BACKGROUND: In recent years, targeted alpha therapy has gained importance in the clinics, and in particular, the alpha-emitter 225Ac plays a fundamental role in this clinical development. Nevertheless, depending on the chelating system no real diagnostic alternative has been established which shares similar chemical properties with this alpha-emitting radionuclide. In fact, the race to launch a diagnostic radionuclide to form a matched pair with 225Ac is still open, and 133La features attractive radiation properties to claim this place. However, in order to enable its translation into clinical use, upscaling of the production of this PET radionuclide is needed.
RESULTS: A study on optimal irradiation parameters, separation conditions and an exhaustive product characterization was carried out. In this framework, a proton irradiation of 2 h, 60 µA and 18.7 MeV produced 133La activities of up to 10.7 GBq at end of bombardment. In addition, the performance of four different chromatographic resins were tested and two optimized purification methods presented, taking approximately 20 min with a 133La recovery efficiencies of over 98%, decay corrected. High radionuclide purity and apparent molar activity was proved, of over 99.5% and 120 GBq/µmol, respectively, at end of purification. Furthermore, quantitative complexation of PSMA-617 and mcp-M-PSMA were obtained with molar activities up to 80 GBq/µmol. In addition, both 133La-radioconjugates offered high stability in serum, of over (98.5 ± 0.3)% and (99.20 ± 0.08)%, respectively, for up to 24 h. A first dosimetry estimation was also performed and it was calculated that an 133La application for imaging with between 350 and 750 MBq would only have an effective dose of 2.1-4.4 mSv, which is comparable to that of 18F and 68Ga based radiopharmaceuticals.
CONCLUSIONS: In this article we present an overarching study on 133La production, from the radiation parameters optimization to a clinical dose estimation. Lanthanum-133 activities in the GBq range could be produced, formulated as [133La]LaCl3 with high quality regarding radiolabeling and radionuclide purity. We believe that increasing the 133La availability will further promote the development of radiopharmaceuticals based on macropa or other chelators suitable for 225Ac.

Diffuse intrinsic pontine glioma (DIPG) is a rare childhood malignancy with poor prognosis. There are no effective treatment options other than external beam therapy. We conducted a pilot, first-in-human study using 124I-omburtamab imaging and theranostics as a therapeutic approach using a localized convection-enhanced delivery (CED) technique for administering radiolabeled antibody. We report the detailed pharmacokinetics and dosimetry results of intratumoral delivery of 124I-omburtamab. Methods: Forty-five DIPG patients who received 9.0-370.7 MBq of 124I-omburtamab intratumorally via CED underwent serial brain and whole-body PET/CT imaging at 3-5 time points after injection within 4, 24-48, 72-96, 120-144, and 168-240 h from the end of infusion. Serial blood samples were obtained for kinetic analysis. Whole-body, blood, lesion, and normal-tissue activities were measured, kinetic parameters (uptake and clearance half-life times) estimated, and radiation-absorbed doses calculated using the OLINDA software program. Results: All patients showed prominent activity within the lesion that was retained over several days and was detectable up to the last time point of imaging, with a mean 124I residence time in the lesion of 24.9 h and dose equivalent of 353 ± 181 mSv/MBq. Whole-body doses were low, with a dose equivalent of 0.69 ± 0.28 mSv/MBq. Systemic distribution and activities in normal organs and blood were low. Radiation dose to blood was very low, with a mean value of 0.27 ± 0.21 mGy/MBq. Whole-body clearance was monoexponential with a mean biologic half-life of 62.7 h and an effective half-life of 37.9 h. Blood clearance was biexponential, with a mean biologic half-life of 22.2 h for the rapid α phase and 155 h for the slower β phase. Conclusion: Intratumoral CED of 124I-omburtamab is a novel theranostics approach in DIPG. It allows for delivery of high radiation doses to the DIPG lesions, with high lesion activities and low systemic activities and high tumor-to-normal-tissue ratios and achieving a wide safety margin. Imaging of the actual therapeutic administration of 124I-omburtamab allows for direct estimation of the therapeutic lesion and normal-tissue-absorbed doses.

Over the last decades, the use of artificial intelligence, machine learning and deep learning in medical fields has skyrocketed. Well known for their results in segmentation, motion management and posttreatment outcome tasks, investigations of machine learning and deep learning models as fast dose calculation or quality assurance tools have been present since 2000. The main motivation for this increasing research and interest in artificial intelligence, machine learning and deep learning is the enhancement of treatment workflows, specifically dosimetry and quality assurance accuracy and time points, which remain important time-consuming aspects of clinical patient management. Since 2014, the evolution of models and architectures for dose calculation has been related to innovations and interest in the theory of information research with pronounced improvements in architecture design. The use of knowledge-based approaches to patient-specific methods has also considerably improved the accuracy of dose predictions. This paper covers the state of all known deep learning architectures and models applied to external radiotherapy with a description of each architecture, followed by a discussion on the performance and future of deep learning predictive models in external radiotherapy.

OBJECTIVE: To develop a machine learning-based pipeline for multi-organ/tissue personalized radiation dosimetry in CT.
METHODS: For the study, 95 chest CT scans and 85 abdominal CT scans were collected retrospectively. For each CT scan, a personalized Monte Carlo (MC) simulation was carried out. The produced 3D dose distributions and the respective CT examinations were utilized for the development of organ/tissue-specific dose prediction deep neural networks (DNNs). A pipeline that integrates a robust open-source organ segmentation tool with the dose prediction DNNs was developed for the automatic estimation of radiation doses for 30 organs/tissues including sub-volumes of the heart and lungs. The accuracy and time efficiency of the presented methodology was assessed. Statistical analysis (t-tests) was conducted to determine if the differences between the ground truth organ/tissue radiation dose estimates and the respective dose predictions were significant.
RESULTS: The lowest median percentage differences between MC-derived organ/tissue doses and DNN dose predictions were observed for the lung vessels (4.3%), small bowel (4.7%), pulmonary artery (4.7%), and colon (5.2%), while the highest differences were observed for the right lung\'s upper lobe (13.3%), spleen (13.1%), pancreas (12.1%), and stomach (11.6%). Statistical analysis showed that the differences were not significant (p-value > 0.18). Furthermore, the mean inference time, regarding the validation cohort, of the developed methodology was 77.0 ± 11.0 s.
CONCLUSIONS: The proposed workflow enables fast and accurate organ/tissue radiation dose estimations. The developed algorithms and dose prediction DNNs are publicly available ( https://github.com/eltzanis/multi-structure-CT-dosimetry ).
CONCLUSIONS: The accuracy and time efficiency of the developed pipeline compose a useful tool for personalized dosimetry in CT. By adopting the proposed workflow, institutions can utilize an automated pipeline for patient-specific dosimetry in CT.
CONCLUSIONS: Personalized dosimetry is ideal, but is time-consuming. The proposed pipeline composes a tool for facilitating patient-specific CT dosimetry in routine clinical practice. The developed workflow integrates a robust open-source segmentation tool with organ/tissue-specific dose prediction neural networks.

OBJECTIVE: This work explores the enhancement of ionization clustering and its radial dependence around a gold nanoparticle (NP), indicative of the induction of DNA lesions, a potential trigger for cell-death. Approach: Monte Carlo track structure simulations were performed to determine (a) the spectral fluence of incident photons and electrons in water around a gold NP under charged particle equilibrium conditions and (b) the density of ionization clusters produced on average as well as conditional on the occurrence of at east one interaction in the nanoparticle using Associated Volume Clustering. Absorbed dose was determined for comparison with a recent benchmark intercomparison. Reported quantities are normalized to primary fluence, allowing to establish a connection to macroscopic dosimetric quantities. Main results: The modification of the electron spectral fluence by the gold NP is minor and mainly occurs at low energies. The net fluence of electrons emitted from the NP is dominated by electrons resulting from photon interactions. Similar to the known dose enhancement, increased ionization clustering is limited to a distance from the NP surface of up to 200 nm. The number of clusters per energy imparted is increased at distances of up to 150 nm, and accordingly the enhancement in clustering notably surpasses that of dose enhancement. Smaller NPs cause noticeable peaks in the conditional frequency of clusters between 50 nm to 100 nm from the NP surface. Significance: This work shows that low energy electrons emitted by nanoparticles lead to an increase of ionization clustering in their vicinity exceeding that of energy imparted. While the electron component of the radiation field plays an important role in determining the background contribution to ionization clustering and energy imparted, the dosimetric effects of nanoparticles are governed by the interplay of secondary electron production by photon interaction and their ability to leave the nanoparticle. .

Background and purpose: Proton therapy has been shown to provide dosimetric benefits in comparison with IMRT when treating prostate cancer with whole pelvis radiation; however, the optimal proton beam arrangement has yet to be established. The aim of this study was to evaluate three different intensity-modulated proton therapy (IMPT) beam arrangements when treating the prostate bed and pelvis in the postoperative setting. Materials and Methods: Twenty-three post-prostatectomy patients were planned using three different beam arrangements: two-field (IMPT2B) (opposed laterals), three-field (IMPT3B) (opposed laterals inferiorly matched to a posterior-anterior beam superiorly), and four-field (IMPT4B) (opposed laterals inferiorly matched to two posterior oblique beams superiorly) arrangements. The prescription was 50 Gy radiobiological equivalent (GyE) to the pelvis and 70 GyE to the prostate bed. Comparisons were made using paired two-sided Wilcoxon signed-rank tests. Results: CTV coverages were met for all IMPT plans, with 99% of CTVs receiving ≥ 100% of prescription doses. All organ at risk (OAR) objectives were met with IMPT3B and IMPT4B plans, while several rectum objectives were exceeded by IMPT2B plans. IMPT4B provided the lowest doses to OARs for the majority of analyzed outcomes, with significantly lower doses than IMPT2B +/- IMPT3B for bladder V30-V50 and mean dose; bowel V15-V45 and mean dose; sigmoid maximum dose; rectum V40-V72.1, maximum dose, and mean dose; femoral head V37-40 and maximum dose; bone V40 and mean dose; penile bulb mean dose; and skin maximum dose. Conclusion: This study is the first to compare proton beam arrangements when treating the prostate bed and pelvis. four-field plans provided better sparing of the bladder, bowel, and rectum than 2- and three-field plans. The data presented herein may help inform the future delivery of whole pelvis IMPT for prostate cancer.

In this paper, we demonstrated the biological effects of acute low-dose neutrons on the whole body of rats and investigated the impact of that level of neutron dose to induce an in vivo radio-adaptive response. To understand the radio-adaptive response, the examined animals were exposed to acute neutron radiation doses of 5 and 10 mSv, followed by a 50 mSv challenge dose after 14 days. After irradiation, all groups receiving single and double doses were kept in cages for one day before sampling. The electron paramagnetic resonance (EPR) method was used to estimate the radiation-induced radicals in the blood, and some hematological parameters and lipid peroxidation (MDA) were determined. A comet assay was performed beside some of the antioxidant enzymes [catalase enzyme (CAT), superoxide dismutase (SOD), and glutathione (GSH)]. Seven groups of adult male rats were classified according to their dose of neutron exposure. Measurements of all studied markers are taken one week after harvesting, except for hematological markers, within 2 h. The results indicated lower production of antioxidant enzymes (CAT by 1.18-5.83%, SOD by 1.47-17.8%, and GSH by 11.3-82.1%). Additionally, there was an increase in red cell distribution width (RDW) (from 4.61 to 25.19%) and in comet assay parameters such as Tail Length, (from 6.16 to 10.81 µm), Tail Moment, (from 1.17 to 2.46 µm), and percentage of DNA in tail length (DNA%) (from 9.58 to 17.32%) in all groups exposed to acute doses of radiation ranging from 5 to 50 mSv, respectively. This emphasizes the ascending harmful effect with the increased acute thermal neutron doses. The values of the introduced factor of radio adaptive response for all markers under study reveal that the lower priming dose promotes a higher adaptation response and vice versa. Ultimately, the results indicate significant variations in DNA%, SOD enzyme levels, EPR intensity, total Hb concentration, and RDWs, suggesting their potential use as biomarkers for acute thermal neutron dosimetry. Further research is necessary to validate these measurements as biodosimetry for radiation exposure, including investigations involving the response impact of RAR with varied challenge doses and post-irradiation behavior.

OBJECTIVE: In diffusing alpha-emitters radiation therapy (DaRT), the diffusion-leakage (DL) model is used to determine the spatial distributions of the emitters and the corresponding alpha dose, critical for a successful treatment. This work presents how variations over realistic ranges of the DL model parameters related to desorption, diffusion and leakage processes affect the alpha dose distribution and the position of the clinically significant alpha particle 10 Gy isodose. This work also presents the effects of three modeling approximations: two source geometry approximations (solid cylinder instead of hollow, pixelized cross section instead of circular), and the single-source dose superposition (instead of the multiple sources direct dose calculation). Approach. A finite volume approach was used to develop numerical schemes to simulate the DL model in one, two and three dimensions and obtain the spatial distributions of the emitters. The corresponding alpha dose distributions were calculated under the assumption of a local deposition of the alpha particles\' energies. Variation ranges of the DL model parameters were based on previously published data. For each modeling approximation studied, the error and relative error on the alpha dose distribution were calculated and the displacement of the 10 Gy isodose was evaluated. Main results. Over realistic ranges, the desorption probabilities, diffusion lengths, and leakage probabilities respectively affect the position of the alpha particle 10 Gy isodose by ∼ 0.1 mm, ∼ 1.5 mm and ∼ 0.5 mm. The three modeling approximations studied have a negligible effect on the alpha particle 10 Gy isodose position, with displacements ≤ 0.01 mm. Significance. This work quantitatively evaluates the relative importance of different parameters and approximations in DaRT alpha dose calculations based on their impact not only on the dose variation at a given distance from the source but also on the displacement of clinically significant isodoses. .

[This corrects the article DOI: 10.3389/ftox.2024.1376118.].

UNASSIGNED: Organ dose distribution calculation in radiotherapy and knowledge about its side effects in cancer etiology is the most concern for medical physicists. Calculation of organ dose distribution for breast cancer treatment plans with Monte Carlo (MC) simulation is the main goal of this study.
UNASSIGNED: Elekta Precise linear accelerator (LINAC) photon mode was simulated and verified using the GEANT4 application for tomographic emission. Eight different radiotherapy treatment plans on RANDO\'s phantom left breast were produced with the ISOgray treatment planning system (TPS). The simulated plans verified photon dose distribution in clinical tumor volume (CTV) with TPS dose volume histogram (DVH) and gamma index tools. To verify photon dose distribution in out-of-field organs, the point dose measurement results were compared with the same point doses in the MC simulation. Eventually, the DVHs for out-of-field organs that were extracted from the TPS and MC simulation were compared.
UNASSIGNED: Based on the implementation of gamma index tools with 2%/2 mm criteria, the simulated LINAC output demonstrated high agreement with the experimental measurements. Plan simulation for in-field and out-of-field organs had an acceptable agreement with TPS and experimental measurement, respectively. There was a difference between DVHs extracted from the TPS and MC simulation for out-of-field organs in low-dose parts. This difference is due to the inability of the TPS to calculate dose distribution in out-of-field organs.
UNASSIGNED: Based on the results, it was concluded that the treatment plans with the MC simulation have a high accuracy for the calculation of out-of-field dose distribution and could play a significant role in evaluating the important role of dose distribution for second primary cancer estimation.