Alqerban Ali, Jacobs Reinhilde, Fieuws Steffen, Willems Guy
*Department of Preventive Dental Sciences, College of Dentistry, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia, ****Department of Oral Health Sciences, KU Leuven and Dentistry, University Hospitals Leuven, Belgium.
**Department of Imaging and Pathology/OMFS-IMPATH Research Group, KU Leuven.
Eur J Orthod. 2016 Jun;38(3):292-9. doi: 10.1093/ejo/cjv047. Epub 2015 Jul 6.
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.
旨在基于二维全景X线片评估的影像学变量，确定阻生尖牙所致牙根吸收（RR）的预测模型，以减少额外锥形束计算机断层扫描（CBCT）成像的需求。
306例患者（188例女性，118例男性；平均年龄14.7岁；标准差5.6；范围8.4 - 47.2岁）纳入本研究。共研究了406颗上颌阻生尖牙，其中206例为单侧阻生患者，100例为双侧阻生患者。有初始二维全景X线片，根据临床指征获取三维CBCT成像。在二维全景成像上收集所产生的影像学变量和所研究的特定特征，并与CBCT上检测到的RR的有无相关联。收集了由45例上颌尖牙阻生患者的55颗尖牙组成的验证样本，以验证本研究的结果。
邻牙RR的发生率为33.8%。建立了一个使用全景图像预测RR可能存在的模型[曲线下面积（AUC）= 0.74，95%置信区间（CI）：0.69 - 0.79]，并通过留一法交叉验证进行验证（AUC = 0.71，95% CI：0.66 - 0.77）。对于严重RR存在的亚组，判别能力提高到0.80。在这个预测模型中，患者性别、尖牙根尖、尖牙冠垂直位置和尖牙放大率是RR的最强预测因素。
基于现有全景X线片的RR最终预测模型可能是证明是否需要额外CBCT检查的有用工具。
