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Optimization of X-ray microplanar beam radiation therapy for deep-seated tumors by a simulation study

Article type: Research Article

Authors: Shinohara, Kunio | Kondoh, Takeshi; | Nariyama, Nobuteru | Fujita, Hajime | Washio, Masakazu | Aoki, Yukimasa

Affiliations: Research Institute for Science and Engineering, Waseda University, Shinjuku-ku, Tokyo, Japan | Department of Neurosurgery, Kobe University Graduate School of Medicine, Kobe-shi, Hyogo, Japan | Shinsuma General Hospital, Kobe-shi, Hyogo, Japan | Japan Synchrotron Radiation Research Institute, Sayo-gun, Hyogo, Japan | Medical Corporation YUKOUKAI Clinic, Funabashi-shi, Chiba, Japan

Note: [] Corresponding author: Kunio Shinohara, Research Institute for Science and Engineering, Waseda University, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555, Japan. Tel.: +81 3 5286 3093; E-mail: [email protected]

Keywords: Microbeam radiation therapy, X-rays, Monte Carlo simulation, transverse dose distribution, energy dependence

DOI: 10.3233/XST-140434

Journal: Journal of X-Ray Science and Technology, vol. 22, no. 3, pp. 395-406, 2014

Received 14 September 2013
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Accepted 16 March 2014
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Published: 2014
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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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