Robertson Emilie, Boulanger Pierre, Kwan Peter, Louie Gorman, Aalto Daniel
Division of Plastic Surgery, University of Alberta, Edmonton, AB, Canada.
Institute for Reconstructive Sciences in Medicine, Misericordia Hospital, Edmonton, AB, Canada.
Craniomaxillofac Trauma Reconstr. 2024 Sep;17(3):203-213. doi: 10.1177/19433875231178912. Epub 2023 Jun 16.
Cranial vault remodeling (CVR) for unicoronal synostosis is challenging due to the asymmetric nature of the deformity. Computer-automated surgical planning has demonstrated success in reducing the subjectivity of decision making in CVR in symmetric subtypes. This proof of concept study presents a novel method using Boolean functions and image registration to automatically suggest surgical steps in asymmetric craniosynostosis.
The objective of this study is to introduce automated surgical planning into a CVR virtual workflow for an asymmetric craniosynostosis subtype.
Virtual workflows were developed using Geomagic Freeform Plus software. Hausdorff distances and color maps were used to compare reconstruction models to the preoperative model and a control skull. Reconstruction models were rated as high or low performing based on similarity to the normal skull and the amount of advancement of the frontal bone (FB) and supra-orbital bar (SOB). Fifteen partially and fully automated workflow iterations were carried out.
FB and SOB advancement ranged from 3.08 to 10.48 mm, and -1.75 to 7.78 mm, respectively. Regarding distance from a normal skull, models ranged from .85 to 5.49 mm at the FB and 5.40 to 10.84 mm at the SOB. An advancement of 8.43 mm at the FB and 7.73 mm at the SOB was achieved in the highest performing model, and it differed to a comparative normal skull by .02 mm at the FB and .48 mm at the SOB.
This is the first known attempt at developing an automated virtual surgical workflow for CVR in asymmetric craniosynostosis. Key regions of interest were outlined using Boolean operations, and surgical steps were suggested using image registration. These techniques improved post-operative skull morphology.
由于单冠状缝早闭畸形的不对称性,颅骨重塑(CVR)具有挑战性。计算机自动化手术规划已证明在减少对称亚型CVR决策的主观性方面取得了成功。这项概念验证研究提出了一种使用布尔函数和图像配准的新方法,以自动建议不对称颅骨缝早闭的手术步骤。
本研究的目的是将自动化手术规划引入不对称颅骨缝早闭亚型的CVR虚拟工作流程。
使用Geomagic Freeform Plus软件开发虚拟工作流程。使用豪斯多夫距离和彩色图将重建模型与术前模型和对照颅骨进行比较。根据与正常颅骨的相似性以及额骨(FB)和眶上缘(SOB)的前移量,将重建模型评为高性能或低性能。进行了15次部分和完全自动化的工作流程迭代。
FB和SOB的前移量分别为3.08至10.48毫米和-1.75至7.78毫米。关于与正常颅骨的距离,模型在FB处为0.85至5.49毫米,在SOB处为5.40至10.84毫米。在性能最高的模型中,FB处前移8.43毫米,SOB处前移7.73毫米,与对照正常颅骨相比,FB处相差0.02毫米,SOB处相差0.48毫米。
这是首次尝试为不对称颅骨缝早闭的CVR开发自动化虚拟手术工作流程。使用布尔运算勾勒出关键感兴趣区域,并使用图像配准建议手术步骤。这些技术改善了术后颅骨形态。