Alt Sophie, Gajny Laurent, Tilotta Françoise, Schouman Thomas, Dot Gauthier
Institut de Biomecanique Humaine Georges Charpak, Arts et Metiers Institute of Technology, Paris, France.
Université Paris Cité and Sorbonne Paris Nord, UMR1333 INSERM Santé Orale, Montrouge, F-92120, France.
Clin Oral Investig. 2025 May 26;29(6):311. doi: 10.1007/s00784-025-06397-z.
The determination of the mid-sagittal plane (MSP) on three-dimensional (3D) head imaging is key to the assessment of facial asymmetry. The aim of this study was to evaluate the reliability of an automated landmark-based MSP to quantify mandibular asymmetry on head computed tomography (CT) scans.
A dataset of 368 CT scans, including orthognathic surgery patients, was automatically annotated with 3D cephalometric landmarks via a previously published deep learning-based method. Five of these landmarks were used to automatically construct an MSP orthogonal to the Frankfurt horizontal plane. The reliability of automatic MSP construction was compared with the reliability of manual MSP construction based on 6 manual localizations by 3 experienced operators on 19 randomly selected CT scans. The mandibular asymmetry of the 368 CT scans with respect to the MSP was calculated and compared with clinical expert judgment.
The construction of the MSP was found to be highly reliable, both manually and automatically. The manual reproducibility 95% limit of agreement was less than 1 mm for -y translation and less than 1.1° for -x and -z rotation, and the automatic measurement lied within the confidence interval of the manual method. The automatic MSP construction was shown to be clinically relevant, with the mandibular asymmetry measures being consistent with the expertly assessed levels of asymmetry.
The proposed automatic landmark-based MSP construction was found to be as reliable as manual construction and clinically relevant in assessing the mandibular asymmetry of 368 head CT scans.
Once implemented in a clinical software, fully automated landmark-based MSP construction could be clinically used to assess mandibular asymmetry on head CT scans.
在三维（3D）头部成像上确定正中矢状面（MSP）是评估面部不对称的关键。本研究的目的是评估基于自动地标法的MSP在头部计算机断层扫描（CT）上量化下颌不对称的可靠性。
通过先前发表的基于深度学习的方法，对包括正颌手术患者在内的368例CT扫描数据集进行3D头影测量地标自动标注。其中五个地标用于自动构建与法兰克福水平面正交的MSP。基于3名经验丰富的操作人员在19例随机选择的CT扫描上进行的6次手动定位，将自动构建MSP的可靠性与手动构建MSP的可靠性进行比较。计算368例CT扫描相对于MSP的下颌不对称性，并与临床专家判断进行比较。
发现MSP的构建无论是手动还是自动都具有高度可靠性。手动重复性的95%一致性界限在-y平移方面小于1毫米，在-x和-z旋转方面小于1.1°，自动测量值落在手动方法的置信区间内。自动构建的MSP在临床上具有相关性，下颌不对称测量结果与专家评估的不对称水平一致。
所提出的基于自动地标的MSP构建方法与手动构建一样可靠，并且在评估368例头部CT扫描的下颌不对称性方面具有临床相关性。
一旦在临床软件中实施，基于完全自动地标的MSP构建可在临床上用于评估头部CT扫描上的下颌不对称性。
