Dose and DNA damage modelling of diffusing alpha-emitters radiation therapy using Geant4.

PURPOSE: Diffusing alpha-emitters radiation therapy (DaRT) is a brachytherapy technique using α-particles to treat solid tumours. The high linear energy transfer (LET) and short range of α-particles make them good candidates for the targeted treatment of cancer. Treatment planning of DaRT requires a good understanding of the dose from α-particles and the other particles released in the 224Ra decay chain. METHODS: The Geant4 Monte Carlo toolkit has been used to simulate a DaRT seed to better understand the dose contribution from all particles and simulate the DNA damage due to this treatment. RESULTS: Close to the seed α-particles deliver the majority of dose, however at radial distances greater than 4 mm, the contribution of ß-particles is greater. The RBE has been estimated as a function of number of double strand breaks (DSBs) and complex DSBs. A maximum seed spacing of 5.5 mm and 6.5 mm was found to deliver at least 20 Gy RBE weighted dose between the seeds for RBEDSB and RBEcDSB respectively. CONCLUSIONS: The DNA damage changes with radial distance from the seed and has been found to become less complex with distance, which is potentially easier for the cell to repair. Close to the seed α-particles contribute the majority of dose, however the contribution from other particles cannot be neglected and may influence the choice of seed spacing.

Impact of deep learning image reconstruction on volumetric accuracy and image quality of pulmonary nodules with different morphologies in low-dose CT.

BACKGROUND: This study systematically compares the impact of innovative deep learning image reconstruction (DLIR, TrueFidelity) to conventionally used iterative reconstruction (IR) on nodule volumetry and subjective image quality (IQ) at highly reduced radiation doses. This is essential in the context of low-dose CT lung cancer screening where accurate volumetry and characterization of pulmonary nodules in repeated CT scanning are indispensable. MATERIALS AND METHODS: A standardized CT dataset was established using an anthropomorphic chest phantom (Lungman, Kyoto Kaguku Inc., Kyoto, Japan) containing a set of 3D-printed lung nodules including six diameters (4 to 9 mm) and three morphology classes (lobular, spiculated, smooth), with an established ground truth. Images were acquired at varying radiation doses (6.04, 3.03, 1.54, 0.77, 0.41 and 0.20 mGy) and reconstructed with combinations of reconstruction kernels (soft and hard kernel) and reconstruction algorithms (ASIR-V and DLIR at low, medium and high strength). Semi-automatic volumetry measurements and subjective image quality scores recorded by five radiologists were analyzed with multiple linear regression and mixed-effect ordinal logistic regression models. RESULTS: Volumetric errors of nodules imaged with DLIR are up to 50% lower compared to ASIR-V, especially at radiation doses below 1 mGy and when reconstructed with a hard kernel. Also, across all nodule diameters and morphologies, volumetric errors are commonly lower with DLIR. Furthermore, DLIR renders higher subjective IQ, especially at the sub-mGy doses. Radiologists were up to nine times more likely to score the highest IQ-score to these images compared to those reconstructed with ASIR-V. Lung nodules with irregular margins and small diameters also had an increased likelihood (up to five times more likely) to be ascribed the best IQ scores when reconstructed with DLIR. CONCLUSION: We observed that DLIR performs as good as or even outperforms conventionally used reconstruction algorithms in terms of volumetric accuracy and subjective IQ of nodules in an anthropomorphic chest phantom. As such, DLIR potentially allows to lower the radiation dose to participants of lung cancer screening without compromising accurate measurement and characterization of lung nodules.

Influence of deep learning image reconstruction algorithm for reducing radiation dose and image noise compared to iterative reconstruction and filtered back projection for head and chest computed tomography examinations: a systematic review.

Background: The most recent advances in Computed Tomography (CT) image reconstruction technology are Deep learning image reconstruction (DLIR) algorithms. Due to drawbacks in Iterative reconstruction (IR) techniques such as negative image texture and nonlinear spatial resolutions, DLIRs are gradually replacing them. However, the potential use of DLIR in Head and Chest CT has to be examined further. Hence, the purpose of the study is to review the influence of DLIR on Radiation dose (RD), Image noise (IN), and outcomes of the studies compared with IR and FBP in Head and Chest CT examinations. Methods: We performed a detailed search in PubMed, Scopus, Web of Science, Cochrane Library, and Embase to find the articles reported using DLIR for Head and Chest CT examinations between 2017 to 2023. Data were retrieved from the short-listed studies using Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines. Results: Out of 196 articles searched, 15 articles were included. A total of 1292 sample size was included. 14 articles were rated as high and 1 article as moderate quality. All studies compared DLIR to IR techniques. 5 studies compared DLIR with IR and FBP. The review showed that DLIR improved IQ, and reduced RD and IN for CT Head and Chest examinations. Conclusions: DLIR algorithm have demonstrated a noted enhancement in IQ with reduced IN for CT Head and Chest examinations at lower dose compared with IR and FBP. DLIR showed potential for enhancing patient care by reducing radiation risks and increasing diagnostic accuracy.

Development of shielding evaluation and management program for O-ring type linear accelerators.

The shielding parameters can vary depending on the geometrical structure of the linear accelerators (LINAC), treatment techniques, and beam energies. Recently, the introduction of O-ring type linear accelerators is increasing. The objective of this study is to evaluate the shielding parameters of new type of linac using a dedicated program developed by us named ORSE (O-ring type Radiation therapy equipment Shielding Evaluation). The shielding evaluation was conducted for a total of four treatment rooms including Elekta Unity, Varian Halcyon, and Accuray Tomotherapy. The developed program possesses the capability to calculate transmitted dose, maximum treatable patient capacity, and shielding wall thickness based on patient data. The doses were measured for five days using glass dosimeters to compare with the results of program. The IMRT factors and use factors obtained from patient data showed differences of up to 65.0% and 33.8%, respectively, compared to safety management report. The shielding evaluation conducted in each treatment room showed that the transmitted dose at every location was below 1% of the dose limit. The results of program and measurements showed a maximum difference of 0.003 mSv/week in transmitted dose. The ORSE program allows for the shielding evaluation results to the clinical environment of each institution based on patient data.

Radiation exposure during orthodontic treatment: risk to children and adolescents.

OBJECTIVES: To estimate radiation risk to children and adolescents during orthodontic treatment by retrieving number and type of radiographs from the patient records. MATERIAL AND METHODS: Radiographs, along with justifications for radiation exposure, were obtained retrospectively from the patient records of 1,790 children and adolescents referred to two Swedish orthodontic clinics. Data were grouped according to treatment stage: treatment planning, treatment, and follow-up. Estimated risk was calculated using the concept of effective dose. RESULTS: Each patient had received around seven radiographs for orthodontic purposes. The most common exposures during treatment planning were one panoramic, one lateral, and three intraoral periapical radiographs. A small number of patients received a tomographic examination (8.2%). Few justifications for treatment planning and follow-up, but more in the actual treatment stage, had been recorded. The most common examinations were to assess root resorption and the positions of unerupted teeth, or simply carry out an unspecified control. The estimated risk of developing fatal cancer was considered low. The radiation risk from orthodontic treatment was equivalent to about 5-10 days of natural background radiation. CONCLUSIONS: Children and adolescents sometimes undergo multiple radiographic examinations, but despite the low radiation burden, accumulated radiation exposure should be considered and justified in young patients.

Usability of sand samples in TL Radiation Dosimetry.

This study investigated natural sand thermoluminescence (TL) response as a possible option for retrospective high-dose gamma dosimetry. The natural sand under investigation was collected from six locations with selection criteria for sampling sites covering the highest probability of exposure to unexpected radiation on the Egyptian coast. Dose-response, glow curve, chemical composition, linearity, and fading rate for different sand samples were studied. Energy Dispersive X-ray Spectroscopy (EDX) analysis revealed differences in chemical composition among the various geological sites, leading to variations in TL glow curve intensity. Sand samples collected from Ras Sedr, Taba, Suez, and Enshas showed similar TL patterns, although with different TL intensities. Beach sands of Matrouh and North Coastal with a high calcite content did not show a clear linear response to the TL technique, in the dose range of 10 Gy up to 30 kGy. The results show that most sand samples are suitable as a radiation dosimeter at accidental levels of exposure. It is proposed here that for high-dose gamma dosimetry with doses ranging from 3 to 10 kGy, a single calibration factor might be enough for TL measurements using sand samples. However, proper calibration might allow dose assessment for doses even up to 30 kGy. Most of the investigated sand samples had nearly stable fading rates after seven days of storage. The Ras Sedr sands sample was the most reliable for retrospective dose reconstruction.

[Low-dose CT reconstruction based on high-dimensional partial differential equation projection recovery].

OBJECTIVE: We propose a low-dose CT reconstruction method using partial differential equation (PDE) denoising under high-dimensional constraints. METHODS: The projection data were mapped into a high-dimensional space to construct a high-dimensional representation of the data, which were updated by moving the points in the high-dimensional space. The data were denoised using partial differential equations and the CT image was reconstructed using the FBP algorithm. RESULTS: Compared with those by FBP, PWLS-QM and TGV-WLS methods, the relative root mean square error of the Shepp-Logan image reconstructed by the proposed method were reduced by 68.87%, 50.15% and 27.36%, the structural similarity values were increased by 23.50%, 8.83% and 1.62%, and the feature similarity values were increased by 17.30%, 2.71% and 2.82%, respectively. For clinical image reconstruction, the proposed method, as compared with FBP, PWLS-QM and TGV-WLS methods, resulted in reduction of the relative root mean square error by 42.09%, 31.04% and 21.93%, increased the structural similarity values by 18.33%, 13.45% and 4.63%, and increased the feature similarity values by 3.13%, 1.46% and 1.10%, respectively. CONCLUSION: The new method can effectively reduce the streak artifacts and noises while maintaining the spatial resolution in reconstructed low-dose CT images.

Reply to comment on 'Modeling for predicting survival fraction of cells after ultra-high dose rate irradiation'.

Liew and Mairani commented on our paper 'Modeling for predicting survival fraction of cells after ultra-high dose rate irradiation' (Shiraishiet al2024aPhys. Med. Biol.69015017), which proposed a biophysical model to predict the dose-response curve of surviving cell fractions after ultra-high dose rate irradiation following conventional dose rate irradiation by considering DNA damage yields. They suggested the need to consider oxygen concentration in our prediction model and possible issues related to the data selection process used for the benchmarking test in our paper. In this reply, we discuss the limitations of both the present model and the available experimental data for determining the model's parameters. We also demonstrate that our proposed model can reproduce the experimental survival data even when using only the experimental DNA damage data measured reliably under normoxic conditions.

Which is a real valuable screening tool for lung cancer and measure thoracic diseases, chest radiography or low-dose computed tomography?: A review on the current status of Japan and other countries.

Chest radiography (CR) has been used as a screening tool for lung cancer and the use of low-dose computed tomography (LDCT) is not recommended in Japan. We need to reconsider whether CR really contributes to the early detection of lung cancer. In addition, we have not well discussed about other major thoracic disease detection by CR and LDCT compared with lung cancer despite of its high frequency. We review the usefulness of CR and LDCT as veridical screening tools for lung cancer and other thoracic diseases. In the case of lung cancer, many studies showed that LDCT has capability of early detection and improving outcomes compared with CR. Recent large randomized trial also supports former results. In the case of chronic obstructive pulmonary disease (COPD), LDCT contributes to early detection and leads to the implementation of smoking cessation treatments. In the case of pulmonary infections, LDCT can reveal tiny inflammatory changes that are not observed on CR, though many of these cases improve spontaneously. Therefore, LDCT screening for pulmonary infections may be less useful. CR screening is more suitable for the detection of pulmonary infections. In the case of cardiovascular disease (CVD), CR may be a better screening tool for detecting cardiomegaly, whereas LDCT may be a more useful tool for detecting vascular changes. Therefore, the current status of thoracic disease screening is that LDCT may be a better screening tool for detecting lung cancer, COPD, and vascular changes. CR may be a suitable screening tool for pulmonary infections and cardiomegaly.

An adult and pediatric size-based contrast administration reduction phantom study for single and dual-energy CT through preservation of contrast-to-noise ratio.

BACKGROUND: Global shortages of iodinated contrast media (ICM) during COVID-19 pandemic forced the imaging community to use ICM more strategically in CT exams. PURPOSE: The purpose of this work is to provide a quantitative framework for preserving iodine CNR while reducing ICM dosage by either lowering kV in single-energy CT (SECT) or using lower energy virtual monochromatic images (VMI) from dual-energy CT (DECT) in a phantom study. MATERIALS AND METHODS: In SECT study, phantoms with effective diameters of 9.7, 15.9, 21.1, and 28.5 cm were scanned on SECT scanners of two different manufacturers at a range of tube voltages. Statistical based iterative reconstruction and deep learning reconstruction were used. In DECT study, phantoms with effective diameters of 20, 29.5, 34.6, and 39.7 cm were scanned on DECT scanners from three different manufacturers. VMIs were created from 40 to 140 keV. ICM reduction by lowering kV levels for SECT or switching from SECT to DECT was calculated based on the linear relationship between iodine CNR and its concentration under different scanning conditions. RESULTS: On SECT scanner A, while matching CNR at 120 kV, ICM reductions of 21%, 58%, and 72% were achieved at 100, 80, and 70 kV, respectively. On SECT scanner B, 27% and 80% ICM reduction was obtained at 80 and 100 kV. On the Fast-kV switch DECT, with CNR matched at 120 kV, ICM reductions were 35%, 30%, 23%, and 15% with VMIs at 40, 50, 60, and 68 keV, respectively. On the dual-source DECT, ICM reductions were 52%, 48%, 42%, 33%, and 22% with VMIs at 40, 50, 60, 70, and 80 keV. On the dual-layer DECT, ICM reductions were 74%, 62%, 45%, and 22% with VMIs at 40, 50, 60, and 70 keV. CONCLUSIONS: Our work provided a quantitative baseline for other institutions to further optimize their scanning protocols to reduce the use of ICM.

Knowledge-based planning for Gamma Knife.

BACKGROUND: Current methods for Gamma Knife (GK) treatment planning utilizes either manual forward planning, where planners manually place shots in a tumor to achieve a desired dose distribution, or inverse planning, whereby the dose delivered to a tumor is optimized for multiple objectives based on established metrics. For other treatment modalities like IMRT and VMAT, there has been a recent push to develop knowledge-based planning (KBP) pipelines to address the limitations presented by forward and inverse planning. However, no complete KBP pipeline has been created for GK. PURPOSE: To develop a novel (KBP) pipeline, using inverse optimization (IO) with 3D dose predictions for GK. METHODS: Data were obtained for 349 patients from Sunnybrook Health Sciences Centre. A 3D dose prediction model was trained using 322 patients, based on a previously published deep learning methodology, and dose predictions were generated for the remaining 27 out-of-sample patients. A generalized IO model was developed to learn objective function weights from dose predictions. These weights were then used in an inverse planning model to generate deliverable treatment plans. A dose mimicking (DM) model was also implemented for comparison. The quality of the resulting plans was compared to their clinical counterparts using standard GK quality metrics. The performance of the models was also characterized with respect to the dose predictions. RESULTS: Across all quality metrics, plans generated using the IO pipeline performed at least as well as or better than the respective clinical plans. The average conformity and gradient indices of IO plans was 0.737 ± $\pm$ 0.158 and 3.356 ± $\pm$ 1.030 respectively, compared to 0.713 ± $\pm$ 0.124 and 3.452 ± $\pm$ 1.123 for the clinical plans. IO plans also performed better than DM plans for five of the six quality metrics. Plans generated using IO also have average treatment times comparable to that of clinical plans. With regards to the dose predictions, predictions with higher conformity tend to result in higher quality KBP plans. CONCLUSIONS: Plans resulting from an IO KBP pipeline are, on average, of equal or superior quality compared to those obtained through manual planning. The results demonstrate the potential for the use of KBP to generate GK treatment with minimal human intervention.

Assessment of radiation in fishes derived from radiocesium in the port of Fukushima Daiichi nuclear power plant.

This study established specialized radiation dose models to evaluate the internal radiation doses derived from 137Cs and 134Cs in fishes in the port of the Fukushima Daiichi Nuclear Power Plant from 2012 to 2023. By August 2018, the activities of 134Cs and 137Cs in fishes decreased at the T1/2 of 176 d and 191 d, respectively. The corresponding mass concentrations were far lower than 1 mg/kg and the chemical toxicity can be negligible. Regarding radiotoxicity, 18,000 Bq/kgfresh weight of 134Cs and 137Cs in grouper Sebastes schlegelii produced 276 µGy/h of radiation dose, which was below the no-effect-dose-rate benchmarks (400 µGy/h). 740,000 Bq/kgfresh weight of 134Cs and 137Cs in greenling Hexagrammos otakii produced 12,600 µGy/h of radiation dose, which was much higher than 400 µGy/h, indicating the possibility of radiation effects. If a person eats these two reported fishes, the resulting committed effective doses for humans are 7.7 µSv and 6.31 mSv, respectively.

The effect of electron backscatter and charge build up in media on beam current transformer signal for ultra-high dose rate (FLASH) electron beam monitoring.

Objective.Beam current transformers (BCT) are promising detectors for real-time beam monitoring in ultra-high dose rate (UHDR) electron radiotherapy. However, previous studies have reported a significant sensitivity of the BCT signal to changes in source-to-surface distance (SSD), field size, and phantom material which have until now been attributed to the fluctuating levels of electrons backscattered within the BCT. The purpose of this study is to evaluate this hypothesis, with the goal of understanding and mitigating the variations in BCT signal due to changes in irradiation conditions.Approach.Monte Carlo simulations and experimental measurements were conducted with a UHDR-capable intra-operative electron linear accelerator to analyze the impact of backscattered electrons on BCT signal. The potential influence of charge accumulation in media as a mechanism affecting BCT signal perturbation was further investigated by examining the effects of phantom conductivity and electrical grounding. Finally, the effectiveness of Faraday shielding to mitigate BCT signal variations is evaluated.Main Results.Monte Carlo simulations indicated that the fraction of electrons backscattered in water and on the collimator plastic at 6 and 9 MeV is lower than 1%, suggesting that backscattered electrons alone cannot account for the observed BCT signal variations. However, our experimental measurements confirmed previous findings of BCT response variation up to 15% for different field diameters. A significant impact of phantom type on BCT response was also observed, with variations in BCT signal as high as 14.1% when comparing measurements in water and solid water. The introduction of a Faraday shield to our applicators effectively mitigated the dependencies of BCT signal on SSD, field size, and phantom material.Significance.Our results indicate that variations in BCT signal as a function of SSD, field size, and phantom material are likely driven by an electric field originating in dielectric materials exposed to the UHDR electron beam. Strategies such as Faraday shielding were shown to effectively prevent these electric fields from affecting BCT signal, enabling reliable BCT-based electron UHDR beam monitoring.

CNN application for automated determination of the patient's size to obtain the size-specific dose estimated in CT.

Introduction. The currently available dosimetry techniques in computed tomography can be inaccurate which overestimate the absorbed dose. Therefore, we aimed to provide an automated and fast methodology to more accurately calculate the SSDE usingDwobtained by using CNN from thorax and abdominal CT study images.Methods. The SSDE was determined from the 200 records files. For that purpose, patients' size was measured in two ways: (a) by developing an algorithm following the AAPM Report No. 204 methodology; and (b) using a CNN according to AAPM Report No. 220.Results. The patient's size measured by the in-house software in the region of thorax and abdomen was 27.63 ± 3.23 cm and 28.66 ± 3.37 cm, while CNN was 18.90 ± 2.6 cm and 21.77 ± 2.45 cm. The SSDE in thorax according to 204 and 220 reports were 17.26 ± 2.81 mGy and 23.70 ± 2.96 mGy for women and 17.08 ± 2.09 mGy and 23.47 ± 2.34 mGy for men. In abdomen was 18.54 ± 2.25 mGy and 23.40 ± 1.88 mGy in women and 18.37 ± 2.31 mGy and 23.84 ± 2.36 mGy in men.Conclusions. Implementing CNN-based automated methodologies can contribute to fast and accurate dose calculations, thereby improving patient-specific radiation safety in clinical practice.

Influence of helical pitch and gantry rotation time on image quality and file size in ultrahigh-resolution photon-counting detector CT.

The goal of this experimental study was to quantify the influence of helical pitch and gantry rotation time on image quality and file size in ultrahigh-resolution photon-counting CT (UHR-PCCT). Cervical and lumbar spine, pelvis, and upper legs of two fresh-frozen cadaveric specimens were subjected to nine dose-matched UHR-PCCT scan protocols employing a collimation of 120 × 0.2 mm with varying pitch (0.3/1.0/1.2) and rotation time (0.25/0.5/1.0 s). Image quality was analyzed independently by five radiologists and further substantiated by placing normed regions of interest to record mean signal attenuation and noise. Effective mAs, CT dose index (CTDIvol), size-specific dose estimate (SSDE), scan duration, and raw data file size were compared. Regardless of anatomical region, no significant difference was ascertained for CTDIvol (p ≥ 0.204) and SSDE (p ≥ 0.240) among protocols. While exam duration differed substantially (all p ≤ 0.016), the lowest scan time was recorded for high-pitch protocols (4.3 ± 1.0 s) and the highest for low-pitch protocols (43.6 ± 15.4 s). The combination of high helical pitch and short gantry rotation times produced the lowest perceived image quality (intraclass correlation coefficient 0.866; 95% confidence interval 0.807-0.910; p < 0.001) and highest noise. Raw data size increased with acquisition time (15.4 ± 5.0 to 235.0 ± 83.5 GByte; p ≤ 0.013). Rotation time and pitch factor have considerable influence on image quality in UHR-PCCT and must therefore be chosen deliberately for different musculoskeletal imaging tasks. In examinations with long acquisition times, raw data size increases considerably, consequently limiting clinical applicability for larger scan volumes.

Two-view topogram-based anatomy-guided CT reconstruction for prospective risk minimization.

To facilitate a prospective estimation of the effective dose of an CT scan prior to the actual scanning in order to use sophisticated patient risk minimizing methods, a prospective spatial dose estimation and the known anatomical structures are required. To this end, a CT reconstruction method is required to reconstruct CT volumes from as few projections as possible, i.e. by using the topograms, with anatomical structures as correct as possible. In this work, an optimized CT reconstruction model based on a generative adversarial network (GAN) is proposed. The GAN is trained to reconstruct 3D volumes from an anterior-posterior and a lateral CT projection. To enhance anatomical structures, a pre-trained organ segmentation network and the 3D perceptual loss are applied during the training phase, so that the model can then generate both organ-enhanced CT volume and organ segmentation masks. The proposed method can reconstruct CT volumes with PSNR of 26.49, RMSE of 196.17, and SSIM of 0.64, compared to 26.21, 201.55 and 0.63 using the baseline method. In terms of the anatomical structure, the proposed method effectively enhances the organ shapes and boundaries and allows for a straight-forward identification of the relevant anatomical structures. We note that conventional reconstruction metrics fail to indicate the enhancement of anatomical structures. In addition to such metrics, the evaluation is expanded with assessing the organ segmentation performance. The average organ dice of the proposed method is 0.71 compared with 0.63 for the baseline model, indicating the enhancement of anatomical structures.

Assessment of average glandular dose in mammography practice of a teaching hospital in Ghana.

Introduction: above the age of 40, women are advised to begin breast examinations and screenings for early detection of breast cancer. The average glandular dose (AGD) provides dosimetric information about the quantity of radiation received by the mammary glands during mammographic exposures. There is, therefore, the need to analyse the radiation dose received by patients presenting for mammography examinations. Methods: a retrospective cross-sectional design was carried out on the data of 663 participants, conveniently sampled between the months of July 2021 and June 2022. Paired T-test was used to compare imaging parameters for cranio-caudal (CC), medio-lateral (ML), automatic exposure control (AEC), manual exposure control (MEC), and left and right breast. Pearson´s correlation was used to test for relationship between imaging parameters and AGD. Results: the mean AGD per exposure was 1.9 ± 0.7 mGy for CC projections and 2.3 ± 1.2 mGy for ML projections. The mean AGD per examination for the study was 4.1 ± 1.4 mGy. A positive correlation was found between AGD per examination and exposure factors (tube loading and tube voltage), compressed breast thickness, and compression force. Patient age had no statistically significant relationship with the AGD per examination. Conclusion: average glandular dose (AGD) was consistent with other findings in literature studies. It was also observed that MEC yielded lower AGD per exposure values than AEC. There was no significant difference in the mean AGD per exposure for left and right breasts.

XMEA: A New Hybrid Diamond Multielectrode Array for the In Situ Assessment of the Radiation Dose Enhancement by Nanoparticles.

This work presents a novel multielectrode array (MEA) to quantitatively assess the dose enhancement factor (DEF) produced in a medium by embedded nanoparticles. The MEA has 16 nanocrystalline diamond electrodes (in a cell-culture well), and a single-crystal diamond divided into four quadrants for X-ray dosimetry. DEF was assessed in water solutions with up to a 1000 µg/mL concentration of silver, platinum, and gold nanoparticles. The X-ray detectors showed a linear response to radiation dose (r2 ≥ 0.9999). Overall, platinum and gold nanoparticles produced a dose enhancement in the medium (maximum of 1.9 and 3.1, respectively), while silver nanoparticles produced a shielding effect (maximum of 37%), lowering the dose in the medium. This work shows that the novel MEA can be a useful tool in the quantitative assessment of radiation dose enhancement due to nanoparticles. Together with its suitability for cells' exocytosis studies, it proves to be a highly versatile device for several applications.

Deep learning for high-resolution dose prediction in high dose rate brachytherapy for breast cancer treatment.

Objective.Monte Carlo (MC) simulations are the benchmark for accurate radiotherapy dose calculations, notably in patient-specific high dose rate brachytherapy (HDR BT), in cases where considering tissue heterogeneities is critical. However, the lengthy computational time limits the practical application of MC simulations. Prior research used deep learning (DL) for dose prediction as an alternative to MC simulations. While accurate dose predictions akin to MC were attained, graphics processing unit limitations constrained these predictions to large voxels of 3 mm × 3 mm × 3 mm. This study aimed to enable dose predictions as accurate as MC simulations in 1 mm × 1 mm × 1 mm voxels within a clinically acceptable timeframe.Approach.Computed tomography scans of 98 breast cancer patients treated with Iridium-192-based HDR BT were used: 70 for training, 14 for validation, and 14 for testing. A new cropping strategy based on the distance to the seed was devised to reduce the volume size, enabling efficient training of 3D DL models using 1 mm × 1 mm × 1 mm dose grids. Additionally, novel DL architecture with layer-level fusion were proposed to predict MC simulated dose to medium-in-medium (Dm,m). These architectures fuse information from TG-43 dose to water-in-water (Dw,w) with patient tissue composition at the layer-level. Different inputs describing patient body composition were investigated.Main results.The proposed approach demonstrated state-of-the-art performance, on par with the MCDm,mmaps, but 300 times faster. The mean absolute percent error for dosimetric indices between the MC and DL-predicted complete treatment plans was 0.17% ± 0.15% for the planning target volumeV100, 0.30% ± 0.32% for the skinD2cc, 0.82% ± 0.79% for the lungD2cc, 0.34% ± 0.29% for the chest wallD2ccand 1.08% ± 0.98% for the heartD2cc.Significance.Unlike the time-consuming MC simulations, the proposed novel strategy efficiently converts TG-43Dw,wmaps into preciseDm,mmaps at high resolution, enabling clinical integration.

Impact of flight route changes on cosmic ray exposure: consequences of the conflict between Ukraine and the Russian federation.

This work investigates the impact on cosmic ray exposures to aircrew due to changing flight routes operated in the context of the recent conflict between Ukraine and the Russian Federation. All analyses were done based on Paris-Tokyo and Tokyo-Paris flights taken as examples, and differences in radiation exposures were quantified by comparing the situation before and after the beginning of the conflict. Regarding space weather scenarios, a quiet solar period and an extreme solar event (ground level enhancement (GLE) 5) were considered in the study. Analyses showed that the new Paris-Tokyo flight route established after the beginning of the conflict results in a smaller radiation dose to aircrew than that operated before the conflict, particularly during solar events. In contrast, for Tokyo-Paris flights the new high-latitude route crossing the Atlantic Ocean and North America increases the dose significantly (+ 50% in the worst case). Although this analysis is limited only to flights connecting Paris and Tokyo, it allowed for an evaluation of the consequences of new routes (particularly polar ones) on ambient dose equivalent values.