Comparative evaluation of commercially available AI-based cephalometric tracing programs

• Published in: BMC oral health Vol. 24; no. 1; pp. 1241 - 8
• Main Authors: Baig, Nida, Gyasudeen, Kabir Syed, Bhattacharjee, Tanmoy, Chaudhry, Jahanzeb, Prasad, Sabarinath
• Format: Journal Article
• Language: English
• Published: London BioMed Central 18.10.2024; BioMed Central Ltd; Springer Nature B.V; BMC
• Subjects: Accuracy; Algorithms; Anatomic Landmarks; Artificial Intelligence; Automation; Cephalometry; Cephalometry - methods; Computer-aided medical diagnosis; Consent; Deep learning; Dentistry; Diagnosis; Facial Bones - anatomy & histology; Facial Bones - diagnostic imaging; Humans; Image Processing, Computer-Assisted - methods; Lateral cephalometric; Mandible - anatomy & histology; Mandible - diagnostic imaging; Medical diagnosis; Medical imaging equipment; Medicine; Methods; Observer Variation; Oral and Maxillofacial Surgery; Orthodontics; Reproducibility of Results; Review boards; Sensitivity analysis; Sensitivity and Specificity; Software; United Arab Emirates; United States > US; Dubai United Arab Emirates; Accuracy; Diagnosis; Orthodontics; Artificial intelligence; Lateral cephalometric
• ISSN: 1472-6831; 1472-6831
• DOI: 10.1186/s12903-024-05032-9

Objectives Compare the accuracy and diagnostic concordance of three commercially available AI-based lateral cephalometric tracing software. Materials and methods Sixty-three lateral cephalometric radiographs were analyzed using semi-automatic (Dolphin Imaging Systems LLC) and AI-based software programs (WebCeph™, Cephio, and Ceppro DDH Inc.). Intra- and inter-observer reliability were assessed for human expert measurements, and repeated-measures one-way ANOVA was used to compare the AI and human expert measurements. The diagnostic performance was evaluated using sensitivity and specificity tests. Results Human expert reliability was excellent (ICC > 0.9) for most cephalometric parameters. Compared to human experts, significant differences were observed for all three AI-based cephalometric programs (WebCeph™ – 10 of 11, Cephio – 7 of 11, and Ceppro DDH Inc. – 7 of 11 cephalometric measurements). Variations exceeding two units were noted for most parameters, and differences in defining the sagittal and vertical skeletal patterns, dental, and soft tissue characteristics were observed. Conclusion All three AI-based tracing programs showed inaccuracies compared to human expert measurements and lacked reliability in measuring key cephalometric parameters. Clinicians should exercise caution when relying solely on AI-based analyses for orthodontic treatment planning and assessment.