Search Results (18)

Background/Objectives: Artificial intelligence (AI) is rapidly emerging as a transformative force in healthcare education, including orthodontics. This systematic review and meta-analysis aimed to evaluate the integration of AI into orthodontic training programs, focusing on its effectiveness in improving diagnostic accuracy, learner engagement, and the perceived quality of AI-generated educational content. Materials and Methods: A comprehensive literature search was conducted across PubMed, Scopus, Web of Science, and Embase through May 2025. Eligible studies involved AI-assisted educational interventions in orthodontics. A mixed-methods approach was applied, combining meta-analysis and narrative synthesis based on data availability and consistency. Results: Seven studies involving 1101 participants—including orthodontic students, clinicians, faculty, and program directors—were included. AI tools ranged from cephalometric landmarking platforms to ChatGPT-based learning modules. A fixed-effects meta-analysis using two studies yielded a pooled Global Quality Scale (GQS) score of 3.69 (95% CI: 3.58–3.80), indicating moderate perceived quality of AI-generated content (I² = 64.5%). Due to methodological heterogeneity and limited statistical reporting in most studies, a narrative synthesis was used to summarize additional outcomes. AI tools enhanced diagnostic skills, learner autonomy, and perceived satisfaction, particularly among students and junior faculty. However, barriers such as limited curricular integration, lack of training, and faculty skepticism were recurrent. Conclusions: AI technologies, especially ChatGPT and digital cephalometry tools, show promise in orthodontic education. While learners demonstrate high acceptance, full integration is hindered by institutional and perceptual challenges. Strategic curricular reforms and targeted faculty development are needed to optimize AI adoption in clinical training. Full article

Background/Objectives: This study evaluates the diagnostic and referral skills of final-year dental students at Al-Iraqia University using a questionnaire based on malocclusion cases ranging from mild to severe. Methods: The questionnaire, featuring photos and radiographs of five selected treated cases from two textbooks, was answered by 165 students who were asked to assess each case and determine whether orthodontic or surgical treatment was necessary, as well as to identify factors contributing to an unesthetic profile, such as irregular teeth. Frequency distribution and the Chi-square test were used for statistical analysis. Results: The results indicated good overall clinical competence. The unesthetic profile and irregular teeth were the main reasons for referring both Class II and III cases for surgery, with mandibular retrusion being the most common factor in aesthetic concerns. Maxillary protrusion was less frequently selected as a key factor in Class II malocclusion cases. Conclusions: The findings suggest that students demonstrated a high level of diagnostic accuracy in identifying treatment needs for various malocclusion cases. Full article

Background/Objectives: Clinical photography is an essential component of orthodontic records, alongside radiographs, dental scanners, and cone beam computed tomography. However, neither the American Association of Orthodontists nor the Spanish Society of Orthodontics provides a standardized protocol for dental photography. This study aimed to evaluate the current practices, challenges, and training needs related to clinical photography among orthodontists in Spain. Methods: A cross-sectional survey was designed using Google Forms^® and distributed to orthodontists practising in Spain. A sample size of 303 participants was calculated (95% confidence level; 0.1 precision). The questionnaire covered photographic practices, equipment usage, self-assessed skills, interest in training, and legal considerations. Descriptive and inferential analyses were performed using R software (significance level 0.05; version 4.4.1). Results: A total of 304 valid responses were analyzed, with a predominance of female participants (77.96%) and a mean age of 37.54 years (SD: 9.08). Digital single-lens reflex (DSLR) cameras with macro lenses and ring flashes were the most used equipment (68.09%). The primary software for cropping and editing images were Windows Photos (28.95%) and MacOS Photos (16.12%). Male participants rated their photography skills higher than female participants (p = 0.003), and those with full-time orthodontic training considered their skills better than those with other types of training (p = 0.014). Photography was most valued for diagnosis in the exclusive orthodontics group (p = 0.019). Additionally, 75.99% of respondents expressed interest in improving their photography skills through specialized courses. Conclusions: This study highlights significant variability in photographic practices among orthodontists in Spain. The findings emphasize the need for standardized photography protocols to enhance diagnostic accuracy, clinical documentation, and professional training. Full article

Artificial intelligence (AI) is an area of computer science that focuses on designing machines or systems that can perform operations that would typically need human intelligence. AI is a rapidly developing technology that has grabbed the interest of researchers from all across the globe in the healthcare industry. Advancements in machine learning and data analysis have revolutionized oral health diagnosis, treatment, and management, making it a transformative force in healthcare, particularly in dentistry. Particularly in dentistry, AI is becoming increasingly prevalent as it contributes to the diagnosis of oro-facial diseases, offers treatment modalities, and manages practice in the dental operatory. All dental disciplines, including oral medicine, operative dentistry, pediatric dentistry, periodontology, orthodontics, oral and maxillofacial surgery, prosthodontics, and forensic odontology, have adopted AI. The majority of AI applications in dentistry are for diagnoses based on radiographic or optical images, while other tasks are less applicable due to constraints such as data availability, uniformity, and computational power. Evidence-based dentistry is considered the gold standard for decision making by dental professionals, while AI machine learning models learn from human expertise. Dentistry AI and technology systems can provide numerous benefits, such as improved diagnosis accuracy and increased administrative task efficiency. Dental practices are already implementing various AI applications, such as imaging and diagnosis, treatment planning, robotics and automation, augmented and virtual reality, data analysis and predictive analytics, and administrative support. The dentistry field has extensively used artificial intelligence to assist less-skilled practitioners in reaching a more precise diagnosis. These AI models effectively recognize and classify patients with various oro-facial problems into different risk categories, both individually and on a group basis. The objective of this descriptive review is to review the most recent developments of AI in the field of dentistry. Full article

In orthodontics, the manual tracing of cephalometric radiographs is a common practice, where the Sella Turcica (ST) serves as a reference point. The radiologist often manually traces the outline of the sella using manual tools (e.g., calipers on radiographs). Perhaps the inherent complexity and variability in the shapes of sella and the lack of advanced assessment tools make the classification of sella challenging, as it requires extensive training, skills, time, and manpower to detect subtle changes that often may not be apparent. Moreover, existing semi-supervised learning (SSL) methods face key limitations such as shift invariance, inadequate feature representation, overfitting on small datasets, and a lack of generalization to unseen variations in ST morphology. Medical imaging data are often unlabeled, limiting the training of automated classification systems for ST morphology. To address these limitations, a novel semi-supervised deep subspace embedding (SSLDSE) framework is proposed. This approach integrates real-time stochastic augmentation to significantly expand the training dataset and introduce natural variability in the ST morphology, overcoming the constraints of small and non-representative datasets. Non-linear features are extracted and mapped to a non-linear subspace using Kullback–Leibler divergence, which ensures that the model remains consistent despite image transformations, thus resolving issues related to shift invariance. Additionally, fine-tuning the Inception-ResNet-v2 network on these enriched features reduces retraining costs when new unlabeled data becomes available. t-distributed stochastic neighbor embedding (t-SNE) is employed for effective feature representation through manifold learning, capturing complex patterns that previous methods might miss. Finally, a zero-shot classifier is utilized to accurately categorize the ST, addressing the challenge of classifying new or unseen variations. Further, the proposed SSLDSE framework is evaluated through comparative analysis with the existing methods (Active SSL, GAN SSL, Contrastive SSL, Modified Inception-ResNet-v2) for ST classification using various evaluation metrics. The SSLDSE and the existing methods are trained on our dataset (sourced from PGI Chandigarh, India), and a blind test is conducted on the benchmark dataset (IEEE ISBI 2015). The proposed method improves classification accuracy by 15% compared to state-of-the-art models and reduces retraining costs. Full article

The swift integration of ‘Gummetal’ into the orthodontic armamentarium can be attributed to its distinct advantages as an entirely new Ti-Nb-based beta titanium alloy. Developed by Toyota Central R&D Labs and publicly revealed in April 2003, this innovative material is rapidly reshaping orthodontic practices. Its sui generis properties allow its use as a potential substitute for the Multi-Loop Edgewise Archwire (MEAW) method. Three-dimensional orthodontic movement using this new alloy could eliminate the disadvantages of the MEAW method, such as its technical complexity and patient discomfort. In our comprehensive review of the current literature, we examined relevant publications sourced from the PUBMED database and explored one seminal work on Gummetal from the journal literature. Characteristic properties of Gummetal, such as its exceptional flexibility, superelasticity, and malleability (approximately 10 times greater than conventional metals), enable seamless formation of bends without posing challenges, thereby allowing precise control over orthodontic force application. Also worthy of mention are Gummetal’s biocompatibility and non-toxic properties, along with its low coefficient of friction. The wire seems to be a relatively easy way to achieve good occlusion. Its usage does not require extensive experience in terms of manual skill, and it is not time consuming. Diligent usage of any prescribed plastics by the patient is crucial to prevent complications and ensure successful orthodontic outcomes. Full article

Craniofacial surgery is proposed and performed for a variety of reasons, ranging from congenital or acquired malformations to emotional disorders and parafunctions of the masticatory, respiratory, auditory, and visual systems. Surgery of the mandible and its orthostatic repositioning is the most common of these corrections of craniofacial anomalies. Throughout the history of these procedures, various techniques have been proposed and perfected, but always with a high rate of minor and major complications. The recurrence rate of mandibular malposition is high, as is the temporary loss of facial sensitivity and motor skills. These outcomes are often related to the choice of surgical technique rather than the skill of the surgeon, which is considered to be one of the most important factors in the final outcome. Surgical techniques involving direct manipulation of the vascular-nervous bundles, such as bilateral sagittal split osteotomy, clearly present the possibility of major or minor complications. In this study, an orthognathic surgical technique, performed by the same team for over 40 years and now available through a 20-year postoperative patient follow-up study, is presented with a literature review relating it to biomechanical concepts and bone remodeling to analyze the evolution of orthognathic surgery since it became common practice to correct maxillofacial discrepancies. In this review, we also present a case report in which previous orthodontic treatment prepared a patient for surgical correction of mandibular bone discrepancy without the need for combined maxillary and/or genioplasty, and we describe the most commonly used techniques today, as well as their advantages and disadvantages. The combination of established concepts together promotes favorable stability of mandibular osteotomies, functional anatomical positioning of the temporomandibular joint, reduced risk of injury to the mandibular vasculo-nervous bundle, and good aesthetics with positive patient acceptance and no relapse, thus these are the objectives for proposing innovative treatments that combine the technologies available today. Full article

Objectives: To provide safe and effective local anesthesia, dentists must have knowledge of neuroanatomy, anesthesia agents, techniques, equipment, and proper use of local anesthetics. This study aims to explore the knowledge, practices, and confidence regarding local anesthetics and anesthetic techniques in dentistry. Material and Methods: The online cross-sectional questionnaire was conducted via social media, and yielded 441 responses from across the country (69.8% women and 30.2% men; 70.7% general dentists; and 29.3 specialists). The data collected included sociodemographic characteristics, knowledge, and practices pertaining to the usage of local anesthesia. The questionnaire also documents their self-assessed confidence level in applying different local anesthetic techniques and experiences with adverse reactions. The obtained data were processed by description and using a generalized linear model for regression. Results: The respondents had a median knowledge score of 6 out of a possible 14 points regarding local anesthetics in dental medicine, and their median self-confidence level in the successful application of various techniques of local anesthesia was 54 out of a maximum of 85 points. The results showed that a higher knowledge level was associated with the female gender (OR 1.83, CI 1.13–2.98, p = 0.014) and specialization in oral surgery (OR 7.04, CI 1.71–29.07, p = 0.007). In contrast, a lack of confidence in using various local anesthetic techniques was also associated with the female gender (OR 0.63, CI 0.41–0.99, p = 0.047) and specialization in orthodontics (OR 0.16, CI 0.03–0.88, p = 0.035). Of the respondents, 81.4% (n = 371) experienced a local complication, and 42.2% (n = 186) experienced a systemic complication during local anesthesia. The complications experienced cannot be associated with a lack of knowledge or self-confidence (p > 0.05). The majority of respondents (364 of the 441 total—82.5%) expressed interest in receiving further education on the topic of local anesthesia. Conclusions: The research results show that the dentists involved in the study have poor knowledge of local anesthetics and moderate self-reported confidence levels in using various local anesthetic techniques. Moreover, dentists’ self-confidence in applying different techniques of local anesthesia is not related to their knowledge. Therefore, it would be necessary for dentists to undergo a continuing dental education program that enables them to enhance their skills and knowledge in local anesthesia. Full article

Learning games that are based on current scientific concepts are underutilized in dental education. This paper explores the relevant science of learning and discusses several principles that are conducive to learning and teaching in an educational setting, namely retrieval practice, feedback, motivation, and engagement. A discussion of learning games in health professional education ensues, followed by a description of relevant best practices in game design for learning. This paper concludes by presenting Dealodontics©, a card game developed at New York University College of Dentistry with the goal of helping second-year dental students review, practice, and apply basic skills relevant to their orthodontics competency requirements. Full article

Removing dental plaque by using a toothbrush is the most important measure for oral hygiene. The aim of the present study was to estimate the impact of the coordination skills of children and adolescents on their oral health (plaque level, DMF/T: decayed, missing, filled teeth). Within a prospective cohort study, 996 children (10 to 18 years) were examined. The results of three coordination tests from the Motorik Modul (MoMo) were included to evaluate the coordination skills. Other parameters taken into account were age, sex, orthodontic treatment and socioeconomic status (SES). Univariate and various multivariate analyses were performed to evaluate relationships. Better results in precision coordination tests were significantly related to a better oral hygiene (backward balancing: logistic regression OR 0.86, 95%CI: 0.73–0.99, p = 0.051, proportional odds model OR 0.86, 95%CI: 0.75–0.99, p = 0.037; one-leg-stand: logistic regression OR 0.78, 95%CI: 0.63–0.96, p = 0.018, proportional odds model OR 0.77, 95%CI: 0.64–0.92, p = 0.003). Higher scores on one-leg-stand were significantly related to a lower caries prevalence (logistic regression OR 0.81, 95%CI: 0.66–0.99, p = 0.037; Poisson regression exp(ß) 0.82, 95%CI: 0.74–0.91, p < 0.001). Coordination test under a time constraint (jumping side-to-side) showed no significant relation. Oral hygiene was poorer in younger children, boys and low SES. Caries prevalence increased with low SES and increasing age. The present results suggest that oral health is influenced by coordinative skills. Full article

Background: The use of digital technology has exponentially increased over recent years. Intraoral scanners, especially, have gained traction within orthodontics. The objective of the present review is to investigate the available evidence to create an up-to-date presentation of various clinical aspects of intraoral scanners in orthodontics. Methods: Search without restrictions in seven databases (Pubmed, CENTRAL, Cochrane Reviews, Scopus, Web of Science, Clinical Trials, Proquest) since inception, and hand searching until October 2020, were conducted. Results: The majority of studies were either cross-over or parallel group studies. The accuracy and reproducibility of intraoral scanners, in comparison to conventional methods, were investigated in several studies, with controversial results. The duration of the procedure did not report any clear outcome in favor of any method. Patients seem to prefer intraoral scanning, even though numerous studies point out the importance of operators’ experience and skills. Conclusions: Despite the innovations that intraoral scanners have brought in orthodontic clinical practice, there are still some challenges and limitations in their use. The majority of existing limitations may be overcome with experience and good clinical skills. More high-quality studies need to be conducted so that clinicians can have a clear image of this new technology. Full article

A gradual transition from traditional face-to-face learning to online learning has been observed globally following the COVID-19 pandemic. The aim of the study was to compare online and traditional learning methods in relation to orthodontic knowledge and skills acquired in undergraduate courses. A quasi-experimental design was used with two consecutive year classes of 198 dental students at Jazan University, Saudi Arabia. The experimental (virtual) group of 92 students received the content of a clinical orthodontic course virtually using the Blackboard Collaborate™ platform. The control (traditional) group consisted of a previous cohort of 106 students who enrolled in the same course but received traditional classroom education. The students were evaluated through a semester, and both groups obtained the same content and exam questions. The students in the virtual group scored higher in the final theory exam than the traditional group (p-value < 0.05). However, no significant difference in the overall orthodontic knowledge and skills was observed between the groups at the end of the course. Both learning methods showed moderate positive correlation between orthodontic knowledge and skills. In conclusion, virtual learning can serve as an effective alternative to traditional face-to-face learning for teaching orthodontic knowledge and skills to the dental students. Full article

Among the innovations that have changed modern orthodontics, the introduction of new digital technologies in daily clinical practice has had a major impact, in particular the use of 3D models of dental arches. The possibility for direct 3D capture of arches using intraoral scanners has brought many clinicians closer to the digital world. The digital revolution of orthodontic practice requires both hardware components and dedicated software for the analysis of STL models and all other files generated by the digital workflow. However, there are some negative aspects, including the need for the clinician and technicians to learn how to use new software. In this context, we can distinguish two main software types: dedicated software (i.e., developed by orthodontic companies) and open-source software. Dedicated software tend to have a much more user-friendly interface, and be easier to use and more intuitive, due to being designed and developed for a non-expert user, but very high rental or purchase costs are an issue. Therefore, younger clinicians with more extensive digital skills have begun to look with increasing interest at open-source software. The aim of the present study was to present and discuss some of the best-known open-source software for analysis of 3D models and the creation of orthodontic devices: Blue Sky Plan, MeshMixer, ViewBox, and Blender. Full article

Who does refer patients for an orthodontic consultation? Which are the main reasons for the referral? Does the visit of the orthodontic specialist confirm these reasons or reveal undiagnosed problems? Is there the risk that only evident dental problems are addressed, while craniofacial malformations remain underdiagnosed? This cross-sectional epidemiologic study aims to answer these questions, analysing the clinical data collected during the orthodontic visits of 500 Caucasian young patients referred to a public health structure of northern Italy. All patients were visited by the same expert specialist in orthodontics. Clinical data were collected, analysing both dental and skeletal features. The reasons for the referral of the visit were analysed and compared with the specialistic diagnoses. In our sample, dentists, relatives/friends and paediatricians were the major source of the referrals, followed by family doctors and other facial specialists. In most cases, the reasons for the referral were dental irregularities, but approximately 80% of dental irregularities were associated with undiagnosed facial dysmorphism. Skeletal facial anomalies need an early diagnosis to prevent the development of severe facial malformations that would require invasive and expensive treatments. These findings reveal poor diagnostic skills regarding skeletal anomalies in dentists and paediatricians and the need for better specific training. Full article

Study Design: Retrospective cohort study. Objective: The purpose of this study was to evaluate and share our experience with the surgery first approach (SFA) for correction of skeletal malocclusion. Methods: After consultation with the department of orthodontics, 45 patients with skeletal malocclusions suitable to undergo SFA were enrolled in this study (14 bimaxillary protrusion and 31 skeletal class III malocclusion). Le Fort I maxillary osteotomy, bilateral sagittal split ramus osteotomy, subapical osteotomy, and genioplasty were performed as required. After a healing period of 2 weeks, postoperative orthodontic treatment was started to achieve the final occlusion. Results: The mean duration of postoperative orthodontic treatment was 15.2 months, which is much shorter than the conventional orthodontic first approach (OFA) where presurgical orthodontic duration alone takes 12–24 months according to an individual. In the bimaxillary protrusion group, it was 18 months, which was significantly longer than for the other group (p < 0.05). Conclusions: SFA offers an efficient alternative to conventional OFA with shorter total treatment duration, immediate marked improvement in facial profile, reduced biological costs, and similar operative stability. However, it comes at the cost of heightened challenges regarding case selection, accurate prediction, and surgical precision. With a joint venture between skilled and experienced surgeons and orthodontists, the outcome can be very promising. Full article