Li Zhuoying, Hung Kuo Feng, Ai Qi Yong H, Gu Min, Su Yu-Xiong, Shan Zhiyi
Division of Paediatric Dentistry and Orthodontics, Faculty of Dentistry, The University of Hong Kong, Hong Kong SAR, China.
Applied Oral Sciences & Community Dental Care, Faculty of Dentistry, The University of Hong Kong, Hong Kong SAR, China.
Diagnostics (Basel). 2024 Mar 4;14(5):544. doi: 10.3390/diagnostics14050544.
Skeletal Class III malocclusion is one type of dentofacial deformity that significantly affects patients' facial aesthetics and oral health. The orthodontic treatment of skeletal Class III malocclusion presents challenges due to uncertainties surrounding mandibular growth patterns and treatment outcomes. In recent years, disease-specific radiographic features have garnered interest from researchers in various fields including orthodontics, for their exceptional performance in enhancing diagnostic precision and treatment effect predictability. The aim of this narrative review is to provide an overview of the valuable radiographic features in the diagnosis and management of skeletal Class III malocclusion. Based on the existing literature, a series of analyses on lateral cephalograms have been concluded to identify the significant variables related to facial type classification, growth prediction, and decision-making for tooth extractions and orthognathic surgery in patients with skeletal Class III malocclusion. Furthermore, we summarize the parameters regarding the inter-maxillary relationship, as well as different anatomical structures including the maxilla, mandible, craniofacial base, and soft tissues from conventional and machine learning statistical models. Several distinct radiographic features for Class III malocclusion have also been preliminarily observed using cone beam computed tomography (CBCT) and magnetic resonance imaging (MRI).
骨性III类错牙合畸形是一种严重影响患者面部美观和口腔健康的牙颌面畸形。由于下颌生长模式和治疗结果存在不确定性,骨性III类错牙合畸形的正畸治疗面临挑战。近年来,特定疾病的影像学特征因其在提高诊断准确性和治疗效果可预测性方面的卓越表现,受到了包括正畸学在内的各个领域研究人员的关注。本叙述性综述的目的是概述在骨性III类错牙合畸形的诊断和治疗中具有价值的影像学特征。基于现有文献,对头颅侧位片进行了一系列分析,以确定与骨性III类错牙合畸形患者的面部类型分类、生长预测以及拔牙和正颌外科手术决策相关的显著变量。此外,我们总结了传统和机器学习统计模型中关于上下颌关系以及包括上颌骨、下颌骨、颅面基底和软组织在内的不同解剖结构的参数。使用锥形束计算机断层扫描(CBCT)和磁共振成像(MRI)也初步观察到了III类错牙合畸形的几个独特影像学特征。