Clinical Research Directory

Cephalometric and Digital Dental Arch Characteristics Across Angle Malocclusion Groups in Orthodontic Patients From the Mekong Delta, Vietnam

This clinic-based cross-sectional study compared skeletal, dental, soft-tissue, and digital dental arch characteristics among adolescents aged 11-18 years with Angle Class I, Class II, and Class III malocclusions in the Mekong Delta, Vietnam. Lateral cephalometric radiographs and three-dimensional intraoral scans were used to evaluate craniofacial morphology and dental arch dimensions. Significant differences were observed in sagittal skeletal relationships, vertical facial characteristics, dentoalveolar measurements, overjet, overbite, and maxillary arch dimensions among the three malocclusion groups. These findings provide clinically relevant information that may support individualized orthodontic diagnosis and treatment planning for adolescents in comparable clinical settings, while not representing population norms or regional prevalence estimates

Comparison of Digital Analysis and Artificial Intelligence for Cephalometric Tracing

This study aims to evaluate the accuracy and reliability of artificial intelligence (AI)-based cephalometric analysis compared with digital manual tracing. A total of 100 standardized lateral cephalometric radiographs will be analyzed using Delta-Dent software with manual landmark identification and three fully automated AI-based systems (WebCeph, QuantX, and Smartee). Sagittal, vertical, dental, and soft tissue cephalometric parameters will be compared among the different methods. Statistical analysis will assess inter-method agreement and the clinical relevance of any observed discrepancies. The study seeks to determine whether AI-based systems provide measurements comparable to conventional digital tracing and whether they can be considered reliable adjunctive tools in orthodontic diagnosis and treatment planning.