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Monte Carlo Simulation of Dose Enhancement in Gold Nanoparticle Mediated Radiation Therapy

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S BASHIR

S Bashir1 , Z Koreshi2*, (1) Preston University, Islamabad, Pakistan, (2) Air University, Islamabad, Pakistan

Presentations

SU-I-GPD-T-659 (Sunday, July 30, 2017) 3:00 PM - 6:00 PM Room: Exhibit Hall


Purpose: This work is carried out to estimate radiation dose delivered to tumor cells for inducing hyperthermia, and subsequent apoptosis, by injecting gold nanoparticles (GNPs) through nano-sized fenestrations in cancer cells. It is aimed to provide optimal parameters for increasing the efficacy of radiation brachytherapy by tuning properties of nanoparticles.

Methods: Monte Carlo (MC) simulation, using MCNP5, is carried out for simulating radiation transport, from radiation ‘seeds’ implanted in the vicinity of cancer cells, into the tissue injected with GNPs to estimate the energy deposited in GNPs by the incident radiation. Further, the sensitivity of cell density on the energy deposition is estimated as a perturbation by sampling first and second derivatives from a single MC simulation.

Results: Results are obtained from MCNP5 for energy deposition using a number of radiation sources: Yb169, Pd103, I125, Ir192 and Te99, with concentric shell GNPs of gold (thickness 2-20 nm) on silicon core of 100nm. It is shown that for each source there is a ‘best’ or optimal size of GNP for which the deposition is maximum. The effect of cell density on deposition has also been obtained, over 20% density variation, using second-order perturbation estimates.

Conclusion: From an MC simulation, it has been found that the optimal size of spherical GNP shells depends on the source energy, and has to be ‘tuned’ with the plasmon resonance frequency by controlling the size of the shells. These are well within the fenestration dimensions. It is further concluded that there is slight variation in the deposition with small perturbations in the cell density. For this, Monte Carlo perturbation runs can greatly reduce the computational effort to obtain reliable MC estimates. Thus, effective use of nanotechnology for radiation oncology offers vast improvements in cancer therapy by the use of optimally designed GNPs.


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