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基于统计形状模型的眶底缺损的虚拟重建。

Virtual reconstruction of orbital floor defects using a statistical shape model.

机构信息

Department of Oral and Maxillofacial Surgery, Albert-Ludwigs University Freiburg, Freiburg, Germany.

Department of Physical Anthropology, Albert-Ludwigs-University Freiburg, Freiburg, Germany.

出版信息

J Anat. 2022 Feb;240(2):323-329. doi: 10.1111/joa.13550. Epub 2021 Oct 17.

Abstract

PURPOSE

The current standard in reconstructing defects of the orbital floor, by using the concept of mirroring, is time-consuming and ignores the natural asymmetry of the skull. By using a statistical shape model (SSM), the reconstruction can be automatized and improved in accuracy. The present study aims to show the possibilities of the virtual reconstruction of artificial defects of the orbital floor using an SSM and its potentials for clinical implementation.

METHODS

Based on 131 unaffected CT scans of the midface, an SSM was created which contained the shape variability of the orbital floor. Nineteen midface CT scans, that were not included in the SSM, were manually segmented to establish ground truth (control group). Then artificial defects of larger and smaller sizes were created and reconstructed using SSM (Group I) and the gold standard of mirroring (Group II). Eventually, a comparison to the surface of the manual segmentation (control group) was performed.

RESULTS

The proposed method of reconstruction using an SSM leads to more precise reconstruction results, compared with the conventional method of mirroring. Whereas mirroring led to the reconstruction errors of 0.7 mm for small defects and 0.73 mm for large defects, reconstruction using SSM led to deviations of 0.26 mm (small defect) and, respectively, 0.34 mm (large defect).

CONCLUSIONS

The presented approach is an effective and accurate method for reconstructing the orbital floor. In connection with modern computer-aided design and manufacturing, individual patient-specific implants could be produced according to SSM-based reconstructions and could replace current methods using manual bending techniques. By acknowledging the natural asymmetry of the human skull, the SSM-based approach achieves higher accuracy in reconstructing injured orbits.

摘要

目的

目前,通过镜像的概念来重建眶底缺损是一种耗时的方法,且忽略了颅骨的自然不对称性。通过使用统计形状模型(SSM),重建过程可以实现自动化,并提高准确性。本研究旨在展示使用 SSM 对人工眶底缺损进行虚拟重建的可能性,以及其在临床应用中的潜力。

方法

基于 131 例无异常的中面部 CT 扫描,创建了一个包含眶底形状变异性的 SSM。19 例未包含在 SSM 中的中面部 CT 扫描被手动分割以建立真实数据(对照组)。然后,使用 SSM(第 I 组)和镜像的金标准(第 II 组)创建和重建大小更大和更小的人工缺损。最终,与手动分割的表面(对照组)进行了比较。

结果

与传统的镜像方法相比,使用 SSM 进行重建的方法导致更精确的重建结果。镜像导致小缺陷的重建误差为 0.7mm,大缺陷的重建误差为 0.73mm,而使用 SSM 进行重建导致的偏差分别为 0.26mm(小缺陷)和 0.34mm(大缺陷)。

结论

所提出的方法是一种有效且准确的重建眶底的方法。结合现代计算机辅助设计和制造,可以根据 SSM 重建制作个体化的患者特异性植入物,替代当前使用手动弯曲技术的方法。通过承认人类颅骨的自然不对称性,基于 SSM 的方法在重建受伤的眼眶时可以达到更高的准确性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0ea/8742960/77c3291e6ba7/JOA-240-323-g003.jpg

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