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International recommendations and regulations require developing of National Radon Action Plans (NRAPs) to effectively manage the protection of workers and population from radon exposure. In Italy, a NRAP was published in 2002 and several activities have been carried out in this framework. Information and data regarding these and previous activities have been collected in a National Radon Archive (NRA). Activities carried out by institutionally involved institutes and agencies include several national and regional surveys, involving more than 50 000 indoor environments (dwellings, schools and workplaces), and remedial actions performed in ~350 buildings, largely in schools. Data collected in the NRA allowed also to estimate that lung cancer deaths attributable to radon exposure in Italy are ~3400 per year. On-going developments of the Italian NRA finalized to effectively use it as tool for developing, monitoring and updating the NRAP are also described. [ABSTRACT FROM AUTHOR]

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 125 I $^{125}I$ 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., (© 2025 The Author(s). Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine.)

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.

Uncertainty on long-term average radon concentration has a large impact on lung cancer risk assessment in epidemiological studies. The uncertainty can be estimated by year-to-year radon concentration variability, however few data are available. In Italy a study has been planned and conducted to evaluate year-to-year radon variability over several years in normally inhabited dwellings, mainly located in Rome. This is the longest study of this kind in Europe; repeat radon measurements are carried out for 10 years using LR-115 radon detectors in the same home in consecutive years. The study includes 84 dwellings with long-term average radon concentration ranging from 28 to 636 Bq/m 3 . The result shows that year-to-year variability of repeated measurements made in the same home in different years is low, with an overall coefficient of variation of 17%. This is smaller than most of those observed in studies from other European countries and USA, ranging from 15% to 62%. Influencing factors that may explain the differences between this study and other studies have been discussed. Due to the low yearly variability estimated in the present 10-year study, a negligible impact on lung cancer risk estimate for the Italian epidemiological study is expected., Competing Interests: Declaration of competing interest None of the authors has any actual or potential competing financial and non-financial interests to declare., (Copyright © 2020 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background: In radiotherapy, Monte Carlo (MC) methods are considered a gold standard to calculate accurate dose distributions, particularly in heterogeneous tissues. EURADOS organized an international comparison with six participants applying different MC models to a real medical linear accelerator and to one homogeneous and four heterogeneous dosimetric phantoms., Aims: The aim of this exercise was to identify, by comparison of different MC models with a complete experimental dataset, critical aspects useful for MC users to build and calibrate a simulation and perform a dosimetric analysis., Results: Results show on average a good agreement between simulated and experimental data. However, some significant differences have been observed especially in presence of heterogeneities. Moreover, the results are critically dependent on the different choices of the initial electron source parameters., Conclusions: This intercomparison allowed the participants to identify some critical issues in MC modelling of a medical linear accelerator. Therefore, the complete experimental dataset assembled for this intercomparison will be available to all the MC users, thus providing them an opportunity to build and calibrate a model for a real medical linear accelerator.

Background: High Intensity Focused Ultrasound (HIFU) is a noninvasive treatment for therapeutic applications, in particular the treatment of either benign or malignant tumor lesions. HIFU treatment is based on the power of a focused ultrasound beam to locally heat biological tissues over a necrotic level with minimal impact on the surrounding tissues. Therapies based on HIFU are becoming widely spread in the panorama of options offered by the Health Care System. Consequently, there is an ever increasing need to standardise quality assurance protocols and to develop computational tools to evaluate the output of clinical HIFU devices and ensuring safe delivery of HIFU treatment., Aims: Goal of this study is the development of a computational tool for HIFU ablation therapy to assure safety of the patient and effectiveness of the treatment., Results: The simulated results provide information about the behaviour of the focalized ultrasound in their interaction with different biological tissues., Conclusions: Numerical simulation represents a useful approach to predict the heath deposition and, consequently, to assess the safety and effectiveness of HIFU devices.

Dose distribution evaluation in oncological radiotherapy treatments is an outstanding problem that requires sophisticated computing technologies to optimize the clinical results (i.e. increase the dose to the tumour and reduce the dose to the healthy tissues). Nowdays, dose calculation algorithms based on the Monte Carlo method are generally regarded as the most accurate tools for radiotherapy. The flexibility of the GEANT4 (GEometry ANd Tracking) Monte Carlo particle transport simulation code allows a wide range of applications, from high-energy to medical physics. In order to disseminate and encourage the use of Monte Carlo method in oncological radiotherapy, a software package based on the GEANT4 Monte Carlo toolkit has been developed. The developed package (MedLinac2) allows to simulate in an adequate flexible way a linear accelerator for radiotherapy and to evaluate the dose distributions.

Intensity-modulated radiotherapy (IMRT) (1) is an advanced form of 3-D conformal radiotherapy. It uses non uniform spatial modifications in the intensity of the beams across the irradiated field. Consequently, it is necessary to develop sophisticated tools to compare measured and calculated dose distributions in order to verify the accuracy of the results of the planned dose distribution. Different methods have been developed to evaluate the accordance between measured and calculated doses, such as the point-to-point dose difference or the evaluation of the distance between two closed points having the same dose value (2-4). The verification method proposed by Low (5-7) seems to be more complete since it takes into account both the dose difference (DD) and the distance to agreement (DTA), allowing to define a "score", the gamma value, at each point of interest. A software tool (DDE: Dose Distribution Evaluator), based on Low's method, to evaluate the agreement between dose distribution matrices has been implemented. In particular, the proposed gamma curve, as a function of the isodose levels, gives real-time information useful for decision making about the treatment plan. The paper describes the software, and reports the obtained results in a simple geometry and in several clinical cases (head-neck and prostate). Comparison between measured data (film and MapCheck) and calculated data (CadPlan) using DDE has shown very good agreements. Thanks to its higher resolution, film dosimetry showed better accuracy than the MapCheck technique. Similar results can be obtained also with the MapCheck technique when proper measurement methods are used.

We aim at (1) defining and measuring a "complexity" index for the optimization process of an intensity modulated radiation therapy treatment plan (IMRT TP), (2) devising an efficient approximate optimization strategy, and (3) evaluating the impact of the complexity of the optimization process on the radiobiological quality of the treatment. In this work, for a prostate therapy case, the IMRT TP optimization problem has been formulated in terms of dose-volume constraints. The cost function has been minimized in order to achieve the optimal solution, by means of an iterative procedure, which is repeated for many initial modulation profiles, and for each of them the final optimal solution is recorded. To explore the complexity of the space of such solutions we have chosen to minimize the cost function with an algorithm that is unable to avoid local minima. The size of the (sub)optimal solutions distribution is taken as an indicator of the complexity of the optimization problem. The impact of the estimated complexity on the probability of success of the therapy is evaluated using radiobiological indicators (Poissonian TCP model [S. Webb and A. E. Nahum, Phys. Med. Biol. 38(6), 653-666 (1993)] and NTCP relative seriality model [Kallman et al., Int. J. Radiat. Biol. 62(2), 249-262 (1992)]). We find in the examined prostate case a nontrivial distribution of local minima, which has symmetry properties allowing a good estimate of near-optimal solutions with a moderate computational load. We finally demonstrate that reducing the a priori uncertainty in the optimal solution results in a significant improvement of the probability of success of the TP, based on TCP and NTCP estimates.

Intensity modulated radiation therapy (IMRT) is one of the most innovative techniques in oncological radiotherapy, allowing to conform the dose delivery to the tumoral target, preserving the normal tissue. The high number of parameters involved in the IMRT treatment planning requires an automated approach to the beam modulation. Such optimization process consists in the search of the global minimum of a cost function representing a quality index for the treatment. The complexity of this task, has been analyzed with a statistical approach for three clinical cases of particular interest in IMRT. Our main result is that a cost function based on dose-volume constraints entails lower complexity of the optimization process, in terms of the choice of the parameters defining the cost function and in a smaller sensitivity to the initial conditions for the optimization algorithm.