Common positioning errors in panoramic radiography: A review

AI-Powered Identification of Osteoporosis in Dental Panoramic Radiographs: Addressing Methodological Flaws in Current Research

Background: Osteoporosis, a systemic skeletal disorder, is expected to affect 60% of women over 50. While dual-energy X-ray absorptiometry (DXA) scans are the current gold standard for diagnosis, they are typically used only after fractures occur, highlighting the need for early detection tools. Initial studies have shown panoramic radiographs (PRs) to be a potential medium, but these have methodological flaws. This study aims to address these shortcomings by developing a robust AI application for accurate osteoporosis identification in PRs. Methods: A total of 348 PRs were used for development, 58 PRs for validation, and 51 PRs for hold-out testing. Initially, the YOLOv8 object detection model was employed to predict the regions of interest. Subsequently, the predicted regions of interest were extracted from the PRs and processed by the EfficientNet classification model. Results: The model for osteoporosis detection on a PR achieved an overall sensitivity of 0.83 and an F1-score of 0.53. The area under the curve (AUC) was 0.76. The lowest detection sensitivity was for the cropped angulus region (0.66), while the highest sensitivity was for the cropped mental foramen region (0.80). Conclusion: This research presents a proof-of-concept algorithm showing the potential of deep learning to identify osteoporosis in dental radiographs. Furthermore, our thorough evaluation of existing algorithms revealed that many optimistic outcomes lack credibility when subjected to rigorous methodological scrutiny.

Demirjian's and Cameriere's Methods for the Assessment of Dental Age Estimation in Children from a Southern Brazilian City

The chronological age estimation of living individuals is a crucial part of forensic practice and clinical practice, such as in orthodontic treatment. It is well-known that methods for age estimation in living children should be tested on different populations. Ethnic affiliations in Brazil are divided into several major groups depending on the region, with the south of Brazil being known for its German immigration. (1) Background: This study aimed to evaluate the correlation between chronological age and dental age using Demirjian's method and Cameriere's method in a group of children from Joinville, South Brazil to investigate if both methods can be used to estimate dental age in this population. (2) Methods: The sample consisted of 229 panoramic radiographs (119 were males and were 110 females) from Brazilian children (ages ranging from 6 to 12 years). The chronological age at the time of the panoramic radiographic exam was calculated for each child. The dental age was estimated according to Demirjian's method and Cameriere's method. All continuous data were tested for normality by using the Shapiro-Wilk test. The Pearson correlation coefficient test was applied. An alpha of 5% (p < 0.05) was used for all analyses. (3) Results: The mean chronological age was 8.75 years. According to Demirjian's method, the mean dental age was 9.3 years, while according to Cameriere's method, the mean dental age was 8.66 years. A strong correlation between chronological age and dental age according to Demirjian (r = 0.776 and p < 0.0001) and Cameriere (r = 0.735 and p < 0.0001) was observed for both genders. (4) Conclusions: Both methods presented a good correlation with chronological age in the studied population and could be used to assess dental age in this population.

Utilizing Deep Learning for Diagnosing Radicular Cysts

OBJECTIVES

The purpose of this study was to develop a deep learning algorithm capable of diagnosing radicular cysts in the lower jaw on panoramic radiographs.

MATERIALS AND METHODS

In this study, we conducted a comprehensive analysis of 138 radicular cysts and 100 normal panoramic radiographs collected from 2013 to 2023 at Clinical Hospital Dubrava. The images were annotated by a team comprising a radiologist and a maxillofacial surgeon, utilizing the GNU Image Manipulation Program. Furthermore, the dataset was enriched through the application of various augmentation techniques to improve its robustness. The evaluation of the algorithm's performance and a deep dive into its mechanics were achieved using performance metrics and EigenCAM maps.

RESULTS

In the task of diagnosing radicular cysts, the initial algorithm performance-without the use of augmentation techniques-yielded the following scores: precision at 85.8%, recall at 66.7%, mean average precision (mAP)@50 threshold at 70.9%, and mAP@50-95 thresholds at 60.2%. The introduction of image augmentation techniques led to the precision of 74%, recall of 77.8%, mAP@50 threshold to 89.6%, and mAP@50-95 thresholds of 71.7, respectively. Also, the precision and recall were transformed into F1 scores to provide a balanced evaluation of model performance. The weighted function of these metrics determined the overall efficacy of our models. In our evaluation, non-augmented data achieved F1 scores of 0.750, while augmented data achieved slightly higher scores of 0.758.

CONCLUSION

Our study underscores the pivotal role that deep learning is poised to play in the future of oral and maxillofacial radiology. Furthermore, the algorithm developed through this research demonstrates a capability to diagnose radicular cysts accurately, heralding a significant advancement in the field.

Effect of using different strips on reducing the most common error in panoramic imaging: A randomised controlled trial on palatoglossal air space shadow

INTRODUCTION

Panoramic radiography quality can be impaired by some errors such as positioning errors. Palatoglossal air space shadow error is one of the most common positioning errors and it is due to the tongue not sticking to the roof of the palate. Techniques used to deal with this error might help prevent unnecessary radiation to patients and save them time and money. The study aimed to investigate the effects of using celluloid matrix and edible tapes (fruit leather and chewing gum) on reducing the palatoglossal air space shadow error in panoramic imaging.

METHODS

In our study, 270 patients referred to the Department of Radiology were randomised into three groups: a control group, a celluloid matrix group and an edible tapes group. Before panoramic imaging, all patients were instructed to adhere their tongues to the roof of their mouths, with the distinction that for the celluloid matrix and edible tapes groups, patients were asked to place celluloid tapes, fruit leathers, or chewing gums on their tongues before doing so. The routine imaging process was then performed, and the results were compared across groups to evaluate the incidence of palatoglossal air space shadow error.

RESULTS

The number of error-free images in each fruit leather, chewing gum and celluloid tape group were significantly higher than the control group (all cases P < 0.05). The chances of error-free images in the fruit leather groups were the highest (9.57 times). The age (P = 0.136) and gender (P = 0.272) of patients had no significant effect on the results of interventions.

CONCLUSION

The application of fruit leathers, chewing gums and celluloid tapes reduced the palatoglossal air space shadow error of panoramic imaging.

Fully automated deep learning approach to dental development assessment in panoramic radiographs

BACKGROUND

Dental development assessment is an important factor in dental age estimation and dental maturity evaluation. This study aimed to develop and evaluate the performance of an automated dental development staging system based on Demirjian's method using deep learning.

METHODS

The study included 5133 anonymous panoramic radiographs obtained from the Department of Pediatric Dentistry database at Seoul National University Dental Hospital between 2020 and 2021. The proposed methodology involves a three-step procedure for dental staging: detection, segmentation, and classification. The panoramic data were randomly divided into training and validating sets (8:2), and YOLOv5, U-Net, and EfficientNet were trained and employed for each stage. The models' performance, along with the Grad-CAM analysis of EfficientNet, was evaluated.

RESULTS

The mean average precision (mAP) was 0.995 for detection, and the segmentation achieved an accuracy of 0.978. The classification performance showed F1 scores of 69.23, 80.67, 84.97, and 90.81 for the Incisor, Canine, Premolar, and Molar models, respectively. In the Grad-CAM analysis, the classification model focused on the apical portion of the developing tooth, a crucial feature for staging according to Demirjian's method.

CONCLUSIONS

These results indicate that the proposed deep learning approach for automated dental staging can serve as a supportive tool for dentists, facilitating rapid and objective dental age estimation and dental maturity evaluation.

Panoramic imaging errors in machine learning model development: a systematic review

OBJECTIVES

To investigate the management of imaging errors from panoramic radiography (PAN) datasets used in the development of machine learning (ML) models.

METHODS

This systematic literature followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses and used three databases. Keywords were selected from relevant literature.

ELIGIBILITY CRITERIA

PAN studies that used ML models and mentioned image quality concerns.

RESULTS

Out of 400 articles, 41 papers satisfied the inclusion criteria. All the studies used ML models, with 35 papers using deep learning (DL) models. PAN quality assessment was approached in 3 ways: acknowledgement and acceptance of imaging errors in the ML model, removal of low-quality radiographs from the dataset before building the model, and application of image enhancement methods prior to model development. The criteria for determining PAN image quality varied widely across studies and were prone to bias.

CONCLUSIONS

This study revealed significant inconsistencies in the management of PAN imaging errors in ML research. However, most studies agree that such errors are detrimental when building ML models. More research is needed to understand the impact of low-quality inputs on model performance. Prospective studies may streamline image quality assessment by leveraging DL models, which excel at pattern recognition tasks.

Third Molar Eruption in Dental Panoramic Radiographs as a Feature for Forensic Age Assessment-Presentation of a New Non-Staging Method Based on Measurements

The evaluation of third molar eruption in dental panoramic radiographs (DPRs) constitutes an evidence-based approach for forensic age assessment in living individuals. Existing methodologies involve staging morphological radiographic findings and comparing them to reference populations. Conversely, the existing literature presents an alternative method where the distance between third molars and the occlusal plane is measured on dental plaster models. The aim of this study was to adapt this measurement principle for DPRs and to determine correlation between eruption and chronological age. A total of 423 DPRs, encompassing 220 females and 203 males aged 15 to 25 years, were examined, including teeth 38 [FDI] and 48. Two independent examiners conducted the measurements, with one examiner providing dual assessments. Ultimately, a quotient was derived by comparing orthogonal distances from the mesial cementoenamel junctions of the second and third molars to a simplified radiological occlusal plane. This quotient was subsequently correlated with the individual's age. We estimated correlations between age and quotients, as well as inter- and intra-rater reliability. Correlation coefficients (Spearman's rho) between measurements and individuals' ages ranged from 0.555 to 0.597, conditional on sex and tooth. Intra-rater agreement (Krippendorf's alpha) ranged from 0.932 to 0.991, varying according to the tooth and sex. Inter-rater agreement ranged from 0.984 to 0.992, with distinctions drawn for different teeth and sex. Notably, all observer agreement values fell within the "very good" range. In summary, assessing the distance of third molars from a simplified occlusal plane in DPRs emerges as a new and promising method for evaluating eruption status in forensic age assessment. Subsequent reference studies should validate these findings.

Panoramic errors in pediatric patients with special needs

This study aimed to analyze the types and frequencies of panoramic technical errors in pediatric patients with special needs, as compared to matching images of patients with normal developmental patterns. Panoramic images of 100 pediatric patients, with equal numbers of either special needs or healthy controls, referred to our Oral Maxillofacial Imaging unit, were retrospectively examined by four blinded observers for the presence of four common technical errors: palatoglossal air space, movement, positioning errors, and foreign bodies appearance. In addition, they subjectively determined the image quality on an ordinal scale. The statistical examination included inter-observer correlation and correlations between demographic factors (age, gender, developmental status) and the number and types of errors. The frequencies of demonstrated errors were, in descending order: movement, positioning, palatoglossal air space, and foreign bodies' appearance. The special needs group images showed significantly more errors and were rated as low-quality radiographs. Younger patients in both groups showed more movement and positioning errors. Technical errors in panoramic images of patients with special needs were more frequently found. Therefore, increased awareness of the staff and appropriate pre-imaging instructions to the patients, are required when imaging pediatric patients, especially those with special needs.

Refinement of image quality in panoramic radiography using a generative adversarial network

OBJECTIVE

We aimed to develop and assess the clinical usefulness of a generative adversarial network (GAN) model for improving image quality in panoramic radiography.

METHODS

Panoramic radiographs obtained at Yonsei University Dental Hospital were randomly selected for study inclusion (n = 100). Datasets with degraded image quality (n = 400) were prepared using four different processing methods: blur, noise, blur with noise, and blur in the anterior teeth region. The images were distributed to the training and test datasets in a ratio of 9:1 for each group. The Pix2Pix GAN model was trained using pairs of the original and degraded image datasets for 100 epochs. The peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) were obtained for the test dataset, and two oral and maxillofacial radiologists rated the quality of clinical images.

RESULTS

Among the degraded images, the GAN model enabled the greatest improvement in those with blur in the region of the anterior teeth but was least effective in improving images exhibiting blur with noise (PSNR, 36.27 > 32.74; SSIM, 0.90 > 0.82). While the mean clinical image quality score of the original radiographs was 44.6 out of 46.0, the highest and lowest predicted scores were observed in the blur (45.2) and noise (36.0) groups.

CONCLUSION

The GAN model developed in this study has the potential to improve panoramic radiographs with degraded image quality, both quantitatively and qualitatively. As the model performs better in refining blurred images, further research is required to identify the most effective methods for handling noisy images.

How old are you? A systematic review investigating the relationship between age and mandibular third molar maturity

INTRODUCTION AND OBJECTIVE

Radiographic evaluation of the maturity of mandibular third molars is a common method used for age estimation of adolescents and young adults. The aim of this systematic review was to examine the scientific base for the relationship between a fully matured mandibular third molar based on Demirjian's method and chronological age, in order to assess whether an individual is above or below the age of 18 years.

METHODS

The literature search was conducted in six databases until February 2022 for studies reporting data evaluating the tooth maturity using Demirjian´s method (specifically stage H) within populations ranging from 8 to 30 years (chronological age). Two reviewers screened the titles and abstracts identified through the search strategy independently. All studies of potential relevance according to the inclusion criteria were obtained in full text, after which they were assessed for inclusion by two independent reviewers. Any disagreement was resolved by a discussion. Two reviewers independently evaluated the risk of bias using the assessment tool QUADAS-2 and extracted the data from the studies with low or moderate risk of bias. Logistic regression was used to estimate the relationship between chronological age and proportion of subjects with a fully matured mandibular third molar (Demirjian´s tooth stage H).

RESULTS

A total of 15 studies with low or moderate risk of bias were included in the review. The studies were conducted in 13 countries and the chronological age of the investigated participants ranged from 3 to 27 years and the number of participants ranged between 208 and 5,769. Ten of the studies presented the results as mean age per Demirjian´s tooth stage H, but only five studies showed the distribution of developmental stages according to validated age. The proportion of subjects with a mandibular tooth in Demirjian´s tooth stage H at 18 years ranged from 0% to 22% among males and 0 to 16% in females. Since the studies were too heterogenous to perform a meta-analysis or a meaningful narrative review, we decided to refrain from a GRADE assessment.

CONCLUSION

The identified literature does not provide scientific evidence for the relationship between Demirjian´s stage H of a mandibular third molar and chronologic age in order to assess if an individual is under or above the age of 18 years.

Fusion extracted features from deep learning for identification of multiple positioning errors in dental panoramic imaging

BACKGROUND

Dental panoramic imaging plays a pivotal role in dentistry for diagnosis and treatment planning. However, correctly positioning patients can be challenging for technicians due to the complexity of the imaging equipment and variations in patient anatomy, leading to positioning errors. These errors can compromise image quality and potentially result in misdiagnoses.

OBJECTIVE

This research aims to develop and validate a deep learning model capable of accurately and efficiently identifying multiple positioning errors in dental panoramic imaging.

METHODS AND MATERIALS

This retrospective study used 552 panoramic images selected from a hospital Picture Archiving and Communication System (PACS). We defined six types of errors (E1-E6) namely, (1) slumped position, (2) chin tipped low, (3) open lip, (4) head turned to one side, (5) head tilted to one side, and (6) tongue against the palate. First, six Convolutional Neural Network (CNN) models were employed to extract image features, which were then fused using transfer learning. Next, a Support Vector Machine (SVM) was applied to create a classifier for multiple positioning errors, using the fused image features. Finally, the classifier performance was evaluated using 3 indices of precision, recall rate, and accuracy.

RESULTS

Experimental results show that the fusion of image features with six binary SVM classifiers yielded high accuracy, recall rates, and precision. Specifically, the classifier achieved an accuracy of 0.832 for identifying multiple positioning errors.

CONCLUSIONS

This study demonstrates that six SVM classifiers effectively identify multiple positioning errors in dental panoramic imaging. The fusion of extracted image features and the employment of SVM classifiers improve diagnostic precision, suggesting potential enhancements in dental imaging efficiency and diagnostic accuracy. Future research should consider larger datasets and explore real-time clinical application.

Post-Traumatic-Related Technical Errors in Orthopantomographic Imaging

Background: This study aimed at identifying errors encountered in orthopantomography (OPG) in post-traumatic patients caused by limitations in performing a correct technique. Methods: A retrospective observational study was performed. Diagnosis, exposure/processing mistakes, positioning-related errors, and bimaxillary immobilization were evaluated. Results: Thirty panoramic radiographs with mandible fractures were examined. Twelve error types were encountered: errors in exposure or processing, air radiolucency in the palatoglossal space, errors in the alignment of the Frankfort horizontal plane: head in flexion, with a joyful expression or head extended, with a somber appearance, errors towards the mid-sagittal plane (lateral head inclination, deviation, or rotation), errors caused by the non-use of the bite-block or inappropriate position on the device, errors caused by positioning outside the focal plane, artifacts/shadow images produced by post-operative metal plates, and bimaxillary immobilization errors. The number of errors per radiograph ranged from two to a maximum of five. The most dominant ones were inappropriate alignment in the focal plane and lateral rotation of the head in over 70% of cases. Lateral deviation and palatoglossal air were present in more than 50% of images. Conclusions: In trauma cases, technical difficulties in obtaining a proper OPG image are common and often insurmountable, limiting the diagnosis.

Combined Deep Learning Techniques for Mandibular Fracture Diagnosis Assistance

Mandibular fractures are the most common fractures in dentistry. Since diagnosing a mandibular fracture is difficult when only panoramic radiographic images are used, most doctors use cone beam computed tomography (CBCT) to identify the patient's fracture location. In this study, considering the diagnosis of mandibular fractures using the combined deep learning technique, YOLO and U-Net were used as auxiliary diagnostic methods to detect the location of mandibular fractures based on panoramic images without CBCT. In a previous study, mandibular fracture diagnosis was performed using YOLO learning; in the detection performance result of the YOLOv4-based mandibular fracture diagnosis module, the precision score was approximately 97%, indicating that there was almost no misdiagnosis. In particular, fractures in the symphysis, body, angle, and ramus tend to be distributed in the middle of the mandible. Owing to the irregular fracture types and overlapping location information, the recall score was approximately 79%, which increased the detection of undiagnosed fractures. In many cases, fractures that are clearly visible to the human eye cannot be grasped. To overcome these shortcomings, the number of undiagnosed fractures can be reduced using a combination of the U-Net and YOLOv4 learning modules. U-Net is advantageous for the segmentation of fractures spread over a wide area because it performs semantic segmentation. Consequently, the undiagnosed case in the middle of the mandible, where YOLO was weak, was somewhat supplemented by the U-Net module. The precision score of the combined module was 95%, similar to that of the previous method, and the recall score improved to 87%, as the number of undiagnosed cases was reduced. Through this study, the performance of a deep learning method that can be used for the diagnosis of the mandibular bone has been improved, and it is anticipated that as an auxiliary diagnostic inspection device, it will assist dentists in making diagnoses.

Prevalence of dental anomalies in different facial patterns and malocclusions in an Iranian population

Objective

This study aimed to evaluate the prevalence and association of dental anomalies with different types of malocclusions and facial patterns.

Methods

In this cross-sectional study, the records of patients referred to the Orthodontics Department at 12-20 years of age were collected. The patients were classified into four types of malocclusion: Cl I, Cl II div 1, Cl II div 2, and Cl III, and three types of facial patterns: normal, long, and short. Fifteen dental anomalies were searched within the documents. The statistical analysis of data was performed with chi-squared and Fisher's exact test.

Results

Among 602 patients evaluated in this study, 28.6% were males, and 71.4% were females. The prevalence of Cl I, Cl II div1, Cl II div 2, and Cl III was 58.3%, 28.7%, 5.5%, and 7.5%, respectively. The normal facial pattern was most prevalent (47.2%), followed by the long facial pattern (41.4%) and short facial pattern (11.5%); 60.7% of the study population had at least one dental anomaly. Dilaceration was the most common anomaly (27.7%), followed by impaction (21.8%) and hypodontia (18.9%). Most dental anomalies were found in females, Cl II malocclusion, and long face samples. A statistically significant association was found between transposition and male gender (P = 0.006) and between short roots and Cl II malocclusion (P = 0.047). No significant association was found between dental anomalies and facial patterns.

Conclusion

Significant associations were reported between transposition and male gender and between short roots and Cl II malocclusion. In our population, dilaceration was the most common dental anomaly.

Quantitative Three-Dimensional Computed Tomography Measurements Provide a Precise Diagnosis of Fractures of the Mandibular Condylar Process

As 2D quantitative measurements are often insufficient, a standardized 3D quantitative measurement method was developed to analyze mandibular condylar fractures, and correlate the results with the mandibular condylar fracture classifications of Loukota and Spiessl and Schroll and clinical parameters. Thirty-two patients with a unilateral mandibular condylar fracture were evaluated using OPT, 2D (CB)CT images, and 3D imaging to measure the extent of the fractures. The maximum mouth opening (MMO) was measured. Ramus height loss could be measured only in OPT, but not in 2D CT images. The Intraclass Correlation Coefficient was excellent in the 3D measurements. In the Loukota classification, condylar neck fractures had the largest median 3D displacement and the highest rotations of the fracture fragments. The largest fracture volume was observed in base fractures. According to the Spiessl and Schroll classification, type V fractures had the largest median 3D displacement and the highest rotation in the X-axis and Z-axis. Type I fractures had the largest fracture volume. We found a moderate negative correlation between MMO and 3D displacement and rotation on Z-axis. The 2D quantitative analysis of condylar fractures is limited, imprecise, and not reproducible, while quantitative 3D measurements provide extensive, precise, objective, and reproducible information.

Panoramic radiography and patients with disability: a new simple breathing technique to reduce common airspace error

Patients with intellectual disabilities often fail to follow traditional tongue position instructions for panoramic radiographs resulting in missed pathology or unnecessary further radiation. This simple breathing technique is a new clinical instruction method for panoramic radiography developed to reduce the most common patient position error: patient failure to hold the tongue to the roof of the mouth. The technique is suitable for all patients including young patients and those with intellectual disabilities. The simple breathing technique uses 'tell-show-do' communication methods and does not mention the tongue but utilises the known tongue positions that occur during breathing and swallowing. This simple breathing technique instruction for panoramic radiography uses a demonstration of 'breathe-in, breathe-out, swallow, lips closed and hold still' to reduce the intensity of both the palatoglossal and pharyngeal airspaces on panoramic radiographs. This method, referred in this article as the simple breathing technique, can improve the diagnostic potential of panoramic radiographs and can be used with young children and patients with intellectual disabilities, and this slow breathing technique can help them further relax.

A retrospective institutional study of human age determination by evaluating the pulp length and width ratio of the maxillary lateral incisor on panoramic radiographs in Indonesian subjects

Purpose

The pulp length to width (PL/W) ratio of the maxillary lateral incisor can be used as an age determination method. This study aimed to investigate the correlation between the PL/W ratio of the maxillary lateral incisor on panoramic radiographs and human chronological age in Indonesian subjects.

Materials and Methods

This study analyzed with 134 maxillary lateral incisors on 113 panoramic radiographs from patients who visited the Oral and Maxillofacial Radiology Unit of Dental Hospital Universitas Padjadjaran, Bandung, Jawa Barat, Indonesia, from 2013 to 2018 (age range: between 11 to 60 years). The pulp length was measured from the pulp chamber roof to the apical foramen, and the pulp width was measured on the cervical area of the cementoenamel junction in millimeters using Fiji ImageJ open-source software. Simple linear regression (in SPSS) was used to analyze the results. The reliability of the observers was evaluated.

Results

The PL/W ratio of the maxillary lateral incisor was significantly correlated with chronological age (P<0.01). No statistically significant difference was found in the PL/W ratio between the left and right maxillary lateral incisors (P=0.333). There was a very strong correlation (r=0.939) between the PL/W ratio of the maxillary lateral incisor and human chronological age, with the following formula: age= -3.057+1.875×PL/W ratio (R²=0.882, standard error of estimate: 4.659).

Conclusion

The PL/W ratio of the maxillary lateral incisor on panoramic radiograph can be used for age determination in Indonesian subjects.

Improper patient positioning incidence for panoramic radiographic imaging of pediatric patients: Retrospective study

Background/Aim: Improper positioning of the patient reduces the diagnostic quality of panoramic radiographs. It is important to perfect the panoramic patient positioning technique to avoid unnecessary repeat exposures especially in pediatric patients. In this study, pediatric patient sample of records collected from an oral and dental health center were analyzed to determine the relative incidence of positioning errors of panoramic radiographs. Material and Methods: 3788 (1928 girls, 1860 boys) digital panoramic radiographs obtained from the stored data in the system were selected randomly. The radiographs were evaluated by two radiology specialists, by recording separately. The positioning errors of the images were categorized into ten groups: the chin tipped high, chin tipped low, a slumped position, the patient positioned forward, the patient positioned backward, failure to position the tongue against the palate, patient movement during exposure, the head tilted, and the head turned to one side. The results were statistically analyzed for positioning errors according to age and gender. Results: In 3788 radiographs, 2138 (56.4%) were error-free and 1650 (43.6%) were present with positioning errors. In the improper images, a single positional error was present in 1379 (83.6%); two positional errors were present in 248 (15%) and three or more positional errors in 23 (1.4%). The most common error observed was the tongue not being in contact with the hard palate (32.1%). On the other hand, the least common experienced error was patient movement during exposure (2.0%). Conclusions: The positioning errors of panoramic radiographs were common in the sample group of this study. Careful patient positioning can play a significant role in improving the radiographic quality and reducing the number of retakes.

A fully automated method of human identification based on dental panoramic radiographs using a convolutional neural network

OBJECTIVES

This study aimed to develop a fully automated human identification method based on a convolutional neural network (CNN) with a large-scale dental panoramic radiograph (DPR) data set.

METHODS

In total, 2760 DPRs from 746 subjects who had 2-17 DPRs with various changes in image characteristics due to various dental treatments (tooth extraction, oral surgery, prosthetics, orthodontics, or tooth development) were collected. The test data set included the latest DPR of each subject (746 images) and the other DPRs (2014 images) were used for model training. A modified VGG16 model with two fully connected layers was applied for human identification. The proposed model was evaluated with rank-1, -3, and -5 accuracies, running time, and gradient-weighted class activation mapping (Grad-CAM)-applied images.

RESULTS

This model had rank-1, -3, and -5 accuracies of 82.84%, 89.14%, and 92.23%, respectively. All rank-1 accuracy values of the proposed model were above 80% regardless of changes in image characteristics. The average running time to train the proposed model was 60.9 s per epoch, and the prediction time for 746 test DPRs was short (3.2 s/image). The Grad-CAM technique verified that the model automatically identified humans by focusing on identifiable dental information.

CONCLUSION

The proposed model showed good performance in fully automatic human identification despite differing image characteristics of DPRs acquired from the same patients. Our model is expected to assist in the fast and accurate identification by experts by comparing large amounts of images and proposing identification candidates at high speed.

Basic Knowledge and New Advances in Panoramic Radiography Imaging Techniques: A Narrative Review on What Dentists and Radiologists Should Know

Objectives: A panoramic radiograph (PAN) is the most frequently diagnostic imaging technique carried out in dentistry and oral surgery. The correct performance of image acquisition is crucial to obtain adequate image quality. The aim of the present study is to (i) review the principles of PAN image acquisition and (ii) describe positioning errors and artefacts that may affect PAN image quality. Methods: Articles regarding PAN acquisition principles, patient’s positioning errors, artefacts, and image quality were retrieved from the literature. Results: Head orientation is of the utmost importance in guaranteeing correct image acquisition. Symmetry, occlusal plane inclination, mandibular condyles localization, cervical spine position, aspect of upper teeth root apexes, exposure parameters, and metal and motion artefacts are factors that greatly affect the image quality of a successful PAN. Conclusions: Several factors are the basis for PAN performance; therefore, a systematic approach that takes into account correct patient positioning and preparation is strongly suggested to improve overall examination quality.

Imaging studies used as aid in the diagnosis of cleidocranial dysplasia. A review

Cleidocranial dysplasia (CCD), also known as Marie-Sainton syndrome, is a rare disorder of autosomal dominant type that presents specific characteristics at the skeletal and dental level. The diagnosis of CCD is based on clinical and radiographic findings. Panoramic, cephalometric and anterior poster radiographs have been used for its diagnosis in dentistry. However, these radiological techniques have limitations, and advances in technology with new imaging studies such as magnetic resonance imaging (MRI) and ultrasound have emerged, contributing to the diagnosis of CCD. Therefore, the aim of this review was to identify and describe current imaging studies that contribute to both the diagnosis and adequate and efficient treatment planning of CCD, and describe the clinical and radiographic characteristics of patients with this syndrome.

Evaluation of Panoramic Radiographs in Relation to the Mandibular Third Molar and to Incidental Findings in an Adult Population

OBJECTIVES

 The aim was to evaluate the characteristics of the mandibular third molars, especially in relation to the inferior alveolar nerve. Further aims were to investigate incidental findings in panoramic radiographs in an adult population, and to investigate image quality related to patient positioning.

MATERIALS AND METHODS

 From a previous study with 451 randomly selected adult participants who lived in Sweden, 442 panoramic radiographs from four dental public health clinics were used. The third molars' characteristics and relation to inferior alveolar nerve were evaluated. Incidental findings and patient positioning were recorded.

STATISTICAL ANALYSIS

 Frequency analysis was used to investigate the occurrence of all findings and their possible interconnections. Whether the patients' age or gender had an impact or not was also analyzed.

RESULTS

 The third molars were erupted in vertical position among 73% regardless of age. When retained or semi-retained, they were most commonly in mesioangular positions. The inferior alveolar nerve was located inferior to the roots in 52%, whereas an overlapped position was most common if the third molar was retained (90%), semi-retained (83%) or the age was less than 30 years (66%). Common incidental findings were apical radiolucencies, idiopathic osteosclerosis, and tooth fragments. Suboptimal patient positioning was found in one-third of the radiographs.

CONCLUSIONS

 Panoramic radiography is a useful method to evaluate third molar prior to surgical removal and may be the only image required. Most incidental findings on panoramic radiographs does not seem to require any further odontological management.

A Secondary Analysis of Panoramic Radiographs Reveals Hotspots in the Maxillofacial Region Associated with Diabetes

Diabetes mellitus is the putative cause of a number of pathologies occurring in the bony and soft tissues of the maxillo-facial region and is known to exacerbate other oral diseases such as periodontitis.We present the first use of clinical panoramic radiographs for a secondary analysis of disease, with a focus on identifying hotspots in the maxillofacial region that are associated with diabetes. We developed a curated data set using Consensus Landmark Points (CLPs) and used that data to develop an analysis pipeline. This pipeline entailed automatic data cleansing, registration, and intensity normalization. The pipeline was used to process 7280 uncurated images that were subsequently analyzed using pixel-wise methods for a case/control study of patients with a history of diabetes. We detected statistically significant clusters of pixels that demarcated anatomical hotspots specific to the diabetic patients.

Prediction of maxillary canine impaction based on panoramic radiographs

OBJECTIVES

The objective of this article is to establish a large sample-based prediction model for maxillary canine impaction based on linear and angular measurements on panoramic radiographs and to validate this model.

MATERIALS AND METHODS

All patients with at least two panoramic radiographs taken between the ages of 7 and 14 years with an interval of minimum 1 year and maximum 3 years (T1 and T2) were selected from the Department of Oral Health Sciences, University Hospital Leuven database. Linear and angular measurements were performed at T1. From 2361 records, 572 patients with unilateral or bilateral canine impaction were selected at T1. Of those, 306 patients were still untreated at T2 and were used as study sample. To construct the prediction model, logistic regression analysis was used.

RESULTS

The parameters analyzed through backward selection procedure were canine to midline angle, canine to first premolar angle, canine cusp to midline distance, canine cusp to maxillary plane distance, sector, quadratic trends for continuous predictors, and all pairwise interactions. The final model was applied to calculate the likelihood of impaction and yielded an area under the curve equal to 0.783 (95% CI [0.742-0.823]). The cut-off point was fixed on 0.342 with a sensitivity of 0.800 and a specificity of 0.598. The cross-validated area under the curve was equal to 0.750 (95% CI [0.700, 0.799]).

CONCLUSION

The prediction model based on the above mentioned parameters measured on panoramic radiographs is a valuable tool to decide between early intervention and regular follow-up of impacted canines.

Evaluation of bone texture imaging parameters on panoramic radiographs of patients with Sheehan's syndrome: a STROBE-compliant case-control study

Sheehan's syndrome (SHS) is a rare condition related to the risk of osteoporosis and evaluation of bone texture imaging features on panoramic radiographs would be suitable for this condition, which was the aim of the present study. Fractal dimension, lacunarity, and trabecular morphologic aspects were significantly altered in these patients.

INTRODUCTION

SHS is an important public health problem particularly in developing countries. It is characterized as postpartum hypopituitarism secondary to obstetric complications-related ischemic pituitary necrosis that shows significant systemic metabolic repercussions. Thus, this study aimed to evaluate bone texture parameters in digital panoramic radiographs of patients with SHS.

METHODS

A case-control study was conducted with 30 SHS patients from an Endocrinology and Diabetology Service of reference in Brazil, and 30 age- and sex-matched healthy controls. A custom computer program measured fractal dimension, lacunarity, and some morphologic features in the following mandibular regions of interest (50 × 50 pixels): below the mental foramen (F1), between the first and second molars (M1), and at the center of the mandibular ramus (R1).

RESULTS

The fractal analysis showed a statistically significant difference between the studied groups in all regions of interest. The fractal dimension in F1 (p = 0.016), M1 (p = 0.043), and R1 (p = 0.028) was significantly lower in SHS group, as well as lacunarity in R1 (p = 0.008). Additionally, several morphologic features were statistically significant in the SHS group (p < 0.05).

CONCLUSION

Therefore, individuals with SHS showed altered imaging texture parameters on panoramic radiographs, which reflect a smaller spatial organization of the bone trabeculae and, possibly, a state of reduced mineral bone density.

Development of a new ball-type phantom for evaluation of the image layer of panoramic radiography

Purpose

This study proposes a new ball-type phantom for evaluation of the image layer of panoramic radiography.

Materials and Methods

The arch shape of an acrylic resin phantom was derived from average data on the lower dental arch in Korean adult males. Metal balls with a 2-mm diameter were placed along the center line of the phantom at a 4-mm mesiodistal interval. Additional metal balls were placed along the 22 arch-shaped lines that ran parallel to the center line at 2-mm buccolingual intervals. The height of each ball in the horizontal plane was spaced by 2.5 mm, and consequently, the balls appeared oblique when viewed from the side. The resulting phantom was named the Panorama phantom. The distortion rate of the balls in the acquired image was measured by automatically calculating the difference between the vertical and horizontal length using MATLAB®. Image layer boundaries were obtained by applying various distortion rate thresholds.

Results

Most areas containing metal balls (91.5%) were included in the image layer with a 50% distortion rate threshold. When a 5% distortion rate threshold was applied, the image layer was formed with a small buccolingual width along the arch-shaped center line. However, it was medially located in the temporomandibular joint region.

Conclusion

The Panorama phantom could be used to evaluate the image layer of panoramic radiography, including all mesiodistal areas with large buccolingual width.

Automatic analysis algorithm for acquiring standard dental and mandibular shape data using cone-beam computed tomography

This study aims to introduce a new algorithm developed using retrospective cone-beam computed tomography (CBCT) data to obtain a standard dental and mandibular arch shape automatically for an optimal panoramic focal trough. A custom-made program was developed to analyze each arch shape of randomly collected 30 CBCT images. First, volumetric data of the mandible were binarized and projected in the axial direction to obtain 2-dimensional arch images. Second, 30 patients’ mandibular arches were superimposed on the center of the bilateral distal contact points of the mandibular canines to generate an average arch shape. Third, the center and boundary of a panoramic focal trough were obtained using smoothing splines. As a result, the minimum thickness and transition of the focal trough could be obtained. If this new algorithm is applied to big data of retrospective CBCT images, standard focal troughs could be established by race, sex, and age group, which would improve the image quality of dental panoramic radiography.

Reliability and validity of mandibular posterior vertical asymmetry index in panoramic radiography compared with cone-beam computed tomography

INTRODUCTION

The purposes of this study were to compare the asymmetry index using panoramic radiography and cone-beam computed tomography for detecting mandibular posterior asymmetry and to evaluate the diagnostic value of the asymmetry index on panoramic radiography.

METHODS

A total of 43 patients were included in this study. Ten mandibular posterior distances were measured using panoramic radiography and cone-beam computed tomography, and 10 asymmetry index values were calculated. The reliability of each asymmetry index was assessed. For evaluating validity of each asymmetry index using panoramic radiography, the paired t test and the Bland-Altman analysis were used. The accuracy of the asymmetry index and the area under the curve of receiver operator characteristic were calculated.

RESULTS

The asymmetry index of total ramal height showed good reliability (ICC, >0.888). In condylar height 1, specificity and negative predictive value were low (0.08 and 0.17, respectively), 95% limits of agreement were ±17.9%, and area under the curve was 0.484. In total, ramal height accuracy was 0.86, and areas under the curve were 0.926 to 0.957.

CONCLUSIONS

For detecting asymmetry of the condyle region, the asymmetry index using panoramic radiography had little diagnostic value, and we recommend using cone-beam computed tomography images. However, the asymmetry index for total ramal height showed good reliability and relatively higher validity, and its diagnostic value was excellent.

An investigation in to the impact of acquisition location on error type and rate when undertaking panoramic radiography

INTRODUCTION

Panoramic radiography is a common radiographic examination carried out in the UK. This study was carried out to determine if acquisition site has an impact on image quality.

METHODS

An image quality audit was carried out in South Wales across a number of dental and general radiology settings. The image quality was assessed retrospectively against national standards. A total of 174 radiographs were assessed from general radiology departments and 141 from dental radiology units. Chi-squared analysis was used to investigate whether there were differences in the grading between dental radiology units and general radiology departments. Differences between the two settings in terms of the number of errors in the radiographs was analysed using the Mann-Whitney test. Chi-squared analysis was used to see if there were differences between the types of errors in the two clinical settings.

RESULTS

There was a significant association (p = 0.021) between the quality of the radiograph grading and type of radiology department. However when excellent and diagnostically acceptable radiographs were grouped together there was no significant difference between the two clinical settings. Although the vast majority of radiographs were diagnostic (89% for general radiology and 92% for dental radiology units), neither reached the required standards. The most common errors were patient positioning errors (54.6% radiographs affected) and preparation/instructional errors (47.9% radiographs affected).

CONCLUSION

Errors in panoramic radiography are relatively high and further instruction to staff undertaking these procedures is required to ensure the targets are reached.

Mandibular Canal Enlargement: Clinical and Radiological Characteristics

Enlargement of the mandibular canal is a rare radiological finding. Clinically, it may or may not be associated with sensory deficits. We report four cases of widening of the mandibular canal observed with various methods of imaging with different clinical characteristics. We describe this unique radiological finding and elaborate the importance of quality assessment of the imaging that is vital for accurate diagnosis and treatment planning. Clinicians should be mindful when assessing the imaging whenever the size of the mandibular canal is implicated. The case ranged from a benign tumor to malignancy, radiological errors, and artifacts. A more superior imaging or treatment modality was necessary to ascertain the diagnosis.

Can tongue shadow in panoramic radiographs be avoided by using the tongue repositioning maneuver?

OBJECTIVE

The purpose of this study was to evaluate the use of the tongue repositioning maneuver (TRM) during panoramic radiography so as to avoid the error of tongue shadow.

STUDY DESIGN

A total of 300 panoramic radiographs were evaluated. One hundred and fifty orthopantomograms with conventional positioning technique were used as a control group, while other 150 were taken with the patient performing the TRM. The tongue shadow was measured in each radiograph in the first molar regions bilaterally and in the midsagittal plane. Wilcoxon Mann-Whitney U-Test was used to test the significance difference between the groups.

RESULTS

The tongue-palate distance in the study group was reduced from a mean value of 6.4 mm to 1 mm in the right first molar, 8.0 mm to 2.2 mm in the midsagittal region, and 6.6 mm to 1.2 mm in the left first molar position. Statistical evaluation exhibited significant differences of tongue shadow at all measuring sites between study and control group (P < .0001).

CONCLUSIONS

The present study demonstrates that the TRM leads to a substantial reduction of the tongue position error in panoramic radiography.

Assessment of panoral radiograph quality in a dental treatment center

Purpose

The quality of orthopantogram (OPG) images is primarily a function of patient positioning during image capture. The purpose of the investigation was to evaluate the quality of digital panoral radiographic images obtained by using the same imaging device in a large dental treatment center on the basis of the radiography technician operator securing the image.

Materials and Methods

Three hundred OPGs radiographs taken on a Kodak 8000C Digital Panoramic and Cephalometric System device in a large dental treatment center comprised the sample. The most recent OPGs beginning at May 2010 through 2007 were selected for three radiography technicians until subgroups of 100 OPGs per technician were obtained. Each panoral was evaluated by two investigators for 21 OPG image errors.

Results

Mean panoral total score was 14.71 and mean grade was 2.41 for the entire sample indicating a “good” quality. Significant differences were found among technicians for 3 of 21 panoral fault variables. The relative contribution to inferior OPG quality was greatest for the following positioning faults in rank order: Gazebo effect (11.3%), condyles pushed out (11.0%), unclear nasal structures (10.0%), airspace over U6s (9.5%), and condyles image top (9.0%).

Conclusions

There were no significant differences among technicians for overall quality indicators (total score and grade). However, statistically significant differences among the three technicians were found for image error wide anterior teeth, Gazebo effect, and unclear nasal structures.

Imaging findings of bisphosphonate-related osteonecrosis of the jaws: a critical review of the quantitative studies

Objectives. This paper offers a critical review of published information on the imaging strategies used for diagnosing bisphosphonate-associated osteonecrosis of the jaw (BRONJ) in patients taking intravenous bisphosphonates, pointing at the different methodologies and results of existing literature. Methods. Electronic literature search was performed in order to identify as many quantitative studies that discussed the imaging findings of BRONJ up to February 2014. Initially, the search for articles was based on the following four types of imaging modalities for evaluating BRONJ: computed tomography, plain film radiographs, magnetic resonance imaging, and nuclear bone scanning. Results. Eleven out of the 79 initially selected articles met the inclusion criteria. Most of the selected articles were cross-sectional studies. Regarding the selected studies, 54.5% have used plain films radiographs and 54.5% were based on computed tomography findings. All of the selected studies showed a small number of patients and none of the selected studies have tested the accuracy of the imaging examination for evaluating BRONJ. Conclusions. This critical review showed a scarcity of quantitative studies that analyzed the typical imaging findings related to BRONJ. Further studies are necessary in order to analyze the role of different imaging techniques in the assessment of BRONJ.