Background: Geant4, a Monte Carlo Simulation Toolkit extensively used in bio‐medical physics, is in continuous evolution to include newest research findings to improve its accuracy and to respond to the evolving needs of a very diverse user community. In 2014, the G4‐Med benchmarking system was born from the effort of the Geant4 Medical Simulation Benchmarking Group, to benchmark and monitor the evolution of Geant4 for medical physics applications. The G4‐Med system was first described in our Medical Physics Special Report published in 2021. Results of the tests were reported for Geant4 10.5. Purpose: In this work, we describe the evolution of the G4‐Med benchmarking system. Methods: The G4‐Med benchmarking suite currently includes 23 tests, which benchmark Geant4 from the calculation of basic physical quantities to the simulation of more clinically relevant set‐ups. New tests concern the benchmarking of Geant4‐DNA physics and chemistry components for regression testing purposes, dosimetry for brachytherapy with a source, dosimetry for external x‐ray and electron FLASH radiotherapy, experimental microdosimetry for proton therapy, and in vivo PET for carbon and oxygen beams. Regression testing has been performed between Geant4 10.5 and 11.1. Finally, a simple Geant4 simulation has been developed and used to compare Geant4 EM physics constructors and physics lists in terms of execution times. Results: In summary, our EM tests show that the parameters of the multiple scattering in the Geant4 EM constructor G4EmStandardPhysics_option3 in Geant4 11.1, while improving the modeling of the electron backscattering in high atomic number targets, are not adequate for dosimetry for clinical x‐ray and electron beams. Therefore, these parameters have been reverted back to those of Geant4 10.5 in Geant4 11.2.1. The x‐ray radiotherapy test shows significant differences in the modeling of the bremsstrahlung process, especially between G4EmPenelopePhysics and the other constructors under study ( G4EmLivermorePhysics , G4EmStandardPhysics_option3 , and G4EmStandardPhysics_option4 ). These differences will be studied in an in‐depth investigation within our Group. Improvement in Geant4 11.1 has been observed for the modeling of the proton and carbon ion Bragg peak with energies of clinical interest, thanks to the adoption of ICRU90 to calculate the low energy proton stopping powers in water and of the Linhard–Sorensen ion model, available in Geant4 since version 11.0. Nuclear fragmentation tests of interest for carbon ion therapy show differences between Geant4 10.5 and 11.1 in terms of fragment yields. In particular, a higher production of boron fragments is observed with Geant4 11.1, leading to a better agreement with reference data for this fragment. Conclusions: Based on the overall results of our tests, we recommend to use G4EmStandardPhysics_option4 as EM constructor and QGSP_BIC_HP with G4EmStandardPhysics_option4 , for hadrontherapy applications. The Geant4‐DNA physics lists report differences in modeling electron interactions in water, however, the tests have a pure regression testing purpose so no recommendation can be formulated.

Recent evidence indicates that transcranial ultrasound stimulation (TUS) modulates sensorimotor cortex excitability. However, no study has assessed possible TUS effects on the excitability of deeper brain areas, such as the brainstem. In this study, we investigated whether TUS delivered on the substantia nigra, superior colliculus, and nucleus raphe magnus modulates the excitability of trigeminal blink reflex, a reliable neurophysiological technique to assess brainstem functions in humans. The recovery cycle of the trigeminal blink reflex (interstimulus intervals of 250 and 500 ms) was tested before (T0), and 3 (T1) and 30 min (T2) after TUS. The effects of substantia nigra-TUS, superior colliculus-TUS, nucleus raphe magnus-TUS and sham-TUS were assessed in separate and randomized sessions. In the superior colliculus-TUS session, the conditioned R2 area increased at T1 compared with T0, while T2 and T0 values did not differ. Results were independent of the interstimulus intervals tested and were not related to trigeminal blink reflex baseline (T0) excitability. Conversely, the conditioned R2 area was comparable at T0, T1, and T2 in the nucleus raphe magnus-TUS and substantia nigra-TUS sessions. Our findings demonstrate that the excitability of brainstem circuits, as evaluated by testing the recovery cycle of the trigeminal blink reflex, can be increased by TUS. This result may reflect the modulation of inhibitory interneurons within the superior colliculus.

Working Group (WG) 6 ‘Computational Dosimetry’ of the European Radiation Dosimetry Group promotes good practice in the application of computational methods for radiation dosimetry in radiation protection and the medical use of ionising radiation. Its cross-sectional activities within the association cover a large range of current topics in radiation dosimetry, including more fundamental studies of radiation effects in complex systems. In addition, WG 6 also performs scientific research and development as well as knowledge transfer activities, such as training courses. Monte Carlo techniques, including the use of anthropomorphic and other numerical phantoms based on voxelised geometrical models, play a strong part in the activities pursued in WG 6. However, other aspects and techniques, such as neutron spectra unfolding, have an important role as well. A number of intercomparison exercises have been carried out in the past to provide information on the accuracy with which computational methods are applied and whether best practice is being followed. Within the exercises that are still ongoing, the focus has changed towards assessing the uncertainty that can be achieved with these computational methods. Furthermore, the future strategy of WG 6 also includes an extension of the scope toward experimental benchmark activities and evaluation of cross-sections and algorithms, with the vision of establishing a gold standard for Monte Carlo methods used in medical and radiobiological applications.

Graphs are versatile structures for the representation of many real-world data. Deep Learning on graphs is currently able to solve a wide range of problems with excellent results. However, both the generation of graphs and the handling of large graphs still remain open challenges. This work aims to introduce techniques for generating large graphs and test the approach on a complex problem such as the calculation of dose distribution in oncological radiotherapy applications. To this end, we introduced a pooling technique (ReNN-Pool) capable of sampling nodes that are spatially uniform without computational requirements in both model training and inference. By construction, the ReNN-Pool also allows the definition of a symmetric un-pooling operation to recover the original dimensionality of the graphs. We also present a Variational AutoEncoder (VAE) for generating graphs, based on the defined pooling and un-pooling operations, which employs convolutional graph layers in both encoding and decoding phases. The performance of the model was tested on both the realistic use case of a cylindrical graph dataset for a radiotherapy application and the standard benchmark dataset sprite. Compared to other graph pooling techniques, ReNN-Pool proved to improve both performance and computational requirements.

Cosmic rays have the potential to induce significant changes in atmospheric chemical reactions by generating ions, thereby influencing the atmosphere's chemical composition. The use of particle-molecule interaction models that account for the molecular structure of the atmospheric medium can advance our understanding on the role of ions, and enables a quantitative analysis of the impact of ion-molecule reactions on atmospheric modifications. This study marks the initial effort to expand the Geant-DNA toolkit for atmospheric applications. Building on our previous work, we extended the validation of new electron impact interaction models with the nitrogen and oxygen molecules up to 10 MeV. Additionally, we introduce electron cross sections for the carbon dioxide molecule, due to its crucial role as a major greenhouse gas. We present the implementation of the cross section models in Geant4-DNA, along with their validation through simulations of stopping power and range. The differential cross sections have been verified against analytical calculations, demonstrating good agreement with existing literature data for all three molecules. The implementation has been validated through simulations of stopping power and range in N₂, O₂, CO₂, and air. Results demonstrate agreement within 6% compared to reference data from the ESTAR database. The cross section models for the N₂, O₂, and CO₂ atmospheric molecules have been implemented in the Geant4-DNA toolkit. This evolution is crucial for studying ionic reactive chemical networks in a quantitative manner, assessing the impact of ionization on chemical reactions occurring in the atmosphere and their implications for climate.

This study aims at evaluating the effects of different lung densities on dose distribution after irradiation at different field sizes, by comparing experimental measurements, GEANT4 Monte Carlo (MC) simulations and two TPS calculation algorithms on ad hoc phantoms. Irradiations were performed with a Varian Clinac 2100 C/D with a nominal energy of 6 MV. Dosimetric experimental measurements were obtained with radiochromic films. A model based on GEANT4 MC code was developed to simulate both the accelerator and the phantoms. Results of dose distribution show an acceptable agreement between MC simulations and experimental measurements, both in the tumour-equivalent region and in the normal tissue-equivalent ones. On the opposite, results vary among the TPS algorithms, especially in regions of lung-equivalent material at low density, but also at the interface between lung- and tumour-equivalent materials.