Radiotherapy is one of the most useful modalities applied for tumor treatments, which use ionization radiation to eradicate the tumor, in major cases. Cells with normal oxygenation are more sensitive to the effects of ionizing radiation than those with hypoxic conditions, because O2 molecules react rapidly with free radicals, produced by irradiation, originating highly reactive radicals. Thus, the different concentrations of hypoxia in tumors can modulate the response of the irradiation through the radioresistance they present and consequently the success of the treatment. This chapter deals with the dose distributions in cranial tumors with different concentrations of hypoxia through a code based on Monte Carlo simulation.
Part of the book: Translational Research in Cancer
Monte Carlo simulations have been applied to determine and study different parameters that are challenged in experimental measurements, due to its capability in simulating the radiation transport with a probability distribution to interact with electrosferic electrons and some cases with the nucleus from an arbitrary material, which such particle track or history can carry out physical quantities providing data from a studied or investigating quantities. For this reason, simulation codes, based on Monte Carlo, have been proposed. The codes currently available are MNCP, EGSnrc, Geant, FLUKA, PENELOPE, as well as GAMOS and TOPAS. These simulation codes have become a tool for dose and dose distributions, essentially, but also for other applications such as design clinical, tool for commissioning of an accelerator linear, shielding, radiation protection, some radiobiologic aspect, treatment planning systems, prediction of data from results of simulation scenarios. In this chapter will be present some applications for radiotherapy procedures with use, specifically, megavoltage x-rays and electrons beams, in scenarios with homogeneous and anatomical phantoms for determining dose, dose distribution, as well dosimetric parameters through the PENELOPE and TOPAS code.
Part of the book: The Monte Carlo Methods