Abstract
In this paper, two heuristic algorithms are proposed to solve the direct aperture optimisation problem (DAO) in radiation therapy for cancer treatment. In the DAO problem, the goal is to find a set of deliverable aperture shapes and intensities so we can irradiate the tumor according to a medical prescription without producing any harm to the surrounding healthy tissues. Unlike the traditional two-step approach used in intensity modulated radiation therapy (IMRT) where the intensities are computed and then the apertures shapes are determined by solving a sequencing problem, in the DAO problem, constraints associated to the number of deliverable aperture shapes as well as physical constraints are taken into account during the intensities optimisation process. Thus, we do not longer need any leaves sequencing procedure after solving the DAO problem. We try our heuristic algorithms on a prostate case and compare the obtained treatment plan to the one obtained using the traditional two-step approach. Results show that our algorithms are able to find treatment plans that are very competitive when considering the number of deliverable aperture shapes.
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Notes
- 1.
i.e., only beamlets \(x_{i}\) that belong to a beam angle in \(\mathscr {A}\) are allowed to be greater than zero.
- 2.
Even disregarding the impact on the clinical schedule, long treatment times are uncomfortable for the patients and carry an increased risk of intra-fraction motion, which may compromise plan quality [9].
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Acknowledgement
Guillermo Cabrera-Guerrero wishes to thank FONDECYT/INICIACION/11170456 project for partially support this research.
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Pérez Cáceres, L., Araya, I., Soto, D., Cabrera-Guerrero, G. (2019). Stochastic Local Search Algorithms for the Direct Aperture Optimisation Problem in IMRT. In: Blesa Aguilera, M., Blum, C., Gambini Santos, H., Pinacho-Davidson, P., Godoy del Campo, J. (eds) Hybrid Metaheuristics. HM 2019. Lecture Notes in Computer Science(), vol 11299. Springer, Cham. https://doi.org/10.1007/978-3-030-05983-5_8
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