Purpose: To systematically evaluate the diagnostic efficacy of intraoral radiographs and evidence supporting the indications for taking of intraoral radiographs in children in the following five clinical categories: caries, pathological conditions (including acute odontogenic infections and periodontal disease), dental/developmental anomalies, dental trauma, and enhancement of comfort/technique for taking radiographs in children. This was carried out to facilitate the updating of existing European Academy of Paediatric Dentistry (EAPD) guidelines on dental radiography in pediatric dentistry.
Methods: A systematic electronic literature search was conducted on Cochrane Library (1992-24 July 2018), MEDLINE (PubMed, 1946-24 July 2018), EMBASE (Embase.com, 1974-24 July 2018) and Scopus (pre-1970-24 July 2018). Hand search of handbooks and grey literature search was also performed. Study screening and study inclusions were agreed upon by three authors. Data extraction, and methodological quality and risk of bias assessment were carried out in duplicate for each of the included studies.
Results: A total of 9581 papers were identified. Following the primary and secondary assessment process, 36 papers were included in the final analysis. The included studies were further categorized into five main clinical categories for analysis: caries, pathological conditions, dental/developmental anomalies, dental trauma and comfort/technique-related studies. Only one paper was found to be of good quality and at low risk of bias; while, 9 papers were found of be at moderate risk of bias and 26 papers were at high risk of bias. Meta-analysis was not possible for any of the aforementioned clinical situations, and only a narrative synthesis was done.
Conclusion: There is insufficient high-quality evidence for the use of intraoral radiographs in pediatric dentistry and current guidelines are based largely on expert opinion. There is a clear need for well-conducted and standardized studies regarding the use of intraoral radiography in pediatric dentistry.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1007/s40368-020-00532-y | DOI Listing |
J Endod
January 2025
State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan, China; Department of Cariology and Endodontics, School and Hospital of Stomatology, Wuhan University, Wuhan, China. Electronic address:
Introduction: Fiber posts present significant challenges for nonsurgical endodontic retreatment, as improper removal may result in iatrogenic root perforation or even root fracture. Recently, robotic technology has attracted considerable attention in dentistry and active dental robotic (ADR) systems can perform procedures based on preset instructions, minimizing reliance on the dentist's experience. This case report describes the application of an ADR system for fiber post removal through an existing zirconia crown.
View Article and Find Full Text PDFCureus
December 2024
Department of Orthodontics, School of Dentistry, Shahid Beheshti University of Medical Sciences, Tehran, IRN.
Background Orthodontic diagnostic workflows often rely on manual classification and archiving of large volumes of patient images, a process that is both time-consuming and prone to errors such as mislabeling and incomplete documentation. These challenges can compromise treatment accuracy and overall patient care. To address these issues, we propose an artificial intelligence (AI)-driven deep learning framework based on convolutional neural networks (CNNs) to automate the classification and archiving of orthodontic diagnostic images.
View Article and Find Full Text PDFBMC Oral Health
January 2025
Center for Plastic & Reconstructive Surgery, Department of Stomatology, Affiliated People's Hospital, Zhejiang Provincial People's Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, China.
Background: The purpose of this study was to evaluate the validity of near-infrared light reflection for detecting different depths of proximal caries in posterior teeth and to compare it with commonly used clinical oral examinations and bitewing radiography images.
Methods: Twenty-six patients with a total of 516 proximal surfaces were included in this study. The ground truth of the proximal caries was determined through a consensus reached by two experienced dentists after an intraoral examination assisted by bitewing radiographs.
Bioengineering (Basel)
December 2024
Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, 720, Swanston Street, Carlton, VIC 3053, Australia.
Artificial intelligence (AI) has gained significant traction in medical image analysis, including dentistry, aiding clinicians in making timely and accurate diagnoses. Radiographs, such as orthopantomograms (OPGs) and intraoral radiographs, along with clinical photographs, are the primary imaging modalities employed for AI-powered analysis in the dental field. In this review, we discuss the most recent research and product developments concerning the clinical application of AI as a visual aid in dentistry and introduce the concept of Observational Diagnostics (ODs) as a structured method to standardise image analysis.
View Article and Find Full Text PDFOrthod Fr
January 2025
Nantes Université, Université Angers, CHU Nantes, INSERM, CNRS, CRCI2NA, 44000 Nantes, France
Introduction: The aim of this article is to present the diagnostic and therapeutic approach to unilateral posterior vertical insufficiency.
Material And Methods: The authors describe the management protocol.
Results: Posterior vertical insufficiency (PVI) manifests clinically as obliquity of the maxillo-mandibular occlusal plane and bicommissural line, and deviation of the chin.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!