A simple model for predicting the signal for a head-mounted transmission chamber system, allowing IMRT in-vivo dosimetry without pretreatment linac time.
J Appl Clin Med Phys
; 15(4): 4842, 2014 Jul 08.
Article
em En
| MEDLINE
| ID: mdl-25207413
The DAVID is a transparent, multi-wire transmission-style detector that attaches to a linear accelerator (linac) collimator for use as an in vivo detector. Currently, the normal method for using the DAVID is to measure a signal at the time of phantom-based pretreatment verification and use that signal as a baseline to compare with in vivo measurements for subsequent treatment fractions. The device has previously been shown to be both stable and accurate.(1,2) This work presents the development of a predictive algorithm for the expected signal, eradicating the need to spend time on the linac prior to treatment, and thereby making the process more efficient. The DAVID response at each wire is a consequence of both primary radiation, from the leaf pair associated with the wire, and scatter radiation as a result of radiation incident on other parts of the detector scattering in the Perspex plate. The primary radiation was shown to be linearly proportional to both leaf separation and delivered monitor units (MU). The scatter signal dropped off exponentially with regard to distance. Both of these effects were modeled; the resulting algorithm was used to predict the response from ten five-field IMRT head and neck plans. The system predicted all DAVID signals to within 5%, and was able to detect artificially generated changes in linac output. Having shown that the algorithm works, a new working paradigm is suggested, and the errors that can be detected are outlined.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Aceleradores de Partículas
/
Radiometria
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Planejamento da Radioterapia Assistida por Computador
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Radioterapia de Intensidade Modulada
/
Neoplasias de Cabeça e Pescoço
Tipo de estudo:
Health_economic_evaluation
/
Prognostic_studies
/
Risk_factors_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2014
Tipo de documento:
Article