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A broad scope knowledge based model for optimization of VMAT in esophageal cancer: validation and assessment of plan quality among different treatment centers
BACKGROUND: To evaluate the performance of a broad scope model-based optimisation process for volumetric modulated arc therapy applied to esophageal cancer. METHODS AND MATERIALS: A set of 70 previously treated patients in two different institutions, were selected to train a model for the prediction...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4628288/ https://www.ncbi.nlm.nih.gov/pubmed/26521015 http://dx.doi.org/10.1186/s13014-015-0530-5 |
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author | Fogliata, Antonella Nicolini, Giorgia Clivio, Alessandro Vanetti, Eugenio Laksar, Sarbani Tozzi, Angelo Scorsetti, Marta Cozzi, Luca |
author_facet | Fogliata, Antonella Nicolini, Giorgia Clivio, Alessandro Vanetti, Eugenio Laksar, Sarbani Tozzi, Angelo Scorsetti, Marta Cozzi, Luca |
author_sort | Fogliata, Antonella |
collection | PubMed |
description | BACKGROUND: To evaluate the performance of a broad scope model-based optimisation process for volumetric modulated arc therapy applied to esophageal cancer. METHODS AND MATERIALS: A set of 70 previously treated patients in two different institutions, were selected to train a model for the prediction of dose-volume constraints. The model was built with a broad-scope purpose, aiming to be effective for different dose prescriptions and tumour localisations. It was validated on three groups of patients from the same institution and from another clinic not providing patients for the training phase. Comparison of the automated plans was done against reference cases given by the clinically accepted plans. RESULTS: Quantitative improvements (statistically significant for the majority of the analysed dose-volume parameters) were observed between the benchmark and the test plans. Of 624 dose-volume objectives assessed for plan evaluation, in 21 cases (3.3 %) the reference plans failed to respect the constraints while the model-based plans succeeded. Only in 3 cases (<0.5 %) the reference plans passed the criteria while the model-based failed. In 5.3 % of the cases both groups of plans failed and in the remaining cases both passed the tests. CONCLUSIONS: Plans were optimised using a broad scope knowledge-based model to determine the dose-volume constraints. The results showed dosimetric improvements when compared to the benchmark data. Particularly the plans optimised for patients from the third centre, not participating to the training, resulted in superior quality. The data suggests that the new engine is reliable and could encourage its application to clinical practice. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13014-015-0530-5) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4628288 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-46282882015-11-01 A broad scope knowledge based model for optimization of VMAT in esophageal cancer: validation and assessment of plan quality among different treatment centers Fogliata, Antonella Nicolini, Giorgia Clivio, Alessandro Vanetti, Eugenio Laksar, Sarbani Tozzi, Angelo Scorsetti, Marta Cozzi, Luca Radiat Oncol Methodology BACKGROUND: To evaluate the performance of a broad scope model-based optimisation process for volumetric modulated arc therapy applied to esophageal cancer. METHODS AND MATERIALS: A set of 70 previously treated patients in two different institutions, were selected to train a model for the prediction of dose-volume constraints. The model was built with a broad-scope purpose, aiming to be effective for different dose prescriptions and tumour localisations. It was validated on three groups of patients from the same institution and from another clinic not providing patients for the training phase. Comparison of the automated plans was done against reference cases given by the clinically accepted plans. RESULTS: Quantitative improvements (statistically significant for the majority of the analysed dose-volume parameters) were observed between the benchmark and the test plans. Of 624 dose-volume objectives assessed for plan evaluation, in 21 cases (3.3 %) the reference plans failed to respect the constraints while the model-based plans succeeded. Only in 3 cases (<0.5 %) the reference plans passed the criteria while the model-based failed. In 5.3 % of the cases both groups of plans failed and in the remaining cases both passed the tests. CONCLUSIONS: Plans were optimised using a broad scope knowledge-based model to determine the dose-volume constraints. The results showed dosimetric improvements when compared to the benchmark data. Particularly the plans optimised for patients from the third centre, not participating to the training, resulted in superior quality. The data suggests that the new engine is reliable and could encourage its application to clinical practice. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13014-015-0530-5) contains supplementary material, which is available to authorized users. BioMed Central 2015-10-31 /pmc/articles/PMC4628288/ /pubmed/26521015 http://dx.doi.org/10.1186/s13014-015-0530-5 Text en © Fogliata et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Methodology Fogliata, Antonella Nicolini, Giorgia Clivio, Alessandro Vanetti, Eugenio Laksar, Sarbani Tozzi, Angelo Scorsetti, Marta Cozzi, Luca A broad scope knowledge based model for optimization of VMAT in esophageal cancer: validation and assessment of plan quality among different treatment centers |
title | A broad scope knowledge based model for optimization of VMAT in esophageal cancer: validation and assessment of plan quality among different treatment centers |
title_full | A broad scope knowledge based model for optimization of VMAT in esophageal cancer: validation and assessment of plan quality among different treatment centers |
title_fullStr | A broad scope knowledge based model for optimization of VMAT in esophageal cancer: validation and assessment of plan quality among different treatment centers |
title_full_unstemmed | A broad scope knowledge based model for optimization of VMAT in esophageal cancer: validation and assessment of plan quality among different treatment centers |
title_short | A broad scope knowledge based model for optimization of VMAT in esophageal cancer: validation and assessment of plan quality among different treatment centers |
title_sort | broad scope knowledge based model for optimization of vmat in esophageal cancer: validation and assessment of plan quality among different treatment centers |
topic | Methodology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4628288/ https://www.ncbi.nlm.nih.gov/pubmed/26521015 http://dx.doi.org/10.1186/s13014-015-0530-5 |
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