Accuracy of eyes of AITM artificial intelligence-driven platform for lateral cephalometric analysis

ABSTRACT

Aim: The objective of this prospective study was to evaluate the accuracy of cephalometric analyses acquired through manualtracing and the Eyes of AITM AI-driven web-based program.Materials and Methods: This prospective study employed randomization conducted via computer software, with a determinedsample size of 150 cases. Inclusion criteria encompassed good quality lateral cephalograms available in both digital and printformats, absence of artifacts that might hinder anatomical point location, and presence of a clear calibration ruler for magnificationdetermination. Exclusion criteria included lateral cephalograms with identifiable motion artifacts, resolution disparity, orcontrast, as well as those exhibiting positional errors indicated by ear rod markers. Each lateral cephalogramunderwent tracing and analysis using the manual method, as well as Eyes of AITM software. Following landmark plotting, linearand angular measurements of Steiner, Downs, McNamara, and Jefferson analyses were calculated.Results: A comparison of thirty-six cephalometric measurements of Steiner, Downs, McNamara, and Jefferson analyses obtainedfrom manual tracing and AI-driven Eyes of AITM revealed a Concordance Correlation Coefficient (CCC) value above 0.76 for all parameters, indicating strong agreement between manual and AI-driven cephalometric measurements. Furthermore, a CCC valueexceeding 0.9 was observed for twenty-eight parameters, indicative of very strong agreement. Conclusion: Automated lateral cephalometric measurements obtained from Eyes of AITM are accurate when compared to manualmeasurements.