Objective. Protons have advantageous dose distributions and are increasingly used in cancer therapy. At the depth of the Bragg peak range, protons produce a mixed radiation field consisting of low- and high-linear energy transfer (LET) components, the latter of which is characterized by an increased ionization density on the microscopic scale associated with increased biological effectiveness. Prediction of the yield and LET of primary and secondary charged particles at a certain depth in the patient is performed by Monte Carlo simulations but is difficult to verify experimentally. Approach. Here, the results of measurements performed with Timepix detector in the mixed radiation field produced by a therapeutic proton beam in water are presented and compared to Monte Carlo simulations. The unique capability of the detector to perform high-resolution single particle tracking and identification enhanced by artificial intelligence allowed to resolve the particle type and measure the deposited energy of each particle comprising the mixed radiation field. Based on the collected data, biologically important physics parameters, the LET of single protons and dose-averaged LET, were computed. Main results. An accuracy over 95% was achieved for proton recognition with a developed neural network model. For recognized protons, the measured LET spectra generally agree with the results of Monte Carlo simulations. The mean difference between dose-averaged LET values obtained from measurements and simulations is 17%. We observed a broad spectrum of LET values ranging from a fraction of keV μm⁻¹ to about 10 keV μm⁻¹ for most of the measurements performed in the mixed radiation fields. Significance. It has been demonstrated that the introduced measurement method provides experimental data for validation of LET_D or LET spectra in any treatment planning system. The simplicity and accessibility of the presented methodology make it easy to be translated into a clinical routine in any proton therapy facility.

We investigated the relationship between RBE-weighted dose (DRBE) calculated with constant (cRBE) and variable RBE (vRBE), dose-averaged linear energy transfer (LETd) and the risk of radiographic changes in skull base patients treated with protons. Clinical treatment plans of 45 patients were recalculated with Monte Carlo tool FRED. Radiographic changes (i.e. edema and/or necrosis) were identified by MRI. Dosimetric parameters for cRBE and vRBE were computed. Biological margin extension and voxel-based analysis were employed looking for association of DRBE(vRBE) and LETd with brain edema and/or necrosis. When using vRBE, Dmax in the brain was above the highest dose limits for 38% of patients, while such limit was never exceeded assuming cRBE. Similar values of Dmax were observed in necrotic regions, brain and temporal lobes. Most of the brain necrosis was in proximity to the PTV. The voxel-based analysis did not show evidence of an association with high LETd values. When looking at standard dosimetric parameters, the higher dose associated with vRBE seems to be responsible for an enhanced risk of radiographic changes. However, as revealed by a voxel-based analysis, the large inter-patient variability hinders the identification of a clear effect for high LETd.

A questionnaire was developed by the members of WG12 of EURADOS in order to establish an overview of the current status of eye lens radiation dose monitoring in hospitals. The questionnaire was sent to medical physicists and radiation protection officers in hospitals across Europe. Specific topics were addressed in the questionnaire such as: knowledge of the proposed eye lens dose limit; monitoring and dosimetry issues; training and radiation protection measures. The results of the survey highlighted that the new eye lens dose limit can be exceeded in interventional radiology procedures and that eye lens protection is crucial. Personnel should be properly trained in how to use protective equipment in order to keep eye lens doses as low as reasonably achievable. Finally, the results also highlighted the need to improve the design of eye dosemeters in order to ensure satisfactory use by workers.

Measurements of the response of thermoluminescent (TL) detectors after gamma ray doses high enough to observe signal saturation provide input to microdosimetric models which relate this gamma-ray response with the energy response after low doses of photons (gamma rays and low-energy X rays) and after high-LET irradiation. To measure their gamma ray response up to saturation, LiF:Mg,Ti (MTS-7 and MTT), LiF:Mg,Cu,P (MCP-7), CaSO₄:Dy (KCD) and Al₂O₃:C detectors were irradiated with ⁶⁰Co gamma rays over the range 1–5000 Gy. The X-ray photon energy response and TL efficiency (relative to gamma rays) after doses of beta rays and alpha particles, were also measured, for CaSO₄:Dy and for Al₂O₃:C. Microdosimetric and track structure modelling was then applied to the experimental data. In a manner similar to LiF:Mg,Cu,P, the experimentally observed under response of α-Al₂O₃:C to X rays <100 keV, compared with cross-section calculations, is explained as a microdosimetric effect caused by the saturation of response of this detector without prior supralinearity (saturation of traps along the tracks). The enhanced X-ray photon energy response of CaSO₄:Dy is related to the supralinearity observed in this material after high gamma ray doses, similarly to that in LiF:Mg,Ti. The discussed model approaches support the general rule relating dose-, energy- and ionisation density-responses in TL detectors: if their gamma ray response is sublinear prior to saturation, the measured photon energy response is lower, and if it is supralinear, it may be higher than that expected from the calculation of the interaction cross sections alone. Since similar rules have been found to apply to other solid-state detector systems, microdosimetry may offer a valuable contribution to solid-state dosimetry even prior to mechanistic explanations of physical phenomena in different TL detectors.

Objective. This paper reports on the implementation and shows examples of the use of the ProTheRaMon framework for simulating the delivery of proton therapy treatment plans and range monitoring using positron emission tomography (PET). ProTheRaMon offers complete processing of proton therapy treatment plans, patient CT geometries, and intra-treatment PET imaging, taking into account therapy and imaging coordinate systems and activity decay during the PET imaging protocol specific to a given proton therapy facility. We present the ProTheRaMon framework and illustrate its potential use case and data processing steps for a patient treated at the Cyclotron Centre Bronowice (CCB) proton therapy center in Krakow, Poland. Approach. The ProTheRaMon framework is based on GATE Monte Carlo software, the CASToR reconstruction package and in-house developed Python and bash scripts. The framework consists of five separated simulation and data processing steps, that can be further optimized according to the user’s needs and specific settings of a given proton therapy facility and PET scanner design. Main results. ProTheRaMon is presented using example data from a patient treated at CCB and the J-PET scanner to demonstrate the application of the framework for proton therapy range monitoring. The output of each simulation and data processing stage is described and visualized. Significance. We demonstrate that the ProTheRaMon simulation platform is a high-performance tool, capable of running on a computational cluster and suitable for multi-parameter studies, with databases consisting of large number of patients, as well as different PET scanner geometries and settings for range monitoring in a clinical environment. Due to its modular structure, the ProTheRaMon framework can be adjusted for different proton therapy centers and/or different PET detector geometries. It is available to the community via github (Borys et al 2022).