Classification of presence of missing teeth in each quadrant using deep learning artificial intelligence on panoramic radiographs of pediatric patients.

Early tooth loss in pediatric patients can lead to various complications, making quick and accurate diagnosis essential. This study aimed to develop a novel deep learning model for classification of missing teeth on panoramic radiographs in pediatric patients and to assess the accuracy. The study included patients aged 8-16 years who visited the Pusan National University Dental Hospital and underwent panoramic radiography. A total of 806 panoramic radiographs were retrospectively analyzed to determine the presence or absence of missing teeth for each tooth number. Moreover, each panoramic radiograph was divided into four quadrants, each of a smaller size, containing both primary and permanent teeth, generating 3224 data. Quadrants with missing teeth (n = 1457) were set as the experimental group, and quadrants without missing teeth (n = 1767) were set as the control group. The data were split into training and validation sets in a 4:1 ratio, and a 5-fold cross-validation was conducted. A gradient-weighted class activation map was used to visualize the deep learning model. The average values of sensitivity, specificity, accuracy, precision, recall and F1-score of this deep learning model were 0.635, 0.814, 0.738, 0.730, 0.732 and 0.731, respectively. In the experimental group, the accuracy was the highest for missing canines and premolars, and the lowest for molars. The deep learning model exhibited a moderate to good distinguishing power with a classification performance of 0.730. This deep learning model and the newly defined small sized region of interest proved adequate for classifying the presence of missing teeth.

Effect of bimaxillary surgery on adaptive condylar head remodeling: metric analysis and image interpretation using cone-beam computed tomography volume superimposition.

PURPOSE: The aim of the present study was to use cone-beam computed tomography volume superimposition to investigate the effect of bimaxillary orthognathic surgery on condylar head remodeling. MATERIALS AND METHODS: Using a retrospective study design, 2 investigators evaluated the cone-beam computed tomography data of subjects who had undergone Le Fort I osteotomy and mandibular setback surgery. The predictor variable was time, grouped as preoperative versus postoperative. The outcome variables were the measurement changes of the condylar heads and the distribution of the condylar head remodeling signs. Paired t and χ(2) tests were performed for the purposes of the 2-dimensional metric analysis and the condylar head remodeling distribution. P < .05 was considered significant. RESULTS: The sample was composed of 22 adults (11 men and 11 women, age 20.3 ± 3.2 years) diagnosed with skeletal Class III malocclusion. The intra- and interoperator reliabilities of the image interpretation showed substantial agreement, according to Cohen's kappa index. The condylar heights on the sagittal and coronal planes decreased after surgery. Bone resorption occurred predominantly in the anterior and superior areas on the sagittal plane, the superior and lateral areas on the coronal plane, and the anterolateral and posterolateral areas on the axial plane (P < .05). Bone formation was apparent only in the anteromedial area on the axial plane (P < .05). CONCLUSIONS: Bimaxillary orthognathic surgery caused a decrease in the condylar heights and condylar head remodeling. The cone-beam computed tomography volume superimposition method showed that the condylar head had undergone remodeling after bimaxillary surgery.

Aggressive central odontogenic fibroma in the maxilla: A case report.

A central odontogenic fibroma is a rare benign tumor composed of mature fibrous connective tissue with variable amounts of odontogenic epithelium. It appears at similar rates in the maxilla and mandible. In the maxilla, it usually occurs anterior to the molars. Radiographically, central odontogenic fibroma commonly presents as a multilocular or unilocular radiolucency with a distinct border. This paper reports a case of an aggressive central odontogenic fibroma involving the right posterior maxilla of a 53-year-old man. Radiographs showed an extensive soft tissue mass involving the entire right maxilla with frank bone resorption. The patient had a history of 2 operations in the region, both more than 2 decades ago. Although it was impossible to confirm the previous diagnoses, it was presumed that this case was a recurrent lesion.

Analysis of the root position and angulation of maxillary premolars in alveolar bone using cone-beam computed tomography.

Purpose: This study investigated whether the relationship between the maxillary sinus and the root of the maxillary premolar is correlated with the root position and whether there is a difference in the long axis angle of premolars and the buccal bone thickness according to the sinus-root relationship and root position. Materials and Methods: Cone-beam computed tomographic images of 587 maxillary first premolars and 580 second premolars from 303 patients were retrospectively reviewed. The maxillary sinus floor-root relationship was classified into 4 types, and the root position in the alveolar bone was evaluated as buccal, middle, or palatal. The long axis angle of the maxillary premolars in the alveolar bone and the buccal bone thickness were measured. The correlation between these parameters was analyzed. Results: The maxillary sinus floor-root relationship showed a statistically significant correlation with the root position in the alveolar bone. Most maxillary first premolars were buccally located, and more than half of the second premolars had their roots in the middle. The long axis angle of the premolars was significantly larger in buccal-positioned teeth than in middle-positioned teeth, and the buccal bone was thinner. Conclusion: When the root of the maxillary premolar was separated from the sinus floor, the premolar was often located on the buccal side. Most of the maxillary first premolars had a thinner buccal bone and larger inclination than the second premolars. It is recommended to evaluate the root position, sagittal angle and buccal bone thickness using CBCT for implant treatment planning.

Deep learning-based identification of mesiodens using automatic maxillary anterior region estimation in panoramic radiography of children.

OBJECTIVES: The purpose of this study is to develop and evaluate the performance of a model that automatically sets a region of interest (ROI) and diagnoses mesiodens in panoramic radiographs of growing children using deep learning technology. METHODS: Out of 988 panoramic radiographs, 489 patients with mesiodens were classified as an experimental group, and 499 patients without mesiodens were classified as a control group. This study consists of two networks. The first network (DeeplabV3plus) is a segmentation model that uses the posterior molar space to set the ROI in the maxillary anterior region with the mesiodens in the panoramic radiograph. The second network (Inception-resnet-v2) is a classification model that uses cropped maxillary anterior teeth to determine the presence of mesiodens. The data were divided into five groups and cross-validated. Deep learning model were created and trained using Inception-ResNet-v2. The performance of the segmentation network was evaluated using accuracy, Intersection over Union (IoU), and MeanBFscore. The overall network performance was evaluated using accuracy, precision, recall, and F1-score. RESULTS: Segmentation performance using posterior molar space in panoramic radiographs was 0.839, IoU 0.762, and MeanBFscore 0.907. The mean values of accuracy, precision, recall, F1-score, and area under the curve for the diagnosis of mesiodens using automatic segmentation were 0.971, 0.971, 0.971, 0.971, and 0.971, respectively. CONCLUSIONS: The diagnostic performance of the deep learning system using posterior molar space on the panoramic radiograph was sufficiently useful. The results of the deep learning system confirmed the possibility of complete automation of the classification of mesiodens.

Effect of diode-pumped solid state laser on polymerization shrinkage and color change in composite resins.

A diode-pumped solid state (DPSS) laser emitting at 473 nm was used to test its influence on the degree of polymerization of composite resins. Eight composite resins were chosen and light cured with three different light-curing systems [a quartz-tungsten-halogen (QTH) lamp-based unit, a light-emitting diode (LED) unit, and a DPSS laser]. Polymerization shrinkage and color change in specimens were measured. According to the statistical analysis, each light-curing system produced a significantly different value of maximum polymerization shrinkage. In most specimens, the DPSS laser induced the least polymerization shrinkage. After being immersed in distilled water for 10 days, specimens light-cured by the DPSS laser had undergone less color change than those cured by the other units. In conclusion, the DPSS laser induced better or similar polymerization in terms of polymerization shrinkage and color change in composite resins compared with those of the QTH lamp-based and LED units.

Comparison of panoramic radiography and cone-beam computed tomography for assessing radiographic signs indicating root protrusion into the maxillary sinus.

PURPOSE: This study investigated correlations between findings on panoramic radiographs and cone-beam computed tomography (CBCT) to assess the relationship between the maxillary sinus floor and the roots of maxillary posterior teeth. In addition, radiographic signs indicating actual root protrusion into the maxillary sinus were evaluated on panoramic radiographs. MATERIALS AND METHODS: Paired panoramic radiographs and CBCT images from 305 subjects were analyzed. This analysis classified 2,440 maxillary premolars and molars according to their relationship with the maxillary sinus floor on panoramic radiographs and CBCT images. In addition, interruption of the sinus floor was examined on panoramic radiographs. RESULTS: Root protrusion into the maxillary sinus occurred most frequently in the mesiobuccal roots of the second molars. The classification according to panoramic radiographs and CBCT images was the same in more than 90% of cases when there was no contact between the root apex and the sinus floor. When the panoramic radiograph showed root protrusion into the sinus, the CBCT images showed the same classification in 67.5% of second molars, 48.8% of first molars, and 53.3% of second premolars. There was a statistically significant relationship between interruption of the sinus floor on panoramic radiographs and root protrusion into the sinus on CBCT images. CONCLUSION: The presence of root protrusion into the sinus on panoramic radiographs demonstrated a moderate ability to predict root protrusion into the maxillary sinus. Interruption of the maxillary sinus floor could be considered an indicator of actual root protrusion into the maxillary sinus.

Ameloblastic carcinoma of the mandible: A case report.

Ameloblastic carcinoma is a rare odontogenic malignant tumor with the histologic features of both ameloblastoma and carcinoma. It occurs more frequently in the mandible than in the maxilla and it may appear de novo or develop from a preexisting ameloblastoma or odontogenic cyst. Rapidly progressing, painful swelling is the most common symptom, and radiographically, it shows significant bone resorption and cortical perforation. This report described a case of ameloblastic carcinoma in a 45-year-old man who presented with swelling in the left mandible. The lesion showed combined features of benign findings, such as an expansile cortex with a distinct border, and malignant findings, such as a large exophytic mass with frank bone resorption. Excisional biopsy was performed and a final diagnosis of ameloblastic carcinoma was made.

Very deep super-resolution for efficient cone-beam computed tomographic image restoration.

PURPOSE: As cone-beam computed tomography (CBCT) has become the most widely used 3-dimensional (3D) imaging modality in the dental field, storage space and costs for large-capacity data have become an important issue. Therefore, if 3D data can be stored at a clinically acceptable compression rate, the burden in terms of storage space and cost can be reduced and data can be managed more efficiently. In this study, a deep learning network for super-resolution was tested to restore compressed virtual CBCT images. MATERIALS AND METHODS: Virtual CBCT image data were created with a publicly available online dataset (CQ500) of multidetector computed tomography images using CBCT reconstruction software (TIGRE). A very deep super-resolution (VDSR) network was trained to restore high-resolution virtual CBCT images from the low-resolution virtual CBCT images. RESULTS: The images reconstructed by VDSR showed better image quality than bicubic interpolation in restored images at various scale ratios. The highest scale ratio with clinically acceptable reconstruction accuracy using VDSR was 2.1. CONCLUSION: VDSR showed promising restoration accuracy in this study. In the future, it will be necessary to experiment with new deep learning algorithms and large-scale data for clinical application of this technology.

Transfer Learning via Deep Neural Networks for Implant Fixture System Classification Using Periapical Radiographs.

In the absence of accurate medical records, it is critical to correctly classify implant fixture systems using periapical radiographs to provide accurate diagnoses and treatments to patients or to respond to complications. The purpose of this study was to evaluate whether deep neural networks can identify four different types of implants on intraoral radiographs. In this study, images of 801 patients who underwent periapical radiographs between 2005 and 2019 at Yonsei University Dental Hospital were used. Images containing the following four types of implants were selected: Brånemark Mk TiUnite, Dentium Implantium, Straumann Bone Level, and Straumann Tissue Level. SqueezeNet, GoogLeNet, ResNet-18, MobileNet-v2, and ResNet-50 were tested to determine the optimal pre-trained network architecture. The accuracy, precision, recall, and F1 score were calculated for each network using a confusion matrix. All five models showed a test accuracy exceeding 90%. SqueezeNet and MobileNet-v2, which are small networks with less than four million parameters, showed an accuracy of approximately 96% and 97%, respectively. The results of this study confirmed that convolutional neural networks can classify the four implant fixtures with high accuracy even with a relatively small network and a small number of images. This may solve the inconveniences associated with unnecessary treatments and medical expenses caused by lack of knowledge about the exact type of implant.

Automatic mandibular canal detection using a deep convolutional neural network.

The practicability of deep learning techniques has been demonstrated by their successful implementation in varied fields, including diagnostic imaging for clinicians. In accordance with the increasing demands in the healthcare industry, techniques for automatic prediction and detection are being widely researched. Particularly in dentistry, for various reasons, automated mandibular canal detection has become highly desirable. The positioning of the inferior alveolar nerve (IAN), which is one of the major structures in the mandible, is crucial to prevent nerve injury during surgical procedures. However, automatic segmentation using Cone beam computed tomography (CBCT) poses certain difficulties, such as the complex appearance of the human skull, limited number of datasets, unclear edges, and noisy images. Using work-in-progress automation software, experiments were conducted with models based on 2D SegNet, 2D and 3D U-Nets as preliminary research for a dental segmentation automation tool. The 2D U-Net with adjacent images demonstrates higher global accuracy of 0.82 than naïve U-Net variants. The 2D SegNet showed the second highest global accuracy of 0.96, and the 3D U-Net showed the best global accuracy of 0.99. The automated canal detection system through deep learning will contribute significantly to efficient treatment planning and to reducing patients' discomfort by a dentist. This study will be a preliminary report and an opportunity to explore the application of deep learning to other dental fields.

Maxillary antroliths detected by cone-beam computed tomography in an adult dental population.

PURPOSE: This study evaluated the prevalence and characteristics of maxillary antroliths using cone-beam computed tomography (CBCT) scans performed for maxillofacial diagnostic purposes. MATERIALS AND METHODS: CBCT scans of 13,946 patients over the age of 20 were reviewed for maxillary antroliths, and prevalence according to sex, age, and the side of the jaw was calculated. The relationships of single or multiple antroliths with sex, side, and the degree of sinus inflammation were evaluated. The shape and dimension of antroliths were also assessed. The data were analyzed using descriptive statistics, the chi-square or Fisher exact tests, and Kendall's tau-b. RESULTS: A total of 138 (0.99%) of the 13,946 patients showed an antrolith in at least 1 sinus. Only 18 patients presented a bilateral manifestation, which brought the total number of sinuses containing an antrolith to 156 (0.56%). Multiple antroliths were observed in 36 sinuses, and the total number of antroliths was 207: 110 punctate, 65 linear, and 32 amorphous. The antrolith dimensions varied from 1 mm2 to 91 mm2 (average, 10.2±15.5 mm2). No statistically significant differences were found according to sex, side, and age group (P>0.05). However, there was a statistically significant difference between the multiplicity of antrolith and the degree of sinus inflammation (P<0.05). CONCLUSION: Cone-beam computed tomography is an effective modality for the detection of incidental antroliths. Maxillary antroliths were found to be very rare and were usually asymptomatic. Dentists should have a comprehensive understanding of their diagnosis and treatment in light of possible associated dental problems.

An overview of deep learning in the field of dentistry.

PURPOSE: Artificial intelligence (AI), represented by deep learning, can be used for real-life problems and is applied across all sectors of society including medical and dental field. The purpose of this study is to review articles about deep learning that were applied to the field of oral and maxillofacial radiology. MATERIALS AND METHODS: A systematic review was performed using Pubmed, Scopus, and IEEE explore databases to identify articles using deep learning in English literature. The variables from 25 articles included network architecture, number of training data, evaluation result, pros and cons, study object and imaging modality. RESULTS: Convolutional Neural network (CNN) was used as a main network component. The number of published paper and training datasets tended to increase, dealing with various field of dentistry. CONCLUSION: Dental public datasets need to be constructed and data standardization is necessary for clinical application of deep learning in dental field.

Automatic three-dimensional analysis of bone volume and quality change after maxillary sinus augmentation.

INTRODUCTION: Maxillary sinus augmentation is a widely used surgical procedure to increase the bone volume before implant placement. In order to predict the stability of the implant, analysis of the change in bone volume and quality after a sinus graft procedure is necessary. The purpose of this study was to analyze the change in volume and quality of bone graft material after maxillary sinus augmentation using cone beam computed tomography (CBCT). METHODS AND MATERIALS: Maxillary sinus lift procedures using bovine bone materials (Bio-Oss, Geistrich, Swiss) without immediate implantation were performed at the Pusan National University Dental Hospital in 22 patients, from 2014 to 2017. CBCT images were captured before surgery (T1), a day after surgery (T2), and after 4 to 7 months at follow-up (T3). The T2 and T3 images were registered to the T1 image using histogram matching and intensity-based registration. A total of 30 sinuses were analyzed three-dimensionally (3-D), using self-made software MATLAB 2018a (MathWorks, Natick, Massachusetts). The volume and structural indices of the bone graft material were measured and analyzed. RESULTS: The average volume of graft material showed a decrease, while the average gray value showed an increase during the follow-up period, but these changes were not statistically significant. The structural indices of the graft material after histogram matching showed a significant difference in homogeneity, connectivity, thickness, and roughness at the postoperative follow-up. CONCLUSIONS: The volume and gray value showed no statistically significant changes after the maxillary sinus lift procedures. The results of this study show that structural analysis using histogram matching can be used as a promising tool to analyze the quality of graft materials.

Similarity index for intuitive assessment of three-dimensional facial asymmetry.

Evaluation of facial asymmetry generally involves landmark-based analyses that cannot intuitively assess differences in three-dimensional (3D) stereoscopic structures between deviation and non-deviation sides. This study tested a newly developed similarity index that uses a mirroring technique to intuitively evaluate 3D mandibular asymmetry, and characterised the resulting lower facial soft tissue asymmetry. The similarity index was used to evaluate asymmetry before and after surgery in 46 adult patients (27 men, 19 women; age, 22 ± 4.8 years) with skeletal Class III malocclusion and facial asymmetry who underwent conventional bimaxillary orthognathic surgery. Relative to the midsagittal plane used as the reference plane, the non-overlapping volume of the mandible significantly decreased, and the similarity index significantly increased after surgery. Similarity indexes of the mandible and lower facial soft tissue were strongly negatively correlated with non-overlapping volumes of each measurement. Differences in bilateral hemi-mandibular and hemi-lower facial soft tissue surface and volume measurements before surgery were significantly negatively correlated with similarity indexes of the mandible before and after surgery. This newly developed similarity index and non-overlapping volume using a mirroring technique can easily and intuitively evaluate overall 3D morphological discrepancies, especially 3D mandibular asymmetry, before and after surgery in skeletal Class III patients with facial asymmetry.

Location and shape of the mandibular lingula: Comparison of skeletal class I and class III patients using panoramic radiography and cone-beam computed tomography.

PURPOSE: The aim of this study was to compare the location and the shape of the mandibular lingula in skeletal class I and III patients using panoramic radiography and cone-beam computed tomography. MATERIALS AND METHODS: The sample group included 190 skeletal class I patients and 157 class III patients. The location of the lingula in relation to the deepest point of the coronoid notch was classified into 3 types using panoramic radiographs. The shapes of the lingulae were classified into nodular, triangular, truncated, or assimilated types using cone-beam computed tomographic images. The data were analyzed using the chi-square test. RESULTS: The tips of the lingulae were at the same level as the coronoid notch in 75.3% of skeletal class I patients and above the coronoid notch in 66.6% of class III patients. The positions of the lingulae in relation to the deepest point of the coronoid notch showed statistically significant differences between class I and class III patients. The most common shape was nodular, and the least common was the assimilated shape. Although this trend was not statistically significant, the triangular shape was more frequently observed in class III patients than in class I patients. CONCLUSION: The locations and the shapes of the mandibular lingulae were variable. Most of the lingulae were at the same level as the coronoid notch in skeletal class I patients and above the coronoid notch in skeletal class III patients. The nodular and assimilated-shaped lingulae were the most and the least prevalent, respectively.

Widely disseminated sporadic Burkitt lymphoma initially presented as oral manifestations in a 6-year-old boy.

Burkitt lymphoma, a subtype of non-Hodgkin's lymphoma, is an aggressive neoplasm with three variants that are endemic, sporadic, and immunodeficiency associated. We present an unusual case of sporadic Burkitt lymphoma in a 6-year-old boy who initially presented with hypermobile teeth and no other specific signs or symptoms. On dental radiography, the patient was found to have alveolar bone resorption adjacent to the maxillary first molars, with the appearance of floating teeth. In addition, magnetic resonance imaging (MRI) showed extensive soft tissue masses involving four quadrants of the jaws. A definitive diagnosis of Burkitt lymphoma was made based on tissue and bone marrow biopsy. Subsequent images, including abdominal computed tomography (CT) and bone scan, revealed wide dissemination of the lymphoma into the abdominal cavity, pancreas, and numerous bones. This case suggests the possibility of dental complaints as an initial clinical manifestation of sporadic Burkitt lymphoma and emphasizes the role of dentists in early detection of the disease to improve prognosis.

Acetylshikonin suppresses invasion of Porphyromonas gingivalis­infected YD10B oral cancer cells by modulating the interleukin-8/matrix metalloproteinase axis.

The development of pharmaceutical agents possessing anti­invasive and anti­metastatic abilities, as well as apoptotic activity, is important in decreasing the incidence and recurrence of oral cancer. Cancer cells are known to acquire invasiveness not only through epigenetic changes, but also from inflammatory stimuli within the tumor microenvironment. Accordingly, the identification of agents that can suppress the inflammation­promoted invasiveness of cancer cells may be important in treating cancer and improving the prognosis of patients with cancer. Acetylshikonin, a flavonoid with anti­inflammatory activity, inhibits proliferation and induces apoptosis of oral cancer cells. In the present study, the anti­invasive effect of acetylshikonin on YD10B oral cancer cells infected with Porphyromonas gingivalis, a major pathogen of chronic periodontitis, and the mechanisms involved were investigated. Firstly, we examined whether P. gingivalis infection increased the invasiveness of YD10B cells. Results suggested that YD10B oral cancer cells become more aggressive when they are infected with P. gingivalis. Secondly, acetylshikonin significantly inhibited the invasion of P. gingivalis­infected YD10B cells by suppressing IL­8 release and IL­8­dependent MMP release. These data suggest that acetylshikonin may be a useful preventive and therapeutic candidate for oral cancer that is chronically infected with periodontal pathogens.

Analysis of the root position of the maxillary incisors in the alveolar bone using cone-beam computed tomography.

PURPOSE: The purpose of this study was to measure the buccal bone thickness and angulation of the maxillary incisors and to analyze the correlation between these parameters and the root position in the alveolar bone using cone-beam computed tomography (CBCT). MATERIALS AND METHODS: CBCT images of 398 maxillary central and lateral incisors from 199 patients were retrospectively reviewed. The root position in the alveolar bone was classified as buccal, middle, or palatal, and the buccal type was further classified into subtypes I, II, and III. In addition, the buccolingual inclination of the tooth and buccal bone thickness were evaluated. RESULTS: A majority of the maxillary incisors were positioned more buccally within the alveolar bone, and only 2 lateral incisors (0.5%) were positioned more palatally. The angulation of buccal subtype III was the greatest and that of the middle type was the lowest. Most of the maxillary incisors exhibited a thin facial bone wall, and the lateral incisors had a significantly thinner buccal bone than the central incisors. The buccal bone of buccal subtypes II and III was significantly thinner than that of buccal subtype I. CONCLUSION: A majority of the maxillary incisor roots were positioned close to the buccal cortical plate and had a thin buccal bone wall. Significant relationships were observed between the root position in the alveolar bone, the angulation of the tooth in the alveolar bone, and buccal bone thickness. CBCT analyses of the buccal bone and sagittal root position are recommended for the selection of the appropriate treatment approach.

The effects of impacted premaxillary supernumerary teeth on permanent incisors.

PURPOSE: The aim of this study was to examine the radiographic features associated with impacted premaxillary supernumerary teeth, to determine the relationship between their characteristics and their effects on permanent incisors, and to investigate the types of orthodontic treatment that patients received after the extraction of impacted supernumerary teeth. MATERIALS AND METHODS: The clinical records and radiographs of 193 patients whose impacted premaxillary supernumerary teeth were removed were retrospectively reviewed, and 241 impacted supernumerary teeth were examined. Cone-beam computed tomographic images and panoramic radiographs were examined to determine the number, location, sagittal position, orientation, and morphology of the supernumerary teeth. Their effects on permanent incisors and the orthodontic treatment received by patients after the extraction of the supernumeraries were also investigated. RESULTS: Supernumerary teeth were most frequently observed in the central incisor region, in the palatal position, in the inverted orientation, and were most commonly conical in shape. The most common complication was median diastema, followed by displacement and delayed eruption of the adjacent incisors. Ten (71.4%) of the 14 odontomas showed delayed eruption of the adjacent incisors. Displacement of the incisors was more frequently observed in association with supernumerary teeth with tuberculate or supplemental shapes. Orthodontic traction was most frequently performed after the removal of odontomas. In 32 cases (13.3%), permanent incisors erupted after the orthodontic creation of sufficient space. CONCLUSION: Median diastema was most common complication. The delayed eruption of incisors was common in supernumerary teeth with a vertical orientation and an odontoma shape.