The 3D skull 0–4 years: A validated, generative, statistical shape model

AbstractBackgroundThis study aims to capture the 3D shape of the human skull in a healthy paediatric population (0–4 years old) and construct a generative statistical shape model. MethodsThe skull bones of 178 healthy children (55% male, 20.8 ± 12.9 months) were reconstructed from computed tomograph...

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Published in:Bone Reports Vol. 15; p. 101154
Main Authors: O' Sullivan, Eimear, van de Lande, Lara S, Oosting, Anne-Jet C, Papaioannou, Athanasios, Jeelani, N. Owase, Koudstaal, Maarten J, Khonsari, Roman H, Dunaway, David J, Zafeiriou, Stefanos, Schievano, Silvia
Format: Journal Article
Language:English
Published: United States Elsevier Inc 01.12.2021
Elsevier
Subjects:
3D morphable model
Full Length
Morphometrics
Orthopedics
Paediatric skull
Statistical shape model
Synthetic shapes
Statistical shape model
3D morphable model
Morphometrics
Paediatric skull
Synthetic shapes
ISSN:2352-1872, 2352-1872
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Summary:AbstractBackgroundThis study aims to capture the 3D shape of the human skull in a healthy paediatric population (0–4 years old) and construct a generative statistical shape model. MethodsThe skull bones of 178 healthy children (55% male, 20.8 ± 12.9 months) were reconstructed from computed tomography (CT) images. 29 anatomical landmarks were placed on the 3D skull reconstructions. Rotation, translation and size were removed, and all skull meshes were placed in dense correspondence using a dimensionless skull mesh template and a non-rigid iterative closest point algorithm. A 3D morphable model (3DMM) was created using principal component analysis, and intrinsically and geometrically validated with anthropometric measurements. Synthetic skull instances were generated exploiting the 3DMM and validated by comparison of the anthropometric measurements with the selected input population. ResultsThe 3DMM of the paediatric skull 0–4 years was successfully constructed. The model was reasonably compact - 90% of the model shape variance was captured within the first 10 principal components. The generalisation error, quantifying the ability of the 3DMM to represent shape instances not encountered during training, was 0.47 mm when all model components were used. The specificity value was <0.7 mm demonstrating that novel skull instances generated by the model are realistic. The 3DMM mean shape was representative of the selected population (differences <2%). Overall, good agreement was observed in the anthropometric measures extracted from the selected population, and compared to normative literature data (max difference in the intertemporal distance) and to the synthetic generated cases. ConclusionThis study presents a reliable statistical shape model of the paediatric skull 0–4 years that adheres to known skull morphometric measures, can accurately represent unseen skull samples not used during model construction and can generate novel realistic skull instances, thus presenting a solution to limited availability of normative data in this field.
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These authors contributed equally to this work.
ISSN:2352-1872
2352-1872
DOI:10.1016/j.bonr.2021.101154