The effects of low energy electrons in biological tissues have proved to lead to severe damages at the cellular and sub-cellular level. It is due to an increase in the relative biological effectiveness (RBE) of these electrons with a decrease in their penetration range. That is, lower the range higher will be its RBE.Therefore, accurate determination of low energy electron range becomes a key issue for radiation dosimetry. This work reports on in-water electron tracks evaluated at low kinetic energy (1-50 keV) using isotropic mono-energetic point source approach suitably implemented by different general-purpose Monte Carlo codes. For this aim, simulations were performed using PENELOPE, EGSnrc, MCNP6, FLUKA and Geant4-DNA Monte Carlo codes to obtain the particle range, R,R₉₀,R₅₀. Finally, evaluation of dose point kernel (DPK), as used for internal dosimetry, was carried out as an application example. Scaled dose point kernels (sDPK) were estimated for a range of mono-energetic low energy electron sources. The non-negligible differences among the calculated sDPK using different codes were obtained for energy electrons up to 5 keV. It was also observed that differences of in-water range for low-energy electrons, due to the different general-purpose Monte Carlo codes, affected the DPKs used for dosimetry by convolution approach. Finally, the 3D dosimetry was found to be almost not affected at macroscopic clinical scale, whereas non-negligible differences appeared at the microscopic level. Hence, a thorough validation of the used sDPKs have to be performed before they could be used in applications to derive any conclusions.

Fricke solution has a wide range of applications as radiation detector and dosimetry. It is particularly appreciated in terms of relevant comparative advantages, like tissue‐equivalence when prepared in aqueous media like gel matrix, continuous mapping capability, independence of dose rate and incident direction, as well as linear dose response. This work presents the development and characterization of an improved Fricke gel system, based on modified chemical compositions, making possible its application in clinical radiology due to its improved sensitivity. Properties of standard Fricke gel dosimeter for high‐dose levels are used as a starting point, and suitable chemical modifications are introduced and carefully investigated in order to attain high resolution for low‐dose ranges, like those corresponding to radiology interventions. The developed Fricke gel radiation dosimeter system achieves the expected typical dose‐dependency, showing linear response in the dose range from 20 up to 4000 mGy. Systematic investigations including several chemical compositions are carried out in order to obtain an adequate dosimeter response for low‐dose levels. A suitable composition from among those studied is selected as a good candidate for low‐dose‐level radiation dosimetry consisting of a modified Fricke solution fixed to a gel matrix containing benzoic acid along with sulfuric acid, ferrous sulfate, Xylenol orange, and tridistilled water. Dosimeter samples are prepared in standard vials for in‐phantom irradiation and further characterization by spectrophotometry measuring visible light transmission and absorbance before and after irradiation. Samples are irradiated using typical X‐ray tubes for radiology and calibrated Farmer‐type ionization chamber is used as reference to measure dose rates inside phantoms at vial locations. Once sensitive material composition is optimized, dose‐response curves show significant improvement regarding overall sensitivity for low dose levels. The aim of this work consists of implementing the optimized gel dosimeter to perform direct measurements of absorbed dose in samples irradiated during microcomputed tomography scanning in order to preliminary assess dose levels for further scanning of small animals for further applications in veterinary and paleontology. As a first attempt, dose distributions were measured in water‐equivalent phantoms having dimensions comparable to small animals, 100 to 1000 cm³, approximately. According to the obtained results, it is found that the proposed method shows satisfactory reliability and adequate performance for a promising gel dosimetry system.PACS number(s): 87.53.Bn, 87.57.uq, 87.59.‐e

Purpose: Absorbed dose calculation by kernel convolution requires the prior determination of dose point kernels (DPK). This study reports on the design, implementation, and test of a multi-target regressor approach to generate the DPKs for monoenergetic sources and a model to obtain DPKs for beta emitters.Methods: DPK for monoenergetic electron sources were calculated using the FLUKA Monte Carlo (MC) code for many materials of clinical interest and initial energies ranging from 10 to 3000 keV. Regressor Chains (RC) with three different coefficients regularization/shrinkage models were used as base regressors. Electron monoenergetic scaled DPKs (sDPKs) were used to assess the corresponding sDPKs for beta emitters typically used in nuclear medicine, which were compared against reference published data. Finally, the beta emitters sDPK were applied to a patient-specific case calculating the Voxel Dose Kernel (VDK) for a hepatic radioembolization treatment with $$^{90}$$90 Y.Results: The three trained machine learning models demonstrated a promising capacity to predict the sDPK for both monoenergetic emissions and beta emitters of clinical interest attaining differences lower than $$10\%$$10% in the mean average percentage error (MAPE) as compared with previous studies. Furthermore, differences lower than $$7 \%$$7% were obtained for the absorbed dose in patient-specific dosimetry comparing against full stochastic MC calculations.Conclusion: An ML model was developed to assess dosimetry calculations in nuclear medicine. The implemented approach has shown the capacity to accurately predict the sDPK for monoenergetic beta sources in a wide range of energy in different materials. The ML model to calculate the sDPK for beta-emitting radionuclides allowed to obtain VDK useful to achieve reliable patient-specific absorbed dose distributions required short computation times.

Nanoparticles have proven to be biocompatible and suitable for many biomedical applications. Currently, hyperthermia cancer treatments based on Fe nanoparticle infusion excited by alternating magnetic fields are commonly used. In addition to this, MRI-based image-guided radiotherapy represents, nowadays, one of the most promising accurate radiotherapy modalities. Hence, assessing the feasibility of combining both techniques requires preliminary characterization of the corresponding dosimetry effects. The present work reports on a theoretical and numerical simulation feasibility study aimed at pointing out preliminary dosimetry issues. Spatial dose distributions incorporating magnetic nanoparticles in MRI-based image-guided radiotherapy have been obtained by Monte Carlo simulation approaches accounting for all relevant radiation interaction properties as well as charged particles coupling with strong external magnetic fields, which are representative of typical MRI-LINAC devices. Two main effects have been evidenced: local dose enhancement (up to 60% at local level) within the infused volume, and non-negligible changes in the dose distribution at the interfaces between different tissues, developing to over 70% for low-density anatomical cavities. Moreover, cellular uptakes up to 10% have been modeled by means of considering different Fe nanoparticle concentrations. A theoretical temperature-dependent model for the thermal enhancement ratio (TER) has been used to account for radiosensitization due to hyperthermia. The outcomes demonstrated the reliability of the Monte Carlo approach in accounting for strong magnetic fields and mass distributions from patient-specific anatomy CT scans to assess dose distributions in MRI-based image-guided radiotherapy combined with magnetic nanoparticles, while the hyperthermic radiosensitization provides further and synergic contributions.