In this work an innovative approach was developed to address a significant challenge in the field of radiation dosimetry: the accurate measurement of spatial dose distributions using Fricke gel dosimeters. Hydrogels are widely used in radiation dosimetry due to their ability to simulate the tissue-equivalent properties of human tissue, making them ideal for measuring and mapping radiation dose distributions. Among the various gel dosimeters, Fricke gels exploit the radiation-induced oxidation of ferrous ions to ferric ions and are particularly notable due to their sensitivity. The concentration of ferric ions can be measured using various techniques, including magnetic resonance imaging (MRI) or spectrophotometry. While Fricke gels offer several advantages, a significant hurdle to their widespread application is the diffusion of ferric ions within the gel matrix. This phenomenon leads to a blurring of the dose distribution over time, compromising the accuracy of dose measurements. To mitigate the issue of ferric ion diffusion, researchers have explored various strategies such as the incorporation of additives or modification of the gel composition to either reduce the mobility of ferric ions or stabilize the gel matrix. The computational method proposed leverages the power of artificial intelligence, particularly deep learning, to mitigate the effects of ferric ion diffusion that can compromise measurement precision. By employing Physics Informed Neural Networks (PINNs), the method introduces a novel way to apply physical laws directly within the learning process, optimizing the network to adhere to the principles governing ion diffusion. This is particularly advantageous for solving the partial differential equations that describe the diffusion process in 2D and 3D. By inputting the spatial distribution of ferric ions at a given time, along with boundary conditions and the diffusion coefficient, the model can backtrack to accurately reconstruct the original ion distribution. This capability is crucial for enhancing the fidelity of 3D spatial dose measurements, ensuring that the data reflect the true dose distribution without the artifacts introduced by ion migration. Here, multidimensional models able to handle 2D and 3D data were developed and tested against dose distributions numerically evolved in time from 20 to 100 h. The results in terms of various metrics show a significant agreement in both 2D and 3D dose distributions. In particular, the mean square error of the prediction spans the range $1\times {10}^{-6}$–$1\times {10}^{-4}$, while the gamma analysis results in a 90–100% passing rate with 3%/2 mm, depending on the elapsed time, the type of distribution modeled and the dimensionality. This method could expand the applicability of Fricke gel dosimeters to a wider range of measurement tasks, from simple planar dose assessments to intricate volumetric analyses. The proposed technique holds great promise for overcoming the limitations imposed by ion diffusion in Fricke gel dosimeters.

This work presents the computational analysis of the sensitivity improvements that could be achieved in lithium formate monohydrate (LFM) electron paramagnetic resonance (EPR) dosemeters exposed to neutron beams. Monte Carlo (MC) simulations were performed on LFM pellets exposed to neutron beams with different energy spectra at various depths inside a water phantom. Various computations were carried out by considering different enrichments of ⁶Li inside the LFM matrix as well as addition of different amounts of gadolinium oxide inside the pellet blend. The energy released per unit mass was calculated with the aim of predicting the increase in dose achievable by the addition of sensitizers inside the pellets. As expected, a larger amount of ⁶Li induces an increase of energy released because of the charged secondary particles (i.e. ³H ions and α-particles) produced after neutron capture. For small depths in water phantom and low-energy neutron spectra the dose increase due to ⁶Li enrichment is high (more than three orders of magnitude with respect to the case of with ⁷Li). In case of epithermal neutron beams the energy released in ⁶Li-enriched LFM compound is smaller but larger than in the case of fast neutron beams. On the other hand, the computational analysis evidenced that gadolinium is less effective than ⁶Li in improving neutron sensitivity of the LFM pellets. Discussion based on the features of MC transport code is provided. This result suggests that ⁶Li enrichment of LFM dosemeters would be more effective for neutron sensitivity improvement and these EPR dosemeters could be tested for dosimetric applications in Neutron Capture Therapy.

Hadrontherapy with proton and carbon ion scanning beams is an advanced radiation treatment modality mainly exploiting the finite range of those particles in the matter, to better spare critical organs close to the tumor volume as compared to photons. However, its complexity requires careful management of dosimetric uncertainties to guarantee patient safety. This study aims to reassess the suitability of alanine-based dosimetry for modern hadrontherapy applications. Alanine pellets based on electron spin resonance (ESR) were used as dosimeters. The response was taken from the peak-to-peak amplitude and compared to the ionization chamber one. Dose response and dependence on energy, beam direction, and linear energy transfer (LET), for both pristine Bragg peak and spread-out Bragg peak (SOBP) were evaluated. The ESR ratio x/y was evaluated as a function of LET and microwave power. Photon irradiations were performed with a 6 MV linear accelerator at the San Matteo Hospital, while with charged particles at CNAO, both located in Pavia, Italy. Alanine showed a linear dose-response for both protons and carbon ions in the range of 10-45 Gy. For carbon ions, a pronounced quenching effect in the Bragg peak and energy dependence were observed. Alanine effectiveness was reduced by up to 30% due to LET effects. Moreover, the use of the x/y ratio showed potential for LET differentiation. Alanine may be a promising dosimeter for hadrontherapy. However, further studies are required to investigate factors of correction due to the effects of LET and energy dependence.

The roundtable discussion at EPR BioDose 2024 focused on identifying challenges for using biodosimetry in a large nuclear incident and exploring potential solutions to strengthen preparedness and response frameworks. This report outlines the major themes discussed, including advancements in techniques, challenges in scaling operations, and the future of biodosimetry in emergency response. Initiated by International Association of Biological and EPR Radiation Dosimetry (IABERD), a group of experts comprised of professionals in academia, government and other agencies, were asked to discuss the question: 'When and how should biodosimetry be used for an unplanned radiation explosion in the short or long term?' This question challenged participants to consider a range of scenarios, from immediate triage in the aftermath of an incident to long-term health monitoring and risk assessment. Panelists acknowledged that, while biodosimetry plays a crucial role in rapidly assessing exposure levels to guide medical response, its practical implementation can vary based on scale, resources, and timing. They emphasized that in the short term, methods that provide quick, large-scale screening are important, whereas long-term strategies might include more detailed biological assessments to understand cumulative effects and potential health risks. Despite the difficulty of a one-size-fits-all approach, the insights gathered aimed to inform strategies that balance speed, accuracy, and sustainability in biodosimetry practices. Finally, panelists emphasized the need for better communication about preparedness with the general public and healthcare providers, and a more collaborative approach that also takes into account evaluating the practicality of various methods for triage or guiding treatment.

The combination of target and beam motions is a concern in radiotherapy, as it results in the so-called interplay effects. These effects may lead to an inappropriate dose distribution delivered to patients, potentially compromising treatment outcomes, being particularly common in the case of thoracic tumours. An excellent external radiotherapy treatment option - compared to conventional photon modality - is proton beams delivered with pencil beam scanning (PBS), which might offer better sparing of healthy tissues with comparable dose tumour coverage. This study, therefore, aimed to evaluate whether alanine, based on electron spin resonance (ESR), a well-established dosimeter, can be applied in the context of moving targets of clinical photon and proton beams and assessing interplay effects. Alanine/ESR dosimeters (Harwell, UK) inserted in an anthropomorphic moving phantom (CIRS, USA) were irradiated with photon and proton beams, at the San Matteo Hospital and Fondazione CNAO, respectively, both in Pavia (Italy). Different moving conditions, simulating or not abdominal compression (20-mm maximum respiratory excursion), were evaluated. ESR measurements were performed in an ELEXSYS spectrometer (Bruker, Germany), and the peak-to-peak amplitude was used to reconstruct the dose. Good agreement between planned and measured doses was obtained with deviations within 3.3 % and 2.2 % for photons (flattening-filter) and protons, respectively, in all moving conditions. No significant differences were observed as a function of the moving regimen. This study showed that alanine/ESR can be a suitable dosimetric system for use in end-to-end tests for moving targets, including the evaluation of interplay effects.