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◆ Radiation and Environmental Biophysics2026-08-08· Monte Carlo method

Range of dose enhancement factor for gold nanoparticles in radiotherapy using Monte Carlo simulations

Wei Bo Li, Mario A. Bernal, Z. Francis

原始摘要(英文原文)· Original abstract
Abstract Gold nanoparticles (GNPs) have been widely investigated as radiosensitizers in preclinical radiotherapy studies and are now advancing into clinical trials. To enhance tumour targeting, various molecular vectors are conjugated with GNPs. The localized radiation energy deposited near GNPs mainly originates from photoelectrons, Auger electrons, x-ray fluorescence, and Compton electrons, resulting in higher tumour doses compared to conventional radiotherapy. Due to the nanometer-scale size of GNPs, the energy from secondary low-energy electrons is confined to nanometer to micrometer ranges, making direct dose measurements impractical. Monte Carlo (MC) simulations are therefore commonly employed to estimate absorbed dose distributions around GNPs under different experimental conditions. However, published MC results show significant variability due to diverse simulation parameters. This review presents a quantitative analysis of reported dose distributions and dose enhancement factors (DEFs) from MC simulations. It also discusses the range of physical radiation doses and DEFs for GNPs irradiated by various radiation types, including kV/MV x-rays, synchrotrons, electrons, protons, heavy ions, and therapeutic radionuclides. To support understanding of the dose enhancement mechanisms, the underlying physical interaction processes of these radiation types with water and gold are reviewed. The range of reported DEFs helps bridge the gap between physical dose enhancement and observed biological effects. Finally, we recommend a qualitative estimate of the contribution of chemical species produced by the GNPs interactions to the consequent enhanced biological effects. This allows total dose enhancement from GNPs in radiotherapy, considering physical and chemical aspects, to be estimated using MC simulations as a complement to experiments.
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