Accurate Dose Estimates Research Articles

Application of multiple-centers ESR dating to middle Pleistocene fluviolacustrine sediments and insights into the dose underestimation from the Ti–H center at high equivalent doses

The Ti–H center exhibits rapid and complete optical bleaching properties, meaning it has significant potential for dating applications. However, the equivalent dose of Ti–H centers is underestimated when total doses received by quartz during its geological history reaches a higher level, and there appears to be linked to saturation of the equivalent dose obtained from Ti–H centers. To investigate this phenomenon, a series of samples were analyzed from two sections at Ximachi in Heqing County, China, which have strong Ti–H signals. The sample ages were obtained using the electron spin resonance (ESR) multiple-centers approach, and the reliability of the ages was validated by comparison with optically simulated luminescence (OSL) ages and between different paramagnetic centers. The ESR data demonstrate that the Ti–H centers can provide accurate dose estimates up to 750–950 Gy, with varying degrees of underestimation at high doses. Combined with previously published Ti–H data, it is evident that the upper threshold of the accurate data obtained from Ti–H centers depends on the sample, and may be positively correlated with the Ti–H/(Ti–Li + Ti–H) ratio (option C/D). According to the provenance significance of the Ti–H/(Ti–Li + Ti–H) ratio, we propose that the Ximachi samples have high Ti–H/(Ti–Li + Ti–H) ratios and then equivalent dose saturation values of Ti–H centers, which may be related to the thermal history of the analyzed quartz grains.

Quality assurance for online adaptive radiotherapy: a secondary dose verification model with geometry-encoded U-Net

Abstract Background & Purpose: In online adaptive radiotherapy (ART), quick computation-based secondary dose verification is crucial for ensuring the quality of ART plans while the patient is positioned on the treatment couch. However, traditional dose verification algorithms are generally time-consuming, reducing the efficiency of ART workflow. This study aims to develop an ultra-fast deep-learning (DL) based secondary dose verification algorithm to accurately estimate dose distributions using CT and fluence maps (FMs). 
Methods: We integrated FMs into the CT image domain by explicitly resolving the geometry of treatment delivery. For each gantry angle, an FM was constructed based on the optimized multi-leaf collimator apertures and corresponding monitoring units (MUs). To effectively encode treatment beam configuration, the constructed FMs were back-projected to 30 cm away from the isocenter with respect to the exact geometry of the treatment machines. Then, a 3D U-Net was utilized to take the integrated CT and FM volume as input to estimate dose. Training and validation were performed on 381 prostate cancer cases, with an additional 40 testing cases for independent evaluation of model performance.
Results: The proposed model can estimate dose in ~15 ms for each patient. The average γ passing rate (3%/2mm, 10% threshold) for the estimated dose was 99.9% ± 0.15% on testing patients. The mean dose differences for the planning target volume (PTV) and organs at risk (OARs) were 0.07%±0.34% and 0.48%±0.72%, respectively.
Conclusion: We have developed a geometry-resolved DL framework for accurate dose estimation and demonstrated its potential in real-time online ART doses verification.

MPPD: A User-Friendly Posture Deformation Program for Mesh-Type Computational Phantoms.

Recently, the International Commission on Radiological Protection (ICRP) released adult Mesh-type Reference Computational Phantoms (MRCPs), which have great advantage in high deformability. Previous studies have exploited their high deformability to investigate the dosimetric influence of varying statures and postures, demonstrating significant variations in radiation doses. However, the previous studies are constrained by their inability to consider both stature and posture concurrently and by the limited range of postures analyzed. In the present study, a computer program named MPPD (Mesh-type Phantom Posture Deformer) was developed, a user-friendly graphical user interface that enables users to adjust the posture of adult MRCPs and corresponding library phantoms. The MPPD program was applied to deform five adult male phantoms of different statures into sitting and kneeling postures, showcasing its rapid computational speed and minimal RAM usage. The effectiveness of the MPPD program for dose calculation was also investigated by computing the detriment-weighted doses for MPPD-deformed adult male MRCPs, which showed good agreement with dose values for existing posture-deformed phantoms of the previous study. Furthermore, as an application of the MPPD program, the combined dosimetric impact of stature and posture was investigated, which is the inaugural effort to estimate doses by considering these factors concurrently. The result showed that the impact of stature and posture on radiation doses could largely vary depending on the radiation source, highlighting the importance of simultaneous consideration of stature and posture for accurate dose estimation.

Sex differences in constructing dose-response calibration curves for micronuclei using cytokinesis-blocked micronucleus assay for radiation biological dosimetry in the Iranian population

Biological dosimetry, using chromosome damage biomarkers, can be considered as a key measure for radiation overexposure assessment. Therefore, for accurate dose estimation through biodosimetry, it's imperative for each biological dosimetry laboratory to establish its own specific dose-response calibration curve. In this research, the cytokinesis-blocked micronucleus (CBMN) assay was utilized to determine the frequencies of micronuclei (MN) per binucleated cell in human peripheral blood lymphocytes exposed to x-ray radiation using a LINAC (6 MV) at doses up to 4 Gy. The aim was to establish an in vitro dose-response calibration curve in our laboratory for the Iranian demographic by analyzing blood samples of ten participants (5 males and 5 females) through CABAS and Dose Estimate software. Our findings indicate an over-dispersion of the Poisson distribution in the pooled data across both sexes, coupled with a linear-quadratic increase in MN yield with dose which was particularly pronounced in the female group. The constructed dose-response curves for micronuclei yield are represented by equations Y= (0.0102 ± 0.0016) +(0.0296 ± 0.0054) D+(0.0232 ± 0.0017) D2 and Y= (0.0084 ± 0.0010) +(0.0212 ± 0.0034) D+(0.0160 ± 0.0011) D2 for the female groups, respectively. The alpha and beta coefficients, derived from the Dose Estimate software for each male and female group, were closely comparable with those obtained from the CABAS program and previous studies. The analysis of statistical parameters such as the Weighted Chi Squared (χ2) and p-value suggests that using distinct curves for each sex, rather than a unified biodosimetry formula for pooled data, ensures more accurate radiation dose estimates. Consequently, the findings of this study provide us with the assurance to utilize the derived calibration curve of MN for upcoming biological dosimetry needs in Iran. However, to enhance the reliability of results, it's essential to use biodosimetry with diverse assays and consider all clinical and physical parameters, given the limitations of cytogenetic assays.

New technologies for beam spectrometry, quality assurance, real-time monitoring and microdosimetry in BNCT

Boron neutron capture therapy (BNCT) is a next-generation radiotherapy that combines neutron beams with boron compounds that selectively accumulate in cancer cells. Because this therapy requires neutrons for irradiation, compact accelerator-based neutron source devices that can be installed in hospitals are being developed around the world. Clinical trials of several devices have been conducted in Japan, China, and South Korea. The most advanced device was approved by the Japanese regulatory authorities in 2020. As a result, BNCT with the device is being implemented as an insured therapy for recurrent head and neck cancer at two hospitals in Japan. Thus, the development of accelerator-based neutron generators is proceeding in the field of BNCT. However, much remains to be done to establish this therapy as a common cancer treatment and to make it available worldwide. Dosimetry methods in BNCT are one of the issues. In the treatment, the dose given to a patient by neutron irradiation has to be estimated accurately. However, it is difficult to measure neutrons accurately and in real time. Currently, the neutron dose delivered to patients during treatment is not measured. Instead, the current of the charged particles that irradiate the neutron target material is measured to indirectly evaluate the neutron fluence and dose. In addition, accurate dose estimation based on reactions with neutrons and various elements in a human body uses the Monte Carlo method, which is computationally time-consuming. To address these dosimetry issues, several neutron fluence and dose measurement methods are being developed. This review briefly describes the current dosimetry methods and then presents several methods under development that allow real-time neutron measurements applicable to BNCT.

Long-Term, Non-Invasive Detection of Low-Dose Ionizing Radiation Exposure

Ionizing radiation induces complex changes in cells and tissues. The conventional approach to biological dosimetry has been to integrate physical and clinical measurements to optimize dose assessment. Molecular biodosimetry is an effective strategy to monitor radiation exposure and hematologic, cytogenetic, protein and transcript-based approaches have been developed to increase dose estimation accuracy. However, these approaches are invasive, time-consuming, have limited effectiveness over time, and importantly do not accurately inform on low dose radiation exposures. Therefore, novel, non-invasive, biomarkers are required that can overcome these limitations. We developed a pipeline that employs Fourier transform infrared (FTIR) spectroscopy in the mid-infrared spectrum to identify a signature of low dose ionizing radiation exposure in mouse ear pinnae over time. Two cohorts of C57BL/6J and one cohort of BALB/c mice were followed for ninety days after total body X-ray exposures of 10, 50, 100 or 200 cGy. The stratum corneum layer of the ear pinnae were repeatedly measured with attenuated total reflectance - focal plane array (ATR-FPA)-FTIR at 5, 14, 21, 49 and 90 days after radiation exposure. We found statistically significant discriminative power for all doses and all tested time-points out to 90 days after exposure. Classification accuracy was maximized when testing 14 days after exposure (specificity > 0.9 with a sensitivity threshold of 0.9) and dropped by roughly 30% sensitivity at 90 days. Since only hundreds of samples were required to learn highly discriminative signatures, developing human-relevant diagnostic capabilities is likely feasible and this non-invasive procedure points toward future non-invasive biodosimetry applications at population scales.

Continuous Glucose, Insulin and Lifestyle Data Augmentation in Artificial Pancreas Using Adaptive Generative and Discriminative Models.

Artificial pancreas requires data from multiple sources for accurate insulin dose estimation. These include data from continuous glucose sensors, past insulin dosage information, meal quantity and time and physical activity data. The effectiveness of closed-loop diabetes management systems might be hampered by the absence of these data caused by device error or lack of compliance by patients. In this study, we demonstrate the effect of output sequence length-driven generative and discriminative model selection in high quality data generation and augmentation. This novel generative adversarial network (GAN) based architecture automatically selects the generator and discriminator architecture based on the desired output sequence length. The proposed model is able to generate glucose, physical activity, meal information data for individual patients. The discriminative scores for Ohio T1DM (2018) dataset were 0.17 ±0.03 (Inputs: CGM, CHO, Insulin) and 0.15 ±0.02 (Inputs: CGM, CHO, Insulin, Heart Rate, Steps) and for Ohio T1D (2020) dataset was 0.16 ±0.02 (Inputs: CGM, CHO, Insulin) and 0.15 ±0.02 (Inputs: CGM, CHO, Insulin, acceleration). A mixture of generated and real data was used to test predictive scores for glucose forecasting models. The best RMSE and MARD achieved for OhioT1DM patients were 17.19 ±3.22 and 7.14 ±1.76 for PH=30 min with CGM, CHO, Insulin, heartrate and steps as inputs. Similarly, the RMSE and MARD for real+synthetic data were 15.63 ±2.57 and 5.86 ±1.69 respectively. Compared to existing generative models, we demonstrate that sequence length based architecture selection leads to better synthetic data generation for multiple output sequences (CGM, CHO, Insulin) and forecasting accuracy.

Proton dose deposition matrix prediction using multi-source feature driven deep learning approach

Proton dose deposition results are influenced by various factors, such as irradiation angle, beamlet energy and other parameters. The calculation of the proton dose deposition matrix (DDM) can be highly complex but is crucial in intensity-modulated proton therapy (IMPT). In this work, we present a novel deep learning (DL) approach using multi-source features for proton DDM prediction. The DL5 proton DDM prediction method involves five input features containing beamlet geometry, dosimetry and treatment machine information like patient CT data, beamlet energy, distance from voxel to beamlet axis, distance from voxel to body surface, and pencil beam (PB) dose. The dose calculated by Monte Carlo (MC) method was used as the ground truth dose label. A total of 40 000 features, corresponding to 8000 beamlets, were obtained from head patient datasets and used for the training data. Additionally, seventeen head patients not included in the training process were utilized as testing cases. The DL5 method demonstrates high proton beamlet dose prediction accuracy, with an average determination coefficient R 2 of 0.93 when compared to the MC dose. Accurate beamlet dose estimation can be achieved in as little as 1.5 milliseconds for an individual proton beamlet. For IMPT plan dose comparisons to the dose calculated by the MC method, the DL5 method exhibited gamma pass rates of γ(2 mm, 2%) and γ(3 mm, 3%) ranging from 98.15% to 99.89% and 98.80% to 99.98%, respectively, across all 17 testing cases. On average, the DL5 method increased the gamma pass rates to γ(2 mm, 2%) from 82.97% to 99.23% and to γ(3 mm, 3%) from 85.27% to 99.75% when compared with the PB method. The proposed DL5 model enables rapid and precise dose calculation in IMPT plan, which has the potential to significantly enhance the efficiency and quality of proton radiation therapy.

G0-PCC-FISH derived multi-parametric biodosimetry methodology for accidental high dose and partial body exposures

High dose radiation exposures are rare. However, medical management of such incidents is crucial due to mortality and tissue injury risks. Rapid radiation biodosimetry of high dose accidental exposures is highly challenging, considering that they usually involve non uniform fields leading to partial body exposures. The gold standard, dicentric assay and other conventional methods have limited application in such scenarios. As an alternative, we propose Premature Chromosome Condensation combined with Fluorescent In-situ Hybridization (G0-PCC-FISH) as a promising tool for partial body exposure biodosimetry. In the present study, partial body exposures were simulated ex-vivo by mixing of uniformly exposed blood with unexposed blood in varying proportions. After G0-PCC-FISH, Dolphin’s approach with background correction was used to provide partial body exposure dose estimates and these were compared with those obtained from conventional dicentric assay and G0-PCC-Fragment assay (conventional G0-PCC). Dispersion analysis of aberrations from partial body exposures was carried out and compared with that of whole-body exposures. The latter was inferred from a multi-donor, wide dose range calibration curve, a-priori established for whole-body exposures. With the dispersion analysis, novel multi-parametric methodology for discerning the partial body exposure from whole body exposure and accurate dose estimation has been formulated and elucidated with the help of an example. Dose and proportion dependent reduction in sensitivity and dose estimation accuracy was observed for Dicentric assay, but not in the two PCC methods. G0-PCC-FISH was found to be most accurate for the dose estimation. G0-PCC-FISH has potential to overcome the shortcomings of current available methods and can provide rapid, accurate dose estimation of partial body and high dose accidental exposures. Biological dose estimation can be useful to predict progression of disease manifestation and can help in pre-planning of appropriate & timely medical intervention.

Characterizing pediatric head patient size in Moroccan population: Establishing age-dependent relationships for accurate CT dose estimation

Accurate dose estimation in computed tomography (CT) scans is crucial and relies on precise normalization of output dose, typically measured by the volume CT dose index (CTDIvol). Key metrics, including effective diameter (Deff) and water-equivalent diameter (Dw), play pivotal roles in characterizing patient size. However, a notable gap exists in delineating the specific relationships between age and head patient size (Deff and Dw) for pediatric patients in Morocco. The primary objective of this study was to establish these critical associations between patient age and head patient size (Deff and Dw), providing a foundation for calculating size-specific dose estimates (SSDE) in pediatric head CT examinations. A retrospective analysis of data from 134 pediatric patients, aged 0–13 yr, comprising 71 males and 63 females who underwent head CT scans, was conducted. Utilizing the Radiant DICOM Viewer, patient sizes were measured in terms of both lateral and anterior-posterior dimensions for Deff and Dw calculations based on CT images in DICOM format. Our analysis revealed robust correlations between patient size (Deff and Dw) and the patient’s age, with R2 values ranging from 0.65 to 0.86. Notably, larger Dw values were consistently observed compared to Deff. For male patients, Deff measurements ranged from 9.02 to 18.77 cm, with Dw values spanning 9.83 to 20.16 cm. Female patients exhibited Deff values ranging from 8.77 to 17.41 cm and Dw values ranging from 8.92 to 18.37 cm. These findings shed light on the crucial relationship between age and patient size, facilitating more precise dose calculations.

Effects of cell parameters on accurate calculation of activation dose after DT explosion for local hot spots in laser-driven ICF facilities

Instruments placed in the target chamber will be highly activated after DT explosion in laser-driven ICF experiments, especially for the part near the chamber center. Operations near those local hot spots are the main concern for radiation protection due to its high contribution to the occupation exposure dose, therefore it becomes very important to calculate the dose during the operating process accurately. Cell-based rigorous two-step (R2S) method has been introduced to deal with the activated objects with highly heterogeneous distribution, and the effects of cell size, materials as well as radiation source have also been specified to improve the accuracy of simulations. Results for a typical model sample show that with a given distribution of radiation source, cell size in the simulations placed a significant influence on the accuracy of the radiation field. A cell size of 50 cm for a 100 cm cone-shaped sample will lead to the inaccuracy of the radiation field as large as an order in magnitude within the location 50 cm from the surface of the sample. While for the same sample model, cell size should be limited to smaller than 2 cm to ensure an accuracy lower than ±10 %. In addition, the effects of the material and source energy on the calculation accuracy for the radiation field could be neglected if the cell size is limited to smaller than 5 cm. Furthermore, the influence of cell size increased as the distance from the sample surface decreased, which indicates that appropriate cell size must be chosen to ensure the accuracy of dose estimation, especially for surface contact operations. Besides, a significant difference between the effective dose and skin-equivalent dose has been observed for the typical mode used in the calculations.

Spectroscopic and dosimetric comparison of tooth enamel separation methods for EPR retrospective dosimetry

Precise estimation of individual radiation dose utilizing biomaterials (fingernail, bone, and tooth) is very challenging due to their complex sample processing. Despite, tooth enamel, the most mineralized tissue of tooth is used for this purpose due to its high radiation sensitivity and ability to produce radiation induced long lived CO2− radicals. However, human teeth are not always available, and invasive nature of sample collection adds to the complexity making dose estimation difficult. In such cases, animal teeth (goat, cow, and moose) can be used as a substitute for human teeth due to comparable enamel sensitivity. Moreover, separation of enamel from dentine is a crucial step towards accurate dose estimation from irradiated teeth. In this work, Indian goat teeth were used as it was readily available to us and the comparison of goat enamel sensitivity to radiation was found to be within ∼7.4 % that of human. The enamel samples were separated following two chemical methods; (1) density separation using sodium polytungstate, (2) alkaline denaturation using NaOH and the quality was compared based on their purity and radiation sensitivity. Combined results of spectroscopic characterization using X-ray diffraction (XRD), Fourier transform infrared (FTIR), and Raman analysis authenticated the crystallinity and purity of the separated enamel samples. The radiation sensitivity of separated enamel samples was compared by electron paramagnetic resonance (EPR) analysis as a part of dosimetric characterization. The suitability of both the samples for retrospective dosimetry and epidemiological studies was checked by validating the dose estimated from separated enamel samples with standard alanine/EPR dosimeter.

Accuracy of patient-specific CT organ doses from Monte Carlo simulations: influence of CT-based voxel models

Monte Carlo simulations using patient CT images as input are the gold standard to perform patient-specific dosimetry. However, in standard clinical practice patient’s CT images are limited to the reconstructed CT scan range. In this study, organ dose calculations were performed with ImpactMC for chest and cardiac CT using whole-body and anatomy-specific voxel models to estimate the accuracy of CT organ doses based on the latter model. When the 3D patient model is limited to the CT scan range, CT organ doses from Monte Carlo simulations are the most accurate for organs entirely in the field of view. For these organs only the radiation dose related to scatter from the rest of the body is not incorporated. For organs lying partially outside the field of view organ doses are overestimated by not accounting for the non-irradiated tissue mass. This overestimation depends strongly on the amount of the organ volume located outside the field of view. To get a more accurate estimation of the radiation dose to these organs, the ICRP reference organ masses and densities could form a solution. Except for the breast, good agreement in dose was found for most organs. Voxel models generated from clinical CT examinations do not include the overscan in the z-direction. The availability of whole-body voxel models allowed to study this influence as well. As expected, overscan induces slightly higher organ doses.

ISIT-QA: In Silico Imaging Trial to Evaluate a Low-Count Quantitative SPECT Method Across Multiple Scanner-Collimator Configurations for 223Ra-Based Radiopharmaceutical Therapies.

Personalized dose-based treatment planning requires accurate and reproducible noninvasive measurements to ensure safety and effectiveness. Dose estimation using SPECT is possible but challenging for alpha (α)-particle-emitting radiopharmaceutical therapy (α-RPT) because of complex γ-emission spectra, extremely low counts, and various image-degrading artifacts across a plethora of scanner-collimator configurations. Through the incorporation of physics-based considerations and skipping of the potentially lossy voxel-based reconstruction step, a recently developed projection-domain low-count quantitative SPECT (LC-QSPECT) method has the potential to provide reproducible, accurate, and precise activity concentration and dose measures across multiple scanners, as is typically the case in multicenter settings. To assess this potential, we conducted an in silico imaging trial to evaluate the LC-QSPECT method for a 223Ra-based α-RPT, with the trial recapitulating patient and imaging system variabilities. Methods: A virtual imaging trial titled In Silico Imaging Trial for Quantitation Accuracy (ISIT-QA) was designed with the objectives of evaluating the performance of the LC-QSPECT method across multiple scanner-collimator configurations and comparing performance with a conventional reconstruction-based quantification method. In this trial, we simulated 280 realistic virtual patients with bone-metastatic castration-resistant prostate cancer treated with 223Ra-based α-RPT. The trial was conducted with 9 simulated SPECT scanner-collimator configurations. The primary objective of this trial was to evaluate the reproducibility of dose estimates across multiple scanner-collimator configurations using LC-QSPECT by calculating the intraclass correlation coefficient. Additionally, we compared the reproducibility and evaluated the accuracy of both considered quantification methods across multiple scanner-collimator configurations. Finally, the repeatability of the methods was evaluated in a test-retest study. Results: In this trial, data from 268 223RaCl2 treated virtual prostate cancer patients, with a total of 2,903 lesions, were used to evaluate LC-QSPECT. LC-QSPECT provided dose estimates with good reproducibility across the 9 scanner-collimator configurations (intraclass correlation coefficient > 0.75) and high accuracy (ensemble average values of recovery coefficients ranged from 1.00 to 1.02). Compared with conventional reconstruction-based quantification, LC-QSPECT yielded significantly improved reproducibility across scanner-collimator configurations, accuracy, and test-retest repeatability ([Formula: see text] Conclusion: LC-QSPECT provides reproducible, accurate, and repeatable dose estimations in 223Ra-based α-RPT as evaluated in ISIT-QA. These findings provide a strong impetus for multicenter clinical evaluations of LC-QSPECT in dose quantification for α-RPTs.

Pediatric phantom library constructed from ICRP mesh-type reference computational phantoms (MRCPs)

International Commission on Radiological Protection (ICRP) recently developed the adult and pediatric mesh-type reference computational phantoms (MRCPs) in high-quality/fidelity mesh format, featuring high deformability into various body sizes and poses. Utilizing this feature, the adult MRCPs-based body-size-dependent phantom library was developed for individualized dosimetry. To complete the full phantom library set, the present study produced the pediatric-MRCPs-based body-size-dependent pediatric phantom library. The library comprises a total of 637 phantoms (356 males and 281 females) with varying standing heights and body weights, covering a wide range of body sizes (i.e., including from 1st to 99th percentile height and weight values) for infants, children, and adolescents, offering a realistic representation of body shapes by reflecting ten secondary anthropometric parameters. The phantoms were automatically constructed utilizing automatic deformation program. The dosimetric impact of the library was investigated by calculating organ doses for external exposures to broad parallel photon beams in anterior-posterior direction. Compared with the values of the pediatric MRCPs, significant differences were observed at energies <0.05 MeV, showing larger values for underweight phantom and smaller values for obese phantom. The results highlight the importance of using the pediatric phantom library for accurate dose estimates of individual children with various body sizes.

Redefining Radiation Metrics: Evaluating Actual Doses in Computed Tomography Scans.

Computed tomography (CT) contributes significantly to the collective dose from medical sources, raising concerns about potential health risks. However, existing radiation dose estimation tools, such as volume computed tomography dose index (CTDIvol), dose-length product (DLP), effective dose (ED), and size-specific dose estimate (SSDE), have limitations in accurately reflecting patient exposure. This study introduces a new parameter, size-specific dose-length product (DLPss), aiming to enhance the precision of radiation dose estimation in real-life scenarios. A retrospective analysis of 134 chest CT studies was conducted. Relationships between CTDIvol and anthropometric parameters were examined, and SSDE was calculated based on effective diameter. Additionally, the novel parameter, DLPss, was introduced, considering scan length and cross-sectional dimensions. Analysis reveals variations in scan length, effective diameter, and CTDIvol between genders. Strong correlations were observed between CTDIvol and effective diameter, particularly in men. The average CTDIvol for the entire group was 7.83 ± 2.92 mGy, with statistically significant differences between women (7.38 ± 3.23 mGy) and men (8.30 ± 2.49 mGy). SSDE values showed significant gender differences, with men exhibiting higher values. The average SSDE values for women and men were 9.15 ± 2.5 mGy and 9.6 ± 2.09 mGy, respectively, with a statistically significant difference (p = 0.03). The newly introduced DLPss values ranged around 343.90 ± 81.66 mGy·cm for the entire group, with statistically significant differences between women (323.53 ± 78.69 mGy·cm) and men (364.89 ± 79.87 mGy·cm) (p < 0.05), providing a comprehensive assessment of total radiation dose. The study highlights the need for accurate radiation dose estimation, emphasizing the impact of CT examination parameters on dose variability. The proposed DLPss parameter offers a promising approach to enhancing precision in assessing radiation risk during CT scans. Further research is warranted to explore additional parameters for a comprehensive understanding of radiation exposure and to optimize imaging protocols for patient safety.

The Role of Lung Density in the Voxel-Based Dosimetry of 90Y-TARE Evaluated with the Voxel S-Value (VSV) Method and Fast Monte Carlo Simulation

(1) Background: In 90Y-TARE treatments, lung-absorbed doses should be calculated according to the manufacturer’s instructions, using the MIRD-scheme. This scheme is derived from the assumption that 90Y-microspheres deliver the dose in a water-equivalent medium. Since the density of the lungs is quite different from that of the liver, the absorbed dose to the lungs could vary considerably, especially at the liver/lungs interface. The aim of this work is to compare the dosimetric results obtained by two dedicated software packages implementing a water-equivalent dose calculation and a Monte Carlo (MC) simulation, respectively. (2) Methods: An anthropomorphic IEC phantom and a retrospective selection of 24 patients with a diagnosis of HCC were taken into account. In the phantom study, starting from a 90Y-PET/CT acquisition, the liver cavity was manually fixed with a uniform activity concentration on PET series, while the lung compartment was manually expanded on a CT series to simulate a realistic situation in which the liver and lungs are adjacent. These steps were performed by using MIM 90Y SurePlan. Then, a first simulation was carried out with only the liver cavity filled, while a second one was carried out, in which the lung compartment was also manually fixed with a uniform activity concentration corresponding to 10% lung shunt fraction. MIM 90Y SurePlan was used to obtain Voxel S-Value (VSV) approach dose values; instead, Torch was used to obtain MC approach dose values for both the phantom and the patients. (3) Results: In the phantom study, the percentage mean dose differences (∆D%) between VSV and MC in the first and second simulation, respectively were found to be 1.2 and 0.5% (absolute dose variation, ∆D, of 0.7 and 0.3 Gy) for the liver, −56 and 70% (∆D of −0.3 and −16.2 Gy) for the lungs, and −48 and −60% (∆D of −4.3 and −16.5 Gy) for the Liver/Lungs Edge region. The patient study reports similar results with ∆D% between VSV and MC of 7.0%, 4.1% and 6.7% for the whole liver, healthy liver, and tumor, respectively, while the result was −61.2% for the left lung and −61.1% for both the right lung and lungs. (4) Conclusion: Both VSV and MC allowed accurate radiation dose estimation with small differences (&lt;7%) in regions of uniform water-equivalent density (i.e., within the liver). Larger differences between the two methods (&gt;50%) were observed for air-equivalent regions in the phantom simulation and the patient study.

Dose measurement of optic chiasm and parotid organs using OCTAVIUS 4D phantom: a dynamic IMRT method for nasopharyngeal cancer treatment

IntroductionIn intensity-modulated radiation therapy (IMRT) techniques, although the dose conformity increases, the out-of-field doses would not decrease. This study aimed to assess the dose error calculated by the treatment planning system (TPS) in the out-of-field regions using the dynamic IMRT (D-IMRT) method in nasopharyngeal cancer (NPC) patients. MethodsThe out-of-field doses were measured for the chiasm and parotid organs using the D-IMRT technique (6 MV energy) with Monaco TPS. Computed tomography (CT) images of 10 NPC patients (54–77 years, mean: 61.6 ± 12.2 years) were considered and countered using 7-field and 11-field methods. The OCTAVIUS 4D phantom was utilized for dose assessment. ResultsAccording to the OCTAVIUS measurements, the Monaco TPS dose errors ranged from −58.8 to 105.5%. The average dose error for optic chiasm and parotid organs was −25% and 8.5%, respectively, with several cases falling within tolerance (±5%). ConclusionThere were considerable dose calculation errors by Monaco TPS for organs located in out-of-field regions (optic chiasm and parotid) during IMRT for NPC patients. Therefore, accurate dose estimation in the out-of-field regions should be considered in clinical practices.

Exploring Deep Learning for Estimating the Isoeffective Dose of FLASH Irradiation From Mouse Intestinal Histological Images

PurposeUltra-high dose rate (FLASH) irradiation has been reported to reduce normal tissue damage compared with conventional dose rate (CONV) irradiation without compromising tumor control. This proof-of-concept study aims to develop a deep learning (DL) approach to quantify the FLASH isoeffective dose (dose of CONV that would be required to produce the same effect as the given physical FLASH dose) with post-irradiation mouse intestinal histological images. Methods and materials84 healthy C57BL/6J female mice underwent 16 MeV electron CONV (0.12Gy/s; n=41) or FLASH (200Gy/s; n=43) single fraction whole abdominal irradiation. Physical dose ranged from 12 to 16Gy for FLASH and 11 to 15Gy for CONV in 1Gy increments. 4 days after irradiation, 9 jejunum cross-sections from each mouse were H&E stained and digitized for histological analysis. CONV dataset was randomly split into training (n=33) and testing (n=8) datasets. ResNet101-based DL models were retrained using the CONV training dataset to estimate the dose based on histological features. The classical manual crypt counting (CC) approach was implemented for model comparison. Cross-section-wise mean squared error (CS-MSE) was computed to evaluate the dose estimation accuracy of both approaches. The validated DL model was applied to the FLASH dataset to map the physical FLASH dose into the isoeffective dose. ResultsThe DL model achieved a CS-MSE of 0.20Gy2 on the CONV testing dataset compared with 0.40Gy2 of the CC approach. Isoeffective doses estimated by the DL model for FLASH doses of 12, 13, 14, 15, and 16 Gy were 12.19±0.46, 12.54±0.37, 12.69±0.26, 12.84±0.26, and 13.03±0.28 Gy, respectively. ConclusionsOur proposed DL model achieved accurate CONV dose estimation. The DL model results indicate that in the physical dose range of 13 to 16 Gy, the biological dose response of small intestinal tissue to FLASH irradiation is represented by a lower isoeffective dose compared to the physical dose. Our DL approach can be a tool for studying isoeffective doses of other radiation dose modifying interventions.

An open source auto-segmentation algorithm for delineating heart and substructures – Development and validation within a multicenter lung cancer cohort

Background and purposeIrradiation of the heart in thoracic cancers raises toxicity concerns. For accurate dose estimation, automated heart and substructure segmentation is potentially useful. In this study, a hybrid automatic segmentation is developed. The accuracy of delineation and dose predictions were evaluated, testing the method's potential within heart toxicity studies. Materials and MethodsThe hybrid segmentation method delineated the heart, four chambers, three large vessels, and the coronary arteries. The method consisted of a nnU-net heart segmentation and partly atlas- and model-based segmentation of the substructures. The nnU-net training and atlas segmentation was based on lung cancer patients and was validated against a national consensus dataset of 12 patients with breast cancer. The accuracy of dose predictions between manual and auto-segmented heart and substructures was evaluated by transferring the dose distribution of 240 previously treated lung cancer patients to the consensus data set. ResultsThe hybrid auto-segmentation method performed well with a heart dice similarity coefficient (DSC) of 0.95, with no statistically significant difference between the automatic and manual delineations. The DSC for the chambers varied from 0.78-0.86 for the automatic segmentation and was comparable with the inter-observer variability. Most importantly, the automatic segmentation was as precise as the clinical experts in predicting the dose distribution to the heart and all substructures. ConclusionThe hybrid segmentation method performed well in delineating the heart and substructures. The prediction of dose by the automatic segmentation was aligned with the manual delineations, enabling measurement of heart and substructure dose in large cohorts. The delineation algorithm will be available for download.