Eichner classification based on panoramic X-ray images using deep learning: A pilot study.

BACKGROUND: Research using panoramic X-ray images using deep learning has been progressing in recent years. There is a need to propose methods that can classify and predict from image information. OBJECTIVE: In this study, Eichner classification was performed on image processing based on panoramic X-ray images. The Eichner classification was based on the remaining teeth, with the aim of making partial dentures. This classification was based on the condition that the occlusal position was supported by the remaining teeth in the upper and lower jaws. METHODS: Classification models were constructed using two convolutional neural network methods: the sequential and VGG19 models. The accuracy was compared with the accuracy of Eichner classification using the sequential and VGG19 models. RESULTS: Both accuracies were greater than 81%, and they had sufficient functions for the Eichner classification. CONCLUSION: We were able to build a highly accurate prediction model using deep learning scratch sequential model and VGG19. This predictive model will become part of the basic considerations for future AI research in dentistry.

A new dataset of oral panoramic x-ray images and parallel network using transformers for medical image segmentation.

INTRODUCTION: Accurate segmentation of the key mandibular region in the oral panoramic X-ray image is crucial for the diagnosis of the mandibular region and the planning of implant surgery. Because the oral panoramic X-ray image contains many important anatomical information for implant treatment evaluation. However, the fuzzy boundary between each region in the image makes the segmentation task very challenging. In data-driven segmentation methods, corresponding datasets are often required. Due to the limited oral data set at present, there is a bottleneck in clinical application. MATERIALS AND METHODS: In this paper, we build a panoramic X-ray image dataset for the mandibular region. The dataset has a total of 711 images. The dataset is divided into 8 categories based on the number of teeth and treatment conditions. The annotations include mandible, normal teeth, treated teeth and implants. In terms of network segmentation. According to the local and global characteristics of the dataset, we designed a CBTrans partition network by paralleling the convolution block and the Swin-transform block of the bottleneck structure. RESULTS: The experimental results show that our proposed network achieves excellent performance on the mandibular region segmentation dataset and the common retina dataset DRIVE. CONCLUSION: CBTrans can better extract features locally and globally by combining CNN of the bottleneck structure and Swin Transformer in parallel. CBTrans demonstrates performance advantages over other similar hybrid architecture models.

Effect of data size on tooth numbering performance via artificial intelligence using panoramic radiographs.

OBJECTIVE: This study aims to investigate the effect of number of data on model performance, for the detection of tooth numbering problem on dental panoramic radiographs, with the help of image processing and deep learning algorithms. STUDY DESIGN: The data set consists of 3000 anonymous dental panoramic X-rays of adult individuals. Panoramic X-rays were labeled on the basis of 32 classes in line with the FDI tooth numbering system. In order to examine the relationship between the number of data used in image processing algorithms and model performance, four different datasets which include 1000, 1500, 2000 and 2500 panoramic X-rays, were used. The training of the models was carried out with the YOLOv4 algorithm and trained models were tested on a fixed test dataset with 500 data and compared based on F1 score, mAP, sensitivity, precision and recall metrics. RESULTS: The performance of the model increased as the number of data used during the training of the model increased. Therefore, the last model trained with 2500 data showed the highest success among all the trained models. CONCLUSION: Dataset size is important for dental enumeration, and large samples should be considered as more reliable.

The panoramic radiograph archive of the human craniological collection housed at the Human Anatomy Museum in Turin.

The craniological collection at the Human Anatomy Museum of the University of Turin consists of 1090 skulls and 64 postcranial skeletons prepared mostly during the second half of the nineteenth century. The collection presents individuals of both sexes and of different age groups and includes 712 skulls of known age and sex and 378 of which only the sex is known. Most individuals are associated with a documentation that includes sex, age-at-death, dates of birth and a death certificate. The collection comes from several regions of Italy, between 1880 and 1915, received by the former Anatomical Institute of the University of Turin from city's prisons and hospitals. The whole craniological collection of known age was subjected to panoramic radiographs. The craniological collection combined with the panoramic digital X-ray images represents an important contribution in anthropology and forensic odontology, as there is now no craniological collection available in the world available from a radiological perspective, for investigating dental age assessment and sex dimorphism using radiographs as well as other research and teaching potentials.

Prevalencia del pseudoquiste antral y mucositis apical en los senos maxilares como entidades frecuentes encontradas en radiografías panorámicas en pacientes de un centro radiológico de Huacho, Lima-Perú, 2019 / Prevalence of antral pseudocyst and apical mucositis in the maxillary sinus as common entities found in panoramic x-rays among patients at a radiological center in Huacho, Lima, Peru, 2019

RESUMEN Antecedentes: Los senos maxilares están directamente relacionados con el proceso dentoalveolar, por lo que el conocimiento de las patologías que pueden afectar y comprometer cualquiera de ambas estructuras facilitará un correcto diagnóstico y tratamiento. Objetivo: Determinar la prevalencia de pseudoquiste antral y mucositis como entidades frecuentes encontradas en radiografías panorámicas en pacientes de un centro radiológico de Huacho, Lima-Perú, en 2019. Material y métodos: Estudio transversal, observacional, descriptivo y retrospectivo. De un total de 1646 radiografías panorámicas virtuales recolectadas en el centro radiológico de Huacho, se asignó como población muestral 1224 radiografías, luego de tener en cuenta los criterios de inclusión y exclusión. Las variables fueron pseudoquiste antral, engrosamiento de la mucosa, periodontitis apical, mucositis, edad, sexo y mes de toma radiográfica. Se realizó análisis descriptivo y bivariado. Resultados: La prevalencia de pseudoquiste antral de origen respiratorio fue de 5,71 %; de mucositis, 13,07 %; y de ambas entidades correlacionadas, 0,90 %. Se encontró asociación significativa entre la presencia de pseudoquiste antral de origen respiratorio y el sexo masculino (p = 0,007). Conclusiones: La presencia de lesiones apicales que condicionan tanto el engrosamiento de la mucosa antral como la presencia de pseudoquiste antral odontogénico, correlacionadas, resultó poco prevalente (y no rara).

ABSTRACT Maxillary sinuses are directly related to the dentoalveolar process, so knowledge of the pathologies that may affect and compromise either of the two structures can facilitate a correct diagnosis and treatment. Objective: To determine antral pseudocyst and apical mucositis prevalence as frequent entities found in panoramic x-rays among patients at a radiological center in Huacho, Lima, Peru, 2019. Material and Methods: Cross-sectional, observational, descriptive and retrospective study. From a total of 1,646 virtual panoramic x-rays collected at a radiological center in Huacho, 1,224 x-rays were used as sample population after taking into account the inclusion and exclusion criteria. The variables were antral pseudocyst, thickening of the mucosa, apical periodontitis, apical mucositis, age, gender, and month in which x-ray was taken. Descriptive and bivariate analysis was performed. Results: Antral pseudocyst of respiratory origin prevalence was 5.71%, mucositis prevalence was 13.07%, and prevalence of both correlated entities was 0.90%. A significant association was found between the presence of antral pseudocyst of respiratory origin and male gender (p=0,007). Conclusion: The occurrence of apical lesions leading to both thickening of the antral mucosa and the presence of odontogenic antral pseudocysts, while not rare, was found to be of low prevalence.

Resorción intracoronal preeruptiva: reportes radiográficos y tomográficos de cuatro casos / Preeruptive Intracoronal Resorption: X-Ray and Tomographic Reports of Four Cases

RESUMEN La resorción intracoronal preeruptiva (RIPE) se presenta como un defecto ubicado en la dentina coronal próxima a la unión amelodentinaria en la corona de un germen dentario. Este defecto de profundidad y ubicación anteroposterior variables solo puede ser diagnosticado mediante radiografías extraorales, intraorales y tomografías dentales. La etiología no ha sido determinada, pero los estudios de histopatología sugieren que este defecto sería una secuela de resorción dentaria. En el presente manuscrito, se presentan radiografías panorámicas y tomografías de haz cónico (THC) de cuatro pacientes con dicha afección, en las que encontramos los defectos dentinarios y discontinuidades en el esmalte adyacente, por lo que se discutirá la utilidad de la THC en el diagnóstico y la planificación de tratamiento de los casos con RIPE.

ABSTRACT Preeruptive Intracoronal Resorption (PIR) manifests as a defect located in the dentin of a dental germ, adjacent to the amelodentinal junction in the crown. This defect, which varies in depth and anteroposterior location, can only be diagnosed through extraoral and intraoral x-rays, as well as dental tomography. The etiology of PIR remains undetermined, although histopathological studies suggest it could be a consequence of dental resorption. In this paper, panoramic x-rays and cone beam computed tomography (CBCT) scans of four patients with PIR are presented. The dental defects and enamel discontinuities adjacent to them are identified, highlighting the usefulness of CBCT in diagnosing and planning treatment for PIR cases.

Deep learning for automatic mandible segmentation on dental panoramic x-ray images.

Many studies in the last decades have correlated mandible bone structure with systemic diseases like osteoporosis. Mandible segmentation, as well as segmentation of other oral structures, is an essential step in studies that correlate oral structures' conditions with systemic diseases in general. However, manual mandible segmentation is a time-consuming and training-required task that suffers from inter and intra-user variability. Further, the dental panoramic x-ray image (PAN), the most used image in oral studies, contains overlapping of many structures and lacks contrast on structures' interface. Those facts make both manual and automatic mandible segmentation a challenge. In the present study, we propose a precise and robust set of deep learning-based algorithms for automatic mandible segmentation (AMS) on PAN images. Two datasets were considered. An in-house image dataset with 393 image/segmentation pairs was prepared using image data of 321 image patient data and the corresponding manual segmentation performed by an experienced specialist. Additionally, a publicly available third-party image dataset (TPD) composed of 116 image/segmentation pairs was used to train the models. Four deep learning models were trained using U-Net and HRNet architectures with and without data augmentation. An additional morphological refinement routine was proposed to enhance the models' prediction. An ensemble model was proposed combining the four best-trained segmentation models. The ensemble model with morphological refinement achieved the highest scores on the test set (98.27%, 97.60%, 97.18%, ACC, DICE, and IoU respectively), with the other models scoring above 95% in all performance metrics on the test set. The present study achieved the highest ranked performance considering all the previously published results on AMS for PAN images. Additionally, those are the most robust results achieved since it was performed over an image set with considerable gender representativeness, a wide age range, a large variety of oral conditions, and images from different imaging scans.

Application of liquid scintillation light guide (LSLG) to scattered X-ray measurement from dental panoramic radiography system.

A 1.2 m flexible liquid scintillation light guide (LSLG) detector connected to a portable electric device was developed and applied to monitor X-rays scattered from a panoramic dental X-ray imaging apparatus. The X-ray absorption of the LSLG tube was simulated for 20 and 40 keV X-rays. The LSLG detector was calibrated by comparing doses measured by a 3-inch NaI(Tl) detector using Am-241 and Cs-137 sources. A linear relationship was obtained between dose rates (µSv/h) and count rates (cps). The elapsed time profile of scattered radiation from a panoramic dental X-ray imaging apparatus was determined. Local absorbed doses were measured with small OSL dosimeters on the LSLG tube suspended over the shoulder and the eyeglass. Behind the ears and neck (in the center of the LSLG tube) showed high doses. The LSLG detector was useful for real-time monitoring of scattered X-rays.

Exploiting multimodal CNN architecture for automated teeth segmentation on dental panoramic X-ray images.

Panoramic X-ray images are the major source used in field of dental image segmentation. However, such images suffers from the disturbances like low contrast, presence of jaw bones, nose bones, spinal bone, and artifacts. Thus, to observe these images manually is a tedious task, requires expertise of dentist and is time consuming. Hence, there is need to develop an automated tool for teeth segmentation. Recently, few deep models have been developed for dental image segmentation. But, such models possess large number of training parameters, thus making the segmentation a very complex task. Also, these models are based only on conventional CNN and lacks in exploiting multimodal CNN features for dental image segmentation. Thus, to address these issues, a novel encoder-decoder model based on multimodal-feature extraction for automatic segmentation of teeth area is proposed. The encoder has three different CNN based architectures: conventional CNN, atrous-CNN, and separable CNN to encode rich contextual information. Whereas decoder contains a single stream of deconvolutional layers for segmentation. The proposed model is tested on 1500 panoramic X-ray images and uses very less parameters when compared to state-of-the-art methods. Besides this, the precision and recall are 95.01% and 94.06%, which out performs the state-of-the art methods.

Implementation of a personal identification system using alveolar bone images.

OBJECTIVE: In recent years, personal identification has been performed using antemortem panoramic X-ray images and postmortem-CT images. Using these, we have developed a personal identification method that focuses on the alveolar bone. This study examined the effectiveness of this method and aimed to implement a reproducible system. MATERIALS AND METHODS: For personal identification, a total of 633 CT images and panoramic X-ray images belonging to three groups with different conditions were used.　These images were 160 sets in the same person group and 96,820 in the other groups. The similarity of alveolar bone images was calculated using the landmark method of Procrustes analysis. The processes were system implemented and the methodology was validated. RESULTS: The ability to identify between the same person group and other person groups showed 0.9769 as the area under the curve (AUC: ROC curve). At the cutoff value of 4.978, there was no false rejection rate, but false acceptance rate was slightly higher. CONCLUSION: This method was useful as a screening method for personal identification. In addition, system implementation was efficient and reduced human error. In the future, we aim to realize a more efficient personal identification method using distortion-corrected images and including auto-detective landmarks using deep learning.

Teeth U-Net: A segmentation model of dental panoramic X-ray images for context semantics and contrast enhancement.

BACKGROUND AND OBJECTIVE: It is very significant in orthodontics and restorative dentistry that the teeth are segmented from dental panoramic X-ray images. Nevertheless, there are some problems in panoramic X-ray images of teeth, such as blurred interdental boundaries, low contrast between teeth and alveolar bone. METHODS: In this paper, The Teeth U-Net model is proposed in this paper to resolve these problems. This paper makes the following contributions: Firstly, a Squeeze-Excitation Module is utilized in the encoder and the decoder. And proposing a dense skip connection between encoder and decoder to reduce the semantic gap. Secondly, due to the irregular shape of the teeth and the low contrast of the dental panoramic X-ray images. A Multi-scale Aggregation attention Block (MAB) in the bottleneck layer is designed to resolve this problem, which can effectively extract teeth shape features and fuse multi-scale features adaptively. Thirdly, in order to capture dental feature information in a larger field of perception, this paper designs a Dilated Hybrid self-Attentive Block (DHAB) at the bottleneck layer. This module effectively suppresses the task-irrelevant background region information without increasing the network parameters. Finally, the effectiveness of the algorithm is validated using a clinical dental panoramic X-ray image datasets. RESULTS: The results of the three comparison experiments are shown that Accuracy, Precision, Recall, Dice, Volumetric Overlap Error and Relative Volume Difference for dental panoramic X-ray teeth segmentation are 98.53%, 95.62%, 94.51%, 94.28%, 88.92% and 95.97% by the proposed model respectively. CONCLUSION: The proposed modules complement each other in processing every detail of the dental panoramic X-ray images, which can effectively improve the efficiency of preoperative preparation and postoperative evaluation, and promote the application of dental panoramic X-ray in medical image segmentation. There are more accuracy about Teeth U-Net than others model in dental panoramic X-ray teeth segmentation. That is very important to clinical doctors to cure in orthodontics and restorative dentistry.

Tooth detection for each tooth type by application of faster R-CNNs to divided analysis areas of dental panoramic X-ray images.

This study aimed to propose a computerized method for detecting the tooth region for each tooth type as the initial stage in the development of a computer-aided diagnosis (CAD) scheme for dental panoramic X-ray images. Our database consists of 160 panoramic dental X-ray images obtained from 160 adult patients. To reduce false positives (FPs), the proposed method first extracts a rectangular area including all teeth from a dental panoramic X-ray image with a faster region using a convolutional neural network (Faster R-CNN). From the rectangular area including all teeth, six divided areas are then extracted with Faster R-CNN: top left, top center, top right, bottom left, bottom center, and bottom right. Faster R-CNNs for detecting tooth regions for each tooth type were trained individually for each of the divided areas that narrowed down the target tooth types. By applying these Faster R-CNNs to each divided area, the bounding boxes of each tooth were detected and classified into 32 tooth types. A k-fold cross-validation method with k = 4 was used for training and testing the proposed method. The detection rate for each tooth, number of FPs per image, mean intersection over union for each tooth, and classification accuracy for the 32 tooth types were 98.9%, 0.415, 0.748, and 91.7%, respectively, showing an improvement compared to the application of the Faster R-CNN once to the entire image (98.0%, 1.194, 0.736, and 88.8%).

Does Panoramic X-ray Induce Cytogenetic Damage to Oral Cells? A Systematic Review With Meta-analysis.

AIM: The aim of this review was to evaluate the scientific literature regarding the cytogenetic damage in oral exfoliated cells of adult patients submitted to panoramic X-ray. MATERIALS AND METHODS: An extensive search of the literature was conducted on PubMed, Scopus and Web of Science databases for all studies published until April 2021 using combinations of the following keywords: "panoramic X-ray," "DNA damage," "genetic damage", "genotoxicity", "mutagenicity", cytotoxicity", "buccal cells", "oral mucosa", "tongue", "gingiva", "micronucleus assay", according to the PRISMA guidelines. All clinical studies in English language were included in the study. A total of 10 studies were identified. RESULTS: As expected, the results regarding the cytogenetic damage induced by panoramic X-ray are conflicting. Some authors have demonstrated that panoramic X-ray induces mutagenesis in oral cells, whereas others did not. After reviewing the 10 studies, two were classified as strong, four were considered moderate, and four were considered weak, according to the quality assessment components of the Effective Public Health Practice Project (EPHPP). Meta-analysis data revealed a negative response related to mutagenicity in oral cells by panoramic X-ray. CONCLUSION: Taken together, this review failed to demonstrate the association between micronucleus frequency and panoramic X-ray.

Individual tooth detection and identification from dental panoramic X-ray images via point-wise localization and distance regularization.

Dental panoramic X-ray imaging is a popular diagnostic method owing to its very small dose of radiation. For an automated computer-aided diagnosis system in dental clinics, automatic detection and identification of individual teeth from panoramic X-ray images are critical prerequisites. In this study, we propose a point-wise tooth localization neural network by introducing a spatial distance regularization loss. The proposed network initially performs center point regression for all the anatomical teeth (i.e., 32 points), which automatically identifies each tooth. A novel distance regularization penalty is employed on the 32 points by considering L2 regularization loss of Laplacian on spatial distances. Subsequently, teeth boxes are individually localized using a multitask neural network on a patch basis. A multitask offset training is employed on the final output to improve the localization accuracy. Our method successfully localizes not only the existing teeth but also missing teeth; consequently, highly accurate detection and identification are achieved. The experimental results demonstrate that the proposed algorithm outperforms state-of-the-art approaches by increasing the average precision of teeth detection by 15.71 % compared to the best performing method. The accuracy of identification achieved a precision of 0.997 and recall value of 0.972. Moreover, the proposed network does not require any additional identification algorithm owing to the preceding regression of the fixed 32 points regardless of the existence of the teeth.

Jaw and Teeth Segmentation on the Panoramic X-Ray Images for Dental Human Identification.

Due to the damage to biometric properties in the event of natural disasters, like fire or earthquakes, it is very difficult to identify human remains. As teeth are more durable than other biometric properties, identifying information obtained from them is much more reliable. Therefore, in cases where alternative biometric properties cannot be obtained or used, information taken from teeth may be used to identify a person's remains. In recent years, many studies have shown how the identification process, previously performed manually by a forensic dental specialist, can be made faster and more reliable with the assistance of computers and technology. In these studies, the x-ray image is subdivided into meaningful parts, including jaws and teeth, and dental properties are extracted and matched. In order to extract the features accurately and ensure better matching, it is important to segment images properly. In this study, (i) lower and upper jaw and (ii) tooth separation was performed to segment panoramic dental x-ray images to assist in identifying human remains. To separate the jaws, a novel meta-heuristic optimization-based model is proposed. To separate teeth, a user-assisted, semi-automatic approach is presented. The proposed methods have been performed with a computer program. The results of the implementation of these methods of jaw and tooth separation in panoramic tooth images are encouraging.

Risk assessment of bisphosphonate-related osteonecrosis of the jaw based on CBCT scans / A biszfoszfonátkezelés állcsontnekrózist eloidézo kockázatának megítélése CBCT-felvételek alapján.

INTRODUCTION: Bisphosphonate-related osteonecrosis of the jaw is a condition that severely affects the quality of life, therefore an early diagnosis is of utmost importance (both from a general and a surgical point of view), alongside with an accurate assessment of the risk of emergence of the disease. AIM: Estimation of the prognosis is not resolved; among several radiological options those used in dentistry seem the most fit for the purpose, with cone-beam computed tomography (CBCT) being superior in this task. Assessment of the risk of BRONJ developed following orally applied bisphosphonate is unemphatic in most case studies - these focus more on the intravenous application carrying a greater risk of BRONJ. METHOD: In contrast with the studies published so far, we performed our measurements on preoperative CBCT scans, thereby directly studying the possibility of risk assessment. Our measurements were conducted through evaluating CBCT scans. We chose the frontal section in the midline of the mental foramen as the representative area. We measured density and thickness of the cortical bone on several given points; the diameter of the mental foramen was also measured. In the first group, we examined patients suffering from osteoporosis who had developed BRONJ following oral bisphosphonate treatment. In the second group, we looked at patients suffering from osteoporosis, who had received oral bisphosphonate therapy for this condition but did not develop BRONJ after oral surgery. As control group, we chose patients suffering from osteoporosis who had not received any of the medications known to cause BRONJ. RESULTS: Based on our results, it is clear that there is no significant difference in the bone density of those patients who developed BRONJ and those who did not, examining the preoperative CBCT scans. CONCLUSIONS: Using CBCT scans (and thereby submitting the patient to radiation exposure) in order to estimate the possibility of BRONJ following oral bisphosphonate treatment for osteoporosis is not recommended. It is important not to expose patients to more radiation than strictly necessary to predict BRONJ following oral bisphosphonate treatment in accordance with the ALARA (as low as reasonably achievable) principle. Orv Hetil. 2020; 161(21): 867-872.

Frecuencia y características de hallazgos y variaciones óseas en radiografías panorámicas de personas con edentulismo total / Frequency and characteristics of incidental findings in panoramic radiographs and bone variations in people with total edentulism

Antecedentes: Según el Estudio Nacional de Salud Bucal del 2014, el 5,20 % de la población colombiana presenta edentulismo total y el 32,8 % en la población de más de 65 años. Sin embargo, otros parámetros relevantes para el correcto abordaje del edentulismo, deben ser analizados con estudios radiográficos. Objetivo: Identificar la frecuencia y características de los hallazgos y las variaciones óseas en radiografías panorámicas de pacientes totalmente edéntulos. Métodos: Se realizó un estudio observacional descriptivo en 10.000 radiografías panorámicas de las cuales se analizaron las que correspondían a pacientes con edentulismo total mediante el programa CliniView 9.3. Se registraron variables de sexo, edad, altura de rebordes alveolares, altura de rama y cóndilo mandibulares, así como los hallazgos radiográficos. Resultados: Se encontraron 112 radiografías de pacientes con edentulismo total, 51,8 % con algún tipo de hallazgo. El más frecuente fueron los implantes 33,9 % seguido por restos radiculares en 13,4 %. No hubo diferencias en los promedios de las medidas óseas en los dos lados. Los hombres tienen mayor altura de reborde alveolar en el maxilar inferior que las mujeres (p<0,05). Los valores de altura condilar fueron similares para ambos sexos. Se encontró mayor valor de la altura de la rama mandibular en los hombres (p<0,05). Conclusiones: La frecuencia de hallazgos radiográficos en pacientes edéntulos totales es considerable. Las variaciones óseas ocasionadas por la ausencia de dientes, deben ser tenidas en cuenta para la toma de las decisiones clínicas de restauración con prótesis total o con implantes.

Background: According to the 2014 National Oral Health Study, 5.20 % of the Colombian population has total edentulism and 32.8 % in the population over 65 years of age. However, other parameters relevant to the correct approach to edentulism should be analyzed with radiographic studies. Purpose: To identify the frequency and characteristics of the findings and bone variations in panoramic radiographs of totally edentulous patients. Methods: A descriptive, observational study was carried out on 10.000 panoramic radiographs, from which those corresponding to patients with total edentulism were analyzed using the CliniView 9.3 program. Variables of sex, age, alveolar ridge height, mandibular branch height and condyle, as well as radiographic findings were recorded. Results: 112 radiographs of patients with total edentulism were found, 51.8 % with some type of incidental finding. Most frequent were implants 33.9 % followed by root remains in 13.4 %. There were no differences in the averages of the bone measurements on both sides. Men have higher alveolar ridge height in the lower jaw than women (p <0.05). Condylar height values were similar for both sexes. A higher value of the height of the mandibular branch was found in men (p <0.05). Conclusions: Frequency of radiographic incidental findings in total edentulous patients is considerable. The bony variations caused by the absence of teeth must be taken into account when making clinical decisions of restoration with total prosthesis or with implants.

[Study of the canalis mandibulae morphology in different vertical facial types]. / A canalis mandibulae lefutásának vizsgálata különbözo vertikális arctípusokban.

INTRODUCTION: The precise knowledge of the position of canalis mandibulae and foramen mandibulae is important for surgical and endodontic interventions on the mandible. AIM: The aim of the study is to examine the position of these anatomical landmarks in different vertical facial types. METHOD: In the panorama radiograph of 26 normodivergent, 26 hypodivergent and 28 hyperdivergent arthritis (total of 1360 measurements) we measured the distance between the canalis mandibulae and interdental septums, the apex of the lateral teeth, the mandibular base, the goniac angle, and the steepness of the canal and the distance the foramen mandibulae to the anterior and posterior margin of the ramus. RESULTS: ANOVA and t-test statistical analysis showed that the foramen mandibulae is farer from the posterior margin of the ramus in hipodivergent facial types, in hyperdivergent facial types the canalis mandibulae was closer to the root apex of posterior teeth and in hypodivergent types to the base of the mandible. In normal and hyperdivergent individuals, the canalis mandibulae runs steeper and in the course of running it is increasingly distanced from the tangent to the base of the mandible. CONCLUSION: The position of the canalis mandibulae and the foramen mandibulae showed significant differences in the different vertical facial types. Orv Hetil. 2017; 158(46): 1841-1847.

Frequency and position of the mental foramen in panoramic X-rays: literature review / Frecuencia y posición del foramen mental en radiografías panorámicas: revisión bibliográfica

The mental foramen (MF), located in the body of mandible in the region below the inferior premolars, is the anatomical structure through which the mental neurovascular bundle emerges. The MF can be seen clearly in panoramic X-rays. The object of the present study was to carry out a literature review in order to identify the frequency and position of the MF in panoramic X-rays. We looked for articles in the SCiELO, Pubmed, Scopus, LILACS, Web of Science and EBSCOhost databases, for the years 2006 to 2016. The key words used were "mental foramen", "mandibular canal", "inferior alveolar nerve", "anatomy" and "panoramic X-ray". Once the articles had been selected, an analysis was made of their methodological quality; poor-quality articles were excluded. In each article the frequency and position of the MF in each hemi-mandible was analyzed. We found 82 articles, of which 20 were retained after application of the exclusion criteria. The MF was found in 4,824 hemi-mandibles (95.2 %), with greater presence on the left side (50.29 %) than the right (49.71 %). The MF is most commonly located between the apices of the inferior premolars (42.22 %), coincident with the root of the second inferior premolar (33.98 %) or distal of the root of the second inferior premolar (10.98 %). The MF is a very frequent anatomical structure. Knowledge of its location is fundamental for reducing the risk of accidents and unexpected events during clinical and surgical manoeuvres.

El foramen mental (FM), ubicado en el cuerpo de la mandíbula, inferiormente a la región de los dientes premolares inferiores, es la estructura anatómica por donde emerge el paquete vásculonervioso mental. El FM se logra visualizar con buena precisión en una radiografía panorámica. El objetivo del presente estudio fue realizar una revisión de la literatura para identificar la frecuencia y posición del FM en radiografías panorámicas. Se buscaron artículos en las bases de datos SCiELO, Pubmed, Scopus, LILACS, Web of Science y EBSCOhost, entre los años 2006 y 2016. Las palabras clave utilizadas fueron "foramen mental", "canal mandibular", "nervio alveolar inferior", "anatomía" y "radiografía panorámica". Tras la selección de los artículos se realizó un análisis de la calidad metodológica de los mismos, donde se excluyó artículos de baja calidad. Se analizó en cada artículo la frecuencia y posición del FM en cada hemimandíbula. Se encontraron 82 artículos, de los cuales quedaron sólo 20 al aplicar criterios de exclusión. El FM fue encontrado en 4824 hemimandíbulas (95,2 %), siendo el lado izquierdo donde hubo mayor presencia de forámenes (50,29 %) en comparación al lado derecho (49,71 %). El FM se localiza entre los ápices de los premolares inferiores en 42,22 %, es coincidente con la raíz del segundo premolar inferior en 33,98 %, y es distal a la raíz del segundo premolar inferior en 10,98 %, siendo éstos los más relevantes. El FM es una estructura anatómica muy frecuente, ubicada en general inferiormente a los premolares inferiores. Es una estructura de gran importancia clínica, por ello el conocimiento detallado de sus características y variaciones anatómicas es muy importante para evitar complicaciones y disminuir el riesgo de accidentes durante procedimientos clínico-quirúrgicos en la región. Además, a pesar de que la RP presenta buena precisión en la identificación del FM hay condiciones clínicas que requieren otros métodos imagenológicos para su identificación.

Caracterización de la Impactación de Segundos Molares Mandibulares Permanentes en una Población Sudamericana / Characterization of Permanent Mandibular Second Molars Impaction in a Southamerican Population

El objetivo de este estudio fue describir las características epidemiológicas de segundos molares mandibulares permanentes impactados unilateralmente en una muestra de la ciudad de Medellín, Colombia. Se trató de un estudio retrospectivo en el cual se evaluaron radiografías panorámicas de 6785 pacientes, de las cuales se analizaron un total de 28 radiografías en la muestra final. Fueron correlacionados el segundo molar mandibular impactado (grupo de estudio) y el contralateral no impactado (grupo control) con respecto a tres ángulos de referencia (intermolar, del plano oclusal e interplanar), el sexo y lado de impactación. Se encontró una prevalencia de 3,5 por cada 1000 radiografías evaluadas. El lado de mayor impactación fue el derecho; dos de los tres ángulos analizados (intermolar e interplanar) fueron los que arrojaron las diferencias más grandes entre el grupo de estudio y el grupo control. No se encontraron diferencias estadísticamente significativas según el sexo. Se concluyó que la prevalencia de segundos molares mandibulares permanentes impactados es baja, siendo mayor en el lado derecho, sin diferencias por sexo, y de preferencia el uso del ángulo interplanar como medida para la evaluación del riesgo de impactación (>7,9°).

The objective of this study was to describe the epidemiological characteristics of unilateral permanent mandibular second molars impacted, in a sample from Medellín, Colombia. It was a retrospective study in which we evaluated panoramic radiographs of 6785 patients, for a total of 28 radiographs analyzed in the final sample. The mandibular second molar impacted (study group) and the contralateral not impacted (control group) were correlated, with respect to three reference angles (intermolar, of the oclussal plane and interplanar), sex and impaction side. We found a prevalence of 3.5 for every 1000 radiographs evaluated. The most frequent side of impaction was the right side; two of the three angular measurements (intermolar and interplanar) had the biggest differences between the study and control group. We did not find significant statistical differences between males and females. It was concluded that the prevalence of impacted permanent mandibular second molars is low, there is a highest impaction in the right side, there are no differences between genders, and the use of the interplanar angle is preferable as a measurement to predict the impaction of permanent mandibular second molars (>7.9°).