Robustness Analysis of Treatment Planning System for Proton Therapy

Proton radiotherapy represents one of the most advanced methods for treating treat- ment of cancer patients. Treatment with proton beams is a strategy therapy that is receiving considerable interest in the clinical field and in research. The most in- novative aspect of proton therapy is the ability to deposit the energy of ionizing radiation in a highly precise and finite way. This advantage, compared with other types of external radiation therapy, is due to the very nature of proton transport in matter. The protons release the greatest amount of energy at the end of their path through the matter. By adjusting the energy of the beam, it is therefore possible to target the tumor mass, significantly limiting the amount of the dose deposited in healthy tissues. Proton therapy is performed thanks to the beam generated by a particles accelerator. The cost and complexity of a facility, capable of generating a beam of protons at very high energies, remain two of the main obstacles to the spread of this oncology treatment technique. The treatment plan, performed at the beginning of therapy, is evaluated by models of inverse planning that allow the beam characteristics to be defined, in order to perform the correct irradiation of the target. The treatment plan is defined from the axial Computed Tomography (CT) scan of the patient and the dose of ionizing radiation intended to be deposited in diseased tissues. The analytical methods that are used, however, are sensitive to physical and physiological uncertainties that may occur in the patient during treatment sessions. It is possible, with the help of algo- rithms termed ’direct’ to verify the distribution of dose obtained from the treatment plan. It is possible to check that any uncertainties do not compromise the effective- ness of the therapy. The direct models are principally two: the analytical method and the method based on a simulation Monte Carlo. The purpose of this work is to evaluate the effects of uncertainties in the distribution effective dose within the domain. The perturbations are introduced by modifying the density values of the tissues of the patient. By acting on the characteristics of the CT scan, two perturbed scenarios are considered: one, in which the tissues are denser than actual ones, and the other, in which they are less dense. The objective is to verify, through the direct methods, with the same treatment plan, the pertur- bation of the dose distribution in the two scenarios in which the uncertainties on the density are introduced. In this way, it becomes possible to predict whether the treatment plan is still valid or whether it is compromised. In the second case, it will be necessary to make a new plan. Finally, the purpose is to compare the sensitivity of the direct methods used as a control tool. Starting from the characteristics of the two methods, it is necessary to understand which one is the most suitable for the simulation of cancer treatment.