Journal of Radiation Research and Applied Sciences最新文献

Objective

As artificial intelligence (AI) increasingly integrates into healthcare sectors globally, it becomes crucial to examine its impact within specific contexts. This study aims to explore MRI technologists' perceptions towards AI in radiology in Saudi Arabia and to identify the demographic factors influencing these perceptions.

Methodology

A cross-sectional survey was conducted among 128 MRI technologists in Saudi Arabian healthcare facilities. The 10-question survey captured key aspects of their perceptions towards AI integration. Statistical analyses using R software included logistic regression to identify significant associations between demographic factors and AI perceptions. Odds ratios (ORs), 95% confidence intervals (CIs), and p-values were computed, with statistical significance set at an alpha level of 0.05.

Results

The survey results indicated that a significant majority (84.4%) of technologists agree that AI will play a crucial role in the future of radiology. Higher education levels were significantly associated with positive perceptions of AI (OR 1.75, p = 0.028). Male technologists and those aged 40–49 showed more pronounced apprehensions about AI's disruptions. Specifically, the odds ratio for male technologists perceiving AI will disrupt MRI practice was 2.05 (p = 0.009), and for those aged 40–49, the odds ratio was 1.60 (p = 0.013). The odds ratio for male technologists believing AI will disrupt careers was 1.85 (p = 0.012), and for those aged 40–49, it was 1.50 (p = 0.030). Additionally, the odds of believing AI integration will not change their work were significantly higher among males (OR 2.25, p = 0.002).

Conclusion

These findings highlight the need for targeted educational programs and support initiatives for MRI technologists in Saudi Arabia. Addressing the concerns of apprehensive groups, particularly older and male technologists, through continuous education and realistic information sessions can facilitate smoother AI integration. These initiatives are essential for aligning AI advancements with Saudi Arabian cultural and professional standards, ensuring a prepared and supportive workforce.

Nanotechnology has revolutionized the different fields of forensic science, particularly in the efficient examination of evidence. In this study, we report scalable synthesis of copper oxide (CuO) nanosheets by using hydrothermal method and its exploration in the forensic examination of latent fingerprints. The identification and structural characterization of CuO nanoparticles were carried out using advanced spectroscopic methods such as powder X-ray diffraction (PXRD), Raman spectroscopy, and Fourier transform infrared spectroscopy (FTIR). The stabilization of CuO nanosheets in monoclinic symmetry (space group C2/c) was confirmed through Le Bail refinements. Morphological studies based on scanning electron microscopy (SEM) revealed that the CuO nanosheets exhibit, a rectangular, thin plate like morphology.

The applicability of these nanosheets was tested for examining and developing fresh and aged (7 days old) latent fingerprints on dry, non-absorbent substrates using the powder dusting method. The formulation successfully developed sharp and clear fingerprints on various substrates, allowing the second-level details of the fingerprints to be viewed without any background interference. Additionally, these nanosheets are non-hazardous and cost-effective, making them a suitable fingerprint developing agent for a wide range of dry, non-absorbent surfaces recovered from crime scenes.

Radiation can cause life-threatening intestinal damage, whether intentional or unintentional. The present study investigated the effects of mild hypothermia on radiation-induced intestinal injury and survival. For 1 h before and after a lethal dose of whole-body irradiation (13 Gy), mice were either maintained at normothermia (37 °C) or exposed to mild hypothermia (32 °C). The survival of the mice was monitored for 30 days, and the morphological changes in the intestine and the cytokine levels in the serum of the irradiated mice at normothermia or hypothermia were assessed by histological examination at 12 h, 3.5 days, and 5 days after irradiation. Hypothermia delayed the death of the mice and attenuated the damage to the intestine. Hypothermia reduced apoptosis in the jejunum 12 h after irradiation exposure and restored crypt number, villi length, and epithelial length of the jejunum after 3.5 days. Mild hypothermia also reduced serum levels of proinflammatory cytokines after radiation exposure. Furthermore, heme oxygenase-1 (HO-1) was specifically upregulated in the mouse intestine by hypothermia. The HO-1 inhibitor Sn(IV) protoporphyrin IX dichloride partially reversed the effect mild hypothermia had on HO-1. These results suggest that hypothermia is a protective factor against radiation-induced intestinal damage and can, therefore, be effectively used as a radioprotective condition. In summary, mild hypothermia reduced cell death and inflammation in radiation-induced intestinal injury, partly through the regulation of HO-1.

In order to provide method support for remote sensing image classification of weak texture region and improve the classification effect, a remote sensing image classification model for weak texture region was constructed. Firstly, the Gray Level Co-occurrence Matrix (GLCM) was used to extract texture features, then the correlation between texture features was reduced by dimensionality reduction method, and finally the spectral features were fused to classify remote sensing images. In the experimental part, neural network classifier was used to classify images based on texture feature, spectral feature and spectral features combined with texture features, and the results ware compared with object-oriented classification method. The analysis of texture extraction in the study area shows that the texture feature image obtained in the 5 × 5 window has higher resolution than that in the 7 × 7 window, and more robust texture features can be obtained in the range of 4∼8 pixel pairs. When using neural network classifier for classification, compared with images based on spectral features and texture features, the overall classification accuracy (OA) of the proposed classification model is increased by 16.72% and 11.16%, respectively, and the Kappa coefficient is increased by 0.2824 and 0.1943, respectively. Compared with the object-oriented classification method, the overall classification accuracy of the proposed classification scheme is increased by 1.15%, and the Kappa coefficient is increased by 0.0191. The constructed model has good classification effect and high classification accuracy for remote sensing images of weak texture region, and can provide scientific reference for remote sensing image classification of weak texture region.

A neurological disorder that affects many people globally, multiple sclerosis (MS) is mysterious and complicated. MRI is an efficient tool in diagnosing and monitoring MS, that enables visualizing the characteristic demyelinating lesions that are a hallmark of MS. To evaluate the effectiveness of DIR sequence in identifying MS lesions, we compared DIR sequences at both 1.5 and 3 T MRI scanners with FLAIR. The study spanned 6–9 months at Ain Shams University, Egypt. The study comprised 50 individuals who had a confirmed diagnosis of MS. A cohort of 50 patients were divided between two MRI scanners: 25 at 1.5 T and 25 at 3 T. The group has 42 females (84% of the participants) and 8 males (16% of the participants). The average age was 31.5 years (±6.7) for those who underwent the 1.5 T MRI scan and 32.47 years (±6.7) for those who underwent the 3 T MRI scan. With p-values of 0.6 and 0.8, respectively, the results showed that there were no statistically significant variations in lesion size between DIR and FLAIR at 1.5 T and 3 T MRI scanners. With p-values less than 0.05, the results showed that DIR considerably outperformed FLAIR in terms of lesion intensity at both 1.5 T and 3 T. Regarding the number of lesions, the results demonstrated that DIR was more effective than FLAIR at both 1.5 T and 3 T, with p-values of 0.008 and 0.006 respectively. DIR has become an indispensable tool in diagnosing and managing multiple sclerosis. Comparing FLAIR to DIR showed superiority in detecting number of lesions and intensity of lesions by DIR.

Parkinson's disease (PD) is a progressive neurological illness characterized by symptoms such as bradykinesia (slowness of movement), tremor, rigidity, and postural instability. Diagnosing parkinsonian syndromes (PS) can be challenging, even for specialized neurology centers, due to the high rate of diagnostic errors. This review article highlights the challenges in diagnosing PS and the importance of accurately differentiating it from PD. It discusses the utility of various magnetic resonance imaging (MRI) techniques and transcranial ultrasound (TUS) in improving diagnostic accuracy. The focus is on both conventional and cutting-edge MRI procedures, including T₂*/T₂-weighted MRI, susceptibility-weighted imaging (SWI), diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI), magnetization transfer imaging (MTI), magnetic resonance spectroscopy (MRS), and ultra-high-resolution MRI. These advanced techniques have shown promising potential in aiding diagnosis and identifying early signs of PD. The review emphasizes the clinical relevance of these imaging modalities in discriminating PD from other parkinsonian disorders and detecting early-stage disease before the onset of clinical symptoms.

Competing risks models are invaluable probabilistic models in survival analysis, a particular part of medical research. Such models deal with research problems that involve multiple potential risk factors that compete with each other to cause death (i.e., failure from a statistical perspective). Competing risks models' flexibility must be thoroughly explored to guarantee suitability for multifaceted risk scenarios (e.g., modeling data of malicious diseases where factors such as treatment response and progression are intertwined). This article considers a new competing risks model called the additive generalized linear-exponential (AGLE) competing risks model. The proposed model is expected to be more robust and superior to other well-known models when modeling real-life data. A mathematical treatment for the properties of the new model is first considered. Afterward, model parameters estimation via various estimation methods is discussed. The critical role of estimating shape parameters in understanding blood cancer's survival and failure mechanisms is highlighted. Furthermore, the bias and root mean square error of different estimation methods are examined numerically through Monte Carlo simulations. The simulation study indicated that the maximum product of spacings estimation method for the model parameters has the optimal balance of bias and variance as the sample sizes increase. Two real-life blood cancer data sets are analyzed to illustrate the application of the proposed model. The analysis outcomes support the AGLE model's robustness, with low Kolmogorov-Smirnov statistics and high p-value, affirming its superior fit for blood cancer data compared to other well-known models.

This study investigates the influence of moisture on soil radon exhalation, natural radioactivity in soil, and indoor radon concentrations in offices and laboratories at the Ghana Atomic Energy Commission (GAEC) and their associated radiological risks to workers. Radon exhalation rates were determined using the Sealed Can method. CR-39 SSNTD detectors were used to measure indoor radon concentrations. Gamma spectroscopy using HpGe detector was used to determine the activity concentrations of U-238, Ra-226, Th-232, and K-40 in the soil samples. The results showed mean concentrations of 14.3 ± 2.0 Bq/kg (CI 95%: 10.0–18.0) for U-238, 145.0 ± 10.0 Bq/kg (CI 95%:123.0–167.0) for K-40, 31.5 ± 6.0 Bq/kg (CI 95%: 24.0–39.0) for Th-232, and 15.6 ± 2.0 Bq/kg (CI 95%:14.0–29.0) for Ra-226. The results showed mean surface and mass exhalation rates of 6.9 ± 2.3 × 10⁻⁴ Bq/m²/h¹ (CI 95%: 5.7 × 10⁻⁴ –12.6 × 10⁻⁴) and 2.4 ± 0.4 (CI 95%: 1.9–4.2) nBq/kg¹/h¹ respectively. The findings revealed mean indoor radon concentrations of 93.0 ± 10.0 Bq/m³ (CI 95%: 88.0–98.0), 111.0 ± 12.0 Bq/m³ (CI 95%: 102.0–119.0) and 145.0 ± 13.0 Bq/m³ (CI 95%: 135.0–155.0) in the offices, laboratories, and basements respectively, with laboratories and basements exceeding the WHO reference level of 100 Bq/m³. A strong inverse relationship between moisture levels and exhalation rates (r = −0.8) was observed, leading to a negative correlation (r = −0.3). Between the moisture levels and indoor radon levels. The research findings indicated a mean annual effective dose of 0.6 mSv/yr. (CI 95%: 0.5–0.6) to the workers, which is well below occupational and public dose limits. The lung cancer cases of workers were computed which ranged from 0.9 × 10⁻⁸ to 1.2 × 10⁻⁸ cases per million people per year, which is less than the limit range of 170–230 per million people per year recommended by ICRP but remaining with safe radiological limits for workers. This study identified moderate radon exposure risks at the GAEC, exceeding the WHO recommendation. The correlation and trend analysis demonstrate strong relationships between moisture, exhalation rates, radium, and indoor radon.

Background

Radiologic fluoroscopy procedures have been imposing considerable exposure dose to staff with serious consequences relative to dose quantity which is still continuing as challenge of studies, hence the aims were to assess the animal behavior, quantify blood components and red blood cells morphology after exposure to x-ray urologic fluoroscopy doses (0.3, 0.8, 1.8 and 2.5 mSv).

Methods

urologic exposure doses measured by TLDs chips and TLD reader Model 5500 from selected hospitals. These doses used to expose Wister male rats weighted (275 ± 2.0 g). The collected data were animal behavior, quantity of blood components and cellular changes in RBCs, kidneys, liver & testicles then analyzed by SPSS- 20 (SPSS Inc., Chicago, IL, USA)

Results

showed that a dose of 2.5 mSv decreased significantly (p value = 0.00) the motor activity of rats. and the blood components decreased as follows: WBC (30.2%), Lymphocytes (40%.0), Neutrophils (35.7%), RBC (37.9%), MCV (32.2%) and RCDW (31.5%). At exposure dose of 0.3 mSv a mild morphological changes as circular shape deformity and loss of bi-concavity of RBCs. At 0.8 mSv RBCs diameter increment (10 ± 0.4 μm) and formation of spikes. At 1.8 mSv RBC underwent anisocytosis and poikilocytosis. While at 2.5 mSv the RBC showed intensive spikes, clustering and some underwent hemolysis. Morphological changes were induced also, at 2.5 mSv for the followings: The renal cortex showed bleeding & congestion at 2.5 mSv. The Renal medulla showed bleeding at 2.5 mSv. The liver texture showed bleeding and congestion with two nuclei- Kupffer cells hyperplasia, ballooning of hepatocytes with Acidophilic bodies at 2.5 mSv. the testicles tissues developed congestion and bleeding.

Conclusion

fluoroscopic urologic exposure dose can induce significant behavioral, RBCs changes and reduction in blood components.