There is a growing need to develop lead-free shielding materials that are safe, low weight, durable, environmentally friendly, chemically and mechanically stable and customizable for specific applications. Fused deposition modeling (FDM), an additive manufacturing technique based on the extrusion of a thermoplastic filament into a 3D printed object one layer at a time, could be employed well in applications involving ionizing radiation due to its relatively low cost, design flexibility and high manufacturing precision. This study aimed at developing 3D printing composites that contain Titanium dioxide as a filler agent for shielding in a medical radiation environment. First, the effect of low-dose ionizing radiation (up to 15 Gy) on the mechanical properties of common 3D printing polymers, ABS, ULTRAT, PLA, NYLON, ASA and PETG, was investigated. Since ABS experienced the lowest variation in its ultimate tensile strength (±5%) and Young’s modulus (−5%/+11%), it was chosen as a matrix for a new extruded 3D filament containing TiO₂ at 1 wt.%, 3 wt.%, and 5 wt.%. With the incorporation of TiO₂ at different filler contents, the UTS of the ABS composites varied between 24.1 MPa and 28.4 MPa, with the highest value recorded for 3 wt.% TiO₂. Young’s modulus values were dependent on both the TiO₂ concentration and on the irradiation dose. In addition, the ABS/TiO₂ composites with a higher filler content (3 wt.% and 5 wt.%) maintained their attenuation ability even after exposure to a radiation dose of 100 Gy as opposed to pure ABS, which exhibited a ~2.5% reduction in its mass attenuation coefficient after exposure to the same dose of radiation. The pilot investigation performed demonstrated that the newly developed ABS/TiO₂ composite containing 5 wt.% of filler can be successfully employed to shield electronic devices operating in a radiotherapy room.

In radiation therapy, a bolus is used to improve dose distribution in superficial tumors; however, commercial boluses lack conformity to patient surface leading to the formation of an air gap between the bolus and patient surface and suboptimal tumor control. The aim of this study was to explore 3D-printing technology for the development of patient-specific conformal 3D-printed devices, which can be used for the radiation treatment of superficial head and neck cancer (HNC). Two 3D boluses (0.5 and 1.0 cm thick) for surface dose build-up and patient-specific 3D phantom were printed based on reconstruction of computed tomography (CT) images of a patient with HNC. The 3D-printed patient-specific phantom indicated good tissue equivalency (HU = −32) and geometric accuracy (DSC = 0.957). Both boluses indicated high conformity to the irregular skin surface with minimal air gaps (0.4–2.1 mm for 0.5 cm bolus and 0.6–2.2 mm for 1.0 cm bolus). The performed dose assessment showed that boluses of both thicknesses have comparable effectiveness, increasing the dose that covers 99% of the target volume by 52% and 26% for single field and intensity modulated fields, respectively, when compared with no bolus case. The performed investigation showed the potential of 3D printing in development of cost effective, patient specific and patient friendly conformal devices for dose verification in radiotherapy.

The essential component of modern radiation therapy is the application of steep dose gradients during patient treatment in order to maximize the radiation dose to the target volume and protect neighboring heathy tissues. However, volumetric dose distribution in an irradiated target is still a bottleneck of dose verification in modern radiotherapy. Dose gels are almost the only known dosimetry tool which allows for the evaluation of dose distribution in the irradiated volume due to gel’s polymerization upon irradiation. The accuracy of dose gel dosimetry has its own obstacle, which is related to the continuation of the gel’s polymerization after the radiation treatment procedure is finished. In this article, a method to monitor the polymerization dynamics of dose gels in real-time is proposed using a modified optical spectrometry system. Using the proposed method, the changes of the optical characteristics of irradiated nMAG dose gels in situ were assessed. The investigation revealed that the detectable polymerization in dose gel proceeds up to 6 h after irradiation. This time is significantly shorter compared with a commonly recommended 24 h waiting time allocated for polymer gel to settle. It was also found that dose rate significantly influences the temporal response of the nMAG dosimeter. By increasing the irradiation dose rate by a factor of 2, the time needed for the polymerization process to settle was increased by 22%. Identification of the gel’s post-irradiation polymerization time interval and its dependence on irradiation parameters will contribute to more accurate dose verification using dose gel dosimetry.

Background and Objectives: To our knowledge, this is the first study that investigated the prognostic value of radiomics features extracted from not only staging 18F-fluorodeoxyglucose positron emission tomography (FDG PET/CT) images, but also post-induction chemotherapy (ICT) PET/CT images. This study aimed to construct a training model based on radiomics features obtained from PET/CT in a cohort of patients with locally advanced head and neck squamous cell carcinoma treated with ICT, to predict locoregional recurrence, development of distant metastases, and the overall survival, and to extract the most significant radiomics features, which were included in the final model. Materials and Methods: This retrospective study analyzed data of 55 patients. All patients underwent PET/CT at the initial staging and after ICT. Along the classical set of 13 parameters, the original 52 parameters were extracted from each PET/CT study and an additional 52 parameters were generated as a difference between radiomics parameters before and after the ICT. Five machine learning algorithms were tested. Results: The Random Forest algorithm demonstrated the best performance (R² 0.963–0.998) in the majority of datasets. The strongest correlation in the classical dataset was between the time to disease progression and time to death (r = 0.89). Another strong correlation (r ≥ 0.8) was between higher-order texture indices GLRLM_GLNU, GLRLM_SZLGE, and GLRLM_ZLNU and standard PET parameters MTV, TLG, and SUVmax. Patients with a higher numerical expression of GLCM_ContrastVariance, extracted from the delta dataset, had a longer survival and longer time until progression (p = 0.001). Good correlations were observed between Discretized_SUVstd or Discretized_SUVSkewness and time until progression (p = 0.007). Conclusions: Radiomics features extracted from the delta dataset produced the most robust data. Most of the parameters had a positive impact on the prediction of the overall survival and the time until progression. The strongest single parameter was GLCM_ContrastVariance. Discretized_SUVstd or Discretized_SUVSkewness demonstrated a strong correlation with the time until progression.

This report analyzes the different standard methods of quantity measurement, which, when applied in the processes of receiving and transferring fuel quantities, lead to discrepancies and accounting losses. Three main factors contribute to these discrepancies: unavoidable errors of measuring devices (calibration uncertainty ranging from 0.1 to 0.5% at best), systematic errors due to non-applied corrections during transactions, and systematic errors due to different regulations, which result in inconsistent conversion rules applied throughout the entire purchase-production-sales chain. Modeling of air buoyancy effects showed that neglecting buoyancy correction can lead to measurable and economically significant discrepancies, especially in large-scale operations. The mass of light petroleum products can be underestimated by up to 0.15%, potentially resulting in approximately $3 million in annual financial losses for a medium-sized refinery processing 10,000 tonnes per day. These findings underscore the necessity of applying buoyancy corrections for conventional weighing, especially for liquid petroleum products (LPP) measured in open systems. Conversely, for LPG weighed in closed, pressurized containers, a constant correction factor (0.99985) applies, but its economic impact is negligible. Therefore, the study recommends omitting this LPG correction unless contractually required, to streamline processes and reduce complexity. Achieving result comparability throughout the entire petroleum supply chain requires implementing uniform quantity calculation provisions using calibrated instruments and standardized methods under different conditions. This necessitates that all measurement results are traceable to reference conditions (mass in vacuum, volume at +15 °C). The proposed algorithms for oil mass and volume measurement and recalculation highlight the need for unified international regulations and a robust system.

Tanks, as instruments in oil and its product’s amount measurement system chain, must be regularly maintained and metrologically inspected, as they significantly contribute to measurement uncertainty. However, when measuring a change in the amount of stored material (i.e., transfer), the measurement uncertainty becomes highly dependent not only on the mass of the transaction but also on the initial liquid level in the tank. This paper provides modeling of the uncertainties of the measuring system, which involves tanks, oil, and its product loading/unloading processes. It is shown that the accuracy of volume/mass measurement depends not only on the tank calibration table but also on the accuracy of other measuring instruments used and on the level of the liquid at the moment of measurement. The relative uncertainty of the measurement of the change in product mass depends linearly on the tank fill level present at the time of the transaction but nonlinearly on the transaction mass quantity.