Biomechanical analysis of miniscrew-assisted molar distalization with clear aligners: a three-dimensional finite element study.

BACKGROUND/OBJECTIVES: To compare the biomechanical characteristics of maxillary molar distalization with clear aligners in conjunction with three types of miniscrew anchorage. MATERIALS/METHODS: Three-dimensional (3D) finite element models of maxillary molar distalization with clear aligners and three types of miniscrew anchorage were established, including (A) control group, (B) direct buccal miniscrew anchorage group, (C) direct palatal miniscrew anchorage group, and (D) indirect buccal miniscrew anchorage group. The 3D displacement of maxillary teeth and the principal stress (maximum tensile and compressive stress) on the root and periodontal ligament (PDL) during molar distalization were recorded. RESULTS: The tooth displacement pattern during maxillary molar distalization in the four groups showed similarities, including labial tipping of anterior teeth, mesial and buccal tipping of premolars, and distal and buccal tipping of molars, but with varying magnitudes. Group C exhibited the greatest molar distalization, with the first molar achieving 0.1334 mm of crown distalization. Group D demonstrated a notable buccal crown movement (0.0682 mm) and intrusion (0.0316 mm) of the first premolar. Compared to Groups A and B, Groups C and D showed less labial crown tipping of the central incisor. Group B showed the greatest amount of maxillary incisor intrusion (central incisor: 0.0145 mm, lateral incisor: 0.0094 mm). Moreover, Groups C and D displayed significantly lower levels of compressive and tensile stress in the roots and PDL of the maxillary central and lateral incisors. LIMITATION: Molar distalization is a dynamic process involving sequential tooth movement stages; however, our research primarily examined the tooth movement patterns in the initial aligner. CONCLUSIONS/IMPLICATIONS: The use of miniscrew anchorage, especially direct palatal miniscrew anchorage, may enhance the treatment efficacy of maxillary molar distalization with clear aligners, leading to increased molar distalization, reduced mesial movement of premolars, and minimized labial tipping of anterior teeth.

The 100 Most-Cited Randomised Controlled Trials in Orthodontics: A Bibliometric Study.

INTRODUCTION AND AIM: Randomised controlled trials (RCTs) are recognised as the highest level of original evidence and provide essential evidence for dentists to practice evidence-based dentistry. By analysing the top 100 most-cited RCT reports in orthodontics, this study aimed to determine popular research topics, key authors, countries, journals, and their impacts. METHODS: A comprehensive search was performed in the Web of Science (WoS) electronic database to identify the top 100 most-cited RCT reports in orthodontics. Publication and citation data were retrieved and further analysed and visualised using R Biblioshiny. The primary themes of the 100 articles were also determined. Additionally, the correlation between number of years since publication and citation counts was examined. RESULTS: The top 100 most-cited RCT reports were published between 1992 and 2018, contributed by 419 authors across 22 journals, with an average citation count of 93.48. The US led with the highest number of publications (28) and citations (2552), followed by the UK (22 and 2061) and Australia (8 and 912). Notably, 20 of the top 24 authors with at least 4 publications are from the UK. The primary focus areas of the articles included early Class II treatment (n = 14), obstructive sleep apnoea (n = 14), demineralisation (n = 12), and pain and quality of life (n = 12). Besides, a positive correlation was found between the number of years since publication and citation counts (P < .001). CONCLUSIONS: The top 100 most-cited RCT reports in orthodontics encompass a wide range of topics with varying focus areas across different time periods. This analysis recognises the contributions of scholars and offers valuable insights into the research trends within the field of orthodontics.

Artificial intelligence in orthodontics and orthognathic surgery: a bibliometric analysis of the 100 most-cited articles.

BACKGROUND: The application of artificial intelligence (AI) in orthodontics and orthognathic surgery has gained significant attention in recent years. However, there is a lack of bibliometric reports that analyze the academic literature in this field to identify publishing and citation trends. By conducting an analysis of the top 100 most-cited articles on AI in orthodontics and orthognathic surgery, we aim to unveil popular research topics, key authors, institutions, countries, and journals in this area. METHODS: A comprehensive search was conducted in the Web of Science (WOS) electronic database to identify the top 100 most-cited articles on AI in orthodontics and orthognathic surgery. Publication and citation data were obtained and further analyzed and visualized using R Biblioshiny. The key domains of the 100 articles were also identified. RESULTS: The top 100 most-cited articles were published between 2005 and 2022, contributed by 458 authors, with an average citation count of 22.09. South Korea emerged as the leading contributor with the highest number of publications (28) and citations (595), followed by China (16, 373), and the United States (7, 248). Notably, six South Korean authors ranked among the top 10 contributors, and three South Korean institutions were listed as the most productive. International collaborations were predominantly observed between the United States, China, and South Korea. The main domains of the articles focused on automated imaging assessment (42%), aiding diagnosis and treatment planning (34%), and the assessment of growth and development (10%). Besides, a positive correlation was observed between the testing sample size and citation counts (P = 0.010), as well as between the time of publication and citation counts (P < 0.001). CONCLUSIONS: The utilization of AI in orthodontics and orthognathic surgery has shown remarkable progress, particularly in the domains of imaging analysis, diagnosis and treatment planning, and growth and development assessment. This bibliometric analysis provides valuable insights into the top-cited articles and the trends of AI research in this field.