Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/88866
Title: Monte Carlo study on electron contamination and output factors of small field dosimetry in 6 MV photon beam
Authors: Yani, Sitti
Dirgayussa, I Gde Eka
Rhani, Mohamad Fahdillah
Soh, Roger C. X.
Haryanto, Freddy
Arif, Idam
Keywords: Monte Carlo
Photon Beam
DRNTU::Science::Physics
Issue Date: 2016
Source: Yani, S., Dirgayussa, I. G. E., Rhani, M. F., Soh, R. C. X., Haryanto, F., & Arif, I. (2016). Monte Carlo study on electron contamination and output factors of small field dosimetry in 6 MV photon beam. Smart Science, 4(2), 87-94. doi:10.1080/23080477.2016.1195609
Series/Report no.: Smart Science
Abstract: The purpose of this study was to investigate the characteristics of electron contamination and Output Factors (OFs) from Varian Trilogy Clinac iX 6 MV photon beam at small field sizes. EGSnrc Monte Carlo (MC) code system was used to model the photon beam for this Linear Accelerator (Linac) head and analyze the electron contamination and OFs from this treatment head. The electron contamination was analyzed for field sizes of 1 × 1, 2 × 2, 3 × 3, 4 × 4, and 5 × 5 cm2. The number of electron contamination increases with increasing field sizes, but the maximum energy of the electron contamination stays constant (at around 1.87 MeV for each field size). The contaminants contribute to the dose at the surface of the water phantom (1–5 cm from the surface) for field size 4 × 4 and 5 × 5 cm2 and this dose decreases with depth. The OFs are simulated by EGSnrc code system and have a good agreement with measurement (deviation 3.45, 1.76, and 0.86 for field of 2, 3 and 4, respectively). This study presented that MC methods have great potential to accurately predict the electron contamination and OFs for 6 MV photon beam.
URI: https://hdl.handle.net/10356/88866
http://hdl.handle.net/10220/45989
DOI: http://dx.doi.org/10.1080/23080477.2016.1195609
Rights: © 2016 The Author(s) (published by Taylor & Francis). This paper was published in Smart Science and is made available as an electronic reprint (preprint) with permission of The Author(s) (published by Taylor & Francis). The published version is available at: [http://dx.doi.org/10.1080/23080477.2016.1195609]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SPMS Journal Articles

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