Imaging Science in Dentistry

Korean Academy of Oral and Maxillofacial Radiology (대한영상치의학회)
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Comparative accuracy of artificial intelligence-based AudaxCeph software, Dolphin software, and the manual technique for orthodontic landmark identification and tracing of lateral cephalograms

  • Maryam Foroozandeh (Department of Oral and Maxillofacial Radiology, Dental School, Dental Research Center, Hamadan University of Medical Sciences) ;
  • Fatemeh Salemi (Department of Oral and Maxillofacial Radiology, Dental School, Dental Research Center, Hamadan University of Medical Sciences) ;
  • Abbas Shokri (Department of Oral and Maxillofacial Radiology, Dental School, Dental Research Center, Hamadan University of Medical Sciences) ;
  • Nasrin Farhadian (Department of Orthodontics, School of Dentistry, Dental Research Center, Hamadan University of Medical Sciences) ;
  • Nesa Aeini (Farhangian Dental Clinic) ;
  • Roghayyeh Hassanzadeh (Student Research Committee, Hamadan University of Medical Sciences)
  • Received : 2024.05.02
  • Accepted : 2024.10.15
  • Published : 2025.03.31
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Abstract

Purpose: The aim of this study was to compare the accuracy of AI-based AudaxCeph software, Dolphin software, and the manual technique for identifying orthodontic landmarks and tracing lateral cephalograms. Materials and Methods: In this cross-sectional study, 23 anatomical landmarks were identified on 60 randomly selected lateral cephalograms, and 5 dental indices, 4 skeletal indices, and 1 soft tissue index were measured. Each cephalogram was traced using 4 different methods: manually, with the Dolphin software, with the AudaxCeph software automatically, and with the AudaxCeph software in semi-automatic mode. The intra-class correlation coefficient (ICC) and Bland-Altman plots were used to evaluate the agreement between methods. Inter-observer and intra-observer agreements, calculated using the ICC, confirmed the accuracy, reliability, and reproducibility of the results. Results: There was strong agreement among the AudexCeph (semi-automated or automated) AudaxCeph, Dolphin, and manual methods in measuring orthodontic indices, with ICC values consistently above 0.90. Bland-Altman plots confirmed satisfactory agreement between both versions of AudaxCeph (semi-automated and automated) with the manual method, with mean differences close to 0 and about 95% of data points within the limits of agreement. However, the semi-automated AudaxCeph showed greater agreement and precision than the automated version, as indicated by narrower limits of agreement. The ICC values for inter-observer and intra-observer agreements exceeded 0.98 and 0.99, respectively. Conclusion: The semi-automated AudaxCeph software offers a robust and cost-effective solution for cephalometric analysis. Its high accuracy and affordability make it a compelling alternative to Dolphin software and the manual method.

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Acknowledgement

This study was derived from a DDS thesis (140011129431) submitted to the Vice Chancellor of Research of Hamadan University of Medical Sciences. The authors wish to express their gratitude to the Vice Chancellor of Research of Hamadan University of Medical Sciences.