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Optimization of X-ray microplanar beam radiation therapy for deep-seated tumors by a simulation study.
Shinohara, Kunio; Kondoh, Takeshi; Nariyama, Nobuteru; Fujita, Hajime; Washio, Masakazu; Aoki, Yukimasa.
Afiliação
  • Shinohara K; Research Institute for Science and Engineering, Waseda University, Shinjuku-ku, Tokyo, Japan.
  • Kondoh T; Department of Neurosurgery, Kobe University Graduate School of Medicine, Kobe-shi, Hyogo, Japan Shinsuma General Hospital, Kobe-shi, Hyogo, Japan.
  • Nariyama N; Japan Synchrotron Radiation Research Institute, Sayo-gun, Hyogo, Japan.
  • Fujita H; Research Institute for Science and Engineering, Waseda University, Shinjuku-ku, Tokyo, Japan.
  • Washio M; Research Institute for Science and Engineering, Waseda University, Shinjuku-ku, Tokyo, Japan.
  • Aoki Y; Medical Corporation YUKOUKAI Clinic, Funabashi-shi, Chiba, Japan.
J Xray Sci Technol ; 22(3): 395-406, 2014.
Article em En | MEDLINE | ID: mdl-24865214
ABSTRACT
A Monte Carlo simulation was applied to study the energy dependence on the transverse dose distribution of microplanar beam radiation therapy (MRT) for deep-seated tumors. The distribution was found to be the peak (in-beam) dose and the decay from the edge of the beam down to the valley. The area below the same valley dose level (valley region) was decreased with the increase in the energy of X-rays at the same beam separation. To optimize the MRT, we made the following two assumptions the therapeutic gain may be attributed to the efficient recovery of normal tissue caused by the beam separation; and a key factor for the efficient recovery of normal tissue depends on the area size of the valley region. Based on these assumptions and the results of the simulated dose distribution, we concluded that the optimum X-ray energy was in the range of 100-300 keV depending on the effective peak dose to the target tumors and/or tolerable surface dose. In addition, we proposed parameters to be studied for the optimization of MRT to deep-seated tumors.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Simulação por Computador / Radioterapia Assistida por Computador / Modelos Biológicos / Neoplasias Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2014 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Simulação por Computador / Radioterapia Assistida por Computador / Modelos Biológicos / Neoplasias Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2014 Tipo de documento: Article