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Dependence and independence of survival parameters on linear energy transfer in cells and tissues

Carbon-ion radiotherapy has been used to treat more than 9000 cancer patients in the world since 1994. Spreading of the Bragg peak is necessary for carbon-ion radiotherapy, and is designed based on the linear–quadratic model that is commonly used for photon therapy. Our recent analysis using in vitr...

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Autores principales: Ando, Koichi, Goodhead, Dudley T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5137290/
https://www.ncbi.nlm.nih.gov/pubmed/27380803
http://dx.doi.org/10.1093/jrr/rrw058
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author Ando, Koichi
Goodhead, Dudley T.
author_facet Ando, Koichi
Goodhead, Dudley T.
author_sort Ando, Koichi
collection PubMed
description Carbon-ion radiotherapy has been used to treat more than 9000 cancer patients in the world since 1994. Spreading of the Bragg peak is necessary for carbon-ion radiotherapy, and is designed based on the linear–quadratic model that is commonly used for photon therapy. Our recent analysis using in vitro cell kills and in vivo mouse tissue reaction indicates that radiation quality affects mainly the alpha terms, but much less the beta terms, which raises the question of whether this is true in other biological systems. Survival parameters alpha and beta for 45 in vitro mammalian cell lines were obtained by colony formation after irradiation with carbon ions, fast neutrons and X-rays. Relationships between survival parameters and linear energy transfer (LET) below 100 keV/μm were obtained for 4 mammalian cell lines. Mouse skin reaction and tumor growth delay were measured after fractionated irradiation. The Fe-plot provided survival parameters of the tissue reactions. A clear separation between X-rays and high-LET radiation was observed for alpha values, but not for beta values. Alpha values/terms increased with increasing LET in any cells and tissues studied, while beta did not show a systematic change. We have found a puzzle or contradiction in common interpretations of the linear-quadratic model that causes us to question whether the model is appropriate for interpreting biological effectiveness of high-LET radiation up to 500 keV/μm, probably because of inconsistency in the concept of damage interaction. A repair saturation model proposed here was good enough to fit cell kill efficiency by radiation of wide-ranged LET. A model incorporating damage complexity and repair saturation would be suitable for heavy-ion radiotherapy.
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spelling pubmed-51372902016-12-06 Dependence and independence of survival parameters on linear energy transfer in cells and tissues Ando, Koichi Goodhead, Dudley T. J Radiat Res Regular Paper Carbon-ion radiotherapy has been used to treat more than 9000 cancer patients in the world since 1994. Spreading of the Bragg peak is necessary for carbon-ion radiotherapy, and is designed based on the linear–quadratic model that is commonly used for photon therapy. Our recent analysis using in vitro cell kills and in vivo mouse tissue reaction indicates that radiation quality affects mainly the alpha terms, but much less the beta terms, which raises the question of whether this is true in other biological systems. Survival parameters alpha and beta for 45 in vitro mammalian cell lines were obtained by colony formation after irradiation with carbon ions, fast neutrons and X-rays. Relationships between survival parameters and linear energy transfer (LET) below 100 keV/μm were obtained for 4 mammalian cell lines. Mouse skin reaction and tumor growth delay were measured after fractionated irradiation. The Fe-plot provided survival parameters of the tissue reactions. A clear separation between X-rays and high-LET radiation was observed for alpha values, but not for beta values. Alpha values/terms increased with increasing LET in any cells and tissues studied, while beta did not show a systematic change. We have found a puzzle or contradiction in common interpretations of the linear-quadratic model that causes us to question whether the model is appropriate for interpreting biological effectiveness of high-LET radiation up to 500 keV/μm, probably because of inconsistency in the concept of damage interaction. A repair saturation model proposed here was good enough to fit cell kill efficiency by radiation of wide-ranged LET. A model incorporating damage complexity and repair saturation would be suitable for heavy-ion radiotherapy. Oxford University Press 2016-11 2016-12-02 /pmc/articles/PMC5137290/ /pubmed/27380803 http://dx.doi.org/10.1093/jrr/rrw058 Text en © The Author 2016. Published by Oxford University Press on behalf of The Japan Radiation Research Society and Japanese Society for Radiation Oncology. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Regular Paper
Ando, Koichi
Goodhead, Dudley T.
Dependence and independence of survival parameters on linear energy transfer in cells and tissues
title Dependence and independence of survival parameters on linear energy transfer in cells and tissues
title_full Dependence and independence of survival parameters on linear energy transfer in cells and tissues
title_fullStr Dependence and independence of survival parameters on linear energy transfer in cells and tissues
title_full_unstemmed Dependence and independence of survival parameters on linear energy transfer in cells and tissues
title_short Dependence and independence of survival parameters on linear energy transfer in cells and tissues
title_sort dependence and independence of survival parameters on linear energy transfer in cells and tissues
topic Regular Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5137290/
https://www.ncbi.nlm.nih.gov/pubmed/27380803
http://dx.doi.org/10.1093/jrr/rrw058
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