Hyer Jenna C, Deas David E, Palaiologou A Archontia, Noujeim Marcel E, Mader Michael J, Mealey Brian L
Department of Periodontics, UT Health San Antonio School of Dentistry, San Antonio, TX.
Private consultant, formerly Oral and Maxillofacial Radiology program director, UT Health San Antonio, San Antonio, TX.
J Periodontol. 2021 Mar;92(3):419-427. doi: 10.1002/JPER.19-0669. Epub 2020 Sep 2.
The aim of this study was to determine if image enhancement improves a clinician's ability to identify the presence of calculus on digital radiographs.
Seventy-one hopeless teeth were collected from 34 patients. Teeth were stained with 1% methylene blue, the largest interproximal calculus deposit was scored, and photographs of each interproximal root surface were taken. The surface area of calculus deposit was determined as a percentage of the total interproximal root surface area. Digital radiographs of teeth taken before extraction were modified using the following enhancements: auto-contrast, emboss, invert, and sharpen. Radiographic presence of calculus was determined by two examiners. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for each examiner and enhancement. A receiver operating characteristic curve was used to compare differences between the image enhancements in the detection of dental calculus. The kappa statistic was used to compare ratings between examiners.
None of the enhanced images were statistically superior to original images in identifying radiographic calculus (P > 0.05). The average sensitivity of digital radiography was 50%, average specificity was 82.2%, PPV was 94%, and NPV 23.2%. A threshold of >30% of interproximal root surface covered with calculus and increasing size of deposits were associated with improved detection (P < 0.05).
Digital enhancements do not significantly improve radiographic detection of dental calculus. As area of calculus on the root surface and size of calculus deposits increased, sensitivity of detection also increased.
本研究的目的是确定图像增强是否能提高临床医生在数字X线片上识别牙结石存在的能力。
从34例患者中收集了71颗无法保留的牙齿。牙齿用1%亚甲蓝染色,对最大的邻面牙结石沉积物进行评分,并拍摄每个邻面牙根表面的照片。牙结石沉积物的表面积以邻面牙根总面积的百分比来确定。拔牙前拍摄的牙齿数字X线片使用以下增强方法进行修改:自动对比度、浮雕、反转和锐化。由两名检查者确定X线片上牙结石的存在情况。计算每名检查者和每种增强方法的灵敏度、特异度、阳性预测值(PPV)和阴性预测值(NPV)。使用受试者工作特征曲线比较图像增强方法在牙结石检测中的差异。kappa统计量用于比较检查者之间的评级。
在识别X线片上的牙结石方面,没有一种增强后的图像在统计学上优于原始图像(P>0.05)。数字X线摄影的平均灵敏度为50%,平均特异度为82.2%,PPV为94%,NPV为23.2%。邻面牙根表面有超过30%被牙结石覆盖以及牙结石沉积物增大的阈值与检测效果改善相关(P<0.05)。
数字增强不能显著提高X线片对牙结石的检测能力。随着牙根表面牙结石面积和牙结石沉积物大小的增加,检测灵敏度也会增加。