Morphology of the Roots and Canals of Mandibular Third Molars, Their Symmetry and Related Factors Using Cone-Beam Computed Tomography

Introduction: Adequate knowledge about the anatomy of the roots and canals of mandibular third molars is imperative for a successful treatment. This study aimed to use cone-beam computed tomography (CBCT) to evaluate the morphology of the roots and canals of mandibular third molars and their symmetry. Methods and Materials: Totally, 110 CBCT images of bilateral mandibular third molars were evaluated in terms of the number of roots and canals, canal type, isthmus location, location of accessory canals, degree of root curvature and its direction, age and sex of patients and the symmetry of variables in the right and left sides of the mandible. The descriptive statistics, t-test and chi-square test were applied to analyze data. Results: Of all, 71.36% of mandibular third molars had two roots, 20.9% had one single root and 7.72% had three roots. The distal root had one single canal in 89.08%. The mesial root had one single canal in 44.25% and two canals in 49.42%. The Vertucci’s types I (45.40%) and IV (34.48%) had the highest frequency in the mesial root while type I (91.95%) had the highest frequency in the distal root. The deviation of mesial root was towards the distal while distal roots were mainly straight. Conclusion: The symmetry between the right and left mandibular third molars was significantly high. In case of encountering anatomical complexities in dental treatment of a mandibular third molar, dental clinicians should consider the high possibility of presence of the same condition in the contralateral mandibular third molar.Keywords: Anatomy; Cone-Beam Computed Tomography; Mandible; Third Mola

Anatomy of Permanent‎ ‎Mandibular‎ First‎ Molars in a Selected Iranian Population Using ‎Cone-beam Computed Tomography

Introduction: Knowledge of radicular anatomy has a crucial impact on endodontic practices. Since some anatomic features such as modifications of Vertucci are not evaluated adequately, this study was conducted. Methods and Materials: In this in vivo study, cone-beam computed tomography (CBCT) images of‎ 312‎ intact bilateral first‎ molars‎ from‎ 156‎ patients‎ (‎79‎ ‎males‎ and‎ 77‎ females with an average age of ‎35.58‎±‎11.17‎ years‎)‎ were‎ investigated by a trained dentist in terms of number‎ of‎ roots,‎ number‎ of‎ canals‎ in‎ each‎ root‎ and‎ in‎ ‎each‎ tooth,‎ and shapes‎ of‎ canals‎ according‎ to‎ Vertucci’s‎ classification‎ and‎ its‎ modifications.‎ Groups were compared using the Chi-square test. The level of significance was set at 0.05. Results: Of all teeth, 5.2%‎ had‎ 3‎ roots.‎‎ ‎Mesial‎ roots‎ had‎ mostly‎ 2‎ canals‎ while distal roots had a similar frequency of 1 and 2 canals.‎ ‎Of‎ all‎ teeth,‎ ‎‎39.7%‎ had‎ 3‎ canals,‎ 45.2%‎ had‎ 4‎ canals,‎ 13.8%‎ had‎ 5‎ canals,‎ and‎ 1.3%‎ had‎ 6‎ canals.‎ There were no significant differences between males and females, ‎in terms of number of roots (P=0.137), number of canals in mesial (P=0.453) or distal roots (P‎‎=0.328), and total number of canals (P=0.138).‎ The most frequent Vertucci classes in mesial and distal roots were IV ‎‎followed‎ by‎ II and I‎, respectively. There were no significant differences between males and females in terms of Vertucci classes of mesial (P=0.211) or distal (P=0.205) roots. Conclusion: In this population, there were 3 to 6 canals per tooth (mostly 4 and 3 canals).‎ Males and female’s ‎might be similar regarding the number of roots, or number of canals in each root, number of ‎canals in each tooth, or the predominant canal shape in each root.Keywords: Anatomy;‎ Cone-beam Computed Tomography; Endodontics;‎ Root Anatom

Genomic investigations of unexplained acute hepatitis in children

Since its first identification in Scotland, over 1,000 cases of unexplained paediatric hepatitis in children have been reported worldwide, including 278 cases in the UK1. Here we report an investigation of 38 cases, 66 age-matched immunocompetent controls and 21 immunocompromised comparator participants, using a combination of genomic, transcriptomic, proteomic and immunohistochemical methods. We detected high levels of adeno-associated virus 2 (AAV2) DNA in the liver, blood, plasma or stool from 27 of 28 cases. We found low levels of adenovirus (HAdV) and human herpesvirus 6B (HHV-6B) in 23 of 31 and 16 of 23, respectively, of the cases tested. By contrast, AAV2 was infrequently detected and at low titre in the blood or the liver from control children with HAdV, even when profoundly immunosuppressed. AAV2, HAdV and HHV-6 phylogeny excluded the emergence of novel strains in cases. Histological analyses of explanted livers showed enrichment for T cells and B lineage cells. Proteomic comparison of liver tissue from cases and healthy controls identified increased expression of HLA class 2, immunoglobulin variable regions and complement proteins. HAdV and AAV2 proteins were not detected in the livers. Instead, we identified AAV2 DNA complexes reflecting both HAdV-mediated and HHV-6B-mediated replication. We hypothesize that high levels of abnormal AAV2 replication products aided by HAdV and, in severe cases, HHV-6B may have triggered immune-mediated hepatic disease in genetically and immunologically predisposed children

Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background Detailed, comprehensive, and timely reporting on population health by underlying causes of disability and premature death is crucial to understanding and responding to complex patterns of disease and injury burden over time and across age groups, sexes, and locations. The availability of disease burden estimates can promote evidence-based interventions that enable public health researchers, policy makers, and other professionals to implement strategies that can mitigate diseases. It can also facilitate more rigorous monitoring of progress towards national and international health targets, such as the Sustainable Development Goals. For three decades, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) has filled that need. A global network of collaborators contributed to the production of GBD 2021 by providing, reviewing, and analysing all available data. GBD estimates are updated routinely with additional data and refined analytical methods. GBD 2021 presents, for the first time, estimates of health loss due to the COVID-19 pandemic. Methods The GBD 2021 disease and injury burden analysis estimated years lived with disability (YLDs), years of life lost (YLLs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries using 100 983 data sources. Data were extracted from vital registration systems, verbal autopsies, censuses, household surveys, disease-specific registries, health service contact data, and other sources. YLDs were calculated by multiplying cause-age-sex-location-year-specific prevalence of sequelae by their respective disability weights, for each disease and injury. YLLs were calculated by multiplying cause-age-sex-location-year-specific deaths by the standard life expectancy at the age that death occurred. DALYs were calculated by summing YLDs and YLLs. HALE estimates were produced using YLDs per capita and age-specific mortality rates by location, age, sex, year, and cause. 95% uncertainty intervals (UIs) were generated for all final estimates as the 2·5th and 97·5th percentiles values of 500 draws. Uncertainty was propagated at each step of the estimation process. Counts and age-standardised rates were calculated globally, for seven super-regions, 21 regions, 204 countries and territories (including 21 countries with subnational locations), and 811 subnational locations, from 1990 to 2021. Here we report data for 2010 to 2021 to highlight trends in disease burden over the past decade and through the first 2 years of the COVID-19 pandemic. Findings Global DALYs increased from 2·63 billion (95% UI 2·44–2·85) in 2010 to 2·88 billion (2·64–3·15) in 2021 for all causes combined. Much of this increase in the number of DALYs was due to population growth and ageing, as indicated by a decrease in global age-standardised all-cause DALY rates of 14·2% (95% UI 10·7–17·3) between 2010 and 2019. Notably, however, this decrease in rates reversed during the first 2 years of the COVID-19 pandemic, with increases in global age-standardised all-cause DALY rates since 2019 of 4·1% (1·8–6·3) in 2020 and 7·2% (4·7–10·0) in 2021. In 2021, COVID-19 was the leading cause of DALYs globally (212·0 million [198·0–234·5] DALYs), followed by ischaemic heart disease (188·3 million [176·7–198·3]), neonatal disorders (186·3 million [162·3–214·9]), and stroke (160·4 million [148·0–171·7]). However, notable health gains were seen among other leading communicable, maternal, neonatal, and nutritional (CMNN) diseases. Globally between 2010 and 2021, the age-standardised DALY rates for HIV/AIDS decreased by 47·8% (43·3–51·7) and for diarrhoeal diseases decreased by 47·0% (39·9–52·9). Non-communicable diseases contributed 1·73 billion (95% UI 1·54–1·94) DALYs in 2021, with a decrease in age-standardised DALY rates since 2010 of 6·4% (95% UI 3·5–9·5). Between 2010 and 2021, among the 25 leading Level 3 causes, age-standardised DALY rates increased most substantially for anxiety disorders (16·7% [14·0–19·8]), depressive disorders (16·4% [11·9–21·3]), and diabetes (14·0% [10·0–17·4]). Age-standardised DALY rates due to injuries decreased globally by 24·0% (20·7–27·2) between 2010 and 2021, although improvements were not uniform across locations, ages, and sexes. Globally, HALE at birth improved slightly, from 61·3 years (58·6–63·6) in 2010 to 62·2 years (59·4–64·7) in 2021. However, despite this overall increase, HALE decreased by 2·2% (1·6–2·9) between 2019 and 2021. Interpretation Putting the COVID-19 pandemic in the context of a mutually exclusive and collectively exhaustive list of causes of health loss is crucial to understanding its impact and ensuring that health funding and policy address needs at both local and global levels through cost-effective and evidence-based interventions. A global epidemiological transition remains underway. Our findings suggest that prioritising non-communicable disease prevention and treatment policies, as well as strengthening health systems, continues to be crucially important. The progress on reducing the burden of CMNN diseases must not stall; although global trends are improving, the burden of CMNN diseases remains unacceptably high. Evidence-based interventions will help save the lives of young children and mothers and improve the overall health and economic conditions of societies across the world. Governments and multilateral organisations should prioritise pandemic preparedness planning alongside efforts to reduce the burden of diseases and injuries that will strain resources in the coming decades

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. Methods The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model—a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates—with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality—which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. Findings The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2–100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1–290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1–211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4–48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3–37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7–9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. Interpretation Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

The effect of film and paper on quality of Cone beam CT image and their diagnostic accuracy in detection of inferior alveolar canal

Background and Aims: According to the research background and need to print CBCT images in case of emergency, this study has been done to compare the quality and accuracy of the two methods of film and paper printing for CBCT images. Materials and Methods: The study of CBCT images taken from 5 patients was done and the cross-sectional slices on Fotolusio DNP papers and film AGFA were printed. Afterward, the images was exmined by a maxillofacial radiologist. The images’ quality were identified and recorded with anatomical, from 1 to 4 on forms. The accuracy was determined by the diagnosis of alveolar canal area and the comparison with the gold standard. Data were analyzed using independent chi-square and Fisher exact tests’. Results: The images quality in anatomical landmarks consisting PDL (P=0.02), lamina dura (P=0.006), the inferior alveolar canal (P=0.01) and the filling (P=0.006) had a significant difference. There was no significant difference. For the lower border of the mandible landmark, there was no difference between the two methods of printing. In comparing the diagnostic accuracy between the two methods (P=1). Conclusion: The results showed that the diagnostic quality in film printing is better than paper printing and the diagnostic accuracy is the same in both methods

Comparing the Diagnostic Accuracy of PSP Digital Intraoral Receptor Software Options in Assessment of Vertical Fractures of Mandibular Posterior Teeth: The Effects of Digital Image Processing Options on Detection of Vertical Root Fracture

Objectives Root fracture detection may be a challenging process due to difficulties in clinical and radiographic assessments. This study compared the diagnostic efficacy of Photostimulable Phosphor (PSP) intraoral digital receptor software alternatives for detection of vertical fractures in mandibular posterior teeth. Methods In this diagnostic research, 60 human mandibular posterior teeth were chosen. Vertical fracture was induced on half of teeth using a hammer through a random method. Thereafter, the broken pieces were glued together using a superglue, and placed inside a sheep mandible. Next, utilizing a digital intraoral technique and a PSP sensor, radiographic images of every tooth were taken. All radiographies  were then subjected to computer adjustments such as sharpening, reverse-contrast, and enhancement. Three radiologists investigated the images of teeth after application of computer adjustments regarding existence of fracture. SPSS 22 was used for data analysis. Results Among processed images, sharpness had the highest accuracy (89.3%) followed by enhancement (89%), and reverse-contrast (87%). Statistically, no significant difference was observed in diagnosis of vertical fractures of mandibular posterior teeth regarding sensitivity, specificity, accuracy, as well as positive and negative predictive value among main images (no effect) and the images on which sharpness, reverse-contrast, and enhancement by software were applied (P-value>0.05). For intra-observer agreement, Kappa value > 0.70 and for inter-observer agreement, kappa value=0.50-0.7 were found. Conclusion Usage of sharpness, reverse-contrast, and enhancement software had no significant impact in diagnosing vertical root fracture of multi-rooted teeth (P-value>0.05).

Modified Newman and Friedman Extraoral Radiographic Technique

Introduction: Good radiographs are required for endodontic therapy and because some patient’s are intolerant to intraoral films and/or sensors, this can cause complications in endodontic treatment. Extraoral film placement can be used to obtain clinically diagnostic and working radiographs. Materials and Methods: The no. 2 receptor was placed against the model’s cheek and centered in the molar-premolar area. The central beam was directed toward this area from the opposite side. The vertical and horizontal angles that achieved the most accurate radiograph were calculated by trial and error. Results: The best method equated with the patient sitting upright and the Frankfort plane being horizontal to the floor and when the head was tilted 10 degrees toward the side being examined. For the upper posterior teeth the center of the image receptor was placed on the intersection of the ala-tragus and a parasagittal line while the upper border of receptor was parallel to the canthomeatal line; the cone was positioned a negative 25 degrees from the horizontal plane. The central beam was directed from midway between maxillary and mandibular premolars and molars of the opposite side. For the lower posterior teeth, the receptor was placed against the cheek on the side of interest and its lower border was parallel and 2 cm above the inferior border of the mandible. The cone was angled -20 degrees from the horizontal plane while the central beam was directed towards the mandibular molar-premolar region 1 cm below the lower border of the mandibular of the contralateral premolar/molar region. Conclusion: Using this novel technique, high quality images can be acquired for patients who cannot tolerate intraoral radiographs

The effects of anatomical location and distance from dental implants on the quality and quantity of metal artifacts in cone beam computed tomography scans: a cross-sectional study

Abstract Background Artifacts in cone beam computed tomography (CBCT) images can cause disruptions in diagnosis and treatment. Multiple factors influence the artifacts, including the quality and technology of devices, positions, patient-related factors, device settings, and bone density. Besides, anatomical area and distance from the implant affect the artifacts. This study aimed to investigate the effects of anatomical location and distance from the implant on the quality and quantity of artifacts. Methods A total of 200 CBCT images of patients with titanium implants and prostheses in the anterior and posterior regions of the maxilla and mandible were evaluated in this study. Four areas were assessed for each implant in three apical, middle, and cervical regions with distances of 3 mm, 4 mm, and 5 mm from the implant. Besides, the impact of adjacent implants on the artifacts was investigated. An ANOVA test with post hoc Bonferroni correction was used to analyze variable differences between subgroups. Results The differences were statistically significant, except for the difference between the posterior areas of the upper and lower jaws. A comparison of different areas revealed that most artifacts were related to the anterior maxilla, followed by anterior mandibular regions. The results of covariance analysis indicated that region and location had independent effects on the amount of artifacts. Conclusions Artifacts are more frequent in the anterior region compared to the posterior site. They are also more frequent in the maxilla than the mandible and cervical areas close to the implant than the middle and apical regions