Kunz Felix, Stellzig-Eisenhauer Angelika, Zeman Florian, Boldt Julian
Poliklinik für Kieferorthopädie, Universitätsklinikum Würzburg, Pleicherwall 2, 97070, Würzburg, Germany.
Zentrum für Klinische Studien, Universitätsklinikum Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany.
J Orofac Orthop. 2020 Jan;81(1):52-68. doi: 10.1007/s00056-019-00203-8. Epub 2019 Dec 18.
The aim of this investigation was to create an automated cephalometric X‑ray analysis using a specialized artificial intelligence (AI) algorithm. We compared the accuracy of this analysis to the current gold standard (analyses performed by human experts) to evaluate precision and clinical application of such an approach in orthodontic routine.
For training of the network, 12 experienced examiners identified 18 landmarks on a total of 1792 cephalometric X‑rays. To evaluate quality of the predictions of the AI, both AI and each examiner analyzed 12 commonly used orthodontic parameters on a basis of 50 cephalometric X‑rays that were not part of the training data for the AI. Median values of the 12 examiners for each parameter were defined as humans' gold standard and compared to the AI's predictions.
There were almost no statistically significant differences between humans' gold standard and the AI's predictions. Differences between the two analyses do not seem to be clinically relevant.
We created an AI algorithm able to analyze unknown cephalometric X‑rays at almost the same quality level as experienced human examiners (current gold standard). This study is one of the first to successfully enable implementation of AI into dentistry, in particular orthodontics, satisfying medical requirements.
本研究旨在使用专门的人工智能（AI）算法创建一种自动头影测量X线分析方法。我们将这种分析的准确性与当前的金标准（由人类专家进行的分析）进行比较，以评估这种方法在正畸常规中的精度和临床应用。
为了训练网络，12名经验丰富的检查人员在总共1792张头影测量X线片上识别出18个标志点。为了评估AI预测的质量，AI和每位检查人员都基于50张头影测量X线片分析了12个常用的正畸参数，这些X线片不是AI训练数据的一部分。将12名检查人员对每个参数的中位数定义为人类的金标准，并与AI的预测结果进行比较。
人类金标准与AI预测之间几乎没有统计学上的显著差异。两种分析之间的差异似乎在临床上并不相关。
我们创建了一种AI算法，能够以与经验丰富的人类检查人员（当前金标准）几乎相同的质量水平分析未知的头影测量X线片。本研究是首批成功将AI应用于牙科，特别是正畸领域并满足医学要求的研究之一。
