Ferramentas Computacionais para Otimização de Mapa de Fluência Radioterápico
Autor(a) principal: | |
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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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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 |
format |
masterThesis |
status_str |
publishedVersion |
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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por |
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600 600 |
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http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess |
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http://creativecommons.org/licenses/by/4.0/ |
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openAccess |
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application/pdf |
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Universidade Estadual do Oeste do Paraná Cascavel |
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Programa de Pós-Graduação em Ciência da Computação |
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UNIOESTE |
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Brasil |
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Centro de Ciências Exatas e Tecnológicas |
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Universidade Estadual do Oeste do Paraná Cascavel |
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