijing, Beijing (China); UT Southwestern Medical Center, Dallas, TX (United States); Tian, Z; Jiang, S; Jia, X [UT Southwestern Medical Center, Dallas, TX (United States); Song, T [Southern Medical University, Guangzhou, Guangdong (China); UT Southwestern Medical Center, Dallas, TX (United States); Wu, Z; Liu, Y [Tsinghua University, Beijing, Beijing (China)

    2015-06-15

    Purpose: Intensity-modulated proton therapy (IMPT) is increasingly used in proton therapy. For IMPT optimization, Monte Carlo (MC) is desired for spots dose calculations because of its high accuracy, especially in cases with a high level of heterogeneity. It is also preferred in biological optimization problems due to the capability of computing quantities related to biological effects. However, MC simulation is typically too slow to be used for this purpose. Although GPU-based MC engines have become available, the achieved efficiency is still not ideal. The purpose of this work is to develop a new optimization scheme to include GPU-based MC into IMPT. Methods: A conventional approach using MC in IMPT simply calls the MC dose engine repeatedly for each spot dose calculations. However, this is not the optimal approach, because of the unnecessary computations on some spots that turned out to have very small weights after solving the optimization problem. GPU-memory writing conflict occurring at a small beam size also reduces computational efficiency. To solve these problems, we developed a new framework that iteratively performs MC dose calculations and plan optimizations. At each dose calculation step, the particles were sampled from different spots altogether with Metropolis algorithm, such that the particle number is proportional to the latest optimized spot intensity. Simultaneously transporting particles from multiple spots also mitigated the memory writing conflict problem. Results: We have validated the proposed MC-based optimization schemes in one prostate case. The total computation time of our method was ∼5–6 min on one NVIDIA GPU card, including both spot dose calculation and plan optimization, whereas a conventional method naively using the same GPU-based MC engine were ∼3 times slower. Conclusion: A fast GPU-based MC dose calculation method along with a novel optimization workflow is developed. The high efficiency makes it attractive for clinical

  12. Optimizing clozapine treatment

    DEFF Research Database (Denmark)

    Nielsen, Jimmi; Damkier, P; Lublin, Henrik

    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....

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

    Science.gov (United States)

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

    2017-12-01

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

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

    International Nuclear Information System (INIS)

    Tian, Z; Shi, F; Jia, X; Jiang, S; Peng, F

    2014-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

    Tian, Z; Shi, F; Jia, X; Jiang, S [UT Southwestern Medical Ctr at Dallas, Dallas, TX (United States); Peng, F [Carnegie Mellon University, Pittsburgh, PA (United States)

    2014-06-01

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

  16. Automatic planning of head and neck treatment plans

    DEFF Research Database (Denmark)

    Hazell, Irene; Bzdusek, Karl; Kumar, Prashant

    2016-01-01

    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...... 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......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...

  17. 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

  18. Optimization of importance factors in inverse planning

    International Nuclear Information System (INIS)

    Xing, L.

    1999-01-01

    Inverse treatment planning starts with a treatment objective and obtains the solution by optimizing an objective function. The clinical objectives are usually multifaceted and potentially incompatible with one another. A set of importance factors is often incorporated in the objective function to parametrize trade-off strategies and to prioritize the dose conformality in different anatomical structures. Whereas the general formalism remains the same, different sets of importance factors characterize plans of obviously different flavour and thus critically determine the final plan. Up to now, the determination of these parameters has been a 'guessing' game based on empirical knowledge because the final dose distribution depends on the parameters in a complex and implicit way. The influence of these parameters is not known until the plan optimization is completed. In order to compromise properly the conflicting requirements of the target and sensitive structures, the parameters are usually adjusted through a trial-and-error process. In this paper, a method to estimate these parameters computationally is proposed and an iterative computer algorithm is described to determine these parameters numerically. The treatment plan selection is done in two steps. First, a set of importance factors are chosen and the corresponding beam parameters (e.g. beam profiles) are optimized under the guidance of a quadratic objective function using an iterative algorithm reported earlier. The 'optimal' plan is then evaluated by an additional scoring function. The importance factors in the objective function are accordingly adjusted to improve the ranking of the plan. For every change in the importance factors, the beam parameters need to be re-optimized. This process continues in an iterative fashion until the scoring function is saturated. The algorithm was applied to two clinical cases and the results demonstrated that it has the potential to improve significantly the existing method of

  19. Comparison of different treatment planning optimization methods for vaginal HDR brachytherapy with multichannel applicators: A reduction of the high doses to the vaginal mucosa is possible.

    Science.gov (United States)

    Carrara, Mauro; Cusumano, Davide; Giandini, Tommaso; Tenconi, Chiara; Mazzarella, Ester; Grisotto, Simone; Massari, Eleonora; Mazzeo, Davide; Cerrotta, Annamaria; Pappalardi, Brigida; Fallai, Carlo; Pignoli, Emanuele

    2017-12-01

    A direct planning approach with multi-channel vaginal cylinders (MVCs) used for HDR brachytherapy of vaginal cancers is particularly challenging. Purpose of this study was to compare the dosimetric performances of different forward and inverse methods used for the optimization of MVC-based vaginal treatments for endometrial cancer, with a particular attention to the definition of strategies useful to limit the high doses to the vaginal mucosa. Twelve postoperative vaginal HDR brachytherapy treatments performed with MVCs were considered. Plans were retrospectively optimized with three different methods: Dose Point Optimization followed by Graphical Optimization (DPO + GrO), Inverse Planning Simulated Annealing with two different class solutions as starting conditions (surflPSA and homogIPSA) and Hybrid Inverse Planning Optimization (HIPO). Several dosimetric parameters related to target coverage, hot spot extensions and sparing of organs at risk were analyzed to evaluate the quality of the achieved treatment plans. Dose homogeneity index (DHI), conformal index (COIN) and a further parameter quantifying the proportion of the central catheter loading with respect to the overall loading (i.e., the central catheter loading index: CCLI) were also quantified. The achieved PTV coverage parameters were highly correlated with each other but uncorrelated with the hot spot quantifiers. HomogIPSA and HIPO achieved higher DHIs and CCLIs and lower volumes of high doses than DPO + GrO and surflPSA. Within the investigated optimization methods, HIPO and homoglPSA showed the highest dose homogeneity to the target. In particular, homogIPSA resulted also the most effective in reducing hot spots to the vaginal mucosa. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

  20. SU-G-BRC-02: A Novel Multi-Criteria Optimization Approach to Generate Deliverable Intensity-Modulated Radiation Therapy (IMRT) Treatment Plans

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-06-15

    Purpose: To present a novel multi-criteria optimization (MCO) solution approach that generates treatment plans with deliverable apertures using column generation. Methods: We demonstrate our method with 10 locally advanced head-and-neck cancer cases retrospectively. In our MCO formulation, we defined an objective function for each structure in the treatment volume. This resulted in 9 objective functions, including 3 distinct objectives for primary target volume, high-risk and low-risk target volumes, 5 objectives for each of the organs-at-risk (OARs) (two parotid glands, spinal cord, brain stem and oral cavity), and one for the non-target non-OAR normal tissue. Conditional value-at-risk (CVaR) constraints were utilized to ensure at least certain fraction of the target volumes receiving the prescription doses. To directly generate deliverable plans, column generation algorithm was embedded within our MCO approach for aperture shape generation. Final dose distributions for all plans were generated using a Monte Carlo kernel-superposition dose calculation. We compared the MCO plans with the clinical plans, which were created by clinicians. Results: At least 95% target coverage was achieved by both MCO plans and clinical plans. However, the average conformity indices of clinical plans and the MCO plans were 1.95 and 1.35, respectively (31% reduction, p<0.01). Compared to the conventional clinical plan, the proposed MCO method achieved average reductions in left parotid mean dose of 5% (p=0.06), right parotid mean dose of 18% (p<0.01), oral cavity mean dose of 21% (p=0.03), spinal cord maximum dose of 20% (p<0.01), brain stem maximum dose of 61% (p<0.01), and normal tissue maximum dose of 5% (p<0.01), respectively. Conclusion: We demonstrated that the proposed MCO method was able to obtain deliverable IMRT treatment plans while achieving significant improvements in dosimetric plan quality.

  1. WE-AB-209-07: Explicit and Convex Optimization of Plan Quality Metrics in Intensity-Modulated Radiation Therapy Treatment Planning

    International Nuclear Information System (INIS)

    Engberg, L; Eriksson, K; Hardemark, B; Forsgren, A

    2016-01-01

    Purpose: To formulate objective functions of a multicriteria fluence map optimization model that correlate well with plan quality metrics, and to solve this multicriteria model by convex approximation. Methods: In this study, objectives of a multicriteria model are formulated to explicitly either minimize or maximize a dose-at-volume measure. Given the widespread agreement that dose-at-volume levels play important roles in plan quality assessment, these objectives correlate well with plan quality metrics. This is in contrast to the conventional objectives, which are to maximize clinical goal achievement by relating to deviations from given dose-at-volume thresholds: while balancing the new objectives means explicitly balancing dose-at-volume levels, balancing the conventional objectives effectively means balancing deviations. Constituted by the inherently non-convex dose-at-volume measure, the new objectives are approximated by the convex mean-tail-dose measure (CVaR measure), yielding a convex approximation of the multicriteria model. Results: Advantages of using the convex approximation are investigated through juxtaposition with the conventional objectives in a computational study of two patient cases. Clinical goals of each case respectively point out three ROI dose-at-volume measures to be considered for plan quality assessment. This is translated in the convex approximation into minimizing three mean-tail-dose measures. Evaluations of the three ROI dose-at-volume measures on Pareto optimal plans are used to represent plan quality of the Pareto sets. Besides providing increased accuracy in terms of feasibility of solutions, the convex approximation generates Pareto sets with overall improved plan quality. In one case, the Pareto set generated by the convex approximation entirely dominates that generated with the conventional objectives. Conclusion: The initial computational study indicates that the convex approximation outperforms the conventional objectives

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

    Energy Technology Data Exchange (ETDEWEB)

    Tabibian, A; Kim, A; Rose, J; Alvelo, M; Perel, C; Laiken, K; Sheth, N [Bayonne Medical Center, Bayonne, New Jersey (United States)

    2016-06-15

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

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

    International Nuclear Information System (INIS)

    Tabibian, A; Kim, A; Rose, J; Alvelo, M; Perel, C; Laiken, K; Sheth, N

    2016-01-01

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

  4. 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.

  5. 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.

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

    International Nuclear Information System (INIS)

    Chow, J

    2015-01-01

    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

  7. 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.

  8. OEDIPE, a software for personalized Monte Carlo dosimetry and treatment planning optimization in nuclear medicine: absorbed dose and biologically effective dose considerations

    International Nuclear Information System (INIS)

    Petitguillaume, A.; Broggio, D.; Franck, D.; Desbree, A.; Bernardini, M.; Labriolle Vaylet, C. de

    2014-01-01

    For targeted radionuclide therapies, treatment planning usually consists of the administration of standard activities without accounting for the patient-specific activity distribution, pharmacokinetics and dosimetry to organs at risk. The OEDIPE software is a user-friendly interface which has an automation level suitable for performing personalized Monte Carlo 3D dosimetry for diagnostic and therapeutic radionuclide administrations. Mean absorbed doses to regions of interest (ROIs), isodose curves superimposed on a personalized anatomical model of the patient and dose-volume histograms can be extracted from the absorbed dose 3D distribution. Moreover, to account for the differences in radiosensitivity between tumoral and healthy tissues, additional functionalities have been implemented to calculate the 3D distribution of the biologically effective dose (BED), mean BEDs to ROIs, isoBED curves and BED-volume histograms along with the Equivalent Uniform Biologically Effective Dose (EUD) to ROIs. Finally, optimization tools are available for treatment planning optimization using either the absorbed dose or BED distributions. These tools enable one to calculate the maximal injectable activity which meets tolerance criteria to organs at risk for a chosen fractionation protocol. This paper describes the functionalities available in the latest version of the OEDIPE software to perform personalized Monte Carlo dosimetry and treatment planning optimization in targeted radionuclide therapies. (authors)

  9. An image-guided system for optimized volumetric treatment planning and execution for radiofrequency ablation of liver tumors

    Energy Technology Data Exchange (ETDEWEB)

    Banovac, F.; Popa, T.; Cheng, P.; Cleary, K. [Computer Aided Interventions and Medical Robotics (CAIMR), Imaging Science and Information Systems (ISIS) Center, Georgetown Univ. Medical Center, Washington, DC (United States); Abeledo, H.; Campos-Nanez, E. [Dept. of Engineering Management and System Engineering, George Washington Univ., Washington, DC (United States); Wood, B.J. [Diagnostic Radiology Dept., NIH Clinical Center, Bethesda, MD (United States)

    2007-06-15

    Radiofrequency ablation of liver tumors is becoming an increasingly popular option for the treatment of cancer. However, the procedure has several technical challenges, mostly associated with precision targeting of the tumor and ensuring complete ablation coverage. In this paper we describe an image-guided system that we are developing for improved visualization and probe placement during these procedures. The system will include a pre-procedure optimization module and an intra-procedure guidance component. The system concept is explained and some preliminary results are given. While this system is designed for radiofrequency ablation of liver tumors, the methods are applicable to other organs and treatment methods. (orig.)

  10. Treatment planning systems for external whole brain radiation therapy: With and without MLC (multi leaf collimator) optimization

    Science.gov (United States)

    Budiyono, T.; Budi, W. S.; Hidayanto, E.

    2016-03-01

    Radiation therapy for brain malignancy is done by giving a dose of radiation to a whole volume of the brain (WBRT) followed by a booster at the primary tumor with more advanced techniques. Two external radiation fields given from the right and left side. Because the shape of the head, there will be an unavoidable hotspot radiation dose of greater than 107%. This study aims to optimize planning of radiation therapy using field in field multi-leaf collimator technique. A study of 15 WBRT samples with CT slices is done by adding some segments of radiation in each field of radiation and delivering appropriate dose weighting using a TPS precise plan Elekta R 2.15. Results showed that this optimization a more homogeneous radiation on CTV target volume, lower dose in healthy tissue, and reduced hotspots in CTV target volume. Comparison results of field in field multi segmented MLC technique with standard conventional technique for WBRT are: higher average minimum dose (77.25% ± 0:47%) vs (60% ± 3:35%); lower average maximum dose (110.27% ± 0.26%) vs (114.53% ± 1.56%); lower hotspot volume (5.71% vs 27.43%); and lower dose on eye lenses (right eye: 9.52% vs 18.20%); (left eye: 8.60% vs 16.53%).

  11. Treatment planning systems for external whole brain radiation therapy: With and without MLC (multi leaf collimator) optimization

    International Nuclear Information System (INIS)

    Budiyono, T; Budi, W S; Hidayanto, E

    2016-01-01

    Radiation therapy for brain malignancy is done by giving a dose of radiation to a whole volume of the brain (WBRT) followed by a booster at the primary tumor with more advanced techniques. Two external radiation fields given from the right and left side. Because the shape of the head, there will be an unavoidable hotspot radiation dose of greater than 107%. This study aims to optimize planning of radiation therapy using field in field multi-leaf collimator technique. A study of 15 WBRT samples with CT slices is done by adding some segments of radiation in each field of radiation and delivering appropriate dose weighting using a TPS precise plan Elekta R 2.15. Results showed that this optimization a more homogeneous radiation on CTV target volume, lower dose in healthy tissue, and reduced hotspots in CTV target volume. Comparison results of field in field multi segmented MLC technique with standard conventional technique for WBRT are: higher average minimum dose (77.25% ± 0:47%) vs (60% ± 3:35%); lower average maximum dose (110.27% ± 0.26%) vs (114.53% ± 1.56%); lower hotspot volume (5.71% vs 27.43%); and lower dose on eye lenses (right eye: 9.52% vs 18.20%); (left eye: 8.60% vs 16.53%). (paper)

  12. Completion of treatment planning

    International Nuclear Information System (INIS)

    Lief, Eugene

    2008-01-01

    The outline of the lecture included the following topics: entering prescription; plan printout; print and transfer DDR; segment BEV; export to R and V; physician approval; and second check. Considerable attention, analysis and discussion. The summary is as follows: Treatment planning completion is a very responsible process which requires maximum attention; Should be independently checked by the planner, physicist, radiation oncologist and a therapist; Should not be done in a last minute rush; Proper communication between team members; Properly set procedure should prevent propagation of an error by one individual to the treatment: the error should be caught by somebody else. (P.A.)

  13. SU-F-T-501: Dosimetric Comparison of Single Arc-Per-Beam and Two Arc-Per-Beam VMAT Optimization in the Monaco Treatment Planning System

    Energy Technology Data Exchange (ETDEWEB)

    Kalet, A; Cao, N; Meyer, J; Dempsey, C [University of Washington Medical Center, Seattle, WA (United States); Seattle Cancer Care Alliance, Seattle, WA (United States); Richardson, H [Seattle Cancer Care Alliance, Seattle, WA (United States)

    2016-06-15

    Purpose: The purpose of this study was to evaluate the dosimetric and practical effects of the Monaco treatment planning system “max arcs-per-beam” optimization parameter in pelvic radiotherapy treatments. Methods: A total of 17 previously treated patients were selected for this study with a range of pelvic disease site including prostate(9), bladder(1), uterus(3), rectum(3), and cervix(1). For each patient, two plans were generated, one using a arc-per-beam setting of ‘1’ and another with setting of ‘2’. The setting allows the optimizer to add a gantry direction change, creating multiple arc passes per beam sequence. Volumes and constraints established from the initial clinical treatments were used for planning. All constraints and dose coverage objects were kept the same between plans, and all plans were normalized to 99.7% to ensure 100% of the PTV received 95% of the prescription dose. We evaluated the PTV conformity index, homogeneity index, total monitor units, number of control points, and various dose volume histogram (DVH) points for statistical comparison (alpha=0.05). Results: We found for the 10 complex shaped target volumes (small central volumes with extending bilateral ‘arms’ to cover nodal regions) that the use of 2 arcs-per-beam achieved significantly lower average DVH values for the bladder V20 (p=0.036) and rectum V30 (p=0.001) while still meeting the high dose target constraints. DVH values for the simpler, more spherical PTVs were not found significantly different. Additionally, we found a beam delivery time reduction of approximately 25%. Conclusion: In summary, the dosimetric benefit, while moderate, was improved over a 1 arc-per-beam setting for complex PTVs, and equivalent in other cases. The overall reduced delivery time suggests that the use of multiple arcs-per-beam could lead to reduced patient on table time, increased clinical throughput, and reduced medical physics quality assurance effort.

  14. Treatment Planning for Ion Beam Therapy

    Science.gov (United States)

    Jäkel, Oliver

    The special aspects of treatment planning for ion beams are outlined in this chapter, starting with positioning and immobilization of the patient, describing imaging and segmentation, definition of treatment parameters, dose calculation and optimization, and, finally, plan assessment, verification, and quality assurance.

  15. Schedule optimization study implementation plan

    International Nuclear Information System (INIS)

    1993-11-01

    This Implementation Plan is intended to provide a basis for improvements in the conduct of the Environmental Restoration (ER) Program at Hanford. The Plan is based on the findings of the Schedule Optimization Study (SOS) team which was convened for two weeks in September 1992 at the request of the U.S. Department of Energy (DOE) Richland Operations Office (RL). The need for the study arose out of a schedule dispute regarding the submission of the 1100-EM-1 Operable Unit (OU) Remedial Investigation/Feasibility Study (RI/FS) Work Plan. The SOS team was comprised of independent professionals from other federal agencies and the private sector experienced in environmental restoration within the federal system. The objective of the team was to examine reasons for the lengthy RI/FS process and recommend ways to expedite it. The SOS team issued their Final Report in December 1992. The report found the most serious impediments to cleanup relate to a series of management and policy issues which are within the control of the three parties managing and monitoring Hanford -- the DOE, U.S. Environmental Protection Agency (EPA), and the State of Washington Department of Ecology (Ecology). The SOS Report identified the following eight cross-cutting issues as the root of major impediments to the Hanford Site cleanup. Each of these eight issues is quoted from the SOS Report followed by a brief, general description of the proposed approach being developed

  16. Fuzzy logic guided inverse treatment planning

    International Nuclear Information System (INIS)

    Yan Hui; Yin Fangfang; Guan Huaiqun; Kim, Jae Ho

    2003-01-01

    A fuzzy logic technique was applied to optimize the weighting factors in the objective function of an inverse treatment planning system for intensity-modulated radiation therapy (IMRT). Based on this technique, the optimization of weighting factors is guided by the fuzzy rules while the intensity spectrum is optimized by a fast-monotonic-descent method. The resultant fuzzy logic guided inverse planning system is capable of finding the optimal combination of weighting factors for different anatomical structures involved in treatment planning. This system was tested using one simulated (but clinically relevant) case and one clinical case. The results indicate that the optimal balance between the target dose and the critical organ dose is achieved by a refined combination of weighting factors. With the help of fuzzy inference, the efficiency and effectiveness of inverse planning for IMRT are substantially improved

  17. DPM, a fast, accurate Monte Carlo code optimized for photon and electron radiotherapy treatment planning dose calculations

    International Nuclear Information System (INIS)

    Sempau, Josep; Wilderman, Scott J.; Bielajew, Alex F.

    2000-01-01

    A new Monte Carlo (MC) algorithm, the 'dose planning method' (DPM), and its associated computer program for simulating the transport of electrons and photons in radiotherapy class problems employing primary electron beams, is presented. DPM is intended to be a high-accuracy MC alternative to the current generation of treatment planning codes which rely on analytical algorithms based on an approximate solution of the photon/electron Boltzmann transport equation. For primary electron beams, DPM is capable of computing 3D dose distributions (in 1 mm 3 voxels) which agree to within 1% in dose maximum with widely used and exhaustively benchmarked general-purpose public-domain MC codes in only a fraction of the CPU time. A representative problem, the simulation of 1 million 10 MeV electrons impinging upon a water phantom of 128 3 voxels of 1 mm on a side, can be performed by DPM in roughly 3 min on a modern desktop workstation. DPM achieves this performance by employing transport mechanics and electron multiple scattering distribution functions which have been derived to permit long transport steps (of the order of 5 mm) which can cross heterogeneity boundaries. The underlying algorithm is a 'mixed' class simulation scheme, with differential cross sections for hard inelastic collisions and bremsstrahlung events described in an approximate manner to simplify their sampling. The continuous energy loss approximation is employed for energy losses below some predefined thresholds, and photon transport (including Compton, photoelectric absorption and pair production) is simulated in an analogue manner. The δ-scattering method (Woodcock tracking) is adopted to minimize the computational costs of transporting photons across voxels. (author)

  18. Dosimetric comparison of single-beam multi-arc and 2-beam multi-arc VMAT optimization in the Monaco treatment planning system

    Energy Technology Data Exchange (ETDEWEB)

    Kalet, Alan M., E-mail: amkalet@uw.edu [Department of Radiation Oncology, University of Washington, Seattle, Washington (United States); Seattle Cancer Care Alliance, Seattle, Washington (United States); Richardson, Hannah L.; Nikolaisen, Darrin A. [Seattle Cancer Care Alliance, Seattle, Washington (United States); Cao, Ning [Department of Radiation Oncology, University of Washington, Seattle, Washington (United States); Seattle Cancer Care Alliance, Seattle, Washington (United States); Lavilla, Myra A. [Seattle Cancer Care Alliance, Seattle, Washington (United States); Dempsey, Claire; Meyer, Juergen; Koh, Wui-Jin; Russell, Kenneth J. [Department of Radiation Oncology, University of Washington, Seattle, Washington (United States); Seattle Cancer Care Alliance, Seattle, Washington (United States)

    2017-07-01

    The purpose of this study was to evaluate the dosimetric and practical effects of the Monaco treatment planning system “max arcs-per-beam” optimization parameter in pelvic radiotherapy treatments. We selected for this study a total of 17 previously treated patients with a range of pelvic disease sites including prostate (9), bladder (1), uterus (3), rectum (3), and cervix (1). For each patient, 2 plans were generated, one using an arc-per-beam setting of “1” and another with an arc-per-beam setting of “2” using the volumes and constraints established from the initial clinical treatments. All constraints and dose coverage objects were kept the same between plans, and all plans were normalized to 99.7% to ensure 100% of the planning target volume (PTV) received 95% of the prescription dose. Plans were evaluated for PTV conformity, homogeneity, number of monitor units, number of control points, and overall plan acceptability. Treatment delivery time, patient-specific quality assurance procedures, and the impact on clinical workflow were also assessed. We found that for complex-shaped target volumes (small central volumes with extending arms to cover nodal regions), the use of 2 arc-per-beam (2APB) parameter setting achieved significantly lower average dose-volume histogram values for the rectum V{sub 20} (p = 0.0012) and bladder V{sub 30} (p = 0.0036) while meeting the high dose target constraints. For simple PTV shapes, we found reduced monitor units (13.47%, p = 0.0009) and control points (8.77%, p = 0.0004) using 2APB planning. In addition, we found a beam delivery time reduction of approximately 25%. In summary, the dosimetric benefit, although moderate, was improved over a 1APB setting for complex PTV, and equivalent in other cases. The overall reduced delivery time suggests that the use of mulitple arcs per beam could lead to reduced patient-on-table time, increased clinical throughput, and reduced medical physics quality assurance

  19. Treatment planning systems

    International Nuclear Information System (INIS)

    Fontenla, D.P.

    2008-01-01

    All aspects of treatment planning in radiotherapy are discussed in detail. Included are, among others, machine data and their acquisition, photon dose calculations and tests thereof, criteria of acceptability, sources of uncertainties, from 2D to 3D and from 3D to IMRT, dosimetric measurements for RTP validation, frequency of QA tests and suggested tolerances for TPS, time and staff requirements, model based segmentation, multi-dimensional radiotherapy (MD C RT), and biological IMRT process. (P.A.)

  20. TU-C-17A-12: Towards a Passively Optimized Phase-Space Monte Carlo (POPMC) Treatment Planning Method: A Proof of Principle

    International Nuclear Information System (INIS)

    Yang, Y M; Bednarz, B; Zankowski, C; Svatos, M

    2014-01-01

    Purpose: The advent of on-line/off-line adaptive, and biologically-conformal radiation therapy has led to a need for treatment planning solutions that utilize voxel-specific penalties, requiring optimization over a large solution space that is performed quickly, and the dose in each voxel calculated accurately. This work proposes a “passive” optimization framework, which is executed concurrently during Monte Carlo dose calculation, evaluating the cost/benefit of each history during transport, and creates a passively optimized fluence map. Methods: The Monte Carlo code Geant4 v9.6 was used for this study. The standard voxel geometry implementation was modified to support the passive optimization framework, with voxel-specific optimization parameters. Dose-benefit functions, which will increase a particle history’s weight upon dose deposition, were defined in a central collection of voxels to effectively create target structures. Histories that deposit energy to voxels are reweighted based on a voxel’s dose multiplied by its cost/benefit value. Upon full termination of each history, the dose contributions of that history are reweighted to reflect a contribution proportional to the history’s final weight. A parallel-planar 1.25 MeV photon fluence is transported through the geometry, and re-weighted at each dose deposition step. The resulting weight is tallied with the incident spatial and directional coordinates in a phase-space distribution. Results: A uniform incident fluence was reweighted during MC dose calculations to create an optimized fluence map which would generate dose profiles in target volumes that exhibit the same dose characteristics as the prescribed optimization parameters. An optimized dose profile, calculated concurrently with the phase-space, reflects the resulting dose distribution. Conclusion: This study demonstrated the feasibility of passively optimizing an incident fluence map during Monte Carlo dose calculations. The flexibility of

  1. 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.

  2. Method of radiation therapy treatment planning

    International Nuclear Information System (INIS)

    Hodes, L.

    1976-01-01

    A technique of radiation therapy treatment planning designed to allow the assignment of dosage limits directly to chosen points in the computer-displayed cross-section of the patient. These dosage limits are used as constraints in a linear programming attempt to solve for beam strengths, minimizing integral dosage. If a feasible plan exists, the optimized plan will be displayed for approval as an isodose pattern. If there is no feasible plan, the operator/therapist can designate some of the point dosage constraints as ''relaxed.'' Linear programming will then optimize for minimum deviation at the relaxed points. This process can be iterated and new points selected until an acceptable plan is realized. In this manner the plan is optimized for uniformity as well as overall low dosage. 6 claims, 6 drawing figures

  3. Improved Planning Time and Plan Quality Through Multicriteria Optimization for Intensity-Modulated Radiotherapy

    International Nuclear Information System (INIS)

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

    2012-01-01

    Purpose: To test whether multicriteria optimization (MCO) can reduce treatment planning time and improve plan quality in intensity-modulated radiotherapy (IMRT). Methods and Materials: 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. Results: 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. Conclusions: 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.

  4. SU-F-T-422: Detection of Optimal Tangential Partial Arc Span for VMAT Planning in IntactLeft-Breast Treatment

    Energy Technology Data Exchange (ETDEWEB)

    Giri, U; Sarkar, B; Munshi, A; Kaur, H; Jassal, K; Rathinamuthu, S; Kumar, S; Ganesh, T; Mohanti, B [Fortis Memorial Research Institute, Gurgaon, Haryana (India)

    2016-06-15

    Purpose: This study was designed to investigate an appropriate arc span for intact partial Left breast irradiation by VMAT planning. Methods: Four cases of carcinoma left intact breast was chosen randomly for this study. Both medial tangential and left-lateral tangential arc (G20°, G25°, G30°, G35°, G40°) were used having the same length and bilaterally symmetric. For each patient base plan was generated for 30° arc and rest of other arc plans were generated by keeping all plan parameters same, only arc span were changed. All patient plans were generated on treatment planning system Monaco (V 5.00.02) for 50 Gy dose in 25 fractions. PTV contours were clipped 3 mm from skin (patient). All plans were normalized in such a way that 95 % of prescription dose would cover 96 % of PTV volume. Results: Mean MU for 20°, 25°, 30°, 35° and 40° were 509 ± 18.8, 529.1 ± 20.2, 544.4 ± 20.8, 579.1 ±51.8, 607.2 ± 40.2 similarly mean hot spot (volume covered by 105% of prescription dose) were 2.9 ± 1.2, 3.7 ± 3.0, 1.5 ± 1.7, 1.3±0.6, 0.4 ± 0.4, mean contralateral breast dose (cGy) were 180.4 ± 242.3, 71.5 ± 52.7, 76.2 ± 58.8, 85.9 ± 70.5, 90.7 ± 70.1, mean heart dose (cGy) were 285.8 ± 87.2, 221.2 ± 62.8, 274.5 ± 95.5, 234.8 ± 73.8, 263.2 ± 81.6, V20 for ipsilateral lung were 15.4 ± 5.3, 14.3 ± 3.6, 15.3 ± 2.9, 14.2 ± 3.9, 14.7 ± 3.2 and V5 for ipsilateral lung were 33.9 ± 8.2, 31.0 ± 3.5, 42.6 ±15.6, 36.4 ± 12.9, 37.0 ± 7.5. Conclusion: The study concluded that appropriate arc span used for tangential intact breast treatment was optimally 30° because larger arc span were giving lower isodose spill in ipsilateral lung and smaller arc were giving heterogeneous dose distribution in PTV.

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

    International Nuclear Information System (INIS)

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

    2013-01-01

    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

  6. Developing Optimized Treatment Plans for Patients with Dyslipidemia in the Era of Proprotein Convertase Subtilisin/Kexin Type 9 Inhibitor Therapeutics.

    Science.gov (United States)

    Underberg, James A; Blaha, Michael J; Jackson, Elizabeth J; Jones, Peter H

    2017-10-01

    This educational content was derived from a live satellite symposium at the American College of Physicians Internal Medicine Meeting 2017 in San Diego, California (online at http://courses.elseviercme.com/acp/702e). This activity will focus on optimized treatment plans for patients with dyslipidemia in the era of proprotein convertase subtilisin/kexin type 9 inhibitor therapeutics. Low-density lipoprotein cholesterol has been identified as an important therapeutic target to prevent the progression of atherosclerotic disease; however, only 1 of every 3 adults with high low-density lipoprotein cholesterol has the condition under control. Expert faculty on this panel will discuss the science of proprotein convertase subtilisin/kexin type 9 inhibitors and aid physicians in the best practices to achieve low-density lipoprotein cholesterol target in their patients. Copyright © 2017. Published by Elsevier Inc.

  7. Treatment planning source assessment

    International Nuclear Information System (INIS)

    Calzetta Larrieu, O.; Blaumann, H.; Longhino, J.

    2000-01-01

    The reactor RA-6 NCT system was improved during the last year mainly in two aspects: the facility itself getting lower contamination factors and using better measurements techniques to obtain lower uncertainties in its characterization. In this job we show the different steps to get the source to be used in the treatment planning code representing the NCT facility. The first one was to compare the dosimetry in a water phantom between the calculation using the entire facility including core, filter and shields and a surface source at the end of the beam. The second one was to transform this particle by particle source in a distribution one regarding the minimum spatial, energy and angular resolution to get similar results. Finally we compare calculation and experimental values with and without the water phantom to adjust the distribution source. The results are discussed. (author)

  8. Inverse planning and class solutions for brachytherapy treatment planning

    International Nuclear Information System (INIS)

    Trnkova, P.

    2010-01-01

    Brachytherapy or interventional radiooncology is a method of radiation therapy. It is a method, where a small encapsulated radioactive source is placed near to / in the tumour and therefore delivers high doses directly to the target volume. Organs at risk (OARs) are spared due to the inverse square dose fall-off. In the past years there was a slight stagnation in the development of techniques for brachytherapy treatment. While external beam radiotherapy became more and more sophisticated, in brachytherapy traditional methods have been still used. Recently, 3D imaging was considered also as the modality for brachytherapy and more precise brachytherapy could expand. Nowadays, an image guided brachytherapy is state-of-art in many centres. Integration of imaging methods lead to the dose distribution individually tailored for each patient. Treatment plan optimization is mostly performed manually as an adaptation of a standard loading pattern. Recently, inverse planning approaches have been introduced into brachytherapy. The aim of this doctoral thesis was to analyze inverse planning and to develop concepts how to integrate inverse planning into cervical cancer brachytherapy. First part of the thesis analyzes the Hybrid Inverse treatment Planning and Optimization (HIPO) algorithm and proposes a workflow how to safely work with this algorithm. The problem of inverse planning generally is that only the dose and volume parameters are taken into account and spatial dose distribution is neglected. This fact can lead to unwanted high dose regions in a normal tissue. A unique implementation of HIPO into the treatment planning system using additional features enabled to create treatment plans similar to the plans resulting from manual optimization and to shape the high dose regions inside the CTV. In the second part the HIPO algorithm is compared to the Inverse Planning Simulated Annealing (IPSA) algorithm. IPSA is implemented into the commercial treatment planning system. It

  9. Automatic interactive optimization for volumetric modulated arc therapy planning

    International Nuclear Information System (INIS)

    Tol, Jim P; Dahele, Max; Peltola, Jarkko; Nord, Janne; Slotman, Ben J; Verbakel, Wilko FAR

    2015-01-01

    Intensity modulated radiotherapy treatment planning for sites with many different organs-at-risk (OAR) is complex and labor-intensive, making it hard to obtain consistent plan quality. With the aim of addressing this, we developed a program (automatic interactive optimizer, AIO) designed to automate the manual interactive process for the Eclipse treatment planning system. We describe AIO and present initial evaluation data. Our current institutional volumetric modulated arc therapy (RapidArc) planning approach for head and neck tumors places 3-4 adjustable OAR optimization objectives along the dose-volume histogram (DVH) curve that is displayed in the optimization window. AIO scans this window and uses color-coding to differentiate between the DVH-lines, allowing it to automatically adjust the location of the optimization objectives frequently and in a more consistent fashion. We compared RapidArc AIO plans (using 9 optimization objectives per OAR) with the clinical plans of 10 patients, and evaluated optimal AIO settings. AIO consistency was tested by replanning a single patient 5 times. Average V95&V107 of the boost planning target volume (PTV) and V95 of the elective PTV differed by ≤0.5%, while average elective PTV V107 improved by 1.5%. Averaged over all patients, AIO reduced mean doses to individual salivary structures by 0.9-1.6Gy and provided mean dose reductions of 5.6Gy and 3.9Gy to the composite swallowing structures and oral cavity, respectively. Re-running AIO five times, resulted in the aforementioned parameters differing by less than 3%. Using the same planning strategy as manually optimized head and neck plans, AIO can automate the interactive Eclipse treatment planning process and deliver dosimetric improvements over existing clinical plans

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

    International Nuclear Information System (INIS)

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

    2011-01-01

    Purpose: 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. Methods: 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. Results: 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

  11. 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

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

    International Nuclear Information System (INIS)

    Cao Ruifen; Pei Xi; Cheng Mengyun; Li Gui; Hu Liqin; Wu Yican; Jing Jia; Li Guoli

    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 plan were transformed into a multi-objective optimization problem with multiple constraints. Then, the fast and elitist multi-objective Non-dominated Sorting Genetic Algorithm (NSGA-II) was introduced to optimize the problem. A clinical example was tested using this method. The results show that an obtained set of non-dominated solutions were uniformly distributed and the corresponding dose distribution of each solution not only approached the expected dose distribution, but also met the dose-volume constraints. It was indicated that the clinical requirements were better satisfied using the method and the planner could select the optimal treatment plan from the non-dominated solution set. (authors)

  13. Clinical evaluation of treatment plans

    Energy Technology Data Exchange (ETDEWEB)

    Emery, E W [Radiotherapy Department, University College Hospital, London (United Kingdom)

    1966-06-15

    Since the start of radiotherapy, the aim of all radiotherapists has been to treat as many patients who suffer with malignant tumours as possible, so as to give an effective curative dose to the whole tumour, at the same time, doing as little damage as possible to normal tissues. Until 1945, damage to the skin was usually the limiting factor. Since the war, with the rapid development of more powerful X-ray machines and sources of irradiation, we have had at our disposal much more penetrating radiation, allowing us to give effective tumour doses, with little or no damage to the skin. However, with higher tumour doses, there is more likelihood of damage to structures in proximity to the tumour - i.e. bone, nerves, muscle, liver, kidney etc. This has focussed the interest of all radiologists on the need for careful planning, and physicists have worked out with great care the differential absorptions of X-rays on differing tissue, i. e. bone, muscle, fat etc., so that very accurate and correct treatment planning can now be undertaken. This entails a great deal of accurate and complicated work and has had to be done by our physicist colleagues, who may take hours or days to work out a complicated treatment plan. The acceptance of the plan as being the most suitable for a patient is governed by these factors: (a) The dose must be given to the whole tumour area; (b) The nearby structures, i. e. nerves, bowel, kidney etc. must not receive a dose which may cause serious damage; (c) All parts of the tumour must have an effective dose; (d) The integral dose must be such that the patient is not unduly upset. All these factors vary from patient to patient, and thus each plan has to be considered in conjunction with each individual patient so that, although patients have similar tumours, what may be an optimal plan for one may not be for another. Also clinicians themselves vary in their opinions on the size of tumour, general condition of the patient, and the amount of damage

  14. Automated IMRT planning with regional optimization using planning scripts.

    Science.gov (United States)

    Xhaferllari, Ilma; Wong, Eugene; Bzdusek, Karl; Lock, Michael; Chen, Jeff

    2013-01-07

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

  15. Using Optimization to Improve Test Planning

    Science.gov (United States)

    2017-09-01

    OPTIMIZATION TO IMPROVE TEST PLANNING by Arlene M. Payne September 2017 Thesis Advisor: Jeffrey E. Kline Second Reader: Oleg A. Yakimenko THIS... Project (0704-0188) Washington, DC 20503. 1. AGENCY USE ONLY (Leave blank) 2. REPORT DATE September 2017 3. REPORT TYPE AND DATES COVERED Master’s...thesis 4. TITLE AND SUBTITLE USING OPTIMIZATION TO IMPROVE TEST PLANNING 5. FUNDING NUMBERS 6. AUTHOR(S) Arlene M. Payne 7. PERFORMING ORGANIZATION

  16. On the role of modeling parameters in IMRT plan optimization

    International Nuclear Information System (INIS)

    Krause, Michael; Scherrer, Alexander; Thieke, Christian

    2008-01-01

    The formulation of optimization problems in intensity-modulated radiotherapy (IMRT) planning comprises the choice of various values such as function-specific parameters or constraint bounds. In current inverse planning programs that yield a single treatment plan for each optimization, it is often unclear how strongly these modeling parameters affect the resulting plan. This work investigates the mathematical concepts of elasticity and sensitivity to deal with this problem. An artificial planning case with a horse-shoe formed target with different opening angles surrounding a circular risk structure is studied. As evaluation functions the generalized equivalent uniform dose (EUD) and the average underdosage below and average overdosage beyond certain dose thresholds are used. A single IMRT plan is calculated for an exemplary parameter configuration. The elasticity and sensitivity of each parameter are then calculated without re-optimization, and the results are numerically verified. The results show the following. (1) elasticity can quantify the influence of a modeling parameter on the optimization result in terms of how strongly the objective function value varies under modifications of the parameter value. It also can describe how strongly the geometry of the involved planning structures affects the optimization result. (2) Based on the current parameter settings and corresponding treatment plan, sensitivity analysis can predict the optimization result for modified parameter values without re-optimization, and it can estimate the value intervals in which such predictions are valid. In conclusion, elasticity and sensitivity can provide helpful tools in inverse IMRT planning to identify the most critical parameters of an individual planning problem and to modify their values in an appropriate way

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

    International Nuclear Information System (INIS)

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

    2015-01-01

    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

  18. 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

  19. 3D treatment planning systems.

    Science.gov (United States)

    Saw, Cheng B; Li, Sicong

    2018-01-01

    Three-dimensional (3D) treatment planning systems have evolved and become crucial components of modern radiation therapy. The systems are computer-aided designing or planning softwares that speed up the treatment planning processes to arrive at the best dose plans for the patients undergoing radiation therapy. Furthermore, the systems provide new technology to solve problems that would not have been considered without the use of computers such as conformal radiation therapy (CRT), intensity-modulated radiation therapy (IMRT), and volumetric modulated arc therapy (VMAT). The 3D treatment planning systems vary amongst the vendors and also the dose delivery systems they are designed to support. As such these systems have different planning tools to generate the treatment plans and convert the treatment plans into executable instructions that can be implemented by the dose delivery systems. The rapid advancements in computer technology and accelerators have facilitated constant upgrades and the introduction of different and unique dose delivery systems than the traditional C-arm type medical linear accelerators. The focus of this special issue is to gather relevant 3D treatment planning systems for the radiation oncology community to keep abreast of technology advancement by assess the planning tools available as well as those unique "tricks or tips" used to support the different dose delivery systems. Copyright © 2018 American Association of Medical Dosimetrists. Published by Elsevier Inc. All rights reserved.

  20. Computational optimization techniques applied to microgrids planning

    DEFF Research Database (Denmark)

    Gamarra, Carlos; Guerrero, Josep M.

    2015-01-01

    Microgrids are expected to become part of the next electric power system evolution, not only in rural and remote areas but also in urban communities. Since microgrids are expected to coexist with traditional power grids (such as district heating does with traditional heating systems......), their planning process must be addressed to economic feasibility, as a long-term stability guarantee. Planning a microgrid is a complex process due to existing alternatives, goals, constraints and uncertainties. Usually planning goals conflict each other and, as a consequence, different optimization problems...... 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...

  1. Implementation of BNCT treatment planning procedures

    International Nuclear Information System (INIS)

    Capala, J.; Ma, R.; Diaz, A.Z.; Chanana, A.D.; Coderre, J.A.

    2001-01-01

    Estimation of radiation doses delivered during boron neutron capture therapy (BNCT) requires combining data on spatial distribution of both the thermal neutron fluence and the 10 B concentration, as well as the relative biological effectiveness of various radiation dose components in the tumor and normal tissues. Using the treatment planning system created at Idaho National Engineering and Environmental Laboratory and the procedures we had developed for clinical trials, we were able to optimize the treatment position, safely deliver the prescribed BNCT doses, and carry out retrospective analyses and reviews. In this paper we describe the BNCT treatment planning process and its implementation in the ongoing dose escalation trials at Brookhaven National Laboratory. (author)

  2. 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

  3. Reducing the sensitivity of IMPT treatment plans to setup errors and range uncertainties via probabilistic treatment planning

    International Nuclear Information System (INIS)

    Unkelbach, Jan; Bortfeld, Thomas; Martin, Benjamin C.; Soukup, Martin

    2009-01-01

    Treatment plans optimized for intensity modulated proton therapy (IMPT) may be very sensitive to setup errors and range uncertainties. If these errors are not accounted for during treatment planning, the dose distribution realized in the patient may by strongly degraded compared to the planned dose distribution. The authors implemented the probabilistic approach to incorporate uncertainties directly into the optimization of an intensity modulated treatment plan. Following this approach, the dose distribution depends on a set of random variables which parameterize the uncertainty, as does the objective function used to optimize the treatment plan. The authors optimize the expected value of the objective function. They investigate IMPT treatment planning regarding range uncertainties and setup errors. They demonstrate that incorporating these uncertainties into the optimization yields qualitatively different treatment plans compared to conventional plans which do not account for uncertainty. The sensitivity of an IMPT plan depends on the dose contributions of individual beam directions. Roughly speaking, steep dose gradients in beam direction make treatment plans sensitive to range errors. Steep lateral dose gradients make plans sensitive to setup errors. More robust treatment plans are obtained by redistributing dose among different beam directions. This can be achieved by the probabilistic approach. In contrast, the safety margin approach as widely applied in photon therapy fails in IMPT and is neither suitable for handling range variations nor setup errors.

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

    Energy Technology Data Exchange (ETDEWEB)

    Guthier, C [Brigham and Women’s Hospital, Boston, MA (United States); University Medical Center Mannheim, Mannheim (Germany); Harvard Medical School, Boston, MA (United States); Damato, A; Viswanathan, A; Cormack, R [Dana Farber Cancer Institut/Brigham and Women’s Hospital, Boston, MA (United States); Harvard Medical School, Boston, MA (United States); Hesser, J [University Medical Center Mannheim, Mannheim (Germany)

    2016-06-15

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

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

    International Nuclear Information System (INIS)

    Guthier, C; Damato, A; Viswanathan, A; Cormack, R; Hesser, J

    2016-01-01

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

  6. Inverse planning and optimization: a comparison of solutions

    Energy Technology Data Exchange (ETDEWEB)

    Ringor, Michael [School of Health Sciences, Purdue University, West Lafayette, IN (United States); Papiez, Lech [Department of Radiation Oncology, Indiana University, Indianapolis, IN (United States)

    1998-09-01

    The basic problem in radiation therapy treatment planning is to determine an appropriate set of treatment parameters that would induce an effective dose distribution inside a patient. One can approach this task as an inverse problem, or as an optimization problem. In this presentation, we compare both approaches. The inverse problem is presented as a dose reconstruction problem similar to tomography reconstruction. We formulate the optimization problem as linear and quadratic programs. Explicit comparisons are made between the solutions obtained by inversion and those obtained by optimization for the case in which scatter and attenuation are ignored (the NS-NA approximation)

  7. Three-dimensional teletherapy treatment planning

    International Nuclear Information System (INIS)

    Panthaleon van Eck, R.B. van.

    1986-01-01

    This thesis deals with physical/mathematical backgrounds of computerized teletherapy treatment planning. The subjects discussed in this thesis can be subdivided into three main categories: a) Three-dimensional treatment planning. A method is evaluated which can be used for the purpose of simulation and optimization of dose distributions in three dimensions. b) The use of Computed Tomography. The use of patient information obtained from Computed Tomography for the purpose of dose computations is evaluated. c) Dose computational models for photon- and electron beams. Models are evaluated which provide information regarding the way in which the radiation dose is distributed in the patient (viz. is absorbed and/or dispersed). (Auth.)

  8. Optimization approaches for robot trajectory planning

    Directory of Open Access Journals (Sweden)

    Carlos Llopis-Albert

    2018-03-01

    Full Text Available The development of optimal trajectory planning algorithms for autonomous robots is a key issue in order to efficiently perform the robot tasks. This problem is hampered by the complex environment regarding the kinematics and dynamics of robots with several arms and/or degrees of freedom (dof, the design of collision-free trajectories and the physical limitations of the robots. This paper presents a review about the existing robot motion planning techniques and discusses their pros and cons regarding completeness, optimality, efficiency, accuracy, smoothness, stability, safety and scalability.

  9. 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.

  10. Maintenance optimization plan for essential equipment reliability

    International Nuclear Information System (INIS)

    Steffen, D.H.

    1996-02-01

    The Maintenance Optimization Plan (MOP) for Essential Equipment Reliability will furnish Tank Waste Remediation System (TWRS) management with a pro-active, forward-thinking process for maintaining essential structures, systems, and components (ESSC) at the Hanford Site tank farms in their designed condition, and to ensure optimum ESSC availability and reliability

  11. 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...

  12. Optimization of lime treatment processes

    International Nuclear Information System (INIS)

    Zinck, J. M.; Aube, B. C.

    2000-01-01

    Lime neutralization technology used in the treatment of acid mine drainage and other acidic effluents is discussed. Theoretical studies and laboratory experiments designed to optimize the technology of lime neutralization processes and to improve the cost efficiency of the treatment process are described. Effluent quality, slaking temperature, aeration, solid-liquid separation, sludge production and geochemical stability have been studied experimentally and on site. Results show that through minor modification of the treatment process, costs, sludge volume generated, and metal released to the environment can be significantly reduced. 17 refs., 4 figs

  13. Spatiotemporal radiotherapy planning using a global optimization approach

    Science.gov (United States)

    Adibi, Ali; Salari, Ehsan

    2018-02-01

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

  14. Optimized planning methodologies of ASON implementation

    Science.gov (United States)

    Zhou, Michael M.; Tamil, Lakshman S.

    2005-02-01

    Advanced network planning concerns effective network-resource allocation for dynamic and open business environment. Planning methodologies of ASON implementation based on qualitative analysis and mathematical modeling are presented in this paper. The methodology includes method of rationalizing technology and architecture, building network and nodal models, and developing dynamic programming for multi-period deployment. The multi-layered nodal architecture proposed here can accommodate various nodal configurations for a multi-plane optical network and the network modeling presented here computes the required network elements for optimizing resource allocation.

  15. Impact of 'optimized' treatment planning for tandem and ring, and tandem and ovoids, using high dose rate brachytherapy for cervical cancer

    International Nuclear Information System (INIS)

    Noyes, William R.; Peters, Nancy E.; Thomadsen, Bruce R.; Fowler, Jack F.; Buchler, Dolores A.; Stitt, Judith A.; Kinsella, Timothy J.

    1995-01-01

    Purpose: Different treatment techniques are used in high dose rate (HDR) remote afterloading intracavitary brachytherapy for uterine cervical cancer. We have investigated the differences between 'optimized' and 'nonoptimized' therapy using both a tandem and ring (T/R) applicator, and a tandem and ovoids (T/O), applicator. Methods and Materials: HDR afterloading brachytherapy using the Madison System for Stage IB cervical cancer was simulated for 10 different patients using both a T/R applicator and a T/O applicator. A treatment course consists of external beam irradiation and five insertions of HDR afterloading brachytherapy. Full dosimetry calculations were performed at the initial insertion for both applicators and used as a reference for the following four insertions of the appropriate applicator. Forty dosimetry calculations were performed to determine the dose delivered to Point M (similar to Point A), Point E (obturator lymph nodes), vaginal surface, bladder, and rectum. 'Optimized' doses were specified to Point M and to the vaginal surface. 'Nonoptimized' doses were specified to Point M only. Using the linear-quadratic equation, calculations have been performed to convert the delivered dose using HDR to the biologically equivalent doses at the conventional low dose rate (LDR) at 0.60 Gy/h. Results: Major differences between 'optimized' and 'nonoptimized' LDR equivalent doses were found at the vaginal surface, bladder, and rectum. Overdoses at the vaginal surface, bladder, and rectum were calculated to be 208%, nil, and 42%, respectively, for the T/R applicator with 'nonoptimization'. However, for the T/O applicator, the overdoses were smaller, being nil, 32%, and 27%, respectively, with 'nonoptimization'. Conclusion: Doses given in high dose rate intracavitary brachytherapy border on tissue tolerance. 'Optimization' of either applicator decreases the risk of a dose that may have potential for complications. Optimization of a tandem and ovoids best ensures

  16. Frontiers in planning optimization for lung SBRT.

    Science.gov (United States)

    Giglioli, Francesca Romana; Clemente, Stefania; Esposito, Marco; Fiandra, Christian; Marino, Carmelo; Russo, Serenella; Strigari, Lidia; Villaggi, Elena; Stasi, Michele; Mancosu, Pietro

    2017-12-01

    Emerging data are showing the safety and the efficacy of Stereotactic Body Radiation therapy (SBRT) in lung cancer management. In this context, the very high doses delivered to the Planning Target Volume, make the planning phase essential for achieving high dose levels conformed to the shape of the target in order to have a good prognosis for tumor control and to avoid an overdose in relevant healthy adjacent tissue. In this non-systematic review we analyzed the technological and the physics aspects of SBRT planning for lung cancer. In particular, the aims of the study were: (i) to evaluate prescription strategies (homogeneous or inhomogeneous), (ii) to outline possible geometrical solutions by comparing the dosimetric results (iii) to describe the technological possibilities for a safe and effective treatment, (iv) to present the issues concerning radiobiological planning and the automation of the planning process. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

  17. Resampling: An optimization method for inverse planning in robotic radiosurgery

    International Nuclear Information System (INIS)

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

    2006-01-01

    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

  18. 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. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  19. 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.

  20. Applications of NTCP calculations to treatment planning

    International Nuclear Information System (INIS)

    Kutcher, G.J.

    1995-01-01

    A fundamental step in the treatment decision process is the evaluation of a treatment plan. Most often treatment plans are judged by tradition using guidelines like target homogeneity and maximum dose to non-target tissues. While such judgments implicitly assume a relationship between dose distribution parameters and patient response, the judgment process is essentially supported by clinical outcomes from previous treatments. With the development of conformal therapy, new and unusual dose distributions and escalated doses are possible, while the clinical consequences are unknown. this situation has instigated attempts to place plan evaluation on a more systematic platform. One such endeavor has centered around attempts to calculate normal tissue complication probability (NTCP) and its sibling, tumor control probability (TCP). This lecture will be composed of two parts. The first will begin with a review of two categories of NTCP models: (1) an 'empirical' approach, based upon a power-law relationship between partial organ tolerance and irradiated volume, and histogram reduction to account for inhomogeneous irradiation: (2) a 'statistical' approach in which local responses are combined according to the underlying tissue architecture. Since both rely upon clinical data - often of limited and questionable validity - we will review some examples from the clinical and biological literature. The second part of the lecture will review clinical applications of biological-index based models: ranking competing treatment plans; design of dose escalation protocols; optimization of treatment plans with intensity modulation. We will also demonstrate how biological indices can be used to derive dose-volume histograms which account for treatment uncertainty

  1. An Approach for Practical Multiobjective IMRT Treatment Planning

    International Nuclear Information System (INIS)

    Craft, David; Halabi, Tarek; Shih, Helen A.; Bortfeld, Thomas

    2007-01-01

    Purpose: To introduce and demonstrate a practical multiobjective treatment planning procedure for intensity-modulated radiation therapy (IMRT) planning. Methods and Materials: The creation of a database of Pareto optimal treatment plans proceeds in two steps. The first step solves an optimization problem that finds a single treatment plan which is close to a set of clinical aspirations. This plan provides an example of what is feasible, and is then used to determine mutually satisfiable hard constraints for the subsequent generation of the plan database. All optimizations are done using linear programming. Results: The two-step procedure is applied to a brain, a prostate, and a lung case. The plan databases created allow for the selection of a final treatment plan based on the observed tradeoffs between the various organs involved. Conclusions: The proposed method reduces the human iteration time common in IMRT treatment planning. Additionally, the database of plans, when properly viewed, allows the decision maker to make an informed final plan selection

  2. 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

    2006-12-01

    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 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.

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

    International Nuclear Information System (INIS)

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

    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 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

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

    International Nuclear Information System (INIS)

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

    2012-01-01

    Purpose: 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. Methods: 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. Results: 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. Conclusions: The POpR is a feasible and practical method to significantly improve IMRT-plan quality without compromising the planning efficiency.

  5. 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

  6. 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.

  7. Automated radiotherapy treatment plan integrity verification

    International Nuclear Information System (INIS)

    Yang Deshan; Moore, Kevin L.

    2012-01-01

    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. Feature-based plan adaptation for fast treatment planning in scanned ion beam therapy

    International Nuclear Information System (INIS)

    Chen Wenjing; Gemmel, Alexander; Rietzel, Eike

    2013-01-01

    We propose a plan adaptation method for fast treatment plan generation in scanned ion beam therapy. Analysis of optimized treatment plans with carbon ions indicates that the particle number modulation of consecutive rasterspots in depth shows little variation throughout target volumes with convex shape. Thus, we extract a depth-modulation curve (DMC) from existing reference plans and adapt it for creation of new plans in similar treatment situations. The proposed method is tested with seven CT serials of prostate patients and three digital phantom datasets generated with the MATLAB code. Plans are generated with a treatment planning software developed by GSI using single-field uniform dose optimization for all the CT datasets to serve as reference plans and ‘gold standard’. The adapted plans are generated based on the DMC derived from the reference plans of the same patient (intra-patient), different patient (inter-patient) and phantoms (phantom-patient). They are compared with the reference plans and a re-positioning strategy. Generally, in 1 min on a standard PC, either a physical plan or a biological plan can be generated with the adaptive method provided that the new target contour is available. In all the cases, the V95 values of the adapted plans can achieve 97% for either physical or biological plans. V107 is always 0 indicating no overdosage, and target dose homogeneity is above 0.98 in all cases. The dose received by the organs at risk is comparable to the optimized plans. The plan adaptation method has the potential for on-line adaptation to deal with inter-fractional motion, as well as fast off-line treatment planning, with either the prescribed physical dose or the RBE-weighted dose. (paper)

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

    International Nuclear Information System (INIS)

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

    2015-01-01

    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. (paper)

  11. Automated treatment planning engine for prostate seed implant brachytherapy

    International Nuclear Information System (INIS)

    Yu Yan; Zhang, J.B.Y.; Brasacchio, Ralph A.; Okunieff, Paul G.; Rubens, Deborah J.; Strang, John G.; Soni, Arvind; Messing, Edward M.

    1999-01-01

    Purpose: To develop a computer-intelligent planning engine for automated treatment planning and optimization of ultrasound- and template-guided prostate seed implants. Methods and Materials: The genetic algorithm was modified to reflect the 2D nature of the implantation template. A multi-objective decision scheme was used to rank competing solutions, taking into account dose uniformity and conformity to the planning target volume (PTV), dose-sparing of the urethra and the rectum, and the sensitivity of the resulting dosimetry to seed misplacement. Optimized treatment plans were evaluated using selected dosimetric quantifiers, dose-volume histogram (DVH), and sensitivity analysis based on simulated seed placement errors. These dosimetric planning components were integrated into the Prostate Implant Planning Engine for Radiotherapy (PIPER). Results: PIPER has been used to produce a variety of plans for prostate seed implants. In general, maximization of the minimum peripheral dose (mPD) for given implanted total source strength tended to produce peripherally weighted seed patterns. Minimization of the urethral dose further reduced the loading in the central region of the PTV. Isodose conformity to the PTV was achieved when the set of objectives did not reflect seed positioning uncertainties; the corresponding optimal plan generally required fewer seeds and higher source strength per seed compared to the manual planning experience. When seed placement uncertainties were introduced into the set of treatment planning objectives, the optimal plan tended to reach a compromise between the preplanned outcome and the likelihood of retaining the preferred outcome after implantation. The reduction in the volatility of such seed configurations optimized under uncertainty was verified by sensitivity studies. Conclusion: An automated treatment planning engine incorporating real-time sensitivity analysis was found to be a useful tool in dosimetric planning for prostate

  12. Admission and capacity planning for the implementation of one-stop-shop in skin cancer treatment using simulation-based optimization.

    Science.gov (United States)

    Romero, H L; Dellaert, N P; van der Geer, S; Frunt, M; Jansen-Vullers, M H; Krekels, G A M

    2013-03-01

    Hospitals and health care institutions are facing the challenge of improving the quality of their services while reducing their costs. The current study presents the application of operations management practices in a dermatology oncology outpatient clinic specialized in skin cancer treatment. An interesting alternative considered by the clinic is the implementation of a one-stop-shop concept for the treatment of new patients diagnosed with basal cell carcinoma. This alternative proposes a significant improvement in the average waiting time that a patient spends between the diagnosis and treatment. This study is focused on the identification of factors that influence the average throughput time of patients treated in the clinic from the logistic perspective. A two-phase approach was followed to achieve the goals stated in this study. The first phase included an integrated approach for the deterministic analysis of the capacity using a demand-supply model for the hospital processes, while the second phase involved the development of a simulation model to include variability to the activities involved in the process and to evaluate different scenarios. Results showed that by managing three factors: the admission rule, resources allocation and capacity planning in the dermato-oncology unit throughput times for treatments of new patients can be decreased with more than 90 %, even with the same resource level. Finally, a pilot study with 16 patients was also conducted to evaluate the impact of implementing the one stop shop concept from a clinical perspective. Patients turned out to be satisfied with the fast diagnosis and treatment.

  13. An FDTD code for hyperthermia treatment planning

    Energy Technology Data Exchange (ETDEWEB)

    Marrocco, G.; Bardati, F. [Rome Univ. Tor Vergata (Italy). Dipt. di Informatica, sistemi e produzione; Tognolatti, P. [L' Aquila Univ. (Italy). Dipt. di Ingegneria Elettrica

    1999-08-01

    Radio-frequency hyperthermia is an anticancer modality based on the heating of tumours by radiating sources. A set of antennas is frequently used to enhance power depositions in tissues. Treatments planning needs electromagnetic field computation within realistic body models. Since several simulation may be required the optimize the antenna-body configuration, the electromagnetic solver should be designed in such a way that new configuration of the antenna set-up can be solved without heavy changes of the basic numerical code. In this paper a numerical investigation on the effects of a segmentation technique will be presented, with reference to an FDTD computation and the heating of a paediatric tumour.

  14. 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.

  15. Considering FACTS in Optimal Transmission Expansion Planning

    Directory of Open Access Journals (Sweden)

    K. Soleimani

    2017-10-01

    Full Text Available The expansion of power transmission systems is an important part of the expansion of power systems that requires enormous investment costs. Since the construction of new transmission lines is very expensive, it is necessary to choose the most efficient expansion plan that ensures system security with a minimal number of new lines. In this paper, the role of Flexible AC Transmission System (FACTS devices in the effective operation and expansion planning of transmission systems is examined. Effort was taken to implement a method based on sensitivity analysis to select the optimal number and location of FACTS devices, lines and other elements of the transmission system. Using this method, the transmission expansion plan for a 9 and a 39 bus power system was performed with and without the presence of FACTS with the use of DPL environment in Digsilent software 15.1. Results show that the use of these devices reduces the need for new transmission lines and minimizes the investment cost.

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

    International Nuclear Information System (INIS)

    Orton, C.

    2015-01-01

    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

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

    International Nuclear Information System (INIS)

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

    2010-01-01

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

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

    Science.gov (United States)

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

    2010-09-01

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

  19. 3-D CT for cardiovascular treatment planning

    International Nuclear Information System (INIS)

    Wildermuth, S.; Leschka, S.; Duru, F.; Alkadhi, H.

    2005-01-01

    The recently developed 64-slice CT scanner together with the use of 2-D and 3-D reconstructions can aid the cardiovascular surgeon and interventional radiologist in visualizing exact geometric relationships to plan and execute complex procedures via minimally invasive or standard approaches.Cardiac 64-slice CT considerably benefits from the high temporal and spatial resolution allowing the reliable depiction of small coronary segments. Similarly, abdominal vascular 64-slice CT became possible within short examination times and allowing an optimal arterial contrast bolus exploitation. We demonstrate four representative cardiac and abdominal examples using the new 64-slice CT technology which reveal the impact of the new scanner generation for cardiovascular treatment planning. (orig.)

  20. Treatment planning with ion beams

    International Nuclear Information System (INIS)

    Foss, M.H.

    1985-01-01

    Ions have higher linear energy transfer (LET) near the end of their range and lower LET away from the end of their range. Mixing radiations of different LET complicates treatment planning because radiation kills cells in two statistically independent ways. In some cases, cells are killed by a single-particle, which causes a linear decrease in log survival at low dosage. When the linear decrease is subtracted from the log survival curve, the remaining curve has zero slope at zero dosage. This curve is the log survival curve for cells that are killed only by two or more particles. These two mechanisms are statistically independent. To calculate survival, these two kinds of doses must be accumulated separately. The effect of each accumulated dosage must be read from its survival curve, and the logarithms of the two effects added to get the log survival. Treatment plans for doses of protons, He 3 ions, and He 4 ions suggest that these ions will be useful therapeutic modalities

  1. Volumetric Modulated Arc Therapy (VMAT) Treatment Planning for Superficial Tumors

    International Nuclear Information System (INIS)

    Zacarias, Albert S.; Brown, Mellonie F.; Mills, Michael D.

    2010-01-01

    The physician's planning objective is often a uniform dose distribution throughout the planning target volume (PTV), including superficial PTVs on or near the surface of a patient's body. Varian's Eclipse treatment planning system uses a progressive resolution optimizer (PRO), version 8.2.23, for RapidArc dynamic multileaf collimator volumetric modulated arc therapy planning. Because the PRO is a fast optimizer, optimization convergence errors (OCEs) produce dose nonuniformity in the superficial area of the PTV. We present a postsurgical cranial case demonstrating the recursive method our clinic uses to produce RapidArc treatment plans. The initial RapidArc treatment plan generated using one 360 o arc resulted in substantial dose nonuniformity in the superficial section of the PTV. We demonstrate the use of multiple arcs to produce improved dose uniformity in this region. We also compare the results of this superficial dose compensation method to the results of a recursive method of dose correction that we developed in-house to correct optimization convergence errors in static intensity-modulated radiation therapy treatment plans. The results show that up to 4 arcs may be necessary to provide uniform dose to the surface of the PTV with the current version of the PRO.

  2. [Treatment strategy and planning for pilon fractures].

    Science.gov (United States)

    Mittlmeier, Thomas; Wichelhaus, Alice

    2017-08-01

    Pilon fractures are mainly severe and prognostically serious injuries with a high rate of relevant soft tissue involvement. The adequate decision making and choice of treatment in the early phase of trauma are of paramount importance for the final outcome. This essentially encompasses the management of the soft tissue damage, the surgical planning and the differentiated selection of procedures. Most concepts of staged treatment nowadays offer a wide range of options which are integrated into expert-based algorithms. The aim of the present analysis was to display the strategy variations for the treatment of pilon fractures taking into account the advantages and disadvantages of the corresponding treatment concepts. A staged procedure including primary closed reduction employing ligamentotaxis and fixation of the joints of the hindfoot via tibiocalcaneal metatarsal fixation offers a safe basis for consecutive imaging and the selection of specific approaches for definitive reconstruction. A simultaneous reconstruction and fixation of the fibula during the primary intervention are generally not recommended in order to avoid any limitations for subsequent reconstructive procedures. A time frame for definitive reconstruction covers a period of up to 3 weeks after trauma and allows a detailed planning considering the individual dynamics of the soft tissue situation and any logistic requirements. For the choice of the definitive treatment concept a wide range of procedures and implants are available. There are also valid concepts for primary treatment of defined fracture constellations while primary arthrodesis represents a solution in cases of major destruction of the joint surface. Knowledge of the multiple procedural variations for pilon fracture treatment creates the basis to optimize the treatment modalities and to take into account individual parameters of the fracture.

  3. Functional avoidance of lung in plan optimization with an aperture-based inverse planning system

    International Nuclear Information System (INIS)

    St-Hilaire, Jason; Lavoie, Caroline; Dagnault, Anne; Beaulieu, Frederic; Morin, Francis; Beaulieu, Luc; Tremblay, Daniel

    2011-01-01

    Purpose: To implement SPECT-based optimization in an anatomy-based aperture inverse planning system for the functional avoidance of lung in thoracic irradiation. Material and methods: SPECT information has been introduced as a voxel-by-voxel modulation of lung importance factors proportionally to the local perfusion count. Fifteen cases of lung cancer have been retrospectively analyzed by generating angle-optimized non-coplanar plans, comparing a purely anatomical approach and our functional approach. Planning target volume coverage and lung sparing have been compared. Statistical significance was assessed by a Wilcoxon matched pairs test. Results: For similar target coverage, perfusion-weighted volume receiving 10 Gy was reduced by a median of 2.2% (p = 0.022) and mean perfusion-weighted lung dose, by a median of 0.9 Gy (p = 0.001). A separate analysis of patients with localized or non-uniform hypoperfusion could not show which would benefit more from SPECT-based treatment planning. Redirection of dose sometimes created overdosage regions in the target volume. Plans consisted of a similar number of segments and monitor units. Conclusions: Angle optimization and SPECT-based modulation of importance factors allowed for functional avoidance of the lung while preserving target coverage. The technique could be also applied to implement PET-based modulation inside the target volume, leading to a safer dose escalation.

  4. Real-time interactive treatment planning

    International Nuclear Information System (INIS)

    Otto, Karl

    2014-01-01

    The goal of this work is to develop an interactive treatment planning platform that permits real-time manipulation of dose distributions including DVHs and other dose metrics. The hypothesis underlying the approach proposed here is that the process of evaluating potential dose distribution options and deciding on the best clinical trade-offs may be separated from the derivation of the actual delivery parameters used for the patient’s treatment. For this purpose a novel algorithm for deriving an Achievable Dose Estimate (ADE) was developed. The ADE algorithm is computationally efficient so as to update dose distributions in effectively real-time while accurately incorporating the limits of what can be achieved in practice. The resulting system is a software environment for interactive real-time manipulation of dose that permits the clinician to rapidly develop a fully customized 3D dose distribution. Graphical navigation of dose distributions is achieved by a sophisticated method of identifying contributing fluence elements, modifying those elements and re-computing the entire dose distribution. 3D dose distributions are calculated in ∼2–20 ms. Including graphics processing overhead, clinicians may visually interact with the dose distribution (e.g. ‘drag’ a DVH) and display updates of the dose distribution at a rate of more than 20 times per second. Preliminary testing on various sites shows that interactive planning may be completed in ∼1–5 min, depending on the complexity of the case (number of targets and OARs). Final DVHs are derived through a separate plan optimization step using a conventional VMAT planning system and were shown to be achievable within 2% and 4% in high and low dose regions respectively. With real-time interactive planning trade-offs between Target(s) and OARs may be evaluated efficiently providing a better understanding of the dosimetric options available to each patient in static or adaptive RT. (paper)

  5. 3-D conformal radiation therapy - Part I: Treatment planning

    International Nuclear Information System (INIS)

    Burman, Chandra M.; Mageras, Gikas S.

    1997-01-01

    Objective: In this presentation we will look into the basic components of 3-dimensional conformal treatment planning, and will discuss planning for some selected sites. We will also review some current and future trends in 3-D treatment planning. External beam radiation therapy is one of the arms of cancer treatment. In the recent years 3-D conformal therapy had significant impact on the practice of external beam radiation therapy. Conformal radiation therapy shapes the high-dose volume so as to conform to the target volume while minimizing the dose to the surrounding normal tissues. The advances that have been achieved in conformal therapy are in part due to the development of 3-D treatment planning, which in turn has capitalized on 3-D imaging for tumor and normal tissue localization, as well as on available computational power for the calculation of 3-D dose distributions, visualization of anatomical and dose volumes, and numerical evaluation of treatment plans. In this course we will give an overview of how 3-D conformal treatments are designed and transferred to the patient. Topics will include: 1) description of the major components of a 3-D treatment planning system, 2) techniques for designing treatments, 3) evaluation of treatment plans using dose distribution displays, dose-volume histograms and normal tissue complication probabilities, 4) implementation of treatments using shaped blocks and multileaf collimators, 5) verification of treatment delivery using portal films and electronic portal imaging devices. We will also discuss some current and future trends in 3-D treatment planning, such as field shaping with multileaf collimation, computerized treatment plan optimization, including the use of nonuniform beam profiles (intensity modulation), and incorporating treatment uncertainties due to patient positioning errors and organ motion into treatment planning process

  6. Optimization of the production plan and risk control in Third Qinshan Nuclear Power Co.,Ltd

    International Nuclear Information System (INIS)

    Zhou Jun

    2009-01-01

    Some optimized and improved measures have been taken in Third Qinshan Nuclear Power Co., Ltd. (TQNPC) to optimize the routine production plan management, strengthen the maintenance work risk analysis, and improve the plan execution capability. Which involve unified management of generation, refueling, periodic test and maintenance plans; simplifying the defect scale and reducing the intermediate link of defect treatment; intensifying the appraisal on plan execution and adopting star performance evaluation and merit rating measures. In this paper, the above-mentioned improvement and optimization are introduced comprehensively and systematically. (authors)

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

    International Nuclear Information System (INIS)

    Fogliata, Antonella; Nicolini, Giorgia; Clivio, Alessandro; Vanetti, Eugenio; Laksar, Sarbani; Tozzi, Angelo; Scorsetti, Marta; Cozzi, Luca

    2015-01-01

    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. The online version of this article (doi:10.1186/s13014-015-0530-5) contains supplementary material, which is available to authorized users

  8. Assessment of PlanIQ Feasibility DVH for head and neck treatment planning.

    Science.gov (United States)

    Fried, David V; Chera, Bhishamjit S; Das, Shiva K

    2017-09-01

    Designing a radiation plan that optimally delivers both target coverage and normal tissue sparing is challenging. There are limited tools to determine what is dosimetrically achievable and frequently the experience of the planner/physician is relied upon to make these determinations. PlanIQ software provides a tool that uses target and organ at risk (OAR) geometry to indicate the difficulty of achieving different points for organ dose-volume histograms (DVH). We hypothesized that PlanIQ Feasibility DVH may aid planners in reducing dose to OARs. Clinically delivered head and neck treatments (clinical plan) were re-planned (re-plan) putting high emphasis on maximally sparing the contralateral parotid gland, contralateral submandibular gland, and larynx while maintaining routine clinical dosimetric objectives. The planner was blinded to the results of the clinically delivered plan as well as the Feasibility DVHs from PlanIQ. The re-plan treatments were designed using 3-arc VMAT in Raystation (RaySearch Laboratories, Sweden). The planner was then given the results from the PlanIQ Feasibility DVH analysis and developed an additional plan incorporating this information using 4-arc VMAT (IQ plan). The DVHs across the three treatment plans were compared with what was deemed "impossible" by PlanIQ's Feasibility DVH (Impossible DVH). The impossible DVH (red) is defined as the DVH generated using the minimal dose that any voxel outside the targets must receive given 100% target coverage. The re-plans performed blinded to PlanIQ Feasibilty DVH achieved superior sparing of aforementioned OARs compared to the clinically delivered plans and resulted in discrepancies from the impossible DVHs by an average of 200-700 cGy. Using the PlanIQ Feasibility DVH led to additionalOAR sparing compared to both the re-plans and clinical plans and reduced the discrepancies from the impossible DVHs to an average of approximately 100 cGy. The dose reduction from clinical to re-plan and re-plan to

  9. Automated Planning of Tangential Breast Intensity-Modulated Radiotherapy Using Heuristic Optimization

    International Nuclear Information System (INIS)

    Purdie, Thomas G.; Dinniwell, Robert E.; Letourneau, Daniel; Hill, Christine; Sharpe, Michael B.

    2011-01-01

    Purpose: To present an automated technique for two-field tangential breast intensity-modulated radiotherapy (IMRT) treatment planning. Method and Materials: A total of 158 planned patients with Stage 0, I, and II breast cancer treated using whole-breast IMRT were retrospectively replanned using automated treatment planning tools. The tools developed are integrated into the existing clinical treatment planning system (Pinnacle 3 ) and are designed to perform the manual volume delineation, beam placement, and IMRT treatment planning steps carried out by the treatment planning radiation therapist. The automated algorithm, using only the radio-opaque markers placed at CT simulation as inputs, optimizes the tangential beam parameters to geometrically minimize the amount of lung and heart treated while covering the whole-breast volume. The IMRT parameters are optimized according to the automatically delineated whole-breast volume. Results: The mean time to generate a complete treatment plan was 6 min, 50 s ± 1 min 12 s. For the automated plans, 157 of 158 plans (99%) were deemed clinically acceptable, and 138 of 158 plans (87%) were deemed clinically improved or equal to the corresponding clinical plan when reviewed in a randomized, double-blinded study by one experienced breast radiation oncologist. In addition, overall the automated plans were dosimetrically equivalent to the clinical plans when scored for target coverage and lung and heart doses. Conclusion: We have developed robust and efficient automated tools for fully inversed planned tangential breast IMRT planning that can be readily integrated into clinical practice. The tools produce clinically acceptable plans using only the common anatomic landmarks from the CT simulation process as an input. We anticipate the tools will improve patient access to high-quality IMRT treatment by simplifying the planning process and will reduce the effort and cost of incorporating more advanced planning into clinical practice.

  10. Vector-model-supported approach in prostate plan optimization

    International Nuclear Information System (INIS)

    Liu, Eva Sau Fan; Wu, Vincent Wing Cheung; Harris, Benjamin; Lehman, Margot; Pryor, David; Chan, Lawrence Wing Chi

    2017-01-01

    Lengthy time consumed in traditional manual plan optimization can limit the use of step-and-shoot intensity-modulated radiotherapy/volumetric-modulated radiotherapy (S&S IMRT/VMAT). A vector model base, retrieving similar radiotherapy cases, was developed with respect to the structural and physiologic features extracted from the Digital Imaging and Communications in Medicine (DICOM) files. Planning parameters were retrieved from the selected similar reference case and applied to the test case to bypass the gradual adjustment of planning parameters. Therefore, the planning time spent on the traditional trial-and-error manual optimization approach in the beginning of optimization could be reduced. Each S&S IMRT/VMAT prostate reference database comprised 100 previously treated cases. Prostate cases were replanned with both traditional optimization and vector-model-supported optimization based on the oncologists' clinical dose prescriptions. A total of 360 plans, which consisted of 30 cases of S&S IMRT, 30 cases of 1-arc VMAT, and 30 cases of 2-arc VMAT plans including first optimization and final optimization with/without vector-model-supported optimization, were compared using the 2-sided t-test and paired Wilcoxon signed rank test, with a significance level of 0.05 and a false discovery rate of less than 0.05. For S&S IMRT, 1-arc VMAT, and 2-arc VMAT prostate plans, there was a significant reduction in the planning time and iteration with vector-model-supported optimization by almost 50%. When the first optimization plans were compared, 2-arc VMAT prostate plans had better plan quality than 1-arc VMAT plans. The volume receiving 35 Gy in the femoral head for 2-arc VMAT plans was reduced with the vector-model-supported optimization compared with the traditional manual optimization approach. Otherwise, the quality of plans from both approaches was comparable. Vector-model-supported optimization was shown to offer much shortened planning time and iteration

  11. Vector-model-supported approach in prostate plan optimization

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Eva Sau Fan [Department of Radiation Oncology, Princess Alexandra Hospital, Brisbane (Australia); Department of Health Technology and Informatics, The Hong Kong Polytechnic University (Hong Kong); Wu, Vincent Wing Cheung [Department of Health Technology and Informatics, The Hong Kong Polytechnic University (Hong Kong); Harris, Benjamin [Department of Radiation Oncology, Princess Alexandra Hospital, Brisbane (Australia); Lehman, Margot; Pryor, David [Department of Radiation Oncology, Princess Alexandra Hospital, Brisbane (Australia); School of Medicine, University of Queensland (Australia); Chan, Lawrence Wing Chi, E-mail: wing.chi.chan@polyu.edu.hk [Department of Health Technology and Informatics, The Hong Kong Polytechnic University (Hong Kong)

    2017-07-01

    Lengthy time consumed in traditional manual plan optimization can limit the use of step-and-shoot intensity-modulated radiotherapy/volumetric-modulated radiotherapy (S&S IMRT/VMAT). A vector model base, retrieving similar radiotherapy cases, was developed with respect to the structural and physiologic features extracted from the Digital Imaging and Communications in Medicine (DICOM) files. Planning parameters were retrieved from the selected similar reference case and applied to the test case to bypass the gradual adjustment of planning parameters. Therefore, the planning time spent on the traditional trial-and-error manual optimization approach in the beginning of optimization could be reduced. Each S&S IMRT/VMAT prostate reference database comprised 100 previously treated cases. Prostate cases were replanned with both traditional optimization and vector-model-supported optimization based on the oncologists' clinical dose prescriptions. A total of 360 plans, which consisted of 30 cases of S&S IMRT, 30 cases of 1-arc VMAT, and 30 cases of 2-arc VMAT plans including first optimization and final optimization with/without vector-model-supported optimization, were compared using the 2-sided t-test and paired Wilcoxon signed rank test, with a significance level of 0.05 and a false discovery rate of less than 0.05. For S&S IMRT, 1-arc VMAT, and 2-arc VMAT prostate plans, there was a significant reduction in the planning time and iteration with vector-model-supported optimization by almost 50%. When the first optimization plans were compared, 2-arc VMAT prostate plans had better plan quality than 1-arc VMAT plans. The volume receiving 35 Gy in the femoral head for 2-arc VMAT plans was reduced with the vector-model-supported optimization compared with the traditional manual optimization approach. Otherwise, the quality of plans from both approaches was comparable. Vector-model-supported optimization was shown to offer much shortened planning time and iteration

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

    Science.gov (United States)

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

    2010-11-01

    Both spatial and biological information are necessary in order to perform true optimization of a treatment plan and for predicting clinical outcome. The goal of this work is to develop an enhanced treatment plan evaluation tool which incorporates biological parameters and retains spatial dose information. A software system is developed which provides biological plan evaluation with a novel combination of features. It incorporates hyper-radiosensitivity using the induced-repair model and applies the new concept of dose convolution filter (DCF) to simulate dose wash-out effects due to cell migration, bystander effect, and/or tissue motion during treatment. Further, the concept of spatial DVH (sDVH) is introduced to evaluate and potentially optimize the spatial dose distribution in the target volume. Finally, generalized equivalent uniform dose is derived from both the physical dose distribution (gEUD) and the distribution of equivalent dose in 2 Gy fractions (gEUD2) and the software provides three separate models for calculation of tumor control probability (TCP), normal tissue complication probability (NTCP), and probability of uncomplicated tumor control (P+). TCP, NTCP, and P+ are provided as a function of prescribed dose and multivariable TCP, NTCP, and P+ plots are provided to illustrate the dependence on individual parameters used to calculate these quantities. Ten plans from two clinical treatment sites are selected to test the three calculation models provided by this software. By retaining both spatial and biological information about the dose distribution, the software is able to distinguish features of radiotherapy treatment plans not discernible using commercial systems. Plans that have similar DVHs may have different spatial and biological characteristics and the application of novel tools such as sDVH and DCF within the software may substantially change the apparent plan quality or predicted plan metrics such as TCP and NTCP. For the cases examined

  13. Accuracy requirements in radiotherapy treatment planning

    International Nuclear Information System (INIS)

    Buzdar, S. A.; Afzal, M.; Nazir, A.; Gadhi, M. A.

    2013-01-01

    Radiation therapy attempts to deliver ionizing radiation to the tumour and can improve the survival chances and/or quality of life of patients. There are chances of errors and uncertainties in the entire process of radiotherapy that may affect the accuracy and precision of treatment management and decrease degree of conformation. All expected inaccuracies, like radiation dose determination, volume calculation, complete evaluation of the full extent of the tumour, biological behaviour of specific tumour types, organ motion during radiotherapy, imaging, biological/molecular uncertainties, sub-clinical diseases, microscopic spread of the disease, uncertainty in normal tissue responses and radiation morbidity need sound appreciation. Conformity can be increased by reduction of such inaccuracies. With the yearly increase in computing speed and advancement in other technologies the future will provide the opportunity to optimize a greater number of variables and reduce the errors in the treatment planning process. In multi-disciplined task of radiotherapy, efforts are needed to overcome the errors and uncertainty, not only by the physicists but also by radiologists, pathologists and oncologists to reduce molecular and biological uncertainties. The radiation therapy physics is advancing towards an optimal goal that is definitely to improve accuracy where necessary and to reduce uncertainty where possible. (author)

  14. 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.

  15. Conversion of helical tomotherapy plans to step-and-shoot IMRT plans--Pareto front evaluation of plans from a new treatment planning system.

    Science.gov (United States)

    Petersson, Kristoffer; Ceberg, Crister; Engström, Per; Benedek, Hunor; Nilsson, Per; Knöös, Tommy

    2011-06-01

    The resulting plans from a new type of treatment planning system called SharePlan have been studied. This software allows for the conversion of treatment plans generated in a TomoTherapy system for helical delivery, into plans deliverable on C-arm linear accelerators (linacs), which is of particular interest for clinics with a single TomoTherapy unit. The purpose of this work was to evaluate and compare the plans generated in the SharePlan system with the original TomoTherapy plans and with plans produced in our clinical treatment planning system for intensity-modulated radiation therapy (IMRT) on C-arm linacs. In addition, we have analyzed how the agreement between SharePlan and TomoTherapy plans depends on the number of beams and the total number of segments used in the optimization. Optimized plans were generated for three prostate and three head-and-neck (H&N) cases in the TomoTherapy system, and in our clinical treatment planning systems (TPS) used for IMRT planning with step-and-shoot delivery. The TomoTherapy plans were converted into step-and-shoot IMRT plans in SharePlan. For each case, a large number of Pareto optimal plans were created to compare plans generated in SharePlan with plans generated in the Tomotherapy system and in the clinical TPS. In addition, plans were generated in SharePlan for the three head-and-neck cases to evaluate how the plan quality varied with the number of beams used. Plans were also generated with different number of beams and segments for other patient cases. This allowed for an evaluation of how to minimize the number of required segments in the converted IMRT plans without compromising the agreement between them and the original TomoTherapy plans. The plans made in SharePlan were as good as or better than plans from our clinical system, but they were not as good as the original TomoTherapy plans. This was true for both the head-and-neck and the prostate cases, although the differences between the plans for the latter were

  16. Adaptive treatment-length optimization in spatiobiologically integrated radiotherapy

    Science.gov (United States)

    Ajdari, Ali; Ghate, Archis; Kim, Minsun

    2018-04-01

    Recent theoretical research on spatiobiologically integrated radiotherapy has focused on optimization models that adapt fluence-maps to the evolution of tumor state, for example, cell densities, as observed in quantitative functional images acquired over the treatment course. We propose an optimization model that adapts the length of the treatment course as well as the fluence-maps to such imaged tumor state. Specifically, after observing the tumor cell densities at the beginning of a session, the treatment planner solves a group of convex optimization problems to determine an optimal number of remaining treatment sessions, and a corresponding optimal fluence-map for each of these sessions. The objective is to minimize the total number of tumor cells remaining (TNTCR) at the end of this proposed treatment course, subject to upper limits on the biologically effective dose delivered to the organs-at-risk. This fluence-map is administered in future sessions until the next image is available, and then the number of sessions and the fluence-map are re-optimized based on the latest cell density information. We demonstrate via computer simulations on five head-and-neck test cases that such adaptive treatment-length and fluence-map planning reduces the TNTCR and increases the biological effect on the tumor while employing shorter treatment courses, as compared to only adapting fluence-maps and using a pre-determined treatment course length based on one-size-fits-all guidelines.

  17. 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

    International Nuclear Information System (INIS)

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

    2016-01-01

    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. (paper)

  18. 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

  19. SBNCT plan: A 3-dimensional treatment planning system for boron neutron capture therapy

    International Nuclear Information System (INIS)

    Reinstein, L.E.; Ramsay, E.B.; Gajewski, J.; Ramamoorthy, S.; Meek, A.G.

    1993-01-01

    The need for accurate and comprehensive 3-dimensional treatment planning for boron neutron capture therapy (BNCT) has been debated for the past several years. Although many argue against the need for elaborate and expensive treatment planning programs which mimic conventional radiotherapy planning systems, it is clear that in order to realize significant gains over conventional fractionated radiation therapy, patients must be treated to the edge of normal tissue tolerance. Just how close to this edge is dictated by the uncertainties in dosimetry. Hence the focus of BNCT planning is the determination of dose distribution throughout normal tissue volumes. Although precise geometric manipulation of the epithermal neutron beam is not achievable, the following variables play an important role in BNCT optimization: patient orientation, dose fractionation, number of fields, megawatt-minutes per fraction, use of surface bolus, and use of collimation. Other variables which are not as easily adjustable and would not, therefore, be part of treatment planning optimization, include external patient contour, internal patient heterogeneities, boron compound distributions, and RBE's. The boron neutron capture therapy planning system developed at SUNY Stony Brook (SBNCT-Plan) was designed as an interactive graphic tool to assist the radiation oncologist in generating the optimum plan for a neutron capture treatment

  20. Optimal treatment of acute cholecystitis

    NARCIS (Netherlands)

    Loozen, C.S.

    2017-01-01

    The studies presented in this thesis focus on two main issues: treatment strategies for acute calculous cholecystitis (Part I), and the management of acute calculous cholecystitis in high-risk patients in particular (Part II). The last chapter focuses on the surgical treatment of common bile duct

  1. Optimal Treatment of Symptomatic Hemorrhoids

    Science.gov (United States)

    Kim, Soung-Ho

    2011-01-01

    Hemorrhoids are the most common anorectal complaint, and approximately 10 to 20 percent of patients with symptomatic hemorrhoids require surgery. Symptoms of hemorrhoids, such as painless rectal bleeding, tissue protrusion and mucous discharge, vary. The traditional therapeutic strategies of medicine include surgical, as well as non-surgical, treatment. To alleviate symptoms caused by hemorrhoids, oral treatments, such as fiber, suppositories and Sitz baths have been applied to patients. Other non-surgical treatments, such as infrared photocoagulation, injection sclerotherapy and rubber band ligation have been used to fixate the hemorrhoid's cushion. If non-surgical treatment has no effect, surgical treatments, such as a hemorrhoidectomy, procedure for prolapsed hemorrhoids, and transanal hemorrhoidal dearterialization are used. PMID:22259741

  2. Clinical physics for charged particle treatment planning

    International Nuclear Information System (INIS)

    Chen, G.T.Y.; Pitluck, S.; Lyman, J.T.

    1981-01-01

    The installation of a computerized tomography (CT) scanner which can be used with the patient in an upright position is described. This technique will enhance precise location of tumor position relative to critical structures for accurate charged particle dose delivery during fixed horizontal beam radiotherapy. Pixel-by-pixel treatment planning programs have been developed to calculate the dose distribution from multi-port charged particle beams. The plan includes CT scans, data interpretation, and dose calculations. The treatment planning computer is discussed. Treatment planning for irradiation of ocular melanomas is described

  3. Optimal Treatment of Symptomatic Hemorrhoids

    OpenAIRE

    Song, Seok-Gyu; Kim, Soung-Ho

    2011-01-01

    Hemorrhoids are the most common anorectal complaint, and approximately 10 to 20 percent of patients with symptomatic hemorrhoids require surgery. Symptoms of hemorrhoids, such as painless rectal bleeding, tissue protrusion and mucous discharge, vary. The traditional therapeutic strategies of medicine include surgical, as well as non-surgical, treatment. To alleviate symptoms caused by hemorrhoids, oral treatments, such as fiber, suppositories and Sitz baths have been applied to patients. Othe...

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

    Science.gov (United States)

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

    2018-01-01

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

  5. Monte Carlo Treatment Planning for Advanced Radiotherapy

    DEFF Research Database (Denmark)

    Cronholm, Rickard

    This Ph.d. project describes the development of a workflow for Monte Carlo Treatment Planning for clinical radiotherapy plans. The workflow may be utilized to perform an independent dose verification of treatment plans. Modern radiotherapy treatment delivery is often conducted by dynamically...... modulating the intensity of the field during the irradiation. The workflow described has the potential to fully model the dynamic delivery, including gantry rotation during irradiation, of modern radiotherapy. Three corner stones of Monte Carlo Treatment Planning are identified: Building, commissioning...... 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...

  6. Inverse treatment planning based on MRI for HDR prostate brachytherapy

    International Nuclear Information System (INIS)

    Citrin, Deborah; Ning, Holly; Guion, Peter; Li Guang; Susil, Robert C.; Miller, Robert W.; Lessard, Etienne; Pouliot, Jean; Xie Huchen; Capala, Jacek; Coleman, C. Norman; Camphausen, Kevin; Menard, Cynthia

    2005-01-01

    Purpose: To develop and optimize a technique for inverse treatment planning based solely on magnetic resonance imaging (MRI) during high-dose-rate brachytherapy for prostate cancer. Methods and materials: Phantom studies were performed to verify the spatial integrity of treatment planning based on MRI. Data were evaluated from 10 patients with clinically localized prostate cancer who had undergone two high-dose-rate prostate brachytherapy boosts under MRI guidance before and after pelvic radiotherapy. Treatment planning MRI scans were systematically evaluated to derive a class solution for inverse planning constraints that would reproducibly result in acceptable target and normal tissue dosimetry. Results: We verified the spatial integrity of MRI for treatment planning. MRI anatomic evaluation revealed no significant displacement of the prostate in the left lateral decubitus position, a mean distance of 14.47 mm from the prostatic apex to the penile bulb, and clear demarcation of the neurovascular bundles on postcontrast imaging. Derivation of a class solution for inverse planning constraints resulted in a mean target volume receiving 100% of the prescribed dose of 95.69%, while maintaining a rectal volume receiving 75% of the prescribed dose of <5% (mean 1.36%) and urethral volume receiving 125% of the prescribed dose of <2% (mean 0.54%). Conclusion: Systematic evaluation of image spatial integrity, delineation uncertainty, and inverse planning constraints in our procedure reduced uncertainty in planning and treatment

  7. 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

  8. Admission and capacity planning for the implementation of one-stop-shop in skin cancer treatment using simulation-based optimization

    NARCIS (Netherlands)

    Romero, H.L.; Dellaert, N.P.; Geer, van de S.A.; Frunt, M.; Vullers - Jansen, M.H.; Krekels, G.A.M.

    2013-01-01

    Hospitals and health care institutions are facing the challenge of improving the quality of their services while reducing their costs. The current study presents the application of operations management practices in a dermatology oncology outpatient clinic specialized in skin cancer treatment. An

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

    Science.gov (United States)

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

    2017-11-06

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

  10. 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

  11. The equivalence of multi-criteria methods for radiotherapy plan optimization

    International Nuclear Information System (INIS)

    Breedveld, Sebastiaan; Storchi, Pascal R M; Heijmen, Ben J M

    2009-01-01

    Several methods can be used to achieve multi-criteria optimization of radiation therapy treatment planning, which strive for Pareto-optimality. The property of the solution being Pareto optimal is desired, because it guarantees that no criteria can be improved without deteriorating another criteria. The most widely used methods are the weighted-sum method, in which the different treatment objectives are weighted, and constrained optimization methods, in which treatment goals are set and the algorithm has to find the best plan fulfilling these goals. The constrained method used in this paper, the 2pεc (2-phase ε-constraint) method is based on the ε-constraint method, which generates Pareto-optimal solutions. Both approaches are uniquely related to each other. In this paper, we will show that it is possible to switch from the constrained method to the weighted-sum method by using the Lagrange multipliers from the constrained optimization problem, and vice versa by setting the appropriate constraints. In general, the theory presented in this paper can be useful in cases where a new situation is slightly different from the original situation, e.g. in online treatment planning, with deformations of the volumes of interest, or in automated treatment planning, where changes to the automated plan have to be made. An example of the latter is given where the planner is not satisfied with the result from the constrained method and wishes to decrease the dose in a structure. By using the Lagrange multipliers, a weighted-sum optimization problem is constructed, which generates a Pareto-optimal solution in the neighbourhood of the original plan, but fulfills the new treatment objectives.

  12. 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...

  13. 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.

  14. Evolutionary optimization technique for site layout planning

    KAUST Repository

    El Ansary, Ayman M.; Shalaby, Mohamed

    2014-01-01

    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

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

    Science.gov (United States)

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

    2012-01-01

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

  16. 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.

  17. 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......, 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...... 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...

  18. Using heuristic search for optimizing maintenance plans

    International Nuclear Information System (INIS)

    Mutanen, Teemu

    2012-01-01

    This work addresses the maintenance action selection process. Maintenance personnel need to evaluate maintenance actions and costs to keep the machines in working condition. Group of actions are evaluated together as maintenance plans. The maintenance plans as output provide information to the user about which actions to take if any and what future actions should be prepared for. The heuristic search method is implemented as part of general use toolbox for analysis of measurements from movable work machines. Impacts from machine's usage restrictions and maintenance activities are analysed. The results show that once put on a temporal perspective, the prioritized order of the actions is different and provide additional information to the user.

  19. Optimization of energy planning strategies in municipalities

    DEFF Research Database (Denmark)

    Petersen, Jens-Phillip

    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...

  20. Software for CATV Design and Frequency Plan Optimization

    OpenAIRE

    Hala, O.

    2007-01-01

    The paper deals with the structure of a software medium used for design and sub-optimization of frequency plan in CATV networks, their description and design method. The software performance is described and a simple design example of energy balance of a simplified CATV network is given. The software was created in programming environment called Delphi and local optimization was made in Matlab.

  1. Evaluation of a commercial biologically based IMRT treatment planning system

    International Nuclear Information System (INIS)

    Semenenko, Vladimir A.; Reitz, Bodo; Day, Ellen; Qi, X. Sharon; Miften, Moyed; Li, X. Allen

    2008-01-01

    A new inverse treatment planning system (TPS) for external beam radiation therapy with high energy photons is commercially available that utilizes both dose-volume-based cost functions and a selection of cost functions which are based on biological models. The purpose of this work is to evaluate quality of intensity-modulated radiation therapy (IMRT) plans resulting from the use of biological cost functions in comparison to plans designed using a traditional TPS employing dose-volume-based optimization. Treatment planning was performed independently at two institutions. For six cancer patients, including head and neck (one case from each institution), prostate, brain, liver, and rectal cases, segmental multileaf collimator IMRT plans were designed using biological cost functions and compared with clinically used dose-based plans for the same patients. Dose-volume histograms and dosimetric indices, such as minimum, maximum, and mean dose, were extracted and compared between the two types of treatment plans. Comparisons of the generalized equivalent uniform dose (EUD), a previously proposed plan quality index (fEUD), target conformity and heterogeneity indices, and the number of segments and monitor units were also performed. The most prominent feature of the biologically based plans was better sparing of organs at risk (OARs). When all plans from both institutions were combined, the biologically based plans resulted in smaller EUD values for 26 out of 33 OARs by an average of 5.6 Gy (range 0.24 to 15 Gy). Owing to more efficient beam segmentation and leaf sequencing tools implemented in the biologically based TPS compared to the dose-based TPS, an estimated treatment delivery time was shorter in most (five out of six) cases with some plans showing up to 50% reduction. The biologically based plans were generally characterized by a smaller conformity index, but greater heterogeneity index compared to the dose-based plans. Overall, compared to plans based on dose

  2. Optimal transmission planning under the Mexican new electricity market

    International Nuclear Information System (INIS)

    Zenón, Eric; Rosellón, Juan

    2017-01-01

    This paper addresses electricity transmission planning under the new industry and institutional structure of the Mexican electricity market, which has engaged in a deep reform process after decades of a state-owned-vertically-integrated-non-competitive-closed industry. Under this new structure, characterized by a nodal pricing system and an independent system operator (ISO), we analyze welfare-optimal network expansion with two modeling strategies. In a first model, we propose the use of an incentive price-cap mechanism to promote the expansion of Mexican networks. In a second model, we study centrally-planned grid expansion in Mexico by an ISO within a power-flow model. We carry out comparisons of these models which provide us with hints to evaluate the actual transmission planning process proposed by Mexican authorities (PRODESEN). We obtain that the PRODESEN plan appears to be a convergent welfare-optimal planning process. - Highlights: • We model transmission planning (PRODESEN) in the Mexican new electricity market. • We propose a first model with a price-cap mechanism to promote network expansion. • In a second power-flow model, we study centrally-planned grid expansions. • The PRODESEN appears to be a convergent welfare-optimal planning process. • Incentive regulation could further help to implement such an optimal process.

  3. Optimization in underground mine planning - developments and opportunities

    OpenAIRE

    Musingwini, C.

    2016-01-01

    The application of mining-specific and generic optimization techniques in the mining industry is deeply rooted in the discipline of operations research (OR). OR has its origins in the British Royal Air Force and Army around the early 1930s. Its development continued during and after World War II. The application of OR techniques to optimization in the mining industry started to emerge in the early 1960s. Since then, optimization techniques have been applied to solve widely different mine plan...

  4. Optimal motion planning using navigation measure

    Science.gov (United States)

    Vaidya, Umesh

    2018-05-01

    We introduce navigation measure as a new tool to solve the motion planning problem in the presence of static obstacles. Existence of navigation measure guarantees collision-free convergence at the final destination set beginning with almost every initial condition with respect to the Lebesgue measure. Navigation measure can be viewed as a dual to the navigation function. While the navigation function has its minimum at the final destination set and peaks at the obstacle set, navigation measure takes the maximum value at the destination set and is zero at the obstacle set. A linear programming formalism is proposed for the construction of navigation measure. Set-oriented numerical methods are utilised to obtain finite dimensional approximation of this navigation measure. Application of the proposed navigation measure-based theoretical and computational framework is demonstrated for a motion planning problem in a complex fluid flow.

  5. Improving treatment planning accuracy through multimodality imaging

    International Nuclear Information System (INIS)

    Sailer, Scott L.; Rosenman, Julian G.; Soltys, Mitchel; Cullip, Tim J.; Chen, Jun

    1996-01-01

    Purpose: In clinical practice, physicians are constantly comparing multiple images taken at various times during the patient's treatment course. One goal of such a comparison is to accurately define the gross tumor volume (GTV). The introduction of three-dimensional treatment planning has greatly enhanced the ability to define the GTV, but there are times when the GTV is not visible on the treatment-planning computed tomography (CT) scan. We have modified our treatment-planning software to allow for interactive display of multiple, registered images that enhance the physician's ability to accurately determine the GTV. Methods and Materials: Images are registered using interactive tools developed at the University of North Carolina at Chapel Hill (UNC). Automated methods are also available. Images registered with the treatment-planning CT scan are digitized from film. After a physician has approved the registration, the registered images are made available to the treatment-planning software. Structures and volumes of interest are contoured on all images. In the beam's eye view, wire loop representations of these structures can be visualized from all image types simultaneously. Each registered image can be seamlessly viewed during the treatment-planning process, and all contours from all image types can be seen on any registered image. A beam may, therefore, be designed based on any contour. Results: Nineteen patients have been planned and treated using multimodality imaging from November 1993 through August 1994. All registered images were digitized from film, and many were from outside institutions. Brain has been the most common site (12), but the techniques of registration and image display have also been used for the thorax (4), abdomen (2), and extremity (1). The registered image has been an magnetic resonance (MR) scan in 15 cases and a diagnostic CT scan in 5 cases. In one case, sequential MRs, one before treatment and another after 30 Gy, were used to plan

  6. Spatial planning via extremal optimization enhanced by cell-based local search

    International Nuclear Information System (INIS)

    Sidiropoulos, Epaminondas

    2014-01-01

    A new treatment is presented for land use planning problems by means of extremal optimization in conjunction to cell-based neighborhood local search. Extremal optimization, inspired by self-organized critical models of evolution has been applied mainly to the solution of classical combinatorial optimization problems. Cell-based local search has been employed by the author elsewhere in problems of spatial resource allocation in combination with genetic algorithms and simulated annealing. In this paper it complements extremal optimization in order to enhance its capacity for a spatial optimization problem. The hybrid method thus formed is compared to methods of the literature on a specific characteristic problem. It yields better results both in terms of objective function values and in terms of compactness. The latter is an important quantity for spatial planning. The present treatment yields significant compactness values as emergent results

  7. Radwaste treatment complex. DRAWMACS planned maintenance system

    International Nuclear Information System (INIS)

    Keel, A.J.

    1992-07-01

    This document describes the operation of the Planned Maintenance System for the Radwaste Treatment Complex. The Planned Maintenance System forms part of the Decommissioning and Radwaste Management Computer System (DRAWMACS). Further detailed information about the data structure of the system is contained in Database Design for the DRAWMACS Planned Maintenance System (AEA-D and R-0285, 2nd issue, 25th February 1992). Information for other components of DRAWMACS is contained in Basic User Guide for the Radwaste Treatment Plant Computer System (AEA-D and R-0019, July 1990). (author)

  8. Biological-based and physical-based optimization for biological evaluation of prostate patient's plans

    Science.gov (United States)

    Sukhikh, E.; Sheino, I.; Vertinsky, A.

    2017-09-01

    Modern modalities of radiation treatment therapy allow irradiation of the tumor to high dose values and irradiation of organs at risk (OARs) to low dose values at the same time. In this paper we study optimal radiation treatment plans made in Monaco system. The first aim of this study was to evaluate dosimetric features of Monaco treatment planning system using biological versus dose-based cost functions for the OARs and irradiation targets (namely tumors) when the full potential of built-in biological cost functions is utilized. The second aim was to develop criteria for the evaluation of radiation dosimetry plans for patients based on the macroscopic radiobiological criteria - TCP/NTCP. In the framework of the study four dosimetric plans were created utilizing the full extent of biological and physical cost functions using dose calculation-based treatment planning for IMRT Step-and-Shoot delivery of stereotactic body radiation therapy (SBRT) in prostate case (5 fractions per 7 Gy).

  9. A retrospective planning analysis comparing intensity modulated radiation therapy (IMRT) to volumetric modulated arc therapy (VMAT) using two optimization algorithms for the treatment of early-stage prostate cancer

    International Nuclear Information System (INIS)

    Elith, Craig A; Dempsey, Shane E; Warren-Forward, Helen M

    2013-01-01

    The primary aim of this study is to compare intensity modulated radiation therapy (IMRT) to volumetric modulated arc therapy (VMAT) for the radical treatment of prostate cancer using version 10.0 (v10.0) of Varian Medical Systems, RapidArc radiation oncology system. Particular focus was placed on plan quality and the implications on departmental resources. The secondary objective was to compare the results in v10.0 to the preceding version 8.6 (v8.6). Twenty prostate cancer cases were retrospectively planned using v10.0 of Varian's Eclipse and RapidArc software. Three planning techniques were performed: a 5-field IMRT, VMAT using one arc (VMAT-1A), and VMAT with two arcs (VMAT-2A). Plan quality was assessed by examining homogeneity, conformity, the number of monitor units (MUs) utilized, and dose to the organs at risk (OAR). Resource implications were assessed by examining planning and treatment times. The results obtained using v10.0 were also compared to those previously reported by our group for v8.6. In v10.0, each technique was able to produce a dose distribution that achieved the departmental planning guidelines. The IMRT plans were produced faster than VMAT plans and displayed improved homogeneity. The VMAT plans provided better conformity to the target volume, improved dose to the OAR, and required fewer MUs. Treatments using VMAT-1A were significantly faster than both IMRT and VMAT-2A. Comparison between versions 8.6 and 10.0 revealed that in the newer version, VMAT planning was significantly faster and the quality of the VMAT dose distributions produced were of a better quality. VMAT (v10.0) using one or two arcs provides an acceptable alternative to IMRT for the treatment of prostate cancer. VMAT-1A has the greatest impact on reducing treatment time

  10. Modeling Vertical Flow Treatment Wetland Hydraulics to Optimize Treatment Efficiency

    Science.gov (United States)

    2011-03-24

    be forced to flow in a 90 serpentine manner back and forth as it moves upward through the wetland (think waiting in line at Disneyland ). This...Flow Treatment Wetland Hydraulics to Optimize Treatment Efficiency 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR

  11. 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.

  12. Optimizing treatment success in multiple sclerosis

    OpenAIRE

    Ziemssen, T; Derfuss, T; de Stefano, N; Giovannoni, G; Palavra, F; Tomic, D; Vollmer, T; Schippling, S

    2016-01-01

    Despite important advances in the treatment of multiple sclerosis (MS) over recent years, the introduction of several disease-modifying therapies (DMTs), the burden of progressive disability and premature mortality associated with the condition remains substantial. This burden, together with the high healthcare and societal costs associated with MS, creates a compelling case for early treatment optimization with highly efficacious therapies. Often, patients receive several first-line therapie...

  13. Clinical treatment planning in gynecologic cancer

    International Nuclear Information System (INIS)

    Brady, L.W.; Markoe, A.M.; Micaily, B.; Damsker, J.I.; Karlsson, U.L.; Amendola, B.E.

    1987-01-01

    Treatment planning in gynecologic cancer is a complicated and difficult procedure. It requires an adequate preoperative assessment of the true extent of the patient's disease process and oftentimes this can be achieved not only by conventional studies but must employ surgical exploratory techniques in order to truly define the extent of the disease. However, with contemporary sophisticated treatment planning techniques that are now available in most contemporary departments of radiation oncology, radiation therapy is reemerging as an important and major treatment technique in the management of patients with gynecologic cancer

  14. Threshold-driven optimization for reference-based auto-planning

    Science.gov (United States)

    Long, Troy; Chen, Mingli; Jiang, Steve; Lu, Weiguo

    2018-02-01

    We study threshold-driven optimization methodology for automatically generating a treatment plan that is motivated by a reference DVH for IMRT treatment planning. We present a framework for threshold-driven optimization for reference-based auto-planning (TORA). Commonly used voxel-based quadratic penalties have two components for penalizing under- and over-dosing of voxels: a reference dose threshold and associated penalty weight. Conventional manual- and auto-planning using such a function involves iteratively updating the preference weights while keeping the thresholds constant, an unintuitive and often inconsistent method for planning toward some reference DVH. However, driving a dose distribution by threshold values instead of preference weights can achieve similar plans with less computational effort. The proposed methodology spatially assigns reference DVH information to threshold values, and iteratively improves the quality of that assignment. The methodology effectively handles both sub-optimal and infeasible DVHs. TORA was applied to a prostate case and a liver case as a proof-of-concept. Reference DVHs were generated using a conventional voxel-based objective, then altered to be either infeasible or easy-to-achieve. TORA was able to closely recreate reference DVHs in 5-15 iterations of solving a simple convex sub-problem. TORA has the potential to be effective for auto-planning based on reference DVHs. As dose prediction and knowledge-based planning becomes more prevalent in the clinical setting, incorporating such data into the treatment planning model in a clear, efficient way will be crucial for automated planning. A threshold-focused objective tuning should be explored over conventional methods of updating preference weights for DVH-guided treatment planning.

  15. Optimized Treatment Schedules for Chronic Myeloid Leukemia.

    Directory of Open Access Journals (Sweden)

    Qie He

    2016-10-01

    Full Text Available Over the past decade, several targeted therapies (e.g. imatinib, dasatinib, nilotinib have been developed to treat Chronic Myeloid Leukemia (CML. Despite an initial response to therapy, drug resistance remains a problem for some CML patients. Recent studies have shown that resistance mutations that preexist treatment can be detected in a substantial number of patients, and that this may be associated with eventual treatment failure. One proposed method to extend treatment efficacy is to use a combination of multiple targeted therapies. However, the design of such combination therapies (timing, sequence, etc. remains an open challenge. In this work we mathematically model the dynamics of CML response to combination therapy and analyze the impact of combination treatment schedules on treatment efficacy in patients with preexisting resistance. We then propose an optimization problem to find the best schedule of multiple therapies based on the evolution of CML according to our ordinary differential equation model. This resulting optimization problem is nontrivial due to the presence of ordinary different equation constraints and integer variables. Our model also incorporates drug toxicity constraints by tracking the dynamics of patient neutrophil counts in response to therapy. We determine optimal combination strategies that maximize time until treatment failure on hypothetical patients, using parameters estimated from clinical data in the literature.

  16. 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.

  17. Tolerance doses for treatment planning

    International Nuclear Information System (INIS)

    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 5 ) or 50% (TD 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

  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.

    2016-01-01

    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 PMID:27929478

  19. Automation of radiation treatment planning. Evaluation of head and neck cancer patient plans created by the Pinnacle"3 scripting and Auto-Planning functions

    International Nuclear Information System (INIS)

    Speer, Stefan; Weiss, Alexander; Bert, Christoph; Klein, Andreas; Kober, Lukas; Yohannes, Indra

    2017-01-01

    Intensity-modulated radiotherapy (IMRT) techniques are now standard practice. IMRT or volumetric-modulated arc therapy (VMAT) allow treatment of the tumor while simultaneously sparing organs at risk. Nevertheless, treatment plan quality still depends on the physicist's individual skills, experiences, and personal preferences. It would therefore be advantageous to automate the planning process. This possibility is offered by the Pinnacle"3 treatment planning system (Philips Healthcare, Hamburg, Germany) via its scripting language or Auto-Planning (AP) module. AP module results were compared to in-house scripts and manually optimized treatment plans for standard head and neck cancer plans. Multiple treatment parameters were scored to judge plan quality (100 points = optimum plan). Patients were initially planned manually by different physicists and re-planned using scripts or AP. Script-based head and neck plans achieved a mean of 67.0 points and were, on average, superior to manually created (59.1 points) and AP plans (62.3 points). Moreover, they are characterized by reproducibility and lower standard deviation of treatment parameters. Even less experienced staff are able to create at least a good starting point for further optimization in a short time. However, for particular plans, experienced planners perform even better than scripts or AP. Experienced-user input is needed when setting up scripts or AP templates for the first time. Moreover, some minor drawbacks exist, such as the increase of monitor units (+35.5% for scripted plans). On average, automatically created plans are superior to manually created treatment plans. For particular plans, experienced physicists were able to perform better than scripts or AP; thus, the benefit is greatest when time is short or staff inexperienced. (orig.) [de

  20. Automation of radiation treatment planning : Evaluation of head and neck cancer patient plans created by the Pinnacle3 scripting and Auto-Planning functions.

    Science.gov (United States)

    Speer, Stefan; Klein, Andreas; Kober, Lukas; Weiss, Alexander; Yohannes, Indra; Bert, Christoph

    2017-08-01

    Intensity-modulated radiotherapy (IMRT) techniques are now standard practice. IMRT or volumetric-modulated arc therapy (VMAT) allow treatment of the tumor while simultaneously sparing organs at risk. Nevertheless, treatment plan quality still depends on the physicist's individual skills, experiences, and personal preferences. It would therefore be advantageous to automate the planning process. This possibility is offered by the Pinnacle 3 treatment planning system (Philips Healthcare, Hamburg, Germany) via its scripting language or Auto-Planning (AP) module. AP module results were compared to in-house scripts and manually optimized treatment plans for standard head and neck cancer plans. Multiple treatment parameters were scored to judge plan quality (100 points = optimum plan). Patients were initially planned manually by different physicists and re-planned using scripts or AP. Script-based head and neck plans achieved a mean of 67.0 points and were, on average, superior to manually created (59.1 points) and AP plans (62.3 points). Moreover, they are characterized by reproducibility and lower standard deviation of treatment parameters. Even less experienced staff are able to create at least a good starting point for further optimization in a short time. However, for particular plans, experienced planners perform even better than scripts or AP. Experienced-user input is needed when setting up scripts or AP templates for the first time. Moreover, some minor drawbacks exist, such as the increase of monitor units (+35.5% for scripted plans). On average, automatically created plans are superior to manually created treatment plans. For particular plans, experienced physicists were able to perform better than scripts or AP; thus, the benefit is greatest when time is short or staff inexperienced.

  1. Optimizing the treatment of rhegmatogenous retinal detachment

    DEFF Research Database (Denmark)

    Hajari, Javad Nouri

    2016-01-01

    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...... 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...... to establish optimal conditions in the treatment of RRD....

  2. 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.

  3. 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...... 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...

  4. Software for CATV Design and Frequency Plan Optimization

    Directory of Open Access Journals (Sweden)

    O. Hala

    2007-09-01

    Full Text Available The paper deals with the structure of a software medium used for design and sub-optimization of frequency plan in CATV networks, their description and design method. The software performance is described and a simple design example of energy balance of a simplified CATV network is given. The software was created in programming environment called Delphi and local optimization was made in Matlab.

  5. The evolution of brachytherapy treatment planning

    International Nuclear Information System (INIS)

    Rivard, Mark J.; Venselaar, Jack L. M.; Beaulieu, Luc

    2009-01-01

    Brachytherapy is a mature treatment modality that has benefited from technological advances. Treatment planning has advanced from simple lookup tables to complex, computer-based dose-calculation algorithms. The current approach is based on the AAPM TG-43 formalism with recent advances in acquiring single-source dose distributions. However, this formalism has clinically relevant limitations for calculating patient dose. Dose-calculation algorithms are being developed based on Monte Carlo methods, collapsed cone, and solving the linear Boltzmann transport equation. In addition to improved dose-calculation tools, planning systems and brachytherapy treatment planning will account for material heterogeneities, scatter conditions, radiobiology, and image guidance. The AAPM, ESTRO, and other professional societies are working to coordinate clinical integration of these advancements. This Vision 20/20 article provides insight into these endeavors.

  6. Treatment planning systems for high precision radiotherapy

    International Nuclear Information System (INIS)

    Deshpande, D.D.

    2008-01-01

    Computerized Treatment Planning System (TPS) play an important role in radiotherapy with the intent to maximize tumor control and minimize normal tissue complications. Treatment planning during earlier days was generally carried out through the manual summations of standard isodose charts on to patient body contours that were generated by direct tracing or lead wire representation, and relied heavily on the careful choices of beam weights and wedging. Since then there had been tremendous advances in field of Radiation Oncology in last few decades. The linear accelerators had evolved from MLC's to IGRT, the techniques like 3DCRT, IMRT has become almost routine affair. The simulation has seen transition from simple 2D film/fluoroscopy localization to CT Simulator with added development in PET, PET- CT and MR imaging. The Networking and advances in computer technology has made it possible to direct transfer of Images, contours to the treatment planning systems

  7. Robust Optimization Model for Production Planning Problem under Uncertainty

    Directory of Open Access Journals (Sweden)

    Pembe GÜÇLÜ

    2017-01-01

    Full Text Available Conditions of businesses change very quickly. To take into account the uncertainty engendered by changes has become almost a rule while planning. Robust optimization techniques that are methods of handling uncertainty ensure to produce less sensitive results to changing conditions. Production planning, is to decide from which product, when and how much will be produced, with a most basic definition. Modeling and solution of the Production planning problems changes depending on structure of the production processes, parameters and variables. In this paper, it is aimed to generate and apply scenario based robust optimization model for capacitated two-stage multi-product production planning problem under parameter and demand uncertainty. With this purpose, production planning problem of a textile company that operate in İzmir has been modeled and solved, then deterministic scenarios’ and robust method’s results have been compared. Robust method has provided a production plan that has higher cost but, will result close to feasible and optimal for most of the different scenarios in the future.

  8. Analytical incorporation of fractionation effects in probabilistic treatment planning for intensity-modulated proton therapy.

    Science.gov (United States)

    Wahl, Niklas; Hennig, Philipp; Wieser, Hans-Peter; Bangert, Mark

    2018-04-01

    We show that it is possible to explicitly incorporate fractionation effects into closed-form probabilistic treatment plan analysis and optimization for intensity-modulated proton therapy with analytical probabilistic modeling (APM). We study the impact of different fractionation schemes on the dosimetric uncertainty induced by random and systematic sources of range and setup uncertainty for treatment plans that were optimized with and without consideration of the number of treatment fractions. The APM framework is capable of handling arbitrarily correlated uncertainty models including systematic and random errors in the context of fractionation. On this basis, we construct an analytical dose variance computation pipeline that explicitly considers the number of treatment fractions for uncertainty quantitation and minimization during treatment planning. We evaluate the variance computation model in comparison to random sampling of 100 treatments for conventional and probabilistic treatment plans under different fractionation schemes (1, 5, 30 fractions) for an intracranial, a paraspinal and a prostate case. The impact of neglecting the fractionation scheme during treatment planning is investigated by applying treatment plans that were generated with probabilistic optimization for 1 fraction in a higher number of fractions and comparing them to the probabilistic plans optimized under explicit consideration of the number of fractions. APM enables the construction of an analytical variance computation model for dose uncertainty considering fractionation at negligible computational overhead. It is computationally feasible (a) to simultaneously perform a robustness analysis for all possible fraction numbers and (b) to perform a probabilistic treatment plan optimization for a specific fraction number. The incorporation of fractionation assumptions for robustness analysis exposes a dose to uncertainty trade-off, i.e., the dose in the organs at risk is increased for a

  9. MO-D-BRC-04: Multiple-Criteria Optimization Planning

    Energy Technology Data Exchange (ETDEWEB)

    Donaghue, J. [Akron General Medical Center (United States)

    2016-06-15

    Treatment planning is a central part of radiation therapy, including delineation in tumor volumes and critical organs, setting treatment goals of prescription doses to the tumor targets and tolerance doses to the critical organs, and finally generation of treatment plans to meet the treatment goals. National groups like RTOG have led the effort to standardize treatment goals of the prescription doses to the tumor targets and tolerance doses to the critical organs based on accumulated knowledge from decades of abundant clinical trial experience. The challenge for each clinical department is how to achieve or surpass these set goals within the time constraints of clinical practice. Using fifteen testing cases from different treatment sites such as head and neck, prostate with and without pelvic lymph nodes, SBRT spine, we will present clinically utility of advanced planning tools, including knowledge based, automatic based, and multiple criteria based tools that are clinically implemented. The objectives of this session are: Understand differences among these three advanced planning tools Provide clinical assessments on the utility of the advanced planning tools Discuss clinical challenges of treatment planning with large variations in tumor volumes and their relationships with adjacent critical organs. Ping Xia received research grant from Philips. Jackie Wu received research grant from Varian; P. Xia, Research support by Philips and Varian; Q. Wu, NIH, Varian Medical.

  10. MO-D-BRC-04: Multiple-Criteria Optimization Planning

    International Nuclear Information System (INIS)

    Donaghue, J.

    2016-01-01

    Treatment planning is a central part of radiation therapy, including delineation in tumor volumes and critical organs, setting treatment goals of prescription doses to the tumor targets and tolerance doses to the critical organs, and finally generation of treatment plans to meet the treatment goals. National groups like RTOG have led the effort to standardize treatment goals of the prescription doses to the tumor targets and tolerance doses to the critical organs based on accumulated knowledge from decades of abundant clinical trial experience. The challenge for each clinical department is how to achieve or surpass these set goals within the time constraints of clinical practice. Using fifteen testing cases from different treatment sites such as head and neck, prostate with and without pelvic lymph nodes, SBRT spine, we will present clinically utility of advanced planning tools, including knowledge based, automatic based, and multiple criteria based tools that are clinically implemented. The objectives of this session are: Understand differences among these three advanced planning tools Provide clinical assessments on the utility of the advanced planning tools Discuss clinical challenges of treatment planning with large variations in tumor volumes and their relationships with adjacent critical organs. Ping Xia received research grant from Philips. Jackie Wu received research grant from Varian; P. Xia, Research support by Philips and Varian; Q. Wu, NIH, Varian Medical

  11. Margins for treatment planning of proton therapy

    International Nuclear Information System (INIS)

    Thomas, Simon J

    2006-01-01

    For protons and other charged particles, the effect of set-up errors on the position of isodoses is considerably less in the direction of the incident beam than it is laterally. Therefore, the margins required between the clinical target volume (CTV) and planning target volume (PTV) can be less in the direction of the incident beam than laterally. Margins have been calculated for a typical head plan and a typical prostate plan, for a single field, a parallel opposed and a four-field arrangement of protons, and compared with margins calculated for photons, assuming identical geometrical uncertainties for each modality. In the head plan, where internal motion was assumed negligible, the CTV-PTV margin reduced from approximately 10 mm to 3 mm in the axial direction for the single field and parallel opposed plans. For a prostate plan, where internal motion cannot be ignored, the corresponding reduction in margin was from 11 mm to 7 mm. The planning organ at risk (PRV) margin in the axial direction reduced from 6 mm to 2 mm for the head plan, and from 7 mm to 4 mm for the prostate plan. No reduction was seen on the other axes, or for any axis of the four-field plans. Owing to the shape of proton dose distributions, there are many clinical cases in which good dose distributions can be obtained with one or two fields. When this is done, it is possible to use smaller PTV and PRV margins. This has the potential to convert untreatable cases, in which the PTV and PRV overlap, into cases with a gap between PTV and PRV of adequate size for treatment planning

  12. Mixed integer programming improves comprehensibility and plan quality in inverse optimization of prostate HDR Brachytherapy

    NARCIS (Netherlands)

    Gorissen, B.L.; den Hertog, D.; Hoffmann, A.L.

    2013-01-01

    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

  13. Multi-GPU configuration of 4D intensity modulated radiation therapy inverse planning using global optimization

    Science.gov (United States)

    Hagan, Aaron; Sawant, Amit; Folkerts, Michael; Modiri, Arezoo

    2018-01-01

    We report on the design, implementation and characterization of a multi-graphic processing unit (GPU) computational platform for higher-order optimization in radiotherapy treatment planning. In collaboration with a commercial vendor (Varian Medical Systems, Palo Alto, CA), a research prototype GPU-enabled Eclipse (V13.6) workstation was configured. The hardware consisted of dual 8-core Xeon processors, 256 GB RAM and four NVIDIA Tesla K80 general purpose GPUs. We demonstrate the utility of this platform for large radiotherapy optimization problems through the development and characterization of a parallelized particle swarm optimization (PSO) four dimensional (4D) intensity modulated radiation therapy (IMRT) technique. The PSO engine was coupled to the Eclipse treatment planning system via a vendor-provided scripting interface. Specific challenges addressed in this implementation were (i) data management and (ii) non-uniform memory access (NUMA). For the former, we alternated between parameters over which the computation process was parallelized. For the latter, we reduced the amount of data required to be transferred over the NUMA bridge. The datasets examined in this study were approximately 300 GB in size, including 4D computed tomography images, anatomical structure contours and dose deposition matrices. For evaluation, we created a 4D-IMRT treatment plan for one lung cancer patient and analyzed computation speed while varying several parameters (number of respiratory phases, GPUs, PSO particles, and data matrix sizes). The optimized 4D-IMRT plan enhanced sparing of organs at risk by an average reduction of 26% in maximum dose, compared to the clinical optimized IMRT plan, where the internal target volume was used. We validated our computation time analyses in two additional cases. The computation speed in our implementation did not monotonically increase with the number of GPUs. The optimal number of GPUs (five, in our study) is directly related to the

  14. Optimal day-ahead operational planning of microgrids

    International Nuclear Information System (INIS)

    Hosseinnezhad, Vahid; Rafiee, Mansour; Ahmadian, Mohammad; Siano, Pierluigi

    2016-01-01

    Highlights: • A new multi-objective model for optimal day-ahead operational planning of microgrids is proposed. • A new concept called seamlessness is introduced to control the sustainability of microgrid. • A new method is developed to manage the load and renewable energy resources estimation errors. • A new solution based on a combination of numerical and evolutionary approaches is proposed. - Abstract: Providing a cost-efficient, eco-friendly and sustainable energy is one of the main issues in modern societies. In response to this demand, new features of microgrid technology have provided huge potentials while distributing electricity more effectively, economically and securely. Accordingly, this paper presents a new multi-objective generation management model for optimal day-ahead operational planning of medium voltage microgrids. The proposed model optimizes both pollutant emission and operating cost of a microgrid by using multi-objective optimization. Besides, a seamlessness-selective algorithm is integrated into the model, which can be adopted to achieve the desired self-sufficiency level for microgrids along a specified planning horizon. Furthermore, the model is characterized by a reserve-assessment strategy developed to handle the load and renewable energy resources estimation errors. The introduced model is solved using a combination of numerical and evolutionary methods of species-based quantum particle swarm optimization to find the optimal scheduling scheme and minos-based optimal power flow to optimize the operating cost and emission. In addition, the suggested solution approach also incorporates an efficient mechanism for considering energy storage systems and coding the candidate solutions in the evolutionary algorithm. The proposed model is implemented on a test microgrid and is investigated through simulations to study the different aspects of the problem. The results show significant improvements and benefits which are obtained by

  15. Optimal farm plans for sustainable environmental and economic ...

    African Journals Online (AJOL)

    The optimal farm plans indicated that the cassava/maize intercrop gave the best results in Ijemo-Fadipe and Ajura, while the cassava/melon and sole cassava enterprises were best in Ijale-Papa and Ilewo-Orile respectively. Operating expenses was found to be the most limiting factors in all the villages. The study concluded ...

  16. Constrained optimal motion planning for autonomous vehicles using PRONTO

    NARCIS (Netherlands)

    Aguiar, A.P.; Bayer, F.A.; Hauser, J.; Häusler, A.J.; Notarstefano, G.; Pascoal, A.M.; Rucco, A.; Saccon, A.

    2017-01-01

    This chapter provides an overview of the authors’ efforts in vehicle trajectory exploration and motion planning based on PRONTO, a numerical method for solving optimal control problems developed over the last two decades. The chapter reviews the basics of PRONTO, providing the appropriate references

  17. 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

  18. Classical-Equivalent Bayesian Portfolio Optimization for Electricity Generation Planning

    Directory of Open Access Journals (Sweden)

    Hellinton H. Takada

    2018-01-01

    Full Text Available There are several electricity generation technologies based on different sources such as wind, biomass, gas, coal, and so on. The consideration of the uncertainties associated with the future costs of such technologies is crucial for planning purposes. In the literature, the allocation of resources in the available technologies has been solved as a mean-variance optimization problem assuming knowledge of the expected values and the covariance matrix of the costs. However, in practice, they are not exactly known parameters. Consequently, the obtained optimal allocations from the mean-variance optimization are not robust to possible estimation errors of such parameters. Additionally, it is usual to have electricity generation technology specialists participating in the planning processes and, obviously, the consideration of useful prior information based on their previous experience is of utmost importance. The Bayesian models consider not only the uncertainty in the parameters, but also the prior information from the specialists. In this paper, we introduce the classical-equivalent Bayesian mean-variance optimization to solve the electricity generation planning problem using both improper and proper prior distributions for the parameters. In order to illustrate our approach, we present an application comparing the classical-equivalent Bayesian with the naive mean-variance optimal portfolios.

  19. Evaluation of an automated knowledge based treatment planning system for head and neck

    International Nuclear Information System (INIS)

    Krayenbuehl, Jerome; Norton, Ian; Studer, Gabriela; Guckenberger, Matthias

    2015-01-01

    This study evaluated an automated inverse treatment planning algorithm, Pinnacle Auto-Planning (AP), and compared automatically generated plans with historical plans in a large cohort of head and neck cancer patients. Fifty consecutive patients treated with volumetric modulated arc therapy (Eclipse, Varian Medical System, Palo Alto, CA) for head and neck were re-planned with AP version 9.10. Only one single cycle of plan optimization using one single template was allowed for AP. The dose to the planning target volumes (PTV’s; 3–4 dose levels), the organs at risk (OAR’s) and the effective working time for planning was evaluated. Additionally, two experienced radiation oncologists blind-reviewed and ranked 10 plans. Dose coverage and dose homogeneity of the PTV were significantly improved with AP, however manually optimized plans showed significantly improved dose conformity. The mean dose to the parotid glands, oral mucosa, swallowing muscles, dorsal neck tissue and maximal dose to the spinal cord were significantly reduced with AP. In 64 % of the plans, the mean dose to any OAR (spinal cord excluded) was reduced by >20 % with AP in comparison to the manually optimized plans. In 12 % of the plans, the manually optimized plans showed reduced doses by >20 % in at least one OAR. The experienced radiation oncologists preferred the AP plan and the clinical plan in 80 and 20 % of the cases, respectively. The average effective working time was 3.8 min ± 1.1 min in comparison to 48.5 min ± 6.0 min using AP compared to the manually optimized plans, respectively. The evaluated automated planning algorithm achieved highly consistent and significantly improved treatment plans with potentially clinically relevant OAR sparing by >20 % in 64 % of the cases. The effective working time was substantially reduced with Auto-Planning

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

    International Nuclear Information System (INIS)

    McGarry, Conor K.; Bokrantz, Rasmus; O’Sullivan, Joe M.; Hounsell, Alan R.

    2014-01-01

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

  1. Standardization of prostate brachytherapy treatment plans

    International Nuclear Information System (INIS)

    Ove, Roger; Wallner, Kent; Badiozamani, Kas; Korjsseon, Tammy; Sutlief, Steven

    2001-01-01

    Purpose: Whereas custom-designed plans are the norm for prostate brachytherapy, the relationship between linear prostate dimensions and volume calls into question the routine need for customized treatment planning. With the goal of streamlining the treatment-planning process, we have compared the treatment margins (TMs) achieved with one standard plan applied to patients with a wide range of prostate volumes. Methods and Materials: Preimplant transrectal ultrasound (TRUS) images of 50 unselected University of Washington patients with T1-T2 cancer and a prostate volume between 20 cc and 50 cc were studied. Patients were arbitrarily grouped into categories of 20-30 cc, 30-40 cc, and 40-50 cc. A standard 19-needle plan was devised for patients in the 30- to 40-cc range, using an arbitrary minimum margin of 5 mm around the gross tumor volume (GTV), making use of inverse planning technology to achieve 100% coverage of the target volume with accentuation of dose at the periphery and sparing of the central region. The idealized plan was applied to each patient's TRUS study. The distances (TMs) between the prostatic edge (GTV) and treated volume (TV) were determined perpendicular to the prostatic margin. Results: Averaged over the entire patient group, the ratio of thickness to width was 1.4, whereas the ratio of length to width was 1.3. These values were fairly constant over the range of volumes, emphasizing that the prostate retains its general shape as volume increases. The idealized standard plan was overlaid on the ultrasound images of the 17 patients in the 30- to 40-cc group and the V100, the percentage of target volume receiving 100% or more of the prescription dose, was 98% or greater for 15 of the 17 patients. The lateral and posterior TMs fell within a narrow range, most being within 2 mm of the idealized 5-mm TM. To estimate whether a 10-cc volume-interval stratification was reasonable, the standard plan generated from the 30- to 40-cc prostate model was

  2. Development of Consensus Treatment Plans for Juvenile Localized Scleroderma

    Science.gov (United States)

    Li, Suzanne C.; Torok, Kathryn S.; Pope, Elena; Dedeoglu, Fatma; Hong, Sandy; Jacobe, Heidi T.; Rabinovich, C. Egla; Laxer, Ronald M.; Higgins, Gloria C.; Ferguson, Polly J.; Lasky, Andrew; Baszis, Kevin; Becker, Mara; Campillo, Sarah; Cartwright, Victoria; Cidon, Michael; Inman, Christi J; Jerath, Rita; O'Neil, Kathleen M.; Vora, Sheetal; Zeft, Andrew; Wallace, Carol A.; Ilowite, Norman T.; Fuhlbrigge, Robert C

    2013-01-01

    Objective To develop standardized treatment plans, clinical assessments, and response criteria for active, moderate to high severity juvenile localized scleroderma (jLS). Background jLS is a chronic inflammatory skin disorder associated with substantial morbidity and disability. Although a wide range of therapeutic strategies have been reported in the literature, a lack of agreement on treatment specifics and accepted methods for clinical assessment of have made it difficult to compare approaches and identify optimal therapy. Methods A core group of pediatric rheumatologists, dermatologists and a lay advisor was engaged by the Childhood Arthritis and Rheumatology Research Alliance (CARRA) to develop standardized treatment plans and assessment parameters for jLS using consensus methods/nominal group techniques. Recommendations were validated in two face-to-face conferences with a larger group of practitioners with expertise in jLS and with the full membership of CARRA, which encompasses the majority of pediatric rheumatologists in the U.S and Canada. Results Consensus was achieved on standardized treatment plans that reflect the prevailing treatment practices of CARRA members. Standardized clinical assessment methods and provisional treatment response criteria were also developed. Greater than 90% of pediatric rheumatologists responding to a survey (67% of CARRA membership) affirmed the final recommendations and agreed to utilize these consensus plans to treat patients with jLS. Conclusions Using consensus methodology, we have developed standardized treatment plans and assessment methods for jLS. The high level of support among pediatric rheumatologists will support future comparative effectiveness studies and enable the development of evidence-based guidelines for the treatment of jLS. PMID:22505322

  3. 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...

  4. Improvements in patient treatment planning systems

    International Nuclear Information System (INIS)

    Wheeler, F.J.; Wessol, D.E.; Nigg, D.W.; Atkinson, C.A.; Babcock, R.; Evans, J.

    1995-01-01

    The Boron Neutron Capture Therapy, Radiation treatment planning environment (BNCT-Rtpe) software system is used to develop treatment planning information. In typical use BNCT-Rtpe consists of three main components: (1) Semi-automated geometric modeling of objects (brain, target, eyes, sinus) derived from MRI, CT, and other medical imaging modalities, (2) Dose computations for these geometric models with rtt-MC, the INEL Monte Carlo radiation transport computer code, and (3) Dose contouring overlaid on medical images as well as generation of other dose displays. We continue to develop a planning system based on three-dimensional image-based reconstructions using Bspline surfaces. Even though this software is in an experimental state, it has been applied for large animal research and for an isolated case of treatment for a human glioma. Radiation transport is based on Monte Carlo, however there will be implementations of faster methods (e.g. diffusion theory) in the future. The important thing for treatment planning is the output which must convey, to the radiologist, the deposition of dose to healthy and target tissue. Many edits are available such that one can obtain contours registered to medical image, dose/volume histograms and most information required for treatment planning and response assessment. Recent work has been to make the process more automatic and easier to use. The interface, now implemented for contouring and reconstruction, utilizes the Xwindowing system and the MOTIF graphical users interface for effective interaction with the planner. Much work still remains before the tool can be applied in a routine clinical setting

  5. 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

  6. Optimality of profit-including prices under ideal planning.

    Science.gov (United States)

    Samuelson, P A

    1973-07-01

    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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, Qianqian; Blohm, Andrew; 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.

  8. Patient performance–based plan parameter optimization for prostate cancer in tomotherapy

    Energy Technology Data Exchange (ETDEWEB)

    Cao, Yuan Jie; Lee, Suk, E-mail: sukmp@korea.ac.kr; Chang, Kyung Hwan; Shim, Jang Bo; Kim, Kwang Hyeon; Park, Young Je; Kim, Chul Yong

    2015-01-01

    The purpose of this study is to evaluate the influence of treatment-planning parameters on the quality of treatment plans in tomotherapy and to find the optimized planning parameter combinations when treating patients with prostate cancer under different performances. A total of 3 patients with prostate cancer with Eastern Cooperative Oncology Group (ECOG) performance status of 2 or 3 were included in this study. For each patient, 27 treatment plans were created using a combination of planning parameters (field width of 1, 2.5, and 5 cm; pitch of 0.172, 0.287, and 0.43; and modulation factor of 1.8, 3, and 3.5). Then, plans were analyzed using several dosimetrical indices: the prescription isodose to target volume (PITV) ratio, homogeneity index (HI), conformity index (CI), target coverage index (TCI), modified dose HI (MHI), conformity number (CN), and quality factor (QF). Furthermore, dose-volume histogram of critical structures and critical organ scoring index (COSI) were used to analyze organs at risk (OAR) sparing. Interestingly, treatment plans with a field width of 1 cm showed more favorable results than others in the planning target volume (PTV) and OAR indices. However, the treatment time of the 1-cm field width was 3 times longer than that of plans with a field width of 5 cm. There was no substantial decrease in treatment time when the pitch was increased from 0.172 to 0.43, but the PTV indices were slightly compromised. As expected, field width had the most significant influence on all of the indices including PTV, OAR, and treatment time. For the patients with good performance who can tolerate a longer treatment time, we suggest a field width of 1 cm, pitch of 0.172, and modulation factor of 1.8; for the patients with poor performance status, field width of 5 cm, pitch of 0.287, and a modulation factor of 3.5 should be considered.

  9. 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

    India's ever increasing population has made it necessary to develop alternative modes of transportation with electric vehicles being the most preferred option. The major obstacle is the deteriorating impact on the utility distribution system brought about by improper setup of these charging...... stations. This paper deals with the optimal planning (siting and sizing) of charging station infrastructure in the city of Allahabad, India. This city is one of the upcoming smart cities, where electric vehicle transportation pilot project is going on under Government of India initiative. In this context......, 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...

  10. A critical evaluation of worst case optimization methods for robust intensity-modulated proton therapy planning

    International Nuclear Information System (INIS)

    Fredriksson, Albin; Bokrantz, Rasmus

    2014-01-01

    Purpose: To critically evaluate and compare three worst case optimization methods that have been previously employed to generate intensity-modulated proton therapy treatment plans that are robust against systematic errors. The goal of the evaluation is to identify circumstances when the methods behave differently and to describe the mechanism behind the differences when they occur. Methods: The worst case methods optimize plans to perform as well as possible under the worst case scenario that can physically occur (composite worst case), the combination of the worst case scenarios for each objective constituent considered independently (objectivewise worst case), and the combination of the worst case scenarios for each voxel considered independently (voxelwise worst case). These three methods were assessed with respect to treatment planning for prostate under systematic setup uncertainty. An equivalence with probabilistic optimization was used to identify the scenarios that determine the outcome of the optimization. Results: If the conflict between target coverage and normal tissue sparing is small and no dose-volume histogram (DVH) constraints are present, then all three methods yield robust plans. Otherwise, they all have their shortcomings: Composite worst case led to unnecessarily low plan quality in boundary scenarios that were less difficult than the worst case ones. Objectivewise worst case generally led to nonrobust plans. Voxelwise worst case led to overly conservative plans with respect to DVH constraints, which resulted in excessive dose to normal tissue, and less sharp dose fall-off than the other two methods. Conclusions: The three worst case methods have clearly different behaviors. These behaviors can be understood from which scenarios that are active in the optimization. No particular method is superior to the others under all circumstances: composite worst case is suitable if the conflicts are not very severe or there are DVH constraints whereas

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

    International Nuclear Information System (INIS)

    Matthews, Q; Mestrovic, A; Otto, K

    2014-01-01

    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

  12. Quality assurance in dosimetry and treatment planning

    International Nuclear Information System (INIS)

    Cunningham, J.R.

    1984-01-01

    The considerations of tissue response to radiation absorbed dose suggest a need for an accuracy of +/-5% in its delivery. This is very demanding and its regular achievement requires careful quality control. There are three distinct phases to the delivery of the planned treatment: calibration of the radiation beam in a reference situation, calculation of the dose distribution for a patient relative to the reference dose and the delivery of the radiation to the patient as planned. Each has distinctly different quality assurance requirements and must be diligently observed if the desired accuracy is to be achieved

  13. 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.

  14. An optimization planning technique for Suez Canal Network in Egypt

    Energy Technology Data Exchange (ETDEWEB)

    Abou El-Ela, A.A.; El-Zeftawy, A.A.; Allam, S.M.; Atta, Gasir M. [Electrical Engineering Dept., Faculty of Eng., Shebin El-Kom (Egypt)

    2010-02-15

    This paper introduces a proposed optimization technique POT for predicting the peak load demand and planning of transmission line systems. Many of traditional methods have been presented for long-term load forecasting of electrical power systems. But, the results of these methods are approximated. Therefore, the artificial neural network (ANN) technique for long-term peak load forecasting is modified and discussed as a modern technique in long-term load forecasting. The modified technique is applied on the Egyptian electrical network dependent on its historical data to predict the electrical peak load demand forecasting up to year 2017. This technique is compared with extrapolation of trend curves as a traditional method. The POT is applied also to obtain the optimal planning of transmission lines for the 220 kV of Suez Canal Network (SCN) using the ANN technique. The minimization of the transmission network costs are considered as an objective function, while the transmission lines (TL) planning constraints are satisfied. Zafarana site on the Red Sea coast is considered as an optimal site for installing big wind farm (WF) units in Egypt. So, the POT is applied to plan both the peak load and the electrical transmission of SCN with and without considering WF to develop the impact of WF units on the electrical transmission system of Egypt, considering the reliability constraints which were taken as a separate model in the previous techniques. The application on SCN shows the capability and the efficiently of the proposed techniques to obtain the predicting peak load demand and the optimal planning of transmission lines of SCN up to year 2017. (author)

  15. TH-CD-209-06: LET-Based Adjustment of IMPT Plans Using Prioritized Optimization

    Energy Technology Data Exchange (ETDEWEB)

    Unkelbach, J; Giantsoudi, D; Paganetti, H [Massachusetts General Hospital, Boston, MA (United States); Botas, P [Massachusetts General Hospital, Boston, MA (United States); Heidelberg University, Heidelberg, DE (Germany); Qin, N; Jia, X [The University of Texas Southwestern Medical Ctr, Dallas, TX (United States)

    2016-06-15

    Purpose: In-vitro experiments suggest an increase in proton relative biological effectiveness (RBE) towards the end of range. However, proton treatment planning and dose reporting for clinical outcome assessment has been based on physical dose and constant RBE. Therefore, treatment planning for intensity-modulated proton therapy (IMPT) is unlikely to transition radically to pure RBE-based planning. We suggest a hybrid approach where treatment plans are initially created based on physical dose constraints and prescriptions, and are subsequently altered to avoid high linear energy transfer (LET) in critical structures while limiting the degradation of the physical dose distribution. Methods: To allow fast optimization based on dose and LET we extended a GPU-based Monte-Carlo code towards providing dose-averaged LET in addition to dose for all pencil beams. After optimizing an initial IMPT plan based on physical dose, a prioritized optimization scheme is used to modify the LET distribution while constraining the physical dose objectives to values close to the initial plan. The LET optimization step is performed based on objective functions evaluated for the product of physical dose and LET (LETxD). To first approximation, LETxD represents a measure of the additional biological dose that is caused by high LET. Regarding optimization techniques, LETxD has the advantage of being a linear function of the pencil beam intensities. Results: The method is applicable to treatments where serial critical structures with maximum dose constraint are located in or near the target. We studied intra-cranial tumors (high-grade meningiomas, base-of-skull chordomas) where the target (CTV) overlaps with the brainstem and optic structures. Often, high LETxD in critical structures can be avoided while minimally compromising physical dose planning objectives. Conclusion: LET-based re-optimization of IMPT plans represents a pragmatic approach to bridge the gap between purely physical dose

  16. Optimization of Investment Planning Based on Game-Theoretic Approach

    Directory of Open Access Journals (Sweden)

    Elena Vladimirovna Butsenko

    2018-03-01

    Full Text Available The game-theoretic approach has a vast potential in solving economic problems. On the other hand, the theory of games itself can be enriched by the studies of real problems of decision-making. Hence, this study is aimed at developing and testing the game-theoretic technique to optimize the management of investment planning. This technique enables to forecast the results and manage the processes of investment planning. The proposed method of optimizing the management of investment planning allows to choose the best development strategy of an enterprise. This technique uses the “game with nature” model, and the Wald criterion, the maximum criterion and the Hurwitz criterion as criteria. The article presents a new algorithm for constructing the proposed econometric method to optimize investment project management. This algorithm combines the methods of matrix games. Furthermore, I show the implementation of this technique in a block diagram. The algorithm includes the formation of initial data, the elements of the payment matrix, as well as the definition of maximin, maximal, compromise and optimal management strategies. The methodology is tested on the example of the passenger transportation enterprise of the Sverdlovsk Railway in Ekaterinburg. The application of the proposed methodology and the corresponding algorithm allowed to obtain an optimal price strategy for transporting passengers for one direction of traffic. This price strategy contributes to an increase in the company’s income with minimal risk from the launch of this direction. The obtained results and conclusions show the effectiveness of using the developed methodology for optimizing the management of investment processes in the enterprise. The results of the research can be used as a basis for the development of an appropriate tool and applied by any economic entity in its investment activities.

  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* (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.

  18. Energy-Performance as a driver for optimal production planning

    International Nuclear Information System (INIS)

    Salahi, Niloofar; Jafari, Mohsen A.

    2016-01-01

    Highlights: • A 2-dimensional Energy-Performance measure is proposed for energy aware production. • This is a novel approach integrates energy efficiency with production requirements. • This approach simultaneously incorporates machine and process related specifications. • The problem is solved as stochastic MILP with constraints addressing risk averseness. • The optimization is illustrated for 2 cases of single and serial machining operation. • Impact of various electricity pricing schemes on proposed production plan is analyzed. - Abstract: In this paper, we present energy-aware production planning using a two-dimensional “Energy-Performance” measure. With this measure, the production plan explicitly takes into account machine-level requirements, process control strategies, product types and demand patterns. The “Energy-Performance” measure is developed based on an existing concept, namely, “Specific Energy” at machine level. It is further expanded to an “Energy-Performance” profile for a production line. A production planning problem is formulated as a stochastic MILP with risk-averse constraints to account for manufacturer’s risk averseness. The objective is to attain an optimal production plan that minimizes the total loss distribution subject to system throughput targets, probabilistic risk constraints and constraints imposed by the underlying “Energy-Performance” pattern. Electricity price and demand per unit time are assumed to be stochastic. Conditional Value at Risk (CVaR) of loss distributions is used as the manufacturer’s risk measure. Both single-machine and production lines are studied for different profiles and electricity pricing schemes. It is shown that the shape of “Energy-Performance” profile can change optimal plans.

  19. Comparison of optimization algorithms in intensity-modulated radiation therapy planning

    Science.gov (United States)

    Kendrick, Rachel

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

  20. An optimal control approach to manpower planning problem

    Directory of Open Access Journals (Sweden)

    H. W. J. Lee

    2001-01-01

    Full Text Available A manpower planning problem is studied in this paper. The model includes scheduling different types of workers over different tasks, employing and terminating different types of workers, and assigning different types of workers to various trainning programmes. The aim is to find an optimal way to do all these while keeping the time-varying demand for minimum number of workers working on each different tasks satisfied. The problem is posed as an optimal discrete-valued control problem in discrete time. A novel numerical scheme is proposed to solve the problem, and an illustrative example is provided.

  1. An Optimal Turkish Private Pension Plan with a Guarantee Feature

    Directory of Open Access Journals (Sweden)

    Ayşegül İşcanog̃lu-Çekiç

    2016-06-01

    Full Text Available The Turkish Private Pension System is an investment system which aims to generate income for future consumption. This is a volunteer system, and the contributions are held in individual portfolios. Therefore, management of the funds is an important issue for both the participants and the insurance company. In this study, we propose an optimal private pension plan with a guarantee feature that is based on Constant Proportion Portfolio Insurance (CPPI. We derive a closed form formula for the optimal strategy with the help of dynamic programming. Moreover, our model is evaluated with numerical examples, and we compare its performance by implementing a sensitivity analysis.

  2. Collision detection and avoidance during treatment planning

    International Nuclear Information System (INIS)

    Humm, John L.; Pizzuto, Domenico; Fleischman, Eric; Mohan, Radhe

    1995-01-01

    Purpose: To develop computer software that assists the planner avoid potential gantry collisions with the patient or patient support assembly during the treatment planning process. Methods and Materials: The approach uses a simulation of the therapy room with a scale model of the treatment machine. Because the dimensions of the machine and patient are known, one can calculate a priori whether any desired therapy field is possible or will result in a collision. To assist the planner, we have developed a graphical interface enabling the accurate visualization of each treatment field configuration with a 'room's eye view' treatment planning window. This enables the planner to be aware of, and alleviate any potential collision hazards. To circumvent blind spots in the graphic representation, an analytical software module precomputes whether each update of the gantry or turntable position is safe. Results: If a collision is detected, the module alerts the planner and suggests collision evasive actions such as either an extended distance treatment or the gantry angle of closest approach. Conclusions: The model enables the planner to experiment with unconventional noncoplanar treatment fields, and immediately test their feasibility

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

    International Nuclear Information System (INIS)

    Chang, J.

    2015-01-01

    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

  4. 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

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

    International Nuclear Information System (INIS)

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

    2012-01-01

    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

  6. Optimization of personalized therapies for anticancer treatment.

    Science.gov (United States)

    Vazquez, Alexei

    2013-04-12

    As today, there are hundreds of targeted therapies for the treatment of cancer, many of which have companion biomarkers that are in use to inform treatment decisions. If we would consider this whole arsenal of targeted therapies as a treatment option for every patient, very soon we will reach a scenario where each patient is positive for several markers suggesting their treatment with several targeted therapies. Given the documented side effects of anticancer drugs, it is clear that such a strategy is unfeasible. Here, we propose a strategy that optimizes the design of combinatorial therapies to achieve the best response rates with the minimal toxicity. In this methodology markers are assigned to drugs such that we achieve a high overall response rate while using personalized combinations of minimal size. We tested this methodology in an in silico cancer patient cohort, constructed from in vitro data for 714 cell lines and 138 drugs reported by the Sanger Institute. Our analysis indicates that, even in the context of personalized medicine, combinations of three or more drugs are required to achieve high response rates. Furthermore, patient-to-patient variations in pharmacokinetics have a significant impact in the overall response rate. A 10 fold increase in the pharmacokinetics variations resulted in a significant drop the overall response rate. The design of optimal combinatorial therapy for anticancer treatment requires a transition from the one-drug/one-biomarker approach to global strategies that simultaneously assign makers to a catalog of drugs. The methodology reported here provides a framework to achieve this transition.

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

    Science.gov (United States)

    Masi, Kathryn; Archer, Paul; Jackson, William; Sun, Yilun; Schipper, Matthew; Hamstra, Daniel; Matuszak, Martha

    2017-11-22

    Commissioning a new treatment planning system (TPS) involves many time-consuming tasks. We investigated the role that knowledge-based planning (KBP) can play in aiding a clinic's transition to a new TPS. Sixty clinically treated prostate/prostate bed intensity-modulated radiation therapy (IMRT) plans were exported from an in-house TPS and were used to create a KBP model in a newly implemented commercial application. To determine the benefit that KBP may have in a TPS transition, the model was tested on 2 groups of patients. Group 1 consisted of the first 10 prostate/prostate bed patients treated in the commercial TPS after the transition from the in-house TPS. Group 2 consisted of 10 patients planned in the commercial TPS after 8 months of clinical use. The KBP-generated plan was compared with the clinically used plan in terms of plan quality (ability to meet planning objectives and overall dose metrics) and planning efficiency (time required to generate clinically acceptable plans). The KBP-generated plans provided a significantly improved target coverage (p = 0.01) compared with the clinically used plans for Group 1, but yielded plans of comparable target coverage to the clinically used plans for Group 2. For the organs at risk, the KBP-generated plans produced lower doses, on average, for every normal-tissue objective except for the maximum dose to 0.1 cc of rectum. The time needed for the KBP-generated plans ranged from 6 to 15 minutes compared to 30 to 150 and 15 to 60 minutes for manual planning in Groups 1 and 2, respectively. KBP is a promising tool to aid in the transition to a new TPS. Our study indicates that high-quality treatment plans could have been generated in the newly implemented TPS more efficiently compared with not using KBP. Even after 8 months of the clinical use, KBP still showed an increase in plan quality and planning efficiency compared with manual planning. Copyright © 2017 American Association of Medical Dosimetrists. Published

  8. Effects of spot parameters in pencil beam scanning treatment planning.

    Science.gov (United States)

    Kraan, Aafke Christine; Depauw, Nicolas; Clasie, Ben; Giunta, Marina; Madden, Tom; Kooy, Hanne M

    2018-01-01

    distances, many beam directions, and low fractional dose values. The choice of spot parameters values is a trade-off between accelerator and beam line design, plan quality, and treatment efficiency. We recommend the use of small spot sizes for better organ-at-risk sparing and lateral interspot distances of 1.5σ to avoid long treatment times. We note that plan quality is influenced by the charge cutoff. Our results show that the charge cutoff can be sufficiently large (i.e., 10 6 protons) to accommodate limitations on beam delivery systems. It is, therefore, not necessary per se to include the charge cutoff in the treatment planning optimization such that Pareto navigation (e.g., as practiced at our institution) is not excluded and optimal plans can be obtained without, perhaps, a bias from the charge cutoff. We recommend that the impact of a minimum charge cut impact is carefully verified for the spot sizes and spot distances applied or that it is accommodated in the TPS. © 2017 American Association of Physicists in Medicine.

  9. TH-E-BRE-08: GPU-Monte Carlo Based Fast IMRT Plan Optimization

    Energy Technology Data Exchange (ETDEWEB)

    Li, Y; Tian, Z; Shi, F; Jiang, S; Jia, X [The University of Texas Southwestern Medical Ctr, Dallas, TX (United States)

    2014-06-15

    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, rough beamlet dose calculations is conducted with only a small number of particles 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, 10{sup 5} particles per beamlet in the first round, and 10{sup 8} 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.

  10. 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.

  11. An efficient inverse radiotherapy planning method for VMAT using quadratic programming optimization.

    Science.gov (United States)

    Hoegele, W; Loeschel, R; Merkle, N; Zygmanski, P

    2012-01-01

    The purpose of this study is to investigate the feasibility of an inverse planning optimization approach for the Volumetric Modulated Arc Therapy (VMAT) based on quadratic programming and the projection method. The performance of this method is evaluated against a reference commercial planning system (eclipse(TM) for rapidarc(TM)) for clinically relevant cases. The inverse problem is posed in terms of a linear combination of basis functions representing arclet dose contributions and their respective linear coefficients as degrees of freedom. MLC motion is decomposed into basic motion patterns in an intuitive manner leading to a system of equations with a relatively small number of equations and unknowns. These equations are solved using quadratic programming under certain limiting physical conditions for the solution, such as the avoidance of negative dose during optimization and Monitor Unit reduction. The modeling by the projection method assures a unique treatment plan with beneficial properties, such as the explicit relation between organ weightings and the final dose distribution. Clinical cases studied include prostate and spine treatments. The optimized plans are evaluated by comparing isodose lines, DVH profiles for target and normal organs, and Monitor Units to those obtained by the clinical treatment planning system eclipse(TM). The resulting dose distributions for a prostate (with rectum and bladder as organs at risk), and for a spine case (with kidneys, liver, lung and heart as organs at risk) are presented. Overall, the results indicate that similar plan qualities for quadratic programming (QP) and rapidarc(TM) could be achieved at significantly more efficient computational and planning effort using QP. Additionally, results for the quasimodo phantom [Bohsung et al., "IMRT treatment planning: A comparative inter-system and inter-centre planning exercise of the estro quasimodo group," Radiother. Oncol. 76(3), 354-361 (2005)] are presented as an example

  12. Application of super-omni wedge concept to conformal radiotherapy treatment planning

    International Nuclear Information System (INIS)

    Dai Jianrong; Fu Weihua; Hu Yimin

    2004-01-01

    Objective: To describe a method which can optimize beam weight, wedge angle, and wedge orientation simultaneously by combining the super-omni wedge (SOW) concept with the function of beam weight optimization provided by a commercial treatment planning system. Methods: A five-step procedure including: Step 1. To set up four 60 degree nominal wedged beams for each beam direction with the wedge orientations of 'LEFT', 'IN', 'RIGHT', 'OUT', respectively; Step 2. To define an optimization request, including an optimization goal and constraints. Authors use CMS Focus treatment planning system which allows us to choose 'maximize target dose' or 'minimize critical structure dose' as the optimization goal, and to set minimum target dose, maximum target dose, and maximum average dose of critical structures as constraints. Then the optimization process was launched as step 3; Step 4. To evaluate the plan using isodose distributions and dose-volume histograms. If acceptable, go to Step 5. Otherwise, go back to Step 2 to modify optimization constraints; and Step 5. Transform the SOW beams into the beams of omni wedge so as to reduce the number of to-be-delivered beams. Results: This procedure was found being able to demonstrate successfully in two clinical cases: an esophageal carcinoma and a brain tumor. Compared with manually designed plan, the optimized plan showed better dose homogeneity in the targets and better sparing of the critical structures. Conclusions: This method described is able to optimize beam weights while working with a treatment planning system. Not only does it improve treatment plans' quality, but also shorten the treatment planning process

  13. Electron Density Calibration for Radiotherapy Treatment Planning

    International Nuclear Information System (INIS)

    Herrera-Martinez, F.; Rodriguez-Villafuerte, M.; Martinez-Davalos, A.; Ruiz-Trejo, C.; Celis-Lopez, M. A.; Larraga-Gutierrez, J. M.; Garcia-Garduno, A.

    2006-01-01

    Computed tomography (CT) images are used as basic input data for most modern radiosurgery treatment planning systems (TPS). CT data not only provide anatomic information to delineate target volumes, but also allow the introduction of corrections for tissue inhomogeneities into dose calculations during the treatment planning procedure. These corrections involve the determination of a relationship between tissue electron density (ρe) and their corresponding Hounsfield Units (HU). In this work, an elemental analysis of different commercial tissue equivalent materials using Scanning Electron Microscopy was carried out to characterize their chemical composition. The tissue equivalent materials were chosen to ensure a large range of ρe to be included in the CT scanner calibration. A phantom was designed and constructed with these materials to simulate the size of a human head

  14. 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.

  15. Trajectory planning and optimal tracking for an industrial mobile robot

    Science.gov (United States)

    Hu, Huosheng; Brady, J. Michael; Probert, Penelope J.

    1994-02-01

    This paper introduces a unified approach to trajectory planning and tracking for an industrial mobile robot subject to non-holonomic constraints. We show (1) how a smooth trajectory is generated that takes into account the constraints from the dynamic environment and the robot kinematics; and (2) how a general predictive controller works to provide optimal tracking capability for nonlinear systems. The tracking performance of the proposed guidance system is analyzed by simulation.

  16. Optimal Multi-Level Lot Sizing for Requirements Planning Systems

    OpenAIRE

    Earle Steinberg; H. Albert Napier

    1980-01-01

    The wide spread use of advanced information systems such as Material Requirements Planning (MRP) has significantly altered the practice of dependent demand inventory management. Recent research has focused on development of multi-level lot sizing heuristics for such systems. In this paper, we develop an optimal procedure for the multi-period, multi-product, multi-level lot sizing problem by modeling the system as a constrained generalized network with fixed charge arcs and side constraints. T...

  17. Three-dimensional radiation treatment planning

    International Nuclear Information System (INIS)

    Mohan, R.

    1989-01-01

    A major aim of radiation therapy is to deliver sufficient dose to the tumour volume to kill the cancer cells while sparing the nearby health organs to prevent complications. With the introduction of devices such as CT and MR scanners, radiation therapy treatment planners have access to full three-dimensional anatomical information to define, simulate, and evaluate treatments. There are a limited number of prototype software systems that allow 3D treatment planning currently in use. In addition, there are more advanced tools under development or still in the planning stages. They require sophisticated graphics and computation equipment, complex physical and mathematical algorithms, and new radiation treatment machines that deliver dose very precisely under computer control. Components of these systems include programs for the identification and delineation of the anatomy and tumour, the definition of radiation beams, the calculation of dose distribution patterns, the display of dose on 2D images and as three dimensional surfaces, and the generation of computer images to verify proper patient positioning in treatment. Some of these functions can be performed more quickly and accurately if artificial intelligence or expert systems techniques are employed. 28 refs., figs

  18. CT treatment planning of the liver

    International Nuclear Information System (INIS)

    Lim, M.

    1988-01-01

    The article deals with CT treatment planning of the liver to maximize the dose to the liver but minimize the dose to the right kidney, spinal cord, and bowels. (The left kidney is out of the field due to the oblique angles of the fields.) This is achieved by right kidney shielding reconstruction from multislice CT treatment planning and by the oblique angles of the fields. Without CT, it is not possible to utilize oblique fields to cover the liver. With conventional AP-PA fields, not only is the whole liver treated but also most of the right kidney, half of the left kidney, bowels and spinal cord. Tolerance dose to the kidneys is exceeded if adequate dose is delivered to the liver. Some new computer algorithms display a bird's eye view of the shielding but this paper presents for the first time, a technique for actual shielding reconstruction from multislice CT treatment planning for use by the radiation oncologist when shielding blocks are drawn on the simulator films

  19. 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...

  20. Optimal pricing and marketing planning for deteriorating items.

    Directory of Open Access Journals (Sweden)

    Seyed Reza Moosavi Tabatabaei

    Full Text Available 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.

  1. 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

  2. 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.

  3. Incorporating organ movements in IMRT treatment planning for prostate cancer: Minimizing uncertainties in the inverse planning process

    International Nuclear Information System (INIS)

    Unkelbach, Jan; Oelfke, Uwe

    2005-01-01

    We investigate an off-line strategy to incorporate inter fraction organ movements in IMRT treatment planning. Nowadays, imaging modalities located in the treatment room allow for several CT scans of a patient during the course of treatment. These multiple CT scans can be used to estimate a probability distribution of possible patient geometries. This probability distribution can subsequently be used to calculate the expectation value of the delivered dose distribution. In order to incorporate organ movements into the treatment planning process, it was suggested that inverse planning could be based on that probability distribution of patient geometries instead of a single snapshot. However, it was shown that a straightforward optimization of the expectation value of the dose may be insufficient since the expected dose distribution is related to several uncertainties: first, this probability distribution has to be estimated from only a few images. And second, the distribution is only sparsely sampled over the treatment course due to a finite number of fractions. In order to obtain a robust treatment plan these uncertainties should be considered and minimized in the inverse planning process. In the current paper, we calculate a 3D variance distribution in addition to the expectation value of the dose distribution which are simultaniously optimized. The variance is used as a surrogate to quantify the associated risks of a treatment plan. The feasibility of this approach is demonstrated for clinical data of prostate patients. Different scenarios of dose expectation values and corresponding variances are discussed

  4. Optimal Risk-Based Inspection Planning for Offshore Wind Turbines

    DEFF Research Database (Denmark)

    Rangel-Ramirez, Jose G.; Sørensen, John Dalsgaard

    2008-01-01

    , 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......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...... for optimal inspection and maintenance planning of offshore wind turbines is presented. Special aspects for offshore wind turbines are considered: usually the wind loading are dominating the wave loading, wake effects in wind farms are important and the reliability level is typically significantly lower than...

  5. Motor planning flexibly optimizes performance under uncertainty about task goals.

    Science.gov (United States)

    Wong, Aaron L; Haith, Adrian M

    2017-03-03

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

  6. 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.

  7. 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.

  8. Development of independent MU/treatment time verification algorithm for non-IMRT treatment planning: A clinical experience

    Science.gov (United States)

    Tatli, Hamza; Yucel, Derya; Yilmaz, Sercan; Fayda, Merdan

    2018-02-01

    The aim of this study is to develop an algorithm for independent MU/treatment time (TT) verification for non-IMRT treatment plans, as a part of QA program to ensure treatment delivery accuracy. Two radiotherapy delivery units and their treatment planning systems (TPS) were commissioned in Liv Hospital Radiation Medicine Center, Tbilisi, Georgia. Beam data were collected according to vendors' collection guidelines, and AAPM reports recommendations, and processed by Microsoft Excel during in-house algorithm development. The algorithm is designed and optimized for calculating SSD and SAD treatment plans, based on AAPM TG114 dose calculation recommendations, coded and embedded in MS Excel spreadsheet, as a preliminary verification algorithm (VA). Treatment verification plans were created by TPSs based on IAEA TRS 430 recommendations, also calculated by VA, and point measurements were collected by solid water phantom, and compared. Study showed that, in-house VA can be used for non-IMRT plans MU/TT verifications.

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

    Science.gov (United States)

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

    2015-09-17

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

  10. 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.

  11. Sequential use of simulation and optimization in analysis and planning

    Science.gov (United States)

    Hans R. Zuuring; Jimmie D. Chew; J. Greg Jones

    2000-01-01

    Management activities are analyzed at landscape scales employing both simulation and optimization. SIMPPLLE, a stochastic simulation modeling system, is initially applied to assess the risks associated with a specific natural process occurring on the current landscape without management treatments, but with fire suppression. These simulation results are input into...

  12. Strategic planning of treatment for hyperthyroid disease

    International Nuclear Information System (INIS)

    Hoeffer, R.

    1994-01-01

    Strategic planning of treatment of hyperthyroid disease must correspond to the pathophysiological mechanism of elevation of thyroid hormone serum concentration, i.e. excess stimulation, autonomous thyroid function, destruction induced hyperthyoroxinemia. In cases of excess stimulation one should go to extremes to save the essentially 'normal' thyroid gland and life-long antithyroid drug treatment confronts with total ablation of the thyroid gland in non remitting disease. Size and quantity of regions of autonomously functioning follicles/cells will be the determinant of therapeutic strategy in cases of autonomous thyroid function. Selective surgery confronts with radioiodine treatment aiming at 'restitutio ad integrum'. In destruction induced hyperthyroxinemia antiintlammatory and symptomatic measures may help to bridge the time to the return of normal hormone concentrations. Based on these considerations a detailed therapeutic strategy for hyperthyroid disease can be designed. (author)

  13. Physical treatment planning by several approaches

    International Nuclear Information System (INIS)

    Burger, G.; Morhart, A.; Wittmann, A.

    1985-01-01

    Neutron isodose planning may be performed by commercial treatment planning systems for photons, providing that certain modifications are applied. All geometry-related corrections such as for nonregular surfaces and oblique incidence remain unchanged. The main modifications concern the tissue-air-ratio, containing essentially the attenuation correction function. We have as a first step applied this modified commercial system to a few regular exposure situations in a homogenious water phantom and compared the generated isodose charts with those derived by direct Monte Carlo calculations of the neutron transport for the corresponding fields. As expected the commercial methods do not incorporate the necessary corrections for the change of scatter conditions in case of oblique incidence or wedged fields. For this reason we developed another approach, based upon the numerical superposition of dose matrices for pencil beams. These matrices were again Monte Carlo calculated. From it build-up functions can be derived by partial radial integration. The isodose charts generated by superposition of pencil beam dose distributions agree much better with directly Monte Carlo calculated ones, than those from the commercial treatment planning system. Based upon these results the method was finally applied to real patients cross sections, as derived from CT or MR-tomography. In the latter case one can even perform a pixelwise attenuation correction, if spin density images are available

  14. 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.

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

    International Nuclear Information System (INIS)

    De Wagter, C.

    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

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

    International Nuclear Information System (INIS)

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

    2002-01-01

    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. (author)

  17. 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.

  18. 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)

  19. Treatment planning for MLC based robotic radiosurgery for brain metastases: plan comparison with circular fields and suggestions for planning strategies

    Directory of Open Access Journals (Sweden)

    Schmitt Daniela

    2017-09-01

    Full Text Available To evaluate the possible range of application of the new InCise2 MLC for the CyberKnife M6 system in brain radiosurgery, a plan comparison was made for 10 brain metastases sized between 1.5 and 9cm3 in 10 patients treated in a single fraction each. The target volumes consist of a PTV derived by expanding the GTV by 1mm and were chosen to have diversity in the cohort regarding regularity of shape, location and the structures needed to be blocked for beam transmission in the vicinity. For each case, two treatment plans were optimized: one using the MLC and one using the IRIS-collimator providing variable circular fields. Plan re-quirements were: dose prescription to the 70% isodose line (18 or 20Gy, 100% GTV coverage, ≥98% PTV coverage, undisturbed central high dose region (95% of maximum dose and a conformity index as low as possible. Plan com-parison parameters were: conformity index (CI, high-dose gradient index (GIH, low-dose gradient index (GIL, total number of monitor units (MU and expected treatment time (TT. For all cases, clinically acceptable plans could be gen-erated with the following results (mean±SD for CI, GIH, GIL, MU and TT, respectively for the MLC plans: 1.09±0.03, 2.77±0.26, 2.61±0.08, 4514±830MU and 27±5min and for the IRIS plans: 1.05±0.01, 3.00±0.35, 2.46±0.08, 8557±1335MU and 42±7min. In summary, the MLC plans were on average less conformal and had a shallower dose gradient in the low dose region, but a steeper dose gradient in the high dose region. This is accompanied by a smaller vol-ume receiving 10Gy. A plan by plan comparison shows that usage of the MLC can spare about one half of the MUs and one third of treatment time. From these experiences and results suggestions for MLC planning strategy can be de-duced.

  20. Optimized Planning Target Volume for Intact Cervical Cancer

    International Nuclear Information System (INIS)

    Khan, Alvin; Jensen, Lindsay G.; Sun Shuai; Song, William Y.; Yashar, Catheryn M.; Mundt, Arno J.; Zhang Fuquan; Jiang, Steve B.; Mell, Loren K.

    2012-01-01

    Purpose: To model interfraction clinical target volume (CTV) variation in patients with intact cervical cancer and design a planning target volume (PTV) that minimizes normal tissue dose while maximizing CTV coverage. Methods and Materials: We analyzed 50 patients undergoing external-beam radiotherapy for intact cervical cancer using daily online cone-beam computed tomography (CBCT). The CBCTs (n = 972) for each patient were rigidly registered to the planning CT. The CTV was delineated on the planning CT (CTV 0 ) and the set of CBCTs ({CTV 1 –CTV 25 }). Manual (n = 98) and automated (n = 668) landmarks were placed over the surface of CTV 0 with reference to defined anatomic structures. Normal vectors were extended from each landmark, and the minimum length required for a given probability of encompassing CTV 1 –CTV 25 was computed. The resulting expansions were used to generate an optimized PTV. Results: The mean (SD; range) normal vector length to ensure 95% coverage was 4.3 mm (2.7 mm; 1–16 mm). The uniform expansion required to ensure 95% probability of CTV coverage was 13 mm. An anisotropic margin of 20 mm anteriorly and posteriorly and 10 mm superiorly, inferiorly, and laterally also would have ensured a 95% probability of CTV coverage. The volume of the 95% optimized PTV (1470 cm 3 ) was significantly lower than both the anisotropic PTV (2220 cm 3 ) and the uniformly expanded PTV (2110 cm 3 ) (p 0 , 5–10 mm along the interfaces of CTV 0 with the bladder and rectum, and 10–14 mm along the anterior surface of CTV 0 at the level of the uterus. Conclusion: Optimizing PTV definition according to surface landmarking resulted in a high probability of CTV coverage with reduced PTV volumes. Our results provide data justifying planning margins to use in practice and clinical trials.

  1. 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.

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

    International Nuclear Information System (INIS)

    Purdie, Thomas G.; Dinniwell, Robert E.; Fyles, Anthony; Sharpe, Michael B.

    2014-01-01

    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

  3. Intracavitary radiation treatment planning and dose evaluation

    International Nuclear Information System (INIS)

    Anderson, L.L.; Masterson, M.E.; Nori, D.

    1987-01-01

    Intracavitary radiation therapy with encapsulated radionuclide sources has generally involved, since the advent of afterloading techniques, inserting the sources in tubing previously positioned within a body cavity near the region to be treated. Because of the constraints on source locations relative to the target region, the functions of treatment planning and dose evaluation, usually clearly separable in interstitial brachytherapy, tend to merge in intracavitary therapy. Dose evaluation is typically performed for multiple source-strength configurations in the process of planning and thus may be regarded as complete when a particular configuration has been selected. The input data for each dose evaluation, of course, must include reliable dose distribution information for the source-applicator combinations used. Ultimately, the goal is to discover the source-strength configuration that results in the closest possible approach to the dose distribution desired

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

    International Nuclear Information System (INIS)

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

    2013-01-01

    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 mm distance

  5. Optimal treatment cost allocation methods in pollution control

    International Nuclear Information System (INIS)

    Chen Wenying; Fang Dong; Xue Dazhi

    1999-01-01

    Total emission control is an effective pollution control strategy. However, Chinese application of total emission control lacks reasonable and fair methods for optimal treatment cost allocation, a critical issue in total emission control. The author considers four approaches to allocate treatment costs. The first approach is to set up a multiple-objective planning model and to solve the model using the shortest distance ideal point method. The second approach is to define degree of satisfaction for cost allocation results for each polluter and to establish a method based on this concept. The third is to apply bargaining and arbitration theory to develop a model. The fourth is to establish a cooperative N-person game model which can be solved using the Shapley value method, the core method, the Cost Gap Allocation method or the Minimum Costs-Remaining Savings method. These approaches are compared using a practicable case study

  6. 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.

  7. Adaptive brachytherapy of cervical cancer, comparison of conventional point A and CT based individual treatment planning

    International Nuclear Information System (INIS)

    Wanderaas, Anne D.; Langdal, Ingrid; Danielsen, Signe; Frykholm, Gunilla; Marthinsen, Anne B. L; Sundset, Marit

    2012-01-01

    Background. Locally advanced cervical cancer is commonly treated with external radiation therapy combined with local brachytherapy. The brachytherapy is traditionally given based on standard dose planning with prescription of dose to point A. Dosimetric aspects when changing from former standard treatment to individualized treatment plans based on computed tomography (CT) images are here investigated. Material and methods. Brachytherapy data from 19 patients with a total of 72 individual treatment fractions were retrospectively reviewed. Standard library plans were analyzed with respect to doses to organs at risk (OARs), and the result was compared to corresponding delivered individualized plans. The theoretical potential of further optimization based on prescription to target volumes was investigated. The treatments were performed with a Fletcher applicator. Results. For standard treatment planning, the tolerance dose limits were exceeded in the bladder, rectum and sigmoid in 26%, 4% and 15% of the plans, respectively. This was observed most often for the smallest target volumes. The individualized planning of the delivered treatment gave the possibility of controlling the dose to critical organs to below certain limits. The dose was still prescribed to point A. An increase in target dose coverage was achieved when additional individual optimization was performed, while still keeping the dose to the OARs below predefined limits. Relatively low average target coverage, especially for the largest volumes was however seen. Conclusion. The individualized delivered treatment plans ensured that doses to OARs were within acceptable limits. This was not the case in 42% of the corresponding standard plans. Further optimized treatment plans were found to give an overall better dose coverage. In lack of MR capacity, it may be favorable to use CT for planning due to possible protection of OARs. The CT based target volumes were, however, not equivalent to the volumes described

  8. 71: Three dimensional radiation treatment planning system

    International Nuclear Information System (INIS)

    Purdy, J.A.; Wong, J.W.; Harms, W.B.; Drzymala, R.E.; Emami, B.

    1987-01-01

    A prototype 3-dimensional (3-D) radiation treatment planning (RTP) system has been developed and is in use. The system features a real-time display device and an array processor for computer intensive computations. The dose distribution can be displayed as 2-D isodose distributions superimposed on 2-D gray scale images of the patient's anatomy for any arbitrary plane and as a display of isodose surfaces in 3-D. In addition, dose-volume histograms can be generated. 7 refs.; 2 figs

  9. Automatic liver contouring for radiotherapy treatment planning

    International Nuclear Information System (INIS)

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

    2015-01-01

    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

  10. Science-based strategic planning for hazardous fuel treatment.

    Science.gov (United States)

    D.L. Peterson; M.C. Johnson

    2007-01-01

    A scientific foundation coupled with technical support is needed to develop long-term strategic plans for fuel and vegetation treatments on public lands. These plans are developed at several spatial scales and are typically a component of fire management plans and other types of resource management plans. Such plans need to be compatible with national, regional, and...

  11. 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...

  12. 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.

  13. 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.

  14. Hierarchical artificial bee colony algorithm for RFID network planning optimization.

    Science.gov (United States)

    Ma, Lianbo; Chen, Hanning; Hu, Kunyuan; Zhu, Yunlong

    2014-01-01

    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.

  15. Optimal Diet Planning for Eczema Patient Using Integer Programming

    Science.gov (United States)

    Zhen Sheng, Low; Sufahani, Suliadi

    2018-04-01

    Human diet planning is conducted by choosing appropriate food items that fulfill the nutritional requirements into the diet formulation. This paper discusses the application of integer programming to build the mathematical model of diet planning for eczema patients. The model developed is used to solve the diet problem of eczema patients from young age group. The integer programming is a scientific approach to select suitable food items, which seeks to minimize the costs, under conditions of meeting desired nutrient quantities, avoiding food allergens and getting certain foods into the diet that brings relief to the eczema conditions. This paper illustrates that the integer programming approach able to produce the optimal and feasible solution to deal with the diet problem of eczema patient.

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

    Science.gov (United States)

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

    2018-03-13

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

  17. A Generalized Orienteering Problem for Optimal Search and Interdiction Planning

    Science.gov (United States)

    2013-09-01

    proposed for the TOP. Boussier et al. (2007) presents a branch-and- price algorithm that relies on a pricing step within the column generation phase...dominates in all metric categories and B&B appears to be the least favorable. We use performance proles ( Dolan and Moré 2002) as a method for comparing...exceeded, with greater computing power it may be possible to obtain the optimal solution in a period of time that can support a 24-hour planning

  18. Recovery post treatment: plans, barriers and motivators.

    Science.gov (United States)

    Duffy, Paul; Baldwin, Helen

    2013-01-30

    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. 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. 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. 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 maintaining aspects of a 'normal' life i.e. 'social and physical

  19. 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

  20. Volumetric visualization of anatomy for treatment planning

    International Nuclear Information System (INIS)

    Pelizzari, Charles A.; Grzeszczuk, Robert; Chen, George T. Y.; Heimann, Ruth; Haraf, Daniel J.; Vijayakumar, Srinivasan; Ryan, Martin J.

    1996-01-01

    Purpose: Delineation of volumes of interest for three-dimensional (3D) treatment planning is usually performed by contouring on two-dimensional sections. We explore the usage of segmentation-free volumetric rendering of the three-dimensional image data set for tumor and normal tissue visualization. Methods and Materials: Standard treatment planning computed tomography (CT) studies, with typically 5 to 10 mm slice thickness, and spiral CT studies with 3 mm slice thickness were used. The data were visualized using locally developed volume-rendering software. Similar to the method of Drebin et al., CT voxels are automatically assigned an opacity and other visual properties (e.g., color) based on a probabilistic classification into tissue types. Using volumetric compositing, a projection into the opacity-weighted volume is produced. Depth cueing, perspective, and gradient-based shading are incorporated to achieve realistic images. Unlike surface-rendered displays, no hand segmentation is required to produce detailed renditions of skin, muscle, or bony anatomy. By suitable manipulation of the opacity map, tissue classes can be made transparent, revealing muscle, vessels, or bone, for example. Manually supervised tissue masking allows irrelevant tissues overlying tumors or other structures of interest to be removed. Results: Very high-quality renditions are produced in from 5 s to 1 min on midrange computer workstations. In the pelvis, an anteroposterior (AP) volume rendered view from a typical planning CT scan clearly shows the skin and bony anatomy. A muscle opacity map permits clear visualization of the superficial thigh muscles, femoral veins, and arteries. Lymph nodes are seen in the femoral triangle. When overlying muscle and bone are cut away, the prostate, seminal vessels, bladder, and rectum are seen in 3D perspective. Similar results are obtained for thorax and for head and neck scans. Conclusion: Volumetric visualization of anatomy is useful in treatment

  1. 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

  2. Constrained treatment planning using sequential beam selection

    International Nuclear Information System (INIS)

    Woudstra, E.; Storchi, P.R.M.

    2000-01-01

    In this paper an algorithm is described for automated treatment plan generation. The algorithm aims at delivery of the prescribed dose to the target volume without violation of constraints for target, organs at risk and the surrounding normal tissue. Pre-calculated dose distributions for all candidate orientations are used as input. Treatment beams are selected in a sequential way. A score function designed for beam selection is used for the simultaneous selection of beam orientations and weights. In order to determine the optimum choice for the orientation and the corresponding weight of each new beam, the score function is first redefined to account for the dose distribution of the previously selected beams. Addition of more beams to the plan is stopped when the target dose is reached or when no additional dose can be delivered without violating a constraint. In the latter case the score function is modified by importance factor changes to enforce better sparing of the organ with the limiting constraint and the algorithm is run again. (author)

  3. Novel tracer for radiation treatment planning

    International Nuclear Information System (INIS)

    Schwarzenboeck, S.; Krause, B.J.; Herrmann, K.; Gaertner, F.; Souvatzoglou, M.; Klaesner, B.

    2011-01-01

    PET and PET/CT with innovative tracers gain increasing importance in diagnosis and therapy management, and radiation treatment planning in radio-oncology besides the widely established FDG. The introduction of [ 18 F]Fluorothymidine ([ 18 F]FLT) as marker of proliferation, [ 18 F]Fluoromisonidazole ([ 18 F]FMISO) and [ 18 F]Fluoroazomycin-Arabinoside ([ 18 F]FAZA) as tracer of hypoxia, [ 18 F]Fluoroethyltyrosine ([ 18 F]FET) and [ 11 C]Methionine for brain tumour imaging, [ 68 Ga]DOTATOC for somatostatin receptor imaging, [ 18 F]FDOPA for dopamine synthesis and radioactively labeled choline derivatives for imaging phospholipid metabolism have opened novel approaches to tumour imaging. Some of these tracers have already been implemented into radio-oncology: Amino acid PET and PET/CT have the potential to optimise radiation treatment planning of brain tumours through accurate delineation of tumour tissue from normal tissue, necrosis and edema. Hypoxia represents a major therapeutic problem in radiation therapy. Hypoxia imaging is very attractive as it may allow to increase the dose in hypoxic tumours potentially allowing for a better tumour control. Advances in hybrid imaging, i.e. the introduction of MR/PET, may also have an impact in radio-oncology through synergies related to the combination of molecular signals of PET and a high soft tissue contrast of MRI as well as functional MRI capabilities. (orig.)

  4. A complex of optimization problems in planning for the development of mining operations in coal mines

    Energy Technology Data Exchange (ETDEWEB)

    Todorov, A K; Arnaudov, B K; Brankova, B A; Gyuleva, B I; Zakhariyev, G K

    1977-01-01

    The system for planning for the development of coal mines is a complex of interrelated plan optimization, plan calculation and supporting (accounting-analytical and standards) tasks. An important point in this complex is held by the plan optimization tasks. The questions about the synthesis and the structural peculiarities of the system, the essence and machine realization of the tasks are examined.

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

    International Nuclear Information System (INIS)

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

    2015-01-01

    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

  6. Evaluation of a commercial automatic treatment planning system for prostate cancers.

    Science.gov (United States)

    Nawa, Kanabu; Haga, Akihiro; Nomoto, Akihiro; Sarmiento, Raniel A; Shiraishi, Kenshiro; Yamashita, Hideomi; Nakagawa, Keiichi

    2017-01-01

    Recent developments in Radiation Oncology treatment planning have led to the development of software packages that facilitate automated intensity-modulated radiation therapy (IMRT) and volumetric-modulated arc therapy (VMAT) planning. Such solutions include site-specific modules, plan library methods, and algorithm-based methods. In this study, the plan quality for prostate cancer generated by the Auto-Planning module of the Pinnacle 3 radiation therapy treatment planning system (v9.10, Fitchburg, WI) is retrospectively evaluated. The Auto-Planning module of Pinnacle 3 uses a progressive optimization algorithm. Twenty-three prostate cancer cases, which had previously been planned and treated without lymph node irradiation, were replanned using the Auto-Planning module. Dose distributions were statistically compared with those of manual planning by the paired t-test at 5% significance level. Auto-Planning was performed without any manual intervention. Planning target volume (PTV) dose and dose to rectum were comparable between Auto-Planning and manual planning. The former, however, significantly reduced the dose to the bladder and femurs. Regression analysis was performed to examine the correlation between volume overlap between bladder and PTV divided by the total bladder volume and resultant V70. The findings showed that manual planning typically exhibits a logistic way for dose constraint, whereas Auto-Planning shows a more linear tendency. By calculating the Akaike information criterion (AIC) to validate the statistical model, a reduction of interoperator variation in Auto-Planning was shown. We showed that, for prostate cancer, the Auto-Planning module provided plans that are better than or comparable with those of manual planning. By comparing our results with those previously reported for head and neck cancer treatment, we recommend the homogeneous plan quality generated by the Auto-Planning module, which exhibits less dependence on anatomic complexity

  7. MRI-based treatment planning for radiotherapy: Dosimetric verification for prostate IMRT

    International Nuclear Information System (INIS)

    Chen, Lili; Price, Robert A.; Wang Lu; Li Jinsheng; Qin Lihong; McNeeley, Shawn; Ma, C.-M. Charlie; Freedman, Gary M.; Pollack, Alan

    2004-01-01

    Purpose: Magnetic resonance (MR) and computed tomography (CT) image fusion with CT-based dose calculation is the gold standard for prostate treatment planning. MR and CT fusion with CT-based dose calculation has become a routine procedure for intensity-modulated radiation therapy (IMRT) treatment planning at Fox Chase Cancer Center. The use of MRI alone for treatment planning (or MRI simulation) will remove any errors associated with image fusion. Furthermore, it will reduce treatment cost by avoiding redundant CT scans and save patient, staff, and machine time. The purpose of this study is to investigate the dosimetric accuracy of MRI-based treatment planning for prostate IMRT. Methods and materials: A total of 30 IMRT plans for 15 patients were generated using both MRI and CT data. The MRI distortion was corrected using gradient distortion correction (GDC) software provided by the vendor (Philips Medical System, Cleveland, OH). The same internal contours were used for the paired plans. The external contours were drawn separately between CT-based and MR imaging-based plans to evaluate the effect of any residual distortions on dosimetric accuracy. The same energy, beam angles, dose constrains, and optimization parameters were used for dose calculations for each paired plans using a treatment optimization system. The resulting plans were compared in terms of isodose distributions and dose-volume histograms (DVHs). Hybrid phantom plans were generated for both the CT-based plans and the MR-based plans using the same leaf sequences and associated monitor units (MU). The physical phantom was then irradiated using the same leaf sequences to verify the dosimetry accuracy of the treatment plans. Results: Our results show that dose distributions between CT-based and MRI-based plans were equally acceptable based on our clinical criteria. The absolute dose agreement for the planning target volume was within 2% between CT-based and MR-based plans and 3% between measured dose

  8. Radiation treatment planning techniques for lymphoma of the stomach

    International Nuclear Information System (INIS)

    Della Biancia, Cesar; Hunt, Margie; Furhang, Eli; Wu, Elisa; Yahalom, Joachim

    2005-01-01

    Purpose: Involved-field radiation therapy of the stomach is often used in the curative treatment of gastric lymphoma. Yet, the optimal technique to irradiate the stomach with minimal morbidity has not been well established. This study was designed to evaluate treatment planning alternatives for stomach irradiation, including intensity-modulated radiation therapy (IMRT), to determine which approach resulted in improved dose distribution and to identify patient-specific anatomic factors that might influence a treatment planning choice. Methods and Materials: Fifteen patients with lymphoma of the stomach (14 mucosa-associated lymphoid tissue lymphomas and 1 diffuse large B-cell lymphoma) were categorized into 3 types, depending on the geometric relationship between the planning target volume (PTV) and kidneys. AP/PA and 3D conformal radiation therapy (3DCRT) plans were generated for each patient. IMRT was planned for 4 patients with challenging geometric relationship between the PTV and the kidneys to determine whether it was advantageous to use IMRT. Results: For type I patients (no overlap between PTV and kidneys), there was essentially no benefit from using 3DCRT over AP/PA. However, for patients with PTVs in close proximity to the kidneys (type II) or with high degree of overlap (type III), the 4-field 3DCRT plans were superior, reducing the kidney V 15Gy by approximately 90% for type II and 50% for type III patients. For type III, the use of a 3DCRT plan rather than an AP/PA plan decreased the V 15Gy by approximately 65% for the right kidney and 45% for the left kidney. In the selected cases, IMRT led to a further decrease in left kidney dose as well as in mean liver dose. Conclusions: The geometric relationship between the target and kidneys has a significant impact on the selection of the optimum beam arrangement. Using 4-field 3DCRT markedly decreases the kidney dose. The addition of IMRT led to further incremental improvements in the left kidney and liver

  9. Computer optimization of noncoplanar beam setups improves stereotactic treatment of liver tumors

    International Nuclear Information System (INIS)

    Pooter, Jacco A. de; Mendez Romero, Alejandra; Jansen, Wim; Storchi, Pascal; Woudstra, Evert; Levendag, Peter C.; Heijmen, Ben

    2006-01-01

    Purpose: To investigate whether computer-optimized fully noncoplanar beam setups may improve treatment plans for the stereotactic treatment of liver tumors. Methods: An algorithm for automated beam orientation and weight selection (Cycle) was extended for noncoplanar stereotactic treatments. For 8 liver patients previously treated in our clinic using a prescription isodose of 65%, Cycle was used to generate noncoplanar and coplanar plans with the highest achievable minimum planning target volume (PTV) dose for the clinically delivered isocenter and mean liver doses, while not violating the clinically applied hard planning constraints. The clinical and the optimized coplanar and noncoplanar plans were compared, with respect to D PTV,99% , the dose received by 99% of the PTV, the PTV generalized equivalent uniform dose (gEUD), and the compliance with the clinical constraints. Results: For each patient, the ratio between D PTV,99% and D isoc , and the gEUD -5 and gEUD -2 values of the optimized noncoplanar plan were higher than for the clinical plan with an average increase of respectively 18.8% (range, 7.8-24.0%), 6.4 Gy (range, 3.4-11.8 Gy), and 10.3 Gy (range, 6.7-12.5). D PTV,99% /D isoc , gEUD -5 , and gEUD -2 of the optimized noncoplanar plan was always higher than for the optimized coplanar plan with an average increase of, respectively, 4.5% (range, 0.2-9.7%), 2.7 Gy (range, 0.6-9.7 Gy), and 3.4 Gy (range, 0.6-9.9 Gy). All plans were within the imposed hard constraints. On average, the organs at risk were better spared with the optimized noncoplanar plan than with the optimized coplanar plan and the clinical plan. Conclusions: The use of automatically generated, fully noncoplanar beam setups results in plans that are favorable compared with coplanar techniques. Because of the automation, we found that the planning workload can be decreased from 1 to 2 days to 1 to 2 h

  10. 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.

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

    International Nuclear Information System (INIS)

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

    2013-01-01

    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

  12. 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.

  13. Incorporating model parameter uncertainty into inverse treatment planning

    International Nuclear Information System (INIS)

    Lian Jun; Xing Lei

    2004-01-01

    Radiobiological treatment planning depends not only on the accuracy of the models describing the dose-response relation of different tumors and normal tissues but also on the accuracy of tissue specific radiobiological parameters in these models. Whereas the general formalism remains the same, different sets of model parameters lead to different solutions and thus critically determine the final plan. Here we describe an inverse planning formalism with inclusion of model parameter uncertainties. This is made possible by using a statistical analysis-based frameset developed by our group. In this formalism, the uncertainties of model parameters, such as the parameter a that describes tissue-specific effect in the equivalent uniform dose (EUD) model, are expressed by probability density function and are included in the dose optimization process. We found that the final solution strongly depends on distribution functions of the model parameters. Considering that currently available models for computing biological effects of radiation are simplistic, and the clinical data used to derive the models are sparse and of questionable quality, the proposed technique provides us with an effective tool to minimize the effect caused by the uncertainties in a statistical sense. With the incorporation of the uncertainties, the technique has potential for us to maximally utilize the available radiobiology knowledge for better IMRT treatment

  14. Treatment planning systems dosimetry auditing project in Portugal.

    Science.gov (United States)

    Lopes, M C; Cavaco, A; Jacob, K; Madureira, L; Germano, S; Faustino, S; Lencart, J; Trindade, M; Vale, J; Batel, V; Sousa, M; Bernardo, A; Brás, S; Macedo, S; Pimparel, D; Ponte, F; Diaz, E; Martins, A; Pinheiro, A; Marques, F; Batista, C; Silva, L; Rodrigues, M; Carita, L; Gershkevitsh, E; Izewska, J

    2014-02-01

    The Medical Physics Division of the Portuguese Physics Society (DFM_SPF) in collaboration with the IAEA, carried out a national auditing project in radiotherapy, between September 2011 and April 2012. The objective of this audit was to ensure the optimal usage of treatment planning systems. The national results are presented in this paper. The audit methodology simulated all steps of external beam radiotherapy workflow, from image acquisition to treatment planning and dose delivery. A thorax CIRS phantom lend by IAEA was used in 8 planning test-cases for photon beams corresponding to 15 measuring points (33 point dose results, including individual fields in multi-field test cases and 5 sum results) in different phantom materials covering a set of typical clinical delivery techniques in 3D Conformal Radiotherapy. All 24 radiotherapy centers in Portugal have participated. 50 photon beams with energies 4-18 MV have been audited using 25 linear accelerators and 32 calculation algorithms. In general a very good consistency was observed for the same type of algorithm in all centres and for each beam quality. The overall results confirmed that the national status of TPS calculations and dose delivery for 3D conformal radiotherapy is generally acceptable with no major causes for concern. This project contributed to the strengthening of the cooperation between the centres and professionals, paving the way to further national collaborations. Copyright © 2013 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

  15. Hexone Storage and Treatment Facility closure plan

    International Nuclear Information System (INIS)

    1992-11-01

    The HSTF is a storage and treatment unit subject to the requirements for the storage and treatment of dangerous waste. Closure is being conducted under interim status and will be completed pursuant to the requirements of Washington State Department of Ecology (Ecology) Dangerous Waste Regulations, Washington Administrative Code (WAC) 173-303-610 and WAC 173-303-640. Because dangerous waste does not include the source, special nuclear, and by-product material components of mixed waste, radionuclides are not within the scope of WAC 173-303 or of this closure plan. The information on radionuclides is provided only for general knowledge where appropriate. The known hazardous/dangerous waste remaining at the site before commencing other closure activities consists of the still vessels, a tarry sludge in the storage tanks, and residual contamination in equipment, piping, filters, etc. The treatment and removal of waste at the HSTF are closure activities as defined in the Resource Conservation and Recovery Act (RCRA) of 1976 and WAC 173-303

  16. 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. Copyright © 2013 Elsevier Ltd. All rights reserved.

  17. Optimal planning in a developing industrial microgrid with sensitive loads

    Directory of Open Access Journals (Sweden)

    M. Naderi

    2017-11-01

    Full Text Available Computer numerical control (CNC machines are known as sensitive loads in industrial estates. These machines require reliable and qualified electricity in their often long work periods. Supplying these loads with distributed energy resources (DERs in a microgrid (MG can be done as an appropriate solution. The aim of this paper is to analyze the implementation potential of a real and developing MG in Shad-Abad industrial estate, Tehran, Iran. Three MG planning objectives are considered including assurance of sustainable and secure operation of CNC machines as sensitive loads, minimizing the costs of MG construction and operation, and using available capacities to penetrate the highest possible renewable energy sources (RESs which subsequently results in decreasing the air pollutants specially carbon dioxide (CO2. The HOMER (hybrid optimization model for electric renewable software is used to specify the technical feasibility of MG planning and to select the best plan economically and environmentally. Different scenarios are considered in this regard to determine suitable capacity of production participants, and to assess the MG indices such as the reliability.

  18. Optimal Investment Planning of Bulk Energy Storage Systems

    Directory of Open Access Journals (Sweden)

    Dina Khastieva

    2018-02-01

    Full Text Available Many countries have the ambition to increase the share of renewable sources in electricity generation. However, continuously varying renewable sources, such as wind power or solar energy, require that the power system can manage the variability and uncertainty of the power generation. One solution to increase flexibility of the system is to use various forms of energy storage, which can provide flexibility to the system at different time ranges and smooth the effect of variability of the renewable generation. In this paper, we investigate three questions connected to investment planning of energy storage systems. First, how the existing flexibility in the system will affect the need for energy storage investments. Second, how presence of energy storage will affect renewable generation expansion and affect electricity prices. Third, who should be responsible for energy storage investments planning. This paper proposes to assess these questions through two different mathematical models. The first model is designed for centralized investment planning and the second model deals with a decentralized investment approach where a single independent profit maximizing utility is responsible for energy storage investments. The models have been applied in various case studies with different generation mixes and flexibility levels. The results show that energy storage system is beneficial for power system operation. However, additional regulation should be considered to achieve optimal investment and allocation of energy storage.

  19. Treatment planning of electroporation-based medical interventions: electrochemotherapy, gene electrotransfer and irreversible electroporation

    International Nuclear Information System (INIS)

    Zupanic, Anze; Kos, Bor; Miklavcic, Damijan

    2012-01-01

    In recent years, cancer electrochemotherapy (ECT), gene electrotransfer for gene therapy and DNA vaccination (GET) and tissue ablation with irreversible electroporation (IRE) have all entered clinical practice. We present a method for a personalized treatment planning procedure for ECT, GET and IRE, based on medical image analysis, numerical modelling of electroporation and optimization with the genetic algorithm, and several visualization tools for treatment plan assessment. Each treatment plan provides the attending physician with optimal positions of electrodes in the body and electric pulse parameters for optimal electroporation of the target tissues. For the studied case of a deep-seated tumour, the optimal treatment plans for ECT and IRE require at least two electrodes to be inserted into the target tissue, thus lowering the necessary voltage for electroporation and limiting damage to the surrounding healthy tissue. In GET, it is necessary to place the electrodes outside the target tissue to prevent damage to target cells intended to express the transfected genes. The presented treatment planning procedure is a valuable tool for clinical and experimental use and evaluation of electroporation-based treatments. (paper)

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

    Science.gov (United States)

    Herrera, M S; González, S J; Burlon, A A; Minsky, D M; Kreiner, A J

    2011-12-01

    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. Copyright © 2011 Elsevier Ltd. All rights reserved.

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

    International Nuclear Information System (INIS)

    Herrera, M.S.; González, S.J.; Burlon, A.A.; Minsky, D.M.; Kreiner, A.J.

    2011-01-01

    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.

  2. Radiation treatment planning using a microcomputer

    International Nuclear Information System (INIS)

    Lunsqui, A.R.; Calil, S.J.; Rocha, J.R.O.; Alexandre, A.C.

    1990-01-01

    The radiation treatment planning requires a lenght manipulation of data from isodose charts to obtain the best irradiation technique. Over the past 25 years this tedious operation has been replaced by computerized methods. These can reduce the working time by at least 20 times. It is being developed at the Biomedical Engineering Center a software to generate a polychromatic image of dose distribution. By means of a digitizing board, the patient contour and the beam data are transfered to the computer and stored as polinomial and Fourier series respectively. To calculate the dose distribution, the irradiated region is represented by a variable size bidimensional dot matrix. The dose at each point is calculated by correcting and adding the stored data for each beam. An algorithm for color definition according to the dose intensity was developed to display on a computer monitor the resultant matrix. A hard copy can be obtained be means of a six color plotter. (author)

  3. Direct aperture optimization as a means of reducing the complexity of intensity modulated radiation therapy plans

    International Nuclear Information System (INIS)

    Broderick, Maria; Leech, Michelle; Coffey, Mary

    2009-01-01

    Intensity Modulated Radiation Therapy (IMRT) is a means of delivering radiation therapy where the intensity of the beam is varied within the treatment field. This is done by dividing a large beam into many small beamlets. Dose constraints are assigned to both the target and sensitive structures and computerised inverse optimization is performed to find the individual weights of this large number of beamlets. The computer adjusts the intensities of these beamlets according to the required planning dose objectives. The optimized intensity patterns are then decomposed into a series of deliverable multi leaf collimator (MLC) shapes in the sequencing step. One of the main problems of IMRT, which becomes even more apparent as the complexity of the IMRT plan increases, is the dramatic increase in the number of Monitor Units (MU) required to deliver a fractionated treatment. The difficulty with this increase in MU is its association with increased treatment times and a greater leakage of radiation from the MLCs increasing the total body dose and the risk of secondary cancers in patients. Therefore one attempts to find ways of reducing these MU without compromising plan quality. The design of inverse planning systems where the beam is divided into small beamlets to produce the required intensity map automatically introduces complexity into IMRT treatment planning. Plan complexity is associated with many negative factors such as dosimetric uncertainty and delivery issues A large search space is required necessitating much computing power. However, the limitations of the delivery technology are not taken into consideration when designing the ideal intensity map therefore a further step termed the sequencing step is required to convert the ideal intensity map into a deliverable one. Many approaches have been taken to reduce the complexity. These include setting intensity limits, putting penalties on the cost function and using smoothing filters Direct Aperture optimization

  4. Direct aperture optimization as a means of reducing the complexity of intensity modulated radiation therapy plans

    Directory of Open Access Journals (Sweden)

    Coffey Mary

    2009-02-01

    Full Text Available Abstract Intensity Modulated Radiation Therapy (IMRT is a means of delivering radiation therapy where the intensity of the beam is varied within the treatment field. This is done by dividing a large beam into many small beamlets. Dose constraints are assigned to both the target and sensitive structures and computerised inverse optimization is performed to find the individual weights of this large number of beamlets. The computer adjusts the intensities of these beamlets according to the required planning dose objectives. The optimized intensity patterns are then decomposed into a series of deliverable multi leaf collimator (MLC shapes in the sequencing step. One of the main problems of IMRT, which becomes even more apparent as the complexity of the IMRT plan increases, is the dramatic increase in the number of Monitor Units (MU required to deliver a fractionated treatment. The difficulty with this increase in MU is its association with increased treatment times and a greater leakage of radiation from the MLCs increasing the total body dose and the risk of secondary cancers in patients. Therefore one attempts to find ways of reducing these MU without compromising plan quality. The design of inverse planning systems where the beam is divided into small beamlets to produce the required intensity map automatically introduces complexity into IMRT treatment planning. Plan complexity is associated with many negative factors such as dosimetric uncertainty and delivery issues A large search space is required necessitating much computing power. However, the limitations of the delivery technology are not taken into consideration when designing the ideal intensity map therefore a further step termed the sequencing step is required to convert the ideal intensity map into a deliverable one. Many approaches have been taken to reduce the complexity. These include setting intensity limits, putting penalties on the cost function and using smoothing filters Direct

  5. Direct aperture optimization as a means of reducing the complexity of intensity modulated radiation therapy plans

    Energy Technology Data Exchange (ETDEWEB)

    Broderick, Maria; Leech, Michelle; Coffey, Mary [Division of Radiation Therapy, School of Medicine, Trinity College Dublin, Dublin, Ireland (United Kingdom)

    2009-02-16

    Intensity Modulated Radiation Therapy (IMRT) is a means of delivering radiation therapy where the intensity of the beam is varied within the treatment field. This is done by dividing a large beam into many small beamlets. Dose constraints are assigned to both the target and sensitive structures and computerised inverse optimization is performed to find the individual weights of this large number of beamlets. The computer adjusts the intensities of these beamlets according to the required planning dose objectives. The optimized intensity patterns are then decomposed into a series of deliverable multi leaf collimator (MLC) shapes in the sequencing step. One of the main problems of IMRT, which becomes even more apparent as the complexity of the IMRT plan increases, is the dramatic increase in the number of Monitor Units (MU) required to deliver a fractionated treatment. The difficulty with this increase in MU is its association with increased treatment times and a greater leakage of radiation from the MLCs increasing the total body dose and the risk of secondary cancers in patients. Therefore one attempts to find ways of reducing these MU without compromising plan quality. The design of inverse planning systems where the beam is divided into small beamlets to produce the required intensity map automatically introduces complexity into IMRT treatment planning. Plan complexity is associated with many negative factors such as dosimetric uncertainty and delivery issues A large search space is required necessitating much computing power. However, the limitations of the delivery technology are not taken into consideration when designing the ideal intensity map therefore a further step termed the sequencing step is required to convert the ideal intensity map into a deliverable one. Many approaches have been taken to reduce the complexity. These include setting intensity limits, putting penalties on the cost function and using smoothing filters Direct Aperture optimization

  6. Monte Carlo treatment planning with modulated electron radiotherapy: framework development and application

    Science.gov (United States)

    Alexander, Andrew William

    Within the field of medical physics, Monte Carlo radiation transport simulations are considered to be the most accurate method for the determination of dose distributions in patients. The McGill Monte Carlo treatment planning system (MMCTP), provides a flexible software environment to integrate Monte Carlo simulations with current and new treatment modalities. A developing treatment modality called energy and intensity modulated electron radiotherapy (MERT) is a promising modality, which has the fundamental capabilities to enhance the dosimetry of superficial targets. An objective of this work is to advance the research and development of MERT with the end goal of clinical use. To this end, we present the MMCTP system with an integrated toolkit for MERT planning and delivery of MERT fields. Delivery is achieved using an automated "few leaf electron collimator" (FLEC) and a controller. Aside from the MERT planning toolkit, the MMCTP system required numerous add-ons to perform the complex task of large-scale autonomous Monte Carlo simulations. The first was a DICOM import filter, followed by the implementation of DOSXYZnrc as a dose calculation engine and by logic methods for submitting and updating the status of Monte Carlo simulations. Within this work we validated the MMCTP system with a head and neck Monte Carlo recalculation study performed by a medical dosimetrist. The impact of MMCTP lies in the fact that it allows for systematic and platform independent large-scale Monte Carlo dose calculations for different treatment sites and treatment modalities. In addition to the MERT planning tools, various optimization algorithms were created external to MMCTP. The algorithms produced MERT treatment plans based on dose volume constraints that employ Monte Carlo pre-generated patient-specific kernels. The Monte Carlo kernels are generated from patient-specific Monte Carlo dose distributions within MMCTP. The structure of the MERT planning toolkit software and

  7. 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...

  8. Federal Facilities Compliance Act, Draft Site Treatment Plan: Compliance Plan Volume. Part 2, Volume 2

    International Nuclear Information System (INIS)

    1994-01-01

    This document presents the details of the implementation of the Site Treatment Plan developed by Ames Laboratory in compliance with the Federal Facilities Compliance Act. Topics discussed in this document include: implementation of the plan; milestones; annual updates to the plan; inclusion of new waste streams; modifications of the plan; funding considerations; low-level mixed waste treatment plan and schedules; and TRU mixed waste streams

  9. Improved Beam Angle Arrangement in Intensity Modulated Proton Therapy Treatment Planning for Localized Prostate Cancer

    International Nuclear Information System (INIS)

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

    2015-01-01

    Purpose: This study investigates potential gains of an improved beam angle arrangement compared to a conventional fixed gantry setup in intensity modulated proton therapy (IMPT) treatment for localized prostate cancer patients based on a proof of principle study. Materials and Methods: Three patients with localized prostate cancer retrospectively selected from our institution were studied. For each patient, IMPT plans were designed using two, three and four beam angles, respectively, obtained from a beam angle optimization algorithm. Those plans were then compared with ones using two lateral parallel-opposed beams according to the conventional planning protocol for localized prostate cancer adopted at our institution. Results: IMPT plans with two optimized angles achieved significant improvements in rectum sparing and moderate improvements in bladder sparing against those with two lateral angles. Plans with three optimized angles further improved rectum sparing significantly over those two-angle plans, whereas four-angle plans found no advantage over three-angle plans. A possible three-beam class solution for localized prostate patients was suggested and demonstrated with preserved dosimetric benefits because individually optimized three-angle solutions were found sharing a very similar pattern. Conclusions: This study has demonstrated the potential of using an improved beam angle arrangement to better exploit the theoretical dosimetric benefits of proton therapy and provided insights of selecting quality beam angles for localized prostate cancer treatment

  10. SU-E-T-337: Treatment Planning Study of Craniospinal Irradiation with Spot Scanning Proton Therapy

    International Nuclear Information System (INIS)

    Tasson, A; Beltran, C; Laack, N; Childs, S; Tryggestad, E; Whitaker, T

    2014-01-01

    Purpose: To develop a treatment planning technique that achieves optimal robustness against systematic position and range uncertainties, and interfield position errors for craniospinal irradiation (CSI) using spot scanning proton radiotherapy. Methods: Eighteen CSI patients who had previously been treated using photon radiation were used for this study. Eight patients were less than 10 years old. The prescription dose was 23.4Gy in 1.8Gy fractions. Two different field arrangement types were investigated: 1 posterior field per isocenter and 2 posterior oblique fields per isocenter. For each field type, two delivery configurations were used: 5cm bolus attached to the treatment table and a 4.5cm range shifter located inside the nozzle. The target for each plan was the whole brain and thecal sac. For children under the age of 10, all plan types were repeated with an additional dose of 21Gy prescribed to the vertebral bodies. Treatment fields were matched by stepping down the dose in 10% increments over 9cm. Robustness against 3% and 3mm uncertainties, as well as a 3mm inter-field error was analyzed. Dose coverage of the target and critical structure sparing for each plan type will be considered. Ease of planning and treatment delivery was also considered for each plan type. Results: The mean dose volume histograms show that the bolus plan with posterior beams gave the best overall plan, and all proton plans were comparable to or better than the photon plans. The plan type that was the most robust against the imposed uncertainties was also the bolus plan with posterior beams. This is also the plan configuration that is the easiest to deliver and plan. Conclusion: The bolus plan with posterior beams achieved optimal robustness against systematic position and range uncertainties, as well as inter-field position errors

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

    International Nuclear Information System (INIS)

    Klippel, Norbert; Schmuecking, Michael; Terribilini, Dario; Geretschlaeger, Andreas; Aebersold, Daniel M.; Manser, Peter

    2015-01-01

    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 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 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 with better

  12. Radiation therapy tolerance doses for treatment planning

    International Nuclear Information System (INIS)

    Lyman, J.T.

    1987-01-01

    To adequately plan acceptable dose distributions for radiation therapy treatments it is necessary to ensure that normal structures do not receive unacceptable doses. Acceptable doses are generally those that are below a stated tolerance dose for development of some level of complication. To support the work sponsored by the National Cancer Institute, data for the tolerance of normal tissues or organs to low-LET radiation has been compiled from a number of sources. These tolerance dose data are ostensibly for uniform irradiation of all or part of an organ, and are for either 5% (TD 5 ) or 50% (TD 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 represent 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 end point. 20 refs., 1 fig., 1 tab

  13. 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.

  14. [Virtual Planning of Prosthetic Treatment of the Orbit].

    Science.gov (United States)

    Veit, Johannes A; Thierauf, Julia; Egner, Kornelius; Wiggenhauser, Paul Severin; Friedrich, Daniel; Greve, Jens; Schuler, Patrick J; Hoffmann, Thomas K; Schramm, Alexander

    2017-06-01

    Optimal positioning of bone-anchored implants in the treatment of patients with orbital prosthesis is challenging. The definition of implant axis as well as the positioning of the implants is important to prevent failures in prosthetic rehabilitation in these patients. We performed virtual planning of enossal implants at a base of a standard fan beam CT scan using the software CoDiagnostiX™ (DentalWings, Montréal, Canada). By 3D-printing a surgical guide for drilling and implant insertion was manufactured (Med-610™, Stratasys, Rehovot, Israel). An orbital exenteration was performed in a patient after shrinkage of the eyelids 20 years after enucleation and radiation of the orbit due to rhabdomyosarcoma. 4 Vistafix-3 implants (Cochlear™, Cochlea, Centennial, USA) were primarily inserted after resection with the help of the 3D-surgical guide. Prosthetic rehabilitation could be achieved as preplanned to a predictable result. The individual prosthesis of the orbit showed good functional and esthetic outcome. The virtual 3D-planning of endosseous implants for prosthetic orbital and periorbital reconstruction is easy to use and facilitates optimal placement of implants especially in posttherapeutically altered anatomic situations. © Georg Thieme Verlag KG Stuttgart · New York.

  15. Generation Expansion Planning as Particle Swarm Optimization with Gridified SATyrus

    International Nuclear Information System (INIS)

    Diacovo, R.; Franca, F. M. G.; Lima, P. M. V.

    2007-01-01

    This work introduces our first attempt on using the Grid to solve a real-life problem with the SATyrus platform. In electrical engineering, a challenging task is to find the less expensive ways to expand the energy production capacity, supporting an increasing demand. This is the definition of the generation expansion planning problem (GEP). We decided to investigate the Particle Swarm Optimization (PSO) paradigm for this task, due to its efficiency and arbitrary memory requirements, the last one being a desirable characteristic for any solver running on a Grid environment. The PSO was used in conjunction with the SATyrus platform, which stands for an energy function synthesizer. We hope the results presented here will help to evolve SATyrus into a reliable generic problem solver. (Author)

  16. Radiotherapy Treatment Planning for Testicular Seminoma

    International Nuclear Information System (INIS)

    Wilder, Richard B.; Buyyounouski, Mark K.; Efstathiou, Jason A.; Beard, Clair J.

    2012-01-01

    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 × 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).

  17. 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).

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

    International Nuclear Information System (INIS)

    Barragán, A. M.; Differding, S.; Lee, J. A.; Sterpin, E.; Janssens, G.

    2015-01-01

    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 PET ) was calculated from 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 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 PET (worst case) were above 5% of DPBN

  19. 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

  20. Realizing a new paradigm in radiation therapy treatment planning

    International Nuclear Information System (INIS)

    Ziegenhein, Peter

    2013-01-01

    This thesis investigates the feasibility of a new IMRT planning paradigm called Interactive Dose Shaping (IDS). The IDS paradigm enables the therapist to directly impose local dose features into the therapy plan. In contrast to the conventional IMRT planning approach, IDS does not employ an objective function to drive an iterative optimization procedure. In the first part of this work, the conventional IMRT plan optimization method is investigated. Concepts for a near-optimal implementation of the planning problem are provided. The second part of this work introduces the IDS concept. It is designed to overcome clinical drawbacks of the conventional method on the one hand and to provide interactive planning strategies which exploit the full potential of modern high-performance computer hardware on the other hand. The realization of the IDS concept consists of three main parts. (1)A two-step Dose Variation and Recovery (DVR) strategy which imposes localized plan features and recovers for unintentional plan modifications elsewhere. (2)A new dose calculation method (3)The design of an IDS planning framework which provides a powerful graphical user interface. It could be shown that the IDS paradigm is able to reproduce conventionally optimized therapy plans and that the IDS concepts can be realized in real-time.

  1. Effect of MLC leaf width on the planning and delivery of SMLC IMRT using the CORVUS inverse treatment planning system

    International Nuclear Information System (INIS)

    Burmeister, Jay; McDermott, Patrick N.; Bossenberger, Todd; Ben-Josef, Edgar; Levin, Kenneth; Forman, Jeffrey D.

    2004-01-01

    This study investigates the influence of multileaf collimator (MLC) leaf width on intensity modulated radiation therapy (IMRT) plans delivered via the segmented multileaf collimator (SMLC) technique. IMRT plans were calculated using the Corvus treatment planning system for three brain, three prostate, and three pancreas cases using leaf widths of 0.5 and 1 cm. Resulting differences in plan quality and complexity are presented here. Plans calculated using a 1 cm leaf width were chosen over the 0.5 cm leaf width plans in seven out of nine cases based on clinical judgment. Conversely, optimization results revealed a superior objective function result for the 0.5 cm leaf width plans in seven out of the nine comparisons. The 1 cm leaf width objective function result was superior only for very large target volumes, indicating that expanding the solution space for plan optimization by using narrower leaves may result in a decreased probability of finding the global minimum. In the remaining cases, we can conclude that we are often not utilizing the objective function as proficiently as possible to meet our clinical goals. There was often no apparent clinically significant difference between the two plans, and in such cases the issue becomes one of plan complexity. A comparison of plan complexity revealed that the average 1 cm leaf width plan required roughly 60% fewer segments and over 40% fewer monitor units than required by 0.5 cm leaf width plans. This allows a significant decrease in whole body dose and total treatment time. For very complex IMRT plans, the treatment delivery time may affect the biologically effective dose. A clinically significant improvement in plan quality from using narrower leaves was evident only in cases with very small target volumes or those with concavities that are small with respect to the MLC leaf width. For the remaining cases investigated in this study, there was no clinical advantage to reducing the MLC leaf width from 1 to 0.5 cm. In

  2. A clinical distance measure for evaluating treatment plan quality difference with Pareto fronts in radiotherapy

    Directory of Open Access Journals (Sweden)

    Kristoffer Petersson

    2017-07-01

    Full Text Available We present a clinical distance measure for Pareto front evaluation studies in radiotherapy, which we show strongly correlates (r = 0.74 and 0.90 with clinical plan quality evaluation. For five prostate cases, sub-optimal treatment plans located at a clinical distance value of >0.32 (0.28–0.35 from fronts of Pareto optimal plans, were assessed to be of lower plan quality by our (12 observers (p < .05. In conclusion, the clinical distance measure can be used to determine if the difference between a front and a given plan (or between different fronts corresponds to a clinically significant plan quality difference.

  3. 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...

  4. Optimal inspection planning for onshore pipelines subject to external corrosion

    International Nuclear Information System (INIS)

    Gomes, Wellison J.S.; Beck, André T.; Haukaas, Terje

    2013-01-01

    Continuous operation of pipeline systems involves significant expenditures in inspection and maintenance activities. The cost-effective safety management of such systems involves allocating the optimal amount of resources to inspection and maintenance activities, in order to control risks (expected costs of failure). In this context, this article addresses the optimal inspection planning for onshore pipelines subject to external corrosion. The investigation addresses a challenging problem of practical relevance, and strives for using the best available models to describe random corrosion growth and the relevant limit state functions. A single pipeline segment is considered in this paper. Expected numbers of failures and repairs are evaluated by Monte Carlo sampling, and a novel procedure is employed to evaluate sensitivities of the objective function with respect to design parameters. This procedure is shown to be accurate and more efficient than finite differences. The optimum inspection interval is found for an example problem, and the robustness of this optimum to the assumed inspection and failure costs is investigated. It is shown that optimum total expected costs found herein are not highly sensitive to the assumed costs of inspection and failure. -- Highlights: • Inspection, repair and failure costs of pipeline systems considered. • Optimum inspection schedule (OIS) obtained by minimizing total expected life-cycle costs. • Robustness of OIS evaluated w.r.t. estimated costs of inspection and failure. • Accurate non-conservative models of corrosion growth employed

  5. Linear programming based on neural networks for radiotherapy treatment planning

    International Nuclear Information System (INIS)

    Xingen Wu; Limin Luo

    2000-01-01

    In this paper, we propose a neural network model for linear programming that is designed to optimize radiotherapy treatment planning (RTP). This kind of neural network can be easily implemented by using a kind of 'neural' electronic system in order to obtain an optimization solution in real time. We first give an introduction to the RTP problem and construct a non-constraint objective function for the neural network model. We adopt a gradient algorithm to minimize the objective function and design the structure of the neural network for RTP. Compared to traditional linear programming methods, this neural network model can reduce the time needed for convergence, the size of problems (i.e., the number of variables to be searched) and the number of extra slack and surplus variables needed. We obtained a set of optimized beam weights that result in a better dose distribution as compared to that obtained using the simplex algorithm under the same initial condition. The example presented in this paper shows that this model is feasible in three-dimensional RTP. (author)

  6. 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.

  7. Radiation Planning Assistant - A Streamlined, Fully Automated Radiotherapy Treatment Planning System

    Science.gov (United States)

    Court, Laurence E.; Kisling, Kelly; McCarroll, Rachel; Zhang, Lifei; Yang, Jinzhong; Simonds, Hannah; du Toit, Monique; Trauernicht, Chris; Burger, Hester; Parkes, Jeannette; Mejia, Mike; Bojador, Maureen; Balter, Peter; Branco, Daniela; Steinmann, Angela; Baltz, Garrett; Gay, Skylar; Anderson, Brian; Cardenas, Carlos; Jhingran, Anuja; Shaitelman, Simona; Bogler, Oliver; Schmeller, Kathleen; Followill, David; Howell, Rebecca; Nelson, Christopher; Peterson, Christine; Beadle, Beth

    2018-01-01

    The Radiation Planning Assistant (RPA) is a system developed for the fully automated creation of radiotherapy treatment plans, including volume-modulated arc therapy (VMAT) plans for patients with head/neck cancer and 4-field box plans for patients with cervical cancer. It is a combination of specially developed in-house software that uses an application programming interface to communicate with a commercial radiotherapy treatment planning system. It also interfaces with a commercial secondary dose verification software. The necessary inputs to the system are a Treatment Plan Order, approved by the radiation oncologist, and a simulation computed tomography (CT) image, approved by the radiographer. The RPA then generates a complete radiotherapy treatment plan. For the cervical cancer treatment plans, no additional user intervention is necessary until the plan is complete. For head/neck treatment plans, after the normal tissue and some of the target structures are automatically delineated on the CT image, the radiation oncologist must review the contours, making edits if necessary. They also delineate the gross tumor volume. The RPA then completes the treatment planning process, creating a VMAT plan. Finally, the completed plan must be reviewed by qualified clinical staff. PMID:29708544

  8. Genetic algorithm optimization for dynamic construction site layout planning

    Directory of Open Access Journals (Sweden)

    Farmakis Panagiotis M.

    2018-02-01

    Full Text Available The dynamic construction site layout planning (DCSLP problem refers to the efficient placement and relocation of temporary construction facilities within a dynamically changing construction site environment considering the characteristics of facilities and work interrelationships, the shape and topography of the construction site, and the time-varying project needs. A multi-objective dynamic optimization model is developed for this problem that considers construction and relocation costs of facilities, transportation costs of resources moving from one facility to another or to workplaces, as well as s