Radiographic Imaging for the Diagnosis and Treatment of Patients with Skeletal Class III Malocclusion

被引:1
|
作者
Li, Zhuoying [1 ]
Hung, Kuo Feng [2 ]
Ai, Qi Yong H. [3 ]
Gu, Min [1 ]
Su, Yu-xiong [4 ]
Shan, Zhiyi [1 ]
机构
[1] Univ Hong Kong, Fac Dent, Div Paediat Dent & Orthodont, Hong Kong, Peoples R China
[2] Univ Hong Kong, Fac Dent, Appl Oral Sci & Community Dent Care, Hong Kong, Peoples R China
[3] Hong Kong Polytech Univ, Dept Hlth Technol & Informat, Hung Hom, Kowloon, Hong Kong, Peoples R China
[4] Univ Hong Kong, Fac Dent, Div Oral & Maxillofacial Surg, Hong Kong, Peoples R China
关键词
artificial intelligence; Class III malocclusion; diagnosis and treatment; radiographic imaging; LONG-TERM STABILITY; ORTHODONTIC TREATMENT; CEPHALOMETRIC VARIABLES; ORTHOGNATHIC SURGERY; CLASS-I; PREDICTION; GROWTH; CAMOUFLAGE; CHILDREN; SUCCESS;
D O I
10.3390/diagnostics14050544
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
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).
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页数:28
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