An alternate model to describe the radio-potentializing effects of metal-based nanoparticles in radiation therapy

Background and objectives: The use of numerical models to predict radiosensitizing properties induced by metal-based nanoparticles (NPs) remains a real challenge in oncology. As most of the interactions due to radiation in biological environments originate from the secondary particles produced, we aim to formalize the relationship between these secondary particles, the irradiation dose and the NP concentration, to optimize mathematical and numerical tools for assessing NP-induced radiosensitization. Methods: GATE simulations were carried out to demonstrate a linear and affine relationship between specific radiophysical quantities, the irradiation dose and NP concentration. This research has led to an effective new method for predicting radiophysical events and the proposal of a new model for predicting cell death. This model was confirmed by experimental biological results obtained from a clonogenic assay performed on U251 and U87 glioblastoma cells after exposure to different concentrations of metal-based NPs. Results: We achieved an efficient method for quantifying certain radiophysical species (number of ionizations, photo- and compton electrons, bremsstrahlung and deposited dose) in the presence of NPs and at different irradiation doses. These findings have enabled us to suggest an extension of the linear quadratic (LQ) cell survival model. The LQ extension model was compared with experimental data both obtained in the laboratory and extracted from the literature. Conclusions: Radiophysical events provide valuable information for predicting the radiobiological and radiosensitizing effects of metal-based NPs in the context of X-ray photon irradiation. The extension of the LQ model we developed enables cell death to be predicted for different NP concentrations based on concentration effects alone.