Dose Uncertainty Research Articles

Verification of dose distribution in high dose-rate brachytherapy for cervical cancer using a normoxic N-vinylpyrrolidone polymer gel dosimeter.

The polymer gel dosimeter has been proposed for use as a 3D dosimeter for complex dose distribution measurement of high dose-rate (HDR) brachytherapy. However, various shapes of catheter/applicator for sealed radioactive source transport used in clinical cases must be placed in the gel sample. The absorbed dose readout for the magnetic resonance (MR)-based polymer gel dosimeters requires calibration data for the dose-transverse relaxation rate (R2) response. In this study, we evaluated in detail the dose uncertainty and dose resolution of three calibration methods, the multi-sample and distance methods using the Ir-192 source and the linear accelerator (linac) method using 6MV X-rays. The use of Ir-192 sources increases dose uncertainty with steep dose gradients. We clarified that the uniformly irradiated gel sample improved the signal-to-noise ratio (SNR) due to the large slice thickness of MR images and could acquire an accurate calibration curve using the linac method. The curved tandem and ovoid applicator used for intracavitary irradiation of HDR brachytherapy for cervical cancer were reproduced with a glass tube to verify the dose distribution. The results of comparison with the treatment planning system (TPS) calculation by gamma analysis on the 3%/2mm criterion were in good agreement with a gamma pass rate of 90%. In addition, the prescription dose could be evaluated accurately. We conclude that it is easy to place catheter/applicator in the polymer gel dosimeters, making them a useful tool for verifying the 3D dose distribution of HDR brachytherapy with accurate calibration methods.

A fast GPU-accelerated Monte Carlo engine for calculation of MLC-collimated electron fields.

Although intensity-modulated radiation therapy and volumetric arc therapy have revolutionized photon external beam therapies, the technological advances associated with electron beam therapy have fallen behind. Modern linear accelerators contain technologies that would allow for more advanced forms of electron treatments, such as beam collimation, using the conventional photon multi-leaf collimator (MLC); however, no commercial solutions exist that calculate dose from such beam delivery modes. Additionally, for clinical adoption to occur, dose calculation times would need to be on par with that of modern dose calculation algorithms. This work developed a graphics processing unit (GPU)-accelerated Monte Carlo (MC) engine incorporating the Varian TrueBeam linac head geometry for a rapid calculation of electron beams collimated using the conventional photon MLC. A compute unified device architecture framework was created for the following: (1) transport of electrons and photons through the linac head geometry, considering multiple scattering, Bremsstrahlung, Møller, Compton, and pair production interactions; (2) electron and photon propagation through the CT geometry, considering all interactions plus the photoelectric effect; and (3) secondary particle cascades through the linac head and within the CT geometry. The linac head collimating geometry was modeled according to the specifications provided by the vendor, who also provided phase-space files. The MC was benchmarked against EGSnrc/DOSXYZnrc/GEANT by simulating individual interactions with simple geometries, pencil, and square beam dose calculations in various phantoms. MC-calculated dose distributions for MLC and jaw-collimated electron fields were compared to measurements in a water phantom and with radiochromic film. Pencil and square beam dose distributions are in good agreement with DOSXYZnrc. Angular and spatial distributions for multiple scattering and secondary particle production in thin slab geometries are in good agreement with EGSnrc and GEANT. Dose profiles for MLC and jaw-collimated 6-20-MeV electron beams showed an average absolute difference of 1.1 and 1.9mm for the FWHM and 80%-20% penumbra from measured profiles. Percent depth doses showed differences of <5% for as compared to measurement. The computation time on an NVIDIA Tesla V100 card was 2.5min to achieve a dose uncertainty of <1%, which is ∼300 times faster than published results in a similar geometry using a single-CPU core. The GPU-based MC can quickly calculate dose for electron fields collimated using the conventional photon MLC. The fast calculation times will allow for a rapid calculation of electron fields for mixed photon and electron particle therapy.

TID evaluation based on variabilities of space radiation and device failure dose in typical navigation satellite orbits

Navigation satellites mainly operate in Medium Earth Orbit (MEO), Geostationary Earth Orbit (GEO), and Inclined Geosynchronous Satellite Orbit (IGSO). These orbits lie in or repeatedly cross the outer Van Allen belt of Earth. With large uncertainty, the radiation in these orbits mainly comes from electrons trapped in the outer radiation belt and solar energetic protons. The accurate design of the radiation shielding structure plays an important role in improving the efficiency of satellites. We introduce a method that incorporates the radiation variability in space and failure dose uncertainty of devices to evaluate the survival probability of devices caused by the Total Ionizing Dose (TID) effect. After fitting the failure dose data of operational amplifier TL084 by the Weibull distribution, we calculate the Confidence Levels (CLs) of all possible parameters of the distribution. Based on these parameters and the cumulative probability distribution of TID from space, we evaluate the effects of shielding thickness and mission duration on TL084's failure possibility at different CLs in MEO/GEO/IGSO. Furthermore, the required shielding thickness and the expected survival duration to ensure that TL084 could operate safely at specific CL are also investigated. By using this method, we could approach a balance among the device's ability, the shielding thickness, the expected duration of safe operation, and the confidence level of the design.

Performance evaluation of an LED flatbed scanner for triple channel film dosimetry with EBT3 and EBT-XD film.

We investigate the properties of a light emitting diode (LED) flatbed scanner for use with EBT3 and EBT-XD film types in a clinical radiochromic film (RCF) dosimetry program with modern treatment techniques. The flatbed scanner was characterised in terms of lateral and longitudinal response, X-Y scaling integrity, scanning reproducibility, scanner warm up dependence and film orientation dependence. The preferred lateral response artefact (LRA) corrections are investigated for the LED light source. Supporting evidence is provided regarding the dose independent nature of the corrections while also providing results suggesting a potential film type independence. Results from 2D gamma analysis of four patient treatments were compared between the new 12000XL and existing 10000XL model. Lastly, a dose uncertainty analysis was performed for the film-scanner system combination. It may be concluded that the lateral response variation requires correction while the longitudinal response variation is insignificant. The linear scaling in the lateral and longitudinal directions are within 0.5% and the scanner reproducibility is stable. Scanner warm up dependence no longer exists, and effort should be made to maintain all film orientation in a study set within 15°. The LRA corrections are as reported substantially dose independent and there is evidence to support film type independence. Comparative gamma analysis of patient specific dose maps between the EPSON 10000XL (xenon fluorescent lamp) and 12000XL (LED) scanners showed that results are indistinguishable for both film types across the two scanner models when the necessary corrections are applied. Dose uncertainty is in agreement with the literature and can be kept below 3% with necessary corrections applied.

Experimental determination of the effective point of measurement for cylindrical ionization chambers in megavoltage photon beams.

Current dosimetry protocols specify an effective point of measurement (EPOM) shift of 0.6r for a cylindrical ionization chamber in photon beams. However, prior studies have reported that this shift was excessively large. The objective of this study was to experimentally evaluate the EPOM shifts in photon beams for cylindrical ionization chambers, which are widely used in clinical practice, and thus determine the appropriate EPOM shift. A microdiamond detector, which is a semiconductor detector with a small sensitive volume, was used as a reference detector, and the EPOM shifts of 11 types of cylindrical ionization chambers were evaluated at 6MV and 10MV. The depth shift from the percent depth dose (PDD) of the reference detector to that of the evaluated chamber was calculated using the least-squares method and was defined as the EPOM shift. The EPOM shift of the 10 MV condition was slightly larger than that of the 6MV condition. However, because this trend was not observed for all chambers, the results of the two energies were averaged, and the EPOM shifts were determined to be 0.33r-0.43r (± 0.05) for 10 types of ionization chambers, and 0.03r (± 0.03) for the A1SL chamber. The shifts for all ionization chambers were smaller than 0.6r, indicating that the recommended EPOM shifts were overestimated and the absorbed dose was underestimated at the calibration depth. Hence, the appropriate EPOM shift of the 10 types of ionization chambers was 0.4r (the geometric center of the A1SL chamber), with a dose uncertainty of 0.05%.

ВЛИЯНИЕ НЕОПРЕДЕЛЁННОСТИ ДОЗ НА ОЦЕНКУ РАДИАЦИОННЫХ РИСКОВ ЗАБОЛЕВАЕМОСТИ СОЛИДНЫМИ ЗЛОКАЧЕСТВЕННЫМИ НОВООБРАЗОВАНИЯМИ В КОГОРТЕ РОССИЙСКИХ УЧАСТНИКОВ ЛИКВИДАЦИИ ПОСЛЕДСТВИЙ АВАРИИ НА ЧЕРНОБЫЛЬСКОЙ АЭС

Purpose: Investigation of the influence of the possible uncertainty of exposure doses of Russian participants in the liquidation of the consequences of the Chernobyl accident on the assessment of radiation risks of the incidence of solid cancer in this cohort. Material and methods: Epidemiological and dosimetric data on a cohort of Russian participants in the liquidation of the consequences of the accident at the Chernobyl NPP, registered in the National Radiation and Epidemiological Register (NRER), are used as initial data for assessing radiation risks. The assessment of radiation risks is carried out by the statistical method of maximum likelihood in the framework of a linear non-threshold model of excess relative risk. Uncertainties in the liquidator’s exposure dose in the adopted risk assessment method are considered in the form of two error models. Dose estimates based on data from individual dosimeters are characterized by a classical model of measurement errors. In the case of estimates of unknown individual doses from group dosimetry data or group route doses, the Berkson assignment error model is used. Results: A method for assessing radiation risks has been developed, accounting for the uncertainty in dose estimates, based on the observed likelihood function. When taking into account the uncertainty of estimates of individual doses in the cohort of Russian liquidators, the estimate of the coefficient of the excess relative rate per dose unit (ERR/Gy) for the incidence of solid malignancies decreases by 7%, compared with the estimate obtained directly from the doses registered in the NRER database. The ERR/Gy estimate derived from the doses recorded in the NRER database was 0.69 with a 95% confidence interval (CI) of 0.37–1.04. The estimate of ERR/Gy, obtained accounting for the uncertainty in estimates of individual doses of liquidators, was 0.64 at 95% CI (0.33–0.98). This estimate bias is not significant, since it is within 95% CI for both ERR/Gy estimates, the statistical range of which is of the order of magnitude of the estimates themselves. Conclusions: Considering the uncertainty of individual dose estimates in the cohort of Russian liquidators, the estimate of the excess relative rate per dose unit (ERR/Gy) for the incidence of solid cancer does not statistically significantly differ from the estimate obtained directly from the doses registered in the NRER database. The bias in the estimate of the radiation risk coefficient observed, due to the dose uncertainty introduced into the calculation, is due to the statistical properties of the traditional radiation risk models used for radiation epidemiology. The results obtained confirm the high stability and validity of the radiation risk assessments obtained earlier from the doses registered in the NRER for the Russian cohort of Chernobyl liquidators. Further research will allow generalization of the developed method for assessing radiation risks, accounting for the uncertainty of dose estimates, based on the observed likelihood function, to other types of radiation epidemiological risk studies, including case-control and case-cohort studies.

Multi-Institutional Study of End-to-End Dose Delivery Quality Assurance Testing for Image-Guided Brachytherapy Using a Gel Dosimeter

To quantify dose delivery errors for high-dose-rate image-guided brachytherapy (HDR-IGBT) using an independent end-to-end dose delivery quality assurance test at multiple institutions. The novelty of our study is that this is the first multi-institutional end-to-end dose delivery study in the world. The postal audit used a polymer gel dosimeter in a cylindrical acrylic container for the afterloading system. Image acquisition using computed tomography, treatment planning, and irradiation were performed at each institution. Dose distribution comparison between the plan and gel measurement was performed. The percentage of pixels satisfying the absolute-dose gamma criterion was reviewed. Thirty-five institutions participated in this study. The dose uncertainty was 3.6% ± 2.3% (mean ± 1.96σ). The geometric uncertainty with a coverage factor of k = 2 was 3.5 mm. The tolerance level was set to the gamma passing rate of 95% with the agreement criterion of 5% (global)/3 mm, which was determined from the uncertainty estimation. The percentage of pixels satisfying the gamma criterion was 90.4% ± 32.2% (mean ± 1.96σ). Sixty-six percent (23/35) of the institutions passed the verification. Of the institutions that failed the verification, 75% (9/12) had incorrect inputs of the offset between the catheter tip and indexer length in treatment planning and 17% (2/12) had incorrect catheter reconstruction in treatment planning. The methodology should be useful for comprehensively checking the accuracy of HDR-IGBT dose delivery and credentialing clinical studies. The results of our study highlight the high risk of large source positional errors while delivering dose for HDR-IGBT in clinical practices.

Current Approaches for Predicting Human PK for Small Molecule Development Candidates: Findings from the IQ Human PK Prediction Working Group Survey.

Accurate prediction of human clearance (CL) and volume of distribution at steady state (Vd,ss) for small molecule drug candidates is an essential component of assessing likely efficacious dose and clinical safety margins. In 2021, the IQ Consortium Human PK Prediction Working Group undertook a survey of IQ member companies to understand the current PK prediction methods being used to estimate these parameters across the pharmaceutical industry. The survey revealed a heterogeneity in approaches being used across the industry (e.g., the use of allometric approaches, differing incorporation of binding terms, and inconsistent use of empirical correction factors for in vitro-in vivo extrapolation, IVIVE), which could lead to different PK predictions with the same input data. Member companies expressed an interest in improving human PK predictions by identifying the most appropriate compound-class specific methods, as determined by physiochemical properties and knowledge of CL pathways. Furthermore, there was consensus that increased understanding of the uncertainty inherent to the compound class-dependent prediction would be invaluable in aiding communication of human PK and dose uncertainty at the time of candidate nomination for development. The human PK Prediction Working Group is utilizing these survey findings to help interrogate clinical IV datasets from across the IQ consortium member companies to understand PK prediction accuracy and uncertainty from preclinical datasets.

Research on new treatment mode of radiotherapy based on pseudo-medical images

Background and objectiveMulti-modal medical images with multiple feature information are beneficial for radiotherapy. A new radiotherapy treatment mode based on triangle generative adversarial network (TGAN) model was proposed to synthesize pseudo-medical images between multi-modal datasets. MethodsCBCT, MRI and CT images of 80 patients with nasopharyngeal carcinoma were selected. The TGAN model based on multi-scale discriminant network was used for data training between different image domains. The generator of the TGAN model refers to cGAN and CycleGAN, and only one generation network can establish the non-linear mapping relationship between multiple image domains. The discriminator used multi-scale discrimination network to guide the generator to synthesize pseudo-medical images that are similar to real images from both shallow and deep aspects. The accuracy of pseudo-medical images was verified in anatomy and dosimetry. ResultsIn the three synthetic directions, namely, CBCT → CT, CBCT → MRI, and MRI → CT, significant differences (p < 0.05) in the three-fold-cross validation results on PSNR and SSIM metrics between the pseudo-medical images obtained based on TGAN and the real images. In the testing stage, for TGAN, the MAE metric results in the three synthesis directions (CBCT → CT, CBCT → MRI, and MRI → CT) were presented as mean (standard deviation), which were 68.67 (5.83), 83.14 (8.48), and 79.96 (7.59), and the NMI metric results were 0.8643 (0.0253), 0.8051 (0.0268), and 0.8146 (0.0267) respectively. In terms of dose verification, the differences in dose distribution between the pseudo-CT obtained by TGAN and the real CT were minimal. The H values of the measurement results of dose uncertainty in PGTV, PGTVnd, PTV1, and PTV2 were 42.510, 43.121, 17.054, and 7.795, respectively (P < 0.05). The differences were statistically significant. The gamma pass rate (2%/2 mm) of pseudo-CT obtained by the new model was 94.94% (0.73%), and the numerical results were better than those of the three other comparison models. ConclusionsThe pseudo-medical images acquired based on TGAN were close to the real images in anatomy and dosimetry. The pseudo-medical images synthesized by the TGAN model have good application prospects in clinical adaptive radiotherapy.

Reliability of Questionnaire-Based Dose Reconstruction: Human Factor Uncertainties in the Radiation Dosimetry of Chernobyl Cleanup Workers.

This original study aims to quantify the human factor uncertainties in radiation doses for Chernobyl cleanup workers that are associated with errors in direct or proxy personal interviews due to poor memory recall a long time after exposure. Two types of doses due to external irradiation during cleanup mission were calculated independently. First, a "reference" dose, that was calculated using the historical description of cleanup activities reported by 47 cleanup workers shortly after the completion of the cleanup mission. Second, a "current" dose that was calculated using information reported by 47 cleanup workers and respective 24 proxies (colleagues) nominated by cleanup workers during a personal interview conducted more recently, as part of this study, i.e., 25-30 years after their cleanup missions. The Jaccard similarity coefficient for reference and current doses was moderate: the arithmetic mean ± standard deviation was 0.29 ± 0.18 (median = 0.31) and 0.23 ± 0.18 (median = 0.22) for the cleanup worker's and proxy's interviews, respectively. The agreement between two doses was better if the cleanup worker was interviewed rather than his proxy: the median ratio of current to reference dose was 1.0 and 0.56 for cleanup workers and proxies, respectively. The present study has shown that human factor uncertainties lead to underestimation or overestimation of the "true" reference dose for most cleanup workers up to 3 times. In turn, the potential impact of these errors on radiation-related risk estimates should be assessed.

Measurement-based validation of a commercial Monte Carlo dose calculation algorithm for electron beams.

This work presents the clinical validation of RayStation's electron Monte Carlo code by the use of diodes and plane parallel radiation detectors in homogenous and heterogeneous tissues. Results are evaluated against internationally accepted criteria. The Monte Carlo-based electron beam dose calculation code was validated using diodes, air- and liquid-filled parallel radiation detectors on an Elekta linac with beam energies of 4, 6, 8, 10, and 12MeV. Treatment setups with varying source-to-skin distances, different applicators, various cutouts, and oblique beam incidences were addressed, together with dose prediction behind lung-, air-, and bone-equivalent inserts. According to NCS (Netherlands Commission for Radiation Dosimetry) report 15 for nonstandard treatment setups, a dose agreement of 3% in the δ1 region (high-dose region around Zref ), a distance-to-agreement (DTA) of 3mm or a dose agreement of 10% in the δ2 region (regions with high-dose gradients), and 4% in the δ4 region (photon tail/low-dose region) were applied. During validation, clinical routine settings of 2×2×2-mm3 dose voxels and a statistically dose uncertainty of 0.6% (250000 histories/cm2 ) were used. RayStation's electron Monte Carlo code dose prediction was able to achieve the tolerances of NCS report 15. Output predictions as a function of the SSD improve with energy and applicator size. Cutout data revealed no field size or energy dependence on the accuracy of the dose prediction. Excellent agreement for the oblique incidence data was achieved and a maximum of one voxel difference was obtained for the DTA behind heterogeneous inserts. The accuracy of RayStation's Monte Carlo-based electron beam dose prediction for Elekta accelerators is confirmed for clinical treatment planning that is not only performed within an acceptable timeframe in terms of the number of histories but also addresses for homogenous and heterogeneous media.

The dose accumulation and the impact of deformable image registration on dose reporting parameters in a moving patient undergoing proton radiotherapy.

IntroductionPotential changes in patient anatomy during proton radiotherapy may lead to a deviation of the delivered dose. A dose estimate can be computed through a deformable image registration (DIR) driven dose accumulation. The present study evaluates the accumulated dose uncertainties in a patient subject to an inadvertent breathing associated motion.Materials and methodsA virtual lung tumour was inserted into a pair of single participant landmark annotated computed tomography images depicting opposite breathing phases, with the deep inspiration breath-hold the planning reference and the exhale the off-reference geometry. A novel Monte Carlo N-Particle, Version 6 (MCNP6) dose engine was developed, validated and used in treatment plan optimization. Three DIR methods were compared and used to transfer the exhale simulated dose to the reference geometry. Dose conformity and homogeneity measures from International Committee on Radioactivity Units and Measurements (ICRU) reports 78 and 83 were evaluated on simulated dose distributions registered with different DIR algorithms.ResultsThe MCNP6 dose engine handled patient-like geometries in reasonable dose calculation times. All registration methods were able to align image associated landmarks to distances, comparable to voxel sizes. A moderate deterioration of ICRU measures was encountered in comparing doses in on and off-reference anatomy. There were statistically significant DIR driven differences in ICRU measures, particularly a 10% difference in the relative D98% for planning tumour volume and in the 3 mm/3% gamma passing rate.ConclusionsT he dose accumulation over two anatomies resulted in a DIR driven uncertainty, important in reporting the associated ICRU measures for quality assurance.

Evaluation of Biomechanical and Chemical Properties of Gamma-Irradiated Polycaprolactone Microfilaments for Musculoskeletal Tissue Engineering Applications.

An appropriate and reliable sterilization technique is crucial for tissue engineering scaffolds. Skeletal muscle scaffolds are often fabricated using microfilaments of a wide variety of polymers. One method for sterilization is 25 kGy of gamma irradiation. In addition, sterilization through irradiation should administer a dose within a specific range. Radiation directly affects the chemical and mechanical properties of scaffolds. The accuracy and effects of irradiation are often not considered during sterilization procedures; however, these are important since they provide insight on whether the sterilization procedure is reliable and reproducible. This study focused on the chemical and mechanical characterization of 25 kGy gamma-irradiated scaffold. The accuracy and uncertainty of the irradiation procedure were also obtained. X-ray diffraction (XRD) and differential scanning calorimetry (DSC) analyses were performed to determine whether the crystallinity of the polymer changed after irradiation and whether gamma rays influenced its thermal properties. The tensile parameters of the microfilaments were analyzed by comparing irradiated and nonirradiated scaffolds to determine whether gamma radiation changed their elastic behavior. Dose distribution and uncertainty were recorded with several dosimeters. The results showed that the irradiation process slightly affected the mechanical parameters of the scaffold; however, it did not modify its crystallinity or thermal properties. The irradiation was uniform, since the measured uncertainty was low. The scaffold was pathogen-free after 7 days; this meant sterilization was achieved. These results indicated that gamma-sterilized scaffolds were a promising material for use as a skeletal muscle analog material for tissue-engineering applications because they can be sterilized with gamma rays without changing their chemical structure and mechanical properties. This study provided the dose distribution measurement and uncertainty calculations for the sterilization procedure.

A Pipeline for Automated Voxel Dosimetry: Application in Patients with Multi-SPECT/CT Imaging After 177Lu-Peptide Receptor Radionuclide Therapy.

Patient-specific dosimetry in radiopharmaceutical therapy (RPT) is impeded by the lack of tools that are accurate and practical for the clinic. Our aims were to construct and test an integrated voxel-level pipeline that automates key components (organ segmentation, registration, dose-rate estimation, and curve fitting) of the RPT dosimetry process and then to use it to report patient-specific dosimetry in 177Lu-DOTATATE therapy. Methods: An integrated workflow that automates the entire dosimetry process, except tumor segmentation, was constructed. First, convolutional neural networks (CNNs) are used to automatically segment organs on the CT portion of one post-therapy SPECT/CT scan. Second, local contour intensity-based SPECT--SPECT alignment results in volume-of-interest propagation to other time points. Third, dose rate is estimated by explicit Monte Carlo (MC) radiation transport using the fast, Dose Planning Method code. Fourth, the optimal function for dose-rate fitting is automatically selected for each voxel. When reporting mean dose, we apply partial-volume correction, and uncertainty is estimated by an empiric approach of perturbing segmentations. Results: The workflow was used with 4-time-point 177Lu SPECT/CT imaging data from 20 patients with 77 neuroendocrine tumors, segmented by a radiologist. CNN-defined kidneys resulted in high Dice values (0.91-0.94) and only small differences (2%-5%) in mean dose when compared with manual segmentation. Contour intensity-based registration led to visually enhanced alignment, and the voxel-level fitting had high R 2 values. Across patients, dosimetry results were highly variable; for example, the average of the mean absorbed dose (Gy/GBq) was 3.2 (range, 0.2-10.4) for lesions, 0.49 (range, 0.24-1.02) for left kidney, 0.54 (range, 0.31-1.07) for right kidney, and 0.51 (range, 0.27-1.04) for healthy liver. Patient results further demonstrated the high variability in the number of cycles needed to deliver hypothetical threshold absorbed doses of 23 Gy to kidney and 100 Gy to tumor. The uncertainty in mean dose, attributable to variability in segmentation, averaged 6% (range, 3%-17%) for organs and 10% (range, 3%-37%) for lesions. For a typical patient, the time for the entire process was about 25 min (∼2 min manual time) on a desktop computer, including time for CNN organ segmentation, coregistration, MC dosimetry, and voxel curve fitting. Conclusion: A pipeline integrating novel tools that are fast and automated provides the capacity for clinical translation of dosimetry-guided RPT.

Mathematical characterization of dose uncertainty effects on functions summarizing findings of community noise attitudinal surveys.

Previous Monte Carlo simulations have quantified the extent to which dose (sound level) uncertainty in community noise dose-response surveys can bias the shape of inferred dose-response functions. The present work extends the prior findings to create a mathematical model of the biasing effect. The exact effect on any particular data set depends on additional attributes (situational variables) beyond dose uncertainty itself. Several variables and their interaction effects are accounted for in the model. The model produced identical results to the prior Monte Carlo simulations and thereby demonstrated the same slope reduction effect. This model was further exercised to demonstrate the nature and extent of situational variable interaction effects related to the range of doses employed and their distribution across the range. One manifestation was a false asymptotic behavior in the observed dose-response relationship. The mathematical model provides a means to not only predict dose uncertainty effects but also to serve as a foundation for correcting for such effects in regression analyses of transportation noise dose-response relationships.

Assessment of internal exposure to 131I and short-lived radioiodine isotopes and associated uncertainties in the Ukrainian cohort of persons exposed in utero.

This study revised the thyroid doses for 2582 Ukrainian in utero cohort members exposed to Chornobyl fallout (the Ukrainian in utero cohort) based on revision of: (i) 131I thyroid activity measured in the Ukrainian population, (ii) thyroid dosimetry system for entire Ukraine, and (iii) 131I ground deposition densities in Ukraine. Other major improvements included: (i) assessment of uncertainties in the thyroid doses considering shared and unshared error, and (ii) accounting for intake of short-lived radioisotopes of tellurium and iodine (132Te+132I and 133I). Intake of 131I was the major pathway for thyroid exposure, its median contribution to the thyroid dose was 97.4%. The mean prenatal and postnatal thyroid dose from 131I was 87mGy (median = 17mGy), higher than previous deterministic dose of 72mGy (median = 12mGy). For 39 individuals (1.5%) the dose exceeded 1.0Gy, while the highest dose among the cohort members was 2.7Gy. The geometric standard deviation (GSD) of 1000 individual stochastic doses varied from 1.9 to 5.2 with a mean of 3.1 and a median of 3.2. The lowest uncertainty (mean GSD = 2.3, median GSD = 2.2) was found for the subjects whose mothers were measured for 131I thyroid activity, while for individuals, whose mothers were not measured, the mean and median GSDs were 3.4. Uncertainties in thyroid doses were driven by shared errors associated with the parameters of the ecological model.

Uncertainties in occupational eye lens doses from dosimeters over the apron in interventional practices

It is relevant to estimate the uncertainties in the measurement of eye lens doses from a personal dosimeter over the protective apron without using additional dosimetry near the eyes. Additional dosimetry for interventionists represents a difficulty for routine clinical practice. This study analyses the estimated eye doses from dosimeter values taken at chest level over the apron and their uncertainties. Measurements of H p(0.07) using optically stimulated luminescence dosimeters located on the chest over the apron and on the glasses (in the inner and outer part of the protection) were taken from ten interventionalists in a university hospital, in the period 2018–2019 during standard clinical practice. For a total sample of 133 interventional procedures included in our study, the ratio between the H p(0.07) on the glasses (left-outer side) and on the chest over the apron had an average of 0.74, with quartiles of 0.47, 0.64, 0.88. Statistically significant differences were found among operators using the U-Mann–Whitney test. The average transmission factor for the glasses was 0.30, with quartiles of 0.21, 0.25, and 0.32. Different complexity in the procedures, in the quality of the scatter radiation and in the individual operational practices, involve a relevant dispersion in the results for lens dose estimations from the over apron dosimeter. Lens doses may be between a 64% and an 88% of the over apron dosimeter values (using median or 3rd quartile). The use of 88% may be a conservative approach.

Quantifying uncertainty in dose–response screenings of nanoparticles: a Bayesian data analysis

Fitting theoretical models to experimental data for dose–response screenings of nanoparticles yields values of several hazard metrics that can support risk management. In this paper, we describe a Bayesian approach to the analysis of dose–response data for nanoparticles that takes into account multiple sources of uncertainty. Specifically, we develop a Bayesian model for the analysis of data for the cytotoxicity of ZnO nanoparticles that follow the log-logistic equation. This model reproduces the unequal variance across doses observed in the experimental data, incorporates information about the sensitivity of the cytotoxicity assay used (i.e. resazurin), and complements experimental data with historical information about the system. The model determines probability distributions for multiple values of toxicity potency (EC50), and exponential decay (the slope s); these distributions provide a direct measure of uncertainty in terms of probabilistic credibility intervals. By substituting these distributions in the log-logistic equation, we determine upper and lower limits of the benchmark dose (BMD), corresponding to upper and lower limits of credibility intervals with 95% probability given the experimental data, multiple sources of uncertainty, and historical information. In view of a reduction of costs and time of dose–response screenings, we use the Bayesian model for the cytotoxicity of ZnO nanoparticles to identify the experimental design that uses the minimum number of data while reducing uncertainty in the estimation of both fitting parameters and BMD.

AAPM Task Group Report 290: Respiratory motion management for particle therapy.

Dose uncertainty induced by respiratory motion remains a major concern for treating thoracic and abdominal lesions using particle beams. This Task Group report reviews the impact of tumor motion and dosimetric considerations in particle radiotherapy, current motion‐management techniques, and limitations for different particle‐beam delivery modes (i.e., passive scattering, uniform scanning, and pencil‐beam scanning). Furthermore, the report provides guidance and risk analysis for quality assurance of the motion‐management procedures to ensure consistency and accuracy, and discusses future development and emerging motion‐management strategies. This report supplements previously published AAPM report TG76, and considers aspects of motion management that are crucial to the accurate and safe delivery of particle‐beam therapy. To that end, this report produces general recommendations for commissioning and facility‐specific dosimetric characterization, motion assessment, treatment planning, active and passive motion‐management techniques, image guidance and related decision‐making, monitoring throughout therapy, and recommendations for vendors. Key among these recommendations are that: (1) facilities should perform thorough planning studies (using retrospective data) and develop standard operating procedures that address all aspects of therapy for any treatment site involving respiratory motion; (2) a risk‐based methodology should be adopted for quality management and ongoing process improvement.

Synthesis of pseudo-CT images from pelvic MRI images based on an MD-CycleGAN model for radiotherapy

Objective. A multi-discriminator-based cycle generative adversarial network (MD-CycleGAN) model is proposed to synthesize higher-quality pseudo-CT from MRI images. Approach. MRI and CT images obtained at the simulation stage with cervical cancer were selected to train the model. The generator adopted DenseNet as the main architecture. The local and global discriminators based on a convolutional neural network jointly discriminated the authenticity of the input image data. In the testing phase, the model was verified by a fourfold cross-validation method. In the prediction stage, the data were selected to evaluate the accuracy of the pseudo-CT in anatomy and dosimetry, and they were compared with the pseudo-CT synthesized by GAN with the generator based on the architectures of ResNet, sUNet, and FCN. Main results. There are significant differences (P < 0.05) in the fourfold cross-validation results on the peak signal-to-noise ratio and structural similarity index metrics between the pseudo-CT obtained based on MD-CycleGAN and the ground truth CT (CTgt). The pseudo-CT synthesized by MD-CycleGAN had closer anatomical information to the CTgt with a root mean square error of 47.83 ± 2.92 HU, a normalized mutual information value of 0.9014 ± 0.0212, and a mean absolute error value of 46.79 ± 2.76 HU. The differences in dose distribution between the pseudo-CT obtained by MD-CycleGAN and the CTgt were minimal. The mean absolute dose errors of Dosemax, Dosemin, and Dosemean based on the planning target volume were used to evaluate the dose uncertainty of the four pseudo-CT. The u-values of the Wilcoxon test were 55.407, 41.82, and 56.208, and the differences were statistically significant. The 2%/2 mm-based gamma pass rate (%) of the proposed method was 95.45 ± 1.91, and the comparison methods (ResNet_GAN, sUnet_GAN, and FCN_GAN) were 93.33 ± 1.20, 89.64 ± 1.63, and 87.31 ± 1.94, respectively. Significance. The pseudo-CT images obtained based on MD-CycleGAN have higher imaging quality and are closer to the CTgt in terms of anatomy and dosimetry than other GAN models.