, Hilzingen, Germany.
Department of Prosthetic Dentistry, Center of Dentistry, Ulm University, Albert-Einstein-Allee 1, 89081, Ulm, Germany.
Oral Radiol. 2019 May;35(2):152-158. doi: 10.1007/s11282-018-0340-1. Epub 2018 Jul 27.
For correct implant planning based on cone-beam computed tomography (CBCT), the bone contour must be accurately determined. Identification of the contour is difficult in bones with incomplete mineralization. In this clinical study, we investigated the intrapersonal and interpersonal reproducibilities of manual bone contour determination on CBCT images using a semi-automated computerized process.
The bone surface level in the area of the socket in 20 patients who had undergone tooth extraction from the upper jaw at 10 ± 1 weeks previously was determined on CBCT images. Two investigators with different levels of experience determined the bone structure initially (T) and repeated the procedure after 3 months (T). The bone structure marked on CBCT images was converted into a surface data set. The resulting data sets were superimposed on one another. In the analyses, the shortest distances between the datasets were identified and measured. The average deviations were statistically evaluated.
The intrapersonal evaluation resulted in an average deviation of 0.18 mm across both investigators. The interpersonal analysis comparing the two investigators resulted in average deviations of 0.15 mm at T and 0.26 mm at T. Significant differences were not found.
The low intrapersonal deviation indicates that the procedure has satisfactory reproducibility. All deviations were within the range of the selected resolution of the CBCT device. Application of a semi-automated procedure to detect the bone border in areas with incomplete mineralization is a predictable process.
The study was registered in the German Clinical Trials Register and the International Clinical Trials Registry Platform of the WHO: DRKS00004769, date of registration: 28 February 2013; and DRKS00005978, date of registration: 09 November 2015.
为了基于锥形束 CT(CBCT)进行正确的植入物规划,必须准确确定骨轮廓。在不完全矿化的骨中,轮廓的识别较为困难。在这项临床研究中,我们使用半自动计算机处理方法,研究了手动 CBCT 图像上骨轮廓确定的个体内和个体间的可重复性。
在 20 名于 10±1 周前接受过上颌拔牙的患者的 CBCT 图像上,确定拔牙窝区域的骨表面水平。两名经验不同的调查员首先确定骨结构(T),并在 3 个月后(T)重复该程序。在 CBCT 图像上标记的骨结构被转换为表面数据集。将生成的数据集相互叠加。在分析中,确定并测量了数据集之间的最短距离。对平均偏差进行了统计学评估。
个体内评估结果显示,两名调查员的平均偏差为 0.18mm。比较两名调查员的个体间分析得出,T 时的平均偏差为 0.15mm,T 时的平均偏差为 0.26mm。未发现显著差异。
低个体内偏差表明该程序具有良好的可重复性。所有偏差均在所选 CBCT 设备分辨率的范围内。在不完全矿化区域应用半自动程序检测骨边界是一个可预测的过程。
该研究在德国临床试验注册中心和世界卫生组织国际临床试验注册平台上注册:DRKS00004769,注册日期:2013 年 2 月 28 日;DRKS00005978,注册日期:2015 年 11 月 9 日。