Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/110145
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Title: Radiographic imaging for the diagnosis and treatment of patients with skeletal class III malocclusion
Authors: Li, Z
Hung, KF
Ai, QYH 
Gu, M
Su, YX
Shan, Z
Issue Date: Mar-2024
Source: Diagnostics, Mar. 2024, v. 14, no. 5, 544
Abstract: 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).
Keywords: Artificial intelligence
Class III malocclusion
Diagnosis and treatment
Radiographic imaging
Publisher: MDPI AG
Journal: Diagnostics 
EISSN: 2075-4418
DOI: 10.3390/diagnostics14050544
Rights: Copyright: © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
The following publication Li Z, Hung KF, Ai QYH, Gu M, Su Y-x, Shan Z. Radiographic Imaging for the Diagnosis and Treatment of Patients with Skeletal Class III Malocclusion. Diagnostics. 2024; 14(5):544 is available at https://doi.org/10.3390/diagnostics14050544.
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