Monte Carlo simulations of nanodosimetry and radiolytic species production for monoenergetic proton and electron beams: Benchmarking of GEANT4-DNA and LPCHEM codes

Radiosensitization with metallic nanoparticles under MeV proton beams: local dose enhancement

In addition to specific dosimetric properties of protons, their higher biological effectiveness makes them superior to X-rays and gamma radiation, in radiation therapy. In recent years, enrichment of tumours with metallic nanoparticles as radiosensitizer agents has generated high interest, with several studies attempting to confirm the efficacy of nanoparticles in proton therapy. In the present study Geant4 Monte Carlo (MC) code was used to quantify the increased nanoscopic dose deposition of 50 nm metallic nanoparticles including gold, bismuth, iridium, and gadolinium in water upon exposure to 5, 25, and 50 MeV protons. Dose enhancement factors, radial dose distributions in nano-scale, as well as secondary electron and photon energy spectra were calculated for the studied nanoparticles and proton beams. The obtained results demonstrated that in the presence of metallic nanoparticles an increase in proton energy leads to a decrease in secondary electron and photon production yield. Additionally, an increase in the radial dose enhancement factor from 1.4 to 16 was calculated for the studied nanoparticles when the proton energy was increased from 5 to 50 MeV. It is concluded that the dosimetric advantages of proton beams could be improved significantly in the presence of metallic nanoparticles.

Estimate of the Biological Dose in Hadrontherapy Using GATE

For the evaluation of the biological effects, Monte Carlo toolkits were used to provide an RBE-weighted dose using databases of survival fraction coefficients predicted through biophysical models. Biophysics models, such as the mMKM and NanOx models, have previously been developed to estimate a biological dose. Using the mMKM model, we calculated the saturation corrected dose mean specific energy z1D* (Gy) and the dose at 10% D10 for human salivary gland (HSG) cells using Monte Carlo Track Structure codes LPCHEM and Geant4-DNA, and compared these with data from the literature for monoenergetic ions. These two models were used to create databases of survival fraction coefficients for several ion types (hydrogen, carbon, helium and oxygen) and for energies ranging from 0.1 to 400 MeV/n. We calculated α values as a function of LET with the mMKM and the NanOx models, and compared these with the literature. In order to estimate the biological dose for SOBPs, these databases were used with a Monte Carlo toolkit. We considered GATE, an open-source software based on the GEANT4 Monte Carlo toolkit. We implemented a tool, the BioDoseActor, in GATE, using the mMKM and NanOx databases of cell survival predictions as input, to estimate, at a voxel scale, biological outcomes when treating a patient. We modeled the HIBMC 320 MeV/u carbon-ion beam line. We then tested the BioDoseActor for the estimation of biological dose, the relative biological effectiveness (RBE) and the cell survival fraction for the irradiation of the HSG cell line. We then tested the implementation for the prediction of cell survival fraction, RBE and biological dose for the HIBMC 320 MeV/u carbon-ion beamline. For the cell survival fraction, we obtained satisfying results. Concerning the prediction of the biological dose, a 10% relative difference between mMKM and NanOx was reported.