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A comparison of two commercial treatment‐planning systems for IMRT

This study compared the clinical functionality of BrainSCAN (BrainLAB) and Helios (Eclipse, Varian) for intensity‐modulated radiation therapy (IMRT) treatment planning with the aim of identifying practical and technical issues. The study considered implementation and commissioning, dose optimization...

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Autores principales: Petric, M. Peter, Clark, Brenda G., Robar, James L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2005
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5723501/
https://www.ncbi.nlm.nih.gov/pubmed/16143792
http://dx.doi.org/10.1120/jacmp.v6i3.2054
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author Petric, M. Peter
Clark, Brenda G.
Robar, James L.
author_facet Petric, M. Peter
Clark, Brenda G.
Robar, James L.
author_sort Petric, M. Peter
collection PubMed
description This study compared the clinical functionality of BrainSCAN (BrainLAB) and Helios (Eclipse, Varian) for intensity‐modulated radiation therapy (IMRT) treatment planning with the aim of identifying practical and technical issues. The study considered implementation and commissioning, dose optimization, and plan assessment. Both systems were commissioned for the same 6 MV photon beam equipped with a high‐resolution multileaf collimator (Varian Millennium 120 leaf). The software was applied to three test plans having identical imaging and contour data. Analysis considered 3D axial dose distributions, dose‐volume histograms, and monitor unit calculations. Each system requires somewhat different input data to characterize the beam prior to use, so the same data cannot be used for commissioning. In addition, whereas measured beam data was entered directly into Helios with minimal data processing, the BrainSCAN system required configured beam data to be sent to BrainLAB before clinical use. One key difference with respect to system commissioning was that BrainSCAN required high resolution data, which necessitated the use of detectors with small active volumes. This difference was found to impact on the ability of the systems to accurately calculate dose for highly modulated fields, with BrainSCAN being more successful than Helios. In terms of functionality, the BrainSCAN system uses a dynamically penalized likelihood inverse planning algorithm and calculates four plans at once with various relative weighting of the planning target and organ‐at‐risk volumes. Helios uses a gradient algorithm that allows the user to make changes to some of the input parameters during optimization. An analysis of the dosimetry output shows that, although the systems are different in many respects, they are each capable of producing substantially equivalent dose plans in terms of target coverage and normal tissue sparing. PACS number: 87.53.Tf
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spelling pubmed-57235012018-04-02 A comparison of two commercial treatment‐planning systems for IMRT Petric, M. Peter Clark, Brenda G. Robar, James L. J Appl Clin Med Phys Radiation Oncology Physics This study compared the clinical functionality of BrainSCAN (BrainLAB) and Helios (Eclipse, Varian) for intensity‐modulated radiation therapy (IMRT) treatment planning with the aim of identifying practical and technical issues. The study considered implementation and commissioning, dose optimization, and plan assessment. Both systems were commissioned for the same 6 MV photon beam equipped with a high‐resolution multileaf collimator (Varian Millennium 120 leaf). The software was applied to three test plans having identical imaging and contour data. Analysis considered 3D axial dose distributions, dose‐volume histograms, and monitor unit calculations. Each system requires somewhat different input data to characterize the beam prior to use, so the same data cannot be used for commissioning. In addition, whereas measured beam data was entered directly into Helios with minimal data processing, the BrainSCAN system required configured beam data to be sent to BrainLAB before clinical use. One key difference with respect to system commissioning was that BrainSCAN required high resolution data, which necessitated the use of detectors with small active volumes. This difference was found to impact on the ability of the systems to accurately calculate dose for highly modulated fields, with BrainSCAN being more successful than Helios. In terms of functionality, the BrainSCAN system uses a dynamically penalized likelihood inverse planning algorithm and calculates four plans at once with various relative weighting of the planning target and organ‐at‐risk volumes. Helios uses a gradient algorithm that allows the user to make changes to some of the input parameters during optimization. An analysis of the dosimetry output shows that, although the systems are different in many respects, they are each capable of producing substantially equivalent dose plans in terms of target coverage and normal tissue sparing. PACS number: 87.53.Tf John Wiley and Sons Inc. 2005-08-17 /pmc/articles/PMC5723501/ /pubmed/16143792 http://dx.doi.org/10.1120/jacmp.v6i3.2054 Text en © 2005 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
Petric, M. Peter
Clark, Brenda G.
Robar, James L.
A comparison of two commercial treatment‐planning systems for IMRT
title A comparison of two commercial treatment‐planning systems for IMRT
title_full A comparison of two commercial treatment‐planning systems for IMRT
title_fullStr A comparison of two commercial treatment‐planning systems for IMRT
title_full_unstemmed A comparison of two commercial treatment‐planning systems for IMRT
title_short A comparison of two commercial treatment‐planning systems for IMRT
title_sort comparison of two commercial treatment‐planning systems for imrt
topic Radiation Oncology Physics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5723501/
https://www.ncbi.nlm.nih.gov/pubmed/16143792
http://dx.doi.org/10.1120/jacmp.v6i3.2054
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