Veronica Ferrero1,2, Giovanni Visonà1, Federico Dalmasso1,2, Andrea Gobbato1,2, Piergiorgio Cerello2, Lidia Strigari3, Sonja Visentin2,4, Andrea Attili2. 1. Physics Department, Università degli Studi di Torino, Torino, Italy. 2. Istituto Nazionale di Fisica Nucleare (INFN), Torino, Italy. 3. Laboratory of Medical Physics and Expert Systems, National Cancer Institute Regina Elena, Roma, Italy. 4. Molecular Biotechnology and Health Sciences Department, Università degli Studi di Torino, Torino, Italy.
Abstract
PURPOSE: Gold nanoparticles (GNPs) are being proposed in combination with radiotherapy to improve tumor control. However, the exact mechanisms underlying GNP radiosensitization are yet to be understood, thus, we present a new approach to estimate the nanoparticle-driven increase in radiosensitivity. METHODS: A stochastic radiobiological model, derived from the Local Effect Model (LEM), was coupled with Monte Carlo simulations to estimate the increase in radiosensitivity produced by the interactions between photons and GNPs at nanometric scale. The model was validated using in vitro survival data of MDA-MB-231 breast cancer cells containing different concentrations of 2 nm diameter GNPs receiving different doses using 160 kVp, 6 MV, and 15 MV photons. A closed analytical formulation of the model was also derived and a study of RBE and TCP behavior was conducted. RESULTS: Results support the increased radiosensitivity due to GNP-driven dose inhomogeneities on a nanometric scale. The model is in good agreement with experimental clonogenic survival assays for 160 kVp, 6 MV, and 15 MV photons. The model suggests a RBE and TCP enhancement when lower energies and lower doses per fraction are used in the presence of GNPs. CONCLUSIONS: The evolution of the local effect model was implemented to assess cellular radiosensitization in the presence of GNPs and then validated with in vitro data. The model provides a useful framework to estimate the nanoparticle-driven radiosensitivity in treatment irradiations and could be applied to real clinical treatment predictions (described in a second part of this paper).
PURPOSE: Gold nanoparticles (GNPs) are being proposed in combination with radiotherapy to improve tumor control. However, the exact mechanisms underlying GNP radiosensitization are yet to be understood, thus, we present a new approach to estimate the nanoparticle-driven increase in radiosensitivity. METHODS: A stochastic radiobiological model, derived from the Local Effect Model (LEM), was coupled with Monte Carlo simulations to estimate the increase in radiosensitivity produced by the interactions between photons and GNPs at nanometric scale. The model was validated using in vitro survival data of MDA-MB-231 breast cancer cells containing different concentrations of 2 nm diameter GNPs receiving different doses using 160 kVp, 6 MV, and 15 MV photons. A closed analytical formulation of the model was also derived and a study of RBE and TCP behavior was conducted. RESULTS: Results support the increased radiosensitivity due to GNP-driven dose inhomogeneities on a nanometric scale. The model is in good agreement with experimental clonogenic survival assays for 160 kVp, 6 MV, and 15 MV photons. The model suggests a RBE and TCP enhancement when lower energies and lower doses per fraction are used in the presence of GNPs. CONCLUSIONS: The evolution of the local effect model was implemented to assess cellular radiosensitization in the presence of GNPs and then validated with in vitro data. The model provides a useful framework to estimate the nanoparticle-driven radiosensitivity in treatment irradiations and could be applied to real clinical treatment predictions (described in a second part of this paper).
Authors: Jeremy M C Brown; Gerard G Hanna; Nathanael Lampe; Balder Villagomez-Bernabe; James R Nicol; Jonathan A Coulter; Fred J Currell Journal: Cancer Nanotechnol Date: 2018-11-09
Authors: Jeffrey R Ashton; Katherine D Castle; Yi Qi; David G Kirsch; Jennifer L West; Cristian T Badea Journal: Theranostics Date: 2018-02-12 Impact factor: 11.600