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Digital Models for the Analysis of Little’s Irregularity Index in Subjects with a Different Degree of Crowding: A Reproducibility Study by Palazzo, Giuseppe; Ronsivalle, Vincenzo; Rustico, Lorenzo; Martina, Stefano; Fichera, Grazia; Campagna, Paola; Nucera, Riccardo is a Engineering article available to read on EtoBox.
What is Digital Models for the Analysis of Little’s Irregularity Index in Subjects with a Different Degree of Crowding: A Reproducibility Study about?
Background: To investigate the accuracy and reproducibility of digital measurements of Little’s Irregularity Index and to evaluate if different degrees of dental crowding could influence these measurements. Methods: The study included 40 dental models and 5 sub-groups were created according to the severity of the crowding. In both the digital models and the study cast, Little’s Irregularity Index was recorded by measuring (1) the mesiodistal width of each tooth and (2) the arch lengths in both the maxillary and mandibular jaw. Two operators performed measurements on plaster and digital models using, respectively, a digital caliper and OrthoAnalyzerTM 3D software (3Shape A/S, Copenhagen, Denmark). Statistical analysis was performed to assess intra- and inter-operator variability, the accuracy between manual and digital measurements and if the amount of crowding could affect the accuracy of the digital measurements. Results: Concerning intra-examiner reliability, no statistically significant differences were detected (p > 0.05). In the maxillary and mandibular arch, the Intraclass Correlation Coefficient (ICC) value was 0.996 and 0.997 for the analogic measurements and 0.998 and 0.97
Who reads Digital Models for the Analysis of Little’s Irregularity Index in Subjects with a Different Degree of Crowding: A Reproducibility Study?
It is typically read by researchers, students, and practitioners in Engineering.
- Author
- Palazzo, Giuseppe; Ronsivalle, Vincenzo; Rustico, Lorenzo; Martina, Stefano; Fichera, Grazia; Campagna, Paola; Nucera, Riccardo
- Publisher
- MDPI AG; Multidisciplinary Digital Publishing Institute (MDPI); Basel: MDPI AG, 2011- (ISSN 2076-3417)
- Published
- 2020
- Language
- EN
- Field
- Engineering (Physical Sciences)