The advent of artificial intelligence (AI) in medicine has transformed various medical specialties, including orthodontics. AI has shown promising results in enhancing the accuracy of diagnoses, treatment planning, and predicting treatment outcomes. Its usage in orthodontic practices worldwide has increased with the availability of various AI applications and tools. This review explores the principles of AI, its applications in orthodontics, and its implementation in clinical practice. A comprehensive literature review was conducted, focusing on AI applications in dental diagnostics, cephalometric evaluation, skeletal age determination, temporomandibular joint (TMJ) evaluation, decision making, and patient telemonitoring. Due to study heterogeneity, no meta-analysis was possible. AI has demonstrated high efficacy in all these areas, but variations in performance and the need for manual supervision suggest caution in clinical settings. The complexity and unpredictability of AI algorithms call for cautious implementation and regular manual validation. Continuous AI learning, proper governance, and addressing privacy and ethical concerns are crucial for successful integration into orthodontic practice.

After orthodontic treatment, brackets are debonded and residual adhesive is removed, causing iatrogenic enamel damage. The aim of this study was to review the methods of orthodontic adhesive removal, find clear evidence, and provide a rationale for this procedure. A literature search was performed in PubMed, Dentistry and Oral Sciences, Scopus, Cochrane, Google, and Google Scholar using keywords: orthodontic adhesive removal, orthodontic debonding, orthodontic clean-up. Studies concerning human enamel roughness or loss from debonding and adhesive removal were considered. Forty-four full-text articles were analyzed and 3 were rejected after detailed reading; finally 41 papers were included. Fifteen qualitative studies, 13 studies based on indices of enamel surface, and 13 quantitative studies were found. No meta-analysis could be performed due to a lack of homogenous quantitative evidence. The most popular tools were tungsten carbide burs, which were faster and more effective than Sof-Lex discs, ultrasonic tools, hand instruments, rubbers, or composite burs. They remove a substantial layer of enamel and roughen its surface, but are less destructive than Arkansas stones, green stones, diamond burs, steel burs, and lasers. Multi-step Sof-Lex discs and pumice slurry are the most predictable enamel polishing tools. Arkansas stones, green stones, diamond burs, steel burs, and lasers should not be used for adhesive removal. The use of tungsten carbide bur requires multistep polishing. Further efforts should be made to find tools and methods for complete removal of adhesive remnants, minimizing enamel loss and achieving a smooth surface.

Background: In recent years the burden of aligner treatment has been growing. However, the sole use of aligners is characterized by limitations; thus attachments are bonded to the teeth to improve aligner retention and tooth movement. Nevertheless, it is often still a challenge to clinically achieve the planned movement. Thus, the aim of this study is to discuss the evidence of the shape, placement and bonding of composite attachments. Methods: A query was carried out in six databases on 10 December 2022 using the search string (“orthodontics” OR “malocclusion” OR “Tooth movement techniques AND (“aligner*” OR “thermoformed splints” OR “invisible splint*” AND (“attachment*” OR “accessor*” OR “auxill*” AND “position*”). Results: There were 209 potential articles identified. Finally, twenty-six articles were included. Four referred to attachment bonding, and twenty-two comprised the influence of composite attachment on movement efficacy. Quality assessment tools were used according to the study type. Conclusions: The use of attachments significantly improves the expression of orthodontic movement and aligner retention. It is possible to indicate sites on the teeth where attachments have a better effect on tooth movement and to assess which attachments facilitate movement. The research received no external funding. The PROSPERO database number is CRD42022383276.

Background/Objectives: Periapical lesions (PLs) are frequently detected in dental radiology. Accurate diagnosis of these lesions is essential for proper treatment planning. Imaging techniques such as orthopantomogram (OPG) and cone-beam CT (CBCT) imaging are used to identify PLs. The aim of this study was to assess the diagnostic accuracy of artificial intelligence (AI) software Diagnocat for PL detection in OPG and CBCT images. Methods: The study included 49 patients, totaling 1223 teeth. Both OPG and CBCT images were analyzed by AI software and by three experienced clinicians. All the images were obtained in one patient cohort, and findings were compared to the consensus of human readers using CBCT. The AI’s diagnostic accuracy was compared to a reference method, calculating sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV), and F1 score. Results: The AI’s sensitivity for OPG images was 33.33% with an F1 score of 32.73%. For CBCT images, the AI’s sensitivity was 77.78% with an F1 score of 84.00%. The AI’s specificity was over 98% for both OPG and CBCT images. Conclusions: The AI demonstrated high sensitivity and high specificity in detecting PLs in CBCT images but lower sensitivity in OPG images.

Background: Orthodontic retention aims to maintain optimal teeth positions after active treatment. The stability is affected by numerous factors, including patients’ individual features, thus retention should be adjusted in the most optimal way. Bonding a retainer makes retention less dependent on patient’s compliance. Questions arise: What wire or fiber splint type provides the best treatment stability? What materials should be used to bond the wire or fiber splint? Should be the bonding procedure be direct or indirect? The aim of the study is to assess and synthesize available controlled trials investigating failures of fixed retainers. Methods: Literature searches of free text and MeSH terms were performed in Scopus, Web of Science, Embase and PubMed Central in order to find studies, referring to failures of fixed retention (12th February 2021). The keywords were: (“orthodontic retainers AND failure AND wire”). The framework of this systematic review according to PICO was: Population: orthodontic patients; Intervention: fixed orthodontic retainer bonding; Comparison: Different protocols of fixed orthodontic retention applied; Outcomes: failure rate, survival rate. Three different specific scales from the Cochrane Collaboration Handbook were used, according to each study type. Additionally, a meta-analysis was conducted to compare the effectiveness of retention using fiber reinforced composite and multistranded steel wire. Results: The search identified 177 potential articles: 114 from PubMed, 41 from Scopus, 20 from Web of Science and 2 from Embase. After excluding studies inconsistent with selection criteria, 21 studies were included and subjected to qualitative analysis. The main outcome investigated was failure rate. This systematic review has some potential limitations due to the heterogeneity of design between included studies. Conclusions: No retainer is proved to guarantee a perfect stability of dental alignment. The retainer should be bonded to all adherent teeth, preferably with additional use of bonding resin. No wire or fiber splint present superior characteristics concerning failure rate. Fiber reinforced composite retention is more sensitive to operator skills, and with imperfect bonding technique, failure rate is much higher. During the first 6 months after bonding retainer the patient should be under frequent control. The study protocol was registered in PROSPERO database with the number CRD42021233406.