Avaliação de um acelerador linear médico usando o código PHITS

• Ano de defesa: 2024
• Autor(a) principal: Silva, Fellipe Oliveira Ferraz
• Orientador(a): Lalic, Susana de Souza
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Programa de Pós-Graduação: Pós-Graduação em Física
• Palavras-chave em Português: Radioterapia; Método Monte Carlo; Acelerador Linear; Código PHITS
• Palavras-chave em Inglês: Radiotherapy; Monte Carlo Method; Linear Accelerator; PHITS Code
• Área do conhecimento CNPq: CIENCIAS EXATAS E DA TERRA::FISICA
• Link de acesso: https://ri.ufs.br/jspui/handle/riufs/19156

Radiation therapy is a crucial modality in cancer treatment, utilizing 3D planning systems to assess healthy tissues and adjacent targets. During planning, the medical radiation team aims to maximize the dose to the target organ and minimize doses to at-risk organs using images from radiodiagnosis images. However, verifying the actual dose distribution in the patient's tissue is challenging due to the impossibility of placing dosimeters inside the body. To evaluate the real dose distribution in patients' internal organs, virtual anthropomorphic simulators have been developed and integrated into Monte Carlo codes. This allows the reproduction of clinical situations and prevents undue irradiation. Monte Carlo simulation of radiation transport is considered the most accurate method for calculating dose distribution in radiotherapy and has become widely used for modeling linear accelerators in medical physics. Calculating the dose distribution in a patient is not straightforward. Before computerized treatment planning systems became widely available, dose distributions were manually calculated by adding estimated percentages from isodose charts. In this study, we propose simulating an Elekta Precise linear accelerator using a 6 MV beam in the PHITS code. The depth-dose curve was initially simulated in 10 x 10 cm² and 40 x 40 cm² fields. Results obtained through Tally T-Deposit were compared with experimental measurements, showing equivalence with variations below 5%. This numerical assessment method represents the best approach to validate measured and calculated dose distribution values in radiotherapy, enabling assessments in patients using virtual anthropomorphic computational simulators.