WEKO3
アイテム
Computational models and tools
https://repo.qst.go.jp/records/49269
https://repo.qst.go.jp/records/492699c80da38-a0d3-4126-9723-6994b9ce232a
| Item type | 学術雑誌論文 / Journal Article(1) | |||||
|---|---|---|---|---|---|---|
| 公開日 | 2018-11-20 | |||||
| タイトル | ||||||
| タイトル | Computational models and tools | |||||
| 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 |
Schuemann, Jan
× Schuemann, Jan× Bassler, Niels× 稲庭, 拓× Inaniwa, Taku |
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| 抄録 | ||||||
| 内容記述タイプ | Abstract | |||||
| 内容記述 | In this chapter, we describe two different methods, analytical (pencil beam) algorithms and Monte Carlo simulations, used to obtain the intended dose distributions in patients and evaluate their strengths and shortcomings. We discuss the difference between the prescribed physical dose and the biologically effective dose, the relative biological effectiveness (RBE) between ions and photons and the dependence of RBE on the linear energy transfer (LET). Lastly, we show how LET- or RBEbased optimization can be used to improve treatment plans and explore how the availability of multimodality ion beam facilities can be used to design a tumor-specific optimal treatment. | |||||
| 書誌情報 |
Medical Physics 巻 45, 号 11, p. e1073-e1085, 発行日 2018-11 |
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| 出版者 | ||||||
| 出版者 | Wiley | |||||
| ISSN | ||||||
| 収録物識別子タイプ | ISSN | |||||
| 収録物識別子 | 0094-2405 | |||||
| DOI | ||||||
| 識別子タイプ | DOI | |||||
| 関連識別子 | 10.1002/mp.12521 | |||||
| 関連サイト | ||||||
| 識別子タイプ | URI | |||||
| 関連識別子 | https://aapm.onlinelibrary.wiley.com/doi/full/10.1002/mp.12521 | |||||
