Multiple levels of stochasticity accounted for in different radiation biophysical models: from physics to biology.

IF 2.1 4区 医学 Q2 BIOLOGY
Francesco G Cordoni, Marta Missiaggia, Chiara La Tessa, Emanuele Scifoni
{"title":"Multiple levels of stochasticity accounted for in different radiation biophysical models: from physics to biology.","authors":"Francesco G Cordoni,&nbsp;Marta Missiaggia,&nbsp;Chiara La Tessa,&nbsp;Emanuele Scifoni","doi":"10.1080/09553002.2023.2146230","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>In the present paper we investigate how some stochastic effects are included in a class of radiobiological models with particular emphasis on how such randomnesses reflect into the predicted cell survival curve.</p><p><strong>Materials and methods: </strong>We consider four different models, namely the <i>Generalized Stochastic Microdosimetric Model</i> GSM<sup>2</sup>, in its original full form, the <i>Dirac</i> GSM<sup>2</sup> the <i>Poisson</i> GSM<sup>2</sup><math></math> and the <i>Repair-Misrepair Model</i> (RMR). While GSM<sup>2</sup><math></math> and the RMR models are known in literature, the Dirac and the Poisson GSM<sup>2</sup><math><mi> </mi></math> have been newly introduced in this work. We further numerically investigate via Monte Carlo simulation of four different particle beams, how the proposed stochastic approximations reflect into the predicted survival curves. To achieve these results, we consider different ion species at energies of interest for therapeutic applications, also including a mixed field scenario.</p><p><strong>Results: </strong>We show how the <i>Dirac</i> GSM<sup>2</sup><math><mo>,</mo></math> the <i>Poisson</i> GSM<sup>2</sup><math></math> and the RMR can be obtained from the GSM<sup>2</sup><math></math> under suitable approximations on the stochasticity considered. We analytically derive the cell survival curve predicted by the four models, characterizing rigorously the high and low dose limits. We further study how the theoretical findings emerge also using Monte Carlo numerical simulations.</p><p><strong>Conclusions: </strong>We show how different models include different levels of stochasticity in the description of cellular response to radiation. This translates into different cell survival predictions depending on the radiation quality.</p>","PeriodicalId":14261,"journal":{"name":"International Journal of Radiation Biology","volume":null,"pages":null},"PeriodicalIF":2.1000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Radiation Biology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/09553002.2023.2146230","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOLOGY","Score":null,"Total":0}
引用次数: 5

Abstract

Purpose: In the present paper we investigate how some stochastic effects are included in a class of radiobiological models with particular emphasis on how such randomnesses reflect into the predicted cell survival curve.

Materials and methods: We consider four different models, namely the Generalized Stochastic Microdosimetric Model GSM2, in its original full form, the Dirac GSM2 the Poisson GSM2 and the Repair-Misrepair Model (RMR). While GSM2 and the RMR models are known in literature, the Dirac and the Poisson GSM2  have been newly introduced in this work. We further numerically investigate via Monte Carlo simulation of four different particle beams, how the proposed stochastic approximations reflect into the predicted survival curves. To achieve these results, we consider different ion species at energies of interest for therapeutic applications, also including a mixed field scenario.

Results: We show how the Dirac GSM2, the Poisson GSM2 and the RMR can be obtained from the GSM2 under suitable approximations on the stochasticity considered. We analytically derive the cell survival curve predicted by the four models, characterizing rigorously the high and low dose limits. We further study how the theoretical findings emerge also using Monte Carlo numerical simulations.

Conclusions: We show how different models include different levels of stochasticity in the description of cellular response to radiation. This translates into different cell survival predictions depending on the radiation quality.

在不同的辐射生物物理模型中考虑了多重水平的随机性:从物理学到生物学。
目的:在本文中,我们研究了一些随机效应是如何包含在一类放射生物学模型中的,特别强调了这种随机性是如何反映到预测的细胞存活曲线中的。材料和方法:我们考虑了四种不同的模型,即原始完整形式的广义随机微剂量模型GSM2、狄拉克模型GSM2、泊松模型GSM2和修复-误修复模型(RMR)。虽然GSM2和RMR模型在文献中是已知的,但Dirac和泊松GSM2在这项工作中是新引入的。我们通过蒙特卡罗模拟进一步研究了四种不同粒子束的随机近似如何反映到预测的生存曲线中。为了获得这些结果,我们考虑了不同的离子种类在治疗应用的兴趣能量,也包括混合场场景。结果:我们展示了在考虑随机性的适当近似下,如何从GSM2得到狄拉克GSM2、泊松GSM2和RMR。我们分析地推导出了四种模型预测的细胞存活曲线,严格地描述了高、低剂量极限。我们还使用蒙特卡罗数值模拟进一步研究了理论结果是如何出现的。结论:我们展示了不同的模型如何在描述细胞对辐射的反应时包含不同水平的随机性。根据辐射质量的不同,这转化为不同的细胞存活预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
5.00
自引率
11.50%
发文量
142
审稿时长
3 months
期刊介绍: The International Journal of Radiation Biology publishes original papers, reviews, current topic articles, technical notes/reports, and meeting reports on the effects of ionizing, UV and visible radiation, accelerated particles, electromagnetic fields, ultrasound, heat and related modalities. The focus is on the biological effects of such radiations: from radiation chemistry to the spectrum of responses of living organisms and underlying mechanisms, including genetic abnormalities, repair phenomena, cell death, dose modifying agents and tissue responses. Application of basic studies to medical uses of radiation extends the coverage to practical problems such as physical and chemical adjuvants which improve the effectiveness of radiation in cancer therapy. Assessment of the hazards of low doses of radiation is also considered.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信