/library/oar/handle/123456789/427 Sat, 07 Nov 2026 14:15:31 GMT 2026-11-07T14:15:31Z /library/oar/handle/123456789/149760 Title: Intaglio surface accuracy of temporary crowns fabricated by additive versus subtractive CAD/CAM methods Authors: Ayres, Ana Paula; Rodrigues, Nicole; Pinhata-Baptista, Otavio Henrique; Pradies, Guillermo; Cortes, Arthur R. G. Abstract: The success of temporary restorations depends on their marginal and internal adaptation, which are influenced by the manufacturing method. This study evaluated the intaglio surface accuracy, internal fit, and marginal fit of provisional crowns fabricated via subtractive (milling) and additive (3D printing) CAD/CAM technologies. Three milling systems—CEREC Primemill (4-axis), PrograMill Dry (5-axis), and Zirkonzahn M1 (5-axis)—and three 3D printers—Phrozen Mini 4K (LCD), SprintRay Pro95S (DLP), and Stratasys Objet30 (PolyJet)—were evaluated. For 3D printing, five build orientations (0°, 30°, 45°, 60°, and 90°) were tested. A total of 360 crowns were fabricated. Accuracy was quantified by Root Mean Square (RMS) deviation, and fit was assessed using the triple-scan method. Results indicated that build angles of 0° and 30° yielded the best performance for printed crowns (p < 0.05). While milling systems showed significantly superior intaglio accuracy and marginal fit compared to 3D printing (p < 0.05), no significant differences were found in internal fit between the two methods (p > 0.05). Milling offers higher dimensional predictability, but both approaches are clinically viable when optimized parameters are utilized. Thu, 01 Jan 2026 00:00:00 GMT /library/oar/handle/123456789/149760 2026-01-01T00:00:00Z /library/oar/handle/123456789/149758 Title: Diagnostic performance of an intraoral scanner for caries detection on permanent tooth surfaces Authors: Agius, Anne-Marie; No-Cortes, Juliana; Cortes, Arthur R. G.; Attard, Nikolai J.; Gatt, Gabriella Abstract: Intraoral scanners with fluorescence technology (IOSFT) include a caries detection feature in addition to their standard scanning function. The aim of this study was to determine the diagnostic performance of the caries detection tool of the IOSFT Trios 4® on permanent premolar and molar surfaces when compared to visual and radiographic International Caries Detection and Assessment System (ICDAS). Methods: Participants (n = 71, age 6–88 years) were examined under standardised conditions using ICDAS criteria for visual caries detection of occlusal and smooth surfaces. Bitewing (BW) radiographs were used to examine proximal surfaces using ICDAS radiographic criteria. Finally, participants underwent an intraoral scan of both the maxilla and the mandible according to the manufacturer’s instructions. The automated caries detection (ACD) output on the IOSFT software was compared to the visual ICDAS scores obtained clinically for occlusal and free smooth (buccal and lingual) surfaces; the IOSFT caries de detection output was compared to radiographic ICDAS scores from BW radiographs for interproximal (mesial and distal) surfaces. Sensitivity, specificity, and accuracy values for each tooth surface were calculated. Results: Out of 3,684 permanent tooth surfaces examined, 461 surfaces with dental caries were included in the analysis. 392 were initial lesions (ICDAS 1–2), while 69 were moderate/severe (ICDAS 3–6). There was a moderate positive correlation (r = 0.4, p < 0.001) when comparing all ICDAS scores to IOSFT ACD categories for unrestored permanent occlusal surfaces. IOSFT ACD accuracy was higher for moderate/advanced lesions (ICDAS 3–6) lesions when compared to initial (ICDAS 1–2) ones (81% vs. 37.7%). For unrestored smooth surfaces, weak positive correlations were found when comparing all ICDAS scores to IOSFT ACD categories (r = 0.19, p < 0.001). Accuracy results for smooth surfaces were 93.5% for moderate/advanced and 77.1% for initial lesions. Correlations between BW ICDAS scores and IOSFT ACD scores for proximal surfaces were weak (r = 0.07, p = 0.019). Diagnostic accuracy was higher for moderate/ advanced lesions when compared to initial ones (83.5% vs. 40.4%). There was a weak correlation between IOSFT ACD categories and ICDAS/visual categories for restored occlusal surfaces (r = 0.029, p = 0.68). Conclusion: IOSFT cannot currently replace visual and radiographic exams for caries detection. Wed, 01 Jan 2025 00:00:00 GMT /library/oar/handle/123456789/149758 2025-01-01T00:00:00Z /library/oar/handle/123456789/149756 Title: Patient acceptance, time efficiency, and inter-operator agreement in intra-oral scanning with fluorescence technology for caries detection Authors: Agius, Anne-Marie; No-Cortes, Juliana; Cortes, Arthur R. G.; Attard, Nikolai J.; Gatt, Gabriella Abstract: Background: Intra-oral scanners (IOS) have been widely used to obtain digital impressions for treatment planning and to enable a full digital workflow on virtual patients. Much less is known about the use of IOS for caries detection. This study focuses on the use of the scanners for caries detection and investigates the number of images, time and patient experiences as well as differences between operators.; Methods: Participants were recruited if they had caries present, their teeth were cleaned using a prophy brush and water and then scanned in a standardised manner. Some participants were scanned a second time by another operator. The automated caries detection results as well as the number of images needed and time taken per jaw scanned was noted. Participants were also asked to complete a questionnaire regarding their experience during the scanning process.; Results: Data sets (scanning time and number of images) from 78 participants were both found to be non-normal using the Shapiro Wilk test (p < 0.001). A Mann-Whitney U test revealed that both the time taken (U = 17772.500, z = -8.066, p < 0.001) as well as the number of images needed (U = 15252.000, z =-9.651, p < 0.0001) were significantly higher for the maxilla when compared to the mandible. The same test also showed that significantly more time (U = 102718.500, z = 14.505, p < 0.0001) and images (U = 108395.500, z = 16.457, p < 0.0001) were needed for scanning permanent teeth when compared to primary teeth. The questionnaire revealed that the vast majority of participants (87%) found the scanning procedure comfortable and acceptable but there were statistically significant differences in discomfort experienced in different areas of the mouth, with the most uncomfortable area scanned being the distal surfaces of the upper molars (p < 0.001). A Wilcoxon Signed Rank test revealed no significance difference in jaw scanning time (z = 0.118, n = 12, p = 0.906) and number of images taken per arch (z = 1.255, n = 12, p = 0.209) between the operators. Cohen’s Weighted Kappa yielded the following significant result: κ = 0.744, p < 0.0001 showing good agreement between the operators’ automated caries detection results. Wed, 01 Jan 2025 00:00:00 GMT /library/oar/handle/123456789/149756 2025-01-01T00:00:00Z /library/oar/handle/123456789/148353 Title: Dental clinical procedures using artificial intelligence Authors: Cortes, Arthur R. G. Abstract: This book explores how artificial intelligence is reshaping diagnostic and therapeutic paradigms in contemporary dentistry and offers step-by-step guidance through real-life cases. It is divided into two main sections. The first section presents a systematic approach to AI-assisted diagnostic procedures, including anatomical assessment of the jaws, detection of caries and tooth wear, evaluation of oral lesions, and periodontal analysis. It also examines the current limitations and ethical considerations surrounding the deployment of AI in diagnostic contexts. The second section delves into AI-based digital planning tools, covering advanced techniques in tissue segmentation, orthodontic treatment planning, oral surgical simulations, and prosthetic and restorative design. Each chapter integrates theoretical foundations with clinical applications, supported by emerging research and case-based insights. This book serves as a resource for integrating artificial intelligence into dental workflows, offering evidence-based guidance and fostering interdisciplinary dialogue between dental science and computational innovation. Thu, 01 Jan 2026 00:00:00 GMT /library/oar/handle/123456789/148353 2026-01-01T00:00:00Z