Optimization model applied to radiotherapy planning problem with dose intensity and beam choice

Freitas, Juliana Campos de; Florentino, Helenice de Oliveira; Benedito, Antone dos Santos; Cantane, Daniela Renata

doi:10.1016/j.amc.2019.124786

Cited by 3 publications

(3 citation statements)

References 16 publications

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“…The main reason for the clinical use of equispaced beam angle ensembles is inherent to the challenge of solving the BAO problem, a nonconvex problem with many local minima on a large search space (Craft, 2007). The vast majority of the approaches proposed to address the BAO problem consider a discrete subset of all continuous beam angle directions solving the resulting combinatorial optimization problem (Pugachev et al, 2001; Aleman et al., 2008; Lim and Cao, 2012; Bertsimas et al., 2013; Dias et al., 2014, 2015; Cabrera et al., 2018; Freitas et al., 2020), either relying on geometric measures or in dosimetric values. However, the optimal solution of the combinatorial BAO problem cannot be calculated in a polynomial run time—NP‐hard problem (Bangert et al., 2012).…”

Section: Noncoplanar Arc Trajectory Optimization Frameworkmentioning

confidence: 99%

An automated treatment planning strategy for highly noncoplanar radiotherapy arc trajectories

Carrasqueira

Rocha

Dias

et al. 2021

Int Trans Operational Res

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Radiation therapy is a technology-driven cancer treatment modality that has experienced significant advances over the last decades, due to multidisciplinary contributions that include engineering and computing. Recent technological developments allow the use of noncoplanar volumetric modulated arc therapy (VMAT), one of the most recent photon treatment techniques, in clinical practice. In this work, an automated noncoplanar arc trajectory optimization framework designed in two modular phases is presented. First, a noncoplanar beam angle optimization algorithm is used to obtain a set of noncoplanar irradiation directions. Then, anchored in these directions, an optimization strategy is proposed to compute an optimal arc trajectory. The computational experiments considered a pool of twelve difficult head-and-neck tumor cases. It was possible to observe that, for some of these cases, the optimized noncoplanar arc trajectories led to significant treatment planning quality improvements, when compared with coplanar VMAT treatment plans. Although these experiments were done in a research environment treatment planning software (matRad), the conclusions can be of interest for a clinical setting: automated procedures can simplify the current treatment workflow, produce high-quality treatment plans, making better use of human resources and allowing for unbiased comparisons between different treatment techniques.

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Section: Noncoplanar Arc Trajectory Optimization Frameworkmentioning

confidence: 99%

An automated treatment planning strategy for highly noncoplanar radiotherapy arc trajectories

Carrasqueira

Rocha

Dias

et al. 2021

Int Trans Operational Res

View full text Add to dashboard Cite

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“…Freitas et al. (2019) propose a mixed‐integer nonlinear optimization model addressing both dose intensity and beam selection. In Cabrera et al.…”

Section: Bi‐level Optimization For Imrtmentioning

confidence: 99%

“…In these approaches, the beam ensemble is selected before the FMO problem is tackled. Freitas et al (2019) propose a mixed-integer nonlinear optimization model addressing both dose intensity and beam selection.…”

Section: Beam Angle Optimization Approachesmentioning

confidence: 99%

An automated bi‐level optimization approach for IMRT

Carrasqueira

Alves

Dias

et al. 2021

Int Trans Operational Res

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Intensity-modulated radiation therapy is used worldwide to treat cancer patients. The objective of this treatment is to deliver a prescribed radiation dose to the tumor while sparing, as much as possible, all the healthy tissues, especially organs at risk (OAR). This means that the planning of a radiotherapy treatment should take into consideration conflicting objectives: to be able to spare as much as possible the OAR guaranteeing, at the same time, that the desired radiation is delivered to the volumes to treat. While the volumes to treat can be adequately irradiated from almost any set of directions, the radiation directions that are chosen have a determinant impact on the OAR. This means that those directions that provide an improved OAR sparing should be selected. The choice of radiation directions (beam angles) can thus be interpreted as being fundamentally determined by the OAR, with the radiation intensities associated with each of these directions being determined by the needed radiation to be delivered to the volumes to treat. In this work, we interpret the radiotherapy treatment planning problem as a bi-level optimization problem. At the upper level, OAR control the choice of the beam angles, which are selected aiming at OAR sparing. At the lower level, the optimal radiation intensities are decided by the volumes to treat, considering the beam angle ensemble obtained at the upper level. The proposed bi-level approach was tested using 10 clinical head-and-neck cancer cases already treated at the Portuguese Institute of Oncology in Coimbra.

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