Perforations are complications that may occur during root canal treatment (RCT), requiring complex management if the tooth is to be retained. The influence of perforations and their management on long-term tooth retention and treatment costs remains unclear.
Here, we evaluate endodontic perforations and resulting or alternative treatments for their cost-effectiveness.
A Markov model was developed to follow a molar with a perforation occurring during RCT in an initially 25-year-old patient. The perforation was either managed by repair or tooth extraction with subsequent implant placement. The absence of a perforation served as a control. Our health outcome was the retention time of the tooth or implant. Tooth or implant costs, as well as costs for treatments during follow-up were drawn from public and private fee item catalogues (BEMA and GOZ) in Germany. Costs were calculated in euros (EUR) in the year 2025 and discounted at an annual rate of 3%. Transition probabilities were drawn from systematic reviews.
The cumulative retention time after RCT without perforation was 52.9 years at cumulative lifetime costs of 2000.78 EUR. Perforation repair resulted in a longer retention time of 49.4 years but was also more costly (3485.94 EUR) compared to extraction and implant placement, which yielded a retention time of 44.0 years at a cost of 2813.46 EUR. In the first 13 years after treatment, perforation repair dominated extraction and implant placement, with lower costs and higher effectiveness, because initially perforation repair was less expensive.
Perforation repair increases tooth retention time and comes with only limited or no additional costs depending on the age group. Perforations are associated with significant treatment needs and costs, and endodontic therapy should focus on avoiding them, likely justifying additional efforts if needed to do so.
To evaluate the performance of an artificial intelligence (AI) system in diagnosing pulp conditions in adult patients, using a modified Wolters diagnostic classification.
A cross-sectional study was conducted. Data from 200 teeth of 200 patients were collected. A clinical evaluation was performed, and a dataset containing 21 diagnostic attributes was compiled. A modified Wolters classification was used for more objective and reproducible diagnostic criteria. AI models (Decision Tree (DT), Support Vector Machine (SVM), Multi-Layer Perceptron (MLP), and XGBoost) were trained using a K-fold cross-validation approach. Hyperparameters were optimised, and model performance was assessed through precision, recall, F1-score and area under the receiver operating curves (AUCs). The final metrics were calculated over several iterations. To estimate model variability, bootstrap resampling was applied. Additionally, attribute importance was analysed using the permutation method.
The diagnoses were distributed in normal pulp (NP) (21.5%), initial pulpitis (IP) (13%), mild pulpitis (MIP) (21.5%), moderate pulpitis (MP) (25%) and severe pulpitis (SP) (19%). During validation, the models that achieved the highest performance were XGBoost (mean F1-score (0.85)) and SVM (mean F1-score (0.85)). Regarding ROC curve analysis, both models demonstrated AUC values exceeding 0.93 for all diagnostic classes. SVM reached perfect AUCs for SP and near-perfect values for NP (0.98), while XGBoost achieved a perfect AUC for NP and values above 0.90 for all other classes. Bootstrap analysis confirmed that XGBoost has the lowest variability and the best average values for precision (0.81), recall (0.81) and F1-score (0.80). On the other hand, pain to cold stimulus emerged as the most relevant attribute for diagnosis.
The AI-based system demonstrated significant potential for achieving accurate pulp diagnoses, contributing to more objective diagnostic decisions. Pain intensity in response to thermal stimuli and spontaneous pain was a key feature that allowed correct classification, highlighting its relevance in the diagnostic process.
Background: In recent years, many universities have incorporated engine-driven nickel-titanium (NiTi) instruments into their undergraduate endodontic programs, aiming to enhance the efficiency and precision of root canal treatments. While these techniques might offer advantages, concerns remain regarding their implementation, particularly in ensuring adequate training and supervision to prevent potential procedural errors that could compromise treatment outcomes.
Objectives: This systematic review and meta-analysis aimed to evaluate the quality of clinical root canal treatments performed by undergraduate students, comparing outcomes between the use of engine-driven NiTi files and stainless-steel hand files.
Methods: The search was conducted across four electronic databases up to April 2025. The selection process adhered to the Population, Intervention, Comparison, Outcomes and Study (PICOS) criteria, including clinical studies evaluating the quality of root canal treatments performed by undergraduate students using engine-driven NiTi files versus stainless-steel hand files. Study quality was assessed using the Risk of Bias 2 (RoB-2) tool for randomised clinical studies and Risk of Bias in Non-randomised Studies of Interventions (ROBINS-I) for nonrandomized studies. Meta-analyses were performed to compare the prevalence of adequate root canal treatment quality, root canal filling quality, and procedural errors between the two techniques, using RevMan 5.3 software. The Grading of Recommendations Assessment, Development, and Evaluation (GRADE) tool was applied to determine the overall certainty of evidence.
Results: Ten studies were included, with most demonstrating a high risk of bias. Meta-analyses revealed that engine-driven NiTi root canal preparation with both rotary and reciprocating instruments resulted in significantly higher quality of root canal treatment, improving root canal filling quality, and reducing the incidence of ledge formation compared to stainless-steel hand files. However, no significant differences were found between the techniques regarding overfilling, perforations, apical transportation, or instrument separation. The certainty of evidence was rated as low.
Conclusions: Engine-driven NiTi instruments improve the quality of root canal treatments performed by undergraduate students, particularly by enhancing filling quality and reducing ledge formation without increasing other iatrogenic risks. Nevertheless, these conclusions are based on evidence of low certainty.
Trial registration: This systematic review was registered in the PROSPERO database (CRD42024600660).
The study aims to experimentally characterize the flow inside lateral canals during ultrasonic irrigation. The effect of the canal angle as well as the relative position of the endodontic file with the inlet of the channel was quantified.
An idealized endodontic geometry was 3D printed and used as a mould to fabricate a channel made of PEG-modified hydrophilic PDMS. The mould comprises a 20 mm tapered (6%) root canal with a 0.4 mm apical diameter and a 5 mm long lateral canal with a 200 μm square cross section, forming an angle of either 90° or 60° with the axis of the root canal and placed 6 mm from the apex. The channel was filled with a NaI-water solution and seeded with 1 μm particles. An ultrasonic instrument with a 15# K-file was employed for the irrigation. The flow field was characterized by Particle Image Velocimetry.
The flow inside the lateral canals is notably affected by the position of the endodontic file. There is a competition between the impingement of the ultrasound-induced jets on the walls of the root canal and the recirculation flows around the file, leading to either flow into the lateral canal or suction phenomena that generate backflow towards the root canal. Aligning the jet with the axis of the lateral canal maximizes the magnitude of the velocities that can be achieved therein. This alignment can only be achieved in the 90° channel. Inclining the lateral canal to 60° leads to lower velocities and a domination of the backflows towards the root canal. In both cases, a recirculation zone forms near the inlet of the channel where transverse velocities are comparable with the axial ones. The recirculation zone length is affected by the inclination of the channel. Further inside the canal, the flow becomes uniaxial.
The flow during ultrasonic irrigation inside lateral features of the root canal is complex and considerably affected by the position of the endodontic file and the inclination of the channel. An optimum location of the file tip leads to maximization of the induced velocity inside the lateral canal, suggesting more effective cleaning.
A case report to describe the use of a novel 3D printed surgical decompression device to induce healing of large periapical lesions.
The development of periapical pathology is influenced by a variety of factors including local microbiology and pathophysiology. In large lesions, lone orthograde endodontic treatment is often insufficient in promoting healing of the periapical tissues and therefore is followed by apical surgery to reduce inflammation. While traditional surgical treatments often involve enucleation for cystic lesions, decompression techniques have shown to provide a less invasive alternative when combined with non-surgical and/or surgical endodontic treatment.
The case presented here is a 21-year-old male with a large periapical lesion involving a root canal-treated right maxillary central incisor and nasopalatine canal; extending from the maxillary right lateral incisor to the maxillary left central incisor and having perforated buccal and lingual cortical plates. Clinically, the patient reported an associated fluctuant, non-tender buccal swelling. CBCT confirmed a well-condensed root canal filling; hence, it was decided to first treat the lesion conservatively using only the surgical decompression technique. Following a discussion about treatment options, the patient consented to surgical decompression. CBCT imaging alongside digital software was used to fabricate a customised decompression device that was sutured in situ for 4 weeks. Nine months following the removal of the device, CBCT showed evidence of osseous deposition, with a significant reduction of the periapical radiolucency and separation from the nasopalatine canal, thus portraying the use of decompression in its own right as a treatment option.
Surgical decompression is not a novel technique, and the literature describes the use of various dental equipment such as suction tubing, needle hub, or dental dam material to facilitate decompression of a lesion. These devices have, however, shown to cause irritation, discomfort, and instability and are therefore not always effective in inducing healing. This case report describes the use of a novel digital workflow to fabricate a customised decompression device in the management of a large periapical lesion. The reduction of intra-cystic pressure alongside active irrigation reduced inflammatory compounds, contributing to a reduction in the lesion size and promoting osseous healing.
This study aimed to compare the shaping ability of 3 single-file systems in flat-shaped canals.
Thirty-six extracted mandibular incisors with flat-shaped canals were anatomically matched using micro-CT technology and assigned to three groups (n = 12) based on the single-file system used for root canal preparation: 1.5-mm SAF Infinitum, Reciproc Blue R25, or XP-endo Rise Shaper. After a new micro-CT scan, pre- and post-preparation datasets were co-registered and analysed to quantify changes in canal volume, surface area, unprepared canal areas, dentine thickness and hard-tissue debris volume. Parametric (One-way ANOVA, Student's t-test for repeated measures) and non-parametric (Kruskal–Wallis and Wilcoxon Signed Rank) tests were applied for statistical comparisons (α = 5%).
All groups showed significant increases in canal volume and surface area and reductions in unprepared canal areas after each preparation step (p < 0.05), with no significant differences among SAF Infinitum, Reciproc Blue and XP-endo Rise Shaper in shaping parameters at any time point (p > 0.05). Dentine thickness significantly decreased over time in all groups (p < 0.001), except for Reciproc at the buccal pericervical region and lingual midroot (p > 0.05), with greater reductions in the lingual pericervical region (SAF Infinitum) and mesiodistal mid-root level (Reciproc Blue and XP-endo Rise Shaper) (p < 0.05). Critically thin dentine areas (< 0.5 mm) were only observed mesiodistally at the mid-root level after preparation. Hard-tissue debris volumes did not differ significantly among groups (p > 0.05).
SAF Infinitum, Reciproc Blue and XP-endo Rise Shaper systems provide comparable shaping performance and dentine preservation in flat-shaped canals. While all systems cause some dentine thinning, critically thin areas remained limited and localised.
To describe an unusual case of post-traumatic trigeminal neuropathy affecting an accessory canal of the canalis sinuosus related to a maxillary central incisor.
This case report presents a 48-year-old female patient who suffered from neuropathic pain following the crown placement and endodontic treatment of a left maxillary central incisor (tooth 21). A cone beam computed tomographic (CBCT) scan of the anterior maxilla revealed an accessory canal apical to tooth 21, with extruded sealer within the bony channel. A sustained resolution of the patient's symptoms was achieved following apicectomy of the tooth and surgical resection of the accessory canal. The tooth remained asymptomatic at the 5-year follow-up.
This prognostic study aims to develop a machine learning (ML) survival model for estimating the longevity (success and survival rate) of restorations in endodontically treated teeth (ETT).
Data were consolidated from four controlled clinical trials conducted in the Netherlands and Brazil, involving 424 patients and 618 restorations with up to 17 years of follow-up. The evaluated predictive models included Gradient Boosting Survival, Random Survival Forests and Survival Support Vector Machine. The dataset was split into 70% for training and 30% for testing. Hyperparameter tuning was optimised via 10-fold cross-validation with 50 iterations using hyperopt. Performance was assessed through the time-dependent area under the ROC curve (AUC), concordance index (C-index), inverse probability of censoring weights (IPCW C-index) and time-dependent Brier score.
The Gradient Boosting Survival model achieved the highest AUC mean (0.83, 95% confidence interval [CI], 0.81–0.78), C-index (0.80), IPCW C-index (0.78) and Brier score (0.06) for survival rate predictions, maintaining predictive stability over time. For success rate, the Random Survival Forest model outperformed others (AUC = 0.73, 95% CI [0.70–0.75]), C-index (0.66), IPCW C-index (0.64) and Brier score (0.14). SHAP analysis identified patient age and tooth type as having the highest variable importance for survival, while the dentist's experience was critical for success outcomes. Fairness analysis revealed performance disparities across sexes and countries in the models.
The models demonstrated high predictive performance, mainly in survival rate prediction. ML models show promise for developing a robust, data-driven framework to evaluate success and survival outcomes in ETT.
To determine whether the combined use of periapical radiography (PR) and cone beam computed tomography (CBCT) improves agreement among three endodontic experts compared with using either diagnostic tool alone.
Sixty clinical records with CBCT scans were selected from cases performed by postgraduate and master's students in endodontics at the University of Barcelona Dental Hospital. Three endodontic experts independently evaluated each case using a standardised questionnaire. Initially, they assessed the PR images. After 4 months, they reassessed the cases using CBCT. One year later, they reviewed both PR and CBCT together. Agreement levels were analysed for pulpal and periradicular diagnoses, treatment recommendations and aetiological assessments.
Inter-observer agreement improved across the study phases, peaking in phase 3—particularly for treatment recommendations. In this final phase, where both PR and CBCT were evaluated together, the agreement rate for pulpal diagnosis was 73.33%, with substantial reliability (κ = 0.67). Periradicular diagnosis showed a 40.00% agreement rate, with moderate inter-observer concordance (κ = 0.44). The lowest agreement was observed in the aetiology category (28.33%), with moderate concordance (κ = 0.50). Agreement on treatment recommendations reached 43.33% (κ = 0.51) and was the only category to show statistically significant differences between phases (p = 0.01). No significant differences were found for pulpal diagnosis (p = 0.39), periradicular diagnosis (p = 0.19) or aetiology (p = 0.36). Intra-observer agreement varied among experts, with some showing lower consistency in their responses when evaluating PR, CBCT and the combination of both, highlighting the influence of imaging modality on clinical decision-making.
The combination of PR and CBCT improved inter-observer agreement across all categories compared to the use of a single imaging modality. However, this improvement reached statistical significance only for treatment recommendations. These findings suggest that, whereas combining PR and CBCT may support more consistent therapeutic decision-making, its impact on diagnostic agreement may vary depending on the specific diagnostic domain.
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