The aim of this study was to evaluate cortical bone formation on the mandibular condyle using cone-beam computed tomography (CBCT) in asymptomatic adolescents and young adults and to evaluate the relationship between age and sex. CBCT images that can evaluate the shape of the mandibular condyle were selected from asymptomatic patients aged 13–25. The degree of cortication on the mandibular condyle (CMC) was evaluated using CBCT images reconstructed in the axial, sagittal, and coronal planes. CBCT data of 829 patients (413 males, 416 females) were selected and then the left and right images of all patients were acquired; consequently, a total of 1658 temporomandibular joint-related images were evaluated in this study. The degree of CMC was correlated with age in men and women (p < 0.05). The frequency of CMC 0 disappeared in woman aged 20 years and in men aged 21 years. Cortical bone formation of the mandibular condyle was completed at age 22 years in women and 24 years in men. The degrees of cortical bone formation of the mandibular condyle between men and women showed significant differences between the ages of 15–19 and 22 years. This difference can be interpreted as a different mandible growth period between the sexes.

Background: Tongue squamous cell carcinoma (TSCC) is an aggressive oral malignancy characterized by early submucosal invasion and a high risk of cervical lymph node metastasis. Accurate and timely diagnosis is essential, but it remains challenging when relying solely on conventional imaging and histopathology. This systematic review aimed to evaluate studies applying artificial intelligence (AI) in the diagnostic imaging of TSCC. Methods: This review was conducted under PRISMA 2020 guidelines and included studies from January 2020 to December 2024 that utilized AI in TSCC imaging. A total of 13 studies were included, employing AI models such as Convolutional Neural Networks (CNNs), Support Vector Machines (SVMs), and Random Forest (RF). Imaging modalities analyzed included MRI, CT, PET, ultrasound, histopathological whole-slide images (WSI), and endoscopic photographs. Results: Diagnostic performance was generally high, with area under the curve (AUC) values ranging from 0.717 to 0.991, sensitivity from 63.3% to 100%, and specificity from 70.0% to 96.7%. Several models demonstrated superior performance compared to expert clinicians, particularly in delineating tumor margins and estimating the depth of invasion (DOI). However, only one study conducted external validation, and most exhibited moderate risk of bias in patient selection or index test interpretation. Conclusions: AI-based diagnostic tools hold strong potential for enhancing TSCC detection, but future research must address external validation, standardization, and clinical integration to ensure their reliable and widespread adoption.

The relationship between fixed orthodontic treatment and the development of temporomandibular disorders (TMDs) in adolescents has been a topic of considerable debate. This systematic review and meta-analysis aimed to evaluate the impact of fixed orthodontic treatment on the prevalence of TMDs in adolescents. A comprehensive literature search was conducted using PubMed, Web of Science, EMBASE, Google Scholar, and the Cochrane Library, yielding 886 records. After duplicate removal, 665 records were screened, and 8 studies were assessed for eligibility. Following quality assessment using the Joanna Briggs Institute checklist, 4 studies were included in the final analysis. Data were analyzed using a random-effects model in RevMan software. The meta-analysis revealed an overall odds ratio of 0.75 (95% CI: 0.37–1.51, p = 0.42), indicating no statistically significant association between fixed orthodontic treatment and the risk of developing TMDs. Substantial heterogeneity was observed (I² = 73%), attributed to variations in study designs, populations, and outcome measures. The risk of bias analysis highlighted concerns in several domains, particularly selection bias and measurement of outcomes. While confounding bias and missing data bias were generally well-controlled, deviations in intervention and inconsistent outcome measurements were noted across the studies. These findings suggest that fixed orthodontic treatment does not significantly alter the risk of developing TMDs in adolescents. However, the substantial heterogeneity and potential biases across the included studies emphasize the need for further high-quality, standardized research to confirm these results and provide clearer clinical guidance.

Jeong SR, et al. Korean J Orthod. 2019 Mar;49(2):116-123. https://doi.org/10.4041/kjod.2019.49.2.116

The aim of this study was to evaluate the distance between the maxillary central incisor root and the incisive canal based on skeletal malocclusion classification and to analyze the morphology of the incisive canal using cone-beam computed tomography (CBCT). Skeletal malocclusion was categorized into Class I, II, and III using lateral cephalometric analysis. Measurements of the distance between the maxillary central incisor root and the incisive canal were taken at two levels: 2 mm (L1) and 4 mm (L2) superior to the labial cementoenamel junction of the maxillary central incisor. At L1, the distance was found to be closer in the Class II group compared to the Class I or Class III groups. Similarly, at L2, the Class II group exhibited a closer distance than the Class III group. Interestingly, females showed a closer distance compared to males at both L1 and L2. Further analysis revealed a significant gender difference in the Class I and III groups, but not in the Class II group. These findings emphasize the significance of evaluating the distance between the maxillary central incisor root and the incisive canal in patients with skeletal Class II malocclusion, regardless of gender.

Hyun-Jeong Park and Seorin Jeong. Oral Biol Res 2024;48:69-74. https://doi.org/10.21851/obr.48.03.202409.69