TY - GEN
T1 - Stochastic local search algorithms for the direct aperture optimisation problem in IMRT
AU - Pérez Cáceres, Leslie
AU - Araya, Ignacio
AU - Soto, Denisse
AU - Cabrera-Guerrero, Guillermo
N1 - Publisher Copyright:
© 2019, Springer Nature Switzerland AG.
PY - 2019
Y1 - 2019
N2 - 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.
AB - 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.
KW - Direct aperture optimisation
KW - Intensity modulated radiation therapy
KW - Multi-leaf collimator sequencing
UR - http://www.scopus.com/inward/record.url?scp=85059944844&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-05983-5_8
DO - 10.1007/978-3-030-05983-5_8
M3 - Conference contribution
AN - SCOPUS:85059944844
SN - 9783030059828
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 108
EP - 123
BT - Hybrid Metaheuristics - 11th International Workshop, HM 2019, Proceedings
A2 - Blesa Aguilera, Maria J.
A2 - Blum, Christian
A2 - Pinacho-Davidson, Pedro
A2 - Godoy del Campo, Julio
A2 - Gambini Santos, Haroldo
PB - Springer Verlag
T2 - 11th International Workshop on Hybrid Metaheuristics, HM 2019
Y2 - 16 January 2019 through 18 January 2019
ER -
