Ferramentas Computacionais para Otimização de Mapa de Fluência Radioterápico

Detalhes bibliográficos
Autor(a) principal: Elias, Thiago dos Santos
Data de Publicação: 2023
Tipo de documento: Dissertação
Idioma: por
Título da fonte: Biblioteca Digital de Teses e Dissertações do UNIOESTE
Texto Completo: https://tede.unioeste.br/handle/tede/6901
Resumo: Cancer is one of the main causes of death in the world, for which the main form of treatment is radiotherapy, with Intensity Modulated Radiotherapy (IMRT) being the most advanced technique in terms of dose delivery. Different mathematical optimization models can be built as well as different solvers used to propose the dose to be emitted so that the dose absorbed in the tumor is the prescribed one and in other tissues it is the minimum. Thus, this work presents three instances, including two linear models and a quadratic model, which were used to evaluate their performance and implications regarding the construction of the optimization function in models that deal with the beam creep problem ( FMO) for the treatment of cancer in the prostate region. Open source and commercial solvers were used in the computational tests. Open source solvers included Clarabel, COSMO, HiGHS, and OSQP, while commercial solvers comprised Gurobi and CPLEX. In all instances, the results were evaluated in relation to the dose coverage in the tumor, and the percentage dose limits in the organs at risk, in addition to evaluating the performance in the different solvers. The results obtained showed that both commercial and open source solvers can find the solution to the problem in a short space of time. The histograms demonstrate that by minimizing the largest dose deviation with the N3 instance it is possible to reach 100% of the tumor tissue. By minimizing the average dose deviation, it is possible to reach 60% of the tissues of the tumor structure through instance N1 with the prescribed dose of 60 Gy, while instance N2 reaches only 33% of tumor tissue with 60 G
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spelling Miloca, Simone AparecidaObal, Thalita MonteiroKonowalenko, FláviaObal, Thalita MonteiroCatarina, Adair Santahttp://lattes.cnpq.br/8495387425419380Elias, Thiago dos Santos2023-11-21T17:59:21Z2023-10-05Elias, Thiago dos Santos. Ferramentas Computacionais para Otimização de Mapa de Fluência Radioterápico. 2023. 71 f. Dissertação( Mestrado em Ciência da Computação) - Universidade Estadual do Oeste do Paraná, Cascavel.https://tede.unioeste.br/handle/tede/6901Cancer is one of the main causes of death in the world, for which the main form of treatment is radiotherapy, with Intensity Modulated Radiotherapy (IMRT) being the most advanced technique in terms of dose delivery. Different mathematical optimization models can be built as well as different solvers used to propose the dose to be emitted so that the dose absorbed in the tumor is the prescribed one and in other tissues it is the minimum. Thus, this work presents three instances, including two linear models and a quadratic model, which were used to evaluate their performance and implications regarding the construction of the optimization function in models that deal with the beam creep problem ( FMO) for the treatment of cancer in the prostate region. Open source and commercial solvers were used in the computational tests. Open source solvers included Clarabel, COSMO, HiGHS, and OSQP, while commercial solvers comprised Gurobi and CPLEX. In all instances, the results were evaluated in relation to the dose coverage in the tumor, and the percentage dose limits in the organs at risk, in addition to evaluating the performance in the different solvers. The results obtained showed that both commercial and open source solvers can find the solution to the problem in a short space of time. The histograms demonstrate that by minimizing the largest dose deviation with the N3 instance it is possible to reach 100% of the tumor tissue. By minimizing the average dose deviation, it is possible to reach 60% of the tissues of the tumor structure through instance N1 with the prescribed dose of 60 Gy, while instance N2 reaches only 33% of tumor tissue with 60 GO câncer é uma das principais causas de morte no mundo, para o qual a principal forma de tratamento é a radioterapia, sendo a Radioterapia de Intensidade Modulada (IMRT) a técnica mais avançada em termos de entrega de doses. Diferentes modelos matemáticos de otimização podem ser construídos bem como diferentes solucionadores utilizados para propor a dose a ser emitida de modo que a dose absorvida no tumor seja a prescrita e nos demais tecidos seja a mínima. Desta forma, este trabalho apresenta três instâncias, incluindo dois modelos lineares e um modelo quadrático, que foram utilizadas para avaliar seus desempenhos e suas implicações no que diz respeito a construção da função de otimização nos modelos que lidam com o problema de fluência de feixe (FMO) para o tratamento de câncer na região da próstata. Nos testes computacionais foram utilizados solucionadores de código aberto e comerciais. Os solucionadores de código aberto incluíram Clarabel, COSMO, HiGHS e OSQP, enquanto os solucionadores comerciais compreenderam Gurobi e CPLEX. Em todas as instâncias, foram avaliados os resultados em relação à cobertura de dose no tumor, e aos limites percentuais de dose nos órgãos de risco, além de avaliar a performance nos diferentes solucionadores. Os resultados obtidos mostraram que tanto os solucionadores comerciais, quanto os de código aberto podem encontrar a solução para o problema em um curto espaço de tempo. Os histogramas demostram que ao minimizar o maior desvio de dose com a instância N3 é possível atingir 100% do tecido de tumor. Já ao minimizar o desvio médio de dose é possível atingir 60% dos tecidos da estrutura tumoral por meio instância N1 com a dose prescrita de 60 Gy, enquanto a instância N2 atinge apenas 33% de tecido tumoral com 60 GySubmitted by Edineia Teixeira (edineia.teixeira@unioeste.br) on 2023-11-21T17:59:21Z No. of bitstreams: 1 Thiago_Elias.2023.pdf: 34059754 bytes, checksum: a13c10fe4a6b2b755daccb834a9da1c8 (MD5)Made available in DSpace on 2023-11-21T17:59:21Z (GMT). No. of bitstreams: 1 Thiago_Elias.2023.pdf: 34059754 bytes, checksum: a13c10fe4a6b2b755daccb834a9da1c8 (MD5) Previous issue date: 2023-10-05application/pdfpor6588633818200016417500Universidade Estadual do Oeste do ParanáCascavelPrograma de Pós-Graduação em Ciência da ComputaçãoUNIOESTEBrasilCentro de Ciências Exatas e Tecnológicashttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessIMRTProgramação LinearProgramação Não LinearIMRTLinear ProgrammingNon-Linear ProgrammingCOMPUTAÇÃO APLICADAFerramentas Computacionais para Otimização de Mapa de Fluência RadioterápicoComputational Tools for Radiotherapy Fluency Map Optimizationinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesis19749965330812744706006002214374442868382015reponame:Biblioteca Digital de Teses e Dissertações do UNIOESTEinstname:Universidade Estadual do Oeste do Paraná (UNIOESTE)instacron:UNIOESTEORIGINALThiago_Elias.2023.pdfThiago_Elias.2023.pdfapplication/pdf34059754http://tede.unioeste.br:8080/tede/bitstream/tede/6901/2/Thiago_Elias.2023.pdfa13c10fe4a6b2b755daccb834a9da1c8MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-82165http://tede.unioeste.br:8080/tede/bitstream/tede/6901/1/license.txtbd3efa91386c1718a7f26a329fdcb468MD51tede/69012024-01-08 09:28:25.892oai:tede.unioeste.br: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Biblioteca Digital de Teses e Dissertaçõeshttp://tede.unioeste.br/PUBhttp://tede.unioeste.br/oai/requestbiblioteca.repositorio@unioeste.bropendoar:2024-01-08T12:28:25Biblioteca Digital de Teses e Dissertações do UNIOESTE - Universidade Estadual do Oeste do Paraná (UNIOESTE)false
dc.title.por.fl_str_mv Ferramentas Computacionais para Otimização de Mapa de Fluência Radioterápico
dc.title.alternative.eng.fl_str_mv Computational Tools for Radiotherapy Fluency Map Optimization
title Ferramentas Computacionais para Otimização de Mapa de Fluência Radioterápico
spellingShingle Ferramentas Computacionais para Otimização de Mapa de Fluência Radioterápico
Elias, Thiago dos Santos
IMRT
Programação Linear
Programação Não Linear
IMRT
Linear Programming
Non-Linear Programming
COMPUTAÇÃO APLICADA
title_short Ferramentas Computacionais para Otimização de Mapa de Fluência Radioterápico
title_full Ferramentas Computacionais para Otimização de Mapa de Fluência Radioterápico
title_fullStr Ferramentas Computacionais para Otimização de Mapa de Fluência Radioterápico
title_full_unstemmed Ferramentas Computacionais para Otimização de Mapa de Fluência Radioterápico
title_sort Ferramentas Computacionais para Otimização de Mapa de Fluência Radioterápico
author Elias, Thiago dos Santos
author_facet Elias, Thiago dos Santos
author_role author
dc.contributor.advisor1.fl_str_mv Miloca, Simone Aparecida
dc.contributor.advisor-co1.fl_str_mv Obal, Thalita Monteiro
dc.contributor.referee1.fl_str_mv Konowalenko, Flávia
dc.contributor.referee2.fl_str_mv Obal, Thalita Monteiro
dc.contributor.referee3.fl_str_mv Catarina, Adair Santa
dc.contributor.authorLattes.fl_str_mv http://lattes.cnpq.br/8495387425419380
dc.contributor.author.fl_str_mv Elias, Thiago dos Santos
contributor_str_mv Miloca, Simone Aparecida
Obal, Thalita Monteiro
Konowalenko, Flávia
Obal, Thalita Monteiro
Catarina, Adair Santa
dc.subject.por.fl_str_mv IMRT
Programação Linear
Programação Não Linear
topic IMRT
Programação Linear
Programação Não Linear
IMRT
Linear Programming
Non-Linear Programming
COMPUTAÇÃO APLICADA
dc.subject.eng.fl_str_mv IMRT
Linear Programming
Non-Linear Programming
dc.subject.cnpq.fl_str_mv COMPUTAÇÃO APLICADA
description Cancer is one of the main causes of death in the world, for which the main form of treatment is radiotherapy, with Intensity Modulated Radiotherapy (IMRT) being the most advanced technique in terms of dose delivery. Different mathematical optimization models can be built as well as different solvers used to propose the dose to be emitted so that the dose absorbed in the tumor is the prescribed one and in other tissues it is the minimum. Thus, this work presents three instances, including two linear models and a quadratic model, which were used to evaluate their performance and implications regarding the construction of the optimization function in models that deal with the beam creep problem ( FMO) for the treatment of cancer in the prostate region. Open source and commercial solvers were used in the computational tests. Open source solvers included Clarabel, COSMO, HiGHS, and OSQP, while commercial solvers comprised Gurobi and CPLEX. In all instances, the results were evaluated in relation to the dose coverage in the tumor, and the percentage dose limits in the organs at risk, in addition to evaluating the performance in the different solvers. The results obtained showed that both commercial and open source solvers can find the solution to the problem in a short space of time. The histograms demonstrate that by minimizing the largest dose deviation with the N3 instance it is possible to reach 100% of the tumor tissue. By minimizing the average dose deviation, it is possible to reach 60% of the tissues of the tumor structure through instance N1 with the prescribed dose of 60 Gy, while instance N2 reaches only 33% of tumor tissue with 60 G
publishDate 2023
dc.date.accessioned.fl_str_mv 2023-11-21T17:59:21Z
dc.date.issued.fl_str_mv 2023-10-05
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
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dc.identifier.citation.fl_str_mv Elias, Thiago dos Santos. Ferramentas Computacionais para Otimização de Mapa de Fluência Radioterápico. 2023. 71 f. Dissertação( Mestrado em Ciência da Computação) - Universidade Estadual do Oeste do Paraná, Cascavel.
dc.identifier.uri.fl_str_mv https://tede.unioeste.br/handle/tede/6901
identifier_str_mv Elias, Thiago dos Santos. Ferramentas Computacionais para Otimização de Mapa de Fluência Radioterápico. 2023. 71 f. Dissertação( Mestrado em Ciência da Computação) - Universidade Estadual do Oeste do Paraná, Cascavel.
url https://tede.unioeste.br/handle/tede/6901
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dc.relation.confidence.fl_str_mv 600
600
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dc.publisher.none.fl_str_mv Universidade Estadual do Oeste do Paraná
Cascavel
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dc.publisher.initials.fl_str_mv UNIOESTE
dc.publisher.country.fl_str_mv Brasil
dc.publisher.department.fl_str_mv Centro de Ciências Exatas e Tecnológicas
publisher.none.fl_str_mv Universidade Estadual do Oeste do Paraná
Cascavel
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