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Cone‐beam computed tomography (CBCT) imaging of the maxillary sinus is indispensable for implantologists, offering three‐dimensional anatomical visualization, morphological variation detection, and abnormality identification, all critical for diagnostics and treatment planning in digital implant workflows. The following systematic review presented the current evidence pertaining to the use of artificial intelligence (AI) for CBCT‐derived maxillary sinus imaging tasks. An electronic search was conducted on PubMed, Web of Science, and Cochrane up until January 2024. Based on the eligibility criteria, 14 articles were included that reported on the use of AI for the automation of CBCT‐derived maxillary sinus assessment tasks. The QUADAS‐2 (Quality Assessment of Diagnostic Accuracy Studies 2) tool was used to evaluate the risk of bias and applicability concerns. The AI models used were designed to automate tasks such as segmentation, classification, and prediction. Most studies related to automated maxillary sinus segmentation demonstrated high performance. In terms of classification tasks, the highest accuracy was observed for diagnosing sinusitis (99.7%), whereas the lowest accuracy was detected for classifying abnormalities such as fungal balls and chronic rhinosinusitis (83.0%). Regarding implant treatment planning, the classification of automated surgical plans for maxillary sinus floor augmentation based on residual bone height showed high accuracy (97%). Additionally, AI demonstrated high performance in predicting gender and sinus volume. In conclusion, although AI shows promising potential in automating maxillary sinus imaging tasks which could be useful for diagnostic and planning tasks in implantology, there is a need for more diverse datasets to improve the generalizability and clinical relevance of AI models. Future studies are suggested to focus on expanding the datasets, making the AI model's source available, and adhering to standardized AI reporting guidelines. [ABSTRACT FROM AUTHOR]

This study investigated retreatment of oval canals filled with gutta-percha and different sealers using WaveOne Gold (WOG). Single oval canals were prepared to size 30, 0.04 and obturated with gutta percha and AH Plus (AHP) or TotalFill bioceramic (TFBC) sealer. After 6-month incubation, the canals were retreated with WOG Primary (25, 0.07) under simulated body temperature, and the developed load and torque were simultaneously measured. The time and regaining the apical patency were checked. Micro-computed tomography scanning was performed to calculate the remaining obturating materials. An independent t-test and chi-square test were performed at a 95% confidence level. A shorter retreatment time was needed in TFBC than in AHP (P = 0.003). However, a higher maximum apical load was reported with AHP (P = 0.000). Meanwhile, comparable maximum coronal load and maximum torque values were observed. Apical patency was regained in all TFBC roots and only 75% of the AHP samples (P = 0.217). The remaining obturating materials were comparable in TFBC (13.02 ± 8.12%) and AHP (10.11 ± 8.46%) (P = 0.398). WOG was able to remove 89.89% and 86.98% of obturating materials in TFBC and AHP, respectively. The TFBC presented lower apical loads and faster retreatment compared to AHP. [ABSTRACT FROM AUTHOR]

Purpose: To investigate, in vitro, the magnitudes of vertical load and torque generated during post space preparation of root canal treated teeth and their influence on microcrack development. Materials and Methods: Forty extracted premolars with single canals were decoronated. The roots were prepared using ProTaper Next system (Dentsply Sirona) to X3 file, obturated, and provisionalized. After a 3‐week incubation period, the roots were distributed into 2 groups according to the post drill system used (ParaPost fiber post and RelyX fiber post). During post space preparation, the vertical load, torque, and preparation time were recorded. Before and after the post space preparation, the roots were imaged with micro‐computed tomography (SkyScan 1172; Bruker micro‐CT) to detect new microcracks. The data were analyzed using the Mann‐Whitney U‐test and chi‐square test. Results: In ParaPost and RelyX, the post space was prepared in 48.31 ±25.28 and 47.71 ±13.36 seconds, respectively (p = 0.360). The peak vertical load generated with ParaPost (20.23 ±7.80 N) was significantly lower than that of RelyX (29.43 ±5.82 N) (p = 0.010). The maximum torque attained with ParaPost (1.42 ±0.61 N.cm) was found to be significantly lower than that of RelyX (3.23 ±1.58 N.cm) (p = 0.000). No post drill fracture or visible deformation was noticed throughout the experiment. New microcracks were found in three ParaPost samples only. Conclusions: The choice of postdrill influenced the loads and torques generated during postspace preparation. The ParaPost system showed favorably lower load and torque values during the postspace preparation compared with the RelyX system. [ABSTRACT FROM AUTHOR]