Performance of Artificial Intelligence Models Designed for Automated Estimation of Age Using Dento-Maxillofacial Radiographs-A Systematic Review.

Automatic age estimation has garnered significant interest among researchers because of its potential practical uses. The current systematic review was undertaken to critically appraise developments and performance of AI models designed for automated estimation using dento-maxillofacial radiographic images. In order to ensure consistency in their approach, the researchers followed the diagnostic test accuracy guidelines outlined in PRISMA-DTA for this systematic review. They conducted an electronic search across various databases such as PubMed, Scopus, Embase, Cochrane, Web of Science, Google Scholar, and the Saudi Digital Library to identify relevant articles published between the years 2000 and 2024. A total of 26 articles that satisfied the inclusion criteria were subjected to a risk of bias assessment using QUADAS-2, which revealed a flawless risk of bias in both arms for the patient-selection domain. Additionally, the certainty of evidence was evaluated using the GRADE approach. AI technology has primarily been utilized for automated age estimation through tooth development stages, tooth and bone parameters, bone age measurements, and pulp-tooth ratio. The AI models employed in the studies achieved a remarkably high precision of 99.05% and accuracy of 99.98% in the age estimation for models using tooth development stages and bone age measurements, respectively. The application of AI as an additional diagnostic tool within the realm of age estimation demonstrates significant promise.

Unveiling the Impact of Electronic Cigarettes (EC) on Health: An Evidence-Based Review of EC as an Alternative to Combustible Cigarettes.

Cigarette smoking has been considered a major public health concern due to its serious impact on health. However, smokers intending to quit may find long-term abstinence challenging. When smoking an electronic cigarette (EC), users can experience a sensation and taste similar to that of smoking a combustible cigarette. Therefore, manufacturers promote these products as a viable substitute for combustible cigarettes. However, several researchers report the serious health impacts experienced by EC users. Therefore, this review aims to examine the health impacts of EC use. Based on the findings of the research papers reported in the literature, the role of EC as a smoking cessation tool is unclear. Several researchers have also reported a significant association between EC usage among non-smokers at baseline and the future initiation of combustible cigarette smoking. EC use significantly impacts user health. The nicotine that is present in EC e-liquids can elevate blood pressure, resulting in blood vessel constriction and an increase in heart rate, ultimately leading the body to an ischemic condition, resulting in myocardial infarction (MI), stroke, and increased arterial stiffness. Researchers report a higher likelihood of prediabetes among EC users; its usage was associated with higher OR of having asthma attacks and higher OR of reporting depression and has an impact on birth outcomes among pregnant women. Men using EC are more likely to report erectile dysfunction than non-users. EC also has a significant impact on oral health, which includes periodontal diseases, mucosal lesions, irritation in the mouth and throat, reduced salivary flow, and an increased risk of developing cancer. The physical injury resulting from exploding EC is another health concern. The frequently burned areas included the hands, face, genitalia, and thighs. Marketers promote EC as an alternative to combustible cigarettes and a tool for quitting smoking. However, the Food and Drug Administration has not approved them for smoking cessation. EC can have a serious impact on the health of their users; hence, the findings of this paper have several implications, including the need for regulation of the sales and marketing of these products and educating the users on the impact of these products on their health and safety.

The barriers, motives, perceptions, and attitudes toward research among radiology practitioners and interns in Saudi Arabia: a cross-sectional study.

Background: Research and the use of evidence-based practices are imperative to the advancement of diagnostic imaging modalities. The aim of this study was to assess the perceptions and attitudes of radiology practitioners (i.e., Technicians, Technologists or Specialists, and Senior Specialists) and interns in King Abdulaziz Medical Cities (KAMCs), Kingdom of Saudi Arabia, toward research, and to explore the various barriers and obstacles that hinder their research efforts. Methods: A cross-sectional descriptive investigation was carried out from December 2022 to March 2023 among 112-KAMCs' radiology practitioners and interns, using previously developed and validated questionnaire comprised of five distinct sections, each serving a specific purpose, and with a non-probability convenient sampling technique. Descriptive statistics were generated for participants' demographics, and chi-square and fisher's exact tests were used to examine the association between participants' demographics and their involvement in research. Results: Among the 137 KAMCs' radiology practitioners and interns who were invited to participate, 112 responded and completed the questionnaire, resulting in an overall response rate of 81.75%. Radiology practitioners and interns from various medical imaging subspecialties were found to be involved in research to the extent of 83%, with nearly half (40.9%) of them have had publications, and 53.3% of these publications being either cross-sectional studies or retrospective clinical studies. A lack of time (66.1%), a lack of a professional supervisor support program (50.9%), and deficiency in research skills (45.5%) were common obstacles that may impede the participants' ability to conduct research. The most common motives for participants to conduct research were the desire to improve their resumes (69.6%), get accepted into postgraduate radiology programs (58%), and improve their research skills (52.7%). Conclusion: KAMCs' radiology practitioners and interns have a positive attitude toward performing research. Despite the high percentage (83%) of those involved in research, the number of publications remains low. A crucial step to advancing the profession's evidence base is engaging radiology practitioners and interns in research and encouraging radiology practitioner-led research. The study findings can serve as a valuable basis for designing developmental programs aimed at overcoming research obstacles among healthcare professionals in Saudi Arabia.

Application and Performance of Artificial Intelligence (AI) in Oral Cancer Diagnosis and Prediction Using Histopathological Images: A Systematic Review.

Oral cancer (OC) is one of the most common forms of head and neck cancer and continues to have the lowest survival rates worldwide, even with advancements in research and therapy. The prognosis of OC has not significantly improved in recent years, presenting a persistent challenge in the biomedical field. In the field of oncology, artificial intelligence (AI) has seen rapid development, with notable successes being reported in recent times. This systematic review aimed to critically appraise the available evidence regarding the utilization of AI in the diagnosis, classification, and prediction of oral cancer (OC) using histopathological images. An electronic search of several databases, including PubMed, Scopus, Embase, the Cochrane Library, Web of Science, Google Scholar, and the Saudi Digital Library, was conducted for articles published between January 2000 and January 2023. Nineteen articles that met the inclusion criteria were then subjected to critical analysis utilizing QUADAS-2, and the certainty of the evidence was assessed using the GRADE approach. AI models have been widely applied in diagnosing oral cancer, differentiating normal and malignant regions, predicting the survival of OC patients, and grading OC. The AI models used in these studies displayed an accuracy in a range from 89.47% to 100%, sensitivity from 97.76% to 99.26%, and specificity ranging from 92% to 99.42%. The models' abilities to diagnose, classify, and predict the occurrence of OC outperform existing clinical approaches. This demonstrates the potential for AI to deliver a superior level of precision and accuracy, helping pathologists significantly improve their diagnostic outcomes and reduce the probability of errors. Considering these advantages, regulatory bodies and policymakers should expedite the process of approval and marketing of these products for application in clinical scenarios.

Job Satisfaction of Radiographers in Saudi Arabia.

PURPOSE: To examine the various facets of job satisfaction among radiographers in Saudi Arabia and compare the influential contributing factors locally and internationally. METHODS: A cross-sectional survey was conducted in June and July 2020 with an electronic questionnaire distributed to radiographers in Saudi Arabia. The validated Job Satisfaction Survey was used to measure overall job satisfaction and specific satisfaction regarding pay, promotions, supervision, benefits, contingent rewards, operating conditions, coworkers, nature of work, and communication (total Job Satisfaction Survey score can range from 36 to 216). Additional personal and work-related characteristics were collected as explanatory variables. Data were analyzed with descriptive and inferential statistics, including 1-way analysis of variance, independent sample t test, and Spearman correlation. RESULTS: A total of 412 radiographers in Saudi Arabia completed the survey. The total job satisfaction score was 140.0 (95% confidence interval [CI], 138.7-141.2), showing that 6 respondents (1.5%) were dissatisfied with their job, while the remaining majority were neutral (63%) or satisfied (36%). The radiographers were satisfied with the nature of work, contingent rewards, and coworkers. However, they were less satisfied with promotions, pay, operating conditions, and benefits. The only significant variable in overall job satisfaction was the working sector (P = .03), with radiographers working at Ministry of Health hospitals who were more satisfied than were their colleagues who worked at other types of facilities. DISCUSSION: The radiographers in Saudi Arabia had higher overall job satisfaction than had other allied health science professionals in Saudi Arabia. The differences in job satisfaction subscales between radiographers from different countries suggest that their job satisfaction likely is related to culture and socioeconomics. Job satisfaction improvement programs should be tailored for each radiographer's community. CONCLUSION: Radiographers in Saudi Arabia expressed moderate to high job satisfaction, which is relatively higher than their international peers and national colleagues in physical therapy and nursing. These job satisfaction results call for governmental policymakers to focus their efforts on improving radiographer promotion schemes and career development.

Predictive value and reference ranges of anogenital distance for determining fetal gender in the first trimester: A retrospective cohort study.

OBJECTIVES: To assess the usefulness of sonographically measured anogenital distance (AGD) in predicting fetal gender in Saudi fetuses during the first trimester and to provide normal reference centiles for AGD. METHODS: A retrospective cohort study was conducted at King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia between November 2020 and May 2021. The ultrasound scans of 313 singleton pregnancies between 11-13 plus 6 gestational weeks and their gender-at-birth were collected. Anogenital distance was measured from the inferior base of the genital tubercle to the rump. Binominal logistic regression and receiver operating characteristic curves (ROC) evaluated the predictive performance of AGD for determining fetal gender. RESULTS: There was a significant difference of approximately 15% in mean AGD between female (5.92 mm [95% CI= 6.70, 6.14]) and male (6.80 mm [95% CI= 6.61,7.00]) fetuses (p<0.001). Anogenital distance significantly correlated with gestational age (r=0.573, p<0.001) and crown-rump length (r=0.562, p<0.001). The logistic regression determined AGD as a significant predictor of fetal gender (p<0.001). However, ROC analysis showed that overall accuracies were low at 68% (p=0.001) for 11 weeks, 70% (p<0.001) for 12 weeks, and 64% (p=0.017), and for 13 weeks. The average AGD of our Saudi cohort was longer than what the literature reported from other populations. CONCLUSION: The first-trimester ultrasound evaluation of AGD was feasible and reliable. It showed a difference between the genders but did not yield high predictive accuracy. Future research should consider racial factors when evaluating AGD.

Investigating Microstructural Changes in White Matter in Multiple Sclerosis: A Systematic Review and Meta-Analysis of Neurite Orientation Dispersion and Density Imaging.

Multiple sclerosis (MS) is characterised by widespread damage of the central nervous system that includes alterations in normal-appearing white matter (NAWM) and demyelinating white matter (WM) lesions. Neurite orientation dispersion and density imaging (NODDI) has been proposed to provide a precise characterisation of WM microstructures. NODDI maps can be calculated for the Neurite Density Index (NDI) and Orientation Dispersion Index (ODI), which estimate orientation dispersion and neurite density. Although NODDI has not been widely applied in MS, this technique is promising in investigating the complexity of MS pathology, as it is more specific than diffusion tensor imaging (DTI) in capturing microstructural alterations. We conducted a meta-analysis of studies using NODDI metrics to assess brain microstructural changes and neuroaxonal pathology in WM lesions and NAWM in patients with MS. Three reviewers conducted a literature search of four electronic databases. We performed a random-effect meta-analysis and the extent of between-study heterogeneity was assessed with the I2 statistic. Funnel plots and Egger's tests were used to assess publication bias. We identified seven studies analysing 374 participants (202 MS and 172 controls). The NDI in WM lesions and NAWM were significantly reduced compared to healthy WM and the standardised mean difference of each was -3.08 (95%CI -4.22 to (-1.95), p ≤ 0.00001, I2 = 88%) and -0.70 (95%CI -0.99 to (-0.40), p ≤ 0.00001, I2 = 35%), respectively. There was no statistically significant difference of the ODI in MS WM lesions and NAWM compared to healthy controls. This systematic review and meta-analysis confirmed that the NDI is significantly reduced in MS lesions and NAWM than in WM from healthy participants, corresponding to reduced intracellular signal fraction, which may reflect underlying damage or loss of neurites.

Occupational exposure and radiobiological risk from thyroid radioiodine therapy in Saudi Arabia.

Worldwide, thyroid cancer accounts for some 10% of total cancer incidence, most markedly for females. Thyroid cancer radiotherapy, typically using 131I (T1/2 8.02 days; ß- max energy 606 keV, branching ratio 89.9%), is widely adopted as an adjunct to surgery or to treat inoperable cancer and hyperthyroidism. With staff potentially receiving significant doses during source preparation and administration, radiation protection and safety assessment are required in ensuring practice complies with international guidelines. The present study, concerning a total of 206 patient radioiodine therapies carried out at King Faisal Specialist Hospital and Research Center over a 6-month period, seeks to evaluate patient and occupational exposures during hospitalization, measuring ambient doses and estimating radiation risk. Using calibrated survey meters, patient exposure dose-rate estimates were obtained at a distance of 30-, 100- and 300 cm from the neck region of each patient. Occupational and ambient doses were measured using calibrated thermoluminescent dosimeters. The mean and range of administered activity (AA, in MBq) for the thyroid cancer and hyperthyroidism treatment groups were 4244 ± 2021 (1669-8066), 1507.9 ± 324.1 (977.9-1836.9), respectively. The mean annual occupational doses were 1.2 mSv, that for ambient doses outside of the isolation room corridors were found to be 0.2 mSv, while ambient doses at the nursing station were below the lower limit of detection. Exposures to staff from patients being treated for thyroid cancer were less compared to hyperthyroidism patients. With a well-defined protocol, also complying with international safety requirements, occupational exposures were found to be relatively high, greater than most reported in previous studies.

Investigating Brain Microstructural Alterations in Type 1 and Type 2 Diabetes Using Diffusion Tensor Imaging: A Systematic Review.

Type 1 and type 2 diabetes mellitus have an impact on the microstructural environment and cognitive functions of the brain due to its microvascular/macrovascular complications. Conventional Magnetic Resonance Imaging (MRI) techniques can allow detection of brain volume reduction in people with diabetes. However, conventional MRI is insufficiently sensitive to quantify microstructural changes. Diffusion Tensor Imaging (DTI) has been used as a sensitive MRI-based technique for quantifying and assessing brain microstructural abnormalities in patients with diabetes. This systematic review aims to summarise the original research literature using DTI to quantify microstructural alterations in diabetes and the relation of such changes to cognitive status and metabolic profile. A total of thirty-eight published studies that demonstrate the impact of diabetes mellitus on brain microstructure using DTI are included, and these demonstrate that both type 1 diabetes mellitus and type 2 diabetes mellitus may affect cognitive abilities due to the alterations in brain microstructures.