Validation of 2D lateral cephalometric analysis using artificial intelligence-processed low-dose cone beam computed tomography

Abstract

Objectives: Traditional cephalometric radiographs depict a three-dimensional structure in a two-dimensional plane; therefore, errors may occur during a quantitative assessment. Cone beam computed tomography, on the other hand, minimizes image distortion, allowing essential areas to be observed without overlap. Artificial intelligence can be used to enhance low-dose cone beam computed tomography images. This study aimed to clinically validate the use of artificial intelligence-processed low-dose cone beam computed tomography for generating two-dimensional lateral cephalometric radiographs by comparing these artificial intelligence-enhanced radiographs with traditional two-dimensional lateral cephalograms and those derived from standard cone beam computed tomography. Methods: Sixteen participants who had previously undergone both cone beam computed tomography and plain radiography were selected. Group I included standard lateral cephalometric radiographs. Group II included cone beam computed tomography-produced lateral cephalometric radiographs, and Group III included artificial intelligence-processed low-dose cone beam computed tomography-produced lateral cephalometric radiographs. Lateral cephalometric radiographs of the three groups were analyzed using an artificial intelligence-based cephalometric analysis platform. Results: A total of six angles and five lengths were measured for dentofacial diagnosis. There were no significant differences in measurements except for nasion-menton among the three groups. Conclusions: Low-dose cone beam computed tomography could be an efficient method for cephalometric analyses in dentofacial treatment. Artificial intelligence-processed low-dose cone beam computed tomography imaging procedures have the potential in a wide range of dental applications. Further research is required to develop artificial intelligence technologies capable of producing acceptable and effective outcomes in various clinical situations. Clinical significance: Replacing standard cephalograms with cone beam computed tomography (CBCT) to evaluate the craniofacial relationship has the potential to significantly enhance the diagnosis and treatment of selected patients. The effectiveness of low-dose (LD)-CBCT was assessed in this study. The results indicated that lateral cephalograms reconstructed using LD-CBCT were comparable to standard lateral cephalograms.

Keywords

• Cephalometric analysis
• Cone beam computed tomography (CBCT)
• Low-dose CBCT
• Artificial intelligence (AI)
• Dentofacial treatment