five

Three-Dimensional Assessment of Unerupted Mandibular Second Premolar using CBCT Technique

收藏
NIAID Data Ecosystem2026-05-10 收录
下载链接:
https://data.mendeley.com/datasets/hfnksntd5h
下载链接
链接失效反馈
官方服务:
资源简介:
Purpose To assess unerupted mandibular second premolar (UMSP) position using CBCT technique. Methods Thirty-four CBCT images of pediatric patients from the Egyptian population, ranging between 13- and 16-year-old, were included in this study. The CBCT images were assessed for the presence of unilateral or bilateral impaction, root resorption of adjacent teeth, root dilacerations, residual deciduous teeth, pathology incidence, type and depth of impaction, and distance relative to important anatomical structures. The collected data were statistically analyzed using SPSS v.23 at a p-value  0.05. Results From the assessment of 45 unerupted mandibular second premolars featured important differences related to gender and age. Unilateral impactions were found to be more common in males (p = 0.022). Aspects such as root dilaceration with an angle greater than 45° (0.026), presence of pathological lesions (0.003), and retained primary teeth (0.03) have a greater incidence in the older age group. The relative three-dimensional positioning of UMSP indicated 46.7%, 31.1%, and 13.3% for disto-angular, vertical, and mesio-angular type, respectively. With respect to depth, 55.6% of cases were classified as severely deep from the bony crest. Proximity to critical structures ranked UMSP as follows; N3 (31.1%), followed by N2 (26.7%), N1 (22.2%), and N4 (20.0%). Conclusion The identified percentage of unerupted mandibular second premolars was 1.59% with significant male predilection for unilateral impactions. Older age group (16-18 years), were more frequently associated with root dilaceration. Most UMSPs were disto-angular or vertical, with over half positioned at severe depth and nearly one-third in proximity to inferior alveolar canal.
创建时间:
2025-10-06
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作