Barone Selene, Cevidanes Lucia, Bianchi Jonas, Goncalves Joao Roberto, Giudice Amerigo
Department of Health Sciences, School of Dentistry, Magna Graecia University of Catanzaro, Catanzaro, Italy.
Department of Orthodontics and Pediatric Dentistry, School of Dentistry, University of Michigan, Ann Arbor, Michigan, USA.
Orthod Craniofac Res. 2025 Jun;28(3):441-448. doi: 10.1111/ocr.12895. Epub 2025 Jan 4.
This retrospective study aimed to evaluate morphometric changes in mandibular condyles of patients with skeletal Class III malocclusion following two-jaw orthognathic surgery planned using virtual surgical planning (VSP) and analysed with automated three-dimensional (3D) image analysis based on deep-learning techniques.
Pre-operative (T1) and 12-18 months post-operative (T2) Cone-Beam Computed Tomography (CBCT) scans of 17 patients (mean age: 24.8 ± 3.5 years) were analysed using 3DSlicer software. Deep-learning algorithms automated CBCT orientation, registration, bone segmentation, and landmark identification. By utilising voxel-based superimposition of pre- and post-operative CBCT scans and shape correspondence, the overall changes in condylar morphology were assessed, with a focus on bone resorption and apposition at specific regions (superior, lateral and medial poles). The correlation between these modifications and the extent of actual condylar movements post-surgery was investigated. Statistical analysis was conducted with a significance level of α = 0.05.
Overall condylar remodelling was minimal, with mean changes of < 1 mm. Small but statistically significant bone resorption occurred at the condylar superior articular surface, while bone apposition was primarily observed at the lateral pole. The bone apposition at the lateral pole and resorption at the superior articular surface were significantly correlated with medial condylar displacement (p < 0.05).
The automated 3D analysis revealed distinct patterns of condylar remodelling following orthognathic surgery in skeletal Class III patients, with minimal overall changes but significant regional variations. The correlation between condylar displacements and remodelling patterns highlights the need for precise pre-operative planning to optimise condylar positioning, potentially minimising harmful remodelling and enhancing stability.
本回顾性研究旨在评估采用虚拟手术规划（VSP）进行双颌正颌手术的骨性III类错牙合患者下颌髁突的形态计量学变化，并基于深度学习技术通过自动三维（3D）图像分析进行分析。
使用3DSlicer软件分析17例患者（平均年龄：24.8±3.5岁）术前（T1）和术后12 - 18个月（T2）的锥形束计算机断层扫描（CBCT）图像。深度学习算法自动进行CBCT定位、配准、骨分割和地标识别。通过利用术前和术后CBCT扫描的基于体素的叠加以及形状对应关系，评估髁突形态的总体变化，重点关注特定区域（上极、外侧极和内侧极）的骨吸收和骨增生情况。研究这些改变与术后髁突实际移动程度之间的相关性。采用α = 0.05的显著性水平进行统计分析。
髁突的总体重塑程度极小，平均变化<1mm。髁突上关节面出现小但具有统计学意义的骨吸收，而骨增生主要见于外侧极。外侧极的骨增生和上关节面的骨吸收与髁突内侧移位显著相关（p < 0.05）。
自动三维分析揭示了骨性III类患者正颌手术后髁突重塑的独特模式，总体变化极小，但存在显著的区域差异。髁突移位与重塑模式之间的相关性凸显了精确术前规划以优化髁突定位的必要性，这可能会将有害重塑降至最低并增强稳定性。
