ArticleScientific reports2019
Evaluation of dose point kernel rescaling methods for nanoscale dose estimation around gold nanoparticles using Geant4 Monte Carlo simulations.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
7 citing papers in PubMed, 13 citations in OpenAlex.
- Monte Carlo study of gold nanoparticle-mediated radiosensitization effects using nanoscale cell model combined with fractal-based DNA model.Medical physics · 2025Article
- Nanoscale gold nanoparticle (GNP)-laden tumor cell model and its use for estimation of intracellular dose from GNP-induced secondary electrons.Medical physics · 2024Article
- Deep Learning-Based TEM Image Analysis for Fully Automated Detection of Gold Nanoparticles Internalized Within Tumor Cell.Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada · 2023Article
- Pancreatic tumor microenvironmental acidosis and hypoxia transform gold nanorods into cell-penetrant particles for potent radiosensitization.Science advances · 2022Article
- A detailed experimental and Monte Carlo analysis of gold nanoparticle dose enhancement using 6 MV and 18 MV external beam energies in a macroscopic scale.Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine · 2021Article
- Dose point kernels for 2,174 radionuclides.Medical physics · 2019Article
- Artificial intelligence in radiotherapy.Reports of practical oncology and radiotherapy : journal of Greatpoland Cancer Center in Poznan and Polish Society of Radiation OncologyReview
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
The absence of proper nanoscale experimental techniques to investigate the dose-enhancing properties of gold nanoparticles (GNPs) interacting with radiation has prompted the development of various Monte Carlo (MC)-based nanodosimetry techniques that generally require considerable computational knowledge, time and specific tools/platforms. Thus, this study investigated a hybrid computational framework, based on the electron dose point kernel (DPK) method, by combining Geant4 MC simulations with an analytical approach. This hybrid framework was applied to estimate the dose distributions around GNPs due to the secondary electrons emitted from GNPs irradiated by various photon sources. Specifically, the equivalent path length approximation was used to rescale the homogeneous DPKs for heterogeneous GNPs embedded in water/tissue. Compared with Geant4 simulations, the hybrid framework halved calculation time while utilizing fewer computer resources, and also resulted in mean discrepancies less than 20 and 5% for Yb-169 and 6 MV photon irradiation, respectively. Its appropriateness and computational efficiency in handling more complex cases were also demonstrated using an example derived from a transmission electron microscopy image of a cancer cell containing internalized GNPs. Overall, the currently proposed hybrid computational framework can be a practical alternative to full-fledged MC simulations, benefiting a wide range of GNP- and radiation-related applications.
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Registered trials
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