Three-dimensional evaluation of mandibular anterior dental crowding in digital dental casts

Luciana Quintanilha Pires FERNANDES, Livia Kelly Ferraz NUNES, Luana Santos ALVES, Felipe de Assis Carvalho RIBEIRO, Jonas CAPELLI JÚNIOR

Introduction: Digital dental models provide a more accurate and comprehensive assessment of orthodontic cases. Although this technique is quite promising, there are few three-dimensional measurements methods described in the literature. Objective: The aim of this study was to propose a method for assessing the degree of mandibular anterior dental crowding in the three planes of space, using digital dental models. Methods: Thirty dental casts were selected and scanned by Maestro 3D Dental Scanner and imported by Geomagic Qualify 2013 software. The degree of crowding was calculated by two examiners, based on the Little’s Irregularity Index, by means of the definition of axial, coronal and sagittal planes for each model. Intraexaminer analysis was performed with Dahlberg’s Formula (DF) and Intraclass Correlation Coefficients (ICC), and interexaminer analysis was performed with ICC and paired t-test. Results: The ICC showed an excellent agreement (p < 0.05) for all measurements, except for the intraexaminer and interexaminer in the Z-axis, in which it was found a moderate agreement. The DF showed a satisfactory accuracy with all measurements showing less than 1 mm difference. The paired t-test showed statistical difference between the examiners in two measurements, although it was clinical irrelevant. Conclusion: When comparing the three planes of space, the Z-axis showed the greatest variation in landmarks placement; however, overall, the present method seems precise and reproducible.

Keywords: Orthodontics. Diagnosis. Dental models. Malocclusion.

How to cite: Fernandes LQP, Nunes LKF, Alves LS, Ribeiro FAC, Capelli Júnior J. Three-dimensional evaluation of mandibular anterior dental crowding in digital dental casts. Dental Press J Orthod. 2017 May-June; 22(3):64-71. DOI: https://doi.org/10.1590/2177-6709.22.3.064-071.oar

Saturday, November 23, 2024 01:50