Background: Cephalometric analysis (CA) is an indispensable diagnostic tool in orthodontics
for treatment planning and outcome assessment. Manual CA is time-consuming and prone
to variability. Methods: This study aims to compare the accuracy and repeatability
of CA results among three commercial AI-driven programs: CephX, WebCeph, and AudaxCeph.
This study involved a retrospective analysis of lateral cephalograms from a single
orthodontic center. Automated CA was performed using the AI programs, focusing on
common parameters defined by Downs, Ricketts, and Steiner. Repeatability was tested
through 50 randomly reanalyzed cases by each software. Statistical analyses included
intraclass correlation coefficients (ICC3) for agreement and the Friedman test for
concordance. Results: One hundred twenty-four cephalograms were analyzed. High agreement
between the AI systems was noted for most parameters (ICC3 > 0.9). Notable differences
were found in the measurements of angle convexity and the occlusal plane, where discrepancies
suggested different methodologies among the programs. Some analyses presented high
variability in the results, indicating errors. Repeatability analysis revealed perfect
agreement within each program. Conclusions: AI-driven cephalometric analysis tools
demonstrate a high potential for reliable and efficient orthodontic assessments, with
substantial agreement in repeated analyses. Despite this, the observed discrepancies
and high variability in part of analyses underscore the need for standardization across
AI platforms and the critical evaluation of automated results by clinicians, particularly
in parameters with significant treatment implications.
