Accuracy and reliability of automated landmark identification and cephalometric measurements on cone beam computed tomography using Invivo software.

Abstract

Objectives: To evaluate the accuracy and reliability of an automated landmark identification (ALI) system and the impact of ALI errors on cephalometric measurements on cone-beam computed tomography (CBCT) images.

Materials and methods: Thirty-one landmarks were identified on 76 CBCT images using Invivo7 software (Anatomage, San Jose, Calif). Ground truth was established by averaging landmark coordinates from two calibrated human examiners. The accuracy of the ALI system was assessed by the mean absolute error (MAE, mm) across coordinate axes, the mean error distance (mm), and the successful detection rate (SDR) for each landmark. Interexaminer reliability between the ALI and manual landmark location was evaluated. Eighteen cephalometric measurements were computed from 25 landmarks. Accuracy of measurements from the ALI system was assessed with the MAE and successful measurement rates (SMR).

Results: The ALI system closely matched human examiners in landmark identification, with an average MAE of 0.94 ± 0.99 mm. Across all three coordinate axes, 87% of the landmarks had <2 mm MAE. ALI average MAE for conventional linear and angular cephalometric measurements were 1.35 ± 1.33 mm and 0.89 ± 0.89 degrees, respectively. Only one measurement, Intercondylar Width, showed MAE >3 mm.

Conclusions: The ALI system showed clinically acceptable accuracy and reliability for the majority of cephalometric landmarks and measurements. Clinicians are advised to critically evaluate ALI landmarks with substantial errors, to fully utilize the capabilities of commercial software effectively.