Mandibular bone imaging assessment in thalassemia - a systematic review.

OBJECTIVE: This systematic review aimed to verify if individuals with thalassemia present changes in radiomorphometric indices and fractal analysis that can be accessed using panoramic radiographs. MATERIAL AND METHODS: Observational studies that evaluated cortical and trabecular bone patterns in dental routine radiographs were selected from six bibliographic databases. Risk of bias was analyzed using the Joanna Briggs Institute Critical Appraisal Checklists. Quality of evidence was verified using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach. RESULTS: Two hundred three studies were initially retrieved from databases. Three cross-sectional studies, encompassing a total of 129 thalassemic patients, were deemed eligible after applying the inclusion criteria. Bone mineral density (BMD) evaluations were performed using panoramic radiographs and considered the following radiomorphometric indexes: mandibular cortical index (MCI), mandibular cortical width (MCW), panoramic mandibular index (PMI). Fractal dimension analysis (FDA) and simple visual estimation (SVE) were also employed. Overall, FDA and MCW from thalassemia individuals were lower than controls. CONCLUSION: FDA and MCW are frequently altered in patients with thalassemia and may be employed as screening tools for reduced BMD. However, the certainty of evidence for this outcome was very low, mainly due to methodological flaws.

Prevalence of Radiolucent and Radiopaque Jawbone Lesions Using Panoramic Radiographic Analysis in Hail, Saudi Arabia: A Retrospective, Cross-Sectional, Observational Study.

Background Oral diseases are among the most prevalent public health issues worldwide, underscoring the importance of early diagnosis and effective prevention programs. Determining the prevalence of jawbone lesions is crucial for developing targeted interventions and ensuring timely treatment. Panoramic radiography, also known as orthopantomogram, has become a cornerstone in radiographic examinations, offering a comprehensive view of the dental and maxillofacial regions. Its accessibility and ability to detect a wide range of pathologies make it an invaluable diagnostic tool. This study aimed to assess the prevalence and distribution of radiolucent and radiopaque jawbone lesions in the population of Hail, Saudi Arabia, using panoramic radiographic analysis. Methodology A retrospective, cross-sectional study was conducted using pre-existing panoramic radiographs of individuals aged 18 years and older in Hail, Saudi Arabia. The radiographs were analyzed for the presence of jawbone lesions, classified as radiolucent, radiopaque, or mixed, and their anatomical distribution was recorded. Statistical analysis was performed using the chi-square test, with a significance level set at p-values <0.05. Results A total of 389 jawbone lesions were identified in 177 subjects, representing a prevalence of 45.5%. Radiolucent lesions were the most common, observed in 153 (39.3%) subjects, while radiopaque lesions were found in 18 (4.6%) subjects, and mixed lesions in six (1.5%) subjects. The mandible was more frequently affected than the maxilla, with 104 (59%) lesions occurring in the mandible and 52 (29%) lesions in the maxilla. The posterior region of the jaw was the most commonly involved site, accounting for 124 (31.9%) cases. Gender and age did not significantly influence the prevalence or type of lesions, although a higher incidence was noted in the 31-45-year age group. Conclusions This study revealed a significant prevalence of jawbone lesions in the Hail population, with radiolucent lesions being the most common type, predominantly affecting the posterior region of the mandible. The findings highlight the importance of early detection and targeted dental health initiatives in this region. Further research, particularly longitudinal studies, is recommended to explore the natural history of these lesions and their impact on oral health over time.

Mandibular morphology in schizophrenia patients compared with non-psychiatric controls using digital panoramic radiography: a retrospective cross-sectional study from Istanbul, Türkiye.

BACKGROUND: Schizophrenia is a chronic severe mental disorder characterized by impairment in cognition, emotion, perception, and other aspects of behavior. In light of the association of craniofacial dysmorphology with schizophrenia, mandibular morphology may provide clues about the role of neurodevelopment in the pathophysiology of schizophrenia. This retrospective cross-sectional study aimed to compare the mandibular morphology of patients with schizophrenia with controls using digital panoramic radiography (DPR). METHODS: 302 recorded diagnostic panoramic images obtained from 143 schizophrenia patients (98 males, 45 females), and 159 controls (73 males, 86 females), aged 18-45 years, were evaluated. Seven mandibular measurements consisting of ramus height, condylar height, gonial angle, antegonial angle, antegonial notch depth, ramal notch depth and bigonial width were measured from the DPRs in a double-blinded manner. Bivariate comparisons were carried out using the Independent t-test and Mann-Whitney U test. Logistic regression analysis was used for multivariate comparisons. RESULTS: Linear measurements were higher while angular measurements were lower in schizophrenia patients. Regression analyses indicated that female patients had greater ramus height (OR = 1.243; P = 0.001), condylar height (OR = 1.463; P = 0.048) and bigonial width (OR = 1.082; P < 0.001); male patients had greater ramus heights (OR = 1.216; P = 0.001) and bigonial width (OR = 1.076; P < 0.001) as well as lower antegonial angle (OR = 0.908; P = 0.012) compared to their respective controls. CONCLUSION: Quantitative differences in mandibular morphology in schizophrenia patients versus controls deserve attention and corroborate with the concept of abnormal neurodevelopment in schizophrenia.

Publicly Available Dental Image Datasets for Artificial Intelligence.

The development of artificial intelligence (AI) in dentistry requires large and well-annotated datasets. However, the availability of public dental imaging datasets remains unclear. This study aimed to provide a comprehensive overview of all publicly available dental imaging datasets to address this gap and support AI development. This observational study searched all publicly available dataset resources (academic databases, preprints, and AI challenges), focusing on datasets/articles from 2020 to 2023, with PubMed searches extending back to 2011. We comprehensively searched for dental AI datasets containing images (intraoral photos, scans, radiographs, etc.) using relevant keywords. We included datasets of >50 images obtained from publicly available sources. We extracted dataset characteristics, patient demographics, country of origin, dataset size, ethical clearance, image details, FAIRness metrics, and metadata completeness. We screened 131,028 records and extracted 16 unique dental imaging datasets. The datasets were obtained from Kaggle (18.8%), GitHub, Google, Mendeley, PubMed, Zenodo (each 12.5%), Grand-Challenge, OSF, and arXiv (each 6.25%). The primary focus was tooth segmentation (62.5%) and labeling (56.2%). Panoramic radiography was the most common imaging modality (58.8%). Of the 13 countries, China contributed the most images (2,413). Of the datasets, 75% contained annotations, whereas the methods used to establish labels were often unclear and inconsistent. Only 31.2% of the datasets reported ethical approval, and 56.25% did not specify a license. Most data were obtained from dental clinics (50%). Intraoral radiographs had the highest findability score in the FAIR assessment, whereas cone-beam computed tomography datasets scored the lowest in all categories. These findings revealed a scarcity of publicly available imaging dental data and inconsistent metadata reporting. To promote the development of robust, equitable, and generalizable AI tools for dental diagnostics, treatment, and research, efforts are needed to address data scarcity, increase diversity, mandate metadata completeness, and ensure FAIRness in AI dental imaging research.

A novel method for measuring the direction and angle of Central ray and predicting rotation center via panorama phantom.

OBJECTIVES: The aim of this study is to propose and evaluate a novel method for measuring the central ray direction and detecting the rotation center of panoramic radiography using the panorama phantom. METHODS: To determine the central ray direction, two points passing through the same x-coordinate in a panoramic radiograph were identified and connected. The angles formed by the central ray with the midline and the angle to the arch form were measured using mathematical calculations. Further, by analyzing the continuous changes in the central ray obtained in this manner, the movement of the rotation center was detected and visualized. RESULTS: The angle between the central ray and the midline exhibited a progressive decrease from the anterior to the posterior direction. With regards to the arch form, the angle of the central ray exhibited an increasing pattern as it moved from the anterior to the posterior direction, culminating in its peak value at the lower second premolar cusp region, followed by a consistent decrease. The rotation center approximately started from the distolateral aspect of the coronoid process and then anteromedially moved to the midline in a curved line passing between the mandibular notch and coronoid process. CONCLUSIONS: By using the panorama phantom, we successfully obtained the central ray direction and detected the rotation center of the panoramic radiography.

Evaluation of fractal analysis and radiomorphometric measurements of mandibular bone structure in bruxism and non-bruxism paediatric patients.

OBJECTIVES: The goal of this examination was to compare the impact of probable sleep/awake bruxism on the mandibular trabecular bone structure by fractal analysis (FA) with digital panoramic radiograph (DPR) and radiomorphometric measurements in paediatric patients with bruxism. METHODS: The examination included 130 participants with 63 patients with probable sleep/awake bruxism and 67 control groups. Bilateral regions of interest (ROI) in three regions were examined as ROI1: mandibular ramus, ROI2: mandibular angulus, ROI3: anterior to the molar teeth. Radiomorphometric measurements were taken of the mandibular cortical width (MCW), panoramic mandibular index (PMI), and mandibular cortical index (MCI). p < 0.05 was approved for statistical significance. RESULTS: The ROI-1, ROI-2, and ROI-3 values were defined to be statistically significantly high in the bruxism group (p < 0.05). No significant difference was found between the groups in the other values (p > 0.05). There was no difference in the age and gender for any of the parameters (p > 0.05). CONCLUSION: In children and adolescents, the mandibular trabecular bone can be affected by bruxism. FA can be used as an auxiliary method for finding the mandibular trabecular differences of patients with bruxism in paediatric dentistry just as it can for adults.

Fractal Analysis of Mandible in Panoramic Radiographs of Patients Received Radiotherapy for Nasopharyngeal Carcinoma.

PURPOSE: This study aimed to assess the impact of radiotherapy on the internal structure complexity of mandibular cortical and trabecular bone and to determine the duration required for a return to healthy values post-radiotherapy. MATERIALS AND METHODS: Panoramic radiographs from patients undergoing radiotherapy for nasopharyngeal carcinoma were analyzed before and after treatment. Four groups were formed based on post-radiotherapy radiography timing (0-6 months, 6-12 months, 12-24 months, and 24-36 months), comprising a total of 59 cases and 118 radiographs. Fractal analysis was conducted on four bilateral regions (ROI) in both trabecular and cortical bone on each radiograph. Additionally, measurements of inferior alveolar canal width and mandibular cortical width were performed. Mean and maximum radiation dose values to the mandible were measured, and their correlation with changes in fractal dimension, inferior alveolar canal width, and mandibular cortical width values was assessed. RESULTS: Fractal dimension values in regions over trabecular bone showed a statistically significant decrease in all groups, although no significant difference was observed among the four groups. In ROI-4 from cortical bone, a significant fractal dimension decrease was noted in all groups except the 0-6 month group. The magnitude of fractal dimension decrease was higher in the 12-24 and 24-36 month groups compared to the 0-6 month group. inferior alveolar canal width and mandibular cortical width values significantly decreased post-radiotherapy in all groups, with a consistent decrease across the groups. CONCLUSIONS: Radiotherapy induces a reduction in the internal complexity of trabecular and cortical bone structures in the mandible. Osteoradionecrosis risk persists even three years post-radiotherapy, suggesting a cautious approach to interventional procedures on the bone.

Automating Dental Condition Detection on Panoramic Radiographs: Challenges, Pitfalls, and Opportunities.

Background/Objectives: The integration of AI into dentistry holds promise for improving diagnostic workflows, particularly in the detection of dental pathologies and pre-radiotherapy screening for head and neck cancer patients. This study aimed to develop and validate an AI model for detecting various dental conditions, with a focus on identifying teeth at risk prior to radiotherapy. Methods: A YOLOv8 model was trained on a dataset of 1628 annotated panoramic radiographs and externally validated on 180 radiographs from multiple centers. The model was designed to detect a variety of dental conditions, including periapical lesions, impacted teeth, root fragments, prosthetic restorations, and orthodontic devices. Results: The model showed strong performance in detecting implants, endodontic treatments, and surgical devices, with precision and recall values exceeding 0.8 for several conditions. However, performance declined during external validation, highlighting the need for improvements in generalizability. Conclusions: YOLOv8 demonstrated robust detection capabilities for several dental conditions, especially in training data. However, further refinement is needed to enhance generalizability in external datasets and improve performance for conditions like periapical lesions and bone loss.

Evaluation of External Apical Root Resorption in Cases with Extraction and Non-Extraction Fixed Orthodontic Treatment.

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.

Artificial Intelligence (AI) Assessment of Pediatric Dental Panoramic Radiographs (DPRs): A Clinical Study.

This clinical study aimed to evaluate the sensitivity, specificity, accuracy, and precision of artificial intelligence (AI) in assessing permanent teeth in pediatric patients. Over one thousand consecutive DPRs taken in Kielce, Poland, with the Carestream CS9600 device were screened. In the study material, 35 dental panoramic radiographs (DPRs) of patients of developmental age were identified and included. They were automatically evaluated with an AI algorithm. The DPRs were then analyzed by researchers. The status of the following dichotomous variables was assessed: (1) decay, (2) missing tooth, (3) filled tooth, (4) root canal filling, and (5) endodontic lesion. The results showed high specificity and accuracy (all above 85%) in detecting caries, dental fillings, and missing teeth but low precision. This study provided a detailed assessment of AI performance in a previously neglected age group. In conclusion, the overall accuracy of AI algorithms for evaluating permanent dentition in dental panoramic radiographs is lower for pediatric patients than adults or the entire population. Hence, identifying primary teeth should be implemented in AI-driven software, at least so as to ignore them when assessing mixed dentition (ClinicalTrials.gov registration number: NCT06258798).

Evaluation of tooth development stages with deep learning-based artificial intelligence algorithm.

BACKGROUND: This study aims to evaluate the performance of a deep learning system for the evaluation of tooth development stages on images obtained from panoramic radiographs from child patients. METHODS: The study collected a total of 1500 images obtained from panoramic radiographs from child patients between the ages of 5 and 14 years. YOLOv5, a convolutional neural network (CNN)-based object detection model, was used to automatically detect the calcification states of teeth. Images obtained from panoramic radiographs from child patients were trained and tested in the YOLOv5 algorithm. True-positive (TP), false-positive (FP), and false-negative (FN) ratios were calculated. A confusion matrix was used to evaluate the performance of the model. RESULTS: Among the 146 test group images with 1022 labels, there were 828 TPs, 308 FPs, and 1 FN. The sensitivity, precision, and F1-score values of the detection model of the tooth stage development model were 0.99, 0.72, and 0.84, respectively. CONCLUSIONS: In conclusion, utilizing a deep learning-based approach for the detection of dental development on pediatric panoramic radiographs may facilitate a precise evaluation of the chronological correlation between tooth development stages and age. This can help clinicians make treatment decisions and aid dentists in finding more accurate treatment options.

Comparison of the accuracy and bias of Demirjian's method for East Asian children and development of Japanese population-specific age estimation formulae.

Despite the increased global mobility owing to the development of the international community, there remains a need for population-specific methods to estimate children's ages. Therefore, this study aimed to substantiate the necessity for a Japanese-specific age estimation method by contrasting the formerly reported age estimation accuracy and bias using Demirjian's method for Chinese, Taiwanese, South Korean, and Japanese children. We analyzed 1,558 panoramic radiographs from Japanese children (777 boys and 781 girls), assessed the maturity of seven left permanent teeth using Demirjian's criteria, and calculated the estimated age using Demirjian's method. The accuracy of the estimated ages was compared with previous reports of children from other East Asian countries which used the same age estimation method. Chinese, Taiwanese, and South Korean boys and girls were all reported to be older than their chronological ages, with the Eastern and Northern Chinese regions being the only exceptions. The same was true for Japanese children: the estimated ages of both sexes tended to be higher than their chronological age. However, there were significant variations in the values, indicating the differences in tooth growth and development between East Asian countries and sexes. Therefore, new regression equations specific to the Japanese population were formulated, and their accuracy was evaluated as the final result of this study.

Longitudinal Analysis of Diagnostic Accuracy of Panoramic Radiography in Oral Pathology.

Objective: The purpose of this 5-year longitudinal study was to assess the diagnostic accuracy of panoramic radiography (PR) in identifying oral pathology at a tertiary care facility. Methods: A retrospective review of patient files was done, encompassing those of patients who had PR for suspected oral lesions, followed by a biopsy. At various times, several diagnostic accuracy metrics were computed, such as sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic odds ratio (DOR). Results: The research had 250 patients in total. In terms of identifying oral pathology, PR showed a sensitivity of 85% and a specificity of 90%. There were 80% and 92% PPV and NPV, respectively. With a computed DOR of 25, PR's total discriminating power was found to be high. Conclusion: In summary, PR consistently demonstrates great diagnostic accuracy in identifying oral pathology at a tertiary care facility. These results confirm that PR is a useful screening technique for oral lesions in standard clinical practice. In order to overcome PR's shortcomings and investigate methods for enhancing its diagnostic effectiveness, more investigation is necessary.

An attempt to generate panoramic radiographs including jaw cysts using StyleGAN3.

OBJECTIVES: The purpose of this study was to generate radiographs including dentigerous cysts by applying the latest generative adversarial network (GAN; StyleGAN3) to panoramic radiography. METHODS: A total of 459 cystic lesions were selected, and 409 images were randomly assigned as training data and 50 images as test data. StyleGAN3 training was performed for 500 000 images. Fifty generated images were objectively evaluated by comparing them with 50 real images according to four metrics: Fréchet inception distance (FID), kernel inception distance (KID), precision and recall, and inception score (IS). A subjective evaluation of the generated images was performed by three specialists who compared them with the real images in a visual Turing test. RESULTS: The results of the metrics were as follows: FID, 199.28; KID, 0.14; precision, 0.0047; recall, 0.00; and IS, 2.48. The overall results of the visual Turing test were 82.3%. No significant difference was found in the human scoring of root resorption. CONCLUSIONS: The images generated by StyleGAN3 were of such high quality that specialists could not distinguish them from the real images.

Diagnostic accuracy of periapical radiography and panoramic radiography in the detection of apical periodontitis: a systematic review and meta-analysis.

OBJECTIVE: Apical periodontitis (AP) is one of the most common pathologies of the oral cavity. An early and accurate diagnosis of AP lesions is crucial for proper management and planning of endodontic treatments. This study investigated the diagnostic accuracy of periapical radiography (PR) and panoramic radiography (PAN) in the detection of clinically/surgically/histopathologically confirmed AP lesions. METHOD: A systematic literature review was conducted in accordance with the PRISMA guidelines. The search strategy was limited to English language articles via PubMed, Embase and Web of Science databases up to June 30, 2023. Such articles provided diagnostic accuracy values of PR and/or PAN in the detection of AP lesions or alternatively data needed to calculate them. RESULTS: Twelve studies met inclusion criteria and were considered for the analysis. The average value of diagnostic accuracy in assessing AP lesions was 71% for PR and 66% for PAN. According to different accuracy for specific anatomical areas, it is recommended to use PR in the analysis of AP lesions located in the upper arch and lower incisor area, whereas lower premolar and molar areas may be investigated with the same accuracy with PR or PAN. CONCLUSIONS: Two-dimensional imaging must be considered the first-level examination for the diagnosis of AP lesions. PR had an overall slightly higher diagnostic accuracy than PAN. Evidence from this review provided a useful tool to support radiologists and dentists in their decision-making when inflammatory periapical bone lesions are suspected to achieve the best clinical outcome for patients, improving the quality of clinical practice.

Diagnostic accuracy of artificial intelligence models in detecting osteoporosis using dental images: a systematic review and meta-analysis.

The current study aimed to systematically review the literature on the accuracy of artificial intelligence (AI) models for osteoporosis (OP) diagnosis using dental images. A thorough literature search was executed in October 2022 and updated in November 2023 across multiple databases, including PubMed, Scopus, Web of Science, and Google Scholar. The research targeted studies using AI models for OP diagnosis from dental radiographs. The main outcomes were the sensitivity and specificity of AI models regarding OP diagnosis. The "meta" package from the R Foundation was selected for statistical analysis. A random-effects model, along with 95% confidence intervals, was utilized to estimate pooled values. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool was employed for risk of bias and applicability assessment. Among 640 records, 22 studies were included in the qualitative analysis and 12 in the meta-analysis. The overall sensitivity for AI-assisted OP diagnosis was 0.85 (95% CI, 0.70-0.93), while the pooled specificity equaled 0.95 (95% CI, 0.91-0.97). Conventional algorithms led to a pooled sensitivity of 0.82 (95% CI, 0.57-0.94) and a pooled specificity of 0.96 (95% CI, 0.93-0.97). Deep convolutional neural networks exhibited a pooled sensitivity of 0.87 (95% CI, 0.68-0.95) and a pooled specificity of 0.92 (95% CI, 0.83-0.96). This systematic review corroborates the accuracy of AI in OP diagnosis using dental images. Future research should expand sample sizes in test and training datasets and standardize imaging techniques to establish the reliability of AI-assisted methods in OP diagnosis through dental images.

Artificial Intelligence Application in a Case of Mandibular Third Molar Impaction: A Systematic Review of the Literature.

Objective: This systematic review aims to summarize the evidence on the use and applicability of AI in impacted mandibular third molars. Methods: Searches were performed in the following databases: PubMed, Scopus, and Google Scholar. The study protocol is registered at the International Platform of Registered Systematic Review and Meta-analysis Protocols (INPLASY202460081). The retrieved articles were subjected to an exhaustive review based on the inclusion and exclusion criteria for the study. Articles on the use of AI for diagnosis, treatment, and treatment planning in patients with impacted mandibular third molars were included. Results: Twenty-one articles were selected and evaluated using the Scottish Intercollegiate Guidelines Network (SIGN) evidence quality scale. Most of the analyzed studies dealt with using AI to determine the relationship between the mandibular canal and the impacted mandibular third molar. The average quality of the articles included in this review was 2+, which indicated that the level of evidence, according to the SIGN protocol, was B. Conclusions: Compared to human observers, AI models have demonstrated decent performance in determining the morphology, anatomy, and relationship of the impaction with the inferior alveolar nerve canal. However, the prediction of eruptions and future horizons of AI models are still in the early developmental stages. Additional studies estimating the eruption in mixed and permanent dentition are warranted to establish a comprehensive model for identifying, diagnosing, and predicting third molar eruptions and determining the treatment outcomes in the case of impacted teeth. This will help clinicians make better decisions and achieve better treatment outcomes.

Genotoxicity and Micronucleus Formation as a Result of Panoramic Radiography in Epithelial Cells of the Buccal Mucosa: A Cross-sectional Study in Adults.

OBJECTIVES: To determine the genetic effects of panoramic radiography on the epithelial cells of the buccal mucosa by examining the micronucleus formation in these cells. MATERIALS AND METHODS: In this cross-sectional study, exfoliative cytology samples were prepared from the buccal mucosa of 36 patients immediately before and 10 days after panoramic radiography. The samples were prepared using liquid-based cytology with Papanicolaou staining. The slides were simultaneously evaluated by two expert pathologists and the ratio of the number of cells with micronuclei to the total number of cells on the slide was reported as a percentage. Data analysis was done using paired-samples T test, Pearson's correlation coefficient, and covariance analysis (α = 0.05). RESULTS: The study sample consisted of 24 (66.67%) males and 12 females (33.33%) with a mean (SD) age of 27.36 (8.19) years. The frequency of cells with micronucleus before and after panoramic radiography was not statistically different (p = 0.468). Additionally, the frequency of micronucleated cells was not correlated with age (p = 0.737) and sex (p = 0.211). CONCLUSION: Panoramic exposure slightly increased the frequency of cells with micronucleus in epithelial cells of the buccal mucosa. However, this increase was not statistically significant.

Evaluation of mandibular trabecular bone by fractal analysis in pediatric patients with hypodontia of the mandibular second premolar tooth.

BACKGROUND: It is still unclear whether the trabecular structure of the jaw is different in individuals with hypodontia than in those without hypodontia; this is important for clinicians. The aim was to determine whether the mandibular trabecular bone structure of children and adolescents with hypodontia differs from the control group by using the fractal analysis (FA) method in this study. METHODS: A total of 138 panoramic radiographs of 69 cases and 69 control subjects (mean age 13.2 ± 10.1) were evaluated. The age and gender of subjects in the case and control groups were matched. Three regions of interest (ROIs) were selected from the panoramic radiographs. ROI1 refers to the center of the ramus rising above the mandibular foramen. ROI2 refers to the area between the apical level of the mandibular molar and the upper border of the mandibular canal. ROI3, the missing tooth region, refers to the apical third of the mesial side of the erupting or fully erupted permanent mandibular first molar. Mann-Whitney U and Wilcoxon tests were used. p < 0.05 was accepted for the significance value. RESULTS: The mean fractal dimension (FD) values of ROI1, ROI2, and ROI3 were 1,25, 1,20, and 1,13, respectively. The means FD values obtained from the ramus region were higher than the other regions (p < 0.05). The FD values did not differ significantly according to gender and age (p > 0.05). The FD values of the case group were lower than the control group for ROI3 (p < 0.05). CONCLUSION: The results of this study showed that the mandibular trabecular bone quality of pediatric patients with one missing tooth was different from the healthy group. The difference in the mean FD values from the ROIs indicates that the ramus has a denser structure than the mandibular corpus. Clinicians should factor this into their dental treatment planning process.

Osteoporosis and Apical Periodontitis Prevalence: A Systematic Review.

Osteoporosis is a common systemic bone disorder in the elderly, characterized by low bone mineral density and deterioration of bone structure. Apical periodontitis is an inflammatory response to the microbial infection of root canals, typically characterized by apical bone destruction surrounding the tooth's apex. This systematic review aimed to determine if osteoporosis affects the prevalence of apical periodontitis in adults. PRISMA guidelines have been followed. It included randomized clinical trials, cross-sectional, cohort, and case-control studies, and excluded non-relevant investigations and various secondary sources. A comprehensive search was performed in PubMed, Scopus, and Web of Science, until 13 March 2024. The Newcastle-Ottawa Scale was used to assess the quality of the three selected studies: two cross-sectional studies and one case-control study. One investigation only included post-menopausal women recruited at a dental university clinic, the other integrated data from the total hospital patients' population, and the third selected patients referred to the university dental clinic from the university hospital. The findings varied: one study noted a marginal association between low bone mineral density and apical periodontitis, another found a significant association, and the third, with the lowest risk of bias, reported no link. The main limitations were the scarcity of eligible studies and their overall quality. The review was registered in the PROSPERO database (CRD42024523705), applied strict inclusion criteria and thorough searches by experienced and independent reviewers. There is no strong evidence that adult individuals with osteoporosis have a higher probability of developing apical periodontitis. However, clinicians should remain cautious of osteoporosis's potential impact on apical periodontitis development.