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

Bibliographic Details
Main Author: Dias, Joana
Publication Date: 2015
Other Authors: Rocha, Humberto, Ferreira, Brígida, Lopes, Maria do Carmo
Format: Article
Language: por
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: https://hdl.handle.net/10316/44632
https://doi.org/10.1016/j.ejmp.2015.03.005
Summary: Electing irradiation directions to use in IMRT treatments is one of the first decisions to make in treatment planning. Beam angle optimization (BAO) is a difficult problem to tackle from the mathematical optimization point of view. It is highly non-convex, and optimization approaches based on gradient descent methods will probably get trapped in one of the many local minima. Simulated Annealing (SA) is a local search probabilistic procedure that is known to be able to deal with multimodal problems. SA for BAO was retrospectively applied to ten clinical examples of treated cases of head-and neck tumors signalized as complex cases where proper target coverage and organ sparing proved difficult to achieve. The number of directions to use was considered fixed and equal to 5 or 7. It is shown that SA can lead to solutions that significantly improve organ sparing, even considering a reduced number of angles, without jeopardizing tumor coverage.
id RCAP_28f824b0d2f6dbc076f512abb111c380
oai_identifier_str oai:estudogeral.uc.pt:10316/44632
network_acronym_str RCAP
network_name_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository_id_str https://opendoar.ac.uk/repository/7160
spelling Simulated annealing applied to IMRT beam angle optimization: A computational studyAlgorithmsHead and Neck NeoplasmsHumansRadiotherapy Planning, Computer-AssistedRadiotherapy, Intensity-ModulatedRetrospective StudiesElecting irradiation directions to use in IMRT treatments is one of the first decisions to make in treatment planning. Beam angle optimization (BAO) is a difficult problem to tackle from the mathematical optimization point of view. It is highly non-convex, and optimization approaches based on gradient descent methods will probably get trapped in one of the many local minima. Simulated Annealing (SA) is a local search probabilistic procedure that is known to be able to deal with multimodal problems. SA for BAO was retrospectively applied to ten clinical examples of treated cases of head-and neck tumors signalized as complex cases where proper target coverage and organ sparing proved difficult to achieve. The number of directions to use was considered fixed and equal to 5 or 7. It is shown that SA can lead to solutions that significantly improve organ sparing, even considering a reduced number of angles, without jeopardizing tumor coverage.2015info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttps://hdl.handle.net/10316/44632https://hdl.handle.net/10316/44632https://doi.org/10.1016/j.ejmp.2015.03.005porhttp://www.sciencedirect.com/science/article/pii/S1120179715000654Dias, JoanaRocha, HumbertoFerreira, BrígidaLopes, Maria do Carmoinfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2021-08-24T10:08:19Zoai:estudogeral.uc.pt:10316/44632Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T04:58:24.084484Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Simulated annealing applied to IMRT beam angle optimization: A computational study
title Simulated annealing applied to IMRT beam angle optimization: A computational study
spellingShingle Simulated annealing applied to IMRT beam angle optimization: A computational study
Dias, Joana
Algorithms
Head and Neck Neoplasms
Humans
Radiotherapy Planning, Computer-Assisted
Radiotherapy, Intensity-Modulated
Retrospective Studies
title_short Simulated annealing applied to IMRT beam angle optimization: A computational study
title_full Simulated annealing applied to IMRT beam angle optimization: A computational study
title_fullStr Simulated annealing applied to IMRT beam angle optimization: A computational study
title_full_unstemmed Simulated annealing applied to IMRT beam angle optimization: A computational study
title_sort Simulated annealing applied to IMRT beam angle optimization: A computational study
author Dias, Joana
author_facet Dias, Joana
Rocha, Humberto
Ferreira, Brígida
Lopes, Maria do Carmo
author_role author
author2 Rocha, Humberto
Ferreira, Brígida
Lopes, Maria do Carmo
author2_role author
author
author
dc.contributor.author.fl_str_mv Dias, Joana
Rocha, Humberto
Ferreira, Brígida
Lopes, Maria do Carmo
dc.subject.por.fl_str_mv Algorithms
Head and Neck Neoplasms
Humans
Radiotherapy Planning, Computer-Assisted
Radiotherapy, Intensity-Modulated
Retrospective Studies
topic Algorithms
Head and Neck Neoplasms
Humans
Radiotherapy Planning, Computer-Assisted
Radiotherapy, Intensity-Modulated
Retrospective Studies
description Electing irradiation directions to use in IMRT treatments is one of the first decisions to make in treatment planning. Beam angle optimization (BAO) is a difficult problem to tackle from the mathematical optimization point of view. It is highly non-convex, and optimization approaches based on gradient descent methods will probably get trapped in one of the many local minima. Simulated Annealing (SA) is a local search probabilistic procedure that is known to be able to deal with multimodal problems. SA for BAO was retrospectively applied to ten clinical examples of treated cases of head-and neck tumors signalized as complex cases where proper target coverage and organ sparing proved difficult to achieve. The number of directions to use was considered fixed and equal to 5 or 7. It is shown that SA can lead to solutions that significantly improve organ sparing, even considering a reduced number of angles, without jeopardizing tumor coverage.
publishDate 2015
dc.date.none.fl_str_mv 2015
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://hdl.handle.net/10316/44632
https://hdl.handle.net/10316/44632
https://doi.org/10.1016/j.ejmp.2015.03.005
url https://hdl.handle.net/10316/44632
https://doi.org/10.1016/j.ejmp.2015.03.005
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv http://www.sciencedirect.com/science/article/pii/S1120179715000654
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
_version_ 1833602211202990081