Purpose
This study proposes a novel computational platform that we refer to as IDDRRA (DNA Damage Response to Ionizing RAdiation), which uses Monte Carlo (MC) simulations to score radiation induced DNA damage. MC simulations provide results of high accuracy on the interaction of radiation with matter while scoring the energy deposition based on state-of-the-art physics and chemistry models and probabilistic methods.

Methods
The IDDRRA software is based on the Geant4-DNA toolkit together with new tools that were developed for the purpose of this study, including a new algorithm that was developed in Python for the design of the DNA molecules. New classes were developed in C++ to integrate the GUI and produce the simulation’s output in text format. An algorithm was also developed to analyze the simulation’s output in terms of energy deposition, Single Strand Breaks (SSB), Double Strand Breaks (DSB) and Cluster Damage Sites (CDS). Finally, a new tool was developed to implement probabilistic SSB and DSB repair models using MC techniques.

Results
This article provides the first benchmarks that the user of the IDDRRA tool can use to validate the functionality of the software as well as to provide a starting point to produce different types of DNA simulations. These benchmarks incorporate different kind of particles (e-, e+, protons, electron spectrum) and DNA molecules.

Conclusion
We have developed the IDDRRA tool and demonstrated its use to study various aspects of the modeling and simulation of a DNA irradiation experiment. The tool is expandable and can be expanded by other users with new benchmarks and applications based on the user’s needs and experience. New functionality will be added over time, including the quantification of the indirect damage.

Optical Monte Carlo simulations have been extensively used for the accurate modeling of light transport in scintillators for the improvement of detector designs. In the present work, a GATE Monte Carlo toolkit was used to study the effect of scintillator thicknesses and septa materials in the performance parameters evaluation of a commercially available small animal gamma-optical camera, named “γ-eye”. Firstly, the simulated γ-eye system was validated against experimental data. Then, part of the validated camera was modeled defining all of the optical properties by means of the UNIFIED model of GATE. Different CsI:Na scintillator crystals with varying thicknesses (from 4 mm up to 6 mm) and different reflector (septa) materials were simulated and compared in terms of sensitivity, light output and spatial resolution. Results have demonstrated the reliability of the model and indicate that the thicker crystal array presents higher sensitivity values, but degraded spatial resolution properties. Moreover, the use of black tape around crystals leads to an improvement in spatial resolution values compared to a standard white reflector material.

Purpose
This study aims to standardize the simulation procedure in measuring DNA double-strand breaks (DSBs), by using advanced Monte Carlo toolkits, and newly introduced experimental methods for DNA DSB measurement.

Methods
For the experimental quantification of DNA DSB, an innovative DNA dosimeter was used to produce experimental data. GATE in combination with Geant4-DNA toolkit were exploited to simulate the experimental environment. The PDB4DNA example of Geant4-DNA was upgraded and investigated. Parameters of the simulation such energy threshold (ET) for a strand break and base pair threshold (BPT) for a DSB were evaluated, depending on the dose.

Results
Simulations resulted to minimum differentiation in comparison to experimental data for ET = 19 ± 1 eV and BPT = 10 bp, and high differentiation for ET<17.5 eV or ET>22.5 eV and BPT = 10 bp. There was also small differentiation for ET = 17.5 eV and BPT = 6 bp. Uncertainty has been kept lower than 3%.

Conclusions
This study includes first results on the quantification of DNA double-strand breaks. The energy spectrum of a LINAC was simulated and used for the first time to irradiate DNA molecules. Simulation outcome was validated on experimental data that were produced by a prototype DNA dosimeter.

The investigation of biological effects in living tissues requires the modeling of physical, chemical, and physico-chemical interactions. Strong effort has been given in the 3D modeling of DNA structure, such as to describe the cell nucleus. In 2015, a new application, Geant4-DNA was presented, enabling the atomic level description of DNA molecules and the possibility of evaluating the direct damage induced on the DNA molecule by ionizing radiation [1]. Recently, a DNA Double-Strand Break (DSB) dosimeter was developed for the detection and quantification of DNA-DSBs after irradiation[2]. Our goal is to validate the simulated data, and standardize the experimental procedure for measuring the biological damage.

In the present study, we investigated the PDB4DNA tool and developed a new G4-DNA class for the quantification of DSBs after irradiation. Experimental measures were used for testing the G4-DNA classes. A DNA molecule (1329bp, the largest in PDBlib) was irradiated with 3 different absorbed doses equal to 10, 25 and 50Gy. In our simulation study, we used a structure of a single DNA molecule (based on experimental data), and irradiated it multiple times to quantify the probability of DSBs.

The simulations, on G4-DNA DSB quantification, resulted in DSB probabilities equal to 9.0%, 17.0%, and 31% for doses 10Gy, 25Gy, and 50Gy respectively. Thus, the statistical difference between experimental and simulated DSBs was calculated to 8.09%, 9.23%, and 13.43% accordingly. Comparing our simulations with the standard used PDB4DNA class, differences varied from 40–70%.

This is a preliminary study for the modeling, and the quantification of DNA-DSBs based on experimental data. The limitations of this study need to be addressed, such as the modeling of multiple DNA molecules for accurate statistical simulations, and chemical reactions need to be taken into account for the total quantification of the biological damage on DNA structures.

Purpose:
Pediatric tumors are generally treated with multi-modal procedures. Brachytherapy can be used with pediatric tumors, especially given that in this patient population low toxicity on normal tissues is critical as is the suppression of the probability for late malignancies. Our goal is to validate the GATE toolkit on realistic brachytherapy applications, and evaluate brachytherapy plans on pediatrics for accurate dosimetry on sensitive and critical organs of interest.

Methods:
The GATE Monte Carlo (MC) toolkit was used. Two High Dose Rate (HDR) 192Ir brachytherapy sources were simulated (Nucletron mHDR-v1 and Varian VS2000), and fully validated using the AAPM and ESTRO protocols. A realistic brachytherapy plan was also simulated using the XCAT anthropomorphic computational model .The simulated data were compared to the clinical dose points. Finally, a 14 years old girl with vaginal rhabdomyosarcoma was modelled based on clinical procedures for the calculation of the absorbed dose per organ.

Results:
The MC simulations resulted in accurate dosimetry in terms of dose rate constant (Λ), radial dose gL(r) and anisotropy function F(r,θ) for both sources. The simulations were executed using ∼1010 number of primaries resulting in statistical uncertainties lower than 2%.The differences between the theoretical values and the simulated ones ranged from 0.01% up to 3.3%, with the largest discrepancy (6%) being observed in the dose rate constant calculation. The simulated DVH using an adult female XCAT model was also compared to a clinical one resulting in differences smaller than 5%. Finally, a realistic pediatric brachytherapy simulation was performed to evaluate the absorbed dose per organ and to calculate DVH with respect to heterogeneities of the human anatomy.

Conclusion:
GATE is a reliable tool for brachytherapy simulations both for source modeling and for dosimetry in anthropomorphic voxelized models. Our project aims to evaluate a variety of pediatric brachytherapy schemes using a population of pediatric phantoms for several pathological cases.