The Efficacy of Metal Artifact Reduction Mode in Cone-Beam Computed Tomography Images on Diagnostic Accuracy of Root Fractures in Teeth with Intracanal Posts

Introduction: The purpose of this study was to evaluate the efficacy of cone-beam computed tomography CBCT in the diagnosis of RF in the presence of an intracanal posts with and without applying “metal artifact reduction” (MAR) mode. Methods and Materials: This in vitro study included 60 single-canal endodontically treated premolars. Post spaces were created in all roots. RFs were simulated in 30 of the 60 teeth. Dentatus posts were cemented in 15 of 30 roots with and without RFs. Teeth were arranged randomly in 6 artificial dental arches. Images were taken using a Vatech CBCT machine with and without MAR (MAR and WMAR, respectively). A radiologist and an endodontist evaluated the CBCT images for the presence of RFs. Sensitivity, Specificity, positive and negative predictive values were determined for each mode. MC Nemar’s and Kappa tests were used for data analysis. Results: The percentage of correct diagnosis using the WMAR mode in both the post space and pin groups in the presence of root fracture was 46.6%; with MAR, it increased to 86.6% and 66.6%, respectively. There was no significant difference between two modes in post space (P=0.503) and metal pin groups (0.549). The overall sensitivity of VRF diagnosis in WMAR mode was 46.67%; in MAR mode, sensitivity was 76.67%. The specificity of WMAR and MAR modes were 60% and 53.33%. The levels of agreement between two modes and real findings were less than 0.45. Conclusions: There were no significant differences between the efficacies of imaging modes. The sensitivity of the MAR mode for diagnosis of VRF in both the pin and post space groups was higher than the WMAR mode. The specificity of MAR in comparison with WMAR was less or equal in dental groups. The agreement between CBCT and real findings was poor.Keywords: Artifact; Cone-Beam Computed Tomography; Diagnosis; Tooth Fracture; Vertical Root Fractur

Accuracy of Cone-beam Computed Tomography in Comparing with Clearing and Staining Method in Evaluating the Root Canal Morphology: An In Vitro Study

Introduction: In order to successfully perform root canal treatment, thorough knowledge of the root canal anatomy is essential. Cone-beam computed tomography (CBCT) has the ability to improve our understanding of the root canal system. The goal of the present study was to compare the accuracy of CBCT in revealing the number and form of the root canals of different maxillary and mandibular teeth with clearing and staining method. Methods and Materials: CBCT images were taken from 80 extracted human teeth fixed in agar arch models. The number and configuration of the root canals of each tooth were determined by the two observers. Then the teeth were cleared and stained. Two endodontists evaluated the number and forms of the root canals. The accuracy of CBCT was determined and compared with clearing and staining by Fisher’s exact test. The agreement of two methods in detection of the number and form of the root canals were evaluated by Kappa test, P≤0.05. Results: CBCT accurately detected the number of root canals in 129 (92.1%) of 140 roots and the form of the canals in 119 (85%) of the roots. There was no significant difference between the accuracy of CBCT in the detection of the number (P=0.13) and forms (P=0.4) of root canals of maxillary and mandibular teeth. The agreement between CBCT, and tooth clearing and staining in detection of the number of root canals was excellent in the maxilla (kappa=0.88±0.05) and good in the mandible (kappa=0.720±0.097). The agreement between the two methods in demonstration of the form of root canals was good in both maxillary (kappa=0.73±0.07) and mandibular (kappa=0.67±0.09) teeth. Conclusion: CBCT provides accurate information about root canal morphology. Application of this technique could result in more successful endodontic treatments.Keywords: Anatomy; Cone-beam Computed Tomography; Root Canal

Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

BackgroundFuture trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050.MethodsUsing forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline.FindingsIn the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8–63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0–45·0] in 2050) and south Asia (31·7% [29·2–34·1] to 15·5% [13·7–17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4–40·3) to 41·1% (33·9–48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6–25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5–43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5–17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7–11·3) in the high-income super-region to 23·9% (20·7–27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5–6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2–26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [–0·6 to 3·6]).InterpretationGlobally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions.FundingBill & Melinda Gates Foundation.</p