Faculty of Dentistry, University of Cuenca, Av. 12 de Abril s;n, Cuenca, Ecuador.
Research Article
World Journal of Advanced Research and Reviews, 2023, 17(01), 1286-1296
Article DOI: 10.30574/wjarr.2023.17.1.0142
Received on 13 December 2022; revised on 22 January 2023; accepted on 25 January 2023
Model measurements and analysis are essential for the diagnosis of orthodontic cases and in the last decade orthodontic diagnosis has increased with technological advances, leaving aside traditional diagnostic methods, such as model analysis, especially when it comes to cross-sectional analysis. The present study seeks to propose to the clinician a simple option in the diagnosis of the transversal problem, through analysis with the CBCT. To support this proposal, data was collected from 40 students who were evaluated according to the parameters established in the study, between the ages of 21 and 27. Data were taken from digital study models in STL format, as well as CBCT. The UPenn analysis was used in the CBCT and applying the Korkhaus and Wala Ridge analyzes for the STL digital models, establishing comparisons of the validity of the results by calculating the predictive values of the positive test and the negative test. Model analysis was performed by measuring, using the NemoCast3D software. The comparison of means of both measures was carried out, which showed that there is no significant difference and then the correlation of measures was made, which proved to be significant in 5 of 7 measures. This model analysis proposal (AN-BAR) can be useful for the clinician in making a decision when performing a maxillary expansion.
Digital models; Cone beam computed tomography; Transverse discrepancy; Korkhaus analysis; Wala Ridge analysis; Penn analysis
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Andrea Carolina Ulloa Gómez, Wendy Paola Parra Hidalgo, Eliana Elizabeth González Rodas and Manuel Estuardo Bravo Calderón. Comparison of cross-sectional orthodontic analysis on digital models using Nemocast and CBCT software. World Journal of Advanced Research and Reviews, 2023, 17(1), 1286-1296. Article DOI: https://doi.org/10.30574/wjarr.2023.17.1.0142