目的:本研究旨在开发和评估一种全自动方法,该方法使用成对的口腔内扫描(IOSs)与手动方案进行比较,以可视化和测量牙齿磨损进展。
方法:回顾性纳入了8例严重牙齿磨损进展的患者,在基线和1年时采取IOS,3年,5年随访。为了对齐,自动化方法将牙弓分割成IOS中的单独牙齿。齿对配准所选择的可能不受牙齿磨损影响的牙齿表面,并且在所选择的表面上执行点集配准。使用手动3D磨损分析(3DWA)协议和自动化方法,基于带符号距离确定从基线到每次随访的最大齿形损失。通过将牙齿分割与Dice-Sørensen系数(DSC)和交叉结合(IoU)进行比较,针对3DWA协议评估了自动方法。将牙齿轮廓损失测量值与回归图和Bland-Altman图进行比较。此外,显示了时间间隔与两种方法测量差异之间的关系。
结果:自动方法在两分钟内完成。对于牙齿实例分割非常有效(826颗牙齿,DSC=0.947,IoU=0.907),并且在牙齿轮廓损失测量结果上观察到0.932的相关性(516对牙齿,平均差=0.021mm,95%置信区间=[-0.085,0.138])。测量差异的可变性在较大的时间间隔内增加。
结论:与全弓IOS的手动方案相比,所提出的用于监测牙齿磨损进展的自动化方法更快,并且在准确性方面没有临床上的显着差异。
结论:全科医生和患者可以从牙齿磨损的可视化中受益,允许有关磨损牙齿的治疗要求的量化和标准化的决定。与手动方法相比,所提出的用于牙齿磨损监测的方法将所需的时间减少到不到两分钟,至少花了两个小时.
OBJECTIVE: This study aimed to develop and evaluate a fully automated method for visualizing and measuring tooth wear progression using pairs of intraoral scans (IOSs) in comparison with a manual protocol.
METHODS: Eight patients with severe tooth wear progression were retrospectively included, with IOSs taken at baseline and 1-year, 3-year, and 5-year follow-ups. For alignment, the automated method segmented the arch into separate teeth in the IOSs. Tooth pair registration selected tooth surfaces that were likely unaffected by tooth wear and performed point set registration on the selected surfaces. Maximum tooth profile losses from baseline to each follow-up were determined based on signed distances using the manual 3D Wear Analysis (3DWA) protocol and the automated method. The automated method was evaluated against the 3DWA protocol by comparing tooth segmentations with the Dice-Sørensen coefficient (DSC) and intersection over union (IoU). The tooth profile loss measurements were compared with regression and Bland-Altman plots. Additionally, the relationship between the time interval and the measurement differences between the two methods was shown.
RESULTS: The automated method completed within two minutes. It was very effective for tooth instance segmentation (826 teeth, DSC = 0.947, IoU = 0.907), and a correlation of 0.932 was observed for agreement on tooth profile loss measurements (516 tooth pairs, mean difference = 0.021mm, 95% confidence interval = [-0.085, 0.138]). The variability in measurement differences increased for larger time intervals.
CONCLUSIONS: The proposed automated method for monitoring tooth wear progression was faster and not clinically significantly different in accuracy compared to a manual protocol for full-arch IOSs.
CONCLUSIONS: General practitioners and patients can benefit from the visualization of tooth wear, allowing quantifiable and standardized decisions concerning therapy requirements of worn teeth. The proposed method for tooth wear monitoring decreased the time required to less than two minutes compared with the manual approach, which took at least two hours.