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Cell-Survival Fraction Estimation Based on the Probability Densities of Domain and Cell Nucleus Specific Energies Using Improved Microdosimetric Kinetic Models
https://repo.qst.go.jp/records/46396
https://repo.qst.go.jp/records/46396a1ece989-a4b9-40ae-979b-f5b7922ff076
Item type | 学術雑誌論文 / Journal Article(1) | |||||
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公開日 | 2012-09-26 | |||||
タイトル | ||||||
タイトル | Cell-Survival Fraction Estimation Based on the Probability Densities of Domain and Cell Nucleus Specific Energies Using Improved Microdosimetric Kinetic Models | |||||
言語 | ||||||
言語 | eng | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
資源タイプ | journal article | |||||
アクセス権 | ||||||
アクセス権 | metadata only access | |||||
アクセス権URI | http://purl.org/coar/access_right/c_14cb | |||||
著者 |
Sato, Tatsuhiko
× Sato, Tatsuhiko× Furusawa, Yoshiya× 古澤 佳也 |
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抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | Estimation of the survival fractions of cells irradiated with various particles over a wide linear energy transfer (LET) range is of great importance in the treatment planning of charged-particle therapy. Two computational models were developed for estimating the survival fractions on the basis of the concept of the microdosimetric kinetic (MK) model. They were designated as the double-stochastic microdosimetric kinetic (DSMK) and stochastic microdosimetric kinetic (SMK) models. The former model takes the stochastic natures of both domain and cell-nucleus specific energies into account, whereas the latter considers the stochastic natures of only cell-nucleus specific energy in order to reduce the computational time. The probability densities of the domain and cell-nucleus specific energies are the fundamental quantities for expressing survival fractions in these models. These densities are calculated using the microdosimetric and LET-estimator functions implemented in the Particle and Heavy Ion Transport code System (PHITS) in combination with the convolution or database method. Both the DSMK and SMK models can reproduce the measured survival fractions even for high-LET and high-dose irradiations, whereas the original MK model predicts lower values for these fractions due to the ignorance of the stochastic natures in the calculation. Our developed models are therefore capable of contributing to the better understanding of the mechanism of cell inactivation as well as improving the accuracy of the treatment planning of charged-particle therapy. | |||||
書誌情報 |
Radiation Research 巻 178, 号 4, p. 341-356, 発行日 2012-08 |
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ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 0033-7587 | |||||
DOI | ||||||
識別子タイプ | DOI | |||||
関連識別子 | 10.1667/rr2842.1 |