Laurenziello Michele, Montaruli Graziano, Gallo Crescenzio, Tepedino Michele, Guida Laura, Perillo Letizia, Troiano Giuseppe, Lo Muzio Lorenzo, Ciavarella Domenico
University of Foggia, Department of Clinical and Experimental Medicine; Foggia,Italy.
University of Aquila, Applied Clinical Sciences and Biotecnology, Aquila, Italy.
J Clin Exp Dent. 2017 Nov 1;9(11):e1304-e1309. doi: 10.4317/jced.54095. eCollection 2017 Nov.
The aim of this study is to evaluate determinants of maxillary canine impaction taking into account both canine position related variables and the pattern of facial growth.
A retrospective clinical and radiographic analysis was carried out on 109 patients aged between 9 and 10 years at the time of first evaluation. At baseline, SN-GoMe angle, the interincisal angle, the canine angle α and the canine distance d were used to characterize canine location and vertical facial growth. At the end of a two years follow up period the eruption state of each canine of each patient was recorded and accordingly classified as erupted or impacted on a clinical and radiographic basis. Univariate and multivariate statistical analyses were performed, including correlation among the studied variables and principal components analysis; several machine learning methods were also used in order to built a predictive model.
At the end of the two years follow up period after the first examination, 54 (24.77%) canines were classified as impacted. Except for Angle α values, there were no statistically significant differences between impacted and erupted canines. The studied variables were not significantly correlated, except for the SN-GoMe Angle and the distance d in the impacted canine group and the angle α and the distance d in erupted canines group. All variables, except for SN-GoMe Angle in erupted canines, have a partial communality with the first two principal components greater than 50%. Among the learning machine methods tested to classify data, the best performance was obtained by the random forest method, with an overall accuracy in predicting canine eruption of 88.3%.
The studied determinants are easy to perform measurements on 2D routinely executed radiographic images; they seems independently related to canine impaction and have reliable accuracy in predicting maxillary canine eruption. Canine impaction, Determinants, Facial growth.
本研究的目的是评估上颌尖牙阻生的决定因素,同时考虑与尖牙位置相关的变量和面部生长模式。
对首次评估时年龄在9至10岁之间的109例患者进行回顾性临床和影像学分析。在基线时,使用SN-GoMe角、切牙间角、尖牙角α和尖牙距离d来表征尖牙位置和垂直面部生长。在两年随访期结束时,记录每位患者每颗尖牙的萌出状态,并根据临床和影像学结果将其分类为萌出或阻生。进行了单变量和多变量统计分析,包括研究变量之间的相关性和主成分分析;还使用了几种机器学习方法来建立预测模型。
在首次检查后的两年随访期结束时,54颗(24.77%)尖牙被分类为阻生。除了角α值外,阻生尖牙和萌出尖牙之间没有统计学上的显著差异。所研究的变量之间没有显著相关性,除了阻生尖牙组中的SN-GoMe角和距离d以及萌出尖牙组中的角α和距离d。除了萌出尖牙中的SN-GoMe角外,所有变量与前两个主成分的部分共同度均大于50%。在测试用于分类数据的机器学习方法中,随机森林方法表现最佳,预测尖牙萌出的总体准确率为88.3%。
所研究的决定因素易于在常规执行的二维放射影像上进行测量;它们似乎与尖牙阻生独立相关,并且在预测上颌尖牙萌出方面具有可靠的准确性。尖牙阻生、决定因素、面部生长。