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Modulation factors calculated with an EPID‐derived MLC fluence model to streamline IMRT/VMAT second checks
This work outlines the development of a robust method of calculating modulation factors used for the independent verification of MUs for IMRT and VMAT treatments, to replace onerous ion chamber measurements. Two‐dimensional fluence maps were calculated for dynamic MLC fields that include MLC interle...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5714641/ https://www.ncbi.nlm.nih.gov/pubmed/24257271 http://dx.doi.org/10.1120/jacmp.v14i6.4274 |
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author | Steciw, Stephen Rathee, Satyapal Warkentin, Brad |
author_facet | Steciw, Stephen Rathee, Satyapal Warkentin, Brad |
author_sort | Steciw, Stephen |
collection | PubMed |
description | This work outlines the development of a robust method of calculating modulation factors used for the independent verification of MUs for IMRT and VMAT treatments, to replace onerous ion chamber measurements. Two‐dimensional fluence maps were calculated for dynamic MLC fields that include MLC interleaf leakage, transmission, and tongue‐and‐groove effects, as characterized from EPID‐acquired images. Monte Carlo‐generated dose kernels were then used to calculate doses for a modulated field and that field with the modulation removed at a depth specific to the calculation point in the patient using in‐house written software, Mod_Calc. The ratio of these two doses was taken to calculate modulation factors. Comparison between Mod_Calc calculation and ion chamber measurement of modulation factors for 121 IMRT fields yielded excellent agreement, where the mean difference between the two was [Formula: see text]. This validated use of Mod_Calc clinically. Analysis of 5,271 dynamic fields from clinical use of Mod_Calc gave a mean difference of [Formula: see text] between Mod_Calc and Eclipse‐generated factors. In addition, 99.3% and 96.5% fields pass 5% and 2% criteria, respectively, for agreement between these two predictions. The development and use of Mod_Calc at our clinic has considerably streamlined our QA process for IMRT and RapidArc fields, compared to our previous method based on ion chamber measurements. As a result, it has made it feasible to maintain our established and trusted current in‐house method of MU verification, without resorting to commercial software alternatives. PACS numbers: 87.55.km, 87.55.Qr, 87.55.kd, 87.57.uq |
format | Online Article Text |
id | pubmed-5714641 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-57146412018-04-02 Modulation factors calculated with an EPID‐derived MLC fluence model to streamline IMRT/VMAT second checks Steciw, Stephen Rathee, Satyapal Warkentin, Brad J Appl Clin Med Phys Radiation Oncology Physics This work outlines the development of a robust method of calculating modulation factors used for the independent verification of MUs for IMRT and VMAT treatments, to replace onerous ion chamber measurements. Two‐dimensional fluence maps were calculated for dynamic MLC fields that include MLC interleaf leakage, transmission, and tongue‐and‐groove effects, as characterized from EPID‐acquired images. Monte Carlo‐generated dose kernels were then used to calculate doses for a modulated field and that field with the modulation removed at a depth specific to the calculation point in the patient using in‐house written software, Mod_Calc. The ratio of these two doses was taken to calculate modulation factors. Comparison between Mod_Calc calculation and ion chamber measurement of modulation factors for 121 IMRT fields yielded excellent agreement, where the mean difference between the two was [Formula: see text]. This validated use of Mod_Calc clinically. Analysis of 5,271 dynamic fields from clinical use of Mod_Calc gave a mean difference of [Formula: see text] between Mod_Calc and Eclipse‐generated factors. In addition, 99.3% and 96.5% fields pass 5% and 2% criteria, respectively, for agreement between these two predictions. The development and use of Mod_Calc at our clinic has considerably streamlined our QA process for IMRT and RapidArc fields, compared to our previous method based on ion chamber measurements. As a result, it has made it feasible to maintain our established and trusted current in‐house method of MU verification, without resorting to commercial software alternatives. PACS numbers: 87.55.km, 87.55.Qr, 87.55.kd, 87.57.uq John Wiley and Sons Inc. 2013-11-08 /pmc/articles/PMC5714641/ /pubmed/24257271 http://dx.doi.org/10.1120/jacmp.v14i6.4274 Text en © 2013 The Authors. This is an open access article under the terms of the Creative Commons Attribution (http://creativecommons.org/licenses/by/3.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Radiation Oncology Physics Steciw, Stephen Rathee, Satyapal Warkentin, Brad Modulation factors calculated with an EPID‐derived MLC fluence model to streamline IMRT/VMAT second checks |
title | Modulation factors calculated with an EPID‐derived MLC fluence model to streamline IMRT/VMAT second checks |
title_full | Modulation factors calculated with an EPID‐derived MLC fluence model to streamline IMRT/VMAT second checks |
title_fullStr | Modulation factors calculated with an EPID‐derived MLC fluence model to streamline IMRT/VMAT second checks |
title_full_unstemmed | Modulation factors calculated with an EPID‐derived MLC fluence model to streamline IMRT/VMAT second checks |
title_short | Modulation factors calculated with an EPID‐derived MLC fluence model to streamline IMRT/VMAT second checks |
title_sort | modulation factors calculated with an epid‐derived mlc fluence model to streamline imrt/vmat second checks |
topic | Radiation Oncology Physics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5714641/ https://www.ncbi.nlm.nih.gov/pubmed/24257271 http://dx.doi.org/10.1120/jacmp.v14i6.4274 |
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