ESTRO 2024 - Abstract Book

S4666

Physics - Optimisation, algorithms and applications for ion beam treatment planning

ESTR0 2024

[2] National Prostate Cancer Audit. The Clatterbridge Cancer Centre NHS Foundation Trust Provider Outcomes: Annual Report 2021. National Prostate Cancer Audit 2022. https://www.npca.org.uk/provider-results/trust/the clatterbridge-cancer-centre-nhs-foundation-trust/plot/?filter_timespan=2019-2020 (accessed November 15, 2022).

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Digital Poster

CELL: A user-friendly tool for computing cell survival based on radiation-induced DNA damage

Maria Pia Valenzuela 1 , Andrea Ciardiello 2 , Lucas Buvic 1 , Ignacio Espinoza 1 , Sophia Galvez 1 , Sebastian Salgado Maldonado 1 , Hugo Videla 1 , Andrea Russomando 1 1 Pontificia Universidad Católica de Chile, Physics, Santiago, Chile. 2 Istituto Nazionale di Física Nucleare, Physics, Rome, Italy

Purpose/Objective:

Radiation therapy utilizes ionizing radiation to target and eliminate tumor cells. Recent developments like particle therapies, have further improved the effectiveness of the treatments. However, gaining a comprehensive understanding of the biological effects of radiation, which would potentially impact treatment design, remains a challenge. To address this task, numerous research groups developed models that integrate experimental data with a deeper understanding of cellular process. Phenomenological models, primarily rooted in the linear-quadratic (LQ) model [1], aim to describe the physical and biological processes involved in cell killing. This highlights the importance of bridging biological and physical processes and the potentiality of Monte Carlo (MC) codes that allow the simulation of microscopic processes involved in radiation-DNA interactions [2]. By estimating DSB lesions occurrence and subsequent DNA damage, it becomes possible to predict cell survival probabilities. Since in the last years several theoretical models have been proposed, this work aimed to develop a framework to ease and streamline their study and comparison. The graphical user interface is written entirely in Python using PyQt5, allowing easy portability across various operating systems. To estimate the DNA damage caused by the ionizing radiation, the Monte Carlo Damage Simulation (MCDS [3]) algorithm is used. MCDS allows for the estimations of various factors, such as the yield of DSB and the complexity of lesion clusters. To assess cell survival, two models were pre-loaded in the system: the Wang's model [4] and the TLKM [5]. The interface allows the users to redefine the model parameters or to integrate other models according to their needs. If it is necessary to simulate a more complex setup, the system can read the output of generic MC codes such as FLUKA [6]. By extracting particle spectra at any point of interest, it becomes possible to estimate the corresponding survival probability. Material/Methods: