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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/21794

Title: Predictors of root resorption associated with maxillary canine impaction in panoramic images
Authors: Alqerban, Ali
Jacobs, Reinhilde
Fieuws, Steffen
Willems, Guy
Issue Date: 2016
Citation: EUROPEAN JOURNAL OF ORTHODONTICS, 38 (3), p. 292-299
Abstract: The aim was to identify a prediction model for root resorption (RR) caused by impacted canines based on radiographic variables assessed on 2D panoramic radiographs with the intention to reduce the need for additional cone beam computed tomography (CBCT) imaging. Three hundred and six patients (188 female, 118 male; mean age, 14.7 years; standard deviation, 5.6; range, 8.4-47.2 years) were included in the study. In total, 406 impacted maxillary canines were studied, from 206 patients with unilateral impaction and from 100 patients with bilateral impaction. Initial 2D panoramic radiography was available, and 3D CBCT imaging was obtained upon clinical indication. The generated radiographic variables and specific features investigated were collected on 2D panoramic imaging and were correlated to the presence/absence of RR detected on CBCT. A validation sample consisting of 55 canines from 45 patients with maxillary canine impactions was collected to validate the outcome of the present study. The incidence of RR of the adjacent teeth was 33.8%. A prediction model using panoramic images for the possible presence of RR was established [area under the curve (AUC) = 0.74, 95% confidence interval (CI): 0.69-0.79] and validated by applying leave-one-out cross-validation (AUC = 0.71, 95% CI: 0.66-0.77). For the subgroup of presence of severe RR the discriminative ability increased to 0.80. In this prediction model, patient gender, canine apex, vertical canine crown position, and canine magnification were the strongest predictors for RR. The final prediction model for RR based on available panoramic radiographs could be a helpful tool in justifying the need of additional CBCT examination.
Notes: [Alqerban, Ali] Prince Sattam Bin Abdulaziz Univ, Coll Dent, Dept Prevent Dent Sci, Al Kharj, Saudi Arabia. [Jacobs, Reinhilde] Katholieke Univ Leuven, Dept Imaging & Pathol, OMFS IMPATH Res Grp, Leuven, Belgium. [Fieuws, Steffen] Katholieke Univ Leuven, Dept Publ Hlth, Leuven, Belgium. [Fieuws, Steffen] Univ Hasselt, Hasselt, Belgium. [Alqerban, Ali; Willems, Guy] Katholieke Univ Leuven, Dept Oral Hlth Sci, B-3000 Leuven, Belgium. [Alqerban, Ali; Willems, Guy] Univ Hosp Leuven, Dent, B-3000 Leuven, Belgium.
URI: http://hdl.handle.net/1942/21794
DOI: 10.1093/ejo/cjv047
ISI #: 000377921000011
ISSN: 0141-5387
Category: A1
Type: Journal Contribution
Validation: ecoom, 2017
Appears in Collections: Research publications

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