中华口腔医学杂志最新文献

Root canal therapy (RCT) is the most effective treatments for pulp and periradicular diseases. Its primary goals are to eliminate the infectious sources within the root canal system, cure the disease, and preserve the natural teeth. The therapeutic outcomes of RCT are influenced by multiple factors, including the patient's systemic health, tooth position, root canal anatomy, severity of infection, and the choice of instruments and treatment techniques. Establishing a difficulty assessment standard for RCT based on the anatomical characteristics of the Chinese root canal systems is crucial. By comprehensively considering the basic and additional factors related to intraoperative procedures, determining the distribution range of difficulty coefficients for each tooth position, and setting the grading criteria for RCT difficulty, clinicians can conduct pre-treatment assessments of the patient's systemic and oral conditions, as well as the specific conditions of the affected tooth and root canals. This pre-treatment evaluations and outcome predictions are keys to improve therapeutic efficacy. In 2004, Zhou Xuedong with her team spearheaded the formulation of the Difficulty Assessment Criteria for Root Canal Therapy by the Endodontics Committee of the Chinese Stomatological Association, which had since been widely promoted and applied. Based on advances in the understanding of the pathogenesis of endodontic diseases, Huang et al. proposed difficulty assessment for endodontic therapy in 2024. Building on recent evidence regarding tooth development and the anatomical characteristics of root canal system in the Chinese population, as well as in accordance with national requirements for clinical pathways and hierarchical diagnosis and treatment of RCT, this expert consensus was developed by 47 experts from 28 institutions across China. It further refines the clinical definitions and grading criteria for relevant risk factors. Through quantitative assessment, the consensus aims to identify potential treatment difficulties and risks before treatment, guide the selection of appropriate treatment strategies and operative techniques, and provide an objective preoperative assessment of case difficulty and treatment prognosis. It also establishes the correspondence between different levels of treatment difficulty and clinician competency, case referral, and clinical education. These measures are intended to facilitate effective clinician-patient communication, mitigate clinical risks, standardize clinical treatment pathways, and support hierarchical diagnosis and treatment of pulp and periradicular diseases based on treatment difficulty. Ultimately, the expert consensus aims to improve the success rate of RCT and tooth preservation, promoting the high-quality development of endodontics in China.

Due to differences in location and type of soft tissue defects, periodontal or peri-implant soft tissue augmentation surgeries vary significantly in surgical difficulty and prognostic outcomes. Based on the indicators including location and type of soft tissue defects, surgical difficulty and prognosis, this article divides soft tissue augmentation surgeries into five categories: augmentation in the pontic area, horizontal augmentation for natural teeth or implants, vertical augmentation for natural teeth or implants, keratinized gingiva widening surgery, and gingival papilla augmentation. It further elaborates on the clinical application scenarios of each type, and incorporates the authors' clinical experience, viewpoints and reflections.

Objective: To develop and evaluate artificial intelligence (AI) models for automated segmentation and three-dimensional (3D) landmark localization of the mandibular condyle on cone beam CT (CBCT) images, and to preliminarily investigate the 3D morphological developmental characteristics of the condyle from mixed dentition to early permanent dentition based on AI-assisted analysis. Methods: CBCT data of 639 patients (6-14 years old) with oral diseases (non-temporomandibular joint-related) who underwent imaging at the Department of Medical Imaging, College and Hospital of Stomatology, Anhui Medical University, between December 2021 and June 2024 were retrospectively collected. Of these, 100 cases were assigned to the condylar morphological analysis set and 539 to the AI model development set (training set: 443 cases; validation set: 49 cases; test set: 47 cases). Two clinicians independently performed condylar segmentation and annotated 12 osseous landmarks on the development set, and the annotations that passed consistency evaluation served as the ground truth. The PointRend model (adaptive point sampling) and the PoseNet-3D model (supervised learning with 3D Gaussian heatmaps) were separately trained on the training and validation sets. On the test set, the performance of the PointRend model was evaluated using the Dice similarity coefficient (DSC), 95% Hausdorff distance (HD95), and recall rate, and that of the PoseNet-3D model was evaluated using the mean radial error (MRE) and successful detection rate (SDR). The two models were then applied to the morphological analysis set to obtain condylar morphological parameters, including the anteroposterior diameter, mediolateral diameter, and height, as well as their bilateral means and absolute differences. Generalized Procrustes analysis (GPA), Pearson correlation analysis, principal component analysis (PCA), and K-means clustering were used to evaluate age-related condylar morphological differences, major sources of variation, and natural groupings. Results: The PointRend model achieved a DSC of 93.67%, a HD95 of (0.63±0.19) mm, and a recall rate of (89.27±5.91)%. The PoseNet-3D model achieved a MRE of (1.20±0.23) mm, with the SDR within 2.5 mm reaching 94.53%. The predominant trend in condylar morphology from 6 to 14 years of age was the enhancement of vertical features. K-means clustering partitioned the samples into three developmental stages (6-7, 8-10, and 11-14 years), and condylar height was the most discriminative growth parameter. Conclusions: The two AI models developed in this study enable automated segmentation and quantitative evaluation of three-dimensional condylar morphology, reveal the stage-specific developmental patterns and allometric growth of the condyle, and establish condylar growth reference values from mixed dentition to early permanent dentition.

Dental fluorosis alters the structure and acid resistance of dental hard tissues and impairs bonding performance. For fluorotic teeth requiring direct composite resin restorations, veneers/full-crown restorations for abnormal color and morphology, as well as orthodontic bracket bonding, reliable enamel-dentin bonding remains a key clinical concern. Based on the histopathological features of hard tissues in fluorotic teeth, this paper reviews advances in clinical-bonding research and summarizes appropriate clinical bonding strategies to inform clinical diagnosis, treatment and further related research.

Objective: To investigate the effects of storage conditions on the dimensional stability of peri-implant soft tissue (PIST) replicas, and to identify both the time-dependent deformation and the clinically acceptable storage duration. Methods: A patient who had received single dental implant and temporary prosthesis in the anterior aesthetic region undergoing final restoration was selected in October 2020 from Department of Oral Implantation, School of Stomatology, The Fourth Military Medical University. Based on digital impression, twenty-four maxillary die-trimmed arch and PIST replicas were fabricated by a digital light projection three-dimensional (3D) printer, followed by implant-level assembly. The combined models were enrolled into different groups according to storage conditions: light-exposed (n=12); and dark-stored (n=12). Storage times were divided into 0, 3, 5, 7, 14, 28, 60, 90 d. 3D model scanner was performed to obtain standard tessellation language (STL) files of the combined models within 24 h of printing completion, while models saved under experimental conditions were scanned to generate the ".stl" dataset. The dataset of N-Lit/Box-Tx was then pairwise aligned with the reference file (N-T0) using surface-matching software of Geomagic Control X, with the emergence profile defined as the region of interest (ROI). Root mean square error (RMSE) was used to conduct the dimensional stability of PIST replicas. Results: Two-dimensional deviation analysis using three-way ANOVA revealed that storage time (F=32.89, P<0.001) and storage condition (F=18.76, P<0.001) significantly influenced the dimensional stability of the emergence profile. The 3D RMSE increased significantly from day 5 onward (P<0.05) and did not reach a stable state by 90 d. At 90 d, the RMSE values in both groups reached their maxima, with (55.6±2.5) μm in the light-exposed group and (51.1±5.5) μm in the dark-stored group. Conclusions: The 3D-printed PIST replicas exhibited time-dependent deformation, with early changes being most pronounced. Light exposure accelerated instability in the emergence profile, while dark storage preserved dimensional stability.

Gingival epithelial cells and fibroblasts maintain oral mucosal homeostasis. In periodontitis, these cells undergo pathological reprogramming to drive chronic inflammation and tissue destruction. This review outlines the mechanisms underlying this transformation. Epithelial barrier disruption initiates inflammation, activating gingival fibroblasts via epithelial-derived extracellular vesicles, microbial engagement, and cytokines. These gingival fibroblasts differentiate into pro-inflammatory gingival fibroblasts such as those highly expressing serum amyloid A1 and those with a senescence-associated secretory phenotype. Cellular senescence, its associated secretory phenotype and epigenetic modifications synergistically stabilize these pathological phenotypes. Reprogrammed cells, including epithelial cells undergoing epithelial-mesenchymal transition and fibroblasts with a senescence-associated secretory phenotype, ultimately drive extracellular matrix degradation and alveolar bone resorption by overproducing matrix metalloproteinases and upregulating receptor activator of NF-κB ligand. Targeting pro-inflammatory gingival fibroblasts subpopulations may offer precision interventions for periodontitis.

High-translucency zirconia (4Y/5Y-TZP) is widely used in dental prosthetics due to its excellent aesthetic property. However, it is susceptible to low-temperature degradation (LTD) in the oral environment, leading to deterioration of mechanical and optical properties. This article systematically reviews the mechanisms, influencing factors, and in vitro simulation protocols of LTD, with a focus on its impact on the optical properties of high-translucency zirconia. Existing studies indicate that enhanced light scattering, which is the result of phase transformation, surface roughening, and microcracks induced by LTD, is the primary cause of optical degradation. Nevertheless, conflicting findings exist regarding in the influences of LTD on translucency and color difference. To optimize the esthetic properties of high-translucency zirconia, future efforts can be devoted to establish a standardized multi-factor coupled aging evaluation system and explore the relationship between the spatial distribution of phase transformation and optical degradation.

Adult dentition diastemata are induced by multiple factors including congenital developmental abnormalities, pathological remodeling of periodontal tissue, dentition defects, occlusal trauma and systemic metabolic diseases, and are frequently accompanied by a series of complications such as impaired masticatory function, compromised anterior esthetics and progressive periodontal destruction. Due to decreased alveolar bone remodeling activity and prolonged tooth movement cycle in adults, monodisciplinary treatment cannot simultaneously achieve balanced function, satisfactory esthetics and long-term dental arch stability. This paper systematically describes the classification criteria of adult dentition diastemata and establishes a hierarchical clinical decision-making system. Four clinical protocols are elaborated, namely orthodontic treatment alone, combined orthodontic-aesthetic restoration, orthodontic-implant rehabilitation, and integrated periodontal-orthodontic-restorative multidisciplinary therapy. A three-tiered standard for therapeutic efficacy evaluation is formulated. Patients are stratified into low-risk, medium-risk and high-risk groups based on periodontal status, severity of bone defects and systemic risk factors, with differentiated follow-up intervals, examination items and stepped intervention strategies proposed. The etiological factors contributing to post-treatment recurrence of adult dentition diastemata and corresponding preventive measures are also analyzed. This study provides clinical references for individualized multidisciplinary management of adult dentition diastemata.