Comparison of Cephalometric Measurements Obtained by Digital Software, Artificial Intelligence-Assisted Software and Manual Tracing
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Abstract
Background: Cephalometric analysis is essential in orthodontic treatment, gradually transforming from manual to digital tracing. With the advent of artificial intelligence (AI), landmark identification is now automated; offering precision, speed, and space efficiency. As machine errors may occur during landmark identification, it is necessary to verify whether digital software and AI-assisted software are reproducible and reliable when compared to manual tracing. Objective: To evaluate and compare the reproducibility and reliability of linear and angular measurements obtained by manual tracing, digital software and AI-assisted software. Materials and methods: Pretreatment lateral cephalograms of fifty patients were used. The same investigator conducted all analyses using manual tracing, digital software (AutoCeph) and AI-assisted software (WebCeph). Seventeen cephalometric parameters were constructed from 27 anatomical landmarks. Seven linear, nine angular and one ratio were taken from cephalometric analyses. Kruskal Wallis test was used to compare the difference in parameters obtained by three methods. Intraclass correlation coefficient (ICC) was used to determine reproducibility and reliability between linear and angular measurements obtained by three methods. Results: Statistically significant differences were observed for upper incisor to point A (P = 0.02), Jarabak’s ratio (P = 0.03) and N perpendicular to point A (P = 0.02). ICC values for repeated cephalometric measurements were highest for AI-assisted software (> 0.98), followed by digital software (> 0.87) and manual tracing (> 0.86). Conclusion: Digital software and AI-assisted software perform good reproducibility and reliability compared to manual tracing.
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