Growth patterns and shape development of the paediatric mandible - A 3D statistical model

Eimear O' Sullivan; Lara S van de Lande; Khalid El Ghoul; Maarten J Koudstaal; Silvia Schievano; Roman H Khonsari; David J Dunaway; Stefanos Zafeiriou

doi:10.1016/j.bonr.2022.101528

Growth patterns and shape development of the paediatric mandible - A 3D statistical model

Bone Rep. 2022 Mar 31:16:101528. doi: 10.1016/j.bonr.2022.101528. eCollection 2022 Jun.

Authors

Eimear O' Sullivan^{1

2

3}, Lara S van de Lande^{1

2

4

5}, Khalid El Ghoul⁵, Maarten J Koudstaal^{1

2

5}, Silvia Schievano^{1

2}, Roman H Khonsari⁴, David J Dunaway^{1

2}, Stefanos Zafeiriou³

Affiliations

¹ UCL Great Ormond Street Institute of Child Health, London, UK.
² Craniofacial Unit, Great Ormond Street Hospital for Children, London, UK.
³ Department of Computing, Imperial College London, London, UK.
⁴ Department of Maxillofacial Surgery and Plastic Surgery, Necker - Enfants Malades University Hospital, Assistance Publique - Hôpitaux de Paris, Faculty of Medicine, University of Paris, Paris, France.
⁵ Department of Oral and Maxillofacial Surgery, Erasmus Medical Centre, Rotterdam, the Netherlands.

Abstract

Background/aim: To develop a 3D morphable model of the normal paediatric mandible to analyse shape development and growth patterns for males and females.

Methods: Computed tomography (CT) data was collected for 242 healthy children referred for CT scan between 2011 and 2018 aged between 0 and 47 months (mean, 20.6 ± 13.4 months, 59.9% male). Thresholding techniques were used to segment the mandible from the CT scans. All mandible meshes were annotated using a defined set of 52 landmarks and processed such that all meshes followed a consistent triangulation. Following this, the mandible meshes were rigidly aligned to remove translation and rotation effects, while size effects were retained. Principal component analysis (PCA) was applied to the processed meshes to construct a generative 3D morphable model. Partial least squares (PLS) regression was also applied to the processed data to extract the shape modes with which to evaluate shape differences for age and sex. Growth curves were constructed for anthropometric measurements.

Results: A 3D morphable model of the paediatric mandible was constructed and validated with good generalisation, compactness, and specificity. Growth curves of the assessed anthropometric measurements were plotted without significant differences between male and female subjects. The first principal component was dominated by size effects and is highly correlated with age at time of scan (Spearman's r = 0.94, p < 0.01). As with PCA, the first extracted PLS mode captures much of the size variation within the dataset and is highly correlated with age (Spearman's r = -0.94, p < 0.01). Little correlation was observed between extracted shape modes and sex with either PCA or PLS for this study population.

Conclusion: The presented 3D morphable model of the paediatric mandible enables an understanding of mandibular shape development and variation by age and sex. It allowed for the construction of growth curves, which contains valuable information that can be used to enhance our understanding of various disorders that affect the mandibular development. Knowledge of shape changes in the growing mandible has potential to improve diagnostic accuracy for craniofacial conditions that impact the mandibular morphology, objective evaluation, surgical planning, and patient follow-up.

Keywords: 3D morphable model; Infant mandible; Morphometrics; Paediatric mandible; Partial least squares; Statistical model.