Introduction: The purpose of this study was to evaluate whether the presence of orthodontic brackets influences the accuracy of digital models generated by intraoral and extraoral scanning from the same patients.
Methods: Eighteen orthodontic patients in permanent dentition underwent full-arch intraoral scanning with a CEREC Omnicam scanner (Dentsply Sirona, York, Pa). Alginate impressions from each patient's arch were taken, and plaster models were made and scanned. Intermolar, intercanine, and mesiodistal width of the incisors were measured on 2 digital and 1 plaster models. Analysis of variance or Friedman's test was used, with differences between pairs verified by the Bonferroni test or Wilcoxon test, respectively. Both digital models were superimposed using surface-based registration.
Results: Lin's lowest coefficient of agreement was 0.960 (95% confidence interval, 0.900-0.984), which was clinically adequate. No statistically significant differences between the 3 types of model measurements were observed, except for the mandibular left lateral incisor in which scanned intraoral digital models presented Δmedium of 0.05 mm, which was higher than the plaster model. The superimposition of the extraoral and intraoral digital models revealed a minimum difference between models with a mean of means of 0.12 ± 0.03 mm.
Conclusions: Brackets bonded to teeth affected intraoral scanning; however, the intraoral digital models are clinically comparable and present fewer distortions than plaster models. Moreover, measurements on intraoral and extraoral digital models are excellent in terms of trueness and precision and can be used clinically and in plaster models.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.ajodo.2021.03.021 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
An Explainable CNN and Vision Transformer-Based Approach for Real-Time Food Recognition.
Nutrients
January 2025
Department of Computer Engineering, Inje University, Gimhae 50834, Republic of Korea.
Background: Food image recognition, a crucial step in computational gastronomy, has diverse applications across nutritional platforms. Convolutional neural networks (CNNs) are widely used for this task due to their ability to capture hierarchical features. However, they struggle with long-range dependencies and global feature extraction, which are vital in distinguishing visually similar foods or images where the context of the whole dish is crucial, thus necessitating transformer architecture.
View Article and Find Full Text PDFVat photopolymerization (VPP) is an additive manufacturing method that requires the design of photocurable resins to act as feedstock and binder for the printing of parts, both monolithic and composite. The design of a suitable photoresin is costly and time-consuming. The development of one formulation requires the consumption of kilograms of costly materials, weeks of printing and performance testing, as well as the need to have developers with the expertise and knowledge of the materials used, making the development process cost thousands.
View Article and Find Full Text PDFDecoding the Biobased Blueprint: Key Players and Evolutionary Trends in Materials Innovation.
Polymers (Basel)
January 2025
Department of Mechanical Engineering, Debre Markos University, Debre Markos 251, Ethiopia.
In the rapidly evolving biobased materials innovation landscape, our research identifies key players and explores the evolutionary perspective of biobased innovation, offering insights into promising research areas to be further developed by biobased material scientists in search of exploiting their knowledge in novel applications. Despite the crucial role of these materials in promoting sustainable production and consumption models, systematic studies on the current innovation terrain are lacking, leaving gaps in understanding key players, emerging technologies, and market trends. To address this void, we focused on examining patents related to biobased monomers and polymers, aiming to describe the innovation strategies and business dynamics of leading assignees.
View Article and Find Full Text PDFFacilitation of Tumor Stroma-Targeted Therapy: Model Difficulty and Co-Culture Organoid Method.
Pharmaceuticals (Basel)
January 2025
Department of Oral and Maxillofacial Surgery, Peking University School and Hospital of Stomatology & National Center of Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, 22# Zhongguancun South Avenue, Haidian District, Beijing 100081, China.
Tumors, as intricate ecosystems, comprise oncocytes and the highly dynamic tumor stroma. Tumor stroma, representing the non-cancerous and non-cellular composition of the tumor microenvironment (TME), plays a crucial role in oncogenesis and progression, through its interactions with biological, chemical, and mechanical signals. This review aims to analyze the challenges of stroma mimicry models, and highlight advanced personalized co-culture approaches for recapitulating tumor stroma using patient-derived tumor organoids (PDTOs).
View Article and Find Full Text PDFZero-Trust Access Control Mechanism Based on Blockchain and Inner-Product Encryption in the Internet of Things in a 6G Environment.
Sensors (Basel)
January 2025
State Grid Zaozhuang Power Supply Company, Zaozhuang 277899, China.
Within the framework of 6G networks, the rapid proliferation of Internet of Things (IoT) devices, coupled with their decentralized and heterogeneous characteristics, presents substantial security challenges. Conventional centralized systems face significant challenges in effectively managing the diverse range of IoT devices, and they are inadequate in addressing the requirements for reduced latency and the efficient processing and analysis of large-scale data. To tackle these challenges, this paper introduces a zero-trust access control framework that integrates blockchain technology with inner-product encryption.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!