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Beam Angle

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David Craft – One of the best experts on this subject based on the ideXlab platform.

  • effective heuristics for Beam Angle optimization in radiation therapy
    Simulation, 2018
    Co-Authors: Hamed Yarmand, David Craft

    Abstract:

    In radiation therapy, the main challenge is to deliver the dose to the tumor while sparing healthy tissues around the tumor. One important decision to make is the Beam configuration. The corresponding mathematical problem, known as Beam Angle optimization (BAO), is a large-scale problem. We propose three novel heuristic approaches to reduce the computation time and find high-quality treatment plans for BAO. The first heuristic is based on the fact that the Beams that are geometrically close to each other (i.e., ‘adjacent’ Beams) have similar impacts, and hence are less likely to be used in the optimal configuration simultaneously. Therefore, in this heuristic, referred to as ‘neighbor cuts’, their use is limited. The second heuristic is to eliminate the Beams with small contribution to dose delivery in the ideal plan when all candidate Beams can be used. Finally, the number of Beams is reduced in the third heuristic while ensuring the quality of the plan remains within a pre-specified range. These heurist…

  • A hybrid approach to Beam Angle optimization in intensity-modulated radiation therapy
    Computers & Operations Research, 2013
    Co-Authors: Dimitris Bertsimas, David Craft, Valentina Cacchiani, Omid Nohadani

    Abstract:

    Intensity-Modulated Radiation Therapy is the technique of delivering radiation to cancer patients by using non-uniform radiation fields from selected Angles, with the aim of reducing the intensity of the Beams that go through critical structures while reaching the dose prescription in the target volume. Two decisions are of fundamental importance: to select the Beam Angles and to compute the intensity of the Beams used to deliver the radiation to the patient. Often, these two decisions are made separately: first, the treatment planners, on the basis of experience and intuition, decide the orientation of the Beams and then the intensities of the Beams are optimized by using an automated software tool. Automatic Beam Angle selection (also known as Beam Angle Optimization) is an important problem and is today often based on human experience. In this context, we face the problem of optimizing both the decisions, developing an algorithm which automatically selects the Beam Angles and computes the Beam intensities. We propose a hybrid heuristic method, which combines a simulated annealing procedure with the knowledge of the gradient. Gradient information is used to quickly find a local minimum, while simulated annealing allows to search for global minima. As an integral part of this procedure, the Beam intensities are optimized by solving a Linear Programming model. The proposed method presents a main difference from previous works: it does not require to have on input a set of candidate Beam Angles. Indeed, it dynamically explores Angles and the only discretization that is necessary is due to the maximum accuracy that can be achieved by the linear accelerator machine. Experimental results are performed on phantom and real-life case studies, showing the advantages that come from our approach.

  • mo a 137 03 effective heuristic cuts for Beam Angle optimization in radiation therapy
    Medical Physics, 2013
    Co-Authors: Hamed Yarmand, David Craft

    Abstract:

    Purpose: To improve the solution efficiency (i.e., reducing computation time while obtaining high‐quality treatment plans) for the Beam Angle optimization problem (BAO) in radiation therapy treatment planning. Methods: We formulate BAO as a mixed integer programming problem (MIP) whose solution gives the optimal Beam orientation as well as optimal Beam intensity map. We then incorporate a family of heuristic cuts into the resultant MIP based on the observation that the number of candidate Beams is usually much larger than the number of Beams used in the treatment plan, and therefore, it is less likely that adjacent Beams are simultaneously used in the optimal treatment plan. The proposed cuts, referred to as ((neighbor cuts)), force the optimization system to choose one or a few Beams from any set of adjacent Beams. As a Result, the search space and the computation time are reduced considerably. The neighbor cuts can be added to any MIP formulation for BAO including the cases of coplanar/noncoplanar Beams for intensity modulated radiation therapy (IMRT) and stereotactic body radiation therapy (SBRT). For the numerical experiments a liver case (both IMRT and SBRT) with 34 and a head and neck case (only IMRT) with 36 coplanar Beams were considered. Each Beam was divided into 109‐144 Beamlets of size 1*1 cm2. Results: We first solved the corresponding MIP without the neighbor cuts and recorded the optimal solution and the computation time. Then we incorporated the neighbor cuts into the MIP and resolved it. Our results show that incorporating the neighbor cuts into the MIP reduces the computation time considerably and results in solutions with negligible optimality gaps. Conclusion: This research incorporates the observation that optimal Beam configurations are typically a sparse set of well‐spaced Beams to improve the efficiency of the solution technique drastically. The project was supported by the Federal Share of program income earned by Massachusetts General Hospital on C06 CA059267, Proton Therapy Research and Treatment Center and also partially by RaySearch laboratories.

Radhe Mohan – One of the best experts on this subject based on the ideXlab platform.

  • iterative solution methods for Beam Angle and fluence map optimization in intensity modulated radiation therapy planning
    OR Spectrum, 2008
    Co-Authors: Jaewon Choi, Radhe Mohan

    Abstract:

    We present computational approaches for optimizing Beam Angles and fluence maps in Intensity Modulated Radiation Therapy (IMRT) planning. We assume that the number of Angles to be used for the treatment is given by the treatment planner. A mixed integer programming (MIP) model and a linear programming (LP) model are used to find an optimal set of Beam Angles and their corresponding fluence maps. The MIP model is solved using the branch-and-bound method while the LP model is solved using the interior point method. In order to reduce the computational burden for solving the optimization models, we introduce iterative Beam Angle elimination algorithms in which an insignificant Beam Angle is eliminated in each iteration. Other techniques are also explored including feasible set reduction for LP and data reduction. Experiments are made to show the computational advantage of the iterative methods for optimizing Angles using real patient cases.

  • Iterative solution methods for Beam Angle and fluence map optimization in intensity modulated radiation therapy planning
    OR Spectrum, 2007
    Co-Authors: Gino J. Lim, Jaewon Choi, Radhe Mohan

    Abstract:

    We present computational approaches for optimizing Beam Angles and fluence maps in Intensity Modulated Radiation Therapy (IMRT) planning. We assume that the number of Angles to be used for the treatment is given by the treatment planner. A mixed integer programming (MIP) model and a linear programming (LP) model are used to find an optimal set of Beam Angles and their corresponding fluence maps. The MIP model is solved using the branch-and-bound method while the LP model is solved using the interior point method. In order to reduce the computational burden for solving the optimization models, we introduce iterative Beam Angle elimination algorithms in which an insignificant Beam Angle is eliminated in each iteration. Other techniques are also explored including feasible set reduction for LP and data reduction. Experiments are made to show the computational advantage of the iterative methods for optimizing Angles using real patient cases.

  • Beam Angle optimization and reduction for intensity-modulated radiation therapy of non–small-cell lung cancers
    International Journal of Radiation Oncology Biology Physics, 2006
    Co-Authors: H. Helen Liu, Xiaochun Wang, Xiaodong Zhang, Lei Dong, Maria Jauregui, Radhe Mohan

    Abstract:

    Purpose: To optimize Beam Angles and reduce the number of Beams used for intensity-modulated radiation therapy (IMRT) of non–small-cell lung cancer (NSCLC). Methods and Materials: An exhaustive search scheme was used to perform Beam Angle optimization (BAO) for IMRT of NSCLC. This approach involved intercomparison of all possible Beam Angle combinations and selection of the best Angles based on the scores or costs of the objective functions used in the treatment plan optimization. Ten Stage III NSCLC cases were selected to evaluate the BAO algorithm and dosimetry benefits of IMRT-BAO. IMRT plans using five or seven coplanar Beams were optimized and compared with those using nine equal-spaced Beams. Results of BAO were also compared between plans using different numbers of Beams with or without fluence modulation. Results: Each anatomic structure, e.g., tumor or lung, had its own preferred Beam Angles. Thus, BAO required appropriate balance of competing objective functions. Plans using fewer Angles (five or seven Beams) could achieve plan quality similar to those using nine equal-spaced Beams, however with reduced monitor units and field segments. The number of Beams used for the treatment (five vs. seven) and the fluence modulation (open or IMRT Beams) did not have a significant impact on the results of the BAO. Conclusions: Use of fewer Beams (e.g., five) for lung IMRT could result in acceptable plan quality but improved treatment efficiency. A multiresolution search scheme could be developed for BAO using fewer and nonmodulated Beams to reduce the computation cost of BAO.

Ben J.m. Heijmen – One of the best experts on this subject based on the ideXlab platform.

  • Noncoplanar Beam Angle Class Solutions to Replace Time-Consuming Patient-Specific Beam Angle Optimization in Robotic Prostate Stereotactic Body Radiation Therapy.
    International Journal of Radiation Oncology Biology Physics, 2015
    Co-Authors: L. Rossi, Sebastiaan Breedveld, Shafak Aluwini, Ben J.m. Heijmen

    Abstract:

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

  • icycle integrated multicriterial Beam Angle and profile optimization for generation of coplanar and noncoplanar imrt plans
    Medical Physics, 2012
    Co-Authors: S Breedveld, Pascal R.m. Storchi, P Voet, Ben J.m. Heijmen

    Abstract:

    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 calledwish-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 liver patient treated with SBRT. Plans generated with Beam Angle optimization did better meet the clinical goals than equiangular or manually selected configurations. For the maxillary sinus and liver cases, significant improvements for noncoplanar setups were seen. The cervix case showed that also in IMRT with coplanar setups, Beam Angle optimization with iCycle may improve plan quality. Computation times for coplanar plans were around 1–2 h and for noncoplanar plans 4–7 h, depending on the number of Beams and the complexity of the site.

    Conclusions:
    Integrated Beam Angle and profile optimization with iCycle may result in significant improvements in treatment plan quality. Due to automation, the plan generation workload is minimal. Clinical application has started.

  • Multi-criteria Beam Angle IMRT optimization with iCycle
    , 2009
    Co-Authors: Sebastiaan Breedveld, Pascal R.m. Storchi, Ben J.m. Heijmen

    Abstract:

    An essential ingredient for making a good treatment plan for radiation therapy treatment is the selection of suitable Beam Angles. A sub-optimal Beam Angle configuration limits the possibilities of optimization. However, just as with normal IMRT optimization, the trade-offs between the PTV and OARs are not clear a priori. The introduction of multi-criteria optimization offered an intuitive planning approach.