'Survival': a simulation toolkit introducing a modular approach for radiobiological evaluations in ion beam therapy. (5th April 2018)

• Record Type: Journal Article
• Authors: Manganaro, L; Russo, G; Bourhaleb, F; Fausti, F; Giordanengo, S; Monaco, V; Sacchi, R; Vignati, A; Cirio, R; Attili, A
• Is Part Of: Physics in medicine & biology. Volume 63:Number 8(2018:Apr.)
• Publication Date: 2018-04-05
• Subjects: RBE -- LEM -- MKM -- radiobiological modelling; Biophysics -- Periodicals; Medical physics -- Periodicals; 610.153
• DOI: 10.1088/1361-6560/aab697
• Languages: English
• ISSNs: 0031-9155

Abstract

Abstract: One major rationale for the application of heavy ion beams in tumour therapy is their increased relative biological effectiveness (RBE). The complex dependencies of the RBE on dose, biological endpoint, position in the field etc require the use of biophysical models in treatment planning and clinical analysis. This study aims to introduce a new software, named 'Survival', to facilitate the radiobiological computations needed in ion therapy. The simulation toolkit was written in C++ and it was developed with a modular architecture in order to easily incorporate different radiobiological models. The following models were successfully implemented: the local effect model (LEM, version I, II and III) and variants of the microdosimetric-kinetic model (MKM). Different numerical evaluation approaches were also implemented: Monte Carlo (MC) numerical methods and a set of faster analytical approximations. Among the possible applications, the toolkit was used to reproduce the RBE versus LET for different ions (proton, He, C, O, Ne) and different cell lines (CHO, HSG). Intercomparison between different models (LEM and MKM) and computational approaches (MC and fast approximations) were performed. The developed software could represent an important tool for the evaluation of the biological effectiveness of charged particles in ion beam therapy, in particular when coupled with treatment simulations. Its modular architecture facilitates benchmarking and inter-comparison between different models and evaluation approaches. The code is open source (GPL2 license) and available athttps://github.com/batuff/Survival .