Cirio, R

Manganaro, L

Monaco, V

Sacchi, R

Vignati, A

English

Institutional Research Information System University of Turin

18 October 2023AperTO - Archivio Istituzionale Open Access dell'Università di TorinoOriginal Citation:Survival: a radiobiological simulation toolkit for ion beam therapyTerms of use:Open Access(Article begins on next page)Anyone can freely access the full text of works made available as "Open Access". Works made availableunder a Creative Commons license can be used according to the terms and conditions of said license. Useof all other works requires consent of the right holder (author or publisher) if not exempted from copyrightprotection by the applicable law.Availability:This is the author's manuscriptThis version is available http://hdl.handle.net/2318/1732089 since 2020-02-28T09:48:25ZSubmission type: Proffered Submission Title: “Survival”: a radiobiological simulation toolkit for ion beam therapy Category: Therapy Physics - Particle Therapy (Protons and Heavy Ions) Presentation mode: Oral Presentation   “Survival”: a radiobiological simulation toolkit for ion beam therapy  L. Manganaro​(1,2)​, G. Russo​(1,*)​, S. Giordanengo​(1)​, A. Vignati​(1)​, V. Monaco​(1,2)​, R. Sacchi​(1,2)​, F. Bourhaleb​(2,**)​, R. Cirio​(1,2)​, ​A. Attili​(1)  1. Istituto Nazionale di Fisica Nucleare, Sez. Torino, (Torino Italy) 2. Università degli Studi di Torino (Torino, Italy)  *  Now at EurixGROUP, Torino, Italy ** Now at I-See (Internet-Simulation Evaluation, Envision), Torino, Italy  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. 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 models. The following radiobiological models were successfully implemented: the Local Effect Model (LEM, version I, II and III) [1,2] and variants of the Microdosimetric Kinetic Model (MKM) [3,4]. Different numerical evaluation approaches were also implemented: Monte Carlo (MC) numerical methods and a set of faster analytical approximations. [5,6]  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.   Conclusions​: 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​.  1. M. Scholz et al., Rad Env Res (1997) 2. T. Elsasser et al., Int J Radiat Oncol (2008) 3. R.B. Hawkins, Int J Radiat Biol (1996) 4. R.B. Hawkins, Rad Res (2003) 5. M. Kramer et al., Phys Med Biol (2006) 6. Y. Kase et al., Phys Med Biol (2008) 7. L. Manganaro et al., Med Phys (2017)    

Survival: a radiobiological simulation toolkit for ion beam therapy

https://iris.unito.it/bitstream/2318/1732089/1/AAPM_2017_Attili_abstract.pdf

Survival: a radiobiological simulation toolkit for ion beam therapy

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