Abstract ID: 67 MC codes and range monitoring in particle therapy: The case of secondary charged particles. (October 2017) - Muraro, S.; Battistoni, G.; De Lucia, E.; Mancini-Terracciano, C.; Marafini, M.; Mattei, I.; Mirabelli, R.; Sarti, A.; Sciubba, A.; Solfaroli Camillocci, E.; Toppi, M.; Traini, G.; et al.
Abstract : Particle therapy planning gets fundamental information from MC codes. Its millimetric precision needs the assurance of the successfulness of the treatment session. Different range monitoring techniques are under development exploiting secondary particles which are generated in the patient during the treatment: prompt gammas, annihilation gammas from beta+ induced activity, charged fragments. The yield of produced particles and their propagation in the human tissue must be studied with MC codes. In this contribution, in the framework of the INSIDE collaboration (Innovative Solutions for In-beam Dosimetry in hadrontherapy), the case of secondary charged fragments emission during the treatment is considered[1] . A detector named Dose Profiler (DP), able to track secondary charged fragments (mainly protons) emitted at large angles with respect to the beam direction, is under construction and test. The tracker is made by six layers (20 × 20 cm 2 ) of BCF-12 square scintillating fibres (500 μm) coupled to Silicon Photo-Multipliers, followed by two plastic scintillator layers of 6 mm thickness. The detector characterization with cosmic rays has been performed and a calibration data taking campaign with protons is currently undergoing. The attenuation of the secondary charged particles emission profile due to the crossed material is studied and parametrized with the FLUKA MC code. A full simulation of a treatment in a realistic patient-detector system and the secondary charged fragments reconstruction is presented. Track reconstruction is performed by means of a Kalman filter algorithm using the GenFit code. The on-line operation of DP requires the real-time reconstruction of the amount of material crossed in the patient by each detected proton. This task will be accomplished using FRED, a fast GPU-MC code.