Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 2 de 2
Filtrar
Mais filtros

Base de dados
Ano de publicação
Tipo de documento
Intervalo de ano de publicação
1.
Phys Eng Sci Med ; 47(2): 551-561, 2024 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-38285272

RESUMO

Bolus is commonly used to improve dose distributions in radiotherapy in particular if dose to skin must be optimised such as in breast or head and neck cancer. We are documenting four years of experience with 3D printed bolus at a large cancer centre. In addition to this we review the quality assurance (QA) program developed to support it. More than 2000 boluses were produced between Nov 2018 and Feb 2023 using fused deposition modelling (FDM) printing with polylactic acid (PLA) on up to five Raise 3D printers. Bolus is designed in the radiotherapy treatment planning system (Varian Eclipse), exported to an STL file followed by pre-processing. After checking each bolus with CT scanning initially we now produce standard quality control (QC) wedges every month and whenever a major change in printing processes occurs. A database records every bolus printed and manufacturing details. It takes about 3 days from designing the bolus in the planning system to delivering it to treatment. A 'premium' PLA material (Spidermaker) was found to be best in terms of homogeneity and CT number consistency (80 HU +/- 8HU). Most boluses were produced for photon beams (93.6%) with the rest used for electrons. We process about 120 kg of PLA per year with a typical bolus weighing less than 500 g and the majority of boluses 5 mm thick. Print times are proportional to bolus weight with about 24 h required for 500 g material deposited. 3D printing using FDM produces smooth and reproducible boluses. Quality control is essential but can be streamlined.


Assuntos
Impressão Tridimensional , Humanos , Garantia da Qualidade dos Cuidados de Saúde/normas , Controle de Qualidade , Planejamento da Radioterapia Assistida por Computador , Tomografia Computadorizada por Raios X , Dosagem Radioterapêutica , Poliésteres/química
2.
Australas Phys Eng Sci Med ; 40(2): 305-315, 2017 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-28243923

RESUMO

This study investigates the potential benefits of planning target volume (PTV) margin reduction for whole breast radiotherapy in relation to dose received by organs at risk (OARs), as well as reductions in radiation-induced secondary cancer risk. Such benefits were compared to the increased radiation-induced secondary cancer risk attributed from increased ionizing radiation imaging doses. Ten retrospective patients' computed tomography datasets were considered. Three computerized treatment plans with varied PTV margins (0, 5 and 10 mm) were created for each patient complying with the Radiation Therapy Oncology Group (RTOG) 1005 protocol requirements. The BEIR VII lifetime attributable risk (LAR) model was used to estimate secondary cancer risk to OARs. The LAR was assessed for all treatment plans considering (a) doses from PTV margin variation and (b) doses from two (daily and weekly) kilovoltage cone beam computed tomography (kV CBCT) imaging protocols during the course of treatment. We found PTV margins from largest to smallest resulted in a mean OAR relative dose reduction of 31% (heart), 28% (lung) and 23% (contralateral breast) and the risk of radiation-induced secondary cancer by a relative 23% (contralateral breast) and 22% (contralateral lung). Daily image-guidance using kV CBCT increased the risk of radiation induced secondary cancer to the contralateral breast and contralateral lung by a relative 1.6-1.9% and 1.9-2.5% respectively. Despite the additional dose from kV CBCT for the two considered imaging protocols, smaller PTV margins would still result in an overall reduction in secondary cancer risk.


Assuntos
Neoplasias da Mama/radioterapia , Neoplasias da Mama/diagnóstico por imagem , Tomografia Computadorizada de Feixe Cônico , Feminino , Humanos , Especificidade de Órgãos/efeitos da radiação , Dosagem Radioterapêutica , Planejamento da Radioterapia Assistida por Computador , Fatores de Risco
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA