Search Results (7)

Background/Objectives: Our study aimed to determine the accuracy of the artificial intelligence-based Diagnocat system (DC) in detecting periapical lesions (PL) on panoramic radiographs (PRs). Methods: 616 teeth were selected from 357 panoramic radiographs, including 308 teeth with clearly visible periapical radiolucency and 308 without any periapical lesion. Three groups were generated: teeth with radiographic signs of caries (Group 1), teeth with coronal restoration (Group 2), and teeth with root canal filling (Group 3). The PRs were uploaded to the Diagnocat system for evaluation. The performance of the convolutional neural network in detecting PLs was assessed by its sensitivity, specificity, and positive and negative predictive values, as well as the diagnostic accuracy value. We investigated the possible effect of the palatoglossal air space (PGAS) on the evaluation of the AI tool. Results: DC identified periapical lesions in 240 (77.9%) cases out of the 308 teeth with PL and detected no PL in 68 (22.1%) teeth with PL. The AI-based system detected no PL in any of the groups without PL. The overall sensitivity, specificity, and diagnostic accuracy of DC were 0.78, 1.00, and 0.89, respectively. Considering these parameters for each group, Group 2 showed the highest values at 0.84, 1.00, and 0.95, respectively. Fisher’s Exact test showed that PGAS does not significantly affect (p = 1) the detection of PL in the upper teeth. The AI-based system showed lower probability values for detecting PL in the case of central incisors, wisdom teeth, and canines. The sensitivity and diagnostic accuracy of DC for detecting PL on canines showed lower values at 0.27 and 0.64, respectively. Conclusions: The CNN-based Diagnocat system can support the diagnosis of PL on PRs and serves as a decision-support tool during radiographic assessments. Full article

Panoramic radiography is vital in dentistry, where accurate detection and segmentation of diseased regions aid clinicians in fast, precise diagnosis. However, the current methods struggle with accuracy, speed, feature extraction, and suitability for low-resource devices. To overcome these challenges, this research introduces a unique YOLO-DentSeg model, a lightweight architecture designed for real-time detection and segmentation of oral dental diseases, which is based on an enhanced version of the YOLOv8n-seg framework. First, the C2f(Channel to Feature Map)-Faster structure is introduced in the backbone network, achieving a lightweight design while improving the model accuracy. Next, the BiFPN(Bidirectional Feature Pyramid Network) structure is employed to enhance its multi-scale feature extraction capabilities. Then, the EMCA(Enhanced Efficient Multi-Channel Attention) attention mechanism is introduced to improve the model’s focus on key disease features. Finally, the Powerful-IOU(Intersection over Union) loss function is used to optimize the detection box localization accuracy. Experiments show that YOLO-DentSeg achieves a detection precision (mAP50(Box)) of 87%, segmentation precision (mAP50(Seg)) of 85.5%, and a speed of 90.3 FPS. Compared to YOLOv8n-seg, it achieves superior precise and faster inference times while decreasing the model size, computational load, and parameter count by 44.9%, 17.5%, and 44.5%, respectively. YOLO-DentSeg enables fast, accurate disease detection and segmentation, making it practical for devices with limited computing power and ideal for real-world dental applications. Full article

Objectives: The present scoping review aims to provide a panoramic view of the current state of knowledge, highlighting the strengths, limitations, and future directions, on the use of CBCT in orthodontic practice. Methods: This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines to identify eligible studies from the following databases: PubMed, Scopus, and Web of Science. The research question was formulated as follows: “What is the scientific evidence concerning the preferential use of 3D CBCT over 2D radiography in orthodontics”? Results: Through database searching, 521 records were identified, and ultimately, 37 studies that compared 3D CBCT with 2D conventional radiography were included. Of these, 16 articles regarded the use of CBCT for cephalometric analysis, 5 papers analyzed the evaluation of root resorption, 10 studies evaluated the diagnostic accuracy of root angulation and determining tooth position, and the remaining 6 articles were conducted for miscellaneous applications: determining the size of the nasopharyngeal airway (n = 2), miniscrew positioning (n = 1), estimating cervical vertebrae maturity (n = 1), and evaluating the correctness of the root location when placing digital indirect brackets (n = 1). Conclusions: The choice between 3D CBCT or CBCT-generated radiography and conventional 2D radiography in orthodontics involves careful consideration of the specific clinical context, the complexity of the case, and the balance between the diagnostic advantages and the associated limitations. Future Directions: Future studies with a prospective design and standardized imaging protocols are encouraged to facilitate the development of a consensus on the best practices. Full article

Objective: The objective of this study was to evaluate external apical root resorption (EARR) in cases with extraction and non-extraction fixed orthodontic treatment. Methods: Ninety subjects were included in this study. The patients were divided into two groups: 43 with extraction treatment and 47 with non-extraction orthodontic treatment. EARR was measured using the crown-to-root ratio of the maxillary and mandibular incisors and canines on panoramic radiographs taken at the beginning (T0) and end of the treatment (T1). The Bonferroni corrected Z test was used for multiple comparisons. Results: There were 24 (55.8%) individuals in the extraction group and 12 (25.5%) in the non-extraction group, with a minimum of one tooth with severe resorption. There was no resorption in 0% of individuals in the extraction group and five (10.6%) individuals in the non-extraction group. There was a statistically significant correlation between the groups and the degree of resorption (p = 0.008). When the maxillary and mandibular teeth in the extraction group were compared, a significant difference was found in all degrees of resorption except for mild resorption. Conclusions: There was a significant difference in EARR between the extraction and non-extraction treatment groups, with maxillary incisors showing more resorption in the extraction treatment. Full article

Osteoporosis is often detected late and becomes severe because of a lack of subjective symptoms. Digital panoramic radiography (DPR) has been reported to be useful for osteoporosis screening based on the morphological classification of the mandibular inferior cortex. The purpose of this study was to evaluate the sensitivity and specificity of the mandibular cortical index (MCI) in the diagnosis of osteoporosis in a group of patients who were and were not using antiosteoporosis medication (AOM). Three hundred and fifty female patients aged 40 years or older who had DPR imaging performed during a 6-year period from December 2015 to February 2022 met the selection criteria. Two examiners recorded mandibular cortical width and MCI from the images. These results were statistically examined together with the patients’ demographic data. Forty-nine patients were using AOM (13 nonbisphosphonate/denosumab and 36 bisphosphonate/denosumab). MCI type 3 was the most common in the AOM group. In the MCI classification, DPR imaging among the AOM group was more sensitive (0.95) than that of the control group. This method of estimating osteoporosis based on MCI classification using DPR images has high sensitivity, especially in patients using AOM, suggesting that this method is useful as a screening test. Full article

The Panoramic radiography is the result of a radiological technique that allows the reproduction of the dental arches and the support structures of a unique image. The clinical utility of panoramic radiography allows the overall assessment as well as the detection of structural abnormalities and/or possibly relates to pathological lesions. The disadvantage of this technique is related to the lower quality of the images compared to endoral radiographs and TC scans but especially to the attempt to represent a three-dimensional, curved anatomic region on a two-dimensional plane. This inevitably leads to geometric distortions of shape, enlargements and overlaps that adversely affect the detection of any pathological entities. However, the most important advantage is the possibility of reducing patient exposure to ionizing rays. The aim of digital radiology is to improve the characteristics of radiological machinery (through increasingly innovative and sophisticated data processing software and hardware) in order to obtain high-quality images while reducing dosimetry and to reduce “disturbing elements” in radiological images. To overcome the limitations of the panoramic technique and to improve the quality of radiological images, and thus the effectiveness of diagnosis, image optimization software can be used. In this regard, a tool called Pipeline for Advanced Contrast Enhancement (PACE) is being developed: This is an algorithm that allows image quality to be improved by optimizing contrast and reducing brightness inhomogeneity, resulting in increased definition, making details more evident. The purpose of the proposed investigation is to evaluate if the application of the PACE algorithm in dental radiology could be an advantage because of the possibility of enhancing the quality of radiological images to make details of anatomical structures and related pathological lesions more obvious. Full article

In this digital era, dental students often search for online resources for self-directed learning. YouTube is one of the most commonly sought online platforms for educational or instructional videos. No prior study has examined the validity of panoramic radiography videos available on YouTube. This study provides a content analysis of these YouTube videos. A search for relevant YouTube videos was conducted in April 2022. The search string was: (panoramic OR pan OR OPG) AND (dental OR dentistry OR X-ray). The first 100 videos that resulted from the search and their related videos were screened. Exclusion criteria included irrelevance (e.g., no demonstration of panoramic radiography procedures) and non-English videos. For each included video, the following parameters were recorded: image receptor type, patient age, patient type (real patient, animation, or phantom head), patient preparation procedures, machine preparation, patient positioning, and operator safety. The number of views, comments, likes, and channel subscribers were recorded, as well as the video duration and the age of the video. Forty videos were included and analyzed. Most of the videos demonstrated digital panoramic radiography with an adult patient. Procedures on the patient and machine preparations as well as patient positioning were generally explained well. However, most videos did not well-demonstrate operator safety details concerning the use of adequate personal protective equipment. View count, comment count, and channel subscriber count positively correlated with the like count. Clinicians and students should carefully critique the content of such instructional videos and refer to the contents from other sources such as user manuals and latest recommendations from local authorities. Full article