A three-dimensional statistical shape model of the growing mandible

• Published in: Scientific reports Vol. 11; no. 1; pp. 18843 - 10
• Main Author: Klop, C.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 22-09-2021; Nature Publishing Group; Nature Portfolio
• Subjects: 631/114; 631/114/2415; 631/136/2060/2068; 692/698; 692/698/1671/63; Age Factors; Cadavers; Child; Child, Preschool; Computed tomography; Databases as Topic; Female; Humanities and Social Sciences; Humans; Imaging, Three-Dimensional; Infant; Male; Mandible; Mandible - anatomy & histology; Mandible - diagnostic imaging; Mandible - growth & development; Mathematical models; Maxillofacial; Models, Statistical; multidisciplinary; Principal Component Analysis; Principal components analysis; Science; Science (multidisciplinary); Sex Factors; Tomography, X-Ray Computed
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-021-98421-x

Mandibular growth and morphology are important topics in the field of oral and maxillofacial surgery. For diagnostic and planning purposes, a normative database or statistical shape model of the growing mandible can be of great benefit. A collection of 874 cadaveric children’s mandibles with dental age between 1 and 12 years old were digitized using computed tomography scanning and reconstructed to three-dimensional models. Point correspondence was achieved using iterative closest point and coherent point drift algorithms. Principal component analysis (PCA) was applied to find the main modes of variation in the data set. The average mandible was presented, along with the first ten PCA modes. The first mode explained 78% of the total variance; combining the first ten modes accumulated to 95% of the total variance. The first mode was strongly correlated with age and hence, with natural growth. This is the largest study on three-dimensional mandibular shape and development conducted thus far. The main limitation is that the samples lack information such as gender and cause of death. Clinical application of the model first requires validation with contemporary samples.