Towards an early 3D-diagnosis of craniofacial asymmetry by computing the accurate midplane: A PCA-based method

Highlights

• PCA-based method identified the midplane compensating the asymmetry of children's skull.

• 3D workflow proposed improves the analytical study of craniofacial development.

• Morphological 3D analysis displayed malformations in the cranial base and soft tissues.

• Unilateral chewing could lead to the abnormal growth of both the maxilla and jaw.

• Maxilla and jaw malformations seem to be correlated in patients with unilateral crossbite.

Abstract

Background and objective

Craniofacial asymmetry is a common growth disorder often caused by unilateral chewing. Although an early orthodontic treatment would avoid surgical procedures later in life, the uncertainty of defining the accurate sagittal midplane potentially leads to misdiagnosis and therefore inaccurate orthodontic treatment plans. This novel study aims to 3D-diagnose craniofacial complex malformations in children with unilateral crossbite (UXB) considering a midplane which compensates the asymmetric morphology.

Methods

The sagittal midplane of 20 children, fifteen of whom exhibited UXB, was computed by a PCA-based method which compensates the asymmetry mirroring the 3D models obtained from cone-beam computed tomography data. Once determined, one side of the data was mirrored using the computed midplane to visualize the malformations on the hard and soft tissues by 3D-computing the distances between both halves. Additionally, 31 skull's landmarks were manually placed in each model to study the principal variation modes and the significant differences in the group of subjects with and without UXB through PCA and Mann-Whitney U test analyses respectively.

Results

Morphological 3D-analysis showed pronounced deformities and aesthetic implications for patients with severe asymmetry (jaw deviation > 0.8 mm) in whole craniofacial system, while initial signs of asymmetry were found indistinctly in the mandible or maxilla. We detected significant (p < 0.05) malformations for example in mandibular ramus length (0.0086), maxillary palate width (0.0481) and condylar head width (0.0408). Craniofacial malformations increased the landmarks’ variability in the group of patients with UXB over the control group requiring 8 variation modes more to define 99% of the sample’ variability.

Conclusions

Our findings demonstrated the viability of early diagnosis of craniofacial asymmetry through computing the accurate sagittal midplane which compensates the individual's asymmetrical morphology. Furthermore, this study provides important computational insights into the determination of craniofacial deformities which are caused by UXB, following some empirical findings of previous clinical studies. Hence, this computational approach can be useful for the development of new software in craniofacial surgery or for its use in biomedical research and clinical practice.