Background and Objectives: The widespread use of tobacco has evolved with the popularity of vapes, especially among young people, despite the lack of clarity in warnings about their risks. Studies indicate the need for more effective communication about the oral risks of vaping. In addition to systemic, respiratory, and cardiovascular effects, vaping is associated with an increased risk of gingivitis and periodontal disease as well as reduced antioxidant capacity of saliva. The objectives of this narrative review are to summarize the existing information in the literature on the effects of vaping at the oral level and to bring together knowledge about the mechanism of action of vaping in oral tissues. Materials and Methods: In the present study, articles were searched in PubMed, Elsevier Scopus, and Web of Science using the keywords “oral health”, “vaping”, and “vape”. Studies published in the last 6 years that addressed the effects of oral vaping were selected, including comparisons among vape users, smokers, and non-smokers. Repeated articles, prior to 2017 and in languages other than English, were excluded. Two review authors (A.M.I and M.F.E.M) independently selected the papers based on titles and abstracts and conducted a full review of the remaining papers. In cases of disagreement, a third reviewer was used. Results: A total of 113 results were obtained, distributed as 16 from PubMed, 35 from Web of Science, and 62 from Elsevier Scopus. After removing duplicates, 67 articles were filtered by reviewing titles and abstracts, and finally, 22 articles were selected for comprehensive reading. Subsequently, eight of these articles were chosen for qualitative synthesis and are presented in standardized tables. The sample size of all included studies was composed of 31,647 participants, (14,477 male and 17,170 female) with a mean of 35.016 ± 7.57 years of age. Conclusions: This review indicates that the use of vapes is associated with an increased risk of periodontitis and caries. Although users experience more oral problems than non-smokers, these are less severe than those of traditional smokers. The widespread prevalence, especially among young people, highlights the urgency of awareness campaigns to warn of risks and understand potential harm.

Artificial intelligence is an emerging tool that is being used in multiple fields, including dentistry. An example of this is the diagnosis of periodontal bone loss by analyzing two-dimensional (2D) radiographs (periapical, bitewing, and panoramic). Objectives: The objectives of this systematic review are to bring together the existing evidence and evaluate the effectiveness of the different artificial intelligence architectures that have been used in recent studies. Materials and Methods: This work has been carried out following the PRISMA criteria and has been recorded in PROSPERO (ID = CRD 42025640049). We searched six different databases, and the results were filtered according to previously established inclusion and exclusion criteria. We extracted data independently by three review authors and analyzed the risk of bias of the studies using the QUADAS-2 test, calculating Cohen’s kappa index (κ) to measure the agreement between assessors. Results: We included 20 diagnostic accuracy studies according to the inclusion and exclusion criteria, published between 2019 and 2024. All included studies described the detection of periodontal bone loss on radiographs. Limitations: One of the main limitations identified was heterogeneity in the indices used to assess the accuracy of models, which made it difficult to compare results between studies. In addition, many works use different imaging protocols and X-ray equipment, introducing variability into the data and limiting reproducibility. Conclusions: Artificial intelligence is a promising technique for the automated detection of periodontal bone loss, allowing the accurate measurement of bone loss, identifying lesions such as apical periodontitis and stage periodontitis, in addition to reducing diagnostic errors associated with fatigue or inexperience. However, improvements are still required to optimize its accuracy and clinical applicability.

The automated segmentation of maxillary and mandibular bones in cone-beam computed tomography (CBCT) using artificial intelligence (AI) is redefining the standards of digital dentistry and orthodontics, with applications in mini-implant placement, dental implantology, orthognathic surgery, and bone graft planning. To systematically assess the performance of AI models - particularly U-Net-based convolutional neural networks (CNNs) - for automated segmentation of maxillary bone structures in CBCT, following the PICOS model (Population - CBCT scans of human maxillae; Intervention - AI-based segmentation; Comparator - manual segmentation; Outcome - accuracy; Study design - diagnostic accuracy studies). This systematic review adhered to PRISMA 2020 guidelines and was registered in PROSPERO (CRD42024592182). Eligibility criteria included studies applying AI to maxillary bone segmentation in CBCT and reporting quantitative accuracy metrics. Risk of bias was evaluated using the QUADAS-2 tool. The GRADE tool for formulating and grading recommendations in clinical practice was also employed. Data collected comprised number of CBCT scans, AI model architecture, evaluation metrics, and reported clinical applications. Thirty-one studies, analysing 11,432 CBCT scans, met the inclusion criteria. AI models consistently achieved high segmentation accuracy, with Dice similarity coefficients frequently exceeding 0.98, while substantially reducing processing time compared to manual segmentation. Applications ranged from implant planning and orthognathic surgery to digital orthodontics. Persistent challenges included anatomical variability, imaging artifacts, and the limited availability of high-quality annotated datasets. AI-based segmentation of maxillary and mandibular bones in CBCT demonstrates promising accuracy and efficiency compared with manual techniques. Nevertheless, the certainty of evidence is limited by retrospective designs and small, heterogeneous samples. Large-scale, prospective multicentre studies with standardized evaluation are needed before these methods can be reliably adopted in routine clinical practice.

Background: The primary aim of this study was to evaluate, using conventional radiographic imaging, the height, angulation, and mesiodistal position of impacted maxillary canines to determine if these variables are significantly associated with the palatal or buccal positioning of the tooth. Methods: A retrospective analysis was conducted on all patients diagnosed and treated for at least one impacted maxillary canine over a 4-year period in the Principality of Asturias. The final sample included 159 impacted canines. The variables analyzed were age, gender, associated pathology, location, angulation, height, mesiodistal position, buccopalatal position, and treatment method. Follow-up periods ranged from 12 to 50 months. Results: The mean age of the patients was 21 years (range 10–41 years), with most cases occurring in patients aged 14 to 30 years. Females accounted for 66.1% of the sample, with a female-to-male ratio of 1.95:1. The type of treatment (extraction/traction, surgical–orthodontic approach) was significantly associated with patient age. Additionally, the proximity of the impacted canine crown to the palatal or buccal cortices was significantly related to the treatment choice. However, no significant relationship was observed between the palatal/buccal position of the canine crown and its height or angulation. Conclusions: In the present work, the upper canines included by the palatal did not have a greater height or angulation than the canines included by the vestibule.

This systematic review aimed to assess whether the initial apical position of impacted maxillary canines, evaluated using cone-beam computed tomography [CBCT], influences three-dimensional root displacement during orthodontic traction. An extensive literature search was conducted in PubMed/MEDLINE, Web of Science, Embase, Scopus, and the Cochrane Library up to November 2025. Prospective and retrospective clinical studies including pre-treatment CBCT assessment and reporting either direct apical displacement or CBCT-derived three-dimensional position parameters were considered eligible. Study selection, data extraction, and quality appraisal were carried out independently by two reviewers. Seven studies met the inclusion criteria. Substantial heterogeneity was observed in imaging protocols, reference systems, traction mechanics, and outcome measures, precluding quantitative synthesis. Only two studies directly quantified three-dimensional apical displacement using CBCT–CBCT or CBCT–STL superimposition methods, predominantly suggesting bodily movement patterns; although, this is based on limited direct evidence, with velocities ranging from 0.29 to 0.84 mm/month. The remaining studies provided indirect evidence based on angular changes, positional parameters, or traction duration. Taken together, the available evidence suggests that unfavorable initial apical positions, including palatal or bicortical impactions and increased root angulation, may be associated with greater biomechanical complexity and longer traction duration. Although CBCT-based three-dimensional evaluation provides clinically relevant diagnostic information, standardized measurement protocols are required to improve comparability and reproducibility across studies.

Background/Objectives: Transverse maxillary deficiency in growing patients can be treated using rapid maxillary expansion (RME) or slow maxillary expansion (SME) with spring-based appliances, such as the Leaf Expander (LE), but their comparative dentoskeletal effects remain debated. This study evaluated the transverse dentoskeletal outcomes of LE-based SME versus conventional RME. Methods: A systematic review was conducted in accordance with PRISMA 2020 guidelines and registered in PROSPERO. Electronic searches were performed in PubMed, Scopus, Embase, Web of Science, and Cochrane Library up to 9 January 2026. Randomized controlled trials (RCTs) comparing LE-based SME and RME in skeletally immature patients were included. Primary outcomes were transverse maxillary change; secondary outcomes included dentoalveolar side effects. Risk of bias was assessed using the RoB 2 tool, and certainty of evidence was evaluated using the GRADE framework. When possible, a meta-analysis was performed using standardized mean differences and a random-effects model. Results: Four RCTs met the inclusion criteria. Both SME and RME achieved significant transverse expansion. Meta-analysis showed no statistically significant differences between protocols for inter-canine distance, inter-second deciduous molar distance, inter-first permanent molar distance, or basal maxillary width. Intergroup differences varied by anatomical site and measurement method: RME showed greater anterior dental and skeletal transverse gains, whereas SME achieved comparable intermolar expansion with greater molar distorotation. Three-dimensional analyses indicated similar morphological enlargement. Risk of bias ranged from low to high; the certainty of evidence was low to very low for most transverse parameters and moderate only for molar distorotation. Conclusions: Both LE-based SME and RME effectively correct transverse maxillary deficiency. Quantitative synthesis showed comparable overall transverse expansion, with differences mainly related to the distribution and biomechanical pattern of dentoskeletal effects rather than the absolute amount of expansion achieved. Appliance selection should be guided by biomechanical features and individual treatment objectives. Further high-quality RCTs with standardized three-dimensional protocols and longer follow-up are needed.