Statistical shape modelling for the analysis of head shape variations

Pam Heutinck; Paul Knoops; Naiara Rodriguez Florez; Benedetta Biffi; William Breakey; Greg James; Maarten Koudstaal; Silvia Schievano; David Dunaway; Owase Jeelani; Alessandro Borghi

doi:10.1016/j.jcms.2021.02.020

Statistical shape modelling for the analysis of head shape variations

Pam Heutinck, Paul Knoops, Naiara Rodriguez Florez, Benedetta Biffi, William Breakey, Greg James, Maarten Koudstaal, Silvia Schievano, David Dunaway, Owase Jeelani, Alessandro Borghi^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

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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.

Original language	English
Pages (from-to)	449-455
Number of pages	7
Journal	Journal of Cranio-Maxillofacial Surgery
Volume	49
Issue number	6
DOIs	https://doi.org/10.1016/j.jcms.2021.02.020
Publication status	Published - Jun 2021

Bibliographical note

Funding Information:
The work has been funded by Great Ormond Street Hospital for Children Charity (grant number 12SG15) as well as the NIHR GOSH Biomedical Research Centre Advanced Therapies for Structural Malformations and Tissue Damage pump-prime funding call (grant n. 17DS18), the Engineering and Physical Sciences Research Council (EP/N02124X/1) and the European Research Council (ERC-2017-StG-757923). This report incorporates independent research from the National Institute for Health Research Biomedical Research Centre Funding Scheme. The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health.

Publisher Copyright: © 2021 European Association for Cranio-Maxillo-Facial Surgery

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Borghi_JCMS-D-19-00053 - REVISED MANUSCRIPT_PH2_REPOSITORYAccepted author manuscript, 246 KBLicence: CC BY-NC-ND

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title = "Statistical shape modelling for the analysis of head shape variations",

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.",

author = "Pam Heutinck and Paul Knoops and Florez, {Naiara Rodriguez} and Benedetta Biffi and William Breakey and Greg James and Maarten Koudstaal and Silvia Schievano and David Dunaway and Owase Jeelani and Alessandro Borghi",

note = "Funding Information: The work has been funded by Great Ormond Street Hospital for Children Charity (grant number 12SG15) as well as the NIHR GOSH Biomedical Research Centre Advanced Therapies for Structural Malformations and Tissue Damage pump-prime funding call (grant n. 17DS18), the Engineering and Physical Sciences Research Council (EP/N02124X/1) and the European Research Council (ERC-2017-StG-757923). This report incorporates independent research from the National Institute for Health Research Biomedical Research Centre Funding Scheme. The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health. Publisher Copyright: {\textcopyright} 2021 European Association for Cranio-Maxillo-Facial Surgery",

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doi = "10.1016/j.jcms.2021.02.020",

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AU - Heutinck, Pam

AU - Knoops, Paul

AU - Florez, Naiara Rodriguez

AU - Biffi, Benedetta

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AU - James, Greg

AU - Koudstaal, Maarten

AU - Schievano, Silvia

AU - Dunaway, David

AU - Jeelani, Owase

AU - Borghi, Alessandro

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PY - 2021/6

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Statistical shape modelling for the analysis of head shape variations

Abstract

Bibliographical note

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