Aims:The aim of this cross-sectional study was to determine the prevalence of periradicular radiolucencies (PR) from an urban adult Indian population and to investigate the quality of root canal procedures and coronal restorations and their association with prevalence of PR in root-filled teeth.Settings and Design:Cross-sectional study.Material and Methods:A total of 1,340 subjects (18+ years of age) who reported for non-emergency dental care to 5 different dental care centers had their panoramic radiographs taken during the period from January to December 2013. The periradicular status of 30,098 teeth in these radiographs was evaluated using the Periapical Index Score (PAI). The assessment of the technical quality of the procedure was evaluated based on the criteria of root canal filling length and quality of coronal restoration.Statistical Analysis Used:The data was analyzed statistically by chi-squared test and odds ratio.Results:PR was found in 65% of subjects (n = 865) and 5.8% (n = 1,759) of the 30,098 teeth evaluated (4.30% untreated teeth and 1.53% were root-filled teeth). In all, 4.1% of the teeth (n = 1,234) had some filling material in the root canal(s) and the prevalence of PR in these root-filled teeth was 37.4%, while the remaining 62.6% of root canal-filled teeth showed no evidence of PR. PR occurred significantly more often in teeth where root canal filling was filled more than 2 mm short of radiographic apex or when root filling extruded through the apex.Conclusions:The prevalence of PR in teeth with untreated root canals in India is 4.30%, which is more than twice the weighted world average, while the prevalence of root-filled teeth (4.1%) is lower than the world average (9.6%). The prevalence of PR in root-filled teeth in India is comparable to that in other populations. Inadequate root canal treatment and poor quality of coronal restoration were associated with increased prevalence of PR.

Aim. This comprehensive review is aimed at evaluating the diagnostic and prognostic accuracy of artificial intelligence in endodontic dentistry. Introduction. Artificial intelligence (AI) is a relatively new technology that has widespread use in dentistry. The AI technologies have primarily been used in dentistry to diagnose dental diseases, plan treatment, make clinical decisions, and predict the prognosis. AI models like convolutional neural networks (CNN) and artificial neural networks (ANN) have been used in endodontics to study root canal system anatomy, determine working length measurements, detect periapical lesions and root fractures, predict the success of retreatment procedures, and predict the viability of dental pulp stem cells. Methodology. The literature was searched in electronic databases such as Google Scholar, Medline, PubMed, Embase, Web of Science, and Scopus, published over the last four decades (January 1980 to September 15, 2021) by using keywords such as artificial intelligence, machine learning, deep learning, application, endodontics, and dentistry. Results. The preliminary search yielded 2560 articles relevant enough to the paper’s purpose. A total of 88 articles met the eligibility criteria. The majority of research on AI application in endodontics has concentrated on tracing apical foramen, verifying the working length, projection of periapical pathologies, root morphologies, and retreatment predictions and discovering the vertical root fractures. Conclusion. In endodontics, AI displayed accuracy in terms of diagnostic and prognostic evaluations. The use of AI can help enhance the treatment plan, which in turn can lead to an increase in the success rate of endodontic treatment outcomes. The AI is used extensively in endodontics and could help in clinical applications, such as detecting root fractures, periapical pathologies, determining working length, tracing apical foramen, the morphology of root, and disease prediction.

The objective of this prospective study was to assess tooth-related factors that play a role in the incidence of postoperative pain (PP) and determining if procedural errors influence PP occurrence. A total of 442 patients referred for root canal treatment met the inclusion criteria and were included in this prospective study. The same protocol was used in all root canal treatments. Patient, tooth, treatment related factors and the occurrence of procedural errors were registered. Incidence and intensity of PP was assessed at 24 and 48 h by telephonic interview and in person seven and 15 days after treatment. A logistic and ordinal regression analysis was used to assess the role of patient, tooth and treatment related factors in the incidence and intensity of PP, respectively. Preoperative and intraoperative factors differently affected the incidence of PP at the different time intervals. The presence of procedural errors did not significantly influence PP occurrence. The presence of preoperative pain and the need of additional anesthesia during treatment were associated with higher incidence of PP 24 and 48 h after treatment; the extent of apical enlargement played a significant role in the presence of PP after seven days of treatment; and the excessive occlusal load induced by the absence of a contralateral tooth was the only factor related to the maintenance of PP up to 15 days. In conclusion, the presence of preoperative pain, the need of additional anesthesia during treatment, the extent of apical enlargement and the excessive occlusal load induced by the absence of a contralateral tooth were related to a higher incidence of PP.

Key Clinical MessageMatrix technique described in this article combines the advantages of both flexible and rigid matrix in anterior composite restorations. Using mylar strip provide advantages, of one utilizing the mylar strip for contouring the labial aspect of restoration thereby, and overcomes the problem in adapting the teflon tape around the tooth.