Program Information
Survival: A Radiobiological Simulation Toolkit for Ion Beam Therapy
L Manganaro1,2 , G Russo1,3 , S Giordanengo2 , A Vignati2 , V Monaco1,2 , R Sacchi1,2 , F Bourhaleb1,4 , R Cirio1,2 , A Attili9*, (1) Universita' degli Studi di Torino, Torino, Italy, (2) Istituto Nazionale di Fisica Nucleare, sez. Torino, Torino, Italy, (3) now at: EurixGROUP, Torino, Italy, (4) now at: I-See (Internet-Simulation Evaluation, Envision), Torino, Italy
Presentations
SU-I-GPD-T-105 (Sunday, July 30, 2017) 3:00 PM - 6:00 PM Room: Exhibit Hall
Purpose: One major rationale for the application of heavy ion beams in tumor therapy is their increased relative biological effectiveness (RBE). The complex dependencies of RBE on the dose, biological endpoint, position in the field etc. require the use of biophysical models in planning and clinical analysis. This study aims at introducing a new software, named “Survival”, to facilitate the radiobiological computations needed in ion therapy.
Methods: The proposed code 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) [M. Scholz et al., Rad Env Res (1997); T. Elsasser et al., Int J Radiat Oncol (2008)] and variants of the Microdosimetric Kinetic Model (MKM) [R.B. Hawkins, Int J Radiat Biol (1996); R.B. Hawkins, Rad Res (2003)]. Different numerical evaluation approaches were also implemented: Monte Carlo (MC) numerical methods and a set of faster analytical approximations. [M. Kramer et al., Phys Med Biol (2006); Y. Kase et al., Phys Med Biol (2008); L. Manganaro et al., Med Phys (2017)]
Results: As examples of possible applications, the toolkit was used to reproduce the RBE versus LET for different Ions (proton, He, C, O, N) and different cell lines (CHO, HSG). Intercomparison between different models (LEM and MKM) and computational approaches (MC and fast approximations) were performed.
Conclusion: 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 intercomparison between different models and evaluation approaches. The code is open source (GPL2 license) and can be downloaded at https://github.com/batuff/Survival.
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