Department of Orthodontics and Dentofacial Orthopedics, Kathmandu University School of Medical Sciences, Dhulikhel, Nepal.
BMC Oral Health. 2022 Apr 19;22(1):132. doi: 10.1186/s12903-022-02170-w.
Artificial Intelligence has created a huge impact in different areas of dentistry. Automated cephalometric analysis is one of the major applications of artificial intelligence in the field of orthodontics. Various automated cephalometric software have been developed which utilizes artificial intelligence and claim to be reliable. The purpose of this study was to compare the linear and angular cephalometric measurements obtained from web-based fully automated Artificial Intelligence (AI) driven platform "WebCeph"™ with that from manual tracing and evaluate the validity and reliability of automated cephalometric measurements obtained from "WebCeph"™.
Thirty pre-treatment lateral cephalograms of patients were randomly selected. For manual tracing, digital images of same cephalograms were printed using compatible X-ray printer. After calibration, a total of 18 landmarks was plotted and 12 measurements (8 angular and 4 linear) were obtained using standard protocols. The digital images of each cephalogram were uploaded to "WebCeph"™ server. After image calibration, the automated cephalometric measurements obtained through AI digitization were downloaded for each image. Intraclass correlation coefficient (ICC) was used to determine agreement between the measurements obtained from two methods. ICC value < 0.75 was considered as poor to moderate agreement while an ICC value between 0.75 and 0.90 was considered as good agreement. Agreement was rated as excellent when ICC value > 0.90 was obtained.
All the measurements had ICC value above 0.75. A higher ICC value > 0.9 was obtained for seven parameters i.e. ANB, FMA, IMPA/L1 to MP (°), LL to E-line, L1 to NB (mm), L1 to NB (°), S-N to Go-Gn whereas five parameters i.e. UL to E-line, U1 to NA (mm), SNA, SNB, U1 to NA (°) showed ICC value between 0.75 and 0.90.
A good agreement was found between the cephalometric measurements obtained from "WebCeph"™ and manual tracing.
人工智能在牙科的不同领域产生了巨大的影响。自动头影测量分析是人工智能在正畸领域的主要应用之一。已经开发出各种利用人工智能并声称可靠的自动头影测量软件。本研究的目的是比较从基于网络的完全自动化人工智能（AI）驱动平台“WebCeph”™获得的线性和角度头影测量值与手动追踪获得的测量值，并评估从“WebCeph”™获得的自动头影测量值的有效性和可靠性。
随机选择 30 名治疗前的侧位头颅侧位片。对于手动追踪，使用兼容的 X 射线打印机打印相同头颅侧位片的数字图像。经过校准后，总共标记了 18 个标志点，并按照标准协议获得了 12 个测量值（8 个角度和 4 个线性）。每个头颅侧位片的数字图像都上传到“WebCeph”™服务器。图像校准后，下载 AI 数字化获得的自动头影测量值。使用组内相关系数（ICC）来确定两种方法获得的测量值之间的一致性。ICC 值<0.75 被认为是较差到中等一致性，而 ICC 值在 0.75 和 0.90 之间被认为是良好的一致性。当获得 ICC 值>0.90 时，一致性被评为优秀。
所有测量值的 ICC 值均高于 0.75。有七个参数（ANB、FMA、IMPA/L1 到 MP（°）、LL 到 E-line、L1 到 NB（mm）、L1 到 NB（°）、S-N 到 Go-Gn）的 ICC 值较高，超过 0.9，而五个参数（UL 到 E-line、U1 到 NA（mm）、SNA、SNB、U1 到 NA（°）的 ICC 值在 0.75 和 0.90 之间。
从“WebCeph”™获得的头影测量值与手动追踪获得的测量值之间存在良好的一致性。
