five

Population average skull model obtained by means of statistical shape modelling

收藏
NIAID Data Ecosystem2026-03-14 收录
下载链接:
http://datadryad.org/dataset/doi%253A10.5061%252Fdryad.mw6m9061b
下载链接
链接失效反馈
官方服务:
资源简介:
Sagittal Craniosynostosis (SC) is a congenital condition whereby the newborn skull develops abnormally due to premature ossification of the sagittal suture. Spring-assisted cranioplasty (SAC) is a minimally invasive surgical technique to treat SC where metallic distractors are used to reshape the newborn’s head. Although safe and effective, SAC outcomes remain uncertain due to the limited understanding of skull-distractor interaction and limited information provided by the analysis of single surgical cases. Hereby, an SC population average skull model was created to simulate spring insertion by means of finite element analysis. Methods The GOSH Craniofacial Unit patient database was reviewed, and 13 SAC patients (11 male, age at SAC = 5.6 ± 0.7 months [4.6–6.7 months]), operated between 2011 and 2016, were included in this study. Each patient had a pre-op computer tomography (CT) performed between 3.2 months and 6 days earlier (age at CT = 4.2 ± 0.7 months [3.0–5.3 months]). Ethical approval was obtained for the use of patient image data for research purposes (UK REC 15/ LO/0386 - Research Ethics Committee approval - study n.14DS25).  The skull 3D shape (triangular mesh) of each patient was reconstructed from CT scans using Mimics (Materialise, Leuven) and further processed in Rhino3D (McNeel, WA) and Meshmixer (Autodesk, CA) to: 1)) create a reference plane through the nation, and the right and left external auditory meatus for consistency; 2) fill in skull defects and sutures, and obtain a smooth continuous surface; and 3) separate the inner surface of the skull bone from the outer surface. The outer skull surfaces were aligned and an average shape model was calculated for the population using statistical shape modelling, implemented in Deformetrica (www.deformetrica.org) (Durrleman et al., 2009).
创建时间:
2023-01-03
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作