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タイトル: Microdosimetric Modeling of Biological Effectiveness for Boron Neutron Capture Therapy Considering Intra- and Intercellular Heterogeneity in 10B Distribution
著者: Sato, Tatsuhiko
Masunaga, Shin-ichiro  KAKEN_id
Kumada, Hiroaki
Hamada, Nobuyuki
著者名の別形: 佐藤, 達彦
増永, 慎一郎
熊田, 博明
浜田, 信行
キーワード: Cancer
Computational models
Drug development
発行日: 17-Jan-2018
出版者: Springer Nature
誌名: Scientific Reports
巻: 8
論文番号: 988
抄録: We here propose a new model for estimating the biological effectiveness for boron neutron capture therapy (BNCT) considering intra- and intercellular heterogeneity in 10B distribution. The new model was developed from our previously established stochastic microdosimetric kinetic model that determines the surviving fraction of cells irradiated with any radiations. In the model, the probability density of the absorbed doses in microscopic scales is the fundamental physical index for characterizing the radiation fields. A new computational method was established to determine the probability density for application to BNCT using the Particle and Heavy Ion Transport code System PHITS. The parameters used in the model were determined from the measured surviving fraction of tumor cells administrated with two kinds of 10B compounds. The model quantitatively highlighted the indispensable need to consider the synergetic effect and the dose dependence of the biological effectiveness in the estimate of the therapeutic effect of BNCT. The model can predict the biological effectiveness of newly developed 10B compounds based on their intra- and intercellular distributions, and thus, it can play important roles not only in treatment planning but also in drug discovery research for future BNCT.
記述: ホウ素中性子捕捉療法(BNCT)によるがん細胞殺傷効果の理論的な予測に成功 --新しい薬剤の開発や治療計画の最適化に役立つ数理モデルを開発--. 京都大学プレスリリース. 2018-02-06.
著作権等: © The Author(s) 2018. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
URI: http://hdl.handle.net/2433/229015
DOI(出版社版): 10.1038/s41598-017-18871-0
PubMed ID: 29343841
関連リンク: https://www.kyoto-u.ac.jp/ja/research-news/2018-02-06-0
出現コレクション:学術雑誌掲載論文等

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