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Background Artificial Intelligence has created a huge impact in different areas of dentistry. Automated cephalometric analysis is one of the major applications of artificial intelligence in the field of orthodontics. Various automated cephalometric software have been developed which utilizes artificial intelligence and claim to be reliable. The purpose of this study was to compare the linear and angular cephalometric measurements obtained from web-based fully automated Artificial Intelligence (AI) driven platform “WebCeph”™ with that from manual tracing and evaluate the validity and reliability of automated cephalometric measurements obtained from “WebCeph”™. Methods Thirty pre-treatment lateral cephalograms of patients were randomly selected. For manual tracing, digital images of same cephalograms were printed using compatible X-ray printer. After calibration, a total of 18 landmarks was plotted and 12 measurements (8 angular and 4 linear) were obtained using standard protocols. The digital images of each cephalogram were uploaded to “WebCeph”™ server. After image calibration, the automated cephalometric measurements obtained through AI digitization were downloaded for each image. Intraclass correlation coefficient (ICC) was used to determine agreement between the measurements obtained from two methods. ICC value < 0.75 was considered as poor to moderate agreement while an ICC value between 0.75 and 0.90 was considered as good agreement. Agreement was rated as excellent when ICC value > 0.90 was obtained. Results All the measurements had ICC value above 0.75. A higher ICC value > 0.9 was obtained for seven parameters i.e. ANB, FMA, IMPA/L1 to MP (°), LL to E-line, L1 to NB (mm), L1 to NB (°), S-N to Go-Gn whereas five parameters i.e. UL to E-line, U1 to NA (mm), SNA, SNB, U1 to NA (°) showed ICC value between 0.75 and 0.90. Conclusion A good agreement was found between the cephalometric measurements obtained from “WebCeph”™ and manual tracing.

Supernumerary tooth/hyperdontia is defined as those teeth which are present in excess of the usual distribution of twenty deciduous and thirty-two permanent teeth. It can be seen in both syndromic and nonsyndromic patients. In Nepalese population, prevalence of supernumerary tooth is documented to be 1.6%. To the best of our knowledge, no studies from Nepal have reported the incidence of bilateral maxillary paramolars or the combination of unilateral maxillary paramolar and distomolar till date. Hence, we are reporting these two cases with a brief review of literature to put emphasis on incidence, prevalence, proposed hypothesis for etiology, and management of supernumerary teeth.

Considering the widespread transmission of Coronavirus disease (COVID-19) globally, India is also facing the same crisis. As India already has inadequate waste treatment facilities, and the sudden outbreak of the COVID-19 virus has led to significant growth of Bio-medical waste (BMW), consequently safe disposal of a large quantity of waste has become a more serious concern. This study provides a comprehensive assessment of BMW of India before and during the COVID-19 pandemic. Additionally, this article highlights the gaps in the implementation of BMW rules in India. This study uses various government and non-government organizations, reports and data specifically from the Central Pollution Control Board (CPCB). The finding of the study demonstrated that most of the States/Union Territories (UTs) of India are lacking in terms of COVID-19 waste management. India has generated over 32,996 mt of COVID-19 waste between June and December 2020. During this period, Maharashtra (789.99 mt/month) is highest average generator of COVID-19 waste, followed by Kerala (459.86 mt/month), Gujarat (434.87 mt/month), Tamil Nadu (427.23 mt/month), Uttar Pradesh (371.39 mt/month), Delhi (358.83 mt/month) and West Bengal (303.15 mt/month), and others respectively. We draw attention to the fact that many gaps were identified with compliance of BMW management rules. For example, out of all 35 States/UTs, health care facilitates (HCFs), only eight states received authorization as per BMW management rules. Moreover, the government strictly restricted the practice of deep burials; however, 23 States/UTs are still using the deep burial methods for BMW disposal. The present research suggests that those States/UTs generated on an average of 100 mt/month COVID-19 waste in the last 7 months (June–December 2020) should be considered as a high priority state. These states need special attention to implement BMW rules and should upgrade their BMW treatment capacity.

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Introduction: Variations in facial soft tissue thickness have been established previously by studies conducted in different population. Hence, it is essential to obtain facial soft tissue thickness measurement data specific to a population and develop individual standards. The objective of this research is to obtain facial soft tissue thickness data of Nepalese adult male and female subjects seeking orthodontic treatment with different sagittal skeletal malocclusion and evaluate variations in facial soft tissue thickness. Materials & Method: Facial soft tissue thicknesses was measured manually on ninety pretreatment lateral cephalogram at eleven points (Glabella, Nasion, Rhinion, Subnasale, Labrale superius, Stomion, Labrale inferius, Labiomentale, Pogonion,Gnathion and Menton). One-way Analysis of variances [one-way ANOVA] followed by Least significant difference (LSD) post hoc test was used to determine difference in facial soft tissue thickness measurements among three sagittal skeletal group for both sexes. In addition, Student’s t-test was used to find difference in facial soft tissue thickness between the male and female subjects in each skeletal Class. Result: Statistically significant differences were found at points Rhinion, Subnasale, Labrale superius, Stomion and Gnathion in males and at Subnasale, Labrale superius, Stomion and Labrale inferius in females while comparing facial soft tissue thickness among three sagittal skeletal classes. Also, it was observed that mean facial soft tissue thickness was greater for males as compared to female subjects with significant differences at Subnasale, Labrale superius, and Labrale inferius in each skeletal Class. Conclusion: Facial soft tissue thickness varies considerably among different population group, sex and sagittal relationship of jaws.

Cephalometric radiography is an indispensable tool in orthodontics for studying growth and development of dentofacial skeleton, diagnosis, treatment planning, and evaluating treatment results. [1][2][3][4] Conventionally, manual tracing is considered "Gold standard" in cephalometric analysis. However, it is cumbersome, time consuming and can be associated with various errors. These errors can occur due to improper tracing, inaccurate landmark identification, measurement and calculation errors in addition to errors occurring due to human fatigue. [3][4][5][6][7][8] With recent technological advances and increasing use of computers in the field of orthodontics cephalometric analysis using computerized cephalometric analysis softwares have gained popularity. These softwares have eliminated various errors associated with manual tracings and are less time consuming. Another big advantage of using computerized cephalometry is that multiple analyses can be done in a very short period. [9][10][11][12][13][14] Over the years, various softwares have been developed which claim to be as reliable and accurate if not more than manual tracings. Most of the studies which evaluated the reliability

Introduction: Knowledge of the safe zone of mini-implant placement guides clinicians in choosing where to place mini-implants. Several studies evaluated the safe zone for mini-implants placement, but only a very few previous studies have taken different skeletal patterns into account when assessing measurements. Objective: The purpose of this cross-sectional, comparative study was to compare the inter-radicular distance and buccal cortical bone thickness in Class I and Class II skeletal malocclusion patterns. Materials and Methods: A total of 62 CBCT images of patients with Class I and Class II skeletal malocclusion were obtained from the records of the department of Oral medicine and Radiology, Kathmandu University Teaching Hospital. The inter-radicular distance and buccal cortical bone thickness were measured at four different heights (2, 4, 6 and 8 mm) from the CEJ towards the apex. These measurements were measured between different skeletal pattern and gender with independent t-test. The intergroup comparison at different height from CEJ was done with ANOVAfollowed by Tukey's post-hoc test to see the difference within the category. Result: There was a statistically significant difference observed in the inter-radicular distance between the maxillary first and second premolars at a height of 6 mm between Class I and Class II malocclusion patterns (p = 0.03). There were differences observed in the inter-radicular distance of the mandible at a different height based on skeletal malocclusion pattern, which was not statistically significant (p > 0.05). The buccal cortical bone thickness between the maxillary central and lateral incisors at the height of 2 mm from CEJ between Class I and Class II skeletal malocclusion patterns was statistically significant (p = 0.01). The buccal cortical bone thickness of the mandible at different heights based on skeletal malocclusion pattern there were differences observed which were not statistically significant (p > 0.05). Conclusion: The inter-radicular distance and buccal cortical bone thickness could be influenced by different skeletal patterns and tend to increase from the CEJ to the apex in both Class I and Class II skeletal patterns.