'Survival': a simulation toolkit introducing a modular approach for radiobiological evaluations in ion beam therapy

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 clinica...

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Bibliographic Details
Published in:Physics in medicine & biology 2018-04, Vol.63 (8), p.08NT01-08NT01
Main Authors: Manganaro, L, Russo, G, Bourhaleb, F, Fausti, F, Giordanengo, S, Monaco, V, Sacchi, R, Vignati, A, Cirio, R, Attili, A
Format: Article
Language:English
Subjects:
Humans
Kinetics
LEM
MKM
Monte Carlo Method
Proton Therapy - methods
radiobiological modelling
Radiobiology - methods
Radiotherapy Dosage
Radiotherapy Planning, Computer-Assisted
RBE
Relative Biological Effectiveness
Software
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Summary: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 at https://github.com/batuff/Survival.
ISSN:0031-9155
1361-6560
1361-6560
DOI:10.1088/1361-6560/aab697