Simulated annealing applied to IMRT beam angle optimization: A computational study

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

doi:10.1016/j.ejmp.2014.07.073

Cited by 11 publications

(12 citation statements)

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“…The OF PLAN was recalculated and was accepted if it decreased. A larger OF PLAN can be accepted based on a calculated probability of acceptance of worsening solutions, which decays with time . This feature of simulated annealing facilitates a more thorough search of the OF parameter space and reduces the likelihood of becoming trapped in a local minimum in the solution space.…”

Section: Methodsmentioning

confidence: 99%

Intra‐arc binary collimation algorithm for the optimization of stereotactic radiotherapy treatment of multiple metastases with multiple prescriptions

et al. 2018

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Purpose To design and implement a novel treatment planning algorithm based on a modification of dynamic conformal arc (DCA) therapy for the treatment of multiple cranial metastases with variable prescription doses. Methods A workflow was developed in which separate dose matrices were calculated for each target at each control point (i.e., the multileaf collimator (MLC) was fit conformally to that single target). A cost function was used to quantify the relative contributions of each dose matrix in the plan to the overall plan objectives. Simulated annealing was used to allow for the inclusion or exclusion of individual dose matrices at each control point. The exclusion of individual targets at a given control point is termed intra‐arc binary collimation (iABC) in this work and is accomplished by closing the MLCs over the target for a duration specified by simulated annealing optimization. Dynamic collimator motions were employed to minimize the variation between the idealized dose matrices (i.e., perfectly collimated targets) and actual dose matrices (i.e., MLC apertures that include quantities of nontarget tissue due to the relative orientations of targets in the field). An additional simulated annealing optimization was performed to weight the relative contributions of dose at each control point [referred to as the monitor unit distribution (MUD)] to improve compliance with plan objectives. The algorithm was tested on seven previously treated multiple metastases patients and plans were compared to the clinically treated VMAT plans. Results Treatment plans generated with iABC used an average of 2716 (34%) fewer MU in the total plan than VMAT (P = 0.01). All normal tissue metrics for all plans and all patients were clinically acceptable. There were no statistically significant differences in any normal tissue dose metrics. Normalized prescription target coverage accuracy for all targets was 3% better on average for VMAT plans when compared to iABC (P = 0.07), and 14% better on average for iABC when compared to optimized DCA (P = 0.03). Conclusion A novel method of aperture and dose distribution design has been developed to significantly increase the MU efficiency of single isocenter treatment of multiple metastases with variable prescription doses when compared to VMAT, and which improves target coverage accuracy significantly when compared to optimized DCA. By applying a DCA approach to subsets of targets across control points, a hybrid method of treatment delivery has been developed that combines the efficiency of dynamic conformal treatments and the dosimetric flexibility of VMAT.

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Section: Methodsmentioning

confidence: 99%

Intra‐arc binary collimation algorithm for the optimization of stereotactic radiotherapy treatment of multiple metastases with multiple prescriptions

et al. 2018

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“…In this paper a very simple equidistant beam angle optimization is proposed, by enumerating the possible equidistant solutions and finding the best treatment plan for each of them. Further developments will consider embedding FIS into beam angle optimization algorithms [28][29][30][31][32][33] in order to further contribute to automated treatment planning. The presented methodology lends itself naturally to parallel implementations, which will help tackle the computational burden.…”

Section: Discussionmentioning

confidence: 99%

Automated Radiotherapy Treatment Planning Using Fuzzy Inference Systems

Dias

Rocha

Ventura

et al. 2017

Computational Science and Its Applications – ICCSA 2017

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Abstract. Radiotherapy is one of the treatments available for cancer patients, aiming to irradiate the tumor while preserving healthy structures. The planning of a treatment is a lengthy trial and error procedure, where treatment parameters are iteratively changed and the delivered dose is calculated to see whether it complies with the desired medical prescription. In this paper, a procedure based on fuzzy inference systems (FIS) for automated treatment planning is developed, allowing the calculation of high quality treatment plans without requiring human intervention. The procedure is structured in two different phases, incorporating the automatic selection of the best set of equidistant beam irradiation directions by an enumeration procedure. The developed method is extensively tested using ten head-and-neck cancer cases.

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“…In this paper, we propose a two-step approach based on dosimetric criteria for the optimization of noncoplanar arc trajectories. In the first step, an initial set of anchor points (noncoplanar beam directions) is computed taking advantage of the work previously developed in BAO for step-and-shoot IMRT [7][8][9][10][11][12][13]. In the second step, anchored in the beam directions already calculated, the noncoplanar arc trajectory is defined by iteratively computing additional anchor points considering the same dosimetric criteria used for the noncoplanar BAO.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Highly Noncoplanar Arc Therapy Trajectories: A Dosimetric Approach

et al. 2019

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The latest generation of linear accelerators allows the use of noncoplanar trajectories in arc therapy which combine the benefits of noncoplanar intensity-modulated radiation therapy (IMRT) treatment plans, such as improved organ sparing, with the benefits of arc therapy treatment plans, such as short treatment times. In this paper, we propose a two-step approach based on dosimetric criteria for the optimization of noncoplanar arc trajectories. In the first step, an initial set of anchor points (noncoplanar beam directions) is computed using a beam angle optimization (BAO) algorithm. In the second step, anchored in the beam directions already calculated, the noncoplanar arc trajectory is defined by iteratively computing additional anchor points considering the same dosimetric criteria used for the noncoplanar BAO. A nasopharyngeal tumor case already treated at the Portuguese Institute of Oncology of Coimbra (IPOC), is used to illustrate the benefits of the proposed optimization approach.

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Simulated annealing applied to IMRT beam angle optimization: A computational study

Cited by 11 publications

References 0 publications

Intra‐arc binary collimation algorithm for the optimization of stereotactic radiotherapy treatment of multiple metastases with multiple prescriptions

Intra‐arc binary collimation algorithm for the optimization of stereotactic radiotherapy treatment of multiple metastases with multiple prescriptions

Automated Radiotherapy Treatment Planning Using Fuzzy Inference Systems

Optimization of Highly Noncoplanar Arc Therapy Trajectories: A Dosimetric Approach

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