Search Results (618)

Background/Objectives: The quality of intraoral scanner-derived digital models depends not only on deviation-based accuracy, but also on how scanned surfaces are reconstructed into a polygonal mesh. The aim of this prospective within-subject observational study was to evaluate whether tooth morphology influences local mesh density distribution in intraoral scanner-derived STL models of selected maxillary teeth. Methods: Twenty participants underwent maxillary intraoral scanning using a Medit i900 wired intraoral scanner under standardized clinical conditions. For each participant, the buccal surfaces of the maxillary right central incisor (11), canine (13), first premolar (15), and first molar (16) were selected as regions of interest. Surface area (A), number of vertices (V), and number of faces (F) were recorded, and the surface-normalized mesh density parameters vertices per unit area (V/A) and faces per unit area (F/A) were calculated. Comparisons among tooth types were performed using repeated-measures analysis of variance (ANOVA) with Bonferroni post hoc correction. Results: Significant differences were found among tooth types for both V/A and F/A (p < 0.001). Mean V/A values were 18.2 ± 1.9 for tooth 11, 19.8 ± 1.4 for tooth 13, 23.8 ± 1.7 for tooth 15, and 22.9 ± 2.0 vertices/mm² for tooth 16. Mean F/A values were 34.3 ± 3.6, 37.5 ± 2.7, 44.4 ± 3.3, and 42.9 ± 3.8 faces/mm², respectively. Post hoc comparisons showed significant differences between teeth 11 and 13, 11 and 15, 11 and 16, 13 and 15, and 13 and 16, whereas no significant difference was observed between teeth 15 and 16. Conclusions: Tooth morphology significantly influenced local mesh density distribution in intraoral scanner-derived STL models of selected maxillary teeth. These findings suggest that local anatomical form affects STL mesh reconstruction under standardized in vivo scanning conditions and support local mesh density analysis as a useful complementary approach to conventional deviation-based digital assessment. Full article

Monolithic zirconia restorations are frequently affected by the unnoticed growth of subcritical cracks, a failure process that is not captured by traditional imaging methods like radiographs and ultrasounds in sophisticated dental architectures. To address this evaluative inadequacy, this research introduces a hierarchical deep learning framework for microcrack detection and spatial localization. We promote a hierarchical deep learning system that integrates Acoustic Emission (AE) detection alongside signal processing. Raw AE signals utilized during dynamic loading are enhanced via Kalman filtering and Continuous Wavelet Transform (CWT) to construct high-fidelity time–frequency scalograms. The diagnostic pipeline operates in two stages: first, a hybrid CNN–BiGRU network with temporal attention fulfills zirconia component-level classification; second, a ResNet-18 backbone integrated with Bidirectional LSTM and Multi-Head Attention precisely localizes defects across five anatomical crown regions. This hierarchical design effectively captures the non-stationary, transient nature of fracture-induced stress waves. The framework achieved an F1-score of 99.00% and an AUC of 0.994, significantly outperforming conventional convolutional networks. By enabling predictive maintenance through early, non-invasive damage localization, this study demonstrates a promising laboratory framework for AE-based crack detection in zirconia dental structures and prosthetics and toward enhanced clinical reliability in digital dentistry. Full article

This research presents an artificial intelligence (AI)-driven 3D scanning and printing system for the fabrication of personalized dental prosthetics, implants, and orthodontic appliances. The proposed system integrates high-resolution intraoral scanning, AI-based data analysis, and additive manufacturing to enhance precision, customization, and treatment efficiency. Patient-specific anatomical data and medical history are incorporated to optimize implant design, material selection, and functional performance. Nano-enhanced biocompatible materials are utilized to improve mechanical strength, durability, and antibacterial properties. Specifically, these materials demonstrate a 30% increase in overall precision and a 50% improvement in durability compared to traditional dental materials. In addition, the system adopts a zero-waste manufacturing strategy by recycling excess materials, supporting sustainable dental practices. The results demonstrate significant improvements in accuracy, patient comfort, and environmental responsibility in modern digital dentistry. Full article

Additive manufacturing enables the fabrication of patient-specific zirconia devices with integrated surface features; however, the biological effects of meso-scale topographies remain insufficiently understood. This in vitro study evaluated the influence of defined meso-scale surface modifications on osteoblast behavior using Digital Light Processing (DLP)-fabricated 3Y tetragonal zirconia polycrystal (3Y-TZP) and 5Y partially stabilized zirconia (5Y-PSZ). Planar control specimens and surfaces incorporating regularly distributed columnar structures (height: 100 µm; width: 40 µm; center-to-center spacing: 80, 120, and 160 µm; Mod-80, Mod-120, Mod-160) were fabricated and characterized after sintering. Cytotoxicity was assessed by elution testing and showed cell viability >98% for all groups. Osteoblast adhesion and proliferation (hFOB 1.19) were quantified using metabolic assays. Meso-scale modifications significantly increased early cell adhesion compared to planar controls (p < 0.05), with the strongest effect observed for Mod-160. No significant differences in proliferation rates were detected between groups (p > 0.05). Osteogenic differentiation was evaluated by RT-qPCR (RUNX2, ALPL, COL1A1, BGLAP), revealing material- and geometry-dependent responses. On 3Y-TZP, meso-scale structures, particularly Mod-160, were associated with sustained upregulation of BGLAP, whereas 5Y-PSZ exhibited less pronounced effects. Within the limitations of this in vitro study, meso-scale surface structuring of additively manufactured zirconia enhances early osteoblast adhesion without affecting proliferation and may influence osteogenic differentiation in a material-dependent manner. Full article

Objectives: The aim of this study was to compare the relationship between psychological factors and the thickness of masticatory muscles in patients with temporomandibular disorders (TMD) and healthy controls. Methods: This cross-sectional study included 106 female participants aged 18–35 years, recruited from students of the Medical University of Lublin. The study group consisted of individuals diagnosed with myalgia based on the Diagnostic Criteria for Temporomandibular Disorders (DC/TMD), while the control group included participants without TMD. Psychological factors were assessed using the PHQ-9, GAD-7, and PHQ-15 questionnaires. The thickness of the temporalis and masseter muscles was measured using an M-Turbo (Sonosite) ultrasound device under relaxed and contracted conditions. Results: Participants with TMD-related myalgia scored significantly higher on the PHQ-9 (mean ± SD: 8.82 ± 5.02 vs. 5.00 ± 3.41; p < 0.001), GAD-7 (8.53 ± 4.48 vs. 4.65 ± 3.58; p < 0.001), and PHQ-15 (9.47 ± 4.07 vs. 6.02 ± 3.89; p < 0.001) compared to controls. No statistically significant differences were observed in temporalis or masseter muscle thickness at rest or during contraction between groups (p > 0.05). Significant differences in correlations were found between depression scores and temporalis muscle thickness in the study group compared to the control group (r = 0.32 vs. −0.13, p = 0.011) as well as between anxiety scores and temporalis muscle thickness (r = 0.25 vs. −0.30, p = 0.002) No significant associations were found for the masseter muscle. Conclusions: Individuals with myalgia did not show increased muscle thickness compared to healthy individuals. Psychological distress, particularly depression and anxiety, was differentially related to temporalis muscle morphology in individuals with myalgia compared to healthy controls. Full article

With the advancement of 3D digital dentistry, accurate 3D tooth segmentation has become increasingly important in orthodontics and computer-aided diagnosis. However, existing supervised approaches heavily rely on exhaustive face-wise annotations and often exhibit limited generalization across complex clinical meshes. Although self-supervised learning offers a promising alternative to alleviate annotation costs, current paradigms remain challenged by sensitivity to data augmentations, suboptimal representation learning in pure masking schemes, and the complex structural characteristics of dental geometry. To address these limitations, we propose Dental-CMAE, a graph-enhanced hierarchical Contrastive masked AutoEncoder framework tailored for 3D tooth segmentation. The framework incorporates a dual-branch masking strategy that leverages graph-based structural priors to generate distinct corrupted views while preserving intrinsic mesh topology, thereby facilitating robust reconstruction. This is integrated with a feature-level contrastive objective designed to enforce semantic consistency between co-masked regions, which enhances representation discriminability without the requirement for negative sample queues. Additionally, the architecture utilizes a hierarchical multi-scale attention mechanism that partitions feature channels into parallel streams, enabling the simultaneous capture of fine-grained morphological variations and the overarching global dental arch context. Extensive experiments demonstrate that our Dental-CMAE consistently outperforms state-of-the-art fully supervised and self-supervised methods across multiple evaluation metrics. Specifically, our framework achieves an Overall Accuracy (OA) of 95.57%, a mean Intersection-over-Union (mIoU) of 88.14%, and a mean Accuracy (mAcc) of 90.85%. Supported by these quantitative findings, our method validates its effectiveness for robust 3D tooth segmentation, highlighting its strong potential to alleviate annotation bottlenecks and improve the reliability of automated 3D digital dental workflows. Full article

Objective: To report a rare case of pulp space tissue growth in a mature mandibular molar with severe endo-periodontal involvement after conservative endodontic treatment and to discuss the possible biological explanations, including regeneration and granulation tissue healing. Severe endo-periodontal lesions are challenging, particularly as endodontic regeneration is usually observed in immature teeth, while revascularization in mature teeth, especially in cases of advanced periodontal disease, is rare, as demonstrated in this case. Methods: This study reports a rare case of tissue regeneration versus granulation tissue healing in the pulp space, occurring alongside periodontal healing, in a mature mandibular molar with necrotic pulp and severe periodontal involvement. A 52-year-old patient presented with a mature mandibular molar (tooth #19) exhibiting necrotic pulp with severe endo-periodontal involvement, including grade-3 mobility, tenderness to percussion, a 12 mm probing depth, and extensive periradicular radiolucency. The tooth was diagnosed with necrotic pulp and symptomatic apical periodontitis and was deemed hopeless, with extraction planned. Results: Following patient refusal, endodontic treatment was initiated, including cleaning, shaping, and placement of the intracanal medicament, Ledermix. The patient canceled the extraction due to symptom resolution and disappeared for 12 months. On return, the patient presented with spontaneous pain exacerbated by thermal stimuli, consistent with symptoms of irreversible pulpitis. Clinical examination revealed significant clinical and radiographic improvements, including reduced probing depth (3 mm), no mobility, resolution of apical translucency, radiographic findings suggestive of canal narrowing, and a positive pulp sensibility response. Re-entry elicited profuse bleeding with newly formed vital tissue beneath the medicament. Sodium hypochlorite irrigation failed to achieve hemostasis; inflamed tissue was removed; root canals were cleaned, shaped and obturated; and treatment was completed with placement of a permanent coronal resin composite restoration. A forty-month follow-up showed an asymptomatic tooth with clinical and radiographic healing. Conclusions: This case demonstrates that conservative endodontic management may result in favorable clinical and radiographic outcomes in mature teeth with severe endo-peroidontal involvement, influencing extraction decisions. It provides clinical evidence suggestive of tissue regeneration and periodontal healing in a mature tooth with necrotic pulp and severe periodontal compromise, challenging conventional prognosis. The observed pulp space tissue growth may be suggestive of regeneration; however, alternative explanations, including granulation tissue healing or repair processes, cannot be excluded. Healing by granulation tissue in the pulp space remains possible. Root canal treatment in advanced endo-perio lesions can yield favorable outcomes and may influence extraction decisions. Further clinical and histological studies are needed to clarify underlying mechanisms and optimize treatment strategies. Full article

Background/Objectives: Pterygoid implant placement represents a valuable alternative to conventional bone grafting procedures in the rehabilitation of the atrophic posterior maxilla; however, the procedure remains technically demanding because of limited visibility, difficult access, complex pterygomaxillary anatomy, and the need for precise angulation and distal bicortical anchorage. Although digital guidance has increasingly been applied in implant dentistry, a clearly described workflow integrating automatic segmentation, selective virtual trimming of the posterior maxillary anatomy, and direct three-dimensional planning for static-guided pterygoid implant placement remains insufficiently detailed in the literature. The aim of this report was to describe and illustrate such a workflow in a proof-of-concept clinical application. Methods: This work was designed as a methodological proof-of-concept with a single clinical illustration. A CBCT dataset was imported into BlueSkyPlan, where automatic segmentation was used to generate three-dimensional models of the maxilla, teeth, and pterygoid process. The segmented volumes were then selectively trimmed to expose the relevant pterygomaxillary anatomy and to support direct three-dimensional planning of the implant axis in the rendered model. A static surgical guide with combined tooth and mucosal support was subsequently designed, positioned on a printed jaw model derived from the intraoral scan, and assessed by CBCT-based internal verification. Results: In this proof-of-concept application, the workflow enabled three-dimensional visualization of the pterygomaxillary trajectory, supported implant axis planning in the rendered model, and facilitated guide design and radiographic verification of the planned trajectory. The verification step provided an internal methodological consistency check between the planned implant axis and the drill-guided direction visible on CBCT. Conclusions: The present report describes a segmentation-assisted three-dimensional planning workflow for static-guided pterygoid implant placement in a single proof-of-concept clinical application. The workflow should be interpreted as a methodological illustration rather than a quantitative validation study. Further investigations are required to evaluate accuracy, inter-operator reproducibility, and broader clinical applicability. Full article

This systematic review critically examines the use of 2D and 3D digital imaging technologies of the face and teeth, with and without integration of artificial intelligence, for human identification in forensic and medicolegal contexts. Following PRISMA 2020 guidelines, Scopus, PubMed and Web of Science were systematically searched, identifying 26 studies published between 2011 and 2025 that met predefined eligibility criteria framed by a PECO-style question. Eighteen studies focused on facial imaging, six on dental imaging and two on integrated orofacial workflows, using digital photography, CCTV/video, 3D surface imaging, intraoral scanners, and three-dimensional superimposition methods, sometimes combined with classical algorithms and deep learning models. In controlled or semi-controlled settings, state-of-the-art facial algorithms often reported very high accuracy, with values up to 99.85%. By contrast, studies using real CCTV or other challenging forensic imagery showed more variable performance, with accuracies ranging from about 72.8% to 96.6%. Dental and orofacial studies reported 100% correct identifications for 3D superimposition of intraoral scans in small samples, and around 83% accuracy for automated AI-based dental identification. Crucially, fulfilling the promise of a true orofacial approach, this review proposes a structured research agenda focused on creating realistic multi-modal databases, standardizing protocols, and implementing probabilistic reporting (likelihood ratios) to guide future validation and legal admissibility. Full article

Selective laser melting (SLM) is an additive manufacturing method based on powder bed fusion that has gained prominence in prosthodontics for its capability to create intricate, patient-specific metal restorations with precision and consistency. SLM has become an important part of digital dental workflows, allowing for the direct creation of dental frameworks from computer-aided design (CAD), offering advantages over traditional casting and subtractive milling techniques. This review outlines the fundamentals of SLM, the dental alloys commonly employed, and the microstructural characteristics that affect mechanical properties, corrosion resistance, and biocompatibility. It explores current uses in removable partial denture frameworks, fixed dental prostheses, metal–ceramic restorations, implant-supported prosthetics, and maxillofacial rehabilitation. Alloys based on cobalt–chromium and titanium produced through SLM exhibit strong mechanical properties, fatigue resistance, and biological compatibility when suitable post-processing is conducted. Despite these advantages, issues such as surface roughness, porosity, anisotropy, powder handling, and high costs remain, and there is a lack of extensive long-term clinical data. Ongoing process refinement and clinical validation are crucial for the wider integration of SLM into standard prosthodontic practice. Full article

Background: Accurate digital impressions are crucial for the long-term success of implant-supported prostheses, with scan bodies playing a pivotal role in transferring the implant position into the virtual model. Recent work has focused on PEEK (polyether-etherketone) scan bodies because their optical behavior may facilitate intraoral scanning; however, the breadth and quality of supporting evidence remain unclear. Methods: This scoping review followed PRISMA-ScR reporting guidelines and was registered in the Open Science Framework (OSF; Registration DOI 10.17605/OSF.IO/CU3V8). Pub-Med/MEDLINE, Embase, and Scopus were searched through September 2025. Eligible designs included in vitro studies, randomized trials, observational studies, and technical reports evaluating PEEK scan bodies in implant dentistry. Screening and data extraction were performed in duplicate, and findings were synthesized descriptively. Results: The search identified 227 records, and after screening, 31 studies met the inclusion criteria. Most studies were in vitro, with limited clinical evidence, and only one prospective clinical study was identified. Outcomes commonly addressed trueness, precision, scan time, and handling. Comparators varied (e.g., titanium, resin; splinted vs. unsplinted), and the results on accuracy were heterogeneous, with deviations typically within clinically acceptable limits (<100 µm). Conclusions: PEEK scan bodies are applicable for digital implant impressions. Clinical data are sparse, though, and methods vary. Controlled clinical studies are necessary to confirm the accuracy, reliability, and indications of this approach compared to titanium ISBs. Full article

Background/Objectives: Metabolic syndrome (MetS) causes significant oral manifestations that negatively impact oral health-related quality of life (OHRQoL). This randomized controlled trial evaluated the effects of combined dental interventions and lifestyle guidance on OHRQoL in patients with MetS. Methods: In total, 82 participants with MetS were randomized into an intervention group (IG; n = 39), receiving dental treatment plus lifestyle guidance, or a control group (CG; n = 43), receiving lifestyle guidance only. OHRQoL was assessed using GOHAI and OHIP-14 at baseline, 1 month, and 3 months. Data were analyzed using repeated-measures ANOVA and multivariable ANCOVA, adjusting for age, sex, baseline OHRQoL, and waist circumference. Pearson correlations examined the relationship between metabolic changes (Δ) and OHRQoL. Results: At 3 months, the IG demonstrated significantly superior OHIP-14 scores (p = 0.020) and a large effect size in social disability (${\eta }_p^2$ = 0.148, p < 0.001) compared to the CG. Within-group analysis showed the IG achieved highly significant longitudinal improvements in pain and psychological discomfort (all p < 0.001). Subgroup analysis confirmed these gains were primarily driven by participants with missing teeth (${\eta }_p^2$ = 0.447, p < 0.001), whereas the periodontitis-only subgroup showed non-significant shifts. Multivariable analysis identified age and baseline scores as primary predictors. Notably, OHRQoL improvements significantly correlated with reductions in body weight (r = 0.355, p = 0.001) and waist circumference (r = 0.238, p = 0.031). Conclusions: Integrated dental and lifestyle interventions significantly improved OHRQoL in MetS patients by enhancing psychosocial well-being and social reintegration. Gains were functionally driven by systemic metabolic success. Addressing “nutritional barriers” through dental rehabilitation, while targeting weight loss goals, was essential for holistic MetS management. Full article

Background/Objective: To evaluate the reliability, diagnostic accuracy and time efficiency of an artificial intelligence (AI)-automated method (CephX) and a semiautomated method (INVIVO) for upper airway segmentation, the manual digital method (ITK-SNAP) was used as the reference standard. Methods: This retrospective study analyzed cone-beam computed tomography (CBCT) scans from 133 patients. The upper airway volume and narrowest cross-sectional area were measured via the three methods. Reliability and repeatability were assessed via the intraclass correlation coefficient (ICC). The time required for each segmentation method was also recorded and compared. Results: Both the AI-automated (ICC = 0.945) and semiautomated (ICC = 0.992) methods demonstrated excellent reliability for total volume measurements compared with the manual reference. For the narrowest area, the automated method showed excellent agreement (ICC = 0.943), whereas the semiautomated method showed good agreement (ICC = 0.868). All methods demonstrated excellent intrareader repeatability (ICC > 0.95) and high test–retest reliability. The AI-automated method was significantly more time-efficient, requiring less than 30 s per analysis, compared with 161.4 s for the semiautomated method and 336.6 s for the manual method. Conclusions: AI-automated and semiautomated segmentation methods are reliable and accurate alternatives to manual upper airway analysis. The AI-based approach offers a substantial advantage in time efficiency, making it a valuable tool for clinical practice. Full article

Background/Objectives: Modern dentistry focuses on the ongoing development of digital alternative technologies and the study of the properties of these innovative materials is deemed essential. Therefore, the objectives of this study were to evaluate the optical and surface characteristics of six computer-aided design/Computer-Aided Manufacturing (CAD-CAM) dental materials, both subtractive and additive, in relation to in vitro degradation. Methods: CAD-CAM dental materials, subtractively processed (Vita Enamic, Cerasmart, Brilliant and Tetric) and additively manufactured (Saremco Crowntec and Voco C&B), were prepared to standard dimensions of 14 × 10 × 1 mm, with baseline measurements taken prior to, and after, the degradation procedures, consisting of immersion in an ADA-recommended staining broth, artificial aging (thermocycling), and the combined effects of staining and in vitro aging. Additionally, two different surface treatments were investigated (polished and glazed). Results: The poorest color stability was observed for Tetric glazed specimens (mean value 25.585) subjected to staining, while the best performance was recorded for Brilliant polished Control (average value of 0.781). The staining procedure produced the most pronounced color changes. Surface treatment did not significantly affect color stability, and surface roughness was not influenced by either the degradation method or the surface treatment (p > 0.05). Atomic Force Microscopy (AFM) evaluation revealed superior performance of the glazed surfaces, characterized by lower nanoroughness values compared with polished surfaces and a smoother surface appearance. Conclusions: The staining potential of staining broth was demonstrated in this study, with the highest values recorded after the staining procedures. In addition, the influence of artificial aging alone and artificial aging combined with staining was investigated, providing relevant results for a better clinical approach. Moreover, surface treatment demonstrated reliability and therefore clinical applicability. Full article

Background: Oral healthcare workers play a pivotal role in exploring the significant potential of integrating oral healthcare with overall health within a healthcare system. This review aims to identify the main barriers and facilitators to integrating oral health into primary and general healthcare from the perspectives of oral healthcare professionals. Methods: The study adhered to the Arksey and O’Malley methodological framework for scoping reviews. Five main databases were systematically searched, namely Web of Science, PubMed, Scopus, ProQuest, and Embase, spanning from 1 January 2000 to 31 December 2024. The Rainbow Model served as the framework for content analysis, organizing the advantages, disadvantages, barriers, and facilitators into micro, meso, and macro levels. Results: Five integration domains were identified across macro, meso, and micro levels, illustrating how oral health can be systematically embedded within general health through the utilization of oral healthcare professionals. These domains encompassed chronic disease management (screening, counseling, and referral), emergency management, electronic health records, interprofessional education, and tele-dentistry, highlighting policy, organizational, and workforce levers for strengthening care integration, enhancing system efficiency, and improving access and equity. Conclusions: This scoping review synthesizes five integration domains and four cross-cutting strategic directions for embedding oral health within broader healthcare systems. By conceptualizing integration across macro, meso, and micro levels, the study provides a structured framework that may serve as a reference for policymakers, educators, and health service leaders. The findings highlight potential enablers, such as coordinated governance, workforce development, digital infrastructure, and community engagement, which could support integration. Full article