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Spatial distributions of dose enhancement around a gold nanoparticle at several depths of proton Bragg peak
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Spatial distributions of dose enhancement around a gold nanoparticle at several depths of proton Bragg peak

Jihun Kwon, Kenneth Sutherland, Takayuki Hashimoto, Hiroki Shirato, Hiroyuki Date 和 Fang-Hsin Chen
Nuclear instruments & methods in physics research. Section B, Beam interactions with materials and atoms, 卷.384, 頁碼.113-120
01/10/2016
Web of Science ID: WOS:000383941400016

摘要

Dose enhancement Gold nanoparticles Monte Carlo simulation Proton therapy Radial dose distribution Radiation sensitizer
Gold nanoparticles (GNPs) have been recognized as a promising candidate for a radiation sensitizer. A proton beam incident on a GNP can produce secondary electrons, resulting in an enhancement of the dose around the GNP. However, little is known about the spatial distribution of dose enhancement around the GNP, especially in the direction along the incident proton. The purpose of this study is to determine the spatial distribution of dose enhancement by taking the incident direction into account. Two steps of calculation were conducted using the Geant4 Monte Carlo simulation toolkit. First, the energy spectra of 100 and 195MeV protons colliding with a GNP were calculated at the Bragg peak and three other depths around the peak in liquid water. Second, the GNP was bombarded by protons with the obtained energy spectra. Radial dose distributions were computed along the incident beam direction. The spatial distributions of the dose enhancement factor (DEF) and subtracted dose (Dsub) were then evaluated. The spatial DEF distributions showed hot spots in the distal radial region from the proton beam axis. The spatial Dsub distribution isotropically spread out around the GNP. Low energy protons caused higher and wider dose enhancement. The macroscopic dose enhancement in clinical applications was also evaluated. The results suggest that the consideration of the spatial distribution of GNPs in treatment planning will maximize the potential of GNPs.

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