Background/Objectives: The purpose of this preliminary study was to evaluate the diagnostic performance of an AI-driven platform, Diagnocat (Diagnocat Ltd., San Francisco, CA, USA), for assessing endodontic treatment outcomes using panoramic radiographs (PANs). Materials and Methods: The study included 55 PAN images of 55 patients (15 males and 40 females, aged 12-70) who underwent imaging at a private dental center. All images were acquired using a Hyperion X9 PRO digital cephalometer and were evaluated using Diagnocat, a cloud-based AI platform. The AI system assessed the following endodontic treatment features: filling probability, obturation adequacy, density, overfilling, voids in filling, and short filling. Two human observers independently evaluated the images, and their consensus served as the reference standard. The diagnostic accuracy metrics were calculated. Results: The AI system demonstrated high accuracy (90.72%) and a strong F1 score (95.12%) in detecting the probability of endodontic filling. However, the system showed variable performance in other categories, with lower accuracy metrics and unacceptable F1 scores for short filling and voids in filling assessments (8.33% and 14.29%, respectively). The accuracy for detecting adequate obturation and density was 55.81% and 62.79%, respectively. Conclusions: The AI-based system showed very high accuracy in identifying endodontically treated teeth but exhibited variable diagnostic accuracy for other qualitative features of endodontic treatment.

Stroke is one of the major causes of death worldwide, and is closely associated with atherosclerosis of the carotid artery. Panoramic radiographs (PRs) are routinely used in dental practice, and can be used to visualize carotid artery calcification (CAC). The purpose of this study was to automatically and robustly classify and segment CACs with large variations in size, shape, and location, and those overlapping with anatomical structures based on deep learning analysis of PRs. We developed a cascaded deep learning network (CACSNet) consisting of classification and segmentation networks for CACs on PRs. This network was trained on ground truth data accurately determined with reference to CT images using the Tversky loss function with optimized weights by balancing between precision and recall. CACSNet with EfficientNet-B4 achieved an AUC of 0.996, accuracy of 0.985, sensitivity of 0.980, and specificity of 0.988 in classification for normal or abnormal PRs. Segmentation performances for CAC lesions were 0.595 for the Jaccard index, 0.722 for the Dice similarity coefficient, 0.749 for precision, and 0.756 for recall. Our network demonstrated superior classification performance to previous methods based on PRs, and had comparable segmentation performance to studies based on other imaging modalities. Therefore, CACSNet can be used for robust classification and segmentation of CAC lesions that are morphologically variable and overlap with surrounding structures over the entire posterior inferior region of the mandibular angle on PRs.

OBJECTIVE: To investigate the prevalence of tooth agenesis and associated dental anomalies in Latvian adolescent dental patients and compare it to other European countries.
METHODS: Cross-sectional study of 2692 11-to-14-year-old patients (39.9% males and 60.1% females) attending Riga Stradins University Institute of Stomatology with panoramic radiographs taken between August 2020 and September 2021. Patients with any genetic syndromes were excluded. Data on tooth agenesis (excluding third molars) and other dental anomalies were recorded.
RESULTS: The prevalence of tooth agenesis in Latvian adolescent dental patients was 9.3% with no statistically significant difference between genders (χ2 test, p = 0.472). The most commonly missing teeth were mandibular second premolars, followed by upper lateral incisors and upper second premolars. There was a statistically significant association with the presence of other dental anomalies in tooth agenesis patients (p < 0.001).
CONCLUSIONS: This study found that the prevalence of non-syndromic tooth agenesis in Latvian adolescent dental patients was 9.3% with no statistically significant differences between the genders. Patients with tooth agenesis have a statistically significant possibility of the presence of other dental anomalies (p < 0.001).

BACKGROUND: Accurate bracket positioning remains challenging. To avoid angulation errors, some recommend examining the panoramic radiograph during bonding. However, it can cause distortions. Cone-beam computed tomography (CBCT) provides a more precise panoramic reconstruction but with higher radiation doses. The main objective of this study is to compare the accuracy of axial positioning between direct bonding without radiography, with conventional panoramic radiograph, and with panoramic reconstruction from CBCT. The secondary objectives are to evaluate positioning accuracy of each tooth and to assess the influence of practitioner level of experience.
METHODS: Thirty practitioners, divided into two groups based on their experience performed direct bonding on a model thrice: without radiography, then with the conventional panoramic radiograph, then with the panoramic reconstruction from CBCT. Models were scanned, and angulation errors were measured using OrthoAnalyzer. Values were compared using the Friedman\'s test followed by the Bonferroni correction for multiple comparisons (P-value = 0.05).
RESULTS: For the low level of experience group, angulation errors were significantly greater than the accepted limit without radiographic reference, and significantly lower with CBCT reconstruction. For the high level of experience group, angulation errors were significantly lower than the accepted limit for the three bonding methods. For every tooth, using the panoramic reconstruction from CBCT as a reference, was the most accurate method, regardless of the level of experience. More experienced practitioners made fewer errors for the three methods.
CONCLUSIONS: Panoramic reconstruction from CBCT is the most accurate method to limit angulation errors during direct bonding. Conventional panoramic radiography remains a reliable tool if used with caution. Bonding without any radiographic reference should be avoided especially for less experienced practitioners.

Background/Objectives: Periapical lesions (PLs) are frequently detected in dental radiology. Accurate diagnosis of these lesions is essential for proper treatment planning. Imaging techniques such as orthopantomogram (OPG) and cone-beam CT (CBCT) imaging are used to identify PLs. The aim of this study was to assess the diagnostic accuracy of artificial intelligence (AI) software Diagnocat for PL detection in OPG and CBCT images. Methods: The study included 49 patients, totaling 1223 teeth. Both OPG and CBCT images were analyzed by AI software and by three experienced clinicians. All the images were obtained in one patient cohort, and findings were compared to the consensus of human readers using CBCT. The AI\'s diagnostic accuracy was compared to a reference method, calculating sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV), and F1 score. Results: The AI\'s sensitivity for OPG images was 33.33% with an F1 score of 32.73%. For CBCT images, the AI\'s sensitivity was 77.78% with an F1 score of 84.00%. The AI\'s specificity was over 98% for both OPG and CBCT images. Conclusions: The AI demonstrated high sensitivity and high specificity in detecting PLs in CBCT images but lower sensitivity in OPG images.

BACKGROUND: Diffuse idiopathic skeletal hyperostosis (DISH) is a potentially serious osteopathic disorder associated with coalescing ossifications of the anterior vertebrae and may be concomitant with a constellation of symptomatology and systemic comorbidities. There is limited dental literature describing this finding on panoramic radiographs and cone beam computed tomography (CBCT) scans.
METHODS: Two case reports of DISH are provided. One patient manifested extensive ossifications along the cervical vertebrae and consequent episodes of dysphagia and hoarseness. The other affected patient\'s cervical ossification was found at an earlier stage of formation and without symptomatology. Panoramic radiography, cervical spine radiography, and CBCT examinations have been provided.
CONCLUSIONS: Attending dental healthcare practitioners should carefully evaluate all areas of interest and surrounding fields of view when taking panoramic radiographs and CBCT scans for manifestations of DISH and other potential disorders of the cervical vertebrae. A suspected radiologic finding of DISH should prompt timely referral for comprehensive medical assessment to mitigate neurologic deficits and other comorbidities.

OBJECTIVE: The styloid process (SP) becomes clinically relevant when it shows enlargement (>30 mm) in the sense of an elongated SP (ESP) and/or increasing calcification leading to Eagle Syndrome (ES). Panoramic radiograph (PR) or computed tomography (CT) are part of the routine diagnostics in ES. Currently, CT is considered the gold standard. The aim of this study was to investigate the accuracy in the diagnostics/measurements of SP/ESP throughout a comparative study between PR and CT. Furthermore, in addition to measuring established parameters, this study aimed to determine the currently unexamined width in the base and tip of the SP.
METHODS: The present study examined the radiological findings of bilateral SP in 100 patients who received both PR and CT on the same day. Measurements of the length of the SP and width at the basis and tip were performed. Furthermore, calcification patterns, Langlais classification and the prevalence of ESP were analyzed.
RESULTS: There was a highly significant correlation between PR and CT measuring SP for every parameter. Males showed significantly longer SP than females among the age group between 18-75 years. The results of the length measurements of the SP (male: right SP=32.98 mm; left SP=35.21 mm; female: right SP=30.31 mm; left SP=30.92 mm) significantly exceeded the values of comparable studies.
CONCLUSIONS: Consequently, it can be concluded that PR provides accurate measurements when compared to CT for measuring and diagnosing SP/ESP/Eagle syndrome. This study was one of the first to examine the width of the SP in the base and tip, thus these measurements can serve as a baseline for further studies. Since the mean lengths of SP exceeded 30.0 mm in the present study, these findings raise the question of whether the cut-off of 30.0 mm is adequate for the diagnosis of ESP.

OBJECTIVE: This study aims to investigate the incidence and clinical characteristics of concomitant hypodontia and hyperdontia (CHH) by performing panoramic radiographs.
METHODS: A total of 41 648 panoramic radiographs of pediatric patients who were admitted to the hospitals from January 2019 to May 2021 were reviewed, and 145 CHH patients were included in the study. The presence of CHH was recorded. SPSS 24.0 software was used for statistical analysis.
RESULTS: The prevalence of CHH was 0.35% (145/41 648). Males (102 cases) were obviously more than females (43 cases), and the difference between genders was statistically significant (P<0.001). The features of congenital permanent tooth loss in this group were predominantly 1 and 2 teeth missing and preferably mandibular lateral incisors and mandibular second premolars missing. The incidence of congenital permanent teeth loss was higher in the mandible than in the maxilla (P<0.001), but no difference was found in the distribution between left and right (P=0.84). The features of supernumerary teeth in this group were 1 and 2 teeth, mostly in the maxillary anterior area, mostly conical, mostly vertical inversion and orthotopic growth.
CONCLUSIONS: CHH is a rare mixed numeric dental anomaly characterized by congenital missing teeth and supernumerary teeth occurring in the same individual. CHH cases are higher in men than in women. The characteristics of their hypodontia and hyperdontia are similar to those of patients with congenital permanent tooth absence or supernumerary teeth. Early diagnosis of the condition and a multidisciplinary approach for management of such case is recommended.
目的: 应用曲面体层技术探讨少牙多牙症（CHH）的发生率和临床特征。方法: 收集2019年1月—2021年5月就诊的41 648例儿童口腔科患者的曲面体层片，纳入CHH患者145例，观察记录CHH的发生情况。应用SPSS 24.0软件统计分析所得的数据。结果: CHH的发生率为0.35%（145/41 648），男性（102例）多于女性（43例），性别间差异有统计学意义（P<0.001）。恒牙先天缺失特征：缺失1~2颗为主；最好发下颌侧切牙和下颌第二前磨牙；下颌恒牙先天缺失多于上颌恒牙先天缺失，二者差异有统计学意义（P<0.001）；左侧先天缺失与右侧先天缺失差异无统计学意义（P=0.84）。多生牙特征：数目1~2颗；多见于上颌前牙区；多为圆锥形；垂直倒置生长和垂直正位生长为主。结论: CHH是一种少见的混合牙齿数目异常，男性多于女性，恒牙先天缺失和多生牙的特征与单独发生的恒牙先天缺失/多生牙的特征相似，建议早期诊断和多学科治疗。.

UNASSIGNED: To report the radiographic preferences during dental implant therapy in Palestine.
UNASSIGNED: Fourteen multiple-choice questions were delivered in electronic and hardcopy formats questionnaires during the Sixth International Implantology Conference (Palestine). The questions investigated the radiographic techniques that are mostly used based on various clinical scenarios and treatment phases.
UNASSIGNED: One hundred and thirty-seven responses were captured. The majority of the participants were general dentists with implant experience (79.6%). Less than a third of the participants (27.2%) were members of the Palestinian Association of Dental Implantology. The majority (85.9%) of them have their practice in a city zone. Panoramic radiograph (PAN) combined with cone beam computed tomography (CBCT) was the most preferred radiographic technique during the planning stage.
UNASSIGNED: PAN and CBCT was the preferred choice during the planning stages. A PAN was preferred postoperatively and if no complications were associated. In the case of symptomatic patients, CBCT was the radiograph of choice.

The aim of this study is to compare a technique using Convolutional Neural Network (CNN) with the Demirjian\'s method for chronological age estimation of living individuals based on tooth age from panoramic radiographs. This research used 5898 panoramic X-ray images collected for diagnostic from pediatric patients aged 4-17 who sought treatment at Antalya Oral and Dental Health Hospital between 2015 and 2020. The Demirjian\'s method\'s grading was executed by researchers who possessed appropriate training and experience. In the CNN method, various CNN architectures including Alexnet, VGG16, ResNet152, DenseNet201, InceptionV3, Xception, NASNetLarge, InceptionResNetV2, and MobieNetV2 have been evaluated. Densenet201 exhibited the lowest MAE value of 0.73 years, emphasizing its superior accuracy in age estimation compared to other architectures. In most age categories, the predicted age closely matches the actual age. The most inconsistent results are observed at ages 12 and 13. The results highlight correspondence between the age predicted by CNN and the Demirjian\'s approach. In conclusion, the results show that the CNN method is adequate to be an alternative to the Demirjian\'s age estimation method. We suggest that convolutional neural network can effectively optimize the accuracy of age estimation and can be faster than traditional methods, eliminating the need for additional learning from experts.