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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

Academic Article
Publication Date:
2020
abstract:
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 0.978 for the digital measurements. For the maxillary arch, the mean difference between the analogic and digital Little’s Irregularity Index (LII) measurements was 0.43 mm while for the mandibular arch the mean difference was 0.24 mm, showing some overestimation of the digital measurements (p < 0.05). No differences were found according to crowding subgroups (p > 0.05). Conclusions: Digital measurements of LII could be considered as a valid substitute of the gold standard analogical measurement.
Iris type:
14.a.1 Articolo su rivista
Keywords:
Arch length discrepancy, Dental crowding, Digital dentistry, Digital models, Little’s index, Space analysis
List of contributors:
Palazzo, G.; Ronsivalle, V.; Rustico, L.; Martina, S.; Fichera, G.; Campagna, P.; Nucera, R.
Authors of the University:
NUCERA Riccardo
Handle:
https://iris.unime.it/handle/11570/3191002
Full Text:
https://iris.unime.it//retrieve/handle/11570/3191002/383984/applsci-10-07108%20(1).pdf
Published in:
APPLIED SCIENCES
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https://www.mdpi.com/2076-3417/10/20/7108/pdf?version=1602583550
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