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TOPAS-NBio: A Monte Carlo Simulation Toolkit for Nanometer-Scale Radiobiology

J Schuemann1*, A McNamara1 , J Ramos-Mendez2 , J Perl3 , K Held1 , H Paganetti1 , S Incerti4 , B Faddegon2 , (1) Massachusetts General Hospital & Harvard Medical School, Boston, MA, (2) University of California San Francisco, San Francisco, CA, (3) Stanford Linear Accelerator Center, Menlo Park, CA, (4) CENBG, CNRS, Bordeaux, France

Presentations

(Monday, 7/15/2019) 4:30 PM - 6:00 PM

Room: 301

Purpose: To make nanometer-scale Monte Carlo (MC) simulations for radiobiology experiments more accessible to biologists and physicists, with interest in biology, by removing the hurdle of requiring programming expertise.

Methods: The MC method has been successfully employed to simulate radiotherapy down to the cellular scale. In order to understand how energy deposition within irradiated cells (physics) connects via molecular reactions (chemistry) to cell kill/repair (biology), one has to understand how damage and repair of cellular components is linked to frequencies of energy depositions in sub-cellular targets such as DNA. MC simulations offer a unique tool to explore these effects. The TOPAS MC system is used in radiation therapy and played a significant role in making MC simulations widely available for proton therapy related research. While TOPAS provides detailed simulations of patient scale properties, the fundamental unit of the biological response to radiation is a cell. We used the TOPAS framework to develop a track-structure MC system layered on top of the Geant4/Geant4-DNA MC toolkit.

Results: We develop TOPAS-nBio, an extension of TOPAS dedicated to advance understanding of radiobiological effects at the (sub-)cellular, (i.e., the cellular and sub- cellular) scale. It includes detailed biological geometries, such as various DNA models, mitochondria and cells (e.g. fibroblasts or neurons). Two implementations of chemistry can be used with up to 72 reactions classified into 6 types between neutral and charged species. We reproduced time-dependent G-values within experimental errors for •OH, e-aq for H₂O₂ as well as DNA damage in plasmids within 50%. The physical and chemical simulations depict direct and indirect damages to cells which are propagated using mechanistic models of DNA repair kinetics.

Conclusion: TOPAS-nBio promises to advance our understanding of the fundamental processes within a cell immediately after radiation induced damages, aiming to close the gap between physics and biology.

Keywords

Monte Carlo, Radiobiology, Software

Taxonomy

TH- Radiobiology(RBio)/Biology(Bio): RBio- general

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