Prediction of maxillary canine impaction based on panoramic radiographs

Abstract Objectives The objective of this article is to establish a large sample‐based prediction model for maxillary canine impaction based on linear and angular measurements on panoramic radiographs and to validate this model. Materials and methods All patients with at least two panoramic radiogra...

Full description

Bibliographic Details
Main Authors: Raes Margot, Cadenas De Llano‐Pérula Maria, Alqerban Ali, Laenen Annouschka, Verdonck Anna, Willems Guy
Format: Article
Language:English
Published: Wiley 2020-02-01
Series:Clinical and Experimental Dental Research
Subjects:
Online Access:https://doi.org/10.1002/cre2.246
id doaj-b0df35598ed64de9910bb8b3d8cfd8a6
record_format Article
spelling doaj-b0df35598ed64de9910bb8b3d8cfd8a62020-11-25T02:09:41ZengWileyClinical and Experimental Dental Research2057-43472020-02-0161445010.1002/cre2.246Prediction of maxillary canine impaction based on panoramic radiographsRaes Margot0Cadenas De Llano‐Pérula Maria1Alqerban Ali2Laenen Annouschka3Verdonck Anna4Willems Guy5Department of Oral Health Sciences–Orthodontics, KU Leuven and Dentistry University Hospitals Leuven Leuven BelgiumDepartment of Oral Health Sciences–Orthodontics, KU Leuven and Dentistry University Hospitals Leuven Leuven BelgiumDepartment of Preventive Dental Sciences, College of Dentistry Prince Sattam Bin Abdulaziz University Al‐Kharj Saudi ArabiaInteruniversity Institute for Biostatistics and statistical Bioinformatics KU Leuven and University Hasselt BelgiumDepartment of Oral Health Sciences–Orthodontics, KU Leuven and Dentistry University Hospitals Leuven Leuven BelgiumDepartment of Oral Health Sciences–Orthodontics, KU Leuven and Dentistry University Hospitals Leuven Leuven BelgiumAbstract Objectives The objective of this article is to establish a large sample‐based prediction model for maxillary canine impaction based on linear and angular measurements on panoramic radiographs and to validate this model. Materials and methods All patients with at least two panoramic radiographs taken between the ages of 7 and 14 years with an interval of minimum 1 year and maximum 3 years (T1 and T2) were selected from the Department of Oral Health Sciences, University Hospital Leuven database. Linear and angular measurements were performed at T1. From 2361 records, 572 patients with unilateral or bilateral canine impaction were selected at T1. Of those, 306 patients were still untreated at T2 and were used as study sample. To construct the prediction model, logistic regression analysis was used. Results The parameters analyzed through backward selection procedure were canine to midline angle, canine to first premolar angle, canine cusp to midline distance, canine cusp to maxillary plane distance, sector, quadratic trends for continuous predictors, and all pairwise interactions. The final model was applied to calculate the likelihood of impaction and yielded an area under the curve equal to 0.783 (95% CI [0.742–0.823]). The cut‐off point was fixed on 0.342 with a sensitivity of 0.800 and a specificity of 0.598. The cross‐validated area under the curve was equal to 0.750 (95% CI [0.700, 0.799]). Conclusion The prediction model based on the above mentioned parameters measured on panoramic radiographs is a valuable tool to decide between early intervention and regular follow‐up of impacted canines.https://doi.org/10.1002/cre2.246cuspidimpacted toothpanoramic radiographypredictor
collection DOAJ
language English
format Article
sources DOAJ
author Raes Margot
Cadenas De Llano‐Pérula Maria
Alqerban Ali
Laenen Annouschka
Verdonck Anna
Willems Guy
spellingShingle Raes Margot
Cadenas De Llano‐Pérula Maria
Alqerban Ali
Laenen Annouschka
Verdonck Anna
Willems Guy
Prediction of maxillary canine impaction based on panoramic radiographs
Clinical and Experimental Dental Research
cuspid
impacted tooth
panoramic radiography
predictor
author_facet Raes Margot
Cadenas De Llano‐Pérula Maria
Alqerban Ali
Laenen Annouschka
Verdonck Anna
Willems Guy
author_sort Raes Margot
title Prediction of maxillary canine impaction based on panoramic radiographs
title_short Prediction of maxillary canine impaction based on panoramic radiographs
title_full Prediction of maxillary canine impaction based on panoramic radiographs
title_fullStr Prediction of maxillary canine impaction based on panoramic radiographs
title_full_unstemmed Prediction of maxillary canine impaction based on panoramic radiographs
title_sort prediction of maxillary canine impaction based on panoramic radiographs
publisher Wiley
series Clinical and Experimental Dental Research
issn 2057-4347
publishDate 2020-02-01
description Abstract Objectives The objective of this article is to establish a large sample‐based prediction model for maxillary canine impaction based on linear and angular measurements on panoramic radiographs and to validate this model. Materials and methods All patients with at least two panoramic radiographs taken between the ages of 7 and 14 years with an interval of minimum 1 year and maximum 3 years (T1 and T2) were selected from the Department of Oral Health Sciences, University Hospital Leuven database. Linear and angular measurements were performed at T1. From 2361 records, 572 patients with unilateral or bilateral canine impaction were selected at T1. Of those, 306 patients were still untreated at T2 and were used as study sample. To construct the prediction model, logistic regression analysis was used. Results The parameters analyzed through backward selection procedure were canine to midline angle, canine to first premolar angle, canine cusp to midline distance, canine cusp to maxillary plane distance, sector, quadratic trends for continuous predictors, and all pairwise interactions. The final model was applied to calculate the likelihood of impaction and yielded an area under the curve equal to 0.783 (95% CI [0.742–0.823]). The cut‐off point was fixed on 0.342 with a sensitivity of 0.800 and a specificity of 0.598. The cross‐validated area under the curve was equal to 0.750 (95% CI [0.700, 0.799]). Conclusion The prediction model based on the above mentioned parameters measured on panoramic radiographs is a valuable tool to decide between early intervention and regular follow‐up of impacted canines.
topic cuspid
impacted tooth
panoramic radiography
predictor
url https://doi.org/10.1002/cre2.246
work_keys_str_mv AT raesmargot predictionofmaxillarycanineimpactionbasedonpanoramicradiographs
AT cadenasdellanoperulamaria predictionofmaxillarycanineimpactionbasedonpanoramicradiographs
AT alqerbanali predictionofmaxillarycanineimpactionbasedonpanoramicradiographs
AT laenenannouschka predictionofmaxillarycanineimpactionbasedonpanoramicradiographs
AT verdonckanna predictionofmaxillarycanineimpactionbasedonpanoramicradiographs
AT willemsguy predictionofmaxillarycanineimpactionbasedonpanoramicradiographs
_version_ 1724922275979853824