Statistical shape analysis of metopic craniosynostosis: a preliminary study.

Charlie Srivilasa*, Linping Zhao, Pravin K. Patel, Tadanori Tomita, Shu Q. Liu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


This preliminary study was conducted to explore different analytical shape methods for use in evaluating children born with cranial vault deformities. Twenty skull outlines from patients with metopic craniosynostosis were ascribed landmarks. Scale, location, and rotational factors were removed using Procrustes analysis. A single index of severity from 0-5, with 5 being the most severe, was developed using Procrustes distance in shape space. Skull 20 had the highest score in our data set. Principal component analysis was performed to determine areas of large shape variability. Principal component 1 and 2 accounted for 86 % of the shape variability which was attributed to early closure of the metopic suture. Procrustes analysis used in combination with Procrustes distance and principal component analysis are powerful tools for the evaluation of cranial vault deformities and can be used to objectively categorize the severity of the skull deformity and outcome from surgical reconstructive surgery.

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

Fingerprint Dive into the research topics of 'Statistical shape analysis of metopic craniosynostosis: a preliminary study.'. Together they form a unique fingerprint.

Cite this