ABSTRACT
The available reference data for the mandible and mandibular growth consists primarily of two-dimensional linear or angular measurements. The aim of this study was to create the first open-source, three-dimensional statistical shape model of the mandible that spans the complete growth period. Computed tomography scans of 678 mandibles from children and young adults between 0 and 22 years old were included in the model. The mandibles were segmented using a semi-automatic or automatic (artificial intelligence-based) segmentation method. Point correspondence among the samples was achieved by rigid registration, followed by non-rigid registration of a symmetrical template onto each sample. The registration process was validated with adequate results. Principal component analysis was used to gain insight in the variation within the dataset and to investigate age-related changes and sexual dimorphism. The presented growth model is accessible globally and free-of-charge for scientists, physicians and forensic investigators for any kind of purpose deemed suitable. The versatility of the model opens up new possibilities in the fields of oral and maxillofacial surgery, forensic sciences or biological anthropology. In clinical settings, the model may aid diagnostic decision-making, treatment planning and treatment evaluation.
Subject(s)
Imaging, Three-Dimensional , Mandible , Humans , Mandible/diagnostic imaging , Mandible/growth & development , Female , Male , Adolescent , Child , Child, Preschool , Infant , Imaging, Three-Dimensional/methods , Young Adult , Tomography, X-Ray Computed , Infant, Newborn , Adult , Models, Biological , Models, AnatomicABSTRACT
Virtual planning of open cranial vault reconstruction is used to simulate and define an pre-operative plan for craniosynostosis surgery. However, virtual planning techniques are subjective and dependent on the experience and preferences of the surgical team. To develop an objective automated 3D pre-operative planning technique for open cranial vault reconstructions, we used curvature maps for the shape comparison of the patient's skull with an age-specific reference skull. We created an average skull for the age-group of 11-14 months. Also, we created an artificial test object and selected a cranial CT-scan of an 11 months old trigonocephaly patient as test case. Mesh data of skulls were created using marching cubes and raycasting. Curvature maps were computed using quadric surface fitting. The shape comparison was tested for the test object and the average skull. Finally, shape comparison was performed for the trigonocephalic skull with the average skull. Similar shapes and the area on the patient's skull that maximally corresponded in shape with the reference shape were correctly identified. This study showed that curvature maps allow the comparison of craniosynostosis skulls with age-appropriate average skulls and a first step towards an objective user-independent pre-operative planning technique for open cranial vault reconstructions is made.