A retrospective study of alveolar bone remodelling after anterior retraction in orthodontic tooth extraction cases with clear aligners and fixed appliances

牙槽 医学 牙科 前牙 锥束ct 口腔正畸科 裂开 计算机断层摄影术 外科
作者
Ziyu Guo,Ruijie Zhang,Changgang Guo,Xin Li,Zuolin Jin,Qian Liu
出处
期刊:Orthodontics & Craniofacial Research [Wiley]
卷期号:27 (2): 220-227 被引量:16
标识
DOI:10.1111/ocr.12705
摘要

OBJECTIVES: To evaluate alveolar bone dimensions and its relationship with tooth movement (retraction, intrusion and torque) during orthodontic treatment with fixed appliance and clear aligners. METHODS: Thirty-two patients were included in this retrospective clinical study. Cone beam computed tomography (CBCT) was collected before and after treatment to measure the volume of dehiscence and fenestrations in the maxillary anterior region, anterior alveolar bone thickness and height and degree of tooth movement. Rank-sum tests were used to compare the differences in alveolar bone defect volumes between clear aligners and fixed appliance, multiple linear regression analysis was used for study evaluation, and kappa statistics were used to assess internal consistency and test-retest reliability. RESULTS: Post-operatively, most alveolar bone defects occurred on the labial side. The incidence of bone fenestration was 23.96% in the clear aligner group and 26.18% in the fixed appliance group, which was higher than the incidence of bone dehiscence (5.21%). The labial bone height decreased by 0.272 mm, and the palatal bone height increased by 0.617 mm for every 1 mm downward intrusion of the anterior tooth apex in the fixed appliance group. In the clear aligner group, there was no significant change in the labial bone height, and the palatal bone height decreased by 0.447 mm for every 1 mm of anterior tooth retraction coronally. CONCLUSIONS: In the fixed appliance group, anterior tooth intrusion and retraction may have led to alveolar bone resorption by its compression at the cervical level. This study provides a three-dimensional tooth movement evaluation method by using CBCT.
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