RESUMO
PURPOSE: Special properties and recent advances in the synthesis and biomolecular functionalization of gold nanoparticles (GNPs) have led to the evolution of their use in biomedical applications such as photon radiotherapy. Simulation-based studies on the effect of various parameters that govern the dose enhancement due to utilizing GNPs have facilitated the progress of knowledge in this field. Due to their flexibility and easier accessibility compared with experimental works, simulations have the potential to be considered for pre-clinical tests and, therefore, should be close to the realistic conditions as much as possible. MATERIALS AND METHODS: To this aim, the present work investigates the effect of the presence of GNPs that are accumulated in the cytoplasm of the constituent cells in healthy tissues of a human eye phantom, inspired by the published experimental results which report that non-target tissues also receive the drugs containing GNPs. The GNPs' concentrations are assumed to decrease by moving from the tumor toward the depth of the phantom through a suggested pattern. The MCNPX Monte Carlo code is used for the simulations. RESULTS: The results show that for four concentrations tested, the dose enhancement factor in the shallower layer reaches 6, and decreases to 1.2 in the last layer. The dose enhancements are also examined for critical structures of the iris, cornea, sclera, and lens, showing maximum deviations of about 3 to 200% compared with the absence of GNPs in the healthy tissue. Considering the reported doses to the lens by clinical institutions, the effect of penetration of GNPs to deep layers on treatment time is also investigated. CONCLUSIONS: The results show that the penetration of GNPs from the tumor toward healthy tissues strongly controls the dose enhancement over the various eye structures and emphasizes the importance of modeling the GNPs' distribution in the medium on the overall dose enhancement. Considering the current challenges in the clinical use of GNPs, more effort needs to be made to reach an effective endpoint in treatment.
RESUMO
Occupational radiation protection should be applied to the design of treatment rooms for various radiation therapy techniques, including BNCT, where escaping particles from the beam port of the beam shaping assembly (BSA) may reach the walls or penetrate through the entrance door. The focus of the present study is to design an alternative shielding material, other than the conventional material of lead, that can be considered as the material used in the door and be able to effectively absorb the BSA neutrons which have slowed down to the thermal energy range of < 1 eV after passing through the walls and the maze of the room. To this aim, a thermal neutron shield, composed of polymer composite and polyethylene, has been simulated using the Geant4 Monte Carlo code. The neutron flux and dose values were predicted using an artificial neural network (ANN), eliminating the need for time-consuming Monte Carlo simulations in all possible suggestions. Additionally, this technique enables simultaneous optimization of the parameters involved, which is more effective than the traditional sequential and separate optimization process. The results indicated that the optimized shielding material, chosen through ANN calculations that determined the appropriate thickness and weight percent of its compositions, can decrease the dose behind the door to lower than the allowable limit for occupational exposure. The stability of ANN was tested by considering uncertainties with the Gaussian distributions of random numbers to the testing data. The results are promising as they indicate that ANNs could be used as a reliable tool for accurately predicting the dosimetric results, providing a drastically powerful alternative approach to the time-consuming Monte Carlo simulations.
