Physics of ion beam cancer therapy: a multi-scale approach

We propose a multi-scale approach to understand the physics related to ion-beam cancer therapy. It allows the calculation of the probability of DNA damage as a result of irradiation of tissues with energetic ions, up to 430 MeV/u. This approach covers different scales, starting from the large scale, defined by the ion stopping, followed by a smaller scale, defined by secondary electrons and radicals, and ending with the shortest scale, defined by interactions of secondaries with the DNA. We present calculations of the probabilities of single and double strand breaks of DNA, suggest a way to further expand such calculations, and also make some estimates for glial cells exposed to radiation.Comment: 18 pag,5 fig, submitted to PR

An Artificial Intelligence-based model for cell killing prediction: development, validation and explainability analysis of the ANAKIN model

The present work develops ANAKIN: an Artificial iNtelligence bAsed model for (radiation induced) cell KIlliNg prediction. ANAKIN is trained and tested over 513 cell survival experiments with different types of radiation contained in the publicly available PIDE database. We show how ANAKIN accurately predicts several relevant biological endpoints over a wide broad range on ions beams and for a high number of cell--lines. We compare the prediction of ANAKIN to the only two radiobiological model for RBE prediction used in clinics, that is the Microdosimetric Kinetic Model (MKM) and the Local Effect Model (LEM version III), showing how ANAKIN has higher accuracy over the all considered biological endpoints. At last, via modern techniques of Explainable Artificial Intelligence (XAI), we show how ANAKIN predictions can be understood and explained, highlighting how ANAKIN is in fact able to reproduce relevant well-known biological patterns, such as the overkilling effect

Integrating microdosimetric in vitro RBE models for particle therapy into TOPAS MC using the MicrOdosimetry-based modeling for RBE Assessment (MONAS) tool

We present MONAS (MicrOdosimetry-based modelliNg for relative biological effectiveness (RBE) ASsessment) toolkit. MONAS is a TOPAS Monte Carlo extension, that combines simulations of microdosimetric distributions with radiobiological microdosimetry-based models for predicting cell survival curves and dose-dependent RBE. MONAS expands TOPAS microdosimetric extension, by including novel specific energy scorers. These spectra are used as physical input to three different formulations of the Microdosimetric Kinetic Model (MKM), and to the Generalized Stochastic Microdosimetric Model (GSM2), to predict dose-dependent cell survival fraction and RBE. MONAS predictions are then validated against experimental microdosimetric spectra and in vitro survival fraction data. We present two different applications of the code: i) the depth-RBE curve calculation from a passively scattered proton SOBP, and ii) the calculation of the 3D RBE distribution on a real head and neck patient geometry treated with protons. MONAS can estimate dose dependent RBE and cell survival curves from experimentally validated microdosimetric spectra with four clinically relevant radiobiological models. From the radiobiological characterization of a proton SOBP field, we observe the well-known trend of increasing RBE values at the distal edge of the radiation field. The 3D RBE map calculated confirmed the trend observed in the analysis of the SOBP, with the highest RBE values found in the distal edge of the target. MONAS extension offers a comprehensive microdosimetry-based framework for assessing the biological effects of particle radiation in both research and clinical environments, contributing to bridging the gap between a microdosimetric description of the radiation field and its application in proton therapy treatment with variable RBE

Ion-beam therapy: from electron production in tissue like media to DNA damage estimations

Radiation damage induced by ion beams is traditionally treated at different levels of theoretical approaches, for the different scales and mechanisms involved.We present here details of a combined approach that, from a method at a nanoscopic scale, attempts to merge with higher scales existing results, by tuning the analytical method employed when extended to larger scale and so yielding a consistent picture of the entire process. Results will show the possibility to get a good agreement with macroscale methods and, on the other hand, to produce a reliable electron energy spectra to be used for DNA damage estimations.Comment: 7 pages,5 figures, class files for AIP include

TRAX-CHEMxt: Towards the Homogeneous Chemical Stage of Radiation Damage

The indirect effect of radiation plays an important role in radio-induced biological damages. Monte Carlo codes have been widely used in recent years to study the chemical evolution of particle tracks. However, due to the large computational efforts required, their applicability is typically limited to simulations in pure water targets and to temporal scales up to the µs. In this work, a new extension of TRAX-CHEM is presented, namely TRAX-CHEMxt, able to predict the chemical yields at longer times, with the capability of exploring the homogeneous biochemical stage. Based on the species coordinates produced around one track, the set of reaction–diffusion equations is solved numerically with a computationally light approach based on concentration distributions. In the overlapping time scale (500 ns–1 µs), a very good agreement to standard TRAX-CHEM is found, with deviations below 6% for different beam qualities and oxygenations. Moreover, an improvement in the computational speed by more than three orders of magnitude is achieved. The results of this work are also compared with those from another Monte Carlo-based algorithm and a fully homogeneous code (Kinetiscope). TRAX-CHEMxt will allow for studying the variation in chemical endpoints at longer timescales with the introduction, as the next step, of biomolecules, for more realistic assessments of biological response under different radiation and environmental conditions

Helium ions for radiotherapy? Physical and biological verifications of a novel treatment modality

Purpose: Modern facilities for actively scanned ion beam radiotherapy allow in principle the use of helium beams, which could present specific advantages, especially for pediatric tumors. In order to assess the potential use of these beams for radiotherapy, i.e., to create realistic treatment plans, the authors set up a dedicated He-4 beam model, providing base data for their treatment planning system TRiP98, and they have reported that in this work together with its physical and biological validations. Methods: A semiempirical beam model for the physical depth dose deposition and the production of nuclear fragments was developed and introduced in TRiP98. For the biological effect calculations the last version of the local effect model was used. The model predictions were experimentally verified at the HIT facility. The primary beam attenuation and the characteristics of secondary charged particles at various depth in water were investigated using He-4 ion beams of 200 MeV/u. The nuclear charge of secondary fragments was identified using a Delta E/E telescope. 3D absorbed dose distributions were measured with pin point ionization chambers and the biological dosimetry experiments were realized irradiating a Chinese hamster ovary cells stack arranged in an extended target. Results: The few experimental data available on basic physical processes are reproduced by their beam model. The experimental verification of absorbed dose distributions in extended target volumes yields an overall agreement, with a slight underestimation of the lateral spread. Cell survival along a 4 cm extended target is reproduced with remarkable accuracy. Conclusions: The authors presented a simple simulation model for therapeutical He-4 beams which they introduced in TRiP98, and which is validated experimentally by means of physical and biological dosimetries. Thus, it is now possible to perform detailed treatment planning studies with He-4 beams, either exclusively or in combination with other ion modalities. (C) 2016 Author(s)

Overview of DISCOVER22 experiment in the framework of INFN-LNGS Cosmic Silence activity: challenges and improvements in underground radiobiology

One of the most intriguing and still pending questions in radiobiology is to understand whether and how natural environmental background radiation has shaped Life over millions of years of evolution on Earth. Deep Underground Laboratories (DULs) represent the ideal below-background exposure facilities where to address such a question. Among the few worldwide DULs, INFN-Laboratorio Nazionale del Gran Sasso (LNGS) is one of the largest in terms of size and infrastructure. Designed and built to host neutrino and dark matter experiments, since the 1990 s the LNGS has been one of the first DULs to systematically host radiobiology experiments. Here we present the DISCOVER22 (DNA Damage and Immune System Cooperation in VEry low Radiation environment 2022) experiment recently started at LNGS. DISCOVER22 aims at investigating how the low radiation background modulates the Immune System (IS) response in in vitro and in vivo models. Underground radiobiology experiments are particularly complex and tricky to design and perform. In these studies, the accurate characterization of exposure scenarios is mandatory, but a challenging aspect is to understand how the very few ionizing tracks in the ultra-Low Radiation Environment (LRE) interact with the living matter in space and time in order to trigger different biological responses. In this Perspective, we describe these challenges and how we address them through a microdosimetric and a radiobiological approaches. We aim at linking physical microdosimetric measurements and the corresponding biological radiation responses by using radiation biophysical models that could shed light on many as yet unresolved questions