Statistical shape modelling for the analysis of head shape variations

The aim of this study is, firstly, to create a population-based 3D head shape model for the 0 to 2-year-old subjects to describe head shape variability within a normal population and, secondly, to test a combined normal and sagittal craniosynostosis (SAG) population model, able to provide surgical o...

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Published inJournal of cranio-maxillo-facial surgery Vol. 49; no. 6; pp. 449 - 455
Main Authors Heutinck, Pam, Knoops, Paul, Florez, Naiara Rodriguez, Biffi, Benedetta, Breakey, William, James, Greg, Koudstaal, Maarten, Schievano, Silvia, Dunaway, David, Jeelani, Owase, Borghi, Alessandro
Format Journal Article
LanguageEnglish
Published Scotland Elsevier Ltd 01.06.2021
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ISSN1010-5182
1878-4119
1878-4119
DOI10.1016/j.jcms.2021.02.020

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Abstract The aim of this study is, firstly, to create a population-based 3D head shape model for the 0 to 2-year-old subjects to describe head shape variability within a normal population and, secondly, to test a combined normal and sagittal craniosynostosis (SAG) population model, able to provide surgical outcome assessment. 3D head shapes of patients affected by non-cranial related pathologies and of SAG patients (pre- and post-op) were extracted either from head CTs or 3D stereophotography scans, and processed. Statistical shape modelling (SSM) was used to describe shape variability using two models – a normal population model (MODEL1) and a combined normal and SAG population model (MODEL2). Head shape variability was described via principal components analysis (PCA) which calculates shape modes describing specific shape features. MODEL1 (n = 65) mode 1 showed statistical correlation (p < 0.001) with width (125.8 ± 13.6 mm), length (151.3 ± 17.4 mm) and height (112.5 ± 11.1 mm) whilst mode 2 showed correlation with cranial index (83.5 mm ± 6.3 mm, p < 0.001). The remaining 9 modes showed more subtle head shape variability. MODEL2 (n = 159) revealed that post-operative head shape still did not achieve full shape normalization with either spring cranioplasty or total calvarial remodelling. This study proves that SSM has the potential to describe detailed anatomical variations in a paediatric population.
AbstractList The aim of this study is, firstly, to create a population-based 3D head shape model for the 0 to 2-year-old subjects to describe head shape variability within a normal population and, secondly, to test a combined normal and sagittal craniosynostosis (SAG) population model, able to provide surgical outcome assessment. 3D head shapes of patients affected by non-cranial related pathologies and of SAG patients (pre- and post-op) were extracted either from head CTs or 3D stereophotography scans, and processed. Statistical shape modelling (SSM) was used to describe shape variability using two models - a normal population model (MODEL1) and a combined normal and SAG population model (MODEL2). Head shape variability was described via principal components analysis (PCA) which calculates shape modes describing specific shape features. MODEL1 (n = 65) mode 1 showed statistical correlation (p < 0.001) with width (125.8 ± 13.6 mm), length (151.3 ± 17.4 mm) and height (112.5 ± 11.1 mm) whilst mode 2 showed correlation with cranial index (83.5 mm ± 6.3 mm, p < 0.001). The remaining 9 modes showed more subtle head shape variability. MODEL2 (n = 159) revealed that post-operative head shape still did not achieve full shape normalization with either spring cranioplasty or total calvarial remodelling. This study proves that SSM has the potential to describe detailed anatomical variations in a paediatric population.
The aim of this study is, firstly, to create a population-based 3D head shape model for the 0 to 2-year-old subjects to describe head shape variability within a normal population and, secondly, to test a combined normal and sagittal craniosynostosis (SAG) population model, able to provide surgical outcome assessment. 3D head shapes of patients affected by non-cranial related pathologies and of SAG patients (pre- and post-op) were extracted either from head CTs or 3D stereophotography scans, and processed. Statistical shape modelling (SSM) was used to describe shape variability using two models - a normal population model (MODEL1) and a combined normal and SAG population model (MODEL2). Head shape variability was described via principal components analysis (PCA) which calculates shape modes describing specific shape features. MODEL1 (n = 65) mode 1 showed statistical correlation (p < 0.001) with width (125.8 ± 13.6 mm), length (151.3 ± 17.4 mm) and height (112.5 ± 11.1 mm) whilst mode 2 showed correlation with cranial index (83.5 mm ± 6.3 mm, p < 0.001). The remaining 9 modes showed more subtle head shape variability. MODEL2 (n = 159) revealed that post-operative head shape still did not achieve full shape normalization with either spring cranioplasty or total calvarial remodelling. This study proves that SSM has the potential to describe detailed anatomical variations in a paediatric population.The aim of this study is, firstly, to create a population-based 3D head shape model for the 0 to 2-year-old subjects to describe head shape variability within a normal population and, secondly, to test a combined normal and sagittal craniosynostosis (SAG) population model, able to provide surgical outcome assessment. 3D head shapes of patients affected by non-cranial related pathologies and of SAG patients (pre- and post-op) were extracted either from head CTs or 3D stereophotography scans, and processed. Statistical shape modelling (SSM) was used to describe shape variability using two models - a normal population model (MODEL1) and a combined normal and SAG population model (MODEL2). Head shape variability was described via principal components analysis (PCA) which calculates shape modes describing specific shape features. MODEL1 (n = 65) mode 1 showed statistical correlation (p < 0.001) with width (125.8 ± 13.6 mm), length (151.3 ± 17.4 mm) and height (112.5 ± 11.1 mm) whilst mode 2 showed correlation with cranial index (83.5 mm ± 6.3 mm, p < 0.001). The remaining 9 modes showed more subtle head shape variability. MODEL2 (n = 159) revealed that post-operative head shape still did not achieve full shape normalization with either spring cranioplasty or total calvarial remodelling. This study proves that SSM has the potential to describe detailed anatomical variations in a paediatric population.
The aim of this study is, firstly, to create a population-based 3D head shape model for the 0 to 2-year-old subjects to describe head shape variability within a normal population and, secondly, to test a combined normal and sagittal craniosynostosis (SAG) population model, able to provide surgical outcome assessment. 3D head shapes of patients affected by non-cranial related pathologies and of SAG patients (pre- and post-op) were extracted either from head CTs or 3D stereophotography scans, and processed. Statistical shape modelling (SSM) was used to describe shape variability using two models – a normal population model (MODEL1) and a combined normal and SAG population model (MODEL2). Head shape variability was described via principal components analysis (PCA) which calculates shape modes describing specific shape features. MODEL1 (n = 65) mode 1 showed statistical correlation (p < 0.001) with width (125.8 ± 13.6 mm), length (151.3 ± 17.4 mm) and height (112.5 ± 11.1 mm) whilst mode 2 showed correlation with cranial index (83.5 mm ± 6.3 mm, p < 0.001). The remaining 9 modes showed more subtle head shape variability. MODEL2 (n = 159) revealed that post-operative head shape still did not achieve full shape normalization with either spring cranioplasty or total calvarial remodelling. This study proves that SSM has the potential to describe detailed anatomical variations in a paediatric population.
Author Knoops, Paul
Florez, Naiara Rodriguez
Breakey, William
Heutinck, Pam
Dunaway, David
James, Greg
Borghi, Alessandro
Schievano, Silvia
Biffi, Benedetta
Jeelani, Owase
Koudstaal, Maarten
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Issue 6
Keywords Spring assisted cranioplasty
Statistical shape modelling
Normal head shape
Craniosynostosis
Language English
License Copyright © 2021 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.
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Snippet The aim of this study is, firstly, to create a population-based 3D head shape model for the 0 to 2-year-old subjects to describe head shape variability within...
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SubjectTerms Child
Child, Preschool
Craniosynostoses - diagnostic imaging
Craniosynostoses - surgery
Craniosynostosis
Head - diagnostic imaging
Humans
Imaging, Three-Dimensional
Infant
Infant, Newborn
Models, Statistical
Normal head shape
Skull - diagnostic imaging
Spring assisted cranioplasty
Statistical shape modelling
Title Statistical shape modelling for the analysis of head shape variations
URI https://www.clinicalkey.com/#!/content/1-s2.0-S1010518221000779
https://dx.doi.org/10.1016/j.jcms.2021.02.020
https://www.ncbi.nlm.nih.gov/pubmed/33712336
https://www.proquest.com/docview/2501262825
Volume 49
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