Quantitative morphological analysis framework of infant cranial sutures and fontanelles based on CT images.
infant fontanelle
infant suture
morphological variation
morphology analysis framework
statistical model
Journal
Journal of anatomy
ISSN: 1469-7580
Titre abrégé: J Anat
Pays: England
ID NLM: 0137162
Informations de publication
Date de publication:
09 May 2024
09 May 2024
Historique:
revised:
16
04
2024
received:
02
11
2023
accepted:
22
04
2024
medline:
9
5
2024
pubmed:
9
5
2024
entrez:
9
5
2024
Statut:
aheadofprint
Résumé
Characterizing the suture morphological variation is a crucial step to investigate the influence of sutures on infant head biomechanics. This study aimed to establish a comprehensive quantitative framework for accurately capturing the cranial suture and fontanelle morphologies in infants. A total of 69 CT scans of 2-4 month-old infant heads were segmented to identify semilandmarks at the borders of cranial sutures and fontanelles. Morphological characteristics, including length, width, sinuosity index (SI), and surface area, were measured. For this, an automatic method was developed to determine the junction points between sutures and fontanelles, and thin-plate-spline (TPS) was utilized for area calculation. Different dimensionality reduction methods were compared, including nonlinear and linear principal component analysis (PCA), as well as deep-learning-based variational autoencoder (VAE). Finally, the significance of various covariates was analyzed, and regression analysis was performed to establish a statistical model relating morphological parameters with global parameters. This study successfully developed a quantitative morphological framework and demonstrate its application in quantifying morphologies of infant sutures and fontanelles, which were shown to significantly relate to global parameters of cranial size, suture SI, and surface area for infants aged 2-4 months. The developed framework proved to be reliable and applicable in extracting infant suture morphology features from CT scans. The demonstrated application highlighted its potential to provide valuable insights into the morphologies of infant cranial sutures and fontanelles, aiding in the diagnosis of suture-related skull fractures. Infant suture, Infant fontanelle, Morphological variation, Morphology analysis framework, Statistical model.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : Vetenskapsrådet
ID : 2016-04203
Organisme : Vetenskapsrådet
ID : 2020-04496
Organisme : Vetenskapsrådet
ID : 2020-04724
Informations de copyright
© 2024 The Authors. Journal of Anatomy published by John Wiley & Sons Ltd on behalf of Anatomical Society.
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