International endodontic journal最新文献

Background: There is a strong association between root canal curvatures and iatrogenic complications during root canal treatment.

Introduction: This study compared the curvature of mesiobuccal (MB) and mesiolingual (ML) canals in mandibular first molars between sagittal and coronal planes using cone-beam computed tomography.

Methods: Two hundred mesial roots (400) canals from a Brazilian subpopulation were analysed. Curvature angles were measured in sagittal and coronal planes using Schneider's and Weine's methods, while curvature radii were calculated geometrically. The prevalence of S-shaped canals was also recorded. Curvature severity was classified according to the American Association of Endodontists Case Difficulty Assessment form, EndoApp, and modified versions incorporating curvature and radius. The influence of the angle measurement method and radius on case complexity was evaluated. Statistical analyses were performed using t-tests and chi-squared tests, with significance set at p ≤ 0.05.

Results: Sagittal planes showed significantly greater angles and smaller radii than coronal planes. Weine's method yielded consistently higher angles and smaller radii than Schneider's. Severe single curvatures (≥ 30°) were more frequent in sagittal planes, whereas S-shaped canals were more prevalent in coronal planes. MB was more often classified as higher difficulty than ML canals. Incorporating radius into the classification systems generally shifted cases towards greater severity.

Conclusions: Sagittal planes revealed more severe single curvatures, whereas coronal planes showed a higher prevalence of S-shaped canals. Weine's method resulted in greater curvature severity than Schneider's. Inclusion of radius increased case severity grading. These findings highlight the importance of considering both measurement method and projection plane in endodontic treatment planning and research.

Background: The ability of dental pulp stem cells (DPSCs) to undergo differentiation into odonto/osteogenic lineages is governed by complex cell signalling regulatory networks and interactions between cells and the extracellular matrix (ECM).

Aim: This article provides a comprehensive evaluation of cell signalling pathways and ECM that modulate odonto/osteogenic differentiation of DPSCs.

Methods: A comprehensive narrative review method was utilised to examine the key cell signalling mechanisms that govern odonto/osteogenic differentiation in DPSCs, aiming to clarify their significance and critically evaluate their prospective implications for future applications in dentine/pulp repair and regenerative strategies.

Results: Current literatures demonstrate that transforming growth factor-β (TGF-β), Wnt, Notch, and fibroblast growth factor (FGF) signalling, both individually and through interactions, influence stem cell fate. TGF-β1 is essential in regulating DPSC differentiation toward odonto/osteogenic lineages. Wnt signalling crucially contributes to reparative dentine formation, evidenced by its upregulation in animal models following pulp capping. Wnt activators significantly promote dentine regeneration. Notch signalling activates in the dental pulp niches, facilitating reparative dentinogenesis post-injury. Interactions between Notch and other pathways influence DPSC odonto/osteogenic differentiation. Basic fibroblast growth factor (bFGF) regulates DPSC stemness and differentiation, with factors such as dosage and exposure time influencing its biological impact. Furthermore, ECM components play a significant role in differentiating stem cells by enhancing biological factors in the microenvironment and providing physical support, thereby promoting dentine and pulp repair.

Conclusion: A comprehensive understanding of these regulatory mechanisms has the potential to augment insights into the control of DPSC differentiation and facilitate their utilisation in repair and regenerative therapies for the dentine-pulp complex.

Aim: This study was conducted to evaluate the effect of maintaining optimal serum vitamin D levels through supplementation on the healing rate and quality of newly formed bone at 3, 6, 9, and 12 months in teeth with periapical lesions following endodontic treatment. Additionally, TNF-α levels were measured to investigate whether the potential healing effect was related to the anti-inflammatory properties of vitamin D.

Methodology: This study was designed as a parallel, triple-blind, randomised controlled clinical trial registered at the Clinical Trials Registry. Seventy-three male patients with mature mandibular molars presenting with periapical lesions and meeting the inclusion criteria were allocated into two groups: the vitamin D group (n = 37) and the control group (n = 36). All patients received root canal treatment according to a standardised endodontic protocol. The vitamin D group received oral vitamin D supplements to raise serum 25(OH)D level to the optimal range (30-50 ng/mL), while the control group, with insufficient serum 25(OH)D levels (20-30 ng/mL), did not receive any supplementation. Periapical radiographs (pre-op, 3, 6, 9, 12 months), serum 25(OH)D (chemiluminescence), and TNF-α (ELISA) levels were assessed. The reduction in lesion area was calculated in mm2 and bone quality was assessed through fractal analysis. The data were statistically analysed using the Mann-Whitney U and Friedman tests (p < 0.05).

Results: Lesion area reduction was significantly greater in the vitamin D group versus the control group (p < 0.05). However, no significant difference was found between the vitamin D and control groups in terms of fractal analysis values and TNF-α levels (p > 0.05).

Conclusions: A more rapid decrease in periapical lesion size was observed in individuals with serum vitamin D levels maintained within the optimal range (30-50 ng/mL). It is concluded that optimising vitamin D levels by supplementation, when appropriate, may be beneficial for the healing process of teeth with periapical lesions.

Trial registration: ClinicalTrials.gov identifier: TCTR20221020006.

Aim: This study aimed to investigate the effects of copaiba oil-resin on induced apical periodontitis in rats.

Methodology: A total of 24 male Wistar rats were divided equally into three groups (eight animals each): control (C), apical periodontitis (AP) and apical periodontitis with copaiba administration (AP + COP). The AP was induced by exposing the pulp chambers of the mandibular first molars to the oral environment. The openings were maintained for 28 days to allow lesion development. The AP + COP group received systemic administration of 200 mg/kg of copaiba oil-resin via intragastric gavage during the final 7 days of the AP induction period. The rats were then euthanised, and their hemimandibles were subjected to histopathological analysis to assess tissue preservation, histochemical staining with picrosirius red to evaluate collagen content, and microcomputed tomography to assess lesion volume and bone quality parameters. Statistical analyses were performed using a one-way ANOVA, followed by Tukey's post hoc test for parametric data and the Kruskal-Wallis test for nonparametric data. The results are expressed as mean and standard error of the mean for parametric tests, and median and interquartile deviation for the nonparametric test.

Results: The findings showed that copaiba oil-resin reduced lesion volume compared to the untreated group (p = 0.0261), as well as reducing the space between the bone trabeculae found in the AP group (p = 0.0063). Additionally, copaiba oil-resin preserved the collagen fibres, which were more degraded in the untreated group (p = 0.0009). Histopathological analysis showed that copaiba oil-resin reduced tissue damage, preserving a significant area of alveolar bone surrounding the lesion.

Conclusions: These results indicate that copaiba oil resin has a promising adjunct therapeutic potential to reduce the bone loss caused by apical periodontitis and contribute to the maintenance of quality in the remaining bone.

Introduction: This study aimed to validate a commonly used in vitro methodology of testing the performance of the EALs. For that, clinical data obtained from teeth already scheduled for extraction were used to compare the accuracy and precision of an EAL in determining the position of the apical foramen in both clinical and laboratory settings using micro-CT imaging.

Methods: In a clinical setting, the working length of 11 canals was established using the Root ZX II apex locator. Subsequently, these teeth were extracted and imaged with and without the file in place using micro-CT technology. In vitro measurements of the working length were then obtained in these same teeth using an alginate model and new micro-CT scans were performed. Datasets were co-registered and the accuracy and precision of both in vivo and in vitro models were compared by measuring the distance from the file tip to a tangential line crossing the foramen margins, with a tolerance level of ±0.5 mm. Statistical comparisons were performed using Friedman post hoc Related Samples Sign and Bland-Altman tests with a significance level set at 5%.

Results: Statistical analysis revealed no significant difference between the accuracy (p = 0.368) and precision (p = 0.761) measurements obtained in both in vivo and in vitro conditions. Additionally, the Bland-Altman analysis revealed an agreement between in vivo and in vitro methods (p > 0.05).

Conclusions: The in vitro methodology using freshly mixed alginate demonstrated consistent accuracy and precision in identifying the position of the apical foramen, when compared to in vivo measurements.

Background: Inflammatory radicular cysts (IRCs) arise from periapical granulomas (PGs). IRCs originate from Malassez epithelial remnants (ERMs), which can proliferate under specific biological stimuli. Although ERMs are common within PGs, only a subset of lesions evolves into IRCs, suggesting that specific molecular and immunoregulatory mechanisms govern this selective transformation.

Objectives: Molecular mechanisms and cellular signalling pathways modulating the epithelial proliferation of the ERM represent an inflexion point in the progression from PG to IRC. The objective of this review is to analyse the mechanisms and pathways involved in uncontrolled ERM proliferation, intending to elucidate why only a subset of epithelium-containing PGs progress to IRCs.

Methods: A systematic literature search was conducted across MEDLINE (PubMed), Web of Science and Scopus from inception to July 2025. Sixty-one articles met the inclusion criteria for narrative analysis and synthesis.

Results: ERM proliferation emerges from a coordinated interplay between immune, stromal and epithelial compartments. Fibroblast growth factor-7 (FGF-7/KGF) activates the FGFR2-IIIb-MAPK/PI3K-AKT pathways, maintaining homeostasis of ERM proliferation. Transforming growth factor-β (TGF-β1/β2) and Smad2/3 signalling sustain epithelial quiescence. IGF-BP-6 sequesters bioavailable insulin growth factor (IGF-II), avoiding mitogenic signalling. Proteolytic cleavage of IGF-BP-6 releases bioactive IGF-II, enhancing ERM pathological proliferation. Intense AP upregulates epidermal growth factor (EGF) and its receptor (EGF-R), promoting uncontrolled ERM proliferation. IL-1β antagonises TGF-β/Smad2 suppression through NF-κB (p65) activation. IL-6 promotes pathological ERM proliferation and migration via classic and trans-signalling. Persistent M1 macrophage polarisation and Th1/Th17 dominance reinforce this microenvironment. Activated dendritic cells potentiate T-cell responses and cytokine release.

Conclusion: Not all PGs progress to IRCs because cystic transformation requires the convergence of epithelial, stromal and immune thresholds that override ERM quiescence. This review proposes an integrative theoretical model that redefines ERMs as dynamic, inflammation-responsive progenitors whose activation depends on immune-epithelial cross-talk rather than infection alone. By delineating specific biomarker clusters-epithelial, immune/co-stimulatory and stromal/remodelling-this work proposes a mechanistic framework capable of predicting lesion behaviour. It may establish the foundation for molecularly guided diagnosis and the rational design of targeted therapeutic strategies aimed at preventing or reversing cystic transformation, ultimately bridging molecular insight with clinical endodontic practice.

Aim: Artificial intelligence (AI) has the potential to aid clinicians in assessing case difficulty in endodontics. The objectives of this study were to develop and validate deep learning models for the detection of clinically negotiable MB2 canals in periapical images of maxillary first and second molars, and to compare the performance of AI models with that of human clinicians.

Methodology: A total of 1504 pre-operative periapical images of maxillary first and second molars that were treated by endodontic specialists were collected with clinical data as to the presence or absence of a clinically negotiable MB2 canal. Six pretrained supervised convolutional neural networks (ResNet-18, ResNet-50, ResNeXt-101, VGG-16, DenseNet-121 and MobileNetV2) and three self-supervised models (DINO, SimCLR and BYOL) were fine-tuned using fivefold cross-validation. Model performance was evaluated on a hold-out test set using accuracy, precision, sensitivity, specificity, and F1-score with 95% confidence intervals. Three independent clinicians (an endodontist, an endodontic resident, and an oral and maxillofacial radiologist) also assessed the test set.

Results: In cross-validation, ResNet-50 achieved the highest mean accuracy (67.6%), while DINO was the top-performing self-supervised model (62.8%). ResNet-18, ResNet-50, ResNeXt-101, DenseNet-121 and DINO significantly outperformed BYOL (p < 0.01), while no significant differences were observed among the top-performing models. ResNet-18 achieved the highest accuracy at 66.0% (95% CI, 63.0-68.9) on the test set while human expert accuracy ranged from 53.6% to 61.4%. Stratified analysis showed a general trend for improved AI model performance in maxillary first molars and in teeth without full-crown restorations. There was no significant difference in the accuracy of the top-performing AI model and human experts (p > 0.05).

Conclusion: Deep learning models performed similarly to clinician experts in identifying clinically negotiable MB2 canals in periapical images of maxillary first and second molars. These findings support the potential role of AI in endodontic case difficulty assessment.