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Radiobiological outcomes, microdosimetric evaluations and monte carlo predictions in eye proton therapy

Academic Article
Publication Date:
2021
abstract:
CATANA (Centro di AdroTerapia ed Applicazioni Nucleari Avanzate) was the first Italian protontherapy facility dedicated to the treatment of ocular neoplastic pathologies. It is in operation at the LNS Laboratories of the Italian Institute for Nuclear Physics (INFN-LNS) and to date, 500 patients have been successfully treated. Even though proton therapy has demonstrated success in clinical settings, there is still a need for more accurate models because they are crucial for the estimation of clinically relevant RBE values. Since RBE can vary depending on several physical and biological parameters, there is a clear need for more experimental data to generate predictions. Establishing a database of cell survival experiments is therefore useful to accurately predict the effects of irradiations on both cancerous and normal tissue. The main aim of this work was to compare RBE values obtained from in-vitro experimental data with predictions made by the LEM II (Local Effect Model), Monte Carlo approaches, and semi-empirical models based on LET experimental measurements. For this purpose, the 92.1 uveal melanoma and ARPE-19 cells derived from normal retinal pigmented epithelium were selected and irradiated in the middle of clinical SOBP of the CATANA proton therapy facility. The remarkable results show the potentiality of using microdosimetric spectrum, Monte Carlo simulations and LEM model to predict not only the RBE but also the survival curves.
Iris type:
01.01 Articolo in rivista
Keywords:
protontherapy; proton; RBE; radiobiology; microdosimetry; Geant4
List of contributors:
Calvaruso, Marco; Russo, Giorgio; Forte, GIUSI IRMA; Minafra, Luigi; Cammarata, FRANCESCO PAOLO; Bravata', Valentina
Authors of the University:
BRAVATA' VALENTINA
CAMMARATA FRANCESCO PAOLO
FORTE GIUSI IRMA
MINAFRA LUIGI
RUSSO GIORGIO
Handle:
https://iris.cnr.it/handle/20.500.14243/442566
Published in:
APPLIED SCIENCES
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