Development of Brief Image Quality Evaluation Criteria for Digital OrthoPantomography （OPG） Images in Dental Radiography

An OPG （orthopantmography） is an extra-oral radiographic imaging method which provides a panoramic or wide view of both jaws and teeth on a single image. Digital OPG images provide high contrast with more details of the dentitions. The research main objective was to produce sophisticated and effective criteria that can be used by any radiographer with sound knowledge to identify common errors of digital OPG images and to increase the concern of high frequency of errors to minimize them to give an optimum image quality. The study was designed as retrospective cross sectional study. Hundred digital OPG images are evaluated by three qualified radiographers who had dental radiography experience and four student radiographers. Paired t-test was used to see the difference between the responses of radiographers and student radiographers. Kruskal-Wallis Test was used to see difference between each evaluator. Possible errors of OPG were divided into four main categories （identification, artifact, anatomical coverage and patient positioning）. Each main category consists of sub-categories. Values of subcategories were given according to their importance to get the total of 100% for each main category. The results showed that there is no significant difference between radiographers and student radiographers’ responses and also between each evaluator. Hence it shows that the criteria were an easy understandable and user-friendly tool. And results showed the frequent error category was loss of anatomical coverage and frequent error was absence of positioning the tongue against the palate.

Classification and detection of dental images using meta-learning

Meta-learning of dental X-rays is a machine learning technique that can be used to train models to perform new tasks quickly and with minimal input.Instead of just memorizing a task,this is accomplished through teaching a model how to learn.Algorithms for meta-learning are typically trained on a collection of training problems,each of which has a limited number of labelled instances.Multiple Xray classification tasks,including the detection of pneumonia,coronavirus disease 2019,and other disorders,have demonstrated the effectiveness of meta-learning.Meta-learning has the benefit of allowing models to be trained on dental X-ray datasets that are too few for more conventional machine learning methods.Due to the high cost and lengthy collection process associated with dental imaging datasets,this is significant for dental X-ray classification jobs.The ability to train models that are more resistant to fresh input is another benefit of meta-learning.

Radiation protection knowledge and practices among Moroccan dentists:A cross-sectional study

Objective:To analyze the current status of knowledge and practices among the Moroccan dentists in the region of Rabat-Sale-Kenitra,towards radiation protection.Methods:This is a cross-sectional study based on a questionnaire related to knowledge and practice regarding radiation protection of patients and dental staff from April to June 2022.The study sample included 325 dentists practicing in the Rabat-Sale-Kenitra region.The target population consisted of all dentists working in public,semipublic and private workplaces.Results:96.6%of dentists were aware of radiation protection.However,nearly 35%were aware of ALARA(as low as reasonably achievable)principle and 73.9%thought that dental X-rays are harmful.63.6%of subjects used digital image receptor.Only 16.7%of them used a film holder and more than 60%didn't follow the position and distance rule.The median knowledge score was 7[5,9],and there was a statistically significant difference according to dentist qualification(P=0.007),dental radiation protection continuous training(P<0.0001),age(P=0.007)and years of experience(P=0.039).The median practice score was 5[4,6]and there was a statically significance association according to workplace setting(P=0.001).There was a significant positive relationship between knowledge score and practice score(r=0.24,P<0.0001).Dentist qualification(OR 0.51,95%CI:0.27–0.94,P=0.03)and continuous training(OR 2.40,95%CI:1.47–3.93,P<0.0001)were significant predictors of knowledge,while workplace setting(OR 0.54,95%CI:0.32–0.93,P=0.027)and knowledge score(OR 1.24,95%CI:1.12–1.38,P<0.0001)were predictors of practices.Conclusion:Improving dentists'knowledge of radiation protection measures and tools as well as dose reduction techniques could increase their safe practices in dental radiology.