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  1. 原著論文

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/46396
a1ece989-a4b9-40ae-979b-f5b7922ff076
Item type 学術雑誌論文 / Journal Article(1)
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

WEKO 462186

Sato, Tatsuhiko

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Furusawa, Yoshiya

× Furusawa, Yoshiya

WEKO 462187

Furusawa, Yoshiya

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古澤 佳也

× 古澤 佳也

WEKO 462188

en 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
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
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