4.6 Review

Metallic nanoparticle radiosensitization: The role of Monte Carlo simulations towards progress

期刊

RADIATION PHYSICS AND CHEMISTRY
卷 180, 期 -, 页码 -

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.radphyschem.2020.109294

关键词

Radiosensitization; Gold nanoparticle; Monte Carlo simulation; Dose enhancement; Radiotherapy

资金

  1. Iran's National Elites Foundation (INEF)

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Metallic nanoparticle radiosensitization is receiving significant attention for its potential to improve radiation therapy efficiency without harming surrounding normal tissues or requiring changes to radiation setups. Monte Carlo simulations have been instrumental in evaluating the physical effects during radioenhancement processes, leading to a better understanding of the underlying chemical and biological processes. Current challenges and future potentials of MC simulations in this field are also discussed.
Metallic nanoparticle radiosensitization (MNPR) is attracting a good deal of attention, promising enhanced efficiency target volume radiation therapy without escalation of damage to surrounding normal tissues, also devoid of modification to the irradiation setup. To study the process of DNA damage in MNPR, physical dose in the subcellular scale should be known. This, together with the lack of accurate measurement methods, has demanded micro and nanodosimetric calculations. Accordingly, Monte Carlo (MC) simulations have been supportive with evaluation of physical effects in the radioenhancement process, which together with experimental findings resulted in improved understanding of the underlying chemical and biological processes. This review discusses current progress in nanoparticle (NP) radiosensitization, summarizing findings from both experiment and MC simulation in respect of the various parameters that affect the efficiency of radioenhancement in photon and charged particle therapies. We describe the role of MC transport calculations in progress of NP radioenhancement and discuss the main perceptions achieved in use of MC simulations along with biological survival studies. Current challenges of MC simulations for the use in this field and future potentials are also discussed.

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