Pattern search methods framework for beam angle optimization in radiotherapy design

Rocha, Humberto; Dias, Joana; Ferreira, B.; Lopes, Maria do Carmo

doi:10.1016/j.amc.2013.05.006

Cited by 20 publications

(35 citation statements)

References 40 publications

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“…To address the convex nonlinear formulation of the FMO problem we used a trust-region-reflective algorithm (fmincon) of MATLAB 7.4.0 (R2007a) Optimization Toolbox. We choose to implement the non-descent PSM algorithm taking advantage of the availability of an existing PSM framework implementation used successfully by us to tackle the BAO problem [16,17,18,19] -the last version of SID-PSM [6,7]. The spanning set used was the positive spanning set ([e − e I − I].…”

Section: Computational Results For Head-and-neck Clinical Examplesmentioning

confidence: 99%

“…Therefore, methods that avoid being easily trapped in local minima and that require few function value evaluations to progress and converge are advantageous. The pattern search methods (PSM) framework has been used by us to address the BAO problem successfully due to its ability to avoid local entrapment and its need for few function value evaluations to converge [16,17,18,19].…”

Section: Introductionmentioning

confidence: 99%

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IMRT Beam Angle Optimization Using Non-descent Pattern Search Methods

Rocha

Dias

Ferreira

et al. 2014

Computational Science and Its Applications – ICCSA 2014

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Abstract. The intensity-modulated radiation therapy (IMRT) treatment planning is usually a sequential process where initially a given number of beam directions are selected followed by the fluence map optimization (FMO) considering those beam directions. The beam angle optimization (BAO) problem consists on the selection of appropriate radiation incidence directions in radiation therapy treatment planning and may be decisive for the quality of the treatment plan, both for appropriate tumor coverage and for enhancement of better organs sparing. This selection must be based on the optimal value of the FMO problem otherwise the resulting beam angle set has no guarantee of optimality and has questionable reliability. Pattern search methods (PSM) have been used successfully to address the BAO problem driven by the optimal fluence value of the FMO problem. PSM are iterative methods generating a sequence of non-increasing iterates such that iterate progression is solely based on a finite number of function evaluations in each iteration, without explicit or implicit use of derivatives. Typically, in IMRT optimization, the quality of the solutions obtained is not simply related to the final value of an objective function but rather judged by dosevolume histograms or considering a set of physical dose metrics. These dose metrics can be simply described as obtaining a minimum prescribed dose for the target volumes (the regions that have to be irradiated) and a maximum or mean tolerance dose values for the remaining surrounding structures (the regions that should be spared). The goal of this paper is to present a non-descent PSM that can be guided both by an objective function formulation of the FMO problem and by physical dose metrics. Four retrospective treated cases of head-and-neck tumors at the Portuguese Institute of Oncology of Coimbra are used to discuss the benefits of non-descent PSM for the optimization of the BAO problem.

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Section: Computational Results For Head-and-neck Clinical Examplesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

IMRT Beam Angle Optimization Using Non-descent Pattern Search Methods

Rocha

Dias

Ferreira

et al. 2014

Computational Science and Its Applications – ICCSA 2014

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“…To address the convex nonlinear formulation of the FMO problem we used a trust-region-reflective algorithm (fmincon) of MATLAB 7.4.0 (R2007a) Optimization Toolbox. We choose to implement the incorporation of BEVD into the pattern search methods framework taking advantage of the availability of an existing pattern search methods framework implementation used successfully by us to tackle the BAO problem [8,9,10] -the last version of SID-PSM [14,15].…”

Section: Numerical Tests and Discussionmentioning

confidence: 99%

“…The FMO optimal value is used to compare the solutions obtained by single-beam approaches and to drive the derivative-free approach we propose [8,9,10]. Our formulation of the BAO problem is briefly presented.…”

Section: Beam Angle Optimization Problemmentioning

confidence: 99%

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On the Global Optimization of the Beam Angle Optimization Problem in Intensity-Modulated Radiation Therapy

et al. 2014

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Abstract-The beam angle optimization (BAO) problem remains an important and challenging problem in intensitymodulated radiation therapy (IMRT) treatment planning. BAO consists on the selection of appropriate radiation incidence directions and may influence the quality of the IMRT plans, both to enhance organs sparing and to improve tumor coverage. This is a very difficult global optimization problem since it is a highly non-convex continuous optimization problem with many local minima. Many conventional BAO approaches are based on single-beam metrics to solve a relaxed combinatorial formulation of the BAO problem. Typically, the quality of the solutions obtained is not simply related to the final value of an objective function but rather judged by dose-volume histograms or considering a set of physical dose metrics. For that reason, and also due to the fact that the global optimum value is unknown, it is difficult to perceive, in medical physics point of view, how good a solution is or how much could it be improved. In a mathematical point of view, it is difficult to acknowledge how far a solution is from the global optimum. The objective of this paper is to present the difficulties in obtaining near global optimum solutions for the BAO problem, particularly when using single-beam approaches considering discrete subsets of all possible beam angles. The benefits of using a derivative-free approach for a continuous formulation of the BAO problem are discussed using a retrospective treated case of head-and-neck tumor at the Portuguese Institute of Oncology of Coimbra.

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An Optimization Approach for Noncoplanar Intensity-Modulated Arc Therapy Trajectories

Rocha

Dias

Ventura

et al. 2019

Computational Science and Its Applications – ICCSA 2019

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The latest generation of linear accelerators allows the simultaneous motion of gantry and couch leading to highly noncoplanar arc trajectories. The use of noncoplanar trajectories in arc radiotherapy was recently proposed to combine the benefits of arc treatment plans, such as short treatment times, with the benefits of step-and-shoot noncoplanar intensity-modulated radiation therapy (IMRT) treatment plans, such as improved organ sparing. In this paper, a two-step approach for the optimization of highly noncoplanar arc trajectories is presented and tested using a complex nasopharyngeal tumor case already treated at the Portuguese Institute of Oncology of Coimbra. In the first step, a set of noncoplanar beam directions is calculated resorting to one of the beam angle optimization (BAO) algorithms proposed in our previous works for step-and-shoot IMRT. In the second step, anchored in the points (beam directions) calculated in the first step, the proposed optimization strategy determines iteratively more anchor points that will define the noncoplanar arc trajectory, considering the dosimetric criteria used for the noncoplanar BAO search rather than geometric or time criteria commonly used. For the patient tested, the resulting noncoplanar arc therapy plan has undoubtedly greater overall quality compared to both the coplanar arc therapy plan and the typically used coplanar equispaced step-and-shoot IMRT plan.

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Pattern search methods framework for beam angle optimization in radiotherapy design

Cited by 20 publications

References 40 publications

IMRT Beam Angle Optimization Using Non-descent Pattern Search Methods

IMRT Beam Angle Optimization Using Non-descent Pattern Search Methods

On the Global Optimization of the Beam Angle Optimization Problem in Intensity-Modulated Radiation Therapy

An Optimization Approach for Noncoplanar Intensity-Modulated Arc Therapy Trajectories

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