TOPAS-nBio simulation of temperature-dependent indirect DNA strand break yields

Current Monte Carlo simulations of DNA damage have been reported only at ambient temperature. The aim of this work is to use TOPAS-nBio to simulate the yields of DNA single-strand breaks (SSBs) and double-strand breaks (DSBs) produced in plasmids under low-LET irradiation incorporating the effect of the temperature changes in the environment. A new feature was implemented in TOPAS-nBio to incorporate reaction rates used in the simulation of the chemical stage of water radiolysis as a function of temperature. The implemented feature was verified by simulating temperature-dependent G-values of chemical species in liquid water from 20 °C to 90 °C. For radiobiology applications, temperature dependent SSB and DSB yields were calculated from 0 °C to 42 °C, the range of available published measured data. For that, supercoiled DNA plasmids dissolved in aerated solutions containing EDTA irradiated by Cobalt-60 gamma-rays were simulated. TOPAS-nBio well reproduced published temperature-dependent G-values in liquid water and the yields of SSB and DSB for the temperature range considered. For strand break simulations, the model shows that the yield of SSB and DSB increased linearly with the temperature at a rate of (2.94 ± 0.17) × 10−10 Gy–1 Da–1 °C–1 (R 2 = 0.99) and (0.13 ± 0.01) × 10−10 Gy–1 Da–1 °C–1 (R 2 = 0.99), respectively. The extended capability of TOPAS-nBio is a complementary tool to simulate realistic conditions for a large range of environmental temperatures, allowing refined investigations of the biological effects of radiation.

DNA damage modeled with Geant4-DNA: effects of plasmid DNA conformation and experimental conditions

The chemical stage of the Monte Carlo track-structure (MCTS) code Geant4-DNA was extended for its use in DNA strand break (SB) simulations and compared against published experimental data. Geant4-DNA simulations were performed using pUC19 plasmids (2686 base pairs) in a buffered solution of DMSO irradiated by⁶⁰Co or¹³⁷Csγ-rays. A comprehensive evaluation of SSB yields was performed considering DMSO, DNA concentration, dose and plasmid supercoiling. The latter was measured using the super helix density value used in a Brownian dynamics plasmid generation algorithm. The Geant4-DNA implementation of the independent reaction times method (IRT), developed to simulate the reaction kinetics of radiochemical species, allowed to score the fraction of supercoiled, relaxed and linearized plasmid fractions as a function of the absorbed dose. The percentage of the number of SB after •OH + DNA and H• + DNA reactions, referred as SSB efficiency, obtained using MCTS were 13.77% and 0.74% respectively. This is in reasonable agreement with published values of 12% and 0.8%. The SSB yields as a function of DMSO concentration, DNA concentration and super helix density recreated the expected published experimental behaviors within 5%, one standard deviation. The dose response of SSB and DSB yields agreed with published measurements within 5%, one standard deviation. We demonstrated that the developed extension of IRT in Geant4-DNA, facilitated the reproduction of experimental conditions. Furthermore, its calculations were strongly in agreement with experimental data. These two facts will facilitate the use of this extension in future radiobiological applications, aiding the study of DNA damage mechanisms with a high level of detail.

Independent reaction times method in Geant4-DNA: Implementation and performance

PURPOSE

The simulation of individual particle tracks and the chemical stage following water radiolysis in biological tissue is an effective means of improving our knowledge of the physico-chemical contribution to the biological effect of ionizing radiation. However, the step-by-step simulation of the reaction kinetics of radiolytic species is the most time-consuming task in Monte Carlo track-structure simulations, with long simulation times that are an impediment to research. In this work, we present the implementation of the independent reaction times (IRT) method in Geant4-DNA Monte Carlo toolkit to improve the computational efficiency of calculating G-values, defined as the number of chemical species created or lost per 100 eV of deposited energy.

METHODS

The computational efficiency of IRT, as implemented, is compared to that from available Geant4-DNA step-by-step simulations for electrons, protons and alpha particles covering a wide range of linear energy transfer (LET). The accuracy of both methods is verified using published measured data from fast electron irradiations for ^• OH and e aq - for time-dependent G-values. For IRT, simulations in the presence of scavengers irradiated by cobalt-60 γ-ray and 2 MeV protons are compared with measured data for different scavenging capacities. In addition, a qualitative assessment comparing measured LET-dependent G-values with Geant4-DNA calculations in pure liquid water is presented.

RESULTS

The IRT improved the computational efficiency by three orders of magnitude relative to the step-by-step method while differences in G-values by 3.9% at 1 μs were found. At 7 ps, ^• OH and e aq - yields calculated with IRT differed from recent published measured data by 5% ± 4% and 2% ± 4%, respectively. At 1 μs, differences were 9% ± 5% and 6% ± 7% for ^• OH and e aq - , respectively. Uncertainties are one standard deviation. Finally, G-values at different scavenging capacities and LET-dependent G-values reproduced the behavior of measurements for all radiation qualities.

CONCLUSION

The comprehensive validation of the Geant4-DNA capabilities to accurately simulate the chemistry following water radiolysis is an ongoing work. The implementation presented in this work is a necessary step to facilitate performing such a task.

Monte Carlo simulation of the effect of magnetic fields on brachytherapy dose distributions in lung tissue material

The aim of this work was to use TOPAS Monte Carlo simulations to model the effect of magnetic fields on dose distributions in brachytherapy lung treatments, under ideal and clinical conditions. Idealistic studies were modeled consisting of either a monoenergetic electron source of 432 keV, or a polyenergetic electron source using the spectrum of secondary electrons produced by ¹⁹²Ir gamma-ray irradiation. The electron source was positioned in the center of a homogeneous, lung tissue phantom (ρ = 0.26 g/cm³). Conversely, the clinical study was simulated using the VariSource VS2000 ¹⁹²Ir source in a patient with a lung tumor. Three contoured volumes were considered: the tumor, the planning tumor volume (PTV), and the lung. In all studies, dose distributions were calculated in the presence or absence of a constant magnetic field of 3T. Also, TG-43 parameters were calculated for the VariSource and compared with published data from EGS-brachy (EGSnrc) and PENELOPE. The magnetic field affected the dose distributions in the idealistic studies. For the monoenergetic and poly-energetic studies, the radial distance of the 10% iso-dose line was reduced in the presence of the magnetic field by 64.9% and 24.6%, respectively. For the clinical study, the magnetic field caused differences of 10% on average in the patient dose distributions. Nevertheless, differences in dose-volume histograms were below 2%. Finally, for TG-43 parameters, the dose-rate constant from TOPAS differed by 0.09% ± 0.33% and 0.18% ± 0.33% with respect to EGS-brachy and PENELOPE, respectively. The geometry and anisotropy functions differed within 1.2% ± 1.1%, and within 0.0% ± 0.3%, respectively. The Lorentz forces inside a 3T magnetic resonance machine during ¹⁹²Ir brachytherapy treatment of the lung are not large enough to affect the tumor dose distributions significantly, as expected. Nevertheless, large local differences were found in the lung tissue. Applications of this effect are therefore limited by the fact that meaningful differences appeared only in regions containing air, which is not abundant inside the human.

LET-Dependent Intertrack Yields in Proton Irradiation at Ultra-High Dose Rates Relevant for FLASH Therapy

FLASH radiotherapy delivers a high dose (≥10 Gy) at a high rate (≥40 Gy/s). In this way, particles are delivered in pulses as short as a few nanoseconds. At that rate, intertrack reactions between chemical species produced within the same pulse may affect the heterogeneous chemistry stage of water radiolysis. This stochastic process suits the capabilities of the Monte Carlo method, which can model intertrack effects to aid in radiobiology research, including the design and interpretation of experiments. In this work, the TOPAS-nBio Monte Carlo track-structure code was expanded to allow simulations of intertrack effects in the chemical stage of water radiolysis. Simulation of the behavior of radiolytic yields over a long period of time (up to 50 s) was verified by simulating radiolysis in a Fricke dosimeter irradiated by 60Co γ rays. In addition, LET-dependent G values of protons delivered in single squared pulses of widths, 1 ns, 1 µs and 10 µs, were obtained and compared to simulations using no intertrack considerations. The Fricke simulation for the calculated G value of Fe3+ ion at 50 s was within 0.4% of the accepted value from ICRU Report 34. For LET-dependent G values at the end of the chemical stage, intertrack effects were significant at LET values below 2 keV/µm. Above 2 keV/µm the reaction kinetics remained limited locally within each track and thus, effects of intertrack reactions remained low. Therefore, when track structure simulations are used to investigate the biological damage of FLASH irradiation, these intertrack reactions should be considered. The TOPAS-nBio framework with the expansion to intertrack chemistry simulation provides a useful tool to assist in this task.

A simple model for glioma grading based on texture analysis applied to conventional brain MRI

Accuracy of glioma grading is fundamental for the diagnosis, treatment planning and prognosis of patients. The purpose of this work was to develop a low-cost and easy-to-implement classification model which distinguishes low-grade gliomas (LGGs) from high-grade gliomas (HGGs), through texture analysis applied to conventional brain MRI. Different combinations of MRI contrasts (T1Gd and T2) and one segmented glioma region (necrotic and non-enhancing tumor core, NCR/NET) were studied. Texture features obtained from the gray level size zone matrix (GLSZM) were calculated. An under-sampling method was proposed to divide the data into different training subsets and subsequently extract complementary information for the creation of distinct classification models. The sensitivity, specificity and accuracy of the models were calculated, and the best model explicitly reported. The best model included only three texture features and reached a sensitivity, specificity and accuracy of 94.12%, 88.24% and 91.18%, respectively. According to the features of the model, when the NCR/NET region was studied, HGGs had a more heterogeneous texture than LGGs in the T1Gd images, and LGGs had a more heterogeneous texture than HGGs in the T2 images. These novel results partially contrast with results from the literature. The best model proved to be useful for the classification of gliomas. Complementary results showed that the heterogeneity of gliomas depended on the MRI contrast studied. The chosen model stands out as a simple, low-cost, easy-to-implement, reproducible and highly accurate glioma classifier. Importantly, it should be accessible to populations with reduced economic and scientific resources.

Efficient CT Image Reconstruction in a GPU Parallel Environment

Computed tomography is nowadays an indispensable tool in medicine used to diagnose multiple diseases. In clinical and emergency room environments, the speed of acquisition and information processing are crucial. CUDA is a software architecture used to work with NVIDIA graphics processing units. In this paper a methodology to accelerate tomographic image reconstruction based on maximum likelihood expectation maximization iterative algorithm and combined with the use of graphics processing units programmed in CUDA framework is presented. Implementations developed here are used to reconstruct images with clinical use. Timewise, parallel versions showed improvement with respect to serial implementations. These differences reached, in some cases, 2 orders of magnitude in time while preserving image quality. The image quality and reconstruction times were not affected significantly by the addition of Poisson noise to projections. Furthermore, our implementations showed good performance when compared with reconstruction methods provided by commercial software. One of the goals of this work was to provide a fast, portable, simple, and cheap image reconstruction system, and our results support the statement that the goal was achieved.

Different Food Odors Control Brain Connectivity in Impulsive Children

BACKGROUND

Impulsivity is a complex multi-dimensional combination of behaviors which include: ineffective impulse control, premature decision-making and inability to delay gratification.

OBJECTIVE

The aim of this work was to explore how food odor perception and its emotional value is affected in impulsive children.

METHODS

Here we compared two cohorts of impulsive and control children with ages between 10 and 16 years. Both groups underwent a functional magnetic resonance imaging experiment, in which foodrelated odor-cues were presented to all of them.

RESULTS

Differences in regions of blood oxygen level dependent activation, as well as connectivity, were calculated. Activations were significant for all odors in the impulsive group in the temporal lobe, cerebellum, supplementary motor area, frontal cortex, medial cingulate cortex, insula, precuneus, precentral, para-hippocampal and calcarine cortices.

CONCLUSION

Connectivity results showed that the expected emotional reward, based on odor perceived and processed in temporal lobes, was the main cue driving responses of impulsive children. This was followed by self-consciousness, the sensation of interaction with the surroundings and feelings of comfort and happiness, modulated by the precuneus together with somatosensory cortex and cingulum. Furthermore, reduced connectivity to frontal areas as well as to other sensory integration areas (piriform cortex), combined to show different sensory processing strategies for olfactory emotional cues in impulsive children. Finally, we hypothesize that the cerebellum plays a pivotal role in modulating decision-making for impulsive children.

Luminescent Properties of Eu3+-Doped Hybrid SiO₂-PMMA Material for Photonic Applications

Hybrid organic-inorganic materials are of great interest for various applications. Here, we report on the synthesis and optical characterization of silica-PMMA samples with different Eu³⁺ molar concentrations. The optical properties of this material make it suitable for photonic applications. The samples were prepared using the sol-gel method, mixing tetraethyl orthosilicate (TEOS) as a silica glass precursor and methyl methacrylate (PMMA) as a polymer component. Europium nitrate pentahydrate was then added in six different molar concentrations (0.0, 0.1, 0.25, 0.5, 0.75, and 1%) to obtain as many different samples of the material. The absorption spectra were obtained applying the Kubelka–Munk formula to the diffuse reflectance spectra of the samples, all in the wavelength range between 240 and 2500 nm. The emission and excitation measurements were made in the visible range. Five bands could be identified in the emission spectra, related to electronic transitions of the ion Eu³⁺ (⁴D₀→⁷F_i, i from 0 to 4). In the excitation spectra, the following bands were detected: ⁷F₀→⁵G₃ (379 nm), ⁷F₀→⁵G₂ (380 nm), ⁷F₀→⁵L₆ (392 nm), ⁷F₀→⁵D₃ (407 nm), ⁷F₀→⁵D₂ (462 nm), and ⁷F₀→⁵D₁ (530 nm). The emission decay times were measured for the different samples and showed an inverse dependence with the Eu³⁺ concentration.