Estimation and comparison of the effective dose and lifetime attributable risk of thyroid cancer between males and females in routine head computed tomography scans: a multicentre study.

INTRODUCTION: A significant number of head computed tomography (CT) scans are performed annually. However, due to the close proximity of the thyroid gland to the radiation field, this procedure can expose the gland to ionising radiation. Consequently, this study aimed to estimate organ dose, effective dose (ED) and lifetime attributable risk (LAR) of thyroid cancer from head CT scans in adults. METHODS: Head CT scans of 74 patients (38 males and 36 females) were collected using three different CT scanners. Age, sex, and scanning parameters, including scan length, tube current-time product (mAs), pitch, CT dose index, and dose-length product (DLP) were collected. CT-Expo software was used to calculate thyroid dose and ED for each patient based on scan parameters. LARs were subsequently computed using the methodology presented in the Biologic Effects of Ionizing Radiation (BEIR) Phase VII report. RESULTS: Although the mean thyroid organ dose (2.66 ± 1.03 mGy) and ED (1.6 ± 0.4 mSv) were slightly higher in females, these differences were not statistically significant compared to males (mean thyroid dose, 2.52 ± 1.31 mGy; mean ED, 1.5 ± 0.4 mSv). Conversely, there was a significant difference between the mean thyroid LAR of females (0.91 ± 1.35) and males (0.20136 ± 0.29) (P = 0.001). However, the influencing parameters were virtually identical for both groups. CONCLUSIONS: The study's results indicate that females have a higher LAR than males, which can be attributed to higher radiation sensitivity of the thyroid in females. Thus, additional care in the choice of scan parameters and irradiated scan field for female patients is recommended.

The feasibility of the pretreatment verification of 2D dose distributions in radiation therapy with small fields using the electronic portal imaging device.

BACKGROUND: The present study aims to evaluate the performance of an Electronic portal imaging device (EPID) for measuring dosimetric parameters and for verification of dose in small photon fields. MATERIAL AND METHODS: In this study, the beam profiles were obtained using the amorphous silicon (a-Si) EPID for field sizes ranging from 1 × 1 to 10 × 10 cm 2 at energies 6 and 18 mega-voltage (MV). For comparison, the dosimetric parameters, including penumbra widths and field sizes, were measured with the pinpoint, diode, and Semiflex dosimeters. Finally, Rando Phantom was used to compare the two-dimensional (2D) Dose distribution between EPID and Treatment Planning System (TPS). RESULTS: In both 5 cm and 10 cm depths, there were large differences between the measured doses obtained from TPS, Pinpoint detector, and Farmer detector in 1 × 1 field size. The differences become negligible as the field sizes increase and from 3 × 3 field size to 10 × 10 field size, the maximum observed differences are 2 cGy and 2.4 cGy for 5 cm and 10 cm depths, respectively. The results indicate that the penumbra widths are smaller in the Gantry-Target (GT) direction compared to the Right-Left (RL) direction. The maximum difference (47.6%) was observed for EPID in the 10 × 10 field size, and the minimum difference (16.6%) was observed for TPS in the 1 × 1 field size. Finally, 2D dose distributions obtained by EPID and TPS exhibit excellent agreement. CONCLUSION: EPID is an excellent tool for the measurement of dosimetry parameters such as dose profiles, penumbra widths, field sizes, and pretreatment verification of 2D dose distributions, especially in small fields.

Electromagnetic fields exposure on fetal and childhood abnormalities: Systematic review and meta-analysis.

Today, in the modern world, people are often exposed to electromagnetic waves, which can have undesirable effects on cell components that lead to differentiation and abnormalities in cell proliferation, deoxyribonucleic acid (DNA) damage, chromosomal abnormalities, cancers, and birth defects. This study aimed to investigate the effect of electromagnetic waves on fetal and childhood abnormalities. PubMed, Scopus, Web of Science, ProQuest, Cochrane Library, and Google Scholar were searched on 1 January 2023. The Cochran's Q-test and I 2 statistics were applied to assess heterogeneity, a random-effects model was used to estimate the pooled odds ratio (OR), standardized mean difference (SMD), and mean difference for different outcomes, and a meta-regression method was utilized to investigate the factors affecting heterogeneity between studies. A total of 14 studies were included in the analysis, and the outcomes investigated were: change in gene expression, oxidant parameters, antioxidant parameters, and DNA damage parameters in the umbilical cord blood of the fetus and fetal developmental disorders, cancers, and childhood development disorders. Totally, the events of fetal and childhood abnormalities were more common in parents who have been exposed to EMFs compared to those who have not (SMD and 95% confidence interval [CI], 0.25 [0.15-0.35]; I 2, 91%). Moreover, fetal developmental disorders (OR, 1.34; CI, 1.17-1.52; I 2, 0%); cancer (OR, 1.14; CI, 1.05-1.23; I 2, 60.1%); childhood development disorders (OR, 2.10; CI, 1.00-3.21; I 2, 0%); changes in gene expression (mean difference [MD], 1.02; CI, 0.67-1.37; I 2, 93%); oxidant parameters (MD, 0.94; CI, 0.70-1.18; I 2, 61.3%); and DNA damage parameters (MD, 1.01; CI, 0.17-1.86; I 2, 91.6%) in parents who have been exposed to EMFs were more than those in parents who have not. According to meta-regression, publication year has a significant effect on heterogeneity (coefficient: 0.033; 0.009-0.057). Maternal exposure to electromagnetic fields, especially in the first trimester of pregnancy, due to the high level of stem cells and their high sensitivity to this radiation, the biochemical parameters of the umbilical cord blood examined was shown increased oxidative stress reactions, changes in protein gene expression, DNA damage, and increased embryonic abnormalities. In addition, parental exposure to ionizing and non-ionizing radiation can lead to the enhancement of different cell-based cancers and developmental disorders such as speech problems in childhood.

Automated deep learning-based segmentation of COVID-19 lesions from chest computed tomography images.

Purpose: The novel coronavirus COVID-19, which spread globally in late December 2019, is a global health crisis. Chest computed tomography (CT) has played a pivotal role in providing useful information for clinicians to detect COVID-19. However, segmenting COVID-19-infected regions from chest CT results is challenging. Therefore, it is desirable to develop an efficient tool for automated segmentation of COVID-19 lesions using chest CT. Hence, we aimed to propose 2D deep-learning algorithms to automatically segment COVID-19-infected regions from chest CT slices and evaluate their performance. Material and methods: Herein, 3 known deep learning networks: U-Net, U-Net++, and Res-Unet, were trained from scratch for automated segmenting of COVID-19 lesions using chest CT images. The dataset consists of 20 labelled COVID-19 chest CT volumes. A total of 2112 images were used. The dataset was split into 80% for training and validation and 20% for testing the proposed models. Segmentation performance was assessed using Dice similarity coefficient, average symmetric surface distance (ASSD), mean absolute error (MAE), sensitivity, specificity, and precision. Results: All proposed models achieved good performance for COVID-19 lesion segmentation. Compared with Res-Unet, the U-Net and U-Net++ models provided better results, with a mean Dice value of 85.0%. Compared with all models, U-Net gained the highest segmentation performance, with 86.0% sensitivity and 2.22 mm ASSD. The U-Net model obtained 1%, 2%, and 0.66 mm improvement over the Res-Unet model in the Dice, sensitivity, and ASSD, respectively. Compared with Res-Unet, U-Net++ achieved 1%, 2%, 0.1 mm, and 0.23 mm improvement in the Dice, sensitivity, ASSD, and MAE, respectively. Conclusions: Our data indicated that the proposed models achieve an average Dice value greater than 84.0%. Two-dimensional deep learning models were able to accurately segment COVID-19 lesions from chest CT images, assisting the radiologists in faster screening and quantification of the lesion regions for further treatment. Nevertheless, further studies will be required to evaluate the clinical performance and robustness of the proposed models for COVID-19 semantic segmentation.

Assessment of background radiation levels in the southeast of Iran.

Background: Measuring background radiation (BR) is highly important from different perspectives, especially from that of human health. This study was conducted to measure BR in the southeast of Iran. Methods: BR was measured in Hormozgan and Sistan-Bluchestan provinces using portable Environmental Radiation Meter Type 6- 80 detector. The average value was used to calculate the absorbed dose rate and indoor annual effective dose (AED) from BR. In addition, excess lifetime cancer risk (ELCR) was evaluated. Results: The results showed that the maximum and minimum absorbed dose rates were 71.9 and 34.2 nGy.h-1 in Abomoosa and Minab in Hormozgan province and 90.0 and 47.8 nGy.h-1 in Zahedan and Chabahar in Sistan-Bluchestan province, respectively. Data indicated that these areas had a lower BR level compared with the worldwide level. The ELCR from indoor AED was larger compared with the worldwide average of 0.29 × 10-3. Conclusion: This study provided a reference for designing and developing specific regional surveys associated with the measurement of natural BR in the southeast of Iran.

Application of rectal retractor for postprostatectomy salvage radiotherapy of prostate cancer: A case report and literature review.

Using a rectal retractor (RR) during salvage radiotherapy after radical prostatectomy is a promising approach for reducing dose to the rectum. The patient well tolerated the daily RR insertion. This area of research encourages researchers for a comprehensive evaluation of the role of the RR in postprostatectomy radiotherapy.

Benchmarking of Monte Carlo model of Siemens Oncor® linear accelerator for 18MV photon beam: Determination of initial electron beam parameters.

OBJECTIVE: This study aims to benchmark a Monte Carlo (MC) model of the 18 MV photon beam produced by the Siemens Oncor® linac using the BEAMnrc and DOSXYZnrc codes. METHODS: By matching the percentage depth doses and beam profiles calculated by MC simulations with measurements, the initial electron beam parameters including electron energy, full width at half maximum (spatial FWHM), and mean angular spread were derived for the 10×10 cm2 and 20×20 cm2 field sizes. The MC model of the 18 MV photon beam was then validated against the measurements for different field sizes (5×5, 30×30 and 40×40 cm2) by gamma index analysis. RESULTS: The optimum values for electron energy, spatial FWHM and mean angular spread were 14.2 MeV, 0.08 cm and 0.8 degree, respectively. The MC simulations yielded the comparable measurement results of these optimum parameters. The gamma passing rates (with acceptance criteria of 1% /1 mm) for percentage depth doses were found to be 100% for all field sizes. For cross-line profiles, the gamma passing rates were 100%, 97%, 95%, 96% and 95% for 5×5, 10×10, 20×20, 30×30 and 40×40 cm2 field sizes, respectively. CONCLUSIONS: By validation of the MC model of Siemens Oncor® linac using various field sizes, it was found that both dose profiles of small and large field sizes were very sensitive to the changes in spatial FWHM and mean angular spread of the primary electron beam from the bending magnet. Hence, it is recommended that both small and large field sizes of the 18 MV photon beams should be considered in the Monte Carlo linac modeling.