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...
Main Authors: | , , , , , |
---|---|
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 |