Department of Restorative Dentistry and Endodontics, University Medical Centre Ljubljana, Ljubljana, Slovenia.
Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia.
J Clin Periodontol. 2022 Feb;49(2):153-163. doi: 10.1111/jcpe.13573. Epub 2021 Dec 14.
To introduce and validate a computer-aided method for direct measurements and visualization of gingival margin (GM) changes.
The method consists of five main steps: digital model acquisition, superimposition, computer-aided GM detection, distance calculation between the GM curves, and visualization. The precision of the method was evaluated with repeatability and reproducibility analysis (n = 78 teeth). The method's repeatability was evaluated by repeating the algorithm on the same digital models by two operators. The reproducibility was evaluated by repeating the algorithm on two consecutive digital models obtained with a scan-rescan process at the same time point on the same patient. For demonstration, the proposed method for direct measurements of GM changes was performed on patients who had undergone root coverage procedures and treatment of periodontal disease.
Excellent repeatability was found for both intra- and inter-operator variability, that is, 0.00 mm, regarding computer-aided GM detection. The reproducibility of computer-aided GM detection evaluated on scan-rescan models was 0.10 mm.
The presented method enables the evaluation of GM changes in a simple, precise, and comprehensive manner through non-invasive acquisition and superimposition of digital models.
介绍并验证一种用于直接测量和可视化牙龈边缘（GM）变化的计算机辅助方法。
该方法包括五个主要步骤：数字模型获取、叠加、计算机辅助 GM 检测、GM 曲线之间的距离计算和可视化。通过重复性和再现性分析（n=78 颗牙齿）评估该方法的精度。该方法的重复性通过由两名操作员对同一数字模型重复算法进行评估。再现性通过在同一患者的同一时间点使用扫描-重扫过程获得两个连续的数字模型并重复算法进行评估。为了演示，对接受根覆盖术和牙周病治疗的患者进行了 GM 变化的直接测量的建议方法。
在计算机辅助 GM 检测方面，无论是内部还是外部操作员的可重复性都非常好，即 0.00mm。在扫描-重扫模型上评估的计算机辅助 GM 检测的再现性为 0.10mm。
该方法通过数字模型的非侵入式获取和叠加，以简单、精确和全面的方式评估 GM 变化。
