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A unified multi‐activation (UMA) model of cell survival curves over the entire dose range for calculating equivalent doses in stereotactic body radiation therapy (SBRT), high dose rate brachytherapy (HDRB), and stereotactic radiosurgery (SRS)
PURPOSE: Application of linear‐quadratic (LQ) model to large fractional dose treatments is inconsistent with observed cell survival curves having a straight portion at high doses. We have proposed a unified multi‐activation (UMA) model to fit cell survival curves over the entire dose range that allo...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8248130/ https://www.ncbi.nlm.nih.gov/pubmed/33590493 http://dx.doi.org/10.1002/mp.14690 |
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author | Li, Shidong Miyamoto, Curtis Wang, Bin Giaddui, Tawfik Micaily, Bizhan Hollander, Andrew Weiss, Stephanie E. Weaver, Michael |
author_facet | Li, Shidong Miyamoto, Curtis Wang, Bin Giaddui, Tawfik Micaily, Bizhan Hollander, Andrew Weiss, Stephanie E. Weaver, Michael |
author_sort | Li, Shidong |
collection | PubMed |
description | PURPOSE: Application of linear‐quadratic (LQ) model to large fractional dose treatments is inconsistent with observed cell survival curves having a straight portion at high doses. We have proposed a unified multi‐activation (UMA) model to fit cell survival curves over the entire dose range that allows us to calculate EQD2 for hypofractionated SBRT, SRT, SRS, and HDRB. METHODS: A unified formula of cell survival [Formula: see text] using only the extrapolation number of n and the dose slope of D(o) was derived. Coefficient of determination, R(2), relative residuals, r, and relative experimental errors, e, normalized to survival fraction at each dose point, were calculated to quantify the goodness in modeling of a survival curve. Analytical solutions for α and β, the coefficients respectively describe the linear and quadratic parts of the survival curve, as well as the α/β ratio for the LQ model and EQD2 at any fractional doses were derived for tumor cells undertaking any fractionated radiation therapy. RESULTS: Our proposed model fits survival curves of in‐vivo and in‐vitro tumor cells with R(2) > 0.97 and r < e. The predicted α, β, and α/β ratio are significantly different from their values in the LQ model. Average EQD2 of 20‐Gy SRS of glioblastomas and melanomas metastatic to the brain, 10‐Gy × 5 SBRT of the lung cancer, and 7‐Gy × 5 HDRB of endometrial and cervical carcinomas are 36.7 (24.3–48.5), 114.1 (86.6–173.1),, and 45.5 (35–52.6) Gy, different from the LQ model estimates of 50.0, 90.0, and 49.6 Gy, respectively. CONCLUSION: Our UMA model validated through many tumor cell lines can fit cell survival curves over the entire dose range within their experimental errors. The unified formula theoretically indicates a common mechanism of cell inactivation and can estimate EQD2 at all dose levels. |
format | Online Article Text |
id | pubmed-8248130 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-82481302021-07-02 A unified multi‐activation (UMA) model of cell survival curves over the entire dose range for calculating equivalent doses in stereotactic body radiation therapy (SBRT), high dose rate brachytherapy (HDRB), and stereotactic radiosurgery (SRS) Li, Shidong Miyamoto, Curtis Wang, Bin Giaddui, Tawfik Micaily, Bizhan Hollander, Andrew Weiss, Stephanie E. Weaver, Michael Med Phys BIOLOGICAL PHYSICS AND RESPONSE PREDICTION PURPOSE: Application of linear‐quadratic (LQ) model to large fractional dose treatments is inconsistent with observed cell survival curves having a straight portion at high doses. We have proposed a unified multi‐activation (UMA) model to fit cell survival curves over the entire dose range that allows us to calculate EQD2 for hypofractionated SBRT, SRT, SRS, and HDRB. METHODS: A unified formula of cell survival [Formula: see text] using only the extrapolation number of n and the dose slope of D(o) was derived. Coefficient of determination, R(2), relative residuals, r, and relative experimental errors, e, normalized to survival fraction at each dose point, were calculated to quantify the goodness in modeling of a survival curve. Analytical solutions for α and β, the coefficients respectively describe the linear and quadratic parts of the survival curve, as well as the α/β ratio for the LQ model and EQD2 at any fractional doses were derived for tumor cells undertaking any fractionated radiation therapy. RESULTS: Our proposed model fits survival curves of in‐vivo and in‐vitro tumor cells with R(2) > 0.97 and r < e. The predicted α, β, and α/β ratio are significantly different from their values in the LQ model. Average EQD2 of 20‐Gy SRS of glioblastomas and melanomas metastatic to the brain, 10‐Gy × 5 SBRT of the lung cancer, and 7‐Gy × 5 HDRB of endometrial and cervical carcinomas are 36.7 (24.3–48.5), 114.1 (86.6–173.1),, and 45.5 (35–52.6) Gy, different from the LQ model estimates of 50.0, 90.0, and 49.6 Gy, respectively. CONCLUSION: Our UMA model validated through many tumor cell lines can fit cell survival curves over the entire dose range within their experimental errors. The unified formula theoretically indicates a common mechanism of cell inactivation and can estimate EQD2 at all dose levels. John Wiley and Sons Inc. 2021-02-16 2021-04 /pmc/articles/PMC8248130/ /pubmed/33590493 http://dx.doi.org/10.1002/mp.14690 Text en © 2021 The Authors. Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | BIOLOGICAL PHYSICS AND RESPONSE PREDICTION Li, Shidong Miyamoto, Curtis Wang, Bin Giaddui, Tawfik Micaily, Bizhan Hollander, Andrew Weiss, Stephanie E. Weaver, Michael A unified multi‐activation (UMA) model of cell survival curves over the entire dose range for calculating equivalent doses in stereotactic body radiation therapy (SBRT), high dose rate brachytherapy (HDRB), and stereotactic radiosurgery (SRS) |
title | A unified multi‐activation (UMA) model of cell survival curves over the entire dose range for calculating equivalent doses in stereotactic body radiation therapy (SBRT), high dose rate brachytherapy (HDRB), and stereotactic radiosurgery (SRS) |
title_full | A unified multi‐activation (UMA) model of cell survival curves over the entire dose range for calculating equivalent doses in stereotactic body radiation therapy (SBRT), high dose rate brachytherapy (HDRB), and stereotactic radiosurgery (SRS) |
title_fullStr | A unified multi‐activation (UMA) model of cell survival curves over the entire dose range for calculating equivalent doses in stereotactic body radiation therapy (SBRT), high dose rate brachytherapy (HDRB), and stereotactic radiosurgery (SRS) |
title_full_unstemmed | A unified multi‐activation (UMA) model of cell survival curves over the entire dose range for calculating equivalent doses in stereotactic body radiation therapy (SBRT), high dose rate brachytherapy (HDRB), and stereotactic radiosurgery (SRS) |
title_short | A unified multi‐activation (UMA) model of cell survival curves over the entire dose range for calculating equivalent doses in stereotactic body radiation therapy (SBRT), high dose rate brachytherapy (HDRB), and stereotactic radiosurgery (SRS) |
title_sort | unified multi‐activation (uma) model of cell survival curves over the entire dose range for calculating equivalent doses in stereotactic body radiation therapy (sbrt), high dose rate brachytherapy (hdrb), and stereotactic radiosurgery (srs) |
topic | BIOLOGICAL PHYSICS AND RESPONSE PREDICTION |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8248130/ https://www.ncbi.nlm.nih.gov/pubmed/33590493 http://dx.doi.org/10.1002/mp.14690 |
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