Feasibility of occlusal plane in predicting the changes in anteroposterior mandibular position: a comprehensive analysis using deep learning-based three-dimensional models

作者：Bingran Du, Kaichen Li, Zhiling Shen, Yihang Cheng, Jiayan Yu, Yaopeng Pan, Ziyan Huang, Fei Hu, Xiaohui Rausch‐Fan, Yuanpeng Zhu, Xueyang Zhang · 发表于：BMC Oral Health · 年份：2025 · DOI：10.1186/s12903-024-05345-9 · 被引用次数：4 · 研究领域：Temporomandibular Joint Disorders、Orthodontics and Dentofacial Orthopedics、Obstructive Sleep Apnea Research

A comprehensive analysis of the occlusal plane (OP) inclination in predicting anteroposterior mandibular position (APMP) changes is still lacking. This study aimed to analyse the relationships between inclinations of different OPs and APMP metrics and explore the feasibility of OP inclination in predicting changes in APMP. Overall, 115 three-dimensional (3D) models were reconstructed using deep learning-based cone-beam computed tomography (CBCT) segmentation, and their accuracy in supporting cusps was compared with that of intraoral scanning models. The anatomical landmarks of seven OPs and three APMP metrics were identified, and their values were measured on the sagittal reference plane. The receiver operating characteristic curves of inclinations of seven OPs in distinguishing different anteroposterior skeletal patterns and correlations between inclinations of these OPs and APMP metrics were calculated and compared. For the OP inclination wit h the highest area under the curve (AUC) values and correlation coefficients, the regression models between this OP inclination and APMP metrics were further calculated. The deviations in supporting cusps between deep learning-based and intraoral scanning models were < 0.300 mm. The improved functional OP (IFOP) inclination could distinguish different skeletal classification determinations (AUC Class I VS Class II = 0.693, AUC Class I VS Class II I = 0.763, AUC Class II VS Class II I = 0.899, all P values < 0.01) and the AUC value in s...