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Radiobiological Outcomes, Microdosimetric Evaluations and Monte Carlo Predictions in Eye Proton Therapy

Authors :
Giada Petringa
Marco Calvaruso
Valeria Conte
Pavel Bláha
Valentina Bravatà
Francesco Paolo Cammarata
Giacomo Cuttone
Giusi Irma Forte
Otilija Keta
Lorenzo Manti
Luigi Minafra
Vladana Petković
Ivan Petrović
Selene Richiusa
Aleksandra Ristić Fira
Giorgio Russo
Giuseppe Antonio Pablo Cirrone
Source :
Applied Sciences, Vol 11, Iss 19, p 8822 (2021)
Publication Year :
2021
Publisher :
MDPI AG, 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.

Details

Language :
English
ISSN :
20763417
Volume :
11
Issue :
19
Database :
Directory of Open Access Journals
Journal :
Applied Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.072910e0542647618f76c8ef89e4414d
Document Type :
article
Full Text :
https://doi.org/10.3390/app11198822