Accuracy of cephalometric landmark identification on artificial intelligence-based software: a comparative study
Clinical Snapshot
PICO Framework
| P — Population | 25 lateral cephalometric radiographs from orthodontic patients |
| I — Intervention | AI-based cephalometric software (CephNinja and WebCeph™) for automatic landmark identification |
| C — Comparator | Manual landmark identification by two orthodontists using NemoCeph digital software |
| O — Outcomes | Accuracy of anatomical landmark identification (17 landmarks: 15 hard tissue, 2 soft tissue points) |
Bottom Line
This small comparative study (n=25) found statistically significant positional differences between AI-based cephalometric software and manual landmark identification by orthodontists at key anatomical points including porion, basion, gonion, and incisor apexes. While AI tools offer speed and reproducibility, the clinical significance of these discrepancies remains unclear. The study's major limitations include very small sample size, lack of traditional diagnostic accuracy metrics (sensitivity/specificity), and insufficient methodological detail. Clinicians should exercise caution when relying solely on AI-based cephalometric analysis for treatment planning. Larger validation studies with diverse patient populations and clear clinical outcome measures are needed before widespread adoption. The findings suggest AI technology may complement but not replace expert clinical assessment in orthodontic diagnosis.
Key Findings
P Value: p < 0.05 for specified landmarks
Effect Size: Statistically significant differences at porion, basion, gonion, and incisor apexes
Primary Outcome: Positional accuracy of 17 cephalometric landmarks
Nnt Or Sensitivity: AI software placed landmarks in more distal and superior positions compared to manual identification
Confidence Interval: Not reported
Clinical Application
AI software offers rapid assessment but requires validation for clinical accuracy Relevant to Australian orthodontic practice where digital cephalometry is standard. TGA approval status of AI software unclear. RACGP guidelines emphasise evidence-based diagnostic tools Orthodontic patients requiring cephalometric analysis
Abstract
INTRODUCTION: Cephalometry has long been a cornerstone of orthodontic diagnosis and treatment planning. While traditionally performed manually, cephalometric analysis has increasingly shifted toward semi-automated or fully automated computer-based software, due to advances in technology. OBJECTIVE: This study aims to evaluate and compare the accuracy of anatomical landmarks identified manually by orthodontists using digital tools versus those identified automatically by various artificial intelligence (AI)-based cephalometric software. METHODS: A total of 25 lateral cephalometric radiographs were selected for analysis. Manual landmark identification was independently performed by two orthodontists using the digital cephalometric software NemoCeph. These were compared to the automatic landmark identifications generated by two AI-based programs: CephNinja and WebCeph™. A total of 17 anatomical landmarks, 15 hard tissue and 2 soft tissue points, were evaluated. The 17 cephalometric landmarks selected in this study are among the most commonly used and reliably identifiable reference points in the literature. To facilitate direct visual comparison, landmark positions derived from all three methods were overlaid using semi-transparent image layers. One-way ANOVA and intraclass correlation coefficient (ICC) tests were conducted to assess inter-method differences. The threshold for statistical significance was set at p < 0.05 and p < 0.01. RESULTS: Statistically significant differences were observed at the porion, basion, gonion, and the apexes of the upper and lower incisors (p < 0.05). Compared to the manual tracings in NemoCeph, AI-based software generally placed these landmarks in more distal and superior positions. Among the AI tools, CephNinja showed greater similarity to NemoCeph for the gonion and basion points, while WebCeph™ was closer at the incisor apexes. CONCLUSION: Although AI-based cephalometric software offers rapid and reproducible assessments, certain anatomical landmarks - particularly porion, basion, gonion, and the apexes of the upper and lower incisors - demonstrate statistically significant positional discrepancies, compared to manual tracings. Clinicians should be cautious when relying exclusively on automated analyses for diagnostic or treatment planning purposes, since AI struggles with certain landmarks, due to algorithmic limitations.
References
- 1.Şavkan, İ., Özçankaya, S. N., & Turan, Ö. N. (2026). Accuracy of cephalometric landmark identification on artificial intelligence-based software: a comparative study. Dental Press Journal of Orthodontics, 31(2), e2625144. https://doi.org/10.1590/2177-6709.31.2.e2625144.oar
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