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A Simpler Energy Transfer Efficiency Model to Predict Relative Biological Effect for Protons and Heavier Ions

The aim of this work is to predict relative biological effectiveness (RBE) for protons and clinically relevant heavier ions, by using a simplified semi-empirical process based on rational expectations and published experimental results using different ion species. The model input parameters are: Z (...

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Autor principal: Jones, Bleddyn
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4531328/
https://www.ncbi.nlm.nih.gov/pubmed/26322274
http://dx.doi.org/10.3389/fonc.2015.00184
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author Jones, Bleddyn
author_facet Jones, Bleddyn
author_sort Jones, Bleddyn
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description The aim of this work is to predict relative biological effectiveness (RBE) for protons and clinically relevant heavier ions, by using a simplified semi-empirical process based on rational expectations and published experimental results using different ion species. The model input parameters are: Z (effective nuclear charge) and radiosensitivity parameters α(L) and β(L) of the control low linear energy transfer (LET) radiation. Sequential saturation processes are assumed for: (a) the position of the turnover point (LET(U)) for the LET–RBE relationship with Z, and (b) the ultimate value of α at this point (α(U)) being non-linearly related to α(L). Using the same procedure for β, on the logical assumption that the changes in β with LET, although smaller than α, are symmetrical with those of α, since there is symmetry of the fall off of LET–RBE curves with increasing dose, which suggests that LET(U) must be identical for α and β. Then, using iso-effective linear quadratic model equations, the estimated RBE is scaled between α(U) and α(L) and between β(U) and β(L) from for any input value of Z, α(L), β(L), and dose. The model described is fitted to the data of Barendsen (alpha particles), Weyrather et al. (carbon ions), and Todd for nine different ions (deuterons to Argon), which include variations in cell surviving fraction and dose. In principle, this new system can be used to complement the more complex methods to predict RBE with LET such as the local effect and MKM models which already have been incorporated into treatment planning systems in various countries. It would be useful to have a secondary check to such systems, especially to alert clinicians of potential risks by relatively easy estimation of relevant RBEs. In clinical practice, LET values smaller than LET(U) are mostly encountered, but the model extends to higher values beyond LET(U) for other purposes such as radiation, protection, and astrobiology. Considerable further research is required, perhaps in a dedicated international laboratory, using a basket of different models to determine what the best system or combination of systems will be to make proton and ion beam radiotherapy as safe as possible and to produce the best possible clinical results.
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spelling pubmed-45313282015-08-28 A Simpler Energy Transfer Efficiency Model to Predict Relative Biological Effect for Protons and Heavier Ions Jones, Bleddyn Front Oncol Oncology The aim of this work is to predict relative biological effectiveness (RBE) for protons and clinically relevant heavier ions, by using a simplified semi-empirical process based on rational expectations and published experimental results using different ion species. The model input parameters are: Z (effective nuclear charge) and radiosensitivity parameters α(L) and β(L) of the control low linear energy transfer (LET) radiation. Sequential saturation processes are assumed for: (a) the position of the turnover point (LET(U)) for the LET–RBE relationship with Z, and (b) the ultimate value of α at this point (α(U)) being non-linearly related to α(L). Using the same procedure for β, on the logical assumption that the changes in β with LET, although smaller than α, are symmetrical with those of α, since there is symmetry of the fall off of LET–RBE curves with increasing dose, which suggests that LET(U) must be identical for α and β. Then, using iso-effective linear quadratic model equations, the estimated RBE is scaled between α(U) and α(L) and between β(U) and β(L) from for any input value of Z, α(L), β(L), and dose. The model described is fitted to the data of Barendsen (alpha particles), Weyrather et al. (carbon ions), and Todd for nine different ions (deuterons to Argon), which include variations in cell surviving fraction and dose. In principle, this new system can be used to complement the more complex methods to predict RBE with LET such as the local effect and MKM models which already have been incorporated into treatment planning systems in various countries. It would be useful to have a secondary check to such systems, especially to alert clinicians of potential risks by relatively easy estimation of relevant RBEs. In clinical practice, LET values smaller than LET(U) are mostly encountered, but the model extends to higher values beyond LET(U) for other purposes such as radiation, protection, and astrobiology. Considerable further research is required, perhaps in a dedicated international laboratory, using a basket of different models to determine what the best system or combination of systems will be to make proton and ion beam radiotherapy as safe as possible and to produce the best possible clinical results. Frontiers Media S.A. 2015-08-11 /pmc/articles/PMC4531328/ /pubmed/26322274 http://dx.doi.org/10.3389/fonc.2015.00184 Text en Copyright © 2015 Jones. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Jones, Bleddyn
A Simpler Energy Transfer Efficiency Model to Predict Relative Biological Effect for Protons and Heavier Ions
title A Simpler Energy Transfer Efficiency Model to Predict Relative Biological Effect for Protons and Heavier Ions
title_full A Simpler Energy Transfer Efficiency Model to Predict Relative Biological Effect for Protons and Heavier Ions
title_fullStr A Simpler Energy Transfer Efficiency Model to Predict Relative Biological Effect for Protons and Heavier Ions
title_full_unstemmed A Simpler Energy Transfer Efficiency Model to Predict Relative Biological Effect for Protons and Heavier Ions
title_short A Simpler Energy Transfer Efficiency Model to Predict Relative Biological Effect for Protons and Heavier Ions
title_sort simpler energy transfer efficiency model to predict relative biological effect for protons and heavier ions
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4531328/
https://www.ncbi.nlm.nih.gov/pubmed/26322274
http://dx.doi.org/10.3389/fonc.2015.00184
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