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Radiotoxicity in robotic radiosurgery: proposing a new quality index for optimizing the treatment planning of brain metastases
BACKGROUND: As irradiated brain volume at 12 Gy (V12) is a predictor for radionecrosis, the purpose of the study was to develop a model for Cyberknife (CK) plans that is able to predict the lowest achievable V12 at a given tumor size and prescription dose (PD), and to suggest a new quality index reg...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5561581/ https://www.ncbi.nlm.nih.gov/pubmed/28818094 http://dx.doi.org/10.1186/s13014-017-0867-z |
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author | Hellerbach, Alexandra Luyken, Klaus Hoevels, Mauritius Gierich, Andreas Rueß, Daniel Baus, Wolfgang W. Kocher, Martin Ruge, Maximilian I. Treuer, Harald |
author_facet | Hellerbach, Alexandra Luyken, Klaus Hoevels, Mauritius Gierich, Andreas Rueß, Daniel Baus, Wolfgang W. Kocher, Martin Ruge, Maximilian I. Treuer, Harald |
author_sort | Hellerbach, Alexandra |
collection | PubMed |
description | BACKGROUND: As irradiated brain volume at 12 Gy (V12) is a predictor for radionecrosis, the purpose of the study was to develop a model for Cyberknife (CK) plans that is able to predict the lowest achievable V12 at a given tumor size and prescription dose (PD), and to suggest a new quality index regarding V12 for optimizing the treatment planning of brain metastases. METHOD: In our model V12 was approximated as a spherical shell around the tumor volume. The radial distance between tumor surface and the 12 Gy isodose line was calculated using an approximation of the mean dose gradient in that area. Assuming a radially symmetrical irradiation from the upper half space, the dose distribution is given by the superposition of single fields. The dose profiles of a single field were derived by the measured off-center ratios (OCR) of the CK system. Using the calculated gradients of the sum dose profiles, minimal-V12 was estimated for different tumor sizes. The model calculation was tested using a phantom dataset and retrospectively applied on clinical cases. RESULTS: Our model allows the prediction of a best-case scenario for V12 at a given tumor size and PD which was confirmed by the results of the isocentric phantom plans. The results of the non-isocentric phantom plans showed that an optimization of coverage caused an increase in V12. This was in accordance with the results of the retrospective analysis. V12 s of the clinical cases were on average twice that of the predicted model calculation. A good agreement was achieved for plans with an optimal conformity index (nCI). Re-planning of cases with high V12 showed that lower values could be reached by selecting smaller collimators and by allowing a larger number of total MU and more MU per beam. CONCLUSIONS: V12 is a main parameter for assessing plan quality in terms of radiotoxicity. The index f12 defined as the ratio of V12 from the actual plan with the evaluated V12 from our model describes the conformity of an optimally possible V12 and thus can be used as a new quality index for optimizing treatment plans. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13014-017-0867-z) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5561581 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-55615812017-08-18 Radiotoxicity in robotic radiosurgery: proposing a new quality index for optimizing the treatment planning of brain metastases Hellerbach, Alexandra Luyken, Klaus Hoevels, Mauritius Gierich, Andreas Rueß, Daniel Baus, Wolfgang W. Kocher, Martin Ruge, Maximilian I. Treuer, Harald Radiat Oncol Research BACKGROUND: As irradiated brain volume at 12 Gy (V12) is a predictor for radionecrosis, the purpose of the study was to develop a model for Cyberknife (CK) plans that is able to predict the lowest achievable V12 at a given tumor size and prescription dose (PD), and to suggest a new quality index regarding V12 for optimizing the treatment planning of brain metastases. METHOD: In our model V12 was approximated as a spherical shell around the tumor volume. The radial distance between tumor surface and the 12 Gy isodose line was calculated using an approximation of the mean dose gradient in that area. Assuming a radially symmetrical irradiation from the upper half space, the dose distribution is given by the superposition of single fields. The dose profiles of a single field were derived by the measured off-center ratios (OCR) of the CK system. Using the calculated gradients of the sum dose profiles, minimal-V12 was estimated for different tumor sizes. The model calculation was tested using a phantom dataset and retrospectively applied on clinical cases. RESULTS: Our model allows the prediction of a best-case scenario for V12 at a given tumor size and PD which was confirmed by the results of the isocentric phantom plans. The results of the non-isocentric phantom plans showed that an optimization of coverage caused an increase in V12. This was in accordance with the results of the retrospective analysis. V12 s of the clinical cases were on average twice that of the predicted model calculation. A good agreement was achieved for plans with an optimal conformity index (nCI). Re-planning of cases with high V12 showed that lower values could be reached by selecting smaller collimators and by allowing a larger number of total MU and more MU per beam. CONCLUSIONS: V12 is a main parameter for assessing plan quality in terms of radiotoxicity. The index f12 defined as the ratio of V12 from the actual plan with the evaluated V12 from our model describes the conformity of an optimally possible V12 and thus can be used as a new quality index for optimizing treatment plans. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13014-017-0867-z) contains supplementary material, which is available to authorized users. BioMed Central 2017-08-17 /pmc/articles/PMC5561581/ /pubmed/28818094 http://dx.doi.org/10.1186/s13014-017-0867-z Text en © The Author(s). 2017 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 | Research Hellerbach, Alexandra Luyken, Klaus Hoevels, Mauritius Gierich, Andreas Rueß, Daniel Baus, Wolfgang W. Kocher, Martin Ruge, Maximilian I. Treuer, Harald Radiotoxicity in robotic radiosurgery: proposing a new quality index for optimizing the treatment planning of brain metastases |
title | Radiotoxicity in robotic radiosurgery: proposing a new quality index for optimizing the treatment planning of brain metastases |
title_full | Radiotoxicity in robotic radiosurgery: proposing a new quality index for optimizing the treatment planning of brain metastases |
title_fullStr | Radiotoxicity in robotic radiosurgery: proposing a new quality index for optimizing the treatment planning of brain metastases |
title_full_unstemmed | Radiotoxicity in robotic radiosurgery: proposing a new quality index for optimizing the treatment planning of brain metastases |
title_short | Radiotoxicity in robotic radiosurgery: proposing a new quality index for optimizing the treatment planning of brain metastases |
title_sort | radiotoxicity in robotic radiosurgery: proposing a new quality index for optimizing the treatment planning of brain metastases |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5561581/ https://www.ncbi.nlm.nih.gov/pubmed/28818094 http://dx.doi.org/10.1186/s13014-017-0867-z |
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