This literature research had two main objectives. The first objective was to quantify how frequently artificial intelligence (AI) was utilized in dental literature from 2011 until 2021. The second objective was to distinguish the focus of such publications; in particular, dental field and topic. The main inclusion criterium was an original article or review in English focused on dental utilization of AI. All other types of publications or non-dental or non-AI-focused were excluded. The information sources were Web of Science, PubMed, Scopus, and Google Scholar, queried on 19 April 2022. The search string was “artificial intelligence” AND (dental OR dentistry OR tooth OR teeth OR dentofacial OR maxillofacial OR orofacial OR orthodontics OR endodontics OR periodontics OR prosthodontics). Following the removal of duplicates, all remaining publications were returned by searches and were screened by three independent operators to minimize the risk of bias. The analysis of 2011–2021 publications identified 4413 records, from which 1497 were finally selected and calculated according to the year of publication. The results confirmed a historically unprecedented boom in AI dental publications, with an average increase of 21.6% per year over the last decade and a 34.9% increase per year over the last 5 years. In the achievement of the second objective, qualitative assessment of dental AI publications since 2021 identified 1717 records, with 497 papers finally selected. The results of this assessment indicated the relative proportions of focal topics, as follows: radiology 26.36%, orthodontics 18.31%, general scope 17.10%, restorative 12.09%, surgery 11.87% and education 5.63%. The review confirms that the current use of artificial intelligence in dentistry is concentrated mainly around the evaluation of digital diagnostic methods, especially radiology; however, its implementation is expected to gradually penetrate all parts of the profession.

Three-dimensional (3D) printing with biocompatible resins offers new competition to its opposition—subtractive manufacturing, which currently dominates in dentistry. Removing dental material layer-by-layer with lathes, mills or grinders faces its limits when it comes to the fabrication of detailed complex structures. The aim of this original research was to design, materialize and clinically evaluate a functional and resilient shape of the orthodontic power-arm by means of biocompatible 3D printing. To improve power-arm resiliency, we have employed finite element modelling and analyzed stress distribution to improve the original design of the power-arm. After 3D printing, we have also evaluated both designs clinically. This multidisciplinary approach is described in this paper as a feasible workflow that might inspire application other individualized biomechanical appliances in orthodontics. The design is a biocompatible power-arm, a miniature device bonded to a tooth surface, translating significant bio-mechanical force vectors to move a tooth in the bone. Its design must be also resilient and fully individualized to patient oral anatomy. Clinical evaluation of the debonding rate in 50 randomized clinical applications for each power-arm-variant showed significantly less debonding incidents in the improved power-arm design (two failures = 4%) than in the original variant (nine failures = 18%).

Background and Objectives: The symptoms of Eagle’s syndrome are associated with the elongated styloid process of the temporal bone or calcification of the stylohyoid ligament. The first mention of pain syndrome associated with the elongated styloid process dates back to 1937, when it was described by Watt Weems Eagle. Over the last decade, experts in the field have shown a lively interest in the issue of the relationship between the elongated styloid process and various symptoms. This article presents the correlation between the clinical signs of Eagle’s syndrome and alterations in surrounding anatomical structures. It includes a brief review of the evolutionary, embryological and clinical anatomical background of the elongated styloid process. Materials and Methods: Between 2018 and 2019, five patients were admitted to our workplace with 1–3-year history of bilateral or unilateral throat pain, otalgia and pharyngeal foreign body sensation. As a therapeutic novelty in the surgical approach to this condition, we used individual 3D printed models to measure and identify the exact location of the resection of the styloid process without damaging the surrounding anatomical structures, such as the facial, accessory, hypoglossal, and vagal nerves; the internal jugular vein; and the internal carotid artery. Results: Compared to traditional surgical methods without 3D models, 3D models helped to better identify cutting edges and major landmarks used in surgical treatment of Eagle’s syndrome. Printed models provided assistance with the exact location of the styloid process resection position without damaging the surrounding anatomical structures such as the facial, accessory, hypoglossal, and vagal nerves; the internal jugular vein; and the internal carotid artery. Conclusion: In our clinical report, we used 3D printed models for navigation and planning during surgical procedures involving resections of the elongated styloid process. Additionally, we can formulate a new hypothesis: the elongated styloid process is a form of atavism of the bony hyoid apparatus in our evolutionary ancestors that is evolutionarily encoded or arises from disrupted degeneration of the middle portion of embryonal Reichert´s cartilage of the second pharyngeal arch. Under normal conditions, this portion does not ossify but degenerates and transforms into a connective tissue band, the future stylohyoid ligament.

Artificial intelligence (AI), deep learning (DL), and machine learning (ML) are computer, machine, and engineering systems that mimic human intelligence to devise procedures. These technologies also provide opportunities to advance diagnostics and planning in human medicine and dentistry. The purpose of this literature review was to ascertain the applicability and significance of AI and to highlight its uses in maxillofacial surgery. Our primary inclusion criterion was an original paper written in English focusing on the use of AI, DL, or ML in maxillofacial surgery. The sources were PubMed, Scopus, and Web of Science, and the queries were made on the 31 December 2023. The search strings used were “artificial intelligence maxillofacial surgery”, “machine learning maxillofacial surgery”, and “deep learning maxillofacial surgery”. Following the removal of duplicates, the remaining search results were screened by three independent operators to minimize the risk of bias. A total of 324 publications from 1992 to 2023 were finally selected. These were calculated according to the year of publication with a continuous increase (excluding 2012 and 2013) and R² = 0.9295. Generally, in orthognathic dentistry and maxillofacial surgery, AI and ML have gained popularity over the past few decades. When we included the keywords “planning in maxillofacial surgery” and “planning in orthognathic surgery”, the number significantly increased to 7535 publications. The first publication appeared in 1965, with an increasing trend (excluding 2014–2018), with an R² value of 0.8642. These technologies have been found to be useful in diagnosis and treatment planning in head and neck surgical oncology, cosmetic and aesthetic surgery, and oral pathology. In orthognathic surgery, they have been utilized for diagnosis, treatment planning, assessment of treatment needs, and cephalometric analyses, among other applications. This review confirms that the current use of AI and ML in maxillofacial surgery is focused mainly on evaluating digital diagnostic methods, especially radiology, treatment plans, and postoperative results. However, as these technologies become integrated into maxillofacial surgery and robotic surgery in the head and neck region, it is expected that they will be gradually utilized to plan and comprehensively evaluate the success of maxillofacial surgeries.

Purpose: The aim of this study is to analyze mandibular condyle position changes after bilateral sagittal split osteotomy (BSSO) and bimaxillary orthognathic surgery in patients operated at a single department by two surgeons in 2013–2022. Compared were groups of mandibular advancement vs setback and bimaxillary vs BSSO. Methods: Ninety-nine subjects were included. Inclusion criteria were patients who underwent one of the BSSO or bimaxillary surgery and had CT scans performed before and after surgery. Preoperative CT scans were performed 1 day before surgery and postoperative CT scans 6–12 months afterwards. Changes in mandibular condyle position were measured in axial and sagittal planes. Results: CT condylar position measurements indicated significant postoperative changes in AB angle bilaterally (p = < 0.001). In mandibular advancement and setback comparison, values were significantly lower in ABL angle values in the setback group (p = 0.011326) and significantly higher in FDR in the advancement group (p = 0.005795). There were no statistically significant changes found in BSSO and bimaxillary group comparison. Conclusion: Within the limitations of this study, it can be concluded that orthognathic surgery does have a moderate effect on position of the condyles, especially condylar rotation in transversal axis.

Objective: Bisphosphonate-related osteonecrosis of the jaws is considered to be a rare but severe complication of bisphosphonate therapy. To understand this condition better, data collection is essential. Although the number of scientific papers about this subject is large, to date only a few multicenter reports have been published. Study design: We present a novel cloud-based data collection system for the evaluation of the risk factors of bisphosphonate-related osteonecrosis of the jaws. Web-based questionnaire and database have been set up and made available to voluntary researchers and clinicians in oral and maxillofacial surgery in Hungary and Slovakia. Results: To date, fifteen colleagues from eight maxillofacial units have joined the study. Data of 180 patients have been recorded. Collected data were statistically analysed and evaluated from an epidemiological point of view. Conclusions: Authors consider cloud-based multicenter data collection a useful tool that allows for real-time collaboration between users, facilitates fast data entry and analysis, and thus considerably contributes to widening our knowledge of bisphosphonate-related osteonecrosis of the jaws.