Post-operative pain in non-surgical root canal treatment after sealer-based obturation versus warm vertical compaction: A randomized clinical trial.

AIM: Post-operative pain may occur after non-surgical root canal treatment (NSRCT). The root filling technique and choice of sealer may be contributing factors. This randomized controlled clinical trial compared post-operative pain and analgesics intake after NSRCT using a sealer-based obturation technique (SBO) with single-cone gutta-percha and calcium silicate sealer (CSS) versus a warm-vertical compaction (WVC) technique with gutta-percha and a resin-based sealer (RBS). METHODOLOGY: This study was designed as a parallel-two arm, double-blind, randomized superiority clinical trial registered at www. CLINICALTRIALS: gov (NCT04753138). Patients referred for NSRCT fulfilling the inclusion criteria participated in this study. Pre-operative periapical radiographs and CBCT scans were taken and numerical rating scale (NRS) pain scores were recorded. Upon completion of canal instrumentation, participants were randomly allocated to either Group SBO: SBO with CSS or Group WVC: Warm-vertical compaction with RBS. Post-operative pain and analgesics intake were recorded at 1, 3 and 7 days after endodontic treatment completion. Non-parametric Mann-Whitney U and Friedman tests and a generalized estimating equation were used to assess differences in pain scores between the groups, within each treatment group at different time points and for correlations, respectively. RESULTS: The study included 195 participants (212 teeth). One participant declined to submit the NRS form. Therefore, 194 participants (211 teeth) were included in the final analysis (99.5% response rate). No statistically significant differences in post-operative pain or analgesic intake existed between the two groups at any time point (p > .05). Age, pre-operative pain, apical diagnosis and post-operative analgesic intake were significantly related to post-operative pain (p < .05). CONCLUSIONS: Sealer-based obturation technique with CSS was associated with similar post-operative pain levels and analgesics intake as WVC with RBS. Regarding post-operative pain, SBO with CSSs may be a suitable clinical alternative.

PRIDASE 2024 guidelines for reporting diagnostic accuracy studies in endodontics: A consensus-based development.

Studies investigating the accuracy of diagnostic tests should provide data on how effectively they identify or exclude disease in order to inform clinicians responsible for managing patients. This consensus-based project was undertaken to develop reporting guidelines for authors submitting manuscripts, which describe studies that have evaluated the accuracy of diagnostic tests in endodontics. These guidelines are known as the Preferred Reporting Items for Diagnostic Accuracy Studies in Endodontics (PRIDASE) 2024 guidelines. A nine-member steering committee created an initial checklist by integrating and modifying items from the Standards for Reporting of Diagnostic Accuracy (STARD) 2015 checklist and the Clinical and Laboratory Images in Publications (CLIP) principles, as well as adding a number of new items specific to the specialty of endodontics. Thereafter, the steering committee formed the PRIDASE Delphi Group (PDG) and the PRIDASE Online Meeting Group (POMG) in order to collect expert feedback on the preliminary draft checklist. Members of the Delphi group engaged in an online Delphi process to reach consensus on the clarity and suitability of the items in the checklist. The online meeting group then held an in-depth discussion on the online Delphi-generated items via the Zoom platform on 20 October 2023. According to the feedback obtained, the steering committee revised the PRIDASE checklist, which was then piloted by several authors when preparing manuscripts describing diagnostic accuracy studies in endodontics. Feedback from this process resulted in the final version of the PRIDASE 2024 checklist, which has 11 sections and 66 items. Authors are encouraged to use the PRIDASE 2024 guidelines when developing manuscripts on diagnostic accuracy in endodontics in order to improve the quality of reporting in this area. Editors of relevant journals will be invited to include these guidelines in their instructions to authors.

Knowledge of undergraduate and postgraduate dental students about managing traumatic dental injuries based on the 2020 International Association of Dental Traumatology guidelines: A online survey of 10 dental schools from 10 countries.

BACKGROUND/AIM: The knowledge of dental students about managing traumatic dental injuries (TDIs) may not be uniform, depending on global location and dental education. The aim of this study was to evaluate the level of knowledge of undergraduate and postgraduate students specializing in endodontics and pediatric dentistry at 10 dental schools in 10 countries about the 2020 International Association of Dental Traumatology (IADT) guidelines regarding the management of TDIs. MATERIALS & METHODS: A previously published questionnaire was used in the current survey. It was an online survey with 12 questions regarding the management of TDIs and some additional questions regarding sociodemographic and professional profiles of the participants were added. The survey was distributed to final-year undergraduate students and postgraduate students in pediatric dentistry and endodontics from 10 dental schools. Simple frequency distributions and descriptive statistics were predominantly used to describe the data. Differences in the median percentage scores among the student categories were assessed using the Kruskal-Wallis test followed by Dwass-Steel-Critchlow-Fligner pairwise comparisons. RESULTS: A total of 347 undergraduates, 126 postgraduates in endodontics, and 72 postgraduates in pediatric dentistry from 10 dental schools participated in this survey. The postgraduates had a significantly higher percentage score for correct responses compared with the undergraduates. No significant difference was observed between the endodontic and pediatric dentistry postgraduates. CONCLUSION: The knowledge possessed by undergraduate and postgraduate students concerning the IADT-recommended management of TDIs varied across the globe and some aspects were found to be deficient. This study emphasizes the critical importance of reassessing the teaching and learning activities pertaining to the management of TDIs.

Present status and future directions: Surgical endodontics.

Endodontic surgery encompasses several procedures for the treatment of teeth with a history of failed root canal treatment, such as root-end surgery, crown and root resections, surgical perforation repair and intentional replantation. Endodontic microsurgery is the evolution of the traditional apicoectomy techniques and incorporates high magnification, ultrasonic root-end preparation and root-end filling with biocompatible filling materials. Modern endodontic surgery uses the dental operating microscope, incorporates cone-beam computed tomography (CBCT) for preoperative diagnosis and treatment planning, and has adopted piezoelectric approaches to osteotomy and root manipulation. Crown and root resection techniques have benefitted from the same technological advances. This review focuses on the current state of root-end surgery by comparing the techniques and materials applied during endodontic microsurgery to the most widely used earlier methods and materials. The most recent additions to the clinical protocol and technical improvements are discussed, and an outlook on future directions is given. Whilst nonsurgical retreatment remains the first choice to address most cases with a history of endodontic failure, modern endodontic microsurgery has become a predictable and minimally invasive alternative for the retention of natural teeth.

Prevalence of dens invaginatus and its association with periapical lesions in a Western Indian population-a study using cone-beam computed tomography.

OBJECTIVES: This study aimed to assess the prevalence of dens invaginatus (DI) and its association with periapical lesions (PLs) in a Western Indian population by means of cone-beam computed tomography (CBCT). MATERIALS AND METHODS: CBCT volumes of 5201 subjects were evaluated. Associations among gender, tooth type, DI type (Oehler's classification), and presence of PL were investigated. PL was codified using Estrela's Cone Beam Computed Tomography Periapical Index (CBCTPAI). Chi-square tests and descriptive statistics were used at p = 0.05. RESULTS: Overall, 7048 CBCTs were assessed, containing 19,798 maxillary and mandibular anteriors, of which 77 maxillary teeth demonstrated DI (0.39% of all anteriors). Of all 5201 subjects, 57 had DI (1.1%). Bilateral DI was more common in females than in males (p = 0.046). DI type distribution was as follows: type I (22.1%), type II (61.03%), type IIIa (10.4%), and type IIIb (6.5%), which was significantly different (p < 0.001). Maxillary lateral incisors were the most associated with PL (p < 0.001). Type I was frequently associated with CBCTPAI scores 1 and 2 (absence of PL), whereas types II, IIIa, and IIIb were associated with CBCTPAI scores 3, 4, and 5 (presence of PL). CONCLUSIONS: A prevalence of 1.1% identifies DI as a common developmental tooth anomaly in a Western Indian subpopulation. The percentage of maxillary anteriors affected by DI and associated PLs should be considered before diagnosis and treatment planning. CLINICAL RELEVANCE: Knowledge about the prevalence of DI and its subtypes, and their association with/without periapical pathosis may aid clinicians in treatment planning and execution to improve patient outcomes.

Comparison of loupes versus microscope-enhanced CAD-CAM crown preparations: A microcomputed tomography analysis of marginal gaps.

STATEMENT OF PROBLEM: Long-term restoration success depends on a precision marginal fit to prevent marginal leakage and caries. The successful fit of a computer-aided design and computer-aided manufactured (CAD-CAM) crown may be affected by different workflow variables, including preparation, scanning, crown design, milling, sintering, and cementation. Discrepancies in any of these steps may result in poor marginal and internal fit. Evidence suggests that tooth preparation may be the most important step in the workflow for a successful outcome. Compared with the traditional means of crown preparation using the naked eye or loupes, the dental operating microscope provides higher magnification and more direct illumination. However, the impact of high magnification during preparation on the marginal quality of CAD-CAM crowns is unclear. PURPOSE: The purpose of this in vitro study was to compare marginal fits of CAD-CAM crowns fabricated after initial preparation with loupes and subsequent preparation refinement with either loupes or a microscope. The null hypothesis was that no significant difference would be found in the marginal gap between the preparations with loupes and those with a microscope. MATERIAL AND METHODS: Mounted extracted molars (N=18) received initial crown preparations with a coarse grit, rounded shoulder, diamond rotary instrument with loupes of ×3.0 magnification. The teeth were then randomly divided into 2 groups and refined for an additional 2 minutes with fine grit, rounded shoulder, diamond rotary instruments with either loupes (LOUP) or a microscope up to ×10.0 magnification (DOM). The prepared teeth were scanned with an intraoral scanner to fabricate zirconia-reinforced lithium silicate crowns manufactured with a 4-axis milling machine, sintered in a dental furnace in accordance with the manufacturer's instructions, and cemented with self-adhesive resin cement. All teeth with crowns were mounted and scanned with a microcomputed tomography (µCT) system at 21-µm nominal voxel size. The resulting Digital Imaging and Communications in Medicine (DICOM) images were imported into a semiautomatic segmentation software program. Marginal and absolute gaps were measured at 24 consistent circumferential points per specimen. Absolute gaps were labeled, and the total volume was calculated. Paired and unpaired t tests were used for statistical analysis (α=.05). RESULTS: The mean marginal gap was 145.0 ±259.6 µm for LOUP and 35.6 ±110.6 µm for DOM, with a statistically significant difference (P<.001). The mean gap volume for LOUP was 0.975 ±0.811 mm3, and 0.250 ±0.477 mm3 for DOM, also statistically significantly different (P=.023). A significant difference was found between the absolute and marginal gaps for LOUP (P=.007), but for DOM, the difference was not significant (P=.063). CONCLUSIONS: This study demonstrated that the higher magnification used during tooth preparation played a significant role in the size of marginal gaps present around CAD-CAM crowns. Crown preparations finished by using fine grit diamond rotary instruments with a microscope at higher magnification than loupes resulted in a more precise marginal fit with smaller gaps.

Leveraging Pretrained Transformers for Efficient Segmentation and Lesion Detection in Cone-Beam Computed Tomography Scans.

INTRODUCTION: Cone-beam computed tomography (CBCT) is widely used to detect jaw lesions, although CBCT interpretation is time-consuming and challenging. Artificial intelligence for CBCT segmentation may improve lesion detection accuracy. However, consistent automated lesion detection remains difficult, especially with limited training data. This study aimed to assess the applicability of pretrained transformer-based architectures for semantic segmentation of CBCT volumes when applied to periapical lesion detection. METHODS: CBCT volumes (n = 138) were collected and annotated by expert clinicians using 5 labels - "lesion," "restorative material," "bone," "tooth structure," and "background." U-Net (convolutional neural network-based) and Swin-UNETR (transformer-based) models, pretrained (Swin-UNETR-PRETRAIN), and from scratch (Swin-UNETR-SCRATCH), were trained with subsets of the annotated CBCTs. These models were then evaluated for semantic segmentation performance using the Sørensen-Dice coefficient (DICE), lesion detection performance using sensitivity and specificity, and training sample size requirements by comparing models trained with 20, 40, 60, or 103 samples. RESULTS: Trained with 103 samples, Swin-UNETR-PRETRAIN achieved a DICE of 0.8512 for "lesion," 0.8282 for "restorative materials," 0.9178 for "bone," 0.9029 for "tooth structure," and 0.9901 for "background." "Lesion" DICE was statistically similar between Swin-UNETR-PRETRAIN trained with 103 and 60 images (P > .05), with the latter achieving 1.00 sensitivity and 0.94 specificity in lesion detection. With small training sets, Swin-UNETR-PRETRAIN outperformed Swin-UNETR-SCRATCH in DICE over all labels (P < .001 [n = 20], P < .001 [n = 40]), and U-Net in lesion detection specificity (P = .006 [n = 20], P = .031 [n = 40]). CONCLUSIONS: Transformer-based Swin-UNETR architectures allowed for excellent semantic segmentation and periapical lesion detection. Pretrained, it may provide an alternative with smaller training datasets compared to classic U-Net architectures.

Uncertainty-based Active Learning by Bayesian U-Net for Multi-label Cone-beam CT Segmentation.

INTRODUCTION: Training of Artificial Intelligence (AI) for biomedical image analysis depends on large annotated datasets. This study assessed the efficacy of Active Learning (AL) strategies training AI models for accurate multilabel segmentation and detection of periapical lesions in cone-beam CTs (CBCTs) using a limited dataset. METHODS: Limited field-of-view CBCT volumes (n = 20) were segmented by clinicians (clinician segmentation [CS]) and Bayesian U-Net-based AL strategies. Two AL functions, Bayesian Active Learning by Disagreement [BALD] and Max_Entropy [ME], were used for multilabel segmentation ("Lesion"-"Tooth Structure"-"Bone"-"Restorative Materials"-"Background"), and compared to a non-AL benchmark Bayesian U-Net function. The training-to-testing set ratio was 4:1. Comparisons between the AL and Bayesian U-Net functions versus CS were made by evaluating the segmentation accuracy with the Dice indices and lesion detection accuracy. The Kruskal-Wallis test was used to assess statistically significant differences. RESULTS: The final training set contained 26 images. After 8 AL iterations, lesion detection sensitivity was 84.0% for BALD, 76.0% for ME, and 32.0% for Bayesian U-Net, which was significantly different (P < .0001; H = 16.989). The mean Dice index for all labels was 0.680 ± 0.155 for Bayesian U-Net and 0.703 ± 0.166 for ME after eight AL iterations, compared to 0.601 ± 0.267 for Bayesian U-Net over the mean of all iterations. The Dice index for "Lesion" was 0.504 for BALD and 0.501 for ME after 8 AL iterations, and at a maximum 0.288 for Bayesian U-Net. CONCLUSIONS: Both AL strategies based on uncertainty quantification from Bayesian U-Net BALD, and ME, provided improved segmentation and lesion detection accuracy for CBCTs. AL may contribute to reducing extensive labeling needs for training AI algorithms for biomedical image analysis in dentistry.

Artificial Intelligence in Endodontic Education.

AIMS: The future dental and endodontic education must adapt to the current digitalized healthcare system in a hyper-connected world. The purpose of this scoping review was to investigate the ways an endodontic education curriculum could benefit from the implementation of artificial intelligence (AI) and overcome the limitations of this technology in the delivery of healthcare to patients. METHODS: An electronic search was carried out up to December 2023 using MEDLINE, Web of Science, Cochrane Library, and a manual search of reference literature. Grey literature, ongoing clinical trials were also searched using ClinicalTrials.gov. RESULTS: The search identified 251 records, of which 35 were deemed relevant to artificial intelligence (AI) and Endodontic education. Areas in which AI might aid students with their didactic and clinical endodontic education were identified as follows: 1) radiographic interpretation; 2) differential diagnosis; 3) treatment planning and decision-making; 4) case difficulty assessment; 5) preclinical training; 6) advanced clinical simulation and case-based training, 7) real-time clinical guidance; 8) autonomous systems and robotics; 9) progress evaluation and personalized education; 10) calibration and standardization. CONCLUSIONS: AI in endodontic education will support clinical and didactic teaching through individualized feedback; enhanced, augmented, and virtually generated training aids; automated detection and diagnosis; treatment planning and decision support; and AI-based student progress evaluation, and personalized education. Its implementation will inarguably change the current concept of teaching Endodontics. Dental educators would benefit from introducing AI in clinical and didactic pedagogy; however, they must be aware of AI's limitations and challenges to overcome.

Comparison of Reverse Sandwich Restorations Versus Composite Fillings for the Restoration of External Cervical Resorptions: An In-Vitro Study.

OBJECTIVE: The aim was to compare the 'reverse sandwich restoration' to resin composite restorations re- garding marginal adaptation, fracture resistance, favourable/unfavourable fractures in the management of external cervical resorption. METHODS: Forty-eight extracted maxillary central incisors were selected and endodontically treated. Cervical regions of the labial root surfaces received simulated resorptive defects and were restored as three randomly allocated groups: Reverse Sandwich Restoration (resin composite + resin-modified glass ionomer) (RSR); resin composite restoration (COMP), and no restoration (NR). Each group was further divided into two subgroups (n=8 each): Thermomechanical Aging (TA) (equivalent to one year) and No Aging (NA). Marginal adaptation was scored by scanning electron microscopy. Fracture resistance was tested using a universal testing machine. Favourable versus unfavourable fractures were classified based on fracture extent. RESULTS: TA decreased the marginal adaptation for both RSR and COMP. Mean fracture resistance per groups were: RSR-NA 1522.4+-94.9N, RSR-TA 939.6+-72.9N, COMP-NA 1197.6+-95.7N, COMP-TA 870.4+-86.3N, NR-NA 1057.1+-88.1N, and NR-TA 836.6+-81.9N, respectively. Fracture resistance was the highest for RSR- NA compared to all other groups (p<0.05). TA decreased the fracture resistance in all groups (p<0.05), there was no significant difference between RSR and COMP regarding fracture resistance and favourable/ unfavourable fractures (p>0.05). CONCLUSION: RSR provided comparable results to resin composite fillings to restore artificial cervical defects pertaining to marginal adaptation, fracture resistance, and favourable versus unfavourable fractures. RSR is preferable due to its inherent biocompatibility to the periodontium. (EEJ-2023-04-050).

XP-endo Finisher effectively reduces hard-tissue debris accumulated in root canals with isthmus after preparation with a reciprocating file system.

This study compared the accumulated hard-tissue debris (AHTD) after preparation with WaveOne Gold (WOG) to XP-endo Shaper (XPS), without and with a supplementary step using XP-endo Finisher (XPF) using clinically applicable irrigation. Twenty-four mesial roots with two canals and single foramen were micro-CT-scanned and matched. Scans were also taken after preparation with WOG or XPS, and after XPF. Irrigation with 2.5% NaOCl (total: 17 ml per canal) and 17% EDTA (2.5 ml per canal) was performed using a 30ga Max-I-Probe needle placed up to the working length. Morphological parameters were calculated and compared within and among groups. XPF significantly reduced unprepared area within XPS and WOG groups, and AHTD within WOG (p < 0.05). There were no significant differences between WOG and XPS after preparation and after XPF (p > 0.05). In conclusion, WOG and XPS produced a similar volume of AHTD, but the supplementary step with XPF decreased the AHTD in the WOG group.

Effect of Preoperative Oral Steroids in Comparison to Anti-inflammatory on Anesthetic Success of Inferior Alveolar Nerve Block in Mandibular Molars with Symptomatic Irreversible Pulpitis-A Double-blinded Randomized Clinical Trial.

INTRODUCTION: This randomized double-blinded trial aimed to compare the anesthetic success of inferior alveolar nerve blocks (IANBs) with 2% lidocaine in mandibular molars with symptomatic irreversible pulpitis (SIP) after oral premedication of prednisolone, dexamethasone, and ketorolac with placebo. METHODS: One hundred eighty-four patients diagnosed with SIP in mandibular molars randomly received prednisolone, dexamethasone, ketorolac, or placebo (n = 46 each) 60 minutes before the administration of an IANB. The access cavity preparation was initiated after successfully confirming lip numbness and two consecutive negative responses to electric pulp testing. The success of the anesthesia was clinically confirmed when pain was absent during the endodontic access or instrumentation. A one-way analysis of variance test was used to compare quantitative variables among the groups, and chi-square tests were used for comparing categorical variables. Binary logistic regression was performed to analyze the relationship of age, preoperative pain, and preoperative medications. RESULTS: When premedicated with oral dexamethasone, ketorolac, prednisolone, and placebo, the success rate of IANB was determined to be 60.86 %, 65.21 %, 56.52 %, and 21.73 %, respectively. Compared to the placebo, the success rate of IANB was significantly increased when patients were premedicated with prednisolone, dexamethasone, or ketorolac. However, there were no statistically significant differences among prednisolone, dexamethasone, and ketorolac. One individual in the ketorolac group reported gastritis, whereas no adverse effects were reported in the dexamethasone or prednisolone groups. CONCLUSIONS: Preoperative use of oral ketorolac, dexamethasone, or prednisolone may increase the anesthetic efficacy of IANB in mandibular molars with SIP.

Assessment of biomechanical behavior of immature non-vital incisors with various treatment modalities by means of three-dimensional quasi-static finite element analysis.

The objectives of this study were to evaluate the stress distribution and risk of fracture of a non-vital immature maxillary central incisor subjected to various clinical procedures using finite element analysis (FEA). A three-dimensional model of an immature central incisor was developed, from which six main models were designed: untreated immature tooth (C), standard apical plug (AP), resin composite (RC), glass-fibre post (GFP), regeneration procedure (RET), and regeneration with induced root maturation (RRM). Mineral trioxide aggregate (MTA) or Biodentine® were used as an apical or coronal plug. All models simulated masticatory forces in a quasi-static approach with an oblique force of 240 Newton at a 120° to the longitudinal tooth axis. The maximum principal stress, maximum shear stress, risk of fracture, and the strengthening percentage were evaluated. The mean maximum principal stress values were highest in model C [90.3 MPa (SD = 4.4)] and lowest in the GFP models treated with either MTA and Biodentine®; 64.1 (SD = 1.7) and 64.0 (SD = 1.6) MPa, respectively. Regarding the shear stress values, the dentine tooth structure in model C [14.4 MPa (SD = 0.8)] and GFP models [15.4 MPa (SD = 1.1)] reported significantly higher maximum shear stress values compared to other tested models (p < 0.001), while no significant differences were reported between the other models (p > 0.05). No significant differences between MTA and Biodentine® regarding maximum principal stress and maximum shear stress values for each tested model (p > 0.05). A maximum strain value of 4.07E-03 and maximum displacement magnitude of 0.128 mm was recorded in model C. In terms of strengthening percentage, the GFP models were associated with the highest increase (22%). The use of a GFP improved the biomechanical performance and resulted in a lower risk of fracture of a non-vital immature maxillary central incisor in a FEA model.

Radiology in Endodontics.

Endodontics requires radiographic imaging for diagnosis, treatment planning, therapy, and follow-up. Dental radiography allows for the identification of pathologic changes in the periradicular tissues that cannot be visualized by clinical inspection. For the precise execution of endodontic therapy, regular radiographic verification of individual treatment steps is necessary. As a review for clinicians, normal and pathologic findings relevant to Endodontics are presented. Key radiographic imaging techniques, such as the paralleling and bisecting techniques, as well as horizontal and vertical eccentric radiographs, are discussed. The increasing utilization and impact of cone-beam computed tomography providing 3-dimensional volume imaging are reviewed.

Novel 3D segmentation for reliable volumetric assessment of the nasal airway: a CBCT study.

OBJECTIVE: Nasal airway obstruction affects up to one-third of Americans and is one of the most common complaints by patients to otolaryngologists. Nasal airway obstruction and obstructive sleep apnea syndrome (OSAS) are closely related. The aim of this study was to use the 3D imaging software, ITK-SNAP as a platform to define a gold standard for anatomically accurate boundaries of the nasal airway in 3D CBCT and to create a more reliable and precise 3D CBCT segmentation of the nasal airway for assisting diagnosis, treatment, and monitoring of nasal airway obstruction and OSAS. METHOD AND MATERIALS: After review of the literature to identify established parameters using CBCT and CT technology for the segmentation of the nasal airway, and the existing drawbacks, a gold standard for locating the anatomical boundaries of the nasal airway using CBCT is proposed. This new method aims at standardization of segmentation and quantification, allowing for more reliable comparison between studies. ITK-SNAP software was used to segment three CBCT samples of healthy patients aged 21 to 59 years, who were patients of record, with CBCT obtained for either orthodontic, endodontic, or prosthodontic treatment planning purposes.
Results: The literature search identified 11 studies describing nasal airway parameters utilizing CBCT and CT. A great variation was detected on where the anatomical boundaries for the nasal airway were selected. A new standard in the identification of anatomical boundaries of the nasal airway is proposed for consistent segmentation and quantification using 3D CBCT by using the following landmarks: the inferior ANS-PNS border, the anterior nares border, the posterior sella-PNS border, and superiorly the border in alignment with the base of the skull (excluding the ostia, frontal, ethmoidal, and sphenoidal air cells). The three segmented samples were volumetrically measured, and statistically analyzed. The mean average Hounsfield unit intensity using the CBCT samples in this study was 629 with a standard deviation of 190.
Conclusion: The literature indicates a lack of a gold standard using CBCT technology for the segmentation of the nasal airway. With the proposed standard in this study, it is possible to quantify the nasal airway volume and thereby its reduction. For the general dental practitioner, this is an important aspect during the evaluation of overall airway assessment. This information can be useful in the diagnosis and treatment of airway compromised dental patients. (Quintessence Int 2021;52:154-164; doi: 10.3290/j.qi.a45429).

A Modified Partial Platform Technique to Retrieve Instrument Fragments from Curved and Narrow Canals: A Report of 2 Cases.

Two cases are reported to present the "Burrow platform" (BP) technique. The BP technique uses a partial platform for retrieving instrument fragments, thereby reducing the loss of radicular dentin.The BP technique is a microscope-aided approach implementing coated ultrasonic tips to create an access to instrument fragments in the middle and apical thirds of the root canal. The technique consists of 4 steps: (1) coronal access, (2) radicular access, (3) partial platform, and (4) exposure of the fragment and retrieval. A precise, angulated access pathway is specific to the BP technique. In the coronal half, the radicular access pathway extends toward the outer wall of the curvature. In the apical half, the radicular access pathway is oriented toward the inside of the curvature. One and 4 instrument fragments were successfully retrieved in the respective cases. At follow-up, all teeth were asymptomatic and had responded favorably to the treatment.The BP technique may present a suitable alternative to fragment removal from curved canals and slender roots to avoid ledge formation, transportation, and perforation. Instrument retrieval using the BP technique can be performed using commonly available armamentarium.

A Deep Learning Approach to Segment and Classify C-Shaped Canal Morphologies in Mandibular Second Molars Using Cone-beam Computed Tomography.

INTRODUCTION: The identification of C-shaped root canal anatomy on radiographic images affects clinical decision making and treatment. The aims of this study were to develop a deep learning (DL) model to classify C-shaped canal anatomy in mandibular second molars from cone-beam computed tomographic (CBCT) volumes and to compare the performance of 3 different architectures. METHODS: U-Net, residual U-Net, and Xception U-Net architectures were used for image segmentation and classification of C-shaped anatomies. Model training and validation were performed on 100 of a total of 135 available limited field of view CBCT images containing mandibular molars with C-shaped anatomy. Thirty-five CBCT images were used for testing. Voxel-matching accuracy of the automated labeling of the C-shaped anatomy was assessed with the Dice index. The mean sensitivity of predicting the correct C-shape subcategory was calculated based on detection accuracy. One-way analysis of variance and post hoc Tukey honestly significant difference tests were used for statistical evaluation. RESULTS: The mean Dice coefficients were 0.768 ± 0.0349 for Xception U-Net, 0.736 ± 0.0297 for residual U-Net, and 0.660 ± 0.0354 for U-Net on the test data set. The performance of the 3 models was significantly different overall (analysis of variance, P = .000779). Both Xception U-Net (Q = 7.23, P = .00070) and residual U-Net (Q = 5.09, P = .00951) performed significantly better than U-Net (post hoc Tukey honestly significant difference test). The mean sensitivity values were 0.786 ± 0.0378 for Xception U-Net, 0.746 ± 0.0391 for residual U-Net, and 0.720 ± 0.0495 for U-Net. The mean positive predictive values were 77.6% ± 0.1998% for U-Net, 78.2% ± 0.0.1971% for residual U-Net, and 80.0% ± 0.1098% for Xception U-Net. The addition of contrast-limited adaptive histogram equalization had improved overall architecture efficacy by a mean of 4.6% (P < .0001). CONCLUSIONS: DL may aid in the detection and classification of C-shaped canal anatomy.

Combined Regenerative and Vital Pulp Therapies in an Immature Mandibular Molar: A Case Report.

INTRODUCTION: This report describes the treatment of an immature mandibular molar by combining vital pulp therapy (VPT) and regenerative endodontic procedures (REPs). It details the use of REP to regain functionality and continued root development of an immature root with pulp necrosis and VPT for an immature root containing vital pulpal tissues. METHODS: An 8-year old male presented for evaluation of a mandibular first right molar with mild buccal swelling and a nontraceable sinus tract. He recently had received a restoration. After intraoral and radiographic examination, a diagnosis of pulp necrosis and chronic apical abscess was made. After access, pulp necrosis was confirmed in the distal root; however, vital pulp tissues were present in the mesial canals. It was decided on pulpotomy (VPT) in the mesial and REP in the distal root. At the initial visit, pulpotomy was completed in the mesial root, and REP was initiated in the distal root. Three weeks later, the patient was asymptomatic and the sinus tract absent. REP was completed in the distal root, and the tooth was restored. RESULTS: At the 6-, 12-, and 18-month follow-up, the patient presented without symptoms, and the tooth responded positively to pulp sensibility tests. Radiographic examinations showed resolution of the apical radiolucency and completed root development. CONCLUSIONS: Combined treatment using both VPT and REP for immature molars with different pulpal status in individual roots may be a preferable treatment option because preservation of vital pulp tissues and regeneration of new vital tissues allow for continued root development and functionality.

Artificial Intelligence for the Computer-aided Detection of Periapical Lesions in Cone-beam Computed Tomographic Images.

INTRODUCTION: The aim of this study was to use a Deep Learning (DL) algorithm for the automated segmentation of cone-beam computed tomographic (CBCT) images and the detection of periapical lesions. METHODS: Limited field of view CBCT volumes (n = 20) containing 61 roots with and without lesions were segmented clinician dependent versus using the DL approach based on a U-Net architecture. Segmentation labeled each voxel as 1 of 5 categories: "lesion" (periapical lesion), "tooth structure," "bone," "restorative materials," and "background." Repeated splits of all images into a training set and a validation set based on 5-fold cross validation were performed using Deep Learning segmentation (DLS), and the results were averaged. DLS versus clinical-dependent segmentation was assessed by dichotomized lesion detection accuracy evaluating sensitivity, specificity, positive predictive value, negative predictive value, and voxel-matching accuracy using the DICE index for each of the 5 labels. RESULTS: DLS lesion detection accuracy was 0.93 with specificity of 0.88, positive predictive value of 0.87, and negative predictive value of 0.93. The overall cumulative DICE indexes for the individual labels were lesion = 0.52, tooth structure = 0.74, bone = 0.78, restorative materials = 0.58, and background = 0.95. The cumulative DICE index for all actual true lesions was 0.67. CONCLUSIONS: This DL algorithm trained in a limited CBCT environment showed excellent results in lesion detection accuracy. Overall voxel-matching accuracy may be benefited by enhanced versions of artificial intelligence.