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Abstract Condylar resorption is a feared complication of orthognathic surgery. This study investigated condylar resorption in a cohort of 200 patients This allowed for a powerful update on incidence and risk factors. 9.5% of patients developed resorption. These patients had on average, 17% volume loss with 3.9 mm ramal height loss and 3.1 mm posterior mandibular displacement. 2% of patients had bilateral resorption. Univariable analysis identified a younger age, a bimaxillary + genioplasty procedure, larger mandibular advancements, upward movements of the distal segment, a higher counterclockwise pitch of the distal segment, smaller preoperative condylar volumes and a higher anterior/posterior lower facial height ratio as risk factors on a patient level. Univariable analysis on a condylar level also identified compressive movements of the ramus and a higher mandibular plane angle as risk factors. Using machine learning for the multivariable analysis, the amount of mandibular advancement was the most important predictor for condylar resorption. There were no differences in preoperative mandibular, ramal or condylar shape between patients with or without resorption. These findings suggest condylar resorption may be more common than thought. Identifying risk factors allows surgical plans to be adjusted to reduce the likelihood of resorption, and patients can be more selectively screened postoperatively.

Abstract Background Tooth segmentation on intraoral scanned (IOS) data is a prerequisite for clinical applications in digital workflows. Current state-of-the-art methods lack the robustness to handle variability in dental conditions. This study aims to propose and evaluate the performance of a convolutional neural network (CNN) model for automatic tooth segmentation on IOS images. Methods A dataset of 761 IOS images (380 upper jaws, 381 lower jaws) was acquired using an intraoral scanner. The inclusion criteria included a full set of permanent teeth, teeth with orthodontic brackets, and partially edentulous dentition. A multi-step 3D U-Net pipeline was designed for automated tooth segmentation on IOS images. The model’s performance was assessed in terms of time and accuracy. Additionally, the model was deployed on an online cloud-based platform, where a separate subsample of 18 IOS images was used to test the clinical applicability of the model by comparing three modes of segmentation: automated artificial intelligence-driven (A-AI), refined (R-AI), and semi-automatic (SA) segmentation. Results The average time for automated segmentation was 31.7 ± 8.1 s per jaw. The CNN model achieved an Intersection over Union (IoU) score of 91%, with the full set of teeth achieving the highest performance and the partially edentulous group scoring the lowest. In terms of clinical applicability, SA took an average of 860.4 s per case, whereas R-AI showed a 2.6-fold decrease in time (328.5 s). Furthermore, R-AI offered higher performance and reliability compared to SA, regardless of the dentition group. Conclusions The 3D U-Net pipeline was accurate, efficient, and consistent for automatic tooth segmentation on IOS images. The online cloud-based platform could serve as a viable alternative for IOS segmentation.

Abstract The purpose of this study was to report root remodeling/resorption percentages of maxillary teeth following the different maxillary osteotomies; i.e. one-piece, two-pieces, three-pieces Le Fort I, surgically assisted rapid palatal expansion (SARPE). The possibility of relationships between root remodeling and various patient- and/or treatment-related factors were further investigated. A total of 110 patients (1075 teeth) who underwent combined orthodontic and orthognathic surgery were studied retrospectively. The sample size was divided into: 30 patients in one-piece Le Fort I group, 30 patients in multi-pieces Le Fort I group, 20 patients in SARPE group and 30 patients in orthodontic group. Preoperative and 1 year postoperative cone beam computed tomography (CBCT) scans were obtained. A validated and automated method for evaluating root remodeling and resorption in three dimensions (3D) was applied. SARPE group showed the highest percentage of root remodeling. Spearman correlation coefficient revealed a positive relationship between maxillary advancement and root remodeling, with more advancement contributing to more root remodeling. On the other hand, the orthodontic group showed a negative correlation with age indicating increased root remodeling in younger patients. Based on the reported results of linear, volumetric and morphological changes of the root after 1 year, clinical recommendations were provided in the form of decision tree flowchart and tables. These recommendations can serve as a valuable resource for surgeons in estimating and managing root remodeling and resorption associated with different maxillary surgical techniques.

Abstract The process of creating virtual models of dentomaxillofacial structures through three-dimensional segmentation is a crucial component of most digital dental workflows. This process is typically performed using manual or semi-automated approaches, which can be time-consuming and subject to observer bias. The aim of this study was to train and assess the performance of a convolutional neural network (CNN)-based online cloud platform for automated segmentation of maxillary impacted canine on CBCT image. A total of 100 CBCT images with maxillary canine impactions were randomly allocated into two groups: a training set (n = 50) and a testing set (n = 50). The training set was used to train the CNN model and the testing set was employed to evaluate the model performance. Both tasks were performed on an online cloud-based platform, ‘Virtual patient creator’ (Relu, Leuven, Belgium). The performance was assessed using voxel- and surface-based comparison between automated and semi-automated ground truth segmentations. In addition, the time required for segmentation was also calculated. The automated tool showed high performance for segmenting impacted canines with a dice similarity coefficient of 0.99 ± 0.02. Moreover, it was 24 times faster than semi-automated approach. The proposed CNN model achieved fast, consistent, and precise segmentation of maxillary impacted canines.

Abstract Objectives To evaluate the histological parameters and bone mechanical properties around implants with low primary stability (PS) in grafted bone substitutes within an oversized osteotomy. Materials and methods An oversized osteotomy penetrating the double cortical bone layers was made on both femora of 24 New Zealand white rabbits. Bilaterally in the femur of all animals, 48 implants were installed, subdivided into four groups, corresponding to four prepared tissue-engineering bone complexes (TEBCs), which were placed between the implant surface and native bone wall: A: tricalcium phosphate β (TCP-β); B: autologous adipose derived-stem cells with TCP-β (ASCs/TCP-β); C: ASCs transfected with the enhanced-GFP gene with TCP-β (EGFP-ASCs/TCP-β); D: ASCs transfected with the BMP-2 gene with TCP-β (BMP2-ASCs/TCP-β). Trichrome fluorescent labeling was conducted. Animals were sacrificed after eight weeks. The trichromatic fluorescent labeling (%TFL), area of new bone (%NB), residual material (%RM), bone-implant contact (%BIC), and the removal torque force (RTF, N/cm) were assessed. Results ASCs were successfully isolated from adipose tissue, and the primary ASCs were induced into osteogenic, chondrogenic, and adipogenic differentiation. The BMP-2 overexpression of ASCs sustained for ten days and greatly enhanced the expression of osteopontin (OPN). At eight weeks post-implantation, increased %NB and RTF were found in all groups. The most significant value of %TFL, %BIC and lowest %RM was detected in group D. Conclusion The low PS implants osseointegrate with considerable new bone in grafted TEBCs within an oversized osteotomy. Applying BMP-2 overexpressing ASCs-based TEBC promoted earlier osseointegration and more solid bone mechanical properties on low PS implants. Bone graft offers a wedging effect for the implant with low PS at placement and promotes osteogenesis on their surface in the healing period.

Abstract Prediction of lower third molar eruption is crucial for its timely extraction. Therefore, the primary aim of this study was to investigate the prediction of lower third molar eruption and its uprighting with the assistance of an artificial intelligence (AI) tool. The secondary aim was identifying the incidence of fully erupted lower third molars with hygienic cleansability. In total, 771 patients having two panoramic radiographs were recruited, where the first radiograph was acquired at 8–15 years of age (T1) and the second acquisition was between 16 and 23 years (T2). The predictive model for third molar eruption could not be obtained as few teeth reached full eruption. However, uprighting model at T2 showed that in cases with sufficient retromolar space, an initial angulation of

Background/Objectives: The integration of AI into dentistry holds promise for improving diagnostic workflows, particularly in the detection of dental pathologies and pre-radiotherapy screening for head and neck cancer patients. This study aimed to develop and validate an AI model for detecting various dental conditions, with a focus on identifying teeth at risk prior to radiotherapy. Methods: A YOLOv8 model was trained on a dataset of 1628 annotated panoramic radiographs and externally validated on 180 radiographs from multiple centers. The model was designed to detect a variety of dental conditions, including periapical lesions, impacted teeth, root fragments, prosthetic restorations, and orthodontic devices. Results: The model showed strong performance in detecting implants, endodontic treatments, and surgical devices, with precision and recall values exceeding 0.8 for several conditions. However, performance declined during external validation, highlighting the need for improvements in generalizability. Conclusions: YOLOv8 demonstrated robust detection capabilities for several dental conditions, especially in training data. However, further refinement is needed to enhance generalizability in external datasets and improve performance for conditions like periapical lesions and bone loss.

Abstract The aim of this study was to assess the morphological characteristics of the coronoid process (CP) and define coronoid hyperplasia (CH) using cadaveric mandibles of a Caucasian population. A sample of 151 adult dry cadaveric mandibles (302 CPs) was acquired. Three distances were measured, which included the width, height, and length of CP. The surface area measurements involved area A: above the width distance line; area B: between incisura mandibulae—Alveolar ridge line and width distance line; area C: between distance lines of width and height. Finally, angulations of the CP and gonial angles were identified. Both length and surface area A + B acted as hyperplastic indicators. Based on the selection criteria, a sample of 197 CPs was included. The hooked shape (59%) was most commonly observed. No significant difference existed between left and right sides (p > 0.05). The mean values of length and surface area A + B were 2.2 ± 0.3 cm and 3.3 ± 0.8 cm2, and any values above 2.7 cm (n = 5 CPs- 2.5%) and 5.0 cm2 (n = 9 CPs- 4.6%) were described as hyperplastic, respectively. The presented data could act as quantitative reference for differentiating between normal and hyperplastic conditions.

Abstract Accurate mandibular canal (MC) detection is crucial to avoid nerve injury during surgical procedures. Moreover, the anatomic complexity of the interforaminal region requires a precise delineation of anatomical variations such as the anterior loop (AL). Therefore, CBCT-based presurgical planning is recommended, even though anatomical variations and lack of MC cortication make canal delineation challenging. To overcome these limitations, artificial intelligence (AI) may aid presurgical MC delineation. In the present study, we aim to train and validate an AI-driven tool capable of performing accurate segmentation of the MC even in the presence of anatomical variation such as AL. Results achieved high accuracy metrics, with 0.997 of global accuracy for both MC with and without AL. The anterior and middle sections of the MC, where most surgical interventions are performed, presented the most accurate segmentation compared to the posterior section. The AI-driven tool provided accurate segmentation of the mandibular canal, even in the presence of anatomical variation such as an anterior loop. Thus, the presently validated dedicated AI tool may aid clinicians in automating the segmentation of neurovascular canals and their anatomical variations. It may significantly contribute to presurgical planning for dental implant placement, especially in the interforaminal region.

Abstract Background Three-dimensional (3D) printing is a novel innovation in the field of craniomaxillofacial surgery, however, a lack of evidence exists related to the comparison of the trueness of skull models fabricated using different technology-based printers belonging to different cost segments. Methods A study was performed to investigate the trueness of cone-beam computed tomography-derived skull models fabricated using different technology based on low-, medium-, and high-cost 3D printers. Following the segmentation of a patient’s skull, the model was printed by: (i) a low-cost fused filament fabrication printer; (ii) a medium-cost stereolithography printer; and (iii) a high-cost material jetting printer. The fabricated models were later scanned by industrial computed tomography and superimposed onto the original reference virtual model by applying surface-based registration. A part comparison color-coded analysis was conducted for assessing the difference between the reference and scanned models. A one-way analysis of variance (ANOVA) with Bonferroni correction was applied for statistical analysis. Results The model printed with the low-cost fused filament fabrication printer showed the highest mean absolute error ( $$1.33\pm 0.24 \text{mm}$$ 1.33 ± 0.24 mm ), whereas both medium-cost stereolithography-based and the high-cost material jetting models had an overall similar dimensional error of $$0.07\pm 0.03 \text{mm}$$ 0.07 ± 0.03 mm and $$0.07\pm 0.01 \text{mm}$$ 0.07 ± 0.01 mm , respectively. Overall, the models printed with medium- and high-cost printers showed a significantly ( $$p

Abstract Background Proper skills in radiographic diagnosis are essential for optimal management of dental trauma. Aim To assess diagnostic accuracy obtained by paediatric dentists using Cone Beam Computed Tomography (CBCT) without specific training and to compare this with their performance using intraoral radiographs. Methods Intraoral and CBCT images of 89 teeth, spread over twenty dental trauma cases were presented in random order to nine paediatric dentists. Diagnostic findings were compared with those of a benchmark reference. Sensitivity and specificity were calculated and compared using paired t-tests. Results Overall, observers’ diagnostic performance was rather poor with significantly higher sensitivity when using 2D images (P = 0.017). Performance differed considerably according to the type of pathology. Using either imaging modality, sensitivity for diagnosing apical pathology and root fractures was high while the opposite was seen for inflammatory root resorption, root cracks and subluxations. Statistically significant differences between imaging modalities were seen for root fractures (P = 0.013) and apical pathology (P = 0.001), in favor of 3D, and for crown fractures (P = 0.009) in favor of 2D. Conclusion Overall poor performance of paediatric dentists indicates that additional training in radiographic diagnosis is required. In order to justify the use of CBCT to increase diagnostic performance, proper training of the paediatric dentist is mandatory.

Abstract Photon-counting computed tomography (PCCT) is an innovative technological advancement in relation to x-ray detectors which offers ultra-high-resolution images. The current study aimed to evaluate the visualization ability of PCCT compared to cone-beam computed tomographic (CBCT) devices for challenging endodontic diagnostic tasks. A reference image of an anthropomorphic phantom was acquired using an industrial micro-CT device. Thereafter, the phantom was scanned with three imaging devices, which included PCCT scanner (NAEOTOM Alpha) and two CBCT devices (3D Accuitomo 170 and NewTom VGi evo) having standard and high-resolution acquisition protocols. The diagnostic tasks involved visualizing fine endodontic structures (apical delta, narrow canal, and isthmus) and root cracks. Three experienced examiners assessed the images and were blinded to the PCCT and CBCT devices. Each image was rated according to a three-grade scale (appropriate, acceptable, or inappropriate) for the diagnostic tasks. In relation to fine endodontic structures grouped together, PCCT showed similar diagnostic performance compared to the reference image (p > 0.05). As for the CBCT devices, an excellent performance was only observed with the 3D Accuitomo 170 device at a high-resolution acquisition mode (p > 0.05). The visualization of root cracks was also better with 3D Accuitomo 170 compared to other devices (p

Abstract The aim of this study was to evaluate CBCT exposure protocols and CBCT devices in terms of image quality for the detection of cracks and fine endodontic structures using 3 conditions of metallic artifacts. An anthropomorphic phantom containing teeth with cracks, isthmus, narrow canal, and apical delta was scanned using ten CBCT devices. A reference industrial CT image was used to detect and measure all structures. Three conditions were created: (1) metal-free, (2) ‘endo’ and (3) ‘implant’ with metallic objects placed next to the teeth of interest. For each condition, three protocols were selected: medium field of view (FOV) standard resolution, small FOV standard and high resolution. The results showed that only small FOV high-resolution metal-free images from two devices (A and H) were appropriate to visualize cracks. For fine structure identification, the best result was observed for small FOV high resolution. However, the visualization significantly worsened in the presence of metallic artefacts. The ability of CBCT images for visualizing cracks is restricted to certain CBCT devices. Once metallic artefacts are present, crack detection becomes unlikely. Overall, small FOV high-resolution protocols may allow detection of fine endodontic structures as long as there are no high-dense objects in the region of interest.

Abstract The aim of this study was to evaluate the foraminal enlargement and its influence on microcrack formation and apical transportation in root canals with apical curvature. Eighteen maxillary lateral incisors with apical curvature were selected by using micro-CT images. Root canals were randomly divided in two groups (n = 9) according to root canal preparation using two working lengths: 1 mm short of the apical foramen (control group) and 1 mm beyond the apical foramen (foraminal enlargement). For both groups Reciproc Blue R40 was used for root canal instrumentation. Specimens were scanned by nano-CT (UniTOM HR) before and after root canal preparation. Percentage, length, and width of microcracks, and apical transportation were assessed. Kappa, chi‐square and McNemar tests were used for qualitative analyses while paired and unpaired t-test were used for quantitative analyses (α = 0.05). For both groups, rather similar and low percentages of microcracks were observed before root canal preparation (P > 0.05). The foraminal enlargement promoted new microcracks, not observed in the control group. An increase in microcrack length was observed when the foraminal enlargement was performed (P

Abstract Lack of evidence exists related to the investigation of the accuracy and efficacy of novice versus experienced practitioners for dental implant placement. Hence, the following in vitro study was conducted to assess the accuracy of implant positioning and self-efficacy of novice compared to experienced surgeons for placing implant using freehand (FH), pilot drill-based partial guidance (PPG) and dynamic navigation (DN) approaches. The findings revealed that DN significantly improved the angular accuracy of implant placement compared with FH (P

Abstract Objectives The aim of this study is to investigate the long‐term effects on jaw and femur bone induced by oncologic doses of zoledronic acid in a young rat model. Material and Methods Six 12‐week‐old male Wistar rats received zoledronic acid (0.6 mg/kg) and six control rats received saline solution in the same volume. Compounds were administered intraperitoneally in five doses every 28 days. Euthanasia was performed 150 days after therapy onset. After animal sacrifice, their mandibles and femurs were scanned ex vivo using a high‐resolution (14 μm) micro‐computed tomography. Morphometric bone parameters were calculated using CT‐Analyzer (Bruker, Belgium) between the first and second mandibular molars and in the distal femur metaphysis and epiphysis. Results The treatment group as compared to the controls showed a significantly (p

Abstract Purpose This study aimed to investigate the performance of novice versus experienced practitioners for placing dental implant using freehand, static guided and dynamic navigation approaches. Methods A total of 72 implants were placed in 36 simulation models. Three experienced and three novice practitioners were recruited for performing the osteotomy and implant insertion with freehand, surgical guide (pilot-drill guidance) and navigation (X-Guide, X-Nav technologies) approaches. Each practitioner inserted 4 implants per approach randomly with a 1-week gap to avoid memory bias (4 insertion sites × 3 approaches × 6 practitioners = 72 implants). The performance of practitioners was assessed by comparing actual implant deviation to the planned position, time required for implant placement and questionnaire-based self-confidence evaluation of practitioners on a scale of 1–30. Results The navigation approach significantly improved angular deviation compared with freehand (P

Quantitative sensory testing (QST) is a valuable tool in the assessment of orofacial somatosensory function and dysfunction. QST is a method where thermal and mechanical stimuli are applied to the area of interest in a noninvasive way. The QST technique can detect patterns of loss of sensation that may happen in case of hypoesthesia, hypoalgesia, anesthesia, or gain of sensation in the context of allodynia, hyperalgesia or spontaneous pain. Normal values have already been recorded for some parts of the face and mouth, but not for the complete innervation area of the trigeminal nerve. This dataset involves orofacial QST gathered from ten healthy volunteers, a standardized QST battery was applied to 24 regions (14 extraoral and 10 intraoral) innervated by the trigeminal nerve. Descriptive statistics were applied to compare the different regions. This dataset can be used to inform future studies involving orofacial sensory function, pain studies and pharmacological trials.

PurposeThis systematic review was performed to assess the potential influence of medication-induced salivary changes on the development of medication-related osteonecrosis of the jaw (MRONJ).MethodsAn electronic search was conducted using PubMed, Web of Science, Cochrane, and Embase databases for articles published up to June 2023. A risk of bias assessment was performed according to the modified Newcastle–Ottawa Scale (NOS). Due to the heterogeneity of the selected studies in relation to the type of medications and outcomes evaluated, a meta-analysis could not be performed.ResultsThe initial search revealed 765 studies. Only 10 articles were found to be eligible based on the inclusion criteria that reported on the impact of salivary changes on MRONJ following the administration of different medications. A total of 272 cases of MRONJ (35% women, 32% men, and 32% with no gender reported) with a mean age of 66 years at the time of diagnosis were included. Patients administered with bisphosphonates, steroids, chemotherapy, thalidomide, interferon, and hormone therapy had a significantly higher association between decreased salivary flow and MRONJ occurrence. In addition, bisphosphonates, denosumab, and other bone-modifying agents showed a significantly higher risk of developing MRONJ owing to the changes in salivary microbiome profiles, cytokine profiles, interleukins, hypotaurine, and binding proteins.ConclusionThe reduction in salivary flow and changes in the concentration of salivary proteins were associated with the development of MRONJ. However, due to the availability of limited evidence, the findings of the review should be interpreted with caution.Prospero review registrationhttps://www.crd.york.ac.uk/PROSPERO/, identifier: CRD42022327645.

The biomechanics of transplanted teeth remain poorly understood due to a lack of models. In this context, finite element (FE) analysis has been used to evaluate the influence of occlusal morphology and root form on the biomechanical behavior of the transplanted tooth, but the construction of a FE model is extremely time-consuming. Model order reduction (MOR) techniques have been used in the medical field to reduce computing time, and the present study aimed to develop a reduced model of a transplanted tooth using the higher-order proper generalized decomposition method. The FE model of a previous study was used to learn von Mises root stress, and axial and lateral forces were used to simulate different occlusions between 75 and 175N. The error of the reduced model varied between 0.1% and 5.9% according to the subdomain, and was the highest for the highest lateral forces. The time for the FE simulation varied between 2.3 and 7.2 h. In comparison, the reduced model was built in 17s and interpolation of new results took approximately 2.10−2s. The use of MOR reduced the time for delivering the root stresses by a mean 5.9 h. The biomechanical behavior of a transplanted tooth simulated by FE models was accurately captured with a significant decrease of computing time. Future studies could include using jaw tracking devices for clinical use and the development of more realistic real-time simulations of tooth autotransplantation surgery.

Abstract The aim of this study was to compare the quantification of hard-tissue debris by using micro-computed tomography (micro-CT) and nano-focus computed tomography (nano-CT) after root canal instrumentation. Ten mandibular molars containing an isthmus in the mesial root were scanned in a SkyScan 1172 micro-CT device with a voxel size of 12.8 µm and in a NanoTom nano-CT device with 5.5 µm. The mesial root canals were irrigated with 5 mL of saline solution at the orifice level, instrumented with Reciproc R25 files and a second scanning was performed by micro-CT and nano-CT devices for post-instrumentation images. DataViewer software was used for registering the pre- and post-operative micro-CT and nano-CT images. The root canal and the debris were segmented for quantitative analysis of the volume of the canal and volume of debris using CTAn software. Statistical analysis was performed using the T test for comparison between volume of the canal after instrumentation and volume of debris in both image modalities. The level of significance was set at p < 0.05. Nano-CT images showed higher values of debris when compared with micro-CT (p < 0.05) after root canal instrumentation. No difference was observed between the volume of the root canal after instrumentation in the two imaging methods used (p > 0.05). Nano-CT technology can be recommended as a more precise method for quantitative analysis of hard-tissue debris. Moreover, in Endodontic research it is a promising method, as it is capable of providing higher spatial and contrast resolution, faster scanning and higher image quality.

Abstract Tooth extraction is a risk factor for the development of osteonecrosis of the jaw following treatment with antiresorptive drugs (ARDs), but not all extraction sites develop this pathology. Therefore, we aimed to identify local radiographic predictors of Medication-Related Osteonecrosis of the Jaw (MRONJ) in panoramic images of oncologic patients undergoing tooth extraction. Based on a retrospective longitudinal cohort study design, patients were included if undergoing one or more tooth extraction, with at least one administration of ARDs, and presence of pre- and post-operative panoramic radiographs. After data collection, blinded and independent observations were performed. Eleven distinct imaging-related parameters were assessed preoperatively and five postoperatively, at each extraction site. A case–control and subgroup analysis assessing MRONJ development was performed. Significance level is set to 0.05 (5%). A total of 77 oncologic patients were selected, undergoing 218 tooth extractions, from which 63 teeth (29%) in 39 patients (51%) developed MRONJ. Results showed that patients developed significantly more MRONJ with longer ARD treatment (p = 0.057), teeth with absent and incomplete endodontic fillings with caries, widened periodontal ligament space and/or periapical lesions (p = 0.005), and sclerotic and heterogenous bone patterns (p = 0.005). In conclusion, tooth extraction sites presenting with infections and bone sclerosis are at higher risk to develop MRONJ.

Abstract Objectives The present study aims to describe the relationship between upper first molar roots and maxillary sinus, for the first time with a truly three‐dimensional approach. Methods From a retrospective cone‐beam computed tomography (CBCT) sample of the upper jaw, a total of 105 upper first molars in contact with maxillary sinus from 74 patients (male 24, female 50, mean age 42) were included in the present study. Segmentation of the upper first molar and maxillary sinus in CBCT was performed utilizing a semiautomatic livewire segmentation tool in MeVisLab v.3.1. The segmentations were analyzed in 3‐matic Medical 20.0 for root volume and the contact area between upper first molar roots and maxillary sinus. Analysis of variance test was applied to detect statistically significant differences between the roots. Results The palatal root had the largest contact area with maxillary sinus 27.8 ± 21.4 mm2 (20% of the root area) followed by the mesiobuccal 20.5 ± 17.9 mm2 (17% of the root area) and distobuccal root 13.7 ± 12 mm2 (14% of the root area). A significant difference in the contact area of the different roots of the upper first molar was seen. Conclusions This study showed that 70% of the upper first molars were in contact with the maxillary sinus. The palatal root had on average a fifth of its root surface in contact with the sinus, while for mesiobuccal this was a sixth of its root surface and distobuccal roots this was somewhat less. The true 3D relationship could help to better understand maxillary anatomy in relation to occurring pathologies and treatment planning in this area.

Abstract Background The aim of this study is to evaluate the impact of experience with traumatic dental injuries (TDI) on paediatric dentists’ performance and self-assessed confidence when radiodiagnosing traumatic dental injuries (TDI) and to explore whether this is influenced by the imaging technique used (2D versus 3D). Materials and methods Both 2D and 3D radiological images of young anterior permanent teeth having experienced dental trauma were assessed randomly by a panel of paediatric dentists using structured scoring sheets. The impact of level of experience with dental traumatology on radiological detection, identification and interpretation of lesions and on observer’s self-assessed confidence was evaluated. Findings were compared to benchmark data deriving from expert consensus of an experienced paediatric endodontologist and dentomaxillofacial radiologist. Results were analysed using generalized linear mixed modelling. Results Overall, observers performed moderately to poor, irrespective of their level of TDI experience and imaging modality used. No proof could be yielded that paediatric dentists with high TDI experience performed better than those with low experience, for any of the outcomes and irrespective of the imaging modality used. When comparing the use of 3D images with 2D images, significantly higher sensitivities for the detection and correct identification of anomalies were observed in the low experienced group (P

While available treatments have addressed a variety of complications in the dentoalveolar region, associated challenges have resulted in exploration of tissue engineering techniques. Often, scaffold biomaterials with specific properties are required for such strategies to be successful, development of which is an active area of research. This study focuses on the development of a copolymer of poly (N-isopropylacrylamide) (pNIPAM) and chitosan, used for 3D printing of scaffolds for dentoalveolar regeneration. The synthesized material was characterized by Fourier transform infrared spectroscopy, and the possibility of printing was evaluated through various printability tests. The rate of degradation and swelling was analyzed through gravimetry, and surface morphology was characterized by scanning electron microscopy. Viability of dental pulp stem cells seeded on the scaffolds was evaluated by live/dead analysis and DNA quantification. The results demonstrated successful copolymerization, and three formulations among various synthesized formulations were successfully 3D printed. Up to 35% degradability was confirmed within 7 days, and a maximum swelling of approximately 1200% was achieved. Furthermore, initial assessment of cell viability demonstrated biocompatibility of the developed scaffolds. While further studies are required to achieve the tissue engineering goals, the present results tend to indicate that the proposed hydrogel might be a valid candidate for scaffold fabrication serving dentoalveolar tissue engineering through 3D printing.

Abstract An accurate three-dimensional (3D) segmentation of the maxillary sinus is crucial for multiple diagnostic and treatment applications. Yet, it is challenging and time-consuming when manually performed on a cone-beam computed tomography (CBCT) dataset. Recently, convolutional neural networks (CNNs) have proven to provide excellent performance in the field of 3D image analysis. Hence, this study developed and validated a novel automated CNN-based methodology for the segmentation of maxillary sinus using CBCT images. A dataset of 264 sinuses were acquired from 2 CBCT devices and randomly divided into 3 subsets: training, validation, and testing. A 3D U-Net architecture CNN model was developed and compared to semi-automatic segmentation in terms of time, accuracy, and consistency. The average time was significantly reduced (p-value

Abstract Aim The aim of the study was to assess the 5-year cumulative survival rate of implant-based dental rehabilitation following maxillofacial reconstruction with a vascularized bone flap and to investigate the potential risk factors which might influence the survival rate. Materials and methods A retrospective cohort study was designed. Inclusion criteria involved 18 years old or above patients with the availability of clinical and radiological data and a minimum follow-up 1 year following implant placement. The cumulative survival rate was analyzed by Kaplan–Meier curves and the influential risk factors were assessed using univariate log-rank tests and multivariable Cox-regression analysis. Results 151 implants were assessed in 40 patients with a mean age of 56.43 ± 15.28 years at the time of implantation. The mean number of implants placed per patient was 3.8 ± 1.3 with a follow-up period of 50.0 ± 32.0 months. The cumulative survival at 1-, 2- and 5-years was 96%, 87%, and 81%. Patients with systemic diseases (HR = 3.75, 95% CI 1.65–8.52; p = 0.002), irradiated flap (HR = 2.27, 95% CI 1.00–5.17; p = 0.05) and poor oral hygiene (HR = 11.67; 95% CI 4.56–29.88; p

Biocompatibility and osteoconductivity of porous scaffolds can be improved through coating technique by creating micro- and nanostructures on the surfaces. In this study, a biomimetic approach was used to construct a bone morphogenetic protein-2 (BMP-2) integrated calcium phosphate (CaP) coating on the surface of porous titanium scaffolds. In vitro characterizations showed that the scaffolds had mechanical properties comparable to those of the human cortical bone. The biomimetic coating has a nano-scaled surface structure, which releases BMP-2 in a stable and effective manner. Bicortical bone defects were prepared in the bilateral mandibles of beagle dogs, and the coated and uncoated scaffolds were fixed in the bone defects for 8 weeks. Based on micro-CT and histological analysis results, the biomimetic coating significantly promoted bone formation in the titanium scaffold. The coated scaffold group had significantly higher bone volume fraction, bone area fraction, and bone-to-implant contact results than the uncoated scaffold group. Besides, hematological indexes and histopathology results of the visceral organs confirmed the scaffold and coating's biocompatibility. Accordingly, the current study demonstrates that BMP-2 integrated biomimetic CaP coating can significantly promote bone formation in porous titanium scaffolds and benefit the healing process of the bicortical mandibular defect in beagle dogs.

Abstract Background Titanium and its alloys have been widely employed for bone tissue repair and implant manufacturing. The rapid development of three-dimensional (3D) printing technology has allowed fabrication of porous titanium scaffolds with controllable microstructures, which is considered to be an effective method for promoting rapid bone formation and decreasing bone absorption. The purpose of this systematic review was to evaluate the osteogenic potential of 3D-printed porous Ti6Al4V (Ti64) scaffold for repairing long bone defects in animal models and to investigate the influential factors that might affect its osteogenic capacity. Methods Electronic literature search was conducted in the following databases: PubMed, Web of Science, and Embase up to September 2021. The SYRCLE's tool and the modified CAMARADES list were used to assess the risk of bias and methodological quality, respectively. Due to heterogeneity of the selected studies in relation to protocol and outcomes evaluated, a meta-analysis could not be performed. Results The initial search revealed 5858 studies. Only 46 animal studies were found to be eligible based on the inclusion criteria. Rabbit was the most commonly utilized animal model. A pore size of around 500–600 µm and porosity of 60–70% were found to be the most ideal parameters for designing the Ti64 scaffold, where both dodecahedron and diamond pores optimally promoted osteogenesis. Histological analysis of the scaffold in a rabbit model revealed that the maximum bone area fraction reached 59.3 ± 8.1% at weeks 8–10. Based on micro-CT assessment, the maximum bone volume fraction was found to be 34.0 ± 6.0% at weeks 12. Conclusions Ti64 scaffold might act as a promising medium for providing sufficient mechanical support and a stable environment for new bone formation in long bone defects. Trail registration The study protocol was registered in the PROSPERO database under the number CRD42020194100.

Objective: The present study aimed to develop and validate a tool for the automated classification of normal, affected, and osteonecrosis mandibular trabecular bone patterns in panoramic radiographs using convolutional neural networks (CNNs). Methods: A dataset of 402 panoramic images from 376 patients was selected, comprising 112 control radiographs from healthy patients and 290 images from patients treated with antiresorptive drugs (ARD). The latter was subdivided in 70 radiographs showing thickening of the lamina dura, 128 with abnormal bone patterns, and 92 images of clinically diagnosed osteonecrosis of the jaw (ONJ). Four pre-trained CNNs were fined-tuned and customized to detect and classify the different bone patterns. The best performing network was selected to develop the classification tool. The output was arranged as a colour-coded risk index showing the category and their odds. Classification performance of the networks was assessed through evaluation metrics, receiver operating characteristic curves (ROC), and a confusion matrix. Furthermore, Gradient-weighted Class Activation Mapping (Grad-CAM) was employed to visualise class-discriminative regions. Results: All networks correctly detected and classified the mandibular bone patterns with optimal performance metrics. InceptionResNetV2 showed the best results with an accuracy of 96 %, precision, recall and F1-score of 93 %, and a specificity of 98 %. Overall, most misclassifications occurred between normal and abnormal trabecular bone patterns. Conclusion: CNNs offer reliable potentials for automatic classification of abnormalities in the mandibular trabecular bone pattern in panoramic radiographs of antiresorptive treated patients. Clinical significance: A novel method that supports clinical decision making by identifying sites at high risk for ONJ.

Background: The use of cone beam computed tomography (CBCT) in dentistry started in the maxillofacial field, where it was used for complex and comprehensive treatment planning. Due to the use of reduced radiation dose compared to a computed tomography (CT) scan, CBCT has become a frequently used diagnostic tool in dental practice. However, published data on the accuracy of CBCT in the diagnosis of buccal bone level is lacking. The aim of this study was to compare the accuracy of intra-oral radiography (IOR) and CBCT in the diagnosis of the extent of buccal bone loss. Methods: A dry skull was used to create a buccal bone defect at the most coronal level of a first premolar; the defect was enlarged apically in steps of 1 mm. After each step, IOR and CBCT were taken. Based on the CBCT data, two observers jointly selected three axial slices at different levels of the buccal bone, as well as one transverse slice. Six dentists participated in the radiographic observations. First, all observers received the 10 intra-oral radiographs, and each observer was asked to rank the intra-oral radiographs on the extent of the buccal bone defect. Afterwards, the procedure was repeated with the CBCT scans based on a combination of axial and transverse information. For the second part of the study, each observer was asked to evaluate the axial and transverse CBCT slices on the presence or absence of a buccal bone defect. Results: The percentage of buccal bone defect progression rankings that were within 1 of the true rank was 32% for IOR and 42% for CBCT. On average, kappa values increased by 0.384 for CBCT compared to intra-oral radiography. The overall sensitivity and specificity of CBCT in the diagnosis of the presence or absence of a buccal bone defect was 0.89 and 0.85, respectively. The average area under the curve (AUC) of the receiver operating curve (ROC) was 0.892 for all observers. Conclusion: When CBCT images are available for justified indications, other than bone level assessment, such 3D images are more accurate and thus preferred to 2D images to assess periodontal buccal bone. For other clinical applications, intra-oral radiography remains the standard method for radiographic evaluation.

The use of Ti6Al4V in bone engineering is limited, due to the biological inertia of the surface. In this study, a porous Ti6Al4V scaffold with mechanical properties similar to cancellous bone was designed and 3D-printed. Under physiological conditions, the scaffold was immersed firstly in a 5-fold-concentrated simulated body fluid, then in a supersaturated CaP solution containing BMP-2, to form a bone-like porous micro/nano structured biomimetic coating on the surface. Scaffolds were implanted in the muscle pouches created in six beagle dogs and were retrieved four weeks later for histologic and histomorphometric analysis. Results showed that BMP-2 integrated biomimetic CaP coating induced ectopic bone formation, which was absent in other two groups. Soft tissue infiltrated the scaffold's outside 1 mm layer, while the new-formed bone was evenly distributed in the longitudinal and horizontal directions within the rest of the scaffold based on BA/TA, BIC and BA measurements. In conclusion, the BMP-2 incorporated biomimetic CaP coating creates a micro/nano surface structure on the Ti6Al4V scaffold, which helps to increase biocompatibility. The integrated BMP-2 is capable of inducing ectopic bone formation in vivo. The proposed combination may have the potential for bone reconstruction, but further studies are needed to explore its clinical applicability.

Sinus floor elevation (SFE) is a standard surgical technique used to compensate for alveolar bone resorption in the posterior maxilla. Such a surgical procedure requires radiographic imaging pre- and postoperatively for diagnosis, treatment planning, and outcome assessment. Cone beam computed tomography (CBCT) has become a well-established imaging modality in the dentomaxillofacial region. The following narrative review is aimed to provide clinicians with an overview of the role of three-dimensional (3D) CBCT imaging for diagnostics, treatment planning, and postoperative monitoring of SFE procedures. CBCT imaging prior to SFE provides surgeons with a more detailed view of the surgical site, allows for the detection of potential pathologies three-dimensionally, and helps to virtually plan the procedure more precisely while reducing patient morbidity. In addition, it serves as a useful follow-up tool for assessing sinus and bone graft changes. Meanwhile, using CBCT imaging has to be standardized and justified based on the recognized diagnostic imaging guidelines, taking into account both the technical and clinical considerations. Future studies are recommended to incorporate artificial intelligence-based solutions for automating and standardizing the diagnostic and decision-making process in the context of SFE procedures to further improve the standards of patient care.

Lack of evidence exists related to the three-dimensional (3D) pharyngeal airway space (PAS) changes at follow-up after isolated bilateral sagittal split osteotomy (BSSO) advancement surgery. The present study assessed the 3D PAS changes following isolated mandibular advancement at a follow-up period of 1 year. A total of 120 patients (40 males, 80 females, mean age: 26.0 ± 12.2) who underwent BSSO advancement surgery were recruited. Cone-beam computed tomography (CBCT) scans were acquired preoperatively (T0), immediately following surgery (T1), and at 1 year of follow-up (T2). The volume, surface area, and minimal cross-sectional area (mCSA) of the airway were assessed. The total airway showed a 38% increase in volume and 13% increase in surface area from T0 to T1, where the oropharyngeal region showed the maximum immediate change. At T1–T2 follow-up, both volumetric and surface area showed a relapse of less than 7% for all sub-regions. The mCSA showed a significant increase of 71% from T0 to T1 (p < 0.0001), whereas a non-significant relapse was observed at T1–T2 (p = 0.1252). The PAS remained stable at a follow-up period of 1 year. In conclusion, BSSO advancement surgery could be regarded as a stable procedure for widening of the PAS with maintenance of positive space at follow-up.