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基于数字手动和基于网络的人工智能头影测量追踪软件的头影测量比较。

Comparison between cephalometric measurements using digital manual and web-based artificial intelligence cephalometric tracing software.

机构信息

Erciyes University, Faculty of Dentistry, Department of Orthodontics (Talas/Kayseri, Turkey).

出版信息

Dental Press J Orthod. 2022 Aug 15;27(4):e222112. doi: 10.1590/2177-6709.27.4.e222112.oar. eCollection 2022.

Abstract

OBJECTIVE

The aim of this study was to compare the measurements performed with digital manual (DM) cephalometric analysis and automatic cephalometric analysis obtained from an online artificial intelligence (AI) platform, according to different sagittal skeletal malocclusions.

METHODS

Cephalometric radiographs of 105 randomly selected individuals (mean age: 17.25 ± 1.87 years) were included in this study. Dolphin Imaging software was used for DM cephalometric analysis, and the WebCeph platform was used for AI-based cephalometric analysis. In total, 10 linear and 12 angular measurements were evaluated. The paired t-test, one-way ANOVA test, and intraclass correlation coefficient tests were used to evaluate the differences between the two methods. The level of statistical significance was set at p< 0.05.

RESULTS

Except for SNB, NPog, U1.SN, U1.NA, L1-APog, I/I, and LLE parameters, all other parameters presented significant differences between the two methods (p< 0.05). While there was no difference (p> 0.05) in both SNA and SNB measurements between the two methods in the Class I malocclusion group, there was a difference between both methods in the Class II malocclusion group. Meanwhile, only the SNA in the Class III malocclusion group was different (p< 0.05). The ANB angle differed significantly in all three malocclusion groups. For both methods, all parameters except CoA and CoGn were found to have good correlation.

CONCLUSION

Although significant differences were detected in some measurements between the two cephalometric analysis methods, not all differences were clinically significant. The AI-based cephalometric analysis method needs to be developed for more specific malocclusions.

摘要

目的

本研究旨在比较数字手动(DM)头影测量分析与在线人工智能(AI)平台获得的自动头影测量分析在不同矢状骨错颌中的测量结果。

方法

本研究纳入了 105 名随机个体的头颅侧位片(平均年龄:17.25±1.87 岁)。使用 Dolphin Imaging 软件进行 DM 头影测量分析,使用 WebCeph 平台进行基于 AI 的头影测量分析。共评估了 10 个线性和 12 个角度测量值。采用配对 t 检验、单因素方差分析和组内相关系数检验来评估两种方法之间的差异。统计学显著性水平设为 p<0.05。

结果

除 SNB、NPog、U1.SN、U1.NA、L1-APog、I/I 和 LLE 外,两种方法的其他参数均存在显著差异(p<0.05)。在 I 类错颌组中,两种方法的 SNA 和 SNB 测量值之间没有差异(p>0.05),而在 II 类错颌组中两种方法之间存在差异。同时,仅 III 类错颌组的 SNA 存在差异(p<0.05)。三种错颌组的 ANB 角均有显著差异。两种方法的所有参数除 CoA 和 CoGn 外,其余参数相关性均较好。

结论

尽管两种头影测量分析方法的一些测量值存在显著差异,但并非所有差异均具有临床意义。需要为更具体的错颌类型开发基于 AI 的头影测量分析方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cadf/9377318/b8f767897dd3/2177-6709-dpjo-27-04-e222112-gf1.jpg

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