Reliability of Artificial Intelligence-Assisted Cephalometric Analysis. A Pilot Study

Abstract

Recently, Artificial Intelligence (AI) has spread in orthodontics, in particular within cephalometric analysis, where computerized digital software is able to provide linear-angular measurements upon manual landmark identification. A step forward is constituted by fully automated AI-assisted cephalometric analysis, where the landmarks are automatically detected by software. The aim of the study was to compare the reliability of a fully automated AI-assisted cephalometric analysis with the one obtained by a computerized digital software upon manual landmark identification. Fully automated AI-assisted cephalometric analysis of 13 lateral cephalograms were retrospectively compared to the cephalometric analysis performed twice by a blinded operator with a computerized software. Intra- and inter-operator (fully automated AI-assisted vs. computerized software with manual landmark identification) reliability in cephalometric parameters (maxillary convexity, facial conicity, facial axis angle, posterior and lower facial height) was tested with the Dahlberg equation and Bland–Altman plot. The results revealed no significant difference in intra- and inter-operator measurements. Although not significant, higher errors were observed within intra-operator measurements of posterior facial height and inter-operator measurements of facial axis angle. In conclusion, despite the small sample, the cephalometric measurements of a fully automated AI-assisted cephalometric software were reliable and accurate. Nevertheless, digital technological advances cannot substitute the critical role of the orthodontist toward a correct diagnosis.

A Comparative Analysis of Artificial Intelligence and Manual Methods for Three-Dimensional Anatomical Landmark Identification in Dentofacial Treatment Planning

“…To address this, clinicians have explored automatic methods for identifying measurement points since Cohen and Linney et al introduced the first one in 1984, aiming to enhance accuracy [20]. Several studies have demonstrated a strong correlation between automatic measurement points and those identified manually [13,21,22]. Meric and Naoumova proposed that fully automated solutions can significantly improve cephalometric analyses [23].…”

“…In recent decades, dentistry has seen significant progress thanks to technological advancements, particularly in the emerging field of artificial intelligence (AI) [10,11]. AI is a branch of computer science that utilizes technology to perform tasks without human intervention or supervision, effectively simulating human intelligence [10][11][12][13]. Various deep learning architectures, such as deep neural networks, convolutional deep neural networks, deep belief networks, and recurrent neural networks, have been employed to develop algorithms for essential domains like natural language processing, computer vision, speech recognition, and bioinformatics.…”

Empowering Modern Dentistry: The Impact of Artificial Intelligence on Patient Care and Clinical Decision Making

“…AI applications in orthodontics primarily focus on cephalometric analysis and treatment planning. The work by Panesar et al and Alessandri-Bonetti et al shows that AI-assisted cephalometric analysis can significantly improve precision and accuracy [ 36 , 37 ]. AI can automate the labor-intensive process of landmark identification, making it faster and more reliable.…”

“…Recent studies have focused on cephalometric landmark identification using AI, with convolutional neural networks (CNNs) and fully automated AI-assisted analysis. According to Panesar et al, the precision and accuracy of the examiners with the aid of AI improved by 10.47% and 27.27%, respectively [ 36 , 37 ]. Kochhar et al assessed bone volume in CBCT scans of patients with a unilateral cleft lip and/or palate using OsiriX software.…”